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The existing concept in the building rating scheme especially in developing countries was more focused on the environment, economic, social and culture. The new approach of the classroom condition index (CCI) assessment scheme has its uniqueness in environmental and social aspects because of high building performance in secondary school buildings. The requirements set by the Ministry of Education Malaysia include providing a conducive learning environment, especially for students who are considered as the main users of classrooms in school buildings. Currently, the school administration needs to manually record the condition of the classroom to increase its comfort level. The lack of a structured scheme for classroom assessment makes it difficult for school administration to focus on the overall classroom condition (physical environmental aspect) in the school building. The purpose of this study is to develop a framework for classroom conditions by proposing a CCI assessment scheme for a secondary school building in Malaysia.

Mixed methods were used to carry out the study. The first stage of this study concentrates on developing a system for CCI that relates to physical elements in the classroom. This is done by reviewing the literature on the classroom physical performance, as well as a comparison between several building rating systems locally and abroad. The structure of the proposed CCI scheme is grouped into four main themes, namely, space management quality (SMQ), building condition (BC), indoor environmental quality (IEQ) and teaching and learning quality (TLQ). In addition, there are 12 categories and 23 indicators listed under this theme. The second stage focuses on formulating assessment categories with their relevant performance indicators. This phase undergoes a validation process by conducting a survey (questionnaire) toward the classroom’s main users, which are students and teachers. This is to ensure the accuracy of classroom conditions in the school building. A semi-structured interview was also conducted among building experts. They are building surveyors, building engineers, building designers and building performance experts to support the main findings in the second stage. Relative importance (RI) index approach has been applied to show the indicators weighting and ranking are used as data collections method by using Statistical Package of Social Science software to examine the RI of each category and indicator, respectively.

The findings show that prominent RI and balanced weights are formed from these four main themes. They are SMQ (19.9%), BC (26.6%), IEQ (33.2%) and TLQ (20.3%). The outcome of this study will contribute to a detailed assessment scheme for CCI at the secondary school building. The contribution of the CCI Assessment Scheme is more comprehensive and holistic than the conventional assessment process for BCs. It focuses specifically on classroom space as it is the most important area to achieve a high level of comfort comparing to other spaces in the school building. This holistic approach encompasses all types of classrooms. The concept of one tool fits all is seen as no longer a relevant adaptation in this context. This proposed tool is to be used only for the classroom (as the name CCI implies) and it cannot be used for the other types of spaces, for instance, teacher room, library, meeting room, toilet, canteen and, etc. This is because different spaces represent different physical indicators to be classified. This, in turn, contributes to a conducive learning environment for students in the school.

This paper provides the current information, knowledge and findings related to the classroom physical indicators in developing the assessment scheme for the classroom environment. It will assist both technical and non-technical experts to clarify the current condition of classroom physical performance that ideally may affect the students’ learning environment. The novelty of CCI development is not only on the adopted method but it also includes the ideas on next generation model of rating system that ideally need specific indicators and weighting to be generated into an intelligent computerized system.

This study examines how asking employees to self-assess their performance during the compensation setting process, when they are unaware of their marginal contribution to firm profit, affects employer welfare. Previous research suggests that giving employees a voice in the compensation setting process can positively affect employee performance and firm profit (Jenkins & Lawler, 1981; Roberts, 2003). However, the study proposes that asking employees to assess their own performance as part of the compensation setting process can have unintended consequences that ultimately lead to higher employee compensation demands. This is because asking employees to assess their performance increases their overconfidence in their own performance and their compensation demands. As a result, employers may face the dilemma of whether to meet these higher compensation demands or risk economic losses due to employee retaliation if their demands are not met. Through experimental evidence comparing a control condition without self-assessments and three self-assessment reporting conditions, the study provides evidence that supports the notion that eliciting employee self-assessments as part of the compensation process reduces employer welfare. Data on employee perceptions of performance further support the notion that asking employees to evaluate their performance leads to an inflated perception of their performance. These findings provide a theory-based explanation of why, in practice, many companies disentangle employee performance assessments from the compensation setting process and that companies are well advised in doing so.

