Search Results (279)

This study provides a comprehensive assessment and synthesis of the literature on short-selling. It performs a lexicometric analysis, providing a quantitative review of 1093 peer-reviewed journal articles to identify and illustrate the main themes in short-selling research. Almost half the published literature on short-selling is thematically clustered around portfolio management techniques. Other key themes involve short-selling as it relates to risk management, strategic management, and market irregularities. Descending hierarchical classification examines the overall structure of the textual corpus of the short-selling literature and the relationships between its key terms. Similarity analysis reveals that the short-selling literature is highly concentrated, with most conceptual groups closely aligned and fitting into overlapping or conceptually similar areas. Some notable groups highlight prior short-selling studies of market dynamics, behavioral factors, technological advancements, and regulatory frameworks, which can serve as a foundation for market regulators to make more informed decisions that enhance overall market stability. Additionally, this study proposes a conceptual framework in which short-selling can be either a driver or an outcome by integrating the literature on its antecedents, consequences, explanatory variables, and boundary conditions. Finally, it suggests directions for future research. Full article

The adoption of artificial intelligence (AI) in marketing and social media is gaining scholarly interest. While AI technologies offer significant potential for enhancing customer engagement (CE), their effectiveness depends on an industry’s level of digital and AI readiness. This is especially relevant for people-centric sectors such as tourism and hospitality, where digital maturity remains relatively low. This study aims to understand how AI supports CE and social media marketing (SMM), and to identify the key antecedents and consequences of its use. Using the PRISMA approach, we conduct a systematic review of 55 peer-reviewed empirical studies on AI-based CE and SMM. Our analysis identifies the main contributing theories and AI technologies in the field, and uncovers four central themes: (1) AI in customer service and user experience design, (2) AI-based customer relationships with brands, (3) AI-driven development of customer trust, and (4) cultural differences and varying levels of AI readiness. We also develop a conceptual framework that outlines the determinants and outcomes of AI-based CE, including relevant moderators and mediators. The study concludes with directions for future research and provides theoretical and managerial implications, particularly for the tourism and hospitality industries. Full article

(1) Background: Intrapartum obstetric violence has become increasingly visible and is portrayed as a cross-cutting and complex phenomenon. Despite numerous international debates and extensive reports in the literature, there is limited consensus on its definition, emphasizing the need to clarify the concept. The aim of this article is to analyze the concept of obstetric violence in the care of women in labor in health institutions; (2) Methods: Search and selection of studies using the scoping review methodology, based on the Joanna Briggs Institute guidelines and Rodgers’ conceptual review method for data extraction and analysis; (3) Results: A sample of 49 studies provided a comprehensive understanding of the concept, revealing in its conceptualization attributes of physical, verbal, psychological, sexual, institutional and structural violence. Identification of antecedents of gender inequality and failure of relational, technical and structural standards at the level of health institutions and their professionals, as the main triggers of obstetric violence. Reporting of consequences with a negative impact on maternal and child health; (4) Conclusions: Conceptual analysis with important contributions to the paradigm shift in the work of health professionals. Multiple dimensions, cultural differences and variations in the concept should continue to be examined to improve its research and application. Full article

Misplaced confidence disguised as competence can lead to broad business blunders. The Dunning–Kruger effect (DKE) is an infamous illusory superiority cognitive bias in which people who perform poorly in certain skills erroneously perceive their task execution as superior to the performance of others. Although it is a metacognitive phenomenon with implications for various domains, it is yet to be directly investigated with managers. The purpose of this study is to bridge the research gap by qualitatively exploring the DKE’s manifestation among managers through 20 semi-structured interviews in agricultural businesses. We found that the DKE manifests at all levels of management; however, it seems that lower-level managers are more susceptible to this cognitive bias. We also present a conceptual framework that highlights the various antecedents and consequences of the DKE, based on our content analysis. This study presents a novel domain affected by the DKE, which was discovered by an unconventional methodological approach. Through the recommendations made, the study also contributes to the SDGs and sustainable leadership and management in agricultural businesses. Full article

