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Article

Forgotten Factors in Knowledge Conversion and Routines: A Fuzzy Analysis of Employee Knowledge Management in Exporting Companies in Boyacá

Facultad de Ciencias Económicas y Administrativas, Escuela de Administración de Empresas, Universidad Pedagógica y Tecnológica de Colombia, Tunja 150003, Colombia
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Author to whom correspondence should be addressed.
Mathematics 2023, 11(2), 412; https://doi.org/10.3390/math11020412
Submission received: 4 November 2022 / Revised: 7 January 2023 / Accepted: 9 January 2023 / Published: 12 January 2023

Abstract

:
The department of Boyacá accounts for only 0.93% of national exports, which means that the participation of exporting companies in the region is low. One of the most important factors within these organizations is the knowledge of the collaborators, since it is an asset that contributes to the daily activities carried out within an organization. Hence, the objective of this research was to analyze the incidence of the forgotten factors in knowledge management through the conversion of knowledge and the routines of the personnel in Boyacá’s exporting companies, by means of causal analysis using fuzzy methodologies. The participants are exporting activity collaborators in the companies, who were consulted as sources of information for the Boyacá chamber of commerce. For the treatment, the forgotten effects theory, the experton method, and the adequacy coefficient are used. The information collected is processed using FuzzyLog software. The findings highlight that there are forgotten factors between the knowledge conversion and routines related to informal communication and social interactions. It is worth noting that it is important to carry out a more in-depth analysis of each of the individual knowledge spiral pillars in exporting companies in different regions of the country, focusing on social interactions (linguistic expression) and informal communication (electronic meetings).

1. Introduction

Knowledge management arises from the need of organizations to know how to create, transmit, and apply knowledge to the processes of each entity [1], which implies the trust and cooperation of the people involved in the organization, who share an organizational vision and develop in an environment that should promote learning [2]. In fact, learning on repeated occasions is centered on transferred knowledge, which is divided into tacit and explicit knowledge. The first refers to personal and subjective knowledge, which is the result of acquired experience; accordingly, it is embedded in people and, thus, difficult to articulate, explain, and learn. The second is objective knowledge that can be codified and systematized, and, for this reason, it is more easily transferable between people [1]. The knowledge management process should include a cyclical development containing the following phases: identification, acquisition (knowledge conversion), classification and storage, distribution, and application. One of the main components of knowledge management is knowledge conversion, which is the process of making available and extending the knowledge created by individuals, as well as crystallizing and connecting it to an organization’s knowledge system [3,4]. Here, knowledge is generated by the collaborators (people) themselves, who follow the routines established by the companies. These routines are transformed into stable patterns of behavior that characterize organizational reactions to internal and external stimuli [5]. In fact, a routine is a repeated action sequence, which may have its roots in algorithms and heuristics on how the enterprise achieves things [6,7].
The main problem with the research is the department of Boyacá’s low participation in the country’s exports, considering that it only represents 0.93% at the national level [8], showing that the companies in the region are at a disadvantage compared with those in other departments. It is important to keep in mind that human capital is the driver of productive activity, and, for this reason, it is relevant to analyze the features and trends in human talent management, which cannot be disengaged from knowledge management to adapt its systems through the nature of that resource [9]. In the same way, companies can gain and understand knowledge, but may not have the skills to transform and exploit it, thus generating profits [10], which demonstrates the low relevance that organizations have given to the creation, conversion, and management of knowledge in a dynamic way [11]. Therefore, it is essential to study and analyze the incidences of knowledge conversion in the routines of exporting company collaborators in Boyacá to understand the factors that can help to improve the flow of knowledge conversion according to the characteristics and environment of the organization. The knowledge spiral is undoubtedly the model that presents the main variables used to determine the relationships between knowledge management and routines, i.e., socialization, internalization, combination, and externalization [12]. Routines are also classified into operational routines and search routines, which are intended to generate current revenues and increase profits in the future, respectively [5]. In fact, the incidence of knowledge conversion in routines may arise from the elements that compose the conversion of tacit and explicit knowledge, the shared context, and/or the set of possible patterns allowed and constrained by a variety of organizational, social, fiscal, and cognitive structures, on the basis of which organizational members carry out certain actions [13]. In this sense, understanding the relationship between knowledge conversion and routines is a complex problem that involves the interrelation among multiple factors, some of which are generally difficult for organizations to perceive, and are critical to the efficiency of data analysis, since they emphasize organizational and human aspects through the application of knowledge conversion theories [14].
On the basis of the above, this study aims to use subjective information to analyze the incidence of neglected factors in knowledge management through knowledge conversion and routines. The study is carried out on exporting companies in Boyacá registered in the Tunja and Sogamoso chambers of commerce. For the treatment of the data and its validity, fuzzy methods, the experton method [15], the adequacy coefficient [16], and the forgotten effects theory [17,18] are used to analyze the second order incidences between the conversion of knowledge and routines to identify an important interrelation between variables that at first seemed nonexistent (see Appendix A, Appendix B, Appendix C). The results show that the key incidence pathways of informal communication and social interactions, belonging to the socialization dimension, present a fracture in the knowledge management related to the incidences of informal communication and social interactions. Furthermore, the research has limitations related to the sample size and the subjective nature of the dataset. Moreover, when using these methodologies, it should be considered that the results obtained depend on the semantic configuration of the research design, even though they do not accurately capture these semantic nuances; hence, a careful design must be made. Here, it is remarkable that these methods give greater relevance to the meaning of the statements than to the measurement that can be derived from them [19]. Lastly, an analysis of the causes and effects is necessary to obtain a better diagnosis and to guide business decision making. Additionally, it is worth noting that a deeper analysis of each of the knowledge spiral pillars individually focusing on social interactions (linguistic expression) and in informal communication (electronic meetings) aids in understanding the particularities of conversion and routines in knowledge management.
The paper is organized as follows: Section 2 deals with the theoretical framework; Section 3 consists of the methodology, the type of approach, the model for finding second-generation relationships, case study, data collection, methods, and direct and indirect causal relationships; Section 4 shows the results; Section 5 comprises the discussion; lastly, Section 6 states the conclusions.

2. Theoretical Framework

This section presents a summary of the central characteristics of knowledge management, knowledge conversion, and routines, which were searched for and examined in the Web of Science (WoS) database using the following keywords: knowledge management OR knowledge conversion OR routines. Knowledge management in organizations favors knowledge exchange environments, by means of different models, as well as knowledge conversion, which is based on the relationship between tacit and explicit knowledge that exists in multiple areas of an organization, specifically in the routines of the collaborators that belong to it.

2.1. Knowledge Management

Knowledge management contributes to the creation of environments that allow the organization to develop scenarios conducive to the exchange and implementation of its knowledge in each of its departments [20]. The main objective of knowledge management is to facilitate organizations to create or capture critical knowledge, and, in the same way, to make it perceptible and evident for people to use it in an effective time or place. Hence, additional effort is made to generate an applicable knowledge base in datasets [14].
Knowledge management has become a relevant topic for organizations, since it generally deals with various groups of success factors that are oriented to the human being, the organization, technology, and management processes [21]. With respect to the human-oriented factors, which include culture, people, and leadership, it is worth highlighting the important role that people play in an organization, since the future of organizations depends to a great extent on people. This is because those people possess the knowledge and develop the skills and abilities that generate vital economic value for organizations, allowing companies to gain a greater competitive advantage over their rivals through the mastery of information [21].
In addition, the productive factor of excellence is knowledge, which serves as leverage in growing and rapid technological change, where all the information that an individual possesses in their mind is personalized and subjectively related to elements that may or may not be unique, useful, precise, or structural [22]. To test the concept of knowledge management, there is a model that identifies three main components: the linking of people with knowledge to help others, the structuring of processes to synthesize the process of filtering, legitimizing, and sharing knowledge, and the development of robust and enjoyable technologies to improve communication [14].
Similarly, knowledge management strategies can be described in two dimensions, manifesting the knowledge management approach. The first is the exchange of knowledge through interpersonal interaction, and the second is the ability to help create, store, share, and use an organization’s explicitly documented knowledge. These strategies also confirm that knowledge creation is associated with cultural factors, such as collaboration, trust, and learning [23].
The theory of organizational knowledge creation is defined as the process of organizationally extending the knowledge created by individuals and crystallizing it as part of an organization’s knowledge system, implying the importance of people in the development of knowledge. This process contemplates the distinction between tacit knowledge and explicit knowledge. The first type of knowledge is a cornerstone in the theory of organizational knowledge creation and covers knowledge that is not articulated but is linked to the senses, movement skills, physical experiences, intuition, or implicit rules. The second type of knowledge is transmissible in a formal and systematic language. Consequently, the two types of knowledge have been developed throughout history by individuals and/or collaborators. Therefore, the relationship between tacit and explicit knowledge configures the characteristics of the knowledge conversion model [12].

