This paper examines the impact of China's 2012 Green Credit Guidelines (GCG) on the green technological innovation of heavily polluting enterprises (HPEs). Using a panel dataset of 491 listed companies from 2009 to 2018, the study employs a Matched Difference-in-Differences (DID) model to analyse the policy's effects, complemented by Triple and Quantile DID models to explore underlying mechanisms. The results indicate that, contrary to expectations, the GCG negatively impacts green innovation among HPEs, particularly affecting private, smaller-scale, financially constrained, and low-profit firms in highly competitive markets. However, the adverse effect is short-term, with firms that have greater financial resilience, access to subsidies, stronger initial green innovation capabilities, and market power better able to withstand financial restrictions. The findings highlight the need for more tailored green credit policies that consider firm-specific characteristics to effectively promote green innovation.

Complex media environments often intertwine multiple focal actors in media reports and different characteristics of media coverage. Credibility differences among various media sub-markets further exacerbate this complexity. Previous studies have limited understanding of the interactions between different focal subjects or media characteristics. This study focuses on the niche media market of official media coverage on corporate artificial intelligence (AI)-related activities to explore the impact of official media evaluations on the duration of corporate initial public offering (IPO) processes and the nonlinear moderating role of leadership media exposure on this impact. We examined the IPO review activities of 735 Chinese firms under the under the registration-based IPO system from 2019 to 2022, with a specific focus on media sentiment analysis through supervised machine learning techniques. Our findings are largely support our hypotheses: positive evaluations by official media of corporate AI activities are associated with shorter IPO process durations, with moderate leadership media exposure being most effective in expediting the process. Additionally, although official media can filter out firms with strong AI capabilities, these firms tend to exhibit poorer profitability after their IPOs. This study establishes connections between the relatively fragmented literature on different focal subjects and media characteristics.

The composition-based view explains how emerging market firms creatively adopt compositional investment, compositional offerings, and compositional capabilities to gain a competitive advantage in the global marketplace. How the composition-based international strategy contributes to organizational resilience under the de-globalization world remains unclear. Using fuzzy-set qualitative comparative analysis, we explore how emerging market firms reconfigure compositional elements and the crucial role of firm heterogeneity in determining organizational resilience. Our analysis of 250 Chinese manufacturing firms revealed five distinct international compositional strategies and asymmetric outcomes. Multiple configurations of composition-based international strategies and firm heterogeneity were found to be related to high and low organizational resilience. Our findings confirm that emerging market firms must reconfigure their compositional elements to achieve sustained and resilient performance throughout the pandemic. Our findings extend the composition-based view by elucidating the multiple pathways and boundary conditions of compositional strategies leading to organizational resilience.

In this paper, we analyze the economic impacts of the West-East Electricity Transmission Project (WEETP) project using the multi-period difference-in-difference (DID) method based on county-level data from 2000 to 2020. Our findings indicate that the WEETP project inhibits firm entry in electricity-exporting regions while encouraging firm entry in electricity-importing regions, thus hindering regional development equalization. Specifically, the initiation of WEETP discouraged firm activity in the southern and central corridors' exporting regions but boosted firm activity in the northern corridor. Additionally, WEETP exacerbated infrastructure overbuilding and environmental damage in energy-exporting regions, further weakening entrepreneurial dynamism (ED) and widening the development gap with energy-importing regions. Our study provides insights into the real impact of national energy strategies on regional development and highlights the institutional factors contributing to the resource curse. The findings demonstrate the limitations of non-market pricing approaches to resource allocation, thereby offering an empirical basis for narrowing the development gap and promoting developmental affirmative action.

Identifying the vital role of climate risk in developing technology is significant to promote the Fourth Industrial Revolution. The research utilises the full and sub-sample methodologies to capture the connection of the Southern Oscillation Index (SOI) and technological progress (TP) from the global perspective. In light of the quantitative discussion, we conclude that positive and adverse effects exist of SOI on TP, and the favourable one suggests that the La Nina phenomenon promotes technological progress. However, this opinion cannot be established in the adverse effect of SOI on TP that accompanies the La Nina phenomenon, which is primarily caused by the global financial crisis. Other adverse effects that accompany the El Nino phenomena point out that these climate risks are conducive to developing technology. In turn, the favourable and adverse influences from TP to SOI are accompanied by the El Nino phenomenon and La Nina event respectively, underlining that the development of technology is beneficial for alleviating climate risk. In the context of an increasingly severe climate crisis and a new round of scientific and technological revolution, this article will put forward valuable suggestions to tackle climate risk in the context of the Fourth Industrial Revolution.

Exploring the role of artificial intelligence (AI) in renewable energy (RE) development is pivotal for seizing technological opportunities and achieving climate objectives. This study uses wavelet analysis to examine the correlation between AI and RE in China. Our findings indicate a co-movement between AI and RE from 2014 to 2016 and a positive influence from AI to RE emerging from late 2018 to 2022. This suggests that AI acts as a facilitator for China's energy transition. Nevertheless, this effect is not constant; it becomes more pronounced with advancements in AI technology. These outcomes align with the techno-economic paradigms framework, implying that China can benefit from AI breakthroughs to accelerate its energy transition. Future policy efforts may focus on fostering collaboration among the government, businesses, and universities to promote AI and RE development.

To uncover the secrets of creating competitive advantage for firms under demand uncertainty, we study the roles of technology level and capacity investment strategies. Specifically, we analyze the Nash equilibrium of two competing firms at different technology levels under two capacity investment strategies, namely flexible or inflexible. We examine both symmetrical competition where the two firms adopt a same capacity type (flexible or inflexible), and asymmetrical competition where the two firms invest different capacity types. We find that an advanced technology level incentivises capacity expansion regardless of the capacity strategy adopted. In addition, the technology-capacity relationship significantly depends on demand distribution when both firms adopt inflexible capacity investment, but is independent of demand distribution when both firms invest in flexible capacity. No overwhelming superiority is observed from either side when both firms adopt the same capacity investment, and firms always co-exist in a profitable market, despite significant differences in technology. However, overwhelming superiority emerges from one side when both firms have different capacity investments. A firm can squeeze out its competitor and capture the entire market by upgrading its technology. When the two firms adopt the same capacity strategy, each firm may increase or decrease its technology level and capacity volume proportionally in equilibrium, regardless of the competition scenarios. We further explore the endogenous capacity investment type and technology flexibility in competition. We show that the competition effect plays an important role when the flexible capacity cost is moderate.

As an overarching goal of the European Union’s (EU) policies, sustainable development has become one of the trickiest challenges in the EU. Despite the burgeoning literature on sustainable development in EU member states, few studies have explored the relationship between green cooperation and sustainable development. From the resource orchestration perspective, we aim to investigate how EU green cooperation affects member states’ pursuit of sustainable development. Empirically, we constructed a sample of well-documented EU joint green projects, and found that the participation of the higher education sector (HES), business sector (BUS), and government (GOV) in EU green cooperation contributes to achieving its member states’ sustainable development goals in different ways. Specifically, the contributions of the HES and BUS, compared to those of the GOV, are more essential for EU green cooperation projects, because of their dominant roles in green knowledge generation and carbon emissions make them pivotal for the EU member states’ sustainable development. Moreover, our findings suggest that green cooperation among the HES, BUS, and GOV has a more significant impact on EU member states’ sustainable development when those states possess a stronger capacity for transnational knowledge spillovers and a higher national digital level. These findings have important implications for the design of green policies in pursuit of sustainability within the EU region.

We study the emerging customer-to-manufacturer (C2M) mode, in which the e-platform analyzes customer data and offers recommendations to manufacturers. We consider two types of C2M mode: the platform establishes its own brand (self-built mode) and the platform conducts joint development with the manufacturer (joint-development mode). We show that the manufacturer always benefits from a lower quality difference, whereas the platform does not. Interestingly, under the self-build mode, a smaller brand devaluation effect benefits not only the platform, but also the manufacturer. Further, we discover that a win-win situation exists if the manufacturer and the platform choose the same mode.

The fairness of vocational contest scoring is key to generating reliable competency assessments. This study examined the performance impact of the motivation of English-as-a-foreign-language learners in contests with vocabulary knowledge antecedents in the contexts of artificial intelligence (AI) and blockchain (BC). The sample comprised 185 participants of an oral English contest at higher vocational institution in China. AI-powered scoring of learners' contest performance and a survey were used to collect data. The findings revealed that learners' intrinsic drive was the main positive factor, outweighing their extrinsic motivation, and that AI and BC increased the trustworthiness and integrity of contest records, thus providing new opportunities to build learner trust and form psychological incentives. This study enriches foreign language motivation theory in the context of contest research and highlights the importance of using AI and BC to enhance the scoring accuracy and credibility of contests as authoritative evaluation instruments in vocational education.

