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Examples of Models for Aggregate Demand

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Modeling Markets

Abstract

In this chapter we give some examples of marketing models which have been estimated using the general linear model. Most of these models have been estimated using aggregate demand data. Aggregate demand refers to the demand across a sample of customers or households and can be measured at levels such as store, chain and market demand.

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Notes

  1. 1.

    We use the terms industry sales and product class (category sales) interchangeably.

  2. 2.

    Guadagni and Little (1983) ; Kamakura and Russell (1989) ; Chintagunta (19921993a) ; Gönül and Srinivasan (1993) ; Gupta and Chintagunta (1994) ; Rossi and Allenby (1994) ; Wedel and Kamakura (1998) ; Yang and Allenby (2000) ; Andrews and Currim (2009) ; Andrews et al. (2011) .

  3. 3.

    See Christen et al. (1997) .

  4. 4.

    See Chap. 8.

  5. 5.

    We closely follow Guadagni and Little (1983) . See also Sect. 8.2.2.

  6. 6.

    Theil (1969) ; McFadden (1974) .

  7. 7.

    See, for example, McFadden and Reid (1975) .

  8. 8.

    See, for example, Sect. 6.8, Andrews et al. (2008) or Andrews et al. (2011) .

  9. 9.

    See, for example, Narayanan et al. (2004) ; Chintagunta and Desiraju (2005) ; Manchanda et al. (2005) nska and Y. Xie (2005); Venkataraman and Stremersch (2007) ; Kremer et al. (2008) ; Leeflang and Wieringa (2010) ; Wieringa and Leeflang (2013) ; Ding et al. (2014) ; Wieringa et al. (2014) .

  10. 10.

    Calls for advertising bans in different areas such as alcohol and cigarettes continue to echo around the world on a continuing basis. This explains why so many product class models have been developed in these areas. See, e.g. Duffy (1996) ; Franses (1991) ; Leeflang and Reuyl (1995) ; Luik and Waterson (1996) ; Nelson (2006) ; Capella et al. (2011) .

  11. 11.

    The assumption being that such variables affect demand for each brand equally. This assumption will often be quite reasonable. If not, however, environmental variables affecting brands differently should be included in the market share function (as well as in the direct estimation of brand sales).

  12. 12.

    See Foekens et al. (1994) .

  13. 13.

    Foekens et al. (1994) ; Gupta et al. (1996) ; Christen et al. (1997) .

  14. 14.

    Foekens et al. (1999) .

  15. 15.

    Van Heerde et al. (2001) .

  16. 16.

    Van Heerde et al. (2000) ; Andrews et al. (2008) .

  17. 17.

    See also Van Heerde et al. (2003) ; Leeflang et al. (2008) .

  18. 18.

    See Van Heerde et al. (2002) .

  19. 19.

    The following text is based on Wieringa and Leeflang (2013) . See also Leeflang and Wieringa (2010) .

  20. 20.

    These markets also have been studied by Windmeijer et al. (2005) .

  21. 21.

    The time and brand index are omitted for notational convenience.

  22. 22.

    In normative marketing mix studies one generally seeks the optimal policy for one brand assuming particular competitive reaction patterns. This means that one does not derive a simultaneous optimum for all brands in the product class. The latter would call for a game theoretical approach. We discuss game theoretical approaches in Volume II.

  23. 23.

    For a more formal treatment, extending to other variables as well, see Lambin et al. (1975, pp. 106–115) . In that paper the special character of quality as a decision variable is also discussed. A generalization to multiproduct markets is given by Bultez (1975) , whereas Plat and Leeflang (1988) extend this model to account for more segments.

  24. 24.

    The MCI models have been developed by Nakanishi and Cooper (19741982) . These and other market share models are discussed extensively in Cooper and Nakanishi (1988) .

  25. 25.

    Cooper and Nakanishi (1988, Chapters 3 and 5) .

  26. 26.

    We assume β , β ℓ j  ≥ 0 for all , j which applies to variables such as distribution, selling effort, advertising, and sales promotions. For variables such as price for which β , β ℓ j  ≤ 0 an analogous reasoning can be formulated.

  27. 27.

    See Luce (1959) ; Debreu (1960) ; Ben-Akiva and Lerman (1985) ; Sethuraman et al. (1999) .

  28. 28.

    See Foekens (1995) ; Bronnenberg and Wathieu (1996) ; Cooper et al. (1996) . Examples are the Cluster-Asymmetry Model (Vanden Abeele et al. 1990) , the CCHM-model (Carpenter et al. 1988) and hierarchical models (Foekens et al. 1997) .

  29. 29.

    For a more thorough discussion see Cooper and Nakanishi (1988, pp. 62–65) .

  30. 30.

    See Nakanishi and Cooper (1982) .

  31. 31.

    This has consequences for the degrees of freedom and the estimated standard errors. See Foekens (1995, p. 169) .

  32. 32.

    We do not discuss the assumptions of the disturbances nor the estimation techniques required to estimate these relations.

  33. 33.

    See also Brodie and De Kluyver (1984) ; Naert and Weverbergh (19811985) ; Leeflang and Reuyl (1984) and Brodie et al. (2001) .

  34. 34.

    Other, more recent application of market share response models are Mukherjee and Kadiyali (2011) and Leeflang and Parreño Selva (2012) .

  35. 35.

    This model is a modification of a model developed by Lambin (1969) .

  36. 36.

    Following the Dorfman and Steiner (1954) theorem derived in the Appendix to this chapter.

  37. 37.

    This rather complex expression results from the fact that in Eq. (7.35) logarithms to the base ten were used.

  38. 38.

    \(\frac{\partial \pi (LT)} {\partial a} = \frac{(p - c)(\partial q/\partial a)} {1 -\lambda /(1 + i)} - 1 = 0\), or \(\frac{p\partial q/\partial a} {1 -\lambda /(1 + i)} = \frac{p} {p - c} = \frac{p} {p -\mathit{MC}} = \frac{1} {w}\).

  39. 39.

    The parameter λ has been estimated from annual data. From Sect. 2.8.2 we know that \(\hat{\lambda }\) may be biased upward.

  40. 40.

    See Albers (2012) Albers (2012) for a recent wake-up call to develop optimization models, see in Sect. 10.5.

  41. 41.

    It is also conceivable, of course, to have both budget determination and allocation in one single model. An example is the “integrated model for sales force structuring” developed by Rangaswamy et al. (1990) .

  42. 42.

    See, for example, Raju (1992) ; Foekens et al. (1999) .

  43. 43.

    See also Tellis and Zufryden (1995) .

  44. 44.

    We assume that second-order conditions are satisfied.

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Appendix: The Dorfman–Steiner Theorem

Appendix: The Dorfman–Steiner Theorem

$$\displaystyle\begin{array}{rcl} \mbox{ Let }q& =& q(p,a,\tilde{x})\mbox{, be demand ($q$) as a function of price ($p$),} {}\\ & & \mbox{ advertising ($a$), and quality ($\tilde{x}$)}. {}\\ c& =& (q,\tilde{x})\mbox{, be variable cost per unit, and} {}\\ \mathit{FC}& =& \mbox{ fixed cost.} {}\\ \end{array}$$

Profit π is:

$$\displaystyle{ \pi = p\,q(p,a,\tilde{x}) - c(q,\tilde{x})q(p,a,\tilde{x}) - a -\mathit{FC}. }$$
(7.47)

If the objective is to maximize profit, at optimality we should haveFootnote 44:

$$\displaystyle\begin{array}{rcl} \frac{\partial \pi } {\partial p}& =& q + p\frac{\partial q} {\partial p} - c\frac{\partial q} {\partial p} - q\frac{\partial c} {\partial q} \frac{\partial q} {\partial p} = 0{}\end{array}$$
(7.48)
$$\displaystyle\begin{array}{rcl} \frac{\partial \pi } {\partial a}& =& p\frac{\partial q} {\partial a} - c\frac{\partial q} {\partial a} - q\frac{\partial c} {\partial q} \frac{\partial q} {\partial a} - 1 = 0{}\end{array}$$
(7.49)
$$\displaystyle\begin{array}{rcl} \frac{\partial \pi } {\partial \tilde{x}}& =& p\frac{\partial q} {\partial \tilde{x}} - c\frac{\partial q} {\partial \tilde{x}} - q\frac{\partial c} {\partial q} \frac{\partial q} {\partial \tilde{x}} - q \frac{\partial c} {\partial \tilde{x}} = 0.{}\end{array}$$
(7.50)

Dividing (7.48) by (∂ q∂ p) we obtain:

$$\displaystyle{ \frac{q} {\partial q/\partial p} + p - c - q\frac{\partial c} {\partial q} = 0. }$$
(7.51)

Total variable production cost equals c ⋅ q. Marginal cost (MC) is then:

$$\displaystyle{ \mathit{MC} = \frac{\partial (cq)} {\partial q} = c + q\frac{\partial c} {\partial q}. }$$
(7.52)

Using (7.52), we can write (7.51) as:

$$\displaystyle\begin{array}{rcl} \frac{-q} {\partial q/\partial p}& =& p -\mathit{MC}. {}\\ \end{array}$$

Dividing both sides by p, and letting:

$$\displaystyle\begin{array}{rcl} w& =& \frac{p -\mathit{MC}} {p} = \mbox{ percentage of gross margin} {}\\ \end{array}$$

we obtain:

$$\displaystyle\begin{array}{rcl} -\eta _{p}& =& 1/w{}\end{array}$$
(7.53)

where

$$\displaystyle\begin{array}{rcl} \eta _{p}& =& \frac{\partial q} {\partial p} \frac{p} {q} = \mbox{ price elasticity.} {}\\ \end{array}$$

Dividing (7.49) by (∂ q∂ a),

$$\displaystyle\begin{array}{rcl} p - c - q\frac{\partial c} {\partial q} - \frac{1} {\partial q/\partial a}& =& 0 {}\\ \end{array}$$

or

$$\displaystyle\begin{array}{rcl} p -\mathit{MC}& =& \frac{1} {\partial q/\partial a}. {}\\ \end{array}$$

After dividing both sides by p, we find:

$$\displaystyle\begin{array}{rcl} \mu & =& 1/w{}\end{array}$$
(7.54)

where

$$\displaystyle\begin{array}{rcl} \mu & =& p\frac{\partial q} {\partial a} = \mbox{ marginal revenue of product advertising.} {}\\ \end{array}$$

Finally, we divide (7.50) by \(\partial q/\partial \tilde{x}\):

$$\displaystyle\begin{array}{rcl} p - c - q\frac{\partial c} {\partial q} - q\frac{\partial c/\partial \tilde{x}} {\partial q/\partial \tilde{x}}& =& 0 {}\\ \end{array}$$

or

$$\displaystyle\begin{array}{rcl} \frac{p -\mathit{MC}} {p} & =& \frac{q\,\partial c/\partial \tilde{x}} {p\,\partial q/\partial \tilde{x}} {}\\ \end{array}$$

or

$$\displaystyle\begin{array}{rcl} \eta _{\tilde{x}}\frac{p} {c}& =& 1/w{}\end{array}$$
(7.55)

where

$$\displaystyle\begin{array}{rcl} \eta _{\tilde{x}}& =& \frac{(\partial q/\partial \tilde{x})/q} {(\partial c/\partial \tilde{x})/c}. {}\\ \end{array}$$

At optimality (7.53), (7.54), and (7.55) should hold simultaneously, or:

$$\displaystyle{ -\eta _{p} =\mu =\eta _{\tilde{x}}\frac{p} {c} = \frac{1} {w}. }$$
(7.56)

This result is generally known as the Dorfman and Steiner (1954) theorem. This theorem has been modified and extended in many directions. Examples are the models of Lambin (1970) ; Lambin et al. (1975) ; Leeflang and Reuyl (1985b) ; Plat and Leeflang (1988) ; Mantrala et al. (2007) .

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Leeflang, P.S.H., Wieringa, J.E., Bijmolt, T.H.A., Pauwels, K.H. (2015). Examples of Models for Aggregate Demand. In: Modeling Markets. International Series in Quantitative Marketing. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2086-0_7

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