Ginevičius, Romualdas

The state of socio-economic phenomena is usually reflected by a large number of indicators of various importance. In order to quantitatively assess the state of such phenomena, it is necessary to know both the values of the indicators and the weights. When there are many indicators, adequate determination of weights becomes complicated, since experts can no longer mentally weigh the mutual relations of importance of all indicators. The solution of the problem is facilitated by determining the weights in two stages. In the first, the importance ranks of the indicators are obtained, and in the second, based on these ranks, the weights. Both the importance ranks and the weights are determined by experts, therefore it is necessary to check the consistency of their opinions. Today, methods have been developed to determine the consistency of expert assessment of indicator weights, and there is almost no talk about checking the consistency of expert assessment of importance ranks. Methods for determining the consistency of expert assessment of indicator weights are not suitable here, since the expert determines the weights quantitatively, i.e. in numbers, and the importance – qualitatively - indicates which of the two indicators is more important. The proposed methodology, named DeA (definition of agreement), is based on the ratio of the difference in the sums of indicators estimated with identical estimates to the total number of estimates. The compatibility criterion obtained in this way shows the minimum number of identical estimates that must be present in order for the experts' opinions to be consistent.

This paper aims to explore the intricate relationships between general trust in technology, perceived benefits, perceived threats, and future intentions to use wireless technology. The study employs Structural Equation Modelling (SEM) to analyse data collected from a representative sample of 1010 Polish respondents. The methodology is rooted in the Technology Acceptance Model (TAM), incorporating modifications to accommodate the specifics of wireless technology acceptance. The results affirm significant positive relationships between general trust in technology and perceived benefits, as well as a negative association between general trust and perceived threats. Interestingly, while perceived threats were expected to negatively impact future usage intentions, this study finds that the positive perceptions of benefits substantially outweigh the concerns related to threats, leading to a strong intention to use future technologies. This study extends the TAM by incorporating trust and perceived threats into the model, providing a more comprehensive understanding of the factors that drive technology acceptance, particularly in the context of next-generation wireless networks. This highlights the pivotal role of trust in moderating the perceived risks associated with new technologies. Demonstrating the importance of enhancing public trust and accurately communicating the benefits of new technologies, this research suggests strategies that could mitigate public apprehension and enhance the adoption rates of new technological systems.

The aim of this article is to propose a methodology to determine an appropriate period for the quantitative evaluation of the development of SER as a process and to validate it using a real-world example. There has been an increasing the analysis and assessment of the state of socio-economic systems (SES) for the purpose of managing their targeted development are gaining importance. The adequacy of such analysis and assessment is largely dependent on the duration of the period under consideration. Recently, the analysis and assessment of the state of socioeconomic systems (SES) for the purpose of managing their targeted development have gained importance. The accuracy of such analysis and assessment depends a lot on the duration of the period under consideration. In the absence of a clearly defined period, time spans of varying durations are used, ranging from a few years to several decades. The determination of an appropriate period is based on the impact of past development periods (years) on recent years. Studies have shown that this influence is strong (r = 0.85–0.95) and can be described using both linear and nonlinear regression models. The appropriate analysis period can be identified on the basis of the selected correlation coefficient between the most recent (base) year and the development observed in the preceding years. The optimal analysis period, expressed in years, corresponds to the point at which this relationship remains statistically significant.

Research on social problems of various natures is gaining more and more attention. Their primary tool is surveying. Various computer programs have been developed to process and analyse the results. On the other hand, the characteristics they calculate may be used only for specific purposes. Their main drawback is that they must provide a generalized picture of the problem in question, i.e., the whole remains unclear. Without this, analogous objects cannot be compared with each other. The proposed methodology, which has the acronym QEQS (Quantitative Evaluation of Quantitative Sizes), provides such opportunities. Its main advantages are that it is possible to combine an unlimited number of answers to questions into a single summarizing size index; any range of scales may be used for assessment; consider the importance of different options for answering the questions; determines not only the aggregated value of the answers to the individual queries but also the index that aggregates them.

The existing functional dependencies between the measured values of quality indicators and their assessment on the dimensionless scale that were used to assess qualimetry objects of various nature have been analyzed. It has been shown that, as a rule, non-linear dependencies should be used for the objective assessment of qualimetry objects. The main task of the researcher is to choose the type of nonlinear dependence, this requires additional scientific research. The tool for choosing one or another non-linear dependence is the understanding of the physical essence of the qualimetry object, that is, the understanding of the regularities of the relationship between the measured value of qualimetry indicators and their assessment. For this, it is important to use methods of expert assessments, because, as a rule, such regularities are unknown. The functional dependence that is used to obtain assessments of indicators of the state of occupational safety in production is stepwise and includes a shape parameter. When the shape parameter changes, the curvature of the dependence changes, thereby changing the assessment on the dimensionless scale. This feature of the applied dependence makes it possible to develop a universal technique, that is, by changing the shape parameter, this dependence can be applied to various indicators of labor safety in any production. As an example, the article examines the machine-building industry and assesses the most dangerous factors. A step-by-step technique for determining a complex indicator of occupational safety in production has been developed, and its effectiveness and universality have been shown by an example of measured numerical values of dangerous factors.

