Melco Management Accounting Research
Discussion Paper Series
No.MDP2019-002

The Influence of Parent-PMS on Subsidiaries’ Decision-Making:Process of Parent-PMS Use and Subsidiaries’ External
Embeddedness

January 2019

Yudai Onitsuka
Graduate School of Business and Commerce, Keio University

2-15-45 Mita, Minato-ku, Tokyo
108-8345, Japane-mail: yudai-onitsuka@keio.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.

The Influence of Parent-PMS on Subsidiaries’ Decision-Making: Process of ParentPMS Use and Subsidiaries’ External Embeddedness

Yudai Onitsuka

Abstract
This study investigates the influence of parent-PMS on subsidiaries’ decision-making, and theinteraction effects of the parent-PMSuseand subsidiaries’ external embeddedness. In
particular, this study analyzes the moderating effects of the subsidiaries’ external
embeddedness on the cause-effect relation between parent-PMS use and the influence ofparent-PMS on subsidiaries’ decision-making. The analyses using survey data from 199 topmanagements in Japanese subsidiaries indicate that subsidiaries’ embeddedness in customers
negatively moderates the influence of the interactive use of PMS by headquarters althoughsubsidiaries’ embeddedness in suppliers positively moderates the influence of the interactive
use of PMS by headquarters.

Keywords
multinational company, headquarter-subsidiary relationship, control subsidiaries, performance management
systems, embedded theory

1. Introduction
Multinational companies’ operations, including control over subsidiaries, are difficult to manage due todifferences and distances (i.e., physical, geographical, cultural, psychological, and so on) between headquarters andsubsidiaries. In addition, market pressures due to developing globalization urged multinational companies (MNCs)
to re-design their strategies, structures, and processes (Govindarajan & Gupta, 2000; Ghoshal & Bartlett, 1996).
Globalization forced MNCs to seek competitive advantage in theglobal market through more standardization andcoordination within, while simultaneously needing flexibility and local responsiveness (Ezzamel et al., 1999).
Moreover, the information and knowledge that subsidiaries can obtain from local environments are also importantin generating a competitive advantage in the global market. Hence, headquarters should delegate decision-making
capabilities to subsidiaries and encourage autonomy (McEvily & Zaheer, 1999). The international business
literature argues that to adapt to such complex environmental and managerial difficulties, MNCs developed
considerably from a dominant headquarters with hierarchically-controlled subsidiaries to a complex set ofinterdependent, globally-dispersed entities structured as multifaceted networks (Dunning & Lundan, 2008;
Harzing, 1999). MNCs thus face the challenge of balancing the delegation of decision-making authority to
subsidiaries effectively, encouraging subsidiaries’ autonomy and independence from headquarters, andcoordinating global activities (Busco et al.,2008; Quattrone &Hopper,2005; Roth &Kostova,2003).
When MNCs delegate decision-making authorityto subsidiaries and encourage autonomy, headquarters
must deploycontrolmechanisms that align subsidiaries’ activities withthe MNCs’globalstrategyandofferrelevant
information for managerial decision-making, both at headquarters and at the subsidiaries (Doz &Prahalad,1984;
Luo 2005). Recently, some management accounting studies find that headquarters performance management
systems (parent-PMS) are effective mechanisms to control subsidiaries and their activities into the firm’s global
strategy(Busco et al.,2008;Dossi&Patelli,2008, 2010;Mahlendorfet al.,2012; Micheliet al.,2011). Thesestudies
argue that parent-PMS provide important information for decision-making at all levels because they reflect thefirm’s global strategy and intentions, and allow MNCs to monitor and follow subsidiaries’ activities. Parent-PMSs
integrate subsidiaries’ autonomous activities into overall corporate goals by assisting and influencing subsidiaries’
decision-making (Mahlendorfet al.,2012). However, priorresearch does not completelyshowthe effectsofparentPMS on subsidiaries, especially the mechanisms and processes of the effects of parent-PMSs on subsidiaries’
decision-making (Busco et al.,2006). The evidence from prior research is mixed and inconsistent.
These issues can be due to two overlooked perspectives. First, prior studies rarely focus on the use ofparent-PMS (Dossi &Patteli, 2008; Franco-Santos et al., 2012). While some do consider the use of parent-PMS(i.e., Dossi & Patelli, 2008; Mahlendorf et al., 2012), the results are limited because these studies focus on the
purpose of the use of PMS, but not on the process of parent-PMS use. According to Ferreira &Otley (2009), this
aspect is important for PMS research to clarify the effects and mechanisms of the influence of PMS withinorganizations. Moreover, when examining the influence of PMS on decision-makers, it is important to address theuse of PMS (Langfield-Smith,1997; Simons,2000). Notwithstanding these arguments, most research focuses onthe structural features and aspects ofthe PMS design, and thus unresolved issues remain about the effects ofparentPMS(Busco et al.,2006;Dossi&Patelli,2008;Doz et al.,2001; Franco-Santos et al.,2012;Nørreklit &Schoenfeld,
2000; O’Donnell,2000).
Second, although prior research explains that the effects ofparent-PMS relate to the relational attributes ofthe multinational network (Dossi & Patelli, 2008), which does not sufficiently capture the relationship between
headquarters and subsidiaries. Some international business studies argue that when investigating this relationship, it
is necessary to focus not only on headquarters’ control mechanisms, but also on the external network, which
influences subsidiaries’ activities directly and indirectly (Andersson & Forsgren, 1996; Doz & Prahalad, 1993;
Forsgren, 1989). Based on the resource dependence theory, the characteristics of the networks of each subsidiary
explain thedifferent attributesofan MNC(Ghoshal&Bartlett, 1990, 1993). Recently, internationalbusiness studies
point out that the external networks in which the subsidiaries are embedded, referred as external embeddedness,
influences the headquarters’ control mechanisms (Andersson & Forsgren, 1996; Andersson et al., 2001;
Anderssonet al.,2005). Similarly, the management accounting literature suggests that the influence ofparent-PMS
on subsidiaries depend on subsidiaries’ external embeddedness (Mahlendorf et al.,2012; Schäffer et al.,2014).
Therefore, this study investigates the influence of parent-PMS on subsidiaries’ decision-making, and therelationship between the use of parent-PMS and subsidiaries’ external embeddedness. In particular, this study
analyzes the moderating effects of the subsidiaries’ external embeddedness on the cause-effect relation between
parent-PMS and subsidiaries’ decision-making by combining theoretical perspectives and the results of data
analysis.
This paper proceeds as follows. Section 2 reviews the PMS and international business literature, andestablishes the hypotheses.Sections3 and4 describe theresearchmethods andresults. Section5discussestheresults,
conclusion, contributions, limitations, and avenues for future research.

