Two Sides of the Same Pillow: Unfolding the Relationship between Objective and Subjective Sleep Quality with Unsupervised Learning

2023 | International Conference on Information Systems | Citations: 0

Authors: Biedebach, Luka; Óskarsdóttir, María; Arnardottir, Erna; Islind, Anna Sigríður

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Topics: mobile system smart watch mobile application smart wearable device healthcare data

Methods: descriptive statistic cluster analysis parametric test ANOVA longitudinal research

Too Good to Be True? An Empirical Study of ChatGPT Capabilities for Academic Writing and Implications for Academic Misconduct

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Busch, Peter André; Hausvik, Geir Inge

Abstract: This study evaluated the capabilities of ChatGPT, a conversational artificial i ... Expand

Abstract: This study evaluated the capabilities of ChatGPT, a conversational artificial intelligence (AI) agent, to generate quality answers to exam questions that are indistinguishable from human-generated text, normally requiring high-level cognitive abilities. This potential capacity is a major threat to academic integrity since ChatGPT may be used for academic misconduct. To determine its capabilities, we asked 15 faculty members to assess a total of ten answers (two each) to an actual IS exam question, of which students wrote five, and ChatGPT generated five. The study found that ChatGPT can generate answers of generally good quality that may pass as human-written text by examiners. The contributions of the study lay in providing empirical results in a novel research area, providing recommendations for teachers, and suggesting ways forward for research. Collapse

Topics: artificial intelligence smartphone evaluation criteria smartphone addiction mobile system

Methods: chatGPT machine learning descriptive statistic correlation analysis personal interview

Cultivating a Leadership Pipeline: Using a Real Options Lens to Understand Executives’ Strategic Staffing Decisions

2023 | Organization Science | Citations: 0

Authors: Campion, Michael C.; Campion, Emily D.; Campion, Michael A.; Bauer, Talya N.

Abstract: This paper adapts real options theory to explain how executives create and maint ... Expand

Abstract: This paper adapts real options theory to explain how executives create and maintain real options portfolios within leadership pipelines. Hypotheses flowing from our theorizing predict that executives often make seemingly risky staffing decisions for leaders who occupy stepping-stone positions. Focusing on their option (future potential) rather than project (current productivity) value, executives laterally transfer leaders in stepping-stone positions frequently, despite it resulting in lower short-term job performance, but often promote these leaders at lower levels of performance and sooner. Once leaders are promoted to destination positions where they may stay indefinitely, executives tend to transfer high-performing leaders more often but not when they are still improving the effectiveness of their current unit. We present evidence suggesting that executives make these decisions to improve other units and maintain a flexible system, possibly recapturing previous investments in developing those leaders. We provide empirical support for our hypotheses using eight years of data in a large retail organization (n = 25,004) where executives overseeing thousands of units made internal mobility decisions. These findings refine real options theory, show that it explains these phenomena better than existing theories, and provide important and immediately usable practical implications for executives. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1608. Collapse

Topics: task productivity real option IT career productivity human resource management

Methods: statistical hypothesis test descriptive statistic theory development logistic regression focus group

Theories: real options theory options theory

Unraveling the behavioral influence of social media on phishing susceptibility: A Personality-Habit-Information Processing model

2023 | Information & Management | Citations: 0

Authors: Frauenstein, Edwin Donald; Flowerday, Stephen; Mishi, Syden; Warkentin, Merrill

Abstract: Frequent and habitual engagement with social media can reinforce certain activit ... Expand

Abstract: Frequent and habitual engagement with social media can reinforce certain activities such as sharing, clicking hyperlinks, and liking, which may be performed with insufficient cognition. In this study, we aimed to examine the associations between personality traits, habits, and information processing to identify social media users who are susceptible to phishing attacks. Our experimental data consisted of 215 social media users. The results revealed two important findings. First, users who scored high on the personality traits of extraversion, agree­ ableness, and neuroticism were more likely to engage in habitual behaviors that increase their susceptibility to phishing attacks, whereas those who scored high on conscientiousness were less likely. Second, users who habitually react to social media posts were more likely to apply heuristic processing, making them more sus­ ceptible to phishing attacks than those who applied systematic processing. Collapse

