Archive for the ‘ Theory ’ Category

Definition of ‘performance management’ in academic literature

Bititci, Carrie & McDevitt, 1997 define performance management as a “process by which the company manages its performance in line with its corporate and functional strategies and objectives”. This definition is often used in management research studies. According to Bititci, Carrie & McDevitt, it is the objective of that process to provide an integrated control system, where the corporate and functional strategies are deployed to all business processes, activities, tasks and personnel, and feedback is obtained through the performance measurement system to enable appropriate management decisions. The ultimate purpose of that process is to improve company performance.

Performance measurement is an essential part of the performance management. By measuring, people transform complex reality into simplified numerical concepts that can be easily communicated and acted upon (Lebas, 1995). According to Lebas, the simplification of reality by measuring is the prerequisite of successful management. Similarly, Bititci et al., 1997 argue that performance measurement is at the heart of the performance management process and it is of critical importance to the effective and efficient functioning of performance management. Performance measurement (PM) can be defined from different perspectives. These perspectives are:

  • processual perspective (e.g. Neely, Gregory & Platts, 1995; Neely, Gregory & Platts, 2005);
  • technological perspective (e.g. Chenhall & Langfield-Smith, 2007; Grafton, Lillis & Widener, 2010);
  • business perspective (e.g. Bourne, Neely, Mills & Platts, 2003; Henri, 2004).

3 suggestions for further reading

A more detailed discussion regarding the “good definition” of performance management is to be found in Franco-Santos et al., 2007. The authors review several definitions from literature and identify the key characteristics of performance management. To better understand why a “good definition” is so important, you may want to look into the guidelines on the concept definitions in management research by Bisbe, Batista-Foguet & Chenhall, 2007. They provide an easy to understand “how to” description. Finally, if you are interested in a recent overview the latest performance management literature, Franco-Santos, Lucianetti & Bourne, 2012 is a good choice. The authors propose a 4-dimensioanal framework how to structure  performance management literature, which can be used for literature reviews.


Bisbe, J., Batista-Foguet, J.-M., & Chenhall, R. H. (2007). Defining management accounting constructs: A methodological note on the risks of conceptual misspecification. Accounting, Organizations and Society, 32(7-8), 789–820.

Bititci, U. S., Carrie, A. S., & McDevitt, L. (1997). Integrated performance measurement systems: A development guide. International Journal of Operations & Production Management, 17(5), 522–534.

PDF: Bourne, M., Neely, A., Mills, J., & Platts, K. (2003). Implementing performance measurement systems: A literature review. International Journal of Business Performance Management, 5(1), 1–24.

PDF: Chenhall, R. H., & Langfield-Smith, K. (2007). Multiple perspectives of performance measures. European Management Journal, 25(4), 266–282.

PDF: Franco-Santos, M., Kennerley, M., Micheli, P., Martinez, V., Mason, S., Marr, B., … (2007). Towards a definition of a business performance measurement system. International Journal of Operations & Production Management, 27(8), 784–801.

Grafton, J., Lillis, A. M., & Widener, S. K. (2010). The role of performance measurement and evaluation in building organizational capabilities and performance. Accounting, Organizations and Society, 35(7), 689–706.

PDF: Henri, J.-F. (2004). Performance measurement and organizational effectiveness: Bridging the gap. Managerial Finance, 30(6), 93–123.

Lebas, M. J. (1995). Performance measurement and performance management: Proceedings of the 12th International Conference on Production Research. International Journal of Production Economics, 41(1-3), 23–35.

PDF: Neely, A., Gregory, M., & Platts, K. (1995). Performance measurement system design: A literature review and research agenda. International Journal of Operations & Production Management, 50(4), 80–116.

Neely, A., Gregory, M., & Platts, K. (2005). Performance measurement system design: A literature review and research agenda. International Journal of Operations & Production Management, 25(12), 1128–1263.


When does performance management increase performance? The role of contingencies.


