روش تصمیم گیری برای انتخاب تامین کنندگان در برون سپاری خدمات چند منظوره
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|636||2011||11 صفحه PDF||سفارش دهید||8020 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Production Economics, Volume 132, Issue 2, August 2011, Pages 240–250
Although supplier selection in multi-service outsourcing is a very important decision problem, research concerning this issue is still relatively scarce. This paper proposes a decision method for selecting a pool of suppliers for the provision of different service process/product elements. It pioneers the use of collaborative utility between partner firms for supplier selection. A multi-objective model is built to select desired suppliers. This model is proved to be NP-hard, so we develop a multi-objective algorithm based on Tabu search for solving it. We then use an example to show the applicability of the proposed model and algorithm. Extensive computational experiments are also conducted to further test the performance of the proposed algorithm.
In today's global service outsourcing arena, increasing numbers of firms adopt multi-service outsourcing; that is, they combine service process/product elements (SPEs) from multiple providers (Levina and Su, 2008). For example, Chinamobile provides M-zone business services, including music online, mobile purse, color ring and mobile news, through service providers (SPs). Multi-service outsourcing has become an important business approach since it can significantly decrease service price, shorten waiting time, improve customer satisfaction and enhance the firm's core competence (McCarthy and Anagnostou, 2004 and Antelo and Bru, 2010). As for the process of multi-service outsourcing, a service process/product disaggregation is first conducted to pinpoint the SPEs that need to be outsourced. SPEs imply sub-services or products that combine to form a whole service process/product. A pool of appropriate suppliers is then selected for providing specific SPEs (Stratman, 2008). The outsourcing firm selects the most appropriate suppliers by considering service price, waiting time or service capacity, and builds long-term and profitable relationships with them (Wang and Yang, 2009 and Qi, 2011). Supplier selection, orienting long-term collaborative relationships in multi-service outsourcing, is a very important decision problem (Lee, 2009, Nordin, 2008, Levina and Su, 2008 and Bustinza et al., 2010). As for multi-service outsourcing, the collaboration between the outsourcing firm and the potential suppliers as well as between the potential suppliers (partner firms for conciseness, hereafter) is an important underlying factor for the development of long-term collaborative relationships, which has been of particular interest (Lee, 2009 and Büyüközkan et al., 2009). The outsourcing firm develops mutually beneficial relationships with their key suppliers so that the suppliers are more willing to invest in skills or technologies that are specific to it (McCutcheon and Stuart, 2000). An outsourcing firm and its suppliers may broaden their contact and share business or technology information. Suppliers may expand their roles to provide related supports beyond traditional outsourcing transactions, such as participating in the outsourcing firm's research and development (R&D) activities or providing technology supports and training by virtue of their areas of expertise (McCutcheon and Stuart, 2000 and Guo et al., 2010). Suppliers may share their service facilities or processes with each other to exploit pooling benefits (Allon and Federgruen, 2009). Particularly, suppliers in service industries need more collaboration than those in manufacturing industries because they perform different activities consecutively in a whole service process and in order to impress customers consistently, they have to employ compatible interface management. Indeed, collaborative utility between partners has gained an increasing attention in some latest research on collaborative organizations, such as alliances (Ding and Liang, 2005 and Emden et al., 2006), bilateral collaboration innovation networks (Cowan et al., 2007), interfirm collaboration networks (Schilling and Phelps, 2007), virtual network organizations (Lavrač et al., 2007), and teams (Fan et al., 2009, Feng et al., 2010a and Feng et al., 2010b). The collaborative utility between partner firms is a valuable input for decision-making. Thus, it is necessary to consider the collaborative utility between partner firms for supplier selection in multi-service outsourcing. In the last two decades, various decision-making methods have been proposed to tackle the problem of supplier evaluation and selection; please refer to a recent review by Ho et al. (2010). However, the vast majority of the published works deal with supplier selection in manufacturing industries and few of them address such a problem in service industries. And usually the individual utility of a single supplier is considered, such as financial stability, business track record, technical expertise, market knowledge and managerial experience (Büyüközkan et al., 2008), while the collaborative utility between pairwise suppliers is seldom involved. Moreover, the criteria (or objectives) focused in service supplier selection differ from those for manufacturing supplier selection. Revenue, cost or the number of suppliers is usually considered in manufacturing supplier selection. However, service price and waiting time are the two most important and irreplaceable objectives for supplier selection in multi-service outsourcing (Allon and Federgruen, 2009). Finally, unlike part or product purchasing, service outsourcing is ordinarily conducted by a long-term contract, not by repeated orders. The outsourcing cost does not contain ordering, transportation, inspection and storage costs. Therefore, the existing decision methods cannot be directly used to solve the problem of supplier selection in multi-service outsourcing. Clearly, there is a need for a straightforward and routine decision method for solving the multi-service outsourcing problem.
نتیجه گیری انگلیسی
Supplier selection orienting long-term collaborative relationships in multi-service outsourcing is a very important decision problem. Close collaboration or interaction may occur between partner firms for the purpose of decreasing costs, sharing resources, exploiting capability complementarities or risk reduction. Collaborative utility, which indicates the potential collaborative level between partner firms, is a very important input for decision-making. It deserves much more attention in supplier selection orienting long-term collaborative relationships. This paper presents a decision method for solving the problem of supplier selection in multi-service outsourcing. A multi-objective 0–1 programming model is built to select a pool of desired suppliers for different SPEs. A multi-objective algorithm based on TS is then developed to solve this model. A Pareto-optimal solution set can be obtained to support the supplier selection decision in multi-service outsourcing. The major contributions of this paper are as follows. First, this paper considers the collaborative utility between partner firms for supplier selection. It is a new idea to use collaborative utility for selecting a pool of suppliers who will form long-term collaborative relationships. It overcomes the limitation in the existing decision-making methods for supplier selection, which only focus on the individual utilities. Second, we build a multi-objective 0–1 programming model for selecting a pool of desired suppliers for the provision of different SPEs. Three objectives including collaborative utility, outsourcing cost and waiting time are involved in this decision model. It is also seen that the acceptable levels on price and waiting time of each SPE are taken into consideration. This model lies within a flexible decision framework, and it can be extended or modified to deal with service supplier selection problems in different scenarios by changing objectives and constrains in the light of actual requirements. Third, we develop a multi-objective algorithm based on TS for solving the multi-objective 0–1 programming model. Several effective mechanisms are employed in this algorithm, such as multi-objective filtering, a succession of intensifications and diversifications for local search and Tabulist management. A Pareto-optimal solution set can be obtained using this algorithm. Extensive computational experiments show the effectiveness and efficiency of the proposed algorithm. The algorithm is universal, and it can be applied to solve other multi-objective assignment problems. Future work will extend the above model and algorithm to the settings where collaborative utility should be considered, such as application service provider (ASP) selection in IT outsourcing or partner selection for codevelopment alliances. As for different decision problems, the proposed model can be modified by changing objectives or adding constraints before it is applied. Moreover, we intend to develop a decision support system (DSS), in which the proposed model and algorithm will be embedded. The DSS will be universal and convenient for DMs to tackle the complex or complicated decision problems of supplier selection in service outsourcing.