The effect of performance measurement systems on firm performance: A cross-sectional and a longitudinal study

Performance measurement (PM) systems have been popularized over the last 20 years and the operations management literature is replete with discussion of metrics and measurement systems. Yet, a comprehensive nomological network relating types of PM system uses to organizational capabilities and performance is lacking. Furthermore, there is scant empirical evidence attesting to the explanatory efficacy of PM systems as it relates to organizational performance. We view PM system uses through the lenses of the Resource Orchestration Theory (ROT) and explore specific relationships of underlying variables by relying on the Organizational Information Processing Theory (OIPT). Resting on the extant literature, we identify two types of uses which include Diagnostic Use (the review of critical performance variables in order to maintain, alter, or justify patterns in an organizational activity) and interactive use (a forward-looking activity exemplified by active and frequent involvement of top management envisioning new ways to orchestrate organizational resources for competitive advantage) and relate them along with their interaction (i.e., dynamic tension) to organizational capabilities. We further link capabilities to target performance, which subsequently impacts organizational performance (operationalized through both perceptual and objective financial performance measures). The nomological network is tested via a cross sectional study (386 Italian firms) while the efficacy of PM systems to explain organizational performance is examined by using longitudinal panel data approaches over a 10 year period. There is sufficient evidence to suggest that the use of PM systems leads to improved capabilities, which then impact performance. Contrary to the extant literature, however, we discovered that Diagnostic Use appears to be the most constructive explanatory variable for capabilities. On the other hand, in light of a longitudinal study, we also uncovered that Diagnostic Use experienced depreciating returns as far as objective financial measures are concerned. Also, when high levels of Diagnostic Use were coupled with low levels of Interactive Use, they produced the lowest levels of organizational capabilities. Conversely, high levels of both types of PM system use generated extraordinary high levels of capabilities. There is sufficient evidence to suggest that organizations cannot rely merely on Diagnostic Use of PM systems. We also learned that the effects of PM systems (measured via adaptation) fade unless high learning rates are applied. We offer detailed recommendations for future research which have theoretical as well as empirical implications.

[1]  Charles J. Corbett,et al.  The Financial Impact of ISO 9000 Certification in the United States: An Empirical Analysis , 2005, Manag. Sci..

[2]  Terry M. Coalter,et al.  Context, Cognition, and Common Method Variance: Psychometric and Verbal Protocol Evidence , 1996 .

[3]  David G. Sirmon,et al.  Managing Firm Resources in Dynamic Environments to Create Value: Looking Inside the Black Box , 2007 .

[4]  Andy Neely,et al.  Performance measurement system design , 1995 .

[5]  S. Lamouri,et al.  A framework for analysing supply chain performance evaluation models , 2013 .

[6]  Laurie L. Burney,et al.  Behavioral Work Outcomes of a Strategic Performance Measurement System-Based Incentive Plan , 2013 .

[7]  A. Neely.  The evolution of performance measurement research: Developments in the last decade and a research agenda for the next , 2005 .

[8]  J. D. Margolis,et al.  Misery Loves Companies: Rethinking Social Initiatives by Business , 2003 .

[9]  Thomas W. Lin,et al.  Strategy, Choice of Performance Measures, and Performance , 2006 .

[10]  John Roberts,et al.  Strategy and accounting in a U.K. conglomerate , 1990 .

[11]  James G. Combs,et al.  Strategic resources and performance: a meta‐analysis , 2008 .

[12]  Thomas Li-Ping Tang,et al.  Learning from Japanese Transplants and American Corporations , 1995 .

[13]  Sally K. Widener,et al.  An Empirical Analysis of the Levers of Control Framework , 2005 .

[14]  Andy Neely,et al.  The Performance Prism: The Scorecard for Measuring and Managing Business Success , 2002 .

[15]  Constance E. Helfat,et al.  Dynamic capabilities : understanding strategic change in organizations , 2007 .

