Don’t They Know or Don’t They Care?
The Role of Knowledge in Private Disability Insurance Purchase Behavior in Germany
DOI:
https://doi.org/10.61190/nzx8vx70Keywords:
insurance demand, insurance literacy, partial least squares structural equation modeling (PLS-SEM), expert interviews, mixed methodsAbstract
The loss of the ability to work poses substantial financial risks that are often not adequately covered by state benefits. Although private disability insurance (DI) may complement public insurance systems, demand remains comparatively moderate in many countries. Using Germany as an empirical setting, this study examines behavioral factors associated with private DI purchase intentions and purchase behavior. An exploratory sequential mixed methods design is employed. First, semi-structured interviews with financial advisors are conducted to assess the practical relevance of the Theory of Planned Behavior (TPB) and to identify additional salient factors for DI demand emerging from advisory practice. Building on these insights, the study develops a two-layered research model in which TPB serves as a behavioral foundation and qualitative findings inform model extensions. Second, the resulting model is tested using survey data from 323 consumers through partial least squares structural equation modeling (PLS-SEM) and importance-performance map analysis (IPMA). The results confirm the suitability of TPB for explaining private DI demand. Beyond this behavioral baseline, perceived product benefits and risks shape attitudes toward private DI. Furthermore, DI knowledge emerges as an important product-specific dimension of insurance literacy that influences perceived product benefits, perceived product risks, and perceived behavioral control. The study contributes to the literature on insurance demand behavior by integrating DI-specific evaluative and knowledge-related mechanisms into a TPB framework. Furthermore, the findings provide practical implications for improving insurance literacy and supporting informed and needs-appropriate decisions regarding protection against disability-related income loss.
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References
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action Control (pp. 11–39). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-69746-3_2
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Alfiero, S., Battisti, E., & Hadjielias, E. (2022). Black box technology, usage-based insurance, and prediction of purchase behavior: Evidence from the auto insurance sector. Technological Forecasting and Social Change, 183, 121896. https://doi.org/10.1016/j.techfore.2022.121896
Amalia, E., & Arifin, A. Z. (2024). The influence of financial literacy, personal sales, and consumer trust on private health insurance product purchase decisions. International Journal of Application on Economics and Business, 2(1), 2842–2851. https://doi.org/10.24912/ijaeb.v2i1.2842-2851
Atinc, G., Simmering, M. J., & Kroll, M. J. (2012). Control variable use and reporting in macro and micro management research. Organizational Research Methods, 15(1), 57–74. https://doi.org/10.1177/1094428110397773
Autor, D., Duggan, M., & Gruber, J. (2014). Moral hazard and claims deterrence in private disability insurance. American Economic Journal: Applied Economics, 6(4), 110–141. https://doi.org/10.1257/app.6.4.110
Azungah, T. (2018). Qualitative research: Deductive and inductive approaches to data analysis. Qualitative Research Journal, 18(4), 383–400. https://doi.org/10.1108/QRJ-D-18-00035
Bartels, C., Sierminska, E., & Schroeder, C. (2023). Wealth creators or inheritors? Unpacking the gender wealth gap from bottom to top and young to old. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4422891
Bogner, A., & Menz, W. (2009). The theory-generating expert interview: Epistemological interest, forms of knowledge, interaction. In A. Bogner, B. Littig, & W. Menz (Eds.), Interviewing Experts (pp. 43–80). Palgrave Macmillan UK. https://doi.org/10.1057/9780230244276_3
Bongini, P., Cucinelli, D., & Soana, M. G. (2023). Insurance holdings: Does individual insurance literacy matter? Finance Research Letters, 58, 104511. https://doi.org/10.1016/j.frl.2023.104511
Bosnjak, M., Ajzen, I., & Schmidt, P. (2020). The theory of planned behavior: Selected recent advances and applications. Europe’s Journal of Psychology, 16(3), 352–356. https://doi.org/10.5964/ejop.v16i3.3107
Brahmana, R., Brahmana, R. K., & Memarista, G. (2018). Planned behaviour in purchasing health insurance. The South East Asian Journal of Management, 12(1). https://doi.org/10.21002/seam.v12i1.7465
Branley-Bell, D., Gómez, Y., Coventry, L., Vila, J., & Briggs, P. (2021). Developing and validating a behavioural model of cyberinsurance adoption. Sustainability, 13(17), Article 9528. https://doi.org/10.3390/su13179528
Brinkmann, S., & Kvale, S. (2015). InterViews: Learning the craft of qualitative research interviewing (3rd ed.). Sage.
