The purpose of this study is to examine the behavior of students when using mobile applications (apps) during physical activity and to identify the determinants of their behavior. Analysis of variance, t test, chi-square test of independence, and chi-squared automatic interaction detection decision trees were utilized. Exploratory analysis was undertaken to identify the motivation behind the use of apps, using the self-determination theory as a framework. The results showed that the main reason for using apps is to record and save data for personal use and to improve the effectiveness of training. Students mostly use apps while running and cycling. The determinants of student app use are gender, place of residence, material situation, and level of higher education (bachelor's or master's degree). The results of the exploratory analysis indicate that motivations for using apps for most surveyed students are autonomous. The results provide a greater understanding of the role of mobile app use during leisure.

The aim of the article is to show the usability of mobile apps in the process of satisfying Generation Z's tourist needs (pre-travel, during-travel, post-travel).Theoretical part includes characteristics of Generation Z and the place of modern technologies in satisfying tourist needs, especially mobile apps' functions and advantages.Empirical part presents survey results (N=669) which positively verified main hypothesis: The motive and length of the trip, and the ways in which the Zs' travel needs are met, significantly determine the choices of mobile apps used at each stage of the trip.They prove a leisure trip is more often a positive determinant of pre-travel mobile apps use than a cognitive trip, while during travel the opposite situation is observed, at post-travel stage a significant dependence of mobile app use on the motive of the trip concerns only the negative influence of leisure trips on the use of communication/entertainmentsocializing apps.

Purpose This work aims to determine how innovation orientation (IO), built from six dimensions (strategic, structural-process, human resources, technological, organizational culture and market) affects organizational performance (OP) with the inclusion of knowledge management (KM) as a mediator and technological readiness (TR) as a moderator in the model. Design/methodology/approach Questionnaires completed by business service companies were analyzed using multiple regression analysis (path analysis), including the mediating variable (KM) and moderating variable (TR). The construct was validated with positive outcomes. Findings Of the eight hypotheses, six were supported. The study results show that strategic, technological, organizational culture and market dimensions of IO positively influence KM. On the other hand, KM plays an important role as a mediator in supporting the relationship between the four dimensions of IO and performance. Moreover, TR, as a moderator, positively affects the relationship between KM and OP. Originality/value The study is the first to explore the relationship between six dimensions of IO and KM in business service sector. Furthermore, this study provides evidence that TR can be beneficial for companies with respect to effective KM, which leads to the better performance.

The modern approach to the management of protected areas (PAs) introduces a holistic perspective on these areas, in which they are not seen as isolated conservation zones, but as units integrated with their natural, social and economic environment. They are expected to harmonize their protective role with tangible benefits for local communities. Fostering both social and economic development is particularly important in underdeveloped, peripheral areas. The efficacy of management within this novel paradigm relies heavily on the attitudes and perceptions of local communities towards the PAs. As a result, the research was undertaken to identify local stakeholders' perceptions of the social and economic role of national parks (NPs) in the Carpathian region of the European Union (EU). The study was based on 170 interviews conducted in eight NPs, among four stakeholder groups (NPs authorities, local authorities, representatives of the tourism sector, local residents). Q-methodology was applied to achieve a comprehensive understanding of respondents' perspectives, along with their nuanced opinions. This methodology enables a statistical analysis that leads to the identification of groups of opinions and the examination of differences between them. Based on it, three main groups of opinions (perspectives) were identified in which the national park was perceived as: I) a stimulant to sustainable local development, II) a partner and a chance for future local development and III) a constraint on local development. Perspective I was dominant (44.7% of respondents), being the most typical for Pieniny NP (Poland) and Aggtelek (Hungary), and - considering stakeholder groups - for national park authorities (the most homogeneous group in terms of opinions). Perspective II was characteristic mainly of Retezat NP (Romania) and Magura NP (Poland) and perspective III appeared most numerously in Poloniny (Slovakia), as well as in Piatra Craiului (Romania). The local context, related to a particular NP, differentiated opinions more strongly than the stakeholder group or country of origin. Opinions regarding the current park-people relationships and impact of the NP on local development as well as expectations as to the commercial use of the park's territory (the vision of tourism development) differed strongly among the representatives of the perspectives. A consensus emerged regarding the belief that NPs should support local development (e.g. by promoting local products and ensuring the benefits of its functioning reach the local residents). Furthermore, there was a consensus in rejecting the top-down management model of NPs, with a vision for future development focused on fostering a park-people partnership. These consensus views provide a positive ground for the implementation of a holistic approach and an integrative management model for NPs in the Carpathians.

