Abstract: This paper describes the SMALLDERS project, a European initiative focused on designing and implementing new business models that strengthen the position of smallholders in the agri-food supply chain. Small farmers are considered the weaker link in the agri-food supply chain, and their vulnerability has been aggravated by recent crises such as the COVID-19 pandemic and the war in Ukraine. In this context, SMALLDERS project aims at designing and implementing a technological platform which, among other functionalities, will provide the small-scale farmers with innovative business models to improve their resilience. Various methodologies have been employed to achieve this objective: a systematic literature review to identify trends in agri-food business models, focus groups, surveys and in-depth interviews to gather perceptions from key stakeholders. As a result, three innovative business models were identified to be implemented in the platform by using the CANVAS methodology. Such implementation will allow to identify specific opportunities for smallholders and offer a valuable basis for strategic decision-making by all agents involved in the agri-food supply chain. Ultimately, the project provides an innovative and replicable approach to boost the economic and social sustainability of small farms in Europe.

Abstract: This research investigates the strategic decision related to original content provision and business model selection within the rapidly evolving online video industry. We develop a two-sided market model involving a video platform, users, and advertisers to analyze how the platform balances subscription and advertising revenue while offering original content. The study finds that the amount of original content provided directly influences market equilibrium, affecting the platform’s choice between a purely subscription-based model or a mixed model. The cost of original content production plays a critical role in this decision-making process. High production costs may lead the platform to favor a mixed model, offering less original content to generate both subscription and ad revenue. Lower costs, however, encourage a subscription model with more original content to boost subscribing revenue. Additionally, factors such as network externalities between users and advertisers also impact the business model choice. Notably, the model shows that allowing free users access to a portion of original content may help platforms expand both subscription and advertising revenue without needing to choose between them.

Abstract: Artificial Intelligence (AI) is transforming leadership and management across industries. This paper reviews recent literature on the intersection of AI and leadership, highlighting key trends, challenges, and future directions. This paper identifies critical gaps in current research and practice regarding the integration of Artificial Intelligence (AI) in leadership roles. It proposes potential solutions based on a review of recent literature. This paper systematically reviews current research on AI's role in leadership, identifying three key areas of impact: (1) enhanced strategic decision-making through human-AI collaboration, (2) evolution of leadership styles in digital environments, and (3) organizational challenges in AI adoption. Based on the peer-reviewed studies, we highlight significant improvements in decision accuracy and speed when combining AI tools with human judgment. The study reveals critical gaps in implementation, including cultural adaptation, ethical governance, and long-term effectiveness measurement. We propose practical frameworks for AI integration in leadership, emphasizing the balance between technological capabilities and human-centered values. Key findings demonstrate the growing importance of digital leadership competencies while underscoring persistent challenges in workforce adaptation and ethical considerations. The paper concludes with actionable recommendations for practitioners and identifies priority areas for future research, including sector-specific adoption strategies and standardized evaluation metrics for AI-enhanced leadership.

Abstract: Conflict is a common term in today’s personal and professional life, which means active disagreements between people with separate opinions. It is harmful when spread across the entire business organization, which is unavoidable while running a project. Moreover, conflicts that originate from too many emotional involvements of the team members mostly complicate the work environments. Hence, the obvious outcome is project failure. In this regard, the role of a project manager is very important while approaching any conflicting situation within a team with efficient time administration. This fact generates an urgent need for the project leaders to standardize professional, effective, and systematic ways of functional conflict managements with controlled emotions to obtain positive effects on time, cost, quality, and productivity of a project; though ways of approaching functional conflicts are very distinct for different personalities and situations. Hence, this manuscript emphasizes the development of conflict resolution tools, which are effective to prevent or manage functional conflicts while running a project, after a proper understanding of conflict dysfunctional issues through investigating the sources and emotional escalation factors. As well as the experiences of specific employees within different project teams of different multinational companies regarding conflict administration were collected from secondary data sources like census surveys, governmental data, the company’s website, and annual reports. Furthermore, a proper correlation of these data highlights the mode of conflict prevention through increasing concern about the behaviour and emotional triggers of the team members as well as the project managers themselves. Again, enhancement of understanding level is another essentiality for conflict competent project leaders to visualize conflict from an independent viewpoint in order to resolve any dispute within projects.

