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Entrepreneurial marketing (EM) literature has evolved recently, but more understanding is needed on how the seven dimensions of EM impact causal and effectual entrepreneurial behavior and, similarly, how entrepreneurial behavior influences the results of all dimensions of the EM construct. This study investigates the association and mutual influence between EM and entrepreneurship.

This study uses a qualitative strategy, addressing gaps due to its low incidence and employs theoretical replication, which is practically unexplored. It investigates two cases in Brazil: small companies (eight cases selected by literal replication) and a structured network of companies (one case selected by theoretical replication), predicting a positive influence of EM in the first case and a negative or neutral influence in the second.

The influence of EM on entrepreneurship is context-dependent and varies according to the empirical object. In turn, the impact of entrepreneurship on the results of the EM dimensions is more stable, primarily causal and varies slightly between structures.

First, by studying how the dimensions of EM impact causal/effectual behavior, this study broadens the understanding of the area, which was previously focused on only a few dimensions. Second, by investigating the impact of entrepreneurship on EM outcomes, this study sheds light on the influence of and differences in causal/effectual behavior in each of the seven dimensions. Finally, it extends the understanding of EM and entrepreneurship in small businesses and a structured network by identifying similarities and distinctions hitherto unexplored.

The aim of this study is, from the perspective of artisan entrepreneurship, to trace and analyse the artisan's profile in the sustainable development of low population density cross-border territories, using the quintuple helix innovation model.

Ten semi-structured interviews were conducted with cultural and traditional artisans to achieve the proposed objective using a qualitative approach. The artisans are from Northeast Portugal (Bragança, Miranda do Douro, Mogadouro, Vimioso and Vinhais) and Northern Spain (Province of Zamora). The interviews were conducted face-to-face between May and June 2022. The interviews were manually transcribed and subjected to content and lexical analyses using IRaMuTeQ software.

An artisan was identified as an enterprising individual whose marketed handicraft pieces transmit the values and teachings of his community. Innovation, technology, sustainability and circular economy in a family environment, where dedication, resilience, happiness and hard work transmit an identity that places the artisan and his artisan practice as the driving force for the enhancement and promotion of his territory, cultural heritage and identity.

This work is the first study to address and treat the issue of artisan entrepreneurship by analysing and defining the cultural-based and traditional artisan profile in a cross-border and low population density territorial context.

This paper explores Lean Six Sigma principles and the DMAIC (define, measure, analyze, improve, control) methodology to propose a new Lean Six Sigma 4.0 (LSS 4.0) framework for employee occupational exams and address the real-world issue of high-variability exams that may arise.

This study uses mixed methods, combining qualitative and quantitative data collection. A detailed case study assesses the impact of LSS interventions on the exam management process and tests the applicability of the proposed LSS 4.0 framework for employee occupational exams.

The results reveal that changing the health service supplier in the explored organization caused a substantial raise in occupational exams, leading to increased costs. By using syntactic interoperability, lean, six sigma and DMAIC approaches, improvements were identified, addressing process deviations and information requirements. Implementing corrective actions improved the exam process, reducing the number of exams and associated expenses.

It is important to acknowledge certain limitations, such as the specific context of the case study and the exclusion of certain exam categories.

The practical implications of this research are substantial, providing organizations with valuable managerial insights into improving efficiency, reducing costs and ensuring regulatory compliance while managing occupational exams.

This study fills a research gap by applying LSS 4.0 to occupational exam management, offering a practical framework for organizations. It contributes to the existing knowledge base by addressing a relatively novel context and providing a detailed roadmap for process optimization.

The healthcare sector relies on knowledge management systems to improve knowledge flows and effectively capture, leverage and share knowledge with several organizational stakeholders. However, knowledge as a resource represents a social construct that involves additional managerial complexities and challenges, including undesirable knowledge behaviours. The aim of the current study is to provide insight on how knowledge management systems, knowledge hoarding, knowledge hiding and task conflict shape the quality of care provided by hospitals. We propose and test an original revealing model.

We follow a quantitative approach to address the structural relationship between variables using a combination of factor analysis and multiple regression analysis. The model is tested adopting a structural equation modelling approach and using survey data conducted to 318 healthcare professionals working in Portuguese hospitals.

The main findings suggest that knowledge hiding is positively related to task conflict in hospitals, and task conflict negatively influences quality of care. Knowledge management systems directly and indirectly (via knowledge hoarding) promote quality of care. Moreover, knowledge management systems also mitigate the negative influence of task conflict over quality of care. We propose a final corollary on the relevant role of HRM as the backstage for the model.

Our research offers a novel insight into an overlap of organizational behaviour and healthcare management research. It provides an original framework on knowledge management systems, counterproductive knowledge behaviours and task conflict in hospital settings.

