Soft Computing

, Volume 23, Issue 4, pp 1357–1373 | Cite as

Combining user preferences and expert opinions: a criteria synergy-based model for decision making on the Web

  • Marcelo Karanik
  • Rubén BernalEmail author
  • José Ignacio Peláez
  • Jose Antonio Gomez-Ruiz
Methodologies and Application


Customers strongly base their e-commerce decisions on the opinions of others by checking reviews and ratings provided by other users. These assessments are overall opinions about the product or service, and it is not possible to establish why they perceive it as good or bad. To understand this “why”, it is necessary an expert’s analysis concerning the relevant factors of the product or service. Frequently, these two visions are not coincident and the best product for experts may not be the best one for users. For this reason, trustworthy decision-making methods that integrate the mentioned views are highly desirable. This article proposes a multi-criteria decision analysis model based on the integration of users’ preferences and experts’ opinions. It combines the majority’s opinion and criteria synergy to provide a unified perspective in order to support consumers’ ranking-based decisions in social media environments. At the same time, the model supplies useful information for managers about strengths and weaknesses of their product or service according to users’ experience and experts’ judgment. The aggregation processes and synergy criteria are modeled in order to obtain an adequate consensus mechanism. Finally, in order to test the proposed model, several simulations using hotel valuations are performed.


Decision making Multi-criteria decision analysis Criteria coalition synergy Majority aggregation Social media 



The authors are grateful to anonymous reviewers for their valuable comments. This work has been supported by the Project UTN4058 of National Technological University (Argentine) and the Fellowship for Short Term Postdoctoral Stays at University of Malaga – International Campus of Excellence Andalucía Tech (Spain, period 2016 – 2017).

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

Additional resources

In order to check the proposed method the examples used in Section 4 can be found in the next URL. The package is distributed containing source code files, data samples and examples used in this manuscript.


