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Cognitive Approach Using SFL Theory in Capt uring Tacit Knowledge in Business Intelligence

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2019 International Conference on Data and Software Engineering (ICoDSE)
13-14 Nov. 2019
https://ieeexplore.ieee.org/document/9092615
DOI: 10.1109/ICoDSE48700.2019.9092615
Publisher: IEEE
Cite as:
H. Surbakti and A. Ta’a, "Cognitive Approach Using SFL Theory in Capt uring Tacit Knowledge in Business Intelligence,"
2019 International Conference on Data and Software Engineering (ICoDSE), Pontianak, Indonesia, 2019, pp. 1-6, doi:
10.1109/ICoDSE48700.2019.9092615.
Cognitive Approach Using SFL Theory in Capturing
Tacit Knowledge in Business Intelligence
1st Herison Surbakti1,2
Information System
Universitas Respati Yogyakarta1
Yogyakarta, Indonesia
https://orcid.org/0000-0003-4193-446X
2nd Azman Ta’a2
School of Computing
Universiti Utara Malaysia2
Sintok, Malaysia
azman@uum.edu.my
Abstract The complexity of Business Intelligence (BI)
processes need to be explored in order to ensure BI system
properly treats the tacit knowledge as part of data source in BI
framework. Therefore, a new approach in handling tacit
knowledge in BI system still needs to be developed. The library
is an ideal place to gather tacit knowledge. It is a place full of
explicit knowledge stored in various bookshelves. Nevertheless,
tacit knowledge is very abundant in the head of the librarians.
The explicit knowledge they gained from education in the field
of libraries and information was not sufficient to deal with a
complex and contextual work environment. Complexity comes
from many interconnected affairs that connect librarians with
the surrounding environment such as supra-organizations,
employees, the physical environment, and library users. This
knowledge is contextual because there are various types of
libraries and there are different types of library users who
demand different management. Since tacit knowledge hard to
capture, we need to use all possible sources of externalization of
tacit knowledge. The effort to capture this knowledge is done
through a social process where the transfer of knowledge takes
place from an expert to an interviewer. For this reason, it is
important for the interview process to be based on SFL theory
(Systemic Functional Linguistics).
Keywords—Business Intelligence, Tacit Knowledge, SFL
theory
I. INTRODUCTION
Cognitive approach is ideally suited for the capturing
knowledge as from among the massive data available these
days. The decision maker typically must integrate multiple
streams of information from information or other
collaboration with the knowledge systems in making decisions
[1]. Furthermore, decisions may be based in organizational
politics or routines [2], and decision makers may limit
themselves to a few choices because of “bounded rationality”
[3]. Ducharme and Angelelli [4] invented the use of cognitive
as an advanced analytics to capture and extract tacit
knowledge by elaborating the predictive analytics, stochastic
analytics, and cognitive computing. Moreover, the advanced
analytics approach still be implemented in Business
Intelligence (BI) environment [17]. Thus, the basic BI
framework with involving a tacit knowledge approach can be
illustrated as shown in Figure 1.
Figure 1 Tacit Knowledge in BI Framework Using
Cognitive Approach [17]
The academic library has consumers who are not as
heterogeneous as the public library because it serves limited
types of consumers, namely students, lecturers, and university
staffs. This study limits the context by taking academic
libraries as research contexts. Context control is a natural thing
because business organizations are also bound to their
respective contexts. This can be relevant to the business
context where business libraries may only serve the internal
needs of an organization with a limited and certain number of
organizational structures. Context control also simplifies the
problem so that it leaves aspects of the complexity of tacit
knowledge in the library.
The simple stages of capturing tacit knowledge can be
illustrated in Figure 2 below. After a theoretical review, the
data collection scheme consists of three stages, namely
interviews to find out the context for tacit knowledge that is
none other than the problems faced by librarians; the survey
stage that detects librarians who have the tacit knowledge
needed to solve the problem; and the second interview stage,
which revealed tacit knowledge from librarians.
Figure 2 Research Data Collection Scheme
II. DESIGN FOR CAPTURING TACIT KNOWLEDGE
There is small number of earlier research about business
intelligence on academic library and library profession.
Example of this research is Cox and Janti [5] on Library Cube
project, a business intelligence system that demonstrate the
value that can be provided by academic libraries. However,
the research is not targeting the tacit knowledge at all since it
is only targeting the provided information in academic
information system. Heims et al [6] mentions that reporting BI
research and creating BI reports are the key area of
responsibility of librarians in information era. We addressed
the problem by open dialog with librarian, which actually what
considered would happen between BI manager and librarian
to develop clear communication channels [7]. Noted that for
librarian, BI is part of their challenge in information era [8].
