The Impact of Firm Reputation on Applicant Inferences, Exams of Psychology

Download The Impact of Firm Reputation on Applicant Inferences and more Exams Psychology in PDF only on Docsity! ABSTRACT DECONSTRUCTING SIGNALING THEORY: THE ROLE OF ORGANIZATIONAL, REFERENT OTHER, AND SELF-REFERENTIAL INFERENCES IN RECRUITMENT By Katie E. Wright Understanding recruitment is crucial for organizations to generate a qualified applicant pool from which they can select employees. Past research on recruitment has looked at applicant willingness to apply for a position and attraction to the company itself. More recently this research has explored the effects of signaling theory to explain these applicant reactions. To date, this research has focused primarily on the signals organizational policies might send to applicants about other aspects of the organization (e.g, profitability, diversity). The results of this research have been mixed, making it unclear as to whether policies act as signals for applicants. However, less emphasis has been placed on what organizational policies might signal to the individual about how they themselves will be treated, or affected if involved with the organization (i.e., self referential inferences). It can be argued that organizational policies will be more important for self-referential inferences than for organizational inferences. This study examined three types of signals that may be sent to applicants’ and the effects of each on applicant’s attraction to a company. Specifically I was interested in learning what kinds of signals firm reputation sends to applicants about a) other aspects of the organization; b) how other employees will be treated; and c) how the applicant will be treated within the company, or affected by the company. To accomplish this research I conducted an experiment using undergraduate psychology students and business students of the university. DECONSTRUCTING SIGNALING THEORY: THE ROLE OF ORGANIZATIONAL, REFERENT OTHER, AND SELF-REFERENTIAL INFERENCES IN RECRUITMENT by Katie E. Wright A Thesis Submitted In Partial Fulfillment of the Requirements For the Degree of Master of Science - Psychology Industrial/Organizational at The University of Wisconsin Oshkosh Oshkosh WI 54901-8621 May 2010 COMMITTEE APPROVAL .tL.k,~- Advisor ')Itt/ID Date Approved Date Approved ~.i~?Jt~.g!---_·__ Member FORMAT APPROVAL $""""1 '"3/10 Date Approved ..~·~Mhy ,C;~-l/fr (-=:~ Member Date Approved __~--,--/_/~1.,..../..;;../_tf__ Date Approved 1 INTRODUCTION Obtaining the best applicant pool possible using effective recruitment practices is critical for most organizations. To advance the understanding of recruitment efforts and applicant attraction, numerous studies have attempted to identify information that would enhance recruiting efforts. Past literature has focused on identifying the influence of various organizational policies and practices on applicant recruitment. For example companies have modified their pay, benefits and working conditions to see what attracts or deters applicants from applying. To understand the processes by which policies and practices influence applicant attraction, researchers have focused on the role of signaling in recruitment. Signaling theory posits that applicants form perceptions about employers based on incomplete information they encounter during the job search process, such as recruitment ads, and recruiters (Rynes & Miller, 1983). While it is seemingly logical to conclude that applicants would make inferences from known information during the job search, the findings with regard to signaling have been somewhat inconsistent. There are at least two possible reasons for this inconsistency: a) by presenting applicants with only positive stimuli or with no stimulus at all, and giving no representation of negative stimulus, past research has not measured the full range of signaling; b) by focusing almost entirely on the signals that are sent about other organizational characteristics or about how other employees will be treated within the organization, past research has missed the most important types of signals; those that indicate how applicants themselves will be affected by the organization. This latter point is particularly important given that 2 applicants tend to interpret characteristics of the job, organization, and the recruiter in light of their own needs and values to determine fit (Chapman et al., 2005). Inferences that are drawn at the individual level, or self-referential inferences, may actually be more important to an applicant than organizational level inferences. These self-referential inferences indicate to the applicant how they will personally be treated within the company, and what they will get out of working in the organization. This present research expands our knowledge of recruitment by addressing both of these deficiencies in the prior research. More specifically, this study first took into consideration the presence of both positive and negative information about an organization. Second, it explored a new dimension to the signaling construct- one that is believed to be of greater importance to applicants as it measures directly how the applicants believe they will be treated within the organization. To examine signaling theory more closely, the current research explored the influence of firm reputation on applicants’ attraction and the inferences applicants make. Firm reputation was chosen as the signal because it is a concept commonly known or found when applying to jobs. It is also a broad concept, unlike statements of equal employment, employment at-will, diversity policies or other similar policies. The hope is that statements of firm reputation will allow applicants more ambiguity than specific statements, and therefore allow applicants to make more inferences. Past research also suggests that job seekers decisions to pursue jobs with organizations are based largely on their overall perceptions of organizational reputation (Turban & Cable, 2003; Gatewood, 3 Gowan & Lautenschlager, 1993; Highhouse et al., 1999), so we can be relatively assured that this information is salient to job seekers. Previous Literature Recruitment Recruitment in organizations serves three primary functions: generating an applicant pool, ensuring demographic representation, and attracting more