Digital agendas in the insurance industry: the importance of comprehensive approaches

Abstract

With a growing awareness of the potential of innovation provided by digital technology, insurance companies have increasingly adopted digital agendas in their business activities. Our paper studies the relationship between the expression of a digital agenda in annual reports and the business performance of 41 publicly-traded European insurance companies for the time period from 2007 to 2017. Our findings show a positive relationship, which is particularly strong in cases where companies take a comprehensive approach by addressing digital technology both in the context of internal activities within their own organisation and external activities in connection with customers and business partners.

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

Fig. 1

Notes

  1. 1.

    In order to be able to calculate Tobin’s Q, we restrict the data set to publicly-traded insurance companies, and we consider companies that disclosed their full annual reports in English for the respective years.

  2. 2.

    Several approaches were conducted and evaluated; the most suitable results in our case were provided by preprocessing with Ghostscript, plain text extraction via Xpdf, and quantitative text analysis using the programming language R (considered alternatives include, amongst others, PDFBox, RapidMiner, and Tika).

  3. 3.

    Note that we explicitly do not use the common word stem “digit” at this point since it could be misleading.

  4. 4.

    This is done by Porter’s word stemming algorithm via SnowballC (see Bouchet-Valat 2014).

  5. 5.

    The word stems were gained from a content analysis of a subset of the complete data set. In order to avoid individual bias, key words were chosen by different researchers and then comprehensively discussed before a common agreement on the most suitable items was reached.

  6. 6.

    By focusing on the European market, we refrain from dealing with market specifics.

  7. 7.

    For \( d_{i,t}^{binary} \), the effect seems to be positive as well, but could not be statistically confirmed.

  8. 8.

    We also calculated \( d_{i,t}^{c50,ei,binary} \), \( d_{i,t}^{c50,e,binary} \), \( d_{i,t}^{c50,i,binary} \), \( d_{i,t}^{c100,ei,binary} \), \( d_{i,t}^{c100,e,binary} \), and \( d_{i,t}^{c100,i,binary} \).

  9. 9.

    In addition to this, we also use, amongst others, k = “c20,e,binary”, “c50,e,binary”, “c20,i,binary”, “c50,i,binary”, “c50,ei,binary”, and “binary” in the robustness analysis.

  10. 10.

    List of English stop words retrieved from xpo6.com/list-of-english-stop-words.

References

  1. ACORD (Association for Cooperative Operations Research and Development). 2017. Insurance Digital Maturity Study.

  2. Agarwal, R., and H.C. Lucas Jr. 2005. The Information Systems Identity Crisis: Focusing on High-Visibility and High-Impact Research. MIS Quarterly 29 (3): 381–398.

    Article  Google Scholar 

  3. Agarwal, R., G. Gao, C. DesRoches, and A.K. Jha. 2010. Research Commentary: The Digital Transformation of Healthcare: Current Status and the Road Ahead. Information Systems Research 21 (4): 796–809.

    Article  Google Scholar 

  4. Atzori, L., A. Iera, and G. Morabito. 2010. The Internet of Things: A Survey. Computer Networks 54 (15): 2787–2805.

    Article  Google Scholar 

  5. Bardhan, I., V. Krishnan, and S. Lin. 2013. Research Note—Business Value of Information Technology: Testing the Interaction Effect of IT and R&D on Tobin’s Q. Information Systems Research 24 (4): 1147–1161.

    Article  Google Scholar 

  6. Barkur, G., K.V.M. Varambally, and L.R. Rodrigues. 2007. Insurance Sector Dynamics: Towards Transformation into Learning Organization. The Learning Organization 14 (6): 510–523.

    Article  Google Scholar 

  7. Beltratti, A., and G. Corvino. 2008. Why are Insurance Companies Different? The Limits of Convergence among Financial Institutions. The Geneva Papers on Risk and Insurance—Issues and Practice 33 (3): 363–388.

    Article  Google Scholar 

  8. Bohnert, A., N. Gatzert, R.E. Hoyt, and P. Lechner. 2018. The Drivers and Value of Enterprise Risk Management: Evidence from ERM Ratings. European Journal of Finance. https://doi.org/10.1080/1351847X.2018.1514314.

  9. Bouchet-Valat, M. 2014. SnowballC: Snowball Stemmers Based on the C libstemmer UTF-8 Library.

  10. Boudreau, M.C., and D. Robey. 2005. Enacting Integrated Information Technology: A Human Agency Perspective. Organization Science 16 (1): 3–18.

