In the European Digital Decade 2030 Policy Program, the following guidelines for European digital transformation are named, which means that more than 90% of small- and medium-sized companies reach at least a basic level of digital intensity. In addition to that, the European Commission pays a lot of attention to implementing the “Green Deal” in order to achieve less environmental impact. ICT SMEs already play a key role in Europe’s green and digital transformation, creating technologies that promote sustainability and strengthen Europe’s position. The limited and fragmented application of today’s digital and sustainable technologies in SMEs is observed at the EU level. The bibliometric literature analytical results show that the number of papers on the digital direction is five times higher than on the sustainable direction topic. The paper seeks to identify directions that could help SMEs to speed up this twin transformation in each EU country. The authors proposed a two-stage methodology, which is used for researching twin transformations in SMEs. According to the methodology, first, the authors analysed the indicators of EU-27 SMEs, representing their activity towards the twin transformation, comparing them among other size classes. The results show that the SME’s numbers in the 16 indicators area are worse than the numbers characterizing EU-27 enterprises, having more than ten employees. In addition, a multi-criteria decision making-based assessment framework was constructed to show the progress towards the twin transition. The provided research shows which areas require more attention from SMEs and policy makers responding to the twin transformation objectives.

Digitalisation provides access to an integrated network of information that can benefit society and businesses. However, the evidence of sustainability in business is less researched. In our paper, by building up the research approach, we address the relevant gap by investigating how sustainable development goals represent the interrelationship between digitalisation and sustainability. Such research is particularly important because understandings of digitalisation and sustainability determine how different actors, including business managers and policymakers, act in response to those imperatives to develop future employees skills starting from school age. Following a multi-method approach, we have combined our analysis into two steps examining the relationship between digitalisation and sustainability. Building digital networks, business managers and policy makers using digital means can create some unique opportunities to strategically address sustainable development challenges for the United Nations Targets (SDG) to ensure higher productivity, education, and an equality-oriented society. This point of view describes the potential of digitalisation for society and businesses of the future. The authors revise the links between digitalisation and sustainability in the European Union countries by using data available in Eurostat and UNECE public databases. The two-stage methodology for the identification of the relationship between ICT and sustainability is used in the paper and a linear regression model is applied. The results showed tiers with five SDGs, focusing on business, and all these tiers are fixed in the constructed equations for each SDG. The recommended solution is statistically valid and proves the novelty of this research. Among digitalisation indicators, only mobile-cellular subscriptions and fixed-broadband sub-basket prices in part do not affect researched sustainable development indicators.

The problems of developing online decision support systems concern the complexity of the transportation management processes, the multi-dimensionality of data warehouses (DWs), and the multi-criteria of decision making. Such issues arise in the management processes by supporting them with adaptable information and communication infrastructure for the management of the freight’s transportation processes. Our research domain involves the assurance of infrastructure for the provision of smart services for the operative management of multi-modal transportation of freights under the conditions of the heterogeneity of communication channels and multi-criteria decision support. The complexity of managing multi-modal transportation processes raises some problems for ensuring the infrastructure for finding more optimal management solutions by the requirements of green development. This research aims to develop the approach for providing the infrastructure of intelligent smart services for adaptable implementation in management processes of online multi-modal freight transportation. The objectives are forwarded to construct the multi-criteria decision-making components and integrate them into the multi-layered, computer-based information management of intelligent systems. We present the steps of extension of the structure of the knowledge-based system with a multi-criteria decision support method, and the possibilities to work under the conditions of wireless networks and the recognition of context-aware situations. The results are demonstrated for the analysis of alternatives by assessing the multi-modal transportation corridors between the East and West regions of Europe, and the opportunities to evaluate them for more effective managerial perspectives under sustainable development requirements.

Consumer demand for organic products, rapidly growing urbanizations levels requires the food supply chain to reduce lead-time and maintain higher product quality. For the food supply chain to cope with the raising issues an e-commerce type of supply chain must be implemented. This approach creates challenges for supply chain, because the food industry must shift towards high variety and low quantity freight forwarding with multiple delivery points. The methodology of the paper consists of scientific literature analysis and macro indicator clustering. The author of the paper proposes a supply chain management framework, which is grounded through complexity theory. The framework mainly consists of 3 characteristics, which organizations should operationalize to maintain system resilience and which in the long-run would evolve to sustainable development–capabilities, collaboration, complexity management. The proposed framework defines how operational and tactical levels should be automated through cyber-physical systems, while the automation should be controlled through strategic level variables. The macro level analysis of existing EU markets of the food industry has been conducted to identify the food industry’s contingencies, in which an agent-based model will be used to validate the proposed framework. Main 3 clusters were identified, which number was chosen based on the elbow method and validated with the silhouette score of 0.749. The food industry can be categorized in to developing, underdeveloped, and developed food industries. Moreover, singularities of different contingencies have been identified which considers population size, population density, market size of the food industry and disruption intensity. The application of the framework depends on the identified contingencies. From strategic level the SCMF is similar in all contingencies, however, depending on the type of market, more emphasize on vehicle routing or demand forecasting should be made.

Mechanisms for sectoral change in the economy are being used to move towards a circular economy. Trade in recycled raw materials could contribute to circular economy development and is treated as the main circular indicator used to monitor progress toward a circular economy. However, the research area surrounding the transition to a circular economy lacks adequate tools, as until now, the circular economy has been investigated from an evolutionary and ecological perspective. In the article, the authors conduct a study identifying important variables for trade in recycled raw materials as the main indicator of CE development. The authors propose a two-step methodology for researching the links between main trade in recyclables and circular economy indicators. The authors found correlations between trade in recyclables and private investments in circular economy sectors. The authors used panel data analysis, compiled a regression matrix, and formed a dynamic regression model. The statistical tests showed that the formed regression model has no significant autocorrelation and heteroscedasticity. The framework can be applied in practice to serve policymakers and the academic community interested in analyzing the move toward a circular economy and its main circular indicators.

Introduction: Many forecasting methods are used to predict sales, such as the moving average method, naive method, exponential smoothing methods, Holt's linear method, and others. The results brought by these models are quite different. Forecast delivered by the naive method is entirely accurate for an extended period, like 3–5 years, Holt's methods are bringing accurate one-year period forecasts. The planning decisions have several levels, meaning different forecasting results. However, the authors that are testing various forecasting methods are not discussing results researched in different planning levels (retail chain and different pharmacies). The study is given to the construction of the forecasting model covering both planning levels, which later is empirically tested for the Lithuania retail case:Purpose: The development of the forecasting model for reduction of shortages in drug supply. To achieve this goal, the author revises the improvement of drug availability weekly.Research Methodology: The construction of the forecasting model is incorporating outliers' detection methods and sales by pharmacies to minimize shortage. In the forecasting model, the author uses Theil's U₂ test to evaluate forecasting accuracy.Findings: During analysis, the author constructs the model application for forecasting drug sales where weekly availability is highly recommended. The results show that forecasting on individual pharmacies level using the integration of these plans approach leads to higher accuracy.Research Limitations: The research covers 3 months of sales data. Das and Chaudhury suggest for short-sales period products use 36 days' time horizon. Ayati et al. discuss short and long-term time horizons for planning sales of drugs. Kanyalkar and Adil analyzed multi-site production and suggest that the time horizon should cover the longest lead time required for delivery of raw material, which is 12 weeks, and select 3 months (i.e., 13 weeks) as short-term time period horizon. Wongsunopparat and Chaveesuk forecast drug sales for 1-month and 12-month periods and compare the results. In this study, the focus is on short-term time-horizon, which is considered as 3 months period and also represents the longest lead-time. In the future, the study could review other periods. The author has incorporated the review of eight forecasting methods into the study by leaving other forecasting methods unresearched. Future studies could also incorporate different ARIMA methods into shortage reduction case analysis.Practical Implications: Presented forecasting model could be useful for practitioners, which analyze the reduction of the shortage of prescribed drugs. There the revision of repeated purchases is recommended for national authorities, wholesalers, and pharmacies aiming to minimize shortage.Originality/Value: The analysis to reach the highest forecast accuracy and identification of a forecasting approach which responds to the fluctuation of weekly sales for the whole pharmacy chain and separate pharmacies. The study contributes to drug sales review, where most authors analyze the total volume, which is not separated by pharmacies.