Psychological Contracts and the Informal Social Structure of Organizations:
Systemic and Local Effects
Guillermo E. Dabos
Management Department
Universidad de San Andrés & UNICEN
Victoria, Buenos Aires B1644BID, Argentina
Tel: (54 11) 4725-7000 (Ext. 7154)
Fax: (54 11) 4725-7010
gdabos@udesa.edu.ar
Denise M. Rousseau
Heinz School of Public Policy and Management
and Tepper School of Business
Carnegie Mellon University
Pittsburgh, Pennsylvania 15213
Tel: (412) 268-8470
Fax: (412) 268-5338
rousseau@andrew.cmu.edu
WORKING PAPER
An earlier version of this paper won the Organizational Behavior Division Best Paper
Award and appears in the 2004 Academy of Management Meeting Proceedings. We wish to
thank David Krackhardt and Violet Ho for their contributions to this paper. A Heinz
Foundation Research Chair supported this research.
ABSTRACT
Using network analysis, the link between informal social structure and psychological contracts is
examined via data collected from 96 university faculty members. Effects vary by type of contract
term. When psychological contract terms involve competitive resources, significant relationships
are found for advice centrality, a systemic or network-wide effect. When psychological contract
terms involve non-competitive resources, proximity yields relationships via both direct
friendship ties (cohesion) and similar friendship ties with other faculty members (structural
equivalence), a local effect.
Psychological Contracts and the Informal Social Structure of Organizations:
Systemic and Local Effects
The relationship between employee and employer is increasingly viewed through the lens
of the psychological contract, that is, the system of beliefs an individual holds regarding the
terms of the exchange agreement with the organization (Rousseau, 1995). During the last decade,
the concept of psychological contract has received a wealth of attention in employment research.
Scholars have predominantly investigated the nature and content of the psychological contract
(e.g., Rousseau, 1990; Herriot, Manning, & Kidd, 1997) and the consequences associated with
contract fulfillment, violation, and change (e.g., Robinson, Kraatz, & Rousseau, 1994; Robinson,
1996; Coyle-Shapiro & Kessler, 2000; Turnley & Feldman, 2000). This research demonstrates
that contract fulfillment increases employee satisfaction, trust in the employer, and intent to
remain in the organization, whereas contract violation engenders intense negative reactions on
the part of employees who, in consequence, often cut back on their commitment and
contributions to the organization. Moreover, it also confirms that individuals with different
psychological contracts respond differently to contract fulfillment, violation, and change (e.g.,
Robinson & Rousseau, 1994; Robinson & Morrison, 1995; Rousseau & Tijoriwala, 1999).
Although these findings are noteworthy in terms of understanding and effectively
managing the employment relationship, research is also needed on how psychological contracts
are formed in the first place. To date, little is known about the factors shaping psychological
contract beliefs. Psychological contract theory postulates that several factors operate in forming
individual beliefs regarding the employment relationship’s terms, including internal individual
predispositions and cognitive schemas, and external cues provided by human resource practices,
communication with managers, recruiters, and coworkers, and other social influences (Rousseau
& Greller, 1994; Rousseau, 1995, 2001, in press). Yet, direct empirical examinations of how
internal individual constructions and external organizational and social influences affect
psychological contract formation are rare (see Raja, Johns, & Ntalianis, 2004, for an exception).
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The present study addresses this often overlooked issue by investigating the relationship of
informal social influence within the organization to employee beliefs regarding promises the
employer has made.
This study examines two levels of informal influences resulting from employee social
interaction. At the individual-level, it investigates the relationship between an individual’s
psychological contract beliefs and those beliefs held by socially-proximate coworkers in both the
informal friendship and advice networks. Individuals tend to hold work-related attitudes,
perceptions, and beliefs similar to those of other employees with whom they interact frequently
in local or confined areas of a social network (e.g., Dean & Brass, 1985; Rice & Aydin, 1991;
Ibarra & Andrews, 1993; Burkhardt, 1994; Pastor, Meindl, & Mayo, 2002). Local effects based
on network proximity reflect social influences transmitted through interpersonal ties. Although
similarity in beliefs can create friendship or advice seeking ties, shared beliefs can also be a
consequence of these social interactions. To examine the basis for this similarity, we investigate
both close ties based upon frequent interaction between two parties such as friends or advicegivers (i.e., cohesion) and indirect ties via similar sets of friends or advice-givers (i.e., structural
equivalence). At the organization-level, the informal social structure can afford individuals
differential access to and control over resources depending upon their network position or social
standing. Individuals in powerful or high status positions in an organization’s informal network
can thus hold beliefs regarding psychological contract terms differing from those of their less
well-positioned counterparts. Systemic effects from informal social position are investigated by
examining the relationship an individual’s centrality in the larger informal social structure has
with his or her beliefs regarding the strength of the employer’s obligations.
This study investigates local and systemic influences resulting from social interaction
across types of contract obligations and network ties. In particular, we examine whether the
effects of social interaction differ for psychological contract terms involving scarce resources
distributed competitively (e.g., support for professional development) and non-competitive
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resources that when offered are widely available (e.g., congenial or safe work environment). We
also examine whether the relationship between social interaction and psychological contract
beliefs differs for network ties based upon personal friendship and work-related advice giving. In
all, the present study addresses three fundamental issues: (1) the link between informal social
network processes and employee psychological contracts, (2) how interpersonal ties among
proximate individuals and position in the informal social structure relate to specific
psychological contract terms (i.e., competitive and non-competitive), and (3) how different types
of network ties (i.e., friendship and advice) are related to psychological contract beliefs.
Psychological Contract Theory
An employee’s psychological contract constitutes his or her interpretations regarding
reciprocal obligations with the employer. The psychological contract, by definition, is subjective
in nature and belongs to the domain of individual beliefs (Rousseau & Parks, 1993; Rousseau,
1995). Employees can develop different understandings of what the employer has promised to
them, even when efforts are made to convey similar promises to all employees (e.g., safe work
environment) or to specific groups of employees (e.g., seniority-based benefits for core workers).
Psychological contracts are shaped by multilevel factors including the individuals’ internal
predispositions (e.g., cognitive styles, self-schemas) and the external influences that operate in
the work setting (e.g., human resource practices, social cues). Among them, the social interaction
patterns at work are particularly likely to affect the creation of meaning around the promises
exchanged and the perceptions of the scope of obligations associated with them. For example,
informal interactions such as helping train newcomers or assisting coworkers in do their jobs can
lead employees to believe that the employer has an obligation to reciprocate (Rousseau, in press).
Psychological contract theory postulates the existence of multiple contract makers within
an organization, including coworkers, managers, mentors, recruiters, and other organizational
actors, along with administrative signals such as human resource practices (Rousseau & Parks,
1993; Rousseau & Greller, 1994; Rousseau, 1995). Organizational insiders play a key role during
3
formal socialization, influencing newcomers’ perceptions of the exchange terms by providing
information and cues that enable them to interpret events, learn about their ropes, and incorporate
work-related norms and standards of behaviors (Louis, 1980; Nelson & Quick, 1991; Morrison,
1993). Coworkers in particular are often the most available and frequently accessed source of
information about the job, the organization, its policies and procedures. For instance, coworkers
can provide overt statements or direct evaluations of the job, make certain aspects of the
workplace more salient by talking frequently about them, or tip the balance in ambiguous
situations by offering socially-constructed interpretations (e.g., depending on whether employees
trust the management, a change in technology may be seen as a threat to the status quo or,
alternatively, as organizational support for improved performance).
An employee can gather information from coworkers through two commonly available
mechanisms: verbal statements providing information about the job and direct observation or
monitoring of practices and behaviors (Rousseau, 1995). The messages various coworkers
convey can sometimes reflect inconsistent or contradictory views of the same practices or
behaviors. Regardless of their consistency, the readily available social cues coworkers offer are
postulated to play an essential role in the psychological contracting process by “providing
messages for contract creation, conveying social pressure to conform to the group’s
understanding of the terms, and shaping how individuals will interpret the organization’s
actions” (Rousseau, 1995: 39).
Recent research has addressed the effect of social influence on employee evaluations of
psychological contract fulfillment (Ho, 2002). Such evaluations involve an assessment of the
discrepancy between what was promised by the employer and what was delivered in turn, an
important concept in explaining how psychological contract violation arises (Rousseau, 1995;
Morrison & Robinson, 1997). Ho (2002) postulates that an employee’s evaluation of fulfillment
is contingent not only on his or her own perceived discrepancy (between what was promised and
delivered), but also on the discrepancy experienced by his or her social referents (i.e., other
4
individuals selected as targets for comparison such as coworkers and supervisors). While Ho
found some support for the role of social referents such as friends and substitutes in shaping
employee evaluations of psychological contract fulfillment, little empirical evidence exists
regarding the relationship between social interaction patterns and psychological contract beliefs.
Social Interaction Patterns
The impact of social interaction on attitudes, perceptions, and beliefs has been broadly
established since the early research on social influence and conformity (e.g., Festinger, 1954;
Asch, 1955, 1956; Deutsch & Gerard, 1955). Asch, for instance, provides compelling evidence
of conformity to group pressure in his experiment using simple comparisons of lines with
obvious differences in length. He found that individuals with normal vision would ignore their
own objective judgment to publicly agree with an inaccurate group judgment. Deutsch and
Gerard identified two main reasons for conformity: (1) the individual’s concern for making
accurate judgments (informational influence), and (2) the individual’s concern for seeking social
approval (normative influence). Festinger’s theory of social comparison offers further insights
into processes of social influence. He argues that individuals use the opinions and beliefs of
similar others as a reference point in evaluating their own opinions and beliefs. Reliance upon
social comparisons is stronger in ambiguous situations where objective standards to validate
one’s own opinions and beliefs are not available. Nonetheless, even in situations that are not
ambiguous, social influence can operate through the impact of authority, individual affiliation or
identification, and desire for group acceptance (Ajzen & Fishbein, 1973; Moscovici, 1976,
1985). In organizations, the social structure plays an active role in the comparison process either
by constraining the availability of information about potential referents (Goodman, 1977) or by
imposing certain non-selected or forced comparisons (Allen & Wilder, 1977; Wood, 1989).
