Classification is an important activity that facilitates theory development in many academic disciplines. Scholars in fields such as organizational science, management science and economics and have long recognized that classification offers an approach for ordering and understanding the diversity of organizational taxa (groups of one or more similar organizational entities). However, even the most prominent organizational classifications have limited utility, as they tend to be shaped by a specific research bias, inadequate units of analysis and a standard neoclassical economic view that does not naturally accommodate the disequilibrium dynamics of modern competition. The result is a relatively large number of individual and unconnected organizational classifications, which tend to ignore the processes of change responsible for organizational diversity. Collectively they fail to provide any sort of universal system for ordering, compiling and presenting knowledge on organizational diversity. This paper has two purposes. First, it reviews the general status of the major theoretical approaches to biological and organizational classification and compares the methods and resulting classifications derived from each approach. Definitions of key terms and a discussion on the three principal schools of biological classification (evolutionary systematics, phenetics and cladistics) are included in this review. Second, this paper aims to encourage critical thinking and debate about the use of the cladistic classification approach for inferring and representing the historical relationships underpinning organizational diversity. This involves examining the feasibility of applying the logic of common ancestry to populations of organizations. Consequently, this paper is exploratory and preparatory in style, with illustrations and assertions concerning the study and classification of organizational diversity.
Organisational diversity, evolution and cladistics classificationsIan McCarthy
This article presents a case for the construction of a formal classification of manufacturing systems using cladistics, a technique from the biological school of classification. A seven-stage framework for producing a manufacturing cladogram is presented, along with a pilot case study example. This article describes the role that classification plays in the pure and applied sciences, the social sciences and reviews the status of existing manufacturing classifications. If organisational diversity and organisational change processes are governed by evolutionary mechanisms, studies of organisations based on an evolutionary approach such as cladistics could have potential, because as March (1994. p. 39], ``there is natural speculation that organisations, like species can be engineered by understanding the evolutionary processes well enough to intervene and produce competitive organisational effects''. It is suggested that a cladistic study could provide organisations with a ``knowledge map'' of the ecosystem in which they exist and by using this phylogenetic and situational analysis, they could determine coherent and appropriate action for the speciation of change.
This study seeks to validate the phenomenon of organizational culture types that purports to support
an organization’s performance. The study further determines if there is any substantive relevance to the
argument proposed by scholars in organizational culture theory that an organization’s culture predicating on
its performance,
When customers get clever: Managerial approaches to dealing with creative con...Ian McCarthy
Creative consumers (defined as customers who adapt, modify, or transform a proprietary offering) represent an intriguing paradox for business. On
one hand, they can signify a black hole for future revenue, with breach of copyright and intellectual property. On the other hand, they represent a gold mine of ideas and business opportunities. Central to business is the need to create and capture value, and creative consumers demand a shift in the mindsets and business models of how firms accomplish both. Based upon their attitude and action toward customer innovation, we develop a typology of firms’ stances toward creative consumers. We then consider the implications of the stances model for corporate strategy and
examine a three-step approach to dealing with creative consumers: awareness, analysis, and response.
Organisational diversity, evolution and cladistics classificationsIan McCarthy
This article presents a case for the construction of a formal classification of manufacturing systems using cladistics, a technique from the biological school of classification. A seven-stage framework for producing a manufacturing cladogram is presented, along with a pilot case study example. This article describes the role that classification plays in the pure and applied sciences, the social sciences and reviews the status of existing manufacturing classifications. If organisational diversity and organisational change processes are governed by evolutionary mechanisms, studies of organisations based on an evolutionary approach such as cladistics could have potential, because as March (1994. p. 39], ``there is natural speculation that organisations, like species can be engineered by understanding the evolutionary processes well enough to intervene and produce competitive organisational effects''. It is suggested that a cladistic study could provide organisations with a ``knowledge map'' of the ecosystem in which they exist and by using this phylogenetic and situational analysis, they could determine coherent and appropriate action for the speciation of change.
This study seeks to validate the phenomenon of organizational culture types that purports to support
an organization’s performance. The study further determines if there is any substantive relevance to the
argument proposed by scholars in organizational culture theory that an organization’s culture predicating on
its performance,
When customers get clever: Managerial approaches to dealing with creative con...Ian McCarthy
Creative consumers (defined as customers who adapt, modify, or transform a proprietary offering) represent an intriguing paradox for business. On
one hand, they can signify a black hole for future revenue, with breach of copyright and intellectual property. On the other hand, they represent a gold mine of ideas and business opportunities. Central to business is the need to create and capture value, and creative consumers demand a shift in the mindsets and business models of how firms accomplish both. Based upon their attitude and action toward customer innovation, we develop a typology of firms’ stances toward creative consumers. We then consider the implications of the stances model for corporate strategy and
examine a three-step approach to dealing with creative consumers: awareness, analysis, and response.
Achieving Agility Using Cladistics: An Evolutionary AnalysisIan McCarthy
To achieve the status of an agile manufacturer, organisations need to clearly understand the concept of agility, relative to their industrial and business circumstances and to then identify and acquire the appropriate characteristics which will result in an agile manufacturing organisation. This paper is not simply another discussion on the definition of agility, or a philosophical debate on the drivers and characteristics of agility. This paper presents an evolutionary modelling technique (cladistics) which could enable organisations to systematically manage and understand the emergence of new manufacturing forms within their business environment. This fundamental, but important insight is valuable for achieving successful organisational design and change. Thus, regardless of the industrial sector, managers could use cladistics as an evolutionary analysis technique for determining ``where they have been and where they are now''. Moving from a non-agile manufacture to an agile manufacture is a process of organisational change and evolutionary development. This evolutionary method will enable organisations to understand the landscape of manufacturing possibilities that exist, to identify appropriate agile forms and to successfully navigate that landscape.
New Product Development as a Complex Adaptive System of DecisionsIan McCarthy
Early research on new product development (NPD) has produced descriptive frameworks and models that view the process as a linear system with sequential and discrete stages. More recently, recursive and chaotic frameworks of NPD have been developed, both of which acknowledge that NPD progresses through a series of stages, but with overlaps, feedback loops, and resulting behaviors that resist reductionism
and linear analysis. This article extends the linear, recursive, and chaotic frameworks by viewing NPD as a complex adaptive system (CAS) governed by three levels of decision making — in-stage, review, and strategic—and the accompanying decision rules. The research develops and presents propositions that predict how the configuration and organization of NPD decision-making agents will influence
the potential for three mutually dependent CAS phenomena: nonlinearity, selforganization, and emergence. Together these phenomena underpin the potential for NPD process adaptability and congruence. To support and to verify the propositions, this study uses comparative case studies, which show that NPD process adaptability occurs and that it is dependent on the number and variety of agents, their corresponding connections and interactions, and the ordering or disordering effect of the decision levels and rules. Thus, the CAS framework developed within this article maintains a fit among descriptive stance, system behavior, and innovation type, as it considers individual NPD processes to be capable of switching or toggling between different behaviors — linear to chaotic — to produce corresponding innovation outputs that range from incremental to radical in accord with market expectations.
Achieving contextual ambidexterity in R&D organizations: a management control...Ian McCarthy
Research on how managers control R&D activities has tended to focus on the performance measurement systems used to exploit existing knowledge and capabilities. This focus has been at the expense of how broader forms of management control could be used to enable R&D contextual ambidexterity, the capacity to attain appropriate levels of exploitation and exploration behaviors in the same R&D organizational unit. In this paper, we develop a conceptual framework for understanding how different types of control system, guided by different R&D strategic goals, can be used to induce and balance both exploitation and exploration. We illustrate the elements of this framework and their relations using data from biotechnology firms, and then discuss how the framework provides a basis to empirically examine a number of important control relationships and phenomena.
Understanding outsourcing contexts through information asymmetry and capabili...Ian McCarthy
Outsourcing is a strategic activity that has long been central to operations management research and practice. Yet, there are still many outsourcing management challenges that remain. In this article, we explore two of the outsourcing challenges that motivated this special issue and are central to the 10 articles included. To do this, we develop a theoretical model that examines how variations in capability fit and information asymmetry combine to present firms with four different outsourcing contexts. We then explain how each of the articles included in this special issue relate to our theoretical model and explore several avenues for future research.
Innovation in manufacturing as an evolutionary complex systemIan McCarthy
The focus of this paper is on innovation in terms of the new product development processes and to discuss its main features. This is followed by a presentation of the new ideas emerging from complex systems science. It is then demonstrated how complex systems provides an overall conceptual framework for thinking about innovation and for considering how this helps to provide understanding and advice for the organisation of new product development in different circumstances. Three case studies are quoted which illustrate the application of these new ideas.
The ability of current statistical classifications to separateservices and ma...Ian McCarthy
This paper explores the performance of current statistical classification systems in classifying firms and, in particular, their ability to distinguish between firms that provide services and firms that provide manufacturing. We find that a large share of firms, almost 20%, are not classified as expected based on a comparison of their statements of activities with the assigned industry codes. This result is robust to analyses on different levels of aggregation and is validated in an additional survey. It is well known from earlier literature that industry classification systems are not perfect. This paper provides a quantification of the flaws in classifications of firms. Moreover, it is explained why the classifications of firms are imprecise. The increasing complexity of production, inertia in changes to statistical systems and the increasing integration of manufacturing products and services are some of the primary and interrelated explanations for this lack of precision. We emphasise, however, that such classification problems are not resolved using a ‘technical fix’. Any statistical classification method involves a number of tradeoffs.
Complex adaptive system mechanisms, adaptive management practices, and firm p...Ian McCarthy
As a fascinating concept, the mechanisms of complex adaptive system (CAS) attracted many researchers from a variety of disciplines. Nevertheless, how the mechanism-related variables, such as strategic resonance, accreting nodes, pattern forming, and catalytic behavior of organization, impact the firm product innovativeness is rarely addressed empirically in the new product development (NPD) literature. Also, there exist limited studies on the antecedents of the mechanisms of CAS in the NPD literature. In this respect, we identified and operationalized the adaptive management practices, which involve bonding, nonlinear, and attractor behaviors of management, as antecedents of mechanisms and firm product innovativeness. By studying 235 firms, we found that (1) strategic resonance and accreting nodes are positively related to firm product innovativeness, (2) bonding, nonlinear, and attractor behaviors of management positively influence the mechanism variables, and (3) market and technology turbulence impact the adaptive management practices. We also found that mechanisms of CAS partially mediate the relationship between adaptive management practices and firm product innovativeness.
Understanding the effects of outsourcing: unpacking the total factor producti...Ian McCarthy
Research on why firms should outsource and how they should do it has proliferated in the past two decades, but few consistent findings have emerged concerning the benefits of outsourcing. We argue that this is in part due to the lack of an adequate framework for measuring the effects of outsourcing. To address this, we present such a framework based upon the Cobb–Douglas productivity function. We explain how our framework can be used to unpack one component of the Cobb–Douglas productivity function, the ‘total factor productivity’, which represents the other numerous sub-variables that affect outsourcing productivity, beyond the capital and labour expenditures. We also demonstrate the framework using a simple illustrative example.
Why do some patents get licensed while others do not?Ian McCarthy
To understand why some patents get licensed and others do not, we estimate a portfolio of firm- and patent-level determinants for why a particular licensor’s patent was licensed over all technologically similar patents held by other licensors. Using data for licensed biopharmaceutical patents, we build a set of alternate patents that could have been licensed-in using topic modeling techniques. This provides a more sophisticated way of controlling for patent characteristics and analyzing the attractiveness of a licensor and the characteristics of the patent itself. We find that patents owned by licensors with technological prestige, experience at licensing, and combined technological depth and breadth have a greater chance at being chosen by licensees. This suggests that a licensor’s standing and organizational learning rather than the quality of its patent alone influence the success of outward licensing.
Technology Management - A Complex Adaptive Systems ApproachIan McCarthy
There are systems methods and evolutionary processes that can help organisations understand the innovative patterns and competitive mechanisms that influence the creation, management and exploitation of technology. This paper presents a specific model based on the evolutionary processes of variation, selection, retention and struggle, coupled with fitness landscape theory. This latter concept is a complex adaptive systems theory that has attained recognition as an approach for visually mapping the strategic options an evolving system could pursue. The relevance and utility of fitness landscape theory to the strategic management of technology is explored, and a definition and model of technological fitness provided. The complex adaptive systems perspective adopted by this paper, views organisations as evolving systems that formulate strategies by classifying, selecting, adopting and exploiting various combinations of technological capabilities. A model called the strategy configuration chain is presented to illustrate this strategic process.
Organisational diversity, evolution and cladistic classificationsIan McCarthy
This article presents a case for the construction of a formal classification of manufacturing systems using cladistics, a technique from the biological school of classification. A seven-stage framework for roducing a manufacturing cladogram is presented, along with a pilot case study example. This article describes the role that classification plays in the pure and applied sciences, the social sciences and reviews the status of existing manufacturing classifications. If organisational diversity and organisational change processes are governed by evolutionary mechanisms, studies of organisations based on an evolutionary approach such as cladistics could have potential, because as March [March JG. The evolution of evolution. In: Baum JAC, Singh JV, editors. Evolutionary dynamics of organizations. Oxford University Press, 1994. p. 39±52], page 45, states ``there is natural speculation that organisations, like species can be engineered by understanding the evolutionary processes well enough to intervene and produce competitive organisational effects''. It is suggested that a cladistic study could provide organisations with a ``knowledge map'' of the ecosystem in which they exist and by using this phylogenetic and situational analysis, they could determine coherent and appropriate action for the specification of change.
Making a face: Graphical illustrations of managerial stances toward customer ...Ian McCarthy
Creative consumers – consumers who adapt, modify or transform a proprietary offering – represent an intriguing paradox for business. On the one hand they can be a black hole for future revenue, with breach of copyright and intellectual property, while on the other hand they represent a gold mine of ideas and business opportunities. This problem is central to business – business needs to both create and capture value; the problem is that creative consumers demand a shift in the mindsets and business models of how firms both create and capture value. We develop a typology of firms’ stances to creative consumers based upon their attitude and action towards customer innovation. We then consider the implications of the stances model for corporate strategy, and examine a three-step approach to dealing with creative consumers, namely, awareness, analysis and response.
Unpacking the Social Media Phenomenon: Towards a Research AgendaIan McCarthy
In this paper, we highlight some of the challenges and opportunities that social media presents to researchers, and offer relevant theoretical avenues to be explored. To do this, we present a model that unpacks social media by using a honeycomb of seven functional building blocks. We then examine each of the seven building blocks and, through appropriate social and socio-technical theories, raise questions that warrant further in-depth research to advance the conceptualization of social media in public affairs research. Finally, we combine the individual research questions for each building block back into the honeycomb model to illustrate how the theories in combination provide a powerful macro-lens for research on social media dynamics.
Game on: Engaging customers and employees through gamificationIan McCarthy
Managers are frequently tasked with increasing the engagement levels of key stakeholders, such as customers and employees. Gamification - defined as the application of game design principles to change behavior in non-gaming contexts - is a tool that, if crafted and implemented properly, can increase engagement. In this article we discuss how gamification can aid customer and employee engagement, and delineate between four different types of customers and employees who act as ‘players’ in gamified experiences. We include illustrative examples of gamification and conclude by presenting five lessons for managers who wish to utilize gamification.
Two related trends characterize the recent past: value propositions are migrating from the physical to the informational, and value creation is shifting from firms to consumers. These two trends meet in the phenomenon of “consumer-generated intellectual property” (CGIP). This article addresses the question: “How should firms manage the intellectual property that their customers create?” It explores how CGIP presents important dilemmas for managers and argues that consumers’ “intellectual property” should not be leveraged at the expense of their “emotional property.” It integrates these perspectives into a diagnostic framework and discusses eight strategies for firms to manage CGIP. (Keywords: Consumer Behavior, Intellectual Property, Innovation Management, New Product Management, Competitive Advantage, Consumers, Product Design)
Product recovery decisions within the context of Extended Producer Responsibi...Ian McCarthy
Environmental and economic evidence is increasingly supporting the need for better analytical tools for evaluating the recovery of consumer products. In response, we present a novel mathematical model for determining what we call the Optimal Recovery Plan (ORP) for any given product. The ORP is based on an evaluation and optimization of the economics of remanufacturing consumer products versus demanufacturing in the context of Extended Producer Responsibility (EPR) legislation, a driving force behind the adoption remanufacturing initiatives by firms. We provide an illustrative application of the model and then discuss its implications for scholars and practitioners concerned with sustainable business development.
An Integrated Approach to Studying Multiplexity in Entrepreneurial NetworksIan McCarthy
Multiplexity occurs in entrepreneurial networks when flows interact within and across relationships. It defines how these networks function and evolve and cannot be examined by studying network structure or flows separately. Despite the growing recognition of the importance of multiplexity, related research has remained limited and lacks an integrated approach to simultaneously examine structure and flows, thus restricting our understanding of entrepreneurial networks. We propose an integrated approach for conducting inductive studies into multiplexity, involving an adaptation of the “business networks” conceptual model, the configuration theory perspective, and the Q-analysis method.
Unpacking the social media phenomenon: towards a research agendaIan McCarthy
In this paper, we highlight some of the challenges and opportunities that social media presents to researchers, and offer relevant theoretical avenues to be explored. To do this, we present a model that unpacks social media by using a honeycomb of seven functional building blocks. We then examine each of the seven building blocks and, through appropriate social and socio-technical theories, raise questions that warrant further in-depth research to advance the conceptualization of social media in public affairs research. Finally, we combine the individual research questions for each building block back into the honeycomb model to illustrate how the theories in combination provide a powerful macro-lens for research on social media dynamics.
Organizational Culture Edgar H. Schein I I I I II I II .docxamit657720
Organizational Culture
Edgar H. Schein
I I I I II I II
ABSTRACT: The concept of organizational culture has
received increasing attention in recent years both from
academics and practitioners. This article presents the au-
thor's view of how culture shouM be defined and analyzed
if it is to be of use in the field of organizational psychology.
Other concepts are reviewed, a brief history is provided,
and case materials are presented to illustrate how to an-
alyze culture and how to think about culture change.
To write a review article about the concept of organiza-
tional culture poses a dilemma because there is presently
little agreement on what the concept does and should
mean, how it should be observed and measured, how it
relates to more traditional industrial and organizational
psychology theories, and how it should be used in our
efforts to help organizations. The popular use of the con-
cept has further muddied the waters by hanging the label
of"culture" on everything from common behavioral pat-
terns to espoused new corporate values that senior man-
agement wishes to inculcate (e.g., Deal & Kennedy, 1982;
Peters & Waterman, 1982).
Serious students of organizational culture point out
that each culture researcher develops explicit or implicit
paradigms that bias not only the definitions of key con-
cepts but the whole approach to the study of the phe-
nomenon (Barley, Meyer, & Gash, 1988; Martin & Mey-
erson, 1988; Ott, 1989; Smircich & Calas, 1987; Van
Maanen, 1988). One probable reason for this diversity of
approaches is that culture, like role, lies at the intersection
of several social sciences and reflects some of the biases
of eachwspecifically, those of anthropology, sociology,
social psychology, and organizational behavior.
