IDEAS home Printed from https://ideas.repec.org/a/spr/custns/v8y2021i1d10.1007_s40547-020-00112-7.html
   My bibliography  Save this article

Adaptive Multidimensional Scaling: Brand Positioning Based on Decision Sets and Dissimilarity Judgments

Author

Listed:
  • Tammo H.A. Bijmolt

    (University of Groningen)

  • Michel Wedel

    (University of Maryland)

  • Wayne S. DeSarbo

    (Pennsylvania State University)

Abstract

Assessing market structure by deriving a brand positioning map and segmenting customers is essential for supporting brand-related marketing decisions. We propose adaptive multidimensional scaling (ADMDS) for simultaneously deriving a brand positioning map and market segments using customer data on cognitive decision sets and brand dissimilarities. In ADMDS, the judgment task is adapted to the individual customer where dissimilarity judgments are collected only for those brands within a customers’ awareness set. Thus, respondent fatigue and unfamiliarity with the brands are circumvented thereby improving the validity of the dissimilarity data obtained, as well as the multidimensional spatial structure derived from them. Estimation of the ADMDS model results in a spatial map in which the brands and derived segments of customers are jointly represented as points. The closer a brand is positioned to a segment’s ideal brand, the higher the probability that the brand is considered and chosen. An assumption underlying this model representation is that brands within a customers’ consideration set are relatively similar. In an experiment with 200 respondents and 4 product categories, this assumption is validated. We illustrate adaptive multidimensional scaling model on commercial data for 20 midsize car brands evaluated by 212 members of an on-line consumer panel. Potential applications of the method and future research opportunities are discussed.

