Adopting a parent-firm perspective, this study investigates how digital transformation and its synergy with the specific advantages of emerging market multinational enterprises affect the performance of overseas subsidiaries. Using panel data from 448 Chinese listed manufacturing multinationals and their 1179 overseas subsidiaries over the period 2011-2021, regression analyses reveal that parent-firm digital transformation significantly enhances overseas subsidiary performance. Moreover, this positive effect is more pronounced when the parent firm exhibits a stronger Institutional void coping capability. The moderating analysis further indicates that the firm's internal business group network strengthens this relationship, whereas parent-firm host-country experience does not show a significant moderating role. By examining how market multinational enterprises integrate home-country-specific advantages with digital capabilities, and by analyzing the contingent roles of organizational capabilities and host-country experience, this research extends the theoretical framework of multinational enterprises' competitive advantage in the digital era. The findings provide a theoretical foundation for emerging market firms to enhance overseas operational efficiency and strengthen sustainable global competitiveness through digital transformation.

Promoting urban energy transition is essential for achieving environmental sustainability, yet how to effectively guide this process through public policy remains a key research question. This study aims to evaluate the effectiveness of government policy in facilitating urban energy transition, with a specific focus on China’s National New Energy Demonstration City Construction (NEDC) Policy. Using a difference-in-differences model with panel data from 274 Chinese cities, the empirical results indicate that the NEDC policy significantly advances urban energy transition, resulting in a notable increase of 0.571 units in the Urban Energy Transition Index and an improvement of 0.0321 units in the Urban Energy Transition Efficiency Index. Mechanism analysis further reveals that the NEDC policy promotes urban energy transition primarily by advancing financial development, strengthening environmental regulations, and encouraging capital-biased technological progress. Heterogeneity analysis indicates that the NEDC policy significantly boosts urban energy transition in resource-based cities, whereas it exerts a suppressive effect on urban energy transition in non-resource-based cities. This study offers valuable policy implications for developing countries seeking sustainable urban transformation.

The issue of corporate social responsibility (CSR) has garnered increasing attention from various sectors of society. However, excessively high executive compensation within enterprises may hinder the fulfillment of CSR. To address this issue, adjustments to compensation policies are necessary. As an essential aspect of compensation policies, pay regulation has also attracted growing interest from scholars. However, the influence of pay regulation on corporate decision-making, particularly its implications for corporate social responsibility, remains uncertain and requires further exploration. In this paper, we attempt to assess the impact of executive compensation regulation on corporate social performance and the influencing mechanism behind it. Using a sample of non-financial A-share listed companies in China from 2010 to 2020 and leveraging the 2015 “pay ceiling order” issued by the Chinese central state-owned enterprise as a quasi-natural experiment, this study applies the difference-in-differences (DID) method to examine the impact of the policy. The findings reveal that the implementation of the “pay ceiling order” policy substantially promotes the enhancement of CSR levels among enterprises. In the mechanism analysis, we find that the internal salary gap, an important indicator of employee well-being within enterprises, plays a significant mediating role in this effect. Additionally, the level of internal control within a company determines the effectiveness of management implementation. This variable can regulate both the direct and indirect impacts of pay regulation on corporate social responsibility. Further research indicates that in companies with either low management compensation levels or high management power, the positive effects of pay regulation on corporate social responsibility are more pronounced. Additionally, the policy of pay regulation has different “corporate social responsibility effects” on various stakeholders. These findings enrich the literature on the factors influencing corporate social responsibility and offer valuable insights for the design of corporate compensation policies and the advancement of social responsibility initiatives.

Although artificial intelligence (AI) serves as a core driver of the new round of technological transformation, its crucial role in improving energy utilization efficiency has not yet received sufficient attention. This analysis empirically explores how the application of AI technology influences energy utilization efficiency using panel data from Chinese cities over the period from 2008 to 2021. The following are the primary conclusions: (1) AI technology applications are able to enhance energy utilization efficiency, and the outcomes remain valid after extensive reliability tests have been conducted; (2) the investigation of the mechanism demonstrates that AI technology applications can optimize energy utilization efficiency through technological and scale effects; (3) environmental regulation and digital infrastructure serve as positive moderators of the impact of AI technology applications on energy utilization efficiency; and (4) a heterogeneity analysis shows that the positive impact of AI technology applications on energy utilization efficiency is more significant within resource-dependent cities, cities with non-traditional industrial foundations, and those with a strong emphasis on environmental protection. The application of AI technology significantly enhances energy efficiency, which is a finding that remains robust across multiple reliability tests.

