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Integration of Effectuation Process and

Knowledge Creation and Knowledge Practice for Risks that are Difficult to Quantify

―Utilization of a Knowledge Generation Process in the Subjective Risk Assessment Process―

Mamoru Uehara

Abstract

  Risk management must distinguish between quantifiable risks and those that are extremely difficult to quantify. This study focuses on a framework in which the effectuation process and causation process are adapted to these two respective risk management types.

Then, knowledge creation and knowledge practice are effective for implementing the effectuation process for risk management, which is extremely difficult to quantify, and it is necessary to integrate the process and those two knowledge. Furthermore, this study proposes the concept that it is effective to utilize the knowledge generation process in the subjective risk evaluation process.

Keywords: Risk Management; Uncertainty; Effectuation; Causation; Knowledge Creation;

Knowledge Practice

1. Introduction

  In a previous study (Uehara, 2020), the author focused on the need for risk recognition to distinguish between two types of uncertainty in risk management: measurable uncertainty and unmeasurable uncertainty. Then, Uehara (2020) presented an “ application framework of effectuation and causation to quantifiable and non-quantifiable risks” in which the effectuation process and causation process proposed by Sarasvathy (2001) were adapted to these respective risks.

  However, the implementation of the effectuation process in the above framework is

considered to be practically challenging. As the basis for the successful implementation of

the effectuation process, it should be noted that entrepreneurial expertise consists of tacit as

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well as learnable and teachable aspects of experience that are related to high performance in specific domains; this is the conceptual foundation of effectuation. The tacit as well as learnable and communicable aspects are believed to correspond to the knowledge creation and SECI Spiral presented by Nonaka and Takeuchi (1995, 2019). Sarasvathy (2001) states that the strategy implemented by many experienced entrepreneurs is an effectuation process-based strategy and indicates that experienced entrepreneurs have enjoyed highly significant achievements by implementing this strategy. The effectuation-based strategy is useful when the future is unpredictable and the objective is uncertain. In other words, it is useful when unmeasurable uncertainties appear. Therefore, in order to smoothly implement the effectuation process in the “application framework of effectuation and causation to quantifiable and non-quantifiable risks,” using knowledge creation in an organization and the SECI Spiral is considered to be effective.

  Considering the fact that it is important to apply knowledge creation in organizations and the SECI Spiral proposed by Nonaka and Takeuchi (1995, 2019) to the effectuation process in the “application framework of effectuation and causation to quantifiable and non- quantifiable risks,” this study presents a new concept of intermediating the knowledge- generating process in the subjective risk assessment process presented by Uehara et al.

(2016) in order to integrate these two elements.

2. Theoretical background

2.1 Existence of uncertainties in risk perception

  Beck (1986) points out that as modernization progresses, mankind produces both wealth and risks at the same time, creating an entirely new risk that has never been experienced.

As he indicated, there have been many accidents and disasters, such as nuclear power plant accidents caused by mankind and unprecedented torrential rains that are believed to be associated with global environmental changes. As evidenced by these examples, there is no mathematical or statistical probability for a risk that has never occurred in the past or for an extremely rare risk that only occurs once every several hundred years. Therefore, when conducting quantitative risk measurement and assessment, one is faced with extremely difficult issues involving uncertainties.

  Knight (1921) distinguishes between two types of uncertainty: measurable uncertainties

in probability (considering this as a risk) and “ true ” uncertainties that are not measurable in

probability. He developed his own theory based on the differences between the two. The

characteristics of the latter differ from those of the former, as it is impossible to identify and

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classify the state that should be the basis of probability formation. Furthermore, the latter is known as the “Knight theory” as it expands the logic that the “law of large numbers”

cannot be applicable because the frequency of occurrence is rare and unique as the situation that becomes a basis for the estimation occurs only on extremely rare occasions, such as a one-time only event. Then, it indicates that if there is no mathematical or statistical probability based on frequentism with the “law of large numbers,” that means there is a

“true” uncertainty as well as an unmeasurable uncertainty.

