The Role of Social Network Ties and Relationships During the Internship Assignment Phil Gardner Michigan State University Portions previously presented at WACE’s 10 th International Symposium University West Trollhattan, Sweden

Overview Experience --- the gatekeeper to labor market More is better --- in larger chunks Focus on boundary spanning skills & competencies

Challenge The “First Job” New Demographics: – Passing Time – Pedigree – Entrepreneurers Employability: Teichler – University of Kassel – Do not know what fosters employability skills – Lag effects are likely New Professional: Expand Inquiry – Refocus on emerging domains – Experienced required but how much

The Real Question of Inquiry How does the growth of social capital during the internship or co-op: – Contribute to successful transition to workplace – Foundation for early career success First step: – Focus on the role of social capital during the internship assignment

Task Mastery Social Integration Team Integration Learning (broad) Social Capital – Weak Ties: Career network – Strong Ties: Supervisor, Mentor, Known in organization Starting Points: Newcomer and Early Socialization Theories

Basic Model SI TI LI CN KO SPI M SPE Mastery Satisfaction

Study Parameters Sample Large Convenience sample drawn from over 200 US schools – current college students Administration One time solicitation through Career Services Partner – so question space limited

Study Parameters Sample Characteristics 8,900 with 80% in internships 65% Women 73% Caucasian 20% Business 62% GPA 3.35 or higher 62% Family Income $80,000 or less

Basic Measures Social Networks Career Network: 14 average Composed of – Peers on campus (5), Faculty/Advisor (2.5), Family (2.6), Relatives/Acquaint. (2.6) Know in organization: 1/3 knew someone with 90% only knowing one person Tended to be someone with 7 to 20 years with the organization

Basic Measures Mentor More likely to be a young professional Supervisor Experienced professional or management Interpersonal Interactions External Interactions Scale Metrics

FIRST MODEL (WITH MASTERY)

First Step: Supervisor/Mentor Influences SE SI M TI LI

2nd Step: Weak Network SE SI M TI IL CN KO + + +

3rd: Mastery SI TI IL TASK MASTERY Et Sr

Final: Satisfaction SITIIL TASK MASTERY Et GP A Satisfaction - SEMSI G CN KO -

Gender – What’s with it with men? – Women seek out faculty more in career advice – Women less likely to have management as supervisor – Women more likely to have less experienced mentor Ethnicity – Non-whites have fewer classmates in their network; also fewer family are involved – Non-whites less likely to have managers as supervisors – Advantages – are they permanent GPA – Tim Judge’s work – Family Income – No statistical impact (yet) Additional Variables

Characteristics of the Internship Credit vs no-credit – No statistical differences (at this time) Paid vs unpaid – Paid are more satisfied with experience Length – Longer experience more satisfied Part or Full time – Part-time (20 hrs or less) more satisfied

Alternative Model Control variables that are used in all models. – Paid versus unpaid – Credit versus no-credit – Internship length – Internship Status – Gender – Race

Serial mediation models: Supervisory support  learning  satisfaction  accept offer Indirect effects.0032 (significant) Supervisory support  team integration  satisfaction  accept offer Indirect effects.0005 (not significant) Supervisory support  social integration  satisfaction  accept offer Indirect effects (not significant) Supervisory support  satisfaction  accept offer Indirect effects.021 (significant)

Mentor Moderation

Control variables that are used in all models. – Paid versus unpaid – Credit versus no-credit – Internship length – Internship Status

Main effects of social capital on outcomes: Social capital  satisfaction =.000 (not significant) Social capital  job offer =.010 (not significant) Social capital  supervisory support =.014 (significant) Social capital  mentorship status =.026 (significant) Main effects of race/ethnicity and gender on outcomes Race/Ethnicity  satisfaction = (not significant)  job offer = (significant)  supervisory support = (significant)  mentorship status =.03 (not significant)

Gender  satisfaction =.006 (not significant)  job offer =.501 (significant)  supervisory support = (not significant)  mentorship status = (not significant)

Implications Ethnicity: Passing Time Gender: Do men gain more simply doing it and ignoring all the breadth stuff – or does it catch up with them Supervisor – always the key Mentors – should not be forgotten Social capital – both strong and weak – play key roles

Shift Gears: Future Administrative Clarity: rise of “big data” Boundary Spanning & Length Story Telling: need for integration New frontiers (i.e.) – Teams – Reverse education and experiential education (the context more important than the content)

Questions