qualified applicants (Thomas & Wise, 1999). Recruitment is defined by Chapman et al. (2005) as a process that encompasses all organizational practices and decisions that affect either the number, or types, of individuals that are willing to apply for, or to accept, a given vacancy. According to a recent study of 33,000 employers from 23 countries, 40% stated they were having difficulties finding desired talent within the recruiting and hiring process (Ployhart, 2006). Spence (1974) also stated that the amount of time and effort it takes to learn an individual’s productive capabilities means that hiring is a time- consuming and invested decision. Thus it is important to improve our understanding of recruitment. Research in recruitment has focused on who and where to target, the best sources to use, how recruiters can affect applicants, and more recently applicant intentions to apply. For example Barber and Roehling (1993) investigated the process of deciding whether or not to apply for a job. They used verbal reports from participants as they evaluated job postings to decide if they wanted to interview. Findings from this research showed the participants responded more favorably to the amount of information supplied 6 places that they work for (Lievens, Van Hoye, & Anseel, 2007). Ashforth (1989) suggested that people try to classify themselves and others into certain social categories (such as the organization that they work for), to order their social environment as well as identify where they fit into their social environment. Social identity theory states that organizational members develop a sense of who they are from their organizational membership (Lievens, Van Hoye, & Anseel, 2007), and this concept has been used in recruitment to explain an applicant’s organizational fit and identification with an organization. While Turban and Cable (2003) were able to use both theories, use of these theories in future research will depend on whether one is aiming to look at how the applicant makes perceptions about the organization during the application process (signaling theory), or if they intend to find the applicant’s organizational fit once in the environment (Social identity theory). It is because of this difference that this study will look at signaling theory, and not Social identity theory. Applicant Attraction Applicant attraction is a construct that is intended to measure the degree to which an applicant finds a particular job opportunity desirable. A company’s prospective applicants are dependent upon their ability to attract individuals to the job opportunities that they offer. When attraction is higher, an organization is more likely to receive a bigger applicant pool and increase the amount of applicants to select from. Attraction encompasses such dimensions as the general attractiveness of, and interest in, an organization and the potential employer, applicant preferences regarding employers, and probability of application (Cober et al., 2004). 7 Applicant Attraction and Firm Reputation Barber (1998) stated that when deciding where to apply applicants are generally not “blank slates,” but that they already have some impression about the organization before they are exposed to recruitment efforts. In most cases these impressions are known as organizational image (firm reputation), and have been shown to affect the organization’s ability to attract applicants (Frombrun & Shanley, 1990). With regard to applicant attraction, Chapman et al. (2005) conducted a meta- analysis in the area of applicant attraction, to clarify processes that might be involved in job choice. Chapman et al. (2005) looked at four recruitment outcomes variables. These variables included job pursuit (applicant’s intentions to pursue a job), acceptance intention (likelihood that an applicant would accept a job offer), job choice (likelihood that an applicant would accept a real job offer), and job-organization attraction (applicant’s overall evaluation of the attractiveness of the job/ or organization). Overall results showed that applicant attraction can be predicted by job – organization characteristics, recruiter behaviors, perceptions of the recruiting process, perceived fit, and hiring expectancies. While this research was able to recognize that applicants are attracted to job-organizational characteristics such as firm reputation, Chapman et al. (2005) did not look at theories which could predict attraction such as signaling theory. Firm Reputation Frombrun and Shanley (1990) identify Firm Reputation as a public’s affective evaluation of a firm’s name relative to other firms. This reputation can be very valuable because it can provide information to constituents about investors and potential 8 applicants (Fombrun, 1996; Fombrun & Shanley, 1990). It also affects applicant pools through initial attraction to a company (Gatewood, Gowan & Lautenschlager, 1993; Rynes, 1991). Rynes (1991) argued that firm reputation is the objective of recruitment, and should be the foundation of future research in the area. Rynes (1991) added that understanding what attracts applicants to a firm should be a priority because if top applicants withdraw from the applicant pool the overall utility of the selection system is diminished. Gatewood, Gowan and Lautenschlager (1993) looked at corporate image and recruitment image among groups of students. The intent of the research was to enhance information about variables that influence initial decisions to apply. Measures used to explore firm reputation included reputation ratings from periodical listings such as Fortune 500. Ratings were found for all organizations listed in the 1990 Fortune survey. Findings, from this research were consistent with Rynes’ (1991) conclusions; that image is highly related to potential job applicants' intentions to pursue further contact with a firm. Further analyses show that image is a function of the amount of information an applicant is given on the organization. Overall corporate image was positively related to potential applicants' interaction with the organization, which includes exposure to advertisements, use of products or services, and studying the organization in class. Later research includes Turban, Forret and Hendrickson (1998). This research looked at applicant attraction to firms both before and after