Knowledge-based assessment applied in Brazilian Toyota plants: employees’ perceptions

Type de publication:

Conference Paper


Gerpisa colloquium, Sao Paolo, Brasil (2018)


Knowledge management, Knowledge Management Assessment, Knowledge Management Evaluation, Knowledge Management Performance, Operations Management, Production Management


Purpose - This study aims to propose an assessment tool for Work, Production and Knowledge to support knowledge sharing among blue-collar workers and performance on the shop floor in Brazilian Toyota plants.
Design/methodology/approach - The methodology applied a comprehensive literature about operations management and knowledge sharing in web of science, which resulted in 20 papers selected from the period of 2001 to 2017. The research fieldwork was based on Action-Research (AR) in Brazilian Toyota plants and the data collecting procedure used a 4-point Likert scale questionnaire and semi-structured interviews to a sample of 55 employees selected from the Toyota 1 (T1) and 22 employees from Toyota 2 (T2).
Research Questions – The study aims to answer the following research questions: What are the factors for a production system to align People, Processes, and Knowledge? How to assess such factors? What is the importance of these factors in the opinion of production managers and workers?
Findings - The results evidence the importance of people factors. They also considered a relation among knowledge and lean techniques and judged that the Brazilian Toyota plants are aligned with this. The evidences indicate that the Brazilian culture does not influence changes in the Toyota work context and the results also provide an overview of the Toyota DNA implemented in Brazil, which supports the improvement actions.
Research limitations/implications - This study was limited to shop floor context and blue-collar workers perception of two Brazilian Toyota plants. The proposed approach is also able to be applied in other departments or organizations, even considering different cultures, worker groups or production sectors.
Practical implications - The findings and assessment instrument support evidence to create a favourable context to promote knowledge sharing through the shop floor context.
Originality/value - This paper contributes understanding the Toyota DNA presence in a different culture and increase the understanding to support managers’ actions on practical implications and KM implementation process. The findings also identify a pattern of Brazilian Toyota companies, which can establish a base of comparison for further researches.
This research is aligned with research opportunities raised in the literature review and develops an integrated approach based on human production, which justify this work as follows:
• Pragmatic orientations on ways to identify how the manager can develop favorable contexts to encourage processes of knowledge conversion in the organization (Nonaka, von Krogh and Voelpel, 2006);
• Identification of factors that influence tacit knowledge in groups of organizations (Erden, von Krogh and Nonaka, 2008);
• Interaction between social practices and the creation of organizational knowledge (Nonaka and von Krogh, 2009).

Texte complet:

