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Hospitality companies increasingly sell their unsold, or so-called rescued meals, on food waste reduction applications (e.g. Too Good To Go [TGTG]). The purpose of this research is to explore the influence of product construal and benefit appeals on consumer evaluations.

Study 1 (N = 277 participants) is an online experiment with a 2 × 3 between subject design analyzed using ANOVA and planned contrast analysis. Study 2 is a 2 × 2 field experiment (N = 147 sold rescued food boxes) using chi-square tests for the main analysis.

This study finds that an abstract product description (e.g. a magic box with an opaque content) matched with an environmental benefit appeal renders significantly higher consumer evaluations in comparison to when the same product is paired with financial benefits. In contrast, a concrete product presentation featuring financial benefits as opposed to environmental benefits increases consumer purchase intentions and willingness to pay.

We empirically show how the interaction and congruency between product construal and benefit appeals affect evaluations in a last-minute purchase context.

To the best of the authors’ knowledge, this is the first study to look at the interactive effect between product construal and benefit appeals in a food waste and technology context.

This study seeks to investigate barriers in the consumer adoption process of technological innovations under different contingencies. The paper aims to focus on barriers impeding adoption of technologies characterized by high incompatibility and high uncertainty – i.e. a “lack of content” (LoC) situation – versus technologies characterized by low incompatibility and low uncertainty – i.e. a “presence of content” (PoC) situation.

Based on a literature study, the paper develops hypotheses that distinguish the diverging effects of both psychological and functional barriers on consumer adoption in different situations (LoC versus PoC). Data were collected by means of a survey, resulting in an effective sample of 229 respondents.

In the case of LoC, the value, risk (financial and performance) and image barrier are negatively related to adoption intention, where the latter barrier is significantly stronger for the LoC situation than for the PoC situation. For PoC, it is found that the value, image, and financial risk barriers are negatively related to adoption intention, where the value barrier outweighs all other barriers. Interestingly, the traditional barrier reveals a positive effect on adoption intention.

The results suggest that managers and retailers should develop a more sophisticated understanding of consumers' adoption intention of new technologies. Distinguishing between LoC and PoC situations offers managers the opportunity to differentiate their communication strategies and design more compelling ways for consumers to overcome the specific barriers they perceive in each situation.

The paper attempts to offer a more fine‐grained understanding of consumer adoption by investigating the extent to which the lack versus the presence of content gives rise to differences regarding the effects of psychological and functional barriers to technology adoption.

This study aims to investigate the effects of two types of expertise (self-service technology and service type) on the disconfirmation of customers’ expectations and the use-related outcomes of technology-based self-service (TBSS).

This empirical study pertains to the mandatory use of a national public transport chip card in The Netherlands based on a sample of 267 users of this TBSS.

The findings show that technology experts experienced a less positive disconfirmation of expectations and reported less positive evaluations of the new self-service than technology novices. Technology experts also showed lower intentions to engage in positive word-of-mouth than technology novices. The evaluation of the self-service by technology novices is more positive for those that are service experts as compared to service novices, while the evaluation by technology experts is more negative for those that are service experts as compared to service novices.

This study provides insight into how different types and levels of customer expertise affect individuals’ assessments of a TBSS upon its mandatory use.

For marketing managers and public policy-makers, understanding the multifaceted role of customer expertise enables more effective market segmentation and targeting, thus improving implementation of TBSS.

This research suggests that customers’ technology and service expertise have some counter-intuitive effects on TBSS use-related outcomes.

So far, the term e‐commerce has been primarily associated with communicating the brand and/or enabling sales transactions. However, the next vista for companies operating in the virtual marketplace seems to be e‐service or, delivering value‐added, interactive services to customers. This e‐business function has been left virtually unexplored in the services research literature. In this article, an attempt is made to investigate the impact of organizational reputation, relative advantage, and perceived risk on perceived service quality, trust and behavioral intentions of customers towards adopting e‐services. In the context of an electronic travel service, hypotheses on the relationships between aforementioned variables are investigated by means of an experimental study. The results suggest that the three factors have a significant main effect on the customers’ attitude and behavior towards e‐service. The only exception is that relative advantage does not appear to have a significant impact on customer trust. The results also show that organizational reputation and perceived risk have a combined effect: a good organizational reputation impacts the effect of perceived risk on the three dependent variables. Finally, the three factors appeared to be evenly important in the forming of customers’ attitude and behavior. Again, the only exception is that organizational reputation and perceived risk appear to be more important in terms of trust than relative advantage.

The purpose of this editorial is to announce the winners of the EJM Reviewer of the Year awards, and also to make some observations about successful and effective practice in reviewing scholarly work.

The authors draw from their own experience as reviewers, authors, and editors to provide a set of considerations for those involved in the review process.

The authors propose a set of guidelines for reviewers who wish to make the most of their role in the scientific method.

These thoughts are preliminary, and are drawn from personal experiences rather than a wide‐ranging survey of stakeholders.

Marketing researchers should ensure that they understand their role in the scholarly reviewing process, and that they provide timely and constructive comments on their areas of expertise.

This piece should offer marketing researchers considerable value in the context of their own efforts, both as authors and reviewer.

