MODELLIN

G THE CRITICAL SUCCESS

FACTORS FOR ADVANCED MANUFACTURING

TECHNOLOGY IMPLEMENTATION IN SMALL

AND MEDIUM SIZED ENTERPRISES

Dattatraya V Bhise

Department of Mechanical Engineering, JSPM Narhe Technical Campus, Pune, (India).

E-mail: dvbhise@gmail.com

Sumant A. Choudhari

Department of Civil Engineering, JSPM Narhe Technical Campus, Pune, (India).

E-mail: sumant.choudhari@gmail.com

Manoj A. Kumbhalkar

Department of Mechanical Engineering, JSPM Narhe Technical Campus, Pune, (India).

E-mail: manoj.kumbhalkar@rediffmail.com

Mhalsakant M. Sardeshmukh

Department of Electronics and Telecommunication Engineering, JSPM Narhe Technical Campus,

Pune, (India).

E-mail: mmsardeshmukh2016@gmail.com

Reception: 28/11/2022 Acceptance: 13/12/2022 Publication: 29/12/2022

Suggested citation:

Bhise, D., Choudhari, S. A., Kumbhalkar, M. A., y Sardeshmukh, M. M. (2022). Modelling the critical success

factors for advanced manufacturing technology implementation in small and medium sized enterprises. 3C

Empresa. Investigación y pensamiento crítico, 11(2), 263-275. https://doi.org/

10.17993/3cemp.2022.110250.263-275

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ABSTRACT

In almost every part of the world, small and medium-sized businesses (SMEs) are seen as the

backbone of economic expansion. Small and medium-sized enterprises (SMEs) typically have a

simpler organisational structure than large corporations, which allows them to be more adaptable,

provide instantaneous feedback, have shorter decision-making chains, and respond more quickly to

customer needs. Even so, SMEs face enormous pressure to stay competitive in both domestic and

international markets. Globalization, new technologies, and evolving consumer preferences are all

contributing to a shift in the competitive landscape. These shifts are compelling small and medium-

sized enterprises to adopt cutting-edge manufacturing techniques. The goal of this research is to

identify the critical success factors (CSFs) that will help and guarantee that SMEs will be able to

successfully implement AMTs (SMEs). Literature-based CSFs for AMT deployment are collected and

fine-tuned using input from professionals in the field and scholars in the academy. The method of

interpretive structural modelling (ISM) is applied to this CSF analysis. According to the ISM study, the

three most important factors influencing the adoption of AMT are "Top management support and

commitment," "entrepreneurial environment," and "financial availability." The desired goal of AMT

implementation is found to be "performance improvement" and "sustainable AMT implementation."

The identified CSFs and the structural relationship between them will help SMEs' top management

create and prioritise business strategies that ease the implementation of AMT. The study's results point

potential AMT financiers in the right direction by highlighting a handful of critical considerations that

will improve the project's chances of success.

KEYWORDS

Small And Medium-Sized Enterprises (SMES), Advanced Manufacturing Technologies (AMTS),

Success Factors, Interpretive Structural Modeling (ISM), MICMAC Analysis.

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1. INTRODUCTION

Today's businesses should be better prepared than ever to meet the challenges of a highly competitive

market. Therefore, in today's world of ever-increasing competition, they must overcome the difficulty

of discovering novel ways to boost their efficiency and effectiveness. Failure to rise to this challenge

may prevent businesses from fortifying their position against rivals or expanding into new markets.

Many factories are now using AMT to improve their competitiveness [1, 2]. It is possible that SMEs

could benefit from AMT implementation if they had a better understanding of and ability to manage the

drivers and barriers. They might be able to improve their efficiency as a result. There is substantial

evidence in the literature that AMT implementation has helped organisations improve their operational

and economic performance [3]. But in most cases, companies that have already implemented AMTs fail

to see the expected benefits. This may be due to the fact that, in many cases, organisations overlook

crucial aspects of AMT implementation that would improve its success. Critical success factors (CSFs)

of AMT implementation refer to these actions. To succeed in a competitive environment, one must

focus on a small number of critical success factors (CSFs). CSFs are the "things must go right" areas of

a business that are essential to the achievement of the manager's goals. [4]. Thus, the CSFs approach is

an effort to disentangle factors that are vital to project management's success [5]. When considered in

the context of their significance at each stage of the implementation process, these CSFs take on a much

richer meaning, helping to push the boundaries of process improvement. In this research, critical

success factors (CSF) refer to anything considered important for the effective use of AMTs by Indian

SMEs.

