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Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential of digital transformation (DT) to advance the circular economy (CE). Nonetheless, the empirical substantiation of the connection between DT and CE remains limited. This study seeks to investigate the impact of DT on CE at the organizational level and examine how various institutional factors may shape this relationship within the Chinese context.

To scrutinize this association, we construct a research framework and formulate hypotheses drawing on institutional theory, obtaining panel data from 238 Chinese-listed high-tech manufacturing firms from 2006 to 2019. A regression analysis approach is adopted for the sample data.

Our regression analysis reveals a positive influence of DT on CE performance at the organizational level. Furthermore, our findings suggest that the strength of this relationship is bolstered in the presence of heightened regional institutional development and industry competition. Notably, we find no discernible effect of a firm’s political connections on the DT–CE performance nexus.

This study furnishes empirical evidence on the relationship between DT and CE performance. By elucidating the determinants of this relationship within the distinct context of Chinese institutions, our research offers theoretical and practical insights, thus laying the groundwork for subsequent investigations into this burgeoning area of inquiry.

Among the various applications involving the use of microwave energy, its growing utility within the mining industry is particularly noteworthy. Conventional grinding processes are often overburdened by energy inefficiencies that are directly related to machine wear, pollution and rising project costs. In this work, we numerically investigate the effects of microwave pretreatment through a series of compression tests as a means to help mitigate these energy inefficiencies.

We investigate the effects of microwave pretreatment on various rock samples, as quantified by uniaxial compression tests. In particular, we assign sample heterogeneity based on a Gaussian statistical distribution and invoke a damage model for elemental tensile and compressive stresses based on the maximum tensile stress and the Mohr–Coulomb theories, respectively. We further couple the electromagnetic, thermal and solid displacement relations using finite element modeling.

(1) Increased power intensity during microwave pretreatment results in decreased axial compressive stress. (2) Leveraging statistics to induce variable compressive and tensile strength can greatly facilitate sample heterogeneity and prove necessary for damage modeling. (3) There exists a nonlinear trend to the reduction in smax with increasing power levels, implying an optimum energy output efficiency to create the maximum degradation-power cost relationship.

Previous research in this area has been largely limited to two-dimensional thermo-electric models. The onset of high-performance computing has allowed for the development of high-fidelity, three-dimensional models with coupled equations for electromagnetics, heat transfer and solid mechanics.

This study aims to systematically review the current academic literature on supply chain transparency (SCT) to explore the impact of SCT on firm performance and identify factors that influencing SCT-related practices.

This review follows the six steps and 14 decisions of conducting a systematic literature review (SLR) to comprehensively review 91 identified papers published between 2007 and 2024.

Based on the content analysis of the selected papers, this study summarizes the antecedents, practices, outcomes as well as potential barriers of SCT. We develop a conceptual framework from the descriptive and thematic findings to enrich the relevant aspects of SCT and propose some critical gaps and directions for future research.

This study links SCT with several outcomes of firm performance, with a particular focus on how SCT affects sustainability in terms of its economic, social, and environmental dimensions as well as supply chain resilience. It proposes potential avenues for enriching SCT in future research.

The purpose of this paper is to elaborate the significance of safeguards in digital ecosystems and their role in generating trust among participants. This paper argues that the right mix and number of safeguards are crucial for an ecosystem’s growth and success. It offers ecosystem orchestrators concrete guidelines for how to implement and monitor safeguards.

This research is based on both consulting experience and publicly available information on several digital ecosystems.

This research conceptualizes safeguards as precautionary mechanisms that mandate or promote desirable behavior in an effort to engender trust among ecosystem participants. Safeguards can take various forms, including passwords, escrow, user privacy controls, ratings and reviews and policies and contracts. Striking the right balance of safeguards – neither too few nor too many – is crucial for ecosystem orchestrators. This paper identifies the factors that determine the optimal mix of safeguards, including the power asymmetry between sellers and buyers, the sophistication of participants, the nature of transactions, the cost of negative outcomes and the cost-benefit tradeoff.

