Utilitarian Value and Hedonic Value of Mobile Service - Focusing on Mobile Addiction

Soon Jae Kwon


Mobile addiction (MA) has become more prevalent nowadays especially with the advancement of mobile services. This study is focus on studying MA in the context of users’ perceived hedonic and utilitarian values. This is done by empirically analysing the moderating effect of MA against three constructs which are users’ perceived hedonic value (PHV), perceived utilitarian value (PUV), perceived usefulness (PU) and fun experienced by using mobile service. A total of 166 participants were involved in the survey. The results showed that only the relationship between perceived hedonic value and fun was not moderated by mobile addiction. Meanwhile, the rest of the hypothesized relationships were supported.


  1. Adams, DA., Nelson, RR, and Todd, PA. (1992) Perceived usefulness, ease of use, and usage of information technology: a replication, MIS Quarterly, 6 (2), 227-247.
  2. Aguinis H and Gottfredson RK (2010) Best-Practice recommendations for estimating interaction effects using moderated regression, Journal of Organizational Behaviour, 31, 776 - 786.
  3. Ajzen I and Fishbein M, Understanding Attitudes and Predicting Social Behavior, New Jersey: Prentice-Hall, Englewood Cliffs; 1980.
  4. Babin BJ, Darden W and Griffin M, (1994) Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value, Journal of Consumer Research, 644-656.
  5. Barclay D, Thompson R and Higgins C, (1995) The Partial Least Squares (PLS) Approach to Causal Modeling: Personal Computer Adoption and Use an Illustration. Technology Studies, 2(2): 285-309.
  6. Bruner II GC and Kumar A, (2005) Explaining Consumer Acceptance of Handled Internet devices, Journal of Business Research, 58: 553-558.
  7. Charlton JP and Danforth IDW, (2007) Distinguishing addiction and high engagement in the context of online game playing, Computers in Human Behavior, 23(3): 1531-1548.
  8. Chin WW, The Partial Least Squares Approach to Structural Equation Modeling. In: Marcoulides GA, editor. Modern Methods for Business Research. NJ: Lawrence Erlbaum, Mahway; 1998. 295-336.
  9. Chin WW, Marcolin BL and Newsted PR, (2003) A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic mail adoption study. Information Systems Research, 14(2), 189-217.
  10. Chiu HC, Hsieh YC, Li YC and Monle L, (2005) Relationship Marketing and Consumer switching behavior, Journal of Business Research, 58, 1681- 1689.
  11. Cohen J., Statistical Power Analysis for the Behavioral Sciences, Lawrence Erlbaum, Hillsdale, NJ, 1988.
  12. Compeau D.R., Higgins C.A. and Huff S., (1999) Social cognitive theory and individual reactions to computing technology: a longitudinal study, MIS Quarterly, 23 (2), 145 - 158.
  13. Davis FD, Bagozzi RP and Warshaw PR, (1992) Extrinsic and intrinsic motivation to use computers in the workplace, Journal of Applied Social Psychology, 22(14), 1111-1132.
  14. Davis FD, (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13(3), 319-340.
  15. Davis FD, Bagozzi RP and Warshaw PR, (1989) User acceptance of computer technology: a comparison of two theoretical models, Management Science, 35(8), 982-1003.
  16. Davis RA, (2001) A cognitive-behavioral model of pathological Internet use, Computers in Human Behavior, 17, 187-195.
  17. Deci E L, Intrinsic Motivation. New York: Plenum Press; 1975.
  18. Fornell C and Bookstein FL, (1982) Two structural equation models: LISREL and PLS applied to consumer exit-voice theory, Journal of Marketing Research, 19, 440-452.
  19. Fornell C and Larcker, D F., (1981) Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, 18 (1), 39 - 50.
  20. Goodhue D, Lewis W and Thompson R, (2003) Statistical power in analyzing interaction effects: Questioning the advantage of PLS with product indicators, Information Systems Research, 18 (2), 211 - 227.
  21. Igbaria M, Parasuraman S and Baroudi JJ, (1996) A motivational model of microcomputer usage, Journal of Management Information Systems, 13(1), 127-143.
  22. Igbaria M, Schiffman SJ and Wieckowshi TS, (1994) The respective roles of perceived usefulness and perceived fun in the acceptance of microcomputer technology, Behavior and Information Technology, 13(6), 349- 361.
  23. Lohmoller JB, (1989) The PLS program system: Latent variables path analysis with partial least squares estimation, Multivariate Behavioral Research, 23(1), 125-127.
  24. Li SM and Chung TM, (2006) Internet function and Internet addictive behavior, Computers in Human Behavior Forthcoming,.
  25. Mathieson K, Peacock F and Chin WW, (2001) Extending the technology acceptance model: The influence of perceived user resources, Data Base Advanced Information Systems, 32(3), 86 - 112.
  26. Mendelson J and Nancy M, The Addictive Personality. New York: Chelsea House; 1986.
  27. O'Guinn TC and Faber RJ, (1989) Compulsive Buying: A Phenomenological Exploration, Journal of Consumer Research, 16, 147-157.
  28. Okada EMJ, (2005) Justification Effects on Consumer Choice of Hedonic and Utilitarian Goods, Journal of Marketing Research, 42, 43-53.
  29. Peter JL and Churchill GA, (1986) Relationships among research design choices and psychometric properties of rating scales: A meta-analysis, Journal of Marketing Research, 23, 1 -10.
  30. Sandelands LE, Asford SJ and Dutton JE, (1983) Reconceptualizing the overjustification effect: a template-matching approach, Motivation and Emotion, 7(3), 229-255.
  31. Terel, O., Serenko, A. and Giles, P., (2011) Integrating Technology Addiction and Use: An Empirical Investigation of Online Auction Users, MIS Quarterly, 35 (4), 1043 - 1061.
  32. Triandis HC, Attitude and Attitude Change. New York: Wiley; 1971.
  33. Venkatesh V, (2000) Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion Into the Technology Acceptance Model, Information Systems Research, 11(4), 342-365.
  34. Voss KE, Spangenberg ER and Grohmann B, (2003) Measuring the Hedonic and Utilitarian Dimensions of Consumer Attitude, Journal of Marketing Research 2003, 40, 310-20.

Paper Citation

in Harvard Style

Jae Kwon S. (2015). Utilitarian Value and Hedonic Value of Mobile Service - Focusing on Mobile Addiction . In Proceedings of the 11th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-106-9, pages 621-626. DOI: 10.5220/0005476106210626

in Bibtex Style

author={Soon Jae Kwon},
title={Utilitarian Value and Hedonic Value of Mobile Service - Focusing on Mobile Addiction},
booktitle={Proceedings of the 11th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},

in EndNote Style

JO - Proceedings of the 11th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Utilitarian Value and Hedonic Value of Mobile Service - Focusing on Mobile Addiction
SN - 978-989-758-106-9
AU - Jae Kwon S.
PY - 2015
SP - 621
EP - 626
DO - 10.5220/0005476106210626