An examination of the antecedents of turnover propensity of engineers: An integrated model

Journal of Engineering Elsevier

and Technology

Management,

9 (1992)

101

101-126

An examination of the antecedents of turnover propensity of engineers: An integrated model Magid Igbaria and Sidney R. Siegel Department

of Management,

Drexel

University,

Philadelphia,

PA 19104, USA

Abstract A survey response from 107 engineers was used to develop and test an integrated model of turnover intentions incorporating role stressors, task characteristics, job involvement, job satisfaction, and organizational commitment as predictors of intention to leave the organization. Results of this study provide moderate support for the proposed model and the pattern of linkages specified among the variables. Results show that organizational commitment had a direct and negative effect on intention to leave the organization. Indirect effects on the intention to leave were found for job satisfaction, job involvement, task characteristics and role stressors. Results also show that job satisfaction is considered the most important factor directly affecting organizational commitment. In addition, job involvement, challenge and role ambiguity had both direct and indirect effects on organizational commitment. Role stressors were found to be the most dysfunctional variables affecting satisfaction of the engineers. We also found that task characteristics play an important role in predicting job involvement, career satisfaction and intention to leave. Implications discussed.

for the management

of engineering

departments

Keywords. Turnover of engineers, Job involvement, Satisfaction, Task characteristics, Role stressors, Multivariate analysis.

and future research

Organizational

are

commitment,

1. Introduction The need for increased research on human resource management issues as they pertain to engineers has been emphasized in a number of recent studies (Allen and Katz, 1986; Badawy, 1975, 1978, 1988; Brooks and Wells, 1989; Chan, 1989; Garden, 1989; Parden, 1981; Saleh and Desai, 1990; Sherman, 1986). The importance of gaining a better understanding of the factors related to recruitment, motivation, and retention of engineers is further underscored by the high demand for engineers, rising personnel costs, and high rates of Correspondence to: Professor Magid Igbaria, Department of Management, Philadelphia, PA 19104, USA. Fax: (215) 895-2891; e-mail: magid@duvm.

092%4748/92/$05.00

0 1992 Elsevier Science Publishers

B.V.

Drexel University,

All rights reserved.

102

turnover among this group of employees (Badawy, 1988; Basta and Johnson, 1989; Garden, 1989; Parden, 1981; Sherman, 1986). With projections of expanding competition from abroad, engineering managers as well as human resource departments are experiencing greater pressure from top management to improve the recruitment, selection and training of fresh engineering talent. At the same time however, they are being encouraged to maintain competitive levels of costs associated with the recruitment and maintenance of this large group of technical personnel. These costs account for a major proportion of the total operating budget in most technology-intensive organizations. Given that costs for bringing new engineers on board can only be pared to a level below which the functions become marginally ineffective, and that other organizations can easily match these standards, Garden (1989) identifies turnover as a major factor which could provide some advantage to engineering managers faced with these pressures. Retention of new engineers as well as current employees could serve to reduce personnel costs in the expensive areas of recruitment and training by lowering the total number of new engineers needed as replacements, as well as minimizing the loss of productivity associated with the learning curve for new employees. Engineering managers are in fact becoming more conscious of the important relationships between personnel costs and turnover (Badawy, 1988; Garden, 1989; Sherman, 1986). While the control of turnover is an obvious foundation of effective engineering management (Garden, 1989; Sherman, 1986)) in order to reduce excessive turnover among engineers it is necessary to understand the reasons behind the turnover. To the extent that specific aspects of jobs held by these engineers contribute to high levels of organizational turnover, and are within the control of the engineering managers, retention levels could be increased through appropriate engineering management actions designed to minimize these problem areas. 2. Relevant literature and research objectives Given the current turnover problem amongst engineers, the ten percent decline of freshmen enrollment in engineering schools (Anderson et al., 1989; Ottinger, 1990), and the projected major shortfall of more than 500,000 engineers, physicists and other scientific graduates by the year 2000 (Tiff& 1989) in the United States, it is surprising that only a handful of studies have explored turnover and its antecedents among engineers. A review of this scant literature as well as the general turnover literature reveals that there has been growing research interest in investigating the multivariate linkages among diverse variables posited to be predictors of turnover among engineers/or and technical professionals such as programmers (Baroudi, 1985; Bartol, 1983; Chan, 1989; Garden, 1989; Parden, 1981; Sherman, 1986). Although these studies have provided a foundation for understanding the variables related to

103

engineers and programmers, additional research is needed to synthesize the findings and to formulate a parsimonious model that helps explain the process by which engineers decide to resign their jobs. Accordingly, the major purpose of this study was to test an integrated model of turnover among engineers which incorporated those variables found consistently to explain and predict turnover. The specific objectives of this study were to address six related research questions: (1) What is the impact of role stressors on the turnover intentions of engineers? (2) What is the impact of task characteristics on the turnover intentions of engineers? (3) Do work-related attitudes (e.g., job involvement, job satisfaction, career satisfaction, and organizational commitment) mediate the effects of role stressors and task characteristics on the turnover intentions of engineers? (4) What is the impact of work-related attitudes on turnover intentions of engineers? (5) Do job satisfaction, career satisfaction, and organizational commitment mediate the effect of job involvement on turnover intentions of engineers? (6) Does organizational commitment mediate the effects of job satisfaction and career satisfaction on turnover intentions of engineers? Current turnover models and related empirical research provide strong support for Fishbein and Ajzen’s (1975) proposition that behavioral intentions constitute the most immediate determinant of actual behavior, in this case turnover (Bluedorn, 1982; Cotton and Tuttle, 1986; Horn et al., 1979; Michaels and Spector, 1982; Williams and Hazer, 1986). Given the modest costs associated with collecting turnover intentions statements compared to generating data about actual turnover, and the problem of temporarily dispersed leaving episodes typically found in most studies using an individual level predictive design, Bluedorn (1982) and Coverdale and Terborg (1980) have recommended using intent to leave attitudes rather than actual staying or leaving behavior as a criterion variable. Supporting this model, Steel and Ovalle’s (1984) meta-analysis suggests that turnover intentions and turnover are related and that turnover intentions are better predictors of turnover than affective variables such as job and career satisfaction, and organizational commitment. The literature, thus, suggests that turnover intentions are a valuable concept that is linked with actual turnover. In addition, turnover intentions are under more individual control, can provide results much more quickly, and are less difficult to predict than turnover. Accordingly, turnover intentions were used in this study instead of actual turnover. 3. The conceptual framework Figure 1 presents the model of turnover intentions examined in this study. The model includes three sets of variables: (a) two role stressors-role ambiguity and role conflict; (b) task characteristics-perceived job characteristics as defined by Job Diagnostic Survey (JDS), and challenging tasks; and (c)

