Mechanism for cooperative partner selection: Dual-factor theory perspective

Abstract With global competition and greater components outsourcing, partners play an important role in the supply chain. Previous research on partner selection from the perspective of partner ability has ignored cooperation factors. Ignoring the cooperation factor can lead to a higher chance of failure, even if the partners have a good track record of performance. For this reason, this paper seeks to study the mechanism on cooperative partner selection from a dual-factor theory perspective. We consider two levels: collaborative level and individual level, as well as their measurements. We propose a novel framework for solving the cooperative partner evaluation and selection problem. This framework applies the compatibility degree of the triangular fuzzy soft set (TFSS) to measure the collaborative level, and an extended TODIM based on TFSS to measure the dominance degree for the individual level. A simple example is used to illustrate the potential application of the proposed method. To highlight our method’s practicality and effectiveness, we compare against an established technique.

[1]  Prakash J. Singh,et al.  The nature and effectiveness of collaboration between firms, their customers and suppliers: a supply chain perspective , 2009 .

[2]  Gülçin Büyüközkan,et al.  A new integrated intuitionistic fuzzy group decision making approach for product development partner selection , 2016, Comput. Ind. Eng..

[3]  Bin Huang,et al.  A multi-criterion partner selection problem for virtual manufacturing enterprises under uncertainty , 2018 .

[4]  Congcong Meng,et al.  The multi-fuzzy soft set and its application in decision making , 2013 .

[5]  Cornelia Dröge,et al.  Collaborating for new product development: Selecting the partner with maximum potential to create value , 2006 .

[6]  Zeshui Xu,et al.  The TODIM analysis approach based on novel measured functions under hesitant fuzzy environment , 2014, Knowl. Based Syst..

[7]  Z. Yue An intuitionistic fuzzy projection-based approach for partner selection , 2013 .

[8]  Rodolfo Lourenzutti,et al.  A study of TODIM in a intuitionistic fuzzy and random environment , 2013, Expert Syst. Appl..

[9]  Chong Wu,et al.  An integrated model for green partner selection and supply chain construction , 2016 .

[10]  Stefan Spinler,et al.  Strategic analysis of manufacturer-supplier partnerships: An ANP model for collaborative CO2 reduction management , 2014, Eur. J. Oper. Res..

[11]  Kim Hua Tan,et al.  Using TODIM to evaluate green supply chain practices under uncertainty , 2014 .

[12]  Zeshui Xu,et al.  Dual hesitant fuzzy VIKOR method for multi-criteria group decision making based on fuzzy measure and new comparison method , 2017, Inf. Sci..

[13]  Gin-Shuh Liang,et al.  Using fuzzy MCDM to select partners of strategic alliances for liner shipping , 2005, Inf. Sci..

[14]  Jing Wang,et al.  An extended TODIM approach with intuitionistic linguistic numbers , 2018, Int. Trans. Oper. Res..

[15]  Rajkumar Buyya,et al.  SELCLOUD: a hybrid multi-criteria decision-making model for selection of cloud services , 2018, Soft Computing.

[16]  Teodor Gabriel Crainic,et al.  Collaboration partner selection for city logistics planning under municipal freight regulations , 2016 .

[17]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[18]  Guan Hongjun,et al.  Fuzzy-valued linguistic soft set theory and multi-attribute decision-making application , 2016 .

[19]  S. Liao,et al.  Assessing the influence of supply chain collaboration value innovation, supply chain capability and competitive advantage in Taiwan's networking communication industry , 2017 .

[20]  Naim Çagman,et al.  Soft set theory and uni-int decision making , 2010, Eur. J. Oper. Res..

[21]  R. Passaro,et al.  AHP-based approaches for supplier evaluation: Problems and perspectives , 2012 .

[22]  Zhiming Zhang,et al.  A novel approach to interval-valued intuitionistic fuzzy soft set based decision making , 2014 .

