Melco Management Accounting Research
Discussion Paper Series
No.MDP2019-006

Sophistication of performance measurement systems in
manufacturing SMEs: Role of interpersonal ties in top management
teams

November 2019

Mohamed Ahmed
Graduate School of Economics, Kyoto University
Yoshida-honmachi, Sakyo-ku, Kyoto, 606-8501, Japanmohamed.ahmed.37r@st.kyoto-u.ac.jp

The Melco Foundation
Nagoya, Japan
Discussion Paper Series of the Melco Management Accounting Research, in order to promote
the study of management accounting, has published this unfinished paper onto the Web. Pleaseobtain the permission of the author when citing this paper.

Sophistication of performance measurement systems in manufacturing SMEs:
Role of interpersonal ties in top management teams
Abstract
This study explores the informal social relationship among top management teams (TMTs) in relation to
the sophistication of the performance measurement system (PMS) in small-and-medium sized
manufacturing companies. Drawing on social network theory, I argue that when TMT members network
based on interpersonal ties, as this would provide managers with easier excess to information andknowledge exchanges. Hence, informal relationships could facilitate their control over day-to-day activities,
thus reducing the need for adopting sophisticated management control practices. Using survey data on
2,058 manufacturing small and medium sized enterprises (SMEs) from World Management Survey
project, the negative impact of interpersonal ties in TMTs on PMS sophistication is confirmed. The results
also shed light on the key role of CEO in SMEs, and this negative association is larger in TMTs lead byinternally promoted CEOs compared to outsider CEOs. Further, interpersonal ties among TMTs moderate
the extent to which SMEs adopt sophisticated PMSs due to pursuing differentiation strategic priorities.
Keywords: performance measurement system; TMT interpersonal ties; CEO origin; social network
theory; differentiation strategy; manufacturing SMEs

1.

Introduction

Small and medium-sized enterprises (SMEs) have been facing increasing pressure to implement
management control systems (MCSs) to face competition and expand their operations. However, scareresources and a lack of managerial skills render adopting MCSs by SMEs challenging (Lavia López, &Hiebl, 2015). Therefore, extant studies on management control call for a better understanding of the drivers
for introducing formal MCSs in SMEs (e.g., Davila, 2005), especially those that influence the use of aperformance measurement system (PMS) (Heinicke, 2018). Over the past two decades, management
control literature has emphasized that the degree to which companies use MCSs is dependent upon several
organizational and environmental factors. One MCS literature stream investigates the influence of top
management team (TMT) characteristics on the adoption of and MCS. According to the upper echelons
theory (Hambrick, & Mason, 1984), MCS can be seen as an aspect of organizational structure (Chenhall,2003) and might thus be influenced by top management characteristics.
In line with this view, prior studies (e.g., Burkert, & Lueg (2013); Naranjo-Gil, Maas, & Hartmann,(2009); Pavlatos, & Kostakis (2018)) have examined the relationship between TMTs’ demographic
characteristics and the design and use of MCS. However, upper echelon theory researchers (Lawrence(1997); Priem, Lyon, & Dess (1999)) have criticized the overreliance on demographic-based attributes,

since they are not convergent with underlying psychological constructs and cannot account for their impact.
This limitation has called for more research to explore intra-TMTs’ behavioral and social relationships that
influence decision making and information and resource sharing (Hambrick, 2007; Lubatkin et al., 2006) .
In this study, I thus focus on the informal social ties (Oh et al., 2004) among TMT members to
explain the design and use of MCS in manufacturing SMEs. While the impact of TMT social ties on
strategic choices has received considerable intention in the management literature (e.g., Cao, Simsek, &Zhang (2010); Ensley, Pearson, & Amason (2002)), little is known about how interpersonal ties might
affect MCS design. One notable exception is the study of Speckbacher , & Wentges (2012), who examine
the relationship between family members involved in TMTs and the use of performance measurement.
However, their findings are moderated by company size, leading to the possible confounding effect ofcompany size, a well-documented factor impacts both the sophistication of MCS and social dynamics inteamwork (Lavia López, & Hiebl, 2015; Oh et al., 2004). Hence, our knowledge on informal social ties
between TMT members is still fragmented.
Therefore, drawing on social network theory (Kilduff, & Tsai, 2003), this paper examines both thedirect and indirect effects of interpersonal ties in TMTs (network density) on PMS sophistication, andwhether this relationship differs if social ties are between the TMT members and the CEO (network
centrality). I also explore how these informal social ties affect the direct relationship between company
strategic priorities and PMS sophistication. Specifically, I focus on the moderating effect of interpersonalties in TMTs on differentiation strategic priorities as an important driver for the adoption of sophisticated
PMS in manufacturing companies (Chenhall, & Langfield-Smith, 1998).
The study uses survey data of 2,058 SMEs manufacturing companies from the WorldManagement Survey (WMS) project. The survey data are collected as part of a larger research project thatgathers data on the quality of management practices in different sectors. I conjecture and prove that TMTs
in which team members have interpersonal ties are negatively associated with PMS sophistication.
Interestingly, this negative association is larger for TMTs lead by an insider CEO than those lead by anoutsider CEO. The analysis also confirms the hypothesized interaction effect of interpersonal ties in TMTs
on the differentiation strategies of companies.
The remainder of this paper is organized as follows. First, I review the literature on PMS
sophistication, upper echelon theory, and social network theory. Second, the research model is developed
based on the literature and the research hypotheses discussed. The research method, utilizing data fromWorld Management Survey (WMS), is described. The results based on construct measurement andordinary least square (OLS) models and analysis of variance (ANOVA) are then presented. Finally, theconcluding section discusses the research findings and their implications.

