The Eighteenth International Conference on Management Science and Engineering Management

Digital adoption indicators are metrics used to measure the extent to which individuals or organisations are effectively leveraging internet and digital technologies to achieve their goals. The most common ones are internet speed for broadband and mobile users and the extent to which governments and businesses use the internet. Since digital adoption encompasses various aspects of technology implementation, usage and integration within organisations or among individuals, it is multidimensional and effectively addressing these dimensions is essential for successful digital adoption initiatives. In order to measure various aspects of digital adoption and readiness in different countries or regions, several organisations and research groups developed various indices. These indices provide a structured and quantitative approach to assess various aspects of digitalisation. However, interpreting index scores and translating them into actionable insights are quite challenging. Thus, this study uses latent class analysis to identify underlying subgroups based on their digital adoption metrices. It is a flexible and powerful approach to studying digital adoption by uncovering the group of countries with similar digital adoption initiatives and implementations and it will provide actionable insights especially for policy makers. Indicators from 131 countries are collected and used in the analysis. According to the findings, countries can be divided into four groups: those with excellent digital adoption, those with excellent internet adoption, those with excellent e-government adoption, and those with poor digital adoption. The discussion of this paper is focused on ASEAN countries. Four ASEAN countries are classified as having excellent overall digital adoption, one having poor internet adoption but good e-government, two having excellent internet adoption but poor e-government and two having poor overall digital adoption.

Although the academic literature provides extensive insight into lifestyle, attitudes, and religiosity, little is known about how perceived quality acts as a moderating variable in the Theory of Planned Behavior approach. This research aims to determine the factors of purchase intention that are moderated by perceived quality and how the Theory of Planned Behavior approach provides a relevant framework for understanding how religiosity, attitudes and lifestyle influence purchase intention. Conducted in Salatiga, Central Java, Indonesia, with 100 respondents, this research used Google Forms to distribute questionnaires. Analysis uses Moderated Regression Analysis (MRA). The findings show that lifestyle has a negative effect on purchase intention, while attitude has a positive effect. Religiosity also has a positive effect. The practical implication is the need for marketers to consider demographic and psychological factors to increase consumer purchasing power through innovation, while perceived quality moderates its influence. The theoretical implications show support for the Theory of Planned Behavior, with perceived quality moderating the effects of attitude and religiosity on purchase intention.

Financial literacy extends beyond mere knowledge, encompassing attitudes, behaviors, and skills. This study draws on the self-efficacy theory to investigate how different levels of financial knowledge impact the rationality of financial behavior among college students. By introducing a moderated mediation model, this research investigates the mediating role of generalized self-efficacy. Through a meticulous survey involving 4676 Chinese college students, the study reveals significant insights. Firstly, it establishes that the financial knowledge possessed by college students significantly and positively influences their financial behavior rationality. Secondly, it reveals that generalized self-efficacy partially mediates the complex relationship between financial knowledge and financial behavior rationality. This research not only contributes to the existing body of financial literacy literature but also enhances our understanding by thoroughly scrutinizing the mechanisms through which college students’ financial knowledge shapes their financial behavior rationality. The findings highlight the importance of considering not only the information students possess but also the role of their self-efficacy in translating that knowledge into prudent financial behavior. As financial literacy is crucial in navigating the complexities of the modern financial landscape, this study provides valuable insights that can inform educational strategies and interventions aimed at enhancing the financial well-being of college students.

Within the realm of digital technology advancements, digital transformation has emerged as a crucial avenue for enterprises to overcome developmental limitations, achieve business transformation, and enhance the value of innovation. However, the innovation enabling mechanism of digital transformation from the perspective of process has not been deeply revealed. Therefore, based on the dual innovation theory and network embedding theory, this study investigates the influence of the extent of digital transformation on enterprises–search behavior for innovation. Using the dataset of listed firms in mainland China, the empirical results illustrate that digital transformation stimulates the acquisition of diverse knowledge through search scope, while impeding the exploration of existing knowledge through search depth, the following results are shown: (1) Digital transformation promotes the search scope of absorbing heterogeneous knowledge, and inhibits the search depth of reusing existing knowledge; (2) In the external cooperative relationship environment with strong relationship embeddedness, enterprises are more inclined to conduct search depth, while in the external cooperative relationship environment with strong structural embeddedness, enterprises are more inclined to conduct search scope; (3) Digital transformation can have a lasting impact on innovative search behavior. From the perspective of innovation process, this paper provides some theoretical and practical references for the innovation enabling mechanism of digital transformation enterprises.

With the rapid development of digitalization and population aging, the elderly have become a vulnerable group in the digital age. In Xi’an, the contradiction between the information society and aging problem is more prominent, and the willingness of the elderly to adopt mobile payment has become an important research object. The results of a citywide study using two-stage sampling show that perceived usefulness, perceived ease of use, intergenerational technical support, and positive aging have a significant positive effect on the willingness of the elderly to adopt mobile payment. Based on this, optimizing the operation process of mobile payment, encouraging intergenerational family technical support, and improving the security of mobile payment can promote the digital integration of the elderly.

With the intensification of social competition, the career development of college students is full of more challenges, and at the same time, there is a higher demand for college students’ career adaptability, and the family upbringing environment will directly affect college students’ ability level. This study aims to explore the effect of two types of budgetary family financial education (subtle education and active education) on college students’ career adaptability. Based on the questionnaire research method and data analysis of 4676 valid questionnaires, this study was found that both types of budgeting family financial education have significant effects on college students’ career adaptability, and the higher the frequency of parents’ active education with college students about their budget plans, the stronger the college students’ career adaptability, with self-efficacy playing a mediating role in this process. The article not only enriches the research on the impact of family financial education, but also provides new guidelines for improving college students’ career adaptability.

As the female leadership continues to be explored in corporate governance, the topic of how female executives influence corporate financial decisions is receiving increasing attention. Our study is based on A-share listed companies in Shanghai and Shenzhen between 2009 and 2019 to examine the relationship between chairmen gender, gender turnover, and corporate tax aggressive behavior. Our empirical findings show that female chairmen significantly cause tax aggression and that the process of chairmen’s gender turnover leads to a reduction in tax aggression. Besides. Our conclusions extend the research related to corporate tax avoidance from a gender perspective, which not only suggests that listed companies should improve the diversification of the management of listed companies, but also provide inspiration for strengthening the supervision of the top leaders.

With the developing of global technologies and industries such as Internet, cloud computing and artificial intelligence, more new career demands are emerging. Thus, how to match employees and enterprises better shows more importance in research and application. Nowadays, there is still a lack of research on different matching types of employee career from the individual and organization in the aspect of employee and organization matching. Based on the relevant literature, this study divides eight types of career adaptability, and makes a hypothesis that the career adaptability types of employees have positive relationships with career success. Taking employees of state-owned enterprises, private enterprises and foreign-funded enterprises as the research objects, this study uses values scale and career success scale to make the questionnaire, as a consequence, 281 samples are collected, and the reliability and validity of each scale are tested. Through empirical analysis, the conclusion is drawn that among the eight career adaptability types of employees, the employees who belong to the all-fit adaptability type have the highest career success. Some suggestions for enterprise management and personal career development are given.

In the context of a surge in patent applications and rapid technological updates, exploring how to reduce patent backlog and how applicants optimize patent application strategies to enhance patent layout is a worthwhile question. Therefore, we collected invention patent applications in the field of photovoltaic industry filed in China from 1997 to 2020. Kaplan-Meier (KM) survival analysis and the Accelerated Failure Time (AFT) model were employed to analyze the factors influencing the examination duration of invention patents. The average examination period for invention patents in photovoltaic industry in China is 38.89 months. Factors like the number of claims, pages of specifications, international patent classifications (IPC), inventors, patentees, and scientific literature citations tend to prolong the time for a patent application to reach the endpoint. Conversely, factors like the number of patent families, engaging a patent agent, filing Patent Cooperation Treaty (PCT) applications, and opting for early publication contribute to a shortened patent examination period. Individual applicants experience longer waiting periods for authorization compared to other types of applicants. The study can serve as a reference for the government to enhance the operational efficiency of the patent examination system and provide guidance for patent applicants on how to expedite the examination period and obtain faster grant.

Most previous studies explored the factors affecting career success from the individual or organizational level, but with economic transformation and upgrading, Chinese enterprises urgently need to conduct in-depth studies based on the integration of individuals and organizations. In the context of economic transformation and upgrading, enterprises need to deeply study the integration relationship between individuals and organizations in order to adapt to the new environment and challenges. This is because with the intensification of market competition and the development of technology, enterprises have an increasing demand for high-quality employees and innovative capabilities. In this context, the matching relationship between individuals and organizations becomes crucial. Economic transformation may lead to changes in the integration relationship between individuals and organizations. Where previously individuals may have focused more on compensation and position, they are now more likely to focus on the culture, values, and support for personal development of the organization. This change has a direct impact on the organization, including increased employee satisfaction, job performance and employee loyalty, as well as helping to promote innovation and teamwork. At the same time, with the advent of borderless careers and the changeable career era, focus is shifting towards the realization of self-value. In this paper, person-organization fit is taken as the antecedent variable and career adaptability as the mediating variable, and the measurement index based on “value realization degree” is used to explore whether the matching degree between individuals and organizations has an impact on career adaptability and career success of individuals. This paper adopts the questionnaire survey method to carry out the empirical study. Analysis of data from 404 questionnaires shows that personal-organizational matching has a significant positive impact on career success.

Childhood socioeconomic status plays an indispensable role in an individual’s developmental journey, with its profound and intricate impact. Drawing inspiration from the theory of delayed gratification, this study delves into how childhood socioeconomic status influences career adaptability. Introducing an intermediate model, it meticulously examines the mediating effect of delayed gratification. Through a detailed survey of 4676 Chinese college students, the findings reveal the following: (1) Childhood socioeconomic status significantly and positively influences the rationality of career adaptability among college students; (2) Delayed gratification acts as a mediator in the complex relationship between childhood socioeconomic status and career adaptability. Through this research, we aim to provide profound insights into understanding the influence of socioeconomic status on the psychological development of college students and offer practical guidance for cultivating resilience and adaptability in university life.

The impact of a new product release on the brand reputation of corporations is crucial. However, existing scholars mainly focus on new physical products or experiential nonphysical products, and the research perspective is mostly static. This paper aims to study the real-time impact of new product releases on the brand reputation of theme parks. Using Shanghai Disneyland as an example, this study employs social media tracking to collect real-time micro-blog data during a new product release using the customer equity framework to compute, furthermore analyse brand reputation and emotion. The results indicated that new product releases and events can affect theme park brand reputation. Stakeholders are particularly concerned about new product quality and user experience. A positive response and heartfelt apology of corporations will help theme parks deal with brand crises. This research has important theoretical and practical implications for the new product release and brand reputation management of theme parks.

Setting the “14th Five-Year Plan for the Development of New Urbanization in Zhejiang Province” as a background, this paper constructs a VAR model to discuss the influence of demographic, spatial, economic, and social urbanization on the development of the eco-environment in Zhejiang Province, based on time series data in the period of 2001–2020. The results show that with an overall contribution rate of more than 80%, the urban development in Zhejiang Province has a significant impact on the eco-environment. In terms of specific urbanization types, spatial urbanization brings the strongest impact and contributes a rate of 53.60% to deteriorating the eco-environment in the long term. Based on the above findings, this paper proposes recommendations on how to avoid the negative impacts of spatial urbanization and fully leverage the positive impacts of urbanization on the eco-environment in Zhejiang Province.

In the current context of economic globalization, international brands continue to come in and local brands continue to emerge, with a large number of brands. Competition in the market is fierce in all industries. And how to stand out from the many brands, correct positioning and timely update the cultural connotation of the brand is an important means of brand personalization, enhance brand image and competitiveness. This paper takes brand identification as the mediating variable, and researches brand culture from three dimensions of emotional value, social value and cognitive value. To establish a research model of cultural influence. On consumer buying behavior. It finally shows that emotional value, social value and cognitive value have a positive impact on brand identity. Therefore, injecting cultural connotation into a brand is crucial for enhancing brand identity and shaping brand characteristics. This study has certain theoretical and practical significance for corporate brand managers.

