Dr Senmao Xia

The visitor economy is responsible for a substantial percentage of the global carbon footprint. The mechanisms used to decarbonize it are insufficient, and the industry is relying on carbon trading with substandard credits that allow businesses to outsource the responsibility to decarbonize. We aim to transform carbon markets, help finance climate investments, and support decarbonization strategies. We identify and define the problem, outline the components and their interactions, and develop a conceptual model to transform carbon markets. The new, blockchain-based Carbon Tokenomics Model rolls out a decentralized database to store, trade, and manage carbon credits, with the goal of enabling sustainable climate finance investment. We outline the criteria needed for an industry-wide carbon calculator. We explain the process needed to increase rigor in climate investments in the visitor economy and introduce a delegated Proof of Commitment consensus mechanism. Our inclusive and transparent model illustrates how to reduce transaction costs and how to build consumer and industry trust, generating much-needed investments for decarbonization.

•It contextualises the UCIB as neglected species of local government debt.•It decomposes the UCIB into a spatial layer and a financial level relative risk factor.•It highlights that the UCIB plays a strategically important role as a bridge between China’s emerging capital market and the development of the real economy. This paper examines the Urban Construction Investment Bond (UCIB) as a tradable product in the financial market and a financial tool for local government in China. The development of this financial product is contextualised in infrastructure finance and local government debt. The creation of UCIB helps finance infrastructure investment and potentially reveal the relative risks through the secondary market. The spatial distribution of UCIB demonstrates different relative risks of this financial instrument in local conditions. The government uses this financial tool to bridge the emerging capital market and infrastructure finance, and the Chinese financial market now treats UCIB as an emerging asset class. The development of UCIB has sped up the pace of financialisation in China. Although relative risks help investors choose different UCIBs, the overall risk of UCIB cannot be ignored.

With a shift to more automation technology, social acceptance of technology plays an important role in the manufacturing sector. To what extent this occurs, and affects the adoption of technology, has been less researched, but is important in deciding how such technology is introduced, and the nature of the shift from labour-intensive manufacturing to automation. This research applies the revised technology acceptance model (TAM) to examine the impact of social and individual antecedents on the acceptance of automation manufacturing technology. Survey data are collected from 258 Chinese manufacturers. Results suggest that perceived norms significantly affect organizational intention to use automation manufacturing technology both directly and via perceived usefulness; organizational efficacy explains the intention to use via mediating effect of perceived usefulness and perceived ease of use. This research is one of the first extending and applying TAM from individuals to organizations.

Few paper notices the black side of trust on technology transfer. This paper utilizes the "Transaction Cost Economics" (TCE) to find out that trust, in some cases, can deter technology transfer between two manufacturing firms. Specifically, trust can influence the transaction cost through three dimensions, including "asset specificity", "transaction frequency" and "uncertainty", and then the relationship between trust and technology transfer can be detected with the help of transaction cost as a media. Finally, this paper finds out that before an optimal threshold point, the trust can decrease the transaction cost and, simultaneously, can improve the technology transfer. But after that, trust may increase the transaction cost, then imposing restrictions on the technology transfer.

To investigate the impact of institutional investors on firms' corporate social responsibility (CSR) engagement while controlling for possible endogeneity concerns, we study how Chinese listed firms adjust their CSR decisions when their institutional investors are distracted by exogenous attention-grabbing events and thus are inattentive. With a sample of Chinese listed firms from 2009 to 2017, we find a significant and robust negative relationship between institutional investor inattention and firms' CSR engagement. This negative relationship is more pronounced for firms with more principal-agent problems and/or weaker corporate governances and is more attributable to the inattention of institutional investors with more monitoring incentives. These findings suggest that managers are less motivated to engage in CSR when they are less monitored by institutional investors, indicating that CSR is beneficial to shareholders of Chinese listed firms. Our findings also indicate that the positive impact of institutional investors on CSR may be constrained by their limited attention.

Considering the extreme significance of artificial intelligence (AI) for the academic research, business practices as well as governmental policies, this article reviews the development and application of AI via a management and development perspective. In particular, this article starts with the discussions how AI might bring about new competition and collaboration relationships among countries and firms. We then analyse key elements for AI firms to secure public funding. In addition, this study summarises the characteristics of AIs new applications in multiple business scenarios, such as entrepreneurial social networks and strategic human resource management. Finally, the relationship between blockchain and AI is briefly introduced.

This study investigates how consumers' willingness-to-pay (WTP) for green products affects the decisions made by the green supply chain players. Through the application of game theory and uncertainty theory, our findings show that a higher consumer WTP for green products usually leads to a higher retail price and market share of green products, which motivates retailers and manufacturers to invest more in green technology. We also find that an increased WTP for green products can spur retailers to reduce the optimal green cost-sharing rate due to the pressure of increasing costs. In addition, we find that retailers are willing to lower the cost sharing rate when the confidence level increases. Regarding the contributions made by this study, it is one of the first to explore the transmission mechanisms involved in the management of the green supply chain by linking consumers' WTP for green products to strategic decisions made by green supply chain players under conditions of uncertainty. Furthermore, our study could help green supply chain players to optimise the cost sharing mechanisms they use to generate more revenue, due to the increase in WTP for green products, which will in turn help to facilitate a low carbon economy.