The purpose of this review is to synthesise the accumulated knowledge on Global Innovation Index (GII) research. We utilised a corpus from the Web of Science Core Collection to systematically examine the antecedents, consequences, and relationships among the GII’s dimensions. Additionally, we employed the bibliometric techniques of bibliographic coupling and co-citation analysis to identify the leading areas of GII research and the foundational literature in this field. Our systematic review of GII empirical research allowed us to graphically represent the significant relationships among its dimensions. The findings from the bibliographic coupling revealed five recent lines of investigation in GII research: configurational methods; innovation efficiency and policy; competitiveness, entrepreneurship, and sustainable development; innovation rankings; and culture. Furthermore, the co-citation analysis highlighted four clusters of literature that have contributed to GII research. We aim to enhance the field of Innovation Studies by showcasing the current state of research on the GII, one of the most promising tools for measuring innovation activity, and to provide insights into potential future research avenues to further develop this area of study. Full article

Background: Cancer is a worldwide public health issue that impacts individuals in many ways. Family caregivers (FCGs) play a crucial role in providing care for cancer patients; as a result, they face several challenges as caregivers that sometimes go unreported. Aim: The purpose of this study was to explore the lived experiences of family caregivers with a developing burden of caring for a relative with a cancer diagnosis in Saudi Arabia. Methods: A qualitative study employing thematic analysis was conducted with ten family caregivers recruited through purposive sampling from the Prince Sultan Military City Hospital’s oncology department. Semi-structured interviews were conducted from July to August 2023 until data saturation was achieved. Results: Ten family caregivers participated in the study. Four main themes emerged from the data: antecedents to the caregiving burden, attributes of the caregiving burden, consequences of the burden, and religion and beliefs. Across these four main themes, there were 12 sub-themes. Conclusions and Implications: Family caregivers are crucial in caring for and supporting cancer patients. Thus, it is essential to shed light on family caregivers, who often remain invisible as secondary patients in healthcare systems, to understand the factors associated with developing caregiver burden. Education and support for family caregivers may decrease the burden on the family caregiver, which can positively impact the whole family unit, including the relative with the cancer diagnosis. Full article

Background/Objectives: Decision making is fundamental to personal autonomy and person-centered, rights-based psychiatric care. This study explored the perceptions and experiences of decision making in psychiatric care from the perspectives of service users, caregivers, and healthcare professionals, identifying contexts that facilitate or hinder these practices. Methods: An exploratory–descriptive qualitative design was applied, using semi-structured interviews with eight service users, six caregivers, and seven healthcare professionals (21 interviews in total). Data were transcribed verbatim and analyzed through inductive content analysis. Results: Four main categories were identified: (1) antecedents for decision making, (2) challenges in decision making, (3) consequences of decision making, and (4) recommendations for improvement. Conclusions: This study provides insight into how decisions in psychiatric care are made in Latvia, highlighting the legal, personal, and institutional factors influencing these processes. Participants offered valuable perspectives, identifying both facilitators and barriers to autonomous decision making, as well as suggesting necessary improvements. The findings suggest the need for legal reform and systemic improvements in practices that favor agency in decision making. Additionally, they underscore the importance of strengthening individual capacities to support meaningful collaboration among service users, caregivers, and healthcare professionals in making healthcare decisions that enhance the quality of care and well-being of people with mental health difficulties. Full article

This study examines the psychological mechanisms underlying virtual reality (VR) tourism experiences through an integrated theoretical framework centered on flow experience and visit destination intention. Drawing upon flow theory, the research investigates how interactivity, perceived vividness, and telepresence influence flow experience and subsequently affect hedonic motivation and perceived visual appeal in VR tourism contexts. Using partial least squares structural equation modeling (PLS-SEM) analysis of data collected from 255 VR tourism users across major Chinese metropolitan centers, the study reveals that perceived vividness and telepresence significantly impact flow experience, while interactivity shows no significant effect. Flow experience demonstrates significant positive relationships with hedonic motivation and perceived visual appeal. Furthermore, hedonic motivation and perceived visual appeal significantly positively affect visit destination intention. The findings advance the theoretical understanding of VR tourism by illuminating the psychological pathways through which technological characteristics influence behavioral intentions. These results offer practical implications for destination marketers and VR tourism developers in designing more effective virtual experiences that enhance destination visit intentions. Full article

