ArticlePDF Available

Revisiting the Portability of Performance Paradox: Employee Mobility and the Utilization of Human and Social Capital Resources

February 2020
Academy of Management Journal 63(1):34-63

February 2020
63(1):34-63

DOI:10.5465/amj.2017.0769

Authors:

Joseph Raffiee

University of Southern California

Descriptive Statistics and Pearson Correlations

…

Regression Results of Lobbyist Utilization Measured as Revenue

…

Post Hoc Regression Results of Firm Revenue

…

Figures - uploaded by Joseph Raffiee

Content may be subject to copyright.

Content uploaded by Joseph Raffiee

Content may be subject to copyright.

rAcademy of Management Journal

2020, Vol. 63, No. 1, 34–63.

https://doi.org/10.5465/amj.2017.0769

REVISITING THE PORTABILITY OF PERFORMANCE

PARADOX: EMPLOYEE MOBILITY AND THE UTILIZATION

OF HUMAN AND SOCIAL CAPITAL RESOURCES

JOSEPH RAFFIEE

University of Southern California

HEEJUNG BYUN

Purdue University

This study revisits the portability of performance paradox—the common finding that

external hires fail to replicate prior performance after switching firms—by examining

how the nature of an employee’s human capital and social capital resources relate to the

ease with which external hires can be utilized in an organization’s value creating ac-

tivities. Drawing theoretically from the person–organization fit and social capital lit-

eratures, we theorize that the integration and utilization of external hires will correlate

with two types of human capital resource fit: similarity and complementarity, and two

dimensions of retained social capital resources: internal and external. Using data from

the U.S. lobbying industry and novel empirical estimates of worker–firm fit, we provide

descriptive evidence that employee utilization (performance) decreases post-mobility,

consistent with the portability paradox. However, this relationship attenuates—in

magnitude and duration—when there is human capital resource complementarity (but

not similarity) between the employee and hiring firm or when the employee transfers

social capital resources (internal or external). We also find some evidence that human

capital and social capital function as substitutes, and post hoc analyses suggest the

characteristics of human and social capital which facilitate the utilization of external

hires also correlate with hiring firm performance.

Interorganizational employee mobility is common

in modern employment (Cappelli, 1999, 2015; Nyberg,

2010; Ployhart, 2006). The use of external labor mar-

kets has become ubiquitous as workers and firms

frequently look to outside organizations to find and

fill jobs (Bidwell, 2013). Yet a tension exists in that

growing evidence has suggested that worker per-

formance may be imperfectly portable across firm

boundaries (Groysberg, 2010). Indeed, a number of

studies have provided evidence of a “portability

paradox”—workers frequently experience a decline

in performance upon moving to new firms (Campbell,

Saxton, & Banerjee, 2014; Dokko, Wilk, & Rothbard,

2009; Groysberg & Lee, 2009; Groysberg, Lee, & Nanda,

2008; Huckman & Pisano, 2006) and internal hires

tend to outperform external hires even when exter-

nal hires exhibit stronger signals of general quality

(Bidwell, 2011; DeOrtentiis, Van Iddekinge, Ployhart,

& Heetderks, 2018).

This paper takes a new perspective on the porta-

bility paradox by underscoring that performance

within a firm is implicitly linked to the degree to

which employees can be integrated and utilized in

an organization’s value creating activities. Firms le-

verage employees in value creation efforts by utiliz-

ing the employees’human capital and social capital

resources (Waldman & Spangler, 1989), the use value

of which is context dependent and heterogeneously

distributed across firms (Lazear, 2009). Human cap-

ital resources reflect individual capacities such as

knowledge, skills, abilities, or other characteristics

(KSAOs) accessible by firms for unit-level purposes

(Ployhart,Nyberg, Reilly, & Maltarich, 2014),whereas

social capital resources reflect the resources embed-

ded in relationships utilizable to create economic

advantages (Adler & Kwon, 2002). As a result, external

Both authors contributed equally. This paper benefitted

substantially from the constructive comments provided by

our action editor Anthony Nyberg and three anonymous

AMJ referees, to whom we express our sincerest gratitude.

We also thank Paul Adler, Forrest Briscoe, Rhett Brymer,

Russ Coff, Paul Davis, Martin Ganco, Nan Jia, and David

Kryscynski for helpful comments, as well as participants

at the 2018 Academy of Management Annual Conference

and the Organizations and Strategy seminar at USC. Any

errors remain our own.

written permission. Users may print, download, or email articles for individual use only.

hires should be less likely to replicate prior perfor-

mance if the employer faces frictions that limit its

ability to utilize the employees’human and social

capital in its value creation efforts.

Using this logic as a starting point, this paper re-

visits the portability of performance paradox by de-

veloping and testing a theory that focuses on how

the nature of human and social capital resources re-

late to differences in the ease of employee integration

and utilization by organizations—a first-order effect

that may manifest in individual performance differ-

ences. Our framework is comprehensive in that it de-

lineates human capital resources from social capital

resources and examines both individual and inter-

active effects.

With respect to human capital resources, our the-

ory moves away from the ongoing debate regarding

the dichotomous distinction between human capital

with is firm-specific versus general (Nyberg, Reilly,

Essman, & Rodrigues, 2017), and embraces the idea

“that most specific human capital is actually general

human capital”(Lazear, 2009: 915), the usability of

which depends on its interrelationship and fit with a

firm’s other human capital resources (Campbell,

Coff, & Kryscynski, 2012a; Ployhart et al., 2014).1

We draw theoretically from the person–organization

(P–O) fit literature, which underscores two typesof fit:

similarity (or supplementary) and complementarity

(Cable & Edwards, 2004; Kristof, 1996; Muchinsky &

Monahan, 1987).2Human capital resource similarity

occurs when an employee’s KSAOs overlap with the

KSAOs of other employees within a firm, or, as Cable

and Edwards (2004: 822) wrote, “if an organization

hires an employee with skills that replicate those al-

ready widely possessed in its workforce.”In contrast,

human capital resource complementarity occurs

when “the weaknesses or needs of the environment

[organization] are offset by the strength of the indi-

vidual, and vice-versa”(Muchinsky & Monahan,

1987: 271), meaning that the employee’s KSAOs dif-

fer from those in a firm’s workforce, but fill a clear

need and void. Thus, in an economic sense, comple-

mentary means increasing one asset increases the

returns to the other asset (Milgrom & Roberts, 1995).

Using the P–O fit literature as a theoretical backdrop,

we argue that a comprehensive explanation of the

portability paradox must account for employee–firm

human capital resource fit, as this should be associ-

ated with a firm’s ability to integrate and utilize ex-

ternal hires in its value creating activities.

With respectto social capital resources, we leverage

theoretical insights from the social capital literature,

which highlights the distinction between internaland

external social capital resources (Adler& Kwon, 2002;

Kwon & Adler, 2014). The internal versus external

distinction reflects firm boundaries—internal social

capital resources refer to relationships developed

within a firm (e.g., coworkers) (Shaw, Duffy, Johnson,

& Lockhart, 2005) and external social capital re-

sources reflect relationships developed with actors

outside the firm(e.g., customers) (Dyer& Singh, 1998).

Consistent with our logic pertaining to human capital

resources, we theorize that the ability for a firm to

utilize an external hire and integrate him or her into

the firm’s value creating activities will be related to

factors that influence the value of the external hire’s

social capital resources in the new firm. Put frankly,

the value of social relationships with coworkers

(internal) or clients (external), and therefore the

ability of the firm to utilize these resources in its or-

ganizational activities, will be minimal unless these

relationships are retained when employees switch

firms. For completeness, our theoretical framework

also addresses the interactive effects of human and

social capital resources (Dokko & Jiang, 2017). The

relationships proposed in our framework are fore-

shadowed in Figure 1.

We test our theory in the professional services

context of U.S. federal lobbying, exploiting the

reporting requirements of the Lobbying Disclosure

Act of 1995 (LDA) to construct a novel employee–

employer linked database spanning the decade

ending in 2008. An advantage of this context and

data is that it affords us the rare opportunity to ob-

serve mobility while also isolating human capital

1The distinction between firm-specific and general hu-

man capital, as originally articulated by Becker (1964), ex-

plicitly acknowledged that few (if any) skills are either

perfectly specific or general. Yet, as Campbell et al. (2012a)

described, strategy research often evokes the strong as-

sumptionthat firm-specifichuman capital is useless outside

the focal firm, while general human capital is of homoge-

nous value across firms. Our goal is to return to a more

balanced and realistic perspective on human capital re-

sources, where the value in use of general human capital is a

function of its fit with the firm’s other resources (Ployhart

et al., 2014),the result of which can influence heterogeneous

worker productivity between firms (Jovanovic, 1979).

2While the notion of fit in the P–O literature extends to

many dimensions, such as value congruence and auton-

omy preferences (Kristof, 1996), our focus is on fit in terms

of human capital resources. This dimension of fit (or

match) will influence the relative value of the employee’s

human capital resources in a given firm, and therefore that

firm’s ability to utilize these resources for value creation

(Weller, Hymer, Nyberg, & Ebert, 2018).

2020 35Raffiee and Byun

resources as distinct from social capital resources

(Sorenson & Rogan, 2014). The nature of our data

also allows us to overcome the challenges of em-

pirically estimating employee–firm fit (Weller et al.,

2018), demarcating similarity from complemen-

tarity (Oyer & Schaefer, 2010), and differentiating

internal from external social capital (Mawdsley &

Somaya, 2016).

Consistent with the idea of a portability paradox,

our results suggest that mobility is associated with a

decrease in the degree to which an employee is uti-

lized in a firm’s value creating activities, a decrease

that persists for about one year. However, this re-

lationship appears to attenuate—in magnitude and

duration—when there is greater human capital re-

source complementarity or social capital resource

transfer. We also find some evidence that human

capital resource fit and social capital resource transfer

function as substitutes rather than complements. We

find no consistent effect linked to human capital re-

source similarity. In addition, our post hoc explor-

atory analyses further exploit the richness of our data

to investigate how the integration and utilization of

external hires into firms may manifest in firm-level

outcomes (Ployhart & Moliterno, 2011), thereby add-

ing to recent work linking the dynamics of human

capital resources and external sourcing with unit-

level outcomes (e.g., DeOrtentiis et al., 2018; Hale,

Ployhart, & Shepherd, 2016). While the effect sizes

of our analysis are modest, theyunderscore a number

of implications for employees and firms.

This study makes several contributions to theory.

Our study responds to the call of Groysberg (2010),

who urged researchers to examine when, why, and

to what degree performance is portable across firms.

We tackle this call by shifting our attention to factors

linked to heterogeneity in firms’ability to utilize

employees in their value creating activities, stressing

that performance is unlikely to be replicable when

firms face frictions integrating external hires. By do-

ing so, we advance existing theory by moving away

from the predominant explanation of firm-specific

human capital (Huckman & Pisano, 2006), and un-

derscore the importance of accounting for general

human capital resource fit (Ployhart et al., 2014) as

well as the main and interactive effects of retained

social capital resources (Mawdsley & Somaya, 2016).

While we make no causal claims, our study allows

us to provide a fresh but complementary perspec-

tive on the portability paradox, and our post hoc

tests add further contribution by linking our the-

ory of utilization to firm-level outcomes (Ployhart &

Moliterno, 2011).

Empirically, our contribution is twofold. First, we

disaggregate human from social capital resources,

thereby allowing us to estimate individual and in-

teractive effects (Byun, Frake, & Agarwal, 2018a).

Second, our study is one of the few to empirically

estimate employee–firm fit (Ployhart & Cragun, 2017;

Weller et al., 2018) and distinguish similarity from

complementarity (Kim & Finkelstein, 2009). Accord-

ingly, our study adds to the strategy literature, where

FIGURE 1

Conceptual Model of the Individual and Interactive Effects of Human and Social Capital Resources on the

Utilization of Employees in Organizational Activities

(Hypothesis 2)

–

(Hypothesis 5a)

–

(Hypothesis 5b)

–

(Hypothesis 6a)

–

(Baseline ex

ectation based on findin

s in

rior research)

Employee

Mobility

Employee

Utilization

Human Capital

Resource

Similarity

Human Capital

Resource

Complementarity

(Hypothesis 1) +

(Hypothesis 4)

(Hypothesis 3)

–

(Hypothesis 6b)

Internal and External

Social Capital

Resource Transfer

36 FebruaryAcademy of Management Journal

these constructs are often conflated (cf. Ethiraj &

Garg, 2012; Kim & Finkelstein, 2009), and to the

personnel literature, where employee–firm comple-

mentarity or match quality is rarely specified con-

ceptually or measured empirically (Jackson, 2013;

Oyer & Schaefer, 2010).

Finally, our study contributes to practice by

underscoring that managers should be cognizant

of the differences between human capital resource

complementarity versus similarity. Managers may

also consider recruiting for either human capital re-

sources or social capital resources, as our results

provide some evidence that there may be decreasing

returns to recruiting both. Understanding these nu-

ances can be quite meaningful, as our post hoc tests

suggest that these factors correlate with subsequent

firm performance.

THEORETICAL FRAMEWORK

AND HYPOTHESES

While it used to be standard practice for firms to

use internal labor markets to fill jobs, the use of

external labor markets has become quite common

(Bidwell, 2013). For example, Cappelli (2015) re-

ported that over two-thirds of jobs are currently

sourced externally, a sharp contrast to the 1950s

when 90% of jobs were internally filled.3However,

recruiting employees from external labor markets

can be potentially hazardous, as evidence suggests

that external hires often fail to replicate their prior

performance upon joining new firms (Groysberg,

2010). This creates a challenge for human resources

managers. Put frankly, “When organizations think

about ‘poaching’talent, are they going to get what

they want?”(Dokko & Jiang, 2017: 116).

While the majority of work in this area has focused

on employee performance (Groysberg, 2010), our

approach underscores that performance within a firm

is in large part determined by the degree to which an

organization is able to integrate and utilize the em-

ployee in its value creating activities. For example, a

football player may be unable to replicate his prior

performance after being traded to a new team if the

new team faces frictions that make it difficult for the

team to integrate the player intothe team’s offense and

utilize his skills. Thus, understanding the portability

paradox implicitly means understanding factors that

influence the ease with which external hires can be

integrated and utilized in a new organization (Lee &

Allen, 1982).4

Given the documented challenges associated with

integrating external hires into organizations (e.g.,

Groysberg, Lee, & Abrahams, 2010; Morrison, 1993b,

2002; Wang & Zatzick, 2019), our framework starts

with the assumption that the degree to which an em-

ployee is utilized in an organization’s activities will,

on average, decrease following a move to a new firm.

This assumption is consistent with the portability

paradox, which is well-accepted in the management

literature (Dokko & Jiang, 2017).5Anchoring our logic

in the idea that firms primarily utilize an employee’s

human and social capital resources in value creating

activities (Waldman & Spangler, 1989), we develop a

theoretical framework to identify contextual condi-

tions where these resources can be more easily utilized

by hiring firms in value creation efforts.

Human Capital Resources

Human capital resources refer to individual KSAOs

that can be accessed by firms for unit-level purposes

(Ployhart et al., 2014). According to human capital

theory (Becker, 1964), a key distinction is between

human capital, which is firm-specific, versus human

capital, which is general. As employees work in firms

they make investments in firm-specific knowledge,

which reflects an understanding of organizational

3We also note that labor flow estimates using census

data suggest that overall labor market fluidity in the

U.S. economy has declined over the past few decades

(Davis & Haltiwanger, 2014). These macro trends warrant

further investigation.

4While performance itself is distinct from utilization,

we operate under the assumption that the two are typically

linked and positively correlated. For example, in our

football example, a wide receiver will have a hard time

performing at a high level (e.g., receiving yards or touch-

downs) if the team does not integrate the player into the

offense and utilize him in the passing scheme. Likewise,

professional basketball has developed advanced statistics

designed to measure “usage rate,”which estimates the

percentage of plays run by a team for a specific player who

is on the floor. The idea is that a number of performance

statistics will be linked to usage rate.

