Using interpretive structural modelling to identify and rank performance measures

Baltic Journal of Management - 2013
SusanaAzevedo1, HelenaCarvalho2, V.Cruz‐Machado2
1Management and Economics Department, University of Beira Interior, Covilhã, Portugal
2Mechanical and Industrial Engineering, Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa, Caparica, Portugal

Tóm tắt

PurposeThe main purpose of this paper is to identify and rank a set of performance measures using the approach of interpretive structural modelling (ISM) to support the evaluation of automotive supply chain performance.Design/methodology/approachThe paper develops a framework to analyze the interactions among a suggested set of performance measures using the ISM approach. To identify the contextual relationships among the suggested measures, five experts from the automotive industry were consulted.FindingsUsing the ISM approach the performance measures were clustered according to their driving power and dependence power. Inventory level and lead time are the two performance measures at the bottom level of the hierarchy, implying higher driving power. Operational costs, business wastage, environmental costs, delivery time and customer satisfaction are identified as autonomous measures. This means that they are relatively disconnected from the other suggested performance measures. It is also observed that the cash‐to‐cash cycle is a weak driver but strongly dependent on the other performance measures.Practical implicationsThe proposed approach gives managers a better understanding of the performance measures that have most influence on others (driving performance measures) and those measures which are most influenced by others (dependent performance measures). This kind of information is strategic for managers who can use it to identify which performance measures they should concentrate on, and how they can manage the trade‐offs between measures.Originality/valueThis paper highlights the deployment of ISM as a management decision support tool in the identification and ranking of a set of performance measures to make part of a system for the measurement of supply chain performance.

Từ khóa


Tài liệu tham khảo

Akyuz, G.A. and Erkan, T.E. (2010), “Supply chain performance measurement: a literature review”, International Journal of Production Research, Vol. 48 No. 17, pp. 5137‐55.

Anderson, P., Aronson, H. and Storhagen, N.G. (1989), “Measuring logistics performance”, Engineering Costs and Production Economics, Vol. 17 Nos 1/4, pp. 253‐62.

Askariazad, M. and Wanous, M. (2009), “A proposed value model for prioritising supply chain performance measures”, International Journal of Business Performance and Supply Chain Modelling, Vol. 1 Nos 2/3, pp. 115‐28.

Azevedo, S., Carvalho, H. and Cruz‐Machado, V. (2011), “The influence of green practices on supply chain performance: a case study approach”, Transportation Research Part E: Logistics and Transportation Review, Vol. 47 No. 6, pp. 850‐71.

Bayraktar, E., Demirbag, M., Koh, S., Tatoglu, E. and Zaim, H. (2009), “A causal analysis of the impact of information systems and supply chain management practices on operational performance: evidence from manufacturing SMEs in Turkey”, International Journal of Production Economics, Vol. 122 No. 1, pp. 133‐49.

Beamon, B. (1999), “Measuring supply chain performance”, International Journal of Operations & Production Management, Vol. 19 Nos 3/4, pp. 275‐92.

Berry, W., Bruun, P. and Ward, P. (2002), “Lean manufacturing: a mapping of competitive, initiatives, practices, and operational performance in Danish manufacturers”, Proceedings of 9th International Conference, European Operations Management Association, Copenhagen, Denmark.

Bourne, M., Mills, J., Wilcox, M., Neely, A. and Platts, K. (2000), “Designing, implementing and updating performance measurement systems”, International Journal of Operations & Production Management, Vol. 20 No. 7, pp. 54‐771.

Cai, J., Liu, X., Xiao, Z. and Liu, J. (2009), “Improving supply chain performance management: a systematic approach to analyzing iterative KPI accomplishment”, Decision Support Systems, Vol. 46 No. 2, pp. 512‐21.

Carvalho, H., Duarte, S. and Machado, V. (2011), “Lean, agile, resilient and green: divergencies and synergies”, International Journal of Lean Six Sigma, Vol. 2 No. 2, pp. 151‐79.

Chaharsooghi, S. and Heydari, J. (2010), “LT variance or LT mean reduction in supply chain management: which one has a higher impact on supply chain performance?”, International Journal of Production Economics, Vol. 124 No. 2, pp. 475‐81.

