Purpose: This study investigates the effect of macroeconomic uncertainty, namely inflation, money supply, long-term interest rates and the real effective exchange rate, on the return volatility of four South African exchange-traded funds listed on the Johannesburg Stock Exchange, addressing a gap in emerging-market ETF volatility literature. Methodology: Monthly data from November 2010 to December 2025 were analysed using univariate GARCH, GJR-GARCH, and E-GARCH models, with model selection guided by the Schwarz information criterion and robustness confirmed via ARCH-LM, unit root, and Nyblom stability tests. Results: All four ETF indices exhibit ARCH effects and volatility clustering; for three of the four ETFs, positive return shocks increase volatility more than negative shocks of equal magnitude, and inflation, money supply, and long-term interest rate growth significantly raise volatility only for the STXSWX index. Theoretical contribution: The paper extends the largely spillover-focused literature on South African ETF volatility by isolating the direct macroeconomic drivers of volatility, offering an emerging-market counterpoint to studies concentrated on developed markets. Practical implications: Findings suggest that passive investors and fund managers should treat the STXSWX index with caution during periods of macroeconomic instability and factor asymmetric shock behaviour into portfolio rebalancing decisions. Sustainable Development Goals (SDGs): SDG 8: Decent Work and Economic Growth; SDG 9: Industry, Innovation and Infrastructure; SDG 10: Reduced Inequalities
Purpose: Automation often displaces workers without adequate retraining, leading to unemployment and reduced income tax contributions, which worsens income inequality. This study explores the rationale for implementing a robot tax to mitigate these effects. Design/Methodology/Approach: Using a pragmatic research philosophy, the study conducts a qualitative scoping review following the framework of Arksey and O’Malley to examine the existing literature on the topic. Findings: Automation reduces employment-based tax revenue and increases public financial pressure. A robot tax is proposed to offset lost income tax revenue, fund workforce retraining, and address tax policy biases that favour capital over labour. This approach supports responsible automation, reduces inequality, and fosters sustainable economic growth. Implications/Originality/Value: The study contributes to a limited body of research on robot taxation and offers guidance on adapting tax systems to technological change. It serves as a resource for policymakers and researchers addressing the economic and social impacts of robotics, artificial intelligence, and automation. Sustainable Development Goals (SDGs): SDG 8: Decent Work and Economic Growth; SDG 10: Reduced Inequalities; SDG 17: Partnerships for the Goals
Purpose. This study synthesizes empirical and methodological evidence on human resource data analytics to provide a practical, decision-oriented blueprint for people management aligned with the United Nations Sustainable Development Goals (SDGs). Methodology. An integrative, PRISMA-compliant systematic review of 20 highly relevant peer-reviewed sources published between 2021 and 2026 was conducted. The synthesis evaluates three core analytical workstreams – Employee Net Promoter Score (eNPS) monitoring, 360-degree feedback, and prescriptive recruitment optimization – mapping extracted evidence onto specific decision interfaces. Due to the methodological heterogeneity of the corpus, a structured narrative synthesis was utilized to evaluate the alignment of data-driven interventions with sustainability targets. Results. Descriptive metrics such as eNPS function most effectively as continuous early-warning signals for retention intention rather than isolated diagnostic tools. Multi-rater 360-degree feedback yields reliable developmental signals exclusively when embedded in structured programs and structurally decoupled from compensation decisions. Furthermore, prescriptive optimization in recruitment generates measurable operational gains, particularly when algorithmic fairness mandates, budget constraints, and organizational capacity limits actively constrain predictive algorithms. Theoretical contribution. The study advances a structured analytical pipeline that bridges the operational gap between technical predictive modeling and corporate social responsibility. It establishes ethical data governance and epistemic alignment as mandatory preconditions for deploying advanced people analytics, integrating previously fragmented literature on digital human resource transformation. Practical implications. Organizations can implement the proposed five-stage blueprint - defining business objectives, specifying decision points, selecting minimal viable data, validating on decision horizons, and embedding governance rails – to convert raw workforce data into traceable, repeatable interventions. This framework directly supports the promotion of decent work (SDG 8), the reduction of algorithmic inequalities (SDG 10), and the establishment of transparent, accountable institutional data governance (SDG 16). SDG 8: Decent Work and Economic Growth; SDG 10: Reduced Inequalities; SDG 16: Peace, Justice and Strong Institutions
