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A Study on Consumer Preferences for Attributes of Wearable Devices: A Conjoint Analysis Reflecting Anticipatory Standardization Activities

웨어러블 디바이스의 소비자 선호 속성에 관한 연구: 예지적 표준화 활동을 반영한 컨조인트 분석

Ji, Ilyong;Park, Hyo Joo
지일용;박효주

  • Received : 2019.03.12
  • Accepted : 2019.04.20
  • Published : 2019.04.28

Abstract

As fierce competition is expected in the wearable devices marekt, it is needed to develop a technology planning that can increase consumer acceptance. This study aims to provide implications for technology planning of wearable devices by examining consumer preferences for the devices. For this purpose we employed a conjoint analysis. In the process of the analysis, we considered the trend of anticipatory standardization for wearable devices in an attempt to improve objectivity of analysis whilst many previous studies relied on focus group interview. For the anticipatory standardization information, we utilized liaisons and projects of wearable devices at International Electrotechnical Commission, and we designed a conjoint survey on the basis of the information. We conducted an online survey, and a total of 229 individuals responded to our survey. The result of conjoint analysis shows that main use and enhanced features were more important attributes than the others were. However, consumer preferences for detailed levels of each attribute were different by gender and age groups. This result implies that technology planning of wearable devices require distinct approaches by consumer segments.