Bryman, A. (2006). Integrating quantitative and qualitative research: How is it done? Qualitative Research, 6(1), 97–113. https://doi.org/10.1177/1468794106058877
Bundesministerium für Finanzen (2025). Überblick bei der Planung der Altersvorsorge – Die Digitale Rentenübersicht. Monatsbericht des BMF April 2025, 31–34.
Carroll, D., Hadjian, A., Collier, N., & McCoy, M. (2024). Disability insurance: The financial planning industry’s great blind spot. Journal of Financial Planning, 36(7), 54–62.
Cenfetelli, R., & Bassellier, G. (2009). Interpretation of formative measurement in information systems research. MIS Quarterly, 33(4), 689–707. https://doi.org/10.2307/20650323
Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Psychology Press. https://doi.org/10.4324/9781410604385
Chin, W. W. (2010). How to write up and report PLS analyses. In V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of Partial Least Squares (pp. 655–690). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-32827-8_29
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). L. Erlbaum Associates. https://doi.org/10.4324/9780203771587
Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE.
De Jonge, P., Ungureanu, O., Zeelenberg, M., & Verlegh, P. W. J. (2024). The acceptability of behavioural interventions in financial decision-making. Behavioural Public Policy, 8(4), 759–772. https://doi.org/10.1017/bpp.2024.10
Destatis. (2025) Bevölkerungsfortschreibung auf Basis Zensus 2022 (EVAS-No. 12411). https://www.statistischebibliothek.de/mir/receive/DEHeft_mods_00156997 (accessed May 30, 2026).
Deutsche Aktuarvereinigung (2021). Berufsunfähigkeit: Die unterschätzte Gefahr?! Aktuar Aktuell, 55, 10–11.
Deutsche Rentenversicherung (2024). Jahresbericht 2023 in Zahlen. https://jahresbericht.deutsche-rentenversicherung.de/artikel/in-zahlen/ (accessed May 30, 2026).
Deutsche Rentenversicherung (2025a). Erwerbsminderungsrente: Das Netz für alle Fälle (20th ed.). https://www.deutsche-rentenversicherung.de/SharedDocs/Downloads/DE/Broschueren/national/erwerbsminderungsrente_das_netz_fuer_alle_faelle.html (accessed May 30, 2026).
Deutsche Rentenversicherung (2025b). Berufsunfähigkeit. https://www.deutsche-rentenversicherung.de/SharedDocs/Glossareintraege/DE/B/berufsunfaehigkeit.html (accessed May 30, 2026).
Dewi, C. S. (2023). The effect of insurance literation, perceived product benefits, trust in insurance & perceived product risk on decision to purchase personal insurance. Jurnal Multidisiplin Madani, 3(6), 1215–1224. https://doi.org/10.55927/mudima.v3i6.3012
Diamantopoulos, A., & Siguaw, J. A. (2006). Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. British Journal of Management, 17(4), 263–282. https://doi.org/10.1111/j.1467-8551.2006.00500.x
Driver, T., Brimble, M., Freudenberg, B., & Hunt, K. H. M. (2018). Insurance literacy in Australia: Not knowing the value of personal insurance. Financial Planning Research Journal, 4, 53–75. https://doi.org/10.2478/fprj-2018-0003
Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149
Fischer, B., Geyer, J. M., & Ziebarth, N. (2024). Fundamentally reforming the DI system: Evidence from German notch cohorts. NBER Working Paper Series. https://doi.org/10.3386/w30812
Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior. Psychology Press. https://doi.org/10.4324/9780203838020
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., & Babin, B. J. (2016). Common methods variance detection in business research. Journal of Business Research, 69(8), 3192–3198. https://doi.org/10.1016/j.jbusres.2015.12.008
Giannikos, C. I., Kakolyris, A., & Suen, T. S. (2024). Risk attitudes and private disability insurance holdings. Journal of Economics and Finance. https://doi.org/10.1007/s12197-024-09689-4
Gough, O., & Nurullah, M. (2009). Understanding what drives the purchase decision in pension and investment products. Journal of Financial Services Marketing, 14(2), 152–172. https://doi.org/10.1057/fsm.2009.14
Greszki, R., Meyer, M., & Schoen, H. (2014). The impact of speeding on data quality in nonprobability and freshly recruited probability‐based online panels. In M. Callegaro, R. Baker, J. Bethlehem, A. S. Göritz, J. A. Krosnick, & P. J. Lavrakas (Eds.), Online Panel Research (1st ed., pp. 238–262). Wiley. https://doi.org/10.1002/9781118763520.ch11