    Article  Google Scholar 

  11. Brettel, M., N. Friederichsen, M. Keller, and M. Rosenberg. 2014. How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective. International Journal of Information and Communication Engineering 8 (1): 37–44.

    Google Scholar 

  12. Brynjolfsson, E., and A. McAfee. 2012. Winning the Race with Ever-Smarter Machines. Management Review 53 (2): 53–60.

    Google Scholar 

  13. Cole, S. 2015. Overcoming Barriers to Microinsurance Adoption: Evidence from the Field. The Geneva Papers on Risk and Insurance—Issues and Practice 40 (4): 720–740.

    Article  Google Scholar 

  14. Desyllas, P., and M. Sako. 2013. Profiting from Business Model Innovation: Evidence from Pay-As-You-Drive Auto Insurance. Research Policy 42 (1): 101–116.

    Article  Google Scholar 

  15. Dhar, V., and A. Sundararajan. 2007. Issues and Opinions: Information Technologies in Business: A Blueprint for Education and Research. Information Systems Research 18 (2): 125–141.

    Article  Google Scholar 

  16. Dumm, R.E., and R.E. Hoyt. 2003. Insurance Distribution Channels: Markets in Transition. Journal of Insurance Regulation 22 (1): 27–47.

    Google Scholar 

  17. Eastman, J.K., A.D. Eastman, and K.L. Eastman. 2002. Insurance Sales Agents and the Internet: The Relationship Between Opinion Leadership, Subjective Knowledge, and Internet Attitudes. Journal of Marketing Management 18 (3–4): 259–285.

    Article  Google Scholar 

  18. Eling, M., and M. Lehmann. 2018. The Impact of Digitalization on the Insurance Value Chain and the Insurability of Risks. The Geneva Papers on Risk and Insurance—Issues and Practice 43 (3): 359–396.

    Article  Google Scholar 

  19. Eling, M., and W. Schnell. 2016. What Do We Know about Cyber Risk and Cyber Risk Insurance? The Journal of Risk Finance 17 (5): 474–491.

    Article  Google Scholar 

  20. Fichman, R.G., B.L. Dos Santos, and Z. Zheng. 2014. Digital Innovation as a Fundamental and Powerful Concept in the Information Systems Curriculum. MIS Quarterly 38 (2): 329–353.

    Article  Google Scholar 

  21. Garven, J.R. 2002. On the Implication of the Internet for Insurance Markets and Institutions. Risk Management and Insurance Review 5 (2): 105–116.

    Article  Google Scholar 

  22. Gehrke, E. 2014. The Insurability Framework Applied to Agricultural Microinsurance: What Do We Know, What Can We Learn? The Geneva Papers on Risk and Insurance—Issues and Practice 39 (2): 264–279.

    Article  Google Scholar 

  23. Gölzer, P., and A. Fritzsche. 2017. Data-driven Operations Management: Organisational Implications of the Digital Transformation in Industrial Practice. Production Planning & Control 28 (16): 1332–1343.

    Article  Google Scholar 

  24. Greene, W.H. 2012. Econometric Analysis, 7th ed. Boston: Pearson.

    Google Scholar 

  25. Gries, S.T., and J. Newman. 2013. Creating and Using Corpora. In Research Methods in Linguistics, ed. R.J. Podesva and D. Sharma, 257–287. Cambridge: Cambridge University Press.

    Google Scholar 

  26. Guo, S., and M.W. Fraser. 2010. Propensity Score Analysis: Statistical Methods and Applications. Thousand Oaks: Sage Publications.

    Google Scholar 

  27. Heckman, J.J. 1978. Dummy Endogenous Variables in a Simultaneous Equation System. Econometrica 46 (4): 931–959.

    Article  Google Scholar 

  28. Heckman, J.J. 1979. Sample Selection Bias as a Specification Error. Econometrica 47 (1): 153–161.

    Google Scholar 

  29. Hess, T., C. Matt, A. Benlian, and F. Wiesböck. 2016. Options for Formulating a Digital Transformation Strategy. MIS Quarterly Executive 15 (2): 123–139.

    Google Scholar 

  30. Hildebrandt, B., A. Hanelt, S. Firk, and L. M. Kolbe. 2015. Entering the Digital Era—The Impact of Digital Technology-related M&As on Business Model Innovations of Automobile OEMs, 36th International Conference on Information Systems, Fort Worth, pp. 1–21.

  31. Hoyt, R.E., and A.P. Liebenberg. 2011. The Value of Enterprise Risk Management. Journal of Risk and Insurance 78 (4): 795–822.

