Esports, Digital Professionals, and Higher Education: An Autoethnography of an Administrator’s Experience with Liminality

2023 | International Conference on Information Systems | Citations: 0

Authors: Ammeter, Tony; Jarvenpaa, Sirkka

Abstract: Professional identity is a means for continued livelihood and, in this digitizi ... Expand

Abstract: Professional identity is a means for continued livelihood and, in this digitizing world, is in constant flux. Constantly changing occupational roles and professional classes are liminal, that is, they are increasingly "betwixt and between" formerly legitimized, stable categories. If, as current writings on the future of work suggest, a need for liminality in work identities persists, how will institutions of higher education help their students acquire "permanent" liminality? Through the eyes of an administrator at a mid-sized higher education institution, we examine how a university creates a new learning environment under the umbrella of esports. The findings raise questions about digital transitions in higher education and about liminality and the future of work by highlighting esports as a liminal category. The study contributes to the literature on the future of work by offering insights into higher education challenges to "institutionalize" liminality and to prepare future digital professionals. Collapse

Topics: esport IT workforce evaluation criteria electronic mail

Methods: qualitative interview triangulation

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

Sensing the Future: A Design Framework for Context-Aware Predictive Systems

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

Authors: Avital, Michel; Chatterjee, Samir; Furtak, Szymon

Abstract: Sensors embedded in smart objects, smart machines, and smart buildings produce ... Expand

Abstract: Sensors embedded in smart objects, smart machines, and smart buildings produce ever-growing streams of contextual data that convey information of interest about their operating environment. Although an increasing number of industries have embraced the utilization of sensors in routine operations, no clear framework is available to guide designers who aim to leverage contextual data collected from these sensors to develop predictive systems. In this paper, we applied design science research methodology to develop and evaluate a general framework that can help designers build predictive systems utilizing sensor data. Specifically, we developed a framework for designing context-aware predictive systems (CAPS). We then evaluated the framework through its application in MAN Diesel & Turbo, which served as a case company. The framework can be generalized into a class of demand-forecasting problems that rely on sensor-generated contextual data. The CAPS framework is unique and can help practitioners make better-informed decisions when designing context-aware predictive systems. Collapse

Topics: data quality evaluation criteria knowledge base systems design systems development

Methods: machine learning design science design artifact data transformation design process

What Makes Digital Technology? A Categorization Based on Purpose

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

Authors: Baier, Marie-Sophie; Berger, Stephan; Kreuzer, Thomas; Oberländer, Anna; Röglinger, Maximilian

Abstract: Digital technology (DT) is creating and shaping today's world. Building on its ... Expand

Abstract: Digital technology (DT) is creating and shaping today's world. Building on its identity and history of technology research, the Information Systems discipline is at the forefront of understanding the nature of DT and related phenomena. Understanding the nature of DT requires understanding its purposes. Because of the growing number of DTs, these purposes are diversifying, and further examination is needed. To that end, we followed an organizational systematics paradigm and present a taxonomic theory for DT that enables its classification through its diverse purposes. The taxonomic theory comprises a multi-layer taxonomy of DT and purpose-related archetypes, which we inferred from a sample of 92 real-world DTs. In our empirical evaluation, we assessed the reliability, validity, and usefulness of the taxonomy and archetypes. The taxonomic theory exceeds existing technology classifications by being the first that (1) has been rigorously developed, (2) considers the nature of DT, (3) is sufficiently concrete to reflect the diverse purposes of DT, and (4) is sufficiently abstract to be persistent. Our findings add to the descriptive knowledge on DT, advance our understanding of the diverse purposes of DT, and lay the ground for further theorizing. Our work also supports practitioners in managing and designing DTs. Collapse

Topics: knowledge base perceived usefulness competitive advantage decision making technology adoption

Methods: cluster analysis theory development longitudinal data analysis focus group computational algorithm

Theories: information systems theory sociomaterialism theory

Applying Random Forests in Federated Learning: A Synthesis of Aggregation Techniques