Abstract: There are many uncertainties in the process of technology projects “Unveiling and Commanding” system which can easily lead to the risk of failing to achieve the expected effect of technology quality. In order to ensure that the implementation of the system can achieve the expected results, the indicator system for risk assessment of technology projects “Unveiling and Commanding” system is established on the basis of expert interviews and field research. The improved game theory multiple combination weighting method is used to weight the indicators to reduce error risk of the weight results. This paper makes a comprehensive risk assessment of technology projects “Unveiling and Commanding” system from the two dimensions of risk possibility and risk impact degree based on two-dimensional cloud model, so as to reduce the subjectivity, randomness and fuzziness of assessment results. The example verifies that the model is reasonable and effective, and has a certain guiding role in the improvement of technology projects “Unveiling and Commanding” system.

Abstract: This research offers an in-depth examination of the financial consequences of the COVID-19 pandemic in Italy for small and medium-sized Food and Beverages Processing enterprises (SMEs) operating in the food and beverage sector. Leveraging financial and managerial data from the AIDA database, the study investigates both the immediate disruptions caused by the health crisis and the recovery patterns observed in its aftermath, aiming to clarify the sector's resilience and vulnerabilities.The analysis draws on an original sample of 1,600 SMEs, observed over a five-year span (2019–2022), with classifications based on firm size and geographical distribution. A range of financial performance indicators—including Return on Equity (ROE), Return on Investment (ROI), debt ratio, and production value per employee—was used to assess the evolution of corporate health before, during, and after the pandemic.The findings show a substantial downturn in profitability in 2020, with ROE plummeting most sharply in northern Italy (–147%), while southern areas and islands were less severely affected (–49%). ROI patterns revealed strained investment efficiency, with incomplete recovery by 2022. The debt ratio exceeded 70% during the height of the crisis, indicating strong reliance on external funding, although signs of gradual improvement emerged in 2023—especially among firms in the north. EBITDA, after contracting by 10% in 2020, experienced a significant rebound the following year, despite rising production costs, such as an 8.3% increase in labor expenses by 2022.A deeper examination reveals that smaller firms faced the greatest pressures during the crisis but demonstrated notable recovery potential by the end of the observation period. The strength of enterprises in northern Italy—both in terms of capital structure and post-pandemic resilience—underscores the role of regional factors in shaping economic recovery. The study ultimately highlights significant disparities in performance by firm size and location, emphasizing the need for targeted policies that promote long-term financial sustainability and improve sectoral preparedness for future shocks.

Abstract: This paper examines how an innovative MBA program integrates global business ecosystems into higher education, analysing its impact across five dimensions: curriculum development, industry partnerships, internationalization networks, graduate competency development, and regulatory recognition. Using a single-case qualitative methodology, the study demonstrates that embedding experiential learning, problem-based approaches, and business linkages within curriculum significantly enhances students' acquisition of strategic and practical competencies. The program's success is evidenced by performance metrics exceeding national standards and strong employability rates, with graduates demonstrating proficiency in project management, organizational leadership, and cross-cultural communication. While methodological limitations affect generalizability, the research offers valuable insights for institutions seeking innovative approaches to business education. The study concludes that systematically connecting learning with authentic commercial ecosystems prepares graduates who possess not merely theoretical knowledge, but the adaptability and strategic acumen required for leadership in today's globalized marketplace.

Abstract: Businesses are facing increasing pressure to transition to a sustainable economy, requiring the integration of environmental, social, and economic factors into their corporate strategies. Despite the proliferation of sustainability frameworks, many companies struggle to implement them effectively due to a lack of strategic focus. This study develops a taxonomy of critical success factors (CSFs) for implementing corporate sustainability strategies in production companies, addressing a gap in current research that often focuses on strategy design rather than practical execution. A systematic literature review was conducted to identify key factors influencing successful implementation and categorise them, providing a comprehensive understanding of their roles. The proposed taxonomy includes five dimensions: organisational culture, organisational structure, performance management, resources (including digitalisation and technology), and stakeholder integration (including sustainable supply chain management). An explanation is provided of the role of identified CSFs in the successful implementation of corporate sustainability strategies and their interrelationships. The taxonomy serves as a tool for production companies to manage internal factors that are critical to the successful integration of sustainability. This research contributes to the growing body of knowledge on sustainability by providing practical insights for effective strategy implementation, and calls for more empirical studies to explore this area further.

