Modelling of critical success factors for implementation of AMTs

Modelling of critical successfactors for implementation

of AMTsRajesh K. Singh and Suresh K. Garg

Mechanical Engineering Department, Delhi College of Engineering, Delhi, India

S.G. DeshmukhMechanical Engineering Department, Indian Institute of Technology, Delhi,

India, and

Mohendra KumarSteel Authority of India Ltd, Bhilai, India

Abstract

Purpose – Globalisation of markets, the knowledge economy, e-business and introduction of newtechnologies pose new challenges to all organizations irrespective of their size and sector forsustaining their competitiveness. In this scenario successful implementation of advancedmanufacturing technologies (AMTs) by firms can give them an edge over their competitors. Thispaper aims to identify and develop the structural relationship among different factors for successfulimplementation of AMTs.

Design/methodology/approach – A questionnaire-based survey and interpretive structuralmodelling (ISM) approach has been applied in this study. In this research, 14 factors have beenidentified such as top management commitment, organization culture, sound financial condition,training, integration of departments, etc. On the basis of survey results and opinion of experts fromindustry and academia, a structural relationship model has been developed through an ISM approach.

Findings – Top management commitment and sound financial condition are the major drivers forimplementing AMTs. Effective implementation of AMTs will improve organization performance interms of lead time, product cost, fast delivery and product quality. For effective implementation ofAMTs, management should not ignore managerial aspects such as organization culture, employeetraining, integration of departments, vendor development, strategy development and customerinvolvement.

Originality/value – Management needs to address driving variables more carefully for successfulimplementation of AMTs.

Keywords Advanced manufacturing technologies, Critical success factors, Business improvement

Paper type Research paper

1. IntroductionGlobalisation of markets, rapidly changing technologies and product features aredriving firms to compete along several dimensions simultaneously such as design,manufacturing, distribution, communication, sales and others. Improvements incompetitors’ capabilities have shortened product life cycles, elevated productcomplexity and expanded accessibility to new technical breakthroughs. Rise inglobal competition has compelled the firms to increase performance standards in manydimensions such as quality, cost, productivity, product introduction time and smooth

The current issue and full text archive of this journal is available at

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Received February 2007Revised July 2007Accepted August 2007

Journal of Modelling in ManagementVol. 2 No. 3, 2007pp. 232-250q Emerald Group Publishing Limited1746-5664DOI 10.1108/17465660710834444

flowing operations (Hitt et al., 2001). Capacity of a firm to maintain reliable andcontinuously improving business and manufacturing processes to meet abovechallenges appears to be a key condition for ensuring its competitiveness in the longrun (Lagace and Bourgault, 2003). O’Regan et al. (2006) have observed thathigh-growth firms place a greater emphasis on external drivers such as strategicorientation, their operating environment and the use of e-commerce compared withfirms having static or declining sales.

Application of advanced manufacturing technology (AMT) is emerging as astrategic weapon in globally competitive market. Technology operates oncompetitiveness in two ways. First by altering the cost structure through thedevelopment of more efficient and flexible processes and second by enabling thecreation of better products of greater quality, better design, after sales service andshort delivery periods, etc (Vinas et al., 2001). Efstathiades et al. (1999) observed thatintroduction of AMTs led to an increase in the competitiveness of the Cypriotmanufacturing industry in terms of improved product market characteristics,improved plant utilization and flexibility and increased local market share. Moreimportantly, if a competitor’s technology is accepted as the industry standard, it canthreaten the existence of the firm (Narula, 2004). Mosey (2005) has observed that SMEscan compete with their larger rivals by developing new to market products using noveland often simpler technologies. Computer integrated manufacturing helps SMEs toreduce lead time, increase flexibility, reliability and to improve customer service(Gunasekaran et al., 2001; Dangayach and Deshmukh, 2005). SMEs can sustain theirgrowth and competitiveness in globalised market by adopting advancedmanufacturing systems (Singh et al., 2006). Growing numbers of organisations arenow adopting advanced management systems to cope with fragmented mass markets,shorter product life cycles and increased consumer demand for customisation(Raymond and Croteau, 2006).

AMTs have widely been regarded as a new and valuable weapon to rise to thechallenges imposed by the new market situation to manufacturing industries. Effectiveimplementation of AMTs results in greater customer satisfaction and lowermanufacturing operating costs (Hottenstein and Casey, 1997). AMTs are givingmany firms the potential to bridge the gap between choosing low-cost dedicatedproduction and high-variety differentiation. AMTs impact not just manufacturing, butthe whole business operations, giving new challenges to a firms’s ability to manageboth manufacturing and information technologies. AMTs include a group of integratedhardware- and software-based technologies which, when properly implemented,monitored and evaluated, can improve the operating efficiency and effectiveness ofadopting firms. They encompass a broad range of computer-based technologicalinnovations which include numerical control machine tools, cellular manufacturing,machining centers, industrial robots, and integrated storage and retrieval systems(AS/RS).

