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Performance Measurement in Shared Services

Empirical Evidence from European Multinational Companies

by Friedrich Kalden (Author)
©2021 Thesis 436 Pages

Summary

Shared Service Organizations (SSOs) are of growing relevance in research and corporate practice since they combine a number of benefits for multinational corporations, such as cost reductions and an improved risk management. However, managers voice concerns about potential negative impacts on the firm’s effectiveness due to a lower service quality. A major reason for the ongoing controversy of the SSOs’ outcome is closely related to the shortcoming of measuring their performance. This study analyzes Performance Measurement System (PMS) design in SSOs and sheds light on its effectiveness. Furthermore, the findings reveal which determinants increase PMS effectiveness. This empirical analysis yields practical design recommendations for practitioners working in a shared service environment.

Table Of Contents

  • Cover
  • Title
  • Copyright
  • About the author
  • About the book
  • This eBook can be cited
  • Preface
  • Acknowledgement
  • Content overview
  • Table of Contents
  • List of figures
  • List of tables
  • List of abbreviations
  • List of symbols
  • 1 Introduction
  • 1.1 Motivation and research questions
  • 1.2 Outline of the study
  • 1.3 Scientific positioning
  • 2 Conceptual basis
  • 2.1 Shared service organizations
  • 2.1.1 Definition of shared service organizations
  • 2.1.2 Objectives of shared service organizations
  • 2.1.3 Design of shared service organizations
  • 2.1.3.1 Functional and process scope
  • 2.1.3.2 Location decisions
  • 2.1.3.3 Legal and economic independence
  • 2.1.3.4 Service level agreements and charging models
  • 2.1.3.5 The use of IT
  • 2.1.4 Conceptual distinction to centralization and outsourcing
  • 2.2 Performance measurement
  • 2.2.1 Definition of performance measurement
  • 2.2.2 Performance measurement objectives
  • 2.2.3 Design of PMS
  • 2.2.3.1 Performance measures
  • 2.2.3.2 Performance measurement process
  • 2.2.3.3 Performance measurement actors
  • 2.2.3.4 Summary
  • 2.2.4 Conceptual distinction to MCS and performance management
  • 2.2.4.1 Management control systems in SSOs
  • 2.2.4.2 Performance management in SSOs
  • 3 State of research
  • 3.1 Studies on shared service organizations
  • 3.1.1 Qualitative studies on shared service organizations
  • 3.1.2 Quantitative studies on shared service organizations
  • 3.2 Studies on performance measurement
  • 3.2.1 Qualitative studies on performance measurement
  • 3.2.2 Quantitative studies on performance measurement
  • 3.3 Summary and research gap
  • 4 Theory and basic hypotheses development
  • 4.1 Theoretical foundation
  • 4.1.1 Contingency theory
  • 4.1.2 New institutionalism
  • 4.1.2.1 Institutionalism
  • 4.1.2.2 New institutional economics
  • 4.1.2.3 New institutional sociology
  • 4.1.3 Promotor model
  • 4.1.4 Summary
  • 4.2 Basic hypotheses development
  • 4.2.1 Determinants of PMS design in SSOs
