Theory of advice as an information object targeted at an unmade decision
| DOI | https://doi.org/10.1108/JD-05-2019-0099 |
| Date | 02 September 2019 |
| Pages | 212-230 |
| Published date | 02 September 2019 |
| Author | Allen J. Flynn |
| Subject Matter | Library & information science,Records management & preservation,Document management,Classification & cataloguing,Information behaviour & retrieval,Collection building & management,Scholarly communications/publishing,Information & knowledge management,Information management & governance,Information management,Information & communications technology,Internet |
Theory of advice as an
information object targeted
at an unmade decision
Allen J. Flynn
Department of Learning Health Sciences, Medical School,
University of Michigan, Ann Arbor, Michigan, USA
Abstract
Purpose –The purpose of this paper is to advance an understanding of the concept of advice and its
relationship to documents, information and knowledge.
Design/methodology/approach –A conceptual analysis of a sample of 48 relevant advice studies and two
books, directly informed by documentation and information theories, was conducted to find out how
researchers have approached advice conceptually since 1940. Further gains in understanding advice came
from analyzing its relationship with environmental uncertainty.
Findings –Researchers have studied advice in the context of human-human, machine-machine and
information and communication technology-intermediated interactions. Advice has been conceptualized and
categorized in many different ways. Over time, conceptualizations of advice have broadened and become
more general. In this light, it is theorized that advice is as an information object targeted at an unmade
decision. This conceptualization of advice permits situated and momentary advice documents. A newly
developed content-based framework of advice leads to an advice typology with four content-based categories
of best possible advice: correct answers, probabilities, possibilities, and acknowledgments of the unknown.
Research limitations/implications –The refined advice theory, content-based advice framework and
related typology of advice contributed here are small steps toward improved clarity about the nature of
advice. These findings are limited in their focus to advice theory and advice categorization.
Practical implications –Scholars, practitioners and information system developers may reconsider advice
theory and make use of the content-based framework and related advice typology in their work. These
contributions will help advice-givers and the developers of advice-giving information systems and advice
networks to provide better advice.
Originality/value –This paper fills a need for a clear and straightforward overall conceptualization of
advice that accounts for advice documents and is informed by how advice has been previously conceptualized
in multiple scientific fields.
Keywords Decision support systems, Environmental uncertainty, Advice, Advice document,
Advice interaction, Advice theory
Paper type Conceptual paper
Introduction
The paper synthesizes and extends advice theory to reveal more about the nature of advice
and expose its relationship to documents, information and knowledge. It addresses several
questions. What is advice, and what are advice documents? What is the purpose of advice?
What types of advice exist?
Since at least the 1940s, researchers h ave studied advice (Williamson and Bordin, 19 41).
Yet, the natureof advice remains unclear.In current English usage, theword advice connotes
variously as “an opinion as to what action to take,”“a recommendation”or as, “information
imparted”(Oxford English Dictionary, 2017). This paper surfaces and extends available
scientifictheory about advice to conceptualize it more clearly.A brief argument for doing this
has three planks. First, adviceis useful (Collier and Ong,2008; Dexter et al., 2001; Schrah et al.,
2006). Second, advice is the product of economically important legal, financial and medical
advisory services (Bates et al., 2003; Gino, 2008; Hadfield, 2014). Third, advice is too scarce, and
so more of it is needed. Studies from law and medicine provide evidence of the negative
consequences of its scarcity (Covell et al., 1985; González-González, 2007; Hadfield, 2014).
Journal of Documentation
Vol. 76 No. 1, 2020
pp. 212-230
© Emerald PublishingLimited
0022-0418
DOI 10.1108/JD-05-2019-0099
Received 29 May 2019
Revised 17 July 2019
Accepted 18 July 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0022-0418.htm
212
JD
76,1
To date, researchers have approached advice from multiple positions illuminating
several lines of inquiry (MacGeorge, Feng and Guntzviller, 2016). Three of these lines
investigate human-to-human, machine-to-machine, and information and communication
technology (ICT)-intermediated advice and advice interactions.
Prior research on advice surfaces several open questions whose answers are not
self-evident. The overall goal of this conceptual analysis is to clarify the concept of
advice by considering its nature, types and purpose through the lens of the information and
documentation sciences in light of past advice research. This work is timely because
advice-giving systems are growing rapidly in scope, scale and impact.
Background
Foundational concepts related to advice
Advice can generally be understood as a category of material, perceivable information
objects having either a verbal or written form. This understanding mirrors Searle’s (1965)
fundamental notion of a speech act being a rule-governed noise or mark produced by a
speaker or writer who has certain intentions in mind. This starting point permits advice to
be analyzed using theories and methods from the information and documentation sciences.
Any material embodiment of information that can be sensed or perceived is referred to
hereon either as an information object or message (Buckland, 1991). At the outset, advice is
considered to be a proper subset of information objects. The challenge taken up is then to
articulate the intrinsic or extrinsic property or properties that distinguish advice objects
from all other information objects (Gorichanaz and Latham, 2016).
A foundational concept is the advice interaction. An advice interaction is an instance of
advisors and advisees, respectively, giving and receiving advice. Advice interactions are
frequently,but not always, social phenomena. There are timeswhen the self becomes its own
subject enabling a person to self-advise (Foucault, 1988). It is also possible for a machine to
advise anothermachine. While machine-to-machine adviceinteractions are artificial, they arise
from human needs that motivate the makers of decision support systems (Simon, 1996).
Placing advice in the context of decision situations
Advice scholars often place advice interactions in the specific context of decision situations
(Bonaccio and Dalal, 2006; Bryson, 1951; Jureta, 2011; MacGeorge, Feng and Guntzviller, 2016;
McCarthy, 1963; Shortliffe, 1987). Some of these scholars have outlined decision-making
processesinvolving advice in detail (Bryson, 1951;Jureta, 2011). Context hererefers to a set of
backgroundphenomena, or a field of action,within which some focal eventis embedded, such
that the field of action and the focal ev ent inform each other (Duranti and Goodwin, 1992).
Advice interactions are focal events embedded in the larger context of a decision situation.
A decisionsituation is any situationwhen two or more alternativesare under consideration
in advance of a decision being made (Allingham, 2002). A decision (or choice) is said to be
made (or taken) when one alternative is selected while otheralternatives are not (Klein, 2008).
Decisions incur opportunity costs (Frederick et al., 2009). Decision situations encapsulate
decision-making processes involving the weighing of alternatives when tradeoffs apply.
Within a decision situation, decision-making processes may begin with problem
representation and goal-setting (Bryson, 1951; MacGeorge, Feng and Guntzviller, 2016;
Simon, 1996). These preliminary steps support imperfect deliberation over what decision to
take and why to take it (S imon, 1996). Human de cision-making inv olves prior
experience, mental simulation and decision problem categorization (Klein, 2008). During
such decision-making processes, advice interactions happen whenever advice is given and
received. Some decision situations with advice interactions do not end in a decision because
not all decisions ultimately matter (Lewis, 1999).
213
Theory of
advice as an
information
object
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