Performance management has been recognized as a success factor for high performing companies. Researchers produced a large body of knowledge trying to discover how performance management impacts performance. One insight from that research is that there is no single best way to performance management (Lee and Yang, 2011). On contrary, various approaches co-exist in different settings and in different companies. Consequently, the question now is to understand which approach is most beneficial given the specific circumstances – the contingencies – of the company. This PhD work provides an overview of the recent contingency research in performance management and is built around two questions: 1) what type of performance management is used by companies given their specific contingencies, and 2) what is the performance impact of PM under different contingencies. Building on Covaleski et al. (2003) and Gerdin and Greve (2004) a literature review framework is created and methodological issues are considered.

By Timur Pasch, PhD cand., OU Heerlen, Supervisor Arco van de Ven


The body of performance management research grew dramatically in the last decade. Bititci et al. (1997) define performance management as a “process by which the company manages its performance in line with its corporate and functional strategies and objectives”. According to them, it is the objective of that process to provide an integrated control system, where the corporate and functional strategies are deployed to all business processes, activities, tasks and personnel, and feedback is obtained through the performance measurement system to enable appropriate management decisions. The ultimate purpose of that process is to improve company performance.

Many researchers study the performance consequences of PM. However, empirical results are often unclear and contradictory (Langfield-Smith, 1997). For example, one group of authors claim that PM is beneficial and leads to performance gains (Ittner et al., 2003; Said et al., 2003; van der Stede et al., 2006), another group of authors found no impact (Ittner and Larcker, 1995) and the last group found negative impact (Ittner and Larcker, 1997). Such unclear empirical evidence limits theory development and therefore additional research needs to be performed.

It has been argued that additional research can benefit from the insights provided by the contingency theory which may help to resolve existing contradictions and lead to a creation of consistent body of knowledge (Ittner and Larcker, 2001; 2009). Chenhall, 2003 provides an overview of contingency-based studies in management accounting. The central message of the contingency theory is that success of any management control initiative (e.g. performance management) is dependent on the contingencies of the company (Govindarajan, 1988; Chenhall, 2003; 2006). Contingencies are factors that are potentially significant for the implications of performance management. These can be externally given (e.g. environmental uncertainty, competition) or internally created (e.g. strategy) (Ittner and Larcker, 2001).

Contingency research in performance management area has its roots in the management accounting and control literature (Chapman, 1997; Chenhall, 2003; Fisher, 1998; Jones, 1985; Otley, 1980). Applied to performance management, the contingency paradigm states that there is no universally appropriate performance management approach equally suitable for all companies in all circumstances (Jermias and Gani, 2004). Consequently, factors such as strategy, environmental uncertainty and size have to be aligned with the performance management to unleash its’ performance effect (Jääskeläinen et al., 2012; Jermias and Gani, 2004).

As a part of the set of rational agent models (Kilfoyle and Richardson, 2011), contingency theory is built on two assumptions: bounded rationality and equilibrium (Covaleski et al., 2003). The bounded rationality assumes that rational agents act to maximize their self-interest, but at the same time they are equipped with only limited cognitive resources (Covaleski et al., 2003). Thus, any initiative that aims at aligning individual behavior with the organizational interest must fail. For example, managers can make mistakes in designing organizational structure or develop sub-optimized processes, and employees’ responses to such mistakes will cause waste of resources and lower performance. On the other hand, the assumption of equilibrium implies that each organization can reach the state of “fit” which is “a combination of organizational and contingent characteristics [that] produces higher organizational performance than alternative combinations” (Covaleski et al., 2003). In the equilibrium state “an underlying congruence between context and structure [exists]” (Drazin and van de Ven, 1985). The consequence of the equilibrium assumption is that organizations either move towards the “fit” or they disappear from the market (Donaldson, 2001). With other words, properly “fitted” organizations have higher chances of survival.

