Xiaoxi Zhou, Hui’e Liang and Zhiya Dong
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Xiaoxi Zhou, Yue Xu and Tui Chen
This paper aims to identify the relationship between users' perception image, clothing design features and users' preference and propose a clothing design scheme based on users…
Abstract
Purpose
This paper aims to identify the relationship between users' perception image, clothing design features and users' preference and propose a clothing design scheme based on users perception image and users' preference.
Design/methodology/approach
In this paper, men's suit is composed into multiple design features under the design elements. Using the orthogonal experiment method, 16 schemes of the representative suit are designed. Through perception evaluation experiment, users' perception images and preference degree of the samples are obtained. By partial least squares (PLS) analysis method, the models between users' perception image, suit design features and users' preference are built.
Findings
The interrelationship between the three is identified by establishing PLS models between users' perception image, suit design features and users' preference. According to the coefficients of the models, the optimization schemes of men's suits considering users' perception image and preference are proposed. Verification results show that the optimization schemes are significantly better than other schemes.
Originality/value
The results of this paper can be used for consumer demand-oriented clothing design and provide references and methods for converting consumer's perceived needs into clothing design features.
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Xiaoxi Zhou and Yunhao Xu
In the process of designing new clothes, designers should identify specific user groups’ preferences and attitudes toward certain types of design, ascertain the design elements…
Abstract
Purpose
In the process of designing new clothes, designers should identify specific user groups’ preferences and attitudes toward certain types of design, ascertain the design elements that make clothes popular in the market, and combine these elements to devise the best clothing design scheme. The purpose of this paper is to discover which design elements influence dress purchases and how age affects consumers’ choices in regard to these elements.
Design/methodology/approach
This study uses conjoint analysis in dress design to provide an effective method for designers to identify consumers’ preferences. First, the important attributes and attribute levels of dress design were determined. Next, the experimental samples for the attitude measurement chart were generated by orthogonal design. Finally, the data of 318 samples were analyzed by conjoint analysis to determine consumers’ preferences.
Findings
The results revealed that the “silhouette” attribute is the most important decision criterion for dress purchase, followed by the “dress length” attribute. In contrast, the “waistline height” attribute is perceived as least important. The study also identified the dress design features’ preferences of consumers of different ages. According to the results of the analysis, user groups’ preferences and acceptability regarding different design features were revealed, and the favorite dress design portfolio for age-specific consumers was obtained.
Originality/value
Currently, there is little information in the literature about consumers’ preferences regarding dress design. In this study, the use of conjoint analysis reveals and visualizes complex statistical results. This research approach is also applicable to the design and decision-making processes used for other apparel, and it can help designers better incorporate different users’ needs into clothing design.
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Xiaoxi Zhou and Hang Xu
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Xiaoxi Zhou, Jianfei Meng, Guosheng Wang and Qin Xiaoxuan
This paper examines the problem of lack of historical data and inadequate consideration of factors influencing demand in the forecasting of demand for fast fashion clothing and…
Abstract
Purpose
This paper examines the problem of lack of historical data and inadequate consideration of factors influencing demand in the forecasting of demand for fast fashion clothing and proposes an improved Bass model for the forecasting of such a demand and the demand for new clothing products.
Design/methodology/approach
From the perspective of how to solve the lack of data and improve the precision of the clothing demand forecast, this paper studies the measurement of clothing similarity and the addition of demand impact factors. Using the fuzzy clustering–rough set method, the degree of resemblance of clothing is determined, which provides a basis for the scientific utilisation of historical data of similar clothing to forecast the demand for new clothing. Besides, combining the influence of consumer preferences and seasonality on demand forecasting, an improved Bass model for a fast fashion clothing demand forecast is proposed. Finally, with a forecasting example of demand for clothing, this study also tests the validity of the method.
Findings
The objective measurement method of clothing similarity in this paper solves the problem of the difficult forecasting of demand for fast fashion clothing due to a lack of sales data at the preliminary stage of the clothing launch. The improved Bass model combines, comprehensively, consumer preferences and seasonality and enhances the forecast precision of demand for fast fashion clothing.
Originality/value
The paper puts forward a scientific, quantitative method for the forecasting of new clothing products using historical sales data of similar clothing, thus solving the problem of lack of sales data of the fashion.
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Chenxi Wang, Xiaoxi Chang, Yu Zhou and Huaiqian Zhu
The paper aims to clarify the relationship between organizational work-family practices and employee work-family conflict in light of the boundary conditions of commitment-based…
Abstract
Purpose
The paper aims to clarify the relationship between organizational work-family practices and employee work-family conflict in light of the boundary conditions of commitment-based human resource management (HRM) and employee human capital.
Design/methodology/approach
The paper opted for a multi-source, multi-level design and surveyed 1,717 individuals (including CEOs, HR managers and employees) from 159 firms in China. The model was tested using hierarchical linear modeling.
Findings
The paper provides empirical insights that the effect of work-family practices on work-family conflict is indispensably dependent on the adoption of commitment-based HRM. In addition, employee human capital further moderated this interaction in that the effect of work-family practices on reducing work-family conflict was most salient with high-education employees who were embedded in a high-commitment HRM system.
