Knowledge sharing is an important initiative in creating competitive advantage. As an important tool in the
successful implementation of Knowledge Management (KM), sharing knowledge is seen to be the most
important practice and resource which organization possesses. Various organizations have developed
strategies to ensure that KM is successful by embedding knowledge sharing practices in their routine work
processes. Nowadays, people have been using virtual platforms and web-based technologies, such as
Internet, Intranet, blogs, social media, and other online technology, for sharing knowledge and
information. The purpose of this study is to evaluate factors that can inculcate knowledge sharing behavior
using the virtual platforms. Therefore, this study will adopt Unified Theory of Acceptance and Use of
Technology (UTAUT) to investigate the key factors on this sharing behavior. The UTAUT model adopted in
this paper is empirically tested on a sample of 510respondents, and significant relationships among these
constructs were found.
Knowledge sharing innovation_and_firm_performance_evidence_from_turkeyMesut DOĞAN
The aim of this study is to determine relationship between knowledge sharing, innovation and firm performance. In the current study, a survey was conducted on a total of 150 high-tech companies operating in Istanbul, Ankara and Antalya. In the analysis results, it is seen that innovation speed and quality affect both the operational and financial performance of firms. In other words, as innovation speed and quality increase, so does the operational and financial performance of firms. Another important finding obtained in the current study is that explicit knowledge sharing, and tacit knowledge sharing have a positive effect on firm performance. A high level of innovation encompasses new products, processes or applications in most company activities. As a result, innovation can create a competitive advantage by creating synergy in the activities of companies and encourage creativity. Keywords: Innovation Speed and Quality, Explicit and Tacit Knowledge Sharing, Firm Performance
JEL Classification: L25, O31, O33
The advancement of the information and communications technology has helped almost all governments across the world as they have exploited these technologies for delivering services to their citizens. However, this phenomenon may face several challenges and barriers that lead to the failure in its adoption, use, or continuous usage. In the Arab countries, the rate of failure in the use of electronic services is high in the public sector. Therefore, previous studies have concentrated on this critical issue and highlighted on the citizens’ perspective andignored the perspective of employees in the government organizations.In addition, very few previous studies dealt with the quality of the services based on the employees’viewpoint. Thus, based on the arguments that have been stated earlier, this preliminary study strives to identify the factors that may affect the electronic administrative adoption according to the employees’ perspective. With regard to the data collection, the quantitative method, self-administered questionnaires will be distributed among the staff of the Al-Mustansiriyah University, Iraq.With regard to data analysis, a partial least squares structural equation modelling will be used as a technique to analyse the collected data from a key respondent (Employee). In fact, this research strivesto enrich the literature by adding more information about the factors that may hinder theadoption of modern technologies in general and electronic administration in particular. With regard to the Al-Mustansiriyah University, the present study is considered as the first study conducted in this area; therefore the outputs will assist the government to remedy these obstacles before beginning any project in the public sector including the use of ICT instead of the conventional manner.The result of the analysis showed that system quality, service quality, trust of organization, and usefulness were found as significant factors that affect the employees’ adoption of e-administration services in University.
Knowledge management is much talked about concept in this era but there are some impediments in its management. Though there is much heat regarding knowledge management, there is less light. When some others hear the concepts information and knowledge management, what comes in their minds are computers yet computers are only enablers There is much confusion in information and knowledge management.. Confusion also exists on the differences between information and knowledge management. There are half life, threat to specialist and mobility as impediments in knowledge management
Managing lifelong learning records through blockchain. Patrick Ocheja , Brend...eraser Juan José Calderón
Managing lifelong learning records through blockchain de Patrick Ocheja , Brendan Flanagan, Hiroshi Ueda and Hiroaki Ogata publicado en Research and Practice in Technology Enhanced Learning (2019) 14:4
Theorising technology in education: an introduction Cristina Costa,Michael Ha...eraser Juan José Calderón
Theorising technology in education: an introduction Cristina Costa,Michael Hammond &Sarah Younie.
GUEST EDITORIAL
Theorising technology in education: an introduction This is a special issue of Technology, Pedagogy and Education which showcases the application of a range of theories in the conceptualisation and analysis of educational technology. In this introduction we describe what led us to organise this issu
Knowledge sharing innovation_and_firm_performance_evidence_from_turkeyMesut DOĞAN
The aim of this study is to determine relationship between knowledge sharing, innovation and firm performance. In the current study, a survey was conducted on a total of 150 high-tech companies operating in Istanbul, Ankara and Antalya. In the analysis results, it is seen that innovation speed and quality affect both the operational and financial performance of firms. In other words, as innovation speed and quality increase, so does the operational and financial performance of firms. Another important finding obtained in the current study is that explicit knowledge sharing, and tacit knowledge sharing have a positive effect on firm performance. A high level of innovation encompasses new products, processes or applications in most company activities. As a result, innovation can create a competitive advantage by creating synergy in the activities of companies and encourage creativity. Keywords: Innovation Speed and Quality, Explicit and Tacit Knowledge Sharing, Firm Performance
JEL Classification: L25, O31, O33
The advancement of the information and communications technology has helped almost all governments across the world as they have exploited these technologies for delivering services to their citizens. However, this phenomenon may face several challenges and barriers that lead to the failure in its adoption, use, or continuous usage. In the Arab countries, the rate of failure in the use of electronic services is high in the public sector. Therefore, previous studies have concentrated on this critical issue and highlighted on the citizens’ perspective andignored the perspective of employees in the government organizations.In addition, very few previous studies dealt with the quality of the services based on the employees’viewpoint. Thus, based on the arguments that have been stated earlier, this preliminary study strives to identify the factors that may affect the electronic administrative adoption according to the employees’ perspective. With regard to the data collection, the quantitative method, self-administered questionnaires will be distributed among the staff of the Al-Mustansiriyah University, Iraq.With regard to data analysis, a partial least squares structural equation modelling will be used as a technique to analyse the collected data from a key respondent (Employee). In fact, this research strivesto enrich the literature by adding more information about the factors that may hinder theadoption of modern technologies in general and electronic administration in particular. With regard to the Al-Mustansiriyah University, the present study is considered as the first study conducted in this area; therefore the outputs will assist the government to remedy these obstacles before beginning any project in the public sector including the use of ICT instead of the conventional manner.The result of the analysis showed that system quality, service quality, trust of organization, and usefulness were found as significant factors that affect the employees’ adoption of e-administration services in University.
Knowledge management is much talked about concept in this era but there are some impediments in its management. Though there is much heat regarding knowledge management, there is less light. When some others hear the concepts information and knowledge management, what comes in their minds are computers yet computers are only enablers There is much confusion in information and knowledge management.. Confusion also exists on the differences between information and knowledge management. There are half life, threat to specialist and mobility as impediments in knowledge management
Managing lifelong learning records through blockchain. Patrick Ocheja , Brend...eraser Juan José Calderón
Managing lifelong learning records through blockchain de Patrick Ocheja , Brendan Flanagan, Hiroshi Ueda and Hiroaki Ogata publicado en Research and Practice in Technology Enhanced Learning (2019) 14:4
Theorising technology in education: an introduction Cristina Costa,Michael Ha...eraser Juan José Calderón
Theorising technology in education: an introduction Cristina Costa,Michael Hammond &Sarah Younie.
GUEST EDITORIAL
Theorising technology in education: an introduction This is a special issue of Technology, Pedagogy and Education which showcases the application of a range of theories in the conceptualisation and analysis of educational technology. In this introduction we describe what led us to organise this issu
Social Media Success Model for Knowledge Sharing (Scale Development and Valid...TELKOMNIKA JOURNAL
This study aimed to evaluate the success of social media as a means of sharing knowledge among scholars in Indonesia. By using Information System Success Model (DeLone and McLean), this study develops a research model that will be used to investigate what factors are contributing to the success of social media as tool for sharing knowledge among academics. This article would focus on the discussion of instrument development and validation process. The method for development and validation the research instrument was refers to the framework proposed by McKanzie et al. This study resulted in a validated instrument, the instrument could use by researchers who are interested in study social media success for knowledge sharing.
Bridging the ‘missing middle’: a design based approach to scalingdebbieholley1
Holley, D., Peffer, G. Santos, P., and Cook, J. (2014). Bridging the ‘missing middle’: a design based approach to scaling. Presented to the ALT-Conference, September 2014
A paper contributing to EU learning layers project,:Scaling up Technologies for Informal Learning in SME Clusters
A 9.9 million EU Framework Project (2012-2016)
Abstract
Taking innovation from concept through to scalable delivery is complex, contested and an under-theorised process. In this paper we outline approaches to scaling that have influenced in our work in the EU Learning Layers Integrating Project, a consortium consisting of 17 institutions from 7 different countries. The two industries identified for the initial work are the Health sector in the UK, and the Construction sector in Germany. The focus of the EU project is scaling informal learning in the workplace through the use of technologies; the focus of our paper, the ‘Help Seeking’ tool, an online tool developed by co-design with GP Practice staff in the North of England. Drawing upon three Scaling taxonomies to underpin our work, we map the complex and interrelated strands influencing scaling of the ‘Help-Seeking’ tool, and go on to suggest that the typical measure of scaling success ‘by number’ needs a more nuanced analysis. Furthermore, we will propose that the emerging framework enables the orchestration of team discourse about theory, the production of artefacts as tools for design discourse, the identification of scalable systemic pain points, and is thus throwing light on the ‘missing middle’ (where key scaling factors reside between top down strategy and bottom up initiatives).
Effect of Knowledge Management Strategies and Innovation on Organizational Pe...AJHSSR Journal
The purpose of this study is about the influence of knowledge management strategies and
innovation can enhance organizational performance. This research was conducted on the electrical railroad
(KRL), a land transportation mode operated by PT. KCJ (Commuter KAI Jabodetabek) Indonesia. The variables
of study are operated by the dimensions of knowledge management strategy (codification and personalization),
innovation (process and product) and organizational performance by using balanced scorecard indicators,
namely financial perspective, customer perspective, internal business process perspective, and learning and
growth process perspective. Analysis Data were used SEM-PLS with vadility test and reliability test and
hypotheses tested using path coefficients. The results of the study shown that knowledge management strategies
influence to innovation on organizational performance on PT. Commuter Line (Jabodetabek) Indonesia.
The healthcare industry is rapidly evolving in tandem with a demand for increased flexibility in the delivery of education in our fast-paced society. As a result, the passive reception of content by students, delivered by an expert from the front of the class, is becoming increasingly redundant. Students are now being taught, ubiquitous connectivity allowing widespread access to online materials (Collier, Gray, & Ahn, 2011). Programs such as nursing are often offered in an external, online delivery mode (Wright, 2013). Due to an increasingly aging population, healthcare is by far one of the fastest-growing industries, and graduate job seekers choosing to enter healthcare, will need to ensure they have developed sound digital literacies, particularly as they apply to professional communication. It is imperative that students develop and leverage emerging communication technologies as part of their portfolio prior to seeking employment (Clark, 2009; Hargittai & Litt, 2013).
