Enhancing Sustained Attention

2021 | Business & Information Systems Engineering | Citations: 2

Authors: Demazure, Théophile; Karran, Alexander; Léger, Pierre-Majorique; Labonté-LeMoyne, Élise; Sénécal, Sylvain; Fredette, Marc; Babin, Gilbert

Abstract: Arguably, automation is fast transforming many enterprise business processes, tr ... Expand

Abstract: Arguably, automation is fast transforming many enterprise business processes, transforming operational jobs into monitoring tasks. Consequently, the ability to sustain attention during extended periods of monitoring is becoming a critical skill. This manuscript presents a Brain-Computer Interface (BCI) prototype which seeks to combat decrements in sustained attention during monitoring tasks within an enterprise system. A brain-computer interface is a system which uses physiological signals output by the user as an input. The goal is to better understand human responses while performing tasks involving decision and monitoring cycles, finding ways to improve performance and decrease on-task error. Decision readiness and the ability to synthesize complex and abundant information in a brief period during critical events has never been more important. Closed-loop control and motivational control theory were synthesized to provide the basis from which a framework for a prototype was developed to demonstrate the feasibility and value of a BCI in critical enterprise activities. In this pilot study, the BCI was implemented and evaluated through laboratory experimentation using an ecologically valid task. The results show that the technological artifact allowed users to regulate sustained attention positively while performing the task. Levels of sustained attention were shown to be higher in the conditions assisted by the BCI. Furthermore, this increased cognitive response seems to be related to increased on-task action and a small reduction in on-task errors. The research concludes with a discussion of the future research directions and their application in the enterprise. Collapse

Topics: digital dashboard logistics management task productivity enterprise resource planning enterprise information system

Methods: design artifact electroencephalography parametric test computational algorithm ANOVA

Theories: control theory

Validity in Design Science Research

2020 | DESRIST | Citations: 9

Authors: Larsen, Kai R.; Lukyanenko, Roman; Mueller, Roland M.; Storey, Veda C.; VanderMeer, Debra; Parsons, Jeffrey; Hovorka, Dirk S.

Abstract: Research in design science has always acknowledged the need for evaluating its k ... Expand

Abstract: Research in design science has always acknowledged the need for evaluating its knowledge outcomes, with particular emphasis on assessing the efficacy and utility of the artifacts produced. However, the need to demonstrate the validity of the research process and outcomes has not received as much attention. This research examines scientific approaches to validity and their applicability to, and use in, design science. To do so, we assembled an extensive data set of research validities articles from various disciplines, as well as design science articles. We then examined the use of validity concepts in these articles and how these concepts could be employed to describe what validity means for design science research. The result is a design science research validity framework to guide how validity can become an integral aspect of design science research. Collapse

Topics: knowledge type IS discipline systems evaluation

Methods: design science literature sample design artifact machine learning design theory

TheoryOn: A Design Framework and System for Unlocking Behavioral Knowledge Through Ontology Learning

2020 | Management Information Systems Quarterly | Citations: 25

Authors: Li, Jingjing; Larsen, Kai; Abbasi, Ahmed

Abstract: The scholarly information-seeking process for behavioral research consists of th ... Expand

Abstract: The scholarly information-seeking process for behavioral research consists of three phases: searching, accessing, and processing of past research. Existing IT artifacts, such as Google Scholar, have in part addressed the searching and accessing phases, but fall short of facilitating the processing phase, creating a knowledge inaccessibility problem. We propose a behavioral ontology learning from text (BOLT) design framework that presents concrete prescriptions for developing systems capable of supporting researchers during their processing of behavioral knowledge. Based upon BOLT, we developed a search engine— TheoryOn—to allow researchers to directly search for constructs, construct relationships, antecedents, and consequents, and to easily integrate related theories. Our design framework and search engine were rigorously evaluated through a series of data mining experiments, a randomized user experiment, and an applicability check. The data mining experiment results lent credence to the design principles prescribed by BOLT. The randomized experiment compared TheoryOn with EBSCOhost and Google Scholar across four information retrieval tasks, illustrating TheoryOn’s ability to reduce false positives and false negatives during the information-seeking process. Furthermore, an in-depth applicability check with IS scholars offered qualitative support for the efficacy of an ontology-based search and the usefulness of TheoryOn during the processing phase of existing research. The evaluation results collectively underscore the significance of our proposed design artifacts for addressing the knowledge inaccessibility problem for behavioral research literature. Collapse

Topics: knowledge representation search engine perceived usefulness usage intention information retrieval

Methods: experiment applicability check design science ontological modelling design artifact

Theories: organizational behavior theory technology acceptance model learning theory information systems theory behavioral theory

Appealing to Sense and Sensibility: System 1 and System 2 Interventions for Fake News on Social Media

2020 | Information Systems Research | Citations: 77

Authors: Moravec, Patricia L.; Kim, Antino; Dennis, Alan R.

