Search results

This study intends to explore the relationship between digital finance and the vertical specialization of firms. The following questions are discussed: (1) As a representative new financial development model, what is the role of digital finance in the vertical specialization of firms? (2) If digital finance improves the level of vertical specialization of firms, what is the mechanism behind such improvement? (3) How does digital finance impact the vertical specialization of firms in different regions, industries, and firms?

A two-way fixed-effect model of panel data is proposed to verify the relationship between digital finance and the vertical specialization of firms. This model is constructed by matching the city-level data of digital finance with the data of China's A-share listed companies from 2011 to 2018. Meanwhile, the instrumental variable (IV) method and difference-in-difference (DID) method are adopted to deal with the endogeneity problem of the model.

The authors' study finds that digital finance has significantly improved the level of vertical specialization of firms. The result is robust under the endogeneity consideration and a series of robustness tests. After the dimensionality of the index is reduced, the depth of digital finance usage is more conducive to the improvement of the vertical specialization of firms compared with the width of digital finance coverage and the level of financial digitization. Digital finance mainly improves the level of vertical specialization of firms by reducing transaction costs and increasing the market thickness of the intermediate products. Moreover, digital finance has certain heterogeneity in promoting the vertical specialization of firms, an effect that is more significant in the eastern region, manufacturing industry and state-owned enterprises (SOEs).

The first limitation is the mechanism test. This research only analyzes the mechanism from transaction cost and the market thickness of the intermediate products. With the rapid development of information technology, digital finance will be further integrated into people's production and life. There will then be more mechanisms that should be explored between digital finance and the vertical specialization of firms. Another limitation is the data sample of this paper. The conclusions of this research are based only on the data of listed companies. However, in the authors' opinion, the specialization level of small and medium-sized enterprise (SMEs) should be higher. Therefore, the conclusions of this work are underestimated, which can be considered as the lower limit of digital finance for enterprise specialization.

As a favorable financing channel to supplement traditional financial service functions, digital finance plays a critical role in the operating efficiency of enterprises and the effective allocation of macro resources. The authors' research shows that digital finance has significantly improved the vertical specialization of firms. This conclusion provides guides to improve the production efficiency of enterprises and the quality of economic development.

This paper has three main contributions. (1) The relationship between financial development and the vertical specialization of firms is innovatively discussed from the perspective of digital finance, which implies that digital finance can effectively promote the level of vertical specialization of firms. (2) This paper provides new perspectives and ideas to reveal the impact mechanism of digital finance on the real economy by systematically analyzing the mechanism of digital finance on the vertical specialization of firms from the perspectives of transaction costs and financing constraints. (3) The regional differences in the development of digital finance, industry differences in the vertical specialization of firms and differences in the nature of enterprise property rights are all under consideration, which improves the effectiveness and pertinence of digital finance in promoting the vertical specialization of firms.

This study aims to assess the use of variational quantum imaginary time evolution for solving partial differential equations using real-amplitude ansätze with full circular entangling layers. A graphical mapping technique for encoding impulse functions is also proposed.

The Smoluchowski equation, including the Derjaguin–Landau–Verwey–Overbeek potential energy, is solved to simulate colloidal deposition on a planar wall. The performance of different types of entangling layers and over-parameterization is evaluated.

Colloidal transport can be modelled adequately with variational quantum simulations. Full circular entangling layers with real-amplitude ansätze lead to higher-fidelity solutions. In most cases, the proposed graphical mapping technique requires only a single bit-flip with a parametric gate. Over-parameterization is necessary to satisfy certain physical boundary conditions, and higher-order time-stepping reduces norm errors.

Variational quantum simulation can solve partial differential equations using near-term quantum devices. The proposed graphical mapping technique could potentially aid quantum simulations for certain applications.

This study shows a concrete application of variational quantum simulation methods in solving practically relevant partial differential equations. It also provides insight into the performance of different types of entangling layers and over-parameterization. The proposed graphical mapping technique could be valuable for quantum simulation implementations. The findings contribute to the growing body of research on using variational quantum simulations for solving partial differential equations.

The coal-fired power plants have been confronted with new operation challenge since the unified carbon trading market was launched in China. To make the optimal decision for the carbon emissions and power production has already been an important subject for the plants. Most of the previous studies only considered the market prices of electricity and coal to optimize the generation plan. However, with the opening of the carbon trading market, carbon emission has become a restrictive factor for power generation. By introducing the carbon-reduction target in the production decision, this study aims to achieve both the environmental and economic benefits for the coal-fired power plants to positively deal with the operational pressure.

