Wooden door preferences based on lifestyle theory and consumer behaviour theory

Abstract

This paper analyses users with different lifestyles and consumer behaviour, and then segments wooden door users with different consumer preferences, to inspire wooden door companies in their product design and further research on wooden doors. In this paper, a wooden door user research questionnaire was created based on Lifestyle Theory and Consumer Behaviour Theory, and data collection was completed at Nanjing Forestry University. The collected data were analysed using cluster analysis, factor analysis, cross-over analysis, and other analysis methods. The Statistical Package for the Social Sciences (SPSS) was used to simplify the analysis model and process the data, and finally the wooden door users were divided into four categories. The categories were trendy home users, budget-conscious sensible users, basic needs users, and impulsive enjoyable users. Male users were found to be more likely to be “trendy home users” and “impulsive enjoyable users,” while female users were more likely to be “budget-conscious sensible users” and “trendy home users.” For the number of users, the “trendy home users” were the most numerous, followed by the “budget-conscious sensible users.” The age of wooden door users in this study was mainly distributed between 21 to 30 years old, of which “freelancers” accounted for the highest percentage.

Full Article

Wooden Door Preferences Based on Lifestyle Theory and Consumer Behaviour Theory

Chengmin Zhou,^a,b,* Qiyu Wang,^a,b Jake Kaner,^c and Yixin Lv ^a,b

This paper analyses users with different lifestyles and consumer behaviour, and then segments wooden door users with different consumer preferences, to inspire wooden door companies in their product design and further research on wooden doors. In this paper, a wooden door user research questionnaire was created based on Lifestyle Theory and Consumer Behaviour Theory, and data collection was completed at Nanjing Forestry University. The collected data were analysed using cluster analysis, factor analysis, cross-over analysis, and other analysis methods. The Statistical Package for the Social Sciences (SPSS) was used to simplify the analysis model and process the data, and finally the wooden door users were divided into four categories. The categories were trendy home users, budget-conscious sensible users, basic needs users, and impulsive enjoyable users. Male users were found to be more likely to be “trendy home users” and “impulsive enjoyable users,” while female users were more likely to be “budget-conscious sensible users” and “trendy home users.” For the number of users, the “trendy home users” were the most numerous, followed by the “budget-conscious sensible users.” The age of wooden door users in this study was mainly distributed between 21 to 30 years old, of which “freelancers” accounted for the highest percentage.

DOI: 10.15376/biores.18.1.1616-1636

Keywords: Lifestyle theory; Consumer behaviour theory; Market segment; Wooden door; Factor analysis

Contact information: a: College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China; b: Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, Jiangsu, China; c: Nottingham School of Art and Design, Nottingham Trent University, Nottingham NG1 5FQ, UK; *Corresponding author: zcm78@163.com

INTRODUCTION

It is known that product differentiation has become progressively more difficult with the increase in the degree of industrial intensification (Pan et al. 2022). Whether the colour, material, surface decoration, and function of the product can make consumers happy has become an important factor for consumers to decide to buy and use the product (Oh et al. 2014). With the gradual segmentation of the wooden door market and the gradual development of new retail, the vast amount of consumer information and user demand has posed a serious challenge to wooden door companies (Wang et al. 2021a). Therefore, accurate access to the emotional needs and usage preferences of users with different lifestyles and consumption characteristics, and the successful translation of this information into design elements for wooden doors, are important factors in improving the success rate of product development (Wang et al. 2021b). With the advent of the Industry 4.0 era, Computerized Numerical Control (CNC), 3D printing, digital intelligence production, and as other high-tech technologies become mature (Shi and Ling 2022), customised production becomes possible. While some traditional wooden door enterprises still retain the “enterprise production, what consumers buy” thinking, it is difficult to seize the rapidly changing market opportunities (Tafesse and Shonde 2016). Therefore, the transformation of wooden door enterprises is imminent, using more flexible production methods to respond to market changes and more accurate user pain points to capture the increasingly segmented market (Song et al. 2022). This transformation is also gradually gaining the full attention of companies and product designers. For decision-makers, it is crucial to accurately target the preferences of different consumer groups. If valuable information can be obtained in the early stages of product development, it will be more beneficial for companies to make favourable decisions (Ren and Xiong 2022). At the same time, if designers have a statistically categorised design guide to follow that contains a breakdown of consumer preferences for different lifestyles and consumption characteristics, it can help designers quickly adapt existing designs or develop new products based on feedback from big data (Parsad et al. 2019).

