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While service failures and recoveries (SFR) constitute a well-explored research domain, such negative consumption experiences have been understudied in the luxury context. The current study undertakes a systematic review to capture current knowledge and stimulate research in this vital domain.

This study adopts a systematic literature review methodology and employs the Theory-Context-Characteristics-Methods (TCCM) framework.

Guiding theories, industry and national contexts, relevant constructs and their relationships, and research methods employed in studying SFR in luxury consumption are identified and synthesized.

A comparative analysis of the luxury SFR with broader extant knowledge is offered. Further, hospitality is revealed as the dominant context, meriting its emphasis.

This study aims to explore when and for what purpose is social media used by tourists in their decision-making; and to further interpret the nature of such usage.

An online questionnaire was administered to 530 Indians who qualified as recent tourists and social media users. Partial least square structural equation modeling (PLS-SEM) is used to analyse hypothesised relationships; the results helped us to unveil the tourist social media cycle which is a conceptual model of the results obtained.

PLS-SEM results indicate that social media is predominantly used in the pre-travel stage for evaluation purposes, during travel stage for purchase purposes and post-travel stage for post-purchase behaviour. Also, it is noted that social media use by a tourist is an ongoing process, and thus, a conceptual model in the form of tourist social media cycle is unveiled.

This study reveals the unique behaviour of Indian tourists with respect to using social media for travel decision-making, which establishes a different perspective of understanding and further strategizing social media’s use in tourism for a developing nation. Also, the tourist social media cycle stresses on the importance of social media as a digital repository where continuously the user-generated content is used by self (existing) or “others” (potential tourists).

To the best of the author’s knowledge, this is the first study that addresses the population and knowledge gap of understanding social media–based tourist behaviour providing a perspective of a developing nation, specifically India. Further, it unveils the nature of social media use by tourist in the form of a first ever tourist social media cycle.

Past research often relies on linear relationship assumptions from the perspective of managers when studying the relationship between attribute performance and satisfaction. However, this study extracts tourists’ online reviews to explore asymmetric relationships and identifies island tourism satisfiers, hybrids and dissatisfiers.

The research uses 3,523 reviews from Tripadvisor to examine Langkawi Island’s tourist satisfaction. Latent Dirichlet allocation (LDA) machine-learning approach, penalty–reward contrast analysis and asymmetric impact-performance analysis (AIPA) were employed to extract and analyse the data.

Langkawi’s dissatisfiers included “hotel and restaurant”, “beach leisure”, “water sport”, “snorkelling”, “commanding view”, “waterfall”, “sky bridge walk”, “animal show”, “animal feeding”, “history culture”, “village activity” and “duty-free mall”. Amongst these, five were low performers. Hybrids encompassed “ticket purchasing”, “amenity” “traditional food market” and “gift and souvenir”, all of which were low performers. Only one attribute was categorised as a satisfier: “nature view” which performed exceptionally well.

This study provides recommendations to enhance tourist satisfaction and address tourist dissatisfaction. The elements requiring immediate attention for enhancement are the five low-performance dissatisfiers, as they represent tourists’ fundamental expectations. Conversely, the satisfier or excitement factor (i.e. nature views – mangroves and wildlife) could be prominently featured in promotional materials.

This research constitutes an early endeavour to categorise attributes of island tourism into groups of satisfaction, hybrid or dissatisfaction based on user-generated data. It is underpinned by two-factor and three-factor theories.