Unlocking the Psychology of Online Travel Booking: How Price Expectations Affect Consumers

2023 | International Conference on Information Systems | Citations: 0

Authors: GAO, YUTING; Jiang, Zhenhui; Chen, Hailiang; Goh, Khim Yong

Abstract: Price fluctuation is a major concern for consumers in making travel plans, such ... Expand

Abstract: Price fluctuation is a major concern for consumers in making travel plans, such as booking flights or hotels. Thus, consumers tend to hesitate over whether to make a booking or not. Online travel booking platforms such as Kayak, Hopper, and Google Flights, have been adopting various digital nudges to influence consumers' price expectations. For example, they may inform users that "Prices are unlikely to decrease within 7 days" (reassurance) or "Prices may rise within 7 days" (alert). Despite the pervasive adoption of reassurance and alert nudges in online travel booking, little is known about how they influence consumers' price expectations and travel booking behavior, and why. We plan to conduct a lab experiment and a randomized field experiment in collaboration with a leading travel metasearch platform to investigate how digital nudges like reassurance and alert may affect individuals' emotions, price expectations, and subsequent online travel booking behavior. Collapse

Topics: mobile application behavioral intention electronic commerce decision making marketing management

Methods: laboratory experiment field experiment survey design experiment randomized field experiment

Prior Experience of Managers and Maladaptive Responses to Performance Feedback: Evidence from Mutual Funds

2023 | Organization Science | Citations: 0

Authors: Gaba, Vibha; Lee, Sunkee; Meyer-Doyle, Philipp; Zhao-Ding, Amy

Abstract: In this study, we examine how the prior experiences of decision makers systemati ... Expand

Abstract: In this study, we examine how the prior experiences of decision makers systematically influence their assessment of and responses to negative performance feedback. We posit that, although greater and more specialized experiences enable managers to build relevant knowledge and expertise in specific domains, they also make them overconfident in their abilities and strategies. Such experience-induced overconfidence further leads to distortions in the performance assessment process, hindering a firm’s ability to recognize and respond to poor performance. We empirically test these arguments in the context of U.S. mutual fund managers making investment decisions in response to fund performance below aspirations. As hypothesized, we find that more experienced and more specialized fund managers change their investment decisions less when faced with negative performance feedback than managers who are less experienced and less specialized. In additional analyses, we further show that the lower responsiveness of more experienced (specialized) managers is associated with the fund’s lower future performance, supporting our proposed theoretical mechanism (overconfidence). This study augments existing performance feedback research by showing how decision makers’ prior experience can impede problem-solving behavior in organizations. It also contributes to the literature on human capital and organizational learning by documenting an unintended consequence of accumulated human capital on firm adaptive behavior. Funding: This work was supported by INSEAD research & development funds. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1605. Collapse

Topics: IT career organizational productivity human resource management unintended consequence problem solving

Methods: robustness check descriptive statistic theory development qualitative content analysis SEC EDGAR

Theories: theory of bounded rationality behavioral theory of the firm

Introduction to the Minitrack on Global Digital Business

2023 | HICSS | Citations: 0

Authors: Gabrielsson, Mika; Fraccastoro, Sara; Ojala, Arto

Abstract: ... Expand

Abstract: Collapse

Topics: digital business digital transformation entrepreneurship marketing management

Methods: mixed method

Consensus-trust Driven Bidirectional Feedback Mechanism for Improving Consensus in Social Network Large-group Decision Making

2023 | Group Decision and Negotiation | Citations: 0

Authors: Gai, Tiantian; Cao, Mingshuo; Chiclana, Francisco; Zhang, Zhen; Dong, Yucheng; Herrera-Viedma, Enrique; Wu, Jian

Abstract: This paper proposes a consensus-trust driven framework of bidirectional interact ... Expand

Abstract: This paper proposes a consensus-trust driven framework of bidirectional interaction for social network large-group decision making. Firstly, the concepts of interaction consensus threshold and interaction trust threshold are defined, which are used to discriminate the interaction modes between subgroups into four categories. Corresponding hybrid feedback strategies are designed in which the consensus level and trust level of subgroups are regarded as reliable resources to facilitate the achievement of group consensus. Secondly, a minimum adjustment bidirectional feedback model considering cohesion is developed to help the interacting subgroups reach mutual consensus with minimum opinion modification. Finally, the proposed consensus framework is applied to a blockchain platform selection problem in supply chain to demonstrate the effectiveness and applicability of the model. Collapse

Topics: blockchain supply chain management decision making social network

Methods: computational algorithm simulation social network analysis trade-off analysis method multi objective optimization

Application of Fourth Industrial Revolution Technologies in Healthcare

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Gama, Nkosinathi; Adebesin, Funmi

Abstract: The aim of this systematic literature review (SLR) is to explore how Fourth Ind ... Expand

Abstract: The aim of this systematic literature review (SLR) is to explore how Fourth Industrial Revolution (4IR) digital technologies are transforming the healthcare sector. Peer-reviewed, full-text research papers published between January 2016 and April 2021, which focused on data-driven healthcare, health data management systems, and the disruptive role of digital technologies in healthcare were retrieved from three electronic databases, namely PubMed Central, Institute of Electrical and Electronics Engineers (IEEE) and MEDLINE. Articles included in the SLR were identified and selected using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guideline. Three main themes were identified from 84 research papers included in the SLR, namely, (i) digital technologies driving the transformation of healthcare, (ii) the impact of digital transformation on healthcare, and (iii) areas of transformation in healthcare. The results showed that technological innovations can mitigate the impact of unequal distribution of healthcare services, reduce healthcare costs, improve the quality of care, and the quality of life for patients and healthcare professionals. Collapse

