Department of International Business, College of Commerce, National Chengchi University; Department of Business Administration, National Taiwan University
本研究探討消費者對產品過時恐懼如何因前次購買時間之遠近而改變，同時檢視在前次購買時間與升級產品購買意願之關係中，不同類型的產品過時恐懼所扮演的中介角色，以及消費者年齡的調節作用。對341位臺灣智慧型手機使用者所做的線上問卷調查分析結果顯示，消費者前次購買時間距離現在越久，購買升級產品之意願越強。心理過時恐懼與科技過時恐懼部分中介前次購買時間對升級意願之效果。消費者年齡對心理過時恐懼影響升級意願之效果有負向調節作用。相較於憂慮經濟過時的年輕人，年長者的經濟過時恐懼越高，升級意願越強。科技過時恐懼對經濟過時恐懼有直接正向效果，而且透過心理過時恐懼對經濟過時恐懼有間接效果。(147_M5eeadaa5aa7bd_Abs.pdf(File does not exist))
This research empirically explores how consumers’ fear of product obsolescence changes with the time elapsed since last purchase. The mediating roles of product obsolescence fears in the relationship between recency and consumers’ intention to purchase high-tech upgrades, along with the moderating role of consumer’s age on the mechanism underlying the fear-intention to upgrade causality, are also examined. Results of an online survey of 341 smartphone users in Taiwan show that recency, i.e., the time elapsed since last purchase, has both direct and indirect effects on consumers’ intention to upgrade. Fears of both psychological and technological obsolescence partially mediate the relationship between recency and intention to upgrade. The positive impact of fear of psychological obsolescence on upgrading intention is weakened by consumer’s age. Older consumers who fear economic obsolescence have stronger intention to upgrade their smartphones than younger consumers who are concerned about economic obsolescence. The three types of obsolescence fears are inter-correlated, with psychological obsolescence partially mediating the relationship between fear of technological obsolescence and economic obsolescence.(147_M5eeadaa5aa7bd_Abs.pdf(File does not exist))
Recency, Fear of Psychological Obsolescence, Fear of Technological Obsolescence, Fear of Economic Obsolescence, Age
This research explores how consumer fears that are specific to product obsolescence change with the time elapsed since last purchase, and investigates the effects of different obsolescence fears on consumers’ intention to purchase high-tech upgrades. The findings may offer several managerial guidelines for managing and launching high-technology consumer products. First, in order to maintain market share, durable goods firms have to keep launching new and better products, in the form of technological improvements and style changes, faster and more frequently than their competitors do. From the marketer’s perspective, understanding consumers’ upgrading behavior is essential to product planning. Product managers of high-tech companies would like to know what fraction of consumers would upgrade to the new product and improved versions of their products, and how quickly or slowly. On the basis of the findings, marketers may help consumers manage the transitions between product generations by offering a migration path. Different fears of product obsolescence must be taken into account when choosing which path to offer. Second, marketers can segment markets by types of fears of product obsolescence. Different consumers may derive different types of benefits from the same product because of their fears of product obsolescence. Specifically, some consumers who have significant fear of economic obsolescence derive benefits from utilitarian functions that products perform; others who worry about psychological obsolescence derive social benefit, while those with fear of technological obsolescence tend to derive benefits from being the first adopters of a new product. Attention to such benefit segmentation may provide marketers with positioning bases for their products, basic appeals in promotional strategy, and specific media to reach the targeted market segments. Third, firms should vary marketing communication efforts according to consumers’ age. Our findings show that consumers suffering from the fear of psychological obsolescence readily perceive the old product to be unfashionable and have high intention to upgrade their product. Young people seem to appreciate product design that focuses on changes in preferences, trends in style or fashion, and desire for social status. Therefore, marketing communications specific to young consumers should be integrated in order to activate the fear of psychological obsolescence fear. On the other hand, older consumers with greater fear of economic obsolescence have greater intention to upgrade. Price-based promotional offers may provide those consumers with quality benefit, which refers to an ability to upgrade to higher-quality products due to the temporary price reduction of previously unaffordable products. Finally, recency has strong positive effects on consumers’ intention to upgrade, suggesting that firms should increase their marketing efforts as the time elapsed since last purchase increases.
