Decision support system for risk management:a case study

This study demonstrates a quantitative approach to construction risk management through analytic hierarchy process and decision tree analysis. All the risk factors are identified, their effects are quantified by determining probability and severity, and various alternative responses are generated with cost implication for mitigating the quantified risks. The expected monetary values are then derived for each alternative in a decision tree framework and subsequent probability analysis aids the decision process in managing risks. The entire methodology is explained through a case application of a cross-country petroleum pipeline project in India and its effectiveness in project management is demonstrated.

Whole life performance bid evaluation in the Korean public sector

Korea has increasingly adopted design-build for public construction projects in the last few years. There is a much greater awareness of the need to change a system based on ‘Value for Money’ which is high on the government's agenda. A whole life performance bid evaluation model is proposed to aid decision makers in the selection of a design-builder. This is based on the integration of a framework using an analytic hierarchy process as the bid awarding system is being changed from one based on lowest price, to one based on best value over the life-cycle. Key criteria like whole life cost, service life planning and design quality are important through the key stages of evaluation process. The model uses a systematic and holistic approach which enables a public sector to make better decisions in design-builder selection, which will deliver whole life benefits, based on long term cost-effectiveness and whole life.

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.

Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector

Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

Multiple criteria decision-making techniques in higher education

Purpose: The purpose of this paper is to review the literature which focuses on four major higher education decision problems. These are: resource allocation; performance measurement; budgeting; and scheduling. Design/methodology/approach: Related articles appearing in the international journals from 1996 to 2005 are gathered and analyzed so that the following three questions can be answered: "What kind of decision problems were paid most attention to?"; "Were the multiple criteria decision-making techniques prevalently adopted?"; and "What are the inadequacies of these approaches?" Findings: Based on the inadequacies, some improvements and possible future work are recommended, and a comprehensive resource allocation model is developed taking account of these factors. Finally, a new knowledge-based goal programming technique which integrates some operations of analytic hierarchy process is proposed to tackle the model intelligently. Originality/value: Higher education has faced the problem of budget cuts or constrained budgets for the past 30 years. Managing the process of the higher education system is, therefore, a crucial and urgent task for the decision makers of universities in order to improve their performance or competitiveness. © Emerald Group Publishing Limited.

Risk-based model aids selection of pipeline inspection, maintenance strategies

The existing method of pipeline monitoring, which requires an entire pipeline to be inspected periodically, wastes time and is expensive. A risk-based model that reduces the amount of time spent on inspection has been developed. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction method and logical insurance plans.The risk-based model uses analytic hierarchy process, a multiple attribute decision-making technique, to identify factors that influence failure on specific segments and analyze their effects by determining the probabilities of risk factors. The severity of failure is determined through consequence analysis, which establishes the effect of a failure in terms of cost caused by each risk factor and determines the cumulative effect of failure through probability analysis.

Planning for project control through risk analysis:a case of petroleum pipeline laying

Projects that are exposed to uncertain environments can be effectively controlled with the application of risk analysis during the planning stage. The Analytic Hierarchy Process, a multiattribute decision-making technique, can be used to analyse and assess project risks which are objective or subjective in nature. Among other advantages, the process logically integrates the various elements in the planning process. The results from risk analysis and activity analysis are then used to develop a logical contingency allowance for the project through the application of probability theory. The contingency allowance is created in two parts: (a) a technical contingency, and (b) a management contingency. This provides a basis for decision making in a changing project environment. Effective control of the project is made possible by the limitation of the changes within the monetary contingency allowance for the work package concerned, and the utilization of the contingency through proper appropriation. The whole methodology is applied to a pipeline-laying project in India, and its effectiveness in project control is demonstrated.

Strategic supplier performance evaluation:a case-based action research of a UK manufacturing organisation

The main aim of this research is to demonstrate strategic supplier performance evaluation of a UK-based manufacturing organisation using an integrated analytical framework. Developing long term relationship with strategic suppliers is common in today's industry. However, monitoring suppliers' performance all through the contractual period is important in order to ensure overall supply chain performance. Therefore, client organisations need to measure suppliers' performance dynamically and inform them on improvement measures. Although there are many studies introducing innovative supplier performance evaluation frameworks and empirical researches on identifying criteria for supplier evaluation, little has been reported on detailed application of strategic supplier performance evaluation and its implication on overall performance of organisation. Additionally, majority of the prior studies emphasise on lagging factors (quality, delivery schedule and value/cost) for supplier selection and evaluation. This research proposes both leading (organisational practices, risk management, environmental and social practices) and lagging factors for supplier evaluation and demonstrates a systematic method for identifying those factors with the involvement of relevant stakeholders and process mapping. The contribution of this article is a real-life case-based action research utilising an integrated analytical model that combines quality function deployment and the analytic hierarchy process method for suppliers' performance evaluation. The effectiveness of the method has been demonstrated through number of validations (e.g. focus group, business results, and statistical analysis). Additionally, the study reveals that enhanced supplier performance results positive impact on operational and business performance of client organisation.

Which is the best solar thermal collection technology for electricity generation in north-west India? Evaluation of options using the analytical hierarchy process

This study of concentrating solar thermal power generation sets out to evaluate the main existing collection technologies using the framework of the Analytical Hierarchy Process (AHP). It encompasses parabolic troughs, heliostat fields, linear Fresnel reflectors, parabolic dishes, compound parabolic concentrators and linear Fresnel lenses. These technologies are compared based on technical, economic and environmental criteria. Within these three categories, numerous sub-criteria are identified; similarly sub-alternatives are considered for each technology. A literature review, thermodynamic calculations and an expert workshop have been used to arrive at quantitative and qualitative assessments. The methodology is applied principally to a case study in Gujarat in north-west India, though case studies based on the Sahara Desert, Southern Spain and California are included for comparison. A sensitivity analysis is carried out for Gujarat. The study concludes that the linear Fresnel lens with a secondary compound parabolic collector, or the parabolic dish reflector, is the preferred technology for north-west India.

