This study aims to scrutinize specific long-term sustainability industrial indicators in Thailand as a representative of an emerging economy. The study uses a Bloomberg database comprising all Thai listed companies on the Stock Exchange of Thailand from 2013 to 2023. The research employs a two-step Generalized Method of Moments (GMM) statistics to assess the enduring impact on industrial sustainability. These results provide consistent, significant and positive relationships between asset turnover and sales with all industrial sustainability. The results additionally reveal that some other factors may moderate industrial sustainability but reveal the GDP growth rate and institutional shareholders are less likely to be corporate sustainability to all indicators. The results provide insight into valuable guidance to management teams, financial statements’ users, investors and other stakeholders on designing effective operations and investment strategies to improve sustainability.

The Malaysian government's efforts to promote solar photovoltaic (PV) usage among households face a challenge due to its low adoption rate. This study delves into the factors influencing the exponential adoption of solar PV electricity generation among landed residential property owners in Malaysia. The research aims to comprehensively examine the predictors influencing the adoption of solar PV systems among Malaysian households. Hence, the study employs an enhanced Theory of Planned Behavior framework, integrating sustainable energy security dimensions such as availability, affordability, efficiency, acceptability, regulation, and governance. The sample comprised 556 Malaysian residents who owned and resided in the landed properties. The home locations where at least one solar PV installation existed within a residential street. Snowball sampling was employed through referrals, leveraging social and community networks. Collected data was analyzed using the partial least squares structural equation modeling. Attitude, affordability, and acceptability emerged as pivotal factors significantly impacting the intention to use solar PV systems among Malaysian households. This research not only enriches academic discourse but also offers practical implications for policymakers, guiding the formulation of targeted strategies to promote sustainable energy practices and facilitate the widespread adoption of solar PV systems in Malaysia.

This research study aims 1) to create a structural equation model for sports sponsorship of halal products in Thailand and 2) to examine the direct and indirect influence of variables that are components of the structural equation model for halal products, specifically in the context of becoming a sports sponsorship for halal products in Thailand. The study focused on a sample group of Thai Muslims interested in watching and following the news and participating in Thai sporting events. The researcher chose a sample size of 400 participants from this population, excluding backup data gathering and data analysis, to ensure the questionnaire’s quality and dependability. The results of the data analysis from the structural equation model created show that it is consistent with empirical data. The results of the statistical hypothesis test reveal that the level of religious adherence and the level of awareness of entering into sponsorship have both direct and indirect influences on consumer attitudes and purchase intentions with statistical significance at 0.01. It can also be identified that if a sponsor increases awareness among Muslim viewers through branding or product presentations in events that feature halal symbols or indicate compliance with religious standards, it will lead to a more positive attitude and higher purchase intentions. This insight can be applied to marketing promotion in administrative regions or countries where the majority of the population is Muslim.

This study explores how Jordanian telecom companies can balance Internet of Things (IoT) driven automation with maintaining genuine consumer-brand connections. It seeks strategies that blend IoT automation with personalized engagement to foster lasting consumer loyalty. Employing qualitative research via semi-structured interviews with IT and customer service managers from Jordanian telecom companies. IoT-driven automation in Jordan’s telecom sector revolutionizes consumer-brand relationships by enabling data-driven personalization. It emphasizes the importance of IoT proficiency, transformed marketing strategies, and the need to balance personalization with consumer privacy. Interviews stress the significance of maintaining authentic human connections amidst automation. Strategies for Jordanian telecom firms include integrating IoT data into CRM systems, employing omnichannel marketing, balancing automation with human interaction, adopting a consumer-centric approach, mitigating security risks, and leveraging IoT insights for adaptive services. These approaches prioritize consumer trust, personalized engagement, and agile service adaptation to meet dynamic consumer preferences. This research provides actionable strategies for telecom firms on effective IoT integration, emphasizing the need to maintain genuine consumer relationships alongside technological advancements. It highlights IoT’s transformative potential while ensuring lasting consumer loyalty and business success. Future research avenues could explore longitudinal studies and the interplay between AI and IoT in telecom services.

State support for agriculture is a crucial tool for adjusting the competitive advantages of agricultural producers to a volatile market environment. In countries with diverse natural conditions for agriculture, however, the allocation of subsidies often focuses on bridging spatial development gaps rather than maximizing the return on inputs. To improve the efficiency of resource use in agriculture, it is essential to tailor subsidy criteria to regional disparities in agricultural potential. Using the example of Russia’s 81 administrative regions, the authors have tested a five-stage methodology for determining the support-generated parameters of output, efficiency, impact, revenue, and profitability. This methodology takes into account both natural and economic factors that contribute to the competitive advantages of each region. The study aims to identify the parts of the performance indicators, such as gross agricultural output and revenue, that are influenced by the amount of subsidies in five different types of territories, which are categorized by the cadastral value of their farmland. It has been found that the allocation of subsidies is not entirely based on the return on the funds allocated. There is a discrepancy between the competitive advantages of these territories in agricultural production and the amount of funds they receive through government support programs. The efficiency of government support differs significantly depending on the type of agricultural product produced in each territory. The approach developed by the authors provides a tool that policy makers can use when tuning the allocation of subsidies based on the differences in the agricultural potential of each territory.