Abstract Cluster policies (CPs) are said to be one of the crucial elements supporting the innovativeness of local and regional economies. However, what drives the success of CPs has not been made fully explicit. We tested the impact of perceived quality and strength of social capital (SC) and the formal institutional environment (FIE) upon CPs. We studied this relationship by applying structural equation modelling to data from quantitative CATI research on members of 20 cluster initiatives from four Polish administrative regions (NUTS 2), referred to as voivodships. We have revealed that the formal institutional environment has a strong influence on CPs, whereas, surprisingly, SC hardly matters.

Contemporary conditions of the functioning of enterprises mean that they are increasingly looking for opportunities to improve organizational performance in strategic management. Scientists are looking for optimal solutions, an appropriate combination of assets and resources, so the debate in the field of strategic orientations is still valid and gaining in importance. Several studies have explored the construct of market orientation, but few include technological orientation with the moderating effects of company assets. In the era of the highly competitive technology market, the area of technological business service providers are particularly interesting, but still undiscovered. This paper examines the effects of market orientation and technological orientation on organizational performance with the inclusion of organizational culture and human resources as moderators. Using questionnaire responses from technological business service providers (n = 689), a regression analysis was conducted to confirm the hypotheses. The results established evidence of positive relationships between market orientation-organizational performance and technological orientation-organizational performance, although in technological firms, the market orientation had a stronger correlation with organizational performance than the technological orientation. Moreover, the organizational culture and human resources play a moderating role in the relationships of market orientation-organizational performance and technological orientation-organizational performance, while weak human resources management weakens relationships market orientation-organizational performance and technological orientation-organizational performance and strong organizational culture reduce the effect of market orientation on organizational performance, significantly reducing the effect of technological orientation on firm performance.

The purpose of this paper is to examine the impact of knowledge absorptive capacity (KAC) on innovation orientation in business services. An empirical analysis was conducted on two samples (scientific experts and-in the next step, business service companies). The authors applied one-way ANOVA, HSD Tukey's post hoc tests, and structural equation modelling. Approached from a knowledge-based view, this research has found that the impact of KAC on all six innovation orientation dimensions is significant and positive. This empirical evidence also supports the thesis that KAC impacts the business performance of firms. Managers should raise a company's competitive advantage by introducing an innovation orientation, which requires a high level of KAC. This study advances the literature on KAC and innovation orientation by confirming the significant impact of KAC on business performance and a firm's innovation orientation.

Although European energy policy supports the reduction of energy consumption, the current economic and political situation in Poland and uncertainty related to the origin of energy sources do not support it. Therefore, the aim of this paper is to identify and assess the factors that affect the energy-saving behaviour of Polish consumers in the process of energy consumption. The research problem concerns the specificity of behaviours that are part of new trends in consumption, such as greening and the ethical dimension of consumption. The research question arises as to what the social responsibility of consumers is in the process of energy consumption. The research problem comes down to the question of factors that determine the behaviour of an individual consumer in the energy market. In order to realise the indicated purpose of the article, a conceptual research model was built and direct research was conducted using the research method, which was an online survey (CAWI). The research was run among 1422 individual consumers. After verifying 14 research hypotheses, it can be concluded that energy-saving behaviour is influenced in similar ways by a set of factors. In the paper there are findings which show that the generally understood energy-saving behaviour (Y1-at home and Y2-off-site) is influenced by the following factors: X1-energy-saving knowledge, X3-green consumer values, X5-social influence, X6-beliefs, and X7-consumer awareness. The specific mechanism of influence of each of the dominant factors is that the higher the intensity of these factors in consumer behaviour, the more actions are taken to save energy inside or outside the home. However, X2-energy-saving cost perception and X4-materialism presents this influence mechanism only for Y1-energy-saving behaviour at home.