5While some studies have suggested a positive re-

lationship between mobility and performance (e.g., Hoisl,

2009; Tartari, Di Lorenzo, & Campbell, Forthcoming), the

general consensus is that mobility is associated with at

least a temporary dip in performance (e.g., Fernandez-

Zubieta, Geuna, & Lawson, 2015; Van Heeringen &

Dijkwel, 1987). We adopt that assumption here with re-

spect to employee integration, which we argue is necessary

step in understanding potential differences in employee

performance across firms.

2020 37Raffiee and Byun

procedures and policies (Raffiee & Coff, 2016). This

knowledge has little value outside the firm but is often

necessary in order for the employee’s other human

capital to be effectively utilized in the firm’svalue

creating activities (Molloy & Barney, 2015). When

employees switch firms, not only does their existing

firm-specific knowledge become irrelevant, but they

must make new investments to learn about their new

organization, a process which creates barriers that

slow the integration and utilization of external hires

(Lee & Allen, 1982).

Yet the ability to integrate an employee into an or-

ganization will also relate to the characteristics of the

employee’s general human capital—human capital

that is not specific to any firm. Although prior work

has often assumed that the value of general human

capital is homogenous across firms (Campbell et al.,

2012a), the usability of general human capital re-

sources depends on its fit with the firm’s other re-

sources (Nyberg et al., 2017). Thus, the ability for

firms to integrate and utilize external hires in firm

activities should depend on how the employee’s

general human capital “fits”with the firm’s other re-

sources (Weller et al., 2018). Better fit should allow

the firm to better utilize the employee, which may

lead to cross-firm productivity differences.6

To identify types of fit, we turn to the P–O fit liter-

ature (Edwards, 2008; Kristof, 1996; Kristof‐Brown,

Zimmerman, & Johnson, 2005). This literature has

underscored two key dimensions of P–Ofit:similarity

(or supplementary) and complementarity (Cable &

Edwards, 2004). Given its origins in organizational

behavior research (Muchinsky & Monahan, 1987), the

P–O fit literature has typically focused on subjective

dimensions of fit, such as autonomy preferences or

organizational culture, rather than objective forms of

fit in terms of human capital resources (Kristof, 1996).

This is in part because measuring human capital re-

source fit is challenging (Ployhart & Cragun, 2017),

and so the majority of extant P–O fit work has focused

on fit dimensions that can be accurately accessed via

self-reports (cf. Weller et al., 2018).

We divert from this to focus on human capital re-

source fit. Given that human capital is comprised of

multiple dimensions (Ployhart et al., 2014), we focus

our attention on fit with respect to the dimension of

human capital resources that are central to a firm’s

value creating process. For example, legal specialties in

the legal sector (Eckardt, Skaggs, & Lepak, 2018), prac-

tice areas in management consulting (Anand, Gardner,

& Morris, 2007), and issue expertise in government

lobbying (Byun et al., 2018a), all represent key inputs to

services rendered and therefore play a central role in

value creation. Thus, even if employees face barriers

to integration due to firm-specific skills (Groysberg,

2010), fit in terms of general human capital resources

may lower these frictions and ease the ability for ex-

ternal hires to be utilized in organizational activities.

Human capital resource similarity. Human capi-

tal resource similarity between an employee and firm

refers to the degree to which an employee’s human

capital resources overlap with the human capital re-

sources embedded within a given firm (Muchinsky &

Monahan, 1987). In other words, fit in terms of similarity

means an employee’s general human capital resources

supplement the general human capital resources of

employees within the firm (Cable & Edwards, 2004). As

an example, similarity in fit would occur if a lawyer who

does bankruptcy law works for a law firm that special-

izes in bankruptcy proceedings—the lawyer’sexpertise

is similar to and supplements the expertise of the firm

and the firm’s other lawyers.

Our argument is that greater fit in terms of human

capital resource similarity should make it easier for

the firm to integrate and utilize an external hire’s

human capital resources, even if barriers to integra-

tion still exist due to firm-specific skills. The idea is

that with greater human capital resource similarity,

the ease with which the recipient firm can insert the

employee into existing projects should increase be-

cause the employee’s KSAOs will be similar to the

core resources utilized by the recipient firm to create

value. For example, a lawyer who specializes in

bankruptcy law should face less friction in contrib-

uting to value creation if the lawyer joins a law firm

that focuses on bankruptcy, relative to a joining a law

firm specializing in family law. In the former case,

the lawyer’s skills map clearly to the capability of the

firm and the work the firm is engaged in.

6It is important to note that prior work has recognized

that the portability of performance may depend on the

characteristics of the recipient firm, particularly firm “ca-

pabilities.”For example, Groysberg et al. (2008) showed

that investment analysts who move to firms with better

capabilities—essentially those who join a premier “bulge

bracket”investment bank, such as Goldman Sachs or

Morgan Stanley—do not experience a decrease in perfor-

mance. Allison and Long (1990) showed that academics

who join more prestigious departments tend to be more

productive after moving, whereas the productivity of those

who join less prestigious departments declines. Tartari

et al. (Forthcoming) found that scientists perform better

when moving to departments with greater endowments.

Note also that the idea of heterogeneous value of workers to

firms is central to assortative labor market matching

models (Jovanovic, 1979).

38 FebruaryAcademy of Management Journal

Accordingly, even if the employee needs to get up

to speed because their specific skills are no longer of

value (e.g., they need to learn new routines), their

general human capital will be more applicable in

the new firm (Ployhart et al., 2014). Thus, while

mobility may be associated with an average de-

crease in terms of employee integration and utili-

zation, similarity in terms of general human capital

resources should at least mitigate this decline (cf. an

employee whose human capital resources are dis-

similar and unrelated). Indeed, this logic is consis-

tent with the result reported by Groysberg and Lee

(2009) that investment analyst performance does

not suffer when analysts join investment banks to

execute a strategy of exploitation (area of invest-

ments they know) rather than exploration (area of

investments that is new to them). Simply put, be-

cause similarity means that the employee’shuman

capital resources supplement what the firm is al-

ready doing (Cable & Edwards, 2004), we expect less

friction in incorporating these employees into value

creating activities.

Hypothesis 1. The negative relationship between

employee mobility and employee utilization in orga-

nizational activities will weaken when there is greater

human capital resource similarity between the em-

ployee and the hiring firm.

Human capital resource complementarity. Com-

plementarity fit in terms of human capital re-

sources differs fundamentally from similarity in

that complementarity involves situations where

an employee’s human capital resources differ from

the human capital resources possessed by a firm

(Muchinsky & Monahan, 1987). However, the dif-

ferences are beneficial in that the employee’s hu-

man capital resources address a limitation or void

in terms of the firm’s human capital resources

(Cable & Edwards, 2004). Thus, while similarity

can be thought of as human capital overlap (e.g.,

focusing on the same things) (Kristof, 1996),

complementarity exists when the employee and

firm possess distinct human capital resources, that,

when combined, have the potential to create an

amount of value that is greater than the sum of the

individual parts (e.g., focusing on different but re-

lated things) (Ethiraj & Garg, 2012). Interestingly,

although complementarity is central to the idea of

assortative matching in labor markets, it is impor-

tant to note that “most of this literature simply as-

sumes a complementarity between, say, firm size

and employee ability, and goes on to derive impli-

cations or equilibrium matching”(Oyer & Schaefer,

2010: 21), and, as Jackson (2013) wrote, what con-

stitutes complementarity has rarely been concep-

tually specified or empirically measured in existing

work.7

In terms of determining the ease with which a firm

can integrate and utilize an employee’s human cap-

ital resources, complementarity between a worker

and firm is beneficial because complementarity

means the employee possesses human capital re-

sources that address a weakness and need of the firm

(Edwards, 2008). This does not mean that the firm

will not face frictions and barriers to employee in-

tegration, as firm-specific skills are still relevant.

Rather, when there is a high level of complementar-

ity between a worker and firm, the frictions to in-

tegrate the employee into the firm and utilize the

employee for value creation should weaken because

the “employee has a skill set that an organization

requires”(Cable & Edwards, 2004: 822). Thus, high

complementarity suggests that there should be

plenty of ways in which an external hire can be uti-

lized in the firm’s value creating activities, because

the employee’s skills fulfill an existing weakness.

Consider an example in the legal sector. If clients

who enlist lawyers for patent prosecution also tend

to hire lawyers for patent litigation work, then the

skills of a patent litigation attorney who joins a

law firm that focuses on patent prosecution but has

clients who need patent litigation work should be

relatively easy for the firm to utilize—the firm can

integrate the lawyer into its existing client business

and use the lawyer’s expertise to serve its client’s

tangible litigation needs. Again, firms may still face

frictions integrating external hires into organiza-

tional activities when human capital resource

complementarity is high, but a greater degree of

complementarity should weaken these frictions by

making the employees’human capital resources

7For example, Hayes, Oyer, and Schaefer (2006: 161)

reasoned that “coworker complementarity should be pos-

itively related to the amount of time employees have

worked together,”and therefore inferred complementarity

with a proxy that captures the degree of joint tenure

between a group of employees. In a similar fashion,

Palomeras and Melero (2010) inferred inventor comple-

mentarity with a proxy that captures the mean number of

coinventors listed on patents. While these proxies provide

a useful start, they likely capture factors such as similarity,

among other things, in addition to complementarity. Our

empirical approach leverages a unique context in which

we can observe and create direct measures of comple-

mentarity and similarity, thereby allowing us to empiri-

cally disentangle the two.

2020 39Raffiee and Byun

more easily deployable in the new organization

(Muchinsky & Monahan, 1987).

Hypothesis 2. The negative relationship between

employee mobility and employee utilization in orga-

nizational activities will weaken when there is greater

human capital resource complementarity between

the employee and the hiring firm.

Social Capital Resources

Social capital resources are developed over the

course of repeated interactions between parties that

lead to the development of mutual goodwill, trust,

and friendship (Kale, Singh, & Perlmutter, 2000;

Nahapiet & Ghoshal, 1998). Within the social capital

literature, a key distinction has been made between

internal and external social capital (Adler & Kwon,

2002). Internal social capital refers to relationships

developed within a firm (Tsai & Ghoshal, 1998),

whereas external social capital refers to relation-

ships developed outside the firm with external con-

stituents (Dyer & Singh, 1998). In the context of

employee mobility and integrating external hires

into an organization’s value creating activities, both

dimensions are relevant.

Internal social capital resources. As highlighted

above, when individuals switch firms, investments

are needed to understand how the new firm func-

tions (Molloy & Barney, 2015). This notably includes

an understanding of the firm’s social landscape that

often occurs through the development of coworker

relationships (Lazear, 2009). This reflects internal

social capital (Adler & Kwon, 2002).

Scholars have long highlighted the importance of

internal social capital as a key input to individual

and collective performance outcomes (Boudreau

& Berger, 1985; Huckman, Staats, & Upton, 2009;

Shaw et al., 2005). Internal social capital built

through repeated interaction with coworkers leads

to coworker familiarity (Huckman et al., 2009),

more effective coordination and communication

(Edmondson, Bohmer, & Pisano, 2001; Reagans,

Argote, & Brooks, 2005), and the development of

transactive memory systems—effectively knowing

who knows what within a group or organization

(Argote & Guo, 2016; Ren & Argote, 2011; Wegner,

1987; Wegner, Giuliano, & Hertel, 1985). This leads

to the development of team-specific capital, the

loss of which can adversely impact the productivity

of workers (Jaravel, Petkova, & Bell, 2018).

When employees switch firms, the value of these

resources can deteriorate (Huckman & Pisano, 2006).

Not only is the employee’s internal social capital

from their prior firm of little value in the new orga-

nization, but the employee must also invest in new

relationships within the hiring firm (Morrison,

1993b). This takes time and adds to the difficulty of

integrating external hires into new firms (Wang &

Zatzick, 2019). That said, a hiring firm may be able to

utilize the benefits of an external hire’s prior invest-

ments in internal social capital if it can be retained

when the employee switches firms (Mawdsley &

Somaya, 2016). One way employees can retain the

benefits of coworker relationships is to move as

group—i.e., “comobility”(Campbell et al., 2014; Marx

& Timmermans, 2017). Comobility allows workers to

preserve the value linked to joint experience, trans-

active memory, and coworker-specific knowledge

(Groysberg & Lee, 2009).

It follows that the transfer of internal social capital

resources via comobility should make it relatively

easier for firms to utilize external hires in value cre-

ating activities, even if the typical barriers to in-

tegrating external hires remain. This is because

comobility allows workers to maintain local fit at the

group level (Kristof‐Brown et al., 2005), and so the

hiring firm is bringing in a unit that better un-

derstands how to effectively communicate and work

together (Shaw et al., 2005).8In contrast, when in-

ternal social capital is not retained, external hires

would not only need to make investments in the new

firm’s procedures, but also make larger investments

to develop relationships and an understanding of

their new colleagues (Molloy & Barney, 2015). At a

minimum, this will increase the amount of time it

takes for the employee to become socialized and

fully integrated into the firm (Lee & Allen, 1982;

Morrison, 1993a, 1993b). Thus, even if external hires

still face a learning curve getting up to speed (Wang

& Zatzick, 2019), the preservation of internal social

capital should make it easier for employees to over-

come these frictions by harnessing the benefits

8While we focus on comobility as a means by which

internal social capital is retained, in certain industries the

value of internal social capital may be retained and lever-

aged without comobility. One key example would be aca-

demia, where universities and academic departments

create value by creating knowledge. If an externally hired

professor is able to retain his or her coauthorship patterns

with prior colleagues, then this would mean that these re-

lationships have value in the new university (e.g., Campbell,

Di Lorenzo, & Tartari, 2017). Note also that, in this example,

the ability to retain internal social capital, even if it is located

in the professor’s prior institution, should render the pro-

fessor’s fit with his or her new colleagues less important, as

we argue below.

40 FebruaryAcademy of Management Journal

associated with coworker relationships (Groysberg

& Abrahams, 2006).9

Taken together, our arguments suggest that even if

frictions exist with respect to employee integration,

the severity of these frictions, and therefore the bar-

riers to employee utilization, should be weaker when

an external hire’s internal social capital retains value

in the new firm (i.e., through comobility).

Hypothesis 3. The negative relationship between

employee mobility and employee utilization in orga-

nizational activities will weaken when the employee

transfers and retains more internal social capital re-

sources (i.e., comobility).

External social capital resources. In many in-

dustries, employees are responsible for developing

and maintaining relationships with external constit-

uents (Mawdsley & Somaya, 2016). This is particu-

larly so in professional and business service contexts

where the strength and stability of external rela-

tionships are central inputs to firm value creation

(Hitt, Bierman, Shimizu, & Kochhar, 2001; Pennings,

Lee, & van Witteloostuijn, 1998). These relationships

represent external social capital resources (Adler &

Kwon, 2002).

While external social capital can be built with a va-

riety of outside stakeholders (Byun, Raffiee, & Ganco,

2018b), the focus of our theoretical framework is on

external social capital in the form of client relation-

ships (Sorenson & Rogan, 2014). This is because our

theory focuses on the integration and utilization of

employees into value creating activities, and the reve-

nue generated from clients is the main source of value

creation. As employees interact with clients over time,

social capital is built as the employee will develop

an understanding of client-specific norms (Chatain,

2011), make investments in client-specific knowledge

(Mayer, Somaya, & Williamson, 2012), and ultimately

develop client-specific capabilities (Ethiraj, Kale,

Krishnan, & Singh, 2005). This can translate into

economic benefits in the form of continued client

business and revenue generation potential (Carnahan

& Somaya, 2013; Somaya, Williamson, & Lorinkova,

2008).

