Skip to main content
SpringerLink
Log in
SpringerLink
Log in

Using PEQUAL Methodology in Auction Platforms Evaluation Process

  • Conference paper
  • First Online:
Information Technology for Management: New Ideas and Real Solutions (ISM 2016, AITM 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 277))

Abstract

Together with the growth of e-commerce sector, companies are focusing more and more attention on website quality evaluations. Evolution along with an ever-growing set of available methods are being observed for online shopping platforms, as well as auctions, and it is creating better representations of various characteristics and parameters. The following article presents a usability study of auction websites based on the PEQUAL methodology. The used method is based on the extended version of classical EQUAL method with taken into account different aspects of preference modelling and aggregation derived from Multi-Criteria Decision Analysis (MCDA). Presented empirical verification has been conducted out for top auction websites and results show significant practical possibilities of analysis of obtained results.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Pinker, E.J., Seidmann, A., Vakrat, Y.: Managing online auctions: current business and research issues. Manage. Sci. 49(11), 1457–1484 (2003). doi:10.1287/mnsc.49.11.1457.20584

    Article  Google Scholar 

  2. Bewsell, G.R.: Distrust, fear and emotional learning: an online auction perspective. J. Theor. Appl. Electron. Comer. Res. 7(2), 1–12 (2012). doi:10.4067/S0718-18762012000200002

    Article  Google Scholar 

  3. Blum, A., Kumar, V., Rudra, A., Wu, F.: Online learning in online auctions. Theor. Comput. Sc. 324(2), 137–146 (2004). doi:10.1016/j.tcs.2004.05.012

    Article  MathSciNet  MATH  Google Scholar 

  4. Paarsch, H.J., Hong, H.: An Introduction to the Structural Econometrics of Auction Data. MIT Press Books (2006)

    Google Scholar 

  5. Lucking-Reiley, D., Bryan, D., Prasad, N., Reeves, D.: Pennies from eBay: the determinants of price in online auctions. J. Ind. Econ. 55(2), 223–233 (2007). doi:10.1111/j.1467-6451.2007.00309.x

    Article  Google Scholar 

  6. Ariely, D., Simonson, I.: Buying, bidding, playing, or competing? value assessment and decision dynamics in online auctions. J. Consum. Psychol. 13(1), 113–123 (2003). doi:10.1207/S15327663JCP13-1&2_10

    Article  Google Scholar 

  7. Yen, C.H., Lu, H.P.: Factors influencing online auction repurchase intention. Internet Res. 18(1), 7–25 (2008). doi:10.1108/10662240810849568

    Article  Google Scholar 

  8. Calisir, F., Elvan Bayraktaroglu, A., Altin Gumussoy, C., Ilker Topcu, Y., Mutlu, T.: The relative importance of usability and functionality factors for online auction and shopping web sites. Online Inform. Rev. 34(3), 420–439 (2010). doi:10.1108/14684521011037025

    Article  Google Scholar 

  9. Gregg, D.G., Walczak, S.: The relationship between website quality, trust and price premiums at online auctions. Electron. Commer. R. 10(1), 1–25 (2010). doi:10.1007/s10660-010-9044-2

    Article  Google Scholar 

  10. Barnes, S.J., Vidgen, R.T.: Assessing the quality of auction web sites. In: Proceedings of the 34th Annual Hawaii International Conference on System Sciences, pp. 10. IEEE (2001). doi:10.1109/HICSS.2001.927087

  11. Yen, C.H., Lu, H.P.: Effects of e-service quality on loyalty intention: an empirical study in online auction. Manag. Serv. Qual. Int. J. 18(2), 127–146 (2008). doi:10.1108/09604520810859193

    Article  Google Scholar 

  12. Hasan, L., Morris, A., Probets, S.: Using google analytics to evaluate the usability of e-commerce sites. In: Kurosu, M. (ed.) HCD 2009. LNCS, vol. 5619, pp. 697–706. Springer, Heidelberg (2009). doi:10.1007/978-3-642-02806-9_81

    Chapter  Google Scholar 

  13. Yadav, J., Mallick, B.: Web Mining: Characteristics and application in ecommerce. Int. J. IJECSE. 1(4), 2020–2025 (2012)

    Google Scholar 

  14. Wu, X., Bolivar, A.: Predicting the conversion probability for items on C2C ecommerce sites. In: Cheung, D., Song, I.-Y. (eds.) Proceedings of the 18th ACM Conference on Information and Knowledge Management, pp. 1377–1386. ACM, New York (2009). doi:10.1145/1645953.16461274567