1. Introduction
This study aims to propose an assessment tool for Work, Production and Knowledge to support knowledge sharing among blue-collar workers and performance on the shop floor in Brazilian Toyota plants. The analysis evaluates the integrated approach of W, P, K and its factors influencing the labor knowledge sharing and the performance on the shop floor according to the perspectives of employees (blue collar workers), also promoting Nonaka´s knowledge conversion process of Socialization, Externalization, Combination and Internalization (Nonaka, 1994).
Knowledge Management (KM) is the systematic, formal and deliberate action to capture, preserve, share and reuse the tacit and explicit knowledge created and employed by the people during the routine tasks and the improvement of the productive processes, in order to generate measurable results for the organization and for the people (Muniz Jr., Trzeniak and Batista, 2009). Industrial competitiveness presents challenges such as how to encourage employees to work together and share their knowledge even considering layoffs and effective readaptation of the remaining employees to new roles. These challenges are directly related to the trinomial: Work (aspects related to people), Production (physical and productive aspects) and Knowledge (addressing the creation and sharing processes of knowledge).
According to Muniz Jr. (2014), since the fragmentation of the task, popularized by the Taylorist perspective of Operations Management, tacit knowledge is one of the few elements that maintain the identity of an individual and his work. The attention to this kind of knowledge has increased with the current practices of lean manufacturing and work groups, especially regarding to the labor knowledge. KM influences the continuous improvement and the creation of incremental innovation on the shop floor. The knowledge sharing on the shop floor can be observed in:
• Informal communication process to share practices among workers;
• Training of new workers by the most experienced and practical interactions during daily activities;
• Discussion of problems during kaizen events.
Ripamonti and Scaratti (2012) indicate the importance of local knowledge and its evaluation as a way to develop and improve human resources in organizations. Important research questions in this scenario are: “What are the factors for a production system to align People, Processes, and Knowledge?”, “How to assess such factors?”, “What is the importance of these factors in the opinion of production managers and workers?”. Therefore, knowledge sharing is directly related to the dimensions of People, Processes and Knowledge, as well as an integrated approach for the seeking of results by organizations.
According to Nonaka and Peltokorpi (2006) the relationship between knowledge and performance is little known, as well as, how organizations need to be managed to create and share knowledge, in other words, the theme and its application presents high relevance for the Operations Management.
The importance of an assessment process of the KM system is constantly increasing. The relevance of the evaluation process for a learning-based growth strategy stands out as a fundamental point for increasing the competitiveness of organizations (Shirouyehzad, Rafiee and Berjis, 2017; Wang et al., 2015). It is also important to highlight the necessity of regular assessments, not only considering the capacity of the KM system, but also of its reliability and performance (Chen and Fong, 2015; Hesamamiri et al., 2015).
The need for efficient methods to evaluate the performance of the KM system have motivated the development of several studies with different approaches (Wang et al., 2015; Reed et al., 2011). In order to maintain the KM system under good conditions, an appropriate model of performance evaluation, which could be able to show the effects obtained and also enable necessary corrections is demanded (Shirouyehzad, Rafiee and Berjis, 2017; Wang et al., 2015; Lin, Chang and Lin, 2011). The evaluation process must support the KM strategy and must consider the moments and the evolution of the market in which the organizations are inserted, verifying if the KM is able to reach its objectives in any time of such moments (Chen and Fong, 2015). Based on this scenario, different researches and approaches regarding the methods of evaluation can be found in the current literature, considering the system, the performance and other factors related to KM (Buyukozkan, Parlak and Tolga, 2016; Dehghani and Ramsin, 2015). A robust KM system demands an appropriate model of performance assessment, which could be able to show its effects and also enable necessary corrections, being this model of great importance for the KM strategy (Shirouyehzad, Rafiee and Berjis, 2017; Wang et al., 2016; Lin, Chang and Lin, 2011).
The dynamic characteristics of KM make the development of a precise evaluation model, a task of high degree of difficulty and great importance (Wang et al., 2015). In addition, the implementation of evaluation methods efficiently requires a well-integrated KM system (Shirouyehzad, Rafiee and Berjis, 2017).
Al-Busaidi (2013), based on studies considering knowledge workers’ perception, indicated the evaluation of the benefits of Inter-organizational knowledge sharing systems as an opportunity for future studies.
The research fieldwork was based on Action-Research (AR) and the data collecting procedure used a 4-point Likert scale questionnaire and semi-structured interviews to a sample of 55 employees selected from the Toyota 1 (T1) and 22 employees from Toyota 2 (T2) including workers of different operational levels and professional qualification. The applied methodology enabled the employees’ perception capture.
The findings of this study provide an overview of the DNA Toyota implemented in Brazil based on blue collars perspective and an assessment instrument that integrate K, P, W context providing a base for improvement actions. This paper contributes understanding the Toyota DNA presence in a different culture and increase the understanding to support managers’ actions to practical implications. The paper offers a pragmatic guideline on how to assess and develop a favorable context to encourage knowledge conversion processes and its sharing in the organization. These theoretical contributions are aligned with research opportunities indicated in previous researches (Eden, Von Krogh and Monika, 2008; Monika, Von Krogh and Voile, 2006; Nakano, Muniz Jr. and Batista Jr., 2013).
The structure of this work presents in the Chapters 2 and 3 its theoretical basis, which presents the main concepts related to KM Assessment (including the main related factors used in this research) and the Knowledge-based Integrated Production Management Model (K-PMM). The Chapter 4 describes the used research methodology, seeking to detail the sequence adopted in its accomplishment. Subsequently, Chapter 5 develops the record of the observed results and discussion, thus sustaining the purpose of this article and its conclusions, finally presented in chapter 6.