Improving total factor productivity is the power source of high-quality development in emerging economies. Family firm in emerging countries represented by China is an important part of economy, it is of great significance to explore the influencing factors of TFP of family firms. This paper takes the family firms listed in Shanghai and Shenzhen stock markets of China from 2012 to 2022 as the research samples, and explores the influence of couples’ joint holding on the total factor productivity of firms. The results show that: (1) There is significant negative influence of couples’ joint holding on the total factor productivity of firms; (2) The differences in educational level between husband and wife can strengthen the negative influence of couples’ joint holding on the total factor productivity of firms; (3) The existence of institutional investors can effectively participate in corporate governance, play a supervisory role, and weaken the negative influence of couples’ joint holding on the total factor productivity of firms. This research can shed light on further TFP improvement and high-quality economic development for emerging countries that are under economic transformation.

Inquiry letters, as a representative measure of non-punitive oversight, have become an important tool for stock exchanges to fulfill their frontline supervisory roles. Based on this background, we examine the relationship between inquiry letters and forward-looking disclosure using OLS regression on A-share-listed companies. The results indicate that, following the receipt of inquiry letters, companies tend to disclose a greater number of future events in their annual report narratives, with a significant increase in the use of future tense statements. The secretary’s financial experience and military background strengthen the relationship between the two phenomena. Furthermore, this phenomenon is significant for both state-owned enterprises (SOEs) and non-state-owned enterprises (non-SOEs), although non-SOEs are more inclined to disclose a greater amount of forward-looking information compared to SOEs. The findings of this paper confirm that “futuristic” textual information in annual reports is an important tool for executives of listed companies to embellish information disclosure and stabilize the market price, and provides direct evidence of the effectiveness of the regulation of stock exchange inquiry letters.

Motivational climate uncertainty perception plays a pivotal role in organizational settings, exerting a significant influence on employees’ emotions and behaviors. Drawing from the uncertainty management theory, we hypothesized that motivational climate uncertainty perception would negatively impact organizational citizenship behavior through the pathways of job burnout and organizational identity. The study constructed a research model with motivational climate uncertainty perception as the independent variable, job burnout and organizational identity as chained mediator variables, and organizational citizenship behavior as the dependent variable, and tested the research hypotheses using data analysis software such as AMOS and SPSS. Findings from a two-wave survey involving 134 Chinese full-time employees indicated that motivational climate uncertainty perception indeed had a significant negative effect on employees’ organizational citizenship behavior. Furthermore, job burnout was found to mediate the relationship between motivational climate uncertainty perception and organizational citizenship behavior, with both job burnout and organizational identity serving as serial mediators in this relationship. Finally, the study discusses the conclusions and implications drawn from these findings.

This study provides empirical evidence on the association between internal control and corporate greenwashing behaviors. Using various measures and a series of robust regression analysis over the period from 2013 to 2021, the results suggest that internal control can inhibit the greenwashing behaviors of the company. Meanwhile, we find that military experience of senior executives plays a significant moderate role between internal control and greenwashing level of company, which means military experience of senior executives can enhance the inhibitory influence of the internal control on the greenwashing level of the certain company. Furthermore, we also find that if the CSR report of the company has been audited by the third party, the inhibitory effect of internal control can also be improved. Our results are also robust after adjusting for endogenous problems using two-stage squares (2SLS) regression.

By examining Chinese listed companies from 2007 to 2019 and finds that green credit policies significantly promote corporate investment efficiency. The results remain robust after conducting parallel trend tests, key variable substitution definitions, and placebo tests. Higher ROA, greater cash flow, and higher analyst coverage are associated with lower investment efficiency, while state-owned enterprises exhibit higher investment efficiency. The mechanisms through which green credit policies affect investment efficiency include cash holdings, agency issues, female executives, investment opportunities, and technological innovation. Green credit policies encourage heavily polluting companies to invest prudently, assist in decision-making and resource allocation, and promote high-quality development of enterprises.

In the context of digital economy, digital transformation is of great significance for enterprises to achieve high-quality development. The extent of enterprise digital transformation primarily relies on the strategic decisions made by management. Institutional investors are important participants in corporate governance and may influence management’s strategic decisions on enterprise digitalization. Taking the A-share manufacturing listed companies in Shanghai and Shenzhen from 2012 to 2022 as the research sample, this paper empirically tests the impact of institutional investors’ shareholding on the digital transformation of enterprises. The research finds that institutional investors’ shareholding can significantly promote the digital transformation of enterprises, and the research conclusion is still valid after robustness test. The mechanism test shows that institutional investors’ shareholding can promote corporate digital transformation by alleviating corporate financing constraints. Heterogeneity analysis finds that the promotion effect of institutional investors’ shareholding on enterprises’ digital transformation is mainly reflected in non-state-owned enterprises and industries with fierce competition. This study enriches the research on the governance effect of institutional investors and the influencing factors of enterprise digital transformation and can provide some reference for institutional investors to participate in corporate governance and enterprises to promote the process of digital transformation.

With the rise of entertainment live streaming, live streaming companies are seeking ways to encourage user payments and boost corporate performance through social media. This article examines the impact of audience numbers on user tipping behavior in a user-generated live streaming model, using data from 1000 rooms in an online music community over a two-month period. The research shows that the number of viewers in the live room has an inverted U-shaped effect on user tipping behavior, whereby tipping frequency increases with audience numbers up to a certain point, and then begins to decline. Interestingly, the streamer’s level of prior interaction and followee count moderates the relationship between audience numbers and tipping behavior. Higher levels of previous interactions and a larger followee count tend to dampen the inverted U-shaped effect, suggesting that more engaged or popular streamers may influence tipping behavior differently. This study not only enriches the theoretical literature on user-generated live streaming but also has practical implications for live streaming companies.

The role of safety culture in preventing accidents in oil and gas field enterprises is paramount, serving as the critical pivot from passive to proactive safety measures. Existing research predominantly focuses on the relationship between safety culture and safety behavior. However, studies examining the establishment of a “chain transmission” perspective in oil and gas field enterprises are relatively scarce. Therefore, this study constructs a theoretical model of the mechanism of action, centering on key variables such as safety conceptual culture, safety institutional culture, safety material culture, safety behavior culture, and safety culture performance. It conducts a survey among employees of oil and gas field enterprises and employs the structural equation modeling software Amos 26 to test direct, mediating, and chain mediating effects based on survey data. Based on empirical results, the study offers practical insights for the development of safety culture in oil and gas field enterprises.

In recent years, the clamor for carbon peaking and carbon neutrality has intensified, underscoring the imperative for airports to embrace green sustainable development. Leveraging bibliometric data analysis, this study delves into the trajectory of green airport. Through comprehensive integration and evaluation of pertinent scientific literature, key themes in research of green airport are discerned via clustering and timeline mapping, elucidating their developmental trajectories and trends. To foster the advancement of eco-friendly and sustainable airports, a holistic approach is advocated, encompassing technological innovation, adoption of clean energy sources, robust management systems, active policy engagement, and community support. We propose the establishment of an integrated system involving airport management, markets, governmental bodies, the public, and other pertinent stakeholders. The insights obtained from scientific data can also be extended to other related areas that need to reduce emissions.

For the EU candidate countries, sustainable agriculture is a transition to developing a systemic concept that will allow them to identify the conditions and opportunities for a new orientation and creation of a socio-ecological development model. Based on this objective, we evaluated the sustainable agriculture of three EU accession candidate countries - Georgia, the Republic of Moldova, and Ukraine, and two neighboring countries from the EU - Poland and Romania. For this purpose, we have applied a non-parametric DEA econometric method to evaluate the efficiency of homogeneous decision-making units based on constructing a general frontier of production possibilities based on actual data (inputs - outputs). As a result of the specificity of the complex concept of sustainable agriculture, two DEA models were chosen (basic radial model and radial super efficiency model): the VRS hypothesis and the input-oriented approach. As a result of applying the DEA basic radial model, the sustainable agriculture systems included in the model obtained a technical efficiency score equal to one, meaning they are all equally efficient. To classify the efficient DMUs, Andersen and Petersen’s super efficiency model was used, and thus, the sustainable agriculture systems of Georgia and Romania were highlighted. In conclusion, the DEA method has generated information that allows further analysis of sustainable agriculture systems for groups of countries chosen according to different criteria.

According to the “14th Five Year Plan” for the development of the construction industry issued by the Chinese Ministry of Housing and Urban Rural Development, by 2025, prefabricated buildings will account for more than 30% of new buildings. Industrialization and intelligence have become important directions for low-carbon transformation, green development and the realization of dual carbon goals in the construction field. Starting from the perspective of green prefabricated construction management based on carbon reduction, this article considers the multi-stage economic carbon emission balance decision-making of prefabricated construction materials supply planning. The economic-carbon emission balance decision is considered from the perspective of green prefabricated construction management. The equilibrium optimization model is constructed for the prefabricated construction decision makers using multi-objective planning. Through the case study of prefabricated construction and supply planning, the emission reduction effects of production and supply operation of prefabricated building materials in different scenarios are analyzed, and relevant suggestions are also proposed for the practitioners.

The mathematical models, describing behavior of the systems with moving servers and finite volumes constructed and investigated. The prototypes of such systems are traffic, cargo, airport facilities, information and communication systems, computer networks and others. One of the main problems in that direction is calculation and optimization of various efficiency indices of such systems. In the capacity of the efficiency index is taken a customer average waiting time before service. For minimizing this efficiency index, a control function is introduced which means delay of beginning service. Such control is easily realized in practice and as is shown in the paper, gives a gain in a customer waiting time before service. The wide class of systems with moving servers for which it is advisable to introduce delay is derived. The optimal function minimizing a customer waiting time before service has been found. Complicated systems are investigated by simulation. Numerical examples demonstrating the theoretical results and results of simulation are given.

In order to keep the sustainable global developing steps and improve the innovation ability in open innovation platforms, sustainable technology catching up is indispensable in China. However, sometimes the international technology catching up paths, such as international import, FDI, and strategic alliances may not play so significant effect for laggard firms in China at their early stage of catching up on account of their weak absorptive capacity, insufficient complementary assets, and far geographical distance from advanced technologies. Therefore, how do these laggard firms expedite their early-stage sustainable technology catching up availably? Based on the extant paths, from the perspective of open innovation, we put forward a new path named learning-by-technology learning intermediary firms to help those laggard firms improve their technology catching up process and build an evolutionary economics model to capture the evolution process of this system. We gave out the technology learning intermediary firms play different roles such as technology pursuers, technology innovators, and technology transfers at different stages during the laggard firms technology catching up process.

This paper proposes a grid-connected hybrid PV/battery system for a drinking water treatment plant to achieve low-carbon and cost-effective operations. A multi-objective model is proposed for the decision-maker to optimize system size and operation schedules. The levelized cost of electricity (LCOE) is minimized while the self-sufficiency ratio target is met and carbon emissions are reduced. The proposed model is further applied to a real case in Foshan, China to demonstrate the applicability for real implementation. The results of this study show that the hybrid system’s LCOE can achieve 0.4597 CNY/kWh (which is 30% lower than the main-grid supplied system), with the self-sufficiency ratio reaching 67.8% and carbon emissions reduced by 32.2%.

This paper develops a bi-level optimization model to manage the entire municipal solid waste disposal process using gasification technology, with the goals of minimizing total carbon emissions of the local authority and maximizing total profits of the municipal solid waste operators. We aim to find an equilibrium point that satisfies both levels’ benefits while also resolving their internal conflicts. The proposed methodology is then applied to a real-life case to test its feasibility. Scenario analyses on electricity subsidies of gasification technology are performed to provide practical suggestions on municipal solid waste management and electricity recovery. It was found that the proposed methodology can orderly regulate waste transportation and gasification, efficiently recover electricity resource, and balance multiple objectives to achieve bi-level harmony. Gasification was found as a promising technology for the municipal solid waste operators to make profits and maintain stable operations without the backing of the local authority, due to its ability to produce abundant energy products.

With the development of urbanization, educational resources have gathered in cities and towns, triggering the educational urbanization. The imbalance between urban and rural areas has caused family education dilemma: rural parents send their children to cities for high-quality education, but their children’s academic performance has not been improved. Based on the data from the China Education Panel Survey (CEPS), this study used multiple linear regression model and interviews to explore why education dilemma formed. This study concludes that parental education participation, family education expenditure and boarding choice are influential factors, and proposes countermeasures accordingly. The findings can help to explore the impact of urban-rural education quality differences on families, so as to promote the high-quality and well-balanced development of urban-rural education.

