Relevant bibliographies by topics / Hospitality robots

Academic literature on the topic 'Hospitality robots'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Hospitality robots"

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Go, Hanyoung, Myunghwa Kang, and SeungBeum Chris Suh. "Machine learning of robots in tourism and hospitality: interactive technology acceptance model (iTAM) – cutting edge." Tourism Review 75, no. 4 (January 31, 2020): 625–36. http://dx.doi.org/10.1108/tr-02-2019-0062.

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Purpose The purpose of this study is to discuss how consumers accept advanced artificial intelligence (AI) robots in hospitality and tourism and provide a typology and conceptual framework to support future research on advanced robot applicability. Design/methodology/approach This research reviews current cases of AI use and technology acceptance model (TAM) studies and proposes a framework, interactive technology acceptance model (iTAM), to identify key determinants that stimulate consumer perceptions of advanced robot technology acceptance. Findings The main constructs and types of advanced robots were identified by reviewing TAM studies and AI robots that are currently used in the tourism and hospitality industry. This research found that as technologies tested in TAM studies have been improved by highly interactive systems, increased capability and a more user-friendly interface, examining perceived interactivity of technology has become more important for advanced robot acceptance models. The examples of advanced robot uses indicate that each machine learning application changes the robots’ task performance and interaction with consumers. Conducting experimental studies and measuring the interactivity of advanced robots are vital for future research. Originality/value To the authors’ knowledge, this is the first study on how consumers accept AI robots with machine learning applications in the tourism and hospitality industry. The iTAM framework provides fundamental constructs for future studies of what influences consumer acceptance of AI robots as innovative technology, and iTAM can be applied to empirical experiments and research to generate long-term strategies and specific tips to implement and manage various advanced robots.
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Collins, Galen R. "Improving human–robot interactions in hospitality settings." International Hospitality Review 34, no. 1 (April 18, 2020): 61–79. http://dx.doi.org/10.1108/ihr-09-2019-0019.

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PurposeService robotics, a branch of robotics that entails the development of robots able to assist humans in their environment, is of growing interest in the hospitality industry. Designing effective autonomous service robots, however, requires an understanding of Human–Robot Interaction (HRI), a relatively young discipline dedicated to understanding, designing, and evaluating robotic systems for use by or with humans. HRI has not yet received sufficient attention in hospitality robotic design, much like Human–Computer Interaction (HCI) in property management system design in the 1980s. This article proposes a set of introductory HRI guidelines with implementation standards for autonomous hospitality service robots.Design/methodology/approachA set of key user-centered HRI guidelines for hospitality service robots were extracted from 52 research articles. These are organized into service performance categories to provide more context for their application in hospitality settings.FindingsBased on an extensive literature review, this article presents some HRI guidelines that may drive higher levels of acceptance of service robots in customer-facing situations. Deriving meaningful HRI guidelines requires an understanding of how customers evaluate service interactions with humans in hospitality settings and to what degree those will differ with service robots.Originality/valueRobots are challenging assumptions on how hospitality businesses operate. They are being increasingly deployed by hotels and restaurants to boost productivity and maintain service levels. Effective HRI guidelines incorporate user requirements and expectations in the design specifications. Compilation of such information for designers of hospitality service robots will offer a clearer roadmap for them to follow.
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Christou, Prokopis, Aspasia Simillidou, and Maria C. Stylianou. "Tourists’ perceptions regarding the use of anthropomorphic robots in tourism and hospitality." International Journal of Contemporary Hospitality Management 32, no. 11 (October 23, 2020): 3665–83. http://dx.doi.org/10.1108/ijchm-05-2020-0423.

