IDEAS home Printed from https://ideas.repec.org/a/rom/merase/v5y2020i1p33-50.html
   My bibliography  Save this article

Online Purchasing and its Determinants: An Experimental Approach

Author

Listed:
  • Zafer AKIN

    (School of Business Administration, American University in Dubai)

Abstract

With the rapid and worldwide emergence of electronic commerce in terms of both number of users and volume, the importance of an in-depth understanding of consumers’ attitudes toward online purchasing has been increasing. There is a broad literature on this topic mainly based on Technology Acceptance Model (TAM) that is extended by including other factors such as trust and risk. This study brings a new angle to the existing literature by measuring risk factor in a laboratory experiment by employing an improved version of a widely used method in experimental economics. Risk preferences are measured for 64 university students who then answer a questionnaire about online purchasing. We propose a comprehensive model based on TAM and employ partial least squares approach to analyze the data. We find that experimentally elicited risk preference measure and variables of hedonic aspect of TAM have significant effects while trust, other risk measures and variables of utilitarian aspect of TAM have no significant effect on online shopping behavior. We finally discuss the implications and limitations of our study and provide some future study suggestions.

Suggested Citation

  • Zafer AKIN, 2020. "Online Purchasing and its Determinants: An Experimental Approach," Management and Economics Review, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 5(1), pages 33-50, June.
    • Handle: RePEc:rom:merase:v:5:y:2020:i:1:p:33-50
    as

