MT on organizational structure

Impact of advanced manufacturing technology
on organizational structure
K. Abdul Ghania,*, V. Jayabalanb
, M. Sugumarc
a
Department of Mechanical Engineering, Technical Teachers Training Institute, Chennai, India
b
Department of Mechanical Engineering, Anna University, Chennai, India
c
Department of Management, Monash University, Churchil Victoria, Australia
Abstract
Advanced manufacturing technology (AMT) has been introduced in Indian manufacturing
industries to have a competitive edge in the global market. Despite the claims that attractive benefits
can accrue through the use of AMT in manufacturing firms, only modest benefits are reported.
Productivity of AMT organizations is found to be low even after several years of implementation of
AMT. One of the reasons attributed for low productivity is the organizational structure that remains
mechanistic and not compatible with new technology in most of the AMT firms. This paper presents
a framework to implement AMT in an existing environment with organic structure to achieve
superior performance. Data collected from 927 employees of 27 AMT firms in a cross-sectional
survey revealed significant information to change existing organizational structure and make it
compatible with change in technology to achieve higher productivity. D 2002 Elsevier Science Inc.
All rights reserved.
Keywords: Advanced manufacturing technology; Organic structure
1. Introduction
Developing countries like India, where technological change is the thrust in manufac-
turing industries, have introduced advanced manufacturing technology (AMT) to have a
1047-8310/02/$ – see front matter D 2002 Elsevier Science Inc. All rights reserved.
PII: S1047-8310(02)00051-2
* Corresponding author. Fax: +91-44-254-1126.
E-mail address: ritsouth@vsnl.com (K. Abdul Ghani).
Journal of High Technology
Management Research 13 (2002) 157–175

competitive edge in the global market. Despite the claims that attractive benefits can accrue
through the use of AMT in manufacturing firms, only modest benefits are reported
(Virmani, 1990). The superior performance of AMT firm, even in higher levels of AMT,
in terms of maximum labor productivity, superior quality, and greater flexibility in response
to changing market demand is still to be achieved. Firms, in which lower levels of AMT
have already been introduced, are unable to progress to higher levels to achieve ma-
nufacturing prosperity (Datta, 1990; Nemetz & Fry, 1988; Virmani, 1990). One of the
greatest challenges facing manufacturing firms in today’s business environment is the
implementation of AMT in the existing environment, which has effected a number of
changes in the work place. Technology used in an organization affects the structure of
work. Reorganization of AMT firm consequent to implementation of AMT is usually feared
because it means disturbance of the status quo, a threat to people’s vested interests in their
jobs and an upset to established ways of doing things. For these reasons, the needed
reorganization is often deferred, resulting in a loss of effectiveness and an increase in the
cost of manufacturing (Kotter & Schlesinger, 1979). If the organization’s design is not
appropriate for the work to be performed, behavioral problems can easily set in and the
effectiveness of the decision-making system can be seriously undermined. Drucker (1988)
has stated:
Organizational structure is an indispensable means and the wrong structure will seriously
impair business performance and may even destroy it. Future organizations will be
information based and composed largely of operation specialists and will have no middle
management at all.
The firm’s technology influences the organizational structure at operational and admin-
istrative levels, and consequently, the performance of the firm (Parthasarthy & Sethi, 1992).
New technologies are most likely to yield productivity gains when they are coupled with
changes in the organizational and human behavior (Preece, 1995). One of the reasons
attributed to the low performance of AMT firm is the organizational structure of that firm
which remains static in the changed environment. The most neglected factors during the
implementation of AMT are overall strategic plan, organizational design, design of jobs, skills
of blue-collar employees and their work attitudes (Bailey, 1993). In a developing country, the
ability to adopt technological change is the measure of success (Noori, 1997), as the firms
face many uncertainties. We are interested to know about the impact of new technology on
organizational structure, whether the organizational structure remains the same or different
after the implementation of AMT.
There has been substantial research documenting the effects of AMT on organizational
structure, but much has been in a developed country’s perspective and less is known about the
implications for a developing country. A systematic empirical investigation of the effects of
AMT on employees and organizational structure is required in a developing economy to
understand the implications of AMT in the context of their socioeconomic conditions. Such a
study is important because many firms which have already implemented AMT and invested
huge money in their manufacturing operations face problems and are unable to progress to
higher levels of AMT. Hence, this research is a more broad-based quantitative investigation
K. Abdul Ghani et al. / Journal of High Technology Management Research 13 (2002) 157–175158

