This study focuses on the knowledge fusion model of e-government information resources that supports user decision-making information needs, it discusses the user decision-making information needs... Show More

This study focuses on the knowledge fusion model of e-government information resources that supports user decision-making information needs, it discusses the user decision-making information needs model, the knowledge fusion service model, and the relationship between them. The inter-layer mapping matching mechanism realizes the ultimate value of knowledge fusion. Therefore, this paper analyses and studies the mapping mechanism between the user information demand model and the knowledge fusion service model. A semantic, similarity-based knowledge fusion service matching method for e-government information resources is proposed to address the problem of lack of semantics in traditional web service matching methods. This method uses the ontology description language OWL-S to map information requirement documents of user decisions and knowledge fusion service function documents into an ontology tree structure. The authors then use this as the basis to calculate the concept similarity and relationship similarity measures, and the service matching based on semantic similarity can be realized.

The influence of leaders on employees' innovative behavior is a new problem. Based on the relationship culture and digital technology situation in China, with reference to information processing and... Show More

The influence of leaders on employees' innovative behavior is a new problem. Based on the relationship culture and digital technology situation in China, with reference to information processing and other theories, this study constructs a double intermediary model of the impact of e-leadership on employee innovation behavior from the perspective of “self” and “relationship,” and introduces employee power distance as the boundary condition. The results show that psychological capital and affective commitment to leadership play a mediating effect between e-leadership and employee innovation behavior, and employee power distance weakens the positive impact of e-leadership on employee innovation behavior through psychological capital and emotional commitment. The research conclusion of this paper provides theoretical basis and practical enlightenment for enterprise leaders to promote employee innovation behavior by improving their e-leadership level and understanding the relationship between themselves and employees.

The E-CLSC (E-closed-loop supply chain) game model dominated by manufacturer is set, and information value about asymmetry fairness concern of E-platform (E-commerce platform) is calculated for... Show More

The E-CLSC (E-closed-loop supply chain) game model dominated by manufacturer is set, and information value about asymmetry fairness concern of E-platform (E-commerce platform) is calculated for manufacturer, recycler, and E-platform. By signaling model under various signal costs, the authors study the condition for E-platform to transmit real information about fairness concern so as to reduce profit loss for all parties in E-CLSC. The authors prove that E-platform has the motivation to disguise or exaggerate fairness concerns in order to obtain more profit, and manufacturers must try to identify the E-platform's real fairness concern to avoid profit loss. Besides, only when different types of E-platforms need significantly different signaling cost, both of them would like to send real fairness-concern signal, and thus manufacturer can effectively identify E-platform's real information about fairness concern so as to improve recycling rate and optimize the whole E-CLSC operation.

This paper utilizes nonfinancial information disclosure to develop a measure of text-based competition network. Using the data of China's listed firms, the authors adopt the textual analysis method... Show More

This paper utilizes nonfinancial information disclosure to develop a measure of text-based competition network. Using the data of China's listed firms, the authors adopt the textual analysis method to identify a unique group of competitors for the focal firm and construct the text-based competition network. In the whole network, leading firms receive increasing attention from competitors, and they play a vital role for the dynamic changes in the whole market. Moreover, the interactions between the focal firm and competitors in the text-based competition network are shown by some financial indicators. The characteristics of the text-based competition network have a significant impact on the future performance of the focal firm. Finally, economic links in the competition network are discussed by varying the number of competitors, which shows the impact of various competitors on economic similarities. The text-based competition network shows the relative importance of competitors for the focal firm and explains firms' decision-making from the perspective of dynamic competition.

At present, internet celebrity marketing has become a driving force for the growth of mobile e-commerce; however, it has also become more apparent that the credibility and authenticity of the... Show More

At present, internet celebrity marketing has become a driving force for the growth of mobile e-commerce; however, it has also become more apparent that the credibility and authenticity of the internet celebrity is directly correlated to the success of the marketing model. Therefore, in order to entice consumers into purchasing products, cooperations and internet celebrities must be deemed trustworthy. In addition, there are several factors that influence the trust between internet celebrities and consumers. To highlight these factors, this paper constructed an internet celebrity marketing model from the perspective of trust and takes internet celebrity features, marketing character, and product factor as three constructs. Furthermore, eight independent variables are defined, and the corresponding items are designed. Through a quite large data survey and analysis, they have three findings: all eight independent variables have significant influence on trust, and internet celebrities' popularity, interactivity, and professionalism are the top three important factors.

As market competition intensifies, companies recognize the value of attracting customers to participate in activities and loyalty programs (LPs) that encourage repeat purchases and maintain customer... Show More

As market competition intensifies, companies recognize the value of attracting customers to participate in activities and loyalty programs (LPs) that encourage repeat purchases and maintain customer loyalty. Literature on LP design explores the positive impact of program structure and rewards on the acquisition of customers. However, research is lacking on the role of LP information transparency on customer participation intention. This study uses 280 college students in China as the survey object to explore the influence of LP information transparency on willingness to participate in such programs. Using experimental design methods, the authors verify whether the type of merchant and channel customers select affect willingness to participate when customers redeem rewards. This study also explains the internal psychological mechanism of information transparency, merchant and channel types, and customer participation intention from the perspective of perceptual psychological distance in construal level theory (CLT) and the elaboration likelihood model (ELM). Both information visibility and accessibility have a positive impact on customer intention to participate in LPs. When a customer redeems a reward from a LP operator, information visibility has a more positive impact on willingness to participate than redeeming a reward from an alliance partner. Moreover, when a customer redeems a reward from online channels, the positive impact of information accessibility on willingness to participate is greater than redeeming from offline channels. Under the influence of multiple psychological distance effects, the synergistic effect of merchant type and channel type is not significant in the relationship between information transparency and willingness to participate in LPs. This article will provide design strategies and management suggestions for retail managers to attract customers to participate in LPs.

From the perspective of social exchange and the conservation of resources theories, the current study investigated the effect of toxic leadership on employee cyberloafing behaviour via the mediating... Show More

From the perspective of social exchange and the conservation of resources theories, the current study investigated the effect of toxic leadership on employee cyberloafing behaviour via the mediating role of emotional exhaustion and the moderating role of organisational commitment. SPSS models 1:moderation, 4: mediation, and 14: moderation mediation of PROCESS Hayes were used to evaluate the data from 357 employees of the Chinese corporate sector. The results show a positive relation between toxic leadership and cyberloafing, and emotional exhaustion mediates this relationship. Further, organisation commitment moderates the indirect, interactive effect of toxic leadership and emotional exhaustion on cyberloafing. The model was tested using 3-wave data; however, since the data were attained from a single source, the problem of common method bias cannot be ruled out. To avoid or lessen instances of cyberloafing behaviour and encourage good working attitudes, organisations must also take action and develop regulations governing internet use in the workplace.