104

2 Task

Characteristics

4 Commitment

Intention

Fig. 1. Antecedents

of intention

bered arrows correspond

to leave controlling

to the hypotheses

for demographic

To Leave

characteristics

(The num-

described in the body of the paper.)

four indicators of work-related attitudes: job involvement, job satisfaction, career satisfaction, and organizational commitment. Figure 1 predicts direct effects of role stressors and task characteristics on job involvement, job satisfaction, career satisfaction, organizational commitment and intention to leave, as well as direct effects of job involvement on job satisfaction, career satisfaction, organizational commitment and intention to leave. The model also predicts direct effects of job satisfaction and career satisfaction on organizational commitment and intention to leave, and a direct effect of organizational commitment on intention to leave. It is important to note that in addition to these direct effects, the model also postulates indirect effects of role stressors and task characteristics on intention to leave through job involvement, job satisfaction, career satisfaction, and organizational commitment. The model further postulates that job involvement has an indirect effect on intention to leave through job satisfaction, career satisfaction, and organizational commitment, and that job satisfaction and career satisfaction have indirect effects on intention to leave through organizational commitment. Since indirect effects are composites of direct effects, only direct effects are presented as hypotheses. The rationale for each hypothesis in the model is presented below. 3.1. Role stressors Two role-based stressors were included in this study: role ambiguity and role conflict. Role ambiguity refers to the difference between what people expect of us on the job and what we feel we should do. This causes uncertainty about what our role should be. It can be a result of misunderstanding what is expected, how to meet the expectations, or the employee thinking the job should be different (Kahn et al., 1964; Muchinsky, 1990). Insufficient information on how to perform the job adequately, unclear expectations of peers and super-

105

visors, ambiguity of performance evaluation methods, extensive job pressures, and lack of consensus on job functions or duties may cause engineers to feel less involved and less satisfied with their jobs and careers, less committed to their organizations, and eventually display a propensity to leave the organization. Role conflict can develop when two or more pressures occur together so that complying with one would make doing the other more difficult (Kahn et al., 1964). This could occur in a variety of ways. It might be a function of conflicting messages, a request for a high-quality work within a very short period of time, or splitting loyalties between co-workers and the organization. It has been reported that role conflict is negatively associated with job satisfaction and organizational commitment, and positively associated with intention to leave (Baroudi, 1985; Bedeian and Armenakis, 1981; Chan, 1989 ). Badawy (1973,199O) found that satisfaction is negatively correlated with role conflict among scientific professionals and R&D personnel. Saleh and Desai (1990) also reported that role stressors could affect satisfaction among engineers. Similar results were found among programmers and other technical professionals (Baroudi, 1985; Goldstein and Rockart, 1984). Indeed, current conceptual models and empirical studies (Baroudi, 1985; Brooke et al., 1988; Cotton and Tuttle, 1986; Igbaria, 1991; Mobley et al., 1979; Parasuraman, 1989) posit that the effect of role ambiguity and role conflict on turnover intentions is mediated through job and career satisfaction. Therefore, Hypothesis 1 predicts that the role stressors have direct effects on job involvement, job satisfaction, career satisfaction, organizational commitment, and intention to leave. Specifically, it is predicted that role stressors are negatively associated with job involvement, job satisfaction, career satisfaction, and organizational commitment, and positively associated with intention to leave. It is important to mention that since the effect of role stressors on career outcomes varies across different groups of people in terms of their age, gender, education, organizational tenure, and organizational level (Cotton and Tuttle, 1986; Garden, 1989), we decided to control for the demographic variables. 3.2. Task characteristics

Task characteristics have been found to be potential determinants of turnover among engineering and technical personnel (Couger, 1988, 1990; Couger and Zawacki, 1980; Garden, 1989; Goldstein and Rockart, 1984). These include the five core job characteristics identified by Hackman and Oldham (1975, 1980): (1) skill variety, which refers to the opportunity to utilize a variety of valued skills and talents on the job; (2) task identity, or the extent to which a job requires completion of a whole and identifiable piece of work-that is, doing a job from beginning to end, with visible results; (3) task significance, which

106

reflects the extent to which the job has a substantial impact on the lives or work of other people, whether within or outside the organization; (4) job autonomy, or the extent to which the job provides freedom, independence, and discretion in scheduling work and determining procedures that the job provides; and (5) job feedback, which refers to the extent to which the job provides information about the effectiveness of one’s performance. Task characteristics have been found to influence turnover intentions through their relationships with job satisfaction and organizational commitment (Michaels and Spector, 1982; Steers, 1977). Furthermore, the engineering and MIS literature has focused extensively on the importance of a job which permits engineers and other technical people to work on challenging and interesting tasks (Badawy, 1978, 1988; Couger, 1988,199O; Garden, 1989; Sherman, 1986). It was suggested that if the job provides technical professionals, including engineers, the opportunity to engage in challenging and exciting tasks, they will be more involved and satisfied in their jobs, more committed to their organizations, and finally, less likely to leave the organization. Task characteristics have also been found to be positively related to job satisfaction and organizational commitment and have direct and indirect effects on turnover intentions through satisfaction and commitment among technical professionals (Igbaria, 1991; Parasuraman, 1989). Note that the job design literature suggests that motivators (e.g., job challenge, autonomy, responsibility, and achievement) lead to satisfaction and commitment and eventually reduce employee’s intention to leave the organization (Hackman and Oldham, 1980). Therefore, Hypothesis 2 predicts that task characteristics have direct effects on job involvement, job satisfaction, career satisfaction, organizational commitment, and intention to leave. Specifically, it is predicted that task characteristics are positively related to job involvement, job satisfaction, career satisfaction, and organizational commitment, and negatively with intention to leave. 3.3. Job involvement Job involvement describes an individual’s ego involvement with work and indicates the extent to which an individual identifies psychologically with his/ her job (Kanungo, 1982). It is also suggested that involvement refers to the internalizing values about the goodness or the importance of work and it was found that job involvement is related to task characteristics. Workers who have a greater variety of tasks and who deal with other people at work may feel more involved in the job. Involvement was also found to influence job satisfaction and organizational commitment. Employees who are more job involved are more satisfied with their jobs and more committed to their organization (Blau and Boal, 1989; Brooke and Price, 1989; Brooke et al., 1988; Kanungo, 1982). It is acknowledged that the relationship between job involvement and satis-

