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This study aims to find how trade development and digitalization affect smart-green production. Four factors are investigated in these effects (certification, technology innovation, natural resource management, low pesticides).

The mix-method approach was employed from validating the measurement scale to test the proposed hypotheses. At first, the grounded theory is the most authoritative and standard research method in qualitative research. Secondly, quantitative analysis was employed to draw conclusions about the impact of digitalization and trade development on smart-green agricultural production.

The results found that digitalization and trade development impact the development of smart-green agricultural production through certification employment, technology innovation, and a decrease in pesticide usage. Moreover, digitalization and trade development also indirectly affect the development of intelligent green agricultural production. Meanwhile, digitalization has a higher impact than trade development.

This research is based on the premise that digitalization and trade development can drive smart green agricultural production. Still, some studies have found a deviation between trade development and environmental protection. Hence, future research can explore the incentive effect of trade development and digitalization on other industries. Second, the measurement of the dependent variables in this study is based on the premise that smart-green agricultural production has not been widely promoted, so the changes in production before and after the whole public participation in smart-green output have yet to be reflected.

Smart green production in agriculture is essential for a transition economy and the world to meet food security and protect the environment. However, the effects of certification, technology innovation, natural resource management, and low pesticides on smart-green agriculture production have yet to be identified. Insights from this study can help governments, policy-makers, and farmers in emerging economies by adapting their strategies within their local contexts.

Limited knowledge exists regarding the adverse effects of artificial intelligence adoption, including platforms like ChatGPT, on users’ mental well-being. The current research seeks to adopt the insight from the stressor-strain-outcome paradigm and a moderated mediation model to examine how technology anxiety moderates the direct and indirect relationships between compulsive use of ChatGPT, technostress, and life satisfaction.

Drawing data from a sample of 2,602 ChatGPT users in Vietnam, PROCESS macro was approached to test the moderated mediation model.

The findings indicate that compulsive use of ChatGPT exhibited a substantial and positive impact on technostress, while technostress was found to have a negative influence on life satisfaction. Moreover, although compulsive use of ChatGPT did not show a significant direct effect, it indirectly impacts life satisfaction via technostress. Remarkably, technology anxiety was found to significantly moderate both direct and indirect associations between compulsive use of ChatGPT, technostress, and life satisfaction.

Based on the findings of this research, some practical implications are provided.

The research offers a fresh perspective by applying the stressor-strain-outcome perspective to provide empirical evidence on the moderated mediation effects of technology anxiety and technostress on the relationship between compulsive use of ChatGPT and users’ life satisfaction. The research thus sheds new light on artificial intelligence adoption and its effects on users’ mental health.

This study aims to explore the ways in which management scholars affiliated with Peruvian universities navigate the tensions between global expectations and local realities in their research practices, drawing on their capitals and habitus.

Drawing on Bourdieu’s field theory, the authors analyse 25 in-depth interviews and a unique database of academic publications in the business and management field from 2000 to 2022. The analysis identifies the positions scholars occupy within the Peruvian management field and examines the factors influencing their research practices.

The authors find that the Peruvian management field is complex and unequal, where actors have different positions and interests, but are all influenced by a logic of academic dependency on the Global North. The authors identify three main positions held by scholars: transnational dominators, who accumulate greater resources and ignore local debates; dominated adaptors, who unsuccessfully try to imitate the dominant logic; and isolated innovators, who critique the dominant model but lack institutional support to develop alternatives.

This research presents an analysis of the Peruvian management field, a site often overlooked in international business studies. By examining scholarly practices, the authors reveal how academic inequalities are reproduced by the forces of globalization. The study underscores the urgent need for greater acknowledgement of regionally informed research, advocating for a more inclusive and diverse understanding in the field of management research.

Deficiencies or imbalances in dietary fat intake may influence on mental and neurological functions of children with autism spectrum disorders (ASD). This study aims to compare body mass index (BMI) and the amount of fatty acids intake in the autistic patients with the comparison group.

This case-control was carried out on 200 randomly selected children from 5 to 15 years old (100 autistic patients as the case group and 100 healthy children as the comparison group) in Tehran, Iran. The food frequency questionnaire (FFQ) was used to assess the intake of calorie, macronutrients and different types of dietary fatty acids including saturated fatty acids (SFA), monounsaturated fatty acids (MUFAs), poly unsaturated fatty acids (PUFAs), linoleic acid (LA), α-Linolenic acid (ALA), eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA) and trans fatty acids.

