Search Results (486)

Reverse Logistics (RL) plays a fundamental role in supply by addressing returns, undelivered or damaged products, exchanges, and environmental concerns, directly contributing to more sustainable supply chain practices. Although firms recognize the importance and benefits of this concept, their supply chain remains focused on direct logistics, often overlooking RL’s potential to enhance sustainability performance. The aim of this article is to analyse the interaction between the barriers that challenge or prevent the implementation of RL in Small and Medium-sized Enterprises (SMEs). First, a literature review identified 22 barriers to developing RL in SMEs. Then, through experts’ opinions gathered in a Focus Group (FG), an Interpretive Structural Modeling (ISM) model was used to understand the hierarchy relations between barriers, and a Matrix Cross Impact Matrix Multiplication (MICMAC) analysis was carried out to aggregate the barriers in four categories according to their influencing power and dependence. Applying the methodology to the Portuguese case resulted in an ISM model with seven hierarchical levels and a MICMAC diagram without dependent barriers. Moreover, six key barriers emerged, namely, Lack of adequate organizational structure and support for RL practices, Lack of corporate social responsibility, Complexity of the operation, Lack of shared understanding of best practices, Difficulty with members of the supply chain, and Lack of support from supply chain players, which proved to be the most critical as they are positioned at the highest hierarchical levels of the ISM model and fall within the independent variable quadrant of the MICMAC analysis, thus revealing a strong driving power over the other barriers. The findings highlight that overcoming these barriers is crucial for SMEs to unlock the full sustainability potential of RL and transition towards supply chain models that are greener through a reduced carbon footprint, improved resource efficiency, and the adoption of circular economy practices. Academically, this research advances the literature by applying the ISM–MICMAC approach to SMEs, offering novel insights into the structural role of barriers in reverse logistics implementation. Full article

Strategic mergers and acquisitions (M&A) can support sustainable business models by enabling firms to adapt their capabilities and competitive positions as conditions change. This study examines how target listing status (public vs. private) and acquirer size shape short-term shareholder wealth in Korean SMEs (Small- and medium-sized enterprise), and links announcement reactions to subsequent operating outcomes. Using an event study and multivariate regressions on 155 M&A announcements by KOSDAQ-listed SMEs (Korean Securities Dealers Automated Quotations) (2016–2020), we find that smaller acquirers earn significantly higher announcement-period cumulative abnormal returns (CAR)—i.e., smaller firm size is positively associated with superior market-adjusted performance around M&A events. Although acquisitions of privately held targets and diversifying deals show higher unadjusted means, their effects become statistically insignificant once firm fundamentals and size are controlled for. To connect M&A strategy with business-model sustainability, we operationalize sustainability as the alignment between short-term market expectations (CAR) and realized operating performance over 1–2 years, measured by return on operating cash flow (ROCF); medium-term checks indicate that the short-run “size effect” attenuates, underscoring the role of execution and scale in longer-run outcomes. Overall, the evidence highlights the primacy of firm-specific fundamentals, strategic fit, and integration capacity in guiding M&A decisions that advance both near-term performance and longer-term resilience. The Korean SME setting—marked by concentrated ownership, resource constraints, and a chaebol-influenced market and policy environment—provides a stringent context for these tests. Full article

Small and medium-sized enterprises (SMEs) chronically face financing frictions. While supply chain finance (SCF) can help, reliable credit risk assessment in SCF is hindered by redundant features, heterogeneous data sources, small samples, and class imbalance. Using 360 A-share–listed SMEs from 2019–2023, we build a 77-indicator, multidimensional system covering SME and core-firm financials, supply chain stability, and macroeconomic conditions. To reduce dimensionality and remove low-contribution variables, feature selection is performed via a genetic algorithm enhanced LightGBM (GA-LightGBM). To mitigate class imbalance, we employ TabDDPM for data augmentation, yielding consistent improvements in downstream performance. For modeling, we propose a two-stage predictive framework that integrates TabNet-based feature engineering with a stacking ensemble (TabNet-Stacking). In our experiments, TabNet-Stacking outperforms strong machine-learning baselines in accuracy, recall, F1 score, and AUC. Full article

