Intellectual capital and performance in temporary teams

Purpose: The purpose of this paper is to deepen resource-based view theory by analyzing how intellectual capital (IC) affects performance in temporary teams and by showing the moderating role of integrative mechanisms. Design/methodology/approach: The research context focuses on 153 national teams of football (NTF), also referred to as national soccer teams, as an example of temporary groups. A partial least squares (PLS) methodology was utilized on a data set built from transfermarkt.com and FIFA world rankings. Three main hypotheses were developed and tested using first a PLS and then an OLS approach. Findings: The results show how IC contributes to performance, extending the findings of previous studies to the context of temporary teams. Additionally, the results show how some integrative mechanisms such as assembly decisions and team leader experience influence temporary team performance by creating an interaction effect with existing IC. Originality/value: This study contributes to IC theories for three reasons. First, it applies IC research to a specific research context: temporary teams, where specific organizational capabilities are required to coordinate resources. Second, the study analyzes the role of integrative mechanisms as moderators of the relationship between IC and performance in temporary teams. Third, the study focuses on NTF as an example of temporary teams

Ultrasound and MR-imaging in preoperative evaluation of two rare cases of scar endometriosis

Scar or incisional endometriosis is a rare, often misdiagnosed, pathologic condition of the abdominal wall. Two cases of incisional endometriosis are presented. Both patients presented with atypical cyclic pain and palpable nodules on scars of previous cesarean sections. In both cases, the mass was totally excised, after accurate preoperative evaluation with 2-D ultrasound, power Doppler and MRI. Microscopic examination confirmed the preoperatively presumed diagnosis of cutaneous endometriosis. In cases of suspected scar endometriosis, preoperative diagnostic imaging is valuable in determining the extent of disease, thus enhancing accurate and total excision

Placenta abruption in a woman with Wilson’s disease: a case report

Wilson’s disease is a rare genetic disorder of copper metabolism that causes primary hepatic cirrhosis, secondary menstrual abnormalities and infertility. Following the appropriate therapy patients are asymptomatic and pregnancy may be achieved. We present a case of placental abruption in a pregnant woman with Wilson’s disease and we review the management dilemmas and treatment options of pregnant women with Wilson’s disease

â-thalassemia and gonadal axis: a cross-sectional, clinical study in a Greek population

ABSTRACT â-thalassemia (â-thal) is characterized by disturbances of the reproductive system. The aim of the present study was: 1) to assess the hypothalamic pituitary -gonadal axis in patients with â-thal in relation to their phenotype and 2) to determine prognostic features of current gonadal status. We studied 135 patients (67 males and 68 females) with â-thal through history, physical examination, spermiograms and GnRH test. These patients were divided into â-thal major (51 males and 62 females) and â-thal intermedia phenotypes (16 males and 6 females). Male patients with â-thal major were subdivided into three groups a) eugonadal (35%, Tanners stage V, normal testicular volume, normal spermiograms, normal basal and stimulated hormone values), b) patients with hypogonadotrophic hypogonadism (HH) of late onset (24%, Tanners stage II-V, low-normal testicular volume, abnormal spermiograms, normal basal gonadotrophin values and abnormal response to GnRH test) and c) patients with HH of early onset (41%, Tanners stage I, small testicular volume, abnormal spermiograms, abnormal basal and stimulated hormone values). Female patients with â-thal major were subdivided into: a) eugonadal (32%, Tanners stage V, regular menstruation, normal basal and stimulated hormone values), b) patients with hypogonadotrophic hypogonadism (HH) of late onset (34%, Tanners stage II-V, secondary amenorrhea, subnormal basal and stimulated gonadotrophin values) and c) patients with HH of early onset (34%, Tanners stage I, primary amenorrhea, subnormal basal and stimulated hormone values). Patients with â-thal intermedia were subdivided into eugonadal (75% of males -33% of females) and hypogonadal (25% of males -67% of females). Current gonadal status could not be predicted by means of transfusion or chelation parameters. In conclusion, â-thal patients could be eugonadal or develop early or late onset HH. â-thal intermedia patients have a more favorable profile than â-thal major individuals. Current gonadal status of â-thal patients cannot be predicted by means of history, clinical or laboratory parameters

