Exploring the Synergies in Human-AI Hybrids: A Longitudinal Analysis in Sales Forecasting

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Fahse, Tobias; Schmitt, Anuschka

Abstract: Despite the promised potential of artificial intelligence (AI), insights into r ... Expand

Abstract: Despite the promised potential of artificial intelligence (AI), insights into real-life human-AI hybrids and their dynamics remain obscure. Based on digital trace data of over 1.4 million forecasting decisions over a 69-month period, we study the implications of an AI sales forecasting system's introduction in a bakery enterprise on decision-makers' overriding of the AI system and resulting hybrid performance. Decisionmakers quickly started to rely on AI forecasts, leading to lower forecast errors. Overall, human intervention deteriorated forecasting performance as overriding resulted in greater forecast error. The results confirm the notion that AI systems outperform humans in forecasting tasks. However, the results also indicate previously neglected, domain-specific implications: As the AI system aimed to reduce forecast error and thus overproduction, forecasting numbers decreased over time, and thereby also sales. We conclude that minimal forecast errors do not inevitably yield optimal business outcomes when detrimental human factors in decision-making are ignored. Collapse

Topics: artificial intelligence task productivity decision making IT productivity usability

Methods: digital trace data longitudinal research theory development ordinary least square qualitative interview

Theories: technology acceptance model socio technical theory

Conversational Agents in Service Context: Towards a Classification of Human-like Design Expectations

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Hildebrandt, Fabian; Lichtenberg, Sascha; Brendel, Alfred Benedikt; Riquel, Johannes; Dechant, David; Bönig, Fabian

Abstract: The increasing application of Conversational Agents (CAs) changes the way custo ... Expand

Abstract: The increasing application of Conversational Agents (CAs) changes the way customers and businesses interact during a service encounter. For instance, chatbots are the first point of contact for many customers. In this context, prior research has shown that CAs implemented with a human-like design lead to improved service satisfaction, perceived service quality, and trustworthiness, among others. Developers have become accustomed to adopting a one-size-fits-all approach by designing CAs human-like. However, not every human-to-human service requires the same social and human-like interaction (e.g., contract cancelation vs. doctors' appointment), which has also been shown in current research. At present, existing research lacks a synthesis of the relationship between CA design and service encounter context. Against this background, we conducted a literature review and derive classifications based on the dimensions of service context (professional/private) and human-like design (low/high), which enables the identification of relevant research gaps and related literature. Collapse

Topics: database system usability human computer interaction user expectation customer service

Methods: literature study literature sample synthesis experiment structured literature research

Designing an Artifact to Empower Chronic Patients for Monitoring Health During a Pandemic: A COVID-19 Screening App

2023 | HICSS | Citations: 0

Authors: John, Blooma; Jose, Savio; Thomas, Jackson; Kurian, Jayan

Abstract: Chronic diseases have been declared an invisible epidemic by the World Health Or ... Expand

Abstract: Chronic diseases have been declared an invisible epidemic by the World Health Organization (WHO, 2005). Over the past fifty years, the prevalence of chronic conditions has increased, leading to the disease burden caused by cancer, cardiovascular diseases, diabetes, and mental and substance use disorders (DOH, 2021). Chronic patients need to reimagine how they will empower themselves to effectively manage and monitor their health and wellbeing in a COVID-19 era when frequent in-person health care visits will no longer be feasible. In this study, we propose the dimensions for the design of a mobile-based application that will aid chronic patients and end-users in self-managing and monitoring their health during the pandemic era. Based on an empirical investigation involving pharmacists and researchers, we designed and developed a prototype capable of empowering chronic patients. This study particularly focuses on how technological interventions can help chronic patients self-manage and monitor their health and well-being related to COVID-19 where the user expectations are met with less attrition rates. Collapse

Topics: mobile application pandemic mobile health digital platform mobile system

Methods: literature study design principle design artifact design science

Using AI to Improve Sustainable Agricultural Practices: A Literature Review and Research Agenda

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

Authors: Lakshmi, Vijaya; Corbett, Jacqueline

Abstract: The world is confronted with the grand challenge of food insecurity amidst grow ... Expand

