A Production Self-Efficacy Scale: An Exploratory Study
By Mosley, Don C Jr Boyar, Scott L; Carson, Charles M; Pearson, Allison W
Self-efficacy is defined as people’s judgments of their capabilities to organize and execute courses of action required to attain designated types of performances (Bandura, 1986). Self- efficacy perceptions, in concert with self-regulatory behaviors, influence the goals people set, strategies people choose, effort people expend, and perseverance people display (Bandura, 1991). Thus, successful performance requires that a person possess both the appropriate skills and abilities and strong feelings of efficacy (Lent et al., 1994). Past research has established the importance of task, domain-specific, and general self-efficacy in determining human behavior (e.g. Ackerman and Kanfer, 1993; Bono and Colbert, 2005; Erez and Judge, 2001; Judge and Bono, 2001; Judge et al., 2000; Judge et al., 2002; Judge et al., 2004; Judge et al., 2005; Lent et al., 1994; Saks, 1995; Stajkovic and Luthans, 1998), but researchers have issued a call for additional studies to further our understanding of the relationship between domain-specific self- efficacy and a broader array of work processes and outcomes (Harrison et al, 1997). Task and general self-efficacy, while important levels of analyses, do not completely address today’s complex business environments in which employees are continually challenged within their job domains; domain-specific measures allow for a rich, contextualized assessment of individual self-efficacy. Efficient and effective performance across a variety of tasks within a given work domain is necessary in order for individuals to remain viably employed. Multitasking, role, work and family, and stress management are not only challenges for employees, but for human resource professionals and managers as well. Today’s management and staff need tools to assist them in making effective developmental and evaluative decisions.
To date, no measure exists to assess applicants or employees’ perceptions of job self-efficacy within production environments, such as automobile manufacturing, shipbuilding, and computer assembly. Considering recent workforce trends, such as the declining competence of the U.S. labor force, the migration of many highly skilled manufacturing jobs abroad, and the influx of foreign-born workers in the U.S. (Latham, 1998; Mosisa, 2006), developing additional tools to assist organizations’ in managing their human capital seems a worthwhile endeavor. Therefore, in order to contribute to our understanding of the manifestation of individual job self-efficacy in more diverse settings, a production self- efficacy (PSE) scale is developed in our study. Given the fact that very little exploration regarding job applicants’ self-efficacy perceptions and post-hire outcomes has been conducted, we utilized two separate organizations’ staffing processes as a means of developing and assessing the PSE scale for reliability and validity.
Next, we provide an overview of the self-efficacy selection and testing literatures. Then, the Methodology and Results section details our efforts of item generation and purification as well as the respondents and procedures used, and reliability and discriminant validity tests for two samples. The Discussion section addresses study limitations and potential future directions for research, and ends with our conclusions based on the study results.
Self-efficacy and Selection
Few studies have explored the influence of self-efficacy during recruitment and selection from either the applicants’ or firm’s perspective, but two such recruiting studies focused on job applicants’ self-efficacy beliefs during the re-employment process. One found that for job seekers with initially low self-efficacy beliefs, job search training led to increased job search self- efficacy perceptions, thereby resulting in more intense job search activities (Eden and Aviram, 1993). Unemployed job seekers with high job search motives and strong feelings of search competence also were found to conduct more intense job searches (Wanberg et al., 1999). Lent et al. (1994) developed a theory of career and job interest and choice based on Bandura’s (1986) social cognitive theory and suggested that self-efficacy perceptions and outcome expectancies were directly and indirectly related to the choice of career and job goals. More recent research examined the relationships among applicants’ personalities, biographical backgrounds, interview self-efficacies, and interview successes. The results indicated that interview self-efficacy mediates the relationships among extraversion, conscientiousness, leadership experience and interview performance (Tay et al., 2006). Positive affectivity is another dispositional characteristic that has been found to predict job search clarity over and above conscientiousness and job search self-efficacy (Cote et al, 2006).