2.2. Knowledge Conversion

Knowledge conversion is based on the fact that human knowledge is created and expanded through the interaction between tacit knowledge and explicit knowledge, which increases both in quality and in quantity through the SECI process, i.e., the four different modes of knowledge conversion: socialization, externalization, combination, and internalization [24,25].
Socialization is the conversion of tacit knowledge to tacit knowledge, which means that it is the process of creating tacit knowledge as shared mental models and technical skills. Externalization is the conversion of tacit knowledge to explicit knowledge, being the process of articulating tacit knowledge into explicit concepts that take the form of metaphors, analogies, concepts, or models. Combination is the conversion of explicit knowledge into explicit knowledge, i.e., the systematization of concepts into a knowledge system, which implies that individuals exchange and combine knowledge through documents, meetings, conversations, or communication networks. Lastly, internalization is the transformation of explicit knowledge into tacit knowledge, which is related to “learning by learning”.
The “knowledge spiral” is the interaction between tacit and explicit knowledge, which increases in scale as the ontological levels ascend; the organization must mobilize the tacit knowledge created and accumulated at the individual level, and this is later amplified organizationally through the four modes of knowledge conversion and crystallized at higher ontological levels. Thus, knowledge creation is a spiral process, which starts at the individual level and advances through the expanding community of interactions, overcoming the limits of sections, departments, divisions, and organizations [24].
Individual actions model organizational actions, leading to environmental responses; then, the learning cycle is complete when these environmental responses alter individual representations and, thus, lead to better individual and organizational action [3]. Furthermore, knowledge requires a physical environment and/or context to be created, based on a concept called “Ba” [11], meaning “place”, i.e., the interaction space inhabited by different actors, where knowledge is shared, created, and used, in addition to providing the energy and quality to make individual conversions and advance in the spiral of knowledge. This space is not only physical (office, workshop, factory, etc.), but also virtual (email, video calls, etc.) and mental (shared ideals, values, beliefs, etc.) [11].
The authors also describe the four types of Ba. The first is the original Ba, which creates a context for socialization, as it is defined by individual and face-to-face interactions, where experiences, feelings, emotions, and mental models are shared. It is the only way to capture the full range of physical senses and psycho-emotional reactions, which are important elements for sharing tacit knowledge [26]. According to [11], the socialization dimension is the process of converting new tacit knowledge through shared experiences. This process derives from group collaborations in which individuals cooperate to share tacit knowledge that has been acquired through the internalization of explicit knowledge gained from information. This correlation results in tacit knowledge that is new to everyone involved (see Table 1) [14].
The second is the dialog Ba, which provides a context for externalization through collective, face-to-face interaction, where individuals’ mental models and skills are shared, converted into common terms, and articulated as concepts. Selecting people with the right combination of specific knowledge and skills is the key to successful knowledge management within the dialog Ba [11]. The externalization dimension is the transformation of tacit knowledge into explicit knowledge, being the process of articulating tacit knowledge into explicit concepts, taking the form of metaphors, analogies, concepts, or models (Table 2) [24]. In a multiorganizational context, externalization can become difficult, considering that tacit knowledge is related to culture and context, i.e., it is rooted in individuals [30].
The other type of Ba is systematization, defined by collective and virtual interactions, mainly providing a context for the combination of explicit knowledge, and generally supported by information technology. The combination dimension is the conversion of explicit-to-explicit knowledge, i.e., the systematization of concepts, which implies that individuals exchange knowledge through documents, meetings, conversations, or communication networks (Table 3) [24]. In this process, aggregated knowledge can become a source of value creation, where participants collaborate to promote and communicate new learning to different teams, such that an organizational knowledge asset is developed [30].
The last classification of Ba is that of exercise, which is constituted by individual and virtual interactions, offering an internalization context, where individuals incorporate explicit knowledge that is communicated through virtual media, written manuals, and simulation programs, among others, to later convert it into tacit knowledge [11]. The internalization dimension is the process of converting explicit knowledge into tacit knowledge. Through internalization, the explicit knowledge created is shared by the whole organization and converted into tacit knowledge by individuals (Table 4) [11]. This procedure changes to an individual dimension, where professionals and operators take explicit knowledge and interpret it according to their own intuition and professional experience, thus internalizing it as tacit knowledge [14].
Both tacit and explicit knowledge are important. However, treating them individually, as applied in the process of combination and socialization, can cause problems, since it can result in a superficial interpretation of the existing knowledge that has little to do with the current reality. Furthermore, this knowledge can be limited and difficult to apply in other fields that are different from the specific one in which it was created, respectively [33].

2.3. Routines

Routines are one of the keys to understanding organizational functioning [34]. Routines have qualities of both stability and change, and, by means of an analogy, it is understood that an organizational routine is not a single pattern; on the contrary, it is a set of possible patterns allowed and limited by diverse organizational, social, physical, and cognitive structures from which the members of the organization perform certain actions [35].
Considering the above, routines are understood as flows of ideas, actions, and connected results. First, ideas produce actions; subsequently, actions produce results, so that these produce new ideas, generating change [6]. However, the relationship among ideas, actions, and results is not always close, as ideas can generate actions that, in fact, do not execute the ideas; actions can generate results that make possible or necessary new and different actions [13]. On the other hand, some authors oppose considering routines as rules that are definitively established, and propose that routines be understood as adaptive rationality [36].
Routines are stable patterns of behavior that characterize organizational reactions to various internal or external stimuli, with two types of routines demarcated: organizational and accumulation of experience [7]. The former involves the execution of known procedures with the objective of generating current revenues and profits, while the latter seeks to bring about desirable changes in the existing set of operating routines, with the purpose of increasing profits in the future.
The dimension of operational routines: The application of processes that are known by staff to achieve current goals (Table 5) [5]. Team behavioral interaction patterns (TBIP) are a very important feature of team adaptation, as research affirms that, to make groups effective in the performance of stable or routine tasks, long and complex interaction patterns are required to increase team efficiency [37].
The dimension of search routines: The objective of these routines is to elicit and generate desirable alterations to previously established operating routines in such a way as to increase future profits (Table 6) [5]. These can be found as organizational functions aimed at learning and change in a specific department, such as innovation and development, marketing, or human resources, or as processes that are requested in response to a need or problem, so that an individual, a committee, a working group, or a consultant studies and analyzes them [38].
The previous theoretical review supports the construction of the instrument, since a theoretical framework was developed, from which the dimensions of knowledge conversion and routines emerged. Subsequently, subdimensions are identified to define the statements according to the practices of the organizations and to consider the knowledge spiral. These are evaluated by means of the semantic scale (see Table 9), to capture the subjective perceptions of the companies’ collaborators.
Considering that the objective is to analyze the second-degree incidences of knowledge conversion in the routines of the collaborators who provided subjective information by means of the instrument, fuzzy methods are used for its treatment. These allow an understanding and comprehension of the meaning of the results, beyond generating a measurement of the results [19].

3. Methodology

This research analyzes the forgotten factors between the conversion of knowledge and the routines of collaborators in exporting companies in Boyacá, using subjective information. Thus, the research type and approach, the model of identification of the second-generation relationships, the description of the case study, and the organization of the subjective data are presented. The methods used to analyze the dataset deal with the subjective information of the collaborators, to correct the underestimation of the data and to obtain the accurate estimates.

3.1. Type and Approach

The present research is of an explanatory or causal type since it intends to establish the incidence of the forgotten factors in knowledge management through the conversion of knowledge and the routines of the personnel of the exporting companies of Boyaca. This section presents the model of forgotten or second-generation factors, the description of the case study, the organization of the subjective data and the methods to be used, which are the experton method, the adequacy coefficient, and forgotten effects theory.

3.2. Model for Finding Second-Generation Relationship

The realization of the model considered the theoretical review presented in the theoretical framework and the methods studied for the design (data collection, called criteria), the dimensions, the methods, and the results of the relationships, presented in Figure 1, establishing a logical sequence that allows aggregation for the treatment process. This process (Figure 1) contains three elements that determine how to find and establish the forgotten factors. The first is the process, which sets out how second-generation relationships can be established. The second is a description that presents the processing of the information and the creation of the working model, where dimensions and the type of information to be collected were defined. The internal processing then considers the proposed methods; lastly, the new relationships found are shown. The third element describes the stages necessary to obtain the findings [41].
The methods implement calculations and procedures to understand the variations within semantic scales, which are transformed into numerical values representative of the same, generating approximate relationships and relative explanations, creating a large number of possibilities [41].
Models used to search for ignored effects can generate multiple data, since they are often binary-valued systems (i.e., they are evaluated through numbers in [0,1] or confidence intervals of [0,1]), which represent the meaning given to the relationships and not a measure of the relationships in absolute terms [17]; that is, they do not consider the relationship between incidence and the linkage between different arguments that apparently have nothing in common. Indeed, the incidence of relationships is determined by intensity and linkage. Intensity considers the presence of a connecting agent in the relationships, making it possible to analyze the convergence of the boundary, periodicity, and non-standardized situations reflected in elements such as time, space, and possible connections [42]. On the other hand, linkage shows the direct and indirect connections in the relationships, analyzing variations in the intensities and strengths of the relationships to observe the behavior and the links that strengthen or weaken them, either in a period or in a sequence of stages [42].

