A Bibliometric Analysis and Review on Performance Modeling Literature

In management practice, performance indicators are considered as a prerequisite to make informed decisions in line with the organization’s goals. On the other hand, indicators summarizes compound phenomena in a few digits, which can induce to inadequate decisions, biased by information loss and conflicting values. Model driven approaches in enterprise engineering can be very effective to avoid these pitfalls, or to take it under control. For that reason, “performance modeling” has the numbers to play a primary role in the “model driven enterprise” scenario, together with process, information and other enterprise-related aspects. In this perspective, we propose a systematic review of the literature on performance modeling in order to retrieve, classify, and summarize existing research, identify the core authors and define areas and opportunities for future research.

[1]  J. Euzenat,et al.  Ontology Matching , 2007, Springer Berlin Heidelberg.

[2]  Alireza Pourshahid,et al.  Business process management with the user requirements notation , 2009, Electron. Commer. Res..

[3]  John Krogstie,et al.  Active knowledge modeling of enterprises , 2008 .

[4]  Paul W. P. J. Grefen,et al.  Measures and mechanisms for process monitoring in evolving business networks , 2012, Data Knowl. Eng..

[5]  John Mylopoulos,et al.  Reasoning with Key Performance Indicators , 2011, PoEM.

[6]  Viara Popova,et al.  Modeling organizational performance indicators , 2010, Inf. Syst..

[7]  Guy Doumeingts,et al.  GRAI integrated methodology and its mapping onto generic enterprise reference architecture and methodology , 1997 .

[8]  Michele Missikoff,et al.  An Approach to the Definition of a Core Enterprise Ontology: CEO , 2001 .

[9]  Faribors Ronaghi,et al.  Integrated Performance Management , 2016, ICEIS.

[10]  Florian Matthes,et al.  Towards a Unified and Configurable Structure for EA Management KPIs , 2012, TEAR/PRET.

[11]  John Mylopoulos,et al.  Composite Indicators for Business Intelligence , 2011, ER.

[12]  R. Kaplan,et al.  Linking the Balanced Scorecard to Strategy , 1996 .

[13]  Guy Doumeingts,et al.  GRAI Grid Decisional Modelling , 1998 .

[14]  Nikolay Mehandjiev,et al.  Future Internet Enterprise Systems (FinES) Cluster.Research Roadmap.Final Report , 2010 .

[15]  Tonci Grubic,et al.  Supply chain ontology: Review, analysis and synthesis , 2010, Comput. Ind..

[16]  Tingting Wang,et al.  Optimized cross-organizational business process monitoring: Design and enactment , 2013, Inf. Sci..

[17]  Carlos Pedrinaci,et al.  SENTINEL: a semantic business process monitoring tool , 2008, OBI '08.

[18]  Manuel Resinas Arias de Reyna,et al.  Defining Process Performance Indicators: an Ontological Approach , 2010 .

[19]  Del-Río-OrtegaAdela,et al.  On the definition and design-time analysis of process performance indicators , 2013 .

[20]  Ulrich Frank,et al.  Multi-perspective enterprise modeling: foundational concepts, prospects and future research challenges , 2014, Software & Systems Modeling.

[21]  Bob J. Wielinga,et al.  Using explicit ontologies in KBS development , 1997, Int. J. Hum. Comput. Stud..

[22]  Manuel Resinas,et al.  Using templates and linguistic patterns to define process performance indicators , 2016, Enterp. Inf. Syst..

[23]  André-René Probst,et al.  Business concepts ontology for an enterprise performance and competences monitoring , 2007, Comput. Ind..

[24]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[25]  Yair Levy,et al.  A Systems Approach to Conduct an Effective Literature Review in Support of Information Systems Research , 2006, Informing Sci. Int. J. an Emerg. Transdiscipl..

[26]  John Mylopoulos,et al.  Conceptualizing and specifying key performance indicators in business strategy models , 2012, CASCON.

[27]  Ulrich Frank,et al.  Designing and Utilising Business Indicator Systems within Enterprise Models-Outline of a Method , 2008, MobIS.