Saks (2006) examined the direct and moderating effects of job search self-efficacy on job search behaviors and job search success. Using a sample of recent university graduates, he found that job search self-efficacy significantly predicted interviews, offers, employment status, and person-job (P-J) fit perceptions, as well as moderated the relationship between job offers and employment status. P-J fit perceptions are typically assessed based on two broad definitions: desires/supplies fit and demands/abilities fit (Saks and Ashforth, 1997). Desires/supplies fit relates to an applicant’s or employee’s evaluation of his or her needs and wants compared to what the organization is willing to provide; whereas, the demand/ abilities fit perspective deals with one’s assessment of the organizational demands and one’s abilities to meet those demands. While self-efficacy involves making judgments about capabilities that relate to a task or a set of tasks, these beliefs are not identical to person-job fit perceptions or an objective assessment of one’s skills (e.g., Lent et al., 1986).
Self-efficacy and Testing
Past selection research utilizing self-efficacy generally focused on either the perceived fairness of employment tests based on the organizational justice perspective or the influence of employment- testing self-efficacy on actual test performance (Ackerman and Kanfer, 1993; Gilliland, 1993; Maertz et al, 2005; Ryan et al., 1996). Based on the organizational justice perspective, Ryan et al (1996) explored which factors influenced the perceived fairness of a physical abilities test (PAT) for firefighters. They found that when both previous experience with a specific PAT and self-efficacy were related to a specific PAT, the test was perceived to be job related. Ackerman and Kanfer (1993) examined employmenttesting self-efficacy and test performance by developing a battery of selection instruments, including a measure of self-efficacy, for the job of air traffic controller. The self-report measure of self-efficacy demonstrated discriminant validity and accounted for an additional four percent of the variance of simulation success. However, they used students and trainees in a simulated environment, not actual job applicants.
Previous research suggests that as a result of different experiences, self-efficacy perceptions may differ among demographic groups depending upon the environmental situation (Bandura, 1997; Lent et al, 1994). One study in particular assessed the antecedents and outcomes of self-efficacy during employment testing and found that past experience with employment tests was positively related to testing self-efficacy. However, neither minority status nor being hired by employment tests in the past had an effect. Additionally, testing self-efficacy was positively related to performance on the employment test (Maertz et al., 2005). Using a self-regulatory job- search framework, LaHuis (2005) investigated the influence of applicants’job pursuit intentions and perceived procedural fairness of selection tests. He found that for clerical jobs, job search self- efficacy moderated the relationship between perceived procedural fairness and job pursuit intentions. Alternatively, the relationships among general and specific self-efficacy in a training experience with newly hired recruits has been studied utilizing a pretest-posttest design. The results indicated that pretraining motivation, training self-efficacy, and performance expectancy influence work-specific self-efficacy (Schwoerer et al., 2005).
In summary, previous research has demonstrated that self- efficacy has important implications for organizational recruitment and selection. However, no study is known to examine individual job self-efficacy in a production setting during the organizational staffing process. Thus, we develop and validate the PSE scale utilizing the staffing processes of two separate manufacturing organizations to enhance our understanding of how self-efficacy manifests itself during recruiting and selection.
