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https://doi.org/10.1177/0018726718778097
human relations
2019, Vol. 72(4) 801 –833
© The Author(s) 2018
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DOI: 10.1177/0018726718778097
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human relations
Am I a peasant or a worker?
An identity strain perspective
on turnover among
developing-world migrants
Xin Qin
Sun Yat-sen University, China
Peter W Hom
Arizona State University, USA
Minya Xu
Peking University, China
Abstract
Developing-world rural migrants provide crucial labor for global supply chains
and economic growth in their native countries. Yet their high turnover engenders
considerable organizational costs and disruptions threatening those contributions.
Organizational scholars thus strive to understand why these workers quit, often applying
turnover models and findings predominantly derived from the United States, Canada,
England or Australia (UCEA). Predominant applications of dominant turnover theories
however provide limited insight into why developing-world migrants quit given that they
significantly differ from UCEA workforces in culture, precarious employment and rural-
to-urban migration. Based on multi-phase, multi-source and multi-level survey data of
173 Chinese migrants working in a construction group, this study adopts an identity
strain perspective to clarify why they quit. This investigation established that migrants
retaining their rural identity experience more identity strain when working and living
in distant urban centers. Moreover, identity strain prompts them to quit when their
Corresponding author:
Minya Xu, Guanghua School of Management, Peking University, Beijing, 100871, China.
Email: minyaxu@gsm.pku.edu.cn
778097HUM0010.1177/0018726718778097Human RelationsQin et al.
research-article2018
802 Human Relations 72(4)
work groups lack supervisory supportive climates. Furthermore, migrants’ adjustment
to urban workplaces and communities mediates the interactive effect of identity strain
and supervisory supportive climate on turnover. Overall, this study highlighted how
identity strain arising from role transitions and urban adjustment can explain why rural
migrants in developing societies quit jobs.
Keywords
adjustment, identity strain, migrant workers, rural identity, supervisory supportive
climate, turnover
Introduction
Employee turnover has become a global phenomenon as more economies enable employ-
ees to freely change jobs as a result of loosened labor laws and reduced state intervention
in labor markets (Lee and Kofman, 2012). Given that workforce mobility occurs world-
wide and affects organizational functioning (Park and Shaw, 2013), scholars increasingly
explore why people quit in a wider array of cultures and economies (Allen and Vardaman,
2017). All the same, international researchers often apply turnover models developed in
the United States, Canada, England or Australia (UCEA) (Maertz et al., 2003), presum-
ing their universal applicability (Chen et al., 2016; Posthuma et al., 2005). Although
Allen and Vardaman (2017: 169) recently concluded that ‘turnover models and processes
. . . generalize quite well across cultural contexts’, other scholars dispute their direct
‘context-free’ transferability (Tsui et al., 2007), especially to societies differing from
UCEA countries in terms of culture and economic development (Maertz et al., 2003;
Peltokorpi, 2013).
Responding to perennial calls to explore turnover outside UCEA societies (Peltokorpi,
2013), we investigate turnover among developing-world (DW) ‘precariats’ (Lee, 2016),
who assume precarious employment lacking job security and benefits in construction or
export-oriented manufacturing (Chih et al., 2016; Loess et al., 2008). Because these indi-
viduals differ greatly from UCEA workforces in culture, precarious employment and
rural-to-urban migration, their scrutiny rigorously tests the generalizability of prevailing
models. Despite pervasive journalistic and qualitative reports (Choi and Peng, 2015;
Romero and Cruthirds, 2009), empirical scrutiny of DW precariat turnover remains
sparse (Chen et al., 2016; Miller et al., 2001; Qin et al., 2014). This scant empirical evi-
dence is surprising given that DW precariats surpass the UCEA labor force (Cirera and
Lakshman, 2014), dominate global manufacturing (The Economist, 2015), and exhibit
extreme turnover (e.g. 60% in the People’s Republic of China [PRC]; Fallows, 2012).
Such attrition causes labor shortages while boosting costs and production shortfalls in
manufacturing, construction and other industries vital for emerging economies (Du et al.,
2006; Jiang et al., 2009).
Apart from scarcity, empirical studies mainly focused on how working conditions
(including attitudes toward ‘3-D’—dirty, demanding and dangerous—jobs) and job pros-
pects impel DW precariat turnover (Chen et al., 2016; Miller et al., 2001; Qin et al.,
2014; Smyth et al., 2009). While confirming UCEA theory promulgating movement
Qin et al. 803
desirability and ease (March and Simon, 1958), this focus neglects turnover causes aris-
ing from transition stress plaguing these subsistence farmers (e.g. 252 million Chinese;
Mozur and Orlik, 2012), who leave behind home and family in the countryside to enter
distant urban labor markets. That is, predominant applications of dominant turnover
theories overlook how the twin challenges of adapting to unfamiliar work and living
environments impel rural migrants to quit. DW migrants endure cultural shock when
adapting to urban society, while being separated from their family in remote villages
(Qin et al., 2014). Thus, provincial migrants’ poor adjustment to urban roles likely com-
pel them to exit urban workplaces.
To close a conspicuous gap in prevailing accounts of DW migrants’ turnover, we
adopt an identity strain perspective to clarify why they quit jobs, contextualizing this
model to enhance its applicability (Lee et al., 2017). Adapting self-verification and iden-
tity-strain theories (Burke, 1991, 2006; Tajfel and Turner, 1986), we contend that
migrants’ decision to leave urban jobs hinges on how well they transition from old to new
role identities (i.e. ‘country folk’ to ‘urbanite’). When entering urban environments, they
undergo sensemaking, prompting them to form new ‘situational identities’ based on their
urban work and lifestyle (Cable et al., 2013). However, many migrants maintain their
provincial identity, regarding village roles in farming, family and civic leadership as
central to their self-concept (Paik, 2014). Such rural identification creates identity strain
when their identity lacks urban affirmation. As a result, they adjust poorly to cosmopoli-
tan employment and lifestyle and thus leave.
Our model further recognizes the critical role that migrants’ supervisors play in their
rural-to-urban transition. We follow Bakker and Demerouti’s (2007) job demands-
resources model, positing that job resources attenuate the harm incurred by job demands.
Specifically, we submit that supervisory supportive climate—or ‘general availability to
work unit members of key object, energy, and social resources provided by their supervi-
sor’ (Wang et al., 2011: 317)—buffers against identity strain. Given weak union and
labor protections (Lee, 2016), supervisors are dominant authorities who can supply pre-
cariats various resources that can alleviate identity-strain duress. We examine supervi-
sors’ collective support given that collectivist developing countries extol homogenous
paternalistic leadership rather than differential support that can undermine group har-
mony (Nishii and Mayer, 2009).
In sum, we propose that DW migrants’ identity strain (sustained by rural identity)
jeopardizes their urban adjustment, in turn prompting their quits, while noting that a sup-
portive supervisory climate can ameliorate this effect. To test our model (see Figure 1),
we conducted a multi-phase, multi-source and multi-level field study among 173 PRC
migrants. By so doing, we advance turnover and identity literatures in several primary
ways. First, we answer the call for more inquiries into workforces outside UCEA socie-
ties by investigating a culturally dissimilar DW precariat workforce, thus providing a
rigorous generalizability test. Second, we deepen insight into DW migrant exits by iden-
tifying a salient but overlooked turnover driver arising from rural-to-urban transitions.
This study not only helps explain the high turnover rate in emerging economies but also
enriches predominant turnover theories by highlighting how drastic work and extra-work
role transitions evoke identity strain that can culminate in leaving. We elaborate on these
and other contributions in the discussion section.
804 Human Relations 72(4)
Theoretical grounding and hypothesis development
Rural identity and identity strain
Burke (1991, 2006) identifies three mechanisms underlying how extant identities invoke
identity strain (Kraimer et al., 2012). One mechanism is the standard or setting of a cer-
tain identity—or ‘set of meanings defining who one is’ (Burke, 2006: 82). In rural China,
migrants form a provincial identity standard (e.g. ‘I am a peasant’) as they have deep
ancestral ties to farming (Silverstein and Cong, 2013). Their ancestors tilled the same
soil for centuries, while they continue to have farming and residential rights to ‘their’
land, where they also maintain a homestead (Friedman and Lee, 2010; Qin et al., 2011).
