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Managerial applicability of graphical formats to support positioning decisions

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Abstract

Issues of segmentation and positioning have always been at the heart of marketing management. In recent years, much methodological progress has been made in order to carry out these two tasks simultaneously, that is, to combine certain types of clustering algorithms with appropriate multidimensional scaling or unfolding procedures. When trying to provide managers with a tool to support marketing decision-making in segmentation and positioning, the ease of use and the visual quality of results must be emphasized. This paper provides a state-of-the-art review of alternative graphical formats designed to assist strategic management. It focuses on three aspects, namely, (I) representing competitive market structures, (II) illustrating preferences for product attributes, and (III) describing customer heterogeneity at the individual as well as segment-specific levels; this paper also explores the interrelations among these aspects. The benefits and limitations of different approaches are discussed, and graphical examples are provided. Advances in academic research are contrasted with the information requirements of marketing managers. Finally, recommendations on the applicability of these alternatives for practical use are offered, and issues for further research are specified.

Zusammenfassung

Seit jeher sind Entscheidungen betreffend die Segmentierung eines Marktes sowie die Positionierung des eigenen Angebots in der Wahrnehmung der Kunden Kernaufgaben des Marketingmanagements. In jüngster Zeit gelangen substanzielle algorithmische Fortschritte, die es erlauben, diese beiden Aufgaben gleichzeitig zu lösen, mit anderen Worten, Clusterverfahren (zur Segmentierung) mit mehrdimensionalen Skalierungstechniken (zur Positionierung) zu verbinden. Erfahrungsgemäß werden solche methodischen Entwicklungen nur dann von der Praxis als Hilfsmittel angenommen, wenn sie leicht zu verwenden und ihre Ergebnisse in graphisch ansprechender und intuitiv interpretierbarer Form darstellbar sind. Dieser Beitrag gibt eine Übersicht über den derzeitigen Stand der Wissenschaft und unterscheidet dabei zwischen den drei Aspekten (I) der Darstellung der Wettbewerbsstruktur zwischen den Anbietern, (II) der Berücksichtigung der Präferenzen für einzelne (Produkt-) Attribute sowie (III) der individuellen und segmentspezifischen Heterogenität der Nachfrager. Dabei werden insbesondere die verschiedenen Möglichkeiten zur graphischen Aufbereitung der Ergebnisse präsentiert und die Vorteile sowie die Einschränkungen der Methoden aufgezeigt. Schließlich gibt der Aufsatz einige Empfehlungen bezüglich der Verwertbarkeit der Modelle in der Marketingpraxis und zeigt Möglichkeiten zu zukünftigen Forschungsbemühungen auf.

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References

  • Andrews RL, Brusco MJ, Currim IS (2009) Amalgamation of partitions from multiple segmentation bases: a comparison of non-model-based and model-based methods. Eur J Oper Res (in press)

  • Arabie P, Carroll JD (1980) MAPCLUS: a mathematical programming approach to fitting the ADCLUS Model. Psychometrika 45(2):211–235

    Article  Google Scholar 

  • Arabie P, Carroll JD, DeSarbo WS, Wind Y (1981) Overlapping clustering: a new method for product positioning. J Mark Res 18(3):310–317

    Article  Google Scholar 

  • Bennett JF, Hays WL (1960) Multidimensional unfolding: determining the dimensionality of ranked preference data. Psychometrika 25(1):27–43

    Article  Google Scholar 

  • Bimler D, Kirkland J (1998) Perceptual modelling of product similarities using sorting data. Mark Bull 9:16–27

    Google Scholar 

  • Böckenholt I, Gaul W (1986) Analysis of choice behavior via probabilistic ideal point and vector models. Appl Stoch Models Data Anal 2(4):209–226

    Article  Google Scholar 

  • Borg I, Groenen PJF (2005) Modern multidimensional scaling: theory and applications. Springer, New York

    Google Scholar 

  • Busing FMTA, Groenen PJK, Heiser WJ (2005) Avoiding degeneracy in multidimensional unfolding by penalizing on the coefficient of variation. Psychometrika 70(1):71–98

    Article  Google Scholar 

  • Carroll JD, Chang JJ (1968) How to use MDPREF, a computer program for multidimensional analysis of preference data. Murray Hill, London

    Google Scholar 

  • Carroll JD, Green PE (1997) Psychometrik methods in marketing research: Part II, Multidimensional scaling. J Mark Res 29(2):193–204