As network technology continues to progress, an escalating multitude of business videos have surfaced. Among the myriad types of business videos, profit-oriented educational videos stand out as a significant category. Due to the proliferation of educational videos on online platforms and their increasing popularity and recognition, watching such videos has become a crucial means of learning for student users. However, discrepancies exist between certain courses, the pace of teachers’ lectures, and users’ requirements have contributed to a decline in course enrollment rates. Therefore, this paper takes the reviews under educational videos related to the sold courses as the object of study. Firstly, an LSTM model is used to analyze the sentiment of these reviews. Secondly, two factors related to the number of likes and follow-up reviews are quantified. Finally, by integrating sentiment tendencies with the number of likes and follow-up reviews, this paper establishes a usefulness evaluation scheme based on the LSTM model. The experiments demonstrate that this approach achieves high accuracy in the classification of review sentiment analysis and ensures the correctness of review usefulness scores, ultimately aiming to boost course sales rates.

In the past few years, the global spread of the COVID-19 pandemic, the rise of populism, anti-globalization, unilateralism, and nationalism, geopolitical crises such as the Russia-Ukraine conflict, and the prolonged economic downturn have brought the world to a crossroads on globalization. In such a context, internalization of higher education is confronted with great challenges, while Sino-foreign institutions have been particularly vulnerable to the effects of the crises and have been forced to respond to the challenges and explore alternative crisis-response methods through new crisis management strategies. Taking Covid-19 pandemic crisis as a case, the current study collected policy documents, news reports, and announcements concerning pandemic crisis governance from the Ministry of Education (MOE), provincial education departments, and Sino-foreign universities within one year after the outbreak the pandemic. Based on these materials, the actions of Sino-foreign institutions associated with crisis management were summarized and tabulated based on the grounded theory method. This study put forward a public crisis collaborative governance model of Sino-Foreign institutions as “the government guides, the university leads, and the society participates”, showing the successful application of collaborative governance in Sino-foreign institutions. This study contributes to the collaborative governance theory, and provides theoretical and practical references for universities, government and society in terms of improving governance abilities and optimizing governance systems for the future.

Under the background of global response to climate change, we divide the countries participating in carbon reduction into developed country group and developing country group. This paper uses differential game model to study the optimal emission reduction strategies, optimal carbon level trajectories, and optimal benefits of two country groups under different game modes., i.e., non-sharing mode N, complete cooperation mode C, and common but differentiated mode S. The results show that Mode C can achieve the maximum emission reduction intensity, the lowest carbon level, and the maximum overall benefit. Under the premise that the discount rate is greater than the natural growth rate of carbon levels, the developing country group achieves Pareto improvement in Model S compared to Model N in terms of emission reduction intensity and optimal benefit as well as the lower optimal carbon level when it is less sensitive to the changes in international reputation brought by carbon reduction – it plays the role of “free rider”. Finally, numerical examples verify the above theoretical results.

As a result of sustained population growth and significant improvement in living standards, the amount of generated food waste is huge and continues to increase. Resource-based treatment of food waste using anaerobic digestion has become the most practice in China. However, the current application of anaerobic digestion is facing problems such as low efficiency and poor reaction stability, which results in hindering the progress of the food waste treatment industry. Therefore, this study proposed a bi-level optimization model to equilibrium the decisions of the local government and the food waste treatment plant, which helps the local government to use the subsidy mechanism to encourage the operation of the food waste treatment plants and improve the effectiveness of food waste treatment. The impact of the feed-in tariffs for food waste cogeneration on the model results is analyzed. It was found that the local authority should subsidise the feed-in tariff and that food waste treatment plants should consider the selection of anaerobic co-digestion substrates in conjunction with costs.

Academic entrepreneurship, characterized by the commercialization of research findings by university scholars, plays a central role in driving global innovation. Within the context of China’s National University Science and Technology Park (NUSTP), this study introduces a robust evaluation index system and employs the Data Envelopment Analysis (DEA) method to assess the efficiency of such endeavors across 30 Chinese provinces, from the horizontal provincial level and the vertical time-series level. Notably, the academic entrepreneurship efficiency of NUSTPs varies significantly among different provinces and regions of China. For instance, regions like North China demonstrate optimal efficiency, while provinces such as Liaoning, Jilin, Ningxia, and Shaanxi lag behind. The findings reveal that while many NUSTPs exhibit DEA inefficiency, scale inefficiencies are more dominant than pure technical inefficiencies. As the global academic landscape evolves, challenges related to institutional management appear to be diminishing, but issues concerning resource allocation are becoming more pronounced. The optimization of resource distribution, alignment with both local and global policies, and adaptation to evolving entrepreneurial landscapes are imperative for institutions to foster innovation and enhance efficiency. These insights, while rooted in the Chinese context, have broader implications for academic institutions worldwide.

$$CO_{2}$$ C O 2 storage in depleted oil and gas reservoirs is an important approach to reducing anthropogenic $$CO_{2}$$ C O 2 emissions owing to its unique advantages. Carbon capture and storage (CCS) projects thus require a practical monitoring program to confirm that injected $$CO_{2}$$ C O 2 remains in reservoirs as intended and that any occurring leakage is promptly detected and corrected. To develop an eco-friendly and cost-effective monitoring program, this study proposes a multi-objective integer model with three considerations: environmental sustainability, economic savings, and reliable detection. The proposed model is then applied to a CCS project in Shaanxi, China, to demonstrate its efficiency and practicality. An enhanced strengthen elitist genetic algorithm is developed as the solution approach. The analyses and discussions under different scenarios yield interesting and valuable proposals. Corresponding management recommendations are proposed to improve practical operations.

The renewable energy consumption influences the economic return and sustainable development of green power, which makes a key effect on carbon neutrality. The renewable portfolios standards (RPS) is a policy to restraint the electricity sellers to consume green power. This paper focuses on the uncertain decision problem of electricity sellers in power and green certificates trading, and builds a two-stage programming model with random and interval variables to describe the uncertainty. The power and green certificates trading are considered in the different time scales in this model to guarantee the decision flexibility. Meanwhile this paper proposes a price curve principle to help the green certificates trading with the unknown price trends. A case study is adopted to indicate the effectiveness of the proposed model, and show the market and policy effect on the renewable energy consumption through the scenario analysis. Based on the scenario analysis, it can be found green certificate price have influence on actual green power consumption enthusiasm. And the effect of policy requirement on promoting green power consumption is more stable and controllable, compared with green certificates price.

This study focuses on the Sichuan and Chongqing Regions Sports Tourism Demonstration Bases, along with their respective host cities, during the period of 2021–2023. And the study is conducted by assessing the network attention garnered by each scenic spot and host city, utilizing data derived from user comments, like Online Travel Agency (OTA) platform. Furthermore, to study deeper into the developmental efficiency of the Sichuan and Chongqing Regions Sports Tourism Demonstration Bases, key indicators are employed. The total area of the Sichuan and Chongqing Regions Sports Tourism Demonstration Bases is chosen as the land input indicator, the quantity of star-rated hotels serves as the capital input indicator, and the combined metrics of total tourism income and network attention are utilized as output indicators. With the help of this approach, this study enables us to calculate and analyze the developmental efficiency of the Sichuan and Chongqing Regions Sports Tourism Demonstration Bases in each city by using the Data envelopment analysis (DEA) model. The aim of this research is to leverage land and capital inputs to propel the rapid expansion of the leisure sports tourism economy in the Sichuan and Chongqing regions. Additionally, this endeavor seeks to diminish regional disparities in the efficiency of integrating the Sichuan and Chongqing regions even all of China.

In the context of carbon peaking and carbon neutralization, China has undertaken the task of carbon emission reduction. The exploitation and utilization of coalbed methane can reduce the carbon emission of the industry supplement the energy structure and reduce the mining risk. The coal-bed methane enterprises and power plants are closely related and there are related interests. However, due to the game relationship between the buyer and the seller on the price of coalbed methane, some decision-making conflicts are caused. In the actual operation process, enterprises should consider the complex relationship between multiple subjects. Thus, this paper constructs a bi-level multi-objective programming model to describe the complex relationship. In order to obtain the optimal solution of the model, the double-layer model is transformed into a single-layer model according to the Karush-Kuhn-Tucher (KKT) condition of the lower model. $$\epsilon $$ ϵ - constraint method transforms the upper multi-objective optimization problem into a single objective optimization problem. Through the example analysis to verify the rationality and effectiveness of the model, it is concluded coalbed methane enterprise should reasonably apply $$CO_{2}$$ C O 2 -ECBM technology to vigorously exploit coalbed methane, and power plants should actively remove coal and reduce coal and expand the scale of coalbed methane power generation.

Survival analysis poses challenges when dealing with right-censored data, characterized by an incomplete structure. Classical estimation methods in the data modeling context face limitations in the presence of right-censored response variables, necessitating a solution to the censorship problem before modeling. This study addresses the censorship challenge using synthetic data transformation, Kaplan-Meier weights, and Buckley-James transformation. In methodology, we focus on modifying the semiparametric kernel smoothers according to the censorship solutions and introducing alternative estimators for the right-censored partially linear model. To present comparative performances of the modified kernel estimators, a simulation study is carried out.

A study was conducted to assess the annual performance and energy efficiency of two types of Tubular Solar Stills (TSS) in the climate of Chennai, India. The first TSS yielded 569.7 kg of distilled water annually, while the second TSS, which incorporated watermelon seeds (WMS), produced 877.5 kg, marking a 35.08% increase. Additionally, the highest monthly energy efficiency observed for the TSS and TSS with WMS were 15.19% and 23.4%, respectively. On an annual basis, the CTSS achieved an energy efficiency of 13.3%, whereas the MTSS with WMS reached 20.49%. The payback period for CTSS and MTSS is 0.467 years and 0.312 years, respectively, achieving a 33.1906% decrease in MTSS in contrast to CTSS.

This paper constructs a quadrant model to measure the house-purchase pressure for urban residents, and it’s temporal and spatial differences were studied based on the date of 284 cities at the prefecture level and above in China from 2005 to 2021. The results show the following: (1) From 2005 to 2021, the downpayment and comprehensive pressure of house purchases decreased, and the monthly payment pressure increased; the house-purchases pressure in first- and second-tier cities increased, the pressure in third- and fourth-tier cities declined. (2) In terms of regional distribution, downpayment and comprehensive pressure were high in the east and west and low in the middle of the country, and the monthly payment pressure in urban agglomeration was relatively high. (3) From the spatial difference, the diversities in house-buying pressure decreased; the house-buying pressure in first-tier cities tended to increase, and the pressure in the third- and fourth-tier cities tended to decrease. (4) From the perspective of spatial correlation, the global correlation of house-buying pressure showed a trend of “decrease-increase-decrease-increase”, with local hot spots concentrated in Jiangsu, Zhejiang, Shanghai, and the southeast coastal areas and cold spots concentrated in the central-southern and northern Shanxi regions.

The study evaluates the performances of two mixed-effect machine learning methods (RE-EM trees and MERF) and mixed effects penalized methods, three classical machine learning methods (random forest, gradient boosting trees, support vector machine), penalized and shrinkage models (Ridge, LASSO, ALASSO, SCAD, shrinkage) in the prediction of high dimensional longitudinal data. It aims to compare mixed effect models and traditional models’ prediction accuracy using correlated data. Two real data applications are used aiming to predict the COVID-19 number of cases and pandemic-related number of deaths. The models are evaluated according to the RMSE values of the predictors.

Wind energy has emerged as one of the most relevant renewable energy sources, requiring novel condition monitoring systems to reach competitiveness and ensure the reliability and maintainability of wind turbines. This paper introduces an innovative non-destructive testing system designed for the acoustic analysis of wind turbine rotatory components, capturing the acoustic signals from the nacelle using an acoustic condition monitoring system. A signal processing procedure employing wavelet transforms to filter and analyse the energy samples is presented, to detect patterns associated with different scenarios. The implementation of different wavelet families together with novel analytic techniques provided high accuracy in pattern classification results. A real case study is presented to test the methodology, concluding that acoustic monitoring is a suitable and reliable technique for fault detection in wind turbines.

