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Embedded within the European social psychological movement (see Doise, 1982; Jaspars, 1980), social identity theory (Tajfel, 1970, 1974, 1978, 1982; Turner, 1982) proposes that an individual's social identity is essential in the formation of the self-concept. Social identity has been defined as “that part of an individual's self-concept which derives from his [sic] knowledge of his [sic] membership in a social group (or groups) together with the value and emotional significance attached to that membership” (Tajfel, 1978, p. 63). Inherent in this definition, is the assumption that society consists of social categories based on nationality, race, class, occupation, sex, and religion, amongst others. Social identity theory (SIT) proposes that people form social identities based on these categories, which, in turn, influence affect and behavior (Abrams, 1996).
Although an in depth analysis is beyond the scope of this paper, SIT has provided the foundation for significant advances in the areas of conformity and social influence (Abrams & Hogg, 1990; Turner, 1991), cohesion and solidarity (Hogg, 1992), stereotyping (Haslam, Oakes, Reynolds & Turner, 1999; Oakes, Haslam & Turner, 1994), and prejudice (Brown, 1995). However, the vast majority of SIT research has been conducted in the laboratory (e.g. Ouwerkerk et al., 2000; Vanbeselaere, 2000). This is not a criticism of individual research per se, as many of the questions posed by SIT are best investigated in experimental contexts. Instead, it reflects a shortcoming in the SIT literature in general; significantly less research has been conducted in applied settings.
Social Identity and the Organization
Following the call from Ashforth and Mael (1989), a number of researchers have started to address the aforementioned gap in the SIT literature by applying the theory to organizational settings (e.g. Barreto & Ellemers, 2000; Hennessy & West, 1999). This organizational application of SIT has contributed to the ecological validity of the theory (Fielding & Hogg, 1997; van Knippenberg & van Schie, 2000), while at the same time, has advanced our understanding of organizational behavior (Hopkins, 1997; Shamir, Brainin, Zakay & Popper, 2000; Suzuki, 1998; Terry & Callan, 1998; Terry, Carey & Callan, 2001).
According to Hogg and Terry (2000, p. 123), an organization can be viewed as a number of “internally structured groups that are located in complex networks of intergroup relations characterised by power, status, and prestige differentials”. This definition is based on the assumption that organizations are comprised of interrelated groups, or social categories. It follows, that organizations can be the object of identification, just as other social categories based on nationality, race, class, occupation, sex, and religion, can be the object of identification. In other words, organizational identification is a specific form of social identification (Ashforth & Mael, 1989; Dutton et al. 1994; Mael & Ashforth, 1992; Mael & Tetrick, 1992).
From the SIT perspective, employees self-categorize organizational membership in order to reduce subjective uncertainty (Grieve & Hogg, 1999; Hogg & Abrams, 1993; Hogg & Mullin, 1999), and gain positive distinctiveness (Tajfel, 1978). Employees form prototypes of organizational membership, which both describe and prescribe organizationally based perceptions, attitudes, feelings and behaviors (Hogg & Terry, 2000). It is argued that the stronger the identification with the self-categorization, the more likely it is that the categorization will guide affect and behavior within the organization, and that the individual will act in the organization's best interests (Dutton et al., 1994; Mael & Ashforth, 1992). Importantly, organizations are comprised of multiple social categories, including work units, professional groups and departmental groups. These groups provide the basis for many nested identities within an organization (Ashforth & Mael, 1989; Hennessy & West, 1999), with each of these identities being a potentially salient source for social identity driven affect and behavior.