Grounding on social learning theory, this study investigates the link between servant leadership, employee creativity, and work role performance. To examine the proposed model, the authors collected... Show More

Grounding on social learning theory, this study investigates the link between servant leadership, employee creativity, and work role performance. To examine the proposed model, the authors collected data from 289 nurses and doctors through a multi-wave (i.e., a time-lag) survey. In this study, servant leadership positively affects employee creativity and work role performance, and knowledge sharing partially mediates the relationship between servant leadership, employee creativity, and work role performance. The results show that self-efficacy directly moderates the positive relationship between servant leadership and knowledge sharing, and indirectly affects the link between servant leadership, employee creativity, and work role performance via knowledge sharing.

Since the 21st century, international corporate social responsibility attracts great attention. With the continuous improvement of consumers' maturity, they become more and more sensitive to... Show More

Since the 21st century, international corporate social responsibility attracts great attention. With the continuous improvement of consumers' maturity, they become more and more sensitive to international corporate social responsibility and have higher requirements for corporate to fulfill social responsibility. Besides, the buying decision is affected by international corporate social responsibility more and more apparently. Hence, the research into the impacts of international corporate social responsibility on consumers' buying behavior is of great significance. In the research, consumer identity was set as intervening variable to investigate how consumer buying behavior was affected by corporate social responsibility. After theoretical model was constructed and research hypothesis was put forward, questionnaire investigation approach was adopted for empirical study. It was demonstrated that the significance values of age, occupation, and education level in each factor were small with great differences.

Consumers' online stickiness and repurchase intention are important issues in the marketing of the global live streaming industry, but there is no clear consensus on its influencing mechanism. Based... Show More

Consumers' online stickiness and repurchase intention are important issues in the marketing of the global live streaming industry, but there is no clear consensus on its influencing mechanism. Based on the theoretical framework of stimulus-organism-response (SOR), this study validates the research model and hypotheses through structural equation modeling (SEM). The model of influencing factors of live streamers' characteristics (professionality, credibility, attractiveness, and interactivity) and perceived value of live streaming platforms has been established to testify how they influence the online satisfaction and online trust of global consumers, which further has impact on online stickiness and eventually on repurchase intention. Online trust and online stickiness have a significant impact on consumers' continuous purchase. Among them, the interactivity of live streamers significantly affects online trust, and the perceived context value of live streaming platforms significantly affects online satisfaction.

Knowledge workers are quite crucial to every enterprise, so exploring the relationship between their salary satisfaction and job performance is significant. Hence, this work observes their salary... Show More

Knowledge workers are quite crucial to every enterprise, so exploring the relationship between their salary satisfaction and job performance is significant. Hence, this work observes their salary satisfaction by identifying the employees' emotions at the time of salary announcement. The relationship between salary satisfaction and job performance is studied through the obtained satisfaction. First, the convolutional neural network (CNN) model is introduced. Then, it is optimized by adding an attention mechanism to improve the accuracy of the emotion recognition model. Finally, through comparative experiments, the effectiveness of the model proposed and the impact of employee's salary satisfaction on job performance are verified. The experimental results show that the recognition accuracy of the model is much higher than that of the traditional model. In particular, the recognition accuracy of neutral emotions is as high as 95%. It verifies the effectiveness of the model.

Sharp rises and falls in stock prices have become increasingly frequent in recent years. Stock market crashes bring great risks to the stability of the securities markets. Using recurrence plot... Show More

Sharp rises and falls in stock prices have become increasingly frequent in recent years. Stock market crashes bring great risks to the stability of the securities markets. Using recurrence plot theory and a heuristic segmentation algorithm for detecting abrupt changes in nonlinear time series, this study investigates the problem of detecting abrupt endogenous structural changes before a stock market crash. Based on an analysis of crash events in 12 developed and 10 emerging countries and regions, the authors find the following: (1) The market laminar flow (LAM) value will fall greatly before a stock market crash; (2) the LAM sequence of the US stock market during the 2008 financial crisis presents a fractal-like self-similar structure, and blank bands appears in the recurrence plot, indicating a phase transition in the LAM sequence before the crash; and. (3) using a heuristic segmentation algorithm to detect abrupt changes in nonlinear time series, this study finds that before a crash, the endogenous structure of the market continuously experiences abnormal abrupt changes, and abnormal abrupt change time.

Agents' irrational behavior would lead to local configuration of complex adaptive system percolation. The corresponding critical point is key to making decisions for improving the system or keeping... Show More

Agents' irrational behavior would lead to local configuration of complex adaptive system percolation. The corresponding critical point is key to making decisions for improving the system or keeping the system from collapsing. The authors construct a complex adaptive system model where agent behavior and its local configuration co-evolve. This model shows, when an arbitrary agent and its neighbors change their strategy and local interactive configuration, how the properties of percolation critical point of this system would emerge under random attack and intentional attack. It is shown that the system is robust if it is attacked randomly, and there are always at least two large components keeping the system connected. However, if the system is attacked intentionally, the result is more interesting. The system is robust if the deleting probability is smaller than a certain critical probability c0, but the system is vulnerable if the probability is larger than c0. Furthermore, the critical probability c0 is determined by the agent payoff, system structure, and noise.

As a new form of agricultural organization, agro-industrialized unions (AIUs) have shown strong effectiveness. Based on data from Hebei Province in China, the triple-hurdle model was used to analyze... Show More

As a new form of agricultural organization, agro-industrialized unions (AIUs) have shown strong effectiveness. Based on data from Hebei Province in China, the triple-hurdle model was used to analyze the impact of the governance structure and perceived interests on satisfaction from three stages. The main findings are: (1) Satisfaction with the AIU was affected by the governance structure and perceived interests. The former significantly impacted the final satisfaction, whereas the latter had significantly positive effects in all three stages. (2) Among the perceived interest factors, operating ability, interest sharing, and risk defense influenced attitude to whether performance had improved. (3) Attitude toward satisfaction was affected by the perceptions of operating ability and benefit sharing, whereas the overall satisfaction was influenced by benefit-sharing and risk-defense ability. Policy recommendations were suggested to strengthen the close bonds among AIU members at last.

This article takes the WeChat public account of agriculture and rural areas in J Province as the research object to explore the influencing factors of satisfaction of organizational information... Show More

This article takes the WeChat public account of agriculture and rural areas in J Province as the research object to explore the influencing factors of satisfaction of organizational information system (IS) in agricultural sector. Firstly, new media is taken as the background, and the characteristics and communication factors of agricultural informatization are analyzed. Secondly, a user satisfaction questionnaire of the WeChat public account of agriculture and rural areas of J Province is designed based on the satisfaction theory and the success model of IS. Finally, the influencing factors of users' satisfaction with agricultural and rural WeChat public accounts are studied through questionnaire survey. The results show that the correlation coefficients among perceived value (PV), information quality (IQ), perceived usefulness (PU), and platform satisfaction are all positive, and p £ 0.01.