Home visits during Chinese New Year and regular mobile phone calls to family reinforce
their rural identity standards (Xu, 2016), as do local networks of migrants from the same
home province (laoxiang) who preserve native customs in the destination society (Liu,
2015; Yue et al., 2013). Burke’s (1991) other mechanisms include ‘input from the envi-
ronment or social situation (including one’s reflected appraisals)’ and the ‘process that
compares the input with the standard (a comparator)’ (p. 837). These mechanisms are
‘tightly linked and involve a self-verification process wherein individuals seek to vali-
date their identity by seeking input from their environment to determine whether their
current social position is consistent with their own “identity standard”’ (Kraimer et al.,
2012: 403).
However, Chinese migrants have trouble validating their provincial identity when
working and residing in cities. As Burke (1991) puts it, they receive inputs from their
urban environment (including reflected appraisals) that conflict with rural identity stand-
ards. When confronting such discrepancies, migrants experience identity strain (Kraimer
et al., 2012) that activates a variety of reactions, including anxiety and depression (Liao
et al., 2015; Naeem et al., 2015). To illustrate, migrants may encounter negative stereo-
types from urbanites who see them as ‘country bumpkins’ doing menial work (Gu et al.,
2007; Kim, 2015; Siu, 2017) or even as vagabonds (Swider, 2015). These stereotypes
clash with migrants’ identity standards as versatile and respected farmers. They may also
Figure 1. The theoretical model about how rural identity and identity strain influence
turnover.
Qin et al. 805
feel stigmatized as second-class citizens as they lack official household registration in
cities (hukou) (Lee and Kofman, 2012), denying them affordable housing and other resi-
dential amenities (Loyalka, 2012; Swider, 2015). Because migrants’ self-concepts are
neither affirmed nor verified (Cable et al., 2013), they may then feel identity strain and
emotional distress (Liao et al., 2015; Myerson et al., 2010; Zhong et al., 2016).
Beyond this, the stronger the migrants’ rural identity, the higher the mismatch between
rural identity and urban inputs, which worsens identity strain (Burke, 1991). Chinese
migrants adhering to rural identities may persist in their pattern of provincial thought and
behavior in urban societies. After all, they ‘[regard] land as the most fundamental secu-
rity, [take] agriculture as main work and [work] in cities as byline, and [deem] the coun-
tryside as their final destination’ (Gu et al., 2007: 3). By clinging onto rural identities,
PRC migrants become less receptive—if not antagonistic—to urban customs, norms and
values. They thus face more difficulty integrating into urban life and forging a new iden-
tity as ‘city people’ (Frenkel and Yu, 2015). As Kraimer et al. (2012: 411) explain, ‘old
identities get carried over to new positions and contexts and continue to influence how
individuals see themselves in their new roles’. Based on the foregoing rationale, we thus
hypothesize:
Hypothesis 1: Migrant workers’ rural identity is positively related to identity strain.
Identity strain and urban adjustment
When leaving rural homelands, Chinese peasants must adapt to unfamiliar factory regimes
and urban lifestyles (Zhou and Sun, 2011), including forming a new situational identity
(Cable et al., 2013; Yue et al., 2013). Migrants initially attempt to reduce identity strain
through a cyclical process of self-verification, whereby they continually seek input from
the social environment to ascertain whether ‘meanings implied by [their] ongoing behav-
ior in the situation’ match previous identity standards (Burke, 2006: 82). Migrants with
weak provincial identities may feel less identity strain (or can better lessen it) because
they sense a closer ‘fit’ with living and working in cities and thus readily adapt to their
new lifestyle. Those harboring strong provincial identities (Gui et al., 2012), on the other
hand, do not feel this fit. In particular, the former eagerly adopt urban values, believe that
cosmopolitan lifestyles are instrumental for achieving the ‘Chinese dream’ (Chan, 2013:
95; Loyalka, 2012), and master the knowhow and skills to find and keep urban jobs (Liu,
2015). They also form social ties with local residents within and outside workplaces,
which help them acculturate and solidify their urban identity (Yue et al., 2013). By inter-
acting with urban residents, rural laborers also resolve uncertainty (Zhu et al., 2016) and
learn appropriate behaviors for work and community contexts (Aycan, 1997; Zhong et al.,
2016). Their adoption of urban habits and lifestyles also elicits acceptance by city dwell-
ers (Tharenou and Caulfield, 2010), enhancing urban adjustment.
Unburdened by identity strain, Chinese migrants may also freely substitute activities
enjoyed in the countryside with urban activities, again facilitating local adjustment
(Shaffer et al., 2006). After all, ‘cultural flexibility’—or receptivity to substitutes—eases
expatriates’ adaptation abroad (Shaffer et al., 2006) as they find alternative outlets for
socializing, recreation and educating children (Tharenou and Caulfield, 2010). In the
806 Human Relations 72(4)
same manner, PRC migrants feeling little identity strain (or managing it better) may
readily find lifestyle substitutes, such as broader mating options, liberation from patriar-
chal control (Myerson et al., 2010), and higher-paid non-agrarian work (Loyalka, 2012).
Consequently, securing gratifying substitutes promotes urban assimilation.
By comparison, rural-urban migrants grappling with identity strain (given large iden-
tity-input discrepancies that they cannot close; Burke, 1991) express an attitude of sepa-
ration and act in culturally inappropriate ways, which can undercut relationships with
local inhabitants (Aycan, 1997). These migrants dislike, disavow or avoid their surround-
ings (Stryker, 1987; Thoits and Virshup, 1997), thus hampering city adaptation. As
migrant laborers cannot withdraw completely from urban society given their and their
family’s dependency on urban employment for subsistence (Lee and Kofman, 2012;
Zhong et al., 2016), their sustained use of avoidant strategies is maladaptive (Aycan,
1997; Herman and Tetrick, 2009), causing dissatisfaction, felt marginality and psychoso-
matic symptoms (Liao et al., 2015). In short, the self-verification cycle breaks down for
rural migrants who can no longer ‘influence the way others behave toward, label, or treat
[them]’ (Burke, 1991: 841). When migrants repeatedly fail to lessen identity strain, they
may feel unable to adapt to urban life. Based on the preceding logic and evidence, we
thus propose that low—rather than high—identity strain expedites provincial migrants’
adaptation to urban environments.
Hypothesis 2: Migrant workers’ identity strain is negatively related to urban
adjustment.
Supervisory supportive climate as a moderator of identity strain effect
Long regarded as some of the most influential people in workplaces affecting employee
well-being and attachment (Waldman et al., 2015), supervisors hold enormous sway over
DW migrants’ shop floor conditions (Kopinak, 1996; Ngai and Huilin, 2010). Given
weak labor laws, poor union representation and a high–power distance culture (Friedman
and Lee, 2010; Gu et al., 2007; Xu, 2013), they enjoy ‘uncircumscribed power’ (Yu,
2008: 518) overseeing DW precariats, rewarding or punishing them, and allocating them
resources (Chen et al., 2002; Kim, 2015; Lee, 2016). Indeed, Siu (2017: 543) noted that
‘most of the rank-and-file operators felt the line leaders had the greatest impact on their
factory lives,’ including the discretion to ‘open up a back door’ for them.
In DW factories or construction sites, a supervisory supportive climate—or how a
supervisor supports his or her entire collective of subordinates (Bacharach and Bamberger,
2007; Wang et al., 2011)—can emerge and can help mitigate identity-strain effects. DW
precariat workers often experience homogeneous supervisory treatment (e.g. monitoring,
production pressures) as they are physically confined to a common workspace for long
working hours. Taylorist industrial regimes also induce supervisors to behave uniformly
toward precariats, even when interacting with them individually (Choi and Peng, 2015;
Yu, 2008). After all, manufacturing or construction supervisors must ensure that all sub-
ordinates meet demanding production goals by performing routinized tasks according to
strict time schedules and comply with a host of regulations through constant surveil-
lance, exhortations or sanctions for infractions (Chan et al., 2013; Siu, 2017; Yu, 2008).
Qin et al. 807
To illustrate, a Foxconn assembly worker recounted how line leaders ‘lecture us on
maintaining high productivity, reaching daily output targets and keeping discipline’ dur-
ing roll calls (Chan, 2013: 88). Given common supervisory encounters, DW precariats
may share interpretations about their supervisor’s benevolence (or lack thereof) during
interactions, which converge and yield consensual views of the supervisory supportive
climate over time (Kozlowski and Klein, 2000; Morgeson and Hofmann, 1999).
Perceptual agreement is further reinforced through precariats’ ongoing interactions after
work shifts as they often live together in company housing (Swider, 2015). Attesting to
its role as a group-level resource, studies reveal how supervisory supportive climate
dampens the impact of workplace stressors and mistreatment (Bacharach and Bamberger,
2007; Bacharach et al., 2008; Wang et al., 2011).