    Article  Google Scholar 

  • Carroll JD, Arabie P, Chaturvedi A, Hubert L (2004) Multidimensional scaling and clustering in marketing: Paul Green’s role. In: Wind Y, Green PE (eds) Market research and modeling: progress and prospects: a tribute to Paul E. Green. Springer, New York, pp 71–102

    Google Scholar 

  • Coombs CH (1950) Psychological scaling without a unit of measurement. Psychol Rev 57(3):148–158

    Article  Google Scholar 

  • Coombs CH (1964) A theory of data. Wiley, New York

    Google Scholar 

  • Cui D, Curry D (2005) Prediction in marketing using the support vector machine. Market Sci 24(4):595–615

    Article  Google Scholar 

  • Danneels E (1996) Market segmentation: normative model versus business reality, an exploratory study of apparel retailing in Belgium. Eur J Mark 30(6):36–51

    Article  Google Scholar 

  • Day GS, Shocker AD, Srivastava RK (1979) Customer-orientated approaches to identifying product markets. J Mark 43(4):8–19

    Article  Google Scholar 

  • DeSarbo WS, Rao VR (1984) GENFOLD2, a set of models and algorithms for the general unfolding analysis of preference/dominance data. J Class 1:147–186

    Google Scholar 

  • DeSarbo WS, Rao VR (1986) A constrained unfolding methodology for product positioning. Mark Sci 5(1):1–19

    Article  Google Scholar 

  • DeSarbo WS, Jedidi K, Cool K, Schendel D (1990) Simultaneous multidimensional unfolding and cluster analysis: an investigation of strategic groups. Mark Lett 2(2):129–146

    Article  Google Scholar 

  • DeSarbo WS, Howard DJ, Jedidi K (1991) MULTICLUS: a new method for simultaneously performing multidimensional scaling and cluster analysis. Psychometrika 56(1):121–136

    Article  Google Scholar 

  • DeSarbo WS, Manrai AK, Manrai LK (1993) Non-spatial tree models for the assessment of competitive market structure: an integrated review of the marketing and psychometric literature. In: Eliashberg J, Lilien GL (eds) Handbooks in operations research and management science. North-Holland, Amsterdam

    Google Scholar 

  • DeSarbo WS, Manrai AK, Manrai LA (1994) Latent class multidimensional scaling: a review of recent developments in the marketing and psychometric literature. In: Bagozzi RP (eds) Advanced methods of marketing research. Blackwell, Cambridge, pp 190–222

    Google Scholar 

  • DeSarbo WS, Jedidi K (1995) The spatial representation of heterogeneous consideration sets. Mark Sci 14(3):326–342

    Article  Google Scholar 

  • DeSarbo WS, Young MR, Rangaswamy A (1997) A parametric multidimensional unfolding procedure for incomplete nonmetric preference/choice set data in marketing research. J Mark Res 34(4):499–516

    Article  Google Scholar 

  • DeSarbo WS, Degeratu AM, Wedel M, Saxton MK (2001) The spatial representation of market information. Mark Sci 20(4):426–441

    Article  Google Scholar 

  • DeSarbo WS, Grewal R, Scott CJ (2008) A clusterwise bilinear multidimensional scaling methodology for simultaneous segmentation and positioning analysis. J Mark Res 45(3):280–292

    Article  Google Scholar 

  • DeSarbo WS, Grewal R, Wang R (2009) Dynamic strategic groups: deriving spatial evolutionary paths. Strat Manag J (in press)

  • Dibb S, Simkin L (1994) Implementation problems in industrial market segmentation. Ind Mark Manag 23(1):55–63

    Article  Google Scholar 

  • Dillon WR, Domzal T, Madden TJ (1986) Evaluating alternative product strategies. J Advert Res 26(4):29–35

    Google Scholar 

  • Dolnicar S (2004) Towards more thorough data-driven segmentation in tourism: a tracking framework of exploring segment development. In: Crouch GI, Perdue RR, Timmermans HJP, Uysal M (eds) Consumer psychology of tourism, hospitality and leisure. CABI Publishing, Wallingford

    Google Scholar 

  • Elrod T, Keane MP (1995) A factor-analytic probit model for repressing the market structure in panel data. J Mark Res (JMR) 32(1):1–16

    Article  Google Scholar 

  • Erdem T (1996) A dynamic analysis of market structure based on panel data. Mark Sci 15(4):359–378

    Article  Google Scholar 

  • Everitt BS, Landau S, Leese M (2001) Cluster analysis. Edward Arnold, London

    Google Scholar 

  • Green PE, Krieger AM. User’s guide to HIERMAPR: a software package for perception/preference mapping and hierarchical cluster analysis

  • Green PE, Rao VR (1972) Applied multidimensional scaling. Holt, Rinehart and Winston, New York

    Google Scholar 

  • Greenacre MJ, Blasius J (2006) Multiple correspondence analysis and related methods. Chapman-Hall, Boca Raton

    Book  Google Scholar 

  • Greenacre MJ (2007) Correspondence analysis in practice (2nd edn), Chapman-Hall/CRC Press, London

    Google Scholar 

  • Greenacre MJ (2009) Dynamic perceptual mapping. Working Paper 1153, Universitat Pompeu Fabra

  • Grover R, Srinivasan V (1987) A simultaneous approach to market segmentation and market structuring. J Mark Res 24(2):139–153

    Article  Google Scholar 

  • Hoffman DL, Franke GR (1986) Correspondence analysis: graphical representation of categorical data in marketing research. J Mark Res (JMR) 23(3):213–227

    Article  Google Scholar 

  • Holbrook MB, Moore WL (1981) Feature interactions in consumer judgements of verbal versus pictorial presentations. J Consumer Res 8(1):103–113

    Article  Google Scholar 

  • Hruschka H (1986) Market definition and segmentation using fuzzy clustering methods. Int J Res Mark 3(2):117–134

    Article  Google Scholar 

  • Hwang H, Dillon WR, Takane Y (2006) An extension of multiple correspondence analysis for identifying heterogeneous subgroups of respondents. Psychometrika 7(1):161–171

    Article  Google Scholar 

  • Inman JJ, Shankar V, Ferraro R (2004) The roles of channel-category associations and geodemographics in channel patronage. J Mark 68(1):51–71

    Article  Google Scholar 

  • Jarvenpaa SL (1989) The effect of task demands and graphical format on information processing strategies. Manag Sci 35(3):285–303

    Article  Google Scholar 

  • Kalafatis SP, Cheston V (1997) Normative models and practical applications of segmentation in business markets. Ind Mark Manag 26(6):519–530

    Article  Google Scholar 

  • Kellogg D, Chase RB (1995) Constructing an empirically derived measure of customer contact. Manag Sci 41(11):1734–1749

    Article  Google Scholar 

  • Kohonen T (1982) Self-organized formation of topologically correct feature maps. Biol Cybern 43:59–69

    Article  Google Scholar 

  • Kotler P (1989) From mass marketing to mass customization. Plann Rev, September–October:10–47

  • Kruskal JB (1964) Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika 29(1):1–27

    Article  Google Scholar 

  • Lattin JM, Carroll JD, Green PE (2003) Analyzing multivariate data. Brooks/Cole-Thomson, Pacific Grove

    Google Scholar 

  • Lilien GL, Rangaswamy A (2003) Marketing engineering: computer-assisted marketing analysis and planning. Prentice Hall, Upper Saddle River

    Google Scholar 

  • Little JDC (1970) Models and managers: the concept of a decision calculus. Manag Sci 16:L466–L485

    Article  Google Scholar 

  • Little JDC (2004) Comments on “Models and managers: the concept of a decision calculus”. Manag Sci 50(12):1854–1860

    Article  Google Scholar 

  • Marbeau Y (1998) Communication of research results. In: McDonald C, Vangelder P (eds) The ESOMAR handbook of market and opinion research. ESOMAR, Amsterdam, pp 519–552

    Google Scholar 

  • Martinez T, Schulten K (1994) Topology representing networks. Neural Net 7:507–522

    Article  Google Scholar 

  • Mazanec JA (1995) Positioning analysis with self-organizing maps: an exploratory study on luxury hotels. Cornell Hotel Restau Adm Q 36:80–95

    Google Scholar 

  • Meulman J, Heiser W, Carroll JD (1986) How to use PREFMAP3. Unpublished manuscript, AT&T Bell Laboratories

  • Moore WL, Pessemier EA (1993) Product planning and management: designing and delivering value. McGraw Hill, New York

    Google Scholar 

  • Natter M, Mild A, Wagner U, Taudes A (2008) Planning new tariffs at tele.ring: the application and impact of an integrated segmentation, targeting, and positioning tool. Mark Sci 27(4):600–609

    Article  Google Scholar 

  • Ozimec AM, Natter M, Reutterer T (2010) GIS-map based marketing decisions: can everybody get it right? Working Paper, University of Frankfurt

  • Ramaswamy V, DeSarbo WS (1990) SCULPTRE: a new methodology for deriving and analyzing hierarchical product-market structures from panel data. J Mark Res 27(4):418–427

    Article  Google Scholar 

  • Reutterer T, Natter M (2000) Segmentation based competitive analysis with MULTICLUS and topology representing networks. Comput Oper Res 27:1227–1247

    Article  Google Scholar 

  • Robinson SL, Bennett RJ (1995) A typology of deviant workplace behaviors: a multidimensional scaling study. Acad Manag J 38(2):555–572

    Article  Google Scholar 

  • Shepard RN, Arabie P (1979) Additive clustering: representation of similarities as combinations of discrete overlapping properties. Psychol Rev 86:87–123

    Article  Google Scholar 

  • Slater P (1960) Inconsistencies in a schedule of paired comparisons. Biometrika 48:303–312

    Google Scholar 

  • Sloman SA (1996) The empirical case for two systems of reasoning. Psychol Bull 119(1):3–22

    Article  Google Scholar 

  • Smelcer JB, Carmel E (1997) The effectiveness of different representations for managerial problem solving: comparing tables and maps. Decis Sci 28(2):391–420

    Article  Google Scholar 

  • Takane Y, Young FW, de Leeuw J (1977) Nonmetric individual differences multidimensional scaling: an alternating least-squares method with optimal scaling features. Psychometrika 42:7–67

    Article  Google Scholar 

  • Tegarden DP (1999) Business information visualization. Comput Assoc Inf Syst 1(4):1–37

    Google Scholar 

  • Torres A, van de Velden M (2007) Perceptual mapping of multiple variable batteries by plotting supplementary variables in correspondence analysis of rating data. Food Quality Preference 18:121–129

    Article  Google Scholar 

  • Tucker LR (1960) Intra-individual and inter-individual multidimensionality. In: Gulliksen H, Messick S (eds) Psychological scaling: theory and applications. Wiley, New York

    Google Scholar 

  • Vukasovic T (2009) Searching for competitive advantage with the aid of the brand potential index. J Product Brand Manag 18(8):165–176

    Article  Google Scholar 

  • Wedel M, DeSarbo WS (1996) An exponential-family multidimensional scaling mixture methodology. J Bus Econ Stat 14(4):447–459

    Article  Google Scholar 

  • Wedel M, Kamakura WA (1998) Market segmentation. Conceptual and methodological foundations. Kluwer Academic, Dordrecht

    Google Scholar 

  • Wernerfelt B (1984) A resource-based view of the firm. Strat Manag J 5(2):171–180

    Article  Google Scholar 

  • Wind Y, Cardoza R (1974) Industrial market segmentation. Ind Mark Manag 3(2):153–166

    Article  Google Scholar 

  • Wu J, DeSarbo WS, Chen P-J, Fu Y-Y (2006) A latent structure factor analytic approach for customer satisfaction measurement. Mark Lett 17:221–238

    Article  Google Scholar 

  • Young MR, DeSarbo WS (1995) A parametric procedure for ultrametric tree estimation from conditional rank order proximity data. Psychometrika 60(1):47–75

    Article  Google Scholar 

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Authors and Affiliations

  1. Competence Particle Strategy & Marketing, Detecon International GmbH, Oberkasseler Straße 2, 53227, Bonn, Germany

    Britta Cornelius

  2. Chair of Marketing, University of Vienna, Brünnerstraße 72, 1210, Vienna, Austria

    Udo Wagner

  3. Strothoff-Chair of Retailing, University of Frankfurt, Grüneburgplatz 1, 60323, Frankfurt am Main, Germany

    Martin Natter

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  1. Britta Cornelius
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  2. Udo Wagner
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  3. Martin Natter
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Correspondence to Britta Cornelius.

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Cornelius, B., Wagner, U. & Natter, M. Managerial applicability of graphical formats to support positioning decisions. J Betriebswirtsch 60, 167–201 (2010). https://doi.org/10.1007/s11301-010-0061-y

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