Suggested Citation

  • Tammo H.A. Bijmolt & Michel Wedel & Wayne S. DeSarbo, 2021. "Adaptive Multidimensional Scaling: Brand Positioning Based on Decision Sets and Dissimilarity Judgments," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 8(1), pages 1-15, June.
    • Handle: RePEc:spr:custns:v:8:y:2021:i:1:d:10.1007_s40547-020-00112-7
    DOI: 10.1007/s40547-020-00112-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40547-020-00112-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40547-020-00112-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nedungadi, Prakash, 1990. "Recall and Consumer Consideration Sets: Influencing Choice without Altering Brand Evaluations," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 17(3), pages 263-276, December.
    2. Moon, Sangkil & Kamakura, Wagner A., 2017. "A picture is worth a thousand words: Translating product reviews into a product positioning map," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 265-285.
    3. J. Ramsay, 1980. "The joint analysis of direct ratings, pairwise preferences, and dissimilarities," Psychometrika, Springer;The Psychometric Society, vol. 45(2), pages 149-165, June.
    4. Wayne S. Desarbo & Kamel Jedidi, 1995. "The Spatial Representation of Heterogeneous Consideration Sets," Marketing Science, INFORMS, vol. 14(3), pages 326-342.
    5. Wayne DeSarbo & Venkatram Ramaswamy & Peter Lenk, 1993. "A latent class procedure for the structural analysis of two-way compositional data," Journal of Classification, Springer;The Classification Society, vol. 10(2), pages 159-193, December.
    6. Giana Eckhardt & Luming Wang, 2015. "The Multidimensional Nature of Product Perceptions within Asia," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(4), pages 290-301, December.
    7. Ian Spence & Dennis Domoney, 1974. "Single subject incomplete designs for nonmetric multidimensional scaling," Psychometrika, Springer;The Psychometric Society, vol. 39(4), pages 469-490, December.
    8. Elisabeth Honka & Ali Hortaçsu & Maria Ana Vitorino, 2017. "Advertising, consumer awareness, and choice: evidence from the U.S. banking industry," RAND Journal of Economics, RAND Corporation, vol. 48(3), pages 611-646, August.
    9. Tammo Bijmolt & Michel Velden, 2012. "Multiattribute perceptual mapping with idiosyncratic brand and attribute sets," Marketing Letters, Springer, vol. 23(3), pages 585-601, September.
    10. Ho, Ying & Chung, Yuho & Lau, Kin-nam, 2010. "Unfolding large-scale marketing data," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 119-132.
    11. James Agarwal & Wayne DeSarbo & Naresh K. Malhotra & Vithala Rao, 2015. "An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 19-40, March.
    12. Joachim Büschken & Thomas Otter & Greg M. Allenby, 2013. "The Dimensionality of Customer Satisfaction Survey Responses and Implications for Driver Analysis," Marketing Science, INFORMS, vol. 32(4), pages 533-553, July.
    13. Wedel, Michel & DeSarbo, Wayne S, 1996. "An Exponential-Family Multidimensional Scaling Mixture Methodology," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 447-459, October.
    14. Rex Green & Peter Bentler, 1979. "Improving the efficiency and effectiveness of interactively selected MDS data designs," Psychometrika, Springer;The Psychometric Society, vol. 44(1), pages 115-119, March.
    15. Suzanne Winsberg & Geert Soete, 1993. "A latent class approach to fitting the weighted Euclidean model, clascal," Psychometrika, Springer;The Psychometric Society, vol. 58(2), pages 315-330, June.
    16. Kardes, Frank R, et al, 1993. "Brand Retrieval, Consideration Set Composition, Consumer Choice, and the Pioneering Advantage," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(1), pages 62-75, June.
    17. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    18. Wayne DeSarbo & Donald Lehmann & Gregory Carpenter & Indrajit Sinha, 1996. "A stochastic multidimensional unfolding approach for representing phased decision outcomes," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 485-508, September.
    19. Wayne DeSarbo & Joonwook Park & Vithala Rao, 2011. "Deriving joint space positioning maps from consumer preference ratings," Marketing Letters, Springer, vol. 22(1), pages 1-14, March.
    20. Wayne DeSarbo & Rabikar Chatterjee & Juyoung Kim, 1994. "Deriving ultrametric tree structures from proximity data confounded by differential stimulus familiarity," Psychometrika, Springer;The Psychometric Society, vol. 59(4), pages 527-566, December.
    21. Kamel Jedidi & Wayne DeSarbo, 1991. "A stochastic multidimensional scaling procedure for the spatial representation of three-mode, three-way pick any/J data," Psychometrika, Springer;The Psychometric Society, vol. 56(3), pages 471-494, September.
    22. Hauser, John R & Wernerfelt, Birger, 1990. "An Evaluation Cost Model of Consideration Sets," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 16(4), pages 393-408, March.
    23. Yoshio Takane, 1981. "Multidimensional successive categories scaling: A maximum likelihood method," Psychometrika, Springer;The Psychometric Society, vol. 46(1), pages 9-28, March.
    24. Joseph Zinnes & David MacKay, 1983. "Probabilistic multidimensional scaling: Complete and incomplete data," Psychometrika, Springer;The Psychometric Society, vol. 48(1), pages 27-48, March.
    25. Ratneshwar, S & Pechmann, Cornelia & Shocker, Allan D, 1996. "Goal-Derived Categories and the Antecedents of Across-Category Consideration," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 23(3), pages 240-250, December.
