THE EFFECTS OF PERCEIVED BARRIERS AND PERCEIVED ENJOYMENT ON USERS’ INTENTION TO USE 3D PRINTER TECHNOLOGY
Year 2018,
Volume: 8 Issue: 2, 136 - 141, 30.11.2018
Levent Çallı
,
Nihal Sütütemiz
,
Büşra Alma Çallı
Abstract
The main purpose of this study is to investigate the
intention of consumers to use desktop 3D printers with taking into account the
dimensions of perceived barriers and enjoyment. This study contributes to the
early understanding of Turkish consumers’ intention to use desktop 3D printers.
According to the results of the research; the effect of the perceived enjoyment
on intention to use of 3D Printer was positive and the effect of the perceived
barrier on intention to use was negative. When the results are anticipated in
terms of 3D Printer ownership; the perceived enjoyment in user group who have
3D Printer was lower than the group who do not have, whereas risk perceptions
stems from barriers was higher for this group.
References
- Adams, S. (2017). HALF MILLION 3D PRINTERS SOLD IN 2017. Retrieved from https://3dprintingindustry.com/news/half-million-3d-printers-sold-2017-track-100m-sold-2030-131642/
Alliedmarketresearch.com. (2018). World Personal 3D Printers Market - Opportunities and Forecasts, 2017-2023. Retrieved from https://www.alliedmarketresearch.com/personal-3d-printers-market
Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology : A Comparison of Two Theoretical Models Author ( s ): Fred D . Davis , Richard P . Bagozzi and Paul R . Warshaw Published by : INFORMS Stable URL : http://www.jstor.org/stable/2632151 REFERENCES Linked references ar. Management Science, 35(8), 982–1003.
Byrne, B. M. (2010). Structural Equation Modeling with AMOS: Basic Concepts. Applications and Programming.
Calli, L., Balcikanli, C., Calli, F., Cebeci, H. I., & Seymen, O. F. (2013). Identifying factors that contribute to the satisfaction of students in e-learning. Turkish Online Journal of Distance Education, 14(1), 85–101.
Clark, L., Calli, L., & Calli, F. (2014). 3D printing and co-creation of value. 12th International Conference E-Society 2014, (Kharif 2012). Retrieved from http://eprints.port.ac.uk/14538/1/IADIS_Conference_2014_Final.pdf
Davis, F. D. (1989). Perceived Usefulness , Perceived Ease of Use , and User Acceptance of. Management Information System Research Center, 13(3), 319–340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology, 22(14), 1111–1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. American Marketing Association, 18(1), 39–50. https://doi.org/http://www.jstor.org
Hair, J. F., C. Black, W., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis, 7th Edition. Decision Support Systems (Vol. 38). Pearson, London.
Harm-Jan, S., Ulusemre, T., & Xin, F. (2018). Technology Strategy and Developments in Consumer 3D Printers Technology Strategy and Developments in Consumer 3D Printers, (June), 0–15.
Im, I., Kim, Y., & Han, H. J. (2008). The effects of perceived risk and technology type on users’ acceptance of technologies. Information and Management, 45(1), 1–9. https://doi.org/10.1016/j.im.2007.03.005
Leering, R. (2017). Economic and Financial Analysis 3D printing: a threat to global trade. https://doi.org/10.1016/B978-0-12-398358-9.00023-9
Lu, J., Yu, C. S., Liu, C., & Yao, J. E. (2003). Technology acceptance model for wireless Internet. Internet Research, 13(3), 206–222. https://doi.org/10.1108/10662240310478222
Malhotra, N. K. (2004). Marketing Research. Prentice Hall, New Jersey.
Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1–13. https://doi.org/10.1016/j.ijinfomgt.2013.06.002
Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: An extension of the technology acceptance model. Internet Research, 14(3), 224–235. https://doi.org/10.1108/10662240410542652
Ram, S., & Sheth, J. N. (1989). Consumer resistance to innovation: The marketing problem and its solutions. Journal of Consumer Marketing, 6(2), 5–14. https://doi.org/10.1108/EUM0000000002542
Schumacker Randall E, & Richard G.Lomax. (2004). A Beginner’s to Structural Equation Modeling, 2nd ed.
