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This study aims to investigate and classify the hospital logistics key performance indicators (KPIs) using the context of public hospitals in remote areas.

The public hospitals in northern Thailand were selected for the case study. The questionnaire was developed and used to collect data from hospital logistics experts. Then, the analytic hierarchy process (AHP) method was used to evaluate the hospital logistics KPIs in each dimension.

This research found that the procurement management dimension is ranked highest. Information and technology management is the last rank in the hospital logistics KPIs used for public hospitals in remote areas.

The public hospitals located in northern Thailand were selected for the case study. Fuzzy multi-criteria decision-making methods can be used to reduce the vagueness of the values.

The results from this study can be a guideline for hospitals to improve the efficiency of their logistics operations.

The decision-makers in the hospital can use these results to improve the hospital’s logistics performance in the future, which could help increase the service level and the safety of the patients.

The hospital logistics KPIs were revised, and the crucial KPIs were prioritized for improving the hospital logistics using the AHP method.

The successful implementation of hospital projects (HPs) tends to confront sundry challenges in the planning and construction (P&C) phases due to their complexity and particularity. Employing key performance indicators (KPIs) facilitates the monitoring of HPs to advance their successful delivery. This study aims to comprehensively investigate the KPIs for hospital planning and construction (HPC).

The KPIs for HPC were identified through a systematic review. Then a comprehensive assessment of these KPIs was performed utilizing a meta-analysis method. In this process, basic statistical analysis, subgroup analysis, sensitive analysis and publication bias analysis were performed.

Results indicate that all 27 KPIs identified from the literature are significant for executing HPs in P&C phases. Also, some unconventional performance indicators are crucial for implementing HPs, such as “Project monitoring effectiveness” and “Industry innovation and synergy,” as their high significance is reflected in this study. Despite the fact that the findings of meta-analysis are more trustworthy than those of individual studies, a high heterogeneity still exists in the findings. It highlights the inherent uncertainty in the construction industry. Hence, this study applied subgroup analysis to explore the underlying factors causing the high level of heterogeneity and used sensitive analysis to assess the robustness of the findings.

There is no consensus among the prior studies on KPIs for HPC specifically and their degree of significance. Additionally, few reviews in this field have focused on the reliability of the results. This study comprehensively assesses the KPIs for HPC and explores the variability and robustness of the results, which provides a multi-dimensional perspective for practitioners and the research community to investigate the performance of HPs during the P&C stages.

The purpose of this paper is to help better understand the translation process of the management control system (MCS) of privatised solid waste management (SWM) towards creating a stable network.

Drawing on the actor network theory (ANT), the case of a privatised SWM was studied. Data were collected from all entities involved in the privatisation process of SWM, which include Department A, Corporation X and the private sector concessionaire. Six documents were reviewed, 20 interviews were conducted and two observations were carried out.

The findings reveal that the control mechanism of SWM is complex, involving the interaction between human and non-human actors. Non-human actors include the key performance indicators (KPIs) and the concessionaire agreement (CA), which are the main control mechanisms towards creating a stable SWM network. Essentially, stability is achieved when the KPIs and CA can influence the activities of both intra- and inter-organisational relationships.

This paper provides a better understanding of the translation process of the MCS that adds to the stability of the network of a privatised SWM from the lens of the ANT.

This paper aims to investigate whether managers use impression management through the presentation of non-financial information in an integrated reporting setting.

The authors performed an experiment with experienced professional controllers and part-time students enrolled in the executive master’s degree in finance and control at universities in the Netherlands. In this experiment, we manipulated the financial performance to test if managers present non-financial information differently based on the firm’s financial performance.

This study found that impression management is not applied by including or excluding non-financial key performance indicators (KPIs) in the integrated report, but by using more prominent presentation forms for positive non-financial performance and non-prominent ones for negative non-financial performance. However, the use of impression management through the presentation form decreased when the firms’ financial performance was positive. In that instance, this study noted that managers statistically significantly more often decided to present poor non-financial performance in a prominent presentation format in comparison to managers who were not aware of the financial performance.