Cloud adoption:prioritizing obstacles and obstacles resolution tactics using AHP

The enormous potential of cloud computing for improved and cost-effective service has generated unprecedented interest in its adoption. However, a potential cloud user faces numerous risks regarding service requirements, cost implications of failure and uncertainty about cloud providers' ability to meet service level agreements. These risks hinder the adoption of cloud. We extend the work on goal-oriented requirements engineering (GORE) and obstacles for informing the adoption process. We argue that obstacles prioritisation and their resolution is core to mitigating risks in the adoption process. We propose a novel systematic method for prioritising obstacles and their resolution tactics using Analytical Hierarchy Process (AHP). We provide an example to demonstrate the applicability and effectiveness of the approach. To assess the AHP choice of the resolution tactics we support the method by stability and sensitivity analysis. Copyright 2014 ACM.

Project risk management in analytic framework

Risks and uncertainties are part and parcel of any project as projects are planned with many assumptions. Therefore, managing those risks is the key to project success. Although risk is present in all most all projects, large-scale construction projects are most vulnerable. Risk is by nature subjective. However, managing risk subjectively posses the danger of non-achievement of project goals. This study introduces an analytical framework for managing risk in projects. All the risk factors are identified, their effects are analyzed, and alternative responses are derived with cost implication for mitigating the identified risks. A decision-making framework is then formulated using decision tree. The expected monetary values are derived for each alternative. The responses, which require least cost is selected. The entire methodology has been explained through a case study of an oil pipeline project in India and its effectiveness in managing projects has been demonstrated. © INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING.

Watch that space! The county hierarchy in firm births and deaths in the UK, 1980-1999

The paper investigates the relationships between registrations, de-registrations and population density at county level in the UK using VAT data for 20 years over the period 1980–1999. The rationale for this is based on the need to understand how the extent to which, in different parts of the UK, differences in the relationship between birth rates and death rates combine to produce an interpretable pattern in net birth rates. The analysis of the net birth rate shows that a strategy aimed at the net birth rate might, in principle, just as well aim at reducing business failure, rather than raising the birth rate. Indeed this might be more efficient, since it implies that less start-ups are ‘‘wasted’’ as it would avoid the necessity, if targets are to be reached, of encouraging those individuals who are patently unsuited to running their own business into business ownership.

The representation of majorities and minorities in the British Press:a content analytic approach

A content analysis examined the way majorities and minorities are represented in the British press. An analysis of the headlines of five British newspapers, over a period of five years, revealed that the words ‘majority’ and ‘minority’ appeared 658 times. Majority headlines were most frequent (66% ), more likely to emphasize the numerical size of the majority, to link majority status with political groups, to be described with positive evaluations, and to cover political issues. By contrast, minority headlines were less frequent (34%), more likely to link minority status with ethnic groups and to other social issues, and less likely to be described with positive evaluations. The implications of examining how real-life majorities and minorities are represented for our understanding of experimental research are discussed.

Understanding learning strategies in the workplace:a factor analytic investigation

The aim of this study was to validate a scale of learning strategies, as derived from the educational literature, in an organizational context. Participants were 628 call centre employees. Both exploratory and confirmatory factor analyses suggested that a six-factor structure most accurately represented the learning strategies examined. Specifically, three cognitive (extrinsic work reflection, intrinsic work reflection, reproduction) and three behavioural strategies (interpersonal help seeking, help seeking from written material, practical application) were found.

Meta-analytic model comparisons of surface- and deep-level relational diversity effects on social integration and individual effectiveness

While diversity might give an organization a competitive advantage, individuals have a tendency to prefer homogenous group settings. Prior research suggests that group members who are dissimilar (vs. similar) to their peers in terms of a given diversity attribute (e.g. demographics, attitudes, values or traits) feel less attached to their work group, experience less satisfying and more conflicted relationships with their colleagues, and consequently are less effective. However, prior empirical findings tend to be weak and inconsistent, and it remains unclear when, how and to what extent such differences affect group members’ social integration (i.e. attachment with their work group, satisfaction and conflicted relationships with their peers) and effectiveness. To address these issues the current study conducted a meta-analysis and integrated the empirical results of 129 studies. For demographic diversity attributes (such as gender, ethnicity, race, nationality, age, functional background, and tenure) the findings support the idea that demographic dissimilarity undermines individual member performance via lower levels of social integration. These negative effects were more pronounced in pseudo teams – i.e. work groups in which group members pursue individual goals, work on individual tasks, and are rewarded for their individual performance. These negative effects were however non-existent in real teams - i.e. work groups in which groups members pursue group goals, work on interdependent tasks, and are rewarded (at least partially) based on their work group’s performance. In contrast, for underlying psychological diversity attributes (such as attitudes, personality, and values), the relationship between dissimilarity and social integration was more negative in real teams than in pseudo teams, which in return translated into even lower individual performance. At the same time however, differences in underlying psychological attributes had an even stronger positive effect on dissimilar group member’s individual performance, when the negative effects of social integration were controlled for. This implies that managers should implement real work groups to overcome the negative effects of group member’s demographic dissimilarity. To harness the positive effects of group members’ dissimilarity on underlying psychological attributes, they need to make sure that dissimilar group members become socially integrated.