Comparing groups versus individuals in decision making: A systematic review protocol

Background Biodiversity management requires effective decision making at various stages. However decision making in the real world is complex, driven by multiple factors and involves a range of stakeholders. Understanding the factors that influence decision making is crucial to addressing the conflicts that arise in conservation. Decisions can be made either by individuals or by groups. This precise context has been studied extensively for several decades by behavioural economists, social psychologists and intelligence analysts. The observations from these disciplines can offer useful insights for biodiversity conservation. A systematic review on group versus individual decision making is currently lacking. This systematic review would enable us to synthesize the key insights from these disciplines for a range of scenarios useful for conservation. Methods The review will document studies that have investigated differences between group and individual decision making. The focus will be on empirical studies; the comparators in this case are decisions made by individuals while the intervention is group decision making. Outcomes include level of bias in decision outcomes or group performance. The search terms will include various combinations of the words “group”, “individual” and “decision-making”. The searches will be conducted in major publication databases, google scholar and specialist databases. Articles will be screened at the title and abstract and full text level by two reviewers. After checking for internal validity, the articles will be synthesized into subsets of decision contexts in which decision making by groups and individuals have been compared. The review process, all extracted data, original studies identified in the systematic review process and inclusion and exclusion decisions will be freely available as Additional file 1 in the final review.NM is funded by the Fondation Weiner Anspach in Belgium. WJS is funded by Arcadia. LVD was supported under the Biodiversity and Ecosystem Service Sustainability (BESS) Programme, grant code NE/K015419/1. GES is funded by The Nature Conservancy.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s13750-016-0066-

The value of design in UK FMCG packaging development: An industry case study exploring practitioner design practice rationale & decision-making

Recognising the value design offers has been of great importance for the effective development and launch of Fast-Moving Consumer Goods (FMCG). Packaging design is acknowledged as a significant success factor in New Product Development (NPD) for the FMCG industry to help provide clear product differentiation and competitive advantage in saturated and complex markets. The search for approaches to maintain or improve market share has driven the field of consumer research over the last few decades. The potential to influence consumer perception of a product through visual design is well documented in the literature. Packaging design relies on effective management of symbolic, semantic, aesthetic and visual information elements. Stakeholders have been increasingly demanding that design practitioners provide a clear rationale and accountability for their design proposals in this risk-averse industry. However, limited research has been produced to address how packaging design and development is managed; and, how design practitioners rationalise and validate their design decision-making. The authors’ look to address this through the study of design practitioners in ‘real-world’ FMCG design practice. A case study is presented with a UK company involved in the design and manufacture of food and beverage packaging for suppliers, retailers and brands in the UK FMCG market. The research aims to identify preliminary insights and a narrative into the factors affecting practitioner rationale, decision-making and explore future research. The study triangulates evidence from interviews, participant observation, direct observation and document analysis to identify influences through a convergence of findings. Nine preliminary influences are recognised that appear to affect practitioner rationale and decision-making.<br

A new model of information seeking stopping behavior

textWeb search engines play an important role in peoples daily life. Widespread usage of search engine poses continuous challenges for designing information search systems that can bring people best user experience. To address this challenges, it is particularly important to understand how people seek information. In spite of a large number of studies on human information seeking, the reasons of when and why users terminate information seeking are uncertain and many proposed theories have a limited capability for predicting this type of behavior. In our study, we conducted lab-based experiments, where participants performed assigned information search tasks on Wikipedia pages. Inspired by theories and methods from cognitive science, we captured participants information search behavior such as query usage, search engine result page visits, Wikipedia page visits, and task duration. Additionally, we used eye-tracking techniques to examine the number of people's eye fixations. Using exploratory factor analysis (EFA), we have confirmed exploratory and validation processes can be distinguished based on different types of costs associated with each of them. Based on the findings of the regression tree model, evaluating the cost and gain in the validation process provide important feedback to people for controlling and monitoring their information search.Informatio

A study of interface support mechanisms for interactive information retrieval

Advances in search technology have meant that search systems can now offer assistance to users beyond simply retrieving a set of documents. For example, search systems are now capable of inferring user interests by observing their interaction, offering suggestions about what terms could be used in a query, or reorganizing search results to make exploration of retrieved material more effective. When providing new search functionality, system designers must decide how the new functionality should be offered to users. One major choice is between (a) offering automatic features that require little human input, but give little human control; or (b) interactive features which allow human control over how the feature is used, but often give little guidance over how the feature should be best used. This article presents a study in which we empirically investigate the issue of control by presenting an experiment in which participants were asked to interact with three experimental systems that vary the degree of control they had in creating queries, indicating which results are relevant in making search decisions. We use our findings to discuss why and how the control users want over search decisions can vary depending on the nature of the decisions and the impact of those decisions on the user's search

