Information Systems Review (경영정보학연구)

The Korea Society of Management Information Systems (한국경영정보학회)
권호 표지
DOI QR코드

DOI QR Code

A Study on the Intention to use Personal Mobility Services: Focused on the SOR(Stimulus-Organism-Response) Model

퍼스널 모빌리티 사용의도에 관한 연구: SOR(Stimulus-Organism-Response) 모델을 중심으로

  • Wonguk Lee (Graduate School of Innovation and Technology Management, College of Business, KAIST) ;
  • Heetae Yang (Department of Management & Economics, Handong Global University)
  • 이원국 (한국과학기술원 기술경영전문대학원) ;
  • 양희태 (한동대학교 경영경제학부)
  • Received : 2021.12.21
  • Accepted : 2022.05.30
  • Published : 2022.05.31
Download PDF
⟨ Previous Next ⟩

Abstract

This study proposed a research model that can explain the usage intentions of users and non-users by considering the performance aspects of personal mobility and external environmental factors based on the SOR (Stimulus-Organism-Response) model, A survey was conducted targeting domestic users and non-users, and research models and hypotheses were verified through Partial Least Square (PLS) and Artificial Neural Network (ANN). As a result of the analysis, it was confirmed that the users' perceived satisfaction and perceived trust had a positive effect on their intention to use, and that perceived risk and environmental value had a significant relationship with perceived satisfaction and perceived trust. For non-users, it was found that there was a positive correlation between perceived satisfaction and intention to use, and it was verified that perceived risk and environmental value, like users, were significant antecedents of perceived satisfaction and perceived trust. Among the remaining variables, the perceived mobility of users and the perceived ease of use of non-users were respectively presented as important influencing factors on perceived satisfaction.

본 연구는 SOR(Stimulus-Organism-Response) 모델을 기반으로 퍼스널 모빌리티의 성능적 측면과 외부 환경적 요인을 고려해 이용자들과 비이용자들의 사용 의도를 설명할 수 있는 연구 모형을 제안하였다. 국내 사용자들과 비사용자들을 대상으로 설문조사를 진행하였고 부분최소자승법(Partial Least Square, PLS)과 인공신경망 분석(Artificial Neural Network, ANN)을 통해 연구모형 및 가설들을 검증하였다. 분석결과, 사용자들은 지각된 만족도와 지각된 신뢰도가 사용 의도에 긍정적인 영향을 미치고, 지각된 위험성과 환경적 가치가 지각된 만족도와 지각된 신뢰도와 유의한 관계가 있음이 확인되었다. 반면, 비사용자들은 지각된 만족도와 사용의도 간에 양의 상관관계가 있음이 밝혀졌고, 사용자들과 마찬가지로 지각된 위험성과 환경적 가치가 지각된 만족도와 지각된 신뢰도의 유의한 선행변수임이 검증되었다. 나머지 변수들 중에서는 사용자들의 지각된 이동성과 비사용자들의 지각된 이용 용이성이 각각 지각된 만족도의 중요한 영향요인으로 파악되었다.

Keywords

Acknowledgement

이 연구는 한동대학교 교내연구지원사업 제202100550001호에 의한 것임.