2. Knowledge Management Assessment
KM is considered an emergent topic of study by organizations and the involved scientific community. KM has increased the number of researches addressing the various aspects, concepts, technologies, approaches and practices related to the development processes based on learning and knowledge (Fteimi and Lehner, 2015; Ingvaldsen, 2015). KM studies also consider the impacts in different levels of an organization, which can be evaluated regarding aspects such as technologies for knowledge creation, knowledge sharing, organizational culture, leadership, knowledge architecture and organizational learning (Armaghan and Renaud, 2017; Hesamamiri et al., 2015).
The achievement of the goals which are planned by knowledge-based organizations in defined periods are directly related to changes in organizational infrastructures and also to the good practices of KM (Hesamamiri et al., 2015).
The maturity in KM starts strongly based in technology, being for companies a mean to identify and manage data and information. Subsequently, it goes through stages of dissemination of KM by the company and exploration of the knowledge and the developed management system, where it is also necessary the commitment of the top managers (Kruger; Johnson, 2009). However, the social or sociocultural aspect existent in organizations with knowledge-based environments is also strongly studied, not only considering KM as a process of generation and exchange of data or information, but also as a social process of learning. Personal involvement in a knowledge-based culture is stimulated by the social engagement of individuals, since socialization allows an openness to learning through continuous interaction that promotes the exchange of experiences with others and the direct observation of practices and skills of the experts in the group. This social influence has a direct impact on the development of a communication system, on the behavior and on the individual learning intention, providing a sharing and acquisition of tacit knowledge (Cleveland, 2016; Cleveland and Ellis, 2015; Ingvaldsen, 2015; Reed et al., 2011).
Considering the growth of knowledge economy, the evaluation of KM performance in recent years has become increasingly important, since it promotes strategic organizational learning and generates the capabilities required to meet customer expectations (Shirouyehzad, Rafiee and Berjis, 2017; Shahbudin, Nejati and Amran, 2011; Chen, Huang and Cheng, 2009; Lee, Lee and Kang, 2005). It is necessary for organizations to be able to assess knowledge (Huang, Chen and Yieh, 2007), and the actions of ‘measuring the value of KM’ and ‘evaluating KM performance’ are of great importance to managers and became also an important agenda among researchers and practitioners (Chin, Lo and Leung, 2010; Chen and Chen, 2006). Even considering such importance, KM assessment remain as one of the least developed aspects of KM (Kuah and Wong, 2012).
Muniz (2014) indicate that the barriers to Knowledge Sharing are addressed in a dispersed way in the literature and can be summarized in:
1. Personnel related to the individual and group factors, with their technical skills, motivations, strategies;
2. Technology that consider Information (IT), infrastructures, user accessibility and equipments. They are related to the activities of recording knowledge and information flow;
3. Organization of the Work, approaching the strategies and practices regarding the development of the product, with its methods and activities;
4. External Environment, which involves the relationship with the environment and influence in the context, referent to the face-to-face interaction to exchange tacit knowledge and geographical distance between team members.
Theoretical and empirical works show that knowledge creation can not be separated from the context in which it is created (Erden, von Krogh and Nonaka, 2008; von Krogh, Ichijo and Nonaka, 2001; Gilmour, 2003). Lee and Choi (2003) indicate the need for organizational factors to stimulate and favor the dissemination and sharing of knowledge between projects in order to stimulate specific activities for this purpose.
Knowledge Management Performance Evaluation is often defined as actions, processes or systems for assessing, controlling and monitoring the status of implementation of KM (Kuah and Wong, 2012; Nejati, 2010). The main objective of performance measurement is to improve KM effectiveness, efficiency and adaptability in order to add more value to the overall performance of an organization (Lyu, Zhou and Zhang, 2016; Kuah and Wong, 2012). The KM performance measurement also enables the organization to evaluate, control, and improve its knowledge processes, which will ultimately lead to organizational improvements (Wong et al., 2015; Kuah and Wong, 2011). The evaluation approach aims to 1) review the implemented KM mechanisms and routines, as well as the achieved performance, and 2) predict the performance evolution of KM drivers and results in a future period in order to facilitate the strategic planning (Shirouyehzad, Rafiee and Berjis, 2017; Kan, Guo and Li, 2016; Chen and Fong, 2015).
Lin, Chang and Lin (2011) considered the KM performance assessment, a model with the inclusion of four levels of evaluation, including the levels of knowledge creation, knowledge transfer, knowledge dissemination and knowledge accumulation, also considering factors of performance indication for each one of the four determined levels. Lee, Lee and Kang (2005) also suggested the Knowledge Management Performance Index (KMPI) considering the levels of knowledge creation and accumulation, but including the terms of knowledge sharing, knowledge utilization and knowledge internalization as components used to evaluate KM.
Wong et al. (2015) reinforces a concept of KM Performance Measures, defined as performance variables, which are equivalent to metrics for key attributes and are considered important elements in KM evaluation, categorized into three main themes: knowledge resources, KM processes, and the factors that affect KM. The categorization of KM measures is also related to qualitative evaluation, which assess the human aspects, such as culture, behavior, practice, perception, and experience, or quantitative evaluation, which assess the tangible aspects, such as the number of knowledge workers and number of research and development projects (Kuah and Wong, 2012; Chin, Lo and Leung, 2010; Chen, Huang and Cheng, 2009).
The KM evaluation is important to identify deficiency origins (causes), corrective actions and improvements (Nejati, 2010). Managers can better understand their KM practices, deficiencies or key elements impacting the development goals through an effective process of KM evaluation, which provides evidences for the aimed continuous improvement. The continuous implementations of actions is required in order to maintain the KM system under control, as well as a continuous feeding back and improvement based on the evaluation results, which immediately provides influence on the KM efficiency (Shirouyehzad, Rafiee and Berjis, 2017; Kan, Guo and Li, 2016; Lyu, Zhou and Zhang, 2016).
Kruger and Johnson (2009) consider that the evolution of KM is based on information technology and concludes that different companies have different levels of KM maturity. Nejati (2010) reinforces that KM assessment processes may be different from one organization to another. However, some common challenges and difficulties can be faced in different organizations.
According to Mohamed, Stankosky and Mohamed (2009), an analysis of knowledge may include the determination of the knowledge gap, which represents the difference between the knowledge needed, and the knowledge available for employment, including the necessary skills for the appropriate knowledge use.
Patton (2001) used the KM evaluation process to identify internal lessons learned and best practices. Muniz Jr. et al. (2010) understand that is important to assess factors related to Production, Work and Knowledge in an integrated way, and Mitri (2003) relates tacit assessment depending on intuition, judgment, and feeling.
The literature analyzed applied different KM Assessment Methods as shown in the Table 1. The use of specific and mixed methods can be perceived among the studies exploring KM assessment, highlighting the application of methods such as Likert scales and Fuzzy logics. The Likert scale method (normally used during the process of data collecting) is used and identified in some KM assessment studies as a way to capture the dimension of the interviewees perception about different KM factors, which are understood as important and relevant for the KM performance (Armaghan and Renaud, 2017; Chawla and Saxena, 2016; Chen and Fong, 2015; Dukić, Kozina and Milković, 2015). Different Fuzzy method approaches are identified in the KM assessment studies, normally perceived in research concepts or factors validation, decision making processes and performance improvement (Hesamamiri et al., 2015; Wang et al., 2015; Lin, Chang and Lin, 2011).

