Quality & Quantity

, Volume 44, Issue 2, pp 217–237 | Cite as

Fuzzy multi-linguistic preferences model of service innovations at wholesale service delivery

Original Paper

Abstract

In group decision making, most researches often assume the linguistic ways with personal preferences have been given and ignore the linguistic evaluated formats involving their knowledge and experience. In practice, people contributing to the judgment tend generally to give ratings about their personal preferences depending on their background. Thus, problems in multiple linguistic preferences go undetected, resulting in the evaluation process not satisfying with decisions’ expectations. In this study, we provide a fuzzy multiple preference integrated model with two stages to better reduce the bias for group decision makings. The first stage focuses on making the information unify on the alternatives according to the individual linguistic preferences, then we compute collective performance values and solve the problems lacking on the integration of respective fuzzy choice subsets. The second stage, we choose the alternatives of retailing service innovations according to the collective performance values by stage one. The goal of the decision process is to reach the subjective fuzzy cognitions in terms of the preference values of all the decision makers. Finally, the survey data of the chain wholesale using multiple preference formats in service innovations determination is verified.

Keywords

Fuzzy multiple preferences Service innovations Decision model 

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References

  1. Barras R.: Towards a theory of innovation in services. Res. Policy 15, 161–173 (1986)CrossRefGoogle Scholar
  2. Barras R.: Interactive innovation in financial and business services: the vanguard of the service revolution. Res. Policy 19, 215–237 (1990)CrossRefGoogle Scholar
  3. Bouchereau V., Rowlands H.: Methods and techniques help quality function deployment (QFD). Benchmarking Int. J. 7(1), 8–20 (2000)CrossRefGoogle Scholar
  4. Burgelman R.A., Maidique M.A., Wheelwright S.C.: Strategic Management Technology Innovation. Irwin, Chicago (1996)Google Scholar
  5. Carlsson C., Fuller R.: Fuzzy multiple criteria decision making: recent developments. Fuzzy Sets Syst. 78, 139–153 (1996)CrossRefGoogle Scholar
  6. Chan L.K., Wu M.L.: Quality function deployment: a literature review. Eur. J. Oper. Res. 143(3), 463–497 (2002)CrossRefGoogle Scholar
  7. Chen C.T.: A fuzzy approach to select the location of the distribution center. Fuzzy Sets Syst. 118, 65–73 (2001)CrossRefGoogle Scholar
  8. Chiclana F., Herrera F., Herrera-Viedma E., Poyatos M.C.: A classification method of alternatives for multiple preference ordering criteria based on fuzzy majority. J Fuzzy Math. 4, 801–813 (1996)Google Scholar
  9. Chiclana F., Herrera F., Herrera-Viedma E.: Integrating three representation models in fuzzy multipurpose decision-making based on fuzzy preference relations. Fuzzy Sets Syst. 97, 33–48 (1998)CrossRefGoogle Scholar
  10. Courtney J.F.: Decision-making and knowledge management in inquiring organizations: toward a view decision-making paradigm for DSS. Dec. Support Syst. 31, 17–38 (2001)CrossRefGoogle Scholar
  11. Dubois D., Prade H.: Ranking fuzzy numbers in the setting of possibility theory. Inform. Sci. 107, 177–194 (1983)Google Scholar
  12. Erol I., Ferrell W.G.: A methodology for selection problems with multiple, conflicting objectives and both qualitative and quantitative criteria. Int. J. Prod. Econ. 86(3), 187–199 (2003)CrossRefGoogle Scholar
  13. Fodor J., Roubens M.: Fuzzy preference modeling and multicriteria decision support. Kluwer, Dordrecht (1994)Google Scholar
  14. Freeman C., Soete L.: The Rise of the Expert Company. Pinter, London (1997)Google Scholar
  15. Gallouj F., Weinstein O.: Innovation in services. Res. Policy 26, 537–556 (1995)CrossRefGoogle Scholar
  16. Hales R.: Adapting QFD to the US. IIE Sol. 27, 15–18 (1995)Google Scholar
  17. Harding J.A., Popplewell K., Fung R.Y.K., Omar A.R.: An intelligent information framework relating customer requirements and product characteristics. Comput. Ind. 44(1), 51–65 (2001)CrossRefGoogle Scholar
  18. Herrera F., Herrera-Viedma E., Chiclana F.: Multiperson decision-making based on multiplicative preference relations. Eur. J. Oper. Res. 129, 372–385 (2001)CrossRefGoogle Scholar
  19. Herrera F., López E., Rodríguez M.A.: A linguistic decision model for promotion mix management solved with genetic algorithms. Fuzzy Sets Syst. 131, 47–61 (2002)CrossRefGoogle Scholar
