Journal of the Korean Society of Clothing and Textiles (한국의류학회지)

The Korean Society of Clothing and Textiles (한국의류학회)
권호 표지
DOI QR코드

DOI QR Code

A Study of Fashion Lifelogging App Adoption -Application of the UTAUT2 Model-

패션 라이프로깅 앱 채택에 관한 연구 -UTAUT2 모델의 적용-

  • Chanhee Kang (Dept. of Fashion and Textiles, Seoul National University) ;
  • Yujeong Won (Dept. of Fashion and Textiles, Seoul National University) ;
  • Hakkyun Kim (Dept. of Global Business Administration, Sungkyunkwan University) ;
  • Yuri Lee (Dept. of Fashion and Textiles, Seoul National University/Research Institute of Human Ecology, Seoul National University)
  • 강찬희 (서울대학교 의류학과) ;
  • 원유정 (서울대학교 의류학과) ;
  • 김학균 (성균관대학교 글로벌경영학과) ;
  • 이유리 (서울대학교 의류학과/서울대학교 생활과학연구소)
  • Received : 2024.05.16
  • Accepted : 2024.08.07
  • Published : 2024.10.31
Download PDF
⟨ Previous Next ⟩

Abstract

This study explores consumer adoption of a fashion lifelogging app (FLA) using the four constructs of the UTAUT2 model. To answer the research questions, empirical data from an online survey was collected, using a sample of participants experienced in using the FLA 'Clothbox', consisting of questions on app usage, UTAUT2 factors, and intentions to use. The study found that utilizing the record feature significantly influenced performance expectancy, effort expectancy, hedonic motivation, and habits. The report feature had a significant effect on performance expectancy. The share feature had a significant effect on social influence. The search feature affected performance expectancy, habits, and social influence. Performance expectancy, effort expectancy, and habits were identified as factors affecting intention to use the FLA. Hedonic motivation and social influence had no significant effect on intention to use the FLA. This research has key significance because it comprises a comprehensive examination of the utility of the UTAUT2 model in determining the influence of UTAUT factors on the adoption of a FLA. The study provides a valuable resource for mobile app developers, planners, and marketers, because it offers insights into how to develop apps that enhance fashion lifelogging experiences for smartphone users.

Keywords

Acknowledgement

본 연구는 강찬희의 서울대학교 대학원 석사학위논문의 일부임.