In the last decade, a number of studies have started to emerge from the SIT literature (Brown et al. 1986; Hennesy & West, 1999; Hinkle et al. 1989; van Knippenberg and van Schie, 2000), as well as the broader communication and management literature (Barker & Tompkins, 1994; Russo, 1998; Scott, 1997; Fontenot & Scott, 2001; Scott & Timmerman, 1999), which examine the way in which multiple targets of identification influence organizational behavior. These studies have measured targets of organizational identification separately and then explored their relationship with other variables. However, with the recognition of multiple targets of identification, it is not enough to examine the way in which these identities, by themselves, relate to other concepts. In addition, it is also important to examine the relationship between identification targets. Two targets of identification are likely to be compatible when the core values associated with each are similar, and when categorization of the self in terms of one group does not preclude categorization of the self in terms of the other group (Gallois, Tluchowska & Callan, 2001).
There are a number of ways in which the compatibility between identification targets may influence organizational behavior. Tompkins and Cheney (1985) contend that in some instances identification with a department over the larger organization may have serious impacts on the organization. This is because what may be a prototypical behavior for one target may be counter-normative, or even maladaptive for another. Alternatively, a lack of compatibility between identification targets may influence organizational attitudes such as job satisfaction. For example, an individual may identify strongly with his or her organization, developing a prototype that embodies the beliefs, attitudes, feelings and behaviors that are associated with organizational membership. However, if these beliefs, attitudes, feelings and behaviors are somehow incompatible with professional or work unit prototypical perceptions, one would expect to see diminished satisfaction. In a like manner, it seems plausible that incompatibility between identification targets may be associated with tension in the employee's workplace, which may in turn, lead to increased levels of emotional exhaustion. Therefore, since the compatibility between identification targets may have discernable outcomes for organizations, research that explores this concept is of practical importance, yet in short supply.
An exception to this, is a study by Gallois et al. (2001) that examined how membership in multiple groups within an organization influences employee acceptance of organizational change. The results of the study indicated that employees who exhibited a high degree of compatibility between multiple identification targets that were nested in the organizational hierarchy, were most open to the changes and assessed the change most positively. Another study that measured the compatibility between different identification targets was conducted by Bennington, Carrol, Trinastich & Scott (2000). The authors adopted an interesting approach to the measurement of identification compatibility, by asking people to graphically indicate the degree of overlap between various identification targets. Interestingly, though, both of these studies measured the compatibility between identification targets in a qualitative manner. Such an approach is certainly valid and often yields rich and useful information. However, there is a need to generate quantitative ways of conceptualizing and measuring the relationship between identification targets in order to complement previous efforts.
To this end, Scott, Cornetto, Tumlin, Marlowe & Marable (2001) explored an alternative way of conceptualizing and operationalizing the compatibility between identification targets. The approach addressed the degree of compatibility and tension between multiple targets of identification, by obtaining various measures of identification congruency. As operationalized by Scott et al., identification congruency is literally the “similarity/difference score between any two targets” (p. 7). Identification congruency scores were calculated in three different ways in the study. First, for each possible pair of targets, the identification score of one target was subtracted from the score of the second target. Second, an absolute difference score was calculated for each pair of targets. Finally, an overall congruency profile was calculated for each respondent, with the standard deviation scores used as an index for identification congruency.
The results of the Scott et al. (2001) study suggested that identification congruency measures do relate to various outcome measures in a way that is different from individual identification targets. In particular, the overall congruency scores, as well as congruency scores involving organizational targets, were more strongly related to the dependent measures in the study than other congruency measures. Contrary to predictions, the authors found that identification with individual targets were better predictors of job satisfaction, turnover intentions and role ambiguity, than identification congruency scores. The exception to this pattern was a measure of role conflict, where the correlation coefficients between identification congruency scores and the DV were of similar magnitude to the individual measures of identification. However, even these coefficients were rather modest, ranging from .12 to .23. Since this was the first study to employ identification congruency measures in this way, more exploratory research is needed to ascertain the relationship between identification congruency measures and other outcome measures.