Boyer and Pagell (2000) have identified three broad categories of AMTs: design,manufacturing and administrative. Design-based AMTs are technologies such as CADthat reduce design cycle times and hence time to market. In addition to reduce designcycle times, these technologies also reduce design costs. Administrative AMTs aretechnologies such as electronic data interchange that enable faster and cheapercommunication both within an organization and across a supply chain.

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Both administrative and design technologies improve the competitiveness of amanufacturing organization by improving many of the processes that supportproduction. Manufacturing AMTs are actual production technologies such as flexiblemanufacturing systems (FMS), computer numerical control and group technology.

AMTs must be used to revise completely the capability of manufacturing, improvemanufacturing parameters and ultimately the company’s order winning criteria, i.e. thedistinctive features of the product or service that cause the customer to buy it.Investment in AMTs is one manner in which manufacturers believe they can improvetheir competitive position in the world markets (Millen and Sohal, 1998). In currentyears, for Indian auto component sector, automation of process has emerged as majorarea of investment (Singh et al., 2007a, b) for competing in global market. Adoption ofAMTs gives a greater number of growth options to enter new markets and to createnew products than firms relying on traditional manufacturing technologies andgeneric strategies.

Technology selection in a manufacturing system and its implementation will be agreat challenge for firms to survive in this hyper competitive market. It has beenreported that majority of AMTs adopters fail in their quest to implement AMTs(Burgess and Gules, 1998). The major challenge in implementing AMTs is integratingthem with the capabilities and constraints of people and organization (Mechling et al.,1995). In addition to this, buyer-supplier relationship also plays a significant role insuccess of AMTs (Burgess and Gules, 1998). It means AMTs cannot be successfullyimplemented till all departments are effectively integrated. For successfulimplementation of AMTs, management need to focus on different aspects oforganisational functioning such as development of competitive strategy, organisationculture, employees training, vendor development, integration of departments, etc. Inaddition to this, management needs to understand structural relationship betweendifferent variables, which will help in developing strategies for effectiveimplementation of AMTs. Keeping in view the complexity in AMTs implementationprocess, this paper will endeavour to:

. identify and rank the critical success factors for implementation of AMTs;

. establish the relationship among identified critical success factors; and

. understand the managerial implications of this research.

This paper is organized as follows. The next section discusses the literature review foridentification of critical success factors. It is followed by the relevant findings of aquestionnaire survey and interpretive structural modelling (ISM) of these factors.Finally, the results and discussion of this research are presented, which is followed byconcluding remarks.

2. Identification of critical success factorsTo effectively compete in global markets, firms must be quick and flexible in theirresponse to customer needs. In today’s rapidly changing world, organizations need toachieve competitive advantage in cost, quality, innovation and deliverysimultaneously. To meet these challenges, successful implementation of AMTs canplay a significant role. Decisions about AMTs implementation should be part of abroadly based business strategy. AMTs represent a wide variety of moderntechnologies devoted to improve operational efficiency and competitiveness of

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manufacturing firms (Small, 2006). AMTs permit functional integration by linkingvarious functional departments’ information systems, common data bases and shopfloor AMTs (Dean and Snell, 1991). It also helps in improving product quality and inreducing cost (Rosnah et al., 2003). The benefits of AMTs can be classified as tangibleand intangible. The tangible benefits include inventory savings, less floor space,improved return on equity and reduced unit cost of production. The intangible benefitsinclude an enhanced competitive advantage, increased flexibility, improved productquality and quick response to customer demand.

AMTs also help in adopting JIT practices. JIT practices help firms in achievingflexibility by reducing impediments to change (Zhang et al., 2002). Despite the greatpotential of AMTs such as FMS, computer-added manufacturing, robotics, etc. toimprove business performance, managers in many companies fail in implementingAMTs successfully. Zhang et al. (2006) have observed that simply purchasingautomation is not important but developing operations improvement practices toeffectively use AMTs is more important. Effective use of AMT can be predicted by thefirm’s competitive strategy, firm vendor relations, and firm’s ability to integrateAMTs, structure and strategy. Greater collaboration with vendors or parts supplierscontributes to improving the level of success of AMTs implementation (Burgess andGules, 1998).

It is important to have top management support, widespread practice of personneltraining, promoting early worker participation, the choice of suppliers based ontechnical expertise and the experience and availability of a project champion for AMTimplementation (Sanchez, 1996). Zammuto and O’Connor (1992) have advocated forimportance of organizational design and cultures for implementing AMTs. Mohantyand Deshmukh (1998) have observed the need of sound financial condition for AMTsimplementation. The selection of the appropriate technology that achieves or matcheswith the organization objective must be made on the basis of sound decision (Mamalis,2005). Implementation of AMTs requires careful planning at all levels of theorganization to achieve the intended goals. It is a complex process with many factors tobe considered before the full benefits of AMTs can be realized (Yusuff, et al., 2001). Forthe manufacturing SME, this implies managing its supply chain through collaborationand partnerships with customers, suppliers, distributors, competitors, and otherorganizations such as consulting firms and research centers (Soh and Roberts, 2005).