METHODOLOGY AND RESULTS
Construct Definition, Item Generation and Purification
In developing the PSE measure, we adhered to Churchill’s (1979) scale development process, which suggested a seven-step process for developing stronger multi-item measures. While self-efficacy has been examined as a general personality variable (Chen et al, 2001; Erez and Judge, 2001), a domain-specific construct (Gist and Mitchell, 1992; Goddard, 2002), and a task-specific variable (Harrison et al, 1997; Schyns and von Collani, 2002), we chose to develop a specific, domain-linked, measure of self-efficacy. The domain of interest is manufacturing and production. As suggested by Churchill (1979), we began creating the PSE scale by specifying the domain of the construct and generating sample items. We obtained key job information for production employees by examining job descriptions and interviewing human resource (HR) personnel at three manufacturing facilities in the southeastern United States. HR professionals were asked to provide the key performance criteria for production jobs in each of the plants. Follow-up questions were provided when necessary to further probe the domain of interest. A comparison was made between the interview responses and the job descriptions to ensure accuracy of the data. For example, a particular interview at one location revealed that promoting a positive image of the organization was important. However, the job descriptions, training and evaluation materials, and other interviews did not support this viewpoint. Thus, it was not included for consideration. Ultimately, the information obtained revealed key performance areas, including work quality, production competence, safety, interpersonal relations, and attendance, which were all used to generate the initial set of sample items. The following paragraphs describe our efforts in carrying out the remaining five steps of Churchill’s (1979) measurement development process: data collection, measurement purification, additional data collection, reliability assessment and, lastly, validity assessment. Initially, 37 items were generated. Six Ph.D.s with expertise in human resource management, scale development, and manufacturing, as well as human resource (HR) directors and managers at each location reviewed the items for the purpose of assessing content validity using the job descriptions, performance criteria, and interview data. Based on their comments, 16 items were retained, modified, and assessed for developmental purposes with actual employees in two separate work settings (see Appendix A). Traditional measures (Bandura, 1986) of self-efficacy have assessed both the magnitude and strength of the construct. These measures are two-part assessments with magnitude responses addressing (with a yes or no answer) specific task performance capabilities and strength responses affirming the respondent’s confidence in those capabilities. However, Maurer and Pierce provided support for using Likert-type “scales as an alternative to the traditional format for measuring self-efficacy” (1998: 329). Subsequent researchers (Tucker and McCarthy, 2001; Carlson et al., 2000) have used such scales as a viable means of assessing self-efficacy. Similarly, we have chosen to use a five- point Likert-type scale with the following response items: 1 = not very confident, 2 = 25% confident, 3 = 50% confident, 4 = 75% confident, 5 = extremely confident.
Respondents and Procedures. The sample consisted of job applicants (N = 117) applying to be production employees with a furniture manufacturing company located in the southeastern United States. Each job applicant was asked to participate by filling out the survey, sealing it in the attached envelope, and dropping it in a locked survey collection box. The applicants were told their responses to the survey would not impact the hiring decision and assured that their answers were confidential. A financial incentive was provided for their participation.
The sample consisted of 14% African-Americans, 61% Caucasians, 17% Hispanic-Americans, 3% Asian-Americans, and 5% Native- Americans. Fifty-eight percent of the sample was male, while forty- two percent was female. The majority of the job applicants were under 40 years of age. Eighty percent of the individuals had related job experience. Fourteen percent of the respondents completed elementary school, 69% finished high school, and 17% graduated from college.
Following procedures established by Joreskog (1993), we utilized confirmatory factor analysis (CFA), employing LISREL 8.5 (Joreskog and Sorbom, 1996) to examine the measurement model. The covariance matrix was used as the input for the analysis. The measurement model was estimated using the maximum likelihood function Sigma = Sigma (Theta), where S is the population covariance matrix and Sigma (Theta) is the predicted population Covariance matrix. A variety of fit indices can be utilized to determine how well the actual data fit the proposed model (Joreskog, 1993). Following Hair et al (1998), we based our evaluation on measures of absolute fit, incremental fit, and parsimonious fit. The chi-square statistic, the goodness-of-fit indicator (GFI), and the root mean square residual (RMSEA) are measures of absolute fit which assess to what degree the proposed model predicts the observed covariance matrix. The normed fit index (NFI) represents the incremental fit measure as recommended by Rentier and Bonnett (1980), which compares the proposed model to the null model. We used the adjusted goodness of fit indicator (AGFI), an extension of the GFI, taking into account degrees of freedom, to measure parsimonious fit. Adjusted goodness of fit indicator (AGFI) assesses whether the overall fit of the model is a result of over-fitting the data. Modification indices for both the lambda-X (LX) and thetadelta (TD) matrices were examined for possible cross-loadings and correlated errors.
