Improving decision-making in the EU. CHALLENGE EUROPE Issue 22 - Challenges and new beginnings: Priorities for the EU's new leadership, September 2014.

The multiple crises the European Union (EU) has experienced in recent years have fundamentally altered decision-making and, more broadly, governance in the EU. Pre-crisis systems and processes were not adequate to react to such critical and systemic challenges, but the speed of the crisis meant that new governance mechanisms have been superimposed on existing processes and structures rather than seeing a fundamental reform of decision-making. Consequently, not all changes have been fully successful. Given the institutional changes this year and the ongoing development of the EMU governance framework, now presents a good opportunity to reform EU decision-making.

Collaborative decision-making processes for maintaining biodiversity: Two Australian case studies

There have been many models developed by scientists to assist decision-makers in making socio-economic and environmental decisions. It is now recognised that there is a shift in the dominant paradigm to making decisions with stakeholders, rather than making decisions for stakeholders. Our paper investigates two case studies where group model building has been undertaken for maintaining biodiversity in Australia. The first case study focuses on preservation and management of green spaces and biodiversity in metropolitan Melbourne under the umbrella of the Melbourne 2030 planning strategy. A geographical information system is used to collate a number of spatial datasets encompassing a range of cultural and natural assets data layers including: existing open spaces, waterways, threatened fauna and flora, ecological vegetation covers, registered cultural heritage sites, and existing land parcel zoning. Group model building is incorporated into the study through eliciting weightings and ratings of importance for each datasets from urban planners to formulate different urban green system scenarios. The second case study focuses on modelling ecoregions from spatial datasets for the state of Queensland. The modelling combines collaborative expert knowledge and a vast amount of environmental data to build biogeographical classifications of regions. An information elicitation process is used to capture expert knowledge of ecoregions as geographical descriptions, and to transform this into prior probability distributions that characterise regions in terms of environmental variables. This prior information is combined with measured data on the environmental variables within a Bayesian modelling technique to produce the final classified regions. We describe how linked views between descriptive information, mapping and statistical plots are used to decide upon representative regions that satisfy a number of criteria for biodiversity and conservation. This paper discusses the advantages and problems encountered when undertaking group model building. Future research will extend the group model building approach to include interested individuals and community groups.

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.

An empirical examination of the strategic decision-making process:the relationship between context, process, and outcomes

Despite concerted academic interest in the strategic decision-making process (SDMP) since the 1980s, a coherent body of theory capable of guiding practice has not materialised. This is because many prior studies focus only on a single process characteristic, often rationality or comprehensiveness, and have paid insufficient attention to context. To further develop theory, research is required which examines: (i) the influence of context from multiple theoretical perspectives (e.g. upper echelons, environmental determinism); (ii) different process characteristics from both synoptic formal (e.g. rationality) and political incremental (e.g. politics) perspectives, and; (iii) the effects of context and process characteristics on a range of SDMP outcomes. Using data from 30 interviews and 357 questionnaires, this thesis addresses several opportunities for theory development by testing an integrative model which incorporates: (i) five SDMP characteristics representing both synoptic formal (procedural rationality, comprehensiveness, and behavioural integration) and political incremental (intuition, and political behaviour) perspectives; (ii) four SDMP outcome variables—strategic decision (SD) quality, implementation success, commitment, and SD speed, and; (iii) contextual variables from the four theoretical perspectives—upper echelons, SD-specific characteristics, environmental determinism, and firm characteristics. The present study makes several substantial and original contributions to knowledge. First, it provides empirical evidence of the contextual boundary conditions under which intuition and political behaviour positively influence SDMP outcomes. Second, it establishes the predominance of the upper echelons perspective; with TMT variables explaining significantly more variance in SDMP characteristics than SD specific characteristics, the external environment, and firm characteristics. A newly developed measure of top management team expertise also demonstrates highly significant direct and indirect effects on the SDMP. Finally, it is evident that SDMP characteristics and contextual variables influence a number of SDMP outcomes, not just overall SD quality, but also implementation success, commitment, and SD speed.

