Curiosity, Farsighted Thinking, and Information Quality: Testing a Theory To Improve Decision Making
Dissertation Proposal
Diana Ascher
IS 298B—Special Topics in Information Studies
Graduate School of Education & Information Studies
University of California, Los Angeles
Committee Chair(s)
Professor Leah Lievrouw, Ph. D
Professor TKTK, Ph. D
Committee Member(s)
Professor Craig Fox, Ph. D
Professor TKTK, Ph. D
March 13, 2013
Abstract
Two factors—farsighted thinking and information quality—have demonstrated a positive correlation to good decision making. In addition, research on the relationships between curiosity and information-seeking behavior, temporal mindset, and decision making, as well as decision making in relation to temporal mindset and information-seeking behavior. The author notes a lack of research examining whether there is a correlation between curiosity and temporal orientation, and/or curiosity and information-seeking behavior as drivers of good decision making. Research is proposed to test a model that determines whether such correlations exist among decision-making factors. If the aims of the research proposal are achieved, the contribution to the knowledge of decision making not only will advance decision-making research in multiple disciplines, but also will provide practitioners and researchers opportunities for creating curiosity-enhanced environments to promote good decision making in all contexts.
Keywords
curiosity, decision making, epistemology, farsighted thinking, information quality, information-seeking behavior, Internet search, intrinsic motivation, long-term decision making, truth threshold
Problem statement
Factors that contribute to improved decision making have been studied in a variety of disciplines. Two of these factors—farsighted thinking and information quality—are among those that have demonstrated a positive correlation to good decision making. (Ascher, 2009; Rieh, 2002, Han and Lerner, 2007; Chiu, 2008) Both of these factors require the opportunity to have and/or acquire knowledge that may better inform a decision.
Further, epistemic curiosity has been studied in relation to:
• information-seeking behavior (Arnone and Small, 1995; Day, 1969; Frick and Cofer, 1972; Golman and Loewenstein, 2012; Harvey et. al., 2007; Litman, 2012; Litman, Hutchins, and Russon, 2005; Maw and Maw, 2012; Menon and Soman, 2012; Mikulincek, 1997; Pluck and Johnson, 2011) in the fields of information studies, management, and psychology
• temporal mindset (Chen, 2007; Wouters, 2012) in the fields of management and game discourse theory
• decision making (Amit and Sagiv, 2013; Lee et. al., 2012; Lowenstein, 1994; Loewenstein et. al., 2003; Macedo and Cardoso, 2012; van Dijk and Zeelenberg, 2007) in the fields of management, organizational behavior, neuroscience, and psychology
Additionally, researchers have studied decision making in relation to temporal mindset (Ascher, 2010; Milkman, 2007; Princen, 2009) and information-seeking behavior (Fallis, 2009; Heath and Gonzalez, 1995; Payne, 1976; Taylor, 1975). However, there has not been research examining whether there is a correlation between curiosity and temporal orientation, nor curiosity and information-seeking behavior as drivers of good decision making. Therefore, a study determining whether any such correlation exists will provide practitioners and researchers opportunities for creating superior environments for good decision making.
Justification and significance
The decision making process has as its ultimate objective to advance human dignity for all people. (Lasswell and McDougal, 1992) With this understanding, it is reasonable to conclude that good decision making is in the public interest, nationally and globally.
It is logical to ask why this study focuses on information quality and farsighted thinking, rather than any number of other variables correlated with good decision making. Research in decision making has yielded dozens of factors that contribute to improved decision making. However, of these factors, both farsighted thinking and information quality additionally are connected directly to epistemic curiosity. (Day, 1969; Arnone, 1995; Mikulincer, 1997; Chen, 2007; Goldman and Loewenstein, 2012; Harvey, 2007 Litman, 2012; Wouters, 2012)
Determining whether curiosity enhancement improves decision making as a result of eliciting farsighted thinking and/or stricter information quality standards not only moves the field of Information Studies toward new approaches for improved decision making, but it also brings together the fields in which any of decision-making factors are key areas of research. Given that researchers have demonstrated a positive correlation between good decision making and epistemic curiosity, farsighted thinking, and information quality, this study will enrich the fields of Behavioral Economics, Education, Information Studies, Management, Neuroscience, Psychology, and Public Policy with a more comprehensive understanding of curiosity’s role in decision making and provide cause to bolster decision making environments with enhanced curiosity.
‘Therefore, this study of the respective roles of curiosity, farsighted thinking, and information quality as they contribute to decision making will contribute significantly to decision making research . Because decision making is a critical element in all disciplines, societal undertakings, and personal experience, lessons from this study will create opportunities for improved decision making, as well as a framework for further research into other determinants of good decision making.
