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This paper aims to investigate the prevailing practice of managing client requirements for design and build (D&B) construction projects in Hong Kong. It attempts to evaluate the limitations and addresses the need for a practical framework for facilitating the implementation of client requirements management within the industry.

Two research instruments were used in this paper: semi‐structured interviews and case studies.

The study revealed that the limitations of the current practice included the lack of a comprehensive client's project brief, inadequate involvement of client in the briefing process, the lack of impartial agents, the controversy caused by the uncertain legal status of end‐users and the improper timing of raising requirements by key project stakeholders. Recommendations are given that an inclusive project brief is necessary in clarifying the goals and covering all‐rounded perspectives. A practical framework is needed to improve the client requirements management practice within the construction industry.

The D&B procurement system adopted in Hong Kong actually exists in various forms within the construction industry, which differ from the prototype that has long been recognized. Therefore, a more detailed study into D&B projects covering a broader area is necessary in the future.

Little research work has been undertaken on the study of client requirements management, especially for D&B construction projects. This paper has improved the comprehension of the nature of client requirements and has provided valuable insights into the prevailing problems associated with the management of client requirements.

In order to find a way to combine traditional culture with modern living needs, taking “Chinese painting” as the breakthrough point, through the study of the development process and artistic characteristics of Chinese painting, four aspects of classical philosophy, natural landscape image, brush and ink composition artistic conception, and abstract aesthetic conception contained in Chinese painting are summed up. The results of the study provide enlightenment for contemporary residential landscape design, and summarize the methods of creating Chinese paintings in residential landscape design. Thus, a residential landscape model with the characteristics of “Chinese painting” is found out.

This study aims to extract knowledge of ancient Chinese scientific and technological documents bibliographic summaries (STDBS) and provide the knowledge graph (KG) comprehensively and systematically. By presenting the relationship among content, discipline, and author, this study focuses on providing services for knowledge discovery of ancient Chinese scientific and technological documents.

This study compiles ancient Chinese STDBS and designs a knowledge mining and graph visualization framework. The authors define the summaries' entities, attributes, and relationships for knowledge representation, use deep learning techniques such as BERT-BiLSTM-CRF models and rules for knowledge extraction, unify the representation of entities for knowledge fusion, and use Neo4j and other visualization techniques for KG construction and application. This study presents the generation, distribution, and evolution of ancient Chinese agricultural scientific and technological knowledge in visualization graphs.

The knowledge mining and graph visualization framework is feasible and effective. The BERT-BiLSTM-CRF model has domain adaptability and accuracy. The knowledge generation of ancient Chinese agricultural scientific and technological documents has distinctive time features. The knowledge distribution is uneven and concentrated, mainly concentrated on C1-Planting and cultivation, C2-Silkworm, and C3-Mulberry and water conservancy. The knowledge evolution is apparent, and differentiation and integration coexist.

This study is the first to visually present the knowledge connotation and association of ancient Chinese STDBS. It solves the problems of the lack of in-depth knowledge mining and connotation visualization of ancient Chinese STDBS.

Tourists’ destination image is crucial for visiting intentions. An ancient capital with diverse characteristics is an important component of China’s urban tourism. The purpose of this paper is to address the following questions: what are the differences and commonalities of the perceived destination image of ancient capitals? What makes the difference of the perceived destination image in these cities? Aside from the exterior factors, are there internal factors of cities that influence tourists’ cognition and perception of destination image?

The comment text data of Baidu tourism website were used to determine the differences in the destination images of China’s four great ancient capitals: Beijing, Xi’an, Nanjing and Luoyang. ROST content mining and semantic network analysis were for differences and commonalities of the perceived destination image, and correlation analysis was used to explore the internal factors of cities that influence tourists’ cognition and perception of destination image.

Though the same as ancient capital, the four ancient capitals’ images are far apart; historical interests are the core of tourism experience in ancient capital city; image perception is from physical carrier, history and culture, and human cognition; tourist’ destination affect of ancient capital is most from its history and culture; protecting identity and maintaining daily life are crucial for ancient city tourism.

