identifying the most influencing success factors of tqm

Proceedings of the International Conference on Industrial Engineering and Operations Management Dubai, UAE, March 10-12, 2020

© IEOM Society International

Identifying the Most Influencing Success Factors of TQM Implementation in Manufacturing Industries using

Analytical Hierarchy Process

Pardeep Gupta1, Ankesh Mittal2 1,2 Department of Mechanical Engineering, Sant Longowal Institute of Engineering and

Technology, Longowal, Sangrur (Punjab), India-148106 [email protected], [email protected]

Abstract

TQM implementation serves the purpose of achieving business excellence which eventually leads to customer satisfaction, increased profits and higher production for the organization. The purpose of this paper is to investigate the most important success factors of TQM and study its comparative importance for enhanced execution in manufacturing industries. In this study a broad literature review was done to identify and prepare the list of success factors for sustaining TQM implementation. Analytic hierarchy process is used to assign the relative importance and ranking the identified success factors of TQM in perspective manufacturing industries. The finding of study demonstrates that ‘Top management commitment’ ranked number one and this factor is fundamental for implementing TQM initiatives successfully. The success factors ‘education and training’ and ‘rewards & recognition’ ranked at second and third positions which need special attention while performing TQM activities in a more effective manner. The results also propose a general hierarchy model for judging the relative importance of success factors that would influence implementation of TQM.

Keywords Total Quality Management, Top Management Commitment, Success Factors, Manufacturing, TQM implementation

1. IntroductionIn the current circumstances of fiercely competitive environment, different business management tools such as Total Quality Management (TQM), Total Productive Maintenance (TPM), Six-Sigma, Just in Time (JIT), etc. are used by many organizations to improve their operational capabilities. In TQM, the organizations used to deploy some statistical and management tools for enhancing organizational capabilities through continuous improvement approach (Ismyrlis and Moschidis, 2015; Ismyrlis, 2017; Silombela et al., 2018). Total Quality management is indeed a joint effort of management, staff members, workforce, suppliers and dealers in order to meet and exceed customer satisfaction level (Prajogo and Sohal, 2003; Singh and Smith, 2004; Thai Hoang, Igel and Laosirihongthong, 2006). Another definition, Total quality management is a continuous endeavor by employees to continuously enhance (Yang, 2006; Prakas and Murali, 2016) the quality of their products and services through customers’ feedback. Total Quality management is indeed a joint effort of management, staff members, workforce, suppliers and dealers in order to meet and exceed customer satisfaction level. In today’s competitive environment, customer satisfaction is a most important concern for all type of organizations (Choi and Eboch, 1998; Reed et al., 2000; Ugboro and Obeng, 2000). TQM attempts to incorporate all the organizational activities like marketing, quality, finance, design, engineering, production and customer service to focus on meeting customer demands and organizational objectives (Soltani and Wilkinson, 2018; Sahoo, 2019). TQM not only improve the business performance of the companies but also boost the morale and skill of the employees.

A number of good researchers have emphasized many success factors like leadership commitment, employee participation, financial resources, suppliers, communication, customer focus, process approach etc. that are essential to effective deployment of TQM implementation in any organization (Kaynak 2003; Rao et al. 2004 and Baird et al. 2011). TQM is not just a management philosophy but a culture of an organization dedicated towards continuous

541

mailto:[email protected]

mailto:[email protected]



improvement and customer satisfaction (Mohammad 2005, Talib et al. 2011). On the other hand implementation of TQM success factors is not easy task and its results are not easy to get (Mohammad 2005, Talib et al. 2011). Thus it is very important for any organization that implementation of these TQM success factors in well structured manner, to achieve employee fulfillment, customer satisfaction, better financial results and business performance (Ashok and Santhakumar 2002; Verma and Rathod 2014). To get maximum benefits and preferred results, priority of these TQM success factors is essential. In order to find out the importance of TQM success factors, the present study exercises an analytic hierarchy process (AHP) approach. The main objective of present study is to identifying the most essential success factor during the TQM implementation in a leading tractor manufacturing company of India. The subsequently sections deal with the literature review followed by identification of TQM success factors. An introduction to AHP is discussed and the comparative significance of the success factors is evaluated by using the AHP approach in the succeeding section. Lastly, results on findings are presented followed by conclusion. 2. Literature review

A broad literature review of the preceding studies on TQM have studied about the concept of TQM and the important success factors for successful implementation of TQM in any organization. Success factors are a set of significant elements that help the organization in achieving its objectives for better business performance. The focus of present study literature review was on the investigation of those critical success factors of TQM implementation that result in improved productivity, market position, sales volume and customer satisfaction particularly in manufacturing industries. In order to investigate the success factors of TQM implementation, various literature has been studied from different areas like from quality Guru’s (Crosby, 1979; Deming, 1982; Ishikawa, 1985; Juran, 1988; Feigenbaum, 1991), quality awards (Malcolm Baldrige National Quality Award, The Deming Award, European Quality Award, Rajiv Gandhi National Quality Award) and from practical research (Kohli and Singh 2015; Sahoo and Yadav 2017; Knol et al. 2018). These studies give a good number of success factors important for implementation of TQM. The success factors identified from the TQM literature are presented in Table 1.

