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Improving the diversity of recommendation information has become one of the latest research hotspots to solve information cocoons. Aiming to achieve both high accuracy and diversity of recommender system, a hybrid method has been proposed in this paper. This study aims to discuss the aforementioned method.

This paper integrates latent Dirichlet allocation (LDA) model and locality-sensitive hashing (LSH) algorithm to design topic recommendation system. To measure the effectiveness of the method, this paper builds three-level categories of journal paper abstracts on the Web of Science platform as experimental data.

(1) The results illustrate that the diversity of recommended items has been significantly enhanced by leveraging hashing function to overcome information cocoons. (2) Integrating topic model and hashing algorithm, the diversity of recommender systems could be achieved without losing the accuracy of recommender systems in a certain degree of refined topic levels.

The hybrid recommendation algorithm developed in this paper can overcome the dilemma of high accuracy and low diversity. The method could ameliorate the recommendation in business and service industries to address the problems of information overload and information cocoons.

This study aims to explore how transformational leadership influences employees' creativity by considering the role of the environment and psychology. The study aims to provide insights into the impact of transformational leadership on team innovation climate, team reflexivity, psychological capital and employee creativity while also examining the moderating effect of environmental dynamism on these relationships.

This study employed a multi-source, multi-wave approach, utilizing data from 618 participants in 118 teams. It constructed a multilevel structural equation model and estimated the confidence intervals of the mediated and moderated effects using the Markov chain Monte Carlo method.

The results of the multilevel analyses indicated that transformational leadership positively influenced the team innovation climate, team reflexivity, psychological capital and employee creativity. Moreover, the study found that environmental dynamism positively moderates the relationships among transformational leadership, team reflexivity, psychological capital and employee creativity.

Drawing on social cognitive theory and the motivated information processing in groups model, this study offers new insights into the interplay between transformational leadership and creativity. It examines the moderating role of cross-level process linkages and environmental dynamism, thereby validating and extending relevant theories.

Based on resource-based theory and intellectual capital theory, this paper aims to investigate the impact of digital investment on enterprise value and the mediating role of intellectual capital. Additionally, it explores the heterogeneous impacts of digital investment on enterprise value and intellectual capital.

The study utilizes a sample of listed companies in Chinese A-shares from 2013 to 2020. The entropy-weighted method is applied to measure digital investment from two dimensions: scale and increment. Finally, the research hypotheses are tested through multiple regression analysis.

The empirical results demonstrate that digital investment significantly and positively impacts enterprise value. From the channel mechanism test, digital investment can enhance enterprise value by influencing intellectual capital through human, structural and relational capital. Of these, the mediating effect of human capital is the most significant. Moreover, the impacts of digital investment on enterprise value and intellectual capital are related to the industry sectors. In the agricultural sector, digital investment has adverse effects. In the industrial and service sectors, digital investment promotes intellectual capital and enterprise value. However, in the service sector, the impact on relational capital is not significant, and the mediating effect of relational capital does not hold.

This research has a limited potential for generalization due to the lack of standard measurement models for the exploration of digital investment.

The research findings are valuable for assessing the economic effects of digital investment comprehensively and providing essential information for policy formulation and strategy implementation.

This study represents the first attempt to evaluate the relationship between digital investment and enterprise value using the entropy-weighted method. In addition, this study investigates the mediating role of intellectual capital.

This study aims to improve the availability of regenerative braking for urban metro vehicles by introducing a sensorless operational temperature estimation method for the braking resistor (BR) onboard the vehicle, which overcomes the vulnerability of having conventional temperature sensor.

In this study, the energy model based sensorless estimation method is developed. By analyzing the structure and the convection dissipation process of the BR onboard the vehicle, the energy-based operational temperature model of the BR and its cooling domain is established. By adopting Newton's law of cooling and the law of conservation of energy, the energy and temperature dynamic of the BR can be stated. To minimize the use of all kinds of sensors (including both thermal and electrical), a novel regenerative braking power calculation method is proposed, which involves only the voltage of DC traction network and the duty cycle of the chopping circuit; both of them are available for the traction control unit (TCU) of the vehicle. By utilizing a real-time iterative calculation and updating the parameter of the energy model, the operational temperature of the BR can be obtained and monitored in a sensorless manner.

