Brand Crisis and Customer Relationship Management on Social Media: Evidence from a Natural Experiment from the Airline Industry

2023 | Information Systems Research | Citations: 0

Authors: Al Balawi, Ramah; Hu, Yuheng; Qiu, Liangfei

Abstract: In this study, we investigate the effect of a brand crisis on the customer relat ... Expand

Abstract: In this study, we investigate the effect of a brand crisis on the customer relationship management (CRM) efforts of brands on social media. Despite the opportunities social media offers to brands to connect and engage with customers, it is still unclear how a brand crisis can change a brand’s social CRM efforts. Social media platforms can amplify the negative consequences of a brand crisis. However, the unique and public nature of social media platforms can offer new means for brands to handle a brand crisis and publicly manage their customer relationships. Compared with traditional CRM, social media enables brands to communicate with their customers publicly, which can strengthen their relationships with customers and maintain higher levels of customer engagement. Leveraging a natural experiment setting, we investigate the impact of the United Airlines crisis on three dimensions of social CRM efforts: informativeness, timeliness, and attentiveness. Contrary to traditional CRM efforts and recommendations, we find that the brand crisis increases informativeness efforts but reduces timeliness and attentiveness efforts.History: Yong Tan, Senior Editor; Beibei Li, Associate Editor.Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1159. Collapse

Topics: social media Twitter customer service customer satisfaction customer relationship management

Methods: mediation analysis longitudinal research robustness check natural experiment experimental group

Sustainable IS Use: What IS Needed to REDUSE

2023 | International Conference on Information Systems | Citations: 0

Authors: Andraschko, Lars; Wunderlich, Philipp; Sarker, Saonee; Veit, Daniel

Abstract: Facing ever-looming climate change, studying the drivers for individuals ' Info ... Expand

Abstract: Facing ever-looming climate change, studying the drivers for individuals ' Information Systems (IS) Use to reduce environmental harm gains momentum. While extant research on the antecedents of sustainable IS Use has focused on specific theories, interventions, contexts, and technologies, a holistic understanding has become increasingly elusive, with a synthesis remaining absent. We employ a systematic literature review methodology to shed light on the driving antecedents for sustainable IS Use among individual consumers. Our results build on findings of 29 empirical studies drawn from 598 articles retrieved from our premier outlets and a forward/backward search. The analysis reveals six salient complementary antecedents: Relief, Empowerment, Default, User-centricity, Salience, and Encouragement. We recommend considering these concepts when developing, deploying, promoting, or regulating digital technologies to mitigate individual consumers' emissions. Along with memorable and implementable concepts, our theoretical framework offers a novel conceptualization and four promising avenues for researchers on sustainable IS Use. Collapse

Topics: information system use green IS electronic commerce individual characteristic willingness to pay

Methods: structured literature research synthesis theory development laboratory experiment field experiment

Theories: extended unified theory of acceptance and use of technology information systems theory unified theory of acceptance and use of technology

How Tourist Group Books Hotels Meeting the Majority Affective Expectations: A Group Selection Frame with Kansei Text Mining and Consensus Coordinating

2023 | Group Decision and Negotiation | Citations: 0

Authors: Chang, Jia-Li; Li, Hui; Wu, Jian

Abstract: The decision on which hotel to book is a high-cost process for individuals and e ... Expand

Abstract: The decision on which hotel to book is a high-cost process for individuals and even more for groups due to the information explosion on online travel agent platforms. To assist group selecting the optimal hotel that meets the majority affective expectations, this study proposes a group hotel selection frame for booking with Kansei text mining and consensus coordinating. Firstly, to quantify the tourists’ affective needs for hotels, a Kansei-related dictionary towards hotel domain is constructed by Kansei text mining. Secondly, the bilattice-based Kansei score of hotels is defined and measured to represent hotel affective information scientifically. Then, a group consensus model with minimum adjustment cost is introduced to coordinate consistency of individual preferences in a tourist group. Moreover, a group hotel ranking based on group affective preference is interactively generated to meet the group personalized demands. Finally, a case study on Trip.com is conducted to demonstrate the proposed method. Collapse

Topics: knowledge representation online review personality website

Methods: natural language processing word2vec computational algorithm sentiment analysis case study

Assessing Organizational Users’ Intentions and Behavior to AI Integrated CRM Systems: a Meta-UTAUT Approach

2023 | Information Systems Frontiers | Citations: 0

Authors: Chatterjee, Sheshadri; Rana, Nripendra P.; Khorana, Sangeeta; Mikalef, Patrick; Sharma, Anuj

