Dealing with supply chain risks
Tóm tắt
The effects of supply chain risk management (SCRM) on the performance of a supply chain remain unexplored. It is assumed that SCRM helps supply chains to cope with vulnerabilities both proactively by supporting robustness and reactively by supporting agility. Both dimensions are assumed to have an influence on the supply chain's customer value and on business performance. The aim of this research is to provide clarity by empirically testing these hypotheses and scrutinizing the findings by the means of case studies.
The research is empirical. Survey data were collected from 270 manufacturing companies for hypotheses testing via structural equation modeling. Additionally, qualitative data were collected to explore the nature of non‐hypothesized findings.
It is found that SCRM is important for agility and robustness of a company. Both agility and robustness show to be important in improving performance. While agility has a strong positive effect only on the supply chain's customer value, but not directly on business performance, robustness has a strong positive effect on both performance dimensions. This important finding directs the strategic attention from agility‐centered supply chains to ones that are both robust and agile. The case studies provide insights to the fact that robustness can be considered a basic prerequisite to deal with supplier‐side risks, while agility is necessary to deal with customer‐side risks. The amount of agility and robustness needs to fit to the competitive strategy.
Since volatility has increasingly become a prevalent state of supply chains, companies need to consider robustness to be of primary importance to withstand everyday risks and exceptions.
This is the first study to view the relationship between SCRM, agility/robustness, and performance.
Tài liệu tham khảo
Aastrup, J. and Halldórsson, Á. (2008), “Epistemological role of case studies in logistics: a critical realist perspective”, International Journal of Physical Distribution & Logistics Management, Vol. 38 No. 10, pp. 746‐63.
Armstrong, J.S. and Overton, T.S. (1977), “Estimating nonresponse bias in mail surveys”, Journal of Marketing Research, Vol. 14 No. 3, pp. 396‐402.
Asbjørnslett, B.E. (2008), “Assessing the vulnerabilty of supply chains”, in Zsidisin, G.A. and Ritchie, B. (Eds), Supply Chain Risk: A Handbook of Assessment, Management & Performance, Springer, New York, NY, pp. 15‐33.
Bagozzi, R.P. and Yi, Y. (1988), “On the evaluation of structural equation models”, Journal of the Academy of Marketing Science, Vol. 16 No. 1, pp. 74‐94.
Bernardes, E.S. and Hanna, M.D. (2009), “A theoretical review of flexibility, agility and responsiveness in the operations management literature: toward a conceptual definition of customer responsiveness”, International Journal of Operations & Production Management, Vol. 29 No. 1, pp. 30‐53.
Blackhurst, J.V., Scheibe, K.P. and Johnson, D.J. (2008), “Supplier risk assessment and monitoring for the automotive industry”, International Journal of Physical Distribution & Logistics Management, Vol. 38 No. 2, pp. 143‐65.
Bode, C., Wagner, S.M., Petersen, K.J. and Ellram, L.M. (2011), “Understanding responses to supply chain disruptions: insights from information processing and resource dependence perspectives”, Academy of Management Journal, Vol. 54 No. 4, pp. 833‐56.
Boyer, K.K. and Swink, M.L. (2008), “Empirical elephants – why multiple methods are essential to quality research in operations and supply chain management”, Journal of Operations Management, Vol. 26 No. 3, pp. 338‐44.
Charles, A., Lauras, M. and Wassenhove, L.V. (2010), “A model to define and assess the agility of supply chains: building on humanitarian experience”, International Journal of Physical Distribution & Logistics Management, Vol. 40 Nos 8/9, pp. 722‐41.
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.
Choi, T.Y., Dooley, K.J. and Rungtusanatham, M. (2001), “Supply networks and complex adaptive systems: control versus emergence”, Journal of Operations Management, Vol. 19 No. 3, pp. 351‐66.
Chopra, S. and Meindl, P. (2009), Supply Chain Management, 4th ed., Prentice‐Hall, Upper Saddle River, NJ.
Christopher, M. (2005), Logistics & Supply Chain Management: Creating Value‐adding Networks, 3rd ed., Pearson, Harlow.
Christopher, M. and Holweg, M. (2011), “‘Supply chain 2.0’: managing supply chains in the era of turbulence”, International Journal of Physical Distribution & Logistics Management, Vol. 41 No. 1, pp. 63‐82.
Christopher, M. and Peck, H. (2004), “Building the resilient supply chain”, The International Journal of Logistics Management, Vol. 15 No. 2, pp. 1‐14.
Christopher, M. and Towill, D. (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.
Christopher, M., Peck, H. and Towill, D. (2006), “A taxonomy for selecting global supply chain strategies”, The International Journal of Logistics Management, Vol. 17 No. 2, pp. 277‐87.
Cohen, J. (1960), “A coefficient of agreement for nominal scales”, Educational and Psychological Measurement, Vol. 20 No. 1, pp. 37‐46.
