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The purpose of this study is to examine Airbnb research using bibliometric methods. Using research performance analysis, this study highlights and provides an updated overview of Airbnb research by revealing patterns in journals, papers and most influential authors and countries. Furthermore, it graphically illustrates how research themes have evolved by mapping a co-word analysis and points out potential trends for future research.

The methodological design for this study involves three phases: the document source selection, the definition of the variables to be analyzed and the bibliometric analysis. A statistical multivariate analysis of all the documents’ characteristics was performed with R software. Furthermore, natural language processing techniques were used to analyze all the abstracts and keywords specified in the 129 selected documents.

Results show the genesis and evolution of publications on Airbnb research, scatter of journals and journals’ characteristics, author and productivity characteristics, geographical distribution of the research and content analysis using keywords.

Despite Airbnb having a history of 10 years, research publications only started in 2015. Therefore, the bibliometric study includes papers from 2015 to 2019. One of the main limitations is that papers were selected in October of 2019, before the year was over. However, the latest academic publications (in press and earlycite) were included in the analysis.

This study analyzed bibliometric set of laws (Price’s, Lotka’s and Bradford’s) to better understand the patterns of the most relevant scientific production regarding Airbnb in tourism and hospitality journals. Using natural language processing techniques, this study analyzes all the abstracts and keywords specified in the selected documents. Results show the evolution of research topics in four periods: 2015-2016, 2017, 2018 and 2019.

This study aims to apply the concept of brand love to a destination and investigate its antecedents and consequences. It also explores the moderating effects of time elapsed since the establishment of the destination brand love relationship on the outcomes of destination brand love.

A total of 5,511 valid responses were obtained from an online survey distributed among former international students from the Erasmus program of the European Union. Partial least squares structural equation modeling was conducted to assess the hypotheses.

Destination brand love was found to have a significant impact on electronic word of mouth (eWOM), WOM, WOM intensity, recommendation and revisit intention. Moderation analysis revealed that the amount of time elapsed since the establishment of the destination brand love relationship did not affect these outcomes. Moreover, destination image and the Erasmus experience had a positive effect on destination brand love.

Destination marketers should focus on enhancing the Erasmus experience and on improving destination image perception, as these factors help develop destination brand love. Marketers should also be aware that this relationship has long-lasting effects.

This study adds to the sparse literature on brand love in relation to a destination. This gives the first results for the importance of Erasmus students to the promotion of a host country. It also contributes to the question of how long the brand love relationship can last.

This paper aims to discuss the estimation of PLS models with second-order formative constructs as existing research has mainly focused on second-order constructs with a reflective measurement.

Using a model grounded on Roger’s innovation diffusion theory applied to online travel shopping, an empirical application is used to assess and compare the different approaches used to estimate a formative second-order construct. The proposed model examines the innovations characteristics that have an impact on intentions to purchase travel online, using data from a convenience sample of 1,732 responses.

The findings show that all approaches produce similar results regarding the path coefficients, the predictive relevance of the model and the explained variance. The main differences between the approaches are related to the weights of the first-order constructs on the second-order construct and the significance of those weights. Several recommendations are made for researchers on which approach to use.

Since most research has focused on second-order constructs with a reflective measurement and there is limited research with formative second-order constructs, this paper provides a comparison of the different approaches typically used to estimate a formative second-order construct and present useful guidelines for researchers to decide the method to analyse a model with second-order constructs and how to assess formative second-order constructs.

由于现有文章大多数研究反应性结构的二阶模型, 所以本论文讨论以二阶形成性结构的PLS模型。

本论文以罗杰斯的创新扩散模型以基础, 应用其在在线旅游购物行为的研究。通过模型建立和背景研究, 多种预估形成性二阶结构的方法得以比较。建立的模型, 通过1,732份样本采样, 分析了各种对于在线购买旅游产品意图的创新特性。

本论文发现, 各种方法产生相似的分析结果, 比如径路系数、模型预测相关、以及被解释变量等。三种方法的主要区别在于, 第一阶段结构与第二阶段结构的比重值, 还有这些比重值的显著程度。本论文结果对于未来理论采用哪种方法做出启示。

由于大多数研究都集中在以反应性二阶结构分析, 很少的文章研究形成性二阶结构。因此, 本论文全面地比较了三种衡量形成性二阶结构的方法, 并且提供有效建议, 采用哪种方式以分析二阶结构, 以及如何衡量形成性二阶结构。

旅游业、在线旅游购物行为、偏最小二乘回归，二阶形成性结构

研究论文

The purpose of this study is to examine factors that affect the likelihood to create travel content online. Research has shown that there are far more people consuming social media than generating it. However, online travel marketers need to pay attention to travelers that share their experiences online, as they have the potential to drive sales.

An online survey was conducted to collect data for this study, by sending e-mail invitations to colleagues, students, personal contacts and other email contacts composed of Portuguese Internet users. A total of 244 complete responses were considered valid to test the hypotheses through partial least squares structural equation modeling.

The results reveal that travelers’ level of involvement with tourism products, innovativeness and use of social media directly influences writing reviews about travel experiences online.

First, the data used in this study were based on a convenience sample containing only the Portuguese population. Therefore, generalization of the results should be made with caution. The replication of this study in other countries would be desirable. Second, the study used a quantitative approach to examine the effect of personal characteristics on travel content creation. A research using also a qualitative approach could shed new light on the understanding of the research hypotheses.

This study provides useful insights for travel social media websites and travel-related organizations, as they can adapt their marketing strategies to the type of travelers that are more likely to write about the travel services that they offer online.

From a theoretical perspective, there are few studies that focus on the personal characteristics of travelers that create content online. The intention of this study is to help close this gap, providing useful insights with respect to this matter.

Inventory management systems in health-care supply chains (HCSC) have been pushed to breaking point by the COVID-19 pandemic. Unanticipated demand shocks due to stockpiling of medical supplies caused stockouts, and the stockouts triggered systematic supply chain (SC) disruptions inconceivable for risk managers working individually with limited information about the pandemic. The purpose of this paper is to respond to calls from the United Nations (UN) and World Health Organization (WHO) for coordinated global action by proposing a research agenda based on a review of current knowledge and knowledge gaps on the role of collaboration in HCSCs in maintaining optimal stock levels and reinforcing resilience against stockout disruptions during pandemics.

A systematic review was conducted, and a total of 752 articles were analyzed.

Collaborative planning, forecasting and replenishment practices are under-researched in the HCSC literature. Similarly, a fragmented application of extant SC collaborative risk management capabilities undermines efforts to enhance resilience against systematic disruptions from medical stockouts. The paucity of HCSC articles in humanitarian logistics and SC journals indicates a need for more research interlinking two interdependent yet critical fields in responding to pandemics.

Although based on an exhaustive search of academic articles addressing HCSCs, there is a possibility of having overlooked other studies due to search variations in language controls, differences in publication cycle time and database search engines.

The paper relies on COVID-19's uniqueness to highlight the limitations in optimization and individualistic approaches to managing medical inventory and stockout risks in HCSCs. The paper proposes a shift from a fragmented to holistic application of relevant collaboration practices and capabilities to enhance the resilience of HCSCs against stockout ripple effects during future pandemics. The study propositions and suggestion for an SC learning curve provide an interdisciplinary research agenda to trigger early preparation of a coordinated HCSC and humanitarian logistics response to future pandemics.