The Mediating Effect Of Jit On The Relationship Between SCOR Model On Supply Chain Performance

The SCOR Model is one of the most applied reference models to support the description of supply chains and understanding the relationship between supply chain operation reference and supply chain performance. The Supply Chain Operations Reference (SCOR) model owes a standard thought to perceive an a...

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Main Author: Kamarudin, Nurhayati
Format: Thesis
Language:English
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Published: 2020
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institution Universiti Teknikal Malaysia Melaka
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advisor Abdul Majid, Izaidin

topic H Social Sciences (General)
H Social Sciences (General)
spellingShingle H Social Sciences (General)
H Social Sciences (General)
Kamarudin, Nurhayati
The Mediating Effect Of Jit On The Relationship Between SCOR Model On Supply Chain Performance
description The SCOR Model is one of the most applied reference models to support the description of supply chains and understanding the relationship between supply chain operation reference and supply chain performance. The Supply Chain Operations Reference (SCOR) model owes a standard thought to perceive an activity of the Supply Chain Council that provides a framework for characterizing supply chain management practices and processes with the result in better performance. This study examines potentials for future extensions of the model. The survey has been distributed to 270 companies in Malaysia manufacturing industry for extension potentials population. By an exhaustive analysis of 158 samples were returns to be evaluated for this study. This study investigates the level of SCOR Model practices in Supply Chain performance and investigates the relationship between supply chain operation reference (SCOR) Model effect by mediating of Just-In-Time (JIT) and supply chain performance in Malaysia manufacturing industry based on the five decision areas provided in SCOR Model Version 10.0 (PLAN, SOURCE, MAKE, DELIVER, RETURN) and five key supply chain performance derived from supply chain business management experts. The questionnaire tool by Supply Chain Council is used to analyse requirements on modelling tools to support the application of a respective extended SCOR Model. A concept of a tool support which accomplishes most of the requirements is described and realised as a prototype which is introduced in this thesis. The results show that planning processes are important in all SCOR supply chain planning decision areas. Collaboration was found to be most important in the Plan, Source and Make planning decision areas, while teaming was most important in supporting the Plan and Source planning decision areas. Process measures, process credibility and process integration were found to be most critical in supporting the deliver planning on the decision area. Using these results, the study discusses the implications of the findings and suggests several venues for future research.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Kamarudin, Nurhayati
author_facet Kamarudin, Nurhayati
author_sort Kamarudin, Nurhayati
title The Mediating Effect Of Jit On The Relationship Between SCOR Model On Supply Chain Performance
title_short The Mediating Effect Of Jit On The Relationship Between SCOR Model On Supply Chain Performance
title_full The Mediating Effect Of Jit On The Relationship Between SCOR Model On Supply Chain Performance
title_fullStr The Mediating Effect Of Jit On The Relationship Between SCOR Model On Supply Chain Performance
title_full_unstemmed The Mediating Effect Of Jit On The Relationship Between SCOR Model On Supply Chain Performance
title_sort mediating effect of jit on the relationship between scor model on supply chain performance
granting_institution Universiti Teknikal Malaysia Melaka
granting_department Faculty of Technology Management and Technopreneurship
publishDate 2020
url http://eprints.utem.edu.my/id/eprint/25425/1/The%20Mediating%20Effect%20Of%20Jit%20On%20The%20Relationship%20Between%20SCOR%20Model%20On%20Supply%20Chain%20Performance.pdf
http://eprints.utem.edu.my/id/eprint/25425/2/The%20Mediating%20Effect%20Of%20Jit%20On%20The%20Relationship%20Between%20SCOR%20Model%20On%20Supply%20Chain%20Performance.pdf
_version_ 1747834125507624960
spelling my-utem-ep.254252021-12-07T13:51:33Z The Mediating Effect Of Jit On The Relationship Between SCOR Model On Supply Chain Performance 2020 Kamarudin, Nurhayati H Social Sciences (General) HD Industries. Land use. Labor The SCOR Model is one of the most applied reference models to support the description of supply chains and understanding the relationship between supply chain operation reference and supply chain performance. The Supply Chain Operations Reference (SCOR) model owes a standard thought to perceive an activity of the Supply Chain Council that provides a framework for characterizing supply chain management practices and processes with the result in better performance. This study examines potentials for future extensions of the model. The survey has been distributed to 270 companies in Malaysia manufacturing industry for extension potentials population. By an exhaustive analysis of 158 samples were returns to be evaluated for this study. This study investigates the level of SCOR Model practices in Supply Chain performance and investigates the relationship between supply chain operation reference (SCOR) Model effect by mediating of Just-In-Time (JIT) and supply chain performance in Malaysia manufacturing industry based on the five decision areas provided in SCOR Model Version 10.0 (PLAN, SOURCE, MAKE, DELIVER, RETURN) and five key supply chain performance derived from supply chain business management experts. The questionnaire tool by Supply Chain Council is used to analyse requirements on modelling tools to support the application of a respective extended SCOR Model. A concept of a tool support which accomplishes most of the requirements is described and realised as a prototype which is introduced in this thesis. The results show that planning processes are important in all SCOR supply chain planning decision areas. Collaboration was found to be most important in the Plan, Source and Make planning decision areas, while teaming was most important in supporting the Plan and Source planning decision areas. Process measures, process credibility and process integration were found to be most critical in supporting the deliver planning on the decision area. Using these results, the study discusses the implications of the findings and suggests several venues for future research. 2020 Thesis http://eprints.utem.edu.my/id/eprint/25425/ http://eprints.utem.edu.my/id/eprint/25425/1/The%20Mediating%20Effect%20Of%20Jit%20On%20The%20Relationship%20Between%20SCOR%20Model%20On%20Supply%20Chain%20Performance.pdf text en public http://eprints.utem.edu.my/id/eprint/25425/2/The%20Mediating%20Effect%20Of%20Jit%20On%20The%20Relationship%20Between%20SCOR%20Model%20On%20Supply%20Chain%20Performance.