Navigating the Paradox of IT Novelty and Strategic Conformity: The Moderating Role of Industry Dynamism

2023 | International Conference on Information Systems | Citations: 0

Authors: Chaturvedi, Devina; Kathuria, Abhishek; Andrade, Mariana; Saldanha, Terence

Abstract: Although achieving strategic distinctiveness is critical for firms in dynamic i ... Expand

Abstract: Although achieving strategic distinctiveness is critical for firms in dynamic industries, where the competitive landscape and market conditions frequently change, there is a paucity of research on the impact of information technology (IT) on a firm's strategic conformity (or distinctiveness). Motivated by the importance of strategic conformity and emergence of novel technologies, we draw on institutional theory and hypothesize that IT Novelty positively impacts strategic conformity. Second, drawing on resource-based view, we hypothesize that market dynamism and competitive dynamism negatively moderate the effect of IT Novelty on strategic conformity. Third, we hypothesize that the moderating impact is stronger for market dynamism than competitive dynamism. We find support for our hypotheses using a fifteen-year dataset from over 300 U.S. manufacturing firms. Our study contributes to theory and managerial practice by combining institutional and resource-based view perspectives to examine how IT Novelty shapes a firm's strategic conformity, particularly in dynamic industry conditions. Collapse

Topics: database system decision making artificial intelligence internet of things mobile system

Methods: longitudinal research autocorrelation analysis hierarchical linear modeling robustness check regression analysis method

Theories: resource based view of the firm institutional theory

Token Incentives in a Volatile Crypto Market: The Effects of Token Price Volatility on User Contribution

2023 | Journal of Management Information Systems | Citations: 0

Authors: Chen, Kun; Fan, Yifan; Liao, Shaoyi Stephen

Abstract: Crypto tokens, issued and managed via smart contracts, function as rewards in bl ... Expand

Abstract: Crypto tokens, issued and managed via smart contracts, function as rewards in blockchain systems to encourage user participation. Distinct from monetary incentives, token incentives are uncertain in reward magnitude due to the large swings in token prices on crypto markets. By focusing on token price volatility, this study investigates how the reward uncertainty affects user contribution in a tokenized digital platform. Our empirical setting is Steemit, a platform where bloggers write posts and share token rewards based on their posts' popularity. We find that while high token price volatility induces a large volume of blog posts, it diminishes post quality. The dichotomous effects are explained via two mechanisms: users' direct reactions to reward uncertainties and their indirect reactions, mediated by altered token preference amid volatility shocks. Deeply exploring this dynamic process, our results reveal that token price volatility facilitates a platform's network short-term effect but impairs long-term user creativity. Our empirical findings thus extend the literature on blockchain economics and cryptocurrencies and have practical implications for the design of incentive mechanisms on tokenized digital platforms. Collapse

Topics: blog blockchain digital platform cryptocurrency user behavior

Methods: longitudinal research instrumental variables estimation data transformation principal component analysis vector autoregression

Theories: motivation crowding theory

Understanding active participation of online dating services: A mixed methods study

2023 | Decision Support Systems | Citations: 0

Authors: Chen, Qi; Yun, Guobiao; Lu, Jiandong; Wang, Xiaolei

Abstract: Online dating has transformed the way people meet and start relationships. Howev ... Expand

Abstract: Online dating has transformed the way people meet and start relationships. However, online dating platforms typically have many lurkers without active participation. Using a self-regulation framework, this paper aims to study users’ active participation in online dating through a mixed methods study. We first conducted qualitative and quantitative investigations with a machine learning method to explore user active participation and its antecedents. We then developed a theoretical model and conducted a statistical analysis of the model. The empirical findings showed that service quality and trust significantly affected individual active participation in a dating site through attachments to the daters and services. The findings of the study contribute to the extant literature by analyzing user participation in online dating from an attachment perspective. Collapse

Topics: service quality online dating participatory design online dating service Python

Methods: design methodology mixed method qualitative coding machine learning machine learning method

Theories: attachment theory marketing theory

Stand for Something or Fall for Everything: Predict Misinformation Spread with Stance-Aware Graph Neural Networks

2023 | International Conference on Information Systems | Citations: 0

Authors: Chen, Zihan; Sun, Jingyi; Liu, Rong Emily; Mai, Feng

Abstract: Although pervasive spread of misinformation on social media platforms has becom ... Expand

