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

The Consequences of Rating Inflation on Platforms: Evidence from a Quasi-Experiment

2023 | Information Systems Research | Citations: 0

Authors: Aziz, Arslan; Li, Hui; Telang, Rahul

Abstract: Informative online ratings enable digital platforms to reduce the search cost fo ... Expand

Abstract: Informative online ratings enable digital platforms to reduce the search cost for buyers to find good sellers. However, rating inflation, a phenomenon in which average rating increases and rating variance across listings decreases, threatens the informativeness of ratings. We empirically identify the consequences of rating inflation by conducting a quasi-experiment with a digital platform that exogenously changed its rating display rule in a treated neighborhood, which resulted in rating inflation. Using a differences-in-differences approach, we find that platforms benefit from one aspect of rating inflation: user purchases and seller sales increase because of the increased average rating. However, they also face negative consequences: rating inflation causes a decrease in user trial and a greater concentration of sales among popular restaurants. Overall, our results illustrate the potential consequences of rating inflation that platforms need to consider when designing and managing their rating system.History: Xiaoquan (Michael) Zhang, Senior Editor; Gordon Burtch, Associate Editor.Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2022.1134. Collapse

Topics: digital platform mobile application word of mouth ease of use consumer behavior

Methods: experiment pilot experiment experimental group robustness check quasi experiment

Privacy Regulation and Its Unintended Consequence on Consumption Behaviors: Evidence From CCPA

2023 | International Conference on Information Systems | Citations: 0

Authors: Bae, Donghwa; Mayya, Raveesh; Nian, Tingting

Abstract: This study explores the unintended consequences of data protection regulations ... Expand

Abstract: This study explores the unintended consequences of data protection regulations on consumer behavior. Specifically, we examine the California Consumer Privacy Act, which restricts companies from collecting Californians' personal information. Privacy regulations may limit firms' ability to suggest products aligned with consumers' taste predicted from data, potentially influencing subsequent consumer behavior. These regulations especially pose a challenge to digital platforms, as their success hinges on seamless data flow between firms and consumers. Using a difference-in-differences approach with transaction data, we find that post-CCPA, Californians reduce purchase by 4.1%, increase returns by 2.9%. Moreover, we find that Californians spend more time online and visit more webpages, potentially indicating increased search efforts. Mechanism analysis suggests that firms under CCPA proactively alter their data collection strategy to reduce the liability. These results reveal the complex interplay between privacy regulation and consumer behavior, highlighting the need for a nuanced understanding of the trade-offs between privacy protection and economic outcomes. Collapse

Topics: information privacy law legal context consumer behavior advertising management website

Methods: experimental group longitudinal research natural experiment archival research difference in differences

The motivation paradox: Understanding contradictory effects of awards on contribution quantity versus quality in virtual community

2023 | Information & Management | Citations: 0

Authors: Banerjee, Shankhadeep; Bhattacharyya, Samadrita; Bose, Indranil

Abstract: We use the lens of the intrinsic/extrinsic motivation theory to holistically mod ... Expand

Abstract: We use the lens of the intrinsic/extrinsic motivation theory to holistically model the effects of intangible awards on member contribution in virtual communities. Using multiple studies on Yelp, we validate that the influence of award stimuli on contribution outcomes become significantly moderated by the aspect of contribution (quantity versus quality) and the novelty of stimuli (time and repetition of awards) to interestingly form divergent (downward versus upward) yet theoretically explicable curvilinear trajectories of contribution. This study contributes to IS literature on virtual communities and social-cognitive literature on work motivation and offers insights to community managers to design better incentive systems. Collapse

Topics: online community intrinsic motivation electronic health blockchain online review

Methods: theory development ANOVA parametric test regression analysis method experimental group

Theories: motivation theory self determination theory cognitive evaluation theory

Telepresence in live-stream shopping: An experimental study comparing Instagram and the metaverse

2023 | Electronic Markets | Citations: 0

Authors: Barta, Sergio; Gurrea, Raquel; Flavián, Carlos

Abstract: Advances in digital platforms allow influencers to use live shows to showcase pr ... Expand

