Journal of Business Research 151 (2022) 593–608
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Journal of Business Research
journal homepage: www.elsevier.com/locate/jbusres
Peer directors’ effort, firm efficiency and performance of diversified firms:
An efficacy-based view of governance
Punit Arora a, Ajai Gaur b, *
a
City University of New York, Colin Powell School for Civic and Global Leadership, 160 Convent Ave, NAC 5/141, New York, NY 10031, United States
Rutgers Business School - Newark and New Brunswick, Department of Management and Global Business, One Washington Park, Room 1098, Newark, NJ 07102,
United States
b
A R T I C L E I N F O
A B S T R A C T
Keywords:
Diversification
Benchmarked firm efficiency
Strategy implementation costs
Peer CEO directors
Director effort
Studying how boards contribute to firm performance and examining implementation costs associated with
diversification strategy are domains of growing interest to strategy scholars. We integrate these incipient liter­
atures to examine the role of Peer Independent Executive Directors’ (PIED) effort in improving the performance
of diversified firms. The efficacy-based view of governance that we propose in this paper contributes to both
corporate governance and diversification research by highlighting the contextual role of director domain
expertise and effort in improving firm performance. Using a longitudinal sample of US firms, we show that the
PIED effort is progressively beneficial for firm performance with successive increases in diversification levels,
irrespective of diversification type. In case of diversified firms, PIED effort helps a firm better manage internal
dynamics and opportunism among various business segments within a firm to benefit from complex diversifi­
cation strategies.
1. Introduction
“Nothing is more important to the well-being of a corporation than
its board of directors. … To the extent that the directors acting
collectively as a board make wise decisions, the corporation will
prosper…” (Leblanc & Gillies, 2005, p. 6).
“Much of the scholarship on boards of directors has examined either
the control (i.e., monitoring)
role or the resource dependence role that boards fill. Relatively little
has examined the service
role, wherein directors provide advice and guidance to management”
(Krause et al., 2013, p. 1628).
The Board of directors is the apex decision-making body for a firm to
make its strategic choices. A key aspect of the strategic decision making
in large diversified firms is to exploit economies of scope and synergies
among various businesses to obtain superior performance (Kuppuswamy
& Villalonga, 2016; Villalonga, 2004). However, research has yet to
establish a clear relationship between board characteristics, diversifi­
cation, and firm performance (e.g., Mackey et al., 2017). While the
research on boards of directors has examined different aspects of board
governance, we lack clarity on how boards can effectively guide
organizations in strategy implementation (Krause et al., 2013; Shrop­
shire, 2019).
Board members fulfill multiple roles, ranging from monitoring, to
resource provisioning and advising the top management (Hillman et al.,
2009; Hillman & Dalziel, 2003). However, boards often fail in these
roles, which could be due to a lack of ability, motivation, or in some
cases, due to role confusion (e.g., Arora, 2018; Boivie et al., 2012, 2016;
Feldman, 2016). Building on the previous work that views board of di­
rectors as a critical strategic resource for organization (Carpenter &
Westphal, 2001; Hambrick et al.; 2015; Hillman & Dalziel, 2003), we
propose an efficacy-based view of governance. The efficacy-based view
of governance suggests a more contextualized perspective on how
governance improves firm performance. In this vein, we highlight the
role of Peer Independent Executive Directors (PIEDs) as a governance
resource that helps diversified firms in managing their business portfolio
and thereby enhancing the operational efficiency and performance.
The importance of PIEDs is highlighted in the work of Hambrick,
Misangyi, & Park (2015), who proposed the quad qualifications
comprising independence, ability, bandwidth and motivation for
assessing the effectiveness of a board member in the monitoring role.
Combining the four quad dimensions into a single construct, we focus on
the effort by PIEDs, i.e., CEOs of other firms, who are independent
* Corresponding author.
E-mail address: ajai@business.rutgers.edu (A. Gaur).
https://doi.org/10.1016/j.jbusres.2022.07.035
Received 26 September 2021; Received in revised form 13 July 2022; Accepted 16 July 2022
Available online 21 July 2022
0148-2963/Published by Elsevier Inc.
P. Arora and A. Gaur
Journal of Business Research 151 (2022) 593–608
directors on the board of the focal firm, to assist it in a strategic and
advisory role.1 Specifically in the context of diversified firms, we argue,
and provide substantial evidence, on the critical advisory role played by
the PIEDs in managing these relationships and enhancing the effec­
tiveness of diversification strategy.
Our research makes three important contributions to governance and
diversification literature. First, we argue that the research on board of
directors needs to focus on specific director characteristics, rather than
looking at the boards in generic terms using the typical measures of size
and independence. Building on the quad-qualification model (Hambrick
et al., 2015), we suggest that not all directors have the time and
expertise necessary to help firms manage its internal dynamics. We
further argue that PIED directors, with their experience and social dis­
tance in running peer firms, are in a better position to help firms manage
complex diversification strategies.
Second, we argue and show that it is not just the managerial
opportunism highlighted by the agency theorists that causes diversifi­
cation costs to rise, but also the lack of expertise relevant to harmonizing
the interests of various business segments. More specifically, even when
managerial opportunism is absent or minimal, the relationship between
core — the largest and often historically the most important business
segment — and noncore segments, directly or indirectly (through
corporate parent), can result in considerable diversification costs
(Kumar, 2013). These costs arise not only because firms have rigid or
complex processes and structures or because their managers are selfserving, but also because of the divergence in the interests of core and
noncore segments (Feldman, 2014). Firms need a governance structure
that allows them to effectively manage multiple divergent interests.
Presence of PIED directors on the boards provide such a governance
arrangement as PIED are uniquely placed to help manage these diver­
gent interests. However, firms may not always have access to such
expertise. Thus, the theoretical model developed in this paper shows
how some firms may incur high implementation costs and dissipate any
potential synergistic benefits that may have been otherwise available. As
this may help resolve the long-standing puzzle on the performance ef­
fects of diversification, our study helps advance the diversification
literature.
Third, we argue that in determining exploitable coordination costs,
the degree of relatedness between business segments is only one part of
the equation. While managers at the core and noncore segments attempt
to advance their own interests, it is incumbent on the corporate parent to
manage their relationship in a manner that provides synergistic benefits
to the whole firm. The efficacy-based view of governance suggests that
PIEDs, with their expertise and detachment from organizational politics
may play the role of neutral arbiters among various segments, especially
in situations of conflict. In doing so, our study contributes to better
understanding the role of ‘parenting’ dynamics in deriving benefits from
diversification.
(Amihud & Lev, 1981, 1999; Denis et al., 1997). Managers are believed
to pursue such value-destroying diversification to inflate firm size and
reduce risk (Meyer et al., 1992). Other scholars suggest that diversifying
firms, in general, outperform non-diversifying ones, and that within
those that diversify, related diversifiers outperform unrelated di­
versifiers (Li & Greenwood, 2004; Rumelt, 1974; Villalonga, 2004).
From this perspective, firms diversifying into related businesses obtain
synergistic benefits and improve their performance, while those diver­
sifying into unrelated businesses flounder in their performance. Yet
others find that related diversification may cause firms to perform
poorly as well (Shaver, 2006).
There have been numerous attempts to reconcile these conflicting
findings. Some scholars (Aupperle et al., 2014; Campa & Kedia, 2002;
Graham et al., 2002) suggest that diversified firms traded at a discount
before diversifying, implying that diversification, as such, had no sub­
sequent impact on firm value. Likewise, some believe that the confusion
surrounding the agency-diversification link is largely an artifact of the
methodologies and the measurement approaches used (Boyd et al.,
2005). Risk-return trade-off has also been pointed out as a potential
confounding factor. Amit and Livnat (1988a, 1988b), for example,
suggested that while related diversifiers had a high return-high risk
profile, unrelated diversifiers had a low return-low risk profile.
Scholars have also tried to identify contingencies for diversification
to succeed. Thus, some assert that strategic relatedness is superior to
market relatedness (Markides & Williamson, 1994) and that related
diversification enhances performance only when it allows a business
preferential access to strategic resources and is accompanied by the right
organizational structure (Markides & Williamson, 1996). Similarly,
research has suggested that for firms to fully capture the economic
benefits from related diversification, they need to manage complex in­
terdependencies among multiple levels of strategy (Kor & Leblebici,
2005; Singh, Gaur, & Schmid, 2010; Xu, Hitt, & Dai, 2020).