2.
2.1.

Literature review

Design and sophistication of management control systems

Contemporary management practices and firm structural innovations have driven MCS design(Chenhall, 2003) over the past decade to provide top management with the necessary information for
decision making and control (Teemu, 1997). The rise of manufacturing flexibility, total quality
management (TQM), and flat and decentralized organizational structures have led to the irrelevance oftraditional, efficiency-based MC practices and the emergency of new tools and techniques (Abernethy, &Lillis, 1995; Chenhall, & Langfield-Smith, 1998; Fullerton, & McWatters, 2002). Examples ofsophisticated MC practices include ABC (e.g., Teemu (1997)), target costing, non-financial performancemeasures (e.g., Fullerton, & McWatters, 2002), and value-based management (e.g., Burkert, & Lueg
(2013)).1
On one hand, as noted by Guenther, & Heinicke (2019, p. 9), "[MCS] sophistication levels should
be differentiated from the degree of embeddedness or dissemination within an organization (e.g. how
many divisions or departments are using the PMS)." In this regard, prior studies focused on the extent of
MCS practices and their determinants (e.g. Davila (2005)). However, this literature stream has been
criticized for not informing theory beyond the simple classification of “adopters versus non-adopters” of
MCS (Burkert, & Lueg, 2013). On the other hand, a few studies (e.g., Burkert, & Lueg (2013); NaranjoGil et al. (2009)) explored sophistication of MCS and the determinants of sophistication level differences.
The difference between the two streams is that the former investigated the use of some dimensions of
MCS, without focusing on what has been used, while the latter addressed specific innovative MC tools or
techniques and explored the differences among adopters. This stream is germane to the scope of this study,
so I will elaborate further on it.
In the literature, there is considerable interest in PMS sophistication as a part of MCSs. To better
understand the concept of PMS sophistication, I define PMS, sophistication, and their uses in the following.
A PMS is a set of metrics that tracks and monitors performance, enables communication andinfluences behavior, and is linked to the company strategy (Franco-Santos et al., 2007). Simons (1995)
distinguished between the diagnostic and interactive use of PMS. The diagnostic use links PMS to a
reward system for monitoring and goal achievement. The interactive use encourages the involvement of
the various managerial levels in the decision making process. Moreover, prior studies (e.g., Speklé, &Verbeeten (2014)) have also classified the uses of PMSs into three categories: (1) incentive-oriented use or
the use of performance measures in the reward system; (2) operational use, which includes monitoring,measuring and evaluating performance; and (3) exploratory use, which helps with strategy formation,communication of goals, and setting strategic priorities.
The PMS sophistication level can be broadly defined as "the extent of development of essential
design features, functions or processes of a specific PMS within a firm" (Guenther, & Heinicke, 2019; p. 3).
In examining the relationship between organizational culture and PMS sophistication, Henri (2006)1

For a review on MCS innovation, see Zawawi & Hoque (2011).

