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. 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).
    2. 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.
    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. 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.
    2. Khouja, Moutaz & Hammami, Ramzi, 2023. "Optimizing price, order quantity, and return policy in the presence of consumer opportunistic behavior for online retailers," European Journal of Operational Research, Elsevier, vol. 309(2), pages 683-703.
    3. Fu, Shuke & Ge, Yingchen & Hao, Yu & Peng, Jiachao & Tian, Jiali, 2024. "Energy supply chain efficiency in the digital era: Evidence from China's listed companies," Energy Economics, Elsevier, vol. 134(C).
    4. Vendrell-Herrero, Ferran & Bustinza, Oscar F. & Opazo-Basaez, Marco, 2021. "Information technologies and product-service innovation: The moderating role of service R&D team structure," Journal of Business Research, Elsevier, vol. 128(C), pages 673-687.
    5. Anhang Chen & Huiqin Zhang & Yuxiang Zhang & Junwei Zhao, 2024. "Manufacturers’ digital transformation under carbon cap-and-trade policy: investment strategy and environmental impact," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    6. Videsh Desingh & Baskaran R, 2022. "Internet of Things adoption barriers in the Indian healthcare supply chain: An ISM‐fuzzy MICMAC approach," International Journal of Health Planning and Management, Wiley Blackwell, vol. 37(1), pages 318-351, January.
    7. Li, Ying & Dai, Jing & Cui, Li, 2020. "The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model," International Journal of Production Economics, Elsevier, vol. 229(C).
    8. Al-Adwan, Ahmad Samed & Al-Debei, Mutaz M. & Dwivedi, Yogesh K., 2022. "E-commerce in high uncertainty avoidance cultures: The driving forces of repurchase and word-of-mouth intentions," Technology in Society, Elsevier, vol. 71(C).
    9. Mohammadreza Akbari & John L. Hopkins, 2022. "Digital technologies as enablers of supply chain sustainability in an emerging economy," Operations Management Research, Springer, vol. 15(3), pages 689-710, December.
    10. Kosiba, John Paul & Acheampong, Audrey & Adeola, Ogechi & Hinson, Robert E., 2020. "The moderating role of demographic variables on customer expectations in airport retail patronage intentions of travellers," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    11. Bin Shen & Hau-Ling Chan, 2017. "Forecast Information Sharing for Managing Supply Chains in the Big Data Era: Recent Development and Future Research," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(01), pages 1-26, February.
    12. Junming Liu & Weiwei Chen & Jingyuan Yang & Hui Xiong & Can Chen, 2022. "Iterative Prediction-and-Optimization for E-Logistics Distribution Network Design," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 769-789, March.
    13. Meriem Riad & Mohamed Naimi & Chafik Okar, 2024. "Enhancing Supply Chain Resilience Through Artificial Intelligence: Developing a Comprehensive Conceptual Framework for AI Implementation and Supply Chain Optimization," Logistics, MDPI, vol. 8(4), pages 1-26, November.
    14. Chen, Jing & Yu, Bo & Chen, Bintong & Liu, Zhuojun, 2023. "Lenient vs. stringent returns policies in the presence of fraudulent returns: The role of customers’ fairness perceptions," Omega, Elsevier, vol. 117(C).
    15. Yun Liu & Zhe Yan & Yijie Cheng & Xuanting Ye, 2018. "Exploring the Technological Collaboration Characteristics of the Global Integrated Circuit Manufacturing Industry," Sustainability, MDPI, vol. 10(1), pages 1-23, January.
    16. Francesco Facchini & Joanna Oleśków-Szłapka & Luigi Ranieri & Andrea Urbinati, 2019. "A Maturity Model for Logistics 4.0: An Empirical Analysis and a Roadmap for Future Research," Sustainability, MDPI, vol. 12(1), pages 1-18, December.
    17. Prikshat, Verma & Islam, Mohammad & Patel, Parth & Malik, Ashish & Budhwar, Pawan & Gupta, Suraksha, 2023. "AI-Augmented HRM: Literature review and a proposed multilevel framework for future research," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    18. Zhan, Yuanzhu & Tan, Kim Hua, 2020. "An analytic infrastructure for harvesting big data to enhance supply chain performance," European Journal of Operational Research, Elsevier, vol. 281(3), pages 559-574.
    19. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    20. Vineet Kaushik & Ashwani Kumar & Himanshu Gupta & Gaurav Dixit, 2022. "Modelling and prioritizing the factors for online apparel return using BWM approach," Electronic Commerce Research, Springer, vol. 22(3), pages 843-873, September.

    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.