2.2 Causation and effectuation in entrepreneurship

  The notion of risk has been at the heart of entrepreneurship since Knight (1921). Knight points out the need to clearly distinguish three types of probability situation. The first type is a priori probability, and the second type is statistical probability. The problem is the third type of probability situation. Knight calls this “estimates.” As described in Section 2.1, the former two types are related to risk, and the third type is related to “true” uncertainty.

Differences between these are very definitive.

  Then, Sarasvathy (2008) noted that entrepreneurial expertise consists in tacit as well as learnable and teachable aspects of experience that are related to high performance in specific domains. She defined an expert as “someone who has attained a high level of performance in the domain as a result of years of experience and deliberate practice.” She focused her attention on what decisions would be made when experienced entrepreneurs with high-level achievements encountered a future that falls under the “third type of true uncertainty described by Knight.” Then, she attempted to find a theory that dealt with

“Knight’s uncertainty” and called it the theory of effectuation. She used “effectuation” as a concept opposite to causation.

  Entrepreneurs can choose different strategies to address the uncertainties associated with the establishment of new venture businesses. In an attempt to address this central research issue in entrepreneurship, Sarasvathy (2001) proposed effectuation as a dominant decision model for entrepreneurs’ decision-making, particularly in the absence of a pre- existing market. Sarasvathy (2008) explained effectuation as follows:

  “Effectuation is the inverse of causation. Causal models begin with an effect to be

created. They seek either to select between means to achieve those effects or to create

new means to achieve preselected ends. Effectual models, in contrast, begin with given

means and seek to create new ends using non-predictive strategies. ” (Sarasvathy, 2008, p. 16)

  She also pointed out that a causation-based strategy is effective when the future is

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predictable and the objective is clear, while an effectuation-based strategy is effective when the future is unpredictable and the objective is unclear.

  Effectuation consists of the following five principles that embody non-predictive control techniques. In other words, it aims to reduce the use of predictive strategies:

・The bird-in-hand principle

This principle does not aim to discover new ways but to create something new with existing means.

・The affordable-loss principle

This principle is to commit beforehand how much you are willing to lose.

・The crazy-quilt principle

This principle is not to select participants based on pre-determined objectives but to actively have participants who intend to make a commitment to take part in the process.

・The lemonade principle

This principle shows the use of unexpected situations as leverages to perceive uncertainties and respond appropriately rather than avoiding, overcoming, and adapting to uncertain situations.

・The pilot-in-the-plane principle

Each of the four principles discussed so far suggests a theory of non-predictive control.

Effectuation focuses on “controllable aspects of an unpredictable future” and aims to overcome the worst-case situation and control the future, even if something undesirable happens or true uncertainty becomes apparent. This principle (the pilot-in-the-plane principle) means that in a problem space characterized by “Knight uncertainty” and

“ambiguity of objectives,” the pilot, who operates an airplane with an automated flight function, is the window to unexpected opportunities and the key to outliving disasters.

Even when uncertainty becomes apparent, the principle states that the future can be controlled if it is possible to respond with agility according to the circumstances, just as an airplane pilot does.

2.3 Enterprise risk management

  The importance of enterprise risk management (ERM) as an approach for organizations to manage risk is increasing in accordance with the demands related to a constantly changing business environment.

  COSO published the “ ERM-Integrated Framework ” in 2004 to help business entities

respond to changes in the business environment. Then, in order to respond to the

uncertainties associated with the diversification of risks and the pursuit of new business

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opportunities based on recent trends, ERM-Integrating with Strategy and Performance (COSO, 2017), as a revised version of the 2004 ERM Framework, was published in 2017. In risk management, since COSO ERM views potential events that may affect a business entity as risks and requires “identifying these potential events,” it is assumed to respond to the uncertainty involving potential events.

