=Paper=
{{Paper
|id=Vol-3857/paper17
|storemode=property
|title=Evaluating cognitive biases and DSS utilization in strategic management: A socio-technical perspective
|pdfUrl=https://ceur-ws.org/Vol-3857/paper17.pdf
|volume=Vol-3857
|authors=Petra Blahova,Jan Saro,Jan Rydval,Helena Brozova
|dblpUrl=https://dblp.org/rec/conf/stpis/BlahovaSRB24
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==Evaluating cognitive biases and DSS utilization in strategic management: A socio-technical perspective==
https://ceur-ws.org/Vol-3857/paper17.pdf
Evaluating cognitive biases and DSS utilization in
strategic management: A socio-technical perspective
Petra Blahova1,†, Jan Saro1,†, Jan Rydval1,†, Helena Brozova1,†
1 Czech University of Life Sciences Prague, Kamycka 129, 165 00 Prague, Czech Republic
Abstract
Senior managers’ perceptions of Decision Support System (DSS) determine DSS implementation in the
context of knowledge management (KM) strategies. Although increasing information complexity
requires advanced decision-making, senior managers often prioritize intuition-based decisions, so low
DSS use may heighten the risk of decision failures. Moreover, behavioral economics research indicates a
high susceptibility to cognitive biases among senior managers. However, little is known about the align-
ment between senior managers' decision-making processes and behavioral patterns, DSS perception and
use, cognitive biases and KM strategy success. This study aims to explore senior managers’ cognitive bi-
ases in decision-making as a function of DSS perception and KM strategy implementation. For this pur-
pose, we used socio-technical methods, including semi-structured interviews with senior managers in in-
ternational corporations, applying Daniel Kahneman’s structured judgment technique to identify cognit-
ive biases. This pilot study provides a glimpse into senior managers’ decision-making behaviors and their
potential effects on KM strategy success. The findings indicate a high level of cognitive biases associated
with low DSS use and unclear or underdeveloped KM strategies. These preliminary insights highlight the
importance of addressing cognitive biases in DSS use and perception during decision-making challenges.
Keywords
Decision support system, strategic management, cognitive bias, behavioral economics, knowledge man-
agement, socio-technical1
1. Introduction
Senior managers’ perceptions of the benefits and challenges of implementing a Decision Support
System (DSS) as a Knowledge Management (KM) strategy may determine organizational
learning and innovation. Industry executives rely on information on the internal and external en-
vironment of their organization for decision-making. Nevertheless, they must seek new avenues to
gain a competitive edge with the increasing complexity and volume of available information. Com-
bined with rapid digitalization, this increasing volume
of information creates a constantly changing environment and, as a result, an urgency to make
more frequent decisions.
As decision frequency increases across all management levels and organizations, executives
must hone their effective and timely decision-making skills. Many strategic management
researchers take the position that executives make strategic decisions based on a structured
10th International Conference on Socio-Technical Perspectives in IS (STPIS’24) August 16-17 2024 Jönköping, Sweden
† These authors contributed equally.
blahovap@pef.czu.cz (P. Blahova); saroj@pef.czu.cz (J. Saro), rydval@pef.czu.cz (J.Rydval), brozova@pef.czu.cz
(H.Brozova)
0000-0002-7686-9613 (P.Blahova); 0009-0001-4355-5271 (J.Saro), 0000-0002-3463-5042 (J.Rydval), 0000-0002-0322-
251X (H.Brozova)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
256
process involving careful consideration of alternatives [1]. However, behavioral economy (BE) re-
search indicates that senior managers tend to follow expert intuition [2], boasting expert know-
ledge and well-developed decision intuition. Consequently, strategic decision-making is primarily
based on expert intuition [3].
According to Winter [13], [25], “In many cases, a strategic decision based on emotion or
intuition may be more efficient than a decision arrived at after thorough and rigorous analysis
of all the possible outcomes and implications.” But in other cases, intuitive and human-centric de-
cision-making may cause critical errors and threaten the entire organization, leading to decision
failures because such a decision-making process necessarily entails cognitive-biases [4]. In fact, not
only a high level of cognitive biases but also a preference for intuitive experiencebased decision-
making characterize the profile of these senior managers, accounting for suboptimal DSS use and
acceptance [2].
