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The present study aims to examine the attitudes of future Saudi female English as a Foreign Language (EFL) student-teachers toward English native-like pronunciation to investigate their misconceptions about English as a Lingua Franca (ELF).

The researcher used a questionnaire to collect the data for the study.

The results indicate that students and teachers have positive attitudes toward native-like pronunciation. However, the results also show a realization on the participants’ part about the status of ELF. The study concludes that although they have positive attitudes toward native-like English pronunciation, students use ELF and recognize that such pronunciation is not essential for global communication. The study results show that the participants are aware of ELF, filling a vacuum in the literature about how Saudi students perceive ELF. It encourages EFL teachers, syllabus designers, developers and researchers to provide more information on this topic and stresses international communicative ability, as ELF speakers require.

As the study has some limitations that could be addressed in future research, other researchers should address these deficiencies in future studies. One limitation is that the study only involved Saudi female future teachers. Further researchers can investigate male Saudi future EFL teachers. Another limitation is that the study focused on future teachers of English in Saudi Arabia in only one institution. Other Saudi EFL teachers and other Arab future teachers could be further investigated to reject or support the study’s findings. Additionally, a more detailed demographic background could be specified in further research for more comprehensive results. In addition, similar studies could be conducted with participants from different EFL-speaking countries. Another limitation of this study is that it covers the attitudes of EFL future teachers toward native-like pronunciation and indirectly investigates their views on ELF. More research is needed to determine how EFL learners and teachers perceive ELF. The actual use of English globally could become more enlightened with further study.

This study’s findings have implications for instructors, syllabus designers and researchers. The results suggest that EFL instructors, syllabus designers and researchers should focus more on international communicative competence than native-like competence. While designing course materials or teaching, teachers and syllabus developers should be fully aware of the status of ELF. Designers of syllabi should include conversations among speakers from different linguistic backgrounds. Effective communication is a priority. Students should become more familiar with global communication outside the classroom and be prepared to engage in it.

Students should become more familiar with global communication outside the classroom and be prepared to engage in it.

Native varieties of English have gained popularity over the years among EFL teachers and learners. However, researchers have debated the importance of EFL students achieving native-like English proficiency.

The study analysed the influence of organizational justice on the duty orientation of employees in the mining sector of Ghana. Also, it examined the mediating role of supervisor-provided resources in the relationship between organizational justice and duty orientation.

The study obtained data through a self-administered questionnaire from 291 employees of a mining firm. The data were analysed and interpreted in light of the hypotheses using the partial least squares structural equation modelling technique.

The findings revealed that organizational justice had a significant positive relationship with duty orientation and supervisor-provided resources. The results again established that supervisor-provided resources had a significant positive relationship with duty orientation. The study finally documented that supervisor-provided resources partially mediate the relationship between organizational justice and duty orientation.

We recommended that the management of the mining companies devote resources to developing organizational justice policies based on fairness in resource allocation, clear roles, employee feedback and effective information dissemination. Furthermore, supervisors should place priority on acquiring and dispensing resources as employees demonstrate their willingness to improve duty orientation.

The study contributes to knowledge in a novel research area. It adds to empirical evidence by highlighting the possible variables that may influence employees to engage in duty orientation.

本研究擬分析於迦納的採礦部門裏,組織公平感對僱員職責導向的影響;研究亦擬探討主管提供的資源,如何在組織公平感與職責導向間的關係上起著中介角色。

研究人員透過一間採礦公司291名僱員自我測試的問卷,取得研究所需的數據,繼而以偏最小平方結構方程式模式分析法,進行數據分析,並按照研究的假設,對數據進行闡釋的工作。

研究結果顯示,組織公平感與職責導向和主管提供的資源之間存在顯著的正向關係;研究結果亦確定了主管提供的資源與職責導向之間存在顯著的正向關係。最後,研究結果證明了主管提供的資源,會一定程度調節組織公平感與職責導向之間的關係。

我們建議採礦企業的管理層應根據資源的公平分配、明確的角色、僱員的回饋和有效的信息傳播,把資源專用於發展組織公平感的政策上;而且,當僱員展示他們願意改善職責導向時,主管應把獲取資源,並加以發放列為優先事項。

本研究在一個新穎的研究領域裏,幫助我們增進知識;研究透過強調影響僱員參與職責導向的可能變數,增加有關的經驗證據。

The purpose of this paper is to introduce an empirical model for house price spillovers between real estate markets. The model is presented by using data from the US-UK and London-New York housing markets over a period of 1975Q1-2016Q1 by employing both static and dynamic methodologies.