In recent years, online consumer reviews have become popular in platform sellers to increase product sales, and the literature has widely recognized those reviews' positive impacts. Nevertheless, this paper identifies online consumer reviews' negative impacts on the intra-brand competition (multi-product), and aims to study such effect on wholesale prices and product design strategies of players in the FMCG (Fast Moving Consumer Goods) O2O (online to offline) supply chain. We model the decentralized O2O supply chain facing intra-brand competition that consists of a platform seller (follower) and a manufacturer (leader) when the new product entries. We find that the intra-brand competition driven by the reviews' increased-sales effect on the incumbent product causes the conflict. The platform seller prefers to limit such an effect if the new product's consumer valuation is not sufficiently high, but the manufacturer benefits from it. Manufacturers can reduce the product line's wholesale prices or lower down the new product quality to pre-empt the platform seller from limiting RE-I to coordinate the channel. This study contributes to O2O supply chain management literature by examining the possible negative impacts of online consumer reviews. Also, this study presents a new perspective to combine consumer reviews, pricing and product design strategies to coordinate the O2O channel.

Crowdsourcing enterprises increasingly seek to attract and persuade makers to contribute their creativity and wisdom through digital storytelling, however, what are the effective components of digital storytelling and the persuasive effect of digital storytelling on creative crowdsourcing intention are still unclear. To fill this gap, this study explores how digital storytelling persuades makers to generate creative crowdsourcing behavioural intention by utilising Unified Theory of Acceptance and Use of Technology (UTAUT). Results reveal that the persuasion activity of digital storytelling has a positive effect on creative crowdsourcing intention. The effective components of digital storytelling are mainly composed of aesthetic perception, narrative structure and self-reference. UTAUT and its four core concepts (performance expectation, effort expectation, social influence and facilitating condition) mediate the impact of digital storytelling on the creative crowdsourcing intention, which reveals the persuasive source of digital storytelling. We highlight the theoretical implications as well as the practical applications in creative crowdsourcing.

Front Distribution Centre (FDC) is a new terminal warehouse which is closer to customers, with its location selection being crucial for e-commerce and customer time satisfaction. We introduce in this paper a joint distribution function of demand based on time and space, which constructs two spatio-time models: spatio-time clustering model and spatio-time optimisation model. A staged clustering algorithm is designed to obtain the candidate FDCs, and an intelligent algorithm based on NSGA-Ⅱ (Non-dominated Sorting Genetic Algorithm II) is applied to determine the final FDCs, in which the location selection problem is formulated as a bi-objective programming model to minimise total costs and maximise customer time satisfaction. Our results indicate that the model considering spatio-temporal joint attribute of demand performs better than the traditional spatial model. Furthermore, when compared with the k-means clustering algorithm, Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) and its improved algorithm Multi-Objective Evolutionary Algorithm based on the Adaptive Neighborhood Adjustment strategy (MOEA/D-ANA), Multi-Objective Particle Swarm Optimisation” (MOPSO) and its enhancing algorithm Competitive Multi-Objective Particle Swarm Optimiser (CMOPSO), the solving method based on staged clustering and NSGA-II absolutely performs more stable and can get a greater number of pareto-optimal solutions with higher qualities. Especially when compared with K-means clustering algorithms, it can reduce total costs by up to 38.84% and improve customer time satisfaction by up to 36.22%. •Based on the introduction of customer demand temporal distribution function, a spatio-temporal clustering model is constructed, utilising a staged clustering algorithm of three-dimensional clustering and then two-dimensional clustering.•A spatio-temporal optimisation model is constructed, simultaneously minimizing total costs and maximising the customer time satisfaction, and then an intelligent algorithm - NSGA-II (Non-dominated Sorting Genetic Algorithm II) is applied.•Compared with K-means clustering algorithm and other multi-objective optimisation methods, the solving method based on staged clustering and NSGA-II shows more stable performance and achieves a greater number of Pareto-optimal solutions with higher qualities, which can provide managers with more alternative solutions to make the results more in line with actual management needs.