Assessing The Tangible And Intangible Impacts Of The Convergence Of E-Learnin...ijistjournal
Learning comes through creating and applying knowledge, whilst learning increases an individual's and organization's knowledge asset. Both e-learning and knowledge management feed off the same root: learning, improved capacity to perform work tasks, ability to make effective decisions, and positively impact the world around us. The difference between KM and e-learning is a function of time; knowledge management is dynamic, e-learning is static. As a medium, e-learning allows for the sharing of knowledge that has been tested, researched and organized. Knowledge management is much livelier. Conversations and sharing understanding happens in real time. Through KM, tacit understanding can be communicated,problems can be jointly solved, and serendipitous connections are formed. KM is chaotic, current. KM is ecology; e-learning is the architecture. E-learning courses become outdated, while KM environments are continually fresh and reflective of current activity in a field. Anyway, the strengths of the two fields need to be brought together. KM should feed into e-learning in order for the content of the "course" to remain fresh and to tap learners into a sustained knowledge environment after the course is done and e-learning should feed into the KM environment to provide easy mechanisms for organizing information in the manner that most of the people function. Thereis no doubt that converging this two technology creates bigger impact in the learning process, but our discussion is focused to justify whether the convergence creates better value or not. In the light of the discussion, the conceptual link between these two key technologies has been drawn and several related issues are discussed.3.
FRAMEWORK FOR EDUCATIONAL COMPETENCE WITH EMERGING SCENARIOijcsit
For effective management and governance of education system, several efforts have been evolving
continuously by using Information Communication and Technology for Educational Management. The role
of the Information and Communication Technology (ICT) infrastructure particularly services require for
the data intensive and communication intensive application becomes more important. Further, due to the
massive growth of information, situation becomes difficult to manage these services. The present paper
discusses the related issues such as competence building, creation of appropriate ICT infrastructure, ICT
acceptance level etc. required for Information Technology for Educational Management(ITEM)
competence building framework, considered in an earlier approach for core competences for ITEM.
Therefore, it becomes essential to consider the global standard and relevant ICT infrastructure. This effort
will help in activities and resource management for effective implementation of the framework.
Rhetoric and reality: critical perspectives on education in a 3D virtual worldHelen Farley
The emergence of any new educational technology is often accompanied by inflated expectations about its potential for transforming pedagogical practice and improving student learning outcomes. A critique of the rhetoric accompanying the evolution of 3D virtual world education
reveals a similar pattern, with the initial hype based more on rhetoric than research demonstrating the extent to which rhetoric matches reality. Addressed are the perceived gaps in the literature through a critique of the rhetoric evident throughout the evolution of the application of virtual worlds in education and the reality based on the reported experiences of experts in the field of educational technology, who are all members of the Australian and New Zealand Virtual Worlds Working Group. The experiences reported highlight a range of effective virtual world collaborative and communicative teaching experiences conducted in members’ institutions.
Perspectives vary from those whose reality is the actuation of the initial rhetoric in the early years of virtual world education, to those whose reality is fraught with challenges that belie the rhetoric. Although there are concerns over institutional resistance, restrictions, and outdated processes on the one-hand, and excitement over the rapid emergence of innovation on the other, the prevailing reality seems to be that virtual world education is both persistent and sustainable. Explored are critical perspectives on the rhetoric and reality on the educational uptake and use of virtual worlds in higher education, providing an overview of the current and future directions for learning in virtual worlds.
At this time, e-governance transformation is considered as one of the most important and biggest challenges among
and within the IT-related sector from the scale and complexity perspective. In this respect, the researches have
reviewed and studied some of the factors that affect implementing the e-governance for Public and private schools in
Governorate of Al Buraimi, Oman. The aim of the study was to determine whether there existed organizational
differences that demanded different approaches and strategies for the implementation of e-governance. The research
considered three organizational factors, which included, the type of the organization (public or private), size of the
organization and the work experience of the employees of the organization. In addition, the research considered the
some of the requirements needed for the implementation of e-governance. These requirements included, physical,
financial, administrative and management requirements. Through the research it was evident that the different types
of requirements needed for the implementation of e-governance varied by the organizational factors. In other words,
the findings indicated that the approaches and strategies that needs to be adopted will differ with the organizational
characteristics. This differences needs to be considered at the time of implementation and should be incorporated
when developing the implementation plans by the implementing organization
Virtual Worlds in Education: Coming of the Third WaveHelen Farley
The Gartner Hype Cycle has placed virtual worlds on the climb up the Slope of Enlightenment. While some authors in the past have made much of the educational use of virtual worlds languishing in the Trough of Disillusionment, there has been a community of authors, designers and educators working to further understanding of the imitations and affordances of such technologies. It is time to pool this knowledge, experience, tools and practice to solidify best practice, focus research on development of specific elements and forge ahead to shape the third wave of educational virtual worlds. This paper attempts to outline this information and practice while offering solutions for further development.
Invited talk: Using Social Media and Mobile Devices to Mediate Informal, Professional, Work-Based Learning
John Cook
Bristol Centre for Research
in Lifelong Learning and Education (BRILLE)
University of the West of England (UWE)
http://www.uwe.ac.uk/research/brille/
http://people.uwe.ac.uk/Pages/person.aspx?accountname=campus\jn-cook
Invited talk: Centre for Learning, Knowing and Interactive Technologies, Graduate School of Education, University of Bristol
26th February, 12.30 to 13.45
The way adults pursue their education through life is changing as the technology around us
relentlessly continues to enhance our quality of life and further enhances every aspect of the
different tasks we set out to perform. This exploratory paper looks into how every adult can
embody a comprehensive set of academic services, platforms and systems to assist every
individual in the educational goals that one sets. A combination of three distinct technologies
are presented together with how they not only come together but complement each other around
a person in what is usually referred to as a personal area network. The network in this case
incorporates an intelligent personal learning environment providing personalised content,
intelligent wearables closer to the user to provide additional contextual customisation, and a
surrounding ambient intelligent environment to close a trio of technologies around every
individual. Each of the three research domains will be presented to uncover how each
contributes to the personal network that embodies what one usually expects from an educational
institution. Three distinct prototype systems have been developed, tested and deployed within a
functional system that will be presented in this paper.
Research on the field of using social media has gained more importance in the recent days due to the rapid development of social media technologies. Looking at the behavioral intention and attitude of using social media for collaborative learning within Malaysian higher educational institutions and the influencing factors in this regard has received little attention by researchers. The study aims at examining the determinants that affect learners’ attitude and behavior intention regarding their use social media to achieve collaborative learning. Such examination is carried out by using the Theory Acceptance Model (TAM) and Unified Theory of Acceptance and Usage of Technology (UTAUT). A total of 243 participants were recruited for this study. The findings indicated that students’ attitudes and behavior are strong indicators of their intentions in terms of using social media in collaborative learning.
An Analytical Study on Knowledge Sharing within the Organizationijcnes
The better management of knowledge within the organization will lead to improved innovation and competitive advantage. The main goal of the firm� better utilization of internal and external knowledge. This core knowledge is found in individuals, communities of interest and their connections. An organization�s data is found in its computer systems but a company�s intelligence is found, in its biological and social systems. Though it is acclaimed as a good method, there are some setbacks in the process of knowledge sharing[KS] among the employees. This paper explores the possible ways to establish organization using social computing tools to facilitate Knowledge Sharing and create a social data mining among all the members of organization. Social Data Mining Network Analysis (SDMNA) techniques have been used to study KS patterns which take place between employees and departments. This SDMNA graph reveals the structure of social data mining network highlighting connectivity, clustering and strength of relationships between employees.
Social Media Success Model for Knowledge Sharing (Scale Development and Valid...TELKOMNIKA JOURNAL
This study aimed to evaluate the success of social media as a means of sharing knowledge among scholars in Indonesia. By using Information System Success Model (DeLone and McLean), this study develops a research model that will be used to investigate what factors are contributing to the success of social media as tool for sharing knowledge among academics. This article would focus on the discussion of instrument development and validation process. The method for development and validation the research instrument was refers to the framework proposed by McKanzie et al. This study resulted in a validated instrument, the instrument could use by researchers who are interested in study social media success for knowledge sharing.
Bridging the ‘missing middle’: a design based approach to scalingdebbieholley1
Holley, D., Peffer, G. Santos, P., and Cook, J. (2014). Bridging the ‘missing middle’: a design based approach to scaling. Presented to the ALT-Conference, September 2014
A paper contributing to EU learning layers project,:Scaling up Technologies for Informal Learning in SME Clusters
A 9.9 million EU Framework Project (2012-2016)
Abstract
Taking innovation from concept through to scalable delivery is complex, contested and an under-theorised process. In this paper we outline approaches to scaling that have influenced in our work in the EU Learning Layers Integrating Project, a consortium consisting of 17 institutions from 7 different countries. The two industries identified for the initial work are the Health sector in the UK, and the Construction sector in Germany. The focus of the EU project is scaling informal learning in the workplace through the use of technologies; the focus of our paper, the ‘Help Seeking’ tool, an online tool developed by co-design with GP Practice staff in the North of England. Drawing upon three Scaling taxonomies to underpin our work, we map the complex and interrelated strands influencing scaling of the ‘Help-Seeking’ tool, and go on to suggest that the typical measure of scaling success ‘by number’ needs a more nuanced analysis. Furthermore, we will propose that the emerging framework enables the orchestration of team discourse about theory, the production of artefacts as tools for design discourse, the identification of scalable systemic pain points, and is thus throwing light on the ‘missing middle’ (where key scaling factors reside between top down strategy and bottom up initiatives).
Effect of Knowledge Management Strategies and Innovation on Organizational Pe...AJHSSR Journal
The purpose of this study is about the influence of knowledge management strategies and
innovation can enhance organizational performance. This research was conducted on the electrical railroad
(KRL), a land transportation mode operated by PT. KCJ (Commuter KAI Jabodetabek) Indonesia. The variables
of study are operated by the dimensions of knowledge management strategy (codification and personalization),
innovation (process and product) and organizational performance by using balanced scorecard indicators,
namely financial perspective, customer perspective, internal business process perspective, and learning and
growth process perspective. Analysis Data were used SEM-PLS with vadility test and reliability test and
hypotheses tested using path coefficients. The results of the study shown that knowledge management strategies
influence to innovation on organizational performance on PT. Commuter Line (Jabodetabek) Indonesia.
The healthcare industry is rapidly evolving in tandem with a demand for increased flexibility in the delivery of education in our fast-paced society. As a result, the passive reception of content by students, delivered by an expert from the front of the class, is becoming increasingly redundant. Students are now being taught, ubiquitous connectivity allowing widespread access to online materials (Collier, Gray, & Ahn, 2011). Programs such as nursing are often offered in an external, online delivery mode (Wright, 2013). Due to an increasingly aging population, healthcare is by far one of the fastest-growing industries, and graduate job seekers choosing to enter healthcare, will need to ensure they have developed sound digital literacies, particularly as they apply to professional communication. It is imperative that students develop and leverage emerging communication technologies as part of their portfolio prior to seeking employment (Clark, 2009; Hargittai & Litt, 2013).
Assessing The Tangible And Intangible Impacts Of The Convergence Of E-Learnin...ijistjournal
Learning comes through creating and applying knowledge, whilst learning increases an individual's and organization's knowledge asset. Both e-learning and knowledge management feed off the same root: learning, improved capacity to perform work tasks, ability to make effective decisions, and positively impact the world around us. The difference between KM and e-learning is a function of time; knowledge management is dynamic, e-learning is static. As a medium, e-learning allows for the sharing of knowledge that has been tested, researched and organized. Knowledge management is much livelier. Conversations and sharing understanding happens in real time. Through KM, tacit understanding can be communicated,problems can be jointly solved, and serendipitous connections are formed. KM is chaotic, current. KM is ecology; e-learning is the architecture. E-learning courses become outdated, while KM environments are continually fresh and reflective of current activity in a field. Anyway, the strengths of the two fields need to be brought together. KM should feed into e-learning in order for the content of the "course" to remain fresh and to tap learners into a sustained knowledge environment after the course is done and e-learning should feed into the KM environment to provide easy mechanisms for organizing information in the manner that most of the people function. Thereis no doubt that converging this two technology creates bigger impact in the learning process, but our discussion is focused to justify whether the convergence creates better value or not. In the light of the discussion, the conceptual link between these two key technologies has been drawn and several related issues are discussed.3.