Lifestyle is a collection of elements that reflect the state of life, thoughts, interests and more of the consumers. The consumption behaviour of the consumers is also influenced by these elements. Therefore, consumer lifestyle and consumer behaviour are mutually influential. Therefore, the lifestyle and behaviour of the consumers are mutually influential (Mridanish 2013). Wijaya (2021) analysed the association between the consumption behaviour and lifestyle of urban youth, the main consumers of 24-hour branded cafes in small, medium, and large cities in Indonesia. The study found that these urban youths often gather here to work, chat, and spend time. Such a lifestyle expresses these urban youth’s desire for worldly pleasures and success. Brunkwall et al. (2019) found that high consumption of sugary drinks (SSB), artificially sweetened beverages (ASB), fruit juices, tea, and coffee were associated with dietary habits of people (low-fat diet or high-fat diet). These studies demonstrate the close link between lifestyle and consumer behaviour, with lifestyle partly determining consumer behaviour, which in turn influences consumer lifestyle. Therefore, the study of consumers’ preferences for different wooden doors can start with their lifestyle and consumption behaviour.

Consumers in different living environments and cultural backgrounds have vastly different purchasing criteria for products, hence the need to segment the market. Market segmentation refers to the division of products produced by companies to face different consumer groups according to the different life patterns and consumption habits of different consumers in the market (Ourania et al. 2021). Market segmentation can help consumers to purchase the products they need at a reasonable price, and also help enterprises to grasp the target market and target users in a targeted manner, highlight the advantages of product differentiation, and maximize the use of resources for product development. Zhu et al. (2010) investigated whether product attributes influence how consumers perceive a product or service to be relevant to their needs. Using field research on the mobile charging needs of consumers in the Chinese mobile phone market, they verified that the preferences of consumers for product attributes are significantly related to their lifestyle and explore the importance of segmenting the market based on lifestyle. Song (2016) categorised wine consumers according to their food-related lifestyle patterns and used the categorisation to identify variations in wine choice attribution. Ultimately, they suggest the need to develop a wine marketing strategy that differentiates wine according to consumer lifestyles. The above studies all show the importance of segmenting the consumer market based on lifestyle and consumer behaviour. This approach to product design is becoming increasingly popular with companies and the market because of its humanistic design approach and diverse product lines, which are oriented towards life forms and combined with analysis of consumer behaviour and market segmentation. This approach to product design is an integrated human (user)-machine (product)-environment (natural and social environment) design approach that highlights the principle of human-centred design, starting with planning the human form of existence for product design. In the past, consumer research in the design world did not start by systematically considering the life form of the consumer but often started with an isolated product or part of it (Andreoni et al. 2012). Today, the study of life forms has matured and is widely used in product development to segment markets by consumer lifestyles rather than by traditional levels of technology (Huang 2014). Therefore, this paper examines wooden door users based on life and consumer behaviour theories and segments wooden door user groups, and thus discusses the differences in consumer behaviour and needs of different segments.

In recent years, global research on wooden doors has focused on a review of wooden door consumer trends and research on the wooden door manufacturing processes, as well as physical and chemical properties, with less research on wooden door design and almost no research on wooden door users. Zhu et al. (2021) proposed an innovative method for reinforcing wooden door frames with channel steel and diagonal bracing to prevent the wooden door frames of traditional rural houses from jamming due to deformation during earthquakes and to improve the seismic resistance of rural houses. Cobut et al. (2015) proposed an ecological design strategy based on alternative scenario generation and assessment based on the results of previous life cycle assessment (LCA) studies on interior wooden doors, by improving the three steps in the manufacturing of wooden doors – particleboard components, transportation, and end-of-life – for ecological design purposes. Xiong et al. (2021) investigated the use of group technology to standardise the production of children’s solid wood furniture parts. Based on the principle of similarity in processing and technology, the authors grouped furniture parts of similar dimensions and established a children’s solid wood furniture parts family, which greatly improved the standardisation of solid wood parts. Jiang et al. (2020) investigated the influence of young children’s colour preferences on furniture selection and concluded a positive correlation, but the extent varied by furniture category and by furniture in different functional spaces. Yu et al. (2021) used a combination of eye-tracking techniques and subjective evaluations to investigate preferences for rosewood and wenge wood of different shades and lightness values. Hu et al. (2020a) summarised the current development status and problems of the traditional wood dyeing process and the induced colour change process and proposed colour improvement with photonic crystal structures—a clean and pollution-free ecological biomimetic colouring technology.

In practice, user groups have different preferences for materials, structures, colours, and styles for the same type of product because of the subtle differences in body structure and life experiences. Therefore, consumers with different lifestyles and consumer preferences will have different choices for wooden doors. However, there is a lack of research on the preferences of different consumers for wooden doors in existing studies. Therefore, based on the theory of user life form and the relationship between consumer behaviour and market segmentation, this paper conducts research on wooden door users and uses cluster analysis, factor analysis, and cross-tabulation analysis to process the data, to generally summarise a wooden door user profile suitable for different life forms and consumption preferences, so as to effectively improve the theoretical and engineering applicability of wooden door design.