Abstract: Disinformation on social media—commonly called “fake news”—has become a major co ... Expand

Abstract: Disinformation on social media—commonly called “fake news”—has become a major concern around the world, and many fact-checking initiatives have been launched to mitigate the problem. The way fact-checking results are presented to social media users is important because if the presentation format is not persuasive, then fact-checking may not be effective. For instance, Facebook tested the idea of flagging dubious articles in 2017 but concluded that it was ineffective and subsequently removed the feature. We conducted three experiments with social media users to investigate two different approaches to implementing a fake news flag—one designed to have its primary effect when processed by automatic cognition (System 1) and the other designed to have its primary effect when processed by deliberate cognition (System 2). We found that both interventions were effective, and an intervention that combined both approaches was about twice as effective. We also found that awareness training on the meaning of the flags increased the effectiveness of the System 2 intervention but not the System 1 intervention, exactly as theory predicts. Believability, in turn, influenced the extent to which users would engage with the article (e.g., read, like, comment, and share). Our results suggest that both theoretical routes can be used—separately or together—in the presentation of fact-checking results in order to reduce the influence of fake news on the users. Collapse

Topics: social media fake news Facebook information system use systems design

Methods: theory development experiment linear regression analysis design artifact Wald test

Theories: cognitive dissonance theory

A Metadesign Theory for Tailorable Decision Support

2019 | Journal of the Association for Information Systems | Citations: 4

Authors: Miah, Shah Jahan; Gammack, John G.; McKay, Judy

Abstract: Despite years of decision support systems (DSS) research, DSS artifacts are freq ... Expand

Abstract: Despite years of decision support systems (DSS) research, DSS artifacts are frequently criticized for lacking practitioner relevance and for neglecting configurability and contextual dynamism. Tailoring in end-user contexts can produce relevant emergent DSS artifacts, but design theory for this is lacking. Design science research (DSR) has important implications for improving DSS uptake, but generally this has not been promoted in the form of metadesigns with design principles applicable to other DSS developments. This paper describes a metadesign theory for tailorable DSS, generated through action design research studies in different primary industries. Design knowledge from a DSS developed in an agricultural domain was distilled and generalized into a design theory comprising: (1) a general solution concept (metadesign), and (2) five hypothesized design principles. These were then instantiated via a second development in which the metadesign and design principles were applied in a different domain (forestry) to produce a successful DSS, thus testing the metadesign and validating the design principles. In addition to contributing to DSR and illustrating innovation in tailorable technology, the paper demonstrates the utility of action design research to support theory development in DSS design. Collapse

Topics: decision support system decision support knowledge sharing spreadsheet rule-based representation

Methods: design principle meta design design artifact design theory focus group

Shopping in Virtual Reality Stores: The Influence of Immersion on System Adoption

2019 | Journal of Management Information Systems | Citations: 52

Authors: Peukert, Christian; Pfeiffer, Jella; Meißner, Martin; Pfeiffer, Thies; Weinhardt, Christof

Abstract: Companies have the opportunity to better engage potential customers by presentin ... Expand

Abstract: Companies have the opportunity to better engage potential customers by presenting products to them in a highly immersive virtual reality (VR) shopping environment. However, a minimal amount is known about why and whether customers will adopt such fully immersive shopping environments. We therefore develop and experimentally validate a theoretical model, which explains how immersion affects adoption. The participants experienced the environment by using a head-mounted display (high immersion) or by viewing product models in 3D on a desktop (low immersion). We find that immersion does not affect the users' intention to reuse the shopping environment, because two paths cancel each other out: Highly immersive shopping environments positively influence a hedonic path through telepresence, but surprisingly, they negatively influence a utilitarian path through product diagnosticity. We can explain this effect via low readability of product information in the VR environment and expect VR's full potential to develop when the technology is further advanced. Our study contributes to literature on immersive systems and IS adoption research by introducing a research model for the adoption of VR shopping environments. A key practical implication of our study is that system designers need to pay special attention to the current state of technology when designing VR applications. Collapse

Topics: virtual reality video conference perceived usefulness electronic commerce decision making

Methods: experiment survey multivariate analysis of variance structural equation modeling Mann Whitney U test

Theories: technology acceptance model

Acting Like Humans? Anthropomorphism and Consumer’s Willingness to Pay in Electronic Commerce

2019 | Journal of Management Information Systems | Citations: 0

Authors: Yuan, Lingyao (Ivy); Dennis, Alan R.

