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A proposition of an emerging technologies expectations model: an example of student attitudes towards blockchain

Abstract

The paper proposes an Emerging Technologies Expectations Model (ETEM) that aims at explaining the differences in perception of new technologies as well as the expectations towards them. These Expectations, classified into Technology Evolution, Technology Revolution, Social Evolution and Social Revolution are explained by Knowledge and Usage that in turn are shaped by Information Sources. The Information Sources factor, which influences both Expectations and Knowledge, and the Usage factor both play an important role in the model. The application of this model was illustrated using blockchain as an example of an emerging technology, and data from a survey conducted among IT university students in Cracow, Poland. The proposed model contributes to filling the research gap concerning a comprehensive explanation of people’s expectations towards emerging technologies, considering the way people absorb knowledge and undertake the usage of technology based on various information sources. It also provides practical implications, since the knowledge of the factors that can influence people’s expectations towards emerging technologies might be useful in shaping these expectations.


First published online 15 November 2021

Keyword : technology adoption model, emerging technology, blockchain, young people’s expectations, students’ sources of knowledge

How to Cite
Dymek, D., Grabowski, M., & Paliwoda-Pękosz, G. (2022). A proposition of an emerging technologies expectations model: an example of student attitudes towards blockchain. Technological and Economic Development of Economy, 28(1), 101–130. https://doi.org/10.3846/tede.2021.15702
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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: From cognition to behavior (pp. 11–39). Springer. https://doi.org/10.1007/978-3-642-69746-3_2

Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Prentice-Hall, Englewood Cliffs, NJ. https://www.worldcat.org/title/understanding-attitudes-and-predicting-social-behavior/oclc/5726878

Althuizen, N. (2018). Using structural technology acceptance models to segment intended users of a new technology: Propositions and an empirical illustration. Information Systems Journal, 28(5), 879–904.

Auger, P. (2017). Information sources in grey literature. Walter de Gruyter GmbH & co KG. https://doi.org/10.1515/9783110977233

Baker, J. (2012). The technology-organization-environment framework. In Y. Dwivedi, M. Wade, & S. Schneberger (Eds.), Information systems theory: Explaining and predicting our digital society (1st ed., pp. 231–245). Springer. https://www.springer.com/gp/book/9781441961075

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall. Englewood Cliffs, NJ.

Bhattacharyya, S. S., & Nair, S. (2019). Explicating the future of work: Perspectives from India. Journal of Management Development, 38(3), 175–194. https://doi.org/10.1108/JMD-01-2019-0032

Bore, N., Karumba, S., Mutahi, J., Darnell, S. S., Wayua, C., & Weldemariam, K. (2017). Towards blockchain-enabled school information Hub. In ICTD ’17, ACM International Conference Proceeding Series, Part F1320. https://doi.org/10.1145/3136560.3136584

Borrás, S., & Edler, J. (2020). The roles of the state in the governance of socio-technical systems’ transformation. Research Policy, 49(5), 103971. https://doi.org/10.1016/j.respol.2020.103971

Buterin, V. (2014). A next-generation smart contract and decentralized application platform. Ethereum White Paper. Retrieved December 4, 2020, from https://blockchainlab.com/pdf/Ethereum_white_paper-a_next_generation_smart_contract_and_decentralized_application_platform-vitalik-buterin.pdf

Cagnin, C., Keenan, M., Johnston, R., Scapolo, F., & Barré, R. (2008). Future-oriented technology analysis. Strategic intelligence for an innovative economy. Springer-Verlag. https://doi.org/10.1007/978-3-540-68811-2

Chen, L., Xu, L., Shah, N., Gao, Z., Lu, Y., & Shi, W. (2017). On security analysis of proof-of- elapsed-time (PoET). In P. Spirakis & P. Tsigas (Eds.), Lecture notes in computer science: Vol. 10616. Stabilization, safety, and security of distributed systems (pp. 282–297). Springer, Cham. https://doi.org/10.1007/978-3-319-69084-1_19

Churchill Jr, G. A., & Surprenant, C. (1982). An investigation into the determinants of customer satisfaction. Journal of Marketing Research, 19(4), 491–504. https://doi.org/10.1177/002224378201900410

Cohen, W., & Levinthal, D. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152. https://doi.org/10.2307/2393553

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Mana-gement Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982

Dhagarra, D., Goswami, M., Sarma, P. R. S., & Choudhury, A. (2019). Big data and blockchain supported conceptual model for enhanced healthcare coverage. Business Process Management Journal, 25(7), 1612–1632. https://doi.org/10.1108/BPMJ-06-2018-0164

Dymek, D., Grabowski, M., & Paliwoda-Pękosz, G. (2020). Students expectations towards new technologies: A case of blockchain. In AMCIS 2020 Proceedings, 1. https://aisel.aisnet.org/amcis2020/global_dev/global_dev/1

Eccles, J. S., & Wigfield, A. (2020). From expectancy-value theory to situated expectancy-value theory: A developmental, social cognitive, and sociocultural perspective on motivation. Contemporary Educational Psychology, 61, 101859. https://doi.org/10.1016/j.cedpsych.2020.101859

