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Key performance indicators (KPIs) play a pivotal role in evaluating the level of success of an organization in achieving its business objectives. The objective of the current research is to identify and prioritize effective KPIs in branding products and construction projects, which contribute to the success of construction companies in a competitive environment.

The present research is of an inferential, descriptive and survey nature. In this study, we identified the influential key performance indicators of construction companies in branding products and construction projects for success in a competitive environment through a literature review and expert opinions. The data were collected using a questionnaire, and a combination of the one-sample t-test method with a 95% confidence level and the fuzzy multiple attribute decision-making (FMADM) method was employed for analysis.

The results indicate that the most influential key performance indicators for construction companies in branding products and construction projects for success in a competitive environment are, in order of significance, the following indices: “Marketing and Advertising,” “Financial,” “Creativity,” “Technical and Operational” and “Social and Political.”

The present research examines the importance of branding construction products and projects for the success of construction companies by improving their business objectives and utilizing key performance indicators throughout the product lifecycle (production and construction). This study provides solutions on how construction companies can increase their competitive advantage through branding and achieve long-term success in the global construction industry.

Sustainable construction deficits are common in developing economies, and resolutions are constrained by the failure to prioritise the plethora of available indicators. This study aims to report on overlapping indicators for benchmarking sustainable construction for construction organisations.

Online survey data were collected from construction professionals, academics and senior managers in government bodies. Pearson chi-squared tests and overlapping analysis were used to determine significant indicators. Kruskal–Wallis tests were used to determine statistically significant differences among the dimensions.

Overlapping analysis determined indicators significant for economic, environmental and social performance. Environmental protection and reporting (pollution and emissions) were significant for all three performance dimensions. The most significant indicators are economic performance (adequate competence of key project staff), environmental performance (environmental protection and reporting – pollution and emissions) and social performance (adequate sustainability expenditure by construction organisations). Significant differences due to dimensions existed for adequate competence of key project staff, sustainable construction and eco-design, adequate governance and organisational excellence of construction projects and satisfactory workers’ morale.

Determining overlapping indicators enables prioritised implementation that ensures sustainable construction. Excluding construction workers was a significant limitation for a holistic interrogation.

To the best of the authors’ knowledge, this is the first study to determine overlapping indicators for sustainable construction performance in Zimbabwe.

Customer experience management (CXM), which aims to achieve and maintain customers' long-term loyalty, has attracted the attention of many organizations. Improving customer experience management in organizations requires that, first, their relevant capabilities be evaluated. The present study aimed to offer a set of key performance indicators for evaluating customer experience management in commercial banks.

The study, first, attempted to identify the components of evaluating customer experience management by reviewing the related literature and conducting interviews with experts. Then, the extracted components were transformed into assessable metrics using the goal question metric method, and the key performance indicators relevant to customer experience management in commercial banks were selected according to the experts' opinions and the Fuzzy Delphi method.

According to the findings of the study, 21 key performance indicators were identified for customer experience management in commercial banks, and customer satisfaction, the mean number of calls to resolve an issue in customer journey touchpoints, the NPS, and the ratio of the budget allocated to the CXM department to the budget of the marketing department were found as the most significant performance indicator according to banking experts.

The present study was among the first research projects intended to evaluate CXM and offer key performance indicators that could help the managers of commercial banks assess the maturity levels of their CXM.

This study examines how circular economy (CE) performance indicators are constructed in an urban context characterised by a multitude of conflicting interests and visions of urban development. It explores the process of constructing a shared consensus about the performance indicators in conditions of low contractibility, where intervention objectives and outcomes are not easily quantifiable because the object is ambiguous and cannot be fully specified in advance.

The construction of performance indicators at the urban level is examined through the lens of an action net. Using group interviews, observations and documentary analysis, this study investigates the case of a CE initiative in the city of Milan.

The study demonstrates that in cases of low contractibility, the development of CE solutions requires actions that span across organisational boundaries, organised in an action net. As the action net unfolds, it is closely knotted with the construction of performance indicators, indicating a co-constitutive relationship between the two processes.

