Economic valuation of product features

Allenby, Greg M.; Brazell, Jeff D.; Howell, John R.; Rossi, Peter E.

doi:10.1007/s11129-014-9150-x

Cited by 67 publications

(18 citation statements)

References 20 publications

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“…Finally, we derive average WTP estimates for nutrition shelf labels as well as for related voluntary FOP nutrition claims by following two commonly used methods described in the literature: (1) dividing the estimates for γ from equation (6) by the average marginal utility of price β from the same equation; (2) using the demand results to estimate the change in consumer welfare (or surplus) due to the label changes in counterfactual simulations that keep prices constant. The second approach is based on simulations that remove shelf labels associated with significant WTP estimates (see Small and Rosen ; Allenby et al ).…”

Section: Results From the Structural Demand Estimationmentioning

confidence: 99%

“…Using the observed consumer choices after our labels were posted, we can compute the resulting consumer surplus and simulate consumer choices if labels would have not been added. We compute the changes in consumer surplus, ceteris paribus (prices unchanged) following Small and Rosen () and Allenby et al (). We first define the compensation variation or average expected consumer surplus, CS i , as:

{CS}_{jt} = \frac{1}{∣ β ∣} italicln \sum_{j} e^{α_{j} + α_{t} + X_{jt} β_{x} - β {price}_{jt}} + C,

where β denotes the average marginal utility of price and C is a constant.…”

Section: Welfare Changes Under Different Labeling Scenariosmentioning

confidence: 99%

“…Finally, we consider potential strategic firm responses resulting from an actual implementation of such labels under several supply scenarios. In simulations we first estimate a pure switching effect induced by our labels while keeping prices constant and then allow prices to adjust in order to estimate overall welfare changes under various degrees of market power (Small and Rosen ; Petrin ; Allenby et al ).…”

mentioning

confidence: 99%

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Consumer and Strategic Firm Response to Nutrition Shelf Labels

Villas-Boas¹,

Kiesel²,

Berning

et al. 2020

American J Agri Economics

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The display of nutrition facts is mandatory on virtually all packaged foods sold in the United States. Yet manufacturers and retailers add their own claims to differentiate their products and capture consumers' attention at point of sale. We implement experimental nutrition claims on shelf labels in a retail setting and test how consumers react to the display of these labels that express information reported on the Nutrition Facts Panel in a different format. We hypothesize that our labels either shift demand for the highlighted healthier products uniformly or trigger more complex demand rotations. Our estimated heterogeneous labeling effects suggest that consumers process nutrition information differently depending on which and how many claims are displayed and prefer products labeled with a single claim overall. When we simultaneously consider demand and supply responses under three price setting behaviors (competitive pricing, Bertrand‐Nash pricing, and monopoly pricing), we find that consumer surplus and overall welfare is highest when our labels display multiple nutrient claims and retailers are able to adjust prices across the entire product category. Firms' profits are highest when single nutrient claims are displayed, however. We conclude that firms with market power have little incentive to voluntarily display nutrition claims that maximize welfare.

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Section: Results From the Structural Demand Estimationmentioning

confidence: 99%

{CS}_{jt} = \frac{1}{∣ β ∣} italicln \sum_{j} e^{α_{j} + α_{t} + X_{jt} β_{x} - β {price}_{jt}} + C,

where β denotes the average marginal utility of price and C is a constant.…”

Section: Welfare Changes Under Different Labeling Scenariosmentioning

confidence: 99%

mentioning

confidence: 99%

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Consumer and Strategic Firm Response to Nutrition Shelf Labels

Villas-Boas¹,

Kiesel²,

Berning

et al. 2020

American J Agri Economics

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“…Specifically, we assume that firm 1 keeps the privacy practice of the status quo scenario and firm 2 differentiates. We use the root-finding method of Allenby et al (2014) to estimate Nash price equilibria for each posterior draw and calculate the mean revenue change to the benchmark scenario of having no differentiation. Equilibria exist in the majority of draws (96.6%, on average).…”

Section: Price Equilibriamentioning

confidence: 99%

The Market for Privacy: Understanding How Consumers Trade Off Privacy Practices

Eggers¹,

Beke²,

Verhoef³

et al. 2023

Journal of Interactive Marketing

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In recent years, firms’ privacy practices have received increasing attention from consumers. While firms largely see this development as a threat, as consumers might prohibit collection or use of data, we suggest that it can also represent an opportunity for firms. On the “market for privacy,” firms can gain a competitive advantage by differentiating and actively promoting preferred privacy practices. In this context, the authors study how consumers trade off five privacy elements, three relating to distributive fairness (i.e., information collection, storage, use) and two relating to procedural fairness (i.e., transparency, control). Moreover, they analyze how the impact of these elements differs among four industries that vary in information sensitivity and interaction intensity. By using discrete choice experiments, the authors show that all privacy elements matter to consumers, even when in a trade-off with price. In highly sensitive industries, differences in information collection and use matter more, while storage matters less, for differentiation. When consumers have less frequent interactions with companies, they require more transparency about their privacy practices. The authors demonstrate empirically that optimizing privacy practices can lead to robust changes in market shares (Study 1) and higher revenues in equilibrium (Study 2) when firms embrace the market for privacy.

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“…From its prevalence in empirical applications, Equation 4 could be regarded as the de facto standard in the marketing literature. Allenby et al (2014a) rely on this model but suggest removing respondents on the basis of small marginal likelihoods from the estimation sample to improve inferred prices from CBC optimization exercises. As some may see dropping informationpoor respondents as an alternative to accounting for unobserved budgets, we include the Allenby et al (2014a) model as a benchmark model in the empirical application.…”

Section: Benchmark Modelsmentioning

confidence: 99%

Omitted Budget Constraint Bias and Implications for Competitive Pricing

Pachali¹,

Kurz²,

Otter³

2023

Journal of Marketing Research

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Standard Choice-Based Conjoint (CBC) models often ignore or insufficiently approximate consumers’ budget constraints, despite the prominent role of budget constraints in economic theory. The authors offer a theoretically motivated improvement to the CBC model that is especially appropriate for high-ticket durable goods and develop a Bayesian method for the inference of unobserved budget constraints. The proposed method leverages respondents’ stated budget constraints that suffer from measurement error and respondents’ financial demographic variables as additional information to reduce the dependency on functional form assumptions in the estimation. The authors show that accounting for budget constraints substantially increases model fit and the accuracy of competitive pricing in an industry-grade discrete-choice experiment on consumer preferences for high-end laptops. The proposed model performs better than the canonical linear price benchmark model, which is not flexible enough to approximate budget constraints. In theory, more flexible utility specifications, such as the non-linear dummy price model, can approximate consumers’ budget constraints. However, they perform poorly when only finite data are available. The authors conclude that applied researchers in industry and academia will benefit from having a better tool for estimating budgets in high-ticket categories.

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Economic valuation of product features

Cited by 67 publications

References 20 publications

Consumer and Strategic Firm Response to Nutrition Shelf Labels

Consumer and Strategic Firm Response to Nutrition Shelf Labels

The Market for Privacy: Understanding How Consumers Trade Off Privacy Practices

Omitted Budget Constraint Bias and Implications for Competitive Pricing

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