Table 1. TQM Success factors with their references/sources

S.No. SUCCESS FACTORS SOURCES

1. Top Management Commitment

Deming, 1982; Oakland (1993); Flynn et al. (1994); Ahir et al. (1996); Schmitz & Platts, 2004; Li et al. (2005); Ho Voon et al. (2014); Talib et al. (2013); Singh and Sushil (2013); Psomas and Jaca (2016)

2. Continuous Improvement Ho Voon et al. (2014); Talib et al. (2013); Singh and Sushil (2013)

3. Supplier Quality Oakland (1993); Ahir et al. (1996); Samson and Terziovska, (1999); Kayank, 2003; Talib et al. (2013)

4. Customer Focus Deming, 1982; Oakland (1993); Flynn et al. (1994); Ahir et al. (1996); Samson and Terziovska, (1999); Li et al. (2005); Ho Voon et al. (2014); Talib et al. (2013); Singh and Sushil (2013); Psomas and Jaca (2016)

5. Rewards and Recognition Ahir et al. (1996); Talib et al. (2013)

6. Education and Training Deming, 1982; Ahir et al. (1996); Ho Voon et al. (2014); Talib et al. (2013); Singh and Sushil (2013); Psomas and Jaca (2016)

7. Total Employee Participation

Deming, 1982; Ahir et al. (1996); Samson and Terziovska, (1999); Kayank, 2003; Ho Voon et al. (2014); Talib et al. (2013); Psomas and Jaca (2016)

8. Review & Monitoring Oakland (1993); Ahir et al. (1996); Samson and Terziovska, (1999); Kayank, 2003; Li et al. (2005); Talib et al. (2013);

9. Quality Management Deming, 1982; Ho Voon et al. (2014); Talib et al. (2013)

10. SPC Usage Ishikawa, 1985; Oakland (1993); Ahir et al. (1996); Ho Voon et al. (2014); Haridy et al. 2017; Baker et al. 2018

11. Quality Citizenship Oakland (1993); Ahir et al. (1996)

12. Process and Product Design

Oakland (1993); Ahir et al. (1996); Kayank, 2003; Talib et al. (2013); Singh and Sushil (2013)

13. Benchmarking Ahir et al. (1996); Talib et al. (2013); Singh and Sushil (2013)

14. Communication Oakland (1993); Ahir et al. (1996); Kayank, 2003; Ho Voon et al. (2014); Talib et al. (2013); Psomas and Jaca (2016)

542



15. Strategic Planning and Management

Deming, 1982; Oakland (1993); Flynn et al. (1994); Samson and Terziovska, (1999); Kayank, 2003; Li et al. (2005); Talib et al. (2013)

2.1 Identification of TQM Success factors

The most prominent success factors for implementing TQM in manufacturing industries are identified using literature review and discussion with professionals and academician. The identification and establishing the interrelationship among the critical success factors through AHP is discussed in this paper. First the TQM implementation success factors (as shown in Table 1) were identified using the literature review and then the eight most prominent success factors were sorted out after discussion with the TQM professionals and academicians. The success factors play a very crucial role in order to achieve business goals and organizational effectiveness (Tseng & McLean, 2008). The following are the eight identified success factors as:

1. Top Management Commitment: Management commitment is vital not only for talking the business objectives and strategies, but also for providing direction and motivation to the employees of the organization (Dale, 1999; Nist, 2000; Kanji, 2002).

2. Rewards and Recognition: Rewards and Recognition can be formal or informal (Crosby, 1998). They provide energy for retaining passion for implementing quality initiatives. Moreover every organization to have rewards and recognition joined with the performance success and employees skills (Harrington 1998).

3. Education and Training: Education and training gives knowledge and skills to employees in order to meet

their work and individual objective. A booming education and training curriculum would generate more positive employee attitude in terms of loyalty and helping nature in their individual growth and job participation (Mellat et al. 2011). Further, Stahl (1995) stresses education and training as the important factor that helps in organizing employees in the direction of managing the TQM philosophy in the process of manufacturing.

4. Total Employee Participation: According to Logothetis (1992) with the total employee participation,

organizations can boost employee’s capability to solve the problems and exploit opportunities. Arumugam et al. (2008) stressed as total employee involvement is a major success factor to develop a partnership between employees and managers.

5. Review & Monitoring: To increase the quality and service, information from customers, competitors and suppliers should be gather in well-organized way. Sila and Embrahimpoor, (2002) examined that quality review & monitoring is positively associated with organizational performance.

6. Strategic Planning and Management: Strategic planning and management combines the improvement and

exploitation of plans, which develop the relationship with stakeholders (Tseng & McLean, 2008). To achieve good financial and organizational results long term policy is supposed to be undoubtedly identified and efficiently passed throughout the organization (Peters, 1998; Brah et al. 2002).

