Search Results (26)

This research analyzes the discourses and narratives surrounding the platform tourism economy in a highly touristified city, using Madrid as a case study. Rather than focusing on the socio-economic or spatial transformations themselves, the study examines how these processes are discussed, identifying the discursive strategies employed by different actors and ideologies, along with the power relations embedded in these narratives. A corpus of literature was compiled from twelve newspapers with varying ideological orientations and categorized according to political stance, access mode, and ideological radicalism. Using the LancsBox concordancer, a quantitative analysis was conducted to identify key discursive categories and preferred lexical items across ideological positions. These findings informed a subsequent in-depth qualitative analysis aimed at uncovering the rationalities behind each discourse: who speaks, how, and with what intent. The results reveal a dominant left-wing narrative that emphasizes institutional and economic mechanisms underlying platform tourism, highlighting associated social and urban harms. In contrast, conservative and liberal narratives are divided into two strands: a ‘heretic’ discourse that promotes and defends this new economic model, but also its urban results (e.g., gentrification), and a more institutional narrative framing platform tourism as inevitable and benign, thereby concealing the underlying structures of power. Full article

This study introduces an integrated lower limb robotic orthosis with near-field electrospinning (NFES) piezoelectric sensors and a fuzzy logic-based gait phase detection system to enhance mobility assistance and rehabilitation. The exoskeleton incorporates embedded pressure sensors within the insoles to capture ground reaction forces (GRFs) in real-time. A fuzzy logic inference system processes these signals, classifying gait phases such as stance, initial contact, mid-stance, and pre-swing. The NFES technique enables the fabrication of highly oriented nanofibers, improving sensor sensitivity and reliability. The system employs a master–slave control framework. A Texas Instruments (TI) TMS320F28069 microcontroller (Texas Instruments, Dallas, TX, USA) processes gait data and transmits actuation commands to motors and harmonic drives at the hip and knee joints. The control strategy follows a three-loop methodology, ensuring stable operation. Experimental validation assesses the system’s accuracy under various conditions, including no-load and loaded scenarios. Results demonstrate that the exoskeleton accurately detects gait phases, achieving a maximum tracking error of 4.23% in an 8-s gait cycle under no-load conditions and 4.34% when tested with a 68 kg user. Faster motion cycles introduce a maximum error of 6.79% for a 3-s gait cycle, confirming the system’s adaptability to dynamic walking conditions. These findings highlight the effectiveness of the developed exoskeleton in interpreting human motion intentions, positioning it as a promising solution for wearable rehabilitation and mobility assistance. Full article

The rapid growth and increasing adoption of cryptocurrencies have reshaped the investment landscape, presenting unique opportunities and challenges for investors. This study examines how advisory information sources influence cryptocurrency investment behaviors and intentions among U.S. investors. Using data from the 2021 National Financial Capability Study, it explores how reliance on financial professionals, media, and social networks shapes investment decisions. The motivation for this research lies in the need to understand the divergent roles of these sources in an era where traditional and emerging financial advice coexist. Findings reveal that reliance on financial advisors correlates with reduced cryptocurrency investment and future investment intentions, reflecting advisors’ cautious stance toward volatile assets. Conversely, reliance on media and social networks significantly increases both current investments and future intentions. The findings also highlight that investor confidence is positively associated with the likelihood and intentions to invest in cryptocurrency. Conversely, heightened risk perceptions associated with cryptocurrency reduce both the likelihood and intentions to invest. The study calls for financial professionals to enhance client education on cryptocurrency risks and for policymakers to strengthen regulations, ensuring accurate information dissemination through media and social networks. By providing a nuanced understanding of advisory influence and investors’ characteristics, this research offers valuable insights for financial professionals, policymakers, and investors navigating the complexities of cryptocurrency investments. Full article

Background: With the rapid expansion of the generative AI market, conducting in-depth research on cognitive conflicts in human–computer interaction is crucial for optimizing user experience and improving the quality of interactions with AI systems. However, existing studies insufficiently explore the role of user cognitive conflicts and the explanation of stance attribution in the design of human–computer interactions. Methods: This research, grounded in mental models theory and employing an improved version of the oddball paradigm, utilizes Event-Related Spectral Perturbations (ERSP) and functional connectivity analysis to reveal how task types and stance attribution explanations in generative AI influence users’ unconscious cognitive processing mechanisms during service failures. Results: The results indicate that under design stance explanations, the ERSP and Phase Locking Value (PLV) in the theta frequency band were significantly lower for emotional task failures than mechanical task failures. In the case of emotional task failures, the ERSP and PLV in the theta frequency band induced by intentional stance explanations were significantly higher than those induced by design stance explanations. Conclusions: This study found that stance attribution explanations profoundly affect users’ mental models of AI, which determine their responses to service failure. Full article

