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Sustainable construction practices are strongly correlated with a profitable and competitive construction industry, improved client satisfaction and efficient use of resources. However, due consideration is not being given to sustainable construction practices in Nigeria. Therefore, this study aims to identify the unsustainable construction practices on construction sites, the barriers to sustainable construction and possible strategies to improve sustainable construction in Nigeria.

A questionnaire survey of 50 construction sites was conducted with construction professionals on the sites as the specific target, out of which only 43 construction sites have at least a construction professional present at the site. Forty-three filled questionnaires from the respondents were used for descriptive (mean score, standard deviation and charts) and inferential analysis (t-test and Kruskal–Wallis) in this study.

The study shows that a large percentage (75%) of construction professionals in Nigeria are aware of sustainable construction. The descriptive and inferential analysis showed a disparity in the ranking of the 12 unsustainable practices, 14 barriers and 11 strategies among the respondents. Five unsustainable practices (“negative externalities”, “excess energy”, “unsustainable technologies”, “non-management of health and safety of workers” and “material waste”), six barriers to sustainable construction (“absence of historical data and exemplary projects on which construction professionals can build and learn from”, “lack of professional to handle the task”, “poverty and low urban investment”, “lack of urban and construction policy”, “lack of awareness” and “lack of technical know-how”) and three strategies to improve sustainable construction practices in Nigeria (“cooperation, partnership and participation”, “protection of biodiversity and conservation of natural resources” and “sustainability assessment system”) were found to be significant.

The study offers significant insights into the construction industry unsustainable practices, barriers to sustainable construction, as well as strategies for improving sustainable construction practices. These insights can be applied to other developing countries with an emphasis on geographical differences.

To the best of the authors’ knowledge, this is one of the recent studies in Nigeria that explored the context of sustainable construction in the construction industry by providing insights into the unsustainable construction practices, barriers and strategies to improve sustainable construction in Nigeria.

The purpose of this study is to evaluate food supply chain stakeholders’ intention to use Industry 5.0 (I5.0) drones for cleaner production in food supply chains.

The authors used a quantitative research design and collected data using an online survey administered to a sample of 264 food supply chain stakeholders in Nigeria. The partial least square structural equation model was conducted to assess the research’s hypothesised relationships.

The authors provide empirical evidence to support the contributions of I5.0 drones for cleaner production. The findings showed that food supply chain stakeholders are more concerned with the use of I5.0 drones in specific operations, such as reducing plant diseases, which invariably enhances cleaner production. However, there is less inclination to drone adoption if the aim was pollution reduction, predicting seasonal output and addressing workers’ health and safety challenges. The findings outline the need for awareness to promote the use of drones for addressing workers’ hazard challenges and knowledge transfer on the potentials of I5.0 in emerging economies.

To the best of the authors’ knowledge, this study is the first to address I5.0 drones’ adoption using a sustainability model. The authors contribute to existing literature by extending the sustainability model to identify the contributions of drone use in promoting cleaner production through addressing specific system operations. This study addresses the gap by augmenting a sustainability model, suggesting that technology adoption for sustainability is motivated by curbing challenges categorised as drivers and mediators.

The agricultural sector is a critical component of global economic development, and its significance has grown significantly in recent years. The risks associated with agriculture and the behaviors of farmers in handling these risks are becoming increasingly important, given the sector’s increasing dependence worldwide. Various activities related to agriculture are vulnerable to multiple risks, which can have severe consequences for farmers’ livelihoods. The purpose of this systematic review is to present a comprehensive analysis of the sources of risk faced by farmers and their choices in adopting risk management strategies worldwide.

The Preferred Reporting Items for Systematic reviews and Meta-Analyses protocol was utilized to select relevant literature, and a total of 102 studies were analyzed. Through the use of Venn diagrams and graphical methods, the authors provide a transparent overview of the risks faced by farmers and the adoption of risk management strategies in developed and developing countries.

From the analysis, the authors found that, in terms of risk management strategies, diversification, reserve credit and accumulated assets are frequently used in developing countries, while developed countries tend to rely on future/forward contracts, crop insurance and hedging. Diversification is the most widely used risk management strategy across both developed and developing countries. Our study also highlights the different perceptions of weather-related risks among growers in developed and developing countries.

This systematic review provides valuable insights into the risks associated with agriculture and farmers' strategies in managing these risks, which could inform policy decisions and promote sustainable agricultural practices. For instance, understanding the individualistic nature of farmers' risk perception and the varying risk sources and management strategies depending on the locality and provide assistance to the farmers accordingly.

The paper explains how farmers behave during uncertainty in terms of risk perception and their decision to adopt risk management strategies in developed and developing countries.

Significant unexplored research gaps exist in relation to assessing how governments influence innovations in the logistics and supply chains of SMEs to mitigate risks. This study emphasizes the impacts of regulatory coercion and government subsidization on logistics and supply chain innovations and the corresponding effect of logistics and supply chain innovations on financial performance, logistics and supply chain robustness, green competitiveness, social and environmental responsibilities.

Using a quantitative approach, partial least square structural equation modeling and a survey research design, data were collected and analyzed on 210 logistics and manufacturing firms.

The results support the fundamentals of the stakeholder theory and natural resources-based view (NRBV) regarding the positive impacts of regulatory coercion and government subsidization on logistics and supply chain innovations. Furthermore, logistics and supply chain innovations significantly influenced firm performance (financial performance, logistics and supply chain robustness and green competitiveness) and societal impact (social and environmental responsibilities). Particularly, while logistics and supply chain innovations had insignificant influence on social and environmental responsibilities, the effects of logistics and supply chain robustness were significant.

The study presents empirical findings on the impact of government influences on logistics and supply chain management and the corresponding implications for firms and society. Thus, this study contributes to corporate social responsibility (CSR) and logistics and supply chain literature and provides guidance for policymakers, industry players, scholars and practitioners.

Social media celebrities are getting popular in promotions, and more people have experienced social media to receive information on diet and health tips. This research presents a study showing how social media can influence young people's diet behavior through collaboration with social media celebrities.

Through recruiting on various social media and online education forums, this research recruited 196 young Hongkongers to participate in an online survey developed based on the AIDA (Action, Interest, Desire, Attention) marketing communication model on how youths access diet information from social media celebrities in Hong Kong.

Hong Kong youths consume diet information from social media celebrities through instant messaging systems, social networking sites and online videos, and, in particular, information on food calories and nutrition. However, sponsorship from vendors would decrease their desire to agree with the messages from social media celebrities. After receiving this information, some participants would follow tips and guides from social media celebrities. However, they seldom share such information. Interestingly, males are more willing to follow these tips and guides.

First, this study fills the gap of prior research, which did not study much on how social media celebrities contribute to diet promotion to youths in Asia. Second, through the AIDA Model, this study shows how social media can affect the awareness and accessibility of diet information by young Hongkongers, followed by initiating their interest in this topic and retrieving more relevant information. Furthermore, the authors further understand their desire to follow and improve their behavior as promoted by social media influencers and how they practice such behavior. Based on these findings, health-related brands could consider using social media influencers helping to promote their products and services, and these brands could further use social media to secure customer engagement.

This study investigates how firms build strong dynamic marketing capability (DMC) from open innovation (OI) to enhance the performance of entrepreneurial firms. Moreover, this study unfolds DMC's mediating and moderating mechanisms underlying inbound and outbound OI and performance relationships, respectively.

To test the research model and hypotheses, this study drew a sample of 251 firms operating in Malaysia using the time-lagged survey method. Structural equation modelling was used in this study to investigate the model relationships.

The findings of this study reveal the positive interplay between inbound OI (knowledge acquisition) and DMC. The outbound OI (knowledge exploitation) in this study is found to mediate the relationship between inbound OI and firm performance. In addition, while the DMC has a mediating effect in the relationship between inbound OI and firm performance, such a capability reinforces the positive relationship between outbound OI and performance.

This study provides a noble insight into the complex interplay between OI and entrepreneurial firms' performance by developing and testing an integrated framework underpinned by a knowledge-based view and dynamic capability theory. The findings highlight the significance of taking an interdisciplinary and integrated approach to better understand the determinants of entrepreneurial firms' performance in an emerging country context.

This study aims to compare and evaluate the application of commonly used machine learning (ML) algorithms used to develop models for assessing energy efficiency of buildings.

This study foremostly combined building energy efficiency ratings from several data sources and used them to create predictive models using a variety of ML methods. Secondly, to test the hypothesis of ensemble techniques, this study designed a hybrid stacking ensemble approach based on the best performing bagging and boosting ensemble methods generated from its predictive analytics.

Based on performance evaluation metrics scores, the extra trees model was shown to be the best predictive model. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method. Finally, it was discovered that stacking is a superior ensemble approach for analysing building energy efficiency than bagging and boosting.

While the proposed contemporary method of analysis is assumed to be applicable in assessing energy efficiency of buildings within the sector, the unique data transformation used in this study may not, as typical of any data driven model, be transferable to the data from other regions other than the UK.

This study aids in the initial selection of appropriate and high-performing ML algorithms for future analysis. This study also assists building managers, residents, government agencies and other stakeholders in better understanding contributing factors and making better decisions about building energy performance. Furthermore, this study will assist the general public in proactively identifying buildings with high energy demands, potentially lowering energy costs by promoting avoidance behaviour and assisting government agencies in making informed decisions about energy tariffs when this novel model is integrated into an energy monitoring system.