[28]  Ulrich Frank,et al.  Use of a Domain Specific Modeling Language for Realizing Versatile Dashboards , 2009 .

[29]  Claudia Diamantini,et al.  A Logic-Based Formalization of KPIs for Virtual Enterprises , 2013, CAiSE Workshops.

[30]  Michael Uschold,et al.  Ontologies: principles, methods and applications , 1996, The Knowledge Engineering Review.

[31]  Frantz Rowe,et al.  What literature review is not: diversity, boundaries and recommendations , 2014, Eur. J. Inf. Syst..

[32]  Carlos Mario Zapata Jaramillo,et al.  Executable pre-conceptual schemas for representing key performance indicators , 2013 .

[33]  Richard T. Watson,et al.  Analyzing the Past to Prepare for the Future: Writing a Literature Review , 2002, MIS Q..

[34]  Ian Horrocks,et al.  Description Logics , 2008, Handbook of Knowledge Representation.

[35]  Alireza Pourshahid,et al.  Business Process Monitoring and Alignment: An Approach Based on the User Requirements Notation and Business Intelligence Tools , 2007, WER.

[36]  Mark Rouncefield,et al.  The State of Practice in Model-Driven Engineering , 2014, IEEE Software.

[37]  Stephen R. Gulliver,et al.  Artefact-oriented Business Process Modelling - An Ontological Dependency Approach , 2013, ICEIS.

[38]  Erich Ortner,et al.  Controlling of Dynamic Enterprises by Indicators - A Foundational Approach , 2010, Business Process Management Workshops.

[39]  Jan Treur,et al.  A specification language for organisational performance indicators , 2005, Applied Intelligence.

[40]  A. Sharpanskykh,et al.  Performance-oriented Organisation Modelling , 2006 .

[41]  Artturi Nurmi,et al.  Towards Semantic Performance Measurement Systems for Supply Chain Management , 2010, OTM Workshops.

[42]  Joerg Evermann,et al.  Ontology based object-oriented domain modelling: fundamental concepts , 2005, Requirements Engineering.

[43]  Mario A. Bochicchio,et al.  Performance Modeling for Collaborative Enterprises: Review and Discussion , 2014, BIR.

[44]  Themis Palpanas,et al.  Integrated model-driven dashboard development , 2007, Inf. Syst. Frontiers.

[45]  D. Tranfield,et al.  Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review , 2003 .

[46]  Asunción Gómez-Pérez,et al.  Ontological Engineering: With Examples from the Areas of Knowledge Management, e-Commerce and the Semantic Web , 2004, Advanced Information and Knowledge Processing.

[47]  Frank Leymann,et al.  Towards Measuring Key Performance Indicators of Semantic Business Processes , 2008, BIS.

[48]  Laila Niedrite,et al.  Performance Measurement Framework with Formal Indicator Definitions , 2011, BIR.

[49]  Faribors Ronaghi A modeling method for integrated performance management , 2005, 16th International Workshop on Database and Expert Systems Applications (DEXA'05).

[50]  Robert Grafton Small,et al.  Platform , 2015, Encyclopedic Dictionary of Archaeology.

[51]  Hans Weigand,et al.  Enterprise Monitoring Ontology , 2011, ER.

[52]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[53]  Pengfei Chen,et al.  Toward an Integrated User Requirements Notation Framework and Tool forBusiness Process Management , 2008, 2008 International MCETECH Conference on e-Technologies (mcetech 2008).

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

[55]  Manuel Resinas,et al.  On the definition and design-time analysis of process performance indicators , 2013, Inf. Syst..

[56]  Claudia Diamantini,et al.  A semi-automatic methodology for the design of performance monitoring systems , 2014, SEBD.

[57]  Vinay Kulkarni,et al.  Modelling and Enterprises - The Past, the Present and the Future , 2013, MODELSWARD.

[58]  Stefan Strecker,et al.  MetricM: a modeling method in support of the reflective design and use of performance measurement systems , 2012, Inf. Syst. E Bus. Manag..

[59]  Claudia Diamantini,et al.  Extending Drill-Down through Semantic Reasoning on Indicator Formulas , 2014, DaWaK.