Small and medium-sized enterprises (SMEs) are the backbone of India's manufacturing sector (SMEs).

Small and medium-sized enterprises (SMEs) in India are responsible for 43% of the country's industrial

output and 40% of its exports. [7]. For India's economy to thrive and for new jobs and growth to be

created over the long term, small and medium-sized enterprises (SMEs) must undergo a process of

industrial modernization. These small and medium-sized enterprises (SMEs) face internal and external

challenges as they adopt new technologies. [8].

Compared to large industries, which are more efficient at scale but slower to adapt to innovations, small

and medium-sized businesses (SMEs) are more nimble when it comes to technology and niche markets.

[9]. Since the decision to invest in AMT is so important, SMEs need to think through the entire

implementation process before making a final decision.

Although the technical capabilities of AMTs are well established, a framework for effective

implementation has not been agreed upon by practitioners or academics. The reason for this is that

researchers have yet to identify all of the factors that either help or hurt when trying to implement AMT.

Therefore, in order to hasten the spread of advanced manufacturing, it has been decided to study the

factors that contribute to the success of implementing advanced manufacturing technology in small and

medium-sized businesses. The connections between AMT factors and firm performance are of critical

strategic importance. Potential investors who are thinking about investing in AMTs in the future can use

the information gleaned from this study. Further, business leaders who take the time to comprehend

these connections will have an easier time crafting efficient strategies for managing technology within

the company.

2. RESEARCH METHODOLOGY

This study employed the following research methodology: I A comprehensive literature review of

success factors for AMT implementation in SMEs. To learn more about how SMEs in India are using

AMT, a questionnaire-based survey was conducted. To analyse the survey questionnaire data, the

researchers used SPSS (20.0). There were two primary methods used to examine the data. The data was

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initially put to use for broad statistical purposes. Second, the proposed relationship between the

business environment, competitiveness, and firm performance was tested using the standard Pearson

correlation test. To model the intricate web of causality linking the most crucial factors influencing the

adoption of AMT, the interpretive structural modelling (ISM) method is employed. The authors hope to

determine which factors have the greatest impact on whether or not an AMT is adopted by using this

method. With ISM, the chaos of such variables can be brought under control. v) Creating a framework

for identifying the critical success factors for implementing AMT in SMEs. vi) The scope of each driver

of the AMT implementation practise is critically examined using a Matrice d Impacts Croises -

Multiplication Applique'and Classment (MICMAC) analysis. When conducting a MICMAC analysis,

the significance of a variable is not determined by the strength of its direct relationships but rather by

the number and types of indirect relationships it has. Understanding how different factors affect the

whole system is revealed. The analysis's purpose is to categorise variables according to their driving

and dependent powers.

3. ISM BASED MODELLING OF THE OF CRITICAL SUCCESS

FACTORS OF AMT IMPLEMENTATION

This section included an Interpretive Structural Modeling of the important success criteria of AMT

implementation in the context of Indian SMEs. The model can be employed to rank and understand the

complex nature of hierarchy and explore the relationship existing among the critical success factors.

3.1. IDENTIFICATION OF CRITICAL SUCCESS FACTORS FOR AMT

IMPLEMENTATION

Eighteen success factors are collected from literature survey and calibrated by industry experts and

academicians are listed as follows:

Table 1: Success factors for AMT implementation.

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3.2. (SSIM) FOR CRITICAL SUCCESS FACTORS

Through the use of expert consultation and the identification of contextual relationships between the success

factors included in the system, a structural self-interaction matrix for the critical success factors is developed. A

'leads to' type contextual relationship is selected to examine the interplay of the success factors. For instance, a

"favourable company image" can result from "better quality." The interrelationships of the variables in their

context are constructed in a similar fashion. The existence of a relation between any two variables I and j) and the

direction of the relation are questioned, while taking into account the contextual relationship for each variable.

There are four signs used to indicate the directional relationship between the I and j variables:

P: The stress caused by I will be reduced by j.

The two variables, I and j, will mutually alleviate one another, as shown in (A) and (X).

O: There is no connection between I and j.

The SSIM is built around the contextual relationships of the 18 variables found to be most important for the AMT

implementation practises of Indian SMEs. The SSIM of critical success factors is shown in table 2.

Table 2: Structural self-interaction matrix of critical success factors.