This article investigates how Renqing and the system affect employees' work quality in Chinese culture. The leader-employee matching questionnaires were gathered using data from businesses in... Show More

This article investigates how Renqing and the system affect employees' work quality in Chinese culture. The leader-employee matching questionnaires were gathered using data from businesses in China's Beijing, Shanghai, Guangdong, Jiangxi, and Yunnan provinces. The article then uses an empirical analytic method to analyze the data. It uses SPSS25.0 software to process data. The results indicate that the three dimensions of emotion relationship, resource relationship, and norm relationship have an equal impact on the quality of work enjoyment; the system has no substantial effect on employees' work quality, but it regulates the impact of Renqing on work quality. If a Chinese company wants employees that produce high-quality work, the article's conclusions suggest that Renqing should be considered. In the meantime, the company should increase its efforts to improve the efficiency of its system.

Green hotels have become the inevitable trend of the hotel industry development under the background of sustainable development. The questionnaire of this study was modified from the scale of the... Show More

Green hotels have become the inevitable trend of the hotel industry development under the background of sustainable development. The questionnaire of this study was modified from the scale of the literature, and the survey was conducted by means of convenience sampling. The respondents were the consumers who had stayed in hotels in the past two years. A total of 566 questionnaires were distributed, and 491 valid questionnaires were collected. The effective recovery rate was 86.7%. The results show that technology products of different learning types have significant influence on tourists' acceptance, and the technostress has significant differences on the acceptance of type of technology products. However, hotel types have no significant impact on technology learning products and tourist acceptance. This study expects to provide the analysis results for the reference of green hotel industry development in order to improve the practical benefits of hotel technology product investment.

Green innovation development is essential to achieve “carbon neutrality and carbon peaking” and drive sustainable urban growth, which greatly influences the global green economy. This paper probes... Show More

Green innovation development is essential to achieve “carbon neutrality and carbon peaking” and drive sustainable urban growth, which greatly influences the global green economy. This paper probes into the influence of e-commerce on urban green innovation and its mechanism using a multi-period double difference model. The authors examine the heterogeneous impact of e-commerce on urban green innovation under various urban characteristics. The study reveals that e-commerce development enhances urban entrepreneurial vitality, promotes investment agglomeration, and fosters favorable social conditions and sufficient financial guarantees for green innovation development. E-commerce development's promotion effect shows a “U-shaped” trend as the extent of urban green innovation increases. Additionally, the impact of e-commerce development on urban green innovation is highly dependent on its resource endowments. Therefore, we should focus on the empowering effect of e-commerce development on green innovation to provide new growth opportunities for the green economy.

To provide strategies for developing and optimising e-learning technology, this paper conducts research on the e-banking platform based on e-learning technology. Firstly, this paper points out the... Show More

To provide strategies for developing and optimising e-learning technology, this paper conducts research on the e-banking platform based on e-learning technology. Firstly, this paper points out the technical content of the electronic banking platform. Secondly, based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, empirical analysis is conducted on the influencing factors of user willingness to use electronic banking platforms, including the introduction, construction, hypothesis formulation, selection of indicator variables, and questionnaire design. Finally, the results of empirical analysis are explored. The result shows that: (1) The Cronbach's α values of the sub-scales of the questionnaire designed are all greater than 0.7, and the load of different factors in each dimension of the scale is more significant than 0.5. (2) Perceived risk has the highest average among all influencing factors, with a value of 4.13. (3) AMOS (Analysis of Moment Structure) 21.0 was calculated using a standardized path coefficient similar to the model.

Presently, text mining in e-commerce reviews predominantly focus on singular sentiment analysis, yet constraints persist in sentiment score computation, semantic inclination discernment, and lexicon... Show More

Presently, text mining in e-commerce reviews predominantly focus on singular sentiment analysis, yet constraints persist in sentiment score computation, semantic inclination discernment, and lexicon construction. To address these limitations, this study establishes an e-commerce user comment management system based on text mining. It performs part-of-speech tagging and dependency grammar analysis on the historical corpus of e-commerce, unveiling collocations that potentially convey users' emotive predispositions. Subsequently, a dependency grammar rule table is formulated for the extraction of emotional words. The enhanced BiGRU model is employed for bidirectional extraction of textual features, which are subsequently fused with the TextCNN model. Test results evince that the system effectively accomplishes the desired objectives, with positive comments attaining accuracy and recall rates of 93.49% and 96.98%, respectively, thereby mitigating the drawbacks associated with laborious operations and inadequate precision inherent in extant e-commerce comment analysis systems.

The objective of utilizing mmWave/subTHz bands in next-generation wireless communications is to be achieved. Despite this, since reconfigurable intelligent surface (RIS)-assisted systems depend on... Show More

The objective of utilizing mmWave/subTHz bands in next-generation wireless communications is to be achieved. Despite this, since reconfigurable intelligent surface (RIS)-assisted systems depend on the transmission channel configuration, the system architecture design, and the methods used to derive channel state information (CSI) on a base station (BS) and RIS, channel estimation continues to be the main problem with these systems. This research proposes an innovative RIS-based and compressed sensing-based channel estimation technique for the internet of vehicles. To obtain the best phase shift matrix, the communication model must first be constructed, and the angle-of-arrival and departure are utilized. Channel estimation is then performed based on the perception matrix. The training overhead and complexity of the channel estimation are reduced by considering the position information of the vehicles in the optimal phase shift matrix. Simulation results show that the proposed algorithm exhibits better channel estimation and low complexity performance compared with existing algorithms.

The promotion of innovation is a crucial leadership function. However, empirical evidence on the role of paradoxical leadership in innovation is scarce. Based on paradox theory, this study presents... Show More

The promotion of innovation is a crucial leadership function. However, empirical evidence on the role of paradoxical leadership in innovation is scarce. Based on paradox theory, this study presents an effective model to investigate the relationship between paradoxical leadership and employee exploratory innovation. Based on a survey of 358 employees in China, it was observed that paradoxical leadership promotes knowledge sharing among employees, consequently stimulating exploratory innovation. The study results showed that environmental dynamism plays a negative moderating role in the relationship between employee knowledge sharing and exploratory innovation. This study contributes to theoretical and empirical studies on paradoxical leadership and provides new perspectives for promoting exploratory innovation.

With the development of digitalization and Internet technology, enterprise information security is facing more and more challenges. Many enterprises have begun to adopt big data (BD) and artificial... Show More

With the development of digitalization and Internet technology, enterprise information security is facing more and more challenges. Many enterprises have begun to adopt big data (BD) and artificial intelligence (AI) technology for risk assessment (RA) and prediction to effectively manage information security risks. This article discusses the application of BD and AI technology in enterprise information security management (ISM) and RA from two aspects. Firstly, the mobile payment signature scheme based on number theory research unit is used to improve the security of the mobile payment system. This scheme uses lattice algorithms to achieve fast key generation, signing, and verification and can resist traditional cryptographic attacks. Secondly, a set of enterprise ISM and RA system is established, including risk identification, RA, monitoring and early warning, emergency response, and other links. BD and AI technology is used to analyze internal and external data to provide accurate RA results to achieve automated RA.

