A myriad of diverse factors affect the contemporary business environment and all business areas, causing organisations to innovate new business models, or to use innovations to navigate the complexity of contemporary HRM practice successfully. Despite the plenitude of notable studies, a particular theoretical gap exists regarding the innovation’s impact on particular HRM practices and on understanding how multiple-criteria decision-making (MCDM) methods can be effectively applied in the context of human resource management (HRM) to address important aspects of successful practices and prioritise the considered alternative solutions. Recognising the potential of the MCDM field highlighted the possibility of involving the MCDM methods in detecting the most influential and innovative HRM practices and defining the rank of companies that are most successful in applying them. The innovative MCDM approach proposed here utilises the CRITIC (CRiteria Importance Through Intercriteria Correlation) method and PIPRECIA-S (Simple PIvot Pairwise RElative Criteria Importance Assessment) method for prioritising innovative HRM practices, and the COBRA (COmprehensive Distance Based RAnking) method for assessing the companies under evaluation. The research, which involved 21 respondent experts from the HRM field and 12 companies from the Republic of Serbia, revealed that employee participation is the most significant innovative HRM practice that yields the best results in the contemporary business environment. Consequently, the first-ranked company most successfully met the requirements of the innovative HRM practices presented.

Since corn is the second most widespread crop globally and its production has an impact on all industries, from animal husbandry to sweeteners, modern agriculture meets the task of preserving yield quality and detecting corn stress. Application of remote sensing techniques enabled more efficient crop monitoring due to the ability to cover large areas and perform non-destructive and non-invasive measurements. By using vegetation indices, it is possible to effectively measure the status of surface vegetation and detect stress on the field. This study describes the methodology for corn stress detection using red-green-blue (RGB) imagery and vegetation indices. Using the Excess Green vegetation index and calculated vegetation index histogram for healthy crop, corn stress has been effectively detected. The obtained results showed higher than 89% accuracy on both experimental plots, confirming that the proposed methodology can be used for corn stress detection using images acquired only with the RGB sensor. The proposed method does not depend on the sensor used for image acquisition and vegetation index used for stress detection, so it can be used in various different setups.

The performance of tax administrations (TAs) is usually described as their capacity to complete activities with the minimum of resources engaged. Accordingly, tax administration performance is a multifaceted phenomenon, and measuring and benchmarking its performance against other countries or regions remains a puzzle for researchers and practitioners. This paper introduces a new approach for measuring tax administration performance using the Composite I-Distance Indicator (CIDI) based on 11 individual performance measures from 35 European tax administrations over two consecutive years (2018–2019). For the given scores of tax administrations, we conducted a correlation analysis with (a) tax evasion loss and (b) the fiscal deficit of countries in which these tax administrations operate, aiming to assess the strength of the statistical relationship between these variables. The study highlights Denmark and the Netherlands as exemplary models for tax administration, with “Revenue Collection” being identified as a crucial driver of excellence and “Operational Performance” (such as “e-filing” and “on-time filing”) forming critical aspects of TA efficiency. Also, the study finds a negative correlation between tax avoidance and tax administration performance.

The performance of tax administrations (TAs) is usually described as their capacity to complete activities with the minimum of resources engaged. Accordingly, tax administration performance is a multifaceted phenomenon, and measuring and benchmarking its performance against other countries or regions remains a puzzle for researchers and practitioners. This paper introduces a new approach for measuring tax administration performance using the Composite I-Distance Indicator based on 11 individual performance measures from 35 European tax administrations over two consecutive years (2018-2019). The findings highlight Denmark and the Netherlands as exemplary models for tax administration, with “Revenue Collection” being identified as a crucial driver of excellence and “Operational Performance” (such as “e-filing” and “on-time filing”) forming critical aspects of TA efficiency. This approach can be valuable for policymakers, public administration analysts, and other stakeholders interested in assessing tax administration efficiency across countries or similar problem areas requiring integrated performance indicators.