How to react to a shock? Effects of Airbnb hosts’ choices and market segmentation at the time of Covid-19

2023 | Information & Management | Citations: 0

Authors: Buzzacchi, Luigi; Milone, Francesco Luigi; Paolucci, Emilio; Raguseo, Elisabetta

Abstract: We investigate the way service providers who operate on an online peer-to-peer ( ... Expand

Abstract: We investigate the way service providers who operate on an online peer-to-peer (P2P) platform readapted their marketing choices to face the Covid-19 pandemic. Through an empirical investigation on a large dataset of Airbnb properties in Rome, observed from January 2018 to December 2020, we provide a threefold contribution by investigating how Airbnb hosts reacted to the Covid-19 pandemic shock, in terms of marketing choices, such as price adjustments and flexible cancellation policies; the direct effects of these choices on their economic returns; and how service providers on Airbnb reacted to address the new needs of their customers during the Covid-19 pandemic. The findings provide useful insights for researchers and practitioners and show that the adoption of combined marketing choices led to more than proportional effects on performances as it allowed Airbnb hosts to exploit profitable market segmentation mechanisms. Collapse

Topics: pandemic Airbnb marketing management price management peer-to-peer model

Methods: econometric modeling descriptive statistic instrumental variables estimation robustness check longitudinal research

Introduction to Opportunities and challenges in the Metaverse Minitrack (CC BY-NC-ND 4.0)

2023 | HICSS | Citations: 0

Authors: Cheng, X.; Mou, J.; Shen, X.; De Vreede, T.

Abstract: The metaverse is recognized as the next generation of disruptive innovation. It ... Expand

Abstract: The metaverse is recognized as the next generation of disruptive innovation. It refers to a virtual world, in which users engage in social activities such as discussing, collaborating, playing, shopping, and learning. Different from traditional online community, metaverse provides an immersive and realistic experience with the use of advanced technologies such as virtual reality (VR), augmented reality (AR), and extended reality (XR). In this sense, the metaverse creates a virtual world parallel to the physical world. For example, Facebook CEO-Mark Zuckerberg recently announced a full-color mixed reality headset namely Meta Quest Pro which is the first in a new line of advanced headsets built for collaboration, creativity and getting things done (Meta 2022).A unique feature of metaverse space is a threedimensional (3D) virtual world that allows social connection through avatars representing human beings themselves. Second Life, a typical example of the metaverse, allows users to design their avatar and enjoys various social gatherings (e.g., live concerts). Therefore, users could perceive a high level of interactivity and immersion in the metaverse space. The idea of the metaverse has attracted considerable attention from practitioners and academic researchers. Organizations attempt to integrate the metaverse into their existing business models. For instance, Wangyi successfully screened the International Conference on Distributed Artificial Intelligence (DAI 2020) in Yaotai metaverse, allowing researchers to create avatars and interact with each other. In addition, education organization such as university on one hand is actively developing metaverse education environment for improving learning and education performance via online social activity and gamified learning (EducationTimes). On another hand, it proactively develop education programs. For instance, Hong Kong Polytechnic University (PolyU) has launched a new postgraduate programme in metaverse technology, as higher education institutions. Moreover, Metaverse has great potential in promoting digital transformation in many industries, such as tourism, leisure and hospitality, citizen-government interaction, health, and education. Although the metaverse has presented numerous opportunities to different industries, we should also pay attention to the possible challenges or risks, such as information security, privacy, delay and ethical issues, and other dark sides in the metaverse. It is noteworthy that, research on opportunities and challenges in the metaverse is still scarce. More specifically, we encourage the academic community to pay more attention to the various influence from behavioural and technological aspects in the Metaverse field.The HICSS minitrack "Opportunities and challenges in the Metaverse" was introduced to fill the void, to a certain extent, in the literature by addressing the opportunities and challenges the metaverse presents, exploring the new interaction and collaboration modes in the metaverse, providing multidisciplinary perspectives, and/or adopting mixed-methods research approaches. We expect more forward-looking insights on the metaverse. For this minitrack, we accepted two papers for inclusion in the HICSS conference proceedings.The first paper is co-authored by Sofia Schöbel, X Jasmin Karatas, Fabian Tingelhoff, and Jan Marco Leimeister and is titled "Not everything is a Metaverse?! A Practitioners Perspective on Characterizing Metaverse Platforms". This study attempts to address how to advance the academic understanding of metaverse platforms by incorporating the practitioner's view and how to characterize or realize metaverse platforms. By conducting a qualitative interview study, the authors use the expertise of practitioners to discuss different examples that claim to represent a metaverse, e.g., Second Life and Decentraland. This study develops a typology named Metagon that is used to evaluate existing metaverse platforms. Metagon describes three categories: social category, economy category, and technology category. For each of these three categories, three sections reflecting different aspects are identified. This study provides a novel method to evaluate the metaverse so that future research could advance the understanding of the nature and meaning of metaverse platforms. Moreover, research findings could guide practitioners to create their metaverse platforms. Collapse