2. Theoretical backgrounds and hypotheses
2.1. The process of PMS use
In management accounting research, several authors define and categorize the use of PMS. Regarding
the use ofPMS, Hopwood (1972) explains that firms use PMS to make use ofaccounting information to evaluate
the performance of the organization and management. Similarly, Bourne et al.,(2000) argues that the use of PMS
is“split into two main subdivisions; first, the initial use to which they should be put is that of measuring the successof the implementation of that strategy, second, the information and feedback from the measures should be used tochallenge the assumptions and test the validity of the strategy (pp. 758)”.

In addition to these procedural aspects, Simons (2000) explains the processes of the use of PMS byadopting the diagnostic and interactive controlaspectsofthe leversofcontrolconcepts suggested bySimons (1995).
In his explanation, the processes of the use of PMS relate to accounting information flow, specifically how
information on performance is communicated within organizations when measuring and evaluating performance,
the feedback process, and reporting the results of activities to superiors. Henri (2006a) similarly points out that the
aspect of accounting information flow is more important in the use of PMS. Moreover, Ferreira &Otley (2009)
argue that “the use made of information and controls is a cornerstone of the PMS (pp.274)”, and captures the useof PMS as a way to use accounting information and adopt control mechanisms. They also argue that it is more
important to capture how and what types of control practices exist within organizations and the information flow
processes in investigating the effects of PMS.
However, there is little researchonparent-PMS and its use processes. For example, Dossi &Patell (2008)
and Mahlendorf et al.,(2012) focus on the purpose of PMS, though do not consider accounting information flow
and control practices within MNCs. Hence, it is unclear that how headquarters can control subsidiaries’ decisions
and actions by using PMS.
Therefore, in this study, the use ofPMS is seen not only in its procedural aspects (i.e., the purpose ofPMS,
measuring and evaluating performance, and reporting and explaining accountability), but also in the processes of.
In doing so, we refer to the “diagnostic use ofPMS” and “interactive use ofPMS” following Simons (1995, 2000)
as a typology to capture the processes of PMS use by considering information flow and control practice byheadquarters.

2.1.1. Diagnostic use ofPMS
Simons (1995) defines diagnostic control as managers’ use information systems to monitor
organizational outcomes and correct deviations from preset standards of performance. Diagnostic PMS use is thesetting of goals and key success factors as opposed to overall strategy, measuring outputs, analyzing variances, andusing variance informationto adjust activities (Simons,2000). When managers use PMS diagnostically, they focus
on and act to correct business units’ and subordinates’ activities only when significant issues occur and when they
identify significant deviations (Simons,2000).
Diagnostic PMS use motivates employees to implement organizational strategy and integrate theiractivities to accomplish the organization’s goals (Widener,2007). Prior research suggests that employees’ activities
belong to categories that top-managers expect or do not expect so employees can understand how to work toaccomplish the organization’s goals by using PMS diagnostically (Tuomela, 2005). On the other hand, Henri(2006b) defines the diagnostic use of PMS as a set of formalized procedures that use information to maintain oralter patterns in an organizational activity, and argues that the diagnostic use of PMS has important characteristics
as a mechanistic control. Firms can enable tight control and elaborate information and communication flow byusing a PMS that includes such characteristics, and thus the diagnostic use of PMS enhances decision-making

