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While digital media changed the nature of communication in service contexts, often allowing customers to interact instantly with service providers, the implications and opportunities for managing service employees are widely unknown. This is surprising, given that service employees are an important determinant of service firms’ success. This article examines the effects of real-time performance feedback on employees’ service performance and investigates both how and under what conditions timely feedback encourages employees’ engagement.

Two experiments test the conceptual model and the proposed hypotheses. A field experiment uses real customer feedback gathered after interaction with the app-chat of a large telecommunications provider. It tests the effect of feedback timing on service employees’ performance and also examines the effect of feedback timing on their engagement. A subsequent scenario-based experiment then investigates the influence of selected moderators on the feedback timing–engagement relationship.

This article finds that real-time feedback leads to greater service performance than subsequent feedback. Furthermore, real-time feedback positively affects service employee engagement through the perceived controllability of the feedback and the service situation. Finally, feedback valence, task goals, individuals’ need for closure (NCL), and gender interact with feedback timing to influence employee engagement.

This research investigates the potential of real-time performance feedback for service firms, combines and extends a variety of literature streams, and provides recommendations for the future management of service employees.

Corporate social responsibility is becoming increasingly important in the retailing industry, whereby retailers are frequently criticized for socially irresponsible business practices by mass media and consumer advocacy groups. The purpose of this research is to find out which retail business practices lead to perceptions of corporate social irresponsibility (CSIR) from the customers' perspective and to develop a measurement scale for this construct.

Using quantitative data from a paper‐based and an online survey, a higher‐order, multi‐group confirmatory factor analysis was conducted.

The research identifies 14 factors which represent perceptions of CSIR in retailing. A measurement scale of this construct is proposed and empirically validated. Demographic differences among consumers' CSIR perceptions are revealed.

The scale remains to be validated in varying cultural settings other than the USA.

The findings provide retailers with a detailed account of business practices that consumers regard as socially irresponsible. The scale can be adopted by retailers in surveys to measure consumers' perceptions.

The paper is first in providing a conceptualization and measurement scale for CSIR which is of increasing importance for both retailing theory and practice.

Shopping motivation is one of the key constructs of research on shopping behavior and exhibits a high relevance for formulating retail marketing strategies. Previous studies of shopping behavior as well as research in the areas of psychology and organizational behavior point towards a need to investigate the hierarchical nature of shopping motivation. The present study intends to take the first steps towards the development of a hierarchical theory of shopping motivation.

Means‐end chain theory is adopted to explore the hierarchical nature of shopping motivation. A total of 40 in‐depths interviews with apparel shoppers were conducted using the laddering technique. Results are depicted in three hierarchical value maps.

Evidence is provided relating to the social, experiential, and utilitarian aspects of shopping as represented by four dominant motivational patterns referring to the issues of shopping pleasure, frictionless shopping, value seeking, and quality seeking. Concrete retail attributes are presented which allow retailers to correspond to these motivations.

The paper identifies the need to introduce a hierarchical perspective to provide an increased understanding of consumers' shopping motivation. First, empirical evidence is provided regarding how consumers' cognitive structures relating to the benefits of shopping are hierarchically organized.

Local and regional entertainers typically perform without a star performer or national recognition. These performers are often an incidental backdrop for the festivities. Is audience satisfaction with the group more than a summation of the satisfaction with individual performers; do factors surrounding the performance aid in determining audience satisfaction? Answers to these questions may allow event planners to engage performers likely to increase event success. This paper develops a model of audience satisfaction with live performances, which began using a theory developed by Grove et al. in 1992. This theory was modified as a result of further conceptualization, qualitative data analysis, and survey results. Results suggest consumers judge performances as the sum of several components, including both elements of the performance and the setting.

Chatbots are increasingly prevalent in the service frontline. Due to advancements in artificial intelligence, chatbots are often indistinguishable from humans. Regarding the question whether firms should disclose their chatbots' nonhuman identity or not, previous studies find negative consumer reactions to chatbot disclosure. By considering the role of trust and service-related context factors, this study explores how negative effects of chatbot disclosure for customer retention can be prevented.

This paper presents two experimental studies that examine the effect of disclosing the nonhuman identity of chatbots on customer retention. While the first study examines the effect of chatbot disclosure for different levels of service criticality, the second study considers different service outcomes. The authors employ analysis of covariance and mediation analysis to test their hypotheses.

Chatbot disclosure has a negative indirect effect on customer retention through mitigated trust for services with high criticality. In cases where a chatbot fails to handle the customer's service issue, disclosing the chatbot identity not only lacks negative impact but even elicits a positive effect on retention.

The authors provide evidence that customers will react differently to chatbot disclosure depending on the service frontline setting. They show that chatbot disclosure does not only have undesirable consequences as previous studies suspect but can lead to positive reactions as well. By doing so, the authors draw a more balanced picture on the consequences of chatbot disclosure.

The sudden arrival of Covid-19 severely disrupted the supply chain of personal protective equipment (PPE) in Australia. This paper aims to examine the development of a geographical cluster, which, through the application of additive manufacturing (AM), responded to the PPE supply crisis.

This longitudinal case study focuses on an AM cluster, which was developed to supply PPE in a responsive and flexible manner from 2019/2020. The study gathered data over three stages of cluster evolution: pre, during and post-peak Covid-19.

The type and nature of exchanges between organizations involved in the cluster established important insights into success factors for cluster creation and development. Using an established complexity framework, this study identifies the characteristics of establishing a cluster. The importance of cluster alignment created initially by a common PPE supply goal led to an emerging commercial and relational imperative to address the longer-term configuration after the disruption.

Clusters can be a viable option for a technology-driven sector when there is a “buzz” that drives and rapidly diffuses knowledge to support cluster formation. This research identifies the structural, socio-political and emergent dimensions, which need to be considered by stakeholders when aiming at improving competitiveness using clusters.

Covid-19 has rapidly and unexpectedly disrupted the supply chain for many industries. Responding to challenges, businesses will investigate different pathways to improve the overall resilience including on-/near-shoring. The results provide insights into how clusters are formed, grow and develop and the differentiating factors that result in successful impacts of clusters on local economies.

Negative perceptions of political risk can prevent capital from being committed to support cross‐border investment. Information about risks that impact infra‐structure projects is often vague, imprecise, subjective, or ambiguous. Political risks in developing countries also often lack meaningful historical and numerical data. A novel fuzzy set approach for quantifying qualitative information on risks (QQIR) in structured finance transactions that bridges the gap between qualitative and quantitative risk assessment methods has been developed. The QQIR Method is validated empirically through the results of an international survey to determine the impact of perceived political risk on Asian infrastructure projects. The impact is measured by the effect on financial project criteria. The impact was assessed across 14 Asian countries and 14 infrastructure sectors. The survey findings are validated by triangulation of three data sets and employing non‐parametric statistics. The validation shows that in 77.5% of all observations the QQIR Method produces mean results that are within 0.85 standard deviations of the absolute values, without elimination of any seemingly unusual or unreasonable responses or data. The validation also shows that with increasing perceived risks, the costs of equity investment, debt finance, and insurance also increase. The QQIR Method is thus a valid tool to quantify perceptions on risks. In this case it has been applied to political risks, but the Method is generic and may be applied to any problem set in which perceptions can be structured and assessed with opinions.