Purpose: This study examines how health insurance coverage and medical cost burden, alongside key socioeconomic and demographic factors, predict financial vulnerability in the United States, with implications for sustainable household financial protection aligned with SDG 3.8. Methodology: A repeated cross-sectional design was employed, using three waves of the US National Financial Capability Survey (NFCS: 2018, 2021, 2024), covering the pre-pandemic, post-pandemic, and recovery periods, respectively. A multidimensional Financial Vulnerability Index (FVI) was constructed following a three-dimensional framework (sensitivity, resilience, exposure) and operationalised as a binary variable using a composite standardised scoring approach. Binary logistic regression models with pairwise comparisons among all predictor categories were estimated for each survey wave. Results: Uninsured individuals face 37-50% higher odds of financial vulnerability relative to uninsured counterparts, while individuals with high medical cost burdens face over four times the odds (OR = 4.18-5.34) across the survey waves. Household income emerges as the single most powerful predictor, with individuals earning less than $25,000 being 8.83 to 16.0 times more likely to be financially vulnerable than those earning $200,000 or more. Education, financial literacy, and household dependency exhibit threshold effects: meaningful protective differences emerge only upon attainment of university-level education or reduction to zero dependents. Theoretical contribution: The study extends Grossman's (1972) Health Capital Model into the domain of financial vulnerability by demonstrating that market-based health financing structures interact with socioeconomic position to generate structural exposure to financial hardship. Rather than adopting a unidimensional index, the application of multidimensional FVI in this study advances methodological practice in financial vulnerability research and reveals threshold effects previously masked in the literature. Practical Implications: The findings call for health and fiscal policy frameworks that extend beyond aggregate economic metrics to address distributional consequences of health financing arrangements. Targeted interventions, including expanded insurance coverage, income support for low-income households, financial literacy programmes, and strengthened social protection for working-age adults, are identified as critical for reducing persistent financial vulnerability and advancing financial sustainability. Sustainable Development Goals (SDGs): SDG 3: Good Health and Well-being; SDG 10: Reduced Inequalities; SDG 1: No Poverty
Purpose. This paper assesses the climate vulnerability of 400 smallholder farming households in rural Gambia by integrating exposure, sensitivity, and adaptive capacity into a composite vulnerability index, providing policy-relevant insights for climate-resilient development. Methodology. Household survey data from three rural regions (North Bank, Central River, Upper River) are analyzed using Principal Component Analysis (PCA) to derive data-driven weights for 23 indicators. The index is validated through associations with NGO support, government assistance, insurance, credit access, and agricultural extension. Results. North Bank exhibits the highest vulnerability (VI = -6.37) driven by low adaptive capacity despite minimal climate exposure. Upper River shows lower vulnerability (VI = +1.56) despite high climate exposure, owing to better socio-economic conditions. Validation reveals that NGO support and insurance reduce vulnerability (r = -0.82, -0.94), whereas government support paradoxically correlates positively (r = 0.79), likely reflecting endogenous targeting. Theoretical contribution. The study advances vulnerability assessment literature by applying PCA-based weighting to household-level data in a low-income African context, demonstrating that adaptive capacity is more decisive than biophysical exposure. Practical implications. Findings emphasize prioritizing investments in education, infrastructure, credit, and insurance over exposure-focused interventions. The index supports policy prioritization under Gambia’s Nationally Determined Contributions and National Adaptation Plans, enabling regional differentiation of adaptation strategies. Sustainable Development Goals (SDGs): SDG 1: No Poverty, SDG 2: Zero Hunger, SDG 13: Climate Action