referred to sophistication as the diversity of financial and non-financial performance measures used by top
managers. Further, Guenther, & Heinicke (2019) highlighted the importance of linking these diverse
performance measures to reward, strategy, and planning systems.
Since measuring performance and rewarding and compensating behavior are among the mostimportant functions of PMSs (Franco-Santos et al., 2007), I define a "sophisticated PMS" as a multiperspective system (Speckbacher, & Wentges, 2012) that employs financial and non-financial measuresfor performance evaluation and promotion. This definition is in-line with previous studies that haveselectively investigated specific PMS purposes. For example, Abernethy, Bouwens, & van Lent (2010)
studied the impact of leadership style on the use of PMSs for compensation. Further, Speckbacher, &Wentges (2012) investigated the relationship between TMT composition and their use of PMS in
incentive contracts and strategic settings.
2.2. Upper echelon theory : Impact of TMT characteristics on MCS design
The seminal work of Hambrick, & Mason (1984) became the core theoretical framework forresearchers interested in the impact of CEO and/or TMTs on organizational outcomes (Carpenter et al.,2004). The premise of the theory is that TMTs’ values, cognition, and perception influence theirinteractions with the organizational environment, which in turn led to strategic choices that ultimately
impact organizational performance.
Upper echelon demographic-based studies used the external and observable characteristics of TMT,
such as gender, tenure, education, functional background, and experience (Bromiley, & Rau, 2016; Smithet al., 1994). These demographic characteristics have served as a proxy for the psychological construct of
the upper echelon theory by capturing the differences in upper-level managers' values, cognition, andperceptions (Carpenter et al., 2004). However, the findings of demographic-based research are divergent,
inconsistent, and have various impacts (Lawrence, 1997; Priem et al., 1999). As Priem et al. (1999) noted,
the overreliance on demographic attributes sacrifices construct validity, explanatory power, andprescriptive practicality. Further, demographic variables lack the hypothesized convergence with thesubjective psychological constructs theorized to influence organizational outcomes (Lawrence, 1997).
These limitations of demographic-based studies have provided the impetus for research employing
more psychological theories to explore what Lawrence (1997) labeled as the "black box" of organizational
demography. As such, a new literature stream examined TMT behavioral integration (Simsek et al., 2005),
social relationships (Cao et al., 2010), and personality traits (Peterson et al., 2003).
Therefore, prior MC studies have examined the link between TMTs’ demographic characteristics,
and the design and use of MCS. Their findings show that younger (e.g. Pavlatos (2012)), short-tenured (e.g.
Naranjo-Gil et al. (2009)), and business educated (e.g. (Morelli, & Lecci (2014)) TMTs are associated with

more sophisticated MC practices. However, these relationships are inconsistent and their results mixed(Hiebl, 2014).
Fewer studies investigated the CEO–TMT relationship and the effect of the social relationships
between TMTs and of CEO personal traits. The literature also studied how leadership (e.g., Abernethy,
Bouwens, & van Lent (2010)), creativity (Pavlatos, & Kostakis (2018)), and interaction with other TMTs((Lee et al., 2014) may impact MCS design.
2.3. Social network theory : Team dynamics and MCS use
Social network theory seeks to understand whether certain patterns of network relationships among
team members or business units affects the decision making patterns (Kilduff, & Tsai, 2003). The theory
helps in understanding how interpersonal ties (i.e., network density) among team members and leaders (i.e.,
network centrality) can lead to advantages (i.e., social capital) that may impact the team’s strategic
decisions.
Two main factors are important here to understand the impact of network ties, structure, andcontent of relationships between team members that determine the flow of resources (e.g., task-related
information) between them (Balkundi & Harrison, 2006). Network structure is concerned with the patternof connections among social parties. When the network is dense, team members have many connections
for example, through friendship or kinship ties, and the members are more inclined to share information
with their peers and trust each other. The theory also sheds light on the centrality of team connections
around one actor (Kilduff & Tsai, 2003). In this regard, if this actor is the team leader, the centrality canhelp improve team performance by providing the leader greater access for information and social support
from the team members, which facilitate control and decision making (Balkundi, & Harrison, 2006).
Network structure can also determine the nature of resources that flow through the network, in otherwords, the social network content, which leads to the classification of networks in instrumental andexpressive (Balkundi, & Harrison, 2006). In expressive networks, when the relationship between teammembers is more informal, members are more likely to show higher levels of collaboration, interaction,and expertise and information sharing beyond relevant team tasks. By contrast, instrumental networks areformal structures, where members only share acceptable and necessary work-related knowledge.
The impact of social ties on organizational outcomes has been widely investigated in management
literature. Related studies explored how the interpersonal relationship between CEO and TMT members
affect strategic choices. For instance, Cao, Simsek, & Zhang (2010) found that CEO network density andcentrality positively influences organizational ambidexterity. They also found that CEOs with wide internaland external networks can gain access to rich and timely information about their firms’ environments and a
deeper understanding of the firms’ exploitative and exploratory options. However, the impact of thisinformational advantage on ambidexterity is hinging upon the richness of communication between theCEO and TMT through discussions and analyses. Westphal (1999) found that CEOs with social ties withboard members are more willing to seek directors’ advice on strategic decisions. The study also found that
CEOs are more likely to take the professional and social risk associated with this advice. since they trust
their board members.
However, few existing MCS studies have hitherto explored the relationship between the social ties
among team members and MCS design. For example, Towry (2003) examined the impact of social ties inteamwork on the effectiveness of two monitoring and incentives systems. She found that, when team
identity is strong, team members are more likely to behave cooperatively in ways that are best for theirteam. However, the directional effect of their cooperative behaviors on effort depends on whether themonitoring and incentive system is vertical or horizontal. Coordination behavior thus undermines theeffectiveness of a vertical incentive system, in which members report the observations of their teammates'
efforts to the leader. Conversely, a strong team identity can enhance the effectiveness of a horizontal
incentive system, in which members directly control the actions of other members.

