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Configural theory for ICT development

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  • Huarng, Kun-Huang

Abstract

This study intends to establish configural theory for ICT development by using fuzzy set/Qualitative Comparative Analysis (fsQCA) and to contrast the results with those from multivariate regression analysis (MRA). The fsQCA results support three propositions: the highly-developed countries, the highly-developed countries with low population density and the highly-developed countries with low corruption are the sufficient conditions for high ICT development. In addition, the improvement toward developed countries and increases in both population density and corruption are a sufficient condition for the improvement in ICT development. However, fsQCA finds a contrary case: the improvement toward developed countries and decreases in both population density and corruption are also a sufficient condition for the improvement in ICT development. MRA is good at model fitting. FsQCA is good at showing the causal complexities to explain the outcome and successfully predicts the withheld data sets.

Suggested Citation

  • Huarng, Kun-Huang, 2015. "Configural theory for ICT development," Journal of Business Research, Elsevier, vol. 68(4), pages 748-756.
    • Handle: RePEc:eee:jbrese:v:68:y:2015:i:4:p:748-756
    DOI: 10.1016/j.jbusres.2014.11.023
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    References listed on IDEAS

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    1. Huarng, Kun-Huang, 2011. "A comparative study to classify ICT developments by economies," Journal of Business Research, Elsevier, vol. 64(11), pages 1174-1177.
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    5. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2014. "A new quantile regression forecasting model," Journal of Business Research, Elsevier, vol. 67(5), pages 779-784.
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    8. Bilal MEHMOOD & Parvez AZIM, 2013. "Does ICT Participate in Economic Convergence among Asian Countries: Evidence from Dynamic Panel Data Model," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 17(2), pages 7-16.
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    Cited by:

    1. Huarng, Kun-Huang, 2016. "Qualitative analysis with structural associations," Journal of Business Research, Elsevier, vol. 69(11), pages 5187-5191.
    2. Yu-Shan Lin, 2017. "Causal complexity for passengers’ intentions to re-ride," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 1925-1937, September.
    3. Yu, Tiffany Hui-Kuang & Huang, Meng-Chen & Huarng, Kun-Huang, 2016. "Causal complexity of economic development by energy consumption," Journal of Business Research, Elsevier, vol. 69(6), pages 2271-2276.
    4. Wu, Chih-Wen, 2015. "Facebook users' intentions in risk communication and food-safety issues," Journal of Business Research, Elsevier, vol. 68(11), pages 2242-2247.
    5. Nikou, Shahrokh, 2018. "Internet of Things: Exploring households' intention to use smart home technology," 22nd ITS Biennial Conference, Seoul 2018. Beyond the boundaries: Challenges for business, policy and society 190335, International Telecommunications Society (ITS).
    6. Lin, Chiu Hui & Wu, Chih-Wen & Cheng, Yi-Han, 2015. "The empirical study of consumers' loyalty for display technology," Journal of Business Research, Elsevier, vol. 68(11), pages 2260-2265.
    7. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2020. "The impact of surge pricing on customer retention," Journal of Business Research, Elsevier, vol. 120(C), pages 175-180.
    8. Kun-Huang Huarng & Tiffany Hui-Kuang Yu, 2017. "Using qualitative approach to forecasting regime switches," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2035-2048, September.
    9. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2015. "Forecasting ICT development through quantile confidence intervals," Journal of Business Research, Elsevier, vol. 68(11), pages 2295-2298.
    10. Sascha Kraus & Domingo Ribeiro-Soriano & Miriam Schüssler, 2018. "Fuzzy-set qualitative comparative analysis (fsQCA) in entrepreneurship and innovation research – the rise of a method," International Entrepreneurship and Management Journal, Springer, vol. 14(1), pages 15-33, March.
    11. Huarng, Kun-Huang, 2016. "Identifying regime switches using causal recipes," Journal of Business Research, Elsevier, vol. 69(4), pages 1498-1502.
    12. Kun-Huang Huarng & Tiffany Hui-Kuang Yu, 2021. "Complexity theory of entrepreneur characteristics," International Entrepreneurship and Management Journal, Springer, vol. 17(3), pages 1037-1048, September.
    13. Ufere, Nnaoke & Gaskin, James & Perelli, Sheri & Somers, Antoinette & Boland, Richard, 2020. "Why is bribery pervasive among firms in sub-Saharan African countries? Multi-industry empirical evidence of organizational isomorphism," Journal of Business Research, Elsevier, vol. 108(C), pages 92-104.
    14. Romero-Martínez, Ana M. & García-Muiña, Fernando E., 2021. "Digitalization level, corruptive practices, and location choice in the hotel industry," Journal of Business Research, Elsevier, vol. 136(C), pages 176-185.
    15. Vizcaíno, Marcos & Chousa, Juan P., 2016. "Analyzing the influence of the funds' support on Tobin's q using SEM and fsQCA," Journal of Business Research, Elsevier, vol. 69(6), pages 2118-2124.
    16. Muñoz, Pablo & Kibler, Ewald, 2016. "Institutional complexity and social entrepreneurship: A fuzzy-set approach," Journal of Business Research, Elsevier, vol. 69(4), pages 1314-1318.
    17. Cheng, Cong & Wang, Limin, 2022. "How companies configure digital innovation attributes for business model innovation? A configurational view," Technovation, Elsevier, vol. 112(C).
    18. Huarng, Kun-Huang & Bresciani, Stefano & Ferraris, Alberto, 2020. "Experiential interaction design model," Journal of Business Research, Elsevier, vol. 118(C), pages 486-490.

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