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The authors examine whether or not applicants and recipients of federal disability insurance (DI) inflate their self-assessed health (SAH) problems relative to others. To do this, the authors employ a technique which uses anchoring vignettes. This approach allows them to examine how various cohorts of the population interpret survey questions associated with subjective self-assessments of health. The results of the analysis suggest that DI participants do inflate the severity of a given health problem, but by a small but significant degree. This tendency to exaggerate the severity of disability problems is much more apparent among those with more education (especially those with a college degree). In contrast, racial minorities tend to underestimate severity ratings for a given disability vignette when compared to their white peers.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

Case study research has been applied across numerous fields and provides an established methodology for exploring and understanding various research contexts. This paper aims to aid in developing methodological rigor by investigating the approaches of establishing validity and reliability.

Based on a systematic review of relevant literature, this paper catalogs the use of validity and reliability measures within academic publications between 2008 and 2018. The review analyzes case study research across 15 peer-reviewed journals (total of 1,372 articles) and highlights the application of validity and reliability measures.

The evidence of the systematic literature review suggests that validity measures appear well established and widely reported within case study–based research articles. However, measures and test procedures related to research reliability appear underrepresented within analyzed articles.

As shown by the presented results, there is a need for more significant reporting of the procedures used related to research reliability. Toward this, the features of a robust case study protocol are defined and discussed.

Performance framework (PF) is a well-established practice to measure innovation performance and identify improvement opportunities. However, whether PFs academic research are applicable to companies remains unclear, as well as their support in the definition of improvement actions. This study aims to present the implementation and assessment of a new and updated PF proposed in previous research in a real industrial context.

The PF was implemented through an in-depth case study carried out in a European machinery manufacturer and further assessed by practitioners.

The results indicate that the PF enabled the creation of a multidimensional view of the innovation performance and the definition of improvement projects in the company. Additionally, the findings also reveal an overall positive assessment of the PF by senior managers who work with the innovation process.

As a case study, this research is inherently limited in the extent to which results can be generalised. Thus, the analyses are reductive and rationalising. Future research is needed to assess the replicability of the PF.

The study's practical contribution is based on the combination of insights and steps that provide a straightforward and actionable approach for the company to improve performance.

This study aims to advance the importance of implementing the new and updated PF after its proposition, which is often overlooked in preceding research. Furthermore, the assessment of the PF also enables to infer its value to the company's employees.

This paper uses the complex proportionality assessment (COPRAS) method to examine the driving factors of Industry 4.0 (I4) technologies for lean implementation in small and medium-sized enterprises (SMEs).

Adopting I4 technology is imperative for SMEs seeking to maintain competitiveness within the manufacturing sector. A thorough understanding of the driving factors involved is required to support the implementation of I4. For this objective, the multi-criteria decision-making (MCDM) tool COPRAS was used to efficiently analyze and rank these driving elements based on their importance. These factors can help small and medium-sized firms (SMEs) prioritize their efforts and investments in I4 technologies for lean implementation.

This study evaluates and prioritizes the nine I4 factors according to the perceptions of SMEs. The ranking offers significant insights into the factors SMEs consider more accessible and effective when adopting I4 technologies.

The author's original contribution is to examine I4 driving factors for lean implementation in SMEs using COPRAS.