High-polluting industries are regarded as the main sources of air pollutant emissions and the major factors that significantly destroy the ecological environment. Corporate innovation in high-polluting industries improves the energy consumption efficiency and reduces the emission of air pollutant, which mitigates the conflict between environment and economy. Using the sample of China's listed firms from 2010 to 2017, this study examines the impact of corporate social responsibility (CSR) and financialization on corporate innovation in high-polluting industries. The results show that there is a positive association between CSR and corporate innovation, while there is a negative association between financialization and corporate innovation. Furthermore, the financialization of high-polluting firms can alleviate the promotion role of CSR in the innovation process. The financialization of state-owned enterprises in high-polluting industries may not have a crowding-out effect on research and development (R&D), but it can limit the R&D promotion effect of CSR engagements. In contrast, the financialization of non-state-owned enterprises will hinder corporate innovation, but it will not affect the association between CSR and technology innovation. We also find that the financialization of high-polluting firms with low financial constraints can alleviate the promotion role of CSR engagements in innovation. Meanwhile, the CSR engagements of high-polluting firms with high financial constraints play a stronger role in corporate innovation. During the implementation of environmental policies, the negative association between financialization and corporate innovation has been strengthened. Our findings can encourage high-polluting firms to make more efforts in environmental protection and social stability.

Consumer green education has significantly affected the green supply chain and recyclers have started to distribute remanufactured products via online platforms. Through a two-period game model, this study examines the effects of consumer green education on the recycler's channel choice. The recyclers sell remanufactured products through either the E-retailer's platform (Agency channel), or their own online platform (Self-Run channel). Surprisingly, our research indicates that a new product seller (E-retailer) can benefit from the remanufactured goods' cannibalisation in the Agency channel, provided the consumer green education is under-developed. This finding challenges the traditional opinion that the cannibalisation causes loss of profit for new-product sellers. Besides, as the consumer green education effect increases, the recycler prefers the Self-Run channel even with high operational costs. This study provides new insights into the recyclers' channel choice by considering the consumer green effect, thereby extending the research on the remanufactured products' distribution channel strategy.

Social media has become a norm for retailers seeking to engage actively with consumers. There is growing evidence that some consumers choose not to engage with social media marketing content and that the depth of consumer engagement varies across different social media. However, there is a lack of empirical research on contextual factors that may contribute to such differences. Moreover, the variation of social media engagement behaviours, namely, consumption, contribution, and creation is underexplored. Hence, we seek to understand the various levels of engagement behaviours that are influenced by key social media contextual factors, namely media richness and content trustworthiness. We analyse 721 survey responses using PLS-SEM. Results reveal significant effects of media context on engagement behaviours. This research contributes to the growing body of literature on social media engagement, in particular, understanding the impact of social media contextual factors on various engagement behaviours.

The proactive change behavior of an employee is the key to promoting organizational innovation. However, the proactive change has a certain risk, and many employees are unwilling to implement initiatively. How to promote the occurrence of a proactive change behavior of an employee has become a hot issue in the theoretical and practical areas. Based on the self-disclosure theory, this study uses the questionnaire survey method, containing a total of 32 items, and uses the 5-point Likert scale (1 = strongly disagree and 5 = strongly agree), with the Mplus and SPSS statistical software to analyze the impact mechanism of work-related information sharing of supervisors on the proactive change behavior of employees through the structural equation model. The regulatory effect of non-work information sharing of leaders is analyzed using the latent regulatory structural equation method. The conclusions are as follows: work-related information sharing positively of supervisors influences the family-like employee–organization relationship of employees; the family-like employee–organization relationship and relationship energy play serial mediating roles in the relationship between work-related information sharing of supervisors and the proactive change behavior of employees; non-work information sharing of supervisors moderates the serial mediating path by enhancing the positive influence of work-related information sharing of supervisors on the family-like employee–organization relationship. Theoretically, this study has complemented and enriched the research on the influence mechanism between the information sharing of supervisors and the proactive change behavior of employees. Practically, this study has important implications for supervisors to promote the proactive change behavior of employees by sharing work-related information and non-work information with employees.

How to balance the central government and local governments' political authority relating to environmental governance has long been a topic of intense debate in China. Since both environmental and economic regulations are regulatory tools of governments, political authority and systems must be considered in deciding to what extent to empower local governments. Central government needs to find a tradeoff point when being placed under the dual pressure of environmental protection and maintaining the economic growth rate. Based on a twolevel principal-agent model, our research compares the effects of centralized and decentralized governance on the efficiency of environmental regulation. Our results suggest that under decentralized environmental governance, the local governments' incentives increase, which results in either "race to the top" or "race to the bottom" competition in environmental regulation. Moreover, such governance prompts local governments to reduce their investment in economic development and environmental protection. However, decentralization in environmental governance will become more beneficial to the central government if the benefits of reducing information asymmetry surpass enhanced agency costs; otherwise, centralized environmental governance is preferred. Our research proposes a hybrid model of centralized and decentralized environmental governance to help cushion firms against high agency costs and local government-firm collusion.