The dark sides of artificial intelligence (AI) have attracted immense attention in recent years. This study produces a synthesis of current research on six dark sides of AI in electronic markets... Show More

The dark sides of artificial intelligence (AI) have attracted immense attention in recent years. This study produces a synthesis of current research on six dark sides of AI in electronic markets through a systematic literature review. The authors searched five different databases and summarized the dark sides of AI in electronic markets from six aspects: privacy concerns, security issues, ethical challenges, criminals and terrorists enabled by AI, trust issues between humans and machines, and AI biases. The literature review presented in this study has provided a rigorous and structured overview of research on AI's dark sides in the electronic markets through a combination of quantitative and qualitative analysis of the AI literature. As AI has made rich contributions to a variety of applications in electronic markets, special care should be taken regarding the dark side of AI. Governments and policymakers are recommended to establish legislation to ensure that AI-powered innovation and implementation are beneficial to the social good while limiting the threats caused by the dark side of AI.

This paper summarized the factors that influence consumers' trust in AI chatbots and divided it into chatbot-related factors (expertise, anthropomorphism, responsiveness, and ease of use)... Show More

This paper summarized the factors that influence consumers' trust in AI chatbots and divided it into chatbot-related factors (expertise, anthropomorphism, responsiveness, and ease of use), company-related factors (perceived risk, brand trust, human support), and consumer-related factors (privacy concerns). This research attempts to explore the mechanism of human-AI chatbots trust formation and answer the question of how to promote consumers' trust in AI chatbots. The results found that the chatbot-related factors (expertise, responsiveness, and anthropomorphism) positively affect consumers' trust in chatbots. The company-related factor (brand trust) positively affects consumers' trust in chatbots, and perceived risk negatively affect consumers' trust in chatbots. Privacy concerns have a moderating effect on company-related factors. This study helps deepen the understanding of human-AI chatbots communication trust, constructs a basic model of human-AI chatbots trust, and provides insights for e-commerce enterprises to improve chatbots and enhance consumer trust.

Virtual knowledge communities have become essential platforms for enterprises to facilitate knowledge sharing. However, due to the lack of effective incentive mechanisms, the traditional virtual... Show More

Virtual knowledge communities have become essential platforms for enterprises to facilitate knowledge sharing. However, due to the lack of effective incentive mechanisms, the traditional virtual knowledge community is generally inefficient in attracting high-quality content and maintaining enthusiasm for users' long-term participation. To address these problems, we theoretically explore the characteristics and economic ecology of enterprise knowledge sharing based on blockchain tokens to promote its sustained development. Specifically, we examine the application scenarios of token-economy activities through system-dynamics simulation and discuss the development status and path of the economic ecology. In addition, we studied the blockchain token-based incentive and penalty mechanisms for virtual knowledge communities to better stimulate knowledge sharing. Finally, the research method is applied to the GienTech supply chain finance community website to validate the proposed model and analysis. The findings contribute to the existing literature and point enterprises in a new direction in designing more effective incentive mechanisms to improve knowledge-sharing in virtual knowledge communities.

Motivated by the need to better understand the ongoing role of artificial intelligence in businesses and to shift the focus from a purely technological and algorithmic perspective to one that... Show More

Motivated by the need to better understand the ongoing role of artificial intelligence in businesses and to shift the focus from a purely technological and algorithmic perspective to one that encompasses human-computer interaction, this article aims to investigate people's intention to use AI for generating images in a business context. The present study employed structural equation modelling to analyse how factors from UTAUT2 such as perceived customer value, effort expectancy, social influence, and facilitating conditions affect behavioural intention. The research introduces new moderators (creativity and English language proficiency), in the context of generative AI. Language proficiency and gender impact AI usage, while the impact of effort expectancy is more pronounced in cases of low creativity.

With the continuous development of information technology and information management systems, they are widely and successfully used in practice. Health behavior and psychological monitoring systems... Show More

With the continuous development of information technology and information management systems, they are widely and successfully used in practice. Health behavior and psychological monitoring systems are a breakthrough in the technological transformation of the therapeutic field. It is widely used in the field of healing and health care with its characteristics of convenience, quickness, accuracy, and timeliness. In this study, 466 valid samples were collected by questionnaires from students. The results show that effort expectation, community influence, and convenience have a positive effect on the health behaviors monitored by the health behavior and psychological monitoring systems of school students, and the three factors indirectly influence the behavioral intention through influencing the perceived value, learning willingness, and perceived trust and then affect the actual behavior. Based on the analysis results of this research, the authors provide research and management recommendations for health behavior and psychological monitoring systems operators and researchers in related fields.

Effective energy financial risk management is crucial to ensure that China's economic system can remain stable. This article utilizes the quantile vector autoregressive spillover index model... Show More

Effective energy financial risk management is crucial to ensure that China's economic system can remain stable. This article utilizes the quantile vector autoregressive spillover index model, complex networks, and deep learning methods to simultaneously assess both the internal and external energy financial market risks in China. Spillover effects under different market conditions are also examined. The research findings indicate that: (1) Under extreme market conditions, static total spillover values between internal and external markets exceed 70%, while under normal market conditions, they are only around 53% and 13%, respectively; (2) Crude oil and fuel oil as well as energy and stocks are important nodes in both internal and external markets; and (3) The attention-convolutional neural network-long short-term memory model outperforms the second-best performing model, and achieves an improvement of 12.9% and 21.4% in terms of mean absolute error and root mean square error, respectively; inclusion of early warning indicators leads to further improvements of 19.8% and 31.9%, respectively.

Computer vision has made significant advancements in emotional design. Designers can now utilize computer vision to create emotionally captivating designs that deeply resonate with people. This... Show More

Computer vision has made significant advancements in emotional design. Designers can now utilize computer vision to create emotionally captivating designs that deeply resonate with people. This article aims at enhancing emotional design selection by separating appearance and color. A two-stage emotional design method is proposed, which yields significantly better results compared to classical single-stage methods.. In the Radboud face dataset (RaFD), facial expressions primarily rely on appearance, while color plays a relatively smaller role. Therefore, the two-stage model presented in this article can focus on shape design. By utilizing the SSIM image quality evaluation index, our model demonstrates a 31.63% improvement in generation performance compared to the CGAN model. Additionally, the PSNR image quality evaluation index shows a 10.78% enhancement in generation performance. The proposed model achieves superior design results and introduces various design elements.This article exhibits certain improvements in design effectiveness and scalability compared to conventional models.

The rapid progress of the digital economy has brought forth a myriad of complexities in economic governance, particularly in the domains of stocks and network finance. The authors propose the... Show More

The rapid progress of the digital economy has brought forth a myriad of complexities in economic governance, particularly in the domains of stocks and network finance. The authors propose the exploration of an innovative economic management model founded on the compound neural network framework. Central to this approach is the utilization of the deep bidirectional long and short-term memory neural network model (Bi-LSTM) as the primary instrument for predictive analysis, complemented by the refinement and enhancement provided by the Markov chain model. Through comparative analysis of experiments, it is found that although the forecast price of this model has a certain lag, it has a more accurate judgment than other prediction models, and the accuracy and recall rate reach 87.66% and 86.31%. At the same time, the error evaluation index R2 is very close to the upper limit 1 of the index, and the mean absolute error MAE Hill inequality coefficient; TIC root; mean square error; RMSE; and symmetric mean percentage error (SMAPE) are 0.2654, 0.0124, 0.3481, and 0.3531, respectively.

