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Abstract

Recruiters and researchers of TMT (top management teams) tend to emphasize the human capital and social capital of the executive in the interfirm migration, but they ignore the role of the former employer’s prestige. We address this issue to argue that the former employer’s organizational prestige attracts the recruiter’s attention to the TMT, and we propose that the TMT from high-prestige organization attracts high rewards than the TMT from a low-prestige organization. We used data from the biotechnology sector on 1,468 TMTs, their 1,482 hiring events, 783 recruiters, 168 source employers—in the interfirm movement of the TMTs from 1997 to 2005. We used three measures for predictors of the organizational prestige of the former employer, and the regression analysis shows some reflections of those predictors of rewards of the hired executive. The result shows that the organizational age, size, and alliance network of the former employer emit value signals to the recruiter. These components of organizational prestige predict increase in the rewards after controlling for the human capital of the TMT. The study contributes to organizational context as a predictor of value, institutional theory, and general implications for practice and policy.

Keywords

interfirm TMT recruitment TMT migration from the incumbent to small and medium enterprises former employer’s prestige post-migration executive rewards institutional theory biopharmaceutical industry

Introduction

The TMT (top management team) recruiting poses a dilemma to high-technology firm whether to acquire human capital of the executive or social capital of the executive. Managerial human capital refers to managerial knowledge, and social capital refers to the managerial ties with other firms. The human capital builds on the explicit and tacit dimensions, and it relies on human capital theory (Bailey & Helfat, 2003). The human capital theory, which takes the technical view of the human resource (Becker, 1964), argues that executives with high human capital attract the attention and rewards from the recruiter for the TMT (Datta & Iskandar-Datta, 2014; Harris & Helfat, 1997; Sturman et al., 2008). The human capital contributes to the recruiter’s technical advantage, economic position, and strategic performance (Datta & Iskandar-Datta, 2014). For instance, the industry-specific human capital of the TMT makes such predictions for the comparative advantage to the recruiter for such a TMT enhances the recruiter’s capabilities (Boeker, 1997). Human capital view of the TMT may under emphasize the social capital view.

The social capital view of the TMT also has important implications for interfirm TMT recruitment and rewards. This social capital of TMT implies that the recruiter’s attention, evaluation, selection, and rewards align with the managerial social capital. The related evidence shows that social capital predicts the executive’s compensation because the recruiter benefits from the social capital of the incoming executive (Belliveau et al., 1996). For instance, TMT’s social capital predicts the turnover and succession of the top executives (Cao et al., 2006). Likewise, from the former employer’s perspectives, the empirical literature shows that firms lose value to competitors when their TMT depart with high social capital (Bamford et al., 2006). Like the human capital flows with the TMT, the social capital flows with the TMT.

The institutional theory supports both sides of the argument: the advantage of social capital like human capital, and the flow of social capital like human capital of the manager (Burt et al., 2000; Malik & Huo, 2019). Together, the human capital argument (Castanias & Helfat, 1991) and the social capital argument (Castanias & Helfat, 2001) predict TMT’s attractiveness and rewards. For instance, the evidence from the stock analyst firms explains the flow of individual analysts to their employers, and from their employers to individual analysts (Malik & Huo, 2019). However, the human capital perspective and social capital perspective have overlooked the notion of the organizational prestige and the TMT’s attractiveness to the recruiter and increase in the rewards. Since the organizational prestige flows from the executive to the employer and vice versa, it should also flow between employers during the TMT’s migration. Thus, the hiring is likely to attract the TMT from prestigious employers.

Based on this assumption within the institutional theory, we ask whether the former employer’s prestige influences the recruiter’s attention with rewards. This question goes beyond the simple notion of human capital literature (Anderson et al., 2001) and the social capital literature (D’Aveni, 1990; D’Aveni & Kesner, 1993). The extant literature focuses focus on the CEO’s social capital (Allen, 1974; Belliveau et al., 1996; Coleman, 1997), but it excludes other positions such as the COO (chief operating officer), CTO (chief technology officer), CFO (chief financial officer), VP (vice president), and other executives. We consider all positions of the TMT. The prior literature considers the organizational prestige (Frandsen, 2012), but it ignores the former employer’s prestige. We address these gaps—multiple positions and former employers—by raising the research question. Does the former employer’s organizational prestige influence its TMT’s attractiveness and rewards?

Based on the evidence from the biotechnology industry, where the TMT exclusively migrates to one direction—from the industrial incumbent to the small and medium enterprise (SME)—this study makes progress in theory and policy at three levels. First, it examines a new phenomenon (rewards based on former employer’s prestige), the new context of the event (flow of TMT from incumbents to SMEs), and the new context of the sector (biopharmaceuticals). Second, it contributes to the institutional theory in the cycle: Social capital flows from the former employer to the executive, then from the executive to the recruiter in the interfirm hiring event. Third, it draws our attention to the general relevance of the finding and policy implications.

