DOI QR코드

DOI QR Code

기술수용모델을 이용한 외식 O2O 서비스 특성이 고객신념에 미치는 영향 연구

The Effect of Food Online-to-Offline (O2O) Service Characteristics on Customer Beliefs using the Technology Acceptance Model

  • 원준연 (상명대학교 서비스경영학과) ;
  • 강형철 (상명대학교 서비스경영학과) ;
  • 김병용 (수원대학교 호텔관광학부)
  • 투고 : 2017.08.19
  • 심사 : 2017.10.10
  • 발행 : 2017.10.30

초록

As a single-person household emerges as an important consumer group, an Online-to-Offline or Offlineto-Online(O2O) service market is rapidly growing. This study attempted to verify the effects of convenience and webrooming characteristics of O2O service using the Technology Acceptance Model (TAM). The purpose of this study was to investigate the effects of the convenience and webrooming of food O2O service on users' perceived ease of use and perceived usefulness, and the effects of perceived ease of use and perceived usefulness on purchase intention of O2O services. Using a convenience sampling technique, an online survey was conducted through Google survey from April 16 to April 30, 2017 and was distributed to 447 O2O service users. A total of 320 questionnaires were included in the final analysis. The results showed that convenience had a significant effect on users' perceived ease of use as well as perceived usefulness. In addition, users' perceived ease of use had a significant impact on users' perceived usefulness. Finally, both perceived ease of use and perceived usefulness positively affected users' purchase intention of O2O services. These findings suggest that differentiated events, promotions, and store information should be provided when launching O2O service because webrooming is a more important factor in enhancing perceived usefulness than the perceived ease of use.

