Directory UMM :Data Elmu:jurnal:J-a:Journal Of Business Research:Vol47.Issue3.2000:
The Influence of Organizational Demography on
Customer-Oriented Prosocial Behavior:
An Exploratory Investigation
Lisa Hope Pelled
UNIVERSITY OF SOUTHERN CALIFORNIA
Thomas G. Cummings
UNIVERSITY OF SOUTHERN CALIFORNIA
Mark A. Kizilos
THE HAY GROUP
This research examines the relationship between two constructs that so
far have been studied independently of each other: organizational demography and prosocial organizational behavior (POB). Drawing on social
psychology and organizational behavior literatures, we develop a conceptual framework that proposes how these constructs are interrelated. The
framework suggests two hypotheses. First, diversity variables high in jobrelatedness and low in visibility will be positively related to customeroriented POB. Second, diversity variables low in job-relatedness and high
in visibility will be negatively related to such POB. In a field study, we
conduct a preliminary test of these predictions. Specifically, we use company records and questionnaire data (from a firm in the nonalcoholic
beverage industry) to compute associations between demographic diversity
and prosocial behavior in 223 work units. Results provide preliminary
support for our hypotheses. Consistent with the first prediction, functional
background diversity has a significant positive association (b 5 0.26, p ,
0.01) with the customer-oriented POB of work units, as does company
tenure diversity (b 5 0.16, p , 0.05). Consistent with the second
prediction, gender diversity has a significant negative association (b 5
20.13, p , 0.05) with customer-oriented POB; race diversity is also
negatively related to POB (b 5 20.11), but at a marginal significance
level. These findings lend credence to our conceptual framework and
suggest that further study of its components is warranted. J BUSN RES
2000. 47.209–216. 1999 Elsevier Science Inc.
O
ver a decade ago, Pfeffer (1983, p. 303) called for
greater attention to organizational demography, “the
composition, in terms of basic attributes such as
age, sex, educational level, length of service or residence, [and]
Address correspondence to: Dr. L. H. Pelled, University of Southern California,
Marshall School of Business, Los Angeles, CA 90089-1421. E-mail: pelled
@almaak.usc.edu
Journal of Business Research 47, 209–216 (2000)
1999 Elsevier Science Inc. All rights reserved.
655 Avenue of the Americas, New York, NY 10010
race” of an organization or subunit. In the ensuing years,
researchers have studied the effects of organizational demography across different levels of social systems, from dyads and
work groups to the total organization. They have examined the
effects of demography on a number of workplace outcomes,
including technical communication (Zenger and Lawrence,
1989), turnover (McCain, O’Reilly, and Pfeffer, 1983; Pfeffer
and O’Reilly, 1987; Wagner, Pfeffer, and O’Reilly, 1984), innovation (Ancona and Caldwell, 1992; Bantel and Jackson, 1989;
O’Reilly and Flatt, 1989), and company financial performance
(Murray, 1989; Siciliano, 1996).
As knowledge of organizational demography has grown,
researchers have extended the range of variables that demography can be expected to affect. Our study continues in this
tradition by examining the relationship between organizational demography and prosocial organizational behavior
(POB), a potentially significant yet neglected variable in demography research. POB has been defined as behavior that
is “(a) performed by a member of an organization, (b) directed
toward an individual, group, or organization with whom he
or she interacts while carrying out his or her organizational
role, and (c) performed with the intention of promoting the
welfare of the individual, group, or organization toward which
it is directed” (Brief and Motowidlo, 1986, p. 711). Behavior
classified as POB can either be in-role (sometimes referred to
as role-prescribed) or extra-role. In-role POB involves the
formal requirements of one’s job; it is discretionary and hence
prosocial, because it is not directly enforced (George and
Bettenhausen, 1990; George and Brief, 1992; McNeely and
Meglino, 1994). Extra-role POB extends beyond job specifications and includes performances that are above the norm
(George and Bettenhausen, 1990; George and Brief, 1992;
McNeely and Meglino, 1994).
ISSN 0148-2963/00/–see front matter
PII S0148-2963(98)00094-0
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POB represents a “sometimes overlooked” dimension of
organizational performance that can have significant implications for organizational functioning (Van Dyne, Graham, and
Dienesch, 1994, p. 766). When customers benefit from the
POB of employees, they are likely to be more satisfied with
the organization (Brief and Motowidlo, 1986). Employees engaged in POB may become sensitive to the discretionary aspects of their jobs (Karambayya, 1990), thereby gaining a
sense of empowerment and motivation. In addition, in the
process of seeking solutions to customers’, co-workers’, or
other POB targets’ problems, employees may uncover critical
areas for organizational improvement.
Although most previous studies have conceptualized POB
as an individual-level phenomenon (e.g., O’Reilly and Chatman, 1986; Puffer, 1987), several scholars (e.g., George and
Bettenhausen, 1990; Organ, 1988) have argued that POB is
also meaningful at higher levels of analysis. More specifically,
they have advocated examining the POB tendencies of work
units (organizations or subunits). Organ (1988) suggested
that it is the aggregate of prosocial behaviors that makes a
difference, because most POBs, taken singly, are modest or
trivial. He offered the example of voting to illustrate his point.
A single vote by a single person (let us hope there are not
many cases of a large number of votes by a single person) is
trivial, except in the most extraordinary and unforeseeable
situations. Yet in the aggregate, voting by the electorate
sustains the democratic system.
At the work-unit level, POB is a particularly promising
candidate for organizational demography research. First, unitlevel behaviors tend to be at least partially explained by workunit characteristics (George and Bettenhausen, 1990); demography is such a characteristic. Second, the demography of a
work unit is one indicator of the similarity of unit members,
and similarity has been linked to helping behavior in prior
research. Dovidio (1984) reviewed over 25 studies suggesting
that similarity on such nondemographic variables as opinions,
attitudes, and dress is associated with such helping behavior
as signing a petition, mailing a stamped letter, or picking up
dropped materials. The typical explanation for these findings
was that similarity leads to feelings of “we-ness” (i.e., closeness
or identification), which encourage helping behavior. Given
the results of these studies, it is reasonable to expect that
demographic similarity among work-unit members may have
a similar affect on prosocial organizational behavior. Presumably, demographic homogeneity among members leads to feelings of closeness, which, in turn, enhance members’ propensity to engage in POB. The relationship between demography
and POB may not be so straightforward, however. Because
POB refers to work-related help, it is likely to demand a greater
variety of skills and knowledge than simple helping behaviors,
such as mailing a stamped letter require. Demographic heterogeneity may provide the diversity of skills and knowledge
needed for POB. Thus, the nature of the relationship between
L. H. Pelled et al.
work- unit demography and POB is not obvious and warrants
investigation.
The purpose of our study is to explore, in a preliminary
manner, the relationship between the demographic diversity
of work units and the POB of their members. We first develop
a conceptual framework suggesting how the demographic diversity of work units is related to prosocial organizational
behavior. We then conduct an exploratory test of the theory
using data from multiple work units in a consumer-products
organization. Because the relevant targets of prosocial behavior
may differ across organizational settings, it is important in
POB research to identify and study those behaviors that are
relevant and considered prosocial in the research site (Organ,
1988). We, therefore, focus on a type of prosocial organizational behavior that researchers (George and Bettenhausen,
1990; Kizilos and Cummings, 1994) and our own observations suggest are particularly relevant to consumer-products
organizations: customer-oriented POB. This refers to discretionary and helpful behavior directed toward customers who are
either internal to the firm (i.e., end-users within the same
organization) or external to it. Customer-oriented POB can
involve either in-role or extra-role efforts that are understood
to provide customers with a genuine benefit (Brief and Motowidlo, 1986; George and Bettenhausen, 1990; Kizilos and Cummings, 1994).
