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The moderating roles of risk and efficiency on the relationship between logistics performance and customer loyalty in e-commerce

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  • Ramanathan, Ramakrishnan

Abstract

Using data from online customer ratings, we explore how the relationships between logistics performance and customer loyalty are affected by risk characteristics of products and efficiencies of the websites. Risk is defined in terms of price and ambiguity of products. Efficiency is interpreted as the ability of the websites to achieve good ratings in terms of operational factors (such as satisfaction of customers with product specifications, refunds/returns, prices, management accessibility, etc.) and also achieve good ratings in terms of customer loyalty. Our results show that efficiency, but not risk, is a significant moderator of the impact of logistics performance on customer loyalty.

Suggested Citation

  • Ramanathan, Ramakrishnan, 2010. "The moderating roles of risk and efficiency on the relationship between logistics performance and customer loyalty in e-commerce," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 950-962, November.
  • Handle: RePEc:eee:transe:v:46:y:2010:i:6:p:950-962
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    Citations

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    Cited by:

    1. Mojgan Bahrami Samani Author_Email: Samani_518@yahoo.com.sg & Ali Attafar & Naser Khani Khouzani, 2011. "A Conceptual Model For Iran’S Car Industry Customers’ Loyalty," 2nd International Conference on Business and Economic Research (2nd ICBER 2011) Proceeding 2011-184, Conference Master Resources.
    2. repec:cmj:seapas:y:2018:i:16:p:37-46 is not listed on IDEAS
    3. Piening, J. & Ehrmann, T. & Meiseberg, B., 2013. "Competing risks for train tickets – An empirical investigation of customer behavior and performance in the railway industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 51(C), pages 1-16.
    4. Ramanathan, Ramakrishnan & Ramanathan, Usha & Zhang, Yubo, 2016. "Linking operations, marketing and environmental capabilities and diversification to hotel performance: A data envelopment analysis approach," International Journal of Production Economics, Elsevier, vol. 176(C), pages 111-122.
    5. Shenle Pan & Vaggelis Giannikas & Yufei Han & Etta Grover-Silva & Bin Qiao, 2017. "Using Customer-related Data to Enhance E-grocery Home Delivery," Post-Print hal-01482901, HAL.
    6. repec:gam:jsusta:v:8:y:2016:i:4:p:341:d:67748 is not listed on IDEAS
    7. YU, Jie & Subramanian, Nachiappan & Ning, Kun & Edwards, David, 2015. "Product delivery service provider selection and customer satisfaction in the era of internet of things: A Chinese e-retailers’ perspective," International Journal of Production Economics, Elsevier, vol. 159(C), pages 104-116.
    8. Vlachos, Ilias & Lin, Zhibin, 2014. "Drivers of airline loyalty: Evidence from the business travelers in China," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 1-17.
    9. Xu, Su Xiu & Cheng, Meng & Huang, George Q., 2015. "Efficient intermodal transportation auctions for B2B e-commerce logistics with transaction costs," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 322-337.
    10. Yandong He & Xu Wang & Yun Lin & Fuli Zhou, 2016. "Optimal Partner Combination for Joint Distribution Alliance using Integrated Fuzzy EW-AHP and TOPSIS for Online Shopping," Sustainability, MDPI, Open Access Journal, vol. 8(4), pages 1-18, April.

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