Performance Measurement System Research Articles

Insights from an intervention of a performance measurement system covering all change steps: the paradox of informed change leadership passivity

This intervention-based action research study describes the design, implementation, use and evaluation of an artefact, a performance measurement system (PMS), for change initiatives. The longitudinal (6-year) research study covers all three steps of planned change—change readiness, implementation, and institutionalisation. The PMS worked well, delivering valid and reliable measurements and information that should require leadership action. However, in the intervention, we observed an unexpected outcome: the PMS information was not used. The PMS repeatedly highlighted change management problems related to problem analysis, goals, management support, organisation, and resources, yet few actions were taken to correct detected problems. We thereby identified a paradox of informed change leadership passivity, and we used process theory and paradox theory to reflect on and explain the tensions behind the paradox. We suggest propositions on how responsibility, accountability, and power of different actors to handle complexities of roles, tasks and procedures are related to the use of the PMS. Finally, we contribute to the discussion on tensions concerning leadership versus management and their impact on organisational change, and suggest future research questions concerning improved use of PMS for change initiatives.

Integrating sustainability into PMM systems of small businesses: some future research directions

Purpose This work aims to provide, from the perspective of small businesses, a state-of-the-art of management and accounting literature concerning the development of performance measurement and management (PMM) systems addressing sustainability and traditional measures of business performance. Design/methodology/approach A systematic review of the literature was developed by using Scopus and ISI Web of Science as sources of data. After a careful screening of the results, 61 articles have been selected and analysed in depth. Findings The article highlights the key theoretical frameworks adopted by articles focussing on PMM and sustainability in SMEs, as well as the methods used, and the key re-sults obtained. Moreover, the article provides several insights for future studies on this emerging topic. Practical implications This contribution provides important elements to design PMM systems aimed at ad-dressing sustainability in SMEs. As such, the results obtained may supports SMEs’ managers in implementing such systems as well as in putting in place reporting ac-tivities Originality/value The topic of measuring and managing sustainability performance in SMEs has re-mained largely underexplored both in theory and in practice. This contribution offers a comprehensive exploration of this theme, while also outlining future research direc-tions for scholars interested in analyzing this research area from the perspective of small businesses.

Designing an Integrated BSC and IPMS Model Performance Optimization

This study aims to design a performance measurement model by integrating two performance measurement methods, namely the Balanced Scorecard (BSC) and Integrated Performance Measurement Systems (IPMS), to optimize the company's performance. This approach is expected to provide a comprehensive view of the company's performance by combining financial and non-financial indicators and ensuring strategic alignment. The research approach used is descriptive-analytical (literture review), which aims to provide an overview of the performance measurement model design by integrating the Balanced Scorecard (BSC) and Integrated Performance Measurement Systems (IPMS). The study will identify how the integration of these two systems can improve productivity and operational effectiveness. The expected outcome is sustainable performance improvement and productivity enhancement through the implementation of a holistic and integrated performance measurement framework. The novelty of this research lies in the absence of a performance measurement model that combines both methods to measure company performance. The research results in a performance measurement model design that can be implemented to optimize performance in an industry.

Development of a Decision Support System for Performance Measurement of Social Movements

Development of a Decision Support System for Performance Measurement of Social Movements

Determining Key Performance Indicators at PT Cahaya Utama Branch Sidoarjo using Integrated Performance Measurement System (IPMS) and Balanced Scorecard Methods

Determining Key Performance Indicators at PT Cahaya Utama Branch Sidoarjo using Integrated Performance Measurement System (IPMS) and Balanced Scorecard Methods

The Effect of Marketing Capability and Brand Reputation on Brand Loyalty of Tomoro Coffee through Competitive Advantage as a Meditation Variable