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Purpose Amidst the COVID-19 outbreak, service organizations rushed to deploy robots to serve people in quarantine, again igniting the ongoing dispute regarding robots in tourism. This study aims to investigate tourists’ perceptions regarding the use of robots and, more specifically, anthropomorphic robots in the tourism domain. Design/methodology/approach A qualitative inquiry was used to delve deep into the issue of tourists’ perceptions regarding the usage of anthropomorphic robots in tourism, with a total number of 78 interviews with tourists being retained in the study. Findings The findings reveal that tourists favor the use of anthropomorphic robots over any other type of robot. The use of anthropomorphic robots in tourism may result in an overall enhanced experiential value. Even so, informants also expressed frustration, sadness and disappointment vis-à-vis the use of robots in a human-driven industry. Research limitations/implications A conceptual continuum of tourists’ perceptions and concerns over the use of robots is presented that can guide future studies. Tourism stakeholders may look at the possibility of incorporating carefully designed anthropomorphic robots in key service positions, but should not give the impression that robots are replacing the human face of the organization. Practical implications Tourism stakeholders may look at the possibility of incorporating carefully designed anthropomorphic robots in key service positions, but should not give the impression that robots are replacing the human face of the organization. Originality/value Tourism organizations that make use of robots run the risk of being perceived as nonanthropocentric. This leads to the conclusion that anthropomorphism could be used but should not replace the sector’s anthropocentrism. The study conveys tourists’ concerns over technological (robot) determinism.
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Murphy, Jamie, Charles Hofacker, and Ulrike Gretzel. "Dawning of the Age of Robots in Hospitality and Tourism: Challenges for Teaching and Research." European Journal of Tourism Research 15 (March 1, 2017): 104–11. http://dx.doi.org/10.54055/ejtr.v15i.265.

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This conceptual paper revisits, refreshes and reinforces a 1984 study that challenged hospitality educators to include robotics in their classes and their research. The paper briefly reviews robotics literature, explains three robot categories—industrial, professional service and personal service—emphasises the importance of autonomy and human robot interaction, and provides hospitality and tourism examples. This literature review leads to six areas of importance for teaching and research of robotics in hospitality and tourism. The paper gives academics and practitioners a foundation for envisioning the current and future state of robots in hospitality and tourism.
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Ivanov, Stanislav. "Ultimate transformation: How will automation technologies disrupt the travel, tourism and hospitality industries?" Zeitschrift für Tourismuswissenschaft 11, no. 1 (April 25, 2019): 25–43. http://dx.doi.org/10.1515/tw-2019-0003.

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Abstract Companies from the travel, tourism and hospitality industry have started adopting robots, artificial intelligence and service automation technologies (RAISA) in their operations. Self-check-in kiosks, robotic pool cleaners, delivery robots, robot concierges, chatbots, etc., are used increasingly by tourism companies and transform the ways they create and deliver services. This paper investigates the impact of RAISA technologies on travel, tourism and hospitality companies – their operations, facilities design, marketing, supply chain management, human resource management, and financial management. The paper emphasises that in the future companies will divide into two large segments – high-tech tourism companies offering standardized cheap robot-delivered services, and high-touch companies, which rely on human employees.
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Bowen, John, and Cristian Morosan. "Beware hospitality industry: the robots are coming." Worldwide Hospitality and Tourism Themes 10, no. 6 (December 3, 2018): 726–33. http://dx.doi.org/10.1108/whatt-07-2018-0045.

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Purpose The purpose of this study is to provide an overview of how artificial intelligence (AI) and robotics can and will be utilized by the hospitality industry, providing a glimpse of what their use will look like in 2030. Design/methodology/approach The paper reviewed both academic and trade literature to provide an overview of how robots will affect the hospitality industry during the 2030s. Findings Experts predict that by 2030, robots will make up about 25 per cent of the “workforce” in the hospitality industry. The paper also explains the industry challenges the robots will solve, as well as other benefits they provide. One of the findings is that the adoption of robots by the industry will be a disruptive paradigm shift. It will create successful new hospitality companies while putting others out of business. Finally, this paper discusses how to keep the hospitality in hospitality businesses, when machines replace employees. Originality/value This paper is one of the first to discuss the disruption that robots will cause in the industry. One of the findings is service delivery systems will need to be redesigned to maximize the benefits of robots, while still maintaining the hospitality of a customer service orientation.
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Carvalho, Inês, Sofia Lopes, Arlindo Madeira, Teresa Palrão, and Alexandra S. Mendes. "Robot Coworkers: The Vision of Future Hoteliers." Human Behavior and Emerging Technologies 2022 (June 20, 2022): 1–13. http://dx.doi.org/10.1155/2022/8567289.

