Analysis of interactions among the variables of supply chain performance measurement system implementation

Emerald - Tập 14 Số 4 - Trang 512-529 - 2008
ParikshitCharan1, RaviShankar1, Rajat K.Baisya
1Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, India

Tóm tắt

PurposeThe purpose of this paper is to determine the key supply chain performance measurement system (SCPMS) implementation variables, on which the top management should focus, so as to improve the effectiveness and efficiency of supply chain (SC).Design/methodology/approachIn this paper, an interpretive structural modeling (ISM)‐based approach has been employed to model the SCPMS implementation variables. These variables have been categorized under “enablers” and “results.” The enablers are the variables that help boost the SCPMS implementation variables, while results variables are the outcome of good SCPMS implementation.FindingsThe paper highlights the variables associated with implementation of SCPMS. A key finding of this modeling is that awareness about performance measurement system (PMS) in SC is a very significant enabler. For better results, top management should focus on improving the high‐driving power enablers such as awareness of PMS in SC, commitment by the top management, consistency with strategic goals, funding for PMS implementation, and effective information systems.Originality/valueIn this paper, an interpretation of SCPMS implementation variables in terms of their driving and dependence powers has been carried out. Those variables possessing higher driving power in the ISM need to be taken care of on a priority basis because there are a few other dependent variables being affected by them.

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Tài liệu tham khảo

Andersen, B. and Pettersen, P‐G. (1996), The Benchmarking Handbook, Chapman & Hall, New York, NY.

Austin, J.E. (1990), Managing in Developing Countries, Free Press, New York, NY.

Balsmeier, P.W. and Voisin, W. (1996), “Supply chain management: a time – based strategy”, Industrial Management, Vol. 38 No. 5, pp. 24‐7.

Beamon, B. (1998), “Supply chain design and analysis: models and methods”, International Journal of Production Economics, Vol. 55, pp. 281‐94.

Beamon, B. (1999), “Measuring supply chain performance”, International Journal of Operations & Production Management, Vol. 19 No. 3, pp. 275‐92.

Bechtel, C. and Jayaram, J. (1997), “Supply chain management: a strategic perspective”, The International Journal of Logistics Management, Vol. 8 No. 1, pp. 15‐34.

Bender, P.S. (2000), “Debunking five supply chain myths”, Supply Chain Management Review, Vol. 4 No. 1, pp. 52‐8.

Brewer, P.C. and Speh, T.W. (2001), “Adapting the balanced scorecard to supply chain management”, Supply Chain Management Review, Vol. 5 No. 2, p. 48.

Chen, I.J. and Paulraj, A. (2004), “Towards a theory of supply chain management: the constructs and measurements”, Journal of Operations Management, Vol. 22 No. 2, pp. 119‐50.

Christopher, M. and Towill, D.R. (2001), “An integrated model for the design of agile supply chains”, International Journal of Physical Distribution & Logistics Management, Vol. 31 No. 4, pp. 235‐46.

Fawcett, S., Smith, S. and Cooper, M. (1997), “Strategic intent, measurement capability, and operational success: making the connection”, International Journal of Physical Distribution & Logistics Management, Vol. 27 No. 7, pp. 410‐21.

Ghalayini, A.M. and James, S.N. (1996), “The changing basis of performance measurement”, International Journal of Operations & Production Management, Vol. 16 No. 8, pp. 63‐80.

Gilmour, P. (1998), “Benchmarking supply chain operations”, Benchmarking for Quality Management & Technology, Vol. 5 No. 4, pp. 283‐90.

Guiffrida, A.L. and Nagi, R. (2005), “Cost characterizations of supply chain delivery performance”, International Journal of Production Economics, Vol. 102, pp. 22‐36.

Gunasekaran, A., Patel, C. and McGaughey, R.E. (2004), “A framework for supply chain performance measurement”, International. Journal of Production Economics, Vol. 87, pp. 333‐47.

Hervani, A.A., Helms, M.M. and Sarkis, J. (2005), “Performance measurement for green supply chain management”, Benchmarking: An International Journal, Vol. 12 No. 4, pp. 330‐53.

Holmberg, S. (2000), “A systems perspective on supply chain measurements”, International Journal of Physical Distribution & Logistics Management, Vol. 30 No. 10, pp. 847‐68.

Jharkharia, S. and Shankar, R. (2005), “IT‐enablement of supply chains: understanding the barriers”, The Journal of Enterprise Information Management, Vol. 18 No. 1, pp. 11‐27.

Jharkharia, S. and Shankar, R. (2006), “Supply chain management: some sectoral dissimilarities in the Indian manufacturing industry”, Supply Chain Management: An International Journal, Vol. 11 No. 4, pp. 345‐52.

Kaplan, R.S. and Norton, D.P. (1992), “The balanced scorecard – measures that drive performance”, Harvard Business Review, Vol. 70 No. 1, pp. 71‐9.

Kilpatrick, J. and Factor, R. (2000), “Logistics in Canada survey: tracking year 2000 supply chain issues and trends”, Materials Management and Distribution, Vol. 45 No. 1, pp. 16‐20.

Mandal, A. and Deshmukh, S.G. (1994), “Vendor selection using interpretive structural modeling (ISM)”, International Journal Operations & Production Management, Vol. 14 No. 6, pp. 52‐9.

Maskell, B.H. (1991), Performance Measurement for World Class Manufacturing, Productivity Press, Inc., Portland, OR.

Morgan, C. (2004), “Structure, speed and salience: performance measurement in the supply chain”, Business Process Management Journal, Vol. 10 No. 5, pp. 522‐36.

Novack, R.A., Langley, C.J. Jr and Rinehart, L.M. (1995), Creating Logistics Value: Themes for the Future, Council of Logistics Management, Oak Brook, IL.

Ravi, V. and Shankar, R. (2005), “Analysis of interactions among the barriers of reverse logistics”, Technological Forecasting & Social Change, Vol. 72 No. 8, pp. 1011‐29.

Saad, M. and Patel, B. (2006), “An investigation of supply chain performance measurement in the Indian automotive sector”, Benchmarking: An International Journal, Vol. 13 Nos 1/2, pp. 36‐53.

Sage, A.P. (1977), Interpretive Structural Modeling: Methodology for Large‐Scale Systems, McGraw‐Hill, New York, NY.

Schroeder, R.G., John, C.A. and Scudder, G.D. (1986), “White collar productivity measurement”, Management Decision, Vol. 24 No. 5, pp. 3‐7.

Shepherd, C. and Günter, H. (2006), “Measuring supply chain performance: current research and future directions”, International Journal of Productivity and Performance Management, Vol. 55 Nos 3/4, pp. 242‐58.

Stewart, G. (1995), “Supply chain performance benchmarking study reveals keys to supply chain excellence”, Logistics Information Management, Vol. 8 No. 2, pp. 38‐44.

Towill, D.R. (1997), “The seamless chain – the predator's strategic advantage”, International Journal of Technology Management, Vol. 13 No. 1, pp. 37‐56.

van Hoek, R.I. (1998), “Measuring the unmeasurable – measuring and improving performance in the supply chain”, Supply Chain Management, Vol. 3 No. 4, pp. 187‐92.

Warfield, J.W. (1974), “Developing interconnected matrices in structural modeling”, IEEE Transactions on Systems, Man and Cybernetics, Vol. 4 No. 1, pp. 51‐81.

Zaire, M. and Whymark, J. (2000), “The transfer of best practice: how to build a culture of benchmarking and continuous learning – part 1”, Benchmarking: An International Journal, Vol. 7 No. 1, pp. 62‐79.

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Emerald

Tập 14 Số 4

512-529

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