Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
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.
This paper had developed an effective information technology (IT) vendor selection model for banking & financial services industries (BFSI). For any business, profitability and growth depends on the right vendor selection in their purchase process. This paper identifies ten most influencing and important criteria with 43 sub-criteria to comprehend the vendor selection process. Furthermore, the authors developed a vendor selection score model using Structural Equation Modelling (SEM) and Analytic Hierarchy Process (AHP). This article intends to inform practice and conclude with practical recommendations to BFSI for vendor selection. The proposed composite technique identified the most eligible vendor to meet up with the buyer’s strategies. This article suggests the most desirable vendor for the required benefit. Vendor 1 (Silverlake) with a score of 44% promised to be the most recommended one that also performed consistently in the sensitivity test.
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