However, research until recently has not paid much attention to
unraveling strategy implementation costs (Kumar, 2013). In other
words, while research highlights the benefits from enhanced economies
of scale, purchasing power, marketing channel coordination, and such
other synergies associated with related diversification (Mackey et al.,
2017), it largely ignores bureaucratic costs owing to coordination needs
and constraints imposed on various business segments by virtue of being
a part of a diversified firm (Lee & Gaur, 2013; Xu et al., 2020). The
efficacy-based view of governance that we propose in this paper looks at
the specific aspect of managing the internal coordination and other
challenges in diversified firms.
2.2. Strategy implementation costs
In the context of challenges of managing diversified firms, three
studies made breakthrough contributions. Rawley (2010) showed co­
ordination costs (the costs of managing task interdependencies) and
organizational rigidity costs (the costs of changing or failing to change
established routines and practices) to be significant in limiting the scope
of the firm. The coordination costs “offset economies of scope for di­
versifiers, particularly in related diversification when achieving syn­
ergies depends upon coordinating activities across divisions” and that
such coordination costs increase in the presence of organizational ri­
gidities that make institutionalized organizational routines costly to
change (Rawley, 2010, p. 873).
Zhou (2011) built on this concept of synergy as a propellant for, and
coordination costs as a limit, to firm scope, and proposes complexity as a
mechanism that potentially causes both synergy and coordination costs
to rise simultaneously with increased relatedness in diversification. She
views complexity both as a cause and source of organizational rigidity,
and suggests that complexity aggravates coordination problems as “it
increases the amount of existing interdependencies that must be
adjusted when a new business imposes its own requirements” on a
shared pool of inputs (Zhou, 2011, p. 625). From this perspective,
2. Literature and theory development
We first encapsulate the diversification literature (See also Table 1)
before outlining the advisory role of PIEDs in this process.
2.1. The context of corporate diversification
The diversification-performance linkage has emerged as one of the
more complex relationships that have been examined in the strategy
field (Arikan & Stulz, 2016; Kuppuswamy & Villalonga, 2016; Miller,
2006). Some scholars argue that diversified firms underperform relative
to focused firms, which is cited as an evidence of agency problems
1
As we focus on their advisory roles as independent peers, we chose to call
them PIEDs rather than external CEO directors, which, as in prior research,
emphasizes their monitoring role rather than the advisory role.
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Journal of Business Research 151 (2022) 593–608
Table 1
Overview of the literature on boards and diversification.
Authors (year)
Foundation
Type
Findings
Limitations
Bureaucratic costs
Kumar (2013)
Agency theory
Empirical
Core business may provide benefits such as scope
economies to a related segment, but it may also exert
power and constrain the segment to act in its interests in
various internal and external transactions.
Zhou (2011)
Diversification
Empirical
Rawley (2010)
Diversification
Empirical
To realize synergies, a firm needs to actively manage the
interdependencies between different business lines,
which, in turn, increases its coordination costs. The
coordination costs may increase faster than synergy and
set a limit to related diversification.
This paper shows that coordination and organizational
rigidity costs are significantly related.
No direct measures and test of managerial
opportunism/ agency relationships. It also does not
include any mechanisms (e.g., boards) by which firms
may manage relationship between core and non-core
segments.
The article recognizes complexity as a challenge to
diversification, but it does not explore strategies firms
may use to manage them.
Natividad &
Rawley (2016)
Diversification
Empirical
A reduction in the scope of activities causes the
productivity of firms’ legacy operations to fall sharply,
before recovering in the long run. The results are most
pronounced for firms with the strongest
interdependencies.
The article recognizes rigidity as a challenge to
diversification, but it does not explore strategies firms
may use to manage them.
The article recognizes dependence as a challenge to
diversification, but it does not explore strategies firms
may use to manage them.
Diversification
Kuppuswamy &
Villalonga
(2016)
Villalonga (2004)
Agency theory
Empirical
The value of diversification varies with financial
constraints and economic conditions.
No standard corporate governance measures.
Agency theory
Empirical
No standard corporate governance measures.
Mackey et al.
(2017)
Diversification
strategy
Empirical
Found evidence for diversification premium, instead of
discount.
Firms maximize value by choosing strategies that exploit
their heterogeneous resources and individual situation.
Information
processing
Theoretical/
review
Moving beyond the logic of incentives and ability, it
conceptualize a model based on the premise of boards as
groups of individuals obtaining, processing and sharing
information and explain how variation in informationprocessing demands at the director, board and firm level
may challenge effective monitoring.
The presence of “dual directors” (i.e., shared director
between parent and spun-off firm) is positively associated
with the average stock market returns of parent and
spinoff firms.
A director’s likelihood of being an effective monitor in
any given domain is greatly increased when s/he has all
four of the following qualities: independence, expertise in
that domain, bandwidth, and motivation.
The incentive to deliver must be paired with the ability to
deliver. The presence of directors who lack top-level
experience, but own large shareholdings, is negatively
associated with firm value.
Combining intrinsic and extrinsic motivations, it finds
that the prestige associated with being a director, the
ability to have influence, and identification with the
director role make directors less likely for directors to
quit; however, demotivating factors related to the time
commitment required, such as holding other board
appointments or serving as a CEO at another company,
increase the likelihood of director exits.
Theoretical. Does not discuss how increased director
involvement (e.g., by meeting attendance) may help
obtain, process and share information.
Boards
Boivie et al. (2016)
Feldman (2016)
Transaction costs
Hambrick,
Misangyi & Park
(2015)
Quad model
Theoretical
Feldman &
Montgomery
(2015)
Agency &
resource-based
view
Empirical
Boivie et al. (2012)
Self-determination
Empirical
diversification is an endogenous decision that firms make on the basis of
perceived market opportunities, synergies, and coordination costs.
Lastly, Kumar (2013), drawing on traditional agency and transaction
cost theories, proposed managerial opportunism, rather than purely
adaptation, as the mechanism by which coordination costs arise. He
showed that “the power and influence exerted by the core business —
and concomitantly, the subsidization of the core business by related
segments — is an important source of costs borne by segments in a
related diversified firm” (Kumar, 2013, p. 3). In contrast to previous
agency theory literature that regards much of unrelated diversification
to be a result of managerial opportunism, his study is the first to show
the prevalence of opportunism in related diversification. He suggests
that under certain conditions, core business segments are not too averse
to exploit other related business segments for their own benefit.
Power games, coalition dynamics, subjectivity, and bounded
Recognizes the role of strategies, but does not include
any mechanisms (e.g., boards) for implementing these
strategies.
Highlights the role of knowledge exchange but misses
the role of opportunism and price-fixing.
Difficult to test propositions as motivation is hard to
observe, except by examining actual effort.
The focus is on using demographic variables rather
than director motivation or effort.
Advances board research, but the focus is still on using
characteristics variables (e.g., audit committee chair to
measure influence and firm performance and media
coverage for reputation) rather than observable
director effort.
rationalities, all play a prominent role, and as a result, strategic de­
cisions may not always embody the best possible outcomes, giving rise
to friction and avoidable implementation costs that impact firm effi­
ciency, and ultimately, firm performance. Thus, in addition to a firm’s
diversification profile — degree of diversification as well as its relat­
edness — we need to account for the manner of its implementation in
studying firm performance. In the following section, we present the
efficacy-based view of governance, discussing how boards, and PIEDs in
particular, can help firms manage challenges associated with
diversification.
2.3. The role of pier independent executive directors (PIED) and their
effort
Boards as the “apex of the firm’s decision control system” (Fama &
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Journal of Business Research 151 (2022) 593–608
Jensen, 1983, p. 311) have a critical role to play in effective strategic
planning and implementation. As independent directors are responsible
primarily for monitoring, resource-provisioning and influencing strat­
egy, but not for day-to-day administration or for implementing strategic
decisions, the involvement of this elite and episodic decision-making
group with the firm is periodic in nature (Forbes & Milliken, 1999;
Klarner et al., 2018). Independent directors have the benefit of distance
from the internal coalitions and politics of the firm, however this dis­
tance can reduce their firm-specific knowledge and disadvantage them
in dealing with strategic issues such as diversification (Farjoun, 1994;
Nonaka, 1994; Sirower, 1997). The quad-qualification model (Hambrick
et al., 2015) recognizes this fact, and suggests that the effectiveness of a
board member is contingent not just on their independence, but also on
their expertise, bandwidth, and motivation.
