Analysis of Sales Promotion Effects on Household Purchase Behavior

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elationship between product category characteristics and the sales promotion reaction mechanisms. But, again, these correlation coefficients are based on only 6 observations. Brand switching (BS) occurs most <strong>of</strong>ten for the higher priced categories c<strong>of</strong>fee and candy bars. Furthermore, brand switching (BS) occurs less <strong>of</strong>ten within more bulky categories. Purchases are not accelerated (TA) for higher priced categories. Quantity net (QN) effects are negatively related with promotional frequency. Households buy more <strong>of</strong> a promoted product that is better storable (QN). As mentioned before, the numbers in Table A8.2 regarding the promotion reaction mechanisms are based on across household averages, meaning loss <strong>of</strong> information. Therefore, instead <strong>of</strong> computing the Spearman correlation coefficient between the product category characteristics and the estimated averages <strong>of</strong> the sales promotion reaction mechanisms, we use data at the individual household level and compute the Pearson correlation coefficient. For each household we have estimates for each <strong>of</strong> the reaction mechanisms. Figure A8.1 in Appendix A8 depicts the general format <strong>of</strong> the dataset used in this chapter. The data matrix contains 200 rows (number <strong>of</strong> households) and 114 columns (6 x 19, 6 product categories, for each category 11 sales promotion reaction mechanism measures and 8 product characteristic ratings are estimated). As not all households purchased from all categories, some matrix elements for the sales promotion reaction mechanism measures contain no information. The product category characteristic ratings are the ratings as introduced in Table 8.3. These ratings differ across the product categories, but are constant within the product category across the different households. We will refer to this data format for clarification purposes throughout the remainder <strong>of</strong> this chapter. So for each sales promotion reaction mechanism, we can compute the correlation coefficient using data from each individual household, where the category characteristics are <strong>of</strong> course constant across the households but differ across the product categories. The resulting Pearson correlation coefficients can be found in Table 8.4. These coefficients are used to test the hypotheses derived in Section 4.3. Note, however, that only 6 product categories are included in this research and therefore the hypotheses can only be tested in a tentative way. 169
Table 8.4: Pearson correlation between product category characteristics and sales Category characteristic N Average price per modal unit-size Average price per purchase occasion Quarterly purchase frequency Quarterly promotional frequency Modal unitsize 170 promotion reaction mechanisms at the household level (two-tailed significance) PU 553 0.37 (0.00) 0.37 (0.00) 0.00 (0.95) -0.06 (0.14) -0.19 (0.00) Storability 0.07 (0.09) Number <strong>of</strong> brands -0.07 (0.09) Impulse 0.07 (0.09) BS 425 0.28 (0.00) 0.27 (0.00) -0.19 (0.00) -0.01 (0.80) -0.27 (0.00) -0.06 (0.22) -0.21 (0.00) 0.03 (0.60) TA 315 -0.03 (0.54) 0.00 (0.98) 0.04 (0.44) -0.02 (0.68) 0.06 (0.26) 0.05 (0.34) 0.08 (0.14) 0.01 (0.85) TR 319 0.20 (0.00) 0.17 (0.00) -0.08 (0.18) -0.02 (0.70) -0.16 (0.01) -0.02 (0.74) -0.12 (0.03) 0.01 (0.79) TN 349 0.13 (0.02) 0.12 (0.03) -0.03 (0.54) -0.02 (0.68) -0.09 (0.11) 0.00 (1.00) -0.05 (0.34) 0.03 (0.57) QB 328 0.02 (0.72) 0.02 (0.75) 0.11 (0.04) -0.12 (0.03) 0.10 (0.08) 0.14 (0.01) 0.16 (0.00) -0.07 (0.22) QP 414 0.21 (0.00) 0.23 (0.00) -0.09 (0.06) -0.12 (0.01) -0.17 (0.00) 0.12 (0.01) -0.08 (0.12) -0.12 (0.01) QA 335 0.06 (0.29) 0.10 (0.08) -0.05 (0.35) -0.14 (0.01) -0.04 (0.50) 0.11 (0.04) 0.06 (0.29) -0.07 (0.21) QN 415 0.21 (0.00) 0.23 (0.00) -0.08 (0.09) -0.17 (0.00) -0.15 (0.00) 0.16 (0.00) -0.03 (0.51) -0.14 (0.01) CE 255 -0.05 (0.42) 0.02 (0.74) -0.15 0.02) -0.11 (0.09) -0.06 (0.32) 0.04 (0.57) 0.01 (0.89) -0.05 (0.42) Based on these results, we can confirm that average price level is positively related with promotion response (promotion utilization) (H1). The average price level is positively related with brand switching (BS) and the promotional (QP) and the net purchase quantity volume (QN). But, no empirical support is found for a relationship with purchase time acceleration (TA). However, households do postpone their next purchase moment for the higher priced categories (TR). Therefore, promotions for higher priced products do seem to
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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
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are called “attributions.” Attr
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and less than 2 percent by stockpil
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into a unit sales decomposition and
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4.3.4 Storability/Perishability Sto
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Economic theory ignores mental deci
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seeking (cf. Assael 1987, Desphande
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there another factor that is relate
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Pr(event) 90 = 1+ 1 z e − Here Z
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5.4.2 Sales <stron
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It represents the fraction
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96 We measure possible time acceler
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promotional post-promotional purcha
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( 12) CategoryExpansion effect : 10
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PART II EMPIRICAL ANALYSIS 103
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more persons living together and di
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6.4 Linking Household and Store Dat
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Table 6.1 contains the results <str
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The age of the sho
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Table 6.4: Frequency distribution <
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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 138 and 139: esponsive the households within tha
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: Table 8.3: Product category rating
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
Page 189 and 190: looked at this promotional bump dec
Page 191 and 192: Table 8.8: Differences in promotion
Page 193 and 194: approach (about one third) are much
Page 195 and 196: promotions lead to large purchase t
Page 197 and 198: studies. Promotion
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Page 201 and 202: categories revealed that the strong
Page 203 and 204: degree. When households switch bran
Page 205 and 206: specific sales promotion reaction m
Page 207 and 208: increasing (Inman and Winer 1998),
Page 209 and 210: indirectly from promotional purchas
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Page 213 and 214: 9.2.2.3 Deal Proneness With respect
Page 215 and 216: 204 related to promotion response.
Page 217 and 218: influenced by out-of</stron
Page 219 and 220: Andrews, K.Z. (1997), “Do Marketi
Page 221 and 222: Blattberg, R.C., Eppen, G.D. and J.
Page 223 and 224: Chintagunta, P. (1993), “Investig
Page 225 and 226: East, R. and K. Hammond (1996), “
Page 227 and 228: Gupta, Sachin and P.K. Chintagunta
Page 229 and 230: 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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