1,003 research outputs found
The sources of management innovation: when firms introduce new management practices
Management innovation is the introduction of management practices new to the firm and intended to enhance firm performance. Building on the organizational reference group literature, this article shows that management innovation is a consequence of a firm's internal context and of the external search for new knowledge. Furthermore the article demonstrates a trade-off between context and search, in that there is a negative effect on management innovation associated with their joint occurrence. Finally the article shows that management innovation is positively associated with firm performance in the form of subsequent productivity growth
A Tool for IT-supported Visualization and Analysis of Virtual Communication Networks in Knowledge Communities
Social Cohesion, Structural Holes, and a Tale of Two Measures
EMBARGOED - author can archive pre-print or post-print on any open access repository after 12 months from publication. Publication date is May 2013 so embargoed until May 2014.This is an author’s accepted manuscript (deposited at arXiv arXiv:1211.0719v2 [physics.soc-ph] ), which was subsequently published in Journal of Statistical Physics May 2013, Volume 151, Issue 3-4, pp 745-764. The final publication is available at link.springer.com http://link.springer.com/article/10.1007/s10955-013-0722-
Learning by hiring: the effects of scientists’ inbound mobility on research performance in academia
This study investigates the effects of scientists’ inbound mobility on the research performance of incumbent scientists in an academic setting. The theoretical framework integrates insights from learning theory and social comparison theory to suggest two main mechanisms behind these effects, localized learning and social comparison. The authors propose several hypotheses about the conditions that might intensify or weaken such effects. Specifically, the arrival of new scientific personnel is likely to exert stronger positive effects on the performance of incumbent scientists with shorter (cf. longer) organizational tenure; in addition, academic departments with less diversified expertise and with higher levels of internal collaborations likely reap greater benefits from learning by hiring. The empirical findings, based on a longitudinal analysis of a sample of 94 U.S. academic chemical engineering departments, provide empirical support for these contentions
MANAGING THE IMPACT OF DIFFERENCES IN NATIONAL CULTURE ON SOCIAL CAPITAL IN MULTINATIONAL IT PROJECT TEAMS – A GERMAN PERSPECTIVE
How can management handle relationship problems arising from cultural differences in multinational IT project teams? This paper uses a social capital lens to better understand the negative impact of cultural differences in IT project teams. In contrast to many previous works we do not consider cultural differences as a whole but explore the role of the different national culture dimensions. This allows for a more detailed view on cultural differences in a team context and thus contributes to a better understanding about which dimensions of national culture drive relationship problems and which management measures can help to dampen the negative effects. Based on several exploratory cases (6 multinational IT projects in 4 companies, headquartered in Germany), the authors identify three patterns showing typical problems in team social relationships which arise from differences in particular dimensions of national culture. Pattern-specific as well as general management measures, employed to address the culture-driven negative effects, are identified as well
Overcoming network overload and redundancy in inter-organizational networks:the roles of potential and latent ties