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). SAGE.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Hwang, I. D. (2021). Prospect theory and insurance demand: Empirical evidence on the role of loss aversion. Journal of Behavioral and Experimental Economics, 95, 101764. https://doi.org/10.1016/j.socec.2021.101764
Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information Systems Journal, 28(1), 227–261. https://doi.org/10.1111/isj.12131
Koning, P., & Van Lent, M. (2024). Workers’ moral hazard and private insurer effort in disability insurance. Journal of Risk and Insurance, 91(4), 1049–1088. https://doi.org/10.1111/jori.12464
Lermer, E., Streicher, B., Sachs, R., Raue, M., & Frey, D. (2016). Thinking concretely increases the perceived likelihood of risks: The effect of construal level on risk estimation. Risk Analysis, 36(3), 623–637. https://doi.org/10.1111/risa.12445
Liengaard, B. D., Sharma, P. N., Hult, G. T. M., Jensen, M. B., Sarstedt, M., Hair, J. F., & Ringle, C. M. (2021). Prediction: Coveted, yet forsaken? Introducing a cross‐validated predictive ability test in partial least squares path modeling. Decision Sciences, 52(2), 362–392. https://doi.org/10.1111/deci.12445
Lin, X., Bruhn, A., & William, J. (2019). Extending financial literacy to insurance literacy: A survey approach. Accounting & Finance, 59(S1), 685–713. https://doi.org/10.1111/acfi.12353
Low, H., & Pistaferri, L. (2020). Disability insurance: Theoretical trade‐offs and empirical evidence. Fiscal Studies, 41(1), 129–164. https://doi.org/10.1111/1475-5890.12215
Mai, T. H., Nguyen, T. C., Vu, L. L., Bui, V. H., Nguyen, T. T. C., & Do, D. T. (2020). A study on behaviors of purchasing life insurance in Vietnam. Management Science Letters, 10, 1693–1700. https://doi.org/10.5267/j.msl.2020.1.011
Mamun, A. A., Rahman, M. K., Munikrishnan, U. T., & Permarupan, P. Y. (2021). Predicting the intention and purchase of health insurance among Malaysian working adults. SAGE Open, 11(4), 21582440211061373. https://doi.org/10.1177/21582440211061373
Masud, M. M., Ahsan, M. R., Ismail, N. A., & Rana, M. S. (2021). The underlying drivers of household purchase behaviour of life insurance. Society and Business Review, 16(3), 442–458. https://doi.org/10.1108/SBR-08-2020-0103
Nam, Y., Olsen, E., Loibl, C., & Scharff, R. (2025). Life insurance product type, financial knowledge, and financial adequacy. Financial Planning Review, 8(1), e70000. https://doi.org/10.1002/cfp2.70000
OECD (2022). Disability, work and inclusion: Mainstreaming in all policies and practices. OECD. https://doi.org/10.1787/1eaa5e9c-en
Omar, O. E., & Owusu-Frimpong, N. (2007). Life insurance in Nigeria: An application of the theory of reasoned action to consumers’ attitudes and purchase intention. The Service Industries Journal, 27(7), 963–976. https://doi.org/10.1080/02642060701570891
Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice (4th ed.). SAGE.
Pitthan, F., & De Witte, K. (2021). Puzzles of insurance demand and its biases: A survey on the role of behavioural biases and financial literacy on insurance demand. Journal of Behavioral and Experimental Finance, 30, 100471. https://doi.org/10.1016/j.jbef.2021.100471
Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531–544. https://doi.org/10.1177/014920638601200408
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63(1), 539–569. https://doi.org/10.1146/annurev-psych-120710-100452
Rahimi, S., & Khatooni, M. (2024). Saturation in qualitative research: An evolutionary concept analysis. International Journal of Nursing Studies Advances, 6, 100174. https://doi.org/10.1016/j.ijnsa.2024.100174
Ringle, C. M., & Sarstedt, M. (2016). Gain more insight from your PLS-SEM results: The importance-performance map analysis. Industrial Management & Data Systems, 116(9), 1865–1886. https://doi.org/10.1108/IMDS-10-2015-0449
Ringle, C. M., Wende, S., & Becker, J.-M. (2024). SmartPLS 4. https://www.smartpls.com (accessed May 30, 2026).