Chan, F. (2003), “Performance measurement in a supply chain”, International Journal of Advanced Manufacturing Technology, Vol. 21 No. 7, pp. 534‐48.

Chan, F. and Qi, H. (2003), “An innovative performance measurement method for supply chain management”, Supply Chain Management: An International Journal, Vol. 8 Nos 3/4, pp. 209‐23.

Charan, P., Shankar, R. and Baisya, R. (2008), “Analysis of interactions among the variables of supply chain performance measurement system implementation”, Business Process Management Journal, Vol. 14 No. 4, pp. 512‐29.

Christiansen, T., Berry, W.L., Bruun, P. and Ward, P. (2003), “A mapping of competitive priorities, manufacturing practices, and operational performance in groups of Danish manufacturing companies”, International Journal of Operations & Production Management, Vol. 23 No. 10, pp. 1163‐83.

Cooper, H.M. (1988), “Organizing knowledge synthesis: a taxonomy of literature reviews”, Knowledge in Society, Vol. 1 No. 1, pp. 104‐26.

Cuthbertson, R. and Piotrowicz, W. (2011), “Performance measurement systems in supply chains: a framework for contextual analysis”, International Journal of Productivity and Performance Management, Vol. 60 No. 6, pp. 583‐602.

Defee, C. and Stank, T. (2005), “Applying the strategy‐structure‐performance paradigm to the supply chain environment”, International Journal of Logistics Management, Vol. 16 No. 1, pp. 28‐50.

Farris, T. and Hutchison, P. (2002), “Cash‐to‐cash: the new supply chain management metric”, International Journal of Physical Distribution & Logistics Management, Vol. 32 Nos 3/4, pp. 288‐98.

Ferreira, A. and Otley, D. (2009), “The design and use of performance management systems: an extended framework for analysis”, Management Accounting Research, Vol. 20 No. 4, pp. 263‐82.

Franco‐Santos, M., Lucianetti, L. and Bourne, M. (2012), “Contemporary performance measurement systems: a review of their consequences and a framework for research”, Management Accounting Research, Vol. 23 No. 2, pp. 79‐119.

Franco‐Santos, M., Kennerley, M., Micheli, P., Martinez, V., Mason, S., Marr, B., Gray, D. and Neely, A. (2007), “Towards a definition of a business performance measurement system”, International Journal of Operations & Production Management, Vol. 27 No. 8, pp. 784‐801.

Galbraith, J.R. and Nathanson, D.A. (1978), Strategy Implementation: The Role of Structure and Process, West Publishing Co., St Paul, MN.

Galunic, D.C. and Eisenhardt, K.M. (1994), “Renewing the strategy‐structure‐performance paradigm”, Research in Organizational Behavior, Vol. 16, pp. 215‐55.

Ghalayini, A. and Noble, J. (1996), “The changing basis of performance measurement”, International Journal of Operation and Production Management, Vol. 16 No. 8, pp. 63‐88.

Goldsby, T., Griffis, S. and Roath, A. (2006), “Modeling lean, agile and leagile supply chain strategies”, Journal of Business Logistics, Vol. 27 No. 1, pp. 57‐80.

Gunasekaran, A., Patel, C. and McGaughey, R.E. (2004), “A framework for supply chain performance measurement”, International Journal of Production Economics, Vol. 87 No. 3, pp. 333‐47.

Gunasekaran, A., Patel, C. and Tirtiroglu, E. (2001), “Performance measures and metrics in a supply chain environment”, International Journal of Operations & Production Management, Vol. 21 Nos 1/2, pp. 71‐87.

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.

Jebas, M.J. (1995), “Performance measurement and performance management”, International Journal of Production Economics, Vol. 41 Nos 1/3, pp. 23‐35.

Kannan, G., Kannan, D. and Haq, A.N. (2010), “Analyzing supplier development criteria for an automobile industry”, Industrial Management+Data Systems, Vol. 110 No. 1, pp. 43‐62.