Table 1: applied methods for KM assessment (Source: Authors)

Different research approaches relating KM performance assessment are also observed in the literature review. Al-Busaidi (2013), assessed the knowledge workers’ perception regarding Inter-organizational knowledge sharing systems in the health sector combining a Delphi technique and a survey instrument including demographic questions such as gender, age, qualifications, work experience and computer skills.
Chen and Fong (2015), conducted a survey study based on a sample of 143 construction contractors, combining a survey study and system dynamics simulation to evaluate the KM performance and strategy, including factors of learning routine and governance mechanism.
Hesamamiri et al. (2015) used the patterns of socialization, externalization, internalization, and combination as the dimensions of the category or process of creation of knowledge. In addition, using a Bayesian belief networks approach, a framework model for assessing the reliability of KM was proposed, which could help organizations to evaluate their ability to implement KM successfully by identifying key reliability variables. In Appendix A it is possible to verify the main factors evaluated in KM and identified in the literature.
Chawla and Saxena (2016), conducted studies in Indian higher educational institutions, considering a research submitted to 450 respondents of 9 institutions including faculty members and research scholars, in order to determine the reliability and to validate a KM Assessment Instrument through exploratory factor analysis and confirmatory factor analysis.
Wang et al. (2015), proposed a synthetic method using a triangular fuzzy numbers and Group Support Systems to evaluate the KM performance.
Zandi and Tavana (2010) discuss the methods of analysis for strategic investment in KM and proposes a model for the evaluation of such opportunities, which is used to estimate the value of KM strategies. Shirouyehzad, Rafiee and Berjis (2017), in order to identify the organizational KM status and provide solutions or perspectives for decisions, assessed the performance of organizations based on the combination of KM and safety management, considering an applied survey submitted to senior and middle managers from 12 automotive companies under study and using data envelopment analysis.

3. K-PMM – The Knowledge-based Integrated Production Management Model
Muniz Jr., Batista Jr. and Loureiro (2010) detailed that production management models have two dimensions, a human or social dimension represented by the work organization called as the W-dimension and, a technical dimension represented by the production organization, which is the P-dimension. The P and W-dimensions essentially capture the explicit structure and the behavior of the production management system. Such a system has also a tacit structure that is progressively converted into explicit, as it is better understood. Tacit knowledge exists, it is important, and it needs to be formally included in a model of production management system, especially to model shop floor environment relationships.
Many authors have defended that only the explicit knowledge can be managed, captured and kept updated (von Krogh, Ichijo and Nonaka, 2001). However, the same authors indicate that better results can be achieved with the existence of a favorable context, stimulated by actions that are focused on tacit knowledge sharing and people integration, facilitating the new knowledge acquisition. This favorable context is hereafter called as ‘Ba’ (von Krogh, Ichijo and Nonaka, 2001). When the organization formalizes and makes such actions explicit, there is a higher potential for obtaining the ‘Ba’. Figure 1 illustrates the traditional production management models adding a third dimension to them, and reinforcing that these three dimensions must be integrated.

Figure 1: Dimensions for promoting the ‘Ba’ (Muniz Jr., Batista Jr. and Loureiro, 2010)

The Knowledge-Based Integrated Production Management Model (Muniz Jr., Batista Jr. and Loureiro, 2010) is a theoretical model, which is depicted in Figure 2. The K-PMM promotes the integration of W, P and K dimensions because it is formally concerned with the tacit and explicit knowledge conversion modes, incorporating them to the procedures and assessing, by measures, their use in the shop floor knowledge identification and sharing activities.

Figure 2: Knowledge-based integrated production management model (K-PMM) with dimensions and factors (Muniz Jr., Batista Jr. and Loureiro, 2010)

The star involving Production Organization and Work Organization represents the set of defined, controlled and integrated factors for carrying out production management in a way that creates the ‘Ba’. As in the Taylorist and Socio-technical models, the dashed line represents the permeability of the production operations shop floor environment to external factors, such as, market, strategic and technological aspects reflected in production processes.
Knowledge conversion process acknowledges the importance of a tacit knowledge and focuses on the various processes of conversion of such knowledge into explicit and other tacit knowledge and vice-versa (Table 2).

