The Role of Social Cognition and Person Perception in Economic Social Decision-Making

Social decision-making is often complex, requiring the decision-maker to make social inferences about another person in addition to engaging traditional decision-making processes. However, until recently, much research in neuroeconomics and behavioral economics has examined social decision-making while failing to take into account the importance of the social context and social cognitive processes that are engaged when viewing another person. Using social psychological theory to guide our hypotheses, four research studies investigate the role of social cognition and person perception in guiding economic decisions made in social contexts. The first study (Chapter 2) demonstrates that only specific types of social information engage brain regions implicated in social cognition and hinder learning in social contexts. Study 2 (Chapter 3) extends these findings and examines contexts in which this social information is used to generalize across contexts to form predictions about another person’s behavior. Study 3 (Chapter 4) demonstrates that under certain contexts these social cognitive processes may be withheld in order to more effectively complete the task at hand. Last, Study 4 (Chapter 5) examines how this knowledge of social cognitive processing can be used to change behavior in a prosocial group context. Taken together, these studies add to the growing body of literature examining decision-making in social contexts and highlight the importance of social cognitive processing in guiding these decisions. Although social cognitive processing typically facilitates social interactions, these processes may alter economic decision-making in social contexts.

Social Decision-Making in Bonobos and Chimpanzees

Humans are natural politicians. We obsessively collect social information that is both observable (e.g., about third-party relationships) and unobservable (e.g., about others’ psychological states), and we strategically employ that information to manage our cooperative and competitive relationships. To what extent are these abilities unique to our species, and how did they evolve? The present dissertation seeks to contribute to these two questions. To do so, I take a comparative perspective, investigating social decision-making in humans’ closest living relatives, bonobos and chimpanzees. In Chapter 1, I review existing literature on theory of mind—or the ability to understand others’ psychological states—in these species. I also present a theoretical framework to guide further investigation of social cognition in bonobos and chimpanzees based on hypotheses about the proximate and ultimate origins of their species differences. In Chapter 2, I experimentally investigate differences in the prosocial behavior of bonobos and chimpanzees, revealing species-specific prosocial motivations that appear to be less flexible than those exhibited by humans. In Chapter 3, I explore through decision-making experiments bonobos’ ability to evaluate others based on their prosocial or antisocial behavior during third-party interactions. Bonobos do track the interactions of third-parties and evaluate actors based on these interactions. However, they do not exhibit the human preference for those who are prosocial towards others, instead consistently favoring an antisocial individual. The motivation to prefer those who demonstrate a prosocial disposition may be a unique feature of human psychology that contributes to our ultra-cooperative nature. In Chapter 4, I investigate the adaptive value of social cognition in wild primates. I show that the recruitment behavior of wild chimpanzees at Gombe National Park, Tanzania is consistent with the use of third-party knowledge, and that those who appear to use third-party knowledge receive immediate proximate benefits. They escape further aggression from their opponents. These findings directly support the social intelligence hypothesis that social cognition has evolved in response to the demands of competing with one’s own group-mates. Thus, the studies presented here help to better characterize the features of social decision-making that are unique to humans, and how these abilities evolved.

Theory and Practice in Sustainability Science: Influence of Urban Form on the Urban Heat Island and Implications for Urban Systems

As the world population continues to grow past seven billion people and global challenges continue to persist including resource availability, biodiversity loss, climate change and human well-being, a new science is required that can address the integrated nature of these challenges and the multiple scales on which they are manifest. Sustainability science has emerged to fill this role. In the fifteen years since it was first called for in the pages of Science, it has rapidly matured, however its place in the history of science and the way it is practiced today must be continually evaluated. In Part I, two chapters address this theoretical and practical grounding. Part II transitions to the applied practice of sustainability science in addressing the urban heat island (UHI) challenge wherein the climate of urban areas are warmer than their surrounding rural environs. The UHI has become increasingly important within the study of earth sciences given the increased focus on climate change and as the balance of humans now live in urban areas.

