计量经济分析 = Econometric analysis

Both practitioners and academics understand that consumer loyalty and satisfaction are linked inextricably. They also understand that this relation is asymmetric. Although loyal consumers are most ...

https://www.jstor.org/stable/pdf/1252099.pdf

Whence Consumer Loyalty

Customer loyalty is viewed as the strength of the relationship between an individual’s relative attitude and repeat patronage. The relationship is seen as mediated by social norms and situational factors. Cognitive, affective, and conative antecedents of relative attitude are identified as contributing to loyalty, along with motivational, perceptual, and behavioral consequences. Implications for research and for the management of loyalty are derived.

Customer Loyalty: Toward an Integrated Conceptual Framework:

1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

Consumer perceived value: The development of a multiple item scale

The author describes a meta-analysis of econometric studies that estimated the elasticity of selective sales or market share to price. The literature review yielded 367 suitable price elasticities ...

The Price Elasticity of Selective Demand: A Meta-Analysis of Econometric Models of Sales:

Information processing theory and findings on advertising response suggest a nonlinear response to repetitive ad exposure, mediated by brand loyalty. The response can occur in either or both of the...

Advertising Exposure, Loyalty, and Brand Purchase: A Two-Stage Model of Choice:

Online chatter, or user-generated content, constitutes an excellent emerging source for marketers to mine meaning at a high temporal frequency. This article posits that this meaning consists of extracting the key latent dimensions of consumer satisfaction with quality and ascertaining the valence, labels, validity, importance, dynamics, and heterogeneity of those dimensions. The authors propose a unified framework for this purpose using unsupervised latent Dirichlet allocation. The sample of user-generated content consists of rich data on product reviews across 15 firms in five markets over four years. The results suggest that a few dimensions with good face validity and external validity are enough to capture quality. Dynamic analysis enables marketers to track dimensions' importance over time and allows for dynamic mapping of competitive brand positions on those dimensions over time. For vertically differentiated markets (e.g., mobile phones, computers), objective dimensions dominate and are similar acr...

Mining Marketing Meaning from Online Chatter: Strategic Brand Analysis of Big Data Using Latent Dirichlet Allocation:

User-Generated Content in online platforms or chatter for short provides a valuable source of consumer feedback on market performance of firms. This study examines whether chatter can predict stock market performance, which metric of chatter has the strongest relationship, and what the dynamics of the relationship are. The authors aggregate chatter (in the form of product reviews) from multiple websites over a four year period across six markets and fifteen firms. They derive multiple metrics of chatter (volume, positive chatter, negative chatter, and 5-start ratings) and use multivariate time series models to assess the short and long term relationship between chatter and stock market performance. They use three measures of stock market performance: abnormal returns, risk, and trading volume.The findings reveal that two metrics of chatter can predict abnormal returns with a lead of a few days. Of four metrics of chatter, volume shows the strongest relationship with returns and trading volume, followed by negative chatter. Whereas negative chatter has a strong effect on returns and trading volume with a short “wearin” and long “wearout,” positive chatter has no effect on these metrics. Negative chatter also increases volatility (risk) in returns.A portfolio analysis of trading stocks based on their chatter provides a return of 8% over and above normal market returns. In addition to the investing opportunities, the results show managers that chatter is an important metric to follow to gauge the performance of their brands and products. Because chatter is available daily and hourly, it 2 can provide an immediate pulse of performance that is not possible with infrequent sales and earnings reports. The fact that negative chatter is more important than positive, indicates that negatives are more diagnostic than positives. The negatives suggest what aspects of the products managers should focus on.

Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance

An emerging consensus in marketing is that consumers respond to price relative to some standard or reference price. Most researchers modeling brand choice have reasoned that this standard is based on past prices of the brand. The authors argue that consumers do use reference prices, but one that is also based on context- other prices in the store-rather than on past prices alone. An analysis of households' brand choices in two subcategories and over three cities support this premise. Within context, the lowest price seems to be an important cue for reference price, whereas within time, a brand's own past prices seem to be the most important cue. Households' use of a contextual reference price also varies predictably across some consumer characteristics. Though their model can be applied to other categories, the findings have important managerial implications: Managerial focus on temporal reference prices could lead to an everyday high price, whereas focus on contextual reference prices could lead to an everyday low price. Only the inclusion of both contextual and temporal reference prices justifies variable pricing.

https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=907228

Gerard J. Tellis

Papers

The Price Elasticity of Selective Demand: A Meta-Analysis of Econometric Models of Sales:

Advertising Exposure, Loyalty, and Brand Purchase: A Two-Stage Model of Choice:

Mining Marketing Meaning from Online Chatter: Strategic Brand Analysis of Big Data Using Latent Dirichlet Allocation:

Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance

Contextual and Temporal Components of Reference Price