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The purpose of this paper is to investigate the suitability of Blockchain technology for applications in the Industrial Internet of Things (IIOT). It provides a taxonomy of system requirements for such applications and maps these requirements against the Blockchain’s technological idiosyncrasies.

A requirement taxonomy is built in an iterative process based on a descriptive literature review. In total, 223 studies have been screened leading to a relevant sample of 48 publications that were analyzed in detail regarding posed system requirements. Subsequently, Blockchain’s capabilities are discussed for each requirement dimension.

The paper presents a taxonomy of six requirement dimensions. In the mapping process, areas of greater fit (e.g., reliability, nonrepudiation and adaptability) were identified. However, there are also several constraints (e.g., scalability, confidentiality and performance) that limit the use of Blockchain.

Due to the limited amount of studies and the vibrant development of Blockchain technology, the results may benefit from practical evidence. Researchers are encouraged to validate the results in qualitative practitioner interviews. Focusing on literature-backed public Blockchain, idiosyncrasies of private implementations and specific distributed ledger technologies may be discussed in future studies.

The paper includes use cases for Blockchain in manufacturing and IIOT applications. Potential caveats for practitioners are presented.

This paper addresses the need to understand to which degree Blockchain is a suitable technology in manufacturing, especially in context of the IIOT. It contributes a requirement taxonomy which serves as the foundation for a systematic fit assessment.

Compulsion to buy is an important but neglected aspect of consumer behavior. This research uses cross‐cultural data from the USA and South Korea to study compulsive consumption behavior by focusing on individual factors. Three compulsive consumption behaviors (i.e. compulsive buying, compulsive substance abuse, and compulsive gambling/lottery play) are analyzed via structural equation modeling. The findings reveal that comorbidity (i.e. coexistence of more than two related compulsive consumption behaviors) is found in both countries. With one exception, the predicted personality traits (i.e. obsessive thoughts, risk‐taking tendencies) are significantly related to compulsive consumption behaviors in both countries.

For nearly 2 decades, the push-pull-mooring (PPM) model has been used frequently by scholars to explain consumers’ service switching intention and behavior. However, heterogeneity and incomparability between PPM model studies are prevalent issues: The chosen predictor variables, their categorization, their measurement, reported effect sizes, and effect directions vary considerably. By addressing these issues, the present meta-analytical review enables future researchers applying the PPM model to identify relevant variables and use valid measurements.

Based on 148 empirical studies employing the PPM model, the variables used to predict consumers’ service switching intention and behavior, their frequency of use, their categorization into push, pull, and mooring factors, and their measurement are assessed. The effect sizes and directions of the relationships between these variables and consumers’ service switching intention and behavior are analyzed using meta-analytic structural equation modeling. Additionally, the predictive capacity of this model and the influence of moderators are assessed.

Among the 148 empirical studies, 382 different independent variables were used. The three most frequently used and distinctly categorized independent variables are dissatisfaction (push), alternative attractiveness (pull), and switching costs (mooring). Overall, 152 unique sources were cited to measure these variables and the dependent variables. Dissatisfaction and alternative attractiveness increase switching intention, which positively affects switching behavior, while switching costs decrease switching intention. The model explains 30% of the variance in switching intention and 31% of the variance in switching behavior.

This study provides the first meta-analytical review of the PPM model to guide future research systematically.

We conceptualized the novel phenomenon of COVID-induced virtual teams and its implications and provided researchers with the required information on how to conduct a phenomenon-based study for conceptualizing novel phenomena in relevant ways.

This article stems from phenomenon-based and, thus, theory-building and grounded qualitative research in the German industrial sector. We conducted 47 problem-centered interviews in two phases (February–July 2021 and February–July 2022) to understand how team members and team leaders experienced COVID-induced virtual teamwork and its subsequent developments.

Empirically, we found COVID-induced virtual teams to be characterized by a high relevance of shaping positive team dynamics via steering internal moderators; crisis is a novel external moderator and transformation becomes the key output factor to be leveraged. Work-from-home leads to specific configuration needs and interrelations between work-from-home and on-site introduce additional dynamics. Methodologically, the phenomenon-based approach is found to be highly suitable for studying the effects of such novel phenomena.

This article is explorative. Thus, we advocate further research on related novel phenomena, such as post-COVID-hybrid and work-from-home teams. A model of how to encourage positive dynamics in post-COVID-hybrid teams is developed and lays the groundwork for further studies on post-COVID teamwork. Concerning methodology, researchers are provided with information on how to conduct phenomenon-based research on novel phenomena, such as the COVID-induced virtual teams that we studied.

Companies receive advice on how to encourage positive dynamics in post-COVID teamwork, e.g. on identifying best practices and resilient individuals.

In a country such as Germany that faces labor shortages, our insights might facilitate better labor-market integration for those with care-work obligations and international workers.

We offer a first conceptualization of a relevant novel phenomenon, namely COVID-induced virtual teams. We exemplify the phenomenon-based approach as a suitable methodology that serves to build relevant theory using active categorization.

The purpose of this paper is to investigate the effect of employee-displayed smiling on customers’ affective states (pleasure, arousal, and dominance) and satisfaction. Building on the stimulus-organism-response framework and theories of emotional contagion and feelings-as-information, the main hypothesis was that a smiling (vs non-smiling) employee significantly increases customer satisfaction through the mediating influence of pleasure.