Abstract: Although pervasive spread of misinformation on social media platforms has become a pressing challenge, existing platform interventions have shown limited success in curbing its dissemination. In this study, we propose a stance-aware graph neural network (stance-aware GNN) that leverages users' stances to proactively predict misinformation spread. As different user stances can form unique echo chambers, we customize four information passing paths in stance-aware GNN, while the trainable attention weights provide explainability by highlighting each structure's importance. Evaluated on a realworld dataset, stance-aware GNN outperforms benchmarks by 32.65% and exceeds advanced GNNs without user stance by over 4.69%. Furthermore, the attention weights indicate that users' opposition stances have a higher impact on their neighbors' behaviors than supportive ones, which function as social correction to halt misinformation propagation. Overall, our study provides an effective predictive model for platforms to combat misinformation, and highlights the impact of user stances in the misinformation propagation. Collapse

Topics: misinformation Twitter filter bubble social media social influence

Methods: machine learning RoBERTa experiment deep learning graph neural network

The Value of Social Media Customer Support During the Pandemic

2023 | HICSS | Citations: 0

Authors: Cheng, Huai-Tzu; Pan, Yang; Hirschheim, Rudy

Abstract: Many companies are utilizing social media as the primary avenue for customer ser ... Expand

Abstract: Many companies are utilizing social media as the primary avenue for customer service during the pandemic. However, how customers’ behaviors and interactions with customer service agents on social media are impacted by the lockdowns has not been well understood. In this study, we examine the impact of lockdowns and physical distancing on changes in customers’ behaviors, such as emotional expressions in tweets and customers’ satisfaction with social media customer service. Using a difference-in-differences research design, we find that with the lockdowns and physical distancing, customers expressed more negative emotions when tweeting the company they were having issues with. Surprisingly, compared to before the pandemic period, customers’ emotional expressions became more positive and they were more likely to express their satisfaction after interacting with customer service agents. Interestingly, our findings reveal that gender differences exist in these scenarios. We also discuss the theoretical and practical implications of these findings. Collapse

Topics: Twitter customer service social media pandemic customer satisfaction

Methods: experimental group two sample t-test with equal variance propensity score matching parametric test robustness check

Pay-for-performance schemes and hospital HIT adoption

2023 | Decision Support Systems | Citations: 0

Authors: Cheng, Ningning; Li, Hongfei; Bang, Youngsok

Abstract: Pay-for-performance (P4P) schemes are implemented to incentivize or penalize hos ... Expand

Abstract: Pay-for-performance (P4P) schemes are implemented to incentivize or penalize hospitals for their safe care­ giving. Given that health information technology (HIT) results in better healthcare outcomes, P4P schemes are expected to promote hospital HIT adoption. However, P4P schemes could also discourage hospitals from adopting HIT because they may take away resources initially allocated for HIT adoption. This paper is one of the first to empirically investigate the double-edged role of P4P schemes in HIT adoption. We leverage a natural experiment in the US healthcare system, which introduced P4P schemes in 2013. Our empirical analysis reveals an unintended side effect of P4P schemes that could potentially impede HIT adoption. We also find that P4P schemes have a negative spillover effect on nonparticipating hospitals in the same multihospital system (MHS) as participating hospitals, particularly for small nonparticipating hospitals. Our findings provide important impli­ cations for health policy design and MHS management. Collapse

Topics: health information system database system technology adoption organization learning missing data

Methods: longitudinal research experimental group natural experiment survey robustness check

The Cost of Free: The Effects of “Wait-for-Free” Pricing Schemes on the Monetization of Serialized Digital Content

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Choi, Angela; Rhee, Ki-Eun; Yoon, Chamna; Oh, Wonseok

Abstract: Leveraging a combination of analytical frameworks and empirical assessments, th ... Expand

Abstract: Leveraging a combination of analytical frameworks and empirical assessments, this study investigates the effects of wait-for-free (WFF) pricing schemes on the monetization of serialized, digital entertainment content, which has become increasingly pervasive on online platforms. WFF pricing is a strategy in which consumers are given the option to either wait a certain amount of time to acquire digital content at no cost or pay to consume it immediately. We evaluate the extent to which habit formation and presentbiased preferences driven by the consumption of addictive stock affect individual consumers' willingness to wait (or pay) for content, which, in turn, determines the efficacy of WFF pricing. We also examine the conditions under which consumers switch from waiting for free content to instantaneously purchasing content. Our findings indicate that WFF pricing increases the sales of serialized digital content, generating new demand from customers who would otherwise forgo participation in the market. In addition, the pricing design effectively generates sustained profits in the long run. We found that most consumers who initiate a purchase either upon initial market entry or upon switching continue to purchase as new episodes become available. Moreover, the results indicate that as a user accumulates free episodes of a specific series, given extended waiting periods, the likelihood of their conversion from a wait-for-free customer to an instant-purchase customer increases. In particular, WFF pricing effectively augments the willingness to pay of low-valuation consumers as habit formation builds up through time with the free consumption of serialized content. One free episode can elevate the likelihood of consumer purchase by up to 13%. However, as the number of free episodes consumed goes beyond a threshold, the likelihood of conversion decreases. We conclude with a discussion of managerial implications that can help content providers monetize their serialized digital content products. Collapse

Topics: price management consumer behavior advertising management digital good customer satisfaction

Methods: mathematical model robustness check econometric modeling proportional hazards model survival analysis

Theories: behavioral economics

Wisdom in the Wild: Generalization and Adaptive Dynamics

2023 | Organization Science | Citations: 0

Authors: Choi, Jaeho; Levinthal, Daniel

Abstract: Learning from experience is a central mechanism underlying organizational capabi ... Expand

Abstract: Learning from experience is a central mechanism underlying organizational capabilities. However, in examining how organizations learn from past experiences, much of the literature has focused on situations in which actors are facing a repeated event. We direct attention to a relatively underexamined question: when an organization experiences a largely idiosyncratic series of events, at what level of granularity should these events, and the associated actions and outcomes, be encoded? How does generalizing from experience impact the wisdom of future choices and what are the boundary conditions or factors that might mitigate the degree of desired generalization? To address these questions, we develop a computational model that incorporates how characteristics of opportunities (e.g., acquisition candidates, new investments, product development) might be encoded so that experiential learning is possible even when the organization’s experience is a series of unique events. Our results highlight the power of learning through generalization in a world of novelty as well as the features of the problem environment that reduce this “power.” Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1609. Collapse

Topics: organization learning new product development

Methods: descriptive statistic reinforcement learning robustness check literature study

Context and Aggregation: An Experimental Study of Bias and Discrimination in Organizational Decisions

2023 | Organization Science | Citations: 1

Authors: Christensen, Michael; Dahl, Christian M.; Knudsen, Thorbjørn; Warglien, Massimo

Abstract: This paper addresses a notable gap at the intersection of organizational economi ... Expand

Abstract: This paper addresses a notable gap at the intersection of organizational economics and organization science: how does organizational context influence aggregation of individual behavior in organizational decisions? Using basic centralized versus decentralized organizational structures as building blocks for our experimental design, we examine whether assignment of organizational positions, incentive schemes, and structural configuration induce endogenous adaptation in the form of change in reservation levels (bias) or modified discrimination capability in subjects’ behavior. We found that evaluators adapted their reservation and discrimination levels in centralized structures, whereas they did not generally adapt their reservation and discrimination levels when placed in decentralized structures. We identify mechanisms that explain these findings; explain how they influence aggregate, organizational behavior; and discuss implications for research and practice.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: M. Warglien acknowledges financial support from the European Union's Horizon 2020 research and innovation programme under [Grant Agreement 732942].Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1502. Collapse

Topics: organization structure organizational context decision making organizational productivity graphical user interface

Methods: experiment statistical hypothesis test experimental design theoretical contribution cluster analysis

Theories: organizational behavior theory

A Taxonomy of Violations in Digital Asset Markets

2023 | International Conference on Information Systems | Citations: 0

Authors: Clapham, Benjamin; Jakobs, Jenny; Schmidt, Julian; Gomber, Peter; Muntermann, Jan

Abstract: Numerous frauds, market manipulations and other violations have recently shaken ... Expand

Abstract: Numerous frauds, market manipulations and other violations have recently shaken investor confidence in digital asset markets and digital assets themselves. Yet, investor confidence and market integrity are key requirements for the continued success of crypto and other digital assets. In order to facilitate the integrity of digital asset markets and avoid integrity incidents in the future, a systematic overview of violations and their main characteristics is needed to develop appropriate countermeasures. Therefore, we develop a taxonomy of violations in digital asset markets and evaluate the taxonomy based on real-world cases. Our results show that many types of market manipulation in traditional financial markets can also be observed in digital asset markets. However, there are new and additional violations in digital asset markets. We also find that many violations depend on specific capabilities of the violator, certain trading conditions, and asset-specific characteristics. Collapse

Topics: IT security threat crypto wallet accounting information technology infrastructure smart contract

Methods: robustness check cluster analysis