Purpose: This paper develops a reproducible algorithmic protocol, the PRISM-Bridge Model, that converts comprehensive marketing audit findings into a transparent, sequenced, and measurable action plan in consulting engagements. Crucially, the framework explicitly embeds measurement readiness and strategic sustainability logic into prioritization decisions, aligning short-term corporate actions with Environmental, Social, and Governance (ESG) criteria and the United Nations Sustainable Development Goals (specifically SDGs 8, 9, and 12). Methodology: The study employs a conceptual-development design grounded in a structured synthesis of established research streams, including marketing audit theory, multi-criteria decision analysis (AHP), and sustainable business strategy. To validate the mechanics of the algorithm without overstating empirical claims, the framework is applied to an illustrative demonstration backlog of 30 typical digital marketing and consulting initiatives. Results: The proposed algorithm produces four interconnected deliverables: a structured intervention register, a weighted multi-criteria priority score (combining impact, effort, risk, dependency load, and sustainability alignment), a dependency-aware three-phase roadmap, and a constrained quick-win portfolio. Demonstration results confirm that the model systematically prevents the execution of initiatives that conflict with sustainable organizational development, while maintaining strategic breadth. Practical and Theoretical Implications: Theoretically, the study addresses a persistent integration gap by unifying audit diagnostics, multi-criteria prioritization, and sustainable execution into a single decision-and-delivery architecture. Practically, the PRISM-Bridge Model provides consulting teams with a reusable governance instrument that reduces arbitrariness in early project decisions, improves client explainability, and establishes a practical bridge between diagnostic audits and performance-oriented execution aligned with long-term sustainable development. Sustainable Development Goals (SDGs): SDG 8: Decent Work and Economic Growth; SDG 9: Industry, Innovation and Infrastructure; SDG 12: Responsible Consumption and Production
Purpose. The purpose of this study is to develop an integrative theoretical framework for medical wellness tourism (MWT) that bridges the tri-sectoral convergence of healthcare management, hospitality operations, and sustainable development governance, domains that have historically evolved in scholarly isolation, producing a body of literature that treats the medicine-hospitality relationship as additive rather than constitutive. Methodology. A systematic narrative literature review was conducted across Scopus, Web of Science, and PubMed (2019–2026). Following PRISMA 2020-compliant screening and PICOS-R-structured inclusion criteria, the final analytical corpus comprised 183 sources (47 core peer-reviewed works). Thematic analysis followed the six-phase Braun and Clarke framework; inter-rater reliability was confirmed at weighted κ = 0.84. Content validity of the coding instrument was assessed using S-CVI/Ave, yielding a score of 0.91. Results. The Integrated Medical Wellness Tourism Convergence Framework (IMWTCF) was developed as a four-layer hierarchical model grounded in Service-Dominant Logic, the Resource-Based View, and the Business Model Canvas. Three business model archetypes were profiled using the MWT Value Creation Index (MWT-VCI): the Medical Hotel (7.33), the Wellness Resort (6.78), and the Digital Platform (6.25). Clinical integration (w = 0.45) emerged as the dominant value driver, generating a 17.3% MWT-VCI advantage for the Medical Hotel despite the Digital Platform's superior digital readiness. SDGs 3, 8, and 12 were confirmed as the natural sustainability cluster for MWT governance. Theoretical contribution. The IMWTCF operationalises tri-sectoral convergence as a legitimate unit of strategic analysis and demonstrates structural complementarity among S-D Logic (value co-creation), RBV (competitive durability), and the Business Model Canvas (operational architecture). Five formally grounded research propositions advance a testable framework for subsequent PLS-SEM validation. Practical implications. MWT enterprise managers should sequence digital investment after clinical integration, as each unit improvement in clinical capability yields 1.8× greater MWT-VCI gain than an equivalent digital upgrade. Policymakers are directed toward cluster-based governance as the primary instrument for overcoming regulatory fragmentation, the highest-severity barrier to MWT convergence, with particular relevance to post-conflict reconstruction contexts such as Ukraine's balneological corridor. Sustainable Development Goals (SDGs): SDG 3: Good Health and Well-Being; SDG 8: Decent Work and Economic Growth; Industry, Innovation and Infrastructure; SDG 12: Responsible Consumption and Production