Topics: virtual reality pandemic

Methods: literature sample mixed method

Understanding visitors' metaverse and in-person tour intentions during the COVID-19 pandemic: A coping perspective

2023 | HICSS | Citations: 0

Authors: Cheng, X.; Zhang, S.; Liu, W.; Mou, J.

Abstract: The COVID-19 pandemic has posed a challenge to the development of global touris ... Expand

Abstract: The COVID-19 pandemic has posed a challenge to the development of global tourism. Metaverse tour, as an emerging travel pattern that combines metaverse characteristics, can bring positive implications for the digital transformation of tourism. However, few studies have integrated time and space to analyze the public's intentions of metaverse tour and in-person tour, calling for a comprehensive research framework. Based on coping theory, a mixed-methods approach was proposed to incorporate several constructs to investigate the factors that influence public participation in metaverse tour. We further analyzed the difference of public's willingness to travel in-metaverse versus in-person at different times. This study enriches our understanding of the popularity of metaverse tour and the reasons for it, and provides insights into the further development of tourism to facilitate changes in the metaverse-based tourism pattern. Collapse

Topics: virtual reality pandemic big data

Methods: qualitative interview survey personal interview mixed method deep learning

The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry

2023 | Information Systems Frontiers | Citations: 0

Authors: Gupta, Shivam; Modgil, Sachin; Lee, Choong-Ki; Sivarajah, Uthayasankar

Abstract: This study aims to investigate the role of artificial intelligence (AI) driven f ... Expand

Abstract: This study aims to investigate the role of artificial intelligence (AI) driven facial recognition to enhance a value proposition by influencing different areas of services in the travel and tourism industry. We adopted semi-structured interviews to derive insights from 26 respondents. Thematic analysis reveals the development of four main themes (personalization, data-driven service offering, security and safety, and seamless payments). Further, we mapped the impact of AI- driven facial recognition to enhance value and experience for corporate guests. Findings indicate that AI-based facial recognition can facilitate the travel and tourism industry in understanding travelers’ needs, optimization of service offers, and value-based services, whereas data-driven services can be realized in the form of customized trip planning, email, and calendar integration, and quick bill summarization. This contributes to strengthening the tourism literature through the lens of organizational information processing theory. Collapse

Topics: artificial intelligence usability personalization human resource management pandemic

Methods: facial recognition system biometric measurement personal interview qualitative interview qualitative content analysis

Theories: organizational information processing theory

Chatbot commerce—How contextual factors affect Chatbot effectiveness

2023 | Electronic Markets | Citations: 0

Authors: Hsu, Pei-Fang; Nguyen, Tuan (Kellan); Wang, Chen-Ya; Huang, Pei-Ju

Abstract: The emergence of Chatbots has attracted many firms to sell their merchandise via ... Expand

