Search Results (2,790)

This study developed internally consistent scenarios for tourism village development to strengthen destination competitiveness and support the local economy. Using an exploratory–constructive design and the Cross-Impact Balance method, the study structured the relationships among development elements, competitiveness, and local economic development into 13 descriptors with 52 states. Expert judgment was used to construct a cross-impact matrix, and ScenarioWizard identified 18 consistent scenarios and their Total Impact Scores. Four scenarios showed positive consistency scores, with one high-road scenario emerging as the most consistent pathway toward very high competitiveness and a stronger role for tourism villages in the local economy. This scenario was characterized by a clear value proposition, full integration of local MSMEs and products, diversified revenue sources, equitable benefit distribution, strong managerial and digital capacity, transparent governance, multi-stakeholder partnerships, strategic use of public funds, and a structured digital marketing and booking system. These findings suggest that policy efforts should prioritize coordinated improvements in value proposition, MSME integration, revenue diversification, governance, partnerships, and digital management to move tourism villages toward the high-road scenario. Full article

Upstream textile small and medium-sized enterprises (SMEs) frequently exhibit constrained supply chain resilience owing to persistent information latency and structural dependence on downstream orders. To address these challenges, this study develops and validates a customer-to-manufacturer (C2M) intelligence framework that enables data-driven production planning using publicly available e-commerce data. The framework incorporates ethically compliant acquisition of consumer demand signals, semantic translation of unstructured market data into textile engineering attributes, machine-learning-based demand forecasting, and human-centric decision support. Utilizing 3.87 million consumer comments from 127,846 product listings, a Neural Boosted Tree model with entity embeddings for textile attributes was constructed. This model achieved a mean R² of 0.921 in cross-validation, surpassing benchmark methods. Consumer comment volume was validated as a proxy for sales activity, facilitating demand estimation. Forecasts were translated into production guidance using Monte Carlo simulation and a decision dashboard. In a 12-month field study at a Taiwanese dyeing SME, implementation resulted in a 28% reduction in inventory value, a 31% decrease in dye lot changeovers, and a 16% increase in capacity utilization. This research extends the C2M paradigm from downstream retail contexts to upstream textile SMEs, proposes an integrated and operationally feasible intelligence framework for resource-constrained manufacturers, and demonstrates how digital intelligence can enhance supply chain resilience while supporting, rather than replacing, human decision-making. The results indicate that upstream textile SMEs can leverage publicly visible e-commerce signals to enhance production planning responsiveness, minimize inventory exposure and dye-lot disruptions, and strengthen resilience to demand uncertainty through planner-centered digital decision support. Full article

The external relations of small towns are an important dimension in the regional urban system. However, the “metropolitan bias” in existing studies results in a lack of empirical verification of their characteristics, hindering effective regional policymaking. Applying Central Flow Theory (CFT), mobile phone data, and a multiscale geographically weighted regression (MGWR) model, this study investigates the spatially non-stationary associations between built environment factors and the “city-ness” and “town-ness” of small towns in the Yangtze River Delta. The results show: (1) Enterprise density in metropolitan shadow areas is positively associated with cross-city jobs–housing separation; in peripheral areas, both enterprise density and housing prices exhibit a strong correlation with intra-municipal jobs–housing separation. (2) Middle schools consistently correlate with localized intra-municipal flows, suggesting a plausible spatial anchoring role; around metropolises, medical and commercial facilities link to recreational flows and commuting town-ness, while in distal small towns, medical facilities coincide with intratown jobs–housing balance, and commercial facilities correlate with localized consumption and cross-town employment mobility. (3) Higher road network density corresponds to a shrinking commuting radius near metropolises and intra-municipal intertown interconnection in distal towns, rather than mere external relation channels. This study empirically supports CFT at the small-town scale, explores plausible mechanisms, and informs differentiated planning strategies. Full article

In the current context of digital transformation, Micro-, Small-, and Medium-Sized Enterprises (MSMEs) are increasingly exposed to cybersecurity risks. This exposure is intensified by the limited adoption of international standards for identifying impacts, low budgets, and shortages of trained personnel, which collectively result in the absence of structured control plans for mitigating cyber risks. (1) This study proposes a mechanism for selecting a cybersecurity risk analysis and management methodology suited to Colombian MSMEs by applying the multi-criteria Analytic Hierarchy Process (AHP) method. (2) The employed approach is qualitative and follows the AHP procedure to select the most suitable option that can be applied to cybersecurity. This selection process evaluated different criteria in five standards: ISO/IEC 27005:2022, NIST SP 800-30, OCTAVE-S, MAGERIT, and EBIOS-RM. (3) The AHP method enabled, in a practical manner, the selection of OCTAVE-S as the primary methodology, complemented with elements from other standards. Finally, the proposed methodology was implemented in a cloud-based web application called the Risk Analysis Module, integrated into the Keru IT security platform. It is concluded that the multi-criteria AHP method is effective and allows organizations to select the standards most appropriate to their needs, with potential applicability to other types of decisions. Full article