Although DSSs help to gain competitive advantage and ultimately to succeed in the
organization, DSS use among senior managers is low, indicating an unwillingness to use or low
trust in these systems, among other reasons. However, the purpose of the study is not to explain
this low use but to examine several mutually related aspects in the decision-making process
potentially related to DSS use. Notwithstanding previous research on DSS perceptions, benefits
and challenges in strategic management, behavioral economics, dynamic capabilities (DC) and KM
strategy, little is known about the alignment between senior managers' decision-making processes
and behavioral patterns, DSS perception, cognitive biases and KM strategy success.
KM strategy success indicates the level of innovation and adaptability of an organization. As
proposed by [14], the learning organization is defined as a means to reflect upon and reassess
knowledge created by individuals in the organizational context. The organization changes as the
result of this learning process, which can be viewed as an ongoing sense-making activity based on
the collective knowledge of its individuals [15]. According to Mumford [16], knowledge creation,
development and team work are key socio-technical design strategies, which must be applied to all
members of an organization, not just top experts or management. In an increasingly complex en-
vironment, organizations must gain dynamic capabilities (DC) to modify behaviors in responding
to external effects, thus enhancing their adaptability and competitiveness [6], [7], [5]. To summar-
ize, dynamic capabilities (DC) are enabled by the success of the KM strategy and the learning pro-
cess. The learning organization and KM strategy context is a necessary element of this research.
In this context, this study aims to explore strategic decision-making challenges, processes, tools,
behaviors, KM strategy and cognitive biases and identify relationships between these phenomena.
For this purpose, we conducted semi-structured interviews with senior managers from interna-
tional global organizations. To guide this exploration, the study sought to answer three research
questions:
RQ1: How can we examine senior managers’ decision-making processes and behaviors, DSS
perception, cognitive biases and KM strategy success?
RQ2: What is the relationship, if any, between senior managers’ DSS perception, cognitive biases
level and KM strategy success within selected decision-making problematic situation?
RQ3: What could be the role of the three examined research elements in an organizational
learning process and can be an organizational learning model designed based in this research?
257
2. Soft Systems Methodology (SSM), strategic thinking, cognitive biases,
DSS, KM, organizational learning and dynamic capabilities
This chapter briefly outlines concepts introduced in this research. The intention is to provide a
conceptual basis for the conducted research while reflecting on reality of the increasing
complexity of organizational concepts.
2.1. SSM
In this research, we leveraged the ability of SSM to mimic a cyclic learning process [20] studied
as a systems model. Human activity can be studied using systems models, but these models
should never be regarded as portraits of objective reality [18]. From a soft systems perspective,
such models are mere tools used by an observer or group of observers to interpret reality. Thus,
systems models enable us to convey these interpretations of reality in a debate among
participants [19].
Based on SSM, semi-structured interviews about a problem, i.e., a situation perceived as
problematic by stakeholders, yield purposeful activity models [20]. These models foster and struc-
ture debate around the problem. When contrasted against perceptions of the actual situation, they
identify desirable and (culturally) feasible changes [20].
2.2. Strategic thinking and cognitive biases
The highly competitive environment and increasing amount and complexity of information
requires a flexible organizational culture that encourages knowledge sharing, collaboration, and
continuous learning where leadership plays a crucial role [5]
Strategic thinking (ST) has been described as an “organization’s ability to create and develop a
strategic vision by exploring all potential future organizational events and challenging traditional
thinking to promote sound decision-making in record time” [21] and as required managerial com-
petency comprising conceptual thinking, visionary thinking, creativity, analytical thinking, learn-
ing, synthesizing, and objectivity [22]. ST helps managers develop better strategies and inspire em-
ployees to collaborate in innovative tactics for the firm’s survival [23]. Senior managers apply stra-
tegic decision-making with unique behavioral patterns.
Strategic decision-making is often based on expert intuition. But while this approach may be
more efficient in some cases, it may also cause critical errors and threaten the organization in
other cases [2]. Intuitive decision-making always includes cognitive biases, which lead to
decision failures [27], [28]. Strategic managers should examine their own cognitive biases and try
their best to mitigate them. Disregarding tools designed to limit biases may result in business fail-
ure. Arnott [2] has provided a comprehensive list of cognitive biases, with a clear description of
categories and types in the context of DSS research.