The investment in AMTs requires long periods of planning and the resulting impacton the firm is not immediate. Organisations should also focus on planning and otherimplementation factors (Monge et al., 2006). Many firms, specially small- andmedium-sized firms, lacked the absorptive capabilities to internalize AMTs due tomanagerial deficiencies and organizational obstacles. The strongest determinant ofAMTs are the level of performing, adequate training and support by AMTsmanufacturer, improvements on existing policies and the modification on existingprocedures as well as the setting of interim targets on which the process ofimplementation shall be evaluated (Efstathiades et al., 2002). When AMTs in designare implemented to high extents, organization and human development should also beconsidered. Technology alone does not provide companies with better overallperformance, but the joint use of technological and organizational innovation can havean effect on several performance measures (Cagliano and Spina, 2000). While makinginvestments on AMTs, organizations should try to maintain balance between


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hardware-based technologies and software-based infrastructure improvementprograms for being successful.

Although AMTs can be considered as a strategic weapon, it is a risky and complextask to undertake because it involves not only high-financial investments but alsoaspects such as internal and external planning and team-based activities (Co et al.,1998). Organizations should have a clear understanding of the objectives andimplications of AMT project. Strategies should be aligned towards these objectives.Critical factors for successful implementation of AMTs will depend on strategies andobjectives. In this study, 14 critical success factors are identified on the basis ofliterature review and opinion of experts from industry and academia (Table I).

3. Research methodologyIn this study, questionnaire-based survey and ISM have been used to achieve theresearch objectives. These methodologies and the respective results are separatelydiscussed in the next two sections.

3.1 Questionnaire surveyQuestionnaire was developed on the basis of literature review and pilot survey.Questionnaire was mailed to about 400 organisations. These organizations wereselected from directories available at Confederation of Indian Industries, AutoComponent Manufacturers Association of India, Federation of Indian Chambers ofCommerce and Industries and Department of industries (Government of India). In spiteof continuous reminders, phone calls, e-mail, only 78 valid responses could be obtained.Detail profile of responding organizations is given in Table II. In this study,respondents were asked to rate the level of importance for each factor given by theirrespective organization on a five-point Likert scale (1 – lowest, 5 – highest). Tomeasure the scale reliability and internal consistency of collected data, Cronbach’scoefficient a was calculated. The coefficients of Cronbach’s a exceed the minimumrequirements of 0.5 for an exploratory study such as this one (Nunnally, 1978). Thedata obtained from survey were analyzed by single sample t test. Results of this

S. No. Critical success factors References

1 Top management commitment Sanchez (1996)2 Organization culture Zammuto and O’Connor (1992)3 Sound financial condition Mohanty and Deshmukh (1998)4 Employee training Efstathiades et al. (2002)5 Integration of departments Dean and Snell (1991)6 Vendor development Burgess and Gules (1998) and Soh and Roberts (2005)7 Development of competitive strategy Mamalis (2005)8 Effective implementation of AMTs Zhang et al. (2006)9 Reduction in lead time Zhang et al. (2002) and Boyer and Pagell (2000)

10 Reduction in delivery time Vinas et al. (2001) and Zhang et al. (2002)11 Improvement in product quality Rosnah et al. (2003) and Dangayach and Deshmukh

(2005)12 Reduction in product cost Hottenstein and Casey (1997) and Rosnah et al. (2003)13 Performance improvement Small (2006)14 Customer involvement Gunasekaran et al. (2001)

Table I.Critical success factorsfor implementationof AMTs

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analysis are given in Table III. All the factors are significant at p , 0.01. Topmanagement commitment, development of competitive strategy and organizationculture are major enablers for AMTs implementation and improvement in productquality, performance improvement, reduction in lead time are major motivatingfactors.

3.2 ISM methodologyISM is an interactive learning process. The method is interpretive in that the group’sjudgment decides whether and how items are related, it is structural in that, on thebasis of the relationship, an overall structure is extracted from the complex set of items,and it is modeling in that the specific relationships and overall structure are portrayed

Salesturnover

Number(per cent) Investment

Number(per cent) Category

Number(per cent)

, Rs 10Crore 14 (17.9) , Rs 1 Crore 7 (9.0) Proprietorship 5 (6.4)Rs 10-50 15 (19.2) Rs 1-25 19 (24.4) Partnership 5 (6.4)Rs 50-200 6 (7.7) Rs 25-50 5 (6.4) Private Ltd 46 (59.0)Rs 200-500 13 (16.7) Rs 500-100 12 (15.4) Public Ltd 11 (14.1).500 Crore 26 (33.3) .100 Crore 31 (39.7) Joint venture 6 (7.7)Did notspecify 4 (5.1)

Did notspecify 4(5.1)

Did notspecify 5 (6.4)

No. ofemployees

Number(per cent)

No. ofprofessionals

Number(per cent) Location

Number(per cent)