The role of the social context in shaping individuals’ attitudes, perceptions, and beliefs
also has been recognized in theories of social information processing (e.g., Salancik & Pfeffer,
1978; Blau & Katerberg, 1982; Zalesny & Ford, 1990) and sensemaking (e.g., Greenberg, 1995;
5
Weick, 1995; Gioia & Thomas, 1996). In particular, social information processing posits that
“the multiple social influences on attitudes [and perceptions] are more consequential for
predicting attitudes [and perceptions] at work than are individual needs or other characteristics”
(Salancik & Pfeffer, 1978: 248). In organizations, these influences stem from social processes
occurring at two different levels: local influences from the individual’s more immediate social
interactions and systemic influences from the larger informal social structure in which
individuals are embedded (Ibarra & Andrews, 1993). In the sections that follow, we use a social
network perspective to discuss both local and systemic influences and to develop a framework
for examining the processes by which social interaction patterns relate to employee
psychological contract beliefs.
Local Influences: Interaction among Socially-Proximate Individuals
The people with whom an individual interacts on the job can directly or indirectly affect
his or her attitudes, perceptions, and beliefs. In the social network literature, two primary
mechanisms account for the influence observed among socially-proximate pairs of individuals:
cohesion and structural equivalence. Influence via cohesion occurs through direct (i.e., nonmediated) relationships with other members of the social system. Cohesion denotes “simple
adjacency whereby two actors are proximate if, and only if, they are directly tied in a network”
(Marsden & Friedkin, 1994: 7). The frequent communication and emotional closeness that
characterize cohesive relationships offer ample opportunities for engaging in information sharing
and social comparison. Over time, people can come to adopt attitudes, perceptions, and beliefs
similar to those of others with whom they are directly tied. Direct exposure to others’ opinions
and behaviors influences the saliency of information and in turn the focal individual’s attitudes,
perceptions, and beliefs (Rice & Aydin, 1991; Burkhardt, 1994). Indirect exposure, occurring
through intermediaries, has weaker effects (Friedkin, 1982; Erickson, 1988). Selection effects
can also operate such that people seek out and remain in relationships with others who share their
beliefs.
6
The effects of cohesion are well-documented in a classic study of social influence in the
diffusion of a medical innovation (Coleman, Katz, & Melzer, 1966). Coleman and colleagues
observed that physicians resolved the uncertainty surrounding the adoption of a new drug by
engaging in informal interactions primarily through direct ties of a professional nature such as
advisors or discussion partners. Moreover, this advice was supplemented by information they
obtained from friends in the medical community. Frequent discussions about the effects of the
new drug and whether others prescribed it led physicians to adopt beliefs and prescribing
behaviors similar to those with whom they had direct ties. Likewise, studies have found cohesion
to influence other work-related perceptions (Ibarra & Andrews, 1993), beliefs about personal
mastery (Burkhardt, 1994), attitudes toward a new technology (Rice & Aydin, 1991), attributions
about fellow employees (Krackhardt & Kilduff, 1990), and patterns of behaviors during jobsearch (Kilduff, 1990). The substantive basis of influence via cohesion hinges upon cooperation
and solidarity among directly tied individuals (Marsden & Friedkin, 1994; Shah, 1998). When
the opinion of members embedded in cohesive networks become manifest, it promotes
agreement and compromise (Friedkin, 1993, 1998).
Alternatively, influence via structural equivalence occurs when individuals share access
to the same people in a social system. Structural equivalence exists when a pair of individuals
has identical ties or relationships with other actors in a network (Lorrain & White, 1971;
Marsden & Friedkin, 1994). That is, two individuals are structural equivalent if both have ties
with (and thus lack ties with) identical sets of other individuals. Because structural equivalent
individuals occupy similar roles in the social system, they are likely to be exposed to similar
information and social demands, and therefore to develop similar attitudes, perceptions, and
beliefs. Two things are worth noting about structural equivalence. First, it defines roles in terms
of the pattern of social ties between members of a social system, not in terms of the formal
organizational structure (Rice & Aydin, 1991). In other words, two product managers who
perform exactly equivalent jobs in the formal organization structure, but lack common ties to
7
other organizational members are not structural equivalent. Second, frequent contact is not
required for a pair of structural equivalent individuals to reach attitudinal or perceptual
convergence. Regardless of the strength of any direct relationship, social influence via structural
equivalence occurs to the extent that two individuals are involved in the same set of ties with
other people from whom they both develop similar attitudes, perceptions, and beliefs. Thus, for
example, two doctoral students are structurally equivalent in the advice network if both have
exactly the same advisory committee (regardless of whether the two students ever interact).
Insofar as structurally equivalent people need not chose their tie to each other, effects of
structural equivalence are less attributable to self-selection. However, structural equivalents may
hold common beliefs as a result of having selected themselves into roles where those beliefs are
compatible with role-senders, as in the case of graduate students who select a similar set of
advisors because of shared interest in a subject. Informal roles are likely to be a source of
information regarding the employer’s obligations since psychological contract beliefs are tied to
post-recruiting communications as well as initial employer promises (Thomas & Anderson,
1998; Rousseau, in press).
Burt (1987) depicted the effects of structural equivalence reexamining Coleman et al.’s
(1966) data from the medical innovation study. He concluded that when social influence
occurred among physicians it was not because of their direct interactions with other colleagues
but because of their perceptions of what a proper action would be given the role each physician
occupied in the social system of colleagues. Structural equivalence also influences attitudes
toward computers (Burkhardt, 1994), perceptions of task variety (Meyer, 1994), judgments
regarding product development (Walker, 1985), attitudes toward technology adoption (Burkhardt
& Brass, 1990; Rice & Aydin, 1991), and perceptions of the social context (Pattison, 1994). The
effects of structural equivalence on shared beliefs have also been attributed to similar
socialization, equivalent role demands, comparable experiences and constraints (Rice & Aydin,
1991; Marsden & Friedkin, 1994; Shah, 1998), such as the case of the two doctoral students with
8
the same advisory committee. Thus, effects of structural equivalence need not come through
direct interaction but from common experiences in the organization and informal social system.
These experiences can form the basis of shared schemata or mental models regarding one’s role
and relationship with the employer, giving rise to comparable psychological contract beliefs
(Rousseau, 2001).
Systemic Influences: Relative Standing in the Informal Social Structure
The larger informal social structure shapes the opportunities and constraints individuals
encounter, affecting their attitudes, perceptions, and beliefs. Systemic influences in organizations
stem from differential access to and control over resources (Emerson, 1962; Pfeffer & Salancik,
1978). The position each individual has in the organization’s informal network impacts his or her
access to valued resources such as financial support and career opportunities. Individuals better
positioned to access and use valued resources enjoy more opportunities for obtaining their
desired goals, and thus are likely to develop more positive perceptions of the employment
exchange. In an informal social network, an important indicator of position is centrality
(Friedkin, 1998). People with greater centrality in the network possess superior resource control,
more power, and higher status compared to their less central counterparts (Ibarra & Andrews,
1993), and thus centrality reflects the relative standing of the individuals in a social system
(Frank, 1985). Accordingly, benefits and opportunities within organizations accrue to those who
occupy a central position in the network of informal relationships because of their superior
access to and control over valued resources (Burt, 1982; Brass, 1984; Ibarra, 1993). Whereas
most research has focused on centrality in organizations as a source of leadership and power
(e.g., Burkhardt & Brass, 1990; Krackhardt, 1990; Brass & Burkhardt, 1993; Ibarra, 1993),
centrality also shapes attitudes, perceptions, and beliefs by enhancing or constraining the
opportunities for individual goal attainment (Friedkin, 1993, 1998; Ibarra & Andrews, 1993).
Centrality in the informal social structure differs from cohesion and structural
equivalence in the way it influences beliefs. In the case of centrality, the frequent interaction
9
characterizing cohesion is not essential to shaping individuals’ beliefs. Neither is the extent to
which individuals are structurally equivalent or involved in similar sets of ties with other people.
Rather, centrality’s influence on individual beliefs stems from power or status differentials in the
larger informal structure that affect the allocation and use of valued resources. Individuals with
high-status informal positions relative to others develop more positive attitudes and perceptions
of the work setting (Frank, 1985, Ibarra & Andrews, 1993).
Types of Psychological Contract Beliefs
The type of beliefs studied matters in understanding informal social effects. In workplace
psychological contracts, the social information workers look to in forming their beliefs can
depend upon the resources involved. In particular, whether these resources are accessed via
competition with others can determine the sources of social information used (Ho, 2002). In a
study of fulfillment evaluations, Ho found that workers rely on different social networks for
competitive and non-competitive resources in gauging whether their employer has fulfilled its
obligations. Competitive resources refer to those that are scarce in an absolute or socially
imposed sense. Resources can be scarce because of constraints in the available amount (e.g.,
limited project budget, promotions in a hierarchical firm) or allocation rules that restrict
attainment (e.g., seniority-based benefits; Hirsch, 1976). In the presence of abundant or noncompetitive resources, an individual’s attainment does not condition the likelihood of others’
future attainment.
