@phdthesis{Maerz2016, author = {M{\"a}rz, Armin}, title = {Three Essays on Understanding Mobile Consumer Behavior: Business Models, Perceptions, and Features}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-3948}, school = {Universit{\"a}t Passau}, pages = {145 S.}, year = {2016}, abstract = {For about a decade, consumers have been carrying the Internet in their pockets. The rapid penetration of modern smartphones has meant that more than two-thirds of the people in the West can access and use online resources, anytime and anywhere. Consumers also can communicate and share their consumption experiences instantaneously. Platforms reach users for time-critical events through highly personal communication channels, in the sense that smartphones serve as constant companions. Many mobile applications and their basic services and contents also are available for free. The digital and mobile worlds thus are changing the very means of communication, suggesting the powerful need for marketing research and practice to find the opportunities and meet the challenges of the mobile Internet. In particular, scientific investigations are required to describe new business models in the free e-service industry and the consumer behavior affected by mobile features. This thesis examines these topics in three essays. Study 1 considers business models that offer their services without charge. Offering services for free is symptomatic of not only mobile apps (90\% of all apps are available for free) but the digital economy in general. For companies offering free e-services, this situation raises several important questions, in that, without any access device restrictions, how do customers of free e-services contribute value without paying? What are the nature and dynamics of nonmonetary value contributions by nonpaying customers? With a literature review and interviews with senior executives of free e-service providers, Study 1 presents a comprehensive overview of nonmonetary value contributions in the free e-service sector, including word of mouth, co-production, and network effects. Moreover, adding attention and data into this framework reveals two further aspects that have not been addressed in prior customer value research. By putting the findings in the context of the existing literature on customer value and customer engagement, this study sheds light on the complex processes of value creation in the emerging e-service sector, while advancing marketing and service research in general. Study 2 deepens the findings from the first study; specifically, the focus is on the way that mobile users co-produce content and how this contribution is perceived by recipients in the network. With field data and a scenario experiment, this study demonstrates that recipients appreciate mobile-generated customer reviews fundamentally differently from other reviews. In particular, they discount the helpfulness of mobile reviews, due to their text-specific content and style particularities. The very fact that a review has been identified as written on a mobile device also lowers recipients' perceptions of its value. Recipients use information about the device as a source cue to assess their compatibility with the review contribution channel. If they perceive themselves as compatible with the method used to generate the review (mobile or non-mobile), recipients regard the review as more helpful, because they attribute the review to the quality of the reviewed subject. If they perceive it as incompatible though, recipients assume that the review reflects the personal dispositions of the reviewer and discount its helpfulness. Finally, Study 3 takes up the attention and cross-market network effects in a mobile setting; these were two nonmonetary dimensions identified by Study 1. Platform providers should develop measures to draw the attention of nonpaying customers to the offers of their paying customers. One attention-grabbing mobile-specific feature is push notifications to the device, which provide information about temporally or spatially relevant events. More concretely, Study 3 investigates how mobile push notifications remind users of upcoming deadlines in online auctions and therefore improve late bidding success. Late bidding is a prevalent strategy, in which bidders submit their bids at the very end of an online auction. This research uses field data about an online auction platform to demonstrate that late bidders use these mobile push notifications more frequently than do bidders with different bidding patterns. Within the group of late bidders, the chance to win an auction increases with their use of push notifications. After a mobile push notification, late bidders submit bids through mobile devices but also through non-mobile channels. Less experienced late bidders also benefit from push notifications, which increase their chances of success. In summary, this dissertation contributes to an enhanced understanding of mobile consumer behavior by using various methods, including qualitative interviews, field observations, and online experiments. From a theoretical perspective, it contributes to current knowledge about nonmonetary costumer value contributions in general and their role in mobile settings in particular. This thesis highlights the role of mobile devices in co-production and perceptions of co-produced content. It also reveals how mobile-specific interactive features, like push notifications, affect late bidding efficiency. Therefore, it specifies the role of mobile devices in cross-market effects, in that they enable the platform to direct the relationship between buyers and sellers. The insights presented herein encourage managers to reevaluate their current practices, think about whether they should label co-produced content as generated through a mobile channel or not, and contemplate whether to develop mobile push notifications as helpful features for users (not as intrusive marketing messages).}, language = {en} } @phdthesis{Anderl2014, author = {Anderl, Eva}, title = {Three Essays on Analyzing and Managing Online Consumer Behavior}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus-27453}, school = {Universit{\"a}t Passau}, year = {2014}, abstract = {Over the last two decades, the Internet has fundamentally changed the ways firms and consumers interact. The ongoing evolution of the Internet-enabled market environment entails new challenges for marketing research and practice, including the emergence of innovative business models, a proliferation of marketing channels, and an unknown wealth of data. This dissertation addresses these issues in three individual essays. Study 1 focuses on business models offering services for free, which have become increasingly prevalent in the online sector. Offering services for free raises new questions for service providers as well as marketing researchers: How do customers of free e-services contribute value without paying? What are the nature and dynamics of nonmonetary value contributions by nonpaying customers? Based on a literature review and depth interviews with senior executives of free e-service providers, Study 1 presents a comprehensive overview of nonmonetary value contributions in the free e-service sector, including not only word of mouth, co-production, and network effects but also attention and data as two new dimensions, which have been disregarded in marketing research. By putting their findings in the context of existing literature on customer value and customer engagement, the authors do not only shed light on the complex processes of value creation in the emerging e-service industry but also advance marketing and service research in general. Studies 2 and 3 investigate the analysis of online multichannel consumer behavior in times of big data. Firms can choose from a plethora of channels to reach consumers on the Internet, such that consumers often use a number of different channels along the customer journey. While the unprecedented availability of individual-level data enables new insights into multichannel consumer behavior, it also makes high demands on the efficiency and scalability of research approaches. Study 2 addresses the challenge of attributing credit to different channels along the customer journey. Because advertisers often do not know to what degree each channel actually contributes to their marketing success, this attribution challenge is of great managerial interest, yet academic approaches to it have not found wide application in practice. To increase practical acceptance, Study 2 introduces a graph-based framework to analyze multichannel online customer path data as first- and higher-order Markov walks. According to a comprehensive set of criteria for attribution models, embracing both scientific rigor and practical applicability, four model variations are evaluated on four, large, real-world data sets from different industries. Results indicate substantial differences to existing heuristics such as "last click wins" and demonstrate that insights into channel effectiveness cannot be generalized from single data sets. The proposed framework offers support to practitioners by facilitating objective budget allocation and improving team decisions and allows for future applications such as real-time bidding. Study 3 investigates how channel usage along the customer journey facilitates inferences on underlying purchase decision processes. To handle increasing complexity and sparse data in online multichannel environments, the author presents a new categorization of online channels and tests the approach on two large clickstream data sets using a proportional hazard model with time-varying covariates. By categorizing channels along the dimensions of contact origin and branded versus generic usage, Study 3 finds meaningful interaction effects between contacts across channel types, corresponding to the theory of choice sets. Including interactions based on the proposed categorization significantly improves model fit and outperforms alternative specifications. The results will help retailers gain a better understanding of customers' decision-making progress in an online multichannel environment and help them develop individualized targeting approaches for real-time bidding. Using a variety of methods including qualitative interviews, Markov graphs, and survival models, this dissertation does not only advance knowledge on analyzing and managing online consumer behavior but also adds new perspectives to marketing and service research in general.}, subject = {Internet}, language = {en} }