Participation, Barriers, and Opportunities in PFI: The United Kingdom Experience

Private finance initiative (PFI) projects play an increasingly important role for both the United Kingdom government and the construction sector. It is still a relatively new form of procurement that requires a wide range of specialist advice during the bidding stage and in-depth knowledge of how the facility will perform in the long term. This paper investigates the level of participation in PFI projects in the United Kingdom, the opportunities available for the construction sector, the types of problems experienced, and the challenges for the future. It achieves this by analyzing the results of a questionnaire survey of a large number of client and construction organizations. The study finds that there is a wide gap in the level of PFI experience between client and construction organizations, affordability of PFI projects, and high bidding costs are key issues for client and construction organizations, respectively, and, given the nature of PFI projects, there is considerable scope for knowledge transfer both during the project and between different PFI projects.     

Perception of Financial Institutions toward Financing PFI Projects in Hong Kong

Private finance initiative (PFI) has emerged to be a viable strategy for governments to transfer financial risks in public projects to the private sector. It does not only help tap the efficiency and finances of the private sector but it also promises to deliver better public services to the community. Despite these obvious incentives, there is still a low PFI diffusion in Hong Kong. Based on this understanding, we have undertaken this exploratory study, which is probably the first of its kind, to investigate the PFI’s financial issues from the perspective of financial suppliers. This study was intended to identify factors that may affect the perception of the supplier side and to explore ways to facilitate their participation in PFI projects. The findings suggest that respondents had low level of understanding and knowledge of the PFI and they perceived that PFI public projects had an average risk and performance. To increase their involvement, several enablers are provided in this paper.     

The Personal Functioning Inventory: A reliable and valid measure of adaptiveness in coping.

This article reports the development and validation of the Personal Functioning Inventory (PFI), a new measure of adaptiveness in coping. In Study 1, two adult samples (Ns of 105 and 101) showed the PFI to be highly reliable and to correlate substantially with a summed rating scale for adaptiveness. Study 2 with 140 undergraduates again showed the PH to be highly reliable and to relate positively to problem-solving confidence and negatively to perceived stress. Study 3, a two-wave longitudinal study with a three-week intersession interval, involved 149 undergraduates at Time 1 and retained 107 at Time 2. It demonstrated strong reliability and stability for the PFI, concurrent and predictive positive relations with selfrated adaptiveness and prolonged state anxiety, and discriminant validity against abstract curiosity. Factor analyses consistently supported a one-factor structure for the PFI. Possible applications for the scale are noted. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

How much insulin-like growth factor I (IGF-I) circulates? Impact of standardization on IGF-I assay accuracy

There is a significant systematic difference between the normal range obtained from ethylenediamine tetraacetate plasma samples using the Genentech total insulin-like growth factor I (IGF-I) RIA and normal ranges for other total IGF-I RIAs. To determine whether the quality of the assay standard was the cause of this systematic difference, we analyzed commercially available preparations of recombinant human IGF-I (rhIGF-I) typical of those used as IGF-I immunoassay standards along with our own well characterized rhIGF-I assay standard. For the commercial standards, high performance liquid chromatography-derived purities were low, and some vendor-assigned protein concentrations were inconsistent with values from quantitative amino acid analysis. The Genentech rhIGF-I assay standard was highly pure and quantitatively correct. However, the poor quality of some commercial rhIGF-I preparations was not the primary reason for the systematic discrepancy between the Genentech total IGF-I RIA normal range and most other normal ranges. Most assays for total IGF-I are calibrated against the WHO International Reference Reagent (IRR) for IGF-I Immunoassays (87/518). The Genentech total IGF-I RIA is not calibrated against WHO IRR 87/518. The protein content assigned to WHO IRR 87/518 was a consensus value from a multicenter collaborative study. Physicochemical analyses showed that WHO IRR 87/518 is Met(-1)-IGF-I of low purity (44%), and that the assigned protein content is higher than the value determined by quantitative amino acid analysis. Thus, assays that are calibrated against WHO IRR 87/518 will report total IGF-I concentrations in excess of actual values. We believe that calibration against WHO IRR 87/518 is the cause of the systematic discrepancy between the Genentech IGF-I assay normal range and most other normal ranges, and that much of the plasma IGF-I concentration data in the literature are of questionable accuracy.     

