Learning from experience to improve future infrastructure public-private partnerships is a focal issue for policy makers, financiers, implementers, and private sector stakeholders. An extensive body of case studies and “lessons learned” aims to improve the likelihood of success and attempts to avoid future contract failures across sectors and geographies. This paper examines whether countries do, indeed, learn from experience to improve the probability of success of public-private partnerships at the national level. The purview of the paper is not to diagnose learning across all aspects of public-private partnerships globally, but rather to focus on whether experience has an effect on the most extreme cases of public-private partnership contract failure, premature contract cancellation. The analysis utilizes mixed-effects probit regression combined with spline models to test empirically whether general public-private partnership experience has an impact on reducing the chances of contract cancellation for future projects. The results confirm what the market intuitively knows, that is, that public-private partnership experience reduces the likelihood of contract cancellation. But the results also provide a perhaps less intuitive finding: the benefits of learning are typically concentrated in the first few public-private partnership deals. Moreover, the results show that the probability of cancellation varies across sectors and suggests the relative complexity of water public-private partnerships compared with energy and transport projects. An estimated $1.5 billion per year could have been saved with interventions and support to reduce cancellations in less experienced countries (those with fewer than 23 prior public-private partnerships).

Ride-hailing or private hire has taken the Singapore transport network by storm in the past few years. Singapore has had more than three revisions of its ride-hailing regulation in the six years since the arrival of the disruptive technology. Often quoted in the list of cities with commendable public transport policy, Singapore still manages to find a viable and significant position for ride-hailing. Cities from around the world are all searching for a model of regulation for ride-hailing that can be elevated as a benchmark. Singapore, to a large extent, has formulated a successful model based on current market parameters and, more importantly, an adaptive one that evolves constantly with the constantly disruptive technology. The experts and regulators of the Singapore transport sector were interviewed in depth, tapping into their opinions and technocratic commentaries on the city-state’s Point-to-Point, or P2P, sector regulation. The data were analyzed using the three-element model of social practice theory as an alternative to conventional behavioral studies, thereby eliminating bias on the commuters and rather shifting focus to the practice. Content analysis utilizing QDA is executed for categorization through fine-level inductive matrix coding to elaborate upon the policy derivatives of the Singapore model. The unique addition of the research to ride-hailing policy is the comprehension of the commonalities and patterns across industrial and technological disruption, practice and policy irrespective of sectoral variations, thanks to the utilization of social practice theory. The first-of-its-kind policy exercise in the sector can be repeated for any city, which is a direct testament to the simplicity and exhaustivity of the methodology, benefiting both operators and investors through equitable policy formulation.

Several studies have discussed the benefits of blockchain in human resources management (HRM) policies to support the efficiency of HRM routine practices in organizations. The discussion ranges from selection and recruitment to employee separation. With the growing interest in digital application usage, research focused on utilization and effective measurement is needed. However, the existing literature review on blockchain-based HRM practices linked to cost efficiency still needs to be improved. Hence, this study aims to review current studies on blockchain human resources management systematically. This study investigates the trends in blockchain application usage in terms of practices, methodologies, and settings. This study used a literature survey and Publish or Perish software with Google Scholar and Scopus as the databases. 123 articles published in 19 journals from 2010 to 2022 were selected. This study used systematic data to reveal trends in HRM practices and qualitative inductive analysis to define relevant themes within the topic. The results show that blockchain applications for efficiency are used mainly in the recruitment and selection process, ranging from personal data verification to the quality of decision-making in skill development and maintenance. Five HRM practices have been discussed, indicating potential explorative and exploitative future research to improve the effectiveness of using blockchain in HRM practices.

Human resource management practices are crucial, especially in the private healthcare sector. This could be because managing personnel in the healthcare sector is particularly challenging; therefore, meeting every employee's needs is crucial. Recently, the healthcare sector has experienced a scarcity and unbalanced distribution of employees due to job turnover. In addition, employee performance in the private healthcare sector has shown a slight drop due to the dissatisfaction of employees toward human resource practices such as unattractive compensation and rewards packages, bias in performance appraisal, lack of training and development, and many more. Therefore, this study is conducted to examine the impact of human resource practices on employees' job performance. Specifically, there are three main human resource practices observed as factors that contribute to an employee's job performance. The three human resource practices are compensation and benefits, performance appraisal, and training and development. There were four private hospitals operating in Selangor, Malaysia, chosen as a sample for this study. The private hospitals are KPJ Selangor Specialist Hospital, Columbia Asia Hospital Puchong, Assunta Hospital PJ, and Sunway Medical Centre. Out of these four private hospitals, there were about 291 employees working at the front desk: nurses, clinical workers, and administration staff were chosen as respondents in this study. The questionnaires were distributed to the respondents by hand. The data collected was analyzed using SPSS version 29. The findings indicate that employee job performance in Malaysian private hospitals is positively correlated with compensation and benefits. Employees feel motivated by compensation, which encourages them to increase their production and work more efficiently. Additionally, the findings also suggest that performance appraisal and training and development significantly contribute to employee job performance.