Organizational commitment constitutes a challenge for organizations. Despite the growing body of literature describing organizational commitment as a positive outcome of ideal job conditions, how organizational commitment develops has not been explored extensively. This study examines how organizational commitment develops in small and medium enterprises in Cyprus by modelling the roles of work–life balance, flexible work arrangements, employee remuneration, motivation, and job satisfaction. To test the hypothesized relationships among the variables, structural equation modelling was used to analyze survey data collected from 462 employees. The findings of this study show a strong effect of work–life balance and employee remuneration on organizational commitment. The results indicate a sequential pattern, in which work–life balance and employee remuneration showed stronger effects within the model, while motivation acted as a first-stage mediator and job satisfaction as a second-stage mediator linking these effects to organizational commitment. These findings suggest that organizational commitment develops primarily through earlier motivational and evaluative experiences, rather than resulting solely from favorable job conditions. The study offers theoretical insight into the process through which organizational commitment develops and provides practical implications for managers of small and medium enterprises seeking to strengthen employee commitment through everyday work conditions. Full article

The contemporary green transformation of the economy is a strategic imperative for businesses, especially small and medium-sized enterprises (SMEs) operating in the energy market, forcing the integration of sustainable practices in decision-making processes, including investment efficiency assessment. Classic financial tools, such as the internal rate of return (IRR) and net present value (NPV), commonly used in the SME sector, do not always adequately account for environmental, regulatory, and social risks associated with green transformation, as—particularly in the case of IRR—they rely on the assumption of stable cash flows and do not incorporate regulatory uncertainty, environmental externalities, or ESG-related risks into discounting parameters. The aim of the study was to determine the impact of nominal and real discount rates, adjusted for a synthetic measure of green transformation, on investment decisions. The research methodology combines advanced multi-criteria decision-making techniques, specifically TOPSIS and CRITIC, with sustainable finance concepts, offering an innovative approach to investment decision-making in the SME sector. The study shows that integrating environmental factors, when treated as a risk component, increases the cost of capital and reduces the net present value, while maintaining the profitability of the analysed projects. Incorporating green components into the discount rate enhances valuation appropriateness and improves investment risk management, particularly under macroeconomic uncertainty. The main contribution of the study lies in linking a synthetic green transformation indicator with dynamic discount rate adjustment within a multicriteria framework, extending existing ESG-adjusted valuation models by enabling a more structured and data-driven incorporation of environmental transition risk. Full article

Background: This study explores sourcing risk in supply chains by identifying key risk categories, trends, and management strategies. It responds to increased vulnerabilities exposed by recent global disruptions such as the COVID-19 pandemic and geopolitical conflicts. Methods: The research applies a Systematic Literature Network Analyses (SLNA) combined with textual analysis to examine 687 peer-reviewed publications over the past three decades using the PRISMA protocol. Citation network analysis, keyword co-occurrence mapping, and main path analysis were conducted to map intellectual developments. Additionally, textual analysis using the Semantic Brand Score (SBS) approach revealed thematic relevance, novelty, and impact. Results: A shift exists from foundational supplier optimization models to resilience-building/strengthening, ethical sourcing, and technology-enabled strategies. Responsible sourcing and modern slavery were found to be the most innovative and underexplored areas. Research on sector-specific challenges, particularly for small and medium-sized enterprises, remains limited.; Conclusions: Sourcing risk has become a systemic challenge requiring resilience, ethics, and data-driven coordination across supply networks. Full article

This study examines whether crises act as catalysts for sustainable digital transformation in Montenegrin small and medium-sized enterprises (SMEs) and identifies the organizational and HR barriers that mediate change. Using a quantitative online survey conducted August 2023–January 2024 with 209 firms (response rate 24.7%), descriptive statistics and chi-square tests assess adoption patterns across marketing, advanced digital tools, platforms, and employee attitudes. Findings show substantial digital presence (≈95% maintain a website or social profile), 37% report full adoption of digital marketing, and 48% use generative AI (ChatGPT), yet over half lack familiarity with other advanced technologies. Primary obstacles are time constraints, organizational and individual resistance, and limited institutional support; substantive transformation frequently occurs reactively during crises rather than through proactive capability development. The findings suggest that technology adoption alone does not ensure sustained value creation. Effective digital transformation requires complementary investments in leadership, HR practices, employee training, and governance. The study is limited by its convenience sample and single-country focus; future research should adopt longitudinal and multivariate designs. Full article

