Individual Versus Group Negotiation in Multiparty Systems: The Effect of Power and Goal Difficulty on Negotiation Outcomes in a Potential Gain Task

2023 | Group Decision and Negotiation | Citations: 0

Authors: Trif, Sabina Ramona; Curșeu, Petru Lucian; Fodor, Oana Cătălina

Abstract: The aim of the present study was to test the extent to which groups manage to at ... Expand

Abstract: The aim of the present study was to test the extent to which groups manage to attain synergy (both strong and weak) in the context of multiparty systems. We also aimed to test the effects of power (budget size), and goal difficulty, alongside their interaction effect. We have used a behavioral multiparty simulation in which Romanian participants first negotiated individually and then, in the second stage, they were organized into groups and asked to engage in intergroup negotiations. Results showed that, in general, best negotiators outperform groups, yet groups obtain higher negotiation payoffs than the average payoff obtained by their members in the first negotiation stage, but only for dyads. Moreover, powerful stakeholders and those that have high goals end up with the highest payoff. Last, our results show that power accentuates the positive relationship between goal difficulty and payoffs. The results have important implications for delegating representatives to multiparty negotiations and for the management of power asymmetry in multiparty systems. Collapse

Topics: negotiation support system individual characteristic information exchange task structure

Methods: simulation longitudinal research analysis of covariance within subject experiment multivariate analysis of variance

Theories: goal setting theory motivation theory

Managing the Double Bind: Women Directors’ Participation Tactics in the Gendered Boardroom

2023 | Organization Science | Citations: 0

Authors: Trzebiatowski, Tiffany; McCluney, Courtney; Hernandez, Morela

Abstract: Women leaders who fail to manage the double bind by displaying both warmth and c ... Expand

Abstract: Women leaders who fail to manage the double bind by displaying both warmth and competence can face backlash, creating pressure for women to invest thought, time, and effort into their self-presentation. Research to date lacks theoretical insights around how women in the highest levels of leadership manage the double bind in natural settings. Our inductive study of interviews with 43 women directors on U.S. publicly traded company boards offers an insider’s perspective of participation tactics that women use to manage the double bind in male-dominated contexts. We found two features unique to advisory roles—a requirement that advisors possess a large breadth of knowledge and a time constraint whereby advisors meet less frequently with their peers—that suggest women directors adapt and learn how to participate on gendered boards. We uncovered six gendered participation tactics that mitigate stereotypical concerns for women to appear warm and/or competent on boards. We further reveal how women directors selectively use specific gendered participation tactics over others to effectively achieve their participation aims, which, in turn, helps them avoid backlash for mismanaging the double bind. Finally, we find that this matching process is constrained by the amount and scope of use related to the unique features of the advisory role. The emergence and trade-offs between the use of these novel gendered participation tactics deepen our theoretical understanding of women’s participation in advisory roles. Supplemental Material: The e-companion is available at https://doi.org/10.1287/orsc.2022.1599. Collapse

Topics: IT career video conference corporate governance organization structure accounting

Methods: qualitative interview theory development company material case study

How Would Individuals Like to Use AI-Enabled Applications? An Empirical Study Based on HCI Framework

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Tu, Cindy Zhiling; Zhao, Gary Yu; Adkins, Joni

Abstract: The market of AI-enabled applications is growing fast and AI-enabled applicatio ... Expand

Abstract: The market of AI-enabled applications is growing fast and AI-enabled application has become a regular part of people's daily lives. Applying the Human-Computer Interaction (HCI) framework, this research attempts to study how likely people would accept using AI-enabled applications and what factors affect individual decisions. An empirical study is conducted through an online survey and tested using a PLS-SEM model. Results show that User characteristics, AI-enabled application characteristics, user interaction, trust, and task-technology fit are the factors that affect users' intention to use AI-enabled applications. Theoretically, this study improves the understanding of how the unique characteristics of AI-enabled applications affect users' acceptance of AI-enabled applications. Practically, the findings of this study can enhance the comprehension of individual users' application usage patterns for developers of AI-powered applications. Collapse

Topics: artificial intelligence usage intention usability human computer interaction technology adoption

Methods: survey partial least squares regression literature study confirmatory factor analysis data transformation

Theories: theory of task technology fit human-computer interaction theory

A Framework for Socio-Developmental Ethics in Educational AI

2023 | HICSS | Citations: 0

Authors: Tuomi, Ilkka

Abstract: In recent years there have been many attempts to create ethical frameworks for A ... Expand

