Purpose: Partial least squares structural equation modeling (PLS-SEM) has become an established social sciences multivariate analysis technique. Since quality management researchers also increasingly using PLS-SEM, this growing interest calls for guidance.Design/methodology/approach: Based on established guidelines for applying PLS-SEM and evaluating the results, this research reviews 107 articles applying the method and published in eight leading quality management journals.Findings: The use of PLS-SEM in quality management often only draws on limited information and analysis results. The discipline would benefit from the method's more comprehensive use by following established guidelines. Specifically, the use of predictive model assessment and more advanced PLS-SEM analyses harbors the potential to provide more detailed findings and conclusions when applying the method.Research limitations/implications: This research provides first insights into PLS-SEM's use in quality management. Future research should identify the key areas and the core quality management models that best support the method's capabilities and researchers' goals.Practical implications: The results of this analysis guide researchers who use the PLS-SEM method for their quality management studies.Originality/value: This is the first article to systematically review the use of PLS-SEM in the quality management discipline.

In the past decade, extensive research has been conducted on the effects of user-generated content (UGC) on consumers’ travel-related attitudes and decisions (Filieri, 2016; Howison, Finger, & Haus...

Purpose: Accommodation sharing is a major trend shaping the hospitality industry, and Airbnb is the most prominent sharing platform driving this growth. While price convenience is reported as one of the main strengths of Airbnb accommodations, only a few studies have examined price determinants. In particular, it is unclear whether hosts dynamically adjust prices for shared accommodation based on their experience with price management and on the level of market demand. The purpose of this paper is to fill this gap by suggesting and testing a comprehensive hedonic pricing model. Design/methodology/approach: Data from all 1,056 Airbnb listings for accommodations available in the city of Verona, Italy on four booking dates in 2016 are collected and analysed through regression analysis. Findings: The results highlight that price is significantly related to the level of the host’s accumulated experience and the level of market demand on a specific booking date. The findings provide support for the ability of hosts to dynamically adjust prices for their accommodations. Practical implications: Drawing on the innovator’s dilemma theory, this study suggests some strategies that traditional hotels may adopt to react to the disruptive nature of Airbnb. Originality/value: This is one of the few studies to address hosts’ pricing strategies and specifically consider price adjustments owing to variations in host experience and market demand.

Purpose: Many firms are investing in digital services to improve customer experiences. Virtual service agents, or “e-service agents” (“e-agents”) such as chatbots, are examples of these efforts. Chatbots are types of virtual-assistant software programs that interact with users through speech or text. This paper aims to investigate whether the perceived hedonic and utilitarian attributes of chatbots can influence customer satisfaction and, consequently, their relationships with brands.Design/methodology/approach: Data were collected through a questionnaire-based survey among a sample of Italian consumers. A convenience sampling technique was used. Data were then analyzed through Partial Least Squares Structural Equation Modeling to provide a prediction-oriented model assessment. The findings were then complemented with an importance–performance map analysis (IPMA) to gain more detailed insights and actionable guidelines for managers.Findings: The findings highlighted that the perceived hedonic and utilitarian attributes of chatbots positively influenced customer satisfaction and improved customer relationships with the brands. However, the IMPA highlighted that the performance levels of two most important attributes – system quality and experience with chatbot – could be improved resulting in additional improvements of customer satisfaction.Practical implications: This study suggests the importance of firms’ investments in and adoption of e-agents to strengthen consumer–brand relationships and of considering both the hedonic and utilitarian attributes of their e-agents.Originality/value: This article attempts to enrich and consolidate the growing body of literature concerning the impacts of new technologies – and, specifically, chatbots – in service marketing.