Tether or Stepping Stone? The Relationship between Perceived External Reputation and Collective Voluntary Turnover Rates

Abstract

Signaling theory suggests that resources such as firm reputation can send multiple signals that create dual pressures on stakeholders. These tensions are apparent when examining the relationship between a firm’s reputation and the collective voluntary turnover rates it experiences. On the one hand, a favorable reputation may tether employees to the firm due to the perceived desirability of working for a reputable company, resulting in lower voluntary turnover rates. On the other hand, a favorable reputation may make employees believe they are more marketable and thus may serve as a stepping stone relating to higher voluntary turnover rates. The purpose of this study is to investigate whether and when reputation acts as a signal of desirability or a signal of ease of movement in predicting collective voluntary turnover rates. We find some evidence for an overall tethering effect for more reputable firms. In addition, our findings demonstrate that reputation is more likely to result in stepping stone effects in certain signaling environments including when firms are in more munificent industries, are younger, and have higher pay levels. Tethering effects are observed when firms are in less munificent industries, are older, and have lower pay levels.

Keywords

collective voluntary turnover reputation signaling theory turnover

Introduction

“One can survive everything, nowadays, except death, and live down everything except a good reputation.” Oscar Wilde

Organizational reputation exerts dual, and often opposing, pressures on organizations and employees (Petkova, Wadhwa, Yao, & Jain, 2014). As a result, reputation can create conflicting outcomes for firms, leading to interesting tensions and seemingly-paradoxical contradictions. In much of the literature, a favorable reputation is seen as desirable, leading to benefits such as higher financial performance and better employment outcomes (Deephouse, 2000; Roberts & Dowling, 2002; Turban & Cable, 2003). Yet, in some cases, the effects of a favorable reputation are less positive, such as making firms risk-averse and creating unrealistically high expectations (Petkova et al., 2014; Zorn, Roper, & Richardson, 2014). Reputation is inherently a reflection of how the organization is viewed and exists within a larger social system, and as such can exert multiple signals with different meanings. In this study, we use signaling theory to examine the different signals that insider perceptions of reputation send in relation to one particular area of importance for firms—collective voluntary turnover rates—in order to answer the question of whether and why employees may leave firms with good reputations.

Voluntary turnover is a critical issue for firms, as the literature has found a significant negative relationship between firms’ voluntary turnover rates and their performance (Park & Shaw, 2013). The voluntary turnover literature suggests that perceptions of mobility most closely relate to the tradeoffs surrounding (1) desirability of staying at the current workplace and (2) ease of movement to new job opportunities (Campbell, Coff, & Kryscynski, 2012; Heavey, Holwerda, & Hausknecht, 2013; March & Simon, 1958). When considering collective voluntary turnover rates, however, reputation can be interpreted as a signal of collective perceptions of both desirability (keeping people in the firm) and a signal of ease of movement (leading individuals to leave). This seems to suggest two alternative relationships between a firm’s reputation and the voluntary turnover rates it experiences.

On the one hand, studies have indicated that a more favorable reputation makes a company more attractive (Gatewood, Gowan, & Lautenschlager, 1993; Turban & Cable, 2003) and increases the satisfaction individuals feel and their desire to remain working for the organization (Dutton, Dukerich, & Harquail, 1994; Herrbach, Mignonac, & Gatignon, 2004; Smidts, Pruyn, & Van Riel, 2001). This indicates that reputation can be a signal of collective desirability, and may be thought of as a “tether” that keeps individuals connected to the firm, relating to lower voluntary turnover rates. On the other hand, other research indicates that employees from firms with favorable reputations are sought after (Rider, 2012; Zuckerman, Kim, Ukanwa, & von Rittmann, 2003) and that employees of these firms may believe that they have greater job alternatives (Heavey et al., 2013; March & Simon, 1958). As such, a favorable reputation may increase perceptions of demand and be considered a signal of collective ease of movement, serving as a “stepping stone” and relating to higher voluntary turnover rates for firms with favorable reputations. Thus, the purpose of this study is to unpack this paradox to better understand whether and when reputation serves more predominantly as a tether or as a stepping stone, resulting in systematic variance in voluntary turnover rates for firms.

By building theory linking a firm’s voluntary turnover rates with perceptions of how favorably it is viewed, we contribute to the literature in three key ways. First, we examine a theoretically relevant antecedent of collective voluntary turnover rates—firm reputation (Connelly, Certo, Ireland, & Reutzel, 2011). Despite the increasing awareness that collective turnover has important and often negative effects on firms (e.g., Park & Shaw, 2013), Hausknecht and Trevor (2011) indicate that collective turnover research “lacks a rigorous analysis of its major antecedents” (p. 353). Second, we empirically test competing hypotheses to address an unresolved theoretical tension in the literature between two signals that make opposite predictions about the relationship between a firm’s reputation and the voluntary turnover rates it experiences. Much of the reputation literature implies that a favorable reputation will keep employees tethered to the firm (Dutton et al., 1994; Herrbach et al., 2004; Smidts et al., 2001). We use signaling theory to argue that reputation might instead serve as a stepping stone to other job opportunities. Third, we investigate contextual factors that may influence when reputation is more likely to be a signal of collective desirability or a signal of ease of movement. Extant research suggests the importance of the signaling environment (Stevens & Makarius, 2015; Stevens, Makarius, & Mukherjee, 2015), yet Connelly and colleagues (2011) indicate that “the signaling environment on the whole is an under-researched aspect of signaling theory” (p. 62). By addressing this limitation in the literature, we examine reputation perceptions within the larger context in which they exist (Seidl & Whittington, 2014; Tsoukas & Dooley, 2011).

We test our ideas using collective turnover data from 137 companies in Finland and find some evidence that all else equal, firms with better reputations experience a tethering effect. However, we also find that it is necessary to consider contextual factors related to the signaling environment (industry munificence, firm age, and pay levels) to fully understand the relationship between a firm’s reputation and the voluntary turnover rates it experiences. In doing so, we find some situations where reputation is more likely to act as a signal of ease of movement, leading to stepping stone effects, and other situations where reputation acts as a signal of desirability, leading to tethering effects.

