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Explores the origins of school‐staff team effectiveness by focusing on team characteristics, especially on team heterogeneity and team support. Based on educational and organizational theory, we derived propositions about how heterogeneity may affect team support and team effectiveness. More specifically, we hypothesized that task‐related attributes of heterogeneity (functional, educational, and team tenure) would relate positively to team support and team effectiveness, whereas relations‐related attributes would relate negatively to team support and team effectiveness. With a sample of 48 teams, identified as intact work teams, we found results partially confirming our propositions. Specifically, high heterogeneous teams in gender and functions were more supportive and effective than low heterogeneous teams in those attributes. By contrast, high heterogeneous teams in tenure were less supportive and effective than low heterogeneous teams in that attribute. The results are discussed in light of the specific context of schools, and several theoretical and managerial implications are drawn.

Online knowledge integration has been an important concern of the online knowledge community as it can lead to various positive outcomes of online knowledge coproduction. This paper identifies online knowledge integration factors by considering group heterogeneity and group interaction process.

Based on the categorization-elaboration model (CEM) and interactive team cognition (ITC) theory, a research model that reflects the antecedent's factors and mediating factors of online knowledge integration was developed and empirically examined based on data collected from 2,339,836 data extracted from Wikipedia.

Group interaction process plays an essential mediator role in online knowledge integration. Group knowledge heterogeneity negatively influences online knowledge integration and group experience heterogeneity positively, and they both positively promote online knowledge integration through group interaction process with different paths.

Our research concerns the OKC context in one setting (Wikipedia). We expect that the results will generalize to other OKC platforms.

The findings of the study could assist the online knowledge community's organizers to understand the motivational mechanisms of online knowledge integration. Group interaction process could be regarded as the key role to promote group wisdom and maintain group independence.

We advance the understanding of the online knowledge integration and gain a richer understanding of the importance of group interaction independence for online knowledge integration based on the agreement of group wisdom. It suggested keeping group interaction independence is an important aspect for highly online knowledge integration among heterogeneity groups.

This study extends CEM and ITC theory to the domain of knowledge integration context and finds the mechanism between group heterogeneity and online knowledge integration by introducing the group interaction process.

Empirically‐based programmes are the cornerstone of the prevention science field. Beyond curriculum content and design, several aspects of school‐based prevention and intervention programmes have been found to contribute to their effectiveness, including implementer training, programme fidelity and principal [head teacher] support. The current investigation examined whether the degree of heterogeneity among classroom members (ie. students' racial or ethnic backgrounds, students' neighbourhood socio‐economic status (SES), students' neighbourhood education level and students' neighbourhood immigrant status) influences the effectiveness of the Promoting Alternative Thinking Strategies (PATHS) social and emotional learning programme. The analyses found a relationship between the degree of classroom heterogeneity and students' pre‐test scores on social and emotional variables. Moreover, gender differences were evident on pre‐test scores, reflecting differential baselines. The findings for analysis on classroom heterogeneity as a moderator of the programme's effectiveness in improving students' social and emotional competence were mixed. Future research and policy implications are discussed related to advancing the field and ensuring culturally relevant evidence‐based programming.

The purpose of this paper, based on first-hand data from 255 chairmen of planting cooperatives in Sichuan province, is threefold: to understand their social network heterogeneity; to understand the significance for members of marketing innovation in farmers' cooperatives and to understand the effects of chairmen's social network heterogeneity on cooperative marketing innovation.

The research employs an empirical survey of the chairmen of planting cooperatives in rural Sichuan province. The researchers use the ordinary least squares method to conduct regression on the data and the generalized linear model to process the data and avoid errors in the model setting. In the study, the following two hypotheses are examined: (1) The heterogeneity of chairmen's social networks has positive effects on cooperative marketing innovation; (2) The effects of heterogeneous external and internal social networks on cooperative marketing innovation are different.

The results show that both external and internal social network heterogeneity has positive effects on cooperative marketing innovation, and the effects of internal heterogeneity are greater than that of external heterogeneity.

This paper contributes to improving the income of farmers, the innovation of farmers' cooperatives and the development of agriculture in China. It provides a new way of managing and serving members to enable the long-term sustainable development of farmers' cooperatives.

The paper aims to examine the nature of competition within an industry by proposing and examining three separate sources of competitive heterogeneity: the strategies that industry members use, the performance that they obtain, and how effectively the strategies are utilized to obtain such performance results.

To do so, a restricted latent structure finite mixture model is devised that can quantify the contribution of these three potential sources of heterogeneity in the formulation of latent competitive groups within an industry. The paper illustrate this modeling framework with respect to COMPUSTAT strategy and performance data collected for public banks in the USA.

The paper shows how traditional conceptualizations via strategic or performance groups are inadequate to fully represent intra‐industry heterogeneity.

This research paper proposes a new class of restricted finite mixture‐based models, which fit a variety of alternative forms/models of heterogeneity. Information heuristics are developed to indicate “best model.”

Few studies investigated the influence of heterogeneous knowledge and social networks on the innovation performance of new ventures in emerging economics. Particularly, as the focus of global economic development is paying more attention to emerging economics such as China, Indonesia and India, innovation research in these countries becomes more and more important. As such, this paper aims to propose a theoretical model and designed a survey based on the Theory of Inventive Problem Solving (TRIZ).

To investigate the influence of network heterogeneity and knowledge heterogeneity on the innovation performance of new ventures, the authors designed a structured questionnaire based on the TRIZ methodology for innovative problem solving to collect data from new ventures established in the past eight years in eastern China.