Theory and Hypotheses

In the theory and hypotheses development, we proceed with the institutional theory that draws on the inter-organizational flow of the prestige through the interaction mechanisms. The institutional theory makes several contextual assumptions. First, prestige such as reputation, legitimacy, or both flow between firms through the interfirm interaction (Deeds et al., 2008). For instance, the social status of the person and firm flows to both direction during a transaction (McPherson & Sauder, 2013; Sauder et al., 2012). Evidence supports this view from the security analysts firms in the biotechnology sector (Malik & Huo, 2019). Second, the interfirm transaction occurs through the flow of personnel, alliances, or other forms of technology transfer. Our focus is on the interfirm managerial flow. Third, the prestige flowing from the former employer of the executive to the new employer suggests that the new employer evaluates and rewards the executive based on the former employer’s prestige. Holding these assumptions in the current context of the institutional theory, we proceed with the multiple logics of the institutional theory (Greenwood et al., 2011). The multiple logic explains that the managerial organizational context is as important as the other factors such as human capital or social capital of the manager. Thus, the multiple logic of the institutional theory contends that economic logic shows a partial view of the decision process.

Unlike the economic logic that explains that executives attract higher rewards because of their economic resources such as human capital flows to the new employer, the normative logic contends that the social context of the executive, organization, and the former employer influence the transaction of the executive between firms. Institutional theory alludes to uncertainty reduction through several mechanisms in support of these assumptions that the recruiter of the TMT is likely to pay attention to the former employer’s social status. First, the prestige of the former employer reduces the uncertainty of the industry. In the biotechnology sector, which symbolizes high uncertainty because of its dynamic nature, the isomorphism diverts this attention to the status. Second, in this sector, small firms that recruit TMTs lack experience to assess some aspect of the values of the TMT. Isomorphism serves this gap. Third, the halo effect compounds the other hidden values as well as visible signals. Therefore, the former employer’s prestige complements the technical skills of the executive in the hiring process.

The institutional theory suggests that the former employer’s prestige plays a part in explaining the uncertainty dilemma of the recruiter. The recruiter faces uncertainty about the executive’s private tacit knowledge, embedded inexperience. Because tacit knowledge of the executive tends to be invisible, the uncertainty increases for the critical needs of the recruiter. This uncertainty turns the recruiter’s attention to other visible sources of signals to evaluate and manage part of the recruiter’s uncertainty about the knowledge of the recruited TMT. For instance, the recruiter needs some visible signals to interpret values and rewards for the TMT (Jackson & Schuler, 1995). Experienced recruiters use their experience to decide for the rewards, and less experienced recruiters (SMEs) need visible signals. This reason supports one part of the institutional theory in uncertainty reduction.

The other reason that supports the institutional theory in the recruiter’s uncertainty reduction is the isomorphic argument. The isomorphic argument of institutional theory suggests that SMEs imitate industry leaders in their structures and practices (DiMaggio & Powell, 1983). In recruiting executives from other firms, the SME turns to the executive from industry leaders to appear appropriate and credible (Deephouse et al., 2008). In other words, hiring the TMT from incumbents meets the normative condition of the industry (D’Aunno et al., 1991; DiMaggio & Powell, 1983; Haveman, 1993; Oliver, 1988). These SMEs that hire TMTs to impart norms of the industry reduces their uncertainty in the decision, improve their legitimacy among their audience, and increase their survival opportunities.

Organizational Prestige

As noted earlier, institutional theory supports the prestige in organizational structure, practice, and decisions two perspectives. One perspective of the institutional theory combines the technical and social core of the organization (Scott, 2003). This view of the institutional theory rejects that technical or social values alone explain the entire decision. Organizations differ in prestige because of variegated combinations of technical and social values (DiMaggio & Powell, 1983; Scott, 2003). As a result, high-prestige organizations tend to have higher legitimacy (social support) and reputation (technical knowledge) for their survival and growth (Bruderl & Schussler, 1990; Carroll & Delacroix, 1982; Singh et al., 1986). The other perspective of institutional theory suggests that prestige flows between organizations. The high-prestige organization becomes the source, and the low-prestige organization becomes the recipient. In the case of SMEs hiring TMTs from incumbents, the prestige flows from the source to the recipient. Evidence from various industries supports the dynamics of prestige between organizations through inter-organizational tractions (Podolny, 1993; Podolny & Stuart, 1995). Thus, the first perspective of the organizational prestige alludes the presence of prestige and its implication for the actor, and the second perspective of the organizational prestige alludes to the fluid nature of the prestige.

The institutional theory elaborates this process of the stock and flow of the organizational prestige by explicating the mechanisms that link the stock and flow of prestige between organizations. The stock of prestige refers to the social status of the organization based on its performance and conformance. The performance measures its technical achievements, and the conformance measures its isomorphic achievements. The human capital that contributes to the stock of the executive or the organization as a whole is one component of the prestige stock; the conformance to the norms and standards complements the human capital of the stock. For instance, organizational ranking based on performance, and organizational legitimacy based on conformance contribute to the stock of prestige. Likewise, the flow of this prestige stock occurs from the source to the recipient in the transaction between firms (Brown & Duguid, 2001).