Research limitations/implications
Testing the hypotheses in the Chinese context has both its merits and drawbacks. Specific results are pursuant to the Chinese context. Therefore, a cross-cultural comparative study is called upon.
Practical implications
The paper includes implications for organizations striving to minimize employee work-family conflict.
Originality/value
This paper primarily applies the resource-building perspective to examine the synergistic effects of organizational resources (targeting work-family practices together with general commitment-based HRM) and individual intellectual resources (human capital) on employee work family conflict.
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Yu Zhou, Lu Lu and Xiaoxi Chang
The purpose of this paper is to examine the impacts of ambidextrous capabilities, explorative capability and exploitative capability on product innovation performance in the…
Abstract
Purpose
The purpose of this paper is to examine the impacts of ambidextrous capabilities, explorative capability and exploitative capability on product innovation performance in the context of internationalization and cross-cultural environment; and to examine the moderating effects of CEO’s preference of risks and opportunities in the international market on the relationship between ambidextrous capabilities and multinational enterprises’ (MNEs) product innovation performance.
Design/methodology/approach
Data were collected from 189 MNEs located in China, which develop international business through export, outsourcing, foreign equity investment or foreign direct investment. Measurement reliability and validity were examined and hierarchical linear regression was used to test the hypotheses.
Findings
Results indicated that both explorative and exploitative capability are positively related to MNEs’ new product development and commercialization of Chinese MNEs; and CEO’s preference of risks and opportunities in international market plays a significant moderating role in the two phases of product innovation.
Research limitations/implications
This study extends organizational ambidextrous capabilities theory to better understand the effects of explorative capability and exploitative capability on innovation performance in the context of internationalization and national cultural differences. Sample constitution is a possible limitation.
Practical implications
MNEs, especially those from emerging economies, should develop both explorative and exploitative capability to be flexible and competitive in dealing with cultural differences. fully take risks and opportunities should be taken into consideration regarding the international market and national cultural differences, and take an effective contingency strategy, driven by the ambidextrous capabilities toward new product innovation development and commercialization.
Originality/value
An empirical examination of how ambidextrous capabilities impact on Chinese MNEs’ new product development and commercialization connects the organizational ambidexterity theory to the innovation and characteristics of upper echelons.
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Xiaoxi Zhu and Jing Xie
Considering behavior-based pricing strategy, we explore the choice of instant logistics service model and pricing strategy of Quick-commerce channel.
Abstract
Purpose
Considering behavior-based pricing strategy, we explore the choice of instant logistics service model and pricing strategy of Quick-commerce channel.
Design/methodology/approach
We adopt the Hotelling framework to develop a two-period game in which two horizontally differentiated suppliers sell repetitively purchased products through a traditional e-commerce channel and an instant e-commerce channel in two periods.
Findings
The results show that: (1) when consumer’s mismatch cost and instant logistics cost coefficient are moderate or relatively high or low, platform-operated logistics (PL) is more beneficial to traditional supplier and traditional e-platform, while Q-commerce platform may prefer self-operated logistics. However, for Q-commerce suppliers, as his/her instant logistics cost coefficient increases, he/she tends to prefer PL. (2) If the instant logistics cost coefficient is moderate, traditional suppliers may always earn more than Q-commerce suppliers in both models, despite the higher commission rate of traditional e-platform. (3) When the instant logistics cost coefficient for Q-commerce suppliers is low, traditional suppliers should significantly reduce price for new customers under PL.
Originality/value
Our research constructs a competition between traditional and quick commerce channels, using game theory methods to examine the impact of different instant logistics models on the dynamic pricing strategies, profitability and instant logistics efficiency of these two online channels.
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Miaomiao Wang, Xinyu Chen, Yuqing Tan and Xiaoxi Zhu
To explore how the blockchain affects the pricing and financing decisions in a low-carbon platform supply chain.
Abstract
Purpose
To explore how the blockchain affects the pricing and financing decisions in a low-carbon platform supply chain.
Design/methodology/approach
Considering the dual roles of the e-commerce platform as a seller and an initiator, a typical game-theoretical method is applied to analyze the behavior of supply chain decision-makers and the impact of key variables on equilibriums.
Findings
When loan interest rates are symmetric, whether blockchain is used or not, the e-commerce platform financing mode will always produce higher wholesale price and unit carbon emission reduction, while the retail price is the opposite. Higher unit additional income brought by the blockchain can bring higher economic and environmental performances, and the e-commerce platform financing mode is superior to bank financing mode. The application of blockchain may cause the manufacturer to change his/her financing choice. For bank financing, with the increase of loan interest rates, the advantages brought by blockchain will gradually disappear, but this situation will not occur under e-commerce platform financing.
Originality/value
Blockchain is known for its information transparency properties and its ability to enhance user trust. However, the impacts of applying blockchain in a low-carbon platform supply chain with different financing options are not clear. The authors examine the manufacturer's strategic choices for platform financing and bank financing, whether to adopt blockchain, and the impact of these decisions on carbon emissions reduction, consumer surplus and social welfare. The research conclusion can provide reference for the operation and financing decisions of platform supply chain under the carbon reduction target in the digital economy era.