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This study aims to investigate the relationship between geopolitical risk (GPR) and gold price bubbles to determine whether rising GPR can drive deviations in the fundamental value of gold, thus leading to speculative bubbles.

Using a data set that spans from January 2002 to December 2023 and covers both GPR data and gold price data, this study applies the log-periodic power law singularity (LPPLS) model to identify gold price bubbles. The analysis explores the effects of GPR and its sub-indices – geopolitical risk–acts (GPRA) and geopolitical risk–threats (GPRT) – on gold price bubbles. The causal relationships are examined through logistic regression, Tobit modelling and machine learning, with a focus on different countries, including major gold producers and consumers.

The results indicate a significant relationship between GPR and gold price bubbles, particularly with GPRA, which exerts a stronger influence than GPRT does. Peaks in GPR often align with the formation of gold price bubbles, both positive and negative. Additionally, geopolitical instability in Russia has a significant effect on US gold price bubbles.

The findings provide valuable insights for investors and policymakers by emphasizing the importance of GPR in shaping gold price dynamics. Investors are advised to consider the nuanced roles of GPRA and GPRT when using gold as a hedge during periods of heightened geopolitical tension.

Understanding the role of GPR in gold price bubbles can help mitigate the financial risk associated with speculative bubbles, thereby offering a better framework for managing assets during geopolitical crises.

This study extends existing research by directly linking GPR with gold price bubbles via the LPPLS model, with a novel emphasis on the differentiation between GPRA and GPRT, providing new perspectives on the safe-haven role of gold during geopolitical uncertainty.

This study aims to find how trade development and digitalization affect smart-green production. Four factors are investigated in these effects (certification, technology innovation, natural resource management, low pesticides).

The mix-method approach was employed from validating the measurement scale to test the proposed hypotheses. At first, the grounded theory is the most authoritative and standard research method in qualitative research. Secondly, quantitative analysis was employed to draw conclusions about the impact of digitalization and trade development on smart-green agricultural production.

The results found that digitalization and trade development impact the development of smart-green agricultural production through certification employment, technology innovation, and a decrease in pesticide usage. Moreover, digitalization and trade development also indirectly affect the development of intelligent green agricultural production. Meanwhile, digitalization has a higher impact than trade development.

This research is based on the premise that digitalization and trade development can drive smart green agricultural production. Still, some studies have found a deviation between trade development and environmental protection. Hence, future research can explore the incentive effect of trade development and digitalization on other industries. Second, the measurement of the dependent variables in this study is based on the premise that smart-green agricultural production has not been widely promoted, so the changes in production before and after the whole public participation in smart-green output have yet to be reflected.

Smart green production in agriculture is essential for a transition economy and the world to meet food security and protect the environment. However, the effects of certification, technology innovation, natural resource management, and low pesticides on smart-green agriculture production have yet to be identified. Insights from this study can help governments, policy-makers, and farmers in emerging economies by adapting their strategies within their local contexts.

This paper bridges the gap between the theory and practice by developing a life cycle sustainability tracker (LCST). The study is seeking to proffer solutions to an observed shortcoming of conventional life cycle sustainability assessment (LCSA) communication platforms. Notably, the static nature of the information provided on such platforms has made it difficult for them to be used for real-time decision-making and predictions. The main aim of this paper is to develop a LCST that facilitates a dynamic visualisation of life cycle sustainability results and allows for an integrated benchmark across the dimensions of sustainability.

The study leverages the model development capabilities of the design science research strategy in accomplishing a dynamic and novel communication platform. A life cycle thinking methodology and appropriate multicriteria decision approach (MCDA) is applied to accomplish a comprehensive, streamlined and replicable approach in mapping and tracking the progress of sustainable development goals (SDGs) in the National Infrastructure Pipeline (NIP) projects in India.

It was found that: (1) The use of the LCST tracker provides a dynamic and holistic insight into the key LCSA indicators with clearly defined benchmarks to assess the impact on the SDG 11, (2) The NIP projects achieve an upward trend across all the regions, and the percentage of opportunities ranges from 11 to 24%, with the South experiencing the highest growth and the North having the minimal increase in percentage and (3) The assessment score (52–58%) provides performance metrics that align well with the LCST – which ranges between “Fair” and “Average” for all the regions in India.

The novelty of this research is that the LCST provides a transparent and harmonised approach to reporting on the LCSA results. The LCST utilises heat maps and radial mapping to achieve an intuitive display of large amounts of highly heterogeneous data, thus allowing the synthesis of large sets of information compactly and with coherence. Progress towards the SDGs change on a yearly basis; hence, a dynamic LCSA tool provides a timely and the valuable context to map and track performance across different regions and contexts.

This study explores the factors that influence platform-to-platform cooperation (PPC) and designs a theoretical framework for platform research.

This multi-case study includes a combination of exploratory and explanatory case studies.