Literature review
Keywords
attention, choice, curiosity, decision, decision analysis, decision making, decision theory, epistemic curiosity, epistemology, farsighted planning, farsighted thinking, fMRI, information, information quality, information gap, information theory, information-seeking behavior, Internet search, intrinsic motivation, judgment, knowledge, knowledge gap, long-term curiosity, long-term consequences, long-term decision making, motivation, neurophysiology, neuroscience, perceptual curiosity, physiology, psychology, science, temporal decision making, temporal mindset, time, truth threshold
Databases
Academic Search Complete, American Medical Association Journals, Applied Science & Technology, BioMed Central, Blackwell Reference Online, Business Source Complete, Chronicle of Higher Education, Directory of Open Access Journals, EBSCOhost, ERIC, Factiva, Foundations and Trends in Business and Economics, Foundations and Trends in Technology, Gartner Research, Google Scholar, Guide to Reference, Handbooks in Economics, Harvard Graduate School of Education Harvard Education Review, Health & Psychosocial Instruments, IEEE Xplore, IEEE-Wiley eBooks Library, INFORMS PubOnline, InfoSci-Journals, ISI Web of Knowledge, JAMA, Journals@Ovid, JSTOR Complete Archive and Current Scholarship Collection, Landes Bioscience, LexisNexis Academic, Library Literature and Information Science, MathSciNet, MEDLINE, MIT CogNet, MIT Press Journals, National Academy of Sciences, NTIS, Oxford Journals, Palgrave Macmillan Journals, Philosopher’s Index, Project MUSE, ProQuest, PsycARTICLES, Psychonomic Society Publications, Public Library of Science, PubMed, SAGE Full-Text Collections, ScienceDirect, Scopus, Social Science Research Network, Springer, SSRN eLibrary, Taylor & Francis, University of California Press Journals, University of Chicago Press Journals, Web of Knowledge, Web of Science, Wiley-Blackwell Journals, Wiley InterScience, WorldCat
Bibliographic style
Publication Manual of the American Psychological Association, Sixth Edition, American Psychological Association
Conversations on curiosity, decision making, farsighted thinking, and information quality are taking place in the following American Psychological Association-styled journals: Journal of Education for Library and Information Science, Cognitive Systems Research, Educational Technology Research and Development, Interacting with Computers, Journal of Experimental Psychology, Journal of Leadership and Organizational Studies, Journal of Neuroscience, Psychology and Economics, Journal of Personality & Social Psychology, Journal of Research in Personality, Journal of the American Society for Information Science, Organizational Behavior and Human Decision Processes, Organizational Behavior and Human Performance, Personality and Individual Differences, Perspectives in Psychological Science.
The following journals publish discourse on similar topics using Chicago Manual of Style guidelines: The Information Society: An International Journal, Global Environmental Politics.
These journals require a house style: Decision Sciences, Health Education Research, Neuroscience Research, Educational Research Bulletin, GESJ: Education Science and Psychology, Journal of Advertising, Journal of Policy Sciences.
Given that the majority of the journals hosting discourse on topics most relevant to curiosity and decision making tend to require the APA 6th Edition style, I employ this style for this work.
Research themes
Curiosity as a driver of factors that influence decision making; information quality and decision making; confidence in information quality; truth thresholds; short- versus long-term consequences and decision making; neuroscientific evidence of curiosity during decision making
Planned process
This study entails a thorough examination of the research literature in several disciplines and identification of the areas where findings in each domain may contribute transversally to decision making research in other fields. The primary areas of study and the key contributors to the relevant literature are detailed in Appendix A.
The literature review focuses on the sources of curiosity (also called intrinsic motivation), which I assert have a domino effect on factors contributing to good decision making—particularly temporal mindset and information quality. Once an overarching understanding of each area of research is attained, focused readings of transdisciplinarily relevant research will lay the groundwork for development of a framework to measure the contribution that curiosity makes to decision making in any discipline.
Theoretical structure
This paper references several terms that have specific meanings in various disciplines. To ensure common understanding of these terms, definitions are provided for review in Appendix B.
Known
Many characteristics of and factors contributing to good decision making are known. Curiosity—an innate element of attention—creates physiological rewards, influences information-seeking behavior by generating a need to fill in information gaps, and positively correlates to good decision making. Attention, farsighted thinking, and high standards for information quality also have positive correlations to good decision making. These and other factors contributing to good decision making are the subject of research in a variety of fields of study.
Unknown
Both the relationship between farsighted thinking and curiosity and the relationship between information quality and curiosity are unknown. Similarly, it is unknown whether heightening curiosity during the decision making process encourages farsighted thinking and/or stricter standards for information quality, resulting in improved decision making. Further, allocation of resources to increase curiosity as a component of farsighted thinking and information quality has not been determined, not investigated.
Theory
Curiosity has been studied in several disciplines. This research has looked at curiosity as it relates to decision making, but not as a driver of good decision making with regard to the thresholds by which information seekers assess their confidence in information quality, nor with regard to the contemplation of short- or long-term consequences.
The following relationships have been well demonstrated in the literature:
1. curiosity/farsighted thinking (C/FST)
2. curiosity/good decision making (C/GDM)
3. curiosity/information quality (C/FQ)
4. farsighted thinking/good decision making (FST/GDM)
5. information quality/good decision making (IQ/GDM)
Given the wide range of occasions for decision making and the multiple factors that inform decision makers’ information-seeking behavior, this study focuses on the relative influences of three variables and the assertion that one of the variables—curiosity—not only leads to better decision making, but does so by enhancing information seekers’ assessment of information quality and contemplation of long-term consequences. In other words, the three variables independently positively correlate to good decision making; taken together, the correlation is stronger and can be bolstered by focusing on curiosity as a mechanism to direct effort toward improvement of information quality assessment and the adoption of a farsighted thinking mentality.