Careful and systematic analyses of these indices indicated that nine of the 16 items were candidates for removal. However, prior to eliminating any item, the authors carefully considered its relevance to the domain of interest. Only poorly fitting items that were repetitive or theoretically unnecessary were removed. Therefore, the final scale consisted of seven items representing key performance areas. see Table 1 for the items’ standardized path coefficients, descriptive statistics, and correlations. As shown in Table 2, the chi-square of 22.89 with 14 degrees of freedom is non-significant (p = .06), indicating the proposed seven-item model fits the data well. The GFI of .95, the AGFI of .89, the RMSEA of .07, and the NFI of .98 provide support for the seven-item measure of PSE.
Reliability and Discriminant Validity Tests. Cronbach’s alpha was used to evaluate the internal consistency of the items. Alpha scores of .70 or higher are deemed to be acceptable (Nunnally, 1978). The seven-item measure of PSE has an acceptable coefficient alpha of .91.
To assess the PSE scale’s disriminant validity, correlation analysis (Cohen and Cohen, 1975) was performed with Saks and Ashforth’s (1997) four-item measure of personjob fit. The person- job (P-J) fit measure’s response set is a five-point Likert-type scale ranging from I (To a very little extent) to 5 (To a very large extent). The coefficient alpha of .80 for PJ fit was acceptable.
Saks and Ashforth’s (1997) measure includes items that tap into the two broad definitions of P-J fit: desires/supplies fit and demands/abilities fit. While self-efficacy involves making judgments about capabilities that relate to a task or a set of tasks, these beliefs are not identical to personjob fit perceptions or an objective assessment of one’s skills (e.g., Lent et al., 1986). Self- efficacy perceptions are dynamic beliefs that relate to specific performance domains and influence the goals people set, strategies people choose, effort people expend, and perseverance people display (Bandura, 1991). Successful task performance requires that a person possess both the appropriate skill and ability, and a strong feeling of efficacy relating to the task (Lent et al., 1994). Thus, PSE and P-J fit should be related, but different constructs. The correlation between PSE and P-J fit was .39, indicating significant differences exist. In addition, a means difference test was performed to determine whether PSE perceptions differed for those hired verses those not hired and the results showed no significant differences.
Respondents and Procedures. This sample consisted of job applicants applying to be production employees with a different furniture manufacturing company located in the southeastern United States (N = 2,029). The survey procedure was identical to that in sample one. The sample consisted of 41% African-Americans, 53% Caucasians, 3% Hispanic-Americans, 2% Native-Americans, and 1% Asian- Americans and those identifying the other category. The modal age range was the 18-24 category. Seven percent of the sample finished elementary school, 85% completed high school, and 8% graduated from college. Eighty percent of the individuals had related job experience. Females represented 52% of the sample, while males comprised 48 percent.
The statistical procedure was identical to that in sample one. The chisquare is 360.46 with 14 degrees of freedom (p = 0.00). As shown in Table 2, the GFI of .95, the AGFI of .90, the RMSEA of .11, and the NFI of .98 indicate, overall, the unidimensional PSE factor structure fits the data well. see Table 3 for the items’ standardized path coefficients, descriptive statistics and correlations.
Reliability and Discriminant Validity. The statistical procedures were identical to that in sample one. The coefficient alpha for the PSE scale of .89 was found to be acceptable.
Person-Job (PJ) fit was again used to assess the PSE scale’s discriminant validity. The coefficient alpha for P-J fit in this sample was .83. The correlation between the two constructs was .44 (N = 2,028), suggesting distinct constructs.