Abstract: Advances in digital platforms allow influencers to use live shows to showcase products, which has given rise to live-stream shopping. Moreover, new communication forms have emerged, such as the metaverse. The social interactions that occur in these immersive environments foster influencer-follower interactions. This research compares the impact of live-stream shopping on followers’ experiences and behaviors on two communication channels (live shows on Instagram and in the metaverse) and analyses the moderating role of content involvement in telepresence. Data were collected in a between-subjects quasi-field experiment. Two scenarios that differed in degree of telepresence were created, a live show on Instagram and a live show in the metaverse. The results showed that telepresence is an important part of the user experience and in the success of live shows. Telepresence was seen to have a major influence on experiential value, but not on instrumental value. Both values provided followers with satisfaction with the experience. This satisfaction generated stickiness intention and intention to recommend the influencers’ live shows. The effect of telepresence on experiential value was greater for followers less involved with the influencer’s content. This research is pioneering in comparing an established platform, Instagram, with the metaverse. Despite the greater experiential value provided by the metaverse, to increase its instrumental value metaverse spaces needs to be further developed. Collapse

Topics: video conference virtual reality Instagram social network social media

Methods: survey field experiment statistical power analysis statistical hypothesis test experimental group

Theories: technology acceptance model

Conversation Analytics: Can Machines Read between the Lines in Real-Time Strategic Conversations?

2023 | HICSS | Citations: 0

Authors: Chen, Y.; Rui, H.; Whinston, A.

Abstract: Strategic conversations involve one party with an informational advantage and t ... Expand

Abstract: Strategic conversations involve one party with an informational advantage and the other with an interest in the information. This paper proposes machinelearning based measures to quantify the degrees of evasiveness and incoherence of the informed party during real-time strategic conversations. The specific empirical context is the questions and answers (Q&A) part of earnings conference calls during which managers endure high pressure as they face analysts' scrutinizing questions. Being reluctant to disclose adverse information, managers may resort to evasive answers and sometimes respond less coherently due to increased cognitive load. Using data from the earnings calls of the S&P 500 companies from 2006 to 2018, we show that the proposed measures predict worse nextquarter earnings. Moreover, the stock market perceives incoherence as a negative signal. This paper contributes methodologically by developing two novel machinepowered measures to automatically evaluate behavioral cues during real-time strategic conversations. The proposed analytical tools are particularly beneficial to resource-constrained and informationally disadvantaged parties such as retail investors who may not be able to effectively trade on signals buried deep in unstructured conversational data. Collapse

Topics: database system artificial intelligence electronic finance missing data accounting

Methods: computational algorithm BERT deep learning machine learning next sentence prediction

Theories: theory of economic growth

Toward Designing Innovation Learning Experiences: Examining Engagement and Affective Traits Based on Learner and Course Characteristics

2023 | HICSS | Citations: 0

Authors: Collins, Regina; Deek, Fadi

Abstract: Expanding innovation education research beyond the business domain, this study i ... Expand

Abstract: Expanding innovation education research beyond the business domain, this study introduces learning assignments using individual and group knowledge acquisition to mimic participation in today’s digital innovation platforms, examining learner affective and course characteristics as important factors for designing appropriate innovation learning experiences. Findings suggest that graduate students are more engaged and report higher perceptions of quality and quantity of social capital as well as learning from such assignments and also report higher perceptions of affective characteristics. Groups assigned by instructors (rather than self-selected) are also more engaged with higher perceptions of learning and quantity of social capital. Learners for whom the course is in their degree program are also more engaged, storing more knowledge resources individually and reporting higher perceptions of perceived learning, quantity of social capital, task value, and system satisfaction. Together, these findings have practical implications for educators seeking to engage students in meaningful innovation learning experiences. Collapse

Topics: social capital self efficacy IS satisfaction innovation management knowledge creation

Methods: Student's t-test parametric test survey descriptive statistic survey design

Navigating AI in Personnel Selection: A Scenario-based Study on Applicants' Perceptions

2023 | International Conference on Information Systems | Citations: 0

Authors: Czernietzki, Charlotte; Märtins, Julian; Westmattelmann, Daniel; Grotenhermen, Jan-Gerrit; Oldeweme, Andreas; Baumeister, Viktoria; Schewe, Gerhard

