Study about the Positive and Negative Affect on the Continuance Intention of Internet only Bank

금융소비자의 지속사용의도에 영향을 미치는 정적·부적 정서 연구: 인터넷전문은행을 중심으로

  • Kim, Jin A (Graduate School of Management of Technology, Korea University) ;
  • Yoon, Jeewhan (Graduate School of Management of Technology, Korea University)
  • 김진아 (고려대학교 기술경영전문대학원 기술경영학과) ;
  • 윤지환 (고려대학교 기술경영전문대학원 기술경영학과)
  • Received : 2018.11.15
  • Accepted : 2018.12.20
  • Published : 2018.12.28


Internet only Banks in Korea have acquired more than seven million customer base, but most of the accounts are not active. As financial products tend to be similar, customer affect plays more crucial role than service features in continuance intention. The purpose of this research is to study about the impact of positive and negative affect on the continuance intention. The result indicated that positive affect is positively related to continuance intention, and negative affect is negatively related to continuance intention. Also expectation confirmation is positively related to positive affect. The results imply Internet only Banks need to focus on customer's positive affect and expectation confirmation to improve continuance intention.

DJTJBT_2018_v16n12_267_f0001.png 이미지

Fig. 1. Research model

DJTJBT_2018_v16n12_267_f0002.png 이미지

Fig. 2. Result of structural equation modeling

Table 1. Measurement construct and items

DJTJBT_2018_v16n12_267_t0001.png 이미지

Table 2. Sample demographics

DJTJBT_2018_v16n12_267_t0002.png 이미지

Table 3. Exploratory factor analysis of affect

DJTJBT_2018_v16n12_267_t0003.png 이미지

Table 4. Result of confirmatory factor analysis

DJTJBT_2018_v16n12_267_t0004.png 이미지

Table 5. Reliability of scales

DJTJBT_2018_v16n12_267_t0005.png 이미지

Table 6. Model fit of structural equation model

DJTJBT_2018_v16n12_267_t0006.png 이미지

Table 7. Hypothesis test result

DJTJBT_2018_v16n12_267_t0007.png 이미지

Table 8. Result of indirect effect

DJTJBT_2018_v16n12_267_t0008.png 이미지


  1. M. Kotarba. (2018). Digital Transformation of Business Models. Foundation of Management, 10(1), 123-142. DOI : 10.2478/fman-2018-0011.
  2. D. S. Choi. (2011). The Price Decision and Product Sales Approach of Digital Goods. Korean Association of Business Education, 26.2, 465-488.
  3. B. King. (2015). Bank 3.0: Why Banking is No Longer Somewhere You Go But Something You Do. Singapore : John Wiley & Sons Singapore Pte. Ltd.
  4. Y. S. Jeon. (2018). Internet Only Bank Will Transform Korea Financial Services Industry through Competition and Innovation. Financial Services Commission.
  5. S. W. Nam. (2018). A Study on the Determinants of Consumer Trust toward Internet-Only Banks. Journal of Convergence for Information Technology, 8(2), 157-162.
  6. S. W. Nam & E. J. Hong. (2018). Gender Difference on Trust in Internet-Only Banks Using the Multi-Group Path Analysis. Journal of Convergence for Information Technology, 8(3), 99-105.
  7. J. H. Kim. (2017). Trend of Internet only Bank and the Actions of Korean Financial Service Providers. Financial Services Commission.
  8. H. Byun, H. R. Lee & J. H. Kim. (2018. 8.25). 76% of Kakao Bank Account Balance is Zero. Money today.
  9. S. H. Ok & K. T. Hwang. (2017). A Study on the Development of the Korean Internet Banks. Journal of Digital Convergence, 15, 111-126. DOI :
  10. A. Bhattacherjee. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25(3), 351-370. DOI : 10.2307/3250921.
  11. C. H. Kim & W. S. Kang. (2017). The Effects of Product and Customer Characteristics on Product Adoption in Mobile Banking Service - Focused on Mediating Roles of Customer Experience. Journal of Marketing Management Research, 22(4), 1-29.
  12. S. Y. Chun. (2010). An Exploratory Study on Marketing of Financial Services Companies in Korea. Asia Marketing Journal, 2010(07), 111-133.
  13. H. W. Yoo. (2017). A study on the Intellectual Property Rights for the Protection of Financial Instruments. Asia-Pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, 7(3), 1-9. DOI :