  • 4.2.2 Effectiveness of PMS design in SSOs
  • 5 Research design
  • 5.1 Qualitative case study research
  • 5.2 Quantitative survey research
  • 5.3 Mixed methods research design
  • 5.3.1 Definition of mixed methods
  • 5.3.2 Objectives of a mixed methods research
  • 5.3.3 Development of the mixed methods research design
  • 5.3.4 Quality criteria in mixed method research
  • 6 Qualitative analysis
  • 6.1 Sample selection and case company description
  • 6.1.1 Case company selection
  • 6.1.2 Case company description
  • 6.2 Data collection and analysis
  • 6.2.1 Data collection
  • 6.2.2 Interview characteristics
  • 6.2.3 Data analysis
  • 6.3 Empirical results
  • 6.3.1 Within-case analysis
  • 6.3.1.1 MedTechCo case
  • 6.3.1.2 CommCo case
  • 6.3.1.3 ChemCo case
  • 6.3.1.4 PharCo case
  • 6.3.1.5 AgriCo case
  • 6.3.1.6 HealthCo case
  • 6.3.1.7 EngineerCo case
  • 6.3.2 Cross-case analysis
  • 6.3.2.1 Context of PMS design in SSOs
  • 6.3.2.1.1 External context
  • 6.3.2.1.2 MNC context
  • 6.3.2.1.3 SSO context
  • 6.3.2.1.4 Summary
  • 6.3.2.2 PMS design in SSOs
  • 6.3.2.2.1 Performance measures
  • 6.3.2.2.2 Performance measurement process
  • 6.3.2.2.3 Performance measurement actors
  • 6.3.2.3 Performance measurement effectiveness
  • 6.3.2.4 Summary
  • 6.4 Hypotheses refinement
  • 6.4.1 External context
  • 6.4.2 MNC context
  • 6.4.3 SSO context
  • 6.4.4 Performance measurement effectiveness
  • 6.4.5 Summary
  • 7 Quantitative analysis
  • 7.1 Sample selection and data collection
  • 7.1.1 Sample definition
  • 7.1.2 Sample characteristics
  • 7.1.3 Data collection
  • 7.2 Construct measurement
  • 7.2.1 Operationalization of the constructs under research
  • 7.2.1.1 PMS design score
  • 7.2.1.1.1 Performance measures
  • 7.2.1.1.2 Performance measurement process
  • 7.2.1.1.3 Performance measurement actors
  • 7.2.1.2 Performance measurement effectiveness
  • 7.2.2 Operationalization of the explanatory factors
  • 7.2.2.1 Environmental factors
  • 7.2.2.2 MNC factors
  • 7.2.2.3 SSO factors
  • 7.2.3 Operationalization of the control variables
  • 7.3 Methods of data analysis
  • 7.3.1 Descriptive statistics and mean comparisons
  • 7.3.2 Multiple regression analysis
  • 7.4 Empirical results
  • 7.4.1 PMS design in SSOs
  • 7.4.1.1 Performance measures
  • 7.4.1.2 Performance measurement process
  • 7.4.1.3 Performance measurement actors
  • 7.4.1.4 Score aggregation and summary
  • 7.4.2 Determinants of PMS design in SSOs
  • 7.4.2.1 Descriptive analysis
  • 7.4.2.1.1 External context
  • 7.4.2.1.2 MNC context
  • 7.4.2.1.3 SSO context
  • 7.4.2.1.4 Summary
  • 7.4.2.2 Correlation analysis
  • 7.4.2.3 Regression analysis
  • 7.4.3 Performance measurement effectiveness
  • 7.4.3.1 Descriptive analysis
  • 7.4.3.2 Regression analysis
  • 7.4.4 Summary and discussion
  • 7.4.4.1 Integration of the qualitative and the quantitative findings
  • 7.4.4.2 Review of the results
  • 8 Conclusions
  • 8.1 Main findings and implications
  • 8.2 Limitations and outlook
  • Appendix A
  • Appendix B
  • Appendix C
  • Bibliography
  • Series index

