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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.

Although online brand communities (OBCs) are extensively demonstrated to be an important social media tool in building brand equity, they may have backfire effects under certain conditions. Drawing from the self–brand connection theory, the purpose of this study is to investigate the effect of group heterogeneity on brand commitment. The mediation effect of self–brand connection and moderation effect of brand symbolism has also been examined.

Data were collected using a survey of 498 users from a range of OBCs. Hierarchical regression and bootstrapping method were used to test the research model.

The findings indicate that group heterogeneity negatively affects brand commitment in which self–brand connection plays a role of mediation. Further, the negative effect is more pronounced for high-symbolic brands than low-symbolic ones.

Brand managers are advised to note the dark side of OBCs in general and alleviate the adverse effects of group heterogeneity in particular, especially for high-symbolic brands.

Previous research pays little attention to the adverse effect of OBCs. This study enriches the literature by revealing that the backfire effect of OBCs arises when users become heterogeneous and uncovering in what situations the negative effect is stronger.

Despite the increasingly common view that online brand community (OBC) members are heterogeneous, knowledge concerning the impact of group heterogeneity on community and brand level outcomes is lacking. In response and drawing from organization research, this paper aims to study the consequences of two types of group heterogeneity (i.e. visible heterogeneity and value heterogeneity) on brand community commitment and brand commitment. The moderating role of tenure in a community is also examined.

A survey of 467 members of OBCs was conducted, and structural equation modeling was used to test hypotheses.

The results show that perceived visible heterogeneity positively affects brand community commitment, whereas perceived value heterogeneity has a negative effect on it. Brand community commitment positively relates to brand commitment; it also mediates the effect of perceived visible heterogeneity and perceived value heterogeneity on brand commitment. Further, the positive effect of visible heterogeneity on brand community commitment is stronger for short-tenure members, but the negative effect of value heterogeneity is stronger for long-tenure members.

The findings suggest that managers should make efforts to foster visible heterogeneity and reduce value heterogeneity. In addition, managers are advised to emphasize the characteristics that carry different appeal for members of different tenure.

This research is one of the first few quantitative studies to examine the influence of brand community heterogeneity on community, and especially brand level outcomes. It extends the literature on the effect of brand community on brands and adds to the emerging heterogeneity view of OBCs.

The resource‐based view (RBV) of the firm has gained much attention in recent years as a means to understand how a strategic business unit obtains a sustainable competitive advantage. In this framework, several research studies have explored the relationships between resources/capabilities and firm performance. This paper seeks to extend this line of research by explicitly modeling the heterogeneity of such relations across firms in various different industries in exploring the interrelationships between capabilities and performance.

A unique latent structure regression model is developed to provide a discrete representation of this heterogeneity in terms of different clusters or groups of firms who employ different paths to achieve firm performance vis‐à‐vis alternative capabilities. An application of the proposed methodology to a sample of 216 US firms were provided.

Finds that the derived four group latent structure regression solution statistically dominates the one aggregate sample regression function. Substantive interpretation for the findings is provided.

The paper contributes to the understanding of the performance effects of investing in capabilities in the RBV framework, which has previously been lacking, especially in the areas of information technology capabilities.

People seem to function according to different models, which implies that in business and social sciences, heterogeneity is a rule rather than an exception. Researchers can investigate such heterogeneity through multigroup analysis (MGA). In the context of partial least squares path modeling (PLS-PM), MGA is currently applied to perform multiple comparisons of parameters across groups. However, this approach has significant drawbacks: first, the whole model is not considered when comparing groups, and second, the family-wise error rate is higher than the predefined significance level when the groups are indeed homogenous, leading to incorrect conclusions. Against this background, the purpose of this paper is to present and validate new MGA tests, which are applicable in the context of PLS-PM, and to compare their efficacy to existing approaches.

The authors propose two tests that adopt the squared Euclidean distance and the geodesic distance to compare the model-implied indicator correlation matrix across groups. The authors employ permutation to obtain the corresponding reference distribution to draw statistical inference about group differences. A Monte Carlo simulation provides insights into the sensitivity and specificity of both permutation tests and their performance, in comparison to existing approaches.

Both proposed tests provide a considerable degree of statistical power. However, the test based on the geodesic distance outperforms the test based on the squared Euclidean distance in this regard. Moreover, both proposed tests lead to rejection rates close to the predefined significance level in the case of no group differences. Hence, our proposed tests are more reliable than an uncontrolled repeated comparison approach.

Current guidelines on MGA in the context of PLS-PM should be extended by applying the proposed tests in an early phase of the analysis. Beyond our initial insights, more research is required to assess the performance of the proposed tests in different situations.