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The purpose of this study is to understand how future employees in the hospitality and tourism industry envision the use of artificial intelligence in the organizations where they wish to work in the future. Through open-ended questions applied to undergraduate and master’s students in the area of tourism and hospitality, we capture their opinions when thinking about the partial or total use of robots in hospitality. Despite the increasing implementation of artificial intelligence in hospitality and tourism, existing research mainly focuses on current hoteliers and/or customers. However, anticipating how digital generations expect their future roles in a close engagement with robots allows researchers to predict and focus their attention on future problems. Their statements were subjected to a qualitative content analysis methodology, based on themes and sentiment. Participants expressed a negative view of the presence of robots in hospitality, mostly associated with a fear of job loss. Many also reported that interacting with robots is negative for both staff and customers due to robots’ lack of emotions. However, there is some division concerning the impact of robots on service quality: some believe that the service will be more efficient and with fewer failures; others believe that the limitations of robots will lead to worse service. The findings suggest that the acceptability and desirability of robotization may vary depending on the level of robotization in hotels, on the type of customer, and on the level of service provided.
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Wu, Jifei, Xiangyun Zhang, Yimin Zhu, and Grace Fang Yu-Buck. "Get Close to the Robot: The Effect of Risk Perception of COVID-19 Pandemic on Customer–Robot Engagement." International Journal of Environmental Research and Public Health 18, no. 12 (June 10, 2021): 6314. http://dx.doi.org/10.3390/ijerph18126314.

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The purpose of this study was to examine the effect of the COVID-19 pandemic on customer–robot engagement in the Chinese hospitality industry. Analysis of a sample of 589 customers using service robots demonstrated that the perceived risk of COVID-19 has a positive influence on customer–robot engagement. The positive effect is mediated by social distancing and moderated by attitudes towards risk. Specifically, the mediating effect of social distancing between the perceived risk of COVID-19 and customer–robot engagement is stronger for risk-avoiding (vs. risk-seeking) customers. Our results provide insights for hotels when they employ service robots to cope with the shock of COVID-19 pandemic.
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Kuo, Chun-Min, Li-Cheng Chen, and Chin-Yao Tseng. "Investigating an innovative service with hospitality robots." International Journal of Contemporary Hospitality Management 29, no. 5 (May 8, 2017): 1305–21. http://dx.doi.org/10.1108/ijchm-08-2015-0414.

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Purpose The purpose of this study is to identify the factors that influence the development of service robots, and to apply a service innovation strategic mindset to the hotel industry in Taiwan. Design/methodology/approach A mixed-methods approach, combining an expert panel and semi-structured interviews using a SMART SWOT ranking survey, was applied to understand the perspectives of hotel owners and robotics experts. Findings Fifty-three items were collected regarding the demand side of the hospitality market, showing that the Taiwan hospitality industry has good potential to implement service robots. Sixty-one items on the supply side of business were collected, showing that this robotics service can help hotels handle seasonal employment and labor utilization. The SWOT analysis identifies “The fun and curiosity aroused in consumers can enhance the promotion of service robots”, “Lack of talent in system integration”, “Taiwan’s aging society can increase the demand for service robots” and “China and South-east countries have aggressively poached talent in the global robotics market” as key issues. Originality/value Few studies have investigated robotics service for hotels using the six-dimensional service innovation model. This model helps identify six factors and implies that this new service concept can position hotels to better compete by using IT and relationship marketing strategies.
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Ivanov, Stanislav, and Craig Webster. "Willingness-to-pay for robot-delivered tourism and hospitality services – an exploratory study." International Journal of Contemporary Hospitality Management 33, no. 11 (August 30, 2021): 3926–55. http://dx.doi.org/10.1108/ijchm-09-2020-1078.

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Purpose This paper aims to investigate potential consumers’ willingness to pay for robot-delivered services in travel, tourism and hospitality, and the factors that shape their willingness to pay. Design/methodology/approach An online survey yielded a sample of 1,573 respondents from 99 countries. Independent samples t-test, Analysis of variance (ANOVA), cluster, factor and regression analyses were used. Findings Respondents expected to pay less for robot-delivered services than human-delivered services. Two clusters were identified: one cluster willing to pay nearly the same price for robotic services as for human-delivered services, whilst the other expected deep discounts for robotic services. The willingness-to-pay was positively associated with the attitudes towards robots in tourism, robotic service experience expectations, men and household size. It was negatively associated to travel frequency, age and education. Research limitations/implications The paper’s main limitation is its exploratory nature and the use of a hypothetical scenario in measuring respondents’ willingness to pay. The data were gathered prior to the COVID-19 pandemic and do not reflect the potential changes in perceptions of robots due to the pandemic. Practical implications Practitioners need to focus on improving the attitudes towards robots in tourism because they are strongly and positively related to the willingness to pay. The marketing messages need to form positive expectations about robotic services. Originality/value This is one of the first papers to investigate consumers’ willingness to pay for robot-delivered services in travel, tourism and hospitality and factors that shape their willingness to pay.
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Dissertations / Theses on the topic "Hospitality robots"

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Geisler, Rafael. "Artificial intelligence in the travel & tourism industry adoption and impact." Master's thesis, 2018. http://hdl.handle.net/10362/39709.

