Consumer Price Sensitivity Research Articles

The Effect of Consumer Participation on Price Sensitivity

This study examined the noneconomic factors affecting consumers’ participation in purchase decisions, focusing in particular on the social aspect of the buyer‐seller interaction. In addition, we attempted to clarify the association between consumer participation and price sensitivity. Of the four social dimensions of consumer participation—preparation, relationship building, information exchange, and intervention—our results indicated that the first three dimensions are negatively associated with price sensitivity but the intervention dimension is not. Additionally, we also found that, given the same level of preparation, industries typically characterized by higher participation, such as hair salons, are associated with lower consumer price sensitivity as compared to those typically characterized by lower participation, such as fast food restaurants. Similarly, given the same level of relationship building, information exchange, and intervention, industries typically characterized by higher participation have lower consumer price sensitivity than those typically characterized by lower participation.

Salesforce design with experience-based learning

This paper proposes and analyzes an integrated model of salesforce learning, product portfolio pricing and salesforce design. We consider a firm selling two products, with a pool of sales representatives that is split into separate salesforces, one for each product. The salesforce assigned to each product is faced with an independent stream of sales leads. The salesforce may also handle leads that overflow from other product salesforces. In addition, salespeople “learn by doing” over their tenure on the job. In particular, the more time they spend selling a particular product, the more productive the sales effort. The objective of the firm is to maximize profits by optimizing the size of all salesforces as well as the prices of all products. Using data collected from the salesforce of a large manufacturer, we provide evidence for the link between experience and sales, and we demonstrate how parameters of the model may be estimated from real data. Numerical experiments using parameters derived from the data analysis indicate that the optimal salesforce size increases with both sales productivity and the learning rate, and decreases with salesforce costs (e.g., wage per representative), product production costs and consumer price sensitivity. We also find that worker learning can significantly dampen the effect of rising costs (or decreasing margins) on staffing levels. Finally, we examine the impact of learning on both the optimal salesforce structure (specialists versus generalists) as well as the optimal routing of sales leads to sales representatives.

Bayesian Analysis of Simultaneous Demand and Supply

In models of demand and supply, consumer price sensitivity affects both the sales of a good through price, and the price that is set by producers and retailers. The relationship between the dependent variables (e.g., demand and price) and the common parameters (e.g., price sensitivity) is typically non-linear, especially when heterogeneity is present. In this paper, we develop a Bayesian method to address the computational challenge of estimating simultaneous demand and supply models that can be applied to both the analysis of household panel data and aggregated demand data. The method is developed within the context of a heterogeneous discrete choice model coupled with pricing equations derived from either specific competitive structures, or linear equations of the kind used in instrumental variable estimation, and applied to a scanner panel dataset of light beer purchases. Our analysis indicates that incorporating heterogeneity into the demand model all but eliminates the bias in the price parameter due to the endogeneity of price. The analysis also supports the use of a full information analysis.

Internet‐induced changes in consumer music procurement behavior: a German perspective

The aim of the present study is to investigate and analyze Internet‐related consumer music procurement behavior and its effects on traditional music procurement using a Web questionnaire with a sample of more than 4,000 Internet users (the word “procurement”, as opposed to purchase, is used because some procurement satisfies the consumers’ need for music but they do not pay for it). Four motive factors for the willingness to pay for online music were found and subsequent cluster analysis identified three meaningful and distinct downloader groups who are willing to pay for online music: demanding downloaders; general download approvers; procurement autonomous. Consumer price sensitivity for two different commercial online‐music distribution models was very similar and the majority of users had similar ideas as to how much a commercial download service should cost. Implications for marketing research and practitioners are discussed.

Smart Agents: When Lower Search Costs for Quality Information Increase Price Sensitivity

Recent consumer research suggests that lowering search costs for quality information reduces consumer price sensitivity by creating greater perceived differentiation among brands (e.g., Kaul and Wittink 1995; Lynch and Ariely 2000). We argue that lowering quality search costs by smart agents can have the opposite effect on differentiation and price sensitivity. Smart agents screen through a universe of alternatives, recommending only a handful well-matched to the customer's quality preferences. In this research, we ask and answer the following questions: In markets in which price and quality are uncorrelated, will the use of screening agents increase or decrease prices paid compared to searching from an unordered list of options? Will increasing the size of the store's underlying assortment increase or decrease prices paid when options have been screened on quality? In markets where higher priced goods have higher quality, will the use of screening agents increase or decrease prices paid and quality selected? Experiments 1 and 2 test the effect of quality screening when price and quality are uncorrelated. We then present an analytic model for markets in which price and quality are correlated. We deduce that ordering can cause price and quality to increase or decrease depending on the slope of the price-quality relationship in comparison with the relative importance of price in the utility function. We find support for this model in experiment 3.