    Article  Google Scholar 

  32. Hylving, L. and U. Schultze. 2013. Evolving the Modular Layered Architecture in Digital Innovation: The Case of the Car’s Instrument Cluster, 34th International Conference on Information Systems, Milan, pp. 1–17.

  33. Imbens, G.W., and J.M. Wooldridge. 2009. Recent Developments in the Econometrics of Program Evaluation. Journal of Economic Literature 47 (1): 5–86.

    Article  Google Scholar 

  34. Insurance Europe. 2016 European Insurance—Key Facts, www.insuranceeurope.eu. Accessed 25 Nov 2016.

  35. Kaiser, T. 2002. The Customer Shall Lead: E-Business Solutions for the New Insurance Industry. The Geneva Papers on Risk and Insurance—Issues and Practice 27 (1): 134–145.

    Article  Google Scholar 

  36. Kohli, R., and S. Devaraj. 2003. Measuring Information Technology Payoff: A Meta-Analysis of Structural Variables in Firm-Level Empirical Research. Information Systems Research 14 (2): 127–145.

    Article  Google Scholar 

  37. Kohli, R., and V. Grover. 2008. Business Value of IT: An Essay on Expanding Research Directions to Keep up with the Times. Journal of the Association for Information Systems 9 (1): 23–39.

    Article  Google Scholar 

  38. Lee, E.A. 2008. Cyber Physical Systems: Design Challenges, Proceedings of the 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing (ISORC), pp. 363–369.

  39. Lee, L.-F. 1978. Unionism and Wage Rates: A Simultaneous Equations Model with Qualitative and Limited Dependent Variables. International Economic Review 19 (2): 415–433.

    Article  Google Scholar 

  40. Legner, C., T. Eymann, T. Hess, C. Matt, T. Böhmann, P. Drews, A. Mädche, N. Urbach, and F. Ahlemann. 2017. Digitalization: Opportunity and Challenge for the Business and Information Systems Engineering Community. Business & Information Systems Engineering 59 (4): 301–308.

    Article  Google Scholar 

  41. Leonardi, P.M. 2011. When Flexible Routines meet Flexible Technologies: Affordance, Constraint, and the Imbrication of Human and Material Agencies. MIS Quarterly 35 (1): 147–167.

    Article  Google Scholar 

  42. Lin, Y., M.-M. Wen, and J. Yu. 2012. Enterprise Risk Management: Strategic Antecedents, Risk Integration, and Performance. North American Actuarial Journal 16 (1): 1–28.

    Article  Google Scholar 

  43. Lindenberg, E.B., and S.A. Ross. 1981. Tobin’s Q Ratio and Industrial Organization. The Journal of Business 54 (1): 1–32.

    Article  Google Scholar 

  44. Lu, Y., and K.R. Ramamurthy. 2011. Understanding the Link between Information Technology Capability and Organizational Agility: An Empirical Examination. MIS Quarterly 35 (4): 931–954.

    Article  Google Scholar 

  45. Lucas, H.C., R. Agarwal, E.K. Clemons, O.A. El Sawy, and B. Weber. 2013. Impactful Research on Transformational Information Technology: An Opportunity to Inform New Audiences. MIS Quarterly 37 (2): 371–382.

    Article  Google Scholar 

  46. Lusch, R.F., and S. Nambisan. 2015. Service Innovation: A Service-dominant Logic Perspective. MIS Quarterly 39 (1): 155–175.

    Article  Google Scholar 

  47. Maddala, G.S. 1983. Limited-Dependent and Qualitative Variables in Econometrics. Cambridge: Cambridge University Press.

    Google Scholar 

  48. Markus, M.L., and D. Robey. 1988. Information Technology and Organizational Change: Causal Structure in Theory and Research. Management Science 34 (5): 583–598.

    Article  Google Scholar 

  49. Markus, M.L. 2004. Technochange Management: Using IT to Drive Organizational Change. Journal of Information Technology 19 (1): 4–20.

    Article  Google Scholar 

  50. Masli, A., V.J. Richardson, J.M. Sanchez, and R.E. Smith. 2011. The Business Value of IT: A Synthesis and Framework of Archival Research. Journal of Information Systems 25 (2): 81–116.

    Article  Google Scholar 

  51. Matt, C., T. Hess, and A. Benlian. 2015. Digital Transformation Strategies. Business & Information Systems Engineering 57 (5): 339–343.

    Article  Google Scholar 

  52. McAfee, A., and E. Brynjolfsson. 2012. Big Data: The Management Revolution. Harvard Business Review 90: 3–9.

    Google Scholar 

  53. Melville, N., K. Kraemer, and V. Gurbaxani. 2004. Review: Information Technology and Organizational Performance: An Integrative Model of IT Business Value. MIS Quarterly 28 (2): 283–322.

