Impact of Group Package Tour Dimensions on Customer Satisfaction (an ANNs Application)

Moutinho, Luiz; Caber, Meltem; Silva, Maria Manuela Santos; Albayrak, Tahir

doi:10.3727/108354215x14464845877913

Cited by 6 publications

(5 citation statements)

References 32 publications

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“…Through the model, the multifactorial character of satisfaction as a construct is confirmed, showing the influences existing between the independent variables that condition it. In this sense it is considered that the results obtained are consistent with the elements identified in similar studies in the literature consulted (Buhalis 2000;Echtner and Ritchie 1993;Kozak and Rimmington 1998;Lin, Lee and Chen 2009;Moutinho Luiz et al 2015;Tosun et al 2015;Wang et al 2000;Wang et al 2007;Wang et al 2013). Differences are associated with the results of one or another author regarding the attributes considered or the nomenclature used to name them, but in general they coincide in the latent variables considered as those of attraction, access, lodging and facilities.…”

Section: Discussionsupporting

confidence: 65%

“…The most significant changes are observed in not considering variables such as the influence of intermediaries, marketing variables (Buhalis 2000;Moutinho Luiz et al 2015), the reputation of the destination or the trading price (Echtner and Ritchie 1993). These attributes were considered in the initial list but the experts proposed to exclude them from the analysis, mentioning that they were largely beyond the reach of destination management since there was no high probability of influencing them.…”

Section: Discussionmentioning

confidence: 99%

“…According to previous research (Buhalis 2000;Moutinho Luiz et al 2015) the results could be considered incomplete by not considering the effects of variables such as fate reputation, marketing mechanisms and price aspects that could be object of future research to analyse the effects of introducing these variables into the analysis.…”

Section: Limitations and Recommendationsmentioning

confidence: 99%

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Structural Equation Model: Influence on Tourist Satisfaction With Destination Atributes

Pérez-Campdesuñer¹,

García-Vidal²,

Sánchez-Rodríguez³

et al. 2017

Tour. hosp. manag.

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Purpose -To present a model that expresses the relationships observed between a set of independent variables that condition overall satisfaction with a tourist destination, allowing to discover the potential for improvement of this indicator. Methodology -An instrument is designed to measure the satisfaction of tourists with a destination, starting from a list of attributes used in the literature that are submitted to the research of experts. A reliability analysis of the results and an evaluation of construct validity were performed. Through a confirmatory factor analysis, the factorial structure of the set of observed variables was identified. Finally, a structural equations model was created to understand the interrelationship between the variables considered in the study and their incidence in general satisfaction with the destination. Findings -The application of the instrument designed to the calculated sample allowed to identify the latent variables existing in the practical construct studied, identifying through the factorial analysis four aspects associated to the satisfaction of tourists with the destination: access, lodging, facilities and attractions. The construction of the structural equations model corroborated the previous results and evidenced the level of incidence of each factor studied in the overall satisfaction as well as the incidence of each attribute in the factor that integrates. Originality -It is achieved define a structural equations model that represents and explains the relationship between the variables considered in the quality management of a destination and the degree to which they relate to each other and influence the level of satisfaction experienced by tourists.

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Section: Discussionsupporting

confidence: 65%

Section: Discussionmentioning

confidence: 99%

Section: Limitations and Recommendationsmentioning

confidence: 99%

See 1 more Smart Citation

Structural Equation Model: Influence on Tourist Satisfaction With Destination Atributes

Pérez-Campdesuñer¹,

García-Vidal²,

Sánchez-Rodríguez³

et al. 2017

Tour. hosp. manag.

