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In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an important issue for the further development of higher education, thus leading to extensive and in-depth research by many scholars. The study summarizes the characteristics and patterns of dual-innovation education at different stages of development, hoping to provide a systematic model for the development of dual-innovation education in China and make up for the shortcomings.

This paper uses Citespace software to visualize and analyze the relevant literature in CNKI and Web of Science databases from a bibliometric perspective, focusing on quantitative analysis in terms of article trends, topic clustering, keyword co-linear networks and topic time evolution, etc., to summarize and sort out the development of innovation and entrepreneurship education research at home and abroad.

The study found that the external characteristics of the literature published in the field of bi-innovation education in China and abroad are slightly different, mainly in that foreign publishers are more closely connected and have formed a more stable ecosystem. In terms of research hotspots, China is still in a critical period of reforming its curriculum and teaching model, and research on the integration of specialization and creative education is in full swing, while foreign countries focus more on the cultivation of students' entrepreneurial awareness and the enhancement of individual effectiveness. In terms of cutting-edge analysis, the main research directions in China are “creative education”, “new engineering”, “integration of industry and education” and “rural revitalization”.

Innovation and entrepreneurship education in China is still in its infancy, and most of the studies lack an overall overview and comparison of foreign studies. Based on the econometric analysis of domestic and foreign literature, this paper proposes a path for domestic innovation and entrepreneurship education reform that can make China's future education reform more effective.

Corporate site visits increase labor investment efficiency.

Our empirical model for the baseline analysis follows those of Jung et al. (2014) and Ghaly et al. (2020).

We show that corporate site visits are associated with significantly higher labor investment efficiency; more specifically, site visits reduce both over-hiring and under-hiring of employees. The effect of site visits on labor investment efficiency is more pronounced for firms with higher labor adjustment costs, greater financial constraints, weaker corporate governance and lower financial reporting quality. We also find that site visits mitigate labor cost stickiness.

First, while the literature has suggested how the presence of institutional investors and analysts may affect labor investment decisions, we focus on institutional investors and analysts’ activities and interactions with firm executives. We provide direct evidence that institutional investors and analysts may use corporate site visits to improve labor investment efficiency. Second, our study adds to a line of recent studies on how corporate site visits reduce information asymmetry and agency conflicts. We show that corporate site visits allow institutional investors and analysts to influence labor investment efficiency. We also provide new evidence that corporate site visits reduce labor cost stickiness.

Product returns are a major challenge for e-businesses as they involve huge logistical and operational costs. Therefore, it becomes crucial to predict returns in advance. This study aims to evaluate different genres of classifiers for product return chance prediction, and further optimizes the best performing model.

An e-commerce data set having categorical type attributes has been used for this study. Feature selection based on chi-square provides a selective features-set which is used as inputs for model building. Predictive models are attempted using individual classifiers, ensemble models and deep neural networks. For performance evaluation, 75:25 train/test split and 10-fold cross-validation strategies are used. To improve the predictability of the best performing classifier, hyperparameter tuning is performed using different optimization methods such as, random search, grid search, Bayesian approach and evolutionary models (genetic algorithm, differential evolution and particle swarm optimization).

A comparison of F1-scores revealed that the Bayesian approach outperformed all other optimization approaches in terms of accuracy. The predictability of the Bayesian-optimized model is further compared with that of other classifiers using experimental analysis. The Bayesian-optimized XGBoost model possessed superior performance, with accuracies of 77.80% and 70.35% for holdout and 10-fold cross-validation methods, respectively.

Given the anonymized data, the effects of individual attributes on outcomes could not be investigated in detail. The Bayesian-optimized predictive model may be used in decision support systems, enabling real-time prediction of returns and the implementation of preventive measures.

There are very few reported studies on predicting the chance of order return in e-businesses. To the best of the authors’ knowledge, this study is the first to compare different optimization methods and classifiers, demonstrating the superiority of the Bayesian-optimized XGBoost classification model for returns prediction.

Although the development of public organisations and the continual enhancement of public services depend on the creative behaviour of public employees, it is uncertain from earlier studies how and when inclusive leadership (IL) affects innovative behaviours (IB). This study aims to resolve the inconsistency in the literature by applying social exchange theory to examine the effect of inclusive leadership on employees’ innovative behaviour, while also examining the mediating role of work engagement and the moderating effect of psychological safety within this relationship.

The research model’s analysis draws from a data set of 200 employee–supervisor dyads. Data was collected from employees across diverse public sector organisations in the United Arab Emirates (UAE).

The results demonstrate that IL indirectly (via WE) and directly has a positive influence on employees’ IBs. This influence is enhanced when employees feel safe and do not have to be concerned about negative consequences.

Our study highlights a less-explored sector, unveiling the motivations behind IB among public sector employees. Moreover, this study provides valuable insights within a non-Western context, offering a unique perspective on the intricate relationship between IL, PS, employee engagement and IBs in the UAE public sector.

The main objective of this article is to visualize the structure and trends of pro-environmental behavior (PEB) between 1999 and 2023 through mapping and in-depth analysis. The aim is to analyze PEB, which has received considerable academic attention in recent years due to its key role in the conservation of the environment and the protection of local communities in tourist destinations. This paper provides an important summary of the recent research that has explored the role that tourists have in protecting the environment through PEB.

This study presents a visual analysis of 2005 scholarly articles between the years 1999 and 2023 related to PEB. Using the knowledge mapping based on VOSviewer it presents the current status of research, which includes the analysis of citation analysis, co-citation analysis, co-citation network and longitudinal analysis.

PEB is an emerging topic due to its relevance to protecting the environment in the context of travel. The citation and co-citation analysis show the relevance of the behavior of tourists with regard to protecting the environment. The co-word analysis highlights the current significance of research concerning green hotels and the destination image of environmentally responsible destinations.

