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An Integrated Structure for Supplier Selection and Configuration of Knowledge-Based Networks Using QFD, ANP, and Mixed-Integer Programming Model

DOI: 10.1155/2013/407573

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Abstract:

Today’s competitive world conditions and shortened product life cycles have led to the rise of attention towards new product development issue which can guarantee both growth and survival of organizations. The agility of new product development is directed by the efficiency and efficacy of knowledge management skills of an organization. A key issue in thorough success of such networks is the developed knowledge preservation amongst the members. Thus, it is important that reliable relations can be established between the members in order to promote further interactions. To do so, an integrated framework is developed in this paper to configure the new product development network so that sustainable collaborations can be maintained amongst the entities. The proposed framework consists of the network configuration in addition to the supplier selection phase. They are taken into consideration using a biobjective mathematical model in which incurred costs and suppliers' superiority determine the final configuration of the network. Finally, different numerical instances are solved to address the applicability of the proposed model. 1. Introduction Over the last years, engineering and manufacturing companies have extensively concentrated on developing innovative and new products, improving their value and design for modern goods and supplies. The emergence and rise of consumer demands for novel products, shortened product life cycles, and contemporary technological developments have highlighted the demand for new and innovative products. The aforementioned issues make the organizations burdened with significant financial and opportunity losses if the development or launch of their new product is postponed. For instance, Kurawarwala and Matsuo [1] stated that a six-eight-month delay in the launch of products such as computers and cellular phones by a computer manufacturer results in a 50–75% loss in revenue. In a more recent study, McGrath and MacMillan [2] showed that a six-month delay in the introduction of the product would decrease the project’s net present value by over $2 million, with all other parameters remaining constant. These stimuli make organizations increasingly pay attention to their new product development capabilities, increase efficiency, reduce development costs, and slash the overall cycle time. New product development (NPD) is an iterative process of gathering, creating, and evaluating information for developing new, defect-free, and quality products. The agility of NPD is governed by the efficiency of knowledge management skills and