of change in organizational structure, consequent to technological change with a framework
to implement new technology in the existing environment.
2. Conceptual framework
The framework conceptualized by Bailey (1993) and adapted by Ghani and Jayabalan
(2000) describes a firm’s technology as an endogenous variable, following the evolutionary
models that undergoes frequent adaptations to remain technically competitive. Any change
in the market demand affects the product of a manufacturing firm and forces it to redesign
the product. Many times the existing technology has been inadequate to incorporate the
required changes in the products. Hence, the firm is forced to introduce new technology to
remain competitive in the market. The framework links the technology, the organizational
structure, the employees, and the product of a manufacturing firm, providing for interactions
between the four variables (Bailey, 1993). The degree of fit among these four affects the
firm’s performance on various dimensions (Ford & Saren, 1996; King & Anderson, 1995;
Preece, 1995).
The framework posits, inter alia, that: (1) the adoption of AMT would suggest that a firm’s
technology is evolutionary; (2) a firm’s technology would influence both its operational and
administrative structures to change; (3) the technological change would affect and demand
changes in design and manufacturing activities; (4) consequently, jobs/tasks of employees
have to be redesigned resulting in change in job characteristics; (5) superior performance may
be achieved by maximum fit between technology, structure, and employees; and (6)
implementation of new technology affects work and work place.
Technological change is necessary not only for the survival of business but also for
maintaining its competitive edge and growth. The adoption of new technology has a
significant bearing on human relations within the firm. A firm is recognized to be successful
if it displays its ability to assimilate technological change without impinging on the harmony
of human relations of its employees. The technological choice, which is evolutionary in
nature, depends on the prevailing technological development in the industry. AMT has been
introduced over the years in piecemeal fashion in Indian manufacturing firms.
Organizational structure has been classified into product, process, or combination and tall
or flat type. A typology that subsumes most classifications and that has become popular is the
mechanistic–organic structure (Burns & Stalker, 1961) also referred to as bureaucratic–
adhocratic (Parthasarthy & Sethi, 1992). A structure is considered mechanistic to the extent
that its behavior is standardized, but it is considered organic (or adhocratic) when
standardization is absent (Mintzberg, 1979). Organizational structure is considered as a
function of the firm’s environment (Lawrence & Lorsch, 1969) and technology (Woodward,
1965). Mixed results have been obtained in research pertaining to technology–structure
relationship. However, the body of literature involving technology–structure investigation is
significant enough to warrant serious consideration while discussing structure (Parthasarthy
& Sethi, 1992). The framework proposed in this research therefore includes technology
relating to the structure.
K. Abdul Ghani et al. / Journal of High Technology Management Research 13 (2002) 157–175 159

3. Proposed framework
Technology is not only artifacts of tools and machines but also a form of knowledge
comprising the entire gamut of technologies as well as the management with their total
hardware and software contents. Technological change, a dynamic and multidimensional
phenomenon, is responsible for lasting social changes and rapid economic development. It is
conceptualized within the framework of an evolutionary epistemology of technological
knowledge. It can be a modification of the existing technology or emergence of new tech-
nology like computer-based manufacturing technology (Lowe, 1995; Parayil, 1991). AMT
has emerged as new technology which is defined as a group of integrated hardware-based and
software-based technologies which, if properly implemented, monitored, and evaluated will
lead to improving the efficiency and effectiveness of the firm in manufacturing a product
(Yousseff, 1992). It includes a variety of computerized technologies such as computer-aided
design (CAD), computer-aided manufacturing (CAM), flexible manufacturing system (FMS),
automated material handling (AMH), automated storage/retrieval system (AS/RS), and so on
(Hunt, 1987; Snell & Dean, 1992). In addition to machine tools for design and manufactur-
ing, AMT includes computer-aided techniques for plant management such as management
information system (MIS), computer-aided process planning (CAPP), material requirement
planning (MRP), artificial intelligence (AI), and so on. Computer integrated manufacturing
(CIM), which leads to a personless factory, has also been added to AMT (Hunt, 1987).
Currently based on the automation and integration of manufacturing activities, AMT has been
classified into four levels as stand-alone machines in Level 1, manufacturing cells in Level 2,
linked islands in Level 3, and integrated manufacturing in Level 4 (Meredith & Hill, 1987;
Snell & Dean, 1992). Implementation of AMT in the existing environment is illustrated in
Fig. 1. The adoption of AMT will not ifso-facto guarantee superior performance but will
further require changes in organizational characteristics. Many firms, which have implemented
Fig. 1. Implementation of AMT with organic structure.