2.3. Organizational learning, dynamic capabilities, DSS
In a rapidly changing environment, a firm cannot thrive without organizational learning,
innovation, and adaptability. The DC [6], [21] theory emphasizes the importance of sensing,
seizing, and transforming to address these changes. Knowledge management (KM) facilitates
knowledge creation, sharing, and use, thereby enhancing decision-making, innovation, and
adaptability.
Strategic management integrates these elements by setting goals and evaluating strategies. The
problem is that strategic decision-making behavior specifics are more reliant on expert
258
knowledge and intuition and have a higher level of cognitive biases [27], [28]. A potential tool to
avoid biased or not fully informed decisions is DSS. DSS, assuming fully integrated with external
and internal systems, providing a real-time analysis, simulations, alternatives from various
perspectives, can enable a positive impact on all above-mentioned elements.
3. Methods
In this study, we applied the theoretical foundations and concepts described in Chapter 2,
namely, SSM, strategic thinking, and behavioral economics, to identify cognitive biases,
organizational learning, KM, dynamic capabilities and DSS.
3.1. Research Procedure
Our research procedure consisted of several steps. First, we selected methods addressing
cognitive biases, perceptions of DSS as a new system and KM strategy success. For this purpose,
we scripted interviews to include all the aforementioned phenomena. The socio-technical
approach was suitable for this complex research. This socio-technical approach encompassed user
participation, high engagement in real problem identification, SSM [20], [24], holistic multi-criteria
benefit analysis, organizational dynamic capabilities and systems model proposal. The interview
procedure included the following steps:
• The decision-making background was developed by drawing ideas upon SSM by
identifying a real problem that respondents wanted and needed to solve. The task was to
provide a challenging decision-making problem or process that was time-consuming and
expensive, with negative results, and therefore requiring a change.
• The organizational decision-making practices were described to better understand the context
and current decision-making patterns and processes, as well as prior knowledge and tools.
• The solution for the given problem was discussed in the context of the new system. The
benefits and challenges of OLD vs NEW were discussed to assess how the managers
perceived the benefits of the new system, which adopted holistic multi-criteria used for po-
tential future system and change (Figure 1). The willingness and intention to adopt and im-
plement potential DSS was also questioned.
• KM strategy success and execution in this specific problem and in the organization were
also examined by the holistic multi-criteria benefit analysis (Figure 1). Benefits and
challenges of current KM strategy success compared to future plan.
• Cognitive Biases were identified and evaluated based on a Kahneman structured
questionnaire.
259
Figure 1: Holistic multi-criteria benefit analysis by Peter Bednar [12]
3.2. Data – participants, context, factors, analysis
Participants of the research were international senior strategic and executive managers from vari-
ous large global corporations and business owners in top executive management roles as these are
involved in strategic decision-making. The participants’ selection was enabled by utilizing a pro-
fessional experience network contact list of a researcher. The researcher’s 20 years of experience in
strategic management roles in various global corporations created a valuable network of senior
managers.
All of the 60-minute, semi-structured interviews were conducted face to face and structured in-
spired by SSM. In the interviews, each manager identified and described in detail an ongoing chal-
lenge or problem of the current decision-making process requiring a solution. The semistructured
interview was separated into problem definition, solution proposal involving a new DSS process,
and benefits and challenges of the new and old systems assessed by holistic multi-criteria benefit
analysis, as shown in Figure 1. In addition, the researcher assessed the willingness to accept the
new solution and to implement a new DSS. KM strategy success was also examined by holistic
multi-criteria benefit analysis, identifying benefits and challenges of current Knowledge manage-
ment and future better one. Lastly, cognitive biases were examined using Daniel Kahneman’s spe-
cific structured questionnaire [27] with fourteen questions, as outlined in Table 1. The answer op-
tions were binary (yes or no), so we were able to count the number of cognitively biased responses
and, therefore, to express the level of cognitive biases as a percentage of biased responses.
To summarize, three research elements /concepts were examined based on the defined problem
and solution discussion; DSS perception and willingness to adopt the new system, KM strategy
success and cognitive bias level.
Analysis of the data was conducted both qualitatively and quantitatively. Qualitative
evaluation was based on manual structuring, categorizing, and coding responses. DSS and KM
strategy was evaluated by ability, level and depth of perceived benefits and challenges. DSS was
260
also evaluated by willingness to implement the new system. Cognitive biases were examined
only quantitatively. Quantification was conducted for all three elements. All are scaled as low,
medium and high levels, which are based on numerical scaling on the scale of 100 points for DSS
and KM and on a percentage of biased answers out of 100% potential ones.