Mobile payment technology (MPT) has emerged as a tool with the potential to advance financial inclusion and sustainable development. However, the existing literature inadequately explains how sustainability factors influence user behavior toward MPT adoption and how this behavior translates into financial inclusion especially under the influence of mobile transaction tax policies in African countries. This study addresses this gap by examining the antecedents of sustainable usage behaviors of MPT and their implications for digital financial inclusion in Ghana. Specifically, it integrates the triple bottom line (TBL) dimensions (economic, social, and environmental impact) with constructs from the theory of planned behavior (TPB) (attitude, perceived behavioral control, and subjective norms) into a unified sustainability-TPB framework. This study further investigates the moderating role of a mobile transaction tax policy (MTTP) on the relationship between sustainable usage behaviors and financial inclusion. The PLS-SEM method was utilized to analyze the theoretical model using the cross-sectional data of 320 respondents. The findings of this study supported that all TBL dimensions and TPB constructs influence behavioral intention and adoption through the usage of mobile payment technology and consequently financial inclusion. Notably, the mobile transaction tax policy negatively impacts the adoption of sustainable behaviors and financial inclusion. This study contributes to the current theoretical discourse on sustainable consumer behaviors and positions it on the broader sustainable development framework through financial inclusion by providing a shred of empirical evidence in the Ghanaian mobile payment industry perspective. The practical and policy implications are also suggested. Full article

A Dynamic Neuro-fuzzy Model (Dynamic Neuro-fuzzy Wind Predictor, DNFWP) is proposed for wind power prediction. The fuzzy rules in DNFWP consist of a typical antecedent part with static inputs, while the consequent part is a small three-layer neural network, incorporating unit feedback connections at the outputs of the neurons of the hidden layer. The inclusion of internal feedback targets to capture the intrinsic temporal relations of the dataset, while maintaining the local modeling approach of traditional fuzzy models. Each rule in DNFWP represents a local model, and the fuzzy rules operate cooperatively through the defuzzification process. The fuzzy rule base is extracted employing the Fuzzy C-means clustering algorithm, and the consequent neural networks’ weights are tuned by the use of Dynamic Resilient Propagation. Two cases with datasets of different volumes are tested and the performance of DNFWP is very promising, according to the results attained using a series of metrics like Root Mean Squared Error, Mean Absolute Error, and the r-squared statistic. The dynamic nature of the predictor allows it to operate effectively with a single input, thus rendering a feature selection phase unnecessary. DNFWP is compared to Machine Learning-based and Deep Learning-based counterparts, such that its prediction capabilities along with its reduced parametric complexity are highlighted. Full article

The growing importance of customer experience management (CEM) in the tourism sector has led to a proliferation of research interests in satisfaction enhancement, loyalty, and value co-creation. This study proposes a systematic and exhaustive thematic and bibliometric analysis of 3874 articles on CEM in the tourism industry published in the Scopus database between 1979 and 2024. Following the guidelines of the PRISMA protocol, the study uses Bibliometrix (version 4.4.1) in R and VOSviewer (version 1.6.20) to map publication trends, author networks, thematic and chronological evolution, and influential contributions. A qualitative content analysis of the most cited works, guided by grounded theory, revealed the main antecedents, consequences, mediators, and moderators of customer experience management. This analysis is embodied in the proposal of a conceptual model that illustrates the dynamic relationship between these elements and provides the basis for future research for theoretical enrichment and empirical validation. The results offer actionable insights for academics and industry practitioners alike, with the aim of promoting authentic and memorable tourism experiences. Full article