  COSO ERM’s “Principle 10: Identifies Risk” states that “The organization identifies risk that impacts the performance of strategy and business objectives” (COSO, 2017, p. 67).

Furthermore, with respect to the risks that need be identified, it says that “The organization identifies new, emerging, and changing risks to the achievement of the entity’s strategy and business objectives” (COSO, 2017, p. 67). Then, as an example of new, emerging, and changing risks, it mentions the risks that have not been experienced or known in the past.

  Based on the matters discussed above, COSO ERM requires the organization to respond to the following points:

・ The organization must address two parts of risks: (a) risks associated with the strategic decision-making process concerning business opportunities (risks associated with business opportunities) and (b) risks associated with the execution of business activities identified in the strategy setting (risks associated with the execution of business activities).

・ The organization needs to identify new, emerging, and changing risks related to the achievement of its strategy and business objectives when recognizing risks.

  Thus, COSO ERM newly presents the significance of making decisions by linking risks to strategy formulation and day-to-day operations and the effectiveness of determining the risks to be taken (risk appetite) that fit business strategies and objectives to achieve targeted performance. Managers and the board of directors are then required to integrate ERM into all areas of the business entity at all times. In other words, ERM needs to have been firmly rooted throughout the organization and must be rooted as a culture of the organization. Therefore, “governance and culture” are listed in the first of the five COSO ERM components.

2.4 Application framework of effectuation and causation to quantifiable and non- quantifiable risks

  As discussed in Section 2.3, COSO ERM highlights the “risks associated with the

strategic decision-making process related to business opportunities ” (risks related to

business opportunities) and requires that “the organization identifies new, emerging, and

changing risks to the achievement of the entity ’ s strategy and business objectives ” with

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respect to the risks faced by a business entity.

  However, on the other hand, in an environment where globalization and informatization are advancing and competition is intensifying, companies are moving into new business areas and aiming for growth and profitability. They continue to implement internal venturing in accordance with the strategic decision-making process associated with new business opportunities. In this context, risk management in response to new opportunities is essential, but there is a dilemma in which the “true” uncertainties pointed out by Knight exist, which makes it difficult to perceive potential risks. Certainly, in addition to pursuing new business opportunities, companies are faced with risks created by mankind as modernization progresses and completely new risks never encountered before when conducting existing business activities arise, as Beck indicated (1986). Therefore, the “true”

uncertainty indicated by Knight can also be found in these situations.

  Regarding risk perception, Uehara (2002) points out that risk management should be conducted by considering measurable uncertainties in probability and “true” uncertainties that are unmeasurable in the probability discussed by Knight (1921) to distinguish between these two types of risk perception. Then, Uehara (2002) introduces the concept framework of “risk management corresponding to the occurrence frequency in the risk evaluation.”

Moreover, Uehara (2020) expands this conceptual framework based on effectuation and causation approaches, which are theories that respond to “Knight’s uncertainties” in the behaviors of entrepreneurs faced with risks and uncertainties, as discussed by Sarasvathy (2001, 2018).

  In other words, for risks that are extremely difficult to quantify in “Zone 1” and those

that are quantifiable in “Zone 2,” Figure 1 is newly presented as an “application framework

of effectuation and causation to quantifiable and non-quantifiable risks” that correspond to

the effectuation process and causation process, respectively. The framework first

distinguishes between “Zone 1,” which shows risks that are extremely difficult to quantify,

and “Zone 2,” which shows risks that are quantifiable based on the “threshold” of risk

perceived by each business entity. This is a framework in which the effectuation process is

used for “Zone 1” while the causation process is used for “Zone 2” for risk perception. As

explained in Section 2.2, the effectuation process is useful when the future is unpredictable

and the objective is unclear. Among the five effectuation principles, the affordable-loss

principle in which the allowable limits of failures and losses are predetermined and risks are

taken within the allowable loss range, the lemonade principle in which the uncertainty is

acknowledged and appropriately handled using the situation even if an unexpected situation

occurs, and the pilot-in-the-plane principle in which the worst situation is overcome and the

future is controlled even if a true uncertainty is manifested, are particularly important.