A complete review of the various paradigms and
their implications is far beyond the scope of this article.
Instead I will provide a brief historical overview leading
to the major approaches currently in use and then de-
scribe in greater detail one paradigm, firmly anchored in
social psychology and anthropology, that is somewhat in-
tegrative in that it allows one to position other paradigms
in a common conceptual space.
This line of thinking will push us conceptually into
territory left insufficiently explored by such concepts as
"climate," "norm," and "attitude." Many of the research
methods of industrial/organizational psychology have
weaknesses when applied to the concept of culture. If we
are to take culture seriously, we must first adopt a more
clinical and ethnographic approach to identify clearly the
kinds of dimensions and variables that can usefully lend
themselves to more precise empirical measurement and
Sloan School of Management,
Massachusetts Institute of Technology
I I [ Illll
hypothesis testing. Though there have been many efforts
to be empirically precise about cultural phenomena, there
is still insufficient linkage of theory wit.
Organizational Culture Edgar H. Schein I I I I II I II .docxvannagoforth
Organizational Culture
Edgar H. Schein
I I I I II I II
ABSTRACT: The concept of organizational culture has
received increasing attention in recent years both from
academics and practitioners. This article presents the au-
thor's view of how culture shouM be defined and analyzed
if it is to be of use in the field of organizational psychology.
Other concepts are reviewed, a brief history is provided,
and case materials are presented to illustrate how to an-
alyze culture and how to think about culture change.
To write a review article about the concept of organiza-
tional culture poses a dilemma because there is presently
little agreement on what the concept does and should
mean, how it should be observed and measured, how it
relates to more traditional industrial and organizational
psychology theories, and how it should be used in our
efforts to help organizations. The popular use of the con-
cept has further muddied the waters by hanging the label
of"culture" on everything from common behavioral pat-
terns to espoused new corporate values that senior man-
agement wishes to inculcate (e.g., Deal & Kennedy, 1982;
Peters & Waterman, 1982).
Serious students of organizational culture point out
that each culture researcher develops explicit or implicit
paradigms that bias not only the definitions of key con-
cepts but the whole approach to the study of the phe-
nomenon (Barley, Meyer, & Gash, 1988; Martin & Mey-
erson, 1988; Ott, 1989; Smircich & Calas, 1987; Van
Maanen, 1988). One probable reason for this diversity of
approaches is that culture, like role, lies at the intersection
of several social sciences and reflects some of the biases
of eachwspecifically, those of anthropology, sociology,
social psychology, and organizational behavior.
A complete review of the various paradigms and
their implications is far beyond the scope of this article.
Instead I will provide a brief historical overview leading
to the major approaches currently in use and then de-
scribe in greater detail one paradigm, firmly anchored in
social psychology and anthropology, that is somewhat in-
tegrative in that it allows one to position other paradigms
in a common conceptual space.
This line of thinking will push us conceptually into
territory left insufficiently explored by such concepts as
"climate," "norm," and "attitude." Many of the research
methods of industrial/organizational psychology have
weaknesses when applied to the concept of culture. If we
are to take culture seriously, we must first adopt a more
clinical and ethnographic approach to identify clearly the
kinds of dimensions and variables that can usefully lend
themselves to more precise empirical measurement and
Sloan School of Management,
Massachusetts Institute of Technology
I I [ Illll
hypothesis testing. Though there have been many efforts
to be empirically precise about cultural phenomena, there
is still insufficient linkage of theory wit ...
Achieving Agility Using Cladistics: An Evolutionary AnalysisIan McCarthy
To achieve the status of an agile manufacturer, organisations need to clearly understand the concept of agility, relative to their industrial and business circumstances and to then identify and acquire the appropriate characteristics which will result in an agile manufacturing organisation. This paper is not simply another discussion on the definition of agility, or a philosophical debate on the drivers and characteristics of agility. This paper presents an evolutionary modelling technique (cladistics) which could enable organisations to systematically manage and understand the emergence of new manufacturing forms within their business environment. This fundamental, but important insight is valuable for achieving successful organisational design and change. Thus, regardless of the industrial sector, managers could use cladistics as an evolutionary analysis technique for determining ``where they have been and where they are now''. Moving from a non-agile manufacture to an agile manufacture is a process of organisational change and evolutionary development. This evolutionary method will enable organisations to understand the landscape of manufacturing possibilities that exist, to identify appropriate agile forms and to successfully navigate that landscape.
New Product Development as a Complex Adaptive System of DecisionsIan McCarthy
Early research on new product development (NPD) has produced descriptive frameworks and models that view the process as a linear system with sequential and discrete stages. More recently, recursive and chaotic frameworks of NPD have been developed, both of which acknowledge that NPD progresses through a series of stages, but with overlaps, feedback loops, and resulting behaviors that resist reductionism
and linear analysis. This article extends the linear, recursive, and chaotic frameworks by viewing NPD as a complex adaptive system (CAS) governed by three levels of decision making — in-stage, review, and strategic—and the accompanying decision rules. The research develops and presents propositions that predict how the configuration and organization of NPD decision-making agents will influence
the potential for three mutually dependent CAS phenomena: nonlinearity, selforganization, and emergence. Together these phenomena underpin the potential for NPD process adaptability and congruence. To support and to verify the propositions, this study uses comparative case studies, which show that NPD process adaptability occurs and that it is dependent on the number and variety of agents, their corresponding connections and interactions, and the ordering or disordering effect of the decision levels and rules. Thus, the CAS framework developed within this article maintains a fit among descriptive stance, system behavior, and innovation type, as it considers individual NPD processes to be capable of switching or toggling between different behaviors — linear to chaotic — to produce corresponding innovation outputs that range from incremental to radical in accord with market expectations.
Achieving contextual ambidexterity in R&D organizations: a management control...Ian McCarthy
Research on how managers control R&D activities has tended to focus on the performance measurement systems used to exploit existing knowledge and capabilities. This focus has been at the expense of how broader forms of management control could be used to enable R&D contextual ambidexterity, the capacity to attain appropriate levels of exploitation and exploration behaviors in the same R&D organizational unit. In this paper, we develop a conceptual framework for understanding how different types of control system, guided by different R&D strategic goals, can be used to induce and balance both exploitation and exploration. We illustrate the elements of this framework and their relations using data from biotechnology firms, and then discuss how the framework provides a basis to empirically examine a number of important control relationships and phenomena.
Understanding outsourcing contexts through information asymmetry and capabili...Ian McCarthy
Outsourcing is a strategic activity that has long been central to operations management research and practice. Yet, there are still many outsourcing management challenges that remain. In this article, we explore two of the outsourcing challenges that motivated this special issue and are central to the 10 articles included. To do this, we develop a theoretical model that examines how variations in capability fit and information asymmetry combine to present firms with four different outsourcing contexts. We then explain how each of the articles included in this special issue relate to our theoretical model and explore several avenues for future research.
Innovation in manufacturing as an evolutionary complex systemIan McCarthy
The focus of this paper is on innovation in terms of the new product development processes and to discuss its main features. This is followed by a presentation of the new ideas emerging from complex systems science. It is then demonstrated how complex systems provides an overall conceptual framework for thinking about innovation and for considering how this helps to provide understanding and advice for the organisation of new product development in different circumstances. Three case studies are quoted which illustrate the application of these new ideas.
The ability of current statistical classifications to separateservices and ma...Ian McCarthy
This paper explores the performance of current statistical classification systems in classifying firms and, in particular, their ability to distinguish between firms that provide services and firms that provide manufacturing. We find that a large share of firms, almost 20%, are not classified as expected based on a comparison of their statements of activities with the assigned industry codes. This result is robust to analyses on different levels of aggregation and is validated in an additional survey. It is well known from earlier literature that industry classification systems are not perfect. This paper provides a quantification of the flaws in classifications of firms. Moreover, it is explained why the classifications of firms are imprecise. The increasing complexity of production, inertia in changes to statistical systems and the increasing integration of manufacturing products and services are some of the primary and interrelated explanations for this lack of precision. We emphasise, however, that such classification problems are not resolved using a ‘technical fix’. Any statistical classification method involves a number of tradeoffs.
Complex adaptive system mechanisms, adaptive management practices, and firm p...Ian McCarthy
As a fascinating concept, the mechanisms of complex adaptive system (CAS) attracted many researchers from a variety of disciplines. Nevertheless, how the mechanism-related variables, such as strategic resonance, accreting nodes, pattern forming, and catalytic behavior of organization, impact the firm product innovativeness is rarely addressed empirically in the new product development (NPD) literature. Also, there exist limited studies on the antecedents of the mechanisms of CAS in the NPD literature. In this respect, we identified and operationalized the adaptive management practices, which involve bonding, nonlinear, and attractor behaviors of management, as antecedents of mechanisms and firm product innovativeness. By studying 235 firms, we found that (1) strategic resonance and accreting nodes are positively related to firm product innovativeness, (2) bonding, nonlinear, and attractor behaviors of management positively influence the mechanism variables, and (3) market and technology turbulence impact the adaptive management practices. We also found that mechanisms of CAS partially mediate the relationship between adaptive management practices and firm product innovativeness.
Understanding the effects of outsourcing: unpacking the total factor producti...Ian McCarthy
Research on why firms should outsource and how they should do it has proliferated in the past two decades, but few consistent findings have emerged concerning the benefits of outsourcing. We argue that this is in part due to the lack of an adequate framework for measuring the effects of outsourcing. To address this, we present such a framework based upon the Cobb–Douglas productivity function. We explain how our framework can be used to unpack one component of the Cobb–Douglas productivity function, the ‘total factor productivity’, which represents the other numerous sub-variables that affect outsourcing productivity, beyond the capital and labour expenditures. We also demonstrate the framework using a simple illustrative example.
Why do some patents get licensed while others do not?Ian McCarthy
To understand why some patents get licensed and others do not, we estimate a portfolio of firm- and patent-level determinants for why a particular licensor’s patent was licensed over all technologically similar patents held by other licensors. Using data for licensed biopharmaceutical patents, we build a set of alternate patents that could have been licensed-in using topic modeling techniques. This provides a more sophisticated way of controlling for patent characteristics and analyzing the attractiveness of a licensor and the characteristics of the patent itself. We find that patents owned by licensors with technological prestige, experience at licensing, and combined technological depth and breadth have a greater chance at being chosen by licensees. This suggests that a licensor’s standing and organizational learning rather than the quality of its patent alone influence the success of outward licensing.
Technology Management - A Complex Adaptive Systems ApproachIan McCarthy
There are systems methods and evolutionary processes that can help organisations understand the innovative patterns and competitive mechanisms that influence the creation, management and exploitation of technology. This paper presents a specific model based on the evolutionary processes of variation, selection, retention and struggle, coupled with fitness landscape theory. This latter concept is a complex adaptive systems theory that has attained recognition as an approach for visually mapping the strategic options an evolving system could pursue. The relevance and utility of fitness landscape theory to the strategic management of technology is explored, and a definition and model of technological fitness provided. The complex adaptive systems perspective adopted by this paper, views organisations as evolving systems that formulate strategies by classifying, selecting, adopting and exploiting various combinations of technological capabilities. A model called the strategy configuration chain is presented to illustrate this strategic process.
Organisational diversity, evolution and cladistic classificationsIan McCarthy
This article presents a case for the construction of a formal classification of manufacturing systems using cladistics, a technique from the biological school of classification. A seven-stage framework for roducing a manufacturing cladogram is presented, along with a pilot case study example. This article describes the role that classification plays in the pure and applied sciences, the social sciences and reviews the status of existing manufacturing classifications. If organisational diversity and organisational change processes are governed by evolutionary mechanisms, studies of organisations based on an evolutionary approach such as cladistics could have potential, because as March [March JG. The evolution of evolution. In: Baum JAC, Singh JV, editors. Evolutionary dynamics of organizations. Oxford University Press, 1994. p. 39±52], page 45, states ``there is natural speculation that organisations, like species can be engineered by understanding the evolutionary processes well enough to intervene and produce competitive organisational effects''. It is suggested that a cladistic study could provide organisations with a ``knowledge map'' of the ecosystem in which they exist and by using this phylogenetic and situational analysis, they could determine coherent and appropriate action for the specification of change.
Making a face: Graphical illustrations of managerial stances toward customer ...Ian McCarthy
Creative consumers – consumers who adapt, modify or transform a proprietary offering – represent an intriguing paradox for business. On the one hand they can be a black hole for future revenue, with breach of copyright and intellectual property, while on the other hand they represent a gold mine of ideas and business opportunities. This problem is central to business – business needs to both create and capture value; the problem is that creative consumers demand a shift in the mindsets and business models of how firms both create and capture value. We develop a typology of firms’ stances to creative consumers based upon their attitude and action towards customer innovation. We then consider the implications of the stances model for corporate strategy, and examine a three-step approach to dealing with creative consumers, namely, awareness, analysis and response.
Unpacking the Social Media Phenomenon: Towards a Research AgendaIan McCarthy
In this paper, we highlight some of the challenges and opportunities that social media presents to researchers, and offer relevant theoretical avenues to be explored. To do this, we present a model that unpacks social media by using a honeycomb of seven functional building blocks. We then examine each of the seven building blocks and, through appropriate social and socio-technical theories, raise questions that warrant further in-depth research to advance the conceptualization of social media in public affairs research. Finally, we combine the individual research questions for each building block back into the honeycomb model to illustrate how the theories in combination provide a powerful macro-lens for research on social media dynamics.
Game on: Engaging customers and employees through gamificationIan McCarthy
Managers are frequently tasked with increasing the engagement levels of key stakeholders, such as customers and employees. Gamification - defined as the application of game design principles to change behavior in non-gaming contexts - is a tool that, if crafted and implemented properly, can increase engagement. In this article we discuss how gamification can aid customer and employee engagement, and delineate between four different types of customers and employees who act as ‘players’ in gamified experiences. We include illustrative examples of gamification and conclude by presenting five lessons for managers who wish to utilize gamification.
Two related trends characterize the recent past: value propositions are migrating from the physical to the informational, and value creation is shifting from firms to consumers. These two trends meet in the phenomenon of “consumer-generated intellectual property” (CGIP). This article addresses the question: “How should firms manage the intellectual property that their customers create?” It explores how CGIP presents important dilemmas for managers and argues that consumers’ “intellectual property” should not be leveraged at the expense of their “emotional property.” It integrates these perspectives into a diagnostic framework and discusses eight strategies for firms to manage CGIP. (Keywords: Consumer Behavior, Intellectual Property, Innovation Management, New Product Management, Competitive Advantage, Consumers, Product Design)
Product recovery decisions within the context of Extended Producer Responsibi...Ian McCarthy
Environmental and economic evidence is increasingly supporting the need for better analytical tools for evaluating the recovery of consumer products. In response, we present a novel mathematical model for determining what we call the Optimal Recovery Plan (ORP) for any given product. The ORP is based on an evaluation and optimization of the economics of remanufacturing consumer products versus demanufacturing in the context of Extended Producer Responsibility (EPR) legislation, a driving force behind the adoption remanufacturing initiatives by firms. We provide an illustrative application of the model and then discuss its implications for scholars and practitioners concerned with sustainable business development.
An Integrated Approach to Studying Multiplexity in Entrepreneurial NetworksIan McCarthy
Multiplexity occurs in entrepreneurial networks when flows interact within and across relationships. It defines how these networks function and evolve and cannot be examined by studying network structure or flows separately. Despite the growing recognition of the importance of multiplexity, related research has remained limited and lacks an integrated approach to simultaneously examine structure and flows, thus restricting our understanding of entrepreneurial networks. We propose an integrated approach for conducting inductive studies into multiplexity, involving an adaptation of the “business networks” conceptual model, the configuration theory perspective, and the Q-analysis method.
Unpacking the social media phenomenon: towards a research agendaIan McCarthy
In this paper, we highlight some of the challenges and opportunities that social media presents to researchers, and offer relevant theoretical avenues to be explored. To do this, we present a model that unpacks social media by using a honeycomb of seven functional building blocks. We then examine each of the seven building blocks and, through appropriate social and socio-technical theories, raise questions that warrant further in-depth research to advance the conceptualization of social media in public affairs research. Finally, we combine the individual research questions for each building block back into the honeycomb model to illustrate how the theories in combination provide a powerful macro-lens for research on social media dynamics.
Organizational Culture Edgar H. Schein I I I I II I II .docxamit657720
Organizational Culture
Edgar H. Schein
I I I I II I II
ABSTRACT: The concept of organizational culture has
received increasing attention in recent years both from
academics and practitioners. This article presents the au-
thor's view of how culture shouM be defined and analyzed
if it is to be of use in the field of organizational psychology.
Other concepts are reviewed, a brief history is provided,
and case materials are presented to illustrate how to an-
alyze culture and how to think about culture change.
To write a review article about the concept of organiza-
tional culture poses a dilemma because there is presently
little agreement on what the concept does and should
mean, how it should be observed and measured, how it
relates to more traditional industrial and organizational
psychology theories, and how it should be used in our
efforts to help organizations. The popular use of the con-
cept has further muddied the waters by hanging the label
of"culture" on everything from common behavioral pat-
terns to espoused new corporate values that senior man-
agement wishes to inculcate (e.g., Deal & Kennedy, 1982;
Peters & Waterman, 1982).
Serious students of organizational culture point out
that each culture researcher develops explicit or implicit
paradigms that bias not only the definitions of key con-
cepts but the whole approach to the study of the phe-
nomenon (Barley, Meyer, & Gash, 1988; Martin & Mey-
erson, 1988; Ott, 1989; Smircich & Calas, 1987; Van
Maanen, 1988). One probable reason for this diversity of
approaches is that culture, like role, lies at the intersection
of several social sciences and reflects some of the biases
of eachwspecifically, those of anthropology, sociology,
social psychology, and organizational behavior.
A complete review of the various paradigms and
their implications is far beyond the scope of this article.
Instead I will provide a brief historical overview leading
to the major approaches currently in use and then de-
scribe in greater detail one paradigm, firmly anchored in
social psychology and anthropology, that is somewhat in-
tegrative in that it allows one to position other paradigms
in a common conceptual space.
This line of thinking will push us conceptually into
territory left insufficiently explored by such concepts as
"climate," "norm," and "attitude." Many of the research
methods of industrial/organizational psychology have
weaknesses when applied to the concept of culture. If we
are to take culture seriously, we must first adopt a more
clinical and ethnographic approach to identify clearly the
kinds of dimensions and variables that can usefully lend
themselves to more precise empirical measurement and
Sloan School of Management,
Massachusetts Institute of Technology
I I [ Illll
hypothesis testing. Though there have been many efforts
to be empirically precise about cultural phenomena, there
is still insufficient linkage of theory wit.
