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This study aims to develop the understanding of learning processes related to the new ways of interacting in the enforced digital workplace over time.

A multiple, longitudinal case study of knowledge-based workers in three firms located in Sweden has been conducted from March 2020 to March 2023. In total, 89 interviews with 32 employees in three knowledge-based firms have been collected.

The study shows how the intricate interaction between rules and norms for interaction and work must be renegotiated as well as un- and relearned when the physical work environment no longer frames the work context. Furthermore, technology can be viewed as both an enable and a barrier, that is, technology has enhanced collaboration between organizational members yet also created social difficulties, for example, related to communication and interaction. The study emphasizes that individuals learned through trial and error. That is, they tried behaviors such as translating social interactions" to a digital arena, appraised the outcomes and modified the practices if the outcomes were poor.

The present study does have several limitations. First, it is based on interviews with respondents within three organizations in Sweden. To broaden and deepen the understanding of both organizational and learning, future studies can contribute by studying other contexts as well as using a mixed method approach in other countries.

Results from the study can provide a practical understanding of how the rapid change from working at the office to working from home using digital technologies can be understood and managed.

Contributions include combining interaction order and un- and relearning among organizational employees. This insight is important given that the rapid digital transformation of our society has changed how work is performed and how the future workplace will be both structured and organized.

Drawing from the resource-based view (RBV), this study aims to develop a parsimonious model in the context of digital platforms that links strategic network resources (SNR) and firm performance through considering dynamic capabilities (DC) as important mediating mechanisms. In addition, we also investigate how platform monitoring shapes the relationship between SNR and DC.

This study uses the survey data from 162 firms in eastern China.

The findings indicate that both two DC dimensions (i.e., sensing and reconfiguring) significantly mediate the relationship of SNR-performance. Moreover, platform monitoring positively moderates the relationship of SNR and sensing as well as SNR and reconfiguring.

With these findings, this study advances SNR and digital platform research and provides insights into how to transform SNR into superior performance through DC.

The advantages of applying big data analytics for organizations to boost innovation performance are enormous. By collecting and analysing substantial amounts of data, firms can discern what works for their customer needs and update existing products while innovating new ones. Notwithstanding the evidence about the effects of big data analytics, the link between big data analytics and innovation performance is still underestimated. Especially in today's fast-changing and complicated environments, companies cannot simply take big data analytics as one innovative technical tool without fully understanding how to deploy it effectively.

This study tries to investigate this relationship by building on the knowledge absorptive capacity perspective. The authors conceptualized effective use of big data analytics tools as one general absorptive capacity rather than a simple technical element or skill. Specifically, effectively utilize big data analytics tools can provide values and insights for new product innovation performance in a turbulent environment. Using online survey data from 108 managers, the authors assessed their hypotheses by applying the structural equation modelling method.

The authors found that big data analytics capacity, which can be conceptualized as one absorptive capacity, can positively influence product innovation performance. The authors also found that environmental turbulence has strong moderation effects on these two main relationships.

These results establish big data analytics can be regarded as one absorptive capacity, which can positively boost an organization's innovation performance.

Previous research has indicated that entrepreneurial marketing (EM) positively influences small and medium-sized enterprises’ (SMEs) performance. While most studies have examined the relationship in a stable environment, EMs’ effectiveness during environmental instability remains uncertain. Therefore, the study aims to investigate the influence of EM on Indian manufacturing-based SMEs’ performance during the COVID-19-induced environmental instability. Additionally, it explores the mediating role of innovative performance in the relationship between EM and SME performance.

The data were collected by distributing a structured survey questionnaire to 302 owners/managers of SMEs. Hypotheses were tested using structural equation modeling (SEM).

The result indicates that EM significantly impacts both innovation and SME performance. Furthermore, the innovative performance partially mediates the link between EM and SME performance. The findings suggest that even within severely affected sectors (manufacturing) during the pandemic, SMEs can achieve growth and innovation through effective EM practices.

This study validates the theoretical notion that EM remains effective even in unpredictable environments such as the COVID-19 pandemic. The findings offer valuable insights for SMEs seeking innovative strategies to enhance their performance, particularly those in emerging economies.

Prior studies have relied on a single layer of abstraction to analyze the impact of EM. The present study is the first to extend standard construct (EM) conceptualization. Furthermore, it evaluated the efficiency of EM in situations characterized by instability, which is rare in the EM and SME literature.

This paper examines the dark side of mentoring, its far-reaching effects and organizational interventions for navigating it.

Literature review and narrative analysis are adopted to achieve the objective of the paper.

Review of extant literature highlights the multiple consequences of the dark side of mentoring. Recommendations include specialized training interventions, period appraisals of formal mentoring arrangements, zero-tolerance ethical frameworks and employee assistance programmers.

A substantive portion of literature on mentoring has lauded its benefits for career progression and competitive advantage. This viewpoint explores its limitations and liabilities in an organization.

This paper aims to examine the financial outcome of reverse logistics among firms in a developing country. The authors draw on the organizational information processing theory to propose that analytics capability moderates the relationship between reverse logistics and financial performance.

The authors collected firm-level survey data from 200 manufacturing firms in Ghana, a developing country in sub-Saharan Africa. Partial least squares structural equations modeling is used to examine the proposed relationships, and the moderating effects are further probed using Hayes PROCESS.

The empirical results show that reverse logistics is negatively related to financial performance. However, analytics capability attenuates this negative relationship, such that firms with high analytics capability obtain a positive relationship between reverse logistics and financial performance.