In Chapter 2 a novel contribution to the historical context of sustainability is argued. Sustainability as a concept characterizing the relationship between humans and nature emerged in the mid to late 20th century as a response to findings used to also characterize the Anthropocene. Emerging from the human-nature relationships that came before it, evidence is provided that suggests Sustainability was enabled by technology and a reorientation of world-view and is unique in its global boundary, systematic approach and ambition for both well being and the continued availability of resources and Earth system function. Sustainability is further an ambition that has wide appeal, making it one of the first normative concepts of the Anthropocene.

Despite its widespread emergence and adoption, sustainability science continues to suffer from definitional ambiguity within the academe. In Chapter 3, a review of efforts to provide direction and structure to the science reveals a continuum of approaches anchored at either end by differing visions of how the science interfaces with practice (solutions). At one end, basic science of societally defined problems informs decisions about possible solutions and their application. At the other end, applied research directly affects the options available to decision makers. While clear from the literature, survey data further suggests that the dichotomy does not appear to be as apparent in the minds of practitioners.

In Chapter 4, the UHI is first addressed at the synoptic, mesoscale. Urban climate is the most immediate manifestation of the warming global climate for the majority of people on earth. Nearly half of those people live in small to medium sized cities, an understudied scale in urban climate research. Widespread characterization would be useful to decision makers in planning and design. Using a multi-method approach, the mesoscale UHI in the study region is characterized and the secular trend over the last sixty years evaluated. Under isolated ideal conditions the findings indicate a UHI of 5.3 ± 0.97 °C to be present in the study area, the magnitude of which is growing over time.

Although urban heat islands (UHI) are well studied, there remain no panaceas for local scale mitigation and adaptation methods, therefore continued attention to characterization of the phenomenon in urban centers of different scales around the globe is required. In Chapter 5, a local scale analysis of the canopy layer and surface UHI in a medium sized city in North Carolina, USA is conducted using multiple methods including stationary urban sensors, mobile transects and remote sensing. Focusing on the ideal conditions for UHI development during an anticyclonic summer heat event, the study observes a range of UHI intensity depending on the method of observation: 8.7 °C from the stationary urban sensors; 6.9 °C from mobile transects; and, 2.2 °C from remote sensing. Additional attention is paid to the diurnal dynamics of the UHI and its correlation with vegetation indices, dewpoint and albedo. Evapotranspiration is shown to drive dynamics in the study region.

Finally, recognizing that a bridge must be established between the physical science community studying the Urban Heat Island (UHI) effect, and the planning community and decision makers implementing urban form and development policies, Chapter 6 evaluates multiple urban form characterization methods. Methods evaluated include local climate zones (LCZ), national land cover database (NCLD) classes and urban cluster analysis (UCA) to determine their utility in describing the distribution of the UHI based on three standard observation types 1) fixed urban temperature sensors, 2) mobile transects and, 3) remote sensing. Bivariate, regression and ANOVA tests are used to conduct the analyses. Findings indicate that the NLCD classes are best correlated to the UHI intensity and distribution in the study area. Further, while the UCA method is not useful directly, the variables included in the method are predictive based on regression analysis so the potential for better model design exists. Land cover variables including albedo, impervious surface fraction and pervious surface fraction are found to dominate the distribution of the UHI in the study area regardless of observation method.

Chapter 7 provides a summary of findings, and offers a brief analysis of their implications for both the scientific discourse generally, and the study area specifically. In general, the work undertaken does not achieve the full ambition of sustainability science, additional work is required to translate findings to practice and more fully evaluate adoption. The implications for planning and development in the local region are addressed in the context of a major light-rail infrastructure project including several systems level considerations like human health and development. Finally, several avenues for future work are outlined. Within the theoretical development of sustainability science, these pathways include more robust evaluations of the theoretical and actual practice. Within the UHI context, these include development of an integrated urban form characterization model, application of study methodology in other geographic areas and at different scales, and use of novel experimental methods including distributed sensor networks and citizen science.

Essays in Empirical Operations Management: Bayesian Learning of Service Quality and Structural Estimation of Complementary Product Pricing and Inventory Management

This dissertation contributes to the rapidly growing empirical research area in the field of operations management. It contains two essays, tackling two different sets of operations management questions which are motivated by and built on field data sets from two very different industries --- air cargo logistics and retailing.

