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While size asymmetry in buyer–supplier relationships has been studied in non-disruption contexts, this research explores how supplier size influences positive and negative supply chain disruptions. Anchoring on the commitment-trust theory (CTT), we explore buyer commitment as a mediating variable and examine how buying firms' mediated power usage depends on different supplier sizes and types of supplier-induced disruptions.

Through two scenario-based behavioral experiments, we discover different patterns in buyers' use of mediated power, contingent on the types of supplier-induced disruptions.

In negative disruptions, buyers prefer more mediated power with large suppliers to control uncertainties, using reward or coercive power strategies. In positive disruptions, we find opposite results, indicating different buyers' perceptions and actions are contingent on both the supplier size and the types of disruptions. These findings underscore the complex interplay between supplier size, buyer commitment and mediated power strategies, revealing that disruption type significantly shapes buyer responses.

This paper extends the CTT framework by considering new antecedents and outcomes. We also provide a more comprehensive understanding of buyer behavior when facing positive and negative supplier-induced disruptions. Our study has limitations. Through vignette-based behavioral experiments, there is a risk that scenarios may not accurately represent real-life situations and that decision-making dynamics could be oversimplified. Future research should incorporate nuanced measurements and conduct additional qualitative research for a comprehensive understanding.

This study enriches the understanding of the buyer-supplier relationship by expanding the CTT framework for a more comprehensive picture. We also offer nuanced insights into size dynamics and disruption types, emphasizing tailored strategies in supply chain management. The findings underscore the importance of understanding these nuances to employ tailored strategy in a business-to-business (B2B) context, as mediated power is contingent on multiple factors.

The rule of law has been tried in many countries under the state of exception during COVID-19. This chapter focusses on the case of Finland, the only Nordic country to declare a state of exception during the pandemic. Drawing from theoretical accounts on the state of exception, it analyses to what extent the Finnish democratic Rechtsstaat has coped in the state of exception.

The authors propose the concepts of a radical and restrained state of exception and argue that while the Finnish states of exception were rather restrained than radical, there are risks involved in the fact that powers granted by the Emergency Powers Act to be used during a state of exception are moved to normal legislation. Indeed, as Giorgio Agamben, among others, has warned, the state of exception may become permanent and undermine democracy and the rule of law. The chapter provides a dialogue between theory and empirics related to a state of exception, applying theoretical insights on the case of Finland during COVID-19.

This study aims to establish a comprehensive framework for adopting mobile-based artificial intelligence (AI) services in Tanzanian manufacturing small and medium enterprises (SMEs).

The methodology involved conducting a literature review and using the combination of Mobile Services Acceptance Model and Innovation Diffusion Theory (IDT) as a theoretical foundation. This synthesis delves into the current knowledge on technology adoption, organizational behavior and innovation diffusion, creating a solid conceptual basis. Expert review was used for framework validation to ensure the framework's accuracy.

This study shows that the factors influencing the adoption of mobile-based AI services in Tanzanian manufacturing SMEs include perceived usefulness, perceived ease of use, context, personal initiatives and characteristics, trust, infrastructure, cost, mobility, power distance, compatibility, observability and trialability.

The framework provides valuable insights tailored to Tanzanian sociocultural and economic nuances. However, its generalizability is limited due to its specificity to Tanzanian manufacturing SMEs.

The framework outlined in this research provides SME leaders, policymakers and technology implementers with valuable guidance to make informed decisions during the adoption process.

This study introduces a novel lens for understanding technology adoption. This study's focus on the Tanzanian context and its nuanced examination of contributing factors add to its originality and practical significance.

HRM decentralization and devolution have been highlighted as key HRM processes in organizations’ quest for increased flexibility. Although they have been extensively studied in the MNC and International HRM literature, they have mainly been examined on a separate basis, and their definition and operationalization have often been confused. Thus, we first clarify the difference between the two concepts by refining the definitions by Hoogendoorn and Brewster (1992), and then empirically examine how they are related.

The relationship between HRM decentralization and devolution is examined by means of a survey in a large multi-country sample of multi-unit organizations.