107

faction can be moderated by internal control and Type A behavior. (“The Type A behavior pattern is considered to be an overt behavioral style of living characterized by extremes of competitiveness, striving for achievement, agressiveness, haste, and feelings of being under the pressure of time and under the challenge of responsibility” (Saleh and Desai, 1990, p. 39 ). ) Job involvement has also been found to be negatively related to turnover intentions (Blau and Boal, 1989). It was reported that job satisfaction and organizational commitment mediate the effect of job involvement on turnover intentions (Parasuraman, 1982 ) . Therefore, Hypothesis 3 predicts that job involvement has direct effects on job satisfaction, career satisfaction, organizational commitment, and intention to leave. Specifically, it is predicted that job involvement is positively related to job satisfaction, career satisfaction, and organizational commitment, and negatively related with intention to leave. 3.4. Job satisfaction, career satisfaction, and organizational commitment Job satisfaction, career satisfaction, and organizational commitment reflecting a positive evaluation of the job and/or of the employing organization are assumed to influence turnover intentions. It has been suggested that satisfaction, job involvement and organizational commitment are related but distinguishable attitudes (Brooke and Price, 1989). Satisfaction represents an affective response to specific aspects of the job or career and denotes the pleasurable or positive emotional state resulting from an appraisal of one’s job or career (Locke, 1976; Porter et al., 1974; Williams and Hazer, 1986). Organizational commitment is an affective response to the whole organization and the degree of attachment or loyalty employees feel toward the organization. Job involvement represents the extent to which employees are absorbed in or preoccupied with their jobs and the extent to which an individual identifies with his/her job (Brooke et al., 1988). Several studies have focused on the relationships between job satisfaction and organizational commitment, and intention to leave (Baroudi, 1985; Bartol, 1983; Bluedorn, 1982). It was suggested that satisfaction and organizational commitment were related but distinguishable attitudes, in that commitment is an affective response to the entire organization, whereas job satisfaction represents an affective response to specific aspects of the job (Locke, 1976; Porter et al., 1974; Williams and Hazer, 1986). Moreover, the findings of Cotton and Tuttle (1986) and Michaels and Spector (1982) provide evidence that job satisfaction has a direct effect on turnover intentions as well as an indirect effect through organizational commitment. In addition, it is reasonable to expect that high levels of career satisfaction would enhance organizational commitment since employees who are satisfied with their careers should perceive

108

greater benefits in retaining membership in their organizations than employees whose careers have been less gratifying. Therefore, Hypothesis 4 predicts that job satisfaction and career satisfaction have direct effects on organizational commitment and intention to leave. Specifically, it is predicted that job satisfaction and career satisfaction are positively related to organizational commitment and negatively with intention to leave. A number of empirical studies confirm the important role of organizational commitment in influencing turnover intentions (Baroudi, 1985; Bartol, 1983; Steers, 1977). Engineers who are highly committed to their organization are less likely to leave than employees who are relatively uncommitted. It has also been reported that organizational commitment is more strongly related to turnover intentions than is job satisfaction (Baroudi, 1985; Peters et al., 1981; Shore and Martin, 1989). Therefore, Hypothesis 5 predicts that organizational commitment has a direct effect on intention to leave. Specifically, it is predicted that organizational commitment is negatively related to intention to leave. 4. Research methodology 4.1. Sample and procedure

A Fortune 500 company located in the northeastern portion of the U.S. with extensive operations in the defense industry agreed to participate in a comprehensive study of engineering careers with special emphasis on intention to leave the organization. Participants in this study were 150 engineers within manufacturing, R&D, systems, design, quality assurance and production control departments. These departments were selected jointly by the Assistant General Manager and the researchers as a representative sample of functional areas for engineers in typical product type organizations. The Vice-President of Operations for the Division personally delivered the survey instruments to the vice-presidents of the participating departments and requested them to distribute the surveys amongst their engineering personnel. Participation was voluntary. The survey was accompanied by a cover letter from the researchers which explained the study and assured that individual responses would be treated as confidential. A postage-paid envelope was provided so that the engineers could return their completed surveys directly to the researchers at their university address. Completed surveys were received from 107 engineers, a 71.3 percent response rate. Table 1 presents a summary of the demographic characteristics of the sample.

109 TABLE

1

Demographic

characteristics

of the sample

(N=

107)

Gender Male

85.0% 15.0%

Female Education High school Bachelor’s degree

14.0% 39.3%

Graduate

46.7%

degree

Marital status Unmarried

15.0% 85.0%

Married Organizational Professionals Supervisors

level (no supervisory

responsibilities)

and managers

Age Mean=44.57

S.D. = 10.89

Organizational tenure (in years) Mean = 13.32 S.D. =9.50

Median = 46

Median = 11

45.8% 54.2%

Range=21-65

Range=

l-34

4.2. Measures

Participants were asked to indicate their job titles in an open-ended item. Education consisted of three levels: (1) high school; (2) Bachelor’s degree; and (3) graduate or professional degree. Organizational tenure was measured by the number of years an individual had been employed in the organization. Level in the organization hierarchy consisted of four tiers: (1) professionals; (2) first-level supervisors; (3) middle management; and (4) strategic management (executives). The demographic items were included in the background information section of the engineer’s survey. Role stressors. Role stressors consist of role ambiguity and role conflict. They

were operationally defined using a combined index of role ambiguity (three items) and role conflict (three items) adopted from Kahn et al. (1964) and Rizzo et al. (1970). Each scale was scored using a &point response mode ranging from (1) very false to (5) very true. The role conflict and role ambiguity items were reverse-scored so that the greater the score, the greater the perceived stress. These scales were chosen because of their established psychological properties (Schuler et al., 1977; Van Sell et al., 1981) and their wide usage