Abstract: The world is confronted with the grand challenge of food insecurity amidst growing populations and the climate crisis. Artificial intelligence (AI) deployed in agricultural decision support systems (AgriDSS) raises both hopes and concerns for increasing agricultural productivity in sustainable ways. We conduct a scoping review to uncover the roadblocks to the use of AI-supported AgriDSS in sustainable agriculture. Based on the corpus of 121 articles, we find that the effective use of AI-supported AgriDSS is hindered at technical, social, ethical, and ecological levels. Then, drawing on the experiential learning perspective, we propose how conjoint experiential learning (CEL) can enhance sustainable agricultural practices by enhancing both AI and human learning and overcoming roadblocks in using AgriDSS. Based on this conceptual framework, we build a research agenda that suggests blind spots and possible directions for future research. Collapse

Topics: artificial intelligence decision support system human computer interaction human in the loop decision making

Methods: literature sample literature study computational algorithm qualitative coding artificial neural network

A conceptual model of feedback mechanisms in adjusted affordances – Insights from usage of a mental mobile health application

2023 | International Journal of Information Management | Citations: 0

Authors: Meske, Christian; Amojo, Ireti; Thapa, Devinder

Abstract: Affordance theory provides one of the most prominent lenses through which the so ... Expand

Abstract: Affordance theory provides one of the most prominent lenses through which the socio-technical aspects of a system’s use can be investigated and understood. In this context, the literature has proposed that perceived and actualized affordances may be adjusted over time. Yet, how the adjustment of affordances occurs has not been explained in detail. Thus, in this article, we develop a conceptual model of feedback mechanisms that includes a more explicit description of how affordances are perceived by users, whether actualized and adjusted. With the model, we introduce the central concept of a generative base, out of which affordance perceptions emerge and which can be updated through affordance actualizations. With this base, we integrate mental model (MM) theory to explain better the differing perceptions before and after actor–artifact interactions. Our conceptual model is illustrated and specified using an empirical case of the mental mobile health (mHealth) app “Between The Lines” in Germany. In this study, we conducted 40 interviews in two rounds with 20 teenage app users. Our results show that the users’ perceptions of mHealth affordances become adjusted and hence change over time due to expe­ riencing the actualization process, which may lead to an update of the generative base, including the user’s MM. Collapse

Topics: affordance user experience usability mobile application mobile health

Methods: conceptual modelling qualitative interview case study single case study literature study

Theories: theory of affordance mental model theory

Eyes on the Prize: Increasing the Prize May Not Benefit the Contest Organizer in Multiple Online Contests

2023 | International Conference on Information Systems | Citations: 0

Authors: Rabinovitch, Sharon; Segev, Ella; Fink, Lior

Abstract: Given the proliferation of online platforms for crowdsourcing contests, we addr ... Expand

Abstract: Given the proliferation of online platforms for crowdsourcing contests, we address the inconsistencies in the extant literature about the behavioral effects of increasing the prize awarded by contest organizers. We endeavor to resolve these inconsistencies by analyzing user behavior in a highly controlled experimental setting in which users can participate (by exerting real effort rather than stated effort) in multiple online contests that vary only in their prizes. The analysis of the behavior of 731 active participants in our first experiment showed that both participation and effort were non-monotonic with the prize, that the low-prize contest was the most effective for the organizers, and that increasing the prize of the low-prize or high-prize contest by 50% actually decreased the benefits for organizers. Our findings advance theory by providing insight into when and why extrinsic incentives fail to produce the desired effects in crowdsourcing contests. Collapse

Topics: crowdsourcing website user behavior participatory design logistics management

Methods: experiment regression analysis method design methodology qualitativ observational study

Theories: game theory

A Matter of Trust: How Trust in AI-Based Systems Changes During Interaction

2023 | Americas Conference on Information Systems | Citations: 0

Authors: de Zoeten, Marc; Ernst, Claus-Peter; Rothlauf, Franz

Abstract: Artificial intelligence (AI) automates decisions, usually without any transpare ... Expand

