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Girişimcilerin Bilişsel Yanlılıklarının Risk Alma Eğilimleri Üzerine Etkisi: PLS-SEM Yöntemi İle Teknoloji Sektöründe Bir Araştırma

Year 2021, , 265 - 284, 30.10.2021
https://doi.org/10.53048/johass.995230

Abstract

Bu araştırmanın amacı, teknoloji sektöründe faaliyet gösteren girişimcilerin ana bilişsel yanlılıklardan olan sonuca atlama yanlılığı ve inanç katılığı yanlılığının risk alma eğilimleri üzerindeki etkisini incelemektir. Araştırmada PLS-SEM analiz yöntemi kullanılmıştır. Teknoloji sektöründe faaliyet gösteren 90 girişimciden veri toplanmıştır. Beklenti teorisinden hareket eden araştırmada sonuca atlama yanlılığı ile inanç katılığı yanlılığının ekonomik, genel ve kariyer bazlı risk alma eğilimleri üzerindeki etkileri sınanmıştır. Sonuca atlama yanlılığının tüm risk alma eğilimleri ile ilişkili olduğu ancak inanç katılığı yanlılığının genel risk alma eğilimi ile ilişkili iken, ekonomik ve kariyer risk alma eğilimi ile ilişkisinin olmadığı bulunmuştur. Bulgular literatür çerçevesinde tartışılmış ve gelecek araştırmalar için önerilerde bulunulmuştur.

