Employment Decisions
David Levinson
Job Search
• Formal Processes (information networks)
• Informal Processes (social networks)
Social Networks
• Traditional Networks– Formal Social Networks– Informal Networks
Traditional Social Networks: Organizations
• animal rights groups • charities • civic, fraternal, service, and p
rofessional organizations
• companies • employer associations • environmental organizations • humanitarian and peace orga
nizations
• interfaith organizations • international organizations • intellectual property organiza
tions
• magical organizations
• political parties • postal organizations • professional sports leagu
es
• religions • research institutes • self-help organizations • terrorist groups• trade unions • youth organizations
• Non-profit organization
Civic organizations• 1 Agricultural Organizations• 2 Civic and Political Organizatio
ns• 3 Consumer Organizations• 4 Fraternal and Service Organis
ations• 5 Environmental Organizations• 6 Ethnic Organizations• 6.1 African-American• 6.2 Finnish-American• 6.3 Greek-American• 6.4 Hispanic-American• 6.5 Italian-American• 6.6 Jewish-American• 6.7 Norwegian-American• 6.8 Polish-American
• 7 Hereditary & Lineage Organizations
• 8 Men's Organizations• 9 Recreational Organizations• 10 Religious Organizations• 11 Women's Organizations• 12 Veterans' Organizations• 13 Youth Organizations• 14 Professional Organizations
Fraternal and Service Organizations
• Aid Association of Lutherans •
Ancient Arabic Order of the Nobles of the Mystic Shrine
• American Association of University Professors
• Ancient Order of Foresters • Ancient Order of United Workme
n
• Apex • Canadian Order for Home Circles • Chautauqua Institute • Civitan • Dramatic Order Knights of Khora
ssan
• Eagles • Eastern Star • Benevolent & Protective Order of
Elks
• Fraternal Forestry • Freemasonry
• Hull House • Independent Order of
Foresters • Jaycees • Kiwanis • Knights of the Golden Eagle • Knights of the Maccabees • Knights of Pythias • Ku Klux Klan • Lions Clubs International • Masons • Modern Brotherhood of Ame
rica
• Moose Lodge • Improved Order of Red Men • Odd Fellows • National Haymakers Associa
tion
•Optimists •Orange Order Order of Scottish Clans •Quota •Red Cross • Rotary International • Royal Neighbors of America •Royal Templars of Temperance
•Ruritan •Samaritans •Shriners •Native Sons of the Golden West •Twilight Club • Volunteers of America •Woodsmen of the World
Strength of Weak Ties
• Granovetter found that most people find jobs through personal contacts.
• [How did you find most recent job?]
Social Networks
Me
Boss Friend
Coworker
ChildFriend
Wife
Friend
Friend
Social Networks 2
Me
Boss Friend
Coworker
ChildFriend
Wife
Friend
Friend
Coworker’s Wife
Coworker’s Friend
Coworker 2
Coworker 3
Next Generation Social Networks
• Friend-nets– Friendster– Orkut– Tribe.net– SixDegrees
(offline)
• Business-nets– LinkedIn– Ryze
(offline)– ecademy
–FriendSurfer–FriendFinder–Friendsync–Everyone'sConnected–Ringo–MySpace–NetPlaya–Yafro–Hi5–Huminity–Pal Junction–Chia Friend–Buddy Bridge–Tickle–Eurekster–Friendzy–Friends of Friends–Impersonals–Hipstir–Friendity.de–Squiby–Spoke–Zero Degrees–INWYK
Job Search Sites: Formal Search with New
Technology
• Monster.com• Yahoo! HotJobs• CareerBuilder• Etc.
Instant Messaging
• Unix Talk• IRC• ICQ• Yahoo• AOL: AIM• MSN
Will the Web Replace Place?
• Question: What does physical proximity have the web doesn’t?
• Question: What does the web have that physical proximity doesn’t?
Factors that Affect Job Choice
• Knowledge of job• Match with skills• Match with desires• Wage• Location
Journey to Work Time and Home Value by Ring
0
50
100
150
200
250
300
350
0 5 10 15 20 25 30 35
Distance from Center (miles)
Average Home Price ($, 000)
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
50.0
Single Family Home Price ($, 000) Journey to Work Time (minutes)
Average Journey to Work Time (minutes)
Gravity Model
• Hypothesis: The interaction between two places decreases with distance, but increases with the size of the two places.
• There is more interaction between Minneapolis and St. Paul than Minneapolis and Chicago, despite the fact that Chicago is bigger.