Further, supervisory supportive climate may more effectively buffer against identity
strain than perceived supervisory support (an individual-level construct) because it rep-
resents a collective resource available to all workers. In collectivist societies, differential
supervisory support (like leader-member exchange [LMX]) creates tension and resent-
ment in work groups (especially among ‘out-groups’) (Erdogan and Bauer, 2010; Hooper
and Martin, 2008; Nishii and Mayer, 2009). When a migrant worker receives high per-
sonal supervisory support, he or she may incur the wrath or antipathy from other group
members (Seo et al., 2018), especially those from the same home province (laoxiang) as
they are expected to care for one another. The ‘privileged’ (in-group) worker may also
feel anxiety or guilt for receiving supervisory support that other group members do not
receive. They may even refuse special treatment to avoid alienating their peers.
Meanwhile, other group members may regard their supervisor’s benevolence toward
them (though less than that accorded to in-groups) less favorably as they envy what
favored members get (Kim et al., 2010). Further, DW precariats may deem supervisors
less competent if they fail to live up to implicit theories about team-oriented (Dorfman
et al., 2012) or paternalistic leadership (Liao et al., 2017), which is dominant and valued
in developing collectivist countries. Such culturally prescribed leadership requires lead-
ers to promote team collaboration, team solidarity (instead of disharmony), and family-
like consideration toward subordinates. Consequently, when such leadership is absent,
workers may question the value of supervisory resources they do receive, such as a
supervisor’s advice about how to handle identity strain.
We thus contend that supervisory supportive climate—rather than personal supervi-
sory support—ameliorates identity strain’s detrimental effects by offering material
resources, emotional support, and uncertainty-reducing information (Bakker and
Demerouti, 2007; House, 1981). In supportive climates, migrants receive more resources
that alleviate worker duress, including identity strain (Kraimer et al., 2001). For exam-
ple, supervisory supportive climates encourage workers to express their authentic selves
(including rural identities; Cable et al., 2013) and enhance diversity-inclusive environ-
ments within work units (McKay et al., 2009) rather than marginalizing workers based
on rural background or dialect (Liu, 2015; Peng and Choi, 2013). Moreover, supervisors
can furnish expressive resources enabling rural laborers to cope with the anxiety and
distress incurred by identity strain (Lazarus and Folkman, 1984). To illustrate, Qin and
Xu (2013) observed supervisors socializing with migrants, such as taking them to din-
ners or outings, in addition to helping them adapt to urban life by teaching them to drive.
808 Human Relations 72(4)
Supportive supervisors also encourage subordinates to form peer friendships and com-
fort distressed peers, including those afflicted by identity strain (Zhong et al., 2016).
Nishii and Mayer (2009) thus attest to how leaders expressing high LMX toward all
followers can sustain camaraderie among followers. They noted that as ‘more employees
feel validated [by high group-mean LMX] and therefore more comfortable behaving
authentically, interpersonal interactions should improve’ (p. 1415). All told, supervisory
supportive climate likely lessens identity strain’s adverse impact on migrants’ urban
adaptation.
In contrast, when migrant workers belong to work groups bereft of such climates, they
receive less expressive or instrumental assistance that help them manage identity strain.
For them, high identity strain directly translates into urban maladjustment. In line with
this notion, Lazarova et al.’s (2010) job demands-resources (JD-R) account of expatriate
adjustment holds that expatriates lacking resources have trouble meeting expatriation
demands and thus poorly cope abroad. Mahajan and De Silva (2012) further build on
JD-R theory and assert that host-country nationals’ social support weakens how unmet
role expectations impair expatriate adjustment. We therefore deduce the following:
Hypothesis 3: Supervisory supportive climate moderates the negative effect of migrant
workers’ identity strain on urban adjustment, such that this effect is weaker when
supervisory supportive climate is high rather than low.
Urban adjustment as a proximal antecedent of voluntary turnover
During international transitions, adjusting to novel living or working circumstances can
be so taxing that it weakens expatriates’ resolve to stay abroad (Aycan, 1997; Bhaskar-
Shrinivas et al., 2005). Likewise, PRC migrants may have difficulty adjusting to the city
because they are appalled by the cramped living quarters, expensive cost of living, and
air pollution there (Wong et al., 2007; Zhong et al., 2016). Additionally, they may have
trouble befriending city inhabitants as they cannot speak the local dialect (Gouttefarde,
1992; Liu, 2015; Yue et al., 2013) nor have the time or energy to socialize externally
(Swider, 2015). Describing the struggles for migrants aspiring to become urbanites,
Zhong et al. (2016: 3) thus observed that ‘rural and urban people are radically different
in terms of etiquette, manners, festival folk customers, eating habits, wedding customs,
religious ceremony, funeral systems, and the ceremony of sacrificing ancestors’. Rather
than the autonomous and seasonal agrarian labor they are used to, these former farmers
are confined to assembly lines or construction sites for long periods, where they must
achieve steep production goals according to strict deadlines and face harsh penalties for
goal failures (Zhou and Sun, 2011; Kim, 2015; Zhong et al., 2016). In short, urban adjust-
ment reflects the entirety of how well rural migrants adjust to urban living (e.g. finding
affordable housing and edible food) and working conditions (e.g. ‘endless assembly line
toil, punishing work schedules, harsh factory discipline’; Chan, 2013: 91).
When PRC migrants fail to fit local conditions or form local links, they may quit
more than those acclimating there (Tanova and Ajayi, 2016). That is, some of those who
have not adjusted well to urban life may quit to go to another job where they might find
better working and living conditions (e.g. joining workplaces employing more
Qin et al. 809
hometown natives). Or else, they may relocate to other urban centers where they might
better adjust (e.g. locales physically closer or culturally similar to provincial homes;
Qin et al., 2014). Others may return home temporarily (resuming factory work later) or
permanently (e.g. farming or caring for dependents; Chang, 2009; Zhou and Sun, 2011),
although the latter option is increasingly foreclosed as migrants cannot earn sufficient
income (Choi and Peng, 2015; Lee and Kofman, 2012; Swider, 2015) nor can farm if
their land has been expropriated by local government or leased to agribusiness (Lee,
2016). All told, urban maladjustment may engender various forms of voluntary turno-
ver, including relocations.
Expatriate studies support our thesis that urban adjustment reduces PRC migrant
departures. For example, Tharenou and Caulfield (2010) found that expatriates poorly
embedded in host countries more often pursued alternative employment. Conversely,
Ren et al. (2014) reported that expatriate adjustment diminished withdrawal cognitions
(e.g. ‘I intend to search for another teaching position so I can leave this school’). Like
expatriates, PRC migrants who inadequately cope with urban life may quit, whereas
those adapting well will find satisfaction in their new living and working environments
and thus remain (Kim et al., 2016; Torbiorn, 1982). Based on the foregoing theory and
research, we thus propose the following:
Hypothesis 4: Migrant workers’ urban adjustment is negatively related to turnover.
Hypothesis 3 specifies that supervisory supportive climate moderates how migrant
workers’ identity strain affects urban adjustment, whereas Hypothesis 4 states that migrants’
adjustment influences their decisions to leave. Logically, it follows that adjustment medi-
ates the interactive effect of identity strain and supervisory supportive climate on turnover
(i.e. mediated moderation; Edwards and Lambert, 2007). Put differently, we envision a
weaker positive indirect effect of identity strain on turnover via adjustment for workers in
high supervisory supportive climates but a stronger positive indirect effect for workers in
low supervisory supportive climates. Accordingly, we put forth the following:
Hypothesis 5: Migrant workers’ urban adjustment mediates the interactive effect of
identity strain and supervisory supportive climates on turnover.