FRAMEWORK FOR EDUCATIONAL COMPETENCE WITH EMERGING SCENARIOijcsit
For effective management and governance of education system, several efforts have been evolving
continuously by using Information Communication and Technology for Educational Management. The role
of the Information and Communication Technology (ICT) infrastructure particularly services require for
the data intensive and communication intensive application becomes more important. Further, due to the
massive growth of information, situation becomes difficult to manage these services. The present paper
discusses the related issues such as competence building, creation of appropriate ICT infrastructure, ICT
acceptance level etc. required for Information Technology for Educational Management(ITEM)
competence building framework, considered in an earlier approach for core competences for ITEM.
Therefore, it becomes essential to consider the global standard and relevant ICT infrastructure. This effort
will help in activities and resource management for effective implementation of the framework.
Rhetoric and reality: critical perspectives on education in a 3D virtual worldHelen Farley
The emergence of any new educational technology is often accompanied by inflated expectations about its potential for transforming pedagogical practice and improving student learning outcomes. A critique of the rhetoric accompanying the evolution of 3D virtual world education
reveals a similar pattern, with the initial hype based more on rhetoric than research demonstrating the extent to which rhetoric matches reality. Addressed are the perceived gaps in the literature through a critique of the rhetoric evident throughout the evolution of the application of virtual worlds in education and the reality based on the reported experiences of experts in the field of educational technology, who are all members of the Australian and New Zealand Virtual Worlds Working Group. The experiences reported highlight a range of effective virtual world collaborative and communicative teaching experiences conducted in members’ institutions.
Perspectives vary from those whose reality is the actuation of the initial rhetoric in the early years of virtual world education, to those whose reality is fraught with challenges that belie the rhetoric. Although there are concerns over institutional resistance, restrictions, and outdated processes on the one-hand, and excitement over the rapid emergence of innovation on the other, the prevailing reality seems to be that virtual world education is both persistent and sustainable. Explored are critical perspectives on the rhetoric and reality on the educational uptake and use of virtual worlds in higher education, providing an overview of the current and future directions for learning in virtual worlds.
At this time, e-governance transformation is considered as one of the most important and biggest challenges among
and within the IT-related sector from the scale and complexity perspective. In this respect, the researches have
reviewed and studied some of the factors that affect implementing the e-governance for Public and private schools in
Governorate of Al Buraimi, Oman. The aim of the study was to determine whether there existed organizational
differences that demanded different approaches and strategies for the implementation of e-governance. The research
considered three organizational factors, which included, the type of the organization (public or private), size of the
organization and the work experience of the employees of the organization. In addition, the research considered the
some of the requirements needed for the implementation of e-governance. These requirements included, physical,
financial, administrative and management requirements. Through the research it was evident that the different types
of requirements needed for the implementation of e-governance varied by the organizational factors. In other words,
the findings indicated that the approaches and strategies that needs to be adopted will differ with the organizational
characteristics. This differences needs to be considered at the time of implementation and should be incorporated
when developing the implementation plans by the implementing organization
Virtual Worlds in Education: Coming of the Third WaveHelen Farley
The Gartner Hype Cycle has placed virtual worlds on the climb up the Slope of Enlightenment. While some authors in the past have made much of the educational use of virtual worlds languishing in the Trough of Disillusionment, there has been a community of authors, designers and educators working to further understanding of the imitations and affordances of such technologies. It is time to pool this knowledge, experience, tools and practice to solidify best practice, focus research on development of specific elements and forge ahead to shape the third wave of educational virtual worlds. This paper attempts to outline this information and practice while offering solutions for further development.
Invited talk: Using Social Media and Mobile Devices to Mediate Informal, Professional, Work-Based Learning
John Cook
Bristol Centre for Research
in Lifelong Learning and Education (BRILLE)
University of the West of England (UWE)
http://www.uwe.ac.uk/research/brille/
http://people.uwe.ac.uk/Pages/person.aspx?accountname=campus\jn-cook
Invited talk: Centre for Learning, Knowing and Interactive Technologies, Graduate School of Education, University of Bristol
26th February, 12.30 to 13.45
The way adults pursue their education through life is changing as the technology around us
relentlessly continues to enhance our quality of life and further enhances every aspect of the
different tasks we set out to perform. This exploratory paper looks into how every adult can
embody a comprehensive set of academic services, platforms and systems to assist every
individual in the educational goals that one sets. A combination of three distinct technologies
are presented together with how they not only come together but complement each other around
a person in what is usually referred to as a personal area network. The network in this case
incorporates an intelligent personal learning environment providing personalised content,
intelligent wearables closer to the user to provide additional contextual customisation, and a
surrounding ambient intelligent environment to close a trio of technologies around every
individual. Each of the three research domains will be presented to uncover how each
contributes to the personal network that embodies what one usually expects from an educational
institution. Three distinct prototype systems have been developed, tested and deployed within a
functional system that will be presented in this paper.
Research on the field of using social media has gained more importance in the recent days due to the rapid development of social media technologies. Looking at the behavioral intention and attitude of using social media for collaborative learning within Malaysian higher educational institutions and the influencing factors in this regard has received little attention by researchers. The study aims at examining the determinants that affect learners’ attitude and behavior intention regarding their use social media to achieve collaborative learning. Such examination is carried out by using the Theory Acceptance Model (TAM) and Unified Theory of Acceptance and Usage of Technology (UTAUT). A total of 243 participants were recruited for this study. The findings indicated that students’ attitudes and behavior are strong indicators of their intentions in terms of using social media in collaborative learning.
An Analytical Study on Knowledge Sharing within the Organizationijcnes
The better management of knowledge within the organization will lead to improved innovation and competitive advantage. The main goal of the firm� better utilization of internal and external knowledge. This core knowledge is found in individuals, communities of interest and their connections. An organization�s data is found in its computer systems but a company�s intelligence is found, in its biological and social systems. Though it is acclaimed as a good method, there are some setbacks in the process of knowledge sharing[KS] among the employees. This paper explores the possible ways to establish organization using social computing tools to facilitate Knowledge Sharing and create a social data mining among all the members of organization. Social Data Mining Network Analysis (SDMNA) techniques have been used to study KS patterns which take place between employees and departments. This SDMNA graph reveals the structure of social data mining network highlighting connectivity, clustering and strength of relationships between employees.
Extending UTAUT to explain social media adoption by microbusinessesDebashish Mandal
This paper establishes inadequacies of the Unified Theory of Acceptance and Use of Technology (UTAUT) theory to explain social media adoption by microbusinesses. Literature review confirms the explaining power of UTAUT in variety of technology adoption by businesses. This paper uses UTAUT theory to implement social media technology in microbusinesses. Canonical action research method is adopted to introduce social media in microbusinesses. A post positivist approach is used to report the results based on a predetermined premise. It was found that the major constructs of performance and effort expectancy played insignificant role in establishing behavioural and adoption intention of social media by microbusinesses. Social influence and facilitating condition did not influence the behavioural intentions of the microbusiness owners. Individual characteristics and codification effort dominated the use behaviour. Goal of gaining customers leads to behavioural modification resulting in replacing of behavioural intention with goals as a superior method of predicting adoption behaviour within the context of microbusinesses. This paper extends the UTAUT to explain social media adoption in microbusinesses.
CREATING AND SHARING KNOWLEDGE THROUGH A CORPORATE SOCIAL NETWORKING SITE: TH...Julio Figueroa
Paper published in PACIS2012
There have been various claims that enterprise social networking sites (ESN) might improve business effectiveness and performance. Nevertheless, many of the initiatives supported by ESNs have failed. This paper argues that divergent perceptions about ESNs across the different levels of the organization may explain failures in ESNs’ design and implementation. Using an extended version of the Technological Frames of Reference framework (Orlikowski & Gash, 1994), this paper reports on a study that analyzed employee’s perceptions about an ESN within a software engineering firm. It was found that significant divergent perceptions in the organization led to a social order that discouraged employees to create and share knowledge through the ESN. This paper highlights the importance of aligning top management perceptions about the ESN with its actual scope. It also highlights the relevance of aligning perceptions about the ESN across the different levels of the organization. This paper proposes extending the original Technological Frames of Reference framework in order to better understand people’s perceptions about technologies that support knowledge management systems. It also proposes an explanatory model for understanding how people’s perceptions about a corporate social networking site impact on its usage.
At present, the state-of-the-art supplies for conducting a face-to-face design thinking workshop typically consists of self-stick notes and stickers, markers, and whiteboards. However, this analog way of working is incongruent with the realities of global software companies, where most products and services are developed by distributed teams. This paper explores the process of facilitating remote design thinking workshops, using information technology and communication tools. The paper is based on a participatory action research undertaken by the author as a part of the doctoral thesis - ‘a study on an approach to prepare the organization mindset to build design-led innovation culture to become a customer-centric and future driven software company’ in the Indian IT sector. The participating company realized the innovation breakthroughs using design thinking can happen only when their organization can collaborate across disciplines, silos, time zones; and were looking for a solution to scale design thinking in their organization. KEYWORDS: Collaboration, Digital Design Thinking, Distributed Teams, Innovation, Remote Design Thinking, Scale Design Thinking
Published in International Research Journal of Marketing and Economics ISSN: (2349-0314) Impact Factor- 5.779, Volume 5, Issue 7, July 2018
APPLICATION OF A MULTILEVEL TECHNOLOGY ACCEPTANCE MANAGEMENT MODEL FOR EFFECT...ijcsit
Effective deployment of a technology in an environment is the desire of many system developers. Positive uptake of a technology coupled with user acceptance is deemed as a key indicator towards technology acceptance. Knowledge is weighed as a strategic resource for any successful data driven decision making initiative. Institutions leverage on technological initiatives and tools to drive knowledge management (KM) initiatives that enhance quality service delivery and prudent data management. These initiatives provide the overall strategy for managing data resources. They make available knowledge organization tools and techniques while enabling regular updates. Derived benefits of positive deployment of a technological intervention are competency enhancement through gained knowledge, raised quality of service and promotion of healthy development of e-commerce. Successful and timely adoption of technological interventions through which knowledge management initiatives are deployed remains a key challenge to many organizations. This paper proposes the application of a wholesome multilevel technology acceptance management model towards effective technology deployment. The proposed model takes into account human, technological and organizational variables, which exist in a deployment environment. This model will be vital in driving early technology acceptance pred
Effective deployment of a technology in an environment is the desire of many system developers. Positive uptake of a technology coupled with user acceptance is deemed as a key indicator towards technology acceptance. Knowledge is weighed as a strategic resource for any successful data driven decision making initiative. Institutions leverage on technological initiatives and tools to drive knowledge management (KM) initiatives that enhance quality service delivery and prudent data management. These initiatives provide the overall strategy for managing data resources. They make available knowledge organization tools and techniques while enabling regular updates. Derived benefits of positive deployment of a technological intervention are competency enhancement through gained knowledge, raised quality of service and promotion of healthy development of e-commerce. Successful and timely adoption of technological interventions through which knowledge management initiatives are deployed remains a key challenge to many organizations. This paper proposes the application of a wholesome multilevel technology acceptance management model towards effective technology deployment. The proposed model takes into account human, technological and organizational variables, which exist in a deployment environment. This model will be vital in driving early technology acceptance prediction and timely deployment of mitigation measures to deploy technological interventions successfully.