TMT’s migration and prestige flow

Evidence supports the argument that prestige flows between firms with the transaction of the TMT. Like the human capital of the TMT flows from one firm to the other, the prestige value flows from one firm to the other through the TMT’s migration (Podolny & Phillips, 1996). The flow of human capital of the manager builds on two assumptions. First, the TMT carries forward technical, social, and organizational values. Based on these signals, the TMT negotiates carrier advancement in the recruitment process. Second, the SME recruiter offers better carrier advancement rewards to the TMT than the incumbents. It means that the SME negotiates with the TMT by using those career advancement opportunities. Thus, the TMT offers value signals to the recruiter, and the recruiter offers rewards to the TMT for those signals of the prestige, comprising functional knowledge such as human capital (Bermiss & Murmann, 2015) and social context such as organizational status (Malik & Huo, 2019).

In comparison to this prestige component as the human capital of the prestige flow with the TMT hiring, the organizational prestige component deals with the TMT’s employer. A recent study uses evidence from the security analyst firms to explain that the organizational prestige of the security analyst firm flows to the individual stock analyst in the biotechnology sector (Malik & Huo, 2019). The study implies that investors face uncertainty because of two reasons. First, the biotechnology sector is a specialized field and investors lack knowledge about it to make effective decisions. Second, the analyst’s private knowledge remains invisible, leaving some uncertainty. As a result, investors in the biotechnology firm turn to the employer of the stock analyst. For instance, large financial institutions emit prestige to their analysts, and investors draw on those prestige signals. In contrast, a security analyst firm based on two partners lacks such prestige, regardless of the capabilities and skill of those two analysts in the market. In short, the stock analyst’s security firm’s organizational prestige has a level of halo effect on the analyst and then on the market (Malik & Huo, 2019).

Another example further elaborates how the organizational prestige matters in the interfirm recruitment decision in other sectors such as inter-university hiring of professors. Chinese universities show tendencies to recruit foreign professor or Chinese professors from abroad in various disciplines (social sciences and natural sciences) based on two direct or implied signals. First, the research output matters because it reflects the human capital of the professor. Second, the organizational prestige of the university matters to the recruiter in China because it emits alternative values. Several cases show that prestige of the organization dominates in the hiring decisions between the two competing values. One author has observed these patterns in Singapore, the United Kingdom and Europe, South Korea, let alone in China. Thus, the organizational prestige takes precedents in attracting the recruiter’s attention and rewards more than the human capital

Organizational prestige and TMT’s rewards

The organizational prestige predicts TMT’s post-migration rewards from multiple perspectives and measures, which rest on various mechanisms of stock and flow of prestige. We focus on three credible, reliable, and useful mechanism of prestige stock and flow. First, the firm’s history represents the organizational prestige through legitimacy mechanisms. For instance, the older organization tends to show a credible context for the audience. Second, the firm’s size represents prestige through its reputation as it shows the organizational market share power and visibility. Organizational size implies a form of its ranking among its competitors, its visibility, and its spatial span. Third, the organizational relations with other organizational through network alliances predict that the audience such as recruiters and investors pay attention in their decisions making processes (Sauder et al., 2012). Thus, we link the firm’s size, age, and alliance network to the TMT’s post-migration rewards based on the underlying institutional reasons.

Employer’s size and TMT’s rewards

The former employer’s firm’s size predicts the TMT’s post-migration rewards. First, the size of the former employer emits prestige signals of visibility across space. Second, the firm’s size shows the firm’s ranking in the industrial field. Third, the size of the firm’s shows its influence and power in the environment. Fourth, the firm’s size shows its leadership in industry standards. Finally, the firm’s size projects its spatial interpretation in the context of the market share. The spatial concept combines social space and physical space (Giddens, 1990). The social context of the firm draws on the constructed structures and values in space and time. The firm’s size combines the spatial context of both types—the social and physical (Pfeffer & Salancik, 1978; Singh et al., 1986). Since most firm’s scholar suggests that the former employer’s size correlates with the firm’s prestige (Podolny & Phillips, 1996), we propose the following hypothesis.

Hypothesis 1: The former employer’s prestige based on the firm’s size positively correlates with the TMT’s post-migration rewards.

Employer’s age and TMT’s rewards

The former employer’s firm’s age predicts the TMT’s post-migration rewards because of the prestige associated with the firm’s age. First, the former employer’s age shows history, prestige, brand, credibility, and trust (Suchman, 1995). This history, prestige, and trust based on the age of the firm correlate with that firm’s prestige (Henderson, 1999). In the current study, the employer’s age stands for the firm’s historical information available to the recruiter. Access to the information with history adds to the firm’s prestige. The firm’s age also signals the incumbent-specific experience of the TMT. Incumbent firms in the industry define the industrial trends, which implies that the TMT brings forward some of those trends. Likewise, the firm’s historical accounts bring the cultural and institutional artifact to the recruiter. Since institutional objects guide the structure, principles, and practice of small firms in the field (Scott, 2003), the SME recruiter of the TMT should positively interpret the value of the prestige signal of the former employer.

Hypothesis 2: The former employer’s prestige based on the firm’s age positively correlates with the TMT’s post-migration rewards.