Employer promises regarding a competitive resource imply that access is granted
selectively. Whether a resource is allocated competitively impacts not only the likelihood that
individuals will expect to receive that resource but also whether they consider their relative
standing compared to others in estimating their likelihood of attainment. Attaining competitive
resources depends on factors shaping individual standing, including performance and factors
affecting it such as resource access and support from powerful others. Workers in powerful or
high status positions are more likely to successfully compete for resources and are better able to
10
negotiate support from powerful others than are their less well-positioned counterparts. Part of
this support from powerful others has been found to include promises regarding developmental
activities, visible projects, participation in key decisions, and information critical to job
performance (Rousseau, in press). It follows that central individuals develop more positive
beliefs regarding promises involving competitive resources than do peripheral individuals.
Hypothesis 1: An individual’s centrality in the organization’s informal social structure will
be positively related to the strength of psychological contract beliefs involving competitive
resources.
Conversely, when promises relate to non-competitive resources, one person’s attainment
need not diminish another’s. Social processes based on mutual support or identification tend to
prevail in the latter case, triggering convergent beliefs in socially-proximate individuals. In the
network literature, accounts of how social influence occurs center around two arguments
described above: cohesion and structural equivalence. Because direct ties are built upon frequent
contact, cooperation, and feelings of kinship such as liking or esteem, cohesive coworkers are
likely to develop similar beliefs in promises relating to non-competitive resources. By
conforming to the beliefs of cohesive others, an individual also satisfies his or her concern for
securing social approval (Deutsch & Gerard, 1955). Alternatively, influence from structural
equivalence occurs by means of similar access to or common ties with other organizational
members. Employees who occupy similar roles in the informal organization are likely to
experience comparable social demands and socialization from the same others. Regardless of the
strength of any direct relationship, employees who share relationships to the same people are
likely to develop similar beliefs regarding promises that relates to non-competitive resources.
Conformity to the opinions held by structurally equivalents satisfies an individual’s concern for
adopting beliefs appropriate for a particular role in the informal organization (Burt, 1987). In
contrast, centrality based on power or status differentials is unlikely to be very influential in
shaping psychological contracts if promises relate to resources that when offered are widely
11
available. Status differences afford no advantage in accessing resources that are abundant. For
promises pertaining to non-competitive resources, cohesion and structural equivalence are
expected to shape employee psychological contracts.
Hypothesis 2a: The psychological contract beliefs of coworkers to whom an individual is
directly tied (cohesion) will be positively related to comparable beliefs of that individual with
regard to non-competitive resources.
Hypothesis 2b: The psychological contract beliefs of coworkers with whom an individual
shares similar ties in the organization (structural equivalence) will be positively related to
comparable beliefs of that individual with regard to non-competitive resources.
Bounding the Effects of Social Interactions
Though we have postulated direct relationships between informal social structure and
psychological contract beliefs, certain boundary conditions can affect the strength of these
relationships. People have different motives when interacting with each other, thus creating a
diverse array of relationships within a social structure (Krackhardt & Brass, 1994; Marsden &
Friedkin, 1994). Social network research categorizes network types by the content of the tie or
nature of the relationship. Two types of ties have been extensively examined: (1) instrumental
ties that arise from work-related interactions such as giving or receiving advice, and (2)
expressive ties that arise from emotional closeness such as friendship and personal support.
Previous research has shown that different ties yield different outcomes (e.g., Krackhardt, 1990,
1992; Ibarra, 1992; Ibarra & Andrews, 1993). For instance, employees tend to rely on friendship
ties for dealing with highly stressful circumstances such as radical change or organizational
crises (Krackhardt, 1992), but often use advice ties for coping with task uncertainty at work
(Burkhardt & Brass, 1990; Rice & Aydin, 1991).
Although both shape work-related beliefs, advice and friendship relationships channel
their influences in different ways. Advice networks reflect instrumental action on the part of the
employee and tend to influence beliefs through the effects of centrality, whereas friendship
12
networks reflect expressive motives and do so through proximity (Ibarra & Andrews, 1993).
Advice relationships are likely to emerge over the course of work-related interactions as
individuals mobilize resources to obtain desired outcomes. Often formed based upon the
centrality of individuals in the informal social structure, advice relationships can be characterized
as “weak, asymmetrical ties that serve as connections to disparate parts of the social system and
that are critical for instrumental action” (Ibarra & Andrews, 1993: 283). As such, their patterns
are likely to reflect systemic influences resulting from power or status differentials. Conversely,
friendship relationships are often formed based upon similarity in interests, personal attributes, or
organizational affiliation. Friendship ties tend to be symmetrical and characterized by frequent
contact and emotional intimacy (Granovetter, 1973, 1982). As such, friends are often perceived
as reliable sources for information regarding their own and third parties’ (e.g., friends of friends,
structural equivalents) opinions and behaviors. The type of network interaction therefore is
expected to bound both systemic and local effects with regard to psychological contract beliefs.
In consequence, the systemic effects of centrality on psychological contract beliefs are more
likely to be observed in advice relationships (Hypothesis 1), and the local effects of proximity
(Hypotheses 2a and 2b) more likely in friendship relationships.
Methods
Sample and Procedure
Data were collected at a bioscience school of a growing national university in Latin
America. The initial phase of the project consisted of regular site-visits and semi-structured
interviews with faculty members, departmental heads, and school’s authorities. The goals were
twofold: (a) to obtain an understanding of the research context, its culture, structure, and
activities, and (b) to adapt a widely-used psychological contract instrument (Rousseau, 2000) to
the specific context of this research so that survey items assessed employment conditions
meaningful to respondents. During the second phase, faculty members completed questionnaires
containing psychological contract statements and sociometric questions. This study used surveys
13
in Spanish. To guarantee consistency with the original English scales, survey measures were
independently translated back and forth from the original English version (Brislin, 1980). The
few discrepancies in meaning resulting from the comparison of the two versions of the
questionnaires in the source language were solved by the bilingual author using a process of
consultation and collaboration with bilingual members of the school’s top management team
(Frey, 1970). School administrators, technical staff, and part-time faculty were not included in
this research due to the very distinct nature and content of their work. Participants were assured
that all survey responses would be confidential. Demographic data were collected from official
administrative records.
All 107 full-time faculty members in the three major academic departments at the school
were surveyed, yielding 96 completed surveys (89.72%). At the school, the dominant human
resource strategy was to develop its own faculty by supporting their formal education for the job.
Almost 60% of the faculty held a graduate degree. Respondents represented the five formal
positions of the tenure system in this university: 21% assistant professors (the typical entry
level), 27% senior assistant professors, 28% associate professors, 18% senior associate
professors, and 6% full professors. They were fairly evenly distributed with respect to gender (51
were male and 45 were female). Average age was 39.42 years (SD = 7.43 years). Average
organizational tenure was 12.36 years (SD = 7.23 years), reflecting a relatively low turnover rate.
Measures
Sociometric indices. Respondents were provided with a complete roster of full-time
faculty and asked to place a check next to the names of the faculty members (1) to whom their
went for help or advice regarding work-related problems and general organizational matters, and
(2) with whom they went to lunch or met socially outside of work on a frequent basis. These
answers provided the raw data to define advice and friendship networks, respectively. A cell
entry Xij in the raw advice sociomatrix was coded 1 if faculty i went to faculty j for advice and 0
otherwise. Because this research also required measures of power or status differences,
14
asymmetries in responses were preserved to make a distinction between being the origin (source)
or destination (object) of a relational tie (Burt, 1982). An actor has higher power or status when
he or she is the destination of a relational tie, reflected by the actor’s indegree in the raw
sociomatrices. In the advice sociomatrix, for example, an actor’s indegree reveals the number of
other people who go to that actor for advice. Thus, the transpose of the raw sociomatrices was
used to represent the relationship (i.e., being sought after for advice).
Structural equivalence. Structural equivalence measures similarity in access to other
people. Two actors are structural equivalent when they have identical relations with others in a
network (Lorrain & White, 1971; Marsden & Friedkin, 1994). That is, the two actors have ties
with and lack ties with identical sets of other actors. However, this restrictive definition of
structural equivalence is seldom realized in actual networks given that the likelihood of having
two actors with exactly identical ties decreases dramatically with the size of the network. For that
reason, structural equivalence was operationalized here in terms of degree using the Pearson
product correlation coefficient of every pair of actors computed on both the rows and columns
entries of the sociomatrices (Borgatti, Everett, & Freeman, 2002). In this procedure, diagonal
elements are treated as missing values. Results are interpreted such that the greater the
correlation coefficient for a given pair of actors, the greater their structural equivalence. We
assessed structural equivalence in both advice and friendship sociomatrices.
Centrality. Because the focus is on power or status differences, centrality was
operationalized using the Bonacich’s c(,) measure which allows for different relationships
between power or status and centrality (Bonacich, 1987). This measure is formally defined as:

c ( ,  )     k R k 1 1
k 1
In this formula,  is a scaling factor used to normalize the measure, R is the transpose of
the raw sociomatrices,  is an attenuation factor, and 1 is a column vector of ones. Central to the
definition of the Bonacich’s power-based centrality measure is the parameter , which reflects
15
the extent to which an actor’s power is contingent on the power of other actors to whom he or
she is connected in the network. When  > 0, it means that not all relationships contribute
equally to an actor’s power; that is, being connected to powerful others increases an actor’s
power in the network, whereas being connected to powerless others is not very consequential. By
simply setting different  values, the c(,) measure can account for all possible relationships
between power and centrality. In particular, when β = 0, the formula yields results proportional
to degree centrality because direct ties are taken into account regardless of the other actors’
centralities. Of particular interest for the present study is the case when β > 0, which reflects that
an actor’s power is positively affected by his or her connections to other powerful actors.