  1. Agichtein E, Castillo C, Donato D, Gionis A, Mishne G (2008) Finding high-quality content in social media. In: Proceedings of the international conference on Web search and web data mining—WSDM ’08. ACM Press, New York, USA, pp 183–194. doi: 10.1145/1341531.1341557
  2. Angilella S, Corrente S, Greco S (2015) Stochastic multiobjective acceptability analysis for the Choquet integral preference model and the scale construction problem. Eur J Oper Res 240(1):172–182. doi: 10.1016/j.ejor.2014.06.031 MathSciNetzbMATHGoogle Scholar
  3. Baethge C, Klier J, Klier M (2016) Social commerce-state-of-the-art and future research directions. Electron Mark 26(3):269–290. doi: 10.1007/s12525-016-0225-2 Google Scholar
  4. Bernal R, Karanik M, Peláez JI (2016) Fuzzy measure identification for criteria coalitions using linguistic information. Soft Comput 20(4):1315–1327. doi: 10.1007/s00500-015-1589-5
  5. Bernroider EWN, Schmöllerl P (2013) A technological, organisational, and environmental analysis of decision making methodologies and satisfaction in the context of IT induced business transformations. Eur J Oper Res 224(1):141–153. doi: 10.1016/j.ejor.2012.07.025 Google Scholar
  6. Branke J, Corrente S, Greco S, Sowiński R, Zielniewicz P (2016) Using Choquet integral as preference model in interactive evolutionary multiobjective optimization. Eur J Oper Res 250(3):884–901. doi: 10.1016/j.ejor.2015.10.027 MathSciNetzbMATHGoogle Scholar
  7. Cabrerizo FJ, López-Gijón J, Martínez MA, Morente-Molinera JA, Herrera-Viedma E (2017) A fuzzy linguistic extended LibQUAL+ model to assess service quality in academic libraries. Int J Inf Technol Decis Mak 16(1):225–244. doi: 10.1142/S0219622015500406 Google Scholar
  8. Cabrerizo FJ, Moreno JM, Pérez IJ, Herrera-Viedma E (2010) Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks. Soft Comput 14(5):451–463. doi: 10.1007/s00500-009-0453-x
  9. Chiclana F, García JMT, del Moral MJ, Herrera-Viedma E (2015) Analyzing consensus measures in group decision making. Procedia Comput Sci 55:1000–1008. doi: 10.1016/j.procs.2015.07.103 Google Scholar
  10. Choquet G (1954) Theory of capacities. Annales de L’institut Fourier 5:131–295MathSciNetzbMATHGoogle Scholar
  11. De Maio C, Fenza G, Loia V, Orciuoli F, Herrera-Viedma E (2016) A framework for context-aware heterogeneous group decision making in business processes. Knowl-Based Syst 102:39–50. doi: 10.1016/j.knosys.2016.03.019 Google Scholar
  12. Deng S, Sinha AP, Zhao H (2017) Adapting sentiment lexicons to domain-specific social media texts. Decis Support Syst 94:65–76. doi: 10.1016/j.dss.2016.11.001 Google Scholar
  13. Ding C, Cheng HK, Duan Y, Jin Y (2017) The power of the “like” button: The impact of social media on box office. Decis Support Syst 94:77–84. doi: 10.1016/j.dss.2016.11.002 Google Scholar
  14. Dong Y, Xiao J, Zhang H, Wang T (2016) Managing consensus and weights in iterative multiple-attribute group decision making. Appl Soft Comput 48:80–90. doi: 10.1016/j.asoc.2016.06.029 Google Scholar
  15. Figueira J, Greco S, Ehrogott M (2005) Multiple criteria decision analysis: state of the art surveys. Methods, vol 78. Springer, New York. doi: 10.1007/b100605
  16. Fodor J, Marichal J-L, Roubens M (1995) Characterization of the ordered weighted averaging operators. Fuzzy Syst IEEE Trans 3(2):236–240. doi: 10.1109/91.388176 Google Scholar
  17. Grabisch M (1997) fuzzy measures and their representation. Fuzzy Sets Syst 92(2):167–189. doi: 10.1016/S0165-0114(97)00168-1 MathSciNetzbMATHGoogle Scholar
  18. Grabisch M, Labreuche C (2016) Fuzzy measures and integrals in MCDA. Int Ser Oper Res Manag Sci 233:553–603. doi: 10.1007/978-1-4939-3094-4_14 zbMATHGoogle Scholar
  19. Herrera F, Herrera-Viedma E, Chiclana F (2001) Multiperson decision-making based on multiplicative preference relations. Eur J Oper Res 129(2):372–385. doi: 10.1016/S0377-2217(99)00197-6 MathSciNetzbMATHGoogle Scholar