ObjectivesEffectiveness of nirmatrelvir/ritonavir (NR) in kidney transplant recipients (KTRs) infected COVID-19 for more than 5 days has not been evaluated.MethodsIn this multicenter retrospective study, 85 KTRs with COVID-19 were enrolled, including 50 moderate, 21 severe, and 14 critical patients.ResultsThe median time from onset to starting NR treatment was 14 (IQR, 11-19) days. Before NR treatment, 96.5% patients reduced use of antimetabolites. They also stopped using calcineurin inhibitors (CNI) 12-24 hours before NR treatment, with CNI concentrations well-controlled during NR treatment. The use of intravenous corticosteroids increased with COVID-19 severity. The median time to reach viral negative conversion was 5 (IQR, 4-8) days for all patients. For moderate and severe COVID-19 patients, they had a low rate of ICU admission (1.4%), exacerbation requiring upgraded oxygen therapy (5.6%), and dialysis (2.8%); no intubation and mechanical ventilation, and no deaths were observed. Patients with critical COVID-19 had a low mortality rate (7.1%).ConclusionsA regimen including NR for clearing SARS-CoV-2 along with reducing immunosuppressants and using intravenous corticosteroids is associated with lower rates of exacerbation and mortality in KTRs who have moderate to critical SARS-CoV-2 infection and the virus still present after 5 days.

Drawing upon the interfirm absorptive capacity relationship and coopetition theory, this study examines how the congruence between a firm's own absorptive capability and its rival's absorptive capability affect the firm's innovation performance. We propose a theoretical framework embodying the interactive hypotheses and test the extent to which the fit versus non-fit between a firm's own absorptive capability and its rival's absorptive capability affect influences the firm's innovation performance by considering the appropriability as a moderator. A The polynomial regression analysis based on a dyad-style sample consisting of 200 manufacturing firms in China indicates that varying the congruence degrees of a firm's absorptive capability and its rival's absorptive capability would affect innovation performance differently. We also discuss some of the implications for firms expecting to enhance their competitiveness in a coopetition environment.

Purpose Based on an ensemble sample of multinational enterprises (MNEs), this study aims to explore the effect of the interactions between Chinese parent firms’ knowledge (including both technological and marketing knowledge), equity control and cultural distance on the business performance of their overseas branches under different subsidiary roles. Design/methodology/approach The study uses a data set compiled from 138 listed Chinese manufacturing enterprises and their 231 overseas subsidiaries to test the hypotheses regarding the interactive effects of transferred knowledge types and the subsidiary’s control mode. Findings The empirical results suggest that the moderating effects of equity control and cultural distance vary with the types of the parent firm’s knowledge and subsidiary roles. Specifically, equity control positively regulates the relationship between technological knowledge and subsidiary performance while negatively moderating the relationship between marketing knowledge and subsidiary performance. Cultural distance appears to negatively regulate the relationship between marketing knowledge and subsidiary performance. This binary relationship is shown to be more significant for the implementer subsidiaries. Originality/value Drawing on the literature on inter-firm governance and knowledge-induced innovation mechanisms, the authors develop a theoretical contingency framework to derive some managerial implications for inter-firm and infra-firm knowledge transfer in light of MNEs’ performance integrity.

Biomass gasification, especially distribution to power generation, is considered as a promising way to tackle global energy and environmental challenges. However, previous researches on integrated analysis of the greenhouse gases (GHG) abatement potentials associated with biomass electrification are sparse and few have taken the freshwater utilization into account within a coherent framework, though both energy and water scarcity are lying in the central concerns in China’s environmental policy. This study employs a Life cycle assessment (LCA) model to analyse the actual performance combined with water footprint (WF) assessment methods. The inextricable trade-offs between three representative energy-producing technologies are explored based on three categories of non-food crops (maize, sorghum and hybrid pennisetum ) cultivated in marginal arable land. WF results demonstrate that the Hybrid pennisetum system has the largest impact on the water resources whereas the other two technology options exhibit the characteristics of environmental sustainability. The large variances in contribution ratio between the four sub-processes in terms of total impacts are reflected by the LCA results. The Anaerobic Digestion process is found to be the main contributor whereas the Digestate management process is shown to be able to effectively mitigate the negative environmental impacts with an absolute share. Sensitivity analysis is implemented to detect the impacts of loss ratios variation, as silage mass and methane, on final results. The methane loss has the largest influence on the Hybrid pennisetum system, followed by the Maize system. Above all, the Sorghum system demonstrates the best performance amongst the considered assessment categories. Our study builds a pilot reference for further driving large-scale project of bioenergy production and conversion. The synergy of combined WF-LCA method allows us to conduct a comprehensive assessment and to provide insights into environmental and resource management.

