Carol L. Esmark

Open versus selective customer loyalty programmes

Purpose This paper aims to examine the impact of an open loyalty programme (anyone can join) versus a selective programme (requirements must be met) to show what types of loyalty programmes are most effective. In-group identification, gratitude, stage of relationship and visibility are additionally examined. Design/methodology/approach Two studies use experimental methodology to initially test the relationships. A third study uses survey and panel data. Findings Open programmes lead to more in-group identification, while selective programmes lead to higher levels of gratitude, especially in mature stages. Visible programmes lead to more in-group identification. Industry differences are presented. Research limitations/implications The first two studies use a student sample (although Study 3 uses penal data). The research is limited to the variables examined. The findings add to theory by showing differences between open and selective loyalty programmes. Practical implications The findings show how different retailer offerings change the value and experience to the customer leading to loyalty intentions. Loyalty programme designers can tailor their programme structure to fit their customers and overall strategy. The findings also shed light on the strategic importance of tiered loyalty programmes. Originality/value The examination of how a customer enters a loyalty programme is not in current literature. The research shows how loyalty intentions are impacted by design of the programme, including how a customer signs up for a programme. The mechanisms through which the relationship works increase the understanding of loyalty programme effectiveness.

Well That’s Embarrassing: An Examination of Product Package Differences and the Impact on Embarrassment: An Abstract

For the first time, online purchases have outnumbered purchases made in store (excluding groceries) with 51% of purchases being made through web channels. One reason shoppers make certain purchases online is to minimize the embarrassment of being seen with certain products (e.g., condoms, diet-related products, or plus-size clothing). While much research talks about the success of product differentiation, our research conversely shows that for embarrassing products, increasing product anonymity can be a more strategic approach to selling products.

Countering Negative Online Reviews: The Impact of Response and Responder—A Structured Abstract

The phenomenon of electronic word of mouth (eWOM) has been the focus of a substantial amount of research, with negative eWOM receiving a great deal of that attention. Compared to positive ratings, negative reviews elicit stronger feelings toward both the brand and its performance (Mizerski 1982). Indeed, research indicates that four out of five online consumers have changed their decision to purchase based on a negative online product review (Cone 2011). While sales effects directly attributable to eWOM have been shown to be short-lived (Moe and Trusov 2011), little is known about the long-term impact of negative eWOM on a brand. A study of movie ticket sales, however, did find that the volume of reviews can have a significant impact on overall movie revenues (Duan et al. 2008), suggesting that there may be long-term effects of eWOM. While the power of eWOM is accepted, to date, extant literature has not specifically addressed the impact of responses to negative eWOM and how those responses may affect readers’ evaluations of the focal brand. Our research examines how a response (i.e., a negative review has been posted online and another person posts in reference to the original comment) can counter a negative online review and empirically examines the differing impact based on who responds.

The Effects of Different Types of Control in Co-production Experiences

Customer participation has become an important firm strategy (Bendapudi and Leone 2003; Vargo and Lusch 2004). Companies are designing their offering(s) to allow customers to participate to various degrees in the process of creating and delivering the offering(s). In this strategy, not only do providers select a level of customer co-production, but also the level of control available to customers. This study examines the effects of control types (cognitive, behavioral, and decisional) and their interaction on customers’ affective responses in service contexts with varying levels of co-production.