2012 INFORMS Marketing Science Conference June 7

More documents

Recommendations

Info

TA10 2 - Stars, Leaders, Free-riders and Losers: Roles in the Category Expansion during Sales Promotions Sergio Meza, Assistant Professor, University of Toronto, Mississauga, Toronto, ON, Canada, sergio.meza@rotman.utoronto.ca In the marketing literature there are opposite views of whether sales promotions expand the category sales or not. Increase in sales may be due to within-category brand switching (Gupta, 1988; Sun et al, 2003) or category expansion (Chintagunta, 1993; Van Heerde, 1999; Nijs et al, 2001). Category expansion can be the result of anticipated consumption (van Heerde et al, 2004; Mace and Neslin, 2004; Bell et al, 2002) or additional consumption (Ailawadi and Neslin, 1998; van Heerde, 1999; van Heerde et al, 2004, Blattberg et al, 1995). The issue is complicated by the fact that sales promotions may be scheduled to coincide with peaks of demand (see Chevalier et al. 2003, Meza 2011)). Are expansions of the category during sales promotions due to the effect of the sales promotions? Or are they due to the fact that sales promotions are scheduled when expansions of the category are expected? In this paper we investigate which brands have a larger effect in expanding the category when promoted, and which brands sell more when others are promoted. Brands that expand the most (when promoted) and sell the most (when others are promoted) are called “stars”. Brands that expand the most (when promoted), but sell the least (when others are promoted) are called “Leaders”. Brands that expand the least (when promoted), but sell the most (when others are promoted) are called “Free-riders”. Brands that do not expand nor sell are called “losers”. 3 - The Impact of Retailer Promotional Activities on Store Traffic Shyda Valizade-Funder, University of Mainz, Jakob- Welder-Weg 9, Mainz, 55099, Germany, valizade@marketing-science.de, Oliver Heil, Kamel Jedidi Building store traffic through marketing activities is one of the major goals for retailers seeking sales growth. By understanding how to build traffic, retailers can assess the productivity of their advertising and promotional activities. This enables retailers to assess which communication media are effective in targeting their customers, determine which promotion activities to implement, and optimize resource allocation across these marketing efforts. The objective of our study is to assess the impact of marketing activities on store traffic for a service provider. Most studies examined the impact of promotions on traffic in a supermarket setting using transaction data. In contrast, we investigate these questions using actual store traffic, which we collected using an advanced video technology that accurately measures head count, overall and by gender. In addition, our unique data encompass all the marketing activities the sponsoring firm uses to drive store traffic (e.g., flyers, radio, outdoor, print, TV, billboard, and window advertising). We propose a set of hypotheses based on the economics of information and promotional literature. Our results show that except for radio advertising, all promotional activities have a positive impact on sales. Moreover, the depth and breadth of promotional activities have a positive and significant effect on female store traffic but did not significantly affect the traffic of male shoppers. This is in contrast to print ads, which have a positive and significant effect on male store traffic but no effect on female traffic. We conclude the paper by discussing managerial implications for retailers as well as suggesting directions for future research. 4 - An Empirical Investigation of Retailer Pass-throughs Across Categories Dinesh Gauri, Syracuse University, 721 University Ave., Syracuse, NY, 13214, United States of America, dkgauri@syr.edu, Debabrata Talukdar, Joseph Pancras Retail pass-through has been extensively analyzed analytically and empirically, and recent empirical work has stressed the importance of appropriate methodology and data for inferring correct retail pass-through. However the literature on retail passthrough has interpreted ‘pass-through’ as being confined to a specific product category, and to brands belonging to this category. This category restriction has been derived from a tradition of modeling the retailer as a ‘category profit maximizer’. Yet it is widely accepted that retailers strive to maximize profits across categories, with several categories specifically functioning as ‘loss leaders’. In this paper we argue that this view of the retailer makes it necessary to reevaluate retailer pass-through from being a ‘within category’ phenomenon to a ‘cross category phenomenon’. Using a unique dataset we empirically evaluate cross pass-throughs with a variety of categories – selected on the basis of profitability. We find that by and large loss leader categories have negative cross category pass-throughs (average 21.5%) while profitable categories have positive cross category pass-throughs (average 21.98%). We also find empirical evidence of the existence of significant cross-category brand level pass-throughs. Category characteristics such as price elasticity and proportion of loss leaders affect the cross-category pass-throughs. We conclude that future work on retailer pass-throughs needs to incorporate cross category analysis in order to capture the ‘true’ strategic