The influence of the digitalization factor on the formation and development of human capital in developing countries

Cover Page

Cite item

Abstract

As developing countries especially in Africa continues to lag behind in their human capital development pursuit in this era of digitalisation, it is necessary to look at the level of influence on digitalisation factors for the formation and development of human capital. Part of this is to look at the critical involvement of digitalisation access in developing countries in Africa. At the end it is necessary to envisage recommendation that can bolster their abilities to succeed due to high investment in these key factors. The research objectives aim at a broad analysis of the influence of the digitalization factor on the formation and development of human capital in developing looking at the relationship between digitalisation and skill development in the context of 14 developing countries. We have used the Kendall’s correlation coefficient (tau-b) to test the association of the variables relating to EDI ranking and Human Capital Development in other to analyse the relationship between variables. The research result shows that Human Capital Index (HCI) and EDI ranking have negative correlation. In any case if the Human Capital of the fourteen (14) developing countries are reached the Electronic Data Interchange ranking will still decrease. The article is concluded with recommendation that developing countries should invest in human capital especially in digital skills and create the atmosphere required for digital access to their citizen in a bid to adopt digital transformation whilst building the human capital development of the people.

Full Text

Introduction The rise of the digital connectivity has created opportunities that have particularly impacted human lifestyle, and every aspect of modern Economic activities. At a global level the growing digitalisation has influence every regions of the world including the continent of Africa. The digital economy involves a host of technologies with the potentials to affect and support the dayto-day systems of individuals, firms, businesses and states. These digital tools may include Machine learning, mobile network, cloud computing, artificial intelligence, Internet of things, big data etc. Be as it may (Usually), all of these digital tools have the abilities to influenced economic activities and improve the social life of people in both developed and the developing world whilst at the same time solving some of the most difficult challenges in institutions, government, agencies etc. However, the digital technologies work only where there is physical ICT infrastructure (Luneborg & Nielsen, 2003). The combination of these ICT infrastructure and the digital technologies allows companies, individuals, and states to go digital and as a result create economic activities that relies on digital accomplishments such as smart machines, platforms, applications and digital products. To achieve such significant infrastructure and digital transformation, developing countries, in African are now asking questions about how the digital process can be adopted especially amongst countries with low level of education and skills. This seems to encourage solutions against the obstacles for the adoption process. However, there are still many gaps for developing countries to match up with develop countries in the areas of very high technologies especially for Mobile network, big data and cloud computing (Tanriverdi & Venkatraman, 2005). According to the World Economic Forum 2015 digital economy in developing countries grew by 15-20 % whilst G20 countries grew at 10 % a year. The percentage of growth in Africa do not indicate that there are more adoptions in Africa than G20 countries. Africa and most developing countries however do not match in top five digital economies. Literature background The continent of Africa is on the rise but by far it is one of the least developing regions in the trajectory that are related to digitalisation. As such the digitalisation process is has not been able to yield immense contribution to the human capital development process either in the field of education, health Care, skills development, work experience and even the labour market efficiency. In comparison with developed and other developing countries the graph below shows the position of Africa in the digital space for mobile technology relating to fix broad band subscriptions (Figure 1). Figure 1. Fixed-broadband subscriptions per 100 inhabitants, 2019, % Source: ITU World Telecommunication /ICT Indicators. Retrieved December 10, 2021, from https://www.itu.int/ en/ITU-D/Statistics/Pages/publications/wtid.aspx The technological success of developed countries is however linked or associated with the pervasive use of big data and cloud computing which ease the e-commerce process especially for the business to consumer segments as well individuals and states (Tippens & Sohi, 2003). However, various channels have been adopted by developing countries in other to match the transformation process. In few