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Today clothing has become the largest category in online shopping in China, and even in Asia-Pacific. The satisfaction degree of apparel online shopping can be improved by effective personalized recommendation. The purpose of this paper is to propose a personalized recommendation model and algorithm based on Kansei engineering, traditional filtering algorithm and the knowledge relating to apparel.

Users’ perceptual image and the design elements of apparel based on Kansei engineering are discussed to build the mapping relation between the design elements and user ratings employing verbal protocol, semantic differential and partial least squares. The implicit knowledge and emotional needs pertaining to users are accessed using analytic hierarchy process. A personalized recommendation model for apparel online shopping is established and the algorithm for the personalized recommendation process is proposed. To present the personalized recommendation model, men’s plaid shirts are taken as the example, and the recommendations of apparel for online shopping were implemented and ranked in the context of differing users’ emotional needs. A comparison between the traditional model and this model is made to verify the effectiveness.

The recommendation model is capable of analyzing data and information effectively, and providing fast, personalized apparel recommendation services in accordance with users’ emotional needs. The experimental results suggest that the model is effective.

Similar researches of recommendation mainly focus on the field of computer science, the basic idea of which is using users’ history accessing records or the preferences of other similar users for determination of users’ preferences. Since the attributes of apparel products are not factored in the approach referred above, the issue of personalized recommendation cannot be solved in a really effective way. Combining Kansei engineering and recommendation algorithm, a framework for apparel product recommendation is presented and it is a new way for improvement of recommendations for apparel products on shopping sites.

As a natural fiber, yakwool has attracted much attention in textile processing due to its excellent properties and wearabilities. However, the main colors of yakwool are black and brown. Therefore, for extending the application scopes of the fiber, the decolorization of the yakwool fiber is usually needed, especially for the black fiber. The paper aims to discuss this issue.

In the paper, the properties of the yakwool fiber were tested first, especially the melanin granules in the fiber. Then, the decolorization of the yakwool fiber was studied using the oxidation–reduction decolorization method, and corresponding optimal process of the decolorization was given. Then, the properties of the decolorized yakwool fiber were tested and compared with those of the original fiber.

It is shown that, after decolorization, the physical and mechanical properties of the fiber were deteriorated, especially in terms of the strength and elongation. Therefore, the fiber became shorter and thinner, and the scales were damaged. When compared with the yarn spun from the original yakwool fiber, it was observed that the properties of the yarn spun from the decolorized yakwool fiber deteriorated because of the deterioration in the properties of the original fiber.

In the paper, for extending the application scopes of the yakwool fiber, the decolorization of the yakwool fiber was studied.

This paper aims to explore one question: to what extent does urban rehabilitation impact the housing search cost of the low-income tenants.

This paper adopts the fixed effects time-on-market (TOM) model and pricing model to study the research question.

Urban rehabilitation lifts the subdivided units (SDUs’) prices by around 7%. For the SDU located in old districts, urban rehabilitation gives rise to the rental price up by 11%–12%. The SDUs in the area without urban rehabilitation experience a short marketing period of 16%–17%. The SDU located in the old district that is without urban rehabilitation would have a short marketing time.

To the best of the authors’ knowledge, this is the pioneering research to investigate the relationship between rehabilitation and low-income rental housing from the improved search theory. The improved search theory posits that under the circumstance of urban rehabilitation, low-income tenants’ options are limited and the search behavior will be restricted in the affordable areas, and then TOM will be shortened. With the concentration of SDUs in Hong Kong, the test of the search theory is broken down into two hypotheses. (H1) Urban rehabilitation leads to low-income housing prices increase. (H2) Low-income housing located in areas without urban rehabilitation has a shorter TOM.

