Sustainability in infrastructure investment : building the business case

Many infrastructure agencies adopt sustainability objectives at a corporate level and incorporate sustainability targets and indicators as part of corporate reporting processes. These objectives are expected to translate to all stages of the project delivery process, including project selection. For infrastructure capital works projects and programs, a robust project management approach involves the development of a business case to guide investment decision making. A key tool in the assessment of project options and selection of a delivery strategy is Cost Benefit Analysis (CBA). Infrastructure providers are required to undertake cost benefit analysis to support project selection through regulatory approval and budgetary processes. This tool has emerged through the prism of economic analysis rather than sustainability. A literature review reveals the limitations of CBA alone to effectively evaluate economic, environmental and social externalities or impacts that apply over a long time frame, and that are ultimately irreversible. Multi-Criteria Analysis (MCA) has been introduced as a means to incorporate a wider array of factors into decision making such as sustainability. This, however, presents new challenges with issues around how to transparently represent wider community values in the selection of a preferred solution. Are these tools effective in assessing the wider sustainability costs and benefits taking into account that these are public works with long life spans and significant impacts across institutional boundaries? The research indicates a need to develop clear guidelines for investment decision making in order to better align with corporate sustainability objectives. Findings from the literature review indicate that a more sustainable approach to investment decision-making framework should include: the incorporation of sustainability goals from corporate planning documents; problem definition and option generation using best practice investment management guidelines; improved guidelines for Business Case development using a combination of both Cost Benefit Analysis and Multi-Criteria Analysis; and an integrated public participation process.

Autoconsumo fotovoltaico, um elemento de eficiência energética. Caso de estudo: ISEP

Mestrado em Energias Sustentáveis

Building dynamic capabilities of adaptation and innovation: a study of micro-foundations in a transition economy

What are the microfoundations of dynamic capabilities that sustain competitive advantage in a highly volatile environment, such as a transition economy? We explore the detailed nature of these dynamic capabilities along with their antecedents by tracing the sequence of their development based on a longitudinal case study of an organization subject to an external context of radical transition — the Russian oil company, Yukos. Our rich qualitative data indicate two distinct types of dynamic capabilities that are pivotal for organizational transformation. Adaptation dynamic capabilities relate to routines of resource exploitation and deployment, which are supported by acquisition, internalization and dissemination of extant knowledge, as well as resource reconfiguration, divestment and integration. Innovation dynamic capabilities relate to the creation of completely new capabilities via exploration and path-creation processes, which are supported by search, experimentation and risk taking, as well as project selection, funding and implementation. Second, we find that sequencing the two types of dynamic capabilities, helped the organization both to secure short-term competitive advantage, and to create the basis for long-term competitive advantage. These dynamic capability constructs advance theoretical understanding of what dynamic capabilities are, whilst their sequencing explains how firms create, leverage and enhance them over time.

Fatores que influenciam a produção de biomassa e glicerol quinase pela levedura recombinante Pichia pastoris

Pós-graduação em Alimentos e Nutrição - FCFAR

Ajuste e balanceamento do portfólio de projetos: o caso de uma empresa do setor químico

O objetivo deste trabalho é compreender a etapa de ajuste no contexto da gestão do portfólio de projetos, destacando sua relação com os processos de categorização e balanceamento. A pesquisa realizada tem caráter qualitativo, sendo a abordagem adotada o estudo de caso longitudinal. A pesquisa foi desenvolvida em uma empresa do setor químico brasileiro. As evidências, de várias fontes, foram coletadas através de entrevistas, documentos e dados dos sistemas corporativos. Para a compreensão do portfólio de projetos da empresa foram coletados e analisados dados de mil projetos realizados entre 2001 e 2005. Os resultados indicam que maior atenção é dada à etapa de seleção, negligenciando a etapa de ajuste. A adoção de ferramentas de balanceamento permitiu evidenciar lacunas e fontes de desbalanceamento no portfólio de projetos, promovendo o debate entre os tomadores de decisão no que concerne ao viés introduzido pelos critérios adotados na etapa de seleção e levantando a necessidade de introdução de uma sistemática de ajuste e balanceamento. Observou-se que sem uma adequada categorização dos projetos da empresa seria difícil promover a análise de balanceamento.