110

in role theory research. A confirmatory factor analysis of the six items using a factor analysis procedure with varimax rotation (the two factors accounted for 75.3 percent of the total variance) revealed the existence of two factors that were correlated at 0.36, suggesting that the measures were assessing distinct constructs. On the basis of this empirical evidence, it was concluded that the two factors should be examined separately in subsequent analyses. The three items of role ambiguity were averaged to obtain an overall index of role ambiguity (alpha = 0.88). Similarly, the three items of role conflict were averaged to develop the role conflict score (alpha = 0.78). Task characteristics. The five core task attributes of skill variety (alpha = 0.82, task identity (alpha = 0.82 ) , task significance (alpha = 0.88)) job autonomy (alpha = 0.84)) and job feedback (alpha = 0.84) were measured by the Hackman and Oldham (1975) Job Diagnostic Survey (JDS), with some modification of the reverse-scored items following Idaszak and Drasgow’s (1987) findings. The reliability and validity of the revised JDS have been well established and documented (Kulik et al., 1988). Dunham (1976) felt that all five dimensions could be subsumed in a single dimension reflecting job complexity without losing the meaning of enriched work. That is, it could be said that an enriched job is simply more complex than a routine job. Following Michaels and Spector (1982) in their test of the model of Mobley et al. (1982) and Dunham (1976), the motivating potential score (MPS) was computed from the five task characteristics using the formula proposed by Hackman and Oldham (1975,198O):

MPS = 3 (Skill variety + Task identity+ Task significance) x Autonomy x Feedback

Additionally, given the importance of challenging and interesting tasks to technical professionals, specifically engineers (Sherman, 1986)) we included one question asking the participants to respond to the following item: “To what extent does your current job situation provide the opportunity to engage in those challenging and exciting projects with which you are most interested?“. Responses to this item were made on a five-point scale ranging from (1) not at all to (5) to a great extent. This was measured using a four-item scale based upon Kanungo’s (1982) study. Job involvement is defined as the extent to which an individual identifies psychologically with his/her job. A Likert-type response format was provided with response options ranging from (1) strongly disagree to (5) strongly agree. The construct included the following items: “I am very much involved personally in my job “; “Most of my interests are centered around my job”; “ I consider my job to be very central to my existence”; and “most of

Job involvement.

111

my personal life goals are job-oriented”. A factor analysis (with varimax rotation) produced a single factor solution with an eigenvalue of 2.58 accounting for 64.5 percent of the explained variance. These four items were averaged to obtain an overall index of job involvement. The internal consistency reliability of the scale was 0.92. Career satisfaction. This was measured by a five-item scale adapted from prior research (Greenhaus et al., 1990)) with appropriate changes to make the items more relevant to the present study. Individuals were asked to indicate their agreement or disagreement with each statement on a five-point Likert-type scale ranging from ( 1) strongly disagree to (5) strongly agree. Sample items include: “I am satisfied with the success I have achieved in my career”, and “I am satisfied with the progress I have made toward achieving my overall career goals”. This measure also included satisfaction with the rate of promotion, the pay level, and with the status that they had achieved during their careers. A factor analysis (with varimax rotation) produced a single factor solution with an eigenvalue 3.32 which accounted for 66.4 percent of the explained variance. Responses to the five items were averaged to create a career satisfaction score (alpha=0.87).

This was operationalized by a three-item scale developed by Hackman and Oldham (1975) reflecting overall satisfaction with the job. Each item required the respondents to indicate their agreement or disagreement on a five-point scale ranging from (1) strongly disagree to (5) strongly agree. A factor analysis (with varimax rotation) produced a single factor solution with an eigenvalue of 1.91 which accounted for 63.7 percent of the explained variance. Responses to the three items were averaged to produce a total job satisfaction score (alphaz0.71). A factor analysis of the five-item scale of career satisfaction and the three-item scale of job satisfaction was used to examine the existence of the two measures previously specified. In this case, factor analysis was used to confirm rather than to discover factors (Nunnally, 1978). The analysis produced two factors with eigenvalues greater than or equal to 1.0 that accounted for 65 percent of the total variance. The five items that loaded highly on the first factor are identical to the items measuring career satisfaction. The remaining three items that loaded highly on the second factor are identical to the three items measuring job satisfaction.

Job satisfaction.

Organizational commitment. This variable, defined as the identification with a particular organization and the desire to maintain membership in the organization, was measured by an abbreviated version of the Organizational Commitment Questionnaire (OCQ) developed by Porter et al. (1976). The nine items used to construct the scale tap two of the three dimensions of commitment included in the longer version of the OCQ: (1) a strong belief in and

112

acceptance of the organization’s goals and values; and (2 ) a willingness to exert considerable effort on behalf of the organization. In order to avoid concept redundancy (Morrow, 1983), the six items reflecting a strong desire to maintain membership in the organization were excluded from the measure of commitment because they overlapped with the measure of turnover intentions. Thus the shorter version of the scale used in this study represents a more “pure” measure of the affective dimensions of commitment to the employing organization. Sample items are “I really care about the fate of my organization”, and “I feel very little loyalty to my organization”. The response options to the items ranged from (1) strongly disagree to (5) strongly agree. The reliability and validity of the nine-item version have been found to be acceptable (Brooke et al., 1988; Price and Mueller, 1981). The items were recoded such that high scores reflected more commitment to the organization. The coefficient of reliability of this measure was 0.90. Intention to leave. This was measured by a single item which asked participants: “Given everything you know about the company in which you are employed and the type of work you like to do, how long do you think you will continue to work at this company ?“. The response options were anchored on a time-linked five-point scale ranging from (1) one year or less to (5) eleven years or more, or until retirement. The items were reversed such that high scores reflected stronger interactions to leave the organization. The efficacy of a single-item measure of intention is supported by the findings of Kraut (1975) and others. 4.3. Data analysis The technique of path analysis using least-squares multiple regression was used to determine whether the observed pattern of relationships among the variables was consistent with the causal model presented in Fig. 1. The choice of path analysis over structural equation modeling techniques such as LISREL is based on the small sample size and the well established measures for all the variables (for more details, see Fornell ( 1982 ) ). However, it was necessary to first take several steps to check for possible violations of the assumptions underlying the use of path analysis (Billings and Wroten, 1978; Heise, 1969). An examination of the alpha coefficients indicated satisfactory levels of internal consistency reliability among all the multi-item scales (alpha coefficients ranged from 0.71 to 0.90). The intercorrelations ranged from -0.66 to 0.65 and the median intercorrelation was 0.07, failing to reveal evidence of extreme multicolinearity (i.e., r’s > 0.80). Additionally, the residuals of the endogenous variables were tested for autocorrelation using the Durbin-Watson d-statistics (Dillon and Goldstein, 1984). The results showed that the distribution of the