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The following thesis evaluates the current adoption level and shows the potential impact of artificial intelligence systems in the travel and tourism industry. The focus of the work project lies on current AI applications such as chat bots or robots and their usage along the traveler journey. The evaluation of the current adoption is based on a collection of use cases. The impact evaluation is based on expert discussions and opinions. In both cases the results of third party studies are also included. The purpose of the work is to give the management and owners a guidance how to handle artificial intelligence in their travel and tourism business.
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Books on the topic "Hospitality robots"

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Webster, Craig, and Stanislav Ivanov. Robots, Artificial Intelligence and Service Automation in Travel, Tourism and Hospitality. Emerald Publishing Limited, 2019.

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Webster, Craig, and Stanislav Ivanov. Robots, Artificial Intelligence and Service Automation in Travel, Tourism and Hospitality. Emerald Publishing Limited, 2019.

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Robots, Artificial Intelligence and Service Automation in Travel, Tourism and Hospitality. Emerald Publishing Limited, 2019.

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Webster, Craig, and Stanislav Ivanov. Robots, Artificial Intelligence and Service Automation in Travel, Tourism and Hospitality. Emerald Publishing Limited, 2022.

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Ivanov, Stanislav, and Craig Webster, eds. Robots, Artificial Intelligence, and Service Automation in Travel, Tourism and Hospitality. Emerald Publishing Limited, 2019. http://dx.doi.org/10.1108/9781787566873.

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Kearney, Richard, and Melissa Fitzpatrick. Radical Hospitality. Fordham University Press, 2021. http://dx.doi.org/10.5422/fordham/9780823294428.001.0001.

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This volume addresses a timely and challenging subject for contemporary philosophy: the ethical responsibility of opening borders, psychic and physical, to the stranger. Drawing on key critical debates on the question of hospitality ranging from phenomenology, hermeneutics and deconstruction to neo-Kantian moral critique and Anglo-American virtue ethics, the book engages with urgent moral conversations regarding the role of identity, nationality, immigration, peace, and justice. The volume is divided into two parts. In the first part, entitled “Four Faces of Hospitality: Linguistic, Narrative, Confessional, Carnal,” Richard Kearney develops his recent research on the philosophy of hospitality, which informs the international Guestbook Project of which he is a founder and director (guestbookproject.org). This part elaborates an ethics of hosting the stranger. In the second part, entitled “Hospitality and Moral Psychology: Exploring the Border between Theory and Practice,” Melissa Fitzpatrick adumbrates a new ethics of hospitality in a robust reengagement with the philosophies of Kant, Levinas, Arendt, and contemporary virtue ethicist Talbot Brewer. In the concluding chapters, Kearney and Fitzpatrick chart novel options for the pedagogical application of an ethics of hospitality to our contemporary world of border anxiety, boundary disputes, migration crisis, and the looming ecological challenge.
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Book chapters on the topic "Hospitality robots"

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Ciftci, Olena, and Katerina Berezina. "Exploring Customer Experience with Service Robots in Hospitality and Tourism: Activity Theory Perspective." In Information and Communication Technologies in Tourism 2023, 65–76. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-25752-0_6.

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AbstractAddressing a call for theoretical development in human-robot interaction research, this study introduces activity theory to the field of service robots (SRs) in hospitality and tourism. Activity theory was used as the foundation for the conceptual analysis of in-depth interviews with hospitality customers. The results of content analysis of the interviews and future research directions are presented based on each of the service activity system’s components: object (customer experience (CE) with SRs in a hospitality unit), subject (customers), technology (SRs), rules (implementation procedures of SRs), community (customers, other customers, and employees), division of labor (a division of service), outcome (satisfaction, overall experience with hospitality establishments, and behavioral intentions), and context. The study provides future research directions in using activity theory in studies on human-robot interaction and CE with SRs in hospitality and tourism. Robot developers and hospitality professionals can use the data analysis framework proposed in this study to evaluate CE with SRs.
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Webster, Craig, and Stanislav Ivanov. "Attitudes towards robots as transformational agents in tourism and hospitality." In Emerging Transformations in Tourism and Hospitality, 66–82. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003105930-6.

