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Impact of Socio-Cultural Factors onto the National Technology Development

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1038))

Abstract

The paper proposes the empiric research of socio-cultural factors’ impact on the national technology development. It is well noted that the rapid technology development gives an increase of living standards, boost country economy, and contributes substantially to the gross domestic product. Being intangible socio-cultural factors are still potential drivers to the technology development enhancement and play an important role in constituting national welfare.

The aim of the present research is to empirically investigate whether socio-cultural factors have significant impact on the national technology development and whether Hofstede’s indices play a mediating role between chosen factors and the technology development. The literature review has shown that results of the similar empiric research are rather controversial. Based on a dataset from more than 100 countries we have designed and analyzed a second-order model that confirmed the impact of the chosen factors to the technology development at a national economy. The most unexpected result deals with the direct impact of the business culture (R2 = 0.92). The received results also confirmed the role of the human capital and the social capital. Hofstede’s indices play a mediating role in two from three cases: between human capital and the national technology development and between business culture and the technology development.

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References

  1. Aghion, P., Howitt, P.: Endogenous Growth Theory. MIT Press, Cambridge (1997)

    MATH  Google Scholar 

  2. Akcomac, S., Weel, B.: Social capital, innovation and growth: evidence from Europe. Eur. Econ. Rev. 53, 544–567 (2009)

    Article  Google Scholar 

  3. Amat, O., Renart, M., Garcia, M.: Factors that determine the evolution of high-growth businesses. Intang. Cap. 9, 379–391 (2013)

    Google Scholar 

  4. Arrow, K.J.: The economic implications of learning by doing. Rev. Econ. Stud. 29, 155–173 (1962)

    Article  Google Scholar 

  5. Arkhipova, M.Y., Sirotin, V.P., Sukhareva, N.A.: The elaboration of composite indicator for measuring dynamics of cyber inequality in RF. Stat. Issues 4, 75–87 (2018)

    Google Scholar 

  6. Ayvazyan, S.A., Stepanov, V.S., Kozlova, M.I.: Measuring of synthetic parameters of living standards of a region and investigating of key directions of social and economic policy improvement (on the example of Samar region). Appl. Econom. 2, 18–84 (2006)

    Google Scholar 

  7. Barro, R.: Economic growth in a cross section of countries. Q. J. Econ. 106, 407–443 (1991)

    Article  Google Scholar 

  8. Baxter, R.: Reflective and formative metrics of relationship value: a commentary essay. J. Bus. Res. 62(12), 1370–1377 (2009)

    Article  Google Scholar 

  9. Blalock, H.M.: Conceptualization and Measurement in the Social Sciences. Sage Publications, Beverly Hills (1982)

    Google Scholar 

  10. Bollen, K.A., Bauldry, S.: Three Cs in measurement models: casual indicators, composite indicators and covariates. Psychol. Methods 16(3), 265–284 (2011)

    Article  Google Scholar 

  11. Bozhechkova, A.V.: The analysis of scientific and technology progress impact on the dynamics of gross domestic product. Audit Financ. Anal. 3, 85–94 (2011)

    Google Scholar 

  12. Bourdieu, P.: Forms of capital. In: Richardson, J.G. (ed.) Handbook of Theory and Research for Sociology of Education. Greenwood, New York (1986)

    Google Scholar 

  13. Burt, R., Hogarth, R.M., Michaud, C.: The social capital of French and American managers. Organ. Sci. 11, 123–147 (2000)

    Article  Google Scholar 

  14. Cadil, J., Petkovova, L., Blatna, D.: Human capital, economic structure and growth. Procedia Econ. Financ. 12, 85–92 (2014)

    Article  Google Scholar 

  15. Camps, S., Marques, P.: Exploring how social capital facilitates innovation: the role of innovation enablers. Technol. Forecast. Soc. Chang. 88, 325–348 (2014)

    Article  Google Scholar 

  16. Coad, A.: Exploring the processes of a firm growth: evidence from a vector autoregression. Ind. Corp. Change 19, 1677–1703 (2010)

    Article  Google Scholar 

  17. Coad, A.: Innovation and firm growth in high-technology sectors: a quantile regression approach. Res. Policy 37(4), 633–648 (2008)

    Article  Google Scholar 

  18. Cohen, D., Soto, M.: Growth and human capital: good data, good results. J. Econ. Growth 12, 51–76 (2007)

    Article  MATH  Google Scholar 

  19. Coleman, J.: Social and human capital. Soc. Sci. Mod. 3, 122–139 (2001)

    Google Scholar 

  20. Coleman, J.: Social capital in the creation of human capital. Am. J. Sociol. 94, 95–120 (1988)

    Article  Google Scholar 

  21. Eurostat main indicators. https://ec.europa.eu/eurostat/web/sdi/main-tables

  22. Churchill Jr., G.A.: A paradigm for developing better measures of marketing constructs. J. Mark. Res. 16(1), 64–73 (1979)

    Article  Google Scholar 

  23. Diamantopoulos, A., Riefler, P., Roth, K.P.: Advancing formative measurement models. J. Bus. Res. 61(12), 1203–1218 (2008)

    Article  Google Scholar 

  24. Drogovoz, P.A., Sadovskaya, T.G., Chursin, A.A., Shiboldenkov, V.A.: The neural network analysis of social and cultural factors impact on state innovation activity. Scientific research and development. Soc. Humanit. Res. Technol. 6(2), 72–80 (2017)

    Google Scholar 

  25. Fornell, C., Bookstein, F.L.: Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. J. Market. Res. 19, 440–452 (1982)