This paper extends the research in three ways. First, it builds on prior work (Cadez and Guilding, 2008; Chenhall, 2003; Chenhall and Langfield-Smith, 2007) and provides a systematic overview of the empirical results in contingency research of performance management. For instance, adding to Chenhall (2003) this paper provides an overview of propositions raised in literature and summarizes supporting and contrasting evidence. Second, following Covaleski et al. (2003) and Gerdin and Greve (2004) results are compared in terms of study design, concepts used, operationalization and validity issues. Finally, gaps in research are identified and avenues for future research are proposed.  

Contact the author for more information


Bititci et al. (1997), “Integrated performance measurement systems: A development guide“, International Journal of Operations & Production Management, Vol. 17 No. 5, pp. 522–534.

Cadez and Guilding (2008), “An exploratory investigation of an integrated contingency model of strategic management accounting“, Accounting, Organizations and Society, Vol. 33 No. 7/8, pp. 836–863.

Chapman (1997), “Reflections on a contingent view of accounting“, Accounting, Organizations and Society, Vol. 22 No. 2, pp. 189–205.

Chenhall (2003), “Management control systems design within its organizational context: Findings from contingency-based research and directions for the future“, Accounting, Organizations and Society, Vol. 28 No. 2-3, pp. 127–168.

Chenhall (2006), “Theorizing contingencies in management control systems research“, In: Chapman, C.S. (Ed.), Handbooks of Management Accounting Research, Elsevier, pp. 163–205.

Chenhall and Langfield-Smith (2007), “Multiple perspectives of performance measures“, European Management Journal, Vol. 25 No. 4, pp. 266–282. [PDF]

Covaleski et al. (2003), “Budgeting research: Three theoretical perspectives and criteria for selective integration“, Journal of Management Accounting Research, Vol. 15, pp. 3–49.

Donaldson (2001), “The contingency theory of organizations“, Sage Publications, Thousand Oaks.

Drazin and van de Ven (1985), “Alternative forms of fit in contingency theory“, Administrative Science Quarterly, Vol. 30 No. 4, pp. 514–539.

Fisher (1998), “Contingency theory, management control systems and firm outcomes: Past results and future directions”, Behavioral Research in Accounting, Vol. 10, pp. 47.

Gerdin and Greve (2004), “Forms of contingency fit in management accounting research: A critical review“, Accounting, Organizations and Society, Vol. 29 No. 3-4, pp. 303–326.

Govindarajan (1988), “A contingency approach to strategy implementation at the business-unit level: Integrating administrative mechanisms with strategy“, Academy of Management Journal, Vol. 31 No. 4, pp. 828–853.

Ittner and Larcker (1995), “Total quality management and the choice of information and reward systems“, Journal of Accounting Research, Vol. 33 No. 33, Supplement, pp. 1–34.

Ittner and Larcker (1997), “Quality strategy, strategic control systems, and organizational performance“, Accounting, Organizations and Society, Vol. 22 No. 3-4, pp. 293–314.

Ittner and Larcker (2001), “Assessing empirical research in managerial accounting: A value-based management perspective“, Journal of Accounting and Economics, Vol. 32 No. 1-3, pp. 349–410.

Ittner and Larcker (2009), “Extending the boundaries: Nonfinancial performance measures“, In: Chapman, C.S., Hopwood, A.G., and Shields, M.D. (Eds.), Handbook of management accounting research, Elsevier Science, Oxford, pp. 1235–1251.

Ittner et al. (2003), “Performance implications of strategic performance measurement in financial services firms“, Accounting, Organizations and Society, Vol. 28 No. 7-8, pp. 715–741.

Jääskeläinen et al. (2012), “A contingency approach to performance measurement in service operations“, Measuring Business Excellence, Vol. 16 No. 1, pp. 43–52.

Jermias and Gani (2004), “Integrating business strategy, organizational configurations and management accounting systems with business unit effectiveness: A fitness landscape approach”, Management Accounting Research, Vol. 15 No. 2, pp. 179–200.