Klarner and colleagues argue that “the underlying capabilities
required to govern effectively remain understudied” (2018, p. 1). Other
researchers, similarly, argue that directors need specific capabilities to
be able to contribute to strategic activities of a firm (Carpenter &
Westphal, 2001; Singh & Delios, 2017). These capabilities include
knowledge on how to manage key stakeholders, integrate new and
existing strategic activities, and allocate resources to various units to
compete effectively. Together, these capabilities are expected to assist
focal firms adapt better in ever-evolving markets (Feldman, 2016;
Feldman & Montgomery, 2015; Ponomareva et al., 2022).
We build on this work to focus on the effort of a certain type of in­
dependent directors, viz., Peer Independent Executive Directors (PIEDs).
We suggest that PIEDs bring certain expertise to the table that is helpful
in effectively managing a diversified firm. Two of the four quad quali­
fications, independence and expertise are satisfied by their independent
status, and by their being peer CEOs, respectively. Attending board
meetings provides some indication that these directors have the moti­
vation and time to contribute to the success of the focal firm. As outlined
below, PIEDs can play a useful role in helping managers negotiate the
treacherous terrain of coalition dynamics (Dalton et al., 1998; Pfeffer &
Salancik, 1978).
PIEDs with their managerial and leadership experience can help
exploit synergies and reduce bureaucratic costs through several mech­
anisms. First, in the more diversified firms, the key executives may not
understand all the different businesses and may make suboptimal de­
cisions for different business segments as well as the firm as a whole.
PIEDs, with their experience of managing other businesses, may bring
deeper insights and expertise to help the management of the focal firms
make optimal decisions (Carpenter & Westphal, 2001; Johnson et al.,
1993). Second, PIEDs may act as arbitrators between different interest
groups. The CEO of the focal firm may rely on PIEDs to make decisions
that would be otherwise seen as unfair by different interest groups
within the firms. Third, the CEO can tap into the network of PIEDs to get
a better understanding of the market trends, which helps in future
planning and resource allocation for different business segments in a
diversified firm. Finally, as peers CEOs, they not only have a high degree
of authority and relevant expertise, but also often have deep social ties
with the incumbent CEO, which enables them a level of access that the
typical independent directors do not have (Fahlenbrach et al., 2010;
Westphal & Zhu, 2019). The PIEDs thus satisfy the two QUAD conditions
of being independent2 and having the required knowledge and experi­
ence to provide strategic guidance for managing diversified firms. We
argue that the other two QUAD qualifications – bandwidth and moti­
vation – can be best gauged by the effort put in by these directors.
Extant research suggests that having capabilities may be a necessary
but not a sufficient condition (Arora, 2018; Freixanet & Renart, 2020;
Nicholson & Kiel, 2007). These researchers question the validity of the
assumption that directors necessarily put their capabilities to use to
advance the interests of the firm, which relies on the expectation of
reputational penalties for directors, who fail to deliver on their direc­
torial obligations.
As important differences in directors’ motivation levels based on
factors such as firm prestige, directors’ identification with the firm and
the required time commitment (Boivie et al., 2012; Hambrick et al.,
2015; Masulis & Mobbs, 2014) are unearthed, scholars realize that di­
rectors do not always perceive or incur reputational penalties for suboptimal effort (Arora, 2018). Moreover, as motivation is hard to infer
in large-scale archival studies, by focusing on their actual effort, we can
more effectively capture their bandwidth and motivation as it can ac­
count for the fact that while some directors may have the time but not a
real desire to assist the firm, others may possess the motivation but lack
in available time.
Thus, we suggest that the effort put in by the PIED directors is in line
with the quad-qualification outlined by Hambrick and colleagues
(Hambrick et al., 2015). In the context of diversification and strategy
implementation, for reasons outlined above, the effort made by PIED
directors helps the firm harmonize the interests of different business
units in diversified firms. This is line with a survey by McKinsey
consulting (2018) indicated that board members with high impact, on
an average, invested eight (8) extra days a year on work pertaining to
firm’s strategy. Such work included three additional days on in­
vestments, executions and mergers and acquisitions.3 Accordingly, we
propose that PIED effort is beneficial for enhancing performance of
diversified firms, leading to the following hypothesis:
Hypothesis 1. There is a positive relationship between PIED effort and
financial performance of diversified firms.
The costs of organizing a diversified set of businesses likely to be
more pronounced in more diversified firms than in less diversified ones.
Diversified firms take advantage of the synergistic benefits, and thereby
improve both segment efficiency as well as profitability when compared
to single-segment firms in the same industry. However, as level of
diversification increases, the potential benefits of this coordination
could easily be overcome by the costs of coordination. In other words,
highly diversified firms may be less profitable and efficient as the costs
of internal coordination start to outweigh the benefits of the synergies.
While managers at the core and noncore segments attempt to advance
their own interests, it is incumbent on the corporate parent to manage
their relationship in a manner that provides synergistic benefits to the
whole firm. The degree to which CEOs and directors can play the role of
neutral arbiters among various segments, therefore, is an important part
of this puzzle.
As managing highly diversified firms requires substantial control and
coordination in order to take advantage of the synergies across different
business segments, the role of corporate headquarters in shaping critical
decisions becomes more and more important (Pattnaik, Lu, & Gaur,
2018). However, the managerial ability to extract greater economies of
scale under conditions of uncertainty can easily translate into greater
bureaucratic costs in practice. This may occur if the resource transfers
between the core and the peripheral segments of the diversified firm are
managed in a way that leads to higher bureaucratic costs. Thus, for
highly diversified firms, CEOs are more likely to need the help of PIEDs.
When PIEDs put in the requisite effort, it can translate into firms better
managing their diverse portfolios. Hence, we argue that while PIED
effort is valuable for all diversified firms, their utility is likely to increase
with increased diversification levels as decision making becomes more
2
As discussed in the next section, the independence, as referred to here,
pertains to their independence from various business segments. As these di­
rectors have deep social ties to the CEO, their effectiveness at typical moni­
toring may be debatable. However, their effectiveness at advising on managing
various business segments is likely not compromised by such ties.
3
This is also in line with the results in Faleye, who found that CEO-directors
are “associated with higher acquisition returns, especially for complex deals
(2011, p. 241).
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P. Arora and A. Gaur
Journal of Business Research 151 (2022) 593–608
and more complex. Accordingly, we propose that PIED effort is likely to
be more beneficial in enhancing firm performance in the case of more
diversified firms than less diversified firms, leading to the following
hypothesis:
likely to differentiate between the needs of the core business and the
firm as a whole. Resultantly, they are in a position to better harmonize
the interests of various segments in accordance with the needs of the
firm. The effectiveness of PIED effort is likely to depend on how effi­
ciently the focal firm is managing its current business portfolio. In the
case of firms that are managing their portfolio efficiently, they can focus
their effort on helping the firms realize their synergistic potential.
However, if the firm is struggling to do so, their attention may be
diverted to managing conflicts and fixing efficiency problems first.
In general, if a firm is operating with a high level of efficiency (when
benchmarked against its single-segment counterparts that require no
inter-segment coordination), there may be little scope for PIEDs to
contribute and further improve efficiency. On the other hand, if firm is
operating with low benchmarked efficiency, PIEDs may help the CEO
better organize and harmonize the interests of different segments to­
wards improved firm performance. Hence,
Hypothesis 2. PIED effort and diversification positively interact in
affecting firm performance such that the benefit of PIED effort is greater for
more diversified firms than less diversified firms.
2.4. Strategy implementation costs, firm efficiency, and PIED effort
As argued before, when compared with single business firms,
different business segments in a firm are subject to several constraints as
they coordinate their activities with other segments, especially those
that form the core of their firms. The core business segments not only
share critical resources with other segments but may also provide the
backbone of a firm’s critical know-how, human capital, and cultural
identity. Because a firm likely owes its origin, existence, stability, cul­
ture, identity, and growth at various points to its core business, it likely
enjoys higher legitimacy among firms’ internal and external stake­
holders, as well as a greater representation in the firms’ upper echelons.
