1,813 research outputs found
Staff training in terms of digital economy development: the experience of Polotsk State University (Republic of Belarus)
The article examines the features of the educational process in conditions of digital transformation of economy, as well as key competencies and skills that required in the digital economy. The main trends in the sphere of education are described. The experience of the Polotsk State University countries in the field of digital transformation of education is presented
Citizens Adoption and Intellectual Capital Approach
νμλ
Όλ¬Έ (λ°μ¬)-- μμΈλνκ΅ λνμ : 곡과λν νλκ³Όμ κΈ°μ κ²½μΒ·κ²½μ Β·μ μ±
μ 곡, 2019. 2. Hwang, Junseok .The emergence of knowledge intensive industries gave rise to the issue of intellectual capital management which is used as an instrument to identify and measure the hidden sources of value creation at the firm, regional and national level. Knowledge-intensive companies are rated much higher than their book value suggests, and thus need to identify the intangible valuables of the company for the improvement and sustainability of their learning and capitalization system. Intellectual capital components are the key resources that can be leveraged for smart city development which intends to use information and communication technologies in order to bring efficiency and sustainability to the urban functions. The role of intellectual capital components in smart city implementation needs to be studied due to the fact that attributes of intellectual capital components would have a distinguished impact on value creation and the increase in productivity and performance.
Despite the existence of a significant number of literatures on intellectual capital, the role of its components in the success of smart city implementation has not been examined. This research aims to investigate the role of intellectual capital components towards smart city success using an analysis of experts preferences for human capital and structural capital. The research also includes the demand-side perspective towards smart city information services characteristics that influences the adoption decision. The analysis is performed using two methodologies: Analytics Hierarchy Process (AHP) for human capital and structural capital and discrete choice analysis using a mixed logit model for the adoption of smart city information services.
The first study employs a multidimensional approach to the development of a model for human capital using individual-level characteristics and the collective behavior. The identification of the sources of value in human capital is critical to the success of smart city implementations as these capabilities can be leveraged and upgraded to improve productivity and performance. Human capital components have been categorized into personal qualifications, personal traits, culture and social factors. The findings reveal that the most important category is personal qualifications followed by culture. Moreover, the overall priority weights estimation shows that the existence of domain-specific tacit knowledge gained through experience, the multi-disciplinary scope of education and the density of R&D personnel are the top-three ranked attributes of human capital towards smart city success.
The study on the structural capital examined 24 smart city cases across the globe to identify the structural capital elements valuable in the smart city development process. The different orchestration of these structural capital elements can influence the outcome of the development process and its impact on the efficiency of the urban systems. The identified structural capital elements have been categorized into process, relational and infrastructural dimensions. The findings reveal that the infrastructural dimension comprising communication and information system is most critical towards the smart city success, followed by the process category with the most dominant component of policy. The overall ranking of these elements suggest that the decision makers need to focus on city-level policies and the development and enforcement of procedures for innovation generation.
Finally, the citizens preferences analysis was performed for the case of Islamabad city in Pakistan which is at the early stage of smart city development and can benefit from a better understanding of the demand-side perspective. The characteristics of smart city information services considered in the study comprise language, access mode, service ownership, interoperability and security. Willingness-to-pay was used to observe the price sensitivity of the end users choices. The findings reveal that citizens in Islamabad have a higher utility towards the use of the English language, a mobile access mode and a high level of security.
In conclusion, the study provides guidelines for policy makers who are concerned with the early stage of smart city development. The demand-side study of Islamabad city provides valuable insights in to existing trends that affect the rapid adoption of smart city services.κ΅λ¬Έμ΄λ‘
μ§μμ§μ½μ μ°μ
μ μΆνμΌλ‘ κΈ°μ
, μ§μ λ° κ΅κ° μ°¨μμμ κ°μΉ μ°½μΆμ μ¨κ²¨μ§ μΆμ²λ₯Ό νμ
νκ³ μΈ‘μ νλ λκ΅¬λ‘ μ¬μ©λλ μ§μ μλ³Έ κ΄λ¦¬κ° μμ μΌλ‘ λ μ¬λλ€. μ§μμ§μ½μ κΈ°μ
μ μμμ°λ³΄λ€ ν¨μ¬ λμ νκ°λ₯Ό λ°κ³ μκΈ° λλ¬Έμ κ·Έλ€μ νμ΅κ³Ό μλ³Έν μμ€ν
μ κ°μ κ³Ό μ§μ κ°λ₯μ±μ μν΄ νμ¬μ 무ν κ°μΉλ₯Ό νμΈν νμκ° μλ€. μ§μ μλ³Έμμλ μ 보ν΅μ κΈ°μ μ μ΄μ©ν΄ λμ κΈ°λ₯μ ν¨μ¨μ±κ³Ό μ§μμ±μ λμ΄λ μ€λ§νΈ μν° κ°λ°μ νμ©λ μ μλ ν΅μ¬ μμμ΄λ€. μ§μ μλ³Έ μμμ μμ±μ κ°μΉ μ°½μΆκ³Ό μμ°μ± λ° μ±λ₯ ν₯μμ κ°λ³μ μΈ μν₯μ λ―ΈμΉ μ μκΈ° λλ¬Έμ μ€λ§νΈ μν° κ΅¬νμμμ μ§μ μλ³Έ μμμ μν μ μ°κ΅¬ν νμκ° μλ€.