Laparoscopic management of mesenteric cyst: a case report

Mesenteric cysts are rare intra-abdominal lesions with variable clinical symptoms and signs that make pre-operative diagnosis difficult. Optimal treatment is surgical excision of the cyst with laparotomy or laparoscopy. We present a case of mesenteric cyst that was misdiagnosed as para-ovarian cyst and managed laparoscopically by gynaecologists

Complete uterine inversion during caesarean section: A case report

Inversion of the uterus through the uterine lower segment incision during a caesarean section is an extremely rare obstetric incident. It consists, though, an emergency complication that is potentially life-threatening, especially in cases of prolonged inversion, because haemodynamic instability and shock may occur. Prompt diagnosis and immediate uterine reversion are the key actions in the management of this serious complication

Effect of exploitation and exploration on the innovative as outcomes in entrepreneurial firms

[EN] The main aim of this study is to establish the effect of the Exploitation and Exploration; and the influence of these learning flows on the Innovative Outcome (IO). The Innovative Outcome refers to new products, services, processes (or improvements) that the organization has obtained as a result of an innovative process. For this purpose, a relationship model is defined, which is empirically contrasted, and can explains and predicts the cyclical dynamization of learning flows on innovative outcome in knowledge intensive firms. The quantitative test for this model use the data from entrepreneurial firms biotechnology sector. The statistical analysis applies a method based on variance using Partial Least Squares (PLS). Research results confirm the hypotheses, that is, they show a positive dynamic effect between the Exploration and the Innovative as outcomes. In the same vein, they results confirm the presence of the cyclic movement of innovative outcome with the Exploitation.In addition, this research is part of the Project ECO2015-71380-R funded by the Spanish Ministry of Economy, Industry and Competitiveness and the State Research Agency. Co-financed by the European Regional Development Fund (ERDF).Vargas-Mendoza, NY.; Lloria, MB.; Salazar Afanador, A.; Vergara Domínguez, L. (2018). Effect of exploitation and exploration on the innovative as outcomes in entrepreneurial firms. International Entrepreneurship and Management Journal. 14(4):1053-1069. https://doi.org/10.1007/s11365-018-0496-5S10531069144Alegre, J., & Chiva, R. (2008). Assessing the impact of organizational learning capability on product innovation performance: an empirical test. Technovation, 28, 315–326.Amara, N., Landry, R., Becheikh, N., & Ouimet, M. (2008). Learning and novelty of innovation in established manufacturing SMEs. Technovation, 28, 450–463.Aragón-Mendoza, J., Pardo del Val, M., & Roig, S. (2016). The influence of institutions development in venture creation decision: a cognitive view. Journal of Business Research, 69(11), 4941–4946.Ardichvili, A. (2008). Learning and knowledge sharing in virtual communities of practice: motivators, barriers, and enablers. Advances in Developing Human Resources, 10(4), 541–554.Argyris, C., & Schön, D. (1978). Organizational learning: a theory of action perspective. Reading: Addison Wesley.Bagozzi, R. P., Yi, Y., & Singh, S. (1991). On the use of structural equation models in experimental designs: two extensions international. Journal of Research in Marketing, 8, 125–140.Belda, J., Vergara L., Salazar, A., & Safont G. (2018). Estimating the Laplacian matrix of Gaussian mixtures for signal processing on graphs, accepted for publication in Signal Processing.Boland, R. J. J., & Tenkasi, R. V. (1995). Perspective making and perspective taking in communities of knowing. Organization Science, 6(4), 350–372.Bontis, N., (1998). Intellectual capital: an exploratory study that develops measures models. Management Decision, 36, 63–76.Bontis, N. (1999). Managing an organizational learning system by aligning stocks and flows of knowledge: an empirical examination of intellectual capital, knowledge management, and business performance. 