Firm Reputation: Is it a Tether or a Stepping Stone?

The literature on voluntary turnover has focused primarily on an individual’s choice to remain at an organization or not (Hom, Mitchell, Lee, & Griffeth, 2012). Yet, the importance of voluntary turnover rates at the collective level is becoming increasingly evident (Shaw, 2011). Collective turnover is the “aggregate levels of employee departures that occur within groups, work units, or organizations” (Hausknecht & Trevor, 2011). Examining voluntary turnover rates at the organizational level, rather than individual turnover intentions, is important as it allows an examination of actual firm-level outcomes rather than individuals’ conjecture about the future. This is important, as there are times when individuals might want to leave but are not able to do so. The research on collective turnover generally highlights negative outcomes such as lower productivity (Campbell, Ganco, Franco, & Agarwal, 2012; Hausknecht & Trevor, 2011; Park & Shaw, 2013). Glebbeek and Bax (2004), however, indicate that “human resource managers have to familiarize themselves with the determinants of turnover before they can estimate its effects” (p. 279). Thus, there is a need to further examine organization-level factors that influence collective voluntary turnover rates. Extant research suggests that the way a firm is perceived by others—its reputation (Carmeli, 2005; Dutton et al., 1994; Shenkar & Yuchtman-Yaar, 1997; Zuckerman et al., 2003) may be important. Yet, the literature is inconsistent about how exactly reputation may relate to voluntary turnover rates experienced by such firms.

In this study, we focus on the perceived external reputation of the work environment.¹ Helm (2013) defines perceived external reputation as “organizational insiders’ perceptions of organizational outsiders’ views of the reputation of the organization” (p. 543). More specifically, we study one specific aspect of reputation: a firm’s “work environment”, which encompasses an organization’s overall consideration for people including leaders, employees, and responsibility to society. Companies with favorable work environments are not only good places to work but also have good employees, vision, and concern for the community around them. Employers aspire to be known for their work environment to attract talent, customers, and other important resources that will promote excellence and success (Cable & Turban, 2003; Dutton et al., 1994; Turban & Cable, 2003). Consistent with the idea of reputation as a signal, we follow the advice of Connelly et al. (2011) and “distinguish between high-quality and low quality firms, but … note that firms reside on a continuum and not a dichotomy” (p. 59). In other words, firms vary on the degree to which their reputation is favorable or unfavorable—reputation is not simply a binary construct.

Signaling theory was originally applied to the job market to look at the signals used in the application and selection process (Spence, 1973). Yet, signals remain salient even after employees join a firm, and likely influence patterns in aggregate employee movement out of the firm as well. Reputation is one of the most common signals, or “visible organizational characteristics used to assess unobservable qualities” (Connelly et al., 2011). Perceived external reputation is important as a signal because (1) it provides information about what to expect in the future and (2) because it provides impressions of familiarity and favorability (Lange, Lee, & Dai, 2011). First, a favorable reputation increases collective desirability because knowing that others have a favorable impression of your workplace provides a sense of stability and reduces uncertainty about the future for employees working in that company. However, it also increases ease of movement perceptions as employees might believe they are more marketable as others know what to expect from a firm with a favorable reputation. Second, by providing impressions of familiarity and favorability, perceived external reputation also enhances collective desirability by basking in the reflected glory of how others view the firm. Yet, it builds collective perceptions of ease of movement as well because believing that others have a favorable impression of the firm may make job alternatives seem easier to attain. Importantly, however, the two aspects of reputation—collective desirability and collective ease of movement—could have different impact on voluntary turnover rates.

Reputation as a tether

In the context of signaling theory, a signal refers to an informational cue (Spence, 2001). Perceived external reputation may be a signal of collective desirability because it provides information to organizational members on how the firm looks to others, which is then reflected in how they themselves are seen. Since organizational affiliation confers social status on members of the organization (Dutton & Dukerich, 1991), employees can experience a more positive self-image by affiliating themselves with a firm that is viewed favorably with respect to how it treats people inside and outside of the firm (Ashforth & Mael, 1989; Cable & Turban, 2003; Dutton et al., 1994).

Previous studies have indicated that employees use the social standing of their organization in assessing themselves, and bask in the reflected glory of being associated with a firm with a favorable reputation (Cialdini et al., 1976; Shenkar & Yuchtman-Yaar, 1997).When an organization is viewed in a positive light, employees as a whole tend to have enhanced self-concepts and a greater desire to remain in the organization (Carmeli, 2005; Hogg, Abrams, Otten, & Hinkle, 2004; Tajfel & Turner, 1979). Because reputation provides information about how employees look to others, employees may be less willing to sacrifice this perception (Collins & Kanar, 2014) and are more likely to stay. Conversely, firms with less favorable reputations would provide less positive information to employees on how they look to others, which would likely lower collective desirability and enhance the likelihood that employees leave. Thus, because a favorable reputation may be a signal of collective desirability of an organization for employees, lower voluntary turnover rates may result.

Hypothesis 1: Reputation will be negatively related to voluntary turnover rates.

Reputation as a stepping stone

Alternatively, perceived external reputation can act as a signal of collective ease of movement, suggesting that firms with more favorable reputations may be used as stepping stones, relating to greater voluntary turnover rates. A belief that a favorable reputation might act as a signal to other organizations that these employees are valuable may make them think they are more marketable to other organizations. Prior employment affiliations are suggested to signal the quality of employees (Burton, Sorensen, & Beckman, 2002; Higgins & Gulati, 2003; Rider, 2012) and are often considered in employment decisions (Zuckerman et al., 2003). If the perceived external reputation suggests that others view the firm—and, by association, its employees—positively, then that firm’s employees may believe that they have more opportunities to move to other organizations (Molloy & Barney, 2015; Shenkar & Yuchtman-Yaar, 1997; Trevor, 2001).

