Analysis of Sales Promotion Effects on Household Purchase Behavior

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Household panel Households with primary store (N=4060) (N=1770) Retail panel h h h h h h h h h h h h h Primary store h h h h Figure 6.1: Pictorial representation <strong>of</strong> household selection process (h represents a household, r represents a retail outlet) This primary store assignment process is at the expense <strong>of</strong> smaller, local, or specialty shops. They have a smaller probability to be included in this study, because <strong>of</strong> smaller assortments, less products, less choice, etc. Households will hardly ever spent 50% or more <strong>of</strong> their grocery expenses in these types <strong>of</strong> shops. The remaining households and their outlets are all members <strong>of</strong> the five biggest retail chains in The Netherlands, which constitute 53.7% <strong>of</strong> the total market share. Before using the resulting 200 household, the representativeness <strong>of</strong> this set <strong>of</strong> households compared to the GfK household ConsumerScan panel has to be determined, to ensure generalizability <strong>of</strong> the findings <strong>of</strong> this study. The next section contains some statistical tests that assess differences and/or similarities between the entire household panel and the set <strong>of</strong> households that will be used to assess the effects <strong>of</strong> sales promotions on household purchase behavior in the remainder <strong>of</strong> this dissertation. 6.5 Representativeness Household <strong>Analysis</strong> Set h The first 13 weeks <strong>of</strong> data are used to investigate whether the 200 households from the household analysis set provide a good representation <strong>of</strong> the entire household panel on a number <strong>of</strong> household and purchase process characteristics, such as social class, household size, age <strong>of</strong> the housewife, household cycle, purchase frequency, and grocery expenditures (as these variables were identified as possible drivers <strong>of</strong> sales promotion response, the representativeness with respect to these variables is very important). r r r r r Households in analysis set (N=200) h h 109
Table 6.1 contains the results <strong>of</strong> several 2-sample independent t-tests, each testing the null hypothesis that two population means are equal, based on the results observed in two independent samples. In this situation, testing whether the two group (the 200 households that are a member <strong>of</strong> the final analysis set versus those 3860 households who are not) means are equal for several variables. Table 6.1: Results independent t-test 110 Variable Observed-two-tail significance level Representative Social class 0.08 YES Size <strong>of</strong> the household 0.07 YES Age <strong>of</strong> the housewife 0.96 YES Household Cycle 0.62 YES Yearly total number <strong>of</strong> grocery shopping trips 0.00 NO Yearly total amount <strong>of</strong> grocery expenditures 0.43 YES The final analysis sample <strong>of</strong> households used in this dissertation seems to differ from the entire household panel with respect to the total number <strong>of</strong> shopping trips. The households in the analysis set make (significantly) less shopping trips (on average 39 compared to 45 shopping trips per year for the remaining 3860 households). Therefore, frequent shoppers are underrepresented in the analysis set <strong>of</strong> households. More frequent shoppers could have the tendency to visit more different stores, resulting in a smaller probability for having a primary store. A more in-depth study revealed that the difference is caused by a small percentage <strong>of</strong> very frequent shoppers (2 or even 3 shopping trips per day on average) in the entire household panel, which is underrepresented in the analysis sample. When excluding the top 10% <strong>of</strong> most frequently shopping households from both the entire panel and the analysis sample, the (two-sample independent) t-statistic does conclude that the average numbers <strong>of</strong> shopping trips are comparable. So the bulk (90%) <strong>of</strong> shoppers in the analysis sample is
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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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Page 73 and 74: less likely to seek variety. More e
Page 75 and 76: 3.3.1 Store Loyalty Store loyalty s
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Page 79 and 80: Table 3.12 continued Hypothesis H9a
Page 81 and 82: 4.2.1 Brand Switching Brand switchi
Page 83 and 84: involvement purchases for most cons
Page 85 and 86: 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
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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: 6.4 Linking Household and Store Dat
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
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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
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another category? Or do households
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and unweighted. With respect to the
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164 In general, the average quantit
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Purchase frequency is defined as th
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Table 8.3: Product category rating
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Table 8.4: Pearson correlation betw
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We hypothesized that within impulse
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measure (PU). Referring to Figure A
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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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