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These principles are central to the framework that focuses on responding to risks in “Zone 1,” which shows risks that are extremely difficult to quantify by using the effectuation process.

2.5 Knowledge generation process in the subjective risk assessment process

  Uehara et al. (2016) presented “the knowledge generation process in the subjective risk assessment process” by integrating “the relationship between the subjective risk assessment process and objective risk assessment process in the risk assessment process” by Ogawa (1993) with “the conceptual framework on knowledge and information” by Yamashita (2007).

  Ogawa (1993) stated that the clear difference between risk and hazard is that the former is quantitatively assessed while the latter is qualitatively assessed. He also indicated that the risk assessment process includes an objective process that can be quantitatively assessed and a subjective process that follows a risk level that is subjectively assessed for risks perceived by individuals. Then, he mentioned that the process of assessing subjective risk is “ risk perception. ”

  Thus, according to Ogawa (1993), the risk assessment process can be expressed by Equation (1).

Figure 1 Application framework of effectuation and causation to

quantifiable and non-quantifiable risks

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Riskassessmentprocess

=objectiveriskassessmentprocess+subjectiveriskassessmentprocess(riskperception)(1)

  Furthermore, Ogawa (1993, p. 30) defines hazard perception as “an information processing process that searches for objects, events, and environmental conditions that are linked to the possibility of an accident from within the situation and grasps or anticipates the situation with the hidden accident possibility.” He points out that hazard perception is evaluated qualitatively. He indicates that hazard perceptions are likely to be influenced by knowledge and experience and that the knowledge of hazards learned in the past will be utilized in the process of appropriately searching for hazards that will arrive in the near future. Here, he states that education and training play a major role and that risk prediction training and risk perception training are ways to improve hazard perception skills.

  Ogawa (1993) also describes the relationship between risk perception and hazard perception as follows: First, it is better to consider that the relationship between two perceptual processes-risk perception and hazard perception-is not a process that proceeds independently but is rather a process that is closely linked. For example, when driving an automobile, we will explore objects and events that are linked to the possibility of an accident based on the traffic situation in front of us and grasp the situation where we find ourselves. This corresponds to the hazard perception process. Then, we perceive the possibility of getting involved in an accident in this situation. This corresponds to the risk perception process. In terms of time-series relationships, hazard perceptions are the step that comes before risk perception. In other words, the result of hazard perception is used as information for risk perception, and once the situation is recognized, it leads to the subjective risk assessment process.

  Based on what Ogawa (1993) indicated, Uehara et al. (2016) express the relation between risk perceptions and hazard perceptions in the risk assessment process as shown in Figure 2.

  According to Ogawa (1993), the outcome of hazard perception is used as information for risk perception. In other words, it means searching for objects and events that are connected with the possibility of an accident (risk), grasping the situation where the person finds themselves (hazard perception), and perceiving the possibility of getting involved in an accident (risk) in this situation (risk perception). Thus, hazard perception is the step that comes before risk perception, followed by using the information obtained from hazard perception for risk perception.

  Corresponding to the “relationship between risk perception and hazard perception in the

risk assessment process ” presented in Figure 2 and the “ application framework of

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effectuation and causation to quantifiable and non-quantifiable risks” described in Figure 1 under Section 2.4, these two can be related as follows:

・ The objective risk assessment process in Figure 2 is a risk assessment for the quantifiable risks in “Zone 2” in Figure 1 and corresponds to the causation process.

・ The subjective risk assessment process of obtaining hazard perceptions as information and reaching risk perceptions in Figure 2 is a risk assessment that is extremely difficult to quantify in “Zone 1” in Figure 1 and corresponds to the effectuation process.