Research on cloud computing (CC) has gained a lot of momentum owing to its massive adoption. It has moved beyond the exploration of inherent capabilities to understand its disruptiveness and... Show More

Research on cloud computing (CC) has gained a lot of momentum owing to its massive adoption. It has moved beyond the exploration of inherent capabilities to understand its disruptiveness and transformative value. In this vein, the authors conducted a comparative literature review of 101 articles to better understand the developments from previous reviews. This article serves as a replication study to evaluate the growth of the business perspective of CC. The authors identify 126 factors guiding the characteristics, adoption, governance, and business impact of the cloud. Further, they employ a rigorous analysis that situates our review at the intersection of these factors and applies a multidimensional scaling technique. The developed matrix (a) helps to clarify the current state of research, (b) identifies research gaps, and (c) identifies potential further research avenues. Unlike previous reviews, this developed multidimensional view of each article uncovers numerous perspectives that can guide future research.

An enormous challenge for project management is to identify similar research projects accurately and efficiently among numerous proposals. To address this challenge, this paper proposes an algorithm... Show More

An enormous challenge for project management is to identify similar research projects accurately and efficiently among numerous proposals. To address this challenge, this paper proposes an algorithm to calculate the similarity between research projects using an improved generating method for fused word order sentence vectors based on USIF (unsupervised random walk sentence embeddings). The experimental results show that the proposed algorithm is about 15.8% more accurate than the existing approaches. The authors also propose a pre-checking algorithm by introducing a complex research cooperation graph to enhance query efficiency. The results show the pre-checking method reduces the query time cost by 96% on average.

Previous studies have focused on the impact of the theory of reasoned action (TRA)'s components on the behavioral intention to donate more. However, whether the mediation roles of social... Show More

Previous studies have focused on the impact of the theory of reasoned action (TRA)'s components on the behavioral intention to donate more. However, whether the mediation roles of social media-presence and cybersecurity affect this impact is unclear. This paper extends the TRA with trust, commitment, and loyalty to explore the integration of cybersecurity and social media-presence into the behavioral intention to donate more. Data were collected from 315 donors to nonprofit organizations and analyzed using partial least squared (PLS) methods. The results indicate that social media-presence positively influences the donor commitment towards the behavioral intention to donate more. However, social media-presence does not increase donor trust and loyalty toward the behavioral intention to donate more. Furthermore, cybersecurity increases donor trust and loyalty toward the behavioral intention to donate more. However, cybersecurity does not influence donor commitment toward the behavioral intention to donate more. Theoretical and practical contributions are offered.

Research has often overlooked the role of digital innovation in driving social transformation, especially in underserved rural areas, but the integration of digital technology is promoting rural... Show More

Research has often overlooked the role of digital innovation in driving social transformation, especially in underserved rural areas, but the integration of digital technology is promoting rural high-quality development through the establishment of digital entrepreneurial ecosystems. Approaching from a complex systems perspective, this study contends that these ecosystems navigate multiple routes to enhance total factor productivity (TFP) in rural settings. Performing a configurational analysis of a sample of 60 demonstration counties for rural revitalization in China, this study identifies three primary pathways yielding high TFP: an investment-led model under government stewardship, a collaborative model steered by both government and social capital, and a talent-centric model governed by digital market forces. Conversely, this study also pinpoints a pathway that does not yield high TFP. Theoretical and practical insights are offered for researchers and practitioners exploring digital innovation and its implications for rural entrepreneurial ecosystems.

This study focuses on meticulously examining energy companies' financial performance, incorporating the principles of environmentally sustainable development. The study employs a comprehensive... Show More

This study focuses on meticulously examining energy companies' financial performance, incorporating the principles of environmentally sustainable development. The study employs a comprehensive assessment approach that integrates various metrics from different departments of these enterprises. These abstract indicators are primarily quantified using the analytic hierarchy process (AHP), emphasizing incorporating low-carbon indicators, such as research and development (R&D) in renewable energy, into the evaluation framework. Subsequently, the study utilizes the long short-term memory (LSTM) model to evaluate the performance of individual departments within these companies. Ultimately, the study provides an overarching evaluation of the financial performance of energy enterprises. The proposed model demonstrates its effectiveness in practical testing, achieving an evaluation error of just 1.7%. Moreover, the research also scrutinizes the implications of these financial evaluation results for the transition toward a low-carbon paradigm.

In recent years, with the increasing homogenization of competition among live commerce streamers, the industry ecology has been deteriorating. As a rising star in the field of livestreaming... Show More

In recent years, with the increasing homogenization of competition among live commerce streamers, the industry ecology has been deteriorating. As a rising star in the field of livestreaming, knowledge-based streamers have brought a huge impact to traditional ones and achieved great business success. They not only create a new trend of differentiated competition among streamers, but also to some extent promote the transformation and upgrading of live commerce industry. To the authors' best knowledge, no studies in research literature have focused on the practical logic of knowledge-based streamers. Therefore, this research takes knowledge-based streamers of China as the research objects, collects and analyzes relevant news, policies, literature, and interview materials. Through the grounded theory, this research summarizes and refines these practical experiences, explores the practical logic in the process of livestreaming, and establishes a theoretical model.

Nowadays, countries in the world have frequent economic exchanges, and the scale of cross-border E-Commerce (CBEC) is getting larger and larger. CBEC refers to trading, payment, logistics, customs... Show More

Nowadays, countries in the world have frequent economic exchanges, and the scale of cross-border E-Commerce (CBEC) is getting larger and larger. CBEC refers to trading, payment, logistics, customs clearance, and other transactions. It also refers to the services between countries or regions through Internet technology and e-commerce platforms. In this article, the authors proposed a consumer preference model by blockchain and topic similarity clustering to obtain more consumer preference information. First, this article builds a blockchain-based consumer information collection system for CBEC to extract various features of consumers in CBEC. Secondly, by improving the performance of multiple characteristics of consumers, the accuracy of consumer preference prediction is improved. Finally, a method of consumer preference prediction based on topic similarity clustering is proposed to obtain consumers' purchase preference types. Experimental results show that the method can reach 84.3% of the H-mean, getting the best predictive performance and assisting CBEC by predicting consumer preferences.

The current development of remote monitoring technology (RMT) has become increasingly mature. The key to implementing this technology lies in the user's willingness to use it. In order to study the... Show More

The current development of remote monitoring technology (RMT) has become increasingly mature. The key to implementing this technology lies in the user's willingness to use it. In order to study the influencing factors of using RMT in green operation and service-oriented manufacturing enterprises, based on organizational behavior, this exploration discusses the reasons that affect the introduction of new technologies into enterprises from the perspectives of perceived risk, conformity and technology acceptance. Moreover, a series of data is obtained through the questionnaire and the results are obtained by analyzing the data. Suggestions to improve the use of RMT in enterprises are put forward. The results show that technology itself, external environment and organizational characteristics can all affect the decision-making of enterprises on new technology.

