The goal of this paper is to connect models of customer satisfaction and financial performance into a single aggregate model of business performance. The contribution of this paper lies in the increased complexity of assessing business performance, which results from connecting the model of customer satisfaction with the model of financial performance. The model of customer satisfaction is constructed based on customer expectations, which differs from the standard approach. The model is constructed based on a questionnaire survey of customers of select businesses. The financial performance of the same businesses was assessed based on publicly available data, which were used as inputs into ratio indicators. Afterward, financial performance was assessed using two methods (TOPSIS and Altman’s Z -score). The results show that the model of customer satisfaction helps us better understand financial performance when incorporating customer expectations. This financial performance was measured using the aggregate model of financial performance, composed of select financial indicators. The magnitude of the effect is greater than if financial performance is measured using standalone ratio indicators.

Generative artificial intelligence (AI) has witnessed a major boom in recent years and is increasingly penetrating the higher education sector. This study focused on the use of ChatGPT by undergraduate management students. We developed a model called the “AI Student Satisfaction with Studies model” (AI 3S-model) to investigate how generative AI, specifically ChatGPT, affects student satisfaction with their management studies. Factors used in the model included AI-related student expectations, AI-related student job expectations, perceived quality of AI among students, and AI-related overall student satisfaction. An online questionnaire was administered to students from economics faculties at various universities in the Czech Republic. We deliberately focused on one specialized economics college and several large economics faculties. The sample comprised 231 respondents. To analyze the data, we applied covariance-based structural equation modelling using maximum likelihood estimation. Our findings indicate that two factors directly and positively affect overall student satisfaction with AI use: their perceived quality of studies and their expectations. Additionally, perceived quality acts as a significant mediator between student expectations and overall satisfaction, as well as between job expectations and overall satisfaction. Students believe that ChatGPT enhances their quality of education, which boosts their overall satisfaction. For management education programs, this means that finding ways to effectively integrate generative AI into students’ learning and establishing reasonable limits is highly beneficial, whereas prohibiting the use of generative AI tools would likely decrease student satisfaction and diminish the perceived quality of their studies.

The subject of this paper is modeling customer satisfaction in the mobile telecommunication industry following the Covid-19 pandemic. Based on standard customer satisfaction models, a specialized model tailored for the mobile telecommunication industry has been developed to account for its unique characteristics, including market concentration. This model was created within the Slovakian context using the Structural Equation Modelling method. The respondents were customers of all mobile operators in this market. The model revealed a positive relationship between image and perceived service quality and a negative relationship between customer expectations and perceived service value. However, it was not possible to demonstrate a relationship between image and customer loyalty or between customer expectations and customer satisfaction. Therefore, it seems that the factors influencing customer satisfaction in the telecommunications sector of an emerging EU economy differ from those in other sectors and economies in the post-Covid-19 context.

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This paper investigates customer lifetime value (CLV) in e-shops, particularly those operated by small on-platform evolving financially independent online resellers (SOEFIOR) e-shops. The aim is to identify factors predicting CLV and assess their associations with CLV. Given the nested structure of the data, where transactions by customers are clustered within e-shops, a multilevel model is employed as the analytical framework. While classical linear regression assumes independence of observations within a sample, our dataset operates across three hierarchical levels: transaction level (I), customer level (II), and e-shop level (III). This hierarchical structure challenges the validity of inferences drawn from linear regression models, as transactions by one customer are not independent, and customers within a single e-shop may exhibit interdependencies. Therefore, a multilevel model is utilised to appropriately address the dependence among transactions within this nested data structure. The analysis reveals that the “number of transactions” exhibits the strongest positive association with CLV, followed by “days to transaction” and “session duration”. Furthermore, we discovered that “direct access” exhibits a positive association with CLV compared to access through Google campaigns, whereas access through Facebook campaigns demonstrates a negative association with CLV when compared to Google campaigns. Additionally, using the e-shop on mobile and landing on the product details page both show negative associations with CLV compared to desktop usage and landing on the e-shop’s home page, respectively. Our research identifies several variables that are associated with CLV in e-shops. This enables e-shop managers to effectively target and engage customers through marketing activities, thereby maximising revenues, financial performance, and customer CLV.