113

d-statistics (mean = 1.98, range = 1.80 to 2.18) strongly indicated the absence of correlated residuals. The application of path analysis to theory development often involves two sets of path analyses to examine the pattern of relationships among variables in a model (Heise, 1969). Initially, a fully recursive model was examined in which multiple regression analyses were performed to assess all possible direct effects of the antecedent variables on each dependent variable. In order to provide a more parsimonious representation of the data, the model was trimmed by deleting the nonsignificant paths revealed by the initial analyses, and by excluding those variables from a given analysis that showed no direct or indirect relationship with the dependent variable being predicted. The omitted-parameter test (James et al., 1982) was used to determine whether the paths in the trimmed model were statistically significant and whether or not the unpredicted paths were significant. This involves testing all the direct paths (predicted or unpredicted) among the model variables. In this manner, one identifies all possible ways to confirm and disconfirm the proposed model. Hierarchical multiple regression (Cohen and Cohen, 1983) was utilized to conduct the omitted-parameter test, and to assess the direct and indirect effects of the independent variables on each dependent variable. Accordingly, we first regressed job involvement on demographic characteristics as control variables, adding role stressors (role ambiguity and role conflict) in step 2, and then the two task characteristics (MPS and challenge) were added in step 3. In a similar manner, job satisfaction and career satisfaction were regressed on demographic characteristics in the first step, adding role stressors in the second step. Task characteristics were added in step 3, and job involvement added in step 4. We also regressed organizational commitment on demographic characteristics in step 1, adding role stressors (step 2). Task characteristics were added in step 3, job involvement in step 4, and job satisfaction and career satisfaction in step 5. Finally, intention to leave was regressed on demographic characteristics in step 1,adding role stressors (step 2). Task characteristics were added in step 3, job involvement in step 4, job satisfaction and career satisfaction in step 5, and organizational commitment added in step 6. In each analysis the significance of the beta weight for the hypothesized independent variable was examined to determine support for the hypothesis. The initial beta weight of the variable when it first enters a regression analysis represents the total effect of the independent variable on the dependent variable, whereas the final beta weight, calculated after all the independent variables have entered the analysis, represents the direct effect of the variable. The difference between the total effect and the direct effect reflects the indirect effect of the variable on the dependent measure (Alwin and Hauser, 1975; Ross, 1975). Indirect effects can also be estimated by the products of direct effects (for more details see Cohen and Cohen, 1983).

114

5. Results

Table 2 presents the means, standard deviations, and intercorrelations among the variables examined in this study. The correlations reveal that task characteristics (MPS and challenge, respectively) are positively correlated with: job involvement (r= 0.30, 0.36, p < 0.001); job satisfaction (r=0.35, 0.35, p < 0.001); career satisfaction (r = 0.41, 0.45, p < 0.001); organizational commitment (r = 0.38,0.43, p d 0.001); and negatively correlated with intention to leave (r = - 0.39, - 0.37, p < 0.001) . Role ambiguity was found to be negatively correlated with job involvement (r = - 0.29, p < 0.001). Role ambiguity and role conflict are negatively correlated with: job satisfaction (r = - 0.55, - 0.31, pdO.001); career satisfaction (r= -0.51, p~0.001; -0.20, ~~0.05); and organizational commitment (r = - 0.39, p d 0.001; - 0.23, p d 0.01); and positively with intention to leave (r zO.22, 0.23, p d 0.01). Furthermore, Table 2 shows that job involvement is positively correlated with job satisfaction, career satisfaction, and organizational commitment (r= 0.43,0.32,0.49, p < 0.001, respectively), and negatively correlated with intention to leave (r= -0.43, p < 0.001) . As expected, job satisfaction and career satisfaction are positively correlated with organizational commitment (r = 0.64, 0.52, p < 0.001, respectively) and negatively with intention to leave (r= - 0.48, - 0.36, p< 0.001, respectively). Finally, the results show that organizational commitment is negatively correlated with intention to leave (r = - 0.52, p 6 0.001) . The results of the initial multiple regression analyses testing the fully recursive model are presented in Table 3. The data show that 22 of the 54 paths tested were statistically significant. Role ambiguity showed significant effects on job involvement, job satisfaction, career satisfaction, and organizational commitment. Role conflict had a significant negative effect only on job satisfaction, and a significant positive effect on intention to leave. Task challenge was found to have positive effects on job involvement, job satisfaction, career satisfaction, and organizational commitment and a negative effect on intention to leave, whereas MPS had only a negative effect on intention to leave. In addition, job involvement had positive effects on job satisfaction and organizational commitment. Job satisfaction had a positive effect on organizational commitment, and a negative effect on intention to leave, and finally, organizational commitment had a negative effect on intention to leave. Among the demographic variables, Table 3 shows that gender, age, and education had no significant effects on either one of the dependent variables. Therefore, they were excluded from further analysis. The results of the analysis of the trimmed model are summarized in Tables 4-6. The large-sample chi square test (Joreskog and Sorbom, 1984; Kim and Kohout, 1975), was performed to determine the adequacy of the restricted model. It showed that the full and reduced models did not differ significantly in their ability to explain variance in the outcome measures.