The fairness of vocational contest scoring is key to generating reliable competency assessments. This study examined the performance impact of the motivation of English-as-a-foreign-language learners in contests with vocabulary knowledge antecedents in the contexts of artificial intelligence (AI) and blockchain (BC). The sample comprised 185 participants of an oral English contest at higher vocational institution in China. AI-powered scoring of learners' contest performance and a survey were used to collect data. The findings revealed that learners' intrinsic drive was the main positive factor, outweighing their extrinsic motivation, and that AI and BC increased the trustworthiness and integrity of contest records, thus providing new opportunities to build learner trust and form psychological incentives. This study enriches foreign language motivation theory in the context of contest research and highlights the importance of using AI and BC to enhance the scoring accuracy and credibility of contests as authoritative evaluation instruments in vocational education.

Uncertainty in the demand of individual customers increases demand volatility in the entire market. In this context, partial volume flexibility can help hedge against demand uncertainty and competition pressure, and subsequently help create value by means of high-quality production decisions and market responsiveness, within the assumption of transformation and applied knowledge incorporated into the production stages. The article aims to investigate this phenomenon. To achieve this, as part of the methodology, a unified measure, the flexibility degree, is taken to represent the level of partial volume flexibility. We find that under demand uncertainty, a firm goes through a process with four stages—capacity decision, stable production, flexible production, and pricing. In a monopoly model, we find that a slight change in the flexibility degree could significantly increase a firm's adjustable production range to respond to demand changes. Furthermore, we develop a general asymmetric duopoly model. We characterize the equilibrium and find that a firm with a higher flexibility degree is more sensitive to demand changes. Accordingly, in response to specific demand, a higher flexibility firm obtains more profit only when the demand is sufficiently high or low, otherwise, the lower flexibility firm wins. Finally, we observe that a firm's capacity increases in its flexibility degree and decreases in its rival's flexibility degree; this is because the firm balances the market share and product profitability.

We examine the effect of financial and manufacturing co-clustering on high-quality green development in China’s 30 provinces from 2005 to 2020. The nexus between financial and manufacturing co-clustering and high-quality green development has been comprehensively investigated from linear and non-linear perspectives. We find that financial and manufacturing co-clustering significantly fosters high-quality green development. Mechanism analysis shows that formal environmental regulation has a significant negative moderating effect on high-quality green development, whereas informal environmental regulation plays a significantly positive moderating role. However, empirical results only show the mediation effect of formal environmental regulation in the incentive role of financial and manufacturing co-clustering to high-quality green development. A dynamic panel threshold model also certifies the non-linear effect between financial and manufacturing co-clustering and high-quality green development. Lastly, the promotion effect of financial and manufacturing co-clustering on high-quality green development creates significant heterogeneity.

Digital innovation has revolutionized organizational processes and outcomes in several industries. Previous studies emphasize the transformational nature of digital innovation in redefining the nature of competition and exposing incumbent industry players to a dire fate. We focus on the retail sector, where platform sponsors leverage digital innovation to intermediate the exchanges between buyers and sellers and orchestrate complementary innovations to make the platform ecosystem more valuable to members. We investigate whether digital innovation in retail platform ecosystem renders established competencies of traditional intermediaries obsolete through a case study of Alibaba Lingshoutong, a business-to-business digital sourcing and distribution platform. The analysis shows the oppositional nature of digital innovation built from a transaction cost rationality and existing practices based upon social capital. This study reveals the incremental nature of digital innovation, a dimension which receives little attention thus far. Based on some preliminary empirical findings and conceptual rationale, we developed three propositions.