Frizzo-Barker, J., Chow-White, P. A., Adams, P. R., Mentanko, J., Ha, D., & Green, S. (2020). Blockchain as a disruptive technology for busi-ness: A systematic review. International Journal of Information Management, 51, 102029. https://doi.org/10.1016/j.ijinfomgt.2019.10.014

Ghatpande, S., Ouattara, H., Ahmat, D., Sawadogo, Z., & Bissyand, T. F. (2019). Secure, transparent and uniform mobile money for Inter-net-underserved areas using sporadically-synchronized blockchain. In G. Mendy, S. Ouya, I. Dioum, & O. Thiaré (Eds.), Lecture notes of the institute for computer sciences, social informatics and telecommunications engineering: Vol. 275. e-infrastructure and e-services for developing countries (pp. 120–130). Springer. https://doi.org/10.1007/978-3-030-16042-5_12

Halicka, K. (2016). Innovative classification of methods of the Future-oriented Technology Analysis. Technological and Economic Development of Economy, 22(4), 574–597. https://doi.org/10.3846/20294913.2016.1197164

Han, T.-I., & Stoel, L. (2017). Explaining socially responsible consumer behavior: A meta-analytic review of theory of planned behavior. Journal of International Consumer Marketing, 29(2), 91–103. https://doi.org/10.1080/08961530.2016.1251870

Hostettler, S. (2018). From innovation to social impact. In S. Hostettler, S. Najih Besson, & J. C. Bolay (Eds.), Technologies for development. UNESCO 2016 (pp. 3–9). Springer, Cham. https://doi.org/10.1007/978-3-319-91068-0_1

Howcroft, D. (2001). After the Goldrush: Deconstructing the myths of the dot.com market. Journal of Information Technology, 16(4), 195–204. https://doi.org/10.1080/02683960110100418

Iansiti, M., & Lakhani, K. (2017). The truth about blockchain. Harvard Business Review, 95(1), 118–127. https://www.hbs.edu/faculty/Pages/item.aspx?num=52100

IT Governance Institute. (2007). COBIT 4.1. IT Governance Institute. Rolling Meadows. https://www.worldcat.org/title/cobit-41/oclc/807062082

Jakobsson, M., & Juels, A. (1999). Proofs of work and bread pudding protocols (extended abstract). In B. Preneel (Ed.), IFIP – The International Federation for Information Processing: Vol. 23. Secure information networks (pp. 258–272). Springer. https://doi.org/10.1007/978-0-387-35568-9_18

Khan, S. N., Shael, M., & Majdalawieh, M. (2019). Blockchain technology as a support infrastructure in E- Government evolution at Dubai Eco-nomic Department. In Proceedings of the 2019 International Electronics Communication Conference (pp. 124–130). https://doi.org/10.1145/3343147.3343164

Kinai, A., Markus, I., Oduor, E., & Diriye, A. (2017). Asset-based lending via a secure distributed platform. In ICTD ’17, ACM International Conference Proceeding Series, Part F1320 (pp. 17–20). Association for Computing Machinery. https://doi.org/10.1145/3136560.3136594

King, S., & Nadal, S. (2012). PPcoin: Peer-to-peer crypto-currency with proof-of-stake. https://www.chainwhy.top/upload/default/20180619/126a057fef926dc286accb372da46955.pdf

Lai, P. C. (2017). The literature review of technology adoption models and theories for the novelty technology. JISTEM-Journal of Information Systems and Technology Management, 14(1), 21–38. https://www.scielo.br/j/jistm/a/D3NXPz5WF4gQX9cSdLKQv6D/?lang=en&format=pdf

Lee, J. Y., Paik, W., & Joo, S. (2012). Information resource selection of undergraduate students in academic search tasks. Information Research: An International Electronic Journal, 17(1), 511. http://informationr.net/ir/17-1/paper511.html

Lemieux, V. L. (2016). Trusting records: Is blockchain technology the answer? Records Management Journal, 26(2), 110–139. https://doi.org/10.1108/RMJ-12-2015-0042

Lin, C. H., Shih, H. Y., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Mar-keting, 24(7), 641–657. https://doi.org/10.1002/mar.20177

Lowry, P. B., Gaskin, J., & Moody, G. D. (2015). Proposing the multi-motive information systems continuance model (MISC) to better explain end-user system evaluations and continuance intentions. Journal of the Association for Information Systems, 16(7), 515–579. https://doi.org/10.17705/1jais.00403

MacKenzie, D., & Wajcman, J. (Eds.) (1999). The social shaping of technology (2nd ed.). Open University Press. https://www.worldcat.org/title/social-shaping-of-technology/oclc/39713267

Magruk, A. (2011). Innovative classification of technology foresight methods. Technological and Economic Development of Economy, 17(4), 700–715. https://doi.org/10.3846/20294913.2011.649912

Mandel, M. J. (2000, February 14). The risk that boom will turn to bust. Business Week, 3668, 120–122.