,500 31 (39.7) 0-50 21 (26.9) Rural 11 (14.1)500-1,000 11 (14.1) 50-500 29 (37.1) Semi urban 18 (23.1)1,000-10,000 31 (39.7) 500-1,000 11 (14.1) Urban 37 (47.4).10,000 5 (6.4) . 1,000 7 (8.9) Did not specify 12 (15.4)Did notspecify 0 (0.0)

Did notspecify 10 (12.8) Total participant¼78

Table II.Profile of responding

organizations

S. No. Enablers for AMT Mean SD t-value Rank

1 Top management commitment 4.08 0.91 10.39 12 Development of competitive strategy 4.04 0.86 10.59 23 Organization culture 3.95 0.81 10.14 34 Customer involvement 3.95 0.85 9.62 45 Sound financial condition 3.92 0.83 9.69 56 Employee training 3.84 0.92 7.94 67 Vendor development 3.69 1.00 6.01 78 Integration of departments 3.61 0.93 5.72 89 Effective implementation of AMTs 3.61 0.95 5.52 9

Motivational factors10 Improvement in product quality 4.45 0.72 17.55 111 Performance improvement 4.14 0.70 14.29 212 Reduction in lead time 4.03 0.92 9.82 313 Reduction in delivery time 3.93 0.82 9.54 414 Reduction in product cost 3.82 0.99 7.19 5

Table III.Critical success factorsfor implementation of

AMTs


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in a diagraph model. ISM methodology helps to impose order and direction on thecomplexity of relationships among elements of a system (Sage, 1977). For complexproblems, like the one under consideration, a number of factors may be critical forsuccessful implementation of AMTs. However, the direct and indirect relationshipsbetween the factors describe the situation far more accurately than the individualfactor taken in isolation. Therefore, ISM develops insights into collectiveunderstandings of these relationships. Jharkharia and Shankar (2005) applied ISM forunderstanding the barriers in IT – enablement of supply chains. Singh et al. (2007a, b)applied ISM for improving SMEs competitiveness. The application of ISM typicallyforces managers to reassess perceived priorities and improve their understanding ofthe linkages among key concerns. The various steps involved in the ISM technique are:

(1) Identification of elements, which are relevant to the problem or issues, thiscould be done by literature review or any group problem solving technique.

(2) Establishing a contextual relationship between elements with respect to whichpairs of elements will be examined.

(3) Developing a structural self-interaction matrix (SSIM) of elements, whichindicates pair-wise relationship between elements of the system?

(4) Developing a reachability matrix from the SSIM, and checking the matrix fortransitivity. Transitivity of the contextual relation is a basic assumption in ISMwhich states that if element A is related to B and B is related to C, then A will benecessarily related to C.

(5) Partitioning of reachability matrix into different levels.

(6) Based on the relationships given above in the reachability matrix draw adirected graph (digraph), and remove transitive links.

(7) Convert the resultant digraph into an ISM, by replacing element nodes withstatements.

(8) Review the ISM model to check for conceptual inconsistency, and make thenecessary modifications.

Above described steps, which lead to the development of ISM model, are discussedbelow.

3.2.1 Structural self-interaction matrix (SSIM). For analyzing the criteria acontextual relationship of “leads to” is chosen here. For developing contextualrelationships among variables, expert opinions based on various managementtechniques such as brainstorming, nominal group technique, idea engineering, etc.were considered. In this exercise, total seven experts, four from industry and three fromacademia finally agreed to participate. For expressing the relationship betweendifferent critical factors for successful implementation of AMTs, four symbols havebeen used to denote the direction of relationship between the parameters i and j(here i , j):

(1) V: parameter i will lead to parameter j;

(2) A: parameter j will lead to parameter i;

(3) X: parameter i and j will lead to each other; and

(4) O: parameters i and j are unrelated.

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The following statements explain the use of symbols V, A, X and O in SSIM:. variable 1 leads to 13 (V);. variable 7 leads to 4 (A); and. variables 9 and 11 are unrelated (O).

Based on contextual relationships the SSIM is developed in Table IV.

3.2.2 Reachability matrix. The SSIM has been converted into a binary matrix, calledthe initial reachability matrix by substituting V, A, X and O by 1 and 0 as per the case.The substitution of 1s and 0s are as per the following rules:

(1) If the (i, j) entry in the SSIM is V, the (i, j) entry in the reachability matrixbecomes 1 and the ( j, i ) entry becomes 0.

(2) If the (i, j) entry in the SSIM is A, the (i, j) entry in the reachability matrixbecomes 0 and the ( j, i ) entry becomes 1.

(3) If the (i, j) entry in the SSIM is X, the (i, j) entry in the reachability matrixbecomes 1 and the ( j, i ) entry also becomes 1.

(4) If the (i, j) entry in the SSIM is O, the (i, j) entry in the reachability matrixbecomes 0 and the ( j, i ) entry also becomes 0.