Because higher values of β give greater weight to the systemic power structure (as opposed to
the local structure), we set the attenuation factor β at three-quarters of its upper bound given by
the reciprocal of the largest eigenvalue of the R matrix (cf. Podolny, 1993). Finally, the
Bonacich’s measure is suitable for both symmetric and asymmetric networks; yet, it measures
centrality in the former and power (as long as  > 0) in the latter. For that reason, it was essential
to preserve the asymmetries in the data. Reciprocation rates of 23.98% for advice and 60.47% for
friendship reflect the distinctive nature of these two types of relationships.
Psychological contract scales. Using items adapted from the Psychological Contract
Inventory (PCI) (Rousseau, 2000), faculty evaluated the extent to which the employer had made
such promises or commitments to them. All items used a 5-point Likert type scale response
format ranging from 1 (not at all) to 5 (to a great extent). Faculty responded to several
statements assessing promises that relate to both competitive and non-competitive resources. In
particular, three dimensions of the PCI were framed in terms of scarce resources and thus used to
denote promises relating to competitive resources. Dynamic performance describes the extent of
the employer provided resource necessary to support faculty projects and successful fulfillment
of performance requirements. The scale consisted of three items including resource support to
16
attain the highest possible levels of performance, to respond to ever greater academic challenges,
and to meet increasingly higher goals. Cronbach’s alpha () for the scale was 0.89. Career
development describes the extent of resource support for faculty advancement and development
opportunities enhancing faculty long-term employability. The scale consisted of three items
including resource support for training and development within the organization, for conference
attendance and participation in professional events, and pursuit of further formal academic
education ( = .79). Involvement in the organization describes the extent to which employees
enjoy opportunities for high involvement in the organization. The scale consisted of three items
including involvement in organizational matters, participation in decision making, and
participation in ad-hoc committees ( = .86).
In our examination of the research setting, we found these three dimensions of the PCI
suitable to reflect promises relating to competitive resources. In the case of support for
performance and for career development, budget constraints limited both resources allocated to
projects and to employee development opportunities. Although the school had several programs
supporting its core activities of teaching, research, and outreach, faculty had to compete for that
funding by submitting internal proposals for project performance and scholarly development.
Due to limited funds many proposals failed to receive support and solid proposals often obtained
only partial support. The competitive nature of organizational involvement derives from
structural requirements restricting faculty involvement and participation. A faculty member’s
participation in one or more of the several committees that governed the school was contingent
on meeting specific criteria (such as rank or tenure) and/or being elected or appointed for the
position (which often necessitated building sufficient political support).
In addition, three other dimensions of the PCI were found suitable to represent promises
relating to non-competitive resources. Security describes whether the employer has committed to
offering stable benefits and long-term employment. The scale consisted of three items including
17
secure employment, wages and benefits the employees can count on, and stable benefits for
employees and families ( = .85). A promise involving wages was categorized as noncompetitive because faculty wages in this university were regulated by the federal government.
Loyalty describes the extent of the employer’s concern for the well-being and long term interests
of employees. The scale consisted of three items including the employer’s concern for employee
welfare, responsiveness to employee concerns and well-being, and whether the employer makes
decisions with employee interests in mind ( = .79). Finally, predictability describes the extent
of certainty regarding the employer’s future commitments. The scale consisted of three items
including predictability regarding the future direction of this employment relationship, future
commitments to employees, and future demands ( = .82). Interviews with top management in
the school indicated that they sought to build an open-ended relational agreement with faculty to
provide a stable personnel base with which to pursue the school’s long-term strategic goals.
Security, loyalty, and predictability are core features of relational employment arrangements.
We examined the discriminant validity of the psychological contract scales using a
confirmatory factor analysis with maximum likelihood estimation. Using Amos 5, the factor
structure reached the standards of good fit along a variety of indices. The ratio of chi-square
relative to its degrees of freedom (2/df) was 1.133, considerably better than the suggested ratio
of 2 (Arbuckle & Wothke, 1999). Incremental fit index (IFI) and comparative fit index (CFI) of
.978, and Tucker-Lewis index (TLI) of .972 were all above the recommended standard of .90.
Finally, the factor structure presented a root-mean-square error of approximation (RMSEA) of
0.037, suggesting a reasonable fit to the hypothetical population covariance matrix of optimally
chosen parameter values (i.e., RMSEA values less than .05, Browne & Cudeck, 1993).
Control Variables. Data analyses controlled for several additional variables to rule out
alternative explanations of the results, including effects of employee characteristics and formal
positions (Rice & Aydin, 1991; Burkhardt, 1994). Among the demographic variables, we
18
controlled for gender, organizational tenure, educational level, and individual prestige. Gender in
particular is often associated with access to opportunities in academic settings (e.g., rank
advancement, Long, Allison, & McGinnis, 1993), with men often enjoying better opportunities
than women. Faculty tenure in the university, measured in years, was controlled for because
employees from similar cohorts are likely to share similar experiences and thus to develop
similar perceptions at work (Krackhardt & Kilduff, 1990). Educational level is also likely to
condition access to and control over resources, with those holding doctoral degrees enjoying
better opportunities within the university. Finally, faculty members with higher reputation or
prestige can have preferred access to resources based on their past achievements. Prestige was
measured using a weighted index of number of referred publications, conference presentations,
and invited seminars that this university used for internal appraisals. In addition, academic
departments and rank were the two structural variables included in the analysis. As described
above, faculty belonged to three different academic departments and represented the five formal
positions of the tenure rank (coded from 1 to 5). Table 1 presents the means, standard deviations,
and correlations between all relevant variables.
-----------------Insert Table 1 about here
-----------------Data Analysis
A central methodological concern in social network research is how to approach the
problem of autocorrelation. The relational observations in the sociomatrices are interdependent
because they represent patterns of location and interaction among individuals in the informal
social structure. A correlation exists between the perceptions of a person in a given location
within the informal social structure and the perceptions of others in neighboring locations (e.g.,
his or her friends, advice-givers, or structural equivalents). In the presence of network
autocorrelation, ordinary-least-squares (OLS) procedures cannot be used to test the significance
19
of regression coefficients. Previous research has shown that increasing autocorrelation weights
produce biased OLS tests, where significance levels tend to be consistently overestimated
(Krackhardt, 1987, 1988). One frequently used technique for coping with the network
autocorrelation problem is the Quadratic Assignment Procedure (QAP), a nonparametric,
permutation-based approach to test for network effects in relationships where both predictor and
outcome variables are represented in network or dyadic form. Yet, QAP has also been used to
test social influence by examining whether the patterns of interaction among pairs of individuals
are related to attitudinal or perceptual similarity (e.g., Burkhardt, 1994; Ho, 2002; Pastor,
Meindl, & Mayo, 2002). To assess the degree of similarity in attitudes and perceptions, these
studies used dissimilarity matrices constructed by transforming the vector of individual ratings
on the scale measuring the attitude or perception of interest into a square matrix composed of
absolute differences between ratings for each pair of individuals. This model presents important
limitations because it does not provide a direct test of social influence (i.e., whether the rating of
an individual in a given location is affected by the ratings of others in neighboring locations)
while incurring in a loss of relevant information (i.e., whether the individuals’ ratings on
attitudes or perceptions were more positive or negative).
A superior model for directly testing the social influence process is the network
autocorrelation model, also known as mixed regressive spatial autoregressive model (Cliff &
Ord, 1981; Doreian, 1982; Doreian, Teuter, & Wang, 1984; Anselin, 1988). This method
accounts for network autocorrelation by including a lagged dependent variable (Wy) as one of
the explanatory variables and yields parameter estimates for the independent variables that can
be interpreted in the same way as in OLS regression. Although several procedures exist for the
estimation of network autocorrelation models, the maximum likelihood (ML) is the most
extensively used and the one with the best overall performance (Leenders, 2002). Formally, the
model can be expressed as
y = ρWy + X + ε
20
where y is a vector of observations on the dependent variable, W represents the strength
of the influence process between every pair of observations, ρ is the network autoregressive
coefficient that represents the average effect of others’ ratings on the dependent variable on one’s
own rating, X is a matrix of observations on the exogenous explanatory variables with its
associated vector of regression coefficients , and ε is the vector of normally distributed random
error terms with zero means and constant variances. Based on the assumption of normal error
term, an iterative maximum likelihood approach can be used to estimate the coefficients of the
network autocorrelation model. The autoregressive coefficient ρ associated with the inclusion of
the lagged term is an estimate of the degree and direction of the network dependence or
proximity effect, such that ρ reflects the extent to which the perception of an individual in a
given location is shaped by the perceptions of others in neighboring locations within the social
space. At the same time, the inclusion of the lagged term allows for an examination of exogenous
variables while controlling for the network dependence in the observations.
Central to the implementation of this model is the specification of the W weight matrix
representing the dyadic-level process by which influences are transmitted among sociallyproximate individuals (Leenders, 2002). Different specifications of the weight matrix can reflect
various proximity-based mechanisms of social influence and types of social ties. In this study,
we computed the weight matrix on the basis of cohesion and structural equivalence in both
advice and friendship networks. However, the alternative weight structures were tested in
separate models due to current limitations in the estimation procedures for network dependence.
Limitations also make it impossible to test directly for differences in the magnitude of effects for
influence mechanisms or types of social ties. To estimate the model, all W matrices were rowstandardized by dividing each element in a row by the corresponding row sum. In the case of
binary matrices (e.g., advice), this means that each outgoing tie exerts the same amount of
influence on the focal actor and that the total influence accepted is equal for all actors.
21
Our model also includes the corresponding measures of centrality, individual
characteristics, and formal position. One caveat for use of this maximum likelihood analysis is
that its standard error of estimate tends to be underestimated in smaller samples. Because
statistical inference in maximum likelihood estimation is based on asymptotic (or large-sample)
properties, it can yield an overly optimistic indication of significance in smaller samples
(Anselin, 1988). This study’s sample size (N=96) is relatively large by network research
standards where N’s typically are below 80 (e.g., Rice & Aydin, 1991; Friedkin, 1993; Ibarra &
Andrews, 1993; Burkhardt, 1994; Meyer, 1994). Because the small sample corrections that exist
do not apply to network autocorrelation models, we employ .01 as our criterion for statistical
significance. Results at the .05 level will be reported but interpreted with caution.
