THE POWER OF BEAUTY: LEVERAGING ON DEEP LEARNING TO DISENTANGLE THE EFFECT OF IMAGE AESTHETICS ON ONLINE PURCHASE

Visuals have been deemed as one of the primary marketing formats in service e-tailing environ-ments to compensate for the abstract and intangible nature of services. Yet, despite the overwhelm-ing empirical evidence attesting to the importance of aesthetics in product and website designs, there is a dearth of research on how the beauty of images depicting service offerings could affect consumers’ behaviour. Subscribing to Stimuli-Organism-Response (S-O-R) framework, we attempt to elucidate the power of aesthetics in shaping consumers’ cognitive and emotional responses when they are exposed to the portal image of a service offering. Additionally, we endeavour to explore the heterogeneity of consumers’ responses or their centrality of visual aesthetics, to such images. Blending computer vision and deep learning techniques, we advance a computable and decomposable aesthetic assessment method for scoring the aesthetics of portal images belonging to more than 299,000 local service offerings on a leading Chinese group buying site. We then em-ploy Propensity Score Matching (PSM) to yield initial evidence demonstrating that aesthetics ex-erts significant effects on the online sales of services

Learning by Doing: Understanding the Role of Affordance Informativity in Information Search Performance

Information search is becoming increasingly demanding due to the booming of Consumer Generated Content (CGC) in online environment. This has led to growing scholarly interest in designing search features to accommodate diverse user preferences. Drawing on the Theory of Affordance Informativity, we advance ostensive informativity and performative informativity as focal mechanisms for search features to convey actions afforded to users. We further put forth a typology of search features that is grounded in both dimensions of search affordance informativities. Next, we construct a research framework that depicts how search affordance informativity bolsters information search performance. By conducting a field experiment on our custom-made online restaurant review website, we discovered that performative informativity increases search result anticipation and reduces search costs whereas ostensive informativity only facilitates the former. Search result anticipation in turn enhances search performance in terms of efficiency and utility, but the opposite effect is observed for search costs

Exploring the Nudging and Counter-Nudging Effects of Campaign Updates in Crowdfunding

Crowdfunding has emerged as a vital financing avenue for entrepreneurs to realize their ventures. With limited information availability, crowd-funders may choose to first follow the progress of interested crowdfunding campaigns, such as monitoring project updates to acquire more information for justifying investment decision, before making pledges. Although campaign updates have been touted to be a salient driver of fundraising success, the underlying mechanism for this relationship remains unclear. Subscribing to nudge theory, we strive to shed light on how update strategies, such as frequency and message length, can serve as nudges to convert project followers to actual funders. Specifically, we posit a dual-role of campaign updates whereby an over-zealous update strategy may induce a counter-nudging effect that deters prospective funders, what we labelled as ‘over-nudging’. This study advances a model to account for both the nudging and counter-nudging effects of campaign updates in crowdfunding, which could yield insights for fundraisers to optimize their update strategy and in turn, get their business off the ground

From Copy to Practice: Follower’s Learning Behavior in Forex Social Trading

Forex social trading platforms endows novice investors with opportunities to trade on foreign exchange markets by mimicking the investment strategies of sophisticated traders. But concurrently, the copy-trading mechanism underlying these platforms foster a conducive learning environment whereby inexperience followers could evolve into independent traders by observing and learning from the trading behaviors of prominent traders. Drawing on observational learning theory, we advance learning efficiency and effectiveness as focal yardsticks to encapsulate followers’ learning performance and explore their effects on the profitability of followers’ first independent trades. Preliminary analysis conducted on a leading forex social trading platform reveals that traders’ trading consistency amplifies followers’ learning efficiency whereas traders’ profitability bolsters followers’ learning effectiveness. Furthermore, while our empirical findings attest to the criticality of learning effectiveness on followers’ ability to profit from their initial independent trades, speeding up the learning process may not guarantee better performance

Unraveling the Relationship between Content Design and Kinesthetic Learning on Communities of Practice Platforms

As a variant of the sharing economy, Communities of Practice (CoP) platforms have allowed kinesthetic learners to acquire skillsets corresponding to their interests for immediate or future use in practice. However, the impact of digital learning content design on kinesthetic learning remains underexplored in the field of information systems. We hence extend prior research by advancing content richness and structure clarity as antecedents affecting kinesthetic learners’ digestibility of contents, culminating in differential kinesthetic learning effects. To substantiate our arguments, we collected data from a leading Chinese recipe sharing platform. Whereas content richness was measured in terms of readability, verb richness, and prototypicality, structure clarity was operationalized as block structure, block quantity, and block regularity. Employing a machine learning model, we simulated and tested learners’ digestibility of image content embodied within recipes. Plans for future research beyond the current study are also discussed

