Data Sharing Frames: How Scientists Understand the Work of Sharing Scientific Data

2023 | International Conference on Information Systems | Citations: 0

Authors: Amagyei, Nana Kwame; Engesmo, Jostein; Panteli, Niki

Abstract: The curation of data is fundamental to their wider dissemination and use. This ... Expand

Abstract: The curation of data is fundamental to their wider dissemination and use. This paper investigates the frames of workers who perform data curation in scientific contexts. We view data curation as a sense-making practice, where workers collaborate to disseminate meaningful data to a broad set of prospective users. Previous Information Systems investigations have suggested that data-related activities are dependent on workers' understanding of their local work context. We expand this with an evolving and longterm view. We use a stepwise-deductive induction method to examine how scientists understand the work involved in curating scientific data for public sharing. We draw on frames as the theoretical lens of the study that enables us to identify three data sharing frames -the object, curation, and aligning frames -as important frames that shape how scientists curate data for public sharing. Our analysis provides a deeper understanding of the nuances of managing scientific data for public access. Our main contribution is the articulation of an evolving and long-term view of how workers approach their tasks in getting data ready for long-term public use. Collapse

Topics: data management Python data governance datafication strategic management

Methods: survey qualitative interview personal interview field study theoretical contribution

Sustainable IS Use: What IS Needed to REDUSE

2023 | International Conference on Information Systems | Citations: 0

Authors: Andraschko, Lars; Wunderlich, Philipp; Sarker, Saonee; Veit, Daniel

Abstract: Facing ever-looming climate change, studying the drivers for individuals ' Info ... Expand

Abstract: Facing ever-looming climate change, studying the drivers for individuals ' Information Systems (IS) Use to reduce environmental harm gains momentum. While extant research on the antecedents of sustainable IS Use has focused on specific theories, interventions, contexts, and technologies, a holistic understanding has become increasingly elusive, with a synthesis remaining absent. We employ a systematic literature review methodology to shed light on the driving antecedents for sustainable IS Use among individual consumers. Our results build on findings of 29 empirical studies drawn from 598 articles retrieved from our premier outlets and a forward/backward search. The analysis reveals six salient complementary antecedents: Relief, Empowerment, Default, User-centricity, Salience, and Encouragement. We recommend considering these concepts when developing, deploying, promoting, or regulating digital technologies to mitigate individual consumers' emissions. Along with memorable and implementable concepts, our theoretical framework offers a novel conceptualization and four promising avenues for researchers on sustainable IS Use. Collapse

Topics: information system use green IS electronic commerce individual characteristic willingness to pay

Methods: structured literature research synthesis theory development laboratory experiment field experiment

Theories: extended unified theory of acceptance and use of technology information systems theory unified theory of acceptance and use of technology

Text-image Relationships in Social Media Communication: A Literature Review

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Bai, Shiqi; Li, Boying; Phang, Chee Wei (David)

Abstract: This study synthesises the literature on content factors in social media commun ... Expand

Abstract: This study synthesises the literature on content factors in social media communication within the Information Systems (IS) field and identifies five dimensions of text-image congruence: quality congruence, quantity congruence, emotion congruence, connotation congruence, and information appeal. Utilizing the S-O-R framework, we provide a comprehensive understanding of text-image congruence and suggest future research directions in IS. Our findings contribute to the knowledge of effective social media communication strategies and lay the groundwork for future research on text-image congruence and relationships. Collapse

Topics: social media electronic commerce artificial intelligence sensemaking IS discipline

Methods: literature study qualitative coding literature sample grounded theory theory development

Employing Machine Learning to Advance Agent-based Modeling in Information Systems Research

2023 | International Conference on Information Systems | Citations: 0

Authors: Bashardoust, Amirsiavosh; Safaei, Negin; Haki, Kazem; Shrestha, Yash Raj

Abstract: ... Expand

Abstract: Collapse

Topics: sensemaking Python organizational context innovation management business-to-business

Methods: sensitivity analysis theory development simulation robustness check artificial neural network

Theories: sociotechnical systems theory

Expl(AI)ned: The Impact of Explainable Artificial Intelligence on Users’ Information Processing

2023 | Information Systems Research | Citations: 0

Authors: Bauer, Kevin; von Zahn, Moritz; Hinz, Oliver

Abstract: Because of a growing number of initiatives and regulations, predictions of moder ... Expand