Bagozzi, R. P., Yi, Y., and Philips, L. W., 1991, “Assessing Construct Validity in Organizational Research,” Administrative Science Quarterly, Vol. 36, No. 3, 421-458.
Bayus, B. L., 1991, “The Consumer Durable Replacement Buyer,” Journal of Marketing, Vol. 55, No. 1, 42-51.
Berger, P. D. and Nasr, N. I., 1998, “Customer Lifetime Value: Marketing Models and Applications,” Journal of Interactive Marketing, Vol. 12, No. 1, 17-30.
Bitran, G. R. and Mondschein, S. V., 1996, “Mailing Decisions in the Catalog Sales Industry,” Management Science, Vol. 42, No. 9, 1364-1381.
Blattberg, R. C., Kim, B.-D., and Neslin, S. A., 2008, Database Marketing Analyzing and Managing Customers, 1st, New York: Springer.
Bloch, P. H., Ridgway, N. M., and Dawson, S. A., 1994, “The Shopping Mall as Consumer Habitat,” Journal of Retailing, Vol. 70, No. 1, 23-42.
Bohrnstedt, G. W. and Marwell, G., 1978, “The Reliability of Products of Two Random Variables,” Sociological Methodology, Vol. 9, 254-273.
Bollen, K. A., 1989, Structural Equations with Latent Variables, 1st, New York: John Wiley & Sons.
Bollen, K. and Lennox, R., 1991, “Conventional Wisdom on Measurement: A Structural Equation Perspective,” Psychological Bulletin, Vol. 110, No. 2, 305-314.
Börsch-Supan, A., Elsner, D., Fabender, H., Kiefer, R., McFadden, D., and Winter, J., 2004, “How to Make Internet Surveys Representative: A Case Study of a Two-Step Weighting Procedure,” MEA Discussion Paper Series 04067, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
Braunsberger, K., Wybenga, H., and Gates, R., 2007, “A Comparison of Reliability between Telephone and Web-Based Surveys,” Journal of Business Research, Vol. 60, No. 7, 758-764.
Brucks, M., Zeithaml, V. A., and Naylor, G., 2000, “Price and Brand Name as Indicators of Quality Dimensions for Consumer Durables,” Journal of the Academy of Marketing Science, Vol. 28, No. 3, 359-374.
Bult, J. R. and Wansbeek, T., 1995, “Optimal Selection for Direct Mail,” Marketing Science, Vol. 14, No. 4, 378-394.
Calantone, R. J., Schmidt, J. B., and Song, X. M., 1996, “Controllable Factors of New Product Success: A Cross-National Comparison,” Marketing Science, Vol. 15, No. 4, 341-358.
Castaño, R., Sujan, M., Kacker, M., and Sujan, H., 2008, “Managing Consumer Uncertainty in the Adoption of New Products: Temporal Distance and Mental Simulation,” Journal of Marketing Research, Vol. 45, No. 3, 320-336.
Cavusgil, S. T. and Zou, S., 1994, “Marketing Strategy-Performance Relationships: An Investigation of the Empirical Link in Export Market Ventures,” Journal of Marketing, Vol. 58, No. 1, 1-21.
Chandon, P., Wansink, B., and Laurent, G., 2000, “A Benefit Congruency Framework of Sales Promotion Effectiveness,” Journal of Marketing, Vol. 64, No. 4, 65-81.
Chandy, R. K. and Tellis, G. J., 1998, “Organizing for Radical Product Innovation：the Overlooked Role of Willingness to Cannibalize,” Journal of Marketing Research, Vol. 19, No. 4, 474-487.
Cohen, J. B. and Areni, C. S., 1991, “Affect and Consumer Behavior” in Robertson, T. S. and Kassarjian, H. H. (eds.), Handbook of Consumer Behavior, First Edition, Englewood Cliffs, NJ: Prentice-Hall, 188-240.
