Favourable context to worker knowledge sharing - Human Resources aspects in Modular Consortium

Résumé:

1. PURPOSE
This research project aims to analyse worker knowledge sharing in complex systems through factors related to Human Resources.
Complexity in the automotive industry relates to unpredictable results, full of uncertainty, and composed of many parts with difficult to characterize relations (Efthymiou et al., 2012). Operational complexity does have effect on the high-content information required for correct manual assembly. A number of decisions are delegated to operators, i.e. relative direction of assembling (backward, forward, etc.) or the screw tightening intensity (El Maraghy, Kuzgunkayaa, & Urbanic, 2005).
Knowledge sharing (KS) supports social decision-making (Gentner et al., 2009), actions relevant to production systems and organizational effectiveness, and is influenced by interpersonal, individual and cultural characteristics (Wang; Noe, 2010) besides organizational factors (Tohidinia and Mosakhani, 2010).
Promoting KS has become increasingly important nowadays as organizations aspire to be more flexible, innovative and sustainable (Wong and Aspinwall, 2004; Chang and Lin, 2015).
However, despite the growing recognition of the factors that drive knowledge sharing in organizations, our understanding about specific challenges found in production contexts is relatively limited. While the Knowledge sharing is still treated rather implicitly in traditional models of production management, and it still lacks attention about it relationship with blue-collar workers (Muniz et al., 2010). Nakano, Muniz Jr.; Batista Jr. (2013) indicate these perspectives in their model to engage blue-collar workers and Weick and Roberts (1993) explore similar effects in a ‘‘heedful environment’’.
The study contributes to a better understanding of how knowledge, human resources and production-related factors interplay to influence the process of knowledge sharing in operations management and it has relevant practical implications.

2. METHODOLOGY DESIGN
The internship will facilitate discussion of two research points. Firstly, existing data from multinational companies working in the Consortium Modular in Brazil and secondly, expanded scope for future research, including other Human Resource perspectives (such as trust, safety behaviour and employee training and development) and cover other industrial sectors such as aerospace. For the first research avenue (analysis of Brazilian data), the following provides a brief outline.
3.1 Conceptualization. We first conducted a comprehensive literature review on knowledge sharing based on the published studies from ISI Web of Science.
3.2 Fieldwork. The questionnaire (Appendix A) was designed using the Incomplete Pairwise Comparisons (IPC) approach (Harker, 1987) based on AHP. It allowed the respondents to assess multiple key factors in hierarchical decision-making process by using 5 points Likert scale (Saaty, 2008). The factors are related KS, HR and OM.
Data available was collected with Workers, Middle and plant managers (144 professionals) of Brazilian automotive plants. The data was collected within the Modular Consortium (MC), a unique production concept, located in Brazil. MC produces vehicles in high-volume/high variety; works with 6 multinational suppliers, which interact directly on the assembly line, sharing physical space, responsibilities, and quality control.
The Modular Consortium belongs to MAN Latin America - Volkswagen Group. MAN is responsible for project development and indirect activities, but it participates with no direct employee in the commercial vehicle assembly line (trucks and bus chassis). The assembly process is divided into seven modules managed by multinational suppliers. The responsibility of each module is the management of direct activities required for delivery and assembly of pre-assembly parts of the final product.
The wide coverage of sampling allowed us to generate a landscape of knowledge sharing practices among the workers. We adopted a convenience sampling approach.

3. FINDINGS
Workers and leaders emphasize conversation among them (Socialization) based standards operating procedures as important point and managers and coordinators give less prominence to this point. Snowden (2002) indicates that Knowledge Management is an extension of Taylorism. Even today, the nature of work on assembly lines and the rationalization of manual labor receive less attention than that given for machinery and automation (Ingvaldsen, 2015).
The real appreciation of the Socialization between blue and white collars still represents an opportunity for process improvement. Socialization is not treated in a systemic way as Internalization, which is explicit responsibility of the managers.
In fact, it is sought to make explicit the use of the Knowledge theme, based on the integration of Knowledge, People and Production factors. A better understanding of this integration will contribute to the promotion of a favorable context for the creation and sharing of knowledge by the people of the working environment, fostering incremental innovation, broadening the field of vision of the production manager for decision making and seeking competitiveness.

4. PRACTICAL IMPLICATIONS
This paper clarifies the scope of managerial actions that impact knowledge sharing among blue-collar workers.

REFERENCES
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Harker, P. T. Incomplete pairwise comparissons in the analytic hierarchy process, Mathl Modelling, v. 9, n. 11, p. 837 – 848, 1987.
Muniz Jr., J., Batista Jr., E. D.; Loureiro, G. (2010), “Knowledge-based integrated Production Management Model applied to automotive companies”, Int. J. Knowledge Management Studies, v. 4, n. 3, 2010a, p. 301–318, 2010a.
Nakano, D. N.; Muniz Jr., J.; Batista Jr., E. D. Engaging Environments: Tacit Knowledge sharing on the shop floor. J. of Knowledge Management, v. 17, p. 290-306, 2013.
Saaty, T. Decision Making with the Analytic Hierarchy Process. Int. J. Services Sciences, v.1, n.1, p.83-98, 2008.
Tohidinia, Z.; Mosakhani, M. Knowledge sharing behaviour and its predictors. Industrial Management & Data Systems, v. 110, n. 4, p. 611 – 631, 2010.
Wang, S.; Noe, R. A. Knowledge sharing: a review and directions for future research. Human Resource Management Review, v. 20, p. 115–131, 2010.
Weick, K.E. and Roberts, K.H. Collective mind in organizations: heedful interrelating on flight decks. Adm. Science Quarterly, v. 38, pp. 357-81, 1993.
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