Urbanisation, environmental sustainability and property markets are intertwined. Consequently, studies on any of these three topics need to take the other two topics into consideration. By critically reviewing 33 hedonic pricing studies in 16 key journals in the urban studies and environmental policies areas, we summarise quantitative evidence on the price of environmental externalities resulting from China's urbanisation process. We find that Chinese residents are willing to pay more for the access to green space and waterbody as well as the treatment of urban pollution. The cost and benefit of these amenities and disamenities have already been capitalised in house prices. The central and local government in China can leverage market force to encourage, support and facilitate sustainable urban development and environmental protection, instead of directly intervening in the property market by using public resources. Meanwhile, the estimated hedonic price of Urban Green, Urban Blue and Urban Grey helps policymakers to understand the cost and benefit of their urban development decisions. Our review of the papers on Urban Green, Urban Blue and Urban Grey suggests that there have been promising and encouraging development in studies on all three topics in the last decade. The quality and quantity of hedonic price research has been improving notably. However, it is also clear that there is virtually no empirical evidence from the second- or third-tier cities, particularly, regarding Urban Green and Urban Blue investigations. The small number of existing hedonic studies is far from sufficient to draw reliable conclusions about the costs of environmental externality for cities that have not been studied. What works in first-tier cities may not hold elsewhere in China due to the large geographical variation in natural endowment, economic development status and local customs. There are many pieces that are missing from this big picture. More hedonic price studies are needed.

The purpose of this study is to survey the quantitative and qualitative indicators of housing in Tabriz and its comparison with urban areas of the province and the country (Iran) and identify the key indicators on the future of the housing situation in the Tabriz metropolis.

Statistical yearbooks, the censuses of different periods and the documentary-environmental scanning methods are used to collect the data and matrix of crossed impact multiplications applied to a classification (MICMAC) software is used for analyzing the data.

The results show that during the years 1976 to 2016, the quantitative and qualitative indicators of housing in Tabriz have improved. Also, by obtaining the environmental scanning method, 61 factors were selected in 5 areas that have the greatest impact on the future of housing in the Tabriz metropolis. Finally, 11 key factors that have the most impact on the future of housing in the Tabriz metropolis were selected. These factors are economic growth, inflation, household income and savings, land and housing prices, sanctions, exchange rate changes, bank facilities, unemployment rates, political changes, purchasing power and management style. Among these factors, economic factors play the most important role, and political-managerial factors come in the next place.

This paper proves two issues, namely, the housing market in Iran, especially in the metropolis of Tabriz is strongly influenced by macroeconomic factors and the political situation of society and slogans of housing market reform without fundamental changes and reforms in both economic and political sectors of society are demagogic and illogical.

Researchers have not widely explored design-based factors that govern buildings’ physical properties and human–building interactions. This paper aims to understand the influence of design-related factors on the time-on-market (TOM) of listed houses and, consequently, study the effect of design features on the desirability of a given house.

This research analyzes a dataset of listed houses, provided by the REALTORS^® Association of Edmonton (RAE) and covers a period extending from January 2009 to August 2019, using Cox proportional-hazards regression model to identify building features that influence people purchasing decisions.

The research findings affirm the statistical insignificance of the price on the TOM compared to other design features, such as the construction method, the installed mechanical systems and cladding materials.

The data used in the analysis comes from a single North American region, i.e. Edmonton, Alberta, Canada. Also, the data provided by the RAE includes only records that involve a realtor.

The observations of the research presented in this paper influence the housing market players’ decisions about housing designs, mainly those concerned with building new residential dwellings such as speculative builders and designers.

The research novelty stems from two aspects: the medium used for analysis, i.e. Cox proportional-hazards regression model, which allows considering the listed-but-not-sold units and helps to eliminate the survivorship bias that leads to over-optimistic outcomes; and the assessment of design-related features which allows to understand people’s preferences in design alternatives.

To explore the state of this conditional Granger causality when other cities are not factors, we investigate housing market networks in China's major cities by using a combination of conditional Granger causality and network analysis.

Although housing market networks have been well discussed for different countries, the question of housing market networks in China's major cities based on the conditional causality perspective has yet to be answered.

We discover that second-tier cities are more influential than first-tier cities. Although the connectivity of the primary housing market is more complex than the diversified connectivity observed in the secondary housing market, both markets are scale-free networks that exhibit high stability. Moreover, we reveal that geographic conditions and economic development jointly determine the housing market's modular hierarchical structure. Our results provide meaningful information for both Chinese policymakers and investors.

