Public sector investment appraisal:the place of flexibility in the decision making process

This thesis reviews the main methodological developments in public sector investment appraisal and finds growing evidence that appraisal techniques are not fulfilling their earlier promise. It is suggested that an important reason for this failure lies in the inability of these techniques to handle uncertainty except in a highly circumscribed fashion. It is argued that a more fruitful approach is to strive for flexibility. Investment projects should be formulated with a view to making them responsive to a wide range of possible future events, rather than embodying a solution which is optimal for one configuration of circumstances only. The distinction drawn in economics between the short and the long run is used to examine the nature of flexibility. The concept of long run flexibility is applied to the pre-investment range of choice open to the decisionmaker. It is demonstrated that flexibility is reduced at a very early stage of decisionmaking by the conventional system of appraisal which evaluates only a small number of options. The pre-appraisal filtering process is considered further in relation to decisionmaking models. It is argued that for public sector projects the narrowing down of options is best understood in relation to an amended mixed scanning model which places importance on the process by which the 'national interest ' is determined. Short run flexibility deals with operational characteristics, the degree to which particular projects may respond to changing demands when the basic investment is already in place. The tension between flexibility and cost is noted. A short case study on the choice of electricity generating plant is presented. The thesis concludes with a brief examination of the approaches used by successive British governments to public sector investment, particularly in relation to the nationalised industries

A reevaluation of achromatic spatio-temporal vision: nonoriented filters are monocular, they adapt, and can be used for decision making at high flicker speeds

Masking, adaptation, and summation paradigms have been used to investigate the characteristics of early spatio-temporal vision. Each has been taken to provide evidence for (i) oriented and (ii) nonoriented spatial-filtering mechanisms. However, subsequent findings suggest that the evidence for nonoriented mechanisms has been misinterpreted: those experiments might have revealed the characteristics of suppression (eg, gain control), not excitation, or merely the isotropic subunits of the oriented detecting mechanisms. To shed light on this, we used all three paradigms to focus on the ‘high-speed’ corner of spatio-temporal vision (low spatial frequency, high temporal frequency), where cross-oriented achromatic effects are greatest. We used flickering Gabor patches as targets and a 2IFC procedure for monocular, binocular, and dichoptic stimulus presentations. To account for our results, we devised a simple model involving an isotropic monocular filter-stage feeding orientation-tuned binocular filters. Both filter stages are adaptable, and their outputs are available to the decision stage following nonlinear contrast transduction. However, the monocular isotropic filters (i) adapt only to high-speed stimuli—consistent with a magnocellular subcortical substrate—and (ii) benefit decision making only for high-speed stimuli (ie, isotropic monocular outputs are available only for high-speed stimuli). According to this model, the visual processes revealed by masking, adaptation, and summation are related but not identical.

Planning and decision-making for energy recovery from waste at the sub-regional level

This research project has developed a novel decision support system using Geographical Information Systems and Multi Criteria Decision Analysis and used it to develop and evaluate energy-from-waste policy options. The system was validated by applying it to the UK administrative areas of Cornwall and Warwickshire. Different strategies have been defined by the size and number of the facilities, as well as the technology chosen. Using sensitivity on the results from the decision support system, it was found that key decision criteria included those affected by cost, energy efficiency, transport impacts and air/dioxin emissions. The conclusions of this work are that distributed small-scale energy-from-waste facilities score most highly overall and that scale is more important than technology design in determining overall policy impact. This project makes its primary contribution to energy-from-waste planning by its development of a Decision Support System that can be used to assist waste disposal authorities to identify preferred energy-from-waste options that have been tailored specifically to the socio-geographic characteristics of their jurisdictional areas. The project also highlights the potential of energy-from-waste policies that are seldom given enough attention to in the UK, namely those of a smaller-scale and distributed nature that often have technology designed specifically to cater for this market.

Does reviewing lead to better learning and decision making? Answers from a randomized stock market experiment

Background - The literature is not univocal about the effects of Peer Review (PR) within the context of constructivist learning. Due to the predominant focus on using PR as an assessment tool, rather than a constructivist learning activity, and because most studies implicitly assume that the benefits of PR are limited to the reviewee, little is known about the effects upon students who are required to review their peers. Much of the theoretical debate in the literature is focused on explaining how and why constructivist learning is beneficial. At the same time these discussions are marked by an underlying presupposition of a causal relationship between reviewing and deep learning. Objectives - The purpose of the study is to investigate whether the writing of PR feedback causes students to benefit in terms of: perceived utility about statistics, actual use of statistics, better understanding of statistical concepts and associated methods, changed attitudes towards market risks, and outcomes of decisions that were made. Methods - We conducted a randomized experiment, assigning students randomly to receive PR or non–PR treatments and used two cohorts with a different time span. The paper discusses the experimental design and all the software components that we used to support the learning process: Reproducible Computing technology which allows students to reproduce or re–use statistical results from peers, Collaborative PR, and an AI–enhanced Stock Market Engine. Results - The results establish that the writing of PR feedback messages causes students to experience benefits in terms of Behavior, Non–Rote Learning, and Attitudes, provided the sequence of PR activities are maintained for a period that is sufficiently long.