3.3. Case Study

The target population of the study consisted of the collaborators in the exporting companies registered in the chamber of commerce of the department of Boyacá, Colombia. Chambers of commerce are private, nonprofit organizations that represent a group of companies and traders in a region, promoting competitiveness, formalization, and regional development, as well as serving as a consultative body on economic issues, among other characteristics [43]. The exporting companies in this study were registered in the chambers of commerce of Tunja and Sogamoso in the department of Boyacá, and were engaged in different economic activities, such as engineering activities, retail and wholesale trade of different products, legal activities, mixed exploitation (agriculture and livestock), data processing, medical activities, call centers, real estate activities, extraction of emeralds, and the processing and preservation of fruits, vegetables, and legumes.
Initially, the research proposed the participation of all the companies registered in the chambers of commerce in the department of Boyacá, but this was not possible due to different limitations. The first limitation was related to the fact that some companies, even though they are registered, had not carried out any commercial movement, i.e., they were never in operation. On the other hand, there were some difficulties in accessing companies registered with outdated data that prevented face-to-face, telephone, or electronic contact. Similarly, when contacted, some companies showed interest in participating in the research, but postponed the application of the instrument. Consequently, the instrument was applied to 40 collaborators in the 40 companies registered in the Tunja and Sogamoso chambers of commerce.
The instrument was applied in three stages. The first stage involved contacting the chambers of commerce to learn about the exporting companies registered in the region. In the second stage, the first contact was made with the collaborators by telephone and email to confirm their participation and to arrange for the link to the instrument to be sent by email or to be applied by telephone. In the third stage, the survey was carried out via telephone and email, where the link was sent and support was provided in resolving doubts and concerns about the instrument, and in person in some cases. Although the population was small, this did not affect the main objective, which was to analyze the incidence of forgotten factors in knowledge conversion in the routines of the personnel. This objective sought to make sense of the information but not to measure it [19]. Therefore, a fuzzy point of view was used to obtain the expected results.

3.4. Data Collection

An instrument was built according to the theory of organizational knowledge creation, which organizationally expands the knowledge created by people and connects it to the knowledge system of an organization, where tacit and explicit knowledge interact dynamically [12]. This instrument was implemented as a scale, considering the forgotten effects theory, since the intention of the study was to establish a causal relationship and to identify forgotten elements that are apparently not related [44,45,46]. Subsequently, for the treatment of the instrument and its validity, fuzzy methods, the experton method, and the adequacy coefficient were used. The use of fuzzy methods allows us to focus on the meaning of the results rather than on their measurement [19]. The experton method facilitates an understanding of the distribution and trend of the subjective opinions of the individuals, aggregating them to obtain an overall opinion. Lastly, the adequacy coefficient calculates the differences between two elements by neutralizing the real value when it exceeds the ideal value [41]. The causes and effects used in the study are presented below with their respective identifiers and statements (see Table 7 and Table 8).
For the evaluation of the elements considered as cause and effect for knowledge conversion, routines and knowledge management are expressed on the scale in Table 9.
After collecting the information, fuzzy methods, the experton method, and the adequacy coefficient were used for its treatment and validity. The approach was from a fuzzy perspective, using software such as FuzzyLog, which is a calculation program that elaborates and works with models on the basis of uncertainty mathematics to recover the so-called forgotten effects in causality relationships.
To achieve the research aim, three methodological phases are proposed, which give a logical order to the research process. In phase one, a review of the literature on knowledge management is carried out. To observe the context of these topics and their main advances in a holistic way, the Web of Science database is used. The following keywords are used in the search: knowledge creation, routines, and knowledge management. These results are then filtered under the concept of “management” so that the information is closer to the expected field of research. A theory of the creation of organizational knowledge, which has a dynamic model that expands through the interaction between tacit and explicit knowledge, was exposed by Nonaka and Takeuchi. Similarly, Nelson and Winter made important contributions to the concept of routines, which allowed the construction of the theoretical framework and the research methodology. In phase two, a scale instrument is implemented, which is treated with the forgotten effects theory, the experton method, and the adequacy coefficient. The information obtained is analyzed using FuzzyLog software. Lastly, in phase three, with the theoretical review complete, the data treatment is carried out and the preliminary conclusions obtained.

3.5. Methods

The present research employed different methods for data analysis, i.e., the experton method, the adequacy coefficient, and the theory of forgotten effects.

3.5.1. Experton Method

The experton method facilitates the addition of close or distant opinions as subjective uncertainty information [15]. The experton is a tool that uses fuzzy set theory and possibility analysis to unify information from different experts using a cumulative distribution function, which is obtained using linguistic expressions from a group of experts on an endecadary scale [0,1]. The experton method is defined as an extension of the probabilistic set, where the probability of each α-slice is replaced by a probability interval according to the experts. The structure of the formula is as follows:
a E : a j a , a j a 0 , 1 ,
where is the inclusion set, and j represents the expert.
Derived from the fact that the experton method is an extension of the probabilistic set, it has the same characteristics, as follows:
  • Non-strict horizontal increasing monotonicity property (i.e., the membership characteristic function of the positively sloping function is less than or equal to the characteristic function of the negative slope function).
  • Non-strict vertical increasing monotonicity property, except at level 0, which always takes the value 1.
Thus,
α 0 , 1 : α 1 a α 2 a e n   α 1 α 1 a , α 2 a ,
α α 0 , 1 : a > a α 1 a α 1 a , α 2 a < a 2 ( a ) ,
a = 0 a 1 a = 1 , a 2 a = 1 .
The variables must be evaluated, using a number 𝛼 ∈ [0,1] or through confidence intervals.
  • The individual opinions should be converted into an overall opinion of the group of individuals.
  • The statistics are generated and the complementary cumulation law is applied.
The importance of the experton method lies in the fact that the distribution and trend of the subjective opinions can be determined and, in the end, aggregated to generate an overall opinion of the group.

3.5.2. Adequacy Coefficient

The notion of distance in the use of fuzzy subsets is based on the premise that every metric is always a distance, but not every distance is a metric [16]. Considering this premise, the adequacy coefficient is a measure of distance called infradistance, which determines appreciable differences by correcting the overestimation of information without being a given metric.
The adequacy coefficient [47,48] is an index that allows us to calculate the differences between two elements, which neutralizes the result when the comparison shows that the real element has a higher value than the ideal element. For the two elements A and B, the adequacy coefficient weight is defined below.
Definition 1. 
A weighted adequacy coefficient of dimension n has a mapping of K : 0 , 1 n x 0 , 1 n 0 , 1 which has associated with it a weighting vector w of dimension n with the sum of the weights 1 y w j 0 , 1 , such as
K ( x 1 , y 1 , , x n , y n , ) = i = 1 n w i 1 1 x i + y i ,
where x j , y, and y j are the i-th arguments of the elements X and Y.

3.5.3. Forgotten Effects Theory

The forgotten effects theory is based on the concept of incidence, which is a subjective notion linked to reasoned action. Incidence is studied based on a network of links that omit several stages and forget conclusions [17].
Therefore, its operation is focused on second-generation effects that make it possible to find the effects forgotten in the first instance. In this way, incidence is a remarkably subjective definition, and its analysis enhances reasoned action and decision making. There is an incidence a i on b j . Here, the values of the characteristic function of the pair ( a i , b j ) are valued between [0,1]:
  a i ,   b j   M a i ,   b j     0 , 1 .
The direct incidence matrix is defined by the set of pairs of valued elements, which shows the cause–effect relationship that occurs in different degrees between the elements of set a (causes) and the elements of set b (effects):
b 1 b 2 b j a 1 u a 1 b 1 u a 1 b 2 u a 1 b j M ˜ = a 2 u a 2 b 1 u a 2 b 1 u a 2 b j a i u a i b 1 u a 1 b 2 u a i b j
All events show three ways of representing cause–effect relationships, which are denoted within the matrix of direct or first-order events. These relationships are considered when establishing the impact of some elements of one set on those of another.

3.6. Direct and Indirect Causal Relationship

It is possible to obtain hidden cause–effect relationships. Causal relationships are given by
M ˜ = M a j b i   ϵ   0 , 1 / i = 1 , 2 ,   , n ; j = 1 , 2 , , m .
According to M a i b j , the characteristic function of the permanence of the elements of the matrix [ M ˜ ] is formed by the rows corresponding to the elements of set a (causes) and the columns corresponding to the elements of set b (effects). In fact, the matrix [M] is formed by the effects that the elements of set a have on set b. If [ M ˜ ] shows the first-generation cause–effect relationships, the next step is to obtain an incidence matrix reflecting the indirect relationships. To do this, it must be considered that the different causes can have effects on themselves, and that the effects can have incidences on themselves. Therefore, two additional relationships are created. Consequently, two auxiliary matrices are formulated and defined as square matrices:
[ A ˜ ] = M a i a j   0 , 1   i , j = 1 , 2 , , n ,
[ B ˜ ] = M b i b j   0 , 1   i , j = 1 , 2 , , m ,
where [ A ˜ ] collects the incidence relationships between the causes, and [ B ˜ ] does so on the effects. Both matrices are reflexive, and it is satisfied that M a i a j = 1     i = 1 ,   2 , n and that M b i b j = 1     i = 1 ,   2 , m . This implies that any element, whether cause or effect, indicates with the maximum assumption about itself; thus, neither [ A ˜ ] nor [ B ˜ ] is a symmetric matrix. With the three matrices defined, the causal relationships between them must be established. Therefore, the maximum–minimum composition of the three matrices is given by [ A ˜ ] [ M ˜ ] [ B ˜ ] = [ M ˜ ] .
a 1 a 2 a n a 1 1 u a 1 a 2 u a 1 a n a 2 u a 2 a 1 1 u a 2 a n a n u a n a 1 u a n a 2 1 A ˜ b 1 b 2 b m a 1 1 u a 1 b 2 u a 1 b m a 2 u a 2 b 1 1 u a 2 b m a n u a n b 1 u a n b 2 1 [ M ] ˜ b 1 b 2 b n b 1 1 u b 1 b 2 u b 1 b m b 2 u b 2 b 1 1 u b 2 b m b m u b m b 1 u b m b 2 1 B ˜ b 1 b 2 b m a 1 u a 1 b 1 u a 1 b 2 u a 1 b m = a 2 u a 2 b 1 u a 2 b 2 u a 2 b m a n u a n b 1 u a n b 2 u a n b m M ˜
The degree of neglect of some causal relationships is given by the difference between the matrix of second-generation effects and the matrix of direct incidences: O ˜ = M ˜ M ˜ . Therefore, if the value of the characteristic function of the matrix elements [ O ˜ ] is high, the degree of forgetting in the initial incidence ratio is the highest.
O ˜ = b 1 b 2 b m a 1 u a 1 b 1 u a 1 b 1 u a 1 b 2 u a 1 b 2 u a 1 b m u a 1 b m a 2 u a 2 b 1 u a 2 b 1 u a 2 b 2 u a 2 b 2 u a 2 b m u a 2 b m a n u a n b 1 u a n b 1 u a n b 2 u a n b 2 u a n b m u a n b m