recruitment interviews. Hypotheses included replicated hypotheses from Rynes (1991) stating that organizational attributes will have a positive effect on applicant attraction to the firm, as well as new 11 company or the organization as a whole might be like or organizational inferences. For example, Behrend, Baker and Thompson (2009) used signaling theory as a way to see the effects of pro-environmental recruitment messages on job applicants. Behrend et al. (2009) believed that when organizations used pro-environmental messages for recruitment, applicant’s perceptions of the organization would increase or become more positive; which would then increase job pursuit intentions. To measure this effect, Behrend et al. (2009) presented applicants with WebPages containing either a pro- environment statement or not providing a statement at all. Findings from this research showed that organizations that use pro-environmental messages in recruitment receive an increase in applicants that want to apply, and have a more positive perception of the organizations reputation. However, contrary to their hypotheses, they found that the message’s effect on job pursuit intentions were not contingent upon the participant’s own environmental stance. Left unanswered is the impact of negative information about the company’s environmental reputation; i.e., whether applicants are repelled from those companies that do not state environmental information. Another example of organizational inferences is in the study conducted by Lievens and Highhouse (2003). This study looked at difference in attraction when comparing trait inferences (innovativeness or prestige) against job and organizational inferences (pay, bonuses, and benefits). Lievens and Highhouse (2003) also looked at the difference in respondent groups considering both the view of senior college students and employees of a bank. Analyses found at least partial support for all hypotheses; stating main findings that, in considering both respondent groups’ trait inferences about the 12 organization, accounted for more variance over job and organizational attributes. This shows support that information about reputation or prestige has a greater impact on applicant attraction than information about pay, bonuses, or benefits. The second construct that is commonly addressed in research is how the company will treat others, or its co-workers, or referent other signals. Rynes and Miller (1983) used this construct from signaling theory to explain if recruiter behaviors such as how informative recruiters were, would lead to perceptions of how the company treats others. To measure this affect, Rynes and Miller (1983) presented applicants with one of two videotaped mock interviews. Participants where either shown situations in which the recruiter knew a lot of information about the organization, or which stated information about the attractiveness of the job. However, while their first study found this to be true, after repeating the study those results could not be replicated. Again, like the study conducted by Behrend et al. (2009), Rynes and Miller (1983) do provide applicants with negative information about the organization, and they measured it in such as way that results were inconsistent. While this is just a glance, the majority of studies within signaling theory center around these two constructs. A more salient question for applicants may be “how I will be affected if I were to work here”. This construct, or self-referential inferences, suggests that when applicants are considering jobs, they are more interested in signals relating to how they will personally be treated within an organization, more so than signals about what the origination is like as a whole, or how they treat potential co-workers. In other words, when applying for jobs applicants are more concerned about what they will get 13 out of the situation, they are with broad organizational characteristics. To my knowledge, the signals directed to the individual, or self-referential signals have only been reported once; Jones, Willness and Macneil (2009) looked at signaling at the individual level by manipulating online recruitment web pages, by stating their participation in corporate social responsibility (CSR), and seeing how the applicant felt that they would fit in that given organization. Jones, Willness and Macneil (2009) believed that companies stating their engagement in CSR would signal more positively to applicants about how they would be affected if they were to work there. To conduct this research at this new level, applicants were asked to review designated web pages, and then respond to a set of items including questions regarding perceived organizational support. Results provided support stating that when the organization announced engagement in CSR, applicants viewed this as a positive signal about how they would be treated if they worked in the organization. While there has only been one reported case of the construct of self-referential signaling, it was shown to be significant and encouraged future research of this inference type. Arguments used in justifying the use of organizational signals state that the selection procedures that an organization uses can affect the organization’s overall ability to attract applicants. While reasons used in past research to justify the construct of how they treat employees’ state that applicants may take recruiter behaviors such as attentiveness or how informative they are about the organization as signals of the quality of interpersonal relationships, or the nature of supervision that they may encounter when working in the organization (Rynes & Miller, 1983). 