Since tacit knowledge is hard to capture, we need to use all
possible sources of externalization of tacit knowledge [9]. The
effort to capture this knowledge is done through a social
process where the transfer of knowledge takes place from an
expert to an interviewer. For this reason, it is important for the
interview process to be based on SFL theory.
According to SFL theory, only a fraction of “can do”
turned into “can mean” and only a fraction of “can mean”
turned into “can say” [9]. This is what is meant by Polanyi
when he said “we know more than we can tell” [10]. Hence,
only a portion of tacit knowledge can be captured by linguistic
means. We need other means that came up from “can mean”
which anything that could analyse semiotically. It could be
non-verbal cues or drawing, written text, etc. We refer to
drawing, photograph, videos, written text, and others as
documented source and beyond our analysis. Here we just
focused on non-verbal cues. However, whenever documented
sources considered relevant, we could use it as source of tacit
knowledge.
A. Linguistic Source of Tacit
According to SFL theory, language is realized in four
strata: semantic, lexicogrammar, phonology, and phonetics
[11]. Semantics is the highest level that explains the hidden
meaning of language. Lexicogrammar is an aspect of language
that explains real meaning, can be seen from the choice of
words and grammar used. Phonology is the meaning that
exists in sound. Phonetics is speech that arises from language
activities. It can be seen that this stratification moves from
something abstract (semantic) to something concrete
(phonetic).
Someone will choose a word to represent his experience
when speaking. What word or wording chosen can distinguish
whether the experience or knowledge expressed is inheritance
or not. In fact, sometimes, a person will find it difficult to find
the right words to describe their knowledge so that they choose
new words, ask the right words, or state their difficulties in
describing them.
From the LCM (Linguistic Categorization Model) and
SFL, it can be concluded that the effort to explore linguistic
knowledge linguistically must be directed to the question
"how" and the words action verbs. This is referred to as
grammar-targeted questioning (GTQ). GTQ are questions that
focus on the word "how" in the interview. It is distinguished
from Content Targeted Questioning (CTQ) which focuses on
"what", "when", and "where" or Semantic Targeted
Questioning (STQ) which focuses on "why".
Zappavigna [9] used GTQ as a supplement to CTQ to
express one's personal knowledge found that GTQ is able to
encourage the concretization of CTQ. In this study, a common
response arises when the resource person is asked "how" is
exposition (‘in other words’), clarification (‘to be precise’), or
exemplification (‘for example’). Responses like these contain
a high load of tacit knowledge because they reach deeper
descriptions of one's knowledge than can be achieved by
content-focused strategies that might only reveal something
very general like 'good', 'well', and 'alright'. If the participant
expresses this in the interview, it is the job of the interviewer
to elaborate this answer in more depth. The interviews need to
be carried out sequentially with the first content-based
interview followed by the grammar-based interview in order
to minimize the substantial learning effect. Substantial
learning effects occur when grammar-based interviews make
participants rethink and reflect on themselves so that it impacts
on subsequent content questions. This results in the answers
given not being comprehensive and depending on the order.
The protocol for running GTQ according to Zappavigna [9] is
as follows:
1. The interviewer asks a general question of the form
“Tell me about your particular area of expertise” (or if
the task/domain is sufficiently specified “Tell me about
task X”).
2. The interviewee responds.
3. The interviewer interrupts the interviewee when he/she
has identified a grammatical feature of under-
representation about the particular content-area of
interest and asks a question aimed at unpacking the
grammatical feature.
4. The interviewee responds to the question
5. The interviewer repeats steps 3 and 4 until he/she has
constructed a coherent argument for a particular
reading of the interviewee’s tacit knowledge about
some topic. The argument is coherent in the sense that
it is supported by multiple patterns of grammatical
features.
6. When the interviewer has achieved an understanding
of the concept/skill that is the topic of the interview he
may present his ‘reading’ to the interviewee, asking a
question of the form “Now I think I have understood
what you mean about X. How do you feel about this
reading?”.
7. The interviewer and interviewee may engage in
unstructured discourse relating to what has occurred in
the interview.
8. The interviewer will conclude the interview at an
interpersonally appropriate juncture.