The commercial performance of a construction company (CC) largely depends on the planned work programme. The annual CC work programme is a set of objects of a specific purpose and structure (a building system). The programme has the following characteristics: first, the number of objects; second, the construction technologies provided for in the projects (fully prefabricated, monolithic, brick, etc.); third, the variation of work scopes among objects; and fourth, the construction technology. These CC work programme features are interrelated, i.e., aligned with each other, forming the technological structure (TS) of the CC work programme. Once these attributes were formalised, four partial indicators were obtained: the first assesses the variation in construction objects’ sizes; the second — their number; the third — the number of applied technologies; and the fourth — the technologies. The importance of these indicators was assessed to combine them into an indicator of the technological structure of the annual CC work programme. Its quantitative assessment has scientific and practical importance, providing an opportunity to analyse its impact on the results of commercial activities, to improve the organisational management structure of the company, etc.

The intensive use of non-renewable production resources and the associated growing environmental pollution forces us to look for new methods of halting these negative trends. Circular economy is one such method. This phenomenon is the subject of numerous studies attempting to assess its condition at both the micro and macro levels, the implementation of circular economy strategies, its environmental impact, the context of waste generation, etc. On the other hand, little attention is paid to assessing its efficiency. Technological efficiency, i.e., the relationship between material footprint and waste generation, is of particular importance, since the amount of waste generated primarily depends on the technology used at the time of production. Thus, this paper aims to analyse and assess the development of technological efficiency over a certain period of time. Further, it is necessary not only to build on the results of development at the end of this period, but also to assess the extent of the changes that have taken place during it in order to reflect the actual state of affairs. Thus, the final result takes into account both the intensity of the development of technological efficiency and the importance of its current state to the overall development process.

The aim of the conducted research was to assess the attitude of the Polish society towards the use of artificial intelligence in medical diagnostics. In the research process, we sought answers to three research questions: how trust in the use of AI for medical diagnostics can be measured; if societal openness to technology determines trust in the use of AI for medical diagnostics purposes; and if a higher level of trust in the use of AI for medical diagnostics influences the potential improvement in the quality of medical diagnostics as perceived by Poles. The authors' particular focus was on the following three constructs and the relationships between them: openness to new technologies (OP), willingness to trust AI in medical diagnostics (T), and perceived impact of AI application on the quality of medical diagnostic services (PI). A survey was conducted on a representative sample of 1063 Polish respondents to seek answers to the above questions. The survey was conducted using the CATI technique.

The conventional approach to assessing the developmental level of any socioeconomic system (SES) is to consider only its state in a given year. However, this approach does not adequately reflect the dynamic and complex nature of SES, which are inherently unstable due to their inertia. In other words, the development indicators at any point in time (year) of the considered period (CP) largely depend on the results of the development that occurred in the previous periods. This makes it difficult to adequately quantify the development of SES over a specific period. This paper presents a novel methodology for obtaining the SES sustained development index by combining the values of two parameters – intensity and uniformity. Since the former must take into account the totality of both positive and negative changes that occurred during the CP, correlation regression analysis is used to calculate the values. The latter is reflected by the value relationships of actual changes in individual periods of CP with SES development taking place without any deviations. Given that the importance of intensity and uniformity for sustained development is not the same, multi-criteria method is used to combine the values in a representative manner.

In the European Union (EU), as a global economic community, there are countries with very different levels of economic development. Therefore, it takes place unevenly – some countries develop intensively, but with significant changes in it, others – stably, without significant changes, but not intensively, etc. In such a situation, it is important to determine adequately the current state of economic development. It is an integral quantity that combines both development changes and intensity. These two components of development form two of its partial indicators. Combined into one size, they comprehensively reflect the current situation of the country’s economic development. Development refers to a process, so it must be assessed not on the basis of the state at the end of the period under consideration, but on the whole of this period. The presentation of development in the sense of recent years does not reflect the overall development process, based on the economic development of countries 2018–2022. Their ranks are determined by the results of the comprehensive assessment. Since they do not adequately reflect the current situation, the countries were combined into homogeneous groups, where countries with close values of the economic development indicator were located. This allows to highlight the economic development trends of EU countries.