This article, in order to address impreciseness, initiated the notion of dual hesitant fermatean fuzzy sets (DHFFSs), as a generalization of the combination of dual hesitant fuzzy set (DHFS), dual... Show More

This article, in order to address impreciseness, initiated the notion of dual hesitant fermatean fuzzy sets (DHFFSs), as a generalization of the combination of dual hesitant fuzzy set (DHFS), dual hesitant Pythagorean fuzzy set (DHPFS) and Fermatean fuzzy set (FFS). The authors defined the fundamental set of operations for DHFFS. Additionally, the authors have also proposed two ranking functions and an accuracy function for the ordering of this novel set. In order to facilitate the pragmatic implementation of DHFFS in optimization, the authors formulated three types of transportation problem with dual hesitant Fermatean fuzzy (DHFF) parameters. To optimize the DHFF-TP, an algorithm was proposed with the help of one of the proposed ranking functions. Artificial neural network is also applied to the transportation problems in DHFF environment. A numerical example based on the transportation of COVID-19 vaccine with DHFF cost has also been carried out to validate out to validate our technique. In this article the proposed fuzzy system is included into this model to control uncertainties in Time, Quality, Cost, Reliability, and Availability induced in the transportation interruptions. The paper illustrates implication of the proposed fuzzy based model using a simulation in the context of a transportation process. The proposed model seeks to satisfy customers' demands for high-quality products and services, on a timely manner, at lowest cost possible. These characteristics are essential during times of disturbance, such as the COVID-19 pandemic.

Unbalanced development among regions is a prominent feature of the current situation of inclusive finance. Few works have been done on how regional culture affects the imbalance of inclusive... Show More

Unbalanced development among regions is a prominent feature of the current situation of inclusive finance. Few works have been done on how regional culture affects the imbalance of inclusive financial development. The authors try to investigate this issue using yearly data of digital financial inclusion in China spanning from 2011 to 2020 and the Hofstede regional culture of China. The results reveal regional culture could be the potential driver which leads to regional imbalance of the development of digital financial inclusion in China. Specifically, under Chinese historical culture background, financial inclusion is positively related with indulgence regionally, while individualism or power distance could exert negative impact. The findings are verified by a two-stage least square approach. Due to the anonymity and platform dependence of digital financial, Hofstede culture could make sense by influencing public trust in the financial sector, the internet, and unfamiliar relationships.

The aim is to improve small and medium-sized enterprises (SMEs)' core competitiveness and financing attainability using deep learning (DL) under economic globalization. Accordingly, this work... Show More

The aim is to improve small and medium-sized enterprises (SMEs)' core competitiveness and financing attainability using deep learning (DL) under economic globalization. Accordingly, this work constructs a supply chain symbiosis system based on DL, economics, and Stackelberg game theory following a status quo analysis of the financing status of SMEs. Afterward, a structural framework of supply chain financing (SCF) is designed. Further, it verifies the effectiveness of the proposed back propagation neural network (BPNN) credit evaluation model through specific enterprise data. The results show that the proposed internet of things (IoT)-based SCF SMEs-oriented BPNN credit evaluation model reaches a prediction accuracy of 91.4%. It effectively eliminates information asymmetry between banks and various capitals. As a result, banks can guarantee operation funds for the supply chain SMEs and help them minimize project risks by lowering financing leverage and through information transparency.

At present, society has entered the era of digital finance, and the information management system (IMS) of financial services has been developing rapidly, so the security of data has become... Show More

At present, society has entered the era of digital finance, and the information management system (IMS) of financial services has been developing rapidly, so the security of data has become particularly important. Firstly, some security techniques in IMS of financial services are introduced. Secondly, this study analyzes how to combine secure muti-party computation with blockchain technology to enhance the security of IMS. Finally, the feasibility and reliability of the scheme are verified by a comparative test. The experimental results reveal that the evaluation index score of the optimized scheme is higher than that of the traditional scheme. Meanwhile, in the comparative experiment of information data encryption, it can be seen that the running time of all schemes will improve with the increase of data. However, the increase rate of the optimized model in this study is much slower than that of the traditional model.

Exploring the joint effects factors affecting high-technology industries' performance is crucial to enhancing the country's overall strength. However, maintaining high industry performance levels... Show More

Exploring the joint effects factors affecting high-technology industries' performance is crucial to enhancing the country's overall strength. However, maintaining high industry performance levels has always been a complex issue. The literature mainly focuses on the net effects of single factors. In that case, the authors put forward a configurational framework that is the performance of high-tech industries, and does not depend on a single condition. Based on a fuzzy-set qualitative comparative analysis of high-tech industry performance across Chinese provinces, the authors identify eight conditions affecting industry performance under four latitudes – economic environment, scientific research, technological progress, and government support. The results show that high and non-high levels of performance can be achieved through the different configurations of antecedents. Both economic development and science and technology inputs play an irreplaceable role in industrial performance.

The purpose is to further analyze the influence of AI technology on the psychology of employees in the computer industry and truly solve the problems encountered in enterprise management, such as... Show More

The purpose is to further analyze the influence of AI technology on the psychology of employees in the computer industry and truly solve the problems encountered in enterprise management, such as difficult organizational relationship and lack of staff morale. With artificial intelligence algorithm as the research object, AI-based employee psychology and performance analysis model is built based on artificial neural network (ANN) from four aspects of work performance, psychological empowerment, work engagement, and perceived dynamic work environment. MATLAB tool is used, employee psychological empowerment index is taken as an input variable, and employee performance index is taken as output index. The validity of the models proposed in different studies is further verified through different test methods. The results show that artificial intelligence technology can positively affect employees' performance by improving their psychological empowerment, and the improvement of work performance is directly related to psychological empowerment.

As the stock market becomes increasingly diverse and complex, an accurate and feasible prediction of stock index has become an urgent demand for stock investors. As an important driver of changes in... Show More

As the stock market becomes increasingly diverse and complex, an accurate and feasible prediction of stock index has become an urgent demand for stock investors. As an important driver of changes in the stock market, financial discourse can guide investors' emotions, thus affecting the trading of stocks and the development of the stock market. Therefore, the prediction of stock index from the perspective of financial discourse emotion has gradually become a hotspot of research. Through the analysis of the existing literature, it is found that the models used in the current relevant research are not ideal, the prediction is not accurate, and there are problems such as single method, few selection indicators, narrow analysis area, etc. To solve the above problems, this study proposes an LSTM model integrating multiple feature emotional indexes, constructs the TextCNN emotional index and the metaphorical power index to quantitatively analyze the emotional expression and semantic use of news text, and then integrates the indexes into the LSTM neural network model to predict the Shanghai Stock Exchange Index.

In order to improve the management mode of the human resources system and enhance the work efficiency of employees, this paper uses artificial intelligence (AI) technology to enhance the... Show More

In order to improve the management mode of the human resources system and enhance the work efficiency of employees, this paper uses artificial intelligence (AI) technology to enhance the psychological empowerment of employees. It affects employees' work performance from a psychological perspective with the help of psychological empowerment. The questionnaire survey method collects data on the influencing factors of employees' psychological empowerment. The statistical data are analyzed by regression. Back propagation neural network (BPNN) algorithm based on deep learning is used to establish the work condition evaluation model. The job satisfaction, pressure, and performance of employees based on psychological empowerment are analyzed.

