Towards Artificial Intelligence Augmenting Facilitation: AI Affordances in Macro-Task Crowdsourcing

2023 | Group Decision and Negotiation | Citations: 0

Authors: Gimpel, Henner; Graf-Seyfried, Vanessa; Laubacher, Robert; Meindl, Oliver

Abstract: Crowdsourcing holds great potential: macro-task crowdsourcing can, for example, ... Expand

Abstract: Crowdsourcing holds great potential: macro-task crowdsourcing can, for example, contribute to work addressing climate change. Macro-task crowdsourcing aims to use the wisdom of a crowd to tackle non-trivial tasks such as wicked problems. However, macro-task crowdsourcing is labor-intensive and complex to facilitate, which limits its efficiency, effectiveness, and use. Technological advancements in artificial intelligence (AI) might overcome these limits by supporting the facilitation of crowdsourcing. However, AI’s potential for macro-task crowdsourcing facilitation needs to be better understood for this to happen. Here, we turn to affordance theory to develop this understanding. Affordances help us describe action possibilities that characterize the relationship between the facilitator and AI, within macro-task crowdsourcing. We follow a two-stage, bottom-up approach: The initial development stage is based on a structured analysis of academic literature. The subsequent validation & refinement stage includes two observed macro-task crowdsourcing initiatives and six expert interviews. From our analysis, we derive seven AI affordances that support 17 facilitation activities in macro-task crowdsourcing. We also identify specific manifestations that illustrate the affordances. Our findings increase the scholarly understanding of macro-task crowdsourcing and advance the discourse on facilitation. Further, they help practitioners identify potential ways to integrate AI into crowdsourcing facilitation. These results could improve the efficiency of facilitation activities and the effectiveness of macro-task crowdsourcing. Collapse

Topics: crowdsourcing artificial intelligence affordance user experience usability

Methods: qualitative interview literature study literature sample personal interview natural language processing

Theories: theory of affordance

Converging Tides Lift All Boats: Consensus in Evaluation Criteria Boosts Investments in Firms in Nascent Technology Sectors

2023 | Organization Science | Citations: 0

Authors: Shen, Xirong (Subrina); Li, Huisi (Jessica); Tolbert, Pamela S.

Abstract: Although previous studies show that the emergence of evaluation criteria for a n ... Expand

Abstract: Although previous studies show that the emergence of evaluation criteria for a new technology improves the life chances of well-performing firms, we theorize that consensus in such criteria among technology experts increases investments to all firms in the new sector. We provide a variety of supportive evidence for this claim. First, in an experiment with 80 Chinese investors (Study 1), we provide evidence of a causal relation between evaluation consensus and investments. We follow this with a second experiment with 412 U.S. participants (Study 2), showing that evaluation criteria consensus increases participants’ propensity to view a firm as technologically competent and to expect others to favor investing in the firm. Analyses of longitudinal archival data on investment in artificial intelligence technology firms in the United States (Study 3a) and China (Study 3b) support the generalizability of our findings. By exploring the social-cognitive processes that link evaluation criteria consensus to investors’ decisions to invest in firms in nascent technology fields, this paper advances the scholarly understanding of the microfoundations of the institutionalization processes in new market sectors.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: This work was supported by Cornell University (Innovation, Entrepreneurship, and Technology Theme Research Grant, Jeffrey S. Lehman Fund for Scholarly Exchange with China).Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1493. Collapse

Topics: evaluation criteria artificial intelligence database system decision making intellectual property

Methods: experiment hazard function archival research survey theory development

Happy to Continue: Satisfaction, Commitment, and Persistence to Use Technology-Supported Collaborative Work Practices

2022 | Group Decision and Negotiation | Citations: 0

Authors: Kocsis, David; de Vreede, Triparna; Alothaim, Abdulrahman

Abstract: This study focused on the persistent use of technology-supported collaborative w ... Expand

Abstract: This study focused on the persistent use of technology-supported collaborative work practices. Using the lenses of the technology transition model and yield shift theory of satisfaction, we examined the effects of satisfaction with process, satisfaction with outcomes, and commitment to outcomes on persistent use of a collaborative work practice. We designed and facilitated technology-supported collaborative work practice sessions with three organizations for 152 respondents. Using structural equation modeling, we found satisfaction with outcomes was an important predictor of whether individuals committed to outcomes of technology-supported collaborative sessions. Moreover, when commitment was strong, individuals tended to persist in using the collaboration technology and work practices in the future. These results can assist designers and facilitators of meetings and collaborative work practices to focus on communicating the importance of the outcomes of meetings and how these outcomes can benefit individuals and their organizations. Collapse

Topics: computer supported cooperative work collaborative work IT supported collaboration behavioral intention organizational commitment

Methods: survey SEM tool statistical hypothesis test descriptive statistic structural equation modeling