Abstract: This study analyzes the economic performance and entrepreneurial dynamics in mountain commerce in Europe during 2021-2022, using 28 economic indicators (I1–I28). The results highlight a series of mixed trends, showing signs of resilience but also major challenges. The sector demonstrated notable stability, maintaining the number of active enterprises (I1) and recording an increase in the business survival rate (I6–I9). Additionally, there was an improvement in productivity (I25–I27), indicating that many businesses adapted to market demands.However, significant difficulties were also present, such as business closures (I5) and challenges in accessing funding (I8), which impacted the development of small and micro enterprises. Dependence on seasonal employment (I21) remained a major limiting factor, and some segments of the sector recorded low revenues (I19–I20), reflecting economic challenges in certain areas.Despite these challenges, the sector continued to show signs of adaptability and long-term growth potential. Progressive digitalization (I24) and the implementation of eco-friendly practices (I25) offer significant opportunities for development. Entrepreneurs' adaptability, combined with the adoption of new technologies and sustainability practices, suggests a possible path for growth and strengthening mountain commerce in the long run, despite financial challenges and seasonality.

Abstract: Mountain entrepreneurship in trade faces specific challenges in mountainous regions, characterized by limited accessibility, poor infrastructure, and economic volatility. This sector plays a crucial role in local economic development, having a significant impact on employment and the preservation of local traditions. The article examines the performance of forecasting models used to estimate relevant economic indicators, such as the birth and death rates of businesses, the survival rate, and the impact on forced employment. The data used comes from official sources, and the analysis relies on advanced statistical techniques (RMSE, MAPE, MAE, etc.). The evaluated indicators reflected both the dynamics of mountain businesses and developments in the workforce. The results showed significant economic fluctuations, with notable forecast errors due to market instability and external conditions such as tax changes and natural conditions. The forecasting models demonstrated greater accuracy regarding long-term employment, and some mountainous regions presented significant opportunities for rapidly growing businesses. Despite the forecasting errors, the analysis provides valuable insights into understanding the economic dynamics of mountain entrepreneurship.

Abstract: Sustainable consumption indicates preferring products that do the least damage to the environment as well as those that support ethical behaviour. Therefore, this study refers and combines ethical and green issues to get a more holistic understanding of consumers’ sustainable practices. The author examines the green and ethical purchases of consumers in an exploratory base. Semi-structured in-depth interviews were carried out with 60 NRI and Resident Indian consumers. Results reveal that both Non-Resident and Resident Indian consumers believe that greenness is a part of ethical behaviour and convert their knowledge of corporate ethics into ethical purchase. Non-Resident Indian consumers have been aware of green issues for a long time now.

Abstract: Green entrepreneurship is a potent force in constructing a more sustainable future. Green entrepreneurs can drive breakthrough ideas, encourage the creation of sustainable businesses, and foster sustainable development through advocating sustainable behaviors and technology. This study addresses Climate Change and Environmental Issues, adding to the recent wave of research on green entrepreneurship. It evaluates empirically whether green economic, social, and environmental performance and green entrepreneurial activities are correlated. Every Maharashtrian entrepreneur or startup business owner who participates in the survey provides data. Structural Equation Modeling was used to statistically analyze the data and show the predictions made based on the literature research. The study's conclusions showed that green entrepreneurship has a favorable influence on green social, economic, and environmental performance. Also, the result shows that green social, economic, and environmental performance has a significant connection between the firms’ climatic change and environmental issues. The study recommends that entrepreneurs who are managing or want to launch new green businesses should receive help from policy initiatives. Policies should thus address other obstacles that green entrepreneurs have to conquer.

Abstract: Megaproject Front-End Engineering Design (FEED) crucially impacts lifecycle value, yet often lacks systematic methods to integrate multi-dimensional value drivers, including Environmental, Social, and Governance (ESG) factors, using advanced analytics. This research aimed to develop foundational knowledge and a methodological framework to address this gap. This study employed a quantitative approach using panel data (c. 2009-2023), merging country-level ESG indicators (World Bank) and house price indices (HPI) from OECD countries as an economic performance proxy. Analyses included multicollinearity assessment (Variance Inflation Factor), panel data regression (Pooled OLS, Fixed Effects, Random Effects with cluster-robust errors), and the development of a machine learning-based Automated Valuation Model (AVM) using Random Forest with lagged predictors. Uncertainty quantification (UQ) for the AVM was performed using Conformal Prediction. The Fixed Effects model (preferred via diagnostic tests; within-R² = 0.59) identified significant within-country correlations between HPI and specific ESG and economic factors (e.g., coastal protection, literacy rate, economic/social rights performance, energy imports/use, internet adoption, demographics). The Random Forest AVM achieved strong predictive performance on test data (R² = 0.87, RMSE = 6.88), with lagged indicators contributing significantly. Conformal Prediction reliably generated 90% prediction intervals with 90.8% empirical coverage. The study demonstrates the feasibility of a quantitative framework integrating diverse ESG and economic factors using panel regression and machine learning with UQ for analysis relevant to megaproject FEED. This provides essential groundwork for developing future automated, data-driven decision support tools to enhance holistic value assessment.