Jones (1985), “An empirical study of the evidence for contingency theories of management accounting systems in conditions of rapid change“, Accounting, Organizations and Society, Vol. 10 No. 3, pp. 303–328.

Kilfoyle and Richardson (2011), “Agency and structure in budgeting: Thesis, antithesis and synthesis: Norman Macintosh and Critical Accounting Research: A Festschrift”, Critical Perspectives on Accounting, Vol. 22 No. 2, pp. 183–199.

Langfield-Smith (1997), “Management control systems and strategy: A critical review“, Accounting, Organizations and Society, Vol. 22 No. 2, pp. 207–232.

Lee and Yang (2011), “Organization structure, competition and performance measurement systems and their joint effects on performance“, Management Accounting Research, Vol. 22 No. 2, pp. 84–104.

Otley (1980), “The contingency theory of management accounting: Achievement and prognosis“, Accounting, Organizations and Society, Vol. 5 No. 4, pp. 413–428.

Said et al. (2003), “An empirical investigation of the performance consequences of nonfinancial measures“, Journal of Management Accounting Research, Vol. 15 No. 1, pp. 193–223.

van der Stede et al. (2006), “Strategy, choice of performance measures, and performance“, Behavioral Research in Accounting, Vol. 18, pp. 185–205.

Integration of performance measurement system and performance – theory

Integration of performance measurement systems is a frequently named success factor for performance measurement. For example, 35% of senior executives surveyed for the recent study by IBM (2010) reported that performance data integration was on the top of their agenda. Other reports by consulting companies indicate the importance of PMS integration for strategy success (Accenture, 2010) and identify the lack of integration as a source of performance management failure (Townsend, Smith, Richards, & Wennekes, 2009).

Peer reviewed articles also identify PMS integration as one of the critical success factors of business management. In fact, claims that the degree of PMS integration, both vertical and horizontal, may have a positive impact on performance are not new (Bititci, 1994). For example in her literature review Langfield-Smith (1997) argues that theoretical and normative research in that area began to appear in the mid-1980s, but still lacked empirical evidence in the mid-1990s. More than a decade later, empirical studies that explicitly model PMS integration as the independent variable and performance as the dependent variabel are still rare.

Since the publications by Kaplan and Norton (1996a, b) integration of PMS has been frequently refered to in academic literature. However, the review by Franco-Santos and Bourne (2005) showed that this concept is not uniformally understood. According to them, two perspectives on integration can be identified (see figure below). The first perspective refers to the integration as the vertical allignment along the reporting chain. This understanding includes the interaction of performance measurement with the organizational strategy, cascading the strategic goals down to operational divisions and the linkage to individual incentives (Bititci, 1994; Chenhall, 2005). The second perspective refers to the horizontal integration, which is the cross functional connection of the performance measurement system along divisions. Horizontal integration includes the interconnection of PMS with other management control systems, such as planning and budgeting (Henri, 2008), strategic accounting systems (Cadez & Guilding, 2008), costing (Anderson, 2006), ERP (Kallunki, Laitinen, & Silvola, forthcoming) and benchmarking (Herzog, Tonchia, & Polajnar, 2009). Both perspectives have been reserached by scholars – with limited results.

For example, the impact of integration (vertical and/or horizontal) on performance is not clearly researched. While some authors state that integration is one of the critical success factors of performance measurement initiatives (Chenhall, 2005; Chenhall & Langfield-Smith, 2007; Franco-Santos & Bourne, 2005), others doubt that integration is important per se (Rom & Rohde, 2007). In fact, it has been argued that companies may need a certain level of PMS integration (Chapman & Kihn, 2009), but may be better off with specialized stand alone solutions instead of creating fully integrated systems (Pike, Tayles, & Abu Mansor, forthcoming). An interesting research question would be therefor, if there is an impact of integrated performance measurement systems on performance. And if there is an effect, through which mechanisms does it take place.


