In conditions where information and communication technologies (ICT) dictate the "rules" of the market, the strong promotion and development of innovation-oriented small and medium-sized enterprises (SMEs) are essential. The transition from a traditional, linear system of waste management and fleet management in utility companies to a digital and circular-oriented system represents not only a significant challenge, but also a necessity. This paper analyses the potential transition of a medium-sized enterprise from a conventional to a sustainable business ecosystem by examining the vehicle fleet of a utility company and proposing its optimisation using the DEA-LOGSTA-MARCOS model. The hybrid DEA-MCDM model, developed and presented in this form for the first time in the literature, represents a methodological contribution of this research. The paper analyses a fleet of utility vehicles used for waste collection and transport that are 15 years old or older. The aforementioned methods are applied to highlight the importance of operationally efficient vehicles that can potentially be integrated into a digital ecosystem (DE), thereby strengthening the company's comparative advantage. In the first stage, the DEA model was applied to determine the efficiency of the vehicles, followed by the LOGSTA method in the second stage to calculate the criteria weights, and finally, the MARCOS method to rank the vehicles according to their overall efficiency. The research results indicate that the most significant barriers to the transformation toward a digital ecosystem within the observed enterprise are regulatory, financial, and technical in nature. From the perspective of the vehicle fleet and its limiting factors, the results indicate the need for an iterative transformation of the fleet structure, aligned with current efficiency levels and future electrification trends. In this context, the findings identify which types of vehicles should be retained during the initial phase of the transformation.
The current paper aims to calculate the efficiency of EU SMEs and investigate which digital determinants may impact the efficiency scores. The research was conducted in two stages. First, the output-oriented VRS model was employed to compute the technical efficiency of SMEs in the EU at the country level. Then, in the second stage, the efficiency scores were regressed against a set of digital determinants that may affect the efficiency. For that issue, Simar-Wilson bootstrap regression was used. The research covered the years from 2021 to 2023, and only one country was efficient during the entire period-the Netherlands. Moreover, the results showed that online sales have a positive influence on SMEs' inefficiency, while e-commerce turnover turned out to be insignificant. Moreover, the regression revealed that a higher level of economic development is associated with lower inefficiency. These findings provide valuable insights for policymakers seeking to design more targeted strategies for SMEs in their respective countries.
Over time, Prof. dr Gabriela Ţigu succeeded Prof. dr Gabriela Stănciulescu (1947-2023) as head of the current Faculty of Business and Tourism at the Academy of Economic Studies in Bucharest. The dean during the 2004-2008 term was the granddaughter of one of the leaders of the National Peasant Party in the 1940s, one of those who, in 1947, was sentenced to hard labour. A volunteer, enthusiastic, with continuous intellectual verve, Prof. GabrielaStănciulescu was always ready to ”move mountains”. Sometimes she succeeded. And if not, she was content to ski down the snowy slopes. She seemed to have the faith of the Christian-Catholic Church, of which she was a member, on her side. She did not hesitate to help others. Like no other, she invited her colleagues to a feast under the walnut tree in the yard. On such occasions, in tandem with her husband, Eng. Doru”Bijou” Stănciulescu, she managed to organiseeverything flawlessly. In the ”presentation guide”sent to guests in June 2000, she kindly mentioned: ”It is good for the children to be in play clothes; we have everything we need for this purpose: water from a hose that sprays with pressure, puppies, sand, dirt, so that the mothers are provided with a full washing machine...” Later, among those puppies, Kim stood out, a gorgeous Labrador whose loss the professor suffered greatly. She was also a perfect housewife, passionately caring for her flowers at home. The successors of Professor Gabriela Stănciulescu are her disciples, those whose steps she guided
Agricultural sustainability assessment has become increasingly complex in the context of the low-carbon transition, as agricultural systems are expected to balance economic viability, environmental protection, and social considerations under conditions of uncertainty and conflicting objectives. Traditional assessment methods that rely on single indicators or deterministic evaluation methods do not provide decision support, particularly in situations where trade-offs and qualitative judgments are critical. Thus, there is a need for clearly outlined decision-support frameworks that cover different dimensions of sustainability and incorporate varying degrees of uncertainty. This study seeks to develop a conceptual methodological framework design for agricultural sustainability assessment that combines the Fuzzy Best-Worst method (Fuzzy-BWM) with the MULTIMORA approach. This framework integrates Fuzzy-BWM with decision-support structures to address each of the evaluation dimensions and to incorporate multi-perspective assessments of alternatives. This study prioritizes the integration of concepts and the complementarity of methodologies of the