All papers are checked using
Volume 15, Number 1
SUSTAINABLE DEVELOPMENT PRACTICES IN ALGERIAN FAMILY BUSINESSES: AN EMPIRICAL INVESTIGATION
Abdellaoui FETHALLAH
Abstract: This research paper investigates the implementation of sustainable development practices in Algerian family businesses. Furthermore, it examines whether the application of these practices varies based on factors such as job title, educational attainment, and professional experience. A quantitative research methodology was employed, utilising a questionnaire survey administered to 100 middle and upper-level management employees in these companies. Data analysis was conducted using SPSS V.25. The findings revealed that Algerian family businesses engage in practices aligned with all three TBLs of SD (economic, social, and environmental). Moreover, no statistically significant differences were observed in the application of these practices across job titles, educational levels, or professional experience. The limitation of this study lies in its relatively small sample size (22 family firms) and its limited scope to the western region of the country. The study concludes by presenting a set of recommendations and prospects aimed at deepening the understanding of the role of family firms in achieving sustainable development and providing valuable insights that contribute to enhancing sustainable practices at both the local and regional levels.
Keywords: Sustainable Development; Algerian Family Businesses; Economic Dimension; Social Dimension; Environmental Dimension.
DOI:10.5937/JEMC2501003F
ОNBOARDING IN SMALL SOFTWARE ENTERPRISES: PRACTICAL RECOMMENDATIONS FROM A QUALITATIVE CASE STUDY
Verica GLUVAKOV, Mila KAVALIĆ, Maja GABOROV, Igor VECŠTEJN, Željko STOJANOV
Abstract: Onboarding is a cornerstone of effective workforce integration in the software industry, enabling rapid and seamless adaptation of employees to organisational workflows and culture. It is particularly critical for small software companies, where limited budgets, resource constraints, and unique organisational structures amplify onboarding challenges. This article investigates onboarding practices in a small software company, focusing on how new hires are effectively integrated into organisational culture and workflows. A qualitative case study approach was employed to uncover actionable insights and context-specific nuances. The findings highlight that cultural alignment, organisational learning, and hands-on knowledge-sharing are pivotal for effective new employee integration. However, challenges such as inconsistent documentation and a lack of standardised processes result in significant variability and inefficiencies. Despite identified shortcomings, the selected company demonstrates flexibility and adaptability in tailoring their approaches to individual needs. The results of this study may have wider implications for the software industry, particularly in creating inclusion strategies that address both human-centred and knowledge-management aspects. Findings from this research can guide small businesses toward more sustainable talent integration practices and contribute to industry-wide workforce development trends. Based on the research findings, recommendations for the practice are proposed.
Keywords:Onboarding; Small software companies; New employee integration; Qualitative case study; practice recommendations.
DOI:10.5937/JEMC2501016G
HOTEL GUESTS' LOYALTY, BEHAVIOR, AND SERVICE RECOVERY SATISFACTION BASED ON RATING PERCEPTION
Milica JOSIMOVIĆ, Milena CVJETKOVIĆ, Slavica PETROVIĆ RADIVOJEVIĆ
Abstract: This paper aims to examine the role of perceived hotel ratings as a mediator of loyalty in the relationship between service recovery satisfaction (SRS) and both the discretionary and dysfunctional behaviour of hotel guests. The research utilised analysis of variance, factor analysis, and structural equation modelling (SEM). The results indicate that perceived hotel ratings have an impact on SRS; specifically, the lower the hotel rating, the greater the impact of SRS on loyalty, and conversely, this is also the case regarding the influence of loyalty on guests' behaviour. Additionally, the findings suggest that the national culture of guests affects both SRS and hotel guest loyalty.
Keywords:Loyalty; Service recovery; Customer citizenship behaviour; Customer dysfunctional behaviour; Hotel industry.
DOI:10.5937/JEMC2501032J
ARTIFICIAL INTELLIGENCE FOR SMALL AND MEDIUM BUSINESS: PERSPECTIVES AND CHALLENGES
Anna KRAMARENKO
Abstract: This research examines the perspectives and challenges of artificial intelligence (AI) implementation in small and medium-sized enterprises (SMEs). Through analysis of academic literature, industry reports, and survey data from 63 companies, the study investigates the potential applications, benefits, and barriers to AI adoption among SMEs. The findings reveal that while AI offers significant opportunities for SMEs in areas such as process automation, data analytics, customer experience personalisation, and operational optimisation, adoption rates remain low. The research identifies several key barriers, including limited access to industry data, insufficient financial resources, lack of technical expertise, and challenges with data integration. Survey results indicate that only 13% of surveyed companies have experience working with AI, despite widespread use of basic information management systems. The study highlights five primary areas where generative AI can enhance SME performance: content creation, automated operations, venture business ideation, financial management, and operational optimisation. The conclusions emphasise the need for targeted support mechanisms, improved educational programmes, and policy frameworks to facilitate AI adoption among SMEs. This research contributes to understanding the role of AI in SME development and provides practical insights for business leaders, policymakers, and researchers working to enhance AI integration in small and medium-sized businesses.
Keywords:Artificial Intelligence, Small and Medium Enterprises (SMEs), Digital Transformation.
DOI:10.5937/JEMC2501043K
A LOGISTIC REGRESSION-BASED MODEL FOR PREDICTING HEART FAILURE MORTALITY
Marija KRSTIĆ, Lazar KRSTIĆ
Abstract: Recent trends in evaluating World Wide Web data include the use of traditional data mining techniques, such as regression, clustering, and classification. This paper aims to develop a model for predicting heart failure mortality based on a publicly available online dataset containing medical records of 299 patients. Since the prediction outcome can have only one of two possible values, the binary logistic regression technique was applied. Research shows that the predictive model created using logistic regression can accurately predict patient mortality based on their clinical characteristics and identify the most significant attributes among those included in their medical records. In addition, applying logistic regression ensures the simplicity and interoperability of the developed model, which was a major drawback of previous studies. The prediction model was created using the RapidMiner software tool. Its contribution lies in incorporating a broader range of clinical attributes, leading to a more comprehensive approach that enhances accuracy and prediction efficiency. The accuracy, precision, and sensitivity values of the developed predictive model are approximately 80%, confirming the model’s high quality. The Area Under the Curve (AUC), which provides a graphical overview of the model’s overall performance, is 86.7%, reflecting its effectiveness. The indicators of the developed model exhibit strong overall performance, creating the potential for its application to assist healthcare institutions in assessing the clinical status of patients with cardiovascular diseases.
Keywords:Predictive model; Logistic regression; Heart failure; Clinical characteristics; Patient mortality.
DOI:10.5937/JEMC2501057K
TOWARDS A SMART FACTORY IN THE PHARMACEUTICAL INDUSTRY
Vidosav D. MAJSTOROVIĆ
Abstract: The Industry 4.0 model is on the way to full maturity in production organisations, after more than a decade of application within them. It can be said that it was a key element for the digitisation of the economy and public services around the world, so today we can discuss the application of this concept in various areas, including the pharmaceutical industry. This paper aims to provide the latest information on the state of development of the Industry 4.0 model in the pharmaceutical industry (Pharma 4.0), which represents the path to a smart factory (SF) in this area. The paper consists of several parts, namely: (i) an analysis of the framework of the Pharma 4.0 model, (ii) its detailed presentation, and (iii) some observations on the future development of this model in application, all to develop a smart pharmaceutical factory (SPF).
Keywords:Industry 4.0, Pharmaceutical Industry, Pharma 4.0, Smart Factory.
DOI:10.5937/JEMC2501065M
Appendix: