DOI: https://doi.org/10.21203/rs.3.rs-2752527/v1
Adaptation of the customer expectations to the product is a requirement of quality-oriented structuring. Starting from here, it is necessary to research the expectations and priorities of the customers at certain time intervals and to reflect these expectations on the product. This study aimed to determine factor priorities in purchasing furniture and effect levels of each factor on furniture purchase decisions according to some socio-demographic characteristics of consumers such as gender, marital status, age and education level in Türkiye. The questionnaire method has been used to determine the effect levels of 1–9 scale of 14 furniture specifications such as material, brand image, quality certificate, service life, safety, aesthetics, durability, etc. on furniture purchase decisions according to consumers’ characteristics. The data obtained from the questionnaire forms of 1218 individuals who participated online through Google Forms were analyzed statistically. Regardless of any socio-demographic characteristics, functionality is the most effective factor in furniture purchasing, followed by lifetime and aesthetics. Ease of assembly is the least effective factor. The furniture specifications such as quality certification, lifetime, reliability, aesthetics, size, functionality, durability, warranty and after-sales services are more effective in women's purchasing decisions than men's. The specifications of brand value, lifetime, aesthetics, size, price and ease of assembly are ineffective in the purchasing decisions of individuals from different age groups. In addition, the effect levels of the factors vary according to marital status and education level. The results obtained from this research will be useful in making managerial decisions about marketing.
Quality is defined as “ability of the goods and services produced by enterprises to satisfy customers and positive and negative effects created on customers”. It includes adequacy of the functional specifications of the products produced by enterprises, as well as the perceived values and benefits it provides to customer (TSE EN ISO 9000, 2015). Other international institutions operating quality make similar definitions: American Association for Quality Control – ASQC: "All characteristics that reveal the ability of products to meet consumer demands", Japanese Industrial Standards Committee - JIS : "A production system that economically produces the products that respond to consumer requests" and European Quality Control Organization - EOQC : "level of conformity of a product to consumer's expectations " (Yeşilbayır, 2007). Based on these definitions, quality can be defined as “Consumer perception of level of satisfaction of the benefits created by product specifications ". Product specifications vary depending on whether a product is Goods or service type. While functionality, durability, reliability, aesthetics, safety, and price are the specifications of goods such as furniture, automobiles, houses etc., competence, courtesy, trust, safety and speed are the specifications of service type products such as banking, logistics, etc. If the benefits created by these product specifications are at a satisfactory level in the mind of a consumer in meeting his/her needs, that product is defined as high quality; otherwise, it is defined as poor quality.
Customer satisfaction is defined as “Suitability of the product purchased by a customer to her/his own wishes and needs”. Each customer has personal expectations about the product they will buy, and after the purchase, they make an evaluation regarding satisfaction of these expectations. As a result of this evaluation, a state of “Satisfaction” or “Dissatisfaction” occurs. Customer satisfaction or dissatisfaction is not a part of goods or services, but a perception that the customer personally attributes to the goods or services. For this reason, satisfaction levels may vary when different customers encounter the same experience or service due to the emotional and cognitive components (Banar & Ekergil, 2010).
In order to ensure customer satisfaction and loyalty, all units of a business should put the customer, not product, at focus, in order to fully meet the wishes and needs of current and potential customers, customers should be recognized, understood and segmented, and efforts should be made to customize products sufficiently. This understanding is called “Customer orientation” (Soysal, 2015).
In the furniture market together with other markets, as a requirement of the customer-oriented approach, many studies are conducted on purchasing behaviors of the customers and the furniture specification highlighted during purchasing process in order to create a quality level that will fully meet customer expectations and wishes regarding the product specifications.