As the core segment of the diversified firm is most likely the segment
that drives firm behavior, its performance would be crucial to the per­
formance of the entire firm. If the core segment is relatively more
profitable and efficient than other firms, it is more likely to transfer
positive practices to other segments and also manage the coordination
costs more effectively. If, on the other hand, the core segment itself is not
very efficient, it is unlikely that it will manage the internal coordination
costs very effectively.
If a diversified firm is not managed properly, it is more likely that the
influence of the core business manifests in the form of the core’s interests
subordinating the interests of other business segments, making them
pliant to the core’s needs (Kumar, 2013). For example, they may feel
compelled to source their inputs from the core despite the availability of
better-quality suppliers or to offer discounts to the customers they share
with the core business to help the latter increase its sales. If the core
segment improves its profitability or efficiency at the expense of the noncore segments, then the firms will begin to incur higher bureaucratic
costs that will outweigh the benefits of coordination.
To the extent that the core segment increases its efficiency at the
expense of non-core segments, diversified firms are more likely to suboptimize their performance.4 Thus, the conflicts between core and
non-core segments could determine the overall efficiency of the focal
firm. In other words, the synergies that potentially provide competitive
advantage to a firm could also turn out to be an albatross for its per­
formance (Kumar, 2013). Firms whose managers ensure that the bene­
fits from such coordination and constraints outweigh the costs are more
likely to be high performers. However, just because there are potential
synergies does not mean that managers always succeed in exploiting
them.
PIEDs can play a salient role in helping managers actualize potential
synergies. Internal directors have a close association with managers of
core business segments, they may themselves have been promoted from
within these segments, and even when hired from outside, they are
likely to be influenced by the dominant logic prevalent in their firms. As
a result of these close associations, they are more likely to perceive the
needs of core segments to be synonymous with the needs of their firms,
which may or may not be true.
PIEDs (i.e., active CEOs of other firms), on the other hand, are neither
deeply vested in the prevailing dominant logic nor are entrenched in
their relationships with division managers. They are, therefore, more
Hypothesis 3. PIED effort and benchmarked efficiency negatively interact
in affecting firm performance such that the benefit of PIED effort is greater for
firms with lower benchmarked efficiency than for those with higher bench­
marked efficiency.
3. Data and methodology
3.1. Data and sample
The Compustat USA is the primary source for the financial and
business segments data. This dataset has a panel structure with obser­
vations spanning the years 2001–2018. We started with all the firms
included in Compustat segments data, which was then merged with
MSCI Directors and governance datasets. The intersection of these
datasets yielded initial sample of 11, 418 observations. Missing obser­
vations on various control variables result in a final sample of 7084
observations for 1096 diversified, i.e., multi-business-segment, firms in
the United States.5
3.2. Variables of main interest
Firm performance. We compute the Return on Assets (ROA) and Total
Shareholder Return (TSR) as alternative measures of firm performance.
ROA — net income to total assets — is commonly used accounting
measure of performance (e.g., Nielsen & Nielsen, 2013). Following prior
research (e.g., Conyon et al., 2001; Dalton & Aguinis, 2013), we
compute annual TSR, a market-based measurement of performance, as
follows:
TSR =
(StockPricen − StockPricen− 1 ) + Dividendn
StockPricen− 1
(Benchmarked) firm efficiency. Following prior research (Arora, 2011;
Kumar, 2013), we first compute the segment efficiency (SEGEFF) of all
of firm’s business segments at the 3-digit SIC code level as follows:
)
(
z
∑
Salesm
SEGEFF A = Sales of Segment A −
*Assets of SegmentA
Wm *
Assetsm
m=1
where m = 1,…z denotes single segment firms in the same 3-digit SIC as
segment A and wm is the sales weight or the proportion of sales
contributed by firm m among these z firms. Assuming a hypothetical
industry (SIC code 737) has only two firms: Orange, which has only one
business, and Mango, which has other businesses as well, and their sales,
5
If we exclude CEO characteristics, we get a final sample of 8287 observa­
tions for 1140 firms. Our results are identical to those reported here. Note that
for benchmarking the performance of these firms, we use all single-segment
firms included in the Compustat segments-dataset.
4
This may be especially true in case managers of related diversified firms,
who can impose more constraints than managers of unrelated diversified firms
in order to exploit the synergies associated with diversification.
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Journal of Business Research 151 (2022) 593–608
assets and SEGEFF are given as follows:
assessed as = (0.875*2 + 0.375*1) *8 = 17.
We use attendance at the board meetings as it is the only observable
measure of director effort, which is legally mandated for reporting.
While advising can and does also happen outside board meetings, if
directors are not even willing to put in the bare minimum effort required
towards attending board meetings, they likely are not very active
beyond these meetings either. In other words, their board meeting
attendance can be used to gauge their interest in putting in a required
minimum level of effort. It is true that some directors may show up for
the meetings, but not put in any effort beyond it. However, board
meeting attendance is still a very good indication on whether directors
are willing to put in at least some degree of effort for the firm (Arora,
2018). Moreover, those, who show up for meetings, likely feel some peer
pressure to contribute what is promised at the meetings.
3.3. Sales assets
Single business firm: Orange 20 15
Multi-business firm: segment 737: Mango 80 85
In this case, efficiency for Mango 737 segment equals –33.33 [80(85*20/15)].
As is apparent from the formula and example above, all singlesegment firms in that segments’ industry are used as the benchmark
(weighted-averages) for calculating the segment efficiency of diversified
firms. Such a comparison of efficiency between the single segment and
diversified firms allows us to impute bureaucratic costs to business
segments in a diversified firm.
We then compute firm efficiency, which is the weighted average of
all of firm’s segments, wherein segment sale is used as the weight. This
methodology — calculating firm efficiency at the segment level — is
advantageous in that it does not allow aggregate measures to obscure
the performance of various business segments, which is critical in
investigating diversification effects. Moreover, this measure does not
also call for information on segment profitability, which in any case, is
rarely, if ever, reported.
For supplementary analysis, we also compute (benchmarked) core
and noncore segment efficiency measures. Benchmarked core efficiency
(BCE) captures the efficiency of the largest segment, whereas bench­
marked noncore efficiency (BNE) computes the weighted average of all
noncore segments of a diversified firm.
Diversification profile. Following previous research, we use the en­
tropy index (Jacquemin & Berry, 1979) to capture three alternative
measures of diversification, viz. total, related and unrelated diversifi­
cation. The related component of the entropy index can be derived by a
partition of total entropy into its related and unrelated parts, wherein
total diversification entropy (DT), unrelated diversification (DU) and
related diversification (DR) are given by:
( )
N
∑
1
DT =
Pi ln
P
i
i=1
3.4. Control variables
Firm size and age. Prior research (Dahiya et al., 2003; Lee & Weng,
2013; Moulton & Thomas, 1993) suggests that older and more estab­
lished firms have better access to human and financial resources.
Therefore, it is important to control for firm size and age. We measure
firm size by the (logged values of) number of employees working for the
firm. As firm efficiency involves total assets as its denominator, it can
potentially cause the problem of multicollinearity if we used total assets
as a measure of firm size also. The use of the number of employees averts
this problem without any loss of information. We control for firm age,
which is computed by subtracting the year of formation from the year of
current reporting.
R&D and advertisement intensity. Prior research (McWilliams & Siegel,
2001) suggests the need to control for effect of R&D and advertisement
intensity to avoid upwardly biased estimates of the financial impact of
various product differentiation initiatives. Therefore, we control for
R&D expenditure to sales ratio and advertisement expenditure to sales
ratio.
Capital intensity. As capital intensity can cause rigidities in imple­
menting and changing corporate strategy (Finkelstein & Boyd, 1998),
we used the ratio of the total plant, property and equipment assets to the
number of employees as a control variable.
Financial condition. To preclude the effect of firm’s financial health
(Altman, 1993; Arora, 2018), we control for three financial ratios, viz.,
(1) Cash and accounts receivables/ total assets, (2) Current assets/ Fixed
assets, and (3) total debt to equity ratio.
Corporate governance. Previous research (Yermack, 1996) shows that
larger boards become too unwieldy, unproductive, and unmanageable,
and therefore provide lower social incentives for directors and
encourage more free riding. Hence, board size is included as one of the
control variables. As greater independent director representation has
been shown to improve monitoring and external legitimacy of the firm
(Ahmed & Duellman, 2007; Chhaochharia & Grinstein, 2007), we
include the number of independent directors in my regression model.
Following prior research, we also include CEO age, CEO tenure and CEO
duality to control for career horizon, entrenchment and power respec­
tively. (Boyd, 1995; Chen & Nadkarni, 2016; Hill & Phan, 1991) CEO
tenure refers to the length of the time CEO had been in his or her po­
sition. CEO duality is a dichotomous measure, which equals 1 if CEO was
also the chair of the board.6
Levels of Diversification. We control for absolute levels of a firm’s
diversification portfolio by including segment count in our regression
models (Villalonga, 2004).
where Pi = Proportion of sales in SIC code (i) for a corporation with “N”
different 4-digit SIC business segments.
DU is computed in a similar manner except using 2-digit SIC business
segments. Finally, DR is simply computed as: DR = DT- DU.
As previous research has shown “moderate levels of diversification
yield higher levels of performance than either limited or extensive
diversification” (Palich et al., 2000), we include square terms of entropy
measures mentioned above in our robustness test.
PIED effort. We start by identifying independent directors who are
active CEOs of other firms as we expect them to bring their experience,
resources, and networks to help the focal firm pursue diversification
strategy successfully. We also expect them to act as neutral arbiters
among core and noncore business segments. After identifying peer in­
dependent executive directors, following prior research (Arora, 2018),
we compute PIED effort as below:
PIEDeffort = (w1*N1 + w2*N2)*M
N1 and N2 are, respectively, the number of active (attended at least
75% of board meetings) and non-active (attended less than 75%) PIEDs;
M is the number of board meetings, and w1 and w2 are the proportion of
meetings attended by active and non-active PIEDs. Note that firms are
only required to report which of their directors attended at least 75
percent of board meetings. Assuming that the percentage of meetings of
the active directors is uniformly distributed between 75 and 100%, and
for the non-active ones between 0 and 75%, we set w1 = 0.875 and w2
= 0.375 (i.e., at mean values for each category). Thus, if a firm held 8
meetings the year prior to reorganization and 2 of its 3 PIEDs attend­
ed>75% of the meetings, but one did not, this board’s total PIED effort is
6
We did not include proportion of busy directors (i.e., directors who sit on
more than three other boards) out of concerns about potential multicollinearity.
However, the inclusion of this variable does not alter the results reported in this
paper.
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Journal of Business Research 151 (2022) 593–608
3.5. Methodology
Hypothesis 2 predicted that the benefit of PIED effort is greater for
more diversified firms than less diversified firms. As seen in Table 2, the
interaction of PIED effort and total diversification is significant (β =
0.02, p = 0.031 in Model 6). However, to interpret interaction effects,
following the best practice recommendations of prior research (Arora &
De, 2020; Brambor et al., 2006; Clark et al., 2021), we use marginsplot
in Stata to depict predicted values along with 95% confidence intervals,
at various plausible values (+/- 1 standard deviations from the mean as
per standard practice) of interacting variables. Note that lastly,
following the best practice recommendations (Dawson & Richter, 2006),
we use standardized independent variables (mean = 0, s.d. = 1) in our
regressions to help with interpretation of interaction effects.
In support of hypothesis 2, we notice in Fig. 1 that as the level of
diversification increases, the significance of PIED effort becomes more
apparent. At low levels of diversification, PIED effort does not make
much of a difference to firm performance, as indicated by a flat blue line
with a negligible upward slope. However, at high levels of diversifica­
tion, PIED effort helps firms close the gap with lesser diversified firms. In
fact, there are essentially no differences among firms, irrespective of
their diversification levels, at the very high PIED effort.
In Hypothesis 3, we predicted that the benefits of PIED effort is
greater for firms with lower benchmarked efficiency than for those with
higher benchmarked efficiency. While the interaction term was not
significant (β = 0.01, p > 0.10 in Model 6), recall that the significance of
these interactions only implies whether (or not) interactions are signif­
icant at the mean values of the interacting variables. It is more important
to depict their marginal values to better understand the nature of their
relationship. Fig. 2 provides the marginsplot for the interaction between
BFE and PIED effort. While we expected that the benefits of PIED effort
would be greater for firms with lower benchmarked efficiency, our
findings yield the results that are slightly to the contrary. Although PIED
effort benefit all firms, we find that these are most helpful for firms with
higher benchmarked efficiency: A combination of high BFE and high
PIED effort leads to the highest firm performance (Marginal effect =
0.10, p = 0.00). While at low levels of BFE, we do not notice statistically
significant effect of PIED effort. This could suggest there may be more
than one channel by which PIEDs help the firm or that a sequential
process exists in which PIEDs first help the firm raise their efficiency,
which, in turn, leads to performance benefits at a subsequent time
period.
We use a longitudinal research methodology to avoid biased and
misleading estimates from cross-sectional snapshots (Finkelstein &
Boyd, 1998; George, 2005; Maddala, 2002). We first examined the
appropriateness of fixed v. random-effects models using the Hausman
test, which indicated fixed-effects (FE) models to be more appropriate
(χ2 = 248.18; p < 0.001) for our sample (Greene, 2003; Hausman,
1978). FE regressions, which use “within-firm variation to identify co­
efficient estimates, advantageous for mitigating certain endogeneity
concerns and ruling out spurious relationships” (Shaver, 2019: 1), help
control for firm and time-specific heterogeneity and produce unbiased
regression coefficients (Greene, 2003). FE regressions also return esti­
mates that are not biased by omitted time-invariant control variables
(Baltagi, 2008; Stock & Watson, 2007). We lagged independent vari­
ables by a year to better establish causality (Hambrick, 2007).
Lastly, we also conducted explicit endogeneity tests by employing
Hausman-Taylor regressions (xthtaylor in Stata) for endogenous cova­
riates (J. Hausman & Taylor, 1981). This technique has been found to be
particularly effective at deriving robust estimates when several
explanatory variables may be endogenously correlated (Baltagi et al.,
2002). For the purpose of our empirical design, we assumed all main
variables of interest — diversification, efficiency, PIED effort, and firm
performance — to be endogenous covariates.
4. Results
We report the descriptive statistics and correlations in Table 1. The
mean values for ROA, PIED effort, and firm efficiency are 0.13, 5.03,
0.08 with standard deviations of 0.08, 8.03, and 0.48 respectively. The
descriptive statistics, including the correlation matrix, with respect to
the other measures, also appear in the table. To ensure that multi­
collinearity is not affecting our results, we examined the variance
inflation factors (VIF) scores. All VIF scores are below 3, with a mean of
1.72, well within the commonly specified rule of thumb of a score of 10
indicating no evidence of multicollinearity problems (Cohen et al.,
2003).
In Table 2, we provide the results of our FE regression models with
ROA as the dependent variable and PIED effort, benchmarked firm ef­
ficiency (BFE), and total diversification (DT) and as the variables of main
interest. We standardized all variables before running our regression
models.
Model 1 in Table 2 shows the results for the regression with control
variables alone, whereas Model 2 introduces DT and Model 3 in­
corporates PIED effort and BFE.7 Models 4 and 5 introduces individual
interactions and Model 6 presents the complete regression models with
all hypothesized direct and indirect (interaction) effects. The table
shows that many of the control variables, such as firm size, firm age,
advertisement intensity, capital intensity, cash ratio and CEO tenure are
significantly — positively or negatively — associated with the ROA.
More interestingly, however, Table 2 lends strong support for our
predictions. Hypothesis 1 predicted that the PIED effort is positively
associated with the ROA. We notice that PIED effort is indeed positively
associated with the ROA across the entire regression table (β = 0.02, p =
0.009 in Model 6). Hence, Hypothesis 1 is supported.8
4.1. Post-hoc robustness tests
As prior research distinguishes between related (DR) and unrelated
diversification (DU) in terms of expected impact on firm performance,
we decompose total diversification (DT) into DR and DU, and rerun the
regression models reported above. We replace DT with DR in Model 7,
and with DU in Model 8 in Table 3. As seen from Models 7 & 8, the
results are essentially identical to those reported in Model 6 in Table 2
above. The marginsplots in Figs. 3 and 4 also very similar except for
slightly steeper slopes. Even when we include both DR and DU in the
same regression model (unreported), these patterns persist.Table 4.
In Models 9–10 in Table 3, we similarly replace firm efficiency with
the core segment (Model 9) and noncore segment efficiency (Model 10)
measures. These models, once again, reproduce identical results. Figs. 5
and 6 also reveal patterns similar to those reported above.