  14. J. K. Kim et al. (2004). Study on the Progress of Financial Regulation and Supervision. Seoul : Korea Development Institute.
  15. M. Hogg. (1995). Social Psychology: An Introduction. Englewood Cliffs, NJ : Prentice-Hall.
  16. T. M. Ostrom. (1969). The Relationship between the Affective, Behavioral, and Cognitive Components of Attitude. Journal of Experimental Social Psychology, 5(1), 12-30.
  17. D. Watson & L. A. Clark. (1988). Development and Validation of Brief Measures of Positive and Negative affect: The PANAS Scales. Journal of Personality and Social Psychology, 54(6), 1063-1070.
  18. S. C. Seol, S. G. Jung & W. Y. Choi. (2017). Effects of Fintech User Motivation on User Attitude and Word of Mouth Intention: Focus on a Innovation Resistance Tendency and Type of Message (Rational, Emotional). Management & Information Systems Review, 36(5), 195-222. DOI :
  19. W. Boonsiritomachai & K. Pitchayadejanant. (2017). Determinants Affecting Mobile Banking Adoption by Generation Y Based on The Unified Theory of Acceptance and Use of Technology Model Modified by The Technology Acceptance Model Concept. Kasetsart Journal of Social Sciences, Online. DOI : 10.1016/j.kjss.2017.10.005
  20. I. U. Chon, H. M. Kang, Y. S. Kang & E. H. Lee. (2016). Effects of Failed Financial Services on Negative Emotion and Behavioral Responses. Journal of the Korean Operations Research and Management Science Society, 41(1), 11-19.
  21. O. R. Kong & H. J. Rhee. (2007). Loyal Customers and Their Experiences of Negative Emotions in case of Service Failures: Findings in the Financial Industries. Journal of Consumer Studies, 18(4), 215-235.
  22. J. I. Choi. (2016). Introduction of the Internet only Bank and Development Direction Proposal. Journal of Digital Convergence, 14(9), 139-147. DOI :
  23. H. S. Chang & J. W. Kim. (2016). Fintech 3.0 - Disruption of Financial Industry Paradigm. Samsung Securities.
  24. D. H. Kim, K. W. Eun & G. E. Kim. (2017). Japan Fintech. Meritz Securities.
  25. B. S. Jeon & J. H. Sung. (2017). Internet only Bank, a Storm in a Tea Cup?. eBest Securities.
  26. S. H. Lee & D. W. Lee. (2015). FinTech-Conversions of Finance Industry based on ICT. Journal of the Korea Convergence Society, 6(3), 97-102.
  27. D. H. Cho & H. G. Lee. (2009). The Critical Success Factors of Internet Banks and Considerable Points when Introducing Into Domestic Markets. Journal of the Korea Contents Association, 12(9), 600-612.
  28. J. H. Lee. (2016). Legal Issues on Plan to Introduce Internet Only Banks. Business Law Review, 3(30), 77-106.
  29. J. H. Chung & S. K. Choi. (2017). Consideration of Regulation and Policy Regarding Separation of Banking and Commerce Aiming at Vitalizing Internet Primary Bank. Soongsil Law Review, 1(37), 215-245.
  30. S. H. Kim & D. K. Park. (2017). Acceptance Factors of Financial Consumers on Internet Primary Banks. Journal of Industrial Economics and Business, 17(4), 589-622. DOI : 10.22558/jieb.2017.
  31. D. W. Kim & S. C. Kim. (2017). Factors to Influence Switching Intention to Internet only Bank from Legacy Bank: Focused on Financial Consumers' Asset Management. Information Society & Media, 4(18), 105-134.
  32. H. J. Kim & J. Y. Rha. (2018). Consumers' Adoption Resistance of Branchless Bank: Non-Users Perspective. Journal of Consumer Studies, 29(4), 97-117.
  33. Y. H. Moon. (2017). Factors Affecting Intention to Use Internet Primary Bank: An Exploratory Difference of Demographic Characteristics. The Journal of Business Education, 3(6), 95-108.
  34. N. Y. Kwak, H. I. Yoo & C. C. Lee. (2018). Study on Factors Affecting Financial Customer's Switching Intention to Internet Only Bank: Focus on Kakao Bank. Journal of Digital Convergence, 16(2), 157-167.
  35. F. D. Davis. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340.
  36. R. L. Oliver. (1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions. Journal of Marketing Research, 17(4), 460-469.