    Article  Google Scholar 

  26. Hall, E.T.: Beoynd Culture. Anchor, Garden City (1976)

    Google Scholar 

  27. Hair, J., Hult, G., Ringle, C., Sarstedt, M.: A Primer on Partial Least Squares Equation Modelling. Sage Publications, Thousand Oaks (2014)

    MATH  Google Scholar 

  28. Hair, J., Ringle, C., Sarstedt, M.: Partial least squares: the better approach to structural equation modelling? Long Range Plan. 45(5–6), 312–319 (2012)

    Article  Google Scholar 

  29. Henseler, J.: Guest editorial. Indus. Manag. Data Syst. 116(9), 1842–1848 (2016)

    Article  Google Scholar 

  30. Henseler, J., Hubona, G.S., Ray, P.A.: Using PLS path modelling in new technology research: updated guidelines. Indus. Manag. Data Syst. 116(1), 1–19 (2016)

    Google Scholar 

  31. Hofstede, G.: Culture’s Consequences: International Differences in Work-Related Values. Sage, Beverly Hills (1980)

    Google Scholar 

  32. Hofstede Insites. http://www.hofstede-insights.com/models/

  33. Hofstede, G., Hofstede, G.J.: Cultures and Organizations: Software of the Mind. McGraw-Hill, New York (2005)

    Google Scholar 

  34. Grzegorczyk, M.: The role of culture moderated social capital in technology transfer insights from Asia and America. Technol. Forecast. Soc. Chang. 143, 132–141 (2019)

    Article  Google Scholar 

  35. Kumar, N., Rego, S.: Level of educational attainment and its impact on technology diffusion in developing countries (2009). http://dx.doi.org/10.2139/ssrn.1350187

  36. Lucas, R.E.: On the mechanics of economic development. J. Monet. Econ. 22, 3–42 (1988)

    Article  Google Scholar 

  37. Landry, R., Amara, N., Lamari, M.: Does social capital determine innovation? To what extent? Technol. Forecast. Soc. Chang. 69(7), 681–701 (2002)

    Article  Google Scholar 

  38. Lockett, M.: Culture and the problems of Chinese management. Organ. Stud. 9(4), 475–496 (1998)

    Article  MathSciNet  Google Scholar 

  39. Lowry, P.B., Gaskin, J.: Partial least squares structural equation modeling for building and testing behavioral causal theory: when to choose it and how to use it. IEEE Trans. Prof. Commun. 57(2), 123–146 (2014)

    Article  Google Scholar 

  40. Magdeeva, M.R., Zhilina, N.N., Zgidulina, T.S.: Social capital: notion and approaches to research. Econ. Manag. Probl. Solut. 1, 18–23 (2017)

    Google Scholar 

  41. Mankiw, G., Romer, D., Wil, D.: A contribution to the empirics of the economic growth. Q. J. Econ. 107, 407–437 (1992)

    Article  MATH  Google Scholar 

  42. Maskell, P.: Social capital, innovation and competitiveness. In: Baron, S., Field, J., Schuller, T. (eds.) Social Capital: Critical Perspectives, pp. 111–123. Oxford University Press, New York (2000)

    Google Scholar 

  43. Nasledov, A.D., Morozova, S.V.: The problem of mathematical implementation in psychological research: institualization of statistic discourse. Herald Saint-Petersburg Univ. 4, 252–261 (2010)

    Google Scholar 

  44. Prokhorov, I.A.: The launch of the seventh technology paradigm. http://www.energoinform.org/pointofview/prohorov/7-tech-structure.aspx

  45. Queiros, M., et al.: Cross-country analysis to high-growth businesses: unveiling its determinants. J. Innov. Knowl. 4(3), 146–153 (2017)

    Article  Google Scholar 

  46. Ramos, R., Surinach, J., Artis, M.: Regional economic growth and human capital: the role of overeducation. Working papers 2009/04, Research Institute of Applied Economics (2009)

    Google Scholar 

  47. Rigdon, E.E.: Rethinking partial least squares path modelling: in praise of simple methods. Long Range Plan. 45, 341–358 (2012)

    Article  Google Scholar 

  48. Romer, P.: Endogenous technological change. J. Polit. Econ. 98, 71–102 (1990)

    Article  Google Scholar 

  49. Romanov, A.A., et al.: The methodology for the creation of an innovative scientific and technical reserve in the rocket and space industry. Rocket Space Ind. Device Build. Inf. Syst. 5(2), 53–64 (2018)

    Google Scholar 

  50. Temple, J.: Growth effects of education and social capital in the OECD countries. OECD Econ. Stud. 33, 57–101 (2001)

    Google Scholar 

  51. Thorton, S., Hennenberg, S., Naude, P.: Conceptualizing and validating organizational networking as a second-order formative construct. Ind. Mark. Manag. 43, 951–956 (2014)

    Article  Google Scholar 

  52. Usawa, H.: Optimum technical change in an aggregative model of economic growth. Int. Econ. Rev. 6, 18–31 (1965)

    Article  Google Scholar 

  53. UNESCO. http://data.uis.unesco.org

  54. Humanitarian Technologies Analitical Portal. http://www.gtmarket.ru

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Correspondence to Evgeniya Gorlacheva .

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Gorlacheva, E., Omelchenko, I., Drogovoz, P., Yusufova, O., Shiboldenkov, V. (2019). Impact of Socio-Cultural Factors onto the National Technology Development. In: Alexandrov, D., Boukhanovsky, A., Chugunov, A., Kabanov, Y., Koltsova, O., Musabirov, I. (eds) Digital Transformation and Global Society. DTGS 2019. Communications in Computer and Information Science, vol 1038. Springer, Cham. https://doi.org/10.1007/978-3-030-37858-5_26

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  • DOI: https://doi.org/10.1007/978-3-030-37858-5_26

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