Conceptual Framework
Recently, Milliken and Martins (1996, p. 403) noted that,
in classifying different types of demographic diversity, “one
common distinction is between diversity on observable or
readily detectable attributes such as race or ethnic background,
age, or gender, and diversity with respect to less visible or
underlying attributes such as education, technical abilities, tenure in the organization, or socioeconomic background . . .”.
Furthermore, many of the nonobservable types of diversity
constitute “diversity of skills or knowledge (e.g., educational
background, functional background, occupational background,
range of industry experience)”(p. 404). Along the same lines,
Pelled (1996) argued that demographic diversity variables may
be placed along two continua. First, job-relatedness is the extent
to which a demographic diversity variable shapes job skills
and captures experiences relative to cognitive tasks in the
workplace. Second, visibility is the extent to which demographic diversity is easily observed. Both properties can help
account for the workplace consequences of a particular demographic diversity variable. Here, we argue that demographic
diversity may either promote or impede work-unit POB, depending upon the job-relatedness and visibility of the particular diversity variable under consideration.
Diversity as Promoter of Customer-Oriented POB
When work-unit members have different demographic backgrounds, they tend to have different belief structures (i.e.,
Influence of Organizational Demography
different priorities, assumptions about future events, and understandings of alternatives), based on their distinct experiences (Hambrick and Mason, 1984, p. 195; Wiersema and
Bantel, 1992). Consequently, they are likely to have different
interpretations of tasks and work situations (Dearborn and
Simon, 1958; Walsh, 1988; Waller, Huber, and Glick, 1995).
These different interpretations tend to manifest themselves as
task-related discourse or debates within the work unit (Bantel
and Jackson, 1989; Sessa and Jackson, 1995). Such discourse
can contribute to customer-oriented POB, as members strive
to reconcile their dissimilar views about tasks. This exchange
of information can lead to a better understanding of task
issues (Bantel and Jackson, 1989); members may gain greater
knowledge about the organization, its products, scheduling,
and customers’ preferences. As a result, the unit as a whole
will be more capable of helping customers, because managing
relationships with customers requires members to:
collect, process, and dispatch an inordinate amount of
information . . . . [They] need to find out information
about those customers and prospects, especially about their
felt or unfelt needs and problems, their buying processes,
their objectives and constraints. They need to process this
information and integrate it with information they have
already collected or will collect from their own organization
about product specification, prices, delivery times, and
maintenance. (Darmon, 1992, p. 13)
Tjosvold, Dann, and Wong (1992) found that an exchange
of differing ideas among departments tends to enhance an
organization’s customer service, a construct that has considerable overlap with customer-oriented POB. As Spencer and
Spencer (1993, p. 42) have pointed out, a component of
customer-service competence is “initiative (discretionary effort) to help or serve” the customer, including “taking routine
or required actions” to meet customers’ needs as well as “going
out of the way to be helpful.” Although having the ability to
help does not guarantee prosocial behavior, research suggests
that when individuals feel more competent and capable of
undertaking particular actions, they are more likely to perform
those actions (Bandura, 1986). Moreover, people are more
likely to help when they perceive that it will effectively improve another’s condition (Utne and Kidd, 1980).
Certain types of demographic diversity are more likely to
induce customer-oriented POB than others, depending upon
their corresponding belief structures. When interpreting a task
that requires information processing, people tend to draw on
those belief structures most relevant to that task (Waller,
Huber, and Glick, 1995, p. 948; Wickens, 1989). Thus, demographic attributes corresponding to task-relevant belief structures should be particularly influential in the perception of
work-unit tasks. As described previously, the job-relatedness
of a demographic attribute is the degree to which it captures
experiences and skills relevant to cognitive tasks in the workplace (Pelled, 1996). If work-unit members differ with respect
J Busn Res
2000:47:209–216
211
to a demographic attribute that is low in job-relatedness, then
their divergent belief structures based on that attribute may
not pertain to the work they do, and opposing task perceptions
may not develop. In contrast, if work-unit members differ
with respect to a highly job-related demographic attribute,
then their divergent belief structures based on that attribute
are likely to be pertinent to their work, and incongruent task
perceptions are likely to emerge (Pelled, Eisenhardt, and Xin,
in press). Thus, job-related types of demographic diversity in
a work unit are more likely than nonjob-related types to trigger
the task-related exchanges that benefit customer-oriented POB.
Diversity as Impediment to
Customer-Oriented POB
Demographic diversity can also be a liability to work units.
As work units become more diverse, members must organize
a greater amount of information about each other; hence, they
are more likely to use cognitive tools that help them cope with
an overload of information. One such tool is categorization, the
tendency for individuals to organize information about others
by classifying them into social categories based on demographic or other attributes (Turner, 1982). According to social
identity theory, people are motivated to maintain a favorable
self-image; thus, upon placing themselves and others into
categories, they tend to make between-category comparisons
that provide themselves with a positive social identity; that
is, “knowledge of his or her memberships in social groups
together with the emotional significance of that knowledge”
(Turner and Giles, 1981, p. 24). Specifically, individuals tend
to favor their own category and to perceive its members as
superior while stereotyping and developing a hostile attitude
toward members of other categories. Hence, work-unit diversity may encourage antagonism among unit members.
Work-unit diversity may also be associated with intra-unit
anxiety (Stephan and Stephan, 1985). Often, individuals have
more exposure to persons in their own social category than
to persons in other social categories. Consequently, they may
view dissimilar coworkers as less predictable and may experience anxiety (e.g., concern about appropriate behavior)
around them.
The hostility and anxiety that stem from work-unit diversity
may distract members from attending to the needs of customers. Numerous studies have shown that negative emotional
states reduce the attentional resources that people can devote
to tasks (e.g., Ellis and Ashbrook, 1988; Roy-Byrne, Weingartner, Bierer, Thompson, and Post, 1986; Sullivan and Conway,
1989) and lead to greater self-focused attention (e.g., Conway,
Giannopoulos, Csank, and Mendelson, 1993; Ingram, 1990).
Clore, Schwarz, and Conway (1994, p. 371) explained that,
as a result of “intruding thoughts and ruminations, negative
affective states may interfere with information processing that
requires more than minimal amounts of attentional resources.”
Hence, when unit members feel tense or anxious around each
other, they may lack the information-processing capability
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required to understand customer needs and to integrate information for the benefit of customers.
In addition, negative emotions arising from work-unit diversity may reduce members’ opportunities to behave prosocially with customers. Because negative affect makes people
less attractive and approachable (Coyne, 1976), customers
may be reluctant to interact with and to seek help from employees experiencing the anxiety and tension associated with
intra-unit diversity. Consequently, a decrease in customeroriented POB may occur.
