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Big data has become omnipresent since most human activities are recorded using various technologies, thus generating huge databases on various platforms such as social media. Human activity has become reflected in these databases, making them suitable for various research that used to be conducted based on more traditional research approaches, such as survey research. Labour markets research is also affected by big data since social media has become one of the most dominant means of communication in various areas, being employed as one of them. This paper aims to map the research field of big data and labor markets using a systematic literature review and bibliography. Web of Science database has been searched using the keywords "big data" and "labo(u)r market". The most relevant papers for the area of big data for labour analysis have been selected, using transparent and consistent criteria. Papers have been analysed using a bibliometric approach supported by the VOSviewer and R bibliometrix, which has been used for detecting various research trends, such as research topics. The assessment of the current research in big data for the labour market has been compiled to detect the research gaps and generate future research directions.

The main aim of this study is to explore the mediating effect of innovation in the relationship between human resource management (HRM) practices and organizational performance. HRM practices are observed through selective hiring, training, participative decision-making, and rewarding. Innovation is conceptualized over behavioral, product, process, and market innovation. The study relies upon the principles of social exchange theory and resource-based theory. Data were collected from 408 managers in an emerging economy context. The proposed conceptual model is evaluated with structural equation modeling using Lisrel 8.8 and SPSS 22. Study findings suggest that innovation influences the relationship between selective hiring, training, and participative decision-making and organizational performance. However, no mediating effect of innovation was found in a relationship between rewarding and organizational business performances. Since human resources and innovation are among the leading sources for building competitive advantage for companies, the study findings contribute to HRM and innovation.

The key to the human resource management progress from a traditional to a strategic function is implementing information technology (IT) solutions, enabling fast, accurate, and effective decision making. The trends are certainly going in that direction ; since Human Resources Information System (HRIS) has proven to be one of the widely used tools in organizations at the beginning of this century. This study’s objective is to determine the characteristics of the companies according to their usage of HRIS. The following characteristics were investigated: the company’s size (measured in the number of employees), size of the market at which the company operates, growth of the market at which the company operates, and company industry. The logistic regression model was developed to investigate to what extent the characteristics mentioned above impact the decision of the company to use HRIS. The results indicate that size, market size, and market growth impact the decision to use HRIS, while there were no differences according to industry types.

Data mining has become the omnipresent requirement in the business environment of abundant data. At the beginning of data mining development, the one- solution approach was mostly used. In the last 20 years, mostly due to the development of various educational programs and the availability of open- source software, data mining has evolved into a mature-leveled software solution that does not necessarily require high-level expertise since numerous prototype solutions have emerged. Small and medium enterprises (SMEs) are still lagging behind large companies in data mining implementation, which raises the question of the determinants of data mining adoption. This paper aims to test the preliminary model of data mining adoption using the Technology-Organization- Environment framework. The survey on the sample of Italian SMEs was conducted to test the model, and the collected company data was analyzed using the PLS-SEM approach.

The hotel industry experienced an immense transformation due to technological advancement and digitalization. Hotel websites evolved from merely online brochures to innovative tools with massive strategic significance. Nowadays, hotel websites are a substantial marketing tool for online branding and reaching potential guests. Furthermore, hotel websites are used as online booking mechanisms for hotels to enforce their direct booking channels. Yet, not all hotel websites generate success, depending on their quality. There are numerous interpretations of what website quality consists of, with the consensus that functionality and usability are the key factors that a quality website must contain. This research aims to conduct a preliminary bibliometric analysis to provide insights and systematize previous work on the topic. First, the Web of Knowledge database was searched with the selected keywords reflecting the research goal. Second, the most frequent words and phrases were extracted, and then finally, cluster analysis was conducted to extract research key topics. Interest findings emerged from the analysis beneficial both for academics and hotel managers. The bibliometric analysis pointed out topics' relevance and increased interest from the authors. The number of papers and citations has been rising in the last few years. The paper's origins are worldwide, confirming international interest in the topic. Moreover, the most frequent word analysis outlined the relationship between booking intention and website quality as a leading interest, confirming that website quality is an important factor for direct hotel booking. The most frequent phrase analysis revealed the researcher's interest in the website quality evaluation methodologies and the connection between website quality and perspectives such as the green economy. Finally, the cluster analysis emerged five key interest topics related to the website quality and hotel industry: booking intention, innovation, methodology, psychology, and special events.

