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Although many conventional level-set approaches can be used for segmenting images containing factors such as noise and intensity inhomogeneities, they still can impact the accuracy of the results seriously. To solve this problem, a level-set method for fast image segmentation based on pre-fitting and bilateral filtering is proposed.

Firstly, an improved bilateral filter was investigated for image preprocessing. Secondly, by computing the local average intensity of the preprocessed enhanced picture, two local pre-fitting functions were defined. Thirdly, a new level-set energy functional was defined. Finally, a new distance regularized energy term based on the logarithmic and polynomial functions is proposed to evolve the level-set function in a smooth state.

The experimental results demonstrate that the proposed model has an excellent segmentation capability for images with noise and intensity inhomogeneities and has different degrees of performance improvement compared with the mainstream models.

(C1) An improved bilateral filter was investigated and integrated into the model. (C2) Proposing two local pre-fitting functions by computing the local average intensity of the preprocessed enhanced image. (C3) Proposing a new level-set energy functional. (C4) A new distance regularized energy term based on the logarithmic and polynomial functions is proposed to evolve the level set function in a smooth state. (C5) Analyzing and comparing the performance of the proposed model with other similar models.

This paper aims to propose a new method to solve the two problems in fabric defect detection. Current state-of-the-art industrial products defect detectors are deep learning-based, which incurs some additional problems: (1) The model is difficult to train due to too few fabric datasets for the difficulty of collecting pictures; (2) The detection accuracy of existing methods is insufficient to implement in the industrial field. This study intends to propose a new method which can be applied to fabric defect detection in the industrial field.

To cope with exist fabric defect detection problems, the article proposes a novel fabric defect detection method based on multi-source feature fusion. In the training process, both layer features and source model information are fused to enhance robustness and accuracy. Additionally, a novel training model called multi-source feature fusion (MSFF) is proposed to tackle the limited samples and demand to obtain fleet and precise quantification automatically.

The paper provides a novel fabric defect detection method, experimental results demonstrate that the proposed method achieves an AP of 93.9 and 98.8% when applied to the TILDA(a public dataset) and ZYFD datasets (a real-shot dataset), respectively, and outperforms 5.9% than fine-tuned SSD (single shot multi-box detector).

Our proposed algorithm can provide a promising tool for fabric defect detection.

The paper includes implications for the development of a powerful brand image, the development of “brand ambassadors” and for managing the balance between stability and change.

This work provides technical support for real-time detection on industrial sites, advances the process of intelligent manual detection of fabric defects and provides a technical reference for object detection on other industrial

Therefore, our proposed algorithm can provide a promising tool for fabric defect detection.

Drawing on the resource-based view, the purpose of this paper is to focus on the influence of relational capability and marketing capabilities on export performance. The study also examines the interaction effects of relational capability on the marketing capabilities – export performance relationships.

A stratified random sample of 1,047 exporting firms was approached. Survey data were collected from 333 Vietnamese exporting firms and analysed using hierarchical moderated regression.

The results reveal that a firm’s relational capability not only strengthens the efficiency of the export pricing capability – performance, marketing intelligence capability – performance, and marketing communication capability – performance relationships, but is also the strongest predictor of export performance amongst those capabilities identified. Whilst engagement in market intelligence, product development, price setting and promotional activities have a positive payoff, the findings confirm that there is less need for exporters to engage in after-sales service and distribution capabilities.

The study introduces the notion of relational capability alongside export marketing capabilities as predictors of export performance. The authors also examine the moderating influence of relational capability on the link between export marketing capabilities and export performance. By focusing on Vietnam, the study provides fresh insights surrounding the development pathway for firms in emerging markets.

This paper aims to use artificial neural network (ANN) methods to predict stock price crashes in the Chinese equity market.

Three ANN models are developed and compared with the logistic regression model.

