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This paper examines how the level of low-carbon awareness (LCA) affects the remanufacturing strategy in a supply chain with an original equipment manufacturer (OEM) and an independent remanufacturer (IR) competing with each other.

Game theory and operations optimization.

The studies analytically characterize the threshold levels of the LCA in response to which the OEM and the IR will change their remanufacturing strategies from no remanufacturing to partial remanufacturing and then to full remanufacturing. In addition, the studies reveal that as compared with the OEM, the IR has more flexibility in terms of the market entry to remanufacturing with the level of LCA increasing. With the extended studies, it is exhibited that the above findings are robust to a good extent.

It can provide decision support for remanufacturing enterprises.

The purpose of this study is to explore the factors influencing viewers’ engagement intention in travel live streaming (TLS) from a perceived value perspective.

This study used a mixed-methods approach. In Study 1, 48 semistructured interviews were analyzed based on grounded theory and perceived value theory, and a research framework was established to investigate the impact of viewers’ engagement intentions in TLS. In Study 2, partial least squares structural equation modeling (PLS-SEM) was used to empirically validate survey data from 255 TLS viewers.

Through an analysis of the interview content, it was found that the expertise and interaction of the live streamer in TLS as well as the immersion, aesthetics and novelty of the live streaming scene are key influencing factors that affect the engagement of TLS viewers. This finding was confirmed through empirical research.

This research provides practical suggestions for live streamers, TLS platforms and local government to increase viewer engagement. Specifically, it provides methods and directions for the individual improvement of live streamers, further promotes the development and construction of the platform and underscores the importance of government initiatives in policy support and regulatory framework development.

This study focuses on the less-researched field of TLS. Using a mixed-methods approach combining interviews and PLS-SEM, this study explores the key factors that affect the engagement of TLS viewers based on the characteristics of live streamers and live streaming scenes.

Air pollution poses a significant global threat to both human health and environmental stability, acknowledged by the World Health Organization as a leading cause of non-communicable diseases (NCDs) and a notable contributor to climate change. This chapter offers a comprehensive review of the impacts of air pollution on health, highlighting the complex interactions with genetic predispositions and epigenetic mechanisms. The consequences of air pollution to health are extensive, spanning respiratory diseases, cardiovascular disorders, adverse pregnancy outcomes, neurodevelopmental disorders, and heightened mortality rates. Genetic factors play a pivotal role in shaping individual responses to air pollution, influencing susceptibility to respiratory illnesses and the severity of symptoms. Additionally, epigenetic changes triggered by exposure to pollutants have been linked to respiratory health issues, cancer development and progression, and even transgenerational effects spanning multiple generations. As countries, including the UK, pursue ambitious targets for reducing emissions, ongoing research into the complex interplay of air pollution, genetics, and epigenetics is essential. By unravelling the underlying mechanisms and advancing preventive and therapeutic strategies, we can protect public health and promote sustainable environmental practices in the face of this pervasive global challenge.

Previous studies on consumer financial fraud (CFF) have primarily focused on micro-level relationships. This study seeks to provide a holistic macro-level perspective of CFF patterns in the USA. We explore whether CFFs follow a geographical pattern in the USA and evaluate whether and how the patterns and strength of spatial interrelations between states have changed over time, particularly pre-, during and post-COVID-19 Pandemic.

This research investigates the spatial patterns inherent in four CFF variables – total reported frauds, percentage of frauds reporting a loss, total losses and median loss – across the contiguous USA from 2018 to 2022. An in-depth examination was conducted at the state level by applying Moran's I method on the consumer sentinel network data, a database administered by the Federal Trade Commission.

The findings provide robust and statistically significant spatial autocorrelation of four CFF variables across the contiguous USA that are persistent from 2018 to 2022, consistent across all discerned patterns. Moreover, upon aggregating average values over the entire study period, total losses emerge as the dimension displaying the most pronounced positive clustering. Finally, the strength of spatial autocorrelation patterns has increased post-COVID-19 Pandemic for total reported frauds, percentage of frauds reporting a loss and total losses, and it has reduced for the median loss.

The sustained spatial autocorrelation in total losses underscores an elevated interconnectedness in economic and social dynamics among neighboring states. This implies that states in close proximity are predisposed to exhibit analogous levels of total and median losses. This reveals a discernible pattern in the distribution of total losses across contiguous US states, even though the values of total reported frauds and total losses variables were adjusted based on the state population.