This paper contributes to the existing PLS-PM literature by proposing two new tests to assess multigroup differences. For the first time, this allows researchers to statistically compare a whole model across groups by applying a single statistical test.

Online collaboration in today's world is a topic of genuine interest to Internet researchers. The purpose of this paper is to explore the role of group knowledge heterogeneity (GKH) in open collaboration performance using the mediating mechanisms of group cognition (GC) and interaction to understand the determinants of the success of online open collaboration platforms.

Study findings are based on partial least squares structural equation modeling (PLS-SEM), the formal mediation test and moderating effect analysis from Wikipedia's 160 online open collaborative groups.

For online knowledge heterogeneous groups, open collaboration performance is mediated by both GC and collaborative interaction (COL). The mediating role of GC is weak, while the mediating role of COL is strengthened when knowledge complexity (KC) is higher. By dividing group interaction into COL and communicative interaction (COM), the authors also observed that COL is effective for online open collaboration, whereas COM is limited.

These findings suggest that for more heterogeneous large groups, group interaction would explain more variance in performance than GC, offering an in-depth understanding of the relationship between group heterogeneity and open collaboration performance, answering what determines the success of online open collaboration platforms as well as explaining the inconsistency in prior findings. In addition, this study expands the application of Interactive Team Cognition (ITC) theory to the online open collaboration context.

This paper aims to examine the evolution of a competitive market structure over time through the lens of competitive group membership dynamics.

A new hidden Markov modeling approach is devised that accounts for the three sources of competitive heterogeneity involving managerial strategy, corporate performance and the impact of strategy on performance. In addition, some observed “entry” and “exit” states are considered to model firms’ entry into and exit from the market. The proposed model is illustrated with an investigation of the US banking industry based on a data set created from the COMPUSTAT database. This paper estimated the model within the Bayesian framework and devised a reversible jump Markov chain Monte Carlo estimation procedure to determine the number of latent competitive groups and uncover the characteristics of each group.

This paper shows that the US banking industry, contrary to the prior findings of having a relatively stable structure, has, in fact, gone through dramatic changes in the past number of decades.

Contrary to prior work that has primarily focused on managerial strategy to study market evolutions, the competitive groups perspective accounts for all three sources of intra-industry competitive heterogeneity. In addition, unlike prior research, the analysis is not limited to firms remaining in the panel of study for the entire observation period. Such limitation results in missing the various changes that occur in the competitive market structure because of the new entrants or the struggling firms that do not survive in the market.

Companies are increasingly bringing personnel together into teams from different countries, physically and/or electronically, to develop products for multiple or worldwide markets. Called global new product teams (GNPTs), these groups face significant challenges, including cultural diversity. Differing cultural values can lead to conflict, misunderstanding, and inefficient work styles on the one hand, and strong idea generation and creative problem solving on the other. A study was conducted to identify team compositions that would optimize the effects of national culture so that product development outcomes are favorable. This began by developing a theoretical framework describing the impact of national culture on product development tasks. The framework was then translated into several mathematical models using analytical derivations and comparative statics. The models identify the levels and variances of culture values that maximize product development success by simultaneously considering four relevant dimensions of GNPT performance. Next, the utility of these models was tested by means of numerical simulations for a range of team scenarios. Concludes by drawing implications of the findings for managers and researchers.

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.

The purpose of this paper is to assess the change in the Italian and Spanish wage polarization degree in a time of economic crisis, taking into account the factors affecting labor force heterogeneity. Gender differences in the evolution of social fractures are considered by carrying out the analysis separately for males and females.

The approach by Palacios-Gonzánlez and García-Fernández (2012) on polarization is applied to the microdata provided by the EU Living Conditions Surveys (2007, 2010 and 2012). According to Palacios-Gonzánlez and García-Fernández’s approach, polarization is generated by two tendencies that contribute to the generation of social tension: the homogeneity or cohesion within group and the heterogeneity between groups. The following labor force characteristics are considered: gender, level of education, type of contract, occupational status and job status.

The results for Italy reveal a higher increase of polarization for women than for men from the perspective of the type of contract. In Spain, the wage polarization of women also increases more intensively compared to men from the perspectives of level of education, job status and occupational status, while in Italy the reduction of the wage polarization index by level of education can be related, above all, to an increase in overqualification of women.

While the empirical literature on polarization has made considerable investigation into employment and job polarization, this paper explores the rather less explored matter of wage polarization. Furthermore, particular attention is paid to the impact on polarization of the Great Recession.