Skip to main content
SpringerLink
Log in

Applying QCA and Cross-impact Analysis to the Study on ICT Adoption and Use by Croatian SMEs

  • Chapter
  • First Online:
Complexity in Entrepreneurship, Innovation and Technology Research

Part of the book series: FGF Studies in Small Business and Entrepreneurship ((FGFS))

  • 1550 Accesses

Abstract

QCA reduces complexity and richness of each individual case through the process of Boolean minimization. This poses a challenge for future development of QCA as a case study method. We address this challenge and propose complementing QCA with cross-impact analysis. This latter method provides an in-depth, holistic analysis of a single case by focusing on the set of factors that are an essential part of each case, and focuses on capturing and analyzing interactions between these factors. That is, after deriving causal explanations, researchers can return to the cases and capture their complexity and interactions. Application of both methods is demonstrated in this paper in the context of ICT adoption and use in Croatian SMEs. While QCA provides a macro overview of a number of cases and identifies seven key factors that influence SMEs’ adoption of ICT, cross-impact analysis has a case-based focus that provides additional insights into SMEs actual experiences and challenges with ICT use. The alignment between the two methods produces important implications for the future development of QCA towards in-depth case analysis and exploring the complexity of each case.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    The results reported in this section are from work previously completed by: Skoko, H., Krivokapic-Skoko, B., Skare, M., & Ceric, A. (2006). ICT Adoption Policy of Australian and Croatian SMEs. Managing Global Transitions, 4(1), 25–40.

References

  • Ackoff, R. L. (1971). Towards a system of systems concepts. Management Science, 17(11), 661–671.

    Article  Google Scholar 

  • Amenta, E., & Poulsen, J. D. (1996). Social politics in context: The institutional politics theory and social spending at the end of the New Deal. Social Forces, 75(1), 33–61.

    Article  Google Scholar 

  • Asan, U., Bozdağ, C. E., & Polat, S. (2004). A fuzzy approach to qualitative cross impact analysis. Omega, 32(6), 443–458.

    Article  Google Scholar 

  • Bar-Yam, Y. (1997). Dynamics of complex systems (Vol. 213). Reading, MA: Addison-Wesley.

    Google Scholar 

  • Biggert, R. (1997). Why labour wins, why labour loses: A test of two theories. The Sociological Quarterly, 38(1), 205–224.

    Article  Google Scholar 

  • Brooksbank, R., Kirby, D., & Kane, S. (1992). IT adoption and the independent retail business: The retail newsagency. International Small Business Journal, 10(3), 53–61.

    Article  Google Scholar 

  • Caren, N., & Panofsky, A. (2005). TQCA: A technique for adding temporality to qualitative comparative analysis. Sociological Methods and Research, 2(34), 147–172.

    Article  Google Scholar 

  • Ceric, A. (2015a). Alternative model of ICT value creation based on cross-impact analysis. Contemporary Management Research, 11(3), 223–248.

    Article  Google Scholar 

  • Ceric, A. (2015b). Bringing together evaluation and management of ICT value: A systems theory approach. Electronic Journal of IS Evaluation, 18(1), 223–248.

    Google Scholar 

  • Cheng, C.-F., Chang, M.-L., & Li, C.-S. (2013). Configurational paths to successful product innovation. Journal of Business Research, 66(12), 2561–2573.

    Article  Google Scholar 

  • Cilliers, P. (1998). Complexity and postmodernism: Understanding complex systems. London: Routledge.

    Google Scholar 

  • Cole, A., Allen, W., Kilvington, M., Fenemor, A., & Bowden, B. (2007). Participatory modelling with an influence matrix and the calculation of whole-of system sustainability values. International Journal of Sustainable Development, 10(4), 382–401.

    Article  Google Scholar 

  • Cooper, B., & Glaesser, J. (2011). Using case-based approach to analyze large datasets: A comparison of Ragin’s fsQCA and fuzzy cluster analysis. International Journal of Social Research Methodology, 14(1), 31–48.

