Using Fuzzy Preference Method for Group Package Tour Based on the Risk Perception

This study explores group package tour (GPT) itineraries based on comparative risk methodology using the fuzzy Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). It combines the concepts of fuzzy sets to represent the uncertain information in intrinsic risks with PROMETHEE, a subgroup of Multi-Criteria Decision Making methods. Based on in-depth interviews with 40 GPT leaders, this study identifies comprehensive intrinsic risk factors. Furthermore, this study compares the risk perceptions associated with 12 factors by applying traditional PROMETHEE and fuzzy PROMETHEE methods to four itineraries. The PROMETHEE method can be used when the input data are numeric and crisp. The fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in GPT itinerary information. Finally, several academic and managerial implications about GPT tour risk controls are outlined.

[1]  Andrew Lepp,et al.  TOURIST ROLES, PERCEIVED RISK AND INTERNATIONAL TOURISM , 2003 .

[2]  Amir Albadvi,et al.  Formulating national information technology strategies: A preference ranking model using PROMETHEE method , 2004, Eur. J. Oper. Res..

[3]  M. Goumas,et al.  An extension of the PROMETHEE method for decision making in fuzzy environment: Ranking of alternative energy exploitation projects , 2000, Eur. J. Oper. Res..

[4]  Jinkook Lee,et al.  An integrated model of risk and risk-reducing strategies , 2006 .

[5]  P. Vincke,et al.  Note-A Preference Ranking Organisation Method: The PROMETHEE Method for Multiple Criteria Decision-Making , 1985 .

[6]  Didier Dubois,et al.  Ranking fuzzy numbers in the setting of possibility theory , 1983, Inf. Sci..

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

[8]  Roger March,et al.  The Japanese Travel Life Cycle , 2000, Japanese Tourists: Socio-Economic, Marketing and Psychological Analysis.

[9]  Komaragiri Srinivasa Raju,et al.  Multicriterion decision making in river basin planning and development , 1999, Eur. J. Oper. Res..

[10]  Sorin G. Gal.  Approximation Theory in Fuzzy Setting , 2000 .

[11]  Reza Baradaran Kazemzadeh,et al.  PROMETHEE: A comprehensive literature review on methodologies and applications , 2010, Eur. J. Oper. Res..

[12]  Habib Chabchoub,et al.  PROMETHEE-MD-2T method for project selection , 2009, Eur. J. Oper. Res..

[13]  Evangelos Triantaphyllou,et al.  USING THE ANALYTIC HIERARCHY PROCESS FOR DECISION MAKING IN ENGINEERING APPLICATIONS: SOME CHALLENGES , 1995 .

[14]  M. Unser.  Lower partial moments as measures of perceived risk: An experimental study , 2000 .

[15]  Jean Pierre Brans,et al.  A PREFERENCE RANKING ORGANIZATION METHOD , 1985 .

[16]  I. Quiroga,et al.  Characteristics of package tours in Europe. , 1990 .

[17]  Soheil Sadi-Nezhad,et al.  Ranking fuzzy numbers by preference ratio , 2001, Fuzzy Sets Syst..

[18]  Matthias Ehrgott,et al.  Multiple criteria decision analysis: state of the art surveys , 2005 .

[19]  Miao-Ling Wang,et al.  Ranking Fuzzy Number Based on Lexicographic Screening Procedure , 2005, Int. J. Inf. Technol. Decis. Mak..

[20]  G. Anastassiou.  Handbook of Analytic Computational Methods in Applied Mathematics , 2000 .

[21]  Teng Wei-feng,et al.  Risks perceived by Mainland Chinese tourists towards Southeast Asia destinations: A fuzzy logic model , 2005 .

[22]  Kuo-Ching Wang,et al.  Who is the decision-maker: the parents or the child in group package tours? , 2004 .

[23]  S. Tesh,et al.  Disease causality and politics. , 1981, Journal of health politics, policy and law.

[24]  Alicja Mieszkowicz-Rolka,et al.  Fuzzy rough approximations of process data , 2008, Int. J. Approx. Reason..

[25]  David L. Olson,et al.  Comparison of three multicriteria methods to predict known outcomes , 2001, Eur. J. Oper. Res..

[26]  Akbar Esfahanipour,et al.  Decision making in stock trading: An application of PROMETHEE , 2007, Eur. J. Oper. Res..

[27]  William C. Wedley,et al.  Modelling risk and uncertainty with the analytic hierarchy process , 2002 .

[28]  Hsuan-Shih Lee,et al.  The revised method of ranking fuzzy numbers with an area between the centroid and original points , 2008, Comput. Math. Appl..

