Adoption Management: A Review of the Benefits Management and the Adoption Literature

2023 | European Conference On Information Systems | Citations: 0

Authors: Falch, Cecilie; Krancher, Oliver

Abstract: The adoption of Information Systems (IS) is among the critical topics for IS re ... Expand

Abstract: The adoption of Information Systems (IS) is among the critical topics for IS research and practice. However, despite rich insights across IS literature streams, many IS implementation projects still struggle with user adoption and realising benefits. This paper argues that a knowledge gap exists because research has paid little attention to the definition, manifestations, and effects of adoption management in mandatory environments. The article proposes definitions and systematically reviews findings related to adoption management at the cross-section of the adoption and benefits management literature. The findings show that adoption management manifests across the two literature streams as constructs, models, and methods. While some articles examine these manifestations in the analysis, many discuss adoption management as an afterthought in the implications for practice in discussion sections, and few articles explicitly label it adoption management. We discuss these and other gaps and provide avenues for future research. Collapse

Topics: systems implementation user behavior enterprise information system organizational value user resistance

Methods: literature study design artifact literature sample cross sectional research structured literature research

Do women and men click differently? Mobile devices mitigate gender differences in online dating

2023 | Information & Management | Citations: 1

Authors: Fink, Lior; Ilany-Tzur, Naama; Yam, Hadar; Sokhina, Svetlana

Abstract: Online dating has replaced traditional offline venues largely because of the str ... Expand

Abstract: Online dating has replaced traditional offline venues largely because of the structured presentation of visual and verbal information about potential partners. This study shows that including verbal information alongside visual information in online dating profiles affects attractiveness assessments by women more favorably than it affects those by men. These gender differences, however, are mitigated by using a mobile device instead of a personal computer. The findings extend the selectivity model, as well as the literature on online dating and mobile use, by highlighting gender differences in processing specific information types and by identifying the device as a boundary condition. Collapse

Topics: online dating mobile system website smartphone user behavior

Methods: experiment statistical hypothesis test regression analysis method descriptive statistic experimental task

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

Resource Allocation for Heterogeneous Computing Tasks in Wirelessly Powered MEC-enabled IIOT Systems

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Hu, Yixiang; Deng, Xiaoheng; Zhu, Congxu; Chen, Xuechen; Chi, Laixin

Abstract: Integrating wireless power transfer with mobile edge computing (MEC) has become ... Expand

Abstract: Integrating wireless power transfer with mobile edge computing (MEC) has become a powerful solution for increasingly complicated and dynamic industrial Internet of Things (IIOT) systems. However, the traditional approaches overlooked the heterogeneity of the tasks and the dynamic arrival of energy in wirelessly powered MEC-enabled IIOT systems. In this article, we formulate the problem of maximizing the product of the computing rate and the task execution success rate for heterogeneous tasks. To manage energy harvesting adaptively and select appropriate computing modes, we devise an online resource allocation and computation offloading approach based on deep reinforcement learning. We decompose this approach into two stages: an offloading decision stage and a stopping decision stage. The purpose of the offloading decision stage is to select the computing mode and dynamically allocate the computation round length for each task after learning from the channel state information and the task experience. This stage allows the system to support heterogeneous computing tasks. Subsequently, in the second stage, we adaptively adjust the number of fading slots devoted to energy harvesting in each round in accordance with the status of each fading slot. Simulation results show that our proposed algorithm can better allocate resources for heterogeneous tasks and reduce the ratio of failed tasks and energy consumption when compared with several existing algorithms. Collapse

Topics: resource allocation edge computing decision quality

Methods: computational algorithm reinforcement learning simulation experiment PyTorch

Unpacking the Black Box: A Cognitive Process Model of Escalation of Commitment in IS Project Management

2023 | International Conference on Business Informatics | Citations: 0

Authors: Marx, Carolin; Uebernickel, Falk

Abstract: In the plethora of challenges associated with managing Information Systems (IS) ... Expand

Abstract: In the plethora of challenges associated with managing Information Systems (IS), deciding when to persist or withdraw from a distressed IS project is of utmost importance. Distressed IS projects are particularly prone to Escalation of Commitment (EoC) -the tendency to persist with failing courses of action. To better understand how the cognitive "black box" behind this tendency unfolds, we uncovered 13 cognitive reasoning patterns and a cognitive process model based on 270 text-based reflections of 56 participants during a sequential decision-making simulation. Cognition differs between the four escalation phases regarding the temporal focus (retrospective, introspective, prospective), the underlying mechanism (starting momentum, path dependency, denial, perceived completion proximity), and the combination of cognitive reasoning patterns. The cognitive process model of EoC helps detangle the complexities of managing IS. Our findings also support IS managers in identifying signs of escalation and selecting the appropriate actions to turn distressed projects around. Collapse

Topics: decision making IT project IT project management decision quality project productivity

Methods: business process modeling simulation qualitative coding

Theories: cognitive dissonance theory self justification theory punctuated equilibrium theory

Machine learning advice in managerial decision-making: The overlooked role of decision makers’ advice utilization

2023 | Journal of Strategic Information Systems | Citations: 0

Authors: Sturm, Timo; Pumplun, Luisa; Gerlach, Jin P.; Kowalczyk, Martin; Buxmann, Peter

Abstract: Machine learning (ML) analyses offer great potential to craft profound advice fo ... Expand