Yet, much like internal social capital resources,

the value of external social capital resources is called

into question when employees switch firms (Sorenson

& Rogan, 2014)—the value of an employee’sclientre-

lationships will largely depend on whether the cli-

ents choose to follow the employee if the employee

switches firms (Bermiss & Greenbaum, 2016; Ganco,

Honor´

e, & Raffiee, 2019; Raffiee, 2017). If clients

chose not to follow mobile employees, then the de-

gree to which these relationships are utilizable by the

hiring firm should be minimal (Mawdsley & Somaya,

2018). At the same time, when clients do not transfer,

external hires will need to make greater investments

to develop relationships with new clients at the hir-

ing firm (Chatain & Mindruta, 2017). This would

contribute to the frictions firms face when integrat-

ing external hires into the organization, as this would

represent another investment needed for employees

to get up to speed.

More broadly, when external hires bring clients

with them it essentially means that they are bringing

their work (Raffiee, 2017). As a result, even if the firm

faces frictions integrating the employee into the or-

ganization, the fact that the employee will be at least

in part performing work for established clients

means that the employee should be better positioned

to contribute to value creation. In contrast, if external

hires do not bring clients, integration frictions may

be exacerbated as employees will need to engage in

the lengthy process of building social capital and

developing relationships with new clients (Chatain

& Mindruta, 2017).

Hypothesis 4. The negative relationship between em-

ployee mobility and employee utilization in organi-

zational activities will weaken when the employee

transfers and retains more external social capital re-

sources (i.e., client relationships).

The Interactive Effects of Human Capital Resource

Fit and Social Capital Resource Transfer

While the sections above have made the case that

the ease with which external hires are integrated and

utilized by a firm in its value creating activities will

be contingent on humancapital resourcefit (similarity

and complementarity) and social capital resource

transfer (internal and external), our arguments have

9Our logic with respect to integration of employees is

consistent with work on comobility and employee perfor-

mance (Campbell et al., 2014). Indeed, Groysberg et al.

(2008), Groysberg and Lee (2009), and Campbell et al.

(2014) all found that individual performance declines fol-

lowing mobility attenuate when employees move with

colleagues. Similarly, Huckman and Pisano (2006) sug-

gested that cardiac surgeons perform worse in hospitals

where they perform fewer procedures due to unfamiliarity

with the operating staff, and Marx and Timmermans (2017)

found that comobile employees tend earn higher wages

as comobility may preserve coworker-specific skills. Our

focus is on comobility and the integration of employees

and utilization into a new firm, which we argue is linked to

performance.

2020 41Raffiee and Byun

thus far treated human capital and social capital re-

sources independently. Therefore, a natural ques-

tion that arises is how human and social capital

resources interact to influence the ability for hiring

firms to integrate and utilize an external hire in the

firm’s value creating activities (Dokko & Jiang, 2017).

Given that we have argued that both human capital

resource fit and social capital resource transfer

should make it easier for firms to utilize employees,

one may expect a symbiotic effect in that these re-

sources function as complements.

However, a complementary relationship means

that the relative effect of one resource—e.g., human

capital resource fit—becomes stronger (more impor-

tant) in the presence of another resource—e.g., social

capital resource transfer. In contrast, a substitutive

relationship means that the relative effect of one

resource becomes weaker (less important) in the

presence of another resource (e.g., Jia, 2014). Recall

that we argued that human capital fit and social

capital transfer facilitate employee integration via

different mechanisms—mechanisms that, we argue,

will be substitutive rather than complementary in

their interaction.

We begin with the interactive effects between in-

ternal social capital resource transfer and human

capital resource fit. As we argued above, comobility

allows for preservation of the benefits associated

with coworker relationships (Campbell et al., 2014).

In essence, the ability to continue to collaborate with

prior coworkers allows the employees to maintain

local fit at the person-group level (Kristof‐Brown

et al., 2005). Human capital resource fit, in contrast,

facilitates integration and utilization because the

employee’s human capital resources fit with the

human capital the firm utilizes in its value creating

activities (Weller et al., 2018).

Our argument is that when an employee retains

internal social capital via comobility, it should ren-

der human capital resource fit less important. This

is because when there is a greater degree of human

capital resource fit at the employee–firm level, the

firm can utilize the employee for tangible client work

and substantive client tasks (e.g., litigation). This

should make familiarity with coworkers potentially

less important because the employee can focus on

and execute concrete needs (either due to similarity

or complementarity)—they fit well with what the

hiring firm is already doing (Cable & Edwards, 2004).

In contrast, if an employee joins a firm where there

is a lack of human capital resource fit, then the em-

ployee’s human capital is not as easily deployable in

existing work (Cable & Edwards, 2004). As a result,

the benefits of retained joint experience and the

ability to collaborate with prior colleagues should

become more important because the employee’sgen-

eral human capital does not lend itself to straight-

forward utilization in existing and tangible tasks.

Here, the benefits of effective communication (Argote

& Guo, 2016), ability to learn (Reagans et al., 2005),

and ability to adapt to new experiences (Edmondson

et al., 2001; Groysberg & Abrahams, 2006) should be-

come more important as the employee will be joining

a firm that differs from his or her core skills. When

employees do not fit well with the firm they are

joining, then the ability to maintain local fit via

comobility should become more relevant as the firm

deploys the worker into tasks.

In essence, our arguments suggest that the benefits

of preserved internal social capital should be more

important when the employee cannot be easily

inserted into the hiring firm’s existing needs via

human capital resource fit. Likewise, when the em-

ployee is more easily deployable in a firm’s existing

needs, as would be the case with high human capital

resource similarity or complementarity, the benefits

of preserving internal social capital will be less im-

portant as the firm can utilize the employee’s skills

more easily in tangible tasks.

Hypothesis 5. In terms of weakening the negative re-

lationship between mobility and employee utiliza-

tion, human capital resource fit ((a) similarity and (b)

complementarity) will be a substitute for the transfer

of internal social capital resources.

The transfer of external social capital interacts

with human capital resource fit works in a similar

way. The logic behind external social capital re-

source transfer hinges on the idea that mobile em-

ployees will bring their work with them to the

recipient firm (Raffiee, 2017). This allows the em-

ployee to preserve and utilize the investments they

made with respect to client-specific knowledge

(Ethiraj et al., 2005), and reduces the need to make

immediate investments in new client relationships

(Chatain & Mindruta, 2017). In this sense, serving

the employee’s prior clients becomes a central part

of the new organization’s efforts to create value.

Therefore, it follows that when employees transfer

external social capital, the relative importance of

human capital resource fit should weaken. This is

because human capital fit is typically most important

in terms of easing the degree to which an employee

can be utilized in an firm’s existing work (Groysberg

& Lee, 2009), whereas external social capital transfer

facilitates utilization because the employee brings

42 FebruaryAcademy of Management Journal

in additional work (Raffiee, 2017). Again, our argu-

ments suggest that external hires can be integrated into

new firms via two mechanisms: (1) they fit well into the

work the hiring firm is already doing (human capital

resource similarity or complementarity), or (2) they are

able to bring their own work with them (external social

capital resource transfer).10 Accordingly, the greater the

presence of one, the less the importance of the other.

Hypothesis 6. In terms of weakening the negative re-

lationship between mobility and employee utiliza-

tion, human capital resource fit ((a) similarity and (b)

complementarity) will be a substitute for the transfer

of external social capital resources.

METHODS

Context and Data

The empirical context for our study is the U.S. fed-

eral lobbying industry. The federal lobbying industry

exhibits several characteristics that make it a unique

and appropriate arena in which to test our theory. First,

federal lobbying is a professional services industry, a

commonempiricalcontextusedinpriorworkexam-

ining the portability paradox (Groysberg, 2010). Sec-

ond, lobbying firms utilize lobbyists’human capital

and social capital resources to create value (Bertrand,

Bombardini,&Trebbi,2014).Third,reportingre-

quirements afford us the ability to overcome empirical

challenges associated with measuring human capital

fit (Weller et al., 2018) and disentangling human from

social capital resources (Mawdsley & Somaya, 2016).

The data we use is compiled from lobbying dis-

closure reports that are filed with the Senate Office of

Public Records, as required by law via the LDA. The

LDA stipulates that lobbying firms must file lobbying

disclosure reports on a semiannual basis that detail

lobbying activity. Each report contains information

that includes the name of the lobbying firm, client

firm, individual lobbyists, revenue earned, and is-

sues lobbied. We use electronic versions of these

reports to construct a longitudinal database that

tracks all registered lobbyists on a semiannual basis

between 1998 and 2008. The LDA data has been used

by the authorship team in several prior research

studies, albeit with different samples and research

questions. Byun et al. (2018a, 2018b) used a subset of

the data constrained to lobbyists who previously

were congressional staffers, and Raffiee (2017) re-

stricted his sample to mobility events.

Sample Construction

We construct our sample by starting with the uni-

verse of registered U.S. federa l lobbyists between 1998

and 2008 (32,322 unique lobbyists). Since our theory

focuses on employee mobility between firms, we ex-

clude firms with fewer than two lobbyists (typically

self-employed individuals). Given the lag structure,

we drop observations in 1998 but use the data when

constructing cumulative variables. We drop lobbyists

who appear once during the sample period because

including these observations when fixed effects are

nested within multiple clusters can bias statistical

inference (Cameron, Gelbach, & Miller, 2011). The

result is a longitudinal database consisting of 16,255

unique lobbyists across 18 semiannual periods. Our

unit of analysis is lobbyist-semiannual period. Our

final sample consists of an unbalanced panel of

125,657 lobbyist-period observations.

Dependent Variable

The level of employee utilization is measured in

terms of revenue from lobbying activities an individual

lobbyist has participated in. We calculate this as the

dollar sum of all lobbying contracts a given lobbyist

wasassociatedwithinagivenperiodt11, following

prior studies that have analyzed lobbyist revenue in the

context of federal lobbying (Bertrand et al., 2014;

BlanesiVidal,Draca,&Fons-Rosen,2012;Byunetal.,

2018a). We use LN Revenue as our dependent variable

(DV) across all models by taking the natural log of

lobbying revenue. Note that this measure captures the

amount of revenue the lobbyist participates in gener-

ating, not how much the lobbyist is compensated by

the lobbying firm, and therefore should objectively

reflect the extent to which the lobbyist has been in-

tegrated into the firm’s value creation activities.11

Independent Variables

Mobility is measured with a variable that takes the

value of 1 in the first period our data indicates that a

10 We thank two anonymous reviewers for helping us

simplify, clarify, and articulate the substitution logic.

11 As robustness checks, we created two alternative

measures of employee utilization as the ratio of activities a

lobbyist participated in out of the total value creating ac-

tivities in the firm. We use two measures, LN Revenue/

Firm Revenue, a logged value of lobbyist revenue divided

by the firm revenue, and LN No. of Deals/Firm’s No. of

Deals, a logged value of the number of lobbying contracts a

lobbyist participates in out of the total number of lobbying

deals in the firm. These results are reported in the Online

Appendix.

2020 43Raffiee and Byun

lobbyist changes employers, and 0 otherwise. The co-

efficient of this variable, therefore, captures the initial

change in the level of integration individuals experi-

ence when they join a new firm. In later analyses, we

examine how long these changes persist by entering

time dummies before and after mobility events. We

exclude mobility events where the employee founds or

joins a start-up firm, or works directly for a client.

Our measures of human capital resource comple-

mentarity and similarity are calculated based on the

extent to which the issues lobbied by a lobbyist overlap

with issues lobbied by a lobbying firm. Our approach is

based on the assumption that the proximity between

lobbying issues covered by lobbyists and firms repre-

sent human capital fit between a lobbyist and a firm.

We use a method similar to that developed by Bloom,

Schankerman, and Van Reenen (2013), which ac-

counts for knowledge complementarities across patent

classes in measuring technological proximities be-

tween firms. To do so, we first measure knowledge

complementarities between 78 predefined lobbying

issues and create a knowledge-relatedness matrix. We

then use this matrix as a weight in calculating issue-

based proximity between a lobbyist and a firm.

The knowledge-relatedness matrix is constructed

based on issue cooccurrence patterns from clients as

clients usually bundle multiple issues of the 78 pre-

defined issues in a typical lobbying contract made with

a lobbying firm. The underlying assumption in this

approach is that categories that are frequently combined

are revealed preferences of the market, which imply

superior performances for firms that follow that pattern

(Teece, Rumelt, Dosi, & Winter, 1994). For example, a

client may hire a lobbying firm to lobby on issues related

to appropriations and energy; both of these issues

would then be jointly listed on the lobbying report.

Following Breschi, Lissoni, and Malerba (2003), the

knowledge-relatedness matrix Vij is calculated as the

angular distance of the issue cooccurrence vectors:

Vij 5+k51Rik Rjk

ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ

+k51R2

qﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ

+k51R2

where R

equals 1 if issue iappears in a lobbying report k,

and 0 otherwise. In essence, the knowledge-relatedness

matrix Vij captures complementarity between issues in

the sense that a high value of an element implies the

issues iand jare jointly utilized in creating a bundle for

a client to purchase. Mechanically, each element is the

normalized count of lobbying reports that bundles issue

iand issue j. In other words, this reflects the prevalence

that clients bundle distinct issues jointly.

Following Jaffe’s (1986) measure of technological

proximity, we compute the degree of overlap between

a lobbyist’s issue portfolio at time t–1andissuesthe

firm lobbies at time t. This approach enables us to

calculate the knowledge fit between a newly hired

employee and the recipient firm. We adopt an ap-

proach proposed by Bloom et al. (2013) and weight the

Jaffe measure with the knowledge-relatedness matrix:

Firm 2Employee Proximitymn

5fmtVe9

nt 21

ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ

fmtVf9

p ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ

ent 21Ve9

nt 21

where fm5ðfmt1,fmt2,...,fmt78Þdenotes firm m’s

share in each issue out of the firm’s total revenue

at time t, and en5ðent211,ent212,...,ent2178Þrepre-

sents employee n’s share in each issue out of the

lobbyist’s total revenue at time t–1.

Our measures of Firm–employee complementarity

and Firm–employee similarity are calculated by

decomposing the firm–employee proximity mea-

sure into (1) the extent to which the lobbyist’s issue

portfolio creates complementarities with the firm’s

portfolio in the next period, and (2) the degree of

issue overlap between the lobbyist and the firm, re-

spectively. Specifically, we measure Firm–employee

complementarity by replacing diagonal entries of Vij

with zeros, and use off-diagonal entries to weight in

calculating firm–employee proximity. Simply put,

we measure how much of the issues covered by a

lobbyist that do not overlap with the firm create more

value for clients, or, in other words, the degree to

which the issues covered by a lobbyist that do not

overlap with the issues of the firm tend to be bundled

together by clients. To measure Firm–employee sim-

ilarity, we use the unweighted Jaffe proximity mea-

sure, which captures the extent of issue overlap

between the firm and the lobbyist. We decided to use

Jaffe’s proximity for two main reasons. First, Jaffe’s

angular separation measure has a long tradition in

measuring “knowledge”distances, and, since its in-

troduction in 1986, has been the most common way of

measuring technological distances between firms

(McNamee, 2013). More importantly, this measure

provides the flexibility that allows us to weight the

knowledge-relatedness matrix (V) in constructing our

complementarity variable.12 We test Hypotheses 1

12 That said, we also calculated the Euclidean similarity

by subtracting the Euclidian distance from one. As ex-

pected, the two similarity measures are highly correlated

(r50.87). The results with the Euclidian similarity are

reported in the Online Appendix.

44 FebruaryAcademy of Management Journal

and 2 via the interaction terms Mobility 3Similarity

and Mobility 3Complementarity,respectively.

