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Purpose This paper aims to investigate participants’ motivations and perceptions of a field trip. Specifically, this paper examines if and how students’ perceptions change with time and it explores the main factors for ensuring success in an experiential learning tourism program. Design/methodology/approach The study gathered and compared data collected in two points in time – immediately at the end of the experience and two months afterward. T-tests for paired samples were used to examine potential differences in perceptions and principal component analysis was used to identify the key factors determining the success of the experience. Findings The findings indicate that there are various motivations behind participation and that time barely affects perceptions of the experience. Furthermore, three factors emerged as important for meeting expectations, namely, social and professional connections, learning and traditional yet engaging teaching. Research limitations/implications While the outcomes are useful, they need to be thoughtfully applied because of the small data set. It is important to repeat similar investigations to allow more certainty in the propositions formulated. Furthermore, future studies should evaluate a broader variety of outcomes to determine whether perceptions remain constant. The implications are that educators and destination managers can easily apply these conclusions for the benefit and the findings can inform other field trips and broader experiential initiatives. Originality/value Despite research on learning outcomes and perceptions of experiential learning having expanded considerably, a fundamental question that remains unanswered is how perceptions of such experiences change and, consequently, when the most appropriate time is to assess participant perceptions.

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The use of event sponsorship or other types of sponsorship as a means to establish, enhance, or change brand image is a fairly common practice for a variety of organizations. This objective has been identified as one of the two most common goals for organizations to engage in sponsorship programs. The rationale behind the popularity of sponsorship as a marketing tool to achieve image goals is the general assumption that, by linking a brand to an event, the image of the event can be transferred to the image of the sponsor.Despite the increasing sophistication of event sponsorship and rising academic interest in understanding sponsorship practice, there is still a lack of in-depth understanding of how sponsorship processes work, in particular in what concerns its brand outcomes. The article addresses this issue by documenting, examining, and critically assessing the existing literature. The main explanations of brand image transfer, including theoretical frameworks and models, are presented; empirical research, divided into effectiveness of brand image transfer and the factors affecting such process, is analyzed; and two main issues found in the more recent articles-direction of brand image transfer and multiple sponsorships-are discussed. Finally, existing gaps are identified and research propositions are presented to guide future research.

This paper argues that the analysis of vast amounts of user-generated content, which are currently dominated by text analytics and machine learning, need more methodical incorporation of reliable traditional methodologies to facilitate deeper understanding of concepts and theory building. Specifically, a systematic approach that integrates machine learning and traditional research methods is needed to overcome inherent drawbacks of both approaches. A step-by-step methodological framework for the analysis of online reviews is proposed and demonstrated. An application of the framework with an example drawn from the context of understanding authenticity in dining experiences illustrates its usefulness in the investigation of complex concepts. This paper represents one of the first attempts to systematise an integrated learning approach to understand complex concepts and build theories in tourism and hospitality, contributing to more rigorous procedures for processing and analysing large data sets of user-generated content.

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