Knowledge Management (KM) has become critical in today's highly competitive, uncertain, and rapidly changing business environment. The objective of this study is to measure the effects of knowledge management processes (knowledge acquisition, knowledge sharing, knowledge creation and knowledge retention) and knowledge management approaches (social networks, codification and personalization) on job satisfaction and examines how they increase employees' work performance. A theoretical model based on KM processes and approaches is proposed. It is empirically tested with structural equation modeling (SEM) and partial least squares (PLS) of survey data collected from employees of the King Fahd National Library in Jeddah, Saudi Arabia. The analysis showed that there is a significant and positive impact of KM processes and approaches on job satisfaction and work performance. Knowledge sharing, knowledge retention, codification and personalization approaches have significant impacts on job satisfaction, and knowledge acquisition, knowledge creation and a social network approach have no significant impacts on job satisfaction. Managers are advised to implement KM activities in their organizations to improve knowledge worker performance and the welfare of employees at work. This is the first study that theoretically examines the effect of knowledge management processes and knowledge management approaches on 'soft' human issues such as the job satisfaction and work performance of individual employees in an academic library.

PurposeIn today's business setting, the business analytic capability, data-driven culture and product development features are highly pronounced in light of the firm's competitive advantage. Though widespread attention has been given to the above concepts, there hasn't been much research done on how it could support achieving competitive advantage.Design/methodology/approachThis research strongly lies on the theoretical background and empirically tests the hypothesized relationships. The primary survey of 272 responses was analysed by using the partial least squares structural equation modelling (PLS-SEM).FindingsThe findings of this study show a significant relationship for the constructs in the research model except for the third hypothesis. Accordingly, the firm's data-driven culture does not have a significant impact on new product newness.Originality/valueThis study empirically tests the business analytics capability, data-driven culture, and new product development features in the context of a firm's competitive advantage. The findings of this study contribute to the theoretical, practical and managerial aspects of this field.

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Purpose The emerging attention in big data has led businesses to improve big data analytics talent capability to enrich firm performance. The big data capability pays off for some companies but not for all, and it appears that very few have achieved a big impact through big data. Rooted in the latest literature on the knowledge-based view, IT capability, big data talent capability and business intelligence, this study aims to examine how big data talent capability impact on business intelligence infrastructure to achieve firm performance. Design/methodology/approach The primary survey data of 272 IT managers and big data analysts from Chinese firms was analyzed by using the structural equation modeling and partial least squares (Smart PLS 3.0). The analysis uncovers a positive and significant relationship in the proposed model. Findings The finding shows that the big data analytics talent capability positively impacts on business intelligence infrastructure that in turn directs to achieve firm financial and marketing performance. Originality/value This study theorized on the multitheoretic lenses, and findings suggest the managers and industry practitioners to develop business intelligence infrastructure capabilities from big data analytics talent capability.

Development of a big data-based m-Health application using a design science framework can support the effective and comprehensive plan of the government of Saudi Arabia for preventing and managing Hajj-related health issues. Our proposed model for developing and designing a big data-based m-Health application could provide direction for developing the most advanced solution for dealing with the Hajj-related health issues in the future.