Following above rules, the initial reachability matrix for the critical success factors isshown in Table V. After incorporating the transitivities as described in Step (4) of theISM methodology, the final reachability matrix is shown in Table VI. In Table VI, thedriving power and dependence of each variable is also shown. Driving power for eachvariable is the total number of variables (including itself), which it may help to achieve.On the other hand, dependence is the total number of variables (including itself), whichmay help in achieving it. These driving power and dependencies will be later used inthe classification of variables into the four groups of autonomous, dependent, linkageand drivers (independent).

S. No. Critical success factors 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1 Top management commitment V O V V V V V V V V V V V2 Organization culture O V V O A V V V V V V O3 Sound financial condition V V V V V V V V V V V4 Employee training V O A V V V V V V O5 Integration of departments O A V V V V V V O6 Vendor development A V V V V V V O7 Development of competitive strategy V V V V V V V8 Effective implementation of AMTs V V V V V O9 Reduction in lead time V O V V O

10 Reduction in delivery time O O V A11 Improvement in product quality O V A12 Product cost V A13 Performance improvement A14 Customer involvement

Notes: Here for i , j; V: factor i leads to factor j; A: factor j leads to factor i; O: no relationship betweeni and j

Table IV.Structural self interaction

matrix


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3.2.3 Final reachability matrix. The final reachability matrix is obtained byincorporating the transitivity as enumerated in Step (4) of the ISM methodology. Thisis shown in Table VI. In this Table, the driving power and dependence of each factorare also shown.

The driving power of a particular factor is the total number of factors (includingitself), which it may help achieve while the dependence is the total number of factors,which may help achieving it. On the basis of driving power and dependencies, thesefactors will be classified into four groups of autonomous, dependent, linkage andindependent (driver) factors.

3.2.4 Level partitions. From the final reachability matrix, the reachability andantecedent set for each factor are found. The reachability set consists of the element

S. No. Critical success factors 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1 Top management commitment 1 1 0 1 1 1 1 1 1 1 1 1 1 12 Organization culture 0 1 0 1 1 0 0 1 1 1 1 1 1 03 Sound financial condition 0 0 1 1 1 1 1 1 1 1 1 1 1 14 Employee training 0 0 0 1 1 0 0 1 1 1 1 1 1 05 Integration of departments 0 0 0 0 1 0 0 1 1 1 1 1 1 06 Vendor development 0 0 0 0 0 1 0 1 1 1 1 1 1 07 Development of competitive strategy 0 1 0 1 1 1 1 1 1 1 1 1 1 18 Effective implementation of AMTs 0 0 0 0 0 0 0 1 1 1 1 1 1 09 Reduction in lead time 0 0 0 0 0 0 0 0 1 1 0 1 1 0

10 Reduction in delivery time 0 0 0 0 0 0 0 0 0 1 0 0 1 011 Improvement in product quality 0 0 0 0 0 0 0 0 0 0 1 0 1 012 Product cost 0 0 0 0 0 0 0 0 0 0 0 1 1 013 Performance improvement 0 0 0 0 0 0 0 0 0 0 0 0 1 014 Customer involvement 0 0 0 0 0 0 0 0 0 1 1 1 1 1

Table V.Initial reachability matrix

S.No. Critical success factors 1 2 3 4 5 6 7 8 9 10 11 12 13 14 D.P.

1 Top management commitment 1 1 0 1 1 1 1 1 1 1 1 1 1 1 132 Organization culture 0 1 0 1 1 0 0 1 1 1 1 1 1 0 93 Sound financial condition 0 1 1 1 1 1 1 1 1 1 1 1 1 1 134 Employee training 0 0 0 1 1 0 0 1 1 1 1 1 1 0 85 Integration of departments 0 0 0 0 1 0 0 1 1 1 1 1 1 0 76 Vendor development 0 0 0 0 0 1 0 1 1 1 1 1 1 0 77 Development of competitive

strategy 0 1 0 1 1 1 1 1 1 1 1 1 1 1 128 Effective implementation of

AMTs 0 0 0 0 0 0 0 1 1 1 1 1 1 0 69 Reduction in lead time 0 0 0 0 0 0 0 0 1 1 0 1 1 0 4

10 Reduction in delivery time 0 0 0 0 0 0 0 0 0 1 0 0 1 0 211 Improvement in product quality 0 0 0 0 0 0 0 0 0 0 1 0 1 0 212 Product cost 0 0 0 0 0 0 0 0 0 0 0 1 1 0 213 Performance improvement 0 0 0 0 0 0 0 0 0 0 0 0 1 0 114 Customer involvement 0 0 0 0 0 0 0 0 0 1 1 1 1 1 5

Dependence 1 4 1 5 6 4 3 8 9 11 10 11 14 4 91

Note: D.P. – driving powerTable VI.Final reachability matrix

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itself and other elements to which it may help achieve, whereas the antecedent setconsists of the element itself and the other elements which may help achieving it. Thenthe intersection of these sets is derived for all elements. The element for which thereachability and intersection sets are same is the top-level element in the ISMhierarchy. The top-level element of the hierarchy would not help achieve any otherelement above their own. Once the top-level element is identified, it is separated outfrom the other elements. Then by the same process, the next level of elements is found.These identified levels help in building the diagraph and final model. From Table VII,it is seen that the performance improvement is found at level I. Thus, it would bepositioned at the top of the ISM hierarchy. This iteration is repeated till the levels ofeach factor are found out (Tables VII-XV). The identified levels aids in building thefinal model of ISM.

