Purpose: This study aims to identify the primary determinants of consumer behavior influencing customer satisfaction in the context of online mobile application (App) purchases of perishable products. Utilizing the well-established SERVQUAL (Service Quality) model, which has been extensively studied in various service-oriented settings, the research seeks to determine the factors with the greatest impact on customer satisfaction during online transactions of perishable products. Design: The investigation focuses on analyzing the five core dimensions of the SERVQUAL model: tangibles, reliability, responsiveness, assurance, and empathy. The study employs a survey methodology administered through Google Forms, targeting the population residing in the Klang Valley of Malaysia. A total of 400 samples were successfully collected using a snowball sampling technique. Methodology: The study employs the SERVQUAL model as the theoretical framework to examine the dimensions of tangibles, reliability, responsiveness, assurance, and empathy. The survey, conducted through Google Forms, targeted the population in the Klang Valley of Malaysia, with a sample size of 400 collected through snowball sampling. Findings: The study’s outcomes reveal the robust predictive capability of the overarching SERVQUAL model in the realm of online perishable product procurement. Notably, the assurance dimension emerges as the most influential factor, emphasizing its pivotal role in shaping and defining customer satisfaction for online retailers of perishable goods in the Malaysian market. Novelty: This research contributes to the understanding of consumer behavior in online perishable product purchases, by identifying determinants of consumer behavior; the study promotes sustainable production and responsible consumption within the perishable products category, offering insights beneficial for online retailers in the Malaysian market. This study aligns with United Nations sustainable development goals especially industry innovation, food security and responsible consumption.

India has experienced notable advancements in trade liberalization, innovation tactics, urbanization, financial expansion, and sophisticated economic development. Researchers are focusing more on how much energy consumption of both renewable and non-renewable accounts for overall system energy consumption in light of these dynamics. In order to gain an understanding of this important and contentious issue, we aim to examine the impact of trade openness, inventions, urbanization, financial expansion, economic development, and carbon emissions affected the usage of renewable and non-renewable energy (REU and N-REU) in India between 1980 and 2020. We apply the econometric approach involving unit root tests, FE-OLS, D-OLS, and FM-OLS, and a new Quantile Regression approach (QR). The empirical results demonstrate that trade openness, urbanization and CO₂ emissions are statistically significant and negatively linked with renewable energy utilization. In contrast, technological innovations, financial development, and economic development in India have become a source of increase in renewable energy utilization. Technological innovations were considered negatively and statistically significant in connection with non-renewable energy utilization, whereas the trade, urbanization, financial growth, economic growth, and carbon emissions have been established that positively and statistically significant influence non-renewable energy utilization. The empirical results of this study offer some policy recommendations. For instance, as financial markets are the primary drivers of economic growth and the renewable energy sector in India, they should be supported in order to reduce CO₂ emissions.

As the second most polluting industry in the world, the fashion industry has a critical impact on the environment. The development of sustainable fashion is conducive to reducing the environmental pollution caused by the fashion industry. China has the largest consumer market in the world, and the Chinese government and major companies have made considerable contributions to the sustainable development of the fashion industry. However, research regarding young women’s attitudes towards this topic remains under-explored. This study interviewed 30 young women of different ages from different places in China. Based on the theory of planned behavior (TPB), a semi-structured interview was used as a data collection method, and thematic analysis was adopted for data analysis. This paper discusses young Chinese female consumers’ attitudes towards sustainable fashion and analyzes the motivating factors and hindrance factors affecting the consumption intentions of young Chinese female consumers towards sustainable fashion. The research found that young Chinese female consumers generally hold a positive and supportive attitude towards sustainable fashion. Consumers’ perceptions of sustainable fashion, their self-perceptions, and their level of green awareness all significantly impact their attitudes and purchase intentions toward sustainable fashion. Consumers feel low social pressure, and Chinese society demonstrates a high level of acceptance and praise for sustainable concepts. However, the lack of purchasing channels and choices for sustainable fashion in China and the high cost of sustainable fashion products discourage consumers from making purchases. This study will be beneficial as a reference when the Chinese government makes sustainable policies to guide consumers toward sustainable fashion consumption. This study helps enterprises select target markets in China and formulate sustainable fashion marketing strategies and targeted advertising. This study contributes to increasing consumer awareness of sustainable fashion, as well as providing reference and reflective value when consumers purchase sustainable fashion products. Finally, this study will help promote the development process of sustainable fashion in Chinese society, make contributions to reducing the waste of social resources, promoting the recycling of resources, and improving social conditions, and put forward specific solutions and feasible suggestions for the development of sustainable fashion in Chinese society.