  15. Srinivasan, S.S., Anderson, R., Ponnavolu, K.: Customer loyalty in e-commerce: an exploration of its antecedents and consequences. J. Retailing. 78(1), 41–50 (2002). doi:10.1016/S0022-4359(01)00065-3

    Article  Google Scholar 

  16. Manchala, D.W.: E-commerce trust metrics and models. IEEE Internet Comput. 4(2), 36–44 (2000). doi:10.1109/4236.832944

    Article  Google Scholar 

  17. Koohang, A., Paliszkiewicz, J.: E-Learning courseware usability: building a theoretical model. J. Comput. Inform. Syst. 56(1), 55–61 (2016). doi:10.1080/08874417.2015.11645801

    Google Scholar 

  18. Ziemba, E., Papaj, T., Żelazny, R.: A model of success factors for e-government adoption–the case of Poland. Issues Inf. Syst. 14(2), 87–100 (2013)

    Google Scholar 

  19. Cao, M., Zhang, Q., Seydel, J.: B2C e-commerce web site quality: an empirical examination. Ind. Manage. Data Syst. 105(5), 645–661 (2005). doi:10.1108/02635570510600000

    Article  Google Scholar 

  20. Ghosh, A.K.: E-commerce Security and Privacy. Springer, New York (2012)

    Google Scholar 

  21. Sohaib, O., Kang, K.: The importance of web accessibility in Business to-Consumer (B2C) websites. In: 22nd Australasian Software Engineering Conference (ASWEC 2013) (2013)

    Google Scholar 

  22. Lituchy, T.R., Barra, R.A.: International issues of the design and usage of websites for e-commerce: Hotel and airline examples. J. Eng. Technol. Manage. 25(1), 93–111 (2008). doi:10.1016/j.jengtecman.2008.01.004

    Article  Google Scholar 

  23. Sohaib, O.: Usability and cultural issues in global e-commerce. J. Eng. Technol. Manage. 25(1), 156–166 (2012)

    Google Scholar 

  24. Belanche, D., Casaló, L.V., Guinalíu, M.: Website usability, consumer satisfaction and the intention to use a website: the moderating effect of perceived risk. J. Retail. Consum. Serv. 19(1), 124–132 (2012). doi:10.1016/j.jretconser.2011.11.001

    Article  Google Scholar 

  25. Jankowski, J., Kolomvatsos, K., Kazienko, P., Wątróbski, J.: Fuzzy modeling of user behaviors and virtual goods purchases in social networking platforms. J. Univers. Comput. Sci. 22(3), 416–437 (2016)

    MathSciNet  Google Scholar 

  26. Koohang, A., Paliszkiewicz, J.: Empirical validation of an learning courseware usability model. Issues Inf. Syst. 15(2), 270–275 (2014)

    Google Scholar 

  27. Ziemba, P., Jankowski, J., Wątróbski, J., Wolski, W., Becker, J.: Integration of domain ontologies in the repository of website evaluation methods. In: Ganzha, M., Maciaszek, L., Paprzycki, M. (eds.) Proceedings of the Federated Conference on Computer Science and Information Systems. ACSIS, vol. 5, pp. 1585–1595. (2015). doi:10.15439/2015F297

  28. Wątróbski, J., Ziemba, P., Jankowski, J., Wolski, W.: PEQUAL-E-commerce websites quality evaluation methodology. In: Ganzha, M., Maciaszek, L., Paprzycki M. (eds.) Proceedings of the Federated Conference on Computer Science and Information Systems. ACSIS, vol. 8, pp. 1317–1327 (2016). doi:10.15439/2016F46

  29. Nielsen, J.: Usability Engineering. Morgan Kaufmann, San Francisco (1993)

    MATH  Google Scholar 

  30. ISO 9241-11:1998(E). http://www.iso.org/iso/catalogue_detail.htm?csnumber=16883

  31. ISO/IEC 25010:2011. http://www.iso.org/iso/home/store/catalogue_ics/catalogue_detail_ics.htm?csnumber=35733

  32. Usability 101: Introduction to Usability. http://www.nngroup.com/articles/usability-101-introduction-to-usability/

  33. Fernandez, A., Insfran, E., Abrahão, S.: Usability evaluation methods for the web: a systematic mapping study. Inform. Softw. Tech. 53(8), 789–817 (2011). doi:10.1016/j.infsof.2011.02.007