Saunders, B., Sim, J., Kingstone, T., Baker, S., Waterfield, J., Bartlam, B., Burroughs, H., & Jinks, C. (2018). Saturation in qualitative research: Exploring its conceptualization and operationalization. Quality & Quantity, 52(4), 1893–1907. https://doi.org/10.1007/s11135-017-0574-8
Scholl, T., & Jeske, K.-J. (2024). Analyse der Einflussfaktoren auf die Risikowahrnehmung und die Kaufentscheidung im Kontext einer Berufsunfähigkeitsversicherung. Zeitschrift für die gesamte Versicherungswissenschaft, 113(2), 181–226. https://doi.org/10.3790/zverswiss.2024.1443301
Scott, J. K., & Finke, M. S. (2013). The demand for disability insurance. Financial Services Review, 22(1), 1–12.
Seibold, A., Seitz, S., & Siegloch, S. (2025). Privatizing disability insurance. Econometrica, 93(5), 1697–1737. https://doi.org/10.3982/ECTA22113
Seitz, S. (2025). Estimating the moral hazard cost of private disability insurance and its welfare consequences (SSRN Scholarly Paper No. 4323015). Social Science Research Network. https://doi.org/10.2139/ssrn.4323015
Sharma, P. N., Liengaard, B. D., Hair, J. F., Sarstedt, M., & Ringle, C. M. (2023). Predictive model assessment and selection in composite-based modeling using PLS-SEM: Extensions and guidelines for using CVPAT. European Journal of Marketing, 57(6), 1662–1677. https://doi.org/10.1108/EJM-08-2020-0636
Sheeran, P. (2002). Intention-behavior relations: A conceptual and empirical review. European Review of Social Psychology, 12(1), 1–36. https://doi.org/10.1080/14792772143000003
Sinnewe, E., & Nicholson, G. (2023). Healthy financial habits in young adults: An exploratory study of the relationship between subjective financial literacy, engagement with finances, and financial decision‐making. Journal of Consumer Affairs, 57(1), 564–592. https://doi.org/10.1111/joca.12512
Soika, S. (2018). Moral hazard and advantageous selection in private disability insurance. The Geneva Papers on Risk and Insurance - Issues and Practice, 43(1), 97–125. https://doi.org/10.1057/s41288-017-0055-2
Streukens, S., Leroi-Werelds, S., & Willems, K. (2017). Dealing with nonlinearity in importance-performance map analysis (IPMA): An integrative framework in a PLS-SEM context. In H. Latan & R. Noonan (Eds.), Partial Least Squares Path Modeling (pp. 367–403). Springer International Publishing. https://doi.org/10.1007/978-3-319-64069-3_17
Tan, K.-L., Leong, C.-M., & Richter, N. F. (2025). Navigating trust in mobile payments: Using necessary condition analysis to identify must-have factors for user acceptance. International Journal of Human–Computer Interaction, 41(5), 3325–3339. https://doi.org/10.1080/10447318.2024.2338319
Tanpoco, M., Katalbas, R. E. I., Roxas, R. R. P., An, J., & Orlina, J. Z. (2022). The moderating role of financial literacy on the effects of subjective norms, product involvement, and perceived behavioral control on investment intention of young investors from a mobile wallet app in the Philippines. International Journal of Multidisciplinary: Applied Business and Education Research, 3(8), 1477–1490. https://doi.org/10.11594/ijmaber.03.08.10
Van der Valk, W., Sumo, R., Dul, J., & Schroeder, R. G. (2016). When are contracts and trust necessary for innovation in buyer-supplier relationships? A necessary condition analysis. Journal of Purchasing and Supply Management, 22(4), 266–277. https://doi.org/10.1016/j.pursup.2016.06.005
VERBI Software (2024). MAXQDA 24. maxqda.com (accessed May 30, 2026).
Von Soest, C. (2023). Why do we speak to experts? Reviving the strength of the expert interview method. Perspectives on Politics, 21(1), 277–287. https://doi.org/10.1017/S1537592722001116
Weedige, S. S., & Ouyang, H. (2019). Consumers’ insurance literacy: Literature review, conceptual definition, and approach for a measurement instrument. European Journal of Business and Management. https://doi.org/10.7176/EJBM/11-26-05
Weedige, S. S., Ouyang, H., Gao, Y., & Liu, Y. (2019). Decision making in personal insurance: Impact of insurance literacy. Sustainability, 11(23), 6795. https://doi.org/10.3390/su11236795
Willis Towers Watson (2022). WTW Studie Lebensversicherung 2021. Willis Towers Watson.
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