Significance Significance of of Guanx Guanxi Yan anji jie e - - PowerPoint PPT Presentation

The Pr he Prevalence and valence and the Incr the Increasing easing Significance Significance of

• f Guanx

Guanxi

Yan anji jie e Bian Bian

University of Minnesota & Xi’an Jiaotong University To

• pr

prese esent a nt at N t Nottingh

• ttingham

am Univ Univer ersity sity, , Octob October 6, 2 er 6, 201 017. 7.

Outline Outline

• 1. W
• 1. Wha

hat is t is Guanxi Guanxi? Some conceptual and ? Some conceptual and theo theoretica etical l issu issues es

• 2. Case study on job sear
• 2. Case study on job search netw

h networ

• rks:

ks: The F he Fate of te of Guanx Guanxi in China’s Economic Transition ansition

• 1. What is Guanxi?

One view: Parnwell (2005) “Chinese guanxi is not a term which can adequately be expressed by an English-language equivalent of one word, the concept is too culture specific.” One definition: Bian (2006) “dyadic, particular, and sentimental tie that has potential of facilitating favor exchange.” One impression: a UoM student (2012), “guanxi network is a network that is hard to get in and it is equally hard to get

• ut.”

Examples of Definitions & Characterizations from 70 years

• Social extensions of kinship ethics and ties: Liang Shuming, 1947
• Differential mode of associations/overlapping egocentric networks: Fei Xiaotong, 1947
• Fabric of social organization: Moten Fried 1953
• Ties as a relational bearer of face: Ambrose King 1985, 1990s
• Instrumental-particular ties: Andrew Walder 1986
• Strategic mixed ties of face and favor: Hwang Kuang-Kuo 1987
• Social exchange ties in a gift economy: Mayfair Yang 1994
• Habitus social connections: Yan Yunxiang 1996
• Strong ties facilitating favor exchanges: Bian Yanjie 1997, 2006
• Obligational and symbiotic ties: David Wank, 1999, 2015
• Asymmetrical social exchange ties: Nan Lin 2001, 2015/2016
• Generalized particularism: Lo and Otis, 2003
• Adaptive purposive network behavior: Chang, 2011
• Isotopic social capital: Bian and Zhang, 2014

5

Conceptualization #1: Changing Relational Bases

• Narrow:
• -Familial ties of sentiment and obligation
• -EX: kin, pseudo-kin
• Broader:
• -Particular-instrumental ties
• -EX: kin, pseudo-kin, patron-client relations
• Broadest:
• -Diverse ties that facilitate favor exchanges
• -EX: kin, pseudo-kin, patron-client relations, significant others
• Characterizations:
• -Exchange: repeated reciprocities
• -Duration: long-lasting
• -Strength: strong
• -Relational constraint: high
• -Resources: significance of “small non-redundancy

Repeated favor exchanges via 熟亲信 ties (acquaintance, intimacy, trust)

6

Conceptulization #2: Isotopic Social Capital

• Relational particularism: a strong personal tie, ensures kin
• r pseudo-kin sentiments, repeated favor exchanges or

Kin-ization, “Differential mode of association”(差序格局 Fei 1992)

• Multiplexity: multi-functions (Verbrugge 1979: 1286), multi-

stranded/channels (Mitchell 1969); norm mixing (King 1994)

• Reciprocal obligations: indebtedness, eagerness, and

effort-giving, as binding mechanisms

• Significance: This conceptualization gives us a basis for

comparative SC studies

7

A General Model of Network Social Capital

Guanxi as a Variable: A 5-Point Understanding

1) Guanxi as connectivity (or dis-connectivity), and its embedded resources are (1) mutual recognition as members of a shared community and (2) communication. 2) Guanxi as a sentimental tie, and its embedded resources are human affections, containing sympathy, care, and a sense of altruist, not reciprocal, help. The stake is small though significant. 3) Guanxi as a sentiment-derived instrumental tie, and its resources are substantial help with reciprocal implications and expectations. 4) Guanxi as an instrumental particular tie, and its resources vary hugely but the norms of reciprocity, face, and favor are primary. 5) Guanxi as an obligational tie, a well-understood informal contract, and its resources are specific, behaviors highly patterned, but relational

• rigins, bases, or forms unclear or vary randomly.

