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This paper aims to deepen the understanding of robust food supply chains (FSC) in SMEs by exploring and analyzing the literature through the lenses of digital technologies.

The study collected data from Scopus spanning from 2010 to 2024, employing selected keywords, and processed it using VOS-viewer and Biblioshiny to derive valid inferences and theoretical arguments.

The review paper identified several key themes shaping the future of supply chain management – Sustainability in SCM, Industry 4.0, Digitalization with FSCM, Circular Economy, Food Waste with Supply Chain, Food Security and Climate Change. These themes collectively bring transformative opportunities for both the adoption of digital technologies and sustainable practices in food supply chains.

The review found limitations are rooted in financial constraints, institutional barriers and expertise-related challenges encountered within the realm of Digitalization and FSC. Government and corporate houses should focus on these limitations as well as convert them to strengthen the SMEs of FSC.

The study stands out as a pioneering review that not only explores Digitalization in FSC but also explores the link and evidence of SMEs in the unorganized sector, providing unique insights into a previously underexplored area.

Healthcare has undergone multiple phases in gaining understanding, accepting and implementing quality and safety, with the last 3 decades being crucial and decisive in making progress. During that time, safety has always been quoted along with quality, but the cost of error in healthcare (both in human lives and monetary cost) has been continuing to rise.

This article discusses the authors’ expert perspective in comparison to the industry’s research and practice outputs.

Healthcare has not yet defined quality and safety. This is allowing the misconception that already established quality management systems (QMSs) are fit for safety purposes as well. Even though aviation has acted as a paradigm for healthcare, further alignment in embedding safety management systems (SMS) has yet to be realised.

In this paper, the distinct nature of safety and its detachment of quality is being discussed, along with the need for clear and safety specific processes. Setting common language is the first step in establishing appropriate safety processes within SMSs, operating in tandem with QMSs, to promote patient safety successfully.

Maritime transportation plays an important role in facilitating both the global and regional merchandise trade, where accurate trend prediction is crucial in assisting decision-making in the industry. This paper aims to conduct a macro-level study to predict world vessel supply and demand.

The automatic autoregressive integrated moving average (ARIMA) is used for the univariate vessel supply and demand time-series forecasting based on the data records from 1980 to 2021.

For the future projection of the demand side, the predicted outcomes for total vessel demand and world dry cargo vessel demand until 2030 indicate upward trends. For the supply side, the predominant upward trends for world total vessel supply, oil tanker vessel supply, container vessel supply and other types of vessel supply are captured. The world bulk carrier vessel supply prediction results indicate an initial upward trend, followed by a slight decline, while the forecasted world general cargo vessel supply values remain relatively stable. By comparing the predicted percentage change rates, there is a gradual convergence between demand and supply change rates in the near future. We also find that the impact of the COVID-19 pandemic on the time-series prediction results is not statistically significant.

The results can provide policy implications in strategic planning and operation to various stakeholders in the shipping industry for vessel building, scrapping and deployment.

The current scenario shows increased adoption of off-chain voting applications in decentralized autonomous organizations (DAOs) to avoid complexity and costs for user engagement in their governance. This paper aims to comprehend the trends and patterns within the DAO community with off-chain voting systems and blockchain usage.

This exploratory study uses a two-pronged quantitative approach, combining descriptive statistical analysis and fuzzy-set qualitative comparative analysis. Input data from different DAO proposals and votes were analyzed.

Results indicate that the 179 DAOs analyzed account for 26,538 proposals and 1,268,474 followers of the entire Snapshot base in January 2023, showing high concentration in engagement. The preferred social media communication channels are Twitter and GitHub, showing a decrease of Ethereum as a main chain, with Polygon and Binance Smart Chain already accounting for 22%. Basic voting can lead to greater user involvement in the voting process.

This study complements the traditional governance theory perspective and advances in the emerging literature on DAOs and blockchain with an empirical analysis.

As blockchain technology gains increasing adoption, comprehending trends and patterns within the DAO community becomes pivotal in identifying opportunities and challenges for innovation and improvement.

Findings can facilitate the development of improved governance models and decision-making processes for DAOs, leading to a more robust and sustainable ecosystem.

This study presents a broader IT-based governance foresight via blockchain while providing an understanding of the voting process, technology features and governance mechanisms for social community engagement and decision-making in DAOs.

Although it is commonly agreed that prescriptive analytics can benefit organizations by enabling better decision-making, the deployment of prescriptive analytics tools can be challenging. Previous studies have primarily focused on methodological issues rather than the organizational deployment of analytics. However, successful deployment is key to achieving the intended benefits of prescriptive analytics tools. Therefore, this study aims to identify the enablers of successful deployment of prescriptive analytics.

The authors examine the enablers for the successful deployment of prescriptive analytics through five organizational case studies. To provide a comprehensive view of the deployment process, each case includes interviews with users, managers and top management.

The findings suggest the key enablers for successful analytics deployment are strong leadership and management support, sufficient resources, user participation in development and a common dialogue between users, managers and top management. However, contrary to the existing literature, the authors found little evidence of external pressures to develop and deploy analytics. Importantly, the success of deployment in each case was related to the similarity with which different actors within the organization viewed the deployment process. Furthermore, end users tended to highlight user participation, skills and training, whereas managers and top management placed greater emphasis on the importance of organizational changes.

The results will help practitioners ensure that key enablers are in place to increase the likelihood of the successful deployment of prescriptive analytics.

Approaching mentoring from the theoretical tradition of continental pedagogy and contrasting it to the neoliberal organization of the academy, this paper aims to analyze how the Croatian higher education document framework constructs mentoring graduate and postgraduate students' research projects.