References

  • Bishop, S. (2021). Influencer Management Tools: Algorithmic Cultures, Brand Safety, and Bias. Social Media+ Society, 7(1), 1-13.
  • Bosma, N. & Kelley, D. (2019). Global entrepreneurship monitor 2018/2019 Global Report. Global Entrepreneurship Research Association (GERA). https://www.c4e.org.cy/reports/2019/Global_GEM_Report_2018_2019.pdf
  • Buss, D. (2016). The handbook of evolutionary psychology. 5th Edition, John Wiley & Sons.
  • Certo, S. T., Busenbark, J. R., Woo, H. S., & Semadeni, M. (2016). Sample selection bias and Heckman models in strategic management research. Strategic Management Journal, 37(13), 2639-2657.
  • Cheung, E. & Mikels, J. A. (2011). I'm feeling lucky: The relationship between affect and risk-seeking in the framing effect. Emotion, 11(4), 852– 859.
  • Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155-159.
  • Dal Mas, F., Piccolo, D., & Ruzza, D. (2020). Overcoming cognitive bias through intellectual capital management: The case of pediatric medicine. In Intellectual Capital in the Digital Economy (pp. 123-133). Routledge.
  • Dudley, R., Taylor, P., Wickham, S., & Hutton, P. (2016). Psychosis, delusions and the “jumping to conclusions” reasoning bias: a systematic review and meta-analysis. Schizophrenia bulletin, 42(3), 652-665.
  • Florea, D. L. (2015). A theory of consumer's perceived risk under the halo effect. Management & Marketing Journal, 13(1), 205-215.
  • Hair Jr, J. F., Hult, G. T. M., Ringle, C. & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). 2nd ed. Thousand Oaks: Sage publications.
  • Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
  • John Bernardin, H., Thomason, S., Ronald Buckley, M., & Kane, J. S. (2016). Rater rating‐level bias and accuracy in performance appraisals: The impact of rater personality, performance management competence, and rater accountability. Human Resource Management, 55(2), 321-340.
  • Kahneman, D. (2011). Thinking, fast and slow. Macmillan.
  • Keh, H. T., Der Foo, M, & Lim, B. C. (2002). Opportunity evaluation under risky conditions: The cognitive processes of entrepreneurs. Entrepreneurship Theory and Practice, 272, 125-148.
  • Kerr, S. P., Kerr, W. R. & Xu, T. (2018). Personality traits of entrepreneurs: A review of recent literature. Foundations and Trends in Entrepreneurship, 14(3), 279-356.
  • Khan, A. R., Azeem, M., & Sarwar, S. (2017). Impact of Overconfidence and Loss Aversion Biases on Investment Decision: Moderating Role of Risk Perception. International Journal of Transformation in Accounting, Auditing & Taxation [ISSN: 2581-7590 (online)], 1(1).
  • Kim, M., & Daniel, J. L. (2020). Common source bias, key informants, and survey-administrative linked data for nonprofit management research. Public Performance & Management Review, 43(1), 232-256.
  • Koçel, T. (2018). İşletme Yöneticiliği, 17. Basım. İstanbul: Beta Yayınları.
  • Kondylis, F., Mueller, V., Sheriff, G., & Zhu, S. (2016). Do female instructors reduce gender bias in diffusion of sustainable land management techniques? Experimental evidence from Mozambique. World Development, 78, 436-449.
  • Lau, C. K. (2020). Measurement uncertainty and management bias in accounting estimates: the perspective of key audit matters reported by Chinese firms' auditors. Asian Review of Accounting, 29(1), 79-95.
  • Li, J., Liu, M., & Liu, X. (2016). Why do employees resist knowledge management systems? An empirical study from the status quo bias and inertia perspectives. Computers in Human Behavior, 65, 189-200.
  • Li, Z., Sha, Y., Song, X., Yang, K., ZHao, K., Jiang, Z., & Zhang, Q. (2020). Impact of risk perception on customer purchase behavior: a meta-analysis. Journal of Business & Industrial Marketing.
  • Liles, P. R. (1974). Who are entrepreneurs. MSU Business Topics, 22(1), 5-14.