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3.3. DEVELOPMENT OF REACHABILITY MATRIX FOR CRITICAL

SUCCESS FACTORS

If you want to create a reachability matrix using SSIM, you'll need to have a firm grasp on transitivity

and reachability. These are the two main tenets of the ISM then 'k' is also related to I this is what is

meant by 'transitivity. The transitive property helps maintain internal coherence in one's ideas. The ISM

methodology relies on the reachability concept. Element pairs with different identifications are

compared with one another in terms of their interconnection. This data is represented as a binary

matrix. If the ith factor aids in achieving the jth factor, then the cell I j) of the reachability matrix is

assigned a 1, otherwise it is assigned a 0. (i, j). Moreover, some of the cells in the reachability matrix

can be filled inductively thanks to the transitivity property [24]. Matrix entries I j) = 1 and (j, k) = 1

imply I k) = 1 because of the identity between the two variables. By exchanging 1s and 0s for Vs, As,

Xs, and Os in the SSIM, we obtain a binary matrix we refer to as the initial reachability matrix. Rules

for exchanging ones and zeros are as follows:if the (i, j) entry in the SSIM is V, then the (i, j) entry in

the reachability matrix becomes 1 and the (j, i) entry becomes 0.

•if the (i, j) entry in the SSIM is A, then the (i, j) entry in the reachability matrix becomes 0 and

the (j, i) entry becomes 1.

•if the (i, j) entry in the SSIM is X, then the (i, j) entry in the reachability matrix becomes 1 and

the (j, i) entry becomes 1.

•if the (i, j) entry in the SSIM is O, then the (i, j) entry in the reachability matrix becomes 0 and

the (j, i) entry also becomes 0.

Following these guidelines, the AMT drivers' initial reachability matrix is determined, and the final

reachability matrix is obtained by incorporating the transitivities, this is shown in table 3. In this table,

the driving power and dependence of each variable are also shown. The driving power of a particular

variable is the total number of variables (including itself), which it may help to achieve while the

dependence is the total number of variables, which may help to achieve it.

Table 3: Reachability matrix for critical success factors.

CSF 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

C1 X V X V V V V V V V V V V V V V V V

C2 A X A V V V V V V V V V V V V V V V

C3 X V X V V V V V V V V V V V V V V V

C4 A A A X A A A A A A V A A O A O V O

C5 A A A V X A A A V V V V V V A O V O

C6 A A A V V X V V V V V V V V X V V V

C7 A A A V V A X X V V V V V V A V V V

C8 A A A V V A X X V V V V V V A V V V

C9 A A A V A A A A X V V X V V A O V O

C10 A A A V A A A A A X V A X V A O V O

C11 A A A A A A A A A A X A A A A A V A

C12 A A A V A A A A X V V X V V A O V O

C13 A A A V A A A A A X V A X V A O V O

C14 A A A O A A A A A A V A A X A O V O

C15 A A A V V X V V V V V V V V X V V V

C16 A A A O O A A A O O V O O O A X V V

C17 A A A A A A A A A A A A A A A A X A

C18 A A A O O A A A O O V O O O A A V X

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3.4. LEVEL PARTITIONS OF THE REACHABILTY MATRIX OF CRITICAL

SUCCESS FACTORS

Using the final reachability matrix, we can establish the reachability and antecedent set of each factor.

The antecedent set includes the element and any other elements that could be useful in achieving the

goal, while the reachability set includes the element and any other elements that could be useful in

reaching the goal. Next, we calculate the intersection of these sets across all variables. The root of the

ISM is the element for which the reachability and intersection sets are identical. Nothing below the top-

level element in the hierarchy could be achieved with the help of the top-level element. Separation from

the other elements occurs after the top-level element has been identified. The same method is then used

to uncover the following tier of elements. Incorporating these discovered levels into the diagraph and

ultimate model is beneficial. Each critical success factor's position in the ISM-based hierarchical model

was determined by first partitioning the reachability matrix into different levels. A total of 10 cycles

were used to determine where each success factor stood in the system. Table 4 displays the first

iteration's results, which show that the performance enhancement factor C17 is the most important

variable in the underlying ISM model. In table 4, the results of iterations II through X are displayed,

revealing the remaining success factors and their relative levels of rest. The ISM digraph and final

model were constructed using the identified variable levels.

Table 4: Results of iteration I of the level partitions of the reachability matrix of critical success factors.