    Article  Google Scholar 

  34. Albert, B., Tullis, T., Tedesco, D.: Beyond The Usability Lab: Conducting Large-scale Online User Experience Studies. Morgan Kaufmann, Elsevier, Amsterdam (2010)

    Google Scholar 

  35. The Usability Methods Toolbox Handbook. http://www.idemployee.id.tue.nl/g.w.m.rauterberg/lecturenotes/UsabilityMethodsToolboxHandbook.pdf

  36. Rubin, J., Chisnell, D.: Handbook of Usability Testing, How to Plan, Design, and Conduct Effective Tests. Wiley, Hoboken (2008)

    Google Scholar 

  37. Holzinger, A.: Usability engineering methods for software developers. Commun. ACM 48(1), 71–74 (2005). doi:10.1145/1039539.1039541

    Article  Google Scholar 

  38. Jankowski, J., Kazienko, P., Wątróbski, J., Lewandowska, A., Ziemba, P., Zioło, M.: Fuzzy multi-objective modeling of effectiveness and user experience in online advertising. Expert Syst. Appl. 65, 315–331 (2016). doi:10.1016/j.eswa.2016.08.049

    Article  Google Scholar 

  39. Jankowski, J., Ziemba, P., Wątróbski, J., Kazienko, P.: Towards the tradeoff between online marketing resources exploitation and the user experience with the use of eye tracking. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, T.-P. (eds.) ACIIDS 2016. LNCS (LNAI), vol. 9621, pp. 330–343. Springer, Heidelberg (2016). doi:10.1007/978-3-662-49381-6_32

    Chapter  Google Scholar 

  40. Ziemba, P., Piwowarski, M., Jankowski, J., Wątróbski, J.: Method of criteria selection and weights calculation in the process of web projects evaluation. In: Hwang, D., Jung, J.J., Nguyen, N.-T. (eds.) ICCCI 2014. LNCS (LNAI), vol. 8733, pp. 684–693. Springer, Heidelberg (2014). doi:10.1007/978-3-319-11289-3_69

    Google Scholar 

  41. Ziemba, P., Wątróbski, J., Jankowski, J., Wolski, W.: Construction and restructuring of the knowledge repository of website evaluation methods. In: Ziemba, E. (ed.). LNBIP, vol. 243, pp. 29–52. Springer, Heidelberg (2016). doi:10.1007/978-3-319-30528-8_3

    Chapter  Google Scholar 

  42. Barnes, S.J., Vidgen, R.: Measuring web site quality improvements: a case study of the forum on strategic management knowledge exchange. Ind. Manage. Data Syst. 103(5), 297–309 (2003). doi:10.1108/02635570310477352

    Article  Google Scholar 

  43. Barnes, S.J., Vidgen, R.T.: Data triangulation and web quality metrics: a case study in e-government. Inform. Manage. 43(6), 767–777 (2006). doi:10.1016/j.im.2006.06.001

    Article  Google Scholar 

  44. Ahn, T., Ryu, S., Han, I.: The impact of the online and offline features on the user acceptance of Internet shopping malls. Electron. Commer. R. A. 3(4), 405–420 (2005). doi:10.1016/j.elerap.2004.05.001

    Article  Google Scholar 

  45. Webb, H.W., Webb, L.A.: Business to consumer electronic commerce website quality: integrating information and service dimensions. In: Association for Information Systems AIS Electronic Library. AMCIS 2001 Proceedings, vol. 111, pp. 559–562 (2001)

    Google Scholar 

  46. Elling, S., Lentz, L., Jong, M.: Website evaluation questionnaire: development of a research-based tool for evaluating informational websites. In: Wimmer, M.A., Scholl, J., Grönlund, Å. (eds.) EGOV 2007. LNCS, vol. 4656, pp. 293–304. Springer, Heidelberg (2007). doi:10.1007/978-3-540-74444-3_25

    Chapter  Google Scholar 

  47. Yang, Z., Cai, S., Zhou, Z., Zhou, N.: Development and validation of an instrument to measure user perceived service quality of information presenting web portals. Inform. Manage. 42(4), 575–589 (2005). doi:10.1016/j.im.2004.03.001

    Article  Google Scholar 

  48. Ping Zhang, G.M.: User expectations and rankings of quality factors in different web site domains. Int. J. Electron. Comm. 6(2), 9–33 (2001)

    Google Scholar 

  49. Parasuraman, A., Zeithaml, V.A., Malhotra, A.: ES-QUAL a multiple-item scale for assessing electronic service quality. J. Serv. Res-US. 7(3), 213–233 (2005). doi:10.1177/1094670504271156