Regarding our clarification objective, we contend that devolution has to do with who takes responsibilities for HRM (i.e. line managers or HRM professionals) while decentralization refers to where HRM responsibilities are allocated (i.e. headquarters or increasingly local units). Regarding the relationship between the two concepts, the results show that higher levels of HRM decentralization are related to higher levels of devolution, but this association is attenuated in organizations with more powerful HRM departments.

The study contributes to theory and practice by disentangling, at the conceptual, operational, empirical and practical levels, two different but related HRM decisions (how much to devolve and how much to decentralize HRM) that organizations must make to efficiently cope with the characteristics of their own structure and competitive environment. It highlights the role of the relative power of HRM departments in how HRM responsibilities are ultimately distributed across the organization.

This paper explains why some firms manage to capture disproportionate value from their network of relationships, leading to superior performance. The paper examines how a firm's dependencies affect its value appropriation potential (VAP) in economic networks.

The paper follows the axiomatic method and the embeddedness perspective of firms to develop an index called nodal power, which captures the power that accrues to a firm in exchange-based economic networks. Thereafter, using the formal method and simulation, it shows nodal power reflects a firm's VAP in economic networks.

The study analysis and findings prove that a firm's dyadic level exchange relations and the embedded network structure determine its VAP by affecting the nodal power. A firm with lesser nodal power is likely to appropriate less value from its relations even if it equally contributes to the value creation. This finding explains how the structural and relational characteristics of a firm's network enable disproportionate value appropriation.

Nodal power furthers the scope of analyzing firms' economic relationships and changing power equations in dynamic networks. It can help firms build optimal strategic networks and manage the portfolio of relationships by predicting the impact of changing relations on firms' VAP.

The paper's original contribution is to explain, through formal analysis, why and how the structure and nature of relations of firms affect their VAP. The paper also formalizes the power-dependence principle through a dependency-based index called nodal power and uses it to show how interfirm dependencies are key to value appropriation.

By focussing on the anticipated emotional reactions of volunteers and drawing on theories of motivation and identity, this study investigates how volunteers react to different options of the entrepreneurial model of Amigos for Children Foundation (ACF). The paper proposes a hypothetical model for volunteer’s emotional reactions to potential business model changes. We suggest the relative importance of intrinsic motivational factors, professional identity and attitudes towards business organisations as mediating variables. ACF works exclusively with university students as volunteers, so their specific characteristics may limit some of the conclusions and propositions of this qualitative research, but public policy consequences of supporting similar entrepreneurial transitions can be generally relevant.

Based on the qualitative analysis of semi-structured interviews with volunteers of ACF, a Hungarian non-profit organisation, we explore the challenges of transitioning into a social enterprise.

Previous research showed controversial results about the impact of pay on the motivations of volunteers. For a non-profit organisation that would like to utilise the competencies of its volunteers, introducing a market-based service may mean additional financial resources and the potential loss of human resources. Understanding the moderating factors of volunteers' reactions might help build better theories for managing the non-profit-social enterprise transition and designing public policies to support scaling up the impact of successful social purpose organisations.

For practitioners, the research underlines the importance of participatory mechanisms in volunteer management. By managing transitions better, non-profit organisations can expand their social impact by acquiring more financial resources through market-based activities closely related to their original activities and keeping their volunteers. The study elucidates the relevance of the crowding-out effect and indicates some hypothetical moderating variables influencing its potential degree.

Unmanned aerial vehicles (UAVs), known for their exceptional flexibility and maneuverability, have become an integral part of mobile edge computing systems in edge networks. This paper aims to minimize system costs within a communication cycle. To this end, this paper has developed a model for task offloading in UAV-assisted edge networks under dynamic channel conditions. This study seeks to efficiently execute task offloading while satisfying UAV energy constraints, and validates the effectiveness of the proposed method through performance comparisons with other similar algorithms.

To address this issue, this paper proposes a task offloading and trajectory optimization algorithm using deep deterministic policy gradient, which jointly optimizes Internet of Things (IoT) device scheduling, power distribution, task offloading and UAV flight trajectory to minimize system costs.

The analysis of simulation results indicates that this algorithm achieves lower redundancy compared to others, along with reductions in task size by 22.8%, flight time by 34.5%, number of IoT devices by 11.8%, UAV computing power by 25.35% and the required cycle for per-bit tasks by 33.6%.

A multi-objective optimization problem is established under dynamic channel conditions, and the effectiveness of this approach is validated.