CO2 emissions from China accounted for 27 per cent of global emisions in 2019. More than one third of China's CO2 emissions come from the thermal electricity and heating sector. Unfortunately, this area has received limited academic attention. This research aims to find the key drivers of CO2 emissions in the thermal electricity and heating sector, as well as investigating how energy policies affect those drivers. We use data from 2007 to 2018 to decompose the drivers of CO2 emissions into four types, namely: energy structure; energy intensity; input-output structure; and the demand for electricity and heating. We find that the demand for electricity and heating is the main driver of the increase in CO2 emissions, and energy intensity has a slight effect on increasing carbon emissions. Improving the input-output structure can significantly help to reduce CO2 emissions, but optimising the energy structure only has a limited influence. This study complements the existing literature and finds that the continuous upgrading of power generation technology is less effective at reducing emissions and needs to be accompanied by the market reform of thermal power prices. Second, this study extends the research on CO2 emissions and enriches the application of the IO-SDA method. In terms of policy implications, we suggest that energy policies should be more flexible and adaptive to the varying socio-economic conditions in different cities and provinces in China. Accelerating the market-oriented reforms with regard to electricity pricing is also important if the benefits of technology upgrading and innovation are to be realised.

There has been renewed interest in assessing the pilot scheme for compiling the natural resources capitalization (NRC). A growing body of evidence highlights the good effects that the policy of NRC has on the construction of ecological civilization. No known empirical research has focused on exploring relationships between the policy of NRC and carbon emissions reduction. This paper employs the NRC as the ecological civilization policy to investigate whether the implementation of NRC has contributed to the carbon emissions reduction with a difference-in-differences (DID) method. The results showed that different variables of carbon emissions in four pilot cities can be effectively affected by the implementation of NRC. There were significant negative correlations between the carbon emissions per GDP (Gross Domestic Product) and the policy for Hulun Buir, Huzhou and Loudi cities, and a significant increase of carbon sequestration was found in Yan'an city. This research provides a timely and necessary study that the NRC policy could be a contributing factor to carbon emissions reduction. As a result of these investigations, suggestions were identified for future research. Further research should be undertaken to investigate the collaborative effects of multi-policies on environmental issues.

•Business incubator capacities impact on the regional innovation performance.•Basic service and financial capacities have less impact than incubation capacity.•Regional communication infrastructure is playing an important moderating role.•Policy makers should focus more on creating free knowledge transfer platforms. Recent years have witnessed the fast development of business incubators in many emerging economies, such as China. Business incubators are seen as important facilitators for innovation which provide office space, equipment, mentoring services, as well as financial, legal and administrative supports for technology entrepreneurs and start-up companies. Much investment has been undertaken to facilitate the development of business incubators, for example in financial frameworks, human resource development and communication infrastructure. This paper investigates the effects of business incubator capacities on the regional innovation performance, using a panel representing 31 Chinese provinces. This study finds that three capacities of business incubators have significant impacts on the regional innovation performance, while the incubation capacity appears to have a much greater effect than the basic capacity and the finance capacity. Moreover, this study also identifies that the regional communication infrastructure is an important moderator of the relationship between business incubator capacities and the regional innovation performance. This paper supports the view that emerging economies should encourage the development of business incubators in order to promote the development of technology entrepreneurs and domestic innovation performance, but more focus should be on creating free knowledge transfer platforms.

Purpose The purpose of this paper is to empirically explore the mechanisms through which Chinese National Science Parks' (NSPs) services facilitate returnee entrepreneurs' (REs) acquisition of resources for their new ventures. Resource acquisition is crucial for new ventures, but it inevitably leads to significant costs increase. Although the NSPs offer various services to REs to reduce these costs, they still struggle to find the right mix of services. Design/methodology/approach From the transaction cost's perspective, an exploratory multiple-case study was conducted with data collected from six NSPs in China. Findings The results reveal that four types of NSP services (mentoring and training, social event, promotion of REs and accreditation of resource holders (RHs)) have both individual and joint effects on reducing REs' resource acquisition costs. Specifically, the "accreditation of RHs" service directly helps REs reduce search costs. The combination of "accreditation of RHs", "promotion of REs" and "social event" services help REs and RHs to establish guanxi. Further, guanxi, working along with the "mentoring and training" service, helps REs to reduce contracting, monitoring and enforcement costs. Originality/value This study is among the first to explore the matching mechanisms between science parks' services and entrepreneurs' cost reduction. This helps reconcile the inconsistent findings on science parks' effect by explaining why some NSPs are able to provide strong support to REs while others are less successful. In addition, the findings are useful for NSPs to develop the right mix of tailored services for REs. Finally, REs will find this study useful to evaluate which NSP is a more suitable location for their new ventures.

This study explores the relationship between R&D investment and economic growth in China, using a newly collected panel data set. Specifically, we investigate how social filters are connected to R&D output. Instead of linking R&D investment directly to economic performance, we adopt a two-step strategy which identifies the impact R&D investment on R&D output, and then study the causal links between R&D output and economic development. Our results suggest that the relationship between R&D input, R&D output and economic growth diverges by different region and sectors. Most of positive associations stem from non-peripheral regions and non-state owned sectors. Social filters are also more effective under these circumstances. These results reveal the complexity of relationships between R&D efforts and economic performance and point to the important role of social filters in innovation and growth. (C) 2020 Elsevier B.V. All rights reserved.