Organizational Culture Edgar H. Schein I I I I II I II .docxvannagoforth
Organizational Culture
Edgar H. Schein
I I I I II I II
ABSTRACT: The concept of organizational culture has
received increasing attention in recent years both from
academics and practitioners. This article presents the au-
thor's view of how culture shouM be defined and analyzed
if it is to be of use in the field of organizational psychology.
Other concepts are reviewed, a brief history is provided,
and case materials are presented to illustrate how to an-
alyze culture and how to think about culture change.
To write a review article about the concept of organiza-
tional culture poses a dilemma because there is presently
little agreement on what the concept does and should
mean, how it should be observed and measured, how it
relates to more traditional industrial and organizational
psychology theories, and how it should be used in our
efforts to help organizations. The popular use of the con-
cept has further muddied the waters by hanging the label
of"culture" on everything from common behavioral pat-
terns to espoused new corporate values that senior man-
agement wishes to inculcate (e.g., Deal & Kennedy, 1982;
Peters & Waterman, 1982).
Serious students of organizational culture point out
that each culture researcher develops explicit or implicit
paradigms that bias not only the definitions of key con-
cepts but the whole approach to the study of the phe-
nomenon (Barley, Meyer, & Gash, 1988; Martin & Mey-
erson, 1988; Ott, 1989; Smircich & Calas, 1987; Van
Maanen, 1988). One probable reason for this diversity of
approaches is that culture, like role, lies at the intersection
of several social sciences and reflects some of the biases
of eachwspecifically, those of anthropology, sociology,
social psychology, and organizational behavior.
A complete review of the various paradigms and
their implications is far beyond the scope of this article.
Instead I will provide a brief historical overview leading
to the major approaches currently in use and then de-
scribe in greater detail one paradigm, firmly anchored in
social psychology and anthropology, that is somewhat in-
tegrative in that it allows one to position other paradigms
in a common conceptual space.
This line of thinking will push us conceptually into
territory left insufficiently explored by such concepts as
"climate," "norm," and "attitude." Many of the research
methods of industrial/organizational psychology have
weaknesses when applied to the concept of culture. If we
are to take culture seriously, we must first adopt a more
clinical and ethnographic approach to identify clearly the
kinds of dimensions and variables that can usefully lend
themselves to more precise empirical measurement and
Sloan School of Management,
Massachusetts Institute of Technology
I I [ Illll
hypothesis testing. Though there have been many efforts
to be empirically precise about cultural phenomena, there
is still insufficient linkage of theory wit ...
Towards a Relational Paradigm in Sustainability Research, Practice, and Educa...Zack Walsh
Relational thinking has recently gained increasing prominence across academic disciplines in an attempt to understand complex phenomena in terms of constitutive processes and relations. Interdisciplinary fields of study, such as science and technology studies (STS), the environmental humanities, and the posthumanities, for example, have started to reformulate academic understanding of nature-cultures based on relational thinking. Although the sustainability crisis serves as a contemporary backdrop and in fact calls for such innovative forms of interdisciplinary scholarship, the field of sustainability research has not yet tapped into the rich possibilities offered by relational thinking. Against this background, the purpose of this paper is to identify relational approaches to ontology, epistemology, and ethics which are relevant to sustainability research. More specifically, we analyze how relational approaches have been understood and conceptualized across a broad range of disciplines and contexts relevant to sustainability to identify and harness connections and contributions for future sustainability-related work. Our results highlight common themes and patterns across relational approaches, helping to identify and characterize a relational paradigm within sustainability research. On this basis, we conclude with a call to action for sustainability researchers to co-develop a research agenda for advancing this relational paradigm within sustainability research, practice, and education.
Leadership and Organizational Culture Linking CEOCharacteri.docxsmile790243
Leadership and Organizational Culture: Linking CEO
Characteristics to Cultural Values
Tomas R. Giberson Æ Christian J. Resick Æ
Marcus W. Dickson Æ Jacqueline K. Mitchelson Æ
Kenneth R. Randall Æ Malissa A. Clark
Published online: 26 April 2009
� Springer Science+Business Media, LLC 2009
Abstract
Purpose The purpose of this study was to empirically
examine organizational culture theorists’ assertions about the
linkages between leadership and the cultures that emerge in
the organizations they lead. Specific hypotheses were
developed and tested regarding relationships between chief
executive officers’ (CEO’s) personality traits, and the cultural
values that are shared among their organization’s members.
Design/Methodology/Approach Thirty-two CEOs com-
pleted measures of the Big-Five personality traits and
personal values. A total of 467 employees across the 32
organizations completed a competing values measure of
organizational culture.
Findings Results indicate support for several hypothe-
sized relationships between CEO personality and cultural
values. Exploratory analyses indicated that several CEO
personal values were related to culture values.
Implications Organizations need to seriously consider the
‘‘fit’’ between the current or desired organizational culture
and CEO characteristics. Organizations attempting to
change fundamental aspects of its functioning may need
significant behavioral—or personnel—changes at the top of
the organization in order to achieve those changes.
Originality/Value This is the first empirical study to
establish a link between specific CEO characteristics and
the cultural values of their organizations. This study pro-
vides evidence that CEO characteristics are felt throughout
the organization by impacting the norms that sanction or
discourage member behavior and decision making, and the
patterns of behavior and interaction among members.
Keywords CEO characteristics � Organizational culture �
Leadership � ASA theory � Multi-level research
Introduction
Organizational culture is a topic of considerable interest to
organizational researchers, management consultants, and
corporate executives alike. For example, organizational
culture has been described as a management tool (Trice and
Beyer 1993), credited with creating a competitive advan-
tage (Bennis and Nanus 1985), as the reason behind merger
and acquisition failure (Donahue 2001), and for providing
the basis for success (Denison 1990). An organization’s
culture is also thought to be intricately related to its lead-
ership, particularly its upper echelon leaders (e.g., Bennis
1986; Davis 1984; Quinn and McGrath 1984; Schein 2004;
Trice and Beyer 1993). Yet, as Schneider and Smith (2004)
noted, there is plenty of theory suggesting that leaders have
an effect in their organizations, but little empirical study of
the linkages between leaders’ individual differences and
organizational characteristics and success.
R ...
GregorThe Nature of Theory in ISMIS Quarterly Vol. 30 No..docxwhittemorelucilla
Gregor/The Nature of Theory in IS
MIS Quarterly Vol. 30 No. 3, pp. 611-642/September 2006 611
RESEARCH ESSAY
THE NATURE OF THEORY IN INFORMATION SYSTEMS1
By: Shirley Gregor
School of Accounting and Business Information
Systems
College of Business and Economics
The Australian National University
Canberra ACT 0200
AUSTRALIA
[email protected]
Abstract
The aim of this research essay is to examine the structural
nature of theory in Information Systems. Despite the impor-
tance of theory, questions relating to its form and structure
are neglected in comparison with questions relating to episte-
mology. The essay addresses issues of causality, explanation,
prediction, and generalization that underlie an understanding
of theory. A taxonomy is proposed that classifies information
systems theories with respect to the manner in which four
central goals are addressed: analysis, explanation, predic-
tion, and prescription. Five interrelated types of theory are
distinguished: (1) theory for analyzing, (2) theory for ex-
plaining, (3) theory for predicting, (4) theory for explaining
and predicting, and (5) theory for design and action.
Examples illustrate the nature of each theory type. The appli-
cability of the taxonomy is demonstrated by classifying a
sample of journal articles. The paper contributes by showing
that multiple views of theory exist and by exposing the
assumptions underlying different viewpoints. In addition, it
is suggested that the type of theory under development can
influence the choice of an epistemological approach. Support
1Allen Lee was the accepting senior editor for this paper. M. Lynne Markus,
Michael D. Myers, and Robert W. Zmud served as reviewers.
is given for the legitimacy and value of each theory type. The
building of integrated bodies of theory that encompass all
theory types is advocated.
Keywords: Theory, theory taxonomy, theory structure, infor-
mation systems discipline, philosophy of science, philosophy
of social sciences, interpretivist theory, design theory, design
science, explanation, prediction, causality, generalization
Introduction
The aim of this essay is to examine the structural nature of
theory in the discipline of Information Systems. There are a
number of grounds for believing that this meta-theoretical
exploration is both necessary and timely. Calls continue for
“good theory” in IS (Watson 2001) and the development of
our “own” theory (Weber 2003). Despite the recognition of
the need for theory development, however, there is limited
discussion in IS forums of what theory means in IS and what
form contributions to knowledge can take.
To place this discussion in context, consider the questions that
arise about the bodies of knowledge or theories encompassed
in a discipline. These questions fall into a number of inter-
related classes2:
1. Domain questions. What phenomena are of interest in
the discipline? What are the core problems or topics of
interest? What are the boundar ...
Examine the Relevance of Processes in How Individuals and Organiza.docxSANSKAR20
Examine the Relevance of Processes in How Individuals and Organizations Learn
Instructions
You will now examine how individuals, teams, and the organization as an entity learn.
Identify the significant differences (or similarities) relevant to how each level of the organization learns. Then, prepare an evaluation of two (2) or three (3) significant opportunities that are most needed or likely to have a positive impact in the organization you have chosen to research.
Discuss how you will implement these opportunities and what changes may be required to overcome any obstacles you can anticipate.
Support your evaluation with a minimum of three resources. In addition to these specified resources, other appropriate scholarly resources, including older articles, may be included.
Length: 5-7 pages, not including title and reference pages
Your evaluation should demonstrate thoughtful consideration of the ideas and concepts presented in the course by providing new thoughts and insights relating directly to this topic. Your response should reflect scholarly writing and current APA standards. Be sure to adhere to Northcentral University's Academic Integrity Policy.
Pedagogic challenges in the learning organization
Full Text
· TranslateFull text
·
Introduction
In recent years pedagogical approaches appear increasingly significant regarding learning in working life, workplace learning and learning organizations. Billett (2008) conceptualizes the relations between educational efforts and peoples' everyday learning processes at work as pedagogic issues and qualities. Pedagogic activities as "work-based learning" (Siebert et al. , 2009) and "work-integrated learning" (Martin et al. , 2012) are structured educational attempts to facilitate learning processes at work showing the importance of linking pedagogy and workplace learning together. Although Senge's (1990) interest in dialogue, team learning and leaders' role as teachers, more elaborated pedagogical perspectives are not emphasized in literature on the learning organization (TLO) tradition or in the knowledge management (KM) approach particularly. However, Lustri et al. (2007) propose to connect the tradition of KM to TLO and describe a link between the technical aspects of organizational creation and storing of knowledge and a sociocultural approach of theories of learning. The authors' approach appears as a pedagogic intervention effort considering especially the strategic steering of interpretative and reflective aspects of individuals' learning processes. They also point to the importance of team learning to spread experiences and individual knowledge. Knowledge in an organization is a contextual construction, practice-based and often tacit (Gherardi, 2009). It is a result of complex social processes of team learning and appears difficult to manage effectively (Sondergaard et al. , 2007). This, in turn, increases the interest of pedagogic leadership described as a research-based inte ...
Student ID No. 1619853Contemporary Issues in International.docxcpatriciarpatricia
Student ID No. 1619853
Contemporary Issues in International Management (MOD004160)
List (A) - The Population Ecology of Organisations
Introduction
The journal paper of Hannan and Freeman (1977) looks at the relationship between organisations and the environment and how organisations emerge, grow and die over a long period of time. They apply the population ecology theories to the population of organisations, which they use as their level of analysis, as opposed to the organisation or community level.
Their research is debating that the selection model is favoured over the adaption model, which at the time of their research, the majority of literature was focussed on the adaption model. They favour the selection model due to the structural inertia limiting the organisations ability to adapt to changing environments. They mention the inertial pressures that arise from both internal structural arrangements and environmental constraints and argue that in order to deal with the various inertial pressures the adaption perspective must be supplemented with a selection orientation (pp. 933).
Two broad issues are considered, the first regarding the unit of analyses where they argue for an explicit focus on populations of organisations, rather than the view of a single organisation and the environment. The second is the application of population ecology models to the study of human social organisations.
All the above they hope to answer their research question ‘why are there so many kinds of organisations?’
Literature Review
The fundamental part of their research started with Hawley’s (1950, 1968) statement on human ecology, they state that Hawley’s perspective serves a useful starting point for population ecology theories when extended to include competition models and niche theory.
When reviewing competition theory they continue to focus on the process of selection, in that isomorphism happens because nonoptimal forms are selected out of a community of organisations (pp.939) and that competition is a mechanism for producing isomorphism (pp.940). They use the literature of Hummon, Dorian, and Teuter (1975) and Blau and Scott (1962) to construct their ecological model of competition by stating the nature of the population growth process and to support their view that the rate of growth or decline in populations of organisations is due to environmental changes.
They represent this environmental change by using Hutchinson’s (1957) formulation model to show Levins (1962, 1968) theory of niche width.
Methodology
The paper is a conceptual paper and does not include any empirical research to support their theories. Throughout the paper there are several references to empirical research and at one point the authors expressed their frustration at the lack of empirical research available on rates of selection in populations of organisations (pp.959).
Rather than start from the beginning, Hannan and Freeman (1977) chose to adopt the methodology of Hawley.
Thomas Jefferson UniversityJefferson Digital CommonsScho.docxjuliennehar
Thomas Jefferson University
Jefferson Digital Commons
School of Nursing Faculty Papers & Presentations Jefferson College of Nursing
2-10-2011
Defining and Assessing Organizational Culture
Jennifer Bellot PhD, RN, MHSA
Thomas Jefferson University, [email protected]
Let us know how access to this document benefits you
Follow this and additional works at: http://jdc.jefferson.edu/nursfp
Part of the Nursing Commons
This Article is brought to you for free and open access by the Jefferson Digital Commons. The Jefferson Digital Commons is a service of Thomas
Jefferson University 's Center for Teaching and Learning (CTL). The Commons is a showcase for Jefferson books and journals, peer-reviewed scholarly
publications, unique historical collections from the University archives, and teaching tools. The Jefferson Digital Commons allows researchers and
interested readers anywhere in the world to learn about and keep up to date with Jefferson scholarship. This article has been accepted for inclusion in
School of Nursing Faculty Papers & Presentations by an authorized administrator of the Jefferson Digital Commons. For more information, please
contact: [email protected]
Recommended Citation
Bellot PhD, RN, MHSA, Jennifer, "Defining and Assessing Organizational Culture" (2011). School of
Nursing Faculty Papers & Presentations. Paper 34.
http://jdc.jefferson.edu/nursfp/34
http://jdc.jefferson.edu?utm_source=jdc.jefferson.edu%2Fnursfp%2F34&utm_medium=PDF&utm_campaign=PDFCoverPages
http://jdc.jefferson.edu/nursfp?utm_source=jdc.jefferson.edu%2Fnursfp%2F34&utm_medium=PDF&utm_campaign=PDFCoverPages
http://jdc.jefferson.edu/nurs?utm_source=jdc.jefferson.edu%2Fnursfp%2F34&utm_medium=PDF&utm_campaign=PDFCoverPages
http://jeffline.jefferson.edu/Education/surveys/jdc.cfm
http://jdc.jefferson.edu/nursfp?utm_source=jdc.jefferson.edu%2Fnursfp%2F34&utm_medium=PDF&utm_campaign=PDFCoverPages
http://network.bepress.com/hgg/discipline/718?utm_source=jdc.jefferson.edu%2Fnursfp%2F34&utm_medium=PDF&utm_campaign=PDFCoverPages
http://www.jefferson.edu/university/teaching-learning.html/
Organizational Culture 1
As submitted to:
Nursing Forum
And later published as:
Defining and Assessing Organizational Culture
Volume 46, Issue 1, pages 29–37, January-March 2011
DOI: 10.1111/j.1744-6198.2010.00207.x
The target of much debate, organizational culture has occupied a prominent
position in multidisciplinary publications since the early 1980s. Fraught with
inconsistencies, the early research and literature addressing organizational culture was
often conflicting and recursive. As one researcher stated, culture is “one of the two or
three most complicated words in the English language” (Williams, 1983). Years of
conceptualization, comparison and assessment have led to an emerging consensus on the
appropriate definition and role for organizational culture. This manuscript documents the
h ...
The open academic: Why and how business academics should use social media to ...Ian McCarthy
Abstract: The mission of many business schools and their researchers is to produce research that that impacts how business leaders, entrepreneurs, managers, and innovators, think and act. However, this mission remains an elusive ideal for many business school academics because they struggle to design and produce research capable of overcoming the "research-practice gap." To help those scholars address this gap, we explain why and how they should use social media to be more 'open' to connecting with, learning from, and working with academics and other stakeholders outside of their field. We describe how social media can be used as a boundary-spanning technology to help bridge the research-practice gap. To do this, we present a process model of five research activities: networking, framing, investigating, dissemination, and assessment. Using recently published research as an illustrative example, we describe how social media was used to make each activity more open. We conclude with a framework of different social media-enabled open academic approaches (connector, observer, promoter, and influencer) and some dos and don'ts for engaging in each approach. This paper aims to help business academics rethink and change their practices so that our profession is more widely regarded for how its research positively impacts practice and societal well-being more generally.
Big Data for Creating and Capturing Value in the Digitalized Environment: Unp...Ian McCarthy
Despite significant academic and managerial interest in big data, there is a dearth of research on how big data impacts
the long-term firm performance. Reasons for this gap include a lack of objective indices to measure big data
availability and its impact, and the tendency of studies to ignore the costs associated with collecting and analyzing
big data, assuming that big data automatically delivers benefits to firms. Focusing on how firms create and capture
value from big data about customers, we use the resource-based view and three dimensions of big data (i.e., volume,
variety, and veracity) to understand when the benefits outweigh the costs. Relying on the number of downloads of
mobile device applications, we find that volume of big data has a negative effect on firm performance. This result
suggests that the “bigness” of big data alone does not ensure value creation for a firm, and could even constitute a
“dark side” of big data. Because big data variety—measured as the number of types of information taken per each
application—moderates the negative effects of big data volume, simultaneous high values of volume and variety
allow firms to create value that positively affects their performance. In addition, high levels of veracity (i.e., a high
percentage of employees devoted to big data analysis), are linked to firms benefiting from big data via value capture.
These findings shed light on the circumstances in which big data can be beneficial for firms, contributing to a better
theoretical understanding of the opportunities and challenges and providing useful indications to managers.
Standardization in a Digital and Global World: State-of-the-Art and Future Pe...Ian McCarthy
We discuss how the standards emerge from an interaction between three main sources, the standards standard-setting organizations (SSOs), the competitive market forces, and the government. We present a framework (see Table I) that highlights how these sources differ and work together to shape the standardization in a digital and global context. Also, using this framework, we introduce the contribution of each article of this issue and their contribution to some of the major issues that the standardization is facing today in a digital and global world. We conclude with the suggestions of avenues for future research on this topic.