3.2.5 Classification of factors. In this section, the critical success factors describedearlier are classified into four clusters (Figure 1). This classification is similar to thatmade by Mandal and Deshmukh (1994). The first cluster consists of the “autonomousfactors” that have weak driving power and weak dependence. These factors arerelatively disconnected from the system, with which they have only few links, whichmay not be strong. The “dependent factors” constitute the second cluster which hasweak driving power but strong dependence. Third cluster has the “linkage factors”that have strong driving power and strong dependence. These factors are unstable dueto the fact that any change occurring to them will have an effect on others and also afeedback on themselves. Fourth cluster includes the “independent factors” havingstrong driving power but weak dependence. The driving power and dependence ofeach of these factors are shown in Table VI. In this table, an entry of “1” added alongthe columns and rows indicates the dependence and driving power, respectively.Subsequently, the driver power-dependence diagram is constructed as shown inFigure 1. For illustration, the factor five having a driving power of 7 and dependence of

Factor Reachability set Antecedent setIntersection

set Level

1 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,14 1 1

2 2, 4, 5, 8, 9, 10, 11, 12, 13 1, 2, 3, 7 23 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,

14 3 34 4, 5, 8, 9, 10, 11, 12, 13 1, 2, 3, 4, 7 45 5, 8, 9, 10, 11, 12, 13 1, 2, 3, 4, 5, 7 56 6, 8, 9, 10, 11, 12, 13 1, 3, 6, 7 67 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 1, 3, 7 78 8, 9, 10, 11, 12, 13 1, 2, 3, 4, 5, 6, 7, 8 89 9, 10, 12, 13 1, 2, 3, 4, 5, 6, 7, 8, 9 9

10 10, 13 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 14 1011 11, 13 1, 2, 3, 4, 5, 6, 7, 8, 11, 14 1112 12, 13 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 14 1213 13 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,

14 13 I14 10, 11, 12, 13, 14 1, 3, 7, 14 14

Table VII.Iteration 1


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Factor Reachability set Antecedent set Intersection set Level

1 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14 1 12 2, 4, 5, 8, 9, 10, 11, 12 1, 2, 3, 7 23 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14 3 34 4, 5, 8, 9, 10, 11, 12 1, 2, 3, 4, 7 45 5, 8, 9, 10, 11, 12 1, 2, 3, 4, 5, 7 56 6, 8, 9, 10, 11, 12 1, 3, 6, 7 67 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14 1, 3, 7 78 8, 9, 10, 11, 12 1, 2, 3, 4, 5, 6, 7, 8 89 9, 10, 12 1, 2, 3, 4, 5, 6, 7, 8, 9 9

10 10 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 14 10 II11 11 1, 2, 3, 4, 5, 6, 7, 8, 11, 14 11 II12 12 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 14 12 II14 10, 11, 12, 14 1, 3, 7, 14 14

Table VIII.Iteration 2


1 1, 2, 4, 5, 6, 7, 8, 9, 14 1 12 2, 4, 5, 8, 9 1, 2, 3, 7 23 2, 3, 4, 5, 6, 7, 8, 9, 14 3 34 4, 5, 8, 9 1, 2, 3, 4, 7 45 5, 8, 9 1, 2, 3, 4, 5, 7 56 6, 8, 9 1, 3, 6, 7 67 2, 4, 5, 6, 7, 8, 9, 14 1, 3, 7 78 8, 9 1, 2, 3, 4, 5, 6, 7, 8 89 9 1, 2, 3, 4, 5, 6, 7, 8, 9 9 III

14 14 1, 3, 7, 14 14 IIITable IX.Iteration 3


1 1, 2, 4, 5, 6, 7, 8 1 12 2, 4, 5, 8 1, 2, 3, 7 23 2, 3, 4, 5, 6, 7, 8 3 34 4, 5, 8 1, 2, 3, 4, 7 45 5, 8 1, 2, 3, 4, 5, 7 56 6, 8 1, 3, 6, 7 67 2, 4, 5, 6, 7, 8 1, 3, 7 78 8 1, 2, 3, 4, 5, 6, 7, 8 8 IV

Table X.Iteration 4


1 1, 2, 4, 5, 6, 7 1 12 2, 4, 5 1, 2, 3, 7 23 2, 3, 4, 5, 6, 7 3 34 4, 5 1, 2, 3, 4, 7 45 5 1, 2, 3, 4, 5, 7 5 V6 6 1, 3, 6, 7 6 V7 2, 4, 5, 6, 7 1, 3, 7 7

Table XI.Iteration 5

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1 is positioned at a place corresponding to driving power of 7 and dependency of 1 inthe Figure 1. Similarly all other factors considered in this study are positioned ondifferent quadrants depending on their driving power and dependency.