Measuring Prices and Price Competition Online: Amazon.com and BarnesandNoble.com

Despite the interest in measuring price sensitivity of online consumers, most academic work on Internet commerce is hindered by a lack of data on quantity. In this paper we use publicly available data on the sales ranks of about 20,000 books to derive quantity proxies at the two leading online booksellers. Matching this information to prices, we can directly estimate the elasticities of demand facing both merchants as well as create a price index for online books. The results show significant price sensitivity at both merchants but demand at BarnesandNoble.com is much more price-elastic than is demand at Amazon.com. The data also allow us to estimate the magnitude of bias in the CPI due to the rise of Internet sales.

Accounting for heterogeneity and dynamics in the loyalty–price sensitivity relationship

Accounting for heterogeneity and dynamics in the loyalty–price sensitivity relationship

Smart Agents: When Lower Search Costs for Quality Information Increase Price Sensitivity

Recent consumer research suggests that lowering search costs for quality information reduces consumer price sensitivity by creating greater perceived differentiation among brands (e.g., Kaul and Wittink 1995; Lynch and Ariely 2000). We argue that lowering quality search costs by smart agents can have the opposite effect on differentiation and price sensitivity. Smart agents screen through a universe of alternatives, recommending only a handful well-matched to the customer's quality preferences. In this research, we ask and answer the following questions: In markets in which price and quality are uncorrelated, will the use of screening agents increase or decrease prices paid compared to searching from an unordered list of options? Will increasing the size of the store's underlying assortment increase or decrease prices paid when options have been screened on quality? In markets where higher priced goods have higher quality, will the use of screening agents increase or decrease prices paid and quality selected? Experiments 1 and 2 test the effect of quality screening when price and quality are uncorrelated. We then present an analytic model for markets in which price and quality are correlated. We deduce that ordering can cause price and quality to increase or decrease depending on the slope of the price quality relationship in comparison with the relative importance of price in the utility function. We find support for this model in Experiment 3.

Managed competition and consumer price sensitivity in social health insurance

This paper examines whether the introduction of managed competition in Dutch social health insurance has resulted in effective price competition among insurance funds. We find evidence of limited price competition, which may be caused by low consumer price sensitivity. Using aggregate panel data from all insurance funds over the period 1996–1998, estimated premium elasticities of market share are −0.3 for compulsory coverage and −0.8 for supplementary coverage. These elasticities are much smaller than in managed competition settings in US group insurance. This may be explained by differences in switching experience and higher search costs associated with individual insurance.

Measuring Prices and Price Competition Online: Amazon and Barnes and Noble

Despite the interest in measuring price sensitivity of online consumers, most academic work on Internet commerce is hindered by a lack of data on quality. In this paper we use publicly available data on the sales ranks of about 20,000 books to derive quantity proxies at the two leading online booksellers. Matching this information to prices, we can directly estimate the elasticities of demand facing both merchants as well as create a consumer price index for online books. The results show significant price sensitivity at both merchants but demand at Barnes and Noble is much more price-elastic than is demand at Amazon. The data also allows us to estimate the magnitude of retail outlet substitution bias in the CPI due to the rise of Internet sales. The estimates suggest that prices online are much more variable than the CPI, which understates inflation by more than double in one period and gets the sign wrong in another.

The impact of brand credibility on consumer price sensitivity

Brands can affect various stages of consumer choice processes, and hence, various components of consumer utility functions. Previous conceptual and empirical work focused on the effects of brands on consumer perceptions of tangible and intangible product attributes. In this paper, we extend the work on brand effects with information economics underpinnings to analyze whether consumer price sensitivity, that is, the weight attached to price in a consumer valuation of a product's overall attractiveness or utility, is impacted by brand credibility. In other words, we investigate how the impact of product price on consumer utility is moderated by brand credibility. To explore the impact of brand credibility on consumer price sensitivity across categories that may involve different levels of consumer uncertainty, we conduct our analysis for four products: frozen concentrate juice, jeans, shampoo and personal computers. These categories vary in the degree of potential consumer uncertainty about product attributes, as well as in a number of other category-specific features that may affect consumer sensitivity to uncertainty. Our results indicate that brand credibility decreases price sensitivity. Our results also indicate that although the direction of the impact is the same, the magnitude of brand credibility's impact on consumer choices and price sensitivity vary across product categories, as a function of product category characteristics that affect potential consumer uncertainty and consumer sensitivity to such uncertainty.

