Customizing a product by choosing each of its attributes individually tends to be onerous for consumers, and the benefits of product customization may thus be offset by an increase in choice complexity. As a remedy for this dilemma, the current research introduces the customization via starting solutions (CvSS) architecture, which substantially reduces the complexity of product customization while preserving all of its advantages. Under CvSS, consumers first select one starting solution from a set of prespecified products, which they then refine to create their final customized product. Evidence from nine studies (three of which were conducted in field settings) across a wide range of product domains (shirts, cars, vacation packages, jewelry, and financial products) shows that the CvSS architecture results in substantial benefits relative to the standard attribute-by-attribute product customization format for both consumers (increased satisfaction with their product choices, reduced choice complexity, and enhanced mental simulation of product use) and firms (purchases of more feature-rich, and thus higher-priced, products).
AlterAdam L. and OppenheimerDaniel M. (2006), “Predicting Short-Term Stock Fluctuations by Using Processing Fluency,”Proceedings of the National Academy of Sciences of the United States of America, 103(24), 9369– 72.
2.
AndrewsRick L. and CurrimImran S. (2009), “Multi-Stage Purchase Decision Models: Accommodating Response Heterogeneity, Common Demand Shocks, and Endogeneity Using Disaggregate Data,”International Journal of Research in Marketing, 26(3), 197– 206.
3.
AnsariAsim and MelaCarl F. (2003), “E-Customization,”Journal of Marketing Research, 40(May), 131– 45.
4.
ArielyDan and NortonMichael I. (2009), “Conceptual Consumption,”Annual Review of Psychology, 60, 475– 99.
5.
BagozziRichard P., YiYoujae, and PhillipsLynn W. (1991), “Assessing Construct Validity in Organizational Research,”Administrative Science Quarterly, 36(3), 421– 58.
6.
BeachLee Roy (1993), “Broadening the Definition of Decision Making: The Role of Prechoice Screening of Options,”Psychological Science, 4(4), 215– 20.
7.
BensonLehmanIII, and BeachLee Roy (1996), “The Effects of Time Constraints on the Prechoice Screening of Decision Options,”Organizational Behavior and Human Decision Processes, 67(2), 222– 28.
8.
BettmanJames R. and ParkC. Whan (1980), “Effects of Prior Knowledge and Experience and Phase of the Choice Process on Consumer Decision Processes: A Protocol Analysis,”Journal of Consumer Research, 7(3), 234– 48.
9.
BottiSimona and HseeChristopher K. (2010), “Dazed and Confused by Choice: How the Temporal Costs of Choice Freedom Lead to Undesirable Outcomes,”Organizational Behavior and Human Decision Processes, 112(2), 161– 71.
10.
BrownChristina L. and KrishnaAradhna (2004), “The Skeptical Shopper: A Metacognitive Account for the Effects of Default Options on Choice,”Journal of Consumer Research, 31(3), 529– 39.
11.
ChakravartiAmitav, JaniszewskiChris, and ÜlkümenGülden (2006), “The Neglect of Prescreening Information,”Journal of Marketing Research, 43(November), 642– 53.
12.
DellaertBenedict G.C. and DabholkarPratibha A. (2009), “Increasing the Attractiveness of Mass Customization: The Role of Complementary On-Line Services and Range of Options,”International Journal of Electronic Commerce, 13(3), 43– 70.
13.
DellaertBenedict G.C., DonkersBas, and Van SoestArthur (2012), “Complexity Effects in Choice Experiment–Based Models,”Journal of Marketing Research, 49(June), 424– 34.
14.
DellaertBenedict G.C. and StremerschStefan (2005), “Marketing Mass-Customized Products: Striking a Balance Between Utility and Complexity,”Journal of Marketing Research, 42(May), 219– 27.
15.
ElderRyan S. and KrishnaAradhna (2012), “The ‘Visual Depiction Effect’ in Advertising: Facilitating Embodied Mental Simulation Through Product Orientation,”Journal of Consumer Research, 38(6), 988– 1003.
16.
ElrodTerry, JohnsonRichard D., and WhiteJoan (2004), “A New Integrated Model of Noncompensatory and Compensatory Decision Strategies,”Organizational Behavior and Human Decision Processes, 95(1), 1– 19.
17.
EngelAndreas K., FriesPascal, and SingerWolf (2001), “Dynamic Predictions: Oscillations and Synchrony in Top-Down Processing,”Nature Reviews Neuroscience, 2(10), 704– 716.
18.
EscalasJennifer Edson (2004), “Imagine Yourself in the Product: Mental Simulation, Narrative Transportation, and Persuasion,”Journal of Advertising, 33(2), 37– 48.
19.
EscalasJennifer Edson and LuceMary Frances (2003), “Process Versus Outcome Thought Focus and Advertising,”Journal of Consumer Psychology, 13(3), 246– 54.