Results
Using network indices derived from advice ties, Table 2 presents the regression analyses
for the psychological contract terms involving competitive resources: support for performance,
support for career development, and involvement opportunities. For each of them, cohesion and
structural equivalence are included in separate regression equations. Then, each regression model
is presented in two steps so that effects of informal social structure can be more clearly
identified. In step I, we report the estimates of all the control variables along with the
corresponding effect of local proximity (cohesion or structural equivalence). In step II, centrality
in the larger informal social structure is also entered into the regression equation allowing for a
simultaneous examination of both local and systemic effects.
Overall, our results provide support for Hypothesis 1 that centrality is related to those
employee psychological contract beliefs involving competitive resources. In particular, centrality
in the advice network was related to employee beliefs regarding the extent to which the employer
had promised support for performance even after controlling for the effects of cohesion (B =
1.951, p < .001) or structural equivalence (B = 1.879, p < .001). Likewise, advice centrality was
significantly related to employee beliefs regarding involvement opportunities (B = 1.483, p <
22
.01, and B = 1.469, p < .01, after controlling for cohesion and structural equivalence,
respectively). In addition, faculty member prestige was positively related to beliefs regarding
performance support, whereas his or her rank or formal position in the tenure system was
positively related to beliefs regarding involvement opportunities. Neither cohesion nor structural
equivalence predicted psychological contract beliefs regarding performance support or
involvement opportunities.
-----------------Insert Table 2 about here
-----------------Advice centrality was not significantly related to beliefs regarding support for career
development. In this case, however, we did find a significant (albeit unexpected) effect of
structural equivalence for advice ties (ρ = 0.377, p < .01, and ρ = 0.358, p < .05, before and after
controlling for advice centrality, respectively). In other words, having similar access to other
faculty in the advice network shapes employee beliefs regarding the extent of support for career
development. It is worth noting, however, that results at the .05 level should be interpreted with
caution in light of the model’s tendency toward underestimating standard errors in small
samples. In addition, tenure was negatively related to psychological contract terms relating to
support for career development, suggesting that more recently-hired faculty held more positive
beliefs regarding advancement and development opportunities than did long-tenured faculty.
Finally, we used network indices derived from friendship ties to examine relationships with those
psychological contract terms involving competitive resources. Unlike findings regarding advice
ties, no significant relationship was found between either proximity or centrality in friendship
ties with employee beliefs involving competitive resources (See Table 3).
-----------------Insert Table 3 about here
-----------------23
Turning to psychological contract terms involving non-competitive resources, results
partially support hypotheses 2a and 2b. Proximity in the advice network, based either on
cohesion or on structural equivalence, had no significant relationship with psychological contract
terms regarding job security and stable benefits or genuine concern for employees (see Table 4).
Cohesion in advice ties, however, was significantly related to employee beliefs regarding the
predictability of the employment relationship’s future direction (ρ = 0.336, p < .01, and ρ =
0.278, p < .05, before and after controlling for advice centrality, respectively). Faculty members
tend to hold beliefs regarding the predictability of their employment relationship’s future that are
similar to those of other faculty to whom they go to for advice regarding work-related issues.
Moreover, advice centrality yielded a significant (albeit unexpected) relationship to beliefs
regarding the future of one’s employment in the organization (B = 0.945, p < .05), suggesting
that individuals who enjoy a central position in the advice network tend to develop more positive
beliefs regarding the future of their employment with the organization. Lastly, faculty rank was
also positively related to beliefs regarding predictability, a result plausible given the nature of the
stable employment relationship characteristic of academia’s higher ranks.
-----------------Insert Table 4 about here
-----------------Table 5 presents the regressions of psychological contract terms involving noncompetitive resources upon the relationship and control variables. The friendship proximity
measures, that is, cohesion and structural equivalence, were strongly related to employee beliefs
regarding job security and stable benefits, even after controlling for friendship centrality (ρ =
0.360, p < .001 for cohesion, and ρ = 0.433, p < .001 for structural equivalence). These results
suggest that, when assessing promises regarding job security and stable benefits, a relationship
exists between the beliefs of an individual and those of both close friends and structural
equivalents in the friendship network. Likewise, both cohesion and structural equivalence in the
24
friendship network were significantly related to beliefs regarding the employer’s genuine
concern for employees (after controlling for friendship centrality, ρ = 0.233, p < .05 for
cohesion, and ρ = 0.303, p < .05 for structural equivalence). As noted above, these latter results
at the .05 level should be interpreted with caution. Proximity in the friendship network, on the
other hand, was not a significant predictor of employee beliefs regarding predictability of the
employment relationship. Finally, friendship centrality was unrelated to the three psychological
contract terms relating to non-competitive resources.
-----------------Insert Table 5 about here
-----------------Taken together, the regressions above provide evidence for boundary conditions
operating on the relationships between social interaction and psychological contract beliefs. The
relationship of centrality to psychological contract beliefs was significant for advice ties but not
for friendship. This pattern was particularly evident for beliefs involving competitive resources
such as support for performance and involvement opportunities in the organization. Centrality in
the friendship network had no significant association with any psychological contract belief
studied here. Because the Bonacich’s centrality measure allows for different relationships
between power and centrality, we also conducted follow-up examinations setting different values
for , that is, the parameter representing the extent to which an actor’s power depends on the
power of the other actors with whom he or she is connected. In results not presented here, we
confirmed that regression coefficients for both advice and friendship centrality were stable and
consistent with those reported here along an ample range of meaningful  values (0.5    1).
Furthermore, we also confirmed the stability and consistency of these relationships when both
advice and friendship centrality were entered into the same equation.
Proximity’s relationships, in contrast, were significant for friendship ties and particularly
with psychological contract terms involving non-competitive resources (e.g., security and stable
25
benefits, concern for employees). Although proximity in the advice network also demonstrated
some significant relationships with psychological contracts (i.e., cohesion on beliefs regarding
predictability and structural equivalence on beliefs regarding career development), overall, the
effects of proximity manifest in the friendship network.
Finally, in the two cases where both proximity-based mechanisms yielded significant
relationships with psychological contract beliefs (i.e., security and stable benefits, and concern
for employees, see Table 5), we conducted a follow-up examination to determine whether
relationships involving cohesion dominated those of structural equivalence, or vice versa.
Augmented regressions were used to test non-nested hypotheses by considering each
specification of the weight matrix (i.e., cohesion or structural equivalence) in turn as an
alternative hypothesis (Anselin, 1984, 1988; Leenders, 2002). In formal terms, the two
alternative specifications are represented in pairwise fashion, as follows:
H0 : y = ρcWcy + Xc + ε
H1 : y = ρseWsey + Xse + ε
where Wc represents the weights for cohesion, Wse represents the weights for structural
equivalence, and the X matrix of observations on the exogenous variables is the same in both
models. First, the structural equivalence model (H1) is considered in an attempt to falsify the
cohesion model (H0, set as the null in the previous formulation). This simply requires a test for
the significance of a nesting coefficient  in the following augmented regression:


y  (1  )(cWcy  Xc)  ( seWsey  X  se )  


where  se and  se are ML estimates calculated from the alternative specification using
structural equivalence only (H1). This test is also known as the J-test (Davidson & MacKinnon,
1981). In the model, a significant  would reveal that the null specification is rejected in favor of
the alternative specification, suggesting that structural equivalence provides a superior account
for the influence structure than does cohesion. However, because the J-test is not symmetric, the
26
test must be carried out again but reversing the roles of null and alternative hypotheses. In other
words, the cohesion model (now set as alternative hypothesis) is considered in an attempt to
falsify the structural equivalence model (now set as null). A problem with the J-test is that
several results are possible. Ideally, one specification is rejected in favor of the other. But is also
possible that neither of the hypotheses can be rejected or that both hypotheses can reject each
other. Therefore, the test may or may not indicate the presence of a superior specification.
Our results reveal that cohesion dominated structural equivalence for psychological
contract terms relating to job security and stable benefits. In particular, when cohesion was set as
null, the alternative specification using structural equivalence could not reject the null hypothesis
( = 0.67, n.s.). On the other hand, when we reversed the roles setting structural equivalence as
null, the alternative specification using cohesion rejected the null hypothesis ( = 2.17, p < 0.05).
Although both proximity-based mechanisms were significantly related to employee beliefs
regarding the extent of job security and stable benefits (see Table 2), this result suggests that
being close friends (cohesion) may provide a superior account for social influence than having
similar friendship ties (structural equivalence). Finally, for psychological contract terms relating
to the employer’s genuine concern for employees, no single specification could falsify the other.
Discussion
This study calls attention to the advantages of examining psychological contracts in the
context of the informal social structure in which employees are embedded. In large measure, the
core hypotheses of this study are supported, underscoring the relationship between social factors
and employee psychological contracts. Simultaneously examining social processes operating at
different levels reveals relationships between psychological contract beliefs and both systemic
effects of centrality in the larger informal social structure and local effects of proximity between
pairs of individuals. The specific relationships involving centrality and proximity depend on the
particular contract obligations and social tie examined. We note also that while causal direction
is not directly tested in the present study, the pattern of results is largely consistent with the role
27
of informal social structure as a source of information regarding the psychological contract
between employees and their organization.
