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

When Reflection Hurts: The Effect of Cognitive Processing Types on Organizational Adaptation to Discontinuous Change

2023 | Organization Science | Citations: 1

Authors: Alves, Marlon Fernandes Rodrigues; Vastola, Vincenzo; Vasconcelos Ribeiro Galina, Simone; Zollo, Maurizio

Abstract: Technological breakthroughs, institutional disruptions, and natural disasters of ... Expand

Abstract: Technological breakthroughs, institutional disruptions, and natural disasters often alter the course of organizations and entire industries. Such discontinuous changes threaten organizations’ survival by affecting the value of the knowledge accumulated in routines and capabilities. Although it is widely acknowledged that managerial cognition is a critical antecedent of organizational responses to discontinuous change, the role of type 1 (intuitive) and type 2 (reflective) processing in the adaptation of shared patterns of behavior, that is, routines, remains understudied. Drawing on dual-process theory, we propose that particular features of type 1 processing render this approach superior to type 2 processing, especially in highly ambiguous environments in which information is limited and difficult to verify. We tested our hypotheses in a longitudinal experiment linking individual-level factors with organizational-level practices of routine adaptation. Experienced managers, paired in 80 groups, developed routines in a first round of a simulation game; in a second round, we then introduced a discontinuous change making previous routines obsolete in order to observe how they adapted. The data show that priming type 1 processing facilitates organizational adaptation more than type 2 processing by providing faster, more routinized, efficiently coordinated, and optimal responses. In addition, type 1 appears to be more functional in highly ambiguous environments, whereas type 1 and type 2 processes yield similar levels of performance under low levels of ambiguity. Overall, our study advances the understanding of the nondeliberative dimension of organizational adaptation to discontinuous change.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Finance Code 001).Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1517. Collapse

Topics: decision making strategic management innovation management problem solving task productivity

Methods: experiment longitudinal research parametric test ANOVA statistical hypothesis test

Theories: dual-system theory dynamic capabilities theory

The Effect of Consensus Algorithm on Ethereum Price and Volume

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Ampel, Benjamin

Abstract: Cryptocurrencies, such as Bitcoin and Ethereum, are digital currencies operatin ... Expand

Abstract: Cryptocurrencies, such as Bitcoin and Ethereum, are digital currencies operating on a peer-to-peer network. Cryptocurrencies rely on consensus algorithms for transaction validation and network security. Ethereum recently replaced its proof-of-work (PoW) consensus algorithm with a proof-of-stake (PoS) algorithm on September 15, 2022. This research aims to study the following research question: Does changing from PoW to PoS consensus increase price and transaction volume? To answer this question, we implemented synthetic control methods to compare the pre-and post-treatment trends of the price and volume of Ethereum against a synthetic counterfactual. The result of our analysis suggests that Ethereum shifting from PoW to PoS had a positive effect on its price and a non-significant negative effect on transaction volume. Price increasing relative to the synthetic counterfactual is promising for convincing other PoW blockchains that a switch to PoS may lead to increased investment opportunities while decreasing the environmental impact. Collapse

Topics: Ethereum cryptocurrency Bitcoin knowledge base decision making

Methods: computational algorithm experiment synthetic control method experimental group longitudinal research

On Predicting ESG Ratings Using Dynamic Company Networks

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

Authors: Ang, Gary; Guo, Zhiling; Lim, Ee-Peng

Abstract: Environmental, social and governance (ESG) considerations play an increasingly i ... Expand

Abstract: Environmental, social and governance (ESG) considerations play an increasingly important role due to the growing focus on sustainability globally. Entities, such as banks and investors, utilize ESG ratings of companies issued by specialized rating agencies to evaluate ESG risks of companies. The process of assigning ESG ratings by human analysts is however laborious and time intensive. Developing methods to predict ESG ratings could alleviate such challenges, allow ESG ratings to be generated in a more timely manner, cover more companies, and be more accessible. Most works study the effects of ESG ratings on target variables such as stock prices or financial fundamentals of companies, but few works study how different types of company information can be utilized to predict ESG ratings. Previous works also largely focus on using only the financial information of individual companies to predict ESG ratings, leaving out the different types of inter-company relationship networks. Such inter-company relationship networks are typically dynamic, i.e., they evolve across time. In this paper, we focus on utilizing dynamic inter-company relationships for ESG ratings prediction, and examine the relative importance of different financial and dynamic network information in this prediction task. Our analysis shows that utilizing dynamic inter-company network information, based on common director, common investor and news event-based knowledge graph relationships, can significantly improve ESG rating prediction performance. Robustness checks over different time-periods and different number of time-steps in the future further validate these insights. Collapse