Pilot study
Given nonexistent measures of migrant workers’ rural identity and identity strain, we
conducted a pilot study to develop and validate new measures of these constructs. In
particular, we adapted Kraimer et al.’s (2012) measures of repatriates’ identity and iden-
tity strain. Both our work and theirs examine role transitions. Kraimer et al. (2012)
focused on repatriates returning home, whereas we considered domestic migrants’ transi-
tion from farmers to urban workers and dwellers. Specifically, we adapted their expatri-
ate identity and identity strain scales by rewording items to better fit migrant workers
(see Appendix).1
We next surveyed 178 Chinese migrant construction laborers to assess our scales’
psychometric characteristics. Among this pilot sample, 93% were men and their average
810 Human Relations 72(4)
age was 33.6 years. They also averaged 10.0 years of education and 1.4 years of tenure
in their current organization. For both pilot and main studies, we translated measurement
scales originally written in English (including new rural identity and identity strain
scales) into mandarin Chinese, which we also back-translated (Brislin, 1980).2 Internal
consistency reliability estimates (α) for rural identity and identity strain measures were
.74 and .83, respectively. Further, we examined these constructs’ nomological network
(Bagozzi et al., 1991; Hinkin, 1998), assessing how they relate to years of farming,
work-family conflict and turnover intentions. Specifically, because rural identity emerges
over a lifetime of countryside experiences (Qin et al., 2011), we expect that years of
farming to positively correlate with rural identity. In addition, because identity strain
decreases migrant workers’ ability to adjust to urban work and life, we expect identity
strain to positively co-vary with work-family conflict and turnover intentions.3
To validate our scales, we first conducted confirmatory factor analyses (CFAs) among
rural identity, identity strain, work-family conflict and turnover intentions. A four-factor
measurement model fitted data well (χ2 = 207.95, d.f. = 113, p < .001; Root Mean Square
Error of Approximation (RMSEA) = .07, Comparative Fit Index (CFI) = .92, Tucker
Lewis Index (TLI) = .91; Coovert and Craiger, 2000) and significantly outperformed all
other alternative models (these results are available from the authors). These tests indi-
cated high convergent and discriminant validity for our newly adapted measures.
Correlations further revealed that years of farming positively related to rural identity
(r = .24, p < .01) and had a positive but not significant relationship with identity strain
(r = .02, NS). Identity strain was positively related to work-family conflict (r = .20,
p < .01) and turnover intentions (r = .17, p < .05), whereas rural identity was marginally
significantly and positively related to work-family conflict (r = .14, p < .10), but not
significantly related to turnover intentions (r = .08, NS). These results additionally vali-
dated our rural identity and identity strain scales. The main study next examined how and
when rural identity and identity strain affect migrant turnover.
Main study method
Participants and procedures
To test our hypotheses, we collected multi-source and multi-phase data from a large
Chinese construction group. We confined the sample to a large organization to control
for potential organizational variance (e.g. insuring consistent human resources policies
across workers). This approach also facilitated the collection of multi-source and multi-
phase data. A large proportion of rural migrants work in construction: 22.3% in 2014
(National Bureau of Statistics of China, 2015). This employer assigns migrant laborers
to different teams handling different construction specialties. Within each team, mem-
bers typically perform the same tasks in collaboration with teammates. Each team has
one direct supervisor. At six construction sites, the authors personally administered sur-
veys to 265 migrant workers who received a small gift (e.g. toothpaste, soap) for survey
participation. To encourage candid answers, we promised respondents that their answers
would remain confidential as only our research team would have access to their survey
data and that we would only report aggregated statistics in future publications. This
Qin et al. 811
survey assessed migrants’ rural identity, identity stain, supervisory supportive climate,
demographics and control variables. All participants were literate enough to read and
answer the questionnaire. A year later, we asked supervisors about respondents’ employ-
ment status.
To reduce common method bias (Podsakoff et al., 2012), we solicited one of the sur-
vey respondent’s co-workers to rate the focal respondent’s urban adjustment. To identify
this informant, we initially asked supervisors to name three co-workers who could
observe and have first-hand knowledge of the focal participant’s attitudes and behaviors.
After all, PRC workers live together at construction jobsites and thus should be familiar
with each other’s adjustment—both on and off the job (Swider, 2015). To reduce poten-
tial selection bias, we then randomly invited one of the named co-workers to rate the
focal migrant’s adjustment. We obtained 205 usable surveys with matched co-worker
ratings (for a response rate of 77%). A year later, we contacted study participants’ super-
visors to identify which participants had voluntarily quit. We ascertained the employ-
ment status of 173 migrants for a response rate of 84% or a final response rate of 65%.
To evaluate potential sample selection bias, t-tests comparing the final sample with the
initial survey respondents revealed no significant demographic differences (e.g. gender:
t = 0.44, NS; age: t = 0.45, NS; marriage status: t = −0.23, NS; education: t = −0.24, NS;
tenure: t = −0.79, NS; these results are available from the authors). Among respondents,
92% were male, and 85% were married. Their average age was 37.6 years. They aver-
aged 9.1 years of education and 2.2 years of firm tenure. On average, they accumulated
13 years of work experience. They belonged to 31 work groups, whose mean group size
was six, ranging from three to 14. They were mostly welders, carpenters, steel fixers,
formwork fixers or bricklayers.
Measures
Unless otherwise noted, all scales used a five-point Likert format from 1 = Strongly disa-
gree to 5 = Strongly agree.
Rural identity. We measured this construct with the scale developed in the pilot study
(α = .77).
Identity strain. The scale developed in the pilot study assessed this construct (α = .82).
Supervisory supportive climate. In line with Wang et al. (2011), we assessed this con-
struct with Bacharach and Bamberger’s (2007) four-item scale. We adapted these four
items to refer to ‘team members.’ That is, migrant laborers reported how often (1=
Never to 5 = Always) their supervisors exhibited the four supportive behaviors toward
the entire team. An example item is ‘How often does your supervisor go out of their
way to do things to make the team members’ work-life easier?’ (α = .78). We aggre-
gated their perceptions to form supervisory supportive climate. We first checked for
sufficient within- and between-group homogeneity to determine whether aggregation
was viable. The rwg (j) statistic (Chan, 1998; Glick, 1985; James et al., 1984) was chosen
to measure within-group homogeneity. It ranged from .74 to 1.00 with a median value
812 Human Relations 72(4)
of .91, indicating relatively high within-group agreement. An F-test and intraclass cor-
relation coefficients ICC[1] and ICC[2] further assessed between-group homogeneity
(Bliese, 2000). Both the F-test and intraclass correlations produced acceptable values
(F(30, 142) = 1.59, p < .05; ICC[1] = .10; ICC[2] = .37). It is worth noting that, even
though the ICC[2] values should ideally exceed .70 (Kozlowski and Klein, 2000), a
low ICC[2] value does not prevent aggregation if the rwg (j) is high and group variance
is significant (Chen and Bliese, 2002). Our ICC[2] value was also comparable to
aggregated statistics reported in previous research (e.g. Liao and Chuang, 2007; Ou
et al., 2014). Thus, we aggregated individual-level perceptions of supervisory support
to form supervisory supportive climate, bearing in mind that ‘the relationships between
the aggregated measures with low ICC[2] and the other study variables might be
underestimated’ (Liao and Chuang, 2007: 1012).
Urban adjustment. Following expatriate studies (e.g. Shaffer et al., 2006), we adapted
Black and Stephens’ (1989) 14-item expatriate adjustment scale to assess migrants’
urban adjustment. This scale is often used to assess individuals’ adjustment in new envi-
ronments or cultures (Herman and Tetrick, 2009). A knowledgeable co-worker described
the focal participant’s level of adjustment to 14 urban features (1 = Strongly unadjusted
to 5 = Strongly adjusted). An example is ‘Entertainment/recreation facilities and oppor-
tunities’ (α = .94).
Turnover. From participants’ supervisors, we learned that 62% of our study participants
had quit in the year following our survey (0 = stayed; 1= quit), all voluntarily. As noted
above, we seek to explain voluntary turnover and thus assessed employees’ withdrawal
from an employing organization rather than a geographical locale.
Control variables. Following Bernerth and Aguinis’s (2016) recommendations, we meas-
ured sex (0 = female; 1 = male), age (years), marital status (0 = single; 1= married),
education level (years), tenure (years), years of work experience, number of children
under 18 years, working with spouse (0 = single or married and the spouse did not work
at the construction site; 1= married and the spouse worked at the construction site), work
category (0 = unprofessional jobs; 1 = professional jobs, such as welders, carpenters,
blasters, etc.), hours worked per day, local dialect proficiency, job satisfaction, perceived
job alternatives and job embeddedness owing to their established relationships to turno-
ver (Boon and Biron, 2016; Griffeth et al., 2000; Griffeth et al., 2005; Jiang et al., 2012;
Mitchel, 1981; Rubenstein et al., 2018; Steel and Griffeth, 1989; Yan, 2006). We con-
trolled for daily work hours as it represents a type of job demand that can trigger turnover
(Angrave and Charlwood, 2015; De Croon et al., 2004). Expected to enhance adjustment
(Ren et al., 2014), local dialect proficiency was measured by a question: ‘How fluently
do you speak the local language?’ (1 = Cannot speak to 5 = Very proficient).
Following prevailing practice to establish incremental validity for new turnover deter-
minants (see Mitchell et al., 2001), we thus controlled for antecedents central to turnover
theory (i.e. movement ease and desirability; March and Simon, 1958) and newer job
embeddedness theory (Lee et al., 2004). For movement desirability, we measured
job satisfaction with the question: ‘In general, how satisfied are you with your job?’
