Sustainability Teaching and Learning in Information Systems: Reflections on Over a Decade of Experience

2023 | Communications of the Association for Information Systems | Citations: 2

Authors: Corbett, Jacqueline

Abstract: Despite calls to integrate sustainability topics into information systems (IS) ... Expand

Abstract: Despite calls to integrate sustainability topics into information systems (IS) curricula, there is little concrete direction on how to do it. The purpose of this paper is to share the author's experience in developing and delivering a master's level course on information systems and sustainable development. The paper highlights key considerations related to designing such a course, discusses the advantages and limitations of different approaches, and offers practical suggestions for IS faculty who seek to develop similar courses for their own programs. Collapse

Topics: environmental sustainability artificial intelligence IS management green IS

Methods: simulation case study

Appreciating the Performance of Neuroscience Mining in NeuroIS Research: A Case Study on Consumer's Product Perceptions in the Two UI Modes-Dark UI vs. Light UI

2023 | HICSS | Citations: 0

Authors: Costello, F.; Kim, M.; Lee, K.

Abstract: The goal of the current study was to explore the potential of neuroscience mini ... Expand

Abstract: The goal of the current study was to explore the potential of neuroscience mining (NSM) for comprehending NeuroIS paradigms. NSM is an interdisciplinary field that combines neuroscience and business mining, which is the application of big data analytics, computational social science, and other areas to business problems. NSM makes it possible to apply predictive models to NeuroIS datasets, such as machine learning and deep learning, to find intricate patterns hidden by conventional regression-based analysis. First, we predicted 28 individual EEG power spectra separated brainwave data using a Random Forest (RF) model. Next, we used NSM to precisely predict how consumers would perceive a product online, depending on whether a light or dark user interface (UI) mode was used. The model was then used to extract more precise results that could not be obtained using more conventional linear-based analytical models using sensitivity analysis. The benefits of using NSM in NeuroIS research are as follows: (1) it can relieve the burden of the threehorned dilemma described by Runkel and McGrath; (2) it can enable more temporal data to be directly analyzed on the target variables; and (3) sensitivity analysis can be performed on a condition/individual basis, strengthening the rigor of findings by reducing sample bias that can be lost in grand averaging of data when analyzed with methods like GLM. Collapse

Topics: user interface big data usability tablet artificial intelligence

Methods: electroencephalography NeuroIS computational algorithm sensitivity analysis machine learning

Augmented Facilitation: Designing a multi-modal Conversational Agent for Group Ideation

2023 | International Conference on Information Systems | Citations: 0

Authors: Cvetkovic, Izabel; Gierlich-Joas, Maren; Tavanapour, Navid; Debowski-Weimann, Nicole; Bittner, Eva

Abstract: Human facilitators face the challenge to structure and collect relevant insight ... Expand

Abstract: Human facilitators face the challenge to structure and collect relevant insights from collaborative creative work sessions, which can suffer if they face a high workload. Hence, for effective value co-creation in organizational ideation we suggest an facilitation augmentation with a conversational agent (CA). CAs have the ability to support respective collaborative work by documenting and analyzing unstructured data. Following the design science research paradigm, and based on the literature about facilitation and human-AI collaboration, we derive design principles to develop a CA prototype that collects ideas from a group ideation session and displays them back in a structured (multi-modal) manner. We evaluate the CA by conducting four focus groups. Key findings show that the CA successfully distills and enriches information. Our study contributes to understanding the role of CA in augmenting facilitation and it provides guidance for practice on how to integrate these technologies in group meetings. Collapse

Topics: SWOT analysis artificial intelligence human AI collaboration human computer interaction participatory design

Methods: design artifact qualitative interview design principle group interview qualitative content analysis

Navigating AI in Personnel Selection: A Scenario-based Study on Applicants' Perceptions

2023 | International Conference on Information Systems | Citations: 0

Authors: Czernietzki, Charlotte; Märtins, Julian; Westmattelmann, Daniel; Grotenhermen, Jan-Gerrit; Oldeweme, Andreas; Baumeister, Viktoria; Schewe, Gerhard

Abstract: AI-based systems are increasingly deployed on organizational tasks, such as per ... Expand

