AHP-CRITIC-TOPSIS-based analysis of the influence of young people’s preferences on the design of Funan wicker home products

Yu, S., Zhu, Y., Liu, F., Zhong, Z., and Sun, J. (2024). "AHP-CRITIC-TOPSIS-based analysis of the influence of young people’s preferences on the design of Funan wicker home products," BioResources 19(4), 8216–8237.

Abstract

Wicker home products, handcrafted from sustainable materials such as willow, vine, and bamboo, embody principles of sustainable development. However, they face a lack of clear appeal among young consumers in the Chinese market. This study utilizes the AHP-CRITIC-TOPSIS method to examine user preferences for Funan Wicker home products to enhance the original products based on young users’ choices in the contemporary era. Using the AHP method, 14 evaluation indicators were selected across three key factors and determined subjective weights. Objective weights were calculated using the CRITIC method to establish a comprehensive ranking. Subsequently, the TOPSIS method was employed to evaluate and order the nine design alternatives. The findings highlight a strong emphasis on emotional criteria in the evaluation process, with variables such as Weaving Fineness, Stress Release, Pleasure, and Cultural Value significantly influencing user preference. According to the calculations, the program IX with the highest proximity emerged as the optimal choice. Based on these results, the study refines design focus and quantitative indexes for willow home product designers, proposing innovative design methods that offer theoretical support and practical guidance for the development of willow products in Funan, China.

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AHP-CRITIC-TOPSIS-based Analysis of the Influence of Young People’s Preferences on the Design of Funan Wicker Home Products

Shulan Yu,^a,* Yalin Zhu,^a Feng Liu,^a,bZhen Zhong,^a and Jing Sun ^a

DOI: 10.15376/biores.19.4.8216-8237

Keywords: Willow weaving; Home products; AHP- CRITIC-TOPSIS; User preference; Innovative design

Contact information: a: College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China; b: Funan Wicker Craft Association, Fuyang 236308, China;

* Corresponding author: yusl@njfu.edu.cn

GRAPHICAL ABSTRACT

INTRODUCTION

Willow weaving is a traditional craft that predominantly utilizes willow as its primary material, employing specialized techniques to fashion various handicrafts and daily essentials (Romero 2005). It is closely related to the lives of working people and aims to improve people’s lives (Inkuer 2019). Various raw materials including different varieties of willow (such as willow, weeping willow, river willow) and fiber resources like vine, bamboo, reed, and straw can be utilized for willow weaving. Natural materials have the traits of being flexible and malleable (Dlamini et al. 2022), allowing for many forms and purposes to create diverse creative aesthetics and experience impacts (Yu et al. 2021). Funan willow weaving has a lengthy history of evolution, a substantial cultural inheritance, uniqueness, and a self-contained style (Wang et al. 2023a). The tradition has been ongoing for over 500 years and originated in Huanggang Town, located in the eastern side of Funan County, Anhui Province (Zhang and Zhang 2020). Funan willow weaving has undergone two significant changes after centuries of development and advancement: first, it is now possible to use a variety of weaving materials instead of just one, such as willow grass, willow iron, willow wood, and willow wood grass iron composite mixed weaving. Secondly, the range of contemporary willow weaving products extends beyond traditional agricultural equipment to include crafts in other domains, including furniture, horticulture, decorations, home goods, and ornaments (Wang et al. 2023b). The scale of the industry has shifted from small family workshops to large-scale enterprises (Zhu 2021), and weaving technology has advanced from a single weaving process to a composite weaving process. At the same time, Funan willow weaving continues to expand overseas markets and export to Southeast Asia, Europe, and other places. Willow weaving has so far grown into the first industry in Funan County, known as the willow culture industry (Niu and Xu 2023). Moreover, Funan wicker was included in the “National Intangible Cultural Heritage Protection List” in 2011 (Sun et al. 2023), possessing a distinct aesthetic expression and utilitarian significance.

Willow weaving is a traditional handicraft with natural, green qualities. It aligns with the idea of sustainable design, which is environmentally favorable at every stage of its life cycle—from production to use to disposal (Zheng and Zhu 2021). Wicker, a natural material known for its eco-friendly properties, is utilized in modern home product design to enhance innovation and diversity in this field (Xiong et al. 2020), as well as to address the market’s need for environmentally friendly materials (Xiong et al. 2017). Simultaneously, willow weaving furniture is created with traditional handicrafts, preserving national culture and traits and enjoying widespread domestic and international praise. Europe and North America have been particularly welcoming to it. The product is now a daily essential in numerous families, with a growing demand (Wang et al. 2023b). In terms of material, craftsmanship, construction, function, and ornamental, the modern home has matured with time (Zhang et al. 2022a). However, as a result of fast urbanization and socioeconomic change, people are living faster, under more mental stress, and dealing with an increasing number of mental health issues (Oh and Boo 2021). Cultural values and emotional expressions incorporated in house design are especially significant because people’s requirements can no longer be satisfied by the practicality and comfort characteristics of existing home products (Ibrahim 2014; Pizzato and Macedo 2019; Liu et al. 2021). This makes Funan willow weaving home goods unique; the organic materials, including the willow’s curved shape and natural hues, evoke a sense of proximity to the natural world. People might feel at ease and serene in this natural setting, which releases tension and stress. The weaving incorporates the thoughts and aesthetic concepts of the willow weavers, reflecting their pursuit of beauty with rich cultural connotations and emotional expression. At the same time, the unique weaving technique tests the skill of the willow weavers and their mastery of the weaving process (Wang et al. 2023a). This handicraft’s human touch has the power to affect people’s feelings, pique their interest in art, and provide them with comfort and pleasure.

Various constraints impede the growth of Funan’s willow weaving home enterprises. Enterprises do not fully grasp the cultural relevance of willow weaving art and the need of conserving traditional crafts (Shen et al. 2022). Furthermore, enhanced promotional efforts are required. Issues including talent attrition and inadequate development of craft skills continue because the cultural significance of willow weaving objects has not been thoroughly investigated (Sun et al. 2023). The willow home furnishings industry is oversaturated because of the changing consumer consumption trends and a lack of innovation and cultural backing for traditional items, resulting in unfulfilled modern customer demands. Moreover, the lack of unique brand attributes and the prevalence of product standardization worsen the problem (Zhu 2021).