The improved simultaneous estimation of the skewness parameters is considered under the uncertain prior information (UPI) that component skewness parameters may be equal. It is advantageous to combine the data to estimate the common skewness parameter. However, the combined estimator becomes biased and inconsistent when the quality of the parameters may not hold. In this situation, estimators based on pretest and shrinkage estimation are proposed. Asymptotic properties of the suggested estimators are established and compared. A simulation study is conducted to appraise the performance of the estimators numerically, as well. Further, a real data example is presented to demonstrate the usefulness of the suggested estimation strategies. The relative dominance picture of the proposed estimators is presented.

We obtained estimates in generalized Orlicz-Morrey spaces are used to study global regularity of the solution of the mixed boundary problem of nonlinear elliptic equations in divergence form over a bounded non-smooth domain. For these is we used of Calderon-Zygmund theory. The exploration of nonlinear reactions, drift, and diffusion processes has garnered significant attention, serving as mathematical models for various applied problems. One such example involves the diffusion processes of electrically charged species during phase transitions and transport in porous media. Additionally, it is worth mentioning that in semiconductor theory, weight functions possess derivatives. Another illustrative instance arises in the context of phase separation problems, where the commonly employed tools include Fermi integrals and Fermi functions. This problems is connected with of nonlinear process which arise as mathematical models of different applied problems. The qualitative property of solution is investigated. The theorems obtained in this article have important applied significance in various issues of mechanics, physics, biology and other applied fields. Also at the end of the article there are specific results where the results obtained in the article are applied. Also at the end of the article there are specific results where the results obtained in the article are applied.

In this research study, the performance of estimation strategies was improved for an inverse Gaussian regression model in the presence of uncertainty regarding the quality of subspace information. It is suggested that the estimation strategies are based on linear shrinkage and shrinkage pretest. To evaluate the relative performance of these estimators, a Monte Carlo simulation for different combinations was conducted. The shrinkage pretest estimation strategy is suggested for use in practical situations, regardless of the quality of subspace information. Furthermore, suggested estimation strategies were applied to a real-data example to evaluate their practicality.

With the continuous development and popularization of sports events, more and more theme songs have emerged and spread widely on the mobile internet, attracting the attention and discussion of netizens. However, the evaluation of music effect in the past can not answer the question of how to evaluate the theme songs of sports events. Therefore, the purpose of this paper is to establish an index evaluation system for the theme song of sports events. In order to solve the above problems, this study constructs an index evaluation system composed of three first-level indicators, six second-level indicators and sixteen third-level indicators by means of literature analysis and expert interviews. With the help of the interpretative structural model, this paper makes a deep theoretical exploration on the influencing factors affecting the evaluation of the theme song effect of sports events. The index evaluation system constructed in this paper takes into account the music quality of songs, the fit with the competition, the communication effect and the public acceptance, which provides a powerful tool for the comprehensive and objective evaluation of the theme song of sports events and promotes the development of the music industry of sports events. It promotes the brand value of sports events in the aspects of promoting the blending development of culture and economy, promoting the image of the city and promoting the innovation of cultural industry.

The article examines the problem of diagnosing and forecasting faults in gas turbines (GT). The novelty of the study lies in the application of machine learning methods for fault diagnosis-a method that can surpass traditional statistical approaches, enabling more efficient and accurate predictions. The researchers’ contribution also includes the creation of datasets characterizing the operation of GT under the influence of defect groups. The research methodology involved the creation and study of these datasets using GT models, assessing technical conditions, and accounting for defects. This approach allowed for the application of machine learning models in the absence of sufficient real-world data. The main goal of the research was to evaluate the effectiveness of machine learning in assessing the technical condition, classifying defect groups, and estimating the development stages of defects based on thermogasdynamic parameters measured during operation. Key research results demonstrate the potential of models to successfully classify fault groups and predict the stage of defect development. The study showed high accuracy in determining the technical condition of GT, confirming the potential of machine learning in improving diagnostic and maintenance systems. However, the research also underscores the need for further studies using real data to confirm these findings.

Blockchain is a widely sought-after technology that acts as a distributed ledger to store documents safely and securely. Many applications of blockchain like service voting systems, document storage systems and EHR (Electronic Health Record) systems attest to the fact that storing data in blockchain is a decision well taken. This annihilates any possibility of single-point failures in the system at any given circumstance. EHR is a valuable document that has to be deposited in a secure environment such that only the authorized people can access it (the doctors and the patients in our case), Authorization is done when the person joins the network.The aim is to create a secure and immutable Electronic Health Record (EHR) storage system using Ethereum which allows patients to upload their documents. The proposed system facilitates secure data storage and transfer between patients and doctors through the InterPlanetary File System which is a protocoled peer-to-peer file sharing and storing system that uniquely identifies each file by employing content addressing in the global namespace. On implementation, the proposed system ensures the secure storage of health records of the patients that can be shared safely with their selected healthcare provider as and when required and free from tampering. The documents are encrypted using the Rivest Shamir Adleman algorithm (RSA), the public key of which is further encrypted using the Nth degree Truncated Polynomial Ring Units algorithm (NTRU) for leveraging extra security to the system. The system itself leans towards being patient-centric and strives to provide them with complete privacy and autonomy over their personal medical data records. As the healthcare sector adopts patient-centred models, patients will have more control over their medical records and receive higher-quality care. Confidential computing and blockchain technology can be combined to build a network of cooperative ecosystems that will facilitate more secure and safe data sharing.

Facing of the existing reception dilemma of rumor refuting information, crowd identification and feature analysis should be realized through big data analysis. Our approach aims to accurately identify rumor refuters and interpret predictions. Initially, we compare six machine learning models, with results demonstrating the superiority of eXtreme Gradient Boosting (XGBoost) over other advanced models. Subsequently, we introduce Shapley additive explanations (SHAP) to interpret the predictions of complex machine learning models and assess the importance of various features. Our findings underscore that utilizing XGBoost alongside the SHAP approach can offer decision support, enhancing the effectiveness of rumor governance.

The provision of scientific knowledge is an important pandemic control strategy as it increases the public’s sense of responsibility and security and changes their behaviors. It is necessary to understand the interactive relationship between scientific knowledge and the pandemic spread. Based on the classic Brusselator model, this paper developed an interplay model considering scientific knowledge and pandemic spread. Through the theoretical analysis of the model, the scientific knowledge-pandemic system was analyzed and demonstrated that it satisfies the Brusselator model’s conditions, and a quantitative discriminant method that can judge whether the system is stable is proposed. That is, the stability of knowledge-pandemic system can be judged by the eigenvalues of linear system transformed from knowledge-pandemic system. A phase diagram was drawn depicting the scientific knowledge and pandemic spread. From the simulation, insufficient scientific knowledge in the early pandemic stage could lead to an uncontrolled spread of the pandemic even if the scientific knowledge dissemination rate increased during the pandemic development stage. According to the results, several effective suggestions are proposed to control the spread of disease and this research is expanding the Brusselator model in the pandemic field, providing scientific strategies for pandemic management.

Seawater desalination refers to the process of making fresh water from sea water. The construction of a seawater desalination project is beneficial for increasing water resources and regarded as a strategic reserve measure. Therefore, a reference-dependent regret theory-based multi-criteria decision-making (MCDM) model under a Pythagorean fuzzy environment is proposed to assess seawater desalination projects. From the production perspective, the criteria system for seawater desalination project assessment is put forward based on aspects of project construction and project operation. Furthermore, considering the influence of the degree of initiative on the perception of regret, positivity is defined as the distance between decision information and reference points. The Dempster-Shafer (D-S) evidence theory is used to determine the group reference point, and a more effective fusion of the expectation level of information is realized. Moreover, to overcome the problem that the objective weight cannot comprehensively reflect the importance, the combined weight method formed by the entropy and BWM methods is adopted to determine the criteria weights. Finally, a practical case of seawater desalination project evaluation is used to verify the effectiveness of the method. This study determines the priority of seawater desalination projects and enriches the Pythagorean fuzzy comprehensive evaluation method theory.

Independent development of Traditional Chinese Medicine (TCM) will strengthen competitive connotation of the relationship between Chinese and Western medicine, and symbiotic strategy of Chinese and Western medicine will be influenced. An evolutionary game model has been established and evolution trend of symbiotic strategy of Chinese and Western medicine has been simulated in different situations. There are three conclusions based on simulation results. One is that if considerable benefits of TCM can be generated when there is not targeted strategy of Western medicine, development oriented strategy has chance to become dominant strategy of TCM. Secondly, if it cannot bring significant benefits for TCM, development oriented strategy will only have strong growth potential when its initial adoption situation is very optimistic. Thirdly, if development oriented strategy has positive externality to Western medicine, its growth potential will be stronger than if it does not has positive externality. Some suggestions for development of TCM have been proposed.

In the face of increasingly severe global issues such as climate change, environmental challenges, and energy constraints, promoting new energy sources has become crucial for accelerating sustainable development worldwide. In this regard, it is significant to establish an effective energy assessment mechanism. However, existing energy assessment methods ignored the uncertainty and reliability of evaluation information, which can lead to an incomplete decision-making process. Additionally, the information heterogeneity may lead to information loss in information fusion. To overcome these limitations, this study proposes a linguistic Z-number belief-based evidential reasoning approach. , which can integrate heterogeneous information and its corresponding reliability using linguistic Z-numbers. Firstly, an evaluation matrix based on linguistic Z-number belief is constructed to express the natural language description information of experts. Next, the comprehensive belief degree is obtained according to the evidence reasoning algorithm. The comprehensive ranking result is obtained by the maximum, average and minimum utility values. An example of energy evaluation is taken to verify the effectiveness of this method. In conclusion, decision-makers in the energy sector can make more informed and reliable choices by adopting the proposed approach, ultimately contributing to the sustainable development of the global energy system.

In recent years, in response to China’s high housing and land prices, some local governments have tried to cap the housing price and change land auction rules to contain housing prices. However, large-scale land auction failure is incurred, which poses threats to social financing and sustainability of urban land resources. This paper proposes a two-stage auction mechanism aiming at controlling land auction failure and stabilizing land prices. Based on the first-price sealed auction model, this paper depicts the principle of the current mechanism and analyzes the reason for land auction failure under the housing price cap, and the threshold condition of auction failure is deduced. Then, the equilibrium bidding strategy of developers in the improved mechanism is solved. On this basis, numerical results show that the improved mechanism can control land auction failure and ensure a reasonable land price level at the same time, and the corresponding mechanism design suggestions are given.

Engineering management (EM) is an interdisciplinary field that aims to plan, organize, guide, and control the implementation of engineering projects to achieve project objectives. It encompasses aspects such as project management, cost control, resource allocation, and risk management, with the goal of ensuring that engineering projects are completed on time, within budget, and to specifications. Engineering management requires coordination among stakeholders, optimization of resource utilization, problem-solving, and maximizing the likelihood of project success. Through scientific methods and tools, engineering management helps improve project efficiency, quality, and sustainability.This article focuses on EM, briefly describing the first volume of the 18th ICMSEM program. Firstly, it reviews the key research areas of EM: Digital Operation, Digital Strategy, Supply Chain Management. Next, it discusses the most prominent issues in the 18th ICMSEM program volume. Finally, future developments are analyzed using CiteSpace. Overall, ICMSEM continues to provide a valuable platform for academic interaction and exchange to ensure innovation in future Management Science and Engineering Management (MSEM).

Due to the rapid development of e-commerce platforms, many manufacturers have opened direct sales channels to sell their products directly to consumers (National Brand products). Manufacturers have resale and direct sales channels with retailers respectively. At the same time, retailers can expand their business by introducing their own branded products (Store Brand products) to expand their interests. This paper takes the supply chain formed by manufacturers and retailers as the object of study, and establishes a game model to explore the strategic interaction between retailers’ private label invasion and manufacturers’ selling different products in dual channels. The results of the study are as follows: on the one hand, the retailer’s intrusion cannot prevent the manufacturer from adopting a vertical product differentiation strategy; on the other hand, the manufacturer’s vertical differentiation strategy can prevent the retailer’s intrusion to a certain extent. Therefore, retailers may not be able to realise the optimal situation. Overall, the findings and managerial insights in this paper can help manufacturers with multi-channel, multi-products to optimise their product and channel strategies.

