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Article
Publication date: 25 March 2024

Zhixue Liao, Xinyu Gou, Qiang Wei and Zhibin Xing

Online reviews serve as valuable sources of information, reflecting tourists’ attentions, preferences and sentiments. However, although the existing research has demonstrated that…

Abstract

Purpose

Online reviews serve as valuable sources of information, reflecting tourists’ attentions, preferences and sentiments. However, although the existing research has demonstrated that incorporating online review data can enhance the performance of tourism demand forecasting models, the reliability of online review data and consumers’ decision-making process have not been given adequate attention. To address the aforementioned problem, the purpose of this study is to forecast tourism demand using online review data derived from the analysis of review helpfulness.

Design/methodology/approach

The authors propose a novel “identification-first, forecasting-second” framework. This framework prioritizes the identification of helpful reviews through a comprehensive analysis of review helpfulness, followed by the integration of helpful online review data into the forecasting system. Using the SARIMAX model with helpful online review data sourced from TripAdvisor, this study forecasts tourist arrivals in Hong Kong during the period from August 2012 to June 2019. The SNAÏVE/SARIMA model was used as the benchmark model. Additionally, artificial intelligence models including long short-term memory, back propagation neural network, extreme learning machine and random forest models were used to assess the robustness of the results.

Findings

The results demonstrate that online review data are subject to noise and bias, which can adversely affect the accuracy of predictions when used directly. However, by identifying helpful online reviews beforehand and incorporating them into the forecasting process, a notable enhancement in predictive performance can be realized.

Originality/value

First, to the best of the authors’ knowledge, this study is one of the first to focus on the data issue of online reviews on tourism arrivals forecasting. Second, this study pioneers the integration of the consumer decision-making process into the domain of tourism demand forecasting, marking one of the earliest endeavors in this area. Third, this study makes a novel attempt to identify helpful online reviews based on reviews helpfulness analysis.

Details

Nankai Business Review International, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-8749

Keywords

Article
Publication date: 1 April 2024

Xiaoxian Yang, Zhifeng Wang, Qi Wang, Ke Wei, Kaiqi Zhang and Jiangang Shi

This study aims to adopt a systematic review approach to examine the existing literature on law and LLMs.It involves analyzing and synthesizing relevant research papers, reports…

Abstract

Purpose

This study aims to adopt a systematic review approach to examine the existing literature on law and LLMs.It involves analyzing and synthesizing relevant research papers, reports and scholarly articles that discuss the use of LLMs in the legal domain. The review encompasses various aspects, including an analysis of LLMs, legal natural language processing (NLP), model tuning techniques, data processing strategies and frameworks for addressing the challenges associated with legal question-and-answer (Q&A) systems. Additionally, the study explores potential applications and services that can benefit from the integration of LLMs in the field of intelligent justice.

Design/methodology/approach

This paper surveys the state-of-the-art research on law LLMs and their application in the field of intelligent justice. The study aims to identify the challenges associated with developing Q&A systems based on LLMs and explores potential directions for future research and development. The ultimate goal is to contribute to the advancement of intelligent justice by effectively leveraging LLMs.

Findings

To effectively apply a law LLM, systematic research on LLM, legal NLP and model adjustment technology is required.

Originality/value

This study contributes to the field of intelligent justice by providing a comprehensive review of the current state of research on law LLMs.

Details

International Journal of Web Information Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1744-0084

Keywords

Book part
Publication date: 8 April 2024

Eva Kotlánová

Factors of production (labour, land, capital), technology and technical progress are usually cited as the main sources of economic growth and development. However, there are a…

Abstract

Factors of production (labour, land, capital), technology and technical progress are usually cited as the main sources of economic growth and development. However, there are a number of other factors that have a significant impact on the possibilities and extent of their use or their further improvement and development. These factors undoubtedly include the institutional environment, within which corruption is also a consideration. In this chapter, attention will be focused on the various institutional variables that are used to assess the quality of a country's institutional environment, including corruption. A number of studies have shown that a quality institutional environment and low levels of corruption are prerequisites for long-term economic growth. Using an analysis of individual indicators of the Worldwide Governance Indicators (WGIs), published annually by the World Bank, supplemented by the Corruption Perception Index (published by Transparency International), we look at where Czechia has moved over the last decade or two in terms of institutional quality and corruption.

