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Measuring the role of factors on website effectiveness using vector autoregressive model

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  • Roy, Gobinda
  • Sharma, Swati

Abstract

Behavioral actions of online customers play an important role in influencing the website's effectiveness for online retailers and online business entities. The leading web analytics software measures the customers' behavior on a website using many key web metrics. However, the role of key metrics in measuring the dynamics nature of website effectiveness has largely been unexplored, especially for the non-transactional website. The study builds on flow theory to fill this gap. It presents a methodology to predict the website's effectiveness by examining the impact of three metrics (average session duration, repeat visit, and bouncing rate) on consumers' online behavioral outcomes witnessed through goal completion (GC) and goal conversion rate (GCR). Vector autoregressive (VAR) method is adopted to analyze the dynamic relations and effect among the metrics. The study provides an in-depth insight into the time-varying effect of each variable on website performance. The findings reveal that an engaged customer with high ASD (average session duration) or who revisits (RV) the site positively impacts GC and GCR. A negative effect of bouncing rate (BR) was found on goal conversion rate and goal completion. Interestingly, the study found granger causality between GC and GCR & ASD, and RV. Based on the findings, the study provides vital theoretical and managerial implications.

Suggested Citation

  • Roy, Gobinda & Sharma, Swati, 2021. "Measuring the role of factors on website effectiveness using vector autoregressive model," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    • Handle: RePEc:eee:joreco:v:62:y:2021:i:c:s0969698921002228
    DOI: 10.1016/j.jretconser.2021.102656
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