    Article  Google Scholar 

  50. Demchak, C.C., Friis, C., La Porte, T.M.: Webbing governance: national differences in constructing the face of public organizations. In: Garson, G.D. (ed.) Handbook of Public Information Systems, pp. 179–196. Marcel Dekker, New York (2000)

    Google Scholar 

  51. Shih, H.P.: Extended technology acceptance model of Internet utilization behaviour. Inform. Manage. 41(6), 719–729 (2004). doi:10.1016/j.im.2003.08.009

    Article  Google Scholar 

  52. Seddon, P.B.: A respecification and extension of the DeLone and McLean model of IS success. Inform. Syst. Res. 8(3), 240–253 (1997). doi:10.1287/isre.8.3.240

    Article  Google Scholar 

  53. Ahn, T., Ryu, S., Han, I.: The impact of Web quality and playfulness on user acceptance of online retailing. Inform. Manage. 44(3), 263–275 (2007). doi:10.1016/j.im.2006.12.008

    Article  Google Scholar 

  54. Suh, B., Han, I.: Effect of trust on customer acceptance of Internet banking. Electron. Commer. R. A. 1(3), 247–263 (2003). doi:10.1016/S1567-4223(02)00017-0

    Google Scholar 

  55. Jafari, S.M., Ali, N.A., Sambasivan, M., Said, M.F.: A respecification and extension of DeLone and McLean model of IS success in the citizen-centric e-governance. In: 2011 IEEE International Conference on Information Reuse and Integration, pp. 342–346. IEEE (2011)

    Google Scholar 

  56. Wang, R.Y., Strong, D.M.: Beyond accuracy: What data quality means to data consumers. J. Manage. Inform. Syst. 12(4), 5–33 (1996). doi:10.1080/07421222.1996.11518099

    Article  Google Scholar 

  57. Muylle, S., Moenaert, R., Despontin, M.: The conceptualization and empirical validation of web site user satisfaction. Inform. Manage. 41(5), 543–560 (2004). doi:10.1016/S0378-7206(03)00089-2

    Article  Google Scholar 

  58. Parasuraman, A., Zeithaml, V.A., Berry, L.L.: SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality. J. Retailing. 64, 12–40 (1988)

    Google Scholar 

  59. Zenebe, A., Zhou, L., Norcio, A.F.: User preferences discovery using fuzzy models. Fuzzy Set. Syst. 161(23), 3044–3063 (2010). doi:10.1016/j.fss.2010.06.006

    Article  MathSciNet  Google Scholar 

  60. Ziemba, P., Jankowski, J., Wątróbski, J., Piwowarski, M.: Web projects evaluation using the method of significant website assessment criteria detection. In: Nguyen, N.T., Kowalczyk, R. (eds.). LNCS, vol. 9655, pp. 167–188. Springer, Heidelberg (2016). doi:10.1007/978-3-662-49619-0_9

    Chapter  Google Scholar 

  61. Kim, S., Stoel, L.: Dimensional hierarchy of retail website quality. Inform. Manage. 41(5), 619–633 (2004). doi:10.1016/j.im.2003.07.002

    Article  Google Scholar 

  62. Lee, Y., Kozar, K.A.: Investigating the effect of website quality on e-business success: an analytic hierarchy process (AHP) approach. Decis. Support Syst. 42(3), 1383–1401 (2006). doi:10.1016/j.dss.2005.11.005

    Article  Google Scholar 

  63. Chmielarz, W., Zborowski, M.: Comparative analysis of electronic banking Websites in selected banks in Poland in 2014. Ann. Comput. Sci. Inf. Syst. 5, 1499–11504 (2015). doi:10.15439/2015F43

    Article  Google Scholar 

  64. Chmielarz, W.: Evaluation of selected mobile applications stores from the user’s perspective. Online J. Appl. Knowl. Manag. 3, 21–36 (2015)

    Google Scholar 

  65. Sun, C.C., Lin, G.T.: Using fuzzy TOPSIS method for evaluating the competitive advantages of shopping websites. Expert Syst. Appl. 36(9), 11764–11771 (2009). doi:10.1016/j.eswa.2009.04.017

    Article  Google Scholar 

  66. Del Vasto-Terrientes, L., Valls, A., Slowinski, R., Zielniewicz, P.: ELECTRE-III-H: an outranking-based decision aiding method for hierarchically structured criteria. Expert Syst. Appl. 42(11), 4910–4926 (2015). doi:10.1016/j.eswa.2015.02.016