Open Access
Article
Publication date: 16 January 2024

Erose Sthapit, Chunli Ji, Yang Ping, Catherine Prentice, Brian Garrod and Huijun Yang

Drawing on the theory of memory-dominant logic, this study aims to examine how the substantive staging of the servicescape, experience co-creation, experiential satisfaction and…

Abstract

Purpose

Drawing on the theory of memory-dominant logic, this study aims to examine how the substantive staging of the servicescape, experience co-creation, experiential satisfaction and experience intensification affect experience memorability and hedonic well-being in the case of unmanned smart hotels.

Design/methodology/approach

An online survey was used, with the target respondents being hotel guests people aged 18 years and older who had been recent guests of the FlyZoo Hotel in Hangzhou, China. Data were collected online from 429 guests who had stayed in the hotel between April and June 2023. Data analysis was undertaken using structural equation modelling.

Findings

The results suggest that all the proposed four constructs are positive drivers of a memorable unmanned smart hotel experience. The relationship between the memorability of the hotel experience and hedonic well-being was found to be significant and positive.

Practical implications

Unmanned smart hotels should ensure that all smart technologies function effectively and dependably and offer highly personalised services to guests, allowing them to co-create their experiences. This will lead to the guest receiving a satisfying and memorable experience. To enable experience co-creation using smart technologies, unmanned smart hotels could provide short instructional videos for guests, as well as work closely with manufacturers and suppliers to ensure that smart technology systems are regularly updated.

Originality/value

This study investigates the antecedents and outcomes of a novel phenomenon and extends the concept of memorable tourism experiences to the context of unmanned smart hotels.

Details

International Journal of Contemporary Hospitality Management, vol. 36 no. 13
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 14 December 2023

Huaxiang Song, Chai Wei and Zhou Yong

The paper aims to tackle the classification of Remote Sensing Images (RSIs), which presents a significant challenge for computer algorithms due to the inherent characteristics of…

Abstract

Purpose

The paper aims to tackle the classification of Remote Sensing Images (RSIs), which presents a significant challenge for computer algorithms due to the inherent characteristics of clustered ground objects and noisy backgrounds. Recent research typically leverages larger volume models to achieve advanced performance. However, the operating environments of remote sensing commonly cannot provide unconstrained computational and storage resources. It requires lightweight algorithms with exceptional generalization capabilities.

Design/methodology/approach

This study introduces an efficient knowledge distillation (KD) method to build a lightweight yet precise convolutional neural network (CNN) classifier. This method also aims to substantially decrease the training time expenses commonly linked with traditional KD techniques. This approach entails extensive alterations to both the model training framework and the distillation process, each tailored to the unique characteristics of RSIs. In particular, this study establishes a robust ensemble teacher by independently training two CNN models using a customized, efficient training algorithm. Following this, this study modifies a KD loss function to mitigate the suppression of non-target category predictions, which are essential for capturing the inter- and intra-similarity of RSIs.

Findings

This study validated the student model, termed KD-enhanced network (KDE-Net), obtained through the KD process on three benchmark RSI data sets. The KDE-Net surpasses 42 other state-of-the-art methods in the literature published from 2020 to 2023. Compared to the top-ranked method’s performance on the challenging NWPU45 data set, KDE-Net demonstrated a noticeable 0.4% increase in overall accuracy with a significant 88% reduction in parameters. Meanwhile, this study’s reformed KD framework significantly enhances the knowledge transfer speed by at least three times.

Originality/value

This study illustrates that the logit-based KD technique can effectively develop lightweight CNN classifiers for RSI classification without substantial sacrifices in computation and storage costs. Compared to neural architecture search or other methods aiming to provide lightweight solutions, this study’s KDE-Net, based on the inherent characteristics of RSIs, is currently more efficient in constructing accurate yet lightweight classifiers for RSI classification.

