Identifying the process of national knowledge creation and learning and evaluating its impact on gross domestic product, considering the mediating role of national intelligencee

Azari Arani, G.; Rezaeenour, J.

doi:10.22061/jte.2018.4334.2049

Document Type : Original Research Paper

Authors

G. Azari Arani ¹
J. Rezaeenour ²

¹ Faculty of Shahid Rajaee Kashan, Isfahan Branch Technical and Vocational University (TVU), Iran

² Department of Industrial Engineering, Faculty of Technology and Engineering, University of Qom, Qom, Iran

https://doi.org/10.22061/jte.2018.4334.2049

Abstract

Background and Objectives: The economic growth of a country depends on several factors, among which the role of knowledge is undeniable. Many studies have shown that countries' GDP is often affected by the country's knowledge infrastructure. A knowledge-based economy is an economy that is directly based on the production, distribution and consumption of knowledge, and investment in knowledge and knowledge-based industries is given special attention. In this economy, where a significant share of GDP is from knowledge-based and knowledge-creating activities, knowledge generates more production than traditional factors such as labor and capital, and the value of many software and biotechnology companies arises from non-physical capitals, i.e. their knowledge and scientific privileges. Accordingly, knowledge creation is an essential weapon in today's world and without a continuous process of knowledge creation, any society is doomed to destruction. Knowledge creation and learning is the creation of new knowledge, or the replacement and improvement of the existing knowledge through social relations and organizational partnerships. The creation and application of knowledge has a major role in increasing wealth in a knowledge-based economy. The problem is that knowledge creation and learning has not been investigated at the national level yet.
Methods: By applying qualitative-quantitative methods, based on Delphi technique, the procedure of identifying and explaining the processes of national knowledge creation and learning has been discussed first. Then by using exploratory and confirmatory factor analysis, a significant t-value of more than 1.96, between the identified dimensions and the variable national knowledge creation and learning, was obtained that was acceptable.
Findings: Additionally, the impact of the process of national knowledge creation and learning on GDP was measured through conducting a survey and using a questionnaire, while taking the mediating role of national intelligence into account by using Sobel test. It was found that by including the mediating variable of national intelligence, the standardized beta for the relationship between national knowledge creation and learning, and gross domestic product was reduced from 0.80 to 0.18, but it is significant.
Conclusion: Therefore, the variable national intelligence plays the role of a partial mediator; in other words, while the impact of national knowledge creation and learning, as the main variable, is maintained, the mediating role of national intelligence also affects GDP. This research had some limitations. One of these limitations was the stereotyped thinking about the process of knowledge creation. In this study, only one dimension of knowledge management, namely ‘knowledge creation’ was used. While we can pay attention to all the processes of the knowledge management cycle in society, instead of just thinking about the creation of knowledge at the national level, in order to promote national performance. Based on this, it is suggested that other researchers consider other dimensions of the knowledge management cycle and go one step further. Researchers can also examine the existing challenges and potential barriers to the national knowledge creation process or the requirements for knowledge creation at the national level. Alternatively, researchers can study international knowledge creation processes by considering cultural differences and provide solutions to increase the likelihood of knowledge creation globally. It is suggested that future researchers make a comparative study of the national knowledge creation model with other models of measuring intellectual capital in the world and examine the strengths and weaknesses of each model and prioritize these models based on their applicability in similar countries. It is also suggested that researchers use fuzzy logic theory to make relative measurements of each of the constructs of the national knowledge creation process and conduct field and academic research in this regard. As another suggestion, researchers can conduct this research on a specific industry and compare its results with the results of this study.

Keywords

20.1001.1.20080441.1399.14.2.20.0

Main Subjects

Educational Management

COPYRIGHTS
©2020 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.

References

[1] Hoegl M, Schulze A. How to support knowledge creation in new product development: An investigation of knowledge management methods. European Management Journal. 2005; 23: 263–273.

[2] Choi B, Lee, H. Knowledge management strategy and its link to knowledge creation process. Expert System with Application. 2002; 23(3): 173–187.

[3] Martin-de-Castro G, Lopez-Saez P, Navas-Lopez J. Processes of knowledge creation in knowledge-intensive firms: Empirical evidence from Boston’s Route 128 and Spain. Technovation. 2008; 28: 222–230.

[4] Lloria MB. Differentiation in knowledge-creating organizations. International Journal of Manpower. 2007; 28(8): 674–693.

[5] Nonaka I, Takeuchi H. The knowledge creating company – How Japanese companies create the dynamics of innovation. London : Oxford University Press; 1995.