The first essay, based on the data set obtained from a world leading third-party logistics company, develops a novel and general Bayesian hierarchical learning framework for estimating customers' spillover learning, that is, customers' learning about the quality of a service (or product) from their previous experiences with similar yet not identical services. We then apply our model to the data set to study how customers' experiences from shipping on a particular route affect their future decisions about shipping not only on that route, but also on other routes serviced by the same logistics company. We find that customers indeed borrow experiences from similar but different services to update their quality beliefs that determine future purchase decisions. Also, service quality beliefs have a significant impact on their future purchasing decisions. Moreover, customers are risk averse; they are averse to not only experience variability but also belief uncertainty (i.e., customer's uncertainty about their beliefs). Finally, belief uncertainty affects customers' utilities more compared to experience variability.

The second essay is based on a data set obtained from a large Chinese supermarket chain, which contains sales as well as both wholesale and retail prices of un-packaged perishable vegetables. Recognizing the special characteristics of this particularly product category, we develop a structural estimation model in a discrete-continuous choice model framework. Building on this framework, we then study an optimization model for joint pricing and inventory management strategies of multiple products, which aims at improving the company's profit from direct sales and at the same time reducing food waste and thus improving social welfare.

Collectively, the studies in this dissertation provide useful modeling ideas, decision tools, insights, and guidance for firms to utilize vast sales and operations data to devise more effective business strategies.

Bayesian Learning with Dependency Structures via Latent Factors, Mixtures, and Copulas

Bayesian methods offer a flexible and convenient probabilistic learning framework to extract interpretable knowledge from complex and structured data. Such methods can characterize dependencies among multiple levels of hidden variables and share statistical strength across heterogeneous sources. In the first part of this dissertation, we develop two dependent variational inference methods for full posterior approximation in non-conjugate Bayesian models through hierarchical mixture- and copula-based variational proposals, respectively. The proposed methods move beyond the widely used factorized approximation to the posterior and provide generic applicability to a broad class of probabilistic models with minimal model-specific derivations. In the second part of this dissertation, we design probabilistic graphical models to accommodate multimodal data, describe dynamical behaviors and account for task heterogeneity. In particular, the sparse latent factor model is able to reveal common low-dimensional structures from high-dimensional data. We demonstrate the effectiveness of the proposed statistical learning methods on both synthetic and real-world data.

Access to Better Education: The School Choice Experience of Families Served by Low-Performing Elementary Public Schools in Miami-Dade County

Public school choice education policy attempts to create an education marketplace. Although school choice research has focused on the parent role in the school choice process, little is known about parents served by low-performing schools. Following market theory, students attending low-performing schools should be the primary students attempting to use school choice policy to access high performing schools rather than moving to a better school. However, students remain in these low-performing schools. This study took place in Miami-Dade County, which offers a wide variety of school choice options through charter schools, magnet schools, and open-choice schools. This dissertation utilized a mixed-methods design to examine the decision-making process and school choice options utilized by the parents of students served by low-performing elementary schools in Miami-Dade County. Twenty-two semi-structured interviews were conducted with the parents of students served by low-performing schools. Binary logistic regression models were fitted to the data to compare the demographic characteristics, academic achievement and distance from alternative schooling options between transfers and non-transfers. Multinomial logistic regression models were fitted to the data to evaluate how demographic characteristics, distance to transfer school, and transfer school grade influenced the type of school a transfer student chose. A geographic analysis was conducted to determine how many miles students lived from alternative schooling options and the miles transfer students lived away from their transfer school. The findings of the interview data illustrated that parents’ perceived needs are not being adequately addressed by state policy and county programs. The statistical analysis found that students from higher socioeconomic social groups were not more likely to transfer than students from lower socioeconomic social groups. Additionally, students who did transfer were not likely to end up at a high achieving school. The findings of the binary logistic regression demonstrated that transfer students were significantly more likely to live near alternative school options.