Therefore, this study will focus on the relationship between curiosity, information quality, and farsighted thinking, as interrelated drivers of good decision making. This means, certainly, that the relative contributions of curiosity, farsighted thinking, and information quality can be taken together to develop methods and techniques to enhance decision making.
This study does not account for any negative effects of curiosity on other factors that may influence decision making. However, I assert that the other factors (such as accountability, tacit knowledge, anxiety, and information aversion) can be assessed by applying the framework created for and used in this study: the Factor Relationship Model.
The proposed research study will test whether curiosity is positively correlated to farsighted thinking and high standards for assessment of information quality in the decision making process. I hypothesize that heightened curiosity affects at least two contributing factors of decision making: temporal mindset and information quality. If there is, indeed, a positive correlation, decision making can be improved by injecting curiosity-enhancing elements into the decision-making process. In addition, the Factor Relationship Model can be employed to evaluate other potentially interdependent decision-making factors.
Purpose
Vision
Curiosity and Information Studies are inextricably linked, because curiosity is an innate, epistemic drive of all human beings that can only be sated by the acquisition of information. Conducting this study will be instrumental in realizing my vision that the relevance of Information Studies be considered transversal—applicable and appealing across fields of study and disciplines of practice—in decision making. I wish to draw from the theory and practice in multiple fields to change the way researchers and practitioners think about the roles of curiosity and information in the decision-making process.
Mission
My mission is to catalyze practical application of approaches and techniques that make best use of resources by emphasizing curiosity—a key component of both farsighted thinking and high standards of information quality—in the decision making process.
Goals
The aim of this study is to demonstrate that curiosity influences at least two key factors of good decision making—temporal mindset and information quality—which depend on information practices and methods. I intend to publish at least one article in a journal such as Decision Sciences, Policy Sciences, and Journal of the American Society for Information Science.
Objectives
The three primary objectives of this study are:
1. To ascribe and analyze the state of research on curiosity, farsighted thinking, and information quality as related to decision making
2. To test a model that reveals whether curiosity influences information-seeking behavior and temporal mindset in a way that improves decision making
3. To determine through fMRI brain activity mapping and computer-assisted questioning if and when curiosity is related to various steps in a decision-making task
Research questions
This study asks the following questions about the role of curiosity as a driver of farsighted thinking and high information quality standards in decision making:
1. [KEY] Does increasing curiosity to encourage farsighted thinking and high standards for information quality result in better decision making?
2. What is the role of curiosity in a decision maker’s assessment of truth claims and time horizon?
3. Does the data demonstrate a relationship among curiosity, farsighted thinking, and information quality in the decision making process? If so, what are the implications of this relationship?
Hypothesis
The influence of curiosity on temporal mindset has been established by Chen (2012) and Wouters, et. al. (2007). Similarly, Day (1969), Litman (2012), Loewenstein (2012), and many other researchers have documented curiosity’s role in information-seeking behavior. In addition, Lowenstein and Lerner (2003), van Dijk and Zeelenberg (2006), Simon (1979), and several others have made clear the causal relationship between curiosity and decision making. It also has been demonstrated that temporal mindset and information quality assessment are key factors in decision making. (Ascher, 2009; Chie et. al., 2008; Han and Lerner, 2010; Milkman et. al., 2008; Princen, 2009; Kahneman and Tversky, 1979; Rosanas, 2008; Fallis, 2009; Payne, 1976; Heath and Gonzalez, 1995; Taylor, 1975; Beach, 1993; Smith, 1959; Rieh, 2002; and Yager, 1988)
I posit that a further connection can be made: Enhancing curiosity serves to bolster both farsighted thinking and high standards for information quality assessment, which both lead to better decision making. In other words, curiosity (arising from information gaps) influences information-seeking behavior by stimulating information seeking that satisfies information quality thresholds and the desire to maintain a farsighted mindset with the overall objective of making better decisions.
It follows, then, that efforts to instigate curiosity not only improve decision making directly, but also by bolstering farsighted thinking and high information quality standards. It may be the case that concentration of resources on curiosity-enhancing efforts will create a greater improvement in decision making than directing resources separately to encourage long-term thinking and improved information quality, though this is beyond the scope of the current study.
I will conduct an experiment in which participants are faced with a decision for which they need information to take action. Participants will have access to the Internet to conduct their research. The decision at hand will have a long-term consequence, as well as an information gap to be filled in order for the participants to make a decision. The farsighted implication requirement is similar to that seen in public policy experiments on decision making under uncertainty. (Ascher, 2009) The information requirement is in line with decision making studies in cognitive psychology. “Normative models show that decisions should be influenced by both prior probabilities…and evidence.” (Delosh and Merritt, 2000, p. 4)
Methodology
I will employ mixed methods to collect data from this experiment: fMRI mutual information analysis and computer-aided questioning, both integrated with a decision-related task. Throughout the exercise, subjects will undergo fMRI monitoring. Subjects’ brain activity will be mapped against the timeline of the decision-related task to determine if and when regions of the brain associated with curiosity are activated during the exercise. For the computer-aided questioning, the following data will be tracked for each study participant:
1. time devoted to information search
2. time horizon of each participant’s strategy projection
3. number of Internet sources visited by each participant
4. number of primary-source Internet visits
5. number of secondary-source Internet visits
The computer-based exercise will present a task to be completed by making a decision for a family friend, Bob. The subject will be asked to recommend the best city from among Boulder, Chicago, Nashville, and San Diego to which Bob can relocate based on a set of preferences. (Instructions for the subject are provided in Appendix C.) The fact that the evaluation is for someone with family ties implies an inherent responsibility for the subject to make his or her best judgment in completing the task.