  20. Herrera F, Herrera-Viedma E, Martınez L (2000) A fusion approach for managing multi-granularity linguistic term sets in decision making. Fuzzy Sets Syst 114(1):43–58. doi: 10.1016/S0165-0114(98)00093-1 zbMATHGoogle Scholar
  21. Hocevar KP, Flanagin AJ, Metzger MJ (2014) Social media self-efficacy and information evaluation online. Comput Hum Behav 39:254–262. doi: 10.1016/j.chb.2014.07.020 Google Scholar
  22. Hu M, Liu B (2004) Mining and Summarizing Customer Reviews. In Proceedings of the tenth ACM SIGKDD international conference on knowledge discovery and data mining. ACM, New York, NY, USA, pp 168–177. doi: 10.1145/1014052.1014073
  23. Huang Z, Benyoucef M (2013) From e-commerce to social commerce: a close look at design features. Electron Commer Res Appl 12(4):246–259. doi: 10.1016/j.elerap.2012.12.003 Google Scholar
  24. Huang Z, Benyoucef M (2015) User preferences of social features on social commerce websites: an empirical study. Technol Forecast Soc Chang 95:57–72. doi: 10.1016/j.techfore.2014.03.005 Google Scholar
  25. Huang Z, Benyoucef M (2017) The effects of social commerce design on consumer purchase decision-making: an empirical study. Electron Commer Res Appl 25:40–58. doi: 10.1016/j.elerap.2017.08.003 Google Scholar
  26. Jang H-J, Sim J, Lee Y, Kwon O (2013) Deep sentiment analysis: mining the causality between personality-value-attitude for analyzing business ads in social media. Expert Syst Appl 40(18):7492–7503. doi: 10.1016/j.eswa.2013.06.069 Google Scholar
  27. Joshi D, Kumar S (2016) Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making. Eur J Oper Res 248(1):183–191. doi: 10.1016/j.ejor.2015.06.047 MathSciNetzbMATHGoogle Scholar
  28. Kaplan AM, Haenlein M (2010) Users of the world, unite! The challenges and opportunities of Social Media. Bus Horiz 53(1):59–68. doi: 10.1016/j.bushor.2009.09.003 Google Scholar
  29. Karanik M, Peláez JI, Bernal R (2016) Selective majority additive ordered weighting averaging operator. Eur J Oper Res 250(3):816–826. doi: 10.1016/j.ejor.2015.10.011 MathSciNetzbMATHGoogle Scholar
  30. Li G, Law R, Vu HQ, Rong J (2013) Discovering the hotel selection preferences of Hong Kong inbound travelers using the Choquet Integral. Tour Manag 36:321–330. doi: 10.1016/j.tourman.2012.10.017 Google Scholar
  31. Li Y, Wu C, Lai C (2013) A social recommender mechanism for e-commerce: combining similarity, trust, and relationship. Decis Support Syst 55(3):740–752. doi: 10.1016/j.dss.2013.02.009 Google Scholar
  32. Liang T-P, Turban E (2011) Introduction to the special issue social commerce: a research framework for social commerce. Int J Electron Commer 16(2):5–14. doi: 10.2753/JEC1086-4415160201
  33. Lockyer T (2005) The perceived importance of price as one hotel selection dimension. Tour Manag. doi: 10.1016/j.tourman.2004.03.009
  34. Massanet S, Vicente Riera J, Torrens J, Herrera-Viedma E (2016) A model based on subjective linguistic preference relations for group decision making problems. Inf Sci 355(356):249–264. doi: 10.1016/j.ins.2016.03.040 Google Scholar
  35. Mata F, Pérez LG, Zhou S-M, Chiclana F (2014) Type-1 OWA methodology to consensus reaching processes in multi-granular linguistic contexts. Knowl-Based Syst 58:11–22. doi: 10.1016/j.knosys.2013.09.017 Google Scholar
  36. Muzychuk A (2011) OWA weight updating in repeated decision making under the influence of additional information. Int J Intell Syst 26(7):591–602. doi: 10.1002/int.20472 Google Scholar
  37. Nguyen TH, Shirai K, Velcin J (2015) Sentiment analysis on social media for stock movement prediction. Expert Syst Appl 42(24):9603–9611. doi: 10.1016/j.eswa.2015.07.052 Google Scholar
  38. Pasi G, Yager RR (2003) Modeling the concept of fuzzy majority opinion. In: Bilgiç T, De Baets B, Kaynak O (eds) Fuzzy sets and systems—IFSA 2003: 10th International Fuzzy Systems Association World Congress Istanbul, Turkey, June 30–July 2, 2003 proceedings. Springer, Berlin, Heidelberg, pp 143–150. doi: 10.1007/3-540-44967-1_16
