Vol. 58 No. 2 (2025)

Background/Purpose: Cultural competence in the healthcare system is a crucial strategy to ensure the availability, accessibility, acceptability, and quality of healthcare services. However, literature on the systemic implementation of this concept in the Central and Eastern European region is scarce. The aim of our study is to present insights into the barriers to cultural competence and measures for its advancement in the Slovenian healthcare system.
Methods: We employed a qualitative methodology, conducting semi-structured interviews with professionals and experts in Slovenian healthcare system. Data was analysed by directed content analysis.
Results: The identified barriers to cultural competence and measures for its advancement pertained to several areas, including staffing, information for healthcare users, multidisciplinary and multi-level approaches, data collection and research, communication possibilities and skills, legislative foundation, flexibility of the healthcare system, quality standards, and educational efforts and policies.
Conclusions: In our study, we found that most barriers to cultural competence exist at the systemic and organizational level. Consequently, the measures identified to address these barriers should also be implemented at these levels. The first step towards achieving safer and more equitable healthcare services should involve incorporating the core principles of cultural competence into strategies and policies at both systemic and organizational levels of healthcare.

Keywords: Cultural competency, Patient diversity, Obstacles, Strategies, Healthcare system

Oğuzhan KODALAK

Necmettin Erbakan University, Department of International Trade and Finance, Turkey

Abstract

Purpose: This study aims to investigate how role overload and work-family conflict influence turnover intention and job satisfaction among public employees, providing insights for management practices to enhance employee well-being and organizational effectiveness.
Design/Methods: Quantitative data were collected from 390 public employees in the Central Anatolia region of Turkey. Structural equation modeling (SEM) was employed to analyze the relationships between role overload, work-family conflict, job satisfaction, and turnover intention.
Results: The study reveals that role overload positively influences work-family conflict, which in turn negatively impacts job satisfaction and increases turnover intention among public sector employees. Furthermore, job satisfaction is found to negatively affect turnover intention.
Conclusion: The findings highlight the importance of addressing role overload and work-family conflict to mitigate turnover intention and enhance job satisfaction among public employees. From a practical perspective, this study suggests that organizations should prioritize initiatives aimed at reducing role overload and managing work-family conflict to foster a positive work environment and retain talented employees. Socially, the study underscores the significance of supporting employees in balancing work and family responsibilities to promote their overall well-being and contribute to societal welfare.

Keywords: Role overload, Work-family conflict, Turnover intention, Job satisfaction, Role conflict theory

University of Maribor, Faculty of Economics and Business, Department of Marketing, Maribor, Slovenia

Tomaž GJERGJEK

University of Maribor, Faculty of Economics and Business, Department of Marketing, Maribor, Slovenia

DOI: https://doi.org/10.2478/orga-2025-0009

Abstract

Background/Purpose: This article explores consumers’ perception of the benefits of intelligent service robots (ISR) in the purchasing process, their trust in artificial intelligence (AI), their perception of AI-related threats, and the impact of these variables on consumer attitudes toward AI. Additionally, the study examines the moderating effect of perceived AI-related threats on the relationship between perceived benefits and trust on one side and the formation of consumer attitudes toward AI on the other.
Methods: The research was conducted in the first half of 2024 on a judgmental sample of 224 employed consumers in the Republic of Slovenia. Data were collected through a structured online questionnaire. For the empirical analysis, a non-parametric approach using SEM-PLS modelling was applied to examine relationships between the studied research constructs.
Results: The findings indicate that perceived benefits of ISR have a strong and positive impact on consumer attitudes toward AI, while perceived AI-related threats strongly and negatively influence these attitudes. Moreover, the results reveal that perceived AI-related threats significantly and negatively moderate the effect of consumers’ perceived trust in AI on the formation of their attitudes toward AI.
Conclusion: The results of this study contribute significantly to the theoretical understanding of employed consumers’ attitudes toward AI. They also provide practical implications for companies in developing predictive models of consumer behaviour and defining effective marketing strategies to encourage AI adoption in the purchasing process.