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List of figures

Figure 1.1:Research objectives of the study

Figure 1.2:Outline of the study

Figure 2.1:Definition of shared service organizations

Figure 2.2:Essential design characteristics of SSOs

Figure 2.3:Mono- and multigeographical SSCs/mono- and multidivisional SSCs

Figure 2.4:Performance as the achievement of objectives

Figure 2.5:PMS design

Figure 2.6:The performance measurement process

Figure 2.7:Management control systems

Figure 3.1:Classification of the related empirical literature

Figure 4.1:Single case, universalistic and contingency approach

Figure 4.2:Application of the basic contingency model

Figure 4.3:Basic principal-agent relationship

Figure 4.4:The promotor model

Figure 4.5:Principal-agent relationships in SSOs.

Figure 4.6:Basic hypotheses of this study

Figure 5.1:Basic types of case study research designs

Figure 5.2:Objectives of mixed methods research

Figure 5.3:Dimensions of mixed methods research designs

Figure 5.4:This study’s mixed methods research design

Figure 5.5:Elements of quality criteria in MMR

Figure 6.1:Interview process

Figure 6.2:Structuring-thematic coding

Figure 6.3:PMS design promotors in SSOs

Figure 6.4:Overview of hypotheses and underlying theories

Figure 7.1:Sample distribution by country

Figure 7.2:Sample distribution by industry

Figure 7.3:Current job title of the respondents

Figure 7.4:Feedback of non-participants

Figure 7.5:Use and proportion of measures linked to variable remuneration

Figure 7.6:The performance measurement process

Figure 7.7:MIS used for performance measure data collection

Figure 7.8:PMS reporting tools used to communicate performance measure analyses

←17 | 18→

Figure 7.9:Performance measure modification frequency

Figure 7.10:Composition of the MEAS score

Figure 7.11:Composition of the PROC score

Figure 7.12:Composition of the ACT score

Figure 7.13:MNCs’ organizational structure

Figure 7.14:MNCs’ management board structure

Figure 7.15:Geographical dispersion of SSCs

Figure 7.16:Legal and economic independence of SSOs

Figure 7.17:Center concepts in SSOs

Figure 7.18:Functional configuration of SSOs

Figure 7.19:Configuration of the service provision in SSOs

Figure 7.20:Obligation to contract for internal SSO customers

Figure 7.21:Use of SLAs

Figure 7.22:SLA design

Figure 7.23:SSO controlling departments in SSOs

Figure 7.24:SSO controlling tasks for SSO management accountants

Figure A.1:Interview guideline

Figure B.1:Survey for SSO managers

Figure C.1:Survey for SSO management accountants

←18 | 19→

List of tables

Table 2.1:Distinction between centralization, shared services and outsourcing

Table 3.1:Overview of qualitative studies on shared service organizations

Table 3.2:Overview of quantitative studies on shared service organizations

Table 3.3:Overview of qualitative studies on performance measurement

Table 3.4:Overview of quantitative studies on performance measurement

Table 4.1:Problems and potential solutions in principal-agent relationships

Table 6.1:Fundamental characteristics of the case companies

Table 6.2:Interview characteristics of the case companies

Table 6.3:External context of PMS design in SSOs

Table 6.4:MNC context of PMS design in SSOs

Table 6.5:SSO context of PMS design

Table 6.6:Performance measure design in SSOs

Table 6.7:Performance measurement process design in SSOs

Table 6.8:Performance measurement actors in SSOs

Table 6.9:PMS effectiveness in SSOs

Table 7.1:Sample selection

Table 7.2:Fundamental characteristics of the sample firms

Table 7.3:Respondents’ characteristics

Table 7.4:Characteristics of the two questionnaires

Table 7.5:Response rates

Table 7.6:Non-response bias test for questionnaire A

Table 7.7:Non-response bias test for questionnaire B

Table 7.8:The PMS design score

Table 7.9:The performance measurement effectiveness score

Table 7.10:Performance measures in SSOs per category

Table 7.11:Performance measure development

Table 7.12:Performance measure target definition

Table 7.13:FTE allocation to performance measure data collection activities

Table 7.14:Automation of data collection by performance measure category

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Table 7.15:Types of performance measure analyses