4. Results

4.1. Knowledge Conversion

Figure 2 describes incidences C14 (the information provided by the company is clear and understandable) and E16 (the information provided by the company has allowed me to solve problems and create solutions), which have a forgotten effect equal to one, indicating that there is no direct relationship between cause and effect. The entry of collaborators into companies implies the transfer of explicit knowledge in a clear and understandable way, which requires time, especially in the detailed description of the functions of each collaborator, with the purpose that this becomes tacit knowledge in the future. This is a challenge for organizations; therefore, by structuring the company in teams based on learning, strategies are implemented that relate the thoughts and concepts known by each of the collaborators. It is possible to have a mutual understanding that allows a process to be executed whereby tacit knowledge becomes explicit and permits this information to contribute to problem solving. This is a strategic competitive factor for the exporting companies in Boyacá, in which tacit knowledge plays a fundamental role [14].
Figure 3 describes incidences C16 (I am motivated to discuss databases, documentation, and manuals, among others, with my colleagues) and E2 (sometimes I do not know how to express what I think in words), which have a forgotten effect equal to one, indicating that there is no direct relationship between cause and effect. The starting point is based on the internalization process, where collaborators could transfer explicit knowledge to tacit knowledge through the discussion of codified knowledge [11]. Therefore, the key relationship is the recording of improvements in a database. However, the effect of this process refers to the difficulty for employees to express their thoughts in words, constituting a disadvantage in socialization [12].

4.2. Routines

Figure 4 describes incidences C1 (my work group is always the same) and E9 (when making a change in each area, the company involves all its personnel), which have a forgotten effect close to one (0.8), indicating that there is no direct relationship between cause and effect. The starting point is the high operational frequency of the work group; that is, generally, the collaborators keep the same team in the long term. In this case, when there is freedom to make changes, either because the execution of the routines is not achieving an expected or desired result, or because such results do not reveal new possibilities, the collaborators will try to repair or improve the routine, affecting other areas of the company. This can expand the repertoire of modification or adaptation, considering that there are more environments involved [5].
Figure 5 describes incidences C6 (forbidden to make any change, both in the tasks I perform and in the way I execute them) and E9 (a change involves all the personnel in the area), which have a forgotten effect close to one (0.8), indicating that there is no direct relationship between cause and effect. In organizations, there is an established routine, which does not allow employees to make changes in their functions. However, often, there are both small and large disturbances. The former is absorbed by the different members of the company, and the latter highlights the differences that exist in the interpretations of the routine in each area, considering that these bring with them understandings and motivations. Therefore, interferences, interactions, and the dynamics of knowledge in the different areas are necessary. In addition, organizations have exceptions at specific times and moments, since these changes can shape the adoption, persistence, or mobilization of routines, resulting in improvements that can be useful in other areas and, in the same way, involve the collaborators who interact in them [5].

4.3. Knowledge Management

On the basis of the theoretical concepts and different tests performed in the FuzzyLog program, the dimensions of socialization, internalization, and search routines are found as cause and effect, specifically the variables of informal communication, social interactions, learning, and active search (Table 10). Among them, the causal relationships between knowledge conversion and routines that presented forgotten effects the most are E2 (sometimes I do not know how to express what I think in words) and E4 (in virtual meetings, I feel it is more difficult to express myself than personally).
Consequently, the fractured routes of incidence were identified for each of the effects, i.e., one was chosen for socialization, another for internalization, and one for search routines for both informal communication and social interactions, considering that this is where the greatest number of forgotten effects occurred.
In informal communication, with respect to socialization, case 32 was selected, where the causes are IS_RE and AP_DBD, and the effects are AP_IMD and CI_EL. In the case of internalization, case 33 was chosen, where the causes are AP_DBD and BA_CD, and the effects are AP_RP and CI_EL. In search routines, case 19 was chosen, where the causes are BA_SAD and BA_CD, and the effects are AP_RP and CI_EL. In social interactions, case 4 was selected for socialization, with IS_RE as cause, and IS_CPC and IS_RV as effects. For internalization, case 6 was chosen, in which the cause is AP_DBD, and the effects are AP_IMD and IS_RV. For the search routines, case 4 was chosen, in which the causes are BA_SAD and BA_CD, and the effects are IS_CPC and IS_RV.

5. Discussion

The results show the most relevant factors in the knowledge conversion and routines of the collaborators in exporting companies in Boyacá. The incidences between the causes and effects of both knowledge conversion and routines were observed using mathematical tools based on fuzzy models, which establish second-generation relationships between factors that apparently had no evident relationship. The research revealed the incidences in knowledge management by means of the forgotten factors between knowledge conversion and routines, evidencing that the effects that most presented forgetfulness are part of informal communication and social interactions, i.e., that these indicators represent the key route of the incidence, which manifested a fractured route for knowledge management in the Boyacá exporting companies, specifically in the capacity to express linguistically and in a virtual way. This fracture refers to the difficulty of sharing and disseminating tacit knowledge electronically, once it has been produced and appropriated by collaborators. In other words, one of the elements that characterizes tacit knowledge is that people are not aware of its full range, as, once it is internalized, it becomes a natural part of one’s behavior or way of thinking [48]; hence, it is more difficult to specify and to express.

Knowledge Management

The knowledge management model showed that the effects presenting the highest number of forgotten effects were part of informal communication (E2) and social interactions (E4), and that in these variables, there was a fractured route in the incidences, which hinders the process of knowledge creation. By virtue of this, it can be observed that the system presented 129 alternative routes for E2 and 29 for E4 (see Table 11).
According to the FuzzyLog results, one case was selected for socialization, one for internalization, and one for search routines, and, both for informal communication and socialization, considering the cases that were most consistent with the theoretical framework (see Table 12 and Table 13). These relationships show that, in informal communication, the causes are part of socialization, internalization, and search routines, which are positive statements, since they refer to situations where employees have the freedom to express their opinions and doubts, discuss codified information, and feel confident enough to ask for help. These causes generated common effects, which are part of learning and informal communication. The effects of learning are favorable, considering that they are based on improvement and problem solving, while the effects that are part of informal communication represent a disadvantage, as it is difficult for employees to express what they think to their colleagues.
This means that organizations have tried to apply collaborative exchange mechanisms that promote the capture, representation, and application of knowledge, improving individual learning [49]. However, the effect of informal communication presented a disadvantage in the linguistic expression of tacit knowledge, evidencing the difficulty of externalizing the level of understanding with words. Consequently, even though the collaborators have the capacity and ability to solve problems, no practices have been developed in socialization for individuals to communicate their ideas, confirming the definition that Michael Polanyi gave to tacit knowledge: “We can know more than we can say” [31].
With respect to relationships in social interactions, the causes reflected are part of social interactions, learning, and active search, showing that there is a deepening in the behavior, emotion (socialization), and cognition (internalization) of the collaborators, which allows an understanding of the daily implementation of routines in the different areas [50]. These causes triggered effects that promoted knowledge conversion and others that limited it. On one hand, the understanding of routines, the discussion of explicit information, and group interactions made possible the connection of individual capabilities with those of employees and managers, resulting in improved functions and spontaneous collaborative exchanges. However, the common effect in the three dimensions reflected the difficulty for employees to express themselves virtually, proving one of the most debated characteristics of tacit knowledge, which states that sharing tacit knowledge through information technology systems is extremely difficult, considering that disseminating tacit knowledge in an explicit and objective way prevents it from being shared electronically [29].
Considering the above relationships, Figure 6 is presented, which exemplifies the second-order incidences for knowledge management. Area one (A1) shows the incidences between knowledge conversion and routines, and the key route of incidence, through informal communication and social interactions. On the other hand, area two (A2) presents a fractured route for knowledge management, i.e., the different constraints found in Boyacá’s exporting companies.

