Modern Centaurs: How Humans and AI Systems Interact in Sales Forecasting

2023 | European Conference On Information Systems | Citations: 0

Authors: Beese, Jannis; Fahse, Tobias

Abstract: Recent achievements of artificial intelligence (AI) have caused organizations t ... Expand

Abstract: Recent achievements of artificial intelligence (AI) have caused organizations to increasingly bring AI capabilities into their core business processes. Such AI-supported business processes often result in human-AI hybrid systems, which consist of an AI system, which performs most of the execution, and humans, who monitor this execution and occasionally provide additional inputs and overrides. Using sales data from Walmart, we conduct an online study to investigate if human supervision can improve upon state-of-the-art AI forecasts. Furthermore, we analyze the perceptions and behavioral intentions of the human participants over time. We find that human interventions consistently lead to less accurate forecasts and that participants initially underestimate the AI system's accuracy and overestimate their own potential to improve upon AI forecasts. However, perceptions quickly shift over the course of the study, causing the participants to perceive the AI system increasingly favorably, which also leads to behavioral changes and better hybrid system performance. Collapse

Topics: artificial intelligence IT productivity information system use task productivity perceived usefulness

Methods: regression analysis method survey LightGBM conceptual modelling experiment

Theories: technology acceptance model

Valuing Flexibility in Low Carbon Electricity Portfolios

2023 | HICSS | Citations: 0

Authors: Blumsack, S.

Abstract: With the increased focus on responding to climate change by accelerating a tran ... Expand

Abstract: With the increased focus on responding to climate change by accelerating a transition to a low carbon energy system, differing views remain on the combination of energy technologies that will best achieve this goal. Identifying technological pathways is complicated by wide uncertainties in economic and technological factors. Analyses that neglect these uncertainties can produce pathways for a low carbon energy future that are highly granular and specific, but which are based on a particular assumption about future conditions and imply a need to make specific technology commitments over a long period of time. We frame the energy transition problem as the identification of one near-term investment strategy that is flexible across a wide range of possible future costs, followed by many alternative subsequent investment plans, each of which responds to realized future costs to achieve an aggressive emissions reduction target. Using an example of planning a low carbon power system under uncertainty, we demonstrate the option value of not ruling out some energy technologies in the near-term. Collapse

Topics: energy information system IT investment technological change

Methods: support vector machine case study machine learning stochastic model descriptive statistic

Social Determinants of Health and ER Utilization: Role of Information Integration during COVID-19

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

Authors: Guo, Tianjian; Bardhan, Indranil; Khurshid, Anjum

Abstract: Emergency room (ER) admissions are the front door for the utilization of a commu ... Expand

Abstract: Emergency room (ER) admissions are the front door for the utilization of a community's health resources and serve as a valuable proxy for a community health system's capacity. While recent research suggests that social determinants of health (SDOH) are important predictors of patient health outcomes, their impact on ER utilization during the COVID-19 pandemic is not well understood. Further, the role of hospital information integration in moderating the impact of SDOH on ER utilization has not received adequate attention. Utilizing longitudinal claims data from a regional health information exchange spanning 6 years including the COVID-19 period, we study how SDOH affects ER utilization and whether effective integration of patient health information across hospitals can moderate its impact. Our results suggest that a patient's economic well-being significantly reduces future ER utilization. The magnitude of this relationship is significant when patients are treated at hospitals with high information integration but is weaker when patients receive care at hospitals with lower levels of information integration. Instead, patients' family and social support can reduce ER utilization when they are treated at hospitals with low information integration. In other words, different dimensions of SDOH are important in low versus high information integration conditions. Furthermore, predictive modeling shows that patient visit type and prior visit history can significantly improve the predictive accuracy of ER utilization. Our research implications support efforts to develop national standards for the collection and sharing of SDOH data and their use and interpretation for clinical decision making by healthcare providers and policy makers. Collapse

Topics: healthcare data pandemic information exchange accounting health information system

Methods: experimental group machine learning XGBoost longitudinal research econometric modeling

Preventive Care Now or Pay Later? A Personalized Medicine Approach for Healthcare Management

2023 | International Conference on Information Systems | Citations: 0

Authors: Guo, Tianjian; Bardhan, Indranil; Wen, Wen

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Topics: health information system mobile system information exchange Python price management

Methods: simulation reinforcement learning Markov decision process PyTorch deep learning

MANTRA: A Topic Modeling-Based Tool to Support Automated Trend Analysis on Unstructured Social Media Data

2023 | International Conference on Information Systems | Citations: 0

Authors: Konadl, Daniel; Wörner, Janik; Schmid, Isabel; Leist, Susanne

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Topics: marketing management social media new product development social media analytics spreadsheet

Methods: topic model machine learning design theory survey kernel theory

Theories: innovation theory

Analyzing Energy Consumption of Appliances in Smart Grids

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Lee, Jonathan; Gupta, Ashish

Abstract: Modern power grids are undergoing many changes to meet the growing energy deman ... Expand

Abstract: Modern power grids are undergoing many changes to meet the growing energy demand. A major limitation of traditional power grids is that they only allow for understanding the overall household's total consumption, which is typically measured with high latency over the entire billing period. Smart grids and smart meters, on the other hand, enable access to timely household data. When such grids are equipped with the ability to read device-level data then they can be used to provide deeper analytic insights into energy utilization patterns at a very granular level. In this study, we propose using Dynamic Time Warping as a distance metric for clustering to examine consumers' device-level energy consumption for four different geographic regions. Additional insight into device-level usage patterns for consumers is likely to lead us to develop persuasive IS systems that can improve energy efficiency and bring benefits to both power suppliers and power consumers. Collapse

Topics: persuasive information system Python database system accounting

Methods: longitudinal research time series analysis linear regression analysis cluster analysis agglomerative hierarchical clustering

Introduction to the Special Issue on IT-enabled Business Management and Decision Making in the (Post) Covid-19 Era

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

Authors: Li, Xin; Kwon, Juhee; Padmanabhan, Balaji; Zhang, Pengzhu

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Topics: covid 19 pandemic IT supported collaboration remote work systems design

Methods: longitudinal research computational algorithm chatbot experiment

Theories: theory of affordance

An Approach for the Direct Inclusion of Weather Information in the Power Flow

2023 | HICSS | Citations: 0

Authors: Overbye, T.; Safdarian, F.; Trinh, W.; Mao, Z.; Snodgrass, J.; Yeo, J.

Abstract: While it is widely recognized that weather impacts the power flow, historically ... Expand

Abstract: While it is widely recognized that weather impacts the power flow, historically weather information has only been implicitly included. This paper presents an approach for the direct inclusion of weather information in the power flow. Key issues addressed by the paper include the availability of weather information, the mapping of weather information to electric grid components, a flexible and extensible modeling approach for relating weather values to the power flow models, and the visualization of the weather impacts. The approach is demonstrated on several electric grids ranging in size from 7000 to 82,000 buses using weather data over several different years. Collapse

Topics: cloud computing geographic information system

Methods: computational algorithm

Anchoring on Historical Round Number Reference Points: Evidence from Durable Goods Resale Prices

2023 | Organization Science | Citations: 0

Authors: Wiltermuth, Scott S.; Gubler, Timothy; Pierce, Lamar

Abstract: This paper examines how people price the resale of durable goods in systematical ... Expand

Abstract: This paper examines how people price the resale of durable goods in systematically biased ways. We show across four studies that the anchoring effect of durable goods’ prior sales prices on subsequent valuations is discontinuous at psychologically salient round number reference points (e.g., $10,000 increments) because these numbers create qualitative differences in how people perceive values below them versus values at/above them. Resellers set disproportionately larger subsequent prices when previous prices move from just below round number thresholds (e.g., $349,000) to those at or just above these thresholds (e.g., $351,000). The findings show that buyers who pay a price just below a round number, therefore, may sacrifice money because they receive disproportionately less when reselling the good. Market forces only partially attenuate this pricing bias, but valuator experience seems to play a moderating role. Archival data show that home buyers who previously paid just under a $10,000 reference point subsequently listed their homes for about 1.8% (over $3,700) less on average than did buyers selling comparable homes who previously paid at or above a round number threshold. This drop is observable controlling for home characteristics and the general relationship between previous and current prices. Three experimental studies looking at housing and used car markets replicate these findings, highlight the mechanism, and increase confidence in causality. Market mechanisms and the negotiation process attenuate discontinuities by about 30%, but lower initial listing prices persist to final sales prices. We find additional weak evidence suggesting that valuator experience may attenuate intergenerational pricing bias. Conflict of Interest: This manuscript was submitted, revised, and accepted prior to the nomination and appointment of Lamar Pierce as Editor-in-Chief. Funding: This project was supported by the University of Southern California Marshall School of Business Behavioral Laboratory. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1632. Collapse

Topics: price management computer hardware decision making human resource management website

Methods: experiment Wald test descriptive statistic parametric test hierarchical linear modeling

Managing information for innovation using knowledge integration capability: The role of boundary spanning objects

2022 | International Journal of Information Management | Citations: 7

Authors: Acharya, Chandan; Ojha, Divesh; Gokhale, Rahul; Patel, Pankaj C.

Abstract: Knowledge Integration (KI) or the capability to collate and process distinctive ... Expand

Abstract: Knowledge Integration (KI) or the capability to collate and process distinctive stocks of organizational infor­ mation is central to innovation. Although an essential capability, KI is also challenging to accomplish in practice due to relational obstacles. The relational obstacles arise because of knowledge boundaries: (a) syntactic boundary where the challenge is to transfer the knowledge; (b) semantic boundary where the challenge is to translate the knowledge; and (c) pragmatic boundary, where the challenge is to transform the knowledge to realize relational rents. In this paper, we propose that these relational obstacles could be resolved through a common lexicon, common meaning, and common interests, or common knowledge of knowledge actors that can serve as potential drivers to realizing relational rents. Analysis of data collected from 139 small firms indicates that common meaning and common interests positively influence KI. Further, KI positively influences organi­ zational innovation. Moreover, the results demonstrate that novelty plays a crucial role in affecting the strength of relational resources’ relationships with KI capability. As novelty increases, the importance of common meaning and common interests on KI capability increases. Our findings contribute to our understanding of the role of relational obstacles and KI and empirically assess the efficacy of boundary-spanning objects in facilitating KI capability and innovation. Collapse

Topics: boundary spanning innovation management research and development knowledge management missing data

Methods: survey data transformation structural equation modeling linear regression analysis factor analysis

Theories: boundary objects theory management theory social capital theory