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Many individuals start a new firm each year, mainly intending to become independent or improve their financial situation. For most of them, the first years of operations mean a substantial investment of time, effort and money with highly insecure outcomes. This study aims to explore how entrepreneurs running new firms perform financially compared with the established ones and how this situation influences their well-being.

A questionnaire survey was completed in 2021 and 2022 by a representative sample of N = 1136 solo self-employed and microentrepreneurs in the Czech Republic, with dependent self-employed excluded. This study used multiple regressions for data analysis.

Early-stage entrepreneurs are less satisfied with their financial situation, have lower disposable income and report more significant financial problems than their established counterparts. The situation is even worse for the subsample of startups. However, this study also finds they do not have lower well-being than established entrepreneurs. While a worse financial situation is generally negatively related to well-being, being a startup founder moderates this link. Startup founders can maintain a good level of well-being even in financial struggles.

The results suggest that policies should focus on reducing the costs related to start-up activities. Further, policy support should not be restricted to new technological firms. Startups from all fields should be eligible to receive support, provided that they meet the milestones of their development. For entrepreneurship education, this study‘s results support action-oriented approaches that help build entrepreneurs’ self-efficacy while making them aware of cognitive biases common in entrepreneurship. This study also underscores that effectuation or lean startup approaches help entrepreneurs develop their startups efficiently and not deprive themselves of resources because of their unjustified overconfidence.

This study contributes to a better understanding of the financial situation and well-being of founders of new firms and, specifically, startups. The personal financial situation of startup founders has been a largely underexplored issue. Compared with other entrepreneurs, this study finds that startup founders are, as individuals, in the worst financial situation. Their well-being remains, however, on a comparable level with that of other entrepreneurs.

Research and development (R&D) projects are often pursued through a project portfolio (PP). R&D PPs involve many stakeholders, and without proactive management, their interactions may lead to conflict risks. These conflict risks change dynamically with different stages of the PP life cycle, increasing the challenge of PP risk management. Existing conflict risk research mainly focuses on source identification but lacks risk assessment work. To better manage the stakeholder conflict risks (SCRs) of R&D PPs, this study employs the dynamic Bayesian network (DBN) to construct its dynamic assessment model.

This study constructs a DBN model to assess the SCRs in R&D PP. First, an indicator system of SCRs is constructed from the life cycle perspective. Then, the risk relationships within each R&D PPs life cycle stage are identified via interpretative structural modeling (ISM). The prior and conditional probabilities of risks are obtained by expert judgment and Monte Carlo simulation (MCS). Finally, crucial SCRs at each stage are identified utilizing propagation analysis, and the corresponding risk responses are proposed.

The results of the study identify the crucial risks at each stage. Also, for the crucial risks, this study suggests appropriate risk response strategies to help managers better perform risk response activities.

This study dynamically assesses the stakeholder conflict risks in R&D PPs from a life-cycle perspective, extending the stakeholder risk management research. Meanwhile, the crucial risks are identified at each stage accordingly, providing managerial insights for R&D PPs.

Prefabricated buildings (PBs) have proven to effectively mitigate carbon emissions in the construction industry. Existing studies have analyzed the environmental performance of PBs considering the shift in construction methods, ignoring the emissions abatement effects of the low-carbon practices adopted by participants in the prefabricated building supply chain (PBSC). Thus, it is challenging to exploit the environmental advantages of PBs. To further reveal the carbon reduction potential of PBs and assist participants in making low-carbon practice strategy decisions, this paper constructs a system dynamics (SD) model to explore the performance of PBSC in low-carbon practices.

This study adopts the SD approach to integrate the complex dynamic relationship between variables and explicitly considers the environmental and economic impacts of PBSC to explore the carbon emission reduction effects of low-carbon practices by enterprises under environmental policies from the supply chain perspective.

Results show that with the advance of prefabrication level, the carbon emissions from production and transportation processes increase, and the total carbon emissions of PBSC show an upward trend. Low-carbon practices of rational transportation route planning and carbon-reduction energy investment can effectively reduce carbon emissions with negative economic impacts on transportation enterprises. The application of sustainable materials in low-carbon practices is both economically and environmentally friendly. In addition, carbon tax does not always promote the implementation of low-carbon practices, and the improvement of enterprises' environmental awareness can further strengthen the effect of low-carbon practices.

This study dynamically assesses the carbon reduction effects of low-carbon practices in PBSC, informing the low-carbon decision-making of participants in building construction projects and guiding the government to formulate environmental policies.

