Insights Lectures

The Insights Lecture is an annual public lecture series sponsored by UniSA’s Centre for Workplace Excellence. A world-renowned international researcher delivers a lecture on a contemporary issue of interest to employers, employees, organisations and the general public.


2022 Insights Lecture - ‘Leading for Inclusion’

The Insights Lecture is an annual public lecture series sponsored by UniSA’s Centre for Workplace Excellence (CWeX). A world-renowned international researcher delivers a lecture on a contemporary issue of interest to employers, employees, organisations, and the general public.


In this public lecture, Prof Elissa Perry considers a confronting issue. The demographic shifts across an increasingly global economy are creating unprecedented challenges for employers. Employee diversity can make organisations more innovative and profitable, but it can also increase conflict, lower cohesion and generate higher turnover. Inclusive leadership can make the difference, yet few line managers are prepared to manage a diverse workforce. Prof Perry discusses the impact of inclusive leadership on employee attitudes, behaviour, and performance – and the cumulative impact that inclusive leaders have in organisational contexts. She provides examples of the day-today behaviours and management practices that inclusive leaders use to support all employees. Additionally, she explains why this leadership style is particularly well-suited for managing diverse employees and leveraging diverse viewpoints to benefit employers.

Elissa Perry.jpg

Elissa Perry is a Professor of Psychology and Education at Teachers College, Columbia University, USA. Her research focuses on inclusive leadership, age discrimination, sexual harassment, and the impact of organisational racial and gender diversity on organisational outcomes. Prof Perry joins an exclusive group of UniSA Visiting Distinguished Thought Leaders. This designation is awarded to world-leading academic figures whose research has the capacity to make a tangible, strategic contribution for the benefit of UniSA.

Previous Insights Lectures

CARMA Live Online Short Courses

April 2022

Centre for Workplace Excellence (CWeX-UniSA Business) is pleased to host two short courses offered by the Consortium for the Advancement of Research Methods and Analysis (CARMA). The sessions are offered in April 2022 delivered by international experts in research methodology.

A great opportunity to practice and develop your skills in research methods and meet some of the greatest names in the field.

Don’t miss the chance to learn best practice from international experts!


 Adelaide Time



11 – 14 April 2022

8:00 am to 1:00 pm

Doing Grounded Theory Research

Dr. Elaine Hollensbe, University of Cincinnati

19 – 22 April 2022

8:00 am to 1:00 pm

Advanced Data Analysis with R

Dr. Chelsea Song, Purdue University

Required Software: R (download here), R Studio (download here)

Registrations are now open on the Carma Website

Session 1: April 11-14, 2022

“Doing Grounded Theory Research”

Introduction Video by Dr. Hollensbe

This course will explore the process of conducting a grounded theory study. Through readings, discussion (exemplar and how-to articles) and hands-on exercises, the session begins with generating research questions and interview protocols; collecting data (e.g., participatory, interview, secondary); the coding process; other data analytic processes beyond coding; generating a grounded model; and navigating the review process. This seminar will examine how to ensure trustworthiness and rigor in grounded theory research and consider challenges of conducting such research when you’ve been trained primarily in quantitative research.

Dr. Elaine Hollensbe, University of Cincinnati

 PhD in organizational behavior and human resource management. Dr. Hollensbe has completed qualitative research in the areas of identity, work-life balance, and emotion and quantitative research on goal setting, compensation and self-efficacy. Her current research is qualitative and focuses on individual and organizational identity work and organizational identification. Her research has been published in such journals as the Academy of Management Journal, Journal of Management, Academy of Management Review, and Human Resource Development Quarterly and has been recognized with national awards, including the Owens Scholarly Achievement Award, the Rosabeth Moss Kanter Award, and the Outstanding Publication in Organizational Behavior Award. She is a former Associate Editor of the Academy of Management Journal.

Session 2: April 19-22, 2022

“Advanced Data Analysis with R”

This short course will begin with an introduction to linear regression analysis with R, including models for single/multiple predictors and model comparison techniques.  Particular attention will be paid to using regression to test models involving mediation and moderation, followed by consideration of advanced topics including multivariate regression, use of polynomial regression, logistic regression, and the general linear model. Exploratory factor analysis and MANOVA will also be covered. For all topics, examples will be discussed, and assignments completed using either data provided by the instructor or by the short course participants.

Dr. Chelsea Song, Purdue University

Ph.D. Industrial-Organizational Psychology, University of Illinois at Urbana-Champaign. Research focus: (1) enhancing diversity in the workplace, (2) person-environment fit and longitudinal development of personality and vocational interests, and (3) research methods. These topics aim to answer questions evolving around personnel selection (e.g., hiring, promotion) such as what predicts workplace outcome (e.g., personality, vocational interests), how to measure them (e.g., psychometrics), and how to make decisions (e.g., diversity in hiring, multiple-objective optimization). My work implements various methods, such as multilevel modeling, longitudinal models, meta-analysis, Monte-Carlo simulation, and I am also particularly interested in studying the application of machine learning and Big Data methods in hiring practices.