Understanding the labor market participation shift associated with an aging population and the challenges of employees who provide care to old-age relatives is essential to ensure progress toward the Sustainable Development Goals. The current study focuses on the decision of employees who combine paid work with unpaid care to relatives aged 65 and above to stay or leave their jobs. We draw on the Turnover Model and the Informal Caregivers Integrative Model (ICIM) to examine how two primary stressors—care burden and work demand—one secondary stressor—work–family conflict—and emotional exhaustion increase the turnover intentions of employees who combine paid work with eldercare to their old relatives aged 65 and over. By synthesizing these two models and using a survey with three chronological waves among 356 Israeli employees, we analyze a mediation model within a Structural Equation Modeling framework. The findings underscore the fact that work–family conflict (a secondary stressor) and the sense of exhaustion act as key mediators in the relationship between employees’ primary stressors and turnover intentions. The presence of primary stressors in themselves does not increase turnover intentions. Our findings imply that, rather than providing sporadic adaptations at work, policymakers, organizations, and human resource management systems should respond proactively to prevent the process from undermining employees’ ability to achieve equilibrium between their desire to work and care for their old-age relatives. Such a proactive stance would reduce their exhaustion and turnover intention. Full article

With the development of large language model technologies, the capability of social robots to interact emotionally with users has been steadily increasing. However, the existing research insufficiently examines the influence of robot stance attribution design cues on the construction of users’ mental models and their effects on human–robot interaction (HRI). This study innovatively combines mental models with the associative–propositional evaluation (APE) model, unveiling the impact of the stance attribution explanations of this design cue on the construction of user mental models and the interaction between the two types of mental models through EEG experiments and survey investigations. The results found that under the influence of intentional stance explanations (compared to design stance explanations), participants displayed higher error rates, higher θ- and β-band Event-Related Spectral Perturbations (ERSPs), and phase-locking value (PLV). Intentional stance explanations trigger a primarily associatively based mental model of users towards robots, which conflicts with the propositionally based mental models of individuals. Users might adjust or “correct” their immediate reactions caused by stance attribution explanations after logical analysis. This study reveals that stance attribution interpretation can significantly affect users’ mental model construction of robots, which provides a new theoretical framework for exploring human interaction with non-human agents and provides theoretical support for the sustainable development of human–robot relations. It also provides new ideas for designing robots that are more humane and can better interact with human users. Full article

This study investigates the relationship between the motives behind CSR and consumer extra-role behavior, as well as green purchase intention, specifically within the hospitality industry of an emerging market. This study uses two scenario-based experiments with high and low CSR fit contexts to examine how ethical corporate identity moderates the relationship. Both studies examine the impact of customers’ perceptions of a company’s CSR motivation (public-serving or firm-serving), on their extra-role behavior towards the company and intention to make green purchases. This influence is particularly relevant when the company actively communicates its ethical identity. The first study is conducted within a high-fit setting where the company’s locus aligns with its CSR program. In contrast, the second study replicates the research in a low-fit situation. The results indicate that CSR activities have a favorable effect on customer extra-role behavior and green purchasing intention, regardless of the CSR fit contexts. This effect is shown when the company’s ethical stance is known before engaging in CSR activities and when the goal is to serve the firm. Nevertheless, these endeavors demonstrate limited efficacy in prompting such conduct when the organization’s ethical identity remains implicit, even within a context driven by a desire to serve the public. Full article