CSF1234567891011 12 13 14 15 16 17 18 DP

C1 11111111111111111118

C2 01011111111111111116

C3 11111111111111111118

C4 0001000000100000103

C5 0001100011111100109

C6 00011111111111111115

C7 00011011111111011113

C8 00011011111111011113

C9 0001000011111100108

C10 0001000001101100106

C11 0000000000100000102

C12 0001000011111100108

C13 0001000001101100106

C14 0000000000100100103

C15 00011111111111111115

C16 0000000000100001114

C17 0000000000000000101

C18 0000000000100000113

DPD 2 3 2 13 8 5 7 7 10 12 17 10 12 13 5 8 18 9 163

CSF Reachability set Antecedent set Intersection Level

C1 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18 1,3 1,3

C2 2,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18 1,2,3 2

C3 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18 1,3 1,3

C4 4,11,17 1,2,3,4,5,6,7,8,9,10,12,13,15 4

C5 4,5,9,10,11,12,13,14,17 1,2,3,5,6,7,8,15 5

C6 4,5,6,7,8,9,10,11,12,13,14,15,16,17,18 1,2,3,6,15 6,15

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Table 5: Results of iteration II-X of the level partitions of the reachability matrix of critical success factors.

3.5 FORMATION OF HIERARCHICAL MODEL

The structural model of the critical success factors is constructed using the level partition shown in

table 4 and table 5, and the final digraph is developed by removing the transitivity as discussed in the

ISM methodology. The digraph is finally transformed into the ISM as shown in Figure 2. ‘Top

management support and commitment’ (C1), ‘entrepreneurial environment’ (C3) lead to ‘finance

availability’ (C2). ‘Finance availability’ leads to ‘clear and long term AMT objectives’ (variable 6),

‘technical know- how’ (C15), which in turn leads to ‘operations strategy’ (C8), ‘linking business and

C7 4,5,7,8,9,10,11,12,13,14,16,17,18 1,2,3,6,7,8,15 7,8

C8 4,5,7,8,9,10,11,12,13,14,16,17,18 1,2,3,6,7,8,15 7,8

C9 4,9,10,11,12,13,14,17 1,2,3,5,6,7,8,9,12,15 9,12

C10 4,10,11,13,14,17 1,2,3,5,6,7,8,9,10,12,13,15 10,13

C11 11,17 1,2,3,4,5,6,7,8,9,10,11,12,13,1

4,15,16,18

C12 4,9,10,11,12,13,14,17 1,2,3,5,6,7,8,9,12,15 9,12

C13 4,10,11,13,14,17 1,2,3,5,6,7,8,9,10,12,13,15 10,13

C14 11,14,17 1,2,3,5,6,7,8,9,10,12,13,14,15 14

C15 4,5,6,7,8,9,10,11,12,13,14,15,16,17,18 1,2,3,6,15 6,15

C16 16,17,18,11 1,2,3,6,7,8,15,16 16

C17 17 1,2,3,4,5,6,7,8,9,10,11,12,13,1

4,15,16,17,18

17 I

C18 17,18,11 1,2,3,6,7,8,15,16,18 18

CSF Reachability set Antecedent set Intersection Level

C1 1,3 1,3 1,3 X

C2 2 1,2,3 2 IX

C3 1,3 1,3 1,3 X

C4 4 1,2,3,4,5,6,7,8,9,10,12,13,15 4 III

C5 5 1,2,3,5,6,7,8,15 5 VI

C6 6,15 1,2,3,6,15 6,15 VIII

C7 7,8 1,2,3,6,7,8,15 7,8 VII

C8 7,8 1,2,3,6,7,8,15 7,8 VII

C9 9,12 1,2,3,5,6,7,8,9,12,15 9,12 V

C10 10,13 1,2,3,5,6,7,8,9,10,12,13,15 10,13 IV

C11 11 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 11 II

C12 9,12 1,2,3,5,6,7,8,9,12,15 9,12 V

C13 10,13 1,2,3,5,6,7,8,9,10,12,13,15 10,13 IV

C14 14 1,2,3,5,6,7,8,9,10,12,13,14,15 14 III

C15 6,15 1,2,3,6,15 6,15 VIII

C16 16 1,2,3,6,7,8,15,16 16 IV

C17 17 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18 17 I

C18 18 1,2,3,6,7,8,15,16,18 18 III

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manufacturing strategy’ (C7). Put together these variables leads to ‘sustainable AMT

implementation’ (variable 11) which ultimately leads to ‘performance improvement’ (variable C17).