    Article  Google Scholar 

  • Coverdill, J. E., Finlay, W., & Martin, J. K. (1994). Labour management in the southern textile industry: Comparing qualitative, quantitative, and qualitative comparative analyses. Sociological Methods and Research, 23(1), 54–85.

    Article  Google Scholar 

  • Dann, Z., & Barclay, I. (2006). Complexity theory and knowledge management application. Electronic Journal of Knowledge Management, 4(1), 11–20.

    Google Scholar 

  • Davern, M. J., & Kauffman, R. J. (2000). Discovering potential and realizing value from information technology investments. Journal of Management Information Systems, 16(4), 121–143.

    Article  Google Scholar 

  • Denk, T. (2010). Comparative multilevel analysis: Proposal for a methodology. International Journal of Social Research Methodology, 13(1), 29–39.

    Article  Google Scholar 

  • Fiss, P. (2007). A set-theoretic approach to organizational configurations. Academy of Management Review, 32(4), 1180–1198.

    Article  Google Scholar 

  • Fiss, P. (2008). Configurations of strategy, structure and environment: A fuzzy set analysis of high technology firms. Retrieved from http://www-rcf.usc.edu/~fiss/research.html

  • Ganter, A., & Hecker, A. (2014). Configurational paths to organizational innovation: Qualitative comparative analysis of antecedents and contingencies. Journal of Business Research, 67(6), 1285–1292.

    Article  Google Scholar 

  • Gordon, T. J., & Hayward, H. (1968). Initial experiments with the cross impact matrix method of forecasting. Futures, 1(2), 100–116.

    Article  Google Scholar 

  • Greckhamer, T., Misangyi, V. F., Elms, H., & Lacey, T. (2008). Using qualitative comparative analysis in strategic management research: An examination of combinations of industry, corporate, and business-unit effects. Organizational Research Methods, 11(4), 695–726.

    Article  Google Scholar 

  • Gregor, S., Fernandez, W., Holtham, D., Martin, M., Stern, S., Vitale, M., et al. (2004). Achieving value from ICT: Key management strategies (ICT research study, Department of Communications, Information Technology and the Arts, Canberra, Australia). Retrieved from http://ict-industry-reports.com/wp-content/uploads/sites/4/2013/10/2005-Achieving-Value-from-ICT-Key-Management-Strategies-Opticon-DCITA.pdf

  • Hellström, E. (1998). Qualitative comparative analysis: A useful tool for research into forest policy and forestry conflicts. Forest Science, 44(2), 254–265.

    Google Scholar 

  • Helmer, O. (1972). Cross-impact gaming. Futures, 4(2), 149–167.

    Article  Google Scholar 

  • Herrmann, A. M., & Cronqvist, L. (2009). When dichotomization becomes a problem for the analysis of middle-sized datasets. International Journal of Social Research Methodology, 12(1), 33–50.

    Article  Google Scholar 

  • Iacovou, C. L., Benbasat, I., & Dexter, A. A. (1995). Electronic data interchange and small organisations: Adoption and impact of technology. MIS Quarterly, 19(4), 465–485.

    Article  Google Scholar 

  • Julien, P. A., & Raymond, L. (1994). Factors of new technology adoption in the retail sector. Entrepreneurship Theory and Practice, 18(5), 79–90.

    Google Scholar 

  • Kardaras, D., & Karakostas, B. (1999). The use of fuzzy cognitive maps to simulate the information systems strategic planning process. Information and Software Technology, 41(4), 197–210.

    Article  Google Scholar 

  • Kirby, D., & Turner, M. (1993). IT and the small retail business. International Journal of Retail and Distribution Management, 21(7), 20–27.

    Article  Google Scholar 

  • Kithenerm, M., Beynon, M., & Harrington, C. (2002). Qualitative comparative analysis and public services research. Public Management Review, 4(2), 485–504.

    Google Scholar 

  • Kogut, B., & Ragin, C. C. (2006). Exploring complexity when diversity is limited: Institutional complementarity in theories of rule of law and national systems revisited. European Management Review, 3(1), 44–59.