Dispute resolution outside of courts: procedural justice and decision acceptance among users of ombuds services in the UK

Attitudes towards legal authorities based on theories of procedural justice have been explored extensively in the criminal and civil justice systems. This has provided considerable empirical evidence concerning the importance of trust and legitimacy in generating cooperation, compliance and decision acceptance. However, not enough attention has been paid to attitudes towards institutions of informal dispute resolution. This paper asks whether the theory of procedural justice applies to the alternative dispute resolution (ADR) context, focusing on ombuds services. What are the predictors of perceptions of procedural justice during the process of dealing with an ombuds, and what factors shape outcome acceptance? These questions are analyzed using a sample of recent ombuds users. The results indicate that outcome favorability is highly correlated with perceived procedural justice, and both predict decision acceptance.

Equitable representation in councils: theory and an application to the United Nations Security Council

We analyze democratic equity in council voting games (CVGs). In a CVG, a voting body containing all members delegates decision-making to a (time-varying) subset of its members, as describes, e.g., the relationship between the United Nations General Assembly and the United Nations Security Council (UNSC). We develop a theoretical framework for analyzing democratic equitability in CVGs at both the country and region levels, and for different assumptions regarding preference correlation. We apply the framework to evaluate the equitability of the UNSC, and the claims of those who seek to reform it. We find that the individual permanent members are overrepresented by between 21.3 times (United Kingdom) and 3.8 times (China) from a country-level perspective, while from a region perspective Eastern Europe is the most heavily overrepresented region with more than twice its equitable representation, and Africa the most heavily underrepresented. Our equity measures do not preclude some UNSC members from exercising veto rights, however.

Performance Evaluation of a Statistical and a Neural Network Model for Nonrigid Shape-Based Registration

Shape-based registration methods frequently encounters in the domains of computer vision, image processing and medical imaging. The registration problem is to find an optimal transformation/mapping between sets of rigid or nonrigid objects and to automatically solve for correspondences. In this paper we present a comparison of two different probabilistic methods, the entropy and the growing neural gas network (GNG), as general feature-based registration algorithms. Using entropy shape modelling is performed by connecting the point sets with the highest probability of curvature information, while with GNG the points sets are connected using nearest-neighbour relationships derived from competitive hebbian learning. In order to compare performances we use different levels of shape deformation starting with a simple shape 2D MRI brain ventricles and moving to more complicated shapes like hands. Results both quantitatively and qualitatively are given for both sets.

Welke 'acteur' neemt de controllerrol als extraverte business partner?

