Analysis of Sales Promotion Effects on Household Purchase Behavior

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4.3.2 Purchase Frequency The study <strong>of</strong> Fader and Lodish (1990) implied a positive relationship between high frequency <strong>of</strong> purchase and promotional elasticity. Based on Bawa and Shoemaker (1987), Narasimhan et al. (1996) hypothesized that shorter consumer interpurchase times result in more brand switching because the consumer must live with the consequences <strong>of</strong> buying a less preferred brand for a shorter period. In addition Narasimhan et al. conjectured that interpurchase times are related to purchase acceleration. Long interpurchase times discourage acceleration because the stockpiled product must be stored for a longer period <strong>of</strong> time. This was supported by empirical findings. Bell et al. (1999) found less stockpiling for <strong>of</strong>ten purchased products. Based on above, we expect to find a positive relationship between purchase frequency and promotional response, mainly due to brand switch effects (H2). Purchase frequency might be related to storability (which is discussed in Section 4.3.4). This will be investigated empirically. 4.3.3 <strong>Promotion</strong>al Activity If a brand is promoted very infrequently, consumers are likely to use these opportunities to stock-up for future consumption (Krishna et al. 1990). Decrease in stockpiling as promotional frequency increases has been shown using simulations in Helsen and Schmittlein (1992), and Assuncao and Meyer (1990). Winer (1986) and Lattin and Bucklin (1989) concluded that more frequent discounts might lower the reference price <strong>of</strong> the promoted brand, which in turn may additionally negate the effect <strong>of</strong> promotions. The study <strong>of</strong> Raju (1992) implies that categories with deeper, infrequent dealing show higher promotional elasticities. Bell et al. (1999) stated that more frequent dealing leads to more opportunities for the consumer to exploit price promotions, leading to lower promotional elasticities. We therefore hypothesize that promotional frequency and promotion response are negatively related (H3). 81
4.3.4 Storability/Perishability Storable products facilitate stockpiling and therefore intertemporal purchase displacement. Narasimhan et al. (1996) reported that promotions get the highest response for brands in easily stockpiled categories, especially due to purchase acceleration. Raju (1992) concluded that bulkiness (volume, which is inversely related to storability) and perishability both have a negative impact on the variability in category sales. Bell et al. (1999) argued that storability and purchase acceleration (both time and quantity) are positively related. They concluded that all refrigerated products had much higher proportions for the time effect than for the quantity effect and that all storable products showed the opposite pattern. Bucklin et al. (1998) argued that purchase quantity effects could be smaller for perishable product categories. It is therefore hypothesized that storability is positively related with promotional effects, mainly due to purchase acceleration (H4). Perishability is negatively related with promotional effects (H5). 4.3.5 Number <strong>of</strong> Brands Narasimhan et al. (1996) observed a negative relationship between number <strong>of</strong> brands and promotional elasticity, which they attributed to brand switching. The presence <strong>of</strong> many brands reflects broader product differentiation, which, in turn, protects an individual brand from the enticement <strong>of</strong>fered by a competitor’s promotion. Bawa et al. (1989), however, found that larger assortments do tend to generate higher trial for new products. Bell et al. (1999) also hypothesized that purchase acceleration effects are positively related to number <strong>of</strong> brands within a category. We expect to find a positive relationship between number <strong>of</strong> brands and promotional effects (H6). 82
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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
Page 42 and 43: X is very popular that it will brin
Page 44 and 45: But, in contrast, economic theory c
Page 46 and 47: compared to a perceived benchmark -
Page 48 and 49: High need-for-cognition (NFC) indiv
Page 50 and 51: 2.3.4.2 Literature Overview Our rev
Page 52 and 53: The previously described research h
Page 54 and 55: has its deficiencies. Any purchase
Page 56 and 57: Chandon et al. 2000). But deal pron
Page 58 and 59: 2.4 Concluding Remarks Regarding th
Page 60: stimulus-organism-response model) c
Page 63 and 64: Shoemaker 1987). Several factors ha
Page 65 and 66: such as display promotions. Althoug
Page 67 and 68: 3.2.3 Type of resi
Page 69 and 70: 3.2.5 Education Education links to
Page 71 and 72: these advantages therefore could be
Page 73 and 74: less likely to seek variety. More e
Page 75 and 76: 3.3.1 Store Loyalty Store loyalty s
Page 77 and 78: more often (probab
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: into a unit sales decomposition and
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
Page 109 and 110: promotional post-promotional purcha
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 138 and 139: esponsive the households within tha
Page 140 and 141: Table 7.3: Relationship promotion r
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indication that decreasing marginal
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Table 7.6: Relationship promotion r
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Table 7.8: Relationship promotion r
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Table 7.10: Relationship promotion
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7.5.2.8 Variety Seeking Two intrins
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anymore. Therefore it is concluded
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Thus, store loyalty and promotion r
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dummies add up to one. This implies
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Table 7.22: Overview empirical test
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enacting-on-impulse hypothesis and
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Table 7.23: Summary of</str
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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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