Results from this study conclude that the ANN approaches outperform the traditional logistic regression model, with fewer hidden layers in the ANN model having superior performance compared to the ANNs with multiple hidden layers. Results from the ANN approach also reveal that foreign institutional ownership, financial leverage, weekly average return and market-to-book ratio are the important variables when predicting stock price crashes, consistent with results from the traditional logistic model.

First, the ANN framework has been used in this study to forecast the stock price crashes and compared to the traditional logistic model in the world’s largest emerging market China. Second, the receiver operating characteristics curves and the area under the ROC curve have been used to evaluate the forecasting performance between the ANNs and the traditional approaches, in addition to some traditional performance evaluation methods.

Despite the fact that extensive studies on public-private partnerships have focused on risk identification and classification, research still lacks concentration on studying the latent structure of risks in build operate transfer (BOT) transportation projects, especially in developing countries. The research was carried out in Vietnam and this paper aims to explore the underlying relationships among risks in the context of BOT transportation projects.

A questionnaire survey was conducted to investigate the perception of stakeholders regarding the probability of occurrence and the severity of the impact of risks related to BOT transportation projects. Factor analysis was performed based on a total of 40 risks.

Seven risk groups were formed as a result of factor analysis, namely, “projects’ viability and political-regulatory risks”, “macroeconomic risks”, “projects’ feasibility study and market risks”, “financial risks”, “organization/coordination and force majeure risks”, “tolling, contractual, approvals risks” and “media and land expropriation risks”.

The research contributes to the current body of knowledge by providing deep insight into the structure of risks in BOT transportation projects in Vietnam through exploring the underlying relationships among risks, to form a latent risk structure from practical viewpoints. The findings are beneficial for involved stakeholders and policymakers to set up and propose suitable management strategies and related policies.

Corruption continues to be a pervasive stain on the construction industry in developing countries worldwide, jeopardising project performance and with wide-ranging negative implications for all facets of society. As such, this study aims to identify and analyse the causes of corruption in the construction sector of an emerging economy such as Malaysia, as it is crucial to uncover the specific facilitating factors involved to devise effective counter strategies.

Following a detailed literature review, 18 causes of corruption are identified. The results of an opinion survey within the Malaysian construction industry are further reported to rank and analyse the causes. The factor analysis technique is then applied to uncover the principal factors involved.

The results indicate that all the considered causes are perceived to be significant, with the most critical causes being avarice, relationships between parties, lack of ethical standards, an intense competitive nature and the involvement of a large amount of money. A factor analysis reveals four major causal dimensions of these causes, comprising the unique nature of the construction industry and the extensive competition involved; unscrupulous leadership, culture and corruption perception; a flawed legal system and lack of accountability; and ineffective enforcement and an inefficient official bureaucracy.

The study presents the Malaysian construction industry’s view of the causes of corruption. Therefore, the arguments made in the study are influenced by the social, economic and cultural settings of Malaysia, which may limit generalisation of the findings.

This paper helps stakeholders understand the root causes and underlying dimensions of corruption in the construction industry, especially in Malaysia. Recommendations for changing cultures that may be conducive to corrupt practices, and anti-corruption measures, are suggested based on the findings of the research.

These findings can guide practitioners and researchers in addressing the impediments that give rise to the vulnerability of the construction industry to corrupt practices and understanding the “red flags” in project delivery.

Though China is taking many steps to offer affordable houses to the public, the gap between the demand and supply for such affordable houses is still huge. Rapidly growing demand for affordable housing has encouraged large Chinese cities, faced with housing imbalance, to invest in developing affordable properties. As a result, the Chinese central government has started to encourage local governments to use Public-Private Partnerships (PPPs) and private capital to supplement the funding deficit. There is also an on-going debate regarding the need to establish prerequisites for institutions to meet in order to achieve effective PPPs. In this paper, we examine what the current institutional environment is in China and how China is meeting these prerequisites for effective PPPs. We also examine the main programs on affordable housing and propose a potential field for using PPPs. We draw the conclusion that PPPs are more favorable for renting-oriented type projects than owning-oriented projects. In this context, the advantages of the PPP model for China's renting-oriented affordable housing programs are would be the provision of private financing, the enhancing efficiency by involving private sector experts and the statement of bundling constructions and maintenance and operation work in the contract, which motivates the private sector to build properties up to standard for its cost efficiency from the whole project perspective.