A dynamic optimization approach with both long- and short-term decisions was proposed in this study to control the carbon emissions and power production. First, the operation rules of carbon, electricity and coal markets are analyzed, and a two-step decision-making algorithm for annual and weekly production is presented. Second, a production profit model based on engineering constraints is established, and a greedy heuristics algorithm is applied in the Gurobi solver to obtain the amounts of weekly carbon emission, power generation and coal purchasing. Finally, an example analysis is carried out with five generators of a coal-fired power plant for illustration.

The results show that the joint information of the multiple markets of carbon, electricity and coal determines the real profitability of power production, which can assist the plants to optimize their production and increase the profits. The case analyses demonstrate that the carbon emission is reduced by 2.89% according to the authors’ method, while the annual profit is improved by 1.55%.

As an important power producer and high carbon emitter, coal-fired power plants should actively participate in the carbon market. Rather than trade blindly at the end of the agreement period, they should deeply associate the prices of carbon, electricity and coal together and realize optimal management of carbon emission and production decision efficiently.

This paper offers an effective method for the coal-fired power plant, which is struggling to survive, to manage its carbon emission and power production optimally.

The purpose of this paper is to examine the impact of directors’ and officers’ liability insurance (D&O insurance hereafter) on corporate governance and firm performance, with a specific focus on investment efficiency.

Using a sample of Chinese A-share listed firms from the period 2007 to 2020, this study uses Ordinary Least Squares regressions to investigate the research questions, as well as moderating and mediating effects. Additionally, alternative measures of investment efficiency are used, and the Heckman two-stage model and propensity score matching model are used to demonstrate the consistency of the findings and to mitigate the risk of endogeneity.

The findings of this study suggest that purchasing D&O insurance has a detrimental impact on corporate investment efficiency, particularly in the context of over-investment activities; robust internal governance mechanisms, exemplified by a higher shareholding ratio of the top shareholder and enhanced internal control quality, alleviate this negative effect; and financing constraints act as a mediating factor in the association between D&O insurance and investment efficiency.

Corporate investment efficiency is of significant importance for both national macroeconomic growth and micro-enterprise development. Notably, the prevalence of D&O insurance among Chinese firms is progressively increasing, thus exerting a growing influence. This study contributes to the existing literature on D&O insurance and corporate investment efficiency, providing valuable insights into the economic impact of D&O insurance on Chinese firms. The empirical evidence presented herein facilitates future reforms and adjustments.

The purpose of this paper is to systematically review the functionalities, safety regulations and product applications of herb Stevia rebaudiana extract. This plant material is embedded with multiple functionalities such as antioxidant, antidiabetics, anti-inflammation and antimicrobial. The regulations released from global authorities are covered to ensure the safety premise of stevia. Besides, the product applications of the extract of aerial parts of the herb S. rebaudiana helps us to recognize its value from commercial side.

Relevant literatures are selected and obtained from main scientific databases such as Google Scholar, Web of Science, PubMed and trade magazines published between 2000 and 2023. The keywords and their possible combinations such as sweetening, antioxidant, antidiabetics, anti-inflammation, safety and product development were used to ensure the preciseness and completeness of literature searching. Major data such as sweetness, total phenolic content and dose together with latter critical conclusions from searched publications were appropriately used and discussed. In this review, approximately 150 scientific literatures were meticulously ordered and analyzed. In applications, it is the first time that sentiment analysis was used to obtain a market assessment of the stevia-containing products.

This review paper helps rearrange the scientific affairs of those stevia extract’s functions like sweetening, antioxidant, antidiabetics and inflammation. Sweetness indexes of steviol glycosides were summarized together for comparison while various in vitro and in vivo approaches were reviewed to quantify those functions’ capacities and to depict the related mechanism. The regulation of steviol glycoside compounds such as rebaudioside A was established by global authorities such as US Food and Drug Administration and Joint FAO/World Health Organization Expert Committee to ensure the safety endorsement before commercialization. Then, this study discussed about the market performance of stevia ingredients or products with the self-developed data analytics. This study also investigated the product development progress of stevia-containing food products in the categories of beverage, bakery, dairy and confectionery. Those stevia-containing food consumer goods can be acceptable by certain consumers.

This review paper precisely presents the evidential information about the stevia’s multiple functionalities with mechanisms and global regulation milestones. To the best of the authors’ knowledge, it is then the first time to probe the stevia-containing products’ market performance through data analytics.

This research aims to empirically investigate the impacts of product and international diversification strategies on firm-level inventory performance.

This study empirically examines the associations between product and international diversification strategies and inventory performance based on a sample of 64,124 observations across 7,367 US publicly traded firms between 1989 and 2019 from the COMPUSTAT Segment, Fundamental Annual and Fundamental Quarterly data files. We employ both linear and nonlinear regression models to perform our empirical analysis.