Preliminary Research on Adoption and Diffusion Model of SMEs E-Learning in Th...www.nbtc.go.th
Preliminary Research on Adoption
and Diffusion Model of SMEs
E-Learning in Thailand
Noppadol Tiamnara
Office of the National Broadcasting
and Telecommunications Commission, Thailand
The contribution of SMEs to
economic growth is widely recognized and
Thailand is one of the countries where
SMEs have always played a primary role in
digital economy environment. This paper is
a research-in-progress which aims to
construct a conceptual framework to
understand adoption and diffusion of
e-learning among small and medium-sized
enterprises (SMEs) in Thailand. Various
models of technology acceptance and
adoption are reviewed in this research to
analyze and apply for developing the
conceptual framework of the research. The
future work of the research is explained.
The results of the research in this paper will
provide recommendations to support SMEs
to utilize e-learning to foster the economic
impacts to the country. Analysis in this
research is based on quantitative approach.
Reference
http://www.ijcim.th.org/SpecialEditions/v23nSP2/02_25A_Preliminary.pdf
A Mediating Role of Knowledge Management System in the Relationship between I...Editor IJCATR
This paper as a qualitative paper attempts to review extant research in term of e-government performance, knowledge
management system, and information technology infrastructure. Nowadays, various countries are trying to improve their performance
by using information technology. In this regard, knowledge management can be considered an influential factor which plays a vital
role in the relationship between IT infrastructure and e-government performance. In the sequel, this paper proposes a framework which
can be applied for future study
A Mediating Role of Knowledge Management System in the Relationship between I...Editor IJCATR
This paper as a qualitative paper attempts to review extant research in term of e-government performance, knowledge
management system, and information technology infrastructure. Nowadays, various countries are trying to improve their performance
by using information technology. In this regard, knowledge management can be considered an influential factor which plays a vital
role in the relationship between IT infrastructure and e-government performance. In the sequel, this paper proposes a framework which
can be applied for future study.
How important is the social” insocial networking A perceivLizbethQuinonez813
How important is the “social” in
social networking? A perceived
value empirical investigation
Mihail Cocosila
Faculty of Business, Athabasca University, Athabasca, Canada, and
Andy Igonor
JR Shaw School of Business, Northern Alberta Institute of Technology,
Edmonton, Canada
Abstract
Purpose – The purpose of this paper is to report on a value-based empirical investigation of the
adoption of Twitter social networking application. The unprecedented popularity of social networking
applications in a short time period warrants exploring theory-based reasons of their success.
Design/methodology/approach – A cross-sectional survey-based study to elicit user views on
Twitter was conducted with participants recruited through the web site of a North-American university.
Findings – All facets of perceived value considered in the study (utilitarian, hedonic and social) had
a significant and relatively strong influence on consumer intent to use Twitter. Quite surprisingly for a
social networking application, though, the social value facet had comparatively the weakest contribution
in the use equation.
Research limitations/implications – User value perception might have been influenced by the
features of the actual social networking application under scrutiny (i.e. Twitter in this case).
Practical implications – To maximize the chances of success of new social networking applications,
developers and marketers of these media should focus on the hedonic and utilitarian sides of their
perceived value.
Social implications – Additional efforts are necessary to better understand the reasons and factors
leading to a comparatively lower social value perception of a social networking application, compared
to its hedonic and utilitarian values.
Originality/value – Overall, the study opens the door for investigating user perceptions on popular
social networking applications in an effort to understand the unparalleled success of these services in a
short time period.
Keywords Perceptions, Social media, Technology adoption, Social networking, Perceived value,
Twitter, User satisfaction
Paper type Research paper
1. Introduction
Social networking applications recorded an unprecedented success in just few of the
recent years. For instance, people in the USA have been spending 22 per cent of
the time they are online on social media sites while nine million users in Australia have
been spending almost nine hours per month, on average, using top social media
applications (Wikipedia, 2012). Despite these astonishing figures, the social networking
domain is still little understood. Definitions and borders of the social networking (also
called social media) phenomenon are still under debate. However, scholars seem to
agree that content generated by users is the key feature of any social networking
application. For instance, some conceptualization attempts define social media as “a
group of Internet-based applications that build on the ideological and technological
Informat ...
Similar to FACTORS AFFECTING KNOWLEDGE SHARING USING VIRTUAL PLATFORMS – A VALIDATION OF UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY (UTAUT) (20)
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
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source for obtaining much needed cooling water for a power
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and mass transfer coefficients and physical properties.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
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In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
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NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
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An Approach to Detecting Writing Styles Based on Clustering Techniques
Authors:
-Devkinandan Jagtap
-Shweta Ambekar
-Harshit Singh
-Nakul Sharma (Assistant Professor)
Institution:
VIIT Pune, India
Abstract:
This paper proposes a system to differentiate between human-generated and AI-generated texts using stylometric analysis. The system analyzes text files and classifies writing styles by employing various clustering algorithms, such as k-means, k-means++, hierarchical, and DBSCAN. The effectiveness of these algorithms is measured using silhouette scores. The system successfully identifies distinct writing styles within documents, demonstrating its potential for plagiarism detection.
Introduction:
Stylometry, the study of linguistic and structural features in texts, is used for tasks like plagiarism detection, genre separation, and author verification. This paper leverages stylometric analysis to identify different writing styles and improve plagiarism detection methods.
Methodology:
The system includes data collection, preprocessing, feature extraction, dimensional reduction, machine learning models for clustering, and performance comparison using silhouette scores. Feature extraction focuses on lexical features, vocabulary richness, and readability scores. The study uses a small dataset of texts from various authors and employs algorithms like k-means, k-means++, hierarchical clustering, and DBSCAN for clustering.
Results:
Experiments show that the system effectively identifies writing styles, with silhouette scores indicating reasonable to strong clustering when k=2. As the number of clusters increases, the silhouette scores decrease, indicating a drop in accuracy. K-means and k-means++ perform similarly, while hierarchical clustering is less optimized.
Conclusion and Future Work:
The system works well for distinguishing writing styles with two clusters but becomes less accurate as the number of clusters increases. Future research could focus on adding more parameters and optimizing the methodology to improve accuracy with higher cluster values. This system can enhance existing plagiarism detection tools, especially in academic settings.
RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Hori...
FACTORS AFFECTING KNOWLEDGE SHARING USING VIRTUAL PLATFORMS – A VALIDATION OF UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY (UTAUT)
1. International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 6, No. 2, June 2015
DOI : 10.5121/ijmpict.2015.6201 1
FACTORS AFFECTING KNOWLEDGE SHARING USING
VIRTUAL PLATFORMS – A VALIDATION OF UNIFIED
THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY
(UTAUT)
HairolAdenanKasim
Faculty of Information Management, MARA Technology University, Shah Alam,
Malaysia
ABSTRACT
Knowledge sharing is an important initiative in creating competitive advantage. As an important tool in the
successful implementation of Knowledge Management (KM), sharing knowledge is seen to be the most
important practice and resource which organization possesses. Various organizations have developed
strategies to ensure that KM is successful by embedding knowledge sharing practices in their routine work
processes. Nowadays, people have been using virtual platforms and web-based technologies, such as
Internet, Intranet, blogs, social media, and other online technology, for sharing knowledge and
information. The purpose of this study is to evaluate factors that can inculcate knowledge sharing behavior
using the virtual platforms. Therefore, this study will adopt Unified Theory of Acceptance and Use of
Technology (UTAUT) to investigate the key factors on this sharing behavior. The UTAUT model adopted in
this paper is empirically tested on a sample of 510respondents, and significant relationships among these
constructs were found.
KEYWORDS
Knowledge Sharing,Knowledge Management, Virtual platforms, Web-Based, UTAUT.
1. INTRODUCTION
Knowledge management (KM) has been widely initiated and practiced in various organizations
around the world. The KM initiative comprises a range of strategies and approaches to identify,
develop, acquire, transfer, share, and enable adoption of wisdom and experiences, by either
individuals or organizations. KM’s definition has been suggested by several academicians,
including Argote et al. (2000) and Huber (1991), who refer to KM as how organizations create,
retain, and share knowledge. Landline and Zollo (2007) have described KM as the methods of
developing, capturing, and adopting knowledge to enhance organizational performance. These
scholars have also asserted this initiative as a range of approaches and procedures exploited by
businesses to determine, represent, and transfer information, skills, experience, intellectual
property, and other forms of knowledge for innovation and learning across the organization. In
line with this argument, KM has been positioned as a business strategy that advances knowledge
as a critical resource and can integrate pieces of this knowledge across the organization as a
distinguishing feature for market success (Davenport &Prusak, 1998; Grant, 1996).Furthermore,
2. International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 6, No. 2, June 2015
2
KM also supports the development, classification, utilization, and sharing of knowledge to assist
situational understanding and decision making (Ismail & Raja Abdullah, 2011).
From the above definitions, the academicians have identified knowledge sharing as one of the
important pillars in KM. Grant (1996) has asserted that knowledge sharing as an important focus
in the KM field, where knowledge is seen as the most important resource an organization can
possess. Argote et al. (2000) have defined knowledge sharing as the process through which a unit,
group, or division is influenced by the experience or skill of another. These scholars also indicate
that the sharing of knowledge can be observed through variances in knowledge or performance of
recipient units. Recently, various organizations have developed strategies to ensure that KM is
successful by embedding knowledge sharing practices in their routine work processes. In fact, the
management and the stakeholders of the companies have realized the importance of sharing
practices for their staff and have embedded KM initiatives in their organizations.
An organization experiences several advantages and benefits to performing knowledge sharing
practices. Knowledge sharing is important because an individual’s knowledge will not have much
impact for the business unless it is available to other individuals (Nonaka& Takeuchi, 1995).
Knowledge sharing behavior has facilitated learning among employees and enable them to
resolve problems related to situations encountered by their colleagues in the past, allowing for
quicker responses to the business needs (Sher& Lee, 2004). Therefore, knowledge sharing
practices will allow product and technical innovation, especially for research organizations, and
this will lead to new product development to accommodate customer needs (Calantone et al.,
2002). The practices of learning and sharing knowledge among employees would improve
organizational capabilities and firm performance in terms of cost reduction, accomplishment of
new products, and growth of market share (Sher& Lee, 2004).
Nowadays, people have been using virtual platforms and web-based technologies, such as
Internet, Intranet, blogs, social media, and other online technology, for sharing knowledge and
information. These are the media through which knowledge or information are acquired,
transferred, shared, and disseminated using the recent network architecture and technology. In
relation to this, previous scholars have identified virtual mode as an effective platform for
knowledge sharing and collaboration. Dubé (2006) has defined the new mode: virtual community
platforms in which members use Information and Communication Technology (ICT) as the
primary media of interaction. Lin (2008) has proposed virtual communities as a cyberspace
community that has several internet-based forms of chat and collaboration, such as discussion
forums, chatting space, social media, or online bulletin boards. These online applications share
several common features, including collaboration elements that support members in different time
zones and areas. They create non-volatile data and record collaboration that is stored in text and
enhanced by multimedia additions.