The need for air conditioning has increased by 72% globally as a result of global warming, consuming 20% of global electricity production. Electricity is produced at the expense of burning fossil fuel causing climate change and global warming. To reduce electric and energy consumption, integrated phase change material (PCM) in a vapour-compression air conditioning system is being used to overcome this problem. In the current study, a prototype model of an air-cooling system using water as PCM was assessed. The study was based on freezing water in an ice container while maintaining air supply in the room to human comfort zones between $$22\,^{\circ }$$ 22 ∘ C to $$ 27\,^{\circ }$$ 27 ∘ C and to look into the effect on supplying cool air passing over the ice, once the compressor is turned off. The total cooling load required for 2 rooms with a volume of 0.21 $$\textrm{m}^3$$ m 3 was found to be 16.89 kWh/day and ice melting time was measured as 5.73 h. The annual electricity savings from thermal backup with 1097.2 units/year was calculated in Pakistani Rupees as 33,278 (USD 119.89/ year). The results showed it utilized 6 h to completely freeze water in the ice container before thermal backup from ice was maintained for 2 h with the temperature kept at $$20.8\,^{\circ }$$ 20.8 ∘ C in the zones. The surface temperature of the ice container decreased from $$11\,^{\circ }$$ 11 ∘ C to $$2\,^{\circ }$$ 2 ∘ C during this period. Due to load shift operation, and economic and environmental benefits, this process can result in reducing the annual energy demand charges, simultaneously reducing the carbon footprint of buildings.

As the concept of ecological civilisation gradually permeates all aspects of life in China, the new driving force of China’s economic growth is becoming green and sustainable development. The concept of ESG has been gradually gaining awareness and attention in society. The Chinese government has also clearly pointed out that companies should pay more attention to responsible investment and continuously practice ESG management concepts to build a green China. This paper takes the impact of ESG on corporate investment efficiency as an entry point and explores the moderating role of the amount of news coverage in it. By extracting data from the CSMAR and the CNRDS and using Stata to extract and analyse the text of financial statements, this paper empirically analyses tens of thousands of corporate data from 6,464 listed companies in China during the period from 2013 to 2020, and finds that ESG positively affects corporate investment efficiency. Finally, the paper makes some suggestions, including that companies should strengthen ESG practice activities, the government should establish a sound system, and companies should emphasise the important role of external media in communicating corporate information.

In the face of changes brought about by the innovative behaviors of peers, adjusting one’s innovation rhythm to enhance enterprise performance has become a crucial challenge for enterprises. This study posits that if peers choose to disclose their patent applications in advance, the resulting knowledge spillover and information spillover may lead to changes in the innovation rhythm of enterprises. By using panel data from 140 sample companies in the computer, communication, and other electronic equipment manufacturing industry from 2008 to 2017, employing generalized linear regression analysis, this study reveals that peers’ early publication of patents enhances the irregularity in the innovation rhythm of enterprises. Moreover, companies with greater financial redundancy experience a lesser impact, while those with stronger technological capabilities are more significantly affected. Consequently, companies with excessively irregular or regular innovation rhythms can adjust their innovation pace by increasing financial redundancy or enhancing technological capabilities, thereby improving enterprise performance. This study expands the research on the dynamics of enterprise innovation and the theories of peer effects and spillover effects in the context of enterprise innovation.

Transitioning into a new phase of blending various mechanisms, does the incorporation of shareholders not owned by the state in governance facilitate the integration of these mechanisms and improve the investment efficacy of Chinese state-owned enterprises? The empirical findings of this study, which examines the involvement of non-state shareholders in governance of China’s A-share listed state-owned firms from 2008 to 2022, demonstrate that these shareholders have a considerable effect on improving the investment efficiency of state-owned enterprises and reducing overinvestment. The impact of non-state shareholders with superior governance is far more pronounced than those without such high-level governance. By examining the influence mechanism, it has been discovered that the dynamic capabilities of invention and change, coordination and integration, and learning and absorption partially mediate their relationship. An examination of the data reveals that, as the level of strategic radicalization of companies rises, the participation of non-state-owned shareholders in governance diminishes the beneficial effect on the investment effectiveness of state-run enterprises. These discoveries are of great importance for the apportionment of control rights and the formation of strategies by non-state-owned shareholders in China’s mixed reform.

Based on the Stimulus-Organism-Response model, this paper examines the influence of four variables in e-commerce live broadcasting: anchor credibility, para-social interaction, and information quality on consumers’ impulsive purchasing intention, as well as the mediating role of consumer trust. A total of 323 questionnaires were collected, and research shows that the anchor credibility, para-social interaction, and information quality have a positive impact on consumers’ impulse purchasing intention; The anchor credibility, para-social interaction, and information quality will significantly positively affect consumer trust; The influence of anchor credibility and para-social interaction on impulsive purchasing intention is mediated by consumer trust. In addition, consumer trust plays a complete mediating role between information quality and impulse purchase intention, between anchor credibility and impulse purchase intentions, and partially mediates between para-social interaction and impulse purchase intentions. These conclusions not only enrich the theoretical foundation of consumer behavior research in e-commerce live broadcasting but also help consumers correctly understand the formation mechanism of impulsive purchasing in live shopping and establish healthy purchasing concepts.

As a rapidly developing financing tool in the green finance sector, green bonds have gained increasing attention and favor. The ESG rating is a comprehensive assessment of a company’s performance in non-financial aspects such as environment, social, and governance. This study analyzes data from select industries among Chinese A-share listed companies between the first quarter of 2010 and the fourth quarter of 2022, using a multi-timepoint difference-in-differences approach to examine the effects of issuing green bonds on corporate ESG scores. The findings indicate that green bond issuance significantly enhances a company’s ESG performance. To confirm the reliability of these findings, the study applies methods like parallel trend analysis, placebo tests, and propensity score matching, confirming the robustness of the results. These outcomes provide compelling evidence supporting the issuance of green bonds as a means to improve corporate ESG ratings.

This study examines the relationship between executive compensation and labor investment efficiency from the standpoint of executive compensation perception, using sample data from A-share listed companies in Shanghai and Shenzhen from 2010 to 2021. The results show that executive compensation and executive-employee pay gap have a U-shaped relationship with labor overinvestment, and an inverted U-shaped relationship with labor underinvestment. Further analyses reveal that the education level of employees negatively moderates the U-shaped relationship between executive compensation and labor overinvestment, while financing constraints positively moderate the inverted U-shaped relationship between executive compensation and labor underinvestment. The heterogeneity tests indicate that the relationship between executive compensation and labor overinvestment is significant in labor- and capital-intensive companies, whereas the relationship between executive compensation and labor underinvestment is significant in technology-intensive companies. The 2015 “Pay Ceiling Order” test confirms the effect of capping executive compensation on raising labor investment efficiency. Accordingly, this paper puts forward suggestions for companies to design executive compensation rationally.

In emerging markets like China, government plays a vital role in corporate economic activities. In recent years, with equity issuance becoming increasingly difficult, debt financing accounts for a growing ratio in a company’s asset and becoming more and more important for firms. Given all these factors, the research, which focuses on the effect of political connections on debt financing, will be of practical significance. Therefore, this paper takes the data of a-share listed companies in China from 2012 to 2020 as an example to discuss the influence of political connections on debt financing in emerging markets based on a fixed effects model. The research indicates corporate political connections can significantly facilitate public debt financing and do not have much influence on corporate private debt financing. Further analysis finds that political connections can facilitate corporate public and private debt financing more significantly in lower marketization regions. This research can help shed light on further market-oriented reform and debt market development for emerging countries that are under economic transformation, provides some suggestions for corporate decision makers to issue public debt financing and private debt financing.

This study determined the profitability of commercial banks in Pakistan through Leverage ratio, liquidity and net profit margin, author have selected this topic to determine the listed commercial bank’s profitability in Pakistan and have collected 19 listed commercial bank’s data from 2015–2021 from financial websites of banks, State bank of Pakistan and Pakistan Stock Exchange. Independent variables of this research were leverage ratio, liquidity and net profit margin and the dependent variable of this research is 6 years’ data have been collected of these said variables. E-Views was applied to analyze the data. Output suggested that there is a positive association of leverage ratio, liquidity and net profit margin with return on equity. This study shows observational prove almost the bond among liquidity and productivity of recorded ordinary banks of Pakistan Stock Exchange over the period of 2015 to 2021. In our study, individual bank characteristics (inside variables as it were) are considered as determinants of bank productivity in Pakistan. It is proposed that future research must tend to a longer period of time with having a broader determination of capital structure and profitability measures can reveal a few modern issues. This study can be amplified by including more banks or by conducting a think about on worldwide level with consideration of all banks around the world.

In the backdrop of escalating global issues such as climate change, social inequality, and governance risks, environmental, social, and governance (ESG) factors have garnered immense attention worldwide. The ESG rating, a crucial metric that assesses a company’s sustainability performance, holds significant importance for investors, managers, and regulatory authorities. Drawing upon comprehensive data from Chinese listed companies between 2015 and 2022, this article delves deeper into the intricate relationship between ESG rating differences and corporate value. Our findings reveal that an increase in ESG rating disparities can lead to a decline in corporate value. This is primarily attributed to investors demanding higher returns to compensate for the potential risks associated with lower ESG ratings, ultimately resulting in increased financing costs for the companies. This research not only enhances investors’ understanding of the impact of ESG ratings on corporate value but also provides managers with practical guidance on how to improve their ESG management practices. Additionally, it offers regulators valuable insights on leveraging ESG rating information for effective risk monitoring and regulation, thereby promoting sustainable business practices and contributing to a more resilient and sustainable future.

This paper explores the barriers facing Knowledge Management (KM) practices in the South African construction sector, with particular focus on the extension of KM beyond the boundaries of an organisation. Despite the sector’s recognition as a key driver for socio-economic sustainability, problems have arisen in extending KM practices beyond organisational boundaries. Using an online questionnaire survey distributed among South African construction professionals, this research identifies barriers such as lack of KM training and managerial support, insufficient time allocated for KM activities, and the complexities of the construction sector, a lack of training, inadequate time for KM activities, resistance to knowledge sharing and the complexity of a multi-organisational and highly diverse construction sector. Contrary to expectations, aspects such as language diversity and job security concerns did not pose significant challenges. The study also reveals a positive attitude towards KM and a willingness to extend KM strategies. Recommendations include investing in KM training, fostering long-term partnerships for knowledge sharing, and ensuring the continuity of project teams. Potential areas for future research are not limited to exploring KM strategies utilised by South African organisations and examining the challenges small and medium enterprises face.

Green credit policy allocates funds through the financial market and continuously guides enterprises to focus on green environmental responsibility. This study examined the effect of green credit policies on company commitments to employ green management strategies. Using Shanghai and Shenzhen A-share listed company-level data from 2009 to 2015, it was found that green credit policies had a significant positive, causal effect on company green commitment. Further, we found that the green policy effect was more pronounced in non-SOEs, pilot low-carbon cities, and are with greater political pressures. This paper sheds new light on the effects of green credit policies on green company behaviours.

The sharing economy is growing rapidly this year. Second-hand trading, as a way of sharing economy, has made a great contribution to reducing carbon emissions. However, some studies have found that as resale has become convenient, it has stimulated materialism to a certain extent, making consumers indulge in consumption. This is contrary to the original intention of the sharing economy. Therefore, it is necessary to explore the influencing factors of consumers’ use of second-hand platforms to better utilize the social value of second-hand platforms. Based on survey data from 273 questionnaires, this paper conducts an empirical study using a structural equation model to explore the impact of the four dimensions of consumer willingness to use: on the one hand, the Platform Social Responsibility Identity of users’ platform favorably affected users’ willingness to use second-hand platforms. At the same time, Materialistic Values also have a beneficial impact on users’ attitude towards the Xianyu platform, making it also display a more positive propensity to utilize it.

With the increasingly prominent ecological environment and resource problems in recent years, sustainable development has become a global topic. As the main and direct producer of these issues, enterprises need to implement green innovation. In the past, scholars have explored the influencing factors of corporate green innovation from different perspectives. This paper will start from the perspective of the informal system of traditional Chinese Confucian management thought, and study the role of key ideas such as “benevolence”, “righteousness” and “harmony between nature and man” in corporate green innovation in China. Based on the sample data of Shanghai and Shenzhen A-share listed companies from 2010 to 2022, the empirical findings show that Confucian management has a positive promoting effect on corporate green innovation. By introducing moderating variables, it is found that regional cultural diversity can promote the influence of Confucian management on corporate green innovation, while regional social trust inhibits it. Heterogeneity analysis shows that enterprises in non-heavy polluting industries are more influenced by Confucian management in green innovation. This research not only provides the necessary theoretical basis for the practical application of Chinese traditional culture, but also provides guidance for the industry to promote the corporate green innovation.