The findings furnish valuable insights for policymakers, consumer protection agencies, federal and local government agencies and law enforcement agencies, offering a nuanced understanding and targeted interventions to address the spatial dimensions of CFF effectively. The increase in the strength of the spatial dependencies following COVID-19 shows the increased importance of considering spatial dependencies when designing policies and activities to combat CFF activities. The sustained spatial autocorrelation in total losses underscores an elevated interconnectedness in economic and social dynamics among neighboring states. States in close proximity are predisposed to exhibit analogous levels of total and median losses. This finding reveals a discernible pattern in the distribution of total losses across contiguous US states. To account for state size, the total number of reported frauds and total monetary losses variables were adjusted based on the state's population.

The study provides empirical evidence for spatial autocorrelation for CFF patterns across the states within the contiguous USA. The work shows that adopting a spatial approach to studying CFF offers a promising area for future research.

The purpose of the study was to investigate both the positive and negative effects of workplace loneliness on innovative behavior. By applying the unified theory on contingencies of self-worth, the study aimed to integrate these effects into a single framework, thereby confirming the presence of the double-edged sword effect of workplace loneliness on innovative behavior.

A survey was conducted among enterprises across China, involving 246 employees. Hierarchical regression analysis was utilized to test the moderating hypotheses. Additionally, the mediating effects and the moderated mediation effects were further explored using the bootstrapping method.

The results indicated that workplace loneliness positively influenced innovative behavior through the desire to prove ability, with the promotion regulatory focus enhancing this relationship. Conversely, workplace loneliness negatively influenced innovative behavior through self-handicapping, with the prevention regulatory focus intensifying this relationship.

The findings revealed that workplace loneliness exerts a double-edged effect on innovative behavior. Lonely employees can enhance their sense of self-worth by engaging in domain switching, thereby alleviating feelings of loneliness.

The research confirmed a novel perspective: workplace loneliness can promote innovative behavior by influencing employees’ desire to prove ability. It also revealed the double-edged sword effect of workplace loneliness on innovative behavior. Based on these findings, employees experiencing loneliness can enhance their self-worth and alleviate feelings of loneliness through domain switching.

This study introduces a comprehensive bibliometric analysis of the foreign direct investment (FDI) literature by multinational corporations (MNCs) focusing on emerging economies to identify the most influential authors, journals and articles in FDI research and reveals the fields' conceptual and intellectual structures. The purpose of this paper is to address these issues.

The study analyzed 533 articles published between 1974 and 2020 in 226 academic journals indexed in the Web of Science (WoS) and Scopus databases. We used the R language for statistical computing to map author collaboration, co-word and develop a conceptual and intellectual map of the field.

The results show that, although the FDI literature has many authors, few dominate the field. The International Business Review (IBR) and International Journal of Emerging Markets (IJoEM) are the main sources of the publications. Moreover, bibliometric laws show that our dataset follows the Lotka law of scientific productivity and Bradford law of scattering, identifying the core journals. Finally, FDI by MNCs in emerging economies research is divided into four sub-research themes related to (1) FDI determinants, (2) entry mode, (3) MNCs and FDI performance and (4) the internationalization process.

The current article provides several starting points for practitioners and researchers investigating FDI. It contributes to broadening the vision of the field and offers recommendations for future studies.

A vaccination strategy to cover the susceptible population is key to containing the spread of any virus during a healthcare emergency. This study quantifies the susceptibility of a region based on initial infection rates to prioritize optimal vaccine distribution strategies. The authors propose a metric, the regional vulnerability index (RVI), that identifies the degree of susceptibility/vulnerability of a region to virus infections for strategically locating hubs for vaccine storage and distribution.

A two-phase methodology is used to address this problem. Phase 1 uses a modified Susceptible-Infected-Recovered (SIR) model, ModSIR, to estimate the RVI. Phase 2 leverages this index to model a P-Center problem, prioritizing vulnerable regions through a Mixed Integer Quadratically Constrained Programming model, along with three variations that incorporate the RVI.

Results indicate a weighting scheme based on the population-to-RVI ratio fosters fair distribution and equitable coverage of vulnerable regions. Comparisons with the public distribution strategy outlined by the Government of India reveal similar zonal segregations. Additionally, the network generated by our model outperforms the actual distribution network, corroborated by network metrics such as degree centrality, weighted degree centrality and closeness centrality.

