We are interested in the hierarchy of the main Romanian companies in the manufacturing industry by considering eight financial and seven non-financial indicators. Thirty three listed companies, that are non-financial institutions, were selected for the study and in order to control the reliability of the data we used the Bucharest Stock Exchange database, official data published by the Romanian Ministry of Public Finance, and the annual reports released by the companies on their websites, collecting information for the years 2011–2015. Because the human thinking is subjective and ambiguous we prefer linguistic variables, converted afterwards in triangular fuzzy numbers, to represent the importance of indicators. Our method involves the calculation of the weights of individual or categories of indicators based on Fuzzy Analytic Hierarchy Process. Then, the level of performance for each company, separately for financial, non-financial and all indicators is obtained by TOPSIS method. We deduce an objective hierarchy of the companies on a rigorous basis, which is however dependent from the choice of indicators and the conversion scale of linguistic variables into triangular fuzzy numbers. Also, following the obtained results we concluded that the overall performance of companies for the analyzed period is significantly influenced by non-financial indicators.

Higher education services are at a crossroads created by the disruptive impact of digitalization. The COVID-19 pandemic experience forced Romanian universities to use digital educational platforms and other online education tools. The questions put into discussion are: Where is Romanian university education headed, what attributes of service quality are relevant for students, how do they see the digitization experience, and what needs to be done to increase satisfaction? A survey was conducted based on an online questionnaire on a sample of 314 students from the University of Oradea that used, for the first time in empirical research, a scale to measure satisfaction with the quality of educational services to which a dimension of digital education is added. Revised importance–performance analysis (importance–performance analysis in nine quadrants with one parameter c-9Qc-IPA) was used for data processing. The results show a still-reserved attitude towards certain aspects of the digitization of services, with priority remaining on aspects related to the material base and the prospects of finding a suitable job after graduation.

Our study introduces an enhanced version of the Importance–Performance Analysis (IPA) method, a powerful tool that can be applied across various domains. This method plays a crucial role in our research, aiding in making well-informed decisions about smart tourism destination attributes. We achieved this by evaluating how 911 consumers from four different generations (Baby Boomers, Generation X, Millennials, and Generation Z) rated these attributes based on their most recent tourist destination visit. Unlike traditional methods that often rely on subjective opinions or complex statistical models, the Improved IPA (IIPA) method offers a clear approach to decision-making. It enables decision-makers to focus on the most crucial attributes that drive consumer interest, thereby optimizing resource allocation and marketing efforts. Specifically, to remain competitive, decision-makers for smart tourist destinations should focus on queuing-time forecast and applications, websites, and content accessible for travelers with disabilities for Baby Boomers; e-complaint handling for Generation X; smart emergency response system for Millennials; and tourist-flow forecast, real-time traffic broadcast, electronic-entrance guard systems, and accessible data about physical design features of accommodation, restaurants, and tourist attractions for Generation Z. Theoretically, this study advances the research on managerial decision-making by demonstrating the effectiveness of the IIPA as a clear and straightforward method for making optimal decisions about product or service attributes. In practice, the study provides decision-makers with valuable insights into the importance of different categories of smart attributes in shaping the overall holiday experience at a tourist destination for Baby Boomers, Generation X, Millennials, and Generation Z tourism consumers.

The Importance-Performance Analysis is a widely used diagnostic tool in many fields of economic activity, such as: transport, health, construction, public food industry, finance, banking, sustainable activities, etc. Despite its use for over 40 years in many economic and social fields, this tool has some important drawbacks that affect the accuracy of managerial decisions. Over time, many variants for improving the standard Importance-performance matrix have been proposed. The aim of our research is to propose a method to solve one of the biggest problems of the standard Importance-Performance Analysis, respectively a method of boosting confidence in the positioning of attributes in the matrix. We use a mathematical method, inspired by classification theory tools, to apply the nine categories division of attributes in the importance-performance plane. Moreover, we introduce a level of confidence in a nine categories Importance-performance matrix, which helps the practitioners to prioritize a decision on attributes, according to the resources, managerial plan, competition, etc. We test and discuss the effectiveness of the new method on two studies: on the green practices in educational restaurant operations and on the financial performance evaluation.