capability (Koufteros et al.,2014).
Although there is no empirical evidence on the diagnostic use of parent-PMS in international businesssettings, we can assume that the effects of parent-PMS on the relationship between headquarters and subsidiaries
correspond withthe suggestions above. The headquarters sets global strategy and overall goals in advance, and thenmonitor subsidiaries’ activities by using the parent-PMS diagnostically, to integrate subsidiaries’ activities into
global strategy and the overall goals, similar to a non-internationalbusiness setting. Hence, the headquarters can use
PMS diagnostically to have a positive effect on subsidiaries’ decision-making. Therefore, we propose our first
hypothesis:
H1. The headquarters’ diagnostic use of parent-PMS is positively correlated with the influence of parent-PMS on
subsidiaries’ decision-making.
2.1.2. Interactive use of PMS
Simons (1995) defines interactive control as managers’ use of information systems for their personal
involvement in subordinates’ decision activities. The interactive use of PMS is very different from diagnostic use.
When managers use PMS interactively, they constantly communicate their intent to subordinates and participate insubordinates’ decision activities to adapt these activities to strategic uncertainties and to find opportunities to growtheir business (Simons 2000). Thus, in organizations in which managers use PMS interactively, all members areconstantly interested in information about performance because communicating this information is a daily activity.
The distinct characteristics of the interactive use of PMS include frequent meetings and face-to-face
discussions about performance between superiors and subordinates (Bisbe et al., 2007), which allow anorganization to deal effectively with problems. Hence, interactively using PMS helps firms make decisions bycommunicating information about performance to decision-makers and sending signals throughout theorganization (Abernethy &Brownell, 1999; Bisbe &Otley, 2004; Henri,2006b). In addition, empirical evidence
suggests that the interactive use ofPMS enables headquarters to capture allofthe activities and conditions within an
organization, and enhances decision-making capabilities, resulting in overall financial performance (Koufteros etal.,2014).
In MNCs, the headquarters’ interactive use of PMS stimulates dialog between headquarters andsubsidiaries and enhances strategic alignment within an organization (Dossi & Patelli, 2010). Conversely,
subsidiaries might understand the headquarter’s intent, their decision making, and the behaviors it expects.
Therefore, our second hypothesis is as follows:
H2. The interactive use of parent-PMS by headquarters is positively correlated with the influence of parent-PMS
on subsidiaries’ decision-making.

2.2. Embeddedness perspective
As mentioned in section1, we should account forthe externalnetwork embeddedness, which affects boththe subsidiaries’ activities and the headquarters’ control mechanisms, when investigating the relationship between
headquarters and subsidiaries (Andersson & Forsgren, 1996; Doz & Prahalad, 1993; Forsgren, 1989). Polyani(1957) proposed embeddedness theory, which Granovetter (1985) developed further. The concept ofembeddedness assumes that social structures have a significant influence on economic behavior. Granovetter(1985) argues that all economic behaviors have structural aspects, and that a certain mechanism of one’s behavior
can beunderstood byconsidering therelations withothers in social structures. Moreover, Granovetter(1992) argues
that because an organization is embedded in social relations, it cannot behave freely like an “atom.” Thus, anorganization’s behavior can be subject to relationships with others in social structures based on the degree that it isembedded in the social structures (Granovetter,1992).
Most business studies referring to embeddedness theory focus on the influence of the network in which
the organizations relate and their embeddedness in the network on organizations’ behaviors, the structuring
processes ofresources and capabilities, andperformance(Gulati,1998, 1999). Inthepast two decades, some studies
focus on the relationship between headquarters and subsidiaries in terms of embeddedness theory, and investigate
the influence of subsidiaries’ external embeddedness on their behaviors (e.g., Andersson & Forsgren, 1996;
Mahlendorf et al., 2012; Schäffer et al., 2014). According to Andersson & Forsgren (1996), subsidiaries’ external
embeddedness is the extent to which they relate to local counterparts and is embedded in local networks. Thesestudies argue that subsidiaries’ external embeddedness significantly influences the effects of the control
mechanisms implemented by headquarters to control subsidiaries’ behaviors.

2.2.1. Interaction effects of the use ofPMS and subsidiaries’ external embeddedness
According to network and embeddedness theory, subsidiaries have two criteria whentheydecide ontheir
behaviors (Forsgren et al., 2005; Ghoshal & Westney 1993): the control mechanisms implemented byheadquarters to integrate subsidiaries’ behavior into global strategy and overall goals and the subsidiaries’
embeddedness in local networks. Whena subsidiary is highly embedded in localnetworks, it has more informationand knowledge peculiar to the local market and behaves based on this information and knowledge. In some cases,
the headquarters lacks the necessary knowledge to manage worldwide operations and encounters fromuncertainty
about subsidiaries’ behaviors (Ciabuschi et al., 2012; Forsgren & Holm, 2010). In this situation, the distances
between headquarters and subsidiaries are extended, and headquarters will capture and understand subsidiaries’
behaviors and norms less, andthereforecannot appropriatelycontroltheir behaviors(Bouquet &Birkinshaw,2008;
Helliwell, 2002). Thus, it becomes more difficult for headquarters to control subsidiaries’ behaviors when they areextensively embedded in local networks (Andersson & Forsgren, 1996).
However, recent empirical management accounting studies show that a subsidiary’s higher externalembeddedness enhances the influence of parent-PMS on subsidiaries’ decision-making (Mahlendorf et al.,2012).
This argument can be understood as a suggestion that parent-PMSs are a mechanism to achieve high levels of
coordination and integration in highlydecentralized MNCs andtosuccessfullycombine localautonomyand global
goal congruence (Busco et al.,2008; Andersson et al.,2002; Dossi & Patelli,2008).
However, these effects do not always occur due to PMS alone. ResearchonPMS in MNCs suggests that
capturing critical areas and key factors, and communicating these factors between headquarters and subsidiaries ismore important, especially in highly decentralized MNCs (Busco et al.,2008; Dossi & Patelli, 2010; Mahlendorf
et al., 2012). Other research also suggests that understanding the business environment well can enhance alldecision-making capabilities within highly decentralized MNCs (Aharoni et al., 2010). On the other hand,subsidiaries’ decisions and actions are more uncertain for headquarters whensubsidiaries have high embeddedness.
In such highly uncertain cases, the interactive use ofPMS is more appropriate than diagnostic use is (Simons,1995,
2000).
Basedonthese studies, we expect that whena subsidiaryis extensivelyembedded, the influence ofparentPMS on the subsidiary’s decisions and actions depend on the characteristics of the use ofthe parent-PMS. While aparent-PMS canaffect subsidiaries’ decisions and actions whenthe systemcancapturethecriticalfactors, andwhen
the firm conducts frequent communication, feedback, and follow-up through the parent-PMS, especially in highly
decentralized MNCs, the parent-PMS cannot affect subsidiaries’ decisions if the parent-PMS lacks a clear process
when subsidiaries’ are extensively embedded. In other words, depending on the different uses of parent-PMS, its
influence on subsidiaries’ decisions and actions might change when subsidiaries are extensively embedded. Thus,
we assume that subsidiary embeddedness positively (negatively) moderates the cause-effect relation between theinteractive (diagnostic) use of parent-PMS and the influence ofthe parent-PMS on subsidiary decision-making.
There are various concepts of embeddedness in business networks (Halinen & Tornroos, 1998).
However, investigating all embeddedness is insubstantial and not rational (Kadushin 2012). Hence, in line withprior research (e.g. Andersson & Forsgren,1996; Andersson et al., 2001), we focus on subsidiaries’ relationships
with the local customers and suppliers that influence subsidiaries’ products and services, and product-and servicerelated processes. In highly decentralized MNCs, subsidiaries need to flexibility respond to the needs of local
counterparts in order to accomplish the MNC’s and subsidiaries’ strategy (Forsgren et al.,2005; Martinez &Jarillo,1989). Therefore, we propose the following hypotheses:
H3a. The subsidiaries’ embeddedness with local customers negatively moderates the relationship between the
diagnostic use of the parent-PMS by headquarters and the influence of the parent-PMS on subsidiaries’ decisionmaking.
H3b. The subsidiaries’ embeddedness with local suppliers negatively moderates the relationship between the
diagnostic use of the parent-PMS by headquarters and the influence of the parent-PMS on subsidiaries’ decisionmaking.

H4a. The subsidiaries’ embeddedness with local customers positively moderates the relationship between theinteractive use of the parent-PMS by headquarters and the influence of the parent-PMS on subsidiaries’ decisionmaking.
H4b. The subsidiaries’ embeddedness with local suppliers positively moderates the relationship between theinteractive use of the parent-PMS by headquarters and the influence of the parent-PMS on subsidiaries’ decisionmaking.

3. Method
3.1. Data collection
Data were collected through a mailed questionnaire-based survey addressed to 1,520 top managers ofJapanese subsidiaries of foreign MNCs in September 2016. The questionnaires were mailed due to the large
difference in the perception of control and practice of decision-making between headquarters and subsidiaries.
Therefore, we cannot observe the real influence of control systems on subsidiaries’ decision-making andsubsidiaries’ external environment, such as subsidiaries’ embeddedness directly (Andersson & Forsgren, 1996;
Mahlendorf et al., 2012). The total sample is 199 questionnaires (a response rate of 13%) after removing somesamples that lack data. The sample includes both manufacturing and non-manufacturing industries. Totest whether
respondents and non-respondents have different industries, we use Chi-square statistics and find that respondentand non-respondent firms had the same distribution across industries (p> .10). Hence, we find no non-respondentbias in terms of firm industry.
3.2. Variables
To ensure comparability with other studies and to enhance internal validity of contents, we adopt
constructs and measures established by prior research. We altered some constructs and measures slightly to adapt
to the MNC setting. Appendix A reports the constructs and measures used in this study and the descriptive statistics.
To measure the diagnostic (DUSE) and interactive (IUSE) use of parent-PMS, which are independent variables,
we follow Henri (2006b), Simons (1995, 2000), and Widener (2007). We use 11 items measured on seven-point
Likert-type scales (1 = not at all; 7 = to a high extent)1 . In terms of the reliability of the variables, the Cronbach’s α
of IUSE is .850 and that of DUSE is .639. While DUSE is not highly reliable, it is within a permissible range foranalysis (Hair et al.,1998).
To measure subsidiaries’ embeddedness with local customers (EMBC) and suppliers (EMBS), which
are moderating variables in this study, we measured 2 items using seven-point Likert-type scales (1 = not at all; 7 =1

DUSE includes 6 items and IUSE includes 5 items, but we removed one DUSE item due to the selling effect.