Keywords: Artificial intelligence (AI), Consumer attitudes, Perceived AI-related threats, Perceived benefits of intelligent service robots (ISR), Perceived consumer trust

JEL Classification: M21, M31

QA Higher Education, Lecturer/Dissertation Supervisor, London, UK

Fayyaz Hussain QURESHI

University of Wales Trinity Saint David (UWTSD), PGR (Doctoral) Supervisor, Lampeter, UK

DOI: https://doi.org/10.2478/orga-2025-0010

Abstract

Background/Purpose: This study examines the relationship between dynamic capabilities (DCs) and environmental performance (EP) in high-tech SMEs in Pakistan, focusing on the key dimensions of sensing, seizing, and reconfiguration. Additionally, it explores the mediating role of environmental innovation (EI) and the moderating effect of female leadership on this relationship.
Methods: A quantitative research approach was employed, using a structured questionnaire distributed among male and female Chief Executive Officers (CEOs), senior management personnel, and executives in high-tech SMEs. Data were analysed using structural equation modelling (SEM) to assess the relationships between DCs, environmental innovation, and environmental performance.
Results: The findings indicate that seizing capabilities significantly enhances environmental performance, with a one-point increase leading to a 0.282-point improvement. Similarly, reconfiguration contributes positively, with a one-point increase resulting in a 0.227-point improvement. Both process innovation (path coefficient = 0.384, p = 0.001) and product innovation (path coefficient = 0.157, p = 0.043) positively influence environmental performance. However, female leadership did not exhibit a significant direct effect on environmental performance. Notably, female moderators negatively impacted the relationship between process innovation and environmental performance (-0.328), suggesting that in lower hierarchical positions, female inclusion may reduce the effectiveness of process innovation in achieving sustainability goals.
Conclusions: The study provides empirical evidence on the role of dynamic capabilities and environmental innovation in enhancing sustainability in high-tech SMEs. It highlights the need for firms to strengthen their seizing and reconfiguration capabilities to improve environmental performance. Additionally, eco-innovation should be encouraged, and gender diversity in leadership should be strategically considered when designing innovation and sustainability strategies. These findings offer valuable insights for policymakers and industry practitioners aiming to foster sustainable business practices in high-tech SMEs in Pakistan.

Keywords: Dynamic capabilities, Environmental performance, High-Tech SMEs, Eco-Innovation, Female leadership

Universidade Europeia (Lisboa, Portugal); Graduate School of Business Leadership, University of South Africa, Pretoria, South Africa; and NECE – Research Unit in Business Sciences, Covilhã, Portugal, ORCID 0000-0002-0114-313X

Anabela MONTEIRO

Universidade Europeia (Lisboa, Portugal); CiTUR – Centre of Applied Research in Tourism and Hospitality of the Polytechnic Institute of Leiria, ORCID 0000-0001-8506-6073

DOI: https://doi.org/10.2478/orga-2025-0011

Abstract

Purpose: The current study has two primary goals: first, to examine the influence of corporate purpose on organizational innovation and second, to analyze the sequential mediation effect of both a people-centric approach and infrastructure between corporate purpose and organizational innovation.
Design/Methodology: A sequential explanatory mixed-method design was used in this study. Confirmatory factor analysis (CFA) and PROCESS macro were applied based on 188 online questionnaires completed by employees of a leading Portuguese publishing company, followed by a thematic analysis of 37 structured interviews.
Results: The quantitative findings indicate that corporate purpose has a positive impact on organizational innovation and that both the people-centric approach and organizational infrastructure serve as significant mediators in the relationship between corporate purpose and organizational innovation. Moreover, the people-centric approach and organizational infrastructure sequentially mediate the relationship between corporate purpose and organizational innovation. The qualitative data corroborate and deepen these findings, revealing the crucial role of a people-centric approach and organizational infrastructure as mediators in corporate purpose to cope with organizational innovation.
Conclusions: Our study provides theoretical and practical implications for practitioners, researchers, and business leaders to better understand the relationship between these concepts and opportunities for further research.

Keywords: Corporate purpose, Organizational infrastructure, Organizational innovation, People-centric approach, Sequential mediation

University of Primorska, Faculty of Management, Koper, Slovenia

DOI: https://doi.org/10.2478/orga-2025-0006

Abstract

Background and Purpose: This article employs the Hugging Face keyphrase-extraction-kbir-inspec machine learning model to analyze 654 abstracts on the topic of energy efficiency in systems and control, computer science and robotics.
Methods: This study targeted specific arXiv categories related to energy efficiency, scraping and processing abstracts with a state-of-the-art Transformer-based Hugging Face AI model to extract keyphrases, thereby enabling the creation of related keyphrase networks and the retrieval of relevant scientific preprints.
Results: The results demonstrate that state-of-the-art open-source machine learning models can extract valuable information from unstructured data, revealing prominent topics in the evolving field of energy-efficiency. Conclusion: This showcases the current landscape and highlights the capability of such information systems to pinpoint both well researched and less researched areas, potentially serving as an information retrieval system or early warning system for emerging technologies that promote environmental sustainability and cost efficiency.

Keywords: Energy efficiency, Keyphrase extraction, Early warning system, Information system, Semantic network, Transformers, Industry 4.0