Abstract: Anthropomorphism is the attribution of human characteristics to a non-human obje ... Expand

Abstract: Anthropomorphism is the attribution of human characteristics to a non-human object. Past research shows that anthropomorphism changes how we perceive objects (e.g., believing them to be more attractive). Does this mean we would be willing to pay more for them? We examined whether displaying a product in an anthropomorphized form influenced how much a consumer was willing to pay. We examined two design aspects, visual (i.e., a face) and auditory (e.g., a voice), in the context of an online auction, and proposed three theoretical routes by which an anthropomorphic product display might affect willingness to pay (emotional, product attachment, and product quality). Results show that adding visual anthropomorphizing features to the way a product was displayed increased the amount bid by 7 percent, but adding auditory anthropomorphizing features had no effect. The visual anthropomorphizing features increased product attachment but had no effect on emotions or perceptions of product quality. Therefore, we conclude that anthropomorphizing the way a product is displayed increases willingness to pay primarily through the theoretical route of creating attachment to the product. There is an additional, as yet undiscovered, theoretical route through which anthropomorphism influences willingness to pay. The results also suggest that the conventional wisdom that the combination of visual and auditory design features is best for triggering anthropomorphism is not always true. Collapse

Topics: willingness to pay tablet online auction website media richness

Methods: survey parametric test ANOVA theory development experiment

Theories: uncanny valley theory

Artifact Sampling: Using Multiple Information Technology Artifacts to Increase Research Rigor

2018 | HICSS | Citations: 5

Authors: Lukyanenko, Roman; Samuel, Binny M; Parsons, Jeffrey

Abstract: Researchers in many scientific disciplines routinely conceptualize information t ... Expand

Abstract: Researchers in many scientific disciplines routinely conceptualize information technologies (IT) as antecedents or outcomes in theoretical models. The ongoing theorizing of IT leads to a novel methodological challenge termed instantiation validity (IV). In this paper, we contribute to research on remediating IV challenges by proposing and advocating the methodological practice of artifact sampling, whereby multiple artifacts are sampled from the population of all possible artifacts (the instantiation space). Artifact sampling extends the practice of employing multiple research subjects or survey respondents, routinely used in social sciences, into the IT artifact design space. Artifact sampling is an important methodological practice that stands to increase the rigor of research dealing with software artifacts. As it is currently not being adequately undertaken in the aforementioned research, many studies may result in biased or unjustified conclusions. Collapse

Topics: systems design technology adoption

Methods: design artifact survey survey design literature study

Flagging Fake News: System 1 vs. System 2

2018 | International Conference on Information Systems | Citations: 21

Authors: Moravec, Patricia; Kim, Antino; Dennis, Alan

Abstract: Misinformation on social media—commonly referred to as “fake news”—has become a ... Expand

Abstract: Misinformation on social media—commonly referred to as “fake news”—has become a major concern around the world, and many fact-checking initiatives have been launched to mitigate the problem. The way fact-checking results are presented to social media users is important because if the presentation format is not persuasive, fact checking may have little desirable effect. We conducted an experiment with 397 social media users to investigate the effect of training on a fake news flag, as well as two different approaches to designing the flag, one designed to trigger automatic cognition (System 1) and the other, deliberate cognition (System 2). We found that training increased the effectiveness of the flag in reducing users’ beliefs in fake news. We found that both System 1 and System 2 interventions were effective, and an intervention that combined both was about twice as effective. Believability, in turn, influenced the extent to which users would engage with the article (e.g., read, like, comment, and share). Our results suggest that both theoretical routes can be used—separately or concurrently—in the presentation of fact-checking results to social media users. These interventions can nudge users to evaluate articles more critically and make more informed decisions on engaging with them. Collapse

Topics: social media fake news Facebook misinformation information system use

Methods: theory development experiment Wald test linear regression analysis functional neuroimaging

Theories: cognitive dissonance theory

ProcessProfiler3D: A visualisation framework for log-based process performance comparison

2017 | Decision Support Systems | Citations: 0

Authors: Wynn, M. T.; Poppe, E.; Xu, J.; ter Hofstede, A. H. M.; Brown, R.; Pini, A.; van der Aalst, W. M. P.

Abstract: An organisation can significantly improve its performance by observing how their ... Expand

Abstract: An organisation can significantly improve its performance by observing how their business operations are currently being carried out. A great way to derive evidence-based process improvement insights is to compare the behaviour and performance of processes for different process cohorts by utilising the information recorded in event logs. A process cohort is a coherent group of process instances that has one or more shared characteristics. Such process performance comparisons can highlight positive or negative variations that can be evident in a particular cohort, thus enabling a tailored approach to process improvement. Although existing process mining techniques can be used to calculate various statistics from event logs for performance analysis, most techniques calculate and display the statistics for each cohort separately. Furthermore, the numerical statistics and simple visualisations may not be intuitive enough to allow users to compare the performance of various cohorts efficiently and effectively. We developed a novel visualisation framework for log-based process performance comparison to address these issues. It enables analysts to quickly identify the performance differences between cohorts. The framework supports the selection of cohorts and a three-dimensional visualisation to compare the cohorts using a variety of performance metrics. The approach has been implemented as a set of plug-ins within the open source process mining framework ProM and has been evaluated using two real-life datasets from the insurance domain to assess the usefulness of such a tool. This paper also derives a set of design principles from our approach which provide guidance for the development of new approaches to process cohort performance comparison. Collapse

Topics: ease of use process mining perceived usefulness online analytical processing task productivity

Methods: design principle event log business process modeling Petri net modeling language

Theories: technology acceptance model