Modelling client satisfaction levels: a comparison of multiple regression and artificial neural network techniques

The performance of contractors is known to be a key determinant of client satisfaction. Here, clients' satisfaction is defined in several dimensions identified using factor analysis techniques. Based on clients’ assessment of contractor performance, a number of satisfaction models are presented, developed using multiple regression (MR) and artificial neural network (ANN) techniques. The MR models identified that various attributes of the contractor, project and client were found to significantly influence satisfaction levels. Results of the ANN modelling were similar, however the importance of independent variables was found to be different. The models demonstrate accurate and reliable predictive power as confirmed by validation tests. While the MR models tend to be more accurate for specific dimensions of client satisfaction, the ANN models were found to be superior for models of average satisfaction and overall satisfaction. The MR models suggest that contractors have more effect on client satisfaction than the ANN models. Contractors could use the models to help improve their performance leading to more satisfied clients. This will also promote the development of harmonious working relationships within the construction project coalition

Modelling client satisfaction levels: the impact of contractor performance

The performance of contractors is known to be a key determinant of client satisfaction. Here, using factor analysis, clients’ satisfaction is defined in several dimensions. Based on clients’ assessment of contractor performance, a number of satisfaction models are presented, developed using the multiple regression (MR) technique. The models identified a range of variables encompassing contractor performance, project performance and respondent (i.e. client) attributes as useful predictors of satisfaction levels. Contractor performance attributes were found to be of utmost importance indicating that client satisfaction levels are mainly dependent on the performance of the contractor. Furthermore, findings suggest that subjectivity is to some extent prevalent in clients’ performance assessment. The models demonstrate accurate and reliable predictive power as confirmed by validation tests. Contractors could use the models to help improve their performance leading to more satisfied clients. This will also promote the development of harmonious working relationships within the construction project coalition

Intelligent models for predicting levels of client satisfaction

Presents the development of artificial neural network models for predicting client satisfaction levels arising from the performance of contractors, based on data from a UK wide questionnaire survey of clients. Important independent variables identified by the models indicate that long-term relationships may encourage higher satisfaction levels. Moreover, the performance of contractors was found to only partly contribute to determining levels of client satisfaction. Attributes of the assessor (i.e. client) were also found to be of importance, confirming that subjectivity is to some extent prevalent in performance assessment. The models demonstrate accurate and consistent predictive performance for ‘unseen’ independent data. It is recommended that the models be used as a platform to develop an expert system aimed at advising project coalition (PC) participants on how to improve performance and enhance satisfaction levels. The use of this tool will ultimately help to create a performance-enhancing environment, leading to harmonious working relationships between PC participants

Impact of flood characteristics on damage caused to UK domestic properties: the perceptions of building surveyors

Flood damage to domestic properties can be considered as a function of two key factors, that is the flood characteristics (e.g. velocity of flow, time duration, and nature of any suspended contaminants) and characteristics of the property (e.g. physical location, materials of construction, and ability to withstand floodwater forces). A thorough literature review identified that little or no consideration is given to the characteristics of the flood when assessing flood-damaged domestic properties. This indicates that the damage caused by floods is considered by many to be a simple problem to resolve, whereas in reality, it is a complex phenomenon, highlighting the need of research in this area. This paper presents the perceptions of 289 building surveyors regarding flood characteristics as part of a two-year research project to benchmark the assessment of flood-damaged domestic properties in the UK. Surveyors perceived the sewage, fasciae and contaminant content, and depth of the floodwater to be the most important factors to be considered in flood damage assessment. This was followed by the time duration and source of the floodwater. The velocity of the floodwater was considered the least important factor. Findings also revealed that methods to determine these factors were primarily a function of individual subjective perceptions and often based on visual inspection of the floodwater alone. Definitive guidance is therefore needed in order to minimise variations in subsequent repair and reinstatement works

Methods of drying flooded domestic properties: the perceptions of UK building surveyors