6. Conclusions

This research summarizes the theory related to knowledge management, knowledge conversion, and routines. A model is applied to identify the second-degree relationships between knowledge conversion and routines in exporting companies. This model deals with subjective information by means of internal processing, considering the proposed methods, which are the experton method, the adequacy coefficient, and the forgotten effects theory [17]. The notion of expertons contributes to foresight in situations where there is a lack of information [51]. The notion of distance used in the adequacy coefficient, called infradistance, makes it possible to determine the appreciable differences, correcting the overestimation of information without a given metric. The notion of incidences facilitates study of the basis of a network of links that omit several stages and forget the conclusions [17]. In this sense, the methods used make it possible to aggregate the subjective criteria of the collaborators, correct the underestimation of the data to obtain the true estimates, and determine the second-generation incidences.
The case study focused on exporting companies registered with the Tunja and Sogamoso chambers of commerce. The collaborators occupy different positions, reflecting the diversity and heterogeneity in the instrument. The findings allow us to observe incidences in the conversion of knowledge, which show that, in the causes, the four pillars of the knowledge spiral are present. Meanwhile, in the effects generated and the alternative route proposed, socialization, externalization, and internalization prevail in a positive way, specifically informal communication, social interactions, learning teams, and learning.
The relationships found in the routines were revealed as causes of the operational frequency in the routines and the mobilization of knowledge. These triggered favorable common effects that are part of the search routines dimension, showing that the improvements implemented by the collaborators helped other areas and, in the same way, involved the personnel who produced the change. For these relationships, different alternative routes were projected, where the indicators of modification or adaptation, knowledge mobilization, and operational frequency prevailed.
The results obtained can help us to understand both the virtues and the fractures that exist in the knowledge management process, offering a vision of knowledge spiral development within organizations. Thus, the practical implications of the research can help to guide the practices of socialization, externalization, combination, and internalization in the routines of individuals to foster knowledge creation. On the other hand, the theoretical implications of the study refer to the findings of incidence among knowledge management, knowledge conversion, and routines, where a relationship was found among the four components of the SECI model, search routines, and operational routines, showing that knowledge creation is a daily organizational issue, and that it is present in each area of the company.
The advantage of using the proposed method is that it is an effective alternative for dealing with subjective information, which is complex for traditional methods to process. For this reason, this method enables the implementation of subjective criteria, and correction of the overestimates that may occur when comparing the values given with those established to obtain the true estimates. Lastly, it makes it possible to determine second-generation cause–effect incidences to find and analyze hidden relationships.
The limitations of the research are associated with the size of the sample, as the number of respondents was small; therefore, being subjective data, the results are based on the subjective perceptions of the employees, focusing on a specific reality that cannot be generalized. Consequently, the population that could be contacted and that applied the instrument totaled 40 employees in the 40 exporting companies.
When using these methodologies, it should be remembered that the results obtained depend on the semantic configuration of the research design, where academic, cultural, and social aspects influence the manner in which we communicate. In this sense, the methods do not allow us to accurately capture these semantic nuances, and a careful prior design must be made. Similarly, it should be considered that fuzzy methods allow us to deal with soft data; thus, their results are flexible in their interpretation with a solid formal methodological structure. Hence, these methods give greater relevance to the meaning of the statements than to the measurement that can be derived from them [19].
Lastly, as recommendations for future research, from a methodological point of view, an analysis of the causes and effects is necessary to achieve a better diagnosis and guide to business decision making. From an academic perspective, it is important to carry out a deeper analysis of each of the pillars of the knowledge spiral individually in exporting companies belonging to different regions of the country, especially in socialization, social interactions (linguistic expression), and informal communication (electronic meetings).

Author Contributions

Conceptualization, Y.C. and O.V.; methodology, F.B.-M.; software, F.B.-M.; validation, F.B.-M., Y.C. and O.V.; formal analysis, F.B.-M.; investigation, Y.C. and O.V.; writing—original draft preparation, F.B.-M.; writing—review and editing, F.B.-M., Y.C. and O.V.; project administration, F.B.-M.; funding acquisition, F.B.-M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Universidad Pedagogica y Tecnologica de Colombia, grant number SGI 3323, and Red Sistemas Inteligentes y Expertos Modelos Computacionales Iberoamericanos (SIEMCI), project number 522RT0130, in Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo (CYTED).

Data Availability Statement

Data are available from the authors.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A. Experton Method Calculus

Table A1. Experton method.
Table A1. Experton method.
FTαCI1CI2CI3CI4CI5IS1IS2IS3IS4IS5EA1EA2EA3EA4EA5EA6EA7EA8TI1TI2TI3TI4TI5DI1DI2DI3DI4DI5
000000000000000000000000000000
10.141105003121100000120000000011
20.292100013001000000201010000000
30.430124102010400000103143000000
40.5701131210031101020607656201020
50.712825252229211625242420812262625241721211925222218202422
60.8658965958658232086731136351291612912
7143304716486976683105681495845
40404040404040404040404040404040404040404040404040404040
RFTαCI1CI2CI3CI4CI5IS1IS2IS3IS4IS5EA1EA2EA3EA4EA5EA6EA7EA8TI1TI2TI3TI4TI5DI1DI2DI3DI4DI5
000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
10.14280.0250.0250.0000.1250.0000.0000.0750.0250.0500.0250.0250.0000.0000.0000.0000.0000.0250.0500.0000.0000.0000.0000.0000.0000.0000.0000.0250.025
20.28560.0500.0250.0000.0000.0000.0250.0750.0000.0000.0250.0000.0000.0000.0000.0000.0000.0500.0000.0250.0000.0250.0000.0000.0000.0000.0000.0000.000
30.42840.0000.0250.0500.1000.0250.0000.0500.0000.0250.0000.1000.0000.0000.0000.0000.0000.0250.0000.0750.0250.1000.0750.0000.0000.0000.0000.0000.000
40.57120.0000.0250.0250.0750.0250.0500.2500.0000.0750.0250.0250.0000.0250.0000.0500.0000.1500.0000.1750.1500.1250.1500.0500.0000.0250.0000.0500.000
50.7140.7000.6250.6250.5500.7250.5250.4000.6250.6000.6000.5000.2000.3000.6500.6500.6250.6000.4250.5250.5250.4750.6250.5500.5500.4500.5000.6000.550
60.85680.1250.2000.2250.1500.1250.2250.1250.2000.1500.1250.2000.5750.5000.2000.1500.1750.0750.2750.0750.1500.0750.1250.3000.2250.4000.3000.2250.300
710.1000.0750.0750.0000.1000.1750.0250.1500.1000.2000.1500.2250.1750.1500.1500.2000.0750.2500.1250.1500.2000.0250.1000.2250.1250.2000.1000.125
AFTαCI1CI2CI3CI4CI5IS1IS2IS3IS4IS5EA1EA2EA3EA4EA5EA6EA7EA8TI1TI2TI3TI4TI5DI1DI2DI3DI4DI5
001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
10.14281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20.28560.9750.9751.0000.8751.0001.0000.9250.9750.9500.9750.9751.0001.0001.0001.0001.0000.9750.9501.0001.0001.0001.0001.0001.0001.0001.0000.9750.975
30.42840.9250.9501.0000.8751.0000.9750.8500.9750.9500.9500.9751.0001.0001.0001.0001.0000.9250.9500.9751.0000.9751.0001.0001.0001.0001.0000.9750.975
40.57120.9250.9250.9500.7750.9750.9750.8000.9750.9250.9500.8751.0001.0001.0001.0001.0000.9000.9500.9000.9750.8750.9251.0001.0001.0001.0000.9750.975
50.7140.9250.9000.9250.7000.9500.9250.5500.9750.8500.9250.8501.0000.9751.0000.9501.0000.7500.9500.7250.8250.7500.7750.9501.0000.9751.0000.9250.975
60.85680.2250.2750.3000.1500.2250.4000.1500.3500.2500.3250.3500.8000.6750.3500.3000.3750.1500.5250.2000.3000.2750.1500.4000.4500.5250.5000.3250.425
710.1000.0750.0750.0000.1000.1750.0250.1500.1000.2000.1500.2250.1750.1500.1500.2000.0750.2500.1250.1500.2000.0250.1000.2250.1250.2000.1000.125
Exp 0.7590.7630.7810.6720.7810.8060.6630.8000.7530.7910.7720.8780.8530.8130.8000.8220.7220.8220.7410.7810.7590.7340.8060.8340.8280.8380.7840.806
AP1AP2AP3AP4AP5FO1FO2FO3FO4FO5H1H2BA1BA2BA3BA4BA5MC1MC2MC3MC4MA1MA2MA3MA4MA5
00000000000000000000000000
00000223042200000315100017
00100363166600011311200005
3031114202113211917000014013120019
7010101177777600110161184173071
20141915189561315828282529259152123112324238
417619171004110679461533561040
69144000200165557471466650
4040404040404040404040404040404040404040404040404040
AP1AP2AP3AP4AP5FO1FO2FO3FO4FO5H1H2BA1BA2BA3BA4BA5MC1MC2MC3MC4MA1MA2MA3MA4MA5
0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
0.0000.0000.0000.0000.0000.0500.0500.0750.0000.1000.0500.0500.0000.0000.0000.0000.0000.0750.0250.1250.0250.0000.0000.0000.0250.175
0.0000.0000.0250.0000.0000.0750.1500.0750.0250.1500.1500.1500.0000.0000.0000.0250.0250.0750.0250.0250.0500.0000.0000.0000.0000.125
0.0750.0000.0750.0250.0250.3500.5000.5250.3250.5250.4750.4250.0000.0000.0000.0000.0250.1000.0000.0250.0750.0250.0500.0000.0000.475
0.1750.0000.2500.0250.0000.2750.1750.1750.1750.1750.1750.1500.0000.0000.0250.0250.0000.4000.2750.2000.1000.4250.0750.0000.1750.025
0.5000.3500.4750.3750.4500.2250.1250.1500.3250.0250.1250.2000.7000.7000.6250.7250.6250.2250.3750.5250.5750.2750.5750.6000.5750.200
0.1000.4250.1500.4750.4250.0250.0000.0000.1000.0250.0250.0000.1500.1750.2250.1000.1500.0250.1250.0750.0750.1250.1500.2500.1000.000
0.1500.2250.0250.1000.1000.0000.0000.0000.0500.0000.0000.0250.1500.1250.1250.1250.1750.1000.1750.0250.1000.1500.1500.1500.1250.000
AP1AP2AP3AP4AP5FO1FO2FO3FO4FO5H1H2BA1BA2BA3BA4BA5MC1MC2MC3MC4MA1MA2MA3MA4MA5
1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
1.0001.0001.0001.0001.0000.9500.9500.9251.0000.9000.9500.9501.0001.0001.0001.0001.0000.9250.9750.8750.9751.0001.0001.0000.9750.825
1.0001.0000.9751.0001.0000.8750.8000.8500.9750.7500.8000.8001.0001.0001.0000.9750.9750.8500.9500.8500.9251.0001.0001.0000.9750.700
0.9251.0000.9000.9750.9750.5250.3000.3250.6500.2250.3250.3751.0001.0001.0000.9750.9500.7500.9500.8250.8500.9750.9501.0000.9750.225
0.7501.0000.6500.9500.9750.2500.1250.1500.4750.0500.1500.2251.0001.0000.9750.9500.9500.3500.6750.6250.7500.5500.8751.0000.8000.200
0.2500.6500.1750.5750.5250.0250.0000.0000.1500.0250.0250.0250.3000.3000.3500.2250.3250.1250.3000.1000.1750.2750.3000.4000.2250.000
0.1500.2250.0250.1000.1000.0000.0000.0000.0500.0000.0000.0250.1500.1250.1250.1250.1750.1000.1750.0250.1000.1500.1500.1500.1250.000
0.7590.8590.7160.8250.8220.5780.5220.5310.6630.4940.5310.5500.8060.8030.8060.7810.7970.6380.7530.6630.7220.7440.7840.8190.7590.494
FT: Frequency table; RFT: Relative Frequency Table; AFT: Accumulated Frequency Table; Exp: Experton.