The transition from soft to hard law is reshaping global agri-food governance, particularly in relation to sustainability and corporate responsibility. This article analyzes this shift by examining two regulatory approaches: voluntary instruments such as the OECD-FAO Guidance for Responsible Agricultural Supply Chains and binding EU directives like the Corporate Sustainability Due Diligence Directive (CSDDD) and the Corporate Sustainability Reporting Directive (CSRD). Using a qualitative and interpretive methodology, the study combines a literature review and two case studies (Nicoverde and Lavazza) to explore the evolution from soft law to hard law and the synergies and analyze how these tools are applied in the Italian agri-food sector and how they can contribute to improving corporate sustainability performance. Findings show that soft law has paved the way for more rigorous regulation, but the increasing compliance burden poses challenges, especially for small and medium-sized enterprises (SMEs). These cases serve as virtuous examples to illustrate how soft and hard law interact in practice, offering concrete insights into the translation of general sustainability principles into corporate strategies. A hybrid governance framework—combining voluntary and binding tools—can foster sustainability if supported by coherent policies, stakeholder collaboration and adequate support mechanisms. The study offers practical insights for both companies and policymakers navigating the evolving legal scenario. Full article

Introduction: This study explores the impact of logistics information technology (LIT) on supply chain relationships and distribution performance in small and medium-sized enterprises (SMEs) using South Africa as a case study. Although digital supply chain solutions are increasingly important, there is limited evidence of SME efficiency in emerging markets using LIT. Methods: This study utilises a survey of 313 SMEs from four South African provinces. Bayesian structural equation modelling (Bayesian SEM) was then used to examine LIT’s effects on distribution performances in terms of timeliness, product availability, and condition. Results: The results show that the adoption of LIT strengthens buyer–seller networks (β = 0.524, CI = [0.434, 0.613]) and improves distribution by enhancing both timeliness performance (β = 0.237, CI = [0.098, 0.372]) and product condition performance (β = 0.175, CI = [0.042, 0.259], β = 0.222, p < 0.001). However, it does not directly enhance product availability performance (β = 0.085, CI = [−0.030, 0.199]), signifying that LIT adoption by itself fails to improve product availability. The results also demonstrate that SME network relationships mediate the connection between LIT adoption and distribution performance metrics. Discussion: This study’s findings contribute to the literature and offer valuable information and guidance to policymakers as they underscore the importance for SMEs to invest in LIT integration and compatibility, as well as inventory optimisation and improved supplier communication to minimise transit time variation. Policymakers should support SMEs’ digital transformation through interventions including funding and training for LIT adoption. This study confirms the essential role of LIT in SME supply chains and illustrates that technology-facilitated relationships enhance distribution performance, which enhances SME competitiveness. Full article

As small–medium-sized enterprises (SMEs) increasingly adopt cloud technologies, understanding the factors influencing this shift is crucial as it helps to optimize cloud integration strategies, enabling SMEs to thrive in today’s digital economy. A cross-sectional, quantitative survey was conducted in February 2022 on 626 employees of SMEs in the USA, based on the TAM-2, TAM-3, and UTAUT-2 models. The questionnaire presented satisfactory reliability, as well as factorial and convergent validity. Employees presented positive behavioral intentions to use cloud technologies, particularly during the COVID-19 period. SMEs were satisfied with the use of Software as a Service (SaaS), Infrastructure as a Service (IaaS), and the public cloud development model in the wake of the COVID-19 period. Behavioral intention to use cloud technologies was linked with higher performance and effort expectancy, price, perceived enjoyment, computer self-efficacy, and social influence. A higher behavioral intention was observed in employees (a) with a mid–top-level role; (b) who worked in finance and insurance, information services data, construction, or software and in an SME with 26–500 employees; (c) who had a master’s degree; (d) were 35–44 years old; and (e) had family obligations. Higher experience with the use of cloud technologies enhanced the positive impacts of effort expectancy, computer self-efficacy, and perceived enjoyment on behavioral intention. 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

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

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

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

In this paper, we introduce a novel, self-hosted Syslog collection platform designed specifically to address the challenges that small and medium enterprises (SMEs) face in implementing comprehensive syslog monitoring solutions. Our analysis begins with an assessment of current network observability practices, evaluating enterprise solutions, on-premises systems, and Software as a Service (SaaS) offerings to identify features crucial for SME environments. The proposed platform represents an advancement in the field through the incorporation of modern practices, including GitOps and continuous integration and continuous delivery/deployment (CI/CD), and its implementation onto a self-managed Kubernetes platform, which is an approach not commonly explored in SME-focused solutions. We will explore its scalability by leveraging dynamic templates, which allow us to select the number and type of nodes when deploying networks of various sizes. This architecture ensures organisations can deploy a pre-designed, scalable network monitoring solution without extensive external support. The resilience of the proposed platform is assessed by providing empirical evidence of the scaling performance and reliability under various failure scenarios, including node failure and high network throughput stress. Full article