References

  1. 고상필, 이준, 천호영, "철도역 접근성 강화를 위한 무선급전 기반 공유형 퍼스널 모빌리티 기반기술 개발에 관한 연구", 교통기술과정책, 제17권, 제2호, 2020, pp. 59-71.
  2. 고석용, "강력 규제에 시민 눈살까지...거리 누비던 공유킥보드 사라지나", 머니투데이, 2021.10.28., Available at https://news.mt.co.kr/mtview.php?no=2021102816352199738.
  3. 김성은, "SOR 모형을 활용한 소셜미디어 이벤트 팬 페이지 이용자 행동 연구", MICE관광연구, 제21권, 제3호, 2020, pp. 151-171. https://doi.org/10.35176/JMTR.21.3.8
  4. 김점산, 빈미영, 조응래, 지우석, 송제룡, 김을식, 성영조, 김태경, 박승준, 장정식, 최서윤, 김서정, 송승현, 정지이, "스마트 모빌리티 서비스의 현황 및 발전방안 연구", 경기연구원정책연구보고서, 2020, pp. 1-186.
  5. 박민숙, "옴니채널 앱만족도 영향요인과 점포이용의도에 관한 연구", Journal of Information Technology Applications & Management, 제28권, 제1호, 2021, pp. 111-121.
  6. 박성민, "퍼스널 모빌리티 충전 기술 개발과 인프라 구축 방향", 전력전자학회지, 제24권, 제1호, 2019, pp. 30-34.
  7. 방영석, 이동주, 배윤수, "개인화 서비스의 수용에 있어서 인지된 개인화와 이해의 역할", 경영학연구, 제40권, 제2호, 2011, pp. 355-382.
  8. 서혜지, 백주영, 이태린, "퍼스널 모빌리티 이용자를 위한 웨어러블 기기 센서 기반 데이터 플랫폼 개발", 한국 HCI 학회 학술대회, 2020, pp. 673-675.
  9. 신상윤, 김철중, "모바일 앱 이용자의 서비스 편의성이 소비자의 신뢰 및 구매의도에 미치는 영향: 지각가치의 조절 및 신뢰의 매개역할을 중심으로", 유통경영학회지, 제22권, 제1호, 2019, pp. 23-33. https://doi.org/10.17961/JDMR.22.1.201902.23
  10. 신희철, 이재용, 김사리, "개인용 교통수단 (Personal Mobility) 의 보급에 따른 제도개선방향", 한국교통연구원 수시연구보고서, 2017, pp. 1-115.
  11. 안준환, 김호준, 이규민, "소셜 커머스의 이용가치가 고객신뢰 및 지속이용의도에 미치는 영향에 관한 연구: 호텔이용고객 중심으로", 관광레저연구, 제33권, 제2호, 2021, pp. 115-129. https://doi.org/10.31336/JTLR.2021.2.33.2.115
  12. 왕정, 김연성, "온라인 쇼핑몰에서 서비스회복방식이 고객용서를 매개로 고객 행동의도에 미치는 영향-SOR 모델을 기반으로", 품질경영학회지, 제47권, 제3호, 2019, pp. 615-630.
  13. 이준영, 전범수, "OTT 서비스 만족도와 지속이용의도 결정 요인 연구", 한국방송학보, 제34권, 제4호, 2020, pp. 116-144. https://doi.org/10.22876/KAB.2020.34.4.004
  14. 이총명, 마완준, 한수정, 김하람, 최재붕, 이태린, "퍼스널 모빌리티 기반 실내 위치 추정 및 주행 시스템 구축", 대한기계학회 춘추학술대회, 2019, pp. 1901-1904.
  15. 트렌드모니터, "아이들 장난감에서 미래 '이동수단'으로 발돋움하는 '퍼스널 모빌리티'", 2020.3., Available at https://www.trendmonitor.co.kr/tmweb/trend/allTrend/detail.do?bIdx=1880&code=0304&trendType=CKOREA.
  16. Anderson, J. C. and D. W. Gerbing, "Structural equation modeling in practice: A review and recommended two-step approach", Psychological Bulletin, Vol.103, No.3, 1988, pp. 411-423. https://doi.org/10.1037//0033-2909.103.3.411
  17. Bland, J. M. and D. G. Altman, "Statistics notes: Cronbach's alpha", Bmj, Vol.314, No.7080, 1997, p. 572.
  18. Chen, C. C. and J. Y. Yao, "What drives impulse buying behaviors in a mobile auction? The perspective of the Stimulus-Organism-Response model", Telematics and Informatics, Vol.35, No.5, 2018, pp. 1249-1262. https://doi.org/10.1016/j.tele.2018.02.007
  19. Chen, S. P. and M. D. Cheng, "An analysis of leisure tourist consumer behavior of single women based on the SOR model system", In 2012 International Conference on Management Science & Engineering 19th Annual Conference Proceedings, 2012, pp. 823-832.
  20. Cheng, W., H. Tsai, H. Chuang, P. Lin, and T. Ho, "How can emerging event sustainably develop in the tourism industry? From the perspective of the sor model on a two-year empirical study", Sustainability, Vol.12, No.23, 2020, p. 10075.
  21. Chin, W. W., B. L. Marcolin, and P. R. Newsted, "A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study", Information Systems Research, Vol.14, No.2, 2003, pp. 189-217. https://doi.org/10.1287/isre.14.2.189.16018
  22. Chiu, C. M., C. S. Chiu, and H. C. Chang, "Examining the integrated influence of fairness and quality on learners' satisfaction and Web-based learning continuance intention", Information Systems Journal, Vol.17, No.3, 2007, pp. 271-287. https://doi.org/10.1111/j.1365-2575.2007.00238.x
  23. Chiu, W., G. E. Oh, and H. Cho, "Impact of COVID-19 on consumers' impulse buying behavior of fitness products: A moderated mediation model", Journal of Consumer Behaviour, 2021, pp. 1-14.
  24. Chong, A. Y. L., "Predicting m-commerce adoption determinants: A neural network approach", Expert Systems with Applications, Vol.40, No.2, 2013, pp. 523-530. https://doi.org/10.1016/j.eswa.2012.07.068