Consumer price sensitivity and price thresholds

We examine consumers’ price sensitivity using a new approach that incorporates probabilistic thresholds for price gains and price losses in the reference price models. We model the threshold as a function of company, competitor and consumer specific factors. Model application to scanner panel data for coffee shows that our model is superior in fit compared to ordinary logit and two existing reference price models. Our results indicate that higher own-price volatility makes consumers more sensitive to gains and less sensitive to losses, while intense price promotion by competing brands makes consumers more sensitive to losses but does not influence consumers’ sensitivity to gains. Two clear segments that differ in the size of their thresholds emerge. Managerial implications of these results for segmentation and understanding brand power are discussed.

Household Electricity Demand, Revisited

respond to price changes. This paper develops a model for evaluating the effects of alternative tariff designs on electricity use. The model concurrently addresses several interrelated difficulties posed by nonlinear pricing, heterogeneity in consumer price sensitivity, and consumption aggregation over appliances and time. We estimate the model using extensive data for a representative sample of 1300 California households. The results imply a strikingly skewed distribution of household electricity price elasticities in the population, with a small fraction of households accounting for most aggregate demand response. We then estimate the aggregate and distributional consequences of recent tariff structure changes Recent efforts to restructure electricity markets have renewed interest in electricity demand and pricing. This interest reflects a broad desire to improve the efficiency of electricity markets, and policy-makers' concerns over the impact of price changes on consumers. How new pricing mechanisms would affect households' consumption and expenditures is a matter of considerable uncertainty, however. This uncertainty has provoked controversy and debate in the regulatory policy arena, hampering market reforms. Using econometric methods to assess the effects of electricity price changes presents several challenges. These include the nonlinear structure of tariff schedules, aggregation of metered consumption behaviour over time and appliances, and the interdependence of energy use with longer-term household decisions over appliance ownership and dwelling characteristics. The first two issues introduce complex simultaneity problems between marginal prices and consumption. The third issue imposes high data requirements (information on household-specific appliance holdings and residence features), and creates heterogeneity in consumption responses related to the characteristics of these durable goods. When the researcher's objective is to develop a model for simulating the effects of prospective tariff changes, ignoring these issues will provide an incomplete assessment of demand responses and potentially misleading predictions of a new tariff's consumption and revenue consequences. In this paper, we estimate a model of household electricity demand that can be used

Salesforce Design with Experience-based Learning

This paper proposes and analyzes an integrated model of salesforce learning, product portfolio pricing and salesforce design. We consider a firm with a pool of sales representatives that is split into separate salesforces, one for each product. The salesforce assigned to each product is faced with an independent stream of sales leads. The salesforce may also handle leads that overflow from other product salesforces. In addition, salespeople learn by doing over their tenure on the job. In particular, the more time they spend selling a particular product, the more productive the sales effort. The objective of the firm is to maximize profits by optimizing the size of all salesforces as well as the prices of all products. The results obtained from this model reveal some important insights into the structure and size of optimal salesforces in environments characterized by learning and product complexity. Numerical experiments with the model indicate that salesforce size increases with salesforce productivity and decreases with salesforce costs (per representative), product production costs and consumer price sensitivity. We also find that learning plays a complex role in determining optimal salesforce staffing. In particular, when calculating the value of an additional salesperson, we identify a tradeoff between the incremental revenue due to increased throughput and the incremental decrease in utilization, learning, and productivity for the entire salesforce. We also examine the issue of specialization in salesforce design and discuss the conditions governing its optimality. The results highlight the value of conducting salesforce design with a full understanding of the related operational issues of experience-based learning and queueing phenomena.