Table 2: Knowledge conversion process – SECI (Adapted from Nonaka, 1994)

The four basic patterns of knowledge conversion, called SECI process, refers to: Socialization (experiences exchange between people), Externalization (registration and formal availability of knowledge for other people), Combination (content explicitly available generating new knowledge) and Internalization (acquisition of knowledge by means already formalized and recorded). The inclusion of the SECI (Socialization, Externalization, Combination and Internalization) conversion process and the knowledge spiral (Nonaka, 1994) formalizes the integration of KM with the traditional production management models highlighting the need for measures and procedures related to results or to the KM factors, establishing a dynamic relationship of cause and effect between such factors and the obtained results.
The K-dimension, as presented in Figure 2, promotes the integration between the P and W-dimensions, because it is formally concerned with the tacit and explicit knowledge conversion modes, incorporating them to the procedures and assessing, by measures, their use in the shop floor knowledge identification and sharing activities. Therefore, K-PMM recognizes the spontaneous and collective knowledge generation process and the workforce flexibility for the operation of shop floor machinery, and for a better communication among the people involved.
Relevant P-factors are the use of the following tools that promote the use of worker knowledge and involvement. The tools contribute for the control and improvement of the daily activities of production workers, which are: Problem Solving Methods (Garvin, 1993); Standard Operating Procedure (Ohno, 1988); 5S (Ohno, 1988); Poka Yoke (Ohno, 1988) and Quick Changeover (Shingo, 1989).
Using the P-factors enhance operators learning by systematically seeking improvement in the production environment. Lean manufacturing and mass production were considered when selecting such factors. In order to promote the ‘Ba’ integrated in the production work routine, the use of P-factors require, not only socialization, externalization and internalization of knowledge (K-factors), but also the implementation and use of the W-factors.
Relevant W-factors are objectives (Smith, 2001), structure, communication (Worley and Doolen, 2006), training (Nonaka, 1994; Darrah, 1995), incentives (Smith, 2001).
The W-factors to promote the ‘Ba’ support the interaction between the operators and the organization, by sharing measurable objectives, by work and communication structure, and by training and incentives. For the selection of these factors, two work organization models were considered: the semi-autonomous models and the enriched model.
The W-factors, adopted in the K-PMM, contribute to organizing people in order to get the best of operators’ knowledge and to obtain better results. They are adequate to the production environment. It is intended, with the use of these factors, to enhance people’s involvement in order to systematically get their organization objectives by the creation, retrieval, share and use of knowledge. The factors consider the needs of the group members when executing their routine and improvement activities, outlining: “who can help to do what?”, material and time resources availability, communication among group members and between the group and the other people in the organization, required training by the various activities, and by the operation of the production machinery and incentives.
Muniz Jr., Batista Jr. and Loureiro (2010) conclude that the theoretical model K-PMM and its factors may influence the ‘Ba’ creation, because they:
• support the socially built knowledge;
• stimulate the cooperation and teamwork;
• emphasize the importance of transferring and transforming knowledge from personal to organizational and from tacit to explicit;
• stimulate interactive work on problems (try and error) as a learning process;
• suggest that a production management model for promoting the ‘Ba’ in shop floor workers should have the three W, P and K integrated dimensions as proposed in the K-PMM and its factors.

4. Methodology strategy
Guided by Nakano and Muniz Jr. (2018) we grounded a comprehensive literature background using "Knowledge Management" AND topics a) Assessment, b) Evaluation or c) Performance, in the Title. We analyzed 20 papers selected by relevance from ISI Web of Science (period of 2001-2017) as shown in the Appendix B.
The research fieldwork was based on Action-Research (Coughlan and Coughlan, 2002). The AR was applied in 2 Brazilian plants from Toyota group as strategy to describe an unfolding series of actions over time; understanding the employees of each plant, identifying how and why their action and perceptions change or improve the working of some aspects of an operational system; and understanding the connection about Work, Production and Knowledge Organization to support process of change or improvement in order to learn from it. Specifically, AR was selected considering as a main reason the fact that AR always involves two goals. This research is aligned with academic and organizational aspects, which is aligned to contribute to:
• practical implication, which is diagnostic of the W, P, K factors;
• theoretical implication, which is aligned with research gaps raised on the literature analyzed.

