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This exploratory research aims to identify the types of social networks established by German and French expatriates.

The authors use the concepts of social capital and social networks, as well as the societal and cultural approaches, to investigate the way expatriates develop their social networks. The authors' empirical study is based on 40 semi-structured interviews conducted with German and French expatriates.

The authors' findings show that German expatriates mainly establish professional networks, whereas their French counterparts also focus on personal networks. They further indicate that managing social capital lies within the individual responsibility of German expatriates, whereas it is part of higher education institutions in France.

The authors highlight the way German and French expatriates manage their social networks and provide novel insights into the role played by higher education systems and the cultural characteristics of their home country context.

This study aims to assess the direct impact of workplace hazing and the indirect impact via moral disengagement on organizational deviance behavior and negative word-of-mouth (WOM) communication in the hospitality industry of Pakistan. This research also addresses the significance of psychological (resilience) and social factors (friendship prevalence) as moderators of the relationship between workplace hazing and moral disengagement.

Using a multirespondent strategy, the data was collected from 319 newcomers employed in the Pakistani hospitality industry and analyzed using structural equation modeling.

The results reveal that workplace hazing increases moral disengagement, organizational deviance and negative WOM communication. Moreover, various psychological factors can significantly decrease and mediate the negative influence of workplace hazing on moral disengagement.

The managers should explicitly and formally handle the workplace hazing issues like harassment and bullying to build a positive working environment for newcomers.

This study addresses a gap in determining the significance of workplace hazing and its impact on moral disengagement, organizational deviance and negative WOM communication. Also, this study contributes to the literature by examining either social or psychological factors that play an important role in dampening the negative impact of workplace hazing.

Technology-enabled business-to-business (B2B) services contribute the largest share to GDP growth and are fundamental for an economy’s value creation. This article aims to identify key service- and digital technology-driven B2B innovation modes and proposes a research agenda for further exploration.

This conceptual paper adopts a techno-demarcation view on service innovation, encompassing three core dimensions: service offering (the service product, or the “what”), service process (the “how”) and service ecosystem (the “who/for whom”). It delineates the implications of three digital technologies – the internet-of-things (IoT), intelligent automation (IA) and digital platforms – for service innovation across these core dimensions in B2B markets.

Digital technology has immense potential ramifications for value creation by reshaping all three core dimensions of service innovation. Specifically, IoT can transform physical resources into reconfigurable service products, IA can augment and automate a rapidly expanding array of service processes, while digital platforms provide the technical and organizational infrastructure for the integration of resources and stakeholders within service ecosystems.

This study suggests an agenda with six themes for further research, each linked to one or more of the three service innovation dimensions. They are (1) new recurring revenue models, (2) service innovation in the metaverse, (3) scaling up service innovations, (4) ecosystem innovations, (5) power dependency and lock-in effects and (6) security and responsibility in digital domains.

This systematic literature review investigates the contribution of design thinking (DT) as a process and tool to drive innovation in a sustainable built environment (SBE) and develops a new model for sustainability research integrating DT and future thinking approaches toward achieving a unified DT and foresight notion for future research and applications.

This review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Open-access English articles published between 2000 and 2022 identified using the EBSCOhost, Emerald Insight, DOJA, JSTOR, Scopus and Taylor and Francis database searches were reviewed. The review framework deploys a previously proposed modified Ansoff matrix with an integrated innovation matrix to identify and analyze the challenges and opportunities for innovation growth in SBE. Additionally, a citation analysis was conducted to explore the impact of DT for innovation in SBE, and a proposed framework based on design by drawing on foresight theory was developed.

Research on DT for innovation in SBE faces the challenge of unanticipated impacts. According to the average number of citations per document, innovation associated with new solutions within a new context seems to become highly influential. Additionally, research gaps exist in the integration of foresight and DT into sustainability research to identify new contexts and solutions to SBE. A model of foresight design thinking (FDT) is proposed to guide future research and support the practical application of DT in sustainability.

This analysis was limited by the selection criteria as only certain keywords were used and English-only articles were selected. Future research should consider the use of DT for innovation in SBE using various important keywords, which would improve research findings and expand the contribution of DT to SBE.

The FDT model offers a new holistic framework for the iterative process of reframing and reperception, focusing on divergent and convergent thinking with the goal of contributing to SBE practices.

The integrated framework of DT and foresight can contribute to the study and development of sustainable innovation and a strategic shift toward a sustainable society.

