Skip to main content
main-content
Top

Hint

Swipe to navigate through the chapters of this book

2018 | OriginalPaper | Chapter

Are Users All the Same? – A Comparative International Analysis of Digital Technology Adoption

Authors: Stefan Hopf, Arnold Picot

Published in: Homo Connectus

Publisher: Springer Fachmedien Wiesbaden

share
SHARE

Abstract

Rapid technological advances have resulted in an array of new digital consumer technologies in the last decade. While there is a continuous uptake in digital technology adoption, certain groups of users are lagging behind, fueling fears of an increasing digital divide. This article attempts to open the “black box” of users by exploring user-centric antecedents of digital technology adoption. Based on an online survey dataset of 7.231 representative Internet users from Germany, Sweden, United States, Brazil, China, and South-Korea, the empirical analysis aims at comparing user-specific demographic, attitudinal and behavioral factors related to digital technology adoption across countries. While we find that users differ significantly in their digital technology adoption among some factors (i.e. age, people in household, education, and being a student or pupil) across countries, we also identify factors with similar impacts across countries (i.e. net income, gender, children in household, and being unemployed). Counteracting tendencies towards an increasing digital divide, this paper pledges for an extensive differentiation of policy measures based on country specific determinants of digital technology adoption. Gaining a better understanding of (dis)similarities among users of digital technologies, these results shall ultimately promote evidence-based business decisions and policymaking.
Footnotes
1
Cf. Srite and Karahanna (2006, pp. 679 ff.).
 
2
Cf. Davis (1985, pp. 2 ff.), and Venkatesh et al. (2003, pp. 425 ff.).
 
3
Cf. Rosenberg (1972, pp. 3 ff.), Caselli and Coleman (2001, pp. 328 ff.), Chinn and Fairlie (2007, pp. 16 ff.), Leidner and Kayworth (2006, pp. 357 ff.), and Srite and Karahanna (2006, pp. 679 ff.).
 
4
Cf. van Dijk and Hacker (2003, pp. 315 ff.), and Porter and Donthu (2006, pp. 999 ff.).
 
5
Cf. Morris and Venkatesh (2000, pp. 375 ff.).
 
6
Cf. Venkatesh and Morris (2000, pp. 115 ff.).
 
7
Cf. Korupp and Szydlik (2005, pp. 409 ff.), and Porter and Donthu (2006, pp. 999 ff.).
 
8
Cf. Wagner and Hanna (1983, pp. 281 ff.), and Korupp and Szydlik (2005, pp. 409 ff.).
 
9
Cf. Belch et al. (1985, pp. 163 ff.), Foxman et al. (1989, pp. 482 ff.), Beatty and Talpade (1994, pp. 332 ff.), and Palan and Wilkes (1997, pp. 159 ff.).
 
10
Cf. Awad and Krishnan (2006, pp. 13 ff.).
 
11
Cf. Chellappa and Sin (2005, pp. 181 ff.), Chellappa and Shivendu (2007, pp. 193 ff.), Bélanger and Crossler (2011, pp. 1017 ff.), and Hong and Thong (2013, pp. 275 ff.).
 
12
Cf. Johnston and Warkentin (2010, pp. 549 ff.).
 
13
Cf. Pavlou et al. (2007, pp. 105 ff.), and Korzaan and Boswell (2008, pp. 15 ff.).
 
14
Cf. Venkatesh (2000, pp. 343 ff.).
 
15
Cf. Münchner Kreis et al. (2011, pp. 1 ff.).
 
16
Chinese survey respondents were exclusively recruited from mega cities with a total population over ten million people.
 
17
Cf. Miller (1981, p. 8).
 
18
The VIFs are lower than 1.66 and indicate no problem of autocorrelation and multicollinearity (cf. Cohen et al. 2003, pp. 423–424).
 
19
Cf. Caselli and Coleman (2001, pp. 328 ff.).
 
20
Cf. Chellappa and Sin (2005, pp. 181 ff.), and Awad and Krishnan (2006, pp. 13 ff.).
 
21
Cf. Davis (1985, pp. 2 ff.), and Legris et al. (2003, pp. 191 ff.).
 
22
Cf. Ajzen (1991, pp. 179 ff.).
 
23
Cf. Ajzen and Fishbein (1980, pp. 1 ff.).
 
24
Cf. Hofstede (1980, pp. 7 ff.).
 
25
Cf. Baldwin and Clark (2000, pp. 1 ff.).
 
26
Cf. Immelt et al. (2009, pp. 56 ff.).
 
27
Percentage of individuals using the Internet in China: 42%, Brazil: 50%, Germany: 84%, South Korea: 84%, Sweden: 94%; cf. ITU (2013).
 