Open branding: Managing the unauthorized use of brand-related intellectual pr...Ian McCarthy
Consumers often innovate with brand-related intellectual property (IP) without permission. Although firms often respond by exercising their legal right to stop such activity, there are a variety of situations in which consumers’ unauthorized use of brand-related IP can be desirable for a brand or in which enforcing IP rights can adversely affect a brand. This article illustrates situations in which managers may benefit from choosing to forgo exercising their IP rights. To assist managers, this article contributes a framework for understanding the managerial approaches to situations in which consumers use IP without permission.
Does getting along matter? Tourist-tourist rapport in guided group activitiesIan McCarthy
Guided group activities, where tourists consume with other tourists, are common and important. Although the
tourism and services literature suggests customer-employee rapport impacts customer satisfaction, the composition
and impact of tourist-tourist rapport in guided group activities have received minimal attention. We use a
three-study mixed method approach to conceptualize and examine tourist-tourist rapport in guided group activities.
Study 1 identifies two recognized dyadic dimensions of tourist-tourist rapport (enjoyable interaction and
personal connection) and two new group-based dimensions (group attentiveness and service congruity). Study 2
(video experiment) and Study 3 (field experiment) find that enjoyable interaction and personal connection
mediate the relationship between group attentiveness and service congruity with satisfaction. Thus, touristtourist
rapport in a group context is more multidimensional and complex than previously conceptualized for
customer-employee rapport and non-group contexts. Further, we find tourist-tourist rapport is a critical service
factor such that high levels satisfy, while low levels dissatisfy.
Social media? It's serious! Understanding the dark side of social mediaIan McCarthy
Research and practice have mostly focused on the “bright side” of social media, aiming to understand and help in leveraging the manifold opportunities afforded by this technology. However, it is increasingly observable that social media present enormous risks for individuals, communities, firms, and even for society as a whole. Examples for this “dark side” of social media include cyberbullying, addictive use, trolling, online witch hunts, fake news, and privacy abuse. In this article, we aim to illustrate the multidimensionality of the dark side of social media and describe the related various undesirable outcomes. To do this, we adapt the established social media honeycomb framework to explain the dark side implications of each of the seven functional building blocks: conversations, sharing, presence, relationships, reputation, groups, and identity. On the basis of these reflections, we present a number of avenues for future research, so as to facilitate a better understanding and use of social media.
Leveraging social capital in university-industry knowledge transfer strategie...Ian McCarthy
University-industry partnerships emphasise the transformation of knowledge into products and processes which can be commercially exploited. This paper presents a framework for understanding how social capital in university-industry partnerships affect knowledge transfer strategies, which impacts on collaborative innovation developments. University-industry partnerships in three different countries, all from regions at varying stages of development, are compared using the proposed framework. These include a developed region (Canada), a transition region (Malta), and a developing region (South Africa). Structural, relational and cognitive social capital dimensions are mapped against the knowledge transfer strategy that the university-industry partnership employed: leveraging existing knowledge or appropriating new knowledge. Exploring the comparative presence of social capital in knowledge transfer strategies assists in better understanding how university-industry partnerships can position themselves to facilitate innovation. The paper proposes a link between social capital and knowledge transfer strategy by illustrating how it impacts the competitive positioning of the university-industry partners involved.
Do your employees think your slogan is “fake news?” A framework for understan...Ian McCarthy
Purpose – This article explores how employees can perceive and be impacted by the fakeness of their company slogans.
Design/methodology/approach – This conceptual study draws on the established literature on company slogans, employee audiences, and fake news to create a framework through which to understand fake company slogans.
Findings – Employees attend to two important dimensions of slogans: whether they accurately reflect a company’s (1) values and (2) value proposition. These dimensions combine to form a typology of four ways in which employees can perceive their company’s slogans: namely, authentic, narcissistic, foreign, or corrupt.
Research limitations/implications – This paper outlines how the typology provides a theoretical basis for more refined empirical research on how company slogans influence a key stakeholder: their employees. Future research could test the arguments about how certain characteristics of slogans are more or less likely to cause employees to conclude that slogans are fake news. Those conclusions will, in turn, have implications for the
morale and engagement of employees. The ideas herein can also enable a more comprehensive assessment of the impact of slogans.
Practical implications – Employees can view three types of slogans as fake news (narcissistic, foreign, and corrupt slogans). This paper identifies the implications of each type and explains how companies can go about developing authentic slogans.
Originality/value – This paper explores the impact of slogan fakeness on employees: an important audience that has been neglected by studies to
date. Thus, the insights and implications specific to this internal stakeholder are novel.
Making sense of text: artificial intelligence-enabled content analysisIan McCarthy
Purpose – The purpose of this paper is to introduce, apply and compare how artificial intelligence (AI), and specifically the IBM Watson system, can be used for content analysis in marketing research relative to manual and computer-aided (non-AI) approaches to content analysis.
Design/methodology/approach – To illustrate the use of AI enabled content analysis, this paper examines the text of leadership speeches, content related to organizational brand. The process and results of using AI are compared to manual and computer-aided approaches by using three performance factors for content analysis: reliability, validity and efficiency.
Findings – Relative to manual and computer-aided approaches, AI-enabled content analysis provides clear advantages with high reliability, high validity and moderate efficiency.
Research limitations/implications – This paper offers three contributions. First, it highlights the continued importance of the content analysis research method, particularly with the explosive growth of natural language-based user-generated content. Second, it provides a road map of how to use AI-enabled content analysis. Third, it applies and compares AI-enabled content analysis to manual and computer-aided, using leadership speeches.
Practical implications – For each of the three approaches, nine steps are outlined and described to allow for replicability of this study. The advantages and disadvantages of using AI for content analysis are discussed. Together these are intended to motivate and guide researchers to apply and develop AI-enabled content analysis for research in marketing and other disciplines.
Originality/value – To the best of the authors’ knowledge, this paper is among the first to introduce, apply and compare how AI can be used for content analysis.
Confronting indifference toward truth: Dealing with workplace bullshitIan McCarthy
Abstract Many organizations are drowning in a flood of corporate bullshit, and this is particularly true of organizations in trouble, whose managers tend to make up stuff on the fly and with little regard for future consequences. Bullshitting and lying are not synonymous. While the liar knows the truth and wittingly bends it to suit their purpose, the bullshitter simply does not care about the truth. Managers can actually do something about organizational bullshit, and this Executive Digest provides a sequential framework that enables them to do so. They can comprehend it, they can recognize it for what it is, they can act against it, and they can take steps to prevent it from happening in the future. While it is unlikely that any organization will ever be able to rid itself of bullshit entirely, this article argues that by taking these steps, astute managers can work toward stemming its flood.
The Promise of Digitalization: Unpacking the Effects of Big Data Volume, Vari...Ian McCarthy
Despite significant academic and managerial interest in big data, there is a dearth of research on how big data impacts long-term firm performance. Reasons for this gap include a lack of objective indices to measure big data availability and its impact, and the tendency of studies to ignore the costs associated with collecting and analyzing big data, assuming that big data automatically delivers benefits to firms. Focusing on how firms create and capture value from big data about customers, we use the resource-based view (RBV) and three dimensions of big data (i.e., volume, variety and veracity) to understand when the benefits outweigh the costs. Relying on the number of downloads of mobile device applications, we find that volume of big data has a negative effect on firm performance. This result suggests that the ‘bigness’ of big data alone does not ensure value creation for a firm, and could even constitute a ‘dark side’ of big data. Because big data variety – measured as the number of types of information taken per each application – moderates the negative effects of big data volume, simultaneous high values of volume and variety allow firms to create value that positively affects their performance. In addition, high levels of veracity (i.e., a high percentage of employees devoted to big data analysis), are linked to firms benefiting from big data via value capture. These findings shed light on the circumstances in which big data can be beneficial for firms, contributing to a better theoretical understanding of the opportunities and challenges and providing useful indications to managers.
Masterclass: Confronting indifference to truthIan McCarthy
Many organizations are drowning in a flood of corporate bullshit, and this is particularly true of organizations in trouble, whose managers tend to make up stuff on the fly and with little regard for future consequences. Bullshitting and lying are not synonymous. While the liar knows the truth and wittingly bends it to suit their purpose, the bullshitter simply does not care about the truth. Managers can actually do something about organizational bullshit, and this Executive Digest provides a sequential framework that enables them to do so. They can comprehend it, they can recognize it for what it is, they can act against it, and they can take steps to prevent it from happening in the future. While it is unlikely that any organization will ever be able to rid itself of bullshit entirely, this article argues that by taking these steps, astute managers can work toward stemming its flood.
Confronting indifference toward truth: Dealing with workplace bullshitIan McCarthy
Many organizations are drowning in a flood of corporate bullshit, and this is particularly true of organizations in trouble, whose managers tend to make up stuff on the fly and with little regard for future consequences. Bullshitting and lying are not synonymous. While the liar knows the truth and wittingly bends it to suit their purpose, the bullshitter simply does not care about the truth. Managers can actually do something about organizational bullshit, and this Executive Digest provides a sequential framework that enables them to do so. They can comprehend it, they can recognize it for what it is, they can act against it, and they can take steps to prevent it from happening in the future. While it is unlikely that any organization will ever be able to rid itself of bullshit entirely, this article argues that by taking these steps, astute managers can work toward stemming its flood.
Although manipulations of visual and auditory media are as old as the media themselves, the recent entrance of deepfakes has marked a turning point in the creation of fake content. Powered by latest technological advances in AI and machine learning, they offer automated procedures to create fake content that is harder and harder to detect to human observers. The possibilities to deceive are endless, including manipulated pictures, videos and audio, that will have large societal impact. Because of this, organizations need to understand the inner workings of the underlying techniques, as well as their strengths and limitations. This article provides a working definition of deepfakes together with an overview of the underlying technology. We classify different deepfake types: photo (face- and body-swapping), audio (voice-swapping, text to speech), video (face-swapping, face-morphing, full body puppetry) and audio & video (lip-synching), and identify risks and opportunities to help organizations think about the future of deepfakes. Finally, we propose the R.E.A.L. framework to manage deepfake risks: Record original content to assure deniability, Expose deepfakes early, Advocate for legal protection and Leverage trust to counter credulity. Following these principles, we hope that our society can be more prepared to counter the deepfake tricks as we appreciate its treats.
Social media? It’s serious! Understanding the dark side of social mediaIan McCarthy
Research and practice have mostly focused on the “bright side” of social media, aiming to understand and help in leveraging the manifold opportunities afforded by this technology. However, it is increasingly observable that social media present enormous risks for individuals, communities, firms, and even the whole of society. Examples for this “dark side” of social media include cyberbullying, addictive use, trolling, online witch hunts, fake news, and privacy abuse. In this article, we aim to illustrate the multidimensionality of the dark side of social media and describe the related various undesirable outcomes. To do this, we adapt the established social media honeycomb framework to explain the dark side implications of each of the seven functional building blocks: conversations, sharing, presence, relationships, reputation, groups, and identity. On the basis of these reflections, we present a number of avenues for future research, so as to facilitate a better understanding and use of social media.
The propensity and speed of technology licensing: at LUISS Guido Carli Univer...Ian McCarthy
Licensing speed: There has been much research interest in the speed of innovation, although few consistent findings have emerged. In this study, we unpack the innovation process and focus on the commercialization stage to examine two questions: Which licensor and patent characteristics determine the speed of licensing? How does the speed of licensing impact the royalties and lumpsum payments to licensors? We addressed these questions by proposing that licensing speed is influenced by variables for licensor prominence (size and experience), licensor knowledge structuration (technological depth, technological breadth and experience), and patent appeal (forward citations, scope and complexity). We predict and find that these variables work to increase the size, complexity and duration of the licensing-out task, while also allowing licensors to take their time to review, negotiate and select agreements with higher royalty rates. These findings are counter to arguments for a fast-paced innovation strategy, as it suggests that for the commercialization stage of the innovation process the relationship between licensing speed and licensor royalty
rates rewards a ‘less haste, greater payoff approach.
Seven steps for framing and testing a research paperIan McCarthy
I use the steps in this presentation to:
(i) test research ideas for research papers,
(ii) shape research papers, and
(iii) help draft the Introduction section of a research paper.
For each step I draft one or two concise paragraphs.
I then present and share these with co-authors, collaborators and colleagues to test the ideas and get feedback on how interesting and valid they are.
I consider and work through these steps several times during the life of a research paper framed.
Cracking the Workplace Discipline Code Main.pptxWorkforce Group
Cultivating and maintaining discipline within teams is a critical differentiator for successful organisations.
Forward-thinking leaders and business managers understand the impact that discipline has on organisational success. A disciplined workforce operates with clarity, focus, and a shared understanding of expectations, ultimately driving better results, optimising productivity, and facilitating seamless collaboration.
Although discipline is not a one-size-fits-all approach, it can help create a work environment that encourages personal growth and accountability rather than solely relying on punitive measures.
In this deck, you will learn the significance of workplace discipline for organisational success. You’ll also learn
• Four (4) workplace discipline methods you should consider
• The best and most practical approach to implementing workplace discipline.
• Three (3) key tips to maintain a disciplined workplace.
Implicitly or explicitly all competing businesses employ a strategy to select a mix
of marketing resources. Formulating such competitive strategies fundamentally
involves recognizing relationships between elements of the marketing mix (e.g.,
price and product quality), as well as assessing competitive and market conditions
(i.e., industry structure in the language of economics).
Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.
"𝑩𝑬𝑮𝑼𝑵 𝑾𝑰𝑻𝑯 𝑻𝑱 𝑰𝑺 𝑯𝑨𝑳𝑭 𝑫𝑶𝑵𝑬"
𝐓𝐉 𝐂𝐨𝐦𝐬 (𝐓𝐉 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬) is a professional event agency that includes experts in the event-organizing market in Vietnam, Korea, and ASEAN countries. We provide unlimited types of events from Music concerts, Fan meetings, and Culture festivals to Corporate events, Internal company events, Golf tournaments, MICE events, and Exhibitions.
𝐓𝐉 𝐂𝐨𝐦𝐬 provides unlimited package services including such as Event organizing, Event planning, Event production, Manpower, PR marketing, Design 2D/3D, VIP protocols, Interpreter agency, etc.
Sports events - Golf competitions/billiards competitions/company sports events: dynamic and challenging
⭐ 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐝 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬:
➢ 2024 BAEKHYUN [Lonsdaleite] IN HO CHI MINH
➢ SUPER JUNIOR-L.S.S. THE SHOW : Th3ee Guys in HO CHI MINH
➢FreenBecky 1st Fan Meeting in Vietnam
➢CHILDREN ART EXHIBITION 2024: BEYOND BARRIERS
➢ WOW K-Music Festival 2023
➢ Winner [CROSS] Tour in HCM
➢ Super Show 9 in HCM with Super Junior
➢ HCMC - Gyeongsangbuk-do Culture and Tourism Festival
➢ Korean Vietnam Partnership - Fair with LG
➢ Korean President visits Samsung Electronics R&D Center
➢ Vietnam Food Expo with Lotte Wellfood
"𝐄𝐯𝐞𝐫𝐲 𝐞𝐯𝐞𝐧𝐭 𝐢𝐬 𝐚 𝐬𝐭𝐨𝐫𝐲, 𝐚 𝐬𝐩𝐞𝐜𝐢𝐚𝐥 𝐣𝐨𝐮𝐫𝐧𝐞𝐲. 𝐖𝐞 𝐚𝐥𝐰𝐚𝐲𝐬 𝐛𝐞𝐥𝐢𝐞𝐯𝐞 𝐭𝐡𝐚𝐭 𝐬𝐡𝐨𝐫𝐭𝐥𝐲 𝐲𝐨𝐮 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐚 𝐩𝐚𝐫𝐭 𝐨𝐟 𝐨𝐮𝐫 𝐬𝐭𝐨𝐫𝐢𝐞𝐬."
Buy Verified PayPal Account | Buy Google 5 Star Reviewsusawebmarket
Buy Verified PayPal Account
Looking to buy verified PayPal accounts? Discover 7 expert tips for safely purchasing a verified PayPal account in 2024. Ensure security and reliability for your transactions.
PayPal Services Features-
🟢 Email Access
🟢 Bank Added
🟢 Card Verified
🟢 Full SSN Provided
🟢 Phone Number Access
🟢 Driving License Copy
🟢 Fasted Delivery
Client Satisfaction is Our First priority. Our services is very appropriate to buy. We assume that the first-rate way to purchase our offerings is to order on the website. If you have any worry in our cooperation usually You can order us on Skype or Telegram.
24/7 Hours Reply/Please Contact
usawebmarketEmail: support@usawebmarket.com
Skype: usawebmarket
Telegram: @usawebmarket
WhatsApp: +1(218) 203-5951
USA WEB MARKET is the Best Verified PayPal, Payoneer, Cash App, Skrill, Neteller, Stripe Account and SEO, SMM Service provider.100%Satisfection granted.100% replacement Granted.
RMD24 | Retail media: hoe zet je dit in als je geen AH of Unilever bent? Heid...BBPMedia1
Grote partijen zijn al een tijdje onderweg met retail media. Ondertussen worden in dit domein ook de kansen zichtbaar voor andere spelers in de markt. Maar met die kansen ontstaan ook vragen: Zelf retail media worden of erop adverteren? In welke fase van de funnel past het en hoe integreer je het in een mediaplan? Wat is nu precies het verschil met marketplaces en Programmatic ads? In dit half uur beslechten we de dilemma's en krijg je antwoorden op wanneer het voor jou tijd is om de volgende stap te zetten.
Unveiling the Secrets How Does Generative AI Work.pdfSam H
At its core, generative artificial intelligence relies on the concept of generative models, which serve as engines that churn out entirely new data resembling their training data. It is like a sculptor who has studied so many forms found in nature and then uses this knowledge to create sculptures from his imagination that have never been seen before anywhere else. If taken to cyberspace, gans work almost the same way.
Premium MEAN Stack Development Solutions for Modern BusinessesSynapseIndia
Stay ahead of the curve with our premium MEAN Stack Development Solutions. Our expert developers utilize MongoDB, Express.js, AngularJS, and Node.js to create modern and responsive web applications. Trust us for cutting-edge solutions that drive your business growth and success.
Know more: https://www.synapseindia.com/technology/mean-stack-development-company.html
Improving profitability for small businessBen Wann
In this comprehensive presentation, we will explore strategies and practical tips for enhancing profitability in small businesses. Tailored to meet the unique challenges faced by small enterprises, this session covers various aspects that directly impact the bottom line. Attendees will learn how to optimize operational efficiency, manage expenses, and increase revenue through innovative marketing and customer engagement techniques.
Skye Residences | Extended Stay Residences Near Toronto Airportmarketingjdass
Experience unparalleled EXTENDED STAY and comfort at Skye Residences located just minutes from Toronto Airport. Discover sophisticated accommodations tailored for discerning travelers.