Promoting knowledge sharing behavior is a challenge for most knowledge-based organizations.
Developing a behavior that values and practices knowledge sharing is an effort involving
attention to social, technological, organizational, and user attitude or behavior. Previous studies
have often assumed that implementing technology, such as virtual platforms, will be enough to
promote knowledge sharing. While this intention has been revealed as an ineffective approach,
frequently, most of companies’ knowledge resources are assigned to technology and not to other
factors that stimulate knowledge sharing (Davenport &Prusak, 1998). Based on previous studies,
several gaps or barriers have been acknowledged by recent scholars regarding knowledge sharing,
including functional silos, ineffective means of knowledge capture, inadequate technology,
3. International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
internal competition, and management gaps in the organization.
several common reasons given by individuals who are reluctant to share their knowledge, such as
pride syndrome because the individuals have pride to seek advice or assistance from their peers
and wanted to discover new ways for themselves (Davenport &Pru
Massey et al. (2002) have indicated other reasons, which include not realizing how useful
particular knowledge is to others because the individuals might have knowledge used in one
situation and do not realize that their colleagues
or time. Therefore, the main purpose of this study is to investigate factors inculcating knowledge
sharing behavior through the virtual platforms.
2. UTAUT AND RESEARCH
Unified Theory of Acceptance and Use of Technology (UTAUT) model is formulated by
Venkatesh and others to explain user intentions to use an information system and subsequent
usage behavior. In this theory, several independent variables are re
core of the original Theory of Reasoned Action (TRA)
(TAM) in predicting the technology acceptance (Venkatesh et al., 2003). In this model,
Venkatesh and Bala (2008) have proposed 12 independent variables, bu
original TAM model, including Perceived Usefulness (PU) and Perceived Ease
This model could provide a significantly higher percentage of technology innovation success and
proclaimed to be up to 70% accurate at pred
al., 2010; Venkatesh et al., 2003).
Figure 1: Unified Theory of Acceptance and Use of Technology (UTAUT) model
To date, Unified Theory of Acceptance and Use of Technology (UTAUT) model has served an
applied to various technologies-
contexts and settings. In relation to this, Venkatesh et al. (2012) have asserted that several
extensions and integrations of the entire model or part of the mo
its generalizability, which include extensions that analyzed UTAUT in new technologies setting,
new user populations and new cultural environment. Moreover, the extensions also include new
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 6, No. 2, June 2015
internal competition, and management gaps in the organization. Prior researchers have propose
several common reasons given by individuals who are reluctant to share their knowledge, such as
pride syndrome because the individuals have pride to seek advice or assistance from their peers
and wanted to discover new ways for themselves (Davenport &Prusak, 1998). In addition,
Massey et al. (2002) have indicated other reasons, which include not realizing how useful
particular knowledge is to others because the individuals might have knowledge used in one
situation and do not realize that their colleagues might face a similar situation at a different venue
Therefore, the main purpose of this study is to investigate factors inculcating knowledge
sharing behavior through the virtual platforms.
ESEARCH MODEL
Unified Theory of Acceptance and Use of Technology (UTAUT) model is formulated by
Venkatesh and others to explain user intentions to use an information system and subsequent
usage behavior. In this theory, several independent variables are re-classified, but retained the
core of the original Theory of Reasoned Action (TRA) and Technology Acceptance Model
in predicting the technology acceptance (Venkatesh et al., 2003). In this model,
Venkatesh and Bala (2008) have proposed 12 independent variables, but retained the core of the
original TAM model, including Perceived Usefulness (PU) and Perceived Ease-of-Use (PEOU).
This model could provide a significantly higher percentage of technology innovation success and
proclaimed to be up to 70% accurate at predicting user acceptance of ICT innovations (Moran et
al., 2010; Venkatesh et al., 2003).
Figure 1: Unified Theory of Acceptance and Use of Technology (UTAUT) model
To date, Unified Theory of Acceptance and Use of Technology (UTAUT) model has served an
-related studies in both organizational and non-organizational
contexts and settings. In relation to this, Venkatesh et al. (2012) have asserted that several
extensions and integrations of the entire model or part of the model has been developed to reclaim
its generalizability, which include extensions that analyzed UTAUT in new technologies setting,
new user populations and new cultural environment. Moreover, the extensions also include new
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
3
Prior researchers have proposed
several common reasons given by individuals who are reluctant to share their knowledge, such as
pride syndrome because the individuals have pride to seek advice or assistance from their peers
sak, 1998). In addition,
Massey et al. (2002) have indicated other reasons, which include not realizing how useful
particular knowledge is to others because the individuals might have knowledge used in one
might face a similar situation at a different venue
Therefore, the main purpose of this study is to investigate factors inculcating knowledge
Unified Theory of Acceptance and Use of Technology (UTAUT) model is formulated by
Venkatesh and others to explain user intentions to use an information system and subsequent
ut retained the
and Technology Acceptance Model
in predicting the technology acceptance (Venkatesh et al., 2003). In this model,
t retained the core of the
Use (PEOU).
This model could provide a significantly higher percentage of technology innovation success and
icting user acceptance of ICT innovations (Moran et
Figure 1: Unified Theory of Acceptance and Use of Technology (UTAUT) model
To date, Unified Theory of Acceptance and Use of Technology (UTAUT) model has served and
organizational
contexts and settings. In relation to this, Venkatesh et al. (2012) have asserted that several
del has been developed to reclaim
its generalizability, which include extensions that analyzed UTAUT in new technologies setting,
new user populations and new cultural environment. Moreover, the extensions also include new
4. International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 6, No. 2, June 2015
4
and additional constructs to expand the scope of the independent variables and inclusion of
dependent predictors of the model variables (Venkatesh et al., 2012). Hence, the extensions and
replications of the model have worthwhile and relevant in expanding the understanding of
technology acceptance and the theoretical boundaries of the UTAUT model. Nevertheless,
although this model provides a better understanding for technology acceptance and adoption, the
initial UTAUT model only focused on large organizations (Marchewka et al., 2007).
Additionally, these experts also indicate that the scales used in this model are still new, and the
relevancy of these scales needs to be further tested and verified.
UTAUT model is developed through review and consolidation of constructs of eight models that
earlier research has employed to explain IS usage behavior (Venkatesh et al., 2003, 2012). The
eight models are Theory of Reasoned Action (TRA), Technology Acceptance Model (TAM),
Theory of Planned Behavior (TPB), Motivational Model, Combined Theory of Planned Behavior
and Technology Acceptance Model, Model of Personal Computer Utilization, Innovation
Diffusion Theory and Social Cognitive Theory.
In general, UTAT theory has four main variables based on the consolidation of the constructs of
eight models that earlier research has employed, as follows:
a. Performance Expectancy
This variable refers to a level that an individual believes that using the system can improve
performance (Venkatesh& Davis 1996; Venkatesh et al., 2003). These scholars have arranged
five additional dimensions from previous studies, i.e. Perceived usefulness (Technology
acceptance model), external motivation (Motivational Model), work correlation (Model of
Personal Computer Utilization), relative advantage (Innovation Diffusion Theory) and
expectancy to the achievement (Social cognitive theory). From these dimensions, the author
also suggested that this variable referred as the ability to obtain significant rewards after
using the system.
b. Effort Expectancy
This component refers to the perceived easiness that an individual thinks of when using the
system (Venkatesh and Davis 1996). In addition, these experts have identified three sub-
dimensions of the previous research, which include consciousness of easy to use (Technology
Acceptance Model), systematic complexity (Model of Personal Computer Utilization) and
operating simplicity (Innovation Diffusion Theory). These authors have suggested that
whether the design of the system, such as virtual platforms can allow the user to navigate it
easily or not is one of the key success factors of accepting the technology.
c. Social Influence
This variable refers to the level that individual senses that the person who is important to
him/her thinks that he/she should use the new system (Venkatesh& Davis, 1996). With this
component, Venkatesh et al. (2003) has categorized three sub-dimensions from the previous
scholar - Subjective Norm (Theory of Reasoned Action, Technology Acceptance Model and
Theory of Planned Behavior), Public Image (Innovation Diffusion Theory) and Social Factor
(Model of Personal Computer Utilization). Furthermore, the effect of social influence
depends on environmental settings, which include compulsory or voluntary, and in another
context, either in individual or organizational settings (Karahanna& Straub, 1999,
Hartwick&Barki, 1994).
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d. Facilitating Conditions
This variable can be described as the level of supporting that an individual received from the
organizational and technical relevant equipment toward system use, such as training, manual,
hands-on and others (Venkatesh& Davis 1996). These scholars have categorized three sub-
dimensions from previous models - Control of conscious behavior (Technology Acceptance
Model and Theory of Planned Behavior), Promoting condition (Model of Personal Computer
Utilization) and Compatibility (Innovation Diffusion Theory).
Other factors, such as gender, age, experience and voluntaries of use are issued to moderate and
strengthen the relationship of the four key variables on usage intention and behavior. Venkatesh
et al. (2003) have asserted that the purpose of these moderating variables is to emphasize that
there is a difference between personal acceptance and strategy of using the system under different
environment and situation. These experts also suggest that the purpose of this model is to weigh
the introduction of the new technology, such as virtual platforms in the organization and predict
and explain the user’s behavior of accepting this new system. On that note, this research uses the
above theories as the foundation of the proposed hypotheses of this study. Eventually, the
research hypotheses are shown below. All the constructs and hypotheses in the research model
are adopted and adapted based on UTAUT model, but have been revised to suit the scopes and
objectives of this study.
H1: User’s performance expectancy has a positive effect on knowledge sharing behavior
H2: User’s effort expectancy has a positive effect on knowledge sharing behavior
H3: User’s social influence has a positive effect on knowledge sharing behavior
H4: User’s facilitating conditions have a positive effect on knowledge sharing behavior
H5a: Age has a significant difference towards knowledge sharing behavior.
H5b: Gender has a significant difference towards knowledge sharing behavior.
H5c: Experience has a significant difference towards knowledge sharing behavior.
3. RESEARCH METHODOLOGY
This study will adapt the Quantitative method for the collection of data from the selected
respondents. Therefore, this research will adapt the Post Positivist paradigm that will study the
behavior and actions of human. As define by Creswell (2009), this research paradigmholds a
philosophy in which causes probably determine effects and outcomes. Thus, the problems studied
using this approach will reflect requirement to identify and asses the causes that influence
outcomes. Post Positivist paradigm also emphasizes meaning of new knowledge to support social
movements that aspire to change the environment and contribute towards social justice (Ryan,
2006). This research will use Quantitative approach for the collection and analysis of data by
conducting surveys and questionnaires from related participants in the Research and
Development (R&D) organization. This method will focus on related variables or factors with the
purpose of formulating a theory or conceptual framework at the conclusion of this research
(Sekaran, 2006). A survey provides numeric report of attitudes or behaviors through the
exploration of a sample of population with the intention of generalizing the hypotheses of the
study (Creswell, 2009).
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3.1 Population and Sampling
The participant of this study is the respondents from five R&D organizations which could assist
in generating meaningful information and explanation to fulfill the objectives of this research.
The list of respondents obtained from the respective research organizations is the basic population
and Stratified Random Sampling technique will be used. This sampling design will provide the
most efficient technique when differentiated information is needed regarding various strata within
the population. According to Sekaran (2006), this sampling technique will involves a process of
segregation, followed by random selection of subjects from each stratum. The population of
participants will be divided into mutually exclusive groups that are relevant, appropriate and
meaningful in the context of this study.
