Search Results (1,338)

This study examines how green talent management (GTM) practices foster sustainable supply chains in micro, small, and medium-sized enterprises (MSMEs) in Quito, Ecuador. It analyzes how sustainable leadership, green organizational culture, and sustainability-oriented training influence employees’ pro-environmental motivation, organizational commitment, and sustainability attitudes, which in turn mediate the adoption of green logistics practices, supply chain efficiency, and organizational resilience. A quantitative design was employed, using survey data from 280 MSMEs analyzed through structural equation modeling. The findings demonstrate that GTM enhances employees’ motivation, commitment, and sustainability attitudes, which act as the primary behavioral mechanisms translating managerial practices into sustainability outcomes. Theoretically, the study integrates Green HRM and supply chain research with multiple organizational behavior theories, including Social Exchange Theory, the AMO model, the Theory of Planned Behavior, and the Resource-Based View. Empirically, it contributes novel evidence from Ecuadorian MSMEs, a context often underexplored in sustainability research. Practically, the study highlights leadership, culture, and training as strategic levers for building greener, more efficient, and more resilient supply chains. The results offer actionable recommendations for MSME managers and policymakers in Ecuador, highlighting the importance of investing in people as the foundation of sustainable competitiveness. Full article

In the tourism industry, loyalty is a crucial factor that can significantly impact a business’s success and survival. In niche markets such as wine and beer, it is even more relevant, as in Mexico, most businesses are small and medium-sized enterprises. This study aimed to compare the influence of experience and price on tourist loyalty between wine and beer, using a sample of 245 adult tourists in Baja California, Mexico. Structural equation modeling using partial least squares (PLS) was employed for data analysis, utilizing an embedded two-stage approach. It was found that there is no significant difference in the influence of experience and price on loyalty, regardless of the type of beverage being consumed. In both cases, price is the variable that most influences tourist loyalty, although the influence of experience on loyalty is also significant but only for beer. These results enable the development of targeted marketing strategies for regions that focus on gastronomic tourism centered on these types of beverages. In addition to practitioners concentrating on developing a sensory, affective, and behavioral experience for tourists, it is also essential to set an attractive price for the consumer. Full article

Small and medium-sized enterprises face significant challenges in effectively implementing design thinking due to limited resources, leadership skepticism, and a paucity of suitable frameworks. This study addresses these challenges by developing and validating a web-based Design Thinking and Innovation Strategy Toolbox tailored to SME needs. The Toolbox is designed to align with the ISO 56001:2024 Innovation Management Systems standard and was developed through systematic literature reviews and expert interviews, shaping practical modules based on previously identified barriers and success factors. A multi-round Delphi study with 14 experienced consultants refined the Toolbox, focusing on usability, ISO compliance, and practical relevance. The results indicate strong consensus among experts regarding its clarity, adaptability, and alignment with SME constraints, while also highlighting areas for improvement such as visual design and continuous feedback mechanisms. Preliminary validation suggests that the Toolbox can support SMEs in improving sustainable innovation, strategic alignment, and capability development. By addressing contextual constraints, this research contributes to the field of design-led innovation in SMEs by offering a practical, ISO-compliant tool that connects theory and practice in resource-limited environments. Full article

The aim of this study was to identify and explore the most significant barriers in implementing smart manufacturing (SM) in terms of small and medium enterprises (SMEs). A two-round Delphi method was used to uncover them in this regard. To assess the reliability of the obtained results, Cronbach’s alpha, Intraclass correlation coefficient, and a statistical F-test were performed for both rounds. Cronbach’s alpha for round 1 was 0.729, and 0.816 for round 2. On this basis, good inter-rater reliability was demonstrated in round 2. At the same time, the Intraclass correlation coefficient from round 1 was 0.54, and from round 2, it was 0.74, indicating a significant improvement in panel consensus. The comparison of the equality of variances within the two rounds using the F-test confirmed that a third round of the survey was not necessary. Moreover, the coefficient of variation and relative interquartile range were applied to assess internal consistency among the involved experts to come to a more comprehensive and cohesive understanding of the issue at hand. A total of 30 barriers/limitations or shortages were identified in the preparatory phase of the research, which, in some sense, do not allow or slow down the implementation of the SM. The Delphi survey found that financial problems, lack of government support, and technological constraints can be considered as the most serious barriers to the implementation of SM in an SME environment. Finally, the obstacles/constraints or shortcomings that proved to be the most critical were analyzed in terms of their impact on the ability of small and medium-sized enterprises to embrace the challenges of smart manufacturing. Full article