키워드

참고문헌

  1. 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). Berlin: Springer.
  2. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
  3. Ajzen, I., & Madden, T. J. (1986). Prediction of goal directed behavior: Attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology, 22(5), 453-474. https://doi.org/10.1016/0022-1031(86)90045-4
  4. Boulding, W., Staelin, R., Kalra, A., & Zeithaml, V. (1993). A dynamic process model of service quality: From expectations to behavioral intentions. Journal of Marketing Research, 30(1), 7-27. https://doi.org/10.2307/3172510
  5. Chandon, P., Wansink, B., & Laurent, G. (2000). A benefit congruency framework of sales promotion effectiveness. Journal of Marketing, 64(4), 65-81. https://doi.org/10.1509/jmkg.64.4.65.18071
  6. Chatterjee, P. (2010). Multiple-channel and cross-channel shopping behavior: Role of consumer shopping orientations. Marketing Intelligence and Planning, 28(1), 9-24. https://doi.org/10.1108/02634501011014589
  7. Chi, Y. S., Kang, M. Y., & Choi, J. I. (2016). A study of O2O-commerce consumers' word-of-mouth intentions based on the value-based adoption model: The comparison of Korean and Chinese consumers. Korean Telecommunications Policy Review, 23(4), 81-116.
  8. Chi, Y. S., Kang, M. Y., & Han, K. S. (2015). An empirical study on consumers' discontinuance intentions towards O2O commerce. The Journal of Internet Electronic Commerce Research, 15(4), 223-245.
  9. Choi, S. J. (2013). Determinants of user perceived value and its influence on the usage of smartphone-based mobile commerce : Focusing on service ubiquity and user control. Journal of Society for e-Business Studies, 18(4), 273-299. https://doi.org/10.7838/jsebs.2013.18.4.273
  10. Choi, W. S., & Lee, S. B. (2013). Effects of the external variables of the RFID system for eco-friendly agricultural products on perceived value and behavioral intention: Applying an expanded TAM. Culinary Science & Hospitality Research, 19(2), 149-166. https://doi.org/10.20878/cshr.2013.19.2.011
  11. Choi, W. S., Kim, M. Y., & Lee, S. B. (2013). The effects of the RFID system for eco-agricultural products on trust and behavior intention: Focusing on an expanded technology acceptance model. Culinary Science & Hospitlaity Research, 19(1), 85-102. https://doi.org/10.20878/cshr.2013.19.1.007
  12. Chunxiang, L. (2014). Study on mobile commerce customer based on value adoption. Journal of Applied Sciences, 14(9), 901-909. https://doi.org/10.3923/jas.2014.901.909
  13. Davis, F. (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
  14. Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task-technology fit constructs. Information & Management, 36(1), 9-21. https://doi.org/10.1016/S0378-7206(98)00101-3
  15. Economy Insight (2015. 5. 1). Single family changes a business concept. Retrieved from: http://www.economyinsight.co.kr/
  16. Evans, K.(2012). 43% of U.S. adults participate in showrooming : And they do it at best buy stores most often, a new poll shows. Retrieved from www.internetretailer.com
  17. Eun, Y.R., & Yoo, Y. J. (2016). The effects of foodservice consumer's consumption value and subjective norm of social commerce usage intention. Journal of Contents, 16(10), 130-139.
  18. Fang, L., & Seo, S. S. (2011). A study on effect on the credibility and word-of-mouth intention bycharacters of social commerce. Journal of Korea E․Commerce Research Academy, 12(2), 89-108.
  19. Fishbein, M. (1963). An investigation of the relationship between beliefs about an object and the attitude toward that object. Human Relations, 16, 233-240. https://doi.org/10.1177/001872676301600302
  20. Hahn, S. B., Yoon, J. H., & Kim, J. M. (2014). Extending the technology acceptance model to examine the intention to use tourism applications on smartphone. Korean Journal of Hospitality & Tourism 23(3), 19-40.
  21. Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20(1), 277-319.
  22. Hyun, Y., Kim, Y. L., Nam, J. Y., & Kim, Y. S. (2014). A study on the acceptance attitude of social commerce by food product consumers : Applying extended TAM. Journal of Tourism Sciences, 38(10), 57-79.
  23. Hyundai Research Institute (2013). Consumption trend characteristics after global financial crisis. VIP Report, 527, 1-18.
  24. Igbaria, M., Guimaraes, T., & Davis, G. (1995). Testing the determinants of microcomputer usage via a structural equation model. Journal of Management Information Systems, 11(4), 87-114. https://doi.org/10.1080/07421222.1995.11518061
  25. Jeon, H. M. (2013). The effect of foodservice consumer's perceived risk and value on social commerce usage intention: Focused on the technology acceptance model. Journal of Foodservice Management, 16(6), 199-222.
  26. Jeong H. Y. (2015). The world to open by O2O. Eugene Investment Co. Ltd. 1-100.
  27. Jeong, Y. J., & Song, Y. U. (2016). A study on the factors affecting the intention to use O2O services. Journal of Information Technology Services, 15(4), 125-151.
  28. Jo, M. N., & Cha, J. B. (2017). Consumer attitudes and behavioral intentions on delivery application quality: Focusing on technology acceptance model(TAM). Journal of Tourism Sciences, 41(4), 171-184.
  29. Joo, Y. H. (2010). Multichannel shopping and customer satisfaction : The role of shopping experience and customer-Firm relationship characteristics. Journal of Channel and Retailing, 15(4), 21-60.
  30. Kim, D. K. (2014). Trends and implications of O2O(online-to-offline). Korea Information Society Development Institute. ICT and Media Policy, 26(22), 1-20.
  31. Kim, Y. O. (2016). A study on single person households in Korea. Korean J of Family Social Work, 52, 139-166.
  32. Kim, G. J., Byun, G. I., & Yang, J. M. (2011). A study on the effect of easiness to use the food service related application of smartphone on intentions of use: Focused on the mediation effect of familarity and usefulness. Korean Journal of Hotel Administration, 20(6), 61-81.
  33. Kim, Y. I., Heo, J., & Kim, C. W. (2015). A study concerning expandability of antecedent variable that influence on perceived usefulness and enjoyment to tourism information of smartphone application. Journal of Tourism & Leisure Research, 27(8), 137-157.
  34. Kim, J. Y., Jo, C. H., Jang, S. J., & Yoon, E. J. (2015). 2015 survey on the internet usage. Ministry of Science and ICT & Future Planning, & Korea Internet & Security Agency.
  35. Kim, M. K., & Kim, J. E. (2016). The study on tourism constraints perception and participation intention by motivation on "Travel alone" - Focused on the university students in Daegu-Gyeongbuk Area -. Tourism Research, 41(3), 1-17.
