Journal of Interactive Marketing

Today's consumers are immersed in a vast and complex array of networks. Each network features an interconnected mesh of people and firms, and now, with the rise of the Internet of Things (IoT), also objects. Technology (particularly mobile devices) enables such connections, and facilitates many kinds of interactions in these networks—from transactions, to social information sharing, to people interfacing with connected devices (e.g., wearable technology).

We introduce the POP-framework, discuss how People, Objects and the Physical world inter-connect with each other and how it results in an increasing amount of connected data, and briefly summarize existing knowledge on these inter-connections. We also provide an agenda for future research focused on examining potential impact of IoT and smart products on consumer behavior and firm strategies.

Individuals increasingly participate in virtual support communities (VSCs) where they conduct numerous aspects of their lives with others whom they may never encounter in person, and they interact within these communities to attain various goals. Research finds that individuals are more likely to achieve success with such goals when they make a public commitment to achieving them. Through our netnographic inquiry, we extend prior theorizing of VSC with an explanation of how public commitment manifests in VSC in support of goal attainment. More specifically, we find these online communities make salient a context relevant social identity which motivates behaviors that facilitate compliance to the public commitment, and hence, more effective goal pursuit. In addition, we create a typology of member roles within these VSC that further influence public commitment. Our findings contribute to theories of VSC and public commitment.

When making important purchase decisions, consumers often consult multiple information sources. This paper examines how consumers allocate their search time across offline and Internet sources using survey data from new automobile purchases. Our analysis shows how time spent on Internet sources interrelates with time spent on offline sources, such as car dealerships, and vice versa. Furthermore, we examine whether longer search times imply higher price satisfaction as an outcome of search. A simultaneous equations Tobit model with latent classes is used. Analysis of a decade of survey data reveals two automobile purchaser segments of which the larger one accounts for 91% of observations. Based on this, we find that (1) specific website types can complement or substitute for offline information sources and for each other and (2) longer search times result in increased price satisfaction but only on specific information sources. Our findings provide automobile manufacturers and dealers an insightful way to utilize and manage different sources for product and price information provision.

During the past two decades, the focus of marketing has moved from the tactics of persuasion to the strategies of value cocreation. After moving toward cognitive science and corporate strategies in the early 2000s, marketing research returned to its traditional domains of consumer psychologies and customer management. While conscientious consumers are gradually restraining themselves from selfish indulgence, marketers have refocused on a new set of values that encompass mental, experiential, and societal well-being. In this regard, we adopt an unprecedented approach by incorporating topic modeling with social network analysis. The results show that, in terms of topic heterogeneity, the most impactful journals are the most diverse, whereas each runner-up has a unique focus. Among the journals, we detect two major co-authorship communities, and among the topics, we detect three. Further, we find that the communities of the most cited papers are composed of heterogeneous clusters of similar topics. The pivots within, and the bridges between, these communities are also reported. In the spirit of collaborative research, our topic model and network analysis are shared via online collaboration and visualization platforms that readers can use to explore our models interactively and to download the dataset for further studies.