A new senior curriculum and assessment policy in Queensland, Australia, is changing the conditions for teaching and learning. The purpose of this study was to consider the personal, structural and cultural conditions that mediated the agency of Senior English teachers as they negotiated these changes. Agency is conceptualised as opportunities for choice in action arising from pedagogic negotiations with students within contexts where teachers’ decision-making is circumscribed by other pressures.

An action inquiry project was conducted with English teachers and students in two secondary schools as they began to adjust their practices in readiness for changes to Queensland senior assessment. Four English teachers (two per school) designed a 10-week unit of work in Senior English with the aim of enhancing students’ critical and creative agency. Five action/reflection cycles occurred over six months with interviews conducted at each stage to trace how teachers were making decisions to prioritise student agency.

Participating teachers drew on a variety of structural, personal and cultural resources, including previous experiences, time to develop shared understandings and the responsiveness of students that mediated their teacher agency. Teachers’ ability to exert agentic influence beyond their own classroom was affected by the perceived flexibility of established resources and the availability of social support to share student success.

These findings indicate that a range of conditions affected the development of teacher agency when they sought to design assessment to prioritise student agency. The variety of enabling conditions that need to be considered when supporting teacher and student agency is an important contribution to theories of agency in schools, and studies of teacher policy enactment in systems moving away from localised control to more remote and centralised quality assurance processes.

This paper aims to provide insight into the use of a standard for condition assessment.

The paper is based on a literature review, an analysis of the development, content and practical use of the Dutch Standard for Condition Assessment of Buildings, and the findings of several research projects about condition assessment and maintenance planning by Dutch housing associations.

By using the standard for condition assessment, building inspectors can provide property managers with objective data about the condition status of building components. Aggregated condition data could be used for setting condition targets for built assets and for benchmarking. It is anticipated that as a result of the standardisation, condition surveys will become more reliable and as a consequence more popular among large‐scale property owners.

The standard has been introduced recently. At present there is little experience of the use of (aggregated) condition data for maintenance planning and benchmarking built assets.

The standard is a tool to assess the technical status of the properties to underpin the long‐term maintenance expectations. Condition assessment is not meant for preparing the annual maintenance budget and planning of the work. Supplementary information is needed in the phase of preparing for the execution of remedial work.

This paper provides practical tools for condition assessment and maintenance planning.

By adopting a condition‐dependent approach to maintenance, facility managers can exercise control over the desired maintenance performance levels and costs. The practice of condition assessment by building inspectors yielded variable results due to subjective perceptions of inspectors. Nowadays well‐trained building inspectors are able to manage condition surveys and provide property managers with objective, reliable information about performance loss and defects in building components. The implementation of various performance levels in planned maintenance requires not only the standardisation of the condition assessment method, but also the related planning methodology. This paper describes the findings from research in the Netherlands which examined the methodology of condition assessment of building components using a six‐point condition scale. Different categories of performance loss in maintenance are distinguished and linked to different kinds of maintenance activities.

Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.

Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.

The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.

This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.

This paper aims to review the elements of facilities condition index (FCI) as one of the most widely used metrics for describing the physical condition of facilities and as a measure of financial indicator related to maintenance activity. This research will benefit future studies that focus on implementation of FCI and encourage the best practice when assessing the physical condition to evaluate the performance of facilities as well as to plan for maintenance action to be taken and financial implication involved based on the findings from FCI.

A total of 33 studies from 2012 to 2022 were identified and extracted from four academic databased, named Scopus, Google Scholar, Web of Science and Mendeley. These published studies were selected because it matches with the inclusion requirements for research question, “What are the elements of facilities condition index discussed in the literature from 2012 to 2022?”. To answer the research question, the studies in ATLAS.ti were grouped into five major themes based on the codes and categories found.

This paper presents the findings of a thematic analysis of the current literature discussed about FCI. A total of 33 studies from 2012 to 2022 were identified and extracted from four academic databased, named Scopus, Google Scholar, Web of Science and Mendeley. A themed review was conducted, and five themes were identified as elements of FCI, which are named as follows: “Condition Assessment”, “Deferred Maintenance”, “Facilities Performance”, “Financial and Fund Allocation” and “Decision Making”.

This paper fulfils the fundamental elements on current FCI practices as well as intended to highlight existing practices that are essential to evaluate facilities performance and planning for maintenance strategies.