References

  1. Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Algharabat, R. (2018). Examining factors influencing Jordanian customers' intentions and adoption of internet banking: Extending UTAUT2 with risk. Journal of Retailing and Consumer Services, 40, 125-138. https://doi.org/10.1016/j.jretconser.2017.08.026
  2. Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Williams, M. D. (2016). Consumer adoption of mobile banking in Jordan: Examining the role of usefulness, ease of use, perceived risk, and self-efficacy. Journal of Enterprise Information Management, 29(1), 118-139. https://doi.org/10.1108/JEIM-04-2015-0035
  3. Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418-430. https://doi.org/10.1016/j.chb.2015.04.024
  4. Biniok, P., & Hulsmann, I. (2016). 21st century men and the digital amalgamation of life: A science and technology perspective on lifelogging. In S. Selke (Ed.), Lifelogging: Digital self-tracking and lifelogging-between disruptive technology and cultural transformation (pp. 81-108). Springer. https://doi.org/10.1007/978-3-658-13137-1_5
  5. Brown, S. A., & Venkatesh, V. (2005). A model of adoption of technology in the household: A baseline model test and extension incorporating household life cycle. Management Information Systems Quarterly, 29(3), 11. http://dx.doi.org/10.2307/25148690
  6. Byrne, D., Kelly, L., & Jones, G. J. (2012). Multiple multimodal mobile devices: Lessons learned from engineering lifelog solutions. In P. Alencar, & D. Cowan (Eds.), Handbook of research on mobile software engineering: Design, implementation, and emergent applications (pp. 706-724). IGI Global.
  7. Chen, L., & Holsapple, C. W. (2013). E-business adoption research: State of the art. Journal of Electronic Commerce Research, 14(3), 261.
  8. Cheng, Y., Sharma, S., Sharma, P., & Kulathunga, K. (2020). Role of personalization in continuous use intention of mobile news apps in India: Extending the UTAUT2 model. Information, 11(1), 33. https://doi.org/10.3390/info11010033
  9. Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77(4), 511-535.
  10. Czerwinski, M., Gage, D. W., Gemmell, J., Marshall, C. C., Perez-Quinones, M. A., Skeels, M. M., & Catarci, T. (2006). Digital memories in an era of ubiquitous computing and abundant storage. Communications of the ACM, 49(1), 44-50.
  11. 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
  12. Dhiman, N., Arora, N., Dogra, N., & Gupta, A. (2020). Consumer adoption of smartphone fitness apps: An extended UTAUT2 perspective. Journal of Indian Business Research, 12(3), 363-388. http://dx.doi.org/10.1108/JIBR-05-2018-0158
  13. Dodge, M., & Kitchin, R. (2007). 'Outlines of a world coming into existence': Pervasive computing and the ethics of forgetting. Environment and Planning B: Planning and Design, 34(3), 431-445. http://dx.doi.org/10.1068/b32041t
  14. Doherty, A. R., Caprani, N., Conaire, C. O., Kalnikaite, V., Gurrin, C., Smeaton, A. F., & O'Connor, N. E. (2011). Passively recognizing human activities through lifelogging. Computers in Human Behavior, 27(5), 1948-1958. https://doi.org/10.1016/j.chb.2011.05.002
  15. Fishbein, M., & Ajzen, I. (2005). Theory-based behavior change interventions: Comments on Hobbis and Sutton. Journal of Health Psychology, 10(1), 27-31. https://doi.org/10.1177/1359105305048552
  16. Gurrin, C., Smeaton, A. F., & Doherty, A. R. (2014). Lifelogging: Personal big data. Foundations and Trends® in Information Retrieval, 8(1), 1-125. https://doi.org/10.1561/1500000033
  17. Hew, J.-J., Lee, V.-H., Ooi, K.-B., & Wei, J. (2015). What catalyses mobile apps usage intention: An empirical analysis. Industrial Management & Data Systems, 115(7), 1269-1291. https://doi.org/10.1108/IMDS-01-2015-0028
  18. Huang, C.-Y., & Kao, Y.-S. (2015). UTAUT2 based predictions of factors influencing the technology acceptance of phablets by DNP. Mathematical Problems in Engineering, 2015, 1-23. http://dx.doi.org/10.1155/2015/603747
  19. Jang, B. (2023, July 19). 2023년 한국 성인 스마트폰 사용률 97% [97% of Korean adults using smartphones in 2023]. Civil Rights News. https://www.crnews.co.kr/news/articleView.html?idxno=4653
  20. Jo, H. S. (2023, January 31). Personal digital transformation 2023. CAD & Graphics. https://www.cadgraphics.co.kr/newsview.php?pages=news&sub=news01&catecode=2&num=72211#
  21. Jo, W., Yang, S., Choi, S., Baek, J., Min, M., Lee, Y., Park, K., & Lee, K. (2014). IoT 를 사용한 라이프로그 빅데이터기반 라이프스타일 (생활패턴) 분석 및 웰니스 예측케어 서비스 시스템 [Analysis of lifestyle (life pattern) based on lifelog big data and wellness prediction care service system using IoT]. Journal of the Korean Institute of Communications and Information Sciences (Information and Communications), 31(12), 17-24.
  22. Jung, H. K., & Kim, H. (2022). Lifelogging in the era of the metaverse: Technological challenges and social issues. Journal of the Korea Institute of Spatial Design, 17(1), 155-164. http://doi.org/10.35216/kisd.2022.17.1.155
