When Reflection Hurts: The Effect of Cognitive Processing Types on Organizational Adaptation to Discontinuous Change

2023 | Organization Science | Citations: 1

Authors: Alves, Marlon Fernandes Rodrigues; Vastola, Vincenzo; Vasconcelos Ribeiro Galina, Simone; Zollo, Maurizio

Abstract: Technological breakthroughs, institutional disruptions, and natural disasters of ... Expand

Abstract: Technological breakthroughs, institutional disruptions, and natural disasters often alter the course of organizations and entire industries. Such discontinuous changes threaten organizations’ survival by affecting the value of the knowledge accumulated in routines and capabilities. Although it is widely acknowledged that managerial cognition is a critical antecedent of organizational responses to discontinuous change, the role of type 1 (intuitive) and type 2 (reflective) processing in the adaptation of shared patterns of behavior, that is, routines, remains understudied. Drawing on dual-process theory, we propose that particular features of type 1 processing render this approach superior to type 2 processing, especially in highly ambiguous environments in which information is limited and difficult to verify. We tested our hypotheses in a longitudinal experiment linking individual-level factors with organizational-level practices of routine adaptation. Experienced managers, paired in 80 groups, developed routines in a first round of a simulation game; in a second round, we then introduced a discontinuous change making previous routines obsolete in order to observe how they adapted. The data show that priming type 1 processing facilitates organizational adaptation more than type 2 processing by providing faster, more routinized, efficiently coordinated, and optimal responses. In addition, type 1 appears to be more functional in highly ambiguous environments, whereas type 1 and type 2 processes yield similar levels of performance under low levels of ambiguity. Overall, our study advances the understanding of the nondeliberative dimension of organizational adaptation to discontinuous change.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Finance Code 001).Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1517. Collapse

Topics: decision making strategic management innovation management problem solving task productivity

Methods: experiment longitudinal research parametric test ANOVA statistical hypothesis test

Theories: dual-system theory dynamic capabilities theory

Investigating the Use of Augmented Reality and Machine Learning in Electrical Engineering Courses

2023 | International Conference on Business Informatics | Citations: 0

Authors: Al Mehdawi, Miles; Dreesbach, Tobias; Gösling, Henning; Brinkmann, Marcel

Abstract: The use of augmented reality (AR) in education and training is growing increasi ... Expand

Abstract: The use of augmented reality (AR) in education and training is growing increasingly. However, applications to integrate augmented reality learning content into training for basic electrical engineering courses are scarce. The individual learning objectives of trainees complicate the digitalization of learning content, particularly for the drawing of circuit diagrams. To increase trainees' learning outcome while simultaneously relieving instructors of classroom supervision, we designed and developed an AR-based prototype, to enhance hand-drawn circuit diagrams in vocational training. The context sensitivity is achieved by combining AR with image recognition. In an experiment with twelve participants, a positive impact of the prototype on trainees' learning outcomes was observed, in comparison to a control group that received instructions without the prototype. Collapse

Topics: augmented reality smart device artificial intelligence smart glass extended reality

Methods: design artifact experimental group qualitative interview survey parametric test

Towards a thematic dimensional framework of online fraud: An exploration of fraudulent email attack tactics and intentions

2023 | Decision Support Systems | Citations: 1

Authors: Bera, Debalina; Ogbanufe, Obi; Kim, Dan J.

Abstract: Despite anti-phishing filters, social engineering-based cyber-attacks still resu ... Expand

Abstract: Despite anti-phishing filters, social engineering-based cyber-attacks still result in billions of dollars lost annually, significant personal identity theft, loss of corporate secrets, and espionage. We review the phishing literature on psychological attacks and design tactics employed for deception by attackers. The result reveals the need to continuously identify tactics embedded in fraudulent email content to understand why users still fall prey to phishing attacks. Using the literature as a backdrop, we identify and conceptualize a thematic dimensional framework of fraudulent phishing attacks. This study uses benchmark datasets of fraudulent email to empirically validate the proposed dimensional framework. Specifically, a combination of machine learning-based content analysis and topic modeling found a majority of the discovered topics were labeled against the proposed di­ mensions. Statistical analysis was employed to provide empirical evidence of the thematic dimensions of fraudulent email attacks. This study thus, not only extends the cybersecurity literature by identifying and vali­ dating eight dimensions that enrich our understanding of phishing and attack identification but stimulates cu­ mulative research endeavors to develop yet more comprehensive dimensional frameworks of phishing email attacks. Collapse