μ§μ μλ³Έμ κ΄ν μ€μν μ°κ΅¬ λ¬Ένλ€μ΄ μμ§λ§ μ€λ§νΈ μν°μ μ±κ³΅μ μΈ κ΅¬νμ μνκ° μμλ€μ μν μ κ²ν λμ§ μμλ€. μ΄ μ°κ΅¬λ μΈμ μλ³Έκ³Ό ꡬ쑰μλ³Έμ λν μ λ¬Έκ°μ μ νΈλ λΆμμ μ¬μ©νμ¬ μ€λ§νΈ μν°μ μ±κ³΅μ μν μ§μ μλ³Έ μμμ μν μ‘°μ¬λ₯Ό λͺ©μ μΌλ‘ νλ€. λν μμ© μμ¬ κ²°μ μ μν₯μ λ―ΈμΉλ μ€λ§νΈ μν° μ 보 μλΉμ€ νΉμ±μ λν μμ μΈ‘λ©΄μ κ΄μ λ μ‘°μ¬νλ€. λΆμμ μΈμ μλ³Έ λ° κ΅¬μ‘°μ μλ³Έμ μν λΆμ κ³μΈ΅ νλ‘μΈμ€(AHP)μ μ€λ§νΈ μν° μ 보 μλΉμ€ μ±νμ μν νΌν© λ‘μ§ λͺ¨λΈμ μ΄μ©ν μ΄μ° μ ν λΆμμ΄λΌλ λ κ°μ§ λ°©λ²μ μ¬μ©νλ€.
첫 λ²μ§Έ μ°κ΅¬λ λ€μ°¨μμ μ κ·Όλ²μ μ¬μ©ν΄ κ°μΈ μμ€μ νΉμ±κ³Ό μ§λ¨ νλμ μ΄μ©ν μΈμ μλ³Έμ λν λͺ¨λΈμ κ°λ°νλ€. μΈμ μλ³Έμ κ°μΉμ κ·Όμμ μλ³νλ κ²μ μ€λ§νΈ μν° κ΅¬ν μ±κ³΅μ λ§€μ° μ€μνλ€. μ΄λ¬ν λ₯λ ₯λ€μ΄ νμ©λκ³ κ°μ λμ΄ μμ°μ±κ³Ό μ±λ₯μ ν₯μμν¬ μ μκΈ° λλ¬Έμ΄λ€. μΈμ μλ³Έ μμλ κ°μΈμ μ격, μ±κ²©, λ¬Έν, μ¬νμ μμΈμΌλ‘ λΆλ₯λμλ€. κ·Έ κ²°κ³Ό, 첫λ²μ§Έλ‘ μ€μν κ²μ κ°μΈμ μ격μ건μ΄λ©° λλ²μ§Έλ λ¬Ένμμ λ°νλλ€. λν, μ 체μ μΈ μ°μ μμ κ°μ€μΉ μΆμ μ κ²½νμ ν΅ν΄ μ»μ λλ©μΈ κ³ μ μ μ묡μ μ§μμ μ‘΄μ¬, λ€λΆμΌμ κ΅μ‘ λ²μ λ° R&D μΈλ ₯μ λ°λλ μ€λ§νΈ μν° μ±κ³΅μ μν μΈμ μλ³Έμ μμ 3λ μμ±μμ 보μ¬μ€λ€.
ꡬ쑰μ μλ³Έμ κ΄ν μ°κ΅¬λ μ μΈκ³ 24κ° μ€λ§νΈ μν° μ¬λ‘λ₯Ό μ‘°μ¬ν΄ μ€λ§νΈ μν° κ°λ° κ³Όμ μμ κ°μΉ μλ ꡬ쑰μ μλ³Έμ μμλ₯Ό νμΈνλ€. μλ‘ λ€λ₯Έ ꡬ쑰μ μλ³Έ μμμ μ‘°μ μ κ°λ° νλ‘μΈμ€μ κ²°κ³Όμ λμ μμ€ν
μ ν¨μ¨μ±μ μν₯μ λ―ΈμΉ μ μλ€. νμΈλ ꡬ쑰μ μλ³Έ μμλ νλ‘μΈμ€, κ΄κ³ λ° κΈ°λ° κ΅¬μ‘° μ°¨μμΌλ‘ λΆλ₯λμλ€. μ΄λ ν΅μ κ³Ό μ 보 μμ€ν
μ ꡬμ±νλ κΈ°λ° κ΅¬μ‘°μ μ°¨μμ΄ μ€λ§νΈ μν°μ μ±κ³΅μ κ°μ₯ μ€μνλ©° κ·Έ λ€μμΌλ‘ μ μ±
μ κ°μ₯ μ°μΈν κ΅¬μ± μμλ₯Ό κ°μ§ νλ‘μΈμ€ λ²μ£Όκ° μ€μνλ€λ κ²μ 보μ¬μ€λ€. μ΄λ€ μμμ μ 체 μμλ μμ¬κ²°μ μλ€μ΄ νμ μμ±μ μν λμ μμ€μ μ μ±
κ³Ό μ μ°¨ κ°λ°κ³Ό μ§νμ μ΄μ μ λ§μΆ νμκ° μμμ μμ¬νλ€.
