The Backstory of “An Adversarial Dance”

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

Authors: Leidner, Dorothy E.; Burns, A. J.; Balozian, Puzant

Abstract: Puzant Balozian is an assistant professor of computer information systems at Ja ... Expand

Abstract: Puzant Balozian is an assistant professor of computer information systems at James Madison University. His research focus is primarily on the impacts of organizational factors on individual user behaviors in the context of information security and privacy and addressing security policy compliance and violation. His research has been published in Collapse

Topics: IT security defense anonymity

Methods: grounded theory qualitative interview case study literature sample survey

Team Adaptation to Discontinuous Task Change: Equity and Equality as Facilitators of Individual and Collective Task Capabilities Redevelopment

2023 | Organization Science | Citations: 0

Authors: Li, Alex Ning; Sherf, Elad N.; Tangirala, Subrahmaniam

Abstract: Teams often need to adapt to planned discontinuous task change or fundamental al ... Expand

Abstract: Teams often need to adapt to planned discontinuous task change or fundamental alteration of tasks, tools, and work systems. Although team adaptation theories have made substantive progress in explaining how teams can respond to change, they have not adequately considered the unique impact that discontinuous task change can have on teams. Such change can render not only collective but also individual task capabilities obsolete and necessitate a multilevel task relearning process. Drawing on the team compilation model, we suggest that adaptation to discontinuous task change is akin to team (re)development. We posit that teams are more effective when they approach discontinuous task change by first focusing on the rebuilding of individual task capabilities and only later shifting their attention to the rebuilding of team-level task capabilities. Moreover, we argue that the uncertainty caused by discontinuous task change makes reward fairness salient such that equity and equality in rewards are particularly useful in motivating members to (re)develop individual and collective task capabilities, respectively. We provide support for these arguments using survey, qualitative, and archival data from 115 manufacturing teams and discuss the implications of our findings for both research and practice. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1621. Collapse

Topics: team productivity human resource management task interdependence social norm task productivity

Methods: theory development survey design archival research qualitative interview survey

Theories: adaptation-level theory

Combating Misinformation by Sharing the Truth: a Study on the Spread of Fact-Checks on Social Media

2023 | Information Systems Frontiers | Citations: 0

Authors: Li, Jiexun; Chang, Xiaohui

Abstract: Misinformation on social media has become a horrendous problem in our society. F ... Expand

Abstract: Misinformation on social media has become a horrendous problem in our society. Fact-checks on information often fall behind the diffusion of misinformation, which can lead to negative impacts on society. This research studies how different factors may affect the spread of fact-checks over the internet. We collected a dataset of fact-checks in a six-month period and analyzed how they spread on Twitter. The spread of fact-checks is measured by the total retweet count. The factors/variables include the truthfulness rating, topic of information, source credibility, etc. The research identifies truthfulness rating as a significant factor: conclusive fact-checks (either true or false) tend to be shared more than others. In addition, the source credibility, political leaning, and the sharing count also affect the spread of fact-checks. The findings of this research provide practical insights into accelerating the spread of the truth in the battle against misinformation online. Collapse

Topics: Twitter misinformation social media internet technology website

Methods: regression analysis method topic model logarithmic transformation mathematical model literature study

Theories: diffusion of innovations theory

The Role of Sentiment Tendency in Affecting Review Helpfulness for Durable Products: Nonlinearity and Complementarity

2023 | Information Systems Frontiers | Citations: 0

Authors: Li, Jin; Zhang, Yulan; Li, Jianping; Du, Jiangze

Abstract: The online review has become an important pillar in the decision-making process ... Expand

Abstract: The online review has become an important pillar in the decision-making process for purchasing experience products, especially durable goods with relatively high prices. Using a rich data set for automobiles, we quantify the sentiment tendency expressed in textual reviews, and empirically examine the nonlinearly inverted U-shaped relationship between customer satisfaction and sentiment tendency. We then investigate the nonlinear influences of review sentiment and depth on helpfulness. Furthermore, we study the relationship between numerical rating and text contents, i.e., sentiment tendency and review depth, in promoting the review helpfulness, and quantitatively identify the complementary effect of sentiment tendency. Our results indicate that both numerical ratings and sentiments expressed in text contents contribute to an increase in review helpfulness. Compared with polarized reviews, the neutral ones better benefit helpfulness and customer satisfaction. We also find that reviews with moderate depth are more helpful. Based on the empirical findings, we discuss several managerial implications for review system designers and consumers in the durable product market. Collapse

