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This study aims to examine how environmental, social and governance (ESG) initiatives and ISO 14001, which is an internationally agreed standard to set out the requirements for an environmental management system, affect firm performance in the context of the Industry 4.0 supply chain.

The authors develop a new chance-constrained network data envelopment analysis (DEA) in the presence of non-positive data to estimate innovation, operational and profitability performances for three main relation groups (suppliers, partners and customers) in Microsoft's supply chain.

Results of this study show the following: (1) the application of ISO 14001 will reduce profitability but increase overall performance (OP); (2) ESG implementation has a convex U-shaped influence on profitability and OP, which means that firms will benefit when ESG investment goes beyond a particular level; (3) the nonlinear U-shape is presented in the E and G components, but not in the S of the individual ESG initiatives, and (4) only specific subcomponents of S and G in the subcomponent of individual ESG initiatives are nonlinearly connected to OP. Research's results reveal that the customer group has a higher performance value than the other two groups, which suggests that this group will create competitive advantages for Microsoft.

Overall, the authors provide an insightful viewpoint into supply chain management by examining the ESG initiatives, ISO 14001 and performances of Microsoft's supply chain.

This study aims to improve detection efficiency of fluorescence biosensor or a graphene field-effect transistor biosensor. Graphene field-effect transistor biosensing and fluorescent biosensing were integrated and combined with magnetic nanoparticles to construct a multi-sensor integrated microfluidic biochip for detecting single-stranded DNA. Multi-sensor integrated biochip demonstrated higher detection reliability for a single target and could simultaneously detect different targets.

In this study, the authors integrated graphene field-effect transistor biosensing and fluorescent biosensing, combined with magnetic nanoparticles, to fabricate a multi-sensor integrated microfluidic biochip for the detection of single-stranded deoxyribonucleic acid (DNA). Graphene films synthesized through chemical vapor deposition were transferred onto a glass substrate featuring two indium tin oxide electrodes, thus establishing conductive channels for the graphene field-effect transistor. Using π-π stacking, 1-pyrenebutanoic acid succinimidyl ester was immobilized onto the graphene film to serve as a medium for anchoring the probe aptamer. The fluorophore-labeled target DNA subsequently underwent hybridization with the probe aptamer, thereby forming a fluorescence detection channel.

This paper presents a novel approach using three channels of light, electricity and magnetism for the detection of single-stranded DNA, accompanied by the design of a microfluidic detection platform integrating biosensor chips. Remarkably, the detection limit achieved is 10 pm, with an impressively low relative standard deviation of 1.007%.

By detecting target DNA, the photo-electro-magnetic multi-sensor graphene field-effect transistor biosensor not only enhances the reliability and efficiency of detection but also exhibits additional advantages such as compact size, affordability, portability and straightforward automation. Real-time display of detection outcomes on the host facilitates a deeper comprehension of biochemical reaction dynamics. Moreover, besides detecting the same target, the sensor can also identify diverse targets, primarily leveraging the penetrative and noninvasive nature of light.

Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.

This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.

This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.

It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.

This study investigates the heterogeneous impact of R&D capital market distortions (CMDs) on the quantity and quality of innovation in Chinese firms by exploring key pathways from a dual-arbitrage perspective.

Using data from Chinese A-share listed companies (2015–2021), we employ a multidimensional fixed effects model to validate the research hypotheses. Under the Systems of National Accounts (SNA, 2008) framework, we use the Bureau of Economic Analysis method to estimate enterprise R&D capital stock and the Cobb-Douglas production function to estimate R&D CMDs.

Results show that R&D CMDs drive firms toward strategic innovation, emphasizing quantity over quality. Policy arbitrage, including policy catering and rent-seeking, emerges as a pivotal mechanism under R&D CMDs, encouraging firms to prioritize quantity over quality in innovation. High-technology firms and those in the decline stage are more inclined to spearhead strategic innovation within the context of R&D CMDs.