[16]  A. Gunasekaran,et al.  Performance measures and metrics in a supply chain environment , 2001 .

[17]  Lorenzo Moreno,et al.  Propensity Score Matching , 2008 .

[18]  Lorenzo Lucianetti,et al.  Contemporary Performance Measurement Systems: A Review of Their Consequences and a Framework for Research , 2012 .

[19]  Umit Bititci,et al.  Dynamics of performance measurement systems , 2000 .

[20]  Jay R. Galbraith.  Organization Design: An Information Processing View , 1974 .

[21]  Naresh K. Malhotra,et al.  Common Method Variance in IS Research: A Comparison of Alternative Approaches and a Reanalysis of Past Research , 2006, Manag. Sci..

[22]  R. Kaplan,et al.  The balanced scorecard--measures that drive performance. , 2015, Harvard business review.

[23]  D. Larcker,et al.  Are nonfinancial measures leading indicators of financial performance? An analysis of customer satisfaction , 1998 .

[24]  Taylor Randall,et al.  Performance Implications of Strategic Performance Measurement in Financial Services Firms , 2003 .

[25]  Steven A. Melnyk,et al.  Metrics and performance measurement in operations management: dealing with the metrics maze , 2004 .

[26]  Kwan Hee Han,et al.  Manufacturing cycle time reduction for batch production in a shared worker environment , 2013 .

[27]  A. Gunasekaran,et al.  A framework for supply chain performance measurement , 2004 .

[28]  Umit Bititci,et al.  Integrated performance measurement systems: a development guide , 1997 .

[29]  William C. Moncrief,et al.  Examining Motivations to Refuse in Industrial Surveys , 1999 .

[30]  Marshall W. Meyer,et al.  Subjectivity and the Weighting of Performance Measures: Evidence from a Balanced Scorecard , 2003 .

[31]  R. Johnston,et al.  Performance Measurement in Service Businesses , 1992 .

[32]  Joseph Sarkis,et al.  Stakeholder pressure and the adoption of environmental practices: The mediating effect of training , 2010 .

[33]  W. Orlikowski,et al.  Windows of Opportunity: Temporal Patterns of Technological Adaptation in Organizations , 2011 .

[34]  Jacob G. Birnberg,et al.  The organizational context of accounting , 1983 .

[35]  Andrew Hess,et al.  Building Dynamic Capabilities: Innovation Driven by Individual-, Firm-, and Network-Level Effects , 2007, Organ. Sci..

[36]  Scott Hamilton,et al.  Evaluating Information Systems Effectiveness - Part I: Comparing Evaluation Approaches , 1981, MIS Q..

[37]  Thomas Ahrens,et al.  Accounting for Flexibility and Efficiency: A Field Study of Management Control Systems in a Restaurant Chain , 2004 .

[38]  K. Merriman,et al.  The Effects of CEO Pay Structure on Corporate Social Performance , 2006 .

[39]  David J. Ketchen,et al.  Supply Chain Knowledge and Performance: A Meta-Analysis , 2013, Decis. Sci..

[40]  R. Chenhall,et al.  Organic decision and communication processes and management accounting systems in entrepreneurial and conservative business organizations , 1995 .

[41]  Andy Neely,et al.  Performance measurement system design: developing and testing a process‐based approach , 2000 .

[42]  C. K. Prahalad,et al.  Competing For the Future : breakthrough strategies for seizing control of your industry and creating the markets of tomorrow , 1994 .

[43]  William B. Tayler,et al.  Strategy Selection, Surrogation, and Strategic Performance Measurement Systems: strategy selection and surrogation , 2013 .

[44]  A. Neely.  The performance measurement revolution: why now and what next? , 1999 .

[45]  Josep Bisbe,et al.  Defining management accounting constructs: A methodological note on the risks of conceptual misspecification , 2007 .

