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This study aims to examine the ramifications of corporate environmental, social and governance (ESG) investing in zombie firms and considers how external funding support may moderate this relationship given the sustainable nature of ESG performance, which often incurs costs.

Panel regression analyses used data from China’s A-share listed companies from 2011 to 2019, resulting in a data set comprising 6,054 observations.

Despite firms’ additional financial burdens, corporate ESG investing emerges as a catalyst in resurrecting zombie firms by attracting investor attention. Further analysis underscores the significance of funding support from entities such as the government and banks in alleviating ESG cost pressures and enhancing the efficacy of corporate ESG investing. Notably, the positive impact of corporate ESG investing is most pronounced in non-heavily polluting and non-state-owned firms. The results of classification tests reveal that social (S) and governance (G) investing yield greater efficacy in revitalizing zombie firms compared to environmental (E) investing.

This research enriches the discourse on corporate ESG investing and offers insights for governing zombie firms and shaping government policies.

By extending the domain of ESG research to encompass zombie firms, this paper sheds light on the multifaceted role of corporate ESG investing. Furthermore, this study comprehensively evaluates the influence of external funding support on the positive outcomes of ESG investing, thereby contributing to the resolution of the longstanding debate on the relationship between ESG performance and corporate financial performance, particularly with regard to ESG costs and benefits.

The purpose of this paper is to present an optimisation of four-point star-shaped structures produced through additive manufacturing (AM) polylactic acid (PLA). The study also aims to investigate the compression failure mechanism of the structure.

A Taguchi L₉ orthogonal array design of the experiment is adopted in which the input parameters are resolution (0.06, 0.15 and 0.30 mm), print speed (60, 70 and 80 mm/s) and bed temperature (55°C, 60°C, 65°C). The response parameters considered were printing time, material usage, compression yield strength, compression modulus and dimensional stability. Empirical observations during compression tests were used to evaluate the load–response mechanism of the structures.

The printing resolution is the most significant input parameter. Material length is not influenced by the printing speed and bed temperature. The compression stress–strain curve exhibits elastic, plateau and densification regions. All the samples exhibit negative Poisson’s ratio values within the elastic and plateau regions. At the beginning of densification, the Poisson’s ratios change to positive values. The metamaterial printed at a resolution of 0.3 mm, 80 mm/s and 60°C exhibits the best mechanical properties (yield strength and modulus of 2.02 and 58.87 MPa, respectively). The failure of the structure occurs through bending and torsion of the unit cells.

The optimisation study is significant for decision-making during the 3D printing and the empirical failure model shall complement the existing techniques for the mechanical analysis of the metamaterials.

To the best of the authors’ knowledge, for the first time, a new empirical model, based on the uniaxial load response and “static truss concept”, for failure mechanisms of the unit cell is presented.

Conceptual and empirical research over the past 20 years has moved the social media (SM) literature beyond the embryotic stage to a well-developed academic discipline. As the lead article in the special issue in the Journal of Research in Interactive Marketing on Cutting-Edge Research in Social Media and Interactive Marketing, this review and agenda article has two key goals: (1) to review key SM and interactive marketing research over the past three years and (2) to identify the next wave of high priority challenges and research opportunities.

Given the “cutting-edge” research focus of the special issue, this review and research agenda paper focused on articles published in 25 key marketing journals between January 2021 and March 2024. Initially, the search request was for articles with “social media, social selling, social commerce” located in the article title, author-selected key words and journal-selected keywords. Later, we conducted searches based on terminology from articles presented in the final review. In total, over 1,000 articles were reviewed across the 25 journals, plus additional ones that were cited in those journals that were not on the initial list.

Our review uncovered eight key content areas: (1) data sources, methodology and scale development; (2) emergent SM technologies; (3) artificial intelligence; (4) virtual reality; (5) sales and sales management; (6) consumer welfare; (7) influencer marketing; and (8) social commerce. Table I provides a summer of key articles and research findings for each of the content areas.

