Catfish (Pangasianodon hypothalamus) are known in Asia, specifically in Southeast Asia. Currently, this fish has been exported to almost all countries in the world. This research aimed to examine the existing conditions of the solid waste produced, analyze the chemical composition of the waste, and look for alternatives for the policy and economical use of waste in the catfish processing business. Using the survey method, data were gathered through measurement at the research location and laboratory, interviews with business owners, and field observations. Proximate analysis was conducted on pink slime meat, belly fat, bones, and fish innards. Analysis of acid number, saponification number, iodine number, and fat fatty acid was carried out on stomach fat. Meanwhile, amino acid analysis was carried out for pink slime meat. Handling catfish industrial waste has yet to be carried out properly, which causes a foul smell and disturbs the environment. The catfish industry waste’s chemical content (protein, fat, water content, carbohydrates, and fatty acids) (pink slime meat, belly fat, fish bones, and innards) is still relatively applicable. The study processed fish waste into products like instant porridge, analogous fish sago rice, and fish sago noodles. The proximate analysis results of these products show figures that exceed the minimum standards for similar products.

Intellectual capital is one of the most crucial determinants of long-term economic development. The countries compete for highly skilled labor and talented youth. State regulatory interventions aim to, on the one hand, facilitate the retention of foreign high-productivity intellectual capital in the host country, transforming ‘educational’ and ‘scientific’ migrants into residents, and on the other hand, prevent the outflow of their own qualified workforce. The paper aims to outline the role of the nation’s higher education system in the influx and outflow of labor resources. A two-stage approach is applied: 1) maximum likelihood—to cluster the EU countries and the potential candidates to become members of EU countries based on the integrated competitiveness of their higher education systems, considering quantitative, qualitative, and internationalization aspects; 2) logit and probit models—to estimate the likelihood of net migration flow surpassing baseline cluster levels and the probability of migration intensity changes for each cluster. Empirical findings allow the identification of four country clusters. Forecasts indicate the highest likelihood of increased net migration flow in the second cluster (66.7%) and a significant likelihood in the third cluster (23.4%). However, the likelihood of such an increase is statistically insignificant for countries in the first and fourth clusters. The conclusions emphasize the need for regulatory interventions that enhance higher education quality, ensure equal access for migrants, foster population literacy, and facilitate lifelong learning. Such measures are imperative to safeguard the nation’s intellectual potential and deter labor emigration.

Cyber-physical Systems (CPS) have revolutionized urban transportation worldwide, but their implementation in developing countries faces significant challenges, including infrastructure modernization, resource constraints, and varying internet accessibility. This paper proposes a methodological framework for optimizing the implementation of Cyber-Physical Urban Mobility Systems (CPUMS) tailored to improve the quality of life in developing countries. Central to this framework is the Dependency Structure Matrix (DSM) approach, augmented with advanced artificial intelligence techniques. The DSM facilitates the visualization and integration of CPUMS components, while statistical and multivariate analysis tool such as Principal Component Analysis (PCA) and artificial intelligence methods such as K-means clustering enhance complex system the analysis and optimization of complex system decisions. These techniques enable engineers and urban planners to design modular and integrated CPUMS components that are crucial for efficient, and sustainable urban mobility solutions. The interdisciplinary approach addresses local challenges and streamlines the design process, fostering economic development and technological innovation. Using DSM and advanced artificial intelligence, this research aims to optimize CPS-based urban mobility solutions, by identifying critical outliers for targeted management and system optimization.

This article is devoted to studying the principles of the relationship between democracy and demoethics as tools for transforming the sustainable development of society. The study is based on the assumption that the effective functioning of democracy is associated with such social phenomena as elections and electoral behavior. The study examined electoral behavior and surveyed members of society about the qualities of candidates to which they pay special attention. An analysis of qualitative and quantitative data demonstrating the democratic foundations of elections of members of society was conducted, and an analysis of the choice of voters in the extraordinary elections of the President of the Republic of Kazakhstan by region was conducted. In this study, Bayesian network modeling is experimentally applied to formalize the problem of identifying and analyzing the behavior of virtuous personality traits. A sociological survey of public opinion was conducted using the questionnaire method with the participation of 826 people from all regions of Kazakhstan from May to June 2023. A questionnaire was used to collect data, the main purpose of which was to compare attitudes and find out what values are considered important for people, what norms of behavior are considered acceptable, and to understand what values and norms prevail in society. It is concluded that the concept of demoethics promotes a positive transformation of humanity and helps to form a new leader of virtue, a ruler of the city, capable of making ethical rational decisions that can ensure a balance between the economic, social, and environmental needs of humanity.

With the popularity of smartphones, consumers’ daily lives and consumption patterns have been changed by using multi-functional apps. Convenience store operators have developed membership apps as a platform to promote their brands to consumers to create the benefits of “membership economy”. This study examined consumer behavior towards convenience store membership apps using UTAUT2. Consumers who have installed the convenience store membership apps were recruited as the target population. SPSS 23.0 was used to conduct item analysis and reliability analysis in the pretest questionnaires. The formal questionnaires were distributed online by convenience sampling method, with 375 valid questionnaires collected. Smart PLS 3.0 was conducted by analyzing the confirmatory factor analysis and structural equation model analysis. The results of the study, “performance expectancy”, “social influence”, “price value” and “habit” of convenience store member app users showed positive and significant effects on “behavioral intention”. “Facilitating conditions”, “habit” and “behavioral intention” have positive and significant effects on “actual use behavior”. “Gender” affects “habit” to have a significant moderating effect on “use behavior”. “Use experience” affects “habit” to have a significant moderating effect on “behavioral intention”. Based on the study results, the further suggestions of marketing management implications and feasible recommendations are proposed for convenience store operators to refer to in the implementation of membership app marketing management.

From the perspective of the corporate life cycle, this study investigates the transmission mechanism of ‘technological innovation-financing constraints-carbon emission reduction’ in energy companies using panel data and mediating models, focusing on listed energy companies from 2014 to 2020. It explores the stage characteristics of this mechanism during different life cycle phases and conducts heterogeneity tests across industries and regions. The results reveal that technological innovation positively influences carbon emission reduction in energy enterprises, demonstrating significant life cycle stage characteristics, specifically more pronounced in mature companies than in growing or declining companies. Financing constraints play a mediating role between technological innovation and carbon reduction, but this is only effective during the growth and maturity stages. Further research shows that the impact of technological innovation on carbon emission reduction and the mediating role of financing constraints exhibit heterogeneity across different stages of the life cycle, industries, and regions. The conclusions of this paper provide references for energy companies in planning rational emission reduction strategies and for government departments in policy-making.