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=119775 phd doctoral Universiti Teknikal Malaysia Melaka Faculty of Technology Management and Technopreneurship Abdul Majid, Izaidin 1. Ab Hamid, M.R., Mustafa, Z., Idris, F., Abdullah, M. and Suradi, N.M., 2011. Measuring value-based productivity: A Confirmatory Factor Analytic (CFA) approach. International Journal of Business and Social Science, 2(6), pp.85-93. 2. Abdelsalam, H.M. and Fahmy, G.A., 2009. Major variables affecting the performance of the textile and clothing supply chain operations in Egypt. International Journal of Logistics: Research and Applications, 12(3), pp.147-163. 3. Abdullah, N.M., Mohammad, W.M.Z.W., Shafei, M.N., Sukeri, S., Idris, Z., Arifin, W.N., Nozmi, N., Saudi, S.N.S., Samsudin, S., Zainudin, A.W. and Hamat, R.A., 2019. Leptospirosis and its prevention: knowledge, attitude and practice of urban community in Selangor, Malaysia. BMC Public Health, 19(1), p.628. 4. Achieng, S.O., 2011. Information Integration on supply chain management in the food processing firms in Kenya. Unpublished MBA Project, University of Nairobi. 5. Agi, M.A. and Nishant, R., 2017. Understanding influential factors on implementing green supply chain management practices: An interpretive structural modelling analysis. Journal of Environmental Management, 188, pp.351-363. 6. Agus, A., 2011. Enhancing production performance and customer performance through total quality management (TQM): strategies for competitive advantage. Procedia-Social and Behavioral Sciences, 24, pp.1650-1662. 7. Agus, A., 2011. The structural influence of supply chain management on product quality and business performance. International Journal of Trade, Economics and Finance, 2(4), p.269. 8. Agus, Arawati and Hassan, 2011. Enhancing production performance and customer performance through total quality management (TQM): strategies for competitive advantage. Procedia-Social and Behavioral Sciences, 24, pp.1650-1662. 9. Akindipe, O.S., 2014. Inventory Management-A Tool for Optimal Use of Resources and Overall Efficiency in Manufacturing SMEs. Journal of Entrepreneurship, Management and Innovation, 10(4), pp.93-114. 10. Alexander, A., Walker, H. and Naim, M., 2014. Decision theory in sustainable supply chain management: a literature review. Supply Chain Management: An International Journal, 19(5/6), pp.504-522. 11. Al-Shboul, M.D.A.R., Barber, K.D., Garza-Reyes, J.A., Kumar, V. and Abdi, M.R., 2017. The effect of supply chain management practices on supply chain and manufacturing firms’ performance. Journal of Manufacturing Technology Management, 28(5), pp.577-609. 12. Anderson, E., 2017. Extended value stream mapping: creating a supply chain view of phytosanitary compliance for export timber. Doctoral dissertation, Lincoln University. 13. Andres, L., 2012. Designing and doing survey research, Sage. 14. Angkiriwang, R., Pujawan, I.N. and Santosa, B., 2014. Managing uncertainty through supply chain flexibility: reactive vs. proactive approaches. Production and Manufacturing Research, 2(1), pp.50-70. 15. Annum, G., 2015. Research instrument for data collection. KNUST GH http://campus. educadium.com/newmediart/file.php/1/giilmadstore/UgradResearh/ThesisWrit4all/files/notes/resInstr. pdf. 16. Armstrong, J.S. and Overton, T.S., 1977. Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14(3), pp.396-402. 17. Asgari, N., Nikbakhsh, E., Hill, A. and Farahani, R.Z., 2016. Supply chain management 1982–2015: a review. IMA Journal of Management Mathematics, 27(3), pp.353-379. 18. Assenova, V.A. and Sorenson, O., 2017. Legitimacy and the benefits of firm formalization. Organization Science, 28(5), pp.804-818. 19. Avunduk, H., 2018. The Relationship between Manufacturing Flexibility and Performance: A Meta Analytical Study. International Journal of Contemporary Economics and Administrative Sciences, 8(1), pp.20-33. 20. Babbie, E.R., 2010. The practice of social research (p. 530). Wadsworth: Cengage Learning. 21. Badawy, M., El-Aziz, A.A., Idress, A.M., Hefny, H. and Hossam, S., 2016. A survey on exploring key performance indicators. Future Computing and Informatics Journal, 1(1-2), pp.47-52. 22. Badri, M., Al Nuaimi, A., Guang, Y. and Al Rashedi, A., 2017. School performance, social networking effects, and learning of school children: Evidence of reciprocal relationships in Abu Dhabi. Telematics and Informatics, 34(8), pp.1433-1444. 23. Baltacioglu, T., Ada, E., Kaplan, M.D., Yurt And, O. and Cem Kaplan, Y., 2007. A new framework for service supply chains. The Service Industries Journal, 27(2), pp.105-124. 24. Barbosa-Povoa, A.P., Mota, B. and Carvalho, A., 2018. How to design and plan sustainable supply chains through optimization models? Pesquisa Operacional, 38(3), pp.363-388. 25. Barnard, J., 2006. A Multi-view Framework for Defining the Services Supply Chain Using Object Oriented Methodology. Electronic Theses and Dissertations. https://stars.library.ucf.edu/etd/1110. 26. Baron, R.M. and Kenny, D.A., 1986. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), p.1173. 27. Bauhof, N., 2004. SCOR Model: Supply Chain Operations Reference Model. Beverage Industry, 95(8), pp.78-88. 28. Bean, W.L., Schmitz, P.M. and Engelbrecht, G.N., 2009. Adapting the SCOR Model to suit the military: A South African Example. 14th Logistics Research Network Annual Conference, Cardiff, UK, 9-11 September 2009. 29. Bernard, H.R. and Bernard, H.R., 2012. Social research methods: Qualitative and quantitative approaches, Sage. 30. Bititci, U.S., Turner, U. and Begemann, C., 2000. Dynamics of performance measurement systems. International Journal of Operations and Production Management, 20(6), pp.692-704. 31. Boehmke, B.C. and Hazen, B.T., 2017. The future of supply chain information systems: The open source ecosystem. Global Journal of Flexible Systems Management, 18(2), pp.163-168. 32. Bolton, R. and Hannon, M., 2016. Governing sustainability transitions through business model innovation: Towards a systems understanding. Research Policy, 45(9), pp.1731-1742. 33. Bozarth, C.C., Warsing, D.P., Flynn, B.B. and Flynn, E.J., 2009. The impact of supply chain complexity on manufacturing plant performance. Journal of Operations Management, 27(1), pp.78-93. 34. Braunerhjelm, P. and Henrekson, M., 2013. Entrepreneurship, institutions, and economic dynamism: lessons from a comparison of the United States and Sweden. Industrial and Corporate Change, 22(1), pp.107-130. 35. BrckaLorenz, A., Chiang, Y.C. and Nelson Laird, T., 2013. Internal consistency. Faculty Survey of Student Engagement. 36. Brown, T.A., Di Nardo, P.A., Lehman, C.L. and Campbell, L.A., 2001. Reliability of DSM-IV anxiety and mood disorders: implications for the classification of emotional disorders. Journal of Abnormal Psychology, 110(1), p.49. 37. Burns, R.P. and Burns, R., 2008. Business research methods and statistics using SPSS, Sage. 38. Butler, B. and Surace, K., 2015. Call for organisational agility in the emergent sector of the service industry. Journal of Business Management, (10). 39. Camarinha-Matos, L.M., Boucher, X. and Afsarmanesh, H. eds., 2010. Collaborative Networks for a Sustainable World: 11th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2010, St. Etienne, France, October 11-13, 2010, Proceedings (Vol. 336). Springer Science and Business Media. 40. Campbell, D.T. and Cook, T.D., 1979. Quasi-experimentation: Design & analysis issues for field settings, Chicago: Rand McNally College Publishing Company. 