  On the other hand, Yamashita (2007) proposes the framework shown in Figure 3 for the concept of information and knowledge. Hereinafter, “the conceptual framework related to knowledge and information” will be described based on Yamashita (2007, pp. 58―60).

  This framework gives a new perspective on the process of generating knowledge to obtain the status T={t

1

, t

2

, ..., t

i

, ..., t

m

, ... t

n

}, which consists of n elements as precisely as possible.

  First, considering the action to collect the information X={x

1

, x

2

, ..., x

i

, ..., x

m

} to understand the status T, the information is fragmental. Thus, it can generally be described as follows:

m<n (2)

Moreover, if T

={t

1

, t

2

, ..., t

i

, ..., t

m

} is described as a “subset of the status” that is the source of m numbers of information, information x

i

generally contains contamination d

i

( d

i

∈ D ) such as errors and noise.

x

i

= t

i

+ d

i

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  Then, we create knowledge f regarding status T by succinctly and smoothly linking as much information as possible while removing this contamination. In doing so, it is necessary to ①relate more information in a wide range and ②try to increase the simplicity and smoothness of the relationship as much as possible. Based on the generated knowledge f ,

Figure 2 Relation between Risk Perception and Hazard Perception in the Risk

Assessment Process (Uehara et al. 2016)

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we infer the status T. Assuming that the status inferred by the process is T',

T' = f ( X ) (4)

Now, knowledge f is regarded as a map of X→T'. That is, in order to know status T as accurately as possible, knowledge f as a map of X → T' is generated by collecting a large amount of information X and linking as much information as possible succinctly while removing information contamination D .

  It is believed that the conceptual framework in Figure 3 will facilitate a conceptual understanding regarding the positioning of information and knowledge. It is the positioning of knowledge as the map f to infer state T from information X, and it is the positioning of information X as the existence in which subset T

of the set of status T becomes the source (fragmental) with contamination D added to this (Yamashita, 2007, pp. 58―60).

  Uehara et al. (2016) integrated the relationship between risk perception and hazard perception mentioned by Ogawa (1993) with the concept of the “conceptual framework of knowledge and information” described by Yamashita (2007) and presented a “knowledge generation process in the subjective risk assessment process” through the processes of ① and ② below. In other words, when evaluating risks that cannot be objectively captured, a subjective risk assessment is conducted. In the subjective risk assessment process, Uehara et al. (2016) views ① as a hazard perception and ② as a risk perception and presents the relationship between hazard and risk perceptions and the information and knowledge generation process (the conceptual diagram is shown in Figure 4).

① To understand status T (an overview of risks that cannot be objectively captured) as accurately as possible, (a) collect a lot of information X (bring n and m closer), (b) remove information contamination D , and (c) generate knowledge f by succinctly linking as much

Figure 3 Conceptual Framework of Knowledge and Information

(Yamashita, 2007, p. 59)

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information as possible. This part corresponds to hazard perception.

② This f estimates the “overall risk ( T ) that cannot be objectively captured.” This part corresponds to “risk perception.”

  Thus, Uehara et al. (2016) described that when assessing risks that are extremely difficult to quantify, ① and ② are closely linked and undergo a subjective risk assessment process.

Here, the assessment of risks that are extremely difficult to quantify corresponds to the risks that are extremely difficult to quantify (Zone 1) shown in Figure 1 under Section 2.4.

2.6 Knowledge creation and knowledge implementation (practical wisdom) in the organization

  Nonaka and Takeuchi (1995) point out that knowledge creation can be achieved by the four knowledge conversion mode processes shown in Figure 5, which are epistemological dimensional interactions generated by two types of knowledge: tacit knowledge and explicit knowledge. This knowledge spiral is called the SECI model (Nonaka and Takeuchi, 2019).

①Socialization: Individuals share implicit knowledge through interactions. Through these interactions, each member of the organization acquires tacit knowledge. As a result, everyone’s ideas will be shared.

