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The study investigates the inter-linkages between geopolitical risk (GPR) and food price (FP).

By employing the bootstrap full- and sub-sample rolling-window Granger causality tests.

The empirical results show that there is a time-varying bidirectional causality between GPR and FP. High GPR leads to a rise in FP, suggesting that geopolitical events usually may disrupt supply and demand conditions in food markets, and even trigger global food crises. However, the negative effect of GPR on FP does not support this view in certain periods. This is mainly because GPR is also related to the global economic situation and oil price, which together have impacts on the food market. These results cannot always be supported by the inter-temporal capital asset pricing model, which states that GPR affects FP in a positive manner. Conversely, there is a positive impact of FP on GPR, indicating that the food market is an effective tool that can reflect global geopolitical environment.

In the context of the Russia–Ukraine conflict, these analyses can assist investors and policymakers to understand the sensitivity of FP to GPR. Also, it will provide significant revelations for governments to attach importance to the role of food price information in predicting geopolitical events, thus contributing to a more stable international environment.

Despite the growing attention being paid to the role of uncertainty in the competitive business environment, few studies have considered uncertainty as an antecedent factor and explored its direct impact on accelerating a firm’s innovation speed. This study develops a conceptual framework that examines the impacts of technological uncertainty and market uncertainty on innovation speed, building on complex adaptive theory. Furthermore, it is important to note that the internal resources of a firm and its external environment are not separate entities. In this study, we investigate the moderating role of a firm's internal and external resource ability (financial constraints level and organizational slack level) in the relationship between environmental uncertainty and innovation speed.

Our data sample is the panel data of China's A-share listed companies. The data year span is from 2000 to 2018. We use a hierarchical regression analysis model.

Our results reveal that both technology uncertainty and market uncertainty can promote innovation speed. Still, a firm’s organizational slack positively moderates the relationship between technology uncertainty and innovation speed, and financial constraints negatively moderate the relationship between demand uncertainty and innovation speed.

Our research contributes to the existing literature on uncertainty and extends its research perspective by no longer taking uncertainty as an environmental factor but exploring its direct impact. Still, our research focuses on innovation speed and discusses the impact of environmental uncertainty (including technology uncertainty and demand uncertainty) on firms’ innovation speed, expanding the limitations of previous research, which usually holds a relatively general perspective on innovation problems.

Construction and demolition waste has emerged as a significant challenge for sustainable development globally. Hence, construction waste management (CWM) is considered one of the critical sustainable deliveries stipulated in various green building rating systems (GBRSs), including Homestar in New Zealand (NZ). The 6 Homestar rating is mandated for use by the national public housing provider. However, no empirical study has been conducted on CWM in 6 Homestar dwellings. This study investigates the current practice of CWM in those projects.

Primary data were extracted from 6 Homestar built assessment submissions for 100 public housing projects. The waste reports provided quantitative data to calculate the waste generation rate (WGR), waste diversion rate (WDR) and diverted waste rate (DWR) for descriptive analysis. These findings underwent further exploration by analysing site waste management plans.

With the aid of on- and off-site sorting and the recycling centre, a significant WDR is achieved at an average of 75.6%. However, diverted waste is treated at a low-priority level in the waste management hierarchy, and WGR remains relatively high.

The findings of this study can serve as valuable resources for managers in formulating comprehensive waste management plans and for policymakers in developing strategies and policies towards enhancing CWM practices. The study suggested the need for further focus towards minimising construction waste (CW) from the early design plan to achieve the construction industry's zero-waste target.

Online food shopping has emerged as a fast-growing market. However, the retail online food supply chain (ROFSC) is attracting increasing attention due to its social, environmental and financial impacts. This study aims to empirically evaluate food waste prevention and mitigation (FWPM) strategies in a real-world case study within the UK ROFSC.

Advanced methodologies are required to explore and address FWPM problems across ROFSC. Surveys and interviews were conducted with practitioners. Hard and soft data were collected from the case online retailer. Experts from an FWPM non-profit organization checked and validated the data collected.