Topics: phishing Facebook personality social media electronic mail

Methods: survey structural equation modeling survey design theory development self reported survey

Theories: big five model Maslow motivation theory uses and gratifications theory technology acceptance model theory of planned behavior

Building an Equilibrium: Rules vs. Principles in Relational Contracts

2023 | Organization Science | Citations: 0

Authors: Gibbons, Robert; Grieder, Manuel; Herz, Holger; Zehnder, Christian

Abstract: Effective collaboration within and between organizations requires efficient adap ... Expand

Abstract: Effective collaboration within and between organizations requires efficient adaptation to unforeseen change. We study how parties build relational contracts that achieve this goal. We focus on the “clarity problem”—whether parties have a shared understanding of the promises they make to each other. Specifically, (a) a buyer and seller play a trading game in several periods; (b) they know their environment will change but do not know how; and (c) before any trading occurs, they can reach a nonbinding agreement about how to play the entire game. We hypothesize that pairs whose initial agreement defines a broad principle rather than a narrow rule are more successful in solving the clarity problem and in achieving efficient adaptation after unforeseen change. In our baseline condition, we indeed observe that pairs who articulate principles achieve significantly higher performance after change occurred. Underlying this correlation, we also find that pairs with principle-based agreements were more likely to both expect and take actions that were consistent with what their agreement prescribed. To investigate a causal link between principle-based agreements and performance, we implement a “nudge” intervention that induces more pairs to articulate principles. The intervention succeeds in coordinating more pairs on efficient quality immediately after the unforeseen change, but it fails to coordinate expectations on price, ultimately leading to conflicts and preventing an increase in long-run performance after the shock. Our results suggest that (1) principle-based agreements may improve organizational performance but (2) high-performing relational contracts may be difficult to build.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: We gratefully acknowledge financial support from the Massachusetts Institute of Technology Sloan School's Program on Innovation in Markets and Organizations.Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1503. Collapse

Topics: competitive advantage organizational productivity organizational culture anonymity

Methods: experiment descriptive statistic survey laboratory experiment statistical power analysis

Theories: game theory organizational theory

Working with AI: How Attitudes Shape Human-AI Collaboration

2023 | International Conference on Information Systems | Citations: 0

Authors: Glienke, Maximilian; Hartwich, Nicole; Antons, David

Abstract: Recent research shows that people tend to avoid relying on artificial intellige ... Expand

Abstract: Recent research shows that people tend to avoid relying on artificial intelligence (AI) when making decisions at work. Although previous studies have investigated the causes and effects of this phenomenon, the role of attitudes, which are considered as a crucial factor in biased decision-making, remains unexplored. To investigate whether and how attitudes toward AI influence decision-making in work-related situations, we developed and conducted a lab experiment in which 156 participants received AI advice on process improvement while performing a manufacturing task. Our results suggest that negative attitudes toward AI are associated with greater reluctance to accept AI advice, resulting in lower performance in work-related situations. Furthermore, we show that human involvement in the process of providing AI advice cannot mitigate the negative effects of strong negative attitudes. Collapse

Topics: artificial intelligence decision making business process improvement human AI collaboration task productivity

Methods: experiment experimental group computational algorithm laboratory experiment regression analysis method

Theories: attitude theory

Market Valuation of Artificial Intelligence Implementation Announcements

2023 | ACM SIGMIS Database | Citations: 0

Authors: Huang, Cheng-Kui (Tony); Lee, Yu-Tsung

Abstract: With the advent of artificial intelligence (AI), more and more enterprises have ... Expand

Abstract: With the advent of artificial intelligence (AI), more and more enterprises have begun developing AI to promote their own competitive advantage and increase their business value. In order to reveal the value-added results of AI implementation, this study adopts an event study methodology to capture the abnormal returns resulting from the announcement of AI implementation. Based on the empirical results of this study, in response to the announcement of AI implementation, we find significant positive abnormal returns on the event day. With respect to the grouping analysis, the results show significant differences in average cumulative abnormal returns between announcements with detailed information and those without detailed information. In addition, our findings present significant differences in average cumulative abnormal returns between IT-companies and non-IT companies on the event day. Ultimately, according to the content analysis, only one characteristic, the frequency of negative words, is modestly and negatively correlated with average cumulative abnormal returns. Collapse

