SIOP (Society for Industrial and Organizational Psychology) Conference
Thursday, 4/14/2016, 10:30-11:50am
Veteran Selection, Performance, and Retention
(1) Trent Burner, VP Global Organizational Effectiveness at Wal-Mart: Trent.Burner@Walmart.comx
– WM has a goal to hire 250k vets by 2020 and has special resources in place for vet hiring. For example, since May 2013, they have had a guaranteed hiring of honorably discharged vets. They also have a “Military Family Promise” program where if a current WM employee (active duty or spouse) is PCS’ed (military term for relocated), they guarantee a job at the nearest WM to them.
– WM estimates that 20% of current US workforce are vets or family members of vets; however, this is based on self-report, so they believe this number is low.
– WM is the largest private sector employer of vets.
– They’ve just started a longitudinal study, measuring the success of vets vs. regular employees. What they’ve found is that in jobs paid hourly, vets tend to get more promotions, need less coaching for deviant workplace behaviors, are more willing to stay in roles for longer period of time, have fewer sick calls, and are more likely to convert from part-time to full-time. They’ve also found in salaried employees, vets tend to leave the job sooner than their non-vet counterparts.
– WM recently launched a “Veteran Champion” program which is a mentor program for vets to mentor newly hired vets. It’s been launched within the past 18-ish months and isn’t in every location yet, but they’re seeing results already. Looking at these three groups: (1) vets who’ve been through the mentoring program; (2) non vets; (3) vets who haven’t been through the mentoring program — WM has found that for a variety of measures (job satisfaction, positive emotions toward WM, ease of transition in adapting to WM culture, length of time they estimate they’ll stay employed at WM) is ranked 1-2-3. So, the happiest group in all measures is vets who have been through the mentoring program. The least happy group in all measures tends to be vets who haven’t gone through mentoring. Non-vets are in the middle.
(2) Nathan D Ainspan, PhD, Research Psychologist from Transitions to Veterans Program Office: Nathan.D.Ainspan.firstname.lastname@example.org
Thursday, 4/14/2016, 3:30-4:50pm
Deviance for the Right Reasons? Understanding Constructive Deviance at Work
– Bella Galperin, U of Tampa
– Melissa Gutworth, Penn State
– Abhijeer Vadera, SMU, Investigating the role of deliberate decision-making mindset on moral behaviors
– Robert Eisenberger, U of Houston, Discussant
7 Key Properties of Sense Making (Weick, 1995)
Cognitive Dissonance Theory
Prospective Theory: losses hurt more than gains
deception game (Geneery? 2005)
deliberate mindset (think about costs and benefits)
intuitive mindset (think about feelings)
social influence too
destructive task/constructive task
majority of whistle blowers live uncomfortable lives
limited theories – cognitive dissonance theory too much
contemplation: could be good in some situations
did his dissertation on whistle blowing (both redemptive and destructive)
intent of constructive deviance is to help the org
Thursday, 4/14/2016, 5:00-5:50pm
Illustrations of Innovative Technology Applications to HR Processes
Leonard Y. Pierce, FMP Consulting
MyCareer@VA: online career development
– career fit tool
– VA job finder
Nick Koenig, Wal-Mart worked with Michael D. Reeves and Marisa Seeds from SHAKER. Pre-Hire PowerUp: Boosting validity with web apps in five minutes
looking at skills
situation judgment items (SJT)
bring in gamification: use of game elements in non-game context
serious games: games with a purpose
in the selection process:
narratives, avatars, interactive simulations, timed
– narratives: why they rapidly fill orders and why getting it right is important
– progression of difficulty
– use of time elements
– interactive simulation
logistics associate virtual job tryout
goal orientation, self-efficacy, conscientiousness tests
good face validity – people had very good things to say, and long sentences
Submitter: Daly Vaughn from SHAKER: email@example.com
Friday, 4/15/2016, 10:30-11:50am
Coaching Nightmares: What Would You DO?
Dale S. Rose, 3D Group – Chair and “Who Is the Client?”
Cynthia H. Alt, Alt Consulting – “Shooting the Messenger”
We had to text 3DGROUP to 22333
Powered by: PollEverywhere.com
Friday, 4/15/2016, 12:00-1:20pm
Ex-Offenders Navigating the Hiring Process: Insights from Research and Practice
Nicole Jones Young, U of Conn
Ban the Box: US legislative initiative intended to improve employment prospects for ex-offenders. There is a stigma, one of the most difficult to overcome. This removes the checkbox from the application asking about criminal history. 21 states have adopted it for public employers; 7 states for private employers.
Social Identity Theory
Friday, 4/15/2016, 1:30-2:50pm
Making Big Data Smart: Challenges in Measurement, Analysis, and Validity
Wei Wang, UCF, Chair, firstname.lastname@example.org
Ryan Boyd, UT Austin, Co-Chair
Jing Jin, Facebook, Discussant
Dr. Eric O’Rourke: People Analytics Team at Facebook, Discussant
Wei Wang, Twitter Analysis: Trends in Work Stress and Emotion
Big Data: Volume, Velocity, Variety
Text Analysis: text mining (ETS: e-rater)
Social Network Analysis
WEIRD: Western, Educated, I, R, D (Henrich, Heirne, & Norenzaya, 2010)
Twitter: micro-blogging service up to 140 characters, 8th most pop website
288 million active users on a monthly basis
500 million sent Tweets per day
33 dif languages, 77% outside USA
Folder and Macy, 2011: looked at positive emotion on an hourly basis
– Large sample, diverse, representative
– Unobtrusive measure, free of self-report bias
Challenges to Measurement:
– how to measure, validate, compute reliability?
Took sample of 510 tweets from across 51 states and ran against stress word dictionary. Did Dynamic Factor Analysis.
Theory: Effort-Recovery Model (Meijman & Mulder, 1998)
Ryan Boyd, Word of Advice: Language and Psychological Features of Work-Related Advice (with Niederhoffer and Pennebaker)
Advice: binary (follow or don’t). broad view: it is a fundamental social process.
Looked at Reddit.com/r/Advice
– 30k advice solicitations
– 111k responses
LIWC 2015 (Pennebaker, Booth, Boyd, & Francis, 2015)
MEH (Boyd, 2016)
To pick topics, looked at MEM Extraction (Boyd, 2016)
advice giving is trait-like, stable across time. .6 up to .85 over time.
Amy Wax, Cal State Long Beach, Understanding Team Self-Assembly: A Mixed Methods Approach
Browser Wars: Netscape, I.E., Mozilla (Netscape desperate, losing market share, gave source code to everyone, and Phoenix arose from the dust – Mozilla)
Social Proof, Familiarity, Proximity (Newcomb, 1956) H1, 2, 3 for Team Membership
Looked at Dragon Nest online, quests, in China.
ERGM (Exponential Random Graph Models): for big data dyads
Tanner Kluth, UCF, with SHAKER peeps, Predicting Job Performance From Text Responses: A Big Data Approach..
– Oreskovic, 2015: tweets lit
– Jinha, 2010: journal article lit
Tausczik & Pennebaker, 200: language is most common and reliable way to translate internal thoughts into emotions
Eichstaedt, et al. 2015: heart disease
Language is prevalent.
virtual job tryout at Shaker, analyzed with LIWC
cut out fewer than 100 words, and people who weren’t at company more than a month.