Abstract: Artificial intelligence (AI) automates decisions, usually without any transparency or insight into its internal mechanisms. Often, missing transparency results in a lack of trust in these systems, reducing their usage and adoption. Explainable AI and the provision of explanations were designed to address these shortcomings. However, the exact effects of explanations remain ambiguous in the literature. We address this empirically by measuring trust at multiple points throughout the interaction with a system. We find the effect of global explanations to be highly dependent on the level of trust already exhibited before receiving the explanations. Furthermore, we find local explanations to only be of use in the case of an expectation violation. Ultimately, the trust recovered with the help of a local explanation cannot entirely make up for the loss of trust associated with an expectation violation. Collapse

Topics: artificial intelligence IS impact user expectation decision support system explainable artificial intelligence

Methods: experiment descriptive statistic Student's t-test field experiment

Meta-Analysis of the Unified Theory of Acceptance and Use of Technology (UTAUT): Challenging its Validity and Charting a Research Agenda in the Red Ocean

2022 | Journal of the Association for Information Systems | Citations: 0

Authors: Blut, Markus; Chong, Alain; Tsigna, Zayyad; Venkatesh, Viswanath

Abstract: There are both formal and informal cries that UTAUT and, by association, the st ... Expand

Abstract: There are both formal and informal cries that UTAUT and, by association, the stream of research on technology adoption has reached its limit, with little or no opportunities for new knowledge creation. Such a conclusion is ironic because the theory has not been sufficiently and suitably replicated. It is possible that misspecifications in the various replications, applications, and extensions have led to the incorrect conclusion that UTAUT is more robust than it really is, leaving limited opportunities for future work. Although work on UTAUT has included important variables, predictors, and moderators, absent a faithful use of the original specification, it is impossible to assess the true nature of the effects of the original and additional variables. The present meta-analysis uses 25,619 effect sizes reported by 737,112 users in 1,935 independent samples to address this issue. Consequently, we develop a clear current state-of-the-art and revised UTAUT that extends the original theory with new endogenous mechanisms from different, other theories (i.e., technology compatibility, user education, personal innovativeness, and costs of technology) and new moderating mechanisms to examine the generalizability of UTAUT in different contexts (e.g., technology type and national culture). Based on this revised UTAUT, we present a research agenda that can guide future research on the topic of technology adoption in general and UTAUT in particular. Collapse

Topics: social influence behavioral intention information system use national culture mobile system

Methods: meta analysis structural equation modeling F-test statistical power analysis chi squared test

Theories: unified theory of acceptance and use of technology extended unified theory of acceptance and use of technology

Introduction to the Digital Government and Artificial Intelligence Minitrack

2022 | HICSS | Citations: 0

Authors: Carter, Lemuria; Grimmelikhuijsen, Stephan; Gascó-Hernández, Mila; Bannister, Frank; Bannister, Frank

Abstract: ... Expand

Abstract: Collapse

Topics: artificial intelligence user satisfaction pandemic contact tracing mobile application digital ecosystem

Methods: natural language processing survey chatbot

Towards designing assistants for well-being: clarifying the relationship between users’ intrinsic motivation and expectations from assistants

2022 | International Conference on Information Systems | Citations: 0

Authors: Dhiman, Hitesh; Nemoto, Yutaro; Mühlan, Holger; Fellmann, Michael; Röcker, Carsten

Abstract: Although considerable research effort has been devoted to understanding the ado ... Expand

Abstract: Although considerable research effort has been devoted to understanding the adoption and use of commercially available intelligent assistants, the relationship between user expectations from assistants and users' endogenous intrinsic motivation to perform an activity has not been explored. Doing so is important to meet user expectations, prevent adoption failures, and design for well-being. In this paper, we investigate whether a person's intrinsic motivation to perform an activity impacts (a) their expectations from an assistant, and, (b) the assistant feature set chosen to meet these expectations. Via a survey based study with N=296 participants, we provide empirical evidence showing that, after controlling for demographic factors, users' prior, endogenous intrinsic motivation influences their intrinsic expectations for competence, stimulation and influence, but not extrinsic and hedonic expectations. Users with low prior motivation prefer an assistant in a supervisor role. Implications for research and practice are discussed. Collapse

Topics: intrinsic motivation user expectation usability personalization human computer interaction

Methods: survey regression analysis method analysis of covariance Levene's test design artifact

Theories: cultural dimensions theory self determination theory