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Using the Stimulus-Organism-Response (SOR) model as a theoretical guide, this study employed a conceptual model involving residents’ place attachment (S) to the destination in which they live and emotional solidarity with tourists (O) as precursors to their involvement in tourism (R). The purpose of this paper is threefold: To determine (1) whether residents’ place attachment explains their emotional solidarity with tourists, (2) if emotional solidarity is an effective predictor of residents’ involvement in tourism planning and development and (3) if emotional solidarity dimensions mediate the relationship between place attachment and involvement.

Data were collected from 378 permanent resident heads of households living in, or adjacent to, central Orlando, using a self-administered survey with a census-guided systematic sampling method. Data were subjected to tests of normality and common method bias, followed by a two-step confirmatory factor analysis and structural equation modeling.

Seven of the 11 proposed model hypotheses were supported, with moderate variances explained in each of the four outcome variables: welcoming nature (R² = 19.3%), emotional closeness (R² = 24.5%), sympathetic understanding (R² = 39.4%) and involvement (R² = 36.8%). Though both place identity and place dependence (as two dimensions of place attachment) were partial mediators, the former proved to be more pronounced.

This study employed non-economic measures—place attachment and emotional solidarity—in determining residents’ involvement in tourism within their community. Such an approach provides fresh insights into how such symbolic constructs can contribute to residents’ positive, actionable involvement in tourism. This research is one of the few that have incorporated emotional solidarity as a construct within the SOR model and the first to examine the indirect effects (through mediation) of emotional solidarity.

Recreational scuba diving is one of the fastest growing tourism industries around the world and has become a popular activity in Taiwan. Few studies focus on enduring involvement with a high risk or difficult activity specialization, so this study aims to explore the causal relationship between enduring involvement and specialization and seeks to explain sustained involvement in scuba diving activity as a recreation specialization.

This research selects four diving sites in Taiwan as survey locations, specifically Yeliou, Longdong, Kenting and Green Island. The questionnaire consists of three sections, including demographic information, enduring involvement and specialization. By analyzing the data collected from 810 scuba divers in Taiwan, structural equation modeling is used to examine the causal relationships among the variables.

The primary findings of this study are as follows: attraction positively affects divers’ commitment and lifestyle through joy, relaxation and sharing diving experiences; the results indicate that self-expression is associated with past experience of participating in scuba diving activity; and centrality indicates that participants’ daily life and recreation are related to each other and become central to their life. Results show that most theoretical hypotheses are supported, but there is no significant evidence of attraction impacting past experience or self-expression influencing commitment and lifestyle.

To the best of the authors’ knowledge, this study is the first to examine the causal influence of enduring involvement and specialization in the scuba diving context. The findings provide a solid theoretical basis for the study of sustained involvement motivation and behavior on specialization. Implications and recommendations for future research are discussed.

休闲水肺潜水是全球发展最快的旅游业之一, 已成为台湾的热门活动。很少有研究关注持续涉入高风险或困难活动的专门化, 因此本研究探讨持续涉入和专门化之间的因果关系, 并试图解释持续参与水肺潜水活动作为休闲专门化。

这项研究选择了台湾的四个潜水地点作为调查地点, 特别是野柳, 龙洞, 垦丁和绿岛。问卷分为三个部分, 包括人口统计信息, 持续参与和专门化。通过分析从台湾810名潜水员那里收集的数据, 使用结构方程模型检查变量之间的因果关系。

这项研究的主要发现是：（1）吸引力通过愉悦, 放松和分享潜水经历积极影响潜水员的承诺和生活方式; （2）结果表明自我表达与过去参加水肺潜水活动的经历有关（3）中心性表示参与者的日常生活和娱乐彼此相关, 并成为他们生活的中心。结果表明, 大多数理论假设均得到支持, 但没有显着证据表明吸引力会影响过去的经历或自我表达影响承诺和生活方式。

据我们所知, 本研究是第一个研究在潜水环境中持续涉入和专门化的因果关系影响的研究。研究结果为专门化持续参与动机和行为的研究提供了坚实的理论基础。 讨论了对未来研究的影响和建议。

El buceo recreativo es una de las industrias turísticas de más rápido crecimiento en todo el mundo y se ha convertido en una actividad popular en Taiwán. Pocos estudios se centran en la participación duradera con una especialización de actividad difícil o de alto riesgo, por lo que este estudio explora la relación causal entre la participación duradera y la especialización y busca explicar la participación sostenida en la actividad de buceo como una especialización recreativa.