Topics: online review customer satisfaction experience good user-generated content website

Methods: sentiment analysis robustness check natural language processing descriptive statistic language model

Metaverse Knowledge Graph Construction: An Unsupervised Relation Extraction Approach based on Semantic Mining

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Li, Litao; Xu, Ruiyun; Zhao, J. Leon

Abstract: Metaverse has gained widespread attention in both academia and industry. As a r ... Expand

Abstract: Metaverse has gained widespread attention in both academia and industry. As a result, many new concepts, methodologies, and applications are emerging in recent years. Constructing a Metaverse knowledge graph can help with knowledge management and facilitate various intelligent tasks such as recommendations, information retrieval, and chatbots in this emerging field. However, existing knowledge graph construction approaches are not directly applicable in the Metaverse domain due to a lack of labeled dataset, making existing supervised relation extraction approaches impracticable. In this study, we develop a novel graph construction framework by integrating the deep learning approach (i.e., BERT-BiLSTM-CRF) with an unsupervised relation extraction approach based on semantic mining. The framework we propose in this paper can automatically construct knowledge graphs while significantly reducing labeling efforts. Further, we plan to implement the proposed framework on a Metaverse corpus to construct a Metaverse knowledge graph. To test our approach, we will employ an expert-survey method to evaluate the quality of triple sets. Collapse

Topics: virtual reality knowledge graph mobile application blog artificial intelligence

Methods: BERT survey word2vec deep learning named entity recognition

Reidentification Risk in Panel Data: Protecting for k-Anonymity

2023 | Information Systems Research | Citations: 0

Authors: Li, Shaobo; Schneider, Matthew J.; Yu, Yan; Gupta, Sachin

Abstract: We consider the risk of reidentification of panelists in marketing research data ... Expand

Abstract: We consider the risk of reidentification of panelists in marketing research data that are widely used to obtain insights into buyer behavior and to develop marketing strategy. We find that 17%–94% of the panelists in 15 frequently bought consumer goods categories are subject to high risk of reidentification through a potential record linkage attack based on their unique purchasing histories even when their identities are anonymized. We first demonstrate that the risk of reidentification is vastly understated by unicity, the conventional measure. Instead, we propose a new measure of reidentification risk, termed sno-unicity, which accounts for the longitudinal nature of panel data, and show that it is much larger than unicity. To protect the privacy of panelists, we consider the well-known privacy notion of k-anonymity and develop a new approach called graph-based minimum movement k-anonymization (k-MM) that is designed especially for panel data. The proposed k-MM approach can be formulated as an optimization problem in which the objective is to minimally distort variables in the original data based on weights that users prespecify corresponding to their use case. We further show how our approach can be extended to achieve l-diversity. We apply the k-MM approach to two different panel data sets that are widely used in marketing research. To achieve a given privacy level, compared with several benchmark protection methods, the protected data from our method result in the least distortion in inferences about key marketing metrics, such as brand market shares, share of category requirements, brand switching rates, and marketing-mix parameters estimated from a hierarchical Bayesian brand choice model. History: Param Singh, Senior Editor and Associate Editor. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1169. Collapse

Topics: privacy marketing management differential privacy data protection record linkage

Methods: longitudinal research optimization model descriptive statistic simulation cluster analysis

How does e-government use affect citizens’ trust in government? Empirical evidence from China

2023 | Information & Management | Citations: 0

Authors: Li, Yan; Shang, Huping

Abstract: Although much literature has discussed the potential of e-government for improvi ... Expand