[6] Esteban GG, Lópezhyphenpueyo C, Sanaú J. Human capital measurement in OECD countries and its relation to gdp growth and innovation. Revista de Economía Mundial. 2015; 39.

[7] Giulioni G. The product innovation process and GDP dynamics. Evolutionary Economics. 2011; 21(4): 595–618.

[8] Rajput N, Khanna A, Oberoi S. Global innovation index and its impact on GDP of BRICS nations-innovation linkages with economic growth: An empirical study. Global Journal of Enterprise Information System. 2012; 4(2): 35–44.

[9] Dettwiler P. Modelling the relationship between business cycles and office location: The growth firms. Facilities. 2008; 26(3/4): 157–172.

[10] Shehata GM. Leveraging organizational performance via knowledge management systems platforms in emerging economies: Evidence from the Egyptian Information and Communication Technology (ICT) industry. VINE. 2015; 45(2): 239–278.

[11] Potas N, Ercetin SS, Kocak S. Multi dimensional organizational intelligence measurements for determining the institutional and managerial capacity of girls technical education institution (Diyarbakir, sanliurfa and Konya/ Turkey). Business Management. 2010; 4(8): 1644–1651.

[12] Resto A. Organizational intelligence: Attitudes and habits of Hispanic entrepreneurs in the process of decision-making and business performance. college of management and technology [dissertation]. Walden University, College of Management and Technology; 2009.

[13] Mooghali, AR, Azizi AR. Relation between organizational intelligence and organizational knowledge management development. World Aapplied Sciences Journal. 2008; 4(1): 1–8.

[14] Jung, Y. An approach to organizational intelligence management (a framework for analyzing organizational intelligence within the construction process [dissertation]. Faculty of the Virginia Polytechnic Instate and State University; 2009.

[15] Satari ghahfarokhi, M. The relationship between knowledge management subsystem in learning organization and organizational intelligence items. Knowledge Management National Conference: 2008 Feb: Tehran, Iran.

[16] Marjani AB, Arabi P. The role of organizational intelligence in organizational knowledge management (The case of the central bank of the Islamic republic of Iran). Social Sciences. 2011; 25(3): 49–58.

[17] Heaven PCL, Ciarrochi J. When IQ is not everything: Intelligence, personality and academic performance at school. Personality and Individual Difference. 2012; 53: 518–522.

[18] Lynn R. Intelligence IQs predict differences in the technological development of nations from 1000 BC through 2000 AD. Intelligence. 2012; 40(5): 439–444.

[19] Burhan NAS, Salleh F, Burhan NMG. National intelligence and private health expenditure: Do high IQ societies spend more on health insurance? Intelligence. 2015; 52: 1–8.

[20] Vanhanen T. National IQs and their demographic correlates. Personality and Individual Differences. 2012; 53(2): 99–102.

[21] Meisenberg G. National IQ and economic outcomes. Personality and Individual Differences. 2012; 53(2): 103–107.

[22] Rindermann H. Intellectual classes, technological progress and economic development: The rise of cognitive capitalism. Personality and Individual Differences. 2012; 53(2): 108–113.

[23] Zajenkowski M, Stolarski M, Meisenberg G. Openness, economic freedom and democracy moderate the relationship between national intelligence and GDP. Personality and Individual Differences. 2013; 55(4): 391–398.

[24] Carl N. IQ and socio-economic development across local authorities of the UK. Intelligence. 2016; 55: 90–94.

[25] Hafer RW. Intelligence Cross-country evidence on the link between IQ and fi nancial development. Intelligence. 2016; 55: 7–13.

[26] Martinsons MG, Davison RM, Huang Q. Strategic knowledge management failures in small professional service firms in China. Information Management. 2017; 37(4): 327–338.

[27] Dalmarco G, Maehler AE, Trevisan M, Schiavini JM. The use of knowledge management practices by Brazilian startup companies. RAI Revista de Administração E Inovação. 2017; 14(3): 226–234.

[28] Barão A, Vasconcelos JB, de, Rocha Á, Pereira R. A knowledge management approach to capture organizational learning networks. Information Management. 2017; 37(6): 735-740.

[29] Nowacki R, Bachnik K. Innovations within knowledge management. Business Research. 2016; 69(5): 1577–1581.

[30] Santoro G, Vrontis D, Thrassou A, Dezi L. The Internet of Things: Building a knowledge management system for open innovation and knowledge management capacity. Technological Forecasting and Social Change. 2017; 136: 347-354.

[31] Edgar Serna M, Oscar Bachiller S, Alexei Serna A. Knowledge meaning and management in requirements engineering. Information Management. 2017; 37(3): 155–161.