This study investigates the biomechanical impact of a passive Arm-Support Exoskeleton (ASE) on workers in wool textile processing. Eight workers, equipped with surface electrodes for electromyography (EMG) recording, performed three industrial tasks, with and without the exoskeleton. All tasks were performed in an upright stance involving repetitive upper limbs actions and overhead work, each presenting different physical demands in terms of cycle duration, load handling and percentage of cycle time with shoulder flexion over 80°. The use of ASE consistently lowered muscle activity in the anterior and medial deltoid compared to the free condition (reduction in signal Root Mean Square (RMS) $-21.6\%$ and $-13.6\%$, respectively), while no difference was found for the Erector Spinae Longissimus (ESL) muscle. All workers reported complete satisfaction with the ASE effectiveness as rated on Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST), and 62% of the subjects rated the usability score as very high (>80 System Usability Scale (SUS)). The reduction in shoulder flexor muscle activity during the performance of industrial tasks is not correlated to the level of ergonomic risk involved. This preliminary study affirms the potential adoption of ASE as support for repetitive activities in wool textile processing, emphasizing its efficacy in reducing shoulder muscle activity. Positive worker acceptance and intention to use ASE supports its broader adoption as a preventive tool in the occupational sector. Full article

To describe something in terms of its purpose or function is to describe its teleology. Previous studies have found that teleological beliefs are positively related to anthropomorphism, and that anthropomorphism decreases the perceived unpredictability of non-human agents. In the current study, we explore these relationships using the highly salient example of beliefs about the coronavirus pandemic. Results showed that both anthropomorphism and teleology were negatively associated with perceived uncertainty and threat, and positively associated with self-reported behavioural change in response to the pandemic. These findings suggest that highly anthropomorphic and teleological individuals may view coronavirus as agentive and goal-directed. While anthropomorphic and teleological beliefs may facilitate behavioural change in response to the pandemic, we also found that the associated reduction in uncertainty and threat may be detrimental to behavioural change. We discuss the implications of these findings for messaging about global events more broadly. Full article

The adoption and results achieved by “smart city” projects heavily rely on citizens’ acceptance and behavioral intention to embrace smart city living. Understanding the factors influencing citizens’ behavioral intention towards smart city living is crucial for the effective development and rollout of smart city initiatives. This research paper aims to assess the factors influencing citizens’ behavioral intention towards smart city living using quantitative research methods. Through a comprehensive literature review, an ideation structure was developed, integrating theoretical perspectives from the Technology Acceptance Model (TAM). The structure encompasses key variables such as perceived utility, convenience of use, engagement, trialability, observability, interoperability, willingness, and propensity to embrace smart city lifestyles. A quantitative methodological stance was employed to gather information from a statistically significant subset of citizens residing in urban areas in developed countries. A structured questionnaire, based on the theoretical framework, was formulated and distributed to the participants. Statistical analysis techniques, including structural equation modeling, were used for investigating connections between identified factors and citizens’ behavioral intention towards smart city living. Preliminary findings indicate that behavioral intention towards smart city living strongly depends on attitude and perceived usefulness. By addressing these factors, smart cities can foster greater citizen engagement, participation, and ultimately, the successful realization of smart city living. Full article

Recently, interest in animal welfare has steadily increased, driven by a growing focus on environmental, social, and governance (ESG) issues. This trend aligns with the Sustainable Development Goals (SDGs) set by the United Nations. This underscores the importance of comprehending consumer attitudes towards products that are respectful to animal welfare. This research aims to employ the Value-Attitude-Behavior (VAB) model as a theoretical basis to explore the behavioral intentions of Taiwanese consumers to buy cage-free eggs. To provide comprehensive insights into consumer behavior in this domain, the study examines key variables such as ‘human–nature connectedness’, ‘trust in labels’, and ‘attitude towards animal welfare’. By addressing an existing research gap in the literature and exploring consumer behavior in relation to animal welfare-friendly products, the research contributes to an area that has received limited attention. We gathered a total of 341 valid questionnaires for this research. Employing Structural Equation Modeling (SEM) along with Maximum Likelihood Estimation (MLE), we investigated the causal connections between variables. The study presents three key observations: First, consumers who value sustainability and ethics tend to maintain a positive perspective on free-range eggs. Second, a favorable stance towards cage-free eggs directly correlates with positive future behaviors. Lastly, label trustworthiness and a supportive view towards animal welfare heavily affect behavioral intentions in consumers. Given these insights and the growing significance of animal welfare in consumer choices, we recommend that participants in the food and livestock sector earnestly advocate for and back practices that prioritize animal well-being. Full article