0.70 0.90 1.54

3.82 3.17 3.07

11. Job satisfaction

12. Career satisfaction

13. Organizational

“The absolute value of correlations

to leave

0.12

0.02

0.04

-0.04

-0.06

-0.12 -0.08

-0.04 -0.18

1.00 -0.25 -0.23 -0.20 -0.29

1

-0.03 -0.13

0.14 0.16

1.oo 0.07

4

-0.32

0.20

0.12

0.23

0.01

0.14 -0.02

-0.02 -0.11

at 0.05 level or better.

-0.03

-0.14

0.26

-0.33

-0.15

0.12 0.08

0.08 -0.10

1.00 -0.10 0.17

3

0.13

0.26 -0.05

-0.17 -0.15

1.00 -0.07 0.65 0.07

2

Correlations”

(N= 107)

> 0.16 are significant

1.08

3.54

10. Job involvement

14. Intention

0.97

2.97

commitment

70.67 1.16

score

0.87 1.15

0.36 10.03 0.71 9.50 1.02

S.D.

163.80 3.03

Task characteristics 8. Motivating potential 9. Challenge

6. Role ambiguity 7. Role conflict

1.90 2.85

1.15 44.99 2.32 13.32 2.02

Demographic characteristics 1. Gender (l=M; 2=F) 2. Age 3. Education 4. Organizational tenure 5. Organizational level

Role stressors

Mean

among study variables

Variables

Matrix of intercorrelations

TABLE 2

-0.19

0.33

0.22

0.25

0.20

0.24 0.33

-0.23 0.02

1.oo

5

0.22

-0.39

-0.51

-0.55

-0.29

-0.49 -0.37

1.00 0.36

6

0.23

-0.23

-0.20

-0.31

0.01

-0.14 -0.03

1.00

I

-0.39

0.38

0.41

0.35

0.30

1.00 0.49

8

-0.37

0.43

0.45

0.35

0.36

1.00

9

-0.48

0.66 0.64

0.32 0.49 -0.30

1.00

11

0.43

1.oo

10

-0.36

0.52

1.00

12

-0.52

1.oo

13

1.00

14

116 TABLE 3 Summary of multiple regression results: total effects of antecedent variables on job involvement, job satisfaction, career satisfaction, organizational commitment and intention to leave Antecedent

Standardized regression coefficients Job involvement

Demographic characteristics Gender (l=M; 2=F) Age Education Organizational tenure Organizational level

-0.02 0.16 -0.16 -0.13 0.21’

Job satisfaction

Career

Organizational

Intention

satisfaction

commitment

to leave

0.07 0.17 -0.14 0.11 0.27’

0.15 0.11 -0.03

0.15 0.03 -0.13

-0.04 -0.19

- 0.44***

-0.46"'

-0.24*

0.09

-0.18’

-0.02

-0.15

0.19*

0.05 0.26’

0.16 0.38***

-0.02 -0.20* -0.18

Role stressors Role ambiguity Role conflict

- 0.25’ 0.07

Task characteristics Motivating potential score Challenge

0.09

0.27’

Job involvement

-0.02 0.20’ 0.24**

0.11 0.26**

0.15 0.25*

- 0.20* -0.29**

0.11

0.34”

-0.16

0.40****

-0.31***

0.07

-0.01 -0.27’

Work attitudes Job satisfaction Career satisfaction Organizational commitment 0.20**

R2 *p’po.o5,

**p
0.48*‘*

0.37”’

0.56***

0.37”’

***p
The data in Table 4 show that the antecedent variables explained 18 percent of the variance in job involvement (p < 0.05). Table 4 reveals that the model explained 47 percent of variance in job satisfaction (p< 0.001) and 37 percent of variation in career satisfaction (p d 0.001). Table 6 shows that the trimmed model explained a total of 54 percent of the variance in organizational commitment (p d 0.001)) and a total of 41 percent of the variation in intention to leave (p
117 TABLE

4

Direct effects of role stressors and task characteristics

on job involvement,

controlling

for demo-

graphic characteristics Antecedent

variables

Job involvement

Demographic characteristics Organizational tenure Organizational level

AR2

-0.01 0.20*

0.04

-0.29** 0.09

0.07*

0.08 0.25*

0.07’

Role stressors Role ambiguity Role conflict Task characteristics Motivating Challenge

potential

score

O.lS*

R2 *p
TABLE

**p < 0.01.

5

Direct, indirect, and total effects on antecedent variables on job satisfaction Antecedent

variables

Job satisfaction Direct

Demographic characteristics Organizational tenure Organizational level

0.22’ 0.07

Role stressors Role ambiguity Role conflict

-0.39*** -0.17*

Task characteristics Motivating potential score Challenge

-0.05 0.12

Job involvement

0.26’.

R2 ‘PGO.05,

Indirect

0.00 0.18

- 0.08 0.02

0.02 0.07

Career satisfaction Total

AR’

Direct

Indirect

Total

AR*

0.22’ 0.23’

0.10”

0.08 0.03

0.01 0.18

0.09 0.21’

-0.47*** -0.15

0.28”’

-0.31” -0.05

-0.15 0.01

- 0.46” -0.04

-0.03 0.19’

0.03

0.09 0.24’

0.01 0.03

0.10 0.27*

0.08”

0.06”

0.12

0.12

0.01

0.26”

0.47*** **p
and career satisfaction

0.06’

0.22***

0.37***

***p< 0.001.

( AR2 = 0.04, NS ) , whereas each of the role stressors and task characteristics explained 7 percent (AR’ = 0.07, p d 0.05) of the variation in job involvement. Table 5 shows that demographic characteristics explained 10 and 6 percent of the variance in job satisfaction and career satisfaction respectively