multi-criteria decision-making approaches over empirical application or numerical validation. The sequence-based assessment logic within the proposed framework separates the definition of the criterion, the weighting of the criterion, and the multi-dimensional assessment. While MULTIMORA provides stable and interpretable rankings across various evaluation perspectives, Fuzzy-BWM captures the expert assessment and the linguistic uncertainty pertaining to the importance of the criteria. This functional separation improves transparency and avoids the mixing of the assessment of uncertainty and the assessment of relative performance. From the perspective of agricultural decision-making under the lowcarbon transition, the framework provides a reference model that is flexible and adaptable, and facilitates learning and dialogue processes more than prescriptive processes. Empirical application and validation are identified as important directions for future research.
In the context of accelerated digitalisation, small and medium-sized enterprises (SMEs) increasingly operate within complex digital ecosystems that both enable growth and amplify systemic risks. Existing bankruptcy prediction models often fail to address these evolving challenges, especially in emerging markets such as Serbia. This study addresses the need for effective early-warning mechanisms by developing a data-driven bankruptcy prediction model tailored to Serbian economy. Unlike general corporate studies, this research represents a pioneering effort in the region by focusing on SMEs and integrating neural network algorithms. Utilising a balanced sample of 212 SMEs (106 solvent and 106 bankrupt), matched on key criteria such as employment, income, liabilities, and industry, the model integrated neural networks with traditional financial ratio analysis to predict bankruptcy one and two years in advance. The dataset comprised financial statements spanning from 2016 to 2022, incorporating 66 explanatory variables covering various dimensions of business performance. The findings confirmed the hypothesis, and this approach yielded superior predictive accuracy compared to established models like the Z-score and EMS. Results demonstrated exceptional accuracy, with one-year-ahead AUC at 0.945 and the two-year-ahead model achieving an AUC of 0.835. These predictive tools serve not only as academic contributions but also as practical instruments for policymakers, financial institutions, and enterprise managers, fostering resilience and sustainable economic development in a rapidly evolving digital landscape.
Small and medium-sized enterprises (SMEs) increasingly compete within European digital ecosystems where digital infrastructure, data analytics capability, and specialised human capital shape both access to advanced technologies and the ability to convert data into economic value. This study examines artificial intelligence (AI) diffusion in European SMEs through an ecosystem capability-stack lens, arguing that AI adoption is more plausibly explained bycomplementary “data readiness” foundations than by single-technology indicators. The analysis uses harmonised Eurostat indicators for EU Member States, combining ICT usage statistics on AI, machine learning for data analysis, cloud-based analytics, in-house analytics capability, and ICT specialist intensity with Structural Business Statistics measures of SMEs value creation (value added per enterprise). Methodologically, the article applies correlation analysis, principal component analysis to derive a composite Data Readiness Index, k-means clustering to identify cross-country ecosystem profiles, and parsimonious regression specifications controlling for GDP per capita in PPS. The results indicate that stronger analytics capabilities align with higher AI uptake, and that the composite data readiness measure predicts cross-country variation in AI diffusion. Furthermore, AI uptake and joint adoption bundles are positively associated with SMEs value creation, while diffusion remains uneven across the digital-intensity distribution, with data analytics growth concentrated among digitally advanced SMEs. These findings operationalise data readiness as a measurable ecosystem foundation for AI diffusion and highlight digital-divide mechanisms that can limit inclusive value creation within European SMEs ecosystems
This study examines how small and medium-sized enterprises (SMEs) assess the importance of sustainability through their attitudes toward key stakeholder groups in the Visegrad Four (V4) countries. Drawing on stakeholder and institutional perspectives, it examines whether community engagement, standardized management of supplier and customer relationships, and customer relations shape positive sustainability evaluations. Using survey data from 1,549 SMEs collected in the Czech Republic, Slovakia, Poland and Hungary, the analysis applies correlation and linear regression techniques at the country level. The findings show that stakeholder-related attitudes significantly influence sustainability assessments, although their relative importance varies between national contexts. Standardized management of supplier and customer relationships emerges as a consistent driver in all countries, while community engagement and customer relations exert differentiated effects. These results indicate that SME sustainability perceptions are grounded in relational practices rather than abstract compliance considerations. This study further highlights the role of stakeholder embeddedness under shared but heterogeneous institutional environments and offers practical insights for fostering sustainability-oriented mindsets among SMEs in Central Europe.