Certain types of diversity are more likely to diminish customer-oriented POB than others, depending upon their visibility. Demographic attributes that fall higher along the visibility
continuum are more likely to be used as a basis for categorization. It takes relatively little effort to use easily observed attributes as categories, because such attributes are highly accessible (Tsui, Egan, and O’Reilly, 1992). People can quickly
identify a highly visible attribute and use it to classify others,
even if they have never spoken with (or about) them; the
process is essentially automatic. In contrast, people must generally make inquiries to identify less visible attributes. Thus,
highly visible types of demographic diversity are more likely
to be associated with categorization and its accompanying
intra-unit tensions. Ultimately, then, highly visible types of
work-unit diversity will have a stronger tendency than less
visible types to impede customer-oriented POB.
Predictions
The above theory and research suggest that, based on the
job-relatedness and visibility properties, we can predict how
demography variables will relate to customer-oriented POB.
Variables high in job-relatedness and low in visibility should
be positively related to customer-oriented POB. Variables high
in visibility and low in job-relatedness should be negatively
related to customer-oriented POB. Formally stated,
H1: Demography variables high in job-relatedness and low
in visibility will have positive associations with customer-related prosocial organizational behavior.
H2: Demography variables high in visibility and low in
job-relatedness will have negative associations with
customer-oriented prosocial organizational behavior.
Exploratory Study
As an exploratory study of the proposed framework, we analyzed survey and personnel data from a consumer-products
(beverage) firm. Although this dataset was collected by the
company for purposes of organizational improvement, it contained relatively strong measures of demography and of customer-oriented POB at the work-unit level. Thus, the data
provided an opportunity to test whether the proposed relationships between demography and POB exist. This preliminary assessment helps determine if those relationships warrant
L. H. Pelled et al.
more complete assessment—in particular, further research
examining not only demographic and POB variables, but also
the sociopsychological processes that link those variables.
Sample and Data Collection
This study included data from multiple work units of a firm
that manufactures, markets, and distributes nonalcoholic beverages. The company’s domestic operations encompass a total
of 248 locations, each typically including all of the functions
necessary for the sales and distribution of the firm’s products.
Not all locations have production facilities on site, but those
that do also have their own sales and distribution capabilities.
The location itself is the focal level of analysis in this study, and
hereafter, is referred to as a work unit. Considering locations as
work units is consistent with Tsui, Egan,ans O’Reilly’s (1992,
p. 560) approach, in which work units were “the lowest-level
operating units in which the actual production of goods or
delivery of services to customers occurred.”
Our sources of data on work units included personnel
records and questionnaires administered to employees on an
annual basis by the company. Data were available from 233 out
of 248 units. We used 223 of these in our sample, excluding 10
units whose inter-rater (i.e., interemployee) agreement scores
for customer-oriented POB fell below an acceptable criterion
for aggregating individual-level scores to the work-unit level.
(Aggregation of data is discussed more fully within the Measures section.) The final sample of 223 work units had an
average size of 98 employees (s.d. 117). Within each work
unit sampled, we excluded survey data from those respondents
who did not complete the customer-oriented POB scale. Thus,
although we used company records (demographic) data from
all of the employees in the 223 work units, we used survey
data (items measuring POB) from 74 % of those employees.
In the average work unit, the mean age of unit members
was 35 years, and the mean tenure of unit members was 8
years. The percentage of minorities in the average work unit
was 15 %, and the percentage of women was 8 %. The average
work unit had 74 % of its employees in sales, 24 % in production, and another 2 % in support functions, including marketing, human resources, and finance/accounting.
Measures
DEMOGRAPHIC DIVERSITY. The demographic variables examined in this study included functional background, company
tenure, age, gender, and race. We classified functional background and company tenure variables as highly job-related.
They are typically related to cognitive tasks in the workplace.
By virtue of one’s tenure in a functional area, one is likely to
learn a particular set of norms or guidelines indicating, for
example, what task procedures to follow or what priorities
to consider. In contrast, we classified age, gender, and race
variables as low in job relatedness, because they are unlikely
to capture a large proportion of experience relevant to a work
unit’s task. As Zenger and Lawrence (1989, p. 357) argued,
Influence of Organizational Demography
J Busn Res
2000:47:209–216
“Although age similarity may produce similarity in general
attitudes about work . . . , such attitudinal similarity is unlikely
to have much direct bearing on conversations about technical
work.”
On the visibility continuum, the relative positions of these
demographic variables differed. We categorized age, race, and
gender as highly visible, because, in regard to the perceptual
salience of demographic variables, these physiological features
are more likely to be visible than other demographic attributes.
For example, Tsui,Egan, and O’Reilly (1992, p. 557) stated,
“Age, sex, and race, because they are easily observable, are
more accessible characteristics than company tenure.” Similarly, Fiske and Taylor (1991) suggested that age, race, and
gender are more easily perceived than other attributes; such
physical features “are not only visually accessed but also they
are present immediately in face-to-face interactions” (p.145).
Conversely, we classfied company tenure and functional background variables as low in visibility because neither can be
determined with certainty nor closely estimated immediately
upon looking at a person.
We obtained data on employee age, gender, race, company
tenure, and functional background from corporate personnel
records. We then measured the demographic diversity of each
work unit with respect to the numeric data (age and company
tenure) using the coefficient of variation (standard deviation
within a work unit divided by the mean within that work
unit). Upon comparing heterogeneity measures for numeric
data, Allison (1978, p. 877) concluded that for “variables like
age, where utility is neither strictly increasing nor especially
relevant, the flat sensitivity of the coefficient of variation makes
it the appropriate choice.” For the categorical variables (race,
gender, and functional background), demographic diversity
was measured using an entropy-based index recommended
by Teachman (1980)[Equation (1)].
213
10 members has three females and seven males, then P1 equals
0.3 and P2 equals 0.7. H then equals 0.61.
CUSTOMER-ORIENTED POB. The dependent variable in this
study, customer-oriented prosocial behavior, was formed using five items from the firm’s questionnaire. The items asked
about unit members’ perceptions of the extent to which their
co-workers: (1) come up with good ideas to exceed what the
customer says she or he wants; (2) act on their ideas to
exceed customer expectations; (3) resolve customer problems
immediately; (4) anticipate customers’ future needs; and (5)
are willing to adapt to meet the changing needs of customers.
Response anchors were as follows: 1 5 strongly disagree; 2 5
disagree; 3 5 have mixed feelings; 4 5 agree; 5 5 strongly
agree. Cronbach’s alpha for the scale was 0.88. Table 1 shows
the correlations among the scale items.
Calculations of within-unit perceptual agreement justified
aggregation of these items to obtain a work-unit measure of
POB (Schneider and Bowen, 1985). Using James, Demaree,
and Wolf’s (1984) measure, 223 units (out of 233 for which
data were available) had within-unit agreement scores of at
least 0.70. James and his colleagues (1984) indicated that
within-setting agreement scores of 0.70 or above provide empirical justification for aggregation.
In examining the demography–POB relationship, we controlled for work-unit size obtained from personnel records. Work-unit size tends to be associated with
greater demographic diversity. In addition, people are less
likely to help others as the number of other people present
increases, because such presence provides an individual with
more opportunity to diffuse responsibility (Darley and Latane´,
1968; Latane´ and Nida, 1981; Latane´, Nida, and Wilson,
1981). Thus, work-unit size is likely to be negatively related
to prosocial organizational behavior.
WORK UNIT SIZE.