Employer’s alliance network and TMT’s rewards

The former employer’s network alliance attracts high post-migration rewards for the TMT. The former employer’s network prestige refers to the structural element (how) of the context. Firm’s network prestige depends on the size, and the size of the network interprets the firm’s embeddedness (Uzzi, 1997). The social network shapes the firm’s prestige because it follows for several interpretative reasons. First, the network size suggests the firm has an identity because it conforms to rules and norms of the network (Human & Provan, 2000). The firm’s identity reflects on the TMT. Second, the network size of the former employer implies that the network members endorse the firm’s structure, principles, and practice. The structure captures the “how” question in the decision process. Third, the firm’s network measures a firm’s prestige that flows with the TMT (Ruef & Scott, 1998). Since the former employer’s network size predicts the flow of the prestige, it predicts the TMT’s post-migration rewards.

Hypothesis 3: The former employer’s prestige based on the firm’s alliance network positively correlates with the TMT’s post-migration rewards.

Method

Sample and Data

This study selected the pharmaceutical industry for the empirical analysis of the central proposition. In this sector, the members of the TMT migrate from industrial incumbents to new firms as a recruiter. The incumbent in the current context means the top 200 industrial companies by revenue and employees. All the incumbents have listed on the stock exchange compared with less than 50% of SME recruiters. All TMT migrated from incumbents to SMEs, and less than 5% of them transitioned between SMEs. In very rare cases, incumbents recruited TMTs from SMEs in the biotechnology sector.

In this context of the TMT flow from the incumbent to the SME, the unit of analysis reflects the TMT’s migration event between firms. The migrating TMT’s position and functions vary before their migrations. On the position scale, the CEO (chief executive officer) takes the top rank, and the VP (vice president) takes the lowest rank on the position scale. Other positions such as president, COO, or CFO come in the middle ranks. Management literature presents similar hierarchical structures about the ranks of the executives across industries (Hambrick & Cannella, 2004; Hambrick & Mason, 1984; Williamson & Cable, 2003). Likewise, the industry-specific confirms these ranks and their importance in the hierarchical structure (Bioworld, 2008). Similar to these ranks, executives vary in their functional portfolios.

We used multiple sources to synthesize data in several steps. First, we obtained the list of biotechnology firms from BIO (biotechnology industry organization), which produced 1,400 firms active in the sector. Second, we obtained a list of the biotechnology firms in Factiva (an interactive database of Dow Jones). Third, we gathered the data on the TMT’s migration from a public announcement documented in the ABI/INFORM database. Fourth, we matched the recruitment event with the former firm and the recruiter based on the focal executive in the unit of analysis. Fifth, we excluded the double entries from the sample. From the incumbent’s perspective, the top 200 firms supplied the TMT to SME recruiters. The following list describes the attributes of the sample.

Incumbent (former) firm = 168

Incumbent’s average age = 91 years

Incumbent’s average size = 47,000 employees

TMTs who moved = 1,468

Recruitment event = 1,382

SME recruiters = 783

International role of TMTs = 3.4%

Data period = 9 years (1997–2005).

Data Coding

We attended to the signals and coded those signals from the press releases of the recruiters. The recruiter—an SME in the current study—evaluates the value signals of the incoming TMT. In this process, the recruiter turns to the former employer of the TMT to bridge the information gaps. The former employer’s information in the public domain helps recruiter evaluate, interpret, and share with the audience through press releases. In the following, we present a typical press release in which the CEO of the recruiting firm makes the announcement, highlighting a junior TMT’s value for the firm based on the former employers. The recruiter provides a temporal signal (multiple former employers) and a prestige signal (a reference to industry leaders in the field). An abbreviated version of a press release gives the gist of this context.

Cambridge, UK and Cambridge, Massachusetts—9 July 2004—Acambis plc (LSE: ACM, NASDAQ: ACAM) announces the appointment of David Lawrence as Chief Financial Officer. Gordon Cameron, CEO of Acambis, commented:

“I am delighted that we have attracted someone of David’s calibre to join Acambis. Mr Lawrence, 41, is currently Vice President of Finance for Chiron Vaccines, the vaccines division of Chiron Corporation (“Chiron”), which he joined in February 2002. In that role, he is responsible for all aspects of finance and accounting for Chiron Vaccines, and also for strategic planning, business development, mergers and acquisitions. In particular, he played a lead role in Chiron’s acquisition of PowderJect Pharmaceuticals plc and the subsequent disposal of various non-core assets/businesses. Chiron Vaccines is the fifth-largest vaccines business in the world and had revenues of nearly $700m in 2003.

“I am delighted that we have attracted someone of David’s calibre to join Acambis. David will be an important member of the Acambis management team, and I look forward to working closely with him through the next stage of our development. His considerable industry knowledge, the strong management and financial skills he has developed throughout his career and the experience he has gained through playing an active role in the rapid growth of Chiron Vaccines will be invaluable in the management of Acambis’ continued growth.”