Global energy agencies and commissions report a sharp increase in energy demand based on commercial, industrial, and residential activities. At this point, we need energy-efficient and high-performance systems to maintain a sustainable environment. More than 30% of the generated electricity has been consumed by HVAC-R units, and heat exchangers are the main components affecting the overall performance. This study combines experimental measurements, numerical investigations, and ANN-aided optimization studies to determine the optimal operating conditions of an industrial shell and tube heat exchanger system. The cold/hot stream temperature level is varied between 10 ℃ and 50 ℃ during the experiments and numerical investigations. Furthermore, the flow rates are altered in a range of 50–500 L/h to investigate the thermal and hydraulic performance under laminar and turbulent regime conditions. The experimental and numerical results indicate that U-tube bundles dominantly affect the total pumping power; therefore, the energy consumption experienced at the cold side is about ten times greater the one at the hot side. Once the required data sets are gathered via the experiments and numerical investigations, ANN-aided stochastic optimization algorithms detected the C10H50 scenario as the optimal operating case when the cold and hot stream flow rates are at 100 L/h and 500 L/h, respectively.

Soil erosion is characterized by the wearing away or loss of the uppermost layer of soil, driven by water, wind, and human activities. This process constitutes a significant environmental issue, with adverse effects on water quality, soil health, and the overall stability of ecosystems across the globe. This study focuses on the Anuppur district of Madhya Pradesh, India, employing the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS) tools to estimate and spatially analyze soil erosion and fertility risk. The various factors of the model, like rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), conservation practices (P), and cover management factor (C), have been computed to measure annual soil loss in the district. Each factor was derived using geospatial datasets, including rainfall records, soil characteristics, a Digital Elevation Model (DEM), land use/land cover (LULC) data, and information on conservation practices. GIS methods are used to map the geographical variation of soil erosion, providing important information on the area's most susceptible to erosion. The outcome of the study reveals that 3371.23 km2, which constitutes 91% of the district's total area, is identified as having mild soil erosion; in contrast, 154 km2, or 4%, is classified as moderate soil erosion, while 92 km2, representing 2.5%, falls under the high soil erosion category. Additionally, 50 km2, or 1.35%, is categorized as very high soil erosion and around 30 km2 of the study area is classified as experiencing severe soil erosion. The analysis further discovers that the annual soil loss in the district varies between 0 and 151 tons per hectare per year. This study indicates that most of the district is classified under low soil erosion; only a tiny fraction of the area is categorized as experiencing high and very high soil erosion. The study provides significant insights into soil erosion for policymakers and human society to bring their attention to the need for sustainable soil conservation practices in the undulating terrain/topography and agriculturally dominated district of Anuppur.

In recent years, China’s economy has undergone rapid development. Increased disposable income and the rapid expansion of Internet-based financial services have positioned China as the largest market for luxury goods. Gen Z, the youngest demographic within emerging markets, is expected to play a pivotal role as the primary driver of the luxury market. However, while China’s luxury market continues to exhibit a high growth rate, this growth has gradually decelerated in comparison to the previous two years according to researchers. This presents a significant challenge for the luxury industry, as maintaining and enhancing the global growth trend has become a pressing concern where consumer behavior is concerned. The second key issue addressed in this study revolves around the concepts of compulsive buying and brand addiction, which can lead individuals, particularly Gen Z, to develop an addiction to luxury consumption. This study is based on an integrated model of conspicuous consumption, social comparison, and impression management theory. The key variables are materialism, brand consciousness, status-seeking, peer pressure, and collectivism to predict the luxury consumption model with debt attitude introduced as a moderating variable to study consumer behaviour in this age group. A non-probability sampling method and 480 people were selected as research samples. Quantitative analysis was used in this study, and SPSS and Smart PLS were used as data analysis tools. Structural equation model (SEM) using partial least squares method was used to determine the relationship of the variables and the moderating effect of debt attitude. The results showed that brand consciousness, status seeking, debt attitude and materialism had the strongest relationship with luxury consumption. Debt attitude as a moderating factor has a significant impact on the hypothesized relationship of the model. This paper provides empirical evidence for research on Gen Z’s luxury consumption, which has practical implications to marketers, luxury companies, local luxury brands and credit institutions.