Coordination and integration among farms within agri-food chains are crucial to tackle the issue of fragmentation within the primary sector, both at the European and national level. The Italian agri-food system still complains about the need to aggregate supply to support market dynamics, especially for niche and quality products that characterize the Made in Italy. It is well known that the Italian agri-food sector is closely linked to the relationship between agriculture on one hand and culture/tradition on the other, which is reflected in the high number of quality products that have obtained EU PDO (Protected Designation of Origin) and PGI (Protected Geographical Indication) recognition. The development of vertical forms of coordination has found significant support in recent years from the integrated supply chain design approach, which is increasingly becoming an essential tool for implementing rural development policies. In this context, the study provides a comparison between companies that have joined the Integrated Supply Chain Projects of the Rural Development Program and those that have not applied. The aim is to highlight any differences in order to understand policy impact. The analysis is based on the Emilia-Romagna region Farm Accountancy Data Network (FADN) data, and the sample consists of more than 2 thousand farms. The statistical analysis conducted compares treated and non-treated using the Welch-t-test for independent unmatched samples. The main results show higher values for treated farms when structural variables are analyzed, like the utilized agricultural area or the agricultural work unit. In general, higher balance sheet performances emerged for treated farms. In conclusion, this study shows that the Integrated Supply Chain Projects represent a worthwhile tool both to increase cooperation, food quality, and to enhance a competitive agricultural sector.

The research is focused on the evolution of the enterprises, in the field of specialized professional services, medium-period, enterprises that implemented projects financed within Regional Operational Program (ROP) during the 2007–2013 financial programming period. The analysis of the economic performance of the micro-enterprises corresponds to general objectives, but there can be outlined connections between these performances and other economic indicators that were not considered or followed through the financing program. The study case is focused on the development of micro-enterprises in the services area, in the Central Region, Romania (one of the eight development regions in Romania). The scientific approach for this article was based on a regressive statistical analysis. The analysis included the economic parameters for the enterprises selected, comparing the economic efficiency of these enterprises, during implementation with the economic efficiency after the implementation of the projects, during medium periods, including the sustainability period. The purpose of the research was to analyse the economic efficiency of the selected micro-enterprises, after finalizing the projects’ implementation. The authors intend to point out the need for a managerial instrument based on the economic efficiency of companies that are benefiting from non-reimbursable funds. This instrument should be taken into consideration in planning regional development at the national level, regarding the conditions and results expected. Although the authors used regressive statistical analysis the purpose was to prove that there is a need for additional managerial instruments when the financial allocations are being designed at the regional level. This study follows the interest of the authors in proving that the efficiency of non-reimbursable funds should be analysed distinctively on the activity sectors.

Most airport development projects entail disputes due to the features that are distinctive and complicated. Disputes can be minimized through creative problem-solving by implementing knowledge management practices into the system. This study investigates the direct influence of knowledge management (KM) on dispute minimization (DM) along with the key factors for developing a strategy that can enhance KM success. A mixed method was adopted including statistical data analysis based on the PLS-SEM and descriptive analysis with the SECI (Socialization, Externalization, Combination, Internalization) model approach for strategy development. These findings show that KM has a positive and significant direct influence on DM, while the factors that are considered to have a significant influence on KM success are human resources management (HR) and learning & training (LT) on airport development projects in state-owned airport companies. This research supports the importance of a well-developed HR system accompanied by regular LT to all members of the organization to optimize and encourage the spread of knowledge in the organization.

The artificial intelligence (AI)-based architect's profile's selection (simply iSelection) uses a polymathic mathematical model and AI-subdomains' integration for enabling automated and optimized human resources (HR) processes and activities. HR-related processes and activities in the selection, support, problem-solving, and just-in-time evaluation of a transformation manager's or key team members' polymathic profile (TPProfile). Where a TPProfile can be a classical business manager, transformation manager, project manager, or an enterprise architect. iSelection-related selection processes use many types of artifacts, like critical success factors (CSF), AI-subdomain' integration environments, and an enterprise-wide decision-making system (DMS). iSelection focuses on TPProfiles for various kinds of transformation projects, like the case of the transformation of enterprises' HRs (EHR) processes, activities, and related fields, like enterprise resources planning (ERP) environments, financial systems, human factors (HF) evolution, and AI-subdomains. The iSelection tries to offer a well-defined (or specific) TPProfile, which includes HF's original-authentic capabilities, education, affinities, and possible polymathical characteristics. Such a profile can also be influenced by educational or training curriculum (ETC), which also takes into account transformation projects’ acquired experiences. Knowing that selected TPProfiles are supported by an internal (or external) transformation framework (TF), which can support standard transformation activities, and solving various types of iSelection’s problems. Enterprise transformation projects (simply projects) face extremely high failure rates (XHFR) of about 95%, which makes EHR selection processes very complex.