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Drawing on a theoretical framework of sustainable career ecosystem theory, our paper aims to consider how domestic and international postgraduates can enhance their employability through participation in a landscape of practice.

The study employed an exploratory, longitudinal case study design to capture students' lived experiences on an 18-month Master of Professional Practice course at a higher education institution in New Zealand. The data collection procedure involved field note observations (months 1–4), a focus group (month 13) and narrative frames (months 16–18). The sample was domestic students from New Zealand (n = 2) and international students from Asia (n = 5).

One’s participation in multiple communities of practice represents their landscape of practice and a commitment to lifewide learning. Through participation in various communities of practice, domestic and international students can enhance their employability in three ways: (1) boundary encounters to develop social capital, (2) transcending contexts to enhance cultural capital, and (3) acknowledging the development of psychological capital and career agency.

Our work offers one of the earliest empirical validations of sustainable career ecosystem theory. Expressly, communities of practice represent various contexts whereby employability capital is developed over time. Additionally, the postgraduate students themselves are portrayed as interconnected and interdependent actors, presenting a novel framing of such dependencies at the micro-level of the ecosystem. The practical implications come from informing universities of the value of a landscape of practice to enhance the employability of domestic and international students in preparation for sustainable careers and to promote the sustainability of the career ecosystem.

This study aims to apply machine learning techniques to efficiently predict leisure firms’ financial performance. Accurate financial forecasting is crucial in leisure and tourism, greatly affecting firms’ strategic decisions and competitive positioning. This study emphasizes the roles of intellectual capital to offer a nuanced understanding of how these types of capital influence firm success.

Using comprehensive firm-level data, this study examines several machine learning algorithms’ predictive capacity across a spectrum of industry sectors (general, manufacturing, service) to identify the most effective model and training dataset. These tools are used to evaluate financial metrics such as return on sales, return on assets and sales growth. A range of variables are incorporated into this process to enhance model accuracy and relevance.

Results demonstrate the support vector machine algorithm’s exceptional performance based on a training data set from the service sector in predicting leisure firms’ return on sales and sales growth. This algorithm is thus an efficacious strategic forecasting instrument. The variables significantly affecting firm performance include demand variation; organizational, product and technological innovation; synergistic innovation between multiple domains; salary levels; market strategy; and the number of employees.

By integrating advanced machine learning techniques with the strategic management of intellectual capital, this study presents a sophisticated approach to predicting leisure firms’ financial performance. Findings enrich the discourse on firm performance forecasting and offer actionable insights into strategic planning and resource allocation for practitioners in the leisure and tourism sectors.

本研究应用机器学习技术来高效预测休闲企业的财务表现。准确的财务预测对于休闲和旅游业至关重要, 极大影响企业的战略决策和竞争定位。本研究强调智力资本的作用, 以深入理解这些资本类型如何影响企业的成功。

本研究使用全面的企业层面数据, 考察多种行业领域（综合、制造、服务）中多个机器学习算法的预测能力, 识别出最有效的模型和训练数据集。这些工具用于评估财务指标, 如销售回报率、资产回报率和销售增长率。过程纳入多种变量, 以提高模型的准确性和相关性。

结果表明, 基于服务行业训练数据集的支持向量机算法在预测休闲企业的销售回报率和销售增长率方面表现出色。因此, 该算法是一种有效的战略预测工具。影响企业绩效的显著变量包括需求变化、组织、产品和技术创新、多领域之间的协同创新、工资水平、市场战略和员工数量。

通过将先进的机器学习技术与智力资本的战略管理相结合, 本研究提出了一种复杂的方法来预测休闲企业的财务表现。研究结果丰富了关于企业绩效预测的讨论, 并为休闲和旅游业的从业者提供了有关战略规划和资源分配的实用见解。

This paper aims to examine the impact of corporate environmental transparency (CET) on corporate financial performance under a mandatory environmental disclosure policy in China, the largest carbon-emitting country. It aims to clarify the concept of CET and investigate its short-term financial implications for key pollutant-discharging entities (KPEs).

A multidimensional model is used to construct a comprehensive CET index for KPEs in China. Empirical tests are conducted to assess the relationship between CET and corporate financial performance.

The study finds a negative relationship between CET and corporate financial performance in the short term. Increased environmental transparency necessitates higher environmental resource allocation, adversely affecting profits. The results remain unchanged from a battery of robustness tests. Despite mandatory disclosure, companies tend to provide general and vague information rather than specific and meaningful environmental data.

The findings provide rich practical implications for policymakers to improve a mandatory environmental disclosure policy. The paper also contributes to the existing knowledge by developing a measure of CET and presenting new evidence to the debate on whether corporate environmental disclosure can be regarded as transparency.

Policymakers are advised to refine mandatory environmental disclosure regulations to ensure genuine transparency and to implement policy measures that alleviate the financial burdens of companies with high CET levels, thereby encouraging sustainable practices.

This paper contributes to the existing knowledge by developing a measure of CET and providing new evidence on the debate over whether environmental, social and governance (ESG) disclosure equates to transparency. It emphasizes the complexity of transparency and the inadequacy of current environmental disclosure practices among KPEs. The study underscores the need for financial support for companies with high CET levels to alleviate short-term financial strains and promote long-term sustainability.

This paper aims to show the possibilities of implementing the idea of sustainability in the context of energy transformation using the concept of an industrial cluster. The implementation of the idea of sustainability is of particular importance from the perspective of the functioning of the meta-organisations involved in the implementation and promotion of decarbonisation processes. Industrial clusters, as collective actors initiating collective actions and providing complex governance structures, seem to have a great fit with regard to the needs of disseminating and implementing the idea of sustainable development, also in conjunction with energy development.

Empirical evidence is derived from a case study of Mazovia Clustes ICT (MC ICT). Based on the experience of this cluster, this study wants to show the evolution of the industrial cluster through the prism of its growing activity in supporting energy transition. The authors conducted the research in the period 2022–2023 using in-depth personal interviews and an analysis of the secondary data. The primary technique for data analysis and interpretation was conventional qualitative content analysis.

As a result of this study, the authors have distinguished three main areas of cluster activity covering the strategic, operational/project and institutional levels. Within the first area, the cluster’s efforts focused on the development of a strategy and involvement in lobbying and co-legislating. The second area refers to the cluster’s activity in the carrying out of national and transnational projects on the creation and implementation of various energy solutions. The activities undertaken in the third area include support for the development of start-ups in the field of energy and involvement in the launch of an energy cluster and the development of distributed energy in Poland. Although the strategic and operational/project levels are characterised by a commonality of activities and goals, there is additionally a commonality of interests at the institutional level.

This paper has its limitations, which primarily relate to the small research sample (the choice of a case study as the main research strategy) and the methods used (qualitative research). Therefore, it is impossible to generalise the results to the entire population of clusters.

This paper has considerable practical value, as the results of this study may be relevant for public authorities interested in implementing energy transition through industrial clusters. The activities described can also be a source of inspiration for other clusters interested in shaping pro-environmental attitudes.

The cluster’s activities are closely linked to the three pillars of sustainable development, including the social pillar. The solutions developed within the cluster in the context of energy development are aimed not only at increasing energy efficiency and protecting the environment but also at broader social welfare.

This paper makes an additional contribution to the state-of-the-art of the industrial cluster concept by linking it to the idea of sustainable development, in the context of energy transformation. In addition, it sheds new light on issues related to cluster co-operation, combining the case of the industrial cluster with the very fresh and as yet poorly described idea of the energy cluster.