References

[1]  A. A. Kurawarwala and H. Matsuo, “Forecasting and inventory management of short life-cycle products,” Operations Research, vol. 44, no. 1, pp. 131–150, 1996.
[2]  R. G. McGrath and I. C. MacMillan, “How to rethink your business during uncertainty,” MIT Sloan Management Review, vol. 50, no. 3, pp. 25–30, 2009.
[3]  R. Shankar, N. Mittal, S. Rabinowitz, A. Baveja, and S. Acharia, “A collaborative framework to minimise knowledge loss in new product development,” International Journal of Production Research, vol. 51, pp. 2049–2059, 2013.
[4]  P. M. Norman, “Knowledge acquisition, knowledge loss, and satisfaction in high technology alliances,” Journal of Business Research, vol. 57, no. 6, pp. 610–619, 2004.
[5]  S. Durst and S. Wilhelm, “Knowledge management in practice: insights into a medium-sized enterprise's exposure to knowledge loss,” Prometheus, vol. 29, no. 1, pp. 23–38, 2011.
[6]  J. Liebowitz, “What practitioners need to know,” KM World, vol. 20, no. 2, pp. 12–13, 2011.
[7]  P. Chinowsky and P. Carrillo, “Knowledge management to learning organization connection,” Journal of Management in Engineering, vol. 23, no. 3, pp. 122–130, 2007.
[8]  W. Xiwei, M. Stolein, and W. Kan, “Designing knowledge chain networks in China—a proposal for a risk management system using linguistic decision making,” Technological Forecasting and Social Change, vol. 77, no. 6, pp. 902–915, 2010.
[9]  I. Nonaka and N. Konno, “The concept of “Ba”: building a foundation for knowledge creation,” California Management Review, no. 3, pp. 40–54, 1998.
[10]  T. Powell, “The knowledge value chain (KVC): how to fix it when it breaks,” in Proceedings of the 22nd National Online Meeting, pp. 301–312, New York, NY, USA, May 2001.
[11]  D. Sams, E. Scarboro, J. Parker, and I. Mayoylov, “Sustainability paradigm: perspective of the small retailers,” WIT Transactions on Ecology and the Environment, vol. 173, pp. 355–366, 2013.
[12]  A. P. de Carvalho and J. C. Barbieri, “Innovation and sustainability in the supply chain of a cosmetics company: a case study,” Journal of Technology Management and Innovation, vol. 7, no. 2, pp. 144–156, 2012.
[13]  Y. Shymko and A. Diaz, “A resource dependence, social network and contingency model of sustainability in supply chain alliances,” International Journal of Business Excellence, vol. 5, no. 5, pp. 502–520, 2012.
[14]  A. Amindoust, S. Ahmed, and A. Saghafinia, “Supplier performance measurement of palm oil industries from a sustainable point of view in malaysia,” BioTechnology, vol. 6, no. 6, pp. 155–158, 2012.
[15]  A. Amindoust, S. Ahmed, A. Saghafinia, and A. Bahreininejad, “Sustainable supplier selection: a ranking model based on fuzzy inference system,” Applied Soft Computing Journal, vol. 12, no. 6, pp. 1668–1677, 2012.
[16]  K. Govindan, R. Khodaverdi, and A. Jafarian, “A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach,” Journal of Cleaner Production, vol. 47, pp. 345–354, 2013.
[17]  A. H. Azadnia, P. Ghadimi, M. Z. M. Saman, K. Y. Wong, and C. Heavey, “An integrated approach for sustainable supplier selection using fuzzy logic and fuzzy AHP,” Applied Mechanics and Materials, vol. 315, pp. 206–210, 2013.
[18]  M.-L. Tseng and A. S. F. Chiu, “Evaluating firm's green supply chain management in linguistic preferences,” Journal of Cleaner Production, vol. 40, pp. 22–31, 2013.
[19]  C. S. Tang, “Perspectives in supply chain risk management,” International Journal of Production Economics, vol. 103, no. 2, pp. 451–488, 2006.
[20]  A. Amiri, “Designing a distribution network in a supply chain system: formulation and efficient solution procedure,” European Journal of Operational Research, vol. 171, no. 2, pp. 567–576, 2006.
[21]  O. ?akir, “Benders decomposition applied to multi-commodity, multi-mode distribution planning,” Expert Systems with Applications, vol. 36, no. 4, pp. 8212–8217, 2009.
[22]  F. Altiparmak, M. Gen, L. Lin, and I. Karaoglan, “A steady-state genetic algorithm for multi-product supply chain network design,” Computers and Industrial Engineering, vol. 56, no. 2, pp. 521–537, 2009.
[23]  N. Susarla and I. A. Karimi, “Integrated supply chain planning for multinational pharmaceutical enterprises,” Computers and Chemical Engineering, vol. 42, pp. 168–177, 2012.
[24]  L.-H. Chen and M.-C. Weng, “An evaluation approach to engineering design in QFD processes using fuzzy goal programming models,” European Journal of Operational Research, vol. 172, no. 1, pp. 230–248, 2006.
[25]  N. D. du Preez and L. Louw, “A framework for managing the innovation process,” in Proceedings of the Portland International Center for Management of Engineering and Technology, Technology Management for a Sustainable Economy (PICMET '08), pp. 546–558, Cape Town, South Africa, July 2008.
[26]  G. Büyük?zkan and ?. Berkol, “Designing a sustainable supply chain using an integrated analytic network process and goal programming approach in quality function deployment,” Expert Systems with Applications, vol. 38, no. 11, pp. 13731–13748, 2011.
[27]  M. A. Farshchi and M. Brown, “Social networks and knowledge creation in the built environment: a case study,” Structural Survey, vol. 29, no. 3, pp. 221–243, 2011.
[28]  L. Shen, Laya Olfat, K. Govindan, R. Khodaverdi, and A. Diabat, “A fuzzy multi criteria approach for evaluating green supplier’s performance in green supply chain with linguistic preferences,” Resources, Conservation and Recycling, vol. 74, pp. 170–179, 2013.
[29]  T. L. Saaty, The AnaLytic Network Process. s.l, Expert Choice, RWS Publications, 1996.
[30]  L. A. Zadeh, “Fuzzy sets,” Information and Control, vol. 8, no. 3, pp. 338–353, 1965.
[31]  B. Chang, C.-W. Chang, and C.-H. Wu, “Fuzzy DEMATEL method for developing supplier selection criteria,” Expert Systems with Applications, vol. 38, no. 3, pp. 1850–1858, 2011.
[32]  H.-T. Liu and C.-H. Wang, “An advanced quality function deployment model using fuzzy analytic network process,” Applied Mathematical Modelling, vol. 34, no. 11, pp. 3333–3351, 2010.
[33]  Z. Liu, S. Guo, L. V. Snyder, A. Lim, and P. Peng, “A p-robust capacitated network design model with facility disruptions,” in Advanced Manufacturing and Sustainable Logistics, vol. 46 of Lecture Notes in Business Information Processing, pp. 269–280, 2010.

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