The purpose of this research is to analyze the influence of marketing capabilities and brand reputation on competitive advantage and brand loyalty among Tomoro Coffee customers in Surabaya. This study employs a quantitative research design using a cross-sectional method. The sample used in this research consisted of 100 respondents who are Tomoro Coffee customers residing in Surabaya. Sampling was conducted randomly through an online questionnaire using a Likert scale. Data analysis was carried out using the Structural Equation Modeling ( SEM ) approach with the Partial Least Squares ( PLS ) methodology. The results of this research indicate that marketing capability and brand reputation have a positive and significant effect on competitive advantage. Competitive advantage, in turn, has a positive and significant effect on brand loyalty. Marketing capability has a negative and insignificant effect on brand loyalty, whereas brand reputation exerts a positive and significant effect on brand loyalty. Furthermore, brand reputation has a significant influence on brand loyalty through competitive advantage as a mediating variable, while marketing capability demonstrates an insignificant effect on brand loyalty through competitive advantage as a mediating variable. The implications of this research suggest that Starbucks and other business actors can enhance their performance measurement systems related to marketing capability, brand reputation, competitive advantage, and brand loyalty. These improvements are essential for maintaining and strengthening their competitive position in the market. Keywords : Marketing Capability, Brand Reputation, Competitive Advantage, Brand Loyalty, Tomoro Coffee

Validasi Instrumen Evaluasi Kinerja di PT DUNKIN DONUT dengan Menggunakan Metode Balance ScoreCard

Goals Performance measurement is a process used to assess the extent to which an individual or organization has achieved the goals that have been set. Existing research explains the relationship between price, promotion, satisfaction, and loyalty, but many aim to explore one aspect without considering the dynamics of the interaction between price and promotion. In some contexts, lower prices are not always matched by high levels of satisfaction, indicating the need for further research. The Balanced Scorecard method can also be used to measure company performance. PT Dunkin Donat is a private company operating in the well-known food and beverage sector. To be able to have an advantage in rapid business competition, PT Dunkin Donat Unggul needs to have an appropriate performance measurement system framework. The following are the research results: 1). Service: The service provided by Dunkin Donuts is considered quite good for consumer needs, 2). Facilities: the facilities provided to consumers are considered quite good in terms of cleanliness and comfort, 3). Menu: the menu served by Dunkin Donuts is quite good because there are various types of menus that suit consumer tastes, dan 4). Appearance: the appearance of Dunkin Donuts employees is quite good because they look attractive so that consumers feel comfortable.

How does a simplified performance measurement system affect decision making within SMEs

How does a simplified performance measurement system affect decision making within SMEs

Unveiling the Determinants of Effective IT Governance: A Conceptual Framework for India's Public Listed Companies

Effective information technology governance (ITG) is critical for ensuring organizational success, particularly in an era where technological advancements shape business operations. For public listed companies in India, ITG effectiveness hinges on specific determinants such as IT strategy, IT risk management, performance measurement, resource allocation, and government support. These elements collectively enable organizations to mitigate financial losses, safeguard sensitive data, and align IT investments with business objectives. This study emphasizes the importance of a well-defined IT strategy to align technology initiatives with organizational goals, robust IT risk management to anticipate and mitigate threats, and performance measurement systems to evaluate the impact of IT on business outcomes. Additionally, efficient resource allocation ensures the optimal utilization of technological and human capital, while proactive government support enhances regulatory compliance and fosters a conducive environment for ITG. Despite the recognized importance of ITG, inconsistencies in its implementation are often attributed to limited awareness among key decision-makers and misaligned policies. By presenting a conceptual framework based on these determinants, this paper addresses a significant research gap and provides actionable insights for optimizing ITG practices. Through this framework, public listed companies can enhance collaboration between IT and business teams, avoid costly inefficiencies, and build resilience in an increasingly competitive and technology-driven environment.