16 METHOD Sample Participants were 251 undergraduate students at the University of Wisconsin Oshkosh. Of those, 9 surveys were dropped for large sections of incomplete data, leaving 242 in our sample. Undergraduate students were those enrolled in business or psychology courses. Those enrolled in psychology courses were recruited through the Psychology Participation Pool using Sona Systems, while business students were those in select business courses. Average age of participants was 22 years, with 60.7 % of them being female, and 39.3% being male. Of those 88.8% indicated an ethnicity of Caucasian/White (non-minority) and 9.9% indicated being a minority, the remaining 1.3% did not identify any ethnicity. Sixty-three percent of participants indicated having a major in the business, 7% of participants were education majors, 7% of participants were undeclared in major, and the remaining 25% were from various other majors. The average grade point average (GPA) was 3.05 out of 4.0. Materials Participants were provided with two things. First they were assigned randomly to one of three company profiles. Profiles consisted of approximately one paragraph stating instructions, and depicting the companies’ profile. Next the students received a survey packet. Survey packets consisted of questions regarding applicant opinions based on information provided in the company profile, and demographic questions in which students were expected to circle the answer best representing their response, or consisting 17 of blanks for students to fill in their own response. Surveys took around 20 - 25 minutes to complete. Firm Reputation Firm reputation was manipulated through the creation of company profiles. Three profiles were created and administered to participants at random. Below Table 1 displays all three profiles in how they manipulated firm reputation. Table 1 Company Profile Manipulation of Firm Reputation at All Levels Favorable (High) Moderate Unfavorable (Low) In a survey of alumni conducted in 2009, this company was ranked in the top 25th percentile of companies they'd like to work for. This company has appeared on one or more published lists (e.g., Business Week, Working Women) as one of "the best places to work In a survey of alumni conducted in 2009, this company was ranked around the median of companies they'd like to work for. This company has never appeared on either a "best" or "worst" companies to work for list In a survey of alumni conducted in 2009, this company was ranked in the bottom 25th percentile of companies they'd like to work for. This company has appeared on one or more published lists (e.g., Business Week, Working Women) as one of "the worst places to work Measures Applicant Attraction Applicant attraction is defined as an applicant’s interest in applying for an employment position, and has been measured using a variety of Likert scales in the past. This study used a measure suggested by Rau and Hyland, 2002. The items in this measure were adjusted from past measurements by Cable and Judge, 1994; Honeycutt and Rosen, 1997; Schwoerer and Rosen, 1989. The measure includes the following items; “I would be interested in pursuing employment opportunities with this company,” “I would sign up for a campus interview with this company,” “I would contact this 18 company directly for an interview,” “I would be interested in learning how I can apply for a job within this company,” “This seems like a company that I would personally like to work for”. Subjects rated responses on a 5-point Likert scale ranging from 1 strongly disagree to 5 strongly agree. Cronbach’s alpha for this scale was .94, indicating a high reliability. Organization Signals Signals directed at the organizational level were assessed using inference questions created by Rau and Hyland (2002). This measure was intended to capture the degree to which applicants make inferences about the organization as a whole, and consisted of 10 questions on a 7-point Likert scale (1- strongly disagree; 7- strongly agree) (see Table 2). Cronbach’s alpha for this scale in the current sample was .86. Self-Referential Signals Self-referential signals were adapted using a measure of Perceived Organizational Support (Eisenberger et al, 1986). 10 items, rated on a 7-point Likert scale (1- strongly disagree; 7- strongly agree), were used to create the self- referential signals. Cronbach’s alpha for these items in the current survey was .94. For a full list of items refer to Table 2. Referent Other Signals Signals directed at co-worker support or referent other signals included 9 items related to co-worker attitudes and actions. These items were rated on a 7-point Likert scale (1- strongly disagree; 7- strongly agree), (Cronbach’s α = .94). Please refer to Table 2 for a full list of items. 21 students were allowed to sign up for each session to ensure no disruption during survey completion. Students participating in the research through business courses were provided with the opportunity to participate during a selected class time. Analysis Preliminary analyses were conducted to identify potential confounding variables by examining correlations between dependent variables and demographic variables (see Table 3). Crosstabs were then run to ensure that random assignment to the three company profiles was distributed evenly among the demographic variables (Appendix D). To test for Hypothesis 1, the dependent variable of applicant attraction was created by averaging the five questions of applicant attraction. Hierarchical multiple regression (HMR) was then conducted. In the first step, the covariates or control variables were added. In the second step dummy variables for the high (coded as 1 if the subject saw the high reputation manipulation and zero otherwise) and moderate (coded 1 if the subject saw the high reputation manipulation and zero otherwise) conditions were added to assess the effects of the experimental manipulation. Significant coefficients on these dummy variables would indicate subjects had higher attraction when they saw either the moderate or high reputation conditions as compared to the low condition. A second regression was then run with moderate as the omitted category to assess if the difference between attraction in the high and moderate conditions was significant as well. To test Hypothesis 2, an exploratory factor analysis was conducted. Exploratory factor analysis is a variable reduction technique that identifies dimensions or constructs that underlie measures (Hinkin, 1998). This was intended to show that there are three 22 distinct constructs for which inferences are drawn (Hypothesis 2). For this analysis principal component extractions were made using an orthogonal rotation varimax. Orthogonal rotations were chosen over oblique rotation because it does not allow the factors to be correlated, and keeps them as unrelated to each other as possible (Floyd & Widaman, 1995). Following exploratory factor analysis, a form of confirmatory factor analysis