Abstract: AI-based systems are increasingly deployed on organizational tasks, such as personnel selection decisions. As existing research indicates that applicants generally react negatively to the use of AI in personnel selection, this study examines how organizations can mitigate adverse reactions to fully exploit the benefits of AI. To obtain robust results, we recruited an online sample of German participants (N = 1,852) and presented them with various selection scenarios. Using a between-subject design, the process stage (preselection vs. interview) and the degree of process automation (augmented vs. automated) were manipulated. By employing a multidimensional conceptualization of transparency, we show that disclosure and accuracy positively impact procedural justice perceptions, a strong predictor of process quality assessment. This relationship is robust across selection contexts. Results indicate that applicants prefer AI for pre-selection and as human decision support, thus offering overall insights into design choices for AI in selection, optimizing applicant reactions. Collapse

Topics: artificial intelligence business process automation data quality electronic mail virtual reality

Methods: qualitative interview partial least squares path modeling survey parametric test ANOVA

Theories: procedural justice theory organizational justice theory

Conducting Design Science Research in Society 5.0 – Proposal of an Explainable Artificial Intelligence Research Methodology

2023 | DESRIST | Citations: 0

Authors: Daase, Christian; Turowski, Klaus

Abstract: Every technological or scientific advance is accompanied by a change in social s ... Expand

Abstract: Every technological or scientific advance is accompanied by a change in social structures, moral concepts, laws and education. As more and more people gain access to the digital world and the technical possibilities increase at the same rate, the excitement to carry out computer-based engineering projects increases. This in turn leads to an elevated demand for appropriate design-oriented methodologies, especially from the field of design science research (DSR), which in a sense democratize digital engineering. The idea of Society 5.0 is one of the major shifts in perspective on the role of technology, humans and their interaction in a shared living world. As a core component, artificial intelligence (AI), together with the Internet of things and big data analytics, is expected to have the most significant impact on the transformation toward smart societies. In this study, a systematic literature review of a total of 137 published articles addressing AI projects using DSR methodologies is conducted with the purpose of establishing a unified methodology for explainable AI-focused DSR projects. The proposed methodology further takes into account the particularities of AI at the varying advanced levels of artificial narrow intelligence (ANI) to the presumed necessities for approaching artificial general intelligence (AGI), which has not yet been fully realized. By allowing AI researchers to rely on a generalized methodological approach, the gap between behavioral science and design science is bridged, with the former laying the foundation for understanding living reality and the latter developing the means to mimic that reality as part of artificiality. Collapse

Topics: artificial intelligence explainable artificial intelligence database system artificial general intelligence

Methods: design science design methodology structured literature research literature sample

RQ Labs: A Cybersecurity Workforce Skills Development Framework

2023 | Information Systems Frontiers | Citations: 1

Authors: Daniel, Clinton; Mullarkey, Matthew; Agrawal, Manish

Abstract: This research contributes to the knowledge of how Information Systems (IS) resea ... Expand

Abstract: This research contributes to the knowledge of how Information Systems (IS) researchers can iteratively intervene with practitioners to co-create instructional programs with a framework designed for fast-paced, rapidly changing IS fields such as cybersecurity. We demonstrate how complex fields, such as cybersecurity, have the need for a skilled workforce that continues to rapidly outpace supply from universities. IS researchers partnering with practitioners can use this research as an exemplar of a method to design, build, and evaluate these innovative co-curricular IS programs. Moreover, we find these co-curricular IS programs are essential to upskilling students, integrating training on the latest tools, systems, and processes in these rapidly evolving disciplines. Collapse

Topics: IT security participatory design online learning system human resource management internet of things

Methods: action design research design methodology design artifact survey qualitative interview

The Concept of Agency in the Era of Artificial Intelligence: Dimensions and Degrees

2023 | Information Systems Frontiers | Citations: 0

Authors: Dattathrani, Sai; De’, Rahul

Abstract: Human and material agency have been investigated in the IS literature to underst ... Expand

