IDEAS home Printed from
   My bibliography  Save this article

Measuring Factors that Influence the Success of Internet Commerce


  • Gholamreza Torkzadeh

    (Department of MIS, College of Business, University of Nevada, Las Vegas, 4505 Maryland Parkway, Las Vegas, Nevada 89154–6034)

  • Gurpreet Dhillon

    (Department of MIS, College of Business, University of Nevada, Las Vegas, 4505 Maryland Parkway, Las Vegas, Nevada 89154–6034)


Efforts to develop measures of Internet commerce success have been hampered by (1) the rapid development and use of Internet technologies and (2) the lack of conceptual bases necessary to develop success measures. In a recent study, Keeney (1999) proposed two sets of variables labeled as means objectives and fundamental objectives that influence Internet shopping. Means objectives, he argues, help businesses achieve what is important for their customers—fundamental objectives. Based on Keeney's work, this paper describes the development of two instruments that together measure the factors that influence Internet commerce success. One instrument measures the means objectives that influence online purchase (e.g., Internet vendor trust) and the other measures the fundamental objectives that customers perceive to be important for Internet commerce (e.g., Internet product value). In phase one of the instrument development process, we generated 125 items for means and fundamental objectives. Using a sample of 199 responses by individuals with Internet shopping experience, these constructs were examined for reliability and validity. The Phase 1 results suggested a 4-factor, 21-item instrument to measure means objectives and a 4-factor, 17-item instrument to measure fundamental objectives. In Phase 2 of the instrument development process, we gathered a sample of 421 responses to further explore the 2 instruments. With minor modifications, the Phase 2 data support the 2 models. The Phase 2 results suggest a 5-factor, 21-item instrument that measures means objectives in terms of Internet product choice, online payment, Internet vendor trust, shopping travel , and Internet shipping errors . Results also suggest a 4-factor, 16-item instrument that measures fundamental objectives in terms of Internet shopping convenience, Internet ecology, Internet customer relation , and Internet product value . Evidence of reliability and discriminant, construct, and content validity is presented for the hypothesized measurement models. The paper concludes with discussions on the usefulness of these measures and future research ideas.

Suggested Citation

  • Gholamreza Torkzadeh & Gurpreet Dhillon, 2002. "Measuring Factors that Influence the Success of Internet Commerce," Information Systems Research, INFORMS, vol. 13(2), pages 187-204, June.
  • Handle: RePEc:inm:orisre:v:13:y:2002:i:2:p:187-204
    DOI: 10.1287/isre.