This study problematizes the prevailing normative and managerial-dominated view of self-initiated employee ambassadorship on social media from a power perspective. The aim is to provide a more nuanced and critical understanding of the negative aspects of this phenomenon.

The empirical material encompasses qualitative interviews with employees from 14 organizations and Foucault’s concept of disciplinary discursive power to analyze which and how discourses exert power over employee communication on social media and what role visibility plays in it.

This study indicates that employee ambassadors’ social media communication is governed by two discourses that create complex tensions, where ambassadors constantly must negotiate between self-branding requirements and an authenticity paradox. These tensions intensify through visibility on social media, where employees strategize and situationally silence their communication through self-monitoring and self-surveillance practices. Conclusively, the findings also outline the need for further critical research to offer a deeper understanding of power relations that influence the communication practices of organizational members.

The paper contributes to a more nuanced understanding of self-initiated employee ambassadorship on social media and highlights disciplinary power relations that go beyond organizational borders.

The findings underscore that organizations need to address the critical aspects of self-initiated employee ambassadorship and act as facilitators to support employees in their navigation process.

This paper contributes a new critical power perspective on employee ambassadorship on social media.

Albeit gradual and uneven, the emergence of social and environmental reporting by publicly held corporations has been a major development in the last few decades. This paper aims to explore patterns of the emergence of these disclosures. Using an institutional theory lens, this paper considers mimetic, normative and coercive possibilities.

US publicly traded company data from 2013 to 2019 is used to test the hypotheses. Mimetic forces are proxied with corporate board interlock frequency. Normative ones use the extent of gender diversity on corporate boards. Measures of business climate and industry regulatory sensitivity proxy coercive potentiality.

Studied in isolation, each of the three forces through which organizations pursue the heightened legitimacy of enhanced environmental and social disclosures has credibility. The strongest support exists for mimetic and normative mechanisms, perhaps because the US government has been reluctant to make these expanded disclosures mandatory.

In the world of voluntary action, more attention to diffusion is needed. For these purposes, better proxies will be needed to study change. Social and environmental information should be separated for individual analysis.

At least in the USA, companies are attentive to what other companies are doing. There is something to be said for the ethical dimension of corporate transparency.

Governmental action in this area has not been effective, at current levels. Corporate leadership is essential. Critical information is shared about disclosure by board members.

Although institutional theory makes several appearances in this area, to the best of the authors’ knowledge, the current study is the first empirical archival study to examine the three forces simultaneously, providing evidence as to the relative magnitude of each institutional force on environmental and social disclosures. Should these disclosures not be mandated by government, this study shows pathways for enhanced disclosures to continue to spread.

Deep learning (DL) is on the rise because it can make predictions and judgments based on data that is unseen. Blockchain technologies are being combined with DL frameworks in various industries to provide a safe and effective infrastructure. The review comprises literature that lists the most recent techniques used in the aforementioned application sectors. We examine the current research trends across several fields and evaluate the literature in terms of its advantages and disadvantages.

The integration of blockchain and DL has been explored in several application domains for the past five years (2018–2023). Our research is guided by five research questions, and based on these questions, we concentrate on key application domains such as the usage of Internet of Things (IoT) in several applications, healthcare and cryptocurrency price prediction. We have analyzed the main challenges and possibilities concerning blockchain technologies. We have discussed the methodologies used in the pertinent publications in these areas and contrasted the research trends during the previous five years. Additionally, we provide a comparison of the widely used blockchain frameworks that are used to create blockchain-based DL frameworks.

By responding to five research objectives, the study highlights and assesses the effectiveness of already published works using blockchain and DL. Our findings indicate that IoT applications, such as their use in smart cities and cars, healthcare and cryptocurrency, are the key areas of research. The primary focus of current research is the enhancement of existing systems, with data analysis, storage and sharing via decentralized systems being the main motivation for this integration. Amongst the various frameworks employed, Ethereum and Hyperledger are popular among researchers in the domain of IoT and healthcare, whereas Bitcoin is popular for research on cryptocurrency.

There is a lack of literature that summarizes the state-of-the-art methods incorporating blockchain and DL in popular domains such as healthcare, IoT and cryptocurrency price prediction. We analyze the existing research done in the past five years (2018–2023) to review the issues and emerging trends.