As a literature review and research agenda article, this paper is one of the most extensive to date on SM marketing, and particularly with regard to emergent research over the past three years. Recommendations for future research are integrated through the paper and summarized in Figure 2.

Consumer welfare is one of the eight emergent content areas uncovered in the literature review. Specific focus is on SM privacy, misinformation, mental health and misbehavior.

This research exclusively focuses on China’s elderly Internet users given how severe a threat disinformation has become for this particular population group as social media platforms thrive and the number of elderly netizens grows in China. The purpose of this study is to explore the mechanism of how elderly social media users’ intention to identify false information is influenced helps supplement the knowledge system of false information governance and provides a basis for correction practices.

This study focuses on the digital literacy of elderly social media users and builds a theoretical model of their intention to identify false information based on the theory of planned behaviour. It introduces two variables – namely, risk perception and self-efficacy – and clarifies the relationships between the variables. Questionnaires were distributed both online and offline, with a total of 468 collected. A structural equation model was built for empirical analysis.

The results show that digital literacy positively influences risk perception, self-efficacy, subjective norms and perceived behavioural control. Risk perception positively influences subjective norms, perceived behavioural control and the attitude towards the identification of false information. Self-efficacy positively influences perceived behavioural control but does not significantly impact the intention to identify. Subjective norms positively influence the attitude towards identification and the intention to identify. Perceived behavioural control positively influences the attitude towards identification but does not significantly impact the intention to identify. The attitude towards identification positively influences the intention to identify.

Based on relevant theories and the results of the empirical analysis, this study provides suggestions for false information governance from the perspectives of social media platform collaboration and elderly social media users.

In the construction of charging piles, traditional gas stations possess significant advantages in terms of regional and financial resources. The transformation of gas stations into “refueling+charging” integrated gas stations relies on charging pile manufacturers and government, involving coordination issues with them. This paper aims to propose a joint coordination contract based on the principles of cost-sharing and revenue-sharing. The objective is to achieve systemic coordination among integrated gas stations, charging pile manufacturers, and the government, optimizing the planning of the quantity of charging piles and charging prices.

We have constructed an operational system model based on the Stackelberg game between charging pile manufacturers, integrated gas stations, and government. We have analyzed the optimal quantity of charging piles and charging prices under the impact of government subsidy policies in both decentralized and centralized operation scenarios. Additionally, we have proposed a joint coordination contract based on cost-sharing and revenue-sharing to coordinate this tripartite operational system.

The study reveals that, under simple cooperative contracts, the optimal decision does not yield maximum profits for the operational system due to the “double-marginal effect”. However, under the impact of the joint coordination contract, which combines cost-sharing and revenue-sharing as proposed in this paper, gas stations will consider the charging pile manufacturer’s costs and government subsidies when determining the optimal quantity and price. This not only achieves system coordination but also results in Pareto improvement in the benefits of all system members by adjusting contract parameters.

The value of this research lies in its insights into operational strategies for the construction of charging piles for electric vehicles. By analyzing optimal decisions under different contract arrangements, the study provides guidance to relevant stakeholders, enabling the operational system to achieve greater efficiency and coordination and realize more extensive Pareto improvements. Furthermore, it extends the application of coordination contract theory in the context of charging pile construction and operations.

While the determinants of voluntary political spending disclosure have been extensively studied in the literature, there remains a lack of clear evidence regarding the specific impacts of managerial ability and political risk on such disclosure. Thus, the purpose of this study is to shed light on whether and how managerial ability and political risk influence firms’ political spending disclosure.

This study uses a sample of 2,242 firm-year observations of S&P 500 companies between 2013 and 2021.

This study finds that firms with high-ability managers generally disclose more information about political spending. This positive relationship between managerial ability and political spending disclosure holds even after conducting additional tests to address potential endogeneity concerns. Furthermore, this study finds that firms operating in high-risk political environments also exhibit a greater propensity to disclose information regarding their political spending. The results remain robust to alternative measures of managerial ability and political risk.

