Journal of management Impact Factor 2024-2025 - ResearchHelpDesk - The Journal of Management - JOM is committed to publishing scholarly empirical and theoretical research articles, that have a high impact on the management field as a whole. The journal encourages new ideas or new perspectives on existing research. The journal covers such areas as: Business strategy & policy Organizational behavior Human resource management Organizational theory Entrepreneurship Research Methods The Journal of Management welcomes empirical and theoretical articles dealing with micro, meso, and macro workplace phenomena. Manuscripts that are suitable for publication in the Journal of Management cover domains such as business strategy and policy, entrepreneurship, human resource management, organizational behavior, organizational theory, and research methods. Abstract & indexing details Business ASAP - Gale Business and Company Resource Center - Gale EBSCO: Business Source - Main Edition Emerald Management Reviews Expanded Academic Index - Gale LexisNexis PAIS International ProQuest: CSA Sociological Abstracts ProQuest: International Bibliography of the Social Sciences (IBSS) PsycINFO Scopus Social SciSearch Social Sciences Citation Index (Web of Science) VINITI Abstracts Journal Wilson Business Periodicals Index/Wilson Business Abstracts

Journal of machine learning research Impact Factor 2024-2025 - ResearchHelpDesk - The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online. JMLR has a commitment to rigorous yet rapid reviewing. Final versions are published electronically (ISSN 1533-7928) immediately upon receipt. Until the end of 2004, paper volumes (ISSN 1532-4435) were published 8 times annually and sold to libraries and individuals by the MIT Press. Paper volumes (ISSN 1532-4435) are now published and sold by Microtome Publishing. JMLR seeks previously unpublished papers on machine learning that contain: new principled algorithms with sound empirical validation, and with justification of theoretical, psychological, or biological nature; experimental and/or theoretical studies yielding new insight into the design and behavior of learning in intelligent systems; accounts of applications of existing techniques that shed light on the strengths and weaknesses of the methods; formalization of new learning tasks (e.g., in the context of new applications) and of methods for assessing performance on those tasks; development of new analytical frameworks that advance theoretical studies of practical learning methods; computational models of data from natural learning systems at the behavioral or neural level; or extremely well-written surveys of existing work.

Introduction: China, as the world’s largest emitter of carbon dioxide, faces significant challenges in agricultural greenhouse gas emissions. The Chinese government has been actively promoting household photovoltaic (PV) power generation, which has great potential for application in rural areas. This study aims to explore whether the promotion of household PV systems in rural areas has a positive impact on farmers’ low-carbon production behavior and to analyze the influencing factors and mechanisms. This research fills the research gap in the analysis of the promotion of household PV systems and farmers’ low-carbon production behavior, providing scientific evidence to support policymakers in promoting widespread use of household PV systems and facilitating the transition of farmers to low-carbon production methods.Methods: This study adopts a qualitative research method and analyzes interview data and semi-structured questionnaire survey data from 48 farmers. By collecting, organizing, comparing, and extracting information and employing the research process of grounded theory, the researchers summarize the model of household PV-driven low-carbon production behavior.Results: The study finds that the installation of household PV systems indeed promotes farmers to adopt more low-carbon production behaviors. Farmers who install household PV systems show a greater willingness to reduce the use of fertilizers and pesticides, conserve water resources, and improve land utilization, among others. They perceive the positive effects of household PV systems and their own capacity for environmental protection, enhancing confidence and motivation to engage in low-carbon production behaviors.Discussion: Existing research methods have mainly relied on theoretical deduction combined with quantitative empirical approaches when exploring farmers’ pro-environmental spillover behaviors. However, these methods often start from the perspectives of either egoism or altruism, resulting in biased tendencies toward negative spillover or positive spillover. Nevertheless, neither egoism nor altruism fully captures the decision-making process when deeply understanding farmers’ production, life, and decision-making processes. The installation of household PV systems can change factors such as farmers’ knowledge, skills, cognition, and resources, enhancing their green self-efficacy and helping them acquire more knowledge and skills in renewable energy. Therefore, this research adopts a qualitative research method to more accurately reflect farmers’ decision-making process and provides practical recommendations to promote farmers’ active transition to pro-environmental spillover behaviors.Conclusion: This study fills the research gap in the analysis of the promotion of household PV systems and farmers’ low-carbon production behavior, providing practical recommendations for policymakers to facilitate farmers’ positive behavioral changes. Qualitative research methods enable a more realistic understanding and promotion of farmers’ pro-environmental spillover behaviors by deeply understanding their contexts. The study offers targeted suggestions to policymakers to drive farmers’ transition to low-carbon production methods.