A limitation of this paper is that the authors focused on only two impression management strategies: opportunistic/under-reporting and the presentation form. This analysis shows that the use of impression management mainly seems to occur through the presentation format. Future research could investigate other impression management strategies in an integrated reporting setting.

The results of this study are of importance for users of integrated reports, because it will provide more insight into whether firms are truly transparent in their integrated reports. Furthermore, the theoretical implication of this study is relevant to regulatory authorities, because it sheds light on the different forms of impression management used in integrated reporting and the influence of positively or negatively performing KPIs on the decisions of preparers of integrated reports.

Therefore, in this study, the authors add to prior literature by investigating the concept of impression management in an integrated reporting setting. More specifically, the authors perform an experiment and focus on different forms of impression management (the presentation format and under-reporting) through non-financial KPIs in an integrated reporting setting and link it to firm financial performance.

The purpose of this study is to integrate the sustainability balanced scorecard (SBSC) framework with decision-making trial and evaluation laboratory (DEMATEL) for proposing a model and identifying the cause-and-effect relationships between the five perspectives of SBSC and then 23 performance indicators within the SBSC framework in a strategy map.

The DEMATEL approach is used to obtain a matrix including direct and indirect influences between the five perspectives of SBSC and among 23 key performance indicators (KPIs). DEMATEL data are gathered from experts to propose a model and establish reliable relationships between performance metrics. Using DEMATEL and the SBSC framework, a strategy map for the SBSC dimensions and KPIs was built to illustrate strategic cause-and-effect relationships among the various dimensions and performance indicators.

The outcomes indicated that internal process and financial perspectives play essential outputs. Sustainability is the most critical predictor (causal) in the model, then customer and learning and growth dimensions, indicating that sustainability, learning and growth and customer dimensions all positively affect other dimensions. Additionally, sustainability has bi-directional in its link to the customer and internal processes and bi-directional in its relationship to finance, learning and growth. Numerous additional linkages are observed among the five SBSC perspectives and KPIs.

The data collected is based on an “average” company in manufacturing sector; thus, companies need to customize this model to ensure that their strategies are clearly translated into KPIs.

The findings gave valuable information to management about manufacturing companies KPIs. They determined which KPIs are regarded as outcome (effect) variables and which KPIs are considered predictor (casual) variables. Additionally, the findings offer management with SBSC perspectives that should be traded as outcomes and those that should be traded as predictors. Additionally, the findings highlighted the critical KPIs and explained their interrelationships. This enables managers to focus on the significant financial besides non-financial indicators and comprehend the logical connection among them.

The results qualify executives and management to analyze and recognize a strategy map by understanding each objective's impacts, including direct and indirect, on all others. The typical analysis comprises determining the strategic objectives that are “cause” and the objectives considered as “effect”. As this study extends the BSC framework to have sustainability perspectives, the results of DEMATEL provide administrators with exceptional information to blend the conventional BSC perspectives with sustainability as added perspective.

The current study proposed an illustration model for strategy map development and also provide an interrelationship among SBSC perspectives.

This paper aims to present a simple and innovative fuzzy methodology-based lean performance measurement system (L-PMS) for an Indian automotive supply chain. The paper also enlightens the influence of coronavirus disease 2019 (COVID-19) on supply chains and the practical implications of the unprecedented disruptions on the performance measurement systems.

The L-PMS is divided into three phases. In the first phase, the key performance indicator (KPI) list, as deemed fit by the organization, is prepared using literature and suggestions from the case organization. The list contains 61 KPIs measuring 24 performance dimensions in seven functional areas of the supply chain. In the second phase, the KPI performance data (actual, best and worst) are collected using the enterprise resource planning (ERP) system. In the last phase, the leanness score of the case organization is calculated at four levels – KPI, dimension, functional area and overall organization.

The overall leanness score of the case organization is 60%. The case organization uses KPIs from all seven functional areas, but it needs to improve the number of KPIs in administration and supplier management functional areas. The case organization uses only quantitative KPIs. However, the performance dimensions at the middle level are adequate. The leanness level of the case organization in different areas is highly variable (ranges from 45% to 91%).