Applications of Horizontal Characterization Techniques in Trenchless Construction

Horizontal site characterization technologies present a rapidly evolving alternative to traditional vertical site investigation methods for subsurface investigations of large diameter trenchless construction projects. A state-of-the-art review of horizontal site characterization tools, both currently available and under development, is presented. Additionally, a rational methodology for the selection and deployment of horizontal site investigation techniques in trenchless construction projects is also presented. The methodology enables the user to define and quantify the risks involved in a particular project, as well as to evaluate the degree to which these risks can be mitigated using various site characterization techniques. The proposed model is demonstrated using a working example. The paper concludes with a discussion of future trends in this exciting new field. The main conclusions drawn from this work are (1) adequate subsurface information is invaluable for underground construction; (2) site investigation programs of linear construction projects can be enhanced by horizontal characterization techniques; and (3) the availability of continuous and near-continuous subsurface information enables the utilization of new approaches for the analysis and representation of subsurface data.     

Individual and situational factors that influence the efficacy of personalized feedback substance use interventions for mandated college students.

Little is known about individual and situational factors that moderate the efficacy of personalized feedback interventions (PFIs). Mandated college students (N = 348) were randomly assigned either to a PFI delivered in the context of a brief motivational interview (BMI; n = 180) or to a written PFI only (WF) condition and were followed up at 4 months and 15 months postintervention. The authors empirically identified heterogeneous subgroups utilizing mixture modeling analysis based on heavy episodic drinking and alcohol-related problems. The 4 identified groups were dichotomized into an improved group (53.4%) and a nonimproved group (46.6%). Logistic regression results indicated that the BMI was no more efficacious than the WF across all mandated students. However, mandated students who experienced a serious incident requiring medical or police attention and those with higher levels of alcohol-related problems at baseline benefited more from the BMI than from the WF. It may be an efficacious and cost-effective approach to provide a written PFI for low-risk mandated students and an enhanced PFI with a BMI for those students who experience a serious incident or have higher baseline alcohol-related problems. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Project Management in Construction: Software Use and Research Directions

This paper focuses on future research and the use of project management software in the construction industry. Data are drawn from an empirical study of project management professionals that yielded 240 replies (35% response rate), 42 of which were from the construction industry. Data were collected on: demographics and work environment, project management software usage patterns, analytical technique usage, data management, and suggestions for future research. The results indicate that construction professionals have different characteristics, needs and preferences, as compared to the overall sample. The study shows that construction professionals are more experienced and educated than the respondents in the overall study, they tend to work on fewer projects with larger numbers of activities, and they are more likely to use Primavera (Primavera, Inc., Bala Cynwyd, Pa.) than Microsoft Project (Microsoft Corp., Redmond, Wash.). Construction respondents are heavy users of critical path analysis for planning and control, resource scheduling for planning, and earned value analysis for control. The number of activities in a typical project and the use of software for all active projects were the key determinants of the usage of specific analytical techniques. These factors are also significant determinants of the types of information entered and updated, although the effect is weaker. Although construction professionals are generally satisfied with the quality of schedules produced by the software, they still expressed a clear interest in future research on resource scheduling∕leveling in general and a net present value option in particular. To maximize the impact on practice, development of new planning and control methods should include their integration into project management software.     

Improving Labor Flow Reliability for Better Productivity as Lean Construction Principle

New management thinking, like that of lean production, has suggested that better labor and cost performance can be achieved by improving the reliability of flows. In this context, lean thinking portrays reliable flows as the timely availability of resources, i.e., materials, information, and equipment. Little attention has been given to labor as a flow. Further, little discussion can be found related to flexible capacity management strategies. Efforts to utilize lean thinking in construction, so far, have generated limited evidence to support the need for more reliable labor flows. This paper investigates the lean principle that more reliable flows lead to better labor performance. Actual data from three bridge construction projects are examined to document the instances of poor flow (resource) reliability and its effect on labor performance. Inefficient labor hours are calculated. The results show that there is strong support that more reliable material, information, and equipment availability contributes to better performance. However, the projects showed considerable deficiencies in the utilization of the labor resource. It is concluded that lean improvement initiatives should focus more on workforce management strategies to improve labor utilization that will lead to better labor performance.     

Bootstrap Technique for Risk Analysis with Interval Numbers in Bridge Construction Projects

Bridges are principal and vital transportation structures. If risk management is not considered in bridge construction projects, objectives cannot be delivered on time, on budget, or with suitable quality results. Risk data set sizes and experts’ judgments are not usually sufficient for analyzing significant risks in bridge construction projects; moreover, the statistical distributions for risk parameter estimates are usually unknown. Standard parametric statistical techniques cannot provide appropriate solutions for cases with small data sets or unknown distributions. This paper proposes a new hybrid approach by using a nonparametric resampling technique and interval computations for risk analysis, in particular, for bridge construction projects. Bootstrap techniques produce more accurate inferences for comparing parametric techniques and are an alternative when the underlying parametric assumptions are not considered. Increasingly, because of the complexity and uncertainty in decision making at bridge projects, it is easier or more natural to provide interval values for parts or all of decision-making judgments. Furthermore, the goal of reducing standard deviations for both risk probability and risk impact compared with the conventional approach is another conclusion of this paper. The proposed approach is applied to a case in Iran to show the validity of the approach.     