Both the decision to join an organization and the decision to continue with the organization reflect a comparative net benefit assessment (Bernard, 1938; Holtom & Inderrieden, 2006; Lee, Mitchell, & Mitchell, 1994). Presented with different employment scenarios, employees consciously choose whether or not they will remain where they are or move on to somewhere else. In one study that looked at the determinants of turnover, results indicated that high turnover intentions can co-exist with relatively high levels of job satisfaction, job security, advancement opportunities, firm pride, and good perceived labor market opportunities (Sousa-Poza & Henneberger, 2004). These results suggest that even individuals who are happy with their job and proud to be a member of their organization may not remain with the company if opportunity arises elsewhere. Conversely, employees working in organizations with less favorable reputations may want to leave, but may have less of an opportunity to do so. Indeed, research has demonstrated that intentions typically share at most 25% of the turnover variance in organizations (Allen, Weeks, & Moffitt, 2005; Hom et al., 2012). Thus, because perceived external reputation may serve as a signal of collective ease of movement, it may act as a stepping stone which manifests as greater collective voluntary turnover rates in more reputable organizations.

Hypothesis 1alt: Reputation will be positively related to voluntary turnover rates.

The Moderating Role of the Signaling Environment

The competing hypotheses proposed above underscore the paradoxical nature of reputation—signaling theory presents reasonable arguments for why reputation might act as a tether or as a stepping stone. However, despite the fact that these determinants of collective turnover do not happen without consideration of the surrounding environment, Johns (2006) indicates that “research on employee turnover … illustrates a frequent lack of concern with context” (p. 390). With respect to the relationship between reputation and turnover, prior research suggests that, in general, tethering effects may be more constant since employees find reputable firms desirable to work for, regardless of the context (Gatewood et al., 1993; Herrbach et al., 2004; Turban & Cable, 2003). On the other hand, perceptions of ease of movement are quite complex and thus the strength of reputation as a signal of ease of movement may depend on the situation (Direnzo & Greenhaus, 2011; Kirschenbaum & Mano-Negrin, 1999; Steel, 2004). Specifically, we suggest that in some contexts, employees may be more likely to act upon perceived ease of movement opportunities and leave companies with a favorable reputation, whereas in other situations they will be less likely to do so. This leads to the question of what type of contexts might tip the balance, resulting in stepping stone effects outweighing tethering effects, and vice versa?

Signaling theory indicates that a better understanding of how signals interact with their environment is needed to answer such questions (Connelly et al., 2011; Park & Mezias, 2005). Understanding signals within their social contexts may help address the question of when stepping stone effects might supersede or be superseded by tethering effects. The strength of reputation as a signal of ease of movement in different signaling environments may vary because of perceived opportunities of employability (Direnzo & Greenhaus, 2011; Trevor, 2001). Conclusions about perceived employment opportunities are made through a process of selective attention on some aspects of the context more so than others. Employees focus on aspects of the context that are perceived to have a “direct bearing on their ability to find replacement employment” (Steel, 2004).

Three salient aspects of the signaling environment may be affected by context include (1) receiver interpretation, (2) receiver attention, and (3) signal consistency (Connelly et al., 2011). Specifically, we predict that reputation is likely to be a stronger signal of ease of movement in companies (1) in munificent industries, (2) that are younger, and (3) that have higher pay levels, because of the perceived opportunities associated with those contexts. This will result in a positive relationship between reputation and voluntary turnover rates in these cases. Conversely, we predict that reputation is likely to be a weaker signal of ease of movement in companies (1) in less munificent industries, (2) that are older, and (3) that have lower pay levels, resulting in a negative relationship between reputation and voluntary turnover rates due to the stronger influence of reputation as a signal of desirability in these situations. Thus, based on signaling theory we expect these environmental factors to have a disordinal, or crossover, moderating effect (Cohen, Cohen, West, & Aiken, 2003; Marsh, Hau, Wen, Nagengast, & Morin, 2013) on the relationship between firms’ reputation and their voluntary turnover rates. We explain our logic and develop moderating hypotheses below.

Industry munificence and receiver interpretation

Signaling theory suggests that receiver interpretation, or the weight and importance of a signal, increases when the signal provides more valuable information (Higgins & Gulati, 2006; Stuart, Hoang, Hybels, Stuart, & Hybels, 1999). Signaling theory indicates that an important part of the signaling environment is the firm’s industry environment, as industries vary in their attributes (Richard, Murthi, & Ismail, 2007; Sanders & Boivie, 2004). One important attribute of a firm’s industry environment is munificence, or “the growth rates of an industry in which a firm operates” (Richard et al., 2007). Depending on the level of munificence in an industry, we expect reputation’s importance as a source of information and the likelihood that it is leveraged as a means to move to new opportunities to vary (Connelly et al., 2011).

Industries that are more munificent tend to have more options available (Cyert & March, 1992; March, 1991; Richard et al., 2007). Thus, perceptions of job opportunities may be greater in these environments as growth provides information on ease of movement. For example, Cappelli (1999) suggested that employers will favor hiring ready-skilled employees at market rates instead of investing in training in markets and industries experiencing rapid change. Thus, we expect that a more favorable reputation will be a greater signal of ease of movement and increase the probability that employees will feel they can successfully obtain alternative employment for firms in industries that are more munificent. Firms with a favorable reputation in munificent industries are more likely to be treated as a stepping stone by their employees, relating to higher voluntary turnover rates because of the increased value of reputation under conditions of greater market opportunities.

In contrast, employees at organizations in industries that are less munificent will have fewer opportunities for mobility. Although individuals in these signaling environments may want to move, they are less likely to have the external options available to do so. Thus, we expect reputation’s value as a signal of desirability to outweigh its strength as a signal of ease of movement, resulting in tethering effects in less munificent industries.

Hypothesis 2: The relationship between reputation and collective voluntary turnover rates will be moderated by industry munificence such that the relationship will be positive for those organizations in more munificent industries while the relationship will be negative for those in less munificent industries.

Firm age and receiver attention

Signaling theory suggests that receiver attention, or the extent to which receivers vigilantly scan the signaling environment, differs depending on the information asymmetry of the context (Connelly et al., 2011). Signals tend to have greater strength in contexts of information asymmetry because they provide more valuable information (Sanders & Boivie, 2004). Surrogate indicators of quality, such as reputation, are more effective information cues in these contexts due to the higher degree of uncertainty involved. Consequently, we expect that the strength of reputation as a signal of ease of movement may differ depending on a firm’s age.