The major limitation of the study is that the case study is done at a single organization.

The managers at the different levels of the hierarchy can use the lean performance measurement score to leverage the better performing areas/dimensions/KPIs and improve poor performing areas/dimensions/KPIs. The lean performance measurement at functional area level can help leadership to give responsibility to different people for the improvement of leanness with respect to different dimensions/functional areas. The disruptive impact of COVID-19 should clearly be understood by the managers to make appropriate decisions based on the severity as measured at different levels.

According to the authors' best knowledge, this is the first lean performance measurement application at the four hierarchical levels (KPI, performance dimension, functional area and overall organization).

Being an efficient mechanism for the value of money, public–private partnership (PPP) is one of the most prominent approaches for infrastructure construction. Hence, many controversies about the performance effectiveness of these delivery systems have been debated. This research aims to develop a novel performance management perspective by revealing the causal effect of key performance indicators (KPIs) on PPP infrastructures.

The literature review was used in this study to extract the PPPs KPIs. Experts’ judgment and interviews, as well as questionnaires, were designed to obtain data. Copula Bayesian network (CBN) has been selected to achieve the research purpose. CBN is one of the most potent tools in statistics for analyzing the causal relationship of different elements and considering their quantitive impact on each other. By utilizing this technique and using Python as one of the best programming languages, this research used machine learning methods, SHAP and XGBoost, to optimize the network.

The sensitivity analysis of the KPIs verified the causation importance in PPPs performance management. This study determined the causal structure of KPIs in PPP projects, assessed each indicator’s priority to performance, and found 7 of them as a critical cluster to optimize the network. These KPIs include innovation for financing, feasibility study, macro-environment impact, appropriate financing option, risk identification, allocation, sharing, and transfer, finance infrastructure, and compliance with the legal and regulatory framework.

Identifying the most scenic indicators helps the private sector to allocate the limited resources more rationally and concentrate on the most influential parts of the project. It also provides the KPIs’ critical cluster that should be controlled and monitored closely by PPP project managers. Additionally, the public sector can evaluate the performance of the private sector more accurately. Finally, this research provides a comprehensive causal insight into the PPPs’ performance management that can be used to develop management systems in future research.

For the first time, this research proposes a model to determine the causal structure of KPIs in PPPs and indicate the importance of this insight. The developed innovative model identifies the KPIs’ behavior and takes a non-linear approach based on CBN and machine learning methods while providing valuable information for construction and performance managers to allocate resources more efficiently.

This study aims to audit the key performance indicators (KPIs) in Ghanaian university libraries. It aimed at finding out the KPIs used by Ghanaian university libraries and how effective they have been in correcting lapses in staff performance.

Employing a quantitative research approach, the views of 218 librarians were elicited from nine universities in Ghana. Due to the manageable size of staff population in the libraries, the census sampling technique was adopted.

Results indicated even though staff members were unaware of KPIs in their libraries, most of the respondents understood the concept and perceived is to be measuring the success and tracking performance in libraries. It was also revealed that most of the libraries did not have clear and measurable KPIs. Close to 80% of the libraries under study did not have clearly stated KPIs of which members of staff were aware. The study revealed that KPIs may differ from one library to the other, depending on the mission and vision statement of the library. For increased staff performance in Ghanaian university libraries the study recommends management to develop clear and measurable outcome-based metrics that will lead to high performance. This will not only address the needs of clients but also improve the libraries' efficiency in terms of information provision. Management should also have clear and measurable KPIs and make them available to library staff.

For increased staff performance in Ghanaian university libraries the study recommends management to develop clear and measurable outcome-based metrics that will lead to high performance. This will not only address the needs of clients but also improve the libraries' efficiency in terms of information provision. Management should also have clear and measurable KPIs and make them available to library staff.

The study provides information on KPIs in Ghanaian university libraries and how to effectively deal with the challenges associated with its usage.

This study aims to explore the potential dynamics between performance measurement at the organisational level and emerging urban development projects at the macro-institutional field level of sustainability governance and accountability.

Using a theoretical triangulation between three theories, namely contingency theory, institutional theory and social cognitive theory, this study investigates not only the macro-micro dynamics, but also the (recursive) micro-macro dynamics between performance measurement and urban development. Using an Egyptian public sector urban development organisation and its sustainable energy project as an empirical example, interviews, documents and observations were collected.

The dynamics emerged between field urban development projects and the (unintended) organisational implementation of the performance measurement system, the sustainability key performance indicators (KPIs) reporting system. Contributing to previous literature, these dynamics have been institutionalised through (three) interrelated levels: the (macro-field) urban development contingencies and pressures for sustainability KPIs reporting, the (organisational) institutionalisation of the urban development performance measurement system and then the (micro-organisational) cognitive role of sustainability KPIs reports in (re)making political urban development decisions.

This study faced some limitations that paved the way for future research axes. For political and security reasons, difficulties were encountered in conducting interviews with government actors in the sustainable energy project under study. Also, due to the practical separation of the environmental sustainability system from the sustainability KPIs reporting system in this case study, environmental sustainability is outside the scope.

Sustainability reports may influence public sector decision-making processes in a specific urban development context. These KPIs reports may also increase public sector management opportunities for urban auditing, transparency, accountability and sustainability governance. These KPIs may also guide public sector management to lower prices in poor villages to increase smart energy consumption and improve community health.

Sustainability reports may increase decision-makers' understanding of consumer behaviours and societal changes. This may help in making appropriate political decisions to improve their welfare and regular smart energy consumption. Not only urban citizens, but this social advantage may also extend to urban development employees through employees' promotion, training and access to government-funded academic and professional scholarships.

This study is an attempt to develop current public sector performance measurement analyses in the emerging urban development field using a triadic analytical approach. This study also fed the literature with an extended case study that clarified the (multi-level) and (two-way) dynamics between performance measurement and urban development.

The purpose of this paper is to identify and prioritize key performance indicators (KPIs) that can be used for stage-based performance assessment of build-operate-transfer (BOT) projects.

This research was conducted through focus group discussions and face-to-face questionnaires. Firstly, stage-level KPIs for BOT projects were identified by conducting a literature survey. The list of KPIs that can be used for measuring performance at different stages of a BOT project was finalized by conducting focus group discussions with 12 participants. The data related to the importance of identified KPIs were collected via a face-to-face questionnaire in which 30 high-level managers participated. Based on these data, KPIs were prioritized considering eight different stages of a BOT project by using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).

The research findings reveal that 63 stage-level KPIs can be used for measuring the performance of BOT projects at eight different stages, which are “feasibility study and preliminary plan,” “announcement and submission of application,” “evaluation and selection,” “negotiation and signing of concession agreement,” “design,” “construction,” “operation” and “transfer.” The most important KPIs were determined as “comprehensiveness of project technical feasibility,” “detailed tendering procedure,” “effectiveness of concessionaires' technical knowledge/capability evaluation,” “good relationships between government and concessionaire,” “technology transfer,” “effectiveness of quality control,” “effectiveness of facility management” and “effectiveness of hand-back management” for each stage. The findings can be used by companies to evaluate performance at each stage of a BOT project and, if necessary, take the necessary actions for performance improvement at the stage level.

The main limitation is the size of the sample, which represents the perspectives of 30 Turkish high-level managers on KPIs in BOT projects. Besides, the selected method, namely, TOPSIS, does not provide quality measures related to the outputs; therefore, it is difficult to see the inconsistencies among the experts.

The study findings will help in devising appropriate performance evaluation practices for BOT projects to overcome the shortfalls of the existing practices and systems proposed in the literature and help in achieving the superior performance while developing infrastructure through the BOT route.

This paper proposes a process-based approach for measuring the performance of a BOT project considering eight different stages. It fills a research gap in the public–private partnership literature by focusing on stages rather than phases. The results can be used by practitioners to establish stage-level performance management systems for BOT projects.