2023 | International Conference on Business Informatics | Citations: 0

Authors: Bodynek, Mattis; Leiser, Florian; Thiebes, Scott; Sunyaev, Ali

Abstract: ... Expand

Abstract: Collapse

Topics: privacy decision making evaluation criteria

Methods: literature study decision tree classification structured literature research

Organizing Entrepreneurial Teams: A Field Experiment on Autonomy over Choosing Teams and Ideas

2023 | Organization Science | Citations: 1

Authors: Boss, Viktoria; Dahlander, Linus; Ihl, Christoph; Jayaraman, Rajshri

Abstract: Scholars have suggested that autonomy can lead to better entrepreneurial team pe ... Expand

Abstract: Scholars have suggested that autonomy can lead to better entrepreneurial team performance. Yet, there are different types of autonomy, and they come at a cost. We shed light on whether two fundamental organizational design choices—granting teams autonomy to (1) choose project ideas to work on and (2) choose team members to work with—affect performance. We run a field experiment involving 939 students in a lean startup entrepreneurship course over 11 weeks. The aim is to disentangle the separate and joint effects of granting autonomy over choosing teams and choosing ideas compared with a baseline treatment with preassigned ideas and team members. We find that teams with autonomy over choosing either ideas or team members outperform teams in the baseline treatment as measured by pitch deck performance. The effect of choosing ideas is significantly stronger than the effect of choosing teams. However, the performance gains vanish for teams that are granted full autonomy over choosing both ideas and teams. This suggests the two forms of autonomy are substitutes. Causal mediation analysis reveals that the main effects of choosing ideas or teams can be partly explained by a better match of ideas with team members’ interests and prior network contacts among team members, respectively. Although homophily and lack of team diversity cannot explain the performance drop among teams with full autonomy, our results suggest that self-selected teams fall prey to overconfidence and complacency too early to fully exploit the potential of their chosen idea. We discuss the implications of these findings for research on organizational design, autonomy, and innovation.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: The authors are grateful for funding from the Innovation Growth Laboratory, the Peter Curtius Foundation, and the Deutsche Forschungsgemeinschaft [Grant CRC TRR 190].Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1520. Collapse

Topics: team productivity entrepreneurship missing data intrinsic motivation evaluation criteria

Methods: experiment experimental group survey causal mediation analysis field experiment

Too Good to Be True? An Empirical Study of ChatGPT Capabilities for Academic Writing and Implications for Academic Misconduct

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Busch, Peter André; Hausvik, Geir Inge

Abstract: This study evaluated the capabilities of ChatGPT, a conversational artificial i ... Expand

Abstract: This study evaluated the capabilities of ChatGPT, a conversational artificial intelligence (AI) agent, to generate quality answers to exam questions that are indistinguishable from human-generated text, normally requiring high-level cognitive abilities. This potential capacity is a major threat to academic integrity since ChatGPT may be used for academic misconduct. To determine its capabilities, we asked 15 faculty members to assess a total of ten answers (two each) to an actual IS exam question, of which students wrote five, and ChatGPT generated five. The study found that ChatGPT can generate answers of generally good quality that may pass as human-written text by examiners. The contributions of the study lay in providing empirical results in a novel research area, providing recommendations for teachers, and suggesting ways forward for research. Collapse

Topics: artificial intelligence smartphone evaluation criteria smartphone addiction mobile system

Methods: chatGPT machine learning descriptive statistic correlation analysis personal interview

Divergent Innovation: Directing the Wisdom of Crowd to Tackle Societal Challenges

2023 | International Conference on Information Systems | Citations: 0

Authors: Cao, Chuhan; Zhu, Jiantao; Xiong, Bingqing; Lim, Eric; Liu, Hefu; Cai, Zhao; Tan, Chee-Wee

Abstract: Crowdsourcing is acknowledged as a promising avenue for addressing societal cha ... Expand