Bob’s preferences will be presented on the computer screen, characterizing his ideal notions of population, environmental rating, public transportation, weather, and cost of living. The subject will have access to scratch paper and pen for note taking and a choice of Internet browsers to do independent research. The subject’s Internet use will not be controlled. In other words, she can seek information to complete the task, or she can browse other websites without researcher judgment.
Supplementary information will appear on the computer screen a total of five times—once for each preference category. For each instance that supplementary information is provided, the subject will be presented with a request to evaluate his or her level of interest in the criterion at hand. At the end of the exercise, the subject will be asked to make his or her recommendation via an online form. The recommendation comprises a selection of city, as well as an optional comment regarding the reasons for the choice.
The population of decision makers is astronomical. Therefore, I am focusing this study on a total population of 20,000 undergraduate students at a state university. There will be 400 study participants in the representatively, systematically selected sample population. I will select a homogenous group of participants for each gender: 200 male and 200 female. The subjects will be divided into four groups of 100, labeled A, B, C, and D. Group A periodically will receive supplementary information (in the form of a newspaper article) designed to encourage thinking about long-term consequences. Group B periodically will receive a news article about the trustworthiness of information. Group C periodically will receive a news article about both long-term consequences and the trustworthiness of information. Group D periodically will receive a news article about an unrelated topic, such as discount moving supplies.
When the exercise begins, the subject will be presented with information about how Bob feels about city size. The subject will be able to search for information about the four cities and their populations (or anything else) until a screen appears, providing Information Supplement 1. After the subject indicates that he has finished reading the supplementary news article, he will be prompted to rate his interest in each of the five preference categories on a seven-point Likert scale. The same routine will proceed for Information Supplements 2, 3, 4, and 5.
Data analysis
Data from both the fMRI monitoring and the computer-aided questioning will be aggregated and analyzed for trends using quantitative data analysis software (NUDIST). Disadvantages of this method include deviation of the experimental environment from how the experience would occur without researcher observation. In addition, subjects may respond differently—consciously or subconsciously—when they know they are being measured physiologically. However, this method is advantageous because it demonstrates neurophysiological activity in response to stimuli over the course of the experiment in a way that can map directly to the decision-making process and the introduction of supplemental information.
The computer-aided questioning will be assessed with a naturalistic qualitative approach. Disadvantages of this method include the risk to precision that derives from subjective assessment. In addition, the controlled experiment is not an exact replication of the decision making exercise as it would occur naturally. I am less concerned about typical criticisms of computer-aided quantitative methods because the way a subject likely would execute this task in reality would be very similar in nature. Therefore, concern about lack of human interaction is not merited in this exercise. This method is advantageous because it is inductive and generalizable to other populations. It is my hope that subsequent studies will reveal similarities and differences in the tendencies and sensitivities within different types of populations.
I will employ an information-theoretic approach for analyzing fMRI data to create a brain activity map during the exercise. I will use a method that leverages the mutual information between two waveforms: the fMRI temporal response of a voxel and the experimental protocol timeline. This method has been applied in numerous studies since the late 1990s because of its robust quantification of the relationship between two waveforms, particularly if the waveforms are nonlinear and/or stochastic. This method is also advantageous over other fMRI methods because “response characteristics of neurons differ between brain regions and in relationship to different stimuli.” The complexity of the relationship between brain activity and stimuli is exacerbated by cognitive and psychological variables, as well. The mutual information method addresses this concern. (Tsai, et. al., 1999)
Data screening for both components of the study will be conducted at the end of each research session, and again at the conclusion of the study. Prior to the start of human testing, IRB certification will be obtained and ethical guidelines will be communicated to all research personnel.
In both data analyses, I will apply a confidence level of .95. This will ensure that the chances of rejecting the null hypothesis is held to .05 alpha. In other words, type I error will be managed to below 5%--it is unlikely that I will conclude that curiosity is not a driver of farsighted thinking and/or high standards for information quality assessment when, in actuality, it is. The risk in this approach is that a .05 alpha increases the likelihood that a type II error will occur. In other words, the low alpha could cause me to accept the hypothesis that curiosity is a driver of farsighted thinking and/or high standards for information quality assessment when, in actuality, it is not.
Schedule
Budget
Personnel
Diana Ascher (Program Director)
PhD Student in Information Studies, University of California, Los Angeles
MBA, Peter F. Drucker Graduate School of Management, 2004; BA, Duke University, 1993
My career began in journalism and public policy. Over the years, I gained significant experience in business, information management, media, publishing, and research. I earned an MBA with concentrations in leadership and strategy and am a first-year PhD student in the Information Studies Department at the University of California, Los Angeles, studying epistemology, information management, and information-seeking behavior.
The common thread woven though my career and education is a fascination with the manner in which information and its transfer affects the ability to take action. Over the years, I've immersed myself in diverse forms of information: writing, reading, theater, music, teaching, programming, multimedia, broadcasting, and other forms of communication aided by technology. For much of my career, I was responsible for content creation, building on my strengths in research, writing, and editing. I had great jobs as newspaper reporter, multimedia producer, news editor, magazine editor, and writer. I am skilled in these areas, but my true passion is information management and communication. In each of my jobs, I've found a way to infuse creativity into information strategy. I enjoy thinking and learning about how individuals and organizations can fashion messages and distribute them effectively so their communications are received as intended. Whether the goal is to generate sales, build relationships, tell a story, solve a problem, or educate, I find information strategy, execution, and the subsequent learning and analysis fascinating.
My own thirst for knowledge and persistent curiosity has led to the proposed scientific investigation. I observe in myself and others different approaches to decision making when curiosity is piqued. In other words, I’m curious about curiosity and its effects on decision making and information selection, assessment, and acquisition. My experience in numerous modes of information creation, management, distribution, and analysis, as well as my technological, analytical aptitude, and passion for the study of information will serve me well in conducting this research.
I am situated to be well-supported in this endeavor. According to the Vice Chancellor for Research at the University of California, Los Angeles, the university “consistently ranks among the nation's leaders in competitively awarded grants and contracts to universities; the campus received more than $1 billion during the 2010-11 fiscal year. At any given time, we have approximately 6,000 funded research projects underway. These projects lead to real-world advances in knowledge and inventions that enhance quality of life around the globe.”
With regard to dissemination of new knowledge created as a result of this study, not only am I well-networked in academic publishing and with multiple universities and their presses, but also the principal investigator has an established reputation in the Information Studies, Communications, and Media fields. In addition, I work with an academic journal co-produced by the Anderson School and Duke University, through which I will have opportunities to publish and network.
I will also have an experienced and talented team. The following is a delineation of the personnel who will compose the research project team and their qualifications:
Dr. Leah Lievrouw (Principal Investigator)
Professor, Department of Information Studies, University of California, Los Angeles
Qualifications
Ph.D., Communication Theory and Research, University of Southern California, 1986; MA, Biomedical Communications, University of Texas Southwestern Medical Center; BJ, University of Texas at Austin
Awards, Honors, Fellowships
Fellow, Sudikoff Family Institute for Education & New Media, 2006-7
Teaching and Research Interests
Dr. Lievrouw’s research and teaching focus on the relationship between media and information technologies and social change. Her most recent book, Alternative and Activist New Media (Polity, 2011) explores the ways that artists and activists use new media technologies to challenge mainstream culture, politics and society. She is co-editor of the four-volume Sage Benchmarks in Communication: New Media (2009), and of The Handbook of New Media (2006). Works in progress include Media and Meaning: Communication Technology and Society (Oxford University Press), and Foundations of Media and Communication Theory (Blackwell). From 2001 to 2005 she was co-editor of the journal New Media & Society.
Previously, Dr. Lievrouw held faculty appointments in the Department of Communication at Rutgers University in New Brunswick, New Jersey, and in the Telecommunication and Film Department at the University of Alabama. She also has been a visiting scholar at the University of Amsterdam's School of Communication Research in the Netherlands and a visiting professor at the ICT & Society Center at the University of Salzburg, Austria.
Other interests include information society, social and cultural aspects of communication/information technologies, scholarly communication, and communication and knowledge.
Expertise
Information-seeking behavior, Internet culture, media & technology, information policy and law; STEM
Ian Fellows (Statistical Consultant)
Consultant, UCLA Statistical Consulting Center
Expertise
Longitudinal clinical trials (Mixed models, Generalized estimating equations, ANCOVA, MANOVA, Repeated Measures ANOVA, etc.), Decision making and artificial intelligence, Survey and psychometric scale design, Hierarchical modeling, Discrete data analysis, Data mining and classification Software; SPSS, R, SAS, R, C++, Java, MATLAB
Super G. S. Student (Researcher)
PhD Student, Department of Information Studies, UCLA
Expertise
Computer-aided and fMRI research studies
S. Graduate School Student (Researcher)
PhD Student, Department of Information Studies, UCLA
Expertise
Computer-aided and fMRI research studies
Evaluation
The proposed study entails research that will be significant to progress in a number of disciplines. In addition, the hypothesis that curiosity encourages both farsighted thinking and high standards of information quality, if accepted, has implications for decision making in all contexts. Therefore, this project will receive significant attention from funding agencies and academic institutions, alike.
The results of the experiment will be objective according to the standards of the scientific method. In addition, the specifications for accepting or rejecting the hypothesis are clear, so a relationship among the identified factors will be determined or it will be determined that the hypothesis is false. This information will be useful in further research, and either outcome will make it possible to achieve the research objectives.
Conclusion
Research on the relationship of curiosity to temporal mindset and standards for assessment of information quality will populate a significant knowledge void in the study of decision making. Previous studies have examined multiple contributing factors of the decision-making process. However, none has investigated whether there are interrelationships among curiosity, farsighted thinking, and information quality as drivers of good decision making. The proposed research will test a model that determines whether such correlations exist among decision-making factors. If the aims of the research proposal are achieved, the contribution to the knowledge of decision making not only will advance decision-making research in multiple disciplines, but also will provide practitioners and researchers opportunities for creating curiosity-enhanced environments to promote good decision making in all contexts.