Assessing the financial impact of 6-Sigma in an automotive company

This paper reports on an assessment of an ongoing 6-Sigma program conducted within a UK based (US owned) automotive company. It gives an overview of the management of the 6-sigma programme and the 23 in-house methodology used. The analysis given in the paper pays particular focus to the financial impacts that individual projects have had. Three projects are chosen from the hundreds that have been completed and are discussed in detail, including which specific techniques have been used and how financially successful the projects were. Commentary is also given on the effectiveness of the overall program along with a critique of how the implementation of 6-Sigma could be more effectively managed in the future. This discussion particularly focuses upon issues such as: project selection and scoping, financial evaluation and data availability, organisational awareness, commitment and involvement, middle management support, functional variation, and maintaining momentum during the rollout of a lengthy program.

Essays on the impact of stakeholders' sentiment on the financial decision making process

The most important factor that affects the decision making process in finance is the risk which is usually measured by variance (total risk) or systematic risk (beta). Since investors’ sentiment (whether she is an optimist or pessimist) plays a very important role in the choice of beta measure, any decision made for the same asset within the same time horizon will be different for different individuals. In other words, there will neither be homogeneity of beliefs nor the rational expectation prevalent in the market due to behavioral traits. This dissertation consists of three essays. In the first essay, “ Investor Sentiment and Intrinsic Stock Prices”, a new technical trading strategy was developed using a firm specific individual sentiment measure. This behavioral based trading strategy forecasts a range within which a stock price moves in a particular period and can be used for stock trading. Results indicate that sample firms trade within a range and give signals as to when to buy or sell. In the second essay, “Managerial Sentiment and the Value of the Firm”, examined the effect of managerial sentiment on the project selection process using net present value criterion and also effect of managerial sentiment on the value of firm. Final analysis reported that high sentiment and low sentiment managers obtain different values for the same firm before and after the acceptance of a project. Changes in the cost of capital, weighted cost of average capital were found due to managerial sentiment. In the last essay, “Investor Sentiment and Optimal Portfolio Selection”, analyzed how the investor sentiment affects the nature and composition of the optimal portfolio as well as the portfolio performance. Results suggested that the choice of the investor sentiment completely changes the portfolio composition, i.e., the high sentiment investor will have a completely different choice of assets in the portfolio in comparison with the low sentiment investor. The results indicated the practical application of behavioral model based technical indicator for stock trading. Additional insights developed include the valuation of firms with a behavioral component and the importance of distinguishing portfolio performance based on sentiment factors.

Essays on the Impact of Stakeholders' Sentiment on the Financial Decision Making Process

The most important factor that affects the decision making process in finance is the risk which is usually measured by variance (total risk) or systematic risk (beta). Since investors' sentiment (whether she is an optimist or pessimist) plays a very important role in the choice of beta measure, any decision made for the same asset within the same time horizon will be different for different individuals. In other words, there will neither be homogeneity of beliefs nor the rational expectation prevalent in the market due to behavioral traits. This dissertation consists of three essays. In the first essay, Investor Sentiment and Intrinsic Stock Prices, a new technical trading strategy is developed using a firm specific individual sentiment measure. This behavioral based trading strategy forecasts a range within which a stock price moves in a particular period and can be used for stock trading. Results show that sample firms trade within a range and show signals as to when to buy or sell. The second essay, Managerial Sentiment and the Value of the Firm, examines the effect of managerial sentiment on the project selection process using net present value criterion and also effect of managerial sentiment on the value of firm. Findings show that high sentiment and low sentiment managers obtain different values for the same firm before and after the acceptance of a project. The last essay, Investor Sentiment and Optimal Portfolio Selection, analyzes how the investor sentiment affects the nature and composition of the optimal portfolio as well as the performance measures. Results suggest that the choice of the investor sentiment completely changes the portfolio composition, i.e., the high sentiment investor will have a completely different choice of assets in the portfolio in comparison with the low sentiment investor. The results indicate the practical application of behavioral model based technical indicators for stock trading. Additional insights developed include the valuation of firms with a behavioral component and the importance of distinguishing portfolio performance based on sentiment factors.

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.

Selection of project procurement methods in the consumer electronics industry : a Hong Kong study

Under pressure from both the ever increasing level of market competition and the global financial crisis, clients in consumer electronics (CE) industry are keen to understand how to choose the most appropriate procurement method and hence to improve their competitiveness. Four rounds of Delphi questionnaire survey were conducted with 12 experts in order to identify the most appropriate procurement method in the Hong Kong CE industry. Five key selection criteria in the CE industry are highlighted, including product quality, capability, price competition, flexibility and speed. This study also revealed that product quality was found to be the most important criteria for the “First type used commercially” and “Major functional improvements” projects. As for “Minor functional improvements” projects, price competition was the most crucial factor to be considered during the PP selection. These research findings provide owners with useful insights to select the procurement strategies.