118

(AR'= 0.10, pd 0.01; AR2 = 0.06,p < 0.05))role stressors explained 28 and 22 percent (AR2=0.28, 0.22, p d O.OOl), task characteristics explained 3 and 8 percent ( AR2 = 0.03, NS; AR2 = 0.08,p d 0.01)) and job involvement explained 6 and 1 percent (AR2=0.06, ~~0.01; AR2=0.01, NS). The path analysis results show that role ambiguity (/I= -0.39, pd 0.001) and role conflict (/?= -0.17, p < 0.05) had direct effects on job satisfaction. Table 5 shows that the total effect of challenge on job satisfaction is significant (/?= 0.19,p d 0.05). Consistent with our prediction, job involvement had a direct effect on job satisfaction, but it had no significant effect on career satisfaction (p=O.12, NS). The results of Table 5 also show that while role ambiguity had a negative effect (/I= -0.31, pfO.OO1) on career satisfaction, challenge had a positive effect (/?=0.24, p< 0.05). Note that role ambiguity and challenge also had indirect effects on career satisfaction and job satisfaction through job involvement. Table 6 shows that job involvement and job satisfaction had positive effects on organizational commitment, and negative effects on intention to leave. No effects were found with regard to the relationship between career satisfaction and organizational commitment and their relationship with intention to leave. Table 6 clearly shows that task challenge had both direct and indirect (through job satisfaction and job involvement) effects on organizational commitment TABLE

6

Direct, indirect, and total effects of antecedent Antecedent

variables

variables on organizational

Organizational Direct

Demographic characteristics Organizational tenure Organizational level

commitment

Indirect

0.06 0.14

0.12 0.18

0.10 -0.11

-0.37 - 0.03

Task characteristics Motivating potential score Challenge

0.09 0.11

0.00 0.16

Job involvement

0.23”

0.11

Work attitudes Job satisfaction Career satisfaction Organizational commitment

0.40**** 0.08

Role stressor Role ambiguity Role conflict

**p< 0.01,

***p
and intention to leave

Intention to leave AR2

Direct

Indirect

Total

AR’

-0.19’

-0.10

- 0.30**

0.14***

-0.01

-0.20

-0.18’

0.11***

-0.20 0.15

-0.30 0.04

0.09 0.27”

0.08”

-0.19’ -0.15

-0.01 -0.11

- 0.20’ -0.26**

O.ll***

0.34**

0.10***

-0.04

-0.14

-0.18’

0.03’

0.40*** 0.08

0.11***

-0.22 0.03 -0.24*

-0.10 -0.02

-0.32’ 0.01 -0.24*

0.05* 0.03’

O.lB* 0.32”’

-0.27” -0.14

0.54***

R2 ‘PGO.05,

Total

commitment

0.10 0.19’

0.13***

0.06*

0.41***

119

Role

Ambiguity

Role

Conflict

Job Job

Satisfaction

Involvement

Organizational Commitment

MPS Challenge

Intention

Fig. 2. Results of the turnover intentions

model of engineers.

To Leave

(The numbered arrows correspond

to the direct effects described in the results section.)

and intention to leave. However, as Table 6 indicates, the indirect effect (0.24) of job involvement on intention to leave was substantially stronger than the direct effect (0.04). Similarly, the indirect effect of role ambiguity ( -0.37) was considerably stronger than the direct effect (0.10). Organizational tenure and organizational level had direct and indirect effects on organizational commitment and intention to leave. Job satisfaction was found to have direct and indirect effects on intention to leave. Finally, organizational commitment (p= - 0.24, p < 0.05) had a negative effect on intention to leave. Figure 2 summarizes the results of our paper. 6. Discussion and implications The results of this study indicate that turnover intention among engineers is the product of complex linkages among role stressors (role conflict and role ambiguity), task characteristics, job involvement, job satisfaction, career satisfaction, and organizational commitment. These findings highlight the importance of organizational commitment as the most immediate determinant of intention to leave. They underscore the key mediating role of organizational commitment defined in the turnover models (Baroudi, 1985; Bartol, 1983; Mobley et al., 1979; Steers, 1977), and demonstrated in empirical studies of turnover intentions among engineers. Job involvement and job satisfaction were found to have indirect effects on turnover intentions through their effects on organizational commitment. The fact that the two task characteristics (MPS and challenge) had direct and indirect effects on turnover intentions emphasizes the importance of interesting and challenging work, feedback, variety, and autonomy among engineers. This is consistent with Garden’s (1989) findings which emphasize the importance of task characteristics in reducing turnover rate among technical professionals. Based on these findings, organizations could reduce voluntary turnover of engineers by properly assigning

120

interesting tasks, providing positive feedback, as well as encouraging freedom to be more creative and original. The results generally support the hypotheses concerning the impact of role stressors on work attitudes. Role ambiguity and role conflict were found to be negatively and strongly associated with job satisfaction, They were also found to be negatively associated with career satisfaction, organizational commitment, and positively related to intention to leave. This emphasizes the importance of role ambiguity and conflict on the career of engineers. Engineering managers can substantially increase job satisfaction and career satisfaction levels, and increase employee commitment and reduce the likelihood to leave the organization by assuring that engineering jobs are clearly defined (they should avoid excessive ambiguity ), that engineers have the necessary information to perform well, and that a job does not require incompatible behavior (Badaway, 1990). Furthermore, if role conflict and role ambiguity are conditions inherent to the engineering environment, engineering managers should pay special attention to recruiting employees who have relatively high tolerance for both role conflict and role ambiguity (Caplan et al., 1980). Whether such characteristics are, in fact, an integral part of the personality profile of engineers is a recommended area for future research. Lastly, engineering managers must manage role conflict and role ambiguity effectively by ensuring that the levels of role conflict and role ambiguity are not raised unnecessarily as a result of poor management practices and policies within the engineering department. Appropriate conflict management techniques should be practiced. A most interesting result is the direct and the indirect effects of task characteristics on job involvement, satisfaction, commitment, and intention to leave. This confirms the notion that changes in the job design (job enrichmentincreasing engineers’ control over their jobs and participation in determining the organizational policy) improve an engineer’s attitude toward the job, career, and organization. Job challenge and autonomy include the intrinsic aspects of job content, which, when present, lead to satisfaction and commitment. This condition provides engineers with greater motivation and opportunities for satisfaction than are provided by routine or simplified tasks. It is important to note that a higher level of motivation will eventually yield decreased turnover. The results of this study support the notion that if jobs provide autonomy and challenge, employees will be more satisfied with their jobs and careers, more committed to their organization, and less likely to leave their organizations. These findings suggest that engineering managers should focus attention on two factors. One, they must provide sufficient challenge and autonomy on the job. This implies that where possible the job should be redesigned to incorporate those two motivators (autonomy and challenge) in order to enrich it and eventually generate positive motivation and commitment. Two, they must again, wherever possible, provide jobs for engineers which permit freedom and autonomy to be creative and pursue their own ideas. It is reason-