Crowther, D. and Lancaster, G. (2008), Research Methods: A Concise Introduction to Research in Management and Business Consultancy, 2nd ed., Butterworth‐Heinemann, Oxford.
Dempster, A.P., Laird, N.M. and Rubin, D.B. (1977), “Maximum likelihood from incomplete data via the EM algorithm”, Journal of the Royal Statistical Society. Series B (Methodological), Vol. 39 No. 1, pp. 1‐38.
Eisenhardt, K.M. (1989), “Building theories from case study research”, The Academy of Management Review, Vol. 14 No. 4, pp. 532‐50.
Ergun, Ö., HeierStamm, J.L., Keskinocak, P. and Swann, J.L. (2010), “Waffle house restaurants hurricane response: a case study”, International Journal of Production Economics, Vol. 126 No. 1, pp. 111‐20.
Fisher, M.L. (1997), “What is the right supply chain for your product?”, Harvard Business Review, Vol. 75 No. 2, pp. 105‐16.
Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1, pp. 39‐50.
Frankel, R., Näslund, D. and Bolumole, Y. (2005), “The ‘white space’ of logistics research: a look at the role of methods usage”, Journal of Business Logistics, Vol. 26 No. 2, pp. 185‐208.
Fugate, B.S., Mentzer, J.T. and Stank, T.P. (2010), “Logistics performance: efficiency, effectiveness, and differentiation”, Journal of Business Logistics, Vol. 31 No. 1, pp. 43‐62.
Goldman, S.L., Nagel, R.N. and Preiss, K. (1995), Agile Competitors and Virtual Organisations, VanNostrand Reinhold, New York, NY.
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.
Hallikas, J., Karvonen, I., Pulkkinen, U., Virolainen, V. and Tuominen, M. (2004), “Risk management processes in supplier networks”, International Journal of Production Economics, Vol. 90 No. 1, pp. 47‐58.
Harrington, K. and O'Connor, J. (2009), “How Cisco succeeds at global risk management”, Supply Chain Management Review, Vol. 13 No. 5, pp. 10‐17.
Harrison, T.P. (2005), “Principles for the strategic design of supply chains”, in Harrison, T.P., Lee, H.L. and Neale, J.J. (Eds), The Practice of Supply Chain Management: Where Theory and Application Converge, Springer, New York, NY, pp. 3‐12.
Hendricks, K.B. and Singhal, V.R. (2005), “Association between supply chain glitches and operating performance”, Management Science, Vol. 51 No. 5, pp. 695‐711.
Huff, A.S. (2008), Designing Research for Publication, Sage, Thousand Oaks, CA.
Husdal, J. (2010), “A conceptual framework for risk and vulnerability in virtual enterprise networks”, in Ponis, S. (Ed.), Managing Risk in Virtual Enterprise Networks: Implementing Supply Chain Principles, IGI, Hershey, PA, pp. 1‐27.
Jarvenpaa, S.L. (1989), “The effect of task demands and graphical format on information processing strategies”, Management Science, Vol. 35 No. 3, pp. 285‐303.
Jick, T.D. (1979), “Mixing qualitative and quantitative methods: triangulation in action”, Administrative Science Quarterly, Vol. 24 No. 4, pp. 602‐11.
Johnson, M. and Templar, S. (2011), “The relationships between supply chain and firm performance: the development and testing of a unified proxy”, International Journal of Physical Distribution & Logistics Management, Vol. 41 No. 2, pp. 88‐103.
Jüttner, U. (2005), “Supply chain risk management: understanding the business requirements from a practitioner perspective”, The International Journal of Logistics Management, Vol. 16 No. 1, pp. 120‐41.
Jüttner, U., Peck, H. and Christopher, M. (2003), “Supply chain risk management: outlining an agenda for future research”, International Journal of Logistics: Research and Applications, Vol. 6 No. 4, pp. 197‐210.
Kaynak, H. (2003), “The relationship between total quality management practices and their effects on firm performance”, Journal of Operations Management, Vol. 21 No. 4, pp. 405‐35.
Kern, D., Moser, R., Hartmann, E. and Moder, M. (2012), “Supply risk management: model development and empirical analysis”, International Journal of Physical Distribution & Logistics Management, Vol. 42 No. 1.
Khan, O., Christopher, M. and Burnes, B. (2008), “The impact of product design on supply chain risk: a case study”, International Journal of Physical Distribution & Logistics Management, Vol. 38 No. 5, pp. 412‐32.
Klibi, W., Martel, A. and Guitouni, A. (2010), “The design of robust value‐creating supply chain networks: a critical review”, European Journal of Operational Research, Vol. 203 No. 2, pp. 283‐93.
Kroes, J.R. and Ghosh, S. (2010), “Outsourcing congruence with competitive priorities: impact on supply chain and firm performance”, Journal of Operations Management, Vol. 28 No. 2, pp. 124‐43.
Lee, H.L. (2002), “Aligning supply chain strategies with product uncertainties”, California Management Review, Vol. 44 No. 3, pp. 105‐19.