Appendix A—Literature Review Outline
The primary areas of study and the key contributors to the relevant literature are:
I. Curiosity (affect, emotion) and decision making
a. Amit, Sagiv (2013)
i. High epistemic motivation encourages deliberation and thoughtful processing of information
b. Beresford, Sloper (2008)
i. Emotion and decision making
ii. Main theoretical models of decision making and choice
iii. Evidence and decision making
iv. Decision making by proxy
c. Dietrich (2010)
i. Decision making heuristics
1. Reactions
a. Pre-, during, post-decision
2. Commitment
a. Curiosity
d. Frijda (2010)
i. Emotions as causal determinants of action
1. Changes in motive states
e. Kang, et. al. (2010)
i. Neural correlates of curiosity
f. Lee, et. al. (2012)
i. fMRI during intrinsic action
ii. spontaneous satisfactions from the psychological needs for autonomy and competence during one’s interactions with the environment
g. Lerner, Keltner (2000)
i. Influence of emotion on judgment and choice
h. Loewenstein, Lerner (2003)
i. Affect in decision making
i. Macedo, Cardoso (2012)
i. Psychological constructs of surprise and curiosity play an important role in decision making, particularly in selection of viewpoints during the process of exploring unknown environments
j. Mehmet (2006)
i. Maslow’s Hierarchy of Needs
ii. Making good choices
iii. Bandura’s Social Learning Theory
k. Naqvi, et. al. (2006)
i. Somatic-market hypothesis
1. Decisions are aided by bodily states elicited during deliberation of future consequences and mark options for behavior
2. Neural systems
l. Pugno (2007)
i. Self-determination theory
1. Human needs and self-determination of behavior
ii. Sense of self and ability to choose
iii. Choice and well being
m. Simon (1979)
i. Decision theory pursued for its intrinsic interest
n. van Dijk, Zeelenberg (2006)
i. Curiosity and regret aversion in decision making
ii. Optimal arousal and curiosity drive theories (Litman, Berlyne)
II. Curiosity and information seeking behavior
a. Arnone (1995)
i. Attention, relevance, confidence, satisfaction (ARCS)
1. Heuristic approach to stimulate and sustain curiosity
b. Day (1969)
i. Test of curiosity
1. Positive affect toward novelty and complexity
2. Approach with purpose of exploring
a. Reduces uncertainty
b. Increases information
c. Frick, Cofer (1972)
i. Subjects given questionnaire and then statements including answers recalled ore than subjects not given the questionnaire
d. Goldman, Loewenstein (2012)
i. Curiosity
ii. Information gaps
iii. Utility of knowledge
iv. Curiosity drives information seeking behavior drives decision making
e. Harvey et. al. (2007)
i. Role of curiosity in global managers’ decision making mindfulness
ii. Six-step assessment
f. Litman (2012)
i. I-EC
1. Positive affect
2. Diverse exploration
3. New knowledge
4. Mastery
ii. D-EC
1. Lower uncertainty
2. Specific exploration
3. Information gap
4. Performance-oriented learning
g. Maw, Maw (2012)
i. Children with high curiosity have better retention than children with low curiosity
h. Menon, Soman (2012)
i. Effects of curiosity on consumer motivation and learning
1. Information gap
2. Hint to guide
3. Time
4. Assurance of curiosity-resolving information
5. Use of measures of consumer elaboration and learning
i. Mikulincer (1997)
i. Active search for new information
ii. Secure attachment style
1. More curious
2. More positive attitude toward curiosity
3. Less need for cognitive closure
a. Open to new information
4. More likely to rely on new information
j. Pluck, Johnson (2011)
i. Information gaps as a source of academic curiosity
ii. History of curiosity in psychology and education
iii. Stimulating curiosity is central to education learning
iv. The way that information is presented can influence curiosity
III. Curiosity and temporal mindset
a. Chen (2007)
i. Management of knowledge workers fostering several factors, especially intrinsic motivation
ii. Drucker as father of knowledge worker concept
iii. Innovation diffusion
iv. Farsightedness and network visualization and analysis for insights into network dynamics for SWOT analysis
v. Data quality assessment and awareness of existing data
vi. Knowledge transfer
b. Wouters, et. al. (2012)
i. GDA increased curiosity but did not yield learning
IV. Decision making and information seeking behavior
a. Beach (1993)
i. Prechoice screening of options governs the contents of the set from which a choice is made and summarizes empirical tests of the theory
ii. Image theory
1. What ought to be
2. What decision maker wants the future to be
3. How he is striving to secure that future
iii. Rejection threshold
iv. Method
b. Fallis (2009)
i. Developing value-theoretic epistemology into a tool for decision making using the framework of decision analysis
c. Heath, Gonzalez (1995)
i. Interactive decision making
ii. People increase in confidence when they construct a case for their position individually, without interaction
1. Rationale construction
d. Payne (1976)
i. Information processing leading to choice will vary as a function of task complexity
e. Rieh (2002)
i. Information quality judgment and cognitive authority
f. Simon (1959)
i. Decision making in economics and behavioral science
1. Models of rational decision making
g. Taylor (1975)
i. Information overload leads to cognitive strain leads to bounded rationality/compensatory choice modes
1. Satisficing
2. Incrementalizing
h. Yager (1988)
i. Aggregating multicriteria to form an overall decision function
1. Order weighted aggregation (OWA)
ii. Criteria satisfaction
V. Decision making and temporal mindset
a. Ascher (2009)
i. Policy and farsightedness