called multitrait-method analysis was conducted to double check that dimensions indicated by the exploratory factor analysis were correct. The advantage of running the confirmatory factor analysis in addition to the initial exploratory analysis is that it looks at the goodness of fit within items to the data where the exploratory factor analysis does not. Confirmatory factor analysis uses maximum likelihood estimation (Floyd & Widaman, 1995). Upon completion of both factor analyses, reliability analyses were run to check for Cronbach’s alpha, and indices were then created from the categories specified. To test Hypothesis 3-5, these indices served as dependent variables in a set of hierarchical multiple regressions (HMR) to examine the effects of the conditions on each type of inference. Control variables were added in the first step, and dummy variables for the high and moderate conditions were added in the second step to assess the effects of the experimental manipulation. A second regression was run for each dependent variable using moderate as the omitted category to assess if the difference in inferences between moderate and high was significant as well. Finally, as there is no test for Hypothesis 6 that will directly assess whether the variables explain one dependent variable better than another, I first examined the 23 difference between total variance explained by the equations testing Hypothesis 3-5 to determine whether a practically significant difference existed. Next I conducted another HMR to see if variance accounted for by the high and moderate conditions was still significant on self-referential/ referent other inferences even after controlling for organizational inferences and covariates. This analysis was done by first accounting for covariates, next accounting for organizational signals, and finally adding in dummy variables. A significant change in R² would indicate that, even after controlling for covariates and the effects of organizational inferences, firm reputation had a significant influence on self referential / referent other inferences. Finally, I examined whether the high condition was more likely to be associated with positive self-referent inferences or organizational inferences. To do this, I conducted a third analysis by stacking the mean organizational and mean self-referential / referent other variables and regressing them on gender, and major in business, a dummy variable for high firm reputation condition, a dummy variable coded 1 if the dependent variable was a self-referential / referent other inference (and zero if it was an organizational inference), and the interaction between the high condition and this dummy variable. The regression equation is stated as: INFERENCES = B0 + B1 GENDER + B2 BUS + B3 HIGH + B4 SRRO + B5 HIGH * SRRO Where HIGH = dummy coded 1 if high condition and 0 if not SRRO= dummy coded 1 if the dependent variable was a self-referential/ referent other inference. 26 Results showed that 37% of the variance was explained by independent variables, F (6,210) = 20.80, p < .05. Thus Hypothesis 1 is supported (Table 4). Table 4 Regression Table of Attraction for High and Low Firm Reputation (n = 217) Independent Variable Step 1 b(1) β(2) Step 2 b(3) β(4) Age .01 (.02) .03 .00 (.01) .01 Gender -.06 (.15) -.03 -.18 (.12) .12 Race .00 (.25) .00 -.03 (.20) .19 COB .26 (.16) .11 .15 (.13) .13 High .31 (.14) .14* Low -1.13 (.14) .14** Constant 2.72 (.39) 3.23 (.32) R² .02 .37** Adjusted R² -.00 .36** Change in R² .36** Notes: Standard errors are in parentheses. Race condition is coded as 0= non minority, 1= minority. Gender condition is coded 0= male, 1= female. COB condition is coded 0= non COB, 1= COB. High condition is coded 0= all other conditions, 1= high condition. Low condition is coded 0= all other conditions, 1= low condition. *p<.05 **p<.01 Results for Hypothesis 2 showed that the 29 inference items yielded a 4 factor structure. These 4 factors were found to have eigenvalues > 1.0. Further examination of eigenvalues and the scree plot indicated retention of 3 factors. To ensure these results, further analysis consisting of a confirmatory factor analysis was conducted. In the analysis, factor 4 was poorly defined, accounting for only four percent of the variance and consisted of only two items, both of which were the only two items having reverse coding. “This company would fail to notice, even if co-workers did their best job possible,” and “This company would show very little concern for co-workers.” Being that these were the only two reverse coded items in the data set it is believed that there was response bias; meaning that participants did not read closely enough to see that these items were to be answered in reverse. 27 For the three factors identified, reliability of subscales using a Cronbach’s alpha coefficient was then calculated. Cronbach’s Alpha is a test for reliability, specifically internal consistency. Alpha coefficients of >.7 are considered sufficient for scale reliability, and those closer to 1.0 are highly reliable (Hinkin, 1998; Nunnally & Bernstein, 1994). Cronbach’s alpha for all signaling questions included in the three factors was .96 showing high reliability. The three factor solution proved to be more satisfying in its interpretability. The three factors accounted for 63.81% of the total variance among items. Self- referential / referent other resulted in 47.41 % of the variance, organizational with 11.38 % of the variance, and 5.01% of the variance was from diversity items. In order to fully interpret the patterns of questions in each factor, a minimum absolute value of .40 for a factor pattern coefficient was selected, with a minimum absolute value of .30 for cross loading (Ford et al., 1986; Floyd & Widaman, 1995). Twenty seven of the questions formed the three factors; one of the questions did not load on any of the three selected factors. Factor loadings for all items are available in Table 5. 