Component suppliers and manufacturers in a supply chain have long faced different dilemmas. The component supplier intends to adopt new technologies to reduce production costs, but the new technologies usually require significant investment costs. The encroachment into retailing can bring more revenue to manufacturers, but the significant costs of establishing and maintaining direct channels and the potential conflicting interests with the retailer might discourage the manufacturer's encroachment. This study aims to address these dilemmas facing the component supplier and manufacturer by investigating an interesting scenario in which they both can obtain benefits. Within the given context, the manufacturer's encroachment increases the order of the components, which motivates the supplier to make more technological investments to reduce production costs. The reduction of component costs enables suppliers and manufacturers to reduce the wholesale prices of components and final products. In this case, the manufacturer's encroachment can benefit both the manufacturer and the retailer. This study is one of the first to investigate how the interaction between the manufacturer and supplier helps solve their respective dilemmas and provide benefits to the whole supply chain. Additionally, we extend the literature on manufacturer encroachment on retailers by considering supplier investment in cost-reduction production.

Foreign direct investment in R&D is one of the popular channels indigenous firms use to upgrade their technological capacities and improve market intelligence following innovation setbacks. Firms often employ various signals to secure higher levels of foreign direct investment in R&D. However, the majority of research on this topic focuses on the role of positive rather than negative signals. Firms are often conservative about communicating negative information regarding their innovation projects due to concerns around competition and managerial performance appraisal. Drawing on signaling theory, this study investigates the impact of a negatively valenced signal - the experience of abandoning innovation projects - on attracting foreign direct investment in R&D. Moreover, although firms are known to send multiple signals simultaneously, little is known about how the interactions between oppositely valenced signals (specifically, the experience of abandoning innovation projects, which is a negative signal, and the filing of patent applications, which is a positive signal) affect foreign direct investment in R&D. A study of 11,354 Spanish firms from the Spanish Technological Innovation Panel during the period 2008-2015 found that the experience of abandoning innovation projects has a positive effect on foreign direct investment in R&D. However, this positive effect is weakened by patent applications due to the signaling of conflicting messages. These results have important theoretical and practical implications for the advancement of signaling theory and the management of innovation setbacks.

With the increasingly prominent problems of global resource consumption and environmental pollution, industrial green transformation has become one of the requirements of China's industrial development in the new era. However, there is a lack of research on the impact of technological innovation and technology introduction on the industrial green transformation of resource-based cities. To bridge this gap, this study uses the panel data of 115 resource-based cities in China from 2003 to 2016, and uses the dynamic panel generalized method of moments (GMM) estimation method to study the impact of technological innovation and technology introduction on industrial green transformation of resource-based cities. The results show that technology introduction has a negative effect on the industrial green transformation of resource-based cities, while technological innovation can have a positive effect. Meanwhile, technology introduction has imparted a greater role to technological innovation in promoting this transformation. In addition, the interactive effects between technological innovation and technology introduction have obvious heterogeneity on the industrial green transformation of different types of resource-based cities. Therefore, resource-based cities should continue to increase investment in scientific research, to constantly improve and consolidate their technological innovation ability, optimize foreign investment strategy in technology introduction, and strengthen the digestion and absorption of imported technology, while increasing technological innovation and personnel training.

Motivated by the observation that firms invest in carbon emissions reduction to decrease the cost of carbon tax as governments in numerous countries increasingly implement carbon tax to improve the environment, and broad researcher and practitioner agreement that carbon tax implementation always benefits the environment. However, we find that a carbon tax may actually hurt the environment based on a stylized game model with a better-informed retailer (one who controls the demand information sharing with the manufacturer) and a manufacturer. In particular, we find that the carbon emissions reduction may harm the environment if the carbon tax is moderate or both the carbon tax and the demand fluctuation are high. We further reveal free-riding behavior by the retailer, who may enjoy more profit sharing from the supply chain in the presence of carbon emissions reduction. Based on these observations, we argue that a carbon tax does not always benefit the environment when a manufacturer who receives demand information from the retailer responds better to market uncertainty.

This paper aims to study the determinants of subjective happiness among working females with a focus on female managers. Drawn on a large social survey data set ( N = 10470) in China, this paper constructs gender development index at sub-national levels to study how institutional settings are related to female managers’ happiness. We find that female managers report higher levels of happiness than non-managerial employees. However, the promoting effect is contingent on individual characteristics and social-economic settings. The full sample regression suggests that female managers behaving in a masculine way generally report a high level of happiness. Meanwhile, female managers who refuse to support gender equality report low happiness levels. Sub-sample analysis reveals that these causalities are conditioned on regional culture. Masculine behavior and gender role orientation significantly predict subjective happiness only in gender-egalitarian regions. This study is one of the first to consider both internal (individual traits) and external (social-economic environment) factors when investigating how female managers’ happiness is impacted. Also, this study challenges the traditional wisdom on the relationship between female managers’ job satisfaction and work-home conflict. This study extends the literature by investigating the impacts of female managers’ masculine behavior on their happiness. This study is useful for promoting female managers’ leadership effectiveness and happiness.