The research analyzes long-run static and dynamic spillover elasticity coefficients by employing three methods, namely, autoregressive distributed lag, the fully modified ordinary least square and dynamic ordinary least squares estimator under a Kalman filter approach. The empirical method also investigates dynamic correlation between the house prices by employing the dynamic control correlation method.

The paper shows how a dynamic spillover pricing analysis can be applied between real estate markets. On the empirical side, the results show that country-level causality in housing prices is running from the USA to UK, whereas city-level causality is running from London to New York. The model outcomes suggest that real estate portfolios involving US and UK assets require a dynamic risk management approach.

One of the findings is that the dynamic conditional correlation between the US and the UK housing prices is broken during the crisis period. The paper does not discuss the reasons for that break, which requires further empirical tests by applying Markov switching regime shifts. The timing of the causality between the house prices is not empirically tested. It can be examined empirically by applying methods such as wavelets.

The authors observed a unidirectional causality from London to New York house prices, which is opposite to the aggregate country-level causality direction. This supports London’s specific power in the real estate markets. London has a leading role in the global urban economies residential housing markets and the behavior of its housing prices has a statistically significant causality impact on the house prices of New York City.

The house price co-integration observed in this research at both country and city levels should be interpreted as a continuity of real estate and financial integration in practice.

The paper is the first research which applies a dynamic spillover analysis to examine the causality between housing prices in real estate markets. It also provides a long-term empirical evidence for a dynamic causal relationship for the global housing markets.

This study focuses on the classification of targets with varying shapes using radar cross section (RCS), which is influenced by the target’s shape. This study aims to develop a robust classification method by considering an incident angle with minor random fluctuations and using a physical optics simulation to generate data sets.

The approach involves several supervised machine learning and classification methods, including traditional algorithms and a deep neural network classifier. It uses histogram-based definitions of the RCS for feature extraction, with an emphasis on resilience against noise in the RCS data. Data enrichment techniques are incorporated, including the use of noise-impacted histogram data sets.

The classification algorithms are extensively evaluated, highlighting their efficacy in feature extraction from RCS histograms. Among the studied algorithms, the K-nearest neighbour is found to be the most accurate of the traditional methods, but it is surpassed in accuracy by a deep learning network classifier. The results demonstrate the robustness of the feature extraction from the RCS histograms, motivated by mm-wave radar applications.

This study presents a novel approach to target classification that extends beyond traditional methods by integrating deep neural networks and focusing on histogram-based methodologies. It also incorporates data enrichment techniques to enhance the analysis, providing a comprehensive perspective for target detection using RCS.

With the help of basic physics, the application of computer algorithms in the form of recent advances such as machine learning and neural networking in textile Industry has been discussed in this review. Scientists have linked the underlying structural or chemical science of textile materials and discovered several strategies for completing some of the most time-consuming tasks with ease and precision. Since the 1980s, computer algorithms and machine learning have been used to aid the majority of the textile testing process. With the rise in demand for automation, deep learning, and neural networks, these two now handle the majority of testing and quality control operations in the form of image processing.

The state-of-the-art of artificial intelligence (AI) applications in the textile sector is reviewed in this paper. Based on several research problems and AI-based methods, the current literature is evaluated. The research issues are categorized into three categories based on the operation processes of the textile industry, including yarn manufacturing, fabric manufacture and coloration.

AI-assisted automation has improved not only machine efficiency but also overall industry operations. AI's fundamental concepts have been examined for real-world challenges. Several scientists conducted the majority of the case studies, and they confirmed that image analysis, backpropagation and neural networking may be specifically used as testing techniques in textile material testing. AI can be used to automate processes in various circumstances.

This research conducts a thorough analysis of artificial neural network applications in the textile sector.