The analysis of 50 national- and university-level documents, which were coded using an adapted strategy described by Saldaña (2014), was guided by the following research questions. 1. Which elements of the mentor’s activity in guiding the research projects of graduate and postgraduate students are addressed by the relevant Croatian higher education documents? 2. Which elements of the graduate and postgraduate students’ activity in conducting research projects are addressed? 3. Which structural dimensions of mentoring these research projects are addressed?

The results point to the construction of mentoring as a pedagogical relationship based on guidance, support and dialog and also signal the processes of quantification of education and responsibilization of individuals.

The results can be used in the critical revision of the documents as well as in supporting mentors in their professional roles.

This is the first analysis of the Croatian higher education document framework focused on mentoring students’ research projects.

Given the interest in sustainable development, this study aims to assess the relationship between CO₂ and urbanization as well as the role of world uncertainty in this association in a South African context.

This study focuses on yearly data from 1968 to 2020. To do this, the authors use the autoregressive distributed lag (ARDL) approach.

The authors find that urbanization’s effect on CO₂ emissions is only significant when it is augmented with world uncertainty. Moreover, this effect is negative (referring to a reduction in CO₂ emissions). Meanwhile, the authors find that GDP has a positive (that is, increasing) and significant effect on CO₂ emissions. Overall, policymakers should focus on decoupling economic growth from traditional fossil fuels that produce greenhouse gas emissions.

The existing body of research contains numerous studies examining the relationship between urbanization and CO₂ emissions. However, the dearth of research on the impact of global uncertainty on this connection is weak. Hence, this study aims to fill this gap and make a significant contribution to the field.

The aim of this paper is to determine whether the dominant integrated water resources management (IWRM) paradigm within which the Pra River Basin is managed holds the key to address the current water security and sustainability issues in Southwestern Ghana.

This study employed a literature review developed based on water security and sustainability studies as well as normative scenarios from the broad scenario planning methodology. The study builds on Wæver’s Theory of Securitization and the Utilitarian theory to protect water bodies through the use of artificial intelligence (AI).

Insights on introducing innovative environmental sustainability technology are presented and propose the Pra-integrated smart water security management decision-making system that uses visual inspections, noise sensors, the potential of hydrogen (pH) probe sensor, real-time collection of hydrological data (streamflow) and wireless transmission of the data in real-time at the basin level. This serves as a robust tool for managing the basin’s sustainable development ecosystem by using AI to protect water bodies against illegal mining.

The proposed innovative environmental technology which is the first of its kind is meant to gain a better understanding of pollution incidents and respond quickly to them by integrating AI and Internet of Things (IoT) technologies with traditional IWRM practices. This addresses water security in the Pra Basin, supports policy development and innovation, strengthens the goal of the government to protect water resources against pollution and contributes to the African Water Vision and the United Nations’ Agenda 2030 Sustainable Development Goals 3 and 6.

The purpose of this paper is to perform a thorough analysis of the literature on the parameters of sustainability of the micro-enterprises. It seeks to provide an organizing framework to identify research gaps and future directions. Using data from Web of Science and Scopus, the study offers insights into key trends, authorship and thematic shifts, informing future research design and positioning.

Researchers used a systematic review methodology, gathering data from Web of Science and Scopus databases. R Studio software facilitated bibliometric analysis. This study scrutinized research papers to construct an organizing framework and identify thematic trends in sustainability parameters for micro-enterprises.

The review presents a comprehensive overview of sustainability parameters in micro-enterprises, revealing significant research trends, key authors, countries and journals. It identifies gaps and suggests future research directions, aiding in the design and positioning of forthcoming studies in this domain.

Limitations may include the scope of databases accessed and potential biases in the selected literature. Future studies could explore additional databases or incorporate qualitative analyses for deeper insights into sustainability parameters in micro-enterprises.

This study offers practical insights for policymakers, practitioners and researchers by highlighting key sustainability parameters in micro-enterprises. It informs decision-making processes concerning resource allocation, policy formulation and support mechanisms for sustainable development.

Understanding sustainability parameters in micro-enterprises has significant social implications, particularly for vulnerable groups like craftsmen, women and young entrepreneurs. By addressing these parameters, interventions can enhance livelihoods and contribute to broader socio-economic development.

By providing a thorough analysis of sustainability factors in micro-enterprises and applying bibliometric analysis to shed light on research trends, this paper adds to the body of literature. Its organized framework identifies gaps and guides future research, offering value to scholars, policymakers and practitioners invested in sustainable development at the grassroots level.

The Indian stock market can be tricky when there's trouble in the world, like wars or big conflicts. It's like trying to read a secret message. We want to figure out what makes investors nervous or happy, because their feelings often affect how they buy and sell stocks. We're building a tool to make prediction that uses both numbers and people's opinions.

Hybrid approach leverages Twitter sentiment, market data, volatility index (VIX) and momentum indicators like moving average convergence divergence (MACD) and relative strength index (RSI) to deliver accurate market insights for informed investment decisions during uncertainty.

Our study reveals that geopolitical tensions' impact on stock markets is fleeting and confined to the short term. Capitalizing on this insight, we built a ground-breaking predictive model with an impressive 98.47% accuracy in forecasting stock market values during such events.

To the best of the authors' knowledge, this model's originality lies in its focus on short-term impact, novel data fusion and high accuracy. Focus on short-term impact: Our model uniquely identifies and quantifies the fleeting effects of geopolitical tensions on market behavior, a previously under-researched area. Novel data fusion: Combining sentiment analysis with established market indicators like VIX and momentum offers a comprehensive and dynamic approach to predicting market movements during volatile periods. Advanced predictive accuracy: Achieving the prediction accuracy (98.47%) sets this model apart from existing solutions, making it a valuable tool for informed decision-making.