Although our theory is descriptive and not causal,

we exploit an exogenous variation in the comple-

mentarity measure to check the robustness of our

findings. Due to macro changes in the political envi-

ronment, issue cooccurrence patterns can unexpect-

edly change year to year. For example, the likelihood

of bundling immigration issues and defense issues

changed following the expansion of the Homeland

Security issue after the9/11 terrorist attack. Using such

changes in the knowledge-relatedness matrix Vij,

we attempt to measure Exogenous complementarity,

which reflects the changes in Firm–employee com-

plementarity between time tand t11. We gauge the

change at time t11, after the lobbyist has moved,

assuming that the pattern of changes in political

agenda is largely unexpected prior to departure.13

For a measure of internal social capital, we create

Comobility by counting the number of lobbyists who

work with the focal lobbyist at time twhoalsoworked

with the lobbyist at the same firm in time t–1, following

(Campbell et al., 2014; Marx & Timmermans, 2017). By

design, this reflects the number of lobbyists moving

together to a new firm together for mobility events. For

periods of no mobility, this measure captures the

number of coworkers at time tfrom the previous pe-

riod. Thus, this variable will naturally be highly cor-

related with the size of the firm. For robustness, we also

create a ratio variable of comobility by calculating the

ratio of the number of comobility incidents to the

number of coworkers at time t, and present our results

without control variables.14 We test Hypothesis 3 with

the interaction term Mobility 3Comobility and test

Hypotheses 5a and 5b with three-way interaction

terms, Mobility 3Comove 3Similarity and Mobility 3

Comove 3Complementarity, respectively.

To measure external social capital resource trans-

fer, we use Retained client ratio as the ratio of unique

clients the lobbyist retained from period to period.

This is an extension of the client transfer measure

used by Raffiee (2017), but extended to observations

where employee mobility does not occur. We test

Hypothesis 4 with theinteraction Mobility 3Retained

client ratio. We test Hypotheses 6a and 6b with three-

way interaction terms, Mobility 3Retained 3Simi-

larity and Mobility 3Retained 3Complementarity,

respectively.

Control Variables

We include a number of covariates to control for

observables. Because firm-specific human capital

can influence the usability of human capital (Becker,

1964), we include Tenure in lobbying firm, measured

as the number of semiannual periods the lobbyist has

been with the lobbying firm. Revenue, particularly in

service contexts, is related to the clients the em-

ployee serves. Therefore, we include Number of cli-

ent ties, which is a count of the unique clients a

lobbyist serves. In our context, multiple lobbyists

can be listed on a given lobbying contract. If lob-

byists are listed on lobbying contracts with large

teams, it is unclear to what degree they are being

utilized, versus freeriding. Therefore, we control for

Team size, which is measured as the average num-

ber of lobbyists on each contract the focal lobbyist is

on. To control for a potential quadratic effect of team

size, we also include Team size

. Larger firms may

have inherent advantages and have more existing

work to utilize employees in. Therefore, we control

for Firm size with the total number of lobbyists

employed by the firm. Specialization may also re-

late to how employees are utilized (Teodoridis,

2017; Teodoridis, Bikard, & Vakili, 2018), so we

include a Herfindahl–Hirschman Index (HHI) based

on the issue-level concentration of cumulative lob-

bying revenue. Revenue can be influenced by the

competition a lobbyist faces in the industry. There-

fore, we include Competitive overlap, which is de-

fined as the average of the number of lobbyists that

participate in the primary issue the focal lobbyist

works in. Finally, in-house lobbyists may differ from

lobbyists at lobbying firms (Bertrand et al., 2014), so

we control for In-house lobbyist, coded 1 if the lob-

byist works for an interest group.

Empirical Strategy

We test our hypotheses by estimating a series of

ordinary least squares (OLS) panel regressions. All

regressions include lobbyist fixed effects that control

for unobserved time-invariant lobbyist characteris-

tics (e.g., underlying ability) and year fixed effects to

control for the potential cyclical nature of lobbying.

To account for potential serial correlations due to the

nested nature of our error terms, we employ Cameron

et al.’s (2011) two-way cluster-robust estimates of the

variance matrix and calculate Huber–White robust

standard errors clustered both at the individual level

and the firm level. We use Stata’s user-written com-

mand, reghdfe.

13 The results with exogenous complementarity are re-

ported in the Online Appendix.

14 The results with comobility ratio are reported in the

Online Appendix.

2020 45Raffiee and Byun

RESULTS

Table 1 presents descriptive statistics and correla-

tions. Table 2 provides the results of our hypotheses

tests. We report within-unit R-squared and changes in

within-unit R-squared at the bottom of each table.

Whereas the economic significance of our coefficient

effect sizes are not trivial, the increase in the within-

unit variance explained by the addition of the mo-

bility variable and interactions in our subsequent

hypothesis tests is small. This is due in part to the

number of mobility events, which account for just

2% of total observations.

Model 1 presents a baseline model with control

variables only. The coefficient estimate of our mobil-

ity indicator suggests that employees experience a

7.1% decrease in revenue in the period after they

move (b5.071; p,.01). To put this in perspective

for firms, if a firm was expecting an external hire

to generate $100,000 in revenue based on the em-

ployee’s performance in their prior firm, the employee

is predicted to generate only $93,000. To graphically

investigate temporal patterns and duration effects, we

plot the predicted values of logged revenue based on

Model 1 in Figure 2. As Figure 2 depicts, predicted

revenue drops sharply at the time of mobility and re-

covers over the next two periods, on average.

The coefficient estimates of human capital similar-

ity and complementarity are both positive and statis-

tically significant (p,.01). The main effects of our

social capital measures are both insignificant. This is

in part due to our construction of social capital mea-

sures in a dynamic way as previous period counts.

Hypothesis 1 predicts that human capital resource

similarity would mitigate the negative relationship

between mobility and employee utilization. The in-

teraction term Mobility 3Similarity in Model 2 is

positive but not statistically significant (b5.116; p.

.1). The term remains insignificant in our full model

(Model 6). An unreported figure of interaction plots

based on Model 2 graphically confirms that there is

no statistical difference between the “mobility”plot

and “no mobility”plot. Thus, Hypothesis 1 does not

receive support.

Hypothesis 2 posits that human capital resource

complementarity will mitigate the negative relation-

ship between mobility and employee utilization. In

Model 3, the interaction term is positive and statisti-

cally significant (b5.145; p,.05). Accordingly, an

employee with one standard deviation higher com-

plementarity (0.46) upon mobility is associated with

6.67% more revenue. Thus, while an employee with

the mean level of complementarity would experience

a 3.46% decrease in revenue, an employee with one

standard deviation higher complementarity would

enjoy a 3.22% increase in revenue. Figure 4 graphi-

cally displays the form of the interaction by calculating

predicted values of LN revenue for different levels of

complementarity, while holding other variables at

their means. The 95% confidence bars displayed in the

plot show that the difference between groups loses its

statistical significance when complementarity exceeds

0.5. Thus, Hypothesis 2 is supported.

To further facilitate a graphical comparison of tem-

poral patterns, we plot a mean-centered predicted value

of LN revenue for high-complementarity and low-

complementarity groups in Figure 3 based on Model 1

using the split samples above and below the median

value of complementarity. Consistent with Hypothesis

2, Figure 3 depicts a larger drop and slower recovery in

revenue for the low-complementarity group.

Hypothesis 3 posits that the negative relationship

between mobility and employee utilization would be

weaker when the employee retains internal social

capital through comobility. In Models 4 and 6, the

term for Mobility 3Comobility are positive and are

close to reaching statistical significance at conven-

tional levels (b5.004; p5.088). In terms of effect

size, an employee with a one standard deviation

higher number of comobility incidents (15.8) at the

time of mobility will have 6.32% more revenue.

Figure 5 shows that mobility will no longer be asso-

ciated with a decrease in employee utilization when

the employee is hired with more than five previous

coworkers. Thus, we find marginal support for Hy-

pothesis 3.

Hypothesis 4 predicts that the negative relation-

ship between mobility and employee utilization will

weaken when external social capital (clients) is

transferred. The interaction term in Model 5 is pos-

itive and statistically significant (b5.134; p,.05).

This coefficient estimate suggests that an employee

with a one standard deviation higher value of the

retained client ratio variable (0.27) is associated with

3.5% more revenue after mobility. Figure 6 plots the

interaction effect using the estimates in Model 5. The

figure shows that the interaction effect loses its sta-

tistical significance when employees retain more

than 60% of client ties from the previous period . This

result provides support for Hypothesis 4.

Hypotheses 5a and 5b posit that the moderating

effect of human capital resource similarity (Hy-

pothesis 5a) and complementarity (Hypothesis 5b)

on the relationship between mobility and employee

utilization will weaken when internal social capital

is transferred. We test Hypothesis 5a in Model 7 by

46 FebruaryAcademy of Management Journal

TABLE 1

Descriptive Statistics and Pearson Correlations

Variable Mean SD 123456789101112

1. LN Revenue 12.8 1.52 1

2. Mobility 0.02 0.14 20.01 1

3. Firm–Employee Similarity 0.9 0.21 0.14* 20.08* 1

4. Firm–Employee

Complementarity

0.61 0.46 0.11* 20.09* 0.47* 1

5. Retained Client Ratio 0.88 0.27 0.02* 20.27* 0.18* 0.26* 1

6. Comobility 10.4 15.8 0.21* 20.09* 20.44* 20.22* 20.08* 1

7. Team Size 7.46 8.44 0.42* 20.01* 0.13* 0.27* 0.07* 0.31* 1

8. Firm Size 14.2 18.6 0.22* 0.02* 20.47* 20.24* 20.13* 0.95* 0.31* 1

9. Specialization (HHI) 0.3 0.3 20.36* 20.02* 20.06* 20.12* 0.04* 20.11* 20.21* 20.12* 1

10. Tenure in Lobbying Firm 6.71 4.8 0.08* 20.03* 0.01* 20.05* 0.06* 0.04* 20.02* 0.02* 20.08* 1

11. No. of Client Ties 4.15 8.04 0.26* 0.03* 20.03* 20.47* 20.15* 0.17* 20.06* 0.18* 20.1* 0.07* 1

12. In-House Lobbyist 0. 57 0.5 20.12* 0.04* 20.53* 20.94* 20.26* 0.27* 20.28* 0.28* 0.12* 0.03* 0.43* 1

13. Competitive Overlap 1708 844 0.01* 0 0.04* 20.14* 20.01* 0.03* 20.08* 0.02* 20.02* 0.1* 0.13* 0.1*

Note: n 5125,657.

*p,0.05

2020 47Raffiee and Byun

TABLE 2

Regression Results of Lobbyist Utilization Measured as Revenue

DV: LN Revenue Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9 Model 10

Team Size 0.038*** 0.038*** 0.038*** 0.038*** 0.038*** 0.038*** 0.038*** 0.036*** 0.038*** 0.038***

(0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005)

Team Size

20.000*** 20.000*** 20.000*** 20.000*** 20.000*** 20.000*** 20.000*** 20.000*** 20.000*** 20.000***

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Firm Size 0.004*** 0.005*** 0.005*** 0.004*** 0.004*** 0.005*** 0.005*** 0.006*** 0.005*** 0.005***

(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)

Specialization (HHI) 20.265*** 20.265*** 20.266*** 20.265*** 20.264*** 20.265*** 20.265*** 20.268*** 20.263*** 20.264***

(0.062) (0.062) (0.062) (0.062) (0.062) (0.062) (0.062) (0.062) (0.062) (0.062)

Tenure in Lobbying Firm 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000 20.000

(0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002)

No. of Client Ties 0.017*** 0.017*** 0.017*** 0.017*** 0.017*** 0.017*** 0.017*** 0.017*** 0.017*** 0.017***

(0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003)

In-House Lobbyist 20.114*** 20.118*** 20.136*** 20.116*** 20.103** 20.127*** 20.121*** 20.150*** 20.108*** 20.126***

(0.031) (0.031) (0.032) (0.031) (0.032) (0.034) (0.031) (0.032) (0.032) (0.034)

Competitive Overlap 20.000†20.000†20.000* 20.000†20.000†20.000* 20.000†20.000†20.000†20.000*

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Firm–Employee Similarity 0.114** 0.104* 0.110* 0.113** 0.113** 0.104* 0.094* 0.120** 0.072 0.108*

(0.043) (0.043) (0.043) (0.043) (0.043) (0.043) (0.046) (0.041) (0.057) (0.043)

Firm–Employee Comp 0.127*** 0.124*** 0.103*** 0.126*** 0.132*** 0.108*** 0.124*** 0.028 0.129*** 0.073†

(0.028) (0.028) (0.028) (0.028) (0.028) (0.028) (0.027) (0.037) (0.028) (0.037)

Comobility 0.000 20.000 20.000 20.000 20.000 20.000 20.001 20.003* 20.000 20.000

(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)

Retained Client Ratio 0.016 0.017 0.017 0.016 0.008 0.009 0.016 0.008 20.025 20.014

(0.014) (0.014) (0.014) (0.014) (0.014) (0.014) (0.014) (0.014) (0.051) (0.022)

Mobility 20.071** 20.164* 20.123*** 20.078** 20.124*** 20.220** 20.208** 20.186*** 20.288** 20.224***

(0.026) (0.074) (0.033) (0.027) (0.033) (0.076) (0.077) (0.037) (0.104) (0.045)

Mobility 3Similarity 0.116 0.057 0.160†0.205

(0.088) (0.092) (0.092) (0.125)

Mobility 3Complementarity 0.145* 0.133* 0.254*** 0.268**

(0.059) (0.062) (0.064) (0.081)

Mobility 3Comobility 0.004†0.004†0.019** 0.011**

(0.002) (0.002) (0.006) (0.003)

Mobility 3Retained Client 0.134* 0.121* 0.306†0.235**

(0.055) (0.055) (0.172) (0.073)

Comobility 3Sim 0.000

(0.002)

Mobility 3Comove 3Sim 20.020*

(0.008)

Comobility 3Comp 0.009**

(0.003)

Mobility 3Comove 3Comp 20.026***

(0.007)

48 FebruaryAcademy of Management Journal

TABLE 2

(Continued)

DV: LN Revenue Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9 Model 10

Retained Client 3Sim 0.040

(0.055)

Mobility 3Retained 3Sim 20.219

(0.206)

Retained Client 3Comp 0.043

(0.030)

Mobility 3Retained 3Comp 20.289*

(0.130)

Constant 12.243*** 12.250*** 12.274*** 12.239*** 12.242*** 12.267*** 12.271*** 12.314*** 12.279*** 12.292***

(0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003)

Year Fixed Effects? YYYYYYYYYY

Lobbyist Fixed Effects? YYYYYYYYYY

n125657 125657 125657 125657 125657 125657 125657 125657 125657 125657

R-Squared (Within) 0.039 0.039 0.039 0.039 0.039 0.040 0.039 0.040 0.040 0.040

Change in R-Squared (Within)

—0.000 0.001 0.001 0.001 0.001 0.000 0.001 0.001 0.001

Note: Standard errors clustered by lobbyists and firms.

aCompared to Model 1.

†p,0.10

*p,0.05

**p,0.01

***p,0.001

2020 49Raffiee and Byun

estimating Mobility 3Comove 3Similarity. The

coefficient is negative and statistically significant

(b52.020; p,.05), indicating that human capital

similarity and internal social capital are substitutes,

suggesting support for Hypothesis 5a. Given the na-

ture of three-way interactions, we graphically plot

the interaction effects using a split sample approach

rather than the 1or 2one standard deviation ap-

proach we used for our two-way interactions, as split

samples ease interpretability. Figure 7 plots the in-

teraction between mobility and comobility by two

levels of human capital resource similarity (above

and below the median). In the high-similarity con-

dition, there is no statistically significant difference

between mobility and no mobility at all levels of

comobility. In contrast, in the low-similarity condi-

tion, comobility is positively correlated with em-

ployee utilization after mobility. Consistent with

Hypothesis 5a, this indicates that similarity and in-

ternal social capital are substitutes.