This study explores whether metacognitive strategy training can influence the lexical knowledge of L2 learners of the present study, and what they think about the use of metacognitive strategies in language learning classes. To do so, a 50-item multiple-choice vocabulary test, developed by the researchers based upon Nation’s (1990) levels of language proficiency, was employed to measure the learners’ vocabulary knowledge progress during the period of instruction. The instruction received by the experimental group was based on the Cognitive Academic Language Learning Approach (CALLA) Model, developed and validated by Chamot and O’Malley (1994). The findings revealed that the experimental group outperformed the control group in their endeavors for comprehending and producing vocabulary. This may be attributed to the fact that after this intervention, participants have developed their metacognitive awareness and their thinking skills. The study concludes with pedagogical implications and highlights avenues for future research.

ﺗ مّ د ﻣ ﺞ ا ﺳ ﺗ ر ا ﺗ ﯾ ﺟ ﯾ ﺎ ت ﻣ ﺎ و ر ا ء ا ﻟ ﻣ ﻌ ر ﻓ ﯾ ﺔ (MS) ، ا ﻟ ﺗ ﻲ ﺗ ﻌ ﺗ ﺑ ر ا ﻟ ﻔ ﺋ ﺔ ا ﻟ ﻔ ر ﻋ ﯾ ﺔ ا ﻟ ر ﺋ ﯾ ﺳ ﯾ ﺔ ﻻ ﺳ ﺗ ر ا ﺗ ﯾ ﺟ ﯾ ﺎ ت ﺗ ﻌ ﻠّ م ا ﻟ ﻠّ ﻐ ﺔ ﻓ ﻲ ﻣ ﻧ ﺎ ھ ﺞ ﺗ ﻌ ﻠّ م ا ﻟ ﻠّ ﻐ ﺔ ا ﻷ ﺟ ﻧ ﺑ ﯾ ﺔ ﻟ ﺗ ﺳ ﮭ ﯾ ل ا ﻟ ﺗ ﻔ ﻛ ﯾ ر ا ﻟ ﻌ ﺎ ﻟ ﻲ و ا ﻟ ﺗ ﺧ ط ﯾ ط ا ﻟ ذ ا ﺗ ﻲ و ا ﻟ ﺗ ﻌ ﻠّ م ا ﻟ ﻣ ﺳ ﺗ ﻘِّل و ا ﻟ ﺗ ﻌ ﻠ م ا ﻷ ﻓ ﺿ ل ﻓ ﻲ ﻧ ﮭ ﺎ ﯾ ﺔ ا