Design of a novel solar thermal collector using a multi-criteria decision-making methodology

Three novel solar thermal collector concepts derived from the Linear Fresnel Reflector (LFR) are developed and evaluated through a multi-criteria decision-making methodology, comprising the following techniques: Quality Function Deployment (QFD), the Analytical Hierarchy Process (AHP) and the Pugh selection matrix. Criteria are specified by technical and customer requirements gathered from Gujarat, India. The concepts are compared to a standard LFR for reference, and as a result, a novel 'Elevation Linear Fresnel Reflector' (ELFR) concept using elevating mirrors is selected. A detailed version of this concept is proposed and compared against two standard LFR configurations, one using constant and the other using variable horizontal mirror spacing. Annual performance is analysed for a typical meteorological year. Financial assessment is made through the construction of a prototype. The novel LFR has an annual optical efficiency of 49% and increases exergy by 13-23%. Operational hours above a target temperature of 300 C are increased by 9-24%. A 17% reduction in land usage is also achievable. However, the ELFR suffers from additional complexity and a 16-28% increase in capital cost. It is concluded that this novel design is particularly promising for industrial applications and locations with restricted land availability or high land costs. The decision analysis methodology adopted is considered to have a wider potential for applications in the fields of renewable energy and sustainable design. © 2013 Elsevier Ltd. All rights reserved.

Too old to choose? The effects of age and age related constructs on consumer decision making

Ageing of societies is a major challenge to academic research as well as to management. The unstoppable trend of an aging society in most western societies offers opportunities and challenges at the same time. This paper sheds light on the impact of age as well as age-related constructs on relevant consumer attitudes and behavior. More precisely, the empirical study, conducted in the market for cars, examining the relationships between four distinct age constructs and assesses the impact of these age constructs on information gathering, a consumer’s evoked set, and on rand loyalty.

ICT and internet use at the household levels:a melting pot of sub-optimum decision making in the case of E-Grocery shopping

Research shows that consumers are readily embracing the Internet to buy products. This paper proposes that, in the case of grocery shopping, this may lead to sub-optimal decisions at the household level. Decisions online on what, where and from who to buy are normally taken by one individual. In the case of grocery shopping, decisions, however, need to be ‘vetted’ by ‘other’ individuals within the household. The ‘household wide related’ decisions influence how information technologies and systems for commerce should be designed and managed for optimum decision making. This paper argues, unlike previous research, that e-grocery retailing is failing to grow to its full potential not solely because of the ‘classical’ hazards and perceived risks associated with doing grocery shopping online but because e-grocery retailing strategy has failed to acknowledge the micro-household level specificities that affect decision making. Our exploratory research is based on empirical evidence which were collected through telephone interviews. We offer an insight into how e-grocery ‘fits’ and is ‘disrupted’ by the reality of day to day consumption decision making at the household level. Our main finding is to advocate a more role-neutral, multi-user and multi-technology approach to e-grocery shopping which re-defines the concept of the main shopper/decision maker thereby reconceptualising the ‘shopping logic’ for grocery products.

Arms, bending discounting functions:how motor actions affect intertemporal decision-making

We demonstrate that task-irrelevant somatic activity influences intertemporal decision making: Arm movements associated with approach (arm flexion), rather than avoidance (arm extension), instigate present-biased preferences. The effect is moderated by the sensitivity of the general reward system and, owing to learning principles, restricted to arm positions of the dominant hand.

Minimizing nasty surprises with better informed decision-making in self-adaptive systems

Designers of self-adaptive systems often formulate adaptive design decisions, making unrealistic or myopic assumptions about the system's requirements and environment. The decisions taken during this formulation are crucial for satisfying requirements. In environments which are characterized by uncertainty and dynamism, deviation from these assumptions is the norm and may trigger 'surprises'. Our method allows designers to make explicit links between the possible emergence of surprises, risks and design trade-offs. The method can be used to explore the design decisions for self-adaptive systems and choose among decisions that better fulfil (or rather partially fulfil) non-functional requirements and address their trade-offs. The analysis can also provide designers with valuable input for refining the adaptation decisions to balance, for example, resilience (i.e. Satisfiability of non-functional requirements and their trade-offs) and stability (i.e. Minimizing the frequency of adaptation). The objective is to provide designers of self adaptive systems with a basis for multi-dimensional what-if analysis to revise and improve the understanding of the environment and its effect on non-functional requirements and thereafter decision-making. We have applied the method to a wireless sensor network for flood prediction. The application shows that the method gives rise to questions that were not explicitly asked before at design-time and assists designers in the process of risk-aware, what-if and trade-off analysis.

