Use of traditional knowledge by the United States Bureau of Ocean Energy Management to support resource management

Professionals who collect and use traditional knowledge to support resource management decisions often are preoccupied with concerns over how and if traditional knowledge should be integrated with science. To move beyond the integration dilemma, we treat traditional knowledge and science as distinct and complementary knowledge systems. We focus on applying traditional knowledge within the decision-making process. We present succinct examples of how the Bureau of Ocean Energy Management has used traditional knowledge in decision making in the North Slope Borough, Alaska: 1) using traditional knowledge in designing, planning, and conducting scientific research; 2) applying information from both knowledge systems at the earliest opportunity in the process; 3) using traditional knowledge in environmental impacts assessment; 4) consulting with indigenous leaders at key decision points; and 5) applying traditional knowledge at a programmatic decision level. Clearly articulating, early in the process, how best to use traditional knowledge and science can allow for more complete and inclusive use of available and pertinent information

Patient delays in seeking help at the onset of rheumatoid arthritis: the problem, its causes and potential solutions

Rheumatoid arthritis (RA) is a chronic inflammatory disease for which early treatment is vital to limit long term joint damage. However, people often delay in seeking medical help at the onset of RA symptoms. The early interpretation of symptoms and the process of making sense of symptoms impacts on both help-seeking decision-making and self-management. Furthermore, the general public’s perceptions and knowledge of RA may also affect the way that symptoms are interpreted. Examining the psychology behind early symptom interpretation, the barriers to help-seeking behaviour and investigating the public understandings of RA, can help us understand how decisions are made and guide us in developing interventions which encourage people to seek help promptly at the onset of RA

Barriers to build asset adaptation in private service sector

It is becoming increasingly acknowledged that adaptation and mitigation are equally important and often interrelated approaches to climate change. Recent adaptation initiatives in the UK include the promotion of many policies, reporting and economic support in the public sector. However, adaptation in the private sector still lacks such structured initiative and is initiated largely in response to external forces. This paper presents a review of UK-based adaptation initiatives and presents a study of the adaptation decisionmaking process for the built assets of a large private sector organisation. The study was undertaken as a part of a PhD research programme that evaluated the usefulness of the UKCIP Risk, Uncertainty and Decision-making Framework as well as the UKCIP 02 climate change projections for facilities management decision-making. The decision-making framework and projections were used by a group of facilities personnel responsible for built asset management to explore various climate risks and develop adaptation solutions. The paper reports on issues associated with implementing the first three stages of the decision-making framework, in particular the problems faced by facilities management professionals in operationalising the risks and evaluating solutions. The following findings were drawn. A) Adaptation in the private sector is initiated against an external change or signal, for example market forces or experience of a climate-related extreme event. B) For many built asset professionals the transformation of scientific climate change data into impacts on their built asset is a demanding task in terms of required knowledge and time. This process is further complicated by the long time horizon (30 years) associated with climate projections compared to the short time horizon (5-10 years) for strategic business decisions, and the uncertainty attached to climate change projections. C) As a result of (B), much of the analysis for decisionmaking remains qualitative and semi-quantitative and lacks gravitas when hard financial decisions have to be made. D) The perception and attitude of managerial and strategic decision-making personnel towards climate change shapes the decision-making process and adaptation option selection. E) Adaptive capacity, in terms of the time, finance and expertise available to organisations is important to achieving successful adaptation goals. Although, the new UKCP09 projections have been made available since the completion of the study, many of the findings are generic in nature and directly applicable to these new tools. In conclusion, by conceptualising the observed adaptation process with that of organisation learning, it is suggested that literature on organisation learning is likely to provide an effective basis for understanding and promoting the adaptation in the private sector