The Industrial Design Competition “Funan, The Capital of Wickerwork in China” Willow Weaving Household Special Competition supports the inventive growth and creative transformation of Funan’s willow weaving culture with the People’s Government of Funan City. To give Funan willow woven home products a new lease on life, more young designers must get involved in the process, delve deeply into the demands of users in the modern era (Li et al. 2023a; Yu et al. 2023a), optimize and upgrade the original products, and design new products that are tailored to modern living. Nonetheless, a great deal of products’ consumer preferences and acceptability remains unknown (Raycheva and Angelova 2017) and relevant design evaluation research is now at an exploratory stage (Tian et al. 2017). Design assessment plays a pivotal role in enhancing the relevance and coherence of design solutions. This paper examines the Funan willow weaving home products crafted by a representative cohort of college students, delving into their design creativity and youth group demand to inform future development strategies for willow weaving products. Additionally, the paper provides recommendations for Funan willow weaving enterprises to tap into the youth market and navigate the transformative landscape of the new era.

EXPERIMENTAL

Methods

Liu et al. (2023a) utilized the Analytic Hierarchy Process (AHP) to determine the weight ranking of 14 factors in the object hierarchy for dining room chair design. This ranking offers design focus and quantitative indexes for designers in the initial stages of the design process. Then, at the late stage of the dining chair design process, the fuzzy hierarchical analysis (FAHP) method was employed to evaluate the three design options statistically and determine the best design solution. Sun et al. (2023) focused on the sustainable development of Huaihe willow wickerwork, assessed consumer willingness to purchase through questionnaires. Four innovation hypotheses were developed based on the diffusion of innovations theory. Subsequently, a hierarchical analysis of hierarchy model consisting of four criteria layers and 20 factor layers was constructed on this basis. Finally, the judgment matrix was then utilized to establish the relative weight values of the criteria and factor layers. Li et al. (2023b), based on the various human-computer interaction (HCI) methods in education, applied the CRITIC technique to assign weights to selected parameters, and employed the TOPSIS strategy to rank alternatives based on performance values to select the best alternative from a pool of 10 options. Zhang et al. (2022b) proposed a multi-criteria decision making method based on interval type 2 fuzzy sets. Subjective weights were obtained by AHP method and objective weights were obtained by CRITIC method. Alternatives are sorted using an enhanced TOPSIS method based on interval type 2 fuzzy sets. This strategy minimizes the numerical discrepancies in assessment outcomes, improving the reliability of the decision-making process when compared to conventional methods.

Fig. 1. Basic flowchart of the method

The findings of the studies mentioned above served as a basis for this paper’s research by offering specific methodological expertise and references. The arrangement of relevant literature leads to the conclusion that various research techniques are available for assessing willow home product design. The AHP approach and the CRITIC method are quite typical weight calculation techniques, and they both hold a significant place in the comprehensive evaluation (Zhao and Xu 2023). The CRITIC method eliminates the errors caused by subjective evaluation, making decision-making more objective and accurate (Krishnan et al. 2021). Meanwhile, the hierarchical analysis method (AHP) can play the importance of subjective evaluation by experts in decision making (Hsu et al. 2008; Liu et al. 2023b). It uses consistency analysis to test subjective judgments and reduce bias (Saaty 1985; Zhou et al. 2022). The sequential selection methodology is also studied using the TOPSIS method for similarity with ideal solutions (Lai et al. 1994). The sorting process determines the hierarchy of solutions, aiding in R and amp; D planning and product positioning. To enhance the data’s accuracy, this study merges subjective assignment weights from AHP with objective assignment weights from CTITIC. Subsequently, the derived comprehensive weights are integrated with the rigorous evaluation approach of TOPSIS, establishing a preference model for designing willow weaving home products based on AHP-CRITIC-TOPSIS. Finally, a logical and scientifically grounded preference method is established, illustrated through an exemplary design program, and a more rational design strategy is proposed in light of the analysis results. To enhance the feasibility of design concepts, this study advocates for evaluating and optimizing wicker home products using the AHP-CRITIC-TOPSIS technique. Figure 1 outlines the fundamental flow of the method.

Sample Selection

The KJ method was utilized to categorize and arrange user-endorsed creative designs of wickerwork home items and to pinpoint typical examples of wickerwork home products. The specific steps that were undertaken are as follows (Cheng and Leu 2011):

The first step was to extensively collect samples. The winning entries from the Anhui Industrial Design Competition’s unique competition, “China Willow Weaving Capital – Funan,” in 2020, 2021, and 2022 were gathered and arranged. All of the material images are the creations of college students and design majors from all over China, and the majority of them have already been produced as actual objects. To guarantee the rationality and impartiality of the study sample, designers collected and examined 34 photos of willow home items to establish a collection of materials, as shown in Fig. 2.

Fig. 2. Willow Woven Home Products Material Library

The next step was making request cards. The study consulted relevant professionals in cat supplies design and concluded that willow weaving material posed a safety hazard to cats, making it unsuitable for use in creating cat supplies. Consequently, all cat supply design products in the material library were deleted. The designers utilized photos from the material repository to produce 34 test cards measuring 10 cm by 10 cm for the next analysis phase. The test analysis was done by a focus group including 8 graduate students in design, one design professor, and one conference facilitator.

The focus group reviewed and confirmed the experimental cards using a hierarchical classification method before rearranging their order. The samples were re-categorized and re-grouped based on design characteristics such as shape, size, function, and context of usage, creating a connection between the originally disorganized samples. The relevant cards were ultimately merged and categorized into a unified group. This process was reiterated until all the cards had been classified and there were no more left. Then the cards were organized. To goal was to create a sample card of home items created from willow weaving. Each sample was identified and processed as S1, S2, S3, S4, S5, S6, S7, S8, S9, as seen in Fig. 3.