Explaining Data-Driven Decisions made by AI Systems: The Counterfactual Approach

We examine counterfactual explanations for explaining the decisions made by model-based AI systems. The counterfactual approach we consider defines an explanation as a set of the system's data inputs that causally drives the decision (i.e., changing the inputs in the set changes the decision) and is irreducible (i.e., changing any subset of the inputs does not change the decision). We (1) demonstrate how this framework may be used to provide explanations for decisions made by general, data-driven AI systems that may incorporate features with arbitrary data types and multiple predictive models, and (2) propose a heuristic procedure to find the most useful explanations depending on the context. We then contrast counterfactual explanations with methods that explain model predictions by weighting features according to their importance (e.g., SHAP, LIME) and present two fundamental reasons why we should carefully consider whether importance-weight explanations are well-suited to explain system decisions. Specifically, we show that (i) features that have a large importance weight for a model prediction may not affect the corresponding decision, and (ii) importance weights are insufficient to communicate whether and how features influence decisions. We demonstrate this with several concise examples and three detailed case studies that compare the counterfactual approach with SHAP to illustrate various conditions under which counterfactual explanations explain data-driven decisions better than importance weights

Stuck in the middle: A case study of conflict experiences by a first-time community college president

Leadership models for community college presidents are in a major transformation from traditional hierarchical, positional authority to participatory models of decision making. As leadership becomes more participatory, and educators experiment with more team and collaborative approaches to leadership, increased conflict is a likely outcome. Inclusiveness often brings diverse voices into decision making, and empowerment of a variety of individuals brings a shift in traditional power dynamics. Different interests may create conflict, and leaders will need to find ways to negotiate these differences in order to enhance creative adaptation of a community college to its changing environment. This study explores the experiences and responses to conflict of a community college president using a field case study method and grounded theory approach. Interviews were conducted with the president over 10 months, triangulated with faculty and staff interviews, onsite observations, document analysis and the results of the Leadership Development Profile questionnaire which was developed by William Torbert to predict a leader\u27s stage of social cognitive development (ego maturity). The results of this study suggest that presidential responses to conflict negatively impacted the organization through habitual avoidance of conflict tensions including disengagement from important and clarifying discussions with the faculty and staff and retreat into bureaucratic routines that kept him separated from faculty interaction. In addition, the results of the Leadership Development Profile suggest a relationship between the president\u27s experiences of conflict and his suggested stage of ego maturity which in turn influenced his choice of conflict responses. The implications of this study are that conflict engagement choices of this president can best be understood (a) as part of the organizational and environmental context and the developmental capacity (ego maturity) of a leader, (b) problem solving and decision making through collaboration require leaders to continually learn on the job, (c) complex, ambiguous problems may require conflict as a catalyst to surface and challenge assumptions that hinder the search for novel solutions

Decision Management Process Improvement Project

A Project Submitted in Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE in Project ManagementIt has become all too common that questions are raised during the execution of a project pertaining to the decisions that were made early on. Without having maintained a concise, accessible record of project decisions, the project manager and team members would find it difficult to provide hard evidence as to how they got to this point and what impacts specific decisions had on the project’s trajectory. This paper introduces the Decision Management Process Improvement Project (DMPIP), which focuses on improving decision management process throughout the lifecycle of a project with the aim of adding value to project performance and helping obtain project success. This new tool was inspired due to a lack of appropriate methods involving complex projects at a local consulting firm. The process along with the tool is being added to the toolset of a local Consulting Firm. This Firm plans to introduce the tools and techniques to clients that will benefit from an increased Project Management maturity level with improvements to its decision-tracking processes and demonstration of downstream effects of important decisions. The final product is a contribution to the Project Management Body of Knowledge (PMBOK) in the form of creating a Project Decision Management knowledge area in the PMBOK format. A decision log that follows a decision throughout the whole process from problem identification and analysis to the eventual outcome is at the core of the created knowledge area.Title Page / Table of Contents / List of Exhibits / Abstract / Keywords / Introduction / Project Purpose / Project Benefits / Research Methodology / Research Results Analysis / Project Management Approach / Final Products / Conclusion and Recommendations / Opportunities for Future Development / Reference

Automated legal sensemaking: the centrality of relevance and intentionality

Introduction: In a perfect world, discovery would ideally be conducted by the senior litigator who is responsible for developing and fully understanding all nuances of their client’s legal strategy. Of course today we must deal with the explosion of electronically stored information (ESI) that never is less than tens-of-thousands of documents in small cases and now increasingly involves multi-million-document populations for internal corporate investigations and litigations. Therefore scalable processes and technologies are required as a substitute for the authority’s judgment. The approaches taken have typically either substituted large teams of surrogate human reviewers using vastly simplified issue coding reference materials or employed increasingly sophisticated computational resources with little focus on quality metrics to insure retrieval consistent with the legal goal. What is required is a system (people, process, and technology) that replicates and automates the senior litigator’s human judgment. In this paper we utilize 15 years of sensemaking research to establish the minimum acceptable basis for conducting a document review that meets the needs of a legal proceeding. There is no substitute for a rigorous characterization of the explicit and tacit goals of the senior litigator. Once a process has been established for capturing the authority’s relevance criteria, we argue that literal translation of requirements into technical specifications does not properly account for the activities or states-of-affairs of interest. Having only a data warehouse of written records, it is also necessary to discover the intentions of actors involved in textual communications. We present quantitative results for a process and technology approach that automates effective legal sensemaking