Are objectives hierarchy related biases observed in practice? A meta-analysis of environmental and energy applications of Multi-Criteria Decision Analysis

Procedural and behavioural biases have received little attention in recent Multi-Criteria Decision Analysis (MCDA) research. Our literature review shows that most research on biases was done 15–30 years ago. This study focuses on biases that are introduced at an early stage of MCDA when building objectives hierarchies and their effect on the weights. The main objective is to investigate whether prior findings regarding such biases, which were mostly based on laboratory experiments, can be found in real-world applications. We conducted a meta-analysis of the objectives hierarchies and weight elicitation procedures in 61 environmental and energy MCDA cases. Relationships between the structural characteristics of the objectives hierarchy and assigned objectives’ weights were analysed with statistical tests. Our main research questions were: (i) How does hierarchy size and structure affect the objectives’ weights? (ii) How are weights distributed across economic, social and environmental objectives? (iii) Is there support for the equalising bias? Our findings are mostly aligned with earlier research and suggest that the hierarchy structure and content can substantially influence weight distributions. For example, hierarchical weighting seems to be sensitive to the asymmetry bias, which can occur when a hierarchy has branches that differ in the number of sub-objectives. We found no evidence for the equalising bias. We highlight issues deserving more attention when developing objectives hierarchies and eliciting weights. The research demonstrates the potential to use meta-analysis, which has not previously been used in this way in the MCDA field, to learn from a collection of applications

Behavioral challenges in policy analysis with conflicting objectives

Public policy problems are rife with conflicting objectives: efficiency versus fairness, technical criteria versus political goals, costs versus multiple benefits. Multi-Criteria Decision Analysis provides robust methodologies to support policy makers in making tough choices and in designing better policy options when considering these conflicting objectives. However, important behavioral challenges exist in developing these models: the use of expert judgments, whenever evidence is not available; the elicitation of preferences and priorities from policy makers and communities; and the effective management of group decision processes. The extensive developments in behavioral decision research, social psychology, facilitated decision modeling, and incomplete preference models shed light on how decision analysts should address these issues, so we can provide better decision support and develop high quality decision models. In this tutorial I discuss the main findings of these extensive, but rather fragmented, literatures providing a coherent and practical framework for managing behavioral issues, minimizing behavioral biases, and optimizing the quality of human judgments in policy analysis models with conflicting objectives. I illustrate these guidelines with policy analysis interventions that we have conducted over the last decade for several organizations, such as the World Health Organization (WHO), the Food and Agriculture Organization of the United Nations (FAO), the UK Department of Environment Food and Rural Affairs (DEFRA), the Malaria Consortium/USAID, the UK National Audit Office, among others

Modeling the values of private sector agents in multi-echelon humanitarian supply chains

© 2018 Elsevier B.V. Humanitarian organizations (HOs) increasingly look to engage private sector supply chains in achieving outcomes. The right engagement approach may require knowledge of agents' preferences across multi-echelon supply chains to align private sector value creation with humanitarian outcomes. We propose a multi-attribute value analysis (MAVA) framework to elucidate such preferences. We formalize this approach and apply it in collaboration with a HO pilot aiming to facilitate better private sector availability of malaria rapid diagnostic tests in Uganda. We demonstrate how HOs could use criteria weights and value functions from MAVA for project evaluation; in the process, we reveal business model insights for importers, distributors, and retailers in the pilot. We also show how MAVA facilitates the impact assessment of hypothetical options (i.e., combinations of products, services, and subsidies) to guide HO resource deployment. This paper offers the first attempt, to our knowledge, to develop quantitative measures for economic and non-economic objectives involving all agents in a multi-echelon supply chain, either humanitarian or commercial. We hope that this initial step stimulates further research to validate results and develop the framework proposed

Strategic technology decision-making in Swedish large-scale forestry

Technological development gives Swedish forest companies and forest owners’ associations opportunities to maintain competitiveness in the highly cost-sensitive market for forest products. Development efforts are typically performed through unstructured decision processes. However, an organization’s success is a product of its decisions, so the quality of these decisions is crucial. The main objectives of this thesis were therefore to describe and critically analyze strategic decision-making about forest technology. Study I investigated how and with what support forest companies and a forest owners’ association make decisions about forest technology. It was concluded that these organizations value collaborations with manufacturers and researchers, that economic criteria were most important in the decision-making process, and that large risks are preferably managed in a stepwise fashion. Study II reviewed the use of Multi-Criteria Decision Analysis (MCDA) methods in forest operations and it was shown that the methods were used at various temporal scales, most commonly when making strategic decisions. Study III developed and compared two modelling approaches for machine system analysis and concluded that they produced similar results despite having different levels of detail and demanding different competences. Study IV used the previously developed modelling approaches to compare the performance of established and new machine systems in Swedish final fellings, revealing an opportunity to reduce costs by adopting the new machine system. A conceptual flowchart for strategic decision making on forest technology development was created to improve the quality and efficiency of the decision-making process

Tools and methods in participatory modeling: Selecting the right tool for the job

© 2018 Elsevier Ltd Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with their choices and decisions. Most available literature provides little justification or information on the reasons for the use of particular methods or tools in a given study. In most of the cases, it seems that the prior experience and skills of the modelers had a dominant effect on the selection of the methods used. While we have not found any real evidence of this approach being wrong, we do think that putting more thought into the method selection process and choosing the most appropriate method for the project can produce better results. Based on expert opinion and a survey of modelers engaged in participatory processes, we offer practical guidelines to improve decisions about method selection at different stages of the participatory modeling process

Influences on Supply Manager Behavior Toward Environmental Responsibility

As firms invest a substantial amount of time, effort, and funds to purchase goods and services, it is questionable if organizations will reach environmental sustainability objectives without supply manager active involvement. Although existing research has identified low supply manager support for environmental buying, there is little theoretical understanding and explanation relating corporate environmental policies and objectives to individual behaviors. Consequently, this dissertation seeks to provide insight into understanding and overcoming a lack of supply manager support for environmental sustainability. A research model based on the Theory of Planned Behavior used survey data from practicing supply managers to study the behavioral aspects of environmentally responsible buying. Support was found for all five hypotheses predicting direct effects on intention to engage in environmentally responsible behavior and actual environmentally responsible behavior. Also, direct effects for non-hypothesized relationships were found for the two moderating variables. This dissertation will potentially help researchers and practitioners better understand the antecedents related to supply manager environmentally responsible behavior and subsequently support implementation of corporate environmental sustainability objectives

Promoting novelty, rigor, and style in energy social science: towards codes of practice for appropriate methods and research design

A series of weaknesses in creativity, research design, and quality of writing continue to handicap energy social science. Many studies ask uninteresting research questions, make only marginal contributions, and lack innovative methods or application to theory. Many studies also have no explicit research design, lack rigor, or suffer from mangled structure and poor quality of writing. To help remedy these shortcomings, this Review offers suggestions for how to construct research questions; thoughtfully engage with concepts; state objectives; and appropriately select research methods. Then, the Review offers suggestions for enhancing theoretical, methodological, and empirical novelty. In terms of rigor, codes of practice are presented across seven method categories: experiments, literature reviews, data collection, data analysis, quantitative energy modeling, qualitative analysis, and case studies. We also recommend that researchers beware of hierarchies of evidence utilized in some disciplines, and that researchers place more emphasis on balance and appropriateness in research design. In terms of style, we offer tips regarding macro and microstructure and analysis, as well as coherent writing. Our hope is that this Review will inspire more interesting, robust, multi-method, comparative, interdisciplinary and impactful research that will accelerate the contribution that energy social science can make to both theory and practice