Psychological capital is recognized as a positive and unique factor that plays a crucial role in human resource development and performance management. It has the potential to increase employees’ efforts towards achieving organizational goals and improving their entrepreneurial strategy skills. The objective of this study was to examine the contribution of psychological capital in enhancing the entrepreneurial strategy skills of employees in Saudi universities. The study employed a descriptive approach, specifically utilizing the survey study method. The study sample was intentionally selected from different categories within the study population. Data was collected from 530 participants using two questionnaires. The findings revealed that employees exhibited an average level of psychological capital, while their practice of entrepreneurial strategy skills was rated as poor. The study also demonstrated that psychological capital significantly contributes to enhancing employees’ entrepreneurial strategy skills. Furthermore, statistically significant differences were observed in the psychological capital of employees across certain variables, such as personal and functional aspects. The average level of psychological capital among employees indicates the need for further development in this area. By focusing on enhancing psychological capital, organizations can effectively improve the entrepreneurial strategy skills of their employees. It is clear that investing in the psychological capital of employees can lead to significant improvements in their entrepreneurial strategy skills. This highlights the potential for organizations to foster a more entrepreneurial mindset and approach among their staff members. Additionally, the study’s findings underscore the need to tailor interventions and development programs to address specific aspects of psychological capital that may vary across different employees. Overall, the study emphasizes that psychological capital is a valuable resource that should be nurtured and developed within the organizational context. By doing so, organizations can not only enhance the entrepreneurial strategy skills of their employees but also cultivate a more resilient, motivated, and engaged workforce. This has the potential to contribute to the overall success and innovation of Saudi universities and similar institutions.

Since 2019, major travel destinations worldwide have issued travel-related restrictions against COVID-19. There is much research on tourism, but few studies have been conducted to explain the relevance of revisiting intention from the perspective of the epidemic or the dramaturgical theory. The purpose of the research is to explore the impact of customer experience on revisit intention during the period of COVID-19 slowdown by using dramaturgical theory. This study used a survey methodology, and the questionnaire was distributed on an online questionnaire platform. The URL of the questionnaire was published on social media (such as Facebook and LINE) to collect data from 389 samples of people who have foreign travel experience. The data was analyzed by employing partial least square structural equation model (PLS-SEM) methodology with the help of the statistical software “SmartPLS”. The research findings are as follows: 1) setting, audience, and performance are the three important elements of dramaturgical theory that impact the experience quality; 2) customer experience of tourists has a significant impact on the experience quality; 3) experience quality has a significant positive impact on the experience value and relationship quality; 4) experience value and relationship quality are important predictors of revisit intention. This study provides academic implications regarding the use of dramaturgical theory in relation to customer experience and relationship constructs in the context of tourism. Furthermore, it also provides some practical implications to tourism practitioners and managers, which would assist tourism industries in developing successful marketing strategies for the possible recovery of COVID-19.

Islamabad’s 2019 ban on single-use plastic shopping bags aimed to reduce plastic waste, but compliance is limited. This study evaluates the effectiveness of the ban as well as other factors in curtailing plastic bag use in Islamabad. Regression modeling within a rational choice framework analyzed survey data from 406 retailers across 18 selected urban and rural markets. We found that the subjective belief that a fine was unlikely (β = −16.10; t = −3.90; p < 0.001), likely (β = −24.99; t = −4.95; p < 0.001), or very likely (β = −43.84; t = −4.07; p < 0.001) for selling bags versus very unlikely was significantly associated with lower usage. Additionally, older retailer age (β = −0.25; p < 0.001) and more education (β = −0.77; p < 0.01) were associated with lower plastic bag usage. Business registration (β = −3.94; p < 0.10) and trade membership (β = −4.04; p < 0.05) also decreased use. Rural location (zone II: β = 13.28; p < 0.001) and plastic bags stock availability (β = 16.75; p < 0.001) increased use. Awareness, viewing bags as “Good”, unlikely fines and lack of substitutes lowered use. Results provide insights to inform more effective policies for reducing plastic waste.

The government’s increased cigarette tariff aims to lower smoking rates and avoid adverse impacts. This study’s goal was to offer process innovation for lowering Asian’ smoking behavior. The participants were chosen by stratified random selection from a total of 738 people residing in Pathum Thani Province, Thailand. The instrument was a questionnaire. A software programmer was used to examine descriptive and inferential statistics using EFA and one-way ANOVA techniques. A strategic framework guideline using a SWOT analysis and TOWS matrix to encourage smoking reduction was proposed. The findings revealed two components: smoking behavior change and continues smoking that were based on SWOT analysis and TOWs matrix. There were nine strategies for the excise department to consider for the adjustment of the next policy in terms of reducing the number of smokers. The practical and policy suggestions could help reduce the negative impact of the cigarette industry on public health and increase government revenue while addressing weaknesses and threats in the industry.

This paper proposes to apply a microfluidic chip combining DSC, DTA, and PCR-like functions for studying synthesis and selection of precursors of the genetic code carriers at hydrothermal conditions including those in natural high frequency fields (such as magnetosphere emission, atmospherics, auroras and lightings).

Abrupt changes in environmental temperature, wind and humidity can lead to great threats to human life safety. The Gansu marathon disaster of China highlights the importance of early warning of hypothermia from extremely low apparent temperature (AT). Here a deep convolutional neural network model together with a statistical downscaling framework is developed to forecast environmental factors for 1 to 12 h in advance to evaluate the effectiveness of deep learning for AT prediction at 1 km resolution. The experiments use data for temperature, wind speed and relative humidity in ERA-5 and the results show that the developed deep learning model can predict the upcoming extreme low temperature AT event in the Gansu marathon region several hours in advance with better accuracy than climatological and persistence forecasting methods. The hypothermia time estimated by the deep learning method with a heat loss model agrees well with the observed estimation at 3-hour lead. Therefore, the developed deep learning forecasting method is effective for short-term AT prediction and hypothermia warnings at local areas.