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The current study investigated the relationship between nostalgia, conspicuous consumption, and impulse buying and compared gender differences in the effects of nostalgia on conspicuous consumption and impulse buying.

A total of 307 college students in western Singapore were recruited. Confirmatory factor analysis and structural equation modeling were conducted to assess the psychometric properties of the scales and estimate model path coefficients. A multi-group analysis was conducted to test if the path coefficients in the research model varied across genders.

This study found that nostalgia had a positive influence on consumers’ conspicuous consumption, which in turn had a positive impact on their impulse buying of sport products. The results of the multi-group analysis also revealed significant differences across gender groups in that the impacts of nostalgia on conspicuous consumption and impulse buying were stronger for male consumers.

This study forges new ground by investigating the intricate dynamics among nostalgia, conspicuous consumption, and impulse buying in the context of sport. By delving into the relationships between them and exploring gender disparities in their effects, this study enhances our understanding of the pivotal role nostalgia plays in shaping consumer behavior in sport. In addition, the identification of gender-specific patterns underscores the significance of tailored marketing approaches for effectively engaging both male and female consumers. Overall, this study presents fresh perspectives that can inform the development of targeted marketing strategies for sport marketers and retailers aiming to optimize their offerings and promotional endeavors.

The purpose of this study was to investigate how to generate innovative work behaviors among Millennial and Generation Z sport employees and its impact on their career satisfaction and psychological well-being.

The authors used structural equation modeling to examine the relationships among predictors of job engagement, innovative work behaviors, career satisfaction and psychological well-being. The model was tested across managerial sport employees of Division I athletics departments (N = 224).

The highlights of the study include job engagement's positive relationship with innovative work behaviors and the positive influence of innovative work behavior on career satisfaction and psychological well-being.

These findings signify the importance of considering job engagement and innovative work behaviors to develop a positive work experience for Millennial and Generation Z sport employees. Doing so is thought to be a critical step in cultivating an organizational competitive advantage via younger generations of sport employees.

This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use to identify the specific factors for predicting Major League Baseball (MLB) attendance. Furthermore, by predicting spectators for each league (American League and National League) and division in MLB, the authors will identify the specific factors that increase accuracy, discuss them and provide implications for marketing strategies for academics and practitioners in sport.

This study used six years of daily MLB game data (2014–2019). All data were collected as predictors, such as game performance, weather and unemployment rate. Also, the attendance rate was obtained as an observation variable. The Random Forest, Lasso regression models and XGBoost were used to build the prediction model, and the analysis was conducted using Python 3.7.

The RMSE value was 0.14, and the R2 was 0.62 as a consequence of fine-tuning the tuning parameters of the XGBoost model, which had the best performance in forecasting the attendance rate. The most influential variables in the model are “Rank” of 0.247 and “Day of the week”, “Home team” and “Day/Night game” were shown as influential variables in order. The result was shown that the “Unemployment rate”, as a macroeconomic factor, has a value of 0.06 and weather factors were a total value of 0.147.

This research highlights unemployment rate as a determinant affecting MLB game attendance rates. Beyond contextual elements such as climate, the findings of this study underscore the significance of economic factors, particularly unemployment rates, necessitating further investigation into these factors to gain a more comprehensive understanding of game attendance.

Three-dimensional (3D) food printing is an innovative technology used to customize food products through the integration of digital technology and food ingredients. The purpose of this study is to assess the current state of research in the field of 3D food printing, identify trending topics and identify promising future research directions.

This bibliometric review systematically evaluates the field of 3D food printing using data from published literature in the Web of Science database. After reference screening, 812 articles were included in the analysis.

The result reveals that research in 3D food printing primarily focuses on the optimization and characterization of mechanical and rheological properties of food inks and that post-printing processing, such as laser treatment, has emerged recently as an important consideration in 3D food printing. However, extant works lack animal and human studies that demonstrate the functionality of 3D-printed food.

This sophisticated bibliometric analysis uncovered the most studied current research topics and the leading figures in the area of 3D food printing, providing promising future research directions.

Considering the inherent relationship between environmental degradation and the process of economic development, the latter is particularly reliant on the accumulation of human capital, which also emerges as one of the fundamental principles underlying green growth. However, this relationship tends to overlook varying levels of human capital. Hence, the purpose of this study is to examine the enduring associations between the stock of high human capital and green economies in terms of environmental sustainability among the key countries in the Asia Pacific region, namely Australia, Japan, Singapore, and South Korea, spanning the period from 1990 to 2022.

This paper employs second-generation techniques. The long-term relationships were estimated using two constantly updated models - fully modified and bias corrected, CUP-FM and CUP-BC, respectively, to guarantee the robustness of our conclusions for the presence of cross-sectional dependency.

There is a long-term relationship between the stock of high human capital and the sustainability of the environment, in the same way that we have also found the same relationship between the development of socioeconomic practices of green economies. Finally, we conclude that, in the same way as the environmental Kuznets curve, the countries in our sample incur less environmental pollution as their level of income increases. This relationship may be motivated by a process of technological substitution and investment in the development of new techniques and technology to improve the efficiency of productivity with respect to the environment.

We suggest that investing in education and promoting green economies can be powerful tools in the fight against climate change and promoting environmental sustainability. By prioritizing investments in renewable energy and sustainable technologies, policymakers can promote long-term economic and environmental health. Moreover, the findings suggest that promoting education in countries with high levels of environmental pollution can develop the knowledge and skills needed to implement sustainable practices and technologies. Ultimately, these efforts can contribute to improving income, productivity, and society's living conditions while reducing the environmental impact.

This research studies for the first time the load capacity curve hypothesis in determining the effects of the stock of high human capital and green economies on the environment. Consequently, limited papers have used the load capacity factor in the study of the relationships that we propose, especially that of human capital, which has scarcely been studied in relation to its contribution to the environmental fight.

The growth of the internet has transformed digital infrastructure in Thailand over the past two decades, with the widespread use of e-commerce, digital money and online services becoming a daily norm for all ages. The COVID-19 restrictions, which limited in-person business operations, boosted demand for takeout and delivery services and fueled the expected steady growth of the online food delivery market in Thailand. The pandemic also resulted in a shift towards online ordering and delivery, reflecting changes in customer behavior. This study focuses on exploring the factors that have driven Bangkokians to use online food delivery services after the COVID-19 restrictions were lifted in June 2022.

Data were collected from 398 participants who had ordered food delivery services after the announcement.

The findings showed that perceived usefulness, time saving benefit and price saving benefit have a significant impact on the intention of customers to use online food delivery services, while food safety risk perception had no effect.

Bangkokians favor online food delivery services due to convenience and time-saving, indicating high demand post-pandemic. Businesses should invest in improving their platforms to meet evolving consumer behavior.

The result of this study offers valuable insights into the attitudes and behaviors of Bangkokians towards online food delivery services and could be beneficial for businesses in the industry to improve their services, enhance customer satisfaction as well as increase their competitiveness.