Abstract: Because of a growing number of initiatives and regulations, predictions of modern artificial intelligence (AI) systems increasingly come with explanations about why they behave the way they do. In this paper, we explore the impact of feature-based explanations on users’ information processing. We designed two complementary empirical studies where participants either made incentivized decisions on their own, with the aid of opaque predictions, or with explained predictions. In Study 1, laypeople engaged in the deliberately abstract investment game task. In Study 2, experts from the real estate industry estimated listing prices for real German apartments. Our results indicate that the provision of feature-based explanations paves the way for AI systems to reshape users’ sense making of information and understanding of the world around them. Specifically, explanations change users’ situational weighting of available information and evoke mental model adjustments. Crucially, mental model adjustments are subject to the confirmation bias so that misconceptions can persist and even accumulate, possibly leading to suboptimal or biased decisions. Additionally, mental model adjustments create spillover effects that alter user behavior in related yet disparate domains. Overall, this paper provides important insights into potential downstream consequences of the broad employment of modern explainable AI methods. In particular, side effects of mental model adjustments present a potential risk of manipulating user behavior, promoting discriminatory inclinations, and increasing noise in decision making. Our findings may inform the refinement of current efforts of companies building AI systems and regulators that aim to mitigate problems associated with the black-box nature of many modern AI systems. History: Alessandro Acquisti, senior editor; Jason Chan, associate editor. Funding: This work was supported by the Deutsche Forschungsgemeinschaft (DFG) (Projek 449023539), Volkswagen Foundation (ML2MT), and LeibnizInstitute for Financial Research SAFE. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2023.1199. Collapse

Topics: explainable artificial intelligence artificial intelligence shapley additive explanation local interpretable model agnostic explanation decision making

Methods: F-test regression analysis method experiment field study robustness check

USING ALGORITHMIC NUDGES TO SAVE ENERGY AND WATER: A PROPOSAL FOR A LONGITUDINAL FIELD EXPERIMENT

2023 | European Conference On Information Systems | Citations: 0

Authors: Beermann, Vincent; Rieder, Annamina

Abstract: Energy and water consumption are significant sources of greenhouse gas emission ... Expand

Abstract: Energy and water consumption are significant sources of greenhouse gas emissions. While facilitating conservation behaviors in private households can help to mitigate these emissions, the effects of such mitigations are often indirect and delayed. Presenting meaningful feedback about consumption can help to make clear the positive effects of conservation behaviors to those who undertake them. We propose a large-scale field experiment to increase energy and water conservation through algorithmic econudges. We use smart metering data to provide transparency, social references, and information about the environmental effects of conservation behavior. The proposed research is planned in a longitudinal design for 8 weeks in the winter of 2022/23 in Germany. The findings are expected to contribute to scholarly research on nudging and practice as well as to housing providers and policymakers who are interested in green nudging. Collapse

Topics: sensemaking mobile application user interface usability smart metering

Methods: experiment computational algorithm field experiment longitudinal research experimental group

Incorporating evolutionary adaptions into the cognitive fit model for data visualization

2023 | Decision Support Systems | Citations: 0

Authors: Bina, Saman; Kaskela, Timothy; Jones, Donald R.; Walden, Eric; Graue, William B.

Abstract: With the proliferation of data has arisen an array of information visualization ... Expand

Abstract: With the proliferation of data has arisen an array of information visualization tools to help humans convert data to information for better decision-making. This ever-expanding visualization toolset has outrun the development of theories of data visualization usage for decision support. In the current research, we contribute to the development of visualization theories in two ways. First, we incorporate our understanding of evolutionary adaptations into the cognitive fit theory to explain why 3-D surface graphs often outperform traditional 2-D graphs in various sensemaking tasks. Drawing on geon theory to interpret the 3-D advantage, we develop the concept of geonic/non-geonic information representations and tasks. We tested and found support for our hy­ potheses that geonic representations have a speed advantage for the tasks we studied, derived from the human evolved capacity for geographic orienteering, but accuracy depends on the match of representation and task, as geonic or non-geonic. Our experiment compared the geonic representation (3-D surface graph) to non-geonic planar representations (cluster bar, heat map, and line) in geonic (integration, proportion) and non-geonic atomic (acquisition, comparison) tasks. For our second contribution, we build on this result to expand the cognitive fit model to incorporate classic human information processes and evolutionary adaptations. We suggest that the cognitive fit model can expand to include new advances in neuroscience. We discuss the theoretical and practical implications of our experiment and our expanded model. Collapse

Topics: data visualization sensemaking decision making spreadsheet Python

Methods: experiment parametric test ANOVA exploratory data analysis descriptive statistic