These findings help policymakers promote high-quality innovation in Chinese enterprises by enhancing patent review mechanisms and shifting policies from quantity-driven to quality-oriented goals.

This study enriches the research on factor market distortions and innovation in emerging markets from the perspective of R&D CMDs, based on the “emerging + transitional” comprehensive framework. Unlike previous studies, which generally use enterprise R&D expenditure flow data, we apply the theory of R&D capitalization accounting to the micro-enterprise level under the SNA (2008) framework, enhancing the accuracy of R&D CMD estimations.

The principal purposes of the research are to empirically investigate three forms of perceived overload on social media and shed light on their associations with users’ passive usage intention by contemplating the mediating influence of social network exhaustion and discontented feelings.

This study employed a cross-sectional methodology to collect statistical data (N = 679) from WeChat users in mainland China. Primitive analysis, confirmatory factor analysis and structural equation modeling were employed to test the corresponding hypotheses.

The findings reveal that three dimensions of perceived overload influence social network exhaustion positively. In addition, communication overload and system feature overload exert positive impacts on the discontented feeling. Furthermore, it is uncovered that social network exhaustion and discontented feeling are related to passive usage intention positively.

Theoretically, this paper offers a conceptual framework to explicate passive usage intention through elucidating social network exhaustion and the discontented feeling that arises from perceived overload in contemporary social media-mediated environments. Practically, the current research has certain realistic implications for WeChat users and SNS operators.

Probing what triggers people’s passive usage intention of social media has been an emerging theme in recent years, yet there is a dearth of discourse that delves into the antecedents of WeChat users’ passive usage intention. The results obtained from the study have enhanced the understanding of the adverse consequences associated with the utilization of social media in mainland China.

Service providers and tourism players have introduced the green hotels concept to mitigate detrimental environmental impact. This study aimed to review the literature on green hotels based on bibliometric analysis.

In analyzing the potential and significant subject of the tourism industry and concern on environmental issues, this study evaluates the themes based on the past, present and future trends in green hotels from a bibliographic database retrieved from the Web of Science (WoS).

Several themes were identified from the role of the theory of planned behavior and predictors of consumers' intention to visit green hotels.

Implications were discussed mainly related to green hotels contribution towards sustainable tourism and its role in shaping the tourism sector's landscape. Among the practical implications include rewards by the authorities in the form of incentives or tax relief to green hotel operators, which will encourage conventional hotel transformation into green hotels. Furthermore, green hotels will be at the forefront of tourism and hospitality brands, requiring substantial green marketing initiatives. Sooner or later, opting for green hotels while traveling will be the norm among travelers.

The green hotels have emerged as a way to tackle the environmental issues related to tourism and hospitality while at the same time, allowing the industry to flourish. This research is one of the scant studies that provide a comprehensive overview about green hotel studies and offer future research agendas.

This study examines the interplay between media-induced emotional crisis framing (anger vs sadness) and message sidedness of crisis response on publics’ attribution of crisis responsibility as well as subsequent company evaluation and supportive behavioral intention.

A 2 (emotion: anger vs sadness) x 2 (crisis response: one-sided vs two-sided) online experiment was conducted among 161 participants in the USA.

Results showed that anger-inducing media framing of the crisis elicited higher levels of crisis responsibility attribution and more negative company evaluation, compared with sadness-inducing media framing. One-sided message response was more effective than two-sided message response in lowering attribution of crisis responsibility when sadness was induced, but no difference was found under the anger-induced condition. Attribution of crisis responsibility fully mediated the effects of emotional crisis framing on company evaluation and supportive behavioral intention toward the company.

This study is among the first to examine the interaction effect between emotional media framing and response message sidedness in an ambiguous crisis. Drawing on the interdisciplinary theoretical frameworks, this study integrates the situational crisis communication theory, appraisal-tendency framework and message sidedness in persuasion literature. As such, it contributes to theoretical development in crisis communication and offers communication managers guidance on how to effectively address emotionally framed crises.