7. Quality Management: A good quality culture crafts a feeling on the customer regarding the company

(Bitner, 1992; Curry & Kadasah, 2002). Quality management is essential for as long as employee empowerment that shows employees to focus on quality and examine their individual errors (Ahire, Golhar, & Waller, 1996).

8. Communication: A proper communication can facilitate the whole organizational employee to manage the

priorities. The stream of information between employees and machines for purposes such as monitoring, safety, maintenance, and analytics is essential to maximizing the organizational efficiency (Talib et al. 2013).

3. AHP Methodology

543



According to Saaty (1980) Analytic hierarchy process (AHP) is one of the qualitative techniques. AHP is a universal judgmental approach for resolving complexes and problems (Saaty 1988). AHP is intended to decompose a multifarious problem into various intermediate steps of hierarchy structure (Crowe, Noble, & Machimada, 1998; Saaty, 1980). In order to explore the most influencing success factors of TQM implementation in manufacturing industries this study uses the AHP methodology. With the assist of professionals and academician judgments the priorities between all the success factors is formulated. With professional’s proficiency pair wise evaluation results are applied to pairs of homogenous criteria (Saaty, 1980). AHP can lodge both objective and sub objective results of the professionals concerned in order to determine priority among the different factors. The process flow chart concerning different steps to conduct the AHP study is shown in Figure 1.

Figure 1. Process Flow to perform AHP methodology 4. Case study (To investigate the impact of TQM success factors)

No

Yes

Objective of the Study

Development of hierarchical framework

Collection of empirical information

Degree of preference and development of pair wise

comparison matrix

Is pair-wise comparison consistent?

Calculate the priority weight and Eigen vector for each

success factor

Integrate results and improve TQM implementation

544



The AHP technique is widely applied in many areas with diverse applications. Application of AHP technique to examine priority and ranking in different areas is well documented in literature as shown in Table 2.

Table 2. Different application areas using AHP

Author (Year) Application (Area) Fong and Choi (2000) Contractor selection Wedley, Choo, and Schoner (2001) Cost Analysis benefit Lewis, Pun, and Lalla (2005) Determination of TQM benefits in SMEs Lam, Poon, and Chin (2008) Learning model for education Chen et al. (2009); Salomon et al. 2019 Aviation safety Mohajeri and Amin (2010) Railway station site selection Chen and Fan (2009) Corporate social responsibility Pourghasemi et al. 2012; Rahaman et al. 2015 Geographical Information Önder et al. 2013 Banking Sector Šoltés and Gavurová (2014) Health care systems Saito et al. 2015 Animal disease response activities Goyal and Kaushal 2016 Optimized mobile network selection Álvarez Pérez et al. 2017 Financial Sector Cahyapratama and Sarno 2018 Singer selection process Srivastava et al. 2019; Lai (2019) Indian railway; Military logistic depot

In order to explore the levels of TQM success factor implementation in manufacturing organizations, this study uses the AHP methodology. The different steps concerned in AHP methodology are as follows. Step-1: Objective of the study The purpose of present study is to investigate the most influencing success factor of TQM implementation for manufacturing industries in order to get maximum advantage during TQM implementation journey. Step-2: Development of AHP hierarchical framework After the objective had been recognized, appropriate and important success factors were identified as discussed in section 3. The identified eight major success factors which affect decision making in TQM implementation are given abbreviations as mentioned below:

1. Top Management Commitment (TMC) 2. Rewards and Recognition (R&R) 3. Education and Training (E&T) 4. Total Employee Participation (TEP) 5. Review and Monitoring (R&M) 6. Strategic Planning and Management (SP&M) 7. Quality Management (QM) 8. Communication (C)

Step-3 Compilation of observed information This section covers the compilation of observed information through the combined judgment of professionals particularly selected from manufacturing organizations and academician. In this present study, a set of 15 professionals provided their opinion for assessment to these success factors. All the professionals have significant knowledge in organization quality improvement activities. Step-4: Perform pair wise comparison of attributes After compilation empirical information, the next step is to evaluate relative importance of success factors and offer a score for alternatives depending upon qualitative factors. Pair wise comparisons of each success factor are made to establish relations within the structure. This is a principal step in developing an AHP model to evaluate relative importance of factors and offer a score for alternatives depending upon qualitative factors. The AHP targets on two factors at a time and their relationship with each other. Invited professionals were asked for assigning relative points with respect to the objective of the study. The comparative importance of every factor is determined by a

545



measurement scale to supply numerical judgments corresponding to verbal judgments. The degree of preference is given to the pair-wise comparisons of decisive factor on 9 point scale (Saaty, 1988), where 1 reflects equal weightage and 9 reflects extreme or absolute importance as shown in Table 3.