Topics: phishing email phishing electronic mail email spam personalization

Methods: term frequency–inverse document frequency natural language processing topic model discriminant analysis literature study

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

The End of the World or Just a Turning Point? Effects of Negative and Positive Wording within Sustainability Campaigns on Social Media

2023 | HICSS | Citations: 0

Authors: Decker, H.; Feier, A.

Abstract: The internet and social media are constantly evolving and providing innovations ... Expand

Abstract: The internet and social media are constantly evolving and providing innovations for communication. Persuasive communication, like advertisements, can be adapted to peoples' personal preferences and desires based on tracked data. Emotions have been found to play an important role within persuasion. Based on theoretical assumptions of framing and affective priming, we hypothesize different effects of positive and negative messages and mood within social media advertising. To investigate the reception of ads regarding their persuasiveness in sustainability campaigns we conducted an online experiment using a 2x2 between design (N=147) measuring ad evaluation and behavioral intention. Our findings revealed that wording can be an influential factor in persuasive messages towards more sustainability. Positive framing led to a better ad evaluation than negative wording. However, behavioral intention was not affected and there was no enhancing effect of recipients' environmental awareness. Collapse

Topics: behavioral intention social media advertising management social norm personality

Methods: experimental group experiment moderation analysis linear regression analysis regression analysis method

Theories: theory of planned behavior

Promoting Learning Through Explainable Artificial Intelligence: An Experimental Study in Radiology

2023 | International Conference on Information Systems | Citations: 0

Authors: Ellenrieder, Sara; Kallina, Emma; Pumplun, Luisa; Gawlitza, Joshua Felix; Ziegelmayer, Sebastian; Buxmann, Peter

Abstract: The deployment of machine learning (ML)-based decision support systems (DSSs) i ... Expand

Abstract: The deployment of machine learning (ML)-based decision support systems (DSSs) in high-risk environments such as radiology is increasing. Despite having achieved high decision accuracy, they are prone to errors. Thus, they are primarily used to assist radiologists in their decision making. However, collaborative decision making poses risks to the decision maker, e.g. automation bias and long-term performance degradation. To address these issues, we propose combining findings of the research streams of explainable artificial intelligence and education to promote human learning through interaction with ML-based DSSs. We provided radiologists with explainable vs nonexplainable decision support that was high-vs low-performing in a between-subject experimental study to support manual segmentation of 690 brain tumor scans. Our results show that explainable ML-based DSSs improved human learning outcomes and prevented false learning triggered by incorrect decision support. In fact, radiologists were able to learn from errors made by the low-performing explainable ML-based DSS. Collapse

Topics: decision support system decision support explainable artificial intelligence decision making artificial intelligence

Methods: experiment qualitative interview magnetic resonance imaging parametric test ANOVA

Thinking Fast and Thinking Slow: Digital Devices' Effects on Cognitive Reflection

2023 | Journal of Management Information Systems | Citations: 0

Authors: Figl, Kathrin; Remus, Ulrich

Abstract: Informed by theoretical perspectives on working memory demands and devices' pote ... Expand

Abstract: Informed by theoretical perspectives on working memory demands and devices' potential to "prime" different types of cognitive processing, this paper investigates whether we tend to think "faster" and more intuitively, with less reflection when we use a smartphone instead of a personal computer (PC) or notebook. Three complementary experimental studies with a total of 823 participants reveal that the results of using such devices surface only when participants can select the smartphone as their preferred device. Controlling for potential confounding variables reveals no evidence of general differences between devices. Our findings caution against overemphasizing the importance of the type of device in thinking slow or fast and establish self-selection bias as an important factor in explaining such differences. This study contributes to clarifying the psychology of smartphone screens and how humans make choices when they are using these devices. Collapse

