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Using beta regression to explore the relationship between service attributes and likelihood of customer retention for the container shipping industry

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  • Chen, Kee Kuo
  • Chiu, Rong-Her
  • Chang, Ching-Ter

Abstract

This study segments container shipping market by analyzing the relationships between service attributes and likelihood of customer retention for the container shipping industry and find: (1) service quality, as a partitioned variable, separates the overall model into five sub-models having different functional relationships, (2) the attributes of price and discount, personal selling and customer relationship have significant impact on likelihood of customer retention, (3) satisfactory price and discounts are a necessary attribute to support the likelihood of customer retention, and (4) satisfactory personal selling is the most important attribute for increasing the likelihood of customer retention.

Suggested Citation

  • Chen, Kee Kuo & Chiu, Rong-Her & Chang, Ching-Ter, 2017. "Using beta regression to explore the relationship between service attributes and likelihood of customer retention for the container shipping industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 1-16.
    • Handle: RePEc:eee:transe:v:104:y:2017:i:c:p:1-16
    DOI: 10.1016/j.tre.2017.04.015
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    1. Paul Klemperer, 1995. "Competition when Consumers have Switching Costs: An Overview with Applications to Industrial Organization, Macroeconomics, and International Trade," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 62(4), pages 515-539.
    2. Grün, Bettina & Kosmidis, Ioannis & Zeileis, Achim, 2012. "Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i11).
    3. Silvia Ferrari & Francisco Cribari-Neto, 2004. "Beta Regression for Modelling Rates and Proportions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 799-815.
    4. Lu, Chin-Shan, 2003. "The impact of carrier service attributes on shipper-carrier partnering relationships: a shipper's perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(5), pages 399-415, September.
    5. Bucklin, Randolph E. & Sismeiro, Catarina, 2009. "Click Here for Internet Insight: Advances in Clickstream Data Analysis in Marketing," Journal of Interactive Marketing, Elsevier, vol. 23(1), pages 35-48.
    6. Sunil Gupta & Valarie Zeithaml, 2006. "Customer Metrics and Their Impact on Financial Performance," Marketing Science, INFORMS, vol. 25(6), pages 718-739, 11-12.
    7. Pei-Yu (Sharon) Chen & Lorin M. Hitt, 2002. "Measuring Switching Costs and the Determinants of Customer Retention in Internet-Enabled Businesses: A Study of the Online Brokerage Industry," Information Systems Research, INFORMS, vol. 13(3), pages 255-274, September.
    8. Sen, Sankar & Gurhan-Canli, Zeynep & Morwitz, Vicki, 2001. "Withholding Consumption: A Social Dilemma Perspective on Consumer Boycotts," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(3), pages 399-417, December.
    9. Cribari-Neto, Francisco & Zeileis, Achim, 2010. "Beta Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 34(i02).
    10. Lai, Kee-hung & Ngai, E. W. T. & Cheng, T. C. E., 2002. "Measures for evaluating supply chain performance in transport logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 38(6), pages 439-456, November.
    11. Jones, Michael A. & Mothersbaugh, David L. & Beatty, Sharon E., 2002. "Why customers stay: measuring the underlying dimensions of services switching costs and managing their differential strategic outcomes," Journal of Business Research, Elsevier, vol. 55(6), pages 441-450, June.
    12. Slack, Brian & Gouvernal, Elisabeth, 2011. "Container freight rates and the role of surcharges," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1482-1489.
    13. Chen, Kee-Kuo & Ho, Hui-Ping & Chang, Ching-Ter, 2015. "Estimating attributes importance for container shipping industry by closing the listening gap with maximum convergent validity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 145-163.
    14. Song, Dong-Ping & Li, Dong & Drake, Paul, 2015. "Multi-objective optimization for planning liner shipping service with uncertain port times," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 84(C), pages 1-22.
    15. Simas, Alexandre B. & Barreto-Souza, Wagner & Rocha, Andréa V., 2010. "Improved estimators for a general class of beta regression models," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 348-366, February.
    16. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
    17. Lu, Chin-Shan, 2000. "Logistics services in Taiwanese maritime firms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 36(2), pages 79-96, June.
    18. Chen, Kee-Kuo & Chang, Ching-Ter & Lai, Cheng-Sheng, 2009. "Service quality gaps of business customers in the shipping industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(1), pages 222-237, January.
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    2. Vural, Ceren Altuntaş & Göçer, Aysu & Halldórsson, Árni, 2019. "Value co-creation in maritime logistics networks: A service triad perspective," Transport Policy, Elsevier, vol. 84(C), pages 27-39.
    3. Ana C Guedes & Francisco Cribari-Neto & Patrícia L Espinheira, 2021. "Bartlett-corrected tests for varying precision beta regressions with application to environmental biometrics," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-26, June.
    4. Yuen, Kum Fai & Wang, Xueqin & Wong, Yiik Diew & Zhou, Qingji, 2018. "The effect of sustainable shipping practices on shippers’ loyalty: The mediating role of perceived value, trust and transaction cost," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 123-135.
    5. Balci, Gökcay, 2021. "Digitalization in container shipping: Do perception and satisfaction regarding digital products in a non-technology industry affect overall customer loyalty?," Technological Forecasting and Social Change, Elsevier, vol. 172(C).

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