Details

International Journal of Web Information Systems, vol. 20 no. 2
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 5 September 2023

Haitian Wei, Rasidah Mohd-Rashid and Chai-Aun Ooi

As a consequence of the proposal of the Carbon Neutral and Carbon Peak policy in 2020, the Chinese Government is paying more attention to developing sustainability performance…

Abstract

Purpose

As a consequence of the proposal of the Carbon Neutral and Carbon Peak policy in 2020, the Chinese Government is paying more attention to developing sustainability performance. This study aims to assess the direct influence of country-level and corporate anti-corruption measures on environmental, social and governance (ESG) and its three dimensions, besides ascertaining the moderating role of firm size.

Design/methodology/approach

This study used the system generalized method of moments on a sample of 820 Chinese listed firms from 2012 to 2021.

Findings

The findings show that country-level and corporate corruption negatively affect ESG performance. Corporate anti-corruption measures have a more pronounced positive influence on the sustainability performance of small firms than large firms due to the limited resources, lower political position and weaker refusal power of small firms.

Research limitations/implications

The study has great implications for governments, corporate boards and ESG rating agencies. Government and corporate boards should mitigate the risks of country-level and corporate corruption to attain sustainable development goals. Rating agencies should add country-level and corporate corruption into the ESG evaluation system.

Originality/value

Some empirical results have proven that anti-corruption measures help reduce the emission of carbon dioxide, but few evidence shows how country-level and corporate corruption affect ESG and its three dimensions.

Details

Journal of Money Laundering Control, vol. 27 no. 3
Type: Research Article
ISSN: 1368-5201

Keywords

Article
Publication date: 7 July 2023

Xiaojie Xu and Yun Zhang

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important…

Abstract

Purpose

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important issue to investors and policymakers. This study aims to examine neural networks (NNs) for office property price index forecasting from 10 major Chinese cities for July 2005–April 2021.

Design/methodology/approach

The authors aim at building simple and accurate NNs to contribute to pure technical forecasts of the Chinese office property market. To facilitate the analysis, the authors explore different model settings over algorithms, delays, hidden neurons and data-spitting ratios.

Findings

The authors reach a simple NN with three delays and three hidden neurons, which leads to stable performance of about 1.45% average relative root mean square error across the 10 cities for the training, validation and testing phases.

Originality/value

The results could be used on a standalone basis or combined with fundamental forecasts to form perspectives of office property price trends and conduct policy analysis.

Details

Journal of Financial Management of Property and Construction , vol. 29 no. 1
Type: Research Article
ISSN: 1366-4387

Keywords

Book part
Publication date: 4 April 2024

Thomas C. Chiang

Using a GED-GARCH model to estimate monthly data from January 1990 to February 2022, we test whether gold acts as a hedge or safe haven asset in 10 countries. With a downturn of…

Abstract

Using a GED-GARCH model to estimate monthly data from January 1990 to February 2022, we test whether gold acts as a hedge or safe haven asset in 10 countries. With a downturn of the stock market, gold can be viewed as a hedge and safe haven asset in the G7 countries. In the case of inflation, gold acts as a hedge and safe haven asset in the United States, United Kingdom, Canada, China, and Indonesia. For currency depreciation, oil price shock, economic policy uncertainty, and US volatility spillover, evidence finds that gold acts as a hedge and safe haven for all countries.

Details

Advances in Pacific Basin Business, Economics and Finance
Type: Book
ISBN: 978-1-83753-865-2

Keywords

Open Access
Article
Publication date: 17 April 2023

Charles O. Manasseh, Ifeoma C. Nwakoby, Ogochukwu C. Okanya, Nnenna G. Nwonye, Onuselogu Odidi, Kesuh Jude Thaddeus, Kenechukwu K. Ede and Williams Nzidee

This paper aims to assess the impact of digital financial innovation on financial system development in Common Market for eastern and Southern Africa (COMESA). This paper…

2796

Abstract

Purpose

This paper aims to assess the impact of digital financial innovation on financial system development in Common Market for eastern and Southern Africa (COMESA). This paper evaluates the dynamic relationship between digital financial innovation measures and financial system development using time series data from COMESA countries for the period 1997–2019.