  23. Jung, J. B., Hur, J. H., Park, H. K., & Shin, B. S. (2018). A study on the acceptance factors and market segmentation of smart devices: Centered on the unified technology acceptance model (UTAUT) and personal innovativeness. Korean Academy of Management Journal, 31(1), 27-47. https://doi.org/10.18032/kaaba.2018.31.1.27
  24. Kang, C., Kim, H., & Lee, Y. (2023, April 22). Functional analysis for the development of fashion life-logging applications [Poster presentation]. Korean Fashion Business Association 2023 Conference, Seoul, Republic of Korea.
  25. Karako, K., Chen, Y., Song, P., & Tang, W. (2019). Super-aged society: Constructing an integrated information platform of self-recording lifelogs and medical records to support health care in Japan. BioScience Trends, 13(3), 276-278. https://doi.org/10.5582/bst.2019.01124
  26. Kelly, K. (2007, February 21). Lifelogging, An Inevitability. The Technium. http://kk.org/thetechnium/2007/02/lifelogging-an/
  27. Ko, J., Shin, J., Ko, E., & Chae, H. (2014). The effects of image contents based fashion brands' SNS toward flow and brand attitude: Focus on pleasure emotion as mediator. Fashion and Textiles Research Journal, 16(6), 908-920. http://dx.doi.org/10.5805/SFTI.2014.16.6.908
  28. Ksibi, A., Alluhaidan, A. S. D., Salhi, A., & El-Rahman, S. A. (2021). Overview of lifelogging: Current challenges and advances. IEEE Access, 9, 62630-62641.
  29. Kwak, S., & Kwon, J. (2016). Funware elements in life-logging applications. Journal of the Korean Society for Computer Game, 29(3), 65-71. http://doi.org/10.22819/kscg.2016.29.3.008
  30. Kwateng, K. O., Atiemo, K. A. O., & Appiah, C. (2018). Acceptance and use of mobile banking: An application of UTAUT2. Journal of Enterprise Information Management, 32(1), 118-151. https://doi.org/10.1108/JEIM-03-2018-0055
  31. Lee, J. O., Whang, J., Kang, S., & Lee, S. (2006). An extended study of the technology acceptance model (TAM) considering functional attributes: A case study of mobile phone adoption. Journal of Information Technology Applications & Management, 13(1), 39-66.
  32. Lee, J. Y., Kim, J. Y., You, S. J., Kim, Y. S., Koo, H. Y., Kim, J. H., Kim, S., Park, J. H., Han, J. S., & Kil, S. (2019). Development and usability of a life-logging behavior monitoring application for obese patients. Journal of Obesity & Metabolic Syndrome, 28(3), 194-202. https://doi.org/10.7570%2Fjomes.2019.28.3.194 https://doi.org/10.7570%2Fjomes.2019.28.3.194
  33. Lee, M. L., & Dey, A. K. (2008, September). Lifelogging memory appliance for people with episodic memory impairment [Paper presentation]. The 10th international conference on Ubiquitous computing. Pittsburgh, United States.
  34. Lee, S. W., Sung, H. J., & Jeon, H. M. (2019). Determinants of continuous intention on food delivery apps: Extending UTAUT2 with information quality. Sustainability, 11(11), 3141. https://doi.org/10.3390/su11113141
  35. Lee, W.-I., & Kim, C.-J. (2021). Delivery apps as new trend: An empirical study of the factors affecting customer continuance intention - Focused on UTAUT, TTF, and ECM. Journal of Cultural Industry, 21(2), 51-63.
  36. Lewin, K. (2013). Principles of topological psychology. Read Books.
  37. Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705-737.
  38. Lu, H.-P., & Yang, Y.-W. (2014). Toward an understanding of the behavioral intention to use a social networking site: An extension of task-technology fit to social-technology fit. Computers in Human Behavior, 34, 323-332. https://doi.org/10.1016/j.chb.2013.10.020
  39. Meditskos, G., Plans, P. M., Stavropoulos, T. G., Benois-Pineau, J., Buso, V., & Kompatsiaris, I. (2018). Multi-modal activity recognition from egocentric vision, semantic enrichment and lifelogging applications for the care of dementia. Journal of Visual Communication and Image Representation, 51, 169-190. https://doi.org/10.1016/j.jvcir.2018.01.009
  40. Melucci, M. (2012). Contextual search: A computational framework. Foundations and Trends® in Information Retrieval, 6(4-5), 257-405. http://dx.doi.org/10.1561/1500000023
  41. Morosan, C., & DeFranco, A. (2016). It's about time: Revisiting UTAUT2 to examine consumers' intentions to use NFC mobile payments in hotels. International Journal of Hospitality Management, 53, 17-29. https://doi.org/10.1016/j.ijhm.2015.11.003
  42. Newcomb, T. M. (1961). The acquaintance process as a prototype of human interaction. Holt, Rinehart & Winston. https://doi.org/10.1037/13156-000
  43. Okumus, B., Ali, F., Bilgihan, A., & Ozturk, A. B. (2018). Psychological factors influencing customers' acceptance of smartphone diet apps when ordering food at restaurants. International Journal of Hospitality Management, 72, 67-77. https://doi.org/10.1016/j.ijhm.2018.01.001
  44. Palau-Saumell, R., Forgas-Coll, S., Sanchez-Garcia, J., & Robres, E. (2019). User acceptance of mobile apps for restaurants: An expanded and extended UTAUT-2. Sustainability, 11(4), 1210. https://doi.org/10.3390/su11041210
  45. Palos-Sanchez, P. R., Correia, M. B., & Saura, J. R. (2019). An empirical examination of adoption of mobile applications in Spain and Portugal, based in UTAUT. International Journal of Mobile Communications, 17(5), 579-603. https://doi.org/10.1504/IJMC.2019.102085