behavior of the retailer. MARKETING SCIENCE CONFERENCE – 2011 6 ■ TA10 Founders IV Consumer Behavior: Perceptions Contributed Session Chair: Jana Diels, Humboldt-Universitaat zu Berlin, Wirtschaftswissenschaftliche Fakultaat, Spandauer Str. 1, Berlin, Germany, diels@wiwi.hu-berlin.de 1 - The Effects of New Product Introduction to Different Category Context on Price Evaluations Akihiro Nishimoto, Otaru University of Commerce, 3-5-21 Midori, Otaru, Japan, i_top0831@msn.com, Sayaka Ishimaru, Sotaro Katsumata, Eiji Motohashi The purpose in this research is to demonstrate the effects of new product introduction to different category context on price evaluations. In particular, we focus on the phenomenon that the heterogeneity of category knowledge among consumers, which is activated in the evaluations of the new product, affects the willingness to pay of it. That is, we investigate on the effects of category knowledge as the priming effects in recognizing the new product. From the past studies, the priming has three effects. The first is assimilation effect. This is the priming effect based on the interpretation of the new product. The second is contrast effect. This priming effect is based on the comparison between the prior knowledge and the new product. And the third is correction contrast effect. This is the priming effect for the experts based on correction for context effect. In this research, we run three experiments. In the first experiment, we have verified the effects of new product introduction to different category context on price evaluations, taking into account the strategic relationship with the priming category and the target category. In the second experiment, we have investigated the priming effects diluting the evaluation of the new product. And the third experiment, we have confirmed the effects of different category context as the priming effect to generalize our results. From the three experiments, we have demonstrated the relationship between the category context as the priming effect and the level of category knowledge. We will show some of the results and implications in the presentation. 2 - How Surprisingly Little Thoughts Count—On Receiver’s Motivated Appreciation for Giver’s Thoughts Yan Zhang, National University of Singapore Business School, 15 Kent Ridge Drive, Singapore, Singapore, yan.zhang@nus.edu.sg Gift-giving is a social exchange that includes both the objective value of a gift as well as the symbolic meaning of the exchange itself. The objective value of a gift is sometimes considered to be of secondary importance in people’s evaluations of a gift, as when people claim, “it’s the thought that counts.” Because it often takes motivation and attentional resources to consider another person’s thoughts, we predicted that thoughts would count for very little in evaluating gift exchanges unless gift receivers were motivated or otherwise triggered to consider a gift giver’s thoughts. Three experiments demonstrate that others’ thoughts are likely to be triggered when a friend’s gift has relatively little objective value, or is considered to be objectively undesirable. Gift givers, however, are directly aware of the amount of thought they put into their gift, and therefore predict that their thoughts will “count” more than they actually do. The fourth experiment found that although thought counts very little in most cases, investing thoughts into a gift made givers feel more socially connected with receivers, which may help maintain and develop the relationship between givers and receivers. 3 - When Looks Can Be Deceptive: Consumer Response to Unfamiliar Product Packaging Descriptors Rishtee Batra, Assistant Professor, Indian School of Business, AC2 Level 1 Office 2116, Indian School of Business- Gachibowli, Hyderabad, AP, 500032, India, rkmishra@gmail.com Marketing scholars are increasingly paying attention to a product’s packaging, often described as a silent salesman that influences consumer decisions. A product’s package informs consumers about many different aspects of product, including the quantity of the goods contained inside. The current paper investigates consumers’ responses to packaging containing unfamiliar measurement units and argues that consumers will anchor on the face value of the measurement unit in arriving at their perceptions of product quality and willingness to pay. Study 1 hypothesizes that when a consumer encounters packaging information that is presented in a foreign unit whose face value is higher than the equivalent in their home units (e.g. an American consumer evaluating a package containing 454 grams of a product versus 1 pound), that consumer will have an overall higher perception of the product quality and will have a higher willingness to pay due to inaccuracies in perceived quantity. Study 2 hypothesizes that the over- or under-estimation of overall product quality and willingness to pay will be moderated by the extent to which consumers can access a similar packaging from their memory. In the case that the product’s packaging is typical of the category, the results of Study 1 are expected to be mitigated. Although consumers might have difficulty interpreting foreign units, they still have a visual anchor to which they can compare the given product and make more accurate judgments. If, however, the packaging is novel, the effect is expected to endure because the consumer has no point of comparison.
