Yabancı Dil Öğretiminde Temel İlkeler

Os resultados encontrados neste trabalho se aplicam ao escopo de equipes de projetos, onde, conforme citado anteriormente, a interação entre os indivíduos é fundamental para o sucesso do projeto. Algumas oportunidades de evolução de alguns temas e ampliação deste escopo foram identificadas ao longo deste trabalho, podendo ser tratadas em futuros estudos, conforme discutido a seguir:

Primeiro, a amostra de dados utilizada neste trabalho é limitada ao setor de automação industrial e a uma empresa, o que pode ter gerado algum viés nos resultados. Portanto, futuras

pesquisas podem ser aplicadas em outros setores, de forma a complementar e verificar os resultados encontrados neste trabalho.

Segundo, como citado na revisão de literatura, este trabalho avalia os fatores que influenciam o compartilhamento de conhecimento, mas não controla por tipo de conhecimento (explícito e tácito). Então, tem-se a oportunidade em futuras pesquisas de avaliar o quanto o compartilhamento destes dois tipos específicos de conhecimento (CHOW, 2012; KOSKINEN; PIHLANTO; VANHARANTA, 2003), é condicionado por cada variável (intensidade relacional, apoio do gestor e estrutura da rede de relacionamentos) considerada no modelo desenvolvido.

Terceiro, a complexidade de cada projeto e a etapa em que se encontravam no momento da coleta de dados, são fatores que também podem influenciar o compartilhamento de conhecimento, e que devem por isso ser considerados em uma futura análise.

Quarto, dada a importância de se buscar informações fora da equipe de projeto e evitar a existência de buracos estruturais locais na equipe, podem ser avaliadas em um próximo trabalho as variáveis de perspectiva de fechamento (closure) e de buracos estruturais (structural holes) na rede, complementando os resultados e avaliando a influência das mesmas no compartilhamento de conhecimento (REAGANS; ZUCKERMAN, 2001).

Quinto, o nível de intensidade da relação entre os indivíduos nos projetos, que representa a proximidade (intimidade) entre os indivíduos, assim como os laços informais, não foram considerados neste trabalho. Estas dimensões podem ser exploradas em um próximo estudo, a fim de verificar quais os tipos de laços (formais ou informais, e fortes ou fracos) que mais influenciam o compartilhamento de conhecimento.

Por último, como discutido neste trabalho, uma rede social de relacionamento ampla é importante para o compartilhamento de conhecimento. Porém, vale ressaltar que relacionamentos implicam custos, como por exemplo, o custo do tempo em manter os relacionamentos ativos (JIN; GIRVAN; NEWMAN, 2001). Portanto, os indivíduos têm um limite do número de contatos na rede (JIN; GIRVAN; NEWMAN, 2001), o que reflete bem o dia-a-dia de equipes de projetos. As equipes de projetos estão limitadas a um escopo com prazo e total de horas de dedicação definidos, portanto a seleção dos contatos deve ser feita com muito critério, a fim de evitar redundância de contatos e desperdício de tempo (LAUMANN; MARSDEN, 1982). Então, esta é uma oportunidade em novos estudos de explorar de forma mais aprofundada a efetividade do tamanho da rede e suas restrições, pois de acordo com Borgatti, Jones e Everett (1998), “quanto mais diferente forem as regiões em

que um ator tem laços, maior é o potencial de informações e controle dos benefícios”, além

REFERÊNCIAS

AFUAH, Allan. Are network effects really all about size? The role of structure and conduct. Strategic Management Journal, v. 37, n.3, p. 257–273, 2013.

AHUJA, Gautam. Collaboration networks, structural holes, and innovation: a longitudinal study. Administrative Science Quarterly, v. 45, n. 3, p. 425, 2000.

AL-ADAILEH, Raid M. The impact of organizational culture on knowledge sharing : the context of Jordan’s phosphate mines company. International Research Journal of Finance and Economics, v. 63, p. 226-229, 2011.

AL-ALAWI, Adel I.; AL-MARZOOQI, Nayla Y.; MOHAMMED, Yasmeen F. Organizational culture and knowledge sharing: critical success factors. Journal of Knowledge Management, v. 11, n. 2, p. 22–42, 2007.

ALLEN, Thomas et al. Project team aging and performance: The roles of project and functional managers. R&D Management, v. 18, n. 4, p. 295-308, 1988.

