IDEAS home Printed from https://ideas.repec.org/a/rbs/ijbrss/v10y2021i1p189-204.html
   My bibliography  Save this article

Examining the relationship between the level of logistics service quality, relationship quality and repurchase intention in e-retail sector of Pakistan

Author

Listed:
  • Muhammad Saqib Khan

    (School of Management, Huazhong University of Science and Technology 1037, Luoyu Road, Wuhan, 430074, P.R.China)

  • Haijun Wang

    (School of Management, Huazhong University of Science and Technology 1037, Luoyu Road, Wuhan, 430074, P.R.China)

  • Qing Wang

    (School of Economics and Management, Huazhong Agricultural University, Wuhan 430072, P.R.China)

  • Waseem Khan

    (Department of Management Sciences, HITEC University Taxila, Pakistan)

  • Tahira Javed

    (School of Management, Huazhong University of Science and Technology 1037, Luoyu Road, Wuhan, 430074, P.R.China)

Abstract

This study examined the relationship between the level of logistics service quality, relationship quality, and repurchase intention in the e-retail sector of Pakistan. Logistics service quality LSQ was integrated into the step-by-step purchasing process including pre-purchase, purchase, and post-purchase factors. This research is unique from existing research work as it validated a holistic model by examining the role of customer’s perception of LSQ in strengthening their RQ and subsequent purchase intentions in the e-retail logistics sector of Pakistan and draw important suggestions to enhance the competitiveness of logistics services of domestic e-retail logistic firms. A survey strategy using self-administered questionnaires was employed from customers of departmental stores, large discount stores, shopping malls & retail outlets. A total of n=241 based on a cluster of conventional retail consumers across Pakistan was drawn. The study results provide a quality framework for the management of logistics service providers working in Pakistan's e-retail industry to evaluate the strengths and limitations of their service provision and then identify areas where improvements might be needed. Key Words: Logistics service quality, Relationship Quality, Repurchase Intention, E-retail sector

Suggested Citation

  • Muhammad Saqib Khan & Haijun Wang & Qing Wang & Waseem Khan & Tahira Javed, 2021. "Examining the relationship between the level of logistics service quality, relationship quality and repurchase intention in e-retail sector of Pakistan," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(1), pages 189-204, January.
    • Handle: RePEc:rbs:ijbrss:v:10:y:2021:i:1:p:189-204
    DOI: 10.20525/ijrbs.v10i1.1028
    as

    Download full text from publisher

    File URL: https://www.ssbfnet.com/ojs/index.php/ijrbs/article/view/1028/787
    Download Restriction: no
    File URL: https://doi.org/10.20525/ijrbs.v10i1.1028
    Download Restriction: no
    File URL: https://libkey.io/10.20525/ijrbs.v10i1.1028?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
    ---><---

    References listed on IDEAS

    as
    1. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
    2. Giao, Ha Nam Khanh, 2019. "The Impact of Perceived Brand Globalness on Consumers Purchase Intention and the Moderating Role of Consumer Ethnocentrism An Evidence from Vietnam," OSF Preprints wygrf, Center for Open Science.
    3. Oghazi, Pejvak & Karlsson, Stefan & Hellström, Daniel & Hjort, Klas, 2018. "Online purchase return policy leniency and purchase decision: Mediating role of consumer trust," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 190-200.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Karolus Karni Lando & Achmad Sudiro & Wahdiyat Moko & Nur Khusniyah Indrawati, 2024. "The Effect of Service Quality on Recertification. Mediated by Customer Satisfaction and Relationship Commitment," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 6, pages 160-179.
    2. Haq, Mahin & Moazzam, Muhammad & Khan, Abdul Salam & Ahmed, Waqas, 2023. "The impact of reverse logistics process coordination on third party relationship quality: A moderated mediation model for multichannel retailers in the fashion industry," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    3. Mujianto Mujianto & Hartoyo Hartoyo & Rita Nurmalina & Eva Z. Yusuf, 2023. "The Unraveling Loyalty Model of Traditional Retail to Suppliers for Business Sustainability in the Digital Transformation Era: Insight from MSMEs in Indonesia," Sustainability, MDPI, vol. 15(3), pages 1-31, February.