Table 3. Pair wise comparison scale

Degree of preference Effect of factors 1 Equal importance 3 Moderate importance of one over another 5 Essential or strong importance 7 Very strong importance 9 Extreme/absolute importance

2,4,6,8 Intermediate values between two adjacent judgments Step-4: Development of pair-wise comparison matrix A set of pair-wise comparison matrices for each of the success factor at intermediate level is built up. The factors at higher level are said to be governing factors which affects the factors at lower level. The factors at the lower level are compared with each other, based upon their effect on the governing factors. This provides an opportunity to develop a pair-wise comparison for developing a structure of n × n reciprocal judgment matrix. The pair-wise comparison matrix highlights the factors which are dominating other factors. These judgments are then expressed as integers. If ith factor is very important or demonstrably more important than jth factor, then based on the above Table 3 degree of preference a number is assigned and entered in ith row, jth column and reciprocally is entered in jth row, ith column. If the evaluators have given a common preference scale to the factors being compared, then number ‘1’ is entered to both positions. The n (n – 1)/2 judgments are helping to develop the matrix, where n is total number of success factors. Table 4, shows the pair-wise comparison matrix.

Table 4. Pair-wise comparison matrix

TMC R&R E&T TEP R&M SP&M QM C

TMC 1 2 2 2 5 2 2 7 R&R 1/2 1 1 2 4 1/3 3 5 E&T 1/2 1 1 3 2 2 5 4 TEP 1/2 1/2 1/3 1 2 2 4 5

R&M 1/5 1/4 1/2 1/2 1 1 2 4 SP&M 1/2 3 1/2 1/2 1 1 4 2

QM 1/2 1/3 1/5 1/4 1/2 1/4 1 1 C 1/7 1/5 1/4 1/5 1/4 1/2 1 1

SUM 3.592 8.2833 5.7833 9.450 15.750 9.083 22.000 29.000

Step-5: Normalization of matrix After making all the pair wise comparisons for each of the success factor, normalize the column of numbers by dividing each entry in column ‘i’ of the Table 4 by the sum of all entries in same column. This creates (Table 5) the normalized comparison matrix. In normalized comparison matrix the sum of the entries in each column is ‘1’ (Saaty, 2000; Chuang, 2001). The normalized value rij is calculated as:

𝑟𝑟𝑖𝑖𝑖𝑖 =𝑎𝑎𝑖𝑖𝑖𝑖

∑ 𝑎𝑎𝑖𝑖𝑖𝑖𝑛𝑛𝑖𝑖=1

Then sum each row of the normalized values and take the average. This provides priority weights for each success factor. Priority means the comparative significance of impact of a norm in relation to other norm that is placed above it in the hierarchy. The approximate priority weight (W1, W2,…….Wj) for each factor is obtained as shown in Table 5.

546



𝑊𝑊𝑖𝑖 =1𝑛𝑛

× �𝑎𝑎𝑖𝑖𝑖𝑖

𝑛𝑛

𝑖𝑖=1

Where, n is number of success factors; a is the cell value assigned in pair wise matrix.

Table 5. Criteria pair wise comparison matrix (Normalized)

TMC R&R E&T TEP R&M SP&M QM C Sum Priority weights

TMC 0.278 0.241 0.346 0.212 0.317 0.220 0.091 0.241 1.947 0.243 R&R 0.139 0.121 0.173 0.212 0.254 0.037 0.136 0.172 1.244 0.155 E&T 0.139 0.121 0.173 0.317 0.127 0.220 0.227 0.138 1.463 0.183 TEP 0.139 0.060 0.058 0.106 0.127 0.220 0.182 0.172 1.064 0.134

R&M 0.056 0.030 0.086 0.053 0.063 0.110 0.091 0.138 0.628 0.078 SP&M 0.139 0.362 0.086 0.053 0.063 0.110 0.182 0.069 1.065 0.133

QM 0.070 0.040 0.035 0.026 0.032 0.028 0.045 0.034 0.310 0.039 C 0.040 0.024 0.043 0.021 0.016 0.055 0.045 0.034 0.279 0.035

Total 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

From the above table one can guess that the priority is given to top management commitment i.e ‘0.243’ go after by education and training ‘0.183’ and so on.

Step-6: Consistency checking in pair wise matrix In this step consistency of obtained pair of norms is checked. One possibility is that professionals may be inconsistent in their evaluation. The weightages of different success factors are determined by calculating the eigen vector weights for making the evaluation. An index of consistency is further calculated for providing information on numerical and transitive consistency. The results can therefore be used to search for additional information and re-examine data used in constructing the scale in order to improve consistency. The relative weights (δ), is calculated by using the formula:

A× Wj = δ , where j = 1, 2,…n

Where ‘A’ represents the pair-wise comparison decision matrix, here in this study it is 8 x 8 matrix and Wj represents priority weight.

