A critical point in making food chains more sustainable is to find different ways to increase efficiency. These can be aimed at shortening the chain, using more sustainable raw materials, etc. Blockchain technology offers the potential for reliable data management and simplified administration and is, therefore, definitely a tool to consider if the aim is to enhance sustainability in food chains. The question arises as to whether food chain operators have the technology and knowledge needed for widespread uptake. The aim of this research was to investigate whether the technical background and knowledge for the use of cryptocurrencies can be compared with the technological background for monitoring the food chain with blockchain-based data management. If so, since data on the uptake of cryptocurrencies is already available, this analysis will provide information on the realistic scope of such an application. The research showed that there is no significant difference in the technology required for the two applications. The data clearly shows that, overall, there are 4.6 billion people who have the tools to use them. In addition, there is evidence that cryptocurrency penetration is weakly correlated with GDP or banking system development. In other words, if other conditions are right (e.g., the interest of producers), the availability of tools and knowledge should not be a barrier to uptake. Neither is the economic performance of a country or the development of its banking system. It is therefore concluded that, based on the aspects examined in this research, blockchain technology can be applied on a large scale worldwide.

The study seeks to answer the question of what strategic directions and opportunities we have for business in the midst of the info-communication changes of our time. In this research, we compare the results of non-representative primary research (cluster analysis and discriminant analysis) with the factors and latest methods of e-commerce or even mobile commerce and traditional commerce and their main differences. Based on the four clusters examined, we develop a new strategic model for practice with suggestions which can be used by small and medium-sized enterprises (SMEs) and which they can incorporate directly into their business models. Starting point of our hypothesis was that in order to develop an effective and delivered communication, a market needs to be targeted and at least four different clusters should be formulated.

The problem of product and process planning analysed so far is how we can take advantage of our strategy in planning. Among the principles of manufacturing and service management concepts is that after planning demand, planning transformation is one of the key steps of integrated efficiency; it makes it possible to save costs that are not value adding and are not necessary from the customer's point of view. Currently, the methods of material requirements and capacity planning can be seen as classic solutions that are based on dependency relations between different resources, which can be dynamic in space and time. Measuring and recording capacities raise several problems in addition to the fact that our planning methods are not always satisfying. In the literature, the methods of material requirements planning or manufacturing resource planning (MRP) are not typically optimization methods, so they do not guarantee the best solution, and even if our planning methods were satisfying, several manufacturing restrictions (the time allowed, the complexity of the planning process, the lack of testing opportunities, etc.) could prevent us from reaching satisfying application. It is necessary to create a simple planning algorithm that can give the planner a greater degree of freedom and that would be simple and algorithmic in order to maintain continuous conscious control, putting an end to planning uncertainty and leading us to the best solution under the given conditions. The aim of our research is to introduce a novel, simple planning algorithm, similar to heuristic methods that eliminates the problem of defining the order quantity when applying traditional methods, which prevents us from determining in advance which method is desirable (causing unnecessary planning steps); computer- based solutions hide the causal relations of the methodology from the planner (causing unreliability uncertainty).