Kaplan, R. and Norton, D. (1996), The Balanced Scorecard, Harvard Business School Press, Boston, MA.

Kaydos, W. (1991), Measuring, Managing and Maximizing Performance, Productivity Press, Portland, OR.

Lambert, D. and Pohlen, L. (2001), “Supply chain metrics”, The International Journal of Logistics Management, Vol. 12 No. 1, pp. 1‐19.

Lambert, D., Stock, J. and Ellram, L. (1998), Fundamentals of Logistics Management, Irwin/McGraw‐Hill, London.

Lancaster, C., Stevens, J. and Jennings, J. (1998), “Corporate liquidity and the significance of earnings versus cash flow”, Journal of Applied Business Research, Vol. 14 No. 4, pp. 27‐38.

Lin, Y.‐T., Lin, C.‐L. and Yu, H.‐C. (2011), “Utilisation of interpretive structural modelling method in the analysis of interrelationship of vendor performance factors”, International Journal of Business Performance Management, Vol. 12 No. 3, pp. 260‐74.

Linton, J.D., Klassen, R. and Jayaraman, V. (2007), “Sustainable supply chains: an introduction”, Journal of Operations Management, Vol. 25 No. 6, pp. 1075‐82.

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

Manoharan, T.R., Muralidharan, C. and Deshmukh, S.G. (2010), “Analyzing the interaction of performance appraisal factors using interpretive structural modeling”, Performance Improvement, Vol. 49 No. 6, pp. 25‐35.

Mathison, S. (1988), “Why triangulate?”, Educational Research, Vol. 17 No. 2, pp. 13‐17.

Meyr, H. (2004), “Supply chain planning in the German automotive industry”, OR Spectrum, Vol. 26 No. 4, pp. 447‐70.

Miles, R.E. and Snow, C.C. (1978), Organizational Strategy, Structure and Process, McGraw‐Hill, New York, NY.

Min, H. and Zhou, G. (2002), “Supply chain modeling: past, present and future”, Computers & Industrial Engineering, Vol. 43 Nos 1/2, pp. 231‐49.

Neely, A. (2000), “Performance measurement system design: developing and testing a process‐based approach”, International Journal of Operations & Production Management, Vol. 20 No. 10, pp. 1119‐45.

Neely, A. (2005), “The evolution of performance measurement research: developments in the last decade and a research agenda for the next”, International Journal of Operations & Production Management, Vol. 25 No. 12, pp. 1264‐77.

Neely, A., Gregory, M. and Platts, K. (2005), “Performance measurement system design: a literature review and research agenda”, International Journal of Operations & Production Management, Vol. 25 No. 12, pp. 1228‐63.

Neto, M. and Pires, S. (2012), “Performance measurement in supply chains: a study in the automotive industry”, in Carmo, J.P. and Ribeiro, J.E. (Eds), New Advances in Vehicular Technology and Automotive Engineering, INTECH, Winchester, pp. 379‐98.

Oppermann, M. (2000), “Triangulation – a methodological discussion”, The International Journal of Tourism Research, Vol. 2 No. 2, pp. 141‐6.

Otley, D.T. (1980), “The contingency theory of management accounting: achievement and prognosis”, Accounting, Organizations and Society, Vol. 5 No. 4, pp. 413‐28.

Otley, D.T. (1999), “Performance management: a framework for management control systems research”, Management Accounting Research, Vol. 10, pp. 363‐82.

Pfohl, H.‐C., Gallus, P. and Thomas, D. (2011), “Interpretive structural modeling of supply chain risks”, International Journal of Physical Distribution & Logistics Management, Vol. 41 No. 9, pp. 839‐59.

Pochampally, K.K., Gupta, S.M. and Govindan, K. (2009), “Metrics for performance measurement of a reverse/closed–loop supply chain”, International Journal of Business Performance and Supply Chain Modelling, Vol. 1 No. 1, pp. 8‐32.

Rao, P. and Holt, D. (2005), “Do green supply chains lead to competitiveness and economic performance?”, International Journal of Operations & Production Management, Vol. 25 No. 9, pp. 898‐916.

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.