Introduction In using online medical manuals, patients that do not speak English natively are in effect “virtual immigrants”, confronted with a problem of low health literacy. Our aim was to investigate the use of diabetes key terms when the official guide for insulin pump was translated into a non-widely spoken language like Croatian. Data set and methods An official guide for insulin pump was translated by the manufacturer into Croatian and compared to its original English version for the ratio of professional and popular key diabetes terms. Analyzed professional terminology included: diabetes (Cro. dijabetes) ; blood glucose (glukoza u krvi) ; retinopathy (retinopatija) ; nephropathy (nefropatija) ; neuropathy (neuropatija) ; cardiovascular (kardiovaskularni) ; hyperglycemia (hiperglikemija) and hypoglycemia (hipoglikemija). Analyzed popular terminology included: sugar disorders (poremećaj šećera u krvi) ; blood sugar (šećer u krvi) ; eye damage (oštećenje oka) ; kidney damage (oštećenje bubrega) ; nerve damage (oštećenje živaca) ; blood system damage (oštećenje krvnih žila/srčanožilnog sustava) ; high/low levels of sugar (povišena vrijednosti šećera) and low level of sugar (niska vrijednost šećera). Results Ratio of professional vs. popular terminology was 5.8 in the English vs. 2.92 in Croatian version resulting in more professional terminology in English manual. Particular terms used more frequently in English were diabetes, blood glucose, hyperglycemia and hypoglycemia. Conclusion Medical manuals often advocate the use of professional terms in addressing the patient ; in case of this guide for insulin pump it could result in less information accessibility. Most insulin pump users have good knowledge on particular terminology but highly professional language can represent a barrier to understand information.

Neural networks or artificial neural networks are a branch of machine learning, a technology based on brain and nervous system studies. Thanks to the fast-technological changes, growing computing power, advanced algorithms, and widely available digital data, the application of neural networks has spread tremendously in many fields of study, from health and medicine, accounting, finance, engineering, manufacturing, and marketing to natural language processing and robotics, wherever the analysis of big sets of data is needed. This paper focuses on using neural networks in higher educational institutions for student performance analysis and prediction, intending to investigate these researches' bibliometric and topical characteristics published in scientific papers. We have searched the indexing service Scopus to track the papers that present the applications of neural networks in higher education in the last five years. The research has been investigated based on the bibliometric characteristics (authors, publications, institutions, funding) as well as the topics of the research. The presented analysis is preliminary and can be relevant for future in- depth research on the applications of neural networks for the analysis of student performance in higher education.

The paper focuses on the importance of e-democracy and the introduction of information and communication technologies in democratic processes. Digitalisation significantly impacts citizens' involvement in e-participation and direct decision-making in developed societies. We want to show the current local and national levels based on comparisons of direct decision-making solutions and e-participatory tools in Austria, Croatia, Greece, Italy, and Slovenia. It should be emphasised that with the development of e- participation tools, Croatia, Greece, and Italy are ahead, while Austria and Slovenia are lagging behind the current trends in the citizen's direct decision making and the emergence of e- participation. This is mainly due to a lack of confidence in online security and a decline in interest in e-democracy, mostly in Slovenia.