THE IMPACT OF IMPLICIT MOTIVES ON THE BUSINESS TO BUSINESS DECISION MAKING PROCESS

To sum up, this research presents various novelties and significant contributions to knowledge. First time a complete coding and decoding process in a B2B decision making situation in a controlled environment was done. The coding and decoding procedure was based on a setup with relevant factors like colours and contrast, form and design and different surfaces and look of materials. The novelty of the research is that there is clear evidence for a limited role of rational decision making in the business to business decision making process. From the perspective of the homo economicus clear non-rational drivers were identified. The hypotheses about the interplay of implicit motives and business to business decision making could be confirmed in personal, management and group decisions. In addition, marketing experts emphasised the importance and potential impacts for future business to business marketing.Abstract THE IMPACT OF IMPLICIT MOTIVES ON THE BUSINESS TO BUSINESS DECISION MAKING PROCESS Christian Chlupsa The purpose of this thesis is to understand how implicit processes determine individual and organisational behaviour in the context of business to business (B2B) decision making. A broad literature review suggests that implicit cognition has a significantly more powerful influence than therefore assumed. The author calls for further research into the motivations driving professional behaviour in B2B situations as new study challenges the classical economic theory of the homo economicus, and focuses on the role of implicit motives as a possible driver. As a first objective, the study attempts to reveal a typical structure of implicit motives based on hierarchy and gender. The second objective is to delineate the interplay between the implicit motives and the decision making process in B2B. The third objective is to examine the consequences and implications for business to business marketing. The methodology is based on an interdisciplinary mixed method approach. To address the gaps in existing knowledge, an experiment and a survey (n=175) in different sectors were conducted. For the analysis, a variety of techniques such as operant motive tests, cluster- and multivariate analysis were employed to analyse the empirical response. Semi-structured qualitative in-depth interviews (n=8) were carried out to detect the consequences and the implications of the new findings for practice. The findings of the research indicate that marketing is much more a selective communication as assumed. The impact of marketing communication is not always consciously perceived by customers and the most part is implicit. In conclusion, there seems to be an interplay between implicit motives and the B2B decision making process. Hypotheses about the interplay of implicit motives and business to business decision making were confirmed in personal, management and group decision experiments. As a contribution to existing theory on the subject, it can be postulated that rational choice in B2B decision making may play a limited role. In addition marketing experts from various industry sectors emphasise the importance and the potential impacts for future B2B marketing. Experts stress the need to reveal the real motivational drivers in marketing communication

Decision Making in Emergency Management: The Role of Social Media

Researchers and practitioners alike recognise the importance of emergency management (EM) in limiting the adverse impacts of crisis events, as well as the promise of social media to support these efforts. Decision making, which is crucial to ensure the effective management of immediate, emerging, and sustained crises, is one facet of EM potentially affected by social media. While much research has investigated social media in a crisis context more generally, little is known thus far about what it means for EM decision making. In this paper, we investigate the current knowledge base of this phenomenon and infer from it factors that are crucial for its understanding. To this end, we propose an analytical framework of EM decision making based on previous work on complex problem solving and social media networks. We then systematically review and rethink existing research from a decision-centred point of view to identify and synthesise key findings that are relevant to the role of social media in the EM decision-making process. Finally, we outline the research gaps that need to be closed to arrive at a more comprehensive understanding of social media for EM decision support and to begin moving towards theoretically grounded explanations of the phenomenon

Probability modelling to reduce decision uncertainty in environmental niche identification and driving factor analysis: CaNaSTA case studies

Hillside agro-ecosystems have a complex spatial and temporal distribution of natural resources. Farmers generally possess a vast body of knowledge about environmental resources on their farms but this knowledge is largely based on locally observable features rather than generalized knowledge. The lack of process-based knowledge concerning agro-ecosystem function creates uncertainty that obstructs sound decision-making under conditions of rising economic and ecologic pressure in many developing countries. Since the past decade, Precision Agriculture provides tools to reduce uncertainty caused by environmental variation. By describing spatial and temporal variation of the environment, Geographic Information Systems help to detect suitable crops for specific environmental niches and support farmers to find optimal management practices for their plot of land. Hence Precision Agriculture helps to raise the economic benefits of farming, ensures consistent product quality and reduces negative environmental impacts caused by inappropriate management practices. A spatial decision support system called CaNaSTA was developed to aid the decision making process of crop adoption in tropical agriculture. Using Bayesian probability statistics, CaNaSTA integrates trial data, spatial data and expert knowledge and provides maps, tables and graphs analyzing and interpreting the probability distributions of spatial phenomena. The International Centre for Tropical Agriculture (CIAT) has applied CaNaSTA to three case studies related to tropical agriculture. The first case study identifies niches for specialty coffee production, the second analyses the potential of cowpea (Vigna unguiculata (L.) Walp.) for tropical hillside environments in Colombia. Finally, Canasta was applied to a non-crop related area by performing a study of carbon concentration in tropical soils.