  39. Peláez JI, Doña JM (2003a) LAMA: a linguistic aggregation of majority additive operator. Int J Intell Syst 18(7):809–820. doi: 10.1002/int.10117 zbMATHGoogle Scholar
  40. Peláez JI, Doña JM (2003b) Majority additive-ordered weighting averaging: a new neat ordered weighting averaging operator based on the majority process. Int J Intell Syst 18(4):469–481zbMATHGoogle Scholar
  41. Peláez JI, Doña JM (2006) A majority model in group decision making using QMA–OWA operators. Int J Intell Syst 21(2):193–208. doi: 10.1002/int.20127 zbMATHGoogle Scholar
  42. Peláez JI, Doña JM, Gómez Ruiz JA (2007) Analysis of OWA operators in decision making for modelling the majority concept. Appl Math Comput 186(2):1263–1275. doi: 10.1016/j.amc.2006.07.161 MathSciNetzbMATHGoogle Scholar
  43. Peláez JI, Bernal R, Karanik M (2016) Majority OWA operator for opinion rating in social media. Soft Comput. doi: 10.1007/s00500-014-1564-6
  44. Ravi K, Ravi V (2015) A survey on opinion mining and sentiment analysis: tasks, approaches and applications. Knowl-Based Syst 89:14–46. doi: 10.1016/j.knosys.2015.06.015 Google Scholar
  45. Rolland A (2013) Reference-based preferences aggregation procedures in multi-criteria decision making. Eur J Oper Res 225(3):479–486. doi: 10.1016/j.ejor.2012.10.013 MathSciNetzbMATHGoogle Scholar
  46. Sohrabi B, Vanani IR, Tahmasebipur K, Fazli S (2012) An exploratory analysis of hotel selection factors: a comprehensive survey of Tehran hotels. Int J Hosp Manag 31(1):96–106. doi: 10.1016/j.ijhm.2011.06.002 Google Scholar
  47. Sugeno M (1974) Theory of fuzzy integrals and its applications. Tokyo Institute of Technology, TokyoGoogle Scholar
  48. Sun Y, Wei KK, Fan C, Lu Y, Gupta S (2016) Does social climate matter? On friendship groups in social commerce. Electron Commer Res Appl 18:37–47. doi: 10.1016/j.elerap.2016.06.002 Google Scholar
  49. Tan C (2011) A multi-criteria interval-valued intuitionistic fuzzy group decision making with Choquet integral-based TOPSIS. Expert Syst Appl 38(4):3023–3033. doi: 10.1016/j.eswa.2010.08.092 Google Scholar
  50. Taylor E, Hewitt K, Reeves RA, Hobbs SH, Lawless WF (2013) Group decision-making: consensus rule versus majority rule. Procedia Technol 9:498–504. doi: 10.1016/j.protcy.2013.12.055 Google Scholar
  51. Wu Z, Xu J (2012) A consistency and consensus based decision support model for group decision making with multiplicative preference relations. Decis Support Syst 52(3):757–767. doi: 10.1016/j.dss.2011.11.022 Google Scholar
  52. Yager RR (1988) On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE Trans Syst Man Cybern 18(1):183–190. doi: 10.1109/21.87068 MathSciNetzbMATHGoogle Scholar
  53. Yager RR, Kacprzyk J, Beliakov G (2011) Recent developments in the ordered weighted averaging operators: theory and practice, 1st edn. Springer (Incorporated), BerlinGoogle Scholar
  54. Yan H-B, Ma T (2015) A group decision-making approach to uncertain quality function deployment based on fuzzy preference relation and fuzzy majority. Eur J Oper Res 241(3):815–829. doi: 10.1016/j.ejor.2014.09.017 MathSciNetzbMATHGoogle Scholar
  55. Yu Y, Cao Q (2013) The impact of social and conventional media on firm equity value: a sentiment analysis approach. Decis Support Syst 55(4):919–926. doi: 10.1016/j.dss.2012.12.028 Google Scholar
  56. Zarghami M, Szidarovszky F (2009) Revising the OWA operator for multi criteria decision making problems under uncertainty. Eur J Oper Res 198(1):259–265. doi: 10.1016/j.ejor.2008.09.014 MathSciNetzbMATHGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Marcelo Karanik
    • 1
    • 2
  • Rubén Bernal
    • 1
    Email author
  • José Ignacio Peláez
    • 2
    • 3
  • Jose Antonio Gomez-Ruiz
    • 2
    • 3
  1. 1.National Technological UniversityResistenciaArgentina
  2. 2.International Campus of Excellence Andalucía TechMálagaSpain
  3. 3.Department of Languages and Computer ScienceInstitute of Biomedical Research of Malaga (IBIMA), University of MalagaMálagaSpain

Personalised recommendations