Research on customer satisfaction in repeat purchases shows that the relationship between customer expectations and customer satisfaction can be inverse to what is commonly reported. This also has an impact on the financial performance of an enterprise, which is therefore directly influenced by customer expectations. The goal of this paper is to determine whether customer satisfaction affects customer expectations and whether these expectations have a direct impact on the financial performance of an enterprise. The variables representing factors of customer satisfaction, including customer expectations, are measured using a customer survey. Business financial performance (BFP) was measured using the ROA, ROE, and Asset Turnover indicators. The model was created using Structural Equation Modelling. The research confirmed a positive direct effect of customer expectations on BFP (specifically ROA). Customer satisfaction impacted financial performance indirectly via customer expectations in two years. This suggests that the influence of customer expectations on BFP is long-term in nature, although this effect is rather weak. As customers make repeat purchases, customer expectations change. These changes reflect relationships primarily with customer satisfaction and loyalty and BFP. Customer satisfaction is shown to influence customer expectations, which in turn influence BFP. Therefore, it is advisable to focus on (raising) customer expectations in repeat purchases if the businesses want to achieve higher financial performance.

Purpose: The goal of this paper is to model customer satisfaction of smartphone select manufacturers in the Czech Republic (CR). Furthermore, the paper aims to model the factors which affect customer satisfaction of the smartphone. Methodology/Approach: A questionnaire was sent to 1,063 respondents in CR to collect data. Using structural equation modelling, relationships between factors of customer satisfaction within three models of customer satisfaction of select smartphone manufacturers were modelled. Findings: Effects of all investigated factors of customer satisfaction were verified, as well as all items which constituted the factors. Additionally, the functioning of the factor of total satisfaction with dimensions of general satisfaction and price tolerance was verified. Research Limitation/Implication: The research is limited by its focus exclusively CR, the number of manufacturers included in the research is rather low and small number of factors and items included in those factors. Originality/Value of paper: The models differed from each other in terms of the strength and direction of the relationships between the factors, which has implications for these recommendations. In general, each manufacturer has its own strengths and weaknesses (factors) that affect customer satisfaction with its product. Individual manufacturers can increase customer satisfaction by strengthening the positive factors or by learning from their competitors and eliminating or improving the factors that currently affect customer satisfaction negatively.

The aim and purpose of the research are to analyse the performance of the technical supervision of the investor within the Czech construction Civil Engineering during the construction, particularly focused on transport line structures. It is about clarifying the meaning and role of technical supervision in the public sector in transport structures. By analysing the activity of the technical supervision, it will be possible to find the space, if and how this service can be automated, or how it can be made more efficient. A questionnaire was conducted among workers who perform technical supervision to analyse the time-consuming nature of individual technical supervision activities. The obtained data were then analysed according to various categorizations, including the BIM model, and possible streamlining forms were proposed.

Purpose: The subject of the article is the relationship between customer satisfaction, loyalty and personality characteristics. It aims to analyse factors that influence customer satisfaction and loyalty, including their mutual relationships. For this purpose, a comprehensive model of customer satisfaction was created. Methodology/Approach: The research was carried out using a questionnaire survey on a sample of 1,530 customers of food producers (and 103 food business products that were non-durable) corresponding to the Czech population in terms of gender, age and region. The questionnaires were statistically evaluated using Structural equation modelling (SEM). Findings: The results show that a strong link between standard customer satisfaction factors (perceived quality, perceived value, customer expectation) overshadows the influence of weaker factors (personality). However, this effect is fully demonstrated when these strong factors are filtered out. Research Limitation/Implication: The paper focuses on foods that are sold through retail intermediaries, which also affect customer satisfaction. It may be different for other types of products and services and for products sold otherwise. It can also be limited to CR, resp. transition economics, ie. that in developed countries it could be different. Originality/Value of paper: The contribution of the paper is the finding that customer satisfaction is influenced by a personality factors, whose effect is at first glance weaker. It also shows that the factor image can be constructed taking into account the competitive ability of the company as a hybrid and the functionality of the customer loyalty factor influences the way of its construction.