We, next, re-run this regression model by replacing ROA with Total
Shareholder Return (TSR) as our dependent variable, and we find even
stronger results with respect to variables of main interest (See Model
11).
Lastly, in Model 12, we run Hausman-Taylor regressions (xthtaylor
in Stata) for endogenous covariates by assuming all our main variables,
i.e., diversification, efficiency, PIED effort, and firm performance, to be
endogenously related. We find results with respect to PIED effort (β =
0.03, p <=0.001), DT (β = -0.09, p = 0.000), PIEDEFF × DT (β = 0.02, p
= 0.026), PIEDEFF × BFE (β = 0.01, p > 0.10) to be identical to those
7
We ran regressions by introducing each of the direct effects separately and
found identical results. These are not included in the table for the sake of
brevity but are available on request.
8
Note that we repeated this regression model with non-PIED effort instead of
PIED effort. Our results showed a statistically insignificant result (β = 0.02, p >
0.10). Further, we also ran regressions with proportional PIED effort (PIED
effort/ Board effort) to capture the effect of PIED effort in relation to total board
effort. We obtained results that are materially identical to those reported in
Table 2.
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P. Arora and A. Gaur
1
2
3
4
5
6
7
8
9
600
10
11
12
13
14
15
16
17
18
19
22
23
24
25
24
23
22
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
Return on Assets
0.13 0.08
Total shareholder
0.12 0.41
0.14
return
PIED Effort
4.76 8.03 − 0.01 − 0.03
Benchmarked firm
0.08 0.48
0.12
0.03
0.01
efficiency
Benchmarked core
0.08 0.57
0.12
0.02
0.01
0.97
efficiency
Benchmarked
0.08 0.31
0.06
0.02
0.04
0.47
noncore efficiency
Total diversification 0.84 0.43 − 0.05 − 0.01
0.09 − 0.09
Unrelated
0.20 0.17 − 0.04 − 0.01
0.06 − 0.06
diversification
Related
0.64 0.36 − 0.04 − 0.01
0.07 − 0.08
diversification
Firm size
1.76 1.47
0.10 − 0.02
0.19
0.00
(employees)
Firm age
32.11 18.52 − 0.03 − 0.02
0.18
0.03
R&D intensity
0.02 0.10 − 0.16 − 0.02 − 0.01
0.01
Advertisement
0.01 0.02
0.04 − 0.01
0.02
0.02
intensity
Capital intensity
4.38 1.47 − 0.11
0.00
0.05 − 0.14
Cash Ratio
0.63 1.03 − 0.06
0.01 − 0.04
0.04
Current assets to
0.92 0.96 − 0.01
0.03 − 0.07
0.31
Fixed assets
Total debt to equity
1.75 2.80 − 0.09
0.03
0.03 − 0.02
Board size
9.22 2.18
0.00 − 0.02
0.19 − 0.05
# of independent
6.73 2.31 − 0.01 − 0.03
0.26 − 0.02
directors
CEO age
61.89 7.24
0.00
0.01 − 0.05 − 0.04
CEO-chairman
0.54 0.50
0.02 − 0.01
0.06 − 0.01
duality
CEO tenure
5.54 5.65
0.01
0.01 − 0.11
0.00
# PIEDs
1.09 1.71 − 0.01 − 0.05
0.50 − 0.02
# of business
4.16 1.61 − 0.06 − 0.01
0.09 − 0.04
segments
Herfindahl index
0.52 0.21
0.05
0.01 − 0.08
0.10
0.32
− 0.11
− 0.08
0.09
0.03
0.55
− 0.10
0.10
0.92
0.18
− 0.01
0.04
0.29
0.17
0.04
0.01
0.01
0.26
0.00
0.18
0.06
0.18
0.30
0.02 − 0.02
0.00 − 0.02 − 0.09 − 0.06
0.06 − 0.01 − 0.03
0.00
0.00 − 0.08
0.00
− 0.14 − 0.16 − 0.07 − 0.04 − 0.06 − 0.27
0.18 − 0.06 − 0.13
0.04
0.02 − 0.10 − 0.05 − 0.10 − 0.30 − 0.15
0.36
0.06 − 0.08
0.31
0.21 − 0.11 − 0.06 − 0.11 − 0.17 − 0.10
0.14
0.06 − 0.43
− 0.02
0.00
− 0.04 − 0.03
− 0.01 − 0.03
0.02
0.18
0.19
0.01
0.07
0.09
0.02
0.18
0.18
0.34
0.12
0.43
0.38
0.04 − 0.04 − 0.06
0.37 − 0.04
0.00
0.43 − 0.05 − 0.03
0.14 − 0.15 − 0.13
0.19 − 0.17 − 0.23
0.20 − 0.18 − 0.21
− 0.03 − 0.04 − 0.02 − 0.04 − 0.01 − 0.02
0.00 − 0.03
0.04
0.02
0.03
0.12
0.06 − 0.03 − 0.07
0.16
0.00 − 0.02
0.02
0.04
0.01 − 0.02 − 0.01 − 0.04
0.01 − 0.02 − 0.01
0.00
0.05
0.12
0.07
0.08
0.77
0.26
0.01 − 0.01 − 0.07 − 0.08 − 0.05 − 0.08 − 0.06
0.04 − 0.02 − 0.07
0.12
0.09 − 0.02 − 0.14 − 0.16
0.33
− 0.01
0.00
0.09
0.06
0.08
0.20
0.16
0.01 − 0.01
0.02 − 0.06 − 0.06
0.03
0.23
0.27 − 0.09
− 0.05
0.04
0.80
0.40
0.76
0.23
0.19 − 0.03 − 0.02
0.06 − 0.09 − 0.12
0.05
0.20
0.19 − 0.02
0.13 − 0.13 − 0.96 − 0.55 − 0.88 − 0.26 − 0.16
0.02
0.02
0.09
0.11
0.11 − 0.01 − 0.15 − 0.16
0.21
0.07 − 0.07
0.05 − 0.06
0.02 − 0.03
0.10
0.07 − 0.08 − 0.67
Journal of Business Research 151 (2022) 593–608
20
21
S.D.
Mean
Table 2
Descriptive statistics and correlation Matrix.
P. Arora and A. Gaur
Journal of Business Research 151 (2022) 593–608
Fig. 1. Interaction effect of total diversification (DT) and PIED effort on firm performance.
Fig. 2. Interaction effect of Benchmarked Firm Efficiency (BFE) and PIED effort on firm performance. Note: As these interaction graphs use standardized variables,
the values plotted above correspond to one standard deviations above (+) or below (-) mean values of depicted variables.
reported in Table 2.
Thus, despite running regression models with various permutations
and combinations of control measures as well as alternate specifications
with regard to variables of main interest, we find very robust support for
our predictions.
which suggests that firms can structure their board of directors in such a
way that the board members help manage the internal dynamics and
enhance efficiency of operations in diversified firms. Presence and active
participation of PIEDs offers such governance setup and helps in navi­
gating the challenges associated with diversification strategies.
Besides clarifying the governance antecedents of diversification
costs, this study makes three important contributions to the literature.
First, we illustrate the need for research to focus on specific expertise
and effort of directors rather than merely examining generic de­
mographic characteristics such as independence. Building on recent
work on director expertise and motivation (Arora, 2018; Boivie et al.,
2012; Hambrick et al., 2015; Masulis & Mobbs, 2014), we demonstrate
that not all directors have the time and expertise to help a firm manage
its internal dynamics. PIED effort can provide the quad-qualification
necessary for firms in managing complex diversification portfolio. This
sets the stage for researchers not just to focus on specific domain
4.2. Discussion and conclusion
This study provides a robust examination of the relationship between
PIED effort and performance of a diversified firm. Recent research has
highlighted the fact that despite potential economies of scope, firms do
not automatically reap synergistic benefits from relatedness as they need
to carry out extensive coordination to serve the greater good of the
overall firm. This stream of research suggests that while relatedness may
be a necessary condition for firms to enjoy economies of scope, it is not
sufficient by itself. We propose an efficacy-based view of governance
601
P. Arora and A. Gaur
Table 3
DT, Benchmarked Firm Efficiency, PIED Effort and Return on Assets: Panel data, fixed effects (F.E.) regression results.