AMMETER, Anthony P.; DUKERICH, Janete M. Leadership, team building, and team member characteristics in high performance project teams. Engineering Management Journal, v. 14, n. 4, p. 3–11, 2002.

ANDERSON, W. T. Jr.; ALPERT, Mark I. Optimal heterophily: aid to effective communication. Public Personnel Management, v.3, p. 279-288, 1974.

BARROSO, Lúcia P.; ARTES, Rinaldo. Tópicos de análise multivariada. São Paulo: 2013. n.1- 218.

BOATH, David; SMITH, David Y. When your best people leave, will their knowledge leave, too. Harvard Management Update, v. 9, n. 9, p. 6–8, 2004.

BORGATTI, Stephen P.; JONES, Candace; EVERETT, Martin G. Network measures of social capital. Connections, v. 21, n. 2, p. 27–36, 1998.

BUNDERSON, J. Stuart; SUTCLIFFE, Kathleen M. Comparing alternative

conceptualizations of functional diversity in management teams: process and performance effects. Academy of Management Journal, v. 45, n. 734, p. 875–893, 2002.

CABRERA, Angel; CABRERA, Elizabeth F. Knowledge-sharing dilemmas. Organization Studies, v. 23, n. 5, p. 687–710, 2002.

CABRERA, Ángel; COLLINS, William C.; SALGADO, Jesús F. Determinants of individual engagement in knowledge sharing. The International Journal of Human Resource

Management, v. 17, n. 2, p. 245–264, 2006.

CHEN, Chung-Jen; HUANG, Jing-Wen. Strategic human resource practices and innovation performance — The mediating role of knowledge management capacity. Journal of Business Research, v. 62, n. 1, p. 104–114, 2009.

CHEUNG, Sai On; WONG, Peter S. P.; LAM, Anna L. An investigation of the relationship between organizational culture and the performance of construction organizations. Journal of Business Economics and Management, v. 13, n. 4, p. 688–704, 2012.

CHIANG, Yen-Sheng; TAKAHASHI, Nobuyuki. Network homophily and the evolution of the pay-it-forward reciprocity. PloS One, v. 6, n. 12, p. e29188, 2011.

CHOW, Irene H. The role of social network and collaborative culture in knowledge sharing and performance relations. SAM Advanced Management Journal, p.24-37, 2012.

COHEN, Susan G.; BAILEY, Diane E. What makes teams work: group effectiveness research from the shop floor to the executive suite. Journal of management, v. 23, n. 3, p. 239–290, 1997.

CONNELLY, Catherine E.; KELLOWAY, E. K. Predictors of employees’ perceptions of knowledge sharing cultures. Leadership & Organization Development Journal, v. 24, n. 5, p. 294–301, 2003.

COOK, R. Dennis; WEISBERG, Sanford. Diagnostics for heteroscedasticity in regression. Biometrika, v. 70, n. 1, p. 1-10, 1983.

CRONBACH, Lee J. Coefficient alpha and the internal structure of testes. Psychometrika, v. 16, n. 3, p. 297–334, 1951.

CROSS, Rob; BORGATTI, Stephen P.; PARKER, Andrew. Making invisible work visible: using social network analysis to support strategic collaboration. California Management Review, v. 44, n. 2, p. 25-46, 2002.

D’ANDREA, Alessia; FERRI, Fernando; GRIFONI, Patrizia. An overview of methods for virtual social networks analysis. In: D’ANDREA, Alessia; FERRI, Fernando; GRIFONI, Patrizia. Computational Social Network Analysis: trends, tools and research advances. 2010. Cap.1, p.3-25.

DING, Zhikun; NG, Fungfai. Personal construct-based factors affecting interpersonal. Journal of Construction Engineering and Management, v. 136, n. 2, p. 227–334, 2010.

DOLEV, Shlomi; ELOVICI, Yuval; PUZIS, Rami. Routing betweenness centrality. Journal of the ACM, v. 57, n. 4, p. 1–27, 2010.

DUIJN, Marijtje A. J. V.; VERMUNT, Jeroen K. What is special about social network analysis? Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, v. 2, n.1, p. 2–6, 2006.

EVERETT, Martin; BORGATTI, Stephen P. Ego network betweenness. Social networks, v. 27, n.1, p. 31–38, 2005.

FONG, Patrick S. W.; LUNG, Bobby W. C. Interorganizational teamwork in the construction industry. Journal of Construction Engineering and Management, v. 133, n. 2, p. 157–168, 2007.

