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Drawing on social information processing theory, this study constructs a multilevel moderated mediation model. This model seeks to delve into the intricate and previously overlooked interplay between supervisor bottom-line mentality (BLM) and knowledge hiding. Within this context, we introduce self-interest as a mediating factor and incorporate performance climate as a team-level moderating variable.

The time-lagged data involve 336 employees nested in 42 teams from 23 automobile sales companies in five regions of China. The analysis was meticulously executed using Hierarchical Linear Modeling, complemented by bias-corrected bootstrapping techniques.

The findings reveal that self-interest acts as a full mediator in the positive link between supervisor BLM and knowledge hiding. Furthermore, the performance climate plays a moderating role in both the relationship between supervisor BLM and self-interest, and the entire mediation process. Notably, these relationships are intensified in environments with a high performance climate compared to those with a low one.

This research stands as one of the pioneering efforts to integrate supervisor BLM into the discourse on knowledge hiding, elucidating the underlying psychological mechanisms and delineating the boundary conditions that shape the “supervisor BLM–knowledge hiding” relationship. Further, our insights provide organizations with critical guidance on strategies to curtail knowledge hiding among their employees.

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.

This study aims to empirically validate the holistic consumer-based brand equity (CBBE) framework and establishment of the cross-over effect using consumer preferences for wine “regions.”

The authors utilize a sample of 275 regular wine purchasers in Australia, who were aged above 30 years old and had consumed regional wine in the last 3 months through an online consumer panel survey.

By testing competing CBBE models, the main research model was found to have the greatest predictive ability, due to its inclusion of both the rational and emotional paths and the cross-over effect between consumer brand judgment and brand feeling. This paper indicates that consumers enhance brand equity and develop a strong ongoing relationship with regional wine brands by simultaneously engaging in both mental behavior paths, where, in the meantime, rational processing has a cross-over effect on emotional processing.

This study expands the brand management literature by answering the future research on the CBBE model identified by Hall et al. (2021). Moreover, it establishes the underexplored cross-over effect within the CBBE literature. Furthermore, it adds to the marketing and wine-marketing literature by extending the concept of the brand to other attributes in consumer choice, such as a wine region as outlined by Giacomarra et al. (2020). Thus, this study advances the existing branding knowledge in a practical sense, which enables regional wine marketers and wine retailers to undertake promotional and product development strategies accordingly.

The purpose of this research is to enhance the Laser Powder Bed Fusion (LPBF) additive manufacturing technique by addressing its susceptibility to defects, specifically lack of fusion. The primary goal is to optimize the LPBF process using a digital twin (DT) approach, integrating physics-based modeling and machine learning to predict the lack of fusion.

This research uses finite element modeling to simulate the physics of LPBF for an AISI 316L stainless steel alloy. Various process parameters are systematically varied to generate a comprehensive data set that captures the relationship between factors such as power and scan speed and the quality of fusion. A novel DT architecture is proposed, combining a classification model (recurrent neural network) with reinforcement learning. This DT model leverages real-time sensor data to predict the lack of fusion and adjusts process parameters through the reinforcement learning system, ensuring the system remains within a controllable zone.

This study's findings reveal that the proposed DT approach successfully predicts and mitigates the lack of fusion in the LPBF process. By using a combination of physics-based modeling and machine learning, the research establishes an efficient framework for optimizing fusion in metal LPBF processes. The DT's ability to adapt and control parameters in real time, guided by machine learning predictions, provides a promising solution to the challenges associated with lack of fusion, potentially overcoming the traditional and costly trial-and-error experimental approach.

Originality lies in the development of a novel DT architecture that integrates physics-based modeling with machine learning techniques, specifically a recurrent neural network and reinforcement learning.

This study aims to identify the key factors that influence household pro-environmental behaviors (HPEBs) and explore the differences caused by the same influencing factors between household waste management behavior (HWM) and household energy-saving behavior (HES).

A meta-analysis was conducted on 90 articles about HPEBs published between 2009 and 2023 to find the key factors. HPEBs were further categorized into HWM and HES to investigate the difference influenced by the above factors on two behaviors. The correlation coefficient was used as the unified effect size, and the random-effect model was adopted to conduct both main effect and moderating effect tests.

The results showed that attitude, subjective norms, and perceived behavioral control all positively influenced intention and HPEBs, but their effects were stronger on intention than on HPEBs. Intention was found to be the strongest predictor of HPEBs. Subjective norms were found to have a more positive effect on HES compared to HWM, while habits had a more positive effect on HWM. Furthermore, household size was negatively correlated with HWM but positively correlated with HES.

The same variables have different influences on HWM and HES. These results can help develop targeted incentives to increase the adoption of HPEBs, ultimately reducing household energy consumption and greenhouse gas emissions and contributing to the mitigation of global warming.

Sustainable manufacturing practices are excessively being practised in the industry today. The impact on sustainability is ever more visible to the stakeholders because of faster and more efficient communication due to social media and the internet. This paper aims to study the impact of greenwashing by corporations and the stakeholders’ environmental concerns on consumers’ sustainable purchase behaviour.

The relationships between the impression of “greenwash”, sustainable purchasing behaviour, green word-of-mouth and green brand loyalty were investigated in this quantitative study. Participants who made up a representative sample filled out written surveys. The variables of interest were evaluated using scales that have undergone validation. Structural equation modelling was used in mediation analysis to investigate the mediating impacts of green word-of-mouth and green brand loyalty. The goal of the study was to offer empirical proof of how these factors affected consumers’ choices for sustainable products.