②Externalization: Individuals integrate tacit knowledge accumulated by socialization at the team level. Through this integration, the essence of implicit knowledge is conceptualized, and implicit knowledge turns into explicit knowledge in the form of rhetoric and metaphor using words, images, and models.

③Combination: Explicit knowledge is gathered, combined, organized, and calculated from Figure 4 Knowledge Generation Process in the Subjective Risk Assessment Process

by Uehara et al. (2016)

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inside and outside the organization to build complex and systematic explicit knowledge at the organization level.

④Internalization: Explicit knowledge amplified by linking is put into practice. Putting it into practice will enrich the most relevant practical tacit knowledge and it will be embodied in the individual.

  Based on the SECI model, Nonaka and Takeuchi (2019) advocate knowledge practices that apply, utilize, and disseminate accumulated knowledge as the ontological dimensions of the individual, organizational, inter-organizational, community, and social levels rise spirally.

They also state that the driving force behind the SECI Spiral is practical wisdom.

  In essence, the SECI Spiral (Figure 6) is an extension of the SECI process (Figure 5) in which the following occurs:

・knowledge is ceaselessly created and practiced;

・the knowledge base is enlarged horizontally;

・more knowledge that is created and disseminated is converted into action;

・both the scale and quality of knowledge practice are amplified;

・which leads to more actions, which catalyze innovation;

・more people get involved in knowledge creation and practice;

・the knowledge base is enlarged over time;

・knowledge that is created at one level spirals to a higher ontological level;

・and that enlarges the knowledge creating/practicing community.

(Nonaka & Takeuchi, 2019, p. 71)

Figure 5 Knowledge spiral (SECI model) (Nonaka & Takeuchi, 1995, p. 71)

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  Figure 6 represents the multidimensionality of the SECI Spiral. The base part of the vertical axis consists of tacit knowledge and explicit knowledge, which make up two poles of the epistemological dimension. The ontological dimension is shown on the vertical axis, and the cycle of SECI rises along this vertical axis from the individual level to the organizational level, then on to the community level and the social level. The figure depicts that as the horizontal cycle of SECI circulating once and SECI gradually rising spirally through the ontological dimension, so that knowledge spreads. Nonaka and Takeuchi (2019) note that one of Aristotle’s three knowledge types, phronesis, is the driving force behind the rise of the SECI Spiral along this vertical axis. “Phronesis, which translates as practical wisdom or prudence, is a true and reasoned state of capacity to act with regard to the things that are good or bad for man” (Nonaka & Takeuchi, 2019, p. 32).

  Moreover, Nonaka and Takeuchi (2019) point out that phronesis (practical wisdom) must permeate through the entire organization. As mentioned at the end of Section 2.3, ERM must be firmly planted and rooted throughout the entire organization as a culture, and it is believed that this corresponds to the phronesis (practical wisdom) indicated by Nonaka and Takeuchi.

Figure 6 The multiple dimensions of the SECI Spiral (Nonaka & Takeuchi,

2019, p. 72)

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3. Integration of the causation and effectuation application framework in risk management and the SECI Spiral

  As noted in Section 2.4, Uehara (2020) highlights the need to practice risk management by distinguishing between almost unquantifiable and quantifiable risks and applying the effectuation and causation processes to each of these risk types. For risks that are extremely difficult to quantify (Zone 1 in Figure 1), it is shown that the use of an effectuation process is useful. In other words, the use of effectuation processes, centered on the affordable-loss principle, the lemonade principle, and the pilot-in-the-plane principle, can respond to risks in an agile and appropriate manner, even when the future is unpredictable and the objective is uncertain.

  Consider the effectiveness of the effectuation process in cases where the future is unpredictable or where the objective is uncertain in relation to the “knowledge generation process in the subjective risk assessment process” (Section 2.5) of Uehara et al. (2016).