Purpose: The continuous unresolved debate that arises between traditional finance and behavioural finance frameworks has dominated empirical literature in recent years. Despite this, the limited literature extends the debate to size-based indices, especially in emerging markets like South Africa that are characterised by alternating market conditions and sentiment-induced markets. Consequently, the objective of this study is to examine the effect of market-wide investor sentiment on the Johannesburg Stock Exchange (JSE) size-based indices’ returns at bullish/bearish market conditions. Methodology: The Markov regime-switching model for the period April 2007 to March 2025 reveals that market-wide investor sentiment has a regime-specific and time-varying effect on JSE size-based indices’ returns. In bullish/bearish market conditions, investor sentiment has a positive significant effect on JSE size-based indices’ returns. However, the magnitude of such effects seems too great in bearish market conditions. Similarly, the JSE size-based indices’ returns are dominated by the bearish market condition, revealing its non-resilient nature to sentiment-induced markets and market fluctuations. Theoretical contribution: The study contributes to resolving the debate in literature that arises from the efficient market hypothesis and behavioural finance frameworks, by demonstrating that JSE size-based indices present adaptive behaviour as supported by the adaptive market hypothesis. Practical implications: Investors must factor in changing market conditions and sentiment levels in the market when determining whether to invest in JSE sized-based indices as it will contribute positively or negative to prospect returns. Policymakers must devise new policy reforms that curb unstable market conditions and noise trading as it contributes directly to alternating market efficiency. Sustainable Development Goals (SDGs): SDG 8: Decent Work and Economic Growth; SDG 10: Reduced Inequalities; SDG 16: Peace, Justice and Strong Institutions
Abstract: Purpose. This study examines the influence of demographic factors on personal income tax (PIT) compliance among taxpayers in Mbombela, Mpumalanga, South Africa, to address persistent revenue shortfalls that undermine government fiscal capacity. Methodology. Employing a positivist research philosophy and cross-sectional survey design, the study utilized a random sample of 103 taxpayers from a population of 2,679 registered taxpayers. Data were collected through a structured questionnaire and analyzed using descriptive statistics and multiple regression analysis in SPSS and STATA. The Slippery Slope Framework, Fiscal Exchange Theory, and Political Legitimacy Theory provided the theoretical foundation. Results. Regression analysis revealed that only employment status (β = 0.168, p < 0.001) and monthly income (β = 0.099, p = 0.001) significantly influence tax compliance. Age, gender, educational background, household size, and SARS registration did not demonstrate significant effects (p > 0.05). Descriptive analysis revealed pervasive non-compliance: 60.2% of respondents reported failing to pay all taxes owed, and 62.1% admitted to incomplete income disclosure. Theoretical contribution. This study challenges conventional assumptions regarding demographic determinants of tax compliance, demonstrating that structural factors - particularly PAYE withholding mechanisms - outweigh individual demographic characteristics. The findings support the Slippery Slope Framework’s emphasis on power-based enforcement while highlighting that institutional legitimacy deficits, rather than demographics, drive non-compliance. Practical implications. Results indicate that SARS and policymakers must extend interventions beyond demographic targeting to address institutional legitimacy, perceived fiscal reciprocity, and equitable enforcement. Recommendations include extending PAYE-style withholding to additional income sources, enhancing transparency, and developing sector-specific compliance strategies. Originality/value. This study provides the first systematic empirical analysis of demographic determinants of PIT compliance in Mbombela, Mpumalanga, demonstrating that institutional factors merit greater attention than demographic segmentation in compliance enhancement strategies. Sustainable Development Goals (SDGs): SDG 16: Peace, Justice and Strong Institutions; SDG 10: Reduced Inequalities; SDG 8: Decent Work and Economic Growth
Purpose. This paper develops a measurement protocol for evaluating organic social media distribution as a resource-efficient alternative to paid advertising in professional service entrepreneurship. Focusing on business coaching, we operationalize how cross-platform short-form video strategies can be measured through sustainability lenses: economic viability, resource efficiency, and labor conditions. Methodology. We synthesize 25+ empirical studies spanning influencer credibility, platform dynamics, and sustainable entrepreneurship. From this synthesis, we construct a field-ready protocol operationalizing four intervention domains: (1) cross-platform posting without paid amplification, (2) standardized identity cues, (3) psychological friction management, and (4) technical production standards. The protocol specifies variable definitions, data collection procedures, fidelity coding rules, and statistical analysis plans. Theoretical contribution. The protocol integrates influencer marketing theory, platform studies, and entrepreneurship research into a unified framework in which content creation functions simultaneously as a distribution mechanism, a trust-building intervention, and a sustainable business practice. By treating organic distribution as economic sustainability question, we extend sustainable entrepreneurship scholarship into the digital creator economy. Practical implications. For entrepreneurs, the protocol translates credibility constructs into measurable behaviors and testable outcomes. For researchers, it provides standardized procedures enabling rigorous field studies examining whether organic strategies generate economically viable lead flows under resource constraints. For educators, it demonstrates how content creation can be taught as core entrepreneurial competency aligned with sustainable business principles. Sustainable Development Goals (SDGs): SDG 8: Decent Work and Economic Growth; SDG 9: Industry, Innovation and Infrastructure