Topics: artificial intelligence organizational value robotic information management Java

Methods: regression analysis method event study longitudinal research qualitative content analysis descriptive statistic

Theories: signaling theory

Can Conversations on Reddit Forecast Future Economic Uncertainty? An Interpretable Machine Learning Approach

2023 | International Conference on Information Systems | Citations: 0

Authors: Jiang, Jinhang; Feng, Mei; Srinivasan, Karthik

Abstract: In recent years, social media has become an indispensable source of information ... Expand

Abstract: In recent years, social media has become an indispensable source of information through which public attitudes, opinions, and concerns can be studied and quantified. This paper proposes an interpretable machine learning framework for predicting the Equity Market-related Economic Uncertainty Index using features generated from a popular discussion forum on Reddit. Our framework consists of a series of custom preprocessing and analytics methods, including BERTopic for latent topic identification and regularized linear models. Using our framework, we evaluate explanatory models with different configurations over a large corpus of Reddit posts belonging to the personal finance category. Our analysis generates valuable insights about discussion topics on Reddit and their efficacy in accurately predicting future economic uncertainty. The study demonstrates the potential of using social media data and interpretable machine learning to inform economic forecasting research. Collapse

Topics: Reddit social media explainable artificial intelligence Python permutation feature importance

Methods: descriptive statistic time series analysis longitudinal research topic model experiment

IT Security and Espoused Cultural Values: A Comparative Analysis of Pakistan and the United States

2023 | Americas Conference on Information Systems | Citations: 0

Authors: John, Asher; Polites, Greta

Abstract: Information technology (IT) security research has investigated how users percei ... Expand

Abstract: Information technology (IT) security research has investigated how users perceive and address IT security threats differently based on their cultural backgrounds and espoused cultural values. We extend prior research, grounded in Protection Motivation Theory (Rogers 1975), that has examined how espoused cultural values influence the relationship between perceived coping efficacy and coping behaviors. Our research model includes two infrequently studied cultural dimensions: indulgence vs. restraint (Hofstede 2022) and survival vs. self-expression (Inglehart-Welzel 2005). The model will be tested using survey data from mid-level managers in the US and Pakistan. The study offers a more nuanced understanding of the impact of cultural factors on the adoption and implementation of IT security measures in diverse organizational contexts. It further contributes to practice by offering guidance to organizations who must design security training and other intervention strategies to modify employee security behaviors. Collapse

Topics: self efficacy IT security cross cultural research information system use national culture

Methods: structural equation modeling descriptive statistic survey

Theories: protection motivation theory

Bringing Light into the Dark - Improving Students’ Black-Box Testing Competencies using Game-Design Elements

2023 | International Conference on Information Systems | Citations: 0

Authors: Jokisch, Christine; Hobert, Sebastian; Schumann, Matthias

Abstract: As software becomes increasingly complex, there is a growing need to enhance qu ... Expand

Abstract: As software becomes increasingly complex, there is a growing need to enhance quality assurance in software engineering. However, the lack of qualified human resources is a barrier to performing software testing activities in software companies. At the same time, software testing can be considered a tedious task and is often not done at the necessary level of detail, e.g., designing test cases. However, it is crucial for novice programmers and testers to acquire and improve their testing competencies, and to utilize testing techniques, e.g., black-box testing. Teaching software testing is often based on theoretical instructions, resulting in limited practical experience. As a result, students may not develop the necessary testing mindset, highlighting the need for more extensive software testing education. To address this issue, this paper utilizes a design science research approach to implement a gamified learning system that promotes black-box testing competencies with empirical insights from a field test. Collapse

Topics: online learning system usability perceived usefulness gamification web application

Methods: design artifact testing descriptive statistic correlation analysis design science survey

Theories: self determination theory cognitive load theory