Appendix B. Adequacy Coefficient Method to Find Cause–Effect, Cause–Cause, and Effect–Effect Matrices to Conversion Knowledge and Routines

Table A2. Cause–effect matrix to conversion knowledge.
Table A2. Cause–effect matrix to conversion knowledge.
E1E2E3E4E5E6E7E8E9E10E11E12E13E14E15E16
C110.910.90111111111111
C210.910.90111111111111
C310.910.90.99110.9910.9111111
C410.910.9111111111111
C510.910.9111110.9111111
C60.900.80.900.80.920.910.920.90.80.9010.90.910.9
C710.910.90.99110.9910.91110.911
C810.910.80.98110.9810.901110.911
C910.910.9111111111111
C1010.910.90111111111111
C1110.910.9111111111111
C1210.910.90.99110.9910.9111111
C130.90.80.90.80.970.910.9710.90.9110.911
C1410.810.80.970.910.9710.91110.911
C1510.910.90.99110.9910.9111111
C161110.9111111111111
C1710.810.80.980.910.9810.901110.911
Table A3. Cause–effect matrix to routines.
Table A3. Cause–effect matrix to routines.
E1E2E3E4E5E6E7E8E9E10E11E12
C10.90.90.90.80.870.9111111
C20.80.70.70.70.730.710.950.90.911
C30.80.70.70.70.730.710.950.90.911
C40.800.70.80.70.750.810.970.9111
C50.80.70.70.700.730.810.960.90.911
C60.90.90.90.90.890.9111111
C70.90.90.90.80.870.9111111
C80.80.80.80.70.770.810.991111
C9111111111111
Table A4. Cause–cause matrix to conversion knowledge.
Table A4. Cause–cause matrix to conversion knowledge.
C1C2C3C4C5C6C7C8C9C10C11C12C13C14C15C16C17
C111111111111111111
C211111111111111111
C31110.911110.910.911110.91
C411111111111111111
C511111111110.911110.91
C60.90.890.90.90.910.90.90.90.90.90.9110.90.80.9
C70.9110.911110.90.90.911110.901
C80.90.9410.911110.90.90.911110.91
C911111111111111111
C1011111111111111111
C1111111111111111111
C121110.911110.910.911110.91
C130.90.9310.911110.90.90.9011110.91
C140.90.9410.911110.90.90.911110.91
C151110.911110.910.911110.91
C1611111111111111111
C170.90.9410.911110.90.90.911110.91
Table A5. Causes–cause matrix to routines.
Table A5. Causes–cause matrix to routines.
C1C2C3C4C5C6C7C8C9
C1111111110.8
C20.911110.80.910.7
C30.911110.80.910.7
C40.911110.90.910.7
C50.911110.80.910.70
C6111111110.9
C7111111110.8
C80.9011110.90.9010.7
C9111111111
Table A6. Effect–effect matrix to conversion knowledge.
Table A6. Effect–effect matrix to conversion knowledge.
E1E2E3E4E5E6E7E8E9E10E11E12E13E14E15E16
E110.8910.9111110.9111111
E21111111111111111
E310.8910.9111110.9111111
E41111111111111111
E510.8710.9111110.9111111
E610.9010.9111111111111
E70.90.820.90.80.950.910.9510.90.910.90.911
E80.980.8710.9111110.9111111
E910.8510.80.98110.9810.901110.911
E101110.9111111111111
E1110.8910.9111110.9111111
E120.90.830.90.80.960.910.9610.90.910.90.911
E1310.8910.9111110.9111111
E1410.9110.90111111111111
E150.90.810.90.800.940.910.9410.90.910.90.9011
E1610.8510.80.98110.9810.901110.911
Table A7. Effect–effect matrix to routines.
Table A7. Effect–effect matrix to routines.
E1E2E3E4E5E6E7E8E9E10E11E12
E110.9410.90.951111111
E2111111111111
E3111111111111
E4111111111111
E5111111111111
E6111111111111
E70.80.720.70.70.730.710.950.90.911
E80.80.770.80.70.780.80111111
E90.90.800.80.80.810.8111111
E100.80.780.80.80.790.8111111
E110.80.740.70.70.750.810.970.9111
E120.80.700.70.70.710.710.930.900.911