The relationship between project management maturity and success has gained significant attention recently. This paper investigates how project management maturity influences project success, focusing on Zambia Electricity Generating, Transmission and Distribution Company (ZESCO), a prominent Zambian company. Utilizing the Project Management Maturity Model (ProMMM) as a framework, this study examines the correlation between maturity levels in project management and the success of projects in terms of cost performance, schedule performance, quality, and customer/stakeholder satisfaction. The study adopted a quantitative research design, employing a structured questionnaire distributed among engineering personnel involved in 52 projects at ZESCO. The findings reveal that while ZESCO projects were of satisfactory quality and customer satisfaction performance, they underperformed in cost and schedule management. Surprisingly, no direct correlation was found between project management maturity and overall project success, suggesting a nuanced relationship that warrants further exploration.

A single indicator does not show the company’s performance in a timely, comprehensive, objective and fair manner. This paper intends to establish a more complete and fair comprehensive index of company performance by combining two objective analysis methods: factor analysis and entropy weighting. Meanwhile, the phenomenon of equity pledges is becoming increasingly common. This paper uses a comprehensive index and selects A-share listed companies in mainland China as the research sample to explore the relationship between equity pledges by controlling shareholders of listed companies and changes in corporate performance. The results show that compared with the enterprises without controlling shareholder’s equity pledges, the operating performance of the listed companies with controlling shareholder’s equity pledges is significantly worse in the following three years, and the performance loss degree increases with the rise of the proportion of equity pledges. The paper’s conclusion verifies the usability of the comprehensive index and has essential practical significance with the mushrooming equity pledge of controlling shareholders. It also provides a theoretical basis for enhancing the supervision and governance level of controlling shareholders and the regulatory authorities to issue relevant regulations to control the pledge of equity in the capital market.

In the management of sales processes in large manufacturing enterprises, it is crucial to have real-time visibility into the overall sales status as it directly impacts the marketing strategy. Generally, exceeding sales targets indicates a positive trend, prompting enterprises to increase market investments and expand their workforce. Conversely, falling behind in sales volume serves as a negative indicator, leading enterprises to focus on cost control measures and freeze hiring activities. Project-oriented manufacturing enterprises usually start to produce equipment after the project is won, and the sales volume depend on the volume of the winning project. Consequently, the sales status is difficult to predict due to great fluctuation. One way to solve this problem is to use a digital sales process management model to integrate the internal data of the enterprise, and manage the whole process of each project tracked by each sale from registration to order. Based on the sales funnel model, this paper proposes a sales process management model and a suitable application for project–oriented large manufacturing enterprises by an enhancement of the accurate management of sales process. Practical application results demonstrate that this approach effectively enhances sales forecasting precision and provides valuable insights for strategic decision–making within organizations.

In recent years, promoting the rapid development of new energy vehicles has become a “carriage” to alleviate energy pressure, promote environmental protection, promote the transformation and upgrading of the automotive industry, and tap new economic growth credits. In 2017, China launched the “double credit policy”, aiming to promote the transformation of fuel vehicle companies to new energy vehicle companies and promote the vigorous development of the new energy vehicle industry. In the future, with the continuous tightening of the double credit policy, the pressure on credit compliance faced by traditional fuel car companies will be increasing, and how to choose the most favorable compliance strategy and reduce the compliance cost of the double credit policy is a problem that every traditional car dealer needs to consider and solve. The main objective of this study is to explore the behavior of the credits market, analyze the impact on new energy vehicle prices, production, and credit prices on the decision-making of new energy vehicle enterprises under the equilibrium results, and provide reference for the government to formulate policies.

The automobile retail industry in China has been affected by COVID-19 with online sales of automobiles experiencing an increase during the pandemic. The empirical problem for auto retailers is the struggle to continue business as usual including confirming the best auto retail channel in the post-pandemic era. The theoretical problem that underpins this paper is the disconnect between extant literature suggesting consumers flocking back to offline dealerships and the empirical facts that online auto retail is constructing to experience growth. To address this problem, this paper tackles the main research question of “Can online auto retail become the ‘new normal’ in a post-pandemic era?” Through the theoretical lens of the multi-level perspective (MLP) framework of Geels. Online interviews using semi-structured questions were carried out with 15 participants, with direct content analysis being used as the analytical method to generate findings. The results indicate few signs of transitions from offline dealerships to online auto retail in the near foreseeable post pandemic future. Abundance of experiential information and transaction costs are also found to be important factors affecting automotive consumers’ choice of purchasing channels. Finally, limitations and suggestions for future studies are also stated.

Controlling the tunneling behavior of major shareholders is the key to the healthy development of financial markets. This paper takes the mixed ownership reform of SOEs in China as the background, examines whether non-state shareholders reduce the tunneling behavior of SOEs. This paper found that, first, the shareholding of non-state shareholders can significantly reduce the capital occupation, but there is no significant relationship with related transactions. Second, the appointment of directors by non-state shareholders can significantly reduce related transactions and the capital occupation of large shareholders. These results suggest that non-state shareholders can indeed reduce the tunneling of SOEs and that appointed directors have a more active role. In addition, strengthening internal controls is a possible governance mechanism.

With the decline of profits in the real economy, non-financial enterprises continue to obtain excess returns by allocating financial assets, crowding out the real economy. As an important part of public economy, there exist many state-owned enterprises allocating financial assets. Although some existed studies examined non-state-owned shareholders’ impact on the financialization of state-owned enterprises, no consensus has been reached. This paper takes A-share listed SOEs from 2007 to 2022 as the research object and uses OLS regression. We investigate the influence of non-state-owned major shareholders on the financialization of state-owned enterprises deeply. The results show that non-state-owned shareholders will significantly inhibit the financialization of SOEs. After the robustness test, the conclusion is still valid. In the further analysis, we find that non-state-owned shareholders mainly inhibit the long-term financial assets that play the “crowding effect”. Non-state-owned major shareholders have a significant inhibitory effect in the regions with a higher degree of marketization. We innovatively discuss the influence of non-state-owned major shareholders on the over-financialization of SOEs, and then we find that major non-state-owned shareholders and shareholders appointing directors can exert an inhibitory effect.

As a form of corporate governance structure, the board system defines the allocation and exercise of internal power within a company, making it an extremely important system. Directors make decisions in the name of the board of directors and are responsible for the long-term operation of the company. The set of connections established between the directors of the board of directors of a company by serving on a board is called the director network. The degree of director network centrality represents the relative position of individual directors and the board of directors in the whole network, and the higher the degree of director network centrality indicates a high degree of direct connection between enterprises. Based on the social network analysis method, this paper examines the influence of director network centrality on listed companies’ participation in Outward Foreign Direct Investment (OFDI). The empirical results show that the improvement of directors’ network centrality has a significant promoting effect on enterprises’ participation in OFDI. Directors’ network centrality may promote enterprises’ participation in OFDI by reducing the degree of financing constraints. The theoretical analysis and empirical findings of this paper not only expand the relevant research on enterprises’ access to resources through the informal system of director relationship network, but also enrich the literature on the influencing factors of OFDI in Chinese enterprises.

As an innovative technological advancement, virtual live streaming has emerged as a prevalent trend across various industries, featuring significant market potential. Upon reviewing existing research about the constituent elements, influential factors, and marketing efficacy of virtual live streaming, it is notable that only a limited number of studies have addressed the impact of scene design within virtual live streaming environments on consumer evaluations and purchase intentions. Based on the S-O-R framework and color psychology theory, we propose a conceptual framework of the effect of the interaction between background color (blue vs. non-blue) and product attributes (tech vs. non-tech) on users’ continuance use intention. Specifically, the matching of blue color and technology products can enhance the sense of presence and continuance use intention. Furthermore, we identify the continuous mediating effects of presence and psychological distance. The results of our studies contribute to current research and the future direction of virtual live streaming, offering practical implications for enhancing consumers’ participation and creating immersive visual experiences through appropriate scene design.

In spite of the widespread adoption of e-procurement systems by organizations, there is a tenacious issue of unsatisfactory performance outcomes resulting from their implementation. This can largely be accredited to the fact that many organizations struggle to translate the initial decision to adopt e-procurement at the organizational level into individual-level acceptance among their employees. The aim of this paper is to investigate the key factors that affect employees’ acceptance of e-procurement systems, using the technology acceptance model (TAM) as a framework. In this study, the authors apply and expand upon the TAM to explore the factors affecting the acceptance of e-procurement by individual employees.The authors primarily emphasis on the potential role of quality dimensions as perceived by the users of e-procurement systems, as precursors to the cognitive aspects of the TAM, specifically perceived usefulness and perceived ease of use. The structural equation model is employed, utilizing survey data collected from 200 e-procurement managers across various companies in Pakistan. The results confirm the central relationships outlined in the TAM within the context of e-procurement. When extending the TAM model to investigate its precursors, the authors discover that the quality dimensions of e-procurement, including processing, usability, and professionalism, have an impact on the levels of acceptance among individual employees. Notably, system-level dimensions such as processing and usability appear to have a more significant influence than support-related dimensions like professionalism in shaping these cognitive mechanisms.These findings suggest that the necessity for e-procurement training and ongoing support may be reduced through effective initial design that shields aspects like system navigation and usability, as well as by ensuring that e-procurement systems facilitate efficient information and product flows between buyers and suppliers.

With the rapid development of China’s civil aviation industry, major airlines have imposed more tightened KPI assessment for the air service of flight attendants to enhancing their market competitiveness. Together with the increasingly stringent assessment pressure and the uncertainty from the external environment, job burnout is more and more common among flight attendants, which has attracted the attention of the aviation industry. This study is designed with qualitative study with application of grounded theory through in-depth interviews with 21 crew of SC airlines to obtain data. With Nvivo software for coding analysis, the study constructs a causes and development model of flight attendant burnout and puts forward countermeasures to combine with career management theory. This study finds that the causes of flight attendant’s burnout are closely related to their career stages and the main causes of crew’s burnout include both organizational factors and individual factors. It proposes managerial measures with the aspects of talent selection, training and development, and career development. The study could rich the practical cases on airline employee development management.

Rural Commercial Bank is one of the forefront positions of China’s national rural revitalization construction. Due to the internal governance problems such as the inappropriate structure of equity, its risk situation is deteriorating. In this regard, this paper uses the data of China Rural Commercial Bank from 2013 to 2022 to empirically test the impact of equity structure on the risk of rural commercial bank, as well as the intermediary role of agricultural loans in it. The results show that: first, the effect of state-owned shareholding on risks will be seriously affected by agriculture-related loans, leading to its insignificant direct impact. That is to say, the scale of agriculture-related loans will cover up the impact of state-owned shareholdings on the risks of banks. Second, the shareholding of individuals will increase the risk by increasing the scale of agriculture-related loans, and agriculture-related loans are the main intermediary variable. Finally, according to the empirical results, countermeasures are put forward from aspects like equity management, credit behavior and risk control.

Under the Belt and Road Initiative, Chinese commercial banks have actively responded to the national policy to set up branches in countries along the route, but the risks exposed by this business process need to be emphasized. Based on the financial data of the four major Chinese commercial banks, namely Bank of China, Agriculture Bank of China, Industrial and Commercial Bank of China and China Construction Bank from 2013 to 2021, this paper empirically examines the impact of geographic diversification on bank risk and the moderating effect of institutional quality. The empirical results show that: geographic diversification has a negative effect on the bank’s risk, i.e., an increase in the level of geographic diversification reduces the risk of the headquarters of Chinese commercial banks, while the institutional quality of host country strengthens this negative effect; dividing the sample data based on whether or not the branches are listed, it shows that only geographic diversification of unlisted branches reduces the risks at the bank’s headquarters; differentiating the geographic distance of branches confirms that setting up branches in areas with higher-than-average geographic distance has a significant risk diversification effect.