Use of the performance measurement system (PMS) as a motivation, satisfaction and engagement tool

This research aims at understanding how the performance measurement system (PMS) is reflected in work engagement, motivation and satisfaction. Data were collected from 11 surveys completed by coordinators and managers from a petroleum refinery located in the southern region of Rio Grande do Sul. Henri (2006) and Simons (1995) approaches on the performance measurement system were adopted together with employee behavioral indicators (such as motivation, satisfaction and engagement) as elements to conduct surveys which were subsequently under content analysis (Bardin, 2016). The results evidenced that PMS is being applied at the company through dialogue, communication, safety and training. The refinery fosters work engagement, motivation and satisfaction, making employees feel proud, content and happy to be part of the organization. This encourages them to have a better performance and carry out their activities enthusiastically and with a clear focus. The findings show that PMS is favorably applied in a diagnostic and interactive manner in the organization under study. The relevance of this research is evident since organizations continually face a rising number of internal and external challenges including the need to motivate employees to increase productivity and reinforce work engagement.

Towards an Integrated Performance Management and Measurement System for healthcare organisations: a case study in Montreal

This study proposes an approach for developing or improving performance management and measurement systems (PMMSs) for healthcare organisations. First, data is collected to analyse and understand the current organisation’s performance management system. Second, the SWOT (Strengths, Weaknesses, Opportunities, Threats) method is used to identify the main aspects of the performance management system to be improved. Third, based on the scientific literature and SWOT analysis, BSC principles are integrated to this performance management system to better align the organisation’s performance objectives and indicators with its strategy. Finally, we develop a performance indicator structure and select indicators to be used as well as how these indicators could be integrated and shared with higher hierarchical levels in the organisation by using AHP (Analytic Hierarchy Process). Our approach is applied to the CIUSSS du Centre-Sud-de-l’île-de-Montreal (CCSMTL), a large healthcare network, in the province of Québec, Canada.

The quest for efficiency in higher education in England: lessons learned for developed economies

AbstractOver recent decades, universities in England have transitioned from providing higher education (HE) for the elite to HE for the masses. Funding mechanisms have changed, cost‐sharing has shifted from public to private sources, and efficiency and productivity have been emphasized. Three excellence frameworks relating to research, teaching, and knowledge exchange have been introduced to assess performance. In this paper, we explore the systems of performance measurement and funding implemented in English HE and critically appraise these against the recommendations from the relevant literature. We conclude that these frameworks, by separately assessing performance in the three missions, inadequately account for synergies between activities, thereby ignoring the civic nature of universities and possibilities for economies of scale and scope. We conclude by highlighting some emerging areas for future research. While the focus of the paper is English HE, the themes and findings are relevant to all HE sectors around the world.

Performance management systems for sustainability in SMEs: An interventionist approach

To address global sustainability, engagement from every social sector is necessary. In this context, businesses can play a pivotal role. Therefore, it is urgent to establish proper management tools in order to support or-ganizations' top management in addressing these goals. While larger firms are making progress in measuring, managing and reporting sustainability performance, small and medium enterprises (SMEs) are lagging behind for various reasons – such as the lack of regulatory frameworks, standards, managerial competence and more. In OECD countries, SMEs account for 40% of private sector GDP. As such, their relevance and role in pursuing sustainability cannot be overlooked. This research aims to advance understanding of the development and implemen-tation of performance measurement and management (PMM) systems taking into account the sustainability dimensions of performance in SMEs. This is key to al-lowing businesses and their management to measure and monitor their impact at the economic, social and environmental levels. In order to do this, the research is based on action research and the incorporation of an interventionist approach. In particular, the authors have developed a sus-tainability PMM for a medium citrus company operating in the B-to-B market and based in Southern Italy.

Sistema de medição de desempenho habilitante: efeito na motivação, nas atitudes gerenciais e no desempenho gerencial

This study analyzes the effect of the enabling performance measurement system (PMS) on management motivation and attitudes and their impact on the managerial performance of middle managers in the largest and best Brazilian companies in 2020. Using structural equation modeling, results revealed that enabling PMS has a positive effect on managerial attitudes and motivation. Furthermore, managerial attitudes directly influence managerial performance, which in turn act as mediators between the enabling PMS and performance. These findings have practical implications by providing insights that lead to improvements in middle management and allowing organizations to evaluate their PMS practices and develop training plans to improve the performance.