Qin et al. 813
(1 = Strongly dissatisfied to 5 = Strongly satisfied). This single-item question can have
validity comparable to multi-item scales (Wanous et al., 1997). We captured movement
ease with Griffeth et al.’s (2005) desirability-of-movement subscale, which assesses the
prospects for landing better jobs (e.g. ‘If I looked for a job, I would probably wind up
with a better job than the one I have now’; α = .88). We measured job embeddedness
with Crossley et al.’s (2007) seven-item global measure of job embeddedness. An exam-
ple item is ‘I feel attached to this organization’ (α = .92). The results of omitting these
control variables (Becker, 2005) from hypotheses testing were qualitatively identical
(including regression coefficients and significance levels) to those shown below (these
results are available from the authors).
Analytical strategy
Because employees are nested in teams (Bryk and Raudenbush, 1992), we conducted
hierarchical linear modeling (HLM) analyses to test Hypotheses 1, 2 and 3, while
using hierarchical logit model analysis to test Hypotheses 4 and 5 as turnover is a
binary variable (French and Finch, 2010; Wong and Mason, 1985). For our analyses,
we chose group-mean centering approach when estimating the cross-level interaction
between identity strain and supervisory supportive climate (Liu et al., 2012). To more
validly test cross-level interaction, our analyses controlled for group-mean identity
strain and the group-mean identity strain × supervisory supportive climate interaction
to avoid confounding cross-level and between-group interactions (Enders and Tofighi,
2007; Hofmann and Gavin, 1998). We also used grand-mean centering to improve
interpretability, control individual-level effects when testing effects of group-level
variables, and lessen multicollinearity in group-level estimation (Hofmann and Gavin,
1998).
Main study results
Table 1 presents the means, standard deviations and correlations for study variables. We
used multi-level CFAs to test the discriminant validity of desirability of movement, job
embeddedness, rural identity, identity strain and supervisory supportive climate. Multi-
level CFA tests revealed that the five-factor measurement model fitted the data better (χ2
= 312.09, d.f. = 220, p < .001; RMSEA = .05, CFI = .94, TLI = .93) than a four-factor
model (rural identity and identity strain were combined; χ2 = 449.80, d.f. = 224, p < .001;
RMSEA = .08, CFI = .85, TLI = .83; Δχ2 = 137.71, Δd.f. = 4, p < .001), a three-factor
model (desirability of movement, rural identity and identity strain were combined; χ2 =
711.05, d.f. = 227, p < .001; RMSEA = .11, CFI = .68, TLI = .64; Δχ2 = 398.96, Δd.f. =
7, p < .001), a 2-factor model (desirability of movement, rural identity and identity strain
were combined; job embeddedness and supervisory supportive climate were combined;
χ2 = 856.34, d.f. = 229, p < .001; RMSEA = .13, CFI = .58, TLI = .54; Δχ2 = 544.25, Δd.f.
= 9, p < .001), and a one-factor model (all the five variables were combined; χ2 = 1087.14,
d.f. = 230, p < .001; RMSEA = .15, CFI = .43, TLI = .37; Δχ2 = 775.05, Δd.f. = 10, p <
.001) (Coovert and Craiger, 2000). Multi-level CFAs thus revealed that these five con-
structs were distinguishable.
814 Human Relations 72(4)
Table 1. Means, standard deviations and correlations of study variables.a.
Variable M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
1. Gender 0.92 0.26
2. Age 37.64 11.56 –.01
3. Marriage status 0.85 0.36 .06 .49***
4. Education 9.09 3.21 –.07 –.34*** –.19*
5. Tenure 2.23 5.45 .06 .29*** .07 .02
6. Years of working outside the home 12.60 9.63 .16*.62*** .34*** –.17*.35***
7. Number of children under 18 years 0.80 0.99 .01 –.06 .19*–.09 –.08 –.07
8. Working with spouse 0.13 0.34 –.47*** .01 .07 .08 –.07 –.11 .03
9. Work category 0.40 0.49 .19*.01 .12 –.17*.11 .11 .05 –.05
10. Working hours per day 9.46 1.60 .12 .03 .07+–.14 .03 .08 .18*–.15+–.01
11. Local dialect proficiency 1.90 1.11 .04 .12 .11 –.23** .06 .03 –.07 –.05 –.03 .02
12. Job satisfaction 3.28 0.72 –.05 .10 –.02 –.05 –.16*–.09 –.01 .03 –.08 –.15+.02
13. Desirability of movement 3.29 0.83 .12 –.23** .01 .10 –.08 –.11 .09 –.08 .11 .13+.01 –.23**
14. Job embeddedness 2.83 0.73 –.15+.28*** .11 –.23** .01 .02 –.12 .07 –.13 –.23** .17*.36*** –.29***
15. Rural identity 3.48 0.79 .06 .12 .14+–.19*.21** .11 .02 .03 .15+.12 .04 –.08 –.06 .11
16. Identity strain 2.80 0.67 .11 .09 .03 –.17*.19*.21** .12 –.16*.04 .03 .07 .00 .10 .02 .25***
17. Urban adjustmentc3.26 0.59 –.11 .22** .07 –.04 .03 .03 –.07 .06 .03 –.27*** .00 .27*** –.08 .26*** –.02 –.10
18. Supervisory supportive climateb3.41 0.31 .03 .15*.15*–.04 .09 .08 .04 .12 .00 –.12 .03 .15+–.07 .13+.14+.09 .38***
19. Turnoverc0.62 0.49 .00 –.07 .00 –.07 –.10 –.17*.07 .10 –.01 .18*.03 –.10 .13+–.09 .09 .07 –.25*** –.11
aThe individual-level N = 173; the group-level N = 31. All variables above were presented at their appropriate levels. Thus, for correlations of individual-level variables, N = 173; for cross-
level correlations, group-level data was aggregated, and N = 173.
bGroup-level variable.
cUrban adjustment was coworker-rated and turnover was assessed a year later.
M = mean; SD = standard deviation.
+p < .10. * p < .05. ** p < .01. *** p < .001.
Qin et al. 815
Tests of the hypotheses
Hypothesis 1 posits that migrant workers’ rural identity is positively associated with
identity strain. As Table 2 showed, the test of Model 2 revealed that migrant workers’
rural identity was positively related to their identity strain (
γ
=<
., .19 01p), after enter-
ing all controls (Model 1). Thus, Hypothesis 1 was supported.
According to Hypotheses 2 and 3, migrant workers’ identity strain is negatively
related to urban adjustment, while supervisory supportive climate attenuates this nega-
tive relationship. Similarly, in Table 3, all control variables and rural identity were first
entered in Model 1. Group-mean identity strain and identity strain were next added to
Model 2, and the test of this model indicated that identity strain was not significantly
related to urban adjustment (
γ
=−.,
..
10 ns ). In Model 3, after controlling for the between-
group interaction (Enders and Tofighi, 2007; Hofmann and Gavin, 1998), the cross-level
interaction between identity strain and supervisory supportive climate was significantly
related to urban adjustment (
γ
=<
., .67 01p). Following Cohen et al. (2003), we plotted
simple slopes in Figure 2 to interpret this interactive effect. Statistical tests of simple
slopes revealed that identity strain was negatively associated with urban adjustment
when supervisory supportive climate was low (
γ
=− <., .33 01p) but not significant
when supervisory supportive climate was high (
γ
=.,
..
08 ns ). Thus, Hypothesis 2 was
not supported, while Hypothesis 3 was supported.
Hypothesis 4 proposes that migrant workers’ urban adjustment is negatively related to
their turnover, while Hypothesis 5 predicts that migrant workers’ adjustment mediates
the interactive effect of identity strain and supervisory supportive climate on turnover. As
shown in Table 4, we estimated this cross-level interaction after including control vari-
ables, rural identity (Model 1), group-mean identity strain and identity strain (Model 2),
and the between-group interaction between group-mean identity strain and supervisory
supportive climate (Model 3). The test of Model 3 indicated that the cross-level interac-
tion was significantly and negatively related to turnover (
γ
=− <42
50
5., .p). Model 3
fitted data better than Model 2 (deviance = 8.81, p < .05). After next including urban
adjustment (Model 4), adjustment was significantly associated with turnover
(
γ
=− <18
30
1., .p), and the effect of the identity strain × supervisory supportive cli-
mate interaction shrank (
γ
=− <42
50
5., .pbecame
γ
=−306.,
..
ns ). Model 4 provided
better fit than Model 3 (deviance = 9.12, p < .01). Affirming Hypotheses 4 and 5, these
findings revealed that urban adjustment mediated the interactive effect of identity strain
and supervisory supportive climate on turnover. Pseudo R2s reported in our test were
comparable to estimates from studies on turnover (e.g. Li et al., 2016) and repatriate
turnover (e.g. Kraimer et al., 2012), which appeared in journals requiring both theoretical
and practical implications. Thus, our model including identity strain and urban adjust-
ment and standard turnover predictors explained a reasonable amount of variance in
migrant workers’ turnover.