    Article  Google Scholar 

  • Krivokapic-Skoko, B. (2001). Understanding ethnic entrepreneurship in agricultural settings: Qualitative comparative analysis of ethnic groups in New Zealand agriculture (Doctoral dissertation, Lincoln University, New Zealand).

    Google Scholar 

  • Kvist, J. (2003). Conceptualisation, configuration, and categorization—Diversity, ideal types and fuzzy sets in comparative welfare state research (COMPASSS working paper series 2003-15). Retrieved from http://www.compasss.org/wpseries/Kvist2003.pdf

  • Lambert, S., & Fairweather, J. (2010). The socio-technical networks of technology users’ innovation in New Zealand: A fuzzy-set qualitative comparative analysis (Research Report No. 320). Retrieved from http://www.lincoln.ac.nz/PageFiles/1494/RR%20320w.pdf

  • Marx, A. (2010). Crips-set qualitative comparative analysis (csQCA) and model specification: Benchmarks for future csQCA applications. International Journal of Multiple Journal Approaches, 4(2), 138–158.

    Article  Google Scholar 

  • Marx, A., Cambré, B., & Rihoux, B. (2013). Crisp-set qualitative comparative analysis in organizational studies. In P. Fiss, B. Cambré, & A. Marx (Eds.), Configurational theory and methods in organizational research (Vol. 38, pp. 23–47). Bingley: Emerald.

    Chapter  Google Scholar 

  • Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Review: Information technology and organizational performance: An integrative model of IT business value. MIS Quarterly, 28(2), 283–322.

    Google Scholar 

  • Messerli, P. (2000). Use of sensitivity analysis to evaluate key factors for improving slash-and-burn cultivation systems on the eastern escarpment of Madagascar. Mountain Research and Development, 20(1), 32–41.

    Article  Google Scholar 

  • Özlem, Ö. (2004). Using Boolean and fuzzy-logic based methods to analysis multiple case study evidence in management research. Journal of Management Inquiry, 13(2), 166–179.

    Article  Google Scholar 

  • Pajunen, K. (2008). Institutions and inflows of foreign direct investment: A fuzzy-set analysis. Journal of International Business Studies, 39(4), 652–669.

    Article  Google Scholar 

  • Poon, S., & Swatman, P. (1999). An exploratory study of small business internet commerce issues. Information and Management, 35(1), 9–18.

    Article  Google Scholar 

  • Premkumar, G., & Roberts, M. (1999). Adoption of new information technologies in rural small businesses. Omega, 27(4), 467–484.

    Article  Google Scholar 

  • Ragin, C. C. (1987). The comparative method: Moving beyond qualitative and quantitative strategies. Berkeley, CA: University of California Press.

    Google Scholar 

  • Ragin, C. C. (2000). Fuzzy-set social science. Chicago: University of Chicago Press.

    Google Scholar 

  • Rantala, K., & Hellström, E. (2011). Qualitative comparative analysis and a hermeneutic approach to interview data. International Journal of Social Research Methodology, 4(2), 87–100.

    Article  Google Scholar 

  • Rashid, M. A., & Al-Qirim, N. A. (2001). E-commerce technology adoption framework by New Zealand small to medium enterprises. Research Letters in the Information Mathematical Science, 2(1), 63–70.

    Google Scholar 

  • Ratnasingham, P. (1997). EDI security—Re-evaluation of controls and its implications on the organisations. Computers and Security, 16(8), 650–656.

    Article  Google Scholar 

  • Rihoux, B. (2003). Bridging the gap between the qualitative and quantitative worlds? A retrospective and prospective view on qualitative comparative analysis. Field Methods, 15(4), 351–365.

    Article  Google Scholar 

  • Rihoux, B., Álamos-Concha, P., Bol, D., Marx, A., & Rezsöhazy, I. (2013). From niche to mainstream method? A comprehensive mapping of QCA applications in journal articles from 1984 to 2011. Political Research Quarterly, 66(1), 175–184.