We examine whether the public environmental concerns promote the development of new energy enterprises through a quasi-experiment China's extreme event of 2011 when the PM2.5 Surge incident escalated public environmental concerns. After this incident, the market power of new energy enterprises in severely polluted regions became 108% higher than that in the mildly polluted regions. It implies that public environmental concerns promote the development of new energy enterprises. This observation is limited to non-state-owned companies, companies without political connections, and regions without new energy subsidies. This increased market power of new energy enterprises with increasing public environmental concerns was because of sales increase instead of reduced non-operational costs. Overall, this study answers several interesting questions associated with the increasing public environmental concerns and the rapid development of energy enterprises.

The gender structure in research and development (R&D) activities has received more and more attention in terms of its increasing importance in R&D management, but it is still not clear what the R&D efficiency discrepancy between female and male personnel is in the science and technology (S&T) field and whether the gender structure affects the R&D efficiency. Based on the region-level panel dataset of China's research institutes, this study uses four types of R&D outputs (papers, books, patents and standards) together and individually to measure R&D efficiency score to reveal this topic. When four types of R&D outputs are jointly considered, this paper applies the multi-output stochastic frontier analysis and finds that in general the higher proportion of male R&D personnel produces the higher R&D efficiency. Nevertheless, in terms of S&T papers or S&T books as a single R&D output, we find that the higher proportion of female R&D personnel leads to the higher R&D efficiency. On the contrary, the R&D efficiency is lower with the higher proportion of female R&D personnel when the single R&D output is measured by invention patent applications or national/industrial standards, respectively. Our findings suggest that the female R&D personnel are more effective in conducting scientific research activities, while their counterparts are more effective in doing technology development activities.

Digital platforms help develop the open value co-creation strategic alliances, reshape traditional B2B relationships, and promote inclusive social innovation. This research explores the nature of coopetition between the digital platform and its participants. The focus is on how the platform-based alliance balances the contradiction between value creation and appropriation. The support evidence derives from a Stackelberg game in the context of cooperative advertising. Either the platform or the participant supporting advertising in the alliance prompts a Pareto improvement for all players. But the increased profit would be mainly occupied by the dominant platform. The incentive mechanism of profit sharing can promote the alliance to co-create value in a sustainable manner. The game illustrates the significance of cooperative relationships to co-create a larger total value and the existence of an unequal win-win relationship in the strategic alliance. The contradictory logic of cooperation and competition can be accommodated in the platform-based alliance. The dynamic coopetition is involved in a partially convergent interest structure and impacted by power asymmetry. The results highlight the balance between the tensions and harmonies through value creation and appropriation.

3-Dimensional Printing (3DP) has been widely used in the circular supply chain. Still, most of the literature focused on addressing only the manufacturer's adoption of 3DP and how it influences the supply chain. A growing number of non-manufacturer (e.g., logistic suppliers) have adopted 3DP, but its impact on manufac-turers and customers is still underexplored. This paper uses a two-player single-period supply chain model, supported by an in-depth interview, to investigate how the logistics supplier's 3DP adoption impacts the circular supply chain in the spare parts aftersales market. The findings show that cost reduction of 3DP does not always benefit the logistics supplier. Still, this finding opens a new revenue stream for the logistics supplier and the integrated supply chain. Further, the manufacturer can financially benefit from such adoption only when the cost of 3DP production is relatively high. Interestingly, the logistics supplier can use 3DP adoption as a game-changer to become a new "green manufacturer", thereby posing a strategic threat that can influence the traditional manufacturer's decisions regarding financial benefits. Customers can also enjoy more surplus when logistics suppliers adopt low-cost 3DP. This study is one of the first to investigate how non-manufacturer 3DP adoption impacts the circular supply chain.

Literature notes that firms are keen to develop big data analytics capability (BDAC, e.g. big data analytics (BDA) management and technology capability) to improve their competitive performance (e.g. financial performance and growth performance). Unfortunately, the extant literature has limited understanding of the mechanisms by which firms' BDAC affects their competitive performance, especially in the context of small and medium-sized enterprises (SMEs). Using resource capability as the theoretical lens, this paper specifically examines how BDAC influences SMEs' competitive performance via the mediating role of business models (BMs). Also, this study explores the moderating effect of COVID-19 on the relationship between BDAC and BMs. Supported by Partial Least Squares-Structural Equation Modelling (PLS-SEM) and data from 242 SMEs in China, this study finds the mediating roles of infrastructure and value attributes of BMs in enhancing the relationship of BDAC on competitive performance. Furthermore, the improvement of financial performance comes from the matching of BDA management capability with infrastructure attributes of BMs, while the improvements in growth come from the matching of BDA management capability and BDA technology capability with value attributes of BMs. The result also confirms the positive moderating effects of COVID-19 on the relationship of BDA management capability and value attributes of BMs. This study enriches the integration of BDAC and BMs literature by showing that the match between BDAC and BMs is vital to achieve competitive performance, and it is helpful for managers to adopt an informed BDA strategy to promote widespread use of BDAs and BMs.