The study used a quasi-experimental two-group between-subjects design. A total of 210 customers at a large retail bank had a brief service encounter at the store entrance with a smiling (vs non-smiling) bank teller. Customers then went into the bank to do what they came to do. Before leaving the bank, customers completed a survey that included demographic information, affect (pleasure, arousal, and dominance), and measures of customer satisfaction.

A smiling (vs non-smiling) employee had a significant positive impact on customer satisfaction. This effect was mediated by pleasure, but also, to a weaker extent, by dominance. These results contradict previous claims that smiling-induced emotional contagion does not remain throughout the completion of a service encounter.

Managers should encourage, and potentially train, employees to act in ways associated with positive emotions. Managers could also hire employees based on how good they are at acting and expressing themselves in a genuinely positive manner and create a pleasant store atmosphere so that the feelings and behaviors displayed by frontline employees are genuine rather than inauthentic.

This is the first experimental field study to examine the isolated effect that employee-displayed smiling has on customers’ affective states and satisfaction. The results provide more direct evidence for the psychological processes justified by emotional contagion and feelings-as-information theories. Furthermore, the finding that dominance mediates the smiling-satisfaction link has never been shown before.

This study systematically explored the role of a range of emotions in the conflict process. In order to do so, we articulated and tested a typology of discreet conflict‐relevant emotion constructs. Emotions were demarcated by the two dimensions of self‐concern versus other‐concern, and motives to approach or withdraw from the other party or conflict. This typology produced four emotion constructs: hostility (self‐focused approach), self‐conscious emotions (self‐focused avoid), relational positivity (other‐focused approach) and fear (other‐focused avoid). Self‐ and other‐blame and self‐ and other‐concern were proposed as cognitive antecedents of emotions and choice of conflict resolution strategy. We measured individual behavior in the conflict using the conflict resolution strategy scale (Rahim & Magner, 1995). A critical incident survey technique was used to gather data on people's self‐report of a conflict experience. We also explored the contextual effects of conflict issue and relative status. Results brought into question the general hypothesis that emotions mediate the effects of cognitive appraisals on choice of conflict resolution strategy. However, there were consistent patterns in the direct links between cognitions, emotions and conflict resolution strategies that shed further light on the complex relationships between these variables.

In Britain, labor−management partnership has been the fulcrum of the Labor Government's employment relations programme since its election in 1997. The Involvement and Participation Association (IPA, 1997; website: http://www.partnership-at-work.com) − the influential employers’ organization − has been at the forefront of promoting labor−management partnership to improve productivity in UK firms through greater employee involvement and participation (see http://www.partnership-at-work.com). The Trades Union Congress (TUC; partnership institute website: http://www.partnership-institute.org.uk) and several of its constituent unions have also endorsed partnership with employers as a route to promote employee ‘voice’ at work, secure better bargaining outcomes and improve union membership levels and density (Undy, 2001). Union density in the UK private sector has declined from 19.9 per cent in autumn 1997 to 17.2 per cent in autumn 2005, while in the public sector it has declined from 60.9 per cent to 58.6 per cent over the same period of time (Grainger, 2006). Advocates of partnership argue that such arrangements deliver mutual gains to the parties involved, viz. higher productivity and profits for employers, better wages and higher employment security to workers and greater influence over management decisions for unions, which in turn help them to attract and recruit new members (e.g. Haynes & Allen, 2001; Deery & Iverson, 2005).

This paper aims to introduce and tests models for point-in-time probability of default (PD) term structures as required by international accounting standards. Corresponding accounting standards prescribe that expected credit losses (ECLs) be recognized for the impairment of financial instruments, for which the probability of default strongly embodies the included default risk. This paper fills the research gap resulting from a lack of models that expand upon existing risk management techniques, link PD term structures of different risk classes and are compliant with accounting standards, e.g. offering the flexibility for business cycle-related variations.

The author modifies the non-homogeneous continuous-time Markov chain model (NHCTMCM) by Bluhm and Overbeck (2007a, 2007b) and introduces the generalized through-the-cycle model (GTTCM), which generalizes the homogeneous Markov chain approach to a point-in-time model. As part of the overall ECL estimation, an empirical study using Standard and Poor’s (S&P) transition data compares the performance of these models using the mean squared error.

The models can reflect observed PD term structures associated with different time periods. The modified NHCTMCM performs best at the expense of higher complexity and only its cumulative PD term structures can be transferred to valid ECL-relevant unconditional PD term structures. For direct calibration to these unconditional PD term structures, the GTTCM is only slightly worse. Moreover, it requires only half of the number of parameters that its competitor does. Both models are useful additions to the implementation of accounting regulations.

The tests are only carried out for 15-year samples within a 35-year span of available S&P transition data. Furthermore, a point-in-time forecast of the PD term structure requires a link to the business cycle, which seems difficult to find, but is in principle necessary corresponding to the accounting requirements.

Research findings are useful for practitioners, who apply and develop the ECL models of financial accounting.

The innovative models expand upon the existing methodologies for assessing financial risks, motivated by the practical requirements of new financial accounting standards.