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![The three stages of value migration. Source: [59].](publication/327356717/figure/fig1/AS:665996511674380@1535797350940/The-three-stages-of-value-migration-Source-59.png)
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![Figure 1. The three stages of value migration. Source: [59].](publication/327356717/figure/fig1/AS:665996511674380@1535797350940/The-three-stages-of-value-migration-Source-59_Q320.jpg)
The topic of a sustainable business model is currently the subject of much scientific research that covers a wide range of topics, from terminological aspects to aspects related to the impact of sustainability factors on company development. So far, however, the topic of sustainability in business models operating in electronic markets has only bee...
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Context 1
... value migration has three stages which were presented in Figure 1: (A) Value inflow: In this phase, a company or an industry captures value from other industries or companies due to superior value proposition. The market share and profit margins of the company or industry expand. (B) Stability: In this phase, competitive equilibrium is established. Growth rates moderate. (C) Value outflow: Value starts to move away towards companies or industries meeting evolving customer needs. In this phase, market share declines, margins contract, and growth stops ...
Context 2
... value migration has three stages which were presented in Figure 1: (A) Value inflow: In this phase, a company or an industry captures value from other industries or companies due to superior value proposition. The market share and profit margins of the company or industry expand. (B) Stability: In this phase, competitive equilibrium is established. Growth rates moderate. (C) Value outflow: Value starts to move away towards companies or industries meeting evolving customer needs. In this phase, market share declines, margins contract, and growth stops [59]. The causes of value migration are: Customer priorities, an essential catalyst for value migration, change due to a multitude of factors. Hence, there could be several drivers of value migration. Some The causes of value migration are: Customer priorities, an essential catalyst for value migration, change due to a multitude of factors. Hence, there could be several drivers of value migration. Some time-tested drivers are (1) technology; (2) cost; (3) convenience; (4) lowering of entry barriers; (5) lower switching costs; (6) easier access to capital and (7) innovation ...
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Citations
... China has acknowledged the significance of the digital economy and has undergone a distinct phase characterized by medium-to-high growth and a focus on innovation and global competitiveness. In short, digitalization is now an essential economic model that will affect the sustainable development of China-and all other countries-in the years ahead [11][12][13]. ...
The digital economy promotes economic development, industrial upgrading, and environmental protection. In this study, we calculated green total factor productivity (GTFP) based on the SBM-DDF model and used the entropy method and principal component analysis to calculate a digital economy index. We used panel data from 282 Chinese cities to measure the driving effect of the digital economy on green total factor productivity. The study results show that the digital economy significantly increases GTFP. We then assessed the heterogeneity of this impact. We also explored the mechanisms by which the digital economy promotes green development and found that the digital economy can indirectly increase industrial production efficiency by promoting innovation in green technologies.
... China has recognized the importance of the digital economy and experienced a new phase characterized by medium-to-high growth and a focus on innovation and global competitiveness. Digitalization is an essential economic model that affects the country's sustainable development in the future [11][12][13]. ...
... Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 11 January 2024 doi:10.20944/preprints202401.0920.v111 ...
The digital economy promotes economic development, industrial upgrading, and environmental protection. This article calculates the green total factor productivity (GTFP) based on the SBM-DDF model and uses the entropy method and principal component analysis to calculate the digital economy index. We use panel data from 282 Chinese cities to test the driving effect of the digital economy on green total factor productivity. The study results show that the digital economy significantly increases GTFP, and the heterogeneity of this impact is further explored. We also explored the mechanism of the digital economy in promoting green. The digital economy can indirectly increase industrial production efficiency by promoting innovation in green technologies.
... How to achieve high-quality economic development? This is an urgent practical problem to be solved [12]. From the existing literature, on the one hand, except for Chen Xiaohong and Jiang Qiping, who have discussed the theoretical issues of the digital economy, there is little literature that systematically explains the connotation of new technologies, new structures, and new values in the digital economy [13]. ...