Previous studies on ancient capitals have focused on the invariable identity of ancient capitals’ destination images, and left a gap on determining from where the invariable identity comes in general and how much it influences destination image. This gap was addressed in this study, by analyzing the destination images of four ancient capitals in China as cases. In this way, this study provided reference to the other ancient cities worldwide.

The purpose of this study is to explore the effect of travel agency’s reputation on customer recommendation behavior by examining the mediating effects of customer-perceived functional and emotional value as well as the moderating effects of tour leader performance and customer flow experience in the travel agency sector.

A statistical analysis of the collected questionnaires was computed based on the 463 usable responses from Taiwan tourists who joining the group package tours traveling to China. Structural equation modeling is the essential analysis methodology used to examine the hypothesized relationships among the variables.

The analysis results confirm that reputation has positive effects on customers recommendation behaviors in which perceived functional and emotional value work as necessary mediating roles. Nevertheless, the effect of reputation through emotional value on customer recommendation behavior provides a much better explanation than through functional value in the model. In addition, regarding the variables of tour leader performance and customer flow experience in the model, only the tour leader performance is confirmed that moderates the relationships among reputation, perceived value, and customer recommendation behavior. According to the findings, managerial implications are discussed as well.

This study develops a conceptual stimulus-organism-response (S-O-R) model that, reflecting the mediating role of perceived value and the moderating role of tour leader performance, indicates the effect of reputation on customer recommendation behavior.

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

This paper aims to investigate the history and distribution of trade ceramics in Southeast Asia over a thousand-year period stretching from the ninth to the early nineteenth century CE.

The study takes a material culture approach to the writing of marketing history by researching the ceramics trade from the starting point of artifacts and their social context. It draws from literatures on Chinese and Southeast Asian ceramics art history and archaeology. It also is informed by first-hand experience inspecting surviving artifacts in shops, talking to dealers and taking in museum displays.

After a brief historical overview of the ceramics trade in Southeast Asia, the research further explores topics in physical distribution (transportation routes, hubs and local marketplaces and ships, cargo and packing) and product assortments, adaptation and globalization of consumer culture.

The art history and archaeological literatures provide a good overview of the ceramics trade and analysis of surviving material artifacts, but only limited information about distribution and consumption. Many questions remain unanswered.

This study contributes to international business and marketing history by documenting a thousand years of trade among China, mainland and insular Southeast Asia, and a long-standing cultural exchange facilitated by seaborne commerce. It also shares a marketing perspective with the fields of Southeast Asian art history and archaeology. Research in marketing history has neglected this region. To fully understand the development of marketing in the pre-industrial era, accounts from civilizations outside the West must be included.

In order to help companies better grasp the perceptual needs of consumers for patterns, so as to carry out more accurate product pattern development and recommendation, this research develops a product pattern design system based on computer-aided design.

First, use the Kansei engineering theory and method to obtain the user's perceptual image, and deconstruct and encode the pattern based on the morphological analysis method, then through the BP neural network to construct the mapping relationship between the user's perceptual image and the pattern design elements, and finally calculate and find the corresponding design code combination according to the design goal to guide the pattern design.

Taking costume paper-cut patterns as an example, the feasibility of this system is verified, the design system can well reflect the user's perceptual image in the pattern design and improve the efficiency of pattern customization service.

Compared with the traditional method that relies on the designer's personal experience to propose a design plan, this research provides scientific and intelligent design methods for product pattern design.

The purpose of this paper is to investigate the influence of incorporating Chinese elements in global brands on consumer purchase likelihood.

Six global brand products from three categories that utilized Chinese elements are used to test hypotheses. The Total Effect Moderation Model is used to analyze by combining moderation and mediation under a general analytical framework.

The results show that cultural compatibility has direct positive effect, in addition to an indirect effect (through local iconness) on purchase likelihood. Meanwhile, consumer cultural identity is found to moderate the impact of brand local iconness on purchase likelihood.

Evaluation and improvement of cultural compatibility in a global brand that incorporates Chinese elements is recommended for multinational marketers entering Chinese consumer markets. Meanwhile, marketers should pay attention to consumer cultural identity in the market segmentation process.

This paper takes a unique perspective to investigate whether and how global brands can succeed when adding local cultural elements to the product design, packaging and promotion in emerging markets like China.