Abstract: In recent years there have been many attempts to create ethical frameworks for AI. Theoretical concepts, such as privacy, fairness, transparency, explainability, responsibility, risk, and trustworthiness have been used as key elements in these frameworks. The use of these concepts is often justified by their wide use in similar frameworks and guidelines but does not seem to result from any coherent shared theoretical foundation. Educational and developmental theories and research have so far had little impact on ethical debates but become important when AI is used in education and learning (AIEd). A socio-developmental view on ethics naturally emerges in the educational context, and the paper shows that it has important implications also beyond the education sector. This paper describes an ethical framework structured in three thematic domains: agency, social fairness, and justified choice, that links AI with theories of education and human development, opening new ways to understand ethics of AI and the social and technical challenges and opportunities in AIEd. Collapse

Topics: artificial intelligence knowledge creation responsible artificial intelligence innovation management systems design

Introduction to Smart Mobility Ecosystems and Services Minitrack

2023 | HICSS | Citations: 0

Authors: Tuunainen, V.; Lindman, J.; Rossi, M.

Abstract: ... Expand

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Methods: literature sample personal interview case study

Introduction to the Digital Services and Service Digitalization Minitrack

2023 | HICSS | Citations: 0

Authors: Tuunanen, T.; Böhmann, T.; Leimeister, J.

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Topics: value creation willingness to pay innovation management business process innovation decentralized finance

Methods: conjoint analysis design methodology

Theories: service-dominant logic

A Social Network Approach for Investigating Social Influences on Effective Use: Demonstration in Virtual Reality Collaboration

2023 | International Conference on Information Systems | Citations: 0

Authors: Tölle, Laura; Slawinski, Elena; Fromm, Jennifer; Mirbabaie, Milad

Abstract: Merely using new collaboration technologies does not necessarily result in the ... Expand

Abstract: Merely using new collaboration technologies does not necessarily result in the desired benefits, which is why it is important to understand what constitutes effective use behavior. In information systems research, the affordance network approach has been developed as a methodological approach to investigate effective use behavior. The approach has already been applied to understand the effective use of electronic medical record systems and fitness wearables; however, it neglects how social influences foster or hinder effective use behavior in collaborative settings. Therefore, we supplemented the affordance network approach for collaborative contexts by using social network methods. We demonstrate our approach based on two university courses in which students carried out group work within the collaborative VR application Spatial. Thereby, we contribute a methodological approach that enables researchers to identify influential users who encourage their team members to actualize affordances leading to goal achievement.With respect to collaboration technologies, social influences are an important factor to consider as they have been found to predict the actual use of collaboration systems (Olschewski et al., 2013). However, simply using collaborative technology is not sufficient to achieve the desired collaboration goals (Seddon, 1997). Instead, information system (IS) research emphasizes the importance of effective use in achieving usage goals (Burton-Jones & Grange, 2013). Burton-Jones and Volkoff (2017) proposed the affordance network approach as a means to examine effective use, which visualizes effective use as a network of realized action potentials (so-called affordance actualizations) and their associated immediate outcomes. This approach is suitable to identify a sequence of affordance actualizations that are critical to achieve desired outcomes. However, the affordance network approach does not consider that specific users might encourage or hinder their team members at effective affordance actualization, thus providing an incomplete picture of effective use behavior in collaborative settings. Furthermore, the sequential nature of the affordance network approach does not reflect the reality of affordance actualizations in collaborative settings, as multiple users may actualize several affordances simultaneously or jointly. As a result, the affordance network approach is less suited for investigating effective use of collaboration technologies such as collaborative VR systems. As stated by Eckhardt et al. (2010), research still lacks a sufficient investigation of the influence of social environments on technology usage. Olschewski et al. (2013) find in a pretest of the Technology Acceptance Model for Collaboration Technology, that social influence is an important factor in collaboration technology adoption, since collaboration technologies are designed to be used jointly with other members and not individually (Brown et al., 2010). Following the work by Blascovich (2002), we seek to understand how social influence effects facilitate immersive virtual environments. Hence, our research goal was to supplement the affordance network approach for collaborative contexts using a social network approach. Thus, we ask the following research question: RQ: How can the affordance network approach be advanced to investigate effective use behavior in collaborative settings? Collapse