3. Hypotheses development
Here, I first elaborate on the hypotheses related to the effect of interpersonal ties in TMT, on thesophistication of PMS and their interaction with strategy. Then, we explore the impact of considering CEO
origin on PMS sophistication.
3.1. Interpersonal ties in TMTs and PMS sophistication
We argue that interpersonal ties in TMTs are negatively related to PMS sophistication. Thisconjecture is supported social network theory and the recent literature on MCS. According to social
network theory, informal or social ties between team members are indicators of high network density, thatis, members are well connected to each other in their work environment (Balkundi & Harrison, 2006).
This richness in communication will facilitate the information flow within the team (Cao et al., 2010),
which may compensate for the need of maintaining or establishing an advanced MCS.
This argument has been further corroborated by recent MCS studies on the involvement of family
members in top management. This literature stream concluded that family-dominant TMTs are less likely
to use formal MCS practices, since loyalty, trust, and a shared vision between team members lowers theneed for these practices (Helsen et al., 2017). In this regard, Hiebl, Feldbauer‐Durstmüller, & Duller (2013)
explored the drivers of MC institutionalization, in terms of hiring management accountants, establishingmanagement accounting departments, and the use of strategic and operational management control
practices, in family firms. They concluded that the presence of family members in TMTs is negatively
associated with MC institutionalization. In a similar vein, Speckbacher, & Wentges (2012) reported thatfamily-dominant TMTs are using PMSs and incentive contracts to a lower extent. Accordingly, I
hypothesize that:
H1: There exists a negative relationship between interpersonal ties among TMTs and PMS
sophistication.
3.2.

Differentiation strategy and PMS sophistication
In line with prior management control studies, this study adopts Porter 's typology (1985) andconceptualizes strategic priorities as an organizational choice between cost-leadership and differentiation
strategies. Manufacturing companies with differentiation strategic priorities are characterized by seeking
new markets, high quality, product uniqueness, fast delivery, and flexibility. However, cost leadershipcompanies face reeducation cost and compete primarily on price and operational efficiency. Any of thesemanufacturing strategic priorities require employing different management techniques (Chenhall, &Langfield-Smith, 1998), and thus different PMSs.
There exists a discussion in the literature on the relationship between manufacturing strategic
priorities and the characteristics of PMSs (Langfield-Smith, 1997). The empirical evidence suggests that
manufacturing strategic priorities (i.e., differentiation strategy) that emphasize team-based structures, justin-time techniques, TQM management, and cross-integrated information systems require more advanced
PMSs (Chenhall, & Langfield-Smith, 1998). As such, a differentiation strategy renders efficiency-based
performance measures irrelevant and requires the inclusion of operational and non-financial performancemeasures to provide more insights than aggregated financial reports (Fullerton, & McWatters, 2002;
Naranjo‐Gil, & Hartmann, 2006). This discussion yields the following hypothesis:
H2: There exists a positive relationship between pursuing a differentiation strategy and PMS
sophistication.
3.3.