This research provides strong evidence that there exists a U-shaped relationship between unrelated product diversification and inventory level and a partially inverted U-shaped relationship between international diversification and inventory level. We also find a positive impact of related product diversification on inventory level, but there is no significant curvilinear relationship between related product diversification and inventory level.

Our research findings offer important insights into top management’s strategic planning for diversification strategies and operations manager’s inventory control policies to achieve the strategic fit between corporate diversification and inventory management.

Product and international diversification strategies not only play an essential role in the firm’s competitive advantage, but also have a significant influence on operations manager’s inventory decision. This research is among the first to systematically investigate how top management’s related product, unrelated product and international diversification strategies may have complex nonlinear impacts on inventory performance.

Although numerous signal modalities are available for emotion recognition, audio and visual modalities are the most common and predominant forms for human beings to express their emotional states in daily communication. Therefore, how to achieve automatic and accurate audiovisual emotion recognition is significantly important for developing engaging and empathetic human–computer interaction environment. However, two major challenges exist in the field of audiovisual emotion recognition: (1) how to effectively capture representations of each single modality and eliminate redundant features and (2) how to efficiently integrate information from these two modalities to generate discriminative representations.

A novel key-frame extraction-based attention fusion network (KE-AFN) is proposed for audiovisual emotion recognition. KE-AFN attempts to integrate key-frame extraction with multimodal interaction and fusion to enhance audiovisual representations and reduce redundant computation, filling the research gaps of existing approaches. Specifically, the local maximum–based content analysis is designed to extract key-frames from videos for the purpose of eliminating data redundancy. Two modules, including “Multi-head Attention-based Intra-modality Interaction Module” and “Multi-head Attention-based Cross-modality Interaction Module”, are proposed to mine and capture intra- and cross-modality interactions for further reducing data redundancy and producing more powerful multimodal representations.

Extensive experiments on two benchmark datasets (i.e. RAVDESS and CMU-MOSEI) demonstrate the effectiveness and rationality of KE-AFN. Specifically, (1) KE-AFN is superior to state-of-the-art baselines for audiovisual emotion recognition. (2) Exploring the supplementary and complementary information of different modalities can provide more emotional clues for better emotion recognition. (3) The proposed key-frame extraction strategy can enhance the performance by more than 2.79 per cent on accuracy. (4) Both exploring intra- and cross-modality interactions and employing attention-based audiovisual fusion can lead to better prediction performance.

The proposed KE-AFN can support the development of engaging and empathetic human–computer interaction environment.

This research investigates whether focal firms employ strategic supply chain information disclosure, focusing on the concealment of supplier and customer identities, as part of their supply chain environmental risk management strategies (supplier sustainability risk and customer loss risk, respectively).

Using a panel dataset of Chinese listed firms from 2009 to 2019 and utilizing the suppliers’ environmental punishment of peer firms (peer events) as an exogenous shock and employing ordinary least squares (OLS) estimation, this study conducts a regression analysis to test how focal firms disclose the identities of their suppliers and customers.

Our results indicate that focal firms prefer to hide the identities of their suppliers and customers following the environmental punishment of peer firms’ suppliers. In addition, supplier concentration weakens the effect of withholding supplier identities, whereas customer concentration strengthens the effect of hiding customer identities. Mechanism analysis shows that firms hide supplier identities to avoid their reputation being affected and hide customer identities to prevent the deterioration of customers’ reputations and thus impact their market share.

Our study reveals that reputation spillover is another crucial factor in supply chain transparency. It is also pioneering in applying the anonymity theory to explain focal firms’ information disclosure strategy in supply chains.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

Building on the intergroup relations perspective on the social identity theory, the authors examine whether firms' environmental, social and governance (ESG) varies when local firms have non-local CEOs. Additionally, the authors examine which contextual factors may strengthen or weaken the effectiveness of ESG in helping non-local CEOs garner trust, legitimacy and resources support from local stakeholders.

Pooled OLS regressions, based on unbalanced panel data and controlling for year and industry fixed effects, were estimated using a sample composed of 836 Chinese A-share listed firms that have Bloomberg ESG disclosure scores data from 2006 to 2019.

Results suggest that companies with non-local CEOs, who are perceived as outgroup members by the local stakeholders, would lead to a higher level of ESG performance to overcome the intergroup bias they face. In addition, results also show that companies with a lower level of previous ESG decoupling and having more slack will mitigate the relationship between non-local CEOs and ESG performance. Conversely, firm visibility at a high level will promote the positive relationship between non-local CEOs and ESG performance.

This study offers theoretical insights that extend the focus of intragroup relation to outgroup identity, by introducing an intergroup relations lens to explore how outgroup (or nonprototypical) leaders utilize ESG to counter intergroup bias they suffer. Moreover, this study also extends current literature focusing on non-local CEOs and ESG performance.