Among the effectuation principles, the following three principles can be used primarily to generate knowledge f as a map of X→T' and to infer the “overall risk that cannot be captured objectively ( T )” as accurately as possible:

・ Determine the allowable failure and loss limit related to the affordable-loss principle in advance and take risks within the allowable loss limit.

・ Even if an unexpected situation arises, as stated in the lemonade principle, accept the uncertain situation and take appropriate measures using the situation.

・ If something undesirable occurs or a true uncertainly manifests, as stated in the pilot-in- the-plane principle, overcome the worst case and control the future.

  According to Yamashita (2007), knowledge f as a map of X→T' is generated by succinctly linking as much information as possible while collecting a large amount of information X and removing contamination D from the information in order to understand status T as accurately as possible. We noted at the end of Section 2.5 that this knowledge f plays an important role in the subjective risk assessment process. Now, consider this knowledge f in relation to knowledge creation in the organization as described by Nonaka and Takeuchi (1995, 2019) and the SECI Spiral (Section 2.6). Knowledge f is “explicit knowledge” and “tacit knowledge” of knowledge creation in the organization, as pointed out by Nonaka and Takeuchi, and it is also phronesis (practical wisdom) as a driving force, which lifts the SECI Spiral while expanding it.

  In this section, we attempt to integrate the two concepts of the effectuation process by

Uehara (2020) in which effectuation is used for risks that are extremely difficult to quantify

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(Section 2.4) and knowledge creation in the organization as described by Nonaka and Takeuchi (1995, 2019) and the SECI Spiral (Section 2.6). We do this by mediating and applying the knowledge generation process to the subjective risk assessment process by Uehara et al. (2016).

  Uehara (2020) applies effectuation and causation to risks that are almost impossible to quantify and those that can be quantified, respectively, and particularly indicates that using the effectuation process is effective for risks that are extremely difficult to quantify (Zone 1 in Figure 1). The key point in implementing this effectuation process includes the affordable-loss principle, the lemonade principle, and the pilot-in-the-plane principle. In order to implement these principles, knowledge f generated by the “knowledge generation process in the subjective risk assessment process” plays an important role. Moreover, the use of organizational knowledge creation and the SECI Spiral in the generation of knowledge f is helpful. Here, in particular, it is essential to increase the SECI Spiral, which applies, utilizes, and disseminates the accumulated knowledge of organizations by using phronesis (practical wisdom), as pointed out by Nonaka Takeuchi (2019), as the driving force.

  As described above, by mediating and applying the subjective risk assessment process by Uehara et al. (2016) to the effectuation process for risks that are extremely difficult to quantify (Zone 1 in Figure 1) and the SECI Spiral indicated by Nonaka and Takeuchi (2019), it is possible to integrate these two. These integration and mediation relationships will be explained through the following Steps 1 and 2 (Figure 7 presents conceptual diagrams of Steps 1 and 2).

Step 1

(1) Section 2.5 indicates that knowledge f was generated via the processes of (a), (b), and (c) in the “knowledge generation process in the subjective risk assessment process,” which corresponds to hazard perception. In this process, knowledge creation in the organization is carried out based on the SECI model pointed out by Nonaka and Takeuchi (1995), and both explicit knowledge and tacit knowledge are generated. Then, both types of knowledge are mobilized along with practical wisdom, which elevates the SECI Spiral of Nonaka and Takeuchi (2019) vertically. While the SECI Spiral is elevated, the knowledge base will be expanded horizontally. As noted in Section 2.6, practical wisdom must penetrate throughout the organization, which corresponds to the organizational culture required by ERM.

(2) As discussed in (of the “knowledge generation process in the subjective risk assessment

process, ” the “ overall risk ( T ) that cannot be objectively captured ” will be inferred from

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knowledge f (this process corresponds to risk perception).