[32] Salehi M, Shahamet N, Dindarloo S, Dindarloo S. Relation between organizational intelligence and knowledge management among faculties members of Azad University of Marvdasht. A New Approach for Research in Educational Management. 2012; 2(3).

[33] Lim MK, Tseng ML, Tan KH, Bui, TD. Knowledge management in sustainable supply chain management: Improving performance through an interpretive structural modelling approach. Cleaner Production. 2017; 162: 806–816.

[34] Weinreich R, Groher I. Software architecture knowledge management approaches and their support for knowledge management activities: A systematic literature review. Information and Software Technology. 2016; 80: 265–286.

[35] Thannhuber MJ, Bruntsch A, Tseng MM. Knowledge Management: Managing Organizational Intelligence and Knowledge in Autopoietic Process Management Systems – Ten Years Into Industrial Application. Procedia CIRP. 2017; 63: 384–389.

[36] Nor’ashikin A, Tretiakov A, Whiddett D, Hunter I. Knowledge management systems success in healthcare: Leadership matters. Medical Informatics. 2017; 97: 331–340.

[37] Vasconcelos PJB, Kimble C, Carreteiro P, Rocha Á. The application of knowledge management to software evolution. Information Management. 2017; 37(1–part A): 1499–1506.

[38] Acar MF, Tarim M, Zaim H, Zaim S, Delen D. Knowledge management and ERP: Complementary or contradictory? Information Management. 2017; 37(6): 703–712.

[39] Rodríguez-Enríquez CA, Alor-Hernández G, Mejia-Miranda J, Sánchez-Cervantes JL, Sánchez-Ramírez C. Supply chain knowledge management supported by a simple knowledge organization system. Electronic Commerce Research and Applications. 2016; 19: 1–18.

[40] Burghaus K, Funk P. Endogenous Growth, Green Innovation and GDP Deceleration in a World with Polluting Production Inputs. Annual Conference 2013 May (Duesseldorf): Competition Policy and Regulation in a Global Economic Order (No. 80022): 2013 May: Verein für Socialpolitik/German Econom.

[41] Cerchione R, Esposito E. Using knowledge management systems: A taxonomy of SME strategies. Information Management. 2017; 37(1 part B): 1551–1562.

[42] Jankelová N, Móricová Š, Masár D. The current state of knowledge management activities in health facilities in Slovakia. Kontakt. 2016; 18(4): e265–e275.

[43] Shakerian H, Dehnavi HD, Shateri F. A Framework for the Implementation of Knowledge Management in Supply Chain Management. Procedia - Social and Behavioral Sciences. 2016; 230: 176–183.

[44] Burhan NAS, Mohamad MR, Kurniawan Y, Sidek AH. National intelligence, basic human needs, and their effect on economic growth. Intelligence. 2014; 44(1): 103–111.

[45] Rindermann H. Relevance of education and intelligence at the national level for the economic welfare of people. Intelligence. 2008; 36(2): 127–142.

[46] Williams MA, Baek G, Li Y, Park LY, Zhao W. Global evidence on the distribution of GDP growth rates. Physica A: Statistical Mechanics and Its Applications. 2017; 468: 750–758.

[47] Bhandari P, Frankel J. Nominal GDP Targeting for Developing Countries. Research in Economics. 2017; 71(3): 491-506.

[48] Bergman LR, Ferrer-Wreder L, Rita Ž, Žukauskienė R. Career outcomes of adolescents with below average IQ: Who succeeded against the odds? Intelligence. 2015; 52: 9–17.

[49] Kunanuntakij K, Varabuntoonvit V, Vorayos N, Panjapornpon C, Mungcharoen T. Thailand Green GDP assessment based on environmentally extended input-output model. Cleaner Production. 2017; 167: 970-977.

[50] Mogliani M, Darné O, Pluyaud B. The new MIBA model: Real-time nowcasting of French GDP using the Banque de France’s monthly business survey. Economic Modelling. 2017; 64: 26–39.

[51] Jiang Y, Guo Y, hang, Y. Forecasting China’s GDP growth using dynamic factors and mixed-frequency data. Economic Modelling. 2017; 66: 132-138.

[52] Creamer K, Botha RT. Assessing nominal GDP targeting in the South African context. Central Bank Review. 2017; 17(1): 1–10.

[53] Jones G, Schneider W, Uni- GM, Davis M, Smith W, Caplan B, Mason G. IQ in the production function: Evidence from immigrant earnings. Economic Inquiry. 2010; 48(3): 743–755.

[54] Hafer RW. Cross-country evidence on the link between IQ and financial development. Intelligence. 2016; 55: 7–13.