Table 1
Exploratory factor analysisresults: Influence of parent-PMS on subsidiaries’ decisions a,b1

2

3

Incentive scheme decisions

.930

.023

-.099

Target setting decisions for employees

.792

-.127

.179

Humanresource decisions

.775

.072

.121

Decisions about performance evaluation

.733

.050

-.128

Responsibilityaccounting decisions

.514

.008

.399

R&D planningand control decisions

.007

.859

-.081

Production planning decisions

-.081

.803

.067

Making or buying decisions

-.136

.761

.201

Investment decisions

.251

.718

-.245

Supply chain management decisions

.019

.625

.185

Target setting decisions for employees

.021

-.092

.987

Distribution channel decisions

.065

.027

.809

Pricing decisions about products or services

-.059

.121

.732

Cronbach’s α

.814

.806

.771

a

promax rotationb

contributionrate: 74.771%, eigenvalue: 1.215

Table 2
Correlation matrix
Variables
INF-C
INF-D
INF-S
DUSE
IUSE
EMBC
EMBS
INF-C
1
INF-D
.310**
1
INF-S.658**.461**
1
DUSE.236**.211**.158*
1
IUSE.366**.205**.288**.705**
1
EMBC.073.249**.101.141.187**
1
EMBS.122.213**
.104
.055
.097
.482**
1*p<.05, **p<.01.All testsare two-tailed
Abbreviations: INF-C = the influence of parent-PMS on subsidiaries internal control decision-making; INF-D = the influence ofparent-PMS on subsidiaries decision-making about developing products and/or services INF-S = the influence of parent-PMS on
subsidiariesdecision-makingabout sellingprocessesDUSE = diagnosticuseof parent-PMS; IUSE = interactive use of parent-PMS;
EMBC= subsidiaries embeddedness inlocal customers;EMBS= subsidiaries embeddedness inlocalsuppliers.

to a high extent) following Andersson & Forsgren (1996). Scale reliability is satisfactory, with a Cronbach’s α of
EMBC of .700 and EMBS of.890.
To measure the influence of parent-PMS on subsidiaries’ decision-making, we refer to Dossi & Patelli(2008) and Mahlendorf et al.(2012) and use 14 items measured on seven-point Likert-type scales (1 = not at all; 7= to a high extent). Prior studies adopt these items as one variable to analyze. However, it is difficult to adopt thisapproach due to the differing contents and aspects ofthese items. Hence, we perform an exploratory factor analysis
in this study and find that 14 items loaded on three factors (Table 1)2 . The first of the three factors includes 5 items
concerning controlwithin the subsidiaries (INF-C). The second includes 5 items about developing products and/or
services in subsidiaries (INF-D). The final factor includes 3 items related to decisions about selling processes at
subsidiaries (INF-S). The Cronbach’s α is .814 for INF-C, .806 for INF-D, and .771 for INF-S, which aresatisfactory. Table 2 shows the Pearson’s correlation coefficients across the variables.

4. Results
4.1. The results of main analyses
We can summarize the six hypotheses in two basic models:𝑌 , , = 𝛼 + 𝛽 𝐷𝑈𝑆𝐸 + 𝛽 𝐼𝑈𝑆𝐸+ 𝛽 𝐸𝑀𝐵𝐶 + 𝛽 𝐸𝑀𝐵𝑆 + +𝛴𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠+𝜀(1)

𝑌 , , = 𝛼 + 𝛽 𝐷𝑈𝑆𝐸 + 𝛽 𝐼𝑈𝑆𝐸+ 𝛽 𝐸𝑀𝐵𝐶 + 𝛽 𝐸𝑀𝐵𝑆 + 𝛽 𝐷𝑈𝑆𝐸 × 𝐸𝑀𝐵𝐶
+ 𝛽 𝐷𝑈𝑆𝐸 × 𝐸𝑀𝐵𝑆 + 𝛽 𝐼𝑈𝑆𝐸× 𝐸𝑀𝐵𝐶 + 𝛽 𝐼𝑈𝑆𝐸× 𝐸𝑀𝐵𝑆
+ 𝛴𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠+𝜀(2)where Y 1 = the influence of parent-PMS on subsidiaries internal control decision-making (INF-C), Y2 = theinfluence ofthe parent-PMS on subsidiaries decision-making about developing products and/or services (INF-D),
Y3 = the influence of the parent-PMS on subsidiaries decision-making about selling processes (INF-C), α is theintercept, β_s are regression coefficients, ΣControls = control variables, and ε = error term.
To test these models, we conducted a hierarchicalregressionanalysis. Regression-based methods may besuitable to test these models compared to covariance-based methods because the models and measures ininternational business research are considered as to be at an early stage of development and lack substantial
empiricalevidence, and becausethe hypotheses include interaction effects(Schäffer et al.,2014;Venaik et al.,2005).
Table 3 reports the analysis results. Model 1 focuses on the main effects of different types ofPMS use on
subsidiaries’ decision-making, and thus focuses on H1 and H2. In Model 1, the direct effects of the diagnostic useof parent-PMS (DUSE) on all independent variables (INF-C, INF-D, and INF-S) are not statistically significant.
2

We removed one item because its factor loading was below .50.