High transition costs remain a major barrier to deeply decarbonizing sectors such as transport in many developing countries. Choice of mode and complementary policies are critical to shaping the costs of climate mitigation in the transport sector. This paper investigates the potentials offered by combined technological and behavioural changes stimulated by strategic infrastructure deployment that can facilitate decarbonization of transport in China. Our study is carried out using IMACLIM-R, a state-of-the-art integrated assessment model, which includes a detailed representation of transport dynamics by incorporating the behavioural determinants of mobility in a standard transport modelling framework. More specifically, this behavioural representation considers (i) the spatial organization of residential dwellings and industrial production, (ii) modal shift induced by transport infrastructure deployment and (iii) the intensity of freight transport production and distribution processes. It is found that supplementing carbon pricing with behavioural measures and a decoupling of economic activity from mobility needs can efficiently promote a modal shift towards low-carbon transport modes and reallocate the sectoral distribution of mitigation efforts. This in turn would significantly reduce the macro-economic impacts of deeply decarbonizing Chinese transport activities over the next decades. Complementary policies should focus on infrastructure, fiscal incentives, land-use, building regulations and other policies affecting the ways urban activities are distributed within the city's boundary, along with industrial policies and other regulations that affect where firms choose to locate. Key policy insights To decarbonize China's transport sector an integrated approach is needed due to strong inertia and distributional effects. Complementary policies have to focus on transport infrastructure, fiscal incentives, land-use and building regulations, as well as spatial organization. Transport-related climate policies interconnect with the ways in which urban activities are distributed within the city's boundary, but also with industrial policies and other regulations that affect where firms choose to locate. A suite of policy instruments is required, including larger institutional incentives and greater financial leverage supporting innovations in the transport sector.

As global public health is under threat by the 2019-nCoV and a potential new wave of large-scale epidemic outbreak and spread is looming, an imminent question to ask is what the optimal strategy of epidemic prevention and control (P&C) measures would be, especially in terms of the timing of enforcing aggressive policy response so as to maximize health efficacy and to contain pandemic spread. Based on the current global pandemic statistic data, here we developed a logistic probability function configured SEIR model to analyse the COVID-19 outbreak and estimate its transmission pattern under different "anticipate- or delay-to-activate" policy response scenarios in containing the pandemic. We found that the potential positive effects of stringent pandemic P&C measures would be almost canceled out in case of significantly delayed action, whereas a partially procrastinatory wait-and-see control policy may still be able to contribute to containing the degree of epidemic spread although its effectiveness may be significantly compromised compared to a scenario of early intervention coupled with stringent P&C measures. A laissez-faire policy adopted by the government and health authority to tackling the uncertainly of COVID19-type pandemic development during the early stage of the outbreak turns out to be a high risk strategy from optimal control perspective, as significant damages would be produced as a consequence.

This paper aims to investigate a new determinant of the demand for children: upward mobility. Upward mobility can affect the demand for children in two opposite directions: upward mobility means more resources to spend on childbearing and increases the demand for children; it also lowers the need to rely on children for old-age support and this leads to lower demand for children. In this paper, we use the difference between the subject's self-evaluations of the future and current social class as the measure of upward mobility, and fertility desire to represent the demand for children. Using the Chinese General Social Survey (CGSS) data, we find that upward mobility significantly increases the demand for children, and the results are robust across various model specifications (pooled data regression, Poisson regression, and IV regression). The effect is concentrated among affluent and/or urban households, suggesting that those from more advantaged social-economic backgrounds appear to have a higher elasticity of fertility in response to upward mobility. Our results imply that improving upward mobility and public services such as education, health care, and social security would be effective to boost fertility in China.

This paper examines ethnic differences in fuelwood consumption in rural households, using an original survey dataset from two western Chinese provinces with large ethnic minority populations. We use a Heckman two-stage selection model to explain the quantity of fuelwood consumed conditional on a decision to use fuelwood. We find that ethnic minority families are more likely than majority Han Chinese families to use fuelwood. We also find that a household's off-farm income has a stronger negative effect on the quantity of fuelwood consumed for the ethnic minority families than for the Han Chinese families. In addition, families owning a larger area of forestland are more likely to use fuelwood. Yet the quantity of fuelwood consumed, especially in ethnic minority families, does not increase with owned forestland. Finally, we find that coal, rather than electricity, is a substitute for fuelwood for residential cooking and heating.