  37. H. J. Kim & J. Y. Rha. (2017). Impacts of the O2O Mobile Order and Pay Services Continued Use Intention: Usage Frequency Moderating Effect. Journal of Consumption Culture, 20(3), 199-226.
  38. J. M. Lee. (2012). Study on the Effect of Sociability, Ease of Use, Usefulness, Enjoyment on Acceptance Intention in e-Learning - A Perspective of the Extended Technology Acceptance Model. The Journal of the Korea Contents Association, 12(4), 417-425. DOI : 417
  39. M. H. Hsu, C. H. Yen, C. M. Chiu & C. M. Chang. (2006). A Longitudinal Investigation of Continued Online Shopping Behavior: An Extension of the Theory of Planned Behavior. International Journal of Human-Computer Studies, 64(9), 889-904.
  40. M. J. Lee. (2017). The Effect of Emotional Response with Selection Factors on Behavioral Intentions in the Airline Industry: From the Perspective of Expectancy-Disconfirmation Theory. International Journal of Tourism and Hospitality Research, 31(9), 97-110. DOI :
  41. S. H. Kim. (2006). A Study on the Effects of Consumer Attributes and Emotions on Dissatisfaction and Behaviors in Case of Negative Expectancy Disconfirmation: Comparison for Relative Influence According to Consumers' Efforts Before Purchase. Korea Management Review, 35(5), 1497-1529.
  42. Y. H. Jung, G. Kim & C. C. Lee (2015). Factors Influencing User Satisfaction and Continuous Usage Intention on Mobile Credit Card: Based on Innovation Diffusion Theory and Post Acceptance Model. The Journal of Society for e-Business Studies, 20(3), 11-28.
  43. M. J. Noh. (2010). An Analysis of the Relationship on the Mobile Banking Characteristics, Satisfaction, and Reuse Intention: According to Gender. Journal of Business Research, 25(4), 305-344.
  44. H. S. Park & J. M. Lee. (2016). A Validation Study of Korean Version of PANAS-Revised. The Korean Journal of Psychology : General, 35(4), 617-641. DOI :
  45. W. J. Havlena & M. B. Holbrook. (1986). The Varieties of Consumption Experience: Comparing Two Typologies of Emotion in Consumer Behavior. Journal of Consumer Research, 13(3), 394-404.
  46. R. B. Zajonc. (1980). Feeling and Thinking: Preferences Need No Inferences. American Psychologist, 35(2), 151-175. DOI : 10.1037/0003-066X.35.2.151.
  47. J. D. Morris, C. M. Woo, J. A. Geason & J. Y. Kim. (2002). The Power of Affect: Predicting Intention. Journal of Advertising Research, 42(3), 7-17.
  48. R. B. Zajonc & H. Markus. (1982). Affective and Cognitive Factors in Preferences. Journal of Consumer Research, 9(2), 123-131.
  49. E. C. Hirschman & M. B. Holbrook. (1982), Hedonic Consumption: Emerging Concepts, Methods and Propositions. Journal of Marketing, 46(3), 92-101.
  50. W. J. Chu & M. J. Im. (2009). Exploring the Role of Investor Expertise in Affective Forecasting and Investment Performance. Journal of Korean Marketing Association, 6(24), 131-149. UCI :
  51. V. Venkatesh, M. G. Morris, G. B. Davis & F. D. Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425-478.
  52. C. S. Lin, S. Wu & R. J. Tsai. (2005). Integrating Perceived Playfulness into Expectation-Confirmation Model for Web Portal Context. Information & Management, 42(5), 683-693. DOI : 10.1016/
  53. W. Boonsiritomachai & K. Pitchayadejanant. (2017). Determinants Affecting Mobile Banking Adoption by Generation Y Based on The Unified Theory of Acceptance and Use of Technology Model Modified by The Technology Acceptance Model Concept. Kasetsart Journal of Social Sciences, 2017, 1-10.
  54. H. H. Lee, E. J. Kim & M. K. Lee. (2003). A Validation Study of Korea Positive and Negative Affect Schedule: The PANAS Scales. Korean Journal of Clinical Psychology, 22(4), 935-946.
  55. S. Lee & S. M. Chang. (2017). Levels and Instability of Positive Affect, Negative Affect, and Self-Esteem and Their Relations with Depression and Neuroticism: Analyses of Multilevel Models with Experience Sampling Methods. The Korean Journal of Social and Personality Psychology, 31(4), 183-202.