  25. Christoforou, Z., C. Gioldasis, A. de Bortoli, and R. Seidowsky, "Who is using e-scooters and how? Evidence from Paris", Transportation Research Part D: Transport and Environment, Vol.92, 2021, 102708.
  26. Eccarius, T. and C. C. Lu, "Adoption intentions for micro-mobility-Insights from electric scooter sharing in Taiwan", Transportation Research Part D: Transport and Environment, Vol.84, 2020, pp. 102-327. https://doi.org/10.1016/j.trd.2020.102327
  27. Fornell, C. and D. F. Larcker, "Evaluating structural equation models with unobservable variables and measurement error", Journal of Marketing Research, Vol.18, No.1, 1981, pp. 39-50. https://doi.org/10.1177/002224378101800104
  28. Hair, J. F., M. Sarstedt, L. Hopkins, and V. G. Kuppelwieser, "Partial least squares structural equation modeling (PLS-SEM): An Emerging Tool in Business Research", European Business Review, Vol.26, No.2, 2014, pp. 106-121. https://doi.org/10.1108/EBR-10-2013-0128
  29. Han, S. and H. Yang, "Understanding adoption of intelligent personal assistants: A parasocial relationship perspective", Industrial Management & Data Systems, Vol.118, No.33, 2018, pp. 618-636. https://doi.org/10.1108/IMDS-05-2017-0214
  30. Henseler, J., G. Hubona, and P. Ray, "Using PLS path modeling in new technology research: Updated guidelines", Industrial Management & Data Systems, Vol.116, No.1, 2016, pp. 2-20. https://doi.org/10.1108/IMDS-09-2015-0382
  31. Hew, J. J., M. N. B. A. Badaruddin, and M. K. Moorthy, "Crafting a smartphone repurchase decision making process: Do brand attachment and gender matter?", Telematics and Informatics, Vol.34, No.4, 2017, pp. 34-56. https://doi.org/10.1016/j.tele.2016.12.009
  32. HMG Journal, "가장 가까운 모빌리티, 퍼스널 모빌리티", 2020.2.24., https://news.hmgjournal.com/Tech/가장-가까운-모빌리티-퍼스널-모빌리티.
  33. Jiang, Z., Z. Wang, and Z. Li, "The effect of mandatory environmental regulation on innovation performance: Evidence from China", Journal of Cleaner Production, Vol.203, 2918, pp. 482-491.
  34. Kamboj, S., B. Sarmah, S. Gupta, and Y. Dwivedi, "Examining branding co-creation in brand communities on social media: Applying the paradigm of Stimulus-Organism-Response", International Journal of Information Management, Vol.39, 2018, pp. 169-185. https://doi.org/10.1016/j.ijinfomgt.2017.12.001
  35. Kock, N., "Common method bias in PLS-SEM: A full collinearity assessment approach", International Journal of e-Collaboration (ijec), Vol.11, No.4, pp. 1-10.
  36. Kopplin, C. S., B. M. Brand, and Y. Reichenberger, "Consumer acceptance of shared e-scooters for urban and short-distance mobility", Transportation Research Part D: Transport and Environment, Vol.91, 2021, 102680.
  37. Leong, L. Y., Hew, T. S., Lee, V. H., & Ooi, K. B., "An SEM-artificial-neural-network analysis of the relationships between SERVPERF, customer satisfaction and loyalty among low-cost and full-service airline", Expert systems with applications, Vol.42, No.19, 2015, pp. 6620-6634. https://doi.org/10.1016/j.eswa.2015.04.043
  38. Leong, L. Y., T. S. Hew, G. W. H. Tan, and K. B. Ooi, "Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach", Expert Systems with Applications, Vol.40, No.14, 2013, pp. 5604-5620. https://doi.org/10.1016/j.eswa.2013.04.018
  39. Li, L., M. Peng, N. Jiang, and R. Law, "An empirical study on the influence of economy hotel website quality on online booking intentions", International Journal of Hospitality Management, Vol.63, 2017, pp. 1-10. https://doi.org/10.1016/j.ijhm.2017.01.001
  40. Liebana-Cabanillas, F., V. Marinkovic, and Z. Kalinic, "A SEM-neural network approach for predicting antecedents of m-commerce acceptance", International Journal of Information Management, Vol.37, No.2, 2017, pp. 14-24. https://doi.org/10.1016/j.ijinfomgt.2016.10.008
  41. Ma, Q., H. Yang, A. Mayhue, Y. Sun, Z. Huang, and Y. Ma, "E-scooter safety: The riding risk analysis based on mobile sensing data", Accident Analysis & Prevention, Vol.151, 2021, 105954.