Analysis of the mediating relationship of perceived customer effectiveness in the relationship between environmental concern and sustainable purchase behaviour has been studied.

This study implicates that a company that primarily markets basic green and sustainable products or services must invest in informing people about environmental concerns and that by proper practices, a lot of the harm to the environment can be reduced.

Corporate greenwashing, also called false greening, has received much public attention recently. The unethical practices by the corporations, which previously majorly went unnoticed, have also recently gained a lot of visibility. This paper is one of the early attempts towards establishing the effect of corporate greenwashing on sustainable consumer behaviour.

This study aims to improve the acceleration in the additive manufacturing (AM) process. AM tools, such as extrusion heads, jets, electric arcs, lasers and electron beams (EB), experience negligible forces. However, their speeds are limited by the positioning systems. In addition, a thin tool must travel several kilometers in tiny motions with several turns while realizing the AM part. Hence, acceleration is a more significant limiting factor than the velocity or precision for all except EB.

The sawtooth (ST) scanning strategy presented in this paper minimizes the time by combining three motion features: zigzag scan, 45º or 135º rotation for successive layers in G00 to avoid the CNC interpolation, and modifying these movements along 45º or 135º into sawtooth to halve the turns.

Sawtooth effectiveness is tested using an in-house developed Sand AM (SaAM) apparatus based on the laser–powder bed fusion AM technique. For a simple rectangle layer, the sawtooth achieved a path length reduction of 0.19%–1.49% and reduced the overall time by 3.508–4.889 times, proving that sawtooth uses increased acceleration more effectively than the other three scans. The complex layer study reduced calculated time by 69.80%–139.96% and manufacturing time by 47.35%–86.85%. Sawtooth samples also exhibited less dimensional variation (0.88%) than zigzag 45° (12.94%) along the build direction.

Sawtooth is limited to flying optics AM process.

Development of scanning strategy for flying optics AM process to reduce the warpage by improving the acceleration.

The study specifically seeks to comprehend the impact of online corporate social responsibility (CSR) initiatives on consumer behaviour, with a focus on Generation Y consumers. It also aims to examine how, particularly within Ghanaian manufacturing firms, the views of Generation Y consumers regarding digital social responsibility (DSR), and how it moderates the relationship between brand loyalty and purchase intention.

This study takes a quantitative approach, using information gathered via a survey questionnaire from 611 Generation Y consumers in Ghana. Examining the connections between DSR, customer engagement, brand loyalty and purchase intention is the main goal of the investigation. Structural equation modelling (SEM) methods are used in the study to examine the data gathered and verify the proposed linkages.

The study reveals a strong positive relationship between corporate social responsibility (DSR) and purchase intention, mediated by consumer engagement and brand loyalty. However, it does not suggest Generation Y's attitudes towards DSR moderating this relationship. The study underscores the importance of DSR for Ghanaian manufacturing businesses.

By studying the relatively unexplored idea of DSR and its effects on consumer behaviour in developing nations – especially in the context of Ghanaian manufacturing enterprises – this study adds to the body of current work. This study sheds light on the ways in which DSR affects Generation Y customers' intentions to buy by examining the mediating roles of brand loyalty and consumer engagement.

Based on the trait activation theory, the current study systematically integrates how autonomy interacts with proactivity to influence the relationship between ethical leadership style and employee creativity.

Using simple random sampling and questionnaires, a sample of 475 engineering employees of 3 leading telecommunication companies in Ghana were obtained. The analysis was done using structured equation modeling (SEM), using SmartPLS.

The results showed that ethical leadership style provides employees with job autonomy which facilitates individual creativity. Employee proactivity also moderates a positive relationship between autonomy and creativity such that high-proactive employees are well placed to produce more creative outcomes when given autonomy. At the individual level, personal characteristics determine the degree of creativity.

The current study implies that telecommunication companies should put in more efforts to train and encourage leaders to be ethical in leaders' dealings with employees and employees must be rewarded for taking initiative.

With a focus on the integrative approach from a developing economy, this work is novel in exploring how contextual and personal features impact creativity.

Progress in agriculture significantly relies on the adoption of innovative farm practices by farmers. Being proactive and risk-taking catalyses this innovativeness. Progressive farmers in general are proving to be effective in developing their farms along entrepreneurial lines. The paper aims to examine the relationship between the entrepreneurial traits of risk-taking, proactiveness, innovativeness and entrepreneurial intention (EI) of progressive farmers in Kashmir.

A quantitative research approach was used to evaluate how innovativeness, risk-taking and proactiveness affect EI. The data was collected from registered progressive farmers using a structured questionnaire via both online and offline means. 203 useable responses were received. The data was then analysed using partial least squares structural equation modelling (PLS-SEM).

The results reveal that progressive farmers' EI is influenced by innovativeness, risk-taking and proactiveness. As hypothesized, a significant and positive relationship was found between entrepreneurial orientation (EO) traits of risk-taking, proactiveness and innovativeness and EI.

The study adds to the existing body of knowledge on agri-entrepreneurship by conceptualizing EO traits influencing EI of progressive farmers and offering insightful advice to policymakers on how to improve progressive farmers' entrepreneurial abilities and in turn convert their EI into agro venture establishment in Kashmir.

This study makes advancements in the field of farming-related EO by examining the EI of progressive farmers. This study covers a knowledge gap as there aren't many empirical studies on agricultural entrepreneurship that concentrate on the EO of progressive farmers and how it influences the EI in general in India and the Kashmir valley in particular.