The Journal of Asian Finance, Economics and Business

Korea Distribution Science Association (한국유통과학회)
권호 표지
DOI QR코드

DOI QR Code

Evaluating Perceived Smartness of Product from Consumer's Point of View: The Concept and Measurement

  • Received : 2018.11.08
  • Accepted : 2019.02.10
  • Published : 2019.02.28
Download PDF
⟨ Previous Next ⟩

Abstract

Due to the rapid development of IT (information technology) and internet, products become smart and able to collect, process and produce information and can think of themselves to provide better service to consumers. However, research on the characteristics of smart product is still sparse. In this paper, we report the systemic development of a scale to measure the perceived product smartness associated with smart product. To develop product smartness scale, this study follows systemic scale development processes of item generation, item reduction, scale validation, reliability and validity test consequently. And, after acquiring a large amount of qualitative interview data asking the definition of smart product, we add a unique process to reduce the initial items using both a text mining method using 'r' s/w and traditional reliability and validity tests including factor analysis. Based on an initial qualitative inquiry and subsequent quantitative survey, an eight-factor scale of product smartness is developed. The eight factors are multi-functionality, human-like touch, ability to cooperate, autonomy, situatedness, network connectivity, integrity, and learning capability consequently. Results from Korean samples support the proposed measures of product smartness in terms of reliability, validity, and dimensionality. Implications and directions for further study are discussed. The developed scale offers important theoretical and pragmatic implications for researchers and practitioners.

Keywords

References

  1. Bagozzi, R. P., & YI, Youjae. (2012). Specification, evaluation, and interpretation of structural equation models. Journal of the Academy of Marketing Science, 40(1), 8-34. https://doi.org/10.1007/s11747-011-0278-x
  2. Churchill, G. A. Jr. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(February), 64-73. https://doi.org/10.2307/3150876
  3. Cook, D., & Das, S. (2004). Smart environment: technology, protocols, & applications. Hoboken, NJ: Wiley.
  4. Dawid, H., Decker, R., Hermann, T., Jahnke, H., Klat, W., Konig, R., & Stummer, C. (2017). Management science in the era of smart consumer products: Challenges and research perspective. Central European Journal of Operation Research, 25(1), 203-230. https://doi.org/10.1007/s10100-016-0436-9
  5. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(February), 39-50. https://doi.org/10.1177/002224378101800104
  6. Gerbing, D. W., & Andersen, J. C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25(May), 186-192. https://doi.org/10.2307/3172650
  7. Homburg, C., Schwemmle, M., & Kuehnl, C. (2015). New product design: Concept, measurement, and consequences. Journal of Marketing, 79(May), 41-56. https://doi.org/10.1509/jm.14.0199
  8. Kim, H., & Cho, H. (2013), The effects of consumption value of smartphone users on relational factors and repurchase intention. Journal of Distribution Science, 11(4), 73-80. https://doi.org/10.13106/jds.2013.vol11.no10.73.
  9. Kwon, Y., Park, J., Lee H., & Kim, M. (2014), Beacon-based O2O marketing for financial institutions. International Journal of Industrial Distribution & Business, 5(4), 23-29. https://doi.org/10.13106/ijidb.2014.vol5.no4.23.
  10. Lee, W., & Shin, S. J. (2018). Effects of product smartness on satisfaction: focused on the perceived characteristics of smartphone. Journal of Theoretical and Applied Electronic Commerce Research, 13(2), 11-14.
  11. Lin, C-Y., Chao, Y-C., & Tang, T-W. (2017). Why not be smarter? examining the factors that influence the behavioral intentions of non-smartphone users. Industrial Management & Data Systems, 117(1), 32-49. https://doi.org/10.1108/IMDS-07-2015-0319
  12. Maass, W., & Janzen, S. (2007). Dynamic product interfaces: A key element for ambient shopping environments. In Proceedings of 20th Bled e-conference, Slovenia.
  13. Maass, W., & Varshney, U. (2008). Preface to the focus theme section: Smart products. Electronic Markets, 18(3), 211-215. https://doi.org/10.1080/10196780802265645
  14. McFarlane, D., Sarma, S., Chirn, J. L., Wong, C. Y., & Ashton, K. (2003). Auto ID systems and intelligent manufacturing control. Engineering Applications of Artificial Intelligence, 16(4), 365-376. https://doi.org/10.1016/S0952-1976(03)00077-0
  15. Meyer, G. G., Framling, K., & Holmstrom, J. (2009). Intelligent product: a survey. Computers in Industry, 60(3), 137-148. https://doi.org/10.1016/j.compind.2008.12.005
  16. Miche, M., Schreiber, D., & Hartmann, M. (2009). Core services for smart products. In Proceedings of AmI-Blocks, 9, 1-4.
  17. Rijsdijk, S. A., & Hultink, E. J. (2003). The impact of product smartness on consumer satisfaction through product advantage, compatibility, and complexity. In Proceedings of the 13th PDMA Research Conference, Orlando.
  18. Rijsdijk, S. A., & Hultink, E. J. (2009). How today's consumers perceive tomorrow's smart products. The Journal of Product Innovation Management, 26(1), 24-42. https://doi.org/10.1111/j.1540-5885.2009.00332.x
  19. Shin, S., & Lee, W. (2014). The effect of technology readiness and technology acceptance on NFC mobile payment services in Korea. Journal of Applied Business Research, 30(6), 1615-1626. https://doi.org/10.19030/jabr.v30i6.8873
  20. Swallow, D., Blythe, M., & Wright, P. (2005). Grounding experience: relating theory and method to evaluate the user experience of smartphones. In Proceedings of the 2005 Annual Conference on European Association of Cognitive Ergonomics, 91-98.
  21. Thompson, C. (2005). Smart devices and soft controllers. Internet Computing, IEEE, 9(1), 82-85. https://doi.org/10.1109/MIC.2005.22
  22. Voss, K. E., Spangenberg, E. R., & Grohmann, B. (2003). Measuring the hedonic and utilitarian dimensions of consumer attitude. Journal of Marketing Research, 40(August), 310-320. https://doi.org/10.1509/jmkr.40.3.310.19238
  23. Wunderlich, N. V., Heinonen, K., Ostrom, A. L., Patricio, L., Sousa, R., Voss, C., & Lemmink, J. G. A. M. (2015). Futurizing smart service: implications for service researchers and managers. Journal of Services Marketing, 29(6/7), 442-447. https://doi.org/10.1108/JSM-01-2015-0040
  24. Yi, S., & Su, S. (2014). A study of the factors that impack Chinese consumer's purchasing intent for high-tech products. East Asian Journal of Business Management, 4(1), 37-40. https://doi.org/10.13106/eajbm.2014.vol4.no1.37.

Cited by

  1. A Study on BMS by BDS for Distribution-Business: Business Model System by Buyer's Decision Step vol.17, pp.4, 2019, https://doi.org/10.15722/jds.17.4.201904.27
  2. Usability Evaluation Scale for Product of Intelligent Homecare based on Retail Consumer vol.17, pp.12, 2019, https://doi.org/10.15722/jds.17.12.201912.55
  3. Factors Influencing the Reuse of Mobile Payment Services in Retail vol.18, pp.3, 2019, https://doi.org/10.15722/jds.18.3.202003.53
  4. Examining Customers' Continuance Intentions towards E-wallet Usage: The Emergence of Mobile Payment Acceptance in Vietnam vol.7, pp.9, 2019, https://doi.org/10.13106/jafeb.2020.vol7.no9.505