Abstract: Human and material agency have been investigated in the IS literature to understand how technology and humans influence each other. Some framings of agency treat humans and technology symmetrically, some privilege the agency of humans over technology, and others do not attribute agency to either humans or non-humans. We argue that with the new generation of technologies, such as AI, the notion of agency needs to differentiate between the actions of AI from that of traditional information systems and humans. We introduce the dimensions of agency to differentiate agencies while not privileging any actor. We illustrate the application of dimensions by using it as a lens to study the case of a technician using an AI solution for screening patients for early-stage breast cancer. Through the use of the dimensions of agency we illustrate how the influence of AI over human practice, such as screening for early-stage breast cancer, is higher than the influence of traditional technology. We discuss our contribution to the theory of agency and conclude with a discussion on potential practical applications of the framework. Collapse

Topics: artificial intelligence laptop computer user interface usability knowledge representation

Methods: field study computational algorithm theory development ontological modelling theoretical contribution

Pickled eggs: Generative AI as research assistant or co-author?

2023 | Information Systems Journal | Citations: 0

Authors: Davison, Robert M.; Laumer, Sven; Tarafdar, Monideepa; Wong, Louie H. M.

Abstract: ChatGPT' indicates approximately 416 million hits, while Google Scholar suggest ... Expand

Abstract: ChatGPT' indicates approximately 416 million hits, while Google Scholar suggests 4710 articles, a number that is likely to rise fast. Generative AI is clearly here to stay, though there are already calls to curtail its use and some countries appear to be banning it. Interestingly, we already see the roll-out of generative AI detection software with tools like GPTZero. The plagiarism detection tool, iThenticate, is likely to follow up and embed generative AI detection as well. In order to reflect on this rapidly developing phenomenon, we conducted a sentiment and topic analysis of Twitter tweets about ChatGPT in academia. We analysed 12 400 tweets over a 3-month period from late 2022 to early 2023. 3680 tweets display a positive sentiment, 2612 display a negative one and 6109 display a neutral view. This pattern already exhibits a shift from the earlier reactions which were predominantly negative. Nevertheless, the topics discussed in these tweets are similar and can be subsumed within two major streams: research and publication. | WHY DOES IT MATTER TO ISJ READERS?Our focus in this editorial is on the practicalities of applying generative AI in the academic research community. The stakeholders of relevance here are authors, reviewers, editors and readers (scholars and practitioners) of ISJ, and also its publisher. All of these stakeholders have a commitment to and interest in the undertaking and publishing of academic research. Indeed, research and publication are the twin pillars on which a scholarly journal stands. Emerging articles comment on the strengths, weaknesses, opportunities and threats of generative AI in the context of research (see for instance Dwivedi et al., 2023, for an extensive account). In academia, there is an ongoing debate on the various implications that the technology may have. | WHY IS GENERATIVE AI RELEVANT TO RESEARCH?The title of this editorial, viz.: "pickled eggs", should have given some pause for thought. As it happened the collaborators of one of the co-authors of this editorial used a generative AI assistant (Microsoft Office 365's transcription function) to convert an audio file (of an interview with a research subject) to text. In that interview, reference was made to "pico-x", the name of a software. The generative AI assistant duly rendered this as "pickled eggs", presumably the closest term in its vocabulary. Reading through the transcript, numerous errors appeared: personal, product or place names were routinely misspelled, but so too were more mundane expressions. Similar errors occurred in Chinese where an interviewee used the English letters EDI (Electronic Data Interchange) in the middle of what was otherwise a Chinese sentence. The generative AI assistant, which was set up to transcribe Chinese audio to Chinese text, correctly transcribed all the Chinese words into characters, but made an error with EDI, which it also converted Collapse

Topics: Twitter knowledge sharing electronic health digital ecosystem participatory design

Methods: experiment survey design methodology action research chatGPT

Theories: affect theory

The practitioner perspective

2023 | Information Systems Journal | Citations: 0

Authors: Davison, Robert M.; Marabelli, Marco; Tim, Yenni; Beath, Cynthia

Abstract: The Information Systems (IS) discipline traces its origins to issues that were ... Expand

