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Open Access
Article
Publication date: 18 November 2021

Fauziah Eddyono, Dudung Darusman, Ujang Sumarwan and Fauziah Sunarminto

This study aims to find a dynamic model in an effort to optimize tourism performance in ecotourism destinations. The model structure is built based on competitive performance in…

5113

Abstract

Purpose

This study aims to find a dynamic model in an effort to optimize tourism performance in ecotourism destinations. The model structure is built based on competitive performance in geographic areas and the application of ecotourism elements that are integrated with big data innovation through artificial intelligence technology.

Design/methodology/approach

Data analysis is performed through dynamic system modeling. Simulations are carried out in three models: First, existing simulation models. Second, Scenario 1 is carried out by utilizing a causal loop through innovation of big data-based artificial intelligence technology to ecotourism elements. Third, Scenario 2 is carried out by utilizing a causal loop through big data-based artificial intelligence technology on aspects of ecotourism elements and destination competitiveness.

Findings

This study provides empirical insight into the competitiveness performance of destinations and the performance of implementing ecotourism elements if integrated with big data innovations that will be able to massively demonstrate the growth of sustainable tourism performance.

Research limitations/implications

This study does not use a primary database, but uses secondary data from official sources that can be accessed by the public.

Practical implications

The paper includes implications for the development of intelligent technology based on big data and also requires policy innovation.

Social implications

Sustainable tourism development.

Originality/value

This study finds the expansion of new theory competitiveness of ecotourism destinations.

Details

Journal of Tourism Futures, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2055-5911

Keywords

Article
Publication date: 6 April 2020

Prameswari Purnamadewi Dhisasmito and Suresh Kumar

The purpose of this study is to identify the drivers of loyalty model in the coffee shop industry in Indonesia based on service quality, store atmosphere and price fairness…

4831

Abstract

Purpose

The purpose of this study is to identify the drivers of loyalty model in the coffee shop industry in Indonesia based on service quality, store atmosphere and price fairness mediated by customer satisfaction.

Design/methodology/approach

The sample size used for this study was 384 customers from 16 most comfortable coffee shops in Jakarta based on Nibble's survey. Confirmatory factor analysis was employed to confirm the attributes of each factor and to assess the validity and reliability, average variance extracted and composite reliability was applied. Further hypothesis testing was performed using structural equation modeling.

Findings

The result shows that customer loyalty is affected by service quality – comprising 5 subdimensions: tangible, reliability, responsiveness, assurance and empathy – and price fairness mediated by customer satisfaction. It was found that service quality plays a significant role in the coffee shop industry in Indonesia. However, the store atmosphere was found rejected.

Originality/value

This is the first study integrating service quality, store atmosphere, price fairness and customer satisfaction to study the customer loyalty model in the coffee shop industry in Jakarta.

Details

British Food Journal, vol. 122 no. 7
Type: Research Article
ISSN: 0007-070X

Keywords

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