9

• 2. Case Study on the Fate of Guanxi in China’s Transition

Per ersistent sistent significance significance Gr Grano anovett etter er (1985) (1985): embed : embeddedness dedness，市场嵌入网络 Powell ell & Smith & Smith-Doer Doerr r (1990) (1990): go : gover ernance str nance structur ucture，治理结构网络 De Declining lining signif significan icance ce Gut Guthrie hrie (1998) (1998): dec : declining lining significance significance of

• f guanxi

guanxi，市场限制网络 Incr Increasing easing significance significance Nee Nee (1992) (1992): rising : rising horiz horizontal

• ntal ties

ties in in hybrid hybrid economy economy，横向网络 Lin Lin (1995) (1995): kinship : kinship netw networ

• rks

ks as as str structur ucture e of

• f villa

village ge industr industry y ，社区网络 Boisot Boisot & Child & Child (1996) (1996): inf : infor

• rma

mation tion & netw & networ

• rk

k ca capitalism pitalism，信息网络 Wank (1999 ank (1999): symbiotic ): symbiotic clientelism lientelism，共生网络 Zhou et Zhou et al al (2003) (2003): enf : enfor

• rcement of

cement of inter inter-fir firm m contr contracts acts，合同网络 Sa Sato to (2003) (2003): netw : networ

• rk r

k ref efer errals als for

• r mig

migrant ant la labor bor，介绍网络 Peng eng (2004) (2004): inf : infor

• rmal

mal pr proper

• perty

ty-right right institut institution ion of

• f TVE

TVEs，产权网络 Mic Michelson helson (2007) (2007): embed : embeddedness dedness in le in legal gal pr prof

• fession

ession，诉讼网络 Guo Guo and Miller and Miller (2010) (2010): cor : core, e, extende xtended, d, oppor

• pportunit

tunity y ties, ties, 机会网络 Luo et Luo et al.

• al. (2012)

(2012): 53 studies : 53 studies of

• f 20,000 or

20,000 organiza ganizations, tions, 组织网络 MOR MOR (2011) (2011) Special Special Issue: Issue: Variet ariety y of

• f ca

capitalism pitalism，共存体制

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A Typology on Guanxi Dynamism

11

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

% Jobs through Social Ties

2014 2009 1999

Resea esearch Design h Design

• Da

Datas tasets ets Mer Merged ged：JSnet JSnet 1999 & 1999 & 2009 2009，CGSS CGSS 2003 & 2003 & 2008 2008

• Period

eriod：Post

• st-Ref

efor

• rm

m Er Era，1978 1978-2009 2009，N=10232 N=10232

• Guanxi

Guanxi User Users：Inf Infor

• rma

mation? tion? F Favor

• rs?

s?

• Mar

Marketiza etization tion Ind Indica icator tors：Non Non-Sta State J te Jobs

• bs、Fan’s Index
• Instit

Institutionaliza utionalization tion Ind Indica icator tors：Mer Merit it Scr Screening I eening Inde ndex x (MSI (MSI) La Latent tent c class lasses es #1 #2 #3 #4 #5 15.45% 30.58% 19.82% 23.44% 10.70% Educa Education/ tion/skill skill 0.9584 0.9584 0.0004 0.6080 0.6080 0.8807 0.8807 0.8136 0.8136 Wri Writt tten en tes test 0.6391 0.6391 0.0217 0.0905 0.0124 1.0000 1.0000 Inter Interview view 0.9685 0.9685 0.0914 0.4606 0.4606 0.4067 0.9068 0.9068 Gender D Gender Disc. isc. 0.4749 0.4749 0.0429 0.4752 0.4752 0.0681 0.0079 Age Disc. Age Disc. 0.81 0.8165 65 0.0287 0.73 0.7390 90 0.0787 0.1444

13

Network Resources from Social Contacts

• Information

– Gave me information about a job opening – Gave me information about the workplace where there are job openings – Gave me advice about how to apply for “that job” – Assisted me in preparing my job application – Prepared my application

• Favor/influence

– Delivered my application to the hiring organization – Recommend me to the hiring organization – Contacted “a relevant person” of the hiring organization – Did something concrete to boost my chances of being hired

• Arranged an informal meeting with a VIP of the hiring organization
• Escorted me to visit the home of a VIP of the hiring organization

– Solved a problem leading to my hire at the organization

• Helped the organization resolve a concrete program
• Promised to help with a proposal

– Directly offer me a job

Table ble 1. ARIMAX

• 1. ARIMAX Mod

Models o els on n Job

• b-Se

Sear arch h Netw Networ

• rks

ks, , Bian Bian & Zh & Zhan ang

Proportion of Using Networks (Y) Yt Yt – Yt-1 Auto-reg Yt-1 0.942* 0.507 0.420 0.955* 0.929*

• 0.371

Ex var Market t 0.485* 0.020 Market t-1 0.465* MSI t

• 0.233

MSI t-1

• 0.214

MSI t - MSIt-1

• 1.128*

BIC

• 83.837
• 90.752
• 83.466
• 80.855
• 76.786
• 88.395

N 32 32 31 32 31 31

Table ble 2.