Discussion
Many international scholars and journalists are documenting exorbitant attrition among
rural migrants in emerging economies, who are essential for economic development of
816 Human Relations 72(4)
Table 2. Hierarchy linear model results for Hypothesis 1: The effect of migrant workers’ rural
identity on their identity strain.a
Variables Identity strain
Model 1 Model 2
Intercept 2.81***
(0.05)
2.81***
(0.05)
Gender –0.02
(0.21)
–0.05
(0.21)
Age −0.01
(0.01)
–0.01
(0.01)
Marriage status –0.12
(0.16)
–0.15
(0.16)
Education –0.03+
(0.02)
–0.03
(0.02)
Tenure 0.02*
(0.01)
0.01
(0.01)
Years of working outside the home 0.02*
(0.01)
0.02*
(0.01)
Number of children under 18 years 0.10*
(0.05)
0.10*
(0.05)
Working with spouse –0.23
(0.16)
−0.27+
(0.16)
Work category –0.06
(0.11)
–0.09
(0.10)
Working hours per day –0.02
(0.03)
–0.04
(0.03)
Local dialect proficiency 0.02
(0.04)
0.03
(0.04)
Job satisfaction 0.05
(0.07)
0.07
(0.07)
Desirability of movement 0.12+
(0.06)
0.13*
(0.06)
Job embeddedness 0.03
(0.08)
0.00
(0.08)
Rural identity 0.19**
(0.06)
σ2.37 .35
τ (intercept) .02 .01
Proportion within-group variance explainedb.05
N (level 1) 173 173
N (level 2) 31 31
Deviancec324.43 315.40
aThe standard errors in the estimations are reported in parentheses.
bThe proportion of variance explained was calculated based on the parameters in Model 1.
cDeviance is a measure of model fit; the smaller the deviance is, the better the model fits. Model deviance =
–2 × log-likelihood of the full maximum-likelihood estimate.
+p < .10. * p < .05. ** p < .01. *** p < .001.
Qin et al. 817
Table 3. Hierarchy linear model results for Hypotheses 2 and 3: The effect of migrant
workers’ identity strain on their urban adjustment.a
Variables Urban adjustment
Model 1 Model 2 Model 3
Intercept 3.27***
(0.05)
3.64***
(0.40)
3.86***
(0.35)
Gender –0.18
(0.18)
–0.19
(0.18)
–0.24
(0.17)
Age 0.01*
(0.01)
0.01*
(0.01)
0.01+
(0.00)
Marriage status 0.00
(0.14)
–0.01
(0.14)
–0.08
(0.13)
Education 0.00
(0.01)
–0.00
(0.01)
–0.00
(0.01)
Tenure 0.00
(0.0–1)
0.00
(0.01)
0.00
(0.01)
Years of working outside the home –0.01
(0.01)
–0.00
(0.01)
−0.00
(0.01)
Number of children under 18 years –0.00
(0.04)
0.01
(0.04)
0.00
(0.04)
Working with spouse –0.07
(0.14)
–0.11
(0.14)
–0.12
(0.13)
Work category 0.08
(0.09)
0.07
(0.09)
0.05
(0.08)
Working hours per day –0.08**
(0.03)
–0.09**
(0.03)
–0.07**
(0.03)
Local dialect proficiency –0.01
(0.04)
–0.01
(0.04)
–0.03
(0.03)
Job satisfaction 0.15*
(0.06)
0.16*
(0.06)
0.12*
(0.06)
Desirability of movement 0.06
(0.05)
0.07
(0.05)
0.06
(0.05)
Job embeddedness 0.08
(0.07)
0.08
(0.07)
0.08
(0.06)
Rural identity –0.01
(0.05)
0.01
(0.06)
–0.02
(0.05)
Group–mean identity strain –0.13
(0.14)
–0.21+
(0.12)
Identity strain –0.10
(0.07)
–0.13+
(0.07)
Supervisory supportive climate 0.97
(0.84)
Between-group interaction
Group-mean identity strain × Supervisory
supportive climate
−0.12
(0.30)
(Continued)
818 Human Relations 72(4)
their societies through their employment in export-oriented manufacturing and domestic
infrastructure (Beamish, 2006; Zhou and Sun, 2011; Harney, 2010; Staelens and Louche,
2017). Yet the available UCEA turnover literature furnishes an incomplete understanding
about why they quit jobs as they are so unlike UCEA workforces in culture, precarious
employment and rural-to-urban transition (Lee, 2016). Contributing to the scant and nar-
row research on DW precariat turnover, we adopt an identity strain perspective to pro-
vide a fuller explanatory account of why Chinese migrants quit. Using a two-wave,
multiple-source and multi-level research design, we found that peasant laborers harbor-
ing strong provincial identities feel identity strain that induces them to quit, especially
when they lack supervisory supportive climates. We further demonstrated that urban
adjustment mediates the interactive effect of identity strain and supervisory supportive
climate on migrant turnover.
Implications for theory
Our findings offer several important theoretical contributions. First, we broaden the
scope of current inquiries into DW precariat attrition by identifying identity strain as a
pivotal turnover driver. Existing empirical studies in emerging economies focus on
migrants’ workplace conditions or job opportunities but neglect how other influences
arising from challenging role transitions and urban adaptation can underpin leaving
(Chen et al., 2016; Miller et al., 2001; West, 2004). Such preoccupation with ‘movement
desirability and ease’ (March and Simon, 1958) as explanatory constructs reflects their
prominence in classic and modern turnover theories (Bluedorn, 1982; Hom et al., 2017;
Variables Urban adjustment
Model 1 Model 2 Model 3
Cross-level interaction
Identity strain × Supervisory supportive climate 0.67**
(0.26)
σ2.259 .253 .227
τ (intercept) .01 .02 .00
Proportion within-group variance explainedb.02 .12
Proportion between-group variance explainedb– 1.00
N (level 1) 173 173 173
N (level 2) 31 31 31
Deviancec266.43 263.66 234.37
aThe standard errors in the estimations are reported in parentheses.
bThe proportion of variance explained was calculated based on the parameters in Model 1.
cDeviance is a measure of model fit; the smaller the deviance is, the better the model fits. Model deviance =
-2 × log-likelihood of the full maximum-likelihood estimate.
+p < .10. * p < .05. ** p < .01. *** p < .001.
Table 3. (Continued)
Qin et al. 819
Lee and Mitchell, 1994; Price and Mueller, 1981) as well as the well-documented plight
of DW migrants who assume 3-D jobs to escape rural poverty (Friedman and Lee, 2010;
Maertz et al., 2003; Ngai and Huilin, 2010; Xu, 2013). By contrast, our study demon-
strates that identity strain can be a salient trigger of rural migrants’ turnover. We propose
that migrant workers’ role transitions—from peasants in rural villages to wage workers
in metropolises—evoke psychological strain that initiates their leaving urban work-
places. Our research thus extends longstanding scholarship on how work-related identi-
fication deters leaving (Mael and Ashforth, 1995; Riketta, 2005). Organizational
identification studies rarely—if ever—scrutinize how other identification targets (e.g.
prior occupation or lifestyle) interfere with employees’ identification with a current
employer (Shapiro et al., 2016) and induce leaving by creating identity strain.
Second, we established that supervisory supportive climate, serving as a job resource,
can lessen identity strain’s deleterious effects on job loyalty. Our findings thus sustain a
key JD-R tenet that holds that resources can attenuate the adverse impact of job demands
on employee welfare or performance (Bakker and Demerouti, 2007; Qin et al., 2014).
For migrants in teams exposed to poor supervisory supportive climates, high identity
strain boosts their quit likelihood. In comparison, high supervisory supportive climates
can mute how identity strain impels workers to quit. As role transitions and identity
strain tend to increase turnover, identifying factors counteracting their effects are
noteworthy.
Third, we identify urban adjustment as a central mechanism underlying the interactive
effects of identity strain and supervisory supportive climate on turnover. That is, high
identity strain diminishes urban adjustment, and such diminution is greater when peasant
laborers belong to groups subject to poor supervisory supportive climates. Poor urban
adjustment thus triggers turnover. Prior research suggests identity strain owing to expa-
triate-repatriate role transitions directly boosts quits (Kraimer et al., 2012), yet our
Figure 2. The moderating role of supervisory supportive climate on the relationship between
identity strain and urban adjustment.