Which 'actor' takes the management accountant role as an extravert business partner? Does a relation between the personal trait Extraversion and fulfilling a management accountant role as a business partner exist? Open Universiteit Nederland End thesis MSc Management, Accounting & Finance Support 1: Prof. dr. A.C.N. van de Ven RA Support 2: dr. P.C.M. Claes Examinator: dr. P. Kamminga Date of approval: September 3, 2014 student: P.R. van der Wal (studentnumber 839104017 email petervanderwal2003@yahoo.com The main question of this research is: Does a relation between the personal trait Extraversion and fulfilling a management accountant role as a business partner exist? This research is based on the dataset obtained by the controller survey 2013, executed in commission of the 'Open Universiteit' (Bork & van der Wal, 2014). From the literature review it is clear: among other management accountant roles we need business partners. And there is a relation between the personal trait Extraversion and fulfilling the role as business partner. At the same time a lack of necessary personal traits for this role has been noticed, among which is Extraversion. The factor- and cluster analyses reported by Bork & van der Wal (2014) resulted in the identification of two types of management accountant roles. In this extended research TYPE II is identified as a business partner because (s)he practices activity-combinations which are related to strategy, analyzing, supporting management in decision making, advisory, change-agency and representing the organization. 36% of the population of Dutch management accountants with a master degree (or similar) meet with the role of the business partner. Although the fulfillment of the role (TYPE II) is not purely business partnering. E.g. reporting and scorekeeping are still activities executed by TYPE II and it is not clear to what extent. Apart from that, role TYPE I executes change management and risk-management activities, which are (according to the definition) activities that belong to the business partner. The role as business partner is practiced but not that optimal as defined in theory. The logistic regression analyses on the survey-data show that Extraversion among three other triggers is significant for the prediction of the fulfillment of the management accountant role (Bork & van der Wal, 2014). A more extravert personal trait predicts a preference for TYPE II, which relates to the business partner. This 'in depth research' concentrated on the relation between the Big Five personal traits and the six activity-combinations (factors) instead of on the two clusters (I and II). The statistic analyses confirm the predicting influence of Extraversion on the business partner role. Although, except for one factor, no extra significance has been found in this additional research. The essential question can be confirmed positively: the management accountant role business partner exists in practice, some management accountants are more extravert then others, and there is a positive relation between extraversion and fulfilling the business partner role. Some formulated research limitations are related to the statistical weakness of some prediction outcomes and to interpretation differences that might occur. Further research can e.g. concentrate on the other personal traits and the significance for role-differentiation in education programs. The management accountant survey 2013 Management accountant roles in 2013 in the Netherlands Open Universiteit Nederland End thesis MSc Management, Accounting & Finance Support 1: Prof. dr. A.C.N. van de Ven RA Support 2: dr. P.C.M. Claes Examinator: dr. P. Kamminga Date of approval: September 3, 2014 student: P.R. van der Wal and H.J. Bork studentnumber: 839104017 and 838532340) email: petervanderwal2003@yahoo.com and hjbork@hotmail.com This paper describes the conceptual model and results of the 'management accountants survey 2013'. The survey is part of a longitudinal survey, earlier executed in 2004, 2007 and 2010 under responsibility of the 'Open Universiteit Nederland'. Secondly the dataset of this survey will be used by us to do our own analyses on the predicting value of the triggers 'personality factor: extraversion' and 'lever of control: interactive controls' on the management accounting role that comes close to a role defined as 'Business Partner'. Scientific research shows that there are different management accounting roles, and that these roles change and that preferences exist for certain roles (Verstegen B. , Loo, Mol, Slagter, & Geerkens, 2007). The main question that will be answered in this paper is which coherent combinations of activities are being executed by management accountants in 2013 in the Netherlands by master-graduates? And secondly which triggers of management accountants' activities predict to which cluster a management accountant belongs? The conceptual model of this research has been developed in 2004 (Verstegen B. , Loo, Mol, Slagter, & Geerkens, 2007). For this research the same 37 activities as in the former researches are included (appendix 1). In the trigger-set (appendix 1) some adaptations have been made for reasons of restricting the length of the survey and to pinpoint on particular research goals (e.g. personality and levers of control). The coherent combinations of activities were found by a factor-analysis and the groups of controllers by a cluster analysis. A regression analysis shows which trigger-items are most significant. The survey has been sent to 2.353 students that finished a controller-study on a Dutch University. There was a 9% (211) response with a completely filled survey. 137 of which indicated to work in a controller-function at the moment. These controllers have been included in the results. The factor-analysis results in six different coherent combinations of activities (factors). Shortly these factors are: advising top management on strategic level with result-effecting information (1), organizing internal reporting (2) organizing and representing the organization on external reporting (3), advising and managing changes by shortcomings in processes and control systems (4), maintaining and managing administrative organization- , information- and control systems (5) and organizing/executing risk management and internal audit (6). Factors 4, 5 and 6 are clustered in cluster TYPE I (125 controllers) and factors 1, 2 and 3 in cluster TYPE II (69 controllers). TYPE II can be associated with the management accountant role 'Business Partner', although the accountant keeps partly active in a scorekeeper role. The four most significant triggers for predicting being a TYPE II controller are 'Executing a risk-management task in order to meet compliance standards' (1), extraversion (2), company size in terms of fte (3) and gender (4).