To the best of the authors’ knowledge, this study is one of the first to illuminate the relationship between safeguards and trust in the context of digital ecosystem. It is also one of the few attempts to provide managerial guidance for ecosystem designers trying to structure their platform for trust.

As the global community increasingly directs its attention towards sustainable urban development, integrating artificial intelligence (AI) into circular economy (CE) management within smart cities has become a potent strategy. This study aims to examine the potential influence of AI-based technologies on optimizing resources and minimizing waste, which constitute critical components of the principles underpinning the CE. The focus is mainly on applying these technologies within smart city environments. Artificial Intelligence can significantly enhance the processes of gathering, analyzing and decision-making by integrating internet of things (IoT) sensors, data analytics, machine learning algorithms and predictive analytics. This chapter explores the potential of AI in predicting trends, optimizing circular supply chains, improving waste management and recycling practices, facilitating sustainable product design, fostering citizen engagement and aiding policy development. The current research presents a comprehensive examination of the interrelated connection between the principles of CE and the advanced technology of AI. Doing so contributes significantly to our holistic comprehension of how these advancements might collectively influence the development of a more sustainable and resilient future for urban populations.

This study aims to explore psychological safety as a potential moderating mechanism for the relation between functional diversity and individual perceptions of learning, and functional diversity and team performance in self-assembled teams.

To test these relationships, the authors conducted a cross-level, time-lagged, quasi-experiment, using a sample of 143 self-assembled teams. In one condition, participants formed into functionally diverse teams, and in another condition, participants formed functionally homogeneous teams.

Results suggest that functional diversity and psychological safety have an interactive effect on both individual learning and self-assembled team performance, albeit in different directions. Specifically, low psychological safety was more deleterious for individuals on functionally diverse teams than functionally homogeneous teams when it came to perceptions of learning, but the opposite was true when it came to team performance.

The results of this study indicate that it is critical to train team members on developing psychological safety, both in traditional and functionally diverse contexts.

This study aims to explore how source type can influence organizational assets proposed by source credibility theory (SCT) when paired with matched situational crisis communication theory (SCCT) strategies for accidental, preventable, and victim crises. Crisis communication delivered online provides an invaluable outlet for organizations to disperse information to stakeholders quickly. It has been shown that receivers of this information have motivational assumptions about sources having their own agenda for producing content. Thus, it is important to explore how sources tasked with delivering crisis responses can influence perceptions of the sincerity and credibility of the message.

The researchers conducted a 3 (crisis response: matched accidental, matched preventable, matched victim) × 3 (source type: organization, CEO, The New York Times) online between-subjects experimental design (N = 623).

By identifying how the source disseminating crisis responses influences message perceptions, findings from this study recognize how the crisis response is situated in a greater context. Since perceived sincerity and credibility were found to influence message acceptance and reputation, making intentional decisions that acknowledge both within a crisis communication strategy may benefit both future practice and research applications.

The current study advances understandings afforded by SCCT, along with SCT, by experimentally testing the influence of these variables within crisis responses on outcomes such as account acceptance and organizational reputation.

Drawing on the social presence theory, this study aims to explore how supplier–customer social media interactions influence supplier observers’ trust in the customers and what mechanisms contribute to variation in trust experience.

A total of 36 semi-structured interviews were conducted with Chinese suppliers using WeChat for business-to-business interactions. Data were analyzed in three steps: open coding, axial coding and selective coding.

Findings reveal that varied trust is based not only on the categories of social presence of interaction – whether social presence is embedded in informative interactions – but also on the perceived selectivity in social presence. Observer suppliers who experience selectivity during social and affective interactions create a perception of hidden information and an unhealthy relationship atmosphere, and report a sense of emotional vulnerability, thus eroding cognitive and affective trust.

The findings contribute new understandings to social presence theory by exploring the social presence of interactions in a supplier–supplier–customer triad and offer valuable insights into business-to-business social media literature by adopting a suppliers’ viewpoint to unpack the mechanisms of how social presence of interaction positively and negatively influences suppliers’ trust and behavioral responses.