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This study aims to address the critical challenge of implementing lean manufacturing (LM) in emerging economies, where sustainability complexities on the production floor hinder production efficiency and the transition towards a circular economy (CE). Addressing a gap in existing research, the paper introduces a path analysis model to systematically identify, prioritize and overcome LM implementation barriers, aiming to enhance performance through strategic removal.

The authors used a mixed-method approach, combining empirical survey data with literature reviews to pinpoint key LM barriers. Using the grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) along with the Network Knowledge (NK) method, they mapped causal relationships and barrier intensities. This formed the basis for developing a path simulation algorithm, integrating heuristic considerations for practical decision-making.

This analysis reveals that the primary barriers to LM adoption is the negative perception and inadequate understanding of lean tools and CE principles. The study provides a strategic framework for managers, offering new insights into barrier prioritization and overcoming strategies to facilitate successful LM adoption.

This research provides a strategic pathway for overcoming LM implementation barriers, empowering managers in emerging economies to enhance sustainability and competitive advantage through LM and CE integration. It emphasizes the significance of structured barrier management in the manufacturing sector.

This research pioneers a systematic exploration of LM implementation barriers in the CE context, making a significant contribution to the literature. It identifies, evaluates barriers and proposes a practical model for overcoming them, enriching sustainable manufacturing practices in emerging markets.

This study aims to explore how university language students evaluate different sustainability themes and examine the overall relevance of ecological, social, cultural and economic sustainability dimensions in language education.

A questionnaire was designed to study Finnish university language students’ (n = 55) order of priority for sustainability dimensions and their sub-themes and the justifications for the priority orders using a mixed methods design. Qualitative content analysis was conducted using NVivo software, and weighted rankings were used to analyse the quantitative data.

The findings of the study showed that language students evaluated the social and cultural dimensions as the most relevant in language teaching. In all dimensions, students approached sustainability mainly by prioritising larger issues and advancing towards smaller ones. Most non-directional responses appeared in the economic dimension. In addition, individual prioritising and justification approaches varied between different sustainability dimensions.

To the best of the authors’ knowledge, no previous studies have examined language students’ evaluations of and justifications for all four sustainability dimensions. The results highlight the need to use multiple, holistic approaches and systems thinking to incorporate education for sustainable development.

This study aims to explore gender performance in entrepreneurial pitching. Understanding pitching as a social practice, the authors argue that pitch content and body gestures contain gender-based norms and practices. The authors focus on early-stage ventures and the hegemonic masculinities and femininities that are performed in entrepreneurial pitches. The main research question is as follows: How is gender performed in entrepreneurial pitching?

The authors carried out the study with the post-structuralist feminist approach. The authors collected and analyzed nine online pitches with the reflexive thematic method to depict hegemonic masculinities and femininities performed at the pitch.

The authors found that heroic and breadwinner masculinities are dominant in pitching. Both male and female founders perform hegemonic masculinities. Entrepreneurs are expected to be assertive but empathetic people. Finally, there are connections between what entrepreneurs do and what investors ask, indicating the iteration of gender performance and expectations.

While the online setting helps the authors to collect data during the pandemic, it limits the observation of the place, space and interactions between the judges/investors and the entrepreneurs. As a result, the linguistic and gesture communication of the investors in the pitch was not discussed in full-length in this paper. Also, as the authors observed, people would come to the pitch knowing what they should perform and how they should interact. Therefore, the preparation of the pitch as a study context could provide rich details on how gender norms and stereotypes influence people's interactions and their entrepreneurial identity. Lastly, the study has a methodological limitation. The authors did not include aspects of space in the analysis. It is mainly due to the variety of settings that the pitching sessions that the data set had.

For social practices and policies, the results indicate barriers to finance for women entrepreneurs. Women entrepreneurs are rewarded when they perform entrepreneurial hegemonic masculinities with a touch of emphasized femininities. Eventually, if women entrepreneurs do not perform correctly as investors expect them to, they will face barriers to acquiring finance. It is important to acknowledge how certain gendered biases might be (re)constructed and (re)produced through entrepreneurial activities, in which pitching is one of them.

Practitioners could utilize research findings to understand how gender stereotypes exist not only on the pitch stage but also before and after the pitch, such as the choice of business idea and pitch training. In other words, it is necessary to create a more enabling environment for women entrepreneurs, such as customizing the accelerator program so that all business ideas receive relevant support from experts. On a macro level, the study has shown that seemingly gender-equal societies do not practically translate into higher participation of women in entrepreneurship.

For theoretical contributions, the study enhances the discussion that entrepreneurship is gendered; women and men entrepreneurs need to perform certain hegemonic traits to be legitimated as founders. The authors also address various pitching practices that shape pitch performance by including both textual and semiotic data in the study. This study provides social implications on the awareness of gendered norms and the design of entrepreneurial pitching.

Sarcasm is a linguistic expression that usually carries the opposite meaning of what is being said by words, thus making it difficult for machines to discover the actual meaning. It is mainly distinguished by the inflection with which it is spoken, with an undercurrent of irony, and is largely dependent on context, which makes it a difficult task for computational analysis. Moreover, sarcasm expresses negative sentiments using positive words, allowing it to easily confuse sentiment analysis models. This paper aims to demonstrate the task of sarcasm detection using the approach of machine and deep learning.

For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre-processed using natural language processing methods, and additional features were extracted and analysed. Several machine learning models, including logistic regression, ridge regression, linear support vector and support vector machines, along with two deep learning models based on bidirectional long short-term memory and one bidirectional encoder representations from transformers (BERT)-based model, were implemented, evaluated and compared.

The performance of machine and deep learning models was compared in the task of sarcasm detection, and possible ways of improvement were discussed. Deep learning models showed more promise, performance-wise, for this type of task. Specifically, a state-of-the-art model in natural language processing, namely, BERT-based model, outperformed other machine and deep learning models.

