Parce que le marketing est en grande partie relationnel, les méthodes de réseaux s'avèrent être des outils importants et appropriés pour étudier des structures d'interconnexions. Dans cet article, nous modélisons des données qui représentent des changements de marque par des consommateurs sur les marchés automobiles français et britannique. Nous décrivons des méthodes de réseaux, des plus simples aux plus sophistiquées. Nous pensons qu'il est novateur de considérer des structures de changement de marque comme des réseaux, d'examiner des résultats obtenus par l'utilisation des méthodologies et philosophies des analyses de réseaux, et de déterminer le pouvoir explicatif que les méthodes de réseaux peuvent avoir dans la compréhension des comportements de transition d'achat. Nos méthodes modélisent des réseaux multiples qui permettent l'étude simultanée de phénomènes tels que des marchés dynamiques et une structure de marché concurrentielle inter-culturelle.
AxelssonB.EastonG. (1992), Industrial Networks: A New View of Reality, London: Routledge.
2.
BayusB.L. (1992), «Brand Loyalty and Marketing Strategy: An Application to Home Appliances», Marketing Sciences, 11, 1, 21–38.
3.
BreigerR.BoormanS.ArabieP. (1975), «An Algorithm for Clustering Relational Data, with Applications to Social Network Analysis and Comparison with Multidimentional Scaling », Journal of Mathematical Psychology, 12, 328–383.
4.
BurtR.S.MinorM.J. (1983), Applied Network Methods, Newbury Park, CA: Sage.
5.
ColomboR.EhrenbergA.SabavalaD. (1994), The Car Challenge: Diversity in Analyzing Brand Switching Tables, Unpublished manuscript.
6.
DeightonJ.NeslinS.A.HendersonC.M. (1994), « The Effects of Advertising on Brand Switching and Repeat Purchasing », Journal of Marketing Research, 31, 1, 28–43.
7.
DeSarboW.S.ManraiA.K. (1992), «A New Multidimentional Scaling Methodology for the Analysis of Asymmetric Proximity Data in Marketing Science », Marketing Science, 11, 1, 1–20.
FreemanL.C. (1979), « Centrality in Social Networks: Conceptual Clarification », Social Networks, 1, 215–239.
10.
FreemanL.C.BorgattiS.P.WhiteD.R. (1991), «Centrality in Valued Graphs: A Measure of Betweenness Based on Network Flow», Social Networks, 13, 141–154.
11.
GaddeL-E.MattssonL-G. (1987), «Stability and Change in network Relationships», International Journal of Research in Marketing, 4, 1, 29–41.
12.
GalaskiewiczJ. (1985), Social Organization of an Urban Grant Economy, New York: Academic Press.
13.
GivonM.MullerE. (1994), « Cyclical Patterns in Brand Switching Behavior: An Issue of Pattern Recognition », European Journal of Operational Research, 76, 290–297.
14.
GroverR.SrinivanV. (1992), « Evaluating the Multiple Effects of Retail Promotions on Brand Loyal and Brand Switching Segments », Journal of Marketing Research, 29, 1, 76–89.
15.
HakanssonH. (1989), Corporate Technical Behavior: Coorperation and Networks, London: Routledge.
16.
HopkinsN.HendersonG.IacobucciD. (1995), « Actor Equivalence in Networks: The Business Ties that Bind », Journal of Business-to-Business Marketing, 2, 3–31.
17.
HubertL.J. (1987), Assigment Methods in Combinatoriel Data Analysis, New York: Marcel Dekker.
18.
HubertL.J.BakerF.B. (1978), «Evaluating the Conformity of Sociometric Measurements », Psychometrika, 43, 31–41.
IacobucciD.HopkinsN. (1994), «Detection of Experimental Effects in Social Network Analysis », Social Networks, 16, 1–41.
21.
IacobucciD.HopkinsN. (1992), « Modeling Dyadic Interactions and Networks in marketing », Journal of Marketing Research, 29, 1, 5–17.
22.
IacobucciD.HopkinsN. (1991), « The Relationship between the Scheiblechner Model and the Holland-Leinhardt ‘pl’ Model », Social Networks, 13, 187–202.
23.
IacobucciD.WassermanS. (1988), «A General Framework for the Statistical Analysis of Sequential Dyadic Interaction Data », Psychological Bulletin, 103, 3, 379–390.
JainD.C.RaoR.C. (1994), « Latent Class Models to Infer Market Structures: A Comparative Analysis », European Journal of Operational Research, 76, 331–343.
26.
KnokeD.KuklinskiJ.H. (1982), Network Analysis, Newbury Park, CA: Sage.
27.
KrumhanslC.L. (1978), « Concerning the Applicability of Geometric Models to Spatial Data: The Interrelationship between Similarity and Spacial Density», Psychological Review, 85, 445–463.
28.
LuceD.PerryA. (1949), « A Method of Matrix Analysis of Group Structure », Psychometrika, 14, 95–116.
29.
McCarthyP.S.ChandrasekharanR.KannanP.K.WrightG.P. (1992), «Estimating Loyalty and Switching with an Application to the Automobile Market, Management Science, 38, 10, 1371–1393.
30.
MizruchiM.S.SchwartzM. (1987), Intercorporate Relations: The Structural Analysis of Business, Cambridge: Cambridge University Press.
31.
PoulsenC.S. (1990), « Mixed Markov and latent Markov Modelling Applied to Brand Choice Behavior », International Journal of Research in Marketing, 7, 1, 5–19.
32.
ScottJ. (1991), Social Network Analysis: A handbook, London: Sage.
33.
StephensonK.ZelenM. (1989), « Rethinking Centrality: Methods and Examples », Social Networks, 11, 1–37.
34.
WassermanS.FaustK. (1994), Social network Analysis: Methods and Applications, New York: Cambridge University Press.
35.
WassermanS.IacobucciD. (1988), « Sequential Social Network Data », Psychometrika, 53, 261–282.
36.
WassermanS.IacobucciD. (1986), «Statistical Analysis of Discrete Relational Data », British Journal of Mathematical and Statistical Psychology, 39, 41–64.
37.
WedelM.DeSarboW.S.KamakuraW.A.HofstedeF.T. (1995), «Implications for Asymmetry, Non-Proportionality, and Heterogeneity in Brand Switching from Piece-Wise Exponential Mixture Hazard Models », Journal of Marketing Research, 32, 4, 457–462.
38.
ZahorikA.J. (1994), « A Nonhierarchical Brand Switching Model for Inferring Market Structure», European Journal of Operational Research, 76, 344–358.