This article aims to understand users' information needs in the metaverse communities and to analyze the similarities and differences between their information needs and those of users in Internet communities.

This study conducted semi-structured interviews with users in the metaverse communities to gather raw data. Grounded theory research methods were employed to code and analyze the collected interview data, resulting in the extraction of 40 initial concepts, 15 subcategories and 5 main categories. Based on Maslow’s hierarchy of needs theory, this paper constructs the hierarchical model of users' information needs in the metaverse communities. It compares the differences between users' information needs in the metaverse and Internet fields.

The user’s information needs in the metaverse communities are divided into two types: deficiency needs and growth needs. Deficiency needs have two levels. The first level is the demand for basic information resources. The second level is the users demand for information assistance. Growth needs have three levels. The first level is the need for information interactions. The second level is the need for community rules. The ownership information in the community rules can provide proof of user status, assets and so on. The third level is the need for users to contribute and share their own created information content.

This article presents the latest research data from in-depth interviews with users in the metaverse communities. It aims to help builders and managers of metaverse communities understand users' information needs and improve the design of virtual communities.

To extend the reuse method and rate of straw biomass, this paper investigated the effect of lignin synthetic phenolic resin (LPF) on the rheological properties of asphalt binder.

Four LPFs with 25%, 50%, 75% and 100% substitution rates were prepared by replacing phenol with lignin in synthetic resins and using it as a modifier to prepare a bio-asphalt binder. Temperature sweep tests were conducted to evaluate aging resistance and temperature sensitivity of the bio-asphalt binder. The rutting resistance of the bio-asphalt binder was evaluated by frequency sweeps and multiple stress creep recovery (MSCR) test. Linear amplitude sweep (LAS) tests were conducted to evaluate the fatigue resistance of the bio-asphalt binder. A master curve was constructed to further analyze the rheological properties of the bio-asphalt binder at different frequencies. The low-temperature cracking resistance of the binder was evaluated by G-R parameters, critical temperatures and ΔTc. Fourier transform infrared spectroscopy (FTIR) was performed to investigate the changes in the functional groups of the binder before and after aging.

The results indicated that adding LPF could improve the high-temperature rutting resistance, fatigue resistance, aging resistance of asphalt and the binders are less affected by temperature. Additionally, LPF slightly prohibited the low-temperature performance of the asphalt binder, which, however, was significantly lower than the base asphalt degradation during aging. Compared with base asphalt binders, the bio-asphalt binder showed no new absorption peaks generated after adding LPF, identifying that the improved asphalt binder performance by LPF was a mainly physical modification.

The main objective of this paper is to further improve the substitution rate (i.e. the mass substitution ratio of lignin to phenol) of lignin and broaden the application of biomass resins, thus realizing resource sustainability.

The purpose of this paper is to achieve the multi-objective optimization design of novel tubular switched reluctance motor (TSRM).

First, the structure and initial dimensions of TSRM are obtained based on design criteria and requirements. Second, the sensitivity analysis rules, process and results of TSRM are performed. Third, three optimization objectives are determined by the average electromagnetic force, smoothing coefficient and copper loss ratio. The analytic hierarchy process-entropy method-a technique for order preference by similarity to an ideal solution-grey relation analysis comprehensive evaluation algorithm is used to optimize TSRM. Finally, a prototype is manufactured, a hardware platform is built and static and dynamic experimental validations are carried out.

The sensitivity analysis reveals that parameters significantly impact the performance of TSRM. The results of multi-objective optimization show that the average electromagnetic force and smoothing coefficient after optimization are better than before, and the copper loss ratio reduces slightly. The experimental and simulated results of TSRM are consistent, which verifies the accuracy of TSRM.

In this paper, only three optimization objectives are selected in the multi-objective optimization process. To improve the performance of TSRM, the heating characteristics, such as iron loss, can be considered as the optimization objective for a more comprehensive analysis of TSRM performance.

A novel motor structure is designed, combining the advantages of the TSRM and the linear motor. The established sensitivity analysis rules are scientific and suitable for the effects of various parameters on motor performance. The proposed multi-objective optimization algorithm is a comprehensive evaluation algorithm. It considers subjective weight and objective weight and fully uses the original data and the relational degree between the optimization objectives.

The purpose of this study is threefold. The first is to conduct a comprehensive examination of the various board attributes to corporate social responsibility (CSR) reporting in the Chinese technology industry. The second is to investigate the impact of ownership and board attributes on CSR. The third is to examine the moderating effect of media reporting on the relationship between CSR and company financial performance.