4 - Understanding Customers` Substitution Patterns when Branded Items Become Unavailable Jana Diels, Humboldt-Universitaat zu Berlin, Wirtschaftswissenschaftliche Fakultaat, Spandauer Str. 1, Berlin, Germany, diels@wiwi.hu-berlin.de, Lutz Hildebrandt, Nicole Wiebach At the point-of-sale customers are often faced with unexpected situations of reduced choice sets, e.g. caused by delistings or temporary out-of-stocks. Accordingly, it is of major importance for retailers and manufacturers to gain insight into individual substitution patterns if choice sets are reduced. Previous experimental research, predominantly directed to product introduction, has revealed that changes in the set of alternatives significantly affect customers` preferences and hence, their product choice. The objective of this research is to analyze whether the unavailability of an item induces comparable systematic shifts in choice probabilities as in the product entry case. Furthermore, a theoretical framework to understand, predict and use substitution patterns is derived by using context and phantom theory. In a series of experiments, we find strong support for the existence of certain context effects when items are permanently removed or temporarily out-of-stock. Thereby, the importance of context theory as major theoretical approach to explain switching patterns for product unavailability is approved. Moreover, implications for retailers when making assortment and inventory decisions can be derived. The results of a real-life quasiexperiment further suggest that manufacturers may encounter substantially larger losses than retailers when items are delisted from the assortment. With regard to temporal unavailability, the outcome of an online experiment extends existing outof-stock research by (1) demonstrating that a negative similarity effect arises in outof-stock situations, (2) highlighting the relevance of promotion as an essential driver for out-of-stock reactions, and (3) including a so far neglected option – branch switching. ■ TA11 Champions Center I Direct Marketing Contributed Session Chair: Eric Schwartz, The Wharton School, 3730 Walnut Street, JMHH 700, Philadelphia, PA, 19103, United States of America, ericschw@wharton.upenn.edu 1 - Calibration? Definition, Motivation and Insights Learned from a Direct Marketing Setting Kristof Coussement, IESEG School of Management, 3 Rue de la Digue, Lille, 59000, France, k.coussement@ieseg.fr, Wouter Buckinx Calibration refers to the adjustment of the posterior probabilities output by a classification algorithm towards the true prior probability distribution of the target classes. This adjustment is necessary to account for the difference in prior distributions between the training set and the test set. This article proposes a new calibration method, called the probability-mapping approach. Two types of mapping are proposed: linear and non-linear probability mapping. These new calibration techniques are applied to 9 real-life direct marketing datasets. The newly-proposed techniques are compared with the original, non-calibrated posterior probabilities and the adjusted posterior probabilities obtained using the rescaling algorithm of Saerens, Latinne, & Decaestecker (2002). The results recommend that marketing researchers must calibrate the posterior probabilities obtained from the classifier. Moreover, it is shown that using a ‘simple’ rescaling algorithm is not a first and workable solution, because the results suggest applying the newly-proposed non-linear probabilitymapping approach for best calibration performance. 2 - Optimizing Target Selection of Direct Mailing by Charities Remco Prins, VU University Amsterdam, FEWEB Marketing - Office 2E-19, De Boelelaan 1105, Amsterdam, 1081 HV, Netherlands, rprins@feweb.vu.nl, Bas Donkers When determining the effectiveness of existing target selection procedures in direct mailing campaigns, correcting for the resulting endogenous sample composition can be a complicated procedure. In the present study, we propose a method to determine the effectiveness of target selection procedures using an additional experimental mailing to a randomly selected group of customers. Through this field experiment, we can provide clear cut directions for improving target selection rules, without the need for explicit corrections for the impact of previous target selection activities. The proposed approach also easily allows an estimation of the net effect of sending an additional mailing, after correcting for possible cannibalization effects. We apply this method to the direct mail campaigns of four large Dutch charitable organizations. The results provide directions for improvement for each of the charities, in terms of selection rules and mail frequency. 