The empirical results verify the assumptions of our theoretical model: network heterogeneity has a positive impact on the innovation performance of new ventures; knowledge heterogeneity has a positive impact on the innovation performance of new ventures; network heterogeneity has a positive impact on knowledge heterogeneity.

The main contribution of this paper is that the proposed theoretical model determining the relationship of network heterogeneity and knowledge heterogeneity with the innovation performance of new ventures was empirically tested and verified. This study also empirically verified what types and what sources of social network and knowledge are critically linked to new venture innovation.

The purpose of this paper is to investigate whether the Boardroom heterogeneity affects IPO underpricing for entrepreneurial firms, where Boardroom heterogeneity was classified in terms of functional background, educational background, age and length of tenure.

A national research design was conducted using data collected from 355 firms listed on China’s Growth Enterprise Market from its start in 2009 to 2012.

The author found that IPO underpricing has a significant negative correlation with functional heterogeneity, a positive correlation with educational heterogeneity, a significant negative correlation with age heterogeneity, but it does not show significant correlation with heterogeneity in tenure. Board heterogeneity affects IPO underpricing of entrepreneurial firms partially, which means functional, educational and age heterogeneity conveys signals to potential investors regarding a firm’s quality.

More entrepreneurial firms in more years for data and long-term performance research design in future research would be required for further understanding of the relationships among the variables in this study.

This paper suggests that IPO firms may make use of such an influencing mechanism to determine the issue price or to control the IPO underpricing by showing the Boardroom heterogeneity.

This paper revealed the influence of the characteristics of board members of such firms on IPO underpricing, which is rare in recent studies comparing to the study for the top management team; also this study provides empirical support for such effect.

There has been an increasing trend toward the creation of senior management teams (SMTs) which are characterized by a high degree of functional heterogeneity. Although such teams may create better linkages to information, along with the benefits of functional heterogeneity comes the potential for conflicts that stem from the value differences among subcultures in an organization. These conflicts can adversely affect performance. The purpose of this paper is to examine how school leaders’ activities mediate the relationship of SMT functional heterogeneity to SMT effectiveness (in-role performance and innovation).

Data, which were obtained through a survey, was collected from a sample of 92 schools in Israel. Data were collected from two sources (principals and SMT members) to minimize problems associated with same source and common method bias. Data were aggregated at the team level of analysis.

The results of structural equation model indicated that principal’s internal activities enhanced SMT in-role performance whereas principals’ external activities enhanced SMT innovation. The results also showed that principal’s internal activities are full mediators of the relationship between functional heterogeneity and SMT in-role performance.

This study has implications for policies involving the design and implementation of leadership tools to effectively manage SMTs. The results of this study can help principals to establish priorities and allocate their time and resources more effectively, both inward and outward the SMT boundary so as to assist functionally heterogeneous SMTs translating the benefits of functional heterogeneity into significant achievements.

Observing across four comparative case organizations, the purpose of this paper is to identify two sources of contingency (i.e. construct and contextual contingency) for the relationship between knowledge heterogeneity and innovation.

The contingencies was explored by conducting a comparative case analyses with rich qualitative data extracted and interpreted from four case companies.

First, the construct contingency is examined by refining knowledge heterogeneity into three dimensions: domain, process, and context heterogeneity. Specifically, the author proposed that knowledge heterogeneity in domain is associated with innovation in an inverted U-shape, while heterogeneity in process and context dimensions both negatively influence innovation. Second, contextual contingency is studied. The author proposed that: trust positively moderates the relationship between knowledge heterogeneity and innovation; depending on the knowledge owner attributes, centralization positively or negatively moderates the relationship between heterogeneous knowledge and innovation; shared knowledge vision positively moderates the relationship between knowledge heterogeneity and innovation.

The influences of knowledge heterogeneity on innovation have yet been inconsistent. The present study set to reconcile such inconsistency with a solution of contingencies that intervene the heterogeneity-innovation relationship. These results offer useful references for future large-scaled, quantitative studies.

Feature space heterogeneity exists widely in various application fields of classification techniques, such as customs inspection decision, credit scoring and medical diagnosis. This paper aims to study the relationship between feature space heterogeneity and classification performance.

A measurement is first developed for measuring and identifying any significant heterogeneity that exists in the feature space of a data set. The main idea of this measurement is derived from a meta-analysis. For the data set with significant feature space heterogeneity, a classification algorithm based on factor analysis and clustering is proposed to learn the data patterns, which, in turn, are used for data classification.

The proposed approach has two main advantages over the previous methods. The first advantage lies in feature transform using orthogonal factor analysis, which results in new features without redundancy and irrelevance. The second advantage rests on samples partitioning to capture the feature space heterogeneity reflected by differences of factor scores. The validity and effectiveness of the proposed approach is verified on a number of benchmarking data sets.

Measurement should be used to guide the heterogeneity elimination process, which is an interesting topic in future research. In addition, to develop a classification algorithm that enables scalable and incremental learning for large data sets with significant feature space heterogeneity is also an important issue.

Measuring and eliminating the feature space heterogeneity possibly existing in the data are important for accurate classification. This study provides a systematical approach to feature space heterogeneity measurement and elimination for better classification performance, which is favorable for applications of classification techniques in real-word problems.

A measurement based on meta-analysis for measuring and identifying any significant feature space heterogeneity in a classification problem is developed, and an ensemble classification framework is proposed to deal with the feature space heterogeneity and improve the classification accuracy.