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

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 ...

Contextual and Temporal Components of Reference Price

This study examines whether user-generated content (UGC) is related to stock market performance, which metric of UGC has the strongest relationship, and what the dynamics of the relationship are. We aggregate UGC from multiple websites over a four-year period across 6 markets and 15 firms. We derive multiple metrics of UGC and use multivariate time-series models to assess the relationship between UGC and stock market performance.

Volume of chatter significantly leads abnormal returns by a few days (supported by Granger causality tests). Of all the metrics of UGC, volume of chatter has the strongest positive effect on abnormal returns and trading volume. The effect of negative and positive metrics of UGC on abnormal returns is asymmetric. Whereas negative UGC has a significant negative effect on abnormal returns with a short “wear-in” and long “wear-out,” positive UGC has no significant effect on these metrics. The volume of chatter and negative chatter have a significant positive effect on trading volume. Idiosyncratic risk increases significantly with negative information in UGC. Positive information does not have much influence on the risk of the firm. An increase in off-line advertising significantly increases the volume of chatter and decreases negative chatter. These results have important implications for managers and investors.

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

Technological change is perhaps the most powerful engine of growth in markets today. To harness this source of growth, firms need answers to key questions about the dynamics of technological change: (1) How do new technologies evolve? (2) How do rival technologies compete? and (3) How do firms deal with technological evolution? Currently, the literature suggests that a new technology seems to evolve along an S-shaped path, which starts below that of an old technology, intersects it once, and ends above the old technology. This belief is based on scattered empirical evidence and some circular definitions. Using new definitions and data on 14 technologies from four markets, the authors examine the shape and competitive dynamics of technological evolution. The results contradict the prediction of a single S-curve. Instead, technological evolution seems to follow a step function, with sharp improvements in performance following long periods of no improvement. Moreover, paths of rival technologies may cross more than once or not at all.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID903882_code117251.pdf?abstractid=903882&mirid=5

Technological Evolution and Radical Innovation

When information on product quality is not perfect, theories in the areas of consumer rationality, inference, and risk-aversion suggest at least three consumer choice strategies: best value, price-...

Best Value, Price-Seeking, and Price Aversion: The Impact of Information and Learning on Consumer Choices:

The authors conduct a meta-analysis of 751 short-term and 402 long-term direct-to-consumer brand advertising elasticities estimated in 56 studies published between 1960 and 2008. The study finds several new empirical generalizations about advertising elasticity. The most important are as follows: The average short-term advertising elasticity is .12, which is substantially lower than the prior meta-analytic mean of .22; there has been a decline in the advertising elasticity over time; and advertising elasticity is higher (1) for durable goods than nondurable goods, (2) in the early stage than the mature stage of the life cycle, (3) for yearly data than quarterly data, and (4) when advertising is measured in gross rating points than monetary terms. The mean long-term advertising elasticity is .24, which is much lower than the implied mean in the prior meta-analysis (.41). Many of the results for short-term elasticity hold for long-term elasticity, with some notable exceptions. The authors discuss t...

Gerard J. Tellis

Papers

Contextual and Temporal Components of Reference Price

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

Technological Evolution and Radical Innovation

Best Value, Price-Seeking, and Price Aversion: The Impact of Information and Learning on Consumer Choices:

How Well Does Advertising Work? Generalizations from Meta-Analysis of Brand Advertising Elasticities