Literature
go back to reference Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. CrossRef Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. CrossRef
go back to reference Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs: Prentice-Hall. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs: Prentice-Hall.
go back to reference Awad, N. F., & Kirshnan, M. S. (2006). The personalization privacy paradox: An empirical evaluation of information transparency and the willingness to be profiled online for personalization. MIS Quaterly, 30(1), 13–28. CrossRef Awad, N. F., & Kirshnan, M. S. (2006). The personalization privacy paradox: An empirical evaluation of information transparency and the willingness to be profiled online for personalization. MIS Quaterly, 30(1), 13–28. CrossRef
go back to reference Baldwin, C. Y. & Clark, K. B. (2000). Design rules: The power of modularity. Cambridge, MIT Press. Baldwin, C. Y. & Clark, K. B. (2000). Design rules: The power of modularity. Cambridge, MIT Press.
go back to reference Beatty, S. E., & Talpade, S. (1994). Adolescent influence in family decision making: A replication with extension. Journal of Consumer Research, 21(2), 332–341. CrossRef Beatty, S. E., & Talpade, S. (1994). Adolescent influence in family decision making: A replication with extension. Journal of Consumer Research, 21(2), 332–341. CrossRef
go back to reference Bélanger, F., & Crossler, R. E. (2011). Privacy in the digital age: A review of information privacy research in information systems. MIS Quaterly, 45(4), 1017–1041. CrossRef Bélanger, F., & Crossler, R. E. (2011). Privacy in the digital age: A review of information privacy research in information systems. MIS Quaterly, 45(4), 1017–1041. CrossRef
go back to reference Belch, G. A., Belch, M. A., & Ceresino, G. (1985). Parental and teenage child influence in family decision making. Journal of Business Research, 13(2), 163–176. CrossRef Belch, G. A., Belch, M. A., & Ceresino, G. (1985). Parental and teenage child influence in family decision making. Journal of Business Research, 13(2), 163–176. CrossRef
go back to reference Caselli, F., & Coleman, W., II. (2011). Cross-country technology diffusion: The case of computers. American Economic Review, 91(2), 328–335. CrossRef Caselli, F., & Coleman, W., II. (2011). Cross-country technology diffusion: The case of computers. American Economic Review, 91(2), 328–335. CrossRef
go back to reference Chellappa, R. K., & Shivendu, S. (2007). An economic model of privacy: A property rights approach to regulatory choices for online personalization. Journal of Management Information Systems, 24(3), 193–225. CrossRef Chellappa, R. K., & Shivendu, S. (2007). An economic model of privacy: A property rights approach to regulatory choices for online personalization. Journal of Management Information Systems, 24(3), 193–225. CrossRef
go back to reference Chellappa, R. K., & Sin, R. G. (2005). Personalization versus privacy: An empirical examination of the online consumer’s dilemma. Information Technology and Management, 6(2), 181–202. CrossRef Chellappa, R. K., & Sin, R. G. (2005). Personalization versus privacy: An empirical examination of the online consumer’s dilemma. Information Technology and Management, 6(2), 181–202. CrossRef
go back to reference Chinn, M., & Fairlie, R. (2007). The determinants of the global digital divide: A cross-country analysis of computer and internet penetration. Oxford Economic Papers, 59(1), 16–44. CrossRef Chinn, M., & Fairlie, R. (2007). The determinants of the global digital divide: A cross-country analysis of computer and internet penetration. Oxford Economic Papers, 59(1), 16–44. CrossRef
go back to reference Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences. Mahwah: Routledge. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences. Mahwah: Routledge.
go back to reference Davis, F. A. (1985). Technology acceptance Model for empirically testing new end-user information systems: Theory and results. Unpublished Ph.D. Dissertation, Massachusetts Institute of Technology, Cambridge. Davis, F. A. (1985). Technology acceptance Model for empirically testing new end-user information systems: Theory and results. Unpublished Ph.D. Dissertation, Massachusetts Institute of Technology, Cambridge.
go back to reference Dijk, J. van, & Hacker, K. (2003). The digital divide as a complex and dynamic phenomenon. The Information Society, 19(4), 315–326. CrossRef Dijk, J. van, & Hacker, K. (2003). The digital divide as a complex and dynamic phenomenon. The Information Society, 19(4), 315–326. CrossRef
go back to reference Foxman, E., Tahsuhaj, P., & Ekstrom, K. M. (1989). Adolescents’ influence in family purchase decisions: A socialization perspective. Journal of Business Research, 15(2), 482–491. Foxman, E., Tahsuhaj, P., & Ekstrom, K. M. (1989). Adolescents’ influence in family purchase decisions: A socialization perspective. Journal of Business Research, 15(2), 482–491.
go back to reference Hofstede, G. (1980). Culture’s consequences: International differences in work – Related values. Newbury Park: Sage. Hofstede, G. (1980). Culture’s consequences: International differences in work – Related values. Newbury Park: Sage.
go back to reference Hong, W., & Thong, J. Y. L. (2013). Internet privacy concerns: An integrated conceptualization and four empirical studies. MIS Quarterly, 37(1), 275–298. CrossRef Hong, W., & Thong, J. Y. L. (2013). Internet privacy concerns: An integrated conceptualization and four empirical studies. MIS Quarterly, 37(1), 275–298. CrossRef