Classifying clinical decision making:a unifying approach

This is the first of two linked papers exploring decision making in nursing which integrate research evidence from different clinical and academic disciplines. Currently there are many decision-making theories, each with their own distinctive concepts and terminology, and there is a tendency for separate disciplines to view their own decision-making processes as unique. Identifying good nursing decisions and where improvements can be made is therefore problematic, and this can undermine clinical and organizational effectiveness, as well as nurses' professional status. Within the unifying framework of psychological classification, the overall aim of the two papers is to clarify and compare terms, concepts and processes identified in a diversity of decision-making theories, and to demonstrate their underlying similarities. It is argued that the range of explanations used across disciplines can usefully be re-conceptualized as classification behaviour. This paper explores problems arising from multiple theories of decision making being applied to separate clinical disciplines. Attention is given to detrimental effects on nursing practice within the context of multidisciplinary health-care organizations and the changing role of nurses. The different theories are outlined and difficulties in applying them to nursing decisions highlighted. An alternative approach based on a general model of classification is then presented in detail to introduce its terminology and the unifying framework for interpreting all types of decisions. The classification model is used to provide the context for relating alternative philosophical approaches and to define decision-making activities common to all clinical domains. This may benefit nurses by improving multidisciplinary collaboration and weakening clinical elitism.

Electronic information sharing in local government authorities:factors influencing the decision-making process

Local Government Authorities (LGAs) are mainly characterised as information-intensive organisations. To satisfy their information requirements, effective information sharing within and among LGAs is necessary. Nevertheless, the dilemma of Inter-Organisational Information Sharing (IOIS) has been regarded as an inevitable issue for the public sector. Despite a decade of active research and practice, the field lacks a comprehensive framework to examine the factors influencing Electronic Information Sharing (EIS) among LGAs. The research presented in this paper contributes towards resolving this problem by developing a conceptual framework of factors influencing EIS in Government-to-Government (G2G) collaboration. By presenting this model, we attempt to clarify that EIS in LGAs is affected by a combination of environmental, organisational, business process, and technological factors and that it should not be scrutinised merely from a technical perspective. To validate the conceptual rationale, multiple case study based research strategy was selected. From an analysis of the empirical data from two case organisations, this paper exemplifies the importance (i.e. prioritisation) of these factors in influencing EIS by utilising the Analytical Hierarchy Process (AHP) technique. The intent herein is to offer LGA decision-makers with a systematic decision-making process in realising the importance (i.e. from most important to least important) of EIS influential factors. This systematic process will also assist LGA decision-makers in better interpreting EIS and its underlying problems. The research reported herein should be of interest to both academics and practitioners who are involved in IOIS, in general, and collaborative e-Government, in particular. © 2013 Elsevier Ltd. All rights reserved.

Az online-fogyasztói elégedettség mérésére alkalmas skála tesztelése és véglegesítése a vállalati döntéshozók támogatása céljából (Testing and finalizing a scale for measuring online consumer satisfaction to support the companies decision making process)

A versenyképesség, illetve a gazdaságos működés elengedhetetlen feltétele a fogyasztói elégedettség, melynek egyik meghatározó eleme az észlelt és elvárt minőség közti kapcsolat. A minőségi elvárások az internettel, mint napjaink egyik meghatározó csatornájával kapcsolatban is megfogalmazódtak már, így kapott jelentős szerepet az online szolgáltatásminőség meghatározása, illetve ezzel összekapcsolódva az online-fogyasztói elégedettségmérés. A tanulmány célja, hogy szakirodalmi áttekintést nyújtson a témában, és a szakirodalomból ismert E-S-QUAL és E-RecS-QUAL online-fogyasztói elégedettségmérésre szolgáló skálát megvizsgálja, érvényességét a magyar körülmények között letesztelje, és a szükségesnek látszó módosítások elvégzésével egy Magyarországon használható skálát hozzon létre. Az online-fogyasztók elégedettségmérésének alapjaként az online szolgáltatásminőség fogyasztói érzékelésével, illetve értékelésével kapcsolatos elméleteket járja körbe a tanulmány, és ezután kerül sor a különböző mérési módszerek bemutatására, kiemelt szerepet szánva az E-S-QUAL és E-RecS-QUAL skálának, mely az egyik leginkább alkalmazott módszernek számít. Az áttekintés középpontjában azok a honlapok állnak, melyeken vásárolni is lehet, a kutatást pedig az egyik jelentős hazai online könyvesbolt ügyfélkörében végeztem el. ______ Over the last decade the business-to-consumer online market has been growing very fast. In marketing literature a lot of studies have been created focusing on understanding and measuring e-service quality (e-sq) and online-customer satisfaction. The aim of the study is to summarize these concepts, analyse the relationship between e-sq and customer’s loyalty, which increases the competitiveness of the companies, and to create a valid and reliable scale to the Hungarian market for measuring online-customer satisfaction. The base of the empirical study is the E-S-QUAL and its second scale the E-RecS-QUAL that are widely used multiple scales measuring e-sq with seven dimensions: efficiency, system availability, fulfilment, privacy, responsiveness, compensation, and contact. The study is focusing on the websites customers use to shop online.

