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Economies
Special Issues
Service Innovation and Digital Economy
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Service Innovation and Digital Economy

A special issue of Economies (ISSN 2227-7099).

Deadline for manuscript submissions: closed (30 December 2022) | Viewed by 29254

Special Issue Editor

Dr. Ronald Beckett

E-Mail Website
Guest Editor
Swinburne Business School, Swinburne University of Technology, Melbourne 3122, Australia
Interests: innovation; collaboration; knowledge management; business ecosystems

Special Issue Information

Dear Colleagues,

There are two aspects of innovation in the digital economy that we wish to explore in this Special Issue. One is where the digital economy acts as an enabler, providing an embedded platform for societal and enterprise innovation. The other is where innovations in multiple fields may enhance digital economy capabilities, for example, via the development of smart sensors and new software tools. Innovation may take many forms, and in this Special Issue our focus is on service innovation, as private and public services are an important element of most economies. Value co-creation is an emergent theme in service innovation (e.g., https://www.sciencedirect.com/science/article/abs/pii/S0148296321008894 ) and articles related to this development will be considered for this Special Issue. Of particular interest is how an innovation may have an impact on regional and global economies. The pervasive use of digital technologies enmeshed in so many aspects of daily life can make the attribution of their benefits difficult, as there may be benefits beyond the economic (e.g., http://digamoo.free.fr/hbr1119.pdf ). Papers discussing this topic will also be considered.

Particular aspects of Economies' scope that may be considered in proposing contributions to this Special Issue include:

  • Economic development services: development policy; formal and informal economy; role of international organizations; foreign aid; industrialization; institutions and development; country studies; urban, rural, and regional studies; industrial policy; welfare; poverty; demographics (e.g., the digital economy and micro-finance, http://www.mibmparidnya.in/index.php/PARIDNYA/article/view/118548)
  • Growth and natural resources sustainment services: growth models; empirical growth studies; productivity; technological change; intellectual property rights; environment; resource policies; renewable resources; energy; primary markets; agriculture; institutions and growth; climate change (e.g., integrating digital and green economies, https://www.jstor.org/stable/24873273?seq=1#metadata_info_tab_contents )
  • Health services economics: health care markets; health policy; regulation in health markets; health insurance; public health systems; health behavior; pandemics; health and economic development; health and productivity; health and inequality (e.g., health care reform and the digital economy, https://www.healthaffairs.org/doi/abs/10.1377/hlthaff.19.6.23 )

Dr. Ronald Beckett
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Economies is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • service innovation
  • digital economy
  • economic development
  • renewable resources
  • health care reform

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Published Papers (5 papers)