Website Link :
https://skyeresidences.com/
https://skyeresidences.com/about-us/
https://skyeresidences.com/gallery/
https://skyeresidences.com/rooms/
https://skyeresidences.com/near-by-attractions/
https://skyeresidences.com/commute/
https://skyeresidences.com/contact/
https://skyeresidences.com/queen-suite-with-sofa-bed/
https://skyeresidences.com/queen-suite-with-sofa-bed-and-balcony/
https://skyeresidences.com/queen-suite-with-sofa-bed-accessible/
https://skyeresidences.com/2-bedroom-deluxe-queen-suite-with-sofa-bed/
https://skyeresidences.com/2-bedroom-deluxe-king-queen-suite-with-sofa-bed/
https://skyeresidences.com/2-bedroom-deluxe-queen-suite-with-sofa-bed-accessible/
#Skye Residences Etobicoke, #Skye Residences Near Toronto Airport, #Skye Residences Toronto, #Skye Hotel Toronto, #Skye Hotel Near Toronto Airport, #Hotel Near Toronto Airport, #Near Toronto Airport Accommodation, #Suites Near Toronto Airport, #Etobicoke Suites Near Airport, #Hotel Near Toronto Pearson International Airport, #Toronto Airport Suite Rentals, #Pearson Airport Hotel Suites
Business Valuation Principles for EntrepreneursBen Wann
This insightful presentation is designed to equip entrepreneurs with the essential knowledge and tools needed to accurately value their businesses. Understanding business valuation is crucial for making informed decisions, whether you're seeking investment, planning to sell, or simply want to gauge your company's worth.
The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
2. 272 McCARTHY
This ability to order and represent differences has aided our philosophical and
scientific studies of biological, social, economic and technological entities, but it
is important to recognize that the cognitive models produced by any classification
are like the classifications themselves, incomplete, parsimonious and constantly
evolving. Consequently, a classification should permit continuous development and
refinement, whilst providing simple and powerful explanations of complex phe-
nomena (Schumacher & Czerwinski 1992). This intellectual and perspicacious
activity was discussed by Good (1965), who explained that classifications are
constructed for reasons that range from the need to conduct rigorous academic
research, to the desire to produce simple and fun check lists. Yet regardless of the
purpose, the value of any good classification is its ability to help organize and reg-
ulate data and thoughts about our reality and then develop and communicate asso-
ciated ideas.
In accord with the academic purpose of classification, scholars concerned with
the economic (Coase 1937, Williamson & Masten 1999), technological (Chan-
dler 1990) and behavioral (Cyert & March 1963, Wernerfelt 1984) views of the
firm, have long sought to understand organizational variety, change and survival.
To help study these issues, it has been necessary to develop appropriate frame-
works, essentially classifications, which characterize the interconnectivity between
the dimensions (managerial, technological, structural, market, etc.) that differenti-
ate organizations. Likewise classifications have been produced to map the develop-
ment and diffusion of different process and product technologies. As early as the
19th century Babbage (1835) sought to promote comprehension and adoption of
the various manufacturing processes that existed. His classification was based on
factors such as the newness of the technology, the type of power consumption,
the process control used, the transformational properties of the technology and
the utility of the technology. Although his ideas never developed into a universal
system of technological classification, they are consistent with the focus of mod-
ern classifications dealing with innovation. These include innovation versus inven-
tion and imitation (Schumpeter 1934), innovation as an output and process (Daft
1978), innovation newness (Dewar & Dutton 1986), and the adoption of innova-
tions (Subramanian 1996).
As a gesture to Good’s (1965) assertion that some people simply produce clas-
sifications for fun, it is worth mentioning an interesting and teasing classification
presented by Borges (1964, pp. 101–105). At first this classification appears to be
strange but genuine, but as no other record of the classification exists, it seems
that Borges fabricated it to amuse and demonstrate the role of perception in clas-
sification. He refers to a Chinese encyclopedia entitled, The Celestial Emporium
of Benevolent Knowledge, in which it is written that ‘animals are divided into: (a)
belonging to the Emperor, (b) embalmed, (c) tame, (d) sucking pigs, (e) sirens, (f)
fabulous, (g) stray dogs, (h) included in the present classification, (i) frenzied, (j)
innumerable, (k) drawn with a very fine camelhair brush, (1) et cetera, (m) having
just broken the water pitcher, (n) that from a long way off look like flies.’ Borges’
3. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 273
classification illustrates how incomprehensible a classification can be to those who
are not familiar with the local context or rationales which govern the criteria for
differentiating. Thus, different societies can sometimes describe and classify things
that bewilder researchers in other societies.
This issue of perception and sense making of reality is central to the process
of classifying organizations, as different areas of organizational science and eco-
nomics will use different perspectives to recognize or ascertain what makes orga-
nizations different. Thus, when determining the unit of analysis for classification,
one must recognize the pitfalls of researcher bias, which can become amplified
through confusion and misuse of the various terms, methods and levels of analysis
involved with classification. Yet these problems are not unique to the classification
of organizations, as there is also a history of significant dispute concerning the unit
of analysis in biological classification literature. This is a problem which Keller
et al. (2003) call ‘semantic schizophrenia’, as many biological researchers appear to
have been largely unaware of the philosophical positions implied by their approach
to classification (de Queiroz 1994). For the study of organizational diversity to
advance, those involved in the discipline must recognize and address these system-
atic issues. Otherwise, they will continue to produce classifications that sometimes
reference each other, but rarely join with or expand on each other.
This situation is the impetus for this paper, which introduces and examines the
feasibility and value of using cladistic analysis to study and represent organiza-
tional genealogy. It argues that the cladistic focus on shared patterns of common
ancestry is an evolutionary logic compatible with the variation, selection and reten-
tion explanations for how and why new organizational taxa emerge. This paper
extends existing research on organizational systematics by (McKelvey 1975, 1978,
1982, Warriner 1979, Haas et al. 1966, Pugh et al. 1969, Rich 1992, Doty & Glick
1994, Bailey 1994) and advances more recent research that has developed ini-
tial and primitive cladistic analyses of organizations (McCarthy et al. 1997, 2000,
Leseure 2000), industries (Leask 2002, Andersen 2003) and organizational innova-
tion and industrial development (Baldwin et al. 2003).
2. A review of classification
The first formal classifications sought to make sense of the natural world and were
produced by philosophers and biologists. This intellectual combination led to the
development of a number of related and competing theoretical stances about how
to classify. As classification is now an established research process in the physical,
life and social sciences, the result is a diverse range of interpretations and fre-
quent misuse of classification terms, theories and methods. This has created seman-
tic barriers which affect how classifications are constructed and reported. With this
section of the paper, I hope to avoid similar misconceptions and provide a degree
of terminological clarity.
4. 274 McCARTHY
First, the overriding term that refers to the general study of diversity is sys-
tematics (Simpson 1961). It is viewed as an area of biology that deals with the
study of different types of organisms, their distinction, classification, and evolution
(Blackwelder & Boyden 1952). The term taxonomy refers to a branch of systemat-
ics concerned with the theory and practice of producing classification systems and
schemes. Thus, constructing a classification is a taxonomic process with rules on
how to form and represent groups (taxa), which are then named (nomy). Within
biology, three schools have dominated the recent history of classification: evolu-
tionary, phenetic and cladistic (these are discussed in next section of the paper),
while the social sciences have two general approaches to classification: empirical
and theoretical. The principal difference between the two social science approaches
is the stage at which a theory of differences is proposed and evidence then sought
to validate the theory (Warriner 1984, Rich 1992, Dotty & Glick 1994). Theoreti-
cal classifications in the social sciences begin by developing a theory of differences
that result in a classification of organizational types, known as a typology. Only
when the classification has been proposed, is a decision made as to where an entity
belongs in the classification. On the other hand, with the empirical approach,
social science classifications begin by gathering data about the entities under study.
The data are then processed using statistical methods (numerical taxonomy) to
produce groups according to the measures of similarity and statistical techniques
used. Thus the overall aim is to use data to construct the classification, instead
of supporting it, but it should be noted that in practice data are seldom collected
without an expectation about what they will reveal or validate. It is also impor-
tant to note, that most organizational classifications (theoretical and empirical) do
not properly define the unit and level of analysis, and therefore misuse the terms
taxon, group, class and type when presenting their classifications. This is probably
the main reason why most organizational classifications remain solitary, undevel-
oped and unconnected to other organizational classifications.
Although the term classification has been used throughout this paper to reflect
the topic of this paper and of this Special Issue of the Journal of Bioeconomics,
there is no agreement among biologists about the general use of the term. But if
we inspect its use across disciplines and relevant entries in dictionaries, there is
a distinction between classification as a process (to classify) and classification as
an output of the process (a classification). In the first instance, it represents the
sorting and arrangement of information in a way that will inform (Ghiselin 1997).
This definition partly relates to the mathematical and information theory concept
of classification, which assumes that given an equivalence relation for a subset of
a set of entities, there will be a partitioning of the set into a number of mutu-
ally disjoint equivalence classes (this use of the term class is not equivalent to the
biological taxonomic terms, classes or categories). Hence, classification as a pro-
cess should not be confused with categorical assignment (Scheffler 1967), deter-
mination (Radford et al. 1974), class identification (Capecchi & Moller 1968) and
5. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 275
identification (Capecchi 1964), which are concerned with determining where enti-
ties, taxa and classes should appear in a classification.
Classification as an output (a product of the process of classifying) deals with
how groups and classes of entities will be arranged, in accord with the taxonomic
approach used (Mayr 1982, McKelvey 1982). It is a framework (e.g. a matrix, a
table, a tree diagram, etc.) for ordering and representing, regardless of whether a
theoretical or empirical approach is used. The terms classification scheme and classi-
fication system are often used to distinguish and identify classification as an output
(Fox 1982). Examples of such schemes and systems include the Linnaean System of
nomenclature, the Periodic Classification of chemical elements, the Dewey Decimal
Classification System for organizing books and other bibliographic items, and the
North American Industrial Classification (NAIC) and Standard Industrial Classifi-
cation (SIC) systems for naming and organizing industry sectors.
2.1. The evolutionary, phenetic, and cladistic schools of classification
To understand the differences between the biological schools of classification, it is
helpful to have a basic appreciation of the history of classification philosophies,
and in particular, the concepts of phylogeny and phenetics. This is because the
three schools vary in how (if at all) they represent phylogeny, the types of groups
they recognize and the different types of characters they use to determine groups
(see Figure 1 and Table 1). As the history of classification is complicated and
made-up of a number interconnected areas and eras of thinking, I will simply sum-
marize some of the key issues. For more detailed accounts of how the competing
schools evolved, the reader is referred to Cain (1962), Mayr (1969), Hull (1988)
and Sneath (1995).
Prior to the publication of The Origin of Species (Darwin 1859, [1996 edition]),
the first formal classifications generally sought to make sense of the natural world
by grouping organisms according to their size, structure, features, mode of repro-
duction, and where they existed (location). This approach to classification can be
traced back to Aristotelian essentialism, a philosophical belief that entities have a
set of characteristics which make them what they are. The focus is on conceiv-
ing of groups according to their hidden reality and the resulting biological classi-
fications are known as typologies, because members of a group are considered to
have the same essence and are therefore the same type (Hull 1965, Mayr 1969).
This notion of classifying using observed features is also the basis of phenetics,
which classifies organisms based on similarities and differences in as many observ-
able characteristics as possible. There is also a doctrine (nominalism) that denies
the existence of universals and therefore rejects the concepts of sets and groups.
Nominalism believes that only individuals exist and that all proposed groupings of
entities are simply artifacts of the human mind. Not surprisingly, it does not fea-
ture as a practicing taxonomic approach.
6. 276 McCARTHY
Figure 1. Types of taxonomic characters and groups. Adapted from Ridley (1993, p. 366).
Table 1. Differences between phenetic, cladistic and evolutionary classifications
Classification Characters used
Groups recognised Homologies
Monophyletic Paraphyletic Polyphyletic Analogies Ancestral Derived
Phenetic Yes Yes Yes Yes Yes Yes
Phylogenetic Yes No No No No Yes
Evolutionary Yes Yes No No Yes Yes
Source: Ridley (1993, p. 367).
With the development of the Linnaean system for assigning and naming spe-
cies, the essentialist approach had a convenient and stable information system,
motivating years of taxonomic activity, much of which was identification rather
than classification (Schuh 2003). However, with the publication of The Origin of
the Species, taxonomists were provided with an alternative to the essentialist and
7. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 277
nominalist views of diversity. In very simple terms, the thesis was that natural
groups did exist and that this is because members of a group have descended from
a recent and common ancestor. The term phylogeny was coined by Haeckel (1866),
a German biologist and philosopher, to indicate these ancestor-descendant rela-
tionships. He showed how these relationships could be represented with his ‘tree
of life’, a branching diagram that illustrated his view of the evolution of life from
bacteria to humans. Thus, phylogenetics, the evolutionary relationships between
organisms, became the central principle which differentiated the evolutionary, phe-
netic and cladistic schools of classification.
In the 1930s and 1940s biologists had accepted the broad premise of Darwin’s
theory of evolution and with advances in genetics this resulted in a resurgence
for evolutionary biology and systematics. The focus was on reconciling Darwin’s
theory of evolution with genetics as the basis for biological inheritance and thus
this era gave rise to the evolutionary school of classification (Mayr 1942, Simp-
son 1961). This school recognizes that evolution occurs and utilizes both phenetic
and phylogenetic relationships. It also recognizes and accepts paraphyletic groups
(a group containing the ancestor together with some, but not all of the descen-
dants) and monophyletic groups (a group containing the ancestor together with
all descendants), thereby using derived and ancestral homologies, which are cor-
respondingly characters with advanced or primitive states shared by two or more
taxa and present in their ancestor (see Figure 1 and Table 1). However, the mixing
of phenetic and phylogenetic information, coupled with the uncertainty of delim-
iting paraphyletic groups results in phylogenies that are difficult to translate into
unequivocal classifications.
The phenetic school of classification emerged in the late 1950s and early
1960s (Michener & Sokal 1957, 1958, Sokal 1962) as an alternative and oppos-
ing approach to the evolutionary school, but the origins of the basic phenetic
approach (observed similarities) can be traced back to the mid 1800s. Whewell
(1840) and Mill (1843) suggested that the grouping of entities on the basis of
shared properties could provide a system that minimizes information management,
while maximizing knowledge. Then Gilmour (1937, p. 1040) in support of the phe-
netic approach, argued that a classification should strive to provide ‘an arrange-
ment of living things which enables the greatest number of inductive statements to
be made regarding its constituent groups and which is therefore the most generally
useful for the classification of living things.’ Thus, the phenetic approach places
emphasis on collecting and processing data to produce what it calls information
rich groups, rather than theory led groups.
Phenetics flourished with the developments in computing technology in the
1950s and the work on numerical taxonomy in the 1960s (Sokal & Sneath 1963).
This was the period when phenetics became a recognized school of classification
concerned with using a set of statistical methods (know as numerical taxonomy) to
group entities on the basis of observed similarities and according to certain mea-
sures of similarity.
8. 278 McCARTHY
Phenetics ignores the evolutionary history of the entities under study and Sneath
(1988, 1995) attempts to justify this point by reasoning that the periodic table in
chemistry cannot be constructed phylogeneticaly, therefore suggesting that informa-
tion rich groups do not have to evolve. Thus, phenetics discounts any theory that
might explain differences, such as the theory of evolution for biological organisms
and the theory of electron structures for chemical elements. It simply contends that
the best measure of relatedness is overall similarity.
The numerical taxonomy component of the phenetic school is mathematical in
discipline, but biological in application and some of the first applications of these
statistical methods occurred in anthropology (Driver & Kroeber 1932) and psy-
chology (Zubin 1938). As reported by Sokal & Sneath (1963), the early aims and
assumptions of numerical taxonomy in biology revolved around: (1) the need for
repeatability and objectivity; (2) the use of quantitative measures of resemblance
from numerous equally weighted characters; (3) the construction of taxa from
character correlations leading to groups of high information content and (4) the
separation of phenetic and phylogenetic considerations. To address this last objec-
tive, the unit of analysis, called the operational taxonomic unit (OTU), should be
as theory and subject neutral as possible. The OTU is simply a group of entities
that is considered to be the ‘the lowest ranking taxa in a given study’ (Sneath &
Sokal 1973, p. 69).
The product of numerical taxonomy is a dendrogram, or tree diagram (Figure 2).
This term was first introduced by Mayr et al. (1953, pp. 575–578) who defined a
dendrogram as ‘. . . a diagrammatic illustration of relationships based on degrees
of similarity (morphological or otherwise). . . .’ Nearly two thirds of numeri-
cal taxonomy applications involve using the hierarchical agglomerative technique
(Blashfield & Aldenderfer 1978) to produce dendrograms that illustrate the fusions
or divisions of groups of entities made at each consecutive stage of the analysis.
They are an expanding or hierarchical structure that continues until the initial
group can no longer be sub-divided. The different types of agglomerative tech-
niques arise from the various methods of establishing distance (the measure of
the phenetic difference between two groups of entities) or similarity. Other names
for numerical taxonomy include mathematical taxonomy (Jardine & Simpson 1971),
numerical classification (Clifford and Stephenson 1975) and multivariate morpho-
metrics (Blackith & Reyment 1971), while the mathematical mechanics of the
method spawned a host of related techniques, including clustering or cluster analy-
sis (Everitt 1986), clumping (Needham 1965) and pattern recognition (Bezdek 1981).
The acknowledged limitations of phenetics and numerical taxonomy revolve
around the methodological assumptions and operational procedures they follow.
For example, not all characters are equally important and phenetics does not
offer an objective way to select those that are. As a result, emphasis is placed
on using all possible characters to avoid residual weighting. This raises questions
concerning what characters are and how they should be determined. In a gen-
eral and fundamental sense, characters are discernible features of an organism,
9. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 279
A’
Branch
Taxa A
Distance between Taxa A and
Node Taxa B = A’ + B’
Taxa B
B’
Taxa C
Taxa D
Taxa E
Branch Length
Taxa F
Figure 2. A dendrogram.
used to distinguish it from other organisms. But should such features be mor-
phological, physiological, ecological or behavioral? At what level (species, genus,
family, etc.) in a classification would a character be diagnostic? How are the char-
acter states determined? To help understand the complexity and relevance of these
issues, Ghiselin (1997) and Inglis (1991) provide discussions concerning the phi-
losophy and definition of characters for biological classification in general, while
Sneath & Sokal (1973) present categories of inadmissible characters that do not
contribute to the mathematical tightness of a group in numerical taxonomy. A final
and major criticism of the phenetic school of classification is that it does not pro-
vide an explanation of how researchers should actually define and collect the unbi-
ased and theory-free data that is central to its tenet. Thereby suggesting that it is
not possible to both classify and make theory-free observations.
In summary, numerical taxonomy and phenetics have become synonymous, as
the former provides a method and rules that are appropriate to the observed and
empirical nature of the latter. However, it is important to note that with modern
10. 280 McCARTHY
day classification, phenetic, cladistic or otherwise, there is an obvious need to use
numerical methods to help process and order the data that constitute any classifi-
cation. Numerical taxonomy has become an established methodological tool that
is broader than phenetics and cladistics and is used by many disciplines includ-
ing organizational science (Goronzy 1969, Pinto & Pinder 1972, Hayes et al. 1983),
psychiatry (Pilowsky et al. 1969), medicine (Wastell & Gray 1987), market research
(Green et al. 1967), education (Aitken et al. 1981), archaeology (Hodson 1971) and
economics (Wooldridge 2003, Bischi et al. 2003, Sellenthin & Hommen 2002).