1999. Management of Innovation and New Technology Research Centre, McMaster University.Bontis, N., Keow, W., & Richardson, S. (2000). Intellectual capital and the nature of business in Malaysia. Journal of Intellectual Capital, 1(1), 85–100Bontis, N., Hullan, J., & Crossan, M. (2002). Managing an organizational learning system by aligning stocks and flows. Journal of Management Studies, 39, 438–469.Brachos, D., Kostopulos, K., Sodersquist, K. E., & Prastacos, G. (2007). Knowledge effectiveness, social context and innovation. Journal of Knowledge Management, 11(5), 31–44.Calantone, R. J., Cavusgil, S. T., & Zhao, Y. (2002). Learning orientation, firm innovation capability, and firm performance. Industrial Marketing Management, 31, 515–524.Chang, T. J., Yeh, S. P., & Yeh, I. J. (2007). The effects of joint rewards system in new product development. International Journal of Manpower, 28(3/4), 276–297.Chin, W. (1998). The partial least square approach to structural equation modeling. In G. A. Marcoulides (Ed.) (pp. 294–336). New Jersey: Lawrence Erlbaum Associates.Cho, N., Li, G., & Su, C. (2007). An empirical study on the effect of individual factors on knowledge sharing by knowledge type. Journal of Global Business and Technology, 3(2), 1–15.Cohen, W. M., & Levin, R. C. (1989). Empirical studies of innovation and market structure. In R. Schmalansee & R. D. Willing (Eds.), Handbook of industrial organization II. New York: Elsevier.Cohen, W. M., & Levinthal, D. A. (1990). Absorptive-capacity – a new perspective on learning and innovation. Administrative Science Quarterly, 35, 128–152.Cooper, R. G. (2000). New product performance: what distinguishes the star products. Austrian Journal of Management, 25, 17–45.Crossan, M., & Berdrow, I. (2003). Organizational learning and strategic renewal. Strategic Management Journal, 24, 1087–1105.Crossan, M., & Apaydin, M. (2010). A multi-dimensional framework of organizational innovation: a systematic review of the literature. Journal of Management Studies, 47(6), 1154–1191.Crossan, M., Lane, H. W., & White, R. E. (1999). An organizational learning framework: from intuition to institution. Academy of Management Review, 24, 522–537.Damanpour, F., & Aravind, D. (2012). Managerial innovation: conceptions, processes, and antecedents. Management and Organization Review, 8(2), 423–454.Damanpour, F., & Shanthi, G. (2001). The dynamics of the adoption of products and process innovations in organizations. Journal of Management Studies, 38(1), 21–65.Decarolis, D. M., & Deeds, D. L. (1999). The impact of stock and flows of organizational knowledge on firm performance: An empirical investigation of the biotechnology industry. Strategic Management Journal, 20, 953–968.Demartini, C. (2015). Relationships between social and intellectual capital: empirical Evidence from IC statements. Knowledge and Process Management, 22(2), 99–111.Dupuy, F. (2004). Sharing knowledge: they why and how of organizational change. Hampshire: Palgrave Macmillan.Fornell, C., & Bookstein, F. I. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19, 440–452.Ganter, A., & Hecker, A. (2013). Deciphering antecedents of organizational innovation. Journal of Business Research, 66(5), 575–584.Ganter, A., & Hecker, A. (2014). Configurational paths to organizational innovation: qualitative comparative analyses of antecedents and contingencies. Journal of Business Research, 67, 1285–1292.Gopalakrishnan, S., & Damanpour, F. (1997). A review of innovation research in economics, sociology and technology management. International Journal of Management Science, 25, 15–28.Hedberg, B. (1981). How organizations learn and unlearn. In P. Nystrom & W. Starbuck (Eds.), Handbook of organizational design. New York: Oxford