Table 3
Hierarchicalregressionresults
INF-C
Model1cModel2c

INF-D
Model1dModel2d

INF-SModel1s
Model2s

Independent variables
DUSE
H1
-.020
-.034
.156
.146
-.062
-.087
IUSE
H2
.411***.406**.059.069.354**.374**
EMBC
-.074
-.078
.185
.186
.028
.029
EMBS
.153
.141
.109
.097
.114
.095
DUSE×EMBC
H3a
-.151
.312
.275
DUSE×EMBS
H3b
-.022
-.157
-.208
IUSE×EMBC
H4a-.045-.378*-.354*
IUSE×EMBS
H4b
.191
.263*
.325*
Control variables
ESTTYPE
.093
.105
-.058
-.046
-.080
-.070
ESTYEAR
-.085
-.100
-.072
-.078
-.064
-.072
SIZE
.086
.068
.071
.041
.016
-.016
INDUSTRY
-.048
-.045
.069
.075
-.037
-.027
2
R
.190
.221
.147
.187
.138
.181
2
ADJ. R
.135
.144
.089
.107
.079
.101
F-VALUE
3.449***
2.894**
2.536**
2.342**
2.355*
2.263***p<.05, **p<.01, ***p<.001.All tests are two-tailed
Abbreviations: INF-C = the influence of parent-PMS on subsidiaries internal control decision-making; INF-D = the influence ofparent-PMS on subsidiaries decision-making about developing products and/or services INF-S = the influence of parent-PMS on
subsidiariesdecision-makingabout sellingprocessesDUSE = diagnostic useof parent-PMS; IUSE = interactive use of parent-PMS;
EMBC= subsidiariesembeddedness inlocalcustomers;EMBS= subsidiaries embeddednessinlocalsuppliers;ESTTYPE = typesof establishment of subsidiaries(0= green-fieldinvestment; 1= M&A);ESTYEAR= pastyearssincesubsidiarieshasbeeninvolvedin presentMNCs; SIZE = size of subsidiaries; INDUSTRY= industry dummies (0= non-manufacturing; 1= manufacturing).

Therefore, H1 is not supported. For H2, the direct effects of the interactive use of parent-PMS (IUSE) on theinfluence of parent-PMS on subsidiaries’ internal control decision-making (INF-C, standardizedβ= .411; p= .000)
and decision-making about selling processes (INF-C, standardizedβ= .354; p= .003) are significant, although thedirect effect of the influence of parent-PMS on subsidiaries’ decision-making about products and/or services
development is not significant (INF-D, p> 0.1). Therefore, H2 is partially supported and all controlvariables are notsignificant.
Model 2 focuses on the interaction effects between different types of PMS use and subsidiaries’
embeddedness;thus, Model 3 reflects, H3a, 3b, 4a, and 4b. The results do not confirm a significant interaction effectfor H3, so H3a and H3b are not supported. On the other hand, for H4a, the negative interaction effects between
IUSE and EMBC on INF-D (standardizedβ= -.378; p= .021), and on INF-S(standardizedβ= -.354; p= .031) aresignificant. Conversely, the positive interaction effects betweenIUSE and EMBS on INF-D (standardizedβ= .263;
p= .048) and INF-S (standardizedβ= .325; p= .015) are significant. Thus, the results partially support and partiallyreject H4a and H4b, respectively.

4.2. The results of supplemental analyses
The results above show that some interaction effects are statistically significant. In this analysis, we report
the results of a simple slope analysis to clarify and confirm the moderating effects of a subsidiary’s embeddedness
with local customers and suppliers. In line with prior research (e.g. Aiken & West,1991; Cohen et al.,2002) , oursimple slope analysis uses the using moderator values at one standard deviation above and below the mean. Figure
1 illustrates the results ofthe analyses with a focus onthe moderating effect ofEMBC. The cause-effect relationshipbetween IUSE and INF-D is not significant when EMBC is above the mean, though we confirm a significant
relationship between IUSE and INF-D when EMBC is below the mean (standardizedβ= .184; p= .047). On theother hand, the positive cause-effect relationship between IUSE and INF-S is significant, both when EMBC isabove (standardizedβ= .220; p= .029) and below (standardizedβ= .302; p= .000) the mean. Thus, the interactive
use of parent-PMS is likely to have a high (low) influence when subsidiaries’ embeddedness in local customers is
low (high).
Figure 1
The moderatingeffects of subsidiariesembeddedness in localcustomers

Figure 2
The moderatingeffects of subsidiariesembeddedness in local suppliersIn contrast, Figure 2 illustrates the results of the analyses of the moderating effect of EMBS. The causeeffect relation between IUSE and INF-D is significant only when EMBS is above the mean (standardizedβ= .255;
p= .015), while the cause-effect relation between IUSE and INF-S is significant both when EMBS is above(standardizedβ= .386; p= .000) and below (standardizedβ= .201; p= .033) the mean. These results suggest that theuse ofparent-PMS is likely to have a high (low) influence when subsidiaries’ embeddedness with local suppliers ishigh (low).

5. Discussion and Conclusion
5.1. Relevant findings and contributions
This study examines the relationships among the use of parent-PMS, subsidiaries’ embeddedness, andsubsidiaries’ decisions, especially the cause-effect relations between the different types parent-PMS use andsubsidiaries’ decisions, and the moderating effects of subsidiaries’ embeddedness on these cause-effect relations.
We test six hypotheses using survey data collected from 199 Japanese subsidiary top managers. The results show
some relevant findings that extend and contribute to the present discussion about the effects of parent-PMS in
MNCs.
First, by reviewing and summarizing relevant studies that focus on the use of PMS, we generate two
hypotheses about the effects of the different types of parent-PMS use (H1, H2). The results show the cause-effectrelationship between the interactive use of PMS by headquarters and the influence of parent-PMS on subsidiaries’
decisions, though we find no statistically significant effect ofthe diagnostic use ofPMS by headquarters. It suggeststhat the influence ofparent-PMS onsubsidiaries’ decisions is subject to information flow and controlpractice. Thus,
we argue that byusing PMS interactively, headquarters can influence subsidiaries’ decisions and thus integrate theiractions into the company’s overall goals. By using PMS interactively, subsidiaries can frequently communicate
and share relevant information and thoughts to accomplish the overall strategy with their headquarters (Dirks andFerris,2002; Dossi & Patelli, 2010; Maley &Moeller,2014). Hence, subsidiaries’ decisions and actions might bein line with the intentions of headquarters and overall strategy.
Priorresearchoffers empiricalevidence about the determinants ofthe decision-influencing useofa parentPMS (e.g. Dossi& Patelli2008;Mahlendorfet al.,2012), while other studies focusonthe interactive useofaparentPMS by headquarters (e.g. Dossi & Patelli 2010; Schäffer et al., 2014). However, these studies do not provide
evidence on or the implications of how can headquarters control subsidiaries’ decisions and actions using PMS.
This study overcomes these limitations in prior studies and focuses on the processes ofthe use of PMS in terms of
information flow and control practices, and shows how and which types of a headquarters’ use of PMS can
influence subsidiaries’ decisions. Hence, our empirical evidence can complement and extend the findings in priorresearch. Furthermore, the results ofthis study support the arguments ofprior studies that the effects ofPMS withinorganizations depend on the use of PMS (e.g. Koufteros et al., 2014; Henri, 2006a). Therefore, these findings are
an important contribution to PMS research, especially in the MNC setting.

