There are several factors that generate postharvest losses of Citrus sinensis, but none have been focused on the central jungle of the Junín region of Peru. The objective of this research was to evaluate postharvest losses of Citrus sinensis in the province of Satipo, Junín region of Peru, considering the stages of the production chain. The methodology was applied to descriptive and cross-sectional design. A sample of 10 orange trees, 3 transport intermediaries and 5 traders selected for compliance with minimum volume and quality requirements were used. The °Brix, pH and acidity characteristics of the fruit were determined. Subsequently, absolute and percentage losses were quantified through direct observation, surveys and interviews. The main postharvest losses of Citrus sinensis were 1.50% in harvesting and detaching, 1.75% in transport to the collection center, 2.23% in storage and transport by intermediaries, and 2.90% in storage and sale by retailers. The overall loss was 8.12% throughout the production chain and US$5.75 per MT of C. sinensis harvested. The main damages found were mechanical and biological, caused by poor harvesting and packaging techniques, precarious storage and careless transport of the merchandise.

This study assesses Vietnam’s state-level implementation of artificial intelligence (AI) technology and analyses the government’s efforts to encourage AI implementation by focusing on the National Strategy on AI Development Program. This study emphasizes the possibility of implementing AI at the state level in Vietnam and the importance of conducting continuous reviews and enhancements to achieve sustainable and inclusive AI growth. Impact evaluations were conducted in public organizations alone, and implication evaluations were considered optional. AI impact assessments were constrained by societal norms that necessitated establishing relationships among findings. There is a lack of official information regarding the positive impact of Vietnam’s AI policy on the development of AI infrastructure, research, and talent pools. The study’s findings highlight the necessity of facilitating extensive AI legislation, and strengthening international cooperation. The study concludes with the following recommendations for improving Vietnam’s AI policy: implementing a strong AI governance structure and supporting AI education and awareness.

This study investigated the impact of social media on purchasing decision-making using data from a questionnaire survey of 257 randomly sampled students from the College of Business at Imam Muhammad Ibn Saud Islamic University. The study items were selected from the study community through a random sample, where several (257) students were surveyed. To achieve its objectives, the study follows the descriptive analytical approach in addressing its topic. The questionnaire was adopted as a tool for collecting data. The questionnaire collected data on the independent variable social media—and the dimensions of the dependent variables representing the stages of purchasing decision-making: Feeling the need for the advertised goods, collecting information about alternatives, evaluating available options, buying decisions, and post-purchase evaluation of the purchase decision. Then, the data were analyzed based on regression analysis using SPSS and AMOS. The important findings are summarized below: Social media use is directly related to feeling the need for and searching for information on advertised goods. Social communication and the evaluation of alternatives to advertised goods, in addition to the existence of a moral effect and a direct correlation between social media use and making the purchasing decision for advertised goods. Providing honest, sufficient, and accurate information via social media to the buyer can help them make the purchasing decision.

In light of the metaverse’s vast expansion, it’s a crucial intellectual platform that’s transforming the video game industry and spurring creative innovation and technological advancement. Considering the distinctive niche that Taiwan occupies within the realm of the video game industry, this study uses a total of 11 video game companies in Taiwan as samples. The study spans a period of 16 years, from 2007 to 2022, and utilizes the random effect regression model for analysis. The study results illustrate that intellectual capital efficiency exerts varying contributions to the creation of value across different corporate value indicators within the video game industry. Among the factors, HCE, SCE, and CEE demonstrate the highest explanatory power for ROE, reaching up to 82.23%. Following this, they account for 73.57% of the variance in market share, but only a meager 13.67% for Tobin’s Q. This study is the empirical evidence that different methods of measuring intellectual capital and various definitions of value creation in an industry may lead to divergent results and managerial implications in intellectual capital research. Hence, it is worthwhile for subsequent studies to continue clarifying and delving deeper into these aspects.

The purpose of this study is to examine how financial slack and board gender diversity affect carbon emission disclosure and how that disclosure affects firm value in energy sector companies that are listed on the Indonesian stock exchange between 2017 and 2021. Annual reports and sustainability sources provide secondary data for this quantitative study. Purposive sampling was employed in this investigation, including nine companies and a five-year observation period. Thus, 45 samples altogether were employed in the present study. The partial least squares approach is the data analysis strategy used in this investigation. The study’s findings indicate that the Gender Diversity Board does not significantly affect carbon emission disclosure and significantly influences firm value. Financial slack significantly affects carbon emission disclosure but does not directly affect firm value. Financial slack and board gender diversity through carbon emission disclosure have no significant effect on firm value.

The present study aims at analyzing the various factors influencing consumer attitudes towards the adoption of electric vehicles (EVs) in Saudi Arabia. The study evaluates consumer attitudes, their impact on shaping behaviours, and whether consumer intention mediates the relationship between consumer attitude and purchase behaviour towards EVs. This research employs a mixed-method approach, including literature review, surveys, and data analysis. It investigates EV adoption dimensions encompassing individual, social, economic, and environmental factors. Data collected from 397 current and potential EV owners in Saudi Arabia provide insights into their attitudes and behaviours. Survey findings indicate that in Saudi Arabia, safety rating, social influence, economic value, operating cost, and product variety significantly shape consumer attitudes and influence EV adoption. However, factors like range anxiety, charging infrastructure, environmental concern, and performance expectancy are less significant in affecting consumer attitudes toward EVs and their adoption. Investigating multiple dimensions and employing a mixed-method approach, the study enhances the existing knowledge of consumer attitudes toward EVs in the unique context of Saudi Arabia’s sustainable mobility transition. Policymakers and industry stakeholders can utilize these findings to expedite the shift to sustainable transportation in the Kingdom. This research also guides future investigations in this burgeoning field.