Topics: social influence affordance virtual reality usability user experience

Methods: qualitative interview qualitative content analysis social network analysis theoretical contribution qualitativ observational study

Theories: theory of affordance

TECHNOLOGY FOR KNOWLEDGE WORK: A RELATIONAL PERSPECTIVE

2023 | European Conference On Information Systems | Citations: 0

Authors: Ulfsnes, Rasmus; Mikalsen, Marius; Sporsem, Tor; Hatling, Morten

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Topics: knowledge work artificial intelligence information system use

Methods: case study ethnography survey qualitative interview design artifact

Software Components and Product Variety in a Platform Ecosystem: A Dynamic Network Analysis of WordPress

2023 | Information Systems Research | Citations: 0

Authors: Um, Sungyong; Zhang, Bin; Wattal, Sunil; Yoo, Youngjin

Abstract: Software components, such as application programming interfaces (APIs), provided ... Expand

Abstract: Software components, such as application programming interfaces (APIs), provided by both the platform owner and external developers in a platform ecosystem are vital to online digital platforms. These APIs are associated with functionality provided by the platform. A larger number of APIs used is generally associated with an increase in the platform ecosystem’s variety of products. However, the precise nature of the relationship between the use of APIs and product variety in a platform ecosystem is not yet known because of the lack of appropriate methodologies to analyze the complex data generated in such platform ecosystems. Drawing on a recombinatorial design perspective, we use a dynamic network model to create metrics for product variety in a digital ecosystem and study how the use of different types of APIs affects product variety. In particular, we theorize that, contrary to existing models, the structure of APIs in a large platform ecosystem is not limited to a core–periphery structure, but includes an additional third layer that we refer to as the regular core. We further hypothesize that external APIs in the regular core play a crucial role in increasing product variety in the ecosystem. To test our hypothesis, we conduct an empirical study using longitudinal data of all available digital product (i.e., plug-in) source codes on WordPress.org, the world’s largest content management system and one of the most extensive digital platform ecosystems. By analyzing all of the plug-ins on WordPress over 10 years from its inception, we find the support of our three-layer structure of APIs in a platform ecosystem: complete core, regular core, and periphery. Our empirical analysis further supports the role of external APIs in the regular core in increasing product variety. We, however, find that the strength of this effect diminishes in a newly created product category. History: Param Singh, Senior Editor; Pallab Sanyal, Associate Editor. Funding: This work was supported by the Ministry of Education Singapore [Grants R-253-000-122-133 and T1-251RES1916], the National Science Foundation [Grants 1261977 and 1120966], and Club Informatique des Grandes Entreprises Françaises. Supplemental Material: The e-companion is available at https://doi.org/10.1287/isre.2022.1172. Collapse

Topics: application programming interface digital ecosystem digital product innovation management website

Methods: doc2vec hierarchical clustering longitudinal research cluster analysis chi squared test

Don’t Need All Eggs in One Basket: Reconstructing Composite Embeddings of Customers from Individual-Domain Embeddings

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

Authors: Unger, Moshe; Li, Pan; Sen, Sahana (Shahana); Tuzhilin, Alexander

Abstract: Although building a 360-degree comprehensive view of a customer has been a long- ... Expand

Abstract: Although building a 360-degree comprehensive view of a customer has been a long-standing goal in marketing, this challenge has not been successfully addressed in many marketing applications because fractured customer data stored across different “silos” are hard to integrate under “one roof” for several reasons. Instead of integrating customer data, in this article we propose to integrate several domain-specific partial customer views into one consolidated or composite customer profile using a Deep Learning-based method that is theoretically grounded in Kolmogorov’s Mapping Neural Network Existence Theorem. Furthermore, our method needs to securely access domain-specific or siloed customer data only once for building the initial customer embeddings. We conduct extensive studies on two industrial applications to demonstrate that our method effectively reconstructs stable composite customer embeddings that constitute strong approximations of the ground-truth composite embeddings obtained from integrating the siloed raw customer data. Moreover, we show that these data-security preserving reconstructed composite embeddings not only perform as well as the original ground-truth embeddings but significantly outperform partial embeddings and state-of-the-art baselines in recommendation and consumer preference prediction tasks. Collapse

Topics: recommender system data security collaborative filtering marketing management Google+

Methods: BERT artificial neural network survey experiment machine learning