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While well-designed and environmentally conscious infrastructures are essential for economic growth and social progress, their implementation can sometimes neglect the unique characteristics of territories. The chapter explores the issues posed by eco-blind infrastructure projects, challenging the assumption that all forms of greening are universally beneficial. It delves into the implications of urban greening initiatives, showcasing instances where these projects, while aiming for sustainability, have inadvertently exacerbated issues of inequality, displacement, and social marginalization. Through critical analysis of cases, the chapter reveals the complex interplay among environmental improvement, territorial identity, and community involvement, underscoring the importance of community engagement in project planning and execution. This approach is described as a tool to balance environmental considerations with an appreciation for local identity, fostering projects that truly benefit communities while advancing the broader goals of environmental development.

This paper aims to employ a multivariate nonlinear regression analysis to establish a predictive model for the final fracture area, while accounting for the impact of individual parameters.

This analysis is based on the numerical simulation data obtained, using the hybrid finite element–discrete element (FE–DE) method. The forecasting model was compared with the numerical results and the accuracy of the model was evaluated by the root mean square (RMS) and the RMS error, the mean absolute error and the mean absolute percentage error.

The multivariate nonlinear regression model can accurately predict the nonlinear relationships between injection rate, leakoff coefficient, elastic modulus, permeability, Poisson’s ratio, pore pressure and final fracture area. The regression equations obtained from the Newton iteration of the least squares method are strong in terms of the fit to the six sensitive parameters, and the model follow essentially the same trend with the numerical simulation data, with no systematic divergence detected. Least absolutely deviation has a significantly weaker performance than the least squares method. The percentage contribution of sensitive parameters to the final fracture area is available from the simulation results and forecast model. Injection rate, leakoff coefficient, permeability, elastic modulus, pore pressure and Poisson’s ratio contribute 43.4%, −19.4%, 24.8%, −19.2%, −21.3% and 10.1% to the final fracture area, respectively, as they increased gradually. In summary, (1) the fluid injection rate has the greatest influence on the final fracture area. (2)The multivariate nonlinear regression equation was optimally obtained after 59 iterations of the least squares-based Newton method and 27 derivative evaluations, with a decidability coefficient R2 = 0.711 representing the model reliability and the regression equations fit the four parameters of leakoff coefficient, permeability, elastic modulus and pore pressure very satisfactorily. The models follow essentially the identical trend with the numerical simulation data and there is no systematic divergence. The least absolute deviation has a significantly weaker fit than the least squares method. (3)The nonlinear forecasting model of physical parameters of hydraulic fracturing established in this paper can be applied as a standard for optimizing the fracturing strategy and predicting the fracturing efficiency in situ field and numerical simulation. Its effectiveness can be trained and optimized by experimental and simulation data, and taking into account more basic data and establishing regression equations, containing more fracturing parameters will be the further research interests.

The nonlinear forecasting model of physical parameters of hydraulic fracturing established in this paper can be applied as a standard for optimizing the fracturing strategy and predicting the fracturing efficiency in situ field and numerical simulation. Its effectiveness can be trained and optimized by experimental and simulation data, and taking into account more basic data and establishing regression equations, containing more fracturing parameters will be the further research interests.

This study, rooted in affordance-actualization theory and communication theory, aims to critically examine how ChatGPT influences users’ transition from new adopters to loyal advocates within the context of travel decision-making. It incorporates constructs including communication quality, personalization, anthropomorphism, cognitive and emotional trust (ET), loyalty and intention to adopt into a comprehensive model.

This study used quantitative methods to analyze data from 477 respondents, collected online through a self-administered questionnaire by Embrain, a leading market research company in South Korea. Lavaan package within R studio was used for evaluating the measurement model through confirmatory factor analysis and using structural equation modeling to examine the proposed hypotheses.

The findings reveal a pivotal need for enhancing ChatGPT’s communication quality, particularly in terms of accuracy, currency and understandability. Personalization emerges as a key driver for cognitive trust, while anthropomorphism significantly impacts ET. Interestingly, the study unveils that in the context of travel recommendations, users’ trust in ChatGPT predominantly operates at the cognitive level, significantly impacting loyalty and subsequent adoption intentions.

The findings of this research provide valuable insights for improving Generative AI (GenAI) technology and management practices in travel recommendations.