Ideas to improve the selection of NHMRC Project Grants

The starting point for this presentation is that applicants provide a large surplus of information when submitting a NHMRC Project Grant proposal for funding. This is costly in their time, attracts high administration costs, makes the task appear daunting for peer reviewers and may reduce the quality of the peer review leading to less than perfect reliability in decision making. We are currently experimenting with alternate models to see whether similar reliability in funding outcomes are achieved at less cost. We will compare traditional NHMRC Grant Review Panels (GRPs) with panels that use less information and journal style panels. By way of background to this experimental work, we will show some results on current levels of reliability for GRPs, the costs incurred by all who participate in Project Grant selection, and the level of reliability acceptable to researchers. By experimenting in this way and building an evidence base for how research funding should be allocated, the NHMRC is showing international leadership in this important field.

The structured and practical approach in development of decision support system for consultant selection in public sector infrastructure project

Nowadays, most of the infrastructure development projects undertaken are complex in nature. Practically, public clients who do not have a good understanding of the design and management may suffer severe losses, especially for infrastructure projects. There is a need for luring the right consultant to secure client's investment in infrastructure developments. Throughout the project life cycle, consultants play vital role from the inception to completion stage of a project. A few studies in Malaysia show that infrastructure projects involving irrigation and drainage have experience problems such as poor workmanship, delay and cost overrun due to the consultant's inability or the client incompetence of recruiting consultants in time. This highlights the need of aided decision making and an efficient system to select the best consultant by using Decision Support System (DSS). On the other hand, recent trends reveal that most DSS in construction only concentrate on decision model development. These models are impractical and unused as they are complicated or difficult for laymen such as project managers to utilize. Thus, this research attempts to develop an efficient DSS for consultant selection namely consultDeSS. Driven by the motivation and research aims, this study deployed Design Science Research Methodology (DSRM) dominant with a combination of case studies at the Malaysian Department of Irrigation and Drainage (DID). Two real projects involving irrigation and drainage infrastructure were used to design, implement and evaluate the artefact. The 3-tier consultDeSS was revised after the evaluation and the design was significantly improved based on user feedback. By developing desirable tools that fit client's needs will enhance the productivity and minimize conflict within groups and organisations. The tool is more usable and efficient compared to previous studies in construction. Thus, this research has demonstrated a purposeful artefact with a practical and valid structured development approach that is applicable in a variety of problems in construction discipline.

A hybrid quality function deployment and cybernetic analytic network process model for project manager selection

Identifying appropriate decision criteria and making optimal decisions in a structured way is a complex process. This paper presents an approach for doing this in the form of a hybrid Quality Function Deployment (QFD) and Cybernetic Analytic Network Process (CANP) model for project manager selection. This involves the use of QFD to translate the owner's project management expectations into selection criteria and the CANP to weight the expectations and selection criteria. The supermatrix approach then prioritises the candidates with respect to the overall decision-making goal. A case study is used to demonstrate the use of the model in selecting a renovation project manager. This involves the development of 18 selection criteria in response to the owner's three main expectations of time, cost and quality.

Neuro-Fuzzy genetic system for selection of construction project managers

Choosing a project manager for a construction project—particularly, large projects—is a critical project decision. The selection process involves different criteria and should be in accordance with company policies and project specifications. Traditionally, potential candidates are interviewed and the most qualified are selected in compliance with company priorities and project conditions. Precise computing models that could take various candidates’ information into consideration and then pinpoint the most qualified person with a high degree of accuracy would be beneficial. On the basis of the opinions of experienced construction company managers, this paper, through presenting a fuzzy system, identifies the important criteria in selecting a project manager. The proposed fuzzy system is based on IF-THEN rules; a genetic algorithm improves the overall accuracy as well as the functions used by the fuzzy system to make initial estimates of the cluster centers for fuzzy c-means clustering. Moreover, a back-propagation neutral network method was used to train the system. The optimal measures of the inference parameters were identified by calculating the system’s output error and propagating this error within the system. After specifying the system parameters, the membership function parameters—which by means of clustering and projection were approximated—were tuned with the genetic algorithm. Results from this system in selecting project managers show its high capability in making high-quality personnel predictions