Abstract: Machine learning (ML) analyses offer great potential to craft profound advice for augmenting managerial decision-making. Yet, even the most promising ML advice cannot improve decisionmaking if it is not utilized by decision makers. We therefore investigate how ML analyses influ­ ence decision makers’ utilization of advice and resulting decision-making performance. By analyzing data from 239 ML-supported decisions in real-world organizational scenarios, we demonstrate that decision makers’ utilization of ML advice depends on the information quality and transparency of ML advice as well as decision makers’ trust in data scientists’ competence. Furthermore, we find that decision makers’ utilization of ML advice can lead to improved decision-making performance, which is, however, moderated by the decision makers’ manage­ ment level. The study’s results can help organizations leverage ML advice to improve decisionmaking and promote the mutual consideration of technical and social aspects behind ML advice in research and practice as a basic requirement. Collapse

Topics: decision making data quality decision quality organizational context anonymity

Methods: survey survey design descriptive statistic moderation analysis theory development

Neuro-Adaptive Interface System to Evaluate Product Recommendations in the Context of E-Commerce

2023 | DESRIST | Citations: 0

Authors: Tadson, Bella; Boasen, Jared; Courtemanche, François; Beauchemin, Noémie; Karran, Alexander-John; Léger, Pierre-Majorique; Sénécal, Sylvain

Abstract: Personalized product recommendations are widely used by online retailers to comb ... Expand

Abstract: Personalized product recommendations are widely used by online retailers to combat choice overload, a phenomenon where excessive product information adversely increases the cognitive workload of the consumer, thereby degrading their decision quality and shopping experience. However, scientific evidence on the benefits of personalized recommendations remains inconsistent, giving rise to the idea that their effects may be muted unless the consumer is actually experiencing choice overload. The ability to test this idea is thus an important goal for marketing researchers, but challenging to achieve using conventional approaches. To overcome this challenge, the present study followed a design science approach while leveraging cognitive neuroscience to develop a real-time neuro-adaptive interface for e-commerce tasks. The function of the neuro-adaptive interface was to induce choice overload and permit comparisons of cognitive load and decision quality associated with personalized recommendations, which were presented according to the following three conditions: (a) not presented (control), (b) perpetually presented, or (c) presented only when a real-time neurophysiological index indicated that cognitive workload was high. Formative testing cycles produced a neuro-adaptive system in which the personalization of recommendations and neuro-adaptivity function as intended. The artifact is now ready for use in summative testing regarding the effects of personalized recommendations on cognitive workload and decision quality. Collapse

Topics: electronic commerce user interface usability laptop computer web application

Methods: electroencephalography design science self reported survey neurophysiology survey

Exploring the usage of Mixed Reality Dashboards in Business Intelligence and Analytics

2023 | European Conference On Information Systems | Citations: 0

Authors: Toreini, Peyman; Jahromi, Sina Mohazzeb

Abstract: Mixed reality (MR) devices such as HoloLens are expressed as one of the future ... Expand

Abstract: Mixed reality (MR) devices such as HoloLens are expressed as one of the future technology for working environments in Metaverse. However, it is still being determined how such technology can contribute to the Business Intelligence and Analytics (BI&A) context. In this study, following the problem-awareness step of a design science research (DSR) project, we conducted a preliminary user study on MR dashboards applied to the context of BI&A. To reach this goal, we first designed and developed HoloDash, an MR-based system that provides 2D, Cube, and 3D versions of dashboards. Later, we conducted a semi-structured interview, and ten BI&A users shared their opinions about the challenges and opportunities of using MR dashboards in BI&A based on HoloDash. Finally, we aggregated findings and identified nine requirements and three design principles that can serve as the basis for creating future effective MR-based dashboards by practitioners and researchers. Collapse

Topics: digital dashboard analytical information system pandemic mobile application decision quality

Methods: qualitative interview design principle design requirement design science theoretical contribution

Mixed Feelings: Effects of Mood Diversity on Groups’ Discussion of Disconfirming Information and Evaluation of Alternatives

2023 | Group Decision and Negotiation | Citations: 0

Authors: Tuncel, Ece; Doucet, Lorna

Abstract: In organizational groups, expertise and information are often distributed among ... Expand

Abstract: In organizational groups, expertise and information are often distributed among group members, thus making information sharing a necessity for group success. We examine the role of mood diversity on the discussion of disconfirming information and evaluation of decision alternatives in groups. In a laboratory experiment, using a hidden profile task, we manipulated mood diversity in 36 four-person, same-sex groups. Results indicated that mood diversity (vs. homogeneity) was positively related to groups’ focus on disconfirming information, which ultimately led to a more accurate evaluation of their decision alternatives. Results of the study expand our understanding of how mood composition of groups affects their discussion dynamics and decision evaluation. Collapse

Topics: decision making team productivity task characteristic decision quality information exchange

Methods: parametric test group interview one-way ANOVA experiment one sample t-test

The Effect of Online Review Portal Design: The Moderating Role of Explanations for Review Filtering

2023 | International Conference on Information Systems | Citations: 0

Authors: WANG, Guangxu; Xu, David (Jingjun); LIAO, Stephen Shaoyi

Abstract: The flood of non-constructive and fake online consumer reviews erects a conside ... Expand

Abstract: The flood of non-constructive and fake online consumer reviews erects a considerable barrier to consumers making efficient decisions. Various review filtering algorithms have been developed to address this challenge, but the design of post-development review portals continues to lack a consensus. In review portals, disclosing more transparent reviews is efficient for enhancing users' trust. However, it will cause users' diminished focus on recommended reviews, leading to sub-optimal decisions. A research model is then developed to investigate users' cognitive processes in their responses to three review exhibition designs (i.e., informed silent display design, filtered review display design, and composite display design) regarding trust in the review portal and perceived decision quality. We also suggest that explanations for review filtering play a moderating role in users' perceptions, which appears to be a viable resolution to this dilemma. This paper provides significant theoretical and practical insights for the review portal design and implementation. Collapse

Topics: algorithmic transparency decision quality electronic commerce

Methods: experiment experimental task survey statistical power analysis experimental group