In Model 8, we test Hypothesis 5b by estimating

the three-way interaction term for Mobility 3

Comove 3Complementarity, which is negative and

statistically significant (b52.026; p,.001). We

graphically investigate this (Figure 8) using a split

sample approach to human capital resource com-

plementarity (above and below the median). Figure 8

indicates that in the high-complementarity condi-

tion, the confidence intervals between mobility and

no mobility overlap at all levels of comobility. In the

FIGURE 2

Estimated Pre–Post Mobility Revenue Trend

12.72512.712.67512.6512.62512.6

t – 5 t – 4 t – 3 t – 2 t – 1 t t + 1 t + 2 t + 3 t + 4 t + 5

LN Revenue

Semiannual Periods Relative to Mobility

FIGURE 3

Estimated Pre–Post Mobility Revenue Trend by

Complementarity

t – 5 t – 4 t – 3 t – 2 t – 1 t t + 1 t + 2 t + 3 t + 4 t + 5

-.15 -.1 -.05 0 .05

Mean-Centered LN Revenue

Semiannual Periods Relative to Mobility

High Complementarity Low Complementarity

FIGURE 4

Interaction Between Mobility and Complementarity

on Revenue

0.1 .2 .3 .4 .5 .6 .7 .8 .9 1

12.5 12.6 12.7 12.8 12.9

LN Revenue

Firm–Employee Complementarity

No Mobility Mobility

FIGURE 5

Interaction Between Mobility and Comobility

12.6 12.7 12.8 12.9 13 13.1

0510 15 20 25 30

LN Revenue

No. of Comobility Incidents

MobilityNo Mobility

50 FebruaryAcademy of Management Journal

low-complementarity condition, however, greater

comobility is associated with more employee utili-

zation after mobility. This indicates that comple-

mentarity and internal social capital are substitutes,

supporting Hypothesis 5b.

Hypotheses 6a and 6b suggest that the mitigating

effect of human capital resource similarity (H6a) and

complementarity (H6b) on post-mobility employee

utilization declines will weaken when external social

capital is transferred. The coefficient estimate for

Mobility 3Retained 3Similarity in Model 9 is nega-

tive but not statistically significant (b52.219; p..1).

Therefore, we do not find support for Hypothesis 6a.

In Model 10, we estimate the three-way interaction

term for Mobility 3Retained 3Complementarity,

which is negative and statistically significant (b5

2.289; p,.05). We investigate the form of the in-

teraction in Figure 9, which is plotted at high and low

levels of human capital resource complementarity

(above and below the median). As shown in Figure 9,

when there is high complementarity, the relationship

between client retained ratio and LN revenue is vir-

tually the same between mobility and no mobility at

all levels of client retained ratio. In contrast, when

there is low complementarity, employee integration is

easier after mobility when the employee retains more

clients. This provides support for Hypothesis 6b.

Robustness Checks

We performed a number of robustness checks. Given

page constraints, we do not report all our tests here

but provide a summary in Table 3. Across our ro-

bustness checks there are some changes in coefficient

significance levels, but Hypothesis 2 (complementarity)

and Hypothesis 4 (external social capital transfer) receive

consistent support. The substitution effects we hypothe-

sized, however, stand up to the battery of robustness tests

to a weaker degree (which is expected given the nature of

three-way interactions), with Hypotheses 5b and 6b re-

ceiving the most consistent support. Together, our ro-

bustness checks reaffirm that human capital resource

complementarity and external social capital resource

transfer mitigate the negative relationship between mo-

bility and utilization, and suggest that human capital re-

source complementarity is a likely substitute for social

capital resource transfer. The full set of robustness results

are available in the Online Appendix.

Firm-Level Supplemental Analysis

In this section, we exploit the richness of our data to

provide insights that complement our primary empir-

ical analysis. While our theory focused on identifying

FIGURE 6

Interaction Between Mobility and Ratio of Clients

Retained on Revenue

12.6 12.65 12.7 12.75 12.8

0.1 .2 .3 .4 .5 .6 .7 .8 .9 1

LN Revenue

Ratio of Clients Retained

MobilityNo Mobility

FIGURE 7

Interaction Between Mobility and Comobility on

Revenue—High–Low Similarity

0510 15 20 25 30

12 12.5 13 13.5

12.4 12.5 12.6 12.7 12.8 12.9

LN Revenue

High Similarity

Low Similarity

# of Comobility

No Mobility Mobility

2020 51Raffiee and Byun

factors that correlate with the degree to which external

hires are integrated into a firm’s value creating activi-

ties, our goal here is to extend this logic by examining

how integration and utilization of external hires corre-

lates with hiring-firm outcomes. By doing so, we ex-

amine the firm performance implications of our theory.

To that end, we aggregate our individual measures to

the firm and test whether the firm-level analyses yield

patterns consistent with our model.

We construct the sample by aggregating lobbyists by

lobbying firms (excluding in-house lobbyists) for each

semiannual period across the sample period 1999 to

2008. Our firm-level sample consists of 3,137 unique

lobbying firms and 22,836 observations. Our dependent

variable is LN firm revenue, the logged dollar amount of

all lobbying contracts the lobbying firm generates in

each period. Mobility (external hire) is a binary variable

coded 1 when the firm externally hires one or more

lobbyists in the period, and 0 otherwise. We provide

parallel tests of our hypotheses at the firm level by cre-

ating interaction terms between Mobility and four

human capital and social capital measures calcu-

lated as average values among employee of each

firm. Avg firm–employee similarity and Avg firm–

employee complementarity are lobbyist averages of

Firm–employee similarity and Firm–employee com-

plementarity, respectively. As both Comobility and

Retained client ratio are calculated relative to the pre-

vious periods, we take the averages of these variables of

lobbyists who move in creating Avg comobility and Avg

retained client ratio. Thus, Mobility 3Comobility cap-

tures the number of external hires made from the same

source firm. We aggregate all controls in a similar fash-

ion. Firm fixed effects and year fixed effects are included

in all models. Standard errors are clustered by firms.

We present the results in Table 4. Model 1 is a baseline

OLS regression of LN firm revenue. The coefficient esti-

mate of Mobility indicates that an external hiring event is

FIGURE 8

Interaction Between Mobility and Comobility on

Revenue—High–Low Complementarity

0510 15 20 25 30

1312.51311.5

1312.812.612.4

LN RevenueLN Revenue

# of Comobility

High Complementarity

Low Complementarity

No Mobility Mobility

FIGURE 9

Interaction Between Mobility and Ratio of Clients

Retained on Revenue—High–Low

Complementarity

0.1 .2 .3 .4 .5 .6 .7 .8 .9 1

1312.912.812.7

12.712.612.512.4

LN RevenueLN Revenue

Ratio of Clients Retained

High Complementarity

Low Complementarity

No Mobility Mobility

52 FebruaryAcademy of Management Journal

associated with 17.4% more revenue (b5.174; p,

.001). This seemingly high effect size is due to the small

average firm size and multiple comobility events (more

than 25% of mobility events are external hires of more

than one lobbyist). Note that the positive effect of our

mobility indicator is the opposite sign of the mobility

indicator in our lobbyist-level models, something we

return to in our discussion. Models 2 to 4 demonstrate

that the positive association between external hiring

events and firm revenue is stronger when the em-

ployees have high firm–employee similarity (b5.421;

p,.001) and complementarity (b5.681; p,.001),

and when newly joined employees have high internal

or external social capital (b5.151; p,.05 and b5

.479; p,.05). These results are consistent with Hy-

potheses 1 to 4, and further confirm the idea that factors

that increase the relative “use value”of external hires

strengthens the firm performance implications of ex-

ternal hires.

In Models 5 through 8, we estimate the three-way

interaction terms to test whether the substitution ef-

fect in employee integration between human capital

and social capital exists at the firm level. Consistent

with our individual-level results, we find statistically

significant negative coefficients for Mobility 3

Comobility 3Sim,Mobility 3Comobility 3Comp,and

Mobility3Retained 3Sim, which correspond to tests

of Hypotheses 5a, 5b, and 6a, respectively. Taken to-

gether, our firm analysis suggests that hiring externally

is positively associated with firm revenue, and that the

characteristics of human capital and social capital re-

sources that facilitate the integration and utilization of

these hires has implications for firm performance.

DISCUSSION

This study developed a theoretical framework to

explain how the nature of an employee’s human capital

TABLE 3

Alternative Explanations and Robustness Checks

Alternative Explanation Robustness Checks Supported Hypotheses

nAlternative measures of employee integration

that capture the ratio of lobbyist to firm revenue

nDependent variable as the ratio of lobbyist revenue to

firm revenue (Online Appendix Table A1)

1, 2, 4, 5b, 6a, 6b

nDependent variable as the ratio of lobbyist lobbying

deals to the total number of lobbying deals of the firm

(Online Appendix Table A2)

2, 4, 5a, 5b, 6a, 6b

nMobile lobbyists may be different from

nonmobile lobbyists

nCoarsened exact matching based on team size, firm size,

specialization, tenure, client ties, and in-house lobbyist

variables (Online Appendix Table A3)

2, 4, 5b

nSurvivorship bias in revenue trends nSubsample analysis with only lobbyists who appear more

than nine years in our sample (Online Appendix Table A4)

2, 3, 4, 5a, 5b, 6a, 6b

nMobility among freelancing lobbyists

temporally hired

nSubsample analysis with lobbyists whose previous

employer at t–1 and employer at tare both large in size,

employing more than five lobbyists (Online Appendix

Table A5)

2, 3, 4, 5a, 5b

nInvoluntary exits that result in inferior match

quality in the subsequent move

nMobility excluding mobility events after a dissolution

of the previous employer (Online Appendix Table A6)

2, 4, 5a, 5b, 6b

nMobility including voluntarily exits to become an

entrepreneur or to join a startup (Online Appendix

Table A7)

2, 4, 5a, 5b, 6b

nAlternative measure of comobility nComobility measured as the ratio of coworkers from the

previous period to the coworkers in the current period

(Online Appendix Table A8 Models 1–3)

2, 3, 4, 6b

nMeasurement error of firm–employee

similarity and complementarity

nExogenous variation of complementarity (Online

Appendix Table A8 Models 4–6)

2, 3, 4, 5a, 5b

nKnowledge proximity measure, which is a combination

of complementarity and similarity (Online Appendix

Table A9 Models 1–3)

1, 2, 4, 5, 6

nSimilarity measure based on Euclidean distance (Table

A9 Models 4–6)

2, 3, 4, 5b, 6b

nOther concerns nNo control variables included (Online Appendix Table

A10)

2, 4, 5a, 5b, 6b

nStandardized coefficients for independent variables are

reported (Online Appendix Table A11)

2, 3, 4, 5a, 5b, 6b

2020 53Raffiee and Byun

TABLE 4

Post Hoc Regression Results of Firm Revenue

DV: LN Firm Revenue Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8

Firm Size 0.007*** 0.007*** 0.007*** 0.007*** 0.007*** 0.007*** 0.007*** 0.007***

(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)

Firm Entropy 0.467*** 0.466*** 0.466*** 0.466*** 0.463*** 0.465*** 0.465*** 0.466***

(0.023) (0.022) (0.022) (0.022) (0.022) (0.022) (0.022) (0.022)

Firm Age 20.012** 20.012** 20.012** 20.012** 20.011** 20.012** 20.012** 20.012**

(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004)

No. of Client Ties 0.009*** 0.009*** 0.009*** 0.009*** 0.009*** 0.009*** 0.009*** 0.009***

(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)

Firm Competitive Overlap 0.000** 0.000** 0.000** 0.000** 0.000** 0.000** 0.000** 0.000**

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Avg Firm–Employee Similarity 20.985*** 21.065*** 20.986*** 21.057*** 21.087*** 21.007*** 21.065*** 21.006***

(0.111) (0.112) (0.110) (0.111) (0.110) (0.110) (0.112) (0.110)

Avg Firm–Employee Comp 0.220*** 0.162*** 0.205*** 0.163*** 0.204*** 0.156*** 0.198*** 0.163***

(0.041) (0.041) (0.040) (0.041) (0.040) (0.041) (0.040) (0.041)

Avg Comobility 0.225** 0.096 0.061 0.052 0.448*** 0.299** 22.814*** 20.131

(0.084) (0.079) (0.114) (0.115) (0.105) (0.101) (0.741) (0.081)

Avg Retained Client Ratio 0.027* 0.038*** 20.113 20.101 22.416*** 20.267*** 0.047*** 0.039***

(0.011) (0.011) (0.076) (0.076) (0.515) (0.070) (0.011) (0.011)

Mobility (External Hire) 0.174*** 20.319** 0.129*** 20.306** 20.251* 0.018 20.236* 0.040

(0.026) (0.097) (0.025) (0.097) (0.117) (0.033) (0.096) (0.028)

Mobility 3Similarity 0.447*** 0.421*** 0.467** 0.454***

(0.115) (0.114) (0.163) (0.117)

Mobility 3Complementarity 0.840*** 0.681*** 0.920*** 0.735***

(0.128) (0.130) (0.178) (0.135)

Mobility 3Comobility 0.158* 0.151* 2.452*** 0.323***

(0.076) (0.076) (0.519) (0.072)

Mobility 3Retained Client 0.769*** 0.479* 3.626** 0.835**

(0.197) (0.201) (1.129) (0.299)

Comobility 3Sim 2.202***

(0.524)

Mobility 3Comobility 3Sim 22.174***

(0.532)

Comobility 3Comp 0.346*

(0.175)

Mobility 3Comobility 3Comp 20.447*

(0.193)

Retained Client 3Sim 2.810***

(0.772)

Mobility 3Retained 3Sim 22.831*

(1.173)

Retained Client 3Comp 0.193

(0.241)

54 FebruaryAcademy of Management Journal

TABLE 4

(Continued)

DV: LN Firm Revenue Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8

Mobility 3Retained 3Comp 20.421

(0.443)

Constant 12.005*** 12.090*** 12.011*** 12.085*** 12.111*** 12.036*** 12.091*** 12.035***

(0.113) (0.115) (0.113) (0.114) (0.113) (0.113) (0.115) (0.113)

Year Fixed Effects? YYYYYYYY

Firm Fixed Effects? YYYYYYYY

n22836 22836 22836 22836 22836 22836 22836 22836

R-Squared (Within) 0.228 0.233 0.231 0.235 0.232 0.234 0.233 0.234

Change in R-Squared (Within)

—0.005 0.003 0.007 0.004 0.006 0.005 0.006

Note: Standard errors clustered by firms.

aCompared to Model 1.

*p,0.05

**p,0.01

***p,0.001

2020 55Raffiee and Byun

and social capital resources relate to the ease with

which external hires can be integrated and utilized in a

firm’s value creating activities. In doing so, our study

provides a more comprehensive and balanced per-

spective on the portability paradox, thereby making

several contributions to the extant literature.

Theoretical Contributions

This research adds to our theoretical understanding

of the factors that underpin the portability paradox

(Groysberg, 2010). It does so by focusing on the in-

tegration and utilization of employees within orga-

nizations, stressing that performance is unlikely

to be replicated if firms face frictions integrating

external hires in their organizational activities. Our

framework, therefore, provides a fresh perspective on

the portability paradox, the outcome of which serves as

the foundation for several more specific contributions.

While existing theory has largely focused on firm-

specific human capital as the primary culprit explaining

the portability paradox (Groysberg, 2010), we focus

on general human capital resources and how the “fit”

of these resources with the hiring firm may reduce

frictions firms face when integrating external hires.

In doing so, our study contributes by relaxing the as-

sumption that the use value of general human capital is

homogeneous across firms—an assumption that is

embedded in much of the strategy literature (Campbell

et al., 2012a; Morris, Alvarez, Barney, & Molloy, 2017).

Accordingly, we address the calls of Campbell et al.

