New Insights into e-Loyalty of Internet Banking Users in an Emerging Market Context: A Multilevel Analysis

Although internet banking is considered a mature technology, digital failures and breakdowns have resulted in widespread customer dissatisfaction. However, recent examples in developed countries show that customer dissatisfaction with internet banking platforms does not necessarily erode customer loyalty. While this could be due to the strong assurance provided by institutional structures that govern the internet usage, it is not known if similar results can be found in emerging markets where internet banking technology has still not reached its saturation stage and coexists with traditional brick and mortar banking services. Thus, this study aims to develop a better understanding of the e-satisfaction-e-loyalty link in the Indian internet banking context. The moderating effects of structural assurance at the individual level and market share at the firm level are analysed on the e-satisfaction – e-loyalty link applying a multilevel modeling framework. Data collected from customers along with archival data across 21 banks in India demonstrate that structural assurance significantly moderates the e-satisfaction-e-loyalty link at the consumer level and market share regulates the link at the bank level. Also, market share is found to moderate the relationships among e-satisfaction, structural assurance, and e-loyalty. Three-way interaction results suggest that the interaction effect between e-satisfaction and structural assurance is less pronounced when market share is high rather than low. This study advances our understanding of the conditional effects of e-satisfaction on e-loyalty and elucidates how different share banks may optimize customer loyalty in an emerging market context

Big data marketing during the period 2012–2019: a bibliometric review

The present study identifies the most significant trends in production of high impact scientific papers related to the Big Data Marketing variable during the period between the years 2012 and 2019 through a revision of the Scopus database, which manages to highlight the relevance of 113 indexed papers. For this purpose, the following descriptive bibliometric indicators are implemented: production volume, type of document, number of citations, and country of application. In the studied time period, the evidence suggests an annual growth in the production volume of papers related to the variable, but with a significant drop in 2017. The knowledge areas that showcases more researches about the Big Data Marketing variable are computer science, mathematics, decision-making, and engineering domain

PREDICTING ADVERTISING EXPENDITURES USING INTENTION SURVEYS

In this article we study the use of intention surveys to predict the effects of a possible entrant. The case under investigation deals with the introduction of private broadcasting in the Netherlands. Several predictions of the advertising expenditures in various media are given which depend on a number of scenarios. These scenarios are used to reduce the discrepancies between behavioural intentions and actual behaviour. The predictions of the most realistic scenario are compared with their realizations, and the differences are analyzed. To this end the prediction error is decomposed into an intention error and a sampling error. This decomposition offers good opportunities to analyze discrepancies between intentions and actual behaviour