Fig. 3. Samples of typical wickerwork home products

Weights of the Factors were Calculated Using the AHP Approach

The AHP technique can prioritize several interconnected and challenging-to-differentiate choice factors based on decision objectives (Shapira and Goldenberg 2005; Yu et al. 2023b). This approach facilitates the making of trade-offs between decision criteria (Saaty 2008). The goal hierarchy, criterion hierarchy, and object hierarchy comprise the model’s multilevel recursive structure (Darko et al. 2019; Xie et al. 2023).

The key reason for AHP’s popularity is that reliable findings can be obtained without statistically significant large sample numbers (Dias and Ioannou 1996; Doloi 2008). According to Lam and Zhao (1998), since AHP is a subjective methodology dependent on expert judgments for the study of a particular problem, even the opinions of a single competent expert are typically representative (Golden et al. 1989; Abudayyeh et al. 2007; Tavares et al. 2008) and there is no need to use a large sample.

The minimal sample size needed for the AHP (hierarchical analysis) study is not strictly imposed. A small number of studies (Ali and Al Nsairat 2009; El-Sayegh 2009) have utilized sample sizes of more than 30, but some (Hyun et al. 2008; Dalal et al. 2010; Li and Zou 2011; Pan et al. 2012; Akadiri et al. 2013) have used sample sizes between 4 and 9. These results show that the AHP approach can still be helpful in situations with limited sample sizes, giving decision-makers meaningful models and results. Nevertheless, while calculating the AHP sample size, researchers still need to give special consideration to sample quality. A panel of specialists consisting of 8 willow weaving home product designers, 6 willow weaving product users, and 2 university professors of willow weaving home product design was invited to assist in this work.

Step 1: Create a layered recursive structural model for household goods made by willow weaving. After reading and analyzing the literature regarding willow home products, the project team discovered and filtered several characteristics that influence users’ evaluations of willow home products from each article. Subsequently, field research and expert interviews on willow home product design were integrated to further arrange these influential aspects. Ultimately, a multilevel hierarchical structural model of willow home products was built using the collected data.

Fig. 4. Hierarchical analysis model of willow woven home products

Figure 4 displays the overall hierarchical analysis model. The evaluation index system of Willow Home Products (A) is the target layer. It consists of three criterion-level decision-making indexes: Appearance Factor (B1), Functional Factor (B2), and Emotional Demand (B3), and there are a total of 14 element-level evaluation indexes under the three criterion-level decision-making indexes, among which the Appearance Factor (B1) corresponds to the following indexes: Molding (C1), Color (C2), Size (C3), and Weaving Density (C4); the Functional factor (B2) corresponds to the following indexes: Eco-friendly (C5), and Comfortable (C6), Portability (C7), Usability (C8), Durability (C9) and Decorative (C10); and the Emotional Demand (B3) corresponds to the following indexes: Cultural Value (C11), Stress Release (C12), Nostalgia (C13) and Pleasure (C14).

Step 2: An expert panel was asked to compare the criterion and element-level indicators using the scale technique shown in Table 1 (Wind and Saaty 1980). The data were averaged to create judgment matrices for the indicators at each level.

Table 1. 1-9 Degree Scale

Step 3: Calculate the relative importance of the Class I and II indicators to the corresponding factors in the previous level, assign them weights accordingly, and rank them. Next, use Equations (1) and (2) to perform a consistency test and determine the consistency index, or C:

(1) Consistent judgment aims to eliminate inconsistent scoring values and verify the scientific accuracy of scoring. Consistency test needs to calculate the maximum eigenvalue λ_max first, according to Eq. 1 can find the maximum eigenvalue λ_max;

(1)

(2) Then, calculate the consistency index CI,

(2)

where λ is the maximum eigenvalue λ_max calculated in the previous step and n is the order of the judgment matrix;

(3) The random consistency ratio (RI) is then applied to the test, and the random consistency index (RI) is found by searching the table based on matrix order.

Table 2. Consistency Test RI chart

(4) Calculated the consistency ratio CR，

(3)

The results from Eq. 3 are compared to 0.1. If CR<0.1, then the consistency test has been passed (Saaty 2001). Otherwise, modifications and a retest of the matrix mentioned above are necessary.

Step 4: To produce subjective weight values, the data are normalized using the sum and product approach, and the hierarchical total weights are ranked. Higher weight values indicate a higher importance of the indicator.

Calculation of Indicator Weights for the CRITIC Method

CRITIC is an objective weighting method for evaluation indicators proposed by Diakoulaki (1995). It is based on the comparative intensity and conflictability indicators of evaluation indicators to synthesize the objective weights of indicators (Krishnan et al. 2020; Peng et al. 2020). The standard deviation is used to represent the comparative intensity (Vujičić et al. 2017); the correlation coefficient is used to represent the conflictability (Durmaz et al. 2020); and the comparative intensity is multiplied with the conflictiveness indicator and normalized to obtain the final weights.

The study employed a questionnaire to gather data. The participants of this experiment were recruited from students and staff aged 18 to 35 in Nanjing Forestry University, and the survey questionnaire was mainly distributed through WeChat, Questionnaire Star, and other online platforms. To assure the validity of the responses, participants had to complete our electronic questionnaire in a private, peaceful setting with no interruptions and were required to answer the questionnaire in no less than six minutes to ensure the validity of the answers.

The questionnaire consisted of three parts. The first part dealt with the subject’s basic information, including gender, age, educational background. The second part was the subjective evaluation of the Willow home products. Each sample corresponded to 14 subjective evaluation indexes through the display of the sample’s picture. Participants were invited to score the 14 indexes of the nine samples using a percentage system (0 to 20 means immensely dislike, 21 to 40 means less dislike, 41 to 60 indicates general favoritism, 61 to 80 indicates more favoritism, and 81 to 100 indicates great favoritism); the third part is the comprehensive evaluation, in which the subjects rank the overall favoritism among the nine design options according to their subjective feelings.

The data results from the questionnaire were averaged to obtain the initial judgment matrix table.

Step 1: Construct the decision matrix;

Using the available matrix Eq. 4 to construct the decision matrix,

(4)

Included among these, i = 1, 2, 3, 4, …，m and j = 1, 2, 3, 4, …，n.

In the matrix above, the indicator scoring under each sample is represented.