1 2 2 2 5 2 2 7 0.243 2.166 1/2 1 1 2 4 1/3 3 5 0.155 1.375 1/2 1 1 3 2 2 5 4 0.183 1.616 1/2 1/2 1/3 1 2 2 4 5 x 0.133 = 1.146 1/5 1/4 1/2 1/2 1 1 2 4 0.078 0.674 1/2 3 1/2 1/2 1 1 4 2 0.133 1.183 1/2 1/3 1/5 1/4 1/2 1/4 1 1 0.039 0.329 1/7 1/5 1/4 1/5 1/4 1/2 1 1 0.035 0.298

The Eigen vector ‘λ’: λ = 𝑖𝑖𝑖𝑖ℎ 𝑒𝑒𝑛𝑛𝑖𝑖𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑛𝑛 𝑒𝑒𝑒𝑒𝑟𝑟𝑟𝑟𝑖𝑖𝑖𝑖𝑟𝑟𝑒𝑒 𝑤𝑤𝑒𝑒𝑖𝑖𝑤𝑤ℎ𝑖𝑖 (δ)

𝑖𝑖𝑖𝑖ℎ 𝑒𝑒𝑛𝑛𝑖𝑖𝑒𝑒𝑒𝑒 𝑖𝑖𝑛𝑛 𝑝𝑝𝑒𝑒𝑖𝑖𝑝𝑝𝑒𝑒𝑖𝑖𝑖𝑖𝑒𝑒 𝑤𝑤𝑒𝑒𝑖𝑖𝑤𝑤ℎ𝑖𝑖

547



Table 6, shows the value of λ for the eight criteria and maximum value of 𝜆𝜆𝑚𝑚𝑟𝑟𝑚𝑚 is 8.901. With the help of maximum value of λ the consistency index (CI), which measures the inconsistencies of pair-wise comparisons is calculated as:

𝐶𝐶𝐶𝐶 = 𝜆𝜆𝑚𝑚𝑚𝑚𝑚𝑚−𝑛𝑛(𝑛𝑛−1)

= 0.128

Table 6. Eigen vector values

Success Factors δ Priority

weights Eigen vector

λ TMC 2.166 0.243 8.901 R&R 1.375 0.155 8.844 E&T 1.616 0.183 8.837 TEP 1.146 0.133 8.614

R&M 0.674 0.078 8.593 SP&M 1.183 0.133 8.882

QM 0.329 0.039 8.480 C 0.298 0.035 8.541

After calculating the consistency index, it is compared with the appropriate consistency index and this index was called random consistency index (RCI). The average consistencies for different order random matrices are shown in Table 7, (Saaty and Kearns, 1985).

Table 7. Random Consistency Index Table

n 1 2 3 4 5 6 7 8 9 10

RCI 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49 The last ratio that has to be calculated is Consistency Ratio (CR). Generally, if CR is less than 10%, the evaluations are consistent (Dyer & Forman, 1992) and acceptable. But if CR is greater than 10%, the quality of evaluations should be revised to have CR less than or equal to 10%. The formulation of CR is:

CR =CI

RCI

For example, in present study, the consistency ratio is ‘0.0907’; as a result the evaluations are consistent and acceptable. On the basis of calculated priority weights as discussed in Table 5, the ranking of the TQM success factors were done and is shown in Figure 2.

TQM Success factors Ranking

Top management commitment and leadership (TMC) I

Education and training (E&T) II

Rewards & Recognition (R&R) III

Strategic planning and management (SP&M) IV

Total employee participation (TEP) V

Reviewing and monitoring (R&M) VI

548



Quality Management (QM) VII

Communication (C) VIII

Figure 2. Ranking Hierarchy model of TQM Success Factors

5. Conclusion The objective of this study is to investigate the most influencing success factor of TQM implementation for manufacturing industries in order to get maximum advantage during TQM implementation journey. The results of AHP methodology demonstrates that ‘Top management commitment’ ranked number one and this factor is fundamental for implementing TQM initiatives successfully. The factors ‘education & training and ‘rewards & recognition’ ranked at second and third positions which need special attention while performing TQM activities in more effective manner. The other factors ‘strategic planning’ and ‘Total employee participation’ ranked at fourth and fifth places are truly important which need to motivate and promote employees to participate in TQM promotional activities. Last but not the least, factors ‘Monitoring and reviewing implementation of TQM initiatives’, quality management and communication are also important to give continuous growth for the successful implementation of TQM in any type of manufacturing organization. AHP hierarchy model formulated through this study will be very valuable to decision maker in manufacturing organization while implementing TQM.

In this research paper the most influencing success factors have been identified by using AHP. There is a good scope to further establish the relationship between these factors using some other mathematical model methods. REFERENCES Ahire, S.L., Golhar, D.Y. and Waller, M.W., Development and validation of TQM implementation constructs,

Decision Sciences, Vol. 27, No. 1, pp. 23-56, 1996. Ahire, S.L., Landeros, R. and Golhar, D.Y., Total quality management: a literature review and an agenda for future

research, Production and Operations Management, Vol. 4, No. 3, pp. 277-306, 1995. Álvarez Pérez, C., Rodríguez Montequín, V., Ortega Fernández, F. and Villanueva Balsera, J., Integrating analytic

hierarchy process (AHP) and balanced scorecard (BSC) framework for sustainable business in a software factory in the financial sector, Sustainability, 9(4), p.486, 2017.

Arumugam, V., Ooi, K-B. and Fong, T-C., TQM practices and quality management performance- an investigation of their relationship using data from ISO 9001:2000 firms in Malaysia, The TQM Magazine, Vol.20, No.6, pp. 636-650, 2008.

Ashok, S., & Santhakumar, A.R., NLP to promote TQM for effective implementation of ISO9001, Managerial Auditing Journal, Vol.5, 261–265, 2002.