FREEMAN, Linton C. Centered graphs and the structure of ego networks. Mathematical Social Sciences, v. 3, n.3, p. 291–304, 1982.

HAIR, Joseph F. et al. Multivariate data analysis. 5 ed. New Jersey: Prentice Hall, 1998.

HANNEMAN, Robert A.; RIDDLE, Mark. Introduction to social network methods. University of California, Riverside, CA. 2005. Disponível em:

<http://faculty.ucr.edu/~hanneman/>. Acesso em: 28 Apr. 2014.

HANSEN, Morten T.; MORS, Marie L.; LØVAS, BJØRN. Knowledge sharing in organizations: Multiple networks, multiple phases. Academy of Management Journal, v. 48, n. 5, p. 776–793, 2005.

HELLERSTEDT, Karin; ALDRICH, Howard E. The impact of initial team composition and performance on team dynamics and survival. Academy of Management Journal, v. 33, n. 2, p. 334–365, 2008.

HENNEBERG, Sthephan C. et al. The network researchers’ network: a social network analysis of the IMP Group 1984-2006. The IMP Journal, v. 3, n. 1, p. 28–49, 2009.

HILL, R. A.; DUNBAR, R. I. M. Social network size in humans. Human Nature, v. 14, n. 1, p. 53–72, 2003.

HOFSTEDE, Geert et al. Measuring organizational cultures: a qualitative and quantitative study across twenty cases. Administrative Science Quarterly, v. 35, p. 286–316, 1990.

IOANA, Rus; LINDVALL, Mikael; SINHA, Sachin S. Knowledge management in software engineering. IEEE software, v. 19, n. 3, p. 26-38, 2002.

JALAL, Hayati A.; TOULSON, Paul; TWEED, David. Exploring employee perceptions of the relationships among knowledge sharing capability , organisational culture and knowledge sharing success : their implications for HRM practice. In: PROCEEDINGS OF THE

INTERNATIONAL CONFERENCE ON INTELLECTUAL CAPITAL, KNOWLEDGE SHARING & ORGANIZATIONAL LEARNING. Exploring employee perceptions of the relationships among knowledge sharing capability , organisational culture and

knowledge sharing success : their implications for HRM practice. 2010, p. 639–647. JIN, Emily M.; GIRVAN, Michelle; NEWMAN, Mark EJ. The structure of growing social networks. Physical Review E, v. 64, n. 4, p. 046132, 2001.

JONES, Gareth R.; GEORGE, Jennifer M. The experience and evolution of trust: implications for cooperation and teamwork. The Academy of Management Review, v. 23, n. 3, p. 531, 1998.

KAY, Judy et al. Intelligent Tutoring Systems: The big five and visualisations of team work activity. In: 8th International Conference. 2006, Jhongli, Taiwan. Intelligent Tutoring Systems: The big five and visualisations of team work activity. Springer Berlin Heidelberg, 2006, p. 197–206.

KOSKINEN, Kaj U.; PIHLANTO, Pekka; VANHARANTA, Hannu. Tacit knowledge acquisition and sharing in a project work context. International Journal of Project Management., v. 21, n. 4, p. 281–290, 2003.

KRACKHARDT, David; STERN, Robert N. Informal networks and organizational crises: an experimental simulation. Social Psychology Quarterly, v. 51, n. 2, p. 123–140, 1988.

LAUMANN, Edward O.; MARSDEN, Peter V. Microstructural analysis in interorganizational systems. Social Networks, v. 4, n. 4, p. 329–348, 1982.

LEWIS, Kyle. Knowledge and performance in knowledge-worker teams: a longitudinal study of transactive memory systems. Management Science, v. 50, n. 11, p. 1519–1533, 2004.

LI, Stan Xi. et al. Where do social ties come from: institutional framework and governmental tie distribution among chinese managers. Management and Organization Review, v. 7, n. 1, p. 97–124, 2011.

LIAO, Kaiji; XIONG, Huihui. Study on knowledge sharing of community of practice based on social network perspective. iBusiness, v. 03, n. 03, p. 283–286, 2011.

LIN, Hsiu-Fen. Effects of extrinsic and intrinsic motivation on employee knowledge sharing intentions. Journal of Information Science, v. 33, n. 2, p. 135–149, 2007.

LIU, Yuwen; KELLER, Robert T.; SHIH, Hsi-An. The impact of team-member exchange, differentiation, team commitment, and knowledge sharing on R&D project team performance. R&D Management, v. 41, n. 3, p. 274–287, 2011.

