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DETERMINING THE FACTORS AFFECTING INVESTORS’ DECISION MAKING PROCESS IN CRYPTOCURRENCY INVESTMENTS

Year 2018, , 5 - 8, 30.12.2018
https://doi.org/10.17261/Pressacademia.2018.970

Abstract

Purpose- The purpose of this study is to determine the factors influencing investors’ decision making on cryptocurrency investments and create investors’ preference partworths by conducting conjoint analysis. In conjoint method, assessment criteria are called as attributes and each attribute has more than one level.

Methodology- In this study, conjoint analysis has been conducted to create investors’ preference partworths. Conjoint method is a statistical method which is conducting a survey-based research design that provides information on respondents’ choices on attributes and their levels for a specific product or an investment option. In the first step, attributes and their levels have been determined, then conjoint bundles, which form the basis of the survey form, were created. As a third step, data collected have been analyzed and preference partworths have been created.

Findings- Data collected for the study have been analyzed by using Marketing Engineering for Excel software. The findings of this preliminary study indicate investors’ priorities in cryptocurrency investments. By assessing these priorities, a highly competing cryptocurrency can be created.

Conclusion- The conjoint analysis gives a clear view on what investors expect from cryptocurrencies and what are their priorities. The results show the attributes and their preferred levels to improve current cryptocurrency types and to develop new ones.

References

  • Chohan, U. (2017). Cryptocurrencies: A Brief Thematic Review. SSRN.
  • D’Alfonso, A., Langer, P., & Vandelis, Z. (2016). The Future of Cryptocurrency.
  • Glaser, F., & Bezzenberger, L. (2015). Beyond Cryptocurrencies - A Taxonomy Of Decentralized Consensus. ECIS. http://doi.org/10.18151/7217326
  • Green, P. E., & Srinivasan, V. (1978). Conjoint Analysis in Consumer Research: Issues and Outlook. Journal of Consumer Research. http://doi.org/10.1086/208721
  • Jiang, Z., & Liang, J. (2018). Cryptocurrency portfolio management with deep reinforcement learning. In 2017 Intelligent Systems Conference, IntelliSys 2017. http://doi.org/10.1109/IntelliSys.2017.8324237
  • Lee, D., Chuen, K., Guo, L., Wang, Y., Chian, L. K., Farell, R., … White, M. (2015). Analysis of the Cryptocurrency Marketplace. Wharton Research Scholars Journal. Paper. http://doi.org/10.3390/fi8040049
  • Marketing Engineering for Excel Conjoint Tutorial (2018)
  • Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. Www.Bitcoin.Org. http://doi.org/10.1007/s10838-008-9062-0
  • Phillip, A., Chan, J., & Peiris, S. (2018). A new look at Cryptocurrencies. Economics Letters. http://doi.org/10.1016/j.econlet.2017.11.020
  • Smith, S.M. & Albaum S.A. (2005) Fundamentals of Marketing Research, Sage Publishing: UK
  • Swan, M. (2015). Blockchain Blueprint for a New Economy. Geriatric Nursing. http://doi.org/10.1017/CBO9781107415324.004
  • Wang, L., & Liu, Y. (2015). Exploring miner evolution in bitcoin network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). http://doi.org/10.1007/978-3-319-15509-8_22
  • White, L. H. (2015). The market for cryptocurrencies. Cato Journal. http://doi.org/10.2139/ssrn.2538290
  • Yli-Huumo, J., Ko, D., Choi, S., Park, S., & Smolander, K. (2016). Where is current research on Blockchain technology? - A systematic review. PLoS ONE. http://doi.org/10.1371/journal.pone.0163477
Year 2018, , 5 - 8, 30.12.2018
https://doi.org/10.17261/Pressacademia.2018.970