I
H 5 2 o Pi(1nPi)
(1)
i51
This index takes into account how work-unit members are
distributed among possible categories of a variable. The total
number of categories of a variable equals I, and PI is the
fraction of unit members falling into category I. For example,
the gender variable has two possible states or categories (52):
“1” corresponds to female and “2” to male. If a given team of
Results
Table 2 shows the means, standard deviations, and correlations among the variables in this study. Table 3 presents
results of the regression analysis that we used to examine the
proposed relationship between demography and customeroriented POB.
Our conceptual framework suggested that demographic
variables high in job-relatedness and low in visibility would
Table 1. Correlations among Items in the Customer-Oriented POB Scale
Items
1.
2.
3.
4.
5.
Come up with good ideas to exceed what the customer says he/she wants
Act on ideas to exceed customer expectations
Resolve customer problems immediately
Anticipate customers’ future needs
Willing to adapt to meet the changing needs of our customers
All correlations were significant at p , 0.001, two-tailed.
1
2
3
4
5
——
0.69
0.53
0.57
0.54
——
0.59
0.60
0.58
——
0.62
0.58
——
0.58
——
214
J Busn Res
2000:47:209–216
L. H. Pelled et al.
Table 2. Means, Standard Deviations, and Intercorrelations among Study Variables
1.
2.
3.
4.
5.
6.
7.
Customer-oriented prosocial behavior
Work-unit size
Race diversity
Gender diversity
Age diversity
Company tenure diversity
Functional background diversity
Mean
SD
1
2
3
4
5
6
7
3.73
97.62
0.37
0.26
0.25
0.90
0.48
0.20
117.31
0.32
0.15
0.04
0.21
0.28
——
20.19
20.11
20.16
0.08
0.12
0.02
——
0.50
0.50
0.12
0.04
0.63
——
0.31
0.04
0.43
0.36
——
0.06
0.05
0.42
——
0.33
0.14
——
0.04
——
|r| > .10 indicates significance at p , 0.10, one-tailed.
|r| > .15 indicates significance at p , 0.05, one-tailed.
be positively related to customer-oriented POB. Results were
consistent with this proposed relationship. Functional background diversity had a significant positive association (b 5
0.26, p , 0.01) with the customer-oriented POB of work
units, as did company tenure diversity (b 5 0.16, p , 0.05).
The converse proposal, that demographic variables high
in visibility and low in job-relatedness would be negatively
related to customer-oriented POB, received partial support.
Gender diversity had a significant negative association (b 5
20.12, p , 0.05) with the customer-oriented POB of work
units; race diversity was also negatively related to POB (b 5
20.11), but at a marginal significance level slightly over 0.10.
The results showed no support for the proposed negative
association between age diversity and customer-oriented POB.
We performed several checks to assess whether multicollinearity among the independent variables was a problem in our
analysis. First, we reviewed the zero-order correlations shown
in Table 1. Although there is no definitive criterion for the
level of correlation that signals multicollinearity, the general
rule of thumb is that correlations of 0.75 or larger are problemTable 3. Regression of Customer-oriented POB on Diversity and
Control Variables
Independent Variables
Control variable
Work-unit size
Predictor variables
Race diversity
Gender diversity
Age diversity
Company tenure diversity
Functional background
diversity
Constant
R2
F
df
† approximately significant at .10 level.
* p , 0.05; ** p , 0.01; *** p , 0.001.
a
One-tailed tests.
Dependent Variablea
Customer-Oriented
Prosocial Behavior
b
0.000
b
20.247
t
22.58*
20.068
20.173
0.002
0.002
20.107
20.125
0.030
0.162
21.24†
21.65*
0.43
2.05*
0.187
3.57
0.257
0.00
0.11***
4.26
233
3.04**
atic (Kennedy, 1979; Tsui, Ashford, St. Clair, and Xin, 1995).
None of the correlations reached that magnitude. Second, we
examined the variance inflation factor (VIF) of each independent variable. The VIF indicates how much the standard error
of a regression estimate’s variance is increased by the inclusion
of other predictors (Neter, Wasserman, and Kutner, 1989;
Suitor and Pillemer, 1996). It equals 1/(1-R2), where R2 is the
amount of variation in a predictor variable that is accounted
for by other predictor variables. According to Guo, Chumlea,
and Cockram (1996), a rule of thumb is that a VIF exceeding
10 means that multicollinearity is affecting the regression estimates. The largest VIF we found was only 2.2, providing
further evidence that multicollinearity was not a problem in
this study.
Discussion
Despite the prevalence of diversity in organizations and the
importance of prosocial organizational behavior, there has
been relatively little attempt to link these two constructs. To
address this gap in knowledge, we developed a conceptual
framework that suggests how different types of demographic
diversity relate to customer-oriented POB. The findings are
generally consistent with the relationships proposed in the
framework. Demography variables that were high in job-relatedness and low in visibility were positively associated with
customer-oriented POB, and demography variables that were
low in job-relatedness and high in visibility were, for the most
part, negatively associated with customer-oriented POB.
These preliminary findings lend credence to our conceptual
framework and suggest that a more complete assessment of
the demography–POB relationship is warranted. Building on
these results, a logical next step would be to measure and
analyze intervening process variables, such as task debates
and negative affect, that are likely to underlie this linkage. This
would shed light on the “black box” between demographic
diversity and workplace outcomes (Lawrence, 1997). A second
fruitful area for subsequent research is to examine moderators
of diversity–POB relationships, thus extending our framework
to a contingency model. For example, diversity training programs for employees may diminish the negative effects of
Influence of Organizational Demography
diversity on customer-oriented POB. A third promising study
would be examination of the relationship between work-unit
demography and other prosocial behaviors. A given type of
demography may, for example, have a different association
with prosocial behavior toward co-workers than it has with
prosocial behavior toward customers. On a related note, a
more refined treatment of customer-oriented POB is needed.
Future studies of demography and POB could benefit from
distinguishing between intrarole and extrarole customer-oriented POB or between “organizationally consistent” and “organizationally inconsistent” customer-oriented POBs (Brief and
Motowidlo, 1986, p. 713).
Several nuances of our study limit conclusions that can be
drawn from the findings and suggest how future research
should be conducted. First, because the data were cross sectional, they limit our ability to infer causality. Second, the
work units in our sample all belonged to a single parent
corporation in the nonalcoholic beverage industry; it is, therefore, difficult to know whether the results would hold in
different types of organizations. Third, in our study, diversity
variables that were highly job-related happened to be low
in visibility, and diversity variables that were low in jobrelatedness were high in visibility. If we were to focus on
another set of diversity variables, however, we might find that
some are high (or low) in both properties (i.e., visibility and
job-relatedness). These limitations suggest that future research
in this area would benefit from longitudinal data, examination
of different types of organizations, and inclusion of additional
kinds of diversity variables.
In conclusion, the current study—although exploratory in
nature—makes significant contributions. Of these, the most
substantial is the integration of two important, yet relatively
independent, streams of research. The study enhances knowledge of prosocial organizational behavior by identifying organizational demography as a significant correlate of customeroriented POB. Conversely, it adds to our understanding of
organizational demography by examining an outcome variable
that demography researchers have not previously examined.
In doing so, the study incorporates a broader set of diversity
variables than most prior demography studies have incorporated. This investigation also contributes by supporting the
notion that job-relatedness and visibility are useful properties
for classifying demographic variables and understanding their
effects in the workplace. These contributions will likely lead
to greater scholarly interest in demography, in POB, and in the
relationship between these, to date, separate areas of research.