From the internal factor perspective, channel integration capability, technology-based order matching capability and service innovation capability positively affects the PPC. From the perspective of external factors, the impact of a new platform entry on the PPC depends on market power and complementarities between platforms in the supply and value chains. Diversity of demand also has a positive effect on the PPC, which is moderated by network externalities. It is worth noting that the incumbent platform prefers to diversify its services for collaborating platforms with a higher level of cooperation. In addition, the higher diversity of demand, the stronger the service innovation capability, which indirectly impacts cooperation positively.

The PPC has gained immense popularity in recent years. However, no scholars have investigated the factors influencing the PPC decisions, which warrants further exploration. This study sheds light on the factors and mechanisms that influence the PPC from both internal and external perspectives.

This study examines the relationship between board gender diversity (BGD) and financial performance (FP) in the Malaysian emerging market, focusing on the mediating role of Environmental, Social and Governance (ESG) performance.

Using a dataset of 976 observations from Malaysian publicly listed companies from 2016 to 2023, this study explores BGD as the independent variable with FP measured through both accounting and market metrics. ESG performance serves as a mediating variable. The analysis employs Structural Equation Modelling (SEM) to examine direct and mediating effects, supplemented by the Baron and Kenny approach and Two-Stage Least Squares (2SLS) regression for robustness.

The findings indicate that higher BGD positively and significantly impacts all three performance measures: Tobin's Q (TQ), Return on Assets (ROA) and Return on Equity (ROE). ESG performance positively influences these measures. The SEM analysis reveals a significant positive impact of BGD on ESG performance, which fully mediates the relationship between BGD and TQ/ROA and partially mediates the relationship between BGD and ROE.

The results have significant implications for policymakers, board members, scholars and investors, stressing the importance of gender diversity and ESG performance in improving FP. The findings suggest that enhancing board effectiveness through BGD can promote sustainable practices and align corporate strategies with broader sustainability goals, which eventually helps to improve companies’ FP.

This research contributes to the literature by highlighting the mediating role of ESG performance in the relationship between BGD and FP and emphasizing the importance of gender diversity in corporate sustainability. It addresses this gap by providing insights into how ESG performance enhances the impact of BGD on FP.

This paper aims to develop carbon dots using whey as a valuable resource and to create a sustainable and biocompatible nanomaterial with potential applications in a variety of fields owing to its unique optical properties and antimicrobial capabilities, which are frequently used as sensing agents for detecting specific molecules in food, environmental and biomedical applications. Versatility of carbon dots (CDs) allows the utilization of these dots for a wide range of applications in areas such as food safety, antibacterial properties, production of composite polymers for food packaging, treatment of different diseases and detection of food-borne pathogens. Owing to their high brightness, low toxicity and excellent biocompatibility, CDs have attracted significant interest in food safety. This is also a cutting-edge technology that bids new ideas for treating various diseases.

Literature review related to using whey as the carbon source for synthesis of CDs was collected and studied from different sources like Google Scholar, Research Gate, online journals available at library of Banaras Hindu University, Web of Science and Scopus. A database of more than 100 scientific sources from different sources was made as per the headings and sub headings of the paper.

Whey generated as a by-product from the cheese industry contained a good amount of carbon and nitrogen that can be used for the fabrication of CDs. CDs produced using whey exhibited great photostability, high sensitivity and outstanding biocompatibility and also showed that Fe3+ ions could be quickly, sensitively and extremely selectively detected in an aqueous solution of CDs, with a revealing limit of 0.409 µM in the linear range of 0–180 µM. CDs are a promising area of study to a key component of next-generation multifunctional nanomaterials, promoting creativity, sustainability and useful solutions across a variety of industries, including health care and energy. The susceptibility of S. typhimurium (Gram-negative) was found to be higher than that of L. monocytogenes (Gram-positive) bacteria with MIC and MBC of 500  and 1000 µL/mL, respectively.

Whey-derived CDs are an environmentally beneficial substitute for conventional additives and their biocompatibility guarantees that they adhere to food safety regulations. In light of the future, the green volarization of dairy waste for the synthesis of CDs is consistent with the increasing worldwide focus on environmental responsibility and sustainability.

BIM technology has a huge potential for improving the renovation efficiency for as-built buildings. However, due to the absence of raw design drawings and the complex interior environment, it is difficult to implement 3D reconstruction of building interiors in interior renovation projects. Therefore, this study proposes a 3D reconstruction framework of building interiors, with an aim to generate building interiors building information modeling (BIM) models quickly and accurately based on scan-to-BIM and generative design.

The proposed framework begins by reconstructing interior structured elements based on the scan-to-BIM process including collecting accurate information of as-built buildings by laser scanning, obtaining point clouds of structured elements through deep learning and developing an efficient dynamo algorithm workflow for generating structured elements BIM model. For unstructured elements, intelligent layout design and efficient BIM generation are conducted by combining the BIM tools and generative design.

The successful implementation of the proposed framework in a conference room demonstrated the feasibility of the proposed framework. The semantic segmentation scheme based on deep learning also exhibited excellent recognition and high efficiency for interior structured elements. Furthermore, it is proved that the combination of scan-to-BIM and generative design has high application value in the 3D reconstruction of building interiors.

