Using a hybrid method to evaluate service innovation in the hotel industry

The process of evaluating perceptions (qualitative scale) and data from operations (quantitative scale) should be merged for service innovation analysis.Hybrid MCDM methods (TFNs, TODIM and Choquet integral) deal with dependence relations and the shortcomings. This study develops a hybrid method to improve selection decision making in service innovation. Because criteria for customer perceptions tend to be vague and conflicting, the process of evaluating perceptions (qualitative scale) and operational data (quantitative scale) should be combined. This study proposes the concomitant evaluation of qualitative and quantitative scales using a hybrid approach that combines fuzzy set theory, a discrete multi-criteria method based on prospect theory (known as TODIM in Portuguese) and the non-addictive Choquet integral. The study assumes that the criteria possess interdependent relationships. The advantages of the proposed hybrid approach, which exhibits a hierarchical structure, have been demonstrated throughout the hot spring hotel industry. The proposed method demonstrates that it can be extremely useful for recommending operational alternatives because it clearly identifies the main criteria of the expressed alternatives. The results indicate that the approach easily and effectively accommodates criteria with gain and loss functions and can help practitioners improve their performance and reduce overall service innovation risks.

[1]  Adrian. Sargeant,et al.  Business performance in the UK hotel sector - does it pay to be market oriented? , 1999 .

[2]  Evangelos Triantaphyllou,et al.  Development and evaluation of five fuzzy multiattribute decision-making methods , 1996, Int. J. Approx. Reason..

[3]  San-yang Liu,et al.  An extended GRA method for MCDM with interval-valued triangular fuzzy assessments and unknown weights , 2011, Comput. Ind. Eng..

[4]  Albert H. Segars,et al.  Knowledge Management: An Organizational Capabilities Perspective , 2001, J. Manag. Inf. Syst..

[5]  Basil Achilladelis,et al.  The dynamics of technological innovation : the case of the pharmaceutical industry , 2001 .

[6]  F F Nobre,et al.  Multi-criteria decision making--an approach to setting priorities in health care. , 1999, Statistics in medicine.

[7]  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..

[8]  Risto Rajala,et al.  Service Innovation Myopia? A New Recipe for Client-Provider Value Creation , 2008 .

[9]  Jon Sundbo Management of Innovation in Services , 1997 .

[10]  Da Ruan,et al.  Multi-Objective Group Decision Making - Methods, Software and Applications with Fuzzy Set Techniques(With CD-ROM) , 2007, Series in Electrical and Computer Engineering.

[11]  Joaquin Aldas-Manzano,et al.  Market orientation and innovation: an inter‐relationship analysis , 2005 .

[12]  T. Zétényi Fuzzy sets in psychology , 1988 .

[13]  Wei-Wen Wu,et al.  Data mining for exploring hidden patterns between KM and its performance , 2010, Knowl. Based Syst..

[14]  Leyland Pitt,et al.  The market orientation-performance link: the role of service reliability , 2003 .

[15]  Cihan Cobanoglu,et al.  Service quality in Cretan accommodations: marketing strategies for the UK holiday market , 2003 .

[16]  M. Porter Competitive Advantage: Creating and Sustaining Superior Performance , 1985 .

[17]  Paul D. Gader,et al.  Generalized Choquet fuzzy integral fusion , 2002, Inf. Fusion.

[18]  Lance A. Bettencourt,et al.  The secret to true service innovation , 2013 .

[19]  P. Maglio,et al.  The Emergence of Service Science: Toward Systematic Service Innovations to Accelerate Co‐Creation of Value , 2008 .

[20]  Fred Langerak,et al.  An Appraisal of Research on the Predictive Power of Market Orientation , 2003 .

[21]  A. Tversky,et al.  Prospect Theory : An Analysis of Decision under Risk Author ( s ) : , 2007 .

[22]  D. Rajan,et al.  Fuzzy Number Fuzzy Measures and Fuzzy Integrals , 2015 .

[23]  Ming-Lang Tseng,et al.  Using hybrid MCDM to evaluate the service quality expectation in linguistic preference , 2011, Appl. Soft Comput..

[24]  Jerry R. Sheehan Understanding service sector innovation , 2006, CACM.

[25]  Alexander E. Ellinger,et al.  Resource‐based theory and strategic logistics research , 1997 .

[26]  Gwo-Hshiung Tzeng,et al.  A Non-Additive Model for Evaluating Airline Service Quality , 2007 .

[27]  Shu-Hui Chiang,et al.  A resource-based perspective on knowledge management capability and competitive advantage: an empirical investigation , 2004, Expert Syst. Appl..

[28]  Sheng-Hshiung Tsaur,et al.  The evaluation of airline service quality by fuzzy MCDM. , 2002 .

[29]  James A. Fitzsimmons,et al.  Service Management for Competitive Advantage , 1994 .

