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Knowledge is the most important component of sustainable organizational growth and economic performance. This meta‐analysis aims to summarize the determinants of individuals' knowledge sharing (KS) intentions and behaviors in organizations.

The authors organize the knowledge sharing antecedents investigated in 46 studies (n≈10,487, median n=172) into three categories, i.e. knowledge sharer intention and attitude (four variables); rewards for KS (three variables); and organizational culture (nine variables).

Variables in all three antecedent categories positively contribute to KS intentions and behaviors; high between‐study variability exists, and the fail‐safe n statistic suggests the observed effects are robust against a “file drawer” (missing study) bias. Moderator results suggest that motivating KS is easier in collectivist, as opposed to individualist, cultures.

In most of the studies included in this meta‐analysis, participants volunteered to share knowledge with researchers. Hence, an important threat to validity in the existing research is a potential “cooperation bias” in which participants likely overestimate their willingness to share knowledge. Future KS research should investigate the dark underbelly of knowledge activities in organizations, including investigations of knowledge hoarding, withholding of knowledge to gain personal advantage, and “contributing” worthless information to gain (through gaming) personal payoffs.

The meta‐analysis results herein contribute to the KS literature by identifying the determinants of KS, and an important potential limitation of much existing KS research.

The cultivation and maintenance of a brand is becoming increasingly important as politicians seek to connect with constituents. Through the lens of social cognition and group dynamics, this paper aims to understand the impact of evaluations of politician brands on voter intentions.

Three studies utilize the social cognition constructs of warmth and competence from the stereotype content model (SCM) and Brands as Intentional Agents Framework (BIAF) to evaluate the impact of brand perceptions on voting intentions, comparing fit between the models. The first study establishes the impact of these perceptions on existing politicians. The second study replicates these effects while controlling for party affiliation and extraneous factors and explicitly studies politicians as brands. The third study examines the formation of perceptions and assumptions when full information is unavailable.

Social cognition and group dynamics drive responses to politician brands. The data herein support perceptions of warmth and competence as significant predictors of voting intentions. Dependent upon whether the politician is being evaluated as a brand or a person, BIAF or SCM predicts the dimension that will be most impactful. These patterns persist in the absence of full information. As expected, voting intentions increased significantly when the voter was of the same (vs opposing) party as that of the candidate.

Conducted during an election year, evaluations of politicians are susceptible to the current political climate and the predominantly two party political system in which the studies were conducted. The design of Studies 2 and 3 addresses some of these limitations. Results point toward the interrelated nature of warmth and competence perceptions and the usefulness of applying both BIAF and SCM to understand how voters view politicians and the drivers of voting intentions.

This study evidences the depth to which perceptions of candidates impact voting intent, establishing politicians’ unique position as both brands and people. These findings prove useful in interpreting the outcome of elections this year, and beyond.

Expanding a limited body of existing research, this work contributes to our understanding of the application of SCM within the context of politician brands. As the first concurrent investigation of SCM and BIAF, these findings are of value to political strategists and academics alike. The contribution is augmented by the consideration of the impact of party affiliation and missing information.

This study aims to investigate the key elements that influence knowledge sharing practice, primarily the relationship between knowledge sharing practice and organizational performance within the oil and gas (OG) industry.

A sample of 203 responses was collected from the OG industry using an online questionnaire. Data were analyzed using applied structural equation modeling to validate the model and test the hypotheses.

The results indicate that significant relationships exist among the model constructs. These findings provide a better understanding of the factors that influence knowledge sharing practices within the OG industry. These findings prove that knowledge sharing practices positively impact organizational performance through cost reduction, organization growth and intangible benefits.

This study demonstrates that organizations in the OG industry may increase performance by adopting knowledge sharing practices. This study also provides practitioners with important information to enhance knowledge sharing practice within their organizations. For instance, managers should focus on Web 2.0 and other knowledge sharing systems to facilitate both tacit and explicit knowledge sharing. The findings provide empirical evidence that knowledge sharing practices allow organizations to transfer expert knowledge to younger generations of employees. As a result, organizations will be able to capture knowledge and alleviate the negative impact of high staff turnover within the OG industry.

The lack of knowledge sharing practices and the eminent loss of technical knowledge within the (OG) industry, because of retirements and turnover, create a difficult challenge for practitioners. Research on knowledge sharing within the OG industry is limited. Therefore, this study provides an in-depth analysis regarding the critical knowledge sharing practices and valuable information to researcher and practitioners’ knowledge sharing practices within the OG industry.