[29]  Komaragiri Srinivasa Raju,et al.  Multicriterion decision making in performance evaluation of an irrigation system , 1999, Eur. J. Oper. Res..

[30]  Da Ruan,et al.  A fuzzy preference‐ranking model for a quality evaluation of hospital web sites , 2006, Int. J. Intell. Syst..

[31]  Holger R. Maier,et al.  Incorporating uncertainty in the PROMETHEE MCDA method , 2003 .

[32]  Thomas Spengler,et al.  Fuzzy outranking for environmental assessment. Case study: iron and steel making industry , 2000, Fuzzy Sets Syst..

[33]  Laurence Turcksin,et al.  A Combined AHP-PROMETHEE Approach for Selecting the Most Appropriate Policy Scenario to Stimulate a Clean Vehicle Fleet , 2011 .

[34]  Denis Bouyssou,et al.  Conjoint measurement tools for MCDM, A brief introduction , 2004 .

[35]  Ying Luo,et al.  Area ranking of fuzzy numbers based on positive and negative ideal points , 2009, Comput. Math. Appl..

[36]  P. Anand Raj,et al.  Ranking alternatives with fuzzy weights using maximizing set and minimizing set , 1999, Fuzzy Sets Syst..

[37]  F. Choobineh,et al.  An index for ordering fuzzy numbers , 1993 .

[38]  Bo Feng,et al.  Ranking L-R fuzzy number based on deviation degree , 2009, Inf. Sci..

[39]  B. Roy.  Paradigms and Challenges , 2005 .

[40]  Kuo-Ching Wang,et al.  Critical service features in group package tour: An exploratory research , 2000 .

[41]  Bertrand Mareschal,et al.  Prométhée: a new family of outranking methods in multicriteria analysis , 1984 .

[42]  Tzeng Gwo-Hshiung,et al.  Evaluating tourist risks from fuzzy perspectives , 1997 .

[43]  T. K. Pinhey,et al.  Safety Concerns of Japanese Visitors to Guam , 1994 .

[44]  Marc Roubens,et al.  Ranking and defuzzification methods based on area compensation , 1996, Fuzzy Sets Syst..

[45]  H. H. Kassarjian.  Content Analysis in Consumer Research , 1977 .

[46]  Holger R. Maier,et al.  Distance-based and stochastic uncertainty analysis for multi-criteria decision analysis in Excel using Visual Basic for Applications , 2006, Environ. Model. Softw..

[47]  Benedetto Matarazzo,et al.  New approaches for the comparison of L-R fuzzy numbers: a theoretical and operational analysis , 2001, Fuzzy Sets Syst..

[48]  Ronald R. Yager,et al.  Ranking Fuzzy Numbers Using a-Weighted Valuations , 2000, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[49]  A. Pascu.  Operational research '81: J.P. Brans (Ed.) Proceedings of the Ninth IFORS International Conference on Operational Research, Hamburg, Germany, July 20–24, 1981, North-Holland, Amsterdam, 1981, xx + 984 pages, Dfl.250.000 , 1982 .

[50]  Alessio Ishizaka,et al.  Location selection for the construction of a casino in the Greater London region: a triple multi-criteria approach , 2013 .

[51]  Evangelos Triantaphyllou,et al.  Two new cases of rank reversals when the AHP and some of its additive variants are used that do not occur with the multiplicative AHP , 2001 .

[52]  Waldemar Koodziejczyk.  Orlovsky's concept of decision-making with fuzzy preference relation—Further results , 1986 .

[53]  H. Lee-Kwang,et al.  Ranking fuzzy values with satisfaction function , 1994 .

[54]  D. Fesenmaier,et al.  Risk Perceptions and Pleasure Travel: An Exploratory Analysis , 1992 .

[55]  J. Dyer.  Remarks on the analytic hierarchy process , 1990 .

[56]  Paul Hooper,et al.  Evaluation strategies for packaging travel. , 1995 .

[57]  K. Grønhaug,et al.  Perceived Risk: Further Considerations for the Marketing Discipline , 1993 .

[58]  Metin Dagdeviren,et al.  Decision making in equipment selection: an integrated approach with AHP and PROMETHEE , 2008, J. Intell. Manuf..

[59]  Jean Pierre Brans,et al.  HOW TO SELECT AND HOW TO RANK PROJECTS: THE PROMETHEE METHOD , 1986 .

[60]  Deng Yong,et al.  A TOPSIS-BASED CENTROID–INDEX RANKING METHOD OF FUZZY NUMBERS AND ITS APPLICATION IN DECISION-MAKING , 2005 .