b. Chiu, et. Al. (2008)
i. Somatic marker hypothesis
c. Han, Lerner (2007)
i. Expected emotions; temporal decision making
d. Kahneman, Tversky (1979)
i. Decision under risk
ii. Prospect theory
1. Certainty effect
2. Isolation effect
iii. Probabilities
e. Milkman, et. al. (2008)
i. Temporal decision making
f. Princen (2009)
i. Legacy politics as normative project to extend time horizon
1. Structural and cultural factors
ii. Humans’ dual temporal capacities can be manipulated
g. Rosanas (2008)
i. Bounded rationality and self-interest
ii. Short-term emphasis of managerial decision making
VI. Methodology
a. Arnone, et. al. (2012)
i. Call for new ways to study curiosity in the context of today’s information access
ii. Theoretical model for curiosity, interest, and engagement
iii. How individuals tackle research and information seeking tasks
b. Lopatovska, Arapakis (2010)
i. Information science, retrieval, human-computer interaction
ii. Theories, methods, research
c. Saracevic, et. al. (1988)
i. Information seeking behavior methodology
d. Sonnenwald, Wildermuth (2001)
i. Information horizons methodology
ii. Won the ALISE award
VII. Measuring curiosity
a. Berlyne (1957)
i. Human perceptual curiosity increased by
1. Incongruity
2. Surprisingness
3. Relative entropy
4. Absolute entropy
b. Collins, Litman, Spielberger (2003)
i. Berlyne
ii. Perceptual curiosity stimulates exploratory behaviors that are directed primarily towards (sic) gathering new information
iii. Trait scales measuring sensation and novelty
c. Elwyn, Miron-Shatz (2010)
i. Definition of good decision making
1. Measurement
ii. Emphasize decision process over outcomes
d. Kashdan, et. al. (2009)
i. Curiosity and exploration inventory
e. King, et. al. (2002)
i. External influences on intrinsic motivation
1. Social enhancement
2. Cognitive evaluation enhancement
f. Locke, Latham (2006)
i. Because goals refer to future valued outcomes, the setting of goals is first and foremost a discrepancy-creating process
ii. Goals set the primary standards for self-satisfaction with performance
Appendix B—Definitions
bounded rationality
A decision making strategy that accounts for the cognitive shortcomings identified in satisficing
curiosity
The desire for knowledge that motivates individuals to learn new ideas, eliminate information-gaps, and solve intellectual problems. (Litman, 2008)
The desire to obtain new knowledge expected to stimulate positive feelings of intellectual interest (I-type) or reduce undesirable states of informational deprivation (D-type) (Berlyne, 1954; Litman, 2005)
David Hume characterized curiosity as “the love of truth.” (Hume, 1739)
decision optimization
In economics and behavioral economics, good decisions optimize efficiency—resource expenditure is minimized, and financial gain is maximized.
epistemic curiosity (EC)
The desire for knowledge that motivates individuals to learn new ideas, eliminate information gaps, and solve intellectual problems (Berlyne, 1954; Loewenstein, 1994)
epistemology
Study of the origin, nature, and limits of human knowledge. Philosophers have grappled with several issues in epistemology, including whether 1) there are different kinds of knowledge; 2) human knowledge is innate or acquired through experience, or both; 3) knowledge is a mental state; 4) certainty is a form of knowledge; and 5) the primary task of epistemology is to provide justifications for broad categories of knowledge claim or merely to describe what kinds of things are known and how that knowledge is acquired.
flow
When engaged in pursuit to satisfy curiosity, one experiences flow, a state researched and described by Mike Csikszentmihalyi as “the sense of effortless action [felt] in moments that stand out as the best in their lives.” (Csikszentmihalyi, 1997, 29) “On the one hand, we are well aware that some truths are more useful than others, yet when fully immersed in curiosity-driven cognitive activity, the instrumental value of the sought-after truths is often of secondary importance.” (AxelGelfert, 1)
farsighted thinking
A decision making mindset that aims at overcoming shortsighted perspectives in favor of more desirable long-term outcomes, despite the risks and uncertainty that would be resolved with shortsighted action. “Farsightedness does not guarantee good results, but shortsightedness is a far greater threat to desirable long-term consequences.” (Ascher, 2009)
good decision making
In general, the making of a choice that achieves maximum reward and minimum punishment within the personal tolerance range of the decision maker. This reward and punishment may be measured in financial, emotional, physical, or societal terms of gain and loss. Good decision making certainly is relative to circumstance. However, there are several factors recognized in academia and in business that are identified as contributing to good decision making. Definitions of decision optimization exist in several forms across disciplines. In business and public policy, it is the act of finding an alternative with the most cost effective or highest achievable performance under the given constraints, by maximizing desired factors and minimizing undesired ones. In comparison, maximization means trying to attain the highest or maximum result or outcome without regard to cost or expense. Practice of optimization is restricted by the lack of full information, and the lack of time to evaluate what information is available. In computer simulation (modeling) of business problems, optimization is achieved usually by using linear programming techniques of operations research. See also satisficing.