Hotelijerstvo ima snažnu tržišnu moć i svojim utjecajem na gospodarstvo može utjecati na infrastrukturni, ekonomski i digitalni razvoj regije u kojoj posluje. Osim brojnih prednosti, razvoj digitalizacije iznjedrio je i određene izazove za industriju, poput oštre konkurencije i borbe za tržišnom moći, pa tako sudionici konstantno traže nova rješenja za postizanjem prednosti. Hotelske mrežne stranice hotela imaju utjecaj na profitabilnost, no kako bi bio pozitivan, one trebaju biti kvalitetne. Kvalitetnim mrežnim stranicama smatraju se funkcionalne i korisne mrežne stranice, a inovativnost je česti faktor koji se promatra prilikom ispitivanja kvalitete. Cilj ovog rada je dobiti pregled inovativnosti mrežnih stranica hrvatskih hotela, a za potrebe istraživanja koristile su se dvije metode istraživanja: e- MICA okvir i analiza sadržaja. Za analizu rezultata koristila se deskriptivna statistika te značajnost Hi kvadrata. Ustanovljeno je kako su hrvatski hoteli u maloj mjeri usvojili značajke inovativnosti na svojim mrežnim stranicama: u najvećem broju su to hoteli s 5 zvjezdica, lanci i hoteli u stranom vlasništvu te hoteli koji su prodajnu strategiju usmjerili na direktne kanale. Rezultati su značajni i za buduća istraživanja koja bi trebala dublje analizirati problematiku, te hotelijere kojima bi rezultati mogli biti povod za reviziju i unaprjeđenje postojećih strategija.

Uz pomoć bibliografije i sustavnog pretraživanja literature, ovaj rad nastoji analizirati i mapirati područje istraživanja urbane održivosti. Za pretragu baze podataka Web of Science korištene su ključne riječi “urbana održivost“ i „urbanizacija.” U skladu s nepristranim i jasnim kriterijima odabrano je najznačajnije istraživanje u analizi urbane održivosti. Temeljni cilj ovog istraživanja je provesti bibliometrijsku analizu gotovo trideset godina istraživanja urbane održivosti. Iz baze podataka literature na Web of Science izdvojeno je ukupno 787 članaka. Literatura je analizirana pomoću VOSviewera, znanstvenog programa za mapiranje. Uključujući mnogobrojne pristupe mrežnoj analizi poput supojavljivanja ključnih riječi, sucitiranja i bibliografskog združivanja, VOSviewer se koristi kako bi se odredila istaknuta tematska područja i identificirali relevantni autori, publikacije i časopisi. Postojeća razina istraživanja urbane održivosti provedena je kako bi se identificirao jaz u istraživanju te predložili buduće smjernice istraživanja.

Dosadašnja iskustva brojnih organizacija pokazala su kako je rizik neuspješnosti projekta implementacije softvera visok, a kako bi se smanjio navedeni rizik dosada su uloženi značajni napori u smjeru implementacije metodologije projektnog menadžmenta. Međutim, dosadašnja istraživanja pokazuje da, usprkos poboljšanjima u menadžmentu projekata, relativno značajan broj projekata i dalje doživljava neuspjeh po nekom od kriterija izvedbe. Predlaže se metodologija koja uključuje: (i) analizu prethodnih istraživanja ; (ii) dizajn istraživačkog instrument za mjerenje uspješnosti projekata i definiciju ključnih determinanti uspješnosti projekata ; (iii) razvoj višekriterijalnog modela za mjerenje uspješnosti softverskih projekata ; (iv) razvoj modela uspješnosti menadžmenta softverskim projektima za hrvatske organizacije koristeći pristup rudarenja podacima. Ove aktivnosti mogu se provesti korištenjem sljedećih metoda: bibliografska analiza prethodnih istraživanja, metoda anketnog istraživanja, metode deskriptivne i inferencijalne statistike, metoda strukturnih jednadžbi i metode rudarenja podataka (nadzirano i nenadzirano učenje, rudarenje teksta). Rezultati ovog istraživačkog okvira mogu se koristiti kao polazna osnova istraživanja uspješnosti projekata implementacije poslovnog softvera.

Health care has been recently under the strong impact of information and communication technologies, especially the internet. eHealth has become one of the most often mentioned concepts that raise hope for the increasing effectiveness of health care. Patients increasingly seek health information over the internet, thus increasing their access to knowledge and expertise available online. The paper aims to investigate the differences among individuals living in households with different levels of income and different levels of education in European countries according to their habits of seeking health information over the internet. For that purpose, K-means cluster analysis was used. We use the elbow method to determine the optimal number of clusters, which considers the percentage of variance explained as a function of the number of clusters. Data about the habits of seeking health information over the internet from the Eurostat database is used. Results indicate that education and income have a substantial impact on seeking health information on the internet. However, the differences among countries are the largest for the households with the income in the fourth quartile and the smallest for the households with the income in the first quartile.