EXPERIMENTAL

This paper uses the questionnaire method to collect data on wooden door users. The first step was the theoretical research and data collection on lifestyle theory, consumer behaviour theory, wooden door users, and the market, as a basis for questionnaire design. The design of the questionnaire was based on the Values and Lifestyle Survey (VASL) scale (the VASL scale is a lifestyle model proposed by the Stanford Research Centre in 1978). During the questionnaire design process, the opinions of actual users and experts and scholars were extensively solicited, and 3 predetermined proposals were finalised after several revisions. After comprehensive scoring by experts and scholars, the one with the highest rating was selected as the final questionnaire for extensive information collection. After a one-month research process, the data collected were first analysed and collated. Then they were analysed using various analytical methods such as cluster analysis, factor analysis, and cross-over analysis. This made it possible to finally segment wooden door users according to their lifestyle and consumption characteristics and analyse the wooden door preferences of different consumer groups, to form an academic study of the wooden door industry, wooden door companies, wooden door users, and wooden door design. The research results are of high importance and value to the wooden door industry, wooden door companies, wooden door users, and academic research on wooden door design. The basic research line is shown in Fig. 1.

Fig. 1. Basic research approach

Questionnaire Design

This paper was based on the lifestyle theory and consumption behaviour, and conducts a questionnaire survey on wooden door users to obtain information about their lifestyle and consumption behaviour characteristics, such as their basic information, values, and wooden door consumption tendencies, to consider the consumption characteristics and actual needs of different wooden door user groups for wooden door products to provide a basis for market segmentation and product positioning for wooden door enterprises to design products.

The research was based on the VALS scale and the Likert five-step method for questionnaire design (Aren and Yildirim 2019). The questionnaire was divided into 3 parts (Table 1) to collect information from wooden door users, in the order of basic information about wooden door users, life patterns of wooden door users, and product preference characteristics of wooden door users. The second and third parts of the questionnaire were filled in using the Likert five-step scale, with scores ranging from 1, 2, 3, 4, and 5. The respondents needed to score each question. The score on the left was 5, so a higher score to the left indicates that the question was more in line with the thoughts of the respondents. The score on the right was 1, so a core further to the right indicated that the question was far from the thoughts of the respondents.

Table 1. Wooden Door Users Survey Questionnaire

Questionnaire Implementation and Recovery

One aim of this study was to analyse the wooden door preferences of users with different lifestyles and consumption behavior. The idea was to avoid too many subjects with no concept or experience of wooden door consumption participating in the study. Another aim was to collect as comprehensive information as possible from subjects with different lifestyles and consumer behavior. This study used a combination of inviting subjects and widely distributed questionnaires to collect data from members of the community.

To reduce the interference of external environmental factors to obtain more objective and accurate experimental data, the experiment was conducted in a controlled variable format by inviting subjects to the laboratory at Nanjing Forestry University. The laboratory conditions required were daytime, good lighting conditions, quiet area, and suitable temperature and humidity. A total of 35 subjects, all of whom were faculty members, postgraduates, and undergraduate students from the College of Furnishings and Industrial Design at Nanjing Forestry University, were involved in the experiment. The subjects were therefore either actual purchasers of wooden doors or had specialist knowledge of wooden doors. The subjects all had normal colour discrimination (no colour blindness or colour weakness) and a corrected visual acuity of 5.0 in both eyes and participated in the experiment voluntarily. The subjects were required to sit still in the test environment for 10 min before starting the experiment, and after they had sufficiently acclimatised to the test environment, they began the experiment. The experiment began with a chaotic display of four wooden door scenes in the styles of “natural ecology”, “simple modern”, “trendy fashion”, and “light luxury modern”. The purpose of the experiment was to help the subjects construct an impression of the wooden doors and to adapt quickly to the experiment. The images were created by the authors and selected by expert academics to cover as many styles of wooden doors on the market as possible. Each image was displayed for 10 s, a blank image was displayed for 2 s at the end of each image, and the questionnaire was filled in after all the images had been displayed. The questionnaire was widely distributed within Nanjing Forestry University and on the online platform while conducting the experiment inviting subjects to participate. The main targets audience of the questionnaire were the faculty members and students of Nanjing Forestry University, their families, and the surrounding residents. A total of 130 questionnaires were eventually completed, of which 123 were valid, with an effective rate of 94.62% and a total of over 27,000 pieces of useful data obtained. The data are shown in Table 2.