developing countries such as china Nigeria, south Africa Namibia etc companies are deploying artificial intelligence, the “Internet of thing “robotic technology 3D printers[23] and many other digital methods in other to create real impact and as such reduce many obstacles for the digital technology adoption process. The influence of the digitalization factor on the formation and development of human capital in many developing countries haven triggered the adoption strategy of new methods of in education, healthcare, skills development recruitment and training and the creation of frame work to evolve and access new technologies used in modern time suggested that the formation and development of human capital in developing countries is linked with nation moving through different or several hierarchies in their technological development stages. These stages could help to match knowledge and can be very useful for understanding the digital process. The technological driven stages could also serve as driver of the structural change in the development process of the human capital. It enforces relevant changes in the outcome of sectorial prices and other regulations for the access of technology. This subsequently result in use of technology and technical progress for the use of digital tool in developing countries whilst at the same time enhances drastic changes in the sectorial productivity. The higher the relative sectorial accessibility and productivity the lower the relative sectorial prices (Baumӧl, 2017). The development of technological stage in the human capital development process for developing countries could create large service sector that are able to absorb employment growth for developing countries. This stage would underpin the structural changes and technological progress that will help to develop the growth process. However, Africa still lacks the notable infrastructures and is currently undergoing reforms or wireless revolution that could impact digital technologies (Minges et al., 2008). Below is how Africa is compared to other regions of the world for mobile technology mix per region (Figure 2). Figure 2. Mobile technology mix per region, 2019; % of mobile connections Source: GSMA, The Mobile Economy Report 2022. Retrieved February 10, 2022, from https://www.gsma.com/ mobileeconomy/wp-content/uploads/2022/02/280222-The-Mobile-Economy-2022.pdf) Developing countries especially in the African region are required to analyse the digital factors and the different conditions for skills needed through human capital development for the establishment of a well-designed digital economy resource. This can be achieved through basic factor conditions with a focus on the establishment of ICT infrastructure that could create many platforms for labour and even monitor natural resources. This could help in the production of local commodities in many developing countries. This strategy also will be able to reduce cost of importation from developed countries and encourage more exportation leading to currency stabilization amongst developing nation. More appropriate capacities can be achieved with the efficiency in advanced undifferentiated products with a huge development in the digital space. This will eventually reduce the shock in the digital market and encourage more efficiency in production of advance products through education and skills development incentives for real productivity. The trend of technological investment from abroad will reduce with the growing urge to design and improve more capacities for production purposes. As innovation plays key roles as a driver for more market ability to innovate useful product and services becomes very advanced with support systems design for industries. The services of distinguish product will become very competitive due to knowledge base adoptions and a clear support system for both digitalisation and human capital. In the end developing economies can bolster their abilities to succeed due to high investment in these key factors. Traditionally, developing countries are associated with simple commodity production leading to no digital consciousness. Most of the productions occurred in small scales and many materials were supplied by buyers with specific demands. In the digital economy producers are encouraged to take advantage on a wider range of manufacturing options by improving skills and relevant knowledge in other to function in areas included but not limited to manufacturing functions, logistics, marketing etc. Having achieved original design, manufacturers in developing countries can curtain the stage of securing a pathway to controlling the normal value chain just like the case for developed countries. Below is a schematic digitalisation factors on human capital. The digitalization factors for human capital. The impact of these digital factors on human capital can be directly translated into the economic success of a country. In 2020 e-commerce for example accounted for about 41 % of China’s retail. Other developing countries in South Asia such as India represented 5 % of retail sectors (Government of India, 2018) and