Optimal and intelligent decision making in sustainable development of electronic products

Increasing global population and consumption are causing declining natural and social systems. Multi-lifecycle engineering and sustainable development address these issues by integrating strategies for economic successes, environmental quality, and social equity. Based on multi-lifecycle engineering and sustainable development concepts, this doctoral dissertation aims to provide decision making approaches to growing a strong industrial economy while maintaining a clean, healthy environment. The research develops a methodology to complete both the disassembly leveling and bin assignment decisions in demanufacturing through balancing the disassembly efforts, value returns, and environmental impacts. The proposed method is successfully implemented into a demanufacturing module of a Multi-LifeCycle Assessment and Analysis tool. The methodology is illustrated by a computer product example. Since products during the use stage may experience very different conditions, their external and internal status can vary significantly. These products, when coming to a demanufacturing facility, are often associated with incomplete/imprecise information, which complicates demanufacturing process decision making. In order to deal with uncertain information, this research proposes Fuzzy Reasoning Petri nets to model and reason knowledge-based systems and successfully applies them to demanufacturing process decision making to obtain the maximal End-of-Life (BOL) value from discarded products. Besides the BOL management of products by means of product/material recovery to decrease environmental impacts, the concepts of design for environment and sustainable development are investigated. Based on Sustainability Target Method, a sensitivity analysis decision-making method is proposed. It provides a company with suggestions to improve its product\u27s sustainability in the most cost-effective manner

Modeling and Assessing the Sustainability of Dams in the United States

Dam decision-making is often controversial as a choice has to be made between the benefits provided by dams (e.g., recreation, water supply, hydropower) and their potential negative impacts (e.g., effects on natural flow regime, impediment for fish migration). However, our understandings of such tradeoffs under a full range of dam management alternatives remain limited which hinders our ability to make sound and scientifically defensible dam management decisions. The diverse stakeholders involved in the decision-making process with varying perspectives and preferences could further exacerbate the difficulty of decision-making. To advance our knowledge in sustainable dam decision-making, this dissertation developed modeling tools to evaluate dam decisions based on greenhouse gas (GHG) emissions, hydropower generation, sea-run fish population, and management cost from both spatial and temporal perspectives. The developed model was further applied in role-paly simulation workshops to investigate the potential differences between scientifically optimized decisions and the negotiated consensus. The results revealed that although most hydroelectric dams have comparable GHG emissions to other types of renewable energy (e.g., solar, wind energy), electricity produced from tropical reservoir-based dams could potentially have a higher emission rate than fossil-based electricity. It is possible to simultaneously optimize energy, fish, and cost outcomes through strategic dam management actions. Basin-scale management strategies may outperform individual dam management strategies because the former can provide a broader set of solutions for balancing complex tradeoffs than the latter. Furthermore, diversification of management options (e.g., combination of fishway installations, dam removals, and generation capacity) may have the highest potential in balancing fish-energy-cost tradeoffs. Finally, dam management negotiation is helpful in facilitating decisions with more balanced outcomes but not necessary reflect the environmentally optimal outcomes

Improving Sustainability and Circularity of European Food Waste Management with a Life Cycle Approach