AMT, followed the evolutionary approach where the expected outcomes would be achieved
over a period of time.
4. Organizational structure
The organizational structure is defined as the formal allocation of work roles and
administrative mechanism to control and integrate work activities. Traditional structure based
on the specialization of task and hierarchical management may be inappropriate to the new
technology and the changing internal environment in which they operate. The structure of a firm
is more difficult to alter since change involves redefining jobs, changing the reporting
relationships, and even eliminating some units. Studies on organizational theory assert that
technology has an influence over organizational structure (Harvey, 1968; Lawrence & Lorsch,
1969; Reimann, 1980; Singh, 1986; Woodward, 1965). Many of the AMT firms operate under
traditional structure which is mechanistic, more suitable for long runs of standardized
production (Burns & Stalker, 1961). The models of organizational design are mechanistic or
organic. The mechanistic design is synonymous with the bureaucracy, tall and centralized in
that it has extensive departmentalization, high formalization, downward communication, and
little participation by low-level employees in decision-making. The organic model is flat and
uses cross-hierarchical and functional teams. It has low formalization, lateral and upward
and downward communication networks, and high participation in decision-making (Burns &
Stalker, 1961; Mintzberg, 1979). The determinants of organizational structure, which decide an
organization as mechanistic or organic, are strategy, size, technology, and environment. In
addition, the employees’ behavior and their individual differences also have to be considered
for organizational design (Dalton, Todor, Spendolini, Fielding & Porter, 1980; James & Jones,
1976; Snizek & Bullard, 1983). Organization literature asserts about the fit between technology
and structure for better performance (Alexander & Randolph, 1985; Prasad, 1994). A wrong
structure will seriously impair business performance and may even destroy it (Drucker, 1988).
The characteristics of organizational structure may be explained in terms of division of task, job
description, decision-making, communication, control system, coordination, span of control at
supervisory level, vertical levels, and ratio of white-collar to blue-collar employees. The
psychological characteristics are motivation, group relations, leadership style, and reward. The
skill characteristics are operators’ multiskills, supervisory skills, and skill distribution among
the employees. The changes in the above characteristics of an organization with reference to the
change in technology determine the behavior of organization. A firm’s position can be
identified on the mechanistic–organic continuum and can be measured by using a semantic
differential scale comprising bipolar dimensions (Parthasarthy & Sethi, 1992).
5. Planned change process
Change is a complex process. Change activity, which is intentional, goal oriented, and
purposeful is called planned change process (PCP). The purpose of PCP is to improve the

ability of the organization to adapt to changes in its environment and to change employees’
behavior. A planned change in the context of technological change is to make changes in
the structure of organization. The ability of the planning system depends on how the
management focuses its efforts successfully, passes through the preparation stage where
appropriate skills, attitudes, procedures, and structure of organization could be built on to
harnessing the potentials of the AMT. Not only is the planning system important in
motivating the initial process of strategic decision-making, but it also plays a central role in
enabling firms to maintain a proactive edge by anticipating problems of implementation.
The dimensions of planned change efforts (PCE) are communication, decision-making,
control system, coordination, motivation, group relations, reward, training, involvement,
employee counseling, facilitation and support, negotiation, incentives, and manipulations
(Pareek, 1981). The degree or the level of planned change effectiveness, which determines
a firm as reactive or proactive, can be measured by using an instrument (Ghani, 2001).
Change is inevitable in the history of any organization. Organizations that do not change
or keep pace with the changing environment soon become defunct. To function effectively,
organizations have to achieve an equilibrium which is dynamic within the internal
environment in terms of technology, structure, employees, and the external environment
in terms of social, political, economic, and cultural factors. Hence, organizations have to
change, adapting to the changing environment. The change in technology affects any
organization when it is implemented. The change forces the organizations to cope with the
environment to become more adaptive, otherwise they become extinct (Kotter & Schle-
singer, 1979). Technology changes faster than people’s behavior. Any attempt to change the
organization to meet changes in the technology generally takes place before the majority of
people are ready for it. Thus, while the process of organizational change is going on, a
parallel process of preparing employees to accept the change is necessary. In many ways, the
introduction of the new technology is as painful for traditional management as it is for
traditional employees.
6. Organizational performance
The framework suggests that superior performance results when there is a fit between AMT
and organizational structure. David, Pearce II and Randolph (1989), Parthasarthy and Sethi
(1992), Rogers and Larson (1984), and Woodward (1965)concluded that the best fit between
technology and structure was responsible for better performance of AMT plants. As the
structure is evolutionary in most of the Indian manufacturing firms, the fit between technology
and structure is not achieved even after several years of implementation of AMT (Ghani &
Jayabalan, 2000). Hence, the performance of those firms is modest. When a PCP is initiated
before the introduction of AMT to make appropriate changes in the organizational structure, the
performance will increase (Ghani, 2001). For organizational scientists, the performance of
organization is the productivity of that organization.
Process technology has a significant impact on the operational effectiveness of a plant and
hence its productivity (Sumanth, 1998). Though AMT has major benefits like faster machine