Interaction effect of interpersonal ties in TMTs
I expect that interpersonal ties in TMTs as an upper echelon characteristic moderate the effect ofstrategy on the use of sophisticated PMSs. It hypothesize that, while a differentiation strategy requires the
adoption of a sophisticated PMS, TMT interpersonal ties may provide managers with an alternative,
informal way for information exchange and process control, making them more likely to perceive
advanced performance measures as unnecessary.
This argument reflects the substantial evidence from the upper echelon literature on the interaction
between TMT characteristics and the organizational contingencies impact managers’ strategic choices(Naranjo-Gil et al., 2009). According to Ensley, Pearson, & Amason (2002), while complex andambiguous strategies may give rise to a cognitive and affective conflict between TMT members indecision making, the interpersonal ties between the team members promote mutual understanding, trust,better communication, and interaction that overcome any cognitive conflict. This conclusion was
corroborated by Carpenter (2002), who found that TMT social relationships moderate the impact of teamheterogeneity on firm performance in complex strategic environments. (Lubatkin et al., 2006) further
reported that behaviorally integrated TMTs promote the open exchange of contradictory opinions, thus
sharing explicit and implicit knowledge and discussing market opportunities that facilitate the adoption ofambidexterity.
Several MC studies provided evidence on the interaction effect between TMT characteristics andthe strategy–MCS relationship. For instance, de Harlez, & Malagueño (2016) studied how TMT personal
background can impact the effectiveness of using a PMS for supporting hospital strategies. They foundthat top managers with a clinical background can better align the use of PMS with the hospital’s strategic
operational priority than their peers with an administrative background. Naranjo-Gil et al. (2009) reported
that the positive effect of strategy on innovative MCS is more pronounced for younger, less-tenured, andbusiness oriented CFOs. This discussion leads to the following hypothesis:
H3: The interpersonal ties in TMTs moderate the effect of differentiation strategies on PMS
sophistication.
3.4.

CEO origin and PMS sophistication
I predict that the impact of interpersonal ties among TMTs differs based on CEO origin. I

hypothesize that the negative impact of TMTs’ interpersonal ties on PMS sophistication is more
pronounced in teams with insider CEOs than in those with outsider CEOs. This argument is supported by
two literature streams. In the first, strategic management studies on CEO origin as a predictor of strategy
formulation and organizational performance argue that insider and outsider CEOs have different
characteristics. While insider CEOs have a deep knowledge of company operations and accumulated
experience on its markets, customers, and products (Chung, 1987), they may fail to adopt innovation
strategies or cope with uncertainties, since they might lack the experience or required skills (Fondas, &Wiersema, 1997) compared to outsider CEOs. The reason for this is insider CEOs are more constrained bytheir past experience within the firm, while outsider CEOs are more likely to bring relatively novel
practices and knowledge that have a disruptive effect (Zhang et al., 2016). Insider CEOs are thus more
likely developed social ties with their subordinates and senior managers, which might facilitate their control
through better access to information (Chung, 1987).
The second literature stream studied how the interpersonal ties between the CEO and TMT
members may hinder the formalization and introduction of MC practices in organizations. In this regard,
insider CEOs can rely on their social ties to compensate the role of MCS. For example, El Masri, Tekathen,
Magnan, & Boulianne (2017) reported that family CEOs are relying on pragmatic management practices,gut-feeling, trust, people, and familial relationships within the firm as alternatives to formal MC tools.

Even when their businesses grow, they focus on the survival and prosperity of the family through financial
performance aspects (Dello Sbarba, & Marelli, 2018) and do not embrace advanced MC practices. This
discussion suggests the following hypothesis:
H4: The negative impact of TMT interpersonal ties on PMS sophistication is larger in TMTs withinsider CEOs than those with outsider CEOs.

4. Research method
4.1.

Survey data
This study uses data from WMS, which is an international initiative to collect data on the quality ofmanagement practices across countries and industry sectors. The survey instrument and its methodology
are reported by Bloom, & Van Reenen (2007). The WMS uses an innovating survey approach that
reduces respondent and interviewer bias (Bloom, & Van Reenen, 2010). First, the survey collects datafrom plant senior managers over the phone using a double-blind methodology, where managers are notbeing told they are scored and interviewers have no prior knowledge of the organization’s performance.
Second, the survey asks open questions and managers are asked to support their answers with realpractices inside their companies. Third, to reduce interview bias, the survey collects data on the interview
day, time, and duration. The interviewers are also asked to grade the degree of cooperation of theinterviewee to measure interview reliability.
This paper uses a dataset of 7,094 observations of randomly sampled medium-sized firms(employing between 50 and 5,000 workers) in the manufacturing sectors of 17 countries. For the purposeof this study, SMEs are defined using the dominant definition in MC literature, that is, companies withfewer than 500 (Heinicke, 2018). In total, 2,058 SMEs are used in the analysis. Table 1 summarizes the
profiles of respondent companies by country, industry sector, and number of employees.
4.2.