Application of TQM to Environmental Construction

Cost and schedule data were obtained for 40 environmental construction projects built for the United States Navy. Total Quality Management (TQM) techniques were used during the construction of 21 of the projects. The amount of cost escalation during construction, increases in project duration, and the level of supervisory effort required by Navy engineers are compared. Analysis of the data also revealed that projects requiring subsurface remediation work were more likely to have cost overruns and increases in project duration due to changed conditions. Standardized costs and durations are used to compare projects of different magnitudes. Stem and leaf plots are used to provide a means of comparing the distributions of the TQM and non-TQM data sets. Stem and leaf plots are also constructed for projects that included underground remediation work and projects that did not. An analysis of the comparisons suggested that application of the TQM methods may provide benefits by reducing the number and magnitude of duration increases. Project cost escalation appears to be more closely connected to changed conditions as a result of the uncertainties of underground remediation work.     

Alternative Concession Model for Build Operate Transfer Contract Projects

This paper develops an alternative concession model for build operate transfer (BOT) infrastructure projects. The concession period is a measure for deciding when the project ownership will be transferred from the investor back to the government concerned; it also demarcates the benefits, authorities, and responsibilities between the government and private investors. Previous studies have developed various techniques and methods, mainly suggesting proper organization structure, contracting procedures, methods of project financing, and risk allocation strategies when BOT-contract projects are implemented. These works have provided effective methodologies for the development of BOT contracts. Nevertheless, it appears that little has been undertaken in studying the way to determine the concession period in a BOT contract. This paper critically reviews the principles of establishing the concession period in a BOT contract. Such a review leads to developing a quantitative model for determining a proper concession period that can protect the interests of both the government concerned and private investors. An example is given that indicates how the alternative model can be applied to determine the concession periods of BOT infrastructure projects.     

多IRR投资方案的评价

在指出多IRR投资方案技术经济动态评价传统方法存在的缺陷后，提出一种更实用、可行、经济涵义更明确的计算方法。     

Effect of fasting on insulin receptor-related receptor messenger ribonucleic acid in rat kidney

The insulin receptor-related receptor (IRR), a member of the insulin receptor tyrosine kinase family, has structural homology to the insulin receptor (IR) and the IGF-I receptor (IGF-IR). The ligand, gene regulation and biological function of the IRR are not known. Because mRNAs for both the IR and IGF-IR are increased by nutrient restriction, we used RNase protection assays to assess the effects of fasting 48 h on IRR mRNA in kidneys of rats. We compared the changes in IRR with those in IR and IGF-IR mRNAs. We observed a significant increase in steady state levels of IRR (ratio of IRR mRNA to beta-actin in fed P<0.01), suggesting that the ligand for IRR also might be regulated by nutrients.     

Markov chain Monte Carlo methods in biostatistics

Appropriate models in biostatistics are often quite complicated. Such models are typically most easily fit using Bayesian methods, which can often be implemented using simulation techniques. Markov chain Monte Carlo (MCMC) methods are an important set of tools for such simulations. We give an overview and references of this rapidly emerging technology along with a relatively simple example. MCMC techniques can be viewed as extensions of iterative maximization techniques, but with random jumps rather than maximizations at each step. Special care is needed when implementing iterative maximization procedures rather than closed-form methods, and even more care is needed with iterative simulation procedures: it is substantially more difficult to monitor convergence to a distribution than to a point. The most reliable implementations of MCMC build upon results from simpler models fit using combinations of maximization algorithms and noniterative simulations, so that the user has a rough idea of the location and scale of the posterior distribution of the quantities of interest under the more complicated model. These concerns with implementation, however, should not deter the biostatistician from using MCMC methods, but rather help to ensure wise use of these powerful techniques.     

Multiple Simulation Analysis for Probabilistic Cost and Schedule Integration

One of the major goals of the construction industry today is the quantification and minimization of the risk associated with construction engineering performance. When specifically considering the planning of construction projects, one way to control risk is through the development of reliable project cost estimates and schedules. Two techniques available for achieving this goal are range estimating and probabilistic scheduling. This paper looks at the integration of these techniques as a means of further controlling the risk inherent in the undertaking of construction projects. Least-squares linear regression is first considered as a means of relating the data obtained from the application of these techniques. However, because of various limitations, the application of linear regression was not considered the most appropriate means of relating the results of range estimating and probabilistic scheduling. Integration of these techniques was, therefore, achieved through the development of a new procedure called the multiple simulation analysis technique. This new procedure combines the results of range estimating and probabilistic scheduling in order to quantify the relationship existing between them. Having the ability to accurately quantify this relationship enables the selection of high percentile level values for the project cost estimate and schedule simultaneously.     

