Challenges of digitalization and artificial intelligence for modern economies, societies and management

Clauberg, R.

doi:10.22363/2313-2329-2020-28-3-556-567

Cited by 13 publications

(8 citation statements)

References 5 publications

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“…Current research focuses on the link between industrial intelligence and population aging. Clauberg argues that the application of AI technologies in production is more desirable in developed countries with a high level of population ageing compared to developing countries with a large population [63]. Abeliansky & Prettner believed that, for every 1% decrease in the population growth rate in countries with a higher concentration of aging populations, the installed density of robots will increase by nearly 2% [64].…”

Section: Literature Reviewmentioning

confidence: 99%

Population Aging, Industrial Intelligence and Export Technology Complexity

Tang

Zhang

2022

Sustainability

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The ageing of the population has become a serious test for all countries and regions, and industrial intelligence, as a new development model that integrates traditional industries with modern technology, will contribute to the deep integration of the industrial and innovation chains and thus to the enhancement of national core competitiveness. Based on the dual influence of population ageing and industrial intelligence, this paper uses the 2016 version of the World Input-Output Database (WIOD) data for 16 manufacturing industries in 43 countries from 2000 to 2014 to construct an econometric regression model to empirically test the relationship between population ageing, industrial intelligence and technological complexity of exports. The results of the study show, firstly, that population ageing plays a positive role in the technical complexity of exports. Secondly, the introduction of industrial intelligence mitigates the adverse effects of an ageing population through a complementary substitution mechanism on the one hand, and promotes industrial upgrading and transformation through the infiltration and expansion effects of industrial intelligence on the other, which in turn has a positive impact on the increase in technological sophistication of exports. In addition, the paper further divides the level of industry technology, the level of national development and the age structure of the ageing population, and explores the impact of industry intelligence in different dimensions. The results show that industrial intelligence can have a positive impact on export technological sophistication at the industry level, at the national level and in terms of ageing demographics. The research results provide a new way of thinking, through which countries around the world can formulate population policies and industrial policies and improve the complexity of export technology under the background of aging.

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Section: Literature Reviewmentioning

confidence: 99%

Population Aging, Industrial Intelligence and Export Technology Complexity

Tang

Zhang

2022

Sustainability

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“…AI-based image analyzes are used in the medical field to detect certain abnormalities in X-ray or magnetic resonance tomographic images. There are also advances in robotic systems that make these systems safe enough to operate robots that move close to humans (Clauberg, 2020).…”

Section: Smart Human Resources Managementmentioning

confidence: 99%

From traditional to smart human resources management

Kambur

Yıldırım

2022

IJM

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PurposeThe purpose of this article is to examine all the studies carried out within the scope of e-HRM and smart HRM, grouped according to the sub-functions of technical and HRM. The use of technology in HRM has started since the mid-1990s. However, this study focused on the articles published after 2014 in order to keep up to date. Any search strategy should allow for the completeness of the search to be evaluated. The terms “electronic-HRM”, “AI and HRM”, “Industry 4.0 and HRM”, “Society 5.0 and HRM”, “Human Resource Information Systems” and “Digital Technologies and HRM” “Human-robot interaction” has been questioned in IEEE Xplore, ALM digital library, Emerald Insight, SpringerLink, and Science Direct. The Web of Science and Scopus were also queried to double-check the findings and find other relevant articles in lesser-known libraries. Google Scholar was also used for forward and backward searches. These online databases have been chosen because they present the most important peer-reviewed full-text journals, conference proceedings, book chapters. Then, the references of each article were reviewed for additional articles on digital technologies and HRM. Each subsequent article is then reviewed for additional reference.Design/methodology/approachA total of 5,580 articles have been reviewed. Duplicate items have been removed. The titles and abstracts of 3,500 articles have been scanned to identify potential articles. The full-text evaluation of 2,554 was based on compliance with the inclusion criteria. In addition, 2,458 studies have been excluded. In total, 96 studies have been selected for data extraction. Additionally, questionnaires and reviews have been used to provide comprehensive research on e-HRM and smart HRM. The search terms used are expected to cover most, if not all, of the studies involving e-HRM and smart HRM.FindingsThe study carried out in this article is qualitative research. In the article, which methods are used and what has changed in e-HRM and smart HRM are examined. In particular, it has been thought about what can happen with the inclusion of human-machine interaction, AI, chatbots, industry 4.0 and information systems in HRM. Unlike previous studies, this review takes HRM from a broader perspective and groups it by topic, both by technical and HR functions. In addition, the reviewed articles provide brief information about the AI technologies used. In particular, criteria were taken into account according to the field, type and subject of the articles.Originality/valueThis study has the distinction of being the first in the literature in terms of examining all the studies carried out within the scope of e-HRM and smart HRM and grouped according to the sub-functions of technical and HRM in line with its purpose. The article focuses specifically on research published after 2014. It is expected to contribute to the literature in terms of collecting all studies in a single article. Other contributions of this article can be summarized in four main articles: 1) it presents a summary of previous research by grouping the studies on e-HRM and smart HRM according to the interests of researchers. 2) It saves time for the reader as it provides a brief explanation of the studies on the subject. 3) Instead of explaining in detail the general details analyzed in other articles, it offers a practical perspective by focusing on the type, subject and field of the article. 4) With the digitalization of HRM, new, up-to-date research and techniques are introduced.

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“…Digital innovations can increasingly replace humans and their workload at various levels; therefore, digitalisation raises questions about the cooperation between machines and humans. It is often alleged and feared that the technical transformation, especially when it comes to Artificial Intelligence, will destroy jobs (Clauberg, 2020). The term Substitutional Potential describes exactly this scenario.…”

Section: Analysis Of Literaturementioning

confidence: 99%

Development of digital and entrepreneurial competences for the future labour market needs

Labanauskaitė¹,

Župerkienė²,

Kumpf³

et al. 2021

JESI

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This article aims to identify what digital and entrepreneurial competences are required in a concept of New Work orientated labor market. To achieve this, the research takes a two-folded approach by breaking down how digitalisation changes the role of employees in a digital and automated world, which competences and organisational structures are required for a successful adaption of digitalisation in the company and what the digital awareness and the current transformation status in small and medium-sized companies in Bavaria (Germany) and Lithuania looks like. The research methods chosen to deal with a scientific problem in the theoretical part include an analysis of literature sources, systematisation, synthesis, generalisation, and comparison. The status of the research findings shows that digitalisation has arrived in companies, but especially small and medium-sized companies have to overcome various barriers. The focus on employees as stakeholders is crucial to these adaptation processes. Primary research has shown that the employer´s and employee´s sides have recognized the importance of implementation. Nevertheless, there is room for adjustments. Both sides also need to find their own path to adapt requirements and expectations, to start a successful cooperation. It could help adapt to rapidly changing market trends and link stakeholders via user-friendly technology, just because this technology is created through strategic collaboration activities (Laužikas, Miliūtė, 2020).

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Challenges of digitalization and artificial intelligence for modern economies, societies and management

Cited by 13 publications

References 5 publications

Population Aging, Industrial Intelligence and Export Technology Complexity

Population Aging, Industrial Intelligence and Export Technology Complexity

From traditional to smart human resources management

Development of digital and entrepreneurial competences for the future labour market needs

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