[61]  Jing-Shing Yao,et al.  Ranking fuzzy numbers based on decomposition principle and signed distance , 2000, Fuzzy Sets Syst..

[62]  J. Pérez.  Some comments on Saaty's AHP , 1995 .

[63]  J. Buckley,et al.  A fast method of ranking alternatives using fuzzy numbers , 1989 .

[64]  Simon Wong,et al.  Understanding the Behavior of Hong Kong Chinese Tourists on Group Tour Packages , 2001 .

[65]  E. Triantaphyllou,et al.  Ranking irregularities when evaluating alternatives by using some ELECTRE methods , 2008 .

[66]  T. Hsu,et al.  Using fuzzy set theoretic techniques to analyze travel risk: An empirical study , 2005 .

[67]  B. Asady,et al.  RANKING FUZZY NUMBERS BY DISTANCE MINIMIZATION , 2007 .

[68]  Gopal Achari,et al.  A Comparative Approach for Ranking Contaminated Sites Based on the Risk Assessment Paradigm Using Fuzzy PROMETHEE , 2009, Environmental management.

[69]  E. Lee,et al.  Comparison of fuzzy numbers based on the probability measure of fuzzy events , 1988 .

[70]  A. Decrop.  Triangulation in qualitative tourism research , 1999 .

[71]  Cengiz Kahraman,et al.  An integrated fuzzy multi-criteria decision making methodology for material handling equipment selection problem and an application , 2010, Expert Syst. Appl..

[72]  H. Kunzi,et al.  Lectu re Notes in Economics and Mathematical Systems , 1975 .

[73]  D. Dubois,et al.  A unified view of ranking techniques for fuzzy numbers , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

[74]  T. Seager,et al.  Application of Multicriteria Decision Analysis in Environmental Decision Making , 2005, Integrated environmental assessment and management.

[75]  J. Baldwin,et al.  Comparison of fuzzy sets on the same decision space , 1979 .

[76]  M. Vila,et al.  A procedure for ranking fuzzy numbers using fuzzy relations , 1988 .

[77]  V. Mitchell,et al.  A Preliminary Investigation into Pre‐ and Post‐Purchase Risk Perception and Reduction , 1994 .

[78]  Wen-Chieh Chou,et al.  Application of fuzzy theory and PROMETHEE technique to evaluate suitable ecotechnology method: A case study in Shihmen Reservoir Watershed, Taiwan , 2007 .

[79]  Johan Springael,et al.  PROMETHEE and AHP: The design of operational synergies in multicriteria analysis.: Strengthening PROMETHEE with ideas of AHP , 2004, Eur. J. Oper. Res..

[80]  R. Staelin,et al.  A Model of Perceived Risk and Intended Risk-handling Activity , 1994 .

[81]  Nicholas Frank Pidgeon,et al.  Editorial: Risk perception versus risk analysis , 1998 .

[82]  Jean-Philippe Waaub,et al.  Equity in international greenhouse gases abatement scenarios: A multicriteria approach , 2004, Eur. J. Oper. Res..

[83]  J. Bettman.  Perceived Risk and Its Components: A Model and Empirical Test , 1973 .

[84]  L. M. D. C. Ibáñez,et al.  A subjective approach for ranking fuzzy numbers , 1989 .

[85]  D. Yamamoto,et al.  Emerging Trends in Japanese Package Tourism , 1999 .

[86]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[87]  Lucien Duckstein,et al.  Comparison of fuzzy numbers using a fuzzy distance measure , 2002, Fuzzy Sets Syst..

[88]  L. Warg,et al.  Gender and regional differences in risk perception: results from implementing the Seveso II Directive in Sweden , 2002 .

[89]  R. Weber.  Basic Content Analysis , 1986 .

[90]  T. Chu,et al.  Ranking fuzzy numbers with an area between the centroid point and original point , 2002 .

[91]  Shigeaki Mabuchi,et al.  An approach to the comparison of fuzzy subsets with an α-cut dependent index , 1988, IEEE Trans. Syst. Man Cybern..

[92]  Chin-Tsai Lin,et al.  Selecting an Optimal Region by Fuzzy Group Decision Making: Empirical Evidence from Medical Investors , 2012 .

[93]  Ronald R. Yager,et al.  A context-dependent method for ordering fuzzy numbers using probabilities , 2001, Inf. Sci..

[94]  Constantin Zopounidis,et al.  A multicriteria classification approach based on pairwise comparisons , 2004, Eur. J. Oper. Res..

[95]  T. Wallsten,et al.  Individual Decision Behavior , 1972 .