This paper first starts with the positive impact of digital technology on both industry and society levels and puts forward the hypothesis that digital technology has a facilitating effect on economic quality development. Secondly, the evaluation system of economic quality development is established, and the BP neural network algorithm is used to synthesize each basic index in the evaluation index system. Then the basic measurement model is constructed based on the hypothesis, and the objective indicators are given weights by CRITIC-entropy combination weighting model and TOPSIS method. Finally, the hypotheses are analyzed empirically using benchmark regression while robustness tests are conducted. The study shows that for every 1 standard deviation increase in the digital development index, the logarithmic value of economic quality development will increase by 2.38%.
... Authors whose studies we include in the cluster 'The joint contribution of the sharing economy model and the concept of CSR towards reduction of overconsumption and wastage' state that the principles of the sharing economy have great potential in the field of social responsibility precisely because of this sharing. This is to say that sharing makes it possible to significantly reduce excessive consumption (Jabłoński, 2018) and waste (Mazzucchelli et al., 2020), which is one of the basic ideas behind the concept of CSR. The two concepts are therefore intertwined. ...
The sharing of idle assets, on which the sharing economy model is based, is associated with positive economic, environmental, and social effects, the creation of which is the basis of the concept of corporate social responsibility (CSR). It would therefore seem expedient to examine the context of these phenomena, which have recently been gaining in importance, although they still remain outside mainstream research. So far, there is no study which comprehensively characterises the current state of knowledge of the context of the sharing economy and CSR, identifies research gaps, and postulates directions for future research in this area. This article addresses this gap by utilising a standalone literature review approach. An analysis of 20 publications, published on this topic in 2017–2021 in journals registered in the Web of Science and Scopus databases, was carried out. Four main research clusters were identified, these being (1) The sharing economy as a tool of the CSR concept; (2) The joint contribution of the sharing economy model and the concept of CSR towards reduction of overconsumption and wastage; (3) The importance of CSR communication for sharing economy platforms; and (4) The antagonistic relationship between the sharing economy model and the concept of CSR. The performed analysis shows the fragmented nature of existing research, but also the progressive nature of this area of research. At the same time, useful avenues for future research are postulated. This should focus on multiple lines of inquiry, including the possibility of incorporating different forms of B2B sharing into the concept of CSR, assessing the benefits, limitations, and risks of linking these two concepts, as well as exploring the synergies between the sharing economy model and the concept of CSR from the point of view of different industries, sharing segments, or regions.
... The technologies that characterize the digital economy contribute to sustainable development, providing innovations that help improve people's standard of living and providing advanced techniques to protect the planet, ensuring organizational profitability. In this case, ICT is integrated into the three pillars of sustainability -environmental, social, and economic [4]. However, the positive results of the digital revolution taking hold of global economies are associated with multiple sustainability concerns. ...
This study aims to analyze the interconnection between the concepts of digital economy and sustainability. These concepts have become popular due to awareness of climate change and increased development and adoption of technologies. Researchers, business leaders and policymakers are exploring the many ways digital technologies can be used to address sustainability issues. Using a systematic literature review with a bibliometric analysis, we examined a sample of 92 studies indexed in SCOPUS to identify research activity on this topic through April 2023. We found that 2022 had the highest number of peer-reviewed papers on the subject, with 31 publications. During the research, we also identified multiple opportunities for this interconnection, such as developing renewable energy and sustainable technological solutions, smart cities and sustainable urbanization, and sustainable consumption. These opportunities enabled by digital technologies allow companies to adopt sustainable business strategies and develop sustainable products. Despite these opportunities, the digital economy presents several challenges that can hinder efforts to achieve sustainability goals, such as increased e-waste, high energy consumption and rising carbon emissions, digital divide, job insecurity, growing monopolies, and data protection. These issues must be addressed to enable optimal use of the opportunities presented in the digital economy to promote sustainability.
... So, this is quite consistent with the task of maximizing profits in conditions of limited resources. In support of this thesis are, in particular, the theory of the triple bottom line (TBL), an approach to building a competitive advantage based on the attributes of sustainable development, a model of the network economy, the theory of property rights and the concept of corporate social responsibility [30]. In this case, the need to comply with the principles of sustainable development requires appropriate changes in the economic behavior of the company. ...
The object of this study is the economic behavior of companies. The study solved the problem of conceptualizing the economic behavior of companies, taking into account the need to adhere to the goals of sustainable development and the use of smart technologies. It has been established that to assess the level of sustainable development of companies, economic, environmental, social, and managerial criteria based on corporate social responsibility are used. It is determined that smart technologies are associated with the introduction into production of cyber-physical systems integrating information and communication technologies into physical processes. To expand the possibilities of assessing the use of smart technologies, it is proposed to collect data on the expenditure of companies for a particular technology and the amount of revenue generated using this technology. The structural model for measuring the relationships between the use of smart technologies, sustainable development, and the economic behavior of companies was calculated using the PLS-SEM method. It has been established that currently, in fact, an increase in the burden on the environment, extensive use of resources for the countries of the European Union and Ukraine activates the economic behavior of companies because the coefficient of the path for load indicators is 0.916. At the same time, increasing the use of smart technologies by 1 will increase economic development indicators by only 0.104. This indicates a lesser power of the link between economic behavior and the use of smart technologies. However, the statistical significance and positive direction of the relationship between economic behavior and the use of smart technologies gives reason to recommend that the management of industrial companies pay special attention to the development of the integration of smart technologies into business processes.
... The third objective is to transform new energy industries digitally. The increased usage of digital technologies constantly generates new industrial growth points, providing tremendous force for the long-term development of new energy enterprises (Jabłoński, 2018). Besides, scholars also investigate how the digital economy impacts enterprise business models (Tan et al., 2007), organizational structures (Nuryaman, 2015), governance mechanisms (Gopalakrishnan and Mohapatra, 2020), Etc. ...
The integration of digital technologies is exhibiting an upward trend in Chinese enterprises, and the degree of corporate credit risk is directly proportional to their financial sustainability. Based on panel data of new energy enterprises from 2012 to 2020, this article makes an empirical study on the direct effect, mediating effect, and moderating effect of the digital economy (DE) on the new energy enterprises’ credit risk. It is found that the digital economy could significantly mitigate the credit risk of new energy enterprises by improving total factor productivity and amplifying the potential default cost. When the digital economy affects corporate credit risk, the development of the new energy industry acts as an intermediary, and knowledge spillover acts as a moderator. Furthermore, considering knowledge spillover as the threshold variable, the digital economy has a double-threshold effect. The marginal impact fluctuates from dropping to increasing as the knowledge spillover level increases. As for the region’s heterogeneity, the digital economy has benefited eastern China more than central and western China, possibly due to the differences in economic structure, capital intensity, and policy institutions. In view of these findings, this study provides a reference for China to mitigate corporate credit risk in the digital economy era.
... Using this question (what kind of thing is value?), we have identified several explicit definitions of value, which refer to it as a "broad set of benefits derived by a stakeholder from an exchange" (Yang et al., 2014, p. 314), or as "balance between the effort and the result," or "the benefit one gets versus the cost" (M. Jablonski, 2018, p. 3122, based on Mahajan, 2017, or "the delimitation of a . . . need . . . ...
... Accordingly, group (a) types can be blended value (Emerson, 2003;Reficco et al., 2018), collective value (Gauthier & Gilomen, 2016), exchange value versus use value (Bocken et al., 2013;M. Jablonski, 2018), functional value (Joyce & Paquin, 2016), shared value (Al-Saleh & Mahroum, 2015;Baldassarre et al., 2017;Bittencourt Marconatto et al., 2016;Bocken et al., 2013), sustainable value (Abdelkafi & Täuscher, 2016;Bocken et al., 2019;Evans et al., 2017;Maassen, 2018), value (un)captured, value destroyed, and value missed , among others. Som ...