Abstract: Purpose - The manufacturing sector drives industrialisation and contributes substantially to economic growth and employment creation. Despite this, it faces challenges of diminishing size and lack of competitiveness, mainly due to operational uncertainty. This study aims to develop an approach to managing operational uncertainty with Industry 4.0 and 5.0 technologies.Design /methodology/approach - The study employed a multimethod quantitative design based on the post-positivist paradigm, with data collected from 22 experts and 262 responses from a manufacturing firms' survey. It uses an integrated fuzzy decision-making trial and evaluation laboratory (DEMATEL) with structural equation modelling partial least squares (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA). Findings - The results reveal that growing geopolitical tension, cost of living-driven consumer behavioural change, pandemic turbulence, lack of energy stability and security, and entrenchment power of large firms are causal dimensions of operational uncertainty. Industry 4.0 and 5.0 technologies with capabilities for scenario planning and supply chain integration, flexible production and mass customisation, real-time system and process monitoring and response, root cause analysis, and sustainable solutions can manage operational uncertainty. These technologies are artificial intelligence, the Internet of Things, big data analytics and, to a lesser extent, advanced robotics, blockchain, and augmented and virtual reality.Originality - The study advanced the modified neo-configuration theory and a new integrated methodology (fuzzy-DEMATEL-PLS-SEM-fsQCA) to develop solutions for sustained performance during operational uncertainty in manufacturing. This research offers valuable information to advance the subject and make meaningful changes in day-to-day manufacturing operations and promote practical real-world issue solving.

Abstract: This study examines the impact of strategic alliances on organizational performance in Malawi's commercial state-owned enterprises (SOEs). Using a descriptive survey design with data from 37 SOEs, the research investigates four types of strategic alliances: resource sharing, risk sharing, regulatory compliance, and cost efficiency. The findings reveal a strong positive correlation (R=0.942) between strategic alliances and organizational performance, with these partnerships explaining 88.7% of performance variation. Regulatory compliance-based alliances demonstrated the most substantial impact (β=1.171), followed by cost efficiency (β=0.454), risk sharing (β=0.369), and resource sharing alliances (β=0.321). The study concludes that strategic alliances represent a viable approach for revitalizing underperforming SOEs in Malawi, enhancing competitiveness, improving fiscal stability, and fostering sustainable growth, ultimately contributing to national socioeconomic advancement.

Abstract: This study investigates the influence of Human-AI collaboration and digitalization strategies on Green Environmental, Social, and Governance (ESG) performance, examining the moderating role of Corporate Social Responsibility (CSR). Using a comprehensive dataset of 3,600 firm-year observations from Chinese listed companies between 2016 and 2023, we employ multiple regression analyses to test our hypotheses. Our findings reveal that firms with higher levels of Human-AI integration demonstrate significantly enhanced green ESG performance (β = 0.318, p < 0.01). Additionally, digitalization intensity positively correlates with improved environmental metrics (β = 0.245, p < 0.01). Notably, CSR commitment strengthens these relationships, with the interaction effect being particularly pronounced for firms operating in environmentally sensitive industries. These results offer important implications for managers seeking to leverage technological integration while balancing sustainability objectives, and contribute to the growing literature on technology-driven environmental management practices in emerging economies.