3.2.6 Formation of ISM-based model. From the final reachability matrix (Table VI),the structural model is generated by means of vertices or nodes and lines of edges. Ifthere is a relationship between the competitiveness factors i and j this is shown by anarrow which points from i to j. This graph is called a directed graph or digraph. Afterremoving the transitivities as described in ISM methodology, the digraph is finallyconverted into ISM as shown in Figure 2.

4. Results and discussionAMTs have the potential to improve operating performance dramatically and createvital business opportunities for companies which are capable of successfullyimplementing and managing them. For successful implementation of AMTs,organizations need to identify critical factor, so that management may effectively


1 1, 2, 4, 7 1 12 2, 4 1, 2, 3, 7 23 2, 3, 4, 7 3 34 4 1, 2, 3, 4, 7 4 VI7 2, 4, 7 1, 3, 7 7

Table XII.Iteration 6


1 1, 2, 7 1 12 2 1, 2, 3, 7 2 VII3 2, 3, 7 3 37 2, 7 1, 3, 7 7

Table XIII.Iteration 7


1 1, 7 1 13 3, 7 3 37 7 1, 3, 7 7 VIII

Table XIV.Iteration 8


1 1 1 1 IX3 3 3 3 IX

Table XV.Iteration 9


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incorporate these factors at their strategic level as well as operational level. Further,these factors should be structured to find out the factors which are prerequisite for thesuccess and which facilitates the achievement of others. The analysis of interactionamong the factors is provided by ISM. It identifies the hierarchy of actions to be takenby management in order to improve the performance by implementing AMTs. Thedriver power-dependence matrix (Figure 1) gives some valuable insights about therelative importance and interdependencies among critical success factors. Majorfindings of this study are as follows:

. The driver-dependence matrix (Figure 1) indicates that customer involvement isan autonomous factor in this study. Autonomous variables generally appear asweak driver as well as weak dependent and are relatively disconnected from thesystem. These variables do not have much influence on the other variables of thesystem.

. Effective implementation of AMTs, reduction in product cost, lead time anddelivery time, quality improvement and performance are weak drivers butstrongly dependent on other variables. Survey results also indicatethat improvement of quality and performance, reduction in lead time aresignificant and major motivating factors for AMTs application. They are seen atthe top of the ISM hierarchy (Figure 2). These variables represent desiredobjectives for any organization and are classified as dependent variables.

Figure 1.Driving power anddependence diagram

13 1,3

12 7

11

10

9 2

8 4

6 57

6 8

5 14

4 9

3 I II

2 11 10,12

1 13

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Dependence

AUTONOMUS

LINKAGEDRIVERS

DEPENDENTDri

ving

Pow

erIIIIV

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. There is no linkage variable which has a strong driving power as well as strongdependence. Thus, it can be inferred that among all the 14 variables chosen inthis study, no variable is unstable.

. The driver power dependence diagram indicates that variables such as topmanagement commitment, organization culture, sound financial condition,employees training, integration of departments, vendor development,competitive strategies and customer involvement are at the bottom of themodel having strong driving power. Survey results also indicate the importanceof top management commitment, development of competitive strategy andorganization culture for AMTs implementation. These variables will help

Figure 2.ISM-based model for

implementation of AMTsTop management Commitment

Reduction in Lead-Time Customer involvement

Vendor Development

Effective Implementation of AMTs

Reduction in Delivery Time

Performance Improvement

Development of Competitive Strategy

Sound financial condition

Organization Culture

Integration of Department

Employee Training

Improvement in Product qualityReduction in Product Cost


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organizations to achieve its desired objectives and are classified as independentvariables or drivers.

. This study has also tried to find levels for different variables. From the model, itis observed that performance improvement is at the top. Reductions in productcost and delivery time, improvement in product quality are at the second level.Reduction in lead time and customer involvement are at the third level. Effectiveimplementation of AMTs is at fourth level. The remaining variables are at thelower levels. This finding implies that effective implementation of AMTs willhelp in reducing lead time, product cost and delivery time and in improvingproduct quality. Finally, all these factors will help in improving performance ofthe organization.

. Top management commitment and sound financial condition are at the bottomlevel with highest driving power. It means top management commitment andsound financial condition are the major drivers for successful implementation ofAMTs.

The variables with higher driving powers are more of the strategic orientation. On theother hand, the dependent variables are more towards performance orientation. Thus,performance can be improved by continuously improving the driving variables. On thebasis of these levels and driving power, management needs to address these drivingvariables more carefully. In this process, management should also consider therelationship between investment in technology and performance improvement, whichfollows S-curve. According to which as funds are put into new technology, progress isslow. Then, as research uncovers the key pieces of information necessary to make theadvances, the pace surges, Finally, progress slows down again and each successiveinnovation requires a greater outlay of resources. Ultimately, the S-curve levels offentirely, i.e. when the technology approaches some fundamental limit. It is important topay attention to such limits. They are the best clues a manager has for recognizingwhen a new technology must be developed within the company. The important thing,therefore, is selection of timing and appropriateness of technology as per marketrequirements and competitors’ strengths.