Sagheer, S., Yadav, S. and Deshmukh, S. (2009), “An application of interpretative structural modeling of the compliance to food standards”, International Journal of Productivity and Performance Management, Vol. 58 No. 2, pp. 136‐59.

Schermerhorn, J. and Chappell, D. (2000), Introducing Management – The Wiley/Wall Street Journal Series, Wiley, New York, NY.

Schroer, B. (2004), “Simulation as a tool in understanding the concepts of lean manufacturing”, Simulation, Vol. 80 No. 3, pp. 171‐5.

Sharma, R. and Garg, S. (2010), “Interpretive structural modelling of enablers for improving the performance of automobile service centre”, International Journal of Services Operations and Informatics, Vol. 5 No. 4, pp. 351‐72.

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.

Singleton, R.A. and Straits, B.C. (1999), Approaches to Social Research, Oxford University Press, New York, NY.

Smith, M. (2005), Performance Measurement and Management: A Strategic Approach to Management Accounting, Sage, London.

Srivastava, S.K. (2007), “Green supply‐chain management: a state‐of‐the‐art literature review”, International Journal of Management Reviews, Vol. 9 No. 1, pp. 53‐80.

Taticchi, P., Tonelli, F. and Cagnazzo, L. (2010), “Performance measurement and management: a literature review and a research agenda”, Measuring Business Excellence, Vol. 14 No. 1, pp. 4‐18.

Thakkar, J., Deshmukh, S.G., Gupta, A.D. and Shankar, R. (2007), “Development of a balanced scorecard: an integrated approach of interpretive structural modeling (ISM) and analytic network process (ANP)”, International Journal of Productivity and Performance Management, Vol. 56 No. 1, pp. 25‐59.

Ting, C. (2006), “A study of the relationships between business environment characteristics, competitive priorities, supply chain structures, and firm performance in the United States technical textile industry”, The University of North Carolina, Greensboro, NC.

Tsai, W. and Hung, S. (2009), “A fuzzy goal programming approach for green supply chain optimisation”, International Journal of Production Research, Vol. 47 No. 18, pp. 4991‐5017.

Varma, S., Wadhwa, S. and Deshmukh, S. (2008), “Evaluating petroleum supply chain performance: application of analytical hierarchy process to balanced scorecard”, Asia Pacific Journal of Marketing and Logistics, Vol. 20 No. 3, pp. 343‐56.

Voss, C., Tsikriktsis, N. and Frohlich, M. (2002), “Case research in operations management”, International Journal of Operations & Production Management, Vol. 22 No. 2, pp. 195‐219.

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

Warfield, J.N. (1976), “Implication structures for system interconnection matrices”, Transactions on Systems, Man, and Cybernetics, Vol. 6 No. 1, pp. 18‐24.

Whicker, L., Bernon, M., Templar, S. and Mena, C. (2009), “Understanding the relationships between time and cost to improve supply chain performance”, International Journal of Production Economics, Vol. 121 No. 2, pp. 641‐50.

Wong, W.P. (2009), “Performance evaluation of supply chain in stochastic environment: using a simulation based DEA framework”, International Journal of Business Performance and Supply Chain Modelling, Vol. 1 Nos 2/3, pp. 203‐28.

Yin, R. (2002), Case Study Research: Design and Methods, Applied Social Research Methods Series, Vol. 5, Sage, Thousand Oaks, CA.

Zhu, Q. and Sarkis, J. (2004), “Relationships between operational practices and performance among early adopters of green supply chain management practices in Chinese manufacturing enterprises”, Journal of Operations Management, Vol. 22 No. 3, pp. 265‐89.

Zhu, Q., Sarkis, J. and Geng, Y. (2005), “Green supply chain management in China: pressures, practices and performance”, International Journal of Operations & Production Management, Vol. 25 Nos 5/6, pp. 449‐69.

Zhu, Q., Sarkis, J. and Lai, K. (2008), “Confirmation of a measurement model for green supply chain management practices implementation”, International Journal of Production Economics, Vol. 111 No. 2, pp. 261‐73.

Thông tin
Thông tin xuất bản

Baltic Journal of Management

Thông tin tác giả