This research has distributed hardcopy of the survey to 150 respondents and uploaded the
formatted electronic version of the survey to 360 participants. The hardcopy and link of this
website were distributed to a total of 510 participants, of which 220 responded to the survey.
Table 1: Total Respondents
No R&D Organization Total Population Total Respond Percentage (%)
1 Petronas 130 60 46.1
2 TenagaNasionalBerhad 80 34 42.5
3 SIRIM 100 39 39
4 Nuclear Malaysia 150 68 45.3
5 Green Technology Malaysia 50 19 38
TOTAL 510 220 43.1
Based on Table 1, the target respondents are drawn from total population of 510 participants from
five organizations and 220 have responded to the circulated survey. The total respond or
questionnaire returns for this research was on target since more than 40 percent (%) of the
targeted respondent or more than 200 users had given the feedback on the questionnaires that had
been circulated. The response rate of more than 40% are also consistent and equal to sample size
decision model that is proposed by Krejcie and Morgan (1970) and Sekaran (2006).
4. DATA ANALYSIS
4.1 Descriptive Statistical Analysis
The descriptive analysis involved all constructs or variables in this research. This analysis had
determined the mean score and standard deviation value for all constructs. This analysis had been
split into four parts, to justify the relevant factors that can inculcate knowledge sharing behavior:
a. Performance Expectancy Factor
As described in Table 2, majority of respondents (mean = 4.09) believe virtual platforms enable
them to retrieve knowledge needed for problem solving, decision making and learning. On the
other hand, the use of virtual platforms to promote innovativeness and creativity has the lowest
score (mean = 3.99) in sharing knowledge through the virtual environment. The standard
deviations also show consistent variation or dispersion.
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Table 2: Performance Expectancy Factor
b. Effort Expectancy Factor
As shown in Table 3, majority of respondents believe virtual platforms are easy to use and this
item has the highest score (mean = 4.03) for Effort Expectancy Factor. On the contrary, they also
believe not everyone can use the virtual platforms without any difficulties and this item has the
lowest score (mean = 3.58) in promoting the virtual knowledge sharing behavior. The standard
deviations also show consistent variation or dispersion.
Table 3: Effort Expectancy Factor
c. Social Influence Factor
As illustrated in Table 4, the respondents believe all organization should encourage the use of the
virtual platforms for their organizations to promote the virtual knowledge sharing behavior (mean
= 4.06). On the contrary, they also believe the Senior Management hasn’t encouraged them to use
the virtual platforms and this item has the lowest score (mean = 3.65). The standard deviations
also show consistent variation or dispersion.
Table 4: Social Influence Factor
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d. Facilitating Condition Factor
Based on Table 5, most of the respondents believe all organization should give full support to use
the virtual platforms to promote the knowledge sharing behavior (mean = 4.09). However, the
participants also believe users’ guides (manuals) related to virtual platforms are still insufficient
to promote the virtual knowledge sharing behavior (mean = 3.38). The standard deviations also
show consistent variation or dispersion.
Table 5: Facilitating Condition Factor
4.2 Multivariate Analysis
Multivariate analysis was the method for testing the research’s hypotheses that includes
Confirmatory Factor Analysis (CFA), Structural Equation Modeling (SEM) and Multivariate
Analysis of Variance (MANOVA). CFA and SEM are recognized to provide rigorous analysis of
model power in relation to construct and content validity. CFA is a multivariate statistical
procedure in research design stages that are used to test how well the measured variables
represent the number of constructs. According to Raykov and Marcoulides (2008), the main
objective in CFA lies in examining the pattern of relations among the factors, as well as those
between them and the observed variables. Afterwards, after the measurement model has been
analyzed using SEM, the next step is to evaluate the moderator variables (age, gender and
experience) using Multivariate Analysis of Variance (MANOVA). This technique can measure
the differences for two or more dependent variables based on a set of categorical or non-metric
variables acting as independent variables (Hair et al., 2010).
4.2.1 Confirmatory Factor Analysis (CFA)
a. Performance Expectancy Factor
CFA for the independent variable – Performance Expectancy is performed to analyze how well
the measured variables represent the number of constructs.A CFA is conducted for this factor to
determine whether the indicators measured the constructs and are assigned adequately.
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Table 6: Performance Expectancy Indexes
Fit Indices Recommended Level** Output Value Summary
P value (X2
) Not significant p>0.05 .000 Not Accepted
X2
/df <3.0 75.8 Not Accepted
GFI ≥0.80 .89 Accepted
AGFI ≥0.80 .74 Not Accepted
NFI ≥0.80 .89 Accepted
CFI ≥0.90 .90 Accepted
RMSEA <0.10 .19 Not Accepted
**Source: Medsker et al. (1994), Doll et al. (1994), Bentler et al. (1995) and Hair et al. (2010)
Table 6 summarizes the results of these tests. Empirical evidence in CFA is generally assessed
using criteria, such as the Comparative Fit Index (CFI), Normed Fit Index (NFI), Goodness-of-fit
index (GFI), Adjusted Goodness-of-fit index (AGFI) and Root Mean-Squared Error
Approximation (RMSEA). As indicated by Bentler (1995), a CFI value greater than 0.90
indicates an acceptable fit to the data. An analysis of the Table 6 for this study reveals that the
CFI value (0.901) is acceptable, which suggests a good model fits. As for convergent validity,
NFI values of 0.80 or greater indicate an adequate model fit (Bentler, 1995). Thus, the NFI value
(0.89) shown in Table 6 indicates an adequate model fit for this study. In addition, a GFI value
that exceeds 0.80 indicates a good model (Doll et al., 1994). As a result, the GFI value (0.89)
revealed in Table 6 indicates a good model for this study. According to Doll et al. (1994), AGFI
values of 0.80 or greater indicates an adequate model fit. On the contrary, the AGFI for this study
is below the threshold (0.74) and not indicates a good model for this study. As for RMSEA, a
value of about 0.10 or less would indicate a close-fit of the model in relation to the degrees of
freedom (Hair et al., 2010). On the other hand, the RMSEA for this factor is above the threshold
(0.19) and not indicates a good model for this study.
Furthermore, to ensure that the measurement model fit and suitable for this study, Performance
Expectancy indexes are examined. Hair et al. (2010) have suggested that if three or four indexes
are accepted, this measurement model is recommended for further analysis. Therefore, as
described in summary of Table 6, the model has three accepted indexes that indicate Performance
Expectancy measurement model is suitable for this study.
b. Effort Expectancy
CFA for the second independent variable (Effort Expectancy) is performed to analyze how well
the measured variables represent the number of constructs.
Table 7: Indexes Effort Expectancy
Fit Indices Recommended Level** Output
Value
Summary
X2
Not significant p>0.05 .000 Not Accepted
X2
/df <3.0 0.26 Accepted
GFI ≥0.80 0.99 Accepted
AGFI ≥0.80 0.99 Accepted
NFI ≥0.80 0.99 Accepted
CFI ≥0.90 1.00 Accepted
RMSEA <0.10 0.00 Accepted
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**Source: Medsker et al. (1994), Doll et al. (1994), Bentler et al. (1995) and Hair et al. (2010)
A CFA is conducted for these constructs to determine whether the indicators measured the
constructs and are assigned adequately. As revealed in Table 7, CFI value (1.000),NFI value
(0.89), GFI value (0.99), AGFI value (0.99) and RMSEA value (0.00) indicates adequate model
fit and are acceptable for this study. In addition, to ensure that the measurement model fit and
suitable for this study, the relevant indexes are examined. Hair et al. (2010) have suggested that if
three or four indexes are accepted, this measurement model is recommended for further analysis.
Thus, as described in summary for Table 7, the model has six accepted indexes that indicate
Effort Expectancy measurement model is suitable for this study.
c. Social Influence
CFA for the third independent variable – Social Influence is performed to analyze how well the
measured variables represent the number of constructs.
Table 8: Indexes Social Influence
Fit Indices Recommended Level** Output Value Summary
X2
Not significant p>0.05 .000 Not Accepted
X2
/df <3.0 8.57 Not Accepted
GFI ≥0.80 .96 Accepted
AGFI ≥0.80 .79 Not Accepted
NFI ≥0.80 .96 Accepted
CFI ≥0.90 .97 Accepted
RMSEA <0.10 .19 Not Accepted
**Source: Medsker et al. (1994), Doll et al. (1994), Bentler et al. (1995) and Hair et al. (2010)
A CFA is conducted for these constructs to determine whether the indicators measured the
constructs and are assigned adequately. As described in Table 8, CFI value (0.97), NFI value
(0.96), and GFI value (0.96) indicates adequate model fit and are acceptable for this study. On the
contrary, AGFI value (0.79) and RMSEA value (0.19) are below the recommended level and not
adequate as model fit.Furthermore, to ensure that the measurement model fit and suitable for this
study, Social Influence indexes are examined. Hair et al. (2010) have suggested that if three or
four indexes are accepted, this measurement model is recommended for further analysis.
Therefore, as described in summary of Table 8, the model has three accepted indexes that indicate
Social Influence measurement model is still suitable for this study.
d. Facilitating Condition
CFA for the fourth independent variable, Facilitating Condition is performed to analyze how well
the measured variables represent the number of constructs.
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Table 9: Indexes Facilitating Condition
Fit Indices Recommended Level** Output Value Summary
X2
Not significant p>0.05 .000 Not Accepted
X2
/df <3.0 8.76 Not Accepted
GFI ≥0.80 .96 Accepted
AGFI ≥0.80 .81 Accepted
NFI ≥0.80 .94 Accepted
CFI ≥0.90 .95 Accepted
RMSEA <0.10 .19 Not Accepted
**Source: Medsker et al. (1994), Doll et al. (1994), Bentler et al. (1995) and Hair et al. (2010)
A CFA is conducted for these constructs to determine whether the indicators measured the
constructs and are assigned adequately. Based on Table 9, CFI value (0.95), NFI value (0.94),
GFI value (0.96), and AGFI value (0.81) indicates adequate model fit and are acceptable for this
study. On the other hand, RMSEA value (0.19) is above the threshold and not indicates a good
model for this study.In addition, to ensure that the measurement model fit and suitable for this
study, Facilitating Condition indexes are examined. Hair et al. (2010) have suggested that if three
or four indexes are accepted, this measurement model is recommended for further analysis.
Therefore, as described in Table 9, the model has four accepted indexes that indicate Facilitating
Condition measurement model is suitable for this study.
e. Knowledge Sharing Behavior
CFA for the dependent variable – Knowledge Sharing Behavior is performed to analyze how well
the measured variables represent the number of constructs.
Table 10: Indexes Knowledge Sharing Behavior
Fit Indices Recommended Level** Output Value Summary
X2
Not significant p>0.05 .000 Not Accepted
X2
/df <3.0 .00 Accepted
GFI ≥0.80 1.00 Accepted
AGFI ≥0.80 .00 Not Accepted
NFI ≥0.80 1.00 Accepted
CFI ≥0.90 1.00 Accepted
RMSEA <0.10 .36 Not Accepted
**Source: Medsker et al. (1994), Doll et al. (1994), Bentler et al. (1995) and Hair et al. (2010)
A CFA is conducted for these constructs to determine whether the indicators measured the
constructs and are assigned adequately. As revealed in Table 10, CFI value (1.00), NFI value
(1.00), and GFI value (1.00) indicates adequate model fit and are acceptable for this study. On the
contrary, AGFI value (0.00) and RMSEA value (0.36) are below the recommended level and not
adequate as model fit. Furthermore, to ensure that the measurement model fit and suitable for this
study, Knowledge Sharing Behavior indexes are examined. Hair et al. (2010) have suggested that
if three or four indexes are accepted, this measurement model is recommended for further
analysis. Therefore, as described in summary of Table 10, the model has four accepted indexes
that indicate Knowledge Sharing behavior measurement model is reliable and valid for this study.