cycle time, greater reliability, reduced inventory, saving on labor, greater flexibility, and
improved quality (Uzumi & Swanson, 1990), the productivity of the AMT plant will improve
only when it is integrated with the organizational structure.
7. Review of literature
If the objective of implementing AMT is indeed relatively uniform, the question becomes
whether their impacts on different firms are similar as well. It is more or less evident from
the literature and the subjective reactions generated from the industrial personnel and
academicians that the impact of AMT on organizational structure is different and is in fact
mediated by a variety of individual and organizational factors. To explore this more
systematically, an extensive review of literature published in the research journals,
proceedings, and books in developed countries as well as developing countries in the last
two decades was made. The related literature offers insights into the implementation process
of AMT and change in organizational structure. Studies pursuant to the development and
implementation of AMT suggest various changes to be made in organizational structure. A
critical review of literature done in the area of organizational implications of AMT is
presented here.
Woodward (1965) was the first to empirically demonstrate the interaction of technology
with organizational structure to influence performance. She found that a linear relationship
exists between technology and structural measures such as the number of hierarchical levels,
span of control, and personnel ratios. Blau, Falbe, Kinley and Tracy (1976) investigated how
technology influenced organizational structure. The Okayama study (Marsh & Mannari,
1981) found out that technology affected all the aspects of structure–labor inputs,
complexity, span of control, costs, and wages. Randolph (1981) suggested that an
organization must be designed with a proper mix of technology, structure, and human
behavior if it is to achieve goals and accomplish its tasks. Fry (1982) found that a stronger
relationship between technology and structure existed at the group level than at the
organization level. Kim and Utterback (1983), in their research study based on cross-
sectional analysis, revealed that influence of technology on structure in a developing country
was different from a developed country. Rogers and Larson (1984) observed that AMT was
closely associated with organizational structure where performance was more important than
formal position.
Cleveland (1985), Madique and Hayes (1984), and Naisbitt (1984), in their studies of AMT
firms, reported that the hierarchy such as rank, seniority, and specialization is often ignored or
eliminated. Boddy and Buchanan (1986) revealed that new technology influences organiza-
tions to change vertical levels, middle management levels, and decision-making pattern.
Nemetz and Fry (1988) identified the dimensions of AMT organization as organic with a
narrow span of control, few vertical levels, high integration, decentralized decision-making,
horizontal communication, adoptive behavior, group rewards, and self-regulatory.
David et al. (1989) examined the linkages between technology and structural fit. They
found that the best fit between them was responsible for better performance. Several studies

