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This article aims to analyze the strategic work of Polish entrepreneurs in the furniture industry following the political changes in 1989. The authors examined how these entrepreneurs transitioned from local craftsmen or importers into leaders of international manufacturing companies and how their strategizing contributed to the unprecedented growth of the Polish furniture sector.

The authors examined extant data, specifically biographical interviews conducted with 11 prominent leaders in the Polish furniture industry (Hryniewicki, 2015, 2018). They analyzed within a theoretical framework that integrates J.C. Spender’s theory of strategic management with Barry Johnson’s concept of polarity management. Polarity is a way of understanding and managing interdependent, opposing pairs of values or perspectives that give rise to conflict.

The analysis reveals key patterns of strategic challenges at the level of human agency, history and sense-making. The authors identified four key polarities: life and business, knowledge presence and absence, concordance and discordance, and instrumental and non-instrumental sense-making.

The polarity concept illuminates the interplay of agency and determinism in strategic decision-making, offering valuable insights for methodology and a deeper understanding of Poland’s furniture industry.

The aim of this study was to measure the level of challenges faced by novice teachers in South Africa. Findings suggest a need for professional development courses to upskill teachers with effective pedagogies that can incorporate the social and emotional components into teaching and learning.

This study applied a descriptive research methodology by administering a questionnaire to 143 novice teachers. The data analysis technique was the Rasch model.

The findings indicated high item and person reliability, with a good item fit and polarity values that are compatible with the Rasch model. The three major challenges identified are uninvolved parents, discipline problems and a lack of guidance and counselling. These challenges can be related to social and emotional learning (SEL) components.

The study used quantitative methods and discovered the challenges that novice teachers face. If the research uses a combination of qualitative methods, it will be possible to better identify the specific causes of the above three challenges of novice teachers.

Due to the complex nature of South African society, many novice teachers are overwhelmed by the challenges they face when entering the profession. These challenges are often embedded in societal risk factors, which complicate the transition from student teacher to novice teacher. The major challenges identified in this study can be related to SEL components, as the challenges are closely linked to the psychological and social backgrounds of the students. Teachers in this study indicated that they found it difficult to deal with these challenges at the beginning of their careers.

By identifying the challenges facing new teachers in South Africa, they will be better prepared for their work in schools. Therefore, they will improve the above situation to continue developing professionally.

The findings indicated high item and person reliability, with a good item fit and polarity values that are compatible with the Rasch model. Teachers in this study indicated that they found it difficult to deal with these challenges in the beginning of their careers. Professional development courses are suggested to help teachers deal with issues such as discipline, uninvolved parents and guidance and counselling effectively. Higher education programmes should also include these topics in their curricula for student teachers. A greater emphasis on training teachers in their pastoral roles is suggested.

Organizations will be key to realizing the “transformative change for humanity” now being called for. However, the complexity calls for new ways of facilitating change and organizational learning; it also calls for moving beyond sustainability to develop practices that restore and regenerate the world in which we live. Above all, it calls for the development of new frameworks, practices, mindset and capabilities to hold space for and facilitate such transformation, to dance with the “Logic of Life.” The purpose of this study is to contribute to advancing the current leading frameworks and practices of facilitating learning and development towards the enabling of regenerative transformative change in organizations and society.

This study is based on an exploratory qualitative analysis of a facilitation prototype that expands the current framework and practice of Appreciative Inquiry Summits toward regeneration.

This study presents four paradoxes of regenerative facilitation to guide the dance for life in complex ecosystems. It also identifies that the dance needs to be widened, towards inviting more frequently the ends of the four paradoxes noted as regenerative, negative emotions, inner and more-than-human.

This study explores the intersection of practices and frameworks for facilitating complexity with principles from regenerative leadership and complexity theory, potentially making an important contribution to the urgent and widespread need to facilitate a regenerative transformative change for humanity, society and our organizations.

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.

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.

Women working in public relations (PR) in the 1990s developed the power of metamodern pragmatism to avoid being constrained in this decade of contradictions.

This was a time of promise for female empowerment and careers. The PR industry in Britain had quadrupled in size, yet increased feminisation and professionalisation did not resolve gender inequity. Indeed, alongside the existence of ‘old boys clubs’ and hedonistic macho agencies in the industry, the 1990s offered a lad's mag culture and an AbFab image of PR.