Abstract: The emergence of Chatbots has attracted many firms to sell their merchandise via chats and bots. Although Chatbots have received tremendous interest, little is understood about how different usage contexts affect Chatbots’ effectiveness in mobile commerce. Due to differences in their nature, not all shopping contexts are suitable for Chatbots. To address this research gap, this study examines how contextual factors (i.e., intrinsic task complexity that embraces shopping task attributes and group shopping environment, and extrinsic task complexity that entails information intensity) affect user perceptions and adoption intentions of Chatbots as recommendation agents in mobile commerce. Applying the lenses of cognitive load theory (CLT) and common ground theory (CGT), we perform an experiment and apply quantitative analytical approaches. The results show that Chatbots are more suitable in the context of one-attribute, information-light, and group-buying tasks, whereas traditional Apps are suitable for multi-attribute, information-intensive, and single-buying scenarios. These findings make important theoretical contributions to the IT adoption literature as well as to CLT and CGT theory by contextualizing the evolving state of Chatbot commerce and providing guidelines for designing better Chatbot user experiences, thereby enhancing user perceptions and adoption intentions. Collapse

Topics: mobile application task complexity electronic commerce technology adoption recommender system

Methods: chatbot experiment qualitative interview chi squared test survey

Theories: cognitive load theory

Spatial Analytics with Hospitality Big Data: Examining the Impact of Locational Determinants on Customer Satisfaction in the U.S. Hotel Market

2023 | HICSS | Citations: 0

Authors: Lee, Minwoo; Kim, Jinwon; Shin, Hyejo

Abstract: Although hotel location has been recognized as one of the important factors affe ... Expand

Abstract: Although hotel location has been recognized as one of the important factors affecting hotel selection and guest satisfaction, relatively few studies have examined guest satisfaction with hotel location and its locational determinants at a macro level. This study aims to identify the locational determinants of hotel guest satisfaction through big data spatial analytics via a case study of 5,302 hotels in 151 cities in the U.S. Based on the framework of hotel location satisfaction, we classified all location-related factors into three categories: accessibility to points of interest, transport convenience, and surrounding environment. Our findings indicated that hotel property’s proximity to city area, landmark, park, shopping center, and highway as well as, attraction-driven tourism industry specialization, and hotel industry agglomeration were significant determinants. Furthermore, the impacts of these factors were spatially heterogeneous. These findings can provide geographical insights that are critical for developing a customer service experience and satisfaction model. Collapse

Topics: big data geographic information system customer satisfaction online review criminality

Methods: regression analysis method spatial analysis spatial regression case study network analysis

Effects of Managerial Response to Negative Reviews on Future Review Valence and Complaints

2023 | Information Systems Research | Citations: 0

Authors: Ravichandran, T.; Deng, Chaoqun

Abstract: There is limited systematic research on managerial response strategies to online ... Expand

Abstract: There is limited systematic research on managerial response strategies to online customer complaints and negative reviews. In this paper, we synthesize justice theory and service recovery literature to develop a model that explores the mechanisms through which appropriate managerial responses to customer complaints influence aggregate future review valence and complaints. We test our model using data from TripAdvisor.com, a leading travel review platform. Using text analysis (e.g., natural language processing and deep learning), we extract and code the variables in our model from the reviews and the managerial responses to these reviews. Key findings indicate that responding to customer reviews—in particular, negative reviews—will have a positive influence on future review valence. Moreover, responses with more rational cues than emotional cues to customer complaints about procedural unfairness will have a positive influence on future review valence. However, responses with more rational cues than emotional cues to customer complaints about interactional unfairness will have a negative influence on future review valence. Moreover, we find that when reviews have both distributive and interactional unfairness, responses with more rational cues matter. In addition, we find that both rational cues and emotional cues in responses to distributive unfairness and rational cues in responses to procedural unfairness are effective to decrease the future occurrence of similar complaints. We interpret and discuss the implication of these findings for theory and practice.History: Yulin Fang, Senior Editor; Zhengrui Jiang, Associate Editor.Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1122. Collapse

Topics: online review user-generated content marketing management anonymity Python

Methods: deep learning theory development qualitative content analysis computational algorithm longitudinal research

Theories: justice theory expectation confirmation theory

Using Toulmin's Argumentation Model to Enhance Trust in Analytics-Based Advice Giving Systems

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Rubin, Eran; Benbasat, Izak

Abstract: Ecommerce websites increasingly provide predictive analytics-based advice (PAA), ... Expand