When evaluating younger firms, receiver attention is more likely to turn to secondary sources of information to identify quality due to a lack of more objective data (Sanders & Boivie, 2004). According to liability of newness arguments (Hannan, 1998; Stinchcombe, 1965), younger firms are often at a greater risk of failure and entail greater uncertainty for employees due to less information available about their roles, careers, or the future. Thus, employees at younger firms with more favorable reputations may pay more attention to reputation as a signal of ease of movement. Because of the information asymmetry and receiver attention associated with working for a younger firm, employees in these organizations may be more likely to capitalize upon the opportunities provided by working in a highly regarded firm and use it as stepping stone to find positions elsewhere.

On the other hand, when employee insiders think about how others may evaluate established, older firms, they likely consider the many years of objective financial and operating data available (Aldrich & Fiol, 1994) as well as the well-established routines and processes (Stinchcombe, 1965) used to assess quality. When evaluating such firms, there tends to be a lower degree of information asymmetry (Datta, Iskandar-Datta, & Patel, 1999; Hannan & Freeman, 1984) because these organizations have had time to build a series of past behaviors and repeated interactions with others. Because more objective evaluations of quality are available and reliable, receiver attention to signals such as reputation are lower in these environments. As older organizations typically have well-established roles and careers (Singh, Tucker, & House, 1986; Stinchcombe, 1965), employees in these firms may perceive greater internal opportunities as well, making it less likely that they would leave. Consequently, for employees at such older firms, reputation’s value as a signal of desirability may be greater than its value as a signal of ease of movement, resulting in tethering effects.

Hypothesis 3: The relationship between reputation and collective voluntary turnover rates will be moderated by firm age such that the relationship will be positive for younger firms while the relationship will be negative for older firms.

Pay level and signal consistency

Some signaling environments are characterized by high signal consistency, which is defined as “the agreement between multiple signals from one source” (Connelly et al., 2011). The strength of signals is enhanced when signal consistency is high and lower when signals are conflicting (Chung & Kalnins, 2001; Fischer & Reuber, 2007; Gao, Darroch, Mather, & MacGregor, 2008). In other words, when an organization sends multiple signals of quality, those signals are more likely to be believed to be credible and send a stronger message to the market.

A firm’s reputation represents one such signal of quality (Connelly et al., 2011). Pay levels represent another important factor that can be considered a signal of quality (Campbell, Coff, et al., 2012; Motowidlo, 1983; Zenger, 1992). When making decisions about salaries, organizations must decide whether to pay employees below, at, or above market levels (Gerhart & Milkovich, 1990). Paying at a higher level than the market is a deliberate decision, intended to motivate higher quality applicants (Akerlof & Yellen, 1986). However, Campbell, Coff and colleagues (2012) suggest that employees with higher earnings tend to “believe they could generate or appropriate even more value outside their current firm” (p. 70) and find that these individuals are more likely to leave for other opportunities such as starting new ventures. Therefore, because employees with higher earnings tend to have a “higher ability to generate value” (Campbell, Ganco, et al., 2012, p. 71), a relatively high pay level should provide employees a sense of greater opportunities outside the firm. Both reputation and pay levels send positive signals to the market and can act as what Trevor (2001) refers to as “movement capital”, or attributes that enhance mobility. Signal consistency suggests that employees in firms with favorable reputations and high pay levels will perceive their ease of movement into other organizations as particularly high. Thus, these employees may be more likely to use the firm as a stepping stone to other opportunities.

However, a firm with a favorable reputation that has chosen to offer low pay levels might send a conflicting signal. On the one hand, a favorable reputation signals high quality, on the other, lower pay levels may signal that employees possess a lower level of skills or human capital. This conflict harms the credibility of these signals and makes it less likely that they will induce employee movement. As a consequence, employees may believe they are better off staying with a reputable employer known for offering a favorable work environment even if their company offers lower pay. This is consistent with Cable and Turban’s (2003) finding that individuals will find reputable firms attractive even if they have lower pay levels. Thus, we propose that the combination of favorable reputation and low pay levels will make employees at these organizations less likely to leave.

Hypothesis 4: The relationship between reputation and collective voluntary turnover rates will be moderated by pay level such that the relationship will be positive for those organizations that pay above market value while the relationship will be negative for those that pay below market value.

Research Design

This study used survey data provided by human resource professionals working in Finland. A random sample of 1065 private sector companies (derived from Statistics Finland) were contacted about participation in a study on human resource practices in 2008. We first called these companies to obtain email addresses of suitable respondents and then sent out an electronic survey. 137 companies completed the survey (response rate 13%). The respondents were HR managers, directors, and executives, and had been with their company for 14 years on average.

We checked for response bias by conducting an archival analysis comparing the respondents to non-respondents on variables contained in two archival databases (Rogelberg & Stanton, 2007). We retrieved firm performance data from an archival company database (Voitto+). The t-tests were not significant with respect to profit margins or revenue growth, alleviating concerns of performance-related non-response bias. We also used information from Statistics Finland to look at differences in company size. It appears that our data is more representative of large companies than small ones. We control for differences in firm size in our analyses.

Measures

Reputation

A measure of perceived external reputation was adapted from the Reputation Quotient scale developed by Harris Interactive (Fombrun & Gardberg, 2000; Fombrun, Gardberg, & Sever, 2000). The human resource professionals were asked to indicate on a five-point Likert scale the extent to which they agreed or disagreed that the company was known for having a favorable work environment: workplace environment, social responsibility, and leadership. We created a summated scale from these items. The Cronbach’s alpha reliability of the scale was .714. We also correlated our measure with an external dataset that contained reputation ratings for a small portion of our sample (n = 19). These data were gathered and published by Arvopaperilehti, a magazine that aggregated Finnish citizens’ perceptions about companies. The correlation between our measure and the external reputation measure were positive (r = .604), further indicating that our measure is valid.

