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A Study of Smartphone Sustainable Business in the Chinese Market through Conjoint Analysis

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Purpose: This study focuses on the Chinese smartphone market to estimate product attributes influencing Chinese customers’ preference for developing new smartphones through conjoint analysis. Research design, data and methodology: The online questionnaire survey is processed among Chinese potential smartphone customers. Conjoint analysis including traditional conjoint analysis (TCA) and choice-based conjoint analysis (CBCA), is used to analyze the useful data of 500. Results: Results indicate that price is the most important predictor while screen size is the least for Chinese customers’ preference whether the method is TCA or CBCA. However, the importance of brand, capacity, CPU, and screen design is different. Moreover, based on each smartphone attribute level’s utility, the new products with the best combinations are different compared with both methods. Finally, the predicted market shares of the top 3 products are the same with maximum utility rule model between TCA and CBCA. However, when considering with the new best combined product, they are significantly different. Conclusions: Managers should recognize the differences between TCA and CBCA and select the best method to develop new smartphones for sustainable business in the Chinese competitive market based on the important attributes of price, brand, capacity, CPU, screen design, and size.

Abstract

Purpose: This study focuses on the Chinese smartphone market to estimate product attributes influencing Chinese customers’ preference for developing new smartphones through conjoint analysis. Research design, data and methodology: The online questionnaire survey is processed among Chinese potential smartphone customers. Conjoint analysis including traditional conjoint analysis (TCA) and choice-based conjoint analysis (CBCA), is used to analyze the useful data of 500. Results: Results indicate that price is the most important predictor while screen size is the least for Chinese customers’ preference whether the method is TCA or CBCA. However, the importance of brand, capacity, CPU, and screen design is different. Moreover, based on each smartphone attribute level’s utility, the new products with the best combinations are different compared with both methods. Finally, the predicted market shares of the top 3 products are the same with maximum utility rule model between TCA and CBCA. However, when considering with the new best combined product, they are significantly different. Conclusions: Managers should recognize the differences between TCA and CBCA and select the best method to develop new smartphones for sustainable business in the Chinese competitive market based on the important attributes of price, brand, capacity, CPU, screen design, and size.

참고문헌 (42)