Ingratiation is one of the hot topics in enterprise human resource management research. Over these years, researchers in this field have called for work examining how the relationship between leaders and employees impacts employees’ upward ingratiation. To delve into the importance of relationalism in the leader-employee relationship, particularly in Chinese culture, we focused on the key predictive role of leader identification. Based on relational identification theory, a dual-mediator model with leader-follower value congruence and subordinate moqi was constructed to investigate the internal mechanism. Data was collected from 527 Chinese employees across various industries through questionnaires and processed through Amos and Process macro. The results showed that both leader-follower value congruence and subordinate moqi positively mediate the positive relationship between leader identification and upward ingratiation. The study enriches our knowledge of the antecedents of upward ingratiation in the Chinese context and provides theoretical guidance for leaders to understand employees’ upward ingratiation.

Cadre education is instrumental in strengthening the construction of cadre teams and in elevating their comprehensive qualities and professional competencies. This article utilizes a corpus of 1,468 research papers from 1992 to 2023, sourced from the CNKI database, and employs Citespace software to conduct a visual analysis of the research status and trends in China’s cadre education. The study delineates the research into three stages: a stable phase, a leapfrogging phase, and a developmental phase, uncovering a notable paucity of collaboration and exchange among scholars and institutions. The research is predominantly published in journals within the fields of politics, education, and management, revealing a scarcity of specialized journals dedicated to cadre education. The literature mainly revolves around themes such as cadre education, continuing education, and the market economy, closely tracking the central concerns of national policy. Future research on cadre education may achieve significant breakthroughs by focusing on the assessment of educational effects, comparative studies of educational practices, and research on cadre education for specific groups.

With the increasing severity of environmental problems, more and more attention has been paid to the environmental information disclosed by enterprises. In the context of “carbon peak” and “carbon neutrality”, in order to explore the impact of corporate environmental information disclosure on the level of green innovation, this paper constructs a two-way fixed effect model of China’s A-share listed companies from 2008 to 2022, and comprehensively evaluates the level of green innovation of enterprises from the three dimensions of green innovation quantity, green innovation quality and green innovation efficiency. It also explores the influencing mechanism from the perspective of media attention and debt financing cost. The results show that corporate environmental information disclosure can improve the level of corporate green innovation, while media attention and debt financing cost play an intermediary role. These findings provide important reference for enterprises’ green transformation and sustainable development.

Petroleum and natural gas are traditional fossil energy sources; however, low-carbon transformation is viewed as the only path for sustainable development, and there is an industry consensus on the need to reduce carbon emissions through technological innovation and management. This paper employs CiteSpace to construct a knowledge graph of 229 papers from the WOS core collection spanning from 2004 to 2023 and summarizes three important research topics in this field through the analysis of the graph, specific information, and literature review: (1) cleaner and more abundant energy sources, such as natural gas and unconventional natural gas; (2) carbon dioxide treatment and utilization technology exemplified by CCUS; (3) energy conservation and emission reduction in oil and gas exploitation. Based on the highly cited literature and other relevant sources, the paper discusses the aforementioned topics. In future research and development, the digital transformation of oil and gas exploitation and the technology coupling it with new energy sources have broad prospects.

With the popularization and application of internet and the deepening development of economic globalization, the cross-border E-commerce industry has developed rapidly, becoming a new engine for world economic growth. Cross border E-commerce not only reduces the cost of international trade transactions, but also shortens the geographical and cultural distance between countries. This article takes “Silk Road E-commerce” as the background, analyzes the current situation and problems of cross-border E-commerce between China and Germany, and proposes countermeasures and suggestions for the development of cross-border E-commerce between China and Germany. In the context of the “Silk Road E-commerce”, especially in the face of the global public event of the COVID-19, we hope that the two countries can explore some new cross-border E-commerce cooperation models and paths to break through the current difficulties, which will certainly bring important reference value and practical significance to the good development prospects of economic and trade cooperation between China and Germany.

This research investigates the nexus between a country’s international competitiveness, innovation environment, productivity and infrastructure development, with a focus on the Republic of Moldova in comparison to Central European countries. The study emphasizes the pivotal role of competitiveness in enhancing wealth and well-being through policies that boost export-oriented strategies. While acknowledging the significance of innovation in driving competitiveness, findings reveal that Moldova lags behind benchmark countries in innovation indices. The empirical inquiry further explores Moldova’s efforts to bolster competitiveness by investing in critical infrastructure, particularly in transportation and telecommunications. Utilizing a comprehensive methodology blending quantitative and qualitative approaches, the research underscores Moldova’s modest progress in international competitiveness. Preliminary results highlight governmental initiatives to address challenges hindering productivity, competitive prowess, and crisis resilience. Overall, the study provides insights into the interplay between innovation, infrastructure, and competitiveness, offering a nuanced understanding of Moldova’s positioning in the global market.

Since China’s manufacturing sub-industries are diverse and have different advantages, the way to improve industrial advantage in the global value chain is specific. It is crucial to identify the determinants of different kinds of China’s manufacturing industries in the new-normal state. Based on data from forty-two countries, this paper examined the influencing factors of four different advantage types of China’s manufacturing with outward foreign direct investment (OFDI). By calculating the advantage index (ADI), eighteen manufacturing sub-industries of China were classified into four types, i.e., advantageous, disadvantageous, parallel advantageous, and decreased advantageous. And the empirical studies showed that the influencing factors of industrial advantage (IA) are varied for the four advantage types. For those that were labelled advantageous, a focus on each production factor would assist in improving Chinese manufacturing competitiveness, for those labelled disadvantageous and parallel advantageous, expanding local industrial scales and improving creativity abilities were identified as being the most effective method for increasing productivity and global industrial value chain positions, and for those labelled as decreased advantageous, investing in low-end factors in the host country would be the best way to expand the market.

Flood can cause extensive damage and fatalities, and it can also inadvertently lead to the spread of disease, contamination of drinking water and other problems. Individuals and households’ flood adaptation behavior can prevent or reduce the negative consequences of floods, including protection of individuals, others, and the environment. Questionnaire methods provide an important approach to reveal information about the public’s knowledge, attitudes, perceptions, experiences, and preparedness levels during floods, which can facilitate researchers to target scientific adaptive measures to reduce economic and life losses. There is a dearth of review literature that provides a review of questionnaire features, implementation strategies, and data analysis approaches. This includes the questionnaire’s accessibility, sample size, analytical model, analysis technique, and software selection. In this paper, we review 29 literatures on the study of flood adaptation behavior, and emphasize the details that researchers need to pay attention to when adopting questionnaire research, to provide scholars who use questionnaire research to study flood adaptation behavior with some guidance.

This study examines the evolution and factors influencing the joint development of green, low-carbon industries and cities in the Chengdu-Chongqing region. Amid global environmental challenges, this western China economic hub’s green industry growth is crucial for sustainable regional progress. Using a coupling coordination degree model, the paper analyzes the period from 2011 to 2019, revealing improving coordination among cities, with Chengdu and Chongqing’s influence growing. The industry-urban coupling is high and trending upward, suggesting better alignment of industrial and urban planning. While industry-economy coordination is somewhat lacking, it’s improving, with Chengdu notably advancing in industrial and economic restructuring. The study also notes enhanced industry-population-resource and industry-innovation-environment coupling, highlighting the benefits of innovation and environmental efforts. It recommends future research focus on technological innovation, enterprise transformation, and fostering regional collaboration for resource sharing and leveraging strengths to advance green industry clusters and high-quality economic growth.

This paper examines the impact of Project Portfolio Management (PPM) and Construction Management (CM) practices on Urban Infrastructure Projects (UIPs) performance. Through a comprehensive literature review of 108 journal articles, 23 books, 18 conference papers and 3 technical reports, the paper provides insights on the complexities and challenges faced by UIPs in South Africa, emphasizing the importance of effective leadership, Stakeholder Engagement(SE), and project management practices for successful project implementation. Despite advanced project management methods, urban infrastructure projects often suffer poor performance and execution which bring forth the research gap. Theoretical underpinnings from project management, PPM, CM, and SE theories are integrated to offer a holistic understanding of UIPs performance. A conceptual model is proposed to explore the indirect influence of UIPs characteristics on project performance through projectization, stakeholder involvement, success factors, PPM, CM practices, and key performance indicators. Further empirical research are recommended to fill existing gaps in knowledge regarding the influence of project portfolio and construction management practices on the success of South African UIPs and to provide a deeper understanding of key constructs impacting the performance of UIPs in South Africa.

The development of inclusive finance and the enhancement of digital capabilities have gradually become hot topics in the field of financial sustainability, attracting widespread attention from academia and industry. However, there are significant differences in the direction and intensity of the relationship between the two in existing research, and it is not yet clear. In response to the above issues, this study conducted a meta-analysis of 10123 empirical literature from 2005 to 2023, aiming to explore the role of inclusive finance in sustainable financial development, and further discuss the regulatory effects of traditional technology and digital technology on financial stability, financial efficiency, and inclusive growth. The research concludes that: (1) the development of inclusive finance can effectively enhance financial stability; Improve financial efficiency; Promote inclusive growth. (2) Meanwhile, digital technology can further enhance the promoting effect of inclusive finance on financial stability and efficiency. (3) However, compared to traditional inclusive finance, digital inclusive finance has not effectively improved financial inclusive growth. The research findings provide guidance for the application of digital technology in this field and provide a theoretical basis for sustainable financial development.

Applying the Off-Site Manufacturing (OSM), in many ways, can increase productivity, efficiency of performance, and value creation in the construction industry. Unfortunately, barriers to applying OSM have lowered the desire of manufacturers to use it. However, there is little information in both quantitative and qualitative evaluations on enablers and barriers to OSM implementation compared with existing traditional techniques. This study aims to identify and classify the enablers and barriers to applying OSM through in-depth literature review technique. For that, the Meta-Synthesis approach is used to quantitatively analyze existing information on enablers and barriers to OSM application. This study helps to resolve many problems of the construction industry through identifying the OSM enablers and barriers. Classification of the enablers and barriers presents a more realistic approach in enhancing the OSM implementation. In addition, finding these barriers provides a better view of time and cost estimations. Simultaneous identification of enablers and barriers to OSM application provides an appropriate context for better understanding of OSM concept and its proper implementation by the construction industry business owners. It also provides a better foundation for using potential enablers to face existing barriers to its application.

In recent years, with the development of digital technology, the construction industry is facing great changes, especially with the application of BIM (Building information modeling) technology in the construction industry, which has changed the traditional construction supply chain. The application of digital technology has realized the information coordination among all links of the construction supply chain, and improved the efficiency and value added of the construction supply chain. At the same time, the application of digital technology has promoted the low-carbon transformation of the construction supply chain. Based on this, this paper studies the application status of building supply chain based on BIM technology, builds a conceptual model of low-carbon transformation development of building supply chain based on BIM technology, and combined with data and examples to verify the science and rationality of the established model. The transmission process and operation mechanism of the construction supply chain based on BIM technology are studied, and the ideas of low-carbon transformation development of the construction supply chain based on BIM technology are proposed, aiming to provide reference for the low-carbon transformation development of the construction industry supply chain.

In the contemporary world, ensuring food safety has emerged as a critical concern. The conventional approach to food production lacks an efficient system for tracing the origin of produce across the supply chain. Consequently, in the event of a foodborne outbreak, the process of navigating through production data becomes arduous, hindering the tracking of both the affected produce and the outbreak’s source. Nonetheless, the existing methodologies overlooked the need for verifiable food production data. The advent of blockchain-based solutions in recent times has effectively tackled this key challenge. So, we introduced a novel proposition: a secure blockchain-based framework designed to digitally capture food production information. The prime objective is to provide consumers and producers with easy accessibility, traceability and verification of this data. The proposed model created using Python programming language. Our study aimed to enhance the transparency in supply of food by using efficient and secure algorithms. We have achieved this by incorporating practical and convenient means of facilitating these processes. Moreover, an empirical evaluation of the proposed framework was also conducted to substantiate its effectiveness.

To deeply explore the relationship between advertising creativity and consumers’ purchase intention and its influence path, 279 valid questionnaires were collected, and structural equation modeling was used to analyze the collected data. Results show that: (1) advertising creativity is positively correlated with purchase intention; (2) advertising creativity is positively correlated with perceived entertainment and informativeness of advertisements and negatively correlated with perceived irritation of advertisements; (3) perceived entertainment and informativeness of advertisements are positively correlated with advertising value, but there is no negative correlation between perceived irritation of advertisements and advertising value; (4) advertising value is positively correlated with purchase intention.