This study sheds light on the current research progress of PEB in the context of tourism through a comprehensive analysis (citation, co-citation and co-word). In addition, we provide theories and factors that have been previously used to study PEB in the context of tourism. The findings contribute to a broad and diverse understanding of the concept of PEB, which can provide important insights for policymakers in formulating management strategies and policies aimed at reducing environmental impacts in destinations.

This study aims to explore differences in the usability of the Google Drive application based on demographic characteristics, computer skills and use frequency of Google Drive among public library users of Lahore.

The study adopted a quantitative approach and survey-based research method to achieve the study's objectives. The cloud usability model (user perspective) has been used as a theoretical lens to guide the study objectives. It comprises five dimensions of usability – capable, personal, reliable, valuable and secure.

The findings of the study revealed that the usability of Google Drive varied statistically significantly on the basis of depending on the respondents gender, age, academic qualification, computer skills and Google Drive use frequency.

It is a valuable study since it and adds knowledge to existing literature and has implications for practice.

The findings might be helpful for cloud support teams including Google Drive as they can notice the demographic and other differences among users' perceived usability of Google Drive and can enhance certain features of usability which leads attributes to increase its usage among users.

In recent times, stakeholders have called on corporate organizations especially those charged with governance to embrace full disclosure on non-financial issues, especially sustainability reporting. Based on this premise, this study aims to examine the influence of corporate board and assurance on sustainability reporting practices (SRP) of selected 80 firms from 8 countries in sub-Saharan Africa.

To measure the corporate board, the authors use both board variables and audit committee variables. Also, the authors adapted the sustainability score model as used by previous authors in the field of sustainability disclosure to measure SRPs. The analysis was done using both ordered logistic regression and probit regression models.

The results show that the combination of board corporate and assurance has a positive and significant impact on the sustainability reporting practice of selected firms in sub-Saharan Africa.

The study places emphasis on the need for strong collaboration between the corporate board and external assurance in evaluating and enhancing the quality of sustainability disclosure.

The study bridged the gap in the literature in the area of corporate board, assurance and SRP of corporate firms which has received little attention within sub-Saharan Africa.

Reducing CO₂ emissions from transportation is crucial for achieving carbon neutrality in the Gulf Cooperation Council (GCC) countries by 2060 or earlier. This study aimed at analyzing transportation-related energy consumption and CO₂ emissions, along with their determinants and mitigation measures planned to achieve carbon neutrality in GCC countries.

To achieve the study objectives, the pressure-state-response (PSR) framework was utilized. Various methods were employed within the PSR framework, including econometric analysis using EViews, energy modeling using the low emissions analysis platform (LEAP) and content analysis of relevant policy and national documents using NVivo.

The results indicated that population and economic growth, along with increased fuel consumption, have led to a growth in transportation-related energy use and CO₂ emissions in the GCC countries. Per capita transportation-related CO₂ emissions in the GCC countries are higher than those of several countries. To achieve carbon-neutral transportation, approximately 1.8 bn metric tons of CO₂ emissions need to be avoided by 2060 or earlier. Strategies related to fuel alternatives, vehicle technologies and mass transit have been planned to reduce transportation-related CO₂ emissions in the GCC countries.

This study employed a holistic approach to analyze transportation-related energy use and CO₂ emissions in the GCC countries. It provides several policy implications and highlights the urgent need for policy innovations to achieve transformative change in the transportation sectors of the GCC countries.

This paper aims to address the safety concerns of path-planning algorithms in dynamic obstacle warehouse environments. It proposes a method that uses improved artificial potential fields (IAPF) as expert knowledge for an improved deep deterministic policy gradient (IDDPG) and designs a hierarchical strategy for robots through obstacle detection methods.

The IAPF algorithm is used as the expert experience of reinforcement learning (RL) to reduce the useless exploration in the early stage of RL training. A strategy-switching mechanism is introduced during training to adapt to various scenarios and overcome challenges related to sparse rewards. Sensor inputs, including light detection and ranging data, are integrated to detect obstacles around waypoints, guiding the robot toward the target point.

Simulation experiments demonstrate that the integrated use of IDDPG and the IAPF method significantly enhances the safety and training efficiency of path planning for mobile robots.

This method enhances safety by applying safety domain judgment rules to improve APF’s security and designing an obstacle detection method for better danger anticipation. It also boosts training efficiency through using IAPF as expert experience for DDPG and the classification storage and sampling design for the RL experience pool. Additionally, adjustments to the actor network’s update frequency expedite convergence.

Our study aims to understand what is known about happiness at work (HAW) in terms of publication, citations, dimensions and characteristics, as well as how knowledge about HAW is generated regarding theoretical frameworks, context and methods. Additionally, it explores future directions for HAW research.

This paper conducts a systematic literature review of 56 empirical articles published between 2000 and 2022 to comprehensively explore HAW. It examines publication trends, citation patterns, dimensions, characteristics, theoretical frameworks, contextual factors and research methodologies employed in HAW studies.

Our findings suggest that while HAW research has gained momentum, there is still a need for exploration, particularly in developing countries. Various theoretical frameworks such as the job demand-resources model, social exchange theory and broaden-and-build theory are identified, with suggestions for the adoption of less popular theories like the positive emotion, engagement, relationships, meaning and accomplishment (PERMA) model and flow theory for future investigations. The review contributes to workplace happiness literature by offering a comprehensive analysis spanning two decades and provides valuable insights for guiding future research toward exploring factors influencing employee well-being.

Our article offers a structured analysis of HAW literature, emphasizing the necessity for more extensive research, especially in developing nations. It provides valuable insights into the theories and dimensions associated with HAW, guiding future research and assisting organizations in formulating strategies to enhance employee happiness and overall well-being.