Variable measures
Measures for each construct were chosen from the literature, and Table 2 reports the descriptive

statistics of the survey items used in this study. To select survey items that assess PMS sophistication, priorstudies on PMS sophistication (Guenther, & Heinicke (2019); Henri (2006); Speklé, & Verbeeten (2014))
were examined. This resulted in the selection of seven survey items, representing two dimensions of PMS,
namely performance evaluation and reward system.
For the independent variable, familial ties are used to construct interpersonal ties in TMTs. I
followed Speckbacher, & Wentges (2012) in defining family involvement in TMTs as the dominance offamily members on the control and management of the firm, which represents 20% of the sample. Then, I
defined CEO origin, based on whether the CEO is a family (insider CEO) member or non-family member(outsider CEO).

The measurements items for the differentiation strategy are adopted from the studies of Chenhall, &Langfield-Smith (1998), and Fullerton, & McWatters (2002). Three survey items assessing the adoption oflean manufacturing practices were selected as indicators of pursuing a differentiation strategy.
Table 1 Respondent profiles
Panel A: Countries
Argentina
Australia
BrazilChile
China
FranceGermany
Great Britain
GreeceItaly
Japan
Northern Ireland
PolandPortugal
Republic of Ireland
SwedenUnited States
Total

Panel B: Industry
2
3
2
1
129
239
61
550
145
143
68
82
150
150
85
176
72
2058

Construction trade
Food And Kindred Products
Textile Mill Products
Apparel and Other Fabrics
Lumber and Wood Products
Furniture and Fixtures
Paper and Allied Products
Printing, and Publishing
Petroleum Refining
Rubber and Plastics Products
Leather Products
Stone, Clay, Glass, and Concrete Products
Primary Metal Industries
Fabricated Metal Products
Industrial and Commercial Machinery
Electronic and Other Electrical Equipment
Transportation Equipment
Measuring, Analyzing Instruments
Miscellaneous Manufacturing Industries
Wholesale Trade—Durable Goods
Wholesale Trade—Non-Durable Goods
Real Estate
Holding and Other Investment Offices
Business Services
Miscellaneous Repair Services

4
286
70
52
48
43
92
71
11
124
31
84
84
206
195
176
84
93
71
19
19
7
9
12
6

Panel C: Firm size
1–150
151–300
301–450
< 500
Total

773
833
377
75
2058
I also included control variables for the effect of size, country, industry, and interview bias. Prior

studies (Hiebl et al., 2013; Speckbacher, & Wentges, 2012) found that the influence of interpersonal ties inTMTs diminishes in large and medium-sized companies and an increase in size leads toprofessionalization and the adoption of sophisticated MC practices. Therefore, this study controls for firmsize, measured by the number of employees. Since SMEs managers in developing countries may havelower educational level and limited knowledge of MC practices (Lavia López, & Hiebl, 2015), country
dummies are included in the analysis. Finally, to control for interview bias, the interview reliability scores
are also included.
Table 2 Descriptive statistics
Constructs and indicators
Performance evaluation
Track performance using meaningful metrics
Key measures are reviewed regularly
Use a balance of financial and non-financial
measures
Results are discussed in meetings for feedback
Reward system
Reward employees based on theirperformance
Identify and remove bad performers
Promote employees based on theirperformance
Differentiation strategy
Introduce and apply lean manufacturing
techniques
Utilize lean techniques to meet business goals

Theoretical Practical
range
range

Mean

Median

SD

1̶ 5
1̶ 5

1̶ 5
1̶ 5

3.36
3.32

3.00
3.25

0.97
0.95

1̶ 5

1̶ 5

2.88

3.00

1.07

1̶ 5

1̶ 5

3.13

3.00

0.96

1̶ 5

1̶ 5

2.45

2.00

0.96

1̶ 5

1̶ 5

3.08

3.00

0.96

1̶ 5

1̶ 5

2.98

3.00

0.89

1̶ 5

1̶ 5

2.79

3.00

1.08

1̶ 5

1̶ 5

2.86

3.00

1.13

Control variables
Firm size̶̶
208.51
184
113.96
Interview reliability score
1 ̶ 104 ̶ 10
7.88
8.00
1.59
Following the selection of survey items, exploratory factor analysis (EFA) is conducted using R
3.6.0. The method employed is principal component analysis (PCA) with varimax rotation across nine
items using the full dataset of SMEs (n = 2,058). Factor loadings greater than an absolute value of 0.60 are
considered for further analysis. The PCA extracted three factors that explain 68% of the variance and one
item was removed due to cross-loading greater than 0.40. See Table 3 for factors loadings, percentage ofvariance explained, and the Cronbach alpha of each construct. Cronbach’s alphas are between 0.63 and
0.86, thus supporting construct reliability.
4.3. Data analysis