The study explores the correlations between the digitalisation of Romanian firms and their financial performance, liquidity, leverage, and the reputation of the chosen auditor, focusing on SMEs listed on the AERO market. The topic is relevant to understanding the relationships between digitalisation and firms' financial behaviors in the context of the limited empirical evidence available for Romanian SMEs. The analysis used data for the 2024 financial year, collected and validated in August-September 2025 based on publicly available sources and information reported by firms, in order to capture the effective level of digitalisation and the related performance. Digitalisation was operationalised through a composite index (DI), systems, and IT personnel, normalised and aggregated to reflect the overall level of digitalisation of each firm. The unit of analysis was the firm, and the estimated models included Spearman correlations for the association between DI and auditor reputation (H1 and H7), multiple regressions for leverage, profitability, and turnover (H2-H4 and H8), logistic regression for binary liquidity (H5), and Kruskal-Wallis nonparametric tests for sectoral differences (H6). To validate the results, the main hypotheses (H1, H3, and H8) were retested using weighted variants of the DI index, confirming the robustness of the observed trends. The results showed a positive correlation between digitalisation and auditor reputation, a higher level of digitalisation in the IT sector, and associations between digitalisation and certain financial characteristics (leverage and turnover), while firm size and immediate liquidity did not show a significant association. Apart from the relationships identified above, the other hypotheses were not statistically supported, highlighting that digitalisation manifests rather as a strategy of investment and firm resource management than as a direct determinant of financial performance. The results of the study revealed the need to further investigate the identified relationships through longitudinal studies and by using more complex indicators of digitalisation.
Digital transformation has become a defining feature for small and medium-sized enterprises (SMEs), as the adoption of digital platforms reshapes their market presence and facilitates access to new markets. The objective of this research was to determine the impact of digital platforms on the competitiveness of the surveyed SMEs and, in parallel, on their access to new markets. Specifically, the study examined the relationship between Romanian SME managers' self-reported assessments of their firms' competitiveness and their firms' access to new markets. The four research hypotheses were derived from established theoretical frameworks, namely, the Resource-Based View (RBV), Dynamic Capabilities Theory (DCT), and the theory of digital platform ecosystems. Primary quantitative data were collected through a survey administered to Romanian SMEs during October 2025, with the questionnaire completed either by the company's manager or by another company's representative. The analysis of quantitative data for the sample (150 companies) involved computing Cronbach's alpha coefficients and item-total correlations to assess the reliability of the multi-item scales used to measure the impact and benefits of platform use. In addition, Spearman's rank correlation coefficient (rho) and the Mann-Whitney U test were employed to evaluate the four hypotheses, given the violation of the normality assumption. To appropriately model the ordinal self-assessment data and to control for firm-level hypotheses were supported, with the important caveat that the empirical results should be interpreted as associative rather than causal relationships. The main conclusions emphasise the necessity of accelerating digitalisation and formulating integrated strategies or comprehensive digital transformation plans, enabling SMEs to fully exploit the opportunities provided by the contemporary digital economy.