(2012a: 379), who argued that “the very definition of

general human capital must be reexamined in light of a

world where firms have unique portfolios of resources

and capabilities,”and Mawdsley and Somaya (2016:

92), who noted that “a principal challenge appears to

be that even the general human capital of these in-

dividuals does not deliver performance in a vacuum

and relies critically on other aspects of their human

and relational [social] capital that may not transfer

when they move.”Thus, we add to the growing body of

work questioning firm-specific human capital as a

source of sustainable competitive advantage (Coff &

Raffiee, 2015; Kryscynski & Ulrich, 2015; Molloy &

Barney, 2015), and emphasize a return to a more re-

alistic model where the value of workers is heteroge-

neous to firms (Jovanovic, 1979).

By addressing these calls, our framework implicitly

helps reconcile conceptual frictions between the

management literature on performance portability

(Dokko & Jiang, 2017) and classic models of labor

market matching (Jovanovic, 1979). While the general

idea behind the portability paradox is thatsome skills

are not fully transferable, matching models suggest

that workers often exit firms in search of firms that are

better able to utilize their skills in organizational ac-

tivities (i.e., better match quality) (Jovanovic, 1979).

While we do find a negative relationship between

mobility and employee utilization, a result consistent

with the portability paradox (Groysberg, 2010), we

also find that the negative relationship is relatively

short term in nature and dissipates quickly with better

fit or match quality, a result consistent with labor

market matching models (Jovanovic, 1979). That said,

what constitutes match quality is inherently complex

(Weller et al., 2018), and we find that human capital

resource complementarity, but not similarity, eases

the integration of external hires. We encourage re-

searchers to build on this work by theoretically spec-

ifying and empirically testing for other factors that

impact match quality and facilitate the creation and

capture of value (Weller et al., 2018).

Conceptually, our study also contributes to the

P–O fit literature (e.g., Edwards, 2008; Kristof, 1996;

Muchinsky & Monahan, 1987). While this literature

served as the theoretical backbone and basis for our

emphasis on human capital fit in terms of similarity

and complementarity (Cable & Edwards, 2004), our

study adds to this literature by moving away from fit

on subjective dimensions (Weller et al., 2018). Inter-

estingly, we found that fit in terms of complementar-

ity, but not similarity, appears to mitigate frictions to

integration, a result suggesting that similarity in hu-

man capital resource fit may create redundancies,

whereas complementarity in fit may not. Similarity on

subjective dimensions between workers and firms, for

example preferences for autonomy, may not yield

such patterns but rather be beneficial (Kristof‐Brown

et al., 2005). That said, when coupled with P–O re-

search, our focus on human capital fit underscores

the potential for cross-level interaction effects, as the

benefit of complementarity in terms of human capi-

tal may further depend on subjective fit dimensions

(Ployhart & Cragun, 2017). We encourage future re-

search to investigate this further.

Our study also adds to literature on the portability

paradox by focusing on two dimensions of social

capital resources (Adler & Kwon, 2002). Our results

generally point to the fact that the ability of firms to

utilize employees will be in part influenced by the

employees’ability to retain the value of prior social

capital investments. While this can occur by moving

colleagues or by retaining existing client accounts, it

is also important to underscore that these factors may

have a substitutive relationship with human capital

fit—the benefits of transferring social capital resources

56 FebruaryAcademy of Management Journal

isweakerwhentheemployeejoinsafirmwherethere

is fit in terms of human capital resources, and vice

versa. While we are hesitant to make conclusive

claims about substitution, given that support for this

result varies across our battery of robustness checks,

we do call for more research on this subject.

Our post hoc analyses also generate several con-

tributions to the strategic human capital literature,

which has become increasingly interested in un-

derstanding the antecedents of unit- and firm-level

outcomes (Kim, Kim, Kim, & Byun, 2016; Nyberg,

Moliterno, Hale, & Lepak, 2014; Ployhart & Moliterno,

2011; Ployhart et al., 2014). First, it is important to

emphasizethat we found a positive coefficient for our

external hiring indicator at the firm level. This is

noteworthy because the mobility indicator at the em-

ployee level is negative, suggesting that mobility is

associated with a decrease in the degree to which

employees are utilized by their firm (i.e., the porta-

bility paradox). One speculative explanation for the

disconnect between our individual- and firm-level

analysis is that employees who move firms may be

upgrades to the hiring organization, even if their hu-

man and social capital are utilized to a lesser degree

than in their previous firm. As a result, mobile em-

ployees may see a within-person decrease in the degree

to which they are utilized in their new organization,

but adding the employee may still represent a net

positive for the firm. This potential explanation for

the individual–firm inconsistency underscores the

potential dangers of generalizing findings across

levels. For example, because the portability paradox

suggests that individual employees experience de-

creases in individual performance post-move, this

does not necessarily mean that external hiring will be

negatively associated with firm performance. We

caution against making such generalizations.

Finally, our firm-level analysis adds insights into

the questions of when and how employee turnover

relates to firm performance (Park & Shaw, 2013;

Shaw, 2011). Our analysis underscores how charac-

teristics of external hires and their fit with the hiring

firm relates to firm-level revenue generation of a

potential and likely competitive firm. Thus, em-

ployees’destination and their match with the firm

they join may have implications for source firm

performance through competition effects. This nu-

ance has been almost entirely overlooked in the

Human Resource Management (HRM) literature. For

example, after conducting a meta-analytic review,

Hancock, Allen, Bosco, McDaniel, and Pierce (2013:

597) concluded that “research on the turnover–

performance relationship has rarely examined where

leavers go.”This omission was echoed by Lee, Hom,

Eberly, Li, and Mitchell (2017: 211) who, in developing

a turnover research agenda, “prescribe that scholars

track turnover destinations.”While researchers have

begun to examine differential effects associated with

entrepreneurship (Campbell, Ganco, Franco, & Agarwal,

2012b) or cooperators (Somaya et al., 2008), relative to

“competitive mobility”or within-industry mobility

events, our study alludes to the fact that heterogeneity

in within-category or within-industry effects may be

quite substantial. Indeed, “competing”firms or “rivals”

each have unique resource endowments that will in-

fluence how well they can utilize external hires and

potentially compete against the source firm. We en-

courage future work to examine these nuances.

Empirical Contributions

Our empirical context affords us the unique oppor-

tunity to make several empirical contributions. First,

we add to the literature by empirically parsing human

capital resources from social capital resources. The

ability to do so is noteworthy, because, as Mawdsley

and Somaya (2016: 89) noted, “there has been little

attempt to systematically compare and relate different

dimensions of human and relational [social] capital to

their respective implications for employee mobility,”

in large part because “their inextricable linkages

challenge discernment of individual and interactive

effects”(Byun et al., 2018a: 1806). Our context allowed

us to estimate and isolate the individual and joint ef-

fects of these resources, thereby responding to the call

of Mawdsley and Somaya (2016: 104), whose recent

review underscored that “an important opportunity

for future empirical research... is the careful iden-

tification and delineation of the impacts of different

categories of human and relational [social] capital.”

In addressing this opportunity, our study highlights

the nuanced relationships between human capital,

social capital, and employee mobility—providing

some evidence that human capital and social capital

may function as substitutes in terms of facilitating

the utilization of external hires.

Second, we make an empirical contribution by es-

timating employee–firm fit in terms of human capital

resources. This adds to the literature because, as

Ployhart and Cragun (2017) and Weller et al. (2018)

recently highlighted, empirical studies across disci-

plines have rarely been able to do so. Moreover, esti-

mating human capital resource complementarity

as distinct from human capital resource similar-

ity adds further contribution. Indeed, even though

complementarity is a construct central to management

2020 57Raffiee and Byun

and economic theory (Ethiraj & Garg, 2012), researchers

have often empirically conflated similarity with com-

plementarity (cf. Kim & Finkelstein, 2009). In addition,

complementarity has remained an elusive empirical

construct across literatures, meaning that it is fre-

quently inferred but rarely measured (Haltiwanger,

Lane, & Spletzer, 1999; Oyer & Schaefer, 2010). Exist-

ing attempts to measure complementarity, for exam-

ple, between coworkers, have relied on distant proxies,

such as coworker joint tenure (Hayes et al., 2006) or

average coinventors per patent (Palomeras & Melero,

2010). By utilizing our context to construct measures

of complementarity that use revealed preferences of

clients (i.e., issue bundling), we directly measure ex

ante complementarity in a way that plausibly cap-

tures situations where employees and firms have

distinct but complementary skills (Ethiraj & Garg,

2012). This allows us to compare human capital re-

source complementarity with human capital resource

similarity, which we find to have differing effects

with respect to easing external hire integration.

Managerial and Practical Contributions

Lazlo Bock, the head of Google’s People Operations,

recently commented that firms like Google are well

aware of the challenges associated with integrating

external hires into their organizations; however,

Google and many other firms still predominantly

hire externally (Bock, 2015). Our study offers in-

sights that can aide managers such as Bock in iden-

tifying when external talent can be more easily

integrated into their firm.

First, our paper reiterates that managers should be

prepared to stomach adjustment costs when new

hires join their firm, as it takes time for new workers

to come up to speed (Morrison, 1993b). These ex-

pected frictions are worth reemphasizing because

managers often overestimate their ability to integrate

employees into their workforce (Bidwell & Keller,

2014). Second, our study suggests that firms should

be cognizant of the differences between similarity

and complementarity, and consider prioritizing com-

plementarity over similarity if the ability to quickly

integrate and utilize the employee is the firm’s ob-

jective (DeOrtentiis et al., 2018). Third, managers

also need to be aware that the ability to integrate em-

ployees into firm activities will also relate to how well

external hires can retain the value of their social capi-

tal, either with existing colleagues or with clientele.

Thus, firms may give further consideration to the

benefits of group hiring efforts (Marx & Timmermans,

2017) or lift-outs (Groysberg & Abrahams, 2006).

Similarly, firms may also consider targeting employees

who hold longstanding and exclusive relationships

with clients, as these employees are most likely to

transfer clients if they join a new firm (Bermiss &

Greenbaum, 2016; Raffiee, 2017). That said, firms and

managers should be aware of the potential tradeoffs

associated with recruiting for human capital and social

capital, as we provide some evidence that there may be

diminishing returns to recruiting for both.

Limitations and Future Research

This study is not without limitations. First, there

may be concerns about its generalizability, as lob-

bying is a context with certain idiosyncrasies (Jia,

2018). That said, lobbing shares a number of char-

acteristics with other professional and business ser-

vice contexts, meaning that our findings should, at a

minimum, be fairly generalizable to such service-

based contexts (Byun et al., 2018b). Future research

that investigates mobility and employee utilization

in nonservice contexts would be valued.

Second, employee mobility is an endogenous pro-

cess. As a result, the level of human capital resource fit

and social capital resource transfer are not outcomes of

random processes. While we implemented a Coars-

ened Exact Matching (CEM) approach and utilized an

exogenous variation of human capital resource com-

plementarity, we cannot claim, and therefore caution

against, a causal interpretation of our results. Future

work that randomly manipulates human capital re-

source fit and social capital resource transfer would be

an exciting direction for future work.

Third, while we focused on fit in terms of human

capital, we cannot observe other dimensions of human

capital resources or fully investigate dynamic com-

plexities in the matching process (Weller et al., 2018).

Future work could examine human capital resource fit

as it pertains to other dimensions of human capital or

cross-level interactions with psychological and attitu-

dinal states (Ployhart & Cragun, 2017).

Fourth, while our theory is motivated by the fact

that the integration and utilization of external hires is

a necessary step to explain differences in individual

performance, our data do not allow us to parse out

individual contributions and therefore explicitly

link employee utilization to individual performance.

The unobservability of individual contributions,

and inability to link utilization to individual per-

formance, is a limitation.

Finally, we are unable to observe managerial factors,

such as variation in human resource management

policies, which may correlate with differences in

58 FebruaryAcademy of Management Journal

employee utilization or employee turnover (e.g.,

Maltarich, Nyberg, Reilly, & Martin, 2017; Trevor &

Nyberg, 2008). Human resource management practices

may also moderate the effects of human capital match

quality (Ployhart & Cragun, 2017; Weller et al., 2018).

This underscores the need for future work to continue

to integrate the human resource management and

turnover literature with the strategy literature on

strategic human capital and employee mobility

(Nyberg & Wright, 2015; Ployhart, 2015; Wright, Coff,

& Moliterno, 2014). Our study is one such attempt.

CONCLUSION

This study provides a new perspective on the

common assumption that employee performance

tends to fall after employees switch firms by under-

scoring that employee performance is implicitly

linked to factors that influence a firm’s ability to

utilize the employee in its value creating activities.

While employee mobility is often an endogenous

process, our analysis of employee–employer linked

data in the U.S. federal lobbying industry provides

descriptive evidence suggesting that the ability for

firms to integrate and utilize external hires in their

organizations varies with the type and degree of hu-

man capital resource fit, social capital resources

retained, and the potential interaction between the

two. More specifically, we find that human capital

resource complementarity, but not similarity, eases

employee utilization, as does the retainment of social

capital resources. We also find some evidence that

human capital resource fit and retained social capital

resources function as substitutes. By highlighting

variation in employee utilization as an antecedent to

performance differences across firms, our theoretical

frameworkand empirical analysis provide afresh and

more realistic perspective on the portability paradox.

REFERENCES

Adler, P. S., & Kwon, S.-W. 2002. Social capital: Pros-

pects for a new concept. Academy of Management

Review, 27: 17–40.

Allison, P. D., & Long, J. S. 1990. Departmental effects on

scientific productivity. American Sociological Re-

view, 55: 469–478.

Anand, N., Gardner, H. K., & Morris, T. 2007. Knowledge-

based innovation: Emergence and embedding of new

practice areas in management consulting firms. Acad-

emy of Management Journal, 50: 406–428.

Argote, L., & Guo, J. M. 2016. Routines and transactive

memory systems: Creating, coordinating, retaining, and

transferring knowledge in organizations. Research in

Organizational Behavior,36:65–84.

Becker, G. S. 1964. Human capital: A theoretical and

empirical analysis, with special reference to edu-

cation. Chicago, IL: University of Chicago Press.

Bermiss, Y. S., & Greenbaum, B. E. 2016. Loyal to whom?

The effect of relational embeddedness and managers’

mobility on market tie dissolution. Administrative

Science Quarterly, 6: 254–290.

Bertrand, M., Bombardini, M., & Trebbi, F. 2014. Is it whom

you know or what you know? An empirical assess-

ment of the lobbying process. American Economic

Review, 104: 3885–3920.

Bidwell, M. 2011. Paying more to get less: The effects of

external hiring versus internal mobility. Administra-

tive Science Quarterly, 56: 369–407.

Bidwell, M., & Keller, J. R. 2014. Within or without? How firms

combine internal and external labor markets to fill jobs.

Academy of Management Journal, 37: 1035–1055.

Bidwell, M. J. 2013. What happened to long-term em-

ployment? The role of worker power and environ-

mental turbulence in explaining declines in worker

tenure. Organization Science, 24: 1061–1082.

Blanes i Vidal, J., Draca, M., & Fons-Rosen, C. 2012. Re-

volving door lobbyists. American Economic Review,

102: 3731–3748.

Bloom, N., Schankerman, M., & Van Reenen, J. 2013.

Identifying technology spillovers and product market

rivalry. Econometrica, 81: 1347–1393.

Bock, L. 2015. Work rules!: Insights from inside Google

that will transform how you live and lead. New

York, NY: Twelve.

Boudreau, J. W., & Berger, C. J. 1985. Decision-theoretic utility

analysis applied to employee separations and acquisi-

tions. Journal of Applied Psychology, 70: 581–612.

Breschi, S., Lissoni, F., & Malerba, F. 2003. Knowledge-

relatedness in firm technological diversification. Re-

search Policy, 32: 69–87.