Theories: yield shift theory of satisfaction

Collaborating with Virtual Assistants in Organizations: Analyzing Social Loafing Tendencies and Responsibility Attribution

2022 | Information Systems Frontiers | Citations: 3

Authors: Stieglitz, Stefan; Mirbabaie, Milad; Möllmann, Nicholas R. J.; Rzyski, Jannik

Abstract: Organizations increasingly introduce collaborative technologies in form of virtu ... Expand

Abstract: Organizations increasingly introduce collaborative technologies in form of virtual assistants (VAs) to save valuable resources, especially when employees are assisted with work-related tasks. However, the effect of VAs on virtual teams and collaboration remains uncertain, particularly whether employees show social loafing (SL) tendencies, i.e., applying less effort for collective tasks compared to working alone. While extant research indicates that VAs collaboratively working in teams exert greater results, less is known about SL in virtual collaboration and how responsibility attribution alters. An online experiment with N = 102 was conducted in which participants were assisted by a VA in solving a task. The results indicate SL tendencies in virtual collaboration with VAs and that participants tend to cede responsibility to the VA. This study makes a first foray and extends the information systems (IS) literature by analyzing SL and responsibility attribution thus updates our knowledge on virtual collaboration with VAs. Collapse

Topics: virtual teamwork brainstorming personality team productivity IT enabled teamwork

Methods: descriptive statistic experiment survey survey design statistical power analysis

The Relationship of Collaboration Technologies and Cognition and Affect

2021 | HICSS | Citations: 0

Authors: Benke, Ivo; Heinzl, Armin; Maedche, Alexander

Abstract: Collaboration technologies (CT) are integral for today’s workplaces and the use ... Expand

Abstract: Collaboration technologies (CT) are integral for today’s workplaces and the use of CT impacts human brain and behavior. The consequences on cognition and affect of CT users have been empirically investigated since the 1970s. However, the research landscape is scattered and a comprehensive overview is missing. Consequently, we systematically analyze research about the relationship of CT and cognitive and affective user states and processes through an advanced systematic literature review based on the conceptual foundation of the time-space matrix, the stimulus-organism-response paradigm, and the workplace outcomes framework. Our results show an increase in remote CT, alongside a focus on individual analysis and affective constructs, while group level studies concentrate relatively stronger on collocated scenarios. We contribute with avenues for future research like the underrepresentation of group level analysis, a need for unified conceptualization and understanding of cognitive and affective constructs in theory and for deriving design knowledge to create advanced, cognition- and affect-sensitive CT features. Collapse

Topics: database system computer supported cooperative work social presence pandemic group support system

Methods: literature sample structured literature research qualitative coding bibliometric analysis literature study

Why Do High-Status People Have Larger Social Networks? Belief in Status-Quality Coupling as a Driver of Network-Broadening Behavior and Social Network Size

2021 | Organization Science | Citations: 0

Authors: Cao, Jiyin; Smith, Edward Bishop

Abstract: Previous research has demonstrated that the size and reach of people’s social ne ... Expand

Abstract: Previous research has demonstrated that the size and reach of people’s social networks tend to be positively related to their social status. Although several explanations help to account for this relationship—for example, higher-status people may be part of multiple social circles and therefore have more social contacts with whom to affiliate—we present a novel argument involving people’s beliefs about the relationship between status and quality, what we call status-quality coupling. Across seven separate studies, we demonstrate that the positive association between social status and network-broadening behavior (as well as social network size) is contingent on the extent to which people believe that status is a reliable indicator of quality. Across each of our studies, high- and low-status people who viewed status and quality as tightly coupled differed in their network-broadening behaviors, as well as in the size of their reported social networks. The effect was largely driven by the perceived self-value and perceived receptivity of the networking target. Such differences were significantly weaker or nonexistent among equivalently high- and low-status people who viewed status as an unreliable indicator of quality. Because the majority of participants—both high- and low-status—exhibited beliefs in status-quality coupling, we conclude that such a belief marks an important and previously unaccounted-for driver of the relationship between status, network-broadening behaviors, and social networks. Implications for research on social capital, advice seeking, and inequality are highlighted in the discussion section. Collapse

Topics: social network group support system personality online community social capital

Methods: survey meta analysis parametric test ANOVA factor analysis

Theories: big five model

Hearing the Participants’ Voice: Recognizing the Dimensions of Procedural and Interactional Justice by Enabling Their Determinants

2021 | Group Decision and Negotiation | Citations: 0

Authors: Kaur, Parmjit; Carreras, Ashley L.