Baird, K., Jia Hu, K. and Reeve, R., The relationships between organizational culture, total quality management practices and operational performance, International Journal of Operations & Production Management, Vol.31, No.7, pp.789-814, 2011.

Baker, A.W., Haridy, S., Salem, J., Ilieş, I., Ergai, A.O., Samareh, A., Andrianas, N., Benneyan, J.C., Sexton, D.J. and Anderson, D.J., Performance of statistical process control methods for regional surgical site infection surveillance: a 10-year multicentre pilot study, BMJ Qual Saf, Vol. 27, No. 8, pp.600-610, 2018.

Bitner, M.J., Servicescapes: The impact of physical surroundings on customers and employees, The Journal of Marketing, Vol.56, No.2, pp.57–71, 1992.

Brah, S.A., Serene, T.S.L., & Rao, B.M., Relationship between TQM and performance of Singapore companies, International Journal of Quality and Reliability Management, Vol.19, No.4, pp.356–379, 2002.

Cahyapratama, A. and Sarno, R., Application of Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods in singer selection process, In International Conference on Information and Communications Technology (ICOIACT), pp. 234-239, IEEE, 2018.

Chen, C.C., Chen, J. and Lin, P.C., Identification of significant threats and errors affecting aviation safety in Taiwan using the analytical hierarchy process, Journal of Air Transport Management, Vol.15, No.5, pp.261-263, 2009.

Chen, S. and Fan, J., Measuring corporate social responsibility based on a fuzzy analytical hierarchy process, International Journal of Computer Network and Information Security, Vol. 3, No.5, p.13, 2011.

549



Choi, T. Y. and Eboch, K. The TQM Paradox: Relations among TQM practices, plant performance, and customer satisfaction, Journal of Operations Management, Vol. 17 No. 1, pp. 59-75, 1998.

Chuang, P.T., Deployment for a location decision from a requirement perspective, International Journal of Advanced Manufacturing Technology, Vol. 18, No.11, pp.842–849, 2001.

Crosby, J. R., Assets and Shareholder Value : A Framework for Analysis, Vol. 62 No. 1, pp. 2–18, 1998. Crosby, P.B., Quality is Free: The Art of Making Quality Certain, Penguin Books, New York, 1979. Crowe, T.J., Noble, S.J., & Machimada, S.J., Multi-attribute analysis of ISO9001 registration using AHP,

International Journal of Quality and Reliability Management, Vol.15, No.2, 205–222, 1998. Curry, A., & Kadasah, N., Focusing on key elements of TQM – evaluation for sustainability, The TQM Magazine,

Vol.14, No.4, pp.207–216, 2002. Dale, B.G., Managing Quality, 3rd ed. Blackwell, Oxford, 1999. Deming, W.E., Out of the Crisis. MIT Centre for Advanced Engineering Study Cambridge, MA, 1986. Dyer, R.F. and Forman, E.H., Group decision support with the analytic hierarchy process, Decision support

systems, Vol. 8, No. 2, pp.99-124, 1992. Feigenbaum, A. V., Total quality control. 3rd ed., McGraw-Hill, New York, 1991. Flynn, B.B., Schroeder, R. and Sakakibara, S., A framework for quality management research and an associated

measurement instrument, Journal of Operations Management, Vol. 11, pp. 339-366, 1994. Fong, P.S.W. and Choi, S.K.Y., Final contractor selection using the analytical hierarchy process, Construction

management and economics, Vol.18, No.5, pp.547-557, 2000. Goyal, T. and Kaushal, S., Optimized network selection during handover using analytic hierarchy process in 4G

network. International Conference on Advances in Computing, Communication, & Automation (ICACCA), pp. 1-4. IEEE, 2016.

Haridy, S., Rahim, M.A., Selim, S.Z., Wu, Z. and Benneyan, J.C., EWMA chart with curtailment for monitoring fraction nonconforming, Quality Technology & Quantitative Management, Vol. 14, No. 4, pp.412-428, 2017.

Harrington, H.J., Performance improvement: was W. Edwards Deming wrong? The TQM Magazine Vol.10, No.4, 230–237, 1998.

Ho Voon, B., Lee, N. and Murray, D., Sports service quality for event venues: evidence from Malaysia. Sport, Business and Management: An International Journal, Vol.4, No.2, pp.125-141, 2014.

Ishikawa, K., What is Total Quality Control? The Japanese Way. Prentice-Hall, Englewood Cliffs, NJ, 1985. Ismyrlis, V., The contribution of quality tools and integration of quality management systems to the organization”,

TQM Journal, Vol. 29 No. 5, pp. 677–689, 2017. Ismyrlis, V. and Moschidis, O., The use of quality management systems, tools, and techniques in ISO 9001:2008

certified companies with multidimensional statistics: the Greek case, Total Quality Management and Business Excellence, Vol. 26 No. 5–6, pp. 497–514, 2015.

