244 The Marketing Book
Evidential Intelligence Analysis of Multiple
Target Tracks, Department of Numerical
Analysis and Computer Science Royal Insti-
tute of Technology, S-100 44 Stockholm,
Sweden.
Serrano Cimca, C. (1998) From financial infor-
mation to strategic groups: a self-organising
neural network approach, Journal of Forecast-
ing, 17 (5–6), 415–428.
Shafer, G. (1976) A Mathematical Theory of
Evidence, Princeton University Press,
Princeton.
Shafer, G. and Pearl, J. (1990) Readings in
Uncertain Reasoning, Morgan Kaufman, San
Mateo, CA.
Speed, R. (1994) Regression type techniques
and small samples, in Hooley, G. J. and
Hussey, M. K. (eds), Quantitative Methods in
Marketing,Academic Press, London, pp. 89–
104.
Stacey, R. D. (1993) Strategic Management and
Organisational Dynamics, Pitman, London.
Stanton, W. W. and Reese, R. M. (1983) Three
conjoint segmentation approaches to the
evaluation of advertising theme creation,
Journal of Business Research, June, 201–216.
Taylor, C. J. (1963) Some developments in the
theory and applications of media scheduling
method, Operational Research Quarterly,
291–305.
Vriens, M. (1994) Solving marketing problems
with conjoint analysis, in Hooley, G. J. and
Hussey, M. K. (eds), Quantitative Methods in
Marketing,Academic Press, London, pp. 37–
56.
Walley, P. (1987) Belief-function representations
of statistical evidence, Ann. Stat., 10 ,
741–761.
Wasserman, D. (1989) Neural Computing: Theory
and Practice, Van Nostrand Reinhold, New
York.
Wilson, J. M. (1975) The handling of goals in
marketing problems, Management Decision,
3 (3), 16–23.
Wilson, P. N. (1992) Some theoretical aspects of
the Dempster–Shafer theory, PhD Thesis,
Oxford Polytechnic.
Yuan, Y. and Shaw, M. J. (1995) Induction of
fuzzy decision trees, Fuzzy Sets and Systems,
125–139.
Ziarko, W. (1993a) Variable precision rough set
model,Journal of Computer and System Scien-
ces, 46 , 39–59.
Ziarko, W. (1993b) Analysis of uncertain infor-
mation in the framework of variable preci-
sion rough sets, Foundations of Computing and
Decision Sciences, 18 , 381–396.
Zimmerman, H. J. (1991) Fuzzy Set Theory
and its Applications, 2nd edn, Kluwer
Academic.Further reading
Diamantopoulos, A. and Schlegelmilch, B. B.
(1997)Taking the Fear Out of Data Analysis,
Dryden Press, London. This is an excellent
text, easy to read, refreshing and amusing,
yet introducing a very robust content.
Finerty, J. J. (1971) Product pricing and invest-
ment analysis, Management Accounting,
December, 21–37.
Hooley, G. J. and Hussey, M. K. (1994) Quantita-
tive Methods in Marketing, Academic Press,
London. This is a good book, introducing a
collection of different quantitative research
methods ranging from LISREL to neural
networks. A new edition was published in
1999.
Kane, G., Richardson, F. and Meade, N. (1998)
Rank transformation and the prediction of
corporate failure, Contemporary Accounting
Research, 15 (2), 145–166.
Kinnear, T. C. and Taylor, J. R. (1996) Marketing
Research: An Applied Approach, 5th edn,
McGraw-Hill, New York. An excellent text-
book for introductory marketing research.
Lillien, G. L. and Rangaswamy, A. (1998)
Marketing Engineering – Computer-Assisted
Marketing Analysis and Planning, Addison-
Wesley, Harlow, UK. Excellent new text on
quantitative and computer modelling tech-
niques with CD-ROM included. Techniques