Electronic Marketing
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Item"Can't Get No Satisfaction?" – The Case for Broadening Information Systems Research on E-Commerce( 2023-01-03)Satisfaction is a crucial construct in information systems research, particularly for investigations of e-commerce. Given profound shifts in the scope and use of e-commerce and the associated proliferation of information systems, we ask whether research should adopt a more encompassing view of information systems in e-commerce. Based on recent propositions in marketing research, we identify "experience" as a construct apt to complement "satisfaction" by broadening the scope of inquiry to include the entire order process. In a systematic literature review, we identify a variety of definitions of key constructs but find very few contributions from information systems research that take experience into account. Based on these findings, we outline possibilities for future research to move from exclusively focusing on satisfaction to directing attention to experience as an affective response to technology on a systems level. Such a change carries several implications touching the very basis of information systems research, such as the role of the IT artifact. In addition, we discuss implications for practice.
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ItemIntroduction to the Minitrack on Electronic Marketing( 2023-01-03)
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ItemMaking Third-Party Sellers More Attractive—The Case of Amazon( 2023-01-03)We provide an analysis of third-party sellers on Amazon’s online marketplace from a customer’s viewpoint. While Amazon as a retailer sometimes directly competes with third-party sellers, Amazon is also interested in making the Amazon marketplace attractive for third-party sellers and making third-party sellers attractive to customers. Based on a large-scale survey (n=772) of Amazon customers in the U.S., we examine how much they like to buy from the different seller types (Amazon itself, third-party sellers with/without the Prime logo, i.e., with/without Fulfillment by Amazon). Among other results, we can show that the Prime logo on the seller side combined with a Prime subscription on the customer side significantly increases trust in a third-party seller, ultimately increasing third-party sales on Amazon’s online marketplace. Furthermore, third-party sellers are implicitly incentivized to use the Fulfillment by Amazon service, which generates additional logistics service revenue for Amazon.
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ItemArtificial Intelligence (AI) and Business Innovation in Insurance: A Comparison of Incumbent Firms versus New Entrants( 2023-01-03)Artificial Intelligence (AI) systems evolve in response to new data by using adaptive algorithms. The insurance industry is data intensive, and dynamic. It is therefore particularly suitable for AI implementation. An innovation triangle framework is proposed that consists of product, process and value chain innovation. A comparison of leading incumbent insurance firms with new entrants illustrates significant competitive differences. The incumbents apply AI to defend their market positions by enhancing existing strengths and capabilities across the three innovation types. The new entrants exploit AI technology to build new products with innovative features that emphasise customer value and user experience. The innovation triangle is a useful managerial tool to analyse the nature and extent of innovation in insurance and can be used to evaluate and plan AI strategies by mapping existing AI initiatives to specific types of innovation and identifying innovation objectives and opportunities. Future trends and research opportunities are outlined.
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ItemAutomated Detection of Skin Tone Diversity in Visual Marketing Communication( 2023-01-03)Companies invest heavily in diversity, equity, and inclusion efforts. Specifically, the representation of people in visual marketing communication is often considered a manifestation of diversity policies. We propose a standard framework built on machine learning to create novel measures quantifying skin tone dynamics. We first use the Swin Transformer to extract skin pixels from images. Next, the K-means algorithm is deployed to classify skin tone components from the extracted skin pixels, accounting for multiple people with distinct skin colors in an image. Using images posted by 34 fashion brands on Instagram and Twitter, we demonstrate a useful application of the tool. The results highlight that, in the past two years, the fashion industry has slightly increased its diversity, represented by the increased variety of skin tones of people included in social media posts. Our method allows for automated detection of objective measures of skin-tone diversity in visual marketing communications.
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ItemThat’s Not Who I Am! Investigating the Role of Uniqueness and Belongingness for Designing Successful Personalized Recommendations( 2023-01-03)Although many firms rely on personalization to enhance the user experience of their digital service, their efforts might backfire if users feel misunderstood by the personalized offerings. So far, the psychological processes underlying the phenomenon of feeling misunderstood by personalization systems and potential means to alleviate this perception remain largely uninvestigated. Building on the psychological concepts of uniqueness and belongingness, we propose a framework to investigate how transparency impacts users’ feeling of being misunderstood by personalization systems. To test our research model, we conduct an online experiment using Spotify’s “Discover Weekly” playlist. The results show that considering not only users’ uniqueness but especially their belongingness is decisive to avoid misunderstanding. Further, we find that transparent explanations of the system’s inner workings elicit a feeling of control among users, which fosters the perception that both users’ uniqueness and belongingness are considered, resulting in less misunderstanding and continued usage.