As digitalization and environmental sustainability advance globally, small and medium-sized enterprises (SMEs) are facing transformative pressures as well as emerging opportunities. Rapid digital innovation promotes intelligent production, cost reduction, efficiency gains, and improved management practices, while green development mandates emphasize energy conservation, emissions reduction, and sustainable supply chains. Amid concurrent digital and green transformations, SMEs are leveraging digital technologies to bolster green learning and enhance sustainable product development. This study investigates the digital–green learning orientation (DGLO) and its influence on ambidextrous research and development (R&D) capabilities, which in turn shape sustainable product development performance (SPDP). Drawing on survey data from 306 SMEs in eastern and southern China, multiple regression analysis was employed to assess the relationships between DGLO, ambidextrous R&D capabilities, and SPDP. The findings reveal that DGLO significantly enhances SPDP. Moreover, DGLO promotes SPDP through both exploitative and exploratory R&D capabilities, with each playing a complementary role. Full article

Serbian SMEs face mounting pressure to stay competitive, agile, and aligned with sustainability goals amid rapid digital change. This mixed-method study—12 qualitative case studies and a survey of 200 firms—examines how AI adoption supports flexible and adaptive strategic transformation. We examine how organizational context and AI readiness translate into the strategic application of AI and, in turn, sustainable development and strategic performance outcomes among Serbian SMEs. Through the AI-Driven Strategic Transformation Framework (AISTF-SME), three adoption types were identified —Traditionalists, Experimenters, and Strategic Adopters—distinguished by digital maturity, strategic integration, and sustainability orientation. While AI is primarily deployed for operational efficiency, firms with higher AI maturity and tighter strategic alignment report stronger gains in agility, innovation, and customer experience; sustainability-oriented use cases remain limited. Key barriers include shortages of technical talent, financial constraints, and insufficient institutional support. We recommend a multi-stakeholder policy approach emphasizing sector-specific AI readiness programs, better access to funding, and stronger university–industry collaboration. The findings enrich digital transformation and sustainability research and offer practical guidance for accelerating AI adoption in transitional economies. Full article

Corporate Social Responsibility (CSR) is increasingly shaping the pathways of Small Medium-sized Enterprises (SMEs). This study presents an entity-relationship diagram (ERD) approach to 184 determinants of SME internationalization success, in order to provide structured inputs for Deep Learning (DL) Recommenders that can support CSR-aligned internationalization strategies. Employing Visual Paradigm 17.2 Professional software for modeling, the research synthesizes state-of-the-art findings on foreign market entry, and export performance, into ERDs. Then the market adoption drivers for such a DL tool are explored through semi-structured interviews with twelve stakeholders. The results reveal a propensity to adopt the DL recommender, with experts highlighting essential features for engagement, pricing, and implementation. The discussion contextualizes these findings, while the conclusion addresses gaps and future directions. The study’s focus in Portugal/Germany may limit worldwide extrapolation, yet it advances knowledge by consolidating success determinants, validating platform requirements, exposing gaps, and suggesting research in both CSR, AI and SME internationalization. Full article

This study examines the influence of institutional pressures and personal attributes on the perceived importance of financial reporting among micro-entrepreneurs in Malaysia. Survey data from 194 micro-entrepreneurs were analyzed using ordinary least squares (OLS) regression to test the proposed hypotheses. The results indicate that institutional pressures from Malaysian regulatory bodies, particularly the Inland Revenue Board, and the financial literacy of micro-entrepreneurs are significantly associated with stronger perceptions of the importance of financial reporting. These findings offer practical insights for policymakers and stakeholders seeking to enhance reporting practices and promote financial literacy within the microenterprise sector. While prior research has largely concentrated on small and medium-sized enterprises (SMEs), the financial reporting practices of micro-enterprises remain underexplored, despite their distinctive characteristics and critical role in the economy. By addressing this gap, this study enriches the financial reporting literature and advances a broader understanding of micro, small, and medium-sized enterprises (MSMEs). Full article