[23]  Ismat Beg,et al.  Triangular dense fuzzy sets and new defuzzification methods , 2016, J. Intell. Fuzzy Syst..

[24]  José Carlos Rodriguez Alcantud,et al.  A novel algorithm for fuzzy soft set based decision making from multiobserver input parameter data set , 2016, Inf. Fusion.

[25]  Zeshui Xu,et al.  Pythagorean fuzzy TODIM approach to multi-criteria decision making , 2016, Appl. Soft Comput..

[26]  Hong-yu Zhang,et al.  Fuzzy decision-making framework for treatment selection based on the combined QUALIFLEX–TODIM method , 2017, Int. J. Syst. Sci..

[27]  Zhi-Ping Fan,et al.  A method for partner selection of codevelopment alliances using individual and collaborative utilities , 2010 .

[28]  D. Molodtsov Soft set theory—First results , 1999 .

[29]  Fei Ye,et al.  An extended TOPSIS method with interval-valued intuitionistic fuzzy numbers for virtual enterprise partner selection , 2010, Expert Syst. Appl..

[30]  F. Paredes,et al.  Robustness analysis in a TODIM-based multicriteria evaluation model of rental properties , 2014 .

[31]  Luís Alberto Duncan Rangel,et al.  An application of the TODIM method to the multicriteria rental evaluation of residential properties , 2009, Eur. J. Oper. Res..

[32]  F. Herzberg,et al.  The motivation to work , 1960 .

[33]  Witold Pedrycz,et al.  An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment , 2017, Eur. J. Oper. Res..

[34]  Gülçin Büyüközkan,et al.  A new combined IF-DEMATEL and IF-ANP approach for CRM partner evaluation , 2017 .

[35]  Tsau Young Lin,et al.  Combination of interval-valued fuzzy set and soft set , 2009, Comput. Math. Appl..

[36]  Yong Yang,et al.  Algorithms for interval-valued fuzzy soft sets in stochastic multi-criteria decision making based on regret theory and prospect theory with combined weight , 2017, Appl. Soft Comput..

[37]  Renato A. Krohling,et al.  Combining prospect theory and fuzzy numbers to multi-criteria decision making , 2012, Expert Syst. Appl..

[38]  Liang Chen,et al.  Partner selection in a virtual enterprise under uncertain information about candidates , 2011, Expert Syst. Appl..

[39]  Zeshui Xu,et al.  Compatibility measures and consensus models for group decision making with intuitionistic multiplicative preference relations , 2013, Appl. Soft Comput..

[40]  Gisella Facchinetti,et al.  A characterization of a general class of ranking functions on triangular fuzzy numbers , 2004, Fuzzy Sets Syst..

[41]  Majid Behzadian,et al.  A fuzzy hybrid group decision support system approach for the supplier evaluation process , 2014 .

[42]  Irfan Deli,et al.  Intuitionistic fuzzy parameterized soft set theory and its decision making , 2013, Appl. Soft Comput..

[43]  V. Swaminathan,et al.  Factors influencing partner selection in strategic alliances: the moderating role of alliance context , 2008 .

[44]  K. Wong,et al.  Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process , 2015 .

[45]  Luís Alberto Duncan Rangel,et al.  Multicriteria analysis of natural gas destination in Brazil: An application of the TODIM method , 2009, Math. Comput. Model..

[46]  Zhi Xiao,et al.  The trapezoidal fuzzy soft set and its application in MCDM , 2012 .

[47]  A. Petruzzelli,et al.  Partner Geographic and Organizational Proximity and the Innovative Performance of Knowledge‐Creating Alliances , 2014 .

[48]  Hong Tau Lee,et al.  An analytic hierarchy process approach with linguistic variables for selection of an R&D strategic alliance partner , 2010, Comput. Ind. Eng..

[49]  Gülçin Büyüközkan,et al.  Selection of the strategic alliance partner in logistics value chain , 2008 .