28 Table 5 Summary of Exploratory Factor Analysis Results for Signaling Likelihood Estimation (N = 242) Factor Loadings Item SRRO Organization Diversity Reverse code 1)This company would be willing to extend itself in order to help me perform my job to the best of my ability .84 .20 .14 .04 2)This company would care about my opinions .82 .17 .19 .11 3)This company would care about my general satisfaction at work .81 .16 .16 .23 4)This company would be complementary of co- worker accomplishment at work .80 .24 .08 .29 5) This company would care about co-worker opinions .79 .04 .09 .24 6) This company would really care about their co- worker’s well-being .78 .14 .20 .31* 7) This company would forgive an honest mistake on my part .78 .02 .18 -.09 8) This company would be willing to help me when I need a special favor .78 .07 .11 -.06 9) This company would really care about my well- being .78 .16 .20 .15 10)This company would care about co-worker general satisfaction at work .77 .10 .10 .29 11) This company would be willing to offer assistance to help co-workers perform their job to the best of their ability .77 .21 .14 .28 12) This company would help co-workers if they has a problem .76 .18 .15 .29 13)This company would be supportive of co-worker goals and values .76 .24 .20 .23 14) This company would understand a long absence due to my illness .73 -.02 .23 -.14 15) This company would strongly consider my goals and values .72 .26 .17 .24 16)This company would value my contribution to its well-being .71 .31* .14 .23 17)This company would understand if I were unable to finish a task on time .65 -.10 .34* -.31* 18) This company expects a lot from its employees .01 .84 .03 -.02 19) This company is aggressive -.03 .76 .00 -.08 20) This company provides challenging work .12 .74 .10 -.04 21) This company supports risk-taking .13 .73 .18 .10 22) This company is competitive .35 .72 .14 .26 23) This company is innovative .22 .69 .17 .11 24) This company provides opportunities for advancement .39* .55 .30* .11 25) This company values diversity .18 .18 .79 .18 26) This company values cultural differences .28 .29 .77 .04 27) This company provides equal opportunities for all .37* .17 .71 .07 28) This company would fail to notice, even if co- workers did their best job possible .19 .01 .10 .79 29) This company would show very little concern for co-workers .48* .07 .15 .65 Eigenvalues 13.75 3.3 1.46 1.26 % of Variance 47.41 11.38 5.01 4.34 Note: Bolded numbers indicate significance of loadings, * indicates cross loading 31 Table 7 Regression Table of Self - Referential / Referent Other Signaling for High and Low Firm Reputation (n = 220) Independent Variable Step 1 b(1) β(2) Step 2 b(3) β(4) Gender .20 (.14) .09 .08 (.11) .04 COB -.11 (.15) -.05 -.23 (.11) -.11* High .49 (.13) .23** Low -1.09 (.13) -.51** Constant 4.01 (.16) 4.38 (.14) R² .01 .44** Adjusted R² .00 .43** Change in R² .43** Note: Standard errors are in parentheses. Gender condition is coded 0= male, 1= female. COB condition is coded 0= non COB, 1= COB. High condition is coded 0= all other conditions, 1= high condition. Low condition is coded 0= all other conditions, 1= low condition. *p<.05 **p<.01 In the first test for Hypothesis 6 the comparison of explained variance between the organizational inference equation (R ² = .14, p <.05) and the self-referential / referent other equation (R² = .44) shows a difference of .30. Thus, it would appear that the variables do a better job of explaining self-referential / referent other inferences than organizational inferences and that this difference is practically significant. However, since the two equations have different dependent variables, I cannot conclude that the difference in variance is statistically significant using standard R² comparisons. Thus, I tested the difference by including organizational inferences as an explanatory variable in a hierarchical regression model predicting self-referential / referent other inferences. The results showed a significant coefficient for both the high (b = 1.34, p <.05), and moderate conditions (b = 1.03, p <.05) even after controlling for the effects of organizational inferences. The difference between high and moderate conditions was also statistically significant (b = .34, p<.05). Results showed that 53% of 32 the variance was explained by the independent variables, F (6, 210) = 40.00, p < .05 (Table 8). These results support Hypothesis 6. Table 8 Regression Table of Self - Referential/ Referent Other Withholding Organizational Inferences for High and Low Firm Reputation (n = 210) Independent Variable Step 1 b(1) β(2) Step 2 b(3) β(4) Step 3 b(5) β (6) Gender .19 (.14) .09 .27 (.13) .13* .14 (.10) .07 COB -.10 (.15) -.05 -.02 (.13) -.01 -.16 (.11) -.07 Organizational .56 (.07) .07** .35 (.06) .31** Low -1.03 (.12) -.48** High .31 (.13) .14* Constant 4.01 (.16) 1.64 (.32) 2.94 (.28) R² .01 .25** .53** Adjusted R² -.00 .23** .52** Change in R² .24** .29** Note: Standard errors are in parentheses. Gender condition is coded 0= male, 1= female. COB condition is coded 0= non COB, 1= COB. High condition is coded 0= all other conditions, 1= high condition. Low condition is coded 0= all other conditions, 1= low condition. *p<.05 **p<.01 Finally, results from the third analysis also showed support for Hypothesis 6. Overall participants who saw the high reputation condition responded higher to both organizational and self-referential / referent other inferences (b = .67, p < .05). In addition, there was a statistically significant interaction between the high condition and making individual inferences, showing that positive reputation has more of an effect on inferences about self-referential / referent other than it does on organizational inferences (b = .39, p <.05). As a side note, there was also evidence that in looking at those who did not receive a high firm reputation the reverse effect was suggested. Data suggests that when applicants were presented with firm reputations that were not high they responded 33 lower on inferences about self-referential / referent other than they did to the organizational inferences. This data is also consistent with Hypothesis 6. Table 9 Regression Table of interaction of Self Referential/ Referent and Organizational Inferences for High Firm Reputation (n = 434) Independent Variable β SE Gender -.00 .09 COB -.20* .09 High .67** .13 Individual -.16 .10 Interaction .39** .18 Constant 4.00 .11 R² .19 Adjusted R² .18 Notes: *p<.05 **p<.01 36 Hypothesis 3 suggested that applicants would make inferences about the organization when presented with information about company reputation. Results for this hypothesis showed support; suggesting that participants were able to make