This study unravels the intellectual structure of virtual reality (VR) in digital marketing (DM) research, identifies core research gaps and presents future research avenues. The study also conducts a performance analysis of publications in the field and identifies the most important stakeholders of the stated topic.

The Web of Science database was used to retrieve the publications that were relevant to the topic between 2012 and 2022. Biblioshiny, a shiny app for the Bibliometrix R package, is used to conduct a bibliometric analysis by decoding the results into several visual representations.

This report includes the most prolific contributors, keyword analysis results, productive nations, authors and connections, as well as the most often cited publications on VR in DM. In DM research, numerous perspectives on VR were looked at, explored and revealed.

The findings provide a new perspective and understanding of the issue for researchers in order to improve their research insights in the field. This study will also benefit marketing practitioners in ensuring the sustainability and innovativeness of technology used to run their DM campaigns.

This research provides the first bibliometric analysis of the citation works and productivity in the field of VR in DM using Biblioshiny, identifies core research gaps and provides future research agenda which can be useful to advance the research understanding in this context.

The rapid development of e-commerce has brought not only great convenience to people but a great challenge to online stores. Phenomenon such as out of stock and slow sales has been common in recent years. These issues can be managed only when the occurrence of the sales volume is predicted in advance, and sufficient warnings can be executed in time. Thus, keeping in mind the importance of the sales prediction system, the purpose of this paper is to propose an effective sales prediction model and make digital marketing strategies with the machine learning model.

Based on the consumer purchasing behavior decision theory, we discuss the factors affecting product sales, including external factors, consumer perception, consumer potential purchase behavior and consumer traffic. Then we propose a sales prediction model, M-GNA-XGBOOST, using the time-series prediction that ensures the effective prediction of sales about each product in a short time on online stores based on the sales data in the previous term or month or year. The proposed M-GNA-XGBOOST model serves as an adaptive prediction model, for which the instant factors and the sales data of the previous period are the input, and the optimal computation is based on the proposed methodology. The adaptive prediction using the proposed model is developed based on the LSTM (Long Short-Term Memory), GAN (Generative Adversarial Networks) and XGBOOST (eXtreme Gradient Boosting). The model inherits the advantages among the algorithms with better accuracy and forecasts the sales of each product in the store with instant data characteristics for the first time.

The analysis using Jingdong dataset proves the effectiveness of the proposed prediction method. The effectiveness of the proposed method is enhanced and the accuracy that instant data as input is found to be better compared with the model that lagged data as input. The root means squared error and mean absolute error of the proposed model are found to be around 11.9 and 8.23. According to the sales prediction of each product, the resource can be arranged in advance, and the marketing strategy of product positioning, product display optimization, inventory management and product promotion is designed for online stores.

The paper proposes and implements a new model, M-GNA-XGBOOST, to predict sales of each product for online stores. Our work provides reference and enlightenment for the establishment of accurate sales-based digital marketing strategies for online stores.

The purpose of this paper is to reflect on the author’s decade-long tenure as the Editor of the European Journal of Marketing (EJM). The paper presents his thoughts on the past 10 years of marketing scholarship, his views on future directions and some advice for those looking to publish their research in academic journals.

The paper takes a reflective, discursive approach, and also reviews a wide range of topics relevant to marketing researchers.

The author finds that EJM has grown substantially on many levels in the past decade. He also finds that there are some concerns around marketing research, and social scientific scholarship in general, that marketing scholars may wish to consider and take into account in their ongoing work.

The paper is partly a personal view, and does not rely on any empirical research. However, the views espoused are justified by theoretical review and conceptual argument.

The implications of this paper are relevant to marketing scholars, journal reviewers, readers of research, as well as those who manage scholarship (e.g. university administrators). The author suggests a number of directions that the research, publication and reward process could move in to improve practice.

The paper brings together a large number of different views and concepts relevant to further development of marketing research, and provides original summaries and extensions.

The purpose of this paper is to deepen our understanding of customers' actual internet banking behaviour by combining the construct of technology readiness with the technology acceptance model and demographics, such as age and gender, into one integrated framework.

The customer‐specific internet banking acceptance model (CSIBAM) is validated through 435 UK internet banking users.

The results indicate the importance of customer‐specific factors in predicting actual behaviour. Technology readiness, age and gender moderate the beliefs‐intention relationship. Customers with varying levels of technology‐related views and demographics hold different beliefs about technology. The relationship between usefulness and behaviour was stronger for younger males with high levels of optimism and innovativeness (explorers and pioneers), whilst the relationship between ease of use and behaviour was stronger for older females with a high level of discomfort (paranoids and laggards).

In today's highly competitive financial services market, knowledge of key customer‐specific factors can help banks to enhance customer experience by focusing more on each segment's particular needs. This knowledge would also help managers to decide about the extent to which technology‐based systems can be used, the appropriate type of these systems, the pace of implementation, and the type of customer support required.

A distinctive contribution of this study is that it does not rely on self‐reported intention or usage, but instead it employs actual behavioural data. Greater understanding of seemingly established relationships could improve the design of the service and the development of differential marketing strategies aimed at driving adoption and allaying rejection.