ABSTRACTThis paper reports on a study of the issue relationships and priorities used by public officials in making local economic‐development policy decisions. Economic success criteria for evaluating distressed areas were compared and were found to vary in importance among officials. Policy bases of expert judges were determined. Their differences, as well as the implications of including this type of knowledge in the decision‐making process, are discussed. Recommendations for a more detailed understanding of the public‐policy decision process in economic development, through the use of a policy‐capture approach, are made.
Considering the critical influencing phenomena, the study explores the causal mechanism of influences, as well as how such process works that lead to shape the dominant implications of influences on local government Union Councils' budgetary autonomy, leading to the impact on their local governance.The research reveals the fact that the effects of the influencing phenomena on the budgetary autonomy of Union Councils in Bangladesh are evident with varying degrees and dimensions, but the influences do not always collide with the budgetary autonomy of Union Councils there. The indicator-based empirical analysis reveals that the magnitude of influences is almost double than that of the budgetary autonomy of Union Councils in Bangladesh. Thus, the autonomy of Union Councils in their budgeting decisions is a concern in the study of decentralization and local governance in Bangladesh.Originality and significance:The research contributed in the literature stream of public administration, specifically in decentralization, local government finance as well as budgeting, and in local governance studies. The study findings to some extent substantiated the rationality of conditional national government transfers to the sub-national governments in Bangladesh. Beyond the general theoretical and practical significance of the study, its findings led to inviting a fundamental debate on the national-local tax base system and appreciated the fact that central hindrance towards effective functioning of the local government Union Councils in Bangladesh is the crisis of ownership and competence of UP representatives.
The goal of this article is to examine to what extent legislators in Estonia use performance information in budgetary decision‐making. Interviews with the members of the finance committee of the parliament show that legislators make only limited use of the formal documents containing performance information. Instead, they rely, for the most part, on informal social networks for gathering information they consider necessary for budget discussions. According to the legislators, the main reasons for limited use of performance information are the following: the documents containing performance are too long and cumbersome, the legislative budget process is too time‐constrained, and the parliament has only a limited role in making substantive changes to the budget. The study also indicates that more experienced politicians are less interested in performance information than the novices but there are no significant differences between legislators from governing and opposition parties.
Climate change poses a significant challenge to primary industries and adaptation will be required to reduce detrimental impacts and realise opportunities. Despite the breadth of information to support adaptation planning however, knowledge is fragmented, obscuring information needs, hampering strategic planning and constraining decision-making capacities. In this letter, we present and apply the Adaptation Knowledge Cycle (AKC), a heuristic for rapidly evaluating and systematising adaptation research by analytical foci: Impacts, Implications, Decisions or Actions. We demonstrate its application through an assessment of ten years' climate change adaptation research for New Zealand's primary industries. The letter draws on the results of systematic review, empirical analysis, workshops, interviews, narrative analyses and pathways planning to synthesise information and identify knowledge gaps. Results show the heuristic's simplicity is valuable for cross- and transdisciplinary communication on adaptation in New Zealand's primary industries. Results also provide insight into what we know and need to know with respect to undertaking adaptation planning. With the development of tools and processes to inform decision making under conditions of uncertainty—such as adaptation pathways—it is increasingly important to efficiently and accurately determine knowledge needs. The combination of systematic data collection techniques, and heuristics such as the AKC may provide researchers and stakeholders with an efficient, robust tool to review and synthesise existing knowledge, and identify emerging research priorities. Results can in turn support the design of targeted research and inform adaptation strategies for policy and practice.
In the face of slow economic growth and development, and the perennial problems of unemployment, poverty and inequality, the South African government and business community have long recognised the importance of growing and diversifying the countrys tangible goods and services export sectors. One of the challenges in designing and implementing effective export promotion strategies is identifying the right markets, given South Africas ever-fluid skills, capacity and trading relationships. The Decision Support Model (DSM) is an export market selection tool that makes use of a sophisticated filtering process to sift through an extensive range of product-/service- and country-related data to reveal those product-/service-country combinations (export opportunities) that are the most realistic and sustainable. The DSM, which has been applied for Belgium, Thailand and South Africa, not only brings greater precision to the export market selection process, but also unveils opportunities that may not have been contemplated before thus supporting the quest for export diversification. This paper examines the role of the DSM for products and the DSM for services, respectively, and illustrates how, using the results from the application of these models, they herald the start of a new era in export market selection and promotion in South Africa.