3 - Test and Learn: A Reinforcement Learning Perspective Eric Schwartz, The Wharton School, 3730 Walnut Street, JMHH 700, Philadelphia, PA, 19103, United States of America, ericschw@wharton.upenn.edu Firms run experiments to test and learn about marketing actions. However, running many so-called A/B or multivariate tests can be slow and costly, and the results from one test do not give necessarily inform what the next test should be. We frame this as an optimization problem, known as the multi-armed bandit problem, involving the tradeoff between exploring uncertain actions and exploiting what has been learned so far. The problem occurs in a range of domains from personalized website design to MARKETING SCIENCE CONFERENCE – 2011 TA12 7 targeted direct marketing. For instance, in customer relationship management, marketers may predict future customer value, but which actions they should select for which customers and in which contexts or channels? To provide new insight on this problem, we use a model-based algorithm to determine an optimal policy of how to run a sequence of tests to learn about the effectiveness of those actions in the most cost-efficient way. To do this, we introduce the reinforcement learning framework to the marketing literature. This approach generalizes methods commonly used in marketing to solve dynamic optimization problems. Unlike prior methods, our approach accommodates a selection among many different actions. By considering the similarity of those actions, the firm may learn about the effectiveness of action without before ever testing it. As one example, we investigate firms with a customerbase engaging in activity for free with the goal of converting some of them into paying customers. Finally, we discuss the design of field experiments for implementation of the optimal sequential marketing tests. ■ TA12 Champions Center II Branding Contributed Session Chair: Xiaoying Zheng, PhD Student, Guanghua School of Management, Peking University, Zhong Guan Xin Yuan No.4 Building, Beijing, 100871, China, zhengxiaoyingpku@gmail.com 1 - Customer Based Multidimensional Brand Equity and Asymmetric Risk Kyoung Nam Ha, Doctoral Candidate, University of Washington, 24003 SE 12th Pl, Sammamish, WA, 98075, United States of America, knha@u.washington.edu, Robert Jacobson, Gary Erickson Based on market asset theory, we investigate brand asset in influencing a firm’s performance, in particular, a firm’s risk. Building on a literature in marketing that suggests several components in constituting brand value and in finance that emphasizes the role of asymmetries in the systematic risk, we assess the extent to which dimensions of brand equity (Differentiation, Relevance, Esteem, Knowledge, and Energy) influence the downside risk, upside risk, and the differential between upside and downside risk. We find that (i) Esteem has a negative effect on the risk differential, which comes from a more pronounced positive effect on downside risk, and (ii) Energy has a positive effect on the risk differential, which comes from a more pronounced positive effect on upside risk. We also find that (iii) Knowledge has a negative effect on downside risk as well as upside risk, and, thus, it does not have a statistically significant effect on the risk differential. The empirical analysis highlights the limitations of working with an aggregate measure of beta (which aggregates over both upturns and downturns) as well as an aggregate measure of brand equity (which aggregates distinct brand equity dimensions). By showing which brand characteristics indeed affect a firm’s risk beyond simply proving the theory in marketing that brand equity will have effect on a firm’s performance, this study provides managers more pragmatic information and sophisticated insights in making strategic decisions. 2 - Brand Equity and Product Recalls Sheila Goins, Assistant Professor, University of Iowa, S320 Pappajohn Business Building, Iowa City, IA, 52242-0944, United States of America, sheila-goins@uiowa.edu, Qiang Fei, Lopo Rego, Cathy Cole Marketing managers and scholars have long recognized brands as fundamental market based firm assets. The marketing literature provides compelling theoretical rationale and empirical evidence linking strong brands with competitive advantages, customer commitment and decreased price sensitivity, thus contributing to firm performance. However, little is known about how customer brand perceptions influence customer response and firm performance in light of negative events such as product recalls. The literature offers competing views with both “customer brand commitment insulate the company,” and “the bigger they are, the harder they fall” arguments being offered. Using a multi-method approach and customer-based brand equity metrics, we explore how customer brand perceptions influence the firm’s product and financial market performance following a recall announcement. We empirically test the product market using experimental data, while the financial market is tested via an event study method. We also examine competitive dynamics in product recalls. Our experimental findings reveal brand quality as critical to recall effects: lower quality recalled brands exhibit smaller decreases in brand perceptions than higher quality recalled brands. We also identify asymmetric competitive dynamics: recalling a high quality brand causes positive increases in lower quality brand evaluations, while high quality brand evaluations do not change when a low quality brand is recalled. Findings from the event study confirm the relevance of customer perceptions: firms with strong brands experience less negative abnormal returns in response to brand recalls. Our findings also indicate competitive asymmetries and distinct time horizons for shareholder responses for focal and competitor firms.