[46]  Umit S. Bititci,et al.  Dynamics of performance measurement systems , 2000, APMS.

[47]  David G. Sirmon,et al.  Managing Resources: Linking Unique Resources, Management, and Wealth Creation in Family Firms , 2003 .

[48]  Robert Simons,et al.  Strategic orientation and top management attention to control systems , 1991 .

[49]  Antonio Davila,et al.  Performance measurement & control systems for implementing strategy : text & cases , 2000 .

[50]  K. Langfield-Smith,et al.  The relationship between strategic priorities, management techniques and management accounting: an empirical investigation using a systems approach , 1998 .

[51]  J. Zimmerman.  Accounting for Decision Making and Control , 1994 .

[52]  P. Cousins,et al.  Performance measurement in strategic buyer‐supplier relationships: The mediating role of socialization mechanisms , 2008 .

[53]  M. Porter.  Towards a dynamic theory of strategy , 1991 .

[54]  P. Schoemaker,et al.  Strategic assets and organizational rent , 1993 .

[55]  Andrew Taylor,et al.  Antecedents of effective performance measurement system implementation: an empirical study of UK manufacturing firms , 2013 .

[56]  Gerald K. Debusk,et al.  The effects of adopting the Balanced Scorecard on shareholder returns , 2008 .

[57]  Nofal Nagles García.  Reseña de "Dynamic capabilities. Understanding strategic change in organizations" de Constance E. Helfat, Sydney Finkelstein, Will Mitchell, Margareth Peteraf, Harbir Singh, David J. Teece, Sidney Winter , 2010 .

[58]  Maximilian Röglinger,et al.  A decision framework for the consolidation of performance measurement systems , 2013, Decis. Support Syst..

[59]  Habib Mahama,et al.  Management control systems, cooperation and performance in strategic supply relationships: A survey in the mines , 2006 .

[60]  Robert A. Simons.  Control in an Age of Empowerment , 2008 .

[61]  David J. Ketchen,et al.  Resource gaps and resource orchestration shortfalls in supply chain management: : the case of product recalls , 2014 .

[62]  Mary J. Benner,et al.  ISO 9000 practices and financial performance: A technology coherence perspective , 2008 .

[63]  Julia Mundy,et al.  Creating Dynamic Tensions Through a Balanced Use of Management Control Systems , 2010 .

[64]  Tuomas Ahola,et al.  Is performance measurement suitable for an extended enterprise , 2010 .

[65]  C. Reese,et al.  A Bayesian operationalization of the resource‐based view , 2004 .

[66]  L. Preston,et al.  The Stakeholder Theory of the Corporation: Concepts, Evidence, and Implications , 1995 .

[67]  Garry L. Adams,et al.  Supply Chain Orientation and Balanced Scorecard Performance , 2008 .

[68]  Patrizia Garengo,et al.  Performance measurement system contingency factors: a cross analysis of Italian and Indian SMEs , 2014 .

[69]  Shawn L. Berman,et al.  Does Stakeholder Orientation Matter? The Relationship Between Stakeholder Management Models and Firm Financial Performance , 1999 .

[70]  E. Nijssen,et al.  Performance effects of using the Balanced Scorecard: a note on the Dutch experience , 2004 .

[71]  Ronald K. Mitchell,et al.  Who Matters to Ceos? An Investigation of Stakeholder Attributes and Salience, Corpate Performance, and Ceo Values , 1999 .

[72]  Brian L. Connelly,et al.  Making the Most of What You've Got: Managerial Ability as a Source of Resource Value Creation , 2008 .

[73]  Sally K. Widener,et al.  The role of performance measurement and evaluation in building organizational capabilities and performance , 2010 .

[74]  Salvatore Sciascia,et al.  Resource orchestration in family firms: investigating how entrepreneurial orientation, generational involvement, and participative strategy affect performance , 2011 .

[75]  R. Kaplan,et al.  Mastering the management system. , 2008, Harvard business review.