  1. Agarwal, M. K., "Adaptive conjoint analysis versus self-explicated models : Some empirical results", International Journal of Research in Marketing, 8(2), pp.141~146 (1991)
  2. Ahmad, W., "Pricing of mobile phone attributes at the retail level in a developing country : Hedonic Analysis", Telecommunications Policy, 43(4), pp.299~309 (2019)
  3. Ahn, S. S., "The study on the selective attributes of restaurant : Compare between choice based conjoint and traditional conjoint method", Korean Journal of Food Marketing Economics, 28(2), pp.107~129 (2011)
  4. Alfaro, V. N., "The perceived value of environmental sustainability for consumers in the air travel industry : A choice-based conjoint analysis", Journal of Cleaner Production, 380, pp.1~10 (2022)
  5. Bruning, E. R., "Cross-national segmentation: An application to the NAFTA airline passenger market", European Journal of Marketing, 43(11, pp.12) (2009), 1498~1522
  6. "Global smartphone market shows signs of stability with a 13% decline in Q1 2023" (2023)[URL]
  7. "Mainland China’s smartphone market shrunk by 11% post-reopening" (2023)[URL]
  8. Cattin, P., "Commercial use of conjoint analysis : A survey", Journal of Marketing, 46(3), pp.44~53 (1982)
  9. Choi, H., "Consumer preferences of attributes of mobile payment services in South Korea", Telematics and Informatics, 51, pp.1~15 (2020)
  10. Dauda, S. Y., "Technology adoption : A conjoint analysis of consumers’ preference on future online banking services", Information Systems, 53, pp.1~15 (2015)
  11. Demirciftci, T., "An application of choice-based conjoint analysis to measure willingness to pay for casino buffets", International Hospitality Review, pp.1~21 (2023)
  12. Djatmiko, T., "Brand image and product price; Its impact for Samsung smartphone purchasing decision", Procedia-Social and Behavioral Sciences, 219, pp.221~227 (2016)
  13. Eggers, F., "Handbook of Market Research", pp.781~819 (2021)
  14. Gao, Z., "Using choice-based conjoint analysis in the China market of imported beer", International Journal of Industrial Distribution & Business, 9(6), pp.57~64 (2018)
  15. Green, P. E., "Conjoint measurement for quantifying judgmental data", Journal of Marketing Research, 8(3), pp.355~363 (1971)
  16. Green, P. E., "Conjoint analysis in consumer research : Issues and outlook", Journal of Consumer Research, 5(2), pp.103~123 (1978)
  17. Halme, M., "Estimation methods for choice-based conjoint analysis of consumer preferences", European Journal of Operational Research, 214(1), pp.160~167 (2011)
  18. Han, S. H., "A study on the consumption value and the consumption satisfaction of smart phone users", Journal of Consumer Studies, 22(3), pp.233~260 (2011)
  19. Hung, K., "Understanding luxury shopping destination preference using conjoint analysis and traditional item-based measurement", Journal of Travel Research, 58(3), pp.411~426 (2019)
  20. Ji, H., "Attribute analysis of cellular phone using conjoint analysis", Journal of the Korean Data and Information Science Society, 20(4), pp.695~703 (2009)
  21. Johnson, R. M., "How many questions should you ask in choice-based conjoint studies?", Sawtooth Software, pp.1~24 (1996)
  22. Kim, B., "Conjoint analysis for the development of new cellular phone", Journal of Korean Society Quality Management, 33(4), pp.103~110 (2005)
  23. Kim, Y., "Measuring the value of mobile telecommunication services using a choice-based approach", Korean Journal of Business Administration, 36(3), pp.513~528 (2023)
  24. Kim, M., "Determinants of customer loyalty in the Korean smartphone market : Moderating effects of usage characteristics", Telematics and Informatics, 33, pp.936~949 (2016)
  25. Lee, H., "Marketing Research by Professor Hoon-Young Lee" (2012), Cheoungram Press
  26. Lee, S. Y., "Examining the factors that influence early adopters’ smartphone adoption : The case of college students", Telematics and Informatics, 31, pp.308~318 (2014)
  27. Ling, C., "A survey of what customers want in a cell phone design", Behaviour & Information Technology, 26(2), pp.149~163 (2007)
  28. Conjoint analysis, "Louviere, J. J.", Advanced Methods of Marketing Research, 223~258 (1994)
  29. Louviere, J. J., "Design and analysis of simulated consumer choice or allocation experiments : An approach based on aggregated data", Journal of Marketing Research, 20(4), pp.350~367 (1983)
  30. "Analysis of the Current Operation Status of China’s Mobile Phone Industry Market from January to October 2023: the Shipment Volume of China’s Mobile Phone Market Reached 230 million Units in the First 10 Months" (2023)[URL]
  31. Malone, T., "Taste trumps health and safety : Incorporating consumer perceptions into a discrete choice experiment for meat", Journal of Agricultural and Applied Economics, 49(1), pp.139~157 (2017)
  32. Mansuy, J., "Understanding preferences for EEE collection services: A choice-based conjoint analysis", Resources, Conservation & Recycling, 161, pp.1~12 (2020)
  33. "China Smartphone Market Analysis: Industry Size, Share, Research Report, Insights, Covid-19 Impact, Statistics, Trends, Growth and Forecast 2023-2030" (2023)[URL]
  34. "China Smartphone Market: Industry Analysis and Forecast (2022-2029), Key Trends, Sales Volume Analysis, Share, Size" (2023)[URL]
  35. Mittal, V., "Attribute-level performance, satisfaction, and behavioral intentions over time : A consumption-system approach", Journal of Marketing, 63(2), pp.88~101 (1999)
  36. Payini, V., "Indian women consumers’ wine choice : a study based on conjoint analysis", International Journal of Wine Business Research, 34(4), pp.469~494 (2022)
  37. "Smartphone Market in China" (2023)[URL]
  38. Silayoi, P., "The importance of packaging attributes: a conjoint analysis approach", European Journal of Marketing, 41(11, pp.12) (2007), 1495~1517
  39. Tano, K., "Using conjoint analysis to estimate farmer’s preferences for cattle traits in West Africa", Ecological Economics, 15(3), pp.393~407 (2003)
  40. Wallner, T. S., "Do consumers mind contamination by previous users? A choice-based conjoint analysis to explore strategies that improve consumers’ choice for refurbished products", Resource, Conservation & Recycling, 177, pp.1~12 (2022)
  41. Yeh, C., "Predicting smartphone brand loyalty : Consumer value and consumer-brand identification perspectives", International Journal of Information Management, 36, pp.245~257 (2016)
  42. Zhang, J., "A Choice-based conjoint analysis of social media picture posting and souvenir purchasing preference : A case study of social analytics on tourism", Information Processing and Management, 58(6), pp.1~12 (2021)

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