Table 7.16:Reporting frequency by performance measure category

Table 7.17:Informal conversation frequency on performance measures

Table 7.18:Eliminated and added performance measures

Table 7.19:Involvement of actors in the performance measurement process

Table 7.20:Summary of the PMS design score

Table 7.21:PMS design control score

Table 7.22:Perceived environmental uncertainty

Table 7.23:Perceived competition intensity

Table 7.24:Differentiation of products and services

Table 7.25:Hierarchical structure of MNCs

Table 7.26:Task complexity

Table 7.27:Number of implemented ERP-Systems

Table 7.28:IT-infrastructure heterogeneity

Table 7.29:Perceived top management support

Table 7.30:Group controlling size

Table 7.31:Collaboration intensity between SSO and group controlling

Table 7.32:SSO characteristics

Table 7.33:SSO controlling size

Table 7.34:SSO customer requirements

Table 7.35:Formal process standardization in SSOs

Table 7.36:Factual process standardization in SSOs

Table 7.37:PMS power promotors in SSOs

Table 7.38:PMS know-how promotors in SSOs

Table 7.39:PMS process promotors in SSOs

Table 7.40:PMS relationship promotors in SSOs

Table 7.41:Pearson and Spearman correlation matrix

Table 7.42:Regression analysis on determinants of PMS design

Table 7.43:Regression analysis on determinants of PMS design – subscore analysis

Table 7.44:PMS support for SSO objectives perceived by managers

Table 7.45:PMS support for SSO objectives perceived by management accountants

Table 7.46:PMS objectives and pursuance perceived by managers

Table 7.47:PMS objectives and pursuance perceived by management accountants

Table 7.48:PMS satisfaction

Table 7.49:PMS acceptance

←20 | 21→

Table 7.50:Regression analysis on performance measurement effectiveness

Table 7.51:Regression analysis on PMS effectiveness – subscore analysis MEAS

Table 7.52:Regression analysis on PMS effectiveness – subscore analysis PROC

Table 7.53:Regression analysis on PMS effectiveness – subscore analysis ACT

Table 7.54:Extended descriptive analysis on performance measurement effectiveness

Table 7.55:Diminishing marginal utility of PMS design in SSOs

Table 7.56:Summary of the hypotheses testing

←22 | 23→

List of abbreviations

ABC

Activity based costing

Adj.

Adjusted

BPO

BSC

Business Process Outsourcing

Balanced Scorecard

Cf.

Confer

CM

CoE

Contribution margin

Center of Expertise

Coeff.

Coefficient

COMP

CoS

PMS design score

Center of Scale

C.p.

Ceteris paribus

E.g.

Exempli gratia

Ed.

Edition

Eds.

Editors

ERP

Enterprise resource planning

Et al.

Et alii

Etc.

Et cetera

EU

European Union

f.

And the following one

ff.

And the following

FY

Fiscal Year

GDP

Gross Domestic Product

GOA

HQ

HR

http

Goal attainment score

Headquarters

Human Resources

Hypertext Transfer Protocol

I.a.

ICS

Inter alia

Internal Control System

I.e.

Id est

IMF

International Monetary Fund

←23 | 24→IT

Information Technology

KPI

Key Performance Indicator

MA

MAS

Management Accounting

Management Accounting System

Max.

Maximum

MCS

Min.

Management Control System

Minimum

MIS

Management Information System

MM

MMR

MMRD

MNC

Mixed methods

Mixed methods research

Mixed methods research design

Multinational Corporation

NIE

NIS

New Institutional Economics

New Institutional Sociology

No.

Number

O2C

Order-to-cash

OCR

Optical Character Recognition

p.

Page

P2P

Purchase-to-pay

PAT

Principal Agent Theory

PDF

PKR

PMI

Portable Document Format

Prozesskostenrechnung

Post-Merger Integration

PMS

Performance Measurement System

pp.

Pages

Q

Quarter

QDA

Qualitative Data Analysis

RQ

Research Question

SAT

SOP

Satisfaction score

Standard Operating Procedure

SSC

Shared Service Center

SSO

Shared Service Organization

Std. Dev.

Details

Pages
436
Year
2021
ISBN (PDF)
9783631862186
ISBN (ePUB)
9783631862193
ISBN (MOBI)
9783631862209
ISBN (Hardcover)
9783631850459
DOI
10.3726/b18738
Language
English
Publication date
2021 (November)
Keywords
Kennzahlensystem KPI Management Control Measures Regression analysis Leistungsmessung Kennzahlen Survey Research Case Study Mixed Methods
Published
Berlin, Bern, Bruxelles, New York, Oxford, Warszawa, Wien, 2021. 436 pp., 67 fig. b/w, 71 tables.

Biographical notes

Friedrich Kalden (Author)

Friedrich Kalden studied Economics at the Helmut-Schmidt University of Hamburg (Germany) and the University of Bretagne Sud (France). He worked as a research assistant for the Chair of International Accounting at the University of Münster (Germany).

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