The autistic patients had higher BMI, birth weight and mother’s BMI compared to the comparison group (All p < 0.01). No significant difference was found in the amount of dietary calorie, protein, carbohydrate and total fat intake between two groups. The risk of ASD was associated with higher intake of MUFAs (OR: 3.18, CI%:1.13–4.56, p = 0.04), PUFAs (OR: 4.12, CI95%: 2.01–6.25, p < 0.01) and LA (OR: 4.76, CI95%: 1.34–14.32, p < 0.01).

The autistic children had higher BMI and higher intake of unsaturated fatty acids except for omega-3 fatty acids. Further longitudinal studies are warranted.

This empirical research aims to provide organisations with useful information on how teleworking has affected employee commuting, allowing organisations to adapt working conditions to the new social context. This research sets out to provide evidence on the behaviour of teleworkers in terms of the mode of transport chosen when commuting to work physically.

This research is based on a survey conducted in Madrid based on a theoretical approach grounded in the theory of planned behaviour (TPB) and discrete choice models. Exploratory factor analysis (EFA) and discriminant analysis have been used to determine the variables that influence the mode of transport chosen by teleworkers when commuting in person.

The results indicate the prevalence of private car use by teleworkers when working at the office, finding that attitudes and satisfaction with modes of transport significantly influence their choice. The characteristics and frequency of teleworking, however, are not significant, which indicates that teleworkers attach greater importance to their preferred mode of transport, regardless of the disadvantages.

This research provides empirical evidence using an inductive approach to understand the challenges that organisations are facing with regard to teleworking since commuting behaviour has changed for teleworkers. This requires organisations to give significant reconsideration to the issue of commuting as an important component of working time that could condition employee satisfaction and, therefore, the retention or recruitment of talent. Furthermore, residence and mobility changes afford organisations better access for recruitment, notwithstanding urban planning implications.

This study aims to analyse the trend of Mpox research in the pre and post-outbreak period. The study compared the growth pattern, major research areas, sources of publications, funding agencies, countries and institutions invested in Mpox research, and institutional and countrywide collaboration patterns in Mpox research in both periods.

This study is based on the data retrieved from the Web of Science database for two time frames: the pre-outbreak period (January 1989–April 2022) and the post-outbreak period (May 2022–December 2022). The study is limited to research articles and reviews articles from Web Science. The study used Microsoft Excel and VOSviewer visualization software to derive results.

The study found few publications on Mpox before the epidemic outbreak, and a steep increase is visible after it. Before and after the Mpox pandemic, the USA ranked first in the production of literature. The focus of research before the outbreak of the epidemic was on virology, which was replaced by infectious diseases during the post-epidemic period. More publications were found available in open-access journals during the post-outbreak time. Author collaboration with US authors from other countries is higher in the post-outbreak period. During the pre-outbreak time, the principal supporters of Mpox research were American funding agencies and institutes. The study reveals that the research in post-outbreak is more concentrated on diagnosis, prevention and treatment of Mpox.

This study offers a systematic literature review on Mpox’s overall research productivity. It contrasted the patterns of this field’s pre- and post-epidemic research. The conclusions of this study will act as a guide for scientists operating all across the world.

A thorough scientometric analysis of the trend of Mpox research in the pre- and post-outbreak period has not been attempted. It will help identify the nature of research on Mpox over the years, which will support future research on Mpox attempted across the globe.

The purpose of this multi-voiced paper is to propose a prosocial paradigm for the field of performance management and management control systems. This new paradigm suggests cultivating prosocial behaviour and prosocial groups in organizations to simultaneously achieve the objectives of economic performance and sustainability.

The authors share a common concern about the future of humanity and nature. They challenge the influential assumption of economic man from neoclassical economic theory and build on evolutionary science and the core design principles of prosocial groups to develop a prosocial paradigm.

Findings are based on the premise of the prosocial paradigm that self-interested behaviour may outperform prosocial behaviour within a group but that prosocial groups outperform groups dominated by self-interest. The authors explore various dimensions of performance management from the prosocial perspective in the private and public sectors.

The authors call for theoretical, conceptual and empirical research that explores the prosocial paradigm. They invite any approach, including positivist, interpretive and critical research, as well as those using qualitative, quantitative and interventionist methods.

This paper offers implications from the prosocial paradigm for practitioners, particularly for executives and managers, policymakers and educators.

