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Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

This study aims to shape the future trajectory of scholarly research on traditional, reputational and societal supply chain risks and their management.

The research uses a narrative literature review of the overview type. To control bias stemming from the subjectivity of the methodology, the authors synthesized the relevant literature transparently and established various safeguarding procedures.

The established research stream on traditional supply chain risk has generated a wealth of concepts that can potentially be transferred to the study of reputational and societal risks. The maturing research stream on reputational risks has mostly focused on risk manifestation, from the upstream perspective of the focal firm. The emerging scholarship on societal supply chain risks has anecdotally highlighted detrimental effects on contextual actors, such as society-at-large.

This study shifts scholarly attention to the role of the context in the risk manifestation process – as a potential risk source for traditional supply chain risk, during the risk materialization for reputational supply chain risk, and as the locus of the risk effect for societal supply chain risk.

This review is unique in that it fosters a holistic understanding of supply chain risk and underscores the increased importance of the context for it. The socioeconomic, institutional and ecological contexts connect the three reviewed research streams. Detailed research agendas for each literature stream are developed, comprising 23 topical areas in total.

COVID-19 has caused critical supply chain problems, especially in sustainable supply chain management, but very few empirical studies have been explored how to improve the firm sustainability through supply chain endeavours such as supply chain agility to manage the impacts of COVID-19. This paper aims to develop a model to incorporate supply chain agility and supply chain relationships that link firm sustainability to mitigate the impacts of the pandemic.

The authors conducted an online survey and collected 203 valid responses from businesses in the United Arab Emirates, and employed an exploratory factor analysis, mediated regression analysis and structural equation modelling methodology to test the models and hypotheses.

The authors find that the adoption of supply chain agility can improve supply chain relationships and positively impact sustainability. Meanwhile, supply chain relationships partially mediate the relationship between supply chain agility and sustainability. In addition, sustainability mitigates the impacts of COVID-19 pandemic on supply chains.

The results provide fruitful insights and implications for the challenges and uncertainties caused by the pandemic post COVID-19 and provide several directions for further research.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

This paper explores sustainability within supply chain management and its link towards resilience through the lens of ethics. The wicked problem of sustainability impacts supply chains and society at large, and the ability of supply chains to remain viable in the future is based on the sustainability of business practices. The paper argues that a substantive proportion of sustainability mechanisms (such as the Triple Bottom Line approach and codes of conducts) can be viewed within the ethical paradigm of deontology, whereby the morality of an action is based on adherence to rules. However, there are numerous critiques of such approaches and their success in creating more sustainable practices. Therefore, the paper proposes there is a need for systems thinking approaches to be incorporated into the exploration of the link between ethics, sustainability and supply chain resilience. Using two examples of social sustainability issues in Australia – modern slavery legislation and horticultural ¹ worker exploitation – the paper demonstrates the utility of various systems thinking methodologies to explore the complexity of these issues. The paper sets out a conceptual call to arms for researchers and practitioners to apply a holistic lens towards how the morality of actions is shaped and influences supply chain sustainability practices.

Mindfulness-based interventions are on the rise in workplace settings to enhance Well-Being and address work stress. Their popularity is in part due to the fact that they are often assumed to have a net positive impact on both workers’ Well-Being and organizational functioning. However, the majority of workplace mindfulness practice and research focuses on individual-level mindfulness interventions and their associated outcomes, like reduced stress. However, the modern workplace is highly dependent on positive team functioning, and the impact of mindfulness in teams is lesser known. This review differentiates individual mindfulness from team mindfulness and explores how both individual and team mindfulness impact team functioning. The authors review mindfulness and teams’ literature to understand antecedents, correlated mediators, and consequences of mindfulness in team contexts, team processes, and the boundary conditions related to mindfulness outcomes. This review adds to the budding theoretical conversation regarding mindfulness at work and contributes valuable insight into the practical applications of mindfulness in teams.

This study aims to identify the enablers of supply chain resilience (SCR) through a literature review and expert panel input in the context of Pakistan and the post-pandemic era. This study also aims to categorize and rank the identified enablers using expert panel input.

A review of the extant literature was conducted to investigate and identify the factors that contribute to SCR. The relative ranking of the enablers was carried out by a group of industry and academic experts. The expert panel was convened to compare the main categories and each enabler in pairs and to score the enablers using triangular fuzzy numbers.

This study identified 16 critical SCR enablers. Using the fuzzy analytic hierarchy process (AHP), these enablers were divided into three groups and analyzed. The results show that financial enablers, technology enablers and then social enablers are prioritized when it comes to SCR in emerging markets. The robustness of the ranking of enablers is tested through sensitivity analysis.

The results shall be helpful for policymakers and managers to understand the important enablers and also help allocate resources to important enablers. Managers will be able to formulate strategies to achieve SCR in an uncertain environment.

This is one of the first attempts to identify and rank the enablers of SCR in an emerging economy context.

Sustainable development is inseparable from rational and responsible use of resources and promotion of green entrepreneurship. The contemporary green development agenda encompasses climate, economic, technical, social, cultural, and political dimensions. International efforts to greening the global development are conducted by the major economies, including China as the world’s largest consumer of energy and the biggest emitter of greenhouse gases. China is aware of its environmental problems, as well as of its part of the overall responsibility for the accomplishment of the sustainable development goals. By means of the decarbonization efforts, the latter are integrated both into the national development agenda (the concept of ecological civilization) and China’s international initiatives (the greening narrative within the Belt and Road Initiative). Over the past decade, China has made a breakthrough on the way to promoting green entrepreneurship and greening of its development (better quality of air and water, renewable energy, electric vehicles, and organic farming). On the other hand, emissions remain high, agricultural land loses productivity, and freshwater resources degrade due to climate change. In conventional industries (oil, coal mining, and electric and thermal energy), decarbonization faces an array of impediments. In this chapter, the authors summarize fundamental provisions of China’s approach to building an ecological civilization and measures to reduce emissions and achieve the carbon neutrality status within the nearest decades. The analysis of obstacles to the decarbonization of the economy and possible prospects for the development of green entrepreneurship summarizes China’s practices for possible use in other countries.

This chapter explores the ethical challenges arising from the integration of advanced artificial intelligence (AI) technologies into intelligent manufacturing systems. Machine learning (ML), augmented reality/virtual reality (AR/VR), digital twins, and human–robot collaboration (HRC) redefine industrial production, they bring forth unprecedented efficiencies and capabilities but also introduce complex ethical considerations. The text delves into issues such as data privacy, job displacement, the impact of automation on workforce dynamics, and the psychological effects of working alongside AI-powered systems. Through a detailed examination of these technologies and their implications, the chapter advocates for a dynamic ethical framework that evolves alongside technological advancements. This framework should prioritize human dignity, safety, and rights, involving all stakeholders in its development and implementation. By addressing the ethical implications of AI, AR/VR, digital twins, and HRC, the chapter underscores the necessity of balancing technological innovation with ethical responsibility. It calls for collaborative efforts involving policymakers, industry leaders, workers, and consumers to navigate the ethical landscape of intelligent manufacturing, aiming to harness the potential of these technologies responsibly for the betterment of society and the workforce.