hero image
Mo Wang - University of Florida. Gainesville, FL, US

Mo Wang Mo Wang

Professor/Chair/Associate Dean | University of Florida

Gainesville, FL, UNITED STATES

Mo Wang studies retirement and the employment of older workers and occupational health psychology.

Biography

Mo Wang is the associate dean for research, Lanzillotti-McKethan Eminent Scholar, Director of the Human Resource Research Center and chair of the management department in the Warrington College of Business. He studies retirement and the employment of older workers, occupational health psychology and leadership and team processes in the workplace.

Industry Expertise (4)

Corporate Training

Corporate Leadership

Business Services

Elder Care

Areas of Expertise (7)

Successful Aging in the Workplace

Occupational Health Psychology

Team Processes

Management

Retirement

Leadership

Business

Media Appearances (4)

Can Being Promoted to Leadership Change Who You Are?

South China Morning Post  online

2021-06-18

Prof. Li carried out the research alongside Prof. Shuping Li of Hong Kong Polytechnic University, Prof. Jie Feng of Rutgers University, Prof. Mo Wang of University of Florida, Prof. Michael Frese of the Asia School of Business and Leuphana University of Lueneburg, Prof. Chia-Huei Wu of the University of Leeds, as well as CUHK Business School PhD candidate Hong Zhang.

view more

Retire or keep working? The healthy answer isn’t that simple.

The Washington Post  online

2020-12-19

Mo Wang, retirement researcher at the University of Florida, says some of the confusion in the studies stems from the fact that often they “do not take into the account the health issues as reasons for retirement.” He says, however, this “healthy worker effect” does not explain all differences in studies between those who stay on their jobs and those who leave. The rest is probably due to retirees being a diverse group — with various types of jobs and life circumstances — so if you lump everyone together, you will get confusing results.

view more

Study: Student debt may hurt chances at full-time employment

EurekAlert!  online

2020-08-25

Mo Wang of the University of Florida, Jaclyn Koopmann of Auburn University and Peter Bamberger of Tel Aviv University co-authored the article. The researchers say that having student loan debt is a financial stressor to students that leads to additional stress during their job search, which in turn can harm their chances of securing a full-time job.

view more

A Q&A with Work, Aging and Retirement Editor, Mo Wang

OUPblog  online

2015-06-10

Recently, we sat down with the Editor of Work, Aging and Retirement, Mo Wang, to discuss how he got involved with the journal and the plans he has in store for Work, Aging and Retirement in the future.

view more

Articles (5)

Effectiveness of stereotype threat interventions: A meta-analytic review.

Journal of Applied Psychology

Songqi Liu, et al.

2021-06-01

This meta-analytic review examined the effectiveness of stereotype threat interventions (STIs). Integrating the identity engagement model (Cohen, Purdie-Vaughns, & Garcia, 2012) with the process model of stereotype threat (Schmader, Johns, & Forbes, 2008), we categorized STIs into 3 types: belief-based, identity-based, and resilience-based STIs. Combining 251 effect sizes from 181 experiments, we found an overall effect size of d = 0.44, with the intervention group outperforming the control group.

view more

Best Not to Know: Pay Secrecy, Employee Voluntary Turnover, and the Conditioning Effect of Distributive Justice

Academy of Management Journal

Valeria Alterman, et al.

2021-04-28

Building on uncertainty management theory, we develop and test a model explicating how and when secrecy in pay communication may affect employee turnover-related outcomes. Underlying this model is the notion that employees triangulate perceptions of pay secrecy with their own or others’ perceptions of distributive justice as a basis for assessing organizational trustworthiness, with the latter serving as an important driver of voluntary turnover intentions and behavior.

view more

From Creative Environment to Administrative Innovation: Creation and Implementation in Top Management Teams

The Journal of Creative Behavior

Lu Chen, et al.

2021-03-19

Drawing upon the stage model of innovation and the ability–motivation–opportunity (AMO) framework, we hypothesize the mediating role of top management team (TMT) creativity and the moderating roles of external social capital and environmental uncertainty in the relationship between TMT creative team environment and a firm’s administrative innovation. We collected multisource data from 136 TMTs and tested the hypotheses using bootstrap method with SPSS 23.0.

view more

The relationship between cultural tightness–looseness and COVID-19 cases and deaths: a global analysis

The Lancet Planetary Health

Michele J Gelfand, et al.

2021-03-10

The COVID-19 pandemic is a global health crisis, yet certain countries have had far more success in limiting COVID-19 cases and deaths. We suggest that collective threats require a tremendous amount of coordination, and that strict adherence to social norms is a key mechanism that enables groups to do so. Here we examine how the strength of social norms—or cultural tightness–looseness—was associated with countries' success in limiting cases and deaths by October, 2020.

view more

Intensive Longitudinal Data Analyses With Dynamic Structural Equation Modeling

Organizational Research Methods

Le Zhou, et al.

2019-03-19

Recent developments in theories and data collection methods have made intensive longitudinal data (ILD) increasingly relevant and available for organizational research. New methods for analyzing ILD have emerged under the multilevel modeling framework. In this article, we first delineate features of ILD. We discuss the analytic challenges for handling ILD using traditional analytic tools familiar to organizational researchers.

view more

Media

Publications:

Documents:

Photos:

loading image loading image loading image

Videos:

Audio/Podcasts:

Research aims to create fairness in AI-assisted hiring systems

Languages (1)

  • English