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Korstanje, Maximiliano E., and Babu George. "Is Hospitality Dying? In Robots We Must Not Trust." In The Nature and Future of Tourism, 113–27. New York: Apple Academic Press, 2022. http://dx.doi.org/10.1201/9781003277507-7.

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Brylska, Patrycja, Cihan Cobanoglu, and Seden Dogan. "Users Versus Non-users: The Impact of Experience on Hotel Guests’ Attitudes Towards Service Robots in Hotels." In Information and Communication Technologies in Tourism 2022, 55–66. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94751-4_5.

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AbstractThe use of robotics and artificial intelligence have created a shift in the ways the service-based hospitality and tourism industry can fulfill the needs and wants of consumers that were earlier fulfilled only by humans. Robots have added the automation and self-service experience that play a vital role in the improvements of efficiency, speed, and the overall experience for the guests using technology. While there are many benefits of using robots in the industry, there are also risks associated with the excessive usage of robots on guest experience. As a result of the pros and cons on the topic, it is very important to gather data and analyze the results to further investigate and understand what the outcomes will be for the industry, its employees, and its customers. The purpose of this study is to examine the perceptions of the use of robots in the hotels as perceived by hotel guests who used a service robot and who did not. A self-administered survey was developed, and 939 usable responses were collected from hotel guests. Factor analysis showed that five factors emerged in the study: Advantages, Attitudes, Disadvantages, Pandemic Related, and Fear. Guests recognize the opportunities that service robots are bringing to their experience while voicing their concerns and fears about the use of them. Findings also showed that there are significant differences between users and non-users.
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Kavoura, Androniki. "Τwo to Tango: Entrepreneurs and Robots’ Users in Hospitality Service Innovation." In Service Excellence in Tourism and Hospitality, 111–31. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-57694-3_8.

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Rosete, Ana, Barbara Soares, Juliana Salvadorinho, João Reis, and Marlene Amorim. "Service Robots in the Hospitality Industry: An Exploratory Literature Review." In Exploring Service Science, 174–86. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38724-2_13.

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Korstanje, Maximiliano E., and Babu George. "Robots and Tourism: Hospitality and the Analysis of Westworld, HBO Saga." In The Nature and Future of Tourism, 149–70. New York: Apple Academic Press, 2022. http://dx.doi.org/10.1201/9781003277507-9.

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Zulfakar, Zufara Arneeda, Fitriya Abdul Rahim, David Ng Ching Yat, Lam Hon Mun, and Tat-Huei Cham. "Say Aye to AI: Customer Acceptance and Intention to Use Service Robots in the Hospitality Industry." In International Conference on Information Systems and Intelligent Applications, 83–92. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16865-9_7.

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Ivanov, Stanislav, Craig Webster, and Katerina Berezina. "Robotics in Tourism and Hospitality." In Handbook of e-Tourism, 1873–99. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-48652-5_112.

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Ivanov, Stanislav, Craig Webster, and Katerina Berezina. "Robotics in Tourism and Hospitality." In Handbook of e-Tourism, 1–27. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-05324-6_112-1.

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Conference papers on the topic "Hospitality robots"

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Yang, Jiaji, and Esyin Chew. "Intelligent Service Robots to enter the Hospitality Industry: Job Termination or Gospel to Waiters." In UKRAS20 Conference: “Robots into the real world”. EPSRC UK-RAS Network, 2020. http://dx.doi.org/10.31256/yo8tk2t.

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"The Effect of Service Robots and Other Technology on Job Profiles in The Hospitality Industry." In Dec. 19-21, 2022 Pattaya (Thailand). Universal Researchers (UAE), 2022. http://dx.doi.org/10.17758/uruae18.uh1222408.

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Chung, Michael Jae-Yoon, and Maya Cakmak. "“How was Your Stay?”: Exploring the Use of Robots for Gathering Customer Feedback in the Hospitality Industry." In 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). IEEE, 2018. http://dx.doi.org/10.1109/roman.2018.8525604.