Design/methodology/approach

A dynamic autoregressive distributed lag model (ARDL) was adopted and the mean group (MG), pooled mean group (PMG) and dynamic fixed effect (DFE) of the model were estimated to evaluate the short- and long-run impact. In addition, the dynamic generalized method of moments (DGMM) was adopted for a robustness check. The Hausman test results show PMG to be the most consistent and efficient estimator, while the coefficient of lagged dependent variable of different GMM is less than the fixed effect coefficient, and, as such, suggests system GMM is the most suitable estimator. Data for the study were sourced from World Bank Development Indicator (WDI, 2020), World Governance Indicator (WGI, 2020) and World Bank Global Financial Development Database (GFD, 2020).

Findings

The result shows that digital financial innovation significantly impacts financial system development in the long run. As such, the evidence revealed that automated teller machines (ATMs), point of sale (POS), mobile payments (MP) and mobile banking are significant and contribute positively to financial system development in the long run, while mobile money (MM) and Internet banking (INB) are insignificant but exhibit positive and inverse relationship with financial development respectively. Further investigation revealed that institutional quality and a stable macroeconomic environment including their interactive term are significantly imperative in predicting financial system development in the COMESA region.

Practical implications

Researchers recommend a cohesive and conscious policy that would checkmate the divergence in the short run and suggest a common regional innovative financial strategy that could be pursued to incentivize technology transfer needed to promote financial system development in the long run. More so, plausible product and process innovations may be adapted to complement innovative institutions in the different components of the COMESA financial system.

Social implications

Digital financial innovation services if well managed increase the inherent benefits in financial system development.

Originality/value

To the best of the authors’ knowledge, this paper presents new background information on digital financial innovation that may stimulate the development of the financial system, particularly in the COMESA region. It also exposes the relevance of digital financial innovation, institutional quality and stable macroeconomic environment as well as their interactive effect on COMESA financial system development.

Details

Asian Journal of Economics and Banking, vol. 8 no. 1
Type: Research Article
ISSN: 2615-9821

Keywords

Article
Publication date: 25 March 2024

Piyush Ranjan

This study aims to develop a moderated mediation model that enables the examination of the direct relationship between brand orientation (BO) and export performance, the mediating…

Abstract

Purpose

This study aims to develop a moderated mediation model that enables the examination of the direct relationship between brand orientation (BO) and export performance, the mediating effects of external and internal branding capabilities on the BO-export performance link, and the moderating influence of institutional environment, i.e. regulatory turbulence and policy support.

Design/methodology/approach

A time-lag primary data was collected from two-wave survey of 684 cross-industry exporting small and medium-sized enterprises (SMEs) using an online-email based survey technique, and the research model was validated using ordinary least squares regression analysis in SPSSV.27 and Hayes’ PROCESS macroV.2.13.

Findings

Regression findings indicate that the relationship between BO and export performance is not direct, but rather mediated by means of both external and internal branding capabilities. It further helps to uncover the dual role of institutional environment, with regulatory turbulence weakening and policy support strengthening the indirect influences of BO on export performance via external and internal branding capabilities.

Research limitations/implications

This study advances branding literature by conceptualizing and empirically testing the role of BO associated with internal and external branding capabilities and, subsequently, with export performance.

Practical implications

The research findings indicate that brand-oriented SMEs must actively engage in the development of branding capabilities to improve their export performance.

Originality/value

While brand creation is essential for the success and growth of SMEs competing in the worldwide marketplaces, there is a dearth of research explaining the underlying mechanisms and boundary conditions through which BO influences export performance.

Details

International Marketing Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0265-1335

Keywords

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