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DETECTING FACTORS WHICH IMPACT THE PARTICIPATION OF YOUTH IN SHARING ECONOMY PRACTICES IN SERBIA
No full textEkonomija deljenja se smatra savremenim poslovnim modelom koji omogućava deljenje proizvoda i
usluga između pojedinaca posredstvom online platformi na određeno vreme, po određenim uslovima i po
dogovorenoj ceni. Od kada je koncept prvi put definisan na ovaj način 2010. godine interesovanje kako
pojedinaca, tako i donosilaca odluka i istraživača za oblast je u značajnom porastu. Jedno od osnovnih pitanja
koje se postavlja je koji su to faktori koji utiču na učešće pojedinca u ekonomiji deljenja, kako i šta se može učiniti
kako bi se što veći broj pojedinaca uključio u ovaj koncept. Ovo istraživanje ima za cilj da analizira uticaj sociodemografskih
faktora na učešće mladih u ekonomiji deljenja, kao i da sagleda razlike u percepciji čitavog
koncepta u zavisnosti od prethodnog iskustva učešća u ekonomiji deljenja. Rezultati ukazuju da stariji ispitanici
i oni koji imaju više novca kojim samostalno raspolažu više učestvuju u ekonomiji deljenja. Takođe, pokazano je
da su oni koji su učestvovali u ekonomiji deljenja svesni da postoji manjak osiguranja ljudi i dobra u ovom
modelu, kao i da oni smatraju da je mogućnost zloupotrebe ličnih podataka veoma mala. Dobijeni rezultati mogu
poslužiti prilikom kreiranja kampanja koje imaju za cilj da podignu svest o mogućnostima i beneficijama učešća
u ekonomiji deljenja.The sharing economy is considered a contemporary business model that enables the sharing of
products and services between individuals through an online platform for a certain period of time, under certain
conditions and at an agreed price. Since the concept was first defined in 2010, the interest of individuals,
decision-makers and researchers in the field has grown visibly. One of the basic questions that emerges is what
are the factors that influence the participation of an individual in the sharing economy, as well as what can be
done and in what way to involve as many individuals as possible in this concept. This research aims to analyse
the impact of socio-demographic factors on the participation of youth in the sharing economy, as well as to look
at the differences in the perception of the whole concept depending on the previous experience with the sharing
economy. The results indicate that older respondents and those with higher amounts of money they spend
independently participate more in the sharing economy. Also, it was shown that those who participated in the
sharing economy are aware that there is a lack of insurance for people and goods in this model, and that they
believe that the possibility of misuse of personal data is minimal. The obtained results can be used to create
campaigns which aim at raising awareness about the possibilities and benefits of participating in the sharing
economy
ANALYSIS OF PERCEPTION AND MOTIVES OF PARTICIPANTS ON THE SHARING ECONOMY MARKET IN SERBIA
No full textEkonomija deljenja, kao novi ekonomsko-društveni model koji promoviše pružanje privremenog
pristupa ograničenim resursima bez prenosa vlasništva nad istim, nosi brojne nepoznanice i kontroverze. Cilj
ovog rada je da sagleda percepciju i najvažnije motive ključnih aktera ekonomije deljenja na području Srbije.
Sprovedeno je eksploratorno istraživanje koje targetira provajdere (pružaoce usluga) i korisnike usluga na tržištu
ekonomije deljenja. Kvalitativno istraživanje putem ekspertskog intervju primenjeno je na uzorku provajdera
usluga ekonomije deljenja dok se kvantitativno istraživanje, sprovedeno putem onlajn anketnog upitnika,
odnosilo na korisnike usluga deljenja. Rezultati pokazuju da su i provajderi i korisnici usluga ekonomije deljenja
u Srbiji generalno zadovoljni iskustvom u ekonomiji deljenja – najviše funkcionisanjem platformi, ali i tačnošću
i ažurnošću realizovanja usluga, pristupačnim cenama i ljubaznošću provajdera. Iako postoji saglasnost u tome
da će se koncept razvijati, dosadašnji umereni intenzitet učestvovanja u ekonomiji deljenja verovatno će ostati
na sličnom nivou. Kao glavno ograničenje navodi se nedovoljno zadovoljstvo promotivnim aktivnostima
ekonomije deljenja. Kod obe grupe ispitanika preovladavaju ekonomski motivi korišćenja, odnosno motivi zarade
i uštede u troškovima. Iako deljenje u svojoj osnovi ima socijalnu komponentu, društveni i ekološki motivi su
znatno manje prisutni u Srbiji, naročito u poređenju sa zemljama EU.The sharing economy, as a new economic-social model that promotes temporary access to limited
resources without transferring ownership, carries numerous unknowns and controversies. The aim of this paper
is to examine the perception and motives of key stakeholders in the sharing economy in Serbia. An exploratory
research targeting service providers and users in the sharing economy market was conducted. Qualitative
research, based on expert interviews, was applied to a sample of sharing economy service providers, while
quantitative research, conducted through an online survey, focused on sharing economy service users. The
results indicate that both providers and users of the sharing economy in Serbia are generally satisfied with their
experience in the sharing economy, particularly with the functioning of platforms, accuracy and timeliness of
service delivery, affordable prices, and provider friendliness. Although there is an agreement that the concept
will continue to develop, the current moderate level of participation in the sharing economy is likely to remain
similar. Insufficient satisfaction with promotional activities is considered the main limitation of the sharing
economy development. Economic motives, such as earnings and cost savings, prevail among both groups of
respondents. Although sharing inherently has a social component, social and environmental motives are
significantly less present in Serbia, especially when compared to EU countries
A Data Warehouse System for an Analysis of Unemployment Rate in the Republic of Serbia
No full textIn the paper, we present a data warehouse system to analyze the unemployment rate in the Republic of Serbia. The goal of our research is to improve the analytical capabilities of the unemployment rate in Serbia by creating a new business intelligence tool and predictive machine learning models. First, we discuss research motives and the unemployment problem, and then we present the development process of the proposed data warehouse system. The Data Warehouse Quality methodology has been deployed to assess the quality of the data. Machine learning algorithms have been utilized to build predictive models and gain insights into the differences in unemployment rates between young and experienced workers. Finally, we have created several reports to visually present the results of the proposed data analyses
Digitalni poslovni sistem ekonomije deljenja: kako se evropske zemlje mogu segmentirati?