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Research

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16 pages, 2412 KiB  
Article
Information Environment Quantifiers as Investment Analysis Basis
by Dmitry G. Rodionov, Polina A. Pashinina, Evgenii A. Konnikov and Olga A. Konnikova
Economies 2022, 10(10), 232; https://doi.org/10.3390/economies10100232 - 20 Sep 2022
Cited by 6 | Viewed by 2036
Abstract
The combination of the processes of widespread digitalization and globalization of the world economy has led to a significant expansion of the global information environment. The modern information environment is dynamically active, and changes in it are indicators of changes in the material [...] Read more.
The combination of the processes of widespread digitalization and globalization of the world economy has led to a significant expansion of the global information environment. The modern information environment is dynamically active, and changes in it are indicators of changes in the material world. This specificity can be used for investment analysis purposes. However, at the time of this research, a universal methodology for analyzing the information environment has not yet been formed. The purpose of this study is to develop tools for quantifying the information environment and testing them as investment predictors. The key result of this study is a stock price forecasting model based on information environment quantifiers and its critical analysis. The results obtained will be useful both for investors of different skill levels and for researchers of the information environment. Full article
(This article belongs to the Special Issue Service Innovation and Digital Economy)
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18 pages, 778 KiB  
Article
Research on the Introduction of a Robotic Process Automation (RPA) System in Small Accounting Firms in Taiwan
by Hsing-Hua Hsiung and Juo-Lien Wang
Economies 2022, 10(8), 200; https://doi.org/10.3390/economies10080200 - 18 Aug 2022
Cited by 7 | Viewed by 4708
Abstract
This study explores the characteristics that influence the success factors of accounting firms in the introduction of a RPA system. The RPA system success factors used in this paper are based on the measurements of the Technology Acceptance Model (TAM) and the Information [...] Read more.
This study explores the characteristics that influence the success factors of accounting firms in the introduction of a RPA system. The RPA system success factors used in this paper are based on the measurements of the Technology Acceptance Model (TAM) and the Information System Success Model (ISS). In this paper, a questionnaire survey method was used, and a total of 140 questionnaires were distributed to 70 small accounting firms in Taiwan. The results of this study showed that three characteristic factors—male, higher familiarity with the system and high CEO support—were significantly positively correlated with the success factors of the RPA system in accounting firms. Due to resource constraints, small- and medium-sized accounting firms have gone through a more difficult journey of digital transformation than the Big Four. Therefore, research on digital transformation with small- and medium-sized firms as samples is a topic worthy of attention. The research conclusions of this paper can provide a reference for the accounting digital transformation strategies of the accounting industry and educational institutions. Full article
(This article belongs to the Special Issue Service Innovation and Digital Economy)
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21 pages, 2034 KiB  
Article
Machine Learning for Credit Risk in the Reactive Peru Program: A Comparison of the Lasso and Ridge Regression Models
by Luis Alberto Geraldo-Campos, Juan J. Soria and Tamara Pando-Ezcurra
Economies 2022, 10(8), 188; https://doi.org/10.3390/economies10080188 - 30 Jul 2022
Cited by 6 | Viewed by 4009
Abstract
COVID-19 has caused an economic crisis in the business world, leaving limitations in the continuity of the payment chain, with companies resorting to credit access. This study aimed to determine the optimal machine learning predictive model for the credit risk of companies under [...] Read more.
COVID-19 has caused an economic crisis in the business world, leaving limitations in the continuity of the payment chain, with companies resorting to credit access. This study aimed to determine the optimal machine learning predictive model for the credit risk of companies under the Reactiva Peru Program because of COVID-19. A multivariate regression analysis was applied with four regressor variables (economic sector, granting entity, amount covered, and department) and one predictor (risk level), with a population of 501,298 companies benefiting from the program, under the CRISP-DM methodology oriented especially for data mining projects, with artificial intelligence techniques under the machine learning Lasso and Ridge regression models, with econometric algebraic mathematical verification to compare and validate the predictive models using SPSS, Jamovi, R Studio, and MATLAB software. The results revealed a better Lasso regression model (λ60 = 0.00038; RMSE = 0.3573685) that optimally predicted the level of risk compared to the Ridge regression model (λ100 = 0.00910; RMSE = 0.3573812) and the least squares model with algebraic mathematics, which corroborates that the Lasso regression model is the best predictive model to detect the level of credit risk of the Reactiva Peru Program. The best predictive model for detecting the level of corporate credit risk is the Lasso regression model. Full article
(This article belongs to the Special Issue Service Innovation and Digital Economy)
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22 pages, 1179 KiB  
Article
Digital Financial Inclusion, Digital Financial Services Tax and Financial Inclusion in the Fourth Industrial Revolution Era in Africa
by Favourate Y. Mpofu and David Mhlanga
Economies 2022, 10(8), 184; https://doi.org/10.3390/economies10080184 - 29 Jul 2022
Cited by 37 | Viewed by 8093
Abstract
The digital economy has risen dramatically in the global environment, and many developing countries, including African countries, have seen a spike in digital activity over recent years. The digital economy’s growth has resulted in an increase in digital financial services (DFS) in Africa [...] Read more.
The digital economy has risen dramatically in the global environment, and many developing countries, including African countries, have seen a spike in digital activity over recent years. The digital economy’s growth has resulted in an increase in digital financial services (DFS) in Africa and other developing regions. Since many African countries are under pressure to raise domestic revenue, taxing the digital economy has become a viable option. As a result, this study attempted to respond to the following questions: first, what is the link between DFS growth and digital inclusion in African countries? Second, what justifies the imposition of DFS taxes in Africa? Third, what are the potential consequences of DFS taxes in African countries? Using secondary data from the literature review and document analysis, a systematic technique for assessing or evaluating printed and electronic documents, and computer-based and internet-transmitted material, the study discovered that digital financial inclusion is driving financial inclusion on the African continent. The study also found that, despite several negative consequences associated with the growth of the digital economy, most African economic activities are informal and are being aided by various digital financial services. Therefore, it is equally crucial that when adopting digital finance taxes, care is taken to avoid excluding low-income earners from the financial sector and to take note of the usage, affordability, and distortive implications of taxation. Full article
(This article belongs to the Special Issue Service Innovation and Digital Economy)
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Review

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28 pages, 1154 KiB  
Review
Taxation of the Digital Economy and Direct Digital Service Taxes: Opportunities, Challenges, and Implications for African Countries
by Favourate Y. Mpofu
Economies 2022, 10(9), 219; https://doi.org/10.3390/economies10090219 - 8 Sep 2022
Cited by 14 | Viewed by 9655
Abstract
Digitalization has intensified globalization and economic interactivity between countries both developed and developing, increasing the complexity and lack of transparency in economic activities. The increase in digital transactions poses a remarkable challenge for tax authorities yet the digital economy is slowly replacing traditional [...] Read more.
Digitalization has intensified globalization and economic interactivity between countries both developed and developing, increasing the complexity and lack of transparency in economic activities. The increase in digital transactions poses a remarkable challenge for tax authorities yet the digital economy is slowly replacing traditional commercialization and transactions. Conventional international tax legislation has not kept abreast with the growth and complexity of the digital economy and its accompanying challenges with respect to taxation. In view of the infant nature of digital tax legislation in African countries as well as the auspicious possibility of increasing tax revenue to fund public expenditure together with the probability of contradictory outcomes of digital tax policy, through a critical literature review this paper assesses digital taxation through direct digital service taxes (DSTs) in Africa. The findings were mixed. While the possibility of tax revenue maximization and improved economic growth were persuasive, the arguments pointing to negative externalities emanating from poor digital service tax policy design were equally pragmatic. Full article
(This article belongs to the Special Issue Service Innovation and Digital Economy)
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