Cole, C. A. and Balasubramanian, S. K., 1993, “Age Differences in Consumers' Search for Information: Public Policy Implications,” Journal of Consumer Research, Vol. 20, No. 1, 157-169.
Cole, C. A. and Gaeth, G. J., 1990, “Cognitive and Age-Related Differences in the Ability to Use Nutritional Information in A Complex Environment,” Journal of Marketing Research, Vol. 27, No. 2, 175-184.
Cooper, T., 2004, “Inadequate Life? Evidence of Consumer Attitudes to Product Obsolescence,” Journal of Consumer Policy, Vol. 27, No. 4, 421-449.
Cortina, J. M., Chen, G., and Dunlap, W. P., 2001, “Testing Interaction Effects in Lisrel: Examination and Illustration of Available Procedures,” Organizational Research Methods, Vol. 4, No. 4, 324-360.
Couper, M. P., 2000, “Review: Web Surveys: A Review of Issues and Approaches,” Public Opinion Quarterly, Vol. 64, No. 4, 464-494.
Cripps, J. D. and Meyer, R. J., 1994, “Heuristics and Biases in Timing the Replacement of Durable Products,” Journal of Consumer Research, Vol. 21, No. 2, 304-318.
Deutskens, E., Jong, A., Ruyter, K., and Wetzels, M., 2006, “Comparing the Generalizability of Online and Mail Surveys in Cross-National Service Quality Research,” Marketing Letters, Vol. 17, No. 2, 119-136.
Dhebar, A., 1996, “Speeding High-Tech Producer, Meet the Balking Consumer,” Sloan Management Review, Vol. 37, No. 2, 37-49.
eMarketer, 2016, “Smartphone Owners Wait Years to Replace Handsets,” https://www.emarketer.com/Article/Smartphone-Owners-Wait-Years-Replace-Handsets/1014149, accessed on August 1, 2018.
Euromonitor, 2018, “Mobile Phone Demand in Detail: Uncounted, New, and Replacement Sales,” http://www.euromonitor.com/mobile-phone-demand-in-detail-uncounted-new-and-replacement-sales/report, accessed on August 2, 2018.
Fader, P. S., Hardie, B. G. S., and Lee, K. L., 2005, “RFM and CLV: Using Iso-Value Curves for Customer Base Analysis,” Journal of Marketing Research, Vol. 42, No. 4, 415-430.
Gatignon, H. and Robertson, T. S., 1991, “Innovative Decision Processes” in Robertson, T. S. and Kassarjian, H. H. (eds.), Handbook of Consumer Behavior, First Edition, Englewood Cliffs, NJ: Prentice-Hall, 316-348.
Gerbing, D. W. and Anderson, J. C., 1988, “An Updated Paradigm for Scale Development Incorporating Unidimensionality and Its Assessment,” Journal of Marketing Research, Vol. 25, No. 2, 186-192.
Gönül, F. and Shi, M. Z., 1998, “Optimal Mailing of Catalogs: A New Methodology Using Estimable Structural Dynamic Programming Models,” Management Science, Vol. 44, No. 9, 1249-1262.
Gönül, F. F., Kim, B.-D., and Shi, M., 2000, “Mailing Smarter to Catalog Customers,” Journal of Interactive Marketing, Vol. 14, No. 2, 2-16.
Gregoire, Y., 2003, “The Impact of Aging on Consumer Responses: What Do We Know?” in Keller, P. A. and Rook, D. W. (eds.), NA - Advances in Consumer Research Valdosta, First Edition, GA: Association for Consumer Research, 19-26.
Gregory, P. M., 1947, “A Theory of Purposeful Obsolescence,” Southern Economic Journal, Vol. 14, No. 1, 24-45.
Grewal, R., Mehta, R., and Kardes, G. R., 2004, “The Timing of Repeat Purchase of Consumer Durable Goods: The Role of Functional Bases of Consumer Attitudes,” Journal of Marketing Research, Vol. 41, No. 1, 101-115.
Guiltinan, J., 2009, “Creative Destruction and Destructive Creations: Environmental Ethics and Planned Obsolescence,” Journal of Business Ethics, Vol. 89, No. 1, 19-28.