go back to reference Immelt, J. R., Govindarajan, V., & Trimble, C. (2009). How GE is disrupting itself. Harvard Business Review, 87(10), 56–65. Immelt, J. R., Govindarajan, V., & Trimble, C. (2009). How GE is disrupting itself. Harvard Business Review, 87(10), 56–65.
go back to reference Johnston, A. C., & Warkentin, M. (2010). Fear appeals and information security behaviors: An empirical study. MIS Quarterly, 34(3), 549–566. CrossRef Johnston, A. C., & Warkentin, M. (2010). Fear appeals and information security behaviors: An empirical study. MIS Quarterly, 34(3), 549–566. CrossRef
go back to reference Korupp, S. E., & Szydlik, M. (2005). Causes and trends of the digital divide. European Sociological Review, 21(4), 409–422. CrossRef Korupp, S. E., & Szydlik, M. (2005). Causes and trends of the digital divide. European Sociological Review, 21(4), 409–422. CrossRef
go back to reference Korzaan, M. L., & Boswell, K. T. (2008). The influence of personality traits and information privacy concerns on behavioral intentions. The Journal of Computer Information Systems, 48(4), 15–24. Korzaan, M. L., & Boswell, K. T. (2008). The influence of personality traits and information privacy concerns on behavioral intentions. The Journal of Computer Information Systems, 48(4), 15–24.
go back to reference Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 48(3), 191–204. CrossRef Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 48(3), 191–204. CrossRef
go back to reference Leidner, D. E., & Kayworth, T. (2006). Review: A review of culture in information systems research: Toward a theory of information technology culture conflict. MIS Quarterly, 30(2), 357–399. CrossRef Leidner, D. E., & Kayworth, T. (2006). Review: A review of culture in information systems research: Toward a theory of information technology culture conflict. MIS Quarterly, 30(2), 357–399. CrossRef
go back to reference Miller, R. G. Jr. (1981). Simultaneous statistical inference. New York, Springer. Miller, R. G. Jr. (1981). Simultaneous statistical inference. New York, Springer.
go back to reference Morris, M. G., & Venkatesh, V. (2000). Age differences in technology adoptions decisions: Implications for a changing workforce. Personal Psychology, 52(2), 375–403. CrossRef Morris, M. G., & Venkatesh, V. (2000). Age differences in technology adoptions decisions: Implications for a changing workforce. Personal Psychology, 52(2), 375–403. CrossRef
go back to reference Palan, K. M., & Wilkes, R. E. (1997). Adolescent-parent interaction in family decision making. Journal of Consumer Research, 24(2), 159–169. CrossRef Palan, K. M., & Wilkes, R. E. (1997). Adolescent-parent interaction in family decision making. Journal of Consumer Research, 24(2), 159–169. CrossRef
go back to reference Pavlou, P. A., Liang, H., & Xue, Y. (2007). Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. MIS Quarterly, 31(1), 105–136. CrossRef Pavlou, P. A., Liang, H., & Xue, Y. (2007). Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. MIS Quarterly, 31(1), 105–136. CrossRef
go back to reference Porter, C. E., & Donthu, N. (2006). Using the technology acceptance model to explain how attitudes determine internet usage: The role of perceived access barriers and demographics. Journal of Business Research, 59(9), 999–1007. CrossRef Porter, C. E., & Donthu, N. (2006). Using the technology acceptance model to explain how attitudes determine internet usage: The role of perceived access barriers and demographics. Journal of Business Research, 59(9), 999–1007. CrossRef
go back to reference Rosenberg, N. (1972). Factors affecting the diffusion of technology. Explorations in Economic History, 10(1), 3–33. CrossRef Rosenberg, N. (1972). Factors affecting the diffusion of technology. Explorations in Economic History, 10(1), 3–33. CrossRef
go back to reference Srite, M., & Karahanna, E. (2006). The role of espoused national cultural values in technology acceptance. MIS Quarterly, 30(3), 679–704. CrossRef Srite, M., & Karahanna, E. (2006). The role of espoused national cultural values in technology acceptance. MIS Quarterly, 30(3), 679–704. CrossRef
go back to reference Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, and emotion into the Technology Acceptance Model. Information Systems Research, 11(4), 343–365. CrossRef Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, and emotion into the Technology Acceptance Model. Information Systems Research, 11(4), 343–365. CrossRef
go back to reference Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop and ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 21(1), 115–140. CrossRef Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop and ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 21(1), 115–140. CrossRef
go back to reference Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Towards a unified view. MIS Quarterly, 27(3), 425–478. CrossRef Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Towards a unified view. MIS Quarterly, 27(3), 425–478. CrossRef
go back to reference Wagner, J., & Hanna, S. (1983). The effectiveness of family life cycle variables in consumer expenditure research. Journal of Consumer Research, 10(3), 281–291. CrossRef Wagner, J., & Hanna, S. (1983). The effectiveness of family life cycle variables in consumer expenditure research. Journal of Consumer Research, 10(3), 281–291. CrossRef
Metadata
Title
Are Users All the Same? – A Comparative International Analysis of Digital Technology Adoption
Authors
Stefan Hopf
Arnold Picot
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-658-19133-7_5