information gap
A lack of data, understanding, or knowledge that motivates a decision maker to search for information that relieves the uncertainty created by its absence
information quality
A user criterion reflecting the assessment of excellence or, in some cases, truthfulness (Taylor, 1986)
probabilistic decision making
In public policy, good decisions result in the maximization of expected values of outcomes (usually monetary outcomes) in situations where future events can be predicted only in terms of probability distributions. Researchers have identified the benefits of and obstacles to farsighted thinking and the effects of a farsighted mentality on decision making.
quality threshold
A personal measure of confidence that one has acquired the knowledge necessary in terms of accuracy, breadth, depth, and reliability to take action.
rewarded decision making
In neuroscience and cognitive psychology, rewards for good decision making come in the form of stimulation in the pleasure centers of the brain, as well as the release of neurochemicals like dopamine, which create pleasure.
satisficing
A decision-making strategy that attempts to meet an acceptability threshold. This is contrasted with decision optimization. (Simon, 1956) Human beings lack the cognitive resources to optimize, because we typically do not know the outcome probabilities, cannot evaluate outcomes precisely, and our memories are unreliable.
truth
Understanding that truth is a topic that has been debated for more than 2,000 years, I will not propose yet another definition. Rather, for the purpose of this study, Peirce’s pragmatic definition is particularly appropriate: Truth is the end of inquiry. (See Hartshorne et al., 1931–58, §3.432.) This definition is apt for my purpose, as the study correlates the end of information seeking activity with satisfaction of an information-seeker’s criteria for truth. In other words, when the information-seeker is satisfied that he has found the information required for him to make an informed decision—when he is confident that the information is true—he stops searching.
truth threshold
The point at which an information seeker is confident that the information under consideration is reliable enough and accurate enough to cease searching for more trustworthy information.
Appendix C—Conferences
September 26, 2013 – EPFL
Stress and Social Economic Decision Making
Stress is a ubiquitous phenomenon in humans’ social environment that can have important consequences both for individuals as well as for society at large. Stress has a major impact on brain function and behaviour, and a wealth of research shows how both chronic and acute stress impact on memory and cognition. Less is known about how stress affects economic judgements, despite a recent surge in research aiming to uncover the neural basis for economic decision making.
The goal of this Symposium is to address the link between stress and social economic decision-making by bringing together leading scientists from the fields of economics, psychology and neuroscience. Experts on stress, emotion, psychopathology and behavioural and neural economics will present their experimental approaches. The symposium includes an overview of current research as well as a debate on where more research is needed, and emphasis is placed on discussions and interactions. There will be a poster session during lunch and coffee breaks and an aperitif for all participants at the end of the symposium.
The symposium will take place on September 26th 2013 in Lausanne, Switzerland. The venue will be the Ecole Polytechnique Fédérale de Lausanne (EPFL) in SV1717a.
The symposium will be a Satellite to the Annual Conference of the Society for Neuroeconomics that will also take place at the EPFL from September 27-29.
Organisers:
• Carmen Sandi (BMI, EPFL, Lausanne) [Lab website]
• Lorenz Goette (HEC, Lausanne) [Department website]
Venue: School of Life Sciences, EPFL, Switzerland
Registration (mandatory) is requested by September 16, 2013 (please note that it is limited to 100 persons; places will be given on a first-come, first-served basis).
Registration fee: 30 CHF (20 CHF for students) which includes lunch, coffee breaks and a welcome drink.
Abstract submission deadline: September 1.
Registration Fees
Your registration fee includes breakfast, lunch, and breaks on all three conference days and the annual Society for Neuroeconomics Friday-night banquet dinner! It also includes admission to all workshops, general and special sessions, lectures, and all other conference events.
Early-bird Discounted Rate
(Register before Aug 30) Registration Fee
(After Aug 30)
Nonmember $585 $605
Regular Member $400 $425
Student/Postdoc
Member $315 $340
SPUDM24
Dear friends and colleagues,
It is our great pleasure to invite you to attend the 24th Subjective Probability, Utility, and Decision Making Conference.
EADM's next biannual conference, SPUDM 2013, will be held at IESE Business School - University of Navarra in Barcelona, Spain from Sunday, the 18th till Thursday, the 22nd of August 2013.
The organizing committee is pleased to announce that the conference will feature the following invited speakers:
• Timothy D. Wilson, University of Virginia, USA
• Colin F. Camerer, California Institute of Technology, USA
• Robin Hogarth, Universitat Pompeu Fabra, Spain
• Ralph Hertwig, Max Planck Institute for Human Development, Berlin, Germany
Attending this meeting will also be an opportunity to discover Barcelona, one of the most unique and architecturally distinctive cities of the world. Barcelona is the capital of Spain’s Catalan region, which has produced a number of the world’s most prominent artists including Pablo Picasso and Salvador Dalí. The architect Antoni Gaudí also left his indelible mark on the city through a number of remarkable buildings such as La Sagrada Familia, La Pedrera, and La Casa Batlló.
We look forward to seeing you and to welcoming you to Barcelona!
The local organizing committee:
Elena Reustkaja, Mario Capizzani, Franz Heukamp, and Robin Hogarth.
Last update: March 2013
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