Step 2

  The close association of (1) and (2) in Step 1 leads to the subjective risk assessment process in assessing risks that are extremely difficult to quantify, as discussed at the end of Section 2.5. The assessment of risks that are extremely difficult to quantify corresponds to Zone 1, as described in Section 2.4. Then, in Zone 1, as discussed in Section 2.3, it leads to the effectuation process that is effective when the future is unpredictable and the objective is unclear.

4. Conclusion

  Uehara (2020) presented the “application framework of effectuation and causation to

quantifiable and non-quantifiable risks, ” which corresponds to the effectuation process and

causation process by Sarasvathy (2001), respectively, for risks that are extremely difficult to

quantify in “ Zone 1 ” and risks that are quantifiable in “ Zone 2 ” under the “ frequency of

occurrence-based risk management” (Uehara, 2002). The application of this new framework

to ERM enables business entities to distinguish between risks that are extremely difficult to

Figure 7 Integration of the “application framework of effectuation and causation to quantifiable

and non-quantifiable risks” and SECI Spiral, mediated by the knowledge generation

process in the subjective risk assessment process

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quantify in “Zone 1” and risks that can be quantified in “Zone 2” based on the risk threshold perceived by each business entity and to respond to them, which makes it possible to perceive risk management that corresponds to the frequency of occurrences in uncertainty.

  In this study, based on the importance of utilizing knowledge creation in organizations as proposed by Nonaka and Takeuchi (1995, 2019) and the SECI Spiral (Section 2.6) in the effectuation process of the “application framework of effectuation and causation to quantifiable and non-quantifiable risks” (Section 2.4) (Uehara, 2020), we were able to present a new concept that integrates these two approaches by mediating and applying the knowledge generation process (Section 2.5) in the subjective risk assessment process of Uehara et al. (2016). As a future challenge, it is necessary to construct a quantitative analytical model and verify the concept presented in this study. In other words, first, we believe that it is essential to clarify the objective appearance of “explicit knowledge” and

“tacit knowledge” in knowledge creation and phronesis (practical wisdom) as the driving force of the SECI Spiral using quantitative analytical models or simulations. Next, it is crucial to examine how to quantitatively capture effectuation, which is a decision-making theory used by experts. If these goals can be achieved, it will be possible to objectively and quantitatively understand the process of estimating the “overall risk ( T ) that cannot be objectively captured” with knowledge f in the “knowledge generation process in the subjective risk evaluation process.”

Acknowledgements

  I would like to thank Editage (www.editage.com) for English language editing and publication support.

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Sarasvathy, S. D. (2001), Causation and effectuation: Towards a theoretical shift from economic inevitability to entrepreneurial contingency, Academy of Management Review, 26(2), 243―263 Sarasvathy, S. D. (2008), Effectuation: Elements of entrepreneurial expertise. Northampton, MA and

Cheltenham: Edward Elgar

Uehara, M. (2002), A conceptual model of risk management focusing on the frequency of occurrence, Journal of the Japan Association for Management Systems, 19(1), 41―47 (in Japanese) Uehara, M. (2020), Application of causation and effectuation processes to risk management, Bulletin

of Aichi Sukutoku University-Faculty of Business, 16, 15―27

Uehara, M., Sumai, S., & Yamashita, H. (2016), Knowledge generation process through subjective risk assessment, Proceedings of the Conference of Japan Association for Management Systems, 57, 216―219 (in Japanese)

Yamashita, H. (2007), Basic theory of information management, Tokyo Keizai-Jouhou Press (in

Japanese)

Figure 1  Application  framework  of  effectuation  and  causation  to  quantifiable and non-quantifiable risks
Figure 2  Relation  between  Risk  Perception  and  Hazard  Perception  in  the  Risk  Assessment Process (Uehara et al
Figure 3  Conceptual  Framework  of  Knowledge  and  Information  (Yamashita, 2007, p
Figure 6  The multiple dimensions of the SECI Spiral (Nonaka & Takeuchi,  2019, p

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