Appendix C. Forgotten Effects Matrices to Conversion Knowledge and Routines

Table A8. Forgotten effects matrices.
Table A8. Forgotten effects matrices.
Matrix [ M ] ˜ : conversion knowledge
E1E2E3E4E5E6E7E8E9E10E11E12E13E14E15E16
C110.9110.9111110.96111111
C210.9110.9111110.96111111
C30.980.870.980.860.990.9710.9910.920.9810.980.9511
C410.9210.91111110.97111111
C50.990.880.990.8710.981110.930.9910.990.9711
C60.900.790.900.790.920.890.980.920.940.840.900.960.910.880.980.94
C70.970.860.970.850.990.9610.9910.910.9710.970.9511
C80.960.850.960.840.980.9510.9810.900.9610.960.9411
C910.9310.92111110.98111111
C1010.9110.90111110.96111111
C1110.9410.93111110.99111111
C120.980.870.980.860.990.9710.9910.920.9810.980.9511
C130.950.840.950.830.970.9410.970.990.890.9510.950.9310.99
C140.950.840.950.840.970.9410.970.990.890.9510.960.9310.99
C150.980.870.980.860.990.9710.9910.920.9810.980.9511
C1610.9610.95111111111111
C170.960.850.960.840.980.9510.9810.900.9610.960.9311
Matrix [ A ˜ ] [ M ˜ ] conversion knowledge
E1E2E3E4E5E6E7E8E9E10E11E12E13E14E15E16
C110.9610.95111110.98111111
C210.9510.95111110.98111111
C310.9310.93111110.96111111
C410.9610.95111110.98111111
C510.9410.93111110.96111111
C60.950.890.950.890.960.950.980.960.960.920.950.960.950.940.980.96
C710.9310.92111110.96111111
C80.980.920.980.920.990.9710.9910.940.9810.980.9711
C910.9610.95111110.99111111
C1010.9610.95111110.98111111
C1110.9610.95111110.99111111
C1210.9310.93111110.96111111
C130.970.920.970.910.980.9710.980.990.930.9710.970.9610.99
C140.980.920.980.910.990.9710.9910.940.9810.980.9611
C1510.9310.93111100.96111111
C1610.9610.95111111111111
C170.980.920.980.920.990.9710.9910.940.9810.980.9711
Matrix [ A ˜ ] [ M ˜ ] [ B ˜ ] conversion knowledge
E1E2E3E4E5E6E7E8E9E10E11E12E13E14E15E16
C110.9810.96111110.98111111
C210.9810.95111110.98111111
C310.9610.94111110.96111111
C410.9810.96111110.98111111
C510.9610.94111110.96111111
C60.960.920.960.920.960.960.980.960.970.950.960.980.960.960.980.97
C710.9610.94111110.96111111
C80.980.940.980.940.990.9810.9910.960.9810.980.9811
C910.9910.96111110.99111111
C1010.9810.96111110.98111111
C1110.9910.96111110.99111111
C1210.9610.94111110.96111111
C130.980.930.980.930.980.9710.980.990.960.9810.980.9710.99
C140.980.940.980.940.990.9810.9910.960.9810.980.9811
C1510.9610.94111100.96111111
C161110.96111111111111
C170.980.940.980.940.990.9810.9910.960.9810.980.9811
Matrix O ˜ conversion knowledge
E1E2E3E4E5E6E7E8E9E10E11E12E13E14E15E16
C10000000000000000
C20000000000000000
C31010110100101100
C40000000000000000
C51010010000101100
C60000000000000000
C71010110100101100
C80000000000000000
C90000000000000000
C100000000000000000
C110000000000000000
C121010110100101100
C130000000000000000
C140000000010000001
C151010110100101100
C160100000000000000
C170000000000000000
Matrix [ M ] ˜ routines
E1E2E3E4E5E6E7E8E9E10E11E12
C10.920.860.870.830.870.89111111
C20.770.720.730.690.730.7410.950.920.940.981
C30.780.720.730.690.730.7510.950.920.940.981
C40.800.740.750.710.750.7710.970.940.9611
C50.780.730.730.700.730.7510.960.930.950.991
C60.940.880.890.860.890.91111111
C70.920.860.870.830.870.89111111
C80.820.760.770.740.770.7910.990.960.9911
C9111111111111
Matrix [ A ˜ ] [ M ˜ ] routines
E1E2E3E4E5E6E7E8E9E10E11E12
C10.940.880.890.860.890.91111111
C20.860.860.860.830.860.8610.970.950.960.991
C30.860.860.860.840.860.8610.970.960.960.991
C40.880.860.870.860.870.8810.980.960.9811
C50.870.860.870.840.870.8710.970.960.960.991
C60.940.880.890.860.890.91111111
C70.940.880.890.860.890.91111111
C80.900.880.880.860.880.8910.990.960.9911
C9111111111111
Matrix [ A ˜ ] [ M ˜ ] [ B ˜ ] routines
E1E2E3E4E5E6E7E8E9E10E11E12
C10.940.940.940.920.940.94110.98111
C20.860.860.860.860.860.8610.970.970.970.991
C30.860.860.860.860.860.8610.970.970.970.991
C40.880.880.880.880.880.8810.980.980.9811
C50.870.870.870.870.870.8710.970.970.970.991
C60.940.940.940.920.940.94110.98111
C70.940.940.940.920.940.94110.98111
C80.900.900.900.900.900.9010.990.980.9911
C9111111111111
Matrix O ˜ routines
E1E2E3E4E5E6E7E8E9E10E11E12
C1000000000,8000
C2000000000000
C3000000000000
C4000000000000
C5000000000000
C6000000000.8000
C7000000000.8000
C8000000000000
C9000000000000