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Customer-Oriented Prosocial Behavior:
An Exploratory Investigation
Lisa Hope Pelled
UNIVERSITY OF SOUTHERN CALIFORNIA
Thomas G. Cummings
UNIVERSITY OF SOUTHERN CALIFORNIA
Mark A. Kizilos
THE HAY GROUP
This research examines the relationship between two constructs that so
far have been studied independently of each other: organizational demography and prosocial organizational behavior (POB). Drawing on social
psychology and organizational behavior literatures, we develop a conceptual framework that proposes how these constructs are interrelated. The
framework suggests two hypotheses. First, diversity variables high in jobrelatedness and low in visibility will be positively related to customeroriented POB. Second, diversity variables low in job-relatedness and high
in visibility will be negatively related to such POB. In a field study, we
conduct a preliminary test of these predictions. Specifically, we use company records and questionnaire data (from a firm in the nonalcoholic
beverage industry) to compute associations between demographic diversity
and prosocial behavior in 223 work units. Results provide preliminary
support for our hypotheses. Consistent with the first prediction, functional
background diversity has a significant positive association (b 5 0.26, p ,
0.01) with the customer-oriented POB of work units, as does company
tenure diversity (b 5 0.16, p , 0.05). Consistent with the second
prediction, gender diversity has a significant negative association (b 5
20.13, p , 0.05) with customer-oriented POB; race diversity is also
negatively related to POB (b 5 20.11), but at a marginal significance
level. These findings lend credence to our conceptual framework and
suggest that further study of its components is warranted. J BUSN RES
2000. 47.209–216. 1999 Elsevier Science Inc.
O
ver a decade ago, Pfeffer (1983, p. 303) called for
greater attention to organizational demography, “the
composition, in terms of basic attributes such as
age, sex, educational level, length of service or residence, [and]
Address correspondence to: Dr. L. H. Pelled, University of Southern California,
Marshall School of Business, Los Angeles, CA 90089-1421. E-mail: pelled
@almaak.usc.edu
Journal of Business Research 47, 209–216 (2000)
1999 Elsevier Science Inc. All rights reserved.
655 Avenue of the Americas, New York, NY 10010
race” of an organization or subunit. In the ensuing years,
researchers have studied the effects of organizational demography across different levels of social systems, from dyads and
work groups to the total organization. They have examined the
effects of demography on a number of workplace outcomes,
including technical communication (Zenger and Lawrence,
1989), turnover (McCain, O’Reilly, and Pfeffer, 1983; Pfeffer
and O’Reilly, 1987; Wagner, Pfeffer, and O’Reilly, 1984), innovation (Ancona and Caldwell, 1992; Bantel and Jackson, 1989;
O’Reilly and Flatt, 1989), and company financial performance
(Murray, 1989; Siciliano, 1996).
As knowledge of organizational demography has grown,
researchers have extended the range of variables that demography can be expected to affect. Our study continues in this
tradition by examining the relationship between organizational demography and prosocial organizational behavior
(POB), a potentially significant yet neglected variable in demography research. POB has been defined as behavior that
is “(a) performed by a member of an organization, (b) directed
toward an individual, group, or organization with whom he
or she interacts while carrying out his or her organizational
role, and (c) performed with the intention of promoting the
welfare of the individual, group, or organization toward which
it is directed” (Brief and Motowidlo, 1986, p. 711). Behavior
classified as POB can either be in-role (sometimes referred to
as role-prescribed) or extra-role. In-role POB involves the
formal requirements of one’s job; it is discretionary and hence
prosocial, because it is not directly enforced (George and
Bettenhausen, 1990; George and Brief, 1992; McNeely and
Meglino, 1994). Extra-role POB extends beyond job specifications and includes performances that are above the norm
(George and Bettenhausen, 1990; George and Brief, 1992;
McNeely and Meglino, 1994).
ISSN 0148-2963/00/–see front matter
PII S0148-2963(98)00094-0
210
J Busn Res
2000:47:209–216
POB represents a “sometimes overlooked” dimension of
organizational performance that can have significant implications for organizational functioning (Van Dyne, Graham, and
Dienesch, 1994, p. 766). When customers benefit from the
POB of employees, they are likely to be more satisfied with
the organization (Brief and Motowidlo, 1986). Employees engaged in POB may become sensitive to the discretionary aspects of their jobs (Karambayya, 1990), thereby gaining a
sense of empowerment and motivation. In addition, in the
process of seeking solutions to customers’, co-workers’, or
other POB targets’ problems, employees may uncover critical
areas for organizational improvement.
Although most previous studies have conceptualized POB
as an individual-level phenomenon (e.g., O’Reilly and Chatman, 1986; Puffer, 1987), several scholars (e.g., George and
Bettenhausen, 1990; Organ, 1988) have argued that POB is
also meaningful at higher levels of analysis. More specifically,
they have advocated examining the POB tendencies of work
units (organizations or subunits). Organ (1988) suggested
that it is the aggregate of prosocial behaviors that makes a
difference, because most POBs, taken singly, are modest or
trivial. He offered the example of voting to illustrate his point.
A single vote by a single person (let us hope there are not
many cases of a large number of votes by a single person) is
trivial, except in the most extraordinary and unforeseeable
situations. Yet in the aggregate, voting by the electorate
sustains the democratic system.
At the work-unit level, POB is a particularly promising
candidate for organizational demography research. First, unitlevel behaviors tend to be at least partially explained by workunit characteristics (George and Bettenhausen, 1990); demography is such a characteristic. Second, the demography of a
work unit is one indicator of the similarity of unit members,
and similarity has been linked to helping behavior in prior
research. Dovidio (1984) reviewed over 25 studies suggesting
that similarity on such nondemographic variables as opinions,
attitudes, and dress is associated with such helping behavior
as signing a petition, mailing a stamped letter, or picking up
dropped materials. The typical explanation for these findings
was that similarity leads to feelings of “we-ness” (i.e., closeness
or identification), which encourage helping behavior. Given
the results of these studies, it is reasonable to expect that
demographic similarity among work-unit members may have
a similar affect on prosocial organizational behavior. Presumably, demographic homogeneity among members leads to feelings of closeness, which, in turn, enhance members’ propensity to engage in POB. The relationship between demography
and POB may not be so straightforward, however. Because
POB refers to work-related help, it is likely to demand a greater
variety of skills and knowledge than simple helping behaviors,
such as mailing a stamped letter require. Demographic heterogeneity may provide the diversity of skills and knowledge
needed for POB. Thus, the nature of the relationship between
L. H. Pelled et al.
work- unit demography and POB is not obvious and warrants
investigation.
The purpose of our study is to explore, in a preliminary
manner, the relationship between the demographic diversity
of work units and the POB of their members. We first develop
a conceptual framework suggesting how the demographic diversity of work units is related to prosocial organizational
behavior. We then conduct an exploratory test of the theory
using data from multiple work units in a consumer-products
organization. Because the relevant targets of prosocial behavior
may differ across organizational settings, it is important in
POB research to identify and study those behaviors that are
relevant and considered prosocial in the research site (Organ,
1988). We, therefore, focus on a type of prosocial organizational behavior that researchers (George and Bettenhausen,
1990; Kizilos and Cummings, 1994) and our own observations suggest are particularly relevant to consumer-products
organizations: customer-oriented POB. This refers to discretionary and helpful behavior directed toward customers who are
either internal to the firm (i.e., end-users within the same
organization) or external to it. Customer-oriented POB can
involve either in-role or extra-role efforts that are understood
to provide customers with a genuine benefit (Brief and Motowidlo, 1986; George and Bettenhausen, 1990; Kizilos and Cummings, 1994).
Conceptual Framework
Recently, Milliken and Martins (1996, p. 403) noted that,
in classifying different types of demographic diversity, “one
common distinction is between diversity on observable or
readily detectable attributes such as race or ethnic background,
age, or gender, and diversity with respect to less visible or
underlying attributes such as education, technical abilities, tenure in the organization, or socioeconomic background . . .”.
Furthermore, many of the nonobservable types of diversity
constitute “diversity of skills or knowledge (e.g., educational
background, functional background, occupational background,
range of industry experience)”(p. 404). Along the same lines,
Pelled (1996) argued that demographic diversity variables may
be placed along two continua. First, job-relatedness is the extent
to which a demographic diversity variable shapes job skills
and captures experiences relative to cognitive tasks in the
workplace. Second, visibility is the extent to which demographic diversity is easily observed. Both properties can help
account for the workplace consequences of a particular demographic diversity variable. Here, we argue that demographic
diversity may either promote or impede work-unit POB, depending upon the job-relatedness and visibility of the particular diversity variable under consideration.
Diversity as Promoter of Customer-Oriented POB
When work-unit members have different demographic backgrounds, they tend to have different belief structures (i.e.,
Influence of Organizational Demography
different priorities, assumptions about future events, and understandings of alternatives), based on their distinct experiences (Hambrick and Mason, 1984, p. 195; Wiersema and
Bantel, 1992). Consequently, they are likely to have different
interpretations of tasks and work situations (Dearborn and
Simon, 1958; Walsh, 1988; Waller, Huber, and Glick, 1995).
These different interpretations tend to manifest themselves as
task-related discourse or debates within the work unit (Bantel
and Jackson, 1989; Sessa and Jackson, 1995). Such discourse
can contribute to customer-oriented POB, as members strive
to reconcile their dissimilar views about tasks. This exchange
of information can lead to a better understanding of task
issues (Bantel and Jackson, 1989); members may gain greater
knowledge about the organization, its products, scheduling,
and customers’ preferences. As a result, the unit as a whole
will be more capable of helping customers, because managing
relationships with customers requires members to:
collect, process, and dispatch an inordinate amount of
information . . . . [They] need to find out information
about those customers and prospects, especially about their
felt or unfelt needs and problems, their buying processes,
their objectives and constraints. They need to process this
information and integrate it with information they have
already collected or will collect from their own organization
about product specification, prices, delivery times, and
maintenance. (Darmon, 1992, p. 13)
Tjosvold, Dann, and Wong (1992) found that an exchange
of differing ideas among departments tends to enhance an
organization’s customer service, a construct that has considerable overlap with customer-oriented POB. As Spencer and
Spencer (1993, p. 42) have pointed out, a component of
customer-service competence is “initiative (discretionary effort) to help or serve” the customer, including “taking routine
or required actions” to meet customers’ needs as well as “going
out of the way to be helpful.” Although having the ability to
help does not guarantee prosocial behavior, research suggests
that when individuals feel more competent and capable of
undertaking particular actions, they are more likely to perform
those actions (Bandura, 1986). Moreover, people are more
likely to help when they perceive that it will effectively improve another’s condition (Utne and Kidd, 1980).
Certain types of demographic diversity are more likely to
induce customer-oriented POB than others, depending upon
their corresponding belief structures. When interpreting a task
that requires information processing, people tend to draw on
those belief structures most relevant to that task (Waller,
Huber, and Glick, 1995, p. 948; Wickens, 1989). Thus, demographic attributes corresponding to task-relevant belief structures should be particularly influential in the perception of
work-unit tasks. As described previously, the job-relatedness
of a demographic attribute is the degree to which it captures
experiences and skills relevant to cognitive tasks in the workplace (Pelled, 1996). If work-unit members differ with respect
J Busn Res
2000:47:209–216
211
to a demographic attribute that is low in job-relatedness, then
their divergent belief structures based on that attribute may
not pertain to the work they do, and opposing task perceptions
may not develop. In contrast, if work-unit members differ
with respect to a highly job-related demographic attribute,
then their divergent belief structures based on that attribute
are likely to be pertinent to their work, and incongruent task
perceptions are likely to emerge (Pelled, Eisenhardt, and Xin,
in press). Thus, job-related types of demographic diversity in
a work unit are more likely than nonjob-related types to trigger
the task-related exchanges that benefit customer-oriented POB.
Diversity as Impediment to
Customer-Oriented POB
Demographic diversity can also be a liability to work units.
As work units become more diverse, members must organize
a greater amount of information about each other; hence, they
are more likely to use cognitive tools that help them cope with
an overload of information. One such tool is categorization, the
tendency for individuals to organize information about others
by classifying them into social categories based on demographic or other attributes (Turner, 1982). According to social
identity theory, people are motivated to maintain a favorable
self-image; thus, upon placing themselves and others into
categories, they tend to make between-category comparisons
that provide themselves with a positive social identity; that
is, “knowledge of his or her memberships in social groups
together with the emotional significance of that knowledge”
(Turner and Giles, 1981, p. 24). Specifically, individuals tend
to favor their own category and to perceive its members as
superior while stereotyping and developing a hostile attitude
toward members of other categories. Hence, work-unit diversity may encourage antagonism among unit members.
Work-unit diversity may also be associated with intra-unit
anxiety (Stephan and Stephan, 1985). Often, individuals have
more exposure to persons in their own social category than
to persons in other social categories. Consequently, they may
view dissimilar coworkers as less predictable and may experience anxiety (e.g., concern about appropriate behavior)
around them.
The hostility and anxiety that stem from work-unit diversity
may distract members from attending to the needs of customers. Numerous studies have shown that negative emotional
states reduce the attentional resources that people can devote
to tasks (e.g., Ellis and Ashbrook, 1988; Roy-Byrne, Weingartner, Bierer, Thompson, and Post, 1986; Sullivan and Conway,
1989) and lead to greater self-focused attention (e.g., Conway,
Giannopoulos, Csank, and Mendelson, 1993; Ingram, 1990).
Clore, Schwarz, and Conway (1994, p. 371) explained that,
as a result of “intruding thoughts and ruminations, negative
affective states may interfere with information processing that
requires more than minimal amounts of attentional resources.”
Hence, when unit members feel tense or anxious around each
other, they may lack the information-processing capability
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required to understand customer needs and to integrate information for the benefit of customers.
In addition, negative emotions arising from work-unit diversity may reduce members’ opportunities to behave prosocially with customers. Because negative affect makes people
less attractive and approachable (Coyne, 1976), customers
may be reluctant to interact with and to seek help from employees experiencing the anxiety and tension associated with
intra-unit diversity. Consequently, a decrease in customeroriented POB may occur.