λ§μ§λ§μΌλ‘, μ€λ§νΈ μν° κ°λ°μ μ΄κΈ° λ¨κ³μ μμΌλ©° μμ μΈ‘λ©΄ κ΄μ μμ μ μ©ν μ μλ νν€μ€νμ μ΄μ¬λΌλ§λ°λ λμμ λν μλ―Όμ μ νΈ λΆμμ΄ μ΄λ£¨μ΄μ‘λ€. λ³Έ μ°κ΅¬μμ κ³ λ €ν μ€λ§νΈ μν° μ 보 μλΉμ€μ νΉμ±μ μΈμ΄, μ κ·Ό λͺ¨λ, μλΉμ€ μμ κΆ, μνΈμ΄μ©μ± λ° λ³΄μμΌλ‘ ꡬμ±λλ€. μ§λΆ μμ§λ μ΅μ’
μ¬μ©μμ μ νμ λ°λ₯Έ κ°κ²© λ―Όκ°λλ₯Ό κ΄μ°°νκΈ° μν΄ μ¬μ©λμλ€. μ°κ΅¬ κ²°κ³Όλ μ΄μ¬λΌλ§λ°λ μλ―Όλ€μ΄ λμ μμ€μ 보μκ³Ό ν¨κ» μμ΄ μ¬μ©μ λ λμ ν¨μ©μ κ°μ§κ³ μλ€λ κ²μ 보μ¬μ€λ€.
κ²°λ‘ μ μΌλ‘, μ΄ μ°κ΅¬λ νΉλ³ν μ€λ§νΈ μν° κ°λ°μ μ΄κΈ° λ¨κ³μ μλ μ μ±
μ
μμλ€μ μν μ§μΉ¨μ μ 곡νλ€. μ΄μ¬λΌλ§λ°λμμ λν μμ μΈ‘λ©΄ μ°κ΅¬λ μ€λ§νΈ μν° μλΉμ€μ μ μν μ±νμ μ§μνλ κΈ°μ‘΄ μΆμΈμ λν κ·μ€ν ν΅μ°°λ ₯μ μ 곡νλ€.
μ£Όμ λ¨μ΄: μ€λ§νΈ μν°, μ§μ μλ³Έ, μΈμ μλ³Έ, ꡬ쑰μ μλ³Έ, μ 보 μλΉμ€Chapter 1 Introduction 1
1.1 Overview 1
1.2 Purpose of the Research 9
1.3 Contribution of the Research 12
1.4 Research Outline 15
Chapter 2 Literature Review 18
2.1 Smart Cities 18
2.1.1 Smart City Definitions 19
2.1.2 Smart City Components 22
2.1.3 Smart City Systems Architecture 28
2.2 Intellectual Capital 30
2.2.1 Existing Studies on Intellectual Capital 32
2.2.2 Intellectual Capital and Smart Cities 37
2.2.3 Intellectual Capital Components 39
Chapter 3 Study on the Role of Human Capital for Smart City Success 50
3.1 Model 52
3.1.1 Personal Qualifications 54
3.1.2 Personal Traits 57
3.1.3 Culture 58
3.1.4 Social Factors 59
3.2 Methodology 60
3.2.1 Survey for Analytic Hierarchy Process 63
3.3 Estimation of Results 66
Chapter 4 Study on Structural Capital Role for Smart City Success 74
4.1 Model 77
4.1.1 Process Elements 77
4.1.2 Relational Elements 81
4.1.3 Infrastructural Elements 82
4.2 Methodology 85
4.2.1 Survey for Analytic Hierarchy Process 85
4.3 Estimation of Results 87
Chapter 5 Adoption of Smart City Information Services 95
5.1 Citizens Preferences Analysis towards the Adoption of Smart City Information Services 95
5.2 Model 97
5.3 Methodology 101
5.3.1 Random Utility Model 101
5.3.2 Willingness to Pay 104
5.4 Survey Design and Data 105
5.4.1 Survey for Discrete Choice Analysis 105
5.5 Estimation of Results 109
Chapter 6 Discussion and Conclusion 115
6.1 Discussion and Implications 115
6.2 Conclusion 128
6.3 Limitations and Future Work 131
References 134
Appendix A: Description of Attributes for AHP Survey 152
Appendix B: Survey Questionnaire for AHP 155
Appendix C: Conjoint Survey for Citizens Preference Analysis 163
κ΅λ¬Έμ΄λ‘ 166
Acknowledgments 169Docto
- β¦