To identify the effect of digital transformation on the supply chain resilience, we use the outbreak of COVID-19 as a quasi-natural experiment and applies the double-difference method to identify the influence of digital transformation on supply chain resilience. The results verify that digital transformation improves firms’ supply chain resilience. In addition, the heterogeneity analysis revealed that the effect of digital transformation on firms’ supply chain resilience is more significant in non-state-owned firms, non-high-tech industries, and firms located in non-resource-oriented cities. The above study expands the research framework of external macro-environmental shocks and micro-enterprise behaviors, and also provides some insights and helps in understanding the impact of the subsequent transformation.

Affected by the perishable nature of fresh commodities and the high uncertainty of its market demand, decision-makers often have irrational ordering behaviors such as being too conservative or too radical. Based on this, we considered that fresh e-commerce retailers may have waste aversion preference and stock-out aversion preference, and studied the optimal order quantity decision and preservation effort decision under different behavioral preferences. The results show that the optimal order quantity and profit of a fresh e-commerce retailers with waste aversion are always smaller than that of a rational one. When a fresh e-commerce retailer has stock-out aversion preference, the relationship between the optimal order quantity and the degree of stock-out aversion, as well as that between the optimal profit and the degree of stock-out aversion depend on the profit margin of the product. If the degree of stock-out aversion is high, the expected profit of a fresh e-commerce retailer with a waste aversion preference is higher than that of a rational one, that is, stock-out aversion brings a higher profit to the fresh e-commerce enterprise. In addition, Waste aversion and stock-out aversion always have negative impacts on the preservation effort investment.

With the rapid development of urbanization and the popularity of e-commerce, urban logistics and distribution are facing many challenges. As part of smart cities, drone delivery provides new possibilities for solving these problems. This paper studies the urban logistics drone delivery route planning, and applies the operational research method to the field of smart city distribution. Firstly, a multi-objective mixed integer linear programming model is proposed to maximize the lowest customer satisfaction and minimize the total cost. Then a genetic algorithm with matching mechanism is designed to solve the model. Further, the multi-objective mixed integer programming model of urban logistics drone delivery and the genetic algorithm with matching mechanism are applied to solve an urban logistics drone delivery numerical example. Finally, we show the results and findings of this study, and discuss their potential applications in the field of smart city distribution. Especially, to enrich the application of smart cities in operations research, we indicate the development direction of new technologies in the logistics industry.

Moldova is an agricultural country that mainly exports raw materials. However, to ensure sustainable economic growth, the country should produce and export goods with high-added value; it is required to increase its export potential. Therefore, the subject of the study is the export of products manufactured in Moldova and its competitiveness. The study aims to determine priority products based on calculating the competitiveness of goods. Moldova faces the task of promoting domestic goods to foreign markets. This problem has worsened due to the severance of economic relations with the countries of the Eurasian Economic Union and the redirection of commodity flows to the European market. Moldova signed an Association Agreement with the EU in 2014. Eight years later, the country received candidate status for EU membership, so this study tests the hypothesis about the positive effect of redirecting exports to the EU market on high-technology exports, as well as the hypothesis about the positive impact of research and development expenditure on ICT goods exports and high-technology exports. The European market is oversaturated. Therefore, when promoting the export of goods, it is necessary to consider that only competitive products can win the competition.

Large-scale natural disasters result in significant human casualties and economic losses. Effective disaster management strategies require the strategic pre-positioning of relief supplies before a disaster and the rapid distribution of these supplies to affected regions afterward. In this paper, we propose a novel stochastic programming model that integrates the pre-positioning and multi-period distribution of relief supplies in humanitarian logistics. The model takes into account uncertainties related to relief supply demand, potential damage to pre-positioned supplies at relief facilities, and vulnerabilities in the road infrastructure. To assess the practical utility of our model, we conduct a real-world case study based on the earthquakes in Ya’an, China. The results demonstrate the model’s effectiveness in aiding decision-makers to optimize both pre-positioning and distribution strategies for relief supplies.

This study discovered what the key factors influencing Chinese customer’s attitudes and further affecting their purchase intention toward hybrid electric vehicles (HEVs) are based on a brand equity model. This paper adopts quantitative approach and conducts a survey method online to collect the data about Chinese customer’s perception of HEVs. Based on multiple linear regression analysis and further hierarchical regression, the research goal was achieved. Perceived quality, monetary-related functional value, and performance-related functional value are identified as the key factors affecting customer attitudes. The strong linkage between their attitudes and intention to buy is found. In addition, we found age, as a moderating variable is significantly considered, especially in the influence of perceived quality over attitude, functional value (monetary) over attitude, and attitude over intention.

In addressing the challenges of climate change, the Chinese government has established a distinct objective to attain its carbon peak by 2030 and strive for carbon neutrality by 2060. This commitment reflects a concerted effort to progressively achieve a state of net-zero carbon dioxide ( $$CO_2$$ C O 2 ) emissions. China’s agriculture faces the significant task of ensuring food security and contributes to the country’s carbon neutrality goals. This study introduces an innovative model for assessing and prioritizing risks in fresh produce supply chain under carbon peaking and carbon neutrality goals in China, employing a hybrid approach combining the Fuzzy Failure Modes and Effects Analysis (FMEA) and Fuzzy VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje). Nine risk indicators related to carbon emissions are identified through literature review and expert opinion. In the Sichuan company case study, R4 energy consumption emerges as the most severe risk criteria in the supply chain, following closely are R6 product transportation and R1 agricultural practices. This framework provides a useful guide for companies and stakeholders in the fresh produce industry to enhance sustainability and reduce risks in their supply chains.

Floating offshore wind energy is expected to grow in the next years. The EU expects a great increase in the installed capacity of this incipient technology. Floating offshore wind farms can be located in deep water far from shore, reducing the visual impact and reaching a larger generation due to stronger winds. However, there are some challenges such as operation and maintenance (O&M). Maintenance’s implementation of these floating systems is different from fixed offshore ones, resulting in new approaches like “towed to shore”. Towing the turbines to shore or port must be done by adapted vessels according to maintenance actions. This work presents an assessment of a collection of scheduling maintenance policies for a floating wind farm assigning several vessels. A discrete state Markov chain is developed to model the deterioration process and to establish the different actions to take. Maintenance policies are based on time or based on the condition of turbines. Results show that, in general, Index policy keeps the farm in a lower state of deterioration, being the O&M cost of this policy similar to the cost incurred with the Naïve policy. Both, Periodic and Threshold policies reach the worst results in terms of O&M costs and deterioration.

The construction of hydrogen refueling stations is faced with multiple problems such as land approval and high investment. The main way to develop hydrogen refueling stations in the future is to use gas stations as the transitional construction of oil and hydrogen co-construction stations. The renovation and expansion of gas stations involve many factors, so this paper establishes a multi-objective optimization model, considering the three aspects of economy, environment and society: aiming at the minimum investment cost, considering the economic benefits of the whole system, ensuring long-term profits to ensure the effective development of the system; In order to achieve the“double carbon target", the total carbon emission must be strictly controlled, and the total carbon emission of the system must be minimized. Create the most job opportunities for the public. The data of gas station in Qingpu District of Shanghai was simulated and solved by genetic algorithm, which provided scientific and reasonable reference for local government decision-making and verified the effectiveness of the model.

Considering the customer utility in competitive environment, this paper develops a bi-level multi-objective location model for recycling facility location. The upper level decides on the smart bins location of follower enterprise to reduce the total cost and ensure coverage maximization, and the customers as the lower level decide on which kind of facility and which one to provide service based on the competition between the traditional and smart bins to maximize the customer utility. Concerning the complexity of the proposed model, this paper develops an improved NSGA-II to solve it. A special coding rule is employed. Uniform crossover and inversion mutation operator are used to improve the effectiveness of NSGA-II. Finally, based on new instances generated from the existed single objective MCLP benchmark data sets (22 instances), the experimental results indicated that the improved NSGA-II had competitiveness and a better performance in convergence than MOHSA, with the improved algorithm achieving the best average gaps of 0.88% and 3.87% and improving the best-known solutions in some instances. Besides five groups of simulation instances proved that the model proposed and algorithm improved could solve the facility location problem considering customer utility in competition environment in a reasonable time to get pareto solutions. The results of sensitivity analysis proved that the objective values were positively correlated with three important parameters, which suggested that reasonable scale and incentive mechanism could affect the system over the long-term.

As the diesel emergency power supply vehicle has the defects of high noise and large pollution, which makes it no longer applicable in residential areas, hospitals, important meeting places and other scenes need quiet power supply. Power grid companies use mobile energy storage system(MESS) with lithium battery as power supply to replace diesel emergency power supply vehicle in order to provide environmental and noise-free emergency power service. Due to the different levels of damage caused by power outages to different electricity consumers, power users are divided into four classes, each with a different priority for emergency power supply. To guarantee the emergency power supply of power users under a certain service reliability probability, a maximal expected coverage location model is used to determine the location of emergency power service stations and decide the allocation strategy of MESSs to each emergency power service station. An arithmetic example is used to verify the effectiveness of the method. The results show that the model is able to cover all demand nodes based on a reliability probability of 95%. This study provides an effective method for siting emergency service stations and MESS allocation strategy.

This study primarily focuses on the application of aviation emergency rescue in the context of frequent natural and accident disasters in China. Aviation emergency rescue, as a crucial component of the emergency rescue system, possesses characteristics such as wide rescue coverage, rapid response, and precise rescue objectives. It is considered the most effective approach to address natural and accident disasters by preventing the spread of disasters and reducing casualties and property losses. The objective of this study is to ensure the secure operation of multi-aircraft cooperation within complex aviation emergency rescue environments. This involves mitigating flight accidents, minimizing the risk of such accidents, ensuring the safety and precision of operational flights, and enhancing emergency rescue efficiency. The study encompasses three aspects: the application scenarios and requirements of multi-aircraft cooperation in aviation emergency rescue, the aircraft allocation and effectiveness evaluation for joint operations in various scenarios, and airspace route planning and control technology in complex disaster situations. This research employs the curve similarity method, Dubins path planning method, and Astar search algorithm to construct a route specification model and a multi-aircraft cooperation traffic control model. These models form the technical framework of the study.

As global environmental concerns grow, there has been an increased research focus on the development and utilization of distributed renewable energy systems. In this paper, a multi-objective optimization model is established to investigate the effectiveness of a distributed wind-photovoltaic-hydropower hybrid energy system, in which a pumped storage system is integrated to store the excess wind and photovoltaic power. Based on an uncertainty and multi-stage dynamic programming analysis, the optimization model aims to minimize output fluctuations and power curtailment and balance power supply and demand under the energy and grid constraints. It was found that the wind-PV-hydro-pumped system was able to play a balancing role on the power grid, and performed well on controlling power curtailment. The managerial suggestions combined with reality are given, which could be of significant assistance to policymakers and managers to make decisions.

The study introduces the creation and execution of an innovative emergency management system that leverages unmanned aerial vehicles (UAVs) and a terrestrial computer system. The objective of the project is to establish a comprehensive platform that delivers instant, crucial data to first responders in emergencies, such as a building fire. To accomplish this goal, the system utilizes a variety of sensors to collect information on air quality, the detection of hazardous chemicals, and imagery through standard and thermal imaging cameras mounted on the UAVs. This collected data is then stored in a database for subsequent analysis and the generation of alert notifications. Communication between the UAV and the ground-based system is facilitated through a WiFi network architecture, ensuring the immediate transfer and display of data. This system is designed to enhance the efficiency and capabilities of emergency services in handling crisis situations.

Timely and effective post-flood relief is crucial for mitigating the losses caused by disasters, relying heavily on a system capable of rapidly and safely supplying relief goods. The transportation of relief supplies is one of the important functions of non-governmental organizations (NGOs), as they have unique advantages in this area. However, the supply of relief materials is a complex system problem, and traditional supply chain evaluation methods cannot adequately measure the transportation of NGO relief supplies. Therefore, this paper establishes a system dynamics model of post-flood NGO relief supply transportation to investigate this issue. Using the 2021 Henan flood as a case study and introducing the concept of “deprivation level,” this paper simulates the NGO relief supply system. The study found that the coordination center’s decisions are more significantly affected by information delays, and the golden period for emergency supply provision by NGOs typically spans the first seven days after the disaster. Additionally, NGOs adopting an 8-hour dispatch frequency are better able to alleviate supply shortages. This study expands the research on system dynamics simulation in the field of humanitarian logistics and can provide recommendations and guidance for future NGO relief goods supply.