LU, Lin; LEUNG, Kwok; KOCH, Pamela T. Managerial knowledge sharing: The role of individual, interpersonal, and organizational factors. Management and Organization Review, v. 2, n. 1, p. 15–41, 2006.

MAAS, Cora J. M.; HOX, Joop J. Robustness issues in multilevel regression analysis. Statistica Neerlandica, v. 58, n. 2, p. 127–137, 2004.

MARTIN, Angélique; JACOB, Céline; GUÉGUEN, Nicolas. Similarity facilitates

relationships on social networks: a field experiment on facebook. Psychological Reports: Relationships & Communications., v. 113, n. 1, p. 217–220, 2013.

MCNEISH, Joanne; MANN, Inder J. S. Knowledge sharing and trust in organizations. IUP Journal of Knowledge Management, v. 8 n. 1e2, p. 18–39, 2010.

MCPHERSON, Miller; SMITH-LOVIN, Lynn; COOK, James M. Birds of a feather : homophily in social networks. Annual Review of Sociology, v. 27, n. 5, p. 415–444, 2014.

MILLIKEN, Frances J.; MARTINS, Luis L. Searching for common threads: understanding the multiple effects of diversity in organizational groups. The Academy of Management Review, v. 21, n. 2, p. 402, 1996.

MORRISON, Donald F. Multivariate statistical methods. 3 ed. New York: Chapman & Hall / CRC, 2004.

NONAKA, Ikujiro; TOYAMA, Ryoko; KONNO, Noboru. SECI, Ba and leadership: a unified model of dynamic knowledge creation. Knowledge Management: Critical Perspectives on Business and Management, v. 2, p. 5-34, 2005.

PAJARES, Frank. Self-efficacy in academic settings. In: Annual Meeting of the American Educational Research Association, n.4, 1995, San Francisco, CA. Self-Efficacy in Academic Settings.1995, p. 1–38.

PAJARES, Frank; URDAN, Timothy C. Guide for constructing self-efficacy scales. In: BANDURA, Albert. Self-efficacy beliefs of adolescents. Greenwich, CT: IAP, 2006. v. 5,14, p. 307–337.

PETERSON, Robert A. A meta-analysis of Cronbach’s coefficient alpha. Journal of Consumer Research, v. 21, p. 381–391, 1994.

QUINN, James B.; ANDERSON, Philip; FINKELSTEIN, Sydney. Leveraging intellect. The Academy of Management Executive, v. 10, n. 3, p. 78–94, 1996.

REAGANS, Ray. Close encounters: Analyzing how social similarity and propinquity contribute to strong network connections. Organization Science, v. 22, n. 4, p. 835–849, 2011.

REAGANS, Ray; ZUCKERMAN, Ezra W. Networks, diversity, and productivity: the social capital of corporate R&D teams. Organization Science, v. 12, n. 4, p. 502–517, 2001.

ROGERS, Everett M.; BHOWMIK, Dilip K. Homophily-heterophily: relational concepts for communication research. Public Opinion Quarterly, v. 34, n. 4, p. 523–538, 1970.

SCHINKA, John A.; VELICER, Wayne F.; WEINER, Irving B. Handbook of Psychology. John Wiley & Sons, Inc., 2003.

SCOTT, John; CARRINGTON, Peter J. (Ed.). The SAGE Handbook of Social Network Analysis. SAGE publications, 2011.

STAJKOVIC, Alexander D.; LUTHANS, Fred. Self-efficacy and work-related performance: a meta-analysys. Psychological Bulletin, v. 124, n. 2, p. 240, 1998.

THADEWALD, T.; BÜNING, H. Jarque–Bera test and its competitors for testing normality– a power comparison. Journal of Applied Statistics, v. 34, n. 1, p. 87–105, 2007.

WASSERMAN, S.; FAUST, K. Social Network Analysis: Methods and Applications. Cambridge University Press, 1994.

WOOLDRIDGE, Jeffrey M. Introdução à econometria: uma abordagem moderna. Pioneira Thomson Learning, 2006. p. 684

WU, Wei-li; YEH, Ryh-song; HUNG, Hao-kai. Knowledge sharing and work performance. Social behavior and personality, v. 40, n. 229, p. 1113–1120, 2012.

YAMAGUCHI, Kazuo. Homophily and social distance in the choice of multiple friends an analysis based on conditionally symmetric log-bilinear association models. Journal of the American Statistical Association, v. 85, n. 410, p. 356–366, 1990.