An original collaborative historical ‘Café Delphi’ method was developed using three themes (sex, sexuality and sexism) to explore women's careers and contributions in the expanding and increasingly powerful field of PR in the United Kingdom during the 1990s. It built on feminist critique of the industry and paradoxical portrayals of women resulting from significant changes in media, popular culture and a pluralistic marketplace.

Individual and collective experiences of women working in PR at the time reveal the power of attitudes to affect their ability to achieve equality and empowerment. Women navigated tensions between the benefits of accelerated pluralism and the patriarchal resistance in the workplace through performative choices and a deep sense of pragmatism.

This study aims to understand the perceived emotions of human–artificial intelligence (AI) interactions in the private sector. Moreover, this research discusses the transferability of these lessons to the public sector.

This research analysed the comments posted between June 2022 and June 2023 in the global open Reddit online community. A data mining approach was conducted, including a sentiment analysis technique and a qualitative approach.

The results show a prevalence of positive emotions. In addition, a pertinent percentage of negative emotions were found, such as hate, anger and frustration, due to human–AI interactions.

The insights from human–AI interactions in the private sector can be transferred to the governmental sector to leverage organisational performance, governmental decision-making, public service delivery and the creation of economic and social value.

Beyond the positive impacts of AI in government strategies, implementing AI can elicit negative emotions in users and potentially negatively impact the brand of private and government organisations. To the best of the authors’ knowledge, this is the first research bridging the gap by identifying the predominant negative emotions after a human–AI interaction.

Professional learning networks (PLNs) involve teachers’ collaboration with others outside of their school to improve teaching and learning. PLNs can facilitate teachers’ professional growth and school improvement. This study aims to explore the drivers for participation within PLNs, the enactment process and the impact of PLN participation on teachers, students and schools in Greece.

A descriptive phenomenological study was conducted to explore the lived experience of primary school teachers participating in PLNs.

The findings showed that individuals who were open to change were driving innovation to address a need or a lack in their daily practice that was not satisfied within their usual community of practice. The key element of the participation was peer collaboration with openness of communication without attendant accountability pressures. The change was mainly identified in teacher skills and the school climate. An individual could bring change only if the school is already open to change. In some cases, resistance to change in schools was identified before enactment or during enactment. The transformation of teachers’ and leaders’ stances is discussed, enabling the opportunity to maximise school improvement.

The study examines PLNs as European Union-funded initiatives that are developed by teachers in centralised education systems under the phenomenological research paradigm. It explores the PLNs in a different setting compared to the existing conceptual theory of change for PLNs.

The effects of board composition on performance have long been discussed in management research using fractionalization measures. In this study, we propose an alternative measurement approach based on board polarization.

Using an exploratory analysis and applying the polarization measure to German Deutscher Aktienindex (DAX)-, Midcap-DAX (MDAX)- and Small Cap-Index (SDAX)-listed companies, this paper applies the polarization index to examine the relationship between board diversity and performance.

The results show that the polarization concept is well suited to measure principal-agent problems between the members of the management and supervisory boards. We reveal that board polarization is negatively associated with firm performance, as measured by return on investment (ROI).

This exploratory study shows that the measurement of board polarization can be linked to performance differences between companies, which offers promising starting points for further research.

This paper aims to explore the relationship between board composition and a firm’s commitment to combatting climate change. Specifically, this study investigates how various characteristics of the board, namely its size and presence of independent directors, and of the directors themselves, including gender diversity, age, educational background and national homogeneity, affect the corporate-level climate change orientation. From a theoretical standpoint, the authors take a cross-fertilizing perspective, bridging upper echelons theory with agency, resource dependence and critical mass theories.

The study uses ordered probit regression models on a hand-collected multi-country and multi-industry sample of 35 listed firms included in the Global Climate Change Liquid Equity Index (GALPLACC) provided by ECPI. This index is particularly relevant as it focuses on firms that have demonstrated a commitment to climate change, providing a robust dataset for the analysis.

The findings underscore the importance of disentangling various characteristics of corporate boards and directors. Specifically, the orientation toward climate change is negatively influenced by both board size and having a higher number of independent directors, while it is positively affected by reaching a critical mass of women on the board. Conversely, factors such as average age, educational background and the level of national homogeneity do not show significant effects.

This paper has an exploratory nature and contributes to the ongoing debate on the crucial, yet controversial role played by board-level and directors’ sociodemographic characteristics in shaping a firm’s environmental stance. Moreover, this study offers potential recommendations for policymakers regarding board composition to enhance firms’ climate change orientation.