[55] Varjan P, Rovňaníková D, Gnap J. Examining Changes in GDP on the Demand for Road Freight Transport. Procedia Engineering. 2017; 192: 911–916.

[56] Leimbach M, Kriegler E, Roming N, Schwanitz J. Future growth patterns of world regions – A GDP scenario approach. Global Environmental Change. 2017; 42: 215–225.

[57] Salavera C, Usán P, Chaverri I, Gracia N, Delpueyo, M. Emotional Intelligence and Creativity in First- and Second-year Primary School Children. Procedia - Social and Behavioral Sciences. 2017; 237: 1179–1183.

[58] Budrina E. Gender Characteristics of intelligence and academic achievement of younger schoolchildren. Procedia - Social and Behavioral Sciences. 2017; 237: 1390–1397.

[59] Bernardo BI, Presbitero A. Belief in polyculturalism and cultural intelligence: Individual- and country-level differences. Personality and Individual Differences. 2017; 119: 307–310.

[60] Kang, JS, Ojha A, Lee G, Lee M. Difference in brain activation patterns of individuals with high and low intelligence in linguistic and visuo-spatial tasks: An EEG study. Intelligence. 2017; 61: 47–55.

[61] Bahrami MA, MehdiKiani M, Montazeralfaraj R, FallahZadeh H, MohammadZadeh M. The mediating role of organizational learning in the relationship of organizational intelligence and organizational agility. Osong Public Health and Research Perspectives. 2016; 7(3): 190–196.

[62] Zamroziewicz MK, Talukdar MT, Zwilling CE, Barbey AK. Nutritional status, brain network organization, and general intelligence. NeuroImage. 2017; 161: 241-250.

[63] Arnott D, Lizama F, Song Y. Patterns of business intelligence systems use in organizations. Decision Support Systems. 2017; 97: 58–68.

[64] Hunt E, Wittmann W. National intelligence and national prosperity. Intelligence. 2008; 36(1): 1–9.

[65] Meisenberg G. How does racial diversity raise income inequality? Journal of Social, Political and Economic Studies. 2008; 33: 3–26.

[66] Strenze T. Intelligence and socioeconomic success: A meta-analytic review of longitudinal research. Intelligence. 2007; 35: 401–426.

[67] Vinogradov E, Kolvereid L. Home country national intelligence and self-employment rates among immigrants in Norway. Intelligence. 2010; 38(1): 151–159.

[68] Gelade GA. IQ, cultural values, and the technological achievement of nations. Intelligence. 2008; 36(6): 711–718.

[69] Zarei Matin H, Jandaghi G, Hamidizadeh A, Hajkarimi F. Studying status of organizational intelligence in selected public offices of Qom. European Journal of Social Sciences. 2010; 14(4): 613–620.

[70] Halal WE. Organizational intelligence: what is it, and how can manager use it. 2007. Retrieved.

[71] Azma F, Mostafapour M, Rezaei H. The application of information technology and its relationship with organizational intelligence. Procedia Technology. 2012; 1: 94–97.

[72] Must O, Must A, Mikk J. Predicting the Flynn Effect through word abstractness : Results from the National Intelligence Tests support Flynn’s explanation. Intelligence. 2016; 57: 7–14.

[73] Slonim O. National intelligence: A tool for political forecasting and the forecasting of rare events. Technological Forecasting and Social Change. 2017; 128: 245-251.

[74] Jones G, Schneider WJ. Intelligence, human capital, and economic growth: A Bayesian averaging of classical estimates (BACE) approach. Economic Growth. 2006; 11(1): 71–93.

[75] Hendon M, Powell L, Wimmer H. Emotional intelligence and communication levels in information technology professionals. Computers in Human Behavior. 2017; 71: 165–171.

[76] Albrecht K. Organizational intelligence and Knowledge management the executive perspective. 2006. Retrieved.

[77] Lynn R, Harvey J, Nyborg, H. Average intelligence predicts atheism rates across 137 nations. Intelligence. 2009; 37(1): 11–15.

[78] Baron RM, Kenny DA. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology. 1986; 51(6): 1173-1182.

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Identifying the process of national knowledge creation and learning and evaluating its impact on gross domestic product, considering the mediating role of national intelligencee

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Volume 14, Issue 2 - Serial Number 54
April 2020
Pages 477-492

Identifying the process of national knowledge creation and learning and evaluating its impact on gross domestic product, considering the mediating role of national intelligencee

References

References

Send comment about this article

Volume 14, Issue 2 - Serial Number 54April 2020Pages 477-492

Volume 14, Issue 2 - Serial Number 54
April 2020
Pages 477-492