Results revealed that inter/cross-organization integrated collaboration and visibility in the ROFSC influence FWPM. Findings established that consumers are the main source of food waste, followed by suppliers and online retailers, with 18, 11 and 1%, respectively. Worryingly, only 1% of respondents expressed that there is a strong commitment to a zero-waste strategy, emphasizing the necessity for more effective waste reduction initiatives and awareness.

The research outcome calls for further efforts by policymakers and practitioners to guide consumers toward efficient food waste management practices.

The study extends previous literature by proposing a holistic framework for reducing food waste from suppliers and consumers. The study captured interesting insights on food waste, including measuring, reasoning and destinations of online food waste.

This paper aims to investigate the problem of vision based autonomous laparoscope control, which can serve as the primary function for semi-autonomous minimally invasive surgical robot system. Providing the surgical gesture recognition information is a fundamental key component for enabling intelligent context-aware assistance in autonomous laparoscope control task. While significant advances have been made in recent years, how to effectively carry out the efficient integration of surgical gesture recognition and autonomous laparoscope control algorithms for robotic assisted minimally invasive surgical robot system is still an open and challenging topic.

The authors demonstrate a novel surgeon in-loop semi-autonomous robotic-assisted minimally invasive surgery framework by integrating the surgical gesture recognition and autonomous laparoscope control tasks. Specifically, they explore using a transformer-based deep convolutional neural network to effectively recognize the current surgical gesture. Next, they propose an autonomous laparoscope control model to provide optimal field of view which is in line with surgeon intra-operation preferences.

The effectiveness of this surgical gesture recognition methodology is demonstrated on the public JIGSAWS and Cholec80 data sets, outperforming the comparable state-of-the-art methods. Furthermore, the authors have validated the effectiveness of the proposed semi-autonomous framework on the developed HUAQUE surgical robot platforms.

This study demonstrates the feasibility to perform cognitive assistant human–robot shared control for semi-autonomous robotic-assisted minimally invasive surgery, contributing to the reference for further surgical intelligence in computer-assisted intervention systems.

The purpose of the this study is to discover the impact of practices of knowledge management, intellectual property protection and management innovation on entrepreneurial leadership, which in turn leads to sustainable growth in small and medium-sized enterprises.

The data was collected from 292 small and medium-sized businesses (SMEs) in the USA using a cross-sectional survey. To evaluate the study hypotheses and analyse the data, structural equation modelling was used. SMART-PLS software was used for both confirmatory factor analysis and structural analysis.

The work has significantly contributed in revealing that knowledge management practices, management innovation and intellectual property protection have a substantial and constructive impact on entrepreneurial leadership, which in turn leads to sustainable growth in SMEs.

The study findings recommend that SMEs must focus on knowledge management practices, intellectual property protection and management innovation to nurture entrepreneurial leadership, which can lead to sustainable growth. SMEs can benefit from investing in knowledge management practices, protecting their intellectual property and innovating their management practices to achieve sustainable growth. Also, the absorptive capacity of an SME can help it to aggravate the impact of the above factors and lead them to sustainable growth faster.

The current work studies the association between knowledge management practices, intellectual property protection, management innovation, entrepreneurial leadership and sustainable growth in SMEs, thus contributing to the literature. The study provides insights into the factors that can nurture entrepreneurial leadership and contribute to sustainable growth in SMEs, which can inform policy and practice in the field of entrepreneurship.

In light of the challenges and opportunities posed by globalization and technological advancements, this study aims to develop a decision-support system to assist companies in identifying, structuring and prioritizing variables influencing their transformation and adaptation processes to Society 5.0.

The research employs a methodological approach focused on knowledge creation through expert discussions involving diverse backgrounds. Cognitive mapping and interpretive structural modeling (ISM) guide the process, allowing for the integration of subjective elements into the analysis system while ensuring objectivity through ISM. The methodology involves structuring the decision problem, identifying and ranking key factors and evaluating their cause-and-effect relationships.

