Outsourcing modelling using a novel interval-valued fuzzy quantitative strategic planning matrix (QSPM) and multiple criteria decision-making (MCDMs)

Abstract Outsourcing drives companies to focus on: their capabilities, advantages of external resources, and decreasing overall operational costs. Selecting appropriate alliances, which are aligned with the company's strategies, establishes a situation through which the firms can enhance their technical capabilities and achieve new technologies. However, two critical issues in outsourcing modeling should be addressed: how to find strategic indicators for building successful alliances, and how to select these partners. Besides, as the imprecise and vague information (due to a lack of data) existing in the outsourcing models cannot be neglected, the application of fuzzy interval sets could efficiently address the complexity of these problems. To deal with these issues, this paper proposes a two-step interval-based framework for the problem. At the beginning, and for the first time, the novel integration of an interval valued fuzzy (IVF) version of strength-weakness-opportunity-threats (SWOT) technique and the quantitative strategic planning matrix (QSPM) with Gap analysis is designed to find the most effective strategies for the alliance evaluation, and to weight them. In the next step, four interval-valued version of multiple criteria decision-making methods (IVF-MCDMs) are implemented to evaluate the strategic partners. Finally, the results are aggregated with the help of the utility interval approach, and a sensitivity analysis is implemented to assess the robustness of the proposed methodology. To illustrate the efficiency of the proposed approach, a real partner selection problem at a holding car manufacturing factory in Iran is presented.

[1]  Cengiz Kahraman,et al.  Fuzzy COPRAS method for performance measurement in total productive maintenance: a comparative analysis , 2016 .

[2]  L. D. Boer,et al.  A review of methods supporting supplier selection , 2001 .

[3]  R. Westbrook,et al.  SWOT Analysis: It's Time for a Product Recall , 1997 .

[4]  Xiaowei Xu,et al.  Multi-criteria decision making approaches for supplier evaluation and selection: A literature review , 2010, Eur. J. Oper. Res..

[5]  Edmundas Kazimieras Zavadskas,et al.  FACILITIES MANAGEMENT MULTIPLE CRITERIA ANALYSIS , 2001 .

[6]  S. Ali Torabi,et al.  Strategic supplier selection under sustainability and risk criteria , 2019, International Journal of Production Economics.

[7]  Prasanta Kumar Dey,et al.  Strategic supplier performance evaluation: a case-based action research of a UK manufacturing organisation , 2015 .

[8]  M. Gorzałczany A method for inference in approximate reasoning based on interval-valued fuzzy sets , 1987 .

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

[10]  James Nga-Kwok Liu,et al.  Application of decision-making techniques in supplier selection: A systematic review of literature , 2013, Expert Syst. Appl..

[11]  R. Tavakkoli-Moghaddam,et al.  Robot selection by a multiple criteria complex proportional assessment method under an interval-valued fuzzy environment , 2014 .

[12]  Gülçin Büyüközkan,et al.  An extension of ARAS methodology under Interval Valued Intuitionistic Fuzzy environment for Digital Supply Chain , 2018, Appl. Soft Comput..

[13]  W. C. Benton,et al.  A systematic assessment of supplier selection literature – State-of-the-art and future scope , 2016 .

[14]  Xu Wang,et al.  Supplier portfolio of key outsourcing parts selection using a two-stage decision making framework for Chinese domestic auto-maker , 2019, Comput. Ind. Eng..

[15]  Chen-Tung Chen,et al.  Extensions of the TOPSIS for group decision-making under fuzzy environment , 2000, Fuzzy Sets Syst..

[16]  Naglis Malys,et al.  Dispersion of relative importance values contributes to the ranking uncertainty: Sensitivity analysis of Multiple Criteria Decision-Making methods , 2018, Appl. Soft Comput..

[17]  Jurgita Antucheviciene,et al.  A new hybrid simulation-based assignment approach for evaluating airlines with multiple service quality criteria , 2017 .

[18]  Edmundas Kazimieras Zavadskas,et al.  Contractor selection for construction works by applying saw‐g and topsis grey techniques , 2010 .

[19]  Andrew C. Inkpen,et al.  Why Do Some Strategic Alliances Persist beyond Their Useful Life? , 2001 .

[20]  Andrejs Čirjevskis,et al.  THE ANTECEDENTS AND CONSEQUENCES OF COOPERATIVE ARRANGEMENTS INHIBITING THE EMERGENCE OF COOPERATIVE STRATEGIES OF LATVIAN FOREST OWNERS , 2014 .

[21]  W. C. Benton,et al.  Vendor selection criteria and methods , 1991 .

[22]  Ahmad Makui,et al.  Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets , 2009, Appl. Soft Comput..

[23]  Robert G. Dyson,et al.  Strategic development and SWOT analysis at the University of Warwick , 2004, Eur. J. Oper. Res..

[24]  F. Chiclana,et al.  Strategic weight manipulation in multiple attribute decision making , 2018 .

[25]  Hong-yu Zhang,et al.  Selecting an outsourcing provider based on the combined MABAC-ELECTRE method using single-valued neutrosophic linguistic sets , 2018, Comput. Ind. Eng..

[26]  Ahmad Makui,et al.  A new flexible and reliable IVF-TOPSIS method based on uncertainty risk reduction in decision making process , 2014, Appl. Soft Comput..

[27]  Maliheh Mirzakhani,et al.  Strategy Formulation with SWOT Matrix: A Case Study of an Iranian Company , 2014 .

[28]  Huan Neng Chiu,et al.  Vendor selection by integrated fuzzy MCDM techniques with independent and interdependent relationships , 2008, Inf. Sci..