Purpose. This paper investigates the status, drivers and consequences of low employee engagement among domestic workers in resettled farms in rural Zimbabwe. It focuses on how employment conditions and employer practices shape domestic employees’ motivation, morale and turnover intentions. Methodology. The study adopts a quantitative research design based on a single case of resettled farms in Ward 32, Masvingo rural district. Data were collected using a structured questionnaire from 60 conveniently selected domestic workers and analysed using factor analysis and reliability tests in SPSS. Results. Findings show that employee engagement among domestic workers is extremely low, with respondents reporting poor working conditions, inadequate protective clothing, limited access to basic food items and poor housing. Key engagement drivers identified include two-way communication, leadership quality, compensation, regular feedback, working conditions, career development, rewards and recognition, work–life balance, organizational resources and perceptions of fair and equal treatment; depending on how these drivers are managed, they can either enhance or further erode engagement levels. Theoretical contribution. The study extends the employee engagement literature to marginalized and informal agricultural labour settings, highlighting the influence of socio-economic and institutional factors on domestic worker engagement in resettled farms. Practical implications. The results call on farm owners and policymakers to design targeted interventions that improve domestic workers’ material conditions, recognition and voice at the workplace. Addressing basic welfare deficits and strengthening fair employment practices can reduce labour turnover and support more sustainable agricultural production in resettled areas. Sustainable Development Goals (SDGs): SDG 8: Decent Work and Economic Growth
Purpose: This study investigates the financial implications of adopting the ISO 45001 Occupational Health and Safety (OH&S) management standard within the Southern African region. Specifically, it examines whether certification leads to improved revenues, efficiency, and profitability, and how these outcomes are moderated by prior OHSAS 18001 certification and industry sustainability sensitivity. Methodology: The research employs a quantitative approach using a sample of 98 publicly listed companies in Southern Africa that achieved ISO 45001 certification between 2022 and 2024. An extended event study method was used to analyze abnormal performance, complemented by a Weighted Least Squares (WLS) regression to identify moderating contextual factors. Results: The empirical analysis reveals that ISO 45001 certification positively impacts corporate efficiency and return on assets (ROA) but has no statistically significant effect on revenue growth. Furthermore, the positive impact is diminished for firms with prior OHSAS 18001 certification and those operating in sustainability-sensitive sectors. The theoretical contribution: The study contributes to the Resource-Based View (RBV) and Signaling Theory by demonstrating that in developing markets, OH&S standards function primarily as internal resources for operational efficiency rather than external market signals for revenue generation. Practical implications: The findings suggest that managers in Southern Africa should view ISO 45001 as a tool for cost reduction and process optimization. For policymakers, the study provides economic justification for enforcing safety standards, linking employee welfare (SDG 3 and 8) directly to corporate financial health. Sustainable Development Goals (SDGs): SDG 3: Good Health and Well-being; SDG 8: Decent Work and Economic Growth
Purpose: This study examines the extent to which digital technologies - including artificial intelligence (AI), Internet of Things (IoT), blockchain, and predictive analytics - contribute to sustainability outcomes in Dubai's retail sector. Methodology: A mixed methods approach was employed. Quantitative data were collected from 100 retail professionals in Dubai's retail industry and analysed through Pearson's correlation, Chi-square, Friedman, and Spearman tests. Comparative case studies of five international retailers (IKEA, Inditex/Zara, Tesco, Carrefour, and Unilever) contextualised survey findings. Results: The analysis reveals a strong positive correlation between technology adoption and sustainability performance (r = 0.823, p < 0.001). Integration complexity (84%) and workforce skill gaps (79%) constitute the most significant barriers. Case evidence substantiates the effectiveness of phased implementation approaches, employee training investments, and blockchain-enabled traceability systems. Contribution: The research extends the Technology-Organisation-Environment framework to Gulf economies, demonstrating that technology adoption is driven by consumer and competitive forces rather than regulatory compliance. Practical implications address retailer and policy responses facilitating digital transformation aligned with UN Sustainable Development Goals (SDG 9, SDG 12, SDG 17). Sustainable Development Goals (SDGs): SDG 9: Industry, Innovation and Infrastructure; SDG 12: Responsible Consumption and Production; SDG 17: Partnerships for the Goals