Page 1 and 2: 2011 33 RD ANNUAL INFORMS MARKETING
Page 4 and 5: ii 33 rd AnnuAl MArketing Science c
Page 6 and 7: INFORMS MaRkeTINg ScIeNce cONFeReNc
Page 8 and 9: ReSTauRaNTS IN HOuSTON (continued)
Page 10 and 11: ReSTauRaNTS IN HOuSTON (continued)
Page 12 and 13: SIgHTSeeINg IN aNd aROuNd HOuSTON x
Page 14 and 15: SuMMaRy ScHedule xii 33 rd AnnuAl M
Page 16 and 17: INTeRcONTINeNTal HOTel & cONveNTION
Page 18 and 19: TA09 - Founders III Promotions I Ch
Page 20 and 21: TB09 - Founders III Promotions II C
Page 22 and 23: TC09 - Founders III Promotions III
Page 24 and 25: TD09 - Founders III Retailing I: Ge
Page 26 and 27: FA09 - Founders III Retailing II: G
Page 28 and 29: FB09 - Founders III Retailing III:
Page 30 and 31: FC09 - Founders III Retailing IV: C
Page 32 and 33: FD09 - Founders III Retailing V: Lo
Page 34 and 35: SA09 - Founders III Retailing VI: A
Page 36 and 37: SB09 - Founders III International M
Page 38 and 39: SC09 - Founders III International M
Page 40 and 41: TA02 ■ TA02 Legends Ballroom II G
Page 42 and 43: TA06 MARKETING SCIENCE CONFERENCE -
Page 46 and 47: TA13 MARKETING SCIENCE CONFERENCE -
Page 48 and 49: TB01 MARKETING SCIENCE CONFERENCE -
Page 50 and 51: TB05 MARKETING SCIENCE CONFERENCE -
Page 52 and 53: TB08 4 - Evaluating Financial Risk
Page 54 and 55: TB11 ■ TB11 Champions Center I Re
Page 56 and 57: TC01 MARKETING SCIENCE CONFERENCE -
Page 58 and 59: TC04 3 - Is it a Fad or Necessity?
Page 60 and 61: TC08 3 - Optimal Mailing in a Beta-
Page 62 and 63: TC11 MARKETING SCIENCE CONFERENCE -
Page 64 and 65: TC14 ■ TC14 Champions Center VI C
Page 66 and 67: TD03 MARKETING SCIENCE CONFERENCE -
Page 74 and 75: FA02 ■ FA02 Legends Ballroom II U
Page 76 and 77: FA06 2 - Investigating the Relation
Page 78 and 79: FA10 MARKETING SCIENCE CONFERENCE -
Page 80 and 81: FA13 4 - Modeling the Impact of Vis
Page 82 and 83: FB02 MARKETING SCIENCE CONFERENCE -
Page 90 and 91: FB15 4 - Price Pressure and Supplie
Page 92 and 93: FC03 MARKETING SCIENCE CONFERENCE -
Page 94 and 95:
FC07 4 - Price Competition in the S
Page 96 and 97:
FC10 ■ FC10 Founders IV Segmentat
Page 98 and 99:
FC14 MARKETING SCIENCE CONFERENCE -
Page 100 and 101:
FD02 ■ FD02 Legends Ballroom II U
Page 102 and 103:
FD05 ■ FD05 Legends Ballroom VI G
Page 104 and 105:
FD09 MARKETING SCIENCE CONFERENCE -
Page 106 and 107:
FD12 MARKETING SCIENCE CONFERENCE -
Page 108 and 109:
FD15 ■ FD15 Champions Center V CR
Page 110 and 111:
SA04 MARKETING SCIENCE CONFERENCE -
Page 112 and 113:
SA07 ■ SA07 Founders I Entertainm
Page 114 and 115:
Page 116 and 117:
Page 118 and 119:
SB03 MARKETING SCIENCE CONFERENCE -
Page 120 and 121:
SB06 ■ SB06 Legends Ballroom VII
Page 122 and 123:
SB09 ■ SB09 Founders III Internat
Page 124 and 125:
SB14 MARKETING SCIENCE CONFERENCE -
Page 126 and 127:
SC03 3 - Does Higher Transparency L
Page 128 and 129:
SC09 2 - Buy-now Prices at Entertai
Page 130 and 131:
SC14 2 - Analyzing the Dynamics of
Page 132 and 133:
Author Index A Abou Nabout, Nadia F
Page 134 and 135:
Lee, So Young TD15 Leeflang, Peter
Page 136 and 137:
Session Index Thursday, 8:30am - 10
Page 138 and 139:
S A T U R D A Y Auctions and Consum
show all

2012 INFORMS Marketing Science Conference June 7

Create successful ePaper yourself

Delete template?

Save as template?