University.Hedlund, G., & Nonaka, I. (1993). Models of knowledge management in the west and Japan. In: P. Lorange, B. Chacravrarthy, J. Ross, and J. Van de ven (Eds.) Cambridge: Basil Blackwell.Henseler, J., Ringle, C.M., & Sinkovics, R.R. (2009). The use the partial least squares path modeling. In: R. Sinkovics and N. Pervez (Eds.) 277–319.Hsu, I. (2006). Enhancing employee tendencies to share knowledge-case studies on nine companies in Taiwan. International Journal of Information Management, 26(4), 326–338.Hsu, I. (2008). Knowledge sharing practices as a facilitating factor for improving organizational performance though human capital: a preliminary test. Expert Systems with Application, 35, 316–1326.Huang, Q., Davison, R., & Gu, J. (2008). Impact of personal and cultural factors on knowledge sharing in China. Asia Pacific Journal Management, 25(3), 451–471.Ibarra, H. (1993). Network centrality, power, and innovation involvement – determinants of technical and administrative roles. Academy of Management Journal, 36(3), 471–501.Iebra, I. L., Zegarra, P. S., & Zegarra, A. S. (2011). Learning for sharing: an empirical analysis of organizational learning and knowledge sharin. International Entrepreneurship Management Journal, 7, 509–518.Ipe, M. (2003). Knowledge sharing in organizations: a conceptual framework. Human Resource Development Review, 2(4), 337–359.Jenkin, T. (2013). Extending the 4I organizational learning model: information sources, foraging processes and tools. Administrative Sciences, 3, 96–109.Jiménez-Jiménez, D., & Sanz-Valle, R. (2011). Innovation, organizational learning, and performance. Journal of Business Research, 64, 408–417.Kane, G. C., & Alavi, M. (2007). Information technology and organizational learning: an investigation of exploration and exploitation processes. Organization Science, 18(5), 796–812.Kleinbaum, D. G., Kupper, N. N., Muller, K. E. (1988). Applied regression analysis and other Multivariable’s methods, PWS KENT.Klomp, L., & Van Leeuwen, G. (2001). Linking innovation and firm performance: a new approach. International Journal of the Economics of Business, 8(3), 343–364.Lansisalmi, H., Kivimaki, M., Aalto, P., & Ruoranen, R. (2006). Innovation in healthcare: a systematic review of recent research. Nursing Science Quarterly, 19(1), 66–72.Laperrière, A., & Spence, M. (2015). Enacting international opportunities: the role of organizational learning in knowledge-intensive business services. Journal of International Entrepreneurship, 13(3), 212–241.Levitt, B., & March, J. G. (1988). Organizational learning. Annual Review of Sociology, 14, 319–340.Lin, H. (2007). Knowledge sharing and firm innovation capability: an empirical study. International Journal of Manpower, 28(3/4), 315–332.Lloria, M. B., & Moreno-Luzón, M. D. (2014). Organizational learning: proposal of an integrative scale and research instrument. Journal of Business Research, 67, 692–697.March, J. G. (1991). Exploration and exploitation in organizational learning. Organizational Science, 2, 71–87.Matikainen, M., Terho, H., Parvinen, P., & Juppo, A. (2016). The role and impact of firm’s strategic orientations on launch performance: significance of relationship orientation. Journal of Business & Industrial Marketing, 31(5), 625–639.Mone, M. A., McKinley, W., & Barker, V. L. (1998). Organizational decline and innovation: a contingency framework. Academy of Management Review, 23, 115–132.Moreno-Luzón, M. D., & Lloria, B. (2008). The role of non-structural and informal mechanisms of integration and integration as forces in knowledge creation. British Journal of Management, 19, 250–276.Moskaliuk, J., Bokhorst, F., & Cress, U. (2016). Learning from others' experiences: how patterns foster interpersonal transfer of knowledge-in-use. Computers in Human Behavior, 55, 69–75.Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company. How Japanese companies create the dynamics of innovation. New York: Oxford University Press.Nonaka, I., & von Krogh, G. (2009). Perspective tacit knowledge and knowledge conversion: controversy and advancement in organizational knowledge creation theory. Organization Science, 20(3), 635–652.Parida, V., Lahti, T., & Wincent, J. (2016). Exploration and exploitation and firm performance variability: a study of ambidexterity in entrepreneurial firms. International Entrepreneurship Management Journal, 12, 1147–1164.Pew, H., Plowman, D., & Hancock, P. (2008). The involving research on intellectual capital. Journal of Intellectual Capital, 9, 585–608.Potter, R. E., & Balthazard, P. A. (2004). The role of individual memory and attention processes during electronic brainstorming. MIS Quarterly, 28(4), 621–643.Ramadani, V., Hyrije, A. A., Léo-Paul, D., Gadaf, R., & Sadudin, I. (2017). The impact of knowledge spillovers and innovation on firm-performance: findings from the Balkans countries. International Entrepreneurship Management Journal, 13, 299–325.Ren, S., Shu, R., Bao, Y., & Chen, X. (2016). Linking network ties to entrepreneurial opportunity discovery and exploitation: the role of affective and cognitive trust. International Entrepreneurship and Management Journal, 12(2), 465–485.Ringle, C. M., Wende, S., & Will, A. (2005). Smart PLS 2.0 (M3) beta, Hamburg: http://www.smartpls.de .Ringle, C. M., Sarstedt, M., & Straub, D. (2012). A critical look at the use of PLS-SEM. MIS Quarterly, 36(1), iii–xiv.Sanchez, R., & Heene, A. (1997). A competence perspective on strategic learning and knowledge management. En Sanchez, R. and Heene, A. (eds.) Strategic learning and knowledge management. John Wiley and Sons.Seidler-de Alwis, R., & Hartmann, E. (2008). The use of tacit knowledge within innovative companies: knowledge management in innovative enterprises. Journal of Knowledge Management, 12(1), 133–147.Shrivastava, P. (1983). A typology of organizational learning systems. Journal of Management Studies, 20, 7–28.Tansky, J., Ribeiro, D., & Roig, S. (2010). Linking entrepreneurship and human resources in globalization. Human Resource Management, 49(2), 217–223.Teece, D. (2012). Dynamic capabilities: routines versus entrepreneurial action. Journal of Management Studies, 49(8), 1395–1401.Tenenhaus, M., Vinzi, V., Chatelin, Y., & Lauro, C. (2005). PLS path modeling. Computational Statistics and Data Analysis, 49, 159–205.vande Vrande, V., de Jong, J., Vanhaverbeke, W., & Rochemont, M. (2009). Open innovation in SMEs: trends, motives and management challenges. Technovation, 29, 423–437.Vargas, N., & Lloria, M. B. (2014). Dynamizing intellectual capital through enablers and learning flows. Industrial Management and Data Systems, 114(1), 2–20.Vargas, N., & Lloria, M. B. (2017). Performance and intellectual capital: how enablers drive value creation in organisations. Knowledge and Process Management, 24(2), 114–124.Vargas, N., Lloria, M. B., & Roig-Dobón, S. (2016). Main drivers of human capital, learning and performance. The Journal of Technology Transfer, 41(5), 961–978.Vergara, L., Salazar, A., Belda, J., Safont, G., Moral, S., & Iglesias, S. (2017). Signal processing on graphs for improving automatic credit card fraud detection. Proceeding of 2017 I.E. 51st international Carnahan Conference on Security Technology (ICCST 2017), https://doi.org/10.1109/CCST.2017.8167820 , 23–26 Oct, 2017, Madrid, Spain.Wallin, M. W., & Von Krogh, G. (2010). Organizing for open innovation: focus o the integration of knowledge. Organizational Dynamics, 39(2), 145–154.Wang, C. L., & Ahmed, P. K. (2004). Linking innovation and firm performance: a new approach. European International Journal of Technology Management, 27, 674–688.Wold, H. (1980). Model construction and evaluation when theoretical knowledge is scarce. In J. Kmenta & J. B. Ramsey (Eds.), Evaluation of econometric models (pp. 47–74). Cambridge: Academic Press.Wold, H. (1985). Factors influencing the outcome of economic sanctions. In Sixto Ríos Honorary. Trabajos de Estadística and de Investigación Operativa, 36(3), 325–337