Developing and Testing an Algorithm to Identify Future Innovative Research Areas in Digitalization Conditions (using a Medical-sector example)

Rudskaya, Irina; Ozhgikhin, Ivan; Kryzhko, Darya

doi:10.14716/ijtech.v11i6.4438

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…Let us take a closer look at the negative tone of the information environment in the news when the word "Automation" is mentioned. The analysis of the information environment allows us to assess how the tone of the news has changed over time (Rudskaya et al, 2020). The data search algorithm can be divided into 2 stages.…”

Section: Figure 1 Conceptual Model Of the Studymentioning

confidence: 99%

Analyzing The Systemic Impact of Information Technology Development Dynamics on Labor Market Transformation

Rodionov¹,

Gracheva²,

Konnikov³

et al. 2022

IJTech

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Today, humanity is on the verge of the fourth industrial revolution. This can result in a radical transformation of all aspects of society. Information technology is the core of the fourth industrial revolution. The application variety of modern information technologies determines the infinite vectors of their use, which ultimately become the overwhelming number of instruments for life simplifing. Professional activity sphere is also being transformed under the influence of information technology development. However, this transformation process is extremely ambiguous. In connection with this specificity, the purpose of this study is a systematic analysis of the influence of the information technology development dynamics on the transformation of the labor market. The hypothesis assumes that there is a relationship between technology development and changes in the labour market. This research examine digitalization impact on unemployment level and the process of gradual extinction of certain professions. As the results authors defined mathematical formalization of the alleged links and formulate the main vectors of labour market transformation under the digital technologies development.

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Section: Figure 1 Conceptual Model Of the Studymentioning

confidence: 99%

Analyzing The Systemic Impact of Information Technology Development Dynamics on Labor Market Transformation

Rodionov¹,

Gracheva²,

Konnikov³

et al. 2022

IJTech

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“…This emotional color is differentiated in accordance with such basic emotions as positivity, negativity, neutrality, and many others. At the moment, there are many automated tools for assessing the level of one or another emotional component in the general tonal component of the information environment [ 36 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling Changes in the Enterprise Information Capital in the Digital Economy

Rodionov

Zaytsev

Konnikov

et al. 2021

Journal of Open Innovation: Technology, Market, and Complexity

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The global COVID-19 pandemic has led to the self-isolation of people and the transformation of many economic and social processes into an electronic version thus contributing to the digitalization of all spheres. Being part of this environment, enterprises generate information resources to develop their desired image, which may vary according to the factors characterizing the information environment. Information capital is a comprehensive characteristic of an enterprise and determines its effectiveness and sustainability. The purpose of this study is to develop a toolkit that allows one to assess the information capital of an enterprise, reflecting its perception within the digital information environment. It is necessary to develop the methodology for the formation of such tools. As a result, a fuzzy-plural approach has been developed to evaluate the index of external information capital. This model allows us to assess the external information capital and to simulate its changes caused by various kinds of information events. The study of key elements, for example, the stability and tonality indices, index of target perception made it possible to systematize chaotic changes in the external environment and describe them using the Chen–Lee attractor model. The results of this study can be useful for researchers in the field of digital information analysis, in particular for the comparative analysis of enterprises and the assessment of their information capital.

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“…The emergence of higher education has helped establish different factors that make studying a graduate degree valuable (Zhu & Reeves, 2019;Menon et al, 2017). For Jackson (2021), the main factors include: i) the increasing number of employers who require graduate diplomas to hire employees for high-level positions; ii) the growing trend of employers encouraging and supporting their employees to further their professional development in graduate studies based on the perception that it is an added value to human capital (Trachuk & Linder, 2022); and iii) the increasing professionalization of the industry (Rudskaya et al, 2020), whether as a response to new industrial developments or as a matter of personal benefit to attain a higher salary, gain social prestige and have more control of one's working conditions (Santini, Ladeira, Sampaio & Da Silva Costa, 2017;Zaaba et al, 2015). On the one hand, there are factors found in some studies that play an important role in graduate career choices, such as career interest, knowledge, and adaptability, for example, and on the other, there are also some approaches where intervention in the career choice, have a positive impact encouraging reflection on the future, identifying own strengths and building plan future projects (Ginevra et al, 2017;Ashari et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Motivations Behind the Master’s Degree Choices of Colombian Undergraduate Students

Valencia-Arias¹,

Naffah²,

Arango-Botero³

2023

INT J INSTRUCTION

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Financial, personal, and labor variables are well-known for understanding career choices' decision-making process. This research examines the relationship between these different motivating factors and how they influence choosing a master's degree. The research applied quantitative, exploratory methods using a two-part questionnaire: one for the characterization of the sample population and the other with questions with Likert-type scale answers around the constructs determined. Structural equation modeling is used to statistically analyze the responses to 728 self-administered questionnaires completed by undergraduate administrative sciences and management students from two universities in Medellín (Colombia). The factors that most affect the motivation to study a master's degree are labor market competition (β =1.664, p-value = 0.021) and job promotion (β =0.922, pvalue: < 0.001). Understanding the motivations of potential students is important to higher education institutions with graduate degrees because it allows them to adjust their academic opportunities and outreach strategies to meet students' expectations and needs. This study also proposes a model that adapts to developing countries' social, economic, and educational characteristics.

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Developing and Testing an Algorithm to Identify Future Innovative Research Areas in Digitalization Conditions (using a Medical-sector example)

Cited by 7 publications

References 8 publications

Analyzing The Systemic Impact of Information Technology Development Dynamics on Labor Market Transformation

Analyzing The Systemic Impact of Information Technology Development Dynamics on Labor Market Transformation

Modeling Changes in the Enterprise Information Capital in the Digital Economy

Motivations Behind the Master’s Degree Choices of Colombian Undergraduate Students

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