During the same period that phenetics and numerical taxonomy were coming to
prominence, an alternative school began to emerge. The figurehead for this school
was the German entomologist Willi Hennig (1950), who believed that evolutionary
history should play a greater role in taxonomy. With early evolutionary taxonomy
the aim was to produce classifications that reflected all aspects of phylogeny, but
this was problematic (Hull 1985). Hennig recommended that biological classifica-
tions should only focus on one aspect of phylogeny, the relative recency of com-
mon ancestry. In particular, Hennig explained that even if two taxa share a large
number of homologies, their classification within the same group cannot be conclu-
sively assumed, as homologies can result from shared derived characters or shared
ancestral characters (Figure 1). To ascribe evolutionary relationships, only shared
derived homologies (synapomorphies) should be taken into consideration. Hennig’s
work was inspired partly by his desire to counter the German school of idealistic
morphological systematics (Schindewolf 1950), which was a fundamental form of
phenetics. He originally called his approach phylogenetic systematics, but his sup-
porters and to a degree his opponents adopted the name cladistics from the Greek
Kλαδos for branch. Thus, cladistics is approximately equal to phylogenetic system-
atics and originally meant the study of clades, which are ‘the individual branches
in the genealogical nexus’ (Ghiselin 1997, p. 306). The term cladism refers to the
movement that supported Hennig’s approach to classification and the product of
a cladistic analysis is known as a cladogram (Figure 3). Cladograms are tree-like
diagrams that depict the pattern of relationships among clades based upon shared
derived characters. The branches represent taxa, while the tips of the branches are
generally species.
Although Hennig explored mathematical set theory as an underlying reason and
principle to rationalize the resulting hierarchical and nested sets of taxa in a clad-
ogram, his primary justification for grouping by synapomorphy was to try to pro-
duce natural and objective classifications based upon the process of evolution.
There is still significant debate as to whether a theory of evolution is a philosoph-
ical prerequisite for biological classification, or rather that biological classifications
provide evidence to support a theory of evolution (Brower 2000). In support of the
former view, Wiley (1975, p. 234) interpreted and translated Hennig’s justification
of cladistic methods into three axioms: (i) evolution occurs; (ii) only one phylogeny
of all living and extinct organisms exists, and this phylogeny is the result of genea-
logical descent; and (iii) characters may be passed from one generation to the next
11. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 281
node
branches
Ch 1
T1 T2 T3 T4
outgroup ingroup
T- Taxa, a named group of two or more entities.
Ch - Characters, an observable feature of entity, that can be used
to distinguish it from other entities.
Outgroup - The taxon used to help resolve the polarity of characters.
Ingroup - The group of interest.
Node - A point on a cladogram where three or more branches meet.
Branch - A line connecting to two nodes. Indicates taxa.
Figure 3. A cladogram.
generation, modified or unmodified, through genealogical descent. Meanwhile sup-
porters of the alternative view hold that the following axioms are necessary and
sufficient for cladistics: (i) observed character differences among taxa provide the
evidentiary basis; (ii) an irregular bifurcating hierarchy is a useful way to represent
relationships among taxa; and (iii) parsimony is the guiding epistemological prin-
ciple of the systematic approach (Platnick 1979, Nelson & Platnick 1981, Brower
2000). Regardless of whether you believe evolution provides a necessary and under-
lying ontological basis for cladistics, or if you assert that evolution is a relevant,
but methodologically redundant assumption for cladistics (Carpenter 1987), it is
generally accepted that cladistic analysis is valid for representing the patterns of
phylogenetic relationships.
As with phenetics, cladistics has limitations due to its assumptions and proce-
dures. For example, the task of choosing appropriate characters remains problem-
atic. If the cladistic method is applied to lions, tigers and zebras, using only the
single character ‘the presence or absence of stripes’, the result is the logical, but
ridiculous observation, that tigers and zebras are held to be more closely related
to one another than tigers are to lions. As with phenetics, the general rule is to
12. 282 McCARTHY
use as many characters as possible, so as to dilute the impact of any wrongly
selected characters. Also, Kitching et al. (1998) report that continuous characters
with real number values (e.g. wing length) tend to produce cladograms with lower
levels of confidence, compared to those produced using qualitative characters that
are described with words (e.g. the presence or absence of wings). Another criti-
cism of cladistics concerns the type of material appropriate for analysis. As Hennig
and many of the early cladists were entomologists, there was a view that cladis-
tics was only appropriate for organisms whose characters could be found in the
fossil record. Yet cladistics has been used to classify a wide range of biological
organisms including bacteria, plants and animals and phylogeny has been used for
nearly two hundred years to represent the descent of language and manuscripts
(Zumpt 1831, Lachmann 1850, Platnick & Cameron 1977, Bateman et al. 1990,
Robinson & Robert O’Hara 1996). Thus, it is clear that the material suitable for
cladistic analysis does not have to be biological. What is required, are individuals
whose evolutionary history can be inferred and represented as patterns of com-
mon ancestry. This is the concept of species as individuals, as opposed to species
as classes or kinds, both of which are abstract notions (Ghiselin 1966, 1974, Hull
1976, 1978). Individuals, classes and kinds can each be described and differentiated
from other individuals, classes and kinds, but only individuals are real and con-
crete entities that are constrained in space and time, have proper names and can
change. They are the unit of analysis for a cladistic classification.
In summary, the evolutionary and phenetic schools believed that the empirical
and theoretical challenge of properly estimating homology and phylogeny was too
difficult. But it is now generally accepted that cladistic analysis provides an objec-
tive and empirical method to assess and represent phylogeny and homology. This
is because common ancestry is real i.e. a group of taxa either are, or are not
related by ancestry, unlike perceived phenetic similarity which is inherently sub-
jective. Also, the processing of character data using modern cladistic software is
as analytical and repeatable as phenetic methods, but with the added value of
conveying significant information content in terms of character states and testable
hypotheses about phylogenetic relationships. The output of a phenetic study leads
to mere associations.
3. The classification of organizations
Although there is no established field of organizational systematics, researchers
have long examined how organizations differ according to factors such as resource
requirements (Penrose 1959, Barney 1991, Nelson & Winter, 1982), structural fea-
tures (Chandler 1962, 1977), strategic behaviour (Miles & Snow 1978) and dynamic
capabilities and routines (Teece et al. 1997, Eisenhardt & Martin 2000, Winter
2003). This interest in organizational diversity is best associated with the branch of
organizational science known as population ecology; an area of research primarily
13. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 283
concerned with why there is a diversity of organizations and the reasons for the
differences (Hannan & Freeman 1977, 1989). It focuses on the development of the-
ories (which are evolutionary in origin) to explain organizational change and vari-
ety, but it is not overly concerned with classifying the diversity. Consequently and
despite the interest in organizational differences, there has not been a coordinated
effort to produce any form of universal classification suitable for all known organi-
zational taxa. That is not to say that there have been no attempts to classify orga-
nizations. On the contrary, the general areas of organizational and management
science have produced many classifications, but none however, that are adequate
for representing all potential organizational taxa.
One approach to studying organizational form and diversity that does advocate
a systematic view is configuration theory (Lawrence & Lorsch 1967, Miles & Snow
1978, Miller 1986, 1987, 1996, Meyer et al. 1993). It is concerned with explain-
ing the relationship between an organizational form (configuration) and the con-
ditions and demands of its environment; and the use of the term configuration is
generally comparable to the notion of organizational taxa. For example, Romanel-
li (1991, pp. 81–82) views organizational form as ‘those characteristics of an orga-
nization that identify it as a distinct entity and, at the same time, classify it as a
member of a group of similar organizations’ and McKelvey (1982, p. 196) refers to
organizational taxa as ‘a collectivity of the adaptive properties of all its included
organizations.’ But configuration theorists also use terms and language that reflect
the prevalent confusion about the unit of analysis and an ignorance of the species-
as-individuals thesis i.e. they do not recognize differences between entities, clas-
ses and types. For example, Meyer et al. (1993) and Dess et al. (1993) provide
explanations of configurations as gestalts which seem consistent with the notion of
organizational taxa as proper and incorporated individuals, but their suggestions
that gestalt, configuration and archetypes are all synonyms, is not appropriate for
classifications of entities. According to Ghiselin’s (1997) individual thesis, for orga-
nizations to be viewed as taxa, they should be real and not abstractions or types.
This notion of organizations as individuals is broader than the existence of indi-
vidual legally incorporated firms. It has a metaphysical context which implies that
organizational taxa are not classes of organizations, but rather uniform and con-
crete entities constrained in space and time, and that the components of an indi-
vidual are not members of the individual, but parts that help make the individual
whole. Despite the fact that organizational and technological systems by and large
conform to these criteria, the majority of existing organizational classifications are
unaware of the relevance and importance of the organizations as individuals thesis
despite different contexts and system perspectives (e.g. social, technological, legal
and economic).
There are of course differences in how this thesis relates to biological species and
organizational species and these will result in some deviation and points for dis-
cussion. For example, once a biological organism is dead or a biological species
is extinct, it currently remains that way. This is not necessarily the case for social,
14. 284 McCARTHY
economic and technological entities, as information about their components, form
and operation can be recorded and stored in such a way that it is possible to recre-
ate them, if there is wish to and the environment allows. As an example, consider
the Boneshaker bicycle, a technological system whose purpose is to provide ground
transportation by cycling. Historians and enthusiasts (Bijker 1995, Alderson 1972)
would consider this technological entity to be a taxon of bicycles, while the bicycle
would be viewed as a class of transportation technologies. The Boneshaker has a
proper name and a history, indicating that its existence was constrained spatially
and temporally. That is, the Boneshaker emerged in certain regions in the 1870s
and was descended from another group of bicycles, the Hobbyhorse. It is therefore
possible to infer phylogeny and observe shared innovations such as frame struc-
ture, tire technology, wheel technology, drive chain technology and steering system
technology. When the Boneshaker began to disappear some twenty years later with
the advent of the Safety Bicycle, this technological extinction was not permanent.
Today we have archives and manufacturing technologies that allow us to reproduce
and use Boneshakers. As commented by Ghiselin (1997) at the end of his discus-
sion on what constitutes an individual, this ability to make extinct biological sys-
tems extant again only exists in the imagination of science fiction authors.
Prior to configuration theory, one of the earliest formal classifications of orga-
nizations is attributed to Parsons (1956) who attempted to identify and order
types of organizations by viewing them as social systems seeking to attain a spe-
cific type of social goal. This fundamental typology differentiated organizations
according to four dimensions: (i) the value system which defines and legitimizes
the goals of the organization; (ii) the adaptive mechanisms which organize and
operate the resources; (iii) the operative code for directly responding to goals;
and (iv) the integrating mechanisms. Following this work, Woodward (1958) pro-
duced an empirical classification of the functional behavior of manufacturing
firms according to the type and complexity of the production techniques used by
the organization. While Woodward’s classification has been widely accepted and
verified through subsequent studies, it has also been subject to criticism concern-
ing the simplicity and common sense nature of the findings (Clegg 1990). How-
ever, the value of her classification is acknowledged by its robustness, longevity
and impetus for similar work. This includes classifications based on the coercive,
remunerative, or normative power of the organization leaders (Etzioni 1964), the
differentiation of formal organizations according to who is the prime beneficiary
(Blau & Scott 1962), technology as a key determinant of organizational struc-
tures (Perrow 1967), organization size (Kimberly 1976), use of technology (Child
1973), strategies employed (Filley & Aldag 1978, Romanelli 1991), product service
(Fligstein 1985), control systems utilized (Etzioni 1964, Litz 1995), technology,
organization and control (Aldrich & Mueller 1982), the degree of environmental
stability (Lawrence & Lorsch 1967), types based on bureaucracy, value rational
action, rational-legal authority, or inner-worldly asceticism (Weber 1968) and clas-
sifications based on the operative goals (Katz & Kahn 1966), and output goals,
15. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 285
adaptation goals, management goals, motivation goals, and positional goals (Gross
1969).
Many of these organizational classifications are considered to be typologies, as
they are based on a theoretical effort to explain differences, and are often gov-
erned by the ‘limitations, the biases, and/or the organizational frames of refer-
ence of those doing the classification’ (Baudhuin et al. 1985, p. 2). Consequently,
we have a collection of classifications that have been conceptualized using a small
number of organizational dimensions and have no common and proper definition
of the unit of analysis. Despite these limitations, the classifications still provide a
good basis for understanding organizational form and diversity, but as remarked
by Meyer et al. (1993, p. 1182), ‘the allocation of organizations to types often
is not clear cut. Because of their a priori nature and frequent lack of specified
empirical referents and cutoff points, typologies are difficult to use empirically’.
This is evidenced by the relatively low number of empirical studies to use the the-
oretical frameworks developed by these classifications. Also, some of these early
organizational classifications would not be appropriate for further analysis from a
history of evolutionary relationships perspective. This is because the unit of anal-
ysis in these classifications does not conform to the species-as-individuals thesis
and the focus of differences is on functional concepts, rather than the adaptation
of form and function. Evolutionary biologists contend that teleology alone is not
adequate for historical explanation, while early organizational classifications were
based on rational and natural views of organizations (as discussed in the next sec-
tion) and therefore conceptualized and classified organizations in terms of purpose.
For accounts of the role of form, function and adaptation in determining the unit
and focus of a classification study, see Bigelow & Pargetter (1987), Amundson &
Lauder (1994) and Ghiselin (1997).
There are also a significant number of organizational classifications derived
using numerical taxonomy methods (Haas et al. 1966, Goronzy 1969, Pugh
et al. 1969, Samuel & Mannheim 1970, Prien & Ronan 1971, Pinto & Pinder
1972, Reimann 1974, Galbraith & Schendel 1983, Hambrick 1983, Hayes et al.
1983, Hatten & Hatten 1985). In accordance with the phenetic school of biolog-
ical classification, many of these empirical organizational classifications emphasize
the need for theory-free and quantitative data to ensure objectivity and repeat-
ability, but they also failed to explain how researchers could design and conduct
studies using theory-free data. Instead the case for objectivity rests on the automa-
tion of the computations and the fact that these studies tend to collect and pro-
cess data on more organizations than studies based on theoretical classifications
have done. However, even this computational basis for objectivity is unsound, as
researchers using numerical taxonomy methods are still required to make intuitive
and ‘rule of thumb’ decisions concerning which method and parameters to use.
Thus bias and approximations can easily appear in organizational classifications
derived using numerical taxonomy methods.
16. 286 McCARTHY
In a paper that recognizes both the benefits and limits of numerical taxonomy,
Rich (1992) presents a case for combining the empirical, theoretical and evolution-
ary perspectives of organizational diversity. He argues that organizational classifi-
cations should do more than simply present clusters of entities. They should help
explain the causes of the diversity and similarity. To achieve this, Rich proposes
that the phylogenetic, population ecology and numerical perspectives be combined
to understand and explain the ‘blueprint’ of organizational forms. The result, he
suggests, will be a classification method that integrates a theory of differences with
the notion of fit and that uses numerical methods to build a hierarchical classifi-
cation capable of representing the diversity of organizational life. Fourteen years
earlier, McKelvey (1978) suggested that population ecology studies should use clas-
sification methods to study organizational taxa and argued that the formulation
of a classification is a prerequisite for the maturation of organization science. He
proposed that lessons could and should be learned from the area of biological
systematics to classify organizations, and in his work Organizational Systematics
(McKelvey 1982) he discussed the merits of using phylogenetic relationships to rep-
resent organizational change and diversity. Both McKelvey’s and Rich’s proposi-
tions support the underlying tenet of this paper, which is, that there is a need
for organizational science to develop jointly a broad theory on how organiza-
tional diversity is generated, along with a system of organizational classification
that coincides with this theory.
4. A cladistic analysis of organizational diversity
This paper argues that by using cladistic analysis to study and represent organiza-
tional phylogeny, we can develop a theoretical context for organizational diversity
that permits interpretation of data and phenomena from an evolutionary point of
view. For this to be possible though, we must recognize that organizational taxa are
related by descent from a common ancestor, that there is a bifurcating or branch-
ing pattern of new clade development and that the changes in characteristics take
place in lineages over time. It is generally accepted that such conditions do exist for
organizations, but as is evidenced by the variety and number of redundant classifi-
cations of organizations, there is limited agreement about how to conceptualize and
continuously represent organizational diversity. So to proceed with this paper, it is
necessary to consider and present organizations as appropriate entities for cladistic
analysis and examine the assumption that they evolve from common ancestors.
To understand how organizations are distinguished from other types of complex
system and the problem of classification respective, I will refer to use four related
and complementary organizational perspectives: the rational system view (Simon
1945, Cyert & March 1963), the natural system view (Selznick 1957), the open
system view (Boulding 1956, Katz & Kahn 1966) and the complex adaptive view
(Anderson 1999, Dooley & Van de Ven 1999, Allen 2001, McCarthy 2004). The
17. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 287
first three of these views are well established and are used to define organizations
and explain the history of organization studies (Scott 1987, Baum & Rowley 2002).
The fourth is a relatively contemporary view and to an extent unifies and extends
the first three.
With the rational view, the assumption is that organizations are created for a
purpose and will therefore require appropriate capabilities and components (peo-
ple, technology, etc.) to achieve this purpose. They are viewed as machine-like sys-
tems with formal procedures and engineered structures. The natural view assumes
that the purpose of organizations is simply survival and to achieve this, they must
exhibit autonomous and adaptive properties. It moves from the machine metaphor,
to viewing organizations as organic and learning systems.
With both the rational and natural views, organizations are treated as tangible
entities with ‘goal-directed, boundary maintaining, and socially constructed sys-
tems of human activity’ (Aldrich 1999, p. 2), but with the open system view, the
focus is extended to include the connections and interdependences between an
organization and its environment. The open view recognizes that organizations are
transformation systems with internal and external interactions. They interact with
other systems to receive inputs such as energy, materials, information and routines,
and internally transform them into product and service offerings. These interac-
tions are the basis of the complex adaptive view, which considers organizations to
be composed of levels of relatively autonomous sub-systems whose combined and
emergent characteristics cannot easily be reduced to one level of description. Thus,
the complex adaptive view defines organizations as open systems with agency, and
the ability to adapt, learn and create new rules, structures and behaviors at several
interrelated levels (McCarthy 2004). With these multiple levels and interactions,
organizations are considered to be hierarchically arranged (Baum & Singh 1994),
which in turn leads to multiple levels of analysis. For example, we could focus on
populations of organizational entities based on sectoral differences (e.g. agriculture,
banking, electronics, biotechnology, etc.), or in terms of their operational activity
(e.g. retail, service, manufacturing, etc.), or study organizations at the firm level
(e.g. strategies and processes) or focus on intraorganizational activity (e.g. work
groups). Collectively these views and levels constitute a complex adaptive system
which has multiple complex adaptive systems hierarchically nested within.