Step 2: Construct the normalized decision matrix;

To eliminate the influence on the evaluation results due to the difference in the scale, the indicators are dimensionless through Eq. 5, also known as the normalization process.

(5)

Included among these, i = 1, 2, 3, 4, …，m and j = 1, 2, 3, 4, …，n.

Step 3: Correlation coefficient of the metrics;

The correlation coefficient ρ_jk indicates the correlation between indicators, and ρ_jk is calculated through Eq. 6. A higher correlation coefficient indicates a stronger correlation with other indicators. This may diminish the evaluation strength of the indicator, and hence, the weight provided to the indication should be decreased.

(6)

Step 4: Calculate the conflict metric;

Calculate the conflict metric of the evaluation indicators through Eq. 7.

(7)

As Cj increases, the importance of the j^th assessment indicator in the entire evaluation system also increases, requiring a higher weight to be allocated to it.

Step 5: Determine the objective weights;

Finally, the objective weights of the parameters are determined by the given Eq. 8.

(8)

Composite Weighting Calculation

A combination of the AHP method and the CRITIC method was used to calculate the subjective and objective portfolio weights W_i; the formula is shown in Eq. 9.

(9)

TOPSIS Methodology Integrated Evaluation Program

The TOPSIS approach, often referred to as the “Approximate Ideal Solution Ranking Method,” is an assessment technique that ranks things based on their distance to an ideal objective, as proposed by K. Yoon in 1980. This approach assesses each sample’s proximity to the idealized solution by comparing its distance to the positive ideal solution and the negative ideal solution (Behzadian et al. 2012). The choices are rated based on performance scores, and the optimal solution is selected. The precise stages are outlined as follows (Hwang and Yoon 2012):

Step 1: Calculate the normalization matrix; normalize the data by normalizing the data processing through Eq. 10 to derive the normalization matrix that

(10)

Step 2: Construct the weighted normalization decision matrix;

The weighted normalization matrix V is obtained through Eq. 11. where W_j represents the weight vector of each evaluation index, R represents the normalization matrix, and the normalization matrix V is obtained by multiplying the two.

(11)

Step 3: Construct positive and negative ideal solutions;

A positive ideal solution means that each indicator reaches the most desirable data value in the program, and a negative ideal solution means that each indicator is the least desirable value in the sample.

(12)

(13)

Step 4: Calculate the proximity of the height of the distance to the positive and negative ideal solutions to the ideal point for each scheme:

(14)

The values range from 0 to 1, with values closer to 1 indicating a higher program score.

RESULTS AND DISCUSSION

AHP Calculation Results

The judgment matrix of the target layer is shown in Table 3 after calculation. The subjective weight value for emotional needs B3 was the greatest at 49.3%, far surpassing the values of the other two standard layers. Function component B2 had a subjective weight value of 19.6%, whereas appearance element B1 was rated at 31.1%. The analysis shows that the visual aspect is more important than the functionality, and consumers’ emotional desires for willow household goods are the most crucial.

Tables 4 through 6 provide the judgment matrix for criterion-level, and CR is determined by the consistency test. The test results are shown in Table 7, with a consistency ratio (CR) below 0.10. The judgment matrix’s consistency test has been successful, validating the data’s correctness and enabling it to be used as the basis for additional analysis. The data in Table 8 are organized and calculated, the weight value W_j of the subjective indicator system is determined, and the overall weight of the hierarchy is established.

Stress relief had the highest subjective weight of the 14 elemental layers, at 18.0%, followed by pleasure and weave fineness at 16.2% and 13.2%, respectively, and shape, color, and cultural connotations, tied for fourth. Other elements were subjectively weighted in the following order: Decorative (C10) > Comforts (C6) > Nostalgia (C13) > Usability (C8) > Durability (C9) > Eco-friendly (C5) > Portability (C7).

Table 3. A Target Layer Judgment Matrix

Table 4. B1 Target Layer Judgment Matrix

Table 5. B2 Target Layer Judgment Matrix

Table 6. B3 Target Layer Judgment Matrix

Table 7. Consistency Test CR chart

Table 8. Weight Value of Subjective Evaluation Index System

CRITIC Calculation Results

The experiment got 193 returned questionnaires, excluding 11 invalid questionnaires, to collect 182 valid ones. The data from the questionnaires were averaged to obtain the initial judgment matrix, as shown in Table 9. Equation 6 was applied to the above decision matrix to obtain the normalized decision matrix, as shown in Table 10. Equation 7 was applied to the data in Table 3 above to obtain the value of the correlation coefficient, as shown in Table 10. Based on this, the value of the conflict metric is obtained by calculating Eq. 8, which in turn leads to the amount of information. Based on these values, we calculate the standardized objective weights based on the conflict measure and the amount of information, as shown in Table 11.

Total Weight Calculation Results

Both subjective and objective weights were considered while calculating the final weights. The results showed that C11 (Cultural Value) ranked fourth, C2 (Color), C1 (Molding), and C6 (Comforts) ranked fifth, sixth, and seventh, respectively; C10 (Decorative) and C13 (Nostalgia) tied for eighth; C8 (Usability) and C3 (Size) ranked ninth and tenth, respectively; C5 (Eco-friendly) and C9 (Durability) tied for eleventh; and C7 (Portability) ranked last. C4 (Weaving Fineness) had the highest final weight value, followed by C12 (Stress Relief) at 15.6% and C14 (Pleasure) at 12.2%. This demonstrates that the finest quality of willow products is their acceptable density of preparation.

Table 9. Initial Judgment Matrix

Table 10. Normalized Matrix Table

Table 11. Weights of Objective Evaluation Indicators

Table 12. Table of Total Weight Values

TOPSIS Calculation Results

The TOPSIS comprehensive evaluation’s final evaluation scores are displayed in Table 13. The final rankings, ranked in descending order based on the relative progress of the posting, are S9>S8>S4>S7>S3>S6>S1>S7>S5, at the same time, based on the answers to the final section of the questionnaire, the user’s preference for the nine design options is S9>S4>S8>S7>S6>S3>S7>S1>S5, and combining the two leads to the conclusion that option 9 is the best course of action.