• 2. Mix

Mixed ed-Ef Effec ect t Lo Logist gistic ic Regres ession sion, , Bian Bian & Zh & Zhan ang

Ex Var at Job entry Market Model MSI Model Main Inter Main Inter Age 0.034* 0.034* Age2/100

• 0.088*
• 0.087*

Female 0.184*

• 0.039

0.165* 0.001 R-Hukou 0.733*

• 1.240*

0.304*

• 0.002

F's SEI 0.003* 0.007 0.005* 0.000 Party

• 0.389*

0.347

• 0.257*
• 0.001

Education

• 0.055*

0.012

• 0.051*
• 0.000

Market 1.818* 2.047* MSI

• 0.002*
• 0.003*

Constant

• 0.997*
• 1.037*

BIC 13248.542 13260.406 N 10232 10232

Job

• bs

s th throu

• ugh

gh Net Networ

• rks

ks (197 (1978-2009) 2009)

Insti Institutional tutional Uncer ncertainty tainty Mar Market et Compe Competit tition ion Low: Perceived competition 1-3 High: Perceived competition 4-5 High: (Lower MSI value) II: 12.5% Medium to large 1.870 III: 28.6% Highest 3.610 Low: (Higher MSI value) I: 16.9% Nil to small 1.000 IV: 42.0% Medium to large 1.870

Conc Conclusion lusion & Discus & Discussion sion

Conclu lusio ion：

• Increasing trend：Clearly evident since market reforms.
• Mixed resources flowed：Information and favors.
• Competition & institutionalization：Guanxi increases with marketization, but

decrease with MSI institutionalization.

• Greater efficacy for the weak：Women, migrant labor, and more effective when they

are from better families.

• Lower efficacy for the strong：Highly educated and CCP members, as education and

CCP memberships are strong market signals themselves. Discussion:

• Favoritism：To labor market efficiency? To social justice?
• Information：To labor market efficiency？To social justice？
• High skill job markets：MSI is high, thus reducing favoritism?
• Low-skill job markets：How to increase MSI?

Thank hank You

• u

Q & A & A

Empirical Evidence: Mao’s Era

Mao’s era: Regime: state planning, bureaucratic control, shortage economy Guanxi: factory managers for resource allocation village heads for harvest assessments and projects

• rdinary citizens for life necessities, goods, services

Story: instrumental-particular ties with gate keepers for jobs Logic: favoritism ties as survival strategy in organized dependence References: Whyte & Parish 1984, Gold 1985, Walder 1986, Bian 1994, Yang 1994, Yan 1996, Kipnis 1997, Oi 1999 …

Empirical Controversies: Post Mao

Post-Mao era: Nee: market transition, up human capital, down political power Guthrie: factory managers in Shanghai hard budget constraints, profit driven, rationalization favoritism as irrational, guanxi on the decline Hanser: guanxi had no relevance for first-time job seekers Huang: guanxi had limits for college-graduate job seekers Bian et al: growing number of jobs through guanxi ties References: Nee 1989, 1991, 1996, Guthrie 1998, 2002, Hanse 2002, Huang 2008, Bian et al 2008, 2009, 2015, Tian & Lin 2016

Debate: Cultural vs. Structural vs. Institutional

The Guthrie-Yang debate on guanxi dynamism

• Yang 1994: guanxi as persistent cultural

behavior

• Yang 2002: guanxi resilience in the rise of

markets

• Guthrie 1998, declining significance in the rise
• f rationalizing market
• Guthrie 2002, declining significance where

markets are rationalized

• 3. Case Study on Guanxi Advantage and Online Networking

Table 1: Measuring Guanxi Advantage

Variables Mean S.D. Min/Max N 2014 JSNet N=5480 NY net size 25.9 34.3 1/300 5440 Number of NY visitors as alters NY net ceiling 69.9 28.7 0/95 4992 Highest SEI of alters NY net diversity 5.36 4.06 0/20 4992 Number of positions of alters Online greeters 46.1 79.6 0/1000 5451 Via text message, email, QQ, Sina, facebook, we-chat network, etc. SE host 2.37 1.08 1/5 5,441 1=never in past 3 months 2=infrequent 3=sometimes 4=often 5=always SE guest 2.49 1.07 1/5 5,444 SE escort 2.43 1.09 1/5 5,446

Table 2. Measuring Online Networking

Variables Mean S.D. Min/Max N Notes (Total N=5480)

News learned online 3.10 1.41 1/5 5,472 In the past 12 months, 1=never, 2=few, 3=some 4=often, 5=always 60% social media users Knowledge obtained