Voluntary turnover rates

A measure of voluntary turnover rates was constructed using the data provided by the respondents. The respondents provided information from employee records on the number of employees that voluntarily quit over the past year and on the number of employees working in the organization. Consistent with prior research that uses key respondent reports (Glebbeek & Bax, 2004; Shaw, Duffy, Johnson, & Lockhart, 2005), this information was used to calculate a voluntary turnover rate that divides the number of employees by the number of people who voluntarily quit, and consequently multiplying the number with one hundred in order to use a percentage value of voluntary turnover rates (Shaw, Duffy, et al., 2005).

Industry munificence

To capture industry munificence, we first identified the industry each firm operates in using its 2-digit TOL 2008 industry code. Then, we measured each industry’s average change in the ratio of firm openings to firm closures over the years 2005–2008 to get a sense for the opportunities in the industry (Statistics Finland, 2014). Thus, higher values of this measure correspond to expanding (more munificent) industries, where firms are entering in larger proportions than they are exiting.

Firm age

The age of each firm was measured as the current year minus the founding year of an organization, and then the natural log was taken to correct for skewness. This method has been used in prior research (Shaw, Delery, Jenkins, & Gupta, 1998). The average firm age was 53 years old and the median was 38 years. Data for this measure were gathered by asking respondents when the company was founded.

Pay level

Following the approach used in other studies (Guthrie, 2001) pay level was assessed by asking respondents to provide information on average salary rates compared with other employers in the same industry providing similar work. Respondents responded on a five-point scale that ranged from “considerably lower than others” to “considerably higher than others”.

Control variables

We considered several potentially relevant control variables including measures relating to the firm and the workplace environment (Bernerth & Aguinis, 2016). Previous empirical and theoretical research suggests a potential relationship between these variables and the focal variables in our study. To rule out alternative explanations for our findings, we have included the following measures as control variables in our model. Firm size, measured by the number of employees in the organization, was included as a control as larger companies may have lower voluntary turnover rates due to more internal opportunities (Guthrie, 2001; Shaw et al., 1998). Consistent with prior studies, the natural log of company size was used in all analyses to control for skewness (Shaw, Duffy, et al., 2005). The firm’s geographic scope can influence internal opportunities (Heavey et al., 2013), so we controlled for it using a dummy variable that considered whether the company had facilities in just one location (coded 1), or in more than one geographic region (coded 0). We controlled for average employee tenure, which has been found to be negatively associated with turnover at the individual level (Griffeth, Hom, & Gaertner, 2000). Investments in human capital such as training can be related to lower turnover (Shaw, Duffy, et al., 2005) so we controlled for the average number of days employees in each firm received training. Firm performance, an important factor to partial out when analyzing reputation effects (Brown & Perry, 1994), was controlled by asking how respondents assess the firm’s revenue growth on a five-point scale: considerably or somewhat higher, considerably or somewhat lower, or the same as others in the industry.

Statistical analysis approach

Although we had full information on many of the variables, there were some missing data in some of our variables. In order to provide the most accurate estimates given the data (Newman, 2014; Wang, Watts, Anderson, & Little, 2013), we used multiple imputation (20 imputations). To test our hypotheses, we estimated multiple ordinary least squares (OLS) regression models using the imputed dataset. First, we entered the control variables in Model 1. Then we entered reputation to investigate the main effect in Model 2. Next, we entered each interaction term separately in Models 3 through 5. In the final Model 6, we estimated the full model including all variables in one model. The R-squared and adjusted R-squared statistics are estimated using Fisher’s r to z transformation (Harel, 2009). As an estimate of effect size, we provide the Cohen’s f² estimates for sequential multiple regression based on omega-squared statistic (Aguinis & Edwards, 2014; Fritz, Morris, & Richler, 2012). We centered all variables before running analyses and entering interaction product terms (Aiken & West, 1991). Analyses were conducted in Stata 13.

Results

The descriptive statistics and correlations among the variables are reported in Table 1. Reputation was negatively correlated with voluntary turnover rates (r = −.268, p = .002). Pay level was positively related to reputation (r = .206, p = .019) and somewhat negatively related to voluntary turnover rates (r = −.152, p = .083). Industry munificence and firm age were not related to voluntary turnover rates or reputation. Moreover, industry, firm age, and pay level were not related to one another.

Table 1.

Descriptive statistics and pairwise correlations.

		Mean	SD	N	1	2	3	4	5	6	7	8	9	10
1	Reputation	3.56	.76	136	1
2	Firm size	935.51	1731.51	137	0.034	1
3	Location	0.68	0.47	137	−0.014	−0.212*	1
4	Training	5.11	6.15	137	−0.065	−0.182*	−0.0281	1
5	Tenure	13.25	5.71	137	0.285***	0.0212	−0.134	0.012	1
6	Revenue growth	3.61	0.93	130	0.143	0.243**	−0.061	−0.206*	0.082	1
7	Industry munificence	3.49	23.86	137	0.046	−0.114	0.180*	−0.074	0.001	−0.025	1
8	Firm age	56.74	56.73	137	0.019	0.000	0.009	0.019	0.121	−0.113	0.026	1
9	Pay level	3.40	0.69	131	0.206*	−0.078	0.170	0.076	0.142	0.043	−0.082	−0.040	1
10	Voluntary turnover rates	3.64	5.74	134	−0.268**	−0.140	−0.166	0.071	−0.316***	−0.176*	−0.039	−0.024	−0.152	1

Notes: * p < 0.05, ** p < 0.01, *** p < 0.001; Firm size and firm age mean and SD of the original (non-transformed) variable reported. Correlations are reported for the logarithm-transformed variables.

Table 2 shows the results for the regression analyses and tests of the hypotheses. The values in the tables are unstandardized regression coefficients. The set of control variables in Model 1 accounts for about one sixth of the variance in firms’ collective voluntary turnover rates (Cohen’s f² = .157). The results from Model 2 indicate that the relationship between reputation and voluntary turnover rates is negative but not statistically significant at the p ⩽ .05 level (b = −1.218, p = .056). According to f², which is a standardized measure of effect size, reputation has a small effect when it is added to the model (f² = .02). Thus, with a small effect size and a negative regression coefficient approaching statistical significance, we find weak evidence for an overall tethering effect consistent with H1 and in contrast to H1alt. However, these results indicate the value in probing this relationship further by examining the role of the signaling environment (Hypotheses 2, 3, and 4).