Purpose. This study aims to assess the impact of Industry 4.0 technologies - specifically Big Data, Internet of Things (IoT), collaborative robots, and Cyber-Physical Systems (CPS) - on the financial performance of manufacturing companies in Cameroon, addressing the research gap in the Sub-Saharan context. Methodology. Adopting a quantitative approach, primary data were collected via questionnaires from 104 manufacturing firms. The study employed Chi-square tests and binary logistic regression to analyse the relationship between technological adoption and key performance indicators, including Return on Assets (ROA), Return on Equity (ROE), turnover, and productivity. Results. The empirical findings indicate that integrating Big Data and IoT has a statistically significant positive effect on all measured financial indicators. Collaborative robots positively impact turnover, whereas Cyber-Physical Systems showed no significant correlation with financial performance in the studied context. The theoretical contribution. This research extends economic production theory to developing economies. It provides empirical evidence that digital transformation serves as a critical production input, significantly enhancing firm output and challenging the “IT productivity paradox” in African manufacturing sectors. Practical implications. The study suggests that manufacturing leaders in developing regions should prioritise investments in Big Data and IoT for immediate efficiency gains. Furthermore, it advocates for government-led subsidy policies to lower entry barriers for automation and foster international competitiveness. Sustainable Development Goals (SDGs): SDG 8: Decent Work and Economic Growth; SDG 9: Industry, Innovation and Infrastructure
Research Background: Globalisation and rapid technological change are reshaping manufacturing and trade. Industry 4.0, underpinned by cyber-physical production systems, the Internet of Things (IoT), and artificial intelligence, is pivotal to this transformation. In Slovakia, the automotive sector is a national export pillar, while small and medium enterprises (SMEs) underpin the economy. Recent studies have separately examined advanced vision and sensing in automotive production, wireless networks and smart manufacturing for export growth, and barriers to AI and robotics adoption in SMEs. However, an integrated analysis of how these digital innovations collectively drive Slovak Industry 4.0, spanning both the automotive value chain and SME contexts, is lacking. Purpose of the article: This article consolidates and extends findings from three prior manuscripts to provide a unified, in-depth examination of Industry 4.0 applications in Slovakia. We analyse how computer vision, remote sensing, and data fusion enhance automotive manufacturing and supply chains; how wireless and cyber-physical systems accelerate export value-add; and how machine intelligence and autonomous robotics address SMEs’ operational gaps. The goal is to deepen the analysis of digital transformation in Slovak industry, identify synergies and shortfalls, and propose strategic directions. Methodology: We conducted a comprehensive secondary data analysis and case study synthesis. Data sources included governmental and EU statistics, industry reports, and prior survey data. We re-examined datasets from all three studies, including Slovak export and value-added statistics, foreign direct investment (FDI) structures, and automobile manufacturer supply-chain data, combining statistical and visual analysis techniques. Graphical analytics from the previous case study of PSA Group Slovakia were retained (supply-chain graphs for Citroën C3 and Peugeot 208 vehicles), and new charts were created from the same data (e.g., bar charts of FDI by sector and country). All original tables and figures are preserved for reference. We also synthesised qualitative insights from literature reviews across global value chains, Industry 4.0 frameworks, and SME adoption studies. Findings and value added: The analysis reveals that advanced sensing, AI, and network technologies can substantially raise Slovakia’s export value-added. In the automotive sector, Industry 4.0-driven computer vision and IoT platforms are integral to smart factories and connected vehicle networks. Slovakia ranks second in added value for key car models, but its national R&D base lags, threatening future competitiveness. Wireless networks and cyber-physical systems are shown to