Prediction, explanation and big(ger) data: a middle way to measuring and modelling the perceived success of a volunteer tourism sustainability campaign based on ‘nudging’

Jackson, Steven M.

doi:10.1080/13683500.2014.898616

Cited by 23 publications

(16 citation statements)

References 31 publications

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“…Saito et al (2016), in their study about revenue management, introduced an optimal room charge and expected sales model based on features of the fully transparent hotel booking system. Jackson (2016) discussed the dichotomy between explanation and prediction. The author suggested a middle way to measuring and modelling the perceived success of a volunteer tourism sustainability campaign based on ‘nudging,’ which uses automatic linear modelling that can cope with big data and presents the results as visualisations.…”

Section: Discussionmentioning

confidence: 99%

Automated content analysis: The review of the big data systemic discourse in tourism and hospitality

et al. 2021

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Tourism is one of the economic activities that has changed most since large‐scale multidimensional data set, so‐called big data, was provided. The scientific literature on big data and tourism with the hospitality industry has been growing exponentially, which is, for this reason, hard to comprehend and synthesise manually. Our research question is how to familiarise oneself with the current knowledge of the relationship between the big data and the complex changes in the tourism and hospitality industry. An automated content analysis procedure was used to identify key topics and concepts of interest to the researchers. A careful review of the abstracts and full texts was carried out, resulting in a final list of 308 papers published in 154 journals. We used the Leximancer software 5.0 to create an automated content analysis. Seven topics (tourism, data, search, model, industry, online and travel) from papers published between 2011 and 5/2020 were found. We propose future development trends of big data in sustainable tourism.

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Section: Discussionmentioning

confidence: 99%

Automated content analysis: The review of the big data systemic discourse in tourism and hospitality

et al. 2021

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“…= 0.077], but in this case it is the north which differs from Azores most significantly [t (103) = 4.41, p < 0.001, d = 1.45].Sustainability 2019,11, 947 …”

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confidence: 91%

“…The latest trends explore the use and impact of information and communication technologies [2,3] in these cross-cutting areas. Such is the case of social networks [4][5][6][7], e-WOM [8], applications for mobile devices [9,10], big data [11,12], virtual and augmented reality [13,14] and video games [15,16].…”

Section: Introductionmentioning

confidence: 99%

How Do Destinations Frame Cultural Heritage? Content Analysis of Portugal’s Municipal Websites

Piñeiro-Naval

Serra

2019

Sustainability

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In the current media context, heavily influenced by information and communication technologies, tourism destinations have a need to promote the most outstanding aspects of their cultures to attract the visitors who stimulate their economies. Websites are one of the tools available to carry out this task and they must be designed to communicate the destinations' heritages persuasively to a worldwide audience. Taking these premises into consideration, the objective of this research is to analyze the cultural heritage content on Portugal's municipal websites. The specific goals are to classify the most recurrent heritage elements and detect how they frame identity based on the 'local-global dialectic'. The results show that the heritage discourse is built on the selection of certain aspects-namely, culinary and architectural assets-which are emphasized through the combined use of local and national frames that strengthen the municipalities' particular values but also the fact that they are integrated into a broader and unified whole: Portugal.Sustainability 2019, 11, 947 2 of 18 objectives are to identify the most recurrent cultural and natural heritage assets and the framing of identity in these elements based on the local-global dialectic.The organization of the paper is as follows: we first delve into theoretical synergies between the domains of culture, heritage and tourism, and then consider online communication as one of the core elements of the identity discourse related to these fields. Next, the method used in the research is presented, that is, the quantitative content analysis of the country's 308 websites. The results, which reflect both univariable and multivariable descriptive data, are presented and this is followed by a qualitative discussion. Finally, the conclusions highlight some key ideas derived from the research, as well as theoretical and methodological implications, limitations and future research lines. Literature ReviewThis chapter provides a brief overview of related theoretical work and the state of the art in these fields.2.

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“…Generally speaking, it explores utilization of advanced computational theories or approaches to overcome typical research problems in social science [10], in which sustainability prediction acts as a representative one [11]. Nowadays, researches concerning sustainability prediction were mainly implemented upon the basis of conventional sociological approaches like statistical analysis or case study [12]- [18]. However, limited by manual computing power, these sociological mechanism-based methods usually employed simple mathematical theories to model complex social dynamics process filled with uncertainty and nonlinearity.…”

Section: Introductionmentioning

confidence: 99%

Deep Neural Network-Embedded Internet of Social Computing Things for Sustainability Prediction

Qiao

Song

et al. 2020

IEEE Access

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Social computing, exploiting utilization of advanced computational techniques to overcome typical problems in social science, has been a more visualized conception in academia. However, existing researches still suffer from two aspects of challenges: 1) lack of reliable multi-source data acquisition and management; 2) absence of high-performance algorithmic approaches. Fortunately, some newly-emerged cross-discipline technologies offer more opportunities to enhance conventional solutions. For the former, characterized by its property of information collection and integration, Internet of Things (IoT) can be introduced to produce a novel architecture named Internet of Social Computing Things (IoSCT). For the latter, specific neural network models can be set up to manipulate complicated calculation. Thus, taking the issue of sustainability prediction as objective situation, deep neural network-embedded Internet of Social Computing Things (NeSoc) is proposed in this paper. Firstly, IoSCT is put forward as bottom support platform, guaranteeing comprehensive resource involvement of social computing. Secondly, a hybrid neural network mechanism is formulated and embedded into IoSCT for centralized modeling. Finally, a series of experiments are conducted on a real-world dataset to evaluate performance of the proposed NeSoc.

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Prediction, explanation and big(ger) data: a middle way to measuring and modelling the perceived success of a volunteer tourism sustainability campaign based on ‘nudging’

Cited by 23 publications

References 31 publications

Automated content analysis: The review of the big data systemic discourse in tourism and hospitality

Automated content analysis: The review of the big data systemic discourse in tourism and hospitality

How Do Destinations Frame Cultural Heritage? Content Analysis of Portugal’s Municipal Websites

Deep Neural Network-Embedded Internet of Social Computing Things for Sustainability Prediction

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