    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. Majumdar, Adrija & Bose, Indranil, 2019. "Do tweets create value? A multi-period analysis of Twitter use and content of tweets for manufacturing firms," International Journal of Production Economics, Elsevier, vol. 216(C), pages 1-11.
    2. Omar, Yamila M. & Minoufekr, Meysam & Plapper, Peter, 2019. "Business analytics in manufacturing: Current trends, challenges and pathway to market leadership," Operations Research Perspectives, Elsevier, vol. 6(C).
    3. Hans-Joachim Schramm & Carolin Nicole Czaja & Michael Dittrich & Matthias Mentschel, 2019. "Current Advancements of and Future Developments for Fourth Party Logistics in a Digital Future," Logistics, MDPI, vol. 3(1), pages 1-17, February.
    4. Govindan, Kannan & Gholizadeh, Hadi, 2021. "Robust network design for sustainable-resilient reverse logistics network using big data: A case study of end-of-life vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    5. Jean-Sébastien Lacam & David Salvetat, 2021. "Big data and Smart data: two interdependent and synergistic digital policies within a virtuous data exploitation loop," Post-Print hal-03434863, HAL.
    6. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Papadopoulos, Thanos & Luo, Zongwei & Wamba, Samuel Fosso & Roubaud, David, 2019. "Can big data and predictive analytics improve social and environmental sustainability?," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 534-545.
    7. Wang, Hui & Gong, Qiguo & Wang, Shouyang, 2017. "Information processing structures and decision making delays in MRP and JIT," International Journal of Production Economics, Elsevier, vol. 188(C), pages 41-49.
    8. Hazen, Benjamin T. & Weigel, Fred K. & Ezell, Jeremy D. & Boehmke, Bradley C. & Bradley, Randy V., 2017. "Toward understanding outcomes associated with data quality improvement," International Journal of Production Economics, Elsevier, vol. 193(C), pages 737-747.
    9. Leonardo de Assis Santos & Leonardo Marques, 2022. "Big data analytics for supply chain risk management: research opportunities at process crossroads," Post-Print hal-03766121, HAL.
    10. Bag, Surajit & Gupta, Shivam & Kumar, Sameer, 2021. "Industry 4.0 adoption and 10R advance manufacturing capabilities for sustainable development," International Journal of Production Economics, Elsevier, vol. 231(C).
    11. Daniel A. Griffith & Bradley Boehmke & Randy V. Bradley & Benjamin T. Hazen & Alan W. Johnson, 2019. "Embedded analytics: improving decision support for humanitarian logistics operations," Annals of Operations Research, Springer, vol. 283(1), pages 247-265, December.
    12. Xue, Fujing & Li, Xiaoyu & Zhang, Ting & Hu, Nan, 2021. "Stock market reactions to the COVID-19 pandemic: The moderating role of corporate big data strategies based on Word2Vec," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    13. Ewa Stawiarska & Danuta Szwajca & Mirosław Matusek & Radosław Wolniak, 2021. "Diagnosis of the Maturity Level of Implementing Industry 4.0 Solutions in Selected Functional Areas of Management of Automotive Companies in Poland," Sustainability, MDPI, vol. 13(9), pages 1-38, April.
    14. Ginder, Whitney & Byun, Sang-Eun, 2022. "To trust or not to trust? The interplay between labor-related CSR claim type and prior CSR reputation of apparel retailers," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    15. Arunachalam, Deepak & Kumar, Niraj & Kawalek, John Paul, 2018. "Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 416-436.
    16. Muhammad Noman Shafique & Ammar Rashid & Sook Fern Yeo & Umar Adeel, 2023. "Transforming Supply Chains: Powering Circular Economy with Analytics, Integration and Flexibility Using Dual Theory and Deep Learning with PLS-SEM-ANN Analysis," Sustainability, MDPI, vol. 15(15), pages 1-23, August.
    17. Shuai Zhang & Kai Huang & Yufei Yuan, 2021. "Spare Parts Inventory Management: A Literature Review," Sustainability, MDPI, vol. 13(5), pages 1-23, February.
    18. Badr Bentalha, 2020. "Big-Data and Service Supply chain management: Challenges and opportunities [Big-Data et Service Supply chain management: Challenges et opportunités]," Post-Print hal-02680861, HAL.
    19. Maryam Philsoophian & Peyman Akhavan & Morteza Abbasi, 2021. "Strategic Alliance for Resilience in Supply Chain: A Bibliometric Analysis," Sustainability, MDPI, vol. 13(22), pages 1-25, November.
    20. Papanagnou, Christos & Seiler, Andreas & Spanaki, Konstantina & Papadopoulos, Thanos & Bourlakis, Michael, 2022. "Data-driven digital transformation for emergency situations: The case of the UK retail sector," International Journal of Production Economics, Elsevier, vol. 250(C).

    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:rbs:ijbrss:v:10:y:2021:i:1:p:189-204. 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: Umit Hacioglu (email available below). General contact details of provider: https://edirc.repec.org/data/ssbffea.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.