The prediction of more frequent flooding events in the UK necessitates the development of reinstatement standards for flood-damaged domestic properties. This is because current reinstatement methods exhibit significant variance which ultimately influence cost and time needed for repair works as well as their overall performance. Prior to the commencement of repair works, it is important that appropriate drying methods be used so that subsequent repair works are not damaged by latent defects such as fungal attack. This paper presents the perceptions of 289 building surveyors regarding methods used to dry flooded domestic properties. Findings suggest that surveyors consider various methods to assist drying rather than focusing on a single dominant method. Furthermore, the drying method is not a scientific process but rather one based on experience and subjectivity. These facts highlight the lack of definitive guidance on drying out flooded buildings. Further research is recommended towards developing standardised drying out procedures and techniques

The impact of strategic decisions on construction client satisfaction : an assessment framework

For some considerable time, client satisfaction has been a problematic issue in the UK construction industry with many projects failing to satisfy the client needs and meet or exceed the client expectations. Client satisfaction is, however, a key performance measure and a major determinant of project success. There is a common belief that strategic decisions made by clients have a significant impact on the levels of client satisfaction. Strategic decisions in the context of construction projects are often associated with project stages including pre-design, design, tender, construction, occupancy & maintenance and disposal and vary in nature. Consequently the impact of strategic decisions on client satisfaction depends as much on timing as on the subjects of the decisions. While such findings are useful to facilitate the industry’s focus on addressing the failure in achieving client satisfaction, and point to the route for improvement, they are arbitrary and do not provide a systematic basis for investigating the real impact on client satisfaction. The nature of strategic decisions and the significance of its impact on client satisfaction have not been clearly identified and client satisfaction has remained an elusive issue for a majority of construction professionals. This research was hence undertaken to seek empirical evidence of an interrelationship between strategic decisions and client satisfaction. Defining strategic decisions, often associated with project stages, as ones that are complex and made under uncertainty and have a long-term impact on project success, a quantitative research methodology combined with qualitative approaches, was adopted in investigating the interrelationship between strategic decisions and client satisfaction. Findings of a detailed literature review revealed that client satisfaction at any stage depends as much on the service quality attributes of service providers including overall service delivery, people of service providers and communications with clients as on the influence of strategic decisions and the client itself. These performance attributes and the groups of strategic decisions, referred as strategic decision cluster (SDC), were further assessed and the relationships between these measures and strategic decisions were examined using factor analysis and multiple regression modelling techniques. Analyses revealed SDCs including Design Approach, Procurement and Implementation predict better the outcomes of service quality and hence higher levels of client satisfaction. Service delivery and communications with clients have a positively significant correlation with the levels of client satisfaction. Of these two attributes, communications with clients makes the largest unique contribution to the variance and is considered the better predictor for client satisfaction. The developed models is validated via external and internal validation and the findings support the thesis that strategic decisions have a impact on client satisfaction by strongly influencing the performance of service quality although causality cannot be assumed. It is recommended that service providers including contractors and consultants devote more efforts to improve their performance on the attributes of service quality identified as having significant association with client satisfaction, particularly service delivery and communications with clients. Further research efforts focusing on providing a practical tool or expert system so as to address the practical issues for a wider range of clients and service providers are also recommended.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A conceptual model of performance and satisfaction for main participants of construction project coalition

The UK construction industry has long been criticized for engendering adversarial relationships among project participants. The nature of interrelationships ultimately determines overall project performance, in terms of finished product, and levels of performance and satisfaction for the participants. To investigate these interrelationships, the performance and satisfaction of each individual participant must be considered. Better understanding of the interrelationships should help reduce adversarialism and improve the performance and satisfaction of each participant. The possible interrelationships that may exist are discussed based on ‘soft knowledge’ approaches, i.e. psychology, organizational behaviour and sociology. The paper presents a conceptual model of performance and satisfaction for main participants of the project coalition. The ultimate aim of the research is described, that is development of a predictive model for optimizing the interrelationships. The model will determine participant performance levels that would acquire high levels of satisfaction for each participant. This prediction is based on participant performance attributes (i.e. characteristics of that organization, such as past experience, turnover, references, etc.) and interrelationships. This should provide a basis for participant self-evaluation and problem anticipation, ultimately leading to enhancement of overall project performance

Development of a model for performance measurement in just-in-time enabled manufacturing environments