The development of e-commerce has greatly changed the development of social retail formats. Business-to-consumer (B2C) e-commerce model is important. Due to the characteristics of high consumer... Show More

The development of e-commerce has greatly changed the development of social retail formats. Business-to-consumer (B2C) e-commerce model is important. Due to the characteristics of high consumer trust and commodities dominated by electronic products and brand commodities, the income and profits generated are also very considerable. Therefore, the major e-commerce giants have increased the development of B2C formats. Logistics service capability and level have become an important driving force for the development of B2C e-commerce. How to optimize the inventory of B2C e-commerce and realize the organic balance between the economy and service capacity of the whole logistics chain has become a very urgent problem faced by major e-commerce giants. From the perspective of big data, first, the overview of the dataset used is analyzed based on the real operation data of a business to consumer (B2C) e-commerce platform.

Access control data will continue to be exposed to the threat of privacy leakage even if blockchain technology currently offers a new solution for the security and privacy of the internet of things... Show More

Access control data will continue to be exposed to the threat of privacy leakage even if blockchain technology currently offers a new solution for the security and privacy of the internet of things (IoT). However, its usability and privacy are not completely leveraged. This paper first discusses the IoT and blockchain technology and then examines each technology's structural models in order to address the issue of information security and privacy protection for the global organization IoT based on blockchain. Second, the information security and privacy guarantee system based on blockchain is built with ZKP and TEE at its heart after problems with zero-knowledge proof (ZKP) and trusted execution environment (TEE) in information security guarantee based on blockchain are investigated. By comparing the simulation trials, the proposed system's viability is finally confirmed. The results demonstrate that the suggested algorithm's evidence generation time is 352 ms when it reaches the experiment's highest node 28, which is clearly faster than previous techniques.

The integration of big data analytics with effective supply chain practices based on dynamic capability theory is an emerging topic, and the relationship that exists between big data analytics and... Show More

The integration of big data analytics with effective supply chain practices based on dynamic capability theory is an emerging topic, and the relationship that exists between big data analytics and supply chain dynamic capabilities and supply chain practices, and their impact on supply chain performance, requires further research. This article examines the relationship between three supply chain practices and supply chain performance. The information provided by managers of 415 companies in China was used as a sample and the data collected was empirically tested using partial least squares structural equation modelling. The findings show that different supply chain practices have a positive impact on supply chain dynamic capability and supply chain performance, that supply chain dynamic capability has an indirect mediating effect, and that big data analysis has a positive moderating effect on the relationship between supply chain practices and supply chain performance.

This paper aims to analyze the predictive effect of artificial intelligence on user demand in big data social media and to provide suggestions for developing enterprise innovation frameworks and... Show More

This paper aims to analyze the predictive effect of artificial intelligence on user demand in big data social media and to provide suggestions for developing enterprise innovation frameworks and implementing marketing strategies. In response to the inconsistency between the supply of enterprise products and services and market demand, deep learning algorithms have been introduced using social media big data analysis. This algorithm has been improved to construct a user demand prediction model in social media big data based on bidirectional long short-term memory (BiLSTM) fused with Word2Vec. The model uses data acquisition and pre-processing, Word2Vec algorithm to vectorization the data information, and BiLSTM network to model and train the sequence. Finally, the model is evaluated as an example.

Consumers in China highly favor the consumer-to-consumer (C2C) e-commerce model, so it is crucial to understand the relationship between consumers' trust in merchants, perceived benefits, and... Show More

Consumers in China highly favor the consumer-to-consumer (C2C) e-commerce model, so it is crucial to understand the relationship between consumers' trust in merchants, perceived benefits, and purchase intentions. This article first elaborates on applying trust, perceived benefits, and purchase intention in China's C2C e-commerce model. Then, corresponding hypotheses are proposed, and the questionnaire is designed. Finally, reliability, validity, correlation, and regression analysis are applied to analyze the sample structure and the relationships between various variables. The experimental results show that the reliability and validity detection values are higher than 0.8 and 0.75, respectively, indicating that the reliability and validity of the questionnaire designed are qualified. In the correlation analysis, the hypothesis proposed is validated through correlation coefficients, and the rationality of the hypothesis is further verified through regression analysis.

With the popularity and development of the internet, China's consumer-to-consumer (C2C) electronic commerce (EC) system is favored by consumers. Therefore, understanding the relationship among... Show More

With the popularity and development of the internet, China's consumer-to-consumer (C2C) electronic commerce (EC) system is favored by consumers. Therefore, understanding the relationship among consumers' trust, perceived benefits (PBs), and purchase intentions (PIs) is of great significance for studying this system. This article proposes the hypothesis of the interaction among the three and designs a questionnaire to explain the application of trust, PB, and PI in China's C2C EC system. The relationship between the sample structure and the variables is analyzed using reliability, validity, correlation, and regression analysis (RA). The experimental analysis results show that the questionnaire's reliability and validity values are higher than 0.8 and 0.75, respectively, indicating that the questionnaire design is qualified, and the data are valid. The rationality of the hypothesis proposed here is verified through correlation analysis and RA. This indicates a significant mutual influence relationship among trust, PB, and PI.

To enhance the early warning level of financial risks in enterprises, mitigate the financial risks arising from diverse adversities, and drive green technological innovation and sustainable... Show More

To enhance the early warning level of financial risks in enterprises, mitigate the financial risks arising from diverse adversities, and drive green technological innovation and sustainable development, this study proposes a financial risk prediction model (MS-BGRU) that amalgamates multi-scale convolution and two-way GRU. Firstly, a multi-scale feature extraction module is devised that assimilates financial information from various scales by leveraging hole convolution with distinct expansion rates. This assimilated information is then fused to obtain richer context information. Secondly, the BGRU network is employed to discern the sequence characteristics and time information of financial indicators. The empirical results showcase that the model proposed in this paper exhibits a high identification accuracy, surging up to 98.03%, which surpasses other benchmark models. The model can accurately prophesize the financial risk of enterprises and offer guidance to management decision-makers in averting financial risk.

How to enhance the competitiveness of manufacturing enterprises using innovation is an important topic in theory and practice. Data from the world input-output table and the Chinese industrial... Show More

How to enhance the competitiveness of manufacturing enterprises using innovation is an important topic in theory and practice. Data from the world input-output table and the Chinese industrial enterprise database are used to study the difference in the influence of service transformation and product innovation on enterprise competitiveness. The authors show that (1) both service transformation and product innovation contribute to enhancing enterprise competitiveness, but the former has a better effect, and this conclusion is still valid after replacing variables and controlling for endogeneity, and and (2) the “competitiveness effect” of service transformation and product innovation has strong heterogeneity in urban administrative levels, GVC embedding location, and enterprise ownership. (3) As two different innovation methods, service transformation and product innovation have synergistic and balanced effects.