Collision causal discovery and real-time prediction of freeway tunnels: A novel dual-task approach

Although tunnels are critical traffic nodes in freeway networks, academic research addressing their real-time traffic safety is noticeably lacking. This study proposes a novel dual-task approach to analyze causal precursors and predict real-time collision risks in freeway tunnels. Unlike traditional models, which often trade off between predictive accuracy and causal depth, the proposed approach achieves both high causal interpretability and predictive performance. The approach utilizes a structural agnostic model (SAM) to discover causal precursors of freeway tunnel collisions using observational data. The collision causal graph data is then constructed based on the causal relationships identified by SAM. Additionally, the Causal Directed Graph Convolutional Networks (CDGCN) model is developed to capture causal relationships in the graph for real-time collision prediction. Utilizing freeway tunnel collision analysis data collected from the Caltrans Performance Measurement System, the approach performs dual tasks: identifying causal precursors of collisions and predicting future collisions in real time. The SAM results reveal five critical causal precursors influencing the likelihood of collisions. Comparative analyses with existing interpretable machine learning models show similarities between the causal precursors of tunnel collision risk revealed by SAM and the important correlation precursors identified by the comparative models. However, correlation is not the same as causation. When tested against current state-of-the-art real-time collision predictive models, the proposed CDGCN model demonstrates superior accuracy, especially on datasets containing causally relevant precursors, highlighting the potential of this approach for feature selection and risk prediction. This advancement not only provides a practical framework for mitigating collision risks in freeway tunnels but also makes a significant contribution to traffic safety research.

Which Strategic Control Suits Wine Family Companies to Improve Control? A Proposal Through the Balanced Scorecard in a Tuscany Wine Company of Michele Satta

ABSTRACTIn the last few years, growth and increased market and organizational complexity, including the effects of the pandemic era, require family firm members to develop managerial strategies to improve their businesses. This study pays attention to the study of strategic performance measurement systems, as important tools that, if well applied, positively influence business management, being directly linked to critical success factors. First, particular attention is on The Tuscany Region, in the area of Bolgheri. Second, to carry out the empirical study of this research, the first implementation of the Balanced Scorecard (BSC) will be realized with the collaboration of one company in the same Region. This article sheds useful insights for practitioners on the effective implementation of accounting and strategic innovations and it encourages wine companies to seriously weigh investing in developing strategic performance management systems.

Traffic Flow Prediction Using Novel Spatial-Temporal Multi-Head Attention Graph Convolution Networks

For urban development, accurate traffic flow prediction is crucial. Traffic flow prediction data can be used for optimizing public transportation systems, reducing congestion, planning road networks, and improving overall city infrastructure management. Despite numerous spatiotemporal methods used to forecast traffic flow, information aggregation at each site neither produce optimal results, because of the use non-Euclidean distance data. For more accurate results of traffic flow prediction, we propose a spatial-temporal multi-head attention graph convolution network (STMAGCN). It extracts temporal features using temporal convolutional layers and enriches nodes with spatial attention and multi-head attention mechanisms. By combining them, we can extract space characteristics more effectively. We also introduce a novel graph structure construction method that employs graph-based transformations to convert non-connected data points into a comprehensive graph structure, facilitating the effective application of our STMAGCN. This approach improves the predictive efficiency and accuracy of our model by ensuring seamless integration of disparate data sources. Experimental results indicate that the preferential extraction of spatiotemporal data significantly enhances traffic flow prediction accuracy. Compared with the latest models, our performance on the California Department of Transportation Performance Measurement System (PeMS) PeMS04 and PeMS08 datasets shows a slight improvement, with an average increase of 16.8%. Additionally, the average improvement in time is approximately 445.95%.