Mindfulness has recently attracted a great deal of interest in the field of management. However, even though mindfulness - broadly viewed as a state of active awareness - has been described mainly at the individual level, it may also have important effects at aggregated levels. In this article, we adopt a team-based conceptualization of mindfulness, and develop a framework that represents the powerful effect of team mindfulness on facilitating effective decision-making. We further discuss how a conceptualization of team mindfulness may mitigate the process of false consensus by interacting positively with the following five central team processes: open-mindedness, participation, empowerment, conflict management, and value and ambiguity tolerance. A false consensus constitutes a cognitive bias, leading to the perception of a consensus that does not exist. In essence, we argue that, although a conceptualization of team mindfulness does not guarantee effective decision-making in itself, it may successfully reduce false consensus when coupled with these five team processes. Accordingly, this article contributes to the theory and practice of team decision-making by demonstrating how a conceptualization of team mindfulness can be helpful in the increasingly complex and ambiguous situations faced by contemporary teams.
Worldwide electricity markets are undergoing a major restructuring process. One of the main reasons for the ongoing changes is to enable the adaptation of current market models to the new paradigm that arises from the large-scale integration of distributed generation sources. In order to deal with the unpredictability caused by the intermittent nature of the distributed generation and the large number of variables that contribute to the energy sector balance, it is extremely important to use simulation systems that are capable of dealing with the required complexity. This paper presents the Tools Control Center (TOOCC), a framework that allows the interoperability between heterogeneous energy and power simulation systems through the use of ontologies, allowing the simulation of scenarios with a high degree of complexity, through the cooperation of the individual capacities of each system. A case study based on real data is presented in order to demonstrate the interoperability capabilities of TOOCC. The simulation considers the energy management of a microgrid of a real university campus, from the perspective of the network manager and also of its consumers/producers, in a projection for a typical day of the winter of 2050. ; This work has been developed in the scope of the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 641794 (project DREAM-GO); CONTEST project - SAICT-POL/23575/2016; and has also been supported by FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013. ; info:eu-repo/semantics/publishedVersion
Gunung Agung is one of the most potent eruption volcanoes in Indonesia. Reflecting back to 1963 when Mount Agung erupted, the impact was so devastating. Even the impact for months. The lack of food supplies is becoming a central job for the government. The distribution of logistics plays an important role in this regard whether it is food, clothing or other necessities, but the current logistics distribution system is still manual so it is not very efficient and very likely there is a misstatement. The impact of difficulties in managing logistical assistance can be seen, eg uneven distribution of relief goods in terms of number of inter-regions (posts), types of relief items sent are not in accordance with the type desired by individual posts, and especially for fast food, then damaged and outdated because it was sent to the post at the wrong time and improper handling. Needed a solution to minimize the problems that arise in the process of disbursing logistics disaster management is by using the Logistics Management Information System. In this research, the method used using two methods, namely waterfall method for system development, and for decision support system using Topsis method Expected to be able to manage logistical support in a timely, timely, and precise location
During recent years, a great deal of attention has been focused on the financial risk management of natural disasters. One reason behind is that the economic losses from floods, windstorms, earthquakes and other disasters in both the developing and developed countries are escalating dramatically. It has become apparent that an integrated water resource management approach would be beneficial in order to take both the best interests of society and of the environment into consideration. One improvement consists of models capable of handling multiple criteria (conflicting objectives) as well as multiple stakeholders (conflicting interests). A systems approach is applied for coping with complex environmental and societal risk management decisions with respect to flood catastrophe policy formation, wherein the emphasis is on computer-based modeling and simulation techniques combined with methods for evaluating strategies where numerous stakeholders are incorporated in the process. The resulting framework consists of a simulation model, a decision analytical tool, and a set of suggested policy strategies for policy formulation. The framework will aid decision makers with high risk complex environmental decisions subject to significant uncertainties.