    Article  Google Scholar 

  67. Lin, H.F.: An application of fuzzy AHP for evaluating course website quality. Comput. Educ. 54(4), 877–888 (2010). doi:10.1016/j.compedu.2009.09.017

    Article  Google Scholar 

  68. Kong, F., Liu, H.: Applying fuzzy analytic hierarchy process to evaluate success factors of e-commerce. Int. J. Inf. Syst. Sci. 1(3–4), 406–412 (2005)

    MATH  Google Scholar 

  69. Bilsel, R.U., Büyüközkan, G., Ruan, D.: A fuzzy preference-ranking model for a quality evaluation of hospital web sites. Int. J. Intell. Syst. 21(11), 1181–1197 (2006). doi:10.1002/int.20177

    Article  MATH  Google Scholar 

  70. Kaya, T.: Multi-attribute evaluation of website quality in E-business using an integrated fuzzy AHPTOPSIS methodology. Int. J. Comput. Intell. Syst. 3(3), 301–314 (2010). doi:10.1080/18756891.2010.9727701

    Article  Google Scholar 

  71. Huang, J., Jiang, X., Tang, Q.: An e-commerce performance assessment model: Its development and an initial test on e-commerce applications in the retail sector of China. Inform. Manage. 46(2), 100–108 (2009). doi:10.1016/j.im.2008.12.003

    Article  Google Scholar 

  72. The top 500 sites on the web. http://www.alexa.com/topsites/category;3/Business/Shopping

  73. Mobile and Tablet e-Commerce: Is Anyone Really Ready? https://www.mitx.org/files/zmags-top100-web.pdf

  74. Wątróbski, J., Ziemba, P., Jankowski, J., Zioło, M.: Green energy for a green city—A multi-perspective model approach. Sustain. 8(8), 702 (2016). doi:10.3390/su8080702

    Article  Google Scholar 

  75. Brans, J.P., Vincke, P., Mareschal, B.: How to select and how to rank projects: The PROMETHEE method. Eur. J. Oper. Res. 24(2), 228–238 (1986). doi:10.1016/0377-2217(86)90044-5

    Article  MathSciNet  MATH  Google Scholar 

  76. Wątróbski, J., Jankowski, J.: An ontology-based knowledge representation of MCDA methods. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, T.-P. (eds.) ACIIDS 2016. LNCS (LNAI), vol. 9621, pp. 54–64. Springer, Heidelberg (2016). doi:10.1007/978-3-662-49381-6_6

    Chapter  Google Scholar 

  77. Brans, J.P., Mareschal, B.: PROMETHEE methods. In: Multiple Criteria Decision Analysis: State of the Art Surveys. International Series in Operations Research & Management Science, vol. 78, pp. 163–186. Springer, New York (2005). doi:10.1007/0-387-23081-5_5

  78. Brans, J.P., Mareschal, B.: The PROMETHEE methods for MCDM; the PROMCALC, GAIA and BANKADVISER software. In: Bana e Costa, C.A. (ed.) Readings in Multiple Criteria Decision Aid, pp. 216–252. Springer, Heidelberg (1990). doi:10.1007/978-3-642-75935-2_10

Download references

Author information

Authors and Affiliations

  1. Faculty of Computer Science, West Pomeranian University of Technology in Szczecin, Żołnierska 49, 71-210, Szczecin, Poland

    Jarosław Wątróbski & Jarosław Jankowski

  2. The Jacob of Paradyż University of Applied Science in Gorzów Wielkopolski, Chopina 52, 66-400, Gorzów Wielkopolski, Poland

    Paweł Ziemba

  3. University of Szczecin, Mickiewicza 64, 71-101, Szczecin, Poland

    Waldemar Wolski

Authors
  1. Jarosław Wątróbski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Paweł Ziemba
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jarosław Jankowski
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Waldemar Wolski
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jarosław Wątróbski .

Editor information

Editors and Affiliations

  1. University of Economics in Katowice, Katowice, Poland

    Ewa Ziemba

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Wątróbski, J., Ziemba, P., Jankowski, J., Wolski, W. (2017). Using PEQUAL Methodology in Auction Platforms Evaluation Process. In: Ziemba, E. (eds) Information Technology for Management: New Ideas and Real Solutions. ISM AITM 2016 2016. Lecture Notes in Business Information Processing, vol 277. Springer, Cham. https://doi.org/10.1007/978-3-319-53076-5_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-53076-5_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53075-8

  • Online ISBN: 978-3-319-53076-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation