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This study aims to explore the relationship between energy management practices – specifically energy consumption targets, energy efficiency improvement measures and energy consumption monitoring – and firm performance in the developing economies of Egypt and Tunisia. It seeks to determine how these practices impact total sales performance, providing insights for regional firms and policymakers.

This study uses data from the World Bank’s 2020 Enterprise Survey, focusing on firms in Egypt and Tunisia. This study uses partial least squares structural equation modeling to analyze the impact of energy management practices on total sales performance.

The findings reveal that, while energy consumption targets do not directly affect total sales performance in Tunisia, they significantly enhance energy efficiency improvement measures and energy consumption monitoring, indirectly influencing total sales performance. This finding highlights the critical role of comprehensive energy management strategies in improving firm performance.

This study is limited to firms in Egypt and Tunisia, with cross-sectional data that do not capture the dynamic interactions of the variables over time. Future research should consider longitudinal data and expand this study to other developing economies. Using single-item measures for each variable suggests that more nuanced, multi-item measures could offer more profound insights.

For firms in Egypt and Tunisia, adopting comprehensive energy management practices, such as setting energy consumption targets, implementing energy efficiency measures and monitoring energy consumption, can lead to better sales performance by reducing energy costs, which can be reinvested in core business activities. Policymakers should support these practices through incentives and policies that promote energy efficiency and sustainability.

This study contributes to the literature by offering empirical evidence of the indirect impact of energy consumption targets on firm performance in developing economies. This underscores the importance of integrated energy management strategies to achieve the United Nations Sustainable Development Goals (SDGs), mainly SDG 7 (Affordable and Clean Energy) and SDG 12 (Responsible Consumption and Production), providing valuable insights for both policymakers and practitioners.

This study developed an online lesson study, investigated teacher professionalism after following an online lesson study and examined students' environmental literacy.

This study used a mixed-method research design. The qualitative approach entailed observing science learning focussing on environmental issues during Zoom meetings and interviews with teachers to gain insight into the online lesson study design. The quantitative approach involved testing learning outcomes, focussing on students' environmental literacy after one year of learning science by integrating environmental issue.

The result reveal that the online lesson study design is both asynchronous and synchronous. The teachers' teams asynchronously conduct the planning sessions. The implementation, observation and discussion sessions are conducted synchronously using an online meeting platform. Analysis of online learning during the lesson study shows that mind-on activities are performed using an online meeting platform. By contrast, hands-on activities are performed asynchronously with homework assignments. The relationship between teachers’ participation in lesson study and students' environmental literacy acquisition is positive. To improve the students' environmental literacy, online or hybrid lesson study in the future should synergise with environment-based co-curricular activities and science learning using a problem-based approach.

The limitations of this study are linked to the research subjects, who were situated in South Tangerang, an urban area in Indonesia. The outcomes may differ if the teachers and students are situated in rural areas. Additionally, an online lesson study was conducted during the COVID-19 pandemic, when Indonesia was under lockdown. Consequently, students and teachers must be required to engage in remote learning from their homes using digital devices. Online teaching has caused suboptimal environmental literacy among students (64.55 ± 9.04), especially in terms of knowledge, skills and participation. Therefore, it is imperative to strategize for an enhanced teaching approach towards environmental issues in the classrooms. Teaching methods that actively engage students with their surrounding environment positively affect their environmental knowledge and awareness (Kalyanasundaram et al., 2024). In future lesson plans, educators should create learning activities within the classroom (intra-curricular) and involve family members at home (co-curricular). It is pivotal to incorporate tasks into online teaching that facilitate direct interaction between students and nature to shape their attitudes, behaviours and concern for the environment (Douglas et al., 2024).

This study’s practical implication is that integrating environmental issues with science learning by framing them as crucial problems for students significantly influences students’ environmental literacy. Teachers strive to meet environmental education objectives that encompass knowledge, awareness, attitudes, skills and participation. Furthermore, teachers use problem-based learning to further improve their students' environmental literacy.

This study focuses on an analyses of an online lesson study design for science learning integrated with environmental issues. It examines the direct impact of online lesson study on increasing teacher professionalism and its influence on students' environmental literacy.

Continuum robots offer unique advantages in various specialized environments, particularly in confined or hard-to-reach spaces. Inverse kinematics and real-time shape estimation constitute crucial aspects of closed-loop control for continuum robots, presenting challenging problems. This paper aims to present an inverse kinematics and shape reconstruction method, which relies solely on the knowledge of base and end positions and orientations.

Based on the constant curvature assumption, continuum robots are regarded as spatial curves composed of circular arcs. Using geometric relationships, the mathematical relationships between the arc chords, points on the bisecting plane and the coordinate axes are established. On this basis, the analytical solution of the inverse kinematics of the continuum robots is derived. Using the positions and orientations of the base and end of the continuum robots, the Levenberg–Marquardt algorithm is used to solve the positions of the cubic Bezier curves, and a new method of spatial shape reconstruction of continuum robots is proposed.

The inverse kinematics and spatial shape reconstruction simulation of the continuum robot are carried out, and the spatial shape measurement experimental platform for the continuum robot is constructed to compare the measured and reconstructed spatial shapes. The results show that the maximum relative error between the actual shape and the reconstructed shape of the continuum robot is 2.08%, which verifies the inverse kinematics and shape reconstruction model. Additionally, when the bending angle of a single bending section of the continuum robot is less than 135°, the shape reconstruction accuracy is higher.

The proposed inverse kinematics solution method avoids iterative solving, and the shape reconstruction model does not rely on mechanical models. It has the advantages of being simple to solve, highly accurate and fast in computation, making it suitable for real-time control of continuum robots.

Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

Illegitimate tasks are pervasive in organizations, presenting a challenge for employees to mitigate their impact. However, despite their significance, there has been limited research on when and how employees can adapt to these tasks successfully. To address this gap, this study aimed to discover the relationship between illegitimate tasks and adaptive performance, drawing upon the job demands-resources theory. Specifically, this study aimed to examine the moderating role of general self-efficacy and the mediating roles of employee problem-focused and emotion-focused coping.

To examine our hypotheses, we conducted a time-lagged survey, comprising 3 waves and involving 313 employees from twenty enterprises situated in Guangzhou and Sichuan, China. Ordinary least squares (OLS) was adopted to examine our hypotheses.

Our results suggested that general self-efficacy played a crucial role in determining how employees would cope with illegitimate tasks and their subsequent adaptive performance when confronted with illegitimate tasks. Notably, employees who possess high levels of general self-efficacy utilize problem-focused coping, improving adaptive performance in handling illegitimate tasks. Conversely, employees who possess low levels of general self-efficacy rely on emotion-focused coping, leading to lower levels of adaptive performance.

This research contributes to the literature on illegitimate tasks by uncovering when and how such tasks can either promote or hinder adaptive performance. These findings offer practical insights into ways to assist employees in managing illegitimate tasks effectively.

This study investigates the impact of customer stability on the cost of debt and the moderating effect of environmental uncertainty on the above relationship.

An empirical analysis based on the ordinary least squares (OLS) regression model is conducted using China’s A-share listed companies on the Shanghai and Shenzhen Stock Exchanges from 2007 to 2021.

The results indicate that customer stability significantly inhibits the cost of debt, and the higher the environmental uncertainty, the more significant the inhibitory effect of customer stability on the cost of debt. The results of heterogeneity analyses indicate that the more intense the industry competition, the higher the customer concentration or the older the average customer age, the more significant the inhibiting effect of customer stability on the cost of debt.

This study highlights the importance of customer relationship management and supply chain risk management, which have both theoretical and managerial implications. Despite its contributions, this study has limitations, such as China’s institutional context limits, which the generalisability of our results, and the sample size for this study is small because of limitations in measuring customer stability.

Existing literature has not yet reached a consistent conclusion on how customer relationships affect the cost of debt, and such studies are mainly centered around perspectives such as customer concentration and the contagion effect of supply chains. This study constructs an indicator of customer stability using detailed information on the top five customers of China’s A-share listed companies and dynamically examines the impact of customer stability on the cost of debt, which expands the research on the influencing factors of the cost of debt, the economic consequences of customer stability and the theory of customer relationship management.

This paper aims to explain the factors shaping collective action within low-cost housing communities, focusing on parcel holders, through the utilisation of an expanded institutional analysis development (IAD) framework, which extends upon Ostrom’s foundational framework. Additionally, the paper explores four different property management approaches accessible to these communities.

The research employed a mixed-method approach comprising four sequential steps. Firstly, a quantitative inquiry entailed a questionnaire survey administered to 633 parcel holders across four low-cost housing schemes, aimed at discerning factors influencing collective action. Subsequently, a qualitative investigation involved face-to-face interviews with key stakeholders to elucidate the contributing factors of collective action, with a specific focus on Nursa Kurnia (a successful low-cost housing scheme comprising 200 units), accessible via Kuala Lumpur Middle Ring Road II. Thirdly, the study explored the social practice of “commoning the governance”. Lastly, the paper advocated for housing policy interventions, specifically proposing government subsidies for lower-income parcel holders.

Exemplified by the success of Nursa Kurnia, the research findings emphasised the importance of shifting local management’s mindset from a zero-sum approach to a win-win perspective. It highlighted the pivotal role of four factors (resource system, governance system, context and historical development) in shaping collective action and fostering improved property management practices. Moreover, the study highlighted the potential of “commoning the governance” as a new approach capable of addressing collective action challenges in low-cost housing management, presenting a promising avenue for future endeavours.

As more studies utilising the expanded IAD framework become available in the future, there is potential for further refinement and enhancement of the framework.

This study offers valuable insights for policymakers, property developers, local management and local communities, shedding light on challenges associated with the self-organisation of shared resources. Moreover, it highlights the potential of “commoning the governance” as a new property management approach to mitigate the impact of collective action problems.

The well-being of society’s most vulnerable segment is indicative of the overall societal health. This underscores the significance of addressing the interests and needs of these lower-income groups within the broader social context.

Exploring collective action within the context of self-organising low-cost housing, the study delves into an area marked by persistent challenges like free-riding tendencies and vandalism. Despite significant attention given to collective action issues in the past, the novel approach of “commoning the governance” remains unexamined in the realm of low-cost housing maintenance and management.

Existing research on innovation has mainly focused on how to promote technological innovation in megaprojects and management innovation (MI) in megaprojects is still an unknown research field. The purposes of this study are to examine the effect of MI on megaproject performance and how the top management team (TMT) regulatory focus affects the use of MI in projects. At the same time, the moderating effects of project uncertainties are also tested.

On the basis of an explorative/exploitative ambidextrous analysis framework, this study divides MI into two dimensions: explorative and exploitative MI, and integrates the theoretical perspectives of the TMT regulatory focus and project uncertainties into a research model. Taking 314 responses from megaprojects’ TMTs in China as research data, this study empirically tests the above model.

Results show that exploratory MI has a U-shaped relationship with megaproject performance; whereas exploitative MI has an inverted U-shaped relationship with megaproject performance. The TMT promotion focus has a positive effect on exploratory and exploitative MI; and the TMT prevention focus has a negative effect on exploratory MI but has a positive effect on exploitative MI. Project uncertainties have a positive moderating effect on the positive relationship between TMT promotion focus and exploratory MI, whereas it has a negative moderating effect on the negative relationship between the TMT prevention focus and exploratory MI.

By empirically measuring the relationship between two types of MIs and megaproject performance, this study clarifies the differential mechanism of the effect of different MIs on megaproject performance. This study also examines the MI of megaprojects from the perspective of the TMT regulatory focus and expounds how changes in uncertainties affect the relationship between the TMT regulatory focus and MI.

For a wide range of market actors, including policymakers, forecasting changes in commodity prices is crucial. As one of essential edible oil, peanut oil’s price swings are certainly important to predict. In this paper, the weekly wholesale price index for the period of January 1, 2010 to January 10, 2020 is used to address this specific forecasting challenge for the Chinese market.

The nonlinear auto-regressive neural network (NAR-NN) model is the forecasting method used. Forecasting performance based on various settings, such as training techniques, delay counts, hidden neuron counts and data segmentation ratios, are assessed to build the final specification.

With training, validation and testing root mean square errors of 5.89, 4.96 and 5.57, respectively, the final model produces reliable and accurate forecasts. Here, this paper demonstrates the applicability of the NAR-NN approach for commodity price predictions.

On the one hand, the findings may be used as independent technical price movement predictions. Conversely, they may be included in forecast combinations with forecasts derived from other models to form viewpoints of commodity price patterns for policy research.

This study aims to use psychological contract theory to explore the substantial impact of illegitimate tasks on the well-being of hospitality employees. It also examines the mediating role of psychological contract breach and the moderating role of employee emotional intelligence within the proposed moderated mediation model.

Data were collected from 338 hospitality employees in Guangdong, China, and the hypotheses were examined through hierarchical regression analysis.

The results revealed that illegitimate tasks could negatively impact employee well-being through psychological contract breach. Furthermore, employee emotional intelligence was confirmed as a critical moderator that buffers the negative impact of illegitimate tasks on psychological contract breach.

This research offers novel insights into the dynamics affecting hospitality employee well-being by framing illegitimate tasks within psychological contract theory. It identifies the critical conditions under which employees’ well-being is impacted, thus broadening the understanding of employee–organization interactions.