Second, to consider the effects of local networks and counterparts on subsidiaries’ decisions and actions
from the perspective of embeddedness theory. We test four hypotheses about the interaction effect of parent-PMS
use and subsidiaries’ external embeddedness (H3, H4). The results show that the subsidiaries’ embeddedness withlocalcustomers negatively moderatesthe positive influence ofthe interactive useofPMS on subsidiaries’ decisions.
This result supports empirical evidence in international business research showing that subsidiaries’ embeddedness
negatively affects the headquarters’ controlmechanisms (e.g. Andersson & Forsgren,1996) compared to the PMS
research in the MNC setting (e.g. Mahlendorf et al.,2012). We can understand this a firms’ actions to adapt to local
customers’ needs via subsidiaries. MNCs should integrate a variety of needs, information, and knowledge of local
markets into innovation to acquire competitive advantages in both the global and local markets, especially in Japan(Blahová et al.,2015). In doing so, subsidiaries must be embedded inthe local market to obtain this information andknowledge (Johanson and Vahlne,2009). Consequently, subsidiaries’ embeddedness with local customers might
prevail against the parent-PMS. Thus, subsidiaries’ embeddedness with local customers negatively moderates theinfluence ofthe interactive use of PMS by headquarters on subsidiaries’ decisions.
Ontheother hand,we find apositive moderating effect ofsubsidiaries’ embeddednesswithlocalsuppliers
onthe cause-effect relationship between the interactive use ofPMS by headquarters and the influence ofthe parentPMS on subsidiaries’ decisions. This result is in contrast to the result for customer embeddedness. Subsidiaries’
embeddedness that influences products and/or services enhance overall organizational performance, which theparent-PMS can capture and influence (Andersson et al., 2005). MNCs can effectively control Japanesesubsidiaries’ decisions and actions by understanding and adapting to buyer-supplier relationships in the Japanesemarket (Schlunze, 2004). Hence, the headquarters can capture the relationship between subsidiaries and local
suppliers using PMS interactively. Thus, it can communicate important information to subsidiaries. In addition, it
may explain the result that the extent to which headquarters’ delegate authority for developing products and/or
services to subsidiaries is relatively low (see Appendix B).
The findings on subsidiaries’ embeddedness extend the discussions in both the international business and
PMS literature. For PMS research, the empirical evidence in this research helps to reveal the mechanisms andprocesses of the effects of PMS in combination with the empirical evidence on the use of PMS. These results
suggest that the effects ofPMS depend not onlyonthetypeofPMS use, but also onthe embeddedness in networks.
Although this study investigates only subsidiaries’ external embeddedness, other types of embeddedness (i.e.,internal embeddedness in terms of the dependencies of business units on headquarters) might have important
impacts on the effects of PMS. In international business research, few studies classify embeddedness according tolocal counterparts, though prior research considers many types of embeddedness. Thus, this study helps to extend
the discussion on subsidiaries’ embeddedness by showing empirical evidence of the impacts of subsidiaries’
embeddedness depend on the type of local counterpart. However, future research should investigate why the
impacts of embeddedness differ depending on the type of local.

5.2. Implications
This study also has implications for MNCs. The results show that by using parent-PMS interactively, theheadquarters can affect subsidiaries’ decision-making, and can obtain goal congruence between headquarters andsubsidiaries. More precisely, it is important for highly decentralized MNCs to frequently communicate and discussbothglobaland localperformance withsubsidiaries to capture andsharecriticalareasofthe business and keyfactors.
This suggestion is in line with Maley & Moeller’s (2014) argument that frequent communication, feedback, andfollow-up through parent-PMS are important characteristics to integrate subsidiaries’ decisions and actions into
global strategy. They argue that when the process ofPMS use lacks these characteristics, subsidiaries have less trustin headquarters, and might thus disobey the intentions of headquarters.
5.3. Limitations, and suggestions for the future research
Although this study presents relevant findings, they are subject to some limitations. The first is related todata collection and the target companies. The results of this study can be compared with other studies that focus on
similar themes and/or use similar measures in a survey, but that obtain different results. This research has somepeculiarities because the target of this survey is Japanese subsidiaries. Thus, for subsidiaries in other countries, ourresults not be applicable. The second limitation is a perception gap between headquarters and subsidiaries. In thisstudy, we investigate the real influence of parent-PMS on subsidiaries’ decisions and actions and the extent of theeffect of subsidiaries’ embeddedness, though because the survey targeted subsidiaries, the results may not reflect
the thoughts and intentions ofthe parent headquarters.
Future research could extend the findings of this study by overcoming these limitations or focusing onother questions. For example, a case study would clarify why and how subsidiaries’ embeddedness moderates theinfluence of parent-PMS. In addition, by focusing on both headquarters and subsidiaries simultaneously, a future
studycould considerthe perceptiongap betweenheadquarters and subsidiaries. Furthermore, it is necessaryto focus
ontherelationships amongthe structuralfeatures and aspects ofthe design, purpose, and proceduralaspectsofPMS
use. This study accounts for information flow to reveal the processes of PMS use by headquarters and its influenceon subsidiaries. However, we assume that appropriate information flow depends on the design, purpose, andprocedural aspects of PMS. In other words, there might be a “fit” among these elements, which is a relevant topic
for future research to extend the findings.

