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American Community colleges are vital to the country's economic mobility and are leaders in developing and facilitating career, technical, and workforce education. This study explored employer perspectives on employees' common and specialized skills across industries in the United States.

Employers were profiled for one year using a case study and content analysis method. They submitted performance records for at least three employees who graduated from community college career, technical, or workforce programs.

Data revealed that overall, employees were successful at work, but employers focused on employability skills across disciplines (common skills); specialized skills employers focused on were associated with business operations and processes and seemed to be something other than industry-specific technical knowledge.

This article and the research it refers to constitute original work that has not been reproduced or published. The value of this article is premised on new longitudinal data, which could be used to improve and progress institutional CTE and WD programs.

This study intend to investigate a theoretical model looking at how particular tourist emotions, such as “joy,” “love,” and “positive surprise,” might predict their behavior by looking at how satisfied they are with their whole experience when visiting spas, and to examine the relationship of emotional experience, destination image, satisfaction and intention to revisit for spa tourism.

A sample of 345 individuals who traveled to Alleppey as domestic tourists participated in the research study. A non-probability (purposive) sampling method in this study. The structural model was analyzed using Structural Equation modeling (SEM), and the path coefficients were examined to test the hypotheses.

The results supported the hypotheses, indicating that specific emotions, image of the destination, and satisfaction significantly impacted tourists' intentions to revisit Alleppey as a spa tourism destination. This study demonstrated that “emotions of joy, love, and positive surprise” have a considerable influence on the image of the destination and satisfaction. The findings reveal a substantial correlation between satisfaction and behavioral intention (“Intention to revisit”). The research suggests that a higher degree of satisfaction would encourage visitors to revisit the location.

The research suggests that a higher degree of satisfaction would encourage visitors to revisit the location. This research offers vital information for developing, planning, and putting into practice tourism policies in the spa tourism sector. This article focuses on domestic travelers who travel to Alleppey, so the conclusions may not be relevant to research utilizing foreign tourists.

According to the literature study, and to the authors` knowledge, only limited number of studies that look at spa tourism from a wellness perspective. Additionally, Alleppey is used in the study as the study’s setting, providing insight into the visitor experiences of this expanding spa tourism business. This study gives understanding about how emotional experience predicts behavioral intentions.

The purpose of this study is to extend Bippus and Young’s (2005) study and examine the effectiveness of the “I-you,” “I,” “You,” “We,” “But” and Question-based “Why” statements from Winer’s (2021) verbal coding program of conflict management using Bandura’s (1977) social learning theory (SLT).

Mixed methods were used using 175 university students from Texas and New York. A cross-sectional convenience sampling approach was conducted. Survey data was collected using Qualtrics.

Descriptive results demonstrated that the “We” statement was the most passive, the “I-you” statement was the most assertive and the “But,” “I,” “You” and Question statements were perceived to be aggressive. In addition, assertive “I-You” statements were perceived to be more effective in resolving the conflict and maintaining a relationship, whereas aggressive statements were less likely to resolve the conflict and maintain the relationship. Qualitative themes also support the “I-You” statement as the most assertive, while the “But,” “You” and “I” statements were found to be the most aggressive statements.

Implications and applications are discussed to stimulate future research among researchers and practitioners when addressing conflict. Being aware of the verbal statements that de-escalate conflict may be helpful in solving conflict in interpersonal, family and professional relationships. Future trainings can adopt effective verbal statements to resolve conflict when experiencing anger issues. Future research can continue to investigate verbal communication statements using SLT to help practitioners and managers address conflict in interpersonal relationships.

This study examines verbal statements in relation to communication styles and conflict management.

Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.

This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.

This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.

It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.

This paper aims to investigate the increasing trend of multigenerational co-living in the USA and to research the socioeconomic and cultural determinants of such decision.

This study uses the 2017 American Housing Survey data to run descriptive and regression analysis.

The authors find household income appears consistently to be the most significant factor determining multigenerational co-residence decision across all household compositions. Latino households are most likely to co-reside with multiple generations, followed by Asian and African American households. Immigrants tend to live in multigenerational co-residential housing units with smaller sizes and more impoverished neighborhoods, but show greater flexibility in making residential arrangements once they gain better education. In addition, older householders or female householders are significantly more likely to co-reside with multiple generations. Living in metropolitan areas has no impact on co-residence choice, although some evidence suggests that multigenerational co-residential families tend to live in inferior neighborhoods.

This study provides updated evidence on multigenerational co-residence choice in the contemporary United States. The findings provide evidence on how households make residential choices in response to financial hardships and contribute to the theoretical understanding of the variations of such decisions among immigrants and different ethnic and aging groups.

This study on multigenerational co-residence choice imposes important practical implications. The unprecedented COVID-19 pandemic creates ideal research setting to study how households cope with the tremendous uncertainties in the job markets and financial markets. Although multigenerational co-living may work well for some households with lower or moderate-income for financial reasons, it is not an attractive option for every family.

Sharing a home with multiple generations can be challenging. Policymakers should design policies and programs to provide households with guidance on how to live peacefully in multigenerational settings and make multigenerational co-living an appealing and cost-effective housing option for American families of all means.

This study contributes to the existing literature by providing new evidence on the determinants of multigenerational co-residence decision. This study’s findings are fundamental to guide policymakers in carrying out policies and programs aimed at providing a more appealing and cost-effective housing arrangement for American families. The evidence on the senior and minority subsamples are especially meaningful as the vast majority of the baby boom generation in the USA is aging and substantial growth is expected in multigenerational households over the next several decades. Understanding the increasing burden of old-age depression in aging societies will help policymakers prioritize public resources in city planning to address the needs of this rapidly growing population.

This study aims to conduct a bibliometric analysis of sustainable tourism research published in Scopus-indexed journals covering the period from 1997 to 2021. Articles published during these 25 years were subjected to science mapping and performance analysis to propose potential areas for future research.

A bibliometric analysis using performance analysis and science mapping was conducted on 1,754 research papers retrieved from the Scopus database using the keyword “sustainable tourism.” Biblioshiny and VOSviewer are commonly used bibliometric tools. Science mapping techniques use coauthorship, keyword co-occurrence and co-citation analyses.

This study revealed the sustainable tourism publications’ spatial and temporal patterns, indicating a yearly growth rate of 19.9% during a 25-year period. The study identified Stefan Gossling as the most influential author, the “Journal of Sustainable Tourism” as the leading journal and Australia as the most productive country in sustainable tourism literature. The study used co-citation analysis to identify five thematic clusters, namely, reconceptualization and criticism, the role of residents, eco-labeling and the role of stakeholders, community-based tourism and the shift toward establishing sustainability indicators and effective governance and policymaking. The coauthorship analysis identifies the most influential author in collaborative efforts, and the most common pattern of collaboration is between researchers from different institutions in the same country, such as China and the Philippines, followed by collaborations between authors from other countries. The keyword co-occurrence analysis uncovered keywords that aligned with theme clusters generated from the co-citation analysis.

This study comprehensively uncovers five thematic clusters that have never been extracted so far in the literature. Also, it attempts to fill the gaps related to sustainable tourism by suggesting directions for future research.