Firms in developing countries should combine their reverse logistics strategies with developing analytics capabilities that help minimize uncertainties and increase the efficient collection and use of information to reduce the cost of reverse logistics.

This paper examines how reverse logistics relates to financial performance in low-resource contexts. Beyond the novelty of the context, it explores the information processing needs of reverse logistics systems and provides empirical data to support analytics capability. This has yet to be considered in prior studies.

The purpose of this study was to examine entrepreneurs’ learning before, during and after entrepreneurial failure and understand the relationship between learning and recovery from failure.

A qualitative multiple case study was carried out based on entrepreneur interviews who have experienced the failure of their businesses.

The study finds that entrepreneurs learn both during the company’s lifespan and post-failure, with distinct types and intensities of learning at different life cycle phases. It highlights the link between learning and emotions during the failure process, revealing entrepreneurs’ limited awareness of their knowledge gaps, particularly during successful business phases, and shows the difference between women and men.

One limitation of this study is that the companies are all located in northern and central Portugal, and the number of entrepreneurs starting new ventures post-failure is limited. Another is a lack of comprehensive measurement of the economic impact, especially on the health of individuals who have experienced the impact of failure. The absence of concrete data hampers understanding and the development of targeted support mechanisms for these individuals.

This study stands out for its unique approach, thoroughly exploring the intricate, profound and significant experiences during a crisis, such as a business failure, from the entrepreneurs’ perspective. It delves into their learning processes before, during and after the failure, providing a comprehensive understanding. This study evidence that significant learning occurs during the operation of the business, and not during or after failure, due to the limitations imposed by the pain and disorientation it causes. Therefore, if recovery does not occur, learning does not happen either. It also highlights the differences between women and men in their learning experiences, adding a new dimension to the research.

This study aims to investigate the influential factors driving customer-oriented constructive deviance (COCD) within the context of the tourism and hospitality industry. Specifically, the authors explore the role of moral emotions as mediators and moral disengagement as a moderator.

In Study 1, the participant pool consisted of 259 frontline service employees hailing from a diverse selection of 54 four- and five-star hotels. Study 2 took an alternative approach, using a scenario-based experiment with 212 participants.

The results reported that organizational injustice toward customers is positively related to other-condemning emotions and leads to COCD. The results also reported that perceived customer citizenship behavior (CCB) positively relates to other-praising emotions, resulting in constructive deviance from customer-oriented. Moreover, these findings support moral emotions and moral disengagement interactions.

This paper shows that an organization’s injustice of external parties, such as customers, may provide important information that employees use to shape their moral emotions (e.g. other condemning emotions) and behavior toward the organization (e.g. COCD). Furthermore, this study confirms that perceived customer citizenship behavior contributes to COCD through other-praising emotions.

There is growing recognition that transformation of healthcare systems towards health and well-being systems requires a continuous learning process. This explorative study aims to gain insight into the experiences with and investment in these learning processes within regional partnerships for health and in what they need to enhance their learning capacity to use the learning for transformation.

17 interviews were held with programme managers, data scientists, trusted advisors and a citizen representative, all involved in the learning process on a regional level in ten Dutch regional partnerships. The interviews were inductively and thematically analysed, focusing on the experiences and perceptions underlying the learning processes.

Regional partnerships invest in learning processes by organizing interactions between different groups of stakeholders and by reflecting on specific themes or on a region-wide level. Difficulty was found in region-wide reflection and in enhancing the learning capacity within the partnerships. Further enhancing the learning capacity required: (1) Investment in (the use of) expertise for translating learning outcomes into concrete action; (2) Leadership for change, underpinned by a shared sense of urgency to learn for transformation and (3) A facilitative environment for change which is both based on facilitative system structures and a basis of trust and commitment to learn and adapt.

The study highlighted the difficulty of learning on a region-wide level and the struggle to apply this learning for transformation. It provides insights into how learning processes and learning capacity can be further improved.

Conceptual and empirical research over the past 20 years has moved the social media (SM) literature beyond the embryotic stage to a well-developed academic discipline. As the lead article in the special issue in the Journal of Research in Interactive Marketing on Cutting-Edge Research in Social Media and Interactive Marketing, this review and agenda article has two key goals: (1) to review key SM and interactive marketing research over the past three years and (2) to identify the next wave of high priority challenges and research opportunities.

Given the “cutting-edge” research focus of the special issue, this review and research agenda paper focused on articles published in 25 key marketing journals between January 2021 and March 2024. Initially, the search request was for articles with “social media, social selling, social commerce” located in the article title, author-selected key words and journal-selected keywords. Later, we conducted searches based on terminology from articles presented in the final review. In total, over 1,000 articles were reviewed across the 25 journals, plus additional ones that were cited in those journals that were not on the initial list.

Our review uncovered eight key content areas: (1) data sources, methodology and scale development; (2) emergent SM technologies; (3) artificial intelligence; (4) virtual reality; (5) sales and sales management; (6) consumer welfare; (7) influencer marketing; and (8) social commerce. Table I provides a summer of key articles and research findings for each of the content areas.

As a literature review and research agenda article, this paper is one of the most extensive to date on SM marketing, and particularly with regard to emergent research over the past three years. Recommendations for future research are integrated through the paper and summarized in Figure 2.

Consumer welfare is one of the eight emergent content areas uncovered in the literature review. Specific focus is on SM privacy, misinformation, mental health and misbehavior.