ﻟ ﻣ ط ﺎ ف . و ﻓ ﻘًﺎ ﻟ ذ ﻟ ك ، ﺗ ﻌ دّ ھ ذ ه ا ﻟ دّر ا ﺳ ﺔ ﻣ ﺣ ﺎ و ﻟ ﺔً ﻟ ﻺ ﺟ ﺎ ﺑ ﺔ ﻋ ﻣ ﺎ إ ذ ا ﻛ ﺎ ن ا ﻟ ﺗ د ر ﯾ ب ﻋ ﻠ ﻰ ا ﺳ ﺗ ر ا ﺗ ﯾ ﺟ ﯾ ﺔ ﻣ ﺎ و ر ا ء ا ﻟ ﻣ ﻌ ر ﻓ ﻲ ﯾ ﻣ ﻛ ن أ ن ﯾ ؤ ﺛّ ر ﻋ ﻠ ﻰ ا ﻟ ﻣ ﻌ ر ﻓ ﺔ ا ﻟ ﻣُﻌ ﺟ ﻣ ﯾ ﺔ ﻟ ﻠ ﻣ ﺗ ﻌ ﻠ ﻣ ﯾ ن و ﻣ ﺎ ذ ا ﯾ ﻔ ﻛّر ﻓ ﯾ ﮫ ا ﻟ ﻣ ﺗ ﻌ ﻠّ ﻣ و ن ﺣ ول ﺗ د ر ﯾ س ا ﺳ ﺗ ر ا ﺗ ﯾ ﺟ ﯾ ﺎ ت ﻣ ﺎ و ر ا ء ا ﻟ ﻣ ﻌ ر ﻓ ﯾ ﺔ . و ﻟ ﻠ ﻘ ﯾ ﺎ م ﺑ ذ ﻟ ك ، ﺗ مّ ا ﺳ ﺗ ﺧ د ا م ا ﺧ ﺗ ﺑ ﺎ ر ﻣ ﻛ و ن ﻣ ن 50 ﻋ ﻧ ﺻ ر اً ﻣ ﺗ ﻌ د د ا ﻻ ﺧ ﺗ ﯾ ﺎ ر ا ت ا ﻟّ ذ ي ﺗ مّ ﺗ ط و ﯾ ر ه ﺑ و ا ﺳ ط ﺔ ا ﻟ ﺑ ﺎ ﺣ ﺛ ﯾ ن ا ﺳ ﺗ ﻧ ﺎ دًا إ ﻟ ﻰ ﻣ ﺳ ﺗ و ﯾ ﺎ ت ا ﻟ ﻛ ﻔ ﺎ ء ة ا ﻟ ﻠ ﻐ و ﯾ ﺔ ﻟ د ى ا ﻟ ﺷ ﻌ ب (Nation) (1990 م ( ، ﻟ ﻘ ﯾ ﺎ س ﺗ ط وّ ر ﻣ ﻌ ر ﻓ ﺔ ا ﻟ ﻣ ﻔ ر د ا ت أ ﺛ ﻧ ﺎ ء ﻓ ﺗ ر ة اﻟ ﺗد ر ﯾ س . ا ﺳ ﺗ ﻧ د ت ا ﻟ ﺗ ﻌ ﻠ ﯾ ﻣ ﺎ ت ا ﻟ ﺗ ﻲ ﺗ ﻠ ﻘّﺗ ﮭ ﺎ ا ﻟ ﻣ ﺟ ﻣ و ﻋ ﺔ ا ﻟ ﺗ ﺟ ر ﯾ ﺑ ﯾ ﺔ إ ﻟ ﻰ ﻧ ﻣ و ذ ج ﻣ ﻧ ﮭ ﺞ ا ﻟ ﺗ ﻌ ﻠ م ا ﻟ ﻣ ﻌ ر ﻓ ﻲ ا ﻷ ﻛ ﺎ د ﯾ ﻣ ﻲ ) CALLA ( ا ﻟ ذّي أ ﻋ دّه و و ا ﻓ ق ﻋﻠ ﯾ ﮫ ﺷﺎ ﻣو ت وأ وﻣﺎﻟ ﻲ ) 1994 ( . ﻛ ﺷ ﻔ ت ا ﻟ ﻧ ﺗ ﺎ ﺋ ﺞ أ نّ ا ﻟ ﻣ ﺟ ﻣ و ﻋ ﺔ ا ﻟ ﺗ ﺟ ر ﯾ ﺑ ﯾ ﺔ ﺗ ﻔ و ﻗ ت ﻋ ﻠ ﻰ ا ﻟ ﻣ ﺟ ﻣ و ﻋ ﺔ ا ﻟ ﺗ ﺣ ﻛ ﻣ ﯾ ﺔ ﺑ ﺎ ﻟ ﻧّﺳ ﺑ ﺔ ﻟ ﻔ ﮭ م و إ ﻧ ﺗ ﺎ ج ا ﻟ ﻣ ﻔ ر د ا ت . ﻣن اﻟ ﻣﻣﮑن أ ن ﯾﻌود ذ ﻟ ك إ ﻟ ﻰ ﺣ ﻘ ﯾ ﻘ ﺔ أ نّ ا ﻟ ﻣ ﺗ ﻌ ﻠ ﻣ ﯾ ن ﺑ ﻌ د ھ ذ ا ا ﻟ ﻌ ﻼ ج ﯾ ﻣ ﻛ ﻧ ﮭ م ا ﻟ ﺗ ﻔ ﻛ ﯾ ر أ ﻛ ﺛ ر و ر ا ء ا ﻟ ﻣ ﻌ ر ﻓ ﯾ ﺔ و ﺗ ط و ﯾ ر ﺗ ﻘ دّم ﺗ ﻔ ﻛ ﯾ ر ھ م . ﺗ ﺧ ﺗ ﺗ م ا ﻟ دّر ا ﺳ ﺔ ﺑ ذ ﮐ ر ﺑ ﻌ ض ا ﻵ ﻓ ﺎ ق ا ﻟ ﺗ ر ﺑ و ﯾّﺔ و ﺗ ﺳ ﻠ ﯾ ط ا ﻟ ﺿّو ء ﻋ ﻠ ﻰ ﺑ ﻌ ض ا ﻟ ﺳّﺑ ل ﻟ ﻠ ﺑ ﺣ ث ﻓ ﻲ ا ﻟ ﻣ ﺳ ﺗ ﻘ ﺑ ل .