The integration of DT, foresight and sustainability can broaden the horizons of sustainability research by systematically addressing future challenges related to SBE, which can be translated into feasible and innovative solutions. Thus, the FDT model complements the application of DT in sustainable innovation in this research field.

This research aimed to examine the impact of input, process, output, productivity and outcome variables on university research performance and the indicators that represent them in order to improve academic quality and contribute to government policy.

The quantitative approach was used through a survey method that obtained samples using questionnaires from 150 leaders of research institutions and continued analysis using the structural equation modeling-partial least square (SEM-PLS) to test the developed model.

Except for the relationship between process and productivity variables, all variable relationships had a positive and significant effect. Furthermore, the input, process, output, productivity and outcome variables each include seven, twelve, four and ten indicators.

This study has several ramifications because it provides a clear policy input and advances science. As a prelude to developing research performance assessment tools that take into account variances in a tertiary institution, this research aids in the implementation of national policies for assessing research performance in postsecondary institutions.

To improve the accuracy of the information acquired, we conducted a survey among the heads of research units at various higher-ranking Indonesian universities, taking into consideration their skill and experience in leading research organizations and conducting research. Other than that, our belief in the originality of our manuscript is strengthened by the way we applied systems theory to construct a performance evaluation model that examines each contribution made by each system aspect.

The purpose of the paper is to present an integrated methodology for identifying trends in a particular subject area based on a combination of advanced text mining and expert methods. The authors aim to test it in an area of clinical psychology and psychotherapy in 2010–2019.

The authors demonstrate the way of applying text-mining and the Word2Vec model to identify hot topics (HT) and emerging trends (ET) in clinical psychology and psychotherapy. The analysis of 11.3 million scientific publications in the Microsoft Academic Graph database revealed the most rapidly growing clinical psychology and psychotherapy terms – those with the largest increase in the number of publications reflecting real or potential trends.

The proposed approach allows one to identify HT and ET for the six thematic clusters related to mental disorders, symptoms, pharmacology, psychotherapy, treatment techniques and important psychological skills.

The developed methodology allows one to see the broad picture of the most dynamic research areas in the field of clinical psychology and psychotherapy in 2010–2019. For clinicians, who are often overwhelmed by practical work, this map of the current research can help identify the areas worthy of further attention to improve the effectiveness of their clinical work. This methodology might be applied for the identification of trends in any other subject area by taking into account its specificity.

The paper demonstrates the value of the advanced text-mining approach for understanding trends in a subject area. To the best of the authors’ knowledge, for the first time, text-mining and the Word2Vec model have been applied to identifying trends in the field of clinical psychology and psychotherapy.

The mental healthcare is experiencing an ever-growing surge in understanding the consumer (e.g., patient) engagement paradox, aiming to vouch for the quality of care. Despite this surge, scant attention has been given in academia to conceptualize and empirically investigate this particular aspect. Thus, drawing on the Stimulus-Organism-Response (S-O-R) paradigm, the study explores how patients engage with healthcare service providers and how they perceive the quality of the healthcare services.

Data were collected from 279 respondents, and the derived conceptual model was tested by using Smart PLS 3.2.7 and PROCESS. To complement the findings of partial least squares (PLS)-based structural equation modeling (SEM), the present study also applied fuzzy set qualitative comparative analysis (fsQCA) to identify the necessary and sufficient conditions to explore substitute conjunctive paths that emerge.

Findings show that patients’ perceived intimacy (PI), cohesion and privacy enhance the quality of mental healthcare service providers. The results also suggest that patients’ PI, cohesion and privacy have indirect effects on the perceived quality of care (PQC) by the service providers through consumer engagement. The fsQCA results derive that the relationship among conditions leading to patients’ perception of the quality of care in regard to mental healthcare service providers is complex and is best reflected as multiple and conjectural causation configurations.

The findings from this research contribute to the advancement of studies on patients’ experiences by empirically examining the unique dynamics of interaction between consumers (patients) and mental healthcare service providers, thereby enriching both the literature on social interactions and the understanding of the consumer–provider relationship.

The results of this study provide practical implications for mental healthcare service providers on how to combine the study variables to enhance the quality of care and satisfy more patients.

A significant research gap has ascertained the inter-relationship between PI, cohesion, privacy, engagement and PQC from the perspective of mental healthcare service providers. This research is one of the primary studies from a managerial and methodological standpoint. The study contributes by combining symmetric and asymmetric statistical tools in service marketing and healthcare research. Furthermore, the application of fsQCA helps to understand the interactions that might not be immediately obvious through traditional symmetric methods.