Outsourcing Material Availability Decision-Making Research
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Abstract
Strong analytical models and design tools are essential for effective supply chain design. Previous research in this field mostly focused on operations research rather than manufacturing considerations. Product life cycle, product attributes, and product features should drive integration and decision-making in supply chain architecture, according to recent study. Furthermore, a thorough set of performance indicators should drive decision-making processes. In this work, we use the supply chain operations reference (SCOR) model level I performance indicators as our decision-making criterion and establish a relationship between product attributes and supply chain strategy. The next step is to create a multi-criteria decision-making approach that incorporates both quantitative and qualitative elements into supplier selection. This methodology is based on pre-emptive goal programming (PGP) and integrated analytic hierarchy process (AHP). While AHP uses supplier ratings resulting from pairwise comparisons to subjectively identify supply chain strategy by matching product attributes with supplier qualities, PGP uses mathematics to estimate the best order amount from the selected providers. The final order quantity is affected by the changes of pairwise comparisons in AHP since PGP employs AHP ratings as input. Thus, in order to guarantee that supplier evaluations are accurate, users of this technique should place a larger focus on the AHP development.
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References
Alreck, P.L., Settle, R.B., 1994. The Survey Research Handbook, second ed. McGraw-Hill, Chicago, IL.
Argo, J.J., Main, K.J., 2004. Meta-analysis of the effectiveness of warning labels. Journal of Public Policy and Marketing 23 (2),
–208.
Bazerman, M., 2005. Judgment in Managerial Decision Making, sixth ed. John Wiley and Sons, New York. Barney, J., 1991. Firm resources and sustained competitive advantage. Journal of Management 17 (1), 99–120.
Bohn, R.E., 1994. Measuring and managing technological knowledge. Sloan Management Review 36 (1), 61–73.
Cacioppo, J.T., Petty, R.E., 1982. The need for cognition. Journal of Personality and Social Psychology 42 (1), 116–131.
Celsi, R.L., Olson, J.C., 1988. The role of involvement in attention and comprehension processes. Journal of Consumer Research 15 (2), 210–224.
Cohen, J., 1988. Statistical Power Analysis for the Behavioral Sciences, second ed. Lawrence Erlbaum Associates, New Jersey.
Cook, T.D., Campbell, D.T., 1979. Quasi-Experimentation: Design and Analysis Issues for Field Settings. Rand McNally College Publishing Co., Chicago, IL.
Cresswell, J.W., 2002. Research Design: Qualitative, Quantitative and Mixed Methods Approaches, second ed. Sage Publications, Thousand Oaks, CA.
Daft, R.L., Weick, K.E., 1984. Toward a model of organizations as interpretation systems. Academy of Management Review 9 (2), 284–295.
Dubinsky, A.J., Jolson, M.A., Michaels, R.E., Kotabe, M., Lim:, C.U., 1992. Ethical perceptions of field sales personnel: an empirical assessment. The Journal of Personal Selling and Sales Management 12 (4), 9–21.