Certain types of diversity are more likely to diminish customer-oriented POB than others, depending upon their visibility. Demographic attributes that fall higher along the visibility
continuum are more likely to be used as a basis for categorization. It takes relatively little effort to use easily observed attributes as categories, because such attributes are highly accessible (Tsui, Egan, and O’Reilly, 1992). People can quickly
identify a highly visible attribute and use it to classify others,
even if they have never spoken with (or about) them; the
process is essentially automatic. In contrast, people must generally make inquiries to identify less visible attributes. Thus,
highly visible types of demographic diversity are more likely
to be associated with categorization and its accompanying
intra-unit tensions. Ultimately, then, highly visible types of
work-unit diversity will have a stronger tendency than less
visible types to impede customer-oriented POB.
Predictions
The above theory and research suggest that, based on the
job-relatedness and visibility properties, we can predict how
demography variables will relate to customer-oriented POB.
Variables high in job-relatedness and low in visibility should
be positively related to customer-oriented POB. Variables high
in visibility and low in job-relatedness should be negatively
related to customer-oriented POB. Formally stated,
H1: Demography variables high in job-relatedness and low
in visibility will have positive associations with customer-related prosocial organizational behavior.
H2: Demography variables high in visibility and low in
job-relatedness will have negative associations with
customer-oriented prosocial organizational behavior.
Exploratory Study
As an exploratory study of the proposed framework, we analyzed survey and personnel data from a consumer-products
(beverage) firm. Although this dataset was collected by the
company for purposes of organizational improvement, it contained relatively strong measures of demography and of customer-oriented POB at the work-unit level. Thus, the data
provided an opportunity to test whether the proposed relationships between demography and POB exist. This preliminary assessment helps determine if those relationships warrant
L. H. Pelled et al.
more complete assessment—in particular, further research
examining not only demographic and POB variables, but also
the sociopsychological processes that link those variables.
Sample and Data Collection
This study included data from multiple work units of a firm
that manufactures, markets, and distributes nonalcoholic beverages. The company’s domestic operations encompass a total
of 248 locations, each typically including all of the functions
necessary for the sales and distribution of the firm’s products.
Not all locations have production facilities on site, but those
that do also have their own sales and distribution capabilities.
The location itself is the focal level of analysis in this study, and
hereafter, is referred to as a work unit. Considering locations as
work units is consistent with Tsui, Egan,ans O’Reilly’s (1992,
p. 560) approach, in which work units were “the lowest-level
operating units in which the actual production of goods or
delivery of services to customers occurred.”
Our sources of data on work units included personnel
records and questionnaires administered to employees on an
annual basis by the company. Data were available from 233 out
of 248 units. We used 223 of these in our sample, excluding 10
units whose inter-rater (i.e., interemployee) agreement scores
for customer-oriented POB fell below an acceptable criterion
for aggregating individual-level scores to the work-unit level.
(Aggregation of data is discussed more fully within the Measures section.) The final sample of 223 work units had an
average size of 98 employees (s.d. 117). Within each work
unit sampled, we excluded survey data from those respondents
who did not complete the customer-oriented POB scale. Thus,
although we used company records (demographic) data from
all of the employees in the 223 work units, we used survey
data (items measuring POB) from 74 % of those employees.
In the average work unit, the mean age of unit members
was 35 years, and the mean tenure of unit members was 8
years. The percentage of minorities in the average work unit
was 15 %, and the percentage of women was 8 %. The average
work unit had 74 % of its employees in sales, 24 % in production, and another 2 % in support functions, including marketing, human resources, and finance/accounting.
Measures
DEMOGRAPHIC DIVERSITY. The demographic variables examined in this study included functional background, company
tenure, age, gender, and race. We classified functional background and company tenure variables as highly job-related.
They are typically related to cognitive tasks in the workplace.
By virtue of one’s tenure in a functional area, one is likely to
learn a particular set of norms or guidelines indicating, for
example, what task procedures to follow or what priorities
to consider. In contrast, we classified age, gender, and race
variables as low in job relatedness, because they are unlikely
to capture a large proportion of experience relevant to a work
unit’s task. As Zenger and Lawrence (1989, p. 357) argued,
Influence of Organizational Demography
J Busn Res
2000:47:209–216
“Although age similarity may produce similarity in general
attitudes about work . . . , such attitudinal similarity is unlikely
to have much direct bearing on conversations about technical
work.”
On the visibility continuum, the relative positions of these
demographic variables differed. We categorized age, race, and
gender as highly visible, because, in regard to the perceptual
salience of demographic variables, these physiological features
are more likely to be visible than other demographic attributes.
For example, Tsui,Egan, and O’Reilly (1992, p. 557) stated,
“Age, sex, and race, because they are easily observable, are
more accessible characteristics than company tenure.” Similarly, Fiske and Taylor (1991) suggested that age, race, and
gender are more easily perceived than other attributes; such
physical features “are not only visually accessed but also they
are present immediately in face-to-face interactions” (p.145).
Conversely, we classfied company tenure and functional background variables as low in visibility because neither can be
determined with certainty nor closely estimated immediately
upon looking at a person.
We obtained data on employee age, gender, race, company
tenure, and functional background from corporate personnel
records. We then measured the demographic diversity of each
work unit with respect to the numeric data (age and company
tenure) using the coefficient of variation (standard deviation
within a work unit divided by the mean within that work
unit). Upon comparing heterogeneity measures for numeric
data, Allison (1978, p. 877) concluded that for “variables like
age, where utility is neither strictly increasing nor especially
relevant, the flat sensitivity of the coefficient of variation makes
it the appropriate choice.” For the categorical variables (race,
gender, and functional background), demographic diversity
was measured using an entropy-based index recommended
by Teachman (1980)[Equation (1)].
213
10 members has three females and seven males, then P1 equals
0.3 and P2 equals 0.7. H then equals 0.61.
CUSTOMER-ORIENTED POB. The dependent variable in this
study, customer-oriented prosocial behavior, was formed using five items from the firm’s questionnaire. The items asked
about unit members’ perceptions of the extent to which their
co-workers: (1) come up with good ideas to exceed what the
customer says she or he wants; (2) act on their ideas to
exceed customer expectations; (3) resolve customer problems
immediately; (4) anticipate customers’ future needs; and (5)
are willing to adapt to meet the changing needs of customers.
Response anchors were as follows: 1 5 strongly disagree; 2 5
disagree; 3 5 have mixed feelings; 4 5 agree; 5 5 strongly
agree. Cronbach’s alpha for the scale was 0.88. Table 1 shows
the correlations among the scale items.
Calculations of within-unit perceptual agreement justified
aggregation of these items to obtain a work-unit measure of
POB (Schneider and Bowen, 1985). Using James, Demaree,
and Wolf’s (1984) measure, 223 units (out of 233 for which
data were available) had within-unit agreement scores of at
least 0.70. James and his colleagues (1984) indicated that
within-setting agreement scores of 0.70 or above provide empirical justification for aggregation.
In examining the demography–POB relationship, we controlled for work-unit size obtained from personnel records. Work-unit size tends to be associated with
greater demographic diversity. In addition, people are less
likely to help others as the number of other people present
increases, because such presence provides an individual with
more opportunity to diffuse responsibility (Darley and Latane´,
1968; Latane´ and Nida, 1981; Latane´, Nida, and Wilson,
1981). Thus, work-unit size is likely to be negatively related
to prosocial organizational behavior.
WORK UNIT SIZE.