    26. Desai, Kalpesh Kaushik & Hoyer, Wayne D, 2000. "Descriptive Characteristics of Memory-Based Consideration Sets: Influence of Usage Occasion Frequency and Usage Location Familiarity," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 27(3), pages 309-323, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alzate, Miriam & Arce-Urriza, Marta & Cebollada, Javier, 2022. "Mining the text of online consumer reviews to analyze brand image and brand positioning," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bijmolt, T.H.A. & Wedel, M. & DeSarbo, W.S., 2002. "Adaptive Multidimensional Scaling : The Spatial Representation of Brand Consideration and Dissimilarity Judgments," Discussion Paper 2002-82, Tilburg University, Center for Economic Research.
    2. Bijmolt, T.H.A. & Wedel, M. & DeSarbo, W.S., 2002. "Adaptive Multidimensional Scaling : The Spatial Representation of Brand Consideration and Dissimilarity Judgments," Other publications TiSEM 26b65f04-0d5f-42d6-8a85-8, Tilburg University, School of Economics and Management.
    3. Desmichel, Perrine & Kocher, Bruno, 2020. "Luxury Single- versus Multi-Brand Stores: The Effect of Consumers’ Hedonic Goals on Brand Comparisons," Journal of Retailing, Elsevier, vol. 96(2), pages 203-219.
    4. Vishal Bindroo & Xin He & Raj Echambadi, 2016. "Satisfaction—Repurchase Intentions Relationship: Exploring the Contingent Roles of Consideration Set Size and Price Consciousness," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 3(3), pages 115-125, December.
    5. Jianan Wu & Arvind Rangaswamy, 2003. "A Fuzzy Set Model of Search and Consideration with an Application to an Online Market," Marketing Science, INFORMS, vol. 22(3), pages 411-434, March.
    6. Manash Pratim Kashyap, 2011. "Brand Categorization Process for Staple Goods: Comparison between Rural and Urban Customers," Information Management and Business Review, AMH International, vol. 2(4), pages 162-172.
    7. Dawn Iacobucci & Doug Grisaffe & Wayne DeSarbo, 2017. "Statistical perceptual maps: using confidence region ellipses to enhance the interpretations of brand positions in multidimensional scaling," Journal of Marketing Analytics, Palgrave Macmillan, vol. 5(3), pages 81-98, December.
    8. Chadwick J. Miller & Daniel C. Brannon & Jim Salas & Martha Troncoza, 2021. "Advertising, incentives, and the upsell: how advertising differentially moderates customer- vs. retailer-directed price incentives’ impact on consumers’ preferences for premium products," Journal of the Academy of Marketing Science, Springer, vol. 49(6), pages 1043-1064, November.
    9. Hauser, John R., 2014. "Consideration-set heuristics," Journal of Business Research, Elsevier, vol. 67(8), pages 1688-1699.
    10. Nenycz-Thiel, Magda & Sharp, Byron & Dawes, John & Romaniuk, Jenni, 2010. "Competition for memory retrieval between private label and national brands," Journal of Business Research, Elsevier, vol. 63(11), pages 1142-1147, November.
    11. Jooa Baek & Jaeseok Lee, 2021. "A Conceptual Framework on Reconceptualizing Customer Share of Wallet (SOW): As a Perspective of Dynamic Process in the Hospitality Consumption Context," Sustainability, MDPI, vol. 13(3), pages 1-11, January.
    12. Duncan Fong & Wayne DeSarbo & Zhe Chen & Zhuying Xu, 2015. "A Bayesian Vector Multidimensional Scaling Procedure Incorporating Dimension Reparameterization with Variable Selection," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 1043-1065, December.
    13. Tobias Reckmann, 2017. "Verwendung von Word of Mouth-Daten zur Identifikation von Asymmetrie im Wettbewerb: Eine textbasierte Analyse am Beispiel deutscher Automobilmarken [Identification of asymmetric competition by usin," Schmalenbach Journal of Business Research, Springer, vol. 69(2), pages 173-201, June.
    14. Anocha Aribarg & Thomas Otter & Daniel Zantedeschi & Greg M. Allenby & Taylor Bentley & David J. Curry & Marc Dotson & Ty Henderson & Elisabeth Honka & Rajeev Kohli & Kamel Jedidi & Stephan Seiler & X, 2018. "Advancing Non-compensatory Choice Models in Marketing," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 82-92, March.
    15. Michael J. Barone & Alexander Fedorikhin & David E. Hansen, 2017. "The influence of positive affect on consideration set formation in memory-based choice," Marketing Letters, Springer, vol. 28(1), pages 59-69, March.
    16. Wayne DeSarbo & Donald Lehmann & Gregory Carpenter & Indrajit Sinha, 1996. "A stochastic multidimensional unfolding approach for representing phased decision outcomes," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 485-508, September.
    17. Elisabeth Honka & Pradeep Chintagunta, 2017. "Simultaneous or Sequential? Search Strategies in the U.S. Auto Insurance Industry," Marketing Science, INFORMS, vol. 36(1), pages 21-42, January.
    18. Francisco Silva & Samir Mamadehussene, 2020. "The Equivalence Between Sequential and Simultaneous Firm Decisions," Documentos de Trabajo 541, Instituto de Economia. Pontificia Universidad Católica de Chile..
    19. Nitin Mehta & Surendra Rajiv & Kannan Srinivasan, 2003. "Price Uncertainty and Consumer Search: A Structural Model of Consideration Set Formation," Marketing Science, INFORMS, vol. 22(1), pages 58-84, June.
    20. Helmers, Christian & Krishnan, Pramila & Patnam, Manasa, 2019. "Attention and saliency on the internet: Evidence from an online recommendation system," Journal of Economic Behavior & Organization, Elsevier, vol. 161(C), pages 216-242.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:custns:v:8:y:2021:i:1:d:10.1007_s40547-020-00112-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.