Appendix A: Constructs, measures and descriptive statistics
Influence ofparent-PMS on decision-making
To what extent does the parent-PMS influence your decision-making on the following items?
(1 = not at all; 7 = to a high extent)
Budgeting decisions
Pricing decisions about products or services
Decisions about performance evaluation
Target setting decisions for employees
Incentive scheme decisions
Humanresource decisions
Choosing target customer decisions
Responsibilityaccounting decisions
Distribution channel decisions
Investment decisions
Making or buying decisions
Production planning decisions
Supply chain management decisions
R&D planningand control decisions

N
199
199
198
199
199
199
199
199
198
198
185
182
194
189

Min
1
1
1
1
1
1
1
1
1
1
1
1
1
1

Max
7
7
7
7
7
7
7
7
7
7
7
7
7
7

Mean
5.05
4.65
4.64
4.52
4.51
4.38
4.37
4.30
4.12
3.94
3.66
3.65
3.56
3.49

SD
1.41
1.772
1.852
1.941
1.885
1.762
2.005
1.930
2.098
2.034
2.074
2.114
2.069
2.041

Diagnostic and interactive use ofPMS
To what extent do you agree to the following statements about how to use ofthe parent-PMS?
(1 = not at all; 7 = to a high extent)
Diagnostic use of PMS
The parent-company uses the PMS tomonitor performance and results ofyour Japanese company’s operations.
The parent-company uses the PMS to trackprogressof your Japanesecompany’s
activities towards goals.
The parent-company relies heavily on staff
specialists in preparing andinterpreting information from theparent-PMS.
You and/or your Japanese company’s
employees pay attention on theparent-PMS when exception to theparent-PMS happen.
The parent-company pays attention on theactivities of your Japanese company
only when the parent-company
knows exception to a plan happened
through the parent-PMS.

N

Min

Max

Mean

SD

199

1

7

5.24

1.651

199

1

7

5.24

1.621

199

1

7

3.98

1.592

199

1

7

3.06

1.479

198

1

7

3.30

1.727

Interactive use of PMS
The parent-PMS enables continual
challenge and debate of underlying
data,assumption andaction plan.
The parent-PMS enables discussion inmeetings with the parent-company
and other employees.
The parent-company has paid attention on
day-to-day activities of your Japanesecompany through the parent-PMS.
You and/or your Japanese company’s
employees have paid day-to-day
attention tothe parent-PMS.
Formal meetings are frequently held withthe participation of employees in boththe parent-company and yourJapanese company to discuss theparent-PMS.

N

Min

Max

Mean

SD

199

1

7

4.86

1.642

199

1

7

4.84

1.584

199

1

7

4.86

1.589

199

1

7

4.86

1.614

199

1

7

4.86

1.708

Subsidiaries embeddedness
To what extent have relationships with the following local Japanese stakeholders caused your Japanese company
to change its products/services or operation processes?
(1 = not at all; 7 = to a high extent)
Subsidiaries embeddedness in local customers
Relationships with local Japanese customers
have causedchanges in products/services.
Relationships with local Japanese customers
have caused changes in production
technologies/service processes.
Subsidiaries embeddedness in local suppliers
Relationships with local Japanese suppliers havecaused changes inproducts/services.
Relationships with local Japanese suppliers havecaused changes in production
technologies/service processes.

N

Min

Max

Mean

SD

199

1

7

5.38

1.440

199

1

7

4.95

1.695

194

1

7

3.63

2.030

196

1

7

3.52

1.962

Appendix B: Descriptive statics of subsidiaries decision-making authority delegated by headquarters
Choosing target customer decisions
Target setting decisions for employees
Distribution channel decisions
Responsibilityaccounting decisions
Humanresource decisions
Incentive scheme decisions
Pricing decisionsabout products or services
Budgeting decisions

Min
1
2
1
1
1
1
1
1

Max
7
7
7
7
7
7
7
7

Mean
6.11
5.96
5.88
5.70
5.29
5.15
5.07
4.82

SD
1.149
1.145
1.303
1.234
1.357
1.527
1.563
1.273

Decisions about performance evaluation
Supply chain management decisions
Making or buying decisions
Production planning decisions
Investment decisions
R&Dplanningand controldecisions

1
1
1
1
1
1

7
7
7
7
7
7

4.71
4.27
3.85
3.40
3.30
3.02

1.630
1.997
2.063
2.078
1.735
1.802

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