Blockchain hasbecome a widely used information system technology recently because of its effectiveness as an intermediary-free platform. While the use of blockchain in various fields, such as finance, supply chains, healthcare, education, and energy consumption, is increasingly enabling the development of Internet-enabled “distributed databases,” there are not many exploratory studies available to provide an understanding of how the field is progressing. Therefore, it is imperative to explore the status quo of blockchain technology in the finance sector, particularly highlighting how blockchain architectures can aid the finance sector to gain competitive advantage. This systematic literature review analyzes the content of the 50 most relevant articles and professional industry reports through peer-reviewed relevant academic literature in the finance sector from 2008 to 2022 to identify several possible features of blockchain research in the financial sector. This study highlighted the dimensions of blockchain technology, blockchain in finance, its competitive advantages, the current status of finance, and various challenges that keep the implementation of blockchain-based financial information systems at the initial stage. We identified three main areas that require research attention in order for blockchain technology to become the “next-generation networks” that will revolutionize the financial sector.

New energy vehicles (NEVs) are considered to ease energy and environmental pressures. China actively formulates the implementation of NEVs development plans to promote sustainable development of the automotive industry. In view of the diversity of vehicle pollutants, NEV may show controversial environmental results. Therefore, this paper uses the quantile-on-quantile method to explore the relationship between NEVs and skewed patterns of pollutants distribution, aimed to comprehensively evaluate the role of new energy in the automotive industry in the environment improvement. The results show almost invisible environmental-friendly benefits from the current new energisation development. The main reason is that the industry is still growing, and technology and service have to be improved. Traditional and new energy power in the automotive market coexist. Hence, the final air pollution brought by the automotive is also changeable due to the scale of new energy vehicles, which the energy-environment model supports. In particular, the results evidence that the performance of battery electric vehicles (BEVs) is better than plug-in hybrid electric vehicles. As the total amount of BEVs increased, air pollution has effectively alleviated. This also confirms that NEVs play an indispensable role in exhaust emissions pollution prevention, although their effect remains to be displayed more obviously.

Managers and the market place a higher importance on environmental management of businesses as sustainable development becomes the focus of attention. At the same time, the digital economy has become the most dynamic and emerging mode of economic development, driving future business trends and technological innovations. This special issue of Ecological Chemistry and Engineering S (ECE S) collects 6 articles focusing on the challenges and problems in the digital transformation and corporate environment management, which aims to share and discuss the recent advances and future trends of theory and application in academia, and to bring practical implications and experience in industry developers.

Although the importance of artificial intelligence (AI) has often been highlighted in strategic agility and decision outcomes, whether it helps firms strengthen their competitiveness and the means firms use to achieve such competitiveness are still under-researched. Our research thus joins the recent discussion on digitalization trends and strategic responses to COVID-19 to better understand how firms strengthen their competitiveness during such challenging times. Namely, this study incorporates the strategic responses to COVID-19 into the technology–organization–environment (TOE) framework by investigating the impacts of different configurations of TOE contexts and strategic responses on a firm's competitive advantage. We used fuzzy-set qualitative comparative analysis to investigate how TOE contexts and strategic responses integrate into configurations and impact a firm's competiveness. By applying a configurational approach with data from 514 exporting firms in China, we find a strong indication of the equifinality of different strategies, indicating that multiple strategic paths can be used to respond to crises. The adoption of AI, while important, is not sufficient to enhance a firm's competitiveness. Our results stress the significance of data quality, organizational resources and capabilities, and digital business model innovation for AI adoption. We also identify successful strategic paths of AI adoption aversion and ambidextrous strategies. The findings have practical implications for firms seeking effective strategies to respond to future crises and sustain their competitive advantages.

Exploring the connectedness and time-varying attributes of conventional and new energy markets is crucial to the green-oriented transition of energy. This investigation performs bootstrap full-and sub-sample techniques to explore the correlation between the oil and lithium markets, and further probe whether lithium could threaten the status of oil. The empirical outcomes reveal that oil price (OP) exerts positive influences on lithium price (LP). High OP increases the lithium demand and its price through taking new energy vehicles as substitutes for conventional automobiles, indicating that lithium may threaten the status of oil under the oil bull market. But the above opinion could not be supported under the oil bear market, low OP lessens the attraction of new energy vehicles and then reduces lithium demand and LP. In turn, low LP negatively affects OP since oil is also a vital engine for economic development. Thus, these outcomes are consistent with the price correlation model, and lithium can only partially replace oil as a vehicle fuel under certain situations, the latter's status could not be threatened completely. Against a backdrop of urgent green transition and potential oil and lithium bubbles, these conclusions bring meaningful inspirations to the public, enterprises and countries.