Priority setting of health interventions is generally considered as a valuable approach to support low- and middle-income countries (LMICs) in their strive for universal health coverage (UHC). However, present initiatives on priority setting are mainly geared towards the development of more cost-effectiveness information, and this evidence does not sufficiently support countries to make optimal choices. The reason is that priority setting is in reality a value-laden political process in which multiple criteria beyond cost-effectiveness are important, and stakeholders often justifiably disagree about the relative importance of these criteria. Here, we propose the use of 'evidence-informed deliberative processes' as an approach that does explicitly recognise priority setting as a political process and an intrinsically complex task. In these processes, deliberation between stakeholders is crucial to identify, reflect and learn about the meaning and importance of values, informed by evidence on these values. Such processes then result in the use of a broader range of explicit criteria that can be seen as the product of both international learning ('core' criteria, which include eg, cost-effectiveness, priority to the worse off, and financial protection) and learning among local stakeholders ('contextual' criteria). We believe that, with these evidence-informed deliberative processes in place, priority setting can provide a more meaningful contribution to achieving UHC.
Abstract Background There is a need to identify rational criteria and set priorities for vaccines. In Thailand, many licensed vaccines are being considering for introduction into the Expanded Program on Immunization; thus, the government has to make decisions about which vaccines should be adopted. This study aimed to set priorities for new vaccines and to facilitate decision analysis. Methods We used a best-worst scaling study for rank-ordering of vaccines. The candidate vaccines were determined by a set of criteria, including burden of disease, target age group, budget impact, side effect, effectiveness, severity of disease, and cost of vaccine. The criteria were identified from a literature review and by in-depth, open-ended interviews with experts. The priority-setting model was conducted among three groups of stakeholders, including policy makers, healthcare professionals and healthcare administrators. The vaccine data were mapped and then calculated for the probability of selection. Results From the candidate vaccines, the probability of hepatitis B vaccine being selected by all respondents (96.67 %) was ranked first. This was followed, respectively, by pneumococcal conjugate vaccine-13 (95.09 %) and Haemophilus influenzae type b vaccine (90.87 %). The three groups of stakeholders (policy makers, healthcare professionals and healthcare administrators) showed the same ranking trends. Most severe disease, high fever rate and high disease burden showed the highest coefficients for criterion levels being selected by all respondents. This result can be implied that a vaccine which can prevent most severe disease with high disease burden and has low safety has a greater chance of being selected by respondents in this study. Conclusions The priority setting of vaccines through a multiple-criteria approach could contribute to transparency and accountability in the decision-making process. This is a step forward in the development of an evidence-based approach that meets the need of developing country. The methodology is generalizable but its application to another country would require the criteria as relevant to that country.
This research explored health decision-making processes among people recently diagnosed with type 2 diabetes. Our analysis suggested that diagnosis with type 2 was followed by a period of intense emotional and cognitive disequilibrium. Subsequently, the informants were observed to proceed to health decision-making which was affected by three separate and interrelated factors: knowledge, self-efficacy, and purpose. Knowledge included cognitive or factual components and emotional elements. Knowledge influenced the degree of upset or disequilibrium the patient experienced, and affected a second category, agency: the informants' confidence in their ability to enact lifestyle changes. The third factor, purpose, summarized the personal and deeply held reasons people gave as they made decisions concerning their health, eating and exercising. We propose this model, grounded in informant stories, as a heuristic, to guide further inquiry. From these stories, the patient is seen as more active and the interrelated influences of knowledge, agency, and purpose, synergistically interact to explain changes in health behaviors.
The article deals with the problem of constructing a model and algorithm for decision support in self-government bodies using machine learning. The method of multiple linear regression for processing the training sample was chosen as a machine learning method. In the training sample, independent data consists of parametric estimates in numerical form of self-government bodies in three areas of activity, such as education, social environment and crime. And the dependent parameter consists of generalized expert assessments of self-government bodies, also in numerical form. The model and algorithm of the decision support process using the method of multiple linear regression are constructed. Based on the constructed model and the proposed algorithm, the coefficients of the function for decision support are identified. Using this model, a generalized expert assessment is determined for the new self-government body in numerical form, which is interpreted as a proposed solution for improving the condition of the object.
The article deals with the problem of constructing a model and algorithm for decision support in self-government bodies using machine learning. The method of multiple linear regression for processing the training sample was chosen as a machine learning method. In the training sample, independent data consists of parametric estimates in numerical form of self-government bodies in three areas of activity, such as education, social environment and crime. And the dependent parameter consists of generalized expert assessments of self-government bodies, also in numerical form. The model and algorithm of the decision support process using the method of multiple linear regression are constructed. Based on the constructed model and the proposed algorithm, the coefficients of the function for decision support are identified. Using this model, a generalized expert assessment is determined for the new self-government body in numerical form, which is interpreted as a proposed solution for improving the condition of the object.