  • Lüdtke, T., Kriston, L., Schröder, J., Lincoln, T. M., & Moritz, S. (2017). Negative affect and a fluctuating jumping to conclusions bias predict subsequent paranoia in daily life: an online experience sampling study. Journal of Behavior Therapy and Experimental Psychiatry, 56, 106-112.
  • Pappas, N. (2016). Marketing strategies, perceived risks, and consumer trust in online buying behaviour. Journal of retailing and consumer services, 29, 92-103.
  • Pereira, M. B., de Freitas, R. S. G., Stedefeldt, E., & da Cunha, D. T. (2021). Conflicts, informality and risk perception about foodborne diseases in small family and non-family run restaurants. Journal of Foodservice Business Research, 1-27.
  • Pope, D. G., Price, J., & Wolfers, J. (2018). Awareness reduces racial bias. Management Science, 64(11), 4988-4995.
  • Prater, J., Kirytopoulos, K., & Ma, T. (2017). Optimism bias within the project management context: A systematic quantitative literature review. International Journal of Managing Projects in Business.
  • Rausch, F., Eisenacher, S., Elkin, H., Englisch, S., Kayser, S., Striepens, N., ... & Wagner, M. (2016). Evaluation of the ‘Jumping to conclusions’ bias in different subgroups of the at-risk mental state: from cognitive basic symptoms to UHR criteria. Psychological Medicine, 46(10), 2071-2081.
  • Ringle, C. M., Wende, S., & Becker, J.-M. (2016). SmartPLS 3. Boenningstedt: SmartPLS GmbH, http://www.smartpls.com.
  • Rossi, M. D. S. C., Stedefeldt, E., da Cunha, D. T., & de Rosso, V. V. (2017). Food safety knowledge, optimistic bias and risk perception among food handlers in institutional food services. Food Control, 73, 681-688.
  • Simon, M., Houghton, S. M. & Aquino, K. (2000). Cognitive biases, risk perception, and venture formation: How individuals decide to start companies. Journal of Business Venturing, 152, 113-134.
  • Sitkin, S. B. & Pablo, A. L. (1992). Reconceptualizing the determinants of risk behavior. Academy of Management Review, 17(1), 9-38.
  • Sitkin, S. B. & Weingart, L. R. (1995). Determinants of risky decision-making behavior: A test of the mediating role of risk perceptions and propensity. Academy of Management Journal, 38(6), 1573-1592.
  • Timuroğlu, M. K. & Çakır, S. (2014). Girişimcilerin yeni bir girişim yapma niyetlerinin risk alma eğilimi ile ilişkisi. Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 16(2), 119-136.
  • Tversky, A. & Kahneman, D. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
  • Van der Gaag, M., Schütz, C., ten Napel, A., Landa, Y., Delespaul, P., Bak, M. & et al. (2013). Development of the Davos assessment of cognitive biases scale (DACOBS). Schizophrenia Research, 144(1-3), 63-71.
  • Ward, T. & Garety, P. A. (2019). Fast and slow thinking in distressing delusions: A review of the literature and implications for targeted therapy. Schizophrenia Research. 203, 80-87.
  • Ward, T., Peters, E., Jackson, M., Day, F. & Garety, P. A. (2018). Data-gathering, belief flexibility, and reasoning across the psychosis continuum. Schizophrenia Bulletin, 44(1), 126-136.
  • Woodward, T. S., Moritz, S., Cuttler, C. & Whitman, J. C. (2006). The contribution of a cognitive bias against disconfirmatory evidence (BADE) to delusions in schizophrenia. Journal of Clinical and Experimental Neuropsychology, 28(4), 605-617.
  • Yılmaz, V., & Kinaş, Y. (2020). Kısmi En Küçük Kareler Yapısal Eşitlik Modellemesiyle Bir Elektrik Dağıtım Şirketinin Hizmet Kalitesinin Araştırılması. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 15(2), 437-456.
  • Yin, R. K. (2017). Case study research and applications: Design and methods. Los Angeles: Sage Publications.
  • Zhang, S. X., & Cueto, J. (2017). The study of bias in entrepreneurship. Entrepreneurship theory and Practice, 41(3), 419-454.