Our research offers a novel insight into an overlap of organizational behaviour and healthcare management research. It provides an original framework on knowledge management systems, counterproductive knowledge behaviours and task conflict in hospital settings.

The purpose of this study is to evaluate and enhance sustainable manufacturing practices across various industries, focusing on environmental, economic and social dimensions, to promote a comprehensive understanding and implementation of sustainability, thereby improving overall industry performance and fostering long-term ecological and economic health.

The study uses multi-criteria decision-making-multivariate analysis technique to examine sustainable manufacturing practices (SMPs) in the Indian manufacturing sector. It identifies 11 SMP criteria through literature review and expert recommendations. Data are collected through questionnaires, expert committees and interviews. The study focuses on four key industries: automobile, steel, textile and plastic. Techniques like principal component analysis (PCA), technique for order preference by similarity to ideal solution (TOPSIS) and complex proportional assessment (COPRAS) are used to rank and assess performance.

The Indian automobile industry has shown the most effective SMPs compared to steel, textile and plastic sectors. The automobile sector is the benchmark for sustainable measures, emphasizing the importance of green practices for environmental, social and economic performance. Recommendations extend beyond the automobile sector to cement, electronics and construction.

The research emphasizes the importance of SMPs across various industries, focusing on economic, environmental and social considerations. It advocates for a holistic approach that enhances resource efficiency and minimizes ecological footprint.

The study uses ranking methods like PCA-integrated TOPSIS and COPRAS to evaluate performance in different industries, focusing on the benchmarked automobile sector. The research offers valuable insights and advocates for the widespread adoption of sustainable policies beyond the studied sectors.

The primary objective of this study is to understand how gamification elements, perceived teacher support and boredom relate to academic performance and how these relationships are mediated by perceived enjoyment while pointing out such influence on educational outcomes.

A quantitative survey methodology was conducted with 350 Lebanese university students specializing in digital marketing. This study used structural equation modeling (SEM) to analyze the data and provide exciting insights into the complex ties between variables.

The results indicate that well-implemented gamification elements significantly increased perceived enjoyment and positively influenced academic performance. Furthermore, perceived teacher support enhanced the effectiveness of gamification by increasing student engagement and enjoyment. Conversely, boredom negatively affects perceived enjoyment and academic performance, underscoring the need for well-designed gamification strategies that sustain interest and motivation.

Structural equation modeling and other quantitative tools excel at discovering connections but may not reveal the origins of the patterns they uncover. Given the complexity of causation, quantitative studies examining the mediating role of subjective satisfaction may gain more insight using a mixed or qualitative approach. Although the data supplied by the 350 responders were interesting, the sample size was insufficient to make any definitive conclusions. These findings may not be generalizable because Lebanon’s student bodies are diverse. The ability to detect tiny changes in the target variables requires researchers to consider how much time and energy they can dedicate to gathering data while structuring their investigations.

This study contributes to understanding gamification as a powerful tool for innovation in education and reshaping learning into motivating, engaging and sustaining productive experiences to improve educational quality. Therefore, our recommendations shed light on such improvements' impact on society. In this vein, we enrich this path by highlighting the crucial role of teachers and decision-makers in developing new professional programs.

This study demonstrates the importance of perceived enjoyment in the transformative gamification process in education. This study emphasizes the value of effective gamification implementation supported by teachers as a powerful tool for enhancing learning experiences and improving the quality of education.

This study aims to develop a novel diagnostic methodology for implementing ISO13485:2016 and test its applicability to improve quality management systems (QMS) in the medical devices industry context.

First, a literature review on the topic was conducted. Second, insights gained from the literature and expert interviews were employed to develop the new maturity assessment methodology. Subsequently, the methodology was tested on a medical device manufacturer. Next, based on the evaluation of the intervention, actions were recommended to improve the QMS.

Research findings have developed a maturity assessment methodology comprising 52 certifiable requirements structured into four macro-requirements derived from ISO 13485:2016. Findings show that the methodology is valuable for aiding QMS implementation, and the diagnosed maturity levels corresponded with the company’s empirical perceptions of the requirement’s maturity.

Empirical evidence validates the significance and practical utility of the proposed methodology, as evidenced by the company’s attainment of FDA (US Food and Drug Administration) approval after the intervention. Findings suggest that the methodology could be replicated within the medical products industry or adapted to assess other QMS, leveraging the organizational alignment with the international regulations of the sector and the ISO 9000 requirements.

The developed methodology fills existing gaps in both literature and practice within the medical devices industry, providing a valuable contribution by addressing the limited research on diagnostic methodologies designed for ISO 13485:2016 implementation. The article assists medical device enterprises in addressing QMS maturity levels as a metric for evaluating QMS requirements, which is an underexplored avenue in existing QMS evaluation approaches.