20.
FlynnLeisa Reinecke and GoldsmithRonald E. (1999), “A Short, Reliable Measure of Subjective Knowledge,”Journal of Business Research, 46(1), 57– 66.
21.
FornellClaes and LarckerDavid F. (1981), “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error,”Journal of Marketing Research, 18(February), 39– 50.
22.
FrankeNikolaus and PillerFrank (2004), “Value Creation by Toolkits for User Innovation and Design: The Case of the Watch Market,”Journal of Product Innovation Management, 21(6), 401– 415.
23.
FrankeNikolaus and SchreierMartin (2010), “Why Customers Value Self- Designed Products: The Importance of Process Effort and Enjoyment,”Journal of Product Innovation Management, 27(7), 1020– 31.
24.
FrankeNikolaus, SchreierMartin, and KaiserUlrike (2010), “The ‘I Designed It Myself’ Effect in Mass Customization,”Management Science, 56(1), 125– 40.
25.
GalottiKathleen M. (2007), “Decision Structuring in Important Real-Life Choices,”Psychological Science, 18(4), 320– 25.
26.
GeXin, HäublGerald, and ElrodTerry (2012), “What to Say When: Influencing Consumer Choice by Delaying the Presentation of Favorable Information,”Journal of Consumer Research, 38(6), 1004– 1021.
27.
GoldsteinDaniel G., JohnsonEric J., HerrmannAndreas, and HeitmannMark (2008), “Nudge Your Customers Toward Better Choices,”Harvard Business Review, 86(12), 99– 105.
28.
GoodaleMelvyn A. and MilnerA. David (1992), “Separate Visual Pathways for Perception and Action,”Trends in Neurosciences, 15(1), 20– 25.
29.
GregoryW. Larry, CialdiniRobert B., and CarpenterKathleen M. (1982), “Self-Relevant Scenarios as Mediators of Likelihood Estimates and Compliance: Does Imagining Make It So?”Journal of Personality and Social Psychology, 43(1), 89– 99.
30.
HäublGerald and TriftsValerie (2000), “Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids,”Marketing Science, 19(1), 4– 21.
31.
HauserJohn R. and WernerfeltBirger (1990), “An Evaluation Cost Model of Consideration Sets,”Journal of Consumer Research, 16(4), 393– 408.
32.
HerrmannAndreas, HildebrandChristian, SprottDavid E., and SpangenbergEric R. (2013), “Option Framing and Product Feature Recommendations: Product Configuration and Choice,”Psychology & Marketing, 30(12), 1053– 61.
33.
HomburgChristian, KoschateNicole, and HoyerWayne D. (2005), “Do Satisfied Customers Really Pay More? A Study of the Relationship Between Customer Satisfaction and Willingness to Pay,”Journal of Marketing, 69(April), 84– 96.
34.
HuffmanCynthia and KahnBarbara E. (1998), “Variety for Sale: Mass Customization or Mass Confusion?”Journal of Retailing, 74(4), 491– 513.
35.
InmanJ. Jeffrey and ZeelenbergMarcel (2002), “Regret in Repeat Purchase Versus Switching Decisions: The Attenuating Role of Decision Justifiability,”Journal of Consumer Research, 29(1), 116– 28.
36.
JaniszewskiChris (1993), “Preattentive Mere Exposure Effects,”Journal of Consumer Research, 20(3), 376– 92.
KahnemanDaniel and TverskyAmos (1984), “Choices, Values, and Frames,”American Psychologist, 39(4), 341– 50.
39.
LabrooAparna A., DharRavi, and SchwarzNorbert (2008), “Of Frog Wines and Frowning Watches: Semantic Priming, Perceptual Fluency, and Brand Evaluation,”Journal of Consumer Research, 34(6), 819– 31.
40.
LambertonCait Poynor and DiehlKristin (2013), “Retail Choice Architecture: The Effects of Benefit- and Attribute-Based Assortment Organization on Consumer Perceptions and Choice,”Journal of Consumer Research, 40(3), 393– 411.
41.
LauAntonio K.W., YamRichard C.M., and TangEsther (2011), “The Impact of Product Modularity on New Product Performance: Mediation by Product Innovativeness,”Journal of Product Innovation Management, 28(2), 270– 84.
42.
LeeAngela Y. and LabrooAparna A. (2004), “The Effect of Conceptual and Perceptual Fluency on Brand Evaluation,”Journal of Marketing Research, 41(May), 151– 65.
43.
LevavJonathan, HeitmannMark, HerrmannAndreas, and IyengarSheena S. (2010), “Order in Product Customization Decisions: Evidence from Field Experiments,”Journal of Political Economy, 118(2), 274– 99.
44.