    Article  Google Scholar 

  • Rihoux, B., & Lobe, B. (2009). The case for qualitative comparative analysis (QCA): Adding leverage for thick cross-case comparison. In D. Byrne & C. C. Ragin (Eds.), The Sage handbook of case-base methods (pp. 222–242). Thousand Oaks, CA: Sage.

    Chapter  Google Scholar 

  • Rihoux, B., & Ragin, C. C. (Eds.). (2009). Configurational comparative methods: Qualitative comparative analysis (QCA) and related techniques. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.

    Google Scholar 

  • Romme, A. G. L. (1995). Self-organising processes in top management teams: A Boolean comparative approach. Journal of Business Research, 34(1), 11–34.

    Article  Google Scholar 

  • Schlange, L. E. (1995). Linking futures research methodologies: An application of systems thinking and metagame analysis to nuclear energy policy issues. Futures, 27(8), 823–838.

    Article  Google Scholar 

  • Skyttner, L. (1996). General systems theory: An introduction. London: Macmillan.

    Book  Google Scholar 

  • Stokke, O. S. (2007). Qualitative comparative analysis, shaming and international regime effectiveness. Journal of Business Research, 60(5), 501–511.

    Article  Google Scholar 

  • Thong, J., & Yap, C. (1996). Information technology adoption by small business: An empirical study. In K. Kautz & J. Pries-Heje (Eds.), Diffusion and adoption of information technology (pp. 160–175). New York: Springer.

    Chapter  Google Scholar 

  • Trochim, W. M., Cabrera, D. A., Milstein, B., Gallagher, R. S., & Leischow, S. J. (2006). Practical challenges of systems thinking and modelling in public health. American Journal of Public Health, 96(3), 538–546.

    Article  Google Scholar 

  • Van Akeren, J. K., & Cavaye, L. M. A. (2000). Factors impacting on entry-level electronic commerce adoption in the automobile industry in Australia: An empirical study. Paper presented at ICSB World conference, Brisbane, Australia.

    Google Scholar 

  • Vester, F., & Hesler, A. (1982). Sensitivity model. Frankfurt am Main: Umlandverband.

    Google Scholar 

  • Von Bertalanffy, L. (1972). The history and status of general systems theory. Academy of Management Journal, 15(4), 407–426.

    Article  Google Scholar 

  • Wade, M., & Hulland, J. (2004). Review: The resource-based view and information systems research: Review, extension, and suggestions for future research. MIS Quarterly, 28(1), 107–142.

    Google Scholar 

  • Waldrop, M. M. (1992). Complexity: The emerging science at the edge of order and chaos. New York: Simon and Schuster.

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank Professor Kevin Parton for his comments on previous drafts of this paper.

Author information

Authors and Affiliations

  1. School of Management and Marketing, Charles Sturt University, Panorama Avenue, Bathurst, 2795, NSW, Australia

    Arnela Ceric

  2. Branka Krivokapic-Skoko, School of Management and Marketing, Charles Sturt University, Panorama Avenue, Bathurst, 2795, NSW, Australia

    Branka Krivokapic-Skoko

Authors
  1. Arnela Ceric
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Branka Krivokapic-Skoko
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Arnela Ceric .

Editor information

Editors and Affiliations

  1. University of Hohenheim, Stuttgart, Germany

    Elisabeth S.C. Berger

  2. Inst Marketing & Management, University of Hohenheim, Stuttgart, Baden-Württemberg, Germany

    Andreas Kuckertz

Appendix

Appendix

Table 4 Participants in the semi-structured interviews
Full size table

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Ceric, A., Krivokapic-Skoko, B. (2016). Applying QCA and Cross-impact Analysis to the Study on ICT Adoption and Use by Croatian SMEs. In: Berger, E., Kuckertz, A. (eds) Complexity in Entrepreneurship, Innovation and Technology Research. FGF Studies in Small Business and Entrepreneurship. Springer, Cham. https://doi.org/10.1007/978-3-319-27108-8_17

Download citation

Publish with us

Policies and ethics

Search

Navigation