This research explores the critical influence of corporate culture on small and medium-sized enterprises’ (SMEs) crisis response abilities under varied cross-cultural environments. Amid the disruptive backdrop of the COVID-19 pandemic, SMEs globally have faced unprecedented challenges. This study addresses a gap in the existing literature by conducting a cross-cultural analysis of SMEs in China, Thailand, and Germany to understand how corporate culture affects crisis management. Utilizing a competitive cultural value model, the research categorizes corporate culture into four dimensions: group culture, development culture, hierarchy culture, and rational culture. These cultural dimensions are investigated in relation to their impact on crisis response abilities. Additionally, national cultural dimensions such as individualism and uncertainty avoidance are examined as moderating variables. The findings reveal that group and development cultures positively influence crisis response abilities, enhancing organizational resilience and adaptability. Conversely, hierarchy culture negatively affects crisis management, hindering flexible response strategies. Rational culture supports structured crisis response through goal-oriented practices. National culture significantly moderates these relationships, with individualism and high uncertainty avoidance impacting the effectiveness of organizational cultural dimensions in crisis scenarios. This study offers theoretical advancements by integrating cultural dimensions with crisis response strategies and provides practical implications for SMEs striving to enhance their resilience and adaptability in a globalized business environment.

For this, the primary aim of this study was to analyze of the impact of cultural accessibility and ICT (information and communication technology) infrastructure on economic growth in Kazakhstan, employing regression models to asses a single country data from 2008 to 2022. The research focuses on two sets of variables: cultural development variables (e.g., number of theaters, museums, and others) and ICT infrastructure variables (e.g., number of fixed Internet subscribers, total costs of ICT, and others). Principal component analysis (PCA) as employed to reduce the dimensionality of the data and identify the most significant predictors for the regression models. The findings indicate that in the cultural development model (Model 1), the number of recreational parks and students are significant positive predictors of GDP per capita. In the ICT infrastructure model (Model 2), ICT costs are found to have a significant positive impact on GDP per capita. Conversely, traditional connectivity indicators, such as the number of fixed telephone lines, show a low dependence on economic growth, suggesting diminishing returns on investment in these outdated forms of ICT. These results suggest that investments in cultural and ICT infrastructure are crucial for economic development. The study provides valuable insights for policymakers, emphasizing the need for quality improvements in education and strategic modernization of communication technologies.

The rising trend of tourists selecting agrotourism as a tourist destination has become an intriguing study issue. Seremban is a well-known tourist attraction that is popular among visitors. As a result, Seremban has been selected as the study site. However, river pollution may have an influence on Seremban’s natural environment and agrotourism potential. Furthermore, inadequate infrastructure, such as unauthorized parking, exacerbated the inhabitants’ problems. A growing number of young people leave Seremban to pursue employment or further education in other cities, with no desire to work as farmers. The labor scarcity has also made it difficult for farmers to grow their farms. Consequently, the study aims to examine how factors such as the natural environment, tourist infrastructure, perceived social advantages, and perceived barriers influence the attitudes of Seremban residents towards agrotourism, with a focus on its potential for driving economic growth. This study adopts quantitative research methods, employing descriptive and causal research designs. Primary data collection is conducted through questionnaires, supplemented by secondary data. Non-probability quota sampling is utilized due to the absence of a specific sampling frame, with a sample size of 385 respondents determined using G*Power software. Constructs are developed based on previous research, and the questionnaire comprises Likert-scale items to gauge attitudes and perceptions. A pilot study assesses the instrument’s reliability. Data analysis is performed using SPSS software, encompassing multiple linear regression and Pearson correlation analyses in addition to descriptive statistics. The findings provide valuable insights into the factors driving residents’ perceptions of agrotourism in Seremban, emphasizing the importance of the natural environment, tourism infrastructure, perceived social benefits, and perceived barriers in shaping attitudes. Additionally, the study highlights the resilience of residents’ positive attitudes toward agrotourism, despite potential challenges and barriers identified. Overall, these results offer implications for policymakers and stakeholders involved in tourism development in the region.