• nline

2.92 1.39 1/5 5,474 Social media used

• nline

2.97 1.51 1/5 5,475 Online chat groups participated 2.44 0.91 1/4 3,282 1=0, 2=1-5, 3=6-10, 4=>10 Online friends kept 15.25 41.38 0/1000 2,898 # good friends kept online Friends extended

• ffline

2.79 13.61 0/400 2,908 # friends made offline Use of online friends for jobs 0.31 0.46 0/1 2,910 1=yes, 0=no

Table 3. Relate Social Hierarchy to Online Networking, O-Logic/ZINB

News Learned Knowledge

• btained

Use Social Media Chat groups Online Net Size Online tie Conversion Online job help Education High school 2.872*** 2.756*** 2.771*** 2.541*** 0.973 0.747 1.402 College 5.990*** 7.196*** 5.598*** 3.644*** 1.229 0.856 1.468* Income Lower 1.755*** 1.721*** 1.470*** 1.007 0.948 1.159 1.005 Middle 2.549*** 2.410*** 2.086*** 1.196 1.188 0.905 1.211 Higher 3.468*** 3.443*** 3.065*** 1.529** 1.295* 1.080 1.229 Highest 4.514*** 3.983*** 3.502*** 2.042*** 1.465** 1.227 1.152 SEI Middle 1.748*** 1.653*** 1.924*** 1.310** 1.148* 1.174 1.109 Higher 3.152*** 2.992*** 2.615*** 1.387*** 1.233* 0.836 1.051 N 5429 5431 5432 3255 2566 2825 2888 Pseudo R2 0.23 0.25 0.31 0.06

Zero-Inflated Negative Binomial Regression

All models include controls of sex, age, age2, marital status, hukou, CCP, employer, housing, & city.

Table 4. Relate Guanxi Advantage to Online Networking, O-Logic/ZINB

News Learned Knowledge

• btained

Use Social Media Chat groups Online Net Size Online tie Conversion Online job help Net size 1.007*** 1.006*** 1.007*** 1.006*** 1.008*** 1.006*** 1.003* Net ceiling 1.016*** 1.017*** 1.015*** 1.010*** 1.006*** 1.005*** 1.004* Net diversity 1.120*** 1.127*** 1.122*** 1.073*** 1.060*** 1.064*** 1.042*** Host freq 1.744*** 1.648*** 1.673*** 1.318*** 1.109*** 1.222*** 1.106* Guest freq 1.625*** 1.536*** 1.619*** 1.328*** 1.200*** 1.381*** 1.115* Escort freq 1.547*** 1.532*** 1.602*** 1.265*** 1.177*** 1.294*** 1.199*** N 5400 5402 5404 3244 2873 2873 2873 Pseudo R2 0.23 0.23 0.30 0.06

Zero-inflated Negative Binomial Regression

All models include controls of personal attributes, education, income, and SEI.

Table 5. Relate Hierarchy-Guanxi Interaction to Online Networking, O-Logic/ZINB

News Learned Knowledge

• btained

Use Social Media Chat groups Online Net Size Online tie Conversion Online job help Education-Guanxi Host High school 0.840* 0.877 0.985 0.945 0.931 1.740* 0.830 College 0.785** 0.842* 0.925 0.936 0.890 1.931** 0.989 Income-Guanxi Host Lower 0.875 0.788* 0.687*** 0.958 0.841 0.865 0.989 Middle 0.712** 0.717** 0.654*** 0.770* 0.944 1.033 1.163 Higher 0.741** 0.682*** 0.653*** 0.750* 0.998 0.987 1.156 Highest 0.681*** 0.652*** 0.636*** 0.681** 0.983 1.044 1.165 SEI –Guanxi Host Middle 0.807** 0.824** 0.819** 1.006 1.008 1.257* 0.937 Higher 0.735** 0.729** 0.739** 0.792* 0.892 1.063 0.894 N 5396 4785 4785 3255 2566 2825 2888 Pseudo R2 0.24 0.25 0.31 0.06

Zero-inflated Negative Binomial Regression

Main Findings from the Online Networking Study （1）Direct effect of social hierarchy: One’s online networking is positively related to one’s status in the social hierarchies; the higher one’s education, income, or SEI, the greater the probabilities that one is active in online networking, but such association does not apply to online-offline conversion. (2) Direct effect of guanxi advantage: One’s online networking is positively related to one’s offline guanxi advantages (measured by New Year socialization and social eating), even after one’s statuses in the social hierarchies and personal attributes are controlled for. (3）Interactive effect of hierarchy-guanxi: the higher one’s status in the social hierarchies, the lower the effect of guanxi advantage on online networking,

• r vice versa.

Thank hank You

• u

Q & A & A