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

Les auteurs conduisent une meta-analyse sur la base de 751 elasticites a court terme et 402 a long terme concernant des publicites de marque visant directement le consommateur issues de 56 etudes p...

À quel point la publicité est-elle efficace? Généralisations à partir d'une méta-analyse de L'élasticité publicitaire des marques:

Competition is intense among rival technologies and success depends on predicting their future trajectory of performance. To resolve this challenge, managers often follow popular heuristics, generalizations, or “laws” like the Moore’s Law. We propose a model, Step And Wait (SAW), for predicting the path of technological innovation and compare its performance against eight models for 25 technologies and 804 technologies-years across six markets. The estimates of the model provide four important results. First, Moore's Law and Kryder's law do not generalize across markets; none holds for all technologies even in a single market. Second, SAW produces superior predictions over traditional methods, such as the Bass model or Gompertz law, and can form predictions for a completely new technology, by incorporating information from other categories on time varying covariates. Third, analysis of the model parameters suggests that: i) recent technologies improve at a faster rate than old technologies; ii) as the number of competitors increases, performance improves in smaller steps and longer waits; iii) later entrants and technologies that have a number of prior steps tend to have smaller steps and shorter waits; but iv) technologies with long average wait time continue to have large steps. Fourth, technologies cluster in their performance by market.

Predicting the Path of Technological Innovation: SAW Versus Moore, Bass, Gompertz, and Kryder

The product life cycle (PLC) is a central, enduring framework in marketing. The four stages of introduction, growth, maturity, and decline are appealing intuitively and are supported empirically in recent research. Here, we draw on several literatures to develop an integrated theory to explain the observed shape of the PLC. We present specific definitions and metrics for key events and stages of the PLC. On the basis of these definitions and metrics, we present generalizable results for many characteristics of the PLC based on a sample of 30 consumer durables. Results include duration of stages, sales volume, sales growth, price reductions, and penetration. There is a dramatic increase in sales at the transition from the introduction stage to the growth stage, and a sudden change from sales growth to sales decline at the transition from the growth stage to the maturity stage. Overall, the PLC is a useful framework for understanding and anticipating the sales growth of new consumer durables.


Keywords:

diffusion of innovation;
sales takeoff;
Bass model;
new products;
informational cascades

Product Life Cycle

Reply to Comments: Why and How Quality Wins Over Network Effects and What It Means?

This commentary aims to enrich and contextualize the paper by Sheth and Koschmann, “Do Brands Compete or Coexist?” How persistence of brand loyalty segments the market.,This paper is a comment piece written in response to Sheth and Koschmann’s “Do brands compete or coexist? How persistence of brand loyalty segments the market”.,In their article, Sheth and Koschmann present some fascinating insights on competition in mature markets and the concept of brand loyalty, offering three novel hypotheses. However, while the manner in which their findings are stated is novel, the fact that brand loyalty is strong is not new. This note outlines several comments upon the research, three caveats and five opportunities for future research in the area. While Sheth and Koschmann’s approach is novel, their results are not altogether new and their research needs to be related to prior findings on brand loyalty across the canon.,This response to Sheth and Koschmann’s paper provides a scholarly dialogue centered upon the premise of brand loyalty within the context of market competition.

Gerard J. Tellis

Papers

À quel point la publicité est-elle efficace? Généralisations à partir d'une méta-analyse de L'élasticité publicitaire des marques:

Predicting the Path of Technological Innovation: SAW Versus Moore, Bass, Gompertz, and Kryder

Product Life Cycle

Reply to Comments: Why and How Quality Wins Over Network Effects and What It Means?

Comments on “Do brands compete or co-exist?”