The article focuses on the research of the relationship between performance in financial terms and customer satisfaction management in the company. Customer satisfaction management is understood as a process aimed at determining customer satisfaction and dissatisfaction in the form of backflows (from the customer), which is used throughout the company so that the company acquires and uses customer knowledge to change (innovate) in the company (whether in the form of process or product innovation). Through a change in customer satisfaction management, the company's financial performance is to be improved. The research is based on analyses of the relationships of selected factors of customer satisfaction management and their partial variables to the financial performance of the company. The article aims to identify the factors of customer satisfaction management that affect the financial performance of the company. A partial goal of the article is to identify the causes of the identified financial performance of the company, through quantities within the examined factors of customer satisfaction management. The research is carried out quantitatively using a questionnaire on a sample of 113 companies from various industries in the Czech Republic. Financial performance is assessed as profitability subjectively, by respondents to research, which consisted of managers of the surveyed companies. The relationships of individual factors and quantities were analyzed first using factor and then regression analysis. Statistical significance was verified by appropriate standard tests (t-test) and the significance of the model by the coefficient of determination. The results show that financial performance is influenced by customer satisfaction management and depends primarily on reverse flow management (from the customer), innovation and knowledge, the source of which is the customer and the internal customer satisfaction management support system.

Customers today can find the same assortments in a number of retail stores and through the Internet, thus effective store management has become a critical basis for developing strategic advantages. The aim of this research is to identify whether customer satisfaction measured by means of mystery shopping and the results of communication with the public on a company's Facebook profile assessed by quantitative analysis influence the performance of the selected companies. The evaluation of customer satisfaction and loyalty follows the older pilot study and is newly supplemented by an analysis of communication with customers using social media such as Facebook. The company's performance is evaluated through the financial ratios (ROA, ROE and ATO) based on accounting data available in the Magnusweb database. The research is focused on selected companies from the electronics and communication equipment retail industry in the Czech Republic and is unique from that point of view because it analyses communication with customers not only in retail shops but concurrently on their profiles for Facebook. The findings show how it is possible to assess the level of customer-oriented communication in retail shops and also the level of communication with customers on the social network. Retailers are increasing their focus on customers' experience in their shops and on social media sites. The research contributes to a better understanding of marketing in retail and on social media in the selected industry.

The subject of the publication is the research of customer satisfaction and its connection with company performance, quality, innovation and knowledge. The main goal is to analyze the mutual relations of the above factors, including their systematization on the basis of empirical findings in companies across industries in the CR. The publication captures a theoretical analysis of the basic relationships of the above quantities and discusses them with the results of the analysis of primary data from companies. The purpose is to clarify to what extent connections assumed in the literature are reflected in the Czech environment and how much they influence the subjective and objective performance of companies. Both types of indicators were used in the construction of models and it was found that results based on them differ and that models within the different indicators also differ.

The subject of this article is business performance, how it isperceived by managers and how it is reflected in a company’saccounting data. The objective of the article is to determinewhether business performance is understood by managers in thesame way as it is reflected in the accounting data, i.e.whether the manager’s subjective evaluation corresponds withthe objective evaluation of the accounting data. We askedmanagers to evaluate their current business performancerelative to their competition and to the previous year.Subsequently, we computed the performance of their companiesusing selected financial indicators constructed from theaccounting data. The two groups of indicators were thencompared on a sample of companies from various sectors, with amajority from the secondary and tertiary sectors. The resultsdemonstrated that subjective and objective evaluations differ;however, we found a match for the profitability indicators.