Több szempontú részvételi döntések a fenntarthatósági értékelésekben. A legnépszerűbb módszerek összehasonlítása = Participatory multi-criteria decision analysis. A comparison of methodologies

A fenntarthatóság értékelése definíciószerűen többdimenziós probléma. A megfelelő alternatíva, forgatókönyv, eljárás stb. kiválasztásakor ugyanis a döntéshozóknak egyszerre kell figyelembe venniük környezetvédelmi, gazdasági és társadalmi szempontokat. Az ilyen döntéseket alátámaszthatják a több szempontú döntéshozatali modellek. A tanulmány a több szempontú döntési eljárások közül a legfontosabb hétnek az alkalmazhatóságát vizsgálja részvételi körülmények között. Az utóbbi évek e témában publikált esettanulmányainak áttekintésével megállapítható, hogy egyik módszer sem uralja a többit, azok különböző feltételek mellett eltérő sikerrel használhatók. Ennek ellenére a különböző módszerek kombinációjával végrehajthatunk olyan eljárásokat, amelyekkel az egyes módszerek előnyeit még jobban kiaknázhatjuk. ________ Measuring and comparing the sustainability of certain actions, scenarios, technologies, etc. is by definition a multidimensional problem. Decision-makers must consider environmental, economic and social aspects when choosing an alternative course of action. Such decisions can be aided by multi-criteria decision analysis (MCDA). This paper investigates seven different MCDA methodologies: MAU, the Analytic Hierarchic Process (AHP), the ELECTRE, PROMETHEE, REGIME, and NAIADE methods, and "Ideal and reference point" approaches). It is based on a series of reports in which over 30 real-world case studies focusing on participatory MCDA were reviewed. It is stressed, however, that there is no "best" choice in the list of MCDA techniques. Some methods fit certain decision problems better than others. Nonetheless, some complementary benefits of the different techniques can be exploited by combining these methodologies.

Ethical decision making

The self-centeredness of modern organizations leads to environmental destruction and human deprivation. The principle of responsibility developed by Hans Jonas requires caring for the beings affected by our decisions and actions. Ethical decision-making creates a synthesis of reverence for ethical norms, rationality in goal achievement, and respect for the stakeholders. The maximin rule selects the "least worst alternative" in the multidimensional decision space of deontological, goal-achievement and stakeholder values. The ethical decision-maker can be characterized as having the ability to take multiple perspectives and make appropriate balance across diverse value dimensions. Modern organizations should develop a critical sensitivity to and empathy toward human and non-human beings with which they share a common environment.

Information systems to support decision-making in *construction owner organizations: A data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, non-integrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. ^ A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. ^ One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects. ^

Assessing the effects of professionals' career decision -making on their participation reasons in continuing education in Taiwan

The purpose of this study was to assess the relationship between working professionals' Career Decision-Making Self-Efficacy beliefs (CDMSE beliefs) and their reasons for participating in in-service master's level programs in Taiwan. ^ The data collection instruments used were Grotelueschen's (1985) Participation Reasons Scale (PRS), and Betz, Klein, and Taylor's (1996) Career Decision-Making Self-Efficacy-Short Form (CDMSE-SF), and a Demographic Data Form (DDF) developed specifically for this study. ^ Surveys were administered to 800 working professionals who participated in inservice master's level programs at 22 Taiwanese universities. The survey was conducted in May 2004. Data were analyzed by simple descriptive statistics, principal component factor analysis, and multiple regression. Four factors of participation reasons were found and five components of CDMSE beliefs were scored. ^ Five components of CDMSE beliefs are structured into the CDMSE-SF instrument: Self-Appraisal, Occupational Information, Goal-Selection, Planning, and Problem Solving. The reasons for participation found in this study were: Professional Improvement and Development, Professional Service, Personal Benefit and Job Security, and Professional Competence and Collegial Interaction. Pearson-product moment correlations revealed significant positive correlations between the five CDMSE subscales and the four factors of participation reasons. Multiple regression analysis revealed that participants' beliefs in their abilities to obtain information about occupations accounted for the preponderance of variance of scores on the Participation Reasons Scale (PRS). ^ This study concluded that professionals who believed that they were efficacious in obtaining information about occupations or professions tended to believe that the four reasons for participation represented by the factors of the PRS were important to them in making the decision to participate in continuing education. Additionally, it was noted that the reasons for participations for professionals who did not feel confident in their abilities to find such information could not be determined. ^ Recommendations are offered to assist those individuals responsible for developing recruiting programs in continuing education for professionals in Taiwan. These recommendations focus only on strategies intended to attract this target population of professionals who believe that they are efficacious in obtaining information about occupations. ^