Journal of management Acceptance Rate - ResearchHelpDesk - The Journal of Management - JOM is committed to publishing scholarly empirical and theoretical research articles, that have a high impact on the management field as a whole. The journal encourages new ideas or new perspectives on existing research. The journal covers such areas as: Business strategy & policy Organizational behavior Human resource management Organizational theory Entrepreneurship Research Methods The Journal of Management welcomes empirical and theoretical articles dealing with micro, meso, and macro workplace phenomena. Manuscripts that are suitable for publication in the Journal of Management cover domains such as business strategy and policy, entrepreneurship, human resource management, organizational behavior, organizational theory, and research methods. Abstract & indexing details Business ASAP - Gale Business and Company Resource Center - Gale EBSCO: Business Source - Main Edition Emerald Management Reviews Expanded Academic Index - Gale LexisNexis PAIS International ProQuest: CSA Sociological Abstracts ProQuest: International Bibliography of the Social Sciences (IBSS) PsycINFO Scopus Social SciSearch Social Sciences Citation Index (Web of Science) VINITI Abstracts Journal Wilson Business Periodicals Index/Wilson Business Abstracts

IntroductionThis study explores impactful research fronts within the digital educational ecosystem using an extended Clarivate approach with a newly formulated Impact Factor (IF) metric. The research addresses limitations of the original Clarivate Citation Production Trajectory (CPT) by integrating a broader IF metric.MethodsThe IF metric expands evaluation by incorporating publication count, growth rate, core paper presence, and citation behavior. It also measures the publication gap between core and citing articles to track developmental shifts. Scopus data from 2019–2023 serve as the analysis base.ResultsThe analysis reveals key research fronts such as online learning, artificial intelligence, virtual reality, hybrid learning, and digital assessment. Online learning and AI emerge as the most influential.DiscussionThe IF metric enhances precision in detecting impactful fronts over CPT and maps global research activities, highlighting growing contributions from developing regions. This refined approach helps assess both short-term relevance and long-term influence in digital education. The findings emphasize a more inclusive landscape of impactful research across institutions and nations.

Explained inertia by each dimension for group A: Indoor Index, 2007.

aCategories are: adopted the most pro-environmental behaviours (++), adopted slightly fewer (+), adopted much fewer (−) and adopted the fewest (−).

Hierarchical structure characteristics between clusters.

Nodes hierarchy and visit probability among clusters.

In today’s society, time is considered more valuable than money, and researchers often have limited time to find relevant papers for their research. Identifying and accessing essential information can be a challenge in this situation. To address this, the personalized suggestion system has been developed, which uses a user’s behavior data to suggest relevant items. The collaborative filtering strategy has been used to provide a user with the top research articles based on their queries and similarities with other users’ questions, thus saving time by avoiding time-consuming searches. However, when rating data is abundant but sparse, the usual method of determining user similarity is relatively straightforward. Furthermore, it fails to account for changes in users’ interests over time resulting in poor performance. This research proposes a new similarity measure approach that takes both user confidence and time context into account to increase user similarity computation. The experimental results show that the proposed technique works well with sparse data, and improves accuracy by 16.2% compared to existing models, especially during prediction. Furthermore, it enhances the quality of recommendations.

In today’s society, time is considered more valuable than money, and researchers often have limited time to find relevant papers for their research. Identifying and accessing essential information can be a challenge in this situation. To address this, the personalized suggestion system has been developed, which uses a user’s behavior data to suggest relevant items. The collaborative filtering strategy has been used to provide a user with the top research articles based on their queries and similarities with other users’ questions, thus saving time by avoiding time-consuming searches. However, when rating data is abundant but sparse, the usual method of determining user similarity is relatively straightforward. Furthermore, it fails to account for changes in users’ interests over time resulting in poor performance. This research proposes a new similarity measure approach that takes both user confidence and time context into account to increase user similarity computation. The experimental results show that the proposed technique works well with sparse data, and improves accuracy by 16.2% compared to existing models, especially during prediction. Furthermore, it enhances the quality of recommendations.