The Impact of Entrepreneurs’ Cognitive Biases on Their Risk-Taking Propensity: A Research in the Technology Sector via Pls-Sem Method

Year 2021, , 265 - 284, 30.10.2021
https://doi.org/10.53048/johass.995230

Abstract

The purpose of this research was to examine the impact of the two main cognitive biases, i.e., jumping to conclusion bias and the belief inflexibility bias, on the entrepreneurs operating in the technology sector in terms of their risk-taking propensities. The participants of this research are 90 entrepreneurs in the technology sector. The PLS-SEM analysis method was used to analyse the data collected within the scope of this research. Based on the prospect theory, this study aimed to test the effects of jumping-to-conclusions bias and belief inflexibility bias on economic, general and career-based risk-taking propensities. It was observed that jumping-to-conclusions bias is associated with all risk-taking propensities, but belief inflexibility bias is only associated with general risk-taking propensity, but not with economic and career risk taking propensities. The findings were discussed within the framework of the literature and suggestions were made for future research.

References

  • Bishop, S. (2021). Influencer Management Tools: Algorithmic Cultures, Brand Safety, and Bias. Social Media+ Society, 7(1), 1-13.
  • Bosma, N. & Kelley, D. (2019). Global entrepreneurship monitor 2018/2019 Global Report. Global Entrepreneurship Research Association (GERA). https://www.c4e.org.cy/reports/2019/Global_GEM_Report_2018_2019.pdf
  • Buss, D. (2016). The handbook of evolutionary psychology. 5th Edition, John Wiley & Sons.
  • Certo, S. T., Busenbark, J. R., Woo, H. S., & Semadeni, M. (2016). Sample selection bias and Heckman models in strategic management research. Strategic Management Journal, 37(13), 2639-2657.
  • Cheung, E. & Mikels, J. A. (2011). I'm feeling lucky: The relationship between affect and risk-seeking in the framing effect. Emotion, 11(4), 852– 859.
  • Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155-159.
  • Dal Mas, F., Piccolo, D., & Ruzza, D. (2020). Overcoming cognitive bias through intellectual capital management: The case of pediatric medicine. In Intellectual Capital in the Digital Economy (pp. 123-133). Routledge.
  • Dudley, R., Taylor, P., Wickham, S., & Hutton, P. (2016). Psychosis, delusions and the “jumping to conclusions” reasoning bias: a systematic review and meta-analysis. Schizophrenia bulletin, 42(3), 652-665.
  • Florea, D. L. (2015). A theory of consumer's perceived risk under the halo effect. Management & Marketing Journal, 13(1), 205-215.
  • Hair Jr, J. F., Hult, G. T. M., Ringle, C. & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). 2nd ed. Thousand Oaks: Sage publications.
  • Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
  • John Bernardin, H., Thomason, S., Ronald Buckley, M., & Kane, J. S. (2016). Rater rating‐level bias and accuracy in performance appraisals: The impact of rater personality, performance management competence, and rater accountability. Human Resource Management, 55(2), 321-340.
  • Kahneman, D. (2011). Thinking, fast and slow. Macmillan.
  • Keh, H. T., Der Foo, M, & Lim, B. C. (2002). Opportunity evaluation under risky conditions: The cognitive processes of entrepreneurs. Entrepreneurship Theory and Practice, 272, 125-148.
  • Kerr, S. P., Kerr, W. R. & Xu, T. (2018). Personality traits of entrepreneurs: A review of recent literature. Foundations and Trends in Entrepreneurship, 14(3), 279-356.
  • Khan, A. R., Azeem, M., & Sarwar, S. (2017). Impact of Overconfidence and Loss Aversion Biases on Investment Decision: Moderating Role of Risk Perception. International Journal of Transformation in Accounting, Auditing & Taxation [ISSN: 2581-7590 (online)], 1(1).
  • Kim, M., & Daniel, J. L. (2020). Common source bias, key informants, and survey-administrative linked data for nonprofit management research. Public Performance & Management Review, 43(1), 232-256.
  • Koçel, T. (2018). İşletme Yöneticiliği, 17. Basım. İstanbul: Beta Yayınları.
  • Kondylis, F., Mueller, V., Sheriff, G., & Zhu, S. (2016). Do female instructors reduce gender bias in diffusion of sustainable land management techniques? Experimental evidence from Mozambique. World Development, 78, 436-449.
  • Lau, C. K. (2020). Measurement uncertainty and management bias in accounting estimates: the perspective of key audit matters reported by Chinese firms' auditors. Asian Review of Accounting, 29(1), 79-95.
  • Li, J., Liu, M., & Liu, X. (2016). Why do employees resist knowledge management systems? An empirical study from the status quo bias and inertia perspectives. Computers in Human Behavior, 65, 189-200.
