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A flexible decision technology called the Graph Model for Conflict Resolution (GMCR) is applied to a generic aquaculture conflict to illustrate how GMCR can be used to systematically investigate a wide range of conflicts arising in aquaculture in order to obtain meaningful strategic insights and thereby assist in making informed decisions in aquaculture development. To emphasize the importance of being able to resolve aquaculture controversies, a review of the global economic impacts of the aquaculture industry is provided and the key stakeholders who may be involved in aquaculture disputes along with their legitimate interests are identified. The paper aims to discuss these issues.

The GMCR methodology comprises two main stages: modeling and analysis. During the modeling stage, key decision makers (DMs), the options under each DM’s control and each DM’s relative preferences over feasible states are identified based on a thorough background investigation to a given dispute. Within the analysis stage, solution concepts that describe key characteristics of human behavior under conflict are utilized to determine resolutions that could occur when DMs interact under pure competition and cooperatively. Interpretation of the equilibrium results provides meaningful strategic insights for better understanding which strategies a given DM could select as the conflict evolves over time.

The results demonstrate how difficult it can be to balance the interests of different key stakeholders in aquaculture development. In all possible resolutions identified in the generic aquaculture conflict, at least two DMs among First Nations, environmental group and residents (Res) would object to the expansion of aquaculture activities due to the assumption that the government would choose to appease one stakeholder at a time. They also reflect the need for a useful tool box of decision technologies for addressing the vast range of challenges that could arise in the important area of marine economics and management.

The GMCR methodology possesses several unique and key original capabilities in comparison to other conflict analysis models. First, it only requires limited information to calibrate a conflict model. Second, it contains a number of solution concepts that describe how a DM could think and behave under conflict. Third, it furnishes a range of informative output, follow-up analyses and advice for use in real-life decision support. Finally, all of the foregoing advantages of GMCR can be contained within decision support systems that permit practitioners and researchers to readily apply the GMCR methodology to real-life conflicts.

The purpose of this study is to explore existing literature on Building Information Modelling (BIM) in Malaysia and examine the perception of practitioners about the potential of BIM applications in reducing construction waste and enhancing productivity.

First, using 244 bibliographic data extracted from the Scopus database, the paper used scientometric analysis and VOSviewer mapping technique to assess the most impactful publication literature on BIM in Malaysia to identify the existing research gaps. Second, using a structured questionnaire, a total of 100 questionnaires were distributed to practising practitioners who incorporate BIM in the delivery of their projects. Descriptive analysis using cross-tabulation in SPSS software, radar chart, relative importance index and Pearson’s correlation were used to analyze the data.

The research gaps are in the fields of construction projects, buildings, energy efficiency, lifecycle and housing. The findings of the survey indicate that quantity take-off, clash detection, site utilization planning, digital fabrication as well as 4D stimulation were the main BIM applications used among the practitioners in Johor and Selangor.

By assessing the state-of-the-art of BIM and BIM applications in this region, the practical implications of this study provide useful insights to construction stakeholders, funding organizations, policymakers, research institutions, professionals, journal editors, reviewers and researchers to understand the overall trend of BIM in Malaysia and its usage.

This paper is the first to use science mapping using scientometrics to reveal the current BIM research in “Malaysia only”. Relying on the identified gaps, the study further examined the usage of BIM applications in Malaysian construction projects.

This study aims to focus on the analysis of the internal mechanism of farmers’ ecological cognition and the behaviour of Grain for Green Project (GGP), and the further relationship between ecological cognition and ecological aspiration, proposing climate change strategies and management from the perspective of farmers.

Theory of planned behaviour and social exchange theory were used to construct a theoretical framework and an ecological cognition under the influence of external factors, the aspiration and the behaviour of GGP, using ecological fragile areas in Bazhou and Changji, Xinjiang of 618 peasant households’ survey data. The structural equation model and Heckman two-step model were applied to analyse the relationship between ecological cognition and ecological aspiration of farmers, the impact of peasant households’ ecological cognition and aspiration to the behaviour of GGP and the influence factors of GGP behaviour.