  36. Kim, T. H., & Kim, H. S. (2016). Delivery app understanding and acceptance among food tech customers using the modified technology acceptance model. Journal of Tourism Sciences, 40(5), 127-144.
  37. Lee, H. S., & Im, J. H. (2005). SPSS 12.0 manual. Bubmunsa.
  38. Lee. O. J., & Yang, D. W. (2017). Study on the effect of O2O service quality on user satisfaction and intention of reuse. Journal of Digital Convergence, 15(6), 165-178. https://doi.org/10.14400/JDC.2017.15.6.165
  39. Lee. Y. H., & Jeon, I. O. (2017). The effect of characteristics of ICT-based O2O service on user satisfaction - Focusing on the mediating effect of use safety -. Journal of Digital Convergence, 15(4), 157-169. https://doi.org/10.14400/JDC.2017.15.4.157
  40. Lee, I. S., & Yoon, H. H. (2011). A study on system use activity and acceptance of information technology for food-service employees: Based on ETAM (Extended Technology Acceptance Model). Journal of Foodservice Management Society of Korea, 14(3), 91-111.
  41. Lee, S. J. (2016). A study on formation and evolution of O2O market and its policy issues. Korean Journal of Social Science, 37(2), 25-39.
  42. Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40, 191-204. https://doi.org/10.1016/S0378-7206(01)00143-4
  43. Li, M., Dong, Z. Y., & Chen, X. (2012). Factors influencing consumption experience of mobile commerce : A study from experiential view. Internet Research, 22(2), 120-141. https://doi.org/10.1108/10662241211214539
  44. Lorenzo-Romero, C., Constantinides, E., & Alarcón-del-Amo, M. D. C. (2011). Consumer adoption of social networking sites: implications for theory and practice. Journal of Research. in Interactive Marketing, 5(2/3), 170-188. https://doi.org/10.1108/17505931111187794
  45. Monthly Jungang (2017.3.17.). Take 1.2 billion won '1 economy, market. Retrieved from: http://jmagazine.joins.com/monthly/view/315916
  46. Na, Y. S. (2012). A study on the factors influencing behavioral intention related to beef traceability and TAM. Culinary Science & Hospitality Research, 18(1), 77-90. https://doi.org/10.20878/cshr.2012.18.1.007
  47. Institute for Information & Communications Technology Promotion (IITP) (2014). O2O recent trends. ICT Report.
  48. Nunnally, J. C. (1978). Psychometric theory(2nd ed.). New York, NY : McGraw-Hill.
  49. 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/10.2307/3150499
  50. Park, S. O., & Choi, H. J. (2008). A study on the spending and savings behavior of Korean singles. Consumer Policy & Education Review, 4(2), 33-52.
  51. Ryu, H. S. (2014). O2O commerce trend and suggestions. KT Economic Management Research Institute, Digieco Report, 1-10.
  52. Sarita. (2014). Webrooming vs showrooming. The International Journal of Business and Management, 2(7), 13-15.
  53. Sevitt, D., & Samuel, A. (2013). How pinterest puts people in stores. Harvard Business Review, 91(7/8), 26-27.
  54. Shin, D. H., & Kim, W. Y. (2008). Applying the technology acceptance model and flow theory to cyworld user behavior: implication of the web2.0 user acceptance. Cyber Psychology & Behavior, 11(3), 378-382. https://doi.org/10.1089/cpb.2007.0117
  55. Song, W.G., Im, J. E., & Do, H. Y. (2015). Travel pattern and structure of one-person households. Korea Journal of Tourism Research, 30(6), 193-216.
  56. Spaid, B. I., & Flint, D. J. (2014). The meaning of shopping experiences augmented by mobile internet devices. Journal of Marketing Theory and Practice, 22(1), 73-90. https://doi.org/10.2753/MTP1069-6679220105
  57. Sung, Y. A. (2013). Cluster analysis for the consumption expenditure patterns of one-person households of different age groups. Journal of Consumer Research, 24(3), 157-181.
  58. The China perspective (2013). China's O2O market to see strong growth through 2015. Retrieved from: http://www.thechinaperspective.com/articles/china
  59. Tian, X. F. & Lee, J. H. (2016). A study on continuous use intention of hotel O2O application characteristics in China. Korean Journal of Hospitality & Tourism, 25(7), 35-50.
  60. Venkatesh, V. A. & Davis, F. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Sciences, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
  61. Venkatesh, V., Morris, M., Davis, G., & Davis, F. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
  62. Verhoef, P. C., Neslin, S. A., & Vroomen, B. (2007). Multichannel customer management: Understanding the research-shopper phenomenon. International Journa; of Research in Marketing, 24(2), 129-148. https://doi.org/10.1016/j.ijresmar.2006.11.002
  63. Women's Development Institute (2007). A survey on family consciousness and living conditions of single non-single family households.
  64. Won, J. H., & Chung, J. E. (2015). The segmentation of single-person households based on Sheth's Theory of consumption values. Journal of Consumer Research, 26(1), 73-99.
  65. Woo, M. H., Lee, M. J., & Choi, S. B. (2015). A study on leisure activities and family values of the younger generation in the one-person household: Focusing on comparisons with the younger generation in the multi-person household. Korean Society, 16(1), 201-231.
  66. Wu, T.J., Zhao, R. H., & Tzeng, S. Y. (2015). An empirical research of consumer adoption behavior on catering transformation to mobile O2O. Journal of Interdisciplinary Mathematics, 18(6), 769-788. https://doi.org/10.1080/09720502.2015.1108088
  67. Yeo, Y. K., & Yang, S. J. (2011). Differences in consumption patterns of various household types. Journal of Consumer Research, 12(4), 65-81.
  68. Yoon, J. S. & Park, C. (2014). A content analysis on consumer deception behaviors of internet shopping mall as growing internet shopping, a lot of deceptive behaviors. The Journal of Internet Electronic Commerce Research, 14(3), 15-35.
  69. Yoon, S. J., Kim, J. H., & Kim, N. J. (2017). Structural relationship among perceived risk, trust, impulse buying tendencies and use intention in social commerce context for tourism consumption : Applying a extended technology acceptance model. The Journal of Tourism Studies, 29(1), 147-171. https://doi.org/10.21581/jts.2017.02.29.1.147
  70. Zhang, P., & Moon, H. C. (2017). A study on the effects of O2O commerce characteristics and consumer characteristics on trust, desire and intention to use in China. Korea Trade Reviews, 42(1), 141-163.

피인용 문헌

  1. O2O를 활용한 신선한 농산품 전자상거래의 지속적 사용의도에 관한 연구 vol.10, pp.10, 2019, https://doi.org/10.13106/ijidb.2019.vol10.no10.35
  2. Factors affecting customer intention to use online food delivery services before and during the COVID-19 pandemic vol.48, pp.None, 2021, https://doi.org/10.1016/j.jhtm.2021.08.012