Despite the increasing use of information and communications technology (ICT) by enterprises engaged in industrial heritage, the academic community lacks sufficient understanding of how ICT enables... Show More

Despite the increasing use of information and communications technology (ICT) by enterprises engaged in industrial heritage, the academic community lacks sufficient understanding of how ICT enables the sustainable development of industrial heritage. This article fills this gap by analyzing the application of ICT by Taoxichuan Ceramic Art Avenue (the Company) to promote its organizational innovation and achieve the sustainable development of industrial heritage. To start with, the authors conceptualized the two stages, adaptive change, and breakthrough change, of ICT-induced organizational changes in industrial heritage. Secondly, they extended the research of affordance from the technical field to the social theory field and proposed the concept of organizational affordance. Finally, the authors provided suggestions for future research to employ organizational affordance to deepen our understanding of relevant fields.

In the growth process of movie IWOM, the antecedent IWOM has a significant influence on the subsequent IWOM. IWOM does not form all at once, but iteratively over a short period. This article... Show More

In the growth process of movie IWOM, the antecedent IWOM has a significant influence on the subsequent IWOM. IWOM does not form all at once, but iteratively over a short period. This article explores the influence of IWOM publishers on IWOM growth and the dynamic impact of IWOM on movie box office by using vector autoregressive model (VAR model) and impulse response analysis. The findings reveal that highly influential and active users' statements stimulate discussion enthusiasm and increase related topic discussions. These statements also reduce the discreteness of IWOM. On the other hand, highly professional users make IWOM more discreet. Both increased discussion enthusiasm and differentiated IWOM contribute to the growth of movie box office. Additionally, during the growth of IWOM, there is an approximately five day “advance period of word-of-mouth regeneration”: it takes audiences about three days from reading movie reviews to watching a movie, followed by about two days to write their own reviews, and the whole process takes about five days.

This study investigates how the digital business environment affects firms' innovation input variables. It was discovered that digitization leads to ongoing corporate environment optimization, which... Show More

This study investigates how the digital business environment affects firms' innovation input variables. It was discovered that digitization leads to ongoing corporate environment optimization, which improves the effectiveness of innovation. One of the institutional environment factors, digitalization, increases the redundancy of government subsidies on businesses' investments in innovation. It also helps to eliminate duplication in innovation investment through the financial environment and the protection of legal rights. With increasing marketization in the informal institutional framework, the degree of R&D investment redundancy lowers while R&D human resource investment redundancy grows. Digitization not only lowers the grade of innovation, but it also has a negative association with the duplicate nature of commercial R&D investments. The authors' research combines institutional environment theory and digital development to establish a new empirical foundation for corporate development in order to boost innovation efficiency.

Drivers of social commerce usage have been the focus of scholars, but mobile social commerce is currently a sparsely researched area and therefore worth considering. Drawing on the socio-technical... Show More

Drivers of social commerce usage have been the focus of scholars, but mobile social commerce is currently a sparsely researched area and therefore worth considering. Drawing on the socio-technical systems perspective and attachment theory, this article aims to examine the effect of social and technical enablers on user attachment and whether attachment influences users' shopping and sharing intentions. Results of an empirical study (N=305 active Pinduoduo users) indicate that emotional attachment directly impacts users' intentions, while functional attachment does so indirectly through emotional attachment. Besides, social and technical factors impact emotional and functional attachment, respectively. The study provides further insights about the impact of social and technical factors on attachment and attachment on MSC intention, and contributes to MSC research and practice by developing and validating the role of MSC platforms attributes in forming users' s-commerce behavioral outcomes.

Improving the regional innovation system and developing new organizational innovations to continuously enhance regional innovation capabilities are key measures for building a regional innovation... Show More

Improving the regional innovation system and developing new organizational innovations to continuously enhance regional innovation capabilities are key measures for building a regional innovation hub and achieving high-quality economic development. This study first theoretically elucidates the impact mechanism of enterprise innovation agglomeration and government policy uncertainty on regional innovation capability, and thus clarifies such impact on regional organizational innovation. Based on urban panel data, this article empirically analyzes their impact on regional innovation. Based on the research results, the agglomeration of manufacturing industry in cities can significantly improve regional innovation capabilities. The policy uncertainty brought about by the mobility of municipal party secretaries has a restraining effect on the enhancement of regional innovation capabilities. The higher the degree of marketization in a city, the more significant the role of manufacturing agglomeration in enhancing regional innovation capabilities, thereby weakening the inhibitory effect of policies.

Digital transformation in public health has been implemented by governments and has significantly improved the accuracy and timeliness of public health management. Digital transformation in... Show More

Digital transformation in public health has been implemented by governments and has significantly improved the accuracy and timeliness of public health management. Digital transformation in measuring social determinants of health is an emerging research area that has drawn significant scholarly attention. To assess how digital information influences the measurement of social determinants of health, this study performs a systematic literature review. The paper first discusses the background, definitions, conceptual framework, and research issues. Then it summarizes the research results with a focus on disruptions, strategic responses, changes that happened in the process, facilitators and barriers, and negative and positive impacts. After a discussion of the key findings, opportunities for future research are presented along with the conclusion.

For employees, work involves taking breaks as well as engaging in specific required duties, and sometimes that break taking is construed as “cyberslacking” by employers. After historical treatments... Show More

For employees, work involves taking breaks as well as engaging in specific required duties, and sometimes that break taking is construed as “cyberslacking” by employers. After historical treatments of cyberslacking concepts, this article analyzes ways that artificial intelligence (AI) methodologies and the “bossware” platform genre are aiding management to counter the cyberslacking phenomena directly exhibited by employees or projected from previous activities and profiles. It contrasts straightforward “policing” methods that aim toward the identification of cyberslacking instances for selective punishment through surveillance, with “predictive cyberslacking” approaches that profile certain trends and patterns in employee behavior. Such identified inclinations can be used to engage or nudge workers into specific, individualized patterns of work and approved recreational or developmental activity. A medicalization-style approach is often used in bossware to entice employees toward particular mental health-themed activities (including mindfulness and meditation activities).

The COVID-19 pandemic has accelerated the trend of digital transformation (DT) among businesses. DT redefines business models, which significantly changes employees' work practices. If employees... Show More

The COVID-19 pandemic has accelerated the trend of digital transformation (DT) among businesses. DT redefines business models, which significantly changes employees' work practices. If employees lack an appropriate mindset for DT, it can result in DT failure. However, little research has explored the intention of employees to embrace DT. This study proposes a dilemmatic dual-factor research model to examine the factors influencing employees' acceptance of DT, including management support and resistance to change in the outer/explicit aspect and perceived benefits and inertia in the inner/tacit aspect. The study found that the perceived benefits of DT positively impact employees' intention to accept DT, but resistance to change and perceived inertia are significant barriers. Moreover, management support alone is insufficient to encourage employees to accept DT. This study is distinct from prior research, which typically focuses on successfully implementing DT from the firm's perspective. Instead, the study offers valuable insights into promoting employee acceptance of DT.