Centrality is positively related to worker beliefs in psychological contract terms involving
competitive resources. People differing in their standing in the larger informal social structure
hold distinct views of their employment relationship but only for obligations regarding
competitive resources such as financial support and influence over decisions. Insofar as
individuals with high standing are well-positioned to receive employer commitments regarding
both competitive and non-competitive resources, we observe that their standing is related only to
competitive resources. Moreover, if sense of entitlement leads people to seek central positions,
their levels of all psychological contract beliefs should be elevated. Since highly central
individuals do not manifest across-the-board entitlement, it seems more likely that their belief in
access to competitive resources is due to their informal power. Individuals in powerful positions
are better able to fill requests for others, to contribute effectively, and otherwise engage in
actions that create beliefs that the employer is obligated to reciprocate by providing them special
access to scarce resources (cf. Flynn, 2003, Rousseau, in press). This pattern of results suggests
that centrality is a cause rather than a consequence of holding particular psychological contract
beliefs.
The fact that relationships with centrality were found for advice but not for friendship ties
provides support for the notion that advice ties are critical for instrumental action as individuals
mobilize resources to obtain desired goals (Ibarra & Andrews, 1993). It further supports a
resource-based view of centrality predicated upon power or status differentials. Those who are
better positioned to control how resources are allocated often enjoy better organizational
opportunities. In consequence, they develop more positive beliefs in promises involving
competitive resources. Power or status differences often coincide with the rank or position each
individual holds in the formal organizational hierarchy. In this study, rank was positively related
to psychological contract beliefs regarding organizational involvement, suggesting that faculty
28
members with superior positions expect to enjoy better opportunities to participate in decisions.
Nonetheless, effects of rank diminished considerably when advice network centrality was
entered into the equation (see step II, Table 2). This result suggests that the effects of formal
position may in part be captured by relative standing in the informal social structure surrounding
advice ties. In general, the relationship between centrality and psychological contract beliefs are
not only substantial but can be greater than formal sources of influence.
Proximity was expected to be positively related to beliefs pertinent to non-competitive
resources. This relationship was partially supported using both cohesion and structural
equivalence to specify proximity. In particular, for psychological contract terms regarding job
security and stable benefits, workers were found to hold beliefs similar to those of their close
friends (cohesion) and to those of others with whom they shared close friends (structural
equivalence). A comparable albeit weaker relationship was also found for terms regarding the
extent of employer concern for employees. These results suggest that friendship ties
characterized by frequent contact and emotional closeness play a role in shaping promissory
beliefs pertinent to non-competitive resources. Notably, the observed relationships associated
with the friendship network occur both directly through close friends and indirectly via
friendship ties with similar others. To a certain extent, this finding can reflect the confounding
effects of cohesion and structural equivalence (Burt, 1987). When friendship ties are embedded
within cohesive subgroups confined to specific areas of the network (e.g. those based on unit
affiliation or common interest), direct ties are also likely among structurally equivalent
individuals. In situations like this, both cohesion and structural equivalence predict social
influence and “contagion (if for different reasons) between people strongly tied to each other and
similarly tied to other persons” (Burt, 1987: 1291). The confounding effects of these two
proximity-based mechanisms remain important, even though follow-up analyses using
augmented regressions revealed that relationships involving cohesion dominated those involving
structural equivalence in the case of job security and stable benefits. The similarity of
29
relationships involving cohesion and structural equivalence for friendship ties raises the issue of
how social influence operates through structural equivalence. In this setting a highly plausible
explanation is the solidarity and identification among people socialized similarly in an
organization (Marsden & Friedkin, 1994; Friedkin, 1998; Shah, 1998) where shared friendship
ties often occur (e.g., having the same mentor).
Proximity in the advice network demonstrated relationships with one competitive and one
non-competitive psychological contract term, though effects differ for cohesion and structural
equivalence. Individuals tied to the same advisors shared beliefs regarding the extent of support
for career development (a competitive term). One plausible explanation for this finding is that
advisors were instrumental for getting access to career development opportunities, and thus,
faculty members connected to similar advisors reported similar beliefs. This situation might be
particularly likely in settings such as this where the dominant human resource strategy was to
develop its own personnel (typically hired at entry levels) by supporting their formal education
(e.g., pursuing a doctoral degree either at the university or abroad). Advice ties, which often
reflect asymmetries in rank or status, are likely to include junior faculty going to senior
colleagues for guidance regarding scholarly advancement and development. Thus in the case of
the advice network, similarity in beliefs can reflect shared experiences among structurally
equivalent others who rely upon the same advisor for information or commitments regarding the
treatment each can expect from the employer. In addition, we note that faculty held beliefs
regarding predictability of the employment relationship (treated here as a non-competitive term)
similar to those of their advice-givers and that both rank and advice centrality were also related
to predictability. The relationship between these instrumental influences and the predictability of
one’s future with the employer suggests that this belief is a function of competitively allocated
opportunities in this setting.
Interviews with top management in the school confirmed the role senior faculty played in
channeling advancement and development opportunities to their advisees. Ties to senior faculty
30
and other advice-givers can thus impact how faculty foresee their future employment
opportunities in the university. The central role of senior faculty is supported by several other
findings. In particular, tenure was negatively related to psychological contract terms regarding
support for career development, suggesting that the school was targeting most of its training and
development efforts toward younger or more-recently hired faculty. Moreover, neither rank nor
advice centrality yielded significant relationships in this instance. We conjecture that faculty
members in high rank or status positions did not benefit directly from the career development
opportunities available in this organization (largely because most of them already held advanced
degrees). Instead, they were prompted to use their privileged access to resources to ensure
advancement and development opportunities as well as a continuing relationship with the
university for their advisees. This is consistent with the university’s policy of building openended relational agreements with faculty to provide a stable personnel base with which to pursue
long-term strategic goals. Our findings suggest that beliefs regarding predictability of the
employment relationship were shaped simultaneously by the local effects of direct advice ties,
the systemic effects of advice centrality, and the employee’s rank in the formal organization.
Strengths and Limitations
This study overcomes several limitations of previous research on the formation and
development of the psychological contract. Although that research has been largely limited to
theoretical or descriptive explanations, our analysis offers an empirical examination of the
relationship between informal social interaction patterns and employee psychological contracts.
Methodologically, this study demonstrates the advantages of using network autocorrelation
models for investigating social influence (Leenders, 2002). The weight structure of network
dependence was computed on the basis of both cohesion and structural equivalence and, when
deemed necessary, a superior structure was chosen using the falsification approach for testing
non-nested models. This study also simultaneously examined systemic relationships involving
31
centrality and the consistency of the results using alternative weights for the attenuation factor of
the Bonacich’s power-based centrality measure.
This study’s generalizability may be limited by peculiarities in the research context.
Employees cannot always infer that coworkers are party to a comparable psychological contract
with the employer. In firms with diverse employee backgrounds and job categories, the role of
social information in shaping psychological contracts is likely to be limited to interactions
between those doing similar work. In contrast, the university setting studied here may be an
optimal environment for investigating social influence in the employment relationship. Not only
did faculty members do similar work, by they also played a very active role in their school’s
governance by taking on managerial responsibilities and by blessing the selection of other
colleagues. Such active involvement is more characteristic of knowledge-driven organizations
but may be less common in other firms.
Other limitations include use of Spanish translations from survey measures developed in
the United States. Although the scales’ validity and reliability are confirmed in other regions and
different languages (e.g., Rousseau, 2000; Hui, Lee, & Rousseau, 2004), response patterns may
differ from those observed elsewhere. In addition, the sociometric questionnaires assessed
intraorganizational relationships only, whereas social interaction patterns with outsiders
remained unobserved. Future research should investigate the circumstances under which external
relationships are likely to play a role in shaping psychological contracts. Finally, this study
focuses on general promises conveyed to all employees. Although an important number of
contract expectations were several specific to particular departments (e.g., course teaching units,
research centers, extension projects), these expectations did not provide a common base for
comparison across all faculty due to their distinctive tasks and responsibilities.
Implications for Theory and Research
This study has important implications for both psychological contract and social network
theory and research. It provides evidence regarding two key issues in psychological contract
32
research: the antecedents of psychological contract beliefs and the factors shaping mutuality or
agreement among workers regarding these beliefs. The social information employees obtained
directly or indirectly from advice-givers, friends, and their relative standing in the informal
social structure is related to their formulations of the psychological contracts with the employer.
Psychological contracts are based on information from a variety of sources, mentors, coworkers,
supervisors, top managers and from practices including training and performance appraisals
(Rousseau & Greller, 1994; Rousseau, 1995; Cooper & Sparrow, 2003). In the setting studied
here it is reasonable for one faculty member to infer that colleagues on the same faculty are party
to a comparable psychological contract, making social information regarding the employment
information personally relevant. In contrast, where coworkers are not expected to share the same
relationship with the employer, the impact of social information on one’s understanding of the
psychological contract is less likely. Research is needed on the boundary conditions shaping
whether workers actually use the information their social contacts provide in understanding the
psychological contract.
Resource type impacts the kinds of social influence shaping the psychological contract
(Ho, 2002); however, more research is needed regarding the mechanisms behind this influence.
Socialization research indicates that employees can derive information via active inquiry from
friends and advice givers and through monitoring and observation of the conversations and
experiences of others (Morrison, 1993, 2002). Although our results indicate that close friends
and structural equivalents in friendship tend to agree on non-competitive terms, we do not know
how this agreement arises in the first place. For instance, two friends might have spoken about
these employment conditions and arrived at a common point of view, might have become friends
because they think similarly, or might have observed each other accessing the same noncompetitive resources and concluded therefore that they were each entitled to the same thing.
Any and all of these conditions can give rise to perceptual agreement based upon relational
33
proximity. Teasing out these effects necessitates use of in-depth qualitative methods as well as
longitudinal studies of social influence.