In this era of globalisation and fierce competition amongst businesses, there is a need to improve advanced operations management philosophies such as just-in-time (JIT) manufacturing to enhance business performance. Literature review shows that there is no mechanism so far to identify key JIT drivers relevant to a given organisation and its production processes, and their impact on enterprise performance. The research carried out here therefore involved the development of a generic performance measurement model to identify and capture the influence of JIT practices on enterprise performance. A conceptual performance measurement model, which was designed based on comprehensive literature review and informal interviews/discussions with both academic researchers and industry practitioners describes the link between JIT drivers (Xi) and measurable performance (Y). This mathematically determined model is aimed at assisting managers in the systematic identification of the influence of key JIT drivers on enterprise performance using a multidimensional tool such as the extended balanced scorecard. The case study approach was selected as the most suitable methodology for testing and validating the conceptual model in JIT enabled production plant and was applied to the production process of Denso Manufacturing (UK) Ltd., a global automotive component manufacturer. A novel eight-step implementation procedure was designed to collect data, which were analysed and validated by design of experiments, linear mathematical modelling, computer based dynamic simulation and analytic hierarchy process tool. The performance measurement model was then successfully applied to a non-automotive component production plant (Risane Ltd.). In conclusion, the performance measurement model can now be suitably applied to JIT enabled manufacturing environments using relevant organisation specific JIT drivers and key performance indicators to optimise system performance. The contribution to knowledge is an innovative, user friendly, robust and multidimensional performance measurement model enabling industry practitioners to optimise JIT processes with substantial performance enhancement. The model could also be applied by future researchers to other operations management philosophies and industries, and at a higher level could be developed into a self-optimising software package, which will enable rapid determination of the key control parameters needed to optimise process performance just in time.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A knowledge based system for construction health and safety competence assessment

Organisational and individual Health and Safety (H&S) competence is an essential element to the successful completion of a construction project in a safe way and without hazards to the health of all workforce. Under the Construction (Design and Management) (CDM) Regulations 2007, the client should take reasonable steps to ensure that the appointed duty-holders and engaged people are H&S competent to design, build or co-ordinate the project. Although the CDM Regulations 2007 and its Approved Code of Practice (ACoP) have established ‘Core Criteria’ to guide the client to assess duty-holders’ H&S competence in the outset of a project, it is still difficult for most inexperienced clients to discharge the duty of making the key decisions in H&S competence assessment. In order to help the client implement H&S competence assessment, it is important to develop a tool that can effectively and efficiently support the client to make reasonable decisions in the selection of H&S competent duty-holders. According to the findings of the case study of existing formal H&S competence assessment schemes undertaken as part of this work, H&S competence assessment was characterised as a subjective, qualitative and non-linear regulation-compliance checking process. In addition, the case study helped identify the latent shortcomings in the ‘Core Critiera’ and the operational drawbacks in current practice of implementing H&S competence assessment. Based on a review of Information Technology (I.T.) and Artificial Intelligence (A.I.) applications in construction, Knowledge-Based System (KBS) is identified as being a suitable tool to support decision-making in H&S competence assessment, mainly due to its appropriateness to solve regulation-compliance checking problems and support subjective and qualitative decision-making process. Following a decision-making framework for H&S competence assessment, a KBS decision-support model was developed, applying three mechanisms to support the reasonable decision-making for H&S competence assessment. In order to develop an appropriate and practical KBS for H&S competence assessment, a textual knowledge base was developed, specifying the minimum satisfaction standards and a rating indicator system for ‘Core Criteria’. As a result, an online KBS was developed using Java Server Pages (JSP) technology and MySQL. The online KBS applied the textual knowledge base to support the screen, rating, ranking and reporting decision-supporting mechanisms. Simultaneously, the case inquiry and expert inquiry facilities were also included in the KBS for effective decision-making. Finally, construction experts and practitioners in H&S management evaluated the validity and usability of the KBS through a questionnaire survey. The prototype KBS was borne out to be an effective and efficient decision-support tool for H&S competence assessment and have the potential to be applied in practice.EThOS - Electronic Theses Online ServiceGBUnited Kingdo