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.

New dimensions on the economics of the entrepreneurial process

This thesis examines the transition of employees into entrepreneurship, with particular emphasis on the role of workplace characteristics in influencing this movement. The first main chapter examines whether the determinants of becoming an intrapreneur differ from those that support transitions into independent entrepreneurship. The results show that intrapreneurs resemble employees rather than entrepreneurs, contrary to what the entrepreneurship theory would suggest. Yet it shows that those intrapreneurs that expect to acquire an ownership stake in the business, unlike the rest of intrapreneurs, possess traditional entrepreneurial traits. Chapter 3 investigates how workers’ degree of specialisation determines their decision to found a firm. It shows that entrepreneurs emerging from small firms, i.e. generalists, transfer knowledge from more diverse aspects of the business and create firms more related to the main activity of their last employer. Workers in large firms, however, benefit from higher returns to human capital that increase their opportunity costs to switch to entrepreneurship. Since becoming an entrepreneur would make part of their specialised skills unutilised, the minimum quality of the idea at which they would be willing to leave will be higher and, therefore, entrepreneurs emerging from large firms will be of highest quality. Chapter 4 analyses whether the reason to terminate an employment contract is associated with the fact that the majority of entrepreneurs appear to set up their business after having worked for a small firm. Moreover, it studies how this pattern varies as the labour market conditions worsen. The effect of layoffs turns out to be a key driver in the entry to entrepreneurship and it is found to exert a greater effect the smaller the firm workers are dismissed from. This has been reflected in an overall larger flow of employees from small firms moving into entrepreneurship over the recession.

Opportunity, fair process and relationship value:career development as a driver of proactive work behaviour

In line with recent findings from organisational justice theory, we hypothesised that employee proactive behaviour and careerist orientation is predicted by the interplay of perceived favourability of career development opportunities, the perceived fairness of the procedures used to decide them, and employee organisational commitment. Employees (N = 325) of a large financial services organisation responded to a self-completion questionnaire. As predicted, when career development opportunities were viewed unfavourably, perceived procedural justice was significantly and positively related to individual proactive behaviour and significantly and negatively related to careerist orientation but only when organisational commitment was high. It appears that high procedural justice may only 'offset' the negative effects of unfavourable career development opportunities when employees identify with, and are committed to, their organisation. Further support is presented for a relational, rather than instrumental, model of procedural justice when reflecting on employee reactions to their employers' policies and decision-making. Implications for theory and practice are discussed.

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.

Green supply chain performance measurement using the analytic hierarchy process:a comparative analysis of manufacturing organisations

The main purpose of this research is to develop and deploy an analytical framework for measuring the environmental performance of manufacturing supply chains. This work's theoretical bases combine and reconcile three major areas: supply chain management, environmental management and performance measurement. Researchers have suggested many empirical criteria for green supply chain (GSC) performance measurement and proposed both qualitative and quantitative frameworks. However, these are mainly operational in nature and specific to the focal company. This research develops an innovative GSC performance measurement framework by integrating supply chain processes (supplier relationship management, internal supply chain management and customer relationship management) with organisational decision levels (both strategic and operational). Environmental planning, environmental auditing, management commitment, environmental performance, economic performance and operational performance are the key level constructs. The proposed framework is then applied to three selected manufacturing organisations in the UK. Their GSC performance is measured and benchmarked by using the analytic hierarchy process (AHP), a multiple-attribute decision-making technique. The AHP-based framework offers an effective way to measure and benchmark organisations’ GSC performance. This study has both theoretical and practical implications. Theoretically it contributes holistic constructs for designing a GSC and managing it for sustainability; and practically it helps industry practitioners to measure and improve the environmental performance of their supply chain. © 2013 Copyright Taylor and Francis Group, LLC. CORRIGENDUM DOI 10.1080/09537287.2012.751186 In the article ‘Green supply chain performance measurement using the analytic hierarchy process: a comparative analysis of manufacturing organisations’ by Prasanta Kumar Dey and Walid Cheffi, Production Planning & Control, 10.1080/09537287.2012.666859, a third author is added which was not included in the paper as it originally appeared. The third author is Breno Nunes.

Flexible measures in production process:a DEA-based approach

Data envelopment analysis (DEA) has been proven as an excellent data-oriented efficiency analysis method for comparing decision making units (DMUs) with multiple inputs and multiple outputs. In conventional DEA, it is assumed that the status of each measure is clearly known as either input or output. However, in some situations, a performance measure can play input role for some DMUs and output role for others. Cook and Zhu [Eur. J. Oper. Res. 180 (2007) 692–699] referred to these variables as flexible measures. The paper proposes an alternative model in which each flexible measure is treated as either input or output variable to maximize the technical efficiency of the DMU under evaluation. The main focus of this paper is on the impact that the flexible measures has on the definition of the PPS and the assessment of technical efficiency. An example in UK higher education intuitions shows applicability of the proposed approach.

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.