Variables

Dependent variable

The dependent variable measures the difference between the pre-migration and post-migration rank of the TMT. A positive result implies an increase in the post-migration rewards; the negative value means a decrease of it. We included the ranks equal to or above the vice president (VP), and the prior literature offers similar guides on the TMT research (Hambrick & Mason, 1984). Empirical studies have used similar positions of the TMT in the interfirm hiring of the executive and the context of the organizational prestige (Williamson & Cable, 2003).

a. CEO (Chief Executive Officer),

b. President, the COO (Chief operating officer),

c. CFO (chief financial officer),

d. EVP (executive vice president),

e. CTO (chief technology officer) and CSO (chief technology officer),

f. SVP (senior vice president),

g. VP (vice president).

The hierarchical position of the TMT conforms with the past literature (Hambrick & Mason, 1984). The industry-specific literature shows a clear guide to the ranking of the TMTs in the biopharmaceutical firm (BioSpace Corp). We coded the ranks (pre- and post-migration) as: Chairperson/CEO = 7; President = 6, CFO = 5, EVP and CTO = 4; SVP = 3, VP = 2, and other legal TMTs and heads = 1. Since the hierarchical position represents the post-migration variation of the ranking (7 to 1), the dependent variable becomes the ordinal type.

Independent variables

Three main interdependent variables in the analysis are the former employer’s size, age, and social network. The following three steps show the respective levels in the development of the variables.

a. Interfirm size: We used the former employer’s size in proportion to the recruiter’s size. We divided the former firm’s size (employees) with the recruiter’s size. The average firm’s size of the former employer was ten times greater than the average size of the recruiter. Size of the firm represents its context, prestige and influence (Podolny and Phillips, 1996; Pfeffer and Salancik, 1978; Singh et al., 1986). This variable meets the assumption that the former employer’s size exceeds the recruiter’s size—the incumbent is ten times greater than the SME.

b. Interfirm age: We used age differences of the former employer’s age and the recruiter’s age. We subtracted the recruiter’s age from the former employer’s age. For instance, if the TMT migrated in 2002, and the former employer started its operations in 1940, then the former employer’s age was 62 years. The same formula applies to the recruiter’s age (2002 minus the SME’s founding year). Then we deducted the SME’s age from the former employer’s age. Firm’s age depicts a reliable measure of the firm’s history and prestige (Hannan, 1998; Henderson, 1999; Singh et al., 1986). The average age of the former employer reaches 91 years in the sample; the average age of the SME reaches 31 years. Therefore, the former employer’s is seven times older than the SME, which places the prestige of the former employer in the historical context.

c. Interfirm network: We used the former employer’s network size proportion to the recruiter’s network. We estimated it by dividing the size of the network ties of the former employer with the network ties of the new employer. The number of alliances of the firm reflects its social structure (Ahuja, 2000; Burt, 1997), and the social network of the firm constitute its prestige through legitimacy development (Human & Provan, 2000).

Control variables

Five sets of control variables are part of the analysis in the study. The following list defines these variables. Some variables capture TMT-specific values; other variables capture the firm’s related variables.

Performance of the former employer

Performance of the SME recruiter

Number of the TMT hired at the SME

Pre-hired functional portfolio of the TMT

Post-migration functional portfolio of the TMT

a. Performance of the former employer measures the return on assets (ROA) of the firm. The ROA value noted from the financial reports of the firm reflects the year of the TMT migration. The ROA of the firm represents the outcome of the TMTs’ decision (Deephouse & Carter, 2005; Williamson & Cable, 2003).

b. Performance of the SME recruiter: ROA (return on assets) at the time of the TMT recruitment. The evidence of ROA on the SME recruiter came from two sources: the stock exchange for listed companies and annual financial reports of the non-listed companies.

c. TMTs hired: The count of the executives hired during the data period. On average, a typical SME recruited three TMTs, ranging from one to 12 recruitments. Two reasons validate this control variable. First, the increased in recruitment events increases the SME’s experience in hiring. Second, more recruitments of TMTs signal growth of the firm because firms that hire TMTs to move from the upstream to downstream in the value chain.

d. Pre-departed functional portfolio: It counts the number of jobs the TMT had held before departure. The terminology of Miles and Snow (1978) helped in identifying the functional portfolio. The following list of functional domains shows pre-departed TMT’s jobs.

R&D in general

Clinical trials

Manufacturing

Marketing/sales

Administration

Legal affairs

Finance and accounting

Corporate development

The highest number of functional portfolios in the pre-departed portfolio varies from 1 to 5 functions. The functional portfolio depicts the importance and the influence of the TMT in the governance structure (Finkelstein, 1992); therefore, we controlled it.

e. Post-departed functional portfolio: The post-departed functional portfolio also counts TMT assigned at the new employer and position. The count values ranged from 1 to 5 functions. We controlled because such functions confound the rewards through the employer’s prestige.

Analysis and Model

As noted earlier, our dependent variable measures the difference between the post-migration rank and the pre-migration rank of the TMT. We deducted the old rank from the new rank of the TMT, and then we centered the resulting variable to the mean. This transformation made it a continuous variable to be suitable for an ordinary least square regression (Cohen et al., 2002). Prior studies have followed these steps to increase the robustness of the results (Greenwood et al., 2005).

