The Influence of Professional Embeddedness and Public Reputation on Critic Review Behavior

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Deng, Tianjie; Dong, Tianxi; Lee, Young Jin

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Topics: social network online review

Methods: robustness check moderation analysis regression analysis method

Blending Modalities, Pedagogies, and Technologies: Redesigning an Information Systems Course to Encourage Engagement

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

Authors: Doyle, Cathal; Chiu, Yi-Te

Abstract: Having realized that the traditional approach to teaching our IS course on Busi ... Expand

Abstract: Having realized that the traditional approach to teaching our IS course on Business and Systems Analysis was not engaging students enough, we decided we needed to redesign our learning environment. The goal was to develop a course that encourages student participation, allows them to practice the different techniques we introduce them to, and empowers students to take control of their learning. To achieve this, we blended modalities (online and inperson), pedagogies (constructivist and collaborative approaches), and technologies (student-centered technologies). This resulted in a redesign that included replacing the lecture with learning resources of a digestible size and an activity-based discussion, the workshop focusing on a project for authentic problems, sense-making via doing and reflection, hybrid participation in a steady and sustainable pace, and learning communities to enable more interaction. In this paper, we share our experience and lessons that we have learned through a journey toward a student-centered approach to learning. Collapse

Topics: online learning system sensemaking virtual world video conference systems analysis

Methods: experiment

Gatekeeping and the Use of Contested Practices in Creative Industries: The Case of Fur in Fashion

2023 | Organization Science | Citations: 0

Authors: Godart, Frédéric; Hsu, Greta; Negro, Giacomo

Abstract: In creative industries, a producer’s choice to use specific cultural practices i ... Expand

Abstract: In creative industries, a producer’s choice to use specific cultural practices is often driven by considerations of industry-specific notions of creativity and artistic vision. Creative producers claim autonomy over which practices are deemed desirable or legitimate, creating resistance to influences from outside the industry, such as from social movements. This study proposes that in such contexts, externally-driven change depends on the role of prominent gatekeepers. We consider how shifts in their discourse translate and amplify external social movement pressures for producers. We further argue that higher-status producers respond more to the changing discourse of these gatekeepers, to whom they are more tightly connected. This leads to a dynamic that is counterintuitive in the context of creative industries in which higher-status producers, who can benefit most from preserving the status quo, show greater responsiveness to external pressures when translated through gatekeeper discourse. Our empirical analysis uses a unique data set related to a prototypical contested practice: fur use in high-end fashion. These findings highlight the complex role of gatekeepers in creative industries and indirect pathways through which external social movements drive change. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1591. Collapse

Topics: website database system advertising management

Methods: logistic regression Student's t-test parametric test descriptive statistic post-hoc analysis

Collateral Damage: The Relationship Between High-Salience Events and Variation in Racial Discrimination

2023 | Organization Science | Citations: 0

Authors: Gorbatai, Andreea; Younkin, Peter; Burtch, Gordon

Abstract: To what extent are individual or organizational biases affected by racially sali ... Expand

Abstract: To what extent are individual or organizational biases affected by racially salient events? We propose that acts of discrimination and the individual biases that undergird them are sensitive to high-salience events and will oscillate with the salience of the focal attribute. In short, that the propensity to discriminate reflects both individual and environmental differences, and therefore a given person may become more prone to discriminate in the aftermath of a high-salience event. We test our hypothesis in three online experiments that examine how varying the salience of race affects the evaluation of in-group or out-group founders. We find that respondents evaluate their in-group members more favorably, and out-group members less favorably, when exposed to a high-salience event, which translates into a significant disadvantage for the minority (African American) group. We complement these studies with an assessment of how police shootings affect fundraising outcomes on Kickstarter to confirm the external validity of our findings. Together, these studies indicate that racially salient events depress the quality evaluations and success odds of African American entrepreneurs relative to others. Hence, discrimination levels can be affected by salient yet unrelated events, and such events are consequential for the economic fortunes of individuals belonging to minority and disadvantaged groups.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2021.1527. Collapse

Topics: crowdfunding crowdsourcing website criminality application programming interface

Methods: experiment parametric test statistical hypothesis test survey facial recognition system

A Graph Model for Conflict Resolution with Time-varying Attitudes and Its Application to China-US Trade Disputes

2023 | Group Decision and Negotiation | Citations: 0

Authors: He, Shawei; Liu, Xiaohui; Li, Xianmei

Abstract: A novel graph model with time-varying altitudes is developed to interpret the tr ... Expand

Abstract: A novel graph model with time-varying altitudes is developed to interpret the trade disputes between China and the United States (US) during the period between 2017 and 2019. The implementation of strategies for China and the US was affected by their bilateral relations represented by mutual attitudes changing over time along the evolution of the disputes. The Goldstein scale, a numeral system for studying foreign policies and for describing the fluctuating diplomatic relations affected by historical events, is utilized for eliciting preference relations affected by the time-varying attitudes for the first time. By considering two decision makers (DMs) in the trade disputes, the time varying unilateral improvements (TVUIs) for each DM are initiated based on its judgement which reflects not only the gains or losses for the given DM, but also those for the other DM. In investigating the real-world trade disputes between China and the US, the reasoning of imposing retaliating tariffs for the two countries under time frame is explained. How the fluctuation of time-varying altitudes affects the course of the disputes is also demonstrated. The Phase one agreement legally prohibiting retaliation using tariffs from the two countries was signed when mutual attitude increased by positive interstate events, which eventually ended the tit-for-tat situation. This novel methodology extends the structure of attitudes in graph model by flexibly depicting the fluctuation of mutual attitudes using Goldstein scoring system. Meaningful implications can be provided for DMs to explain how equilibrium can be changed by the time-varying attitudes. In analyzing international disputes in particular, nations can be clearly guided to achieve desired outcomes by making efforts to change bilateral or multilateral relations. Collapse

A Collective Opinion Mechanism for Crowdfunding Recommendation

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Jin, Bih-Huang; Li, Yung-Ming; Kamolporn, Sanamlao

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Topics: crowdsourcing crowdfunding Twitter social network Python

Methods: sentiment analysis experiment topic model logistic regression parametric test

Quantifying Learning and Competition among Crowdfunding Projects: Metrics and a Predictive Model

2023 | HICSS | Citations: 0

Authors: Liu, Xiexin; Rahmani Moghaddam, Maryam; Fan, Weiguo (Patrick)

Abstract: The performance of a crowdfunding project is highly situational-dependent. In th ... Expand

Abstract: The performance of a crowdfunding project is highly situational-dependent. In this study, we quantify the interactions between crowdfunding projects in order to understand how these interactions can help predict the performance of crowdfunding campaigns. Specifically, we utilize Natural Language Processing (NLP) techniques to create a semi-automated system to label the associated product for each crowdfunding campaign. We also propose three sets of metrics to measure how crowdfunding projects learn from and compete with each other. Finally, we propose a machine learning model and demonstrate that the proposed metrics and the proposed model outperform other combinations when predicting the performance of crowdfunding projects. Collapse

Topics: crowdsourcing crowdfunding research and development mobile system knowledge sharing

Methods: cluster analysis natural language processing machine learning support vector machine term frequency–inverse document frequency

Determining the optimal release time of movies: A study of movie and market characteristics

2023 | Decision Support Systems | Citations: 0

Authors: Sharma, Megha; Basu, Sumanta; Chakraborty, Soumyakanti; Bose, Indranil

Abstract: The over-the-top (OTT) industry has witnessed remarkable growth in recent years ... Expand

Abstract: The over-the-top (OTT) industry has witnessed remarkable growth in recent years with a sharp increase in the number of subscribers, leading to increased competition among OTT platforms to acquire movie rights. Conse­ quently, the gap between the theatrical and OTT releases has been diminishing over the last few years. An early release of a movie on an OTT platform fetches a higher distribution fee for a movie distributor (MD), however, it reduces the MD’s revenue from the theatrical release. Therefore, it becomes critical for the MD to determine the optimal release time and distribution fee combination. In this paper, we analytically solve the MD’s decision problem and provide a detailed analysis of how the optimal release time varies with changes in platform characteristics such as the proportion of ad revenue and the platform’s risk profile, movie characteristics such as success factor and suitability for OTT, and market characteristics such as broadband penetration, piracy rate and customers’ preferences for viewing channels. We compare our results with the actual release times of 243 movies released during 2015–2022. We find that the optimal release time increases with ad revenue proportion, broadband penetration, and piracy rate, whereas the optimal fee reduces non-linearly with release time and depends on OTT’s risk profile. Our findings also indicate that the optimal release time reduces for movies that do not provide any additional utility for theater goers, and as customers’ preference towards OTT increases. Our work provides much-needed guidelines for professionals dealing with movie releases on OTTs. Collapse

Topics: digital service Netflix Disney+ decision support system Hulu

Methods: parametric test mathematical model ANOVA paired t-test artificial neural network

The Façade, the Face, and the Sympathies: Opening the Black Box of Symbolic Capital as a Source of Philanthropic Attractiveness

2023 | Organization Science | Citations: 0

Authors: Shymko, Yuliya; Roulet, Thomas J; de Melo Pimentel, Bernardo

Abstract: Although most studies on philanthropy have focused on corporate benefactors, lim ... Expand

Abstract: Although most studies on philanthropy have focused on corporate benefactors, limited attention has been given to beneficiaries and their characteristics. The literature thus falls short in explaining how the variance in the perceived value of those characteristics can condition the philanthropic attractiveness of recipients for donors. Drawing from Bourdieu’s concept of symbolic capital and qualitative insights drawn from our empirical context of philanthropy in the field of cultural production in the Russian Federation, we argue that the attractiveness of cultural organizations for potential corporate benefactors depends on a range of determinants, which we classify under the broad umbrellas of respectability and reputability. By using political orientation as a moderator, we show that, although respectability is an indiscriminately attractive part of symbolic capital, reputability, associated with artistic celebrity and renown, can become a deterrent to potential donors when it augments the risk of jeopardizing their relationship with the government. We also demonstrate that a board of trustees, which signals openness to stakeholder involvement, diminishes the returns of reputability for potential donors. We test our hypotheses using original and representative longitudinal data on 449 Russian theaters (2004–2011). Taking an indirect recursive approach to estimate models with high-dimensional fixed effects, we find strong support for our hypotheses across a variety of econometric specifications. Our research offers a unique focus on the beneficiary side of the beneficiary-benefactor relationship, which has both theoretical and practical implications for the literatures on corporate philanthropy, and cultural industries. Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2022.1603. Collapse

Topics: database system decision making website Facebook

Methods: statistical hypothesis test longitudinal research qualitative interview theory development regression analysis method

Unifying Algorithmic and Theoretical Perspectives: Emotions in Online Reviews and Sales

2023 | Management Information Systems Quarterly | Citations: 2

Authors: Yu, Yifan; Yang, Yang; Huang, Jinghua; Tan, Yong

Abstract: Emotion artificial intelligence, the algorithm that recognizes and interprets v ... Expand

Abstract: Emotion artificial intelligence, the algorithm that recognizes and interprets various human emotions beyond valence (positive and negative polarity), is still in its infancy but has attracted attention from industry and academia. Based on discrete emotion theory and statistical language modeling, this work proposes an algorithm to enable automatic domain-adaptive emotion lexicon construction and multidimensional emotion detection in texts. Using a large-scale dataset of China's movie market from 2012 to 2018, we constructed and validated a domain-specific emotion lexicon and demonstrated the predictive power of eight discrete emotions (i.e., surprise, joy, anticipation, love, anxiety, sadness, anger, and disgust) in online reviews on box office sales. We found that representing overall emotions through discrete emotions yields higher prediction accuracy than valence or latent emotion variables generated by topic modeling. To understand the source of the predictive power from a theoretical perspective and to test the cross-culture generalizability of our prediction study, we further conducted an experiment in the U.S. movie market based on theories on emotion, judgment, and decision-making. We found that discrete emotions, mediated by perceived processing fluency, significantly affect the perceived review helpfulness, which further influences purchase intention. Our work shows the economic value of emotions in online reviews, generates insight into the mechanism of their effects, and has managerial implications for online review platform design, movie marketing, and cinema operations. Collapse

Topics: online review Python user-generated content microblog marketing management

Methods: computational algorithm word2vec parametric test product review experiment

Theories: psychological theory