Rayna, T., & Striukova, L. (2016). From rapid prototyping to home fabrication: How 3D printing is changing business model innovation. Technological Forecasting and Social Change, 102, 214–224. https://doi.org/10.1016/j.techfore.2015.07.023
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures. Methods of Psychological Research Online, 8(2), 23–74. https://doi.org/10.1002/0470010940
Schniederjans, D. G. (2017). Adoption of 3D-printing technologies in manufacturing: A survey analysis. International Journal of Production Economics, 183, 287–298. https://doi.org/10.1016/j.ijpe.2016.11.008
Schniederjans, D. G., & Yalcin, M. G. (2018). Perception of 3D-printing: analysis of manufacturing use and adoption. Rapid Prototyping Journal, 24(3), 510–520. https://doi.org/10.1108/RPJ-04-2017-0056
Sun, H., & Zhang, P. (2006). Causal Relationships between Perceived Enjoyment and Perceived Ease of Use: An Alternative Approach. Journal of the Association for Information Systems, 7(9), 618–645. https://doi.org/10.1016/j.chb.2010.06.020
The Economist. (2012). A third industrial revolution. Retrieved from https://www.economist.com/special-report/2012/04/21/a-third-industrial-revolution
Venkatesh, V., Speier, C., & Morris, M. G. (2002). User acceptance enablers in individual decision making about technology: Toward an integrated model. Decision Sciences, 33(2), 297–316. https://doi.org/10.1111/j.15405915.2002.tb01646.x/doi/10.1111/j.15405915.2002.tb01646.x/pdf
Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: The case for an augmented technology acceptance model. Information and Management, 41(6), 747–762. https://doi.org/10.1016/j.im.2003.08.011
Wallenius, V., & Decade, N. (2014). 3D Printing and Retail. Helsinki Metropolia University of Applied Sciences.
Wang, Q., Sun, X., Cobb, S., Lawson, G., & Sharples, S. (2016). 3D printing system: an innovation for small-scale manufacturing in home settings? – early adopters of 3D printing systems in China. International Journal of Production Research, 54(20), 6017–6032. https://doi.org/10.1080/00207543.2016.1154211
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information and Management, 42(5), 719–729. https://doi.org/10.1016/j.im.2004.07.001
Yeh, C. C., & Chen, Y. F. (2018). Critical success factors for adoption of 3D printing. Technological Forecasting and Social Change, 132(June 2017), 209–216. https://doi.org/10.1016/j.techfore.2018.02.003
THE EFFECTS OF PERCEIVED BARRIERS AND PERCEIVED ENJOYMENT ON USERS’ INTENTION TO USE 3D PRINTER TECHNOLOGY
Year 2018,
Volume: 8 Issue: 2, 136 - 141, 30.11.2018
Levent Çallı
,
Nihal Sütütemiz
,
Büşra Alma Çallı
Abstract
The main purpose of this study is to investigate the
intention of consumers to use desktop 3D printers with taking into account the
dimensions of perceived barriers and enjoyment. This study contributes to the
early understanding of Turkish consumers’ intention to use desktop 3D printers.
According to the results of the research; the effect of the perceived enjoyment
on intention to use of 3D Printer was positive and the effect of the perceived
barrier on intention to use was negative. When the results are anticipated in
terms of 3D Printer ownership; the perceived enjoyment in user group who have
3D Printer was lower than the group who do not have, whereas risk perceptions
stems from barriers was higher for this group.
References
- Adams, S. (2017). HALF MILLION 3D PRINTERS SOLD IN 2017. Retrieved from https://3dprintingindustry.com/news/half-million-3d-printers-sold-2017-track-100m-sold-2030-131642/
Alliedmarketresearch.com. (2018). World Personal 3D Printers Market - Opportunities and Forecasts, 2017-2023. Retrieved from https://www.alliedmarketresearch.com/personal-3d-printers-market
Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology : A Comparison of Two Theoretical Models Author ( s ): Fred D . Davis , Richard P . Bagozzi and Paul R . Warshaw Published by : INFORMS Stable URL : http://www.jstor.org/stable/2632151 REFERENCES Linked references ar. Management Science, 35(8), 982–1003.
Byrne, B. M. (2010). Structural Equation Modeling with AMOS: Basic Concepts. Applications and Programming.
Calli, L., Balcikanli, C., Calli, F., Cebeci, H. I., & Seymen, O. F. (2013). Identifying factors that contribute to the satisfaction of students in e-learning. Turkish Online Journal of Distance Education, 14(1), 85–101.