41. Canel, C., Rosen, D. and Anderson, E.A., 2000. Just-in-time is not just for manufacturing: a service perspective. Industrial Management and Data Systems, 100(2), pp.51-60. 42. Caridad, J.M., Hanclova, J. and Černý, J., 2014. An empirical analysis of the influence of risk factors on the frequency and impact of severe events on the supply chain in the Czech Republic. Quality Innovation Prosperity, 18(2), pp.56-78. 43. Carter, C.R. and Washispack, S., 2018. Mapping the Path Forward for Sustainable Supply Chain Management: A Review of Reviews. Journal of Business Logistics, 39(4), pp.242-247. 44. Castelli, C., 2006, September. Supply chain management strategies in the luxury industry. In Doctoral Seminar of the AiIG Conference, Rome. 45. Chan, F.T. and Qi, H.J., 2003. An innovative performance measurement method for supply chain management. Supply Chain Management: An international Journal, 8(3), pp.209-223. 46. Chang, H.J., 2012. The manufacturing sector and the future of Malaysia’s economic development. Jurnal Pengurusan (UKM Journal of Management), 35. 47. Chang, Y.S., Makatsoris, H.C. and Richards, H.D. eds., 2004. Evolution of supply chain management: symbiosis of adaptive value networks and ICT. Springer Science and Business Media. 48. Chau, L.M, 2012. Adding value to customers by improving supply chain performance management for VuHai Company Ltd. 49. Cherrafi, A., Garza-Reyes, J.A., Kumar, V., Mishra, N., Ghobadian, A. and Elfezazi, S., 2018. Lean, green practices and process innovation: A model for green supply chain performance. International Journal of Production Economics, 206, pp.79-92. 50. Cheung, K.L., Peter, M., Smit, C., de Vries, H. and Pieterse, M.E., 2017. The impact of non-response bias due to sampling in public health studies: a comparison of voluntary versus mandatory recruitment in a Dutch national survey on adolescent health. BMC Public Health, 17(1), p.276. 51. Chibba, A., 2017. Supply Chain Quality Management: Exploring performance of manufacturing organizations. Doctoral dissertation, Luleå Tekniska Universitet. 52. Chigbu, U.E., 2019. Visually Hypothesising in Scientific Paper Writing: Confirming and Refuting Qualitative Research Hypotheses Using Diagrams. Publications, 7(1), p.22. 53. Chopra, S. and Meindl, P., 2014. Supply chain management: strategy, planning and operation, 6th ed., New Jersey: Person Prentice Hall. 54. Chopra, S. and Meindl, P., 2007. Supply chain management: Strategy, planning and operation. In Das summa summarum des management, pp.265-275. Gabler. 55. Chopra, S., and Meindl, P., 2003. Supply Chain Management: Strategy, Planning and Operation, Prentice Hall. 56. Christopher, M. and Towill, D., 2001. An integrated model for the design of agile supply chains. International Journal of Physical Distribution and Logistics Management, 31(4), pp.235-246. 57. Chun, K.Y., 2014. Performance measurement framework for engineering supply chain. Master's Thesis, Business Information Systems (MBA). 58. Churchill Jr, G.A., 1979. A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), pp.64-73. 59. Cloerec, B., 2017. Need and Value of Information in ITS: Supply Chain Performance through Predictive Analytics. Bachelor Business of Administration, Metropolia University of Applied Sciences. 60. Cobanoglu, C., Corbaci, K. and Ryan, B., 2001. A comparative study: the impact of technology in lodging properties in the United States and Turkey. International Journal of Hospitality Information Technology, 2(1), pp.23-40. 61. Cocca, P. and Alberti, M., 2010. A framework to assess performance measurement systems in SMEs. International Journal of Productivity and Performance Management, 59(2), pp.186-200. 62. Cohen, J. and Cohen, P., 1983. Applied multiple regression/correlation analysis for the behavioral sciences, 2nd ed., Hillsdale, NJ: Erlbaum. 63. Cole, T.J., Stanojevic, S., Stocks, J., Coates, A.L., Hankinson, J.L. and Wade, A.M., 2009. Age‐and size‐related reference ranges: A case study of spirometry through childhood and adulthood. Statistics in Medicine, 28(5), pp.880-898. 64. Council, S.C., 2008. Supply chain operations reference model version 9.0. Supply-Chain Council, Pittsburgh, USA. 65. Cox, A., Ireland, P., Lonsdale, C., Sanderson, J. and Watson, G., 2003. Supply chains, markets and power: managing buyer and supplier power regimes, Routledge. 66. Craighead, C.W. and Shaw, N.G., 2003. E-commerce value creation and destruction: a resource-based, supply chain perspective. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 34(2), pp.39-49. 67. Creswell, J.W. and Creswell, J.D., 2017. Research design: Qualitative, quantitative, and mixed methods approaches, Sage publications. 68. Croxton, K.L., Garcia-Dastugue, S.J., Lambert, D.M. and Rogers, D.S., 2001. The supply chain management processes. The International Journal of Logistics Management, 12(2), pp.13-36. 69. Cunningham, T., 2015. Cost Control during the Pre-Contract Stage of a Building Project–An Introduction. Dublin Institute of Technology. 70. da Piedade Francisco, R. and Azevedo, A., 2009, October. An SSM-Based approach to implement a dynamic performance management system. Working Conference on Virtual Enterprises, pp.476-483. Springer, Berlin, Heidelberg. 71. Dabholkar, P.A., Shepherd, C.D. and Thorpe, D.I., 2000. A comprehensive framework for service quality: an investigation of critical conceptual and measurement issues through a longitudinal study. Journal of Retailing, 76(2), pp.139-173. 72. De Oliveira, M.P.V., Ladeira, M.B. and McCormack, K.P., 2011. The supply chain process management maturity model–SCPM3. Supply Chain Management-Pathways for Research and Practice, pp.201-218. 73. De Waal, A.A., 2007. Is performance management applicable in developing countries? The case of a Tanzanian college. International Journal of Emerging Markets, 2(1), pp.69-83. 74. Delipinar, G.E. and Kocaoglu, B., 2016. Using SCOR model to gain competitive advantage: A Literature review. Procedia-Social and Behavioral Sciences, 229, pp.398-406. 75. Demartini, C. and Trucco, S., 2017. Are performance measurement systems useful? Perceptions from health care. BMC Health Services Research, 17(1), p.96. 76. Dos Santos, J.X. and Cabrita, M., 2016, July. Lean Banking: Application of lean concepts and tools to the banking industry. The 2016 International Conference on Systematic Innovation July, pp.20-22. 77. Dos Santos, T.F. and Leite, M.S.A., 2016. Performance measurement system in supply chain management: application in the service sector. International Journal of Services and Operations Management, 23(3), pp.298-315. 78. Du Toit, D. and Vlok, P.J., 2014. Supply chain management: A framework of understanding. South African Journal of Industrial Engineering, 25(3), pp.25-38. 79. Edler, J. and Yeow, J., 2016. Connecting demand and supply: The role of intermediation in public procurement of innovation. Research Policy, 45(2), pp.414-426. 80. Ellinger, A., Shin, H., Magnus Northington, W., Adams, F.G., Hofman, D. and O'Marah, K., 2012. The influence of supply chain management competency on customer satisfaction and shareholder value. Supply Chain Management: An International Journal, 17(3), pp.249-262. 