As the population’s demand for food continues to increase, aquaculture is positioned as a productive activity that provides high-quality protein. Aquaculture activity is characterized by its socio-economic impact, the generation of jobs, its contribution to food, and constant growth worldwide. However, in the face of threats of competition, producers must quickly adapt to market needs and innovate. Given this, this research aims to analyze the impact of the knowledge absorption capacity with the adoption of innovations by aquaculture producers in the Mezquital Valley in Hidalgo, Mexico. The methodological strategy was carried out through structural equation modeling using partial least squares and correlation tests. The findings show that knowledge absorption capacities explain 77.8% of the innovations carried out in aquaculture farms. Both variables maintain a medium-high correlation; the more significant the absorption capacity, the greater the innovation.

This research investigates the relationship between the variables of public service reform (PSR) and bureaucratic revitalization and the relationship between digital leadership (DL) and bureaucratic revitalization. The research method used in this research is quantitative survey research which aims to determine the relationship between two or more variables. The research method for this research is quantitative associative, the population of this study is senior immigration officers. The data analysis method uses structural equation modeling (SEM) partial least squares (PLS), the respondents for this study were 634 senior immigration office employees who were determined using the simple random sampling method—non probability sampling, the questionnaire was designed to contain statement items using a 7 point Likert scale. A closed questionnaire is a list of questions or statements that are equipped with multiple answer choices expressed in scale form. The Likert scale used in this research is (1) strongly disagree, (2) disagree, (3) quite disagree, (4) neutral, (5) quite agree, (6) agree, (7) strongly agree. Data processing in this research used SmartPLS software. The independent variables of this research are digital leadership and public service reform and the dependent variable is bureaucratic revitalization. The stages of data analysis in this research are the outer model test which includes convergent validity, discriminant validity and composite reliability as well as inner model analysis, namely hypothesis testing. The results of this research show that public service reform has a positive and significant relationship to bureaucratic revitalization and digital leadership has a positive and significant relationship to bureaucratic revitalization. This research implies that leaders focus on engaging, using, and handling the uncertainty of emerging technologies, digital tools, and data, leaders to support bureaucratic revitalization, the immigration department must implement digital leadership, immigration leaders should encourage the use of digital platforms in their organizations, support and facilitate digital transformation. The immigration department should increase the revitalization of the bureaucracy, the immigration department should carry out public service reforms. Public services are to be good if they fulfill several principles of public interest, legal certainty, equal rights, balance of rights and obligations, professionalism, participativeness, equality of treatment/non-discrimination, openness, accountability, facilities and special treatment for vulnerable groups, timeliness, speed, convenience and affordability.

The United Nations General Assembly declared 2023 the “International Year of Millets” in order to promote millet cultivation, consumption, and conservation. Millets play an important role in food security, livelihoods, and biodiversity. Despite its numerous benefits, millet cultivation and consumption in Uttarakhand have declined due to a variety of constraints. This paper examines the effects of regiocentrism and materialism on intention towards Uttarakhand’s regional food products (millets). It employs PLS-SEM to investigate relationships between latent variables and generate results on a sample of 460 participants. This study elucidates the intricate interplay between materialism, regiocentrism, and intention towards regional food products in the Himalayan region, enriching the theory of planned behavior (TPB) with a nuanced understanding of personal values and regional identity. It reveals materialism’s positive association with attitudes towards regional food products, suggesting materialistic individuals may view these products as status symbols, thus affecting behavioral intentions. Additionally, the research highlights regiocentrism’s dual influence—enhancing attitudes yet deterring purchase intentions—underscoring the complexity of regional pride in consumer decision-making. These findings advance TPB by integrating broader value systems and cultural context, offering significant theoretical and practical insights for promoting sustainable consumption patterns.

A logistics service company in Batam faces challenges related to warehouse load fulfillment and sorting inaccuracies. This study aims to identify proposed efficiency improvements to the goods distribution system using the cross-docking method. The research method chosen is cross-docking, a technique that eliminates the storage process in the warehouse, thus saving time and cost. The research findings show significant benefits, especially in achieving zero inventory efficiency. Data processing and discussion revealed that efficiencies were apparent by increasing the sorting tables from 1 to 6, with an output of 90,000 kg during aircraft loading and unloading (compared to approximately 77,000 kilograms). This efficiency arises from the larger output of the sorting tables compared to the input, eliminating the need for warehousing and adding ten trucks. As a result, the shipment can be completed in one trip, with no goods stored in the warehouse. The analysis shows that implementing cross-docking in the company increases efficiency in distributing goods to forwarding partners.

This work aimed to evaluate the effects of using three different substrates in the semi-hydroponic culture of lettuce (Lactuca sativa L.) using two different nutrient solutions. A first trial was performed with a nutrient solution rich in macronutrients and micronutrients suitable for lettuce culture, and a second trial with a nutrient solution with pretreated wastewater from effluents of a cheese factory. The experimental design was in randomized blocks with three repetitions and three substrates were used: perlite, coconut fiber, and expanded clay, in both trials. The following parameters were observed: number of leaves, diameter of the cabbage, fresh and dry weight of the aerial part, chlorophyll index and mineral composition of the lettuce. For the first trial, the highest result for the number of leaves (20 leaves), fresh weight (142.0 g) and dry weight (7.2 g) of the aerial part was obtained in the plants growing on perlite. In the second trial, the highest result for the number of leaves (28 leaves), diameter of cabbage (26.7 cm), fresh weight (118.8 g) and dry weight (9.5 g) of the aerial part were achieved by the plants that were grown in coconut fiber. The nutrient solutions were analyzed after each irrigation cycle to verify the possibility of their discharge into the environment. Several parameters were analyzed: pH, conductivity, redox potential, nitrates, nitrites, ammoniacal nitrogen, chlorides, hardness, calcium, phosphates, sodium, potassium, chemical oxygen demand (COD) and magnesium. Ammoniacal nitrogen was found to be the only nutrient that can limits the discharge of nutrient solutions into the environment. It was also proven that the plants, besides obtaining the nutrients necessary for their development in the semi-hydroponic system with the nutrient solution with pre-treated residual water, also functioned as a purification system, allowing the said nutrient solution to be discharged into the environment at the end of each cycle.

The cars industry has undergone significant technological advancements, with data analytics and artificial intelligence (AI) reshaping its operations. This study aims to examine the revolutionary influence of artificial intelligence and data analytics on the cars sector, particularly in terms of supporting sustainable business practices and enhancing profitability. Technology-organization-environment model and the triple bottom line technique were both used in this study to estimate the influence of technological factors, organizational factors, and environmental factors on social, environmental (planet), and economic. The data for this research was collected through a structured questionnaire containing closed questions. A total of 327 participants responded to the questionnaire from different professionals in the cars sector. The study was conducted in the cars industry, where the problem of the study revolved around addressing artificial intelligence in its various aspects and how it can affect sustainable business practices and firms’ profitability. The study highlights that the cars industry sector can be transformed significantly by using AI and data analytics within the TOE framework and with a focus on triple bottom line (TBL) outputs. However, in order to fully benefit from these advantages, new technologies need to be implemented while maintaining moral and legal standards and continuously developing them. This approach has the potential to guide the cars industry towards a future that is environmentally friendly, economically feasible, and socially responsible. The paper’s primary contribution is to assist professionals in the industry in strategically utilizing Artificial Intelligence and data analytics to advance and transform the industry.