Exploratory Analysis. The PSE scale was included in a regression analysis with employee job performance as the dependent variable to explore the predictive validity of the measurement instrument. Actual job performance was assessed using employee efficiency rates or scores. Employees’ efficiency rates, which are calculated by the organization, are based on the amount of production achieved by an individual for a given pay period with base rate adjustments to control for pay differentials. An efficiency score of 100% signifies that the production employee is performing at the expected rate given the individual’s job, knowledge, skills, abilities, experiences, etc. Rates below 100% indicate under-performing employees, while rates above 100% represent overachievement. The efficiency scores ranged from 94% to 228%. Employee job performance was obtained directly from the company six weeks after an employee had been hired. Due to certain organizational constraints (i.e., time limitations), the sample size for this analysis is 50. Overall, the results show a positive relationship between pre-hire PSE and post-hire job performance. The t-statistic is 1.81, the unstandardized coefficient and error are 21 and 11.6, respectively, and the standardized regression coefficient is .25. The R-square is .06 and the adjusted R-square is .05. In addition, a means difference test was performed to determine whether PSE perceptions differed for those hired versus those not hired and the results showed no significant differences.
The purpose of this research was to develop and validate the PSE measure to be used in the production domain. To this end, the PSE scale was created and tested using two separate manufacturing samples. The overall, incremental, and parsimonious fit statistics calculated with the first sample suggested that production self- efficacy is a seven-item construct. The PSE measure demonstrated reliability and discriminant validity. Once the measure was developed, we reassessed the scale’s properties. The results were quite similar to those in sample 1. Afterwards, we conducted a post- hoc exploratory analysis to test the PSE scale’s predictive validity. While PSE was positively related to employee job performance six weeks after hire, the sample size precluded the determination of a significant relationship.
Therefore, we recommend this measure be used by organizations for developmental, rather than selection, purposes until further validation studies may be conducted. For example, administering the PSE scale to new hires during the early stages of employment may help managers in several ways. If administered during the formal orientation or socialization process, the results could provide managers with areas that they could specifically target for training and developmental activities. Such assessments, and the subsequent discussions that should follow, would allow managers to clarify work expectations to their employees. The PSE scale could also be utilized to assess employee progress following training and developmental activities thereby aiding managers in their continuous improvement efforts. This study is not without limitations. Even though we took great care to assure the applicants of confidentiality, the high mean PSE item scores could be a result of social desirability. Further, the samples were from the same industry, which limits generalizability. The sample size for the performance data collected was rather small; however, it is not uncommon to have small samples when collecting employment data.
While self-efficacy has been associated with job-related processes and outcomes (e.g., Jex and Bliese, 1999; Stajkovic and Luthans, 1998), more research is needed that examines selfefficacy in alternative venues. This exploratory study partially fills this void by examining job self-efficacy in a production context in actual organizations. The PSE scale can be used by researchers and practitioners in die future to assess employees’ efficacy perceptions to further improve organizational processes and outcomes.
Quality is an important aspect of all organizations today. Production employees need to meet quality production standards, detect quality problems and make appropriate changes, while properly maintaining and operating the equipment with which they work. Likewise, with increased litigation arising from workplace accidents, organizations should place a premium on developing safety- conscious employees. The employee’s ability to operate safely also positively impacts the amount of output produced, while reducing the amount of time actually spent on the job. Employees are ultimately evaluated on how well they produce. Organizations prefer to employ productive individuals that maintain an optimal production pace, keep track of daily schedules, show up for work on time, and embrace learning new skills to stay ahead of the competition.
While the results from this study suggest the PSE scale is reliable and valid, future research efforts should utilize this measure in providing further evidence of construct validity. One recommendation is to employ the PSE scale in diverse production settings, such as automobile, food preparation, and technology plant environments. Additionally, given that foreign-born workers contributed to nearly half of the increase in the U.S. labor force during the period of 1996-2000, with the trend continuing (Mosisa, 2006), future research should also investigate the PSE scale’s usefulness in multicultural work environments. Specifically, Latinos and Asians represent the largest percentage of influx in the U.S. labor market (Mosisa, 2006). Therefore, to assist researchers’ efforts, we have developed a Spanish version of the PSE scale (see Appendix B). Two Spanish translators employed the translationback- translation method (Oquendo et al., 2001) to create the Spanish version. One individual translated the English version into Spanish, and the second person conducted a back translation to validate the process. After the process was completed, the translators collaborated to ensure that both versions of the surveys were communicating the same information. It is our intention that the Spanish version of the PSE will assist practitioners and scholars alike in the collection of self-efficacy data from the growing Spanish-speaking production workforce.