The creation of a new venture is at the heart of entrepreneurship. Chinese governments at different levels are proactive in promoting the entrepreneurial ecosystem (EE) and fostering new venture creation (NVC). However, it is still far from clear how governments as focal actors in the EE affect and regulate the process and pattern of NVC. This study borrows from the theory of temporary organization and conducts a comparative case study of two entrepreneurial projects in the Hangzhou Dream Town EE. This study proposes an integrated conceptual framework to illustrate NVC in two dimensions of projectification (the process of NVC) and partnering (a pattern of NVC) and specifies that the main role of local governments is as a sponsor, feeder, and endorser in that order. The three functional roles enable local governments to catalyze the creation of new ventures through projectification and partnering. Our study not only contributes to the literature on entrepreneurship, governance theory, and the theory of temporary organization but also provides an actionable approach for governments to foster new ventures, especially in transition economies such as China.

Thermal power generation based on coal-fired power plants has the advantages of stability and controllability and has been the largest source of electricity supply in China. Coal-fired power plants, however, are also accompanied by high carbon emissions and the release of harmful substances (mainly including sulfur dioxide, nitrogen oxides, and smoke dust), and are even regarded as the "chief criminal" in terms of air pollution. However, thermal power is also a pioneering industry involved in several environmental regulations and cleaner production techniques before other industries. Evidence of this is China's ultra-low emissions (ULE) policy on coal-fired power plants, implemented in 2015. To verify this policy's effect, this study treats ULE as an exogenous impact variable, examining its emissions reduction effect on SO2, NOx, and smoke dust in Eastern and Central China using the difference-in-difference method (DID). The results show that the total emissions of the three pollutants were abated by 0.133%, 0.057% and 0.036% in Eastern, and by 0.120%, 0.035% and 0.043% in Central China at every 1% rise of thermal power generated after ULE. In addition, several other factors can also argue for the promotion of thermal power. Other industries, such as steel or chemical, have proven that they can contribute significant SO2 and NOx emissions. Based on these results, we provide suggestions on synergistic emissions reduction among multiple industries, as well as a discussion on the necessity of implementing ULE in Western China.

Fierce competition and the mandate for green development have driven cold chain logistics companies to minimize total distribution costs and carbon emissions to gain a competitive advantage and achieve sustainable development. However, the cold chain logistics literature considers carbon trading mechanisms in sharing economy, namely the joint distribution, is limited. Our research builds a Joint Distribution-Green Vehicle Routing Problem (JD-GVRP) model, in which cold chain logistics companies collaborate among each other to deliver cold chain commodities by considering carbon tax policy. Based on the real business data from four cold chain companies and 28 customers, a simulated annealing (SA) algorithm is applied to optimize the model. The results indicate that joint distribution is an effective way to reduce total costs and carbon emissions when compared with the single distribution. The total cost is positively correlated with the carbon price, while the carbon emissions vary differently when the carbon price increases. In addition, carbon quotas have no effect on the delivery path. This research expands cold chain logistics literature by linking it with joint distribution and carbon trading mechanisms. Moreover, this research suggests that cold chain logistics companies could enhance delivery efficiency, reduce the business cost, and improve competitiveness by reinforcing the collaboration at the industry level. Furthermore, the government should advocate the mode of joint distribution and formulate an effective carbon trading policy to better utilize social and industrial resources to achieve the balanced economic and environmental benefits.

A virtual influencer (VI) is a computer-generated, imagery-based digital character. It has become one of the hottest marketing trends, motivating researchers to investigate how consumers perceive VIs. However, consumers’ emotional attachment and benefit seeking behaviour to different types of VIs has remained under-investigated. Therefore, considering the level of perceived humanness and appearance realism, this research examines how consumers’ emotional attachment and benefit seeking differs across the three types of VI (i.e., mimic-human VI, animated-human VI, and non-human VI). We further propose that VIs may influence consumer emotional attachment and different benefit seeking behaviour through social presence because, specifically, when a VI shows a higher level of social presence, a higher level of emotional attachment and stronger benefit seeking behaviour will result. The experimental studies lend support to our theorization. This research provides insights into the different types of VIs in marketing literature and extends the context of social presence theory.