Since the outbreak of the novel coronavirus disease (COVID-19) at the beginning of December 2019, there have been more than 28.69 million cumulative confirmed cases worldwide as of 12th September 2020, affecting over 200 countries and regions with more than 920,463 deaths. The COVID-19 pandemic has been sweeping worldwide with unexpected rapidity. In this paper, a hybrid modelling strategy based on tessellation structure- (TS-) configured SEIR model is adopted to estimate the scale of the pandemic spread. Building on the data pertaining to the global pandemic transmission over the last six months around the world, key impact factors in the transmission and control procedure have been analysed, including isolation rate, number of the infected cases before taking prevention measures, degree of contact scope, and medical level, so as to capture the fundamental factor influencing the pandemic. The quantitative evaluation allowed us to illustrate the magnitude of risks of pandemic and to recommend appropriate national health policy of prevention measures for effectively controlling both intra- and interregional pandemic spread. Our modelling results clearly indicate that the early-stage preventive measures are the most effective action to be taken to contain the pandemic spread of the highly contagious nature of the COVID-19.

Background Since the outbreak of novel coronavirus disease (COVID-19) in Wuhan, China at the beginning of December 2019, there have been over 11,200,000 confirmed cases in the world as of the 3rd July 2020, affecting over 213 countries and regions with nearly 530,000 deaths. The pandemic has been sweeping all continents, North America, Latin America, Europe, Middle East and South Asia among others at an alarming rapidity. Here, we provide an estimate of the scale of the pandemic spread under different scenarios of variation in key influencing parameters with a hybrid model. Methods We developed a new hybrid model of infectious disease transmission based on Cellular Automata (CA)-configured SEIR to analyse the COVID-19 outbreak and estimate its transmission pattern. A probabilistic contamination network is embedded in the pandemic transmission model to capture the randomness feature of person-to-person spread of the novel virus. We used the improved SEIR model to quantify the population contact state with isolation measures under different continuous time series contact probability via CA. We adjusted the modelling parameters to verify the model performance in accordance to the data from the reports published by the Chinese Center for Disease Control and Prevention. We simulated several scenarios by varying such key parameters as number of isolation rate, average contact times of the population, number of infected people before taking prevention and control measures, medical level and number of imported cases. Results In the baseline model, we identified that the isolation control as the most influencing factor that had the largest impact on decreasing the speed of the reproductive number, accelerating the arrival of the “inflection point” of pandemic prevention and control, and the death rate reduction. We estimated that the probability of people contacts and the number of the onset infected cases before prevention measures also had significant effect on the infection rate reduction with appropriate prevention measures adoption, which partly reflects the impact of timely measure on the severity of the outbreak. We found that imported cases will risk the domestic prevention. Conclusions Our modelling results clearly indicate that early-stage preventive measures are the most effective way to contain the pandemic spread and a strong interventionist approach needs to be adopted by policymakers vis-à-vis of the highly contagious nature of the COVID-19. Human resources, intensified isolation and confinement as well as special hospital buildings should be prioritised in countries with large number of infections to constrain the global transmission of the virulent infection. To do so, internationally coordinated actions require to be taken to replicate good practices to less infected countries and regions immediately.

Background: A novel coronavirus (COVID-19) caused pneumonia broke out at the end of 2019 in Wuhan, China. Many cases were subsequently reported in other cities, which has aroused strong reverberations on the Internet and social media around the world. Objective: The aim of this study was to investigate the reaction of global Internet users to the outbreak of COVID-19 by evaluating the possibility of using Internet monitoring as an instrument in handling communicable diseases and responding to public health emergencies. Methods: The disease-related data were retrieved from China's National Health Commission (CNHC) and World Health Organization (WHO) from January 10 to February 29, 2020. Daily Google Trends (GT) and daily Baidu Attention Index (BAI) for the keyword "Coronavirus" were collected from their official websites. Rumors which occurred in the course of this outbreak were mined from Chinese National Platform to Refute Rumors (CNPRR) and Tencent Platform to Refute Rumors (TPRR). Kendall's Tau-B rank test was applied to check the bivariate correlation among the two indexes mentioned above, epidemic trends, and rumors. Results: After the outbreak of COVID-19, both daily BAI and daily GT increased rapidly and remained at a high level, this process lasted about 10 days. When major events occurred, daily BAI, daily GT, and the number of rumors simultaneously reached new peaks. Our study indicates that these indexes and rumors are statistically related to disease-related indicators. Information symmetry was also found to help significantly eliminate the false news and to prevent rumors from spreading across social media through the epidemic outbreak. Conclusion: Compared to traditional methods, Internet monitoring could be particularly efficient and economical in the prevention and control of epidemic and rumors by reflecting public attention and attitude, especially in the early period of an outbreak.