81. Ellram, L., 1995. IBM Smart SCOR – A SCOR Based Supply Chain Transformation Platform through Simulation and Optimization Techniques. Research Report (IBM Research Division, China). 82. Ellram, L.M., Tate, W.L. and Billington, C., 2004. Understanding and managing the services supply chain. Journal of Supply Chain Management, 40(3), pp.17-32. 83. Emejom, A.A., Burgess, C., Pepper, D. and Adkins, J., 2019. Agile Approaches for Successfully Managing and Executing Projects in the Fourth Industrial Revolution. Agile Approaches for Successfully Managing and Executing Projects in the Fourth Industrial Revolution, pp.1-19. IGI Global. 84. Erkan, T.E. and Ugur, B.A.Ç., 2011. Supply chain performance measurement: a case study about applicability of SCOR model in a manufacturing industry firm. International Journal of Business and Management Studies, 3(1), pp.381-390. 85. Farooque, M., Zhang, A., Thurer, M., Qu, T. and Huisingh, D., 2019. Circular supply chain management: A definition and structured literature review. Journal of Cleaner Production, 228, pp.882-900. 86. Fawcett, S.E., Magnan, G.M. and McCarter, M.W., 2008. Benefits, barriers, and bridges to effective supply chain management. Supply Chain Management: An International Journal, 13(1), pp.35-48. 87. Fincham, J.E., 2008. Response rates and responsiveness for surveys, standards, and the Journal. American Journal of Pharmaceutical Education, 72(2), p.43. 88. Fishbein, M. and Ajzen, I., 1977. Belief, attitude, intention, and behavior: An introduction to theory and research. Journal of Business Venuring, 5, pp.177-189. 89. Folan, P. and Browne, J., 2005. A review of performance measurement: Towards performance management. Computers in Industry, 56(7), pp.663-680. 90. Francisco, D. R., and Azevedo, A., 2009.An automated methodology for a comprehensive definition of the supply chains using generic ontological components. Dissertation, University of Central Florida. 91. Frohlich, M.T. and Westbrook, R., 2001. Arcs of integration: an international study of supply chain strategies. Journal of Operations Management, 19(2), pp.185-200. 92. Fronia, P., Wriggers, F.S. and Nyhuis, P., 2008, June. A framework for supply chain design. EngOpt 2008-International Conference on Engineering Optimization, Rio de Janeiro, Brazil, pp.01-05. 93. Fry, G., Chantavanich, S. and Chantavanich, A., 1981. Merging Quantitative and Qualitative Research Techniques: Toward a New Research Paradigm 1. Anthropology and Education Quarterly, 12(2), pp.145-158. 94. Furlan, A., Dal Pont, G. and Vinelli, A., 2011. On the complementarity between internal and external just-in-time bundles to build and sustain high performance manufacturing. International Journal of Production Economics, 133(2), pp.489-495. 95. Gabelica, C., Van den Bossche, P., Fiore, S.M., Segers, M. and Gijselaers, W.H., 2016. Establishing team knowledge coordination from a learning perspective. Human Performance, 29(1), pp.33-53. 96. Ganassali, S., 2008, March. The influence of the design of web survey questionnaires on the quality of responses. Survey Research Methods, 2(1), pp.21-32. 97. Ganeshan, R., 1995. An introduction to supply chain management. http://lcm. csa. iisc. ernet. in/scm/supply_chain_intro. html. 98. Georgise, F.B., Thoben, K.D. and Seifert, M., 2011. Supply Chain Modeling and Improving Manufacturing Industry in Developing Countries: A Research Agenda. World Academy of Science, Engineering and Technology, 60, pp.1998-2003. 99. Georgise, F.B., Wuest, T. and Thoben, K.D., 2017. SCOR model application in developing countries: challenges and requirements. Production Planning and Control, 28(1), pp.17-32. 100. Gerosa, M. and Taisch, M., 2008a. The industrial services reference model. 2008 IEEE International Conference on Industrial Engineering and Engineering Management, pp. 660-664. 101. Gerosa, M. and Taisch, M., 2008b. A novel industrial services reference model. 2008 IEEE International Technology Management Conference (ICE), pp.1-8. 102. Ghasemi, M., Nejad, M.G. and Bagzibagli, K., 2017. Knowledge Management Orientation: An Innovative Perspective to Hospital Management. Iranian Journal of Public Health, 46(12), p.1639. 103. Golden, S.A.R. and Regi, S.B., 2015. Satisfaction of Customers towards User Friendly Technological Services offered by Public and Private Sector banks at Palayamkottai, Tirunelveli District. International Journal of Research, 2(3), pp.775-787. 104. Goldratt, E.M. and Cox, J., 2016. The goal: a process of ongoing improvement, Routledge. 105. Gollan, P.J., Kalfa, S., Agarwal, R., Green, R. and Randhawa, K., 2014. Lean manufacturing as a high-performance work system: the case of Cochlear. International Journal of Production Research, 52(21), pp.6434-6447. 106. Gulati, P.M., 2009. Research Management: Fundamental & Applied Research, Busca Inc. 107. Gunasekaran, A., Patel, C. and McGaughey, R.E., 2004. A framework for supply chain performance measurement. International Journal of Production Economics, 87(3), pp.333-347. 108. Guterres, M.A., 2018. The Business of Globalization and the Globalization of Business. University of New Brunswick, Canada. 109. Hami, N., Muhamad, M.R. and Ebrahim, Z., 2015. The impact of sustainable manufacturing practices and innovation performance on economic sustainability. Procedia CIRP, 26, pp.190-195. 110. Han, D., Kwon, I.W.G., Bae, M. and Sung, H., 2002. Supply chain integration in developing countries for foreign retailers in Korea: Wal-Mart experience. Computers and Industrial Engineering, 43(1-2), pp.111-121. 111. Heizer, J.H. and Render, B., 2008. Operations management (Vol. 1), Pearson Education India. 112. Hicks and Tamas, 2000. Linking SCOR planning practices to supply chain performance, International Journal of Operations and Production Management, ISSN: 0144-3577. 113. Hidiroglou, M.A., Drew, J.D. and Gray, G.B., 1993. A framework for measuring and reducing nonresponse in surveys. Survey Methodology, 19(1), pp.81-94. 114. Hieber, R.F., 2003. Supporting transcorporate logistics by collaborative performance measurement in industrial logistics networks. PhD Thesis, Swiss Federal Institute of Technology, Zurich. 115. Holmberg, S., 2000. A systems perspective on supply chain measurements. International Journal of Physical Distribution and Logistics Management, 30(10), pp.847-868. 116. Holmes, J.S., Amin Gutiérrez de Piñeres, S. and Douglas Kiel, L., 2006. Reforming government agencies internationally: is there a role for the balanced scorecard? International Journal of Public Administration, 29(12), pp.1125-1145. 117. Holweg, M., 2005. The three dimensions of responsiveness. International Journal of Operations and Production Management, 25(7), pp.603-622. 118. Hove, P., 2015. The influence of supply chain practice on supply chain performance in South Africa. Doctoral Dissertation. 119. Houshang and Ehsan, 2012. The investigation of supply chain’s reliability measure: a case study. Journal of Industrial Engineering International, 8(22). 120. Huan, S.H., Sheoran, S.K. and Wang, G., 2004. A review and analysis of supply chain operations reference (SCOR) model. Supply Chain Management: An International Journal, 9(1), pp.23-29. 121. Huang, S.H., Sheoran, S.K. and Keskar, H., 2005. Computer-assisted supply chain configuration based on supply chain operations reference (SCOR) model. Computers and Industrial Engineering, 48(2), pp.377-394. 