A method for systematic artifact selection decision making

Artifact selection decisions typically involve the selection of one from a number of possible/candidate options (decision alternatives). In order to support such decisions, it is important to identify and recognize relevant key issues of problem solving and decision making (Albers, 1996; Harris, 1998a, 1998b; Jacobs & Holten, 1995; Loch & Conger, 1996; Rumble, 1991; Sauter, 1999; Simon, 1986). Sauter classifies four problem solving/decision making styles: (1) left-brain style, (2) right-brain style, (3) accommodating, and (4) integrated (Sauter, 1999). The left-brain style employs analytical and quantitative techniques and relies on rational and logical reasoning. In an effort to achieve predictability and minimize uncertainty, problems are explicitly defined, solution methods are determined, orderly information searches are conducted, and analysis is increasingly refined. Left-brain style decision making works best when it is possible to predict/control, measure, and quantify all relevant variables, and when information is complete. In direct contrast, right-brain style decision making is based on intuitive techniques—it places more emphasis on feelings than facts. Accommodating decision makers use their non-dominant style when they realize that it will work best in a given situation. Lastly, integrated style decision makers are able to combine the left- and right-brain styles—they use analytical processes to filter information and intuition to contend with uncertainty and complexity.

Developing a forest data portal to support multi-scale decision making

Forests play a pivotal role in timber production, maintenance and development of biodiversity and in carbon sequestration and storage in the context of the Kyoto Protocol. Policy makers and forest experts therefore require reliable information on forest extent, type and change for management, planning and modeling purposes. It is becoming increasingly clear that such forest information is frequently inconsistent and unharmonised between countries and continents. This research paper presents a forest information portal that has been developed in line with the GEOSS and INSPIRE frameworks. The web portal provides access to forest resources data at a variety of spatial scales, from global through to regional and local, as well as providing analytical capabilities for monitoring and validating forest change. The system also allows for the utilisation of forest data and processing services within other thematic areas. The web portal has been developed using open standards to facilitate accessibility, interoperability and data transfer.

Supporting decision-making for self-adaptive systems:from goal models to dynamic decision networks

Context/Motivation - Different modeling techniques have been used to model requirements and decision-making of self-adaptive systems (SASs). Specifically, goal models have been prolific in supporting decision-making depending on partial and total fulfilment of functional (goals) and non-functional requirements (softgoals). Different goalrealization strategies can have different effects on softgoals which are specified with weighted contribution-links. The final decision about what strategy to use is based, among other reasons, on a utility function that takes into account the weighted sum of the different effects on softgoals. Questions/Problems - One of the main challenges about decisionmaking in self-adaptive systems is to deal with uncertainty during runtime. New techniques are needed to systematically revise the current model when empirical evidence becomes available from the deployment. Principal ideas/results - In this paper we enrich the decision-making supported by goal models by using Dynamic Decision Networks (DDNs). Goal realization strategies and their impact on softgoals have a correspondence with decision alternatives and conditional probabilities and expected utilities in the DDNs respectively. Our novel approach allows the specification of preferences over the softgoals and supports reasoning about partial satisfaction of softgoals using probabilities. We report results of the application of the approach on two different cases. Our early results suggest the decision-making process of SASs can be improved by using DDNs. © 2013 Springer-Verlag.

Real options in management and organizational strategy:a review of decision-making and performance implications

This paper contributes to the debate on the role of real options theory in business strategy and organizational decision-making. It analyses and critiques the decision-making and performance implications of real options within the management theories of the (multinational) firm, reviews and categorizes the organizational, strategic and operational facets of real options management in large business settings. It also presents the views of scholars and practitioners regarding the incorporation and validity of real options in strategy, international management and business processes. The focus is particularly on the decision-making and performance attributes of the real options logic concerning strategic investments, governance modes and multinational operations management. These attributes are examined from both strategic and operating perspectives of decision-making in organizations, also with an overview of the empirical evidence on real options decision-making and performance.

Real options in multinational decision-making:managerial awareness and risk implications

This paper addresses the theme of real options decision-making in multinational corporations (MNCs) and stresses the role of real options attention and managerial learning in company performance. Using a sample of 278 large MNCs with categorised degrees of managerial real options awareness, we examine the risk implications of switching options in multinational operations, and explore the extent to which the real options logic can be classified as “best practice” in decision-making and risk management. Our results reveal that MNCs which have high managerial awareness about their real options are able to reduce their downside risk through multinationality, organisational slack and other firm characteristics. This finding does not apply fully to MNCs without evidence of such an awareness. Also, although real options awareness does not systematically guarantee lower downside risk from operations, supplementary results indicate that MNCs with evidence of significant investment in the acquisition of real options knowledge tend to outperform competitors that are unaware of their real options. This suggests that if real options are explored and exploited appropriately, real options decision-making can result into superior performance for MNCs in the long-term.