With the open system and complex adaptive view it is possible to recognize, analyze
and classify organizational entities and their histories from multiple levels of abstrac-
tion. For example an economist might focus on sectors, an organizational scientist on
operational behavior and a business historian on companies. Each perspective could
possibly justify their unit of analysis to be real individuals with genealogy, while argu-
ing that the other perspectives are classes or sub-units. Therefore when producing a
classification, the level and perspective of interest should be appropriately reasoned
and explained. Otherwise, there is significant potential to focus on inappropriate units
of analysis and then mistake a classification of classes or grades for a classification of
taxa (groups of one or more similar historical entities) and vice versa.
18. 288 McCARTHY
The open and complex adaptive views have also helped existing and new evolu-
tionary research to blossom in economics (Schumpeter 1934, 1943, 1954, Alchian
1950, Nelson & Winter 1982), technology and innovation (Basalla 1988, Metcalfe
1998), evolutionary philosophy (Campbell 1960, 1969) and organization science
(Weick 1979, Aldrich 1979, McKelvey 1975, 1982). Schumpeter proposed that eco-
nomic change be viewed as an evolutionary process of incremental and bifurcat-
ing change. Nelson & Winter (1982) used evolutionary theory to develop models
of economic change, where routines are deemed to be the equivalent of organi-
zational genes. Routines are considered the norms, rules, procedures, conventions,
and technologies around which organizations are constructed and through which
they operate (Levitt & March 1988). New routines are first produced by innovating
organizations and then shared and retained by other organizations. Campbell was
the first to explain how this form of organizational evolution is governed by the
processes of variation, selection and retention, and Weick offered descriptions and
theories on how these processes relate to the decision making capabilities found in
organizations. These theories and concepts, combined with research on open sys-
tems thinking, influenced the work of Aldrich who explained how the processes
of variation, selection, retention and struggle govern the creation and adoption of
organizational routines.
Despite these significant advances in organizational science, our understanding
of evolution at work in organizations is limited. It is accepted that the process of
descent occurs in organizations and that characteristics such as routines are trans-
ferred from ancestors to descendants (Phillips 2002, Brittain & Freeman 1980, Astley
1985). But we only have a primitive understanding of the rate, direction and mecha-
nisms of change and of how these factors might correlate to the different types and
degrees of adaptive response exhibited by organizations. At present we do not have
an operational philosophy and framework that is capable of explaining these issues
and simultaneously representing the resulting organizational diversity.
Motivated by this need and by McKelvey’s (1982) work on organizational
systematics, preliminary cladistic analyses of organizations were produced by
McCarthy et al. (1997, 2000) and Leseure (2000). From a methodological stand-
point, these studies provide the first demonstrations of what a cladistic analysis
of organizations would involve and look like, and have led to further evaluation
and development by researchers in the social and economic sciences. For exam-
ple, at a recent conference organized by the Danish Research Unit for Indus-
trial Dynamics (DRUID) to celebrate the 20th anniversary of Nelson & Winter’s
work, a paper proposing the use of cladistics to examine evolutionary change in
the pharmaceutical industry was presented by Leask (2002). This was followed
by a paper that was originally delivered at the 2002 meeting of the Brisbane
Club; it modeled the cladogram produced by McCarthy et al. (2000) to exam-
ine the interdependence of the characters possessed by each taxa (Allen 2002,
Allen & Strathern 2003). Returning from the Brisbane Club meeting to DRUID,
Andersen (2003) used phylogeny to represent the evolutionary transformation of
19. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 289
industry sectors and to question existing classification systems used in indus-
trial statistics. Andersen’s approach to producing industry cladograms differs from
McCarthy et al.’s (2000) in that he aggregates organizational activities by using
complete input-output datasets for the whole industry, thus seeking differences
between industries over large and potentially inconsistent sets of characteristics.
Most recently, Baldwin et al. (2003) combine cladistics and evolutionary systems
modeling to address questions concerning how organizational diversity and flexi-
bility can be retained, how organizational and technological innovations interact
in transformations and how the timescales in these kinds of transformations can
be reduced.
5. The cladistic method
The following account of the cladistic method provides a primer to help research-
ers respond to the task of reconstructing the phylogeny of organizational diversity.
It was originally adapted from the work and methods described by Wiley et al.
(1991), Forey et al. (1992), Kitching et al. (1998), Lipscomb (1998) which in turn
were used to develop and explain the organizational classifications by McCarthy
et al. (1997, 2000) and Leseure (2000) and the method presented by Rakotobe-Joel
et al. (2002). The explanation given below follows and develops these accounts.
5.1. Select a clade
This step is concerned with selecting the taxa whose evolutionary history is of
interest and to a great extent is a form of pre-classification, since the selection
is based on some form of pre-existing knowledge and interest in the taxa. It is
necessary that the taxa constitute a clade i.e. a group which includes the most
recent common ancestor as well as all and only all of its descendants. For exam-
ple, if we consider the simple and illustrative cladogram shown in (Figure 4 and
Table 2), it is assumed that evolution occurs and characters may be passed modi-
fied or unmodified, through genealogical descent. Thus, the Craft taxon is the most
recent common ancestor and the other taxa (Standardized Craft, Modern Craft,
Mass and Just-in-Time) are assumed to be all known descendants. With this clad-
ogram the category or class of entity of interest is the manufacturing organiza-
tion, while the named taxa represent entities whose characteristics identify it as
a distinct entity and, at the same time, classify it as a member of a group con-
sisting of two or more similar entities. The taxa are individuals with geographical
and time constraints, and the ability to change through time and give rise to other
individuals. For instance, we find the genesis of Craft production in the European
Craft Guilds in the fifteenth and sixteenth centuries, Mass production appeared in
20. 290 McCARTHY
Ch 1
Ch 2
Ch 3
Ch 4
Ch 5
Ch 6
Ch 7
T1 T2 T3 T4 T 5
Figure 4. Example cladogram of organizational (manufacturing) taxa.
Table 2. Example data set for organizational (manufacturing) taxa
Characters Ch 1 Ch 2 Ch 3 Ch 4 Ch 5 Ch 6 Ch 7
Production Standardized Standardized Automation Vertical assembly Pull
Technology parts processes integration line scheduling
of supply
chain
Taxa
T 1 – Craft 1 0 0 0 0 0 0
T 2 – Standardized 1 1 0 0 0 0 0
Craft
T 3 – Modern 1 1 1 0 0 0 0
Craft
T 4 – Mass 1 1 1 1 1 1 0
T 5 – 1 1 1 1 1 1 1
Just-in-Time
Sweden, France and England in the early 1800s, and Just-in-Time production orig-
inated in Japan in the 1950s. This descent from Craft production to Just-in-Time
production is well documented (Rae 1959, Hounshell 1984, Womack et al. 1990)
and shows technological, structural and behavioral features that are homologies.
Thus, with this most basic of examples, we observe the feasibility of reconstructing
organizational genealogies based on common ancestry.
21. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 291
5.2. Determine characters
The previous step of selecting the clade often reveals a number of different taxa
that appear to be a member of that clade. Initially the complete membership and
the diagnostic characteristics of the clade are not necessarily known, and for both
biological and non-biological systems the problem is determining those charac-
ters that are cladistically valuable from the set of all potential characters. For
example, with the organizational cladogram, evidence should be sought to main-
tain the assumption that the characters selected will infer and represent descent
from common ancestors. Consequently, the aim of this step is to review the his-
tory of the entities and to find evidence that will represent the pattern of his-
torical relationships for the selected taxa. For social and technological entities,
this evidence tends to be in the form of published material or archives, which
can be systematically assembled to produce a data matrix. The matrix indicates
which characters have been selected and how they are coded for cladistic analy-
sis.
The data in Table 2 are deliberately basic to help explain the cladistic method.
They provide a simple and plausible illustration of the key innovations that have
been selected and retained by advanced taxa and are potentially shared derived
characters. An actual cladistic analysis of the entities would almost certainly
involve more taxa and more characters as well as some parallel evolution. This
form of evolution is determined by derived (apomorphic) characters which do not
have a mutual and unique evolutionary origin. A history of similar environmental
selection conditions on different taxa in different locations is a potential explana-
tion for this independent and parallel development.
Characters vary in the properties they represent and their information content.
They can be discrete, continuous, quantitative or qualitative in nature, but regard-
less, they should be easy to measure, unambiguous and the character states should
vary between taxa. This variation can be coded according to the presence or
absence of one character, as binary variables expressing different character states of
one character, or as multi-state characters. As discussed by Kitching et al. (1998)
even though candidate characters normally are filtered to convert continuous and
quantitative characters into a discrete and qualitative form, this should not over-
ride the main issue which is to select characters that indicate common ances-
try.
Once a set of taxa and characters are selected, the initial pattern of relation-
ships will often contain one or more polytomies (a node with more than two
descendant branches) and if the data are completely unresolved the tree dia-
gram will appear as shown in Figure 5. Polytomies exist because the associa-
tions between the taxa have not yet been determined. This is the aim of the next
step.
22. 292 McCARTHY
T1 T2 T3 T4 T1 T3 T4 T2
Polytomy Possible Phylogeny
Figure 5. Polytomy and phylogeny.
5.3. Character coding and polarization
To produce trees with phylogenetic order it is necessary to identify the existence
of shared derived characters. This involves understanding and coding the proper-
ties of the characters and character states. Figure 6 shows how the coding of char-
acter states can reveal three properties: direction, order and polarity (Swofford &
Maddison 1987). Ordering refers to the sequence of character state changes that
occur, whilst direction refers to the transition between character states. When the
direction and order of the character state changes have been determined, then the
character series is considered polarized, revealing whether the character or charac-
ter state is ancestral or derived.
Understanding the properties of characters is relatively straightforward, but
determining them is another matter. If we are fortunate to have a detailed and reli-
able record of the entities histories then this makes the task easier. This is espe-
cially the case, if the record contains information about the changes and dates for
when new taxa emerged, but still the transmission of characters in social and tech-
nological systems is not straightforward. They are complex adaptive systems with
multiple system levels and therefore any study with an inappropriate or poorly
defined unit of analysis could easily confuse and mix multiple levels of selection
and descent. Also, characters can be inherited from a diverse range of sources, and
can be adapted as a consequence of intentional and blind variations. This is not
to say that social and technological evolution is more complicated than biological
evolution, because as Hull (1988) argues, social scientists may understand the com-
plexities of sociocultural transmission, but their limited understanding of biological
evolution often leads them to underestimate its complexities.
If appropriate historical records are not available, a method called polarization
or argumentation (Wiley et al. 1991, Hennig 1950, 1966) is used to determine
which characters are ancestral and which are derived. This method uses outgroup
comparison, where a taxon that is hypothesized to be less closely related to each
of the taxa under consideration than any are to each other is called the outgroup,
23. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 293
0
(a) 0 1
(c) (d) 0 1 2
(b) 0 1
1 2
(a) Un-polarized binary characters (c) Un-ordered transformation series of (d) The same transformation
(b) Polarized binary characters three characters series polarized
Figure 6. Character coding and properties.
and is used to help resolve the polarity of characters. The basic principle is that
for a given character with two or more states within a taxon, the state occurring
in the outgroup is assumed to be the ancestral state (Watrous & Wheeler 1981).
5.4. Constructing cladograms
At this stage we have chosen taxa that are evolutionarily related, selected and
coded characters for the taxa and where possible have determined the polarity of
the characters (ancestral or derived). With this step we begin assessing potential
cladograms by grouping taxa by shared derived characters, rather than by shared
ancestral characters or any shared derived characters that are the result of inde-
pendent evolutionary development.
There are a number of methods for constructing cladograms, including Hennigian
argumentation (Hennig 1950, 1966), Wagner (1961), Farris (1970) optimization,
Fitch (1971) optimization, Dollo optimization (Farris 1977), and Camin-Sokal
(1965) optimization. In general these construction and optimization methods dif-
fer in how they interpret and process the character information content and whether
or not the data have been polarized. For example, the Wagner and Fitch methods are
optimization procedures that seek to reconstruct the minimum number of character
state changes according to an optimality criterion. The Wagner method is used for
ordered characters and the Fitch for unordered characters. The Hennigian argumen-
tation method considers the information provided by each character, at each step of
the construction process. It follows the inclusion/exclusion rule where the informa-
tion available allows for either complete inclusion or complete exclusion of taxa, so
that a hypothesis of relationships can be generated.
Using the example data (Table 3) provided by Rakotobe-Joel et al. (2002) this
section will manually show how the Hennigian argumentation method is applied
to construct a cladogram (see Figure 7). The data represent six organizational taxa
24. 294 McCARTHY
Table 3. Set of cladistic data
Characters Ch 1 Ch 2 Ch 3 Ch 4 Ch 5 Ch 6 Ch 7 Ch 8 Ch 9 Ch 10
Taxa
T 1 0 0 0 0 0 0 0 0 0 0
T 2 0 0 0 0 0 0 0 0 1 1
T 3 0 0 0 0 0 0 1 1 1 1
T 4 0 0 0 0 0 1 1 1 1 1
T 5 0 0 1 1 1 1 1 1 0 1
T 6 1 1 1 1 1 1 1 1 1 1
Data Source: Rakotobe-Joel et al. (2002, p. 340).
(T 1 to T 6) and ten organizational characters (Ch 1 to Ch 10) and are processed
as follows:
• The matrix (Table 3) contains character data for ten characters and six taxa,
one of which T 1 is considered the outgroup. At this stage the relationships
between the taxa have not been determined and the data are considered a poly-
tomy (Figure 7 – step 1).
• Characters Ch 1 and Ch 2 have uniquely derived states as they are found only
in taxon T 6 (Figure 7 – step 2).
• Characters Ch 3, Ch 4 and Ch 5 have shared derived states as they are shared
by and connect taxa T 5 and T 6 (Figure 7 – step 3).
• Character Ch 6 has a shared derived state as it is shared by and connects taxa
T 4, T 5 and T 6 (Figure 7 – step 4).
• Characters Ch 7 and Ch 8 have shared derived states as they are shared by and
connect taxa T 3, T 4, T 5 and T 6 (Figure 7 – step 5).
• Characters Ch 9 and Ch 10 have shared derived states as they are shared by and
connect taxa T 2, T 3, T 4 and T 6 (Figure 7 – step 6). Ch 10 is also present in T
5, but Ch 9 is not and this is indicated by Ch –9 (a character conflict) on T 5.
With only six taxa and ten characters this example data is relatively straightforward.
However, when the data set is larger and more complex, it is usually processed using
cladistic software, of which there are a number for building, comparing and analyz-
ing cladograms. The most widely used are PHYLIP (Felsenstein 1993) and PAUP
(Swofford 1998) for analyzing data sets and searching for cladograms, and MacClade
(Maddison & Maddison 1992) for analyzing cladograms and reconstructing ances-
tral states.
25. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 295
Figure 7. Constructing a cladogram. Rakotobe-Joel et al. (2002, p. 344).
5.5. Cladogram selection
It is important to note that a study involving significantly more characters and
taxa is likely to exhibit numerous conflicts in the relationships. For instance, eco-
nomic, technological and organizational systems are likely to demonstrate parallel
evolution. This assumes that different taxa will develop the same innovations inde-
pendently at different places. Although our knowledge about evolutionary diffusion
26. 296 McCARTHY
versus parallel evolution in social and technological systems is limited, it is most
likely that both occur because of similar selection conditions, which equates to
what Darwin (1859 [1996 edition, p. 114]) referred to as fit: ‘those exquisite adap-
tations of one part of the organization to another part, and to the conditions of
life.’ Thus, with organizations demonstrating evolution which is partially rational
and intentional, and reinforced by environmental factors such as reputation, mar-
ket trends and fashion, the result can be competitive imitation or benchmarking
which is comparable to Campbell’s (1965) notion of cross-lineage borrowing.
With such factors, the data will produce a number of potential cladograms,
rather than just one. These candidate cladograms are assessed using optimization
methods (e.g. Wagner 1961, Fitch 1971, Camin & Sokal 1965) and descriptive sta-
tistics (tree length, consistency index and retention index) that together provide an
indication of the quality of the cladogram according to the principles of parsi-
mony and congruence. Another approach, the Bootstrapping method (Felsenstein
1985, Efron 1979, Efron & Gong 1983), assesses the reliability of the branches
in a cladogram by randomly replicating the real dataset several hundred times
and producing a new phylogeny for each new bootstrapped dataset. These boot-
strapped phylogenies have varying topologies, some with high levels of common-
ality and some with low levels. The overall degree of commonality is used to
estimate whether a cladogram is genuine.
The principle of congruence assumes that a cladogram will seek agreement
between the characters used, to produce a unique phylogenetic relationship. This is
because for any one set of taxa there will be one ‘best fit’ phylogeny, assuming that
the taxa are derived from a common ancestor. If analysis of three different sets of
data all show the same pattern for the different taxa, then it can be assumed that
the pattern represents a good and true approximation of relatedness (Forey et al.
1992). The principle of parsimony is derived from Ockham’s razor (Kluge 1984).
William Ockham (c.1280–1349) proposed that when alternative hypotheses exist,
the one requiring the least assumptions should be preferred. This general principle
has been used in cladistics to argue that a phylogeny is more plausible if it requires
less, rather than more changes in character states. Thus, from all of the theoreti-
cally possible cladograms a set of data may produce, the one with the least number
of steps is chosen.
The tree length descriptive indicates the total number of character state changes
necessary to support the relationships for the taxa shown in any cladogram. Thus,
the cladogram with the minimum length is considered to have fewer homoplasies
(when a character evolves more than once) and as a consequence is assumed to be
the best fit tree. Again using the example provided by Rakotobe-Joel et al. (2002)
it is possible to explain and compare the tree length descriptive for the final clad-
ogram shown in Figure 7, step 6 (now shown as Figure 8(a)), and another poten-
tial tree for the example data (Figure 8(b)). Figure 8(a) involves 11 character state
changes (tree length = 11), as characters 1 to 8 and 10 each change once, and char-
acter 9 changes twice. While Figure 8(b) involves 18 character state changes (tree
27. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 297
Figure 8. Tree length. Adapted from Rakotobe-Joel et al. (2002, p. 344).
length = 18) as characters 1 to 8 each change twice and characters 9 and 10 each
change once. Therefore the tree length descriptive would consider Figure 8(a) to be
more parsimonious than Figure 8(b).
