With the rise of Industry 4.0, novel technologies open new opportunities for business transformation. These technologies change supply chains and drive new ways to create value. However, not all companies chose this path of digitalization due to significant investment costs, and thus risk becoming laggards. This article analyses three key areas of digital technologies development and their impact on the transformation of supply chains, including the emergence of closed loop chains as the basis for a circular economy. This paper provides practical examples of supply chain digitalization, as well as its socioeconomic and environmental effects. It will be shown that the formation of a common information space for all participants and the transformation of the supply chain into an ecosystem has the greatest influence on supply chains.
The article provides terminology for processes of digitalization and digital transformation. For structuring digital transformation processes, the authors offer a modification of the strategic scorecard and distinguish technologies as an additional perspective. Using business cases, the authors analyzed approaches to digital transformation, revealed principal digital transformation models, and described them. The interrelations between targets, models, and strategies of digital transformation are demonstrated. The authors argue that digital transformation has to be considered to be a part of corporate strategy rather than isolated processes, with common strategizing tools and metrics applied. External and internal environment elements for digital transformation are structured. It is shown that the internal digital environment can be evaluated with the companies’ digital maturity models. The external environment has a complex structure that can be described by the digital economy and society development in a country, a region, and a city; digital intensity level in an industry; and a digital ecosystem potential. All the authors’ contributions and conclusions are based on research papers, public statistical data, and analysis of Russian and foreign companies.
Environmental and social impact of the world economy is increasingly attracting public attention around the globe. The society expects from the businesses a responsible action towards depletion of scarce natural resources, environmental pollution, and people-so as to achieve sustainable development goals. An essential element of today's economy, supply chains represent networks of companies that create and deliver products and services to the ultimate customers. The present paper classifies scholarly research in sustainable supply chain management in terms of its main paradigms, and further reviews research work centred around the circular economy paradigm-designated commonly as closed-loop supply chain management. We offer a literature review that updates the taxonomy of this research area originally proposed by Atasu et al. in 2008. To this end, we describe analytical modelling and decision-support approaches adopted in the literature, as well as main insights offered by these. In particular, we focus on the studies that have an integrated perspective at closed-loop supply chain management by addressing supply-chain design and coordination problems and taking into account operational-level aspects. We further classify the work within the design and coordination research stream, identify connections emerged between different streams of literature over time, and suggest directions for future work.
The purpose of the study presented in the paper is to highlight the influence of the microeconomic factors related to the evolutionary stage of the industry’s life cycle on the industry dynamics. The authors use the example of the Russian tourism industry to show that microeconomic factors are important, along with the macroeconomic, market, and demand characteristics external to the industry. Data mining was applied to obtain data from the industrial enterprise database and Rostourism official documents since there are no regular Russian statistics on firms’ exit and new entry. The authors used annual ranked listing of firms by their revenues to determine the structural indicators of the industry. The results confirm that it is important to consider not only the demand and macroeconomic indicators, which are external risks in relation to the industry, but also the internal processes at the different stages of the product cycle. In a sufficiently long period, the influence of microeconomic indicators may be no less strong than the business factors of financial risk. One should take this into consideration in econometric modeling on long time-series.
In the article, we will share the experience of implementing PBL at the Master program on Business Management in the Digital Economy held in Saint Petersburg University. Specific conditions for the PBL organization are highlighted. First, digital transformation process is quite difficult to realize in companies, as no clear methodology for its implementation exist yet. Second, pandemic left the only opportunity for online communication, and all usual administration and education processes had to be changed. The experience is structured and presented with recommendations for similar projects.
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