In this paper, we examine a possible application of ordered weighted average (OWA for short) aggregation operators in the insurance industry. Aggregation operators are essential tools in decision-making when a single value is needed instead of a couple of features. Information aggregation necessarily leads to information loss, at least to a specific extent. Whether we concentrate on extreme values or middle terms, there can be cases when the most important piece of the puzzle is missing. Although the simple or weighted mean considers all the values there is a drawback: the values get the same weight regardless of their magnitude. One possible solution to this issue is the application of the so-called Ordered Weighted Averaging (OWA) operators. This is a broad class of aggregation methods, including the previously mentioned average as a special case. Moreover, using a proper parameter (the so-called orness) one can express the risk awareness of the decision-maker. Using real-life statistical data, we provide a simple model of the decision-making process of insurance companies. The model offers a decision-supporting tool for companies.

Many previous studies find no significant effect of health insurance on health outcome in rural areas of China. Many researchers believe this could be because of the characteristics of health care provision in those areas. In this paper, we aim to examine if urbanization will change the situation. Our research question focuses on if urbanization will change the participation and performance of health insurance on health outcome in a positive direction. Using a longitudinal sample drawn from the China Health and Nutrition Survey (CHNS), we employed multiple estimation strategies for multiple waves to handle the potential selection bias. We find that urbanization factors such as population density, transportations and housing are associated with probability of insurance participation. That is, urbanization related factors tend to increase people’s willingness of insurance participation. We also conclude that urbanization improves the performance of insurance on self-reported health outcome. Results show that the health insurance has a significant positive impact on health production in urbanized areas. Health insurance in general increases the probability of health care utilization for all areas. However, it does not lead to a significant improvement in the health outcomes in under urbanized areas because of the health provision quality or characteristics of health insurance coverage in those areas.

This study aims to identify gaps in Indonesia’s national social health insurance scheme (Jaminan Kesehatan Nasional or JKN) in meeting the right to health for disabled persons in the country and to propose strategies to mitigate the gaps. This study employed descriptive qualitative methodologies. A questionnaire survey and structured interviews were undertaken from the period of October to December 2021, with a purposive sample of 317 disabled persons at their working age. Data collection also included on-site observations to sample of healthcare providers in six provinces and focused group discussions with key stakeholders. This study found that JKN is the primary source of hope for disabled persons. Nevertheless, approximately ten percent of disabled persons have been omitted from the scheme. Moreover, respondents of the survey expressed notably lower satisfaction level compared to the national average. Meanwhile, 25% of them also reported that JKN did not cover certain disability-specific benefits. The findings suggest that the national social health insurance scheme is not well prepared to offer disability-inclusive services. Thereby, policymakers should implement various interventions to improve the admission processes for disabled persons and to develop a system to identify disabled members based on their specific disabilities. Additionally, stipulating standards for disability-friendly minimum services for healthcare providers and incorporating the standards into the credentialing systems, providing regular training on disability-friendly services for healthcare personnel, also enhancing benefits coverage for disabled members in the Indonesian Case Base Groups (INA-CBGs) are the necessary strategies to mitigate the gaps.

The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.

This article presents a comparative analysis and characteristics of the pension insurance systems of foreign countries, namely Germany, Sweden, Estonia, Poland, France with the aim of implementing their effective and noteworthy experience in Ukraine. The key indicators of the characteristics of the pension systems of these countries and Ukraine (amount of insurance contributions to the public pension fund; retirement age; insurance period; the ratio of the average pension to the average wage) have been studied and analyzed. Having examined these indicators, the authors came to the conclusion that the general trend in most countries of the world is that they guarantee only a minimum pension, which is caused by the increase in the share of pensioners in society. To solve the demographic problems affecting pension provision, the most countries increase the retirement age and provide financial incentives to stimulate citizens to work after the retirement age. To increase the pension, there are pension accumulation tools at the expense of the employer or at the expense of one’s own funds. Following the example of foreign countries, the directions for improving the pension insurance system of Ukraine were allocated.