In addition to individual outcome measures, the extent to which targets of identification are congruent may also be related to organizational communication. It is likely, for instance, that a lack of information from organizational sources would decrease identification with the organization. This is because a number of studies have found a link between identification and organizational communication (e.g. Bullis & Bach, 1991; Myers & Kassing, 1998; Scott & Timmerman, 1999). In such a situation, it is possible that the employee will turn to the work unit to obtain information, which may also increase the strength of identification with the work unit. It is argued that this dual dynamic would decrease the identification congruency between the two targets, as work unit and organizational identification would be influenced in an inverse manner. Similarly, identification congruency may also influence communication sending behaviors. For example, the discrepancy between organizational and work unit identification described above, may, in turn, cause the employee to send more information to his or her work unit. At the same time, and given a decrease in identification strength with the organization, the employee is also likely to send less information to organizational sources. As such, the relationship between identification congruency and communication may be cyclical.
Although not explicitly acknowledging the reciprocal relationship described above, Scott et al. (2001) found that measures of identification congruency accounted for more of the variance in communication variables than separate measures of identification. This finding is particularly promising in light of previous studies that have typically found minimal magnitudes between organizational identification and communication variables (Scott & Timmerman, 1999; Wiesenfeld, Raghuram, & Garud, 1999). As with the outcome measures, therefore, more research is needed to further examine the relationship between measures of identification congruency and communication variables.
Accordingly, the current study measured the congruency between the work unit, professional and organizational targets of identification. The overall identification congruency measure was used, as this measure was the best predictor of outcome measures in the Scott et al. study. Due to the conceptual and mathematical similarity between the directional and absolute measures of identification congruency, only the absolute measures were used in this study, as these measures were more strongly related to the outcome measures in the Scott et al. study. The two different ways of calculating identification congruency were compared with the individual measures of identification that were used to generate them, in order to examine whether measures of identification congruency significantly added to the variance in outcome variables already accounted for by individual targets of identification. Formally, then, the study put forward a research question:
Do identification congruency scores add to the predictive utility of single identification targets for job satisfaction, organizational commitment, uncertainty, emotional exhaustion, information sent and information received?
The participants were employees of a public government hospital in the Brisbane region. In total, 189 participants completed the questionnaire, with 55.9% (104) of the sample male, and 44.1% (82) female. The age range of participants was between 20 and 67 years, with a mean age of 40.00 (SD = 10.67). Table 1 contains the professional group of participants.
Background Information for the Sample of Participants
Identification. The identification scale used for the study was developed by Brown et al. (1986). The scale contains 10 items which tap identity, with items 1, 4, 7, 8 and 10 negatively phrased. Responses were rated on a 5-point scale ranging from (1) strongly disagree to (5) strongly agree. The scale was used for all three targets of identification, with the appropriate wording changes (e.g. I identify with my work unit/ my professional group/ Organization). The three identification scales were situated in different places in the questionnaire in order to minimise the impact of any carry over effects from previous identification scales. Brown et al. (1986) reported satisfactory internal reliability for the scale (Cronbach's alpha = 0.71), as well as satisfactory construct validity. Data from the present study also showed satisfactory reliability, with Cronbach's alpha for the three scales above .85 (unit = .88, professional = .86, organization = .87).
Job Satisfaction. Overall job satisfaction was assessed with five items adapted from those developed by Caplan, Cobb, French, Van Harrison and Pinneau (1975). One item asked respondents “All things considered, how satisfied are you with your job?”, using a 5-point scale ranging from (1) very dissatisfied to (5) very satisfied. Previous research has reported satisfactory Cronbach's alpha for the scale 0.88 (Terry et al. 2001), with the present study yielding a Cronbach's alpha of .81.
Organizational Commitment. Organizational commitment was measured using three items that were adapted from Mowday, Steers & Porter's (1979) organizational commitment questionnaire. The items used were: “I feel very committed to the job I currently do”, “I don't care what happens to Organization as long as I get my pay”, and “What happens to Organization is really important to me”. Responses were rated on a 5-point scale ranging from (1) disagree strongly to (5) strongly agree. The scale assesses generalised levels of commitment, and either the 15-item measure (e.g. Hambleton, Kalliath & Taylor, 2000), or adaptations of it (e.g. Chen & Francesco, 2000; Kirby & Richard, 2000; Testa, 2001), have been widely used in the organizational behavior literature.