McKinsey (2010), “The challenges ahead for supply chains”, McKinsey Quarterly, November.
Mangan, J., Lalwani, C. and Gardner, B. (2004), “Combining quantitative and qualitative methodologies in logistics research”, International Journal of Physical Distribution & Logistics Management, Vol. 34 No. 7, pp. 565‐78.
Manuj, I. and Mentzer, J.T. (2008), “Global supply chain risk management strategies”, International Journal of Physical Distribution & Logistics Management, Vol. 38 No. 3, pp. 192‐223.
Mason‐Jones, R., Naylor, B. and Towill, D.R. (2000), “Engineering the leagile supply chain”, International Journal of Agile Management Systems, Vol. 2 No. 1, pp. 54‐61.
Meepetchdee, Y. and Shah, N. (2007), “Logistical network design with robustness and complexity considerations”, International Journal of Physical Distribution & Logistics Management, Vol. 37 No. 3, pp. 201‐22.
Mentzer, J.T. and Flint, D.J. (1997), “Validity in logistics research”, Journal of Business Logistics, Vol. 18 No. 1, pp. 199‐216.
Mo, Y. and Harrison, T.P. (2005), “A conceptual framework for robust supply chain design under demand uncertainty”, in Geunes, J. and Pardalos, P.M. (Eds), Supply Chain Optimization, Springer, New York, NY, pp. 243‐64.
Moore, G.C. and Benbasat, I. (1991), “Development of an instrument to measure the perceptions of adopting an information technology innovation”, Information Systems Research, Vol. 2 No. 3, pp. 192‐222.
Näslund, D. (2002), “Logistics needs qualitative research – especially action research”, International Journal of Physical Distribution & Logistics Management, Vol. 32 No. 5, pp. 321‐38.
Norrman, A. and Jansson, U. (2004), “Ericsson's proactive supply chain risk management approach after a serious sub‐supplier accident”, International Journal of Physical Distribution & Logistics Management, Vol. 34 No. 5, pp. 434‐56.
Nunnally, J.C. (1978), Psychometric Theory, 2nd ed., McGraw‐Hill, New York, NY.
Prater, E., Biehl, M. and Smith, M.A. (2001), “International supply chain agility: tradeoffs between flexibility and uncertainty”, International Journal of Operations & Production Management, Vol. 21 Nos 5/6, pp. 823‐39.
Rao, S. and Goldsby, T.J. (2009), “Supply chain risks: a review and typology”, The International Journal of Logistics Management, Vol. 20 No. 1, pp. 97‐123.
Richard, P.J., Devinney, T.M., Yip, G.S. and Johnson, G. (2009), “Measuring organizational performance: towards methodological best practice”, Journal of Management, Vol. 35 No. 3, pp. 718‐804.
Simchi‐Levi, D. (2010), “The 6 forces driving supply chain design”, MIT Sloan Management Review, Vol. 51 No. 2, pp. 17‐24.
Spens, K.M. and Kovács, G. (2006), “A content analysis of research approaches in logistics research”, International Journal of Physical Distribution & Logistics Management, Vol. 36 No. 5, pp. 374‐90.
Strauss, A.L. and Corbin, J.M. (1998), Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory, Sage, Thousand Oaks, CA.
Swafford, P.M., Ghosh, S. and Murthy, N. (2006), “The antecedents of supply chain agility of a firm: scale development and model testing”, Journal of Operations Management, Vol. 24 No. 2, pp. 170‐88.
Swaminathan, J.M. and Lee, H.L. (2003), “Design for postponement”, in de Kok, A.G. and Graves, S.C. (Eds), Supply Chain Management: Design, Coordination and Operation, Elsevier, Amsterdam, pp. 199‐226.
Tang, C.S. (2006a), “Perspectives in supply chain risk management”, International Journal of Production Economics, Vol. 103 No. 2, pp. 451‐88.
Tang, C.S. (2006b), “Robust strategies for mitigating supply chain disruptions”, International Journal of Logistics: Research and Applications, Vol. 9 No. 1, pp. 33‐45.
Thun, J. and Hoenig, D. (2011), “An empirical analysis of supply chain risk management in the German automotive industry”, International Journal of Production Economics, Vol. 131 No. 1, pp. 242‐9.
van Hoek, R.I., Harrison, A. and Christopher, M. (2001), “Measuring agile capabilities in the supply chain”, International Journal of Operations & Production Management, Vol. 21 Nos 1/2, pp. 126‐48.
Wagner, S.M. and Bode, C. (2008), “An empirical examination of supply chain performance along several dimensions of risk”, Journal of Business Logistics, Vol. 29 No. 1, pp. 307‐25.
Williams, L.J., Hartman, N. and Cavazotte, F. (2010), “Method variance and marker variables: a review and comprehensive CFA marker technique”, Organizational Research Methods, Vol. 13 No. 3, pp. 477‐514.
Yin, R.K. (2009), Case Study Research: Design and Methods, 4th ed., Sage, Thousand Oaks, CA.