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

Platform Refund Insurance or Being Cast Out: Quantifying the Signaling Effect of Refund Options in the Online Service Marketplace

2023 | Information Systems Research | Citations: 0

Authors: Zheng, Jinyang; Wang, Youwei; Tan, Yong

Abstract: This study examines whether and how an online service marketplace can leverage r ... Expand

Abstract: This study examines whether and how an online service marketplace can leverage refund options endorsed by different parties (i.e., the platform or sellers) to address the “lemons” problem that is caused by the intangibility, variability, and unreturnable nature of the services sought. Through developing a signaling mechanism and a corresponding demand estimation model, we show that both platform refund insurance and a seller-guaranteed refund increase service demand, with platform refund insurance as the more effective option and hence having a more effective signaling mechanism. A reduced-form analysis suggests that sellers with a better reputation or less popularity might benefit less from refund options. An investigation on further use of the more effective refund option, a “having platform refund insurance or being cast out” policy (i.e., retaining platform refund-insured sellers but expelling uninsured ones), using counterfactual simulations and supply-side single interrupted time series designs, reveals the effectiveness of this policy in filtering out low-quality sellers, shown as an improved quality of sellers on the platform due to the change in sellers (i.e., new sellers’ replacing those who were expelled) both immediately after the policy and in the (near) equilibrium, yet a cost (i.e., a loss in demand and consumer welfare) for the platform in the (near) equilibrium due to the changes in characteristics (e.g., price) of sellers. This cost, however, is lower than the benefit from the improved quality of the sellers, so that the platform’s overall performance improves. The study also quantifies the consumer welfare of the online service marketplace and provides practical insight for consumers, sellers, and online service marketplace operators. History: Juan Feng, Senior Editor; Beibei Li, Associate Editor. Funding: This work was supported by the National Natural Science Foundation of China [Grants 71972047, 71831005, and 91746302]. Supplemental Material: The online supplement is available at https://doi.org/10.1287/isre.2022.1162. Collapse

Topics: consumer surplus IS economics electronic market service quality smart watch

Methods: simulation longitudinal research robustness check descriptive statistic time series analysis

Theories: lemon market theory signaling theory

The Value of Incorporating Review Tags into an Online Review System for User Review Generation

2022 | International Conference on Information Systems | Citations: 0

Authors: Li, Lun; Huang, Nina; Yin, Qiuju; Yan, Zhijun; Plant, Robert; Hong, Yili

Abstract: Online review mining has become an important way for businesses to understand c ... Expand

Abstract: Online review mining has become an important way for businesses to understand consumer preferences and product characteristics. Many online review platforms have started to incorporate the extracted information as review tags to guide future reviews. In this study, we leverage a quasi-experiment from an online health service platform to investigate the value of incorporating the review tags (extracted from prior reviews) into the online review system in user review generation. Our preliminary results show that after the provision of review tags, more reviews are provided for doctors but the length of those reviews is shorter. Notably, we also find a decrease in sentiment and an increase in novel reviews. Our findings provide actionable managerial insights for platform managers to design online review systems. Collapse

Topics: online review user-generated content electronic health systems design organization learning

Methods: sentiment analysis quasi experiment GloVe econometric modeling computational algorithm

Examining the Impacts of Airbnb Review Policy Change on Listing Reviews

2022 | Journal of the Association for Information Systems | Citations: 0

Authors: Mousavi, Reza; Zhao, Kexin

Abstract: In July 2014, Airbnb, one of the biggest firms in the sharing economy, decided ... Expand

Abstract: In July 2014, Airbnb, one of the biggest firms in the sharing economy, decided to change the way that guests and hosts reviewed each other on the platform. Prior to this change, guests/hosts could post reviews about their experiences asynchronously-the guest/host would be able to see the other party's review whenever it was posted. In contrast, the new review policy rolled out a simultaneous review system, making reviews viewable only after both the guest/host post their own reviews. This study empirically evaluates the impacts of this new review policy on the informativeness of guest reviews, measured by both informational content (semantic diversity and objectivity) and personal opinions (sentiment and sentiment heterogeneity). Using regression discontinuity design and a variety of techniques in the text analytics domain including a novel adaptation of BERT, we demonstrate that Airbnb's review policy change enhanced the informational content of guest reviews in terms of semantic diversity and objectivity. We also show that review sentiment was reduced but became more diverse. Subgroup analysis revealed that low-quality listings were subject to more changes than highquality listings. We further explore the short-term and long-term effects of the review policy change and demonstrate that the simultaneous review system has had a long-lasting impact on the informativeness of guest reviews. Collapse

Topics: Airbnb online review Python sharing platform privacy

Methods: BERT sentiment analysis natural language processing experiment regression discontinuity design

Collaborative Distance Learning via Desktop Videoconferencing

1994 | International Conference on Information Systems | Citations: 0

Authors: Wheeler, Bradley; Alavi, Maryam; Wei, Kwok-Kee; Woo, Lee-Yong

Abstract: Desktop videoconferencing (DVC) with fully interactive collaboration software ha ... Expand

Abstract: Desktop videoconferencing (DVC) with fully interactive collaboration software has recently emerged as a viable cominuIiication mediuin. These systems incorporate multiple collaboration technologies (e. g., voice, video, a mutually controllable shared software screen via dynamic data sharing) into a familiar and integrated desktop environment (i.e., windows-based personal computer). The designers of this technology are promoting it as a key enabler to support distributed teams of knowledge workers in ietwork organizations (Forbes 1993). It is also being promoted as a vehicle to deliver collaborative distance learning (Business Week 1994). We report on an experiment which assessed the efficacy of DVC for enabling collaborative distance learning. Since collaborative learning requires rich interaction between learners, it was hypothesized that face-to-face teams would exhibit greater learning and satisfaction than nonproximate teams which communicated via DVC. Collapse

Topics: spreadsheet IT skill video conference information exchange

Methods: Student's t-test interrupted time series design quasi experiment field experiment experiment