Employers expect business school graduates to possess a wide and diverse range of competencies, because the conditions governing the operations of enterprises are subject to constant and dynamic change. Therefore, adjusting study programs to labor market requirements is one of the main challenges faced by higher education institutions, particularly business schools. Therefore, the expectations of potential employers have become an object of detailed study for most universities. The most frequently applied research approach adopted for such studies involves direct surveys of employer opinions, based on various types of questionnaires. An alternative method is textual analysis of job advertisements using analytical tools that automate the research process. The aim of this article is to identify the gap between the business education offer and the expectations of the labor market in Poland, as well as to show the possibility of using the analysis of the contents of job advertisements to identify employer expectations regarding the competencies of university graduates. The presented research is exploratory in nature, with four questions posed by the authors during the research process. The research is innovative with regard to Poland and in relation to graduates of business schools.

The aim of this paper is to gain a deeper insight into the interrelatedness between online visibility indicators (which are the spheres of digital marketing) and business services performance parameters. A conceptual framework was developed to analyse the online visibility of knowledge-intensive business services (KIBS) using data triangulation on the service industries. The data were analyzed using both netnographic and correlation analysis, and a classification and regression tree. The research adopted an analytic approach on the business services (industry) level. The results reveal that services with the highest level of competition on search engines and strong growth in requests were also those KIBS with the highest profits per employee. Business services with a high monthly search volume range also had the highest salaries per employee in the industry, while those with a low average search volume and stable or rising average monthly search volume dynamics also had low employment levels. This study provides insight into the interrelatedness of the business and digital marketing spheres of the contemporary service economy. We proved that business services that are most competitive on search engines and have the highest level of online visibility indicators are among those who achieve the highest profits.

Purpose: The purpose of this paper is to investigate the relation between human capital and the performance of the various types of knowledge-intensive business services (KIBS). Research Methodology: The analysis conducted on business services industry level took into account the role of education in knowledge transfer, a major factor enriching the KIBS industry. A conceptual framework based on cluster analysis (CA) and classification and regression trees (CART) was developed to analyse human capital, the main asset in the KIBS sector (according to the resource-based theory), and its relations with the performance of KIBS providers. Results: The results pointed to the significant differences between various types of knowledge-based services. Findings suggest that there could be applied additional approach to classifying the KIBS services into three clusters according to the business characteristics (including human capital). Our third cluster closely related to human capital (HC) and information and communication technologies (ICT) demonstrated the best business performance. The results confirmed that KIBS providers with high average remuneration and high wage growth dynamic noted over doubled performance indicator (measured as profit growth). In that group of KIBS providers were (a) Software and IT companies, (b) Temporary employment agency activities and (c) Other human resources provision. Limitations: Our analysis is based on statistical data gathered by a public entity covered 3125 firms aggregated into twenty service types, which limits the scope of the research questions. Contribution: This study contributes to the state of knowledge of the performance dynamics of the various business services. Keywords: Business Services (BS), Human Capital (HC), Performance, Knowledge, Education

The purpose of the paper is to identify the dimensions of the strategy of resources allocation of Polish households members and test the hypothesis concerning risky shift effect in the relationship between strategy of family decision making and trade-off in family scarce resources allocation. These dimensions were identified on the basis of nationwide empirical data gathered on a representative sample of 1020 respondents nested in 410 households. SEM-Tree hybrid models are used in the analysis of the results, which combine the confirmatory structural equation models with exploratory and predictive classification and regression trees. This allows to apply structural modeling for the study of heterogeneous populations and to assess the hierarchical impact of exogenous predictors on the identification of segments with separate and unique model structural parameters. The approach combines the advantages of a model approach (at the stage of constructing hypotheses on structural relationships and specifications of measurement models) and exploration-based data (at the stage of recursive division of the sample).