This research’s results show that the three characterizations of ecological cognitive variables, attitude towards the behaviour (AB), subjective norms (SN) and perceived behaviour control (PBC), have significant positive impact on farmers’ GGP ecological aspiration. The comprehensive impact path coefficients of ecological cognition are PBC (0.498) > SN (0.223) > AB (0.177). Also, income change is a moderating variable, which has a significant moderating effect on the influence of AB and SN on ecological aspiration. Further, farmers’ ecological cognition has an influence on the behaviour of GGP, and the change of farmers’ income has a significant positive effect on farmers’ choice of returning farmland to forests.

The ecological protection policy suggestions and countermeasures can be drawn from the research conclusions, adapted to China’s ecologically fragile regions and even similar regions in the world to response the climate change.

Combining the theory of planning behaviour and social exchange, this paper empirically analyses the path of farmers’ ecological cognition and ecological aspiration, as well as the influencing factors.

Photographs are a kind of cultural heritage and very useful for cultural and historical studies. However, traditional or manual research methods are costly and cannot be applied on a large scale. This paper aims to present an exploratory study for understanding the cultural concerns of libraries based on the automatic analysis of large-scale image collections.

In this work, an image dataset including 85,023 images preserved and shared by 28 libraries is collected from the Flickr Commons project. Then, a method is proposed for representing the culture with a distribution of visual semantic concepts using a state-of-the-art deep learning technique and measuring the cultural concerns of image collections using two metrics. Case studies on this dataset demonstrated the great potential and promise of the method for understanding large-scale image collections from the perspective of cultural concerns.

The proposed method has the ability to discover important cultural units from large-scale image collections. The proposed two metrics are able to quantify the cultural concerns of libraries from different perspectives.

To the best of the authors’ knowledge, this is the first automatic analysis of images for the purpose of understanding cultural concerns of libraries. The significance of this study mainly consists in the proposed method of understanding the cultural concerns of libraries based on the automatic analysis of the visual semantic concepts in image collections. Moreover, this paper has examined the cultural concerns (e.g. important cultural units, cultural focus, trends and volatility of cultural concerns) of 28 libraries.

The purpose of this paper is to effectively deal with querying of classification with membership.

The authors propose a scheme comprising a layer of Bloom filter for membership checking and a second layer based on neural network for dealing with the classification requirement.

Not only could false positives be dramatically decreased, but also classification could be achieved with the proposed scheme.

The experimental data were randomly generated instead of real‐world ones.

It is difficult to implement this scheme in a real‐world environment, such as the internet. Second, the neural network requires time to converge to a satisfactory level.

Internet ethic might be compromised by hackers once they find a way around the filtering mechanism.

The neural network was moditified and utilized for the first time to be suitable for our purpose. Second, the two‐layer design shows effectiveness.

This study aims to measure the association between local retail grocery provision and private residential rental prices in England. Renting is an important sector of the housing market in England and local grocery provision is an important aspect of service provision and consumers are known to be highly sensitive to the branding of this type of retailing.

This research uses a novel data source from a property rental Web platform to estimate a hedonic model for the rental market. These models incorporate information on the nature of the properties and their neighbourhoods, with an emphasis on how different retail brands are associated with rental prices. This retail brand is captured on two scales: the provision of local branded convenience stores and the provision of larger stores.

The study finds clear differentials in how the local grocery brand is associated with rental prices. When controlling for commonly explored confounding factors, “Luxury” retailers such as Waitrose and Marks and Spencer are associated with higher rental prices, while “Discounter” retailers are associated with lower rental prices. This finding has many implications, particularly in relation to potential price changes in an already challenging housing market for many people.

This is an observational study and as such only associations (not causation) can be implied by these findings.

The focus of this research is on the private residential property market, an important market in England but one that has enjoyed less scrutiny than the sales or socially rented markets. Rather than using general accessibility to retail, this research has differentiated the association by the retail brand and store size, two very important aspects of consumer choice.

This paper aims to determine the influence of various corporate characteristics such as total assets (TA), total sales (TSE), return on assets (ROA), return on sales (ROS), liquidity and age on leverage of the listed non-financial companies in the Dhaka Stock Exchange (DSE).

A non-probability sampling technique has been used in this study, and the leverage of 106 companies listed in the DSE has been examined for the time period 2011-2015. Multiple regression models are used to estimate the influence of corporate characteristics on leverage and leverage is measured by the debt ratio, that is, total liabilities divided by total assets (TA).

The results obtained from the regression models show that TA, ROA and age are negatively and significantly related to the leverage of companies.