possibly less than 1 % of the Philippines. However, Africa lacks the available data but managed to represent a small retail share. Despite that South Africa is one of the most advanced technological country in Africa digital economy that account for ecommerce only represented 1.4 % of total retail sales in 2018 in Latin America ecommerce represented only 4 % if sales. Below is the size of digital ecosystems in Africa, Asia and Latin America (Table 1). Table 1 Size of the ‘mobile ecosystem’ in Africa, Asia Pacific and Latin America Region GVA, $ Contribution to GDP, % Africa 155 Billion 9 Asia Pacific’s 1.6 trillion 5 Latin America 216 billion 5 Source: GSMA (2019; 2020). GSM Association 1999-2019. Retrieved February 10, 2022, from https://www. gsma.com/r/wp-content/uploads/2021/09/The-State-of-Mobile-Internet-Connectivity-Report-2021.pdf/ The size of the internet economy in Africa shows the Africa potential to compete with another region especially Latin America. Amongst other developing countries in African Kenya represent highest performance Google and IFC (2020) iGDP accounting for about 7.7 % of total GDP. Ethiopia account for the lower iGPA and many other countries in the region have smaller iGPA economies. Below is the iGDP forecast for developing countries in Africa (Table 2). iGDP forecast for developing countries in Africa, 2020-2050 Table 2 Country 2020, $ 2020, % 2025, $ 2025, % 2050, $ 2050, % Tanzania 2,57 3.98 4.28 4.75 17.03 7.50 Nigeria 24.59 5.68 36.53 6.86 145.28 11.27 South Africa 21.55 6.51 31.4 7.86 125.08 12.92 Ghana 3.01 4.42 5.01 5.31 19.94 8.73 Cameroon 2.06 5.39 3.27 6.19 13.00 10.16 Senegal 1.51 6.22 2.29 7.11 11.61 11.68 Rwanda 0.52 4.98 0.97 5.96 3.85 9.79 Mozambique 0.37 2.45 0.67 2.81 2.65 4.62 Keyna 7.42 7.70 12.84 92.4 51.07 15.17 Morocco 7.80 6.82 12.09 7.84 48.06 12.88 Algeria 9.02 5.60 11.92 6.16 47.39 10.12 Ethiopia 1.26 1.27 2.02 1.39 8.03 2.28 Cote d’Ivoire 3.18 5.27 5.53 6.04 21.98 9.92 % Egypt 15.41 4.98 25.97 5.99 103.29 9.83 Uganda 1.36 3.82 2.26 4.18 8.97 6.87 Angola 2.02 2.17 2.88 2.38 11.44 3.91 Ethopia 1.26 1.27 2.02 1.39 8.03 2.28 Rest of Africa 11.62 1.96 18.55 2.16 73.76 3.54 Source: Calculated by the Author based on the available data from the World Bank. Retrieved February 10, 2021, from https://www.worldbank.org/ Methods Looking at the influence of the digitalization factor on the formation and development of human capital in developing countries, this Article have therefore investigated and analysed the relationship between Human capital Index and digitalisation, and skill development using the Electronic Data Interchange ranking as a useful parameter in this analysis. The Eelectronic Data Interchange (EDI) ranking has been considered as an ordinal variable and Human capital Index is a continuous variable. These two variables have allowed us to use the Kendall’s (1) correlation coefficient (tau-b) to test the association of the variables. Below is a data set from world bank group and World development report for 2019 and 2020 used as secondary data for this study. The table below shows variables for 14 different countries with Electronic Data Interchange (EDI), and Human Capital variables for 14 countries (Although the data is highly irregular due to missing observations for many countries, we can still observe a broad upward trend from the majority of countries) (Table 3). Table 3 Interchange (EDI), and Human Capital variables, 2019-2020 Countries with Lead digital access EDI Ranking 2019 Human Capital Index 2020 Skills Development Tanzania 96 0.55 Not stated Nigeria 99 0.36 Not stated Lesotho 100 0.40 Stated Benin 101 0.40 Not stated Cameroon 103 0.40 Not stated Senegal 104 0.42 Not stated Mali 105 0.42 Not stated Mozambique 106 0.36 Not stated Madagascar 109 0.39 Stated Mauritania 110 0.38 Not stated Guinea 113 0.37 Not stated Ethiopia 111 0.38 Not stated Liberia 115 0.32 Not stated Sierra Leone - 0.36 Not stated Source: Calculated by the Author based on the available data from the World Bank. Retrieved February 10, 2021, from https://www.worldbank.org/ Human capital index calculates the contribution of health and education to worker productivity. The final index score ranges from zero to one and measures the productivity as a future worker of a child born today relative to the benchmark of full health and complete education (Figure 3). Figure 3. Graphical representation of Human Capital and EDI ranking, 2019-2020 Source: calculated by the authors based on the available data from the World Bank. Retrieved February 10, 2021, from https://www.worldbank.org/ Refers to as Electronic data interchange; Normally it shows the ranking of digital access in different countries. There are no adequate skill development results for countries in the world. Results The result shows correlation coefficient (tau-b) test showing the association of the variables which was -0.4537. This means that Human Capital Index (HCI) and EDI ranking have negative correlation. In any case so if the Human Capital of these countries are reached the Electronic Data Interchange ranking will still decrease. This result shows that there