122. Hwang, Y.D., Lin, Y.C. and Lyu Jr, J., 2008. The performance evaluation of SCOR sourcing process—The case study of Taiwan's TFT-LCD industry. International Journal of Production Economics, 115(2), pp.411-423. 123. Iacob, V., 2012. Theoretical outline of supplier relationship management in conditions of economic uncertainty. Studies and Scientific Researches. Economics Edition, (16-17). 124. Iarossi, G., 2006. The power of survey design: A user's guide for managing surveys, interpreting results, and influencing respondents. The World Bank. 125. Irfan, D., Xiaofei, X. and Chun, D.S., 2008. A SCOR Reference Model of the Supply Chain Management System in an Enterprise. International Arab Journal of Information Technology (IAJIT), 5(3), pp.288-295. 126. Ivanov, D., Dolgui, A., Sokolov, B. and Ivanova, M., 2017. Literature review on disruption recovery in the supply chain. International Journal of Production Research, 55(20), pp.6158-6174. 127. Jamehshooran, B.G., Shaharoun, M. and Haron, H.N., 2015. Assessing supply chain performance through applying the SCOR model. International Journal of Supply Chain Management, 4(1), pp.1-11. 128. Jamieson, S., 2004. Likert scales: how to (ab) use them. Medical Education, 38(12), pp.1217-1218. 129. Janvier-James, A.M., 2012. A new introduction to supply chains and supply chain management: Definitions and theories perspective. International Business Research, 5(1), pp.194-207. 130. Jolly-Desodt, A.M., Rabenasolo, B. and Lo, J.L.W., 2006, October. Benchmarking of the textile garment supply chain using the SCOR model. 2006 International Conference on Service Systems and Service Management, 2, pp.1427-1432. 131. Jonsson, P. and Lesshammar, M., 1999. Evaluation and improvement of manufacturing performance measurement systems-the role of OEE. International Journal of Operations and Production Management, 19(1), pp.55-78. 132. Kain, R. and Verma, A., 2018. Logistics management in supply chain–an overview. Materials Today: Proceedings, 5(2), pp.3811-3816. 133. Kaipia, R., Holmström, J., Småros, J. and Rajala, R., 2017. Information sharing for sales and operations planning: Contextualized solutions and mechanisms. Journal of Operations Management, 52, pp.15-29. 134. Kaniganat, T. and Chaipoopirutana, S., 2014. A Study of Factors Influencing Customer Satisfaction: An Implementation on Thai Postal Service, Bangkok Area. International Conference on Business, Law and Corporate Social Responsibility (ICBLcustomer satisfactionP'14), pp.1-2. 135. Kannan, V.R. and Tan, K.C., 2005. Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega, 33(2), pp.153-162. 136. Kannan, V.R. and Tan, K.C., 2004. Supplier alliances: differences in attitudes to supplier and quality management of adopters and non‐adopters. Supply Chain Management, 9(4), pp.279-286. 137. Kapás, J., 2008. Industrial revolutions and the evolution of the firm's organization: an historical perspective. Journal of Innovation Economics Management, (2), pp.15-33. 138. Karl, A.A., Micheluzzi, J., Leite, L.R. and Pereira, C.R., 2018. Supply chain resilience and key performance indicators: a systematic literature review. Production, 28. 139. Kasi, V., 2005, January. Systemic assessment of SCOR for modeling supply chains. Proceedings of the 38th Annual Hawaii International Conference on System Sciences, pp. 87b-91b. 140. Kassahun, T., 2010. Rethinking institutional excellence in Ethiopia: adapting and adopting the balanced scorecard (BSC) model. Journal of Business and Administrative Studies, 2(1), pp.22-53. 141. Khalifa, N., White, A. and ElSayed, A., 2008, September. Supply chain challenges in developing countries: cross industry case studies. 2008 7th IEEE International Conference on Cybernetic Intelligent Systems, pp.1-8. 142. Khan, R.A., Liew, M.S. and Ghazali, Z.B., 2014. Malaysian construction sector and Malaysia vision 2020: developed nation status. Procedia-Social and Behavioral Sciences, 109, pp.507-513. 143. Khine, M.S., 2013. Application of structural equation modeling in educational research and practice, 7th ed., Rotterdam: Sense Publishers. 144. Khorram Niaki, M. and Nonino, F., 2017. Additive manufacturing management: a review and future research agenda. International Journal of Production Research, 55(5), pp.1419-1439. 145. Kim, H., Park, J., Chang, T.W., Jeong, H., Kim, K.T. and Park, J., 2007, October. A Model and Analysis of the Bullwhip Effect Using a SCOR-Based Framework. Asian Simulation Conference, pp.12-20. Springer, Berlin, Heidelberg. 146. Kozlenkova, I.V., Hult, G.T.M., Lund, D.J., Mena, J.A. and Kekec, P., 2015. The role of marketing channels in supply chain management. Journal of Retailing, 91(4), pp.586-609. 147. Kraemer, H.C., Mintz, J., Noda, A., Tinklenberg, J. and Yesavage, J.A., 2006. Caution regarding the use of pilot studies to guide power calculations for study proposals. Archives of General Psychiatry, 63(5), pp.484-489. 148. Krajewski, L., Ritzman, L. and Malhotra, M., 2006. Operations management. Upper Saddle River, NJ. 149. Krejcie, R.V. and Morgan, D.W., 1970. Determining sample size for research activities. Educational and Psychological Measurement, 30(3), pp.607-610. 150. Krishnan, T.N. and Poulose, S., 2016. Response rate in industrial surveys conducted in India: Trends and implications. IIMB Management Review, 28(2), pp.88-97. 151. Krosnick, J.A., 2009. Question and Questionnaire Design, 2nd ed., Handbook of Survey Research. 152. Lai, K.H., Ngai, E.W.T. and Cheng, T.C.E., 2002. Measures for evaluating supply chain performance in transport logistics. Transportation Research Part E: Logistics and Transportation Review, 38(6), pp.439-456. 153. Lambert, D.M., 2008. Supply chain management: processes, partnerships, performance. Supply Chain Management Institute. 154. Lambert, D.M. and Cooper, M.C., 2000. Issues in supply chain management. Industrial Marketing Management, 29(1), pp.65-83. 155. Lange, I., Schnetzler, M., Schneider, O. and Osadsky, P., 2007. Design of a performance measurement system for industrial service operations. 2nd International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV 2007), Toronto, Ontario, Canada, 22-24 July 2007: Book of Abstracts, pp.47-57. 156. Lawson, B., Cousins, P.D., Handfield, R.B. and Petersen, K.J., 2009. Strategic purchasing, supply management practices and buyer performance improvement: an empirical study of UK manufacturing organisations. International Journal of Production Research, 47(10), pp.2649-2667. 157. Le, C., 2012. Adding value to customers by improving supply chain performance management for VuHai Company Ltd. Bachelor's Thesis Degree Programme in International Business. 158. Lee, T. and Nam, H., 2016. An empirical study on the impact of individual and organizational supply chain orientation on supply chain management. The Asian Journal of Shipping and Logistics, 32(4), pp.249-255. 159. LeMay, S., Helms, M.M., Kimball, B. and McMahon, D., 2017. Supply chain management: the elusive concept and definition. The International Journal of Logistics Management, 28(4), pp.1425-1453. 160. Lemghari, R., Okar, C. and Sarsri, D., 2018. Benefits and limitations of the SCOR® model in Automotive Industries. MATEC Web of Conferences, 200, p.00019. EDP Sciences. 161. Lescroël, A., Ballard, G., Grémillet, D., Authier, M. and Ainley, D.G., 2014. Antarctic climate change: extreme events disrupt plastic phenotypic response in Adélie penguins. PloS one, 9(1), p.e85291. 162. Lestari, F., Ismail, K., Hamid, A.A. and Supriyanto, E., 2014. Measuring Supply Chain Using SCOR Model in Palm Oil Downstream Industry: A Review. World Congress on Engineering. 163. Leu, J.D. and Lee, L.J.H., 2017. Enterprise resource planning (ERP) implementation using the value engineering methodology and Six Sigma tools. Enterprise Information Systems, 11(8), pp.1243-1261. 164. Likert, R., 1932. A technique for the measurement of attitudes. Archives of Psychology, 140, pp.5-55. 165. Lin, L.C. and Li, T.S., 2010. An integrated framework for supply chain performance measurement using six-sigma metrics. Software Quality Journal, 18(3), pp.387-406. 166. Lindner, J.R. and Wingenbach, G.J., 2002. Communicating the handling of nonresponse error in Journal of Extension Research in Brief articles. Journal of Extension, 40(6), pp.1-5. 167. Liu, G.J., McKone-Sweet, K. and Shah, R., 2009. Assessing the performance impact of supply chain planning in net-enhanced organizations. Operations Management Research, 2(1-4), pp.33-43. 168. Lockamy III, A. and McCormack, K., 2004. Linking SCOR planning practices to supply chain performance: An exploratory study. International Journal of Operations and Production Management, 24(12), pp.1192-1218. 169. Lucato, W.C., Santos, J.C.D.S. and Pacchini, A.P.T., 2018. Measuring the sustainability of a manufacturing process: A conceptual framework. Sustainability, 10(1), p.81. 170. Lucherini, F. and Rapaccini, M., 2017. Exploring the impact of Lean manufacturing on flexibility in SMEs. Journal of Industrial Engineering and Management (JIEM), 10(5), pp.919-945. 171. MacKinnon, D.P., 2011. Integrating mediators and moderators in research design. Research on Social Work Practice, 21(6), pp.675-681. 172. Maclennan, D., Ong, R. and Wood, G., 2015. Making connections: housing, productivity and economic development. AHURI Final Report, (251), pp.1-122. 173. Magder, D., 2005. Egypt after the multi-fiber arrangement: global apparel and textile supply chains as a route for industrial upgrading. Working Paper Series. 174. Maiseyenka, K., 2016. JIT and Resources. 175. Manataki, A., 2009. Improving Supply Chain Management Understanding through Logic-Based Conceptual Modelling and Automation. 176. Manheim, J.B., Rich, R.C., Willnat, L. and Brians, C.L., 2008. Empirical political analysis: Quantitative and qualitative research methods, New York: Pearson Longman. 177. Manokoran, R., 2019. The Relationship between Supply Chain Management Practices and Customer Satisfaction in Small and Medium Enterprises. Journal of Arts & Social Sciences, 2(2), pp.67-80. 178. Marchi, B. and Zanoni, S., 2017. Supply chain management for improved energy efficiency: Review and opportunities. Energies, 10(10), p.1618. 179. Marriot, D.A., 2017. Using Civilian Supply Chain Management Best Practices to Improve Army Supply Chain Management Procedures. US Army Command and General Staff College Fort Leavenworth United States. 180. Martínez-Mesa, J., González-Chica, D.A., Duquia, R.P., Bonamigo, R.R. and Bastos, J.L., 2016. Sampling: how to select participants in my research study? Anais Brasileiros de Dermatologia, 91(3), pp.326-330. 181. McCormack, K., 2003. B2B collaboration: what is it? Supply Chain Practice, 5, pp.18-29. 182. McCormack, K., Bronzo Ladeira, M. and Paulo Valadares de Oliveira, M., 2008. Supply chain maturity and performance in Brazil. Supply Chain Management: an International Journal, 13(4), pp.272-282. 183. McCormack, K.P. and Johnson, W.C., 2001. Business process orientation: Gaining the e-business competitive advantage. Crc Press. 184. McNabb, D.E., 2008. Research Methods in Public Administration and Non-Profit Management: Quantitative and Qualitative Approaches, ME Sharpe. URL: http://books. google. co. uk/books. 185. Melchert, F., Winter, R. and Klesse, M., 2004, August. Aligning process automation and business intelligence to support corporate performance management. Association for Information Systems. 186. Miemczyk, J. and Howard, M., 2008. Supply strategies for build-to-order: managing global auto operations. Supply Chain Management: an International Journal, 13(1), pp.3-8. 187. Mitchell, R.C. and Carson, R.T., 2013. Using surveys to value public goods: the contingent valuation method. Rff Press. 188. Mogey, N., 1999. Learning technology dissemination initiative. So you want to use a Likert scale. URL: http://www. icbl. hw. ac. uk/ltdi/cookbook/cookbook. pdf [accessed 2013-03-07][WebCite Cache]. 189. Mohajan, H.K., 2017. Two criteria for good measurements in research: Validity and reliability. Annals of Spiru Haret University. Economic Series, 17(4), pp.59-82. 190. Mouaky, M., Berrado, A. and Benabbou, L., 2017. Guidelines to choose Operational Excellence techniques/tools for inventory management: the case of pharmaceuticals supply chain. Proceedings of the International Conference on Industrial Engineering and Operations Management, pp. 2387-2396. 191. Mubiri, J.B., Hukkanen, T. and Assigned, A., 2016. Customer Satisfaction in Hotel Services Case-Lake Kivu Serena Hotel. School of Service and Business Management Degree Programme in Facility Management JAMK University of Applied Sciences. 192. Mukasa, B., Ali, M., Farron, M. and Van de Weerdt, R., 2017. Contraception supply chain challenges: a review of evidence from low-and middle-income countries. The European Journal of Contraception and Reproductive Health Care, 22(5), pp.384-390. 193. Muslimen, R., Yusof, S.R.M. and Abidin, A.S.Z., 2013. A case study of lean manufacturing implementation approach in Malaysian automotive components manufacturer. Electrical Engineering and Intelligent Systems, pp.327-335. Springer, New York, NY. 194. Naude, M.J.A., 2009. Supply chain management problems experienced by South African automotive component manufacturers. Doctoral dissertation. 195. Nawanir, G., Lim, K.T. and Othman, S.N., 2015. Measurement instrument for lean manufacturing. International Journal of Applied Science and Technology, 5(4), pp.102-111. 196. Nguyen, P., 2018. The Empirical Review of Supply Chain Performance Measurement in the Manufacturing Industry. Journal of Science in Management and Production, 1(2), pp.23-32. 197. Nitsche, B., 2018. Unravelling the Complexity of Supply Chain Volatility Management. Logistics, 2(3), p.14. 198. Nyhuis, P. and Wolter, C., 2002. Quantifying the rationalization potential in logistics through supply chain design. International Workshop on Performance Measurement (IFIP WG), 5, pp.13-23. 199. Oakland, J.S. and Marosszeky, M., 2017. Total construction management: Lean quality in construction project delivery, Routledge. 200. O'Connel, 2012. Concepts and trade-offs in supply chain finance. Eindhoven: Technische Universiteit Eindhoven. 201. Pakir, M.I.B.K.H., Omar, S.S. and Wei, L.C., 2015, August. Trustworthiness in buyer-supplier relation on supply chain collaboration among SMEs. 2015 International Symposium on Technology Management and Emerging Technologies (ISTMET), pp.454-458. 202. Palinkas, L.A., Horwitz, S.M., Green, C.A., Wisdom, J.P., Duan, N. and Hoagwood, K., 2015. Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), pp.533-544. 203. Pallant, J., 2011. Survival manual. A step by step guide to data analysis using SPSS. 204. Palma-Mendoza, J.A., 2014. Analytical hierarchy process and SCOR model to support supply chain re-design. International Journal of Information Management, 34(5), pp.634-638. 205. Pearce, A. and Pons, D., 2013. Implementing lean practices: managing the transformation risks. Journal of Industrial Engineering, 2013. 206. Pellissier, R., 2008. Business research made easy, Juta and Company Ltd. 207. Phan, A.C., Nguyen, H.T., Nguyen, H.A. and Matsui, Y., 2019. Effect of Total Quality Management Practices and JIT Production Practices on Flexibility Performance: Empirical Evidence from International Manufacturing Plants. Sustainability, 11(11), p.3093. 208. Phelps, T., 2006. Supply Chain Performance Evaluation: Trends and Challenges. American Journal of Engineering and Applied Sciences, 2(1), pp.202-211. 209. Ponto, J., 2015. Understanding and evaluating survey research. Journal of the Advanced Practitioner in Oncology, 6(2), p.168. 210. Popa, A., Hadad, S., Paiusan, R. and Nastase, M., 2018. A new method for agricultural market share assessment. Sustainability, 11(1), pp.1-13. 211. Porter, M.E. and Guth, C., 2012. Redefining German health care: moving to a value-based system. Springer Science & Business Media. 212. Prabir, J., 2007. An Investigation into Indian Apparel and Textile Supply Chain Networks. Unpublished PhD Dissertation (Nottingham Trent University, UK). 213. Prabir, J., 2007. SCOR and benefits of using process reference models. In Proceedings of the 2006 Supply Chain International Conference, Taipei, Taiwan. 214. Pyke, D.F. and Cohen, M.A., 1990. Push and pull in manufacturing and distribution systems. Journal of Operations Management, 9(1), pp.24-43. 215. Qureshi, M.I., Iftikhar, M., Bhatti, M.N., Shams, T. and Zaman, K., 2013. Critical elements in implementations of just-in-time management: empirical study of cement industry in Pakistan. Springer Plus, 2(1), p.645. 216. Ramalho, R., Adams, P., Huggard, P. and Hoare, K., 2015, August. Literature review and constructivist grounded theory methodology. Forum: Qualitative Social Research, 16(3). 217. Ren, C., Dong, J., Ding, H. and Wang, W., 2006, June. A SCOR-based framework for supply chain performance management. 2006 IEEE International Conference on Service Operations and Logistics, and Informatics, pp.1130-1135. 218. Rezaei, J., Papakonstantinou, A., Tavasszy, L., Pesch, U. and Kana, A., 2019. Sustainable product‐package design in a food supply chain: A multi‐criteria life cycle approach. Packaging Technology and Science, 32(2), pp.85-101. 219. Ricken, A. and Meinberg, T., 2012. A Process Reference for Product Innovation and Lifecycle Management. BPTrends, April. 220. Russell, C.J. and Bobko, P., 1992. Moderated regression analysis and Likert scales: Too coarse for comfort. Journal of Applied Psychology, 77(3), p.336. 221. Russell, D.M., Ruamsook, K. and Thomchick, E.A., 2009. Ethanol and the petroleum supply chain of the future: five strategic priorities of integration. Transportation Journal, 48(1), pp.5-22. 222. Sadikoglu, E. and Olcay, H., 2014. The effects of total quality management practices on performance and the reasons of and the barriers to TQM practices in Turkey. Advances in Decision Sciences, 2014. 223. Saleh, C., Mubiena, G.F., Immawan, T. and Hassan, A., 2016, February. Lean production in improving supply chain performance through hybrid model SCOR 11.0-system dynamics. IOP Conference Series: Materials Science and Engineering, 114(1), p.012069. IOP Publishing. 224. Salkind, N., 2010. Cross-sectional design. Encyclopedia of Research Design, pp.314-315. 225. Schade, A., 2015. Pilot testing: Getting it right (before) the first time. Date Retrieved, 19, p.2015. 226. Schafer, J.L. and Olsen, M.K., 1998. Multiple imputation for multivariate missing-data problems: A data analyst's perspective. Multivariate Behavioral Research, 33(4), pp.545-571. 227. Schmitz, P.M., 2007. Use of supply chains and supply chain managment to improve the efficiency and effectiveness of GIS units. Doctoral dissertation, University of Johannesburg. 228. Schmitz, P.M., Scheepers, L., De Wit, P.W.C. and De la Rey, A., 2007. Understanding data supply chains by using the Supply-Chain Operations Reference (SCOR) model. Logistics Research Network Annual Conference, United Kingdom. 229. Schneider, O., Lange, I. and Nitu, B., 2007, June. Enabling industrial service providers to offer comprehensive service contracts. 2007 IEEE International Technology Management Conference (ICE), pp.1-8. 230. Sebhatu, S.P., 2008, December. Sustainability Performance Measurement for sustainable organizations: beyond compliance and reporting. 11th QMOD Conference. Quality Management and Organizational Development Attaining Sustainability from Organizational Excellence to SustainAble Excellence; 20-22 August; 2008 in Helsingborg; Sweden, 033, pp.75-87. Linköping University Electronic Press. 231. Seifert, M., Wiesner, S. and Thoben, K.D., 2008. Prospective performance measurement in virtual organizations. Collaborative Networks: Reference Modeling, pp.319-326. Springer, Boston, MA. 232. Sekaran, U. and Bougie, R., 2016. Research methods for business: A skill building approach, John Wiley & Sons. 233. Setak, M., Sharifi, S. and Alimohammadian, A., 2012. Supplier selection and order allocation models in supply chain management: a review. World Applied Sciences Journal, 18(1), pp.55-72. 234. Shanahan, M., 2010. Cross-sectional design. Encyclopedia of case study research. 235. Sheehan, K.B., 2001. E-mail survey response rates: A review. Journal of Computer-Mediated Communication, 6(2), p.JCMC621. 236. Simon, A.T., Serio, L.C.D., Pires, S.R.I. and Martins, G.S., 2015. Evaluating supply chain management: A methodology based on a theoretical model. Revista de Administração Contemporânea, 19(1), pp.26-44. 237. Singh, A.R.P., Nag, S., Chattopadhyay, S., Ren, Y., Tiley, J., Viswanathan, G.B., Fraser, H.L. and Banerjee, R., 2013. Mechanisms related to different generations of γ′ precipitation during continuous cooling of a nickel base superalloy. Acta Materialia, 61(1), pp.280-293. 238. Singh, R.J., Sohani, N. and Marmat, H., 2013. Effect of lean/JIT practices and supply chain integration on lead time performance. Journal of Supply Chain Management Systems, 2(2), p.37. 239. Skinner, C.J., 2014. Probability proportional to size (PPS) sampling. Wiley StatsRef: Statistics Reference Online, pp.1-5. 240. Stank, T.P., Goldsby, T.J., Vickery, S.K. and Savitskie, K., 2003. Logistics service performance: estimating its influence on market share. Journal of Business Logistics, 24(1), pp.27-55. 241. Stefanovic, N., 2014. Proactive supply chain performance management with predictive analytics. The Scientific World Journal, 2014. 242. Stephens, S., 2001. Supply chain operations reference model version 5.0: a new tool to improve supply chain efficiency and achieve best practice. Information Systems Frontiers, 3(4), pp.471-476. 243. Storey, J., Emberson, C., Godsell, J. and Harrison, A., 2006. Supply chain management: theory, practice and future challenges. International Journal of Operations and Production Management, 26(7), pp.754-774. 