[29]  Jurgita Antucheviciene,et al.  Supplier evaluation and selection in fuzzy environments: a review of MADM approaches , 2017 .

[30]  Hamidreza Maghsoudlou,et al.  FQSPM-SWOT for strategic alliance planning and partner selection:case study in a holding car manufacturer company , 2015 .

[31]  Edmundas Kazimieras Zavadskas,et al.  A Novel Approach for Evaluation of Projects Using an Interval-Valued Fuzzy Additive Ratio Assessment (ARAS) Method: A Case Study of Oil and Gas Well Drilling Projects , 2018, Symmetry.

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

[33]  Tapan Kumar Pal,et al.  On comparing interval numbers , 2000, Eur. J. Oper. Res..

[34]  George Wright,et al.  The Delphi technique as a forecasting tool: issues and analysis , 1999 .

[35]  Lisa M. Ellram,et al.  Purchasing leverage considerations in the outsourcing decision , 2001 .

[36]  Sasan Barak,et al.  A novel hybrid fuzzy DEA-Fuzzy MADM method for airlines safety evaluation , 2018, Journal of Air Transport Management.

[37]  Ni-Bin Chang,et al.  An AHP-based fuzzy interval TOPSIS assessment for sustainable expansion of the solid waste management system in Setúbal Peninsula, Portugal , 2011 .

[38]  Wann-Yih Wu,et al.  The analytic network process for partner selection criteria in strategic alliances , 2009, Expert Syst. Appl..

[39]  K. Zhou,et al.  How to enhance supplier performance in China: An integrative view of partner selection and partner control☆ , 2016 .

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

[41]  Edmundas Kazimieras Zavadskas,et al.  Assessment of third-party logistics provider using multi-criteria decision-making approach based on interval rough numbers , 2019, Comput. Ind. Eng..

[42]  Claude E. Shannon,et al.  The Mathematical Theory of Communication , 1950 .

[43]  Jurgita Antucheviciene,et al.  Solving Civil Engineering Problems by Means of Fuzzy and Stochastic MCDM Methods: Current State and Future Research , 2015 .

[44]  J. Hätönen,et al.  30+ years of research and practice of outsourcing – Exploring the past and anticipating the future , 2009 .

[45]  Ying-Hsiu Chen,et al.  Strategic decisions using the fuzzy PROMETHEE for IS outsourcing , 2011, Expert Syst. Appl..

[46]  Hakki Ozgur Unver,et al.  A survey of partner selection methodologies for virtual enterprises and development of a goal programming–based approach , 2015, The International Journal of Advanced Manufacturing Technology.

[47]  David J. Barnes,et al.  A literature review of decision-making models and approaches for partner selection in agile supply chains , 2011 .

[48]  Monark Bag,et al.  A review of multi-criteria decision making techniques for supplier evaluation and selection , 2011 .

[49]  Morteza Yazdani,et al.  Developing Optimized Strategy by Comprehensive Framework of Strategy; Case Study in a Construction Inspection Company , 2012 .

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

[51]  F. Franceschini,et al.  Outsourcing: guidelines for a structured approach , 2003 .

[52]  S. Jozi,et al.  Strategic management in urban environment using SWOT and QSPM model , 2017 .

[53]  Witold Pedrycz,et al.  Multi-attribute group decision making based on extended TOPSIS method under interval-valued intuitionistic fuzzy environment , 2018, Appl. Soft Comput..

[54]  Meredith E. David,et al.  The quantitative strategic planning matrix: a new marketing tool , 2017 .

[55]  Jesper Momme,et al.  Framework for outsourcing manufacturing: strategic and operational implications , 2002, Comput. Ind..

[56]  Ahti Salo,et al.  Multi-Criteria Partner Selection in Virtual Organisations With Transportation Costs and Other Network Interdependencies , 2007 .

[57]  Vijay P. Singh,et al.  Hydrologic Synthesis Using Entropy Theory: Review , 2011 .

[58]  Dragisa Stanujkic,et al.  Extension of the ARAS Method for Decision-Making Problems with Interval-Valued Triangular Fuzzy Numbers , 2015, Informatica.

[59]  Reza Tavakkoli-Moghaddam,et al.  Soft computing based on interval valued fuzzy ANP-A novel methodology , 2012, J. Intell. Manuf..

[60]  Abbas S. Milani,et al.  An improvement of quantitative strategic planning matrix using multiple criteria decision making and fuzzy numbers , 2012, Appl. Soft Comput..

[61]  Orlando Troisi,et al.  Business process outsourcing enhanced by fuzzy linguistic consensus model , 2018, Appl. Soft Comput..

[62]  Russell L. Ackoff,et al.  An Approximate Measure of Value , 1954, Oper. Res..

[63]  Jian-Bo Yang,et al.  A preference aggregation method through the estimation of utility intervals , 2005, Comput. Oper. Res..

[64]  Mohsen Varmazyar,et al.  A novel hybrid MCDM model for performance evaluation of research and technology organizations based on BSC approach. , 2016, Evaluation and program planning.

[65]  Shanlin Yang,et al.  Selecting strategic partner for tax information systems based on weight learning with belief structures , 2019, Int. J. Approx. Reason..

[66]  Z. Irani,et al.  Performance measures and metrics in outsourcing decisions: a review for research and applications , 2015 .

[67]  Edmundas Kazimieras Zavadskas,et al.  A new additive ratio assessment (ARAS) method in multicriteria decision‐making , 2010 .

[68]  Chris Cornelis,et al.  Advances and challenges in interval-valued fuzzy logic , 2006, Fuzzy Sets Syst..