This study fills a gap in the lack of a reason for selecting appropriate ML algorithms for assessing building energy efficiency. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method.

Despite carbon reduction commitments, many constraints hinder the delivery of low-carbon buildings (LCBs) in high-rise high-density cities. The collaborative commitment of relevant stakeholders is vital to effectively address and mitigate these constraints. Hence, this study aims to comprehensively explore the required stakeholder collaboration attributes to address and mitigate the “common” constraints of delivering LCBs by focussing on several high-rise high-density cities.

A list of 21 “significant and common” constraints was identified through a systematic literature review followed by a questionnaire survey covering five economies (Hong Kong, Singapore, Australia, Qatar and the UAE). Nineteen influential stakeholders/stakeholder categories were identified through the literature, and their ability to influence the 21 constraints was mapped and identified through a two-round Delphi survey of 15 experienced professionals. The Delphi survey findings were analysed through social network analysis (SNA) methods to assess the stakeholder engagement and collaboration attributes.

The SNA results revealed the ability of stakeholders to influence the constraints, required collaborative stakeholder networks to address the constraints, significance of stakeholders according to the SNA centrality measures, core and periphery stakeholders and individual co-affiliation networks of core stakeholders.

While achieving the planned primary target of exploring stakeholder collaboration and their significance through SNA, this study also presents a useful sequential methodological approach for future researchers to conduct similar studies in different contexts. The findings also provide a foundation for accelerating the delivery of LCBs by strengthening stakeholder collaboration.

There are two purposes in this paper. The first one is to explore the impact mechanisms and paths of service-oriented manufacturing (SOM) on the sustainability performance of green manufacturing firms and to pay particular attention to the mediating role of enterprise costs in the relationship between the two. The second one is to reveal the dynamic process and laws of SOM influencing on the sustainability performance of green manufacturing enterprises.

This paper employs a combination of dynamic and static research from two aspects. On the one hand, based on 495 green manufacturing firms in China, the authors verify the SEM of SOM, enterprise cost and sustainability performance of green manufacturing firms through empirical research, analyze the path relationship and mediation effect, and demonstrate its complex impact mechanism. On the other hand, the authors use agent-based modeling and simulation to reveal the dynamic influence of SOM on the sustainability performance of green manufacturing enterprises and explore its dynamic laws and future development trends.

The study results indicate that (1) SOM has a direct positive effect on firm sustainability performance. (2) Reducing firm costs has a positive effect on firm sustainability performance, and firm costs play a partial mediating role in the mechanism by which SOM influences firm sustainability performance. (3) The dynamic impact of SOM on sustainability performance increases significantly over time. (4) Significant firm heterogeneity exists in the process by which SOM improves sustainability performance. (5) There are differences in the promotion of SOM for economic performance, environmental performance and social performance.

This paper makes two main contributions. First, compared with previous research on sustainability performance focusing on a certain dimension, this paper organically integrates the three dimensions of sustainability performance, regards them as a whole and considers the paths to improve sustainability performance. Second, this paper focuses on the complex relationship among SOM, enterprise costs and sustainability performance and reveals different sustainability performance improvement paths and dynamic impact processes, thereby expanding and deepening previous research on sustainability on the subject. These contributions lead to a better understanding of the driving forces and realization path for green manufacturing firms' sustainability performance from an integrated static and dynamic perspective.

This study aims to examine the international market selection process of entrepreneurs operating internationally.

Four small and medium-sized comparative and rich-information case studies were purposefully selected from among Australian and Arabian firms. Data were collected via in-depth personal interviews, follow-up interviews and questionnaire instrument.

The results revealed that entrepreneurs used a four-stage systematic decision-making process to attain profitable foreign market choices. The decision process was influenced by cognitive boundaries as entrepreneurs relied on the availability experiential, anchoring and adjustment heuristic.

The research’s findings and the proposed decision model will, significantly, assist entrepreneurs, willing to expand internationally, in enhancing their decision-making to attain profitable foreign market choices. Further, it provides benefits to foreign investment policymakers in host countries by assisting them to attract more inward foreign direct investments, and, accordingly, enhance the economic and social development movement in their countries.

This study provides a significant theoretical contribution to the literature on the internationalization process of entrepreneurs and small- and medium-sized enterprises through developing a decision model for selecting and entering foreign markets by entrepreneurs in a cross-country context. Further, the study provides significant methodological contributions with regard to the effectiveness of the qualitative case study method in capturing elements of the foreign market selection process.