This study examines the effects of sustainability-related data requests—spurred by the EU Corporate Sustainability Reporting Directive (CSRD)—on small and medium-sized enterprises (SMEs) in the Netherlands. Using a representative survey of 431 SMEs and 48 qualitative interviews with SME representatives and business stakeholders, the research provides a comprehensive overview of their experiences in late 2024. A key finding is that most Dutch SMEs (72%) have not yet received sustainability data requests. However, SMEs embedded in international value chains report more frequent and complex data demands, particularly concerning environmental indicators like CO₂ emissions and material use. Ratings of perceived relevance reveal a disconnect between external data requests and SMEs’ internal priorities, with many SMEs prioritizing health and safety over climate metrics. While some SMEs see data requests as opportunities for improved sustainability performance and market positioning, many also experience challenges, including limited resources, fragmented IT systems, and regulatory uncertainty. The implementation of CSRD highlights the urgency of supporting SMEs in building data management capacities and standardized processes. The study recommends clearer communication of data relevance, targeted support measures, and further research into cross-national and longitudinal dynamics to foster an effective sustainability transition across value chains. Full article

Small and medium-sized enterprises (SMEs) often face severe resource constraints and operational fragility during crises. However, little is known about how managerial resilience (MR) translates into performance through time-related psychological resources and innovation—two capabilities that are both scarce and critical under such conditions. Drawing on Temporal Motivation Theory (TMT), this study develops and tests a dual-mediation model in which employee temporal psychological capital (TPC) and employee innovative behavior (EIB) transmit the effects of MR on performance. As a core methodological innovation, we adopt a multi-method analytical strategy to provide robust and complementary evidence rather than a hierarchy of results: Partial Least Squares Structural Equation Modeling (PLS-SEM) is used to examine sufficiency-based causal pathways and quantify the mediating mechanisms; Support Vector Machine (SVM) classification offers a non-parametric predictive validation of how MR and its mediators distinguish high- and low-performance cases; and Necessary Condition Analysis (NCA) identifies non-compensatory conditions that must be present for high performance to occur. These three methods address different research questions—sufficiency, classification robustness, and necessity—therefore serving as parallel, equally important components of the analysis. A total of 455 SME managers and employees were surveyed, and results show that MR significantly enhances all three dimensions of TPC (temporal control, temporal fit, time pressure resilience) and EIB (idea generation, idea promotion, idea realization), which in turn improve employee performance. SVM classification confirms that high MR, strong TPC, and active innovation align with high performance, while NCA reveals temporal control, idea generation, and idea realization as necessary bottleneck conditions. By integrating sufficiency–necessity logic with predictive classification, our findings suggest that SMEs should prioritize leadership resilience training to strengthen managers’ adaptive capacity, while simultaneously implementing time management interventions—such as temporal control workshops, workload balancing, and innovation pipeline support—to enhance employees’ ability to align tasks with organizational timelines, execute ideas effectively, and sustain performance during crises. Full article

This study investigates the nexus between leverage and financial performance in a sample of 54 Moroccan agricultural small- and medium-sized enterprises (SMEs) over the period of 2017–2022. Drawing on trade-off, pecking order, and agency theories, this analysis examines whether different levels of indebtedness influence performance, as measured by return on assets (ROA). Using panel data regression models, both linear and nonlinear specifications were tested to explore the potential curvature of the leverage–performance relationship. The empirical results reveal a significant and negative linear relationship between both short-term and long-term leverage and ROA, suggesting that increased indebtedness impairs financial performance. A quadratic specification reveals a persistently negative effect of short-term leverage and a U-shaped relationship between long-term leverage and ROA, indicating that performance may improve beyond certain debt thresholds. To address endogeneity concerns and validate the findings, dynamic panel estimation using the generalized method of moments (GMM) was employed, confirming the leverage’s adverse effects on performance. Thus, this study provides policy-relevant insights into optimal capital structure decisions for small agribusinesses and underscores the need for tailored financial strategies to support their sustainable development. Full article