inferences about the organization based on the firm reputation reported in the company profile. This hypothesis is consistent with information that has been presented in past literature, and confirms that use of this inference in future research should be continued. To assess hypothesis 4 or 5, the combination or self-referential and referent other inferences was created. This combined hypothesis suggested that applicants would make inferences about how they and other co-workers would be treated based on information of firm reputation. Results showed support for hypothesis 4/5; suggesting that participants did make inferences about how employees would be treated at the company when presented with information about the firm’s reputation. This hypothesis points out two interesting conclusions. One is that there is a distinct difference between organizational signals and self-referential / referent other signals that can be made when presented with information about a firm’s reputation. The second conclusion is that because of this finding we may be able to help to clarify why there have been so many discrepancies in results of past research (see Appendix C for a table depicting past literature in signaling theory). Depending on what questions applicants are presented with there could be distinct differences in the type of inferences that they make. Past researchers may have confused or mixed inference types together, and because of this their results may be skewed from other research in the area. 37 Hypothesis 6 suggested that firm reputation would have a stronger effect on self- referential inferences than on either organizational inferences or referent other inferences. Results of the first analysis showed evidence for support of this hypothesis, suggesting that participants are more likely to make self-referential / referent other inferences at a variance of 44% than organizational inferences with a variance of 14%, and this difference is of practical significance at a .30 difference in variance between inference types. The second analysis conducted also supported Hypothesis 6 in that firm reputation had a positive influence on self-referent / referent-other inferences, even after controlling for organizational inferences and covariates. This would suggest that the positive effects of firm reputation on self-referential / referent-other inferences are independent of the effects on organizational inferences. The third analysis was also consistent with Hypothesis 6, showing that positive reputation has more or an effect on self-referential inferences than on organizational inferences, and that when not shown positive firm reputation information, applicants responded lower to self-referential / referent other inferences than to organizational inferences. This hypothesis points to the conclusion that both types of signals are important to applicants, and makes a difference in how they answer questions about the organization. Self-referential inferences are more sensitive to firm reputation than organizational inferences. Conclusions and Future Research This research has several implications for research and theory on signaling in applicant attraction. First, the study shows that there are distinct differences between, 38 self-referential / referent other and organizational inferences. Second, self-referential/ referent other inferences appear to be more sensitive to organizational reputation. Thus, while research should continue to explore the effects of organizational inferences in applicant signaling, it should also take into account self-referential/referent other signals. This research shows evidence that these signals may have more of an effect on applicants than organizational signals, and that the inferences that applicants make about how the company will treat its employees will have a larger impact on their attraction to the organization than do inferences about the organization as a whole. This study did not find a distinction between self-referential and referent other inferences. Future research may wish to examine the constructs to ensure that they are indistinguishable. Another intriguing avenue for research in applicant attraction would be to examine the role of individual differences in determining both types of inferences that are made from various organizational policies. Personality traits such as materialism, locus of control, or extroversion may in general make some individuals more (or less) likely to make self-referential / referent other inferences than organizational inferences. For example, those who are highly extroverted tend to be very assertive, self-confident, and leader-like (Cascio & Aguinis, 2005). Extroverted individuals may see themselves as distinctly different than those that they work with, and perhaps further investigation would find that extroverts are more likely to make self-referential inferences, while those who are lower in extroversion may not see self-referential and referent other inferences as distinctly different. Similarly, there may be an interaction between policies and individual 41 Overall, this research points to an important missing variable in the research on recruitment. By finding a distinct difference between organizational inferences and inferences of self-referential/referent other, I have provided a possible explanation for weak results of past research looking at inferences made in the recruitment process. Not only does firm reputation matter in attraction to the organization, but it signals perceptions about the organization as a whole, and it also creates inferences about how those who work there will be treated. Future researchers should do more to understand the difference between the two inference types. From a practical standpoint, practitioners in the area of recruitment should be made aware of the different types of inferences that can be made by applicants, and understand the types of signals that they may be sending to applicants through recruitment processes. More research is needed to guide practitioners in designing organizational and recruitment policies that send the signals they intend. 