121

able to assume that engineers who are given more challenging assignments and more freedom may develop stronger binds to the organization and eventually be less likely to leave the organization than their counterparts. Whether managers of engineering departments can easily apply these findings and design jobs with enhanced opportunities for creativity and autonomy is somewhat questionable. An issue of conflicting goals between organizational levels needs to be addressed. For an organization at the “maturity” stage of the life cycle with respect to its product or service lines, the degrees of freedom for engineers to be creative and autonomous would be somewhat limited. On the other hand, a technology-driven organization going through the start-up and innovation stages of product or service development would appear to be more suitable for increased levels of creativity and autonomy. Further research needs to be undertaken to asses the limitations of direct application of these findings at various organizational levels as well as across different types of organizations and at different stages of their life cycles. The expectations that job involvement would predict satisfaction, commitment, and intention to leave are only partially confirmed. The data indicate that job involvement had a direct effect on job satisfaction and organizational commitment, and had an indirect effect on intention to leave as well as on organizational commitment through job satisfaction. There was also a positive correlation between job involvement and career satisfaction (r= 0.32, p d 0.001 ), and a negative correlation with intention to leave (r= - 0.30, p < 0.001). Job involvement was also found to be related to task characteristics (r=0.30, 0.36, p < 0.001 for MPS and challenge, respectively) and role ambiguity (r= - 0.29,p < 0.001)) all of them entering the regression analysis prior to job involvement. Thus, it is not job involvement per se that enhances career satisfaction, but rather factors that promote job involvement such as task characteristics and role stressors. Engineering managers desiring to reduce subordinate intentions to leave should focus on enhancing their job involvement and participation. They should try to assign interesting tasks, make sure that the assignments are clear, and provide them with more autonomy and freedom so that engineers can be involved in their jobs. If an organization provides all these features which are found to be important to engineers, they will create an environment conductive to high involvement for them. Such an environment is expected to increase satisfaction and commitment and eventually reduce the likelihood for leaving the organization. Furthermore, note that job involvement had direct and indirect effects on intention to leave through job satisfaction and organizational commitment. This emphasizes the importance of job satisfaction in determining organizational commitment and consequently the decision to leave. These findings suggest that affective reactions of employees to their specific jobs as well as to their organizations as a whole have important consequences for human resource planning by engineering and technology managers. The implications of

122

these findings may be relevant to behaviors of other technical professionals such as scientists and physicists. Consistent with the turnover literature, job satisfaction and career satisfaction were found to have direct effects on organizational commitment (Baroudi, 1985; Bartol, 1983; Shore and Martin, 1989). Additionally, job satisfaction was found to have direct and indirect effects on intention to leave through organizational commitment, thus emphasizing the importance of satisfaction in determining organizational commitment and consequently intention to leave. Therefore, besides implementing the measures discussed earlier regarding the determinants of job satisfaction, managers should also try to encourage employees by providing tasks that they are better at or enjoy doing. It is important that managers try to ensure engineers’ satisfaction with their work, their supervisors, and the people they work with. They should also strive for fair promotion policies, attractive career paths and reward systems, and effective performance appraisal systems (Badawy, 1988). In addition, organizations should stay closely tuned to engineers’ levels of satisfaction. These engineers could become easy targets for raiding organizations and “head hunters”. In some cases, the raiding organizations can be quite successful if they can manage to provide these engineers with opportunities for higher levels of satisfaction. Note that organizational commitment was found to have a direct effect on intention to leave. This suggests that affective reactions of employees to their specific jobs, and to their organization as a whole, are important determinants in the decision to leave the organization, and carries with it direct implications for engineering and technology management. Finally, the present study indicates that organizational tenure and organizational level had effects on job satisfaction, organizational commitment, and intention to leave. Note that organizational level was found to contribute indirectly to job involvement, satisfaction, commitment, and intention to leave, and that organizational tenure had a direct effect on job satisfaction and both direct and indirect effects on organizational commitment and intention to leave. These results show that engineers who had been employed for several years in the organization and engineers who were in high positions were less likely to leave the organization than others. Overall, the results of this study are meaningful and interesting, and provide added insight into the network of factors contributing to an engineer’s decision to leave the organization. However, although the results may be generalized to other engineers in different industries, as well as possibly to other categories of technical professionals and R&D people, it would be prudent to cross-validate the findings of different groups of engineers and technical professionals in other industries. Therefore, additional research, using a wider and a larger sample of engineering employees than those represented in the present sample, is necessary in order to confirm the generalization of the findings to a larger population of engineering employees.

123

In addition, while the results indicate plausibility of the causal links proposed, they do not prove causality (James, 1980 ). It is possible that alternative linkages exist among the variables in the model (the relationships between satisfaction, advancement, commitment, and performance and intention to leave) (Shore and Martin, 1989). Longitudinal research should be conducted to answer some very important questions regarding causal relationships among the variables in this study. Furthermore, it appears that the relationships among the model variables are more complex than we initially proposed. Thus, other variables not included in this study may be relevant to understanding variations in turnover intentions and should be incorporated within the revised model. Further, the nonsignificant paths found for some of the variables indicate the need for caution in interpreting the results. The discrepancies suggest the possibility of unspecified and unmeasured variables (Billings and Wroten, 1978; James, 1980) such as the size of the company, the industry (Garden, 1989)) work activities, organizational rewards and work performance. Additional research is also needed to more thoroughly examine the differences between engineers and other technical professionals such as scientists. This study provides important insights into the role of work attitudes among engineers and represents a significant starting point for additional research using multivariate causal models to investigate the antecedents of turnover intentions. Since several job-related variables had effects on turnover intentions, quasiexperimental research should be conducted to determine whether actual changes in job duties and role characteristics have an impact on the turnover intentions of engineers. Finally since intention to leave was used to predict actual turnover, future research should try to gather actual turnover data and seek to predict the actual turnover instead of its intentions. Nevertheless, the present model provides important insights into the role of role stressors, task characteristics, job involvement, satisfaction, organizational commitment in predicting turnover intentions among engineers.

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