[AISWorld] 6 CFPs @SIGDSA-AMCIS-2023

[Matta, Vic]

There’s still time to send in working paper to SIGDSA @AMCIS2023!

Panama City, Panama, August 10-12, 2023
Paper submission deadline: March 1 (10:00am Eastern Standard Time, US)
Submission link: https://new.precisionconference.com/amcis23c
More information at: https://amcis2023.aisconferences.org/track-descriptions

SIGDSA (SPECIAL INTEREST GROUP IN DECISION SCIENCES AND ANALYTICS)

Organizations are allocating resources to improve and develop innovative applications with advanced analytics or AI capabilities. As organizations transform into analytics-centric enterprises (e.g., health insurers and automotive companies), more research is needed on the technical, behavioral, and organizational aspects of this progress. The “Data Science and Analytics for Decision Support” track at AMCIS 2023 seeks original research that advances technical, theoretical, design, pedagogical, and behavioral science research and emerging applications related to analytics, AI, and Big Data.

There are six mini tracks (and chairs). See

1. AI AND DATA ANALYTICS IN HEALTHCARE

AI and Data Analytics in Healthcare:
Focus: to apply analytics, machine learning, and artificial intelligence over big data to identify actionable patterns and correlations for improving healthcare delivery.
Suggested Topics: solutions to the existing challenges; improving the current solutions; provide insights into adverse consequences of AI and analytics in the healthcare area.
Raj Sharman, University at Buffalo, SUNY, rsharman at buffalo.edu<mailto:rsharman at buffalo.edu>
Pavankumar Mulgund, The University of Memphis, pmulgund at memphis.edu<mailto:pmulgund at memphis.edu>
Joana Gaia, School of Management, University at Buffalo,, joanaalu at buffalo.edu<mailto:joanaalu at buffalo.edu>

2. BEHAVIORAL RESEARCH IN DATA SCIENCE AND ANALYTICS

Focus: to enhance understanding of the behavioral aspects of implementing and using DA and AI technologies in organizational and social settings by exploring perceptions, attitudes, intentions related to analytics and their impact on decision-making processes and outcomes.
Suggested topics: Explainable AI; Ethical and privacy aspects of using AI and DA; Trust in AI and DA; Human-AI augmentation; Algorithm aversion; User-centered DA; DA and decision-making quality; DA and technostress; DA and discrimination; DA and cognitive biases.

Nima Kordzadeh, Worcester Polytechnic Institute, nkordzadeh at wpi.edu<mailto:nkordzadeh at wpi.edu>
Maryam Ghasemaghaei, McMaster University, ghasemm at mcmaster.ca<mailto:ghasemm at mcmaster.ca>


3. SMART TOURISM AND DATA ANALYTICS

Focus: application of data science and data analytics to promote and investigate smart tourism. Suggested Topics: data analytics for tourism decision-making; social media data analytics for destination management; big data analytics for destination management; data analysis and modeling of tourist behavioral data; tourism intelligence and visual data analytics for destination management; analytics for tourism planning; management, and marketing; tourism information management and advanced analytics.

Jahyun Goo, Florida Atlantic University, jgoo at fau.edu<mailto:jgoo at fau.edu>
Derrick Huang, Florida Atlantic University, dhuang at fau.edu<mailto:dhuang at fau.edu>
Chul Woo Yoo, Florida Atlantic University, yooc at fau.edu<mailto:yooc at fau.edu>
Chulmo Koo, Kyung Hee University, helmetgu at khu.ac.kr<mailto:helmetgu at khu.ac.kr>
Sooyoung Park, Florida Atlantic University, soyoungpark at fau.edu<mailto:soyoungpark at fau.edu>


4. COMPUTATIONAL SOCIAL SCIENCE RESEARCH THROUGH ANALYTICS
Focus: to encourage research using trace data from human digital footprint to investigate human activities and relationships to provide innovative and theory-grounded models of the social phenomena.
Suggested Topics: descriptive research process; novel algorithm designs; question forming; new and interesting directions in computational social science; formulation of nascent theories through a bottom-up approach using data.
Ace Vo, Loyola Marymount University, ace.vo at lmu.edu<mailto:ace.vo at lmu.edu>
Yan Li, Claremont Graduate University, yan.li at cgu.edu<mailto:yan.li at cgu.edu>
Anitha Chennamaneni, Texas A & M University Central Texas, anitha.chennamaneni at tamuct.edu<mailto:anitha.chennamaneni at tamuct.edu>

5. THE GEOSPATIAL REALM: A DEEP DIVE

Focus: Using AI to understand interaction of humans in their physical environment to address issues plaguing our society.
Suggested Topics: innovation and collaboration using geospatial platforms and analytics; geospatial AI with Machine Learning and Deep Learning; geospatial big data management and analytics; geospatial data mining and knowledge discovery; geospatial decision making and knowledge management; and emerging areas of geospatial analytics.

Brian Hilton, Claremont Graduate University, brian.hilton at cgu.edu<mailto:brian.hilton at cgu.edu>
Daniel Farkas, Pace University, djf2128 at gmail.com<mailto:djf2128 at gmail.com>
Namchul Shin, Pace University, nshin at pace.edu<mailto:nshin at pace.edu>
James Pick, University of Redlands, james_pick at redlands.edu<mailto:james_pick at redlands.edu>
Avijit Sarkar, University of Redlands, avijit_sarkar at redlands.edu<mailto:avijit_sarkar at redlands.edu>


6. DATA-DRIVEN PROCESS MINING AND INNOVATION
Focus: to discover, monitor, and improve actual business processes by extracting knowledge from existing data generated as a result of the execution of those processes.
Suggested Topics: data-driven modeling, analysis and improvement of organizational processes; design of data-driven decision-making processes; case studies and empirical evaluation of data-driven process innovation; multi-perspective approaches for process mining.
Arti Mann, University of Northern Iowa, arti.mann at uni.edu<mailto:arti.mann at uni.edu>
Sagnika Sen, Pennsylvania State University, sagnika.sen at psu.edu<mailto:sagnika.sen at psu.edu>

AMCIS 2023 SIGDSA Track Chairs,
Ciara Heavin
Ales Popovich
Vic Matta