B. Contextual Resources
Even after knowledge has been expressed verbally and
non-verbally, there is still space where the knowledge of tacit
cannot be expressed at all and can only be demonstrated by
behavior. Apart from observations requiring precise and
specific time, experts generally do not like being observed
while working [12]. In addition, observations become more
complicated when several experts are involved [12]. This can
only be done in a non-intrusive manner such as a surveillance
camera, but it can be a problem with privacy issues.
Alternatively, observations can be made through third-person
testimonies. In this case, the interview was conducted on the
third person who had witnessed the behavior of the first person
who was the target to reveal the knowledge of his possessions.
Fig 3 Design for Capturing Tacit Knowledge
The framework above shows the design used to capture
comprehensive knowledge of experts. Based on SFL theory,
tacit knowledge consists of three levels. The first level is the
most basic level where a person can only do but cannot
interpret it, let alone say it. This knowledge is contextual tacit
knowledge because it can only be raised in a supportive
context. It can only be collected through observation. Even so,
because the context is very specific, in terms of space and
time, only people present in that context can see and
understand from their perspective what the tacit knowledge is.
In this study, it is assumed that the person is a peer.
Researchers collected data on tacit knowledge from peers
through cognitive interviews. Furthermore, we can conclude
there are two ways to collect tacit knowledge:
1. Focused on a stated problem. Participant presented
with a problem which needs tacit knowledge to be
solved. The tacit knowledge needed to solve this
problem can collected with interview, based on
respondents chosen with questionnaire. Questions in
the interview informed by problems urgency, detected
by questionnaire. Here, sequences of the steps
determine the completeness of tacit knowledge. Figure
below show the connection between questionnaire
design and decision.
Figure 4 General flow of information to collect problem
focused tacit data
2. Comprehensive tacit data collection. The technique
above only collects “can say” dimension of tacit
knowledge. Furthermore, the “can say” in this sense
only focused on the problem stated, not all the tacit
knowledge possessed by the participant, at least for the
problem field. The solution is to collect tacit
knowledge data more comprehensive by three means:
a. Using content targeted interview (CTI) and grammar
targeted interview (GTI) to collect “can say”
dimension of tacit knowledge, not bounded by a
problem.
b. Using grammar targeted interview to collect “only can
mean” dimension of tacit knowledge.
c. Using peer cognitive interview (PCI) to collect “only
can do” dimension of tacit knowledge.
The data collection and analysis process are illustrated in
Figure 5.
Note: CTI = Content-targeted interview, GTI = Grammar-
targeted interview, PO = Participant observation, CTK =
Comprehensive tacit knowledge
Figure 5 Comprehensive tacit data collection
As illustrated in Figure 5, data collection process includes
four steps. Each step supplemented by its tool. Notes that text
structures are the input and output from each step. Data results
from “can say” modelling specified as facts, experience,
errors, and anything which only can described by words. For
example, numerical codes or particular reference used by
participants. Data from “Can mean” consisted of words pattern
loaded with emotions or particular stress on something that
signify confidence to a statement. Skills, context,
requirements, or anything which can’t said by words could
results from “can do” modelling.
The two ways to collect tacit knowledge complement each
other. The questionnaire method is quantitative and provides
data focused directly on an issue, which is useful for instant
and standard situations. The interview method is qualitative
and provides more general data. This data must first be
translated into useful data in an instant situation but can be
useful especially when certain problems cannot be obtained
through a questionnaire. General principles from interview
data can be used to be translated quickly at an operational
level.
Figure 6 below could fit well with proposed BI framework
previously modelled in Figure 1. In the model, numeric data
analysis can be considered as part of cognitive analytics using
cognitive mapping process. In itself, problem focused tacit
data is the knowledge component of the model. The same goes
for general tacit knowledge taken by interview process.
Figure 6 Simple Diagram for Tacit Knowledge Capturing
III. RESEARCH DESIGN
This paper focused on tacit data collection problem. This
research is limited to problem focused data collection because
the data is sufficiently structured. However, problem focused
tacit data can achieve comprehension like general tacit data if
the problems are reviewed comprehensively so that they cover
all the problems that exist in the work. This is because tacit
knowledge is procedural, and these procedures are related to
problems. Standard Operating Procedures (SOP) are basically
explicit knowledge to deal with problems in the form of how
to do the job properly. SOP can be part of general public
knowledge if in carrying it out, the resource person is faced
with a different situation from the textbook. If they are the
same, then the only problems are the components of the
knowledge of tacit. The following figure can explain this well.
Figure 7 Scope of tacit knowledge
Mathematically, if E is explicit knowledge and T is tacit
knowledge, then knowledge K is:
K = E + T
T consisted of practices deviates from SOP (D) and
practices to solve problems not stated in SOP (S), then T is
T = D + S
While S itself is problem focused tacit data (F):
S = F
Hence, if D = 0, then T = S = F
This assumes that librarians follow the SOP strictly and all
problems they faced at work is not stated in SOP. Guided by
this assumption, the author feels save to not conduct
observation. Hence, the research steps to collect data
illustrated in Figure 8.
The steps above described as follows:
A. Identify Interview Panel
According to Marshall et al [13], determining sample size
in qualitative Information System (IS) research can be
justified by three methods. First by citing recommendation
from qualitative methodologists. Second, by citing sample
sizes used in studies tackled with similar research problems
and design. Third, by internal justification using statistical
demonstration of data saturation. This study could consider as
case study by focusing in librarian cases. Using first
recommendation, Yin [14] recommends at least six sources for
case study, while Creswell [15] recommends three to five
sources. Meanwhile, looking for case studies in IS research,
Marshall et al [13] recommends that the research should
contain 15 to 30 interviews. For internal justification, the
calculation could infer from Marshall et al [13] graph. The
graph relating sample size with number of codes. Generally,
larger codes mean smallest sample. As we would see in next
section, this research employed 13 codes (questions) for
participants. The value then falls to 7-18 participants in the
research.
Figure 8 Research Design
The interview panel planned to include 23 librarians, each
from different university library in West Java, Indonesia. The
number chosen to compensate the possibility that the next
rounds there are some librarians which declined to participate.
The sample size also fit with average sample size in IS
research, which is between 15-30 interviewees [13]. It is also
larger than sample size recommended by methodologists and
by statistical calculation. If there are reduction of 40% from
each round, in the third round there are still eight librarians
participated, large enough to analyse qualitatively.
B. Conduct First Interview
The first interview consists of two part. The objective
for this interview is to identify points to incorporate into the
questionnaire. To do this, CTI conducted.
Themes for interview were adopted from Si and Yujia
[16] on collective tacit knowledge of librarians. Si and Yujia
[16] mention two forms of librarian’s tacit knowledge:
personal and collective. Our focused only on collective form
since this form ready to share between librarians. Librarian’s
personal tacit knowledge such as librarians’ ability on
scientific research, ability to analyze and solve problems in
the process of knowledge mining and knowledge
reorganization, ability to accept new things and find and solve
the question, and other; is more connected to personality and
as the name implies, highly personal, hence need deeper
reflections and analysis. Furthermore, the collective tacit
knowledge list already exhausted. Given the time and energy
constraint in the interview process, we left the personal tacit
knowledge to further research. The collective tacit knowledge
of librarian according to Si and Yujia [16] includes:
1. The library’s long-established working methods,
2. The common experience of librarians’ dealing with
problems at work;
3. The mechanism of knowledge communications among
librarians, and between librarians and readers;
4. Library’s ability to cope with emergency events and
coordination in internal and external environment;
5. The overall level of library service and reputation;
6. Affinity and cohesion within the library and the
common work philosophy, moral belief and spiritual
outlook embodied in the thoughts and actions of all
librarians.
The questions for interview for informant as follow:
1. Introduction session
2. Ask about ...
a. The library’s long-established working methods
b. List of problems librarians faced at work;
c. List of events when knowledge communication
among librarians needed.
d. List of events when knowledge communication
between librarians and readers needed.
e. List of emergency events in the library.
f. List of coordination events between library and
external environment.
g. List of library current service
h. List of library possible new service
i. List of library’s problems
3. Closing: clarification about next step, ask for second
interview, thank you
C. Develop Questionnaires
Based on the interview results, we made a closed answer
questionnaire. Each question constructed from the abstraction
of each question from CTI. For each question, we assign two
to n number of sub questions according to CTI result. For each
sub question, we provide answer to choose by the librarian.
For example, from CTI, the answer from the question about
“list of problems librarians’ faced at work” could results in
three problems, e.g. noise, broken books, and no returned
book. For this question, questionnaire asked two question.
First: rank the list from the least to the most frequency.
Second: the intensity, asked the respondent to rank the list
from the easiest to solve to hardest to solve. The same goes for
other questions with different criteria to rank.
1. The library’s long-established working methods (highly
inefficient to highly efficient)
2. List of problems librarians faced at work (least frequent
to most frequent)
3. List of problems librarians faced at work (easiest to
hardest to solve)
4. List of events when knowledge communication among
librarians needed (least frequent to most frequent)
5. List of events when knowledge communication among
librarians needed (easiest to hardest to solve)
6. List of events when knowledge communication between
librarians and readers needed (least frequent to most
frequent)
7. List of events when knowledge communication between
librarians and readers needed (easiest to hardest to
solve)
8. List of emergency events in the library (least frequent to
most frequent)
9. List of emergency events in the library (easiest to
hardest to solve)
10. List of coordination events between library and external
environment (least frequent to most frequent)
11. List of coordination events between library and external
environment (easiest to hardest to solve)
12. List of library possible new service (least possible and
most possible)
13. List of library’s reputation problems (least frequent to
most frequent)
D. Second Meeting
In this meeting, we conduct GTI to delve deeper into
interviewee answer to the questions presented in the
questionnaire. The interviewer respond the answer by ask
deeper into the answer provided, by question such as “why this
is the most efficient” respond “what do you mean by”
respond what or how... respond. If the interviewer
understands the answer clearly, give a summary and ask for
improvement: “Now I think I have understood what you mean
about X. How do you feel about this reading?” After this, move
to question two. Same procedure applied. Generally, each
question asked by noting the extreme cases answered by
participant (most or least) The list below listed about what
question to asked after respondent answer a questionnaire
question:
1. Introduction session: thank you, warn about the iterative
character of the interview; informed consent
explanation
2. Based on your questionnaire answer, you stated that:
i. The library’s long-established working methods
(most inefficient to most efficient) why you
think this is the most efficient (most inefficient)?
dig dig summary.
ii. List of problems librarians faced at work (never to
always) why you think this is the most/least
frequent dig dig summary.
iii. List of problems librarians faced at work (easiest
to hardest to solve) why you think this is the
easiest/hardest problem to solve dig dig
summary.
iv. List of events when knowledge communication
among librarians needed (least frequent to most
frequent) why you think this is the most/least
frequent dig dig summary.
v. List of events when knowledge communication
among librarians needed (easiest to hardest to
solve) why you think this is the easiest/hardest
problem to solve dig dig summary.
vi. List of events when knowledge communication
between librarians and readers needed (least
frequent to most frequent) why you think this is
the most/least frequent dig dig summary.
vii. List of events when knowledge communication
between librarians and readers needed (easiest to
hardest to solve) why you think this is the
easiest/hardest problem to solve dig dig
summary.
viii. List of emergency events in the library (least
frequent to most frequent) why you think this is
the most/least frequent dig dig summary.
ix. List of emergency events in the library (easiest to
hardest to solve) why you think this is the
easiest/hardest problem to solve dig dig
summary.
x. List of coordination events between library and
external environment (least frequent to most
frequent) why you think this is the most/least
frequent dig dig summary.
xi. List of coordination events between library and
external environment (easiest to hardest to solve)
why you think this is the easiest/hardest
problem to solve dig dig summary.
xii. List of library possible new service (least possible
and most possible) why you think this is the
most/least possible dig dig summary.
xiii. List of library’s reputation problems (least
frequent to most frequent) why you think this is
the most/least frequent dig dig summary.
3. Ask the possibility that the interviewee have
something to say but unable to say because hard to say
without demonstration.
4. If there any, ask permission to interview his/her peer
about the action because observation from this peer
could tell the difficult thing.
5. If given permission, ask who he/she would
recommend to interviewed.
6. Ask for the last meeting.
IV. CONCLUSION AND FUTURE RESEARCH
This research presents data collection framework that
enables the knowledge of the librarians to be simply captured
and efficiently without requiring large resources. This makes
this framework suitable for Business Intelligence because
data can be integrated and explored quickly. The framework
allows the sharp and pace detection of business problems and
allows users to decide how to implement solutions in different
contexts. The framework is simple and contains only three
stages of data analysis. First is an analysis of structured
interview data to be translated into questionnaires. Second,
analysis of quantitative questionnaire data to be used as
questions in capturing tacit knowledge. Third, data analysis
uses a cognitive-based approach in the form of a cognitive
map to transform tacit knowledge into explicit knowledge.
Our future research is about to develop the framework of
data analysis using a cognitive-based approach in the form of
a cognitive map after the completion of second interview.
Then, the data be analyzed with cognitive mapping technique
using Banxia Decision Explorer software. Data collection and
analysis will produce basic material for the automation of
systems that are relevant for the benefit of BI.
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