Mazambani, L., & Mutambara, E. (2019). Predicting FinTech innovation adoption in South Africa: The case of cryptocurrency. African Journal of Economic and Management Studies, 11(1), 30–50. https://doi.org/10.1108/AJEMS-04-2019-0152

Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org/en/bitcoin-paper

OECD, & SOEC. (1997). Proposed guidelines for collecting and interpreting technological innovation data: Oslo manual. Organisation for Eco-nomic Co-operation and Development & Statistical Office of the European Communities. https://doi.org/10.1787/9789264192263-en

Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469. https://doi.org/10.1177/002224378001700405

Paliwoda-Pękosz, G., Dymek, D., & Grabowski, M. (2021). Adoption of emerging information technologies through the lenses of knowledge acquisition. In AMCIS 2021 Proceedings. https://aisel.aisnet.org/amcis2021/adopt_diffusion/adopt_diffusion/6/

Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307–320. https://doi.org/10.1177/109467050024001

Parasuraman, A., & Colby, C. L. (2015). An updated and streamlined technology readiness index: TRI 2.0. Journal of Service Research, 18(1), 59–74. https://doi.org/10.1177/1094670514539730

Pinch, T. J., & Bijker, W. E. (1984). The social construction of facts and artefacts: Or how the sociology of science and the sociology of technology might benefit each other. Social Studies of Science, 14(3), 399–441. https://doi.org/10.1177/030631284014003004

Ratchford, M., & Barnhart, M. (2012). Development and validation of the technology adoption propensity (TAP) index. Journal of Business Re-search, 65(8), 1209–1215. https://doi.org/10.1016/j.jbusres.2011.07.001

Rayburn, J. D., & Palmgreen, P. (1984). Merging uses and gratifications and expectancy-value theory. Communication Research, 11, 537–562. https://doi.org/10.1177/009365084011004005

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

Rotolo, D., Hicks, D., & Martin, B. R. (2015). What is an emerging technology? Research Policy, 44(10), 1827–1843. https://doi.org/10.1016/j.respol.2015.06.006

Sawyer, S., & Jarrahi, M. H. (2014). Sociotechnical approaches to the study of Information Systems. In H. Topi & A. Tucker (Eds.), Computing handbook: Information systems and information technology (3rd ed., pp. 5-1–5-27). CRC Press. https://doi.org/10.1201/b16768

Schuetz, S., & Venkatesh, V. (2020). Blockchain, adoption, and financial inclusion in India: Research opportunities. International Journal of In-formation Management, 52, 101936. https://doi.org/10.1016/j.ijinfomgt.2019.04.009

Schumpeter, J., & Backhaus, U. (2003). The theory of economic development. In J. Backhaus (Ed.), The European Heritage in Economics and the Social Sciences: Vol. 1. Joseph Alois Schumpeter: Entrepreneurship, style and vision (pp. 61–116). Kluwer Academic Publishers. https://doi.org/10.1007/0-306-48082-4_3

Shin, D. (2019). Blockchain: The emerging technology of digital trust. Telematics and Informatics, 45, 101278. https://doi.org/10.1016/j.tele.2019.101278

Shin, D., & Ibarhine, M. (2020). The socio-technical assemblages of blockchain system: How blockchains are framed and how the framing reflects societal contexts. Digital Policy, Regulation and Governance, 22(3), 245–263. https://doi.org/10.1108/DPRG-11-2019-0095

Shin, D., & Park, Y. J. (2019). Role of fairness, accountability, and transparency in algorithmic affordance. Computers in Human Behavior, 98, 277–284. https://doi.org/10.1016/j.chb.2019.04.019

Silva, F. M., Araujo, E. A., & Moraes, M. B. (2016). Innovation development process in small and medium technology-based companies. RAI Revista de Administração e Inovação, 13, 176–189. https://doi.org/10.1016/j.rai.2016.04.005

Szabo, N. (1997). The idea of smart contracts. Nick Szabo’s Papers and Concise Tutorials. https://www.fon.hum.uva.nl/rob/Courses/InformationInSpeech/CDROM/Literature/LOTwinterschool2006/szabo.best.vwh.net/idea.html

Taherdoost, H. (2018). A review of technology acceptance and adoption models and theories. Procedia Manufacturing, 22, 960–967. https://doi.org/10.1016/j.promfg.2018.03.137

Tholons. (2018). Tholons Services Globalization Index 2018. https://cdn.newswire.com/files/x/24/52/643156aaf14dcb4d5c8cb43d848f.pdf

Tornatzky, L. G., Fleischer, M., & Chakrabarti, A. K. (Eds.). (1990). Processes of technological innovation. Lexington Books.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

Westhuizen, B. van der. (2016). Corporate actions and the need for market efficiency. Journal of Securities Operations & Custody, 8(4), 306–310. https://hstalks.com/article/4465/corporate-actions-and-the-need-for-market-efficien/

Wigfield, A., & Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68–81. https://doi.org/10.1006/ceps.1999.1015

Xu, X., Weber, I., & Staples, M. (2019). Architecture for blockchain applications. Springer, Cham. https://doi.org/10.1007/978-3-030-03035-3