This article explores the role of digitalisation in the internationalisation of Romanian small and medium-sized enterprises (SMEs) in various industries. The purpose of the research is to highlight how SMEs use digital technologies, such as artificial intelligence, cloud computing, and data analysis platforms, to expand their presence in foreign markets and improve their competitiveness and organisational performance. The study is based on a qualitative method using semi-structured interviews with 10 Romanian managers and founders of SMEs active in foreign markets. Thematic analysis of the data identified the main benefits of adopting digital tools, including operational efficiency, access to strategic information, and facilitation of international collaboration, but also the associated challenges, such as adapting technologies to local requirements and technical and cultural barriers. The results highlight the importance of digitalisation in the internationalisation of SMEs and offer useful insights for decision-makers who want to stimulate and support the competitiveness and performance of their organisation, with cloud computing and artificial intelligence digital tools emerging as key catalysts. The contribution of this research is to advance a multivalent and integrative perspective based on the role, benefits, and challenges associated with digitalisation in relation to the internationalisation of SMEs.
The study explored and interpreted the perceptions of managers of Romanian small and medium-sized enterprises (SMEs) in the e-commerce sector regarding the effects of adopting data analytics and artificial intelligence technologies on decision-making processes and financial performance. The research was conducted using a qualitative approach based on 25 semi-structured interviews with managers and business owners. The data were processed through manual coding, supported by thematic analysis using QDA Miner Lite. The following dimensions were examined: the level of adoption of digital technologies, the factors that drove their implementation, the perceived influence on the decision-making process, and the effects on financial performance. The results revealed an intermediate level of digital maturity, dominated by the use of descriptive analytics, while AI applications were only partially implemented. The main barriers identified were the deficit of digital competencies and financial constraints, with variations across firm size categories. As these barriers are overcome, the adoption of data analytics and artificial intelligence technologies contributed to a more rigorous grounding of decision-making and to improved financial performance through sales optimisation, cost reduction, and inventory management efficiency. The study provided a contextualised understanding of the adoption of advanced technologies by Romanian SMEs, capturing specific features and nuances of managerial experiences that are difficult to quantify through quantitative approaches, thus contributing to the expansion of empirical knowledge in the field of e-commerce.
Digital transformation has driven small and medium-sized enterprises (SMEs) to integrate into digital ecosystems (platforms, cloud solutions, and digital collaboration); however, the mechanisms by which this integration translates into performance remain insufficiently explained, particularly in emerging economies. This study investigates the relationships between digital ecosystem integration, data and artificial intelligence capabilities, adoption barriers, and perceived performance among Romanian SMEs using a quantitative methodology. Data were collected via a questionnaire administered to a sample of Romanian companies and analysed using Partial Least Squares Structural Equation Modelling (PLSSEM) with bootstrapping. The empirical results highlight a full mediation phenomenon, indicating that access to and mere presence within digital ecosystems do not directly guarantee performance; rather, performance is achieved only if the firm transforms these resources into data analytics and AI automation capabilities. However, the results confirm that a developed digital ecosystem strongly stimulates firms' capacity to utilise these tools. Multi-Group Analysis (MGA) demonstrated that this mechanism is robust and valid regardless of firm size. The study provides new insights regarding digital ecosystems and the digital capabilities of SMEs, presenting managerial implications for prioritising investments in data, analytics, and AI.