• Similarly there is more interaction between Minneapolis and Chicago than Minneapolis and Los Angeles.
• However, there is more interaction between Minneapolis and Los Angeles than Minneapolis and Las Vegas, despite the fact that Las Vegas is closer.
Illustration of Gravity Model
Gravity Math
Tij = KiKj Oi Dj f(Cij) • Where• Tij = Trips from i to j• Oi = Productions of
trips at origin i • Dj = Productions of
trips at destination j• Ki, Kj = balancing
factors solved iteratively€
Oi = Tijj
∑
Dj = Tiji
∑
€
K i =1
K jDj f (Cijm )∑
€
K j =1
K iOi f Cijm( )∑
f(Cij)
• For auto: • For transit: Where:
• Cija = peak hour auto travel time between zones i and j; and
• Cijt = peak hour transit travel time between zones i and j.
Friction Factors
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0 10 20 30 40 50 60 70 80 90
Travel Time
Friction Factor
Friction-Auto Friction-Transit
€
f Cija( ) = e−0.97−0.08Cija
€
f Cijt( ) = e−1.91−0.08Cijt+ 0.265 Cijt
Testing the Gravity Model
• It is hypothesized that living in an area with relatively high jobs accessibility is associated with shorter trips, as is working in an area of relatively high housing accessibility.
• (the doubly-constrained gravity model)
Data
• MWCOG Household Travel Survey (1987-88) – 8,000 households and
55,000 trips• Accessibility Measures
Jobs and Housing Accessibility and
Commuting Duration
In the gravity model implicitly being tested here, average commute to work time is determined by three factors:
1) a propensity (choices) function which relates willingness to travel with travel cost or time, (individual demand)
2) the opportunities (chances) available at any given distance or time from the origin, (market “supply”) and
3) the number of competing workers. (market demand)
Propensity = f ( tij , Income, Mode, Gender... ) It is hypothesized that this underlying preference is relatively
undifferentiated based solely on location.
Geographic Factors
1) distance between the home and the center of the region (Di0) (the zero mile marker at the ellipse in front of the White House),
2) distance between workplace and the center (Dj0), 3) accessibility to jobs from the home (AiE), 4) accessibility to other houses from the home (AiR),5) accessibility to other jobs from the workplace
(AjE),6) and accessibility to houses from workplace (AjR).
Chart 1: Summary Hypotheses
Trip-EndHome-End Work-
End(Origin)
(Destination)
------------------------------------------------------------Accessibility AiE AjEto Jobs negative positive
Accessibility AiR AjRto Houses positive negative
Distance Di0 Dj0from Center positive negative
Elasticities of Travel Time with respect to
AccessibilityAUTO
COMMUTERS
AUTO COMMUTER
S
TRANSIT COMMUTER
S
TRANSIT COMMUTER
S
VARIABLE ELASTICITY VARIABLE ELASTICITY
AiEa -0.22 AiEt -0.12
AiRa 0.19 AiRt 0.05
AjEa 0.24 AjEt -0.25
AjRa -0.25 AjRt 0.07
Di0 0.25 Di0 0.31
Dj0 -0.16 Dj0 -0.09
Dependent Variable: Travel Time to Work
VARIABLES TRANSIT AUTOAiEt, AiEa -1.15E-03 -8.68E-05
(-2.27) ** (-4.86) ***AiRt, AiRa 1.12E-03 1.18E-04
(0.85) (2.75) ***AjEt, AjEa -1.14E-03 7.13E-05
(-2.56) ** (4.21) ***AjRt, AjRa 1.05E-03 -1.47E-04
(0.75) (-3.26) ***Di0 1.71 0.63
(9.71) *** (5.82) ***Dj0 -1.67 -0.55
(-5.63) *** (-3.77) ***CONSTANT 44.12 23.29
(9.21) *** (4.61) ***Sample Size 346 1950Adj. r-squared 0.38 0.17F 12.96 22.79Significance F 0 0
Conclusions• Location matters, important explanatory variable, but• Ignores self-selection process - creating more high density housing
won’t create more young or old who wish to live in those high density urban areas.
• Information matters, people can’t take a job they don’t know about.
• Social networks, both formal and informal, provide information informal
• People choose to join and participate in networks they are rewarded for
• Informat networks and placeless networks are rising compared with older place-based formal networks (Rotary, Lions Clubs, etc.)
• Other formal informationnetworks: traditional and new media (classifieds, job search sites) remain important.
• Where you work relative to where you live will determine how much peak travel you undertake, and thus is critical in understanding travel demand.