42 APPENDIX A Full Survey Questions 43 Recruitment Survey The following survey will ask you to respond to a series of questions after being presented with a company profile. There are no right or wrong answers. Please answer all items as honestly as possible, and not how you think you are expected to answer. Most of the questions ask you to indicate whether you agree or disagree with a statement. For each of those questions, circle the number on the scale that best represents whether you agree or disagree with the statement. Please give these questions your full attention, if you do not have an opinion about a particular statement, circle the middle number (neither agree nor disagree). Other questions ask you to either fill in a blank or check your answer. If you don’t know the answer to these questions write “I don’t know”. The first part of the questionnaire is directly related to the company profile. The second part asks a few demographic items. Finally, the survey ends with a few questions about your own values, preferences, and beliefs. Please turn the page and begin the survey. 46 Please use the following scale to respond to items below. Begin each question with: This company would… St ro ng ly D isa gr ee D isa gr ee So m ew ha t D isa gr ee N ei th er A gr ee n or D isa gr ee So m ew ha t A gr ee A gr ee St ro ng ly A gr ee 25. value my contribution to its well-being 1 2 3 4 5 6 7 26. strongly consider my goals and values 1 2 3 4 5 6 7 27. understand a long absence due to my illness 1 2 3 4 5 6 7 28. really care about my well- being 1 2 3 4 5 6 7 29. be willing to extend itself in order to help me perform my job to the best of my ability 1 2 3 4 5 6 7 30. forgive an honest mistake on my part 1 2 3 4 5 6 7 31. be willing to help me when I need a special favor 1 2 3 4 5 6 7 32. care about my general satisfaction at work 1 2 3 4 5 6 7 33. care about my opinions 1 2 3 4 5 6 7 34. understand if I were unable to finish a task on time 1 2 3 4 5 6 7 Please use the following scale to respond to items below. MANIPULATION CHECKS St ro ng ly D isa gr ee D isa gr ee So m ew ha t D isa gr ee N ei th er A gr ee n or D isa gr ee So m ew ha t A gr ee A gr ee St ro ng ly A gr ee 35. This company is a prestigious company 1 2 3 4 5 6 7 36. This company is a reputable company 1 2 3 4 5 6 7 37. This is a high-status company 1 2 3 4 5 6 7 38. This company is financially successful 1 2 3 4 5 6 7 47 39. This company has a negative reputation 1 2 3 4 5 6 7 40. This is a low-status company 1 2 3 4 5 6 7 The following questions pertain to your interest in employment at this company. Please state whether you “would” or “would not”, and complete the statement. I would/would not be interested in pursuing employment opportunities with this company because: _______________________________________________________________________ I would /would not like to work for this company because: ______________________________________________________________________ I would/ would not feel like a valued employee at this company: ________________________________________________________________________ The following questions assess how much you remember from the scenario. Please fill in the blanks. If you do not remember the answer to the question, please write “I don’t know”. OPEN-ENDED “ATTENTION” CHECKS What is this company’s primary industry? ________________________________________________________________________ Where is this company located? ________________________________________________________________________ Does this company state financial information? ________________________________________________________________________ OPEN-ENDED MANIPULATION CHECK Was there a positive or negative firm reputation stated in the ad? 48 DEMOGRAPHIC QUESTIONS While we do not ask you to identify yourself by name on this survey, we would like you to answer the following demographic questions. Please provide the following information about yourself: 1. Your age: _____ 2. Your current marital status: Single____ Married____ Divorced____ Other(Please Specify)___________________ 3. Your Gender: Female ____ Male ____ 4. Your ethnicity/race:____________________________________________________ 5. The degree that you are currently working towards (e.g., BA, BS, MA, MS): __________ 6. Your current Major: _______________________________________ 7. Your expected graduation date: ________________________________ 8. Your cumulative undergraduate GPA (if applicable):__________________ 9. Your cumulative graduate GPA (if applicable): ______________________ 10. Please list any college degrees which you hold and your major: DEGREE(s) MAJOR(s) DATE RECEIVED __________ ______________________________________ _________________ __________ ______________________________________ _________________ __________ ______________________________________ _________________ 11. Do you currently have a job related to your major? No____ Yes, part-time____ Yes, temporary or internship____ Yes, Full-time_____ 12. Are you currently looking for a job related to your major? Yes___ No_____ 51 APPENDIX C Table of Past Literature on Signaling 52 Table C-1 Table of Past Literature on Signaling Author Title Type of signaling Pos/mod/neg signals Manipulation type Rynes, Bretz and Gerhart (1991) The importance of recruitment in job choice: A different way of looking Org Pos or Neg Time delays Behrend, Baker and Thompson (2009) Effects of pro- environmental recruiting messages: The role of organizational reputation Org Pos or none Environmental messages Turban and Cable (2003) Firm reputation and applicant pool characteristics Org Pos or none Job posting from actual company, included firm reputation Levins and Highhouse (2003) The relation of instrumental and symbolic attributes to a company’s attractiveness as an employer Org Pos or none Trait inference and org inferences Turban and Greening (1996) Corporate social perform and org attractiveness to prospective emp Org All levels Company profile stating corporate social performance & reputation Rynes and Miller (1983) Recruiter and job inferences on candidates for Employment Co-worker (Referent other) Pos or none Amount of information the recruiter knew about the organization Jones, Willness and Macneil (2009) Corporate social responsibility, recruitment testing p-o fit, and signaling mechanisms Individual (Self- referential) Pos or None Corporate social responsibility 53 APPENDIX D Table of Crosstabs for Conditions and Variables 56 Cober, R. 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