This study integrates the theory of planned behaviour (TPB) and value-belief-norm (VBN) theory to investigate tourists' intention and behaviour to visit green hotels in Malaysia.

A total of 160 valid questionnaire responses were collected via an online survey. The partial least square–structural equation modelling (PLS-SEM) technique was utilised to assess the study framework and the hypothesised relationship.

The study's results confirmed that tourists' intention to stay at a green hotel is directly influenced by their subjective norms and perceived behavioural control. Besides, the study confirms the insignificant relationship between green trust, personal norms and tourists' stay intention. On the other hand, perceived morals, responsibility, willingness to pay more and perceived consumer effectiveness were significant in explaining the customer's subjective norms, personal norms and perceived behaviour control.

The hotel industry may benefit from this empirical outcome to devise effective marketing strategies for retaining their customers, particularly in rejuvenating the impact of the COVID-19 pandemic on the industry.

This study provides valuable practical implications for green hotel operators to develop effective strategies to attract tourists to green hotel visits.

This study is the first to integrate the extended TPB and VBN theory to understand tourist intention to visit a green hotel. Notably, the extended TPB and VBN theory was practical and helpful in predicting tourist intention to visit a green hotel.

This research aims at explaining the phenomenon of the “black children” (heihaizi), a very little-known generation who lived with concealment under the one-child policy in China. The one-child policy was officially introduced to nationwide at the end of 1979 by permitting per couple to have one child only, later modified to a second child allowed if the first was a girl in rural China in 1984. It was officially replaced by a nation-wide two-child policy and most existing research focused on the parents’ sufferings and policy changes. The term “black children” has been mainly used to describe their absence from their family hukou registration and education. However, this research aims at expanding the meaning of being “black” to explain the children who were concealed more than at the level of family formal registration, but also physical freedom and emotional bond. What we do not yet know are the details of their lived experiences from a day-to-day base: where did they live? How were they raised up? Who were involved? Who benefited from it and who did not? In this way, this research challenges the existing scholarship on the one-child policy and repositions the “black children” as primary victims, and reveals the family as a key figure in co-producing their diminished status with the support of state power. It is very important to understand these children’s loss of citizenship and human freedom from the inside of the family because they were concealed in so many ways away from public view and interventions. This research focuses on illustrating how their lack of access to continued, stabilized, and reciprocally recognized family interactions framed their very idea of self-worth and identity.

This study quantitatively investigates the impacts of digital and learning orientations on supply chain resilience (SCR) and firm performance (FP), aiming to fill the gaps in understanding their specific impacts in the context of Industry 4.0 developments and supply chain disruptions.

This study utilized survey techniques and structural equation modelling (SEM) to gather and analyse data through a questionnaire based on a seven-point Likert scale. Hypotheses were formulated based on an extensive literature review and tested using Amos software.

The study confirms SCR’s significant impact on FP, aligning with existing research on resilience’s role in organizational competitiveness. This study uncovers the nuanced impacts of digital and learning orientations on SCR and FP. Internal digital orientation (DOI) positively impacts SCR, while external digital orientation (DOE) does not. Specific dimensions of learning orientation – shared vision (LOS), open-mindedness (LOO) and intraorganizational knowledge sharing (LOI) – enhance SCR, while commitment to learning (LOC) does not. SCR mediates the relationship between DOI and FP but not between DOE and FP.

This research focuses on digital and learning orientations, recommending that future studies investigate other strategic orientations and examine the specific contributions of various digital technologies to SCR across diverse contexts.

The empirical findings emphasize the significance of developing internal digital capabilities and specific learning orientations to enhance SCR and FP, aligning these initiatives with resilience strategies.

This study advances knowledge by distinguishing the impacts of internal and external digital orientations and specific learning dimensions on SCR and FP, offering nuanced insights and empirical validation.