accelerate high-value exports, particularly in the automotive sector, but Slovakia’s integration level (DESI index) is moderate. For SMEs, deep learning and robotics promise process optimisation, but financial and skills gaps hinder adoption. Notably, the lack of skilled labour is cited as a more critical barrier than financing for SMEs. This synthesis highlights that combining Industry 4.0 elements, from autonomous vision and data fusion in cars to smart manufacturing networks, can generate new sources of competitiveness, but requires coordinated investment in R&D, workforce development, and supportive innovation policies. The value of this contribution is an original, holistic framework linking Industry 4.0 technologies with value chain enhancement in the Slovak context, along with concrete policy and managerial recommendations (e.g., establishing an “Intelligent Industry Platform” and targeted innovation incentives). Sustainable Development Goals (SDGs): SDG 7: Affordable and Clean Energy; SDG 9: Industry, Innovation and Infrastructure; SDG 13: Climate Action
Purpose. This study investigates the impact of e-business platforms for animation services on environmental sustainability metrics and revenue performance in the European hospitality sector. It aims to determine how digital transformation in entertainment services contributes to the Sustainable Development Goals while simultaneously optimizing hotel profitability. Methodology. A mixed-methods comparative analysis was conducted on a sample of 147 hotels (3–5 stars) across eight EU countries (2022–2024). The study compared 74 properties utilizing digital booking platforms for animation services against 73 using traditional methods. Data sources included Booking.com analytics, corporate sustainability reports, and Eurostat tourism data. The analysis employed multiple linear regression, independent-samples t-tests, and Pearson correlation to assess the relationships between digital adoption, environmental metrics, and financial outcomes. Results. Hotels adopting digital animation platforms demonstrated a 43.9% reduction in paper consumption, a 10.1% increase in energy efficiency, and a 25.4% improvement in waste reduction compared to traditional operators. Financially, these properties achieved a 26.5% increase in animation service revenue per room night. Mobile-friendly interfaces and real-time availability were identified as critical drivers of guest adoption and satisfaction. Theoretical contribution. The research provides the first systematic empirical evidence linking the digitalization of animation services to measurable sustainability outcomes, extending the Technology Acceptance Model to experiential hospitality services. It validates the integration of environmental impact measurement with financial performance analysis in the context of hotel entertainment. Practical implications. The findings offer hotel managers a validated framework for digital investment, indicating a 4.0-year payback period. The results support decision-making for digital transformation strategies that align operational efficiency with EU Green Deal objectives and corporate sustainability targets. Sustainable Development Goals (SDGs): SDG 8: Decent Work and Economic Growth; SDG 9: Industry, Innovation and Infrastructure; SDG 12: Responsible Consumption and Production
Purpose. This study investigates India’s household investment transformation (2015–2025), examining the shift from bank deposits to market instruments and its implications for financial inclusion, banking stability, and sustainable capital formation. Methodology. Mixed-methods longitudinal design combines descriptive analysis with econometric hypothesis testing. Household data from the Reserve Bank of India, SEBI, and All-India Debt and Investment Survey (48,000 observations) are analysed using logistic regression and time-series models. Results. Household deposit share declined from 48 per cent to 25 per cent, while market instruments rose from 40 per cent to 63 per cent. High financial literacy, income, and urban residence increase market participation by 18.8, 31.2, and 25.1 percentage points, respectively. However, participation disparities persist: urban residents and high-income households account for 55–58 per cent of investors, versus 35–12 per cent of the population. Declining deposit ratios are associated with slower credit growth to the MSME and renewable energy sectors - sectors critical to sustainable development. ESG-classified IPOs exhibit lower underpricing and superior long-run returns, suggesting that sustainability disclosure influences valuation. Theoretical and Practical Contributions. The study extends sustainable finance theory by linking household financial behaviour to macro-level resilience. Recommendations include targeted financial literacy programmes, diversifying bank funding to maintain credit supply to the SDG sector, and strengthening ESG disclosure standards to align retail investment flows with sustainable development objectives. Sustainable Development Goals (SDGs): SDG 10: Reduced Inequalities; SDG 8: Decent Work and Economic Growth; SDG 13: Climate Action
