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The authors study how cloud adoption decision making unfolds in organizations and present the dynamic process leading to a decision to adopt or reject cloud computing. The authors thus complement earlier literature on factors that influence cloud adoption.

The authors adopt an interpretive epistemology to understand the process of cloud adoption decision making. Following an empirical investigation drawing on interviews with senior managers who led the cloud adoption decision making in organizations from across Europe. The authors outline a framework that shows how cloud adoptions follow multiple cycles in three broad phases.

The study findings demonstrate that cloud adoption decision making is a recursive process of learning about cloud through three broad phases: building perception about cloud possibilities, contextualizing cloud possibilities in terms of current computing resources and exposing the cloud proposition to others involved in making the decision. Building on these findings, the authors construct a framework of this process which can inform practitioners in making decisions on cloud adoption.

This work contributes to authors understanding of how cloud adoption decisions unfold and provides a framework for cloud adoption decisions that has theoretical and practical value. The study further demonstrates the role of the decision-leader, typically the CIO, in this process and identifies how other internal and external stakeholders are involved. It sheds light on the relevance of the phases of the cloud adoption decision-making process to different cloud adoption factors identified in the extant literature.

The shift toward a circular economy (CE) represents a collaborative endeavor necessitating the presence of efficient frameworks, conducive contexts and a common comprehension. This research serves as a pivotal stride towards this goal, presenting an exclusive prospect for the investigation and fusion of these frameworks, with particular emphasis on the Quintuple Helix Model (5HM), into a unified theoretical framework that underscores the core principles of the CE. This study is centered on three pivotal questions aimed at decoding the CE transition in specific regional settings.

Adopting an abductive approach firmly anchored in a two-stage qualitative process, this study specifically merges the foundational principles from institutional theory, entrepreneurship literature and CE frameworks to provide insights into the dynamics of circular ecosystems, with a specific focus on the Huelva region in Spain.

The findings demonstrate significant potential in the CE, ranging from the integration of product and service systems to innovations in eco-industrial practices. Yet, a notable deficiency exists: the absence of institutional entrepreneurs, highlighting the essential role that universities can play. As recognized centers of innovation, universities are suggested to be key contributors to the transformation toward a CE, aligning with their societal and economic responsibilities.

This study highlights the importance of managing relationships with entities like SMEs and policymakers or academia for effective CE adoption. Policymakers can refine strategies based on the research’s insights, while the impact of university-driven circular ecosystems on sustainable societies is another crucial area for research.

The sustainability models cited in CE literature may not be comprehensive enough to prevent problem shifting, and it can be argued that they lack a sound theoretical and conceptual basis. Furthermore, the connections between sustainability objectives and the three levels of the CE operating system remain vague. Additionally, there is insufficient information on how regions foster the involvement of the environment in fivefold helix cooperation and how this impacts the CE.

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.

The competition in the academe has always been tough, but today, the academe seems to be more like an industry than an academic community as academics are evaluated through quantified and economic means.

This article leans on Heidegger’s thoughts on the essence of technology and his ontological view on being to show the dangers that lie in this quantification of researchers and research.

Despite the benefits that information systems (ISs) offer to people and research, it seems that technology has made it possible to objectify researchers and research. This has a negative impact on the academe and should thus be looked into especially by the IS field, which should note the problems that exist in its core. This phenomenon of quantified academics is clearly visible at academic quantification sites, where academics are evaluated using metrics that count their output. It seems that the essence of technology has disturbed the way research is valued by emphasising its quantifiable aspects. The study claims that it is important to look for other ways to evaluate researchers rather than trying to maximise research production, which has led to the flooding of articles that few have the time or interest to read.

This paper offers new insights into the current phenomenon of quantification of academics and underlines the need for critical changes if in order to achieve the academic culture that is desirable for future academics.

This paper aims to study the role of artificial intelligence (AI) agents in creating a climate of inclusion for people with special needs in the higher education sector (HES).

A qualitative methodology is used in this research that is mainly based on semistructured interviews conducted with the top ten universities in Lebanon with deans, information technology managers, professors and administrative officers.