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Devavrat, Samak, and Dinesh Salunke. "Development of a non-humanoid robot for hospitality." In THE 3RD INTERNATIONAL CONFERENCE ON MATHEMATICS AND SCIENCES (THE 3RD ICMSc): A Brighter Future with Tropical Innovation in the Application of Industry 4.0. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0110542.

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Higashinaka, Ryuichiro, Takashi Minato, Kurima Sakai, Tomo Funayama, Hiromitsu Nishizaki, and Takayuki Nagai. "Dialogue Robot Competition for the Development of an Android Robot with Hospitality." In 2022 IEEE 11th Global Conference on Consumer Electronics (GCCE). IEEE, 2022. http://dx.doi.org/10.1109/gcce56475.2022.10014410.

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Sugaya, Midori, Yuki Nishida, Reiji Yoshida, and Yuya Takahashi. "An Experiment of Human Feeling for Hospitality Robot Measured with Biological Information." In 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC). IEEE, 2018. http://dx.doi.org/10.1109/compsac.2018.10305.

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Shih, Ru-Chu, Hsin-Tien Hsin, Hsiu-Chu Huang, and Yuh-Ming Cheng. "The Development of a Mobile APP for a Hospitality and Tourism Course at Technological Universities." In 2015 Third International Conference on Robot, Vision and Signal Processing (RVSP). IEEE, 2015. http://dx.doi.org/10.1109/rvsp.2015.67.

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Lestari, Nurul Sukma, Dendy Rosman, and Trias Septyoari Putranto. "The Relationship Between Robot, Artificial Intelligence, and Service Automation (RAISA) Awareness, Career Competency, and Perceived Career Opportunities: Hospitality Student Perspective." In 2021 International Conference on Information Management and Technology (ICIMTech). IEEE, 2021. http://dx.doi.org/10.1109/icimtech53080.2021.9535054.

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Reports on the topic "Hospitality robots"

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Tipton, Kelley, Brian F. Leas, Nikhil K. Mull, Shazia M. Siddique, S. Ryan Greysen, Meghan B. Lane-Fall, and Amy Y. Tsou. Interventions To Decrease Hospital Length of Stay. Agency for Healthcare Research and Quality (AHRQ), September 2021. http://dx.doi.org/10.23970/ahrqepctb40.

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Background. Timely discharge of hospitalized patients can prevent patient harm, improve patient satisfaction and quality of life, and reduce costs. Numerous strategies have been tested to improve the efficiency and safety of patient recovery and discharge, but hospitals continue to face challenges. Purpose. This Technical Brief aimed to identify and synthesize current knowledge and emerging concepts regarding systematic strategies that hospitals and health systems can implement to reduce length of stay (LOS), with emphasis on medically complex or vulnerable patients at high risk for prolonged LOS due to clinical, social, or economic barriers to timely discharge. Methods. We conducted a structured search for published and unpublished studies and conducted interviews with Key Informants representing vulnerable patients, hospitals, health systems, and clinicians. The interviews provided guidance on our research protocol, search strategy, and analysis. Due to the large and diverse evidence base, we limited our evaluation to systematic reviews of interventions to decrease hospital LOS for patients at potentially higher risk for delayed discharge; primary research studies were not included, and searches were restricted to reviews published since 2010. We cataloged the characteristics of relevant interventions and assessed evidence of their effectiveness. Findings. Our searches yielded 4,364 potential studies. After screening, we included 19 systematic reviews reported in 20 articles. The reviews described eight strategies for reducing LOS: discharge planning; geriatric assessment or consultation; medication management; clinical pathways; inter- or multidisciplinary care; case management; hospitalist services; and telehealth. All reviews included adult patients, and two reviews also included children. Interventions were frequently designed for older (often frail) patients or patients with chronic illness. One review included pregnant women at high risk for premature delivery. No reviews focused on factors linking patient vulnerability with social determinants of health. The reviews reported few details about hospital setting, context, or resources associated with the interventions studied. Evidence for effectiveness of interventions was generally not robust and often inconsistent—for example, we identified six reviews of discharge planning; three found no effect on LOS, two found LOS decreased, and one reported an increase. Many reviews also reported patient readmission rates and mortality but with similarly inconsistent results. Conclusions. A broad range of strategies have been employed to reduce LOS, but rigorous systematic reviews have not consistently demonstrated effectiveness within medically complex, high-risk, and vulnerable populations. Health system leaders, researchers, and policymakers must collaborate to address these needs.
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