Clark, L., Calli, L., & Calli, F. (2014). 3D printing and co-creation of value. 12th International Conference E-Society 2014, (Kharif 2012). Retrieved from http://eprints.port.ac.uk/14538/1/IADIS_Conference_2014_Final.pdf
Davis, F. D. (1989). Perceived Usefulness , Perceived Ease of Use , and User Acceptance of. Management Information System Research Center, 13(3), 319–340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology, 22(14), 1111–1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. American Marketing Association, 18(1), 39–50. https://doi.org/http://www.jstor.org
Hair, J. F., C. Black, W., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis, 7th Edition. Decision Support Systems (Vol. 38). Pearson, London.
Harm-Jan, S., Ulusemre, T., & Xin, F. (2018). Technology Strategy and Developments in Consumer 3D Printers Technology Strategy and Developments in Consumer 3D Printers, (June), 0–15.
Im, I., Kim, Y., & Han, H. J. (2008). The effects of perceived risk and technology type on users’ acceptance of technologies. Information and Management, 45(1), 1–9. https://doi.org/10.1016/j.im.2007.03.005
Leering, R. (2017). Economic and Financial Analysis 3D printing: a threat to global trade. https://doi.org/10.1016/B978-0-12-398358-9.00023-9
Lu, J., Yu, C. S., Liu, C., & Yao, J. E. (2003). Technology acceptance model for wireless Internet. Internet Research, 13(3), 206–222. https://doi.org/10.1108/10662240310478222
Malhotra, N. K. (2004). Marketing Research. Prentice Hall, New Jersey.
Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1–13. https://doi.org/10.1016/j.ijinfomgt.2013.06.002
Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: An extension of the technology acceptance model. Internet Research, 14(3), 224–235. https://doi.org/10.1108/10662240410542652
Ram, S., & Sheth, J. N. (1989). Consumer resistance to innovation: The marketing problem and its solutions. Journal of Consumer Marketing, 6(2), 5–14. https://doi.org/10.1108/EUM0000000002542
Schumacker Randall E, & Richard G.Lomax. (2004). A Beginner’s to Structural Equation Modeling, 2nd ed.
Rayna, T., & Striukova, L. (2016). From rapid prototyping to home fabrication: How 3D printing is changing business model innovation. Technological Forecasting and Social Change, 102, 214–224. https://doi.org/10.1016/j.techfore.2015.07.023
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures. Methods of Psychological Research Online, 8(2), 23–74. https://doi.org/10.1002/0470010940
Schniederjans, D. G. (2017). Adoption of 3D-printing technologies in manufacturing: A survey analysis. International Journal of Production Economics, 183, 287–298. https://doi.org/10.1016/j.ijpe.2016.11.008
Schniederjans, D. G., & Yalcin, M. G. (2018). Perception of 3D-printing: analysis of manufacturing use and adoption. Rapid Prototyping Journal, 24(3), 510–520. https://doi.org/10.1108/RPJ-04-2017-0056
Sun, H., & Zhang, P. (2006). Causal Relationships between Perceived Enjoyment and Perceived Ease of Use: An Alternative Approach. Journal of the Association for Information Systems, 7(9), 618–645. https://doi.org/10.1016/j.chb.2010.06.020
The Economist. (2012). A third industrial revolution. Retrieved from https://www.economist.com/special-report/2012/04/21/a-third-industrial-revolution
Venkatesh, V., Speier, C., & Morris, M. G. (2002). User acceptance enablers in individual decision making about technology: Toward an integrated model. Decision Sciences, 33(2), 297–316. https://doi.org/10.1111/j.15405915.2002.tb01646.x/doi/10.1111/j.15405915.2002.tb01646.x/pdf
Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: The case for an augmented technology acceptance model. Information and Management, 41(6), 747–762. https://doi.org/10.1016/j.im.2003.08.011
Wallenius, V., & Decade, N. (2014). 3D Printing and Retail. Helsinki Metropolia University of Applied Sciences.
Wang, Q., Sun, X., Cobb, S., Lawson, G., & Sharples, S. (2016). 3D printing system: an innovation for small-scale manufacturing in home settings? – early adopters of 3D printing systems in China. International Journal of Production Research, 54(20), 6017–6032. https://doi.org/10.1080/00207543.2016.1154211
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information and Management, 42(5), 719–729. https://doi.org/10.1016/j.im.2004.07.001
Yeh, C. C., & Chen, Y. F. (2018). Critical success factors for adoption of 3D printing. Technological Forecasting and Social Change, 132(June 2017), 209–216. https://doi.org/10.1016/j.techfore.2018.02.003