This study compared the performance of the various machine and deep learning models in the task of sarcasm detection using the data set of 1.3 million comments from social media.

The purpose of the study is to understand the relationship between family-driven innovation and the incorporation of corporate sustainability in German family firms.

The study conducted 26 interviews with 22 German family firms. Thematic analysis was undertaken on the collected data resulting in five major themes.

The study identified five main themes of corporate sustainability-oriented innovation in family firms, which include measuring corporate sustainability performances, building corporate sustainability-oriented infrastructure, stabilizing/optimizing operations, enhancing operational flexibility/independence and knowledge management and development. The study also provides an activity-based guide for family firms to use innovation to achieve corporate sustainability goals and present the findings’ implications for policymakers.

The present study is the first study to empirically investigate the relationship between family-driven innovation and the incorporation of corporate sustainability at each of the corporate sustainability maturity levels.

This study aims to explore how to overcome and address the loss of exploratory innovation, thereby achieving greater success in exploratory innovation. This phenomenon of loss occurs when enterprises decrease their investment in and engagement with exploratory innovation, ultimately leading to an insufficient amount of such innovation efforts. Drawing on dynamic capabilities, this study investigates the relationship between organizational foresight and exploratory innovation and examines the moderating role of breakthrough orientation/financial orientation.

This study used survey data collected from 296 Chinese high-tech companies in multiple industries and sectors.

The evidence produced by this study reveals that three elements of organizational foresight (i.e. environmental scanning capabilities, strategic selection capabilities and integrating capabilities) positively influence exploratory innovation. Furthermore, this positive effect is strengthened in the context of a high-breakthrough orientation. Moreover, the relationships among environmental scanning capabilities, strategic selection capabilities and exploratory innovation become weaker as an enterprise’s financial orientation increases, whereas a strong financial orientation does not affect the relationship between integrating capabilities and exploratory innovation.

Ambidexterity is key to successful enterprise innovation. Compared with exploitative innovation, it is by no means easy to engage in exploratory innovation, which is especially important in high-tech companies. While the loss of exploratory innovation has been observed, few empirical studies have explored ways to promote exploratory innovation more effectively. A key research implication of this study pertains to the role of organizational foresight in the improvement of exploratory innovation in the context of high-tech companies.

This paper contributes to the broader literature on exploratory innovation and organizational foresight and provides practical guidance for high-tech companies regarding ways of avoiding the loss of exploratory innovation and becoming more successful at exploratory innovation.

The purpose of the paper is to showcase the significant achievements of Egypt's scientists in the 20th century across various fields of study such as medicine, physics, chemistry, biology, math, geology, astronomy and engineering. The paper highlights the struggles and successes of these scientists, as well as the cultural, social and political factors that influenced their lives and work. The aim is to inspire young people to pursue careers in science and make their own contributions to society by presenting these scientists as role models for hard work and dedication. Ultimately, the paper seeks to promote the importance of science and its impact on society.

The purpose of this review is to present the scientific biographies of Egypt's most distinguished scientists, primarily in the field of Natural Sciences, in a balanced and comprehensive manner. The work is objective, honest and abstract, avoiding any bias or exaggeration. The author provides a clear and concise methodology, including a brief introduction to the scientist and their field of study, an explanation of their major contributions, the impact of their work on society, any challenges or obstacles faced during their career and their lasting legacy. The aim is to showcase the important achievements of these scientists, their impact on their respective fields and to inspire future generations to pursue scientific careers.

The group of outstanding scientists in 20th century Egypt were shaped by various factors, including familial upbringing, education, society, political and cultural atmosphere and state support for scientific research. These scientists made significant contributions to various academic disciplines, including medicine, physics, chemistry, biology, mathematics and engineering. Their impact on their communities and cultures has received international acclaim, making them role models for future generations of scientists and researchers. The history of these scientists highlights the importance of educational investments and supporting scientific research to foster innovation and social progress. The encyclopedia serves as a useful tool for students, instructors and education professionals, preserving Egypt's scientific heritage and honouring the scientists' outstanding accomplishments.

The encyclopedia preserves Egypt's scientific heritage, which has been overlooked for political or other reasons. It is a useful tool for a variety of readers, including students, instructors and education professionals, and it offers insights into universally relevant scientific success factors as well as scientific research methodologies. The encyclopedia honours the outstanding scientific accomplishments of Egyptian researchers and their contributions to the world's scientific community.

The practical implications of this paper are several. First, it highlights the importance of education, family upbringing and societal support for scientific research in fostering innovation and social progress. Second, it underscores the need for continued funding and support for scientific research to maintain and build upon the accomplishments of past generations of scientists. Third, it encourages young people to pursue scientific careers and make their own contributions to society. Fourth, it preserves the scientific heritage of Egypt and honors the contributions of its outstanding scientists. Finally, it serves as a useful tool for students, instructors and education professionals seeking to understand the factors underlying scientific success and research methodologies.

The social implications of the paper include promoting national pride and cultural identity, raising awareness of the importance of education and scientific research in driving social progress, inspiring future generations of scientists and researchers, reducing socioeconomic disparities and emphasizing the role of society, politics and culture in shaping scientific researchers' personalities and interests.

The paper's originality/value lies in its comprehensive documentation of the scientific biographies of Egypt's most prominent scientists in the 20th century, providing unique insights into the factors that contributed to their development and their impact across various academic disciplines. It preserves Egypt's scientific heritage and inspires future generations of scientists and researchers through the promotion of educational investments and scientific research. The encyclopedia serves as a useful tool for education professionals seeking to understand scientific success factors and research methodologies, emphasizing the importance of supportive and inclusive environments for scientific development.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.