Gupta, S., Hanssens, D., Hardie, B., Kahn, W., Kumar, V., Lin, N., Ravishanker, N., and Sriram, S., 2006, “Modeling Customer Lifetime Value,” Journal of Service Research, Vol. 9, No. 2, 139-155.
Hair, J. F., Anderson, R. E., Tatham, R. L., and Black, W. C., 1998, Multivariate Data Analysis with Readings, 5th, Englewood Cliffs, NJ: Prentice-Hall.
Higgins, S. H. and Shanklin, W. L., 1992, “Seeking Mass Market Acceptance for High-Technology Consumer Products,” Journal of Consumer Marketing, Vol. 9, No. 1, 5-14.
Homburg, C. and Giering, A., 2001, “Personal Characteristics as Moderators of the Relationship between Customer Satisfaction and Loyalty—an Empirical Analysis,” Psychology & Marketing, Vol. 18, No. 1, 43-66.
Hughes, A. M., 1996, “Boosting Responses with RFM: Recency, Frequency, and Monetary Analysis Finds the Buyers in Your Database,” Marketing Tools, Vol. 3, No.3, 4-8.
Ilieva, J., Baron, S., and Healey, N. M., 2002, “Online Surveys in Marketing Research,” International Journal of Market Research, Vol. 44, No. 3, 1-14.
Jöreskog, K. G. and Sörbom, D., 1996, Lisrel8: User’s Reference Guide, 1st, Chicago: Scientific Software International Inc.
Khan, R., Lewis, M., and Singh, V., 2009, “Dynamic Customer Management and the Value of One-to-One Marketing,” Marketing Science, Vol. 28, No. 6, 1063-1079.
Kim, S.-H. and Srinivasan, V., 2009, “A Conjoint-Hazard Model of the Timing of Buyers’ Upgrading to Improved Versions of High-Technology Products,” Journal of Product Innovation Management, Vol. 26, No. 3, 278-290.
LaTour, M. and Rotfeld, H. J., 1997, “There Are Threats and (Maybe) Fear-Caused Arousal: Theory and Confusion of Appeals to Fear and Fear Arousal Itself,” Journal of Advertising, Vol. 26, No. 3, 45-59.
LeBoeuf, R. A. and Simmons, J. P., 2010, “Branding Alters Attitude Functions and Reduces the Advantage of Function-Matching Persuasive Appeals,” Journal of Marketing Research, Vol. 47, No. 2, 348-360.
Lee, I. H. and Lee, J., 1998, “A Theory of Economic Obsolescence,” The Journal of Industrial Economics, Vol. 46, No. 3, 383-401.
Levinthal, D. A. and Purohit, D., 1989, “Durable Goods and Product Obsolescence,” Marketing Science, Vol. 8, No. 1, 35-56.
Li, T. and Calantone, R. J., 1998, “The Impact of Market Knowledge Competence on New Product Advantage: Conceptualization and Empirical Examination,” Journal of Marketing, Vol. 62, No. 4, 13-29.
MacKenzie, S. B., Podsakoff, P. M., and Ahearne, M., 1998, “Some Possible Antecedents and Consequences of in-Role and Extra-Role Salesperson Performance,” Journal of Marketing, Vol. 62, No. 3, 87-98.
Mathieu, J. E., Tannenbaum, S. I., and Salas, E., 1992, “Influences of Individual and Situational Characteristics on Measures of Training Effectiveness,” The Academy of Management Journal, Vol. 35, No. 4, 828-847.
Mick, D. G. and Fournier, S., 1998, “Paradoxes of Technology: Consumer Cognizance, Emotions, and Coping Strategies,” Journal of Consumer Research, Vol. 25, No. 2, 123-143.
Mohr, J. J., 2001, Marketing of High-Technology Products and Innovations, 1st, Upper Saddle River, NJ: Prentice Hall.
Morris, M. G., Venkatesh, V., and Ackerman, P. L., 2005, “Gender and Age Differences in Employee Decisions About New Technology: An Extension to the Theory of Planned Behavior,” IEEE Transactions on Engineering Management, Vol. 52, No. 1, 69-84.
Moscovitch, M., 1982, “A Neuropsychological Approach to Perception and Memory in Normal and Pathological Aging” in Craik, F. I. M. and Trehub, S. (eds.), Aging and Cognitive Processes, First Edition, Boston, MA: Springer, 55-78.
Neslin, S. A., Taylor, A., Grantham, K. D., and McNeil, K. R., 2013, “Overcoming the “Recency Trap” in Customer Relationship Management,” Journal of the Academy of Marketing Science, Vol. 41, No. 3, 320-327.
Niehoff, B. P. and Moorman, R. H., 1993, “Justice as A Mediator of the Relationship between Methods of Monitoring and Organizational Citizenship Behavior,” Academy of Management Journal, Vol. 36, No. 3, 527-556.
Nunnally, J. C., 1978, Psychometric Theory, 2nd, New York: McGraw-Hill.
Okada, E. M., 2006, “Upgrades and New Purchases,” Journal of Marketing, Vol. 70, No. October, 92-102.
Pfeifer, P. E. and Carraway, R. L., 2000, “Modeling Customer Relationships as Markov Chains,” Journal of Interactive Marketing, Vol. 14, No. 2, 43-55.
Ping, R. A., 1995, “A Parsimonious Estimating Technique for Interaction and Quadratic Latent Variables,” Journal of Marketing Research, Vol. 32, No. 3, 336-347.
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., and Podsakoff, N. P., 2003, “Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies,” Journal of Applied Psychology, Vol. 88, No. 5, 879-903.
Rao, A. R. and Monroe, K. B., 1988, “The Moderating Effect of Prior Knowledge on Cue Utilization in Product Evaluation,” Journal of Consumer Research, Vol. 15, No. 2, 253-264.
Raymond, J. E., Beard, T. R., and Gropper, D. M., 1993, “Modelling the Consumer's Decision to Replace Durable Goods: A Hazard Function Approach,” Applied Economics, Vol. 25, No. 10, 92-102.
Rhee, S. and McIntyre, S., 2008, “Including the Effects of Prior and Recent Contact Effort in a Customer Scoring Model for Database Marketing,” Journal of the Academy of Marketing Science, Vol. 36, No. 4, 538-551.
Richardson, P. S., Dick, A. S., and Jain, A. K., 1994, “Extrinsic and Intrinsic Cue Effects on Perceptions of Store Brand Quality,” Journal of Marketing, Vol. 58, No. 4, 28-36.
Rosenberg, N., 1976, Perspectives on Technology, 1st, New York: Cambridge University Press.
Strausz, R., 2009, “Planned Obsolescence as an Incentive Device for Unobservable Quality,” The Economic Journal, Vol. 119, No. 540, 1405-1421.
Valliant, R. and Dever, J. A., 2011, “Estimating Propensity Adjustments for Volunteer Web Surveys,” Sociological Methods & Research, Vol. 40, No. 1, 105-137.
Wakefield, K. L. and Baker, J., 1998, “Excitement at the Mall: Determinants and Effects on Shopping Response,” Journal of Retailing, Vol. 74, No. 4, 515-539.
Walsh, G., Evanschitzky, H., and Wunderlich, M., 2008, “Identification and Analysis of Moderator Variables: Investigating the Customer Satisfaction‐Loyalty Link,” European Journal of Marketing, Vol. 42, No. 9/10, 977-1004.
Williams, L. J. and Hazer, J. T., 1986, “Antecedents and Consequences of Organizational Turnover: A Reanalysis Using a Structural Equations Model,” Journal of Applied Psychology, Vol. 71, No. 2, 219-231.
Yoon, C., 1997, “Age Differences in Consumers’ Processing Strategies: An Investigation of Moderating Influences,” Journal of Consumer Research, Vol. 24, No. 3, 329-342.
Zenith, 2018, “Smartphone penetration to reach 66% in 2018,”
https://www.zenithmedia.com/smartphone-penetration-reach-66-2018/, accessed on August 5, 2018.