This research aims to highlight the role of digitalisation and innovation at the level of Small and Medium-sized Enterprises (SMEs) in shaping the business environment and enhancing the economic performance of companies in Central and Eastern Europe (CEE). The methodology is based on two modern econometric modelling techniques, namely spatial analysis, implemented through spatial regression methods founded on Spatial Error Models (SEM), and Quantile-on-Quantile Regression Models (QoQRM) using the bootstrap method, which is employed for the analysis of the conditional distribution of variables. This approach allows the assessment of the impact of digitalisation and innovation within SMEs on firm performance across the entire conditional distribution of results. These models are used at the level of a complex database that includes a set of specific indicators compiled for ten different CEE countries for the 2017-2024 time span. The results show that the economic performance of SMEs in CEE depends on targeted and adapted digitalisation andtechnological innovation strategies that match the companies’ capacities, efficient financingand collaboration mechanisms, as well as the alignment of product and process innovation with economic resources and market orientation. This study is an original contribution that highlights the diverse and conditional effects of digitalisation and innovation on SMEs in CEE countries, demonstrating that their impact on investment, turnover, and employment is not uniform, but depends on the initial level of performance and the structural context of the examined economies. This emphasises the need for tailored policies aimed at strengthening the specific capacities of enterprises and reducing regional disparities.
Digitalisation and sustainability represent essential strategic directions for European SMEs, being driven by both competitive pressures and recent ESG and CSRD reporting requirements. However, the specialised literature provides little empirical evidence on the interdependencies among digital practices, sustainability practices, and sustainable performance, particularly among SMEs that actively use digital tools. This study investigates how digital practices contribute to sustainable development and performance, using an integrated conceptual model and Partial Least Squares Structural Equation Modelling (PLS-SEM) to analyse a sample of 300 SMEs from the services and manufacturing sectors, selected through non-probabilistic convenience sampling. Data was collected through a self-administered questionnaire addressed to SME managers and owners, which should be taken into consideration when interpreting the results. The results indicate that digital practices positively influence both sustainability practices and sustainable performance, and that sustainability partially mediates the relationship between digitalisation and performance. The model demonstrates adequate fit and satisfactory predictive capacity. From a theoretical perspective, the study contributes to the digital sustainability literature by providing an empirically testable, integrated structural framework regarding the relationships among digitalisation, sustainability, and performance in SMEs. From a managerial perspective, the findings provide a solid empirical framework for guiding strategic decisions, highlighting the need for integrated strategies that combine digital transformation with sustainability initiatives in SMEs.
The study addressed a gap in the literature by examining how multiple dimensions of digital transformation jointly shaped performance outcomes among Romanian sportinggoods retailers, a sector rarely analysed in empirical research. The purpose was to determine the extent to which digital usage, strategic digital orientation, data-driven decision-making, and collaborative innovation contributed to perceived competitiveness, market access, and operational efficiency. Primary data were collected through a structured survey of 619 retailers, and three independent ordered logit models were estimated to assess relationships. The analysis revealed differentiated effects across the three outcomes, highlighting the central role of digital engagement and strategic orientation, while showing that collaborative innovation generated selective benefits. The article offered both theoretical contributions (by integrating multiple digital constructs into a unified empirical framework) and practical implications for retailers seeking effective digital ecosystem integration.
The main objective of the research was to analyse the influence of small and medium-sized enterprises involved in e-commerce ecosystems on the recycling of waste electrical and electronic equipment and on the circular use of materials in the European Union. A quantitative, exploratory-explanatory approach was adopted to conduct the research, and two regression equations with panel data were used to test the hypotheses. The model was selected by applying the Hausman test; specific tests for panel data were also applied. The results justified the use of robust Driscoll-Kraay errors, capable of providing consistent estimates. The two regression equations involved two dependent variables (the recycling rate of separately collected waste electrical and electronic equipment and the circular use rate of materials) and four independent variables (percentage of enterprises with e-commerce sales; value of e-commerce sales; percentage of enterprises using social media; percentage of enterprises paying for online advertising). The research results confirmed the positive influence of small and medium-sized enterprises' involvement in e-commerce ecosystems on the circular material use rate in the EU. The analysis of the circular material use rate revealed positive and significant effects on three indicators characterising e-commerce ecosystems: the share of SMEs with online sales, social media use and paid online advertising.