This paper builds on Granovetter's distinction between strong and weak ties [Granovetter, M. S. 1973. The strength of weak ties. Amer. J. Sociol. 78(6) 1360–1380] in order to respond to recent calls for a more dynamic and processual understanding of networks. The concepts of potential and latent tie are deductively identified, and their implications for understanding how and why networks emerge, evolve, and change are explored. A longitudinal empirical study conducted with companies operating in the European motorsport industry reveals that firms take strategic actions to search for potential ties and reactivate latent ties in order to solve problems of network redundancy and overload. Examples are given, and their characteristics are examined to provide theoretical elaboration of the relationship between the types of tie and network evolution. These conceptual and empirical insights move understanding of the managerial challenge of building effective networks beyond static structural contingency models of optimal network forms to highlight the processes and capabilities of dynamic relationship building and network development. In so doing, this paper highlights the interrelationship between search and redundancy and the scope for strategic action alongside path dependence and structural influences on network processes
The impact of ownership structure on earnings quality: the case of South Korea
© 2018, Macmillan Publishers Ltd., part of Springer Nature. This paper investigates the impact of business group ownership structure on the quality of earnings reporting using data from South Korea. In addition, we investigate the impact of ownership disparity and family ownership on earnings quality reporting. Using a self-constructed earnings quality index as a measure of earnings quality, we found that business group ownership structure is significantly associated with higher earnings quality. The result suggests that strong monitoring mechanisms introduced by the government, which are necessary for credibility in external financial markets and beneficial to business group reputation, led to increased transparency in earnings reports. We also found that disparity in ownership between control and cash flow rights in firms, as well as family ownership in group firms, was both associated with lower earnings quality
Nanotechnology researchers' collaboration relationships: A gender analysis of access to scientific information
Women are underrepresented in science, technology, engineering, and mathematics fields, particularly at higher levels of organizations. This article investigates the impact of this underrepresentation on the processes of interpersonal collaboration in nanotechnology. Analyses are conducted to assess: (1) the comparative tie strength of women's and men's collaborations, (2) whether women and men gain equal access to scientific information through collaborators, (3) which tie characteristics are associated with access to information for women and men, and (4) whether women and men acquire equivalent amounts of information by strengthening ties. Our results show that the overall tie strength is less for women's collaborations and that women acquire less strategic information through collaborators. Women and men rely on different tie characteristics in accessing information, but are equally effective in acquiring additional information resources by strengthening ties. This article demonstrates that the underrepresentation of women in science, technology, engineering, and mathematics has an impact on the interpersonal processes of scientific collaboration, to the disadvantage of women scientists.Villanueva-Felez, Á.; Woolley, RD.; Cañibano Sánchez, C. (2015). Nanotechnology researchers' collaboration relationships: A gender analysis of access to scientific information. Social Studies of Science. 45(1):100-129. doi:10.1177/0306312714552347S100129451ACKER, J. (1990). HIERARCHIES, JOBS, BODIES: Gender & Society, 4(2), 139-158. doi:10.1177/089124390004002002Aitken, C., Power, R., & Dwyer, R. (2008). A very low response rate in an on-line survey of medical practitioners. Australian and New Zealand Journal of Public Health, 32(3), 288-289. doi:10.1111/j.1753-6405.2008.00232.xAngrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics. doi:10.1515/9781400829828Baruch, Y., & Holtom, B. C. (2008). Survey response rate levels and trends in organizational research. Human Relations, 61(8), 1139-1160. doi:10.1177/0018726708094863Beaver, D. D. (2001). Scientometrics, 52(3), 365-377. doi:10.1023/a:1014254214337Boardman, P. C., & Corley, E. A. (2008). University research centers and the composition of research collaborations. Research Policy, 37(5), 900-913. doi:10.1016/j.respol.2008.01.012Bourdieu, P. (1975). The specificity of the scientific field and the social conditions of the progress of reason. Social Science Information, 14(6), 19-47. doi:10.1177/053901847501400602Bourdieu, P. (1977). Outline of a Theory of Practice. doi:10.1017/cbo9780511812507Bourdieu, P. (1989). Social Space and Symbolic Power. Sociological Theory, 