Table 1
Cognitive Bias Questionnaire, Daniel Kahneman’s recommended questions
Cognitive Biases Questionnaire
Self-Interested Biases
Is there any reason to suspect motivated errors, or errors driven by the self interest of the
1
recommending team?
2 Does the set of individuals making the proposal stand to gain more than usual from the outcome?
3 Do the options proposed include only one realistic alternative?
4 Do you suspect any intentional or unintentional deception in the proposal?
Affect Heuristic
5 Have the people making the recommendation fallen in love with it?
Does this decision involve a strong emotional component such as those concerning employees,
6
brands, or locations?
Does it seem likely that the risks and costs have been minimized, while the benefits have been
7
exaggerated?
8 Do any team members seem to be deeply attached to the recommendation?
Saliency Bias
9 Could the diagnosis of the situation be overly influenced by an analogy to a memorable success?
10 Has the team cited examples of recent success stories in making the case for the proposal?
Confirmation Bias
11 Have credible alternatives been considered?
12 Were the alternatives fully evaluated in an objective and fact-based way?
13 Did the team actively look for information that would disprove their main assumptions?
14 Were the alternatives presented in a way that made them seem implausible?
4. Research Model – adoption and design
Our research model enabled us to define the research problem, analyze findings and identify
relationships. Although this research examined factors related to organizational learning, KM and
perception of DSS benefits, we adapted a model developed by Atanassova [7], which was originally
designed to analyze organizational learning. According to Atanassova [7], “a detailed framework
for organizational learning starting at the individual and unfolding to organizational strategic level
still is missing”. Therefore, the Market Intelligence Accumulation Through Social Media (MIATSM)
model was adopted because this model conceptualizes the processes and factors that enable/hinder
organizational learning. The MIATSM model was adopted by Bednar [12], and by Atanassova [7]
specifically to study adaptive capabilities
Using Atanassova’s adopted MIATSM model [7], we studied organizations through a sociotech-
nical lens as complex entities changed by their engaged actor’s preferences to transition from the
OLD (existing decision-making processes and tools used for decision-making) to the NEW system
(willingness to adopt a new process and tool allowing effective and better informed decisions).
Figure 2 shows Atanassova’s adapted MIATSM model designed to analyze
261
organizational learning [7] and the model adapted for this research. Below are listed
characteristics of both models:
• Both models assume prior knowledge, triggers driving learning acting upon an executed
activity, and system dynamics.
• Triggers are positive market opportunities understanding development in Atanassova’s
model, sense-making and applying/acting upon the learnt.
• Triggers in our model are undesirable outcome/process/result of OLD process. The
trigger is not perceived as a growth and learning opportunity as in Atanassova’s model,
but rather acting upon a decision-making challenge while being aware that the OLD
process represents the not-helpful approach. The NEW system is represented by DSS
benefits perception and willingness to implement the system, thus sense making
learning step.
• Knowledge management is same in both models.
• What is different in our model is a newly added element of cognitive bias as a trigger
element in the model. This model allows to show not only positive organizational
learning resulting into new positive adaptive and dynamic capabilities, but also negative
loop and returning to the OLD (original processes and tools).
• Combination of the unique characteristics is resulting into desired positive new or
changed adaptive capability; the same as in Atanassova’s model.
Figure 2: MIATSM model adopted by Atanassova [7] and model modified for this research
5. Preliminary Findings
RQ1: We tried to answer the “how” question by applying some ideas of SSM, and holistic benefit
analysis, allowing to obtain perceived benefits and challenges for DSS and KM strategy elements.
Kahneman’s questionnaire was applied to quantify cognitive biases.
RQ2: The managers interviewed in this study showed medium and high levels of cognitive bias.
High levels of cognitive bias were associated with low KM and/or DSS use. Medium levels of
cognitive bias were associated with medium-to-low KM or DSS use. Overall, the level of cognitive
bias was strongly correlated with the level of KM.
