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The purpose of this paper is to test and develop a method for generation and selection of six sigma projects. This is done by testing the use of the generation and selection method for six sigma projects (GSM_SSP) in a Brazilian manufacturing industry with the participation of managers, aiming to gather the user’s perspective and improvement opportunities for the approach itself.

The work adopts the action research (AR) approach once the researchers were busily involved in the training, implementation and use of the GSM_SSP. The intervention was performed in on a series of 15 workshops, with a group of managers, during six months.

The application of the eight steps of the GSM_SSP approach assisted the company’s management team to generate nine project candidates and also to select three six sigma projects. This study also finds and discusses barriers and lessons learned used to improve the GSM_SSP.

This study presents an example of how six sigma project generation and selection has been applied to a manufacturing industry by adapting AR to the process using the eight steps of GSM_SSP, demonstrating how the management team was involved. This study should be replicated in different companies because AR is limited in its generalization.

To the best of the authors’ knowledge, this study represents the first use of AR methodology in six sigma project selection. This study contributes a method that can generate and select six sigma projects. In doing so, the research offers a simple approach that can be used by managers. In addition, the steps of the approach before selection were explored.

The study set out to understand how the regional competitiveness index (RCI) in the department of Ancash related to the human development index (HDI) from 2008 to 2021. For a more complete understanding of the findings, each component or dimension of the RCI was analyzed. Ancash's HDI and its competitiveness index over a 14-year period were used as the population for this applied, longitudinal, descriptive-correlational study, which was based on secondary data extracted from the “Instituto Nacional de Estadística e Informática” (INEI) and business school of the Pontificia Universidad Católica del Perú (CENTRUM) statistical databases. Multiple linear regression was used to find the relationship. The research found a strong and positive correlation between regional competitiveness and human development between 2008 and 2021. No correlations were found between the HDI and the health, education, employment, or institutional dimensions of regional competitiveness, but direct and significant correlations were established between the economic environment and the HDI and between the infrastructure dimension and the HDI.

Employment-related measures play a significant part in preventive and mitigative social policies. The importance of these actions is especially emphasised in times of crisis. This paper provides empirical insights into employment-related measures implemented in a sample of OECD countries as a response to the COVID-19 crisis in 2020. Furthermore, it addresses the continuity of the measures by July 2022.

The research applies and further develops a capability approach in the COVID-19 context to provide a theoretically informed empirical understanding of the implemented employment related measures.

The results indicate that countries expanded the coverage of previous preventive and mitigative employment measures horizontally and vertically while also introducing new schemes to protect workers. The main conclusions suggest that most employment-related measures (65.5%) were preventive aiming at saving jobs and broadening peoples capabilities with bridging measures during the crisis. The employment measures served first as an emergency aid. However, most measures were recalibrated and changed incrementally toward 2022.

The data consisted major employment-related measures and changes in social policies the studied countries. The authors focussed the examination on governmental-level measures. Thus, sub-national or sector-specific responses, for example tripartite agreements in certain employment sectors or social transfers in certain areas, were excluded.

The way in which welfare states reacted to employment problems during the COVID-19 pandemic may have an impact on how governments approach social policies in the future. The capability approach exhibits a pronounced strength by facilitating the establishment of sustainable trajectories for social policy and welfare services.

The capability approach embracing the preactive and proactive role of social policies lends a unique perspective on public policies.

In the big data era, image compression is of significant importance in today’s world. Importantly, compression of large sized images is required for everyday tasks; including electronic data communications and internet transactions. However, two important measures should be considered for any compression algorithm: the compression factor and the quality of the decompressed image. In this paper, we use Frei-Chen bases technique and the Modified Run Length Encoding (RLE) to compress images. The Frei-Chen bases technique is applied at the first stage in which the average subspace is applied to each 3 × 3 block. Those blocks with the highest energy are replaced by a single value that represents the average value of the pixels in the corresponding block. Even though Frei-Chen bases technique provides lossy compression, it maintains the main characteristics of the image. Additionally, the Frei-Chen bases technique enhances the compression factor, making it advantageous to use. In the second stage, RLE is applied to further increase the compression factor. The goal of using RLE is to enhance the compression factor without adding any distortion to the resultant decompressed image. Integrating RLE with Frei-Chen bases technique, as described in the proposed algorithm, ensures high quality decompressed images and high compression rate. The results of the proposed algorithms are shown to be comparable in quality and performance with other existing methods.

This study aims to map and analyze health-care pricing information research. This work highlights current gap in pricing information research in health care and proposes future research avenues to academia and industry professionals.

A bibliometric method was adopted to analyze extant literature on pricing information asymmetry. Semistructured interviews were conducted with key stakeholders in health care to triangulate the findings.

Pricing information is crucial for all stakeholders including health-care consumers, providers and regulators. The popular research areas were the rising health-care cost, cost-saving, outcome-based pricing, price based on service supply and demand, insurance and out-of-pocket spending. Cost–quality perceived linkages, cost–demand correlation in health-care service and cost–price interlinked drivers were the dominant themes in extant literature. The study highlighted that pricing information asymmetry pushed patients from weaker sections into a debt trap due to unplanned out-of-pocket health-care expenses. The study suggests areas of research to minimize this pricing information asymmetry.

The emerging themes in health pricing asymmetry will help key stakeholders to identify areas for improvement and take remedial actions in the health-care domain.

This study is a pioneering effort to summarize extant literature published in the health-care information pricing domain and analyze it from a bibliometric perspective. The study also triangulates the finding with primary data from key stakeholders and highlights emerging research areas.