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A growing number of travelers seek well-being when traveling. As concerning about outdoor air pollution in tourism destinations escalates, little is known about indoor air pollution in hotel guestrooms. The purpose of the present study is to assess particulate matter (PM) pollution in US hotel guestrooms and to provide baseline indoor PM readings in occupied and unoccupied rooms.

A series of field tests and experiments monitoring PM levels were conducted in the guestrooms overnight – with and without occupants – using the sophisticated, industrial-grade PM-monitoring equipment.

The results revealed that PM levels were very low when rooms were unoccupied or when guests were asleep. However, unhealthy PM mass concentrations were observed in occupied rooms when guests engaged in physical activity such as showering and walking around or while room attendants cleaned rooms. Among the physical activities, room cleaning caused hazardous indoor PM pollution, reaching 1,665.9 µg/m³ of PM10 and 140.4 µg/m³ of PM2.5 although they tended to be brief.

Leveraging increasing guest demand in well-being is essential for sustainable business and further growth. Indoor air quality must be recognized as an important factor to be controlled for well-being and health of guests and employees. Major hotel brands should take it into consideration as they infuse well-being DNA into their products and culture.

To the best of the authors’ knowledge, this study is the first empirical investigation of PM pollution both in occupied and unoccupied hotel guestrooms in the USA, which reveals unhealthy PM pollution associated with the routine human activities in occupied guestrooms.

Crowdsourcing food delivery represents great potential for future development and expansion of the restaurant business. Accordingly, job performance and retention of delivery workers are critical for success. Therefore, this paper aims to investigate how to enhance crowdsourced delivery workers’ job performance and intent to continue working by applying the sociotechnical systems theory.

The data analysis was conducted using responses obtained from crowdsourced food delivery workers. A structural equation model was developed to verify the hypothesized relationships. To test the proposed moderating roles of a three-dimensional concept of social capital within the research model, multi-group analyses were implemented.

This study confirmed the significant relationships between crowdsourcing risks related to workers’ low job commitment and technical systems, attributing to reduced job performance and intent to continue working. Results documented that social systems including networks, trust and shared vision mitigated the negative impact of the perceived difficulty and complexity of technical systems and job performance.

Although technology has contributed significantly to the effectiveness of online food delivery, the literature has mainly focused on its benefits and has ignored the critical aspects derived from a virtual and technology-based workplace. This gap was addressed by verifying the important roles of social factors (networks, trust and shared visions) in reducing the negative impacts of technology-driven risks (perceived difficulty of task requirements and technology complexity) within the crowdsourcing food delivery context.