[30]  Ming-Lang Tseng,et al.  Integrated model of hot spring service quality perceptions under uncertainty , 2012, Appl. Soft Comput..

[31]  Ming Lang Tseng,et al.  Selection of Competitive Advantages in TQM Implementation Using Fuzzy AHP and Sensitivity Analysis , 2008 .

[32]  Ram Subramanian,et al.  Examining the Market Orientation-Performance Relationship: A Context-Specific Study , 1998 .

[33]  Rodoula H. Tsiotsou Delineating the effect of market orientation on services performance: a component-wise approach , 2010 .

[34]  Michel Grabisch,et al.  Classification by fuzzy integral: performance and tests , 1994, CVPR 1994.

[35]  Mohammed Almossawi Analyzing Service Quality in the Hospitality Industry: The Case of Bahrain , 2008 .

[36]  Caneel K. Joyce,et al.  Innovation in Services: Corporate Culture and Investment Banking , 2007 .

[37]  G. Klir,et al.  Fuzzy Measure Theory , 1993 .

[38]  Tony C. Garrett,et al.  How does market orientation contribute to service firm performance , 2002 .

[39]  Chie-Bein Chen,et al.  Evaluating firm technological innovation capability under uncertainty , 2008 .

[40]  Ming-Lang Tseng,et al.  A causal and effect decision making model of service quality expectation using grey-fuzzy DEMATEL approach , 2009, Expert Syst. Appl..

[41]  P. Gader,et al.  Advances in fuzzy integration for pattern recognition , 1994, CVPR 1994.

[42]  Gwo-Hshiung Tzeng,et al.  Using fuzzy integral for evaluating subjectively perceived travel costs in a traffic assignment model , 2001, Eur. J. Oper. Res..

[43]  Jung-Hsien Chiang,et al.  Aggregating membership values by a Choquet-fuzzy-integral based operator , 2000, Fuzzy Sets Syst..

[44]  Shuo-Yan Chou,et al.  A decision support system for supplier selection based on a strategy-aligned fuzzy SMART approach , 2008, Expert Syst. Appl..

[45]  菅野 道夫,et al.  Theory of fuzzy integrals and its applications , 1975 .

[46]  M. Sugeno,et al.  A MODEL OF LEARNING BASED ON FUZZY INFORMATION , 1977 .

[47]  K. Zhou,et al.  The Effects of Strategic Orientations on Technology- and Market-Based Breakthrough Innovations , 2005 .

[48]  Richard C.M. Yam,et al.  An audit of technological innovation capabilities in chinese firms: some empirical findings in Beijing, China , 2004 .

[49]  E. Sandberg,et al.  Enabling service innovation: A dynamic capabilities approach , 2013 .

[50]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[51]  Hui-Hua Tsai,et al.  Using fuzzy numbers to evaluate perceived service quality , 2000, Fuzzy Sets Syst..

[52]  Basil Achilladelis,et al.  The dynamics of technological innovation: the case of the pharmaceutical industry , 2001 .

[53]  Ravi Kathuria Competitive priorities and managerial performance: a taxonomy of small manufacturers , 2000 .

[54]  Angela Paladino,et al.  Investigating the Drivers of Innovation and New Product Success: A Comparison of Strategic Orientations* , 2007 .

[55]  A. Parasuraman,et al.  Reassessment of expectations as a comparison standard in measuring service quality: Implications , 1994 .

[56]  Hamideh Afsarmanesh,et al.  Collaborative networks: a new scientific discipline , 2005, J. Intell. Manuf..

[57]  Chung-Hsing Yeh,et al.  A survey analysis of service quality for domestic airlines , 2002, Eur. J. Oper. Res..

[58]  Lawrence W. Lan,et al.  Selection of optimal supplier in supply chain management strategy with analytic network process and choquet integral , 2009, Comput. Ind. Eng..

[59]  George J. Klir,et al.  Constructing fuzzy measures in expert systems , 1997, Fuzzy Sets Syst..

[60]  L. Berry,et al.  Creating new markets through service innovation , 2006 .

[61]  Wei-Wen Wu,et al.  An exploration of relationships between environmental practice and manufacturing performance using the PLS path modeling , 2008 .

[62]  Paul P. Maglio,et al.  Steps Toward a Science of Service Systems , 2007, Computer.

[63]  Jeou-Shyan Horng,et al.  Hospitality teams: Knowledge sharing and service innovation performance , 2009 .

[64]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[65]  Jiancheng Guan,et al.  Innovative capability and export performance of Chinese firms , 2003 .

[66]  B. Edvardsson,et al.  Key Concepts for New Service Development , 1996 .

[67]  Ram Subramanian,et al.  Examining the Market Orientation-Performance Relationship: A Context-Specific Study , 1998 .

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

[69]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .