Analysis of Sales Promotion Effects on Household Purchase Behavior

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esponsive the households within that category are compared to the average household. Another group <strong>of</strong> variables are included as ratio variables (size, age, variety seeking, basket size, shopping frequency, and store loyalty). The resulting estimates for these variables therefore represent the influence <strong>of</strong> an increase <strong>of</strong> one unit on the log-odds. Furthermore, dummy variables are incorporated in the analyses (property possession, and the different types <strong>of</strong> promotion). Note that each record contains only one promotion type dummy that equals 1, except X * , X other , and X *other , which are defined such that their influence is on top <strong>of</strong> the promotion type effect or on top <strong>of</strong> each other. The estimated effects therefore have to be added on top <strong>of</strong> the other promotional types effects. Suppose that a household encounters a display promotion for a favorite brand for a specific category and there are no other promotions within that category, than the log odds increases with the estimated effect <strong>of</strong> display promotions (XD) and the estimated effect for the dummy representing the favorite brand (X * ). Table A7.3 contains the results <strong>of</strong> two logistic regression analyses. With respect to the categorical variables, both the significance <strong>of</strong> the separate levels and <strong>of</strong> the variable itself are provided. As mentioned in Section 7.4, one analysis was carried out incorporating the variable cycle as a categorical variable and the variables age and size as linear variables. The results <strong>of</strong> this analysis can be found in the first column <strong>of</strong> estimates (is the same as the first column <strong>of</strong> estimates from Table A7.2). The second analysis (<strong>of</strong> which the results can be found in the second column <strong>of</strong> estimates) was carried out excluding cycle from the analysis and incorporating age and size as categorical variables. The parameter estimates are comparable across the two analyses, which underlines the robustness <strong>of</strong> our findings. Small changes in the model do not lead to entirely different findings. Because <strong>of</strong> this consistency, we have chosen to use the results <strong>of</strong> the analysis where cycle is incorporated when appropriate. 7.5.2.1 Social Class Table 7.2 contains the resulting estimated regression coefficients describing the relationship between promotion response and social class. 127
Table 7.2: Relationship promotion response and social class SOCIAL CLASS H2: Social class and promotion response are positively related. B S.E. Sign. Exp(B) D (low) -0.6430 0.1084 0.0000 0.5259 C (middle) 0.2549 0.0661 0.0001 1.2904 B-,B+,A (high) 0.3878 0.0620 0.0000 1.4737 Test results: Social class and promotion response are positively related. The results in Table 7.2 indicate that social class is positively related with promotion response. The lowest class uses the available sales promotions the least. More insights can be derived when this relationship is investigated distinguishing between in-store and out-<strong>of</strong>store promotions. We perform two separate analyses for in-store (display related) and out-<strong>of</strong>-store (feature related) promotions to take the interaction effect <strong>of</strong> promotion type into account. The resulting estimated coefficients <strong>of</strong> the binary logistic regression can be found in Table A7.4 (size and age are included linearly, cycle is included as a categorical variable in the analysis) and Table A7.5 (size and age are included as categorical variables, cycle is excluded from the analysis). The estimates for the relationship between social class and promotion response can be found in Table 7.3. 128
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LINDA H. TEUNTER Analysis</
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Analysis o
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Voorwoord Soms valt de appel echt n
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Contents 1 INTRODUCTION AND OVERVIE
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5.4.2.3.1 Inter Purchase Time .....
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1 INTRODUCTION AND OVERVIEW 1.1 Int
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generally generated from a smaller
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switching, purchase acceleration, c
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strategy change (decrease in promot
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of promotions, or
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characteristics are important in ex
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Chapter 5 are applied to study the
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2 THEORIES OF CONSUMER BUYING BEHAV
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systematically explored the decisio
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the part of the co
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As mentioned before, Figure 2.3 is
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product use coupled with the import
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2.3.2 Stimulus-Response Model Appli
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2.3.2.2 Operant Conditioning In ope
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X is very popular that it will brin
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But, in contrast, economic theory c
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compared to a perceived benchmark -
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High need-for-cognition (NFC) indiv
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2.3.4.2 Literature Overview Our rev
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The previously described research h
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has its deficiencies. Any purchase
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Chandon et al. 2000). But deal pron
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2.4 Concluding Remarks Regarding th
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stimulus-organism-response model) c
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Shoemaker 1987). Several factors ha
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such as display promotions. Althoug
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3.2.3 Type of resi
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3.2.5 Education Education links to
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these advantages therefore could be
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less likely to seek variety. More e
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3.3.1 Store Loyalty Store loyalty s
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more often (probab
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Table 3.12 continued Hypothesis H9a
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4.2.1 Brand Switching Brand switchi
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involvement purchases for most cons
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Neslin (1998), there is a great nee
Page 87 and 88: are called “attributions.” Attr
Page 89 and 90: and less than 2 percent by stockpil
Page 91 and 92: into a unit sales decomposition and
Page 93 and 94: 4.3.4 Storability/Perishability Sto
Page 95 and 96: Economic theory ignores mental deci
Page 97 and 98: seeking (cf. Assael 1987, Desphande
Page 99 and 100: there another factor that is relate
Page 101 and 102: Pr(event) 90 = 1+ 1 z e − Here Z
Page 103 and 104: 5.4.2 Sales <stron
Page 105 and 106: It represents the fraction
Page 107 and 108: 96 We measure possible time acceler
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Page 111 and 112: ( 12) CategoryExpansion effect : 10
Page 114: PART II EMPIRICAL ANALYSIS 103
Page 117 and 118: more persons living together and di
Page 119 and 120: 6.4 Linking Household and Store Dat
Page 121 and 122: Table 6.1 contains the results <str
Page 123 and 124: The age of the sho
Page 125 and 126: Table 6.4: Frequency distribution <
Page 128 and 129: 7 EMPIRICAL ANALYSIS ONE: DRIVERS O
Page 130 and 131: Table 7.1: Operationalization <stro
Page 132 and 133: during 435 shopping trips more than
Page 134 and 135: The variables size, age, and cycle
Page 136 and 137: 7.5 Results Drivers of</str
Page 140 and 141: Table 7.3: Relationship promotion r
Page 142 and 143: indication that decreasing marginal
Page 148 and 149: Table 7.10: Relationship promotion
Page 154 and 155: 7.5.2.8 Variety Seeking Two intrins
Page 156 and 157: anymore. Therefore it is concluded
Page 158 and 159: Thus, store loyalty and promotion r
Page 160 and 161: dummies add up to one. This implies
Page 162 and 163: Table 7.22: Overview empirical test
Page 164 and 165: enacting-on-impulse hypothesis and
Page 166 and 167: Table 7.23: Summary of</str
Page 168: Table 7.24: Correlation error coeff
Page 171 and 172: another category? Or do households
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Page 175 and 176: 164 In general, the average quantit
Page 177 and 178: Purchase frequency is defined as th
Page 179 and 180: Table 8.3: Product category rating
Page 181 and 182: Table 8.4: Pearson correlation betw
Page 183 and 184: We hypothesized that within impulse
Page 185 and 186: measure (PU). Referring to Figure A
Page 187 and 188: Table 8.6: Significant within categ
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looked at this promotional bump dec
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Table 8.8: Differences in promotion
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approach (about one third) are much
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promotions lead to large purchase t
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studies. Promotion
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Promotional extra
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categories revealed that the strong
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degree. When households switch bran
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specific sales promotion reaction m
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increasing (Inman and Winer 1998),
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indirectly from promotional purchas
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quantity downward for potato chips.
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9.2.2.3 Deal Proneness With respect
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204 related to promotion response.
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influenced by out-of</stron
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Andrews, K.Z. (1997), “Do Marketi
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Blattberg, R.C., Eppen, G.D. and J.
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Chintagunta, P. (1993), “Investig
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East, R. and K. Hammond (1996), “
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Gupta, Sachin and P.K. Chintagunta
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Kahn, B.E., Morrison, D.G.and G.P.
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Lattin, J.M. and R.E. Bucklin (1989
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McAlister, L. and E. Pessemier (198
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Petty, R.E. and J.T. Cacioppo (1981
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Shimp, T.A. (1990). Promoti
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Van Trijp, H.C.M. and J.B.E.M. Stee
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Winer, R.S., Bucklin, R.E., Deighto
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APPENDIX A4: Research Overview Tabl
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Table A4.1 continued Article Promot
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� Size of munici
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Table A7.1 continued Symbol Descrip
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Table A7.2: Data legitimacy check (
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Table A7.3: Results binary logistic
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Table A7.4: Results interacting wit
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Table A7.5: Results age and size no
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Table A7.5 continued Variable B S.E
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Table A8.1 continued Impulse BS TA
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Table A8.2 continued Number <strong
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Table A8.3: Relative occurrence and
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Figure A8.2: Decomposing total prom
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interessante aanbieding is. Combina
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aantalmerken in een categorie en im
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ERASMUS RESEARCH INSTITUTE OF MANAG
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Title: Beyond Generics;A closer loo
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Title: Planning and Control Concept
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