Knowledge sharing is the deliberate act in which knowledge is made reusable through its transfer from one party to another. It is considered one of the main pillars of knowledge management. For a knowledge management initiative to succeed, a knowledge-sharing culture needs to be created and nurtured within the organisation. Since knowledge is power and no one is willing to give it away freely, there is a need to create a knowledge-sharing environment which takes into account the social and economic factors that influence knowledge sharing. In this paper, we look at the existing knowledge-sharing frameworks and propose a new one that takes into consideration the social and economic issues that might affect knowledge sharing within the organisation. The framework attributes the impact to five factors: the actors participating in the knowledge-sharing activity, the knowledge being shared, the channel used, the organisation concerned and the broader environmental factors. Specific barriers for each of the five sources are suggested.

Many organizations in the private or public sectors in Singapore have started to realize the importance of knowledge management in streamlining their operations. This realization stems from the fact that Singapore, as a small country with no natural resources, has to rely on human capital and its people in positioning itself for the new economy. Many organizations in the public sector are knowledge-intensive organizations and poor knowledge management practices might lead to high costs as a result of lost institutional memory, knowledge gaps and poor decisions. This paper discusses the implementation of knowledge management principles and practices in police work and their implications for policing. With the increased adoption of information technology and the increasing overall quality and IT competence of its police officers, the police organization is well positioned to leverage knowledge management principles and practices to better equip its officers with the necessary knowledge to discharge their duties.

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Abstract.Overcoming cultural resistance from a workforce and gaining sufficient buy-in from senior management are both critical to the successful implementation of Knowledge Management (KM) initiatives in any organization. The main purpose of this study is to identify an effective communication strategy at the onset of the implementation process, aimed at helping the workforce to comprehend the need for KM in the organization and to solicit maximum support from the senior management and staff alike. It is based on a case study of the KM initiatives in Singapore's Civil Service College, a training school for public officials. The strategy will also facilitate effective communication between staff so that effective knowledge sharing can take place and provide proactive and reactive communication, to achieve acceptance of and commitment to KM in the organization. The communication strategy was formulated using inputs collected from focus group discussions and observational field work.

Purpose This paper aims to investigate emerging trends in data analytics and knowledge management (KM) job market by using the knowledge, skills and abilities (KSA) framework. The findings from the study provide insights into curriculum development and academic program design. Design/methodology/approach This study traced and retrieved job ads on LinkedIn to understand how data analytics and KM interplay in terms of job functions, knowledge, skills and abilities required for jobs, as well as career progression. Conducting content analysis using text analytics and multiple correspondence analysis, this paper extends the framework of KSA proposed by Cegielski and Jones‐Farmer to the field of data analytics and KM. Findings Using content analysis, the study analyzes the requisite KSA that connect analytics to KM from the job demand perspective. While Kruskal–Wallis tests assist in examining the relationships between different types of KSA and company’s characteristics, multiple correspondence analysis (MCA) aids in reducing dimensions and representing the KSA data points in two-dimensional space to identify potential associations between levels of categorical variables. The results from the Kruskal–Wallis tests indicate a significant relationship between job experience levels and KSA. The MCA diagrams illustrate key distinctions between hard and soft skills in data across different experience levels. Practical implications The practical implications of the study are two-fold. First, the extended KSA framework can guide KM professionals with their career planning toward data analytics. Second, the findings can inform academic institutions with regard to broadening and refining their data analytics or KM curricula. Originality/value This paper is one of the first studies to investigate the connection between data analytics and KM from the job demand perspective. It contributes to the ongoing discussion and provides insights into curriculum development and academic program design.