For quite a long time, research studies have attempted to combine various analytical tools to build predictive models. It is possible to combine tools of the same type (ensemble models, committees) or tools of different types (hybrid models). Hybrid models are used in such areas as customer relationship management (CRM), web usage mining, medical sciences, petroleum geology and anomaly detection in computer networks. Our hybrid model was created as a sequential combination of a cluster analysis and decision trees. In the first step of the procedure, objects were grouped into clusters using the k-means algorithm. The second step involved building a decision tree model with a new independent variable that indicated which cluster the objects belonged to. The analysis was based on 14 data sets collected from publicly accessible repositories. The performance of the models was assessed with the use of measures derived from the confusion matrix, including the accuracy, precision, recall, F-measure, and the lift in the first and second decile. We tried to find a relationship between the number of clusters and the quality of hybrid predictive models. According to our knowledge, similar studies have not been conducted yet. Our research demonstrates that in some cases building hybrid models can improve the performance of predictive models. It turned out that the models with the highest performance measures require building a relatively large number of clusters (from 9 to 15).

Streszczenie: Artykuł jest poświęcony problemowi porzucania koszyków przez klientów dokonujących zakupów on-line

Rotacyjny las (rotation forest) jest narzędziem analitycznym służącym do budowy zagregowanych modeli predykcyjnych. Pojedyncze modele drzew klasyfikacyjnych powstają na podstawie podprób bootstrapowych, a do ich budowy używa się innych zbiorów zmiennych niezależnych. Początkowo dzieli się zbiór tych zmiennych na k rozłącznych podzbiorów, a następnie w każdym z nich stosuje się analizę głównych składowych w celu uzyskania liniowej kombinacji zmiennych wejściowych. Celem artykułu jest porównanie skuteczności modeli prognostycznych zbudowanych za pomocą rotacyjnego lasu z innymi modelami zagregowanymi: metodą bagging, drzewami wzmacnianymi AdaBoost i losowym lasem. Do analiz wykorzystano 11 zbiorów obserwacji pobranych z popularnego repozytorium on-line. Obliczenia zostały wykonane w programie WEKA (Waikato Environment for Knowledge Analysis), a ocena modeli została dokonana za pomocą czterech miar: dokładności, czułości, precyzji i miary F. Wyniki wskazują na ograniczone możliwości wykorzystania tego modelu zagregowanego w badaniach rynkowych i marketingowych. Najważniejsze przeszkody dotyczą poziomu pomiaru zmiennych niezależnych i zasobów sprzętowych niezbędnych do analizy dużych zbiorów danych

Celem artykulu jest wskazanie trudności, jakie mozna napotkac podczas przygotowania danych do analizy. Zaprezentowane przyklady odnoszą sie do rzeczywistych danych pozyskanych z e-sklepu oferującego obuwie i dotyczą obszaru web mining, nazywanego analizą wzorcow zachowan internautow. W artykule przedstawiono wyniki wstepnej eksploracji danych od momentu ich pozyskania, przez sprawdzenie i na przygotowaniu środowiska danych skonczywszy.

Predictive models in analytical CRM (customer relationship management) are closely related to the customer's life cycle. Prediction of binary dependent variable refers to the most common areas such as customer acquisition, customer development (cross-selling and up-selling), and customer retention (churn analysis). While building static predictive models one usually applies decision trees, logistic regression, support vector machines or ensemble methods such as different algorithms of boosted decision trees or random forest. Recently one can observe increasing use of hybrid models in the analytical CRM, i.e. those that combine several different analytical tools, e.g. cluster analysis with decision trees, genetic algorithms with neural networks, or decision trees with logistic regression. The purpose of this paper is to compare the results obtained by using hybrid predictive CART-logit models with single decision tree models and logistic regression models. All analyses have been conducted on the basis of data sets relating to analytical CRM.

Streszczenie: Współtworzenie wartości oznacza zaangażowanie klientów i dostawców w proces tworzenia produktu. Klienci oferują swoją wiedzę i doświadczenia związane z użytkowaniem produktu lub usługi, natomiast dostawcy oferują swoją wiedzę i umiejętności w zakresie ich wytwarzania. Wynikiem interakcji pomiędzy stronami wymiany jest ulepszony produkt i zwiększony na niego popyt, co ostatecznie oznacza wzrost wartości dla klienta i wzrost wartości klienta. Celem artykułu jest prezentacja wyników analizy komentarzy klientów banku BZWBK, odnoszących się do jakości serwisu bankowości elektronicznej. W badaniach wykorzystano eksplorację opinii, która znajduje się na styku eksploracji sieci, pozyskiwania informacji i analizy danych tekstowych.