Emotional Exhaustion. Emotional exhaustion was measured using the emotional exhaustion sub-scale of the Maslach Burnout Inventory (Maslach & Jackson, 1981). Examples of items in the scale are “I feel used up at the end of a work day”, and “I feel burned out from my work”. Responses were made on a 5-point response scale ranging from (1) strongly disagree to (5) strongly agree. Miller, Ellis, Zook & Lyles (1990) have reported an alpha coefficient of 0.83 for the subscale, with data from the present study finding a Cronbach's alpha of .88. Construct validity for the subscale has also been established in a number of studies (e.g. Kalliath, O'Driscoll, Gillespie & Bluedorn, 2000; Maslach & Jackson, 1981), with Miller et al. (1990) reporting correlations with related concepts such as work load (.50), role stress (.58) and depersonalisation (.48).
Uncertainty. Uncertainty was measured using a 9-item scale that was developed by Bordia, Hunt, Paulsen, Tourish & DiFonzo (2001). The scale was designed to assess uncertainty in times of change. The items, some of which were adapted from Schweiger and Denisi (1991), asked respondents to indicate how uncertain they were regarding outcomes of the change for various work-related dimensions (e.g. whether they will have to learn new job skills and whether they will have to relocate to another section of the organization). Responses were made using a 5-point scale ranging from (1) very little uncertainty to (5) very great uncertainty. Bordia et al. report an internal consistency coefficient of 0.89 for the scale, with the current study also finding high reliability for the measure (Cronbach's alpha = .88). However, since the scale has only been recently developed, no validity data is available.
Communication. Two scales were used from the International Communication Audit (Goldhaber & Rogers, 1979) to measure communication in the study. To assess the amount of information sent by employees, 11 items were included that asked respondents to indicate the amount of information that they send on a variety of topics (e.g. work problems, successes and achievements). Responses were made on a 5-point scale, ranging from (1) very little to (5) a very great amount. More specifically, respondents were asked to indicate for each topic, “the number that accurately represents the amount of information you are sending now and the amount you feel you need to send to do your job most effectively”. Scores from the information that respondents were currently sending were subtracted from the scores that they reported they needed to send, in order to calculate discrepancy scores. The advantage of using discrepancy scores is that they represent the adequacy of communication, relative to the respondent's expectations of communication in the organization. As such, discrepancy scores contain more information than ratings of communication on a single scale. In addition to information sent, a 16-item measure of information received was also calculated using discrepancy scores. For this measure, respondents were asked to report the current and desired levels of information sent on a variety of topics, including job performance, benefits and conditions, promotional opportunities, how problems are dealt with, and the goals of the organization.
An information sheet advising participants about the survey and its aims was forwarded to all employees. In this information sheet, employees were invited to participate in the survey and were assured of the confidentiality of their responses, that no individuals would be identified in the process and that a short summary of the main findings would be made available to all staff. The following week a confidential self-report questionnaire was distributed to all employees in the organization. A second information sheet explaining the aims of the survey and inviting voluntary participation accompanied the survey. Completed surveys were returned in a sealed envelope via internal mail.
All statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS) for Windows. SPSS REGRESSION was used to inspect the data for multivariate outliers. SPSS DESCRIPTIVES was used to examine the data for skewness and kurtosis. Transformation were performed on professional identification, work identification and organizational commitment to reduce skewness and kurtosis. With the inclusion of the transformed variables, the assumption of normality was met in the various analyses. Since the results were minimally changed with the inclusion of the transformed variables, the original variables were used in the main analyses to increase interpretability. In addition, for each of the regression analyses the cases-to-IV ratio was acceptable using Tabachnick and Fidell's (1996) criterion; multicollinearity and singularity were not violated and; the assumptions of linearity, homoscedasticity and independence of residuals were met.
Scale scores were calculated in a number of different ways for the measures. For the two communication variables, discrepancy scores were calculated for each of the items by subtracting the desired levels of information from the current levels reported by participants. These discrepancy scores were then averaged in order to obtain an overall measure of information adequacy. Identification congruency scores were calculated in two different ways. First, the absolute difference between each possible pair of targets was calculated. Thus, absolute congruency scores were calculated between the organization and work unit (IC|OU|), the organization and professional group (IC|OP|), and the work unit and professional group (IC|UP|). Second, an overall congruency profile for each respondent (ICOUP) was used. To calculate this score, a mean score for all items on the three identification scales was calculated. Next, the standard deviation of these scores was calculated, with these deviation scores providing an overall index for congruency between the three targets (larger standard deviation scores indicating less congruency). All other measures in the analysis were calculated by obtaining a mean score for the scale items.
The study put forward one research question: Do identification congruency scores add to the predictive utility of single identification targets for job satisfaction, organizational commitment, uncertainty, emotional exhaustion, information sent and information received? In order to explore this question, a series of hierarchical regression analyses were performed. In order to control for the inflated Type 1 error chance resulting from multiple analyses, a more stringent alpha level was adopted (p < .01).
In one set of analyses, six hierarchical regressions were conducted separately on job satisfaction, organizational commitment, uncertainty, emotional exhaustion, information received and information sent. The first step of these analyses involved regressing the scores for the three individual measures of identification on each variable. Next, the overall identification congruency profile (ICOUP) was regressed on each variable in order to ascertain whether this measure added to the variance that was already accounted for in the DVs by the three identification targets. In all of these analyses, the ÆR2 that resulted with the addition of ICOUP into the equation was not significant at p < .01.
The next set of analyses examined the utility of the absolute measures of identification congruency. Hierarchical regressions were conducted separately on job satisfaction, organizational commitment, uncertainty, emotional exhaustion, information received and information sent. The first step in each analysis was to regress two individual identification targets (e.g. organizational and professional) on each DV. Next, the corresponding measure of absolute identification congruency was added into the equation (e.g. IC|OP|) in order to ascertain whether these measure significantly increased R2. Multiple regressions were carried out for all possible pairs of identification targets and for all outcome variables, resulting in eighteen separate regression analyses. In all cases, the ÆR2 added by the various IC measures was not significant at p < .01 (see Appendix D for regression tables). Therefore, measures of identification congruency did not significantly add to the variance accounted for in the DVs by the individual targets of identification.
This study investigated the efficacy of identification congruency measures in predicting job satisfaction, organizational commitment, uncertainty, emotional exhaustion, information sent and information received. The results of the study suggest that there is little utility in the operationalisations of identification congruency employed in the current research. That is to say, that measures of identification congruency in the present study did not significantly add to the variance that was accounted for in the DVs by the individual targets of identification.
There are a number of possible explanations for this finding. One possibility is that the mathematical computations of identification congruency developed by Scott et al. (2001) may not adequately operationalise the construct. Or, since the outcome measures used in the current study were different to those used by Scott et al., it may be that measures of identification congruency relate differently to different outcome measures. A further explanation for the result is that, despite its intuitive appeal, the concept of identification congruency is of limited use in organizational behavior research. Hence, more research is required to determine the conceptual and operational status of the identification congruency measures. This may involve the development of new scales that test the levels of identification congruency more specifically than computations of scales that are designed to test individual targets. Or, it may be more appropriate to measure identification congruency qualitatively, as discussed earlier. In any event, it appears that the operationalisation of identification congruency as conceptualised by Scott et al. (2001) is of little utility.
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|Received: June 28, 2002
Accepted: August 26, 2002
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