4.1 Plants researched
Automotive companies provide a revolution in the Brazilian way to deal with suppliers, to develop products and to apply the Toyota Production System in the productive process (Salerno et al., 2010). Brazil has its own cultural aspect. Also, the automotive industry is considered a "microcosm", where the characteristics of the Organization of Production and Work Organization in general are "crystallized" and can be observed (Biazzo and Panizzollo, 2000).
Brazilian industry has seen an evolution of units produced. Brazilian automotive industry represents a significant economic sector and its production growth trend has been higher than the industry in general (IBGE, 2018).
Brazil is one of the 10 largest care manufacturers in the world, with some 2,16 million vehicles produced in 2016 (OICA, 2017) and the automotive industry therefore represents a significant Brazilian economic sector. The major global automotive brands are located in Southeastern Brazil, including Ford, GM, VW, Toyota, Hyundai, Fiat, Land Rover, Nissan, PSA Citroen (including Peugeot), Cherry, Honda, Scania, MAN and Mercedes Benz) and South (VW Audi, Renault, Nissan, BMW, Volvo, Agrale). More recently, plants have also been set up in the Northeast by companies such as Ford, Jeep, JAC and Troller. The Brazilian automotive industry has undergone a significant transformation in relations with suppliers, relocating production activities, engineering and product development, work and production organization in recent years and there is evidence that firms are beginning to implement some of the Toyota production system principles, though with varying success.
The growth of Toyota Production System principles in Brazil raises issues about their applicability within a distinctive cultural context that is very different to Japan. Success in sustaining Lean is determined to a large extent by the hybridization (Liker, Fruin, and Adler, 1999) of where it is being implemented. In other words, the implementation of Lean may require different strategies which to some extent adapt to the local culture of the host country.
The new configuration of the Brazilian automotive chain has undergone a significant transformation in relations with suppliers, locating production activities in the area of engineering and product development, and also in the organization of productive processes, manifesting itself as an internal restructuring of the various areas of the organization (Zilbovicius, Marx and Salerno, 2002). This scenario also generates undesirable results, such as loss of focus, redundancies, interdepartmental conflicts, waste of resources (time, financial and personnel) and even layoffs, not contributing to the creation of a favorable context for production and people.
The selection of the plants to be studied is based on theoretical aspects, on the selection of a limited number of ‘polar’ cases, in which the process of interest is “transparently observable”, to get a balance between research complexity and data volume (Eisenhardt, 1989). Plants selection was also based on the following criteria: pure DNA Toyota representatives, also considering that the plants belong to two different business units from the Toyota group, whose headquarters are in Japan, ‘polar’ production models (lean manufacturing) and work organization models (enriched autonomous groups), autoparts makers; medium to small size; belonging to the same region of Paraiba Valley (one of the most developed industrial areas in Brazil) in São Paulo state in Brazil. The researched plants T1 (Toyota 1) and T2 (Toyota 2) are auto-parts manufacturers from the Toyota group and are both detailed described in the profile presented in Table 3.

Table 3: Profile of the studied plants (Source: Authors)

The research was conducted considering a sample of 55 employees selected from T1 and 22 employees from T2, including workers of different operational levels and professional qualification. The T1 group was composed by operators (61.8%), senior operators (10.9%), assemblers (21.8%) and leaders (5.5%) while the second group (T2) was integrated by operators (68.2%), senior operators (13.6%) and assemblers (18.2%). The most part of employees (69.1% in T1 and 40.9% in T2) was identified in the educational level of completed high school. This sample was defined considering the strong relation of the employees with routines such as acquisition, use and sharing of knowledge, also taking into account the KM relevance for such routine. Thus, the perception of these employees in relation to the KM system implemented can offer a KM performance base of measurement. Appendix C presents the complete interviewees’ profile. The interviewees’ sample was no probabilistic.

4.2 Field work stages
The following field work stages wore considered during this work:
Stage A - The assessment Instrument Built, validated by Muniz Jr., Nakano and Batista Jr. (2012), aims to map the Work, Production and Knowledge factors related to the production system. The factors integrating the instrument were selected and confirmed considering the previous validation as well as the current relevance confirmed during the literature review conducted in this work, enabling to build the assessment instrument (closed questionnaire) based on these W, P, K factors. Specifically, it is indicated by the following steps:
A.1 Understanding the production system characteristics: This step provides the "immersion" of a researcher in the shop floor routine, familiarization with production systems and personal relationship with the workers by following their activities in the daily routine during the different shifts;
A.2 Conducting the interviews: the researcher conduct semi-structured interviews with the workers of the production system. The workers are selected following a convenience sampling method. The researcher interviews workers in their different shifts, asking about the factors that contribute to the creation of the favorable context (Ba) to knowledge sharing. Managers are also listened in order to reinforce the level of importance given by the companies to the studied factors, providing support for future analysis and conclusion;
A.3 Transcription and Validation of the interviews content: it is a copy of the written record content that is returned to the interviewees for their validation;
A.4 Factors Mapping: It means a classification of the production system factors based on the answers content analysis (Bardin, 2008);
A.5 Instruments Construction and Validation: the construction of the closed questionnaire (research instrument) is based on the worker perceptions about: (i) "importance" given to each mapped factors and (ii) "attention given by the manager" to its factors. The questions are part of the research protocol and use the 4-point Likert-scale, and exampled as follow. The protocol should be validated by the managers.

Stage B – The Application of Assessment Instrument starts with planning and ends with the application of the instrument for the production system workers, including the following steps:
B.1 Application planning: it means the definition of pre-test instrument for the research instrument revision and consolidation and selection of a pilot-area for final questionnaire application. Also, the application operational aspects are discussed as for the “who, when, how...”;
B.2 Pre-test Application: it means the instrument application for a small sample of members of the pilot-area. The application in the pilot-area should be made in the shift following the pre-test, in order to prevent the questions sharing among other workers before the final application;
B.3 Instrument Application in the “Pilot-Area”: It means the instrument application in the pilot line for all workers directly involved in this area.