Model 1
Model 2
Model 3
Model 4
Model 5
Model 6
602
DV: ROA
β
se
p
β
se
p
β
se
p
β
se
p
β
se
p
β
se
p
Firm size (employees)
Firm age (years)
R&D intensity
Advertisement intensity
Capital intensity
Cash ratio
Current Assets to Fixed Assets
Total debt to equity
Board size
Number of independent directors
CEO age
CEO tenure
CEO-chairman duality
Number of business segments
Total diversification (DT)
Benchmarked firm efficiency (BFE)
PIED Effort (PIEDEFF)
DT × PIEDEFF
BFE × PIEDEFF
Constant
− 0.42
0.05
− 1.92
− 0.15
− 0.36
− 0.05
0.04
− 0.00
− 0.04
− 0.00
0.01
0.03
− 0.02
− 0.04
(0.086)
(0.075)
(1.518)
(0.047)
(0.090)
(0.036)
(0.027)
(0.014)
(0.031)
(0.021)
(0.018)
(0.019)
(0.038)
(0.017)
[0.000]
[0.494]
[0.207]
[0.002]
[0.000]
[0.174]
[0.105]
[0.975]
[0.179]
[0.923]
[0.514]
[0.078]
[0.614]
[0.031]
− 0.41
0.05
− 1.85
− 0.15
− 0.36
− 0.05
0.04
− 0.00
− 0.04
− 0.00
0.01
0.03
− 0.02
0.02
− 0.09
(0.086)
(0.074)
(1.538)
(0.046)
(0.089)
(0.036)
(0.027)
(0.014)
(0.031)
(0.021)
(0.018)
(0.019)
(0.038)
(0.030)
(0.038)
[0.000]
[0.512]
[0.228]
[0.002]
[0.000]
[0.150]
[0.112]
[0.925]
[0.186]
[0.874]
[0.548]
[0.076]
[0.623]
[0.431]
[0.020]
− 0.39
0.03
− 1.80
− 0.15
− 0.35
− 0.05
0.03
0.00
− 0.04
− 0.01
0.01
0.04
− 0.02
0.02
− 0.08
0.05
0.03
(0.087)
(0.074)
(1.509)
(0.046)
(0.090)
(0.036)
(0.027)
(0.014)
(0.031)
(0.021)
(0.018)
(0.019)
(0.038)
(0.029)
(0.037)
(0.020)
(0.009)
[0.000]
[0.650]
[0.233]
[0.001]
[0.000]
[0.138]
[0.236]
[0.984]
[0.212]
[0.720]
[0.590]
[0.058]
[0.600]
[0.431]
[0.026]
[0.020]
[0.001]
− 0.41
0.05
− 1.83
− 0.15
− 0.36
− 0.05
0.04
− 0.00
− 0.04
− 0.01
0.01
0.03
− 0.02
0.02
− 0.09
(0.086)
(0.074)
(1.532)
(0.046)
(0.089)
(0.036)
(0.027)
(0.014)
(0.031)
(0.021)
(0.018)
(0.019)
(0.038)
(0.030)
(0.038)
[0.000]
[0.519]
[0.233]
[0.001]
[0.000]
[0.140]
[0.123]
[0.985]
[0.230]
[0.668]
[0.552]
[0.067]
[0.624]
[0.432]
[0.019]
− 0.40
0.03
− 1.86
− 0.15
− 0.34
− 0.05
0.03
0.00
− 0.04
− 0.01
0.01
0.04
− 0.02
− 0.03
(0.086)
(0.074)
(1.497)
(0.046)
(0.091)
(0.036)
(0.028)
(0.014)
(0.031)
(0.021)
(0.018)
(0.019)
(0.038)
(0.017)
[0.000]
[0.645]
[0.214]
[0.002]
[0.000]
[0.160]
[0.236]
[0.934]
[0.203]
[0.776]
[0.555]
[0.060]
[0.586]
[0.053]
0.03
0.02
(0.009)
(0.008)
[0.008]
[0.039]
0.05
0.03
(0.020)
(0.009)
[0.012]
[0.001]
0.00
(0.027)
[0.911]
− 0.00
(0.027)
[0.972]
0.01
0.00
(0.012)
(0.026)
[0.635]
[0.999]
− 0.39
0.03
− 1.83
− 0.15
− 0.35
− 0.05
0.03
0.00
− 0.04
− 0.01
0.01
0.04
− 0.02
0.02
− 0.08
0.05
0.02
0.02
0.01
0.00
(0.086)
(0.074)
(1.539)
(0.046)
(0.090)
(0.036)
(0.027)
(0.014)
(0.031)
(0.021)
(0.018)
(0.019)
(0.038)
(0.029)
(0.037)
(0.020)
(0.009)
(0.008)
(0.012)
(0.027)
[0.000]
[0.665]
[0.235]
[0.001]
[0.000]
[0.138]
[0.238]
[0.982]
[0.215]
[0.714]
[0.575]
[0.061]
[0.592]
[0.449]
[0.025]
[0.018]
[0.009]
[0.031]
[0.504]
[0.952]
Observations
R-squared
Number of unique firms
F-test
7,084
0.041
1,096
5.427
− 0.00
(0.026)
[0.936]
0.00
7,084
0.044
1,096
5.464
(0.027)
[0.957]
7,084
0.048
1,096
5.932
7,084
0.047
1,096
6.081
7,084
0.046
1,096
5.624
7,084
0.049
1,096
5.922
Journal of Business Research 151 (2022) 593–608
Notes:
(1) We excluded the number of Peer Independent Executive Directors (PIED) from our regression out of concerns regarding potential multicollinearity. However, its inclusion does not affect the results reported above.
(2) While following prior research, we tested for non-linear effects of DT by including its squared term in our regression models. As its inclusion or exclusion had no substantial impact on the nature of relationships depicted
above, we did not use it in our main regression results reported above.
(3) All variables were standardized (0,1) before running regressions above.
P. Arora and A. Gaur
Journal of Business Research 151 (2022) 593–608
Fig. 3. Interaction (margins) effect of related diversification (DR) and PIED effort.
Fig. 4. Interaction (margins) effect of unrelated diversification (DU) and PIED effort.
expertise in evaluating directors’ contributions, but also considering
their willingness to expand effort on behalf of the focal firm. Our results
suggest that only some directors have the time and expertise relevant to
managing its internal dynamics. In showing the relevance of PIED di­
rectors quad-qualification and effort for firms seeking to manage com­
plex diversification strategies, we address a gap in the literature on the
importance of independent directors’ knowledge, skills, abilities, and
motivations that has received limited attention (Klarner et al., 2018; Kor
& Sundaramurthy, 2009), even though some research has shown it to be
of great significance. Thus, for example, Carpenter & Westphal (2001)
argue that directors’ ability to contribute to focal firms could depend on
knowledge schemata developed in similar roles.
Second, we show that even when managerial opportunism is absent
or minimal, divergent interests of core and noncore segments can result
in considerable diversification costs (Kumar, 2013). Thus, harmonizing
the interests of various business segments is critical for not dissipating
potential synergistic benefits from diversification. For management
scholars to resolve the long-standing puzzle on the performance effects
of diversification, we need to account for the way these relationships are
managed.
Third, we show that PIEDs, by virtue of their expertise and
neutrality, can be the impartial arbiters needed to harmonize the
divergent interests of these business segments. While managers at the
core and noncore segments are invested in advancing their own in­
terests, it is incumbent on the corporate parent to harmonize their
divergent interests for the benefit of the whole firm. PIEDs with their
603
P. Arora and A. Gaur
Table 4
Diversification, benchmarked efficiency, PIED effort and ROA: alternate measures.