    Download full text from publisher

    File URL:
    Download Restriction: no

    File URL:
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item

    References listed on IDEAS

    1. Torkzadeh, G. & Doll, W. J., 1999. "The development of a tool for measuring the perceived impact of information technology on work," Omega, Elsevier, vol. 27(3), pages 327-339, June.
    2. Ralph L. Keeney, 1999. "The Value of Internet Commerce to the Customer," Management Science, INFORMS, vol. 45(4), pages 533-542, April.
    3. Wanda J. Orlikowski & C. Suzanne Iacono, 2001. "Research Commentary: Desperately Seeking the “IT” in IT Research—A Call to Theorizing the IT Artifact," Information Systems Research, INFORMS, vol. 12(2), pages 121-134, June.
    4. Detmar W. Straub & Richard T. Watson, 2001. "Research Commentary: Transformational Issues in Researching IS and Net-Enabled Organizations," Information Systems Research, INFORMS, vol. 12(4), pages 337-345, December.
    5. Leon, Orfelio G., 1999. "Value-Focused Thinking versus Alternative-Focused Thinking: Effects on Generation of Objectives," Organizational Behavior and Human Decision Processes, Elsevier, vol. 80(3), pages 213-227, December.
    6. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    7. Segars, A. H., 1997. "Assessing the unidimensionality of measurement: a paradigm and illustration within the context of information systems research," Omega, Elsevier, vol. 25(1), pages 107-121, February.
    8. Jeffrey P. Krischer, 1976. "Utility Structure of a Medical Decision-Making Problem," Operations Research, INFORMS, vol. 24(5), pages 951-972, October.
    9. V. Sambamurthy & Robert W. Zmud, 2000. "Research Commentary: The Organizing Logic for an Enterprise's IT Activities in the Digital Era—A Prognosis of Practice and a Call for Research," Information Systems Research, INFORMS, vol. 11(2), pages 105-114, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Elbashir, Mohamed Z. & Collier, Philip A. & Davern, Michael J., 2008. "Measuring the effects of business intelligence systems: The relationship between business process and organizational performance," International Journal of Accounting Information Systems, Elsevier, vol. 9(3), pages 135-153.
    2. Jaeki Song & Fatemeh Mariam Zahedi, 2005. "A Theoretical Approach to Web Design in E-Commerce: A Belief Reinforcement Model," Management Science, INFORMS, vol. 51(8), pages 1219-1235, August.
    3. Ronald T. Cenfetelli & Izak Benbasat & Sameh Al-Natour, 2008. "Addressing the What and How of Online Services: Positioning Supporting-Services Functionality and Service Quality for Business-to-Consumer Success," Information Systems Research, INFORMS, vol. 19(2), pages 161-181, June.
    4. Severin Oesterle & Arne Buchwald & Nils Urbach, 2022. "Investigating the co-creation of IT consulting service value: empirical findings of a matched pair analysis," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(2), pages 571-597, June.
    5. Sara Moussawi & Marios Koufaris & Raquel Benbunan-Fich, 2021. "How perceptions of intelligence and anthropomorphism affect adoption of personal intelligent agents," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 343-364, June.
    6. Sarv Devaraj & Ming Fan & Rajiv Kohli, 2002. "Antecedents of B2C Channel Satisfaction and Preference: Validating e-Commerce Metrics," Information Systems Research, INFORMS, vol. 13(3), pages 316-333, September.
    7. Verhagen, Tibert & Meents, Selmar, 2007. "A Framework for Developing Semantic Differentials in IS research: Assessing the Meaning of Electronic Marketplace Quality (EMQ)," Serie Research Memoranda 0016, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    8. Barbara H. Wixom & Peter A. Todd, 2005. "A Theoretical Integration of User Satisfaction and Technology Acceptance," Information Systems Research, INFORMS, vol. 16(1), pages 85-102, March.
    9. Damon E. Campbell & John D. Wells & Joseph S. Valacich, 2013. "Breaking the Ice in B2C Relationships: Understanding Pre-Adoption E-Commerce Attraction," Information Systems Research, INFORMS, vol. 24(2), pages 219-238, June.
    10. One-Ki (Daniel) Lee & Vallabh Sambamurthy & Kai H. Lim & Kwok Kee Wei, 2015. "How Does IT Ambidexterity Impact Organizational Agility?," Information Systems Research, INFORMS, vol. 26(2), pages 398-417, June.
    11. John D'Ambra & Concepción S. Wilson & Shahriar Akter, 2013. "Application of the task-technology fit model to structure and evaluate the adoption of E-books by Academics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(1), pages 48-64, January.
    12. Bradley C. Wheeler, 2002. "NEBIC: A Dynamic Capabilities Theory for Assessing Net-Enablement," Information Systems Research, INFORMS, vol. 13(2), pages 125-146, June.
    13. Vicki McKinney & Kanghyun Yoon & Fatemeh “Mariam” Zahedi, 2002. "The Measurement of Web-Customer Satisfaction: An Expectation and Disconfirmation Approach," Information Systems Research, INFORMS, vol. 13(3), pages 296-315, September.
    14. Jaeki Song & Yong Jin Kim, 2006. "Social influence process in the acceptance of a virtual community service," Information Systems Frontiers, Springer, vol. 8(3), pages 241-252, July.
    15. Naresh K. Malhotra & Sung S. Kim & Ashutosh Patil, 2006. "Common Method Variance in IS Research: A Comparison of Alternative Approaches and a Reanalysis of Past Research," Management Science, INFORMS, vol. 52(12), pages 1865-1883, December.
    16. Akter, Shahriar & Wamba, Samuel Fosso & D’Ambra, John, 2019. "Enabling a transformative service system by modeling quality dynamics," International Journal of Production Economics, Elsevier, vol. 207(C), pages 210-226.
    17. Wallbach, Sören, 2020. "Assimilation and Diffusion of Multi-Sided Platforms in Dynamic B2B Networks: Inhibiting Factors and Their Consequences," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 123277, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    18. Chandra, Shalini & Shirish, Anuragini & Srivastava, Shirish C., 2020. "Theorizing technological spatial intrusion for ICT enabled employee innovation: The mediating role of perceived usefulness," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    19. Sun, Jonghak & Teng, James T.C., 2017. "The construct of information systems use benefits: Theoretical explication of its underlying dimensions and the development of a measurement scale," International Journal of Information Management, Elsevier, vol. 37(5), pages 400-416.
    20. Sven Dittes & Stefan Smolnik, 2019. "Towards a digital work environment: the influence of collaboration and networking on employee performance within an enterprise social media platform," Journal of Business Economics, Springer, vol. 89(8), pages 1215-1243, December.


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orisre:v:13:y:2002:i:2:p:187-204. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.