As one of the few empirical research papers in the burgeoning field of GenAI, this study proposes a highly explanatory model for the process from affordance to actualization in the context of using ChatGPT for travel recommendations.

Science policy and practice for open access (OA) books is a rapidly evolving area in the scholarly domain. However, there is much that remains unknown, including how many OA books there are and to what degree they are included in preservation coverage. The purpose of this study is to contribute towards filling this knowledge gap in order to advance both research and practice in the domain of OA books.

This study utilized open bibliometric data sources to aggregate a harmonized dataset of metadata records for OA books (data sources: the Directory of Open Access Books, OpenAIRE, OpenAlex, Scielo Books, The Lens, and WorldCat). This dataset was then cross-matched based on unique identifiers and book titles to openly available content listings of trusted preservation services (data sources: Cariniana Network, CLOCKSS, Global LOCKSS Network, and Portico). The web domains of the OA books were determined by querying the web addresses or digital object identifiers provided in the metadata of the bibliometric database entries.

In total, 396,995 unique records were identified from the OA book bibliometric sources, of which 19% were found to be included in at least one of the preservation services. The results suggest reason for concern for the long tail of OA books distributed at thousands of different web domains as these include volatile cloud storage or sometimes no longer contained the files at all.

Data quality issues, varying definitions of OA across services and inconsistent implementation of unique identifiers were discovered as key challenges. The study includes recommendations for publishers, libraries, data providers and preservation services for improving monitoring and practices for OA book preservation.

This study provides methodological and empirical findings for advancing the practices of OA book publishing, preservation and research.

The focus in professional learning is often on formal activities such as workshops, conferences and courses. There is also a tendency to focus on formal programmes of coaching and mentoring in teacher education. Emphasising the formal activities means that everyday informal learning in educational settings is overlooked. Informal coaching and mentoring could be utilised to support teachers' career-long professional learning.

This is a conceptual paper which draws on the author's research and seeks to expand what is considered as professional learning within teacher education – namely, informal coaching and mentoring. To understand how to support this professional learning, the lens of social practice is used with an emphasis on learning environments and learning practices.

Coaching and mentoring can be identified in informal encounters in the staffroom, school corridors and many places and situations. Findings are presented in relation to the importance of informal learning from and with colleagues and the role of headteachers.

More attention has been paid to informal learning, but there is still a need for what could be termed an “informal turn”. Understanding that informal coaching and mentoring afford professional learning opportunities to the teachers who both provide and receive coaching and mentoring can help to support their learning. Recommendations are provided on how educational settings can facilitate and support these professional learning opportunities while preserving their informality.

This paper examines an identified but unexplored career gap evidenced at a mid-level classification in the academic career path for women in Australia. This career-stalling effect or holding pattern, is examined to determine underlying causes of career trajectory interruption.

Guided by the epistemological stance of standpoint theory, this exploratory abductive study employs a novel arts-based method, draw, write, reflect, to access experiences that may be difficult to convey verbally. The obtained drawings and reflections were thematically analysed.

Drawing on Bourdieu’s concept of illusio this article finds support for female academics’ bifurcated consciousness. Results demonstrate how opposing social role prescriptions result in the deliberate avoidance of work-life conflict, a nuanced lack of confidence in work tasks in combination with other, often competing responsibilities, and the uneven distribution of administrative duties known as “academic housework”, which combine to stall careers. Female academics feel pressure to prioritise their domestic role and eschew career progression.

Despite the small sample size, the findings provide rich career narratives and experiences of female academics in Australia providing additional impetus for increased gender equity efforts.

This study is the first to explore the previously unidentified holding pattern for female academics in Australia. Findings suggest there is a range of previously unexplored impediments resulting in a gendered stalling at a mid-level classification interrupting female academic career progression.

This chapter reviews research on age-related differences in how consumers process information. Specifically, it discusses many of the effects of aging on the quality and quantity of consumers' sensory, cognitive, and emotional functioning. Some studies suggest that the manner in which elderly (age 65 and over) consumers process information may render them more vulnerable than young and middle-aged consumers to malign persuasion attempts. This chapter reveals that age has selective effects on information processing such that elderly consumers are sometimes more susceptible to marketing influence and sometimes they are less susceptible.