262
5.1. Interviews results structure
Table 2 outlines the summarized answers of respondents 1-5. These answers were scaled into low/
medium/high levels. The three columns of results correspond to the three study elements, namely
(i) DSS solution perception, (ii) KM strategy success perception evaluated by level and depth of
provided perceived benefits and challenges of current vs new/future system. And (iii) cognitive
bias, which was determined based on biased responses to 14 questions of the questionnaire (Table
1).
Table 2
Evaluation and quantification of the results from the interviews
Company Role Problematic DSS perception Benefits KM strategy success Cognitive
Type Situation/Challenge Analysis OLD vs NEW Benefits Analysis Current Biases
Definition vs Future
SMB, Legal Partner Lack of reliable legal Defined benefits and 5 Transfer of knowledge only 20 64% 64
assistants, issue on challenges of old and new via person. Hired a special biased
every meeting among process, but was very role to implement KM based on
partners. Decision is negative towards any processes, document based 14
made manually, relying change, thus not considering knowledge management questions
on mix of belief and system driven solution, not system. Perceives benefits
knowing. believing in success. of future KM.
100 20 71% 71
Large CFO Missing standard Agrees to system driven Knowledge held in each
Corporation, expected ROI on solution, process change country, but existing KM biased
online job investments which are documentation, DSS. Believes within functional based on
platform pushed by managers as in a values, change, provides departments (within HR, 14
critical. Missing long- list of perceived benefits of withing Finance, withing IT). questions
term evaluation of such new system. Not connected, but benefits
projects, products. and challenges identified.
5 Knowledge not transferred 10 100% 100
Large CEO Often missing Perceived challenges of
Corporation, information about the current system, but non to local branches, very biased
SW HW market specifics of each perceived benefiits of DSS as difficult to obtain useful and based on
gaming country, relying on ad DSS not needed as finance helping trainings, 14
hoc and subjective systems and sales channels colaboration only directive. questions
information from local provide enough information. Challenges described.
country managers
SMB CEO As a newly starting DSS fully integrated - long list 100 Knowledge sharing, open 80 35% 36
e-commerce company there are of benefits listed and transparency among all biased
missing forecasts related perceived. Agreed to add staff, KM strategy as one of based on
to market information, missing information. the most imporatant pillars - 14
customers preferences all in progress. Describes questions
and competition. benefits and challenges
current vs future
SMB CEO Missing comprehensive Willing to change the process, 50 KM strategy not formalized 40 35% 36
construction forecasts due to but doubts about it's cost and but in construction the biased
seasonality, unreliable implementation in the area of technical knowledge based on
employees thus difficult unreliable employees. handover embedded in the 14
to plan project reliably Perceives benefits of new. leader-teams relationship. questions
Benefits described.
Color meanings DSS perception KM Strategy level Bias level
negative No/Low (0-5) Low (10,20) 67-100 High
medium Medium (50) Medium (40, 50, 60) 34-66
positive High (100) High (80) 0-33 Low
263
5.2. Quantified relationships
Figure 3 shows the quantification results, highlighting medium-to-high cognitive bias. None of
the respondents showed low levels of cognitive bias. High levels of cognitive bias are associated
with low KM and DSS. Medium levels of cognitive bias are associated with medium or high DSS
and KM.
Quantified levels of Cognitive Bias, KM and DSS
120
100
80
60
40
20
0
1 2 3 4 5
Bias KM DSS
Figure 3: Quantified levels of Cognitive Bias, KM success and perception of DSS benefits
perception & willingness to implement a new DSS solution
The level of Cognitive Bias was strongly correlated with the success of the KM strategy (Figure
4), but not with the perception of DSS benefits or willingness to change to a new DSS solution.
Correlation between Bias and KM strategy success - appears
highly correlated.
100
80
60
KM
40
20
0
0 20 40 60 80 100 120
Bias
Figure 4: Correlation between the level of Cognitive Bias and the success of the KM strategy
5.3. Organizational learning model
The Figure (5) shows the results in a research model. Discovered patterns from the pilot study are
that high levels of cognitive bias (red) lead to either low DSS or low KM, thus no learning achieved,
resulting in a return to the OLD process. Medium levels of cognitive bias lead to NEW DSS and
KM, thus increasing learning and new capabilities.