Keywords

wearable;conjoint;standard;convergence;technology acceptance;selection attribute

References

  1. M. Dehgani, K. J. Kim & R. M. Dangelico. (2018). Will Smartwatches last? Factors Contributing to Intention to Keep Using Smart Wearable Technology. Telematics and Informatics, 35(2), 480-490. DOI : 10.12811/JKCS.201.11.2.129 https://doi.org/10.1016/j.tele.2018.01.007
  2. S. H. Choi & S. I. Kim. (2017). A Study on the Factors Affecting the Purchase of Healthcare Smart Bands. Journal of the Korea Convergence Society, 8(7), 175-181. DOI: 10.15207/JKCS.2017.8.7.175 https://doi.org/10.15207/JKCS.2017.8.7.175
  3. S. H., Lee & D. W. Lee. (2015). On Issue and Outlook of Wearable Computer Based on Technology in Convergence. Journal of the Korea Convergence Society, 6(3), 73-78. DOI: 10.15207/JKCS.2015.6.3.073 https://doi.org/10.15207/JKCS.2015.6.3.073
  4. COMPA (2018). Wearable Devices. S&T Market Report. Vol.61. Seoul : Commercializations Promotion Agency for R&D Outcomes.
  5. IDC (2018). IDC Forecasts Sustained Double-Digit Growth for Wearable Devices Led by Steady Adoption of Smartwatches. IDC. https://www.idc.com/getdoc.jsp?containerId=prUS44553518
  6. IITP (2014). Diffusion of Wearable Devices and the Beginning of Platform Competition. Daejeon: Institute for Information & Communications Technology Promotion.
  7. M. Fallon, K. Spohrer & A. Heinzel. (2019). Wearable Devices: A Physiological and Self-Regulatory Intervention for Increasing Attention in the Workplace. Lecture Notes in Information systems and Organization, 29, 229-238. DOI : 10.1007/978-3-030-01087-4_28 https://doi.org/10.1007/978-3-030-01087-4_28
  8. B. Attallah & Z. Il-agure. (2019). Evaluating the Affordances of Wearable Technology in Education, International Journal of Grid and Utility Computing, 10(1), 22-28. DOI : 10.1504/IJGUC.2019.097227 https://doi.org/10.1504/IJGUC.2019.097227
  9. N. Sultan. (2015). Reflective Thoughts on the Potential and Challenges of Wearable Technology for Healthcare Provision and Medical Education. International Journal of Information Management, 35(5), 521-526. DOI : 10.1016/j.ijinfomgt.2015.04.010 https://doi.org/10.1016/j.ijinfomgt.2015.04.010
  10. L. F. Cardoso, S. B. Sorenson, O. Webb & S. Landers. (2019). Recent and Emerging Technologies: Implications for Women's Safety. Technology in Society, Article in Press. DOI: 10.1016/j.techsoc.2019.01.001 https://doi.org/10.1016/j.techsoc.2019.01.001
  11. A. Marasco, P. Buonincontri, M. Niekerk, M. Orlowski & F. Okumus. (2018) Exploring the Role of Next-Generation Virtual Technologies in Destination Marketing. Journal of Destination Marketing & Management, 9, 138-148. DOI: 10.1016/j.jdmm.2017.12.002 https://doi.org/10.1016/j.jdmm.2017.12.002
  12. M. C. T. Dieck, T. H. Jung, & D. T. Diek. (2018). Enhancing Art Gallery Visitors' Learning Experience Using Wearable Augmented Reality: Generic Learning Outcomes Perspective. Current Issues in Tourism, 21, 2014-2034. DOI : 10.1080/13683500.2016.1224818 https://doi.org/10.1080/13683500.2016.1224818
  13. J-Y. Jung & T-W. Roh. (2017). The Intention of Using Wearable Devices: Based on Modified Technology Acceptance Model. Journal of Digital Convergence, 15(4), 205-212. DOI : 10.14400/JDC.2017.15.4.205 https://doi.org/10.14400/JDC.2017.15.4.205
  14. M. Baek, H. Choi, & H. Lee. (2015). Age-Specific Acceptance Intention over Wearable Smart Healthcare Device. Korean Journal of Business Administration, 28(12), 3171-3189. DOI : 10.18032/kaaba.2015.28.12.3171 https://doi.org/10.18032/kaaba.2015.28.12.3171
  15. J. K. Bae. (2016). The Structural Relationships among Innovation Characteristics, Consumer Characteristics, Innovation Resistance, and Intention to Acceptance of Wearable Device Customers: Based on Innovation Resistance Model and Theory of Perceived Risk. Journal of Information Systems, 25(4), 87-104. DOI : 10.5859/KAIS.2016.25.4.87 https://doi.org/10.5859/KAIS.2016.25.4.87
  16. J-Y. Jung, J-S. Lee, & S-J. Kwak. (2017). Consumers' Preference about the Attributes of 3rd Generation Device. Journal of the Korea Academia-Industrial Cooperation Society, 18(3), 703-710. DOI : 10.5762/KAIS.2017.18.3.703 https://doi.org/10.5762/KAIS.2017.18.3.703
  17. Y. Jung, S. Kim, & B. Choi. (2016). Consumer Valuation of Wearables: The Case of Smartwatches. Computers in Human Behavior, 63, 899-905. DOI : 10.1016/j.chb.2016.06.040 https://doi.org/10.1016/j.chb.2016.06.040
  18. J. Kim, K. Ban, Y. Im, & E. S. Jung. (2017). Hook Type Wearable Device Based on User Discomfort. Journal of Ergonomic Society of Korea, 36(6), 765-776. DOI : 10.5143/JESK.2017.36.6.765 https://doi.org/10.5143/JESK.2017.36.6.765
  19. J. F. Hair, W. Black, B. J. Babin, & R. A. Anderson. (2010). Conjoint Analysis. In Multivariate Data Analysis, 7th ed. London: Pearson. 342-413.
  20. C. Park. (2010). Conjoint Analysis. In: J. W. Lim, H. J. Park, & M. S. Kang. Marketing Research Methods, Seoul: Bobmunsa. 271-328.
  21. H. Byeon. (2017), A Convergent Perspective on Preference Attributes by Purchase Channel Choosing Used Cars, Journal of the Korea Convergence Society, 8(3), 215-233. DOI : 10.15207/JKCS.2017.8.3.215 https://doi.org/10.15207/JKCS.2017.8.3.215
  22. J. Shin, Y. Park, & D. Lee. (2015). Google TV or Apple TV?-The Reasons for Smart TV Failure and a User-Centered Strategy for the Success of Smart TV. Sustainability, 7, 15955-15966. DOI : 10.3390/su71215797 https://doi.org/10.3390/su71215797
  23. A. Konig, T. Bonus, J. Grippenkoven. (2018). Analyzing Urban Residents' Appraisal of Ridepooling Service Attributes with Conjoint Analysis. Sustainability, 10, 3711-3726. DOI : doi.org/10.3390/su10103711 https://doi.org/10.3390/su10103711
  24. S. J. Jee, & S. Y. Sohn. (2015). Patent Network Based Conjoint Analysis for Wearable Devices. Technological Forecasting & Social Change, 101, 338-346. DOI : 10.1016/j.techfore.2015.09.018 https://doi.org/10.1016/j.techfore.2015.09.018
  25. I. Ji. (2012). Challenges in the National Standardization of Transport Protocole Expert Group Service Technologies in Korea: Implications for Latecomer Countries. Asian Journal of Technology Innovation, 20(2), 171-185. DOI: 10.1080/19761597.2012.726416 https://doi.org/10.1080/19761597.2012.726416
  26. B. M. Byrne & P. A. Golder, (2002). The Diffusion of Anticipatory Standards with Particular Reference to the ISO/IEC Information Resource Dictionary System Framework Standard. Computer Standards & Interfaces, 24, 369-379. DOI : 10.1016/S0920-5489(02)00057-0 https://doi.org/10.1016/S0920-5489(02)00057-0
  27. M. Bonino, & M. B. Spring. (1991). Standards as Change Agents in the Information Technology Market, Computer Standards and Interfaces, 12, 97-07. DOI :10.1016/S0920-5489(98)00064-6 https://doi.org/10.1016/S0920-5489(98)00064-6
  28. IEC (2019). IEC TC/SCs: IEC Technical Committees & Subcommittees. International Electrotechnical Commission. https://www.iec.ch/dyn/www/f?p=103:62:0::::FSP_LANG_ID:25
  29. IEC (2019). TC124 Wearable Electronic Devices and Technologies. International Electrotechnical Commission. https://www.iec.ch/dyn/www/f?p=103:7:0::::FSP_ORG_ID:20537
  30. J. Swingle. (2018). IDC: Apple and Xiaomi lead the way as wearable shipments reach 32M units. PhoneArena. https://www.phonearena.com/news/Wearables-shipments-Apple-Xiaomi-Samsung-Huawei-Q3-2018_id111615
  31. USA News Hub (2019). IDC: Wearables grew 5.5% in Q2 2018, Apple leads Xiaomi as Fitbit falls. USA News Hub. http://www.allusanewshub.com/2018/09/04/idc-wearables-grew-5-5-in-q2-2018-apple-leads-xiaomi-as-fitbit-falls/
  32. L. Zaninello. (2017). Do you need a smart band or a smartwatch?. AndroidPIThttps://www.androidpit.com/smartwatch-vs-smartband-difference
  33. S. Addelman. (1962). Orthogonal Main-Effects Plans for Asymetrical Factorial Experiments. Technometrics, 4, 21-46. DOI : 10.2307/1266170 https://doi.org/10.2307/1266170

Acknowledgement

Supported by : KOREATECH