In the realm of evolving e-commerce sales channels, the e-commerce sale of agricultural products has become a vital avenue for cherry farmers. However, a notable discrepancy exists between the intentions and actual behaviors of cherry farmers regarding e-commerce participation. In this study, binary logistic regression and interpretive structural model were used, and the cherry producing area of Yantai City, Shandong Province, China, was taken as the study area, and a total of 501 actual valid questionnaires were returned, and the validity rate of the questionnaires was 95.1 per cent. The results of the study show that the deviation of cherry farmers’ willingness and behavior is mainly affected by age, frequency of online shopping, whether to participate in e-commerce training, and whether to join a cooperative in farmers’ individual characteristics, revenue expectations and profit expectations in behavioral attitudes, government publicity and neighborhood effects in subjective norms, e-commerce use in perceived behavioral attitudes, the number of agricultural population in household resource endowment and logistics costs and e-commerce training in external scenarios Impact. On this basis, the 11 influencing factors are analyzed in depth and three transmission paths are analyzed. The study further proposes recommendations to enhance the translation of cherry farmers’ e-commerce intentions into action, such as bolstering e-commerce promotion, increasing the frequency of training, improving supporting infrastructure, and reducing logistics costs.

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.

Surveys are one of the most important tasks to be executed to get valued information. One of the main problems is how the data about many different persons can be processed to give good information about their environment. Modelling environments through Artificial Neural Networks (ANNs) is highly common because ANN’s are excellent to model predictable environments using a set of data. ANN’s are good in dealing with sets of data with some noise, but they are fundamentally surjective mathematical functions, and they aren’t able to give different results for the same input. So, if an ANN is trained using data where samples with the same input configuration has different outputs, which can be the case of survey data, it can be a major problem for the success of modelling the environment. The environment used to demonstrate the study is a strategic environment that is used to predict the impact of the applied strategies to an organization financial result, but the conclusions are not limited to this type of environment. Therefore, is necessary to adjust, eliminate invalid and inconsistent data. This permits one to maximize the probability of success and precision in modeling the desired environment. This study demonstrates, describes and evaluates each step of a process to prepare data for use, to improve the performance and precision of the ANNs used to obtain the model. This is, to improve the model quality. As a result of the studied process, it is possible to see a significant improvement both in the possibility of building a model as in its accuracy.

Purpose: The paper aims to study the methodology and functional of Internal Audit (IA) during the transition to remote working methods necessitated by the COVID-19 pandemic crisis period. Design/methodology/approach: Data are collected over a sample of 352 internal audit departments in retail SMEs distributed in the Gulf Cooperation Council (GCC) region. The six variables are measured using a reflective model. An exploratory factor analysis is applied to gauge the measurement model’s validity and reliability. Findings: The research findings revealed that internal auditing within the Kingdom of Saudi Arabia (KSA) and the Qatari retail sector is not sufficiently advanced. The focus of internal auditing primarily revolves around compliance audits rather than performance audits, thereby limiting their degree of agility and strategy which negatively affects the IA methodology. Conversely, for the United Arab Emirates (UAE) retail companies the research hypotheses were validated showing an IA functions evolution, an IA reassurance and IA agility that are conducted throughout a remote working and a strategic design that affect positively IA working methodology. Originality: The originality impregnates by the fact that reviews of traditional audit working methods were updated and shaped according to the deficiencies that couldn’t be identified during a pre COVID-19 period. A traditional audit plan may not work in this situation. The originality of the study consists of estimating IA methodological review through an agile approach that provides internal reassurance and risk attenuation.

This study conducts a comprehensive analysis of the aquaculture industry across 11 coastal regions in eastern China from 2017 to 2021 to assess their adaptability and resilience in the face of climate change. Cluster analysis was employed to examine regional variations in aquaculture adaptation by analyzing data on annual average temperatures, annual extreme high/low temperatures, annual average relative humidity, annual sunshine duration, and total yearly precipitation alongside various aquaculture practices. The findings reveal that southern regions, such as Fujian and Guangdong, demonstrate higher adaptability and resilience due to their stable subtropical climates and advanced aquaculture technologies. In contrast, northern regions like Liaoning and Shandong, characterized by more significant climatic fluctuations, exhibit varying degrees of cluster changes, indicating a continuous need to adjust aquaculture strategies to cope with climatic challenges. Additionally, the study explores the specific impacts of climate change on species selection, disease management, and water resource utilization in aquaculture, emphasizing the importance of developing region-specific strategies. Based on these insights, several strategic recommendations are proposed, including promoting species diversification, enhancing disease monitoring and control, improving water quality management techniques, and urging governmental support for policies and technical guidance to enhance the climate resilience and sustainability of the aquaculture sector. These strategies and recommendations aim to assist the aquaculture industry in addressing future climate challenges and fostering long-term sustainable development.

This study examines the impact of digitally curated museum exhibitions on visitor behavior, with a particular focus on university students from China and Hungary (n = 308). Using PLS-SEM analysis, the research finds that visitors’ experiences during digital curation visits significantly influence their behavior, and this influence is mediated by perceived value and satisfaction. It is recommended that museums consider the following constructive considerations to facilitate their future development: expanding the application of digital curation, utilizing cutting-edge technologies, implementing data-driven curatorial optimization, enhancing social experiences, integrating education and entertainment, and promoting cultural preservation and environmental stewardship. These insights will help guide museums toward more engaging and sustainable experiences.

 Landscape architects, who guide planning and design decisions by understanding the socio-cultural expectations, functional needs, and social behaviors of the community, create ideal spaces for people by integrating natural, social, cultural, and aesthetic factors with a holistic design approach in urban public areas. Public open green spaces are important urban areas that have a positive impact on people’s physical, mental, and emotional health. In this context, the concept of personal space, its impact on individuals, and related perception studies have been examined. In landscape design, criteria that affect individuals’ personal space distances and personal space perceptions have been identified, providing a basis for sustainable landscape design projects in public open and green spaces.

In the era of rapid technological development, the integration of technology in education has become crucial (Hashim et al., 2022). The digital transformation of education requires universities to transform their traditional operational models, strategic directions, and teaching practices, re-examine their own value propositions, and promote high-quality innovative development in universities. Transformation and change bring challenges to organizational management, especially leadership. Can digital leadership positively influence the innovative behavior of university teachers? Can digital leadership improve organizational innovation performance by influencing innovation behavior? These questions urgently need to be answered through practical surveys of digital transformation in universities. From March 2024 to May 2022, we conducted a survey of 1142 participants from 12 universities in Kunming, southwestern China. Our research findings indicate that digital leadership has a positive impact on the innovation performance of university organizations; Innovation behavior plays a mediating role between digital leadership and organizational performance. These findings provide new insights into the potential mechanisms by which digital leadership influences organizational innovation in universities. The research findings emphasize that in the process of transforming traditional operational models, strategic directions, and teaching practices in higher education, in order to achieve high-quality innovative development, it is necessary to attach importance to digital leadership and continuously stimulate innovative behavior.