Table 2.

Regression results on voluntary turnover rates.

	Model 1			Model 2			Model 3			Model 4			Model 5			Model 6
	b	se	p	b	se	p	b	se	p	b	se	p	b	se	p	b	se	p
Firm size	−0.613	0.34	0.072	−0.577	0.33	0.086	−0.688	0.32	0.034*	−0.567	0.32	0.076	−0.352	0.32	0.281	−0.511	0.31	0.100
Location	−2.923	1.08	0.008**	−2.966	1.07	0.006**	−2.976	1.03	0.004**	−3.318	1.00	0.001**	−2.477	1.02	0.016*	−2.949	0.97	0.003**
Training	0.014	0.08	0.869	0.005	0.08	0.949	−0.041	0.08	0.605	−0.054	0.08	0.485	−0.029	0.08	0.710	−0.096	0.07	0.192
Tenure	−0.327	0.09	0.000***	−0.288	0.09	0.002**	−0.334	0.09	0.000***	−0.307	0.08	0.000***	−0.323	0.09	0.000***	−0.359	0.08	0.000***
Revenue growth	−0.764	0.55	0.165	−0.655	0.55	0.234	−0.528	0.53	0.325	−0.530	0.51	0.301	−0.621	0.53	0.244	−0.443	0.50	0.374
Industry munificence	−0.144	1.04	0.889	−0.038	1.03	0.970	−0.866	1.04	0.405	0.246	0.96	0.798	0.342	0.97	0.725	−0.203	0.96	0.832
Firm age	0.117	0.41	0.776	0.119	0.41	0.772	0.088	0.39	0.824	0.002	0.38	0.996	0.076	0.39	0.845	−0.020	0.36	0.955
Pay level	−0.487	0.72	0.501	−0.214	0.73	0.770	−0.015	0.72	0.984	−0.008	0.70	0.991	0.143	0.70	0.838	0.303	0.67	0.651
Reputation				−1.218	0.63	0.056	−0.827	0.65	0.205	−1.018	0.59	0.085	−0.738	0.63	0.248	−0.482	0.60	0.422
Reputation x industry Munificence							5.265	1.84	0.006 **							3.917	1.72	0.026 *
Reputation x firm age										−2.090	0.45	0.000 ***				–1.620	0.47	0.001 ***
Reputation x pay level													3.286	0.90	0.001 ***	2.022	0.96	0.041 *
Constant	3.682	0.47	0.000***	3.676	0.46	0.000***	3.627	0.45	0.000***	3.693	0.43	0.000***	3.297	0.45	0.000***	3.422	0.42	0.000***
R-squared	.201			.225			.289			.339			.327			.425
Adjusted R-squared	.152			.171			.234			.288			.275			.370
F-value	3.67	***		3.73	***		4.49	***		5.82	***		5.18	***		6.37	***

Notes: Unstandardized mean-centered coefficients reported. Multiple imputation used (N = 137). R-squared statistics are based on Fisher’s z transformation. * p < 0.05, ** p < 0.01, *** p < 0.001.

We next analyzed Hypothesis 2, which suggested that industry munificence would moderate the relationship between reputation and voluntary turnover rates. The interaction term is statistically significant in both Model 3 (b = 5.265, p = .006) and Model 6 (b = 3.917, p = .026). According to Cohen’s f², adding the interactive effect of reputation and industry munificence to the main effect model explains an additional 7% of systematic variance relative to unexplained variance in voluntary turnover rates. Figure 1 depicts the interaction effect.

Figure 1.

The interaction of reputation and industry munificence on voluntary turnover rates.

We further analyzed the interaction in Model 6 by investigating the simple slopes at values of 0, +/– 1, and +/– 2 standard deviations (SD) for the moderating variable (Aiken & West, 1991; Cohen et al., 2003; Preacher, Curran & Bauer, 2006; Younkin, 2016). The simple slope is negative and statistically significant at −2 SD (b = −4.188, t = −2.88, p = 0.005) and -1SD (b = −2.315, t = −2.77, p = 0.007) for firms in less munificent industries, becomes non-significant at moderate levels of industry munificence (b = 1.433, t = 1.44, p = 0.153), and is positive and statistically significant at +2SD (b = 3.307, t = 2.01, p = .047) for firms in more munificent industries. In practical terms, results from the simple slopes analyses show that when industry munificence is low (−2SD), a one point increase in reputation is related to a 4.2 percentage point decrease in voluntary turnover rates. Whereas when it is high (+2SD), a one point increase in reputation is related to a 3.3 percentage point increase in voluntary turnover rates. These results provide support for Hypothesis 2. Reputation appears to serve as a tether for firms with favorable reputations in industries that are less munificent, but it serves as a stepping stone for firms with favorable reputations in more munificent industries.

Hypothesis 3 proposed that firm age would moderate the relationship between reputation and voluntary turnover rates. The interaction term is statistically significant in Model 4 (b = −2.090, p = .000) and Model 6 (b = −1.620, p = .001). According to Cohen’s f², adding the interactive effect of reputation and firm age to the main effect model explains and additional 15% of systematic variance relative to unexplained variance in turnover. The plot of this interaction is portrayed in Figure 2.

Figure 2.

The interaction of reputation and firm age on voluntary turnover rates.

We further explore this interaction using simple slopes in Model 6. The simple slope is significant and negative at +2 SD (b = −4.258, t = −3.45, p = .001) and +1SD (b = −2.349, t = −2.96, p = .004) for older firms, becomes non-significant for firms in the middle of our age range (b = 1.467, t = 1.90, p = .059), and is positive and statistically significant at −2SD (b = 3.376, t = 2.80, p = .006) for younger firms. In practical terms, when firm age is low (−2SD), a one point increase in reputation is related to a 3.4 percentage point increase in voluntary turnover rates. When firm age is high (+2SD), a one point increase in reputation is related to a 4.3 percentage point decrease in voluntary turnover rates. These results support Hypothesis 3, which posits that favorable reputation is more likely to lead to tethering effects for older firms, but stepping stone effects for younger firms.