The purpose of this paper is to investigate the vehicle-based sensor effect and pavement temperature on road condition assessment, as well as to compute a threshold value for the classification of pavement conditions.

Four sensors were placed on the vehicle’s control arms and one inside the vehicle to collect vibration acceleration data for analysis. The Analysis of Variance (ANOVA) tests were performed to diagnose the effect of the vehicle-based sensors’ placement in the field. To classify road conditions and identify pavement distress (point of interest), the probability distribution was applied based on the magnitude values of vibration data.

Results from ANOVA indicate that pavement sensing patterns from the sensors placed on the front control arms were statistically significant, and there is no difference between the sensors placed on the same side of the vehicle (e.g., left or right side). A reference threshold (i.e., 1.7 g) was computed from the distribution fitting method to classify road conditions and identify the road distress based on the magnitude values that combine all acceleration along three axes. In addition, the pavement temperature was found to be highly correlated with the sensing patterns, which is noteworthy for future projects.

The paper investigates the effect of pavement sensors’ placement in assessing road conditions, emphasizing the implications for future road condition assessment projects. A threshold value for classifying road conditions was proposed and applied in class assignments (I-17 highway projects).

Built asset management processes require a long transition period to collect, edit and update asset conditions information from existing data sets. This paper aims to explore and explain whether and how digital technologies, including asset information model (AIM), Internet of Things (IoT) and blockchain, can enhance asset conditions assessment and lead to better asset management.

Mixed methods are applied to achieve the research objective with a focus in universities. The questionnaire aims to test whether the integration of AIM, IoT and blockchain can enhance asset condition assessment (ACA). Descriptive statistical analysis was applied to the quantitative data. The mean, median, mode, standard deviation, variance, skewness and range of the data group were calculated. Semi-structured interviews were designed to answer how the integration of AIM, IoT and blockchain can enhance the ACA. Quantitative data was analysed to define and explain the essential factors for each sub-hypothesis. Meanwhile, to strengthen the evaluation of the research hypothesis, the researcher also obtained secondary data from the literature review.

The research shows that the integration of AIM, IoT and blockchain strongly influences asset conditions assessment. The integration of AIM, IoT and blockchain can improve the asset monitoring and diagnostics through its life cycle and in different aspects, including financial, physical, functional and sustainability. Moreover, the integration of AIM, IoT and blockchain can enhance cross-functional collaboration to avoid misunderstandings, various barriers and enhance trust, communication and collaboration between the team members. Finally, costs and risk could be reduced, and performance could be increased during the ACA.

The contribution of this study indicated that the integration of AIM, IoT and blockchain application in asset assessment could increase the efficiency, accuracy, stability and flexibility of asset assessment to ensure the reliability of assets and lead to a high-efficiency working environment. More importantly, a key performance indicator for ACA based on the asset information, technology and people experience could be developed gradually.

This study can break the gap between transdisciplinary knowledge to improve the integration of people, technology (AIM, IoT and blockchain) and process value-based ACA in built asset management within universities.

The purpose of this study is to develop a condition assessment (CA) model for a building's indoor 21 environments and to improve the building's asset management process.

The methodology is based on dividing the building into spaces, which are the principal evaluated elements based on the building's indoor environmental quality (IEQ). An evaluation scheme was prepared for the identified factors and the analytical hierarchy process (AHP) technique was used to calculate the relative weight of each space inside the building as well as the contribution of each IEQ factors (IEQFs) in the overall environmental condition of each space inside the building. The multi-attribute utility theory (MAUT) was then applied to assess the environmental conditions of the building as a whole and its spaces. An educational building in Canada was evaluated using the developed model.

Each space type was found to have its own IEQFs weights, which confirms the hypothesis that the importance and allocation of each IEQF are dependent on the function and tasks carried out in each space. A similar indoor environmental assessment score was calculated using the developed model and the building CA conducted by the facility management team; “89%” was calculated, using K-mean clustering, for the physical and environmental conditions.

IEQ affects occupants' assessment of their quality of life (QOL). Despite the existence of IEQ evaluation models that correlate the building's IEQ and the occupants' perceived indoor assessments, some limitations have led to the necessity of developing a comprehensive model that integrates all factors and their sub-criteria in an assessment scheme that converts all the indoor environmental factors into objective metrics.