  20. Ho E.S.S.A., Lai Y.J., Chang S.I.: An integrated group decision-making approach to quality function deployment. IIE Trans. 31, 553–567 (1999)Google Scholar
  21. Jiang Q., Chen C.H.: A multi-dimensional fuzzy decision support strategy. Dec. Support Syst. 38, 591–598 (2005)CrossRefGoogle Scholar
  22. Kahraman, C., Ruan, D., Dogan, İ.: Fuzzy group decision making for facility location selection. Inform. Sci. 157, 135–153 (2003)CrossRefGoogle Scholar
  23. Kelly D., Storey C.: New service development: initiation strategies. Int. J. Serv. Ind. Manage. 11(1), 45–62 (2000)CrossRefGoogle Scholar
  24. Kulak O., Kahraman C.: Fuzzy multi-attribute selection among transportation companies using axiomatic design and analytic hierarchy process. Inform. Sci. 170, 191–210 (2005)CrossRefGoogle Scholar
  25. Lee J.W., Kim S.H.: Using analytic network process and goal programming for interdependent information system project selection. Comput. Oper. Res. 27, 367–382 (2000)CrossRefGoogle Scholar
  26. Liang G.: Fuzzy MADM based on ideal and anti-ideal concepts. Eur. J. Oper. Res. 112, 682–691 (1999)CrossRefGoogle Scholar
  27. Martin C.R., Horne D.A.: Services innovation: successful versus unsuccessful firms. Int. J. Serv. Ind. Manage. 4(1), 49–65 (1993)Google Scholar
  28. Matear S., Gray B.J., Garrett T.: Market orientation, brand investment, new service development, market position and performance for service organizations. Int. J. Serv. Ind. Manage. 15(3), 284–301 (2004)CrossRefGoogle Scholar
  29. Matthing J., Sandén B., Edvardsson B.: New service development: learning from and with customers. Int. J. Serv. Ind. Manage. 15(5), 479–498 (2004)CrossRefGoogle Scholar
  30. Miles I.: Innovation in Services: Services in Innovation. Manchester Statistical Society, Manchester (1996)Google Scholar
  31. Miller G.A.: The magical number seven or minus two: some limits on our capacity of processing information. Psychol. Rev. 63, 81–97 (1956)CrossRefGoogle Scholar
  32. Normann R.: 1991) Service Management, Strategy and Leadership in Service Businesses. Wiley, Chicester (1984)Google Scholar
  33. Orlovski S.A.: Decision making with a fuzzy preference relation. Fuzzy Sets Syst. 1, 155–167 (1978)CrossRefGoogle Scholar
  34. Quinn J.B.: Intelligent enterprise. A knowledge and service based paradigm for industry. The Free Press, New York (1992)Google Scholar
  35. Roubens M.: Some properties of choice functions based on valued binary relations. Eur. J. Oper. Res. 40, 309–321 (1989)CrossRefGoogle Scholar
  36. Sundbo J.: Modulization of service production and a thesis of convergence between service and manufacturing organizations. Scand. J. Manage. 10(3), 245–266 (1994)CrossRefGoogle Scholar
  37. Tax S.S., Stuart I.: Designing and implementing new services: the challenges of integrating service systems. J. Retail. 73(1), 105–134 (1997)CrossRefGoogle Scholar
  38. Ulwick A.W.: Turn customer input into innovation. Harvard Bus. Rev. 80(1), 91–97 (2002)Google Scholar
  39. van der Aa W., Elfring T.: Realizing innovation in services. Scand. J. Manage. 18, 155–171 (2002)CrossRefGoogle Scholar
  40. von Hippel E.: User toolkits for innovation. J. Prod. Innov. Manage. 18(3), 113–121 (2001)Google Scholar
  41. Wang Y.M., Parkan C.: A minimax disparity approach for obtaining OWA operator weights. Inform. Sci. 175, 20–29 (2005)CrossRefGoogle Scholar
  42. Wolfe, R.A.: Organizational innovation: review, critique and suggested research directions. J. Manage. Stud. 405–431. (1994)Google Scholar
  43. Xu Z.: A method based on linguistic aggregation operators for group decision making with linguistic preference relations. Inform. Sci. 166, 19–30 (2004)CrossRefGoogle Scholar
  44. Xu Z., Da Q.L.: An overview of operators for aggregating information. Int. J. Intell. Syst. 18, 953–969 (2003)CrossRefGoogle Scholar
  45. Yager R.R.: Quantifier guided aggregation using OWA operators. Int. J. Intell. Syst. 11, 49–73 (1996)CrossRefGoogle Scholar
  46. Zhang Q., Chen J.C.H., Chong P.P.: Decision consolidation: criteria weight determination using multiple preference formats. Dec. Support Syst. 38, 247–258 (2004)CrossRefGoogle Scholar
  47. Zhou, D.N.: Fuzzy group decision support system approach to group decision making under multiple criteria. Ph.D Dissertation, City University of Hong Kong, Hong Kong (2000)Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Department of Marketing ManagementShih Chien UniversityNei-Men Hsiang, Kaohsiung HsienTaiwan, ROC

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