Adoption of the prosocial paradigm in research and practice shapes what the authors call the prosocial market economy. This is an aspired cultural evolution that functions with market competition yet systematically strengthens prosociality as a cultural norm in organizations, markets and society at large.

In the wine industry, maintaining superior quality standards is crucial to meet the expectations of both producers and consumers. Traditional approaches to assessing wine quality involve labor-intensive processes and rely on the expertise of connoisseurs proficient in identifying taste profiles and key quality factors. In this research, we introduce an innovative and efficient approach centered on the analysis of volatile organic compounds (VOCs) signals using an electronic nose, thereby empowering nonexperts to accurately assess wine quality.

To devise an optimal algorithm for this purpose, we conducted four computational experiments, culminating in the development of a specialized deep learning network. This network seamlessly integrates 1D-convolutional and long-short-term memory layers, tailor-made for the intricate task at hand. Rigorous validation ensued, employing a leave-one-out cross-validation methodology to scrutinize the efficacy of our design.

The outcomes of these e-demonstrates were subjected to meticulous evaluation and analysis, which unequivocally demonstrate that our proposed architecture consistently attains promising recognition accuracies, ranging impressively from 87.8% to an astonishing 99.41%. All this is achieved within a remarkably brief timeframe of a mere 4 seconds. These compelling findings have far-reaching implications, promising to revolutionize the assessment and tracking of wine quality, ultimately affording substantial benefits to the wine industry and all its stakeholders, with a particular focus on the critical aspect of VOCs signal analysis.

This research has not been published anywhere else.

This paper aims to delve into the critical examination of retractions in virology to identify the underlying factor that led to the retraction of scientific publications in this specialised domain. Further, this study offers insights into the impact of the retracted publications in the scholarly world vis-à-vis citation and Altmetric indicators.

The top 100 highly cited retracted articles from virology category were taken from the Web of Science (WoS) database. The Retraction Watch database was used for knowing the reasons for retraction for each retracted publication. The citation and Altmetric score of retracted publications were noted down from WoS and Altmetric.com databases, respectively. Journal Citation Report was used to note down the impact factor of the journals that have published these articles.

“Misconduct” (57.73%) is the most prevalent reason for the retraction of publications followed by plagiarism (18.55%) and journal issues (14.43%). The retracted papers are cited even after their retraction. Around 70.52% citations were received before and 29.47% after retraction. The highest number of retracted papers was published in the Journal of Virology (14) and Journal of Chemistry (10). High-impact factor journals such as Lancet, Cell and Nature each own one retracted paper. The study found dissemination of these publications through social media platforms with highest social media mentions (394) followed by policy and patents mentions (373) and news and blog mentions (300).

The research delves into understanding the reasons behind the retraction of virology papers and the impact of these publications through citation and Altmetric analyses. Its impactions include bolstering quality control in virology research, maintaining trust in scientific literature. Citation and Altmetric analyses offer deep insights into the broader impact of retracted papers, informing policy and publishing practices to uphold scientific integrity in virology.

This study addresses a specific and crucial aspect of scientific research retractions within the field of virology. While retractions have been studied in broader terms in scientific research, to the best of the authors’ knowledge, no such study has been conducted in the scientific field of virology.

This study explores the intricate relationship between social media communication, consumer attitude and purchase intention within the context of lifestyle category products. With the rapid proliferation of social media platforms, businesses have turned to these platforms to connect with consumers and influence their purchasing decisions. This study aims to provide an in-depth analysis of how social media communication strategies impact consumer attitudes and, in turn, influence purchase intentions.

The study employs partial least squares structural equation modeling (PLS-SEM) to analyze the data collected from a sample of consumers.

The results of this study present that lack of visibility (LV), low-efficiency levels (LEL) and unpredictable elements (UE) are ranked as the top three major risk hurdles whereas real-time information on a package’s location (LV1), putting a GPS tracking system to track last-mile journey (OT3) and users wants on time location of their package (LV2) are ranked as top three most significant criteria affecting the practices of modern last-mile logistics in e-commerce businesses.

The results of this study contribute to our understanding of how social media influences consumer behavior in the lifestyle product sector, shedding light on the underlying mechanisms that drive consumer purchasing decisions.

By constructing and testing experimentally a research model that reveals a thorough analysis of pertinent literature and identifies multiple important elements influencing consumer behavior in the lifestyle category, this paper adds to the body of knowledge on marketing. Practical ramifications for lifestyle firms are examined, along with suggestions for improving their social media tactics, in light of the findings.