  46. Park, E. J., & Ha, S. J. (2001). Hedonistic motives in apparel buying process. Journal of Global Scholars of Marketing Science, 7, 303-320.
  47. Park, Y., Song, J., Kwon, D., & Chung, D. (2021). Factors affecting users acceptance of voice assistant in vehicles: Focusing on the extended UTAUT model. Innovation Studies, 16(3), 1-43. https://doi.org/10.46251/INNOS.2021.8.16.3.1
  48. Petersen, F., Jacobs, M., & Pather, S. (2020, April 6-8). Barriers for user acceptance of mobile health applications for diabetic patients: applying the UTAUT model [Paper presentation]. Conference on e-Business, e-Services and e-Society, Skukuza, South Africa.
  49. Petroulakis, N. E., Askoxylakis, I. G., & Tryfonas, T. (2012, June 10-15). Life-logging in smart environments: Challenges and security threats [Paper presentation]. 2012 IEEE International Conference on Communications (ICC), Ottawa, Canada.
  50. Rawassizadeh, R., & Tjoa, A. M. (2010, August 20-22). Securing shareable life-logs [Paper presentation]. 2010 IEEE Second International Conference on Social Computing, Minneapolis, United States.
  51. Ristic, D., & Marinkovic, D. (2019). Lifelogging: Digital technologies of the self as the practices of contemporary biopolitics. Sociologija, 61(4), 535-549. http://dx.doi.org/10.2298/SOC1904535R
  52. San Martin, H., & Herrero, A. (2012). Influence of the user's psychological factors on the online purchase intention in rural tourism: Integrating innovativeness to the UTAUT framework. Tourism Management, 33(2), 341-350. https://doi.org/10.1016/j.tourman.2011.04.003
  53. Shepherd, E., & Yeo, G. (2003). Managing records: A handbook of principles and practice. Facet publishing.
  54. Shin, H.-K., Shin, J.-M., & Lee, H. (2011). A study on the factors influencing information sharing in the social network services. Journal of Information Science Theory and Practice, 42(1), 137-156. https://doi.org/10.1633/JIM.2011.42.1.137
  55. Son, H.-J., Lee, S.-W., & Cho, M.-H. (2014). Influential factors of college students' intention to use wearable device: An application of the UTAUT2 model. Korean Journal of Communication & Information, 68(4), 7-33.
  56. Taiwo, A. A., & Downe, A. G. (2013). The theory of user acceptance and use of technology (UTAUT): A meta-analytic review of empirical findings. Journal of Theoretical & Applied Information Technology, 49(1), 48-58.
  57. Tak, P., & Panwar, S. (2017). Using UTAUT 2 model to predict mobile app based shopping: Evidences from India. Journal of Indian Business Research, 9(3), 248-264. http://dx.doi.org/10.1108/JIBR-11-2016-0132
  58. Tam, C., Santos, D., & Oliveira, T. (2020). Exploring the influential factors of continuance intention to use mobile apps: Extending the expectation confirmation model. Information Systems Frontiers, 22, 243-257. https://doi.org/10.1007/s10796-018-9864-5
  59. Tavares, J., & Oliveira, T. (2016). Electronic health record patient portal adoption by health care consumers: An acceptance model and survey. Journal of Medical Internet Research, 18(3), e5069. https://doi.org/10.2196/jmir.5069
  60. Thong, J. Y., Hong, S.-J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human-Computer Studies, 64(9), 799-810. https://doi.org/10.1016/j.ijhcs.2006.05.001
  61. Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695-704. https://doi.org/10.2307/25148660
  62. 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
  63. Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. http://dx.doi.org/10.2307/41410412
  64. Verkijika, S. F. (2018). Factors influencing the adoption of mobile commerce applications in Cameroon. Telematics and Informatics, 35(6), 1665-1674. https://doi.org/10.1016/j.tele.2018.04.012
  65. Verplanken, B., Aarts, H., Van Knippenberg, A., & Moonen, A. (1998). Habit versus planned behaviour: A field experiment. British Journal of Social Psychology, 37(1), 111-128. https://psycnet.apa.org/doi/10.1111/j.2044-8309.1998.tb01160.x
  66. Wang, K.-Y., Ashraf, A. R., Thongpapanl, N. T., & Nguyen, O. (2023). Influence of social augmented reality app usage on customer relationships and continuance intention: The role of shared social experience. Journal of Business Research, 166, 114092. https://doi.org/10.1016/j.jbusres.2023.114092
  67. Wolf, K., Schmidt, A., Bexheti, A., & Langheinrich, M. (2014). Lifelogging: You're wearing a camera. IEEE Pervasive Computing, 13(3), 8-12. https://doi.org/10.1109/MPRV.2014.53
  68. Wong, C.-H., Wei-Han Tan, G., Loke, S.-P., & Ooi, K.-B. (2014). Mobile TV: A new form of entertainment. Industrial Management & Data Systems, 114(7), 1050-1067. https://doi.org/10.1108/IMDS-05-2014-0146
  69. Yen, A. Z., Huang, H. H., & Chen, H. H. (2021, August 21-24). Ten questions in lifelog mining and information recall [Paper presentation]. The 2021 International Conference on Multimedia Retrieval, Taipei, Taiwan.
  70. Yuan, S., Ma, W., Kanthawala, S., & Peng, W. (2015). Keep using my health apps: Discover users' perception of health and fitness apps with the UTAUT2 model. Telemedicine and e-Health, 21(9), 735-741. https://doi.org/10.1089/tmj.2014.0148