The consumer preferences regarding furniture specifications may differ according to countries. The product specifications that were most considered when purchasing furniture in Slovak Republic were, respectively, quality, price and style. As a style, modern designs were more preferred. The purchases were made primarily from store; catalog and online purchases came later (Kaputa & Šupín, 2010). In purchase of indoor and outdoor furniture in Slovakia and Croatia, the consumer preferences related to price, style, production quality and color of furniture did not differ, while significant differences in consumer preferences of two countries related to safety, brand, warranty and environmental impact of furniture have been identified. In both countries, country where furniture was produced was ineffective in the purchase decision, while the local manufacturers are preferred over foreign manufacturers. Although there was no objection to presence of different materials in furniture, solid wood material was primarily preferred in both countries. In both countries, the price was primarily effective in the purchase decision and production quality, style, warranty, safety and color are other effective factors (Kaputa et al., 2018). In the research examining the attitudes of consumers in Germany towards light furniture and the use of light wood-based materials in furniture design, weight feature has not been found to have a primary effect on attracting customers' attention, unlike more relevant factors such as quality, price and design (Knauf, 2015). Except for the 31–40 age group consumers who preferred furniture made of materials such as particleboard and fiberboard in Slovenia and Croatia, other consumers preferred furniture made of solid wood. In Serbia, consumers under age of 40 and over 60 preferred solid wood furniture, while others preferred furniture made of wood-based boards. In Slovenia, consumers aged 31–40 and over 60 preferred high-priced furniture, while others preferred average-priced furniture. In Serbia, the group up to age of 40 preferred high-priced furniture, the group aged 41–60 preferred average price and the group over 60 preferred low-priced furniture. In Croatia, consumers up to age of 40 preferred high-priced furniture, while consumers aged 41–50 and over 60 preferred low-priced furniture. In all three countries, the price was the primary factor in purchasing, followed by material and service factors, respectively (Oblak, Glavonjić, et al., 2020). Since it was higher in terms of design and quality criteria in Tanzania's Dar Es Salaam and Arusha cities, imported furniture was more preferred than local furniture. In low-income groups, local furniture was preferred because of its cheapness (Kumburu & Kessy, 2021). In a study in Finland, focusing on the development of marketing strategies by going to market segmentation depending on the differences in the constructions of wooden home furniture, quality and design are the most important features in all market segments, while style and advertising are determined as the last attributes (Pakarinen & Asikainen, 2001). In terms of naturalness, ecological features, environmental impact, renewability, traditions, health and safety, wood materials were the most preferred materials in indoor furnishing elements in Slovakia and Poland. Combustion strength, health, safety and durability were prominent specifications of consumers' choice of materials in both countries (Paluš et al., 2012).
The preference priorities regarding product specifications such as functionality, reliability, durability, safety, aesthetics, type of material used, price, brand and brand image, economy, origin, etc. vary according to personal, sociological and psychological characteristics of the consumers.
Consumers in Kayseri city/Türkiye planned to use the seating furniture they bought until they were completely worn out, as well as planned to use them for at least 6–10 years. In terms of purchasing preferences, they were taking into consideration aesthetics, ease of use and reasonable price while, in fabric preference, they want the fabric to be of high quality, cleanable and washable (Güzel, 2020a). Durability was the primary factor in furniture preferences of male and female employees on Hacettepe University campuses. Durability was also a top priority for all education levels. While variables of durability and economy came to fore in choice of living furniture by consumers of all education levels, aesthetic variable in dining room furniture and durability in bedroom furniture was also in foreground (Öztop et al., 2008). While consumer groups that followed fashion preferred Ming-style furniture with curved and complex lines, utilitarian consumer groups preferred straight, delicate and simple Ming-style furniture. The consumer group, which was called moderate in terms of style between these two extremes, did not have a clear preference for form (Liu et al., 2017). In used furniture, the consumers made purchases depending on six criteria that were sustainability, originality, quality, having a story, structural integrity and price. The consumers who prioritize sustainability criteria also cared about robustness and structural integrity. The consumers who seek originality in purchase of used furniture did not care about structural integrity and focused on product differences. The consumers who prioritize quality were not sensitive to price and highlighted functional satisfaction of the product. The consumers who expect furniture having a story in the past cared about quality as well as originality and did not care about price. The consumers who seek structural integrity in furniture wanted their robustness and quality materials to be used. Price-priority purchasers were insensitive in terms of sustainability, having a story and originality criteria (Viikari, 2021). When choosing Rattan furniture compared to other furniture, modernity, environmental awareness, social status and sustainability criteria were at the forefront, respectively.