Towards a knowledge-based approach for effective decision-making in railway safety

Purpose – This paper aims to contribute towards understanding how safety knowledge can be elicited from railway experts for the purposes of supporting effective decision-making. Design/methodology/approach – A consortium of safety experts from across the British railway industry is formed. Collaborative modelling of the knowledge domain is used as an approach to the elicitation of safety knowledge from experts. From this, a series of knowledge models is derived to inform decision-making. This is achieved by using Bayesian networks as a knowledge modelling scheme, underpinning a Safety Prognosis tool to serve meaningful prognostics information and visualise such information to predict safety violations. Findings – Collaborative modelling of safety-critical knowledge is a valid approach to knowledge elicitation and its sharing across the railway industry. This approach overcomes some of the key limitations of existing approaches to knowledge elicitation. Such models become an effective tool for prediction of safety cases by using railway data. This is demonstrated using passenger–train interaction safety data. Practical implications – This study contributes to practice in two main directions: by documenting an effective approach to knowledge elicitation and knowledge sharing, while also helping the transport industry to understand safety. Social implications – By supporting the railway industry in their efforts to understand safety, this research has the potential to benefit railway passengers, staff and communities in general, which is a priority for the transport sector. Originality/value – This research applies a knowledge elicitation approach to understanding safety based on collaborative modelling, which is a novel approach in the context of transport.

Behavior change theory, content and delivery of interventions to enhance adherence in chronic respiratory disease: A systematic review

Background: We sought to describe the theory used to design treatment adherence interventions, the content delivered, and the mode of delivery of these interventions in chronic respiratory disease. Methods: We included randomized controlled trials of adherence interventions (compared to another intervention or control) in adults with chronic respiratory disease (8 databases searched; inception until March 2015). Two reviewers screened and extracted data: post-intervention adherence (measured objectively); behavior change theory, content (grouped into psychological, education and self-management/supportive, telemonitoring, shared decision-making); and delivery. “Effective” studies were those with p < 0.05 for adherence rate between groups. We conducted a narrative synthesis and assessed risk of bias. Results: 12,488 articles screened; 46 included studies (n = 42,91% in OSA or asthma) testing 58 interventions (n = 27, 47% were effective). Nineteen (33%) interventions (15 studies) used 12 different behavior change theories. Use of theory (n = 11,41%) was more common amongst effective interventions. Interventions were mainly educational, self-management or supportive interventions (n = 27,47%). They were commonly delivered by a doctor (n = 20,23%), in face-to-face (n = 48,70%), one-to-one (n = 45,78%) outpatient settings (n = 46,79%) across 2–5 sessions (n = 26,45%) for 1–3 months (n = 26,45%). Doctors delivered a lower proportion (n = 7,18% vs n = 13,28%) and pharmacists (n = 6,15% vs n = 1,2%) a higher proportion of effective than ineffective interventions. Risk of bias was high in >1 domain (n = 43, 93%) in most studies. Conclusions: Behavior change theory was more commonly used to design effective interventions. Few adherence interventions have been developed using theory, representing a gap between intervention design recommendations and research practice.

Subliminal or not? : An appraisal of semantic processing in the near absence of visual awareness

Stimuli that cannot be perceived (i.e., that are subliminal) can still elicit neural responses in an observer, but can such stimuli influence behavior and higher-order cognition? Empirical evidence for such effects has periodically been accepted and rejected over the last six decades. Today, many psychologists seem to consider such effects well-established and recent studies have extended the power of subliminal processing to new limits. In this thesis, I examine whether this shift in zeitgeist is matched by a shift in evidential strength for the phenomenon. This thesis consists of three empirical studies involving more than 250 participants, a simulation study, and a quantitative review. The conclusion based on these efforts is that several methodological, statistical, and theoretical issues remain in studies of subliminal processing. These issues mean that claimed subliminal effects might be caused by occasional or weak percepts (given the experimenters’ own definitions of perception) and that it is still unclear what evidence there is for the cognitive processing of subliminal stimuli. New data are presented suggesting that even in conditions traditionally claimed as “subliminal”, occasional or weak percepts may in fact influence cognitive processing more strongly than do the physical stimuli, possibly leading to reversed priming effects. I also summarize and provide methodological, statistical, and theoretical recommendations that could benefit future research aspiring to provide solid evidence for subliminal cognitive processing.

Predictive Analytics and Decision Support for Heart Failure patients

Thesis (Master's)--University of Washington, 2016-08

Evaluating statistical and machine learning methods to predict risk of in-hospital child mortality in Uganda

Thesis (Master's)--University of Washington, 2016-08