Abstract: AI-based systems are increasingly deployed on organizational tasks, such as per ... Expand

Abstract: AI-based systems are increasingly deployed on organizational tasks, such as personnel selection decisions. As existing research indicates that applicants generally react negatively to the use of AI in personnel selection, this study examines how organizations can mitigate adverse reactions to fully exploit the benefits of AI. To obtain robust results, we recruited an online sample of German participants (N = 1,852) and presented them with various selection scenarios. Using a between-subject design, the process stage (preselection vs. interview) and the degree of process automation (augmented vs. automated) were manipulated. By employing a multidimensional conceptualization of transparency, we show that disclosure and accuracy positively impact procedural justice perceptions, a strong predictor of process quality assessment. This relationship is robust across selection contexts. Results indicate that applicants prefer AI for pre-selection and as human decision support, thus offering overall insights into design choices for AI in selection, optimizing applicant reactions. Collapse

Topics: artificial intelligence business process automation data quality electronic mail virtual reality

Methods: qualitative interview partial least squares path modeling survey parametric test ANOVA

Theories: procedural justice theory organizational justice theory

Let Artificial Intelligence Be Your Shelf Watchdog: The Impact of Intelligent Image Processing-Powered Shelf Monitoring on Product Sales

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Deng, Yipu; Zheng, Jinyang; Huang, Liqiang; Kannan, Karthik

Abstract: We collaborated with a leading fast-moving consumer goods (FMCG) manufacturer t ... Expand

Abstract: We collaborated with a leading fast-moving consumer goods (FMCG) manufacturer to investigate how intelligent image processing (IIP)-based shelf monitoring aids manufacturers' shelf management by using data from a quasi-experiment and a field experiment. We discovered that such artificial intelligence (AI) assistance significantly and consistently improves product sales. Several underlying mechanisms were revealed by our quantitative and qualitative analysis. First, retailers are more likely to comply due to the greater monitoring effectiveness enabled by AI assistance. Second, the positive effect of IIP-based shelf monitoring partially persists after it is terminated, implying that human learning takes place. Third, the value of IIP-based shelf monitoring can be attributed to independent retailers rather than chain retailers. Since the degree of contract heterogeneity is the major difference between these retailers in terms of monitoring, this finding further suggests that AI is relatively more scalable when coping with more heterogeneous instances. Apart from these great benefits, we demonstrate the low marginal costs of implementing IIP-powered shelf monitoring, which indicates its long-term applicability and potential to generate incremental value. Our research contributes to several literature streams and provides managerial insights for practitioners who consider AI-assisted operational models. Collapse

Topics: artificial intelligence organizational value cost benefit analysis mobile application human AI collaboration

Methods: experimental group field experiment qualitative interview experiment quasi experiment

When Reward Meets Donation: A Paradoxical Dilemma

2023 | International Conference on Information Systems | Citations: 0

Authors: Deng, Yipu; Zheng, Jinyang; Li, Guoxin; Kannan, Karthik

Abstract: Reward-based crowdfunding platforms are increasingly incorporating donation opt ... Expand

Abstract: Reward-based crowdfunding platforms are increasingly incorporating donation options, allowing backers to financially support campaigns without receiving any tangible rewards in return. Although this option seems to create a novel fundraising channel, our quasi-natural experimental study highlights the potential negative impacts of individual donation occurrences, which ultimately lead to reduced total raised funds, as substantiated by robust empirical evidence. We explore two primary mechanisms responsible for the adverse effect. First, the bystander effect, where prior donations discourage potential backers from supporting the campaign, causing them to either forgo reward purchases or decrease their contribution amounts. Second, the social conformity effect, in which prior donations shape backers' perceptions of social norms and consequently lower their support levels. By offering a comprehensive understanding of behavioral dynamics in crowdfunding, our study enriches the literature on the design and management of crowdfunding platforms and provides valuable insights for industry practitioners. Collapse

Topics: crowdfunding crowdsourcing social norm logistics management willingness to pay

Methods: experimental group propensity score method descriptive statistic quasi experiment experiment

Theories: social influence theory