    Download full text from publisher

    File URL: https://mer.ase.ro/files/2020-1/5-4.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Noussair, Charles & Robin, Stephane & Ruffieux, Bernard, 2004. "Revealing consumers' willingness-to-pay: A comparison of the BDM mechanism and the Vickrey auction," Journal of Economic Psychology, Elsevier, vol. 25(6), pages 725-741, December.
    2. Lisa Anderson & Jennifer Mellor, 2009. "Are risk preferences stable? Comparing an experimental measure with a validated survey-based measure," Journal of Risk and Uncertainty, Springer, vol. 39(2), pages 137-160, October.
    3. Ha, Sejin & Stoel, Leslie, 2009. "Consumer e-shopping acceptance: Antecedents in a technology acceptance model," Journal of Business Research, Elsevier, vol. 62(5), pages 565-571, May.
    4. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde & Jürgen Schupp & Gert G. Wagner, 2011. "Individual Risk Attitudes: Measurement, Determinants, And Behavioral Consequences," Journal of the European Economic Association, European Economic Association, vol. 9(3), pages 522-550, June.
    5. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    6. Kruse, Jamie Brown & Thompson, Mark A., 2003. "Valuing low probability risk: survey and experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 50(4), pages 495-505, April.
    7. Chen, Lei-Da & Tan, Justin, 2004. "Technology Adaptation in E-commerce:: Key Determinants of Virtual Stores Acceptance," European Management Journal, Elsevier, vol. 22(1), pages 74-86, February.
    8. Cummings, Ronald G. & Martinez-Vazquez, Jorge & McKee, Michael & Torgler, Benno, 2009. "Tax morale affects tax compliance: Evidence from surveys and an artefactual field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 70(3), pages 447-457, June.
    9. Lönnqvist, Jan-Erik & Verkasalo, Markku & Walkowitz, Gari & Wichardt, Philipp C., 2015. "Measuring individual risk attitudes in the lab: Task or ask? An empirical comparison," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 254-266.
    10. Benhabib, Jess & Bisin, Alberto & Schotter, Andrew, 2010. "Present-bias, quasi-hyperbolic discounting, and fixed costs," Games and Economic Behavior, Elsevier, vol. 69(2), pages 205-223, July.
    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. Zafer Akýn & Ý. Erdem Seçilmiþ, 2015. "Risk Behavior, Risk Perception and Online Shopping: An Experimental Approach," IPEK Working Papers 1507, Ipek University, Department of Economics, revised Sep 2015.
    2. Ranganathan, Kavitha & Lejarraga, Tomás, 2021. "Elicitation of risk preferences through satisficing," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    3. Tamás Csermely & Alexander Rabas, 2016. "How to reveal people’s preferences: Comparing time consistency and predictive power of multiple price list risk elicitation methods," Journal of Risk and Uncertainty, Springer, vol. 53(2), pages 107-136, December.
    4. Pan He & Marcella Veronesi & Stefanie Engel, 2016. "Consistency of Risk Preference Measures and the Role of Ambiguity: An Artefactual Field Experiment from China," Working Papers 03/2016, University of Verona, Department of Economics.
    5. Stefan Zeisberger & Dennis Vrecko & Thomas Langer, 2012. "Measuring the time stability of Prospect Theory preferences," Theory and Decision, Springer, vol. 72(3), pages 359-386, March.
    6. Islam, Asad & Smyth, Russell & Tan, HongQi Alexis & Wang, Liang C., 2019. "Survey measures versus incentivized measures of risk preferences: Evidence from sex workers' risky sexual transactions," Social Science & Medicine, Elsevier, vol. 238(C), pages 1-1.
    7. Sauter, Philipp A. & Hermann, Daniel & Mußhoff, Oliver, 2018. "Are foresters really risk-averse? A multi-method analysis and a cross-occupational comparison," Forest Policy and Economics, Elsevier, vol. 95(C), pages 37-45.
    8. Goytom Abraha Kahsay & Daniel Osberghaus, 2018. "Storm Damage and Risk Preferences: Panel Evidence from Germany," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(1), pages 301-318, September.
    9. Hermansson, Cecilia, 2018. "Can self-assessed financial risk measures explain and predict bank customers’ objective financial risk?," Journal of Economic Behavior & Organization, Elsevier, vol. 148(C), pages 226-240.
    10. Jan-Erik Loennqvist & Markku Verkasalo & Gari Walkowitz & Philipp C. Wichardt, 2011. "Measuring Individual Risk Attitudes in the Lab: Task or Ask? An Empirical Comparison," Cologne Graduate School Working Paper Series 02-03, Cologne Graduate School in Management, Economics and Social Sciences.
    11. Dasgupta, Utteeyo & Mani, Subha & Sharma, Smriti & Singhal, Saurabh, 2016. "Eliciting Risk Preferences: Firefighting in the Field," IZA Discussion Papers 9765, Institute of Labor Economics (IZA).
    12. Giuseppe Attanasi & Nikolaos Georgantzís & Valentina Rotondi & Daria Vigani, 2018. "Lottery- and survey-based risk attitudes linked through a multichoice elicitation task," Theory and Decision, Springer, vol. 84(3), pages 341-372, May.
    13. Holzmeister, Felix & Stefan, Matthias, 2019. "The Risk Elicitation Puzzle Revisited: Across-Methods (In)consistency?," OSF Preprints pj9u2, Center for Open Science.
    14. Lönnqvist, Jan-Erik & Verkasalo, Markku & Walkowitz, Gari & Wichardt, Philipp C., 2015. "Measuring individual risk attitudes in the lab: Task or ask? An empirical comparison," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 254-266.
    15. Paolo Crosetto & Antonio Filippin & Janna Heider, 2015. "A Study of Outcome Reporting Bias Using Gender Differences in Risk Attitudes," CESifo Economic Studies, CESifo Group, vol. 61(1), pages 239-262.
    16. Gary Charness & Thomas Garcia & Theo Offerman & Marie Claire Villeval, 2020. "Do measures of risk attitude in the laboratory predict behavior under risk in and outside of the laboratory?," Journal of Risk and Uncertainty, Springer, vol. 60(2), pages 99-123, April.
    17. Sepahvand, Mohammad H & Shahbazian, Roujman & Bali Swain, Ranjula, 2018. "Does revolution change risk attitudes? Evidence from Burkina Faso," Working Paper Series 2019:2, Uppsala University, Department of Economics.
    18. Mathieu Lefebvre & Pierre Pestieau & Arno Riedl & Marie-Claire Villeval, 2011. "Tax Evasion, Welfare Fraud, and the « Broken Windows » Effect : An Experiment in Belgium, France and the Netherlands," Working Papers 1116, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    19. Murong Yang & Laurence S. J. Roope & James Buchanan & Arthur E. Attema & Philip M. Clarke & A. Sarah Walker & Sarah Wordsworth, 2022. "Eliciting risk preferences that predict risky health behavior: A comparison of two approaches," Health Economics, John Wiley & Sons, Ltd., vol. 31(5), pages 836-858, May.
    20. Galizzi, Matteo M. & Miraldo, Marisa & Stavropoulou, Charitini & van der Pol, Marjon, 2016. "Doctor–patient differences in risk and time preferences: A field experiment," Journal of Health Economics, Elsevier, vol. 50(C), pages 171-182.

    More about this item

    Keywords

    experiment; online purchasing; questionnaire; risk preference elicitation; Technology Acceptance Model (TAM); trust.;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce

    Statistics

    Access and download statistics

    Corrections

    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:rom:merase:v:5:y:2020:i:1:p:33-50. 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: Ciocoiu Nadia Carmen (email available below). General contact details of provider: https://edirc.repec.org/data/mnasero.html .

    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.