Abstract: This paper tests the meta-analysis based unified theory of acceptance and use of ... Expand

Abstract: This paper tests the meta-analysis based unified theory of acceptance and use of technology (meta-UTAUT) model to predict the behavioral intentions of organizational users and their use behavior to artificial intelligence (AI) integrated customer relationship management (CRM) systems. Data was collected from 315 organizational users in India. The hypotheses draw on the theoretical underpinnings which have been statistically validated. Results show that CRM quality and satisfaction significantly influences an organization’s employees attitudes and intentions to use AI integrated CRM systems. The compatibility of CRM systems has, however, a limited impact on employees attitudes. The findings, which are aligned with the extended UTAUT model, provide useful insights into organizations and decision-makers for designing AI integrated CRM systems. Collapse

Topics: artificial intelligence customer relationship management system behavioral intention usage intention social influence

Methods: survey partial least squares path modeling partial least squares regression mediation analysis theoretical contribution

Theories: unified theory of acceptance and use of technology

The bright side of emotional extremity: Evidence from tipping in live streaming platform

2023 | Information & Management | Citations: 0

Authors: Chen, Xingyu; Ji, Li; Jiang, Ling; Huang, Justin T.

Abstract: Live streaming has enabled viewers to interact with broadcasters and peer viewer ... Expand

Abstract: Live streaming has enabled viewers to interact with broadcasters and peer viewers, as well as tip the broadcaster based on their emotional state. While most tips are small, a minority of viewers tip extremely large. To uncover such unique tipping patterns, we draw on the emotion literature and competitive arousal theory to examine how viewers’ emotional extremity affects tipping behavior and how broadcaster’s emotional response moderates the baseline effect. This study contributes to the emerging live streaming literature by revealing the differential effects of emotional extremity on tipping amount and frequency and provides practical implications for broad­ casters and platforms to steer tipping behavior. Collapse

Topics: live streaming platform marketing management accounting digital platform artificial intelligence

Methods: statistical hypothesis test computational algorithm psychometrics machine learning longitudinal research

Prediction of hotel booking cancellations: Integration of machine learning and probability model based on interpretable feature interaction

2023 | Decision Support Systems | Citations: 0

Authors: Chen, Shuixia; Ngai, Eric W.T.; Ku, Yaoyao; Xu, Zeshui; Gou, Xunjie; Zhang, Chenxi

Abstract: Reliable hotel cancellation prediction can help establish appropriate operationa ... Expand

Abstract: Reliable hotel cancellation prediction can help establish appropriate operational strategies for hotel manage­ ment. In this sector, personal name records (PNR) data may be the most representative information source for prediction tasks. Despite the popularity of PNR, its inherent lack of availability has been commonly disregarded in the literature. Existing studies have directly input PNR into high-dimensional machine learning (ML) models to achieve cancellation predictions. Another type of model generates cancellation prediction based on the proba­ bility modeling of samples. In this study, we propose an interpretable feature interaction method to enrich the existing PNR information. Thereafter, we empirically assess the prediction performance of the two model classes. This study specifically determines whether or not the two methods can cross-fertilize each other to improve cancellation prediction. To do so, we propose a model integrating Bayesian networks (BNs) and Lasso regression for this prediction task. This study utilizes BNs for the probability model consistent with our correlated variables and dichotomous prediction setting. Moreover, we use a linear ML model (i.e., Lasso regression), given its ad­ vantages in reducing ineffective predictors and transparency for ranking feature importance. Empirical results show that the proposed integration model has better prediction performance, and the obtained BN estimators and interactive features are the most important predictors. This study contributes to the booking cancellation liter­ ature by proposing an interpretable feature interaction and a prediction method integrating two types of effective models. The obtained accurate and interpretable cancellation prediction further contributes to offering practical implications to hoteliers in managerial decision-making. Collapse

Topics: missing data decision making competitive advantage price management marketing management

Methods: lasso regression experiment computational algorithm robustness check parametric test

The double-edged effects of data privacy practices on customer responses

2023 | International Journal of Information Management | Citations: 0

Authors: Chen, Shijiao (Joseph); Tran, Khai Trieu; Xia, Zhenhua (Raymond); Waseem, Donia; Zhang, Jing A.; Potdar, Balkrushna

Abstract: Requesting personal information in frontline service encounters raises privacy c ... Expand