Stage C – Results Analyze and Selection of priority factors is the processing and tabulation of data collected through the instrument application in a graphic form:
C.1 Data Processing: consists of the graphs construction for presentation and description of the results obtained with the Assessment Instrument;
C.2 Workers Feedback: it is performed through feedback meetings to share the collected data from all respondents;
C.3 Management Analysis and Selection of the Priority Factors: it is the results discussion with the managers and members of the area. It also aims to identify the top priority factors for further analysis and suggested actions.

Stage D - Focus Group Meeting provides results discussions with a sample of pilot-area workers with different roles and from different shifts:
D.1 Selection of Focus Group participants: it is a selection of the main Pilot-Area representatives, which includes the Area Leader and the Human Resources (HR) representative;
D.2 Meetings to discuss the factors priority among the representatives of the Pilot-Area workers, the HR analyst, and it is conducted by the Leader of the group, aiming to raise elements for developing an action plan for the raised problems and opportunities.

Stage E – The Meetings Results Analysis is conducted by the group leader and provides the consolidation of the focus group meetings members of a preliminary action plan;

Stage F – The Management Analysis for Defining Integrated Action Plan aims to review the preliminary plan for obtaining resources and managerial support;

Stage G – Action Plan Control is to monitor and control the actions decided upon by the management based on the focus groups demands, which contributes to an alignment of both, and the results can be reviewed with a periodic reapplication of the instrument developed for the production system.

The annual application report of the instrument as a means of evaluating progress and identifying new opportunities or actions related to other factors is demanded. It is estimated a period of 16 weeks between the application instrument (Step B) and Management Analysis for Defining Integrated Action Plan (Step F).

4.3 Focus Group
The data collecting procedure used was semi-structured interviews with opened questions. An objective questionnaire, applied to the employees, was developed with 48 questions distributed in 24 promoting factors related to work, production and knowledge organization. In this way, each factor was described containing 2 questions, considering 1 question aimed to obtain the level of importance that the employee attributes to the analyzed factor and 1 question aimed to obtain the employee perception regarding the attention that the company gives to the factor (level of importance given by the company). Each question was dimensioned and distributed in a 4-point Likert scale, considering the score of 0 (zero) for "Not important" response, 1 for "Little importat", 2 for "Important" and 3 for "Very important", for 24 questions aimed to obtaining the level of importance that the employee attributes to the factor. In the same way, the questions aimed to obtaining the employee's perception of the factor in the company were scored in 0 (zero) for "Any attention" response, 1 for "Little attention", 2 for "Reasonable attention" and 3 for "Very attention". The complete questionnaire and results will be presented in Section 5 (See Tables 5, 6 and 7).
The Construction and Validation of the instrument and the assessment process were conducted by plants members and academic researchers, which followed research protocols, validated with managers and director of the production systems studied.

5. Results and Discussion
The interviewees considered the most factors related to people (Work Factors) as important (Very important and Important) and they judged that the companies give attention for these factors in regular basis, offering the support production control action by operators to achieve quality and productivity. This evidence indicates that the Brazilian culture do not influence changes in the Toyota work context. The most interviewed employees were identified in the condition of first industrial job experience and very well trained, which contribute for the good relation observed.
The organizational Work system was positively evaluated, but some points of attention were identified. In T2, the communication between professionals of a production line with others and the communication between production professionals with people in the support areas (maintenance, tooling, quality, PCP) were considered important (Very important and Important) for the production performance according to employees’ perception, however, such factors were not unanimously perceived in the company, taking into account that 50% of employees consider that the company gives attention (very attention or reasonable attention given) to the factor, but 50% consider that the attention is not appropriately given (little attention or any attention given), in other words, the importance given by the company to such practices is not completely perceived by part of the work team, even considering its relevance. This condition demands a preventive in-depth analysis and actions implementation, since the communication practices can be fragile implemented in the production routine or not appropriately understood by employees. A practice considered important but not perceived can negatively affect employees’ motivation and performance in general.
The employees in T2 also presented a different view when dimensioning the perception regarding the attention given by the company to the person’s relationship between production professionals (includes the trust transmitted by individuals). In the same way, 50% of employees consider that the company gives attention (very attention or reasonable attention given) to the factor, but 50% consider that the attention is not appropriately given (little attention or any attention given). However, it is important to observe that this practice was considered as strongly important by employees (considered as Very Important by 81.8% of respondents). This scenario requires more effective efforts on actions able to generate a robust practice implementation and perception in the organization.
Other factors and practices were in general considered relevant (defined as Very important and Important) for the work organization and perceived in both companies. The practices related to factors of ‘Resource’ (time availability), ‘Incentive’ and ‘Personal Characteristics’ were more strongly identified as important in T1, but equally satisfactory perceived in both companies. Other practices related to factors such as ‘Roles and Responsibilities’ (leader) and ‘Resources’ (materials and equipment) were more strongly identified as important in T2, but also equally satisfactory perceived in both companies. A complete overview of the results, including the attributed level of importance and perceptions regarding the work organization are presented in Table 4.