  • Li, Z., Sha, Y., Song, X., Yang, K., ZHao, K., Jiang, Z., & Zhang, Q. (2020). Impact of risk perception on customer purchase behavior: a meta-analysis. Journal of Business & Industrial Marketing.
  • Liles, P. R. (1974). Who are entrepreneurs. MSU Business Topics, 22(1), 5-14.
  • Lüdtke, T., Kriston, L., Schröder, J., Lincoln, T. M., & Moritz, S. (2017). Negative affect and a fluctuating jumping to conclusions bias predict subsequent paranoia in daily life: an online experience sampling study. Journal of Behavior Therapy and Experimental Psychiatry, 56, 106-112.
  • Pappas, N. (2016). Marketing strategies, perceived risks, and consumer trust in online buying behaviour. Journal of retailing and consumer services, 29, 92-103.
  • Pereira, M. B., de Freitas, R. S. G., Stedefeldt, E., & da Cunha, D. T. (2021). Conflicts, informality and risk perception about foodborne diseases in small family and non-family run restaurants. Journal of Foodservice Business Research, 1-27.
  • Pope, D. G., Price, J., & Wolfers, J. (2018). Awareness reduces racial bias. Management Science, 64(11), 4988-4995.
  • Prater, J., Kirytopoulos, K., & Ma, T. (2017). Optimism bias within the project management context: A systematic quantitative literature review. International Journal of Managing Projects in Business.
  • Rausch, F., Eisenacher, S., Elkin, H., Englisch, S., Kayser, S., Striepens, N., ... & Wagner, M. (2016). Evaluation of the ‘Jumping to conclusions’ bias in different subgroups of the at-risk mental state: from cognitive basic symptoms to UHR criteria. Psychological Medicine, 46(10), 2071-2081.
  • Ringle, C. M., Wende, S., & Becker, J.-M. (2016). SmartPLS 3. Boenningstedt: SmartPLS GmbH, http://www.smartpls.com.
  • Rossi, M. D. S. C., Stedefeldt, E., da Cunha, D. T., & de Rosso, V. V. (2017). Food safety knowledge, optimistic bias and risk perception among food handlers in institutional food services. Food Control, 73, 681-688.
  • Simon, M., Houghton, S. M. & Aquino, K. (2000). Cognitive biases, risk perception, and venture formation: How individuals decide to start companies. Journal of Business Venturing, 152, 113-134.
  • Sitkin, S. B. & Pablo, A. L. (1992). Reconceptualizing the determinants of risk behavior. Academy of Management Review, 17(1), 9-38.
  • Sitkin, S. B. & Weingart, L. R. (1995). Determinants of risky decision-making behavior: A test of the mediating role of risk perceptions and propensity. Academy of Management Journal, 38(6), 1573-1592.
  • Timuroğlu, M. K. & Çakır, S. (2014). Girişimcilerin yeni bir girişim yapma niyetlerinin risk alma eğilimi ile ilişkisi. Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 16(2), 119-136.
  • Tversky, A. & Kahneman, D. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
  • Van der Gaag, M., Schütz, C., ten Napel, A., Landa, Y., Delespaul, P., Bak, M. & et al. (2013). Development of the Davos assessment of cognitive biases scale (DACOBS). Schizophrenia Research, 144(1-3), 63-71.
  • Ward, T. & Garety, P. A. (2019). Fast and slow thinking in distressing delusions: A review of the literature and implications for targeted therapy. Schizophrenia Research. 203, 80-87.
  • Ward, T., Peters, E., Jackson, M., Day, F. & Garety, P. A. (2018). Data-gathering, belief flexibility, and reasoning across the psychosis continuum. Schizophrenia Bulletin, 44(1), 126-136.
  • Woodward, T. S., Moritz, S., Cuttler, C. & Whitman, J. C. (2006). The contribution of a cognitive bias against disconfirmatory evidence (BADE) to delusions in schizophrenia. Journal of Clinical and Experimental Neuropsychology, 28(4), 605-617.
  • Yılmaz, V., & Kinaş, Y. (2020). Kısmi En Küçük Kareler Yapısal Eşitlik Modellemesiyle Bir Elektrik Dağıtım Şirketinin Hizmet Kalitesinin Araştırılması. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 15(2), 437-456.
  • Yin, R. K. (2017). Case study research and applications: Design and methods. Los Angeles: Sage Publications.
  • Zhang, S. X., & Cueto, J. (2017). The study of bias in entrepreneurship. Entrepreneurship theory and Practice, 41(3), 419-454.
There are 43 citations in total.

Details

Primary Language English
Journal Section Research Article
Authors

Muhammed Yasin Sağlam 0000-0001-5564-2404

Yasin Şehitoğlu 0000-0003-0074-6446

Publication Date October 30, 2021
Submission Date September 14, 2021
Acceptance Date October 27, 2021
Published in Issue Year 2021

Cite

APA Sağlam, M. Y., & Şehitoğlu, Y. (2021). The Impact of Entrepreneurs’ Cognitive Biases on Their Risk-Taking Propensity: A Research in the Technology Sector via Pls-Sem Method. Journal of Human and Social Sciences, 4(2), 265-284. https://doi.org/10.53048/johass.995230

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