The mining of relevant association rules from transactional databases is a fundamental process in data mining. Traditional algorithms, however, will typically be based on fixed thresholds and general rule generation, with the result being large and redundant outcomes. This paper presents DERAR (Dynamic Extracting of Relevant Association Rules), a dynamic approach integrating structure pattern mining and dynamic multi-criteria filtering. The process begins with the generation of frequent meta-patterns. Each entity is given a stability score for its consistency across various data projections, then sorted by mutual information in order to preserve the most informative dimensions. The resulting association rules from these models are filtered through a dynamic confidence threshold that is adjusted according to the statistical distribution of the dataset. A final semantic filtering phase identifies rules with high coherence between antecedent and consequent. Experimental results show that DERAR reduces rules by up to 85%, improving interpretability and coherence. It outperforms Apriori, FP-Growth, and H-Apriori in rule quality and computational efficiency. DERAR consistently achieves lower execution times and memory use, especially on large or sparse datasets. These results confirm the benefits of adaptive, semantically guided rule mining for generating concise, high-quality, and actionable knowledge. Full article

Organic labeling is a potentially influential factor in shaping consumer behavior toward beef products. However, limited research has examined consumer responses about perceptions of organic beef. This research thus explores the relationship between organic perception of beef, price fairness, and revisit intention. This research also investigates the moderating role of freshness in the impact of organic perception of beef on price fairness using information overload as a theoretical underpinning. An online survey targeted American consumers, with 415 responses collected via Clickworker. All participants were based in the United States regarding the consumption amount in the market. The Hayes Process Macro Model 7 was employed to test the research hypotheses. This research performed a median split analysis to scrutinize the moderating effect of freshness on the relationship between organic perception and price fairness. The findings indicate that the perception of organically produced beef positively affects price fairness and revisit intention. Furthermore, price fairness was found to influence revisit intention. The study also revealed a significant moderating effect of freshness on the relationship between organic perception of beef and price fairness. These outcomes contribute to the literature by clarifying the interrelationships among these four attributes within the context of beef products. Full article

In order to cope with global warming, the Chinese government is actively promoting the “dual-carbon” target policy, a green and efficient system which will become the future development direction of China’s energy system. As the main body of the carbon emissions of enterprises is bound to be the focus of governance, we must accelerate green transformation. In this paper, we use procedural rooting theory, collect data from field interviews, and use open coding, principal axis coding, selective coding, and a theoretical saturation test to explore antecedent motivation mechanisms and the consequent pathway of the green change in corporate environmental behaviours under the “dual-carbon” goal. We aim to clarify the evolution of “internal and external factors—enterprise green change willingness—green change behavior” to construct a theoretical model. The results show that the influence of and interaction effects among the micro-level, macro-environmental level, and meso-industry level dimensions of enterprise will drive companies to make green changes and adopt green change behaviours in the forms of strategic change and innovation optimisation. This study enriches the theoretical framework of green change in corporate environmental behaviour under the rigid constraint of the “dual-carbon” goal and provides countermeasure suggestions for the successful achievement of the “dual-carbon” goal at the corporate body level. Full article

The impact of leaders on organizational success has been widely documented, and consequently, the leadership training industry has expanded over the past decades. However, this investment has not consistently translated into better leaders. Leadership intervention programs have received notable criticism, including (a) lacking individualization (‘one size fits all’ approach), (b) an emphasis on pre-defined skills, and (c) insufficient consideration of context, disregarding other members’ and organizations’ characteristics. This paper introduces and discusses Pro●Leader, an intervention program based on the Leadership Efficacy Model (LEM), which aims to promote leadership through a comprehensive approach to training. In essence, LEM proposes that leadership efficacy increases if leaders are congruent in how they intend to exert leadership (conceptual cycle of leadership) and how they indeed implement the leadership (practical cycle of leadership), considering also the leadership behaviors they display when exerting influence (leadership styles), as well as their own, team members’, and contextual characteristics (antecedent factors). The Pro●Leader intervention program is structured according to the LEM and trains participants across these three components: leadership cycles, styles, and antecedent factors. Full article