A Cluster Analysis for Determining the Effects of Codes of Conduct in the Business Administration

  • David López-Jiménez
  • Salvador Bueno
  • M. Dolores Gallego
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 151)

Abstract

In recent years, the impact that e-commerce has had on the economy has motivated many organizations to adopt codes of conduct. Considering the current wide-spreading of codes of conduct, we aim to analyze the effects that adhering to them have in different areas of firm management as synergy generators that are advantageous to the company. To achieve this, we are going to apply cluster analysis techniques, in combination with ANOVA and determinant analysis to a sample of companies that adhere to the code of conduct. Cluster analysis reveals that there are five significant clusters. Each cluster can be interpreted as different levels of perceptions about the effects of the codes of conduct in company management.

Keywords

B2C Cluster Codes of conduct E-commerce Multivariate analysis 

References

  1. 1.
    Hu X, Lin Z, Zhang H (2002) Trust promoting seals in electronics markets: an exploratory study of their effectiveness for online sales promotion. J Promot Manag 9(1):163–180CrossRefGoogle Scholar
  2. 2.
    Rifon NJ, La Rose R, Choin SM (2005) Your privacy is sealed: effects of privacy seals on trust and personal disclosures. J Consum Aff 39(2):337–360CrossRefGoogle Scholar
  3. 3.
    Luo X (2002) Trust production and privacy concerns on the internet—a framework based on relationship marketing and social exchange theory. Ind Mark Manag 31:111–118CrossRefGoogle Scholar
  4. 4.
    Manolea B (2003) Creating confidence in electronic transactions-trustmarks. Available at: http://www.legi-internet.ro/trustmarks.ppt#2
  5. 5.
    Marcus JS, Carter K, Robinson N, Klautzer L, Marsden C (2007) Comparison of privacy and trust policies in the area of electronic communications, Bad Honnef, 2007. Available at: http://ec.europa.eu/information_society/policy/ecomm/doc/library/ext_studies/privacy_trust_policies/final_report_29_02_08.pdf
  6. 6.
    Gierl H, Winkler S (2000) Neue Gütezeichen als Qualitätssignale. Marketing ZFP 1(3):197–207Google Scholar
  7. 7.
    Riegelsberger J, Sasse MA (2000) Trust me, I’m a.com—the problem of reassuring shoppers in electronic retail environments. Intermedia 28(4) Available at: http://hornbeam.cs.ucl.ac.uk/hcs/people/documents/Angela%20Publications/2000/trustme.htm
  8. 8.
    Russell TT, Lane WR (2002) Kleppner′s advertising procedure. Prentice Hall, Upper Saddle RiverGoogle Scholar
  9. 9.
    Repo P, Nordquist F (2005) Marking and code trust in E-Commerce. In: Wachowicz J (ed) Electronic commerce theory and applications. JIB E-Consulting, GdanskGoogle Scholar
  10. 10.
    Koreto R (1997) In CPAs we trust. J Account 184(6):62–64Google Scholar
  11. 11.
    McKnight DH, Cummings LL, Chervany NL (1998) Initial trust formation in new organizational relationships. Acad Manag Rev 23(3):473–490Google Scholar
  12. 12.
    Sivasailam N, Kim DJ, Rao HR (2002) What companies are(n’t) doing about web site assurance. IT Pro 4(3):33–40CrossRefGoogle Scholar
  13. 13.
    Aiken KD, Osland G, Liu B, Mackoy R (2003) Developing internet consumer trust: exploring trustmarks as third-party signals. In: Henderson GR, Moore MC (eds) Marketing theory and applications, vol 14. American Marketing Association, Chicago, pp 145–146Google Scholar
  14. 14.
    Pavlou PA, Gefen D (2004) Building effective online marketplaces with institution-based trust. Inf Syst Res 15(1):37–59CrossRefGoogle Scholar
  15. 15.
    Balboni P (2005) Managing the legal risk in providing online quality certification services in EU. In: Paulus S, Pohlmann N, Reimer H (eds) ISSE 2005—securing electronic business processes: highlights of the information security solutions Europe 2005 conference, Vieweg, Wiesbaden, pp 189–200Google Scholar