Table 13. Relative Proximity of Programs

DISCUSSION

Using the Analytic Hierarchy Process (AHP) within a standard hierarchical framework, the priority order of contributing criteria for designing willow household items was established. Emotional needs were deemed more crucial than appearance factors, which in turn were considered more significant than functional aspects. Specifically, the aesthetic design of willow-weaving home products was emphasized over their utilitarian design.

In the 14-factor hierarchy, the weights of the first 4 influential factors in willow weaving home product design, determined through the Analytic Hierarchy Process (AHP) and CRITIC comprehensive weight calculation, are ranked as follows: Weaving Density > Stress Relief > Pleasure > Cultural Value. This rating offers a distinct design orientation and emphasis for willow home product design. The future success of willow home furnishing enterprises depends on inventing weaving processes, discovering cultural importance, improving visibility, generating emotional connections, and daring to innovate while pursuing optimum solutions.

The TOPSIS method pinpointed the optimal design for willow weaving household products by comparing evaluation scores, ultimately favoring scheme nine as the prime choice. Scrutinizing the aspects of this exemplary scheme yielded valuable insights for expanding new markets in willow weaving home furnishings. This model facilitated the efficient creation of an evaluation system, ensuring designers consistently capture the core essence of Funan willow weaving products. It curbs the drift caused by empiricism, and it ensures objective evaluation and precise selection of design solutions.

There is value to be gained from investing in scientific and technological research and development to explore innovation and upgrading in the willow weaving industry to enhance product quality. Additionally, mathematical modeling should be integrated with computer-aided design (CAD), 3D printing, and other technologies to create willow weavings (Wang et al. 2023b,c; Xu et al. 2023). Such digital design can achieve more intricate and delicate weaving effects by carefully controlling the wicker’s position and angle (Zheng and Zhu 2021). Furthermore, to fulfill the demands of consumers at all levels, improved production efficiency and product quality are achieved by introducing new production equipment and process technology. It is essential to prioritize environmental concerns and sustainable practices throughout the entire process of sourcing raw materials, manufacturing products, and delivering finished goods (Boran et al. 2013; Ali et al. 2022). Utilizing recyclable, natural, and biodegradable materials is crucial for advancing the willow weaving craft in a more eco-friendly and sustainable direction (Aisyah et al. 2021). This approach aligns with modern societal ideals and adds a fresh, contemporary meaning to willow-weaving items.

Funan willow-weaving household enterprises can benefit from engaging young consumers and implementing industrial upgrades and transformations in the current era. This will lead to the innovative and sustainable development of the Funan willow-weaving household industry. The sample collection for this study primarily consists of individuals from the young age group. Furthermore, the survey participants’ characteristics, including education level, gender, and geographic region, can impact users’ preferred decisions. Future research should increase the sample size to gather user preferences from all age groups for more precise and reliable results. Promoting design innovation in traditional willow weaving items can significantly enhance local inhabitants’ income, facilitate economic change, and support preserving and promoting traditional skills and culture. Those in the business may create new goods that better align with market demands by delving further into users’ requirements and preferences.

CONCLUSIONS

To improve chances for future market success, willow-weaving home product enterprises should thoroughly explore the historical origins, cultural significance, and traditional willow weaving techniques. They should connect these aspects with local folk cultural traditions, festivals, and customs to highlight their importance and role in traditional culture. The cultural elements were found in this work to be the primary competitive advantage of the firm and the cultural basis of the enterprise brand (Wang et al. 2019). Simultaneously, brand building and marketing promotion tailored to the city’s characteristics and user needs (Chen 2021), such as brand storytelling, cultural heritage promotion, and social welfare activities, aim to evoke emotional resonance, strengthen the enterprise’s connection to local culture, enhance humanistic care, and boost brand recognition. This strategy establishes the willow home furnishing enterprise as a regionally distinctive and culturally significant brand.
By merging traditional willow weaving methods with modern aesthetics and market needs (Zheng and Zhu 2021), while preserving unique cultural traits (Zhang and Tsai 2021), utilizing modern technology, and incorporating contemporary creativity and design, the traditional craft will be passed down in a novel manner, fostering its sustainable development. By integrating ancient traditional crafts with modern techniques and design, as well as addressing current life and fashion requirements, the goal is to rejuvenate these crafts through contemporary modes of expression and consistently elevate the cultural significance of willow weaving goods. Incorporate contemporary market awareness to broaden the sales market of willow home products by diversifying product offerings within a reasonable scope. This will align the products with current aesthetic preferences and modern lifestyles, extending beyond furniture to include lamps, ornaments, and other decorative items. The design of wicker household items reflects the peculiarities and appeal of a specific lifestyle, highlighting the importance of traditional handicrafts in contemporary culture.
It is recommended to enhance talent training and skill inheritance to establish a team of specialists in the willow weaving industry and advance the preservation and growth of traditional crafts. The “integration of production, study, and research” approach can be enhanced to improve the current teaching system for sustainable growth of willow weaving abilities by focusing on research, innovation, and creativity to gain consumer market awareness. By promoting the “non-heritage into campus” activity, there is an opportunity to enhance collaboration between schools and businesses (Lee 2005), conduct training and skill competitions, and partner with willow weavers to engage more young individuals in designing willow-weaving household items. This will help comprehend the specific requirements of young people, particularly the millennial generation. The goal is to develop new willow household goods that are modern, high-quality, and crafted with great skill.
It is recommended to proactively in industrial cooperation development, enhance collaboration and interaction with connected local industries, and establish industrial cluster effects. Collaboration with local tourism, cultural creativity, handicrafts, and other industries has potential to boost the overall competitiveness of local cultural industries and collectively advance the development of local distinctive cultural sectors (Sohn 1997). Cultural innovation can drive local economic growth by boosting the cultural spread of Funan willow weaving firms, improving the living standards of local people, and contributing to social advancement.

ACKNOWLEDGMENTS

The authors are grateful the support of the Joint Research Program of Nanjing Forestry University, Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Furnishings and Industrial Design (Nanjing Forestry University, Nanjing 210037, China) and Major Project to Promote the Implementation of the 14th Five-Year Plan for the Integrated Development of the Yangtze River Delta – Public Service Platform for Social Assistance in the Yangtze River Delta (Project Code: 2201.320000-04-04-685162).