Topics: database system electronic health mobile system industry 4.0 production management

Methods: literature sample qualitative content analysis mixed method structured literature research descriptive statistic

Dissecting AI-Generated Fake Reviews: Detection and Analysis of GPT-Based Restaurant Reviews on Social Media

2023 | International Conference on Information Systems | Citations: 0

Authors: Gambetti, Alessandro; Han, Qiwei

Abstract: Recent advances in generative models such as GPT may be used to fabricate indis ... Expand

Abstract: Recent advances in generative models such as GPT may be used to fabricate indistinguishable fake customer reviews at a much lower cost, posing challenges for social media platforms to detect this kind of content. This study addresses two research questions: (1) the effective detection of AI-generated restaurant reviews generated from high-quality elite authentic reviews, and (2) the comparison of out-of-sample predicted AI-generated reviews and authentic reviews across multiple dimensions of review, user, restaurant, and content characteristics. We fine-tuned a GPT text detector to predict fake reviews, significantly outperforming existing solutions. We applied the model to predict non-elite reviews that already passed the Yelp filtering system, revealing that AI-generated reviews typically score higher ratings, users posting such content have less established Yelp reputations and AI-generated reviews are more comprehensible and less linguistically complex than human-generated reviews. Notably, machine-generated reviews are more prevalent in low-traffic restaurants in terms of customer visits. Collapse

Topics: fake review artificial intelligence application programming interface open source pandemic

Methods: machine learning survey computational algorithm sensitivity analysis ANOVA

Effect of IS strategy on environmental sustainability and cybersecurity

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Ganye, Derrick; Palvia, Prashant

Abstract: ... Expand

Abstract: Collapse

Topics: environmental sustainability information systems strategy data breach IT security database system

Methods: longitudinal research robustness check statistical hypothesis test

Examining the role of IT capability, digitization, and CIO strategic position on Green IS

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Ganye, Derrick; Singhal, Sonika

Abstract: Green IS is seen as an important tool by many organizations to achieve environm ... Expand

Abstract: Green IS is seen as an important tool by many organizations to achieve environmental sustainability. However, its adoption is still relatively low. This is because the decision to implement Green IS which is often led by the Chief information officer (CIO) is a complex one involving multiple stakeholders. Additionally, an organization's IT capability and digital capability to implement Green IS is heavily dependent on its IT investment. In this study, we investigate the effects of the CIO's strategic position, IT capability, and digital capability on Green IS. Additionally, we examine the moderating effect of IT investment on IT capability and digital capability. We propose a research model and discuss a methodology to test it. Collapse

Topics: green IS information technology capability Chief Information Officer IT investment environmental sustainability

Methods: partial least squares regression structural equation modeling statistical hypothesis test survey

Live streaming recommendations based on dynamic representation learning

2023 | Decision Support Systems | Citations: 0

Authors: Gao, Ge; Liu, Hongyan; Zhao, Kang

Abstract: As an emerging form of social media, live streaming services (e.g., Twitch and C ... Expand

Abstract: As an emerging form of social media, live streaming services (e.g., Twitch and Clubhouse) allow users to interact with hosts and peers in real time while enjoying shows or participating in discussions. These platforms are also dynamic, with shows or discussions changing quickly inside a room and users frequently switching between rooms. To improve user engagement and experience on such platforms, we design a new recommendation model named Dynamic Representations for Live Streaming Rooms (DRIVER) to provide room recommendations. Guided by the Integrated Framework for Consumer Path Modeling and the social affordance theory, DRIVER infers dynamic representations of live streaming rooms by leveraging users’ behavior paths in entering, staying in, and leaving rooms. One contribution of our model is a new and efficient dynamic learning framework to model instantaneous and ever-changing inter-room relationships by considering individual users’ behavior paths after leaving a room. Also supported by social affordance theory, another methodological novelty of our model is to capture dynamic characteristics of a room by incorporating features of the current audience inside the room. Experiments on real-world datasets from two different types of live streaming platforms demonstrate that DRIVER outperforms state-of-the-art representation learning methods and sequential recommender systems. The proposed method also has implications for recommender system design in other contexts, in which items are characterized by users’ dynamic behavior paths and ongoing social interactions. Collapse

Topics: live streaming platform recommender system user experience knowledge sharing systems design

Methods: experiment sensitivity analysis ablation analysis descriptive statistic deep learning

Theories: theory of affordance

MORE OR LESS PREJUDICE? A STUDY ON REAL-TIME VOLUNTEER APPS FOR VISUALLY IMPAIRED PEOPLE

2023 | European Conference On Information Systems | Citations: 0

Authors: Gao, Huilin; Ng, Evelyn; Deng, Bingjie; Chau, Michael

Abstract: Although digital technologies improve the quality of life for people with visua ... Expand

Abstract: Although digital technologies improve the quality of life for people with visual impairment, their influences on social justice are inconclusive. In this study, we use quantitative and qualitative methods to investigate the effect of real-time volunteer apps on prejudice and social connection from the perspective of both visually impaired people (VIPs) and non-impaired people (NIPs). Counterintuitively, our findings suggest that real-time volunteer apps have even a negative effect on reducing the prejudice perceived by VIPs and have no effect on reducing the prejudice of NIPs. For social connection and social acceptance, we find that these apps have a positive impact on both VIPs and NIPs. We hope this study can inspire more IS research on disability and we suggest several ideas for future research. Collapse

Topics: mobile application social influence information privacy concern online community

Methods: survey qualitative interview mixed method