Merchandising the Intangibles: Unraveling the Benefits of Visualizing Consumption Experience in Service E-Tailing

Images have been extensively employed in service e-tailing to overcome the intangible nature of services. Despite the importance of delineating the physical vibe where service is delivered, there is a paucity of research on how visual cues can be designed in images to communicate the actual consumption experience of a service offering and in turn, drive customers’ purchasing behavior. Synthesizing extant literature on service tangibility, we identify consumption process and outcome as two predominant dimensions of service consumption that entice purchase by enhancing the informativity of a service offering both associatively and epistemically. Additionally, we consider consumer’s reliance on service tangibility as an impetus that alters the power of visualizations. Conceiving human elements as the communicator that transmits consumption information, we employ computer vision techniques to extract human in the portal images of more than 299,000 localized service offerings and propose an experimental design for future investigations

Tell Me What You Want: Exploring the Impact of Offering Option Repertoires on Service Performance in Gig Economy

Confronted with an increasingly competitive business landscape for credence goods in the gig economy, sellers in e-marketplaces must effectively design their services by configuring the service offering specification options to enhance the visibility of their service offerings. Motivated by the gap between the configuration of service offering specification options and its impact on service quality and sales, this study builds on the competitive repertoire theory to advance a research model that seeks to unveil how the volume, complexity, and heterogeneity of service offering specification option repertoires affect service quality and sales. We empirically examined our hypotheses with a dataset comprising 3,307 lifestyle-themed credence goods observations from Fiverr, one of the largest e-marketplaces for gig economy in the world. We discover that the repertoire volume increases both service quality and sales whereas repertoire complexity only increases service quality. Repertoire heterogeneity does not significantly impact on service quality and sales

The Multifaceted Impact of Matching Policy on Crowdfunding Platforms: Evidence from DonorsChoose

Donation-based crowdfunding platforms use matching policies where leadership donors match contributions at certain rates. While matching policy have been applied in many crowdfunding platforms, a lot remains unknown about their effectiveness and how they can be optimized to incentivize charitable donations. Leveraging data from donors choose, this study explores the policy in boosting charitable donations. Our findings demonstrate that, at the platform level, matching policy have a positive impact on the overall donation performance of the platform, but also compromise the fairness of donations. At individual level, we find that donors who have made donations on the platform before are less influenced by matching policy, and it has higher utility for less experienced donors. This work provides one of the first systematic analyses that connect micro-level data patterns with macro-level donor behaviors to disentangle the matching policy

Effects of Personality on Social Performance in Social Trading

On social trading platforms, the income of leader traders is largely dictated by the number of copy trades conducted by their followers. Consequently, it is imperative for leader traders to exhibit appealing personalities to entice their followers to conduct copy trades. Drawing on social capital theory, we endeavor to scrutinize the effects of traders’ personalities on the accumulation of social capital, which in turn bolsters social performance as measured by the number of copy trades. Data was extracted from a leading social trading platform. The Myers–Briggs Type Indicator personality classification system was then employed to depict leader traders’ personalities based on a novel text-based, machine learning approach. Preliminary analytical results reveal significant relationships among personality traits, social capital dimensions, and social performance. Findings from this study generate insights for social trading platforms and leader traders on exhibiting desirable personalities conducive for accumulating social capital that entice followers to conduct copy trades

Divergent Innovation: Directing the Wisdom of Crowd to Tackle Societal Challenges

Crowdsourcing is acknowledged as a promising avenue for addressing societal challenges by drawing on the wisdom of the crowd to offer diverse solutions to complex problems. Advancing a new conceptual framework of ‘divergent innovation’ which delineates between topic and quality divergence as focal metrics of performance when crowdsourcing for solutions to societal challenges, this study investigates the impacts of four ideation stimuli on divergent innovation. These four stimuli include task description concreteness, resource richness, topic entropy, and judging criteria comprehensiveness. Empirical analysis based on data sourced from an online crowd-ideation platform reveals that task description concreteness negatively affects topic divergence but positively influences quality divergence, whereas resource richness positively affects topic divergence but negatively influences quality divergence. Additionally, the relationship between topic entropy and topic divergence is U-shaped, with no significant impact on quality divergence. These findings contribute to extant literature on crowdsourcing and offer invaluable insights for practitioners