This research presents a novel approach to prioritizing vaccine distribution during pandemics by applying epidemiological predictions to an integer-programming framework, optimizing COVID-19 vaccine allocation based on historical infection data. The study highlights the importance of strategic planning in public health response to effectively manage resources in emergencies.

Wind power is the most promising renewable energy source in China. The development of digital technologies has brought about unprecedented growth opportunities and prospects for wind power. However, the relationship between digital technology adoption and total factor productivity (TFP) in the wind power industry in China has not been empirically assessed. This study aims to clarify whether and how digital technology adoption affects the TFP of the wind power industry in China.

Based on the data of listed companies in the Chinese wind power industry from 2006 to 2021, this study proposes and verifies relevant hypotheses with two-way fixed effects regression models.

The empirical results indicate that digital technology adoption is the cornerstone of the TFP of China’s wind power industry. Reconfiguration capability and technological innovation serially mediate the above relationship. In addition, the incentive effect of digital technology adoption varies among wind power firms. The impact of digital technology adoption is more significant in firms that are old and located in economically undeveloped regions.

This study is one of the earliest attempts to investigate the relationship between digital technology adoption and TFP in the renewable energy sectors of emerging economies. By integrating dynamic capability theory and the analytical framework of “Capability-Behavior-Performance” into the digital context, this study offers the theoretical insights into how digital technology adoption can enhance organizational reconfiguration capability, thereby stimulating technological innovation and subsequent TFP. Additionally, the impacts of different digital technologies are estimated in entirety, rather than in isolation.

This study aims to enhance the effectiveness of knowledge markets and overall knowledge management (KM) practices within organisations. By addressing the challenge of internal knowledge stickiness, it seeks to demonstrate how machine learning and AI approaches, specifically a text-based AI method for personality assessment and regression trees for behavioural analysis, can automate and personalise knowledge market incentivisation mechanisms.

The research employs a novel approach by integrating machine learning methodologies to overcome the limitations of traditional statistical methods. A natural language processing (NLP)-based AI tool is used to assess employees’ personalities, and regression tree analysis is applied to predict and categorise behavioural patterns in knowledge-sharing contexts. This approach is designed to capture the complex interplay between individual personality traits and environmental factors, which traditional methods often fail to adequately address.

Cognitive style was confirmed as a key predictor of knowledge-sharing, with extrinsic motivators outweighing intrinsic ones in market-based platforms. These findings underscore the significance of diverse combinations of environmental and individual factors in promoting knowledge sharing, offering key insights that can inform the automatic design of personalised interventions for community managers of such platforms.

This research stands out as it is the first to empirically explore the interaction between the individual and the environment in shaping actual knowledge-sharing behaviours, using advanced methodologies. The increased automation in the process extends the practical contribution of this study, enabling a more efficient, automated assessment process, and thus making critical theoretical and practical advancements in understanding and enhancing knowledge-sharing behaviours.

Amidst global economic uncertainties, small and medium-sized enterprises (SMEs) are confronted with the pressing need to adapt to complex and ambiguous external landscapes. This study aims to investigate how the decision-making strategies of causation and effectuation are related to the performance of Russian SMEs and whether and how this relationship is moderated by CEO tenure.

Using a sample of 602 Russian SMEs, hierarchical linear modeling and its estimation using ordinary least squares is conducted. Robustness checks and post hoc analysis are performed.

The findings provide insights into effectuation theory by looking at and testing its basic tenets in an underexplored context and investigating the direct and moderated effects of causation and effectuation on SME performance. Moreover, the study builds upon upper-echelons theory (UET) by considering CEO tenure – an individual-level characteristic – as a moderator in the effectuation/causation and SME performance relationship. A framework for understanding how executives’ attributes shape organizational strategies and outcomes is provided.

The findings contribute to effectuation theory by testing its core principles in emerging market context, examining both direct and moderated effects of causation and effectuation on SME performance. Moreover, the study builds upon upper-echelons theory (UET) by considering CEO tenure – an individual-level characteristic – as a moderator in the effectuation/causation and SME performance relationship. This study offers a framework for understanding how executive characteristics shape organizational strategies and outcomes in emerging markets.