[PDF] Accenture (2010). Swedish match: Enterprise performance management framework. Retrieved from

Anderson, S. W. (2006). Managing costs and cost structure throughout the value chain: Research on strategic cost management. In C. S. Chapman (Ed.), Handbooks of Management Accounting Research (pp. 481–506). Elsevier.

[PDF] Bititci, U. S. (1994). Measuring your way to profit. Management Decision, 32(4), 16–24.

Cadez, S., & Guilding, C. (2008). An exploratory investigation of an integrated contingency model of strategic management accounting. Accounting, Organizations and Society, 33(7/8), 836–863.

Chapman, C. S., & Kihn, L.-A. (2009). Information system integration, enabling control and performance. Accounting, Organizations and Society, 34(2), 151–169.

Chenhall, R. H. (2005). Integrative strategic performance measurement systems, strategic alignment of manufacturing, learning and strategic outcomes: An exploratory study. Accounting, Organizations and Society, 30(5), 395–422.

[PDF] Chenhall, R. H., & Langfield-Smith, K. (2007). Multiple perspectives of performance measures. European Management Journal, 25(4), 266–282.

[PDF] Franco-Santos, M., & Bourne, M. (2005). An examination of the literature relating to issues affecting how companies manage through measures. Production Planning & Control, 16(2), 114–124.

Henri, J.-F. (2008). Taxonomy of performance measurement systems. Advances in Management Accounting, 17, 247–288.

Herzog, N. V., Tonchia, S., & Polajnar, A. (2009). Linkages between manufacturing strategy, benchmarking, performance measurement and business process reengineering. Computers & Industrial Engineering, 57(3), 963–975.

IBM (2010). Analytics: The new path to value: How the smartest organizations are embedding analytics to transform insights into action: IBM Institute for Business Value. Retrieved from

Kallunki, J.-P., Laitinen, E. K., & Silvola, H. (forthcoming). Impact of enterprise resource planning systems on management control systems and firm performance. International Journal of Accounting Information Systems,

Kaplan, R. S., & Norton, D. P. (1996a). The balanced scorecard: Translating strategy into action. Boston: Harvard Business School Press.

Kaplan, R. S., & Norton, D. P. (1996b). Using the balanced scorecard as a strategic management system. Harvard Business Review, 74(1), 75–85.

Langfield-Smith, K. (1997). Management control systems and strategy: A critical review. Accounting, Organizations and Society, 22(2), 207–232.

Pike, R. H., Tayles, M. E., & Abu Mansor, N. N. (forthcoming). Activity-based costing user satisfaction and type of system: A research note. The British Accounting Review,

[PDF PhD] Rom, A., & Rohde, C. (2007). Management accounting and integrated information systems: A literature review. International Journal of Accounting Information Systems, 8(1), 40–68.

Townsend, P., Smith, S., Richards, G., & Wennekes, K. (2009). Performance management matters: Sustaining superior results in a global economy: PricewaterhouseCoopers.

Literature based characteristics of high performing organizations – a review

According to the literature, high performing organizations (HPO) tend to share similar characteristics. Professor de Waal, the academic director at the Center for Organizational Performance based in the Netherlands, proposed a framework to analyse these factors in his latest paper (de Wall 2010). The literature analysis presented here was based on the review of 262 academic and corporate sources (non english and grey literature excluded).

A new method of literature review – the systematic review – was applied here to address the topic of high performance organizations. The insights extracted from the literature are articulated and presented in a framework developed by de Waal ( 2008, 2010a, b). The paper will only focus on the thematic findings of this literature review and its greatest contribution is the overview of academic and practice work aimed at understanding the secrets of top management practices. The identified success factors of organizations are presented below:

These factors include following capabilities (follow the links provided to each marked key word to discover current management thinking):

Organizational design characteristics

  • D1. Stimulate cross-functional and cross-organizational collaboration.
  • D2. Simplify and flatten the organization by reducing boundaries and barriers between and around units.
  • D3. Foster organization-wide sharing of information, knowledge and best practices.
  • D4. Constantly realign the business with changing internal and external circumstances.

Strategy characteristics

Process characteristics

  • P1. Design a good and fair reward and incentive structure.
  • P2. Continuously innovate products, processes and services.
  • P3. Continuously simplify and improve all the organization’s processes.
  • P4. Create highly interactive internal communication.
  • P5. Measure what matters.
  • P6. Report to everyone financial and non-financial information needed to drive improvement.
  • P9. Strive for continuous process optimalization.
  • P8. Strive to be a best practice organization.
  • P9. Deploy resources effectively.

Technology characteristics

  • T1. Implement flexible ICT-systems throughout the organization.
  • T2. Apply user-friendly ICT-tools to increase usage.

Leadership characteristics

  • L1. Maintain and strengthen trust relationships with people on all levels.
  • L2. Live with integrity and lead by example.
  • L3. Apply decisive action-focused decision-making.
  • L4. Coach and facilitate.
  • L5. Stretch yourselves and your people.
  • L6. Develop effective, focused and strong leadership.
  • L7. Allow experiments and mistakes.
  • L8. Inspire the people to accomplish extraordinary results.
  • L9. Grow leaders from within.
  • L10. Stimulate change and improvement.
  • L11. Assemble a diverse and complementary management team and workforce.
  • L12. Be committed to the organization for the long haul.
  • L13. Be confidently humble.
  • L14. Hold people responsible for results and be decisive about nonperformers.

Individuals & Roles characteristics

  • I1. Create a learning organization.
  • I2. Attract exceptional people with a can-do attitude who fit the culture.
  • I3. Engage and involve the workforce.
  • I4. Create a safe and secure workplace.
  • I5. Master the core competencies and be an innovator in them.
  • I6. Develop people to be resilient and flexible.
  • I7. Align employee behaviour and values with company values and direction.

Culture characteristics

  • C1. Empower people and give them freedom to decide and act.
  • C2. Establish strong and meaningful core values.
  • C3. Develop and maintain a performance-driven culture.
  • C4. Create a culture of transparency, openness and trust.
  • C5. Create a shared identity and a sense of community.

External orientation characteristics

  • E1. Continuously strive to enhance customer value creation.
  • E2. Maintain good and long-term relationships with all stakeholders.
  • E3. Monitor the environment consequently and respond adequately.
  • E4. Choose to compete and compare with the best in the market place .
  • E5. Grow through partnerships and be part of a value creating network.
  • E6. Only enter new business that complement the company‟s strengths.

A more recent work around the characteristics of high performing organizations is provided by Kiron et al. (2011). Please read the Analytics: The Widening Divide for more details.


Additional reading:


Research concept updated

The impact of performance management on corporate performance

Why do some companies perform better using corporate performance measurement and management systems than others?

To cope with the increasing complexity of the business environment, management teams must prioritize effectively and focus their attention on activities that lead to higher performance. For that reason many organizations have invested substantial resources in the implementation of various performance measurement and management techniques. They believe, that performance measurement and management might help them to improve the performance somehow (see illustration below).

However, the added value of that investment often remains unclear with only few organizations reporting tangible payoff on the performance measurement systems. Consequently, managers of today need a clear guidance for their efforts to manage performance and on how to get the most value out of the existing performance measurement systems.

Since Kaplan and Norton (1992) first introduced their Balanced Scorecard, a substantial body of research around the design, implementation, and usage of performance measurement systems (PMS), has emerged (see Neely, 2005, for literature review). Despite the growing academic and professional interest, there is currently little knowledge regarding the impact of PMS on organizations (see Bourne, Kennerley, & Franco-Santos, 2005 for literature review). Furthermore, existing research provides contradictory results concerning performance effects of the PMS usage (Martinez, Kennerley, & Neely, 2004). While some authors clearly see positive effects (Davis & Albright, 2004; deWaal, Kourtit, & Nijkamp, 2009; Ukko, Tenhunen, & Rantanen, 2007; de Geuser, Mooraj, & Oyon, 2009), others found no evidence of increasing performance after the implementation of PMS (Meyer, 2007). Therefore, a consensus in the ongoing discussion regarding the effect of PMS on organizations has not yet been achieved.

