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The sharing economy enables apartment owners to generate income from their assets. “Agoda Homes” is an online travel agent (OTA) that directly competes with Airbnb. A destination has to discover its competitiveness, but few studies have provided an overview of accommodation attributes in each destination, which are crucial to shaping its brand image. This paper aims to illustrate firm-generated content or attributes that apartment owners list about their properties on an OTA platform to comprehend factual information about apartments in each destination with various star ratings and user ratings and to formulate a research model for future studies.

Informational content and accommodation attributes for apartments are automatically collected using a Web scraping tool (the Data Miner). Descriptive statistics and text analysis (word cloud and word frequency) are used to analyze data.

Findings reveal the primary location, facilities, cleanliness and safety attributes for all apartments in each destination, along with star ratings and user ratings. A research framework for scholars is also suggested. Guidelines for stakeholders in the tourism industry are additionally furnished.

This work concentrates on apartments, which have received less attention in the tourism literature. The study gathers factual data from a website to mitigate respondent bias issues inherent in the traditional survey methods.

Indigenous knowledge is an essential element for unveiling the evolutionary journey of socio-culture phenomena. One of the key challenges in foresight exercises is to incorporate social-culture issues such as culture, lifestyle and behavior (referred as indigenous knowledge) into the study. However, the statistical trends of those factors tend to be either not available or limited unlike the population or economic related factors. The purpose of this study is to present the use of valuable data from indigenous knowledge to enhance the foresight exercise through the better understanding of social dynamics and changes.

The fragmented form of indigenous knowledge is analyzed and converted into a structured data format and then interpreted to unveil the evolutionary journey of socio-cultural phenomena. This study applies a scenario development method to visualize the results of foresight by comparing before and after the integration of indigenous knowledge. Finally, an assessment was conducted to reflect the value enhancement resulting from the integration of indigenous knowledge into the foresight process.

With the proposed approach, the foresight study on the future development of Thai food was demonstrated. The findings of this study show that the use of indigenous knowledge on eating behavior, cooking style and food flavor helps improve the alternative scenarios for the future development of Thai foods.

Indigenous knowledge can be applied to develop plausible scenarios and future images in foresight exercises. However, by nature, indigenous knowledge is not well-structured and, therefore, needs to be analyzed and turned into structured data so that it can be interpreted before integrating into the foresight process.

This study is one of few studies addressing the opportunities for integrating indigenous knowledge into foresight process. Indigenous knowledge can unveil the evolution of socio-cultural changes to improve the results of foresight study, especially the cases where statistical data and trends may not be sufficient to foresee future development.

Transnational migration is a key challenge in migrant-sending and host-receiving countries. However, relatively little is known about how migrants use network capital to foster small and medium-sized enterprises (SMEs) in the ASEAN Economic Community (AEC). Therefore, the purpose of this study is to explore how network capital fosters Laotian migrant workers in Thai family SMEs.

This research was conducted using qualitative network analysis (QNA). Referral snowball sampling was used to draw 20 participants from December 2021 to March 2022. Data analysis was performed using Gephi, a software package developed for QNA (coding, network features, measure nodes and network metrics).

The main findings are the following four emerging themes: chain networks, social networks, human networks and financial networks are associated with network capital for fostering Laotian migrant workers in Thai family SMEs.

To the best of the authors’ knowledge, this study is the first QNA to explore how Laotian migrant workers use network capital in Thai family SMEs.

The growth of the internet has transformed digital infrastructure in Thailand over the past two decades, with the widespread use of e-commerce, digital money and online services becoming a daily norm for all ages. The COVID-19 restrictions, which limited in-person business operations, boosted demand for takeout and delivery services and fueled the expected steady growth of the online food delivery market in Thailand. The pandemic also resulted in a shift towards online ordering and delivery, reflecting changes in customer behavior. This study focuses on exploring the factors that have driven Bangkokians to use online food delivery services after the COVID-19 restrictions were lifted in June 2022.

Data were collected from 398 participants who had ordered food delivery services after the announcement.

The findings showed that perceived usefulness, time saving benefit and price saving benefit have a significant impact on the intention of customers to use online food delivery services, while food safety risk perception had no effect.

Bangkokians favor online food delivery services due to convenience and time-saving, indicating high demand post-pandemic. Businesses should invest in improving their platforms to meet evolving consumer behavior.

The result of this study offers valuable insights into the attitudes and behaviors of Bangkokians towards online food delivery services and could be beneficial for businesses in the industry to improve their services, enhance customer satisfaction as well as increase their competitiveness.

The purpose of this study was to investigate the factors impacting the intermediating variable of employee engagement toward employee performance in a hybrid working organization in Bangkok, Thailand.

This study uses secondary data analysis and an archival study; the primary data were gathered from 370 employees who are working in a hybrid model environment in a private agricultural machinery company. To construct a new conceptual framework, this study adopted four frameworks from the previous research.

Perceived organizational support and trust and respect in the organization are found to have a significant positive impact on employee engagement. Moreover, there is a significant positive impact of the employee engagement on employee performance in a hybrid working model.

For hybrid work environments, the research focused mainly on the emotional themes of perceived support, trust and respect in the organization. Therefore, there would be many factors that could possibly affect those dependence variables in any environment, which will have to be investigated more in future research. Either in the organization or in the company, many departments and business units operates for the company, but the researcher specifies only the business units or departments that now use the hybrid working model.

This study focuses on a case study of an agricultural machinery company, which likely produces different results than other industries, other industries may produce different results.

Hybrid working models can blur the boundaries between work and personal life, potentially leading to increased stress and burnout. Organizations should prioritize work-life balance and employee well-being by promoting flexible schedules, encouraging breaks and time off, and providing resources for mental health support.