  16. 16.
    Aiken KD, Bousch DM (2006) Trustmarks, objective-source ratings, and implied investments in advertising: investigating online trust and the context-specific nature of internet signals. J Acad Mark Sci 34(3):308–323CrossRefGoogle Scholar
  17. 17.
    Meziane F, Kasiran MK (2007) Evaluating trust in electronic commerce: a study based on the information provided on merchants’ websites. J Oper Res Soc 59:464–472CrossRefGoogle Scholar
  18. 18.
    Kim DJ, Steinfield C, Lai YL (2008) Revisiting the role of web assurance seals. Decis Support Syst 44(4):1000–1015CrossRefGoogle Scholar
  19. 19.
    Mcknight DH, Choudhary V, Kacmar C (2004) Shifting factors and the ineffectiveness of third party assurance seals: a two-stage model of initial trust in an E-vendor. Electron Mark 14(3):252–266CrossRefGoogle Scholar
  20. 20.
    Zhang H (2005) Trust promoting seals in electronic markets: impact on online shopping decisions. Journal of Inf Technol Theory Appl 6(4):29–40Google Scholar
  21. 21.
    Calliess GP (2007) Transnational consumer law: co-regulation of B2C-E-Commerce. Law Res Inst Res Pap 3(3)Google Scholar
  22. 22.
    Kaihong X, Mingxia W (2007) Economic function of trust seal in E-Commerce: an experiment study based on Chinese subjects. Serv Syst Serv Manag 9–11:1–5Google Scholar
  23. 23.
    Wang S, Beatty SE, Foxx W (2004) Signaling the trustworthiness of small online retailers. J Interact Mark 18(1):53–69CrossRefGoogle Scholar
  24. 24.
    H.H. Bock, “Probabilistic models in cluster analysis”, Computational Statistics & Data Analysis, vol. 23, no. 1, pp. 5-28, 1996.MATHCrossRefGoogle Scholar
  25. 25.
    Luan J (2002) Data mining and its application in Higher education. New Dir Instit Res 113:17–36CrossRefGoogle Scholar
  26. 26.
    Chung W, Chen H, Nunamaker JF (2003) Business intelligence explorer: a knowledge map framework for discovering business intelligence on the web proceedings, 36th Hawaii international conference on system sciencesGoogle Scholar
  27. 27.
    Bucher T, Dinter B (2008) Process orientation of information logistics—an empirical analysis to assess benefits, design factors, and realization approaches. In: Proceedings of the 41st Hawaii international conference on system sciences, p 392Google Scholar
  28. 28.
    Brown MT, Wicker LR (2000) Discriminant analysis. In: Tinsley HEA, Brown SD (eds) Handbook of applied multivariate statistics and mathematical modeling. Academic Press, San Diego, pp 209–235CrossRefGoogle Scholar
  29. 29.
    Hair JF, Anderson RE, Tathan RL, Black WC (2000) Multivariate analysis. Prentice Hall, New YorkGoogle Scholar
  30. 30.
    Salmeron JL, Bueno S (2006) An information technologies and information systems industry-based classification in small and medium-sized enterprises: An institutional view. Eur J Oper Res 173(3):1012–1025MATHCrossRefGoogle Scholar
  31. 31.
    Almeida JAS, Barbosa LMS, Pais AACC, Formosinho SJ (2007) Improving hierarchical cluster analysis: A new method with outlier detection and automatic clustering. Chemometrics Intell Lab Syst 87(2):208–217CrossRefGoogle Scholar
  32. 32.
    Aldenderfer MS, Blashfield RK (1984) Cluster analysis. Sage, LondonGoogle Scholar
  33. 33.
    Cortina JM, Nouri H (2000) Effect size for ANOVA designs. Sage, LondonGoogle Scholar
  34. 34.
    Munroe PT, Salkind NJ (2007) Anova (Analysis of Variance). In: Ritzer G (ed) Blackwell encyclopedia of sociology, Wiley, New YorkGoogle Scholar
  35. 35.
    Žalik KR (2008) An efficient k′-means clustering algorithm. Pattern Recogn Lett 29(9):1385–1391CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • David López-Jiménez
    • 1
  • Salvador Bueno
    • 2
  • M. Dolores Gallego
    • 2
  1. 1.University of SevilleSevilleSpain
  2. 2.University of Pablo de OlavideSevilleSpain

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