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Figure 1. A second-generation relationship model in the incidence of the conversion of knowledge into routines. Source: Own elaboration based on the studies of Blanco-Mesa, Leon-Castro, and Castro-Amado [41].
Figure 1. A second-generation relationship model in the incidence of the conversion of knowledge into routines. Source: Own elaboration based on the studies of Blanco-Mesa, Leon-Castro, and Castro-Amado [41].
Mathematics 11 00412 g001
Figure 2. Incidence between information dissemination and learning C14 E16. Source: Own elaboration. C14 DI_ICE: The information provided by the company is clear and understandable; C17 AP_EF: Upon joining the organization, they took the time to clearly explain my functions to me; E9 EA_RCC: I relate known concepts to express what I know; E16 AP_RP: The information provided by the company has allowed me to solve problems and create solutions. Initially estimated value: 0.99. Accumulated value cause–effect: 1. Difference of values (forgotten effect): 1. Relevant interposed key relationship: AP_EF.
Figure 2. Incidence between information dissemination and learning C14 E16. Source: Own elaboration. C14 DI_ICE: The information provided by the company is clear and understandable; C17 AP_EF: Upon joining the organization, they took the time to clearly explain my functions to me; E9 EA_RCC: I relate known concepts to express what I know; E16 AP_RP: The information provided by the company has allowed me to solve problems and create solutions. Initially estimated value: 0.99. Accumulated value cause–effect: 1. Difference of values (forgotten effect): 1. Relevant interposed key relationship: AP_EF.
Mathematics 11 00412 g002
Figure 3. Incidence between information dissemination and learning C16 E2. Source: Own elaboration. C16 AP_DBD: They motivate me to discuss databases, documentation, and manuals, among others, with my colleagues; E10 EA_BD: My work team records improvement ideas in a database; E2 CI_EL: Sometimes I do not know how to express what I think in words. Initially estimated value: 0.99. Accumulated value cause–effect: 1. Difference of values (forgotten effect): 1. Relevant interposed key relationship: AP_DBD.
Figure 3. Incidence between information dissemination and learning C16 E2. Source: Own elaboration. C16 AP_DBD: They motivate me to discuss databases, documentation, and manuals, among others, with my colleagues; E10 EA_BD: My work team records improvement ideas in a database; E2 CI_EL: Sometimes I do not know how to express what I think in words. Initially estimated value: 0.99. Accumulated value cause–effect: 1. Difference of values (forgotten effect): 1. Relevant interposed key relationship: AP_DBD.
Mathematics 11 00412 g003
Figure 4. Incidences between operating frequency and mobilization of knowledge C1 E9. Source: Own elaboration. C1 FO_GTP: My working group is always the same; C8 MA_LRC: I am free to make changes to my process when I deem it necessary; E10 MA_MAA: The improvements that I implemented in my work helped other areas of the company; E9 MC_CIA: When making a change in a certain area, the company involves all its personnel. Initially estimated value: 1. Cumulative cause–effect value: 0.98. Value difference (forgotten effect): 0.8. Relevant interposed key relationship: MA_LRC.
Figure 4. Incidences between operating frequency and mobilization of knowledge C1 E9. Source: Own elaboration. C1 FO_GTP: My working group is always the same; C8 MA_LRC: I am free to make changes to my process when I deem it necessary; E10 MA_MAA: The improvements that I implemented in my work helped other areas of the company; E9 MC_CIA: When making a change in a certain area, the company involves all its personnel. Initially estimated value: 1. Cumulative cause–effect value: 0.98. Value difference (forgotten effect): 0.8. Relevant interposed key relationship: MA_LRC.
Mathematics 11 00412 g004
Figure 5. Incidence of knowledge mobilization C6 E9. Source: Own elaboration. C6 MC_RAC: I am prohibited from making any changes, both in the tasks I perform and in the way I execute them; C7 MC_IAD: I cannot interfere in an area other than mine, unless the company allows me to; E10 MA_MAA: The improvements that I implemented in my work helped other areas of the company; E9 MC_CIA: When making a change in a certain area, the company involves all its personnel. Initially estimated value: 1. Cumulative cause–effect value: 0.98. Value difference (forgotten effect): 0.8. Relevant interposed key relationship: MC_IAD.
Figure 5. Incidence of knowledge mobilization C6 E9. Source: Own elaboration. C6 MC_RAC: I am prohibited from making any changes, both in the tasks I perform and in the way I execute them; C7 MC_IAD: I cannot interfere in an area other than mine, unless the company allows me to; E10 MA_MAA: The improvements that I implemented in my work helped other areas of the company; E9 MC_CIA: When making a change in a certain area, the company involves all its personnel. Initially estimated value: 1. Cumulative cause–effect value: 0.98. Value difference (forgotten effect): 0.8. Relevant interposed key relationship: MC_IAD.
Mathematics 11 00412 g005
Figure 6. Second-order incidents for knowledge management. Source: Own elaboration.
Figure 6. Second-order incidents for knowledge management. Source: Own elaboration.
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Table 1. The socialization dimension.
Table 1. The socialization dimension.
DimensionSubdimensionDefinition
SocializationInformal communicationSome researchers discussed the importance of informal communication for feedback and socialization [27].
Social interactionsFrom an organizational perspective, experiences are perhaps one of the most significant ways of converting tacit knowledge into tacit knowledge [28]. The epistemology of practice perspective suggests that effective knowledge sharing requires extensive and direct social interactions between people, as only during these processes can the tacit component of knowledge be shared [29].
Source: Own elaboration.
Table 2. The externalization dimension.
Table 2. The externalization dimension.
DimensionSubdimensionDefinition
ExternalizationLearning teamsTacit knowledge can be made explicit at the organizational level through the organization of the company into learning-based teams, where practical experience based on encouragement and a helping attitude predominates [31]. The best way to convert tacit knowledge to explicit knowledge is to organize the company into teams based on learning, considering practical experience based on drive and a predominantly helpful attitude [31].
Source: Own elaboration.
Table 3. The combination dimension.
Table 3. The combination dimension.
DimensionSubdimensionDefinition
CombinationInformation processingThe synthesis and integration of information, whether by means of manuals, documents, and databases, among others, on products, services, processes, etc., in addition to the recovery of material that supports the management or technical information of the entire company [11].
Dissemination of informationOne of the main issues for the management of knowledge resources is the dissemination of knowledge within organizations through computerized communication networks and databases available to the organization. For dissemination to be successful, a process of codification and externalization must first be made [11].
Source: Own elaboration.
Table 4. The internalization dimension.
Table 4. The internalization dimension.
DimensionSubdimensionDefinition
InternalizationLearningIn traditional learning, individuals learn the tacit knowledge needed in their trade through practical experience or by reading and analyzing manuals or through simulations and experiments that trigger learning by doing [4]. Collective learning occurs when individuals express their opinions and beliefs, engage in constructive confrontations, and challenge the views of others [32].
Source: Own elaboration.
Table 5. Dimension of operational routines.
Table 5. Dimension of operational routines.
DimensionSubdimensionDefinition
Operational routinesOperating frequencyFrequency with which the operating routine is activated and executed in a specific time period [5].
HeterogeneityThe variation in the characteristics of the task, as it is presented in different events, or how novel the task appears each time to the unit that has to perform it [5].
Source: Own elaboration.
Table 6. Dimension of search routines.
Table 6. Dimension of search routines.
DimensionSubdimensionDefinition
Search routinesActive searchThe search for knowledge can be a time-consuming activity, and managers often end their search for knowledge too early or rely on their own experience [39].
Knowledge mobilizationMobilize different knowledge components through the different functions, where several knowledge components are located [40].
Modification or adaptation(Re)architecture solutions, which were generated by exploring how to integrate knowledge, leverage, and develop their knowledge architecture competencies, which in turn allows them to design novel solutions [40].
Source: Own elaboration.
Table 7. Causes in the study.
Table 7. Causes in the study.
DimensionIndicatorStatementIdentifier
SocializationInformal communicationExtra workspaceCI_EEL
Spontaneous conversations in workspacesCI_CEEL
Social interactionsBusiness meetingsIS_RE
After work conversations with bossesIS_CEJ
Interactions in different areas and positionsIS_IDAC
ExternalizationLearning teamsWillingness to teach peersEA_DEC
Conversation of work topicsEA_CTL
TeamworkEA_TE
CombinationInformation processingRecord of resultsTI_RR
Reports of work completedTI_ITR
Supplier knowledgeTI_CP
Knowledge about clientsTI_CCL
Dissemination of informationAccess to organization informationDI_AIO
Clear and understandable informationDI_ICE
Access to information from other areasDI_AIA
InternalizationLearningDatabase discussionAP_DBD
Explanation of functionsAP_EF
Operating routinesOperating frequencyPermanent working groupFO_GTP
Search routinesActive searchProblem communicationBA_CP
Share doubtsBA_CD
Ask for help in difficultiesBA_SAD
Search for continuous improvementBA_BMC
Knowledge mobilizationMake some changeMC_RAC
Interference in a different areaMC_IAD
Modification or adaptationFreedom to make changesMA_LRC
Agreements with the working groupMA_AGT
Source: Own elaboration.
Table 8. Effects in the study.
Table 8. Effects in the study.
DimensionIndicatorStatementIdentifier
SocializationInformal communicationPeer relationsCI_RC
Linguistic expressionCI_EL
Everyday vocabularyCI_VC
Social interactionsVirtual meetingsIS_RV
Personal conversations with my colleaguesIS_CPC
ExternalizationLearning teamsTrainingsEA_C
Share knowledge to other areasEA_CCA
Associate words or imagesEA_API
List of known conceptsEA_RCC
DatabaseEA_BD
CombinationInformation processingUse of old reportsTI_UIA
Dissemination of informationSharing information with other areasDI_CIA
Share changes to collaboratorsDI_CCC
InternalizationLearningImplementation of manuals and documentationAP_IMD
Constant practice of functionsAP_PCF
Problem resolutionAP_RP
HeterogeneityOperating frequencyConsult the operation manualsFO_CMO
Constantly changing rolesFO_CFC
Change of functions according to the areaFO_CFA
Change in the way of performing functionsFO_CFRF
HeterogeneityExcessive number of tasksH_CET
Error anticipationH_AE
Search routinesActive searchIdentify actions to improveBA_IAM
Knowledge mobilizationSuggestions are valuedMC_SV
A change involves all areasMC_CIA
Modification or adaptationImprovements help other areasMA_MAA
Training improves my workMA_CMT
Adaptation of functionsMA_AF
Source: Own elaboration.
Table 9. Semantic scale.
Table 9. Semantic scale.
SSTDSDDIIAGSATA
SC0.140.290.430.570.710.861
Source: Own elaboration. SS: semantic scale, SC: standardization criteria, TD: totally disagree, SD: strongly disagree, DI: disagree, I: indifferent, AG: agree, SA: strongly agree, TA: totally agree.
Table 10. Causes and effects of knowledge management.
Table 10. Causes and effects of knowledge management.
Causes
VDISIdTEx
Knowledge conversionSocializationInformal communicationExtra workspaceCI_EELC10.759
Spontaneous conversations in workspacesCI_CEELC20.763
Social interactionsBusiness meetingsIS_REC30.806
After work conversations with bossesIS_CEJC40.753
Interactions in different areas and positionsIS_IDACC50.791
InternalizationLearningDatabase discussionAP_DBDC60.716
Explanation of functionsAP_EFC70.825
RoutinesSearch routinesActive searchProblem communicationBA_CPC80.806
Share doubtsBA_CDC90.803
Ask for help in difficultiesBA_SADC100.781
Search for continuous improvementBA_BMCC110.797
Effects
VDISIdTEx
Knowledge conversionSocializationInformal communicationPeer relationsCI_RCE10.781
Linguistic expressionCI_ELE20.672
Social interactionsEveryday vocabularyCI_VCE30.781
Virtual meetingsIS_RVE40.663
Personal conversations with my colleaguesIS_CPCE50.800
InternalizationLearningImplementation of manuals and documentationAP_IMDE60.759
Constant practice of functionsAP_PCFE70.859
Problem resolutionAP_RPE80.822
RoutinesSearch routinesActive searchIdentify actions to improveBA_IAME90.806
Source: Own elaboration. V: variable; D: dimension; I: indicator; S: statement; Id: identifier; T: type; Ex: expert.
Table 11. Number of alternative routes for knowledge management.
Table 11. Number of alternative routes for knowledge management.
SocializationInternalizationSearch RoutinesTotal
Informal communication (E2)554430129
Social interactions (E4)1310629
Source: Own elaboration.
Table 12. Alternate routes of informal communication.
Table 12. Alternate routes of informal communication.
Informal Communication
SocializationInternalizationSearch routines
Causes
IS_RE
In business meetings, they allow me to express my opinions and share my experiences
AP_DBD
They motivate me to discuss databases, documentation, manuals, among others with my colleagues
BA_SAD
I ask my bosses for help when I have difficulties in carrying out my work
AP_DBD
They motivate me to discuss databases, documentation, manuals, among others with my colleagues
BA_CD
I share my doubts with colleagues from other departments to resolve them
BA_CD
I share my doubts with colleagues from other departments to resolve them
Effects
AP_IMD
Through the implementation of manuals and documentation, among other reports, I have improved the execution of my functions
AP_RP
The information provided by the company has allowed me to solve problems and create solutions
AP_RP
The information provided by the company has allowed me to solve problems and create solutions
CI_EL
Sometimes I do not know how to express what I think in words
CI_EL
Sometimes I do not know how to express what I think in words
CI_EL
Sometimes I do not know how to express what I think in words
Source: Own elaboration.
Table 13. Alternate routes of social interactions.
Table 13. Alternate routes of social interactions.
Social Interactions
SocializationInternalizationSearch routines
Causes
IS_RE
In business meetings, they allow me to express my opinions and share my experiences
AP_DBD
They motivate me to discuss databases, documentation, and manuals, among others, with my colleagues
BA_SAD
I ask my bosses for help when I have difficulties in carrying out my work
BA_CD
I share my doubts with colleagues from other departments to resolve them
Effects
IS_CPC
Personal conversations with my colleagues allow me to give my opinions in a more open and relaxed way
Through the implementation of manuals and documentation, among other reports, I have improved the execution of my functionsIS_CPC
Personal conversations with my colleagues allow me to give my opinions in a more open and relaxed way
IS_RV
In virtual meetings, I feel that it is more difficult to express myself than personally
IS_RV
In virtual meetings, I feel that it is more difficult to express myself than personally
IS_RV
In virtual meetings, I feel that it is more difficult to express myself than personally
Source: Own elaboration.
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MDPI and ACS Style

Blanco-Mesa, F.; Vinchira, O.; Cuy, Y. Forgotten Factors in Knowledge Conversion and Routines: A Fuzzy Analysis of Employee Knowledge Management in Exporting Companies in Boyacá. Mathematics 2023, 11, 412. https://doi.org/10.3390/math11020412

AMA Style

Blanco-Mesa F, Vinchira O, Cuy Y. Forgotten Factors in Knowledge Conversion and Routines: A Fuzzy Analysis of Employee Knowledge Management in Exporting Companies in Boyacá. Mathematics. 2023; 11(2):412. https://doi.org/10.3390/math11020412

Chicago/Turabian Style

Blanco-Mesa, Fabio, Omar Vinchira, and Yesica Cuy. 2023. "Forgotten Factors in Knowledge Conversion and Routines: A Fuzzy Analysis of Employee Knowledge Management in Exporting Companies in Boyacá" Mathematics 11, no. 2: 412. https://doi.org/10.3390/math11020412

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