This paper explores the non-indicative modal meanings that the classical indicative plural inflection -ūn and the preverbal particle b- express in different varieties of Arabic. Moreover, it argues that these two forms allow the speaker to introduce a marked stance in specific grammatical contexts, where the choice of -ūn or b- clearly introduces a modal reading to the proposition. Taking a comparative approach to examine modality in Arabic, I build on examples taken from Classical Arabic (CLA), premodern non-standard written (NSW) documents, and modern dialects to analyze the modal behavior of -ūn and b-. Analysis of the data reveals the following: (1) preverbal b- is used to create rhetorical contrast, and (2) either -ūn or b- can overtly signal authoritative expectations (and orders) and/or intention. These results suggest an interesting connection between the modal roles played by -ūn and b- across Arabic varieties and demonstrate the importance of NSW texts in tracing the historical development of modality in Arabic. Full article

Social media platforms offer their audience the possibility to reply to posts through comments and reactions. This allows social media users to express their ideas and opinions on shared content, thus opening virtual discussions. Most studies on social networks have focused only on user relationships or on the shared content, while ignoring the valuable information hidden in the digital conversations, in terms of structure of the discussion and relation between contents, which is essential for understanding online communication behavior. This work proposes a graph-based framework to assess the shape and structure of online conversations. The analysis was composed of two main stages: intent analysis and network generation. Users’ intention was detected using keyword-based classification, followed by the implementation of machine learning-based classification algorithms for uncategorized comments. Afterwards, human-in-the-loop was involved in improving the keyword-based classification. To extract essential information on social media communication patterns among the users, we built conversation graphs using a directed multigraph network and we show our model at work in two real-life experiments. The first experiment used data from a real social media challenge and it was able to categorize 90% of comments with 98% accuracy. The second experiment focused on COVID vaccine-related discussions in online forums and investigated the stance and sentiment to understand how the comments are affected by their parent discussion. Finally, the most popular online discussion patterns were mined and interpreted. We see that the dynamics obtained from conversation graphs are similar to traditional communication activities. Full article

This study examines the green purchase awareness of Philippine youth consumers and its influence on green purchase intention and, ultimately, their green purchase behaviour. The study used the theory of planned behaviour as a conceptual framework. The research used an online five-point Likert scale questionnaire and gathered data from accounting and business students in the Philippines; data were collected from 923 usable respondents and then validated and analysed using structural equation modelling (SEM). The findings suggest that respondents’ awareness of environmental degradation’s consequences influences green purchase intention and positively mediates green purchase behaviour. The attitudes, norms, and respondents’ perceived behavioural control represent the environmental awareness beliefs; they positively and significantly contributed to green purchase intention, which contributed to green purchase behaviour. The study is original in that it examines the applicability of the theory of planned behaviour in the context of the Philippines, which has legislative backing for environmental awareness among the citizens. It also investigates the extent to which subjective norms can influence personal behavioural control and mediate towards green purchase intention. The findings contribute to the Philippine setting; however, it is extensible with further research on emerging nations that share societal cultures. The data obtained sufficiently explain the phenomenon using the theory of planned behaviour; combining it with Hofstede’s model of societal culture can increase explanatory power for societal-based studies on purchase intention and behaviour. In a high-power distance and collective societal-cultural setting, findings support the argument that environmental awareness contributes to green purchase intention and buyer behaviour. The proactive stance of making the population aware of the environmental effects is noticeable. However, they provide a low-level explanation of their intention to purchase green products and a medium-level explanation of translating purchase intention to purchase behaviour. Hence, we recommend the government review their approach to making people environmentally aware, which measurably translates into green purchasing intention and purchasing behaviour. Full article

The question of the authorship of the Daodejing, otherwise known as the Laozi, is a hotly contested debate, and one’s stance on the existence and role of the author can have potential implications for one’s interpretation of the text. This paper explores how notions of authorship of a text influence, often unconsciously, a reader’s interpretation such that the possible meaning generated within that text becomes limited, reduced, or terminated. Three hermeneutic frameworks, Authorial intentionalism, reader-oriented readings, and intention of the text, are problematized, revealing both how they contribute to the production of meaning, but more importantly how a lack of critical awareness of one’s own hermeneutic stance regarding authorship might terminate potential significance. These hermeneutic frameworks are applied to the work of contemporary scholars and translators of the Laozi in order to assess how implicit notions of authorship contribute to strengths and weaknesses in interpretations of the Laozi as it regards the production of meaning and significance. Being critical in nature, this paper is meant only to reveal how the reader’s unreflexive engagement with their attitude toward authorship can lead to problematic results in interpretation and translation of any work in general and the Laozi in particular. Full article