7(1), 14. doi:10.2307/202060Bouty, I. (2000). INTERPERSONAL AND INTERACTION INFLUENCES ON INFORMAL RESOURCE EXCHANGES BETWEEN R&D RESEARCHERS ACROSS ORGANIZATIONAL BOUNDARIES. Academy of Management Journal, 43(1), 50-65. doi:10.2307/1556385Bozeman, B., & Corley, E. (2004). Scientists’ collaboration strategies: implications for scientific and technical human capital. Research Policy, 33(4), 599-616. doi:10.1016/j.respol.2004.01.008Bozeman, B., & Gaughan, M. (2011). How do men and women differ in research collaborations? An analysis of the collaborative motives and strategies of academic researchers. Research Policy, 40(10), 1393-1402. doi:10.1016/j.respol.2011.07.002Bozeman, B., & Rogers, J. D. (2002). A churn model of scientific knowledge value: Internet researchers as a knowledge value collective. Research Policy, 31(5), 769-794. doi:10.1016/s0048-7333(01)00146-9Bozeman, B., Dietz, J. S., & Gaughan, M. (2001). Scientific and technical human capital: an alternative model for research evaluation. International Journal of Technology Management, 22(7/8), 716. doi:10.1504/ijtm.2001.002988Brass, D. J. (1985). MEN’S AND WOMEN’S NETWORKS: A STUDY OF INTERACTION PATTERNS AND INFLUENCE IN AN ORGANIZATION. Academy of Management Journal, 28(2), 327-343. doi:10.2307/256204Chompalov, I., Genuth, J., & Shrum, W. (2002). The organization of scientific collaborations. Research Policy, 31(5), 749-767. doi:10.1016/s0048-7333(01)00145-7Cook, C., Heath, F., & Thompson, R. L. (2000). A Meta-Analysis of Response Rates in Web- or Internet-Based Surveys. Educational and Psychological Measurement, 60(6), 821-836. doi:10.1177/00131640021970934Durbin, S. (2010). Creating Knowledge through Networks: a Gender Perspective. Gender, Work & Organization, 18(1), 90-112. doi:10.1111/j.1468-0432.2010.00536.xEcklund, E. H., Lincoln, A. E., & Tansey, C. (2012). Gender Segregation in Elite Academic Science. Gender & Society, 26(5), 693-717. doi:10.1177/0891243212451904Ensign, P. C. (2009). Knowledge Sharing among Scientists. doi:10.1057/9780230617131Etzkowitz, H., Kemelgor, C., & Uzzi, B. (2000). Athena Unbound. doi:10.1017/cbo9780511541414Flyvbjerg, B. (2001). Making Social Science Matter. doi:10.1017/cbo9780511810503FOX, M. F. (2001). WOMEN, SCIENCE, AND ACADEMIA. Gender & Society, 15(5), 654-666. doi:10.1177/089124301015005002Fox, M. F. (2010). Women and Men Faculty in Academic Science and Engineering: Social-Organizational Indicators and Implications. American Behavioral Scientist, 53(7), 997-1012. doi:10.1177/0002764209356234Fox, M. F., & Stephan, P. E. (2001). Careers of Young Scientists: Social Studies of Science, 31(1), 109-122. doi:10.1177/030631201031001006Fox, M. F., Sonnert, G., & Nikiforova, I. (2009). Successful Programs for Undergraduate Women in Science and Engineering: Adapting versus Adopting the Institutional Environment. Research in Higher Education, 50(4), 333-353. doi:10.1007/s11162-009-9120-4Friedkin, N. (1980). A test of structural features of granovetter’s strength of weak ties theory. Social Networks, 2(4), 411-422. doi:10.1016/0378-8733(80)90006-4Gaughan, M. (2005). Introduction to the Symposium: Women in Science. The Journal of Technology Transfer, 30(4), 339-342. doi:10.1007/s10961-005-2579-zGaughan, M., & Corley, E. A. (2010). Science faculty at US research universities: The impacts of university research center-affiliation and gender on industrial activities. Technovation, 30(3), 215-222. doi:10.1016/j.technovation.2009.12.001Granovetter, M. S. (1973). The Strength of Weak Ties. American Journal of Sociology, 78(6), 1360-1380. doi:10.1086/225469Hansen, M. T. (1999). The Search-Transfer Problem: The Role of Weak Ties in Sharing Knowledge across Organization Subunits. Administrative Science Quarterly, 44(1), 82. doi:10.2307/2667032Ibarra, H. (1992). Homophily and Differential Returns: Sex Differences in Network Structure and Access in an Advertising Firm. Administrative Science Quarterly, 37(3), 422. doi:10.2307/2393451Islam, N., & Miyazaki, K. (2009). Nanotechnology innovation system: Understanding hidden dynamics of nanoscience fusion trajectories. Technological Forecasting and Social Change, 76(1), 128-140. doi:10.1016/j.techfore.2008.03.021Katz, J. S., & Martin, B. R. (1997). What is research collaboration? Research Policy, 26(1), 1-18. doi:10.1016/s0048-7333(96)00917-1Koch, N. S., & Emrey, J. A. . (2001). The Internet and Opinion Measurement: Surveying Marginalized Populations. Social Science