REFERENCES CITED

Abudayyeh, O., Zidan, S. J., Yehia, S., and Randolph, D. (2007). “Hybrid prequalification-based, innovative contracting model using AHP,” Journal of Management in Engineering 23(2), 88-96. DOI: 10.1061/(ASCE)0742-597X(2007)23:2(88)

Aisyah, H. A., Paridah, M. T., Sapuan, S. M., Ilyas, R. A., Khalina, A., Nurazzi, N. M., … and Lee, C. H. (2021). “A comprehensive review on advanced sustainable woven natural fiber polymer composites,” Polymers 13(3), article 471. DOI: 10.3390/polym13030471

Akadiri, P. O., Olomolaiye, P. O., and Chinyio, E. A. (2013). “Multi-criteria evaluation model for the selection of sustainable materials for building projects,” Automat Constr 30, 113-125. DOI: 10.1016/j.autcon.2012.10.004l

Ali, H. H., and Al Nsairat, S. F. (2009). “Developing a green building assessment tool for developing countries-case of Jordan,” Build Environ 44(5), 1053-1064. DOI: 10.1016/j.buildenv.2008.07.015

Ali, F., Rehman, F., Hadi, R., Raza, G., Khan, N., Ibrahim, F., Aziz, F., Amin, M., Khalil, B., and Mahwish, M., et al. (2022). “Environmental sustainability assessment of wooden furniture produced in Pakistan,” Brazilian Journal of Biology 84. DOI: 10.1590/1519-6984.253107

Behzadian, M., Otaghsara, S. K., Yazdani, M., and Ignatius, J. (2012). “A state-of-the-art survey of TOPSIS applications,” Expert Systems with Applications 39(17), 13051-13069. DOI: 10.1016/j.eswa.2012.05.056

Chen, D. (2021). “Precision design of Dongguan intangible cultural and creative products based on Big Data analysis technology,” In International Conference on Big Data Analytics for Cyber-Physical-Systems (pp. 467–473). Singapore: Springer Singapore. DOI: 10.1007/978-981-16-7466-2_52

Cheng, Y. M., and Leu, S. S. (2011). “Integrating data mining with KJ method to classify bridge construction defects,” Expert Systems with Applications 38(6), 7143-7150. DOI: 10.1016/j.eswa.2010.12.047

Dalal J, Mohapatra PK, Chandra Mitra G. (2010). “Prioritization of rural roads: AHP in group decision,” Eng. Constr. Archit. Manage. 17(2), 135-158. DOI: 10.1108/09699981011024669

Darko, A., Chan, A. P. C., Ameyaw, E. E., Owusu, E. K., Pärn, E., and Edwards, D. J. (2019). “Review of application of analytic hierarchy process (AHP) in construction,” International Journal of Construction Management 19(5), 436-452. DOI: 10.1080/15623599.2018.1452098

Diakoulaki, D., Mavrotas, G., and Papayannakis, L. (1995). “Determining objective weights in multiple criteria problems: The critic method,” Computers & Operations Research 22(7), 763-770. DOI: 10.1016/0305-0548(94)00059-H

Dias Jr, A., and Ioannou, P. G. (1996). “Company and project evaluation model for privately promoted infrastructure projects,” Journal of Construction Engineering and Management 122(1), 71-82. DOI: 10.1061/(ASCE)0733-9364(1996)122:1(71)

Dlamini, L. C., Fakudze, S., Makombe, G. G., Muse, S., and Zhu, J. (2022). “Bamboo as a valuable resource and its utilization in historical and modern-day China,” BioResources 17(1), 1926-1938. DOI: 10.15376/biores.17.1.Dlamini

Doloi, H. (2008). “Application of AHP in improving construction productivity from a management perspective,” Construction Management and Economics 26(8), 841-854. DOI: 10.1080/01446190802244789

Durmaz, E., Akan, Ş., and Bakır, M. (2020). “Service quality and financial performance analysis in low-cost airlines: An integrated multi-criteria quadrant application,” International Journal of Economics and Business Research 20(2), 168-191. DOI: 10.1504/IJEBR.2020.109149

El‐Sayegh, S. M. (2009). “Multi‐criteria decision support model for selecting the appropriate construction management at risk firm,” Construction Management and Economics 27(4), 385-398. DOI: 10.1080/01446190902759009

Golden, B. L., Wasil, E. A., and Harker, P. T. (1989). “The analytic hierarchy process,” Applications and Studies 2(1), 1-273. DOI: 10.1007/978-3-642-50244-6

Hsu, P. F., Wu, C. R., and Li, Z. R. (2008). “Optimizing resource-based allocation for senior citizen housing to ensure a competitive advantage using the analytic hierarchy process,” Building and Environment 43(1), 90-97. DOI: 10.1016/j.buildenv.2006.11.028

Hwang, C. L., and Yoon, K. (2012). “Multiple attribute decision making: Methods and applications a state-of-the-art survey,” Springer Science and Business Media.

Hyun, C., Cho, K., Koo, K., Hong, T., and Moon, H. (2008). “Effect of delivery methods on design performance in multifamily housing projects,” Journal of Construction Engineering and Management 134(7), 468-482. DOI: 10.1061/(ASCE)0733-9364(2008)134:7(468)

Ibrahim, H. S. M. (2014). Emotional Impact on Furniture Design (Action and Reaction) User-Based Approach, Ph.D. Dissertation, Braunschweig, Hochsch. für Bildende Künste.

Inkuer, A. (2019). “Analysis of wickerwork production processes for labor d”evelopment in production processes,” in: International Academic Multidisciplinary Research Conference, Belgium, pp. 59-64.