To test hypotheses H1–H3, an OLS regression model is estimated as follows:
PMSi  β0  β1INTP  TMTit  β2 DIFF  STRATEGY β3( DIFF  STRATEGY*INTP  TMTit )  β4 SIZEit itit
β5 COUNTRY
 β6 INDSTit  β7 RELIABILTY
 εit
it
it

where PMSi is a measure of the PMS sophistication level and INTP-TMT and DIFF-STRATEGY areconstructs for interpersonal ties in TMTs and differentiation strategy, respectively. The interaction term in
the model tests for the moderating effect of the interpersonal ties in TMTs on the differentiation strategy.
The remaining four variables are proxies for the control variables.
ANOVA was also conducted to explore the impact of CEO origin on the sophistication level of
PMS to test H4. The TMT group included in the prior analysis (INTP-TMT) was divided into two groups
according to their CEOs’ origin: family affiliated CEO (insider CEO), and externally hired CEO (outsider
CEO). Additionally, the analysis included the two PMS sub-constructs—performance evaluation andreward system—for a more refined analysis.
Table 3 Exploratory factor analysis, loadings, reliability, and validity
Factor 1
Performance evaluation (four items)
Track performance using meaningful metrics
Key measures are reviewed regularly
Use a balance of financial and non-financial measures
Results are discussed in meetings for feedback

Factor 2

0.73
0.83
0.63
0.80

Reward system (three items)
Reward employees based on their performance
Identify and remove bad performers
Promote employees based on their performance

0.74
0.74
0.66

Differentiation strategy (two items)
Introduce and apply lean manufacturing techniques
Utilize lean techniques to meet business goals
Factor loading
Percentage of variance explained
Cronbach’s alpha (α)

Factor 3

0.90
0.83
2.59
42%
0.82

1.77
29%
0.63

1.80
29%
0.86

5. Results
Table 4 shows the Pearson correlation matrix for the dependent, independent, and control variables.
The table shows that interpersonal ties in TMTs (INTP-TMT) are negatively correlated with thesophistication of PMS (PMS) and both of its two components—performance evaluation (PERF_EVL)
and reward system (REWARD). The existence of a differentiation strategy (DIFF-STRATEGY) ispositively correlated with PMS sophistication (PMS). For the control variables, firm size (SIZE) is
positively correlated with the sophistication of PMS (PMS) and all its sub-constructs. None of the pairwise correlations among the variables is substantially higher than 0.6 and the variance inflation factor (VIF)
ranges from 1.01 to 1.11, suggesting no evidence of multicollinearity.
Table 5 depicts the regression results for the dependent variable, PMS sophistication (PMS). Model
1 includes the control variables and main effect constructs to test H1 (INTP-TMT) and H2 (DIFFSTRATEGY). Model 2 shows the control variables and the two main effects and interaction term (INTPTMT* DIFF-STRATEGY) to test H3. VIF ranges from 1.375 to 1.380, meaning multicollinearity is not a
problem.
Table 4 Pearson correlation matrix
1