In the past years, several research initiatives have been promoted in the area of food waste. Many of these were focused on the identification of key drivers of food wastage and on the quantification of food waste generation. While these initiatives provided fairly accurate information over European food waste generation and management routes, they did not always deliver comprehensive and comparable knowledge on the sustainability of food waste management and on ways to mitigate negative consequences at environmental, economic and social levels. Building on most recent methodological advancement and policy needs, the work presented in this report aims at providing policy/decision makers and waste managers with a life-cycle based framework methodology to quantify the environmental and economic sustainability performance of European food waste management. This methodology can help identify options for improvement of such performance, thus can offer relevant insight to the decision making process. A numerical case study is also developed. This is meant to give an example of simplified application of the proposed methodology to a fictitious European waste management context. The environmental dimension has been evaluated with the Life Cycle Assessment (LCA) software EASETECH, while the economic assessment is conducted based on a number of different indicators expressing the costs associated with food waste management. This methodology makes use of multi-objective optimization and Pareto optimality concepts in order to help identify most sustainable management options for food waste, intended as those that minimize environmental and economic impacts. In any case, the proposed methodology is meant to only provide relevant information that can support science-based decision making. The final choice will in fact depend on a number of additional aspects that are beyond the scope of this report and also depends on the preferences of the decision maker.JRC.H.8-Sustainability Assessmen

Evidence-based management in hospital settings:Unraveling the process and the role of the person and the context

Evidence-based Management in Hospital Settings: Unraveling the Process and the Role of the Person and the Context Lay Summary Tina Sahakian The use of digital healthcare technologies, such as electronic medical records and health information systems, is increasing in hospital settings and is leading to the collection of large amounts of data about patients, employees, and hospital operations. This data, if used by managers as the basis for decisions, can help improve decision-making, and consequently enhance the quality of healthcare services. One approach to encourage managers to use this and other sources of data is evidence-based management (EBMgt). EBMgt involves gathering data from different sources, assessing the reliability and relevance of this data, and using it to make decisions. However, our current knowledge about the EBMgt approach is limited because:(1) there is little research on how managers can apply the EBMgt decision process, (2) there is little research on how factors related to the decision maker, like their competencies, and factors related to the context, like organizational politics, impact EBMgt, (3) there is confusion about what data managers should rely on. The aim of my dissertation is to develop an in-depth data-driven understanding of EBMgt in hospital settings, by unraveling how the EBMgt process can be applied, what evidence is used in this process, and how the decision-maker and the context impact this process. To fulfill this aim, I conducted three studies. In Study 1, I focused on identifying the competencies needed by managers to be able to practice EBMgt in hospital settings. I conducted interviews with managers in hospitals across Lebanon and identified 13 knowledge, skills, abilities, and other characteristics that are necessary to practice EBMgt in hospital settings. These included research knowledge, resourcefulness, relationship building, and open mindedness. In Study 2, I focused on better understanding the EBMgt decision-making process, what evidence is used in the process, and what contextual factors impact the process. I conducted interviews with managers in hospitals across Lebanon and developed the Grounded Model of the EBMgt Process. The model showed that the EBMgt decision-making process involves a series of steps starting from identifying a problem to implementing a solution. The model also showed that different sources of evidence are used in this process, including evidence in the form of experience, scientific research, data from the organization, and feedback from stakeholders. Finally, the model showed that different contextual factors impact the EBMgt process. These factors can relate to the individual, for example, managers’ competencies impact the evidence they gather. These factors can relate to the organization, for example organizational resource constraints impact the solutions managers apply. These factors can also relate to the nation, for example national capacity to gather and disseminate data impact the evidence available to managers. In Study 3, I focused on identifying the gaps in our knowledge of EBMgt in hospital settings, which can be filled with future research. I searched the literature for articles about EBMgt in hospital settings using a systematic approach. I found that there are gaps in our knowledge of how managers reasons for using evidence impact the EBMgt process, how EBMgt can be conducted in developing countries, and how applying EBMgt impacts organizational outcomes. These gaps are important areas for future research. Overall, my dissertation contributes to the literature on EBMgt in hospital settings by determining the competencies needed to practice EBMgt, providing an in-depth understanding about the process of EBMgt and the factors that influence this process, and identifying gaps in our knowledge of EBMgt in hospital settings, which future research can fill