The organization which is operating among a hybrid working model, the increasing of perceived organizational support and trust and respect level, has positively increase the employee engagement toward enhancing the employee performance.

Confidence intervals play a crucial role in economics and finance, providing a credible range of values for an unknown parameter along with a corresponding level of certainty. Their applications encompass economic forecasting, market research, financial forecasting, econometric analysis, policy analysis, financial reporting, investment decision-making, credit risk assessment and consumer confidence surveys. Signal-to-noise ratio (SNR) finds applications in economics and finance across various domains such as economic forecasting, financial modeling, market analysis and risk assessment. A high SNR indicates a robust and dependable signal, simplifying the process of making well-informed decisions. On the other hand, a low SNR indicates a weak signal that could be obscured by noise, so decision-making procedures need to take this into serious consideration. This research focuses on the development of confidence intervals for functions derived from the SNR and explores their application in the fields of economics and finance.

The construction of the confidence intervals involved the application of various methodologies. For the SNR, confidence intervals were formed using the generalized confidence interval (GCI), large sample and Bayesian approaches. The difference between SNRs was estimated through the GCI, large sample, method of variance estimates recovery (MOVER), parametric bootstrap and Bayesian approaches. Additionally, confidence intervals for the common SNR were constructed using the GCI, adjusted MOVER, computational and Bayesian approaches. The performance of these confidence intervals was assessed using coverage probability and average length, evaluated through Monte Carlo simulation.

The GCI approach demonstrated superior performance over other approaches in terms of both coverage probability and average length for the SNR and the difference between SNRs. Hence, employing the GCI approach is advised for constructing confidence intervals for these parameters. As for the common SNR, the Bayesian approach exhibited the shortest average length. Consequently, the Bayesian approach is recommended for constructing confidence intervals for the common SNR.

This research presents confidence intervals for functions of the SNR to assess SNR estimation in the fields of economics and finance.

The present article seeks to further the analysis by examining the epitext employed by the press seeing as the epitext in the digital spaces might have given Animal Farm and its Thai re-translations a new lease on life.

The interest in the study of translation and paratext has primarily been in analysing peritextual material of translated texts, not on the epitext, the distanced elements located outside the book. To add to a limited amount of research into epitext, this study focusses on the element that is external to the published re-translations: the news items published by the media in the Thai and English languages from May–June 2019, immediately after the Thai PM’s book recommendation.

These news items, as an epitextual element, primed, explained, contextualised, justified and tempted readers. The “Afterlife” of Animal Farm in Thailand is sustained by political upheavals and re-translations. Rather than through their textual qualities, the re-translations of Animal Farm compete with each other through epitext.

In discussing literary re-translation of Animal Farm in the digital age, Genette’s categories of paratextual field are not without their merits. The materials examined in this article are posted by web administrators with collective identity or institutional affiliation. In some of these news items or articles, materials created by different paratextual creators are selectively coalesced within a singular textual space. The site users or news readers encounter various elements in the texts that had been curated by journalists. In other words, these elements had been consciously crafted.

In Thailand, the number of higher education institutions (HEIs) offering international programmes has surged dramatically. Internationalisation is seen as key to competing in the higher education market, modernising educational programming, and generating new streams of revenue. Yet, such rapid change is disorientating for the internationalisation of higher education (IHE) in the Thai context. That said, there is little disagreement on what it is not; it is not Thai. This chapter investigates apparent efforts to ‘de-place’ Thailand from IHE and considers how these attempts may connect to (post-)colonial tensions between sovereignty and civilisation. Through a synthesis of scholarship in the areas of higher education, cultural geography and Thai studies, the authors construct a framework for exploring how IHE is both imagined and experienced in Thailand. In particular, they re-examine datasets from studies they conducted with stakeholders over recent years, including executive leadership, international faculty members, and university students. Through a series of narrative portraits, a dialogue of voices is constructed that reflect distinct orientations to ‘Thainess’ in the IHE. The authors argue that a wider and more inclusive orientation to internationalisation is not only respectful of local identity but is enhanced by it. Ultimately, the hope of this study is to offer a vision of what an ‘emplaced’ idea of IHE in Thailand might look like, one grounded in an orientation unique to a particular place with its own cultural and social coordinates.

The purpose of this study is to shed light on the impact of economic policy uncertainty (EPU) on asset redeployability. Capitalizing on a novel measure of asset redeployability, the authors explore the effect of economic policy uncertainty (EPU) on redeployable assets using a unique text-based measure of EPU. Asset redeployability is an important aspect of sustainability that has been largely overlooked. More redeployable assets can be repurposed for a variety of uses, lessening the necessity for new products and thus conserving natural resources.

In addition to the standard regression analysis, the authors execute a variety of robustness checks, i.e. propensity score matching, entropy balancing, instrumental-variable analysis, GMM dynamic panel data analysis and use Oster’s (2019) approach for testing coefficient stability. Importantly, the authors incorporate firm fixed effects in the analysis, which helps mitigate endogeneity due to unobservable firm characteristics.

Based on an immense sample of over 200,000 observations over three decades, the results reveal that greater uncertainty raises asset redeployability significantly. The findings corroborate the managerial prudence hypothesis. The future deployment of assets is less predictable in times of increased uncertainty. Consequently, during uncertain times, it is more prudent to have assets that can be redeployed for multiple purposes.

To the best of the authors’ knowledge, this is the first study to explore the impact of EPU on asset redeployability, which is a critical aspect of sustainability that has rarely been investigated in the literature. The authors fill this important void in the literature. The authors extend the literature in EPU, asset redeployability as well as sustainability.