Hypothesis 4 predicted that pay level would moderate the relationship between reputation and voluntary turnover rates. We find a statistically significant interaction between reputation and pay level on voluntary turnover rates both in Model 5 (b=3.286, p=.001) and Model 6 (b = 2.022, p = .041). According to Cohen’s f², adding the interactive effect of reputation and pay level to the main effect model explains an additional 11% of systematic variance in turnover. Figure 3 shows the graph of our interaction effect.

Figure 3.

The interaction of reputation and pay level on voluntary turnover rates.

We further investigated the simple slopes of the interaction in Model 6. The simple slope is negative and statistically significant at −2SD (b = −3.195, t = −2.38, p = 0.021) and −1SD (b = −1.811, t = −2.26, p = 0.027) for firms who paid wages below industry average, indicating a tethering effect for these firms. In practical terms, when pay level is low (−2SD), a one point increase in reputation is related to 3.2 percentage point decrease in voluntary turnover rates. The simple slope is positive but non-significant for firms who paid above industry average (+2SD: b = 2.340, t = 1.57, p = 0.123) in Model 6, but statistically significant in Model 5 (+2SD: b = 3.710, t = 2.51, p = 0.015). Thus, we find that a better reputation is related to a tethering effect for firms with lower pay levels. We also find some evidence for a stepping stone effect for firms with higher pay levels and favorable reputations. These results are consistent with Hypothesis 4 regarding signal consistency.

In sum, a firm’s reputation appears to have a significant impact on the voluntary turnover rates it experiences. The main effect of reputation was relatively small (f² = 0.02), which is perhaps not surprising given the countervailing tensions entailed by reputation as a signal of both desirability and ease of movement. However, adding the interactive effects of contextual factors explains an additional 25% of systematic variance relative to the unexplained variance in turnover, which signifies a moderate-to-large effect size (f²) according to Cohen’s (1988) guidelines. This indicates that it is critical to consider the signaling environment when attempting to understand the relationship between reputation and voluntary turnover rates.

Robustness checks and supplementary analyses

Because industry munificence could be measured in different ways, we estimated our models using alternative measures as a robustness check. Industry munificence might be captured by the average growth in the number of people employed by that industry in the past three years, as more people gaining employment in a particular industry is a sign of industry’s growth, robustness, and opportunity (Statistics Finland, 2016). This measure of industry munificence also revealed tethering effects for reputable companies (Model 3: b = .835, t = 4.22, p = .000; Model 6: b = .528, t = 2.48, p = .016). We also tried a categorical measure that captured whether a firm was operating in a service industry, a manufacturing industry, or a hybrid industry that represented a mix of both service and manufacturing. We would expect that service industries are generally more munificent than manufacturing industries. Our results are in line with this logic, as reputable firms in manufacturing industries experienced tethering effects (Model 3 b = −3.715, t = −2.65, p = .009; Model 6: b = −4.080, t = −3.16, p = .002), whereas the interaction effects were not significant for service and hybrid industries.

Some of the data for this study are cross-sectional and self-reported, suggesting common method variance (CMV) could be an issue. To explore the extent to which CMV could be an issue in this study, we conducted a post-hoc analysis using a regression-based marker variable technique to correct for common method bias (Podsakoff, MacKenzie, & Podsakoff, 2012). Specifically, we added two marker variables relating to compensation that should be theoretically unrelated but at the same time similarly vulnerable to CMV relative to other study variables (Williams, Hartman, & Cavazotte, 2010). Adding these marker variables did not have an impact on the statistical significance or interpretation of our results. Thus, our interaction effects cannot be artifacts of CMV (Siemsen, Roth, & Oliveira, 2010).

Discussion

Reputation is a complex phenomenon, often with countervailing effects on firms. This study contributes to the literature on firm reputation by investigating a specific type of reputation—perceived external reputation of the work environment—and building an understanding of how it relates to collective voluntary turnover rates. An important theoretical contribution of this study is clarifying the conflicting streams of thought about the relationship between reputation and voluntary turnover rates. Shaw, Gupta, and Delery (2005) suggest that studying “alternative variations of the same theme … and examining them empirically [should be used] more frequently in resolving theoretical conflicts” (p. 66). Our results help distinguish among alternative signals reputation could represent and how those signals might relate to collective voluntary turnover rates. In particular, while we find that—all else equal—a more favorable reputation may result in somewhat lower collective voluntary turnover rates for firms, a lack of consideration of the context (i.e., the signaling environment) would have resulted in the erroneous conclusion that this is always the case. Instead, we find that in many key situations, a more favorable reputation can actually result in increased collective voluntary turnover rates, building on more recent studies that have suggested, somewhat counterintuitively, that there are downsides to having a favorable reputation (Petkova et al., 2014; Zorn et al., 2014). While this paradox might “complicate” the story (Weick, 1969), it helps to “obtain a more complex understanding of how organizations function” (Tsoukas & Dooley, 2011, p. 703).

By using signaling theory to identify contingency factors important to understanding the relationship between reputation and voluntary turnover rates, we are able to demonstrate the complex interplay between a firm’s reputation, its environment and the firm-level outcomes it experiences (Tsoukas, Garud, & Hardy, 2003). Identifying boundary conditions in which firm resources such as reputation serve as tethers or stepping stones is indispensable for theoretical development (Campbell, Coff, et al., 2012; Corley & Gioia, 2011). We find three contextual aspects of the signaling environment that can influence decision making (Connelly et al., 2011; Johns, 2006). More specifically, we find that contexts with greater uncertainty and/or greater opportunities tend to increase the likelihood that reputation will be used as a signal of ease of movement; we find that firms with favorable reputations that are in more munificent industries, are younger, or have higher pay levels are more likely to be used as a stepping stone. In contrast, firms with favorable reputations that are in less munificent industries, are older, or have lower pay levels tend to experience tethering effects and encounter lower voluntary turnover rates than less reputable firms.