Table 4: Question results for Work Organization promoting factors (Source: Authors)

Analyzing the factors related to the management of physical resources used in the production process (Production Factors), which result in services and goods, it is possible to identify an alignment among the interviewees of both companies. In general, all practices were judged as important (Very important and Important) and perceived in regular bases in the companies. The results reinforce the existence of a good support given by the companies, which provides a favorable environment for the TPS culture propagation.
Some Production practices related to factors, such as ‘Quick Changeover’ (SMED) and ‘Poka-yoke’ were more strongly identified as important in T2, but equally satisfactory perceived in both companies (Poka-yoke also more strongly perceived in T2). The practice related to ‘Standard Operation Procedures’ was more strongly identified as important in T1, while the practice related to “Problems Solution Method’ was more strongly perceived in T1. The complete overview of the results for Production Organization is presented in Table 5.

Table 5: Question results for Production Organization promoting factors (Source: Authors)

The practices related to the four patterns of knowledge conversion (SECI) were judged as important (Very important and Important) in both companies and perceived in regular bases, presenting the existence of a favourable context to promote knowledge sharing in the shop floor environment. It is important to highlight in this aspect, the more strongly importance given by T1 employees to the practices related to ‘Externalization’ and ‘Internalization’, while the T2 employees defined the ‘Socialization’ factor as more relevant and the ‘Combination’ factor as the more strongly perceived in. The complete results for KM factors are presented in Table 6.

Table 6: Question results for KM promoting factors (Source: Authors)

5.1 Practical Implications
The knowledge-based industrial assessment method (K-IAM) support managers to analyze and implement appropriate actions, which could maintain and improve the KM system.
The Figure 4 illustrates the four possible scenarios observed in the K-IAM application. The K-IAM may evidence some variation about the worker and manager alignment:
a) Scenario 1 - Worker and Manager consider the factor as important, but both DO NOT "perceive attention" of the company regarding such factor. Therefore, the scenario REQUIRES special management attention;
b) Scenario 2 - Both DO NOT consider the factor as important factor. Both "perceive attention" of the company regarding the factor, therefore, a management analysis is necessary;
c) Scenario 3 - Both consider the factor as important and realize the company's attention; or both DO NOT consider the factor as important and DO NOT realize the company's attention. Therefore, it needs little management attention.
d) Scenario 4 - There is misalignment between both, worker and manager. Therefore, management needs attention.

Figure 4: The K-IAM possible scenarios (Muniz Jr., Nakano and Batista Jr., 2012)

The results observed presents in general a positive relation, considering the importance given by workers to the W, P, K factors and the perception of the factor into the companies, which demonstrate the importance and support given by the companies on the studied aspects. This scenario provides the situation observed in the Figure 4(c), which requires little management attention. The positive relation reinforces the Toyota DNA presence, evidencing that Brazilian culture does not interfere on the appropriate TPS implementation. In addition, the positive relation provides a mechanism able to integrate People, Processes, and Knowledge in the production environment.

6. Conclusion
Based on a strong and comprehensive literature base about operations management and knowledge sharing, we demonstrated in this work, by means of an Action-Research orientation, a valued case of KM assessment instrument application. The instrument, as well as the applied methodology was delineated considering the premises of the Knowledge-based Integrated Production Management Model and aimed to assess the Work, Production and Knowledge organization of the two studied Brazilian plants from the Toyota group as an integrated approach influencing the knowledge sharing among employees (blue-collar workers) and the performance on the shop floor.
An identification of factors able to integrate People, Processes, and Knowledge in the production environment can be observed in this paper, considering the relevance pointed to such factors by means of the conducted literature review and the application results observed in this work. The employee’s perception as well as the companies observed performance can support the capacity of the studied factors (appropriately listed in Tables 5/6/7) to integrate the W, P, K.
A robust view of KM companies’ performance was also obtained, supporting the knowledge-based industrial assessment method conducted in this work as an appropriate way to assess such W, P, K factors.
The results evidence that employees judge the factors related to people (Work Factors) as important. They also considered a relation among knowledge and lean techniques and judged that the plants are aligned with this, also contributing to understand the importance given by its managers to the W, P, K factors. The data indicates that the Brazilian culture does not influence changes in the Toyota work context and the results also provide an overview of the Toyota DNA implemented in Brazil, which supports the improvement actions.
The findings and assessment instrument support evidence to create a favourable context to promote knowledge sharing through the shop floor context and this paper also contributes understanding the Toyota DNA presence in a different culture and increase the understanding to support managers’ actions to practical implications.
This study was limited to assess Work, Production and Knowledge organization in the shop floor context and involving the blue-collar workers perception of two Brazilian plants from the Toyota group. The proposed approach is also able to be applied in other departments or organizations, even considering different cultures, worker groups or production sectors.


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Appendix A: KM factors commonly assessed

Appendix B: Analyzed Articles

Appendix C: Employees profile

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