Curiosity, information quality, and farsighted thinking in decision making:
Measurement and allocation for decision optimization
Research in decision making has demonstrated several factors that correlate positively with decision optimization.[1] Two of these factors—information quality and farsighted thinking—have been identified as significant contributors to decision optimization.[2] Concurrently, research in cognitive psychology and neuroscience provides insight as to the influence of curiosity on information seeking behavior.[3] However, there has been little study of the relationship between curiosity and information seekers’ decision optimization. Therefore, an investigation into the role curiosity plays in farsighted thinking and information quality assessment could provide researchers and practitioners the opportunity to develop methods and techniques that would increase decision optimization by information seekers.
Underline the nouns and then see how the literature defines those terms
Neuroscience has converged with the field of behavioral economics in showing that decision making involves not only the cold-hearted calculation of expected utility based upon explicit knowledge of outcomes but also more subtle and sometimes covert processes that depend critically upon emotion. (Baba Shiv)
a particular neurobiological theory of decision making, termed the somatic-marker hypothesis, in which emotions, in the form of bodily states, bias decision making toward choices that maximize reward and minimize punishment (Shiv)
prospect theory
factors that affect DM
perceived importance
time
information quality
affect
[[I hypothesize that curiosity has an inverse relationship to the perceived costs of information seeking, primarily time and effort. In other words, if one information seeker is curious about a topic about which a decision is to be made and another information seeker is not curious/interested, the curious one will be willing to expend more time and effort to evaluate the quality of the information used to inform the decision. Thus, the cost of time and effort required to evaluate information accuracy is less for the curious information seeker than for the disinterested one. Similarly, the curious information seeker would be more likely than the disinterested one to allocate time and energy to discover information that facilitates farsighted thinking, as he or she would appreciate the added value that contemplating long-term consequences offers the decision maker.
If both of these hypotheses are true, then any methods or techniques that heighten information seekers’ curiosity must have a positive effect on decision optimization, which is desirable from multiple physical, mental, and societal perspectives.]]
The Adaptive Decision-Maker Framework
The Adaptive Decision-Maker Framework is an example of the Information Processing Approach to decision-making. It is concerned with how individuals choose between different courses of action, in particular, in choice situations where no single alternative (or option) is best on all attributes (or qualities, features). These sorts of decisions are known as preferential choice problems.
The Adaptive Decision-Maker Framework argues that preferential choice problems are generally solved through a process of information acquisition and evaluation about the alternatives and their attributes. The attributes by which the different options are defined will vary according to:
• their desirability to the decision-maker;
• the uncertainty of actually receiving the attribute value;
• the willingness of the decision-maker to accept a loss on one attribute for gain on another attribute.
The following example illustrates the role of attributes in the decision-process put forward by the Adaptive Decision-Maker Framework.
Figure 1:
An illustra
tion of the role
of a
ttributes in th
e decision process
An indiv
i
dual is weighing up the meri
ts of various holiday destinations.
The desirabilit
y
of the attr
ibutes to the decision-maker
The following attributes are im
portant to this individual:
•
Weather: very warm and sunny
•
Culture: unspoilt, not touristy
•
Journey time: no more than 10 hours
•
Personal s
a
fety: holidaying al
one, wants to feel safe
•
Location: seaside but near mountains.
•
Language: native language mu
st be Spanish or English widely spoken.
Other attributes of these
destinations (for example,
type of local cuisin
e,
opportunities for shopping) are not important to
this individual.
In addition, two of
the destinations have ‘unique’ des
ired attr
ibutes not shared with the other options
(one offers the opportunity of visiting a
country never visit
ed before, another has
relatives liv
ing in the vicinity thus a
ffording the chance to visit them).
The uncertaint
y
of actually
receiving the a
ttribute
value
Some of the desired attributes are more ce
rtain than others. Thus
the location and
language of the various destinations can
be carefully researched in advance and
the individual can be certain about these.
There is less certainty with respect to
other attributes and the level of certai
nty may vary betw
een alternatives. Thus,
whilst for one destination there is
90% certainty that it will be 75
0
F and will have 8
hours sunshine each day, another destinati
on may be warmer and sunnier but the
weather is less predictable and there is onl
y a 75% chance of temperatures of at
least 80
0
F and 10 hours sunshine per day. A
nother source of uncertainty in this
situation is that the individual
is s
o
mewhat dependent on other people’s
judgements as to how ‘touristy’ each destination is.
Willingness to accept loss on one attribute for gain on another
Finally, in making a decision, this individual
is prepared to forgo a journey ti
me of
less than 10 hours in order to gain a
greater guarantee of
personal safety.
Research Plan for Dissertation Proposal
Search terms
Curiosity literature review
Curiosity neuroscience
Decision making curiosity
Decision making literature review
Decision making psychology curiosity
Epistemology curiosity
Epistemology decision making
Farsighted (and far sighted) neuroscience
Farsighted (and far sighted) decision making
Information quality decision making
Information quality literature review
Information seeking curiosity
Information seeking neuroscience
Knowledge gap curiosity
Long-term curiosity
Neuroscience decision making
Time decision making
Time curiosity
Databases
Web of Knowledge—completed
Google Scholar
Scopus
ProQuest
EBSCO
Also
Identified influential articles and books, and followed their references, as well as the publications in which the author(s) is(are) cited.—under way
[1] 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.
[2] I’ll have to add citations, etc. here.
[3] Citation to come.