Environmental, social, and governance (ESG) has increasingly received attention for its expected capacity to simultaneously enhance sustainability performance and mitigate risks among micro, small, and medium-sized enterprises (MSMEs) in supply chains. This study examines how external drivers, particularly the influences of buying firms and governments, as well as corporate entrepreneurship as an internal driver, foster MSME suppliers’ sustainability innovation management. A survey of the automobile industry in a Republic of Korea context indicates that buying firms and corporate entrepreneurship play critical roles in enhancing MSME suppliers’ sustainability innovation management. This study also reveals that corporate entrepreneurship accentuates the effects of external drivers on MSME suppliers’ sustainability innovation. Although a relationship between sustainability innovation management and operational performance was unconfirmed, this study demonstrates that corporate entrepreneurship enhances operational performance. As one of the first to explore the topic of MSME suppliers’ sustainability innovation from a corporate entrepreneurship perspective, this study has significant implications for academics, practitioners, and policymakers. Full article

Efforts to lower the barriers for 5G uptake have brought forth accelerated innovation rates in a wide range of verticals. Consequently, the demands for 5G experimentation facilities have recently emerged from small- and medium-sized enterprises (SMEs) and 3rd party developers, requiring the abstraction of the complexities of the underlying infrastructure, platform, and related management and orchestration (MANO) systems, especially in multi-domain scenarios. This paper proposes a novel approach towards cross-domain service orchestration, which combines the flexibility of supporting different 5G Service Orchestrators (SOs) in various domains, while preserving compatibility through NetApps. The Cross-domain Service Orchestrator (CDSO) is based on ETSI’s Open Source MANO (OSM), with a Requests Handler module on top, which acts as the main integration point to the different domains’ 5G SOs and other custom systems that are northbound. This would facilitate the interworking among independently orchestrated domains in supporting multi-domain services. The EU Horizon 2020 project, 5GMediaHUB, is presented as a use case, together with a first implementation of the Requests Handler and corresponding integrations. Nonetheless, the proposed approach is vertical-agnostic and is foreseen to accelerate service innovation and digitalization in any industry by laying the foundations in terms of service management and interconnectivity. Full article

In an increasingly interconnected and sustainability-driven digital landscape, effective risk management and robust information security practices are essential not only for protecting organizational assets but also for ensuring long-term operational resilience and regulatory compliance, especially for small and medium-sized enterprises (SMEs), which aim to grow but have limited resources. This paper presents the development of a practical framework and a supporting application—GestionAVR—for implementing an Information Security Management System (ISMS) that integrates structured risk management processes. The research presents some theoretical insights and practitioners’ input, with a focus on the needs of SMEs. The framework includes a predefined set of categorized risks across four key areas: organizational, personnel, physical, and technological. Designed for usability and adaptability, the GestionAVR application facilitates risk identification, prioritization, monitoring, and continuous improvement. Validated through a case study in the engineering sector, the solution proved to be effective in enhancing decision-making, reducing time spent on planning, and minimizing overlooked vulnerabilities. Future developments include integration of sustainability indicators aligning with recent updates to ISO 27001 standards, AI-based data analysis and automated reporting. This research offers a customizable and cost-effective tool that supports information security and sustainable organizational development. Full article

Small and medium-sized enterprises (SMEs) are critical contributors to economic growth, innovation, and employment. However, they often struggle in securing external financing. This financial gap mainly arises from perceived risks and information asymmetries creating barriers between SMEs and potential investors. To address this issue, our study proposes a machine learning (ML) framework for predicting the investment readiness (IR) of SMEs. All the models involved in this study are trained using data provided by the European Central Bank’s Survey on Access to Finance of Enterprises (SAFE). We train, evaluate, and compare the predictive performance of nine (9) machine learning algorithms and various ensemble methods. The results provide evidence on the ability of ML algorithms in identifying investment-ready SMEs in a heavily imbalanced and noisy dataset. In particular, the Gradient Boosting algorithm achieves a balanced accuracy of 75.4% and the highest ROC AUC score at 0.815. Employing a relevant cost function economically enhances these results. The approach can offer specific inference to policymakers seeking to design targeted interventions and can provide investors with data-driven methods for identifying promising SMEs. Full article