Krishnan, A. R., Hamid, R., and Kasim, M. M. (2020). “An unsupervised technique to estimate λ 0-fuzzy measure values and its application to multi-criteria decision making,” in: 2020 IEEE 7^th International Conference on Industrial Engineering and Applications (ICIEA), pp. 969-973. DOI: 10.1109/ICIEA49774.2020.9102098

Krishnan, A. R., Kasim, M. M., Hamid, R., and Ghazali, M. F. (2021). “A modified CRITIC method to estimate the objective weights of decision criteria,” Symmetry 13(6), article 973. DOI: 10.3390/sym13060973

Lai, Y. J., Liu, T. Y., and Hwang, C. L. (1994). “Topsis for MODM,” European Journal of Operational Research 76(3), 486-500. DOI: 10.1016/0377-2217(94)90282-8

Lam, K., and Zhao, X. (1998). “An application of quality function deployment to improve the quality of teaching,” International Journal of Quality and Reliability Management 15(4), 389-413. DOI: 10.1108/02656719810196351

Lee, J. S. (2005). “Through the learners’ eyes: Reconceptualizing the heritage and non‐heritage learner of the less commonly taught languages,” Foreign Language Annals 38(4), 554-563. DOI: 10.1111/j.1944-9720.2005.tb02522.x

Li, J., and Zou, P. X. (2011). “Fuzzy AHP-based risk assessment methodology for PPP projects,” Journal of Construction Engineering and Management 137(12), 1205-1209. DOI: 10.1061/(ASCE)CO.1943-7862.0000362

Li, J., Adnan, H. M., and Gong, J. (2023a). “Exploring cultural meaning construction in social media: An analysis of Liziqi’s YouTube channel,” Journal of Intercultural Communication 23(4), 01-12. DOI: 10.36923/jicc.v23i4.237

Li, Q., Yin, X., Shao, T., Li, X., and Wang, Q. (2023b). “Evaluating human–computer interaction education based on active learning methods using the CRITIC and TOPSIS approach,” Soft Computing 1-14. DOI: 10.1007/s00500-023-08223-8

Liu, J., Kamarudin, K. M., Liu, Y., and Zou, J. (2021). “Developing pandemic prevention and control by ANP-QFD approach: A Case study on urban furniture design in China communities,” International Journal of Environmental Research and Public Health 18(5), article 2653. DOI: 10.3390/ijerph18052653

Liu, M., Zhu, X., Chen, Y., and Kong, Q. (2023a). “Evaluation and design of dining room chair based on analytic hierarchy process (AHP) and Fuzzy AHP,” BioResources 18(2). DOI: 10.15376/biores.18.2.2574-2588

Liu, W., Huang, Y., Sun, Y., and Yu, C. (2023b). “Research on design elements of household medical products for rhinitis based on AHP,” Mathematical Biosciences and Engineering 20(5), 9003-9017. DOI: 10.3934/mbe.2023395

Niu, X., and Xu, D. (2023). “Teaching practice of out-of-school art curriculum in the inheritance of Funan willow weaving technique,” Curriculum and Teaching Methodology 6(13), 38-43. DOI: 10.23977/curtm.2023.061308

Oh, H., and Boo, S. (2021). “Mental health status and health-promoting lifestyle behaviors among call center employees,” Korean Journal of Health Promotion 21(4), DOI: 142-149.KJD: ART002793285

Pan, W., Dainty, A. R., and Gibb, A. G. (2012). “Establishing and weighting decision criteria for building system selection in housing construction,” Journal of Construction Engineering and Management 138(11), 1239-1250. DOI: 10.1061/(ASCE)CO.1943-7862.0000543

Peng, X., Zhang, X., and Luo, Z. (2020). “Pythagorean fuzzy MCDM method based on CoCoSo and CRITIC with score function for 5G industry evaluation,” Artificial Intelligence Review 53(5), 3813-3847. DOI: 10.1007/s10462-019-09780-x

Pizzato, G. Z., and de Macedo Guimarães, L. B. (2019). “Emotional attributes of urban furniture,” in: Proceedings of the 20^th Congress of the International Ergonomics Association (IEA, 2018) Volume VII: Ergonomics in Design, Design for All, Activity Theories for Work Analysis and Design, Affective Design 20 (pp. 2087-2097). Springer International Publishing. DOI: 10.1007/978-3-319-96071-5_218

Raycheva, R., and Angelova, D. (2017). “Woven furniture design: in search of form and texture,” Pro Ligno 13(4).

Romero, M. A. (2005). “Towards development of the Chilean basket willow sector,” UNASYLVA-FAO-, 56(2), 40.

Saaty, T. L. (1985). “Decision making for leaders,” IEEE Transactions on Systems, Man, and Cybernetics (3), 450-452. DOI: 10.1109/TSMC.1985.6313384

Saaty, T. L. (2008). “Decision making with the analytic hierarchy process,” International Journal of Services Sciences 1(1), 83-98. DOI: 10.1504/IJSSCI.2008.017590

Saaty, T. L. (2001). “Fundamentals of the analytic hierarchy process,” in: The Analytic Hierarchy Process in Natural Resource and Environmental Decision Making 15-35. DOI: 10.1007/978-94-015-9799-9_2

Shapira, A., and Goldenberg, M. (2005). “AHP-based equipment selection model for construction projects,” Journal of Construction Engineering and Management 131(12), 1263-1273. DOI: 10.1061/(ASCE)0733-9364(2005)131:12(1263)

Shen, G., Song, X., and Gao, G. (2022). “The development path of the integration of folk art and rural revitalization in the areas along the Huaihe River in Anhui Province,” Highlights in Art and Design 1(3), 94-96. DOI: 10.54097/hiaad.v1i3.3574

Sohn, S. O. (1997). “Issues and concerns in teaching multi-level classes: Syllabus design for heritage and non-heritage learners,” Korean Language in America, 139-158.