Based on results from literature, this study is set to identify the success factors leading to a better use of performance management systems. The research problem is to find out how companies can be successfully managed with measures (see illustration below).

The starting point for the research is the believe, that performance management systems (PMS) can lead to a greater performance only when PMS are used by people to make better business decisions (Chenhall, 2003). If this is the case, and other variables can be controlled for, the interesting question is what makes people take better decisions with PMS. Consequently, the conceptual model includes a link between decision making based on PMS information and performance. This link has been often described qualitatively (Goold & Quinn, 1990; Gunasekaran & Kobu, 2007; Laitinen, 2009; Lipe & Salterio, 2000), but quantitative analysis is rare (e.g. Foster, Swenson, 1997). Thus, this study wants to contribute to the research and provide evidence why some companies use PMS better than others (see illustration below).

To provide a solid answer to that question the study is organized as following:

  1. Identify relevant factors leading to an effective performance management from literature.
  2. Define a solid conceptual model.
  3. Create instrument for measuring concepts based on suggestions from literature.
  4. Gather empirical data and analyse the data.
  5. Arrive at conclusions.
  6. Provide final report.

Key characteristics of the research:

  1. Literature based.
  2. Quantitative, positivistic approach.
  3. Company as unit of analysis.
  4. Cross sectional non probability sample of profit oriented firms.


Bourne, M., Kennerley, M., & Franco-Santos, M. (2005). Managing through measures: A study of impact on performance. Journal of Manufacturing Technology Management, 16(4), 373–395.

Chenhall, R. H. (2003). Management control systems design within its organizational context: findings from contingency-based research and directions for the future. Accounting, Organizations and Society, 28(2-3), 127–168.

[PDF] Davis, S., & Albright, T. (2004). An investigation of the effect of Balanced Scorecard implementation on financial performance. Management Accounting Research, 15(2), 135–153.

de Waal, A., Kourtit, K., & Nijkamp, P. (2009). The relationship between the level of completeness of a strategic performance management system and perceived advantages and disadvantages. International Journal of Operations & Production Management, 29(12), 1242–1265.

[Summary] Foster, George; Swenson, Dan W. (1997): Measuring the success of activity-based cost management and its determinants. In Journal of Management Accounting Research 9, pp. 109–141.

Geuser, F. de, Mooraj, S., & Oyon, D. (2009). Does the balanced scorecard add value? Empirical evidence on its effect on performance. European Accounting Review, 18(1), 93–122.

Goold, M., & Quinn, J. J. (1990). The paradox of strategic controls. Strategic Management Journal, 11(1), 43–57.

Gunasekaran, A., & Kobu, B. (2007). Performance measures and metrics in logistics and supply chain management: A review of recent literature (1995-2004) for research and applications. International Journal of Production Research, 45(12), 2819–2840.

Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard: Measures that drive performance. Harvard Business Review, 71–79.

Laitinen, E. K. (2009). Importance of performance information in managerial work. Industrial Management & Data Systems, 109(4), 550–569.

Lipe, M. G., & Salterio, S. E. (2000). The balanced scorecard: Judgmental effects of common and unique performance measures. Accounting Review, 75(3), 283.

Martinez, V., Kennerley, M., & Neely, A. (2004). Impact of PMS on business performance: A methodological approach. Cranfield.

Neely, A. (2005). The evolution of performance measurement research: Developments in the last decade and a research agenda for the next. International Journal of Operations & Production Management, 25(12), 1264–1277.

Ukko, J., Tenhunen, J., & Rantanen, H. (2007). Performance measurement impacts on management and leadership: Perspectives of management and employees. International Journal of Production Economics, 110(1-2), 39–51.