Digitalization is reshaping entrepreneurship, yet the mechanisms that translate new technological possibilities into entrepreneurial intention remain poorly understood, especially for resource-constrained small and medium-sized enterprises (SMEs). Building on the Theory of Planned Behaviour, Entrepreneurial Risk-Taking Theory and Affordance Theory, this study proposes and tests an integrated model that captures how individual cognition, digital capability and platform-related risk interact to shape digital entrepreneurial intention (DEI). Survey data from 428 Greek SME owner-managers were analyzed with Partial Least Squares Structural Equation Modelling (PLS-SEM). Results show that entrepreneurial self-efficacy, financial risk tolerance, digital literacy and perceived platform affordances each exert significant positive effects on DEI, whereas perceived platform risk exerts a significant negative effect. Importantly, platform risk also dampens the positive impact of self-efficacy, revealing a boundary condition often overlooked in intention research. The findings position digital transformation as a double-edged phenomenon amplifying opportunity through affordances while simultaneously magnifying risk. The study advances theory by integrating risk perceptions and affordance recognition into a TPB framework, and it offers actionable guidance: policy makers should stabilize digital-regulatory regimes, platform providers should increase transparency and reliability, and SME support programs should blend digital-skills training with calibrated risk-management tools. Together, such measures can convert latent entrepreneurial confidence into resilient digital venture creation. This study contributes to theory by extending the Theory of Planned Behaviour with risk-sensitive boundary conditions, broadening Risk-Taking Theory to account for platform-specific uncertainties, and validating Affordance Theory in a digital SME context. Practically, it provides actionable guidance for entrepreneurs, policymakers, and platform operators on balancing digital capability development with systemic risk governance. Full article

Background: Inventory planning in retail supply chains requires balancing cost efficiency and service reliability under demand uncertainty and financial limitations. The literature has seldom addressed the joint integration of stochastic demand, deterministic lead times, and supplier-specific constraints in multi-product and multi-warehouse settings, particularly in the context of small- and medium-sized enterprises. Methods: This study develops a Stochastic Pure Integer Linear Programming (SPILP) model that incorporates stochastic demand, deterministic lead times, budget ceilings, and trade credit conditions across multiple suppliers and warehouses. A two-step solution procedure is proposed, combining a chance-constrained approach to manage uncertainty with warm-start heuristics and relaxation-based preprocessing to improve computational efficiency. Results: Model validation using data from a Colombian retail distributor showed cost reductions of up to 17% (average 15%) while maintaining or improving service levels. Computational experiments confirmed scalability, solving instances with more than 574,000 variables in less than 8800 s. Sensitivity analyses revealed nonlinear trade-offs between service levels and planning horizons, showing that very high service levels or short planning periods substantially increase costs. Conclusions: The findings demonstrate that the proposed model provides an effective decision support system for inventory planning under uncertainty, offering robust, scalable, and practical solutions that integrate operational and financial constraints for medium-sized retailers. Full article

The paper proposes a method for assessing production risks related to potential exceedances of the agreed production lead time for batches of details in small and medium-sized enterprises. The study focuses on a linear production system composed of sequential technological operations, analyzed within the broader context of production and logistics processes. A stochastic model of the production flow has been developed, using dimensionless parameters to describe the state and trajectory of a product in a multidimensional technological space. The internal and external risk factors that affect the duration of operations are taken into account, including equipment failures, delays in material deliveries and labor availability. Analytical expressions enabling the quantitative assessment of the risk of production deadline violations and the resulting losses have been derived. The proposed method was validated on a production line for manufacturing wooden single-leaf windows. The results indicate that the presence of inter-operational reserves significantly reduces the probability of exceeding production deadlines and enhances the stability of the production process under stochastic disturbances. The use of inter-operational buffers in most cases ensured a reduction in the processing time of experimental batches of products by 18–25% and simultaneously led to a reduction in the level of production risk by several times, which confirms the effectiveness of the proposed approach and its practical significance for increasing the sustainability of production systems. Full article