have examined the fit between technology and structure as a predictor of group performance
(Alexander & Randolph, 1985; Campbell & Gingrich, 1986; Kozlowski & Hults, 1986;
Meredith, 1987). Parthasarthy and Sethi (1992) asserted that superior performance could
result when there is a fit between AMT and the structure of organization. Sharit, Chang and
Salvendy (1987) and Susman and Chase (1986) concluded that maximum performance of
operators depends on the multiskill practices.
There is no substantial research in India in the area of organizational technology and the fit
between technology and structure. The following studies were reviewed in general. Kakar
(1972) opined that there was a high degree of control of tasks of subordinates by superiors in
organizations in India. Chowdhary and Prasad (1978), in a study of public sector under-
takings, found that technical delegation was the highest and financial delegation was the
lowest. Prasad (1994), based on the various studies on the relationship between technology
and organizational structure, asserted that the type of technology would influence the type of
organizational structure.
The findings of the research studies are summarized as follows: (1) technology has an
influence over organizational structure, (2) there must be a fit between technology and structure
for superior performance, and (3) the type of AMT organizational structure is organic.
While these studies are optimistic about the influence of technology on structure, there are
studies to indicate that there is no substantial relationship between technology and structure
(Lincoln, Hanada, & McBride, 1986; Mohr, 1971; Reimann, 1980). Considering the
enormous studies, which consistently focus and reiterate that technology has an influence
over structure, this researcher has followed the optimistic approach of fit between technology
and structure for superior performance.
8. Hypotheses
A large number of studies on organizational theory literature assert that technology has an
influence over organizational structure. If the organizational structure is not appropriate for
the work to be performed, the wrong structure will seriously affect business performance.
Hence, a study of organizational structure of AMT firms during and after the implementation
of new technology is necessary to suggest approaches to new organizational design. Changes
in organizational structure consequent to the implementation of AMT will enhance the
productivity. The objective of this research was to study the changes in organizational
structure of AMT firms consequent to the technological change. The following hypotheses
were proposed:
Hypothesis 1: There will be a significant difference in the means of organizational index
(OI) of AMT plants (a) between AMT levels and (b) between the years of imple-
mentation of AMT at the same proactive level (PL).
Hypothesis 2: There will be a significant difference in the means of OI of AMT plants
between their PLs at the same level of AMT.

Hypothesis 3: There will be a significant positive association between OI of AMT plant
and its total productivity.
9. Research methodology
The purpose of this research was to study the impact of AMT on organizational structure in
AMT firms. To have sound results, a cross-sectional design with statistical control was selected.
To test the hypotheses proposed, the data required were: data to measure the level of AMT, data
to measure the PL, and data to measure the OI of each AMT plant. The variables were: advanced
manufacturing technology level (AMTL) and the year after the implementation of AMT
(AMTY) as independent variables, PL as an influencing variable, organic index (OI) and its
factors as dependent variables. As this research was to study the impact of AMT on
organizational structure during and after the implementation of AMT, the sample base was
confined to AMT firms. Since the AMT has been implemented in selected AMT plants, the unit
of analysis was the AMT plant of each AMT firm.
The population to which the results have to be generalized is the AMT firms in the region.
More than 65 large firms and 100 small firms have been using AMTs in their manufacturing
activities. These firms located in different parts of the region, manufacture and export a
variety of products like heavy engines, heavy vehicles, machine tools, engine pistons, textile
machinery, automobile accessories and spares, electrical machines and components, two-
wheelers, and cutting tools. The sample base was the blue-collar employees, supervisors, and
managers of large manufacturing plants where AMT has been implemented. As it was
researched that the impact of technological change was more visible in large-scale manufac-
turing companies, only firms having employees about 1000 were identified (Bamber &
Landsbury, 1989; Bessant, Levy, Ley, Smith & Tranfield, 1991; Boddy & Buchanan, 1986;
Ghani & Sugumar, 1999; Rhodes, 1994). Formal letters seeking permission for data
collection were addressed to 35 large AMT firms in the region identified from the directory
of industries. Out of 35, 27 firms accorded permission. The common feature among all the
firms was that all of them were doing metal cutting operations in their AMT plants. The
understanding was not to disclose the identity of the firms anywhere in the research or
elsewhere. A preliminary survey to identify the AMT firms into four groups based on the
technology level, three groups based on the PL and three groups based on the year of
implementation of AMT was made and categorized accordingly. The sample of 27 AMT
plants was categorized into three groups based on AMTL (as there was no plant using AMTL
4), PL, and AMTY of AMT plants. There were nine AMT plants in each of three PL, three in
each of the first, fifth, and ninth year of implementation of AMT at AMTL 1, 2, and 3. The
first group of nine AMT plants was at a low PL (PL 1), the second group of nine AMT plants
was at partially PL (PL 2), and the third group of nine AMT plants was at a high PL (PL 3).
The sampling matrix is shown in Fig. 2. Each AMT plant has been identified by an alphabet P
followed by a three-digit number. The first digit from the left indicates the level of AMT, the
second, PL, and the third, year of implementation of AMT. Thus, P219 indicates a plant at
AMTL 2, PL 1, and AMTY 9.

Fig.2.Samplematrixwithcrosssectionalsurveydesign.