Topics: shapley additive explanation knowledge graph database system missing data network effect

Methods: machine learning econometric modeling longitudinal research Granger causality robustness check

Detecting Privacy Threats with Machine Learning: A Design Framework for Identifying Side-Channel Risks of Illegitimate User Profiling

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Anwar, Raja Hasnain; Zou, Yi (Zoe); Raza, Muhammad Taqi

Abstract: Privacy leakage has become prevalent and severe with the increasing adoption of ... Expand

Abstract: Privacy leakage has become prevalent and severe with the increasing adoption of the internet of things (IoT), artificial intelligence (AI), and blockchain technologies. Such data-intensive systems are vulnerable to side-channel attacks in which hackers can extract sensitive information from a digital device without actively manipulating the target system. Nevertheless, there is a scarcity of IS research on how businesses can effectively detect and safeguard against side-channel attacks. This study adopts the design science paradigm and lays the groundwork for systematic inquiry into the assessment of privacy risks related to side-channels. In this paper, we a) highlight the privacy threats posed by side-channel attacks, b) propose a machine learning-driven design framework to identify side-channel privacy risks, and c) contribute to the literature on privacy analytics using machine learning techniques. We demonstrate a use case of the proposed framework with a text classification model that uses keystroke timings as side-channel. Collapse

Topics: privacy IT security data breach information system use

Methods: design framework machine learning design science time series analysis longitudinal research

Sensing the Future: A Design Framework for Context-Aware Predictive Systems

2023 | Journal of the Association for Information Systems | Citations: 0

Authors: Avital, Michel; Chatterjee, Samir; Furtak, Szymon

Abstract: Sensors embedded in smart objects, smart machines, and smart buildings produce ... Expand

Abstract: Sensors embedded in smart objects, smart machines, and smart buildings produce ever-growing streams of contextual data that convey information of interest about their operating environment. Although an increasing number of industries have embraced the utilization of sensors in routine operations, no clear framework is available to guide designers who aim to leverage contextual data collected from these sensors to develop predictive systems. In this paper, we applied design science research methodology to develop and evaluate a general framework that can help designers build predictive systems utilizing sensor data. Specifically, we developed a framework for designing context-aware predictive systems (CAPS). We then evaluated the framework through its application in MAN Diesel & Turbo, which served as a case company. The framework can be generalized into a class of demand-forecasting problems that rely on sensor-generated contextual data. The CAPS framework is unique and can help practitioners make better-informed decisions when designing context-aware predictive systems. Collapse

Topics: data quality evaluation criteria knowledge base systems design systems development

Methods: machine learning design science design artifact data transformation design process

The social fabric framework: steps to eliciting the social making of organisations in the digital age

2023 | European Journal of Information Systems | Citations: 0

Authors: Avital, Michel; Jensen, Tina Blegind; Dyrby, Signe

Abstract: The proliferation of enterprise social media generates an ever-growing record of ... Expand

Abstract: The proliferation of enterprise social media generates an ever-growing record of digital traces that provides ample opportunities to study the social making of organisations. Subsequently, we present the social fabric framework, which comprises a structured five-step approach for eliciting, interpreting, and representing the situated social idiosyncrasies and underlying patterns of the social making of organisations. The paper focuses on the application of the social fabric framework as a research method. However, the framework also lends itself to practice as a diagnostic tool that can detect emergent changes in the social fabric of an organisation as well as support organisational development and change. Moreover, by providing a vocabulary for articulating the social making of organisations, the framework can help organisation members reify their dispositions, make sense of the social dynamics, and enable a constructive discussion at the grassroots level about any controversy or aspiration. Collapse

Topics: social media information exchange accounting enterprise social media

Methods: longitudinal research cluster analysis qualitative coding cross sectional research time series analysis

