The development of the circular economy (CE) has become a strategic priority for the EU to achieve the UN’s Sustainable Development Goals. While the number of CE-based start-ups is burgeoning, established companies seem to be slower to adopt CE. Incorporating CE principles requires established firms to transform their business processes and activities from a linear to a circular approach, which often requires the introduction of significant and complementary technological and non-technological innovations, as well as significant investments that may hamper the firm’s overall performance. Thus, the disruptive nature of CE adoption may make established firms reluctant to embrace this process and underlines the need to identify its drivers and to clarify its potential benefits. Accordingly, we analyze the role of entrepreneurial orientation (EO) in promoting circular human resource management (CHRM), circular product innovation and circular manufacturing. This study is the first to define and measure CHRM and one of the few to apply the concept of EO in the context of CE. Using seemingly unrelated regressions (SUR), we find that EO promotes circular innovation directly and indirectly through CHRM. This factor represents a non-technological innovation which directly impacts on circular product innovation and circular manufacturing, whilst reinforcing the complementarity between non- technological and technological innovation. This research also addresses concerns about potential conflicts in achieving different types of CE performance simultaneously. By analyzing firm performance from a holistic perspective, our study confirms that CE implementation leads to environmental, market and social performance improvements together with the moderating role of technological turbulence.

The fashion industry, despite generating great benefits in terms of trade, employment and income worldwide, is considered one of the most polluting industries due to the linearity of its production process with a high consumption of energy and raw materials as well as of waste generation. Furthermore, the short life cycles of its products, where the consumer seeks more to be fashionable than the products’ durability, contribute to this. However, this paradigm is changing due to society’s increased concern for the environment and a healthier way of life, promoting the emergence of a new concept called slow fashion, which seeks to improve the sustainability of fashion items from an environmental and ethical point of view. In this way, many companies are implementing circular economy measures in their production processes and innovating more circular products. The purpose of this work was to determine the consumer orientation toward slow fashion consumption, their perceived value and if they are willing to accept changes in their own behavior. The results confirm this new consumer orientation toward slow fashion consumption, which entails an important business transformation, fostering the innovation of new products and manufacturing systems characterized by a circular approach.

Purpose: Digitalization is revolutionizing the retail sector as today's consumers prefer a seamlessly integrated, fluid and irritation-free shopping experience enhanced with artificial intelligence (AI)-powered technologies. Literature highlights gaps in the understanding of the shopping experience in an omnichannel context, involving aesthetic, cognitive and affective experience dimensions. This research highlights the direct effects and the mechanism triggered in the presence of such device.Design/methodology/approach: A sample of 259 consumers was interviewed at the point of sale. Data have been collected after a shopping experience in two concept stores belonging to the same fashion brand: (1) not equipped with AI-powered technology and (2) equipped with these tools. The measurement scales were validated through ANCOVA analysis and causal relationship analysis with structural equation modeling.Findings: The results show that the presence of an in-store AI-powered technologies in a connected store generates a higher aesthetic reaction when visiting the store, a higher absorption when shopping through the flow and a higher intent to purchase. The authors further investigate the underlying mechanism triggered by the presence of this technology, which enables the authors to outline their consequences regarding purchase intention.Originality/value: The study, conducted within an actual connected store in France, explores the impact of AI technology in connected retail environments on consumer responses. It is an early research in this field, shedding light on a rarely explored area. The authors’ research addresses a significant gap, providing insights into AI-driven retail experiences.

University dropout is a phenomenon of growing interest due to the high financial costs that it involves for both families and states. Various variables have been studied in order to understand why this problem occurs. Satisfaction with the degree choice, study self-regulation and social adaptation within the university are some of the variables that are most important when studying the dropout intention. However, studying these variables is not an easy task and Fuzzy Inference Systems have helped by reducing the subjectivity of language. Therefore, the objective of this research is to adapt Fuzzy Inference Systems to improve knowledge about the intention to remain at university. We performed descriptive analyses, a classification tree and Multiple-criteria Decision-Making based on Analytic Hierarchy Process (AHP) and Fuzzy Inference Systems (FIS) on a sample of 1912 students from different universities in Spain. We saw a relationship between the three variables studied and the intention to remain. In conclusion, there is no single variable for understanding the phenomenon of university dropout, but several variables that interact within a holistic model.

The expansion of Higher Education increased the diversity of students, with heterogenous characteristics, needs, and values. Institutions, intending to preserve the mission and the transformative potential of the tertiary level of education, are facing and implementing policies and practices that enhance success conditions, persistence, and avoid student dropout, in order to meet the goals for sustainable development of people and societies. The present study aims to analyze the impact of personal and academic variables on students’ academic difficulties in adaption to HE, academic achievement, and dropout among first-year STEM students. From a cohort of STEM first-year students at a Portuguese public university, the participants numbered 1376. Applying the structural equation modelling, the results highlight the effect of the variables age, gender, scholarship, and grade point average on access to higher education, difficulties in adapting to higher education, and dropout decision. Understanding STEM students who have already dropped out can contribute to better identification of institutional actions to prevent and reduce its occurrence, especially in first-year students.