  56. E. S. Kim & J. H. Kong. (2014). The Influence of Ego-Resilience, Positive Affect, Negative Affect on Military Life Stress in ROK Air Force Soldiers. Journal of the Korea Academia-Industrial Cooperation Society, 15(4), 2235-2243.
  57. Y. C. Lee & S. J. Lim. (2013). The Effect of Specialty Store's Service Quality on PANAS and Purchase Intention in Organic Products. Korea Distribution Science Association, Fifth International Conference, 259-269.
  58. F. D. Davis, R. P. Bagozzi & P. R. Warshaw. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982-1003.
  59. F. F. Reichheld & P. Schefter. (2000). E-Loyalty - Your Secret Weapon on the Web. Harvard Business Review, 78(4), 105-113.
  60. R. A. Westbrook. (1987). Product /Consumption-Based Affective Responses and Post purchase Processes. Journal of Marketing Research, 24(3), 258-270.
  61. S. Chea & M. M. Luo. (2005). E-Service Customer Retention: The Roles of Negative Affectivity and Perceived Switching Costs. 11th Americas Conference on Information Systems, AMCIS 2005: A Conference on a Human Scale, Association for Information Systems. (pp. 365-371). Omaha, NE : Elsevier B. V.
  62. J. J. Inman & M. Zeelenberg. (2002). Regret in Repeat Purchase versus Switching Decisions: The Attenuating Role of Decision Justifiability. Journal of Consumer Research, 29(1), 116-128.
  63. B. Duchduen & B. Vutthi. (2013). The Empirical Development of Cognitive, Affective, and Behavioral Tendency Measures of Attitudes toward Nuclear Power Plants in Thai University Students. Progress in Nuclear Energy, 73, 86-95. DOI : 1016/j.pnucene.2013.12.013.
  64. J. H. Lee. (2017). Finance Consumer Report (76. Kakao Bank). NICE R&C.
  65. P. M. Bentler & C. Chou. (1987). Practical Issues in Structural Modeling. Sociological Methods & Research, 16(1), 78-117.
  66. H. W. Marsh. (1994). Confirmatory Factor Analysis Models of Factorial Invariance : A Multifaceted Approach. Structural Equation Modeling: A Multidisciplinary Journal, 1(1), 5-34. DOI : 10.1080/10705519409539960.
  67. B. B. Ryul. (2014). Amos 21 Structural Equation Modeling. Seoul : Chungram.
  68. R. J. Vandenberg. (2006). Statistical and Methodological Myths and Urban Legends -Where, Pray tell, Did They Get This Idea?. Organizational Research Methods, 9(2), 194-201. DOI : 10.1177/1094428105285506.
  69. E. M. Rogers. (2002). Diffusion of Preventive Innovations. Addictive Behaviors, 27(6), 989-993. DOI :
  70. G. C. Moore & I. Benbasat. (1991), Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation. Information Systems Research, 2(3), 192-222.
  71. J. S. Lee & J. H. Park. (2018). The Effects of Characteristics of User and System on the Perceived Cognition and the Continuous User Intention of Fintech. The Journal of the Korea Convergence Society, 9(1), 291-301.
  72. R. Agarwal & J. Prasad. (2007). Are Individual Differences Germane to the Acceptance of New Information Technologies. Decision Sciences, 30(2), 361-391. DOI : 5915.1999.tb01614.x.
  73. L. Carolina, M. Francisco, J. & B. Harry. (2008). An Assessment of Advanced Mobile Services Acceptance: Contributions from TAM and Diffusion Theory Models. Information & Management, 45(6), 359-364. DOI : 10.1016/
  74. M. H. Lee. (2003). Determinants of Intention to Use Internet Banking: Social Influence, Perceived Risk and Individual Difference. Korea Journal of Business Administration, 37, 757-776.
  75. H. B. Ham & C. Y. Choi. (2016). The Research on Accepting Attitudes of Financial Consumers for Mobile Payment Systems. The e-Business Studies, 17, 175-189.
  76. Z. Liao & C. Michael tow. (2002). Internet-based e-Banking and Consumer Attitudes : an Empirical Study. Information & Management, 39(4), 283-295.
  77. S. I. Han. (2004). The Determinants of User Adoption of Internet Banking. Journal of Industrial Economics and Business, 17(6), 2405-2428.
  78. L. Pau & J. Dits. (2002), Business Modeling Framework for Personalization in Mobile Business Services: a Case and Sociological Analysis. Erasmus Research Institute of Management(ERIM).