developing countries’ investment in human capital in 2020 was not enough for these countries to reach the high level of digital access based on our dataset. The result also shows that two of the variables have statistically significant correlation at 95 % confidence interval, considering Bonferroni correction for p-value. Table 4 Influence of the digitalization factor on the formation and development of human capital National level impact on African countries Pathways of impact Likely labour market impact Opportunities Increase productivity Increase in jobs Increases in demand for new and existing products Increase in jobs Reduction in cost of production enabling new entrants and SMEs to enter the export market Creation of new jobs Reduction in cost of training leading to GVC participation Increase in jobs Challenges Substitution of labour with automations Decrease in jobs, unskilled workers are likely to be more affected Cognitive robot can be used to replace skilled labour Decrease in skilled job; skill labours moves to less skilled jobs increasing skill mismatching Increase in precious work on digital platforms Reductions in good jobs International level impact on African Countries Pathways of impact Fall in wages of labour Challenges Reshoring of manufacturing Automation can have a backstopping effect; Robot deployment in developed countries can pressure developing countries to become more competitive Exclusions from GVC and concentration of future production of digitally advanced goods in developed countries Loss of potential jobs Source: (Karishama Banga et al., 2018). In other to summarise the whole idea we have taken a close look at the influence of the digitalization factor on the formation and development of Human capital in a tabular analysis with the aim to ease the complexity of the discussion Furthermore, even today the electronics industry in Russia is still viewed as an IDM when it does not produce most devices inhouse. This shows that proper understanding of modern production chain of electronics (in the form of end product) is required. The national level impact of digitalisation has created opportunities despite numerous challenges in the case of developing countries. From a broader perspective the digital influence on the development of human capital has the tendency to increase productivity and expand knowledge base which in turn has a positive relationship in the development process of creating new market and improving job opportunities. The human capital development through technological effort has become competitive. The creation of unique and modern high-tech industries in the developed world has been a huge source for the ongoing digital process for many developing countries. The establishment of these digital infrastructure will help to support education, development of public services, research institutes and the formation of new industries for the establishment of skills development through on the job training and other mechanisms. Discussion and conclusion This article examines the influence of digitalisation factors on the formation and development of human capital development in developing countries. The article introduces digital economy and digital connectivity with their effect on individuals’ businesses and firms. The size of the digital economy as well as the fixed broadband for Digital economies especially for developing countries in the different region were compared in other to look at Africa’s position in the development process of digital adoption. Africa scoring 0.4 % in the Fixed-broadband subscriptions per 100 inhabitants (2019) and lagging behind middle east and Asia shows that the developing countries in Africa needs to develop required infrastructure that could support the digital transition and the adoption process. Europe, America and CIS countries however proved to have an excellent standing and double the progress that have been made in Asia and the middle east, that also consist of many developing countries. Furthermore, mobile technology plays a huge role in the digital adoption process looking at the emergence of social media and other daily electronic usages. The use of 4G technology in both sub-Saharan and North Africa is relatively low compared to other developing regions. China, North America and Europe however shows tremendous progress. The sub-Saharan Africa region consist of most of the countries for this research and the region proves to be weak in its capacity to compete with the rest of the world. The chapter also investigated secondary data from world bank group and World development report for 2019 and 2020 for 14 developing countries and analyse the relationship between Human capital Index and digitalisation using the EDI ranking. The investigation resulted into a negative correlation showing a correlation coefficient of -0.4537. It is recommended that developing countries should invest in human capital especially in digital skills and create the required of digital access to their citizen in a bid to adopt digital transformation whilst building the human capital development of the people.
×