Abstract: This paper examines how a deeper understanding of procedural justice and interac ... Expand

Abstract: This paper examines how a deeper understanding of procedural justice and interactional justice can enhance the effectiveness of causal mapping workshops using Group Explorer® software combined with the Decision Explorer® tool. A dual facilitation model is outlined that explicitly links the determinates of procedural justice and the key elements of interactional justice to the stages of causal mapping workshops. This model serves to illustrate how the participants’ voice in group workshops using causal mapping is strengthened, producing an authentic outcome that more accurately represents participants’ thinking. Enabling the determinants in the model supports the dimensions of procedural and interactional justice, ensuring these more authentic outcomes. A link between these determinants, dimensions and the workshop process is confirmed through qualitative and quantitative analysis. The qualitative analysis draws on causal maps created with relevant concepts/ statements, highlighted to illustrate this more authentic voice. The quantitative work analyses responses to a post-workshop questionnaire using scale reduction techniques and looks for significant relationships between participants’ voice and the determinants of procedural justice, interactional justice and the causal mapping approach adopted. Collapse

Topics: group support system anonymity group decision support system tablet laptop computer

Methods: survey data transformation action research exploratory factor analysis principal component analysis

Theories: procedural justice theory

Novel Information Discovery and Collaborative Filtering to Support Group Creativity

2020 | ACM SIGMIS Database | Citations: 0

Authors: Jenkin, Tracy A.; Skillicorn, David B.; Chan, Yolande E.

Abstract: Teams that innovate encounter challenges in divergent and convergent thinking pr ... Expand

Abstract: Teams that innovate encounter challenges in divergent and convergent thinking processes related to the need to: 1) leverage diverse internal and external knowledge, and 2) produce something that is both novel and valuable. Integrating the extant literature, we describe these challenges and propose a new approach to solving issues related to divergent and convergent thinking in groups in an innovation context. Specifically, we design group processes to support divergent and convergent thinking, including the use of several information technology (IT) tools to support them: 1) a novel-information discovery tool to foster computer-supported divergent thinking and sensemaking, and 2) a collaborative-filtering tool to foster computer-supported convergent thinking and sensegiving. Findings indicate that the novel-information discovery tool increases efficiency and effectiveness in the divergent thinking process and that the collaborative-filtering tool supports convergent thinking by focusing the group's attention on ideas that might otherwise be neglected. Combining these two IT tools with group processes for divergent and convergent thinking has important implications for both research and practice. Collapse

Topics: innovation management collaborative filtering system support organizational context group support system

Methods: group interview mixed method descriptive statistic nonparametric test case study

Machines as teammates: A research agenda on AI in team collaboration

2020 | Information & Management | Citations: 67

Authors: Seeber, Isabella; Bittner, Eva; Briggs, Robert O.; de Vreede, Triparna; de Vreede, Gert-Jan; Elkins, Aaron; Maier, Ronald; Merz, Alexander B.; Oeste-Reiß, Sarah; Randrup, Nils; Schwabe, Gerhard; Söllner, Matthias

Abstract: What if artificial intelligence (AI) machines became teammates rather than tools ... Expand

Abstract: What if artificial intelligence (AI) machines became teammates rather than tools? This paper reports on an international initiative by 65 collaboration scientists to develop a research agenda for exploring the potential risks and benefits of machines as teammates (MaT). They generated 819 research questions. A subteam of 12 converged them to a research agenda comprising three design areas – Machine artifact, Collaboration, and Institution – and 17 dualities – significant effects with the potential for benefit or harm. The MaT research agenda offers a structure and archetypal research questions to organize early thought and research in this new area of study. Collapse

Topics: artificial intelligence IT supported collaboration privacy decision making group support system

Methods: survey design artifact qualitative content analysis chatbot

Theories: socio technical theory

The Impact of Artificial Intelligence on Individual Performance: Exploring the Fit between Task, Data, and Technology

2020 | European Conference On Information Systems | Citations: 10

Authors: Sturm, Timo; Peters, Felix

Abstract: Artificial intelligence (AI) is increasingly deployed in organizations, allowin ... Expand

Abstract: Artificial intelligence (AI) is increasingly deployed in organizations, allowing information systems (IS) to incorporate self-learning mechanisms. Machine learning (ML) is commonly used as the underlying technology, as it enables IS to derive patters from collected data and perform tasks that were previously reserved for humans. While organizations hope to increase their efficiency and effectivity through adopting AI, the actual linkage between AI use and performance impacts for individuals remains largely overlooked in IS research so far. Therefore, we employ a qualitative research approach to develop a theoretical model for this relationship. In detail, we conduct expert interviews and build on the widely used "task-technology-fit" (TTF) theory. We identify relevant dimensions for the main theory constructs and expand the theory with further components to fit the AI context. Our findings enable future empirical research regarding performance impacts of AI use. Practitioners can use our model to evaluate use cases for AI adoption by considering task, data, and technology characteristics. Collapse

Topics: artificial intelligence business process management organizational context task characteristic frequency of use

Methods: qualitative interview literature study theory development triangulation theoretical contribution

Theories: theory of task technology fit