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Purpose This paper aims to explore the differences in the level of knowledge sharing between co-workers in high versus low trust situations, for cognition-based trust and for affect-based trust as well as implicit and explicit knowledge. Design/methodology/approach The differences were examined through data provided by 102 professionals working for a financial organization in The Netherlands. Findings The differences in the level of knowledge sharing in high versus low trust situations are significant. The effect is larger for affect-based trust and for implicit knowledge. Research limitations/implications The survey has been conducted within one organization only. Practical implications Organizations should realize the importance of trust between their co-workers, and in general, there is much to gain by increasing the levels of trust between co-workers, as this will also increase knowledge sharing between co-workers. Originality/value Previous studies have not examined the situation of low trust and its effect on the level of knowledge sharing within a homogeneous group of co-workers.

Performance measurement is a fundamental instrument of management. For maintenance management, one of the key issues is to ensure the maintenance activities planned and executed have given the expected results. This can be facilitated by effective use of rigorously defined key performance indicators (KPI) that are able to measure important aspects of maintenance function. In this paper, an industrial survey was carried out to explore the use of performance measurement in maintenance management. Based on survey responses, analyses were performed on popularly used KPI's, how these KPI's are sourced or chosen; the influence of manufacturing environment and maintenance objectives on KPI choice and effective use of these KPI's in decision support and performance improvement. It was found that maintenance performance measurement is dominated by lagging indicators (equipment, maintenance cost and safety performance). There is lesser use of leading (maintenance work process) indicators. The results showed no direct correlations between the maintenance objectives pursued and the KPI used. Further analysis showed that only a minority of the companies have high percentage of decisions and changes triggered by KPI use and only a few are satisfied with their performance measurement systems. Correlation analysis showed a strong positive linear relationship between degree of satisfaction and process changes/decisions triggered by KPI use, with the least satisfied people having the least decisions and changes triggered by KPI use. The results indicates some ineffectiveness of performance measurement systems in driving performance improvement in industries.

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Objectives The main objectives of this article are 2-fold. First, we explore the application of multicriteria decision analysis (MCDA) methods in different areas of health care, particularly the adoption of various MCDA methods across health care decision making problems. Second, we report on the publication trends on the application of MCDA methods in health care. Method PubMed was searched for literature from 1960 to 2019 in the English language. A wide range of keywords was used to retrieve relevant studies. The literature search was performed in September 2019. Articles were included only if they have reported an MCDA case in health care. Results and Conclusion The search yielded 8,318 abstracts, of which 158 fulfilled the inclusion criteria and were considered for further analysis. Hybrid methods are the most widely used methods in health care decision making problems. When it comes to single methods, analytic hierarchy process (AHP) is the most widely used method followed by TOPSIS (technique for order preference by similarity to ideal solution), multiattribute utility theory, goal programming, EVIDEM (evidence and value: impact on decision making), evidential reasoning, discrete choice experiment, and so on. Interestingly, the usage of hybrid methods has been high in recent years. AHP is most widely applied in screening and diagnosing and followed by treatment, medical devices, resource allocation, and so on. Furthermore, treatment, screening and diagnosing, medical devices, and drug development and assessment got more attention in the MCDA context. It is indicated that the application of MCDA methods to health care decision making problem is determined by the nature and complexity of the health care problem. However, guidelines and tools exist that assist in the selection of an MCDA method.