Consumer–brand identification revisited: An integrative framework of brand identification, customer satisfaction, and price image and their role for brand loyalty and word of mouth

Consumer–brand identification has received considerable attraction among scholars and practitioners in recent years. We contribute to previous research by proposing an integrative model that includes consumer–brand identification, customer satisfaction, and price image to investigate the interrelationships among these constructs as well as their effects on brand loyalty and positive word of mouth. To provide general results, we empirically test the model using a sample of 1443 respondents from a representative consumer panel and 10 service/product brands. The results demonstrate that identification, satisfaction, and price image significantly influence both loyalty and word of mouth. Moreover, we find significant interrelationships among the constructs: Identification positively influences both satisfaction and price image, which also increases satisfaction. By disclosing the relative importance of three separate ways of gaining and retaining customers, this study helps managers more appropriately choose the right mix of branding, pricing, and relationship marketing. From an academic point of view, our research is the first to explicitly examine the effects of the concept of identification for price management and to integrate variables from the fields of branding, relationship marketing, and behavioral pricing, which have separately been identified as particularly important determinants of marketing outcomes

An evaluation of integer programming models for restaurant reservations

A notable difference in rooms (hotel) revenue management reservations versus table (restaurant) revenue management (TRM) reservations is the variation that occurs in duration. In the hotel setting, durations are explicit in the reservation itself: a stay of a specified number of nights. In restaurants, by contrast, there is a natural variation in the amount of time parties are at the table. This duration variation presents interesting challenges to TRM. Dealing with these challenges is our goal in the article. Specifically, we introduce and evaluate 10 different models for restaurant capacity and reservations, five each of two different types. In one type of model, tables are pooled and parties are not explicitly matched to tables; in the other parties are matched to specific tables. The objective is to maximize revenue (or contribution) from known reservation demand. Variables are both the mix of tables in the restaurant and the reservations accepted. An important ancillary goal we have is to evaluate the effectiveness of the models from the perspective of customers, specifically examining whether a table is ready for them at the time of the reservation, an issue of high importance to restaurant patrons. Of the 10 models, seven define a pareto frontier between revenue and service; of those seven, five are pooling models. We use this frontier to offer advice to restaurateurs looking to better manage reservations.Thompson2_Evaluation_of_integer.pdf: 698 downloads, before Aug. 1, 2020