About the authors

Tlesh M. Mamakhatov

Institute of the Far East of the Russian Academy of Sciences; Security Problems Studies Centre of the Russian Academy of Sciences

Author for correspondence.
Email: tmmamakhatov@gmail.com
ORCID iD: 0000-0001-7212-6831

Candidate of Economic Sciences, Leading Researcher, Center for the Studies of the Northeast Asia Strategic Issues and the Shanghai Cooperation Organization, Institute of the Far East of the Russian Academy of Sciences; Science Researcher, Security Problems Studies Centre of the Russian Academy of Sciences

32 Nakhimovsky Av., Moscow, 117997, Russian Federation; 21b Garibaldi St, Moscow, 117335, Russian Federation

James M. Mallah

Southern Federal University

Email: jamesmanaffmallah@gmail.com
PhD student 105/42 Bolshaya Sadovaya St, Rostov-on-Don, 344006, Russian Federation

References

  1. Azu, N.P., Jelivov, G., Aras, O.N., & Isik, A. (2021). Influence of digital economy on youth unemployment in West Africa. Transnational Corporations Review, 13(1), 32-42. https://doi.org /10.1080/19186444.2020.1849936
  2. Banga, K., & te Velde, D.W. (2018). Digitalisation and the Future of Manufacturing in Africa. https://doi.org/10.1596/978-1-4648-1444-0
  3. Bara-Slupski, T.K. (2016). Holistic Approach: paradigm shift in the research agenda for digitalisation of healthcare in Sub-Saharan Africa. The African Journal of Information Systems, 8(4), 3. https://doi.org/10.1080/02681102.2018.1461057
  4. Baumöl, U., & Bockshecker, A. (2017, July). Evolutionary change of higher education driven by digitalization. In 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET) (pp. 1-5). IEEE. https://doi.org/10.1109/ITHET.2017.8067811
  5. Chiang, C.T. (2020). Developing an eMarketing model for tourism and hospitality: a keyword analysis. International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/IJCHM-03-2020-0230
  6. Gil-Garcia, J.R., & Hassan, S. (2008). Structure Theory and Government IT. https://doi.org/10.4018/9781599048574.ch035
  7. Gora, Y. (2020). An exploratory, qualitative study on the factors which influence South African millennials to shop online, using an in-depth interview. The IIE. https://doi.org/10.1186/s40852-018-0090-7
  8. Großer, B., & Baumöl, U. (2017). Why virtual teams work-State of the art. Procedia computer science, 121, 297-305 https://doi.org/10.1016/j.procs.2017.11.041
  9. Hsu, I.C., Yeh-Yun Lin, C.A.R.O.L., Lawler, J.J., & Wu, S.H. (2007). Toward a model of organizational human capital development: Preliminary evidence from Taiwan. Asia Pacific Business Review, 13(2), 251-275. https://doi.org/10.24940/ijird/2019/v8/i1/DEC18038
  10. Ivanova, V.V. (2019). Management of Digital Information Technologies in Digital Economy. https://doi.org/10.21272/mer.2019.85.08
  11. Kendrick, J.W. (1994). Total capital and economic growth. Atlantic Economic Journal, 22(1), 1-18. https://doi.org/10.1007/BF02301693
  12. Kohtamäki, M., Parida, V., Patel, P.C., & Gebauer, H. (2020). The relationship between digitalization and servitization: The role of servitization in capturing the financial potential of digitalization. Technological Forecasting and Social Change, 151. https://doi.org/10.1016/J. TECHFORE.2019.119804
  13. Korovkin, V. (2019). National digital economy strategies: A survey of Africa. ORF Issue Brief. https://doi.org/10.1093/icc/dtab053
  14. Lüneborg, J.L., & Nielsen, J.F. (2003). Customer-focused technology and performance in small and large banks. European Management Journal, 21(2), 258-269. https://doi.org/10.1016/j.indmarman.2010.02.001
  15. Matsuyama, K. (2009). Structural change in an interdependent world: A global view of manufacturing decline. Journal of the European Economic Association, 7(2-3), 478-486. https://doi.org/10.1162/JEEA.2009.7.2-3.478
  16. Matthess, M., & Kunkel, S. (2020). Structural change and digitalization in developing countries: Conceptually linking the two transformations. Technology in Society, 63, 101428. https://doi.org/10.1016/J.TECHSOC.2020.101428
  17. McBride, N., & Stahl, B.C. (2010). Analysing a national information strategy: a critical approach. International Journal of Intercultural Information Management, 2(3), 232. https://doi.org/10.1504/IJIIM.2010.037863
  18. Minges, M., Briceño-Garmendia, C., Williams, M., Ampah, M., Camos, D., & Shkratan, M. (2008). Information and communications technology in sub-Saharan Africa: A sector review. Background paper, 10.
  19. Ndemo, B., & Weiss, T. (2017). Making sense of Africa’s emerging digital transformation and its many futures. Africa Journal of Management, 3(3-4), 328-347. https://doi.org/10.1080/23322373.2017.1400260
  20. Nicholson, J.S. (1891). The Living Capital of the United Kingdom. The Economic Journal, 1(1), 95-107. https://doi.org/10.2307/2955843
  21. Tanriverdi, H., & Venkatraman, N. (2005). Knowledge relatedness and the performance of multibusiness firms. Strategic management journal, 26(2), 97-119. https://doi.org/10.4236/ojbm.2021.96168
  22. Teixeira, P.N. (2014). Gary Becker’s early work on human capital - collaborations and distinctiveness. IZA Journal of Labor Economics, 3(1), 12. https://doi.org/10.1186/s40172-0140012-2
  23. Tippins, M.J., & Sohi, R.S. (2003). IT competency and firm performance: is organizational learning a missing link? Strategic management journal, 24(8), 745-761. https://doi.org/10.1002/smj.337
  24. Tuguskina, G.N. (2019). The Role Of Human Capital In The Digital Economy. https://doi.org/10.15405/epsbs.2019.03.95
  25. Wade, R.H. (2016). Industrial Policy in Response to the Middle-income Trap and the Third Wave of the Digital Revolution. Global Policy, 7(4), 469-480. https://doi.org/10.1111/17585899.12364

Copyright (c) 2022 Mamakhatov T.M., Mallah J.M.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies