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We propose a method for analyzing mergers that uses product characteristics to identify products that compete with each other. Products that compete with one another are termed competitive-neighbors. This method does not require aggregation or complicated econometric modeling and is based on sound economic theory. The treatment emphasizes the difference between characteristics that are differentiated by their level of quality (vertical differentiation) and characteristics for which tastes differ across consumers (horizontal differentiation).

This chapter uses a welfare-based conceptual framework for the assessment of costs and benefits associated with nontariff measures in the presence of market imperfections such as asymmetric information and environmental or health externalities. The framework allows for evidence-based comparative assessments of alternative regulatory approaches addressing these imperfections. The conceptual work is illustrated with an empirical case study of labeling internationally traded fish products.

The main purpose of this chapter is to examine the attitudes and behaviors of digital consumers in omnichannel world. For this purpose, in order to understand the behavior of digital consumers, literature review has been made. The transformation of traditional consumers into digital consumers has been examined within the framework of marketing periods. What are the new types of consumers and demographic and psychographic characteristics of these, and how they are segmented in the market are important issues. Another important issue is how digital environmental factors affect digital consumers when shopping online. Purchasing processes of digital consumers and their behaviors, which channels they use and how they make purchasing decisions play an important role in understanding digital consumer behaviors. After the purchasing decision, it is examined whether digital consumers will transfer their experiences to other consumers, satisfaction and loyalty experiences, and whether they will buy again in digital environmental.

Relationship marketing is not effective in every situation or context. This study investigates the impact of three categories of potential contingency factors on the effectiveness of relationship marketing efforts in a retail services context: demographic characteristics of the consumer (age and gender), personal values of the consumer (social affiliation), and shopping-related consumer characteristics (product category involvement, consumer relationship proneness, and shopping enjoyment). The data relate to more than 1,700 mall intercept personal interviews conducted in the United States, and in two western European countries (the Netherlands and Belgium), covering a wide variety of food and apparel retailers. The found moderating influences were inconsistent across samples, stressing the need for an adapted relationship marketing strategy per country and industry. The results do provide a first indication that relationship marketing efforts are relatively more effective if they are directed at consumers who are young and female, have a high need for social affiliation, and show high levels of product category involvement, consumer relationship proneness, and shopping enjoyment. The results provide a preliminary framework for retailers to optimize the allocation of their relationship marketing budgets.

This research reviews numerous studies of the relationship between consumer knowledge and external search in conventional marketing channels to investigate differences among these studies that have produced conflicting results. The findings provide a benchmark for future researchers and practitioners seeking to gain insight into consumer information search processes unfolding in the new environment of online, mobile, and social networking channels.

A meta-analysis of an extensive array of empirical studies of the relationship between consumer knowledge and external information search was conducted. Regression analysis was used to test whether certain characteristics in the studies can explain variability in the effect sizes in which effect sizes are entered as dependent variables and moderators as independent variables.

Objective and subjective knowledge tend to increase search, while direct experience tends to reduce search. Consumers with higher objective knowledge search more when pursuing credence products. However, they search relatively less when pursuing search products. Consumers with higher subjective knowledge are much more likely to search in the context of experience products, but as is the case for objective knowledge having little effect on search for experience products, subjective knowledge has no significant effect on information seeking for search products. In addition, objective knowledge facilitates more information search in a complex decision-making context while higher subjective knowledge fosters more external information search in a simple decision-marketing context. Finally, the findings indicate that the knowledge search relationship reflects strong linkage in the pre-Internet era.

Relatively little is known about how the relationship between knowledge and information search varies across different types of products in simple or complex decision-making contexts. This study begins to fill this gap by providing insight into the relative importance of objective knowledge, subjective knowledge, and direct experience in influencing consumer information search activities for search, experience, and credence products in simple or complex decision-making contexts.

The standard approach in measuring demand responses and consumer preferences assumes particular parametric models for the consumer preferences and demand functions, and subsequently fits these models to observed data. In principle, the estimated demand models can then be used (i) to test consistency of the data with the theory of consumer behavior, (ii) to infer consumer preferences, and (iii) to predict the consumer's response to, say, new prices following a policy reform. This chapter focuses on an alternative, nonparametric approach. More specifically, we review methods that tackle the earlier issues by merely starting from a minimal set of so-called revealed preference axioms. In contrast to the standard approach, this revealed preference approach avoids the use of parametric models for preferences or demand. The structure of the chapter is as follows. First, we introduce the basic concepts of the revealed preference approach to model consumer demand. Next, we consider issues like goodness-of-fit, power, and measurement error, which are important in the context of empirical applications. Finally, we review a number of interesting extensions of the revealed preference approach, which deal with characteristics models, habit-formation, and the collective model.

Instagram is a social media platform that has quickly evolved from a photo-sharing application to a successful marketing tool. It holds various business opportunities, and its rapid growth helps showcase the business offerings. Its innovative use of adverts entices clients, and its visual nature complements the social media marketing strategy. Thus, looking at the dynamic nature and growth of the platform, this chapter outlines the past research trends in the literature of Instagram marketing as the primary objective. This structured review undertakes the study of 76 articles based on defined inclusion and exclusion criteria and analyzes the literature in different contexts. This chapter includes the hybrid review (narrative and framework-based), and findings from the literature highlight a significant influence of Instagram marketing on users. During the brief description of the literature in a different context, the numerous research gaps are outlined with future research directions based on the ADO framework. Lastly, it also presents a broader overview of the managerial and theoretical implications based on the literature of Instagram marketing.