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Assessing the Effect of Audit Compliance, Conflict Management and Bureaucratic Attitude on the Success of Public Projects

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The construction industry, the largest industry in America, is in disarray because of high costs, sliding productivity, marginal profits, and high turnover. Research and development (R&D) in the industry is at present minimal, but could be a decisive factor needed to spark rejuvination. An R&D policy is proposed, with a discussion of creativity, the skills needed by R&D personnel, the interaction of R&D with bureaucratic activities, and negative side of R&D specialization. Construction education needed to supply research manpower, as well as to upgrade the skills and knowledge of construction personnel in general, may be the second decisive rejuvinating factor. The status of construction education in America is reviewed.
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The identification of key factors for construction project success enables appropriate allocation of limited resources. Most of the related past work only identified critical success factors for construction projects in general. The present study seeks to distinguish these factors according to the project objectives of budget, schedule, and quality. The analytic hierarchy process is adopted to determine the relative importance of success-related factors. A hierarchical model for construction project success is presented. Sixty-seven success-related factors are considered. These factors are grouped under four main project aspects, namely, project characteristics, contractual arrangements, project participants, and interactive processes in the hierarchical model for project success. A questionnaire was developed to facilitate systematic data collection in this study. Experts with an overall average of 20 years of experience in the construction industry were invited to participate in the survey. Critical success factors addressing budget performance, schedule performance, quality performance, and overall project success are identified. Some pertinent findings of the study are discussed. Comparisons with findings of previous studies using neural network approach are also presented.
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Achieving success in public construction projects is difficult because it requires economy, efficiency, quality, fairness and transparency. Such projects are taken up on the requisition of owners/clients and almost always involve multiple entities and are also accountable to external financial audit and vigilance agencies. Identification of the success factors is considered the key to achieving success in these projects. Through an extensive literature review, 36 success attributes were identified and a questionnaire-based survey was undertaken to elicit views of professionals on these success attributes. The responses from 105 professionals with an average of 22 years of experience in public construction projects in India were collected and analysed. The factor analysis yielded four success factors: awareness of and compliance with rules and regulations; pre-project planning and clarity in scope; effective partnering among project participants; and external monitoring and control. These four success factors were also used in multivariate linear regression in order to explore their relative significance for overall performance, and compliance with anti-corruption and financial norms. The most significant factor for overall performance is awareness of and compliance with rules and regulations. The results would be helpful to public construction project professionals in taking proactive measures for successful completion of public projects.
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Despite extensive efforts, corruption in public procurement has reached epidemic proportions and has become one of the major challenges for management. Because corrupt practices mostly occur under wraps, the task of combating corruption becomes even more difficult. In the course of a review of the extant literature on the theme a number of independent constructs with the potential to develop anti-corruption strategies have been identified. A research model was developed on the basis of the hypothesis that anti-corruption strategies lead to corruption free performance in public construction projects. A questionnaire survey was administered and 105 responses were collected. ‘Anti-corruption strategies’ was defined as a second order construct composed of four latent constructs: leadership, rules and regulations, training and fear of punishment. The structural equation modelling (SEM) technique was used to test the hypothesized positive inter-relations between anti-corruption strategies and corruption free performance. The significance of the role of management leadership, rules and regulations, training, as well as fear of punishment is highlighted to help policy makers and construction institutions in understanding the role of various anti-corruption strategies in public construction projects so that they may contribute to this important endeavour in achieving the goal of promoting economy, efficiency, quality, fairness and transparency.
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Although extensive research has been undertaken on factors influencing the decision to tender and mark-up and tender price determination for construction projects, very little of this research contains information appropriate to the factors involved in costing construction projects. The object of this study was to gain an understanding of the factors influencing contractors' cost estimating practice. This was achieved through a comparative study of eighty-four UK contractors classified into four categories, namely, very small, small, medium and large firms. The initial analysis of the 24 factors considered in the study shows that the main factors relevant to cost estimating practice are complexity of the project, scale and scope of construction, market conditions, method of construction, site constraints, client's financial position, buildability and location of the project. Analysis of variance, which tests the null hypothesis that the opinions of the four categories of companies are not significantly different, shows that except for the procurement route and contractual arrangement factor there is no difference of opinion, at the 5% significance level, on the factors influencing cost estimating. Further analysis, based on a factor analysis technique, shows that the variables could be grouped into seven factors; the most important factor grouping being project complexity followed by technological requirements, project information, project team requirement, contract requirement, project duration and, finally, market requirement.
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