View full text Add to dashboard Cite

show abstract

“…A large proportion of articles addresses the theme of “performance” and analyzes which variables affect tourism-business outcomes within a competitive environment. Among the areas that have received most attention in this regard are the quality of hotel services, and hotel attributes and efficiency, in addition to the identification of factors determining tourist satisfaction and appropriate strategic decision-making (Moutinho et al , 2015). The most common types of analysis are spatial (Supak et al , 2015), cluster (Brida et al , 2012), textual (Krawczyk and Xiang, 2016), time series (Claveria and Torra, 2014), fuzzy system (Shahrabi et al , 2013) and photo-sharing analysis (García-Palomares et al , 2015).…”

Section: Mapping the Co-word Analysismentioning

confidence: 99%

Big data in tourism marketing: past research and future opportunities

Blanco-Moreno

González-Fernández

Gallego

2023

SJME

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Purpose The purpose of this study was to uncover representative emergent areas and to examine the research area of marketing, tourism and big data (BD) to assess how these thematic areas have developed over a 27-year time period from 1996 to 2022. This study analyzed 1,152 studies to identify the principal thematic areas and emergent topics, principal theories used, predominant forms of analysis and the most productive authors in terms of research. Design/methodology/approach The articles for this research were all selected from the Web of Science database. A systematic and quantitative literature review was performed. This study used SciMAT software to extract indicators. Specifically, this study analyzed productivity and produced a science map. Findings The findings suggest that interest in this area has increased gradually. The outputs also reveal the innovative effort of industry in new technologies for developing models for tourism marketing. Ten research areas were identified: “destination marketing,” “mobility patterns,” “co-creation,” “gastronomy,” “sustainability,” “tourist behavior,” “market segmentation,” “artificial neural networks,” “pricing” and “tourist satisfaction.” Originality/value This work is unique in proposing an agenda for future research into tourism marketing research with new technologies such as BD and artificial intelligence techniques. In addition, the results presented here fill the current gap in the research since while there have been literature reviews covering tourism with BD or marketing, these areas have not been studied as a whole.

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“…However, the experiences of Chinese package tourists may be influenced and even constrained by a number of factors. These include their limited time in Australia (South Australian Tourism Commission, 2013); operational and managerial difficulty in standardizing and monitoring service due to the just-in-time service promises (Moutinho et al, 2015) and the practice of commission tours where tour operators offer very-low-priced tours and try to reap profits through commissions from shopping and/or entertainment activities (Zhang et al, 2009). These factors, especially commission tours, have resulted in tourist dissatisfaction and associated complaints, which include overpricing of tourist goods, changing and downgrading itineraries at the destination, arranging shopping venues favoured by the tour operator, misguiding and deceiving tourists into the purchase of expensive goods, the misrepresentation of information in the source market by tour operators and even forced shopping (Dwyer et al, 2004, 2007; Keating, 2009; Prideaux et al, 2006; Wang et al, 2015; Zhang and Murphy, 2009).…”

Section: Introductionmentioning

confidence: 99%

Examining service shortfalls

Chen

Weiler

Young

2018

Journal of Vacation Marketing

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Chinese inbound tourism constitutes Australia’s fastest growing and largest international tourist market. Currently, most of this travel is conducted via group package tours (GPTs). While there is anecdotal evidence of dissatisfaction with some aspects of Chinese tourists’ service experience such as commission-based shopping, little empirical evidence is available about the salient dimensions of service quality or their respective performance. The aim of this study is to identify the core service components offered by Chinese GPTs and to examine any service shortfalls. Findings from a survey of 520 tourists revealed three dimensions of Chinese package tour service: attractions, tour leader and food and accommodation. The study identified significant gaps between expectation and performance across all dimensions. Theoretical and service quality implications for researchers, tour operators and policymakers are presented and discussed.

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Impact of Group Package Tour Dimensions on Customer Satisfaction (an ANNs Application)

Cited by 6 publications

References 32 publications

Structural Equation Model: Influence on Tourist Satisfaction With Destination Atributes

Structural Equation Model: Influence on Tourist Satisfaction With Destination Atributes

Big data in tourism marketing: past research and future opportunities

Examining service shortfalls

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