MatzlerKurt, StiegerDaniel, and FüllerJohann (2011), “Consumer Confusion in Internet-Based Mass Customization: Testing a Network of Antecedents and Consequences,”Journal of Consumer Policy, 34(2), 231– 47.
45.
MontgomeryHenry (1994), “Towards a Perspective Theory of Decision Making and Judgment,”Acta Psychologica, 87(2/3), 155– 78.
46.
NormanJoel (2002), “Two Visual Systems and Two Theories of Perception: An Attempt to Reconcile the Constructivist and Ecological Approaches,”Behavioral and Brain Sciences, 25(1), 73– 96.
47.
NortonMichael I., MochonDaniel, and ArielyDan (2012), “The IKEA Effect: When Labor Leads to Love,”Journal of Consumer Psychology, 22(3), 453– 60.
48.
ParkWhan C., JunSung Y., and MacInnisDeborah J. (2000), “Choosing What I Want Versus Rejecting What I Do Not Want: An Application of Decision Framing to Product Option Choice Decisions,”Journal of Marketing Research, 37(May), 187– 202.
49.
PreacherKristopher J. and HayesAndrew F. (2008), “Asymptotic and Resampling Strategies for Assessing and Comparing Indirect Effects in Multiple Mediator Models,”Behavior Research Methods, 40(3), 879– 91.
50.
RichmondSandra M., BissellByron L., and BeachLee Roy (1998), “Image Theory's Compatibility Test and Evaluations of the Status Quo,”Organizational Behavior and Human Decision Processes, 73(1), 39– 53.
51.
RobertsJohn H. and LattinJames M. (1991), “Development and Testing of a Model of Consideration Set Composition,”Journal of Marketing Research, 28(November), 429– 40.
52.
SaatyThomas L. (1987), “A New Macroeconomic Forecasting and Policy Evaluation Method Using the Analytic Hierarchy Process,”Mathematical Modelling, 9(3/5), 219– 31.
53.
SimonsonItamar (2005), “Determinants of Customers' Responses to Customized Offers: Conceptual Framework and Research Propositions,”Journal of Marketing, 69(January), 32– 45.
54.
SmithN. Craig, GoldsteinDaniel G., and JohnsonEric J. (2013), “Choice Without Awareness: Ethical and Policy Implications of Defaults,”Journal of Public Policy & Marketing, 32(Fall), 159– 72.
55.
TanWee-Kek, TanChuan-Hoo, and TeoHock-Hai (2012), “Consumer-Based Decision Aid That Explains Which to Buy: Decision Confirmation or Overconfidence Bias?”Decision Support Systems, 53(1), 127– 41.
56.
ThalerRichard H. and SunsteinCass R. (2008), Nudge: Improving Decisions About Health, Wealth, and Happiness, Style. London: Penguin Group.
57.
ThompsonDebora V., HamiltonRebecca W., and PetrovaPetia K. (2009), “When Mental Simulation Hinders Behavior: The Effects of Process-Oriented Thinking on Decision Difficulty and Performance,”Journal of Consumer Research, 36(4), 562– 74.
58.
ThompsonDebora V., HamiltonRebecca W., and RustRoland T. (2005), “Feature Fatigue: When Product Capabilities Become Too Much of a Good Thing,”Journal of Marketing Research, 42(November), 431– 42.
59.
ThompsonDebora V. and NortonMichael I. (2011), “The Social Utility of Feature Creep,”Journal of Marketing Research, 48(June), 555– 65.
60.
TomasinoBarbara, CeschiaMartina, FabbroFranco, and SkrapMiran (2012), “Motor Simulation During Action Word Processing in Neurosurgical Patients,”Journal of Cognitive Neuroscience, 24(3), 736– 48.
61.
ValenzuelaAna, DharRavi, and ZettelmeyerFlorian (2009), “Contingent Response to Self-Customization Procedures: Implications for Decision Satisfaction and Choice,”Journal of Marketing Research, 46(December), 754– 63.
62.
Von HippelEric (1994), “‘Sticky Information’ and the Locus of Problem Solving: Implications for Innovation,”Management Science, 40(4), 429– 39.
63.
Von HippelEric and KatzRalph (2002), “Shifting Innovation to Users via Toolkits,”Management Science, 48(7), 821– 33.
64.
WhitePeter A. (2012), “The Experience of Force: The Role of Haptic Experience of Forces in Visual Perception of Object Motion and Interactions, Mental Simulation, and Motion-Related Judgments,”Psychological Bulletin, 138(4), 589– 615.
65.
ZhaoMin, HoefflerSteve, and ZaubermanGal (2011), “Mental Simulation and Product Evaluation: The Affective and Cognitive Dimensions of Process Versus Outcome Simulation,”Journal of Marketing Research, 48(October), 827– 39.
66.
ZipkinPaul (2001), “The Limits of Mass Customization,”MIT Sloan Management Review, 42(3), 81– 87.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