\bar{Y} = β_{0} + β_{1} x_{1} + β_{2} x_{2} + β_{3} x_{3} + ... β_{κ} x_{k} + e,

where $\bar{Y}$ = The dependent variable (position reward), $β_{0}$ = the constant, $β_{1} x_{1}$ = the coefficient of the employer’s size, $β_{1} x_{1}$ = the coefficient of the employer’s age, $β_{1} x_{1}$ = the coefficient of employer’s alliances, $β_{κ} x$ = the coefficients of the control variables, and $e$ = the error terms.

Results

Table 1 shows summary statistics in the lower part and inter-variable correlation in the upper part of the table. The inter-variable correlation below 40% suggests that our method conforms to the norms of the field. The norm suggests that the multicollinearity issues arise when the autocorrelation between independent variables is high. We further tested this issue with the variance inflation factor (VIF), and the average VIF (1.39) meets the convention that the VIF should remain below 10 (Cohen et al., 2002).

Table 1.

Summary and Inter-Variable Correlation (N = 1,485).

Variables	1	2	3	4	5	6	7	8	9
Rank gap	1
Performance of the former employer	.04	1
Performance of the SME	.14***	–.02	1
No. of hired TMTs	–.14***	.08***	–.27***	1
Pre-migration functional portfolio	.03	.08***	–.07***	.04^†	1
Post-migration functional portfolio	–.28***	.01	–.11***	.08***	.16***	1
Relative size of the former employer	.07**	.06**	–.16***	–.01	.05*	–.03	1
Relative age of the former employer	.18***	.19***	.17***	–.13***	.06**	–.06**	.01	1
Social capital of the former employer	.15***	.39***	–.03	.05^†	.14***	.01	.12***	0.39***	1
M	–4.82E–08	–2.13	2434.99	2.90	2.12	1.83	1014.32	13.99	97.65
SD	1.9	34.40	2154.47	2.23	0.88	0.70	6230.01	20.40	68.66
Minimum	–6.3	–296.10	–2409.56	1	1	1	1	0.12	1
Maximum	4.7	83.80	4257	12	5	5	115600	175	243

Note. TMTs = top management teams; SME = small and medium enterprise.

†

p < .1. *p < .05. **p < .01. ***p < .001.

Table 2 shows the regression results in four models. The first model signifies the base-model, making up five control variables. It shows a significant coefficient (p < .001). At the variable level, the coefficient of the performance (ROA) of the former employer is positive and significant (p < .05). Hence, it controls the ROA associated with the human capital of the TMT (Castanias & Helfat, 1991). The ROA of the coefficient of the SME also shows a positive and significant result (p < .001).

Table 2.

Regression Analysis (N = 1,485).

Variables	Model 1	Model 2	Model 3	Model 4
Constant	1.05 (.19)***	0.99 (19)***	0.83 (.19)***	0.63 (.20)***
Performance of the former employer	0.003 (.001)*	0.002 (.001)^†	0.001 (.001)	9.2e-03 (001)
Performance of the SME	8.0e + 04 (2.3e + 4)***	9.0e + 04 (2.3e + 04)***	7.4e + 04 (2.3e+04)***	7.8e + 04 (2.3e+04)***
No. of hired TMTs	–0.09 (.022)***	–0.085 (.22)***	–0.07 (0.23)***	–0.08 (.022)***
Pre-migration functional portfolio	0.18 (.05)***	0.17 (.055)***	0.15 (.054)**	0.13 (.054)**
Post-migration functional portfolio	–0.74 (.068)***	–0.73 (.069)***	–0.72 (.068)***	–0.72 (.068)***
The firm’s age		2.1e + 04 (7.7e–06)**	2.1e + 04 (7.6e–06)**	1.8e + 04 (7.6e–06)**
Relative size of the former employer			0.012 (.002)***	0.008 (.003)***
Social capital of the former employer				0.003 (.001)***
F-statistics	35.22***	30.73	30.32***	28.73***
Adjusted R²	.10	.11	.12	.13
df	5	6	7	8

Note. The dependent variable is the TMT hierarchy centered, 7 = high to 1 = low. TMTs = top management teams; df = degrees of freedom; SME = small and medium enterprise.

†

p < .1. *p < .05. **p < .01. ***p < .001.

The coefficient of the number of TMT hired by a recruiter shows a negative and significant result (p < .001). The negative sign shows that the firms that continued hiring TMTs offer lower rewards. Thus, the number of TMT hired show a negative correlation with the rewards.

The coefficient of the pre-migration functional portfolio of the TMT also shows a positive and significant sign (p < .001). It means that the functional portfolio of the TMT before-recruitment predicts an increased in the after-recruitment reward. The coefficient of the post-migration functional portfolio of the TMT further confirms this assumption with the negative and significant sign (p < .001). These control variables support the need for including them in the analysis.

Model 2 introduces the relative size of the former employer of the TMT. As predicted, the coefficient of the relative size of the former employer to the recruiter firm shows a positive and significant sign (p < .01). This hypothesis translates that the size of the former employer predicts an increase in post-migration rewards. Model 3 introduces the relative age of the source of the TMT. The positive and significant (p < .001) coefficient of age translates that the age of the former employer of the TMT predicts the post-migration rewards.