[76]  M. Goh,et al.  Performance measurement in supply chain entities: balanced scorecard perspective , 2009 .

[77]  Heinz Ahn,et al.  Applying the balanced scorecard concept : an experience report , 2001 .

[78]  Matteo Mura,et al.  Generating organisational performance , 2013 .

[79]  Robert A. Simons.  How new top managers use control systems as levers of strategic renewal , 1994 .

[80]  Richard L. Daft,et al.  Organizational information requirements, media richness and structural design , 1986 .

[81]  Jeroen P. van den Berg,et al.  Improving operational performance by influencing shopfloor behavior via performance management practices , 2011 .

[82]  Michael E. Ketzenberg,et al.  Learning and relearning effects with innovative service designs: An empirical analysis of top golf courses , 2011 .

[83]  F. Thoemmes,et al.  Propensity Score Analysis , 2015 .

[84]  Xenophon Koufteros,et al.  A paradigm for examining second-order factor models employing structural equation modeling , 2009 .

[85]  Jean-François Henri.  ORGANIZATIONAL CULTURE AND PERFORMANCE MEASUREMENT SYSTEMS , 2006 .

[86]  Jean-François Henri,et al.  Management control systems and strategy: A resource-based perspective , 2006 .

[87]  David J. Ketchen,et al.  Addressing Common Method Variance: Guidelines for Survey Research on Information Technology, Operations, and Supply Chain Management , 2011, IEEE Transactions on Engineering Management.

[88]  Betty Vandenbosch,et al.  An empirical analysis of the association between the use of executive support systems and perceived organizational competitiveness , 1999 .

[89]  Mike Bourne,et al.  Explaining the effects of performance measurement on performance: An organizational routines perspective , 2011 .

[90]  Petra E. Todd,et al.  Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme , 1997 .

[91]  Hans-Jörg Bullinger,et al.  Analysing supply chain performance using a balanced measurement method , 2002 .

[92]  X. Koufteros.  Testing a model of pull production: a paradigm for manufacturing research using structural equation modeling , 1999 .

[93]  A. Gunasekaran,et al.  Performance measures and metrics in logistics and supply chain management: a review of recent literature (1995–2004) for research and applications , 2007 .

[94]  Robert A. Eckhoff,et al.  The tyranny of the Balanced Scorecard in the innovation economy , 2006 .

[95]  D. Otley,et al.  The effects of the interactive use of management control systems on product innovation , 2004 .

[96]  Ricardo Malagueño,et al.  Using Strategic Performance Measurement Systems for Strategy Formulation: Does It Work in Dynamic Environments? , 2012 .

[97]  Thomas L. Albright,et al.  An investigation of the effect of Balanced Scorecard implementation on financial performance , 2004 .

[98]  R. Duane Ireland,et al.  Resource Orchestration to Create Competitive Advantage , 2010 .

[99]  Andy Neely,et al.  Designing, implementing and updating performance measurement systems , 2000 .

[100]  R. Freeman.  Strategic Management: A Stakeholder Approach , 2010 .

[101]  Zahirul Hoque,et al.  Linking Balanced Scorecard Measures to Size and Market Factors: Impact on Organizational Performance , 2000 .

[102]  David G. Sirmon,et al.  Strategic Entrepreneurship: Creating Value for Individuals, Organizations, and Society , 2011 .

[103]  R. Chenhall.  Integrative strategic performance measurement systems, strategic alignment of manufacturing, learning and strategic outcomes: an exploratory study , 2005 .

[104]  R. Kaplan,et al.  Transforming the Balanced Scorecard from Performance Measurement to Strategic Management: Part II , 2001 .

[105]  Geoffrey B. Sprinkle.  Perspectives on experimental research in managerial accounting , 2003 .

[106]  Willie Choi,et al.  Strategy Selection, Surrogation, and Strategic Performance Measurement Systems , 2012 .