The Built Operate Transfer (BOT) model has been increasingly used in transportation investments in Vietnam. However, there is still an inadequacy of risk management applications in these projects and lack of research in this area. The study aims to improve the success of projects implemented through the BOT model in Vietnam.

The study followed a sequential design including interviews and a questionnaire survey to investigate the perception of stakeholders from public and private sector regarding the probability of occurrence and the severity of impact of risks in BOT transportation projects in Vietnam. Quantitative data from the survey was subjected to descriptive and inferential statistics to explore the priority of risks as well as the differences in the perception between the public and private sectors.

The results showed that the top five most significant risks in BOT transportation projects in Vietnam are: (1) problems with land acquisition and compensation, (2) inappropriate location of toll booths, (3) public resistance to pay, (4) high toll rate and (5) lack of cash flow. With the exception of “lack of cash flow,” there were no statistically significant differences in the rankings of individual risks between the public and private sector. In addition, there is a significant positive correlation in the overall rankings of all risks for both sectors.

This study contributes to the body of knowledge by exploring the probability of occurrence and the severity of the impact of risks in BOT transportation projects in a developing country like Vietnam which has not been extensively explored yet. Second, it provides an insight into the perception of stakeholders from the public and private sector regarding the level of risks which is very useful for potential stakeholders in making decisions when they intend to participate in such partnerships. Third, it enables the Vietnamese government to establish suitable policies related to such projects. These contributions are very important in improving risk management in PPPs in developing countries.

Contractors must check the provisions that may cause disputes in the specifications to manage project risks when bidding for a construction project. However, since the specification is mainly written regarding many national standards, determining which standard each section of the specification is derived from and whether the content is appropriate for the local site is a labor-intensive task. To develop an automatic reference section identification model that helps complete the specification review process in short bidding steps, the authors proposed a framework that integrates rules and machine learning algorithms.

The study begins by collecting 7,795 sections from construction specifications and the national standards from different countries. Then, the collected sections were retrieved for similar section pairs with syntactic rules generated by the construction domain knowledge. Finally, to improve the reliability and expandability of the section paring, the authors built a deep structured semantic model that increases the cosine similarity between documents dealing with the same topic by learning human-labeled similarity information.

The integrated model developed in this study showed 0.812, 0.898, and 0.923 levels of performance in NDCG@1, NDCG@5, and NDCG@10, respectively, confirming that the model can adequately select document candidates that require comparative analysis of clauses for practitioners.

The results contribute to more efficient and objective identification of potential disputes within the specifications by automatically providing practitioners with the reference section most relevant to the analysis target section.

As a crucial counter-equivalent to business ethics, consumer ethics has emerged as a promising research domain for practitioners and academicians alike. Despite its pertinence for both industry and academia, little is known about the existing state of consumer ethics research. To address this limitation, a systematic literature review was conducted to identify key research themes, gaps in the extant literature and set the agenda for future research.

This literature review is based on a sample of 81 research articles drawn from Scopus and EBSCO host databases and analysed on different classification bases, covering a period from 2004 to 2019.

The results reveal that pro-social behaviour has gained recent attention in consumer ethics research. Moreover, there has been a renewed focus to understand and mitigate the attitude–behaviour gap in ethical consumption. The authors also found that majority of the studies have been conducted in Europe and North America, in a single country context.

Consumer ethics has significant economic and social consequences worldwide. Consumer ethics insights can help marketers and practitioners to devise strategies that minimize business losses due to unethical consumer behaviour, incentivize ethical consumption and align corporate social responsibility initiatives that draw consumer support.

To the best of our knowledge, this is the first major (systematic) review on consumer ethics after Vitell’s review of 2003. This review provides valuable directions for future research to carry this domain forward.