The consistency index (CI) measures how well the character data fits to a clad-
ogram and is given by:
CI = M/S (1)
28. 298 McCARTHY
Table 4. Retention index calculation
Characters Ch 1 Ch 2 Ch 3 Ch 4 Ch 5 Ch 6 Ch 7 Ch 8 Ch 9 Ch 10
Taxa
T 1 0 0 0 0 0 0 0 0 0 0
T 2 0 0 0 0 0 0 0 0 1 1
T 3 0 0 0 0 0 0 1 1 1 1
T 4 0 0 0 0 0 1 1 1 1 1
T 5 0 0 1 1 1 1 1 1 0 1
T 6 1 1 1 1 1 1 1 1 1 1
Max Steps (g) 1 1 2 2 2 3 2 2 2 1
G= g = 18
Data Source: Rakotobe-Joel et al. (2002, p. 345)
where M is the minimum possible number of character changes and S is the
actual number of character changes (S). The consistency index can vary from
1 (no homoplasy) to 0 (a lot of homoplasy). For example, with the cladogram
in Figure 7, step 6, there are 10 characters each with two states and therefore
a possible minimum of 10 character changes (M = 10), while the tree length or
actual number of character changes is 11 (S = 11). Thus, the consistency index is
10/11 = 0.90.
The retention index (RI) is similar to the consistency index, but measures the
proportion of synapomorphy in a cladogram i.e. the degree of common ancestry
in a cladogram (Farris 1970). It is defined as:
RI = (G − S)/(G − M) (2)
where M and S are as per the consistency index and G is the total number of taxa
with state 1 or 0 (which ever is smaller). For example, if we use the data in Table
3 we find the total number of steps (G) to be 18 (Table 4), M to be 10, S to be
11 and therefore the RI is 0.875. The closer the RI is to 1 the better the tree is
considered to be.
With the example organizational cladogram in Figure 7, the descriptive statistics
produce near-perfect values, but this is only because the data in Table 3 are basic
and apposite. Actual studies would very likely result in data with a large number
of inconsistencies. This is not a negative result or a flaw in the logic of apply-
ing the cladistic method to non-biological entities. It is a reality of inferring and
representing the evolutionary relationships in social and technological entities. If
our current understanding of evolution in these entities is correct, then we should
expect organizational cladograms to have imperfect descriptive statistics.
29. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 299
6. Conclusions
Classifying organizational diversity and explaining the mechanisms that preside
over the differences are enduring research issues. This paper was motivated by
these and by the belief that we could better understand and advance existing
knowledge by using a system of organizational classification that coincides with
theories that explain organizational change and diversity.
Organizational scholars have developed a significant collection of classifications,
describing how factors such as structure, technology, processes and strategy define
organizational form. There is also a significant body of work that explains how
evolution occurs in organizations and how processes such as variation, selection
and retention govern the creation and adoption of innovations. Yet, despite this
research, our understanding of the genesis of organizational taxa in terms of his-
torical evolutionary relationships is limited. Not only do existing organizational
classifications avoid these issues, they also lack a universal and theoretically rel-
evant framework for ordering and continually developing a natural and objec-
tive system of organizational diversity. Thus, the related tasks of understanding
what produces organizational diversity and classifying the diversity are currently
research activities that are operationally separate. The result is a collection of
mostly speculative and unconnected classifications, where the combined informa-
tion management value is greatly reduced and the potential for theory and hypoth-
esis development diminished.
When it comes to the theory and practice of classification, biologists and philos-
ophers have been and still are, far ahead of the other sciences in the complexity
and rigor of their classification thinking and methods. Their debates about classi-
fication philosophy and logic resulted in competing schools which advanced and
established a relatively effective and organized body of systematic activity. A sim-
ple indicator of this, are the number of academic journals and societies dedicated
to systematics. The biological sciences have at least seven journals (Annual Review
of Ecology and Systematics, Cladistics, Integrative and Comparative Biology, System-
atic Biology, Systematic Botany, Taxon, and Molecular Phylogenetics and Evolution)
and approximately twenty societies; whereas the combined areas of organizational
science, management and economics have none.
To help develop a concerted field of organizational systematics, this paper
proposes that the cladistic school of classification is theoretically relevant to orga-
nizational diversity and methodologically richer than existing classifications of
organizations. This is not simply because cladistics is accepted by most biolo-
gists as the best method for comparative studies in biology. The basis for this
claim is that the concept of shared patterns of common ancestry is an evolu-
tionary logic compatible with existing theories on how and why new organiza-
tional taxa emerge. That is not to say that social, economic and technological
evolution is fully analogous to biological evolution, as it is well known that the
isolating mechanisms, adaptation processes and methods of new system creation
30. 300 McCARTHY
have contextual differences. The fact is, social, economic and technological evo-
lution governs social, economic and technological diversity, and cladistics offers
a theory and methods for deducing and representing the evolutionary relation-
ships that accompany these developments. The reconstruction of organizational
phylogeny has the potential to produce classifications with objective and poten-
tially exhaustive groupings and as phylogeny is a property of any evolving sys-
tem, the classifications would provide a backcloth for contributions in other areas
such as ecological, institutional, transaction costs and resource based theories of
the firm. Also, the representation of a cladistic classification, the cladogram, pro-
vides an information management framework that is capable of developing with
new studies, new data and new organizational taxa. By using this hierarchical sys-
tem of representation we could avoid the relative taxonomic dormancy and redun-
dancy we have with existing matrix and table based classifications of organizations.
A cladogram offers a relatively transparent, accommodating and evolving informa-
tion system, which in turn, enables a more integrated and cumulative development
of organizational science.
Acknowledgements
I would like to thank Jane McCarthy and Brian Gordon for their insightful com-
ments on an earlier version of this paper. I also acknowledge the financial support
of the Social Sciences and Humanities Research Council and the Canada Research
Chair Program of Canada. Finally, I wish to thank an economist reviewer and a
special thanks to the Co-Editor, biologist Michael Ghiselin, for helpful suggestions
and guidance during the revision process.
References cited
Aitken, Murray, Dorothy Anderson & John Hind. 1981. Statistical modeling of data on teaching styles.
Journal of Statistical Sociology 144:419–461.
Alchian, Armen. A. 1950. Uncertainty evolution and economic theory. Journal of Political Economy
58:211–222.
Alderson, Frederick. 1972. Bicycling: a history. Praeger Publishers, New York.
Aldrich, Howard E. 1979. Organizations and environments. Prentice Hall, New York.
Aldrich, Howard E. 1999. Organizations evolving. Sage Publications, London.
Aldrich, Howard E. & Susan Mueller. 1982. The evolution of organizational forms: technology, coordi-
nation and control. Pp. 33–87 in B. Staw & L.L. Cummings (ed.) Research in Organizational Behav-
ior, JAI Press, New York.
Allen, Peter M. 2001. A complex systems approach to learning in adaptive networks. International Jour-
nal of Innovation Management 5(2):149–180.
Allen, Peter M. 2002. The complexity of structure, strategy and decision making. Meeting of the Bris-
bane Club, Manchester 5–7 July.
31. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 301
Allen, Peter M. & Mark Strathern. 2003. Evolution, emergence, and learning in complex systems. Emer-
gence 5(4):8–33.
Amundson, Ron & George V. Lauder. 1994. Function without purpose: the use of causal role function
in evolutionary biology. Biology and Philosophy 9:443–469.
Andersen, Sloth E. 2003. The evolving tree of industrial life: an approach to the transformation of
European industry. Paper for the 2nd Workshop on the Economic Transformation of Europe, Torino
31 Jan–2 Feb.
Anderson, Philip. 1999. Complexity theory and organization science. Organization Science 10:216–232.
Astley, Graham W. 1985. The two ecologies: population and community perspectives on organization
evolution. Administrative Science Quarterly 30: 224–241.
Babbage, Charles. 1835. The economy of machinery and manufactures. Charles Knight, London.
Bailey, Kenneth D. 1994. Typologies and taxonomies: an introduction to classification techniques. Sage
University Paper Series on Quantitative Applications in the Social Sciences, 102. Sage Publications,
Thousand Oaks, USA.
Baldwin, James S., Peter M. Allen, Belinda Winder & Keith Ridgway. 2003. Simulating the cladistic evo-
lution of manufacturing. Innovation: Management, Policy and Practice 5:144–156.
Barney, Jay B. 1991. Firm resources and sustained competitive advantage. Journal of Management
17:99–120.
Basalla, George. 1988. The evolution of technology. Cambridge University Press, New York.
Bateman, Richard, Ives Goddard, Richard T. O’Grady, Vicki A. Funk, Rich Mooi, W.J. Kress & Peter
Cannell. 1990. Speaking of forked tongues: the feasibility of reconciling human phylogeny and the
history of language. Current Anthropology 31:1–24.
Baudhuin, Scott E., Robert. W. Swezey, G. D. Foster & Siegfried Streufert. 1985. An empirically derived
taxonomy of organizational systems (ARI-TR-692). McLean, VA: Science Applications Inc. (DTIC
Report No. AD-A173–440/XAG).
Baum, Joel A. C. & Tim J. Rowley. 2002. Companion to organizations: an introduction. Pp. 1–34 in
Baum, Joel A. C. Companion to Organizations. Oxford UK: Blackwell.
Baum, Joel A. C. & Jitendra V. Singh. 1994. Organizational niches and the dynamics of organizational
mortality. American Journal of Sociology 100:346–80.
Bezdek, James C. 1981. Pattern recognition with fuzzy objective function Algorithms. Plenum Press,
New York.
Bigelow, John & Robert Pargetter. 1987. Functions. Journal of Philosophy 84:181–96.
Bijker, Wiebe E. 1995. Of bicycles, bakelites and bulbs: toward a theory of sociotechnical change. The
MIT Press, Cambridge.
Bischi, Gian-Italo, Herbert Dawid & Michael Kopel. 2003. Spillover effects and the evolution of firm
clusters. Journal of Economic Behavior and Organization 50:47–75.
Blackith, Robert E. & Richard A. Reyment. 1971. Multivariate morphometrics. Academic Press,
London and New York.
Blackwelder, Richard E. & Alan Boyden. 1952. The nature of systematics. Systematic Zoology 1:26–33.
Blashfield, Mark S. & Roger K. Aldenderfer. 1978. The literature on cluster analysis. Multivariate
Behavioral Research 13:271–295.
Blau, Peter M. & Richard W. Scott. 1962. Formal organizations. Chandler, San Francisco.
Borges, Jorge Luis. 1964. The analytical language of John Wilkins. Pp. 101–105 in R. Simms & J. E.
Irby (trans.) Other Inquisitions 1937–1952. University of Texas Press, Austin.
Boulding, Kenneth E. 1956. General systems theory: the skeleton of science. Management Science
2:197–208.
Brittain, Jack W. & John Freeman. 1980. Organizational proliferation and density dependent selection. Pp.
291–338 in J. R. Kimberly & R. H. Miles (ed.) The Organizational Life Cycle. Jossey-Bass, San Francisco.
Brower, Andrew 2000. Evolution is not a necessary assumption of cladistics. Cladistics 16:143–154.
Cain, Arthur J. 1962. The evolution of taxonomic principles. Pp. 1–13 in G. C. Ainsworth & P. H. A.
Sneath (ed.) Microbial Classification. Cambridge University Press, New York.
32. 302 McCARTHY
Camin, Joseph H. & Robert R. Sokal. 1965. A method for deducing branching sequences in phylogeny.
Evolution 19:311–326.
Campbell, Donald T. 1960. Blind variation and selective retention in creative thought as in other knowl-
edge processes. Psychological Review 67:380–400.
Campbell, Donald T. 1965. Variation and selective retention in socio-cultural evolution. Pp. 19–48 in
H. R. Barringer, G. I. Blanksten & R. W. Mack (ed.) Social Change in Developing Areas: A Reinter-
pretation of Evolutionary Theory. Schenkman, Cambridge MA.
Campbell, Donald. T. 1969. Variation and selective retention in socio-cultural evolution. General Sys-
tems 14:69–85.
Capecchi, Vittorio. 1964. I modelli di classificazione e l’analisi della struttura latente. Quaderni di Soci-
ologia XIII:289–340.
Capecchi, Vittorio & Moeller, Frank. 1968. Some applications of entropy to the problems of classifica-
tion. Quality & Quantity II 1–2:63–84.
Carpenter, J. M. 1987. Cladistics of cladists. Cladistics 3:363–375.
Chandler, Alfred D. 1962. Strategy and structure. Doubleday & Company Inc., New York.
Chandler, Alfred D. 1977. The visible hand: the managerial revolution in American business. Belknap,
Cambridge, MA.
Chandler, Alfred D. 1990. Scale and scope: the dynamics of industrial capitalism. Belknap, Cambridge,
MA.
Child, John. 1973. Strategies of control and organizational behavior. Administrative Science Quarterly
18:1–17.
Clegg, Stewart R. 1990. Modern organizations: organization studies in the postmodern world. Sage
Publications, London.
Clifford, Harold T. & William Stephenson. 1975. An introduction to numerical classification. Academic
Press, New York.
Coase, Ronald H. 1937. The nature of the firm. Economica 4:386–405.
Cyert, Richard M. & James G. March. 1963. A behavioral theory of the firm. Englewood Cliffs, New
Jersey.
Daft, Richard L. 1978. A dual core model of organizational innovation. Academy of Management Jour-
nal 21:193–210.
Darwin, Charles [1859] 1996. The origin of species. J. W. Burrow (ed.). Pelican Classics, London.
De Queiroz, Kevin. 1994. Replacement of an essentialist perspective on taxonomic definitions as exem-
plified by the definition of ‘Mammalia’. Systematic Biology 43:497–510.
Dess, Gregory G., Stephanie Newport & Abdul M. Rasheed. 1993. Configuration research in strategic
management: key issues and suggestions. Journal of Management 19 4:775–795.
Dewar, Robert D. & Jane E. Dutton. 1986. The adoption of radical and incremental innovations: an
empirical analysis. Management Science 32:1422–1433.
Dooley, Kevin & Andrew Van de Ven. 1999. Explaining complex organizational dynamics. Organization
Science 10:358–372.
Doty, Harold D. & William H. Glick. 1994. Typologies as a unique form of theory building: toward
improved understanding and modeling. Academy of Management Review 19:230–251.
Driver, Harold E. & Alfred L. Kroeber. 1932. Quantitative expression of cultural relationships. Univer-
sity of California Publications in American Archaeology and Ethnology 31:211–256.
Efron, Bradley 1979. Bootstrap methods: another look at the jackknife. Annals of Statistics 7:1–26.
Efron, Bradley & Gail Gong. 1983. A leisurely look at the bootstrap, the jackknife and cross validation.
American Statistician 37:36–48.
Eisenhardt, Kathleen M. & Jeffrey A. Martin. 2000. Dynamic capabilities: what are they? Strategic
Management Journal 21:1105–1121.
Etzioni, Amitai. 1964. Modern organizations. Free Press, New York.
Everitt, Brian S. 1986. Cluster analysis. 2nd edition. Gower Publishing, Aldershot.
Farris, James S. 1970. Methods for computing Wagner trees. Systematic Zoology 19:83–92.
33. PHYLOGENETIC RECONSTRUCTION OF ORGANIZATIONAL LIFE 303
Farris, James S. 1977. Phylogenetic analysis under Dollo’s Law. Systematic Zoology 26:77–88.
Felsenstein, Joseph. 1985. Confidence limits on phylogenies: an approach using the bootstrap. Evolution
39:783–791.
Felsenstein, Joseph. 1993. PHYLIP – phylogeny inference package, (version 3.5c). Distributed by the
author, Department of Genetics, University of Washington, Seattle.
Filley, Alan C. & Ramon J. Aldag. 1978. Characteristics and measurement of an organizational typol-
ogy. Academy of Management Journal 21:578–591.
Fitch, Walter M. 1971. Toward defining the course of evolution: minimal change for a specific tree
topology. Systematic Zoology 20:406–416.
Fligstein, Neil 1985. The spread of the multidivisional form. American Sociological Review 50:377–391.
Forey, Peter L., Christopher. J. Humphries, Ian J. Kitching, Robert W. Scotland, Darrell J. Siebert &
David M. Williams. 1992. Cladistics: a practical course in systematics. Clarendon Press, Oxford.
Fox, John. 1982. Selective aspects of measuring resemblance for taxonomy. Pp. 127–151 in H. C. Hud-
son (ed.) Classifying Social Data. Jossey-Bass, San Francisco.
Galbraith, Craig & Dan Schendel. 1983. An empirical analysis of strategy types. Strategic Management
Journal 4:153–174.
Ghiselin, Michael T. 1966. On psychologism in the logic of taxonomic controversies. Systematic Zoology
15:207–215.
Ghiselin, Michael T. 1974. A radical solution to the species problem. Systematic Zoology 23:536–544.
Ghiselin, Michael T. 1997. Metaphysics and the Origin of Species. SUNY Press, Albany.
Gilmour, John. S. L. 1937. A taxonomic problem. Nature 139:1040–1042.
Good, Irving. J. 1965. Categorization of classification. Pp. 115–128 in Mathematics and Computer Sci-
ence in Medicine and Biology. H.M.S.O, London.
Goronzy, Freidhelm. 1969. A numerical taxonomy on business enterprises. Pp. 42–52 in A. J. Cole (ed.)
Numerical Taxonomy. Proceedings of the Colloquium on Numerical Taxonomy. Academic Press, St
Andrews University.
Green, Paul E., Ronald E. Frank & Patrick J. Robinson. 1967. Cluster analysis in test market selection.
Management Science l3:387–400.
Gross, Edward. 1969. The definition of organizational goals. British Journal of Sociology 20:277–294.
Haas, Eugene J., Richard H. Hall & Norman I. Johnson. 1966. Toward an empirically derived taxon-
omy of organizations. Pp 157–180 in R. Bowers (ed.) Studies on Behavior in Organizations. Univer-
sity of Georgia Press, Athens GA.
Haeckel, Ernst. 1866. Generelle morphologie der organismen. Zweiter Band: Allgemeine Ent-
wicklungsgeschichte der Organismen. Verlag Georg Reimer, Berlin.
Hambrick, Donald C. 1983. An empirical typology of mature industrial product environment. Academy
of Management Journal 26:213–230.
Hannan, Michael T. & John H. Freeman. 1977. The population ecology of organizations. American
Journal of Sociology 82:929–964.
Hannan, Michael T. & John H. Freeman. 1989. Organizational ecology. Harvard University Press, Cam-
bridge MA.
Hatten, Kenneth J. & Mary L. Hatten. 1985. Some empirical insights for strategic marketers: the case of
beer. Pp. 275–292 in H. Thomas & D. M. Gardner (ed.) Strategic Marketing and Management. Wiley,
Chichester and New York.
Hayes, Samuel L., A. Michael Spence & David Van Praag Marks. 1983. Competition in the investment
banking industry. Harvard University Press, Cambridge MA.
Hennig, Willi. 1950. Grundzuge einer theorie der phylogenetischen systematik. Deutscher Zentraverlag,
Berlin.
Hennig, Willi. 1966. Phylogenetic systematics. Urbana, University of Illinois Press.
Hodson, Frank R. 1931. Numerical typology and prehistoric archaeology. Pp. 30–45 in F. R. Hodson,
D. G. Kendall & .P. A. Tautu (ed.) Mathematics in the Archaeological and Historical Sciences. Uni-
versity Press, Edinburgh.