A decision support framework for infrastructure maintenance investment decision-making

Infrastructure management agencies are facing multiple challenges, including aging infrastructure, reduction in capacity of existing infrastructure, and availability of limited funds. Therefore, decision makers are required to think innovatively and develop inventive ways of using available funds. Maintenance investment decisions are generally made based on physical condition only. It is important to understand that spending money on public infrastructure is synonymous with spending money on people themselves. This also requires consideration of decision parameters, in addition to physical condition, such as strategic importance, socioeconomic contribution and infrastructure utilization. Consideration of multiple decision parameters for infrastructure maintenance investments can be beneficial in case of limited funding. Given this motivation, this dissertation presents a prototype decision support framework to evaluate trade-off, among competing infrastructures, that are candidates for infrastructure maintenance, repair and rehabilitation investments. Decision parameters' performances measured through various factors are combined to determine the integrated state of an infrastructure using Multi-Attribute Utility Theory (MAUT). The integrated state, cost and benefit estimates of probable maintenance actions are utilized alongside expert opinion to develop transition probability and reward matrices for each probable maintenance action for a particular candidate infrastructure. These matrices are then used as an input to the Markov Decision Process (MDP) for the finite-stage dynamic programming model to perform project (candidate)-level analysis to determine optimized maintenance strategies based on reward maximization. The outcomes of project (candidate)-level analysis are then utilized to perform network-level analysis taking the portfolio management approach to determine a suitable portfolio under budgetary constraints. The major decision support outcomes of the prototype framework include performance trend curves, decision logic maps, and a network-level maintenance investment plan for the upcoming years. The framework has been implemented with a set of bridges considered as a network with the assistance of the Pima County DOT, AZ. It is expected that the concept of this prototype framework can help infrastructure management agencies better manage their available funds for maintenance.

Information systems to support decision-making in construction owner organizations : a data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, nonintegrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects.

Primary care physician decision making regarding severe obesity treatment and bariatric surgery: a qualitative study.

BACKGROUND: Less than 1% of severely obese US adults undergo bariatric surgery annually. It is critical to understand the factors that contribute to its utilization. OBJECTIVES: To understand how primary care physicians (PCPs) make decisions regarding severe obesity treatment and bariatric surgery referral. SETTING: Focus groups with PCPs practicing in small, medium, and large cities in Wisconsin. METHODS: PCPs were asked to discuss prioritization of treatment for a severely obese patient with multiple co-morbidities and considerations regarding bariatric surgery referral. Focus group sessions were analyzed by using a directed approach to content analysis. A taxonomy of consensus codes was developed. Code summaries were created and representative quotes identified. RESULTS: Sixteen PCPs participated in 3 focus groups. Four treatment prioritization approaches were identified: (1) treat the disease that is easiest to address; (2) treat the disease that is perceived as the most dangerous; (3) let the patient set the agenda; and (4) address obesity first because it is the common denominator underlying other co-morbid conditions. Only the latter approach placed emphasis on obesity treatment. Five factors made PCPs hesitate to refer patients for bariatric surgery: (1) wanting to "do no harm"; (2) questioning the long-term effectiveness of bariatric surgery; (3) limited knowledge about bariatric surgery; (4) not wanting to recommend bariatric surgery too early; and (5) not knowing if insurance would cover bariatric surgery. CONCLUSION: Decision making by PCPs for severely obese patients seems to underprioritize obesity treatment and overestimate bariatric surgery risks. This could be addressed with PCP education and improvements in communication between PCPs and bariatric surgeons.

A Collaborative Multiagent Framework based on Online Risk-Aware Planning and Decision-Making

Planning is an essential process in teams of multiple agents pursuing a common goal. When the effects of actions undertaken by agents are uncertain, evaluating the potential risk of such actions alongside their utility might lead to more rational decisions upon planning. This challenge has been recently tackled for single agent settings, yet domains with multiple agents that present diverse viewpoints towards risk still necessitate comprehensive decision making mechanisms that balance the utility and risk of actions. In this work, we propose a novel collaborative multi-agent planning framework that integrates (i) a team-level online planner under uncertainty that extends the classical UCT approximate algorithm, and (ii) a preference modeling and multicriteria group decision making approach that allows agents to find accepted and rational solutions for planning problems, predicated on the attitude each agent adopts towards risk. When utilised in risk-pervaded scenarios, the proposed framework can reduce the cost of reaching the common goal sought and increase effectiveness, before making collective decisions by appropriately balancing risk and utility of actions.