By excluding the influence of other cities, our conditional Granger causality identifies the true casual relation between cities' housing markets. Moreover, it is the first paper to consider the primary housing market and secondary housing market separately. Specifically, Chinese prefer new house rather than second-hand house from both speculative and self-housing. Generally speaking, the new house price is lower than the second-hand house price since the new house is off-plan property. Therefore, understanding the difference between primary and secondary housing markets will provide useful information for both policymakers and speculators.

Except the physiological comfort, the design aesthetic of plaid shirts is the decisive factor affecting the purchase decision making of consumers. However, as there is subjectivity and indeterminacy in evaluation of the aesthetic, current research in the literature has little information about the appearance design of checks. The purpose of this paper is to extract the check design features, which influence consumer evaluation, and determine the preferences of men of different ages for the check designs, and the preference differences between them.

Through cluster and preference experiments, the perception and evaluation of the subjects were gained. By cluster analysis, typical classifications of check designs were fixed. With Multidimensional Scaling (MDS) algorithm, users’ perceptual space was revealed as to the plaid samples. In the PREFMAP analysis, results of the ideal vectors of men of different ages were drawn.

The study results revealed four typical classifications of check designs, identified three design dimensions that had effects on users’ evaluation, and built the relationship between design features of checks and consumer evaluation. Besides, in the study, the differences in preference for check designs between men of different ages were also explored. It was found that young men liked modern check designs, but disliked “small and complex” check patterns. Middle aged men preferred dark and cool colors, with dislike for “youthful vigor style.” While they cared more about check colors, young men attached more importance to the design style.

Currently, there is little information in the literature about the evaluation of pattern design. In this study, the use of MDS and PREFMAP analysis reveals visualized complex statistical results. The visualization approach is also applicable to design and positioning of other apparel, and can help designers better understand and position design styles and effects, given their consumer groups and design samples.

The purpose of this paper is to develop a dress design knowledge base (DDKB), which is expected to be further applied to a personalized dress recommendation system.

Dress design knowledge can be expressed as the relationship between designer's fashion perceptions of different dress elements. In order to extract dress design knowledge, a dress shape ontology (DSO) is firstly developed, which can be further used to form a dress element matrix (DEM). A perceptual descriptive space of the dress (DPDS) is developed for the description of the designer's fashion perception of dress. Through a standard sensory evaluation procedure performed by experienced experts (designers), the expected relationship can be obtained. This relationship is then mathematically simulated by fuzzy logic tools for the expected DDKB.

In this paper, a DDKB has been developed. The established knowledge base has been validated, and it can be further applied to dress recommendation system for a specific consumer.

This study introduces the concept of knowledge base to the area of dress individualized design. The knowledge-based design process based on sensory evaluation and fuzzy logic can efficiently solve the individualization of dress design in traditional design processes, which can provide a novel way to dress design individualization.

The purpose of this paper is to figure out the paths about transformation of tacit knowledge into explicit knowledge, i.e. tacit knowledge explicating (TKE) in real estate companies, and determine the influencing factors of TKE in Chinese real estate companies to enable enterprises make better use of their knowledge resources.

The study adopted an exploratory design method using thematic analysis and grounded theory, and semi-structured interviews were conducted to collect data. The interviewees consisted of employees in different positions, who come from Chinese real estate companies with different ranking ranges and different knowledge management levels. Data collection was divided into two rounds for the identification of transformation paths and influencing factors.

This study has shown that 11 paths about TKE divided into solidified organization process and construction of organizational infrastructure go into effect within the real estate companies. Factors influencing TKE in real estate companies concern three main categories: organizational distal factors, contextual proximal factors and individual factors, including 21 subordinates in total. Furthermore, correlation between TKE paths and influencing factors is established.

Research results may lack generalizability due to the method adopted. Therefore, researchers are encouraged to verify the outcomes of this research.

This research provides a new idea and solutions for the tacit knowledge management in real estate companies.

To the best of the authors’ knowledge, this study is the first to systematically identify paths and the influencing factors of TKE in real estate companies, contribute to the incipient but growing understanding of achievement of “tacit to explicit” and enrich the corporate tacit knowledge management literature.