244. Summers, S., 1991. Selecting the sample for a research study. Journal of Post Anesthesia Nursing, 6(5), pp.355-358. 245. Suresh, K., Thomas, S.V. and Suresh, G., 2011. Design, data analysis and sampling techniques for clinical research. Annals of Indian Academy of Neurology, 14(4), p.287. 246. Susan, K.N. and Wagoki, J., 2014. Effect of Strategic Material Sourcing on Operational Performance of Manufacturing Firms: A Case of East African Breweries Ltd., Kenya. International Journal of Science and Research (IJSR), 3(11), pp.124-130. 247. Swee, S.K., Sev, V.N., Amer, Y. and Yen, P.S., 2010, October. Implementation of Six Sigma methodology to improve supply chain network in the context of Malaysian manufacturing industries. 2010 8th International Conference on Supply Chain Management and Information, pp.1-8. 248. Tan, K.C., 2001. A framework of supply chain management literature. European Journal of Purchasing and Supply Management, 7(1), pp.39-48. 249. Tang, O. and Musa, S.N., 2011. Identifying risk issues and research advancements in supply chain risk management. International Journal of Production Economics, 133(1), pp.25-34. 250. Tasmin, R., Soon, K., Abdul Hamid, N.A., Malek, N.A., Shylina, D., Takala, J., Yang, C. and Yang, L., 2013. Sustainable competitive advantage in furniture industry: comparative studies in Finland, China and Malaysia. In Proceedings, the 2nd International Conference on Global Optimization and Its Applications, Malaysia. 251. Tate, W.L., Ellram, L.M., Bals, L., Hartmann, E. and Van der Valk, W., 2010. An agency theory perspective on the purchase of marketing services. Industrial Marketing Management, 39(5), pp.806-819. 252. Tayles, M. and Drury, C., 2001. Moving from make/buy to strategic sourcing: the outsource decision process. Long Range Planning, 34(5), pp.605-622. 253. Theeranuphattana, A. and Tang, J.C., 2007. A conceptual model of performance measurement for supply chains: alternative considerations. Journal of Manufacturing Technology Management, 19(1), pp.125-148. 254. Theeranuphattana, A., Tang, J. and Khang, D.B., 2012. An integrated approach to measuring supply chain performance. Industrial Engineering and Management Systems, 11(1), pp.54-69. 255. Thompson, S., 2012. Chapter 11, Stratified sampling, Sampling, 3rd ed., Wiley, pp.141-156. 256. Thurik, R. and Wennekers, S., 2004. Entrepreneurship, small business and economic growth. Journal of Small Business and Enterprise Development, 11(1), pp.140-149. 257. Trkman, P., McCormack, K., De Oliveira, M.P.V. and Ladeira, M.B., 2010. The impact of business analytics on supply chain performance. Decision Support Systems, 49(3), pp.318-327. 258. Tseng, M.L., 2011. Green supply chain management with linguistic preferences and incomplete information. Applied Soft Computing, 11(8), pp.4894-4903. 259. Uebersax, J.S., 2006. Likert scales: dispelling the confusion. Statistical Methods for Rater Agreement, 31. 260. Van Looy, A. and Shafagatova, A., 2016. Business process performance measurement: a structured literature review of indicators, measures and metrics. Springer Plus, 5(1), p.1797. 261. Vanany, I., Suwignjo, P. and Yulianto, D., 2005. Design of supply chain performance measurement system for lamp industry. In 1st International Conference on Operations and Supply Chain Management, pp.78-86. 262. Varsei, M., Soosay, C., Fahimnia, B. and Sarkis, J., 2014. Framing sustainability performance of supply chains with multidimensional indicators. Supply Chain Management: an International Journal, 19(3), pp.242-257. 263. Velicer, W.F. and Fava, J.L., 1987. An evaluation of the effects of variable sampling on component, image, and factor analysis. Multivariate Behavioral Research, 22(2), pp.193-209. 264. Waal, A. A. de, 2007. Measuring supply chain performance: Current research and future directions. International Journal of Productivity and Performance Management, 55(3), pp.242-258. 265. Walpole, R.E., Myers, R.H., Myers, S.L. and Ye, K., 2012. Probability & statistics for engineers & scientists, Prentice Hall. 266. Wang, W.Y., Chan, H.K. and Pauleen, D.J., 2010. Aligning business process reengineering in implementing global supply chain systems by the SCOR model. International Journal of Production Research, 48(19), pp.5647-5669. 267. Weyers, M., 2017. An application of the supply chain operations reference model for the service supply chain for standardised back office services. Doctoral dissertation, Stellenbosch: Stellenbosch University. 268. Whitfield, K., Pendleton, A., Sengupta, S. and Huxley, K., 2017. Employee share ownership and organisational performance: A tentative opening of the black box. Personnel Review, 46(7), pp.1280-1296. 269. Wieland, A., Durach, C.F., Kembro, J. and Treiblmaier, H., 2017. Statistical and judgmental criteria for scale purification. Supply Chain Management: an International Journal, 22(4), pp.321-328. 270. Williams, B., Onsman, A. and Brown, T., 2010. Exploratory factor analysis: A five-step guide for novices. Australasian Journal of Paramedicine, 8(3). 271. Wilson, J., 2014. Essentials of business research: A guide to doing your research project, Sage. 272. Wrigley, C. and Straker, K., 2016. Designing innovative business models with a framework that promotes experimentation. Strategy and Leadership, 44(1), pp.11-19. 273. Wu, K.J., Liao, C.J., Tseng, M.L., Lim, M.K., Hu, J. and Tan, K., 2017. Toward sustainability: using big data to explore the decisive attributes of supply chain risks and uncertainties. Journal of Cleaner Production, 142, pp.663-676. 274. Xia, L.X.X., 2006, August. Supply chain modelling and improvement in telecom industry: a case study. In 2006 4th IEEE International Conference on Industrial Informatics, pp.1159-1164. 275. Yildiz, T., 2015. An empirical study on the relationship between logistics performance and education. Business, Management and Education, 13(2), pp.249-275. 276. Yong, A.G. and Pearce, S., 2013. A beginner’s guide to factor analysis: Focusing on exploratory factor analysis. Tutorials in Quantitative Methods for Psychology, 9(2), pp.79-94. 277. Youssef, A.E., Dixon, R. and Ragheb, M.A., 2006. The contemporary performance measurement techniques in egypt: a contingency approach. Performance Measurement and Management Control: Improving Organizations and Society, pp.305-333. 278. Yusoff, R. and Mohd Janor, R., 2014. Generation of an interval metric scale to measure attitude. Sage Open, 4(1), p.2158244013516768. 279. Yusup, M.Z., Mahmood, W.W., Salleh, M.R. and Rosdi, M.M., 2013. The trigger signal for lean production practices: a review. Global Engineers ad Technologists Review, 3(6), pp.23-32. 280. Zhao, W., Yu, Q.Q., Li, H.S. and Tian, Y.Z., 2014, August. Study on the relationship between JIT practices and operational performance based on the cost leading strategy. In 2014 International Conference on Management Science and Engineering 21th Annual Conference Proceedings, pp.329-334. 281. Zhou, H., Benton Jr, W.C., Schilling, D.A. and Milligan, G.W., 2011. Supply chain integration and the SCOR model. Journal of Business Logistics, 32(4), pp.332-344. 282. Zintgraf, L.M., Roijers, D.M., Linders, S., Jonker, C.M. and Nowé, A., 2018, July. Ordered preference elicitation strategies for supporting multi-objective decision making. In Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, pp.1477-1485.