Adoption of AMT is a type of innovation that is positively associated with companysize (Sohal et al., 2006). Therefore, level of AMTs implementation may differ betweensmall and large-scale organizations. Authors of the view that an organization shouldimplement new technology when competitors’ technology is at the saturation level or indeclining phase, as it will give competitive edge over others. Today technologicaldiscontinuities continue with increasing frequency, but during these discontinuities theorganizations implementing new technology may have the advantage. In such kind ofenvironment, organizations will have to innovate in new technologies, not once or twicein a decade, but continuously. This will be only possible if top management developcompetitive strategies in a holistic manner. These strategies should focus on enablersand results such as organization culture, employees training, vendor development,integration of departments, product quality, cost and lead-time, etc. According to Boyerand Pagell (2000), new capabilities from AMTs implementation can be only realizedwhen companies make infrastructural investments such as quality leadership, trainingand empowerment of employees. In this process, sound financial condition will alsoplay a crucial role because without finance, organizations will not be able to take

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crucial decision of technology implementation. Therefore, in implementing innovativetechnologies, SMEs may feel some constraints due to their limited resources. In thisscenario, SMEs should develop strategies for collaborative use of technologicalresources and expertise with other organizations as it will reduce the risk of failure.Effective and economical implementation of AMTs will help SMEs in improving theirperformance in global market also.

5. Concluding remarksThis paper has tried to identify the critical factors for successful implementation ofAMTs by organizations to improve their performance. Better performance oforganization on different measures in comparison to its competitors will lead to itscompetitiveness in the market. Successful implementation of AMTs depends ondifferent factors related with technical expertise, resources, processes, managementsystems and performance. In this context, total 14 factors were identified in presentstudy. For establishing relationship between these critical factors, ISM approach hasbeen applied. It has also helped in determining driving and dependence power of allvariables. It is observed that top management commitment and sound financialcondition are the major drivers for implementing AMTs. Effective implementation ofAMTs will improve organisation performance in terms of lead time, product cost, fastdelivery and product quality. For effective implementation of AMTs, managementshould not ignore managerial aspects such as organization culture, employees training,integration of departments, vendor development, strategy development and customerinvolvement.

It has to be noted here that in this analysis it is presumed that cost effectivetechnologies are available in the market. However, these findings will be immenselyhelpful for industry professionals in developing strategies for successfulimplementation of AMTs. In this research, through ISM, a relationship modelamong different critical factors has been developed on the basis of experts’ opinion.Structural equation modeling, also commonly known as linear structural relationshipapproach has the capability of testing the validity of such hypothetical model.Therefore, it may be applied in the future research to test the validity of this model.

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About the authorsRajesh K. Singh is a Senior Lecturer in Mechanical Engineering Department at Delhi College ofEngineering, Delhi, India. His areas of interest include competitiveness, small businessmanagement, technology management and quality management. He has published papers injournals such as International Journal of Productivity and Performance Management, SingaporeManagement Review, International Journals of Productivity and Quality Management,Competitiveness Review, Global Journal of Flexible Systems and Management, International


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Journal of Services and Operations Management, South Asian Journal of Management,International Journal of Global Business and Competitiveness, Productivity, IIMB ManagementReview and Productivity Promotion. Rajesh K. Singh is the corresponding author and can becontacted at: [email protected]

Suresh K. Garg is a Professor in Mechanical Engineering Department at Delhi College ofEngineering, Delhi, India. His areas of interest include competitive strategies, JIT manufacturingsystems, quality management, technology management and supply chain management. He haspublished sixty papers in international and national journals/conferences such as InternationalJournal of Manufacturing Technology and Management, International Journal of ProductionEconomics, Competitiveness Review, International Journals of Productivity and QualityManagement, International Journal of Services and Operations Management, Journal ofModelling in Management, IIMB Management Review, Global Journal of Flexible Systems andManagement and Productivity. E-mail: [email protected]

S.G. Deshmukh is a Professor in Mechanical Engineering Department at Indian Institute ofTechnology, Delhi India. His major research interests include manufacturing management,supply chain management, technology management and quality management. He has a long listof papers published in reputed international and national journals such as International Journalof Operations and Production Management, International Journal of Production Research,Competitiveness Review, International Journal of Manufacturing Technology and Management,Production Planning and Control, International Journal of Production Economics, InternationalJournals of Productivity and Quality Management, International Journal of Services andOperations Management, IIMB Management Review, etc. He is also on the editorial board ofreputed international journals. E-mail: [email protected]

Mohendra Kumar is a Management Trainee at Steel Authority of India Ltd, India. He hasdone his post graduation in Production and Industrial Engineering. His areas of interest aretechnology management, quality management and non destructive testing. He has presentedpapers in reputed international and national conferences. E-mail: [email protected]

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Modelling of critical success factors for implementation of AMTs

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