Sun, N., He, Y., Wang, C., and Zhang, J. (2023). “Research on sustainable design of consumers’ influence factors of Huaihe Willow Weaving based on AHP,” Sustainability 15(14), article 11115. DOI: 10.3390/su151411115

Tavares, R. M., Tavares, J. L., and Parry-Jones, S. L. (2008). “The use of a mathematical multicriteria decision-making model for selecting the fire origin room,” Building and Environment 43(12), 2090-2100. DOI: 10.1016/j.buildenv.2007.12.010

Tian, G., Zhang, H., Zhou, M., and Li, Z. (2017). “AHP, gray correlation, and TOPSIS combined approach to green performance evaluation of design alternatives,” IEEE Transactions on Systems, Man, and Cybernetics: Systems 48(7), 1093-1105. DOI: 10.1109/TSMC.2016.2640179

Vujičić, M. D., Papić, M. Z., and Blagojević, M. D. (2017). “Comparative analysis of objective techniques for criteria weighing in two MCDM methods on example of an air conditioner selection,” Tehnika 72(3), 422-429. DOI: 10.5937/tehnika1703422V

Wang, C., and Zhou, Z. (2023). “Optical properties and lampshade design applications of PLA 3D printing materials,” BioResources 18(1), 1545-1553. DOI: 10.15376/biores.18.1.1545-1553

Wang, T., Fu, J., Yang, L., and Gao, X. (2023a). “Study on the living inheritance strategies of Funan wickerwork in the context of rural revitalization,” in: International Conference on Human-Computer Interaction ,Cham: Springer Nature Switzerland, pp. 518-526. DOI: 10.1007/978-3-031-35998-9_67

Wang, T., Ma, Z., and Yang, L. (2023b). “Creativity and sustainable design of wickerwork handicraft patterns based on artificial intelligence,” Sustainability 15(2), article 1574. DOI: 10.3390/su15021574

Wang, T., Ma, Z., Zhang, F., and Yang, L. (2023c). “Research on wickerwork patterns creative design and development based on style transfer technology,” Applied Sciences 13(3), article 1553. DOI: 10.3390/app13031553l

Wang, W. M., Wang, J. W., Li, Z., Tian, Z. G., and Tsui, E. (2019). “Multiple affective attribute classification of online customer product reviews: A heuristic deep learning method for supporting Kansei engineering,” Engineering Applications of Artificial Intelligence 85, 33-45. DOI: 10.1016/j.engappai.2019.05.015

Wind, Y., and Saaty, T. L. (1980). “Marketing applications of the analytic hierarchy process,” Management science 26(7), 641-658. DOI: 10.1287/mnsc.26.7.641

Xie, X., Zhu, J., Ding, S., and Chen, J. (2023). “AHP and GCA combined approach to green design evaluation of kindergarten furniture,” Sustainability 16(1), article 1. DOI: 10.3390/su16010001

Xiong, X. Q., Guo, W. J., Fang, L., Zhang, M., Wu, Z. H., Lu, R., and Miyakoshi, T. (2017). “Current state and development trend of the Chinese furniture industry,” Journal of Wood Science 63, 433-444. DOI: 10.1007/s10086-017-1643-2

Xiong, X., Ma, Q., Wu, Z., and Zhang, M. (2020). “Current situation and key manufacturing considerations of green furniture in China: A review,” Journal of Cleaner Production 267, article 121957. DOI: 10.1007/s10086-017-1643-2

Xu, J., Gong, J., and Ji, D. (2023). “Exploring the determinants of users’ co-creation behavior on music streaming platforms in China,” PLOS One 18(12), e0291313. DOI: 10.1371/journal.pone.0291313

Yoon, K. (1980). Systems Selection by Multiple Attribute Decision-Making, Kansas State University.

Yu, C., Liu, W., Fei, Y., Chen, J., and Hu, Z. (2023a). “Influencing factors of online furniture purchase behavior based on analytic hierarchy process,” BioResources 18(2), article 2857. DOI: 10.15376/biores.18.2.2857-2873

Yu, N., Wang, J., Hong, L., Tao, B., and Zhang, C. (2021). “Evaluation of the color aesthetics of fine wood based on perceptual cognition,” Bioresources 16(2), 4126-4148. DOI: 10.15376/biores.16.2.4126-4148

Yu, S., Zheng, Q., Chen, T., Zhang, H., and Chen, X. (2023b). “Consumer personality traits vs. their preferences for the characteristics of wood furniture products,” BioResources 18(4), 7443-7459. DOI: 10.15376/biores.18.4.7443-7459

Zhang, H., Bai, X., and Hong, X. (2022a). “Site selection of nursing homes based on interval type-2 fuzzy AHP, CRITIC and improved TOPSIS methods,” Journal of Intelligent and Fuzzy Systems 42(4), 3789-3804. DOI: 10.3233/JIFS-212010

Zhang, L., and Zhang, X. (2020). “Research on the application of Funan willow weaving and ceramic material fusion,” J. Guangxi Norm. Univ. Natl 3, 84-87.

Zhang, S., Zhu, J., Wang, G., Reng, S., and Yan, H. (2022). “Furniture online consumer experience: A literature review,” BioResources 17(1), 1627-1642. DOI: 10.15376/biores.17.1.1627-1642

Zhang, W., and Tsai, S. B. (2021). “An empirical study on the artificial intelligence-aided quantitative design of art images,” Wireless Communications and Mobile Computing 2021, 1-11. DOI: 10.1155/2021/8036323

Zhang, X., Li, H., Tian, X., Zhang, R., and Qi, Q. (2022b). “Certificateless authentication scheme based on blockchain in smart home network,” Mathematical Problems in Engineering 2022(1), article 6458461. DOI: 10.1155/2022/6458461

Zhao, Y., and Xu, Y. (2023). “Evaluation model for modular children’s wooden storage cabinet design,” BioResources 18(4), 7818-7838. DOI: 10.15376/biores.18.4.7818-7838

Zheng, Y., and Zhu, J. (2021). “The application of bamboo weaving in modern furniture,” BioResources 16(3), 5024-5035. DOI: 10.15376/biores.16.3.5024-5035

Zhou, C., Huang, T., Luo, X., Kaner, J., and Fu, X. (2022). “Recognition and analysis of an age-friendly intelligent sofa design based on skeletal key-points,” International Journal of Environmental Research and Public Health 19(18), article 11522. DOI: 10.3390/ijerph191811522

Zhu, H. (2021). “Analysis on the effect of willow weaving service industry development in county industry – Based on Funan willow,” Financial Forum 10(2), 7-15. DOI: 10.18282/ff.v10i2.1942

Article submitted: May 8, 2024; Peer review completed: July 17, 2024; Revised version received: July 19, 2024; Accepted: August 31, 2024; Published: September 12, 2024.

DOI: 10.15376/biores.19.4.8216-8237