In this study, a sensorless estimation/monitoring method of the operational temperature of BR is proposed. The results show that it is possible to utilize the existing electrical sensors that is mandatory for the traction unit’s operation to estimate the operational temperature of BR, instead of adding dedicated thermal sensors. The results also validate the effectiveness of the proposal is acceptable for the engineering practical.

The proposal of this study provides novel concepts for the sensorless operational temperature monitoring of BR onboard rolling stocks. The proposed method only involves quasi-global electrical variable and the internal control signal within the TCU.

Enterprises generally change their organizational structures in an era of uncertainty for flexibility, and accordingly, employee entrepreneurship emerges as employees gain more power and responsibility during this process. This paper aims to explore how employee entrepreneurship impacts enterprises’ sustainable innovation capability. The authors consider the mediating effect of value cocreation and the moderating effect of role stress.

The authors adopted a questionnaire survey to test the hypothesis, and 356 questionnaires were collected from an online questionnaire platform.

The results show that employee entrepreneurship has a positive impact on sustainable innovation capability, value cocreation plays a partial mediating role in this relationship between employee entrepreneurship and value cocreation and role stress plays a negative moderating role in the relationship between employee entrepreneurship and value cocreation.

The study makes three main contributions to the literature concerning entrepreneurship and enterprise sustainable innovation capability. First, in relation to the entrepreneurship literature, the authors shift entrepreneurship research from entrepreneurs/leaders to employees in the digital transformation context and specify the connotation of employee entrepreneurship. This shift further enriches and broadens the research boundary of entrepreneurship (Bhide, 2000; Djankov et al., 2006). Second, we add the micro dynamic mechanism of sustainable innovation capability by focusing on the effect of employee entrepreneurship. Employee entrepreneurship positively contributes to enterprise sustainable innovation capability, which is partially mediated by value cocreation, and its impact on value cocreation is moderated by role stress due to the identity change of employees in the digital transformation context. The authors answer calls to clarify the micromechanisms of building enterprise competitive advantage (Terziovski and Sohal, 2020). The research confirms the relationship change between enterprises and consumers in value creation from separation to cooperation (Tu et al., 2020; Costa and Hafto, 2021). Additionally, the authors discuss the dynamic mechanism and factors of value cocreation at the employee level and further verify the positive effect of an active interaction among enterprises, consumers and other value creators (Matarazzo et al., 2021; Heinonen et al., 2013). This approach compensates for the deficiency of previous studies investigating the influence of value cocreation at the level of organization members.

The theoretical analysis and empirical conclusions of this study have important practical implications. First, employee entrepreneurship positively impacts enterprises’ sustainable innovation capabilities. Therefore, enterprises should stimulate their employees’ entrepreneurship to strengthen organizational resilience and adaptability, which are important for enterprises to survive in the changeable age. For example, enterprises can authorize their frontline employees with more resource allocation power and reduce hierarchical control; thus, their employees can address emergencies in a timely manner and catch fleeting market opportunities. Second, since value cocreation is a partial mechanism by which employee entrepreneurship contributes to an enterprise’s sustainable innovation capability, enterprises should help employees improve their capabilities and knowledge for value cocreation. For instance, enterprises should develop decision-making support toolkits, upscale training courses and efficient coordination tools to help employees achieve the necessary skills and knowledge. Only in this way can they qualify to perform an increasing number of autonomous tasks. Finally, employees’ role stress negatively moderates the relationship between employee entrepreneurship and value cocreation. This finding provides a reference for enterprises in position setting, role rule-making, role responsibility-planning, etc. Specifically, enterprises should build a feedback mechanism to manage employees’ role ambiguity, conflict and overload; thus, they can eliminate the potential negative effects on value cocreation and their sustainable innovation capability in a timely manner.

This study expands the boundary and connotation of entrepreneurship in an era of uncertainty, specifies the micromechanism of sustainable innovation capability and provides new insights for enterprises constructing their sustainable innovation capability.

The purpose of the current study is to analyze the influence that is caused by ethnicity and volunteer self-employment in entrepreneurship on the initial financing and business performance of Chinese enterprises. The increasing trend of entrepreneurship has raised certain ethnic challenges in entrepreneurship owing to globalization and now there are several minority groups that are running their households in China. So, the current study aims to assess whether the minority-operated and majority-operated firms have different access to initial financing and different business performance.