Byun, H., Frake, J., & Agarwal, R. 2018a. Specialization as

insurance: Specialization and social capital in the U.S.

lobbying industry. Strategic Management Journal,39:

1803–1833.

Byun, H., Raffiee, J., & Ganco, M. 2018b. Discontinuities

in the value of relational capital: The effects on em-

ployee entrepreneurship and mobility. Organiza-

tion Science, 30: 1368–1393.

Cable, D. M., & Edwards, J. R. 2004. Complementary and

supplementary fit: A theoretical and empirical inte-

gration. Journal of Applied Psychology, 89: 822–834.

Cameron, A. C., Gelbach, J. B., & Miller, D. L. 2011. Robust

inference with multiway clustering. Journal of Busi-

ness & Economic Statistics, 29: 238–249.

2020 59Raffiee and Byun

Campbell, B. A., Coff, R. W., & Kryscynski, D. 2012a. Re-

thinking competitive advantage from human capital.

Academy of Management Review, 37: 376–395.

Campbell,B.A.,Ganco,M.,Franco, A. M., & Agarwal, R.

2012b. Who leaves, where to, and why worry? employee

mobility, entrepreneurship and effects on source firm

performance. Strategic Management Journal, 33:

65–87.

Campbell, B. A., Saxton, B. M., & Banerjee, P. M. 2014.

Resetting the shot clock: The effect of comobility on

human capital. Journal of Management, 40: 531–556.

Campbell, B. A., Di Lorenzo, F., & Tartari, V. 2017. Cross-

organization collaboration and mobility of knowledge

workers. doi: 10.2139/ssrn.3025497.

Cappelli, P. 1999. The new deal at work: Managing the

market-driven workforce. Cambridge, MA: Harvard

Business Press.

Cappelli, P. 2015. Why we love to hate HR... and what HR

can do about it. Harvard Business Review, 93: 54–61.

Carnahan, S., & Somaya, D. 2013. Alumni effects and re-

lational advantage: The impact on outsourcing when a

buyer hires employees from a supplier’s competitors.

Academy of Management Journal, 56: 1578–1600.

Chatain, O. 2011. Value creation, competition, and per-

formance in buyer‐supplier relationships. Strategic

Management Journal, 32: 76–102.

Chatain, O., & Mindruta, D. 2017. Estimating value creation

from revealed preferences: Application to value‐based

strategies. Strategic Management Journal, 38: 1964–

1985.

Coff, R., & Raffiee, J. 2015. Toward a theory of perceived

firm-specific human capital. Academy of Manage-

ment Perspectives, 29: 326–341.

Davis, S. J., & Haltiwanger, J. 2014. Labor market fluidity

and economic performance (working paper 20479).

Cambridge, MA: National Bureau of Economic Research.

DeOrtentiis, P. S., Van Iddekinge, C. H., Ployhart, R. E., &

Heetderks, T. D. 2018. Build or buy? The individual

and unit-level performance of internally versus ex-

ternally selected managers over time. Journal of Ap-

plied Psychology, 103: 916–928.

Dokko, G., & Jiang, W. 2017. Managing talent across orga-

nizations. In D. G. Collings, K. Mellahi, & W. F. Cascio

(Eds.), The Oxford handbook of talent management,

vol. 115–133. Oxford, U.K.: Oxford University Press.

Dokko, G., Wilk, S. L., & Rothbard, N. P. 2009. Unpacking

prior experience: How career history affects job per-

formance. Organization Science, 20: 51–68.

Dyer, J. H., & Singh, H. 1998. The relational view: Co-

operative strategy and sources of interorganizational

competitive advantage. Academy of Management Re-

view, 23: 660–680.

Eckardt, R., Skaggs, B., & Lepak, D. 2018. An examination

of the firm-level performance impact of cluster hiring

in knowledge-intensive firms. Academy of Manage-

ment Journal, 61: 919–944.

Edmondson, A. C., Bohmer, R. M., & Pisano, G. P. 2001.

Disrupted routines: Team learning and new technol-

ogy implementation in hospitals. Administrative Sci-

ence Quarterly,46:685–716.

Edwards, J. R. 2008. Person–environment fit in organiza-

tions: An assessment of theoretical progress. Academy

of Management Annals,2:167–230.

Ethiraj, S. K., & Garg, P. 2012. The division of gains from

complementarities in human-capital-intensive activ-

ity. Organization Science, 23: 725–742.

Ethiraj, S. K., Kale, P., Krishnan, M. S., & Singh, J. V. 2005.

Where do capabilities come from and how do they

matter? A study in the software services industry.

Strategic Management Journal, 26: 25–45.

Fernandez-Zubieta, A., Geuna, A., & Lawson, C. 2015.

Productivity pay-offs from academic mobility: Should

I stay or should I go? Industrial and Corporate Change,

25: 91–114.

Ganco, M., Honor´

e, F., & Raffiee, J. 2019. Entrepreneurial

team assembly: Knowledge transfer, customer transfer,

and matching models. In S. Matusik & J. Reurer (Eds.),

Oxford handbook of collaboration and entrepreneur-

ship. doi: 10.1093/oxfordhb/9780190633899.013.7.

Groysberg, B. 2010. Chasing stars: The myth of talent and

the portability of performance. Princeton, NJ:

Princeton University Press.

Groysberg, B., & Abrahams, R. 2006. Lift outs: How to ac-

quire a high-functioning team. Harvard Business Re-

view, 84: 133–140.

Groysberg, B., & Lee, L. 2009. Hiring stars and their col-

leagues: Exploration and exploitation in professional

service firms. Organization Science, 20: 740–758.

Groysberg, B., Lee, L., & Abrahams, R. 2010. What it takes to

make “star”hires pay off. MIT Sloan Management

Review, 51: 57–61.

Groysberg, B., Lee, L., & Nanda, A. 2008. Can they take it

with them? The portability of star knowledge workers’

performance. Management Science, 54: 1213–1230.

Hale,D.,Jr.,Ployhart,R.E.,&Shepherd, W. 2016. A two-phase

longitudinal model of a turnover event: Disruption, re-

covery rates, and moderators of collective performance.

Academy of Management Journal, 59: 906–929.

Haltiwanger, J. C., Lane, J. I., & Spletzer, J. 1999. Productivity

differences across employers: The roles of employer

size, age, and human capital. American Economic

Review, 89: 94–98.

Hancock, J. I., Allen, D. G., Bosco, F. A., McDaniel, K. R., &

Pierce, C. A. 2013. Meta-analytic review of employee

60 FebruaryAcademy of Management Journal

turnover as a predictor of firm performance. Journal

of Management, 39: 573–603.

Hayes, R. M., Oyer, P., & Schaefer, S. 2006. Coworker com-

plementarity and the stability of top-management

teams. Journal of Law Economics and Organization,

22: 184–212.

Hitt, M. A., Bierman, L., Shimizu, K., & Kochhar, R. 2001.

Direct and moderating effects of human capital on

strategy and performance in professional service firms:

A resource-based perspective. Academy of Manage-

ment Journal,44:13–29.

Hoisl, K. 2009. Does mobility increase the productivity

of inventors? Journal of Technology Transfer, 34:

212–225.

Huckman, R. S., & Pisano, G. P. 2006. The firm specificity

of individual performance: Evidence from cardiac

surgery. Management Science, 52: 473–488.

Huckman, R. S., Staats, B. R., & Upton, D. M. 2009. Team

familiarity, role experience, and performance: Evi-

dence from Indian software services. Management

Science, 55: 85–100.

Jackson, C. K. 2013. Match quality, worker productivity,

and worker mobility: Direct evidence from teachers.

Review of Economics and Statistics, 95: 1096–1116.

Jaffe, A. B. 1986. Technological opportunity and spillovers

of R&D: Evidence from firms’patents, profits and

market value. American Economic Review, 76:

984–1001.

Jaravel, X., Petkova, N., & Bell, A. 2018. Team-specific

capital and innovation. American Economic Review,

108: 1034–1073.

Jia, N. 2014. Are collective political actions and private

political actions substitutes or complements? Empir-

ical evidence from China’s private sector. Strategic

Management Journal, 35: 292–315.

Jia, N. 2018. The “make and/or buy”decisions of corporate

political lobbying: Integrating the economic efficiency

and legitimacy perspectives. Academy of Manage-

ment Review, 42: 307–326.

Jovanovic, B. 1979. Job matching and the theory of turn-

over. Journal of Political Economy, 87: 972–990.

Kale, P., Singh, H., & Perlmutter, H. 2000. Learning and

protection of proprietary assets in strategic alliances:

Building relational capital. Strategic Management

Journal, 21: 217–237.

Kim, J., & Finkelstein, S. 2009. The effects of strategic and

market complementarity on acquisition performance:

Evidence from the US commercial banking industry,

1989–2001. Strategic Management Journal, 30:

617–646.

Kim, K.-H., Kim, T.-H., Kim, T.-Y., & Byun, H. 2016. Lateral

hiring and the performance of professional service

firms: The moderating effects of leverage ratio. Inter-

national Journal of Human Resource Management,

27: 338–354.

Kristof‐Brown, A. L., Zimmerman, R. D., & Johnson, E. C.

2005. Consequences of individual’s fit at work: A

meta-analysis of person-job, person–organization,

person–group, and person–supervisor fit. Personnel

Psychology, 58: 281–342.

Kristof, A. L. 1996. Person‐organization fit: An integrative

review of its conceptualizations, measurement, and

implications. Personnel Psychology, 49: 1–49.

Kryscynski, D., & Ulrich, D. 2015. Making strategic human

capital relevant: A time sensitive opportunity. Acad-

emy of Management Perspectives, 29: 357–369.

Kwon, S.-W., & Adler, P. S. 2014. Social capital: Matura-

tion of a field of research. Academy of Management

Review, 39: 412–422.

Lazear, E. 2009. Firm-specific human capital: A skill-weights

approach. Journal of Political Economy, 117: 914–940.

Lee, D. M., & Allen, T. J. 1982. Integrating new technical

staff: Implications for acquiring new technology. Man-

agement Science, 28: 1405–1420.

Lee, T. W., Hom, P. W., Eberly, M. B., Li, J. J., & Mitchell,

T. R. 2017. On the next decade of research in voluntary

employee turnover. Academy of Management Per-

spectives, 31: 201–221.

Maltarich, M., Nyberg, A., Reilly, G., & Martin, M. 2017.

Pay-for-performance, sometimes: An interdisciplinary

approach to integrating economic rationality with psy-

chological emotion to predict individual performance.

Academy of Management Journal, 60: 2155–2174.

Marx, M., & Timmermans, B. 2017. Hiring molecules, not

atoms: Comobility and wages. Organization Science,

28: 1115–1133.

Mawdsley, J. K., & Somaya, D. 2016. Employee mobility and

organizational outcomes: An integrative conceptual

framework and research agenda. Journal of Man-

agement, 42: 85–113.

Mawdsley, J. K., & Somaya, D. 2018. Demand-side strategy,

relational advantage, and partner-driven corporate

scope: The case for client-led diversification. Strate-

gic Management Journal, 39: 1834–1859.

Mayer, K., Somaya, D., & Williamson, I. 2012. Firm-specific,

industry-specific and occupational human capital, and

the sourcing of knowledge work. Organization Sci-

ence, 23: 1311–1329.

McNamee, R. C. 2013. Can’t see the forest for the leaves:

Similarity and distance measures for hierarchical

taxonomies with a patent classification example.

Research Policy, 42: 855–873.

Milgrom, P., & Roberts, J. 1995. Complementarities and

fit strategy, structure, and organizational change in

2020 61Raffiee and Byun

manufacturing. Journal of Accounting and Econom-

ics, 19: 179–208.

Molloy, J. C., & Barney, J. B. 2015. Who captures the

value created with human capital? A market-based

view. Academy of Management Perspectives, 29:

309–325.

Morris, S. S., Alvarez, S. A., Barney, J. B., & Molloy, J. C.

2017. Firm‐specific human capital investments as a

signal of general value: Revisiting assumptions about

human capital and how it is managed. Strategic

Management Journal, 38: 912–919.

Morrison, E. W. 1993a. Longitudinal study of the effects

of information seeking on newcomer socialization.

Journal of Applied Psychology, 78: 173–183.

Morrison, E. W. 1993b. Newcomer information-seeking—

Exploring types, modes, sources, and outcomes. Acad-

emy of Management Journal, 36: 557–589.

Morrison, E. W. 2002. Newcomers’relationships: The role

of social network ties during socialization. Academy

of Management Journal, 45: 1149–1160.

Muchinsky, P. M., & Monahan, C. J. 1987. What is person-

environment congruence? Supplementary versus

complementary models of fit. Journal of Vocational

Behavior, 31: 268–277.

Nahapiet, J., & Ghoshal, S. 1998. Social capital, intellectual

capital, and the organizational advantage. Academy

of Management Review, 23: 242–266.

Nyberg, A. 2010. Retaining your high performers: Moder-

ators of the performance–job satisfaction–voluntary

turnover relationship. Journal of Applied Psychol-

ogy, 95: 440–453.

Nyberg, A., Reilly, G., Essman, S., & Rodrigues, J. 2017.

Human capital resources: A call to retire settled de-

bates and to start a few new debates. International

Journal of Human Resource Management, 29: 68–86.

Nyberg, A. J., Moliterno, T. P., Hale, D., & Lepak, D. P. 2014.

Resource-based perspectives on unit-level human

capital a review and integration. Journal of Manage-

ment, 40: 316–346.

Nyberg, A. J., & Wright, P. M. 2015. 50 years of human

capital research: Assessing what we know, exploring

where we go. Academy of Management Perspec-

tives, 29: 287–295.

Oyer, P., & Schaefer, S. 2010. Personnel economics: Hiring

and incentives working paper (15977). Cambrige, MA:

National Bureau of Economic Research.

Palomeras, N., & Melero, E. 2010. Markets for inventors:

Learning-by-hiring as a driver of mobility. Manage-

ment Science, 56: 881–895.

Park, T.-Y., & Shaw, J. D. 2013. Turnover rates and orga-

nizational performance: A meta-analysis. Journal of

Applied Psychology, 98: 268–309.

Pennings, J. M., Lee, K., & van Witteloostuijn, A. 1998.

Human capital, social capital, and firm dissolution.

Academy of Management Journal, 41: 425–440.

Ployhart, R. E. 2006. Staffing in the 21st century: New

challenges and strategic opportunities. Journal of Man-

agement, 32: 868–897.

Ployhart, R. E. 2015. Strategic organizational behavior

(STROBE): The missing voice in the strategic human

capital conversation. Academy of Management Per-

spectives, 29: 342–356.

Ployhart, R. E., & Moliterno, T. P. 2011. Emergence of the

human capital resource: A multilevel model. Acad-

emy of Management Review, 36: 127–150.

Ployhart, R. E., Nyberg, A. J., Reilly, G., & Maltarich, M. A.

2014. Human capital is dead; long live human capital

resources! Journal of Management, 40: 371–398.

Ployhart, R. E., & Cragun, O. R. 2017. Human capital re-

source complementarities. In D. G. Collings, K.

Mellahi, & W. F. Cascio (Eds.), The Oxford handbook

of talent management, vol.115: 134–149. Oxford,

U.K.: Oxford University Press.

Raffiee, J. 2017. Employee mobility and interfirm re-

lationship transfer: Evidence from the mobility and

client attachments of United States federal lobby-

ists, 1998-2014. Strategic Management Journal, 38:

2019–2040.

Raffiee, J., & Coff, R. 2016. Micro-foundations of firm-

specific human capital: When do employees perceive

their skills to be firm-specific? Academy of Manage-

ment Journal, 59: 766–790.

Reagans, R., Argote, L., & Brooks, D. 2005. Individual ex-

perience and experience working together: Predicting

learning rates from knowing who knows what and

knowing how to work together. Management Sci-

ence, 51: 869–881.

