The global agreement on environmentally friendly policies puts pressure on businesses to implement good practices to increase legitimacy in a competitive environment. This research aims to examine business dynamic capabilities and value creation processes through the concept of green dynamic marketing capabilities. This concept addresses the ability of businesses to absorb, manage information and accumulate new knowledge that fuels innovative endeavors. The dynamic capability view and customer value theory are integrated to theoretically explain the value creation process of market-orientated innovative products. A total of 58 global companies in Clean200 were sampled. A quantitative approach was conducted to measure the effect of organizational learning (environment management team, environment management training, environment supply chain management) on green innovation (environmental innovation score, eco design product). The results showed that the contribution of Model-1 (0.473 or 47.3%) explained the effect of organizational learning on environmental innovation score, respectively on the variables of environment management team (2.859/0.005), environment management training (−2.971/0.003), and environment supply chain management (7.786/0.000). The contribution of Model-2 (0.448/44.8%) explains the effect of organizational learning on eco-design product, respectively on the variables of environment management team (4.280/0.000), environment management training (−6.401/0.000), and environment supply chain management (7.910/0.000). Model-3 tested the structural association variables in organizational learning and green innovation. A significant influence can be seen with a probability value smaller than 0.05. This research shows that the concept of green dynamic marketing capabilities can be used to explain the ability of businesses in response to the pressure of green global norms through the development of organizational learning towards creation of green innovation product that has impact on market performance. The implication of this research is the creation of new mindset in which green global norms challenge becomes an opportunity for businesses to improve competitiveness.

This study replicates and extends Corbett and Kirsch (2001) and Vastag (2004) using a new data set to investigate the drivers of ISO 14000 certification diffusions using decision tree analysis. The findings indicate that at the national level, ISO 14000 certification diffusions are influenced by factors other than ISO 9000 certification diffusions, such as the number of environmental treaties signed and ratified, industrial activities as a percentage of GDP, and GDP per capita, thus provides a range of managerial insights and enhances scholarly understanding of sustainability beyond the influence of ISO 9000. Future studies might extend the countries included in this study to see if the results are the same. Future research may include other factors like a country’s Environmental, Social, and Governance (ESG) indicators to better understand its commitment to sustainability, including environmental sustainability. The country’s culture may influence customers, investors, and other stakeholders’ knowledge and desire for sustainable practices and inspire firms to obtain ISO 14000 certifications. Since larger firms may seek ISO 14000 certification, future studies may evaluate the influence of the number of large firms in various countries as drivers of ISO certification diffusions.

This study aimed to determine the socio-economic poverty status of those living in rural areas using data surveys obtained from household expenditure and income. Machine learning-based classification and clustering models were proven to provide an overview of efforts to determine similarities in poverty characteristics. Efforts to address poverty classification and clustering typically involve comprehensive strategies that aim to improve socio-economic conditions in the affected areas. This research focuses on the combined application of machine learning classification and clustering techniques to analyze poverty. It aims to investigate whether the integration of classification and clustering algorithms can enhance the accuracy of poverty analysis by identifying distinct poverty classes or clusters based on multidimensional indicators. The results showed the superiority of machine learning in mapping poverty in rural areas; therefore, it can be adopted in the private sector and government domains. It is important to have access to relevant and reliable data to apply these machine learning techniques effectively. Data sources may include household surveys, census data, administrative records, satellite imagery, and other socioeconomic indicators. Machine learning classification and clustering analyses are used as a decision support tool to gain an understanding of poverty data from each village. These strategies are also used to describe the profile of poverty clusters in the community in terms of significant socio-economic indicators present in the data. Village clusters based on an analysis of existing poverty indicators are grouped into high, moderate, and low poverty levels. Machine learning can be a valuable tool for analyzing and understanding poverty by classifying individuals or households into different poverty categories and identifying patterns and clusters of poverty. These insights can inform targeted interventions, policy decisions, and resource allocation for poverty reduction programs.

The study aims to explain the relationship between the effectiveness of a business and its management through the analysis of working capital. The findings prove the complementary relationship. The analysis of working capital will always have a significant impact on the effectiveness of business management. The main objective of any corporation is to be effective in business, which can be achieved by analyzing the working capital. The result shows that analysis of working capital based on factors like operational efficiency, the company’s earnings and profitability, cash management, corporate receivable management, and corporate inventory management creates room for improvement and effectiveness in business management. Firms might enhance finances for business expansion by lowering their working capital requirements. It has also been revealed that there is a considerable difference in industries across time. It was observed that there is a high association between working capital efficiency and firm profitability. A highly efficient corporation is less vulnerable to liquidity risk and is also self-sufficient in terms of external finance. Numerous studies have been done to regulate the true rapport between working capital investments and their impact on financial presentation. It demonstrates that effective investment in working capital management may boost profitability and business value. The relationship between accounting and finance was explained by measuring working capital management in demand to illustrate the status of profitability. It was suggested that accountants take a more professional approach to updating their accounting and finance skills in their organization through effective working capital management.

Evaluating tourist destinations is extremely important as it is the basis for helping local authorities and the leadership of tourist destinations implement reasonable solutions to strengthen the state management of tourism, encourage investment and upgrade service quality at destinations, better exploit the tourist market, position the tourist destination brand in the international tourism market, increase the length of stay, and increase tourist spending when coming to the tourist destination. The current state of investment and development of tourist destinations means that tourist areas across the country need to be evaluated and classified to have a basis for encouraging investment and strengthening effective management, upgrading service quality at destinations, and gradually positioning the Vietnamese tourism destination brand in the international tourism market. This study evaluates the Ba Na tourist area (Da Nang city, Vietnam) based on the “Set of criteria for evaluating tourist destinations” issued by the Ministry of Culture, Sports and Tourism of Vietnam (2016). issued under Decision No. 4640/QĐ-BVHTTDL on 28 December 2016. Evaluation results show that criteria for tourism resources, landscape, facilities, participation of local communities, and the management of the tourist area are evaluated very well. On the contrary, services for entertainment, shopping, entertainment, and prices of services in the tourist area are limited problems in the Ba Na tourist area.

Climate change is an important factor that must be considered by designers of large infrastructure projects, with its effects anticipated throughout the infrastructure’s useful life. This paper discusses how engineers can address climate change adaptation in design holistically and sustainably. It offers a framework for adaptation in engineering design, focusing on risk evaluation over the entire life cycle. This approach avoids the extremes of inaction and designing for worst-case impacts that may not occur for several decades. The research reviews case studies and best practices from different parts of the world to demonstrate effective design solutions and adjustment measures that contribute to the sustainability and performance of infrastructure. The study highlights the need for interdisciplinary cooperation, sophisticated modeling approaches, and policy interventions for developing robust infrastructure systems.