Nalazimo se u vremenu ubrzanog razvoja digitalnih tehnologija i umjetne inteligencije. Ne čudi stoga što je primjena novih medija i umjetne inteligencije jedna od vrućih tema ne samo u javnoj raspravi nego i u akademskim krugovima. Taj ubrzani razvoj novih medija i primjena umjetne inteligencije posebno utječe na informacijske i komunikacijske znanosti, pa tako i na odnose s javnošću. Znanstvenici, praktičari i oni koji donose regulative trebaju biti svjesni pozitivnih i negativnih aspekata koje u područje odnosa s javnošću donose novi mediji i vezano uz njih stvaranje i iščitavanje velikih podataka. Računalni sustavi koji su sposobni učiti i prilagođavati se ne slijedeći izričite upute, koristeći se algoritmima za izvođenje zaključaka iz velikih podataka, primjenjuju se i u odnosima s javnošću. U uvodnom dijelu ovaj rad sažima glavne pojmove vezane uz umjetnu inteligenciju te objašnjava na koji način algoritmi prikupljaju velike podatke i što mogu iz njih iščitati. Nadalje, u središtu je rada istraživanje dosadašnje literature s obzirom na spomenuti problem. Stoga ovaj rad ima dva ključna cilja. Prvi je cilj donijeti pregled literature i kritički sagledati primjenu umjetne inteligencije u odnosima s javnošću. Drugi je cilj rada otkriti koje etičke izazove donosi primjena umjetne inteligencije u praksi odnosa s javnošću. Istraživanje je pokazalo kako se umjetna inteligencija rabi u različitim područjima odnosa s javnošću: u istraživanju ključnih javnosti, u interpretaciji osjećaja ključnih javnosti, u digitalnom marketingu, u kriznom komuniciranju te u odnosima s medijima. Istraživanje je također pokazalo kako su ključni etički problemi vezani uz primjenu umjetne inteligencije u odnosima s javnošću sljedeći: ugrožavanje prava na privatnost, dehumanizacija komunikacije i ugrožavanje povjerenja u institucije. Na kraju rad nudi etičke smjernice za stručnjake u odnosima s javnošću, posebno s obzirom na zakonsku prazninu koja postoji u tom području.

The term corporate sustainability represents a crucial part of the concept of sustainable development. The main goal of the companies, which adopted corporate sustainability practice is to fulfil a sustainable development agenda and brings a balanced approach to economic and social progress and environmental management. The purpose of the article is to highlight the importance and issues of corporate sustainability in the context of awareness and approaches to social responsibility in the Fourth Industrial Revolution. The paper aims to make order in the plurality of definitions of concept «corporate sustainability» and its practical understanding in terms of «corporate social responsibility». It does so through a literature review and the analysis of different attempts of definition. It identifies the main challenges these concepts bring with them., Cambio. Rivista sulle Trasformazioni Sociali, Vol. 10 No. 19 (2020): Intercepting and Modeling Global Change?

This paper aims to present a deep learning and artificial neural network application in the field of stock market trading, specifically, in the analysis and forecasting of the stock market prices as an additional tool to reduce risk and increase profits. The goal of the paper is to introduce a new form of technology, show its potential, and encourage further research into this subject in the Republic of Croatia. To achieve this goal and to present the potential of this technology, two different artificial neural network prototypes were built, trained, and tested on the available set of historical stock price data from the Zagreb Stock Exchange. Two artificial networks were build using Python programming language: Long Short-Term Memory (LSTM) network and Multilayer Perceptron (MLP) network. Both artificial neural networks were built and the data sets they were trained and tested on were taken from the Zagreb Stock Exchange, containing historical stock prices of Croatian telecommunication companies, Optima Telekom (OPTE), and Hrvatski Telekom (HT). The results, i.e. price predictions, of both neural networks are presented in two parts. First, for OPTE stock prices and then for HT stock prices.