This interdisciplinary study contributes to the public sector accounting literature by exploring the complexity of performance indicator construction at the urban level. It further recognises performance measurement in cities as a dynamic and flexible process, in which the interconnected actions and involvement of multiple actants shape the composition of the indicators.

This paper aims to present the development of a holistic campus facility management (CFM) performance assessment framework that incorporates a fuzzy logic approach and integrates a comprehensive set of key factors for successful management of campus facilities. The devised framework aims to cater to the needs of campus facilities management firms and departments for the purpose of gauging and assessing their performance across different management domains. Through this approach, facility management organizations can detect potential areas of enhancement and adopt preemptive steps to evade issues, foster progress and ensure success.

After a comprehensive analysis of the literature, conducting in-depth interviews with industry experts and employing the Delphi technique in two rounds, a total of 45 indicators critical to CFM success were identified and subsequently sorted into seven distinct groups. Through an online questionnaire, 402 subject-matter experts proficiently assessed the significance of the critical success indicators and their groups. A fuzzy logic framework was developed to evaluate and quantify a firm's compliance with the critical success indicators and groups of indicators. The framework was subsequently weighted using computations of the relative importance index (RII) based on the responses received from the questionnaire participants. The initial section of the framework involved a comprehensive analysis of the firm's performance vis-à-vis the indicators, while the latter part sought to evaluate the impact of the indicators groups on the overall firm's performance.

The utilization of fuzzy logic has uncovered the significant effects each effective CFM key indicator on indicators groups, as well as the distinct effects of each CFM indicators group on the overall performance of CFM. The results reveal that financial management, communications management, sustainability and environment management and workforce management are the most impactful indicators groups on the CFM performance. This suggests that it is imperative for management to allocate increased attention to these specific areas.

This study contributes to the advancement of current knowledge by revealing vital indicators of effective CFM and utilizing them to construct a thorough fuzzy logic framework that can assist in evaluating the effectiveness of CFM firms worldwide. This has the potential to provide crucial assistance to facility management organizations, facility managers and policymakers in their quest for informed decision-making.

This study aims to discover the key performance indicators (KPIs) of the agricultural cold supply chain (ACSC) and analyze their consequences on the performance of ACSC within the bounds of Indian topography.

The KPIs have been explored based on the literature review both in global and Indian context and domain expert's opinions. The interdependency characteristics and cause–effect relationship among the KPIs have been analyzed using a fuzzy decision-making trial and evaluation laboratory (f-DEMATEL) approach.

The findings extracted from the empirical assessment of the problem find strong compliance with the notions of theoretical model assessment. The results highlight that the cost of product waste and operating and performance costs are the two most important performance indicators of an Indian ACSC. Furthermore, governmental policies and regulations and the effectiveness of cold chain (CC) equipment also have a high degree of influencing characteristics on ACSC performance.

To connect the study with practicalities, the assessment of the KPIs is allied with real-time practices by clustering the beliefs of Indian professionals. Therefore, the decision-making behavior of the experts might be influenced by geographical constraints. However, the key findings provide advantages to the ACSC players, a bright hope for future food security and a significant profit for farmers.

The presented paper encompasses various aspects of the ACSC, including theoretical and empirical perspectives exercised to contemplate the system dynamics, which inculcates the essence of the associated practicalities. Thus, this study has various practical contributions relevant to managerial and societal perspectives.

This paper aims to propose an integrated use of balanced scorecard (BSC), data envelopment analysis (DEA) and game theory approach as an enhanced performance measurement technique to determine and rank the importance of manufacturing indicators of a steel company as a real case study.

An efficiency change ratio is defined to examine the characteristic function of each coalition which is super-additive. Then, the Shapley value index is used as the solution of the cooperative game to determine the importance of the BSC indicators of the company and rank order them.

The results reveal that “profitability rate” is the most important BSC indicator, whereas “customer satisfaction” is the least significant one. The ranking order of the importance of all BSC indicators makes it possible for the senior managers of the organization to realize the importance of each index separately and to improve the profitability and the number of customers by presenting programs according to the budget and time constraints.

The main contribution of this paper lies in the adoption of a game theory approach to performance measurement in the industrial sector that determines and ranks the importance of manufacturing indicators.

The study assessed the stakeholders prioritization of key performance indicators (KPIs) on public and private tertiary educational projects in Osun State, Nigeria intending to enhance their performance.

The study used a total enumeration survey to purposively select built environment professionals working in the Physical Planning and Development Unit (PPDU) and procurement units of 17 tertiary educational institutions (7public and 10 private) in Osun State Nigeria for data collection. A quantitative research approach was adopted for the study using a questionnaire. A total of 102 questionnaires were retrieved from the respondents and used for analysis. Analysis of data was done using frequency, percentile, mean score (MS), Cronbach's Alpha coefficient, t-test, and Analysis of variance (ANOVA).

The study found that in the overall opinion of the respondents the most prioritized KPIs for tertiary educational projects are for the project to meet specifications (MS = 4.17), the project must be on time (MS = 4.01), and efficient use of resources (MS = 3.96). The important KPIs for the public tertiary educational projects is that the project should meet specifications (MS = 4.08), deliver the projects on time (MS = 3.96), and be under cost (MS = 3.84). While, the most prioritized KPIs for private tertiary educational projects are for the project to meet specifications (MS = 4.25), efficient use of resources (MS = 4.14), on time, and doing the right thing (effectiveness) (MS = 4.06) each. More findings indicated that there is no significant difference in the manner built environment professionals prioritized KPIs. However, there is only a 7% significant difference in the manner professionals working in the public and private tertiary educational institutions in Nigeria ranked KPIs.

There is a significant difference in the ways and manner built environment professionals working with the public and private tertiary educational institutions in Nigeria view resource utilization on their projects. As such, working environment either as public or private has a significant impact on resource utilization for tertiary educational construction projects.

The study compared opinions of professionals working with public and private tertiary educational institutions on KPIs to enhance project performance.

The application of knowledge management (KM) in government agencies is one strategy to deal with government problems effectively and efficiently. This study aims to identify KM readiness critical success factors (CSFs), measure the level of readiness for KM implementation, identify improvement initiatives and develop KM readiness models for government agencies. This model plays a role in the implementation of KM successful.

The level of readiness is obtained by calculating the factor weights of the opinions of experts using the entropy method. The readiness value is calculated from the results of the questionnaire with average descriptive statistics. The method for analysis of improvement initiatives adopts the Asian Productivity Organization framework. The model was developed based on a systems approach and expert validation.

Reliability testing with a Cronbach’s alpha value for entropy is 0.861 and the questionnaire is 0.920. The result of measuring KM readiness in government agencies is 75.29% which is at level 3 (ready/needs improvement). The improvement in the level of readiness is divided into two parts: increasing the value of factors that are still less than ready (75%) and increasing the value of all factors to level 4 (84%). The model consists of three main sections: input (KMCSFs), process (KM readiness) and output (KM implementation).

The first suggestion is that the sample of employees used in this study is still in limited quantities, that is, 50% of the total population. The second limitation is determining KMCSFs. According to experts, combining this study with factor search and correlation computations would make it more complete. The expert’s advice aims to obtain factors that can be truly tested both subjectively and objectively. Finally, regarding literature selection for future research, it is recommended to use a systematic literature review such as the preferred reporting items for systematic reviews and meta-analyses and Kitchenham procedures.

The management must also prioritize KMCSF according to its level and make KMCSF a key performance indicator. For example, at the priority level, active leadership in KM is the leading performance indicator of a leader. Then at the second priority level, management can make a culture of sharing an indicator of employee performance through a gamification program. The last point that management must pay attention to in implementing all of these recommendations is to collaborate with relevant stakeholders, for example, those authorized to draft regulations and develop human resources.

This study proposes a novel comprehensive framework to measure and improve KM implementation readiness in government agencies. This study also proposes a KMCSF and novel KM readiness model with its improvement initiatives through this framework.

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.