Abstract: Crowdsourcing is acknowledged as a promising avenue for addressing societal challenges by drawing on the wisdom of the crowd to offer diverse solutions to complex problems. Advancing a new conceptual framework of 'divergent innovation' which delineates between topic and quality divergence as focal metrics of performance when crowdsourcing for solutions to societal challenges, this study investigates the impacts of four ideation stimuli on divergent innovation. These four stimuli include task description concreteness, resource richness, topic entropy, and judging criteria comprehensiveness. Empirical analysis based on data sourced from an online crowd-ideation platform reveals that task description concreteness negatively affects topic divergence but positively influences quality divergence, whereas resource richness positively affects topic divergence but negatively influences quality divergence. Additionally, the relationship between topic entropy and topic divergence is U-shaped, with no significant impact on quality divergence. These findings contribute to extant literature on crowdsourcing and offer invaluable insights for practitioners. Collapse

Topics: innovation management societal challenge crowdsourcing evaluation criteria media richness

Methods: BERT literature study statistical hypothesis test regression analysis method language model

Prediction of hotel booking cancellations: Integration of machine learning and probability model based on interpretable feature interaction

2023 | Decision Support Systems | Citations: 0

Authors: Chen, Shuixia; Ngai, Eric W.T.; Ku, Yaoyao; Xu, Zeshui; Gou, Xunjie; Zhang, Chenxi

Abstract: Reliable hotel cancellation prediction can help establish appropriate operationa ... Expand

Abstract: Reliable hotel cancellation prediction can help establish appropriate operational strategies for hotel manage­ ment. In this sector, personal name records (PNR) data may be the most representative information source for prediction tasks. Despite the popularity of PNR, its inherent lack of availability has been commonly disregarded in the literature. Existing studies have directly input PNR into high-dimensional machine learning (ML) models to achieve cancellation predictions. Another type of model generates cancellation prediction based on the proba­ bility modeling of samples. In this study, we propose an interpretable feature interaction method to enrich the existing PNR information. Thereafter, we empirically assess the prediction performance of the two model classes. This study specifically determines whether or not the two methods can cross-fertilize each other to improve cancellation prediction. To do so, we propose a model integrating Bayesian networks (BNs) and Lasso regression for this prediction task. This study utilizes BNs for the probability model consistent with our correlated variables and dichotomous prediction setting. Moreover, we use a linear ML model (i.e., Lasso regression), given its ad­ vantages in reducing ineffective predictors and transparency for ranking feature importance. Empirical results show that the proposed integration model has better prediction performance, and the obtained BN estimators and interactive features are the most important predictors. This study contributes to the booking cancellation liter­ ature by proposing an interpretable feature interaction and a prediction method integrating two types of effective models. The obtained accurate and interpretable cancellation prediction further contributes to offering practical implications to hoteliers in managerial decision-making. Collapse

Topics: missing data decision making competitive advantage price management marketing management

Methods: lasso regression experiment computational algorithm robustness check parametric test

Design Principles for Blockchain-based Applications in Green Bond Reporting

2023 | HICSS | Citations: 0

Authors: Darwish, Ameera; Lindman, Juho; Hjertqvist, Jesper; Tona, Olgerta

Abstract: Emerging sustainable capital markets are crucial in reaching global climate goal ... Expand

Abstract: Emerging sustainable capital markets are crucial in reaching global climate goals. These markets’ credibility depends on the trustworthiness of data used to report the green impact of projects financed by sustainable financial instruments such as green bonds. To ensure credibility and thereby support these types of markets, the information systems field has the potential to create designs that leverage emerging technologies (in our case, blockchain) for green bond reporting. In this paper, we employ a design science research method to derive a set of design principles. These design principles discuss the most relevant blockchain concepts and reflect the characteristics of today’s green bond process. Through an artificial evaluation and demonstration of the design principles, we report on how to make informed design decisions to develop blockchain applications for green bond reporting. These findings are also significant for practitioners to develop new services or re-design current processes. Collapse

Topics: blockchain usability video conference task productivity evaluation criteria

Methods: design principle qualitative interview design science literature study personal interview