Performance management systems: reviewing the rise of dynamics and digitalization

Figures & data

Figure 1. Research design: identification of previous research with subsequent data analysis.

Table 1. Search results from selected keywords on Scopus

Keyword	Results
“Performance measurement system*”	4,643
“Dynamic capabilit*”	1,790
“Algorithmic management”	6

Figure 2. Amount and trendline of number of articles published 1987–2017.

Figure 3. Top 20 keywords in the full sample based on keyword presence.

Figure 4. Top 20 keywords that shows the relative use of the main keywords.

Figure 5. The most used keywords between 2013 and 2018.

Figure 6. Trends for the most frequent keywords between 2013 and 2018.

Figure 7. Top 20 journals and conference proceedings.

Figure 8. The six most used keywords in the sample (cleared for keywords such as “performance measurement systems” or “performance management”).

Figure 9. The 15 Keywords with highest normalized degree centrality.

Table 2. Top 15 centrality measures in descending order. 1 means highest degree, 15 means the lowest degree

	Closeness	Farness	Betweenness	Centrality Degree
1	Performance measurement	Design purposes	Performance management	performance measurement
2	Information management	Financial and non-financial-measures	Information management	information management
3	Artificial intelligence	Impact on business outcomes	Information technology	performance management
4	Performance management	Information quality	Performance measurement	decision support system
5	Benchmarking	Information technology use	Decision support system	benchmarking
6	Balanced scorecard	Information technology optimization	Key performance indicator	information technology
7	Supply chain management	Inventory optimization	Manufacture	decision making
8	Information technology	Resource optimization	Decision making	supply chain management
9	Sustainable development	Domain specific languages	Performance measurement system	sustainable development
10	Alignment	Dynamic web applications	Industrial management	industrial management
11	Aggregate performance	Haskell	Management	competition
12	Aggregates	Html	Performance variables	artificial intelligence
13	Performance variables	Dynamics	Problem solving	innovation
14	Decision support system	Management styles	Innovation	performance measurement system
15	Decision making	Supply chain dynamics	Performance indicators	balanced scorecard

Table 3. Eigenvector for top 15 keywords

Keyword	Eigenvector
Performance measurement	0.452
Information management	0.424
Decision support system	0.201
Benchmarking	0.196
Performance management	0.178
Decision making	0.172
Information technology	0.157
Innovation	0.146
Supply chain management	0.143
Sustainable development	0.137
Competition	0.136
Industrial management	0.128
Key performance indicator	0.126
Artificial intelligence	0.112
Balanced scorecard	0.109

Table 4. Geodesic distance between main topics keywords

Geodesic Distance Main Keywords
Performance measurement	Algorithmic management	NA
Performance measurement system*	Algorithmic management	NA
Performance management system*	Algorithmic management	NA
Performance measurement	Dynamic capabilities	1
Performance measurement system*	Dynamic capabilities	2
Performance management system*	Dynamic capabilities	2
Performance measurement	Dynamic capability perspective	2
Performance measurement system*	Dynamic capability perspective	2
Performance management system*	Dynamic capability perspective	2

Table 5. Main topic keywords centrality by degree and Eigenvector

Main Keyword	nDegree Centrality	Eigenvector
Dynamic capabilities	0 (3 decimals)/geodesic 25	0.013
Dynamic capability perspective	0 (3 decimals)/geodesic 14	0.003
Algorithmic management	NA	NA

Table 6. Presents four articles with links between PMS and DC. The linking keyword is “performance measurement” and “dynamic capabilities”

Author(s)	Title
(Li, Wu, & Holsapple, 2015) Li, X Wu, Q Holsapple, C W	Best-value supply chains and firms’ competitive performance: empirical studies of their linkage
(Hanson, Melnyk, & Calantone, 2011) Hanson, J D Melnyk, S A Calantone, R A	Defining and measuring alignment in performance management
(McAdam, Humphreys, et al., 2017) McAdam, R Humphreys, P Galbraith, B Miller, Kl	Developing management capability within a horizontal supply chain in performance measurement deployment and evolution: a Dynamic Capabilities and Goal Theory perspective
(McAdam, Bititci, et al., 2017) McAdam, R Bititci, U Galbraith, B	Technology alignment and business strategy: a performance measurement and Dynamic Capability perspective

Figure 10. K-core analysis with relations >3 and node size after degree. Five main subgroups identified.

Table 7. Analysis of the potential concept emerging from the subgroups. Group 1 with highest degree centrality

Group	Keywords	Conceptualization/Themes
1 (most influential group)	PMS, performance management, information management, performance measurement, decision support systems, information technology, and supply chain management.	Researching decision support systems that incorporate information and information technology for performance measurement and management. Mainly in a supply chain context.
2	Sustainable development, management, artificial intelligence, innovation, data envelopment analysis, performance management systems, competition, economics, performance indicators, and operational efficiencies.	Researching sustainable development, planning, and operational efficiencies by innovation on artificial intelligence and data analysis as a result of competition.
3	Knowledge management, personnel, organizational level, competitive advantage, risk management, decision theory, customer satisfaction, operations research.	Customer centric organizational research putting peoples’ knowledge at the center for competitive advantage and exploring decision making theory.
4	Data reduction, standards, resource allocation, optimal resource allocation, performance evaluation, computer simulation, system dynamics, inventory control.	Diverse group mainly focusing on manufacturing with strategies of optimization, automation, and quality.
5	Supply chain, efficiency, continuous improvement, manufacture, performance information, and planning.	Supply chain centric with planning based on performance information for continuous improvement.

Figure A1. The full network graph with node size after degree and the 15 nodes with highest degree labeled.

Li, X., Wu, Q., & Holsapple, C. W. (2015). Best-value supply chains and firms’ competitive performance: Empirical studies of their linkage. International Journal of Operations and Production Management, 35(12), 1688–1709. doi:10.1108/IJOPM-01-2014-0014

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Hanson, J. D., Melnyk, S. A., & Calantone, R. A. (2011). Defining and measuring alignment in performance management. International Journal of Operations and Production Management, 31(10), 1089–1114. doi:10.1108/01443571111172444

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McAdam, R., Humphreys, P., Galbraith, B., & Miller, K. (2017). Developing management capability within a horizontal supply chain in performance measurement deployment and evolution: A dynamic capabilities and goal theory perspective. Production Planning & Control, 28(6–8), 610–628. Retrieved from https://www.tandfonline.com/doi/abs/10.1080/09537287.2017.1309706

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McAdam, R., Bititci, U., & Galbraith, B. (2017). Technology alignment and business strategy: A performance measurement and dynamic capability perspective. International Journal of Production Research, 55(23), 7168–7186. doi:10.1080/00207543.2017.1351633

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