International Journal of Research in Marketing最新文献

Advertising has the power to influence how consumers experience, think, and feel about brands, but the sequence of these mindset effects may differ by brand and category. This paper analyzes how the mindset factors of cognition, affect, and experience mediate advertising effects on sales, using data from 178 fast-moving consumer good brands in 18 categories over seven years. The authors compare the models proposed in the literature and conclude that the concept of sequentiality in advertising effects holds up well. Importantly, the sequence varies across brands, with the affect → cognition → experience (ACE) sequence being the most common. Brand differentiation and the hedonic versus utilitarian nature of the product category moderate the incidence of the ACE sequence: this sequence is even more likely for utilitarian products and less differentiated brands. For managers, the results show that the last mindset factor in the sequence is the most important in driving sales, with cognition being most responsive to advertising among the mindset factors. Moreover, in utilitarian categories, highly differentiated brands can expect about seven times higher advertising responsiveness of affect than less differentiated brands.

How does ChatGPT, and other forms of Generative Artificial Intelligence (GenAI) affect the way we have been conducting—and evaluating—academic research, teaching, and business practice? What are the implications for the theory and practice of marketing? What are the opportunities and threats, and what are some interesting avenues for future research? This editorial aims to kick off an initial discussion and stimulate research that will help us better understand how the marketing field can fully exploit the potential of GenAI and effectively cope with its challenges.

Service shutdowns—extended disruptions of operations—caused by exogenous events are on the rise. Such shutdowns pose major challenges for service providers, customers, and regulators. Providers prefer vouchers as a means of service recovery to limit bankruptcy risk, whereas customers demand cash refunds or vouchers that include a generous bonus. Regulators, on the other hand, insist that customers must be granted the right to be reimbursed in cash. This paper shows that a zero bonus is optimal under the voucher-only strategy, whereas the provider should always include a positive bonus with the voucher under the hybrid strategy that allows customers to choose between the cash refund and voucher options. Surprisingly, despite its higher flexibility in service recovery design, the hybrid strategy can be dominated by the voucher-only strategy in terms of profit and welfare. Moreover, we show that the ranking of strategies differs across the two important dimensions of expected profit and survival under shutdown. Finally, we study competition among providers and show that a high-quality provider is more likely to use cash-back as the service recovery strategy than its low-quality competitor.

Fairness is essential for successful crowdsourcing. Without it, companies run the risk of consumers not participating, or worse, sabotaging the crowdsourcing initiative. Yet little is known about how consumers determine what is fair in crowdsourcing. Building on theories of organizational justice and institutional logics, and using a longitudinal netnography of Threadless, a popular crowdsourcing platform, this paper shows how experiences of fairness stem from the interaction between two conflicting crowdsourcing logics: the logic of renewal and the logic of community. The two logics inform notions of fairness in crowdsourcing contests across procedural, distributive, and interactional justice dimensions. A balance between the two logics is ideal for maintaining fairness among a crowdsourcing community. We show the conditions in which crowdsourcing participants tolerate transgressions to each justice dimension, consequently emphasizing one logic over the other. Overall, our study advances theory on crowdsourcing logics and how they guide notions of procedural, distributive, and interactional fairness in crowdsourcing. Our study also offers new guidance on how to manage fairness in crowdsourcing.

While single-brand reward programs encourage customers to remain loyal to that one brand, coalition programs encourage customers to be “promiscuous” by offering points redeemable across partner stores. Despite the benefits of this “open relationship” with customers, store managers face uncertainty as to how rewards offered by partners influence transactions at their own stores. We use a model of multi-store purchase incidence and spend to show how the value of points shared among partner stores can explain patterns in customer-level purchases across them. We also allow reward spillovers to be moderated by three measures of store affinity that characterize a coalition’s portfolio: the relative popularity, geographic distance, and overlap in product categories between each pair of stores.

For the coalition studied, popularity affinity was the main determinant of the valence of cross-reward effects, both before and after the devaluation. In contrast, category and geographic affinity had a smaller and more heterogenous impact. Through the use of an event where the loyalty program uniformly devalued the entire coalition’s value of reward points, we show that cross-reward effects changed (lessened), leading to larger financial losses for the most popular stores. While we do not observe changes to the composition of the coalition’s portfolio, our results also suggest that the value of a shared reward currency may be driven by the inclusion of smaller partners.

One of the main challenges facing the mobile game industry is an alarming level of satiation, that is, a decline in user engagement and consequently in ad viewing, spending, and retention. Satiation lowers users’ CLV to an extent that renders acquisition from the likes of Facebook and Google untenable, driving game publishers to cross-promote, that is, sell and swap users among themselves. We model this cross-promotion as first, a screening mechanism, in that the fact of playing a game indicates specific preferences that might be suitable to an exchange with similar games; and second, as a resetting mechanism that enables the swapped users to reset their engagement in the new game, thus rendering the swap or sell beneficial to both buyer and seller. We show that there exists an optimal level of satiation with a game, and with this level, we show the conditions under which the game publisher cross promotes, and when it does, what the conditions are for selling rather than swapping. We extend the analysis to the case in which advertising costs and conversion rates are related; explain why they might be negatively correlated, and show that our main results still hold.

As customers in technologically disrupted markets migrate from the old to the new technology, they concurrently decide whether to retain their brand or churn. Yet little is known about brand retention at the time of technology migration, which is the topic of this study. Focusing on cloud disruption in the enterprise software industry, we examine the brand retention of software customers migrating from the old on-premise to the new cloud technology. We combine a large panel of 4,659 customers across 30 brands and five horizontal markets (CRM, BI, HR, ERP, Finance) with brand classification data from industry experts. Our findings reveal that brand retention is the lowest at the time of technology migration (compared to before or after migration), yet some brands are significantly more vulnerable to churn of migrating customers than others. Brand retention at the time of migration is lower for brands that face the same rivals across multiple horizontal markets (i.e., high multimarket contact) than for brands that do not, and the retention disadvantage of such high multimarket contact brands even aggravates as the cloud technology diffuses. Furthermore, top-tier brands are less vulnerable than bottom-tier brands, but their advantage levels out as the cloud technology diffuses. Our findings help brands evaluate their vulnerability to churn of migrating customers and hence are highly relevant for B2B brands in technologically disrupted markets. To facilitate such evaluation, we present a simple assessment tool and provide guidance on mitigating vulnerability to churn.