The popularity of the circular economy attracts more attention to balance environmental and economic impacts. Many supply chain remanufacturing firms have started to use the cash flow to invest in cost-reduction technologies to increase profits. However, the uncertainty of cash flow significantly affects the technology investment effectiveness, and therefore, some firms attempt to adopt cash hedging strategies to mitigate the uncertainty. This study investigates the impacts of cash hedging on remanufacturing firms' profits and the environment through the lenses of cost-reduction technologies investments. The proposed nonlinear programming models were drawn on cash hedging and risk management theory. Empirical regression analysis was conducted using longitudinal datasets of listed Chinese remanufacturing firms for ten years ranging from 2010 to 2019. Different from the traditional wisdom which argues that cash hedging has a single effect (i.e., positive, negative, or no impact) on corporate economic performance, this paper's results indicate that the impact of cash hedging on corporate profits varies in different conditions; Further, this study is one of the first to identify some interesting conditions, in which cash hedging can bring along remanufacturing firms with profits while protect environment. This study provides insightful suggestions for the manufacturer's and government's policy design.

The unprecedented COVID‐19 pandemic required millions of people across the world to become remote workers. However, little is known about how to achieve effective remote working for organizations. This study investigates the types of employees that are more suited to accepting remote working by considering two determinants: gender and internet skills. Based on an official data set from China, this study reveals that females are more likely to accept remote working, as are those employees with advanced internet skills. This study further investigates the impacts of perceived benefits on employees’ acceptance of remote working. It appears that the preference of females for remote working is attributed to avoiding face-to-face interaction rather than free time planning. This study is among the first to reveal how skill matching matters in order to be successful remote workers. Meanwhile, this study indicates that it is gender-specific psychological differences rather than the division of labor in families that motivate females to accept remote working, an important observation which has been neglected so far. The findings are helpful for employers and employees in the post-pandemic era.

Purpose Previous experience is a critical factor affecting entrepreneurial activities; however, it has not been fully studied in the existing literature. This study attempts to comprehensively reveal the routes and mechanisms of occupational experience that affect entrepreneurial activities and assess the entrepreneurial potential of different occupational practitioners. Design/methodology/approach By matching occupational characteristics with entrepreneurs' competence, this study proposes ten hypotheses about how occupational experience affects entrepreneurial entry and performance. This empirical study is based on the Occupational Information Network database and Chinese survey data. Factor and regression analyses were used in the empirical research. Findings This study verifies that different occupational practitioners have varied entrepreneurial potential. Occupational experience, including occupational uncertainty, market contact and social capital, gained from previous experience significantly affects entrepreneurial entry. Meanwhile, occupational characteristics, including management experience, marketing experience, social capital, financial capital, risk-taking ability and creativity, accumulated from previous experience, have a significant impact on entrepreneurial performance. Originality/value This study is a pioneering attempt to reveal the relationship between occupational experience and entrepreneurial activities. The transmission mechanism of previous experiences affecting entrepreneurial activities is comprehensively revealed by relaxing the assumption of a representative occupation. These findings provide a theoretical foundation for empirical evidence and have important practical value.

Creativity is key for organizations’ ability to remain relevant in today's disruptive world. In this paper, we identify new ways in which organizations can use artificial intelligence (AI) more effectively for creativity. Drawing on the resource-based view as a background mechanism, we developed and empirically tested a new integrative model. We collected the research data via a large survey of managers distributed to 600 organizations in China. Our findings show that coupling AI capability with strategic agility can directly support creativity. It also mediates the effects of ambidexterity, customer orientation and competitor orientation on organizations’ creativity and performance when developing new products and services. In addition, our findings show that coupling AI capability and strategic agility can significantly improve firms’ new product creativity and new service development performance when there is a high level of government institutional support. Our findings provide theoretical and practical implications for academics and practitioners interested in managing AI for organizational creativity.

Strategic alliance theories have been studied widely over the past few decades. However, their key arguments may face new limitations and challenges brought by emerging technologies such as big data analytics capability (BDAC). This paper aims to identify the challenges BDAC brings to strategic alliance theories and the associated changes to strategic alliance research. Specifically, this paper systematically reviews and identifies how BDAC challenges the key arguments in the strategic alliances' theories through the lens of three stages of strategic alliances: formation, governance and achieving alliance performance. Meanwhile, this study also finds some changes in strategic alliance research brought by BDAC. Finally, this study proposes promising directions for future research on strategic alliances under the influences of BDAC.

This research analyzes managers’ perceptions of the multiple types of artificial intelligence (AI) required at each stage of the business-to-business (B2B) service recovery journey for successful human-AI collaboration in this context. Study 1 is an exploratory study that identifies managers’ perceptions of the main stages of a B2B service recovery journey based on human-AI collaboration and the corresponding roles of the human-AI collaboration at each stage. Study 2 provides an empirical examination of the proposed theoretical framework to identify the specific types of intelligence required by AI to enhance performance in each stage of B2B service recovery, based on managers’ perceptions. Our findings show that the prediction stage benefits from collaborations involving processing-speed and visual-spatial AI. The detection stage requires logic-mathematical, social, and processing-speed AI. The recovery stage requires logic-mathematical, social, verbal-linguistic, and processing-speed AI. The post-recovery stage calls for logic-mathematical, social, verbal-linguistic, and processing-speed AI.