Model 4 introduces the number of business ties of the former employer of the TMT in the analysis. The model significant (p < .001) for F-statistics = 28.73 and 0.13 adjusted R-square. The R-square improved about 30% from Model 1 to Model 3, for 3 degrees of freedom. We predicted that the number of alliances would predict the post-migration rank of the TMT. The results support the hypothesis with a positive correlation.

Discussion

The extant research on the TMT’s recruitment and rewards rests on two links: the TMT’s technical skills such as human capital and experience or social skills such as network across organizations. It has ignored the link between the TMT’s employer’s prestige and the executive’s post-recruitment rewards. Especially, in high-technology industries, the increased demand for managerial resources and shortage of supply of such managerial resource demands a re-examination of the mobility of senior managers between firms (Williams et al., 2017). Moreover, the decades of research on the link between the manager and organization has established that organization and TMT affect and reflect each other (Hambrick & Mason, 1984). However, most of the research takes a detour away from the employer’s prestige as stock and flow (Frandsen, 2012). This previous research often highlights human capital (Brian et al., 1995) or the social capital of the TMT (Bamford et al., 2006; Messersmith et al., 2014). The human capital argument stops at the explicit-tacit duality (Menz, 2012; Williams et al., 2017), and the social capital argument stops at the relationship between the CEO and other TMT members (Bromiley & Rau, 2016). Rarely, any study has addressed whether the employer’s prestige influences the TMT’s attractiveness in the interfirm hiring and the post-migration rewards.

This question triggered our interest to explore whether former employer’s prestige (size, age, interfirm alliance networks) reflect on the departed TMTs’ new position rewards? We defined the new position as a reward because it rises on the vertical scale in position and in fringe benefits. This phenomenon is apparent in the biotechnology sector more than in other sectors because it contributes to a dual structure of the biopharmaceutical industry. The biopharmaceutical industry has a large number of SMEs and a small number of incumbents pharmaceuticals. The biotechnology firms make 80% of the industry, but they take 20% of the market share. In contrast, incumbent pharmaceutical firms make 20% of the industry, but they take 80% of the market share. In this structure of industry and market share, the SME recruits TMTs from the incumbent in almost all cases. Incumbents promote internally and hire TMTs from other competitors, if at all they do. The appendix at the end shows this path of the TMT migration from incumbents to SMEs.

In this flow of TMTs from the incumbent to the SME, the argument posits that the SME recruiter evaluates the former employer’s prestige in recruiting and rewarding the hired TMT at a new position. Like universities prefer to hire professors from incumbents, SMEs prefer to hire from industry leaders to benefit from the former employers’ prestige in the flow of the TMT between organizations. The recruiter’s attention-based view explains this phenomenon in subtle ways.

First, the context of the decision induces meaning and action (March, 1994). In the current context, the former employer’s prestige contextualizes the TMT’s value for the recruiter’s interpretation. Second, the dominant context and its value attract attention away from the less dominant context (Ocasio, 2011). The dominant context means its importance and relevance to the recruiter. For instance, the high prestige takes the attention of the recruiter from the low-prestige employers, despite the TMT from the two sources have similar stocks of human capital, social capital, and industry experience. To mimic the industrial norms, the recruiter needs to hire TMT from prestigious firms to reduce its uncertainty about the appropriate decisions. We used the former’s employers based on the history, size, and relational structure. These sources of the prestige are observable and comparable.

To test these mechanisms of stock and flow of prestige in the TMT hiring between firms, we used the data on TMTs’ migration in the biopharmaceutical to analyze the rise in post-migration rewards in terms of the new position of the TMT at the new employer. We traced 1,684 interfirm TMTs transition events in which the incumbent pharmaceutical firm serves as the departed position, and the SME recruiter reveals the landed position in this transition. Overall, TMT’s post-migration position shows a higher rank than the pre-migration position. The increased in the new rank of the TMT represents an increase in rewards for two reasons. First, the TMT prefers higher ranks for the carrier advancement in any organization and sector (Messersmith et al., 2014; Veiga, 1983). The incumbent employer lacked those positions, and the TMT moved to the SME. Second, the TMT’s position and financial rewards move in the same direction on the hierarchical scale. This combination of preference for the position of the TMT and related rewards influence the executive’s migration decision.

These two assumptions led us to three measures of the former employer’s prestige in stock and flow during the interfirm hiring: the firm’s size, age, and network ties. The former employer’s size positively correlates with the TMT’s rewards—in this case, the positional change. Because the firm’s size of the firm shows organizational visibility, its reputation, and its leadership power in the industry (Singh et al., 1986), the firm’s size reflects on the TMT’s attraction, recruiter’s attention, and post-migration rewards. Second, the former employer’s age positively correlates with the TMT’s rewards in the evidence. The firm’s age represents the legitimacy of the enterprises because it shows history and provides information to the recruiter for evaluative decisions. Like the spatial visibility associated with the size of the firm, the temporal visibility associated with the firm’s history contributes to the prestige of the organization, and the prestige of the organization flows with the flow of TMTs. Third, the former employer’s network alliance positively correlates with the TMT’s rewards. We used network ties of the firm to support the organizational prestige. Organizational scholars from sociological perspective argue that organizational networks contribute to its prestige through legitimacy and reputation. Like the previous authors suggested that interfirm alliances provide a conduit for knowledge flow (Shane & Cable, 2002), we found a positive link between the former employer’s network ties and the departed executive’s new position rewards.