Instruments developed and validated by Ghani (2001) were used to measure the AMT level
(AMTL), PL, and OI of each AMT plant. The extent or degree of the use of AMT in each plant
was determined by the mean score obtained from the total score on a 10-point scale, which
indicates the plant’s position in the AMTscale. The instrument to measure the PL of each AMT
plant had 22 items on the following dimensions: communication, motivation, group relations,
rewards, involvement, training, employee counseling, facilitation and support, negotiation,
incentives, and manipulations. The PL in each plant was determined from the mean score
obtained from the total score marked on a five-point Likert scale from ‘not at all’ to ‘great deal’.
The instrument to measure OI (Ghani, 2001) consisted of 16 factors moving from points 1 to 5
from ‘mechanistic’ to ‘organic’ of AMT organization by using a semantic differential scale,
comprising the bipolar dimensions on division of task, job description, decision-making,
communication, control system, coordination, span of control, vertical levels, ratio of white-
collar to blue-collar employees, motivation, group relations, leadership style, reward, operator
skills, supervisory skills, and skill distribution. The respective dimensions were single task–
variety of task, formal/standardized–informal/flexible, centralized–decentralized, vertical and
directive–vertical and lateral, formal rules–informal rules, work standard–mutual adjustment,
low–high, many–minimum, low–high, economic–economic and noneconomic, formal/
impersonal–informal/personal, authoritarian–democratic and participative, individual/produc-
tion–group/production–group/innovation, single–multiskills, specific–integrative skills, and
low–high. Vernacular versions of the instruments were used in places where the blue-collar
employees knew only local language. The reliability of the vernacular instruments was
established following the appropriate statistical techniques.
Technology has a significant impact on the operational officiencies of a plant. Many
companies use the labor productivity to justify new technologies. Partial productivity
perspective has been used in many companies. This author has selected total productivity
as a measure of improvement because it takes into consideration the joint and simultaneous
impact of all the input resources including the new technology machines on the output. This
measure has received much attention over the past 10 years as evident from case studies
(Sumanth, 1998). The total productivity model defined by Sumanth (1998) is the ratio of
total tangible output to total tangible input. A questionnaire developed to measure total
productivity of each AMT plant included human and material resources inputs, fixed and
working capital, energy input, and value of finished and partially finished units of output
(Ghani, 2001).
10. Data collection
The required data were collected by administering the instruments directly to the
respondents in all 27 AMT plants. Prior to their participation, they were assured of complete
confidentiality of their responses and informed that only generalized findings would be
reported to the company. As each AMT plant has been located at different places,
geographically ranging from 5 to 700 km, data collection process took nearly 6 months for
all the four instruments. The number of completed instruments totaled 927 for each

instrument in 27 AMT plants, which worked out to be 44.78% of 2070 blue-collar employees,
supervisors, and managers. The total productivity of each AMT plant was measured by using
the instrument designed by Ghani (2001) during 1998–1999 for a period of 12 months.
11. Measures
The level of AMT (AMTL) of each plant was obtained from the scores of individuals. The
degree or extent of the use of the particular AMTL was measured by the instrument
administered to 30 supervisors and production managers of each plant. This score enabled
to choose the best plant based on the maximum use if there is more than one in any cell. The
PL of each plant was obtained from the scores of blue-collar employees, supervisors, and
managers. Change in organizational structure of each AMT plant was measured in terms of
Table 1
Means, standard deviations of organizational index and productivity of AMT plants
PL ! 1 2 3
AMTY# AMTL ! 1 2 3 1 2 3 1 2 3
First year SMPL ! 35 39 41 37 35 34 32 30 36
OI M 28.49 28.87 29.00 34.04 36.49 38.47 45.81 47.11 49.33
S.D. 2.42 2.42 2.54 3.30 3.26 2.84 3.13 3.13 2.50
TP 0.88 1.04 0.98 1.93 2.29 2.74 2.11 3.21 3.60
Fifth year SMPL ! 37 40 32 35 32 33 30 38 36
OI M 28.54 29.63 29.13 35.14 35.55 37.39 47.19 49.84 51.51
S.D. 2.20 2.60 2.79 2.35 2.94 2.18 2.93 2.73 2.42
TP 0.90 1.12 1.03 2.58 2.60 2.67 3.73 3.99 4.09
Ninth year SMPL ! 34 33 30 34 31 35 37 31 30
OI M 28.53 28.39 29.38 36.74 37.71 37.80 53.32 55.63 58.67
S.D. 2.10 2.26 2.11 3.02 1.95 2.98 2.26 2.61 2.25
TP 1.11 1.23 1.20 2.99 3.10 3.27 4.17 4.23 4.27
AMTY— year after implementation of AMT; PL — proactive level; AMTL — AMT level; SMPL — sample;
OI — organizational index; M — mean; S.D.— standard deviation; TP — total productivity of AMT plant.
Table 2
Results of two-way ANOVA for testing Hypothesis 1 at PL 1
Source of variation Sum of squares Degrees of freedom Mean square F statistic Significance of F
Between AMTLs 41.316 2 20.658 1.809 .369 (NS)
Between AMTYs 19.243 2 9.621 0.842 .669 (NS)
AMTLs Â AMTYs 306.038 4 76.509 6.699 .000***
Residual 3563.473 312 11.421
Total 3930.067 320 12.281
NS — not significant.
*** Significant at P < .001.