Juran, J.M., Quality trilogy. Quality Progress August, pp.14–24, 1986. Kanji, G.K., & Wallace, W., Business excellence through customer satisfaction. Total Quality Management, Vol.11,

No.7, 979–998, 2000. Kaynak, H., The relationship between total quality management practices and their effects on firm performance,

Journal of Operations Management, Vol.34, No.2, pp.1–31, 2003. Kohli, A. and Singh, R., An empirical study of variations in critical success factors of quality management practices

in indian manufacturing industry, Integral Review: A Journal of Management, 8(2), 2015. Knol, W.H., Slomp, J., Schouteten, R.L. and Lauche, K., Implementing lean practices in manufacturing SMEs:

testing ‘critical success factors’ using necessary condition analysis. International Journal of Production Research, 56(11), pp.3955-3973, 2018.

Lai, C.M., Integrating simplified swarm optimization with AHP for solving capacitated military logistic depot location problem, Applied Soft Computing, 78, pp.1-12, 2019.

Lam, M.Y., Poon, G.K.K., & Chin, K.S., An organizational learning model for vocational education in the context of TQM culture, International Journal of Quality and Reliability Management, 25(3), 238–255, 2008.

Lewis, W.G., Pun, K.F., & Lalla, T.R.M., An AHP-based study of TQM benefits in ISO9001 certified SMEs in Trinidad and Tobago, The TQM Magazine, 17(6), 558–572, 2005.

Li, J. and Lin, J.W., The relation between earnings management and audit quality, Journal of Accounting and Finance Research, 13(1), pp.1-11, 2005.

Logothetis, N., Managing for Total Quality: From Deming to Taguchi and SPC, Prentice Hall, London, 1992. Mellat Parast, M., Adams, S.G. and Jones, E.C., Improving operational and business performance in the petroleum

industry through quality management, International journal of quality & reliability management, 28(4), pp.426-450, 2011.

550



Mohajeri, N. and Amin, G.R., Railway station site selection using analytical hierarchy process and data envelopment analysis, Computers & Industrial Engineering, Vol. 59, No.1, pp.107-114, 2010.

Mohammad Mosadegh Rad, A., A survey of total quality management in Iran: Barriers to successful implementation in health care organizations, Leadership in Health Services, Vol.18, No.3, pp.12-34, 2005.

NIST, Malcolm Baldrige National Quality Award Criteria. National Institute of Standards and Technology, US Department of Commerce, 2000.

Oakland, J.S., Total quality management: The route to improving performance, Butterworth-Heinemann, Oxford Vol. 2, 1993.

Önder, E., Taş, N. and Hepsen, A., Performance evaluation of Turkish banks using analytical hierarchy process and TOPSIS methods, Journal of International Scientific Publication: Economy & Business, Vol.7, No.1, pp.470-503, 2013.

Peters, T., Facing up to the need for a management revolution, California Management Review, 30, 8–38, 1988. Pourghasemi, H.R., Pradhan, B. and Gokceoglu, C., Application of fuzzy logic and analytical hierarchy process

(AHP) to landslide susceptibility mapping at Haraz watershed, Iran, Natural hazards, 63(2), pp.965-996, 2012. Prajogo, D. I. and Sohal, A. S., The relationship between TQM practices, quality performance, and innovation

performance: An empirical examination, International Journal of Quality and Reliability Management, Vol. 20 No. 8, pp. 901–918, 2003.

Prakas, J. and Murali, B., Why Indian manufacturing SMEs are still reluctant in adopting total quality management, International Journal of Productivity and Quality Management, Vol. 17 No. 1, pp. 16–35, 2016.

Psomas, E.L. and Jaca, C., The impact of total quality management on service company performance: evidence from Spain, International Journal of Quality & Reliability Management, Vol. 33, No.3, pp.380-398, 2016.

Rahaman, S.A., Ajeez, S.A., Aruchamy, S. and Jegankumar, R., Prioritization of sub watershed based on morphometric characteristics using fuzzy analytical hierarchy process and geographical information system–A study of Kallar Watershed, Tamil Nadu, Aquatic Procedia, 4, pp.1322-1330, 2015.

Rao, M., Youssef, M. and Stratton, C., Can TQM lift a sinking ship? A case study. Total Quality Management & Business Excellence, 15(2), pp.161-171, 2004.

Reed, R., Lemak, D. J. and Mero, N. P., Meaning of total quality management,Vol. 5, pp. 5–26, 2000. Saaty, T.L., The analytic hierarchy process. New York, NY: Pergamum Press; 1988 . Saaty, T.L., The analytic hierarchy process – planning, priority setting, resource allocation. New York, NY:

McGraw-Hill, 1980. Saaty, T.L., Fundamental of decision making and priority theory with the analytic hierarchy process. Pittsburgh, PA:

RWS Publication, 2000. Saaty, T.L. and Kearns, K.P., Analytic planning, Organization of systems, 1985. Sahoo, S., Assessment of TPM and TQM practices on business performance: a multi-sector analysis”, Journal of

Quality in Maintenance Engineering, 2019. Sahoo, S. and Yadav, S., Entrepreneurial orientation of SMEs, total quality management and firm

performance, Journal of Manufacturing Technology Management, 28(7), pp.892-912, 2017. Saito, E.K., Shea, S., Jones, A., Ramos, G. and Pitesky, M., A cooperative approach to animal disease response

activities: Analytical hierarchy process (AHP) and vvIBD in California poultry. Preventive veterinary medicine, 121(1-2), pp.123-131, 2015.