Esta investigación selecciona cuatro sitios de buceo en Taiwán como lugares de estudio, específicamente Yeliou, Longdong, Kenting y Green Island. El cuestionario consta de tres secciones, que incluyen información demográfica, participación duradera y especialización. Al analizar los datos recopilados de 810 buzos en Taiwán, se utiliza un modelo de ecuaciones estructurales para examinar las relaciones causales entre las variables.

Los hallazgos principales de este estudio son: (1) la atracción afecta positivamente el compromiso y el estilo de vida de los buceadores a través de la alegría, la relajación y el intercambio de experiencias de buceo, (2) los resultados indican que la autoexpresión está asociada con la experiencia pasada de participar en actividades de buceo., y (3) la centralidad indica que la vida diaria y la recreación de los participantes están relacionadas entre sí y se vuelven centrales en su vida. Los resultados muestran que la mayoría de las hipótesis teóricas están respaldadas, pero no hay evidencia significativa de que la atracción afecte la experiencia pasada o la autoexpresión que influya en el compromiso y el estilo de vida.

Hasta donde sabemos, este estudio es el primero en examinar la influencia causal de la participación y la especialización duraderas en el contexto del buceo. Los hallazgos proporcionan una base teórica sólida para el estudio de la motivación y el comportamiento de participación sostenida en la especialización. Se discuten las implicaciones y recomendaciones para futuras investigaciones.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

This paper presents a descriptive analysis of elite women's biographical sketches in Who's Who-type collections, now out of copyright, published in Australia in the 1930s: Victoria (1934), New South Wales (1936) and Queensland (1939). It concentrates on information given about their schooling.

The biographical sketches of the women, defined as “elite” by their inclusion in three collections from the 1930s, were examined for information about their and their daughters' education. Using mixed methods in a prosopographical approach, this is mainly a quantitative analysis. It outlines and compares the schools they attended where given as well as providing basic demographic details of the 491 women.

The paper shows that, for those who gave educational details, the women and their daughters attended private schools almost exclusively. Three types of schools were listed – private venture, corporate, and a very few state schools. The paper demonstrates that the landscape for girls’ secondary schooling was not a settled terrain in terms of type, place, religion, or age of schools available for elite girls' education in the late 19th and early 20th century. Private schools are shown to be part of the “machinery of exclusiveness which characterised the inter-war years” (Teese, 1998, p. 402) and private venture schools survived well into the third decade of the 20th century.

Beyond the histories of individual schools, little is known about the educational profile of Australian elite women in the past. This largely quantitative analysis helps to uncover and compare across state-based cohorts, previously unknown demographic, and schooling details for interwar women who recorded their educational details, as well as for the NSW and Victorian daughters where given.

This study aimed to assess the influence of the community-based campaign on weight loss and healthy lifestyle adoption among Bahrain's adult population.

A cross -sectional self-reported online questionnaire completed in February 2021. The survey evaluated the impact of the community-based campaign health program which includes (exercise, diet plan and psychological eating behavior) weight reduction using social media platforms. The authors employed data from young and middle-aged healthy adults (n = 842) between the ages of 18-55 years, of both sexes. The intervention group (n = 842) was made up of the supporters of the voluntary community initiative called Obesity does not Suit Me (n = 194), and the control group (n = 648) was made up of non-followers of the campaign.

The study showed a statistically significant difference among the followers of the community-based campaign health program in the following parameters: 3.90-4.23 kg less, 1.46-1.59 difference in BMI and 0.05-0.06 WHR. All changes were of low effect size.