    Article  Google Scholar 

  54. Mertens, P., and M. Wiener. 2018. Riding the Digitalization Wave: Toward a Sustainable Nomenclature in Wirtschaftsinformatik. Business & Information Systems Engineering 60 (4): 367–372.

    Article  Google Scholar 

  55. Meyer, S., and G. Krohm. 1999. An Overview of Regulatory Developments of Insurance Transactions on the Internet. Journal of Insurance Regulation 17 (4): 551–554.

    Google Scholar 

  56. Mithas, S., N. Ramasubbu, and V. Sambamurthy. 2011. How Information Management Capability Influences Firm Performance. MIS Quarterly 35 (1): 237–256.

    Article  Google Scholar 

  57. Mithas, S., A. Tafti, I. Bardhan, and J.M. Goh. 2012. Information Technology and Firm Profitability: Mechanisms and Empirical Evidence. MIS Quarterly 36 (1): 205–224.

    Article  Google Scholar 

  58. Nambisan, S., K. Lyytinen, A. Majchrzak, and M. Song. 2017. Digital Innovation Management: Reinventing Innovation Management Research in a Digital World. MIS Quarterly 41 (1): 224.

    Article  Google Scholar 

  59. Nicoletti, B. 2016. Digital Insurance: Business Innovation in the Post-Crisis Era. London: Palgrave MacMillan.

    Google Scholar 

  60. Orlikowski, W.J. 2009. The Sociomateriality of Organisational Life: Considering Technology in Management Research. Cambridge Journal of Economics 34 (1): 125–141.

    Article  Google Scholar 

  61. Pentland, B.T., M.S. Feldman, M.C. Becker, and P. Liu. 2012. Dynamics of Organizational Routines: A Generative Model. Journal of Management Studies 49 (8): 1484–1508.

    Article  Google Scholar 

  62. Porter, M.E., and J.E. Heppelmann. 2014. How Smart Connected Products Are Transforming Competition. Harvard Business Review 92: 3–23.

    Google Scholar 

  63. Riedl, R., A. Benlian, T. Hess, D. Stelzer, and H. Sikora. 2017. On the Relationship between Information Management and Digitalization. Business & Information Systems Engineering 59 (6): 475–482.

    Article  Google Scholar 

  64. Sambamurthy, V., A. Bharadwaj, and V. Grover. 2003. Shaping Agility through Digital Options: Reconceptualizing the Role of Information Technology in Contemporary Firms. MIS Quarterly 27 (2): 237–263.

    Article  Google Scholar 

  65. Salman, S.A. 2014. Contemporary Issues in Takaful (Islamic Insurance). Asian Social Science 10 (22): 210–216.

    Google Scholar 

  66. Saunders, A., and E. Brynjolfsson. 2016. Valuing Information Technology Related Intangible Assets. MIS Quarterly 40 (1): 83–110.

    Article  Google Scholar 

  67. Schmidt, R., M. Möhring, F. Bär, and A. Zimmermann. 2017. The Impact of Digitization on Information System Design—An Explorative Case Study of Digitization in the Insurance Business, Business Information Systems Workshops, pp. 137–149.

  68. Schryen, G. 2013. Revisiting IS Business Value Research: What We Already Know, What We Still Need to Know, and How We Can Get There. European Journal of Information Systems 22 (2): 139–169.

    Article  Google Scholar 

  69. Schulte-Noelle, H. 2001. Technological Changes in IT and Their Influence on Insurance: The Change Ahead (I). The Geneva Papers on Risk and Insurance—Issues and Practice 26 (1): 83–88.

    Article  Google Scholar 

  70. Seitz, M. 2017. Online Insurance Management among German Farmers, The Proceedings of the 17th International Joint Conference Central and Eastern Europe in the Changing Business Environment, pp. 212–220.

  71. Seog, S.H. 2009. Insurance Markets with Differential Information. Journal of Risk and Insurance 76 (2): 279–294.

    Article  Google Scholar 

  72. Skog, D.A., H. Wimelius, and J. Sandberg. 2018. Digital Disruption. Business & Information Systems Engineering 53: 1–7.

    Google Scholar 

  73. Steininger, K., R. Riedl, F. Roithmayr, and P. Mertens. 2009. Fads and Trends in Business and Information Systems Engineering and Information Systems Research–A Comparative Literature Analysis. Business & Information Systems Engineering 1 (6): 411–428.