I
H 5 2 o Pi(1nPi)
(1)
i51
This index takes into account how work-unit members are
distributed among possible categories of a variable. The total
number of categories of a variable equals I, and PI is the
fraction of unit members falling into category I. For example,
the gender variable has two possible states or categories (52):
“1” corresponds to female and “2” to male. If a given team of
Results
Table 2 shows the means, standard deviations, and correlations among the variables in this study. Table 3 presents
results of the regression analysis that we used to examine the
proposed relationship between demography and customeroriented POB.
Our conceptual framework suggested that demographic
variables high in job-relatedness and low in visibility would
Table 1. Correlations among Items in the Customer-Oriented POB Scale
Items
1.
2.
3.
4.
5.
Come up with good ideas to exceed what the customer says he/she wants
Act on ideas to exceed customer expectations
Resolve customer problems immediately
Anticipate customers’ future needs
Willing to adapt to meet the changing needs of our customers
All correlations were significant at p , 0.001, two-tailed.
1
2
3
4
5
——
0.69
0.53
0.57
0.54
——
0.59
0.60
0.58
——
0.62
0.58
——
0.58
——
214
J Busn Res
2000:47:209–216
L. H. Pelled et al.
Table 2. Means, Standard Deviations, and Intercorrelations among Study Variables
1.
2.
3.
4.
5.
6.
7.
Customer-oriented prosocial behavior
Work-unit size
Race diversity
Gender diversity
Age diversity
Company tenure diversity
Functional background diversity
Mean
SD
1
2
3
4
5
6
7
3.73
97.62
0.37
0.26
0.25
0.90
0.48
0.20
117.31
0.32
0.15
0.04
0.21
0.28
——
20.19
20.11
20.16
0.08
0.12
0.02
——
0.50
0.50
0.12
0.04
0.63
——
0.31
0.04
0.43
0.36
——
0.06
0.05
0.42
——
0.33
0.14
——
0.04
——
|r| > .10 indicates significance at p , 0.10, one-tailed.
|r| > .15 indicates significance at p , 0.05, one-tailed.
be positively related to customer-oriented POB. Results were
consistent with this proposed relationship. Functional background diversity had a significant positive association (b 5
0.26, p , 0.01) with the customer-oriented POB of work
units, as did company tenure diversity (b 5 0.16, p , 0.05).
The converse proposal, that demographic variables high
in visibility and low in job-relatedness would be negatively
related to customer-oriented POB, received partial support.
Gender diversity had a significant negative association (b 5
20.12, p , 0.05) with the customer-oriented POB of work
units; race diversity was also negatively related to POB (b 5
20.11), but at a marginal significance level slightly over 0.10.
The results showed no support for the proposed negative
association between age diversity and customer-oriented POB.
We performed several checks to assess whether multicollinearity among the independent variables was a problem in our
analysis. First, we reviewed the zero-order correlations shown
in Table 1. Although there is no definitive criterion for the
level of correlation that signals multicollinearity, the general
rule of thumb is that correlations of 0.75 or larger are problemTable 3. Regression of Customer-oriented POB on Diversity and
Control Variables
Independent Variables
Control variable
Work-unit size
Predictor variables
Race diversity
Gender diversity
Age diversity
Company tenure diversity
Functional background
diversity
Constant
R2
F
df
† approximately significant at .10 level.
* p , 0.05; ** p , 0.01; *** p , 0.001.
a
One-tailed tests.
Dependent Variablea
Customer-Oriented
Prosocial Behavior
b
0.000
b
20.247
t
22.58*
20.068
20.173
0.002
0.002
20.107
20.125
0.030
0.162
21.24†
21.65*
0.43
2.05*
0.187
3.57
0.257
0.00
0.11***
4.26
233
3.04**
atic (Kennedy, 1979; Tsui, Ashford, St. Clair, and Xin, 1995).
None of the correlations reached that magnitude. Second, we
examined the variance inflation factor (VIF) of each independent variable. The VIF indicates how much the standard error
of a regression estimate’s variance is increased by the inclusion
of other predictors (Neter, Wasserman, and Kutner, 1989;
Suitor and Pillemer, 1996). It equals 1/(1-R2), where R2 is the
amount of variation in a predictor variable that is accounted
for by other predictor variables. According to Guo, Chumlea,
and Cockram (1996), a rule of thumb is that a VIF exceeding
10 means that multicollinearity is affecting the regression estimates. The largest VIF we found was only 2.2, providing
further evidence that multicollinearity was not a problem in
this study.
Discussion
Despite the prevalence of diversity in organizations and the
importance of prosocial organizational behavior, there has
been relatively little attempt to link these two constructs. To
address this gap in knowledge, we developed a conceptual
framework that suggests how different types of demographic
diversity relate to customer-oriented POB. The findings are
generally consistent with the relationships proposed in the
framework. Demography variables that were high in job-relatedness and low in visibility were positively associated with
customer-oriented POB, and demography variables that were
low in job-relatedness and high in visibility were, for the most
part, negatively associated with customer-oriented POB.
These preliminary findings lend credence to our conceptual
framework and suggest that a more complete assessment of
the demography–POB relationship is warranted. Building on
these results, a logical next step would be to measure and
analyze intervening process variables, such as task debates
and negative affect, that are likely to underlie this linkage. This
would shed light on the “black box” between demographic
diversity and workplace outcomes (Lawrence, 1997). A second
fruitful area for subsequent research is to examine moderators
of diversity–POB relationships, thus extending our framework
to a contingency model. For example, diversity training programs for employees may diminish the negative effects of
Influence of Organizational Demography
diversity on customer-oriented POB. A third promising study
would be examination of the relationship between work-unit
demography and other prosocial behaviors. A given type of
demography may, for example, have a different association
with prosocial behavior toward co-workers than it has with
prosocial behavior toward customers. On a related note, a
more refined treatment of customer-oriented POB is needed.
Future studies of demography and POB could benefit from
distinguishing between intrarole and extrarole customer-oriented POB or between “organizationally consistent” and “organizationally inconsistent” customer-oriented POBs (Brief and
Motowidlo, 1986, p. 713).
Several nuances of our study limit conclusions that can be
drawn from the findings and suggest how future research
should be conducted. First, because the data were cross sectional, they limit our ability to infer causality. Second, the
work units in our sample all belonged to a single parent
corporation in the nonalcoholic beverage industry; it is, therefore, difficult to know whether the results would hold in
different types of organizations. Third, in our study, diversity
variables that were highly job-related happened to be low
in visibility, and diversity variables that were low in jobrelatedness were high in visibility. If we were to focus on
another set of diversity variables, however, we might find that
some are high (or low) in both properties (i.e., visibility and
job-relatedness). These limitations suggest that future research
in this area would benefit from longitudinal data, examination
of different types of organizations, and inclusion of additional
kinds of diversity variables.
In conclusion, the current study—although exploratory in
nature—makes significant contributions. Of these, the most
substantial is the integration of two important, yet relatively
independent, streams of research. The study enhances knowledge of prosocial organizational behavior by identifying organizational demography as a significant correlate of customeroriented POB. Conversely, it adds to our understanding of
organizational demography by examining an outcome variable
that demography researchers have not previously examined.
In doing so, the study incorporates a broader set of diversity
variables than most prior demography studies have incorporated. This investigation also contributes by supporting the
notion that job-relatedness and visibility are useful properties
for classifying demographic variables and understanding their
effects in the workplace. These contributions will likely lead
to greater scholarly interest in demography, in POB, and in the
relationship between these, to date, separate areas of research.
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