Based on the results in this pilot study it seems that high levels of cognitive bias have a role
in decreasing the organizational learning by triggering back to OLD system. Only in the cases of
high perception of DSS benefits, or DSS usage, the NEW system triggers learning from the change
as well as from considering the challenges of OLD. DSS perception factor overwrites the potential
264
negative effect of highly biased decision-making. On the other hand, medium levels of cognitive
bias are connected with medium or high perception of DSS benefits. Medium or high DSS
perception enables the KM success. In this pilot study, only medium and high DSS perception are
connected to medium and high KM success.
RQ3: The examined elements in this research were included in the adapted model of
organizational learning (Figure 2) indicating their potential role in achieving new or changed
dynamic capabilities.
Figure 5: Research model reflecting the individual unique results
6. Discussion
The results of this pilot study underscore the suitability of the methods and provide insights into
the complexities of senior managers’ decision-making behaviors and thinking. The results are dis-
cussed in several sections on the interviews, SSM and cognitive biases.
The discussion of decision-making problems during the interviews was dynamic and
collaborative. Such active collaboration influenced the researchers, making it essential to
document any deviations from the script, omission of specific topics, and other aspects, after
each interview session. This approach may yield interesting outcomes, such as interviewer's pro-
gression in thinking process or even potential sabotage of the interview's objectives. A tendency to
omit predetermined topics or to experience other deviations will be the topic of the conference
workshop discussion, i.e., how other researchers addressed this topic, to assure the unbiased res-
ults. Given that semi-structured interviews are inherently evolving, some changes are expected,
but they must identified when they are significant. During the interviews, SSM fostered dynamic
discussions and strong engagement, thus providing to be a useful method [20], [24].
Our preliminary findings confirm the ability of our research method to identify a significant
level of cognitive biases. In line with our assumptions, strong cognitive biases were identified
among all senior managers. Considering that these managers lead successful organizations,
these cognitive biases may lead to critical failures in the future. Nevertheless, the problematic
265
situation chosen by the senior managers might not have been perceived as complex or critical for
the business. Problems or errors must be substantial and imminent threats to a business before
managers consider change and adaptation, as shown when applying system dynamics in strategic
management [26]. Therefore, the findings of our pilot study suggest that either the decision prob-
lem was not critical for the business or that the system had not yet displayed failures.
The organizational learning model was adopted [7] to analyze learning process during
addressing a challenge in decision-making management process. The model was adapted
enabling both positive and negative effect of model elements on the desired result; positive and de-
sired new or changed dynamic capabilities. Cognitive bias element is part of learning triggers and
the results showed that high levels of cognitive bias may be a negative factor of organizational
learning, which indicates the potential thread of cognitive bias leading to decision-making failures
[2].
6.1. Limitations
The main limitations of this study are related to participant selection because only one
participant was interviewed per company. Although all participants were level C senior
managers, board members, executives, or owners and all interviews led to in-depth discussions,
these factors limited the research. The preliminary results also provide a single, subjective
perspective, in a limited time frame. The interviews were based on a specific decision problem or
challenge selected and defined by the manager at that time for an interactive and dynamic discus-
sion in line with SSM principles but might have biased the results because they were related to
only one decision problem, not to the decision-making practices of the company and the manager.
Furthermore, these preliminary results may be subject to researcher’s subjective interpretation, es-
pecially in the quantification approach. The level of cognitive bias level quantified in this study
seems appropriate considering the binary response options (yes/no), but the quantification of the
willingness to change and use DSS to solve decision-making problems and the success of the KM
strategy must be supported by previously published results.
The KM strategy expresses dynamic capabilities and organization learning, but this
relationship may be an oversimplification of three similar but different concepts. Although DSS
and KM quantification may be subjective, human behaviors and preferences have been
quantified by Becker [29] and Kahneman [27], [28], among other researchers. The quantification
approach shall be confirmed by previous research.
7. Conclusion
Senior managers show mostly high levels of cognitive biases connected mostly to low levels of
DSS perception and low levels of KM strategy success. The preliminary results indicate stronger re-
lationship between level of cognitive bias and KM than cognitive bias and DSS. These preliminary
findings provide initial insights into the complexities of senior managers’ decisionmaking
behaviors, which affect the success of a KM strategy. KM policies provide the foundation for in-
novation and adaptability, so our preliminary findings of KM relationship to high cognitive bias in-
dicates potential failures in organizational learning. Next research will focus on obtaining twenty
more senior managers while qualitative results coding will be conducted by using suitable applica-
tion.
266
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