3.5 MICMAC ANALYSIS OF THE CRITICAL SUCCESS FACTORS

The critical success factors are categorized into four groups ‘autonomous variables’ (Cluster-I)

‘dependent variable’ (cluster-II), linkage variables (cluster-III) and independent variable (cluster-IV)

through MICMAC analysis. The analysis requires construction of a driving power-dependence

diagram (figure 3). Horizontal axis of this diagram represents the dependence potential while the

vertical axis represents the driving potential of the critical success factors. Allocation of the critical

success factors into different clusters of the driving power-dependence diagram is done based upon

their driving and dependence potential values represented in table 3. For example, it is found from

table 3, that ‘top management support and commitment’ (variable 1), entrepreneurial environment

(variable 3) have a driving power of 18 and a dependence of 2; therefore, the factors are placed at a

position corresponding to driver power of 18 and dependency of 2, in driving-dependence power

diagram (figure 3). Similarly, factor 2 (finance availability), has driving power of 16 and dependence

of 3 therefore, in figure 3, the factor is positioned at a place corresponding to driver power of 16 and

dependency of 3. The factors ‘sustainable AMT development’, ‘performance improvement’,

‘technology champion’, ‘cross functional implementation team’ ‘employee training’, ‘Employee

communication, participation and empowerment’ ‘technology know-how, ‘customer involvement’,

‘absorptive capacity’ and ‘high level system integration’ are positioned in cluster-II, which indicates

that these have strong dependence and weak driving power. Similarly, the variables ‘top management

support and commitment’, ‘entrepreneurial environment’, ‘finance availability’ are placed in fourth

cluster, which is an indication of their strong driving potential and weak dependence.

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Figure 3: Driving power dependence diagram of the critical success factors.

4. DISCUSSION AND MANAGERIAL IMPLICATIONS

Implementation of AMT is a complex and difficult phenomena. Complexity of AMTs implementation

is due to its dependency on several criteria. For effective AMT implementation all the relevant criteria

have to be identified and the existing interrelationship between them has to be understood. This

research has made an attempt to identify various success criteria for AMT implementation in Indian

SMEs and used ISM approach to evaluate the critical success factors. The following managerial

implications emerge from this study.

•The study explored a validated measure of 18 success factors of AMT implementation specific

to Indian SMEs. Prior knowledge of these factors can be useful for the SMEs to consider a

wide range of factors instead of focusing on few factors for successful AMT implementation.

•

Interrelationships among the critical success factors were identified using a logical structure

developed through ISM that can help managers to better prioritize their available resources

while trying to bring desired changes in strategic adjustments that are necessary for

improvements in AMT implementation practices.

•

The driver power-dependence diagram (figure 3) indicates that ‘customer involvement’ and

‘vendor development’ are autonomous factors in this study. Autonomous variables generally

appear as weak driver as well as weak dependent and are relatively disconnected from the

system. These variables do not have much influence on the other variables of the system.

•

Figure 3 (driver power-dependence diagram) shows factors placed in cluster II. The factors

identified as dependent variables and have weak driving potential but strong dependence

power.

•

There is no factor positioned in the third cluster. The absence of linkage variables indicates

that no identified critical success factor is unstable in nature.

Further, it can be observed from figure 3 that the variables that are positioned in fourth cluster are

having strong driving power and weak dependence. These variables demand treatment of these factors

as key drivers for an effective AMT implementation. Owners/managers of SMEs and practitioners

should give priority while addressing these factors to achieve AMT implementation success.

The key findings of the present research are:

‘Top management support and commitment’, ‘entrepreneurial environment’ and ‘finance availability’

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are positioned at the bottom of ISM based hierarchy are the critical success factors of the AMT

implementation process. The factor ‘performance improvement’ occupies the highest hierarchical level

and ‘sustainable AMT implementation’ is placed below it in the hierarchy. These factors represent the

desired objective of successful AMT implementation. For obtaining these objectives the bottom level

variables should be improved continuously.

5. CONCLUSION

AMT implementation has been viewed by SMEs as a significant step forward in their quest to stay

competitive. However, it has been said that SMEs' inadequate resources and skills prevent them from

using AMTs effectively, which is why the acceptance rate of AMT in Indian SMEs is uninspiring. It

has been observed that most of the companies hesitate to adopt full integration whereas others adopt it

partially. This could be due to the fact that the organizations that have adopted AMTs have shown

mixed results. In this regard the knowledge of the potential critical success factors and their relative

importance on effectiveness of AMT implementation practices, explored in this study could be

beneficial for the organizations trying to implement AMTs in their plants. This research work has

identified and prioritized the critical success factors that have to be considered for successful

implementation of AMTs in Indian SMEs.

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