Salomon, M.F.B., Mello, C.H.P. and Salgado, E.G., Prioritization of product-service business model elements at aerospace industry using analytical hierarchy process. Acta Scientiarum. Technology, 41, p.e37934, 2019.

Samson, D. and Terziovski, M., The relationship between total quality management research and operational performance. Journal of Operations Management, Vol. 17, No. 4, pp. 393-409, 1999.

Schmitz, J., & Platts, K.W., Supplier logistics performance measurement: Indications from a study in the automotive industry. International Journal of Production Economics, 89, 231–243, 2004.

Sila, I. and Ebrahimpour, M., An investigation of the total quality management survey based research published between 1989 and 2000: a literature review, International Journal of Quality and Reliability Management, Vol.19, No.7, pp. 902-970, 2002.

Singh, P. J. and Smith, A. J. R., Relationship between TQM and innovation: An empirical study, Journal of Manufacturing Technology Management, Vol. 15 No. 5, pp. 394–401, 2004.

Singh, A.K. and Sushil, Modeling enablers of TQM to improve airline performance, International Journal of Productivity and Performance Management, 62(3), pp.250-275, 2013.

Silombela, T., Mutingi, M. and Chakraborty, A., Impact of quality management tools and techniques, Journal of Quality in Maintenance Engineering, Vol. 24 No. 1, pp. 2–21, 2018.

Soltani, E. and Wilkinson, A., TQM and Performance Appraisal: Complementary or Incompatible? , European

551



Management Review, 2018. Šoltés, V. and Gavurová, B., The functionality comparison of the health care systems by the analytical hierarchy

process method, 2014. Srivastava, A., Gaur, S.K., Swami, S. and Banwet, D.K., Analysis of interpretive structural model of Indian railway

security system by analytic hierarchy process (AHP), Journal of Advances in Management Research, 2019. Stahl, M., Management-Total Quality in a Global Environment, Blackwell, C, 1995. Talib, F. and Rahman, Z., Critical success factors of total quality management in service organization: a proposed

model”. Service Marketing Quarterly, Vol.31, No.3, pp. 363-380, 2010. Talib, F., An overview of total quality management: understanding the fundamentals in service organization,

International Journal of Advanced Quality Management, 1(1), pp.1-20, 2013. Talib, F., Rahman, Z. and Qureshi, M.N., Analysis of interaction among the barriers to total quality management

implementation using interpretive structural modeling approach, Benchmarking: An International Journal, 18(4), pp.563-587, 2011.

Thai Hoang, D., Igel, B. and Laosirihongthong, T., The impact of total quality management on innovation, International Journal of Quality & Reliability Management, Vol. 23 No. 9, pp. 1092–1117, 2006.

Tseng, C.-C., & McLean, G.N., Strategic HRD practices as key factors in organizational learning, Journal of European Industrial Training, 32(6), 418–432, 2008.

Ugboro, I. O. and Obeng, K., Top management leadership, employee empowerment, job satisfaction, and customer satisfaction in TQM organizations: an empirical study, Journal of Quality Management, Vol. 5 No. 2, pp. 247-272, 2000.

Verma Devendra S. and Rathod Ajit, Feasiability Analysis of TQM(TQM) Model in Small Scale Industry, International journal of scientific research, vol.3.pp148- 150, 2014.

Wedley, W.C., Choo, E.U., & Schoner, B., Magnitude adjustment for AHP benefit/cost ratios, European Journal of Operational Research, Vol.133, No.2, 342–351, 2001.

Yang, C., The impact of human resource management practices on the implementation of total quality management, The TQM Magazine, Vol. 18 No. 2, pp. 162–173, 2006.

Biographies Pardeep Gupta is a Professor in Mechanical Engineering Department at Sant Longowal Institute of Engg & Tech Longowal, Punjab, India. He obtained his B.E. and M.E. degrees from PEC, Chandigarh in 1989 & 1997 respectively and PhD. degree from NIT, Kurukshetra in 2004. His areas of interest include Quality and Reliability engineering, Total Preventive Maintenance, TQM, Industrial Engineering, Conventional and Non-Conventional Metal Machining and Optimization Techniques. He has published more than 90 research papers in various national and international journals of repute and conference proceedings. He has more than 28 years of teaching and research experience. Ankesh Mittal is a Research Fellow in Mechanical Engineering Department at Sant Longowal Institute of Engg & Tech Longowal, Punjab, India. He did his B.Tech. and M.Tech. degrees from Chitkara University, Punjab, India and Thapar University, Patiala, India in 2013 & 2015 respectively His areas of research is total quality management and production engineering. He has published various national and international journals of repute and conference proceedings

552

identifying the most influencing success factors of tqm

Documents