Theories: cognitive fit theory

The aestheticization of business processes: Visualizing their Gestalt for collective thinking

2023 | Journal of Information Technology | Citations: 0

Authors: Blattmeier, Monika

Abstract: Business processes, simply defined by Davenport as ‘structures for action’, orga ... Expand

Abstract: Business processes, simply defined by Davenport as ‘structures for action’, organize the creation of value in a company. In addition to being carried out visibly, processes also have an inner dimension which remains hidden in the existing mechanistic metaphor of process management models. Aesthetic business processes draw from systems theory and Gestalt theory in order to uncover this inner dimension. The aim of this phenomenological investigation presented here is to describe the super-summative nature of business processes, in other words, to understand them holistically as a Gestalt. Mechanical Engineering students at a university of applied sciences analyzed business processes at different companies to discover patterns which they then visualized with the process participants at those companies. They used Christopher Alexander’s pattern language as a paradigm to make implicit knowledge buried in those business processes explicit. Using this technique, aesthetic business processes were identified as patterns. The format of the patterns served as a tool for collective thinking and as a form of expression for the Gestalt of aesthetic business processes in their visualization. A pattern language as an overview of the many ways to combine business process patterns has yet to be reconstructed based on this investigation. The shared visualizations highlighted the nature of the business processes and made it possible to see, in a metaphorical way, their significant interactions. Collapse

Topics: business process management sensemaking manufacturing information system covid 19 pandemic

Methods: theory development qualitative interview experiment phenomenological method case study

Theories: gestalt principles of perception general systems theory

Doing good by going digital: A taxonomy of digital social innovation in the context of incumbents

2023 | Journal of Strategic Information Systems | Citations: 0

Authors: Buck, Christoph; Krombacher, Anna; Röglinger, Maximilian; Körner-Wyrtki, Katrin

Abstract: Digital social innovation (DSI) offers incumbents a strategic field of action to ... Expand

Abstract: Digital social innovation (DSI) offers incumbents a strategic field of action to leverage the op­ portunities of digital technologies to address pressing societal challenges. By proposing a tax­ onomy and 12 clusters of incumbents’ DSI initiatives based on a sample of 296 real-world objects, we develop a unified understanding of DSI and its characteristics. This lays the foundation for further theorising on DSI from an incumbent perspective and for researchers to shape the DSI field. The taxonomy provides incumbents with an orientation to realise DSI’s rich strategic po­ tentials throughout the DSI ideation process and in assessing DSI types. Collapse

Topics: innovation management societal challenge database system value creation digital innovation

Methods: literature sample cluster analysis agglomerative hierarchical clustering structured literature research theory development

Theories: information systems theory

Algorithmic Management: Its Implications for Information Systems Research

2023 | Communications of the Association for Information Systems | Citations: 4

Authors: Cameron, Lindsey; Lamers, Laura; Leicht-Deobald, Ulrich; Lutz, Christoph; Meijerink, Jeroen; Möhlmann, Mareike

Abstract: In recent years, the topic of algorithmic management has received increasing at ... Expand

Abstract: In recent years, the topic of algorithmic management has received increasing attention in information systems (IS) research and beyond. As both emerging platform businesses and established companies rely on artificial intelligence and sophisticated software to automate tasks previously done by managers, important organizational, social, and ethical questions emerge. However, a cross-disciplinary approach to algorithmic management that brings together IS perspectives with other (sub-)disciplines such as macro-and micro-organizational behavior, business ethics, and digital sociology is missing, despite its usefulness for IS research. This article engages in cross-disciplinary agenda setting through an in-depth report of a professional development workshop (PDW) entitled "Algorithmic Management: Toward a Cross-Disciplinary Research Agenda" delivered at the 2021 Academy of Management Annual Meeting. Three leading experts (Mareike Möhlmann, Lindsey Cameron, and Laura Lamers) on the topic provide their insights on the current status of algorithmic management research, how their work contributes to this area, where the field is heading in the future, and what important questions should be answered going forward. These accounts are followed up by insights from the breakout group discussions at the PDW that provided further input. Overall, the experts and workshop participants emphasized that future research should examine both the desirable and undesirable outcomes of algorithmic management and should not shy away from posing ethical and normative questions. Collapse

Topics: algorithmic management sensemaking platform worker Uber pandemic

Methods: computational algorithm theory development group interview ethnography grounded theory

Theories: organizational behavior theory enactment theory