Considering only non-financial companies as the sample is a limitation. Hence, the results may not extend across all listed companies in Bangladesh. The study explores only six corporate characteristics variables; other factors influencing the leverage of the firm such as the number of foreign shareholders, ownership structure and auditors’ opinion could be explored in further studies.

The finding of this study contributes to the regulators and enforcement agencies such as Institute of Cost and Management Accountants of Bangladesh (ICMAB), Institute of Chartered Accountants of Bangladesh (ICAB), the Securities and Exchange Commission (SEC) and the DSE. It will enable the regulatory agencies to aim at greater compliance with the local and international standards and also enforce penalties for non-compliance.

This study aims to investigate tourists’ attitudes and intentions regarding the usage of Chat Generative Pre-trained Transformer (ChatGPT) for accessing tourism information. Furthermore, by integrating the perceived risks associated with ChatGPT and the theory of planned behavior (TPB), this research examines the impact of three types of perceived risks, such as privacy risk, accuracy risk and overreliance risk, on tourists’ behavioral intention.

Data were gathered for this study by using two online survey platforms, thus resulting in a sample of 536 respondents. The online survey questionnaire assessed tourists’ perceived risks, attitude, subjective norm, perceived behavioral control, behavioral intention and demographic information related to their usage of ChatGPT.

The structural equation modeling analysis revealed that tourists express concerns about the associated risks of using ChatGPT to search for tourism information, specifically privacy risk, accuracy risk and overreliance risk. It was found that perceived risks significantly influence tourists’ attitude and intention toward the usage of ChatGPT, which is consistent with the hypotheses proposed in previous literature regarding tourists’ perceived risks of ChatGPT.

This work is a preliminary empirical study that assesses tourists’ behavioral intention toward the use of ChatGPT in the field of tourism. Previous research has remained at the hypothetical level, speculating about the impact of ChatGPT on the tourism industry. This study investigates the behavioral intention of tourists who have used ChatGPT to search for travel information. Furthermore, this study provides evidence based on the outcome of this research and offers theoretical foundations for the sustainable development of generative AI in the tourism domain. This study has limitations in that it primarily focused on exploring the risks associated with ChatGPT and did not extensively investigate its range of benefits.

First, to address privacy concerns that pose significant challenges for chatbots various measures, such as data encryption, secure storage and obtaining user consent, are crucial. Second, despite concerns and uncertainties, the introduction of ChatGPT holds promising prospects for the tourism industry. By offering personalized recommendations and enhancing operational efficiency, ChatGPT has the potential to revolutionize travel experiences. Finally, recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises.

Recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises. As their interest in adopting ChatGPT grows, increased investments and resources will be dedicated to developing and implementing ChatGPT solutions. This enhancement may involve creating customized ChatGPT solutions and actively engaging in training and development programs to empower employees in effectively using ChatGPT’s capabilities. Such initiatives can contribute to improved customer service and overall operations within the tourism industry.

This study integrates TPB with perceived risks in ChatGPT, thus providing empirical evidence. It highlights the importance of considering perceived risks in tourists’ intentions and contributes to the sustainable development of generative AI in tourism. As such, it provides valuable insights for practitioners and policymakers.

本研究旨在调查游客对使用ChatGPT获取旅游信息的态度和意向。此外, 通过将与ChatGPT相关的感知风险与计划行为理论（TPB）相结合, 本研究探讨了三种感知风险（隐私风险、准确性风险和过度依赖风险）对游客行为意向的影响。

本研究通过两个在线调查平台收集了536名受访者的数据。在线调查问卷评估了游客对ChatGPT使用的感知风险、态度、主观规范、感知行为控制、行为意向以及与其使用ChatGPT相关的人口统计信息。

结构方程建模分析显示, 游客对使用ChatGPT搜索旅游信息的相关风险表示关切, 特别是隐私风险、准确性风险和过度依赖风险。发现感知风险显著影响游客对使用ChatGPT的态度和意向, 与先前有关游客对ChatGPT感知风险的文献中提出的假设一致。

本研究将TPB与ChatGPT中的感知风险相结合, 提供了实证证据。它强调了在考虑游客意向时考虑感知风险的重要性, 并为旅游中生成AI的可持续发展提供了贡献。因此, 它为从业者和政策制定者提供了宝贵的见解。