IDEAS home Printed from https://ideas.repec.org/a/taf/oabmxx/v4y2017i1p1405509.html
   My bibliography  Save this article

Artemis time: A mathematical model to calculate maximum acceptable waiting time in B2C e-commerce

Author

Listed:
  • Ehsan Mousavi Khaneghah
  • Nosratollah Shadnoush
  • Amin Salem

Abstract

One of the main challenges in e-commerce is how to calculate the maximum acceptable time for response to the customer from the business firms. This case has a direct impact on many business concepts such as customer loyalty, satisfaction, and trust. In this paper, a mathematical model is presented to calculate the maximum acceptable time. In this regard, based on a set of functions, while investigating factors affecting the business from customer’s perspective, this mathematical model has the ability to use in any kind of B2C-based e-commerce system due to the consideration of the partial elongation set between elements that affect time transparency. The business using this function and managing the elements that affect this function is able to manage its operations in a way that conducts business activities in accordance with client time estimates. This will increase satisfaction and customer’ trust in the business.

Suggested Citation

  • Ehsan Mousavi Khaneghah & Nosratollah Shadnoush & Amin Salem, 2017. "Artemis time: A mathematical model to calculate maximum acceptable waiting time in B2C e-commerce," Cogent Business & Management, Taylor & Francis Journals, vol. 4(1), pages 1405509-140, January.
  • Handle: RePEc:taf:oabmxx:v:4:y:2017:i:1:p:1405509
    DOI: 10.1080/23311975.2017.1405509
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23311975.2017.1405509
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/23311975.2017.1405509?utm_source=ideas
    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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Giampaolo Viglia, 2014. "Pricing, Online Marketing Behavior, and Analytics," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-137-41326-0.
    2. Hackl, Franz & Kummer, Michael E. & Winter-Ebmer, Rudolf & Zulehner, Christine, 2014. "Market structure and market performance in E-commerce," European Economic Review, Elsevier, vol. 68(C), pages 199-218.
    3. Nicolas Poggi & David Carrera & Ricard Gavaldà & Eduard Ayguadé & Jordi Torres, 2014. "A methodology for the evaluation of high response time on E-commerce users and sales," Information Systems Frontiers, Springer, vol. 16(5), pages 867-885, November.
    4. Dickinger, Astrid & Stangl, Brigitte, 2013. "Website performance and behavioral consequences: A formative measurement approach," Journal of Business Research, Elsevier, vol. 66(6), pages 771-777.
    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. Saurabh Pratap & Sunil Kumar Jauhar & Yash Daultani & Sanjoy Kumar Paul, 2023. "Benchmarking sustainable E‐commerce enterprises based on evolving customer expectations amidst COVID‐19 pandemic," Business Strategy and the Environment, Wiley Blackwell, vol. 32(1), pages 736-752, January.
    2. Jean-Éric Pelet & Basma Taieb, 2022. "Context-aware optimization of mobile commerce website interfaces from the consumers’ perspective: Effects on behavioral intentions [Optimisation contextuelle des interfaces de sites Web de commerce," Post-Print hal-04138288, HAL.
    3. Pérez-Amaral, Teodosio & Valarezo, Angel & López, Rafael & Garín-Muñoz, Teresa & Herguera, Iñigo, 2020. "E-commerce by individuals in Spain using panel data 2008–2016," Telecommunications Policy, Elsevier, vol. 44(4).
    4. Karol Król & Dariusz Zdonek, 2020. "Aggregated Indices in Website Quality Assessment," Future Internet, MDPI, vol. 12(4), pages 1-23, April.
    5. Al-Qeisi, Kholoud & Dennis, Charles & Alamanos, Eleftherios & Jayawardhena, Chanaka, 2014. "Website design quality and usage behavior: Unified Theory of Acceptance and Use of Technology," Journal of Business Research, Elsevier, vol. 67(11), pages 2282-2290.
    6. Le Thi Hong Minh, 2021. "Factors influence ease of use on Fintech adoption: Mediating by the role of attachment anxiety under Covid-19 pandemic," HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ECONOMICS AND BUSINESS ADMINISTRATION, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, vol. 11(2), pages 137-155.
    7. Díaz, Estrella & Martín-Consuegra, David, 2016. "A latent class segmentation analysis of airlines based on website evaluation," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 20-40.
    8. Bartikowski, Boris & Richard, Marie-Odile & Gierl, Heribert, 2023. "Fit or misfit of culture in marketing communication? Development of the culture-ladenness fit index," Journal of Business Research, Elsevier, vol. 167(C).
    9. Franz Hackl & Michael Hölzl‐Leitner & Rudolf Winter‐Ebmer & Christine Zulehner, 2021. "Successful retailer strategies in price comparison platforms," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(5), pages 1284-1305, July.
    10. Tontini, Gerson, 2016. "Identifying opportunities for improvement in online shopping sites," Journal of Retailing and Consumer Services, Elsevier, vol. 31(C), pages 228-238.
    11. Aljukhadar, Muhammad & Senecal, Sylvain, 2016. "The user multifaceted expertise: Divergent effects of the website versus e-commerce expertise," International Journal of Information Management, Elsevier, vol. 36(3), pages 322-332.
    12. Fleckenstein, David & Klein, Robert & Steinhardt, Claudius, 2023. "Recent advances in integrating demand management and vehicle routing: A methodological review," European Journal of Operational Research, Elsevier, vol. 306(2), pages 499-518.
    13. Loureiro, Sandra M.C. & Cavallero, Luisa & Miranda, Francisco Javier, 2018. "Fashion brands on retail websites: Customer performance expectancy and e-word-of-mouth," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 131-141.
    14. Debarun Chakraborty, 2019. "Customer Satisfaction Towards Food Service Apps in Indian Metro Cities," FIIB Business Review, , vol. 8(3), pages 245-255, September.
    15. Pérez-Amaral, Teodosio & Valarezo, Angel & López, Rafael & Garín-Muñoz, Teresa & Herguera, Iñigo, 2019. "E-commerce and digital divide in Spain using individual panel data 2008-2016," 30th European Regional ITS Conference, Helsinki 2019 205206, International Telecommunications Society (ITS).
    16. Tonghui Lian & Caihua Yu & Zhongqun Wang & Zhiping Hou, 2017. "The evaluation study on tourism websites: from the perspective of triangular intuitionistic fuzzy multiple attribute group decision making," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(16), pages 2877-2889, December.
    17. Duch-Brown, Néstor & Grzybowski, Lukasz & Romahn, André & Verboven, Frank, 2017. "The impact of online sales on consumers and firms. Evidence from consumer electronics," International Journal of Industrial Organization, Elsevier, vol. 52(C), pages 30-62.
    18. Rizov, Marian & Vecchi, Michela & Domenech, Josep, 2022. "Going online: Forecasting the impact of websites on productivity and market structure," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    19. Estrella Díaz & David Martín-Consuegra & Hooman Estelami, 2016. "A persuasive-based latent class segmentation analysis of luxury brand websites," Electronic Commerce Research, Springer, vol. 16(3), pages 401-424, September.
    20. Fernández-Bonilla, Fernando & Gijón, Covadonga & De la Vega, Bárbara, 2022. "E-commerce in Spain: Determining factors and the importance of the e-trust," Telecommunications Policy, Elsevier, vol. 46(1).

    More about this item

    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:taf:oabmxx:v:4:y:2017:i:1:p:1405509. 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 Longhurst (email available below). General contact details of provider: http://cogentoa.tandfonline.com/OABM20 .

    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.