Intimate Partner Violence (IPV) is a global public health issue, with notably high prevalence rates observed within Low-and Middle-Income Countries (LMICs). This systematic review aimed to examine the risk factors and consequences associated with IPV against women in LMICs. Following PRISMA guidelines, we conducted a systematic review using three databases: Web of Science, ProQuest Central, and Scopus, covering the period from January 2010 to January 2022. The study included only peer-reviewed journal articles in English that investigated IPV against women in LMICs. Out of 167 articles screened, 30 met the inclusion criteria, comprising both quantitative and mixed-method studies. Risk factors of IPV were categorised as: demographic risk factors (23 studies), family risk factors (9 studies), community-level factors (1 studies), and behavioural risk factors (14 studies), while consequences of IPV were categorised as mental health impacts (13 studies), physical impacts (5 studies), and societal impacts (4 studies). In this study, several risk factors were identified including lower levels of education, marriage at a young age, poor wealth indices, rural residential areas, and acceptance of gender norms that contribute to the prevalence of IPV in LMICs. It is essential to address these factors through effective preventive policies and programs. Moreover, this review highlights the necessity of large-scale, high-quality policy-driven research to further examine risk factors and consequences, ultimately guiding the development of interventions aimed at preventing IPV against women in LMICs.

Detailed summary of selected articles including quality rating.

BackgroundDepression is the most common psychiatric disorder reported among patients living with Human Immunodeficiency Virus (HIV), resulting from the intricate combination of biological, psychological, and social factors. Biopsychosocial factors can significantly impact the psychological well-being of men who have sex with men (MSM) living with HIV through social stigma, access and compliance to care, economic insecurity, relationship difficulties, and risky behavior. Compared to MSM without HIV, MSM living with HIV were more likely to be depressed. Despite specific vulnerabilities and health needs, MSM living with HIV remain understudied and underserved in Malaysia owing to legal, ethical, and social challenges.ObjectiveThis is merely a published protocol, not the findings of a future study. This study aims to determine and explain the predictors of depressive symptoms among MSM living with HIV. Specifically, this study wants to determine the association between depressive symptoms among MSM living with HIV and biological, psychosocial, and social factors. Finally, the mixed methods will answer to what extent the qualitative results confirm the quantitative results of the predictors of depressive symptoms among MSM living with HIV.MethodsThe study has ethical approval from the Medical Research Ethics Committee (MREC) of the Ministry of Health (MOH) NMRR ID-21-02210-MIT. This study will apply an explanatory sequential mixed methods study design. It comprised two distinct phases: quantitative and qualitative study design for answering the research questions and hypothesis. This study will randomly recruit 941 MSM living with HIV in the quantitative phase, and at least 20 MSM living with HIV purposively will be selected in the qualitative phase. The study will be conducted in ten public Primary Care Clinics in Selangor, Malaysia. A self-administered questionnaire will gather the MSM’s background and social, psychological, and biological factors that could be associated with depressive symptoms. For the quantitative study, descriptive analysis and simple logistic regression will be used for data analysis. Then, variables with a P value < 0.25 will be included in multiple logistic regression to measure the predictors of depressive symptoms. In the qualitative data collection, in-depth interviews will be conducted among those with moderate to severe depressive symptoms from the quantitative phase. The thematic analysis will be used for data analysis in the qualitative phase. Integration occurs at study design, method level, and later during interpretation and report writing.ResultThe quantitative phase was conducted between March 2022 to February 2023, while qualitative data collection is from March 2023 to April 2023, with baseline results anticipated in June 2023.ConclusionIn combination, qualitative and quantitative research provides a better understanding of depressive symptoms among MSM living with HIV. The result could guide us to provide a comprehensive mental healthcare program toward Ending the AIDS epidemic by 2030.

Main challenges or concerns respondents have encountered at the dental clinic (n = 130).