Diet and exercise had significant impact on weight, BMI and WHR among the followers of the community campaign. However, more research is required for sponsorship to increase the motivation and rewards for the community campaign.

Knowledge search is considered a broad concept and semi-intentional behavior. The path and boundary conditions through which search strategies affect intra-organizational knowledge creation remain elusive. Drawing on recombinant search theory and knowledge-based view, the authors seek to identify knowledge complexity as an important intermediate variable between knowledge search and innovation performance, such as research and development (R&D) output and R&D output quality. A second goal of this study is to examine the moderating roles of government support and technological turbulence.

The authors employed a longitudinal panel of 609 global pharmaceutical firms and obtained the firms' patent records from 1980 to 2015 for the analysis. The authors used generalized estimating equations (GEE) to evaluate the models and tested the consistency via panel fixed-effects estimations.

The authors' findings show that organizational routine-guided search has a negative effect on knowledge complexity, while routine-changing search exerts a positive impact on knowledge complexity. Governmental support and technological turbulence moderate these relationships. Notably, knowledge complexity has an inverted U-shaped relationship with innovation performance.

The authors' research context, the pharmaceutical industry, may constrain the generalizability of our findings. In addition, potential types of routine-guided and routine-changing search behaviors were not considered.

Despite these limitations, this study offers important implications. First, knowledge complexity transmits the effects of knowledge search on innovation performance. Practitioners should balance routine-guided and routine-changing search processes to build and manage complex knowledge. Second, a moderate level of knowledge complexity is the key to good R&D output and R&D output quality.

The study identifies knowledge complexity as one important intermediate variable between knowledge search behaviors and intra-organizational knowledge creation.

Through this reflexive, theoretically informed polemical piece, this paper aims to seek to reflect on the role of accounting education in United Kingdom Higher Education (UKHE). The authors reignite an old, but pertinent debate, whether accounting graduates should be educated to be accountants or receive a holistic, critical education.

The authors adopt a theoretical position drawing on the work of Slavoj Žižek and Mark Fisher, and their fusion of Lacanian psychoanalysis and Marxism, in particular Fisher’s (2009) conceptualisation of “capitalist realism” to take a critical standpoint on the effects that UKHE marketisation is having on the teaching of accounting and other business-related disciplines.

The authors outline four key aspects of where accounting education in UKHE is influenced by capitalist realism, as a result of the marketisation of UKHE.

The paper is a reflexive polemic and so is limited by this written style and presentation.

The authors argue that capitalist realism is a dominant theme that influences accounting education. They propose that universities now, more than ever, must focus on their societal duty to foster critical viewpoints in their graduates and dispose of a model that is subject to capitalist realism ontology.

The theoretical stance allows for a potentially deeper consideration of issues surrounding marketisation of higher education, from the micro level of social interaction (that of the accounting academic and their impact/perceptions of the reality).

Bioelectrical impedance vector analysis (BIVA) and phase angle (PA) have importance in assessing nutritional and prognosis, and this study hypothesized that these measurements can have a relationship with nutritional risk and outcomes. This study aims to analyze the association between Nutrition Risk in the Critically ill (NUTRIC) score and bioelectrical impedance measures with hospital mortality in critically ill patients.

A prospective, cohort study was performed with a consecutive sample of patients admitted to an intensive care unit (ICU), between January and June 2017 at a hospital university in Northwest Brazil. The NUTRIC score and the bioelectric measures, such as resistance (R), reactance (Xc), PA and BIVA, were completed within the first 24 h of admission. The Student’s t or Mann–Whitney, Pearson’s or Spearman’s coefficient and Fisher’s exact tests and BIVA were used for statistical analyses.

The sample consisted of 81, with a mean age of 57 (16.7) years, with 60.5% women. It was detected that PA and Xc were lower (p < 0.001), and age was higher (p < 0.001) in a high nutritional-risk group. It was found an association between low nutritional risk and hospital discharge (p < 0.001), and that individuals who died spent more days in the ICU (p = 0.0375), had significantly lower PA and Xc values (p = 0.043 and p = 0.0172, respectively) and higher NUTRIC scores (<0.0001). There was a displacement of the mean impedance vector in men and women with high nutritional risk (p = 0.0037 and p = 0.004, respectively).

The height measurement was estimated using predictive formulas, which may affect the accuracy of the values; BIA was performed only upon admission of the patient to the ICU and the study population was heterogeneous, as it is a general ICU.

This paper shows that, in critically ill patients, nutritional screening and the assessment of bioelectrical measures help in clinical-nutritional decisions, and were able to predict outcomes.

In order to better optimize the internal management system of book publishing and to cope with the changes in the external market environment, the purpose of this paper is to carry out cross-border publishing with the help of a transmedia storytelling model to realize the transformation and upgrading of the industry. Focusing on the relationship between the book publishing transmedia storytelling model and business performance, the moderating effect of the innovation environment on different variables is assessed.

This paper proposes several feasible hypotheses based on existing research. The research data came from 365 managers of Chinese book publishing organizations, and the scale was validated by Cronbach’s a, composite reliability (CR) and average variance extracted (AVE). Reliability and validity were verified, and correlation and regression analyses were used to test the impact of the book publishing transmedia storytelling model on business performance and to analyze the moderating role of the innovation environment.

The results show that the book publishing transmedia storytelling model (content production, technology integration, organizational innovation, marketing integration) helps to improve business performance (market performance, financial performance), and the innovation environment has a positive moderating effect on the relationship between the book publishing transmedia storytelling model and business performance, which provides a guarantee for the transformation and upgrading of book publishing. The market information reflected in the innovation environment has a certain role in promoting the innovation and business performance of the book publishing transmedia storytelling model.

The empirical evidence provides a theoretical link between the book publishing transmedia storytelling model and business performance, but there are still some shortcomings, and more factors, such as equity structure, government subsidies and research and development investment, should be included in future research. In addition, the scope of the research should be broadened on this basis to make the results of the data analysis more objective.

This paper introduces the transmedia storytelling model and deeply analyzes the relationship between the book publishing transmedia storytelling model and business performance, which is of great practical significance for optimizing the application and service quality of book publishing, prolonging the industrial chain, enhancing the interaction and participation of users and perfecting the business management system of the book publishing industry.

The application and research of the book publishing transmedia storytelling model are imperfect. Therefore, this paper not only helps to promote the innovation of book publishing organizational structure and improve the management system of business performance, but also may help to improve the innovation environment of book publishing enterprises and promote the diversification of industrial structure.

We conduct a multidisciplinary systematic literature review on climate neutrality in the supply chain. While carbon neutrality has gained prominence, our study argues that achieving carbon neutrality alone is not enough to address climate change effectively, as non-CO₂ greenhouse gases (GHG) are potent contributors to global warming.

We used multiple databases, including EBSCO, ProQuest, Science Direct, Emerald and Google Scholar, to identify articles related to climate neutrality in the context of non-CO₂ gases. A total of 71 articles in environmental science, climate change, energy systems, agriculture and logistics are reviewed to provide insights into the climate neutrality of supply chains.

We find that, in addition to CO₂, other GHG such as methane, nitrous oxide, ozone and fluorinated gases also significantly contribute to climate change. Our literature review identified several key pillars for achieving net-zero GHG emissions, including end-use efficiency and electrification, clean electricity supply, clean fuel supply, “GHG capture, storage and utilization,” enhanced land sinks, reduced non-CO₂ emissions and improved feed and manure management.

We contribute to the literature on climate neutrality of supply chains by emphasizing the significance of non-CO₂ GHG along with CO₂ and highlighting the need for a comprehensive approach to climate neutrality in addressing climate change. This study advances the understanding of climate neutrality of supply chains and contributes to the discourse on effective climate change mitigation strategies. It provides clear future research directions.