An increasing number of enterprises have begun to turn to cloud-based solutions, such as Cloud ERP systems, to automate and improve their business activities. In order for their use to generate the expected benefits, the informed choice of Cloud ERP (Enterprise ResourcePlanning) services to be implemented can be considered an essential factor. The objectiveof the current study is to analyze users’ opinions on the implementation and use of variousCloud ERP services available internationally. Analyses are performed based on userreviews of the Cloud ERP services they have worked with. A total of 99 reviews for34 Cloud ERP services were collected from the Gartner Peer Insights platform. Excel wasused to analyze the mean scores grouped by each service, by implementation dimensions,by services and by industries, as well as the number of implementations by country. Thecollected data were coded using NVivo 15 and then grouped into general themes.Subsequently, qualitative analyses were performed based on the number of occurrences ofcoded references and sentiment analyses on the responses provided by reviewers in theopen-ended questions. The highest score was achieved by the “Planning and Transition”stage. Most reviews come from India and the US and were made by users in the IT servicesfield. The results obtained illustrate the positive outlook for the use of various Cloud ERPservices at the enterprise level, given that most reviews are positive or moderately positivein tone. The study contributes to the specialized literature in the field by analyzing the realopinions of users, data source rarely used to date.
Digital transformation is a disruptive force that compels SMEs to fundamentally reconfigure their business models to remain competitive. This research analyses the impact of digitalisation factors, namely the digital skills of the staff, the digital transformation strategy, and the digital methods, means, and tools, on the strategic position of SMEs, while exploring the mechanisms that arise. This study used a mixed research methodology, combining based on a survey with 281 respondents from Romania. The PLS-SEM results confirm the influence of digitalisation on strategic performance, especially through the optimisation of organisational processes and the strengthening of the relationship with customers. The ANN analysis complements these findings, capturing nonlinear relationships and identifying the relationship with customers as the most important predictor of strategic success. Valuable insights are thus offered for SME management, demonstrating that the strategic value of technology is conditioned by its functional integration into workflows and interaction with market actors.
This study examines the perceptions of managers in small and medium-sized enterprises (SMEs) operating in the HoReCa sector in Romania regarding the adoption of digital technologies and their impact on competitiveness and organisational processes. The research adopts an exploratory qualitative approach, based on semi-structured interviews conducted with managers of units of various types (hotels, restaurants, caf & eacute;s, guesthouses), size, and geographical location (urban and rural). The reflexive thematic analysis led to the identification of four main analytical themes: digitalisation as a strategic necessity, the benefits of digitalisation, the barriers to digitalisation and the impact on performance. The findings indicate that digitalisation contributes to increased operational efficiency, improved customer relationships and professionalisation of decision-making processes, while being constrained by costs, a lack of digital skills, and structural vulnerabilities specific to the HoReCa sector. The study introduces the concept of dissonant tempo (the divergence between the planned pace of digitalisation and the reactive pace of the HoReCa sector) as an explanatory factor of the underutilisation of adopted technological solutions. The research provides relevant contributions to extend the TOE (Technology-Organisation-Environment) framework and dynamic capabilities theory, with practical implications for public policies and managerial strategies in emerging economies.
Digitisation has become an essential condition for the competitiveness of small and mediumsized enterprises (SMEs). This paper aims to understand how artificial intelligence (AI) is integrated into the business processes of SMEs by conducting quantitative marketing research on a sample of 285 companies operating in different regions of the country. The objectives of the research were to identify the behavioural patterns exhibited by SMEs with regard to the adoption of AI, to explain the factors influencing the perceived relative advantage in adopting new digital technologies, and to highlight the determinants of business performance. Confirmatory factor analysis applied to the data yielded original results and revealed the particularities of implementing the Technology-Organisation-Environment (TOE) model in the adoption of new technologies by SMEs in Romania. The results show that perceived relative advantage is mainly determined by competitive pressure and support from company management, while company size has a modest negative influence. Government support and AI use are not significant predictors. Furthermore, perceived relative advantage is a key mediator linking strategic and organisational factors to performance. It fully mediates the relationship between top management support for AI adoption and business performance and partially mediates the relationship between competitive pressure and performance. Government support has a direct and independent contribution to business performance, while company size and AI use do not have significant effects on performance at present.