This paper highlights findings related to the current status of the higher education institutions (HEIs) in Lebanon vis-à-vis their accreditation and quality assurance processes in accommodating and creating a climate of inclusion for people with special needs. The results show the important role of AI agents in aiding HEI in creating such a climate of inclusion for people with special needs.

The study sheds light on existing gaps in the literature related to creating a climate of inclusion for people with special needs in HEI. Additionally, there is yet a lack of research that focuses on the role of AI technology in general and AI agents in particular in fostering a climate of inclusion for people with special needs within the HES.

The primary objective of this chapter is to synthesize and organize prevailing theoretical perspectives on metacognition into a framework that can enhance understanding of metacognitive phenomena, with the aim of stimulating future research in the field of organizational behavior and human resources management (OBHRM). The author starts with a review of the history of metacognition research, distinguishing it from related theoretical constructs such as cognition, executive function, and self-regulation. Following this, the author outlines five constituent elements of metacognition – metacognitive knowledge, metacognitive experiences, metacognitive monitoring, a dynamic mental model, and metacognitive control – with discussions on their interrelationships and respective functions. Two approaches to metacognition, a process approach and an individual-difference approach, are then presented, summarizing key questions and findings from each. Finally, three broad directions for future research in OBHRM are proposed: examining metacognitive processes, considering mechanisms beyond learning to explain the effects of metacognition, and exploring both domain-specific and general metacognitive knowledge and skills. The implications of these research directions for personnel and human resources management practices are discussed.

Wage employees enter self-employment either directly or in a staged manner and may subsequently undertake multiple stints at self-employment. Extant research on the relationship between entry modes and the persistence and outcomes of self-employment is inconclusive. This study investigates the relationship between wage employees’ initial mode of entry into self-employment and the duration of the subsequent first two stints of self-employment.

This study used a matched longitudinal sample of 9,550 employees who became majority owners of incorporated firms from 2005 to 2016.

The findings demonstrate that the initial mode of entry into self-employment matters for the first two stints at self-employment. Staged entry into self-employment was associated with a shorter first stint and became insignificant for the second stint. Staged entry into self-employment was positively related to the odds of becoming self-employed for the second time in the same firm.

Using a comprehensive and reliable dataset, the paper shifts focus from the aggregated onward journey of novice entrepreneurs (survival as the outcome) to the duration of their self-employment stints. By doing so, the paper offers insights into the process of becoming self-employed and the patterns associated with success/failure in entrepreneurship associated with self-employment duration.

This chapter examines three common fintech use cases transforming the financial industry. First, the chapter introduces fintech's role in enhancing financial services and promoting financial inclusion, especially through digital platforms. Second, it investigates various fintech applications that support financial institution management by harnessing the power of artificial intelligence (AI) and machine learning (ML). Finally, the chapter explores fintech use cases related to the regulatory environment, including regulatory technology (regtech), blockchain technology, and cryptocurrencies. The insights presented in this chapter cater to researchers and practitioners keen on better understanding fintech's diverse applications in the ever-evolving financial industry landscape.

This paper aims to analyze the impact of green people management (GPM) practices on the development of organizational competencies for sustainability in Brazilian publicly traded companies.

To validate the proposed model and hypotheses, a quantitative-descriptive methodological strategy was adopted, empirically investigated through a survey with publicly traded companies listed on B3 S.A. (Brazil, Stock and Exchange). The collected data were analyzed using exploratory factor analysis and multiple linear regression.

The results indicate that green ability has a positive impact on the development of strategic and systemic competence for sustainability. Green motivation has a negative impact on the development of systemic and economic competencies for sustainability. Green opportunity positively impacts the development of strategic, systemic and economic competencies for sustainability.

In terms of academic contributions, this study allowed for an empirical and comprehensive evaluation of variables related to GPM practices and their impact on the development of organizational competencies for sustainability, in line with the research agenda of the management field, focusing on outcomes for individuals (employees) and organizations.

The identification and possible implementation of certain GPM practices as a way to boost recruitment, selection, evaluation, rewards, recognition and involvement of individuals with green values and objectives, minimizing environmental and societal impacts, represent the main managerial and social contribution.