[AISWorld] CFP - Asia Pacific Journal of Information Systems (APJIS) Special Issue: People Analytics in Digital Era

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Call for Papers

Asia Pacific Journal of Information Systems (APJIS)

Special Issue: People Analytics in Digital Era



Special Issue Editors

- Dongwon Lee (Korea University Business School), mislee at korea.ac.kr

- Taekyung Kim (Kwangwoon University), kimtk at kw.ac.kr

- Gunwoong Lee (Korea University Business School), leegw at korea.ac.kr




The demand for people analytics has grown as a result of the development of
big data, digital technologies, and the expanding application of data
science techniques (Yoon, 2021). People analytics, often known as human
resource (HR) analytics, is a process that involves data collection,
activity analysis, and knowledge extraction for an organization to evaluate
the effects of various HR metrics on overall business performance and make
data-driven decisions (Tursunbayeva et al., 2021). In information systems
(IS) research, this kind of interest is not necessarily new, but over the
past few years there has been a significant increase in interest, as seen
by the new publications that explain how to use big data and analytic
techniques to understand organizational issues and new businesses based on
HR data (Giermindl et al., 2022). Despite the increase in interest in
people analytics, research communities have noted that there are still very
few scholarly works on the topic (Pessach et al., 2020).

Thus, the purpose of this special issue is to build on existing
conversations in people analytics and new discussions about how people
analytics can help organizations solve management challenges or how big
data, machine learning and metaverse technologies affects applications of
people analytics in digital era. We welcome contributions from scholars who
can provide novel, theoretically rich insights into the research questions
outlined in this proposal. Topics of interest include but are not limited
to the following:

Examples of topics of interest include:

* The application of machine learning (deep learning) to people related data

* The use of analytic techniques to help validate or evaluate the
introduction of new HR initiatives

* New and novel ways to analyze complex/rich stored qualitative information
to help answer new HR related business questions

* Robots, automation, and work

* Methodologies and empirical analysis on technological shifts in labor
payment, shadow work

* Digital or e-leadership

* Theories or analytic framework on new forms of organizations

* Avatar, people, behavior, and performance in metaverse applications

* The role, scope, and value of people analytics for organizations



Asia Pacific Journal of Information Systems

Asia Pacific Journal of Information Systems (APJIS) is a premier journal on
information systems research in the Asia Pacific region. The journal seeks
to advance knowledge about the effective and efficient utilization of
information technology by individuals, groups, organizations, society, and
nations for the improvement of economic and social welfare. Currently,
APJIS is indexed in the Scopus journal database (from 2018) and in the ABDC
Journal Quality List (from 2019) [http://apjis.or.kr].



Submission Guidelines

• All papers should be submitted to the submission system. (
https://www.manuscriptlink.com/journals/apjis)

• All papers will be double blind reviewed using APJIS’s normal procedures.

• Submissions should follow standard formatting and style guidelines for
the Asia Pacific Journal of Information Systems (
http://apjis.or.kr/common/sub/editorialpolicy03.asp?hoho=1).

• The author(s) should indicate that the submission is for the special
issue (People Analytics in Digital Era) on the first page of the manuscript.

• Any queries in advance of submission can be sent for the attention of the
Guest Editors to mislee at korea.ac.kr, kimtk at kw.ac.kr, or leegw at korea.ac.kr



Projected Timeline

• Submission due: June 30, 2023

• 1st round review decision: August 31, 2023

• Revised submission due: September 30, 2023

• 2nd round final review decision: October 20, 2023

• Publication: December 2023





References:

Giermindl, L. M., Strich, F., Christ, O., Leicht-Deobald, U., & Redzepi, A.
(2022). The dark sides of people analytics: Reviewing the perils for
organisations and employees. European Journal of Information
Systems, 31(3), 410-435.

Pessach, D., Singer, G., Avrahami, D., Ben-Gal, H. C., Shmueli, E., &
Ben-Gal, I. (2020). Employees recruitment: A prescriptive analytics
approach via machine learning and mathematical programming. Decision
Support Systems, 134, 113290.

Tursunbayeva, A., Pagliari, C., Di Lauro, S., & Antonelli, G. (2021). The
ethics of people analytics: risks, opportunities and
recommendations. Personnel Review, 51(3), 900-921.

Yoon, S. W. (2021). Explosion of people analytics, machine learning, and
human resource technologies: Implications and applications for
research. Human Resource Development Quarterly, 32(3), 243-250.



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*Dongwon Lee, PhD*Professor of MIS
Korea University Business School (KUBS)
E-mail: mislee at korea.ac.kr / lee.dongwon at gmail.com
Homepage: http://dongwon.info
Facebook, Twitter, LinkedIn, Skype, Instagram IDs: yhowng
(Work) 82-2-3290-2822 / (Mobile) 82-10-6751-4793
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