The analysis underscores the significance of technology and external factors compared to other areas of interest within the model. Consequently, the study emphasizes the necessity for companies to pay special attention to these types of factors during their transformation processes.

While the study provides valuable insights, the reliance on expert discussions may introduce biases or overlook certain perspectives. Additionally, the findings may not be universally applicable and may require customization based on specific organizational contexts or industries. However, the proposed decision-support system offers a practical tool for companies seeking successful adaptation to Society 5.0.

This study provides a novel approach to addressing the challenges posed by globalization and technological advancements. It presents a valuable resource for organizations striving to adapt effectively in the evolving socioeconomic landscape.

Social media is booming in the digital age, and its rich availability provides many opportunities for companies to innovate across borders. In reality, how enterprises use social media to achieve cross-border innovation also faces important challenges such as breaking path dependency.

This paper explores how social media can facilitate cross-border innovation from the perspective of strategic capability, combined with the path dependency theory and attention-based view. Hierarchical regression analysis and bootstrap method are adopted to test the hypotheses based on survey data provided by 173 firms in China.

The findings show a positive relationship between social media strategic capability and cross-border innovation, with path dependency playing a mediating role. In addition, two internal and external contextual factors, namely customer embeddedness and competitive pressure, play moderating roles, with customer embeddedness negatively moderating the negative relationship between social media strategic capability and path dependency and competitive pressure negatively moderating the negative relationship between path dependency and cross-border innovation.

These findings provide not only new insights into social media and cross-border innovation but also theoretical guidance on how companies can effectively use social media in practice.

The paper aims to examine the influence of closed and open innovation practices on economic performance. This papert also examines the mediating roles of innovation performance and firm performance. The study uses innovation theory based on knowledge management for theoretical support.

The methodology involves two steps. First, all the variables relevant to the adoption of innovative approaches and performance parameters are identified. Subsequently, primary data are gathered from decision-makers of 200 biotechnological firms and a structural equation modeling analysis is performed.

The study's results showed that the open innovation practice, such as interaction with large research and development (R&D) firms and customers, influences the performance parameters. The findings indicate that closed and open innovation practices positively impact performance measures like innovation, firm and economic performance. The results also indicate the mediating role of firm performance. However, the innovation performance was not found to mediate the relationship.

This examination gives experimental bits of knowledge from any confining influence innovation approaches in India. Analysts and specialists of firms can use the results of the current study to comprehend the effect of various innovation practices on different performance measures.

This research paper aims to establish a comprehensive framework for the barriers to CER in the construction industry, assesses the barriers' relative degrees of hindrance and causal mechanisms.

Firstly, 26 carbon emission reduction (CER) barriers in the construction industry were identified based on a systematic literature review (SLR) and categorized into five dimensions: policy, economy, society, technology and organization (PEST + O model). Secondly, the Best–Worst Method (BWM) was used to clarify the degrees of hindrance of the CER barriers. Then, the Grey-Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL) was used to visualize the directional cause–result relationship network among prominent barriers. Finally, the Boston matrix model was used to propose differentiated strategies to address CER barriers in the construction industry.

The calculated centrality and causality of the prominent barriers indicated that the lack of relevant legal policies and normative guidelines, the poor binding force and enforcement of existing relevant policies, the lack of effective economic subsidies and incentives and the difficulty in the operation, transformation and upgrading of existing construction CER are the key barriers that CER needs to address first in the construction industry. Considering the order of priority and the optimal path, differentiated countermeasures are proposed to address key, driving, independent and effect barriers.

This study develops a BWM–Grey-DEMATEL integrated multi-criteria decision-making model. An innovative C-shaped strategic map for addressing CER barriers in the construction industry is proposed by integrating the dual dimensions of time and space. This will guide practitioners, policymakers and decision-makers in developing CER strategies.