The purpose of this paper is to present a quantitatively supported explanation of the intellectual development, the schools of thought and the sub-areas of the food cold chain (FCC) research to derive meaningful avenues for future research.

This study builds on bibliometric analysis and network analysis to systematically evaluate a sample of 1,189 FCC articles published over the past 25 years. The descriptive statistics and science mapping approaches using co-citation analysis were performed with VOSviewer software.

The findings reveal a state-of-the-art overview of the top contributing and influential countries, authors, institutions and articles in the area of FCC research. A co-citation analysis, coupled with content analysis of most co-cited articles, uncovered four underlying research streams including: application of RFID technologies; production and operation planning models; postharvest waste, causes of postharvest wastage and perishable inventory ordering polices and models; and critical issues in FCC. Current research streams, clusters and their sub-themes provided meaningful discussions and insights into key areas for future research in FCC.

This study might reshape practitioners’, researchers’ and policy-makers’ views on the multifaceted areas and themes in the FCC research field, to harness FCC’s benefits at both strategic and tactical level. Finally, the research findings offer a roadmap for additional research to yield more practical and modeling insights that are much needed to enrich the field.

This article aims to map the expectations of manufacturing companies towards suppliers in terms of implementing improvement activities. The article poses two research questions: RQ1: What kind of improvement of activities do the surveyed producers expect from their suppliers? RQ2: Do factors such as size, capital or implemented systems influence different assessments of the analyzed requirements toward suppliers?

The Computer Assisted Telephone Interview (CATI) technique was used to collect data. The sample consists of 150 producers (employing over 50 people) who were suppliers for enterprises from the automotive, electromechanical and chemical sectors operating in the Polish business-to-business (B2B) market. We analyzed 11 improvement activities, while their correlation structure was examined by exploratory factor analysis.

We have identified three latent factors – risk reduction, product innovation and increasing efficiency – which summarize the main expectations of manufacturing companies towards suppliers. Expectations for these factors are independent of the implemented management system, although the analysis showed higher expectations for product innovation in organizations with the implementation of Kaizen.

The article fills the research gap in the literature. The research results presented in the literature so far have focused on the expectations of enterprises towards suppliers in terms of meeting the criteria for their initial and periodic assessment. The research gap in the article is the result of empirical research presenting the expectations of manufacturers towards suppliers in terms of improving their processes. Based on the findings of the presented study, development trends and implications for managers responsible for purchasing processes and relationships with suppliers can be determined.

The purpose of this paper is to examine the impact of intellectual capital and its components on bank diversification choice.

Both asset and income diversification are computed and an unbalanced panel data set of 32 banks covering the period 2000–2015 have been used. The panel corrected standard error regression has been used to account for serial correlation and heteroscedasticity.

The study found that intellectual capital determines the choice of diversifying. Precisely, intellectual capital motivates asset diversity but it dissuades income diversification. Human capital and structural capital are major components that determine asset diversity decisions. Income diversification decision, in this case to choose a focus strategy, is determined by human capital. This gives credence for the human capital theory in Ghana. Competition encourages a focus strategy. Bank size and leverage enhances income diversification while stock exchange listing and government ownership fosters the focus strategy.

Diversification strategy, knowledge base of staff, corporate governance and internal control have been considered as factors leading to the collapse of some Ghanaian banks in 2017–2018. The study provides relevant insights for regulators, decision support units and corporate boards. Intellectual capital and value added metrics should be used for modelling and decision making as they have value relevance.

This is a premier study that has examined the nexus between diversification strategy and intellectual capital in banks.