The post-hoc exploratory analysis revealed an insignificant but positive relationship between PSE and performance. Thus, future researchers might find it fruitful to examine the predictive validity of the PSE scale utilizing controls, such as experience, with larger samples in diverse settings. Additionally, testing for differences based on race and ethnicity and hiring status would assist in establishing PSE as a selection tool.
In summary, the PSE scale demonstrated high internal consistency estimates and validity for two separate samples in a manufacturing environment. Fit indices were acceptable, providing some evidence of construct validity. Through the scale development and validation offered here we have taken an important step in moving self- efficacy measurement away from the generalized measures of the past towards more relevant, domainspecific measures that will allow for a richer, more contextualized assessment of individual self-efficacy.
Self-efficacy has received increased attention in management; in particular, task and domain-specific self-efficacy perceptions have been found to impact organizational commitment, job satisfaction, stress, and performance. More recently, general self-efficacy (GSE) has been linked with important organizational outcomes. While strides have been made, there continues to be a need to examine the impact of domain-specific perceptions of self-efficacy, especially in the manufacturing sector where developing a competent, efficient workforce is critical for the domestic survival of highly skilled production jobs. To assist organizations in effectively managing their employees, a production self-efficacy (PSE) scale is developed using two separate samples. This seven-item measure demonstrates reliability and discriminant validity. Implications and future research directions are discussed.
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Don C. Mosley, Jr.
Assistant Professor of Management
University of South Alabama
Scott L. Boyar
Assistant Professor of Management and Entrepreneurship
Charles M. Carson
Assistant Professor of Management
Allison W. Pearson
Professor of Management and Information Systems
Mississippi State University
Initial 16 Items
1. I can make sure that the materials used to make the furniture are of good quality.
2. I am confident that I can meet the physical demands of my job.
3. I am confident that I can correct mistakes in my work.
4. I am confident that I can maintain the equipment that I work with.
5. I can follow all of the safety rules on the job.
6. I am confident that I can show others how to follow safety rules.
7. I am confident that I can follow all other company rules and policies.
8. I can maintain good work relationships.
9. I can get along with other workers.
10. I am confident that I can get along with my boss.
11. I am confident that I can be on time for work.
12. I am confident that I won’t be late to work.
13. I am confident that I won’t be absent from work.
14. I can keep up with my production pace.
15. I am confident that I can read basic schedules for my job.
16. I can learn all of the right parts and materials used in my job.
PSE Scale (English version):
1. I am confident that I can meet the physical demands of my job.
2. I am confident that I can correct the mistakes in my work.
3. I am confident that I can maintain the equipment that I work with.
4. I can follow all of the safety rules on the job.
5. I am confident that I won’t be late to work.
6. I can keep up with my production pace.
7. I am confident that I can read basic schedules for my job.
PSE Scale (Spanish version):
1. Estoy seguro que puedo cumplir con las exigencias fisicas de mi trabajo.
2. Estoy seguro que puedo corregir errors en mi trabajo.
3. Estoy seguro que puedo mantener las herramientas y la maquinaria con que trabajo en buen estado.
4. Puedo seguir todas las reglas de seguridad en el trabajo.
5. Estoy seguro que no llegar tarde a trabajar. PORFAVOR, CONTINUE AL RESPALDO DE ESTA HOJA.
6. Puedo mantener mi ritmo de produccin.
7. Estoy seguro que puedo leer horarios y tablas simples en mi trabajo si es necesario.
Copyright Pittsburg State University, Department of Economics Summer 2008
(c) 2008 Journal of Managerial Issues; JMI. Provided by ProQuest Information and Learning. All rights Reserved.