No full textEkonomija deljenja, koja se ponekad naziva i kolaborativna potrošnja, je koncept, poslovni model i tržište na kojem pojedinci nude ili iznajmljuju sopstvenu imovinu koja nije u upotrebi. Različiti tipovi ekonomije deljenja su se pojavili od zajedničkog smeštaja do deljenja modnih predmeta. Bez obzira na to šta se deli, dogovor o tome šta se deli i pod kojim okolnostima se obično sklapa preko veb-stranice ili platforme u okviru digitalnog ekosistema. Istraživačko pitanje je kako se evropske zemlje mogu segmentirati na osnovu karakteristika korisnika zajedničkog smeštaja
The Role of Information and Measurement Standards in the Development of Innovative Technology, Product or Service: Examples from Different Industries
No full textAssessment of the Bankruptcy Risk in the Hotel Industry as a Condition of the COVID-19 Crisis Using Time-Delay Neural Networks
No full textIn this paper we demonstrate a new conceptual framework in the application of multilayer perceptron (MLP) artificial neural networks (ANNs) to bankruptcy risk prediction using different time-delay neural network (TDNN) models to assess Altman's EM Z ''-score risk zones of firms for a sample of 100 companies operating in the hotel industry in the Republic of Serbia. Hence, the accuracies of 9580 forecasting ANNs trained for the period 2016 to 2021 are analyzed, and the impact of various input parameters of different ANN models on their forecasting accuracy is investigated, including Altman's bankruptcy risk indicators, market and internal nonfinancial indicators, the lengths of the learning periods of the ANNs and of their input parameters, and the K-means clusters of risk zones. Based on this research, 11 stability indicators (SIs) for the years under analysis are formulated, which represent the generalization capabilities of ANN models, i.e., differences in the generalization errors between the preceding period and the year for which zone assessment is given; these are seen as a consequence of structural changes at the industry level that occurred during the relevant year. SIs are validated through comparison with the relative strength index (RSI) for descriptive indicators of Altman's model, and high correlation is found. Special focus is placed on the identification of the stability in 2020 in order to assess the impact of the COVID-19 crisis during that year. It is established that despite the fact that the development of bankruptcy risk in the hotel industry in the Republic of Serbia is a highly volatile process, the largest changes in the analyzed period occurred in 2020, i.e., the potential applications of ANNs for forecasting zones in 2020 are limited
Analysis and Development of the Model for Google Assistant and Amazon Alexa Voice Assistants Integration
No full textVoice assistants enable various task execution. In addition, voice assistants provide application programming interfaces for designing additional skills and intents. However, the problem is that each assistant defines its own programming interface and there is no interface compatibility. The aim of this research is the analysis and development of a software library for the integration of Google Assistant and Amazon Alexa voice assistants. In this context, similarities and differences were observed, and an API for the integration of voice assistants was defined accordingly. To verify the validity of the model, a project management software system was developed in the Jakarta Enterprise Edition environment. The software system supports interaction with Google Assistant and Amazon Alexa assistants
Generation Z’s Intentions Towards Sustainable Clothing Disposal: Extending the Theory of Planned Behavior
No full textThe objective of the study is to propose and empirically examine a model of the determinants of Generation Z apparel consumers’ intentions to dispose of their used clothing in a sustainable way, via clothing collection and recycling boxes established in fashion retail stores. The study builds upon the acknowledged model for human behavior predictions, the Theory of Planned Behavior, and enhances it by the inclusion of green consumption values. A survey performed in Serbia by means of self-administered questionnaire resulted in 386 responses. Structural equation modeling (SEM) indicated perceived behavioral control as the most influential determinant of customers’ intentions to dispose of used clothing via clothing collection boxes. Subjective norms, in spite of insignificant direct impact on intentions, emerged as the second most relevant determinant of customer disposal intentions, in terms of total effect, followed by green consumption values and attitudes. Implications of the study are discussed and limitations and future research directions are noted
Financial, Accounting and Tax Implications of Ransomware Attack
No full textRansomware is a prime cybersecurity threat at the moment. In this paper we analyze financial implications of ransomware attacks, motivation of the ransomware victim to pay ransom, and legal, accounting and tax implications of such payment. The methodological approach used in the study is a combination of formal-dogmatic method and argumentative literature review. First, we provide an overview of all potential losses which could be incurred by the ransomware attack. Further, we analyze under which conditions is legal to pay any kind of ransom, including cyber ransom, as an organization as well as which other considerations victims should consider when deciding to pay ransom. In that respect we analyze accounting and tax implications of losses inflicted by the ransom-ware attack, putting special attention to the ransom payments. CS