OI from the scores of the above employees. The means and standard deviations of OI of AMT
plants are given in Table 1. The total productivity of each AMT plant was obtained from the
records of concerned AMT firm.
12. Results and analysis
Impacts of AMT on organizational structure was investigated to explore the underlying
pattern of relationships between AMT and organizational characteristics. The inquiries may
be stated as (1) Is technology, particularly AMT, related to organizational structure? (2) Does
the change in organizational structure evolutionary? (3) What possible changes may be
incorporated with AMT? and (4) What insights do these findings hold to achieve higher
performance of AMT plants?
Analysis of variance was performed to test Hypothesis 1(a) and (b) and Hypothesis 2 to
determine whether the difference in the means of OI of the AMT plants is significant
between AMTLs and AMTYs? Tables 2, 3, and 4 show the results of two-way ANOVA
performed for testing Hypothesis 1 at PL 1, 2, and 3 by using SPSS version 6.0. This
statistical model of ANOVA is a fixed model wherein the AMT plants were categorically
selected based on the AMTL and AMTY; the interaction effects have nothing to do with the
main effects (Guilford, 1978). Hence, only the main effects have been considered in the
Table 3
Between AMTLs 602.819 2 301.409 38.187 .000***
Between AMTYs 938.847 2 467.427 59.473 .000***
AMTLs Â AMTYs 661.887 4 165.472 20.964 .000***
Residual 2344.239 297 7.893
Total 4547.792 305 14.899
Table 4
Between AMTLs 3681.525 2 1840.763 202.751 .000***
Between AMTYs 549.991 2 274.995 30.289 .000***
AMTLs Â AMTYs 579.344 4 144.836 15.953 .000***
Residual 2641.968 291 9.079
Total 7452.828 299 24.553

ANOVA. The difference in the means of OI of AMT plants between AMTLs has been found
to be insignificant at PL 1 and significant at PL 2 and 3 (P < .001). The result indicates that
AMT has no effects on organizational structure of AMT plants at low PL, but has significant
effects at high PL.
Hence, it is evident that the organizational structure of AMT plants has been found to have
changed with the implementation of AMT and the change is significant at high PL. In
developing countries, there are several manufacturing plants which are reactive in nature (less
proactive). When the new technology has been introduced in those plants, the expected
changes in the organizational structure do not occur even after the pay back period. However,
in those firms that are proactive in nature, the organizational structure of AMT plants is
different. This finding is in consonance with Blau et al. (1976), Boddy and Buchanan (1986),
David et al. (1989), Marsh and Mannari (1981), Nemetz and Fry (1988), Randolph (1981),
Rogers and Larson (1984), and Woodward (1965).
The difference in the means of OI of AMT plants between AMTYs has been found to be
insignificant at PL 1 and significant at PL 2 and PL 3 (P < .001). The organizational structure
of AMT plants at low PL (PL 1) has been found to be the same at AMTY 1, 5, or 9 whatever
be the level of technology (AMTL). However, it has been found to be significantly different
between the years of implementation of technology viz., AMTY 1, 5, and 9, when the AMT
plants are at high PL (PL 2 or 3), The inference is that the organizational structure of AMT
plants is significantly different between AMTLs or AMTYs only when those plants are at
high PLs. The hypothesis (Hypothesis 1) that there will be a significant difference in the
Table 5
Results of two-way ANOVA for testing Hypothesis 2 at AMTL 1
Between PLs 18,873.111 2 9436.555 853.601 .000***
Between AMTYs 174.409 2 87.204 7.888 .000***
PLs Â AMTYs 456.581 4 114.145 10.325 .000***
Residual 3338.607 302 11.055
Total 23,059.132 310
Table 6
Between PLs 21,087.086 2 10,543.543 1178.505 .000***
Between AMTYs 328.336 2 164.168 18.350 .000***
PLs Â AMTYs 2172.715 4 543.179 60.714 .000***
Residual 2683.963 300 8.947
Total 26,472.570 310 85.950