Method:
DV:
Model 7
FE
ROA
β
604
All control variables
Industry effects
Yes
PIED Effort
Related diversification (DR)
PIEDEFF × DR
Benchmarked firm efficiency (BFE)
PIEDEFF × BFE
Total diversification (DT)
PIEDEFF × DT
Unrelated diversification (DU)
PIEDEFF × DU
Benchmarked core efficiency (BCE)
PIEDEFF × BCE
Benchmarked noncore efficiency (BNE)
PIEDEFF × BNE
Constant
0.02
− 0.04
0.02
0.05
0.01
Observations
R-squared
Number of unique firms
F-test
7,084
0.048
1,096
5.684
0.00
Model 8
FE
ROA
se
p
β
Model 9
FE
ROA
se
p
Yes
(0.009)
(0.027)
(0.008)
(0.020)
(0.012)
(0.027)
[0.008]
[0.143]
[0.024]
[0.013]
[0.544]
[0.997]
(0.009)
[0.002]
0.05
0.01
(0.021)
(0.012)
[0.015]
[0.591]
− 0.02
0.01
(0.014)
(0.007)
[0.224]
[0.287]
7,084
0.047
1,096
5.374
se
p
Yes
0.03
− 0.00
β
Model 10
FE
ROA
(0.026)
[0.996]
0.02
se
p
Yes
(0.009)
[0.009]
− 0.08
0.02
(0.037)
(0.008)
[0.026]
[0.026]
0.04
0.01
(0.017)
(0.011)
[0.029]
[0.334]
0.00
(0.027)
[0.964]
7,084
0.048
1,096
5.975
β
Model 11
FE
TSR
0.03
β
se
p
Yes
(0.010)
β
se
p
Yes
Yes
[0.004]
0.16
(0.015)
[0.000]
0.03
(0.008)
[0.001]
(0.025)
(0.015)
(0.035)
(0.012)
[0.594]
[0.001]
[0.233]
[0.069]
0.06
0.01
− 0.09
0.02
(0.013)
(0.009)
(0.023)
(0.007)
[0.000]
[0.339]
[0.000]
[0.026]
(0.027)
[0.118]
− 2.41
(1.023)
[0.019]
− 0.09
0.02
(0.034)
(0.008)
[0.009]
[0.070]
0.01
0.05
0.04
− 0.02
0.03
− 0.01
− 0.07
(0.016)
(0.007)
(0.027)
[0.044]
[0.254]
[0.007]
− 0.04
6,677
0.057
1,042
7.538
Model 12
xthtaylor
ROA
7,407
0.036
1,118
11.41
7,084
1,096
7.832
Journal of Business Research 151 (2022) 593–608
Notes:
1. All models above used the same control variables as in Table 2. They are not reported above for parsimony.
2. Fixed effects models do not allow inclusion of industry control effects as any time invariant variable is dropped out. Moreover, we also benchmark firm efficiency against all single-segment firms in the same industry.
3. Model 12 summarizes results from Hausmann Taylor regression for endogenous covariates. All other models use fixed effects regressions.
4. Model 11 uses total shareholder returns as the dependent variable. All other models use return on assets as the dependent variable.
P. Arora and A. Gaur
Journal of Business Research 151 (2022) 593–608
Fig. 5. Interaction (margins) effect of Benchmarked Core Efficiency and PIED effort.
Fig. 6. Interaction (margins) effect of Benchmarked Noncore Efficiency and PIED effort.
expertise and distance from organizational politics are in a unique po­
sition of playing the role of neutral arbiters among various segments,
especially in situations of conflict. In doing so, we highlight the
importance of examining ‘parenting’ dynamics in diversification.
Overall, our study develops an efficacy-based view of corporate
governance for increased clarity on the nature of the relationship be­
tween governance, diversification, and firm performance.
For directors, it highlights the significance of their advisory role on top
of their normal monitoring duties to the firm.
4.4. Limitations and future research
Despite its methodological advances, our study is not without its own
limitations. First, we use measures of segment efficiency to proxy for
bureaucratic costs. We do not distinguish between bureaucratic costs
originating from coordination among business segments and parenting
costs (e.g., planning and reporting) imposed by corporate headquarters
(Campbell et al., 1995; Goold et al., 1998). In multi-segment businesses,
the existence of a corporate parent entails significant costs and benefits,
which ideally should be explicitly considered (Mukherjee et al., 2018).
Parsing these bureaucratic costs will help further gain a contextual un­
derstanding into the governance systems. Given the lack of this infor­
mation for our sample, we leave it for future research.
4.3. Practical implications
The role of directors is contextual in nature. Our study highlights the
significance of managing internal dynamics, i.e., the relationship be­
tween core and non-core segments, for reaping rewards from diversifi­
cation. Managers leading multi-business firms can use this
understanding for better firm performance. This study can also help
them understand how to assemble and use their boards in this endeavor.
605
P. Arora and A. Gaur
Journal of Business Research 151 (2022) 593–608
Second, despite its elaborate research design, this study is missing
other important variables that can potentially influence the nature of
these relationships. For instance, we do not consider ownership struc­
ture in our research design. Block ownership, family ownership, and
founders’ presence can all influence the nature of this relationship.
Future research may wish to explicitly account for these factors as well
to understand if various governance systems can compliment or sub­
stitute the advisory role of directors proposed in this study. For example,
is directors’ advisory role more important in family firms? Are firms
with dispersed more ownership more likely to need direct monitoring,
while those with concentrate ownership more reliant on directors’
resource-provisioning and service roles?
Third, our sample consists of mostly large firms from the United
States. For generalizing our results beyond this single institutional
context, we recommend future research to use a multi-country context
and present more conclusive evidence (Bhaumik et al., 2019; Mukher­
jee, et al., 2021). Replicating this study in other contexts will help reveal
the factors that support or impede directors’ efficacy in various insti­
tutional settings (Singh & Gaur, 2009).
Fourth, our findings suggest that there may be more than once
channel by which PIED effort may benefit firms or that these benefits
may be realized sequentially in a process that first results in raising
implementation efficiency, before it leads to a broader increase in firm
performance. We recommend future research to explore these avenues
further.
Lastly, Upper echelons theory has been used as a foundation for
studying the impact of top managers and directors on firm outcomes
since Hambrick & Mason’s (1984) groundbreaking paper on organiza­
tion as a reflection of its top managers. This theory surmises that exec­
utives’ experiences, values, and personalities greatly influence their
interpretations of the situations they face, which in turn affects firm
choices and outcomes. As it is extremely difficult to observe executives’
thoughts, values and processes, research relies on observable charac­
teristics such as age, education, and functional background.
While UET research claims that these more readily observable
characteristics can adequately surrogate for executives’ cognitive pro­
cesses (Talke et al., 2010), it cannot be confirmed with any degree of
certainty. Hambrick (2007, p. 337) laments that very few studies have
attempted to confirm whether and how executive characteristics affect
information processing, and that “psychological and social processes by
which executive profiles are converted into strategic choices still remain
largely a mystery — the proverbial black box.” Much like previous
research on the board of directors, this study also relies on directors’
demographic markers to proxy for their behavior. Despite the challenges
involved in collecting primary data for a large-scale study of this nature,
it will be worth its while for future research to explore that option. In
particular, it will be interesting to understand what motivates directors
to expand their effort in support of a focal firm. Further, as PIEDs also
expect to use their learning from their directorship in their regular
managerial roles (Carpenter & Westphal, 2001), how do they and focal
firms balance these somewhat divergent needs?
In conclusion, this study examined the role of quad-qualified PIED
effort in improving the performance of diversified firms. Using a longi­
tudinal sample of US firms, we show that the PIED effort become
increasingly beneficial to firms with every successive increase in
diversification level. Our results hold irrespective of the diversification
type used by firms. We also find that while the benefit of PIED effort is
apparent for all firms, it is especially useful for firms with high bench­
marked efficiency. This suggests that PIEDs are in a better position to
contribute to firm performance when firms succeed at raising their
implementation efficiency. More broadly, by showing the relevance of
directors’ domain expertise and effort in corporate diversification, we
provide a path forward for corporate governance and diversification
research.
CRediT authorship contribution statement
Punit Arora: Writing – review & editing, Writing – original draft,
Methodology, Formal analysis, Data curation, Conceptualization. Ajai
Gaur: Writing – review & editing, Writing – original draft,
Conceptualization.
Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
Data availability
The authors do not have permission to share data.
Acknowledgment
We thank seminar participants at Rutgers Business School for their
feedback on earlier versions of this paper.
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Punit Arora is an Associate Professor at City University of New York. He has a PhD from
Syracuse University. His research examines corporate governance and social responsibility
in various institutional settings. He is associate editor at Business & Society and Journal of
Asia Business Studies.
Ajai Gaur is a Professor at Rutgers University. He has a PhD from National University of
Singapore. In his research, Ajai studies the distinct institutional influences on firms’ in­
ternational expansion strategies in different institutional contexts. Ajai is a Fellow of the
Academy of International Business and currently serves as the Editor-in-Chief of Journal of
World Business. He was the president of the Asia Academy of Management from 2015 to
2019.
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