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4.3 Hypotheses Testing
After the measurement model for all variables (factors) are analyzed using CFA and consider as
significant, the next step is to analyze the model using Structural Equation Modeling (SEM).
SEM is conducted to examine the possibility of achieving goodness-of-fit of the proposed model
using Analysis of Moment Structures (AMOS) statistical software.
Maximum Likelihood assumes that the underlying variables are normally distributed. For this
study, the maximum likelihood estimates result as describe in Table 11 shows that the
standardized residuals are technically fit index, and provide information about how closely the
estimated matrix corresponds to the observed matrix and described how well the data fits the
model.
Table 11: Maximum Likelihood Estimates Result
Estimate S.E. P
Knowledge Sharing Behavior <-- Performance
Expectancy
3.417 3.475
.000 **
Knowledge Sharing Behavior <-- Effort Expectancy 1.743 1.955 .00 *
Knowledge Sharing Behavior <-- Social Influence .537 1.094 .000 **
Knowledge Sharing Behavior <-- Facilitating Condition .629 1.172 .000 **
Note: Significant levels: * p < .01, ** p < .001
To determine the minimum loading necessary to include an item in its respective constructs, the
general criteria is accepted items with loading of 0.50 or greater (Hair et al., 2010). As shown in
Table 11, this model confirmed that Performance Expectancy and Effort Expectancy constructs
have a significant direct relationship with Knowledge Sharing Behavior (with path coefficient of
3.42 and 1.74), and justified that Social Influence (with path coefficient of 0.54) and Facilitating
Condition (with path coefficient of 0.63) have a positive relationship with Knowledge Sharing
Behavior.
Table 12: Indexes Knowledge Sharing Behavior
Fit Indices Recommended Level** Output Value Summary
X2
Not significant p>0.05 0.00 Not Accepted
X2
/df <3.0 2.89 Accepted
GFI ≥0.80 0.80 Accepted
AGFI ≥0.80 0.70 Not Accepted
NFI ≥0.80 0.74 Not Accepted
CFI ≥0.90 0.81 Not Accepted
RMSEA <0.10 0.09 Accepted
**Source: Medsker et al. (1994), Doll et al. (1994), Bentler et al. (1995) and Hair et al. (2010)
Based on Table 12, The GFI value (0.80) proves to be a good-fit-model (Hair et al., 2010). One
important index for SEM is the RMSEA (Root Mean-Squared Error Approximation), which is an
estimate of fit of the model relative to a saturated model in the population. For RMSEA, a value
of about 0.10 or less would indicate a close-fit of the model in relation to the degrees of freedom
(Hair et al., 2010). On that note, the RMSEA value (0.09) for this study indicates a significant
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close-fit of model. In addition, to ensure that the measurement model fit and suitable for this
study, Knowledge Sharing Behavior indexes as described in Table 12 are examined. Hair et al.
(2010) have suggested that if three or four indexes are accepted, this measurement model is
recommended and significant. Therefore, as described in summary of Table 12, the model has
three out of seven accepted indexes that indicate Knowledge Sharing behavior measurement
model is suitable for empirical data of this study.
The value of SEM lies in its ability in showing both the direct and indirect effects between the
variables. In light of this, this analysis appears to indicate that Performance Expectancy, Effort
Expectancy, Social Influence, and Facilitating Condition factors have direct influences for
Knowledge Sharing Behavior. As a conclusion, the overall analysis of SEM is significant to
support the hypotheses of this research.
4.4 Multivariate Analysis of Variance (MANOVA)
Once the measurement model has been analyzed using SEM, the next step is to analyze the
moderator variables. These demographic factors will act as moderators that modify the original
relationship between the independent and dependent variables. As recommended by previous
scholars, the key outputs of MANOVA analysis would be interpreted using the selected criteria,
as follows
i. Box’s Test of Equality of Covariance Matrices
This analysis indicates whether research data violates the assumption of homogeneity of
variance-covariance matrices (Pallant, 2010). If the Significant (Sig.)value is largerthan
0.001, then analysis have not violated the assumption (Tabachnick&Fidell, 2012)
ii. Levene’s Test of Equality of Error Variances
This analysis indicates whether data has violated the assumption of equality of variance for
that variable or not. In the Sig. Column, this test will look for any values that are lessthan
0.05 (Pallant, 2010).
iii. Multivariate tests
Several multivariate statistics is available in MANOVA programs to test the significance of
main effects and interactions, such as Wilks’ Lambda, Hotelling’s Trace and Pillai’s Trace.
iv. Wilks’ Lambda
This analysis indicates the value of Wilks’ Lambda and its associated significance level. If
the significance level is less than 0.05, then it can conclude that there is a difference among
the groups (Pallant, 2010).
v. Tests of Between-Subjects Effects
If the analysis has obtained a significant result on the multivariate test of significance, this
provides the justification and permission to investigate further in relation to each of the
dependent variables. The most common way of doing this analysis is to apply a Bonferroni
adjustment with the significance level that is less than 0.05 (Tabachnick&Fidell, 2012).
a. Age Differences and Knowledge Sharing Behavior
A one-way between-groups multivariate analysis of variance is performed to investigate age
differences for knowledge sharing behavior. As described in Table 13, the result summary
indicates there is insignificant difference between ages on the combined dependent variables.
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Table 13: MANOVA for Age Differences
Fit Indices Recommended Level** Output Value Summary
Equality of Covariance
Matrices
Sig.value > 0.001 0.00 Not Significant
Levene’s Test Sig. value < 0.05 0.08 Not Significant
Wilks’ Lambda Sig. value < 0.05 0.965 Not Significant
Between-subjects effects Sig. value < 0.05 0.38 Not Significant
**Source: Pallant (2010), Tabachnick&Fidell (2012) and Cohen (1988)
b. Gender Differences and Knowledge Sharing Behavior
MANOVA analysis for the second demographic or moderator variable – Gender is performed to
analyze how well this variable influences the strength of the relationship with the dependent
variable – Knowledge Sharing Behavior.
Table 14: MANOVA for Gender Differences
Fit Indices Recommended Level** Output Value Summary
Equality of Covariance
Matrices
Sig.value > 0.001 0.214 Significant
Levene’s Test Sig. value < 0.05 0.001 Significant
Wilks’ Lambda Sig. value < 0.05 0.022 Significant
Between-subjects effects Sig. value < 0.05 0.023 Significant
**Source: Pallant (2010), Tabachnick&Fidell (2012) and Cohen (1988)
As shown in Table 14, there is a significant difference between gender on the combined
dependent variables: F (4, 196) = 1.45, p = .022; Wilks’ Lambda = .98; partial eta squared = .00.
When the results for the dependent variables are considered separately, the only difference to
reach statistical significance is job function: F (1, 199) = 5.29, p = .023, partial eta squared = .05.
An inspection of the mean scores indicated that females reported slightly higher levels of
knowledge sharing behavior (Mean = 3.81, Std. Deviation = .085) than males (Mean = 3.49, Std.
Deviation = 1.09).
This finding supports that gender has a positive effect on the relationship between promoting
factor variables with knowledge sharing behavior (β = 1.45, p < .05). In addition, the mean scores
for this study show that females reported slightly higher levels of knowledge sharing behavior for
their job function compared to males. This finding has suggested that, compared to men, women
are more people-oriented and concerned about their knowledge sharing behaviors that are related
to job function.
c. Experience Differences and Knowledge Sharing Behavior
MANOVA analysis for the last demographic variable – Experience is performed to analyze how
well this variable influences the strength of the relationship with the dependent variable –
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Knowledge sharing Behavior. As described in Table 15, the result summary indicates there is
insignificant difference between experiences on the combined dependent variables.
Table 15:MANOVA for Experience Differences
Fit Indices Recommended Level** Output Value Summary
Equality of Covariance
Matrices
Sig.value > 0.001 0.002 Significant
Levene’s Test Sig. value < 0.05 0.63 Not Significant
Wilks’ Lambda Sig. value < 0.05 0.36 Not Significant
Between-subjects effects Sig. value < 0.05 0.13 Not Significant
**Source: Pallant (2010), Tabachnick&Fidell (2012) and Cohen (1988)
5. CONCLUSION
This research has empirically validated the UTAUT model in the context of knowledge sharing
behavior through the virtual platforms. The findings of this study offer several significance
implications for the research on antecedents of knowledge sharing behavior. Consistent with
UTAUT,all independent variables — performance expectancy, effort expectancy, social
influence, and facilitating condition — have indicated a positive association with virtual
knowledge sharing behavior. On that note, this study has suggested that these factors to promote
knowledge sharing behavior through virtual platforms for the respective research organizations.
Based on the analysis of this study, the summary of each factors and their ranking in inculcating
knowledge sharing behavior is described in Table 16.
Table 16: Factors for Knowledge Sharing Behavior
No Factors Mean Percentage
1. Performance Expectancy 24.27 80.9
2. Effort Expectancy 22.97 76.6
3. Social Influence 22.67 75.6
4. Facilitating Condition 21.84 72.8
As illustrated in Table 16, the most prominent scores for this study derived from the performance
expectancy factor (80.9%), referring to the abilityto obtain significant rewards after using the
system (Vankatesh et al., 2003). Thus, performance expectancy is shown to be the strongest
predictor or motivator of virtual knowledge sharing behavior. Therefore, it is believed that an
individual with high performance expectancy is more likely to adopt this behavior than is an
individual with lower performance expectancy. The second important factor raised in this study is
the effort expectancy factor (76.6%), which described the users’ acceptance of the new system,
such as virtual platforms are determined by easy-to-use elements and whether the system’s user
interface is developed based on user needs and justification.
The third factor that can promote virtual knowledge sharing behavior is social influence (75.6%).
Previous research has pointed out that the social and individual context is crucial for work group
success. The social factor also has a significant influence toward senior staff in sharing
knowledge due to the recognition or motivational factor that influences the positive culture in the
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organization. For instance, a person might hold the belief that knowledge sharing is good for the
organization, that culture makes organization look strong, or the negative perception that a
sharing culture will burden their time, and they are uncomfortable to share knowledge. The last
factor that is identified by this study is facilitating conditions (72.8%), which refer to the ability
of users to operate and utilize the system and the technology support that is provided by the
environment, such as training, helpdesk system, manuals, and documentation. Because this factor
has the lowest score, this finding suggests that probably most of the respondents are technology-
savvy or already familiar with the virtual environment and platforms. Hence, facilitating
conditions that include technology assistance or support are the lowest antecedent for the
respondents regarding knowledge sharing behavior through the virtual mode.