The present study indicates that agreement regarding psychological contract terms can exist
between workers adjacent to each other or similarly tied to other people in the social network,
particularly regarding non-competitive resources. Agreement in psychological contract terms is
typically conceptualized as mutual understanding between worker and employer. Our findings
suggest that social influence creating agreement among workers can contribute to mutuality of
understanding between workers and their employer. Shared information is critical to mutuality
regarding psychological contracts (Rousseau, 2001). Employers who convey information in a
fashion that builds agreement among work groups and the organization’s broader informal social
structure (e.g., by conveying conditions of employment in a public setting such as a town meeting)
are more likely to create employee-employer mutuality. Mutuality is an important feature of the
employment relationship because it shapes both worker and organizational outcomes associated
with the exchange (Dabos & Rousseau, 2004). More research is needed on the kinds of shared
information used to create mutuality.
In the present study, the role of the social network may be accounted for in part by the fact
that all employees surveyed were faculty members and likely to be party to comparable
psychological contracts and a common underlying normative contract. When there is broad
agreement across the psychological contracts of coworkers, a normative contract exists (Nicholson
& Johns, 1985; Rousseau, 1995). Normative contracts are beliefs regarding terms of employment
shared by a work group. They have the advantage in that social interaction can reinforce shared
interpretation when employers seek to standardize terms of employment throughout the
organization (as in the case of many employers who seek to become employers of choice, Cappelli,
2000) or for members holding comparable positions (Rousseau & Ho, 2000) who are part of the
same social network (e.g., tenure-track faculty in universities, engineers in a product development
firm). Research is needed on the role of social interaction in shaping psychological contract beliefs
34
of workers in different job categories (e.g., faculty and support staff) and units having dissimilar
normative contracts (e.g., departments with different emphases on research or teaching).
Workers also differed in their beliefs regarding their individual psychological contracts.
Findings indicate that one’s relative standing in the larger social structure may itself be a
contract-making signal, particularly in the case of access to competitive resources. People with
greater centrality experience more support for project performance, involvement opportunities,
and predictability regarding their future with the employer than their less central colleagues.
Power or status differences shape both the content and direction of information exchange and play a
potentially important role in differentiating psychological contract terms among workers in the same
organization. When an individual’s psychological contract combines terms coworkers share with
those idiosyncratic to that individual, we would expect social influence processes to operate
differently between these shared and idiosyncratic terms. Those social processes that reinforce
mutuality among shared terms may also foster comparisons that erode agreement where
idiosyncratic terms exist.
Conclusion
This study advances our understanding regarding how psychological contracts in
employment are formed and maintained. The informal social structure provides potentially
important information regarding one’s relationship with an employer. But its influence can
depend upon the type of resources employers offer to workers. This study argues for careful
attention in employment research to how resources are allocated, whether competitively to a few
or widely shared. To network scholars this study speaks to the critical role that the nature of
information plays in shaping how network influence functions.
35
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43
Table 1
Descriptive Statistics and Correlations among Variables
Mean
s.d.
0.53
0.50
12.36
7.23
.13
3. Educational Level (Ph.D.)
0.58
0.50
.26**
.46**
4. Prestige
7.39
3.97
.33**
.34**
5. Academic Department 1
0.26
0.44
.18
6. Academic Department 2
0.42
0.50
-.01
7. Academic Department 3
0.32
0.47
-.15
8. Faculty Rank
2.61
1.18
.33**
.67**
.50**
.62**
-.11
.13
-.04
9. Advice Centrality
0.28
0.23
.44**
.30**
.38**
.51**
.12
-.04
-.07
10. Friendship Centrality
0.32
0.21
.07
-.04
.24*
.09
.04
-.12
.09
.09
.39**
11. Support for Performance
3.06
1.09
.28**
.01
.23*
.44**
.25*
-.18
-.05
.19
.47**
.19
12. Support for Career Development
3.22
0.94
.08
-.23*
.01
.09
.19
-.28**
.12
.05
.17
.18
.18
13. Involvement Opportunities
2.99
1.07
.25*
.38**
.44**
.42**
.11
.00
-.11
.55**
.54**
.15
.20
.11
14. Security and Stable Benefits
3.05
0.92
.25*
.27**
.24*
.33**
.11
-.09
-.01
.40**
.39**
.17
.24*
.09
.20
15. Concern for Employees
3.23
0.89
.09
-.04
.02
.19
.29**
-.38**
.13
.04
.17
.19
.16
.12
.05
.08
16. Predictability regarding Future
3.22
0.93
.23*
.19
.30**
.42**
.06
.02
-.08
.48**
.49**
.17
.29**
.10
.33**
.22*
Variables
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Individual Characteristics
1. Gender (Male)
2. Organizational Tenure
.42**
Formal Position
-.21*
.32**
-.14
.07
.24*
-.01
-.11
-.50**
-.05
-.11
-.41**
-.58**
Structural Centrality
.56**
Psychological Contract Scales
Note. N = 96 for all variables.
* p < 0.05
** p < 0.01
44
.06
Table 2
ML Estimation of Network Autocorrelation Models for the Effects of Advice Ties on Promises Relating to Competitive Resources
Support for Performance
Outcomes
Cohesion
I
Support for Career Development
Equivalence
I
II
II
Cohesion
I
II
Equivalence
I
II
Involvement Opportunities
Cohesion
I
II
Equivalence
I
II
Predictors:
Constant
Gender (Male)
Organizational Tenure
Educational Level (Ph.D.)
Prestige
Academic Department 2
Academic Department 3
Rank
Rho (ρ) – Cohesion
2.772***
(.512)
0.343
(.212)
-0.019
(.020)
0.238
(.236)
0.113***
(.034)
-0.294
(.281)
-0.175
(.273)
-0.047
(.139)
-0.099
(.128)
2.910***
(.481)
0.157
(.205)
-0.015
(.018)
0.163
(.221)
0.096**
(.032)
-0.228
(.261)
-0.123
(.254)
-0.196
(.137)
-0.140
(.124)
Rho (ρ) – Equivalence
2.070***
(.592)
0.288
(.212)
-0.015
(.020)
0.226
(.235)
0.109**
(.034)
-0.234
(.276)
-0.142
(.272)
-0.084
(.139)
0.144
(.163)
1.951***
(.526)
Advice Centrality
2.409***
(.580)
0.112
(.206)
-0.013
(.019)
0.158
(.223)
0.095**
(.032)
-0.197
(.260)
-0.107
(.256)
-0.221
(.138)
2.543***
(.492)
0.001
(.189)
-0.047**
(.017)
-0.009
(.210)
-0.009
(.030)
-0.336
(.246)
-0.065
(.241)
0.291*
(.124)
0.223
(.125)
0.036
(.167)
1.879***
(.531)
2.619***
(.497)
-0.034
(.195)
-0.047**
(.018)
-0.019
(.210)
-0.012
(.030)
-0.333
(.246)
-0.060
(.241)
0.262*
(.130)
0.204
(.126)
2.028***
(.538)
0.057
(.185)
-0.043*
(.017)
-0.033
(.206)
-0.008
(.030)
-0.276
(.243)
-0.054
(.235)
0.255*
(.122)
2.099***
(.543)
0.026
(.191)
-0.042*
(.017)
-0.041
(.206)
-0.011
(.030)
-0.274
(.244)
-0.049
(.236)
0.233
(.128)
0.377**
(.141)
0.358*
(.143)
0.288
(.486)
0.360
(.495)
1.686***
(.453)
0.021
(.194)
0.001
(.018)
0.441*
(.216)
0.007
(.031)
-0.298
(.251)
-0.331
(.251)
0.377**
(.129)
0.063
(.128)
1.972***
(.444)
-0.113
(.193)
0.004
(.017)
0.375
(.208)
-0.004
(.030)
-0.253
(.240)
-0.336
(.240)
0.279*
(.130)
-0.033
(.129)
1.609**
(.540)
0.010
(.195)
0.002
(.018)
0.438*
(.216)
0.007
(.031)
-0.302
(.249)
-0.338
(.248)
0.380**
(.128)
1.965***
(.548)
-0.110
(.193)
0.004
(.017)
0.378
(.208)
-0.004
(.030)
-0.251
(.239)
-0.328
(.238)
0.277*
(.129)
0.093
(.163)
-0.031
(.172)
1.469**
(.496)
1.483**
(.494)
R-Square
.258
.353
.258
.346
.191
.196
.197
.202
.361
.414
.360
.413
df
87
86
87
86
87
86
87
86
87
86
87
86
* p < 0.05; ** p < 0.01; *** p < 0.001.
Unstandardized coefficients. Standard errors are in parentheses.
45
Table 3
ML Estimation of Network Autocorrelation Models for the Effects of Friendship Ties on Promises Relating to Competitive Resources
Support for Performance
Outcomes
Cohesion
I
Support for Career Development
Equivalence
I
II
II
Cohesion
I
II
Equivalence
I
II
Involvement Opportunities
Cohesion
I
II
Equivalence
I
II
Predictors:
Constant
Gender (Male)
Organizational Tenure
Educational Level (Ph.D.)