    Article  Google Scholar 

  74. Svahn, F., O. Henfridsson, and Y. Yoo. 2009. A Threesome Dance of Agency: Mangling the Sociomateriality of Technological Regimes in Digital Innovation, Proceedings of International Conference on Information Systems, Phoenix, pp. 1–18.

  75. Taylor, M. 2001. Technological Changes in IT and Their Influence on Insurance: The Change Ahead (II). The Geneva Papers on Risk and Insurance—Issues and Practice 26 (1): 89–104.

    Article  Google Scholar 

  76. Venkatesh, V., M.G. Morris, G.B. Davis, and F.D. Davis. 2003. User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly 27 (3): 425–478.

    Article  Google Scholar 

  77. Yoo, Y., O. Henfridsson, and K. Lyytinen. 2010. Research Commentary: The New Organizing Logic of Digital Innovation: An Agenda for Information Systems Research. Information Systems Research 21 (4): 724–735.

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Alexander Bohnert.

Additional information

This paper has been granted the 2018 Shin Research Excellence Award—a partnership between The Geneva Association and the International Insurance Society—for its academic quality and relevance by the decision of a panel of judges comprising both business and academic insurance specialists.

Appendix

Appendix

A.1: Treatment-effects model

The treatment-effects model is given by the following two regression equations that are simultaneously estimated via maximum likelihood. We assume \( d_{i,t}^{k} = d_{i,t}^{c20,ei,binary} \) in our base case.Footnote 9 The regression equation (“Q Equation”) is given by

$$ Q_{i,t} = x_{i,t} \beta + d_{i,t}^{k} \delta + \varepsilon_{i,t} $$
(3)

and the selection equation (“Digital Equation”) is defined as

$$ {}^{*}d_{i,t}^{k} = z_{i,t} \gamma + u_{i,t} , $$
(4)

where

$$ d_{i,t}^{k} = \left\{ {\begin{array}{*{20}c} 1 & {{\text{if }}{}^{*}d_{i,t}^{k} > 0} \\ 0 & {\text{otherwise}} \\ \end{array} } \right. $$

and error terms \( \varepsilon_{i,t} \) and ui,t that are assumed to be normally distributed with a mean vector of zero, variances of \( \sigma_{\varepsilon } \) and 1, and a covariance of \( \rho \) (see, e.g. Maddala 1983; Guo and Fraser 2010; Hoyt and Liebenberg 2011; Bohnert et al. 2018).

A.2: Pseudocode

Repeat for each PDF document, i.e. annual report

  • Rename and assign unique identifier (ID) to each PDF document (ID.pdf)

  • Prepare document for text extraction, i.e. remove access restrictions (via Ghostscript)

  • Extract plain text (via Xpdf) and create a text document with identical ID as the PDF document (ID.txt)

Repeat for each plain text document (for all files ID.txt)

  • Create corresponding new (empty) text document for concordances (ID_conc.txt)

  • Translate all characters to lower case characters

  • Wrap all characters that are not alphabetic characters or digits with one space character before and after

  • Replace (multiple) white space characters (including tab keys) and newline with one space character

  • Identify occurrences of words containing the strings “digita” or “digiti”

  • Repeat for each occurrence

    • Extract corresponding keyword string and certain number of words (string wrapped by space characters) before and after the corresponding keyword, i.e. extract concordance of a given length, e.g. 20 words before and 20 words after the keyword in case of c20

    • Add concordance line to ID_conc.txt

    • Repeat for each concordance document (for all files ID_conc.txt)

      • Remove all characters besides alphabetic characters

      • Remove common words from common.listFootnote 10

      • Transform all words into word stems (via Porter’s word stemming algorithm)

      • Set variable d_(i,t)^(c20,e,binary) to 1, if at least one of the following word stems can be found: “channel”, “client”, “custom”, “distribut”, “market”, “online”, “product”, “sale”, “service”

      • set variable to 0 otherwise

      • Set variable d_(i,t)^(c20,i,binary) to 1, if at least one of the following word stems can be found: “board”, “employe”, “group”, “manag”, “model”

      • set variable to 0 otherwise

      • Set variable d_(i,t)^(c20,ei,binary) to 1, if d_(i,t)^(c20,e,binary) == 1 and d_(i,t)^(c20,i,binary) == 1

      • set variable to 0 otherwise

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Bohnert, A., Fritzsche, A. & Gregor, S. Digital agendas in the insurance industry: the importance of comprehensive approaches. Geneva Pap Risk Insur Issues Pract 44, 1–19 (2019). https://doi.org/10.1057/s41288-018-0109-0

Download citation

Keywords

  • Digitalization
  • Firm characteristics
  • Shareholder value
  • Corpus linguistics