Extreme events, organizations and the politics of decision making

Purpose – Threats of extreme events, such as terrorist attacks or infrastructure breakdown, are potentially highly disruptive events for all types of organizations. This paper seeks to take a political perspective to power in strategic decision making and how this influences planning for extreme events. Design/methodology/approach – A sample of 160 informants drawn from 135 organizations, which are part of the critical national infrastructure in the UK, forms the empirical basis of the paper. Most of these organizations had publicly placed business continuity and preparedness as a strategic priority. The paper adopts a qualitative approach, coding data from focus groups. Findings – In nearly all cases there is a pre-existing dominant coalition which keeps business continuity decisions off the strategic agenda. The only exceptions to this are a handful of organizations which provide continuous production, such as some utilities, where disruption to business as usual can be readily quantified. The data reveal structural and decisional elements of the exercise of power. Structurally, the dominant coalition centralizes control by ensuring that only a few functional interests participate in decision making. Research limitations/implications – Decisional elements of power emphasize the dominance of calculative rationality where decisions are primarily made on information and arguments which can be quantified. Finally, the paper notes the recursive aspect of power relations whereby agency and structure are mutually constitutive over time. Organizational structures of control are maintained, despite the involvement of managers charged with organizational preparedness and resilience, who remain outside the dominant coalition. Originality/value – The paper constitutes a first attempt to show how planning for emergencies fits within the strategy-making process and how politically controlled this process is.

Intuition in strategic decision making:implications for strategic decision effectiveness

Intuition can produce effective strategic decisions because of its speed and ability to solve less-structured problems. Despite this, there are only a very small number of empirical studies that have examined intuition in the strategic decision-making process. We examine the relationship between the use of intuition in the strategic decision-making process, and strategic decision effectiveness. We propose that the expertise of the decision-maker, environmental dynamism and the characteristics of the strategic decision itself moderate the relationship between the use of intuition in the strategic decision making process, and strategic decision effectiveness. We make a significant theoretical contribution by integrating the management and social-psychology literatures in order to identify the variables that affect the relationship between the use of intuition in the strategic decision-making process, and strategic decision effectiveness. This article builds upon existing empirical research that has examined intuition in the strategic decision-making process, and reconciles some of the confounding results that have emerged. The paper presents a conceptual model and research propositions, which if empirically examined, would make a significant contribution to knowledge in the strategic decision-making domain of literature.

Green supply chain performance measurement using fuzzy ANP-based balanced scorecard:a collaborative decision-making approach

The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firms decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers performances meet the industry and environment standards with effective human resource. © 2013 Taylor & Francis.

Strategic decision making in small businesses:implications for strategic flexibility and strategic adaptation

Strategic decision making (SDM) in a small business is an informal, highly personalised cognitive process which is emergent in nature. SDM determines the extent to which decision makers generate innovative decision-making options, and is therefore critical in order for small businesses to achieve strategic flexibility to enable strategic adaptation to turbulent environments. By examining SDM in small businesses, this research has the potential to address a major criticism of the extant literature in that it has been pre-occupied with measuring the formality of strategic planning and has neglected the informal, highly personalised and cognitive nature of strategic decision making in a small businesses.

An examination of intuition in strategic decision-making:the role of context

Intuition is a vitally important concept in strategic decision making research because it enables decision-makers to rapidly detect patterns in dynamic environments in order to cope with the time-pressured, ill-structured and non-routine nature of strategic decision-making. Despite a growing body of conceptual literature emphasising the importance of intuition in strategic decision-making; there has been very little development of theory explaining the contextual factors that cause intuition to be used in the strategic decision-making process. This paper demonstrates that by integrating different contextual variables a clear understanding of the influences on the use of intuition in strategic decision-making can be developed. This article develops an integrative theoretical model together with testable research propositions, which if empirically examined, would make a substantial contribution to knowledge.

The influence of patient's age on clinical decision-making about coronary heart disease in the USA and the UK

This paper examines UK and US primary care doctors' decision-making about older (aged 75 years) and midlife (aged 55 years) patients presenting with coronary heart disease (CHD). Using an analytic approach based on conceptualising clinical decision-making as a classification process, it explores the ways in which doctors' cognitive processes contribute to ageism in health-care at three key decision points during consultations. In each country, 56 randomly selected doctors were shown videotaped vignettes of actors portraying patients with CHD. The patients' ages (55 or 75 years), gender, ethnicity and social class were varied systematically. During the interviews, doctors gave free-recall accounts of their decision-making. The results do not establish that there was substantial ageism in the doctors' decisions, but rather suggest that diagnostic processes pay insufficient attention to the significance of older patients' age and its association with the likelihood of co-morbidity and atypical disease presentations. The doctors also demonstrated more limited use of 'knowledge structures' when diagnosing older than midlife patients. With respect to interventions, differences in the national health-care systems rather than patients' age accounted for the differences in doctors' decisions. US doctors were significantly more concerned about the potential for adverse outcomes if important diagnoses were untreated, while UK general practitioners cited greater difficulty in accessing diagnostic tests.