Abstract: Selecting an appropriate business development model is central to strategic decision-making in economic and business management. These models shape sustainable growth, long-term scalability, and strategic flexibility. Existing evaluation methods rely on heuristic or qualitative judgments that lack transparency, reproducibility, and sensitivity to evaluation criteria. To address these limitations, this study introduces a hybrid multi-criteria decision-making (MCDM) framework that integrates VIKOR, entropy weighting, and simulation to evaluate 35 business development models derived from 245 real-world cases. Evaluation covers six strategic criteria: scalability, adaptability, risk exposure, financial sustainability, implementation complexity, and market relevance. Entropy weighting assigns criterion importance based on data variability, and simulation generates input sets for sensitivity and stability analysis. Results highlight Cross-Border Investment, Tiered Access, and Crowd-Backed models as top-performing strategies across multiple dimensions. By combining multiple tools in a unified framework, the research advances MCDM methodology and supports strategic business development planning under uncertainty. This contribution strengthens both academic insight and managerial practice in economics and business management.

Abstract: The main aim of this study was to examine the role financial management practices play in promoting the rapid growth of micro, small, and medium enterprises (MSMEs) in Lusaka’s central business District (CBD), specifically those operating in the retail sector. Its aims were to identify the type of financial management practices utilized by MSMEs, assess whether these practices contribute to their growth, and examine the challenges they face when implementing financial management practices (FMPs). A mixed-method case study design was adopted and data was obtained through questionnaires and interviews. A sample size of 361 businesses was derived from a population of 6000 MSMEs. Using SPSS, a single factor ANOVA test was carried out, and the results showed a P- means of 0. 417229.Which is greater than the 0.05 significant level, and observed F-statistic of 0.982723, is not even close to exceeding critical value, which above is 2.402775. Based on these results we failed to reject the null hypothesis, which proves that different financial management practices will promote MSMEs expansion. Furthermore, financial reporting and analysis emerged as one of the most frequently utilized practice. Among the financial management practices identified Risk management received less attention, indicating a significant imbalance in the adoption of financial techniques. The study concludes that sound financial management practices are critical for MSMEs growth, stability, and availability of finance. However, addressing the challenges faced by MSMEs requires targeted actions. Recommendations include encouraging MSMEs owners to adopt basic financial tools, government-led financial management training for MSMEs in Lusaka CBD, and carrying out additional research to explore the impact of formal financial practices on MSMEs performance and resilience.

Abstract: This study investigates the relationship between Corporate Social Responsibility (CSR) initiatives and Green Environmental, Social, and Governance (ESG) performance, with a particular focus on how Human-AI interaction moderates this relationship. Likewise, using panel data of Chinese listed firms from 2018 to 2022, we analyze 3,900 firm-year observations obtained from Wind and CSMAR databases. Our findings reveal a significant positive association between CSR engagement and Green ESG performance. More importantly, we find that Human-AI interaction significantly enhances this relationship, suggesting that firms leveraging AI technologies in their CSR implementation achieve superior Green ESG outcomes. Additional analyses reveal that this moderating effect is more pronounced in industries with higher pollution intensity and for firms with greater institutional ownership. This research contributes to the literature by identifying an important technological moderator in the CSR-ESG relationship and provides practical implications for corporate sustainability strategies in the digital era.

Abstract: This study investigates the role of artificial intelligence in enhancing supply chain resilience, drawing insights from industry experts to understand the transformative potential and challenges of AI adoption in supply chain management. In recent years, supply chains have faced unprecedented disruptions due to global crises, technological shifts, and evolving consumer demands, making resilience a critical focus. AI technologies, including machine learning, predictive analytics, and real-time data processing, have emerged as vital tools for maintaining continuity and improving decision-making under uncertainty. This research employs a qualitative methodology, engaging with 15 industry experts to gather in-depth perspectives on how AI is being integrated into supply chain practices and the tangible impacts observed. The thematic analysis of expert insights reveals that AI significantly contributes to risk mitigation, supply chain visibility, and adaptive planning. By harnessing real-time data, AI systems enable proactive responses to disruptions, enhancing operational agility. Moreover, AI-driven optimization techniques improve logistics efficiency, while predictive analytics support accurate demand forecasting and inventory management. Despite these advantages, the research identifies several barriers to successful AI implementation, including high initial costs, data integration challenges, and concerns regarding data privacy and workforce adaptation. Addressing these issues requires a strategic, phased approach to technology integration, fostering collaboration between AI developers, supply chain professionals, and policymakers to create sustainable and resilient systems. The study concludes that while AI offers substantial benefits for supply chain resilience, its successful implementation demands a balanced approach that considers technological, organizational, and ethical dimensions. Future research should focus on developing practical frameworks for AI adoption and assessing long-term impacts on supply chain sustainability and workforce dynamics.