Abstract: The Information Systems (IS) discipline traces its origins to issues that were of interest to practitioners, but in recent years the practitioner perspective has often been neglected. Nevertheless, there is increasing recognition that the practitioner's perspective is still important and that the research we undertake can (or should) have implications for practitioners. Journals like MIS Quarterly Executive target this segment exclusively. In this, they complement non-IS journals and magazines in the broader business and technology spheres that also have practitioners in mind, including: Harvard Business Review, Sloan Management Review, California Management Review, Communications of the ACM, McKinsey Quarterly, Academy of Management Perspectives, CIO Magazine, etc. Moreover, some of the existing journals that are predominantly focused on publishing theoretical contributions, for example, the journals that make up the Association of Information Systems' College of Senior Scholars list of eleven premier journals, 1 have also demonstrated that they are open to practitioner-oriented submissions.The Information Systems Journal (ISJ) has for several years championed the publication of what we call Practitioner Papers (PPs). PPs can contribute to knowledge in a number of different ways, but one of our key objectives in promoting PPs is to further the dialogue between academia and practice. As part of this dialogue, PPs should provide deep insights for researchers into the practitioner's experience with IS in a particular context, as well as, of course, prescriptive and actionable recommendations for practice based on well executed research. Insights for practice may include reframing or reimagining specific practitioner problems, offering a thorough exploration of a phenomenon, documenting lessons learned by practitioners, or illustrating good practices and their outcomes. To render these insights actionable, these articles will include action-oriented prescriptions that suggest what practitioners should do differently in practice.While practitioners are the primary intended audience of PPs, academic researchers may also benefit, for instance when PPs engage with new phenomena and propose new insights that challenge and extend the existing discourse. Such outcomes can inspire future academic work to re-examine those prior findings, perhaps as part of the researcher's problematisation of the phenomenon (Chatterjee & Davison, 2021).Although practitioners are commonly thought of as working in or for organisations, we recognise that practitioners can be found in diverse settings and may not necessarily be serving a corporate entity. We can find practitioners in the political spectrum (i.e., lawmakers), non-governmental organisations, charities, villages, and communities. They may be formally employed, working as activists, or simply citizens with an interest in using IS to make the world a better place (Walsham, 2012).Submissions in the PP genre at the ISJ have been sporadic and the quality has varied. Examples of published PPs are Tamm et al. (2022) andTim et al. (2021), while Pan and Pee (2020) offer a framework for demonstrating the impact of research on practice. To further encourage the undertaking of practitioner-oriented research, we have recently both reformulated our PP guidelines 2 and announced a special issue 3 that focuses exclusively on practice.Our aim is to spur further practitioner-oriented work.As with regular research articles, PPs could be written about a wide range of topics within the broad IS domain.Like all premier journals, we seek to publish cutting edge research that advances knowledge in the IS domain. Thus, we do not intend that PPs be used as a vehicle for teaching cases, or low quality (rejected) research articles that have 1 https://aisnet.org/page/SeniorScholarListofPremierJournals Collapse

Topics: blockchain generative AI artificial intelligence robotic digital twin

Methods: simulation

Automated Deductive Content Analysis of Text: A Deep Contrastive and Active Learning Based Approach

2023 | International Conference on Information Systems | Citations: 0

Authors: De Oliveira Silveira, Alysson; Ray, Arindam; Ebrahimi, Mohammadreza; Bhattacherjee, Anol

Abstract: Content analysis traditionally involves human coders manually combing through t ... Expand

Abstract: Content analysis traditionally involves human coders manually combing through text documents to search for relevant concepts and categories. However, this approach is time-intensive and not scalable, particularly for secondary data like social media content, news articles, or corporate reports. To address this problem, the paper presents an automated framework called Automated Deductive Content Analysis of Text (ADCAT) that uses deep learning-based semantic techniques, an ontology of validated construct measures, a large language model, human-in-the-loop disambiguation, and a novel augmentation-based weighted contrastive learning approach for improved language representations, to build a scalable approach for deductive content analysis. We demonstrate the effectiveness of the proposed approach to identify firm innovation strategies from their 10-K reports to obtain inferences reasonably close to human coding. Collapse

Topics: knowledge representation human in the loop human computer interaction innovation management organizational innovation

Methods: ontological modelling machine learning language model large language model qualitative content analysis