Table 2. List of All Valid Items

Methods of Analysis

A description of the user’s lifestyle and consumer behaviour dimensions and variables is numerous, and the complexity of the relationship between the variables and to qualitative description or analysis of the data is difficult, so in this paper, cluster analysis, factor analysis, cross-over analysis, and other analysis methods were adopted to analyse survey data. The software SPSS 26.0 (IBM, Armonk, NY, USA) was used to simplify and analyse these data. Then, the preferences of different wooden door users were summarised.

Cluster Analysis

Cluster analysis is a data processing process that classifies a collection of multiple groups of data into different clusters consisting of similar groups, with strong similarities between the same clusters and large differences between different clusters (Heinz et al. 2020). This paper used systematic cluster analysis to analyse the data, and the process of clustering and the results are visually presented in the form of a tree genealogy diagram. The serial numbers of the lifestyles have been numbered in Table 2, using 1-42 for U11-U39. This facilitates the presentation of pictures and tables later in this discussion. Questions U38 and U39 in the questionnaire were removed from the analysis, as there was no survey respondent selection. So in Fig. 2, only ordinal numbers 1 to 40 are available, missing 41 and 42, the corresponding U38 and U39. Figure 2 shows the results of the cluster analysis of the wooden door user data. Making a vertical line from the quantified value of 5 allows the variables to be grouped into 6 categories, with the classification and characteristics of each category described as follows.

Fig. 2. Cluster analysis of user’s lifestyle

The main characteristics of the first type of user can be summarized as “fashion forward and overspending”. This type of user is mainly characterised by an outgoing personality, a willingness to socialise and make friends, a passion for trends and fashions, a love of trying new things, a bold and avant-garde outlook on consumption, and a tendency to consume impulsively and excessively.

The main characteristics of the second type of user can be summarized as “love of life and enjoy the home”. This type of user is happy to enjoy the fun of life, pay attention to self-image, and prefer home life.

The third type of user has only a “sense of excitement” as a separate variable, which can be analysed as an outlier and clustered with the first and second types in the clustering process.

The main characteristics of the fourth type of user can be summarized as “focus on the whole, seeking a sense of belonging”, mainly focusing on self-respect, the pursuit of a sense of belonging, a sense of security values, concern for the material of wooden door products and the overall effect of the interior.

Table 3. List of All Valid Items

The main characteristics of the fifth type of user can be summarized as “quality of life, seeking a sense of achievement”, manifested as concern for the shape, price, and function of wooden door products, the purchase of products focused on price, brand, quality, and products to bring their own sense of achievement and satisfaction, will be rational consumption through analysis and consideration.

The main characteristics of the sixth type of user can be summarized as “colourful life, cautious shopping”, which shows that they like to live a colourful life and are more concerned about the cost performance and colour of wooden door products, and will purchase cautiously through multiple comparisons, expecting to gain respect from others and self-satisfaction. The characteristics of wooden door users are described in Table 3.

Factor Analysis

Factor analysis is a method of statistical analysis that takes the study of the internal relationships of variables as a starting point. It reduces a large number of intricate variables into a few common factors of multiple variables. In the same group of variables composed of public factors, the similarity and correlation between variables are high, and the variables differ significantly between different groups of public factors (Wang et al. 2022). Through conducting factor analysis on the raw data of different wooden door users’ lifestyles and consumption behaviour, the public factors were extracted and analysed to make the relationship between users’ life patterns and wooden door consumption preferences clearer and more concise.

Fig. 3. Gravel diagram of the common factor

Table 4 shows the total variance explained before and after rotation of the factor analysis, where the eigenvalues of the first 9 public factors are greater than 1 and the eigenvalues after the fifth public factor are extremely small. As can be seen from Fig. 3, the curve gradually slopes from the 3^rd and 4^th factors and tends to zero after the 5^th factor. The first 9 common factors were therefore extracted and their interpretation named. The factor loading values of each common factor after rotation were ranked from largest to smallest, and the factor with the higher loading value was extracted to yield the descriptive statistics of the 9 common factors as shown in Table 4.

User features with large factor loadings (factor loadings > 0.5) were retained, so U21, U29, U211, U35, and U36 were removed and the remaining 35 user preferences were categorised. According to Table 5, public factor 1 is the factor with the highest loadings. The main characteristics of users of this factor are “always use products of your favourite brand”, “be willing to buy only what you think is important”, “feel different and have unique tastes”, “be willing to make new friends”, “prefer popular products over practical ones”, and “do things on a whim”, etc. It can be seen that these users have certain economic power and social status, they focus on the pursuit of quality, enjoy life, and are sociable. This is why this group of users, represented by public factor 1, is named “pursue quality, enjoy life”.

Table 4. Total Variance Explained