Abstract: Requesting personal information in frontline service encounters raises privacy concerns among customers. The proximity contact tracing that occurred during the COVID-19 pandemic provides an intriguing context of in­ formation requests. Hospitality venues required contact tracing details from customers, and customer coopera­ tion varied with concerns about privacy. Drawing on gossip theory, we investigate the roles of businesses’ data privacy practices and government support in driving customers’ responses to contact tracing. Our findings show that perceived transparency of a business’s privacy practices has a positive effect on customers’ commitment to the business, while perceived control exerts a negative effect on commitment. These effects are mediated by customers’ information falsification rather than disclosure, because the former is a sensitive behavioral indicator of privacy concerns. The results also reveal the moderating roles of government support. This research con­ tributes to the customer data privacy literature by demonstrating the distinct effects of perceived transparency and control on commitment and revealing the underlying mechanism. Moreover, the research extends the conceptual understanding of privacy practices from online contexts to face-to-face contexts of frontline service. The findings offer implications for the management of customer data privacy. Collapse

Topics: privacy information privacy concern pandemic unintended consequence behavioral intention

Methods: qualitative interview survey conceptual modelling statistical hypothesis test structural equation modeling

Economic Impacts of Platform-Endorsed Quality Certification: Evidence from Airbnb

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Dewan, Sanjeev; Kim, Jooho; Nian, Tingting

Abstract: We contribute to the emerging literature on quality certification by digital pl ... Expand

Abstract: We contribute to the emerging literature on quality certification by digital platforms by studying the launch of the Airbnb Plus service, wherein the platform inspects properties and provides a badge that presumably signals the quality of the property and the reliability of the host. Our identification strategy relies on the fact that the Airbnb Plus service was launched in different cities at different times, and listings within the cities received the certification at different times. Using a staggered difference-in-differences estimation strategy in conjunction with suitable matching methods, we found that the Airbnb Plus certification increased the weekly booking rate of Plus listings by about 6.8% on average (direct effect). We also found some evidence that non-Plus listings saw a temporary decline in booking rate when one or more nearby properties received a Plus certification (externality effect). The net impact of the Airbnb Plus service on the platform itself was an annual increase in revenue of about $37,500 for the average 2-kilometer zone in a U.S. city that included one or more Plus listings, as compared to matched zones without any Plus listings (local platform effect). We performed additional analyses, including a randomized experiment, to demonstrate the robustness of our findings. Overall, our results suggest that platform-endorsed quality certification has significant economic impacts-not just on the listings that receive the certification but on other listings on the platform as well as on the platform itself. Collapse

Topics: Airbnb website sharing platform peer-to-peer model Google+

Methods: experimental group experiment propensity score method product review robustness check

On the Same Page? What Users Benefit from a Desktop View on Mobile Devices

2023 | Information Systems Research | Citations: 0

Authors: Fink, Lior; Papismedov, Daniele

Abstract: The presentation of online content is routinely adapted to the smaller screens o ... Expand

Abstract: The presentation of online content is routinely adapted to the smaller screens of mobile devices by implementing an information architecture (IA) that hierarchically restructures the information being presented to users, in conjunction with layout and size adaptations. Despite the understanding that users of mobile devices are likely to experience lower usability and higher load without such adaptations, a recent trend is to offer these users the ability to opt out of content adaptation and revert to a desktop view. The prevailing justification for this trend is the existence of websites that fail to provide an optimal mobile experience. In this work, we show that a desktop view may benefit mobile users by increasing the accuracy of their decisions. Focusing on the difference between a desktop IA, where information is presented on a single page, and a mobile IA, where information is hierarchically distributed across pages, we hypothesize that mobile users exhibit lower decision accuracy when a mobile IA is implemented. We theoretically anchor this hypothesis in the effort-accuracy framework, which views decision behavior as contingent on the trade-off between effort and accuracy. This hypothesis is supported in two laboratory experiments in which participants are faced with the multiattribute choice task of making an online hotel reservation. The experiments also highlight a boundary condition for the negative effect of the mobile IA on decision accuracy, depending on whether the mobile IA is congruent with user preferences. The findings suggest that content adaptation on mobile devices deserves greater research attention, particularly from the perspective of adaptive decision behavior.History: Anandasivam Gopal, Senior Editor; Likoebe Maruping, Associate Editor.Funding: The authors thank the Israel Science Foundation [Grant 604/18] for providing funding in support of this research.Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1140. Collapse

Topics: mobile system information storage and retrieval system decision making website smartphone

Methods: experiment descriptive statistic regression analysis method survey statistical hypothesis test

Theories: theory of bounded rationality

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