This study suggests that when designing policy to motivate firms to disclose political spending information, policy makers need to be aware of the critical role of managerial ability and idiosyncratic political risk the firm faces. In addition, this study offers insights to shareholders, advocacy groups, regulators and academics interested in understanding the determinants of political spending disclosure.

This study is among the first to provide empirical evidence that political spending disclosure can be explained by managerial ability and political risk. In addition, this study complements the literature on the consequences of managerial ability and political risk. Focusing on voluntary political spending disclosure, this study contributes to a deeper understanding of the factors shaping the overall corporate information environment.

The ongoing paradigm shift in the energy sector holds paramount implications for the realization of the sustainable development goals, encompassing critical domains such as resource optimization, environmental stewardship and workforce opportunities. Concurrently, this transformative trajectory within the power sector possesses a dual-edged nature; it may ameliorate certain challenges while accentuating others. In light of the burgeoning research stream on open innovation, this study aims to examine the intricate dynamics of knowledge-based industry-university-research networking, with an overarching objective to elucidate and calibrate the equilibrium of ambidextrous innovation within power systems.

The authors scrutinize the role of different innovation organizations in three innovation models: ambidextrous, exploitative and exploratory, and use a multiobjective decision analysis method-entropy weight TOPSIS. The research was conducted within the sphere of the power industry, and the authors mined data from the widely used PatSnap database.

Results show that the breadth of knowledge search and the strength of an organization’s direct relationships are crucial for ambidextrous innovation, with research institutions having the highest impact. In contrast, for exploitative innovation, depth of knowledge search, the number of R&D patents and the number of innovative products are paramount, with universities playing the most significant role. For exploratory innovation, the depth of knowledge search and the quality of two-mode network relations are vital, with research institutions yielding the best effect. Regional analysis reveals Beijing as the primary hub for ambidextrous and exploratory innovation organizations, while Jiangsu leads for exploitative innovation.

The study offers valuable implications to cope with the dynamic state of ambidextrous innovation performance of the entire power system. In light of the findings, the dynamic state of ambidextrous innovation performance within the power system can be adeptly managed. By emphasizing a balance between exploratory and exploitative strategies, stakeholders are better positioned to respond to evolving challenges and opportunities. Thus, the study offers pivotal guidance to ensure sustained adaptability and growth in the power sector’s innovation landscape.

The primary originality is to extend and refine the theoretical understanding of ambidextrous innovation within power systems. By integrating several theoretical frameworks, including social network theory, knowledge-based theory and resource-based theory, the authors enrich the theoretical landscape of power system ambidextrous innovation. Also, this inclusive examination of two-mode network structures, including the interplay between knowledge and cooperation networks, unveils the intricate interdependencies between these networks and the ambidextrous innovation of power systems. This approach significantly widens the theoretical parameters of innovation network research.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

This study used phenomenological narrative methodology to get insights into lived experiences of 10 Asian immigrant woman scholars in science, technology, engineering, and mathematics (STEM) in US institutions of higher learning. A feminist research approach overall guided the study. The concepts and theories of intersectionality, cultures of the academy, mindset, and mind tools framed the examination of the impacts of gender and work–family–community environments on the career pipeline of this group of women. The data were from two sources: (1) 48 documents on the participants and their institutions and (2) in-depth semi-structured interviews with these 10 participants. The findings show that gender and environment impacted the Asian women scholars’ career pipeline and advancement differently. On the negative side, barriers separately or jointly rooted in gender-based, racial, and hierarchical biases at stages of their career pipeline, from professional education to faculty appointment and leadership, challenged them. On the positive side, other gender-based and environmental agents and interventions supported them to overcome obstacles to their upward career mobility. This chapter has implications for how higher education institutions can improve their gender-based and environmental policies and praxis and facilitate the advancement of Asian immigrant women in STEM. It also has implications for how Asian women can prepare themselves to be successful in academic STEM careers.