... SBM literature provides ample knowledge about different valuerelated processes or mechanisms that occur within business models-starting from offering, creating, delivering and capturing value (considered as the pillars defining a business model, as in Richardson, 2008), and extending to a wide range of value transformation processes, including redirecting, exchanging and migrating value (M. Jablonski, 2018), and shaping value (see Geissdoerfer et al., 2018, p. 713 for "value circle"). However, we find that reduction to SBM mechanisms, by which valuing processes are confused with production or exchange of valued objects, is a widespread problematic pattern (P4) and one of the main issues to be addressed, due to its far-reaching implications for theorizing on value in SBMs more generally (as highlighted in the Integrated Discussion section below). ...
Although the concept of value is central to sustainable business models (SBMs), the field has struggled to clarify what value is. SBM research accounts for multiple forms of value directed at multiple stakeholders. We argue that this diversity challenge should be addressed not by seeking a field-unifying definition of value but by developing methodological guidelines for a field-specific approach to defining value in SBM contexts. Based on Aristotelian logic and philosophical phenomenology of value, we develop an analytical framework that can be used for generating good definitions of value. We use this framework to explore approaches to value in extant SBM literature, highlight problematic patterns in applications of this concept, and suggest ways to avoid these patterns. The result is a guide to assist SBM researchers in exploring and defining value, and in applying their definitions consistently in theory building efforts.
... The growth of the significance of innovation in shaping enterprise-value and the isolation of methods that are dedicated to assessing enterprise innovativeness in the context of efficiency of the innovation-management process [28,29]; Creating business models that are focused on increasing the effectiveness of creating enterprise value [30,31]; ...
A study of the efficiency of the energy companies that are listed on the Polish capital market, which will be the object of the analysis in this paper, is focused on assessing the degree of accomplishment of their basic financial objectives, namely, the maximization of their market values. The main research methods that are used in the article are methods for analyzing and evaluating the literature (in order to present the current scientific achievements in the field under study) and descriptive statistics and mathematical statistical methods for analyzing the interdependence of the phenomena (used to characterize and compare the analyzed energy-sector companies, as well as to quantify the determinants of the value-creation efficiency of these companies). This article is focused on the conditions and problems that are related to the decision-making processes that are aimed at increasing efficiency in the area of building enterprise-value. These require the use of tools for efficiency measurement that enable management to quantify and assess changes in an enterprise’s market value and the efficiency of its creation. Within the conducted research, it has also been proven that this is the market perspective that is of key significance from the point of view of the criteria of making financial management decisions. The market perspective reflects the expectations of the majority of company stakeholders, to the fullest. The study showed that the allocation of capital in the listed energy companies during the period of 2014–2020 was subject to a relatively high risk of losing the economic value of the invested capital. In terms of asset value, dividing the studied group of companies into portfolios of two groups of companies additionally showed that the volatility of the market and equity returns for the smaller companies was higher than it was for the larger companies.
... Here, IBM's idea was summarized and extended with energy, sustainable development, and value migration components. First, the digital economy and the established SDG lead to value migration [36]. Intelligent workflows' capabilities are designed and delivered in modules using cloud-centric approaches and they also deliver the new value [5]. ...
Currently, emerging technologies support many problems arising in the energy industry. The “cognitive enterprise” concept, introduced by the IBM company, assumes that emerging technologies are used together with cognitive workflows to increase enterprise intelligence. The pursuit of enterprises from the energy sector to obtain the status of a cognitive enterprise requires the use of many emerging technologies, including cognitive technologies. Thus, the aim of the paper was to present the current state of research and identify the core components of the cognitive enterprise. To analyze the trends and challenges in scientific research development, the bibliometric approach was used. The analysis was made by means of the Web of Science and Scopus platforms; 70,177 records were retrieved. The results comprise the geographic distribution of research and the time analysis as well as the author and affiliation analysis. Additionally, descriptive statistics are provided. Consequently, the research milestones regarding the transformation of the traditional energy enterprise into the cognitive enterprise were defined. The findings of this research have supported the construction of the conceptual framework of the core transformation components for the cognitive energy enterprise. The study have several theoretical and practical implications. The proposed framework could be used to assess the level of readiness for transformation from the traditional to the cognitive energy enterprise. The discovered scientific gaps can constitute future research directions on cognitive enterprise concept.