This article examines how platform-mediated crisis policy shaped inclusion and exclusion outcomes for small, medium, and micro enterprises (SMMEs) in the Western Cape during COVID-19. Integrating a market-failure perspective with entrepreneurial ecosystem theory, we present a theory-driven secondary analysis of 16 qualitative interviews and policy documents. We map five crisis-amplified failures—finance, markets, digital, institutions, and human capital—onto Isenberg’s six ecosystem domains and analyze how provincial interventions, particularly digital marketplaces, voucher schemes, and online coordination tools, functioned as governance mechanisms regulating access, visibility, and participation. The findings show that platform-mediated interventions accelerated coordination and digital market access but disproportionately benefited already connected firms, leaving institutional and inclusion gaps largely unresolved. We conceptualize sub-national crisis response as a form of platform governance and discuss implications for designing more inclusive digital policy infrastructures in middle-income contexts. Full article

Small and medium-sized enterprises (SMEs) struggle to integrate Lean practices with sustainability due to high methodological complexity and the frequent neglect of the social dimension. This study develops the Simple, Sustainable, and Inclusive Lean Model (SSILM), a conceptual framework designed to bridge these gaps. The methodology involved a systematic meta-evaluation of 31 existing Lean–Sustainability models against 14 operational criteria tailored for SMEs. Findings reveal that current models lack social integration and practical scalability for resource-constrained environments. The proposed SSILM is structured in six phases, from characterization to analysis, prioritizing low-cost participatory tools and strategic innovation. This study contributes a theoretical bridge between operational efficiency and the Triple Bottom Line, specifically emphasizing the social pillar. As a conceptual paper, its primary limitation is the lack of empirical field testing, which establishes a clear roadmap for future longitudinal research in industrial contexts. Full article

Background: Small- and medium-sized enterprises (SMEs) constitute a large portion of the industrial energy demand in the emerging economies, but their shift to renewable energy is not well comprehended at the firm level. Bangladesh is a special case, since the country has adopted national commitments to Sustainable Development Goal 7 on clean energy, but the uptake of renewable energy by SMEs remains minimal due to complex socio-economic factors. Most of the literature has concentrated on household access to energy or national policy models, leaving a gap in empirically validated models of firm-level adoption in the manufacturing sector. Method: Based on the diffusion of innovation theory, institutional theory, and the resource-based view, this research paper formulates and empirically verifies a combined socio-economic model of renewable energy adoption. Partial least squares structural equation modeling (PLS-SEM) was used to analyze a cross-sectional survey of 426 owners and managers of manufacturing SMEs in Bangladesh’s textile and food processing sub-sectors. Findings: Four out of five hypothesized direct relationships were supported. The most important drivers were environmental orientation (β = 0.467, p < 0.001, f² = 0.413), market competitiveness (β = 0.287, p < 0.001, f² = 0.413), policy and institutional factors (β = 0.211, p < 0.001, f² = 0.413), and access to finance (β = 0.096, p = 0.004). Perceptions of cost did not become significant (β= −0.036, p = 0.279). Top management support significantly and negatively moderated the relationship between environmental orientation and adoption (β = −0.093, p = 0.003), possibly because it moderates the substitution mechanism in SME decision-making, which is highly centralized. The model accounted for 64.5% of the variation in renewable energy adoption (R² = 0.645). Conclusion: The results show that attitudinal and institutional factors tend to be more important than financial barriers in determining SMEs’ energy transitions. Environmental consciousness, market incentives, and streamlined institutional access should be the focus of policy interventions to hasten inclusive low-carbon transitions in emerging manufacturing economies. Full article