On one hand, a feasible framework is proposed to generate BIM model of building interiors, improve interoperability among different software tools, streamline the complexity of the scan-to-BIM process and meet the reconfiguration requirement of unstructured elements layout scheme in interior renovation projects. On the other hand, the use of BIM and various emerging technologies can drive digital transformation and further advance the industrialization process of interior renovation in as-built buildings.

The purpose of this study is to analyze the impacts of the COVID-19 pandemic on the performance of companies using a hybrid Multi-Criteria Decision-Making (MCDM) approach. Specifically, the study examines Türkiye’s Top 500 Industrial Enterprises to analyze their performance before and during the pandemic, and to capture their performance in determining investment and production strategy.

To achieve the study’s objectives, the Fuzzy Best-Worst Method (F-BWM) was used to obtain importance levels of performance indicators, decreasing the vagueness in experts’ decision-making preferences. The Measurement Alternatives and Ranking According to Compromise Solution (MARCOS) method was used to rank enterprises based on their performance.

The COVID-19 pandemic has clearly had a substantial impact on the performance of Türkiye’s top 500 industrial enterprises. While some companies suffered decreased sales, others reported that their revenues increased or remained constant during the outbreak. The results reveal that the pandemic caused a shift in the initial ranking outcomes for the first two enterprises.

The study’s limitations include the sample size and the time period under consideration, which may have an impact on the generalizability of the findings.

Decision-makers’ investment, employment and operational decisions were influenced by the impact of the COVID-19 pandemic. The results provide insights for decision-makers on how to achieve higher growth and performance under the pressure of the pandemic.

The study’s practical consequences help decision-makers understand how to attain higher growth and performance in the face of the epidemic.

The originality of this study lies in using a hybrid MCDM approach to examine the impact of the COVID-19 pandemic on company performance. A hybrid MCDM approach is proposed to help decision-makers make the best possible investment and implementation decisions.

The purpose of this study is to investigate the influence of corporate governance structure corporate governance on a firm’s performance in the Palestinian business environment between 2016 and 2023. The specific environment of the developing Palestinian economy is the main motivation and emphasis of this investigation.

Data were gathered from 49 financial and non-financial firms listed on the Palestine Stock Exchange between 2016 and 2023. While the random and fixed effects estimates were utilized to be the most suitable for this particular investigation, they were used to undertake the data analysis procedure. The study employed two-stage least squares (2SLS) to assess the robustness and correctness of data to bolster the findings and subsequent implications.

The findings show that the return on equity, a measure of corporate performance, was positively but not significantly impacted by the presence of women on the executive boards of Palestinian companies. This suggests that the variable in question had no bearing on the success of the firms. In terms of moderating influence, corporate governance structure had no bearing on the link between dual chief executives, institution ownership, government ownership, independent directors and firm performance. Family ownership and board size had negative, significant impacts on performance.

The research limitations of this study are that it focuses exclusively on manufacturing firms listed on the Palestine Exchange (PEX) over a seven-year period, which limits its generalizability to other industries and regions. Furthermore, due to a lack of data, the model did not account for global diversity on boards of directors.

The findings of this research help managers understand how management structures impact business success and provide regulatory authorities with insights into gender diversity and corporate governance legislation in Palestine. It suggests enhancing company performance, competitiveness and capital acquisition by improving governance information quality, building investor confidence, raising standards and reforming governance systems.

This study contributes to the literature by enhancing the understanding of how corporate governance and gender diversity affect the financial performance of listed firms, addressing a research gap in the Palestinian market. It is one of the few studies examining company performance during political turmoil, specifically focusing on the increased role of women on Palestinian boards.

The purpose of this study is to evaluate the tannase-assisted extraction of tea stem pigment from waste tea stem, after which the stability of the purified pigment was determined and analyzed.

The extracting process was optimized using the response surface methodology (RSM) approach. Material-liquid ratio, temperature and time were chosen as variables and the absorbance as a response. The stability of the tea stem pigment at the different conditions was tested and analyzed.

The optimized extraction technology was as follows: material-liquid ratio 1:20 g/ml, temperature 50°C and time 60 min. The stability test results showed that tea stem pigment was sensitive to oxidants, but the reducing agents did not affect it. The tea stem pigment was unstable under strong acid and strong alkali and was most stable at pH 6. The light stability was poor. Tea stem pigment would form flocculent precipitation under the action of Fe²⁺ or Fe³⁺ and be relatively stable in Cu²⁺ and Na²⁺ solutions. The tea stem pigment was relatively stable at 60°C and below.

No comprehensive and systematic study reports have been conducted on the extraction of pigment from discarded tea stem, and researchers have not used statistical analysis to optimize the process of tannase-assisted tea stem pigment extraction using RSM. Additionally, there is a lack of special reports on the systematic study of the stability of pigment extracted from tea stem.