820 Human Relations 72(4)
Table 4. Hierarchy logistic model results for Hypothesis 4 and 5: The effects of migrant
workers’ identity strain and urban adjustment on their turnover.a
Variables Turnover
Model 1 Model 2 Model 3 Model 4
Intercept 0.89+
(0.47)
–2.70
(3.43)
–1.28
(3.83)
–0.28
(4.35)
Gender 0.49
(1.17)
0.53
(1.15)
0.34
(1.24)
–0.11
(1.37)
Age –0.00
(0.03)
–0.00
(0.03)
0.01
(0.03)
0.01
(0.04)
Marriage status 0.30
(0.77)
0.34
(0.78)
0.31
(0.82)
0.50
(0.88)
Education –0.02
(0.09)
–0.01
(0.09)
0.02
(0.09)
0.02
(0.10)
Tenure –0.03
(0.05)
–0.03
(0.05)
–0.02
(0.05)
–0.00
(0.05)
Years of working outside the home –0.04
(0.04)
–0.05
(0.04)
–0.05
(0.04)
–0.06
(0.04)
Number of children under 18 years 0.08
(0.23)
0.03
(0.24)
–0.03
(0.25)
–0.09
(0.27)
Working with spouse 1.58+
(0.93)
1.67+
(0.94)
1.66+
(0.97)
1.74
(1.12)
Work category 0.17
(0.57)
0.18
(0.57)
0.19
(0.59)
0.10
(0.64)
Working hours per day 0.43*
(0.20)
0.47*
(0.20)
0.49*
(0.21)
0.46*
(0.23)
Local dialect proficiency 0.05
(0.22)
0.02
(0.22)
0.08
(0.23)
0.06
(0.25)
Job satisfaction –0.07
(0.36)
–0.12
(0.36)
0.02
(0.39)
0.25
(0.45)
Desirability of movement 0.06
(0.29)
0.02
(0.30)
0.03
(0.30)
0.12
(0.33)
Job embeddedness –0.11
(0.40)
–0.09
(0.40)
–0.23
(0.41)
–0.09
(0.43)
Rural identity 0.34
(0.32)
0.22
(0.34)
0.21
(0.38)
0.25
(0.41)
Group-mean identity strain 1.28
(1.22)
0.82
(1.35)
0.54
(1.53)
Identity strain 0.39
(0.42)
0.83
(0.54)
0.75
(0.58)
Supervisory supportive climate 12.14
(8.96)
16.31
(10.55)
Between-group interaction
Group-mean identity strain × Supervisory
supportive climate
–4.89
(3.21)
–6.02
(3.76)
(Continued)
Qin et al. 821
inquiry reveals that adjustment in new challenging contexts, such as unfamiliar host
country or urban locale, is a heretofore missing intervening mechanism.
Finally, we improve upon burgeoning scholarly inquiries into DW precariat quits
by using multiple sources to assess model components, while estimating their ability
to predict rural migrants’ actual turnover independently of its well-established funda-
mental antecedents (Mitchell and Lee, 2013). Past studies on DW precariat attrition
mostly regressed quit intentions or past quits onto antecedents (Jiang et al., 2009; Qin
et al., 2014; Smyth et al., 2009; Tello et al., 2002; Tiano, 1994). Besides common
method bias, their failure to use the ‘standard’ time-lagged or longitudinal research
design to forecast turnover behavior (Hom et al., 2017) overstates predictive validity
as such criteria poorly proxy future behavior (Vardaman et al., 2015). What is more,
the few time-lagged tests fail to assess both movement ease and desirability (March
and Simon, 1958), essential for establishing predictors’ incremental validity or verify-
ing even rudimentary turnover models (Chen et al., 2016; Linneman and Blau, 2003;
Miller et al., 2001).
Implications for practice
A shortage of migrant workers now looms in China, exacerbating the turnover problem
(Choi and Peng, 2015; Siu, 2017). As noted above, excessive migrant attrition adversely
affects organizations (Beamish, 2006; Harney, 2010), such as decreased organizational
efficiency and profitability (Park and Shaw, 2013), and may even undermine a nation’s
development model (especially one ‘predicated on surplus and cheap migrant labor’;
Lee, 2016: 325). Our findings yield several suggestions for abating migrant turnover.
First, managers must recognize that migrant workers’ provincial identity can engender
identity strain and turnover. Organizations can take measures to facilitate their
Variables Turnover
Model 1 Model 2 Model 3 Model 4
Cross-level interaction
Identity strain × Supervisory supportive
climate
–4.25*
(2.11)
–3.06
(2.30)
Urban adjustment –1.83**
(0.70)
N (level 1) 173 173 173 173
N (level 2) 31 31 31 31
Devianceb182.97 181.15 172.34 163.22
R2c .08 .09 .13 .18
aThe standard errors in the estimations are reported in parentheses.
bDeviance is a measure of model fit; the smaller the deviance is, the better the model fits. Model deviance =
-2 × log-likelihood of the full maximum-likelihood estimate.
cR2 is the pseudo R2 (or called McFadden’s R2), which is defined as 1 – log-likelihood of the current model/
log – likelihood of the null model. + p < .10. * p < .05. ** p < .01. *** p < .001.
Table 4. (Continued)
822 Human Relations 72(4)
rural-to-urban adaptation, preventing identity strain from progressing into departures.
Alternatively, employers might recruit migrant workers not only on the basis of technical
competence but also on their rural identity and interpersonal adaptability using employ-
ment testing and interviews (Gui et al., 2012). By so doing, new recruits may better
assimilate to the workplace and community at large (Aycan, 1997). Because of their flex-
ibility in relating to people, interpersonally adaptive migrants may more readily forge
intimate ties to urbanites and develop greater felt belongingness in the new urban envi-
ronment (Zhong et al., 2016).
Like cross-cultural training for expatriates, we also suggest providing new hires—
especially new migrants to urban centers—with realistic previews about urban work and
community roles (Hom et al., 1998). Such work and lifestyle previews would forewarn
them about upcoming urban challenges in employment (e.g. adapting to assembly-line
work rules) and living circumstances (e.g. urban noise and crowds; Howard, 1965;
Zhong et al., 2016). Moreover, such previews might explicitly address the prospects of
identity crisis and offer psychological techniques on how they might cope with identity
conflicts (e.g. self-management tips; Hom and Griffeth, 1995). What is more, employers
can instruct new migrants on local dialect, customs and culture and expand their social
networks to include urban natives (Liu, 2015; Yue et al., 2013). Employers might also
encourage more contact with urbanites by sponsoring outings, hosting social events
involving urbanites, or reducing work hours or days so that peasant workers can socialize
with community members (Swider, 2015; Zhong et al., 2016).
Organizations may also provide migrant workers with mentors from their hometown
with whom they more easily communicate and more readily develop rapport (Liao et al.,
2015; Liu, 2015). As in the situation of expatriates, Feldman and Bolino (1999: 55) sug-
gested that ‘mentors not only play an important part in helping expatriates learn their
new organizational roles, but are also critical in helping them adjust to new national
cultures as well’ (p. 55). Employers may also furnish benefits denied to migrants because
they lack urban hukou, such as housing and medical care, or help them acquire official
temporary residential permits (Kim, 2015; Zhong et al., 2016). By so doing, firms reduce
the stigma of second-class citizenship and thus encourage migrants to identify with local
residents—perceiving that they and city residents are ‘all Chinese’ (Zhong et al., 2016:
10). Greater identification can induce migrants to form social ties with urbanites.
Finally, our results suggest that supervisors play a vital role in whether migrants’ iden-
tity strain translates into higher turnover. Organizations can enlarge resources for supervi-
sors and train supervisors on how to offer instrumental and expressive support to help
migrants handle this distress. Specifically, they can offer emotional comfort to migrants
struggling with identity conflicts or enlist their co-workers who had effectively resolved
identity strain to provide social support (Kraimer et al., 2001). Along these lines, we further
suggest that supervisors avoid excessive LMX differentiation in their dealings with subor-
dinates (Seo et al., 2018) to promote a supervisory supportive climate.
