A Bayesian-based framework for advanced nature-based tourism model

Isfahani, Roxana Norouzi; Malmiri, Ahmad Talaee; BahooToroody, Ahmad; Abaei, Mohammad Mahdi

doi:10.1108/jabes-11-2020-0119

Cited by 5 publications

(4 citation statements)

References 39 publications

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“…Bayesian Belief Network (BBN) is a graphical model used to represent interactions between variables, incorporating arrows and nodes (Isfahani, et al, 2023). BBN combines two critical aspects of decision-making: qualitative and quantitative.…”

Section: Bayesian Belief Networkmentioning

confidence: 99%

Predicting Women's Involvement for Sustainable Tourism in the Local Economy: A Bayesian Network Approach

Krisnayanti,

Saskara

2024

JEP

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This study aims to explore the main factors influencing women's involvement and analyze the interaction between variables to develop policy recommendations that enhance women's involvement in tourism sustainability in Penglipuran Village. This research will use prospective analysis methods, specifically MICMAC Analysis and Bayesian Belief Network (BBN). The study's results identified several potential variables affecting women's involvement, such as awig-awig, gender equality, women empowerment, infrastructure, customary institutions, skills, and culture. Additionally, the study discusses how managing five key nodes with a 100% probability led to a 20% increase in women’s engagement and a 5% increase in tourism sustainability. The findings of this study emphasize the crucial role of handling infrastructure and customary institutions supporting women's tourism involvement. Women are expected to have equal access to resources and opportunities, alongside promoting women’s empowerment.

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Section: Bayesian Belief Networkmentioning

confidence: 99%

Predicting Women's Involvement for Sustainable Tourism in the Local Economy: A Bayesian Network Approach

Krisnayanti,

Saskara

2024

JEP

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“…The tourism sector, as a multi-billion-dollar industry generating 10% of global GDP (Lane 2018 ), has made governments and private SMEs for supplying their capacities (Norouzi Isfahani et al 2021 ). Owing to new problems such as the Covid-19 pandemic and its bidirectional causality with tourism (Shahzad et al 2022 ), this sector requires novel platforms to enhance its sustainable experiences in the future years (Milwood and Maxwell 2020 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Assessment of innovative strategies to improve the tourism sector in Iran

Mahdinia

Daneshvar²

2022

SN Bus Econ

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In the present study, an expert empirical analysis was carried out to assess the innovative strategies to improve the employment rate in the tourism small- and medium-sized enterprises (SMEs) of Iran. The methodology of this paper was extended based on two qualitative and quantitative techniques, namely strengths, weaknesses, opportunities, and threats and quantitative strategic planning matrix. Within this context, three strategies were chosen based on the sum of total attractiveness scores to increase more creation of new jobs and employment positions in tourism SMEs. Two aggressive and competitive strategies were entitled as ‘developing financial support to create the new job and employment positions using tourist’s finances’ and ‘defining smart skills and technologies to improve tourism SMEs toward the pandemic impacts’ in addition to a conservative strategy of ‘providing training support and education technology in the tourism SMEs. Results revealed that the contribution of total direct (indirect) employment to gross domestic product could be anticipated to equal 5.34% (14.86%) in the status quo (2020) by an enhanced rate of 1.97 (2.09) times compared with 2015. Ultimately, technological approaches were described under the innovative strategies to enhance new jobs and employment creation in the tourism SMEs of Iran.

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“…It requires careful coordination between various institutions, program activities, policies, and an understanding of future changes [10]. Effective management of advanced and sustainable rural tourism necessitates a structured governance approach [3] that considers all stages and processes systematically [11].…”

Section: Introductionmentioning

confidence: 99%

“…To address this, the research will utilize the Bayesian Belief Network or Bayesian Network for short, as a suitable tool. Given the complexity and uncertainty inherent in the tourism system [12]; [13]; [14], particularly concerning tourist preferences, loyalty, arrivals, and behavior [3], a Bayesian network model (Bayesian Belief Network-BBN) will be employed for analysis. Bayesian methods excel in handling uncertainty and aiding decision-making processes.…”

Section: Introductionmentioning

confidence: 99%

From Traditional to Thriving: Predicting Rural Tourism Sustainability in Water Based Tourism of Kedung Ombo, Indonesia Using Bayesian Networks

2024

International Conference Proceedings BISET-24, BCBES-24, LEHS2-24 &Amp; BEMEL-24 April 24-26, 2024 Barcelona (Spain)

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Rural tourism is growing in Indonesia as an engine of rural development, offering a mix of nature, culture, and authentic experiences. The Kedung Ombo reservoir area in Central Java Province is one of the rural areas with great tourism potential, providing a variety of attractions like water tourism, culinary experiences, nature exploration, and agro-tourism. Despite its potential for rural development, rural tourism in Kedung Ombo faces challenges due to complex interactions among nature, stakeholders, and institutional aspects. This study aims to identify key factors for effective management of the tourist village in this area, exploring the relationships between tourism management components, external and internal conditions, and their impact on the environment to promote sustainable village tourism. Using the Bayesian Network as a tool, the research reveals that the sustainability of rural water-based tourism in Kedung Ombo relies on factors such as financial incentives, stakeholder engagement, business scale, supporting infrastructure, and the environmental aspect of the reservoir. Valuable insights from this research can improve rural tourism management not only in this area but also in similar destinations.

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A Bayesian-based framework for advanced nature-based tourism model

Cited by 5 publications

References 39 publications

Predicting Women's Involvement for Sustainable Tourism in the Local Economy: A Bayesian Network Approach

Predicting Women's Involvement for Sustainable Tourism in the Local Economy: A Bayesian Network Approach

Assessment of innovative strategies to improve the tourism sector in Iran

From Traditional to Thriving: Predicting Rural Tourism Sustainability in Water Based Tourism of Kedung Ombo, Indonesia Using Bayesian Networks

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