2

3

4

5

6

7

1. PMS
2. PERF_EVL

0.82

3. REWARD

0.85

0.52

4. INTP-TMT

-0.11

-0.08

-0.13

5. DIFF-STRATEGY

0.36

0.62

0.42

-0.06

6. SIZE (LN)

0.15

0.17

0.13

-0.02

0.15

7. RELIABILITY

0.24

0.30

0.16

0.04

0.24

0.05

Correlations with an absolute value of 0.06 or higher are significant at p < 0.05.
H1 predicts that the interpersonal ties in TMTs are negatively associated with the adoption ofsophisticated PMSs. In Model 1, as shown in Table 5, INTP-TMT is negative and significant (t = -3.057; p< 0.01). This result supports H1. H2 presumes a positive effect of pursuing a differentiation strategy on
PMS sophistication. Model 1 shows that DIFF-STRATEGY is positive and significant (t = 12.33; p <0.001). This result provides support for H2.
Regarding the interaction hypothesis, H3 predicts that the positive relationship between adifferentiation strategy and PMS sophistication is moderated by the effect of interpersonal ties in TMTs.
The results of Model 2, as shown in Table 5, support H3. The interaction term (INTP-TMT × DIFFSTRATEGY) is negative and significant (t = 12.33; p < 0.001). The adjusted R2 for Model 2 with theinteraction term (0.197; p < 0.001) is significantly higher than adjusted R2 for Model 1 (0.195; p < 0.001)
without the interaction term (∆R2 = 0.001; p < 0.05).
In testing for the proposed impact of CEO origin, Table 6 shows the results of ANOVA forcomparing the mean value of PMS sophistication between two subsets of TMTs—TMTs with insider
CEO (n = 350) and TMTs with outsider CEO (n = 71). H4 predicts that when TMT members have socialties with their CEO (insider CEO), this would more negatively impact the adoption of a sophisticated PMS
compared to teams with an outsider CEO. ANOVA shows that the two subsets show a significantly
different mean for PMS (F = 12.03; p = 0.000). This result is also significant for the two sub-dimensions of
PMS—performance evaluation (F = 21.51; p = 0.000) and reward system (F = 6.31; p = 0.000)—for thetwo sub-groups of CEOs. Therefore, H4 is supported.
Table 5 Regression results for Hypotheses 1–3
Dependent variable: PMS
Model (1)Model (2)β(t-stat)β(t-stat)Independent variables
Main effects:
INTP-TMT
DIFF-STRATEGY-0.278**0.410***-3.057
12.331

Interaction :INTP-TMT × DIFFSTRATEGY
Control
SIZE
RELIABILITY
COUNT
INDUST

0.143**
0.132***
YES
YES

R2
Adjusted R2

0.265
0.187

3.025
6.449

0.089
0.441***

0.402
12.035

̵ 0.151*0.074

0.143**
0.132***
YES
YES

3.093
6.467

0.266
0.188

* p < 0.05, ** p < 0.01, *** p < 0.001.

6. Discussion and conclusions
This study seeks to understand the factors that support or impede the introduction of advanced MC
techniques in SMEs, particularly the use of sophisticated PMSs in manufacturing companies. I predict anddemonstrate that the adoption of a sophisticated PMS would be influenced by two factors: theinterpersonal relationships between TMT members and organizational strategic priorities, namely adifferentiation strategy. The analysis of the survey data reveals that the need for sophisticated PMS isnegatively associated with TMTs whose social networks are dense due to interpersonal links. I also showthat manufacturing companies pursuing differentiation strategic priorities are more likely to use
sophisticated PMSs. Additionally, the extent to which the use of a differentiation strategy impacts
sophistication is moderated by the interpersonal ties in TMTs.

Furthermore, the study highlights the key role of CEOs in SMEs’ top management by examining
whether having interpersonal ties between TMT members and CEO could predict any difference inadopting sophisticated PMS. The analysis supported the hypothesis that the sophistication of PMS issignificantly different between TMTs with insider CEO, and outsider CEO.
Table 6 Analysis of variance between TMTs with insider and outsider CEOs
PMS

Performance
evaluation

Reward system-0.390
0.231

2.98
3.44

2.84
2.61

ANOVA
Sum of squares
Between groups
Within groups
Total

21.8
710.8
732.6

12.45
238.59251.042.96
194.55
197.51d.f.
Between groups
Within groups
Total

1
393
394

1
412
413

1
415
416

Mean square
Between groups
Within groups

21.7561.809

12.4540.579

2.9584
0.4688

F statistic
Significance

12.03
0.00

21.51
0.00

6.31
0.05

Mean
INSIDER_CEO (n = 350)
OUTSIDER_CEO (n = 71)
Total (n = 421)

The findings of this study contribute to the management control literature by pointing out theimportance of considering social relationships between TMTs and not relying only on demographic
characteristics in studying the effect of TMTs on MCS use and design. In this regard, the study also
contributes to the discussion on the social and personal traits of the CEO–TMT relationship on MCS use(Abernethy et al., 2010; Hartmann et al., 2010; Lee et al., 2014) by explaining the importance of the CEO’s
origin in understanding the effects of TMT social relationships. Specifically, I show that the impact ofinterpersonal ties in TMTs is more pronounced when the CEO is appointed internally than when an
outsider CEO is recruited. Therefore, the study supports and refines the conclusions of Speckbacher, &Wentges (2012) and provide further explanations for their mixed results.

Several studies (de Harlez, & Malagueño, 2016; Naranjo-Gil, & Hartmann, 2007; Naranjo-Gil etal., 2009) explored how TMT characteristics affects the strategy–MCS relationship. This paper also
contributes to this literature stream by reporting the negative interaction effect of interpersonal ties in TMTs
on the relationship between differentiation strategies and PMS sophistication.

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