Prestige
Academic Department 2
Academic Department 3
Rank
Rho (ρ) – Cohesion
2.975***
(.455)
0.342
(.211)
-0.024
(.020)
0.254
(.234)
0.113***
(.034)
-0.312
(.273)
-0.181
(.269)
-0.035
(.138)
-0.161
(.111)
2.814***
(.466)
0.343
(.209)
-0.019
(.020)
0.172
(.240)
0.114***
(.033)
-0.307
(.270)
-0.197
(.267)
-0.047
(.138)
-0.165
(.112)
Rho (ρ) – Equivalence
2.818***
(.539)
0.338
(.212)
-0.020
(.020)
0.245
(.236)
0.114***
(.034)
-0.294
(.277)
-0.187
(.271)
-0.066
(.140)
2.689***
(.550)
0.342
(.210)
-0.015
(.020)
0.162
(.242)
0.116***
(.034)
-0.291
(.274)
-0.206
(.269)
-0.080
(.139)
-0.107
(.144)
-0.123
(.143)
0.627
(.468)
0.612
(.465)
Friendship Centrality
3.563***
(.470)
0.027
(.192)
-0.053**
(.018)
0.048
(.215)
-0.010
(.031)
-0.484
(.250)
-0.130
(.245)
0.287*
(.127)
-0.053
(.114)
3.515***
(.477)
0.029
(.191)
-0.050**
(.018)
-0.022
(.220)
-0.009
(.030)
-0.497*
(.248)
-0.145
(.243)
0.274*
(.126)
-0.086
(.114)
2.736***
(.541)
0.008
(.191)
-0.050**
(.018)
0.008
(.212)
-0.012
(.030)
-0.356
(.248)
-0.090
(.243)
0.297*
(.126)
0.180
(.139)
0.581
(.427)
2.733***
(.556)
0.010
(.190)
-0.048**
(.018)
-0.042
(.219)
-0.011
(.030)
-0.370
(.247)
-0.107
(.242)
0.287*
(.125)
2.101***
(.380)
0.068
(.194)
0.000
(.018)
0.430*
(.215)
0.014
(.031)
-0.279
(.248)
-0.379
(.247)
0.409**
(.128)
-0.113
(.104)
0.149
(.140)
0.402
(.423)
2.013***
(.392)
0.073
(.193)
0.003
(.018)
0.370
(.221)
0.015
(.031)
-0.271
(.246)
-0.393
(.246)
0.402**
(.128)
-0.130
(.104)
1.762***
(.429)
0.025
(.195)
0.000
(.018)
0.428*
(.216)
0.007
(.031)
-0.304
(.250)
-0.358
(.249)
0.388**
(.129)
1.663***
(.445)
0.025
(.194)
0.003
(.019)
0.382
(.223)
0.008
(.031)
-0.300
(.250)
-0.367
(.248)
0.380**
(.129)
0.044
(.133)
0.046
(.133)
0.340
(.431)
0.439
(.428)
R-Square
.264
.277
.257
.270
.169
.183
.175
.185
.366
.372
.360
.364
df
87
86
87
86
87
86
87
86
87
86
87
86
* p < 0.05; ** p < 0.01; *** p < 0.001.
Unstandardized coefficients. Standard errors are in parentheses.
46
Table 4
ML Estimation of Network Autocorrelation Models for the Effects of Advice Ties on Promises Relating to Non-Competitive Resources
Security and Stable Benefits
Outcomes
Cohesion
I
Concern for Employees
Equivalence
I
II
II
Cohesion
I
II
Predictability regarding Future
Equivalence
I
II
Cohesion
I
II
1.165**
(.411)
-0.008
(.169)
-0.028
(.016)
0.188
(.189)
0.032
(.027)
0.119
(.217)
-0.013
(.216)
0.324**
(.112)
0.336**
(.113)
1.362**
(.420)
-0.099
(.172)
-0.027
(.016)
0.152
(.186)
0.024
(.027)
0.139
(.213)
-0.006
(.212)
0.264*
(.115)
0.278*
(.116)
Equivalence
I
II
Predictors:
Constant
Gender (Male)
Organizational Tenure
Educational Level (Ph.D.)
Prestige
Academic Department 2
Academic Department 3
Rank
Rho (ρ) - Cohesion
1.722***
(.456)
0.221
(.182)
0.013
(.017)
-0.010
(.202)
0.014
(.029)
-0.319
(.236)
-0.158
(.234)
0.170
(.120)
0.212
(.127)
1.816***
(.458)
0.154
(.187)
0.014
(.017)
-0.034
(.202)
0.008
(.029)
-0.301
(.234)
-0.138
(.232)
0.129
(.125)
0.180
(.128)
Rho (ρ) - Equivalence
2.135***
(.582)
0.202
(.185)
0.011
(.017)
-0.006
(.206)
0.012
(.029)
-0.347
(.238)
-0.149
(.235)
0.227
(.122)
0.059
(.174)
0.630
(.474)
Advice Centrality
2.305***
(.590)
0.126
(.189)
0.012
(.017)
-0.035
(.204)
0.006
(.029)
-0.326
(.235)
-0.125
(.233)
0.172
(.126)
2.518***
(.504)
0.030
(.179)
0.014
(.017)
-0.185
(.199)
0.027
(.029)
-0.663**
(.242)
-0.207
(.229)
-0.014
(.118)
0.246
(.126)
0.003
(.180)
0.747
(.481)
2.575***
(.505)
-0.005
(.185)
0.015
(.017)
-0.198
(.200)
0.023
(.029)
-0.660**
(.241)
-0.198
(.229)
-0.044
(.124)
0.231
(.126)
3.260***
(.654)
0.068
(.183)
0.011
(.017)
-0.160
(.204)
0.028
(.029)
-0.820***
(.249)
-0.225
(.233)
-0.007
(.120)
0.035
(.174)
0.373
(.468)
3.351***
(.654)
0.019
(.188)
0.012
(.017)
-0.176
(.203)
0.024
(.029)
-0.811**
(.248)
-0.211
(.232)
-0.043
(.126)
0.010
(.176)
0.484
(.476)
1.451**
(.522)
-0.019
(.173)
-0.032*
(.016)
0.166
(.192)
0.033
(.028)
0.029
(.221)
-0.086
(.220)
0.378***
(.114)
1.715**
(.537)
-0.108
(.175)
-0.031
(.016)
0.137
(.189)
0.024
(.027)
0.067
(.217)
-0.071
(.215)
0.310**
(.117)
0.263
(.151)
0.180
(.160)
0.994*
(.452)
0.945*
(.441)
R-Square
.220
.235
.206
.225
.200
.206
.181
.190
.328
.362
.314
.351
df
87
86
87
86
87
86
87
86
87
86
87
86
* p < 0.05; ** p < 0.01; *** p < 0.001.
Unstandardized coefficients. Standard errors are in parentheses.
47
Table 5
ML Estimation of Network Autocorrelation Models for the Effects of Friendship Ties on Promises Relating to Non-Competitive Resources
Security and Stable Benefits
Outcomes
Cohesion
I
Concern for Employees
Equivalence
I
II
II
Cohesion
I
II
Predictability regarding Future
Equivalence
I
II
Cohesion
I
II
Equivalence
I
II
Predictors:
Constant
Gender (Male)
Organizational Tenure
Educational Level (Ph.D.)
Prestige
Academic Department 2
Academic Department 3
Rank
Rho (ρ) - Cohesion
1.466***
(.353)
0.187
(.172)
0.003
(.016)
0.042
(.190)
-0.001
(.027)
-0.207
(.220)
-0.131
(.218)
0.162
(.113)
0.361***
(.097)
1.313***
(.365)
0.187
(.170)
0.007
(.016)
-0.031
(.195)
0.000
(.027)
-0.202
(.217)
-0.145
(.216)
0.150
(.112)
0.360***
(.096)
Rho (ρ) - Equivalence
1.273**
(.390)
0.147
(.172)
0.005
(.016)
0.018
(.190)
-0.003
(.027)
-0.314
(.222)
-0.162
(.218)
0.190
(.113)
0.432***
(.113)
0.545
(.377)
Friendship Centrality
1.115**
(.402)
0.146
(.170)
0.008
(.016)
-0.056
(.195)
-0.002
(.027)
-0.308
(.219)
-0.176
(.216)
0.178
(.112)
2.482***
(.433)
0.034
(.175)
0.011
(.016)
-0.214
(.195)
0.032
(.028)
-0.650**
(.233)
-0.201
(.224)
-0.017
(.116)
0.268*
(.104)
0.433***
(.112)
0.553
(.377)
2.462***
(.452)
0.039
(.174)
0.015
(.016)
-0.270
(.201)
0.032
(.028)
-0.669**
(.232)
-0.217
(.223)
-0.026
(.115)
0.233*
(.106)
2.202***
(.487)
0.048
(.174)
0.016
(.016)
-0.204
(.194)
0.033
(.028)
-0.632**
(.233)
-0.201
(.222)
-0.039
(.115)
2.216***
(.509)
0.050
(.174)
0.019
(.016)
-0.257
(.200)
0.033
(.028)
-0.651**
(.232)
-0.215
(.222)
-0.044
(.115)
0.343**
(.124)
0.303*
(.127)
0.438
(.387)
0.477
(.389)
1.804***
(.377)
0.012
(.174)
-0.033*
(.016)
0.178
(.193)
0.036
(.028)
0.043
(.223)
-0.090
(.222)
0.369**
(.115)
0.149
(.103)
1.709***
(.386)
0.012
(.173)
-0.030
(.016)
0.127
(.199)
0.037
(.028)
0.047
(.222)
-0.101
(.221)
0.362**
(.115)
0.145
(.103)
1.854***
(.449)
-0.001
(.175)
-0.037*
(.016)
0.191
(.195)
0.034
(.028)
0.050
(.224)
-0.096
(.223)
0.396***
(.115)
1.737***
(.459)
-0.002
(.174)
-0.034*
(.017)
0.137
(.201)
0.034
(.028)
0.054
(.223)
-0.107
(.222)
0.387***
(.115)
0.134
(.132)
0.136
(.131)
0.401
(.387)
0.378
(.387)
R-Square
.262
.278
.257
.273
.214
.230
.218
.232
.309
.316
.305
.313
df
87
86
87
86
87
86
87
86
87
86
87
86
* p < 0.05; ** p < 0.01; *** p < 0.001.
Unstandardized coefficients. Standard errors are in parentheses.
48