Automated Storage and Retrieval Systems (AS/RSs) are pivotal hubs in modern intelligent logistics, yet their operational efficiency is often constrained by the complex coupling of storage allocation, equipment scheduling, and path planning. This study proposes a systematic optimization framework to address these three critical control challenges. First, a multi-objective mathematical model for storage location allocation is established, considering efficiency, stability, and correlation. To solve this high-dimensional discrete problem, a Tabu Variable Neighborhood Search (TVNS) algorithm is proposed, integrating short-term memory mechanisms with multi-structure exploration to prevent premature convergence. Second, regarding stacker crane and forklift collaborative scheduling, a Pheromone-guided Artificial Hummingbird Algorithm (PT-AHA) is introduced. By incorporating pheromone feedback into foraging behavior, the algorithm significantly enhances global search capability to minimize total task completion time. Third, stacker crane path planning is modeled as a constrained Traveling Salesman Problem (TSP) and solved using a hybrid Simulated Annealing-Whale Optimization Algorithm (SA-WOA). Quantitative simulation results demonstrate that the TVNS algorithm improves storage allocation fitness by 1.1% over standard Genetic Algorithms, while the PT-AHA reduces task completion time (Makespan) by 21.9% for small-scale batches and consistently outperforms ACO by up to 3.6% in large-scale operations. Validation through an Intelligent Warehouse Management System (WMS) confirms that the integrated framework maintains high industrial resilience by triggering fault alarms and initiating recovery within 3.2 s during simulated equipment failures, providing a robust solution for enterprise-level deployments. Full article

Logistics platforms (LPs) increasingly use multidimensional data to provide supply chain financing (SCF) to small and micro logistics enterprises (SMLEs). However, platform-centered data control can weaken financial institutions’ (FIs’) trust in platform data, thereby reducing the effectiveness of data-driven credit enhancement. To address this issue, this study integrates the social–ecological systems framework with evolutionary game theory and develops a tripartite evolutionary game involving FIs, LPs, and SMLEs. By comparing scenarios with and without regulatory governance, the study examines how regulatory governance affects the strategic evolution of data-driven credit enhancement in SCF for SMLEs. The results show that regulatory governance improves system performance through cost reduction, trust enhancement, and incentive alignment, thereby relaxing the conditions required for the system to evolve toward the Pareto-optimal state of credit granting, strict supervision, and non-default. The strategic choices of the three actors are mainly influenced by data acquisition costs, incentive intensity, and penalties. Numerical simulations further show that government incentives must exceed certain thresholds to promote cooperation, while penalty mechanisms play a critical role in constraining opportunistic behavior and accelerating convergence to the desirable equilibrium. These findings provide theoretical support and practical insights for improving data-driven credit enhancement in SCF for SMLEs. Full article

Small and medium-sized enterprises (SMEs) are critical actors in promoting environmentally sustainable supply chains, particularly in emerging economies where their collective environmental footprint is substantial. Despite growing attention to green supply chain management (GSCM), research has predominantly focused on large firms, leaving the motivational drivers shaping GSCM implementation in SMEs underexplored. Addressing this gap, the present study develops and empirically tests a motivation-based framework to examine how four organizational motives, cost, market, ethical, and legitimacy, drive the depth of GSCM implementation in SMEs. In addition, environmental uncertainty is conceptualized as a key contextual contingency moderating the effectiveness of these motives. Drawing on survey data from Vietnamese SMEs, the findings reveal that all four motives positively influence implementation depth, with ethical motives exerting the strongest effect. Furthermore, environmental uncertainty significantly amplifies these relationships. By integrating multiple theoretical perspectives and emphasizing the contingent role of environmental uncertainty, this study advances GSCM research by providing a nuanced, context-sensitive understanding of how SMEs operationalize sustainability practices in dynamic and resource-constrained environments. Full article

As a highly integrated and increasingly complex high-risk process industry, the petrochemical sector plays a critical role in industrial continuity and social stability, yet faces significant governance adaptability challenges under normalized public health emergencies. Taking a Chinese petrochemical enterprise as a case study, this paper develops an integrated framework combining STAMP/STPA, complex network analysis, and robustness analysis. Based on a reconstructed four-level hierarchical control and feedback structure, STPA was applied to identify 20 unsafe control actions (UCAs). These UCAs and their precursor factors were further abstracted into a relational network of control deficiencies for topological analysis and Monte Carlo-based robustness testing under random failure and targeted attack. The results show pronounced small-world and core–periphery structural characteristics, with vulnerability concentrated in a limited number of high-centrality source and hub nodes. Systemic resilience constraints mainly arise from governmental deficiencies in response experience and training, enterprise-level amplification at hub nodes, and pressure accumulation at frontline execution nodes. Accordingly, three resilience protocols are proposed: distributed authorization for source nodes; digitized dual-channel feedback for hub nodes; and minimum operational redundancy with cross-replacement for terminal nodes. This study provides theoretical basis and strategies for high-risk industrial systems to enhance resilience and sustainable development in uncertain environments. Full article