The phenomenon of globalization has been shaping the world economy and societies for centuries. However, a renewed interest in understanding its impact on marketing and consumers has come into the spotlight in recent years as the COVID-19 pandemic has shown how interdependent the world is. In addition, anti-globalization sentiment is growing worldwide. We believe this is a good time to take stock of the impact of globalization on businesses (especially on positioning and marketing strategies) and consumers’ responses. The aim of this monograph is to provide an overview of globalization as a phenomenon that affects business activities and consumer behavior. Upon providing a brief history of globalization and identifying the key aspects of its conceptualization, we review the impact on the emergence of a global consumer culture, the positioning and marketing strategies adopted by firms, the reactions of consumers to globalization itself (i.e., their attitudes toward it and their identity shifts) and to the diversity of products and services available in a global marketplace, and the idiosyncratic ways in which globalization affects some key industries (e.g., technology, consumer goods, and media and entertainment) and countries. We conclude with a discussion on the need for research to further understand the impact of globalization on consumption, the opportunities at the intersection of globalization and technology development, and the effects of globalization on sustainable business practices.

Examining the impact of technology on marketing has been an important research topic dating to the advent of radio, TV, and the Internet. Whereas each new technology had its own implications in the history of marketing research, it is becoming increasingly clear that the emergence of artificial intelligence (AI) is changing the marketing landscape in an unprecedented way. AI technology has been long out there, but recent breakthrough developments suggest we are entering a new technological zeitgeist with profound implications for both marketers and consumers. The current research provides a systematic review of academic AI research conducted in the domain of marketing and consumer psychology. The current review integrates previous research published in leading marketing and psychology journals between 2018 and 2023, during which behavioral research on AI has grown substantially. We synthesize the existing literature and provide guidance for behavioral researchers working in this area. This review concludes with a discussion on critical issues associated with AI and makes suggestions for future research directions.

Every year billions of users around the world submit trillions of queries through online search engines such as Google, Bing, Baidu, and Yandex. Over the years, aggregated and anonymized search volume data on keywords contained in all these queries have formed an epic database of human intentions that continues to expand every day. Thanks to platforms such as Google Trends, Google Ads Keyword Planner, Microsoft Advertising Keyword Planner, Baidu Index, and Yandex Wordstat, advertisers can readily assess search engine users’ collective interests over time and across geographic areas to optimize their search engine marketing efforts. In this monograph, we illustrate how online search volume data, indexed or otherwise, can be leveraged as a powerful source of marketing insights for purposes beyond search engine marketing. We do so by offering a brief tutorial on Google Trends and Google Ads Keyword Planner, two popular (and free) platforms for gathering online search trend and volume data, respectively. We review prior studies that have examined the use of aggregate online search data as (1) predictors for nowcasting and forecasting, (2) dependent variables in market response modeling, and (3) proxies for otherwise hard-to-measure constructs. In each of these three areas, we provide specific examples of applications to illustrate the power and versatility of online search data. We conclude by offering several ideas for future research where we see the full potential of online search data is still to be uncovered.

The academic discipline of finance has been linked with the field of marketing, an enterprise referred to as “research on the marketing-finance interface.” It investigates the relationships between marketing-related variables and metrics of the behavior of financial-market participants, including analysts, investors, and creditors. Fundamental questions include: Do investors (and, therefore, the stock market) react when companies build brands, launch new products and engage in marketing activities that may not yield immediate cash-flow benefits, but strengthen the long-term viability of the enterprise? Conversely, are managers influenced by investor behavior? A firm’s stock price is a recognized consensus metric of its economic health and, as such, marketers are well served by knowing which of their actions, if any, either lift or depress stock prices. This monograph integrates research in marketing, finance, and accounting into an overarching marketing–finance research framework. The timing is right for this monograph for several reasons. First, the number of empirical articles in major journals has grown to almost 300, with managers and researchers being confronted with an array of metrics, methods, and findings. Second, there has been a broadening of the metrics analyzed on both the marketing and the firm value side. Last, but not least, there is a growing trend in redefining the role of the corporation from maximizing shareholder value to providing value to several stakeholders, and the next-generation consumers will increasingly act on the notion that the primary purpose of a business is not to generate profits, but to improve society.

This monograph introduces and compares the two leading frameworks for analyzing the adoption and diffusion of innovations – the imitation and threshold models. Imitation models perceive the diffusion process as being driven primarily by communication, whether initiated by the firm or between existing and potential customers, and are particularly useful when aggregate data is available, and allows the incorporation of some economic variables. By contrast, the threshold model emphasizes individual micro-economic decision making and explains the differences in the timing of adoption by heterogeneity among individuals or firms while the dynamic processes of learning affect costs as well as perceptions of value that drive the diffusion process. The threshold model provides a foundation to use cross section and panel data to estimate factors that affect differences in adoption patterns including size, wealth, education, and attitude towards risk. We show how to incorporate multiple marketing tools into both models. We find that the threshold model affords a more refined consideration of risk to optimize the choice of marketing tools because the threshold model can explicitly incorporate various economic frameworks such as expected utility, loss aversion and disappointment models, the safety-rule approach, and real-option theory. We illustrate how to manage marketing risk reduction tools in this context, including money back guarantees and demonstrations. Our review suggests that the two models should be treated as complementary models rather than as substitutes for each other. Our analysis expands on the analysis and design of marketing tools in promoting diffusion and discusses how to enhance their relevance and effectiveness. It also provides a bridge between marketing tools and the economic analysis of diffusion.

Machine Learning in Marketing: Overview, Learning Strategies, Applications, and Future Developments

In this monograph, we build on the risk communication and the psychology of information processing and decision-making literatures, while extending this work through an explicit discussion of the philosophical foundations of risk communication, regulations, and the implications for communication and policy decisions. In addition, we explore the multidimensional context in which individuals confront risks and make trade-offs with respect to the costs and benefits in specific situations. We discuss various examples of risk-related products and behaviors, which are offered to illustrate the issues that arise when addressing risk in a multidimensional context where scientific information is incomplete and/or ambiguous and there are economic and social costs, as well as benefits, associated with any policy related to communicating and managing risk. Questions remain about how government and policy can respond to the increasing pace of technology change. The regulatory process is, by definition, slow and has difficulty keeping up with the accelerating dynamics of the environment. Are there more responsive market mechanisms that can substitute for government regulation, while still providing protection to individuals? Finally, as society creates “safer” products and processes, there is the potential for triggering more severe risks as a result of the feeling of safety and security.

This review takes stock of the development of Consumer Culture Theory (CCT) and provides a perspective from which this field of research can be framed, synthesized, and navigated. This review takes a conceptual and historical approach to map the rich theoretical inventory cultivated over almost 40 years of culturally-oriented research on consumption. The authors describe how CCT has emerged, chart various approaches to consumer culture studies, outline the dominant research domains, identify debates and controversies that circulate in the field, discuss the latest conceptual and methodological developments, and share managerial implications of a CCT approach. From this vantage point, they point to some promising directions for CCT research.