Topics: smartphone electronic mail social media decision making laptop computer

Methods: survey within subject experiment longitudinal research experiment hierarchical linear modeling

Theories: dual-system theory cognitive theory

Effort as investment in healthcare dialogue-based agents: On the role of means-goal configurations

2023 | Decision Support Systems | Citations: 0

Authors: Ghasemi, Ehsan; Sheikh-Zadeh, Alireza; Song, Jaeki

Abstract: The recent pandemic and resultant increase in clinical caseload have brought dia ... Expand

Abstract: The recent pandemic and resultant increase in clinical caseload have brought dialogue-based agents (DBAs) to the forefront of attention in the healthcare industry. The ability of these agents to accomplish a variety of sequential and related tasks within a single application software has made them more effortful and complex. While effort requirements and complexity of information systems are generally considered negative attributes, the potential effect of user effort investment on user perceptions and decisions is less investigated. Within the framework of goal systems theory, this study explores how perceived effort could be appropriated to enhance users’ positive perceptions and willingness to accept healthcare DBAs outputs. We find evidence for the positive role both in the perceived effort before and after the actual use of healthcare DBAs as well as in user goal magnitude and means-goal configuration on perceptions of usefulness and probability of considering outputs. Collapse

Topics: technology adoption mobile application user experience decision making mobile phone

Methods: experiment regression analysis method experimental group linear regression analysis descriptive statistic

Theories: general systems theory

Explanation matters: An experimental study on explainable AI

2023 | Electronic Markets | Citations: 0

Authors: Hamm, Pascal; Klesel, Michael; Coberger, Patricia; Wittmann, H. Felix

Abstract: Explainable artificial intelligence (XAI) is an important advance in the field o ... Expand

Abstract: Explainable artificial intelligence (XAI) is an important advance in the field of machine learning to shed light on black box algorithms and thus a promising approach to improving artificial intelligence (AI) adoption. While previous literature has already addressed the technological benefits of XAI, there has been little research on XAI from the user’s perspective. Building upon the theory of trust, we propose a model that hypothesizes that post hoc explainability (using Shapley Additive Explanations) has a significant impact on use-related variables in this context. To test our model, we designed an experiment using a randomized controlled trial design where participants compare signatures and detect forged signatures. Surprisingly, our study shows that XAI only has a small but significant impact on perceived explainability. Nevertheless, we demonstrate that a high level of perceived explainability has a strong impact on important constructs including trust and perceived usefulness. A post hoc analysis shows that hedonic factors are significantly related to perceived explainability and require more attention in future research. We conclude with important directions for academia and for organizations. Collapse

Topics: explainable artificial intelligence artificial intelligence perceived ease of use perceived usefulness digital dashboard

Methods: experimental group experiment parametric test experimental task ANOVA

Theories: information systems theory trust theory

The puzzle of experience vs. memory: Peak-end theory and strategic gamification design in M-commerce

2023 | Information & Management | Citations: 0

Authors: Li, Manning; Jiang, Zhenhui (Jack); Ma, Guanghui

Abstract: As businesses increasingly use gamified mobile marketing campaign (GMMC) systems ... Expand

Abstract: As businesses increasingly use gamified mobile marketing campaign (GMMC) systems to engage mobile shop­ pers, gamification in m-commerce systems warrants more attention in both IS research and design practices. Inspired by peak-end theory, this study focused on the puzzling differences between user experience vs. memory and empirically examined the impact of different experience orders of cognitive load on user perceptions and behavioral intentions. Overall, the outcomes of this research suggest that appropriate applications of the peakend effect, moderated via users’ regulatory focus styles, can alleviate the negative mental utility imagery of users, reducing their perceived uncertainties and opt-out intentions from the GMMC. Important implications for research and practice are then discussed. Collapse

Topics: electronic data interchange marketing management user experience gamification systems design

Methods: experiment electroencephalography survey multivariate analysis of variance survey design

Theories: technology acceptance model flow theory self determination theory theory of planned behavior