Ren, Y., & Argote, L. 2011. Transactive memory systems

1985–2010: An integrative framework of key dimen-

sions, antecedents, and consequences. Academy of

Management Annals, 5: 189–229.

Shaw,J.D.2011.Turnoverratesandorganizationalperfor-

mance: Review, critique, and research agenda. Or-

ganizational Psychology Review,1:187–213.

Shaw, J. D., Duffy, M. K., Johnson, J. L., & Lockhart, D. E.

2005. Turnover, social capital losses, and performance.

Academy of Management Journal, 48: 594–606.

Somaya, D., Williamson, I., & Lorinkova, N. 2008. Gone but

not lost: The different performance impacts of employee

mobility between cooperators versus comp et itors.

Academy of Management Journal, 51: 936–953.

Sorenson, O., & Rogan, M. 2014. (When) do organizations

have social capital? Annual Review of Sociology,

40: 261–280.

62 FebruaryAcademy of Management Journal

Tartari, V., Di Lorenzo, F., & Campbell, B. A. Forthcoming.

“Another roof, another proof”: The impact of mobility

on individual productivity in science. Journal of

Technology Transfer. Published online ahead of print.

Teece, D. J., Rumelt, R., Dosi, G., & Winter, S. 1994. Under-

standing corporate coherence: Theory and evidence. Jour-

nal of Economic Behavior & Organization,23:1–30.

Teodoridis, F. 2017. Generalists, specialists, and the di-

rection of inventive activity. Management Science,

64: 3625–3648.

Teodoridis, F., Bikard, M., & Vakili, K. 2018. Creativity at

the knowledge frontier: The impact of specialization

in fast-and slow-paced domains. Administrative Sci-

ence Quarterly, 64: 894–927.

Trevor, C. O., & Nyberg, A. J. 2008. Keeping your headcount

when all about you are losing theirs: Downsizing, volun-

tary turnover rates, and the moderating role of HR prac-

tices. Academy of Management Journal, 51: 259–276.

Tsai, W., & Ghoshal, S. 1998. Social capital and value

creation: The role of intrafirm networks. Academy of

Management Journal, 41: 464.

Van Heeringen, A., & Dijkwel, P. 1987. The relationships

between age, mobility and scientific productivity. Part

I. Scientometrics, 11: 267–280.

Waldman, D. A., & Spangler, W. D. 1989. Putting together

the pieces: A closer look at the determinants of job

performance. Human Performance,2:29–59.

Wang, T., & Zatzick, C. 2019. Human capital acquisition

and organizational innovation: A temporal perspec-

tive. Academy of Management Journal, 62: 99–116.

Wegner, D. M. 1987. Transactive memory: A contemporary

analysis of the group mind. In B. Mullen & G. R.

Goethals (Eds.), Theories of group behavior:

185–208. New York, NY: Springer-Verlag.

Wegner, D. M., Giuliano, T., & Hertel, P. T. 1985. Cognitive

interdependence in close relationships. In W. J. Ickes

(Ed.), Compatible and incompatible relationships:

253–276. New York, NY: Springer-Verlag.

Weller, I., Hymer, C., Nyberg, A., & Ebert, J. 2018. How

matching creates value: Cogs and wheels for human

capital resources research. Academy of Management

Annals 13: 188–214.

Wright, P. M., Coff, R., & Moliterno, T. P. 2014. Strategic

human capital: Crossing the great divide. Journal of

Management, 40: 353–370.

Joseph Raffiee (joe.raffiee@marshall.usc.edu) is an assistant

professor of strategy in the Management and Organization

Department at the Marshall School of Business, University

of Southern California. He earned his PhD from the Uni-

versity of Wisconsin—Madison. Joe’s research is focused on

understanding the antecedents and consequences of em-

ployee mobility and employee entrepreneurship.

Heejung Byun (byun21@purdue.edu) is an assistant pro-

fessor of management in strategy area at the Krannert

School of Management, Purdue University. He received his

PhD from the University of Maryland, College Park. Heejung’s

research interests are grounded in the embeddedness per-

spective to study issues in diversification, entrepreneurship,

and strategic human capital.

2020 63Raffiee and Byun

Any port in a storm: Emotional stability as a stabilizer for the job performance-voluntary turnover relationship

Article

Full-text available

Feb 2024
J VOCAT BEHAV

The relationship between strategic human resource management, green innovation and environmental performance: a moderated-mediation model

Article

Full-text available

Feb 2024

This study investigates the impact of strategic human resource management (SHRM) on fostering green innovation and enhancing environmental performance among employees in the Asia-Pacific region. In the context of intensifying competition in the industrial sector, it is essential to understand how SHRM influences employees’ innovative capabilities and their alignment with environmental goals. Our research suggests that effective SHRM strategies can significantly increase self-efficacy and stimulate green innovation, thus reinforcing the alignment between individual and organizational environmental objectives. To empirically test these hypotheses, we conducted a survey of 487 employees and used Smart-PLS 4.0 for structural equation modeling. This method allowed us to examine both the mediating and moderating effects within our model. The results indicate that self-efficacy mediates the relationship between SHRM practices and green innovation, while person-organization fit significantly moderates the relationship between green innovation and environmental performance. This study offers novel insights into how SHRM can promote environmental consciousness and innovation within organizations. By underscoring the roles of self-efficacy and person-organization fit, our research enriches the broader scholarly dialog on strategic human resource management and its environmental implications.

Working with stigma: the buffering role of self-compassion

Article

Full-text available

Aug 2023
Asia Pac J Manag

Occupational stigma is often viewed as challenging. Though researchers have proposed several coping strategies, empirical testing on their effectiveness is still insufficient. Focusing on occupational stigma’s negative social evaluation challenges and based on compassion theory, we propose that self-compassion can prompt individuals to craft their stigmatized job cognitively. Specifically, for individuals with higher self-compassion, the negative influence of occupational stigma on cognitive crafting will be weaker. Further, cognitive crafting is positively related to job engagement. Results from a time-lagged field study with 284 employees and their paired 99 leaders supported our hypotheses. Theoretical and practical implications are discussed.

Empirical opportunities for advancing theory and research on strategic human capital

Article

Apr 2024

The strategic human capital conversation is a vibrant research area with many empirical opportunities. In this short editorial, we describe four key research areas that would benefit from empirical advancements: (1) perceptions of mobility prospects and firm-specific human capital theory, (2) firm-specific incentives, (3) emergence of the unit-level human capital resource, and (4) value creation and value capture issues in human capital research. We describe opportunities to validate certain measures, improve existing measures, develop new measures, and replicate initial findings.

Chinese land complex: Hometown ties and corporate land acquisition

Article

Mar 2024
LAND USE POLICY

Social capital and career adaptability: the mediating role of psychological capital

Article

Feb 2024

Purpose This study’s main objective is to determine the extent to which social capital and psychological capital can explain differences in career adaptability among higher education students. Design/methodology/approach The study employed a quantitative approach, utilizing a survey research design. Data were gathered using an online questionnaire completed by 384 fourth-year undergraduate agricultural students in Iran. The inverse square root and multistage sampling methods were used to determine the sample size. The partial least squares-structural equation modelling (PLS-SEM) method examined the associations between latent variables. Findings The results suggest that social and psychological capital significantly influence the career adaptability of agricultural students, highlighting their significance in enhancing career adaptability. Moreover, psychological capital positively mediates the relationship between social capital and career adaptability. Practical implications Agricultural higher education institutions must focus on developing students' social and psychological capital to cultivate career adaptability in agricultural students. Agricultural higher education institutions, for example, should help students develop soft skills. Originality/value This study offers novel insights into the significance of individual resources, such as social and psychological capital, in enhancing the career adaptability of students. In addition, the key contribution of this study is the researchers' empirical evidence that multiple career resources are interconnected (social capital, career adaptability, and psychological capital).

Employee mobility as a knowledge development strategy

Article

Feb 2024
Hum Resource Manag Rev

Gulshan Bibi

Upper Echelon Employment: A Review of the Fundamental Questions Related to the Executive Labor Market

Article

May 2023

The executive labor market (ELM) is a topic of interest that spans several academic fields. The outcomes of the ELM, including executive selection, succession, and compensation, are important considerations as they influence executive decision making and other organizational outcomes. Yet, a comprehensive framework of ELM dynamics currently does not exist. To address this shortcoming, we reviewed the existing literature using five fundamental questions: (1) What executive jobs are available? (2) Who is available to fill executive jobs, and what is valued on the ELM? (3) Who signals interest in the executive jobs? (4) Who gets offered/accepts the executive job, and what is the agreed-upon compensation? (5) How do status and social capital influence ELM outcomes? By answering these questions, our review provides a framework for integrating existing research on the ELM while suggesting avenues for future research.

The impact of client-overlap hiring on PSF client embeddedness

Article

Oct 2023

Professional service firms (PSFs) are commonly perceived to attain success through the acquisition of new clients. However, these firms are not solely reliant on this strategy as PSFs may also achieve competitive advantage by improving their relationships with existing clients. Despite the significance of these established client relationships, limited information exists regarding how PSFs can effectively enhance and utilize them. This study examines how a PSF’s client-related knowledge can be obtained and developed through its hiring practices in order to strengthen relationships with existing clients. Results reveal that when hiring from other PSFs who share similar clients (i.e., client-overlapping PSFs), that this has a positive impact on the firm’s overall relationships with its clients, with the effect being impacted by the firm’s level of practice overlap with the new hires and the degree of co-mobility of the hires.

Performance implications of financial resource allocation in new hiring: the case of major league baseball

Article

Sep 2023
MANAGE DECIS

Purpose Integrating the resource-based view (RBV) with pay dispersion research, the authors examine how the allocation of resources between hiring new employees and compensating current employees, as well as the allocation of resources among new employees, affects organizational performance. Design/methodology/approach The authors use panel data on Major League Baseball teams. The authors also use system generalized method of moments (GMM) estimations to control for the impact of past performance on current performance, unobserved individual heterogeneity and omitted variable bias. Findings The authors find that the larger the portion of the human resources (HR) budget allocated to hiring new employees, the poorer organizational performance becomes unless the focal organization has already significantly underperformed. The authors also find that pay concentration among new employees has a positive impact on organizational performance unless the focal organization has already significantly overperformed. Originality/value This study extends RBV research by examining how resource allocation patterns affect organizational performance, which has rarely been studied. Moreover, by showing the organizational context's significant effect on the outcome of financial allocation for resource acquisition, this study extends both the RBV research and the pay dispersion research.

How Matching Creates Value: Cogs and Wheels for Human Capital Resources Research

Article

Full-text available

Jan 2019

Using selection- and adaptation-based logic, we develop a dynamic matching model to describe how employees are matched with positions to enhance human capital-based value creation. Matching, defined as the process by which individuals are dynamically aligned with organizations and the situations (roles, jobs, tasks, etc.) within them, has historically been examined in silos across a broad range of literatures. Consequently,we know little about how seemingly diverse HR activities, such as recruitment, job design, training, promotions, and terminations, might informeach other through the common lens of matching. Emanating from our review, we integrate relevant literatures to develop a comprehensive matching model (termed the “dynamic matching lifecycle model”). Our model extends prior, more static conceptualizations of matching (like attraction, selection, attrition, or ASA) to include four stages: creation, development, reconfiguration, and termination-based on two broad mechanisms-selection and adaptation. Furthermore,we describe how matching contributes to individual and organizational value creation. By evoking human capital theories, we explain how people and organizations engage in matching across the four stages of the model to create human capital-based value. Our model shows that information and information distribution, organization design, and complementarities play important roles in ensuring successful matching. Promising future research directions are discussed.

Creativity at the Knowledge Frontier: The Impact of Specialization in Fast- and Slow-paced Domains

Article

Full-text available

Jul 2018

Using the impact of the Soviet Union’s collapse on the performance of theoretical mathematicians as a natural experiment, we attempt to resolve the controversy in prior research on whether specialists or generalists have superior creative performance. While many have highlighted generalists’ advantage due to access to a wider set of knowledge components, others have underlined the benefits that specialists can derive from their deep expertise. We argue that this disagreement might be partly driven by the fact that the pace of change in a knowledge domain shapes the relative return from being a specialist or a generalist. We show that generalist scientists performed best when the pace of change was slower and their ability to draw from diverse knowledge domains was an advantage in the field, but specialists gained advantage when the pace of change increased and their deeper expertise allowed them to use new knowledge created at the knowledge frontier. We discuss and test the roles of cognitive mechanisms and of competition for scarce resources. Specifically, we show that specialists became more desirable collaborators when the pace of change was faster, but when the pace of change was slower, generalists were more sought after as collaborators. Overall, our results highlight trade-offs associated with specialization for creative performance.

“Another roof, another proof”: the impact of mobility on individual productivity in science

Article

Full-text available

Feb 2020
J TECHNOL TRANSFER

The mobility of highly skilled employees is seen as a critical way for organizations to transfer knowledge and to improve organizational performance. Yet, the relationship between mobility and individual performance is still largely a theoretical and empirical puzzle. Integrating human capital mobility research and the economics of science literature, we argue that mobility of academics should have a positive effect on individual productivity. Additionally, we argue that this positive effect is strengthened when academics move towards better-endowed institutions. We find support for our predictions using a unique dataset of 348 academics working in biology department in the United Kingdom supplemented with qualitative evidence from a survey of the focal academic researchers. © 2018 Springer Science+Business Media, LLC, part of Springer Nature

Chasing Stars: The Myth of Talent and the Portability of Performance

Book

Apr 2010

Boris Groysberg

Learning and protection of proprietary assets in strategic alliances: building relational capital

Article

Mar 2000
STRATEGIC MANAGE J

One of the main reasons that firms participate in alliances is to learn know‐how and capabilities from their alliance partners. At the same time firms want to protect themselves from the opportunistic behavior of their partner to retain their own core proprietary assets. Most research has generally viewed the achievement of these objectives as mutually exclusive. In contrast, we provide empirical evidence using large‐sample survey data to show that when firms build relational capital in conjunction with an integrative approach to managing conflict, they are able to achieve both objectives simultaneously. Relational capital based on mutual trust and interaction at the individual level between alliance partners creates a basis for learning and know‐how transfer across the exchange interface. At the same time, it curbs opportunistic behavior of alliance partners, thus preventing the leakage of critical know‐how between them. Copyright © 2000 John Wiley & Sons, Ltd.

Discontinuities in the Value of Relational Capital: The Effects on Employee Entrepreneurship and Mobility

Article

Aug 2019

We examine how a discontinuous increase in the value of an employee’s relational capital influences the employee’s mobility and entrepreneurship decisions in professional and business service contexts. Drawing on the unfolding model of voluntary turnover, we develop a theory proposing that positive shocks to external relational capital will catalyze employees to consider alternative employment options, thereby increasing the probability of exit. We further maintain that exit decisions in response to such shocks will be driven by a desire to appropriate more value, making these shocks strong predictors of employee entrepreneurship, especially when the employee works in an area that is peripheral to the firm’s core capabilities. Empirically, we construct a unique employee-employer linked database that tracks employment of lobbyists in the United States federal lobbying industry. Leveraging plausibly exogenous shocks to the value of an employee’s relational capital and a novel market-based measure of the employee’s position in the firm’s knowledge space, we report two sets of findings. First, an increase in the value of relational capital has a positive effect on the likelihood of mobility to established firms and employee entrepreneurship, with the effect for the latter stronger than the former. Second, the magnitude of the effect on employee entrepreneurship becomes stronger when the employee is peripheral to the firm’s core knowledge. Together, our results are consistent with a value creation-value appropriation rationale, where sudden increases in the value of an employee’s relational capital drive exit as a means to appropriate a greater portion of value created.

4 Person–Environment Fit in Organizations: An Assessment of Theoretical Progress

Article