Measuring consumer quality judgements

Many on‐farm‐processed products frequently command a premium price, characterised as they are by unique sensory properties and image. Examines the nature of consumer judgements about product quality for farmhouse Cheddar cheeses based on utilities derived from the product attributes, and the trade‐off against price. Determines key Cheddar cheese attributes through in‐depth interviews with specialist cheese consumers and employs conjoint analysis to estimate the utilities associated with these attributes based on a wider choice‐experiment survey of farmhouse Cheddar consumers. A “price sensitivity meter” technique was used to establish acceptable price ranges as perceived by the latter group. Results from market simulations suggest that the consumer price sensitivity for farmhouse cheese is likely to be low. The analysis also revealed that those attributes associated with the traditional characteristics of farmhouse Cheddar have the highest utilities and that any characteristics similar to industrial Cheddar were largely unattractive to the consumers of farmhouse cheese.

The Effects of Acculturation on Consumers' Sensitivity to Prices

ABSTRACT This study drew upon anthropological learning models, research in cross-cultural psychology, and research in pricing to understand how an immigrant population's learning of a new culture and its norms affects their evaluation of price information and price acceptability for products offered in the host culture. Specifically, this study used a survey methodology to examine the effects of acculturation on the price sensitivity of Asian-Indian consumers. The survey included measures of participants' acculturation levels (measured by the SL-ASIA scale), price acceptability and prior knowledge. Findings suggest that as Asian-Indians' acculturation levels increase, higher prices become more acceptable. In particular, this appears to be true more for Asian-Indian females than males. With increasing acculturation the range of acceptable prices of the highly acculturated Asian-Indian consumers started to resemble those of the U. S. sample, hence supporting thelearning modelsof acculturation.

Market Share and Price Setting Behavior for Private Labels and National Brands

In this paper, we focus on the nature of demand and competitive response in the market for private label and national “branded” grocery products. Specifically,we employ less restrictive functional forms than usedin prior research. Specifically, we incorporateLA/AIDS demands and the corresponding price reactionequations to estimate consumer price sensitivities andsupply side price strategies for national brand andprivate label products. Oligopolistic priceinterdependence is explored further by specifyingbrand share, brand Herfindahl, and a measure of thestructure of the local retail markets in the supplyside relations to evaluate explicitly the impact ofmarket structure.

Missing price and coupon availability data in scanner panels: Correcting for the self-selection bias in choice model parameters

Discrete choice models have been widely estimated on scanner panel data to study consumer choice. One challenge in scanner panel research is that only the prices of the items bought are recorded. The ad hoc models used to fill in the missing prices of non-purchased brands may create a self-selection bias in estimating consumer price sensitivities. This type of bias is also present in existing studies of coupon effects. To obtain consistent estimates of price elasticities in the presence of missing price and coupon values, we estimate a brand choice model jointly with models for the price and coupon processes.

Spatial Pricing in Interdependent Markets: Testing Assumptions and Modeling Price Variation. A Case Study of Gasoline Retailing in St Cloud, Minnesota

In this paper we present an empirical evaluation of assumptions about consumer purchasing behavior for gasoline. Previous research has developed a theoretical model of spatial pricing in oligopolistically competitive markets in which it is hypothesized that retail prices vary because of both consumer price sensitivity and the choice sets available to consumers as well as awareness of prices at competing locations. With the use of household survey data collected from St Cloud, Minnesota we evaluate the plausibility of these assumptions, finding evidence to support the consumer purchasing behavior assumed in the theoretical model. By means of a spatial time series of gasoline price data for the same metropolitan area, we develop an empirical model of spatial price variation that incorporates some of the hypotheses of the original model. The results suggest support for the proposition that spatial price variations depend on the service characteristics of individual retailers and the accessibility or locational advantage of individual gasoline stations within the spatial configuration of the urban market. There also is empirical support for the conjecture that those sites which are more accessible, have larger choice sets, and charge lower prices tend to be those which attract the most sales from other retailers.

A conjoint model of enhanced voice mail services. Implications for new service development and forecasting

Abstract Despite its absence in the literature, conjoint modeling can be a powerful tool for telecom policy and business decisions. Using this technique, we examined the US opportunity for a large number of network-based messaging services. Our model has successfully forecast US voice mail penetration and pricing levels from 1993 to present. The results demonstrate that, when properly applied, conjoint analysis yields: (1) accurate identification of consumer priorities and price sensitivities; (2) underlying benefits-based market segmentation; and (3) realistic, efficient demand forecasts for multiple market scenarios.