[AISWorld] AMCIS 2023 CFP (Last Call): Behavioral Research in Data Science and Analytics (Track: SIGDSA)

[Nima Kordzadeh]

*Mini-track: *Behavioral Research in Data Science and Analytics

*Track:* Data Science and Analytics for Decision Support (SIGDSA)


Panama City, Panama -- August 10-12, 2023

https://amcis2023.aisconferences.org/track-descriptions/#toggle-id-9



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*Mini-track Description:*



The ability to take advantage of data analytics tools and AI technologies
has become an important factor for firm success [1, 2]. With the
availability of data with high velocity, volume, and variety, many firms
have invested in business intelligence and data analytics tools and
technologies to improve the quality of their decisions. However, firms also
recognize the importance of human cognition, judgment, and behavior in
developing, implementing, and using such technologies. For example, data
analysts need to integrate aspects that are not captured by analytical
tools, such as ethical principles and intuition, into their analytics
processes and decisions [3, 4].



The focus of this minitrack is to explore and enhance understanding of the
behavioral aspects of AI and analytics technologies. In particular, this
minitrack focuses on perceptions, attitudes, beliefs, intentions, and
behaviors related to AI and analytics and their potential impacts on
decision-making processes and outcomes in organizational and social
settings [5].



Suggested topics include, but are not limited to:



* Explainable AI and DA

* Ethical and privacy aspects of AI and DA

* Trust in AI and DA

* Human-AI augmentation

* Algorithm aversion

* Algorithmic bias and discrimination

* User-centered DA

* DA and decision-making quality

* DA and cognitive biases



*References:*



*1.* Chen H, Chiang RH, & Storey VC. (2012). Business Intelligence and
Analytics: from Big Data to Big Impact; *MIS Quarterly*.36(4): 1165 – 1188;
https://doi.org/10.2307/41703503
<https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.2307%2F41703503&data=04%7C01%7Cnkordzadeh%40wpi.edu%7C54025d450243468fc0bc08d9f1d10488%7C589c76f5ca1541f9884b55ec15a0672a%7C0%7C0%7C637806702337880211%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=nyJzK5DA3iUpfbHySswgm7cx%2BFCJpiUc1CTRalq9BdM%3D&reserved=0>

*2.* Duan Y, Edwards JS, & Dwivedi YK. (2019). Artificial Intelligence for
Decision Making in the Era of Big Data–Evolution, Challenges and Research
Agenda; *International Journal of Information Management*. 48: 63 – 71;
https://doi.org/10.1016/j.ijinfomgt.2019.01.021
<https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1016%2Fj.ijinfomgt.2019.01.021&data=04%7C01%7Cnkordzadeh%40wpi.edu%7C54025d450243468fc0bc08d9f1d10488%7C589c76f5ca1541f9884b55ec15a0672a%7C0%7C0%7C637806702337880211%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=%2FJ%2Fueuf38swJl7brTKwll5UF%2FvLKGe0sh9zP5s4vZ%2FQ%3D&reserved=0>

*3.* Kordzadeh, N., & Ghasemaghaei, M. (2022). Algorithmic Bias: Review,
Synthesis, and Future Research Directions; *European Journal of Information
Systems*. 31(3): 388 – 409; https://doi.org/10.1080/0960085X.2021.1927212
<https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1080%2F0960085X.2021.1927212&data=04%7C01%7Cnkordzadeh%40wpi.edu%7C54025d450243468fc0bc08d9f1d10488%7C589c76f5ca1541f9884b55ec15a0672a%7C0%7C0%7C637806702337880211%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=rZtFOnMffcmRaq2Xs3TxT0a9sl%2FhAeCwciaTOqzyJII%3D&reserved=0>

*4.* Someh, I., Davern, M., Breidbach, C. F., & Shanks, G. (2019). Ethical
Issues in Big Data Analytics: A Stakeholder Perspective; *Communications of
the Association for Information Systems*. 44(1), 34;
https://doi.org/10.17705/1CAIS.04434
<https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.17705%2F1CAIS.04434&data=04%7C01%7Cnkordzadeh%40wpi.edu%7C54025d450243468fc0bc08d9f1d10488%7C589c76f5ca1541f9884b55ec15a0672a%7C0%7C0%7C637806702337880211%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=07oFO3um71LanzP8ba%2BvruQ5gngQ9SIrM00Bc6QlDSg%3D&reserved=0>

*5.* Baesens B, Bapna R, Marsden JR, Vanthienen J, Zhao JL. (2016).
Transformational Issues of Big Data and Analytics in Networked Business; *MIS
Quarterly*. 40(4): 807 – 818; http://dx.doi.org/10.25300/MISQ/2016/40:4.03

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*IMPORTANT DATES:*

   - January 6, 2023: Manuscript submissions begin
   - March 1, 2023: Submissions are due at 10 am EST
   - May 9, 2023: TREOs, PDS and Panels submissions are due at 10 am EST



*Mini-track Co-chairs:*



   - Nima Kordzadeh, Worcester Polytechnic Institute, nkordzadeh at wpi.edu
   - Maryam Ghasemaghaei, McMaster University, ghasemm at mcmaster.ca



We look forward to receiving your submissions!



----

Nima Kordzadeh, Ph.D.

Assistant Professor of Information Systems & Data Science

Worcester Polytechnic Institute | Business School
<https://www.wpi.edu/academics/business>

100 Institute Rd, Worcester, MA 01609

E-mail: nkordzadeh at wpi.edu