In addition to the determinants of knowledge sharing behavior, this research further investigates
the moderating effect (age, gender and experience) have on the relationships between the
determinants factors with the sharing behavior. The main purpose for examining moderating
variables is to understand the inconsistencies of results across research. Moderating variables can
neutralize, enhance, or lessen the effect of a relationship (Howell, Dorfman, & Kerr, 1986) and
they can unveil the limitations of explanatory powers (Sun & Zhang, 2006). Eventually, these
findings have proposed the effects of knowledge sharing behavior through virtual platforms are
moderated by gender only. The mean scores for this study show that females reported slightly
higher levels of knowledge sharing behavior for their job function compared to males. This
finding has suggested that, compared to men, women are more people-oriented and concerned
about their sharing behaviors that are related to job function. The women probably felt more
conscious of task-oriented factors, such as team collaboration and interaction, being important for
knowledge sharing behavior.
On the contrary, other moderating factors (age and experience) show an invalid relationship as
the moderating variables and indicate insignificant differences with virtual knowledge sharing
behavior. For instance, this result has proposed no differences between younger or junior
respondents with elder or senior respondents in knowledge sharing practices. A possible
justification for these findings is that the technical features used in virtual platforms are quite
simple and low in cost to be adopted; thus, anyone can familiarize themselves with the system
features and tools. In fact, the technical features of the virtual platforms, which includes instant
messaging, chat rooms, online forums, blogs and online databases, are simple to use and also
available everywhere through the widespread use of social media and common web-based
technologies. As indicated by Adams et al. (1992) and Davis et al. (1989), ease-of-use for any
technology or system might be a significant determinant of behavioral intention during the early
stages of usage, and this attribute could have a greater impact in applications that are more
sophisticated and complex.
6. IMPLICATION AND LIMITATIONS OF THE STUDY
Eventually, based on UTAUT model, this research has investigated the antecedents of knowledge
sharing behavior through the virtual platforms. This research hasalso focus on identifying gaps
that would assist in effectively guide government and private sectors in Malaysia, to be more
competitive and innovative. This research has both academic and practical implications, such as
identifying knowledge sharing holistic initiatives asa vehiclefor success in creating valuable
organizational development practices. Furthermore, this study has contributed to the body of
knowledge especially in the knowledge sharing field by proposing a suitable theoretical or
conceptual model (using UTAUT model) for knowledge sharing behavior. This research also
17. International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 6, No. 2, June 2015
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contributes to knowledge sharing literature because it provides a potential measurement of the
organizational, technological, social, and individual behavior factors that are likely to contribute
to knowledge sharing success and acceptance based on the literature review.
The analysis approach used in this research suits the formative and exploratory subjects addressed
in the objective of this study. However, several limitations are worth mentioning in this study. For
instance, the use of 510 participants from five Research and Development (R&D) organizations
in Government-Linked Companies (GLCs) are only meant for sampling and does not described
the whole population of research organization in Malaysia. Furthermore, the sizes of samples
from the five GLCs agencies in one country (Malaysia) limited the possibility of this research
generalization claim and maybe these participants would perceive the knowledge platform
utilization differently from other respondents in different sectors or in other countries. Although
there are several limitations, but this research has successfully executed and achieved the
proposed objectives.
As recommendation for future research, it would be necessary to conduct study with similar
objectives within companies of different sectors, develop more respondents and eventually use
other methods or models for data collection and sampling. In addition, it is recommended that this
research is repeated in other contexts or in different countries and other kinds of knowledge
platform which could complement other recent knowledge sharing studies that are related to the
objective of this research.
ACKNOWLEDGEMENTS
This study was supported by Faculty of Information Management, UniversitiTeknologi MARA,
Shah Alam, Malaysia. Also warm appreciation to respondents from Petronas,
TenagaNasionalBerhad, Nuclear Malaysia, SIRIM and Green Tech Malaysia for their assistance
and cooperation in providing the data and information.
REFERENCES
[1] Argote, L., Ingram, P., Levin, J. M., and Moreland, R. L. (2000). Organizational learning: Creating,
retaining, and transferring knowledge. Boston, MA: Kluwer Academic Publishers.
[2] Bentler, P. (1995). EQS structural equation program manual. Encino, CA: Multivariate Software
Inc
[3] Creswell, J. W. (2009). Research design: Qualitative, Quantitative, And Mixed Methods
Approaches. Sage Publications, Incorporated.
[4] Davenport, T.H. and L. Prusak (1998). Working Knowledge: How Organizations Manage What They
Know. Harvard Business School Press, Boston, MA.
[5] Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use and User Acceptance of
Information Technologies. MIS Quarterly 13 (3), 319–340.
[6] Davis, F. D., Bagozzi, R. P. and Warshaw, P. R. (1992). Extrinsic and instrinsic motivation to use
computers in the workplace. Journal of Applied Social Psychology, 22,1111-1132
[7] Doll, W.J., Xia, W. and Torkzadeh, G. (1994), A confirmatory factor analysis of the end-user
computing satisfaction instrument, MIS Quarterly, Vol. 18 (4), 43-461.
[8] Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic management
journal, 17, 109-122.
[9] Hair, J. F., Anderson, R. E., Tatham, R. L. and Black, W. C. (2010). Multivariate Data Analysis: A
Global Perspective (7th ed). Pearson Prentice-Hall, Upper Saddle River, NJ.
[10] Hartwick, J., &Barki, H. (1994). Explaining the role of user participation in information system
use. Management Science, 40 (4), 440-465.
18. International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 6, No. 2, June 2015
18
[11] Howell, J.P., P.W. Dorfman& S. Kerr. (1986). Moderator variables in leadership research. The
Academy of Management Review, 11 (1), 88-102.
[12] Huber, G. P. (1991). Organizational learning: The contributing processes and the
literatures. Organization science, 2(1), 88-115.
[13] Ismail Manuri& Raja Abdullah Yaacob. (2011). Strategizing knowledge management in the
Malaysian Armed Forces: Towards knowledge-centric organization. Journal Information and
Knowledge Management, 1 (1), 19-36.
[14] Karahanna, E., & Straub, D. W. (1999). The psychological origins of perceived usefulness and ease-
of-use. Information and Management, 35 (4), 237-250
[15] Krejcie, R. V., and Morgan, D. W. (1970). Determining Sample Size for Research Activities.
Educational and Psychological Measurement, 607-610.
[16] Lin, H. F. (2008). Determinants of Successful Virtual Communities: Contributions from System
Characteristics and Social Factors. Information & Management 45 (8), 2008, pp. 522–527.
[17] Marchewka, J. T., Liu, C., &Kostiwa, K. (2007). An application of the UTAUT model for
understanding student perceptions using course management software. Communications of the
IIMA, 7(2), 93-104.
[18] Massey, A. P., Montoya-Weiss, M. M., and O'Driscoll, T. M. (2002). Knowledge management in
pursuit of performance: Insights from Nortel Networks. Mis Quarterly, 269-289.
[19] Medsker G.M., Williams L.J. and Holohan P. (1994). A review of current practices for evaluating
causal models in organizational behavior and human resources management research. J. Manage.
20:439–64
[20] Moran, M., Hawkes, M., & El Gayar, O. (2010). Tablet personal computer integration in higher
education: Applying the Unified Theory of Acceptance and Use Technology model to understand
supporting factors. Journal of Educational Computing Research, 42 (1), 79-101.
[21] Pallant, J. (2010). SPSS Survival Manual: A step by step guide to data analysis using SPSS. New
York: McGraw-Hill International.
[22] Raykov, T., and Marcoulides, G. A. (2008). An introduction to applied multivariate analysis. CRC
Press.
[23] Ryan, A. B. (2006). Post-positivist approaches to research. Researching and Writing your Thesis: a
guide for postgraduate students, 12-26.
[24] Sekaran, U. (2006). Research methods for business: A skill building approach. Wiley. com.
[25] Sun, H., & Zhang, P. (2006). The role of moderating factors in user technology acceptance.
International Journal of Human-Computer Studies, 64 (2), 53-78.
[26] Tabachnick, B. G., &Fidell, L. S. (2012). Using multivariate statistics: International edition.
California: Pearson Education.
[27] Venkatesh, V., &Bala, H. (2008). Technology Acceptance Model 3 and a research agenda on
interventions. Decision Sciences, 39 (2), 273-315.
[28] Venkatesh, V., & Davis, F. D. (2000). Theoretical Extension of the Technology Acceptance Model:
Four Longitudinal Field Studies. Management Science, 46(2), 186-204.
[29] Venkatesh, V., Morris, M.G.., Davis, G. B., Davis, F. D, (2003). User Acceptance of Information
Technology: Toward A Unified View. MIS Quarterly 27 (3), 425–478.
[30] Venkatesh, V., Thong, J. Y. L., &Xu, X. (2012). Consumer acceptance and use of information
technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36
(1), 157–178.
19. International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Author
This author is from Faculty of Information Management, UniversitiTeknologi
MARA, Shah Alam, Malaysia. Born in Kampar, Perak on 12 April 1974. He received
his first degree (Bachelor in Information Technolo
(graduated in 1998) and pursued his study in UniversitiTeknologi Mara, Shah Alam,
Malaysia in Master in Information Technology, from 2003 until 2007.
years of experience during his job with Petroleum
Senior Executive in Information and Technology (IT) field and continues his career
in Telekom Malaysia as Senior Audit Manager for about 2 years. Currently he is pursuing his full time
Doctoral Degree (PhD) study in UniversitiT
Factors Promoting Knowledge Sharing Using Virtual Mode Among Researchers In Government
Companies.HairolAdenanKasim had already presented his research in various occasions and proceedings
Academic Colloquium in Information Science and Information Management in SukhothaiThammathirat
Open University (September 2012), International Conferences on Social Science Research Penang,
Malaysia (July 2013), International Symposium on Information Sci
(November 2013) in Bangkok, Thailand
Scientists (February 2014) in Shah Alam, Malaysia.
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
Vol. 6, No. 2, June 2015
This author is from Faculty of Information Management, UniversitiTeknologi
MARA, Shah Alam, Malaysia. Born in Kampar, Perak on 12 April 1974. He received
his first degree (Bachelor in Information Technology) from Universiti Utara Malaysia
(graduated in 1998) and pursued his study in UniversitiTeknologi Mara, Shah Alam,
Malaysia in Master in Information Technology, from 2003 until 2007. He had 11
years of experience during his job with Petroleum NasionalBerhad (PETRONAS) as
Senior Executive in Information and Technology (IT) field and continues his career
in Telekom Malaysia as Senior Audit Manager for about 2 years. Currently he is pursuing his full time
Doctoral Degree (PhD) study in UniversitiTeknologi Mara, Shah Alam Malaysia for his research entitle
Factors Promoting Knowledge Sharing Using Virtual Mode Among Researchers In Government
Companies.HairolAdenanKasim had already presented his research in various occasions and proceedings
Academic Colloquium in Information Science and Information Management in SukhothaiThammathirat
Open University (September 2012), International Conferences on Social Science Research Penang,
International Symposium on Information Science and Information Management
mber 2013) in Bangkok, Thailand and World Congress of Muslim Librarians and Information
) in Shah Alam, Malaysia.
International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT)
19
in Telekom Malaysia as Senior Audit Manager for about 2 years. Currently he is pursuing his full time
eknologi Mara, Shah Alam Malaysia for his research entitle –
Factors Promoting Knowledge Sharing Using Virtual Mode Among Researchers In Government-Linked
Companies.HairolAdenanKasim had already presented his research in various occasions and proceedings -
Academic Colloquium in Information Science and Information Management in SukhothaiThammathirat
Open University (September 2012), International Conferences on Social Science Research Penang,
ence and Information Management
World Congress of Muslim Librarians and Information