We make a threefold contribution to the literature on executive migration and rewards in the contextual perspective and institutional theory. First, we add that the context of the former organization matters in the TMT migration. Indeed, the human capital argument takes precedent for its salient position in the recruitment decision making because of its objective and credible measures; the influence of the organizational context occurs in everyday life. Universities recruit professors from prestigious organizations. We observe that recruiters proudly announce newly appoint TMT with two types of historical references: their achievements and their former employers who have some prestige.

Second, our research shows that the prestige flows between firms through TMT’s migration, which supports the institutional theory. This interfirm bridge through the TMT’s movement reveals a new avenue of research. For instance, the interfirm alliance literature explains that the inter-organizational prestige flows between firms through alliances, and different types of alliances induce different prestige signals (Stuart et al., 1999). Likewise, the interfirm endorsement fosters the interfirm prestige when the high-prestige firm endorses a low-prestige firm (Higgins & Gulati, 2003). Based on the analogy that the organizational prestige flows between firms through several types of interaction, we suggest that SMEs anticipate that the TMT’s employer’s prestige will inflow through hiring. In other words, the TMT brings forward part of the prestige from the departed organization to the landed organization. Thus, the TMT forms a bridge between the two nodes when the prestige of the incumbent flows to the SME recruiter.

Third, the study points to the socioeconomic logic in the institutional theory for the decision process of the recruiters as it does in the case of investors (Malik & Huo, 2019). The institutional theory proclaims that other than technical skills, the normative context influences the organizational decision. For instance, evidence shows that SMEs hire from incumbents more than from other SMEs of the same level of the position. The extant research is thin on the prestige of the hiring firm, and it is even thinner on the prestige flow with the movement of the TMT to new employers. Evidence from the stock analyst’s employer’s prestige and investors’ responses support this phenomenon that the organizational prestige reflects on the executives of the firm (Malik & Huo, 2019). Thus, the human capital of the TMT is one component of the institutional explanation; the social component of the organizational status is another one in the TMT’s interfirm migration in the high-technology sectors.

First, the large firm—the usual loser of the TMT—should recognize that the prestige can become liabilities when the TMTs leave the firm. The prestige of the firm becomes liable when its valuable executives leave for competitors in search of career advancement. The inherent structural barriers of the incumbent prevent it from creating positions for its TMTs. Most incumbents develop rigidities, which limit opportunities for the TMTs’ career advancement. The TMT moves to the SME that offers a higher post-migration position and rewards. Unless incumbents deal with this issue of the TMT’s career advancement, the incumbent’s prestige becomes its liabilities—the loss of TMTs.

Second, the research has implications for executives. The executive needs to learn how to translate and signal the value of the employer’s prestige to the future recruiters. Although the TMT loses prestige exchange for high rewards (position), he or she can make up this prestige loss in two ways. On one hand, a higher rank at the new position makes up part of the prestige lost. On the other hand, the TMT improves the prestige of the new employer, which translates into future signals. Prior studies focus on the CEO’s position; this study offers value to all executive positions, providing the migrating TMT with a helping hand that they need to learn and use signals. In other words, it strikes a balance between the loss of the prestige the TMT has with the former employer and the gain of career advancement that the TMT receives at the SME. Third, as elaborated earlier, the study has rich information for the recruiting TMT.

Our study has its limitations. First, our research focuses on the biotechnology sector, which limits its general application across industries and countries. Second, this study has limited data. Because of difficulties of accessing data, we used less than 2,000 observations of TMT migration. Third, this study has a few control variables. For instance, it lacks demographic values of the TMT in the data set. Fourth, this study lacks a causal connection between cross-section design. A longitudinal study can make up these deficiencies. Fifth, this study builds on assumptions but lacks a direct account of the recruiter. Direct interviews with the recruiters may explain the propensity of their evaluation of the former employer’s prestige. Likewise, the welcome speeches of the recruiter after hiring the TMT may reveal their attention to the knowledge resource of the recruited person or the former employer. Thus, this study resolves some issues, and it leaves some questions for future research.

Footnotes

Appendix

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Tariq H. Malik

Chunhui Huo

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Former Employer’s Prestige,the TMT’s Post-Migration Rewards in the Biopharma Industry

Abstract

Keywords

Introduction

Theory and Hypotheses

Organizational Prestige

TMT’s migration and prestige flow

Organizational prestige and TMT’s rewards

Employer’s size and TMT’s rewards

Employer’s age and TMT’s rewards

Employer’s alliance network and TMT’s rewards

Method

Sample and Data

Data Coding

Variables

Dependent variable

Independent variables

Control variables

Analysis and Model

Results

Discussion

Footnotes

Appendix

Declaration of Conflicting Interests

Funding

ORCID iDs

References