Spatio-temporal attention based collaborative local–global learning for traffic flow prediction

Traffic flow prediction is crucial for intelligent transportation systems (ITS), providing valuable insights for traffic control, route planning, and operation management. Existing work often separately models the spatial and temporal dependencies and primarily relies on predefined graphs to represent spatio-temporal dependencies, neglecting the traffic dynamics caused by unexpected events and the global relationships among road segments. Unlike previous models that primarily focus on local feature extraction, we propose a novel collaborative local–global learning model (LOGO) that employs spatio-temporal attention (STA) and graph convolutional networks (GCN). Specifically, LOGO simultaneously extracts hidden traffic features from both local and global perspectives. In local feature extraction, a novel STA is devised to directly attend to spatio-temporal coupling interdependencies instead of separately modeling temporal and spatial dependencies, and to capture in-depth spatio-temporal traffic context with an adaptive graph focusing on the dynamics in traffic flow. In global feature extraction, a global correlation matrix is constructed and GCNs are utilized to propagate messages on the obtained matrix to achieve interactions between both adjacent and similar road segments. Finally, the obtained local and global features are concatenated and fed into a gated aggregation to forecast future traffic flow. Extensive experiments on four real-world traffic datasets sourced from the Caltrans Performance Measurement System (PEMS03, PEMS04, PEMS07, and PEMS08) demonstrate the effectiveness of our proposed model. LOGO achieves the best performance over 18 state-of-the-art baselines and the best prediction performance with the highest improvement of 6.06% on the PEMS07 dataset. Additionally, two real-world case studies further substantiate the robustness and interpretability of LOGO.

Measuring Supply Chain Performance Using the SCOR Model: A Case Study of CV. XYZ

This research discusses the design of a performance measurement system for supply chain management using the Supply Chain Operations Reference (SCOR) model developed by the Supply Chain Council. The SCOR model focuses on five main activities within a company's supply chain, namely plan, source, make, deliver, and return. All activities are linked with performance attributes such as reliability, responsiveness, flexibility, cost, and assets. The implementation of this model is applied to CV. XYZ, a company that operates in the production of plain and printed T-shirts, which is located in East Java. The research was conducted from January 2024 to September 2024. The results of the study identified that there are 35 performance indicators representing supply chain activities, with the following breakdown: 9 indicators for the plan activity, 7 indicators for the source activity, 6 indicators for the make activity, 7 indicators for the deliver activity, and 6 indicators for the return activity. The Analytical Hierarchy Process (AHP) method was used to weight each activity in the SCOR model. Based on the results, the highest priority was the source activity (0.252), followed by deliver (0.222), plan (0.221), make (0.209), and return (0.095). From the scoring system, it was found that 23 indicators have a green score, 8 indicators have a yellow score, and 4 indicators have a red score. The limitation of this research is that one SCOR activity, "enable," was not analyzed. Therefore, it is recommended that future research analyze all SCOR activities.

Performance measurement and management in complex environments: a system of systems approach for the public sector

Issues related to rapidly changing digital environments and turbulent or complex settings, such as the public sector, often hinder successful implementations of Performance Measurement and Management (PMM) systems. Despite the availability of PMM methods, the challenge of implementing successful systems in turbulent settings persists. This article introduces a novel PMM framework employing a System of Systems (SoS) approach, integrating Data Envelopment Analysis and Machine Learning to guide organisational changes by enhancing the efficiency of Decision-Making Units (DMU). Validated by a case study within the Brazilian Navy, the framework demonstrates a significant capacity to interpret the impact of DMU characteristics on operational efficiency and draw actionable insights. Our findings suggest that leveraging SoS principles emphasises adaptability and ongoing improvement through a data-driven process, suggesting the framework’s potential to navigate through complexity by enabling more effective management practices and decision-making. Future research directions include longitudinal studies and the incorporation of technologies to support managerial decision-making.