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.

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.

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.

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.

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.

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.

The measurement properties of the menorrhagia multi-attribute quality-of-life scale:a psychometric analysis

Menorrhagia, or heavy menstrual bleeding (HMB), is a common gynaecological condition. As the aim of treatment is to improve women's wellbeing and quality of life (QoL), it is necessary to have effective ways to measure this. This study investigated the reliability and validity of the menorrhagia multi-attribute scale (MMAS), a menorrhagia-specific QoL instrument. Participants (n = 431) completed the MMAS and a battery of other tests as part of the baseline assessment of the ECLIPSE (Effectiveness and Cost-effectiveness of Levonorgestrel-containing Intrauterine system in Primary care against Standard trEatment for menorrhagia) trial. Analyses of their responses suggest that the MMAS has good measurement properties and is therefore an appropriate condition-specific instrument to measure the outcome of treatment for HMB. © 2011 The Authors BJOG An International Journal of Obstetrics and Gynaecology © 2011 RCOG.

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.

Dynamic decision networks for decision-making in self-adaptive systems:a case study

Bayesian decision theory is increasingly applied to support decision-making processes under environmental variability and uncertainty. Researchers from application areas like psychology and biomedicine have applied these techniques successfully. However, in the area of software engineering and speci?cally in the area of self-adaptive systems (SASs), little progress has been made in the application of Bayesian decision theory. We believe that techniques based on Bayesian Networks (BNs) are useful for systems that dynamically adapt themselves at runtime to a changing environment, which is usually uncertain. In this paper, we discuss the case for the use of BNs, speci?cally Dynamic Decision Networks (DDNs), to support the decision-making of self-adaptive systems. We present how such a probabilistic model can be used to support the decision making in SASs and justify its applicability. We have applied our DDN-based approach to the case of an adaptive remote data mirroring system. We discuss results, implications and potential bene?ts of the DDN to enhance the development and operation of self-adaptive systems, by providing mechanisms to cope with uncertainty and automatically make the best decision.

Project risk management using multiple criteria decision-making technique and decision tree analysis:a case study of Indian oil refinery

This study proposes an integrated analytical framework for effective management of project risks using combined multiple criteria decision-making technique and decision tree analysis. First, a conceptual risk management model was developed through thorough literature review. The model was then applied through action research on a petroleum oil refinery construction project in the Central part of India in order to demonstrate its effectiveness. Oil refinery construction projects are risky because of technical complexity, resource unavailability, involvement of many stakeholders and strict environmental requirements. Although project risk management has been researched extensively, practical and easily adoptable framework is missing. In the proposed framework, risks are identified using cause and effect diagram, analysed using the analytic hierarchy process and responses are developed using the risk map. Additionally, decision tree analysis allows modelling various options for risk response development and optimises selection of risk mitigating strategy. The proposed risk management framework could be easily adopted and applied in any project and integrated with other project management knowledge areas.

The interactive effects of mood and trait negative affect in group decision making

Extending the growing interest in affect in work groups, we propose that groups with distributed information make higher quality decisions when they are in a negative rather than a positive mood, but that these effects are moderated by group members' trait negative affect. In support of this hypothesis, an experiment (N = 175 groups) showed that positive mood led to lower quality decisions than did negative or neutral moods when group members were low in trait negative affect, whereas such mood effects were not observed in groups higher in trait negative affect. Mediational analysis based on behavioral observations of group process confirmed that group information elaboration mediated this effect. These results provide an important caveat on the benefits of positive moods in work groups, and suggest that the study of trait × state affect interactions is an important avenue for future research.