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This study integrates previous research on the intention to use Airbnb to determine which antecedents provide a parsimonious explanation.

Meta-analyses based on 61 samples estimate how 8 antecedents are associated with the intention to use Airbnb. Subsequent analyses utilize meta-analyses to estimate a regression model to simultaneously estimate the relationship between the antecedents and the intention to use Airbnb. Relative weight analysis then determined each antecedent’s utility.

A parsimonious model with only four antecedents (hedonic motivation, price value, effort expectancy and social influence) was nearly as predictive as the full eight-antecedent model. Ten moderating variables were examined, but none were deemed to consistently influence the relationships between the antecedents and the intention to use Airbnb.

Relatively few measures (i.e. four) effectively explain customers’ intentions to use Airbnb. When these measures cannot be readily influenced, alternatives are also presented. Implications for the travel industry are considered and straightforward approaches to increasing users are presented.

This is the first integrative review of customers’ intentions to use Airbnb. We integrate what is currently known about customers’ intentions to use Airbnb and then provide a robust model for Airbnb use intentions that both researchers and practitioners can utilize.

This study aims to integrate extant research on eWallet adoption to better understand the key antecedents to eWallet use intention and examine whether the relationships differ across multiple moderators.

To integrate eWallet adoption findings, the unified theory of acceptance and use of technology (UTAUT) and its extensions were utilized. Meta-analyses estimated the relationships between eWallet use intention and seven antecedents and the intercorrelations between antecedents. A total of 28 effects were calculated, utilizing 48 studies and 444 individual effect sizes, using 14,802 subjects. Using meta-analytically derived values, regression and relative weight analysis then determined each antecedent's relative utility. Furthermore, moderator analyses examined whether eight theoretically based moderators influenced the relationships between the antecedents and eWallet use intention.

Price value, hedonic motivation, facilitating conditions and social influence had the strongest relationships with the intention to use eWallets, accounting for virtually all the unique variance. The three weakest antecedents, however, still explained a large percentage of variance. No relationships were significantly moderated.

Due to the lack of data in primary studies, some UTAUT moderators could not be analyzed. Also, common method variance may impact the findings because the primary studies used cross-sectional surveys.

This study provides guidance regarding how companies can increase eWallet adoption rates, which have lagged in certain countries. These recommendations include specific techniques for tailoring messages and emphasizing features and benefits.

To the best of the authors’ knowledge, this is the first integrative meta-analysis conducted on eWallet use. Combining meta-analysis, regression and relative weight analysis, this study provides an integration of what is currently known about eWallet use intentions.

This study examines antecedents to fintech use intention to determine which antecedents can provide a parsimonious, yet accurate explanation.

Meta-analyses based on 42 samples estimate how seven antecedents are associated with fintech use intentions. Subsequent analyses utilize meta-analyses to estimate a regression analysis to simultaneously estimate the relationship between the antecedents and fintech use intention. Relative weight analysis then determined each antecedent's utility.

Hedonic motivation, price value, performance expectations and social influence had the strongest relationships with intention to use fintech. Further analyses found a parsimonious model with only three antecedents was nearly as predictive as the full seven antecedent model. Four moderating variables were examined but played minor roles.

Common method variance may impact the findings because all primary studies used cross-sectional surveys.

Very few measures (i.e. three) can robustly explain fintech use intention. When these measures cannot be readily influenced, alternatives are also presented.

This is the first integrative review of fintech use intentions. The authors integrate what is currently known about fintech use intentions and then provide a robust model for fintech use intentions that both researchers and practitioners can utilize.

The purpose of this paper is to examine the effects of individual difference variables and social relationships on student learning outcomes of short-term study abroad programs.

This study used a social network analysis (SNA) approach to examine the effects of friendship, advice and communication networks on student learning outcomes.

Results indicated that demographic characteristics (e.g. sex, years of work experience) did not influence learning outcomes nor the enjoyment of the experience. Social networks positively influenced students’ perceived improvement in managerial skills, their ability to reflect on their international experience and their intercultural sensitivity.

Social relationships may be an important factor to consider in understanding the relationship between short-term study abroad programs and learning outcomes.

Program directors and faculty members need to consider the design of assignments and activities that may facilitate the development of specific types of social relationships (e.g. friendship, communication and advice). These specific social relationships may have unique influences on specific learning outcomes of short-term study abroad programs.

This study is the first study that examined the effects of different types of social relationships on learning outcomes for short-term study abroad programs. The results have important implications for both future research and the design of international study-abroad programs.