Future research

The theory and results of this study suggest several avenues for future research. The contributions of this paper rely on using signaling theory to acknowledge that collective turnover does not occur in a vacuum—how a firm is perceived by others and the broader environment in which it is embedded impacts this complex phenomenon. In this way, this paper can act as a springboard for other researchers who follow Weick’s (1969) call for complication rather than simplification with regard to understanding organizational phenomena. For instance, a greater appreciation of the networks and institutions in which a firm’s reputation is built and transmitted may lead to novel insights into understanding how perceptions of reputation may evolve as institutions or industries undergo change.

Additionally, although reputation is a relatively stable construct that experiences little variability over time (Fombrun, 1996; Roberts & Dowling, 2002), future research should examine how collective flow in and out of organizations might relate to the reputation of a firm. Studies that collect longitudinal data from multiple sources should help address this concern. In addition to the signaling environment factors examined here, other contextual factors that might play a role in the relationship between reputation and voluntary turnover rates should be examined (e.g., geographical regions, unemployment rates, age of employees) in future research. Indeed, studies that utilize moderated mediation models to examine how a variety of organizational factors affect voluntary turnover rates and thereby firm performance in different signaling contexts would be beneficial.

Practical implications

As extant literature has found, higher voluntary turnover rates are related to lower firm performance (Park & Shaw, 2013). However, if organizations want to reduce voluntary turnover rates, they should make sure to consider the context in which they operate. For instance, we find that the value of a favorable reputation as a signal of ease of movement is higher for younger firms, for firms with higher pay levels, and in industries with higher growth rates. In these situations, managers may attempt to increase the connection to the organization to make it less likely that employees will leave. For example, managers may be able to help employees build links to increase social networks (Mitchell, Holtom, Lee, Sablynski, & Erez, 2001) or offer high-commitment human resource systems (Heavey et al., 2013), strategies that have been found to be negatively associated with collective voluntary turnover rates.

Further, we find that having lower pay levels than competitors is associated with lower voluntary turnover rates for more reputable firms. It is worth noting, however, that having lower pay levels may make it difficult to attract new qualified employees. Although research demonstrates that individuals are willing to accept lower wages to work at a firm with a positive reputation (Cable & Turban, 2003), it is important for managers to consider the tradeoffs between attraction and retention when making pay decisions. Alternatively, rather than attempting to reduce collective voluntary turnover rates, managers at firms prone to being used as a stepping stone might instead embrace this churn and find ways to gain from this increased flow of individuals in and out of the organization. For instance, newcomers inherently are less knowledgeable than those they replace, yet the knowledge they bring to a firm adds diversity and new perspectives (March, 1991). In this way, a reputable firm that is in a more munificent industry, is younger, or pays higher salaries might be in a better position than firms with less-favorable reputations to generate new knowledge, avoid stagnation, and innovate.

Limitations

Although we believe this study clarifies many important issues regarding the link between reputation and voluntary turnover rates, it does have limitations we wish to acknowledge. A limitation in our study is that we cannot rule out the possibility of voluntary turnover rates influencing the self-report of reputation, a reversed causality effect. Indeed, Flanagan and O’Shaughnessy (2005) test and find support for a relationship between employee layoffs and firm reputation. Although the nature of voluntary and involuntary turnover rates is different (Shaw et al., 1998), and theory indicates reputation as a factor likely to influence turnover (Carmeli & Freund, 2009; Herrbach et al., 2004), it is possible that turnover led to certain perceptions of reputation. The implication of our theoretical arguments examining reputation as a signal of collective desirability or collective ease of movement is that we could be missing nuances in the relationship between reputation and voluntary turnover rates by not examining the reverse relationship.

The inferences drawn from our results could also be constrained by our measures. First, although a variety of measures of reputation exist, we adapted our measure from the dimensions of the Reputation Quotient (Fombrun et al., 2000). Lange, Lee, and Dai (2011) indicate that it is important to choose a measure that reflects the type of reputation for which the study is focused. Our measure allowed us to examine more specifically how the firm’s work environment was perceived and separating it from financial performance and other attributes for which a company might be known, such as product quality. Other indicators of reputation used in prior research and widely reported in the media, such as Fortune’s Most Admired Companies, might provide an alternative approach to estimating the effects of reputation on important organizational outcomes.

Conclusion

Consistent with the idea that reputation can have a paradoxical and contradictory influence on firm outcomes, the literature has been unclear as to whether firms with favorable reputations will experience higher or lower voluntary turnover rates relative to firms with unfavorable reputations. We find that, all else equal, reputation may signal collective desirability such that reputable firms experience lower levels of voluntary turnover rates. However, in certain signaling environments, the strength of reputation as a signal of ease of movement is enhanced and a firm with a favorable reputation is more likely to be a stepping stone for individuals, relating to higher voluntary turnover rates in the organization. This suggests that the most salient question might not be whether reputation is a tether or a stepping stone, but rather when it serves as one or the other. We encourage future research investigating the role of reputation on organizational-level phenomena as well as studies that explore other firm characteristics that may serve as tethers or stepping stones relating to collective voluntary turnover rates in organizations.

Footnotes

Acknowledgements

We wish to thank the Finnish Work Environment Fund, which provided funding for the data collection (project number 108125).

Funding

Finnish Work Environment Fund 108125.

Notes

Author biographies

Erin E. Makarius is an assistant professor of Human Resources in the Management Department at The University of Akron. She received her PhD from the Fisher College of Business at The Ohio State University. Her research interests are in the area of boundary spanning, including organizational boundaries, work–life boundaries, and international boundaries.

Charles E. Stevens is an assistant professor of Strategy in the Management Department at Lehigh University, and received his PhD in International Business at the Fisher College of Business, The Ohio State University. His research interests are in the areas of global strategy, foreign entry strategy, national culture, and political risk.

Aino Tenhiälä (nee Salimäki) is an assistant professor of Organizational Behavior and Human Resources at IE Business School. She holds a PhD in Work Psychology from Aalto University. Her research interests include employee motivation and compensation.

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