  42. McCarthy, N., "How Dangerous Are Electric Sco oters?", Forbes, 2019.2.4., Available at https://www.forbes.com/sites/niallmccarthy/2019/02/04/how-dangerous-are-electric-scooters-infographic/?sh=35df94c1469c.
  43. Mehrabian, A. and J. A. Russell, An approach to environmental psychology, the MIT Press, 1974.3.
  44. Nam, C., K. Cho, and Y. D. Kim, "Cross-cultural examination of apparel online purchase intention: SOR paradigm", Journal of Global Fashion Marketing, Vol.12, No.1, 2021, pp. 62-76. https://doi.org/10.1080/20932685.2020.1845766
  45. Nielsen, "200만 이용자 목전에 둔 '퍼스널모빌리티', 대안 교통수단으로 자리잡나?", 뉴스레터 월간토픽, 제310권 제2호, 2020.11.30, Availa ble at www.koreanclick.com/insights/newsletter_view.html?code=topic&id=599&page=1&utm_source=board&utm_medium=board&utm_campaign=topic&utm_content=20201130.
  46. Ooi, K. B. and G. W. H. Tan, "Mobile technology acceptance Model: An investigation using mobile users to explore smartphone credit card", Expert Systems with Applications, Vol.59, 2016, pp. 33-46. https://doi.org/10.1016/j.eswa.2016.04.015
  47. Ooi, K. B., J. J. Hew, and B. Lin, "Unfolding the privacy paradox among mobile social commerce users: A multi-mediation approach", Behaviour & Information Technology, Vol.37, No.6, 2018, pp. 575-595. https://doi.org/10.1080/0144929X.2018.1465997
  48. Ronkko, M. and J. Evermann, "A critical examination of common beliefs about partial least squares path modeling", Organizational Research Methods, Vol.16, No.3, 2013, pp. 425-448. https://doi.org/10.1177/1094428112474693
  49. Sanders, R. L., M. Branion-Calles, and T. A. Nelson, "To scoot or not to scoot: Findings from a recent survey about the benefits and barriers of using E-scooters for riders and non-riders", Transportation Research Part A: Policy and Practice, Vol.139, 2020, pp. 217-227. https://doi.org/10.1016/j.tra.2020.07.009
  50. Scheerlinck, G., C. Buts, M. Cools, and G. Reniers, "The impact of regulation on private security industry dynamics", European Journal of Law and Economics, Vol.50, No.2, 2020, pp. 223-240. https://doi.org/10.1007/s10657-020-09663-5
  51. Sim, J. J., G. W. H. Tan, J. C. J. Wong, K. B. Ooi, and T. S. Hew, "Understanding and predicting the motivators of mobile music acceptance: A multi-stage MRA artificial neural network approach", Telematics and Informatics, Vol.31, No.4, 2014, pp. 569-584. https://doi.org/10.1016/j.tele.2013.11.005
  52. Tan, G. W. H., K. B. Ooi, L. Y. Leong, and B. Lin, "Predicting the drivers of behavioral intention to use mobile learning: A hybrid SEM-Neural Networks approach", Computers in Human Behavior, Vol.36, 2014, pp. 198-213. https://doi.org/10.1016/j.chb.2014.03.052
  53. Teo, A. C., G. W. H. Tan, K. B. Ooi, T. S. Hew, and K. T. Yew, "The effects of convenience and speed in m-payment", Industrial Management & Data Systems, Vol.115, No.2, 2015, pp. 311-331. https://doi.org/10.1108/IMDS-08-2014-0231
  54. Wong, L. W., L. Y. Leong, J. J. Hew, G. W. H. Tan, and K. B. Ooi, "Time to seize the digital evolution: Adoption of blockchain in operations and supply chain management among Malaysian SMEs", International Journal of Information Management, Vol.52, 2020, 101997.
  55. Yang, H. and S. Y. Han, "Understanding virtual reality continuance: An extended perspective of perceived value", Online Information Review, Vol.45, No.2, 2021, pp. 422-439. https://doi.org/10.1108/OIR-02-2020-0058
  56. Yang, H., H. Lee, and H. Zo, "User acceptance of smart home services: an extension of the theory of planned behavior", Industrial Management & Data Systems, Vol.117, No.1, 2017, pp. 68-89. https://doi.org/10.1108/IMDS-01-2016-0017
  57. Zhu, L., H. Li, F. K. Wang, W. He, and Z. Tian, "How online reviews affect purchase intention: A new model based on the stimulus-organism-response (SOR) framework", Aslib Journal of Information Management, Vol.72, No.4, 2020, pp. 463-488. https://doi.org/10.1108/AJIM-11-2019-0308