The paper deals with the influence of several personal factors on customer loyalty, which is one of the main tools of the company´s competitiveness. The aim of the article is to find out whether there is a relationship between selected personality and demographic characteristics and customer loyalty. The research was conducted on a sample of 1530 customers (final consumers) from 102 food industry companies in the Czech Republic. The research was conducted using a cross-comparison method with relevant statistical tests. Research results show that customer loyalty is related to the demographic characteristics examined (especially gender, income and education) and some personality traits (especially the approach to buying cheap things and optimism). Research shows that women are more loyal than men, then optimists and people who are not so rich that they can buy cheap things. On the contrary, with increasing income and education loyalty is rather falling.

The aim of this paper is to identify whether customer satisfaction measured by means of mystery shopping in selected retail companies in the electronics and communication equipment industry and their loyalty expressed by the NPS score correlate with the performance of the selected enterprises. The study contains research into communication with customers at the point of sale and customer satisfaction, with a focus on the five most significant representatives of this industry. The performance of companies is evaluated through the ROA, ROE and ATO indicators based on data available in the Magnusweb database. The study shows that customers satisfied during the sale of products also express their loyalty, which was measured by the NPS score. The said research conducted in the Czech Republic failed to prove the correlation between customer satisfaction and loyalty on the one hand and the selected enterprise performance indicators on the other. The same conclusion has also appeared in several research studies conducted abroad.

The subject of this article is customer satisfaction, loyalty, knowledge and business competitiveness from the perspective of a food-industry customer. This article aims to analyse the relationship between customer satisfaction, customer loyalty, product knowledge, business competitiveness and other selected factors which influence customer satisfaction. The research is aimed at customers who purchase the product in question repeatedly and have personal experience with this product. The research was carried out using a questionnaire which was presented to the respondents, who were customers of the selected companies. In order to model the relationships between the factors, a structural equation model approach was used. The research showed the direct influence of the product-knowledge variable on customer expectation and product competitiveness, as well as the influence of customer loyalty on product knowledge. Increased loyalty thus leads to the customer's increased knowledge of the product. The rate of repeat purchase of the same product is important for the relationship between the variables. In this case, customer expectation was shown to be an important variable which is influenced by customer satisfaction. It can be concluded that when a product's price is set correctly in relation to its quality, the price does not affect other research factors.

The subject of the article is the analysis of the value creation model (hereinafter referred to as the VCM) in selected sectors of the Czech economy, namely in engineering, transport and the food industry. The aim of the article is to determine the stability of the value creation model in selected sectors over time, i.e. whether the model shows the same explanatory power in different years as in the year in which it was created. The research is based on models the authors created for each sector in 2015 and identifies the explanatory power of these models from 2012 to 2014 based on samples of the respective companies. Thanks to the VCM model being developed and tested along with the EVA indicator, the results of the model from other years under review are equally compared with the EVA results. It turns out that the model is stable in the food industry, i.e. it achieves comparable results in the years 2012 - 2014 as in 2015, while in the engineering sector it was necessary to modify the model significantly (similarly in transport). It turns out that it is appropriate to specialize complex indices capable of evaluating the performance of companies not only by industry, i.e. the indices are not universal but also in time, that the indices need not be stable (static), but may need to be dynamized.

The aim of this article is to evaluate customer satisfaction from the perspective of companies in comparison with the perspective of the customers themselves. From the perspective of the company it is necessary to know customer satisfaction, as it is reflected in the company's performance. The research shows that there are significant differences in the evaluation of customer satisfaction from the perspective of companies and from the perspective of their customers, and that these differences are also reflected in the differences in the performance of the companies. The self-evaluation of companies tends to be overestimated in relation to the evaluation of companies by their customers, regardless of whether the companies are high-performing or low-performing. Customers are better able to distinguish the high-performing companies from the low-performing ones, since the high-performing companies received better evaluation from customers. In contrast, in the self-evaluation of companies, there were no statistically significant differences between the high-performing and low-performing companies. Companies evaluate customer satisfaction incorrectly regardless of their level of performance. Even if the evaluation of customer satisfaction from the company's perspective is generally overestimated in comparison with the view of customers, some factors of satisfaction are, at least concerning the trends, in agreement with both perspectives, that is, those of the customers and the companies.