Value Implications of Sourcing Electronic Health Records: The Role of Physician Practice Integration

2023 | Information Systems Research | Citations: 0

Authors: Bardhan, Indranil R.; Bao, Chenzhang; Ayabakan, Sezgin

Abstract: Should hospitals source electronic health records (EHR) systems from a single ve ... Expand

Abstract: Should hospitals source electronic health records (EHR) systems from a single vendor or multiple vendors to deliver high-value care? We study hospitals’ EHR sourcing strategies based on their degree of integration with physician practices and its impact on the value of healthcare delivered. We propose a novel framework to define healthcare value as the extent to which a hospital effectively expends clinical resources to deliver services that improve patient outcomes. Drawing on modular systems and transaction cost economics theories, we propose a moderated-mediation model that explores the pathways through which EHR sourcing strategies can create value in healthcare. We test our research hypotheses on a large, longitudinal sample of U.S. hospitals and observe that hospitals with EHR configurations closer to single sourcing strategies exhibit greater health information sharing compared with hospitals with multisourced EHR systems. Furthermore, we find that hospital-physician practice integration moderates the impact of single sourcing on health information sharing, which in turn, improves value. Specifically, tighter integration between hospitals and physician practices can create greater value if it is aligned with hospitals’ EHR sourcing strategies. As the healthcare industry moves toward value-based payment reform, our findings provide a useful roadmap to practitioners and policy makers to improve the performance of hospitals and healthcare providers. History: Rajiv Kohli, Senior Editor; Sunil Wattal, Associate Editor. Funding: I.R. Bardhan thanks the Foster Parker Centennial Professorship and the Dean’s Research Excellence Grant at the McCombs School of Business at UT Austin for generous financial support. C. Bao thanks the Spears Fellowship at Oklahoma State University for financial support. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1183. Collapse

Topics: information exchange healthcare data health information system accounting database system

Methods: longitudinal research survey robustness check econometric modeling design artifact

Theories: transaction cost economics general systems theory institutional theory

Gold Rushes and Bandwagons: Blockchain’s Markets and Developers

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Barraza, Benjamin; Ravindran, Kiron; Arenas, Alvaro

Abstract: What drives Open-Source Software (OSS) development communities to participate i ... Expand

Abstract: What drives Open-Source Software (OSS) development communities to participate in Blockchain projects? Developer participation incentives in OSS are well studied but the nature of this incentive changes with a novel addition of the token or cryptocurrency. This longitudinal study followed nearly 6,000 OSS blockchain projects, their prices, and developer movements throughout 2020. We find that asset price does impact developer interest and contributions. We find lagged price movements of tokens statistically significant in later developer activity. Social aspects of developer interest are more complex and shift as we consider projects within different market cap strata. We find that lower profile blockchain projects benefit from both price movements and developer activity. Implications for managers include recruitment efforts and equity compensation. Collapse

Topics: blockchain cryptocurrency

Methods: descriptive statistic longitudinal research time series analysis

Modern Centaurs: How Humans and AI Systems Interact in Sales Forecasting

2023 | European Conference On Information Systems | Citations: 0

Authors: Beese, Jannis; Fahse, Tobias

Abstract: Recent achievements of artificial intelligence (AI) have caused organizations t ... Expand

Abstract: Recent achievements of artificial intelligence (AI) have caused organizations to increasingly bring AI capabilities into their core business processes. Such AI-supported business processes often result in human-AI hybrid systems, which consist of an AI system, which performs most of the execution, and humans, who monitor this execution and occasionally provide additional inputs and overrides. Using sales data from Walmart, we conduct an online study to investigate if human supervision can improve upon state-of-the-art AI forecasts. Furthermore, we analyze the perceptions and behavioral intentions of the human participants over time. We find that human interventions consistently lead to less accurate forecasts and that participants initially underestimate the AI system's accuracy and overestimate their own potential to improve upon AI forecasts. However, perceptions quickly shift over the course of the study, causing the participants to perceive the AI system increasingly favorably, which also leads to behavioral changes and better hybrid system performance. Collapse

Topics: artificial intelligence IT productivity information system use task productivity perceived usefulness

Methods: regression analysis method survey LightGBM conceptual modelling experiment

Theories: technology acceptance model