Strengths, limitations and future directions
Using multi-phase, multi-source and multi-level data, the current research adopts an
identity strain perspective to investigate why peasant laborers quit. Going beyond prior
Qin et al. 823
studies of developing-world precariat departures, our predictive research design estab-
lished that urban adjustment (reflecting the interaction between identity strain and super-
visory support climate) explains unique variance in turnover behavior after controlling
key turnover determinants. Despite its multiple methodological strengths, our test suffers
from several shortcomings that future research might address. First, this research studied
only supervisory supportive climate as a buffer against identity strain. Conceivably,
resources a worker personally receives from the supervisor (i.e. perceived supervisory
support, an individual-level construct; Eisenberger et al., 2002) may act as a similar
buffer (though differential support may backfire; Seo et al., 2018). Future research might
thus assess perceived supervisory support as well as other resources, such as supervisor
justice treatment (Qin et al., 2017b), and families or friends relocating to the same urban
community who can help migrants adapt to urban work and life. Some job demands (e.g.
abusive supervision, Qin et al., 2017a) that may exacerbate the detrimental effects of
identity strain also warrant further investigation. Moreover, our demonstration of the
mediating role of urban adjustment does not preclude other mediators that further inquiry
might identify. Further, our test yielded limited evidence for causality. We thus prescribe
future longitudinal research designs to strengthen evidence for theorized causal direc-
tions, such as assessing variables’ change trajectories and their dynamic relationships.
Future research may identify the etiology of precariats’ rural identity. For example,
having close family members (e.g. parents and siblings) still living in the home village
may preserve rural identity. Including such antecedents can deepen understanding of
migrants’ identity strain and turnover. Furthermore, apart from rural identity, subsequent
research might assess how much migrants identify with the host urban society to more
fully decipher the origins of identity strain (Gui et al., 2012). After all, acculturation
scholars conclude that integration of immigrants’ home-country identity and new-coun-
try identity is the optimal adaptive mode of acculturation and most conductive to well-
being (Gui et al., 2012; Phinney et al., 2001). In our research, we presumed a linear,
bipolar model whereby rural and urban identification represent a bipolar continuum such
that strengthening one identity entails weakening the other. Yet Gui et al. (2012) corrobo-
rated a two-dimensional model among PRC migrants who can exhibit both strong or
weak rural and urban identification. Future inquiries might explore how identity strain
and its turnover effects vary across different identification profiles, such as high rural and
urban identities or high rural identity but low urban identity.
Although incorporating well-established turnover causes (i.e. job satisfaction, per-
ceived alternatives and job embeddedness; Hom et al., 2017) and demographic predic-
tors (Rubenstein et al., 2018), our theoretical framework may benefit from additional
explanatory constructs. For example, future conceptual refinements may include fam-
ily embeddedness (Ramesh and Gelfand, 2010) as families hold great sway over turno-
ver decisions, especially when they rely on workers’ wages for subsistence (Myerson
et al., 2010), and turnover contagion, as high turnover in this workforce induce more
turnover (Maertz et al., 2003). Psychological contract fulfillment (Chih et al., 2016) is
another potential addition because labor contractors often violate psychological con-
tracts by failing to pay workers or paying them less than initially promised (Ngai and
Huilin, 2010; Swider, 2015). Also, as revealed in Tables 3 and 4, we found that longer
working hours per day were associated with poorer urban adjustment and higher
824 Human Relations 72(4)
turnover. Thus, combining work characteristics and psychological factors may deepen
insight into precariat turnover.
Furthermore, future scholarship might identify where migrant workers go (Hom et al.,
2012), such as other jobs in the same locales or relocations to other cities or home.
Conceivably, migrants may stay in the city or move to another city but better resolve
identity strain in other companies without returning home. They may receive superior
resources (e.g. tuition aid for children’s local schooling, factory housing) from other
firms that help them transition to urban work and life environments. By relocating to cit-
ies nearer rural homelands, they might find more fellow villagers employed in the same
workplace—that is, their native community ‘embedded’ within the workplace (Mitchell
et al., 2001). Finally, we sampled only PRC migrant workers in a construction group.
While focusing on one company controlled organizational variability in human resource
practices and allowed for more rigorous data collection, it limited our findings’ general-
izability. Also, although we believe that our findings are somewhat generalizable for
precariat rural migrants, we concede that China differs culturally and institutionally from
other countries, while construction work is especially hazardous and offers unstable pay
(unlike other industries; Swider, 2015). We thus urge future replications in other devel-
oping countries and other industries.
Conclusion
Our research sheds new light on why rural migrants in emerging economies quit. We
found that migrant workers’ identity stain—intensified by strong rural identity—
increases turnover for those belonging to work groups with poor supervisory supportive
climates, and that urban adjustment mediates the interactive effect of identity strain and
supervisory supportive climate on turnover. Our study thus reveals how the rural-to
urban transition—and the identity strain it evokes—underlies DW migrant turnover. This
research expands the limited scholarly inquiry into extra-work or noneconomic forces
driving DW laborers to quit. As Ramesh and Gelfand (2010) showed, greater insight into
why workforces in societies outside UCEA countries leave may even enrich and extend
prevailing turnover theories.
Author’s note
All authors contributed equally to this article.
Funding
We would like to thank the National Natural Science Foundation of China (grant numbers:
71502179 and 10901010), a Fulbright Scholarship, the support from Center for Statistical Science
in Peking University, and the Key Laboratory of Mathematical Economics and Quantitative
Finance (Peking University), Ministry of Education.
Notes
1 Given scale definitions, two doctoral candidates in management also evaluated how closely
each item reflects migrant workers’ rural identity or identity strain. These judges correctly
Qin et al. 825
classified all items into their respective scales and rated them as strongly indicative of their
underlying constructs. Our measures thus had content validity (Hinkin, 1998).
2 Specifically, a PRC research assistant fluent in English translated the original English-
language scales into mandarin Chinese. Then, another PRC research assistant also fluent in
English translated those Chinese questions back into English. Reviewing both versions, the
author team concluded that the original English and back-translated English scales had the
same meanings. Further, another bilingual professional copy-editor checked the conceptual
and cultural consistency of the two language versions and confirmed that connotations were
similar across both versions. The translators and copy-editor had no prior knowledge of the
research questions and purpose. When adapting English items assessing rural identity and
identity strain, a member of the author team fluent in both languages ensured that the Chinese
translation retained the original meaning of the English scales.
3 Specifically, years of farming was assessed by asking: ‘How many years of farming experi-
ence do you have?’ We measured work-family conflict with Netemeyer et al.’s (1996) five-
item scale (α = .88). Turnover intentions were assessed by Camman et al.’s (1979) questions
(α = .85).
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Xin Qin is an associate professor in the Sun Yat-sen Business School, Sun Yat-sen University,
China and also is a Fulbright visiting scholar in Harvard Business School. He received his PhD in
Qin et al. 833
organizational management from Guanghua School of Management, Peking University. His
research focuses on leadership, ethics and migrant turnover. He has published papers in Academy
of Management Journal, Strategic Management Journal, Journal of Applied Psychology,
Organizational Behavior and Human Decision Processes, Human Relations, Personnel
Psychology, Journal of Business Ethics, and so on. [Email: qinxin@sysu.edu.cn]
Peter W Hom is a professor of Management at the WP Carey School of Business, Arizona State
University, USA. His research interests include employee turnover and job embeddedness. He has
published in various scholarly journals, including Academy of Management Journal, Journal of
Applied Psychology and Journal of Management. He co-authored two books (with Rodger
Griffeth): Retaining Valued Employees and Employee Turnover. [Email: peter.hom@asu.edu]
Minya Xu is an associate professor in the Guanghua School of Management at Peking University,
China. She received her PhD from Rutgers, the State University of New Jersey, USA. She majored
in statistics and specialized in application of statistical methods to management. In recent years,
she has conducted various research in employee work behavior such as employee voice, deviant
behavior and turnover. Her research has been published in The Annals of Statistics, Biometrika,
Journal of Business & Economic Statistics, Journal of Applied Psychology, Journal of
Organizational Behavior, Journal of Occupational and Organizational Psychology, Journal of
Business Ethics, and so on. [Email: minyaxu@gsm.pku.edu.cn]
Appendix: Scale items for rural identity and identity strain
Rural identity
1. I think of myself as a peasant.
2. My rural experience continues to be a very important part of my life.
3. To me, my (past) rural experience defines a large part of who I am.
4. What distinguishes me from others is that I came from rural areas.
Identity strain
1. As coming from rural areas as a peasant, I have been having trouble defining who
I am here at this company.
2. Sometimes, I feel like my rural experience doesn’t fit my current job.
3. There are times when there seems to be a conflict between what I am asked to do
now and what I had learned as a peasant.
4. There is a tension between who I am on my current job and who I was during my
rural experience.
5. I feel that my role as a former peasant is not compatible with my current role as
a member of this organization.