Abstract

References

  • Chohan, U. (2017). Cryptocurrencies: A Brief Thematic Review. SSRN.
  • D’Alfonso, A., Langer, P., & Vandelis, Z. (2016). The Future of Cryptocurrency.
  • Glaser, F., & Bezzenberger, L. (2015). Beyond Cryptocurrencies - A Taxonomy Of Decentralized Consensus. ECIS. http://doi.org/10.18151/7217326
  • Green, P. E., & Srinivasan, V. (1978). Conjoint Analysis in Consumer Research: Issues and Outlook. Journal of Consumer Research. http://doi.org/10.1086/208721
  • Jiang, Z., & Liang, J. (2018). Cryptocurrency portfolio management with deep reinforcement learning. In 2017 Intelligent Systems Conference, IntelliSys 2017. http://doi.org/10.1109/IntelliSys.2017.8324237
  • Lee, D., Chuen, K., Guo, L., Wang, Y., Chian, L. K., Farell, R., … White, M. (2015). Analysis of the Cryptocurrency Marketplace. Wharton Research Scholars Journal. Paper. http://doi.org/10.3390/fi8040049
  • Marketing Engineering for Excel Conjoint Tutorial (2018)
  • Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. Www.Bitcoin.Org. http://doi.org/10.1007/s10838-008-9062-0
  • Phillip, A., Chan, J., & Peiris, S. (2018). A new look at Cryptocurrencies. Economics Letters. http://doi.org/10.1016/j.econlet.2017.11.020
  • Smith, S.M. & Albaum S.A. (2005) Fundamentals of Marketing Research, Sage Publishing: UK
  • Swan, M. (2015). Blockchain Blueprint for a New Economy. Geriatric Nursing. http://doi.org/10.1017/CBO9781107415324.004
  • Wang, L., & Liu, Y. (2015). Exploring miner evolution in bitcoin network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). http://doi.org/10.1007/978-3-319-15509-8_22
  • White, L. H. (2015). The market for cryptocurrencies. Cato Journal. http://doi.org/10.2139/ssrn.2538290
  • Yli-Huumo, J., Ko, D., Choi, S., Park, S., & Smolander, K. (2016). Where is current research on Blockchain technology? - A systematic review. PLoS ONE. http://doi.org/10.1371/journal.pone.0163477
There are 14 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Nurgun Komsuoglu Yilmaz 0000-0002-9050-9796

Hulya Boydas Hazar This is me 0000-0002-7115-1899

Publication Date December 30, 2018
Published in Issue Year 2018

Cite

APA Yilmaz, N. K., & Hazar, H. B. (2018). DETERMINING THE FACTORS AFFECTING INVESTORS’ DECISION MAKING PROCESS IN CRYPTOCURRENCY INVESTMENTS. PressAcademia Procedia, 8(1), 5-8. https://doi.org/10.17261/Pressacademia.2018.970
AMA Yilmaz NK, Hazar HB. DETERMINING THE FACTORS AFFECTING INVESTORS’ DECISION MAKING PROCESS IN CRYPTOCURRENCY INVESTMENTS. PAP. December 2018;8(1):5-8. doi:10.17261/Pressacademia.2018.970
Chicago Yilmaz, Nurgun Komsuoglu, and Hulya Boydas Hazar. “DETERMINING THE FACTORS AFFECTING INVESTORS’ DECISION MAKING PROCESS IN CRYPTOCURRENCY INVESTMENTS”. PressAcademia Procedia 8, no. 1 (December 2018): 5-8. https://doi.org/10.17261/Pressacademia.2018.970.
EndNote Yilmaz NK, Hazar HB (December 1, 2018) DETERMINING THE FACTORS AFFECTING INVESTORS’ DECISION MAKING PROCESS IN CRYPTOCURRENCY INVESTMENTS. PressAcademia Procedia 8 1 5–8.
IEEE N. K. Yilmaz and H. B. Hazar, “DETERMINING THE FACTORS AFFECTING INVESTORS’ DECISION MAKING PROCESS IN CRYPTOCURRENCY INVESTMENTS”, PAP, vol. 8, no. 1, pp. 5–8, 2018, doi: 10.17261/Pressacademia.2018.970.
ISNAD Yilmaz, Nurgun Komsuoglu - Hazar, Hulya Boydas. “DETERMINING THE FACTORS AFFECTING INVESTORS’ DECISION MAKING PROCESS IN CRYPTOCURRENCY INVESTMENTS”. PressAcademia Procedia 8/1 (December 2018), 5-8. https://doi.org/10.17261/Pressacademia.2018.970.
JAMA Yilmaz NK, Hazar HB. DETERMINING THE FACTORS AFFECTING INVESTORS’ DECISION MAKING PROCESS IN CRYPTOCURRENCY INVESTMENTS. PAP. 2018;8:5–8.
MLA Yilmaz, Nurgun Komsuoglu and Hulya Boydas Hazar. “DETERMINING THE FACTORS AFFECTING INVESTORS’ DECISION MAKING PROCESS IN CRYPTOCURRENCY INVESTMENTS”. PressAcademia Procedia, vol. 8, no. 1, 2018, pp. 5-8, doi:10.17261/Pressacademia.2018.970.
Vancouver Yilmaz NK, Hazar HB. DETERMINING THE FACTORS AFFECTING INVESTORS’ DECISION MAKING PROCESS IN CRYPTOCURRENCY INVESTMENTS. PAP. 2018;8(1):5-8.

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