Drawing on the perspectives of interfirm governance mechanisms, we develop a contingency theoretical framework that examines how contract specificity and trust interact with local suppliers' physical asset specificity and human asset specificity in shaping the relationship performance of offshore cooperation between local suppliers and global buyers. The empirical data for hypothesis testing were collected from a survey of 162 dyads composed of Chinese local suppliers and international buyers. The empirical results reveal an inverted U-shaped relationship between physical asset specificity and relationship performance, and this inverted U-shaped relationship is stronger when the level of contract specificity is higher. There is a linear and positive relationship between human asset specificity and relationship performance, and this relationship becomes stronger when the level of trust between the local supplier and international buyer is higher.

This study develops and tests several bonding theory-derived hypotheses using a panel dataset covering the Chinese firms cross-listed in the US, Hong Kong, Singapore and London over the period 2001-2012. Our empirical results challenge the general postulate of bonding theory that cross-listing in international stock markets helps to improve the corporate and financial performance of firms whose home countries have weaker institutions and lower-level legal enforcement to protect minor investors. We show that the bonding theory only holds partially for Chinese firms cross-listed in the United States markets, whereas it is not evidenced for the rest of share markets in the sample. It is argued that the general bonding theory needs to contextualise endogenous characteristics such as firms' listing locations.

This article describes how technology—i.e. the infrastructure of tools, systems, platforms—enhances knowledge transfer. The effect of tools on the relationship between knowledge characteristics and knowledge transfer effectiveness is under-researched. This article attempts to address the interplay of knowledge characteristics and transfer tools within multinational corporations (MNCs). Based on the structural equation modelling, this research proposes and tests a basic model that captures knowledge characteristics and transfer tools at 125 Japanese subsidiaries operating in China. Drawing on the literature, this article argues that the role of knowledge characteristics and transfer tools need to be considered for effective knowledge transfer between MNCs and their subsidiaries. Knowledge characteristics and transfer tools play differing roles in knowledge transfer. This article also extends the existing studies by focusing on knowledge characteristics and transfer tool constructs simultaneously in a model to understand the notion of knowledge transfer effectiveness in the global business context.

The initiative to build "The Belt and Road" by Chinese government has provided more opportunities for the development of Southeast Asian and South Asian countries.Myanmar is one of the key nodes connected "The Belt and Road".China and Myanmar have maintained good neighborly relations and good cooperation in international and regional affairs for a long period.Especially, in recent years, Sino-Myanmar trade cooperation has expanded to project contracting, investment and multilateral cooperation.Although the achievements have been impressive, many setbacks have also been encountered.One significant setback is that the investment risks are relatively high because the national condition in Myanmar is similar to other unrested countries in Southeast Asia and South Asia.This paper selects the typical major Chinese investment projects in Myanmar and analyzes them by summarizing the deep-seated reasons for the suspension or interruption of certain project as well as revealing the successful experiences of some projects，in order to provide references and principals for investment cooperation in Southeast Asian and South Asian countries.

Purpose - The purpose of this paper is to develop and empirically test a theoretical framework examining how local network ties and global network ties affect firms' innovation performance via their absorptive capacities. Design/methodology/approach - The conceptual framework is empirically tested in a field study with multi-source data collected from a sample of 297 manufacturing firms located in four. Manufacturing clusters in the south-eastern Yangtze River Delta of China. Hypotheses were tested with the use of path analysis with maximum likelihood robust estimates through the structural equation modelling approach. Findings - The asymmetry between local network ties (LNT) and global network ties (GNT) in terms of influences on firms' innovation performance is confirmed by empirical tests. LNT not only significantly and positively contribute to firms' innovation performance directly but also enhance it indirectly via absorptive capability, whereas GNT exhibit only marginal influence on innovation performance. GNT are shown to boost innovation performance (IP) only indirectly via firms' absorptive capacities. Knowledge heterogeneity and the difference between domestic and multinational firms' institutional environment are considered to be the main causes of the asymmetric effects. Originality/value - While the previous literature either focused on the mediating role of firms' knowledge absorptive capacities or investigated the effects of social networks separately, this study incorporates both mechanisms into a single analytical framework to better account for the interactions between network effects and absorptive capacities. The results challenge some previous studies positing that GNT are stronger determinants than LNT in shaping a local firm's innovation capacity in emerging economies, and the findings emphasize the importance of absorptive capacity in helping local enterprises to leverage external linkages to enhance firm's innovation performance.