Case Law and Variations in Cumulative Impact Productivity Claims

Proving and quantifying lost productivity due to cumulative impacts of multiple changes are difficult tasks. This paper presents the most acceptable methods from case law and demonstrates their applications for analyzing the loss of productivity. These methods include earned value analysis, measured mile analysis, and combinations of these two. They are either well established or drawn from recent court and board decisions. A case study is used to illustrate and compare the use of these methods. These methods result in considerably different loss of productivity values though the actual amount (i.e., inefficiency in labor hours) is unique for a particular case and though these methods are often thought to be similar or even the same. How a measured mile analysis and its variants are employed affects the amount of lost productivity estimated. The variants can avoid some drawbacks of measured mile and earned value studies. Nevertheless, which method is more accurate and reliable is difficult to provide for a particular claim. Practitioners should choose between them based on the availability of project records and the nature of changes and cumulative impacts. Practitioners may also employ two or more methods to perform a “sensitivity analysis” of the chosen methods and persuade the other party and/or the jury that their estimate of lost productivity is sufficiently certain.     

Contractor Selection for Design∕Build Projects

As traditional construction procurement approaches are found to be inadequate in meeting the demands and challenges of recent times, alternative procurement routes such as through management contracting or build-operate-transfer are increasingly being adopted. Although design∕build is one of the more popular alternative procurement methods that also has a long history, it does not appear to have well-established contractor selection procedures. This paper focuses on developing a model for contractor prequalification and bid evaluation in design∕build projects. For this purpose, it presents a comparative overview of some international practices in the design∕build contractor selection process. The overall objective is to identify the core aspects of selecting a suitable bidder in order to achieve the best “value for money.” The strengths and weaknesses of current practices of contractor selection are highlighted while identifying some of the best practices followed in design∕build projects by various clients.     

Practical Method to Prevent Liquid-Column Separation

This paper describes a practical method to prevent the phenomenon of liquid-column separation in a pipeline by increasing the polar moment of inertia of the rotating parts of a pump-motor unit. Two examples are presented in detail. The examples indicate the following advantages of this method over other methods (e.g., installing air valves, air vessels, or one-way surge tanks in a pipeline): (1) low in cost for small-capacity motors; (2) safe and reliable; (3) not limited by conveyed media and climates; (4) no additional maintenance required; and (5) applicable to any pumping projects when the size and weight of motors are not limited in manufacture.     

Predicting Cost Deviation in Reconstruction Projects: Artificial Neural Networks versus Regression

This paper investigates the challenging environment of reconstruction projects and describes the development of a predictive model of cost deviation in such high-risk projects. Based on a survey of construction professionals, information was obtained on the reasons behind cost overruns and poor quality from 50 reconstruction projects. For each project, the specific techniques used for project control were reported along with the actual cost deviation from planned values. Two indicators of cost deviation are used in this study: cost overrun to the owner, and the cost of rework to the contractor. Based on the information obtained, 36 factors were identified as having direct impact on the cost performance of reconstruction projects. Two techniques were then used to develop models for predicting cost deviation: statistical analysis, and artificial neural networks (ANNs). While both models had similar accuracy, the ANN model is more sensitive to a larger number of variables. Overall, this study contributes to a better understanding of the reasons for cost deviation in reconstruction projects and provides a decision support tool to quantify that deviation.     

Programmatic Cost Risk Analysis for Highway Megaprojects

Highway megaprojects (construction projects over $100 million) are fraught with uncertainty. These projects have historically experienced increases in project costs from the time that a project is first proposed or programmed until the time that they are completed. Persistent cost underestimation reflects poorly on the industry in general but more specifically on engineers. Traditional methods take a deterministic, conservative approach to project cost estimating and then add a contingency factor that varies depending on the stage of project definition, experience, and other factors. This approach falls short, and no industry standard stochastic estimating practice is currently available. This paper presents a methodology developed by the Washington State Department of Transportation (WSDOT) for its Cost Estimating Validation Process. Nine case studies, with a mean cumulative value of over $22 billion, are presented and analyzed. Programmatic risks are summarized as economic, environmental, third party, right-of-way, program management, geotechnical, design process, construction, and other minor risks. WSDOT is successfully using the range cost output from this procedure to convey project costs to management and the public.