All A-share listed Chinese companies during the years 2011–2019 with 1,573 firm-year observations have been investigated for this study. The data are analysed by CSR metrics in the form of environmental, social and governance (ESG) scores using an ordinary least squares regression analysis and fixed effect regression models.

The results of this longitudinal study reveal that; no matter whether the companies are state-own or non-state-own, there is a significant positive effect of board independence, monetary incentives, director’s age and board size on the CSR disclosure of the Chinese technology industry. Also, the results support the importance of CSR performance in promoting the corporate financial performance (CFP) of the technology sector. Specifically, media reporting has a positive impact on the CSR reporting of both state-own and non-state-own technological companies in China.

To the best of the authors’ knowledge, this is the first study based on the ESG metrics for analysing the CSR and firm performance relationship conducted in the unique setting of the state-own and non-state-own technological companies in China. The study is an attempt to fill the gap in the extant literature, which has a scarce number of studies focused on the influence of media reporting on the relationship between CSR performance and CFP. This paper not only updates the existing understanding of CSR performance by board attributes and company ownership but also explains the significance of media reporting in enhancing the CSR performance of the Chinese technology industry.

In order to analyze the level of independent controllability and its evolution of high-end equipment manufacturing industry from Jiangsu Province, this article introduces the dual-excitation control line method to construct a comprehensive evaluation model for independent controllability.

Through the collection of information of high-end equipment manufacturing industry's independent and controllable capabilities on different indicators, the three aspects of advancement, autonomy and controllability, an empirical evaluation of 10 enterprises in the high-end equipment cluster in Jiangsu Province was conducted in terms of advancement, autonomy and controllability.

It effectively reveals the area and evolution characteristics of the “reward” and “punishment” of different indicators of each representative enterprise and reflects the development status and different characteristics of each representative enterprise on the three indicators. The research results provide decision-making guidance for enterprises in the management and control of advanced manufacturing systems with independent and controllable capabilities.

Existing research focuses on the evaluation of enterprises' independent controllability only on a single angle or index. This paper maps the dynamic evaluation problem of multiple time-point data to the evaluation problem of single time-point multi-index data and investigates the fluctuation of the performance of the same enterprise under different indexes, so as to comprehensively evaluate the independent controllable level of high-end equipment manufacturing industry and analyze the reasons. Further, this paper first establishes an evaluation index system of independent controllable level of high-end equipment manufacturing industry and quantitatively measures the advanced, independent, controllable and other aspects of typical enterprises in this industry by constructing a double incentive control line evaluation model.

Health misinformation on social media threatens public health. A critical question that sheds light on the propagation of health misinformation across social media platforms revolves around identifying the specific types of social media users susceptible to this issue. This study provides an initial insight into this matter by examining the underlying psychological mechanism that renders users susceptible to health misinformation.

In this study, we developed an integrated model of susceptibility to health misinformation, drawing on the motivation-opportunity-ability theory and the elaboration likelihood model. We collected the data from a sample of 342 social media users in China. Furthermore, the fuzzy-set qualitative comparative analysis was adopted to examine the proposed model and uncover the causal recipes associated with susceptibility to health misinformation.

The results indicated that there are three configural types of users that are susceptible to health misinformation: the health-consciousness core-driven type, the popularity-driven core type and the dual-driven type characterized by both high health consciousness and information popularity. Among these, high health-consciousness and the reliance on information popularity-based pathways emerge as pivotal factors influencing susceptibility to health misinformation.

This study contributes to the social media literature by identifying various psychological traits that lead to social media users’ susceptibility to health misinformation. Additionally, the study provides comprehensive guidance on how to mitigate the spread of health misinformation.

Today's marketing is dominated by decision-making based on artificial intelligence and machine learning. This study focuses on one semi- and unsupervised machine learning technique, generative adversarial networks (GANs). GANs are a type of deep learning architecture capable of generating new data similar to the training data that were used to train it, and thus, it is designed to learn a generative model that can produce new samples. GANs have been used in multiple marketing areas, especially in creating images and video and providing customized consumer contents. Through providing a holistic picture of GANs, including its advantage, disadvantage, ethical considerations, and its current application, the study attempts to provide business some strategical orientations, including formulating strong marketing positioning, creating consumer lifetime values, and delivering desired marketing tactics in product, promotion, pricing, and distribution channel. Through using GANs, marketers will create unique experiences for consumers, build strategic focus, and gain competitive advantages. This study is an original endeavor in discussing GANs in marketing, offering fresh insights in this research topic.