Purpose. The paper examines how photo-redox flow batteries can support a sustainable energy transition in Morocco and Poland by simultaneously harvesting and storing solar energy, thereby reducing dependence on fossil fuels and mitigating the intermittency of renewables. Methodology. The study combines a review of national energy policies and renewable energy targets with a comparative techno-economic assessment of photo-redox flow battery deployment scenarios in both countries, focusing on system performance, grid integration, and long-term sustainability indicators. Results. The findings show that photo-redox flow batteries can significantly increase the share of solar energy in national power mixes, improve grid stability, and lower lifecycle emissions compared to conventional storage and fossil-based generation, with particularly strong gains under high-renewables scenarios for Morocco and coal-replacement pathways for Poland. Theoretical contribution. The paper extends the emerging literature on next-generation energy storage by conceptualizing photo-redox flow batteries as a dual harvest–store technology and by linking their deployment to macro-level energy security, decarbonization, and resilience outcomes in middle-income and coal-dependent economies. Practical implications. The results provide policymakers and energy planners with evidence-based guidance on integrating photo-redox flow batteries into national energy strategies, including indicative design parameters, investment priorities, and regulatory measures to accelerate clean energy deployment while managing economic and geopolitical risks. Sustainable Development Goals (SDGs): SDG 7: Affordable and Clean Energy; SDG 9: Industry, Innovation and Infrastructure; SDG 13: Climate Action
This paper analyzes the application of Keynesian theory to identify the determinants of Gross Regional Domestic Product (GRDP) in Java and Sumatra. The study utilizes panel data from 2013 to 2023 across 6 provinces in Java and 10 in Sumatra, employing a fixed effects panel regression to assess the impact of regional expenditure, FDI, DDI, and local taxes on GRDP. Findings reveal that all variables significantly affect GRDP in Java, while in Sumatra, FDI does not have a significant effect. Java demonstrates a more substantial impact of regional expenditure and investment on economic growth than Sumatra. This research extends the empirical application of Keynesian theory to the regional context in Indonesia, highlighting structural differences in economic drivers between Java and Sumatra. The results suggest that policy interventions in Sumatra should focus on enhancing infrastructure and investment climate to improve the effectiveness of FDI and government spending. Sustainable Development Goals (SDGs): SDG 8: Decent Work and Economic Growth; SDG 10: Reduced Inequalities; SDG 17: Partnerships for the Goals
Purpose: The primary purpose of this paper is to evaluate the financial viability and sustainability of launching a new vegetarian restaurant, "Tandoori Tales," in Sri Lanka, using a comprehensive cost-benefit analysis. The study aims to provide actionable insights for entrepreneurs and stakeholders in the hospitality sector, with a particular focus on sustainable business practices. Methodology: The research employs a case study approach, integrating detailed financial modeling, cost and revenue projections, and break-even analysis. The analysis includes both quantitative (financial calculations using Python and Matplotlib) and qualitative (market positioning, eco-friendly strategies) methods to assess the feasibility and sustainability of the business. Results: The findings indicate that "Tandoori Tales" can achieve financial sustainability within the first year of operation, with a projected net profit margin of 15.2% and a break-even point reached within 10 months. The adoption of eco-friendly practices, such as waste reduction, portion control, and the use of technology for inventory management, further enhances the restaurant's operational efficiency and aligns with the United Nations' Sustainable Development Goals. Theoretical Contribution: The paper contributes to the literature on entrepreneurship and sustainable business by demonstrating how rigorous cost-benefit analysis, coupled with sustainability-driven strategies, can inform successful SME start-ups in emerging markets. It bridges the gap between financial planning and sustainable management in the restaurant industry. Practical Implications: This study provides a replicable framework for aspiring entrepreneurs and policymakers to assess the viability of new ventures in the hospitality sector. It underscores the importance of integrating sustainability considerations – such as responsible resource use, waste management, and employee welfare – into business planning to enhance long-term success and contribute to the achievement of the Sustainable Development Goals (SDGs). Sustainable Development Goals (SDGs): SDG 8: Decent Work and Economic Growth; SDG 9: Industry, Innovation, and Infrastructure; SDG 10: Reduced Inequalities; SDG 16: Peace, Justice and Strong Institutions.