Abstract: Although much literature has discussed the potential of e-government for improving citizens’ trust in govern­ ment, the question of how e-government use affects citizens’ trust in government remains underexplored. To investigate the driving mechanism of the effects of different types of e-government use on trust in government, this research develops a conceptual framework based on the institutional-based trust theory, the process-based trust theory, and the expectancy-disconfirmation model. Based on data collected from 1668 citizen users living in five cities in China, the study verifies the proposed mediated moderation model and then tests the robustness of the results using process analysis. The results reveal that citizens’ use of e-government revitalizes their trust in government indirectly, via influence on citizens’ evaluation of government integrity, performance, and responsiveness from the experience of using e-government, while the mediating effects of citizens’ evaluation of government on relationship between e-government use and public trust are diminished by citizens’ expectations for their government. The analysis also offers strong support for the conclusion that the effects of different types of e-government use on public trust are differentially distributed among multiple levels of governments in China. Collapse

Topics: government system website information storage and retrieval system internet technology social capital

Methods: survey descriptive statistic data transformation moderation analysis factor analysis

Theories: trust theory

Toward a campus crisis management system amid the pandemic and beyond

2023 | Information & Management | Citations: 0

Authors: Li, Yaojie; Zhou, Yi; Ge, Linqiang; Chen, Rui; Xiong, Jie

Abstract: This study develops artifact and design principles for a campus-wide crisis mana ... Expand

Abstract: This study develops artifact and design principles for a campus-wide crisis management system amid the COVID19 pandemic and beyond. Drawing upon crisis management literature and the uncertainty reduction theory, we develop a preliminary crisis management system with three fundamental components: dashboard, portal, and forum, geared toward aggregating environmental information, expert knowledge, and stakeholder insights. This immediate, integrated, and interactive campus crisis management system aims to promote organizational learning through knowledge acquisition, dissemination, and utilization while reducing stakeholders’ uncertainty about the crisis. Through comprehensive evaluation, we further synthesize and summarize new design principles for prospective artifacts, including constructing a distributed crisis management network, capitalizing on data mining and knowledge discovery algorithms, and developing the adaptability of the crisis management system in various circumstances. Collapse

Topics: emergency management pandemic organization learning digital dashboard usability

Methods: design principle design science design artifact machine learning kernel theory

Theories: uncertainty reduction theory organizational learning theory theory of abduction

A Chat-based personal recommendation mechanism with opinion intelligence

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Li, Yung-Ming; hsieh, chin yu; Hsu, Cheng-Chi

Abstract: A Chat-based personal recommendation mechanism with opinion intelligence" (2023 ... Expand

Abstract: A Chat-based personal recommendation mechanism with opinion intelligence" (2023). AbstractWith the rapid development of the Internet and mobile devices, users around the world have accumulated a large amount of comment data on the Internet. Nowadays, users tend to search for information on the Internet before making purchase decisions. How to provide personalized services while avoiding information overload has gradually become an important issue. This study proposes a dialogue-based personalized recommendation mechanism with opinion intelligence. In addition to understanding user preferences through dialogue and interaction with users, we further analyze the content of reviews and the social influence of review authors to better help users. The results show that the dialogue mechanism proposed in this study has a good recommendation effect and can effectively improve user experience. Collapse

Topics: recommender system social influence decision making user experience usability

Methods: experiment chatbot term frequency–inverse document frequency naïve bayes natural language processing

Digital Transformation Team’s Capabilities for Process Automation

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Li, Yuzhu

Abstract: Firms face increasing pressure to refine business values and succeed in digital ... Expand

Abstract: Firms face increasing pressure to refine business values and succeed in digital transformation. It is essential for organizations to have the required competence and capabilities to make innovation happen. This study argues that digital transformation teams should build the right competence profiles to deliver the changes using digital tools. Based on the dynamic capability theory, this paper proposes that the team's digital problem-solving capability and benefits management capability are essential for digital transformation success. Using process automation as a context, this paper suggests that digital transformation teams should build data literacy, business process management competence, and computational thinking to form their capabilities for digital transformation, leading to process automation outcomes. This paper develops the conceptual research model and discusses the research method and the future plan. Collapse

Topics: problem solving process automation system business process management digital transformation data literacy

Methods: business process modeling qualitative interview

Theories: dynamic capabilities theory