Challenges related to sustainability have increasingly become pivotal in the realm of business strategy and innovation. Nevertheless, the incorporation of sustainability principles into business strategies and innovative practices remains a subject of ongoing scholarly debate. This paper aims to undertake a thematic literature review on this theme.

Data were gathered from the Scopus, Web of Science and Science Direct databases. The final sample comprised 85 papers. For analytical purposes, this study adopted topic modeling using Latent Dirichlet Allocation (LDA) methodology.

The authors identified five dominant topics concerning the relationship between sustainability, innovation and business strategy. Through a cross-analysis of these topics, the authors theorize that a sustainable innovation strategy encompasses three complementary and interdependent dimensions: capabilities, management and firm. Building on this analysis, the authors outline a research agenda aimed at further exploration and advancement of this theme.

This review enhances the synthesis of research on the theme, prompting reflections on how companies can initiate innovative sustainable actions that align with their business strategy. Additionally, the authors identify specific elements that require improvement to enhance each of the three dimensions of sustainable innovation strategies, such as eco-efficiency, circular economy and the adoption of innovative business models oriented toward services/servitization.

By interweaving sustainability with innovation and business strategy, this study underscores the critical topics that companies and public policymakers should address to support sustainable development at the national level.

While previous literature reviews have focused on the dyadic relationships between sustainability and strategy, or sustainability and innovation, this study extends the boundaries of knowledge by integrating these three concepts into a hybrid theoretical stream.

This study focuses on enhancing the accuracy and efficiency of employee performance prediction to enhance decision making and improve organisational productivity. By introducing advance machine learning (ML) techniques, this study aims to create a more reliable and data-driven approach to evaluate employee performance.

In this study, nine machine learning (ML) models were used for forecasting employee performance: Random Forest, AdaBoost, CatBoost, LGB Classifier, SVM, KNN, XGBoost, Decision Tree and one Hybrid model (SVM + XGBoost). Each ML model is trained on an HR data set covering various features such as employee demographics, job-related factors and past performance records, ensuring reliable performance predictions. Feature scaling techniques, namely, min-max scaling, Standard Scaler and PCA, have been used to enhance the effectiveness of employee performance prediction. The models are trained to classify data, predicting whether an employee’s performance meets expectations or needs improvement.

All proposed models used in the study can correctly categorize data with an average accuracy of 94%. Notably, the Random Forest model demonstrates the highest accuracy across all three scaling techniques, achieving optimise accuracy, respectively. The results presented have significant implications for HR procedures, providing businesses with the opportunity to make data-driven decisions, improve personnel management and foster a more effective and productive workforce.

The scope of the used data set limits the study, despite our models delivering high accuracy. Further research could extend to different data sets or more diverse organisational settings to validate the model’s effectiveness across various contexts.

The proposed ML models in the study provide essential tools for HR departments, enabling them to make more informed data driven decisions with regard to employee performance. This approach can enhance personnel management, improve workforce productivity and fostering a more effective organisational environment.

Although AI models have shown promising outcomes, it is crucial to recognise the constraints and difficulties involved in their use. To ensure the fair and responsible use of AI in employee performance prediction, ethical considerations, privacy problems and any biases in the data should be properly addressed. Future work will be required to improve and broaden the capabilities of AI models in predicting employee performance.

This study introduces an exclusive combination of ML models for accurately predicting employee performance. By employing these advanced techniques, the study offers novel insight into how organisations might transition from a conventional evaluation method to a more advanced and objective, data-backed approach.

This study aims to investigate the contribution of higher education institutions (HEIs) to the sustainable development goals (SDGs) and propose strategies to cultivate a culture centred on the SDGs in HEIs.

The methodology used encompassed an integrative literature review, combining bibliographic analysis on how HEIs incorporate the SDGs into their practices, adopting a qualitative approach for the analysis and categorization of the results.

The multifaceted contributions of HEIs in promoting the SDGs stand out, through their roles in teaching, research, management and integration and communication between university and society.

While influencing policies at various levels, HEIs encounter challenges in the effective integration of SDGs into their strategies. This underscores the need for contextualized governance, understanding students’ perspectives on sustainability and active external collaboration in policy formulation.

There is an urgent need to integrate SDGs into academic programmes, emphasizing the importance of redesigning curricula, actively involving teachers, researchers and students, establishing partnerships and promoting research applied to SDGs.

The social relevance of the study lies in the emphasis on an SDG-centred culture, involving teaching, research, outreach, community engagement and governance practices.

The study’s uniqueness lies in identifying persistent challenges during the transition to an SDG-centred culture, necessitating multisectoral collaboration and educational programmes that integrate sustainability principles into the strategy of HEIs.