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Consumer Preferences for Mass Customization


  • Dellaert, B.G.C.
  • Stremersch, S.


Increasingly, firms adopt mass customization, which allows consumers to customize products by self-selecting their most preferred composition of the product for a predefined set of modules. For example, PC vendors such as Dell allow customers to customize their PC by choosing the type of processor, memory size, monitor, etc. However, how such firms configure the mass customization process determines the utility a consumer may obtain or the complexity a consumer may face in the mass customization task. Mass customization configurations may differ in four important ways – we take the example of the personal computer industry. First, a firm may offer few or many product modules that can be mass customized (e.g., only allow consumers to customize memory and processor of a PC or allow consumers to customize any module of the PC) and few or many levels among which to choose per mass customizable module (e.g., for mass customization of the processor, only two or many more processing speeds are available). Second, a firm may offer the consumer a choice only between very similar module levels (e.g., a 17” or 18” screen) or between very different module levels (e.g., a 15” or 21” screen). Third, a firm may individually price the modules within a mass customization configuration (e.g., showing the price of the different processors the consumer may choose from) along with pricing the total product, or the firm may show only the total product price (e.g., the price of the different processors is not shown, but only the computer’s total price is shown). Fourth, the firm may show a default version (e.g., for the processor, the configuration contains a pre-selected processing speed, which may be a high-end or low-end processor), which consumers may then customize, or the firm may not show a default version and let consumers start from scratch in composing the product. The authors find that the choices that firms make in configuring the mass customization process affect the product utility consumers can achieve in mass customization. The reason is that the mass customization configuration affects how closely the consumer may approach his or her ideal product by mass customizing. Mass customization configurations also affect consumers’ perception of the complexity of mass customization as they affect how many cognitive steps a consumer needs to make in the decision process. Both product utility and complexity in the end determine the utility consumers derive from using a certain mass customization configuration, which in turn will determine main outcome variables for marketers, such as total product sales, satisfaction with the product and the firm, referral behavior and loyalty. The study offers good news for those who wish to provide many mass customization options to consumers, because we find that within the rather large range of modules and module levels we manipulated in this study, consumers did not perceive significant increases in complexity, while they were indeed able to achieve higher product utility. Second, our results imply that firms when increasing the number of module levels, should typically offer consumers more additional options in the most popular range of a module and less additional options at the extremes. Third, pricing should preferably be presented only at the total product level, rather than at the module and product level. We find that this approach reduces complexity and increases product utility. Fourth, firms should offer a default version that consumers can use as a starting point for mass customization, as doing so minimizes the complexity to consumers. The best default version to start out with is a base default version because this type of default version allows the consumer to most closely approach his or her ideal product. The reason is that consumers when presented with an advanced default may buy a product that is more advanced than they actually need. We also found that expert consumers are ideal targets for mass customization offerings. Expert consumers experience lower complexity in mass customization and complexity has a less negative influence on product utility obtained in the mass customization process, all compared to novice consumers. In general, reducing complexity in the mass customization configuration is a promising strategy for firms as it not only increases the utility of the entire process for consumers, but also allows them to compose products that more closely fit their ideal product.

Suggested Citation

  • Dellaert, B.G.C. & Stremersch, S., 2004. "Consumer Preferences for Mass Customization," ERIM Report Series Research in Management ERS-2004-087-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:1804

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    References listed on IDEAS

    1. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, September.
    2. Heath, Timothy B, et al, 2000. "Asymmetric Competition in Choice and the Leveraging of Competitive Disadvantages," Journal of Consumer Research, Oxford University Press, vol. 27(3), pages 291-308, December.
    3. Amos Tversky & Daniel Kahneman, 1991. "Loss Aversion in Riskless Choice: A Reference-Dependent Model," The Quarterly Journal of Economics, Oxford University Press, vol. 106(4), pages 1039-1061.
    4. Subimal Chatterjee & Timothy B. Heath, 1996. "Conflict and Loss Aversion in Multiattribute Choice: The Effects of Trade-Off Size and Reference Dependence on Decision Difficulty," Post-Print hal-00670460, HAL.
    5. Timothy B. Heath & Gangseog Ryu & Subimal Chatterjee & Michael S. Mccarthy & David L. Mothersbaugh & Sandra J. Milberg & Gary J. Gaeth, 2000. "Asymmetric Competition in Choice and the Leveraging of Competitive Disadvantages," Post-Print hal-00668916, HAL.
    6. Alba, Joseph W & Hutchinson, J Wesley, 1987. "Dimensions of Consumer Expertise," Journal of Consumer Research, Oxford University Press, vol. 13(4), pages 411-454, March.
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    More about this item


    PC buying; complexity; consumer choice; customization; mass customization; mass customized products; operations research; utility;

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics

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