means of OI of AMT plants between AMTLs and AMTYs at the same PL has been accepted
only at high PL.
Results of two-way ANOVA for testing Hypothesis 2 at AMTL 1, 2, and 3 are shown in
Tables 5, 6, and 7. The difference in the means of OI of AMT plants between PLs (PL 1, 2,
and 3) has been found to be significant (P < .001) at AMTL 1, 2, and 3. The organizational
structure of AMT plants has been found to be significantly different (P < .001) between their
PLs at the three levels of AMT. It is clearly evident that the PL has emerged as an influencing
factor in reorganizing the organizational structure of AMT plants when AMT is implemented.
The hypothesis that there will be a significant difference in the means of OI of AMT plant
between the PLs at the same level of AMT has been accepted.
The changes in the organizational structure of AMT plants with AMTL/AMTY/PL are
shown in Fig. 3. The OI of AMT plants with low PLs are found to be the same irrespective of
the level of AMT or AMTY. However, the OI of those AMT plants at high PLs has been
found to increase with AMTL at the three levels of AMTY.
Total productivity (mean) of each AMT plant obtained for a period of 12 months is shown in
Table 1. Correlation between the variables OI and total productivity was found out by
Spearman’s correlation coefficients. The correlation coefficients obtained are shown in Table 8.
The correlation coefficients between OI and total productivity have been found to be
insignificant at PL 1 and positive and highly significant (P < .001) at PL 2 and 3. The results
Table 7
Between PLs 31,789.347 2 15,894.673 1874.320 .000***
Between AMTYs 27.979 2 13.990 1.650 .194 (NS)
PLs Â AMTYs 95.329 4 23.832 2.810 .026*
Residual 2527.110 298 8.480
Total 34,514.352 306 112.792
NS—not significant.
* Significant at P < .05.
Table 8
Results of Spearman’s correlation coefficients for testing Hypothesis 3
OI
TP PL 1 PL 2 PL 3 Significance
PL 1 +.0021 – – NS
PL 2 – +.9713 – P < .001
PL 3 – – +.9502 P < .001
OI — organizational index; TP — total productivity; NS — not significant.

indicate a significant positive correlation between OI and total productivity of AMT plants at
high PLs. Hence, Hypothesis 3 is accepted for a significant correlation between OI and total
productivity of AMT plants only at high PLs. This finding is in consonance with Alexander
and Randolph (1985), Parthasarthy and Sethi (1992), Rogers and Larson (1984), and
Woodward (1965).
Fig. 3. Changes in the organisational structure of AMT plant when AMTL/AMTY/PL increases.

13. Conclusion
The impact of AMT on organizational structure in developing countries lacks a body of
research studies. The research findings present the interrelationships between the variables
which were analyzed and investigated. Following the evolutionary model of technology in the
socioeconomic environment, the adoption of new technology will further require appropriate
changes in organizational structure. The successful AMT plant can be distinguished from the
unsuccessful one by comparing the organic index of the organizational structure. The findings
of the research based on the results obtained are reported below.
At a macro level, mechanistic structure is evident in AMT plants as long as the plants
remain at low PL. The structure of AMT plants does not show any change when the level of
AMT increases as long as the PL is low. However, at high PLs, the mechanistic structure of
AMT plants has been found to change significantly into an organic structure. A good, planned
change effectiveness system exemplified by its score of analysis and adaptive ability may be
facilitating a better synthesis between performance gaps and technology’s potential to focus
organizational attention in extracting much higher levels of performance. The findings of this
research reiterate the importance and the need for proactive planning to facilitate changes in
the organizational structure, in order to get productivity gains.
Change is always difficult to implement and it is more difficult for organizations that have
been designed to be rigid for a particular technology. The traditional organizational structure
will increasingly become obsolete. Large manufacturing plants have been slow to adopt the
new technology primarily because they have been so successful with traditional mechanistic
organizations. Many plants have failed to restructure their operations to take advantage of the
benefits of new technology. The technological change in an existing organizational structure
examined in this study has no effect on the organizational structure of several AMT
organizations, which is mostly reactive in nature (less proactive), but has significant effects
on the structure of AMT organizations which are proactive. The research findings reiterate a
series of changes in the AMT organizational structure for higher performance.
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