The data are collected from 25 Chinese enterprises about the current variables, and the relationships are tested. This study has used the ordinary least of square (OLS) regression model to examine the findings.

The purposive sampling is used in the current study because the purpose of the present research is to understand and study the role of ethnicity and self-employment in initial financing and business performance of Chinese enterprises and so the data was collected from related enterprises. This study has used the ordinary least of square (OLS) regression model to examine the findings.

The current findings have significant implications in theory and practice. This study will be a great addition to the literature because the self-employment has never been examined before in such models to assess the role of forceful or volunteer self-employment in entrepreneurship, and so, it will open new doors of research for future researchers.

The purpose of this investigation is to identify, evaluate, integrate and summarize relevant and qualified papers through conducting a systematic literature review (SLR) on the application of recommender systems (RSs) to suggest a scholarly publication venue for researcher's paper.

To identify the relevant papers published up to August 11, 2018, an SLR study on four databases (Scopus, Web of Science, IEEE Xplore and ScienceDirect) was conducted. We pursued the guidelines presented by Kitchenham and Charters (2007) for performing SLRs in software engineering. The papers were analyzed based on data sources, RSs classes, techniques/methods/algorithms, datasets, evaluation methodologies and metrics, as well as future directions.

A total of 32 papers were identified. The most data sources exploited in these papers were textual (title/abstract/keywords) and co-authorship data. The RS classes in the selected papers were almost equally used. DBLP was the main dataset utilized. Cosine similarity, social network analysis (SNA) and term frequency–inverse document frequency (TF–IDF) algorithm were frequently used. In terms of evaluation methodologies, 24 papers applied only offline evaluations. Furthermore, precision, accuracy and recall metrics were the popular performance metrics. In the reviewed papers, “use more datasets” and “new algorithms” were frequently mentioned in the future work part as well as conclusions.

Given that a review study has not been conducted in this area, this paper can provide an insight into the current status in this area and may also contribute to future research in this field.

This study aims to examine whether audit partner public-client specialization and busyness impact the cost of debt.

This paper uses data from companies in Thailand for the 1998–2016 period. To measure the cost of debt, this study uses the realized interest cost, measured as the total interest expense for the one year ahead divided by the average value of total debt outstanding during that year.

The results show a positive association between the cost of debt and two measures of public-client specialization and busyness, which are the number of public clients audited by an individual audit partner in each year and the proportion of the number of public clients divided by the number of total clients in an individual audit partner’s portfolio.

In the literature, there is a lack of research on whether a higher number of public clients in an audit partner’s portfolio leads to better or worse perceived audit quality. This study extends prior literature by examining whether creditors’ perception of audit quality depends on the audit partner specialization or busyness and specifically, on the number of public clients of the auditor. The findings indicate that public-client busyness of a particular audit partner, rather than the audit partner public-client specialization, matters in the cost of debt.

This study aims to examine the characteristics of financial analysts’ earnings forecasts after COVID-19 outbroke in the USA. Specifically, the authors examine how financial analysts tradeoff between accuracy and responsiveness under investors’ heightened information demand when there is market-wide uncertainty. In addition, the authors investigate how COVID-19 may affect analysts’ cognitive bias.

The research uses a sample of US-listed firms from March 2019 to February 2021, the period surrounding the COVID-19 outbreak in the USA.

The empirical analyses reveal that analysts issue timelier, more frequent, but less accurate forecasts after the COVID-19 outbreak, indicating that analysts become more responsive to investors’ intensified demand for information during the pandemic. Yet, the high uncertainty caused by COVID-19 increases forecasting difficulty. There is no systematic difference regarding the forecast accuracy between high- and low-ability analysts. Meanwhile, high-quality audit can improve forecast accuracy. Contrary to prior findings that analysts tend to underreact to bad news, the empirical evidence suggests that analysts, shaped by the salience bias, overestimate the negative impact of the pandemic. Analysts first issue pessimistic forecasts at the start of the outbreak and then revise forecasts upward steadily as the fiscal year-end approaches.

The study contributes to the literature by adding novel evidence on how COVID-19-induced uncertainty affects analyst forecast characteristics. It also provides additional evidence on how high-quality audit is associated with improved analyst forecast accuracy even under heightened uncertainty of COVID-19.