Quarterly, 82(1), 131-138. doi:10.1111/0038-4941.00012Kyvik, S., & Teigen, M. (1996). Child Care, Research Collaboration, and Gender Differences in Scientific Productivity. Science, Technology, & Human Values, 21(1), 54-71. doi:10.1177/016224399602100103Lee, S., & Bozeman, B. (2005). The Impact of Research Collaboration on Scientific Productivity. Social Studies of Science, 35(5), 673-702. doi:10.1177/0306312705052359Levin, D. Z., & Cross, R. (2004). The Strength of Weak Ties You Can Trust: The Mediating Role of Trust in Effective Knowledge Transfer. Management Science, 50(11), 1477-1490. doi:10.1287/mnsc.1030.0136Lin, N. (2001). Social Capital. doi:10.1017/cbo9780511815447McFadyen, M. A., & Cannella, A. A. (2004). SOCIAL CAPITAL AND KNOWLEDGE CREATION: DIMINISHING RETURNS OF THE NUMBER AND STRENGTH OF EXCHANGE RELATIONSHIPS. Academy of Management Journal, 47(5), 735-746. doi:10.2307/20159615McFadyen, M. A., Semadeni, M., & Cannella, A. A. (2009). Value of Strong Ties to Disconnected Others: Examining Knowledge Creation in Biomedicine. Organization Science, 20(3), 552-564. doi:10.1287/orsc.1080.0388Manfreda, K. L., Bosnjak, M., Berzelak, J., Haas, I., & Vehovar, V. (2008). Web Surveys versus other Survey Modes: A Meta-Analysis Comparing Response Rates. International Journal of Market Research, 50(1), 79-104. doi:10.1177/147078530805000107Marsden, P. V., & Campbell, K. E. (1984). Measuring Tie Strength. Social Forces, 63(2), 482. doi:10.2307/2579058Mason, M. A., & Ekman, E. M. (2007). Mothers on the Fast TrackHow a New Generation Can Balance Family and Careers. doi:10.1093/acprof:oso/9780195182675.001.0001Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An Integrative Model Of Organizational Trust. Academy of Management Review, 20(3), 709-734. doi:10.5465/amr.1995.9508080335Nahapiet, J., & Ghoshal, S. (1998). Social Capital, Intellectual Capital, and the Organizational Advantage. Academy of Management Review, 23(2), 242-266. doi:10.5465/amr.1998.533225Oliver, A. L., & Liebeskind, J. P. (1997). Three Levels of Networking for Sourcing Intellectual Capital in Biotechnology. International Studies of Management & Organization, 27(4), 76-103. doi:10.1080/00208825.1997.11656719Podolny, J. M., & Baron, J. N. (1997). Resources and Relationships: Social Networks and Mobility in the Workplace. American Sociological Review, 62(5), 673. doi:10.2307/2657354Rhoton, L. A. (2011). Distancing as a Gendered Barrier. Gender & Society, 25(6), 696-716. doi:10.1177/0891243211422717Rothstein, M. G., & Davey, L. M. (1995). Gender differences in network relationships in academia. Women in Management Review, 10(6), 20-25. doi:10.1108/09649429510095999Rowley, T., Behrens, D., & Krackhardt, D. (2000). Redundant governance structures: an analysis of structural and relational embeddedness in the steel and semiconductor industries. Strategic Management Journal, 21(3), 369-386. doi:10.1002/(sici)1097-0266(200003)21:33.0.co;2-mSCOTT, D. B. (1996). SHATTERING THE INSTRUMENTAL-EXPRESSIVE MYTH. Gender & Society, 10(3), 232-247. doi:10.1177/089124396010003003Shapin, S. (1994). A Social History of Truth. doi:10.7208/chicago/9780226148847.001.0001Shrum, W., Chompalov, I., & Genuth, J. (2001). Trust, Conflict and Performance in Scientific Collaborations. Social Studies of Science, 31(5), 681-730. doi:10.1177/030631201031005002Smith-Doerr, L. (2004). Flexibility and Fairness: Effects of the Network Form of Organization on Gender Equity in Life Science Careers. Sociological Perspectives, 47(1), 25-54. doi:10.1525/sop.2004.47.1.25Stix, G. (2001). Little Big Science. Scientific American, 285(3), 32-37. doi:10.1038/scientificamerican0901-32Uzzi, B. (1996). The Sources and Consequences of Embeddedness for the Economic Performance of Organizations: The Network Effect. American Sociological Review, 61(4), 674. doi:10.2307/2096399Uzzi, B. (1997). Social Structure and Competition in Interfirm Networks: The Paradox of Embeddedness. Administrative Science Quarterly, 42(1), 35. doi:10.2307/2393808Vinck, D. (2010). The Sociology of Scientific Work. doi:10.4337/9781849807197Fan, W., & Yan, Z. (2010). Factors affecting response rates of the web survey: A systematic review. Computers in Human Behavior, 26(2), 132-139. doi:10.1016/j.chb.2009.10.015Ziman, J. M. (Ed.). (1994). Prometheus Bound. doi:10.1017/cbo978051158506
The Impact of Inter-organizational Social Capital in Collaborative Networks Competitiveness: An Empirical Analysis
- …