Abstract: Ecommerce websites increasingly provide predictive analytics-based advice (PAA), such as advice about future potential price reductions. Establishing consumer-trust in these advice-giving systems imposes unique and novel challenges. First, PAA about future alternatives that can benefit the consumer appears to inherently contradict the business goal of selling a product quickly and at high profit margins. Second, PAA is based on mathematical models that are non-transparent to the user. Third, PAA advice is inherently uncertain, and can be perceived as subjectively imposed in algorithms. Utilizing Toulmin's argumentation-model, we investigate the influence of advice-justification statements in overcoming these difficulties. Based on three experimental studies, in which respondents are provided with the advice of PAA systems, we show evidence for the different roles Toulmin's statement-types play in enhancing various trusting-beliefs in PAA systems. Provision of warrants is mostly associated with enhanced competence beliefs; rebuttals with integrity beliefs; backings both competence and benevolence; and data statements enhance competence, integrity, and benevolence beliefs. Implications of the findings for research and practice are provided. Collapse

Topics: website systems design electronic commerce accounting ergonomics

Methods: experiment multivariate analysis of variance parametric test factor analysis statistical hypothesis test

Theories: argumentation theory

Will they take this offer? A machine learning price elasticity model for predicting upselling acceptance of premium airline seating

2023 | Information & Management | Citations: 0

Authors: Thirumuruganathan, Saravanan; Emadi, Noora Al; Jung, Soon-gyo; Salminen, Joni; Robillos, Dianne Ramirez; Jansen, Bernard J.

Abstract: Employing customer information from one of the world’s largest airline companies ... Expand

Abstract: Employing customer information from one of the world’s largest airline companies, we develop a price elasticity model (PREM) using machine learning to identify customers likely to purchase an upgrade offer from economy to premium class and predict a customer’s acceptable price range. A simulation of 64.3 million flight bookings and 14.1 million email offers over three years mirroring actual data indicates that PREM implementation results in approximately 1.12 million (7.94%) fewer non-relevant customer email messages, a predicted increase of 72,200 (37.2%) offers accepted, and an estimated $72.2 million (37.2%) of increased revenue. Our results illustrate the potential of automated pricing information and targeting marketing messages for upselling acceptance. We also identified three customer segments: (1) Never Upgrades are those who never take the upgrade offer, (2) Upgrade Lovers are those who generally upgrade, and (3) Upgrade Lover Lookalikes have no historical record but fit the profile of those that tend to upgrade. We discuss the implications for airline companies and related travel and tourism industries. Collapse

Topics: electronic mail marketing management price management customer satisfaction application programming interface

Methods: autoencoder data transformation machine learning experiment principal component analysis

Theories: optimization theory decision theory

Are We There Yet? Analyzing Progress in the Conversion Funnel Using the Diversity of Searched Products

2022 | Management Information Systems Quarterly | Citations: 0

Authors: Goldstein, Anat; Oestreicher-Singer, Gal; Barzilay, Ohad; Yahav, Inbal

Abstract: The conversion funnel is a model describing the stages consumers go through in t ... Expand

Abstract: The conversion funnel is a model describing the stages consumers go through in their journey toward a purchase. This journey often lasts several days to weeks and can include multiple visits to a seller’s website. A large body of literature has focused on using observable search patterns to identify consumers’ hidden purchasing stages and to estimate their likelihood of conversion. We propose a novel set of measures to better reveal the consumer’s hidden stage in the funnel. These measures are based on the diversity of the searches that a customer engages in while browsing an e-commerce website, and they include not only the number of different products that are searched for, but also measures that rely on unobserved similarities among products, captured in a product network (in which products are assumed to be “similar” if they are frequently co-searched). We operationalize and evaluate our proposed measures using a large-scale dataset from a medium-sized tourism website used for comparing and booking flights. We estimate a hidden Markov model to show that our proposed diversity measures are associated with progress in the funnel and consumers’ conversion likelihood. Specifically, we show that consumers go through different distinguishable stages (states) in their journey, characterized by different values of our proposed diversity measures. To demonstrate the managerial and business implications of our theory, we show that incorporating search-diversity measures into a baseline prediction model significantly improves the model’s performance in predicting purchase likelihood and churn. Collapse

Topics: website electronic commerce accounting marketing management information storage and retrieval system

Methods: XGBoost machine learning random forest classification principal component analysis classification method