Social status, modernity and environmental sensitivity criteria were at the forefront in purchasing rattan furniture (Amoah et al., 2015). Quality, design, price, environmental sensitivity and warranty were main criteria that Iranian consumers highlighted in purchase of furniture. Iranian consumers stated that furniture made of engineered wood was heavy and they could buy furniture made of light panels with filling construction, even if it was at a 5–9% higher price, provided that it was environmentally friendly labeled and guaranteed and provided more product variety (Khojasteh-Khosro et al., 2022). Similarly, in the ANP-based survey study conducted on Iranian consumers' use of light panels in furniture manufacturing and their must-have features; It has been revealed that product design, quality and price are effective sub-criteria for furniture manufacturers (Khojasteh-Khosro et al., 2020). Consumers were aware of the fact that wood is a natural and organic material, and this fact was main reason for preference in purchasing of wood as a material in furniture and other furnishing elements. Consumers stated that they might prefer furniture made of wood composites in the case of product functionality and product diversity in design, since solid wood was expensive (Güzel, 2020b). For furniture made of oak, birch, spruce, cherry, maple and alder, wood species-price relationship was insignificant in sales made at two different prices with and without specifying the wood specie. In sales made at high prices, the products made from cherry were preferred if wood specie was labelled on product, and the products made from oak were preferred wood specie was not labeled. When price level and wood species labeling variables were ignored, cherry and oak were the most preferred wood species in furniture (Bumgardner et al., 2007). In Slovenia, there were differentiations regarding the criteria taken into account in the purchase of furniture between the years 2010–2019. The most preferred material for both indoor and outdoor furniture was solid wood. Between the aforementioned dates, while preference rate for indoor furniture has increased, preference rate for outdoor furniture has decreased. Wood composites and mixed materials are second and third most preferred materials for indoor furniture. In outdoor furniture, mixed material furniture preference was in second place. Quality was the top priority criterion in purchase of furniture, followed by design and color. The country where furniture was produced and product brand were criteria that had the least effect on furniture purchasing (Oblak, Perić, et al., 2020) .
There was no difference before and during the COVID-19 pandemic in communication activities of consumers before making a final decision regarding purchase of furniture. However, rate of online purchasing, which was 6.5% before the COVID-19 pandemic, increased to 14.3% during the pandemic (Pirc Barčić et al., 2021). Product customization was one of the most important criterion in purchasing indoor furniture, followed by price and delivery time criteria (Lihra et al., 2012). In order to ensure a general increase in purchase of green products, it is not sufficient to inform consumers only, but it is necessary to make environmental awareness a lifestyle that manages the behaviors. Green-conscious consumers can tolerate higher product prices if the furniture's ecological label is documented by their manufacturers (Wulandari et al., 2012).
The aim of this study is to determine the factor priorities and the effect levels of furniture specifications (factors) on furniture purchasing decisions of consumers according to the some socio-demographic characteristics.
The questionnaire method was used to determine the factor priorities and effect levels of furniture specifications on purchase decision of consumers according to their socio-demographic characteristics including gender, marital status, age and education level. A questionnaire form has been prepared to record the effect levels of 14-factor such as material, brand image, quality certificate, service life, safety, aesthetics, durability, etc. On furniture purchase decision according to the consumers’ characteristics. The effect level was scaled from one to nine (Table 1).
Factors (furniture specifications) | Effect Level (1: the lowest effect, 9-: the highest effect) | ||||||||
---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | |
Material | |||||||||
Brand Value | |||||||||
Quality Certification | |||||||||
Lifetime | |||||||||
Reliability | |||||||||
Aesthetics | |||||||||
Size | |||||||||
Functionality | |||||||||
Price | |||||||||
Ease of assembly | |||||||||
Durability | |||||||||
Delivery time | |||||||||
Warranty | |||||||||
Service |
Sample size was determined as 1067 people under the conditions of 95% confidence level and ± 0.03 sampling error (p = 0.5; q = 0.5) by using the data suggested by (Yazıcıoğlu & Erdoğan, 2014) that gives the sample size in different universe size and sampling error conditions.
Prepared questionnaire was opened to online access through Google Forms between April 1 and November 1, 2020. Between these dates, 2445 people who had experience in purchasing furniture filled the questionnaire. After consistency analysis of the data, the questionnaires of 1218 people were accepted as valid. Some socio-demographic characteristics of the respondents are given in Table 2.
Socio-Demographic Characteristics | Frequency | Rate (%) | Cumulative Rate (%) | |
---|---|---|---|---|
Gender | Male | 431 | 35.4 | 35.4 |
Female | 787 | 64.6 | 100.0 | |
Marital status | Married | 908 | 74.5 | 74.5 |
Single | 284 | 23.3 | 97.9 | |
Other | 26 | 2.1 | 100.0 | |
Age | 15–24 | 227 | 18.6 | 18.6 |
25–34 | 580 | 47.6 | 66.3 | |
35–44 | 306 | 25.1 | 91.4 | |
45–54 | 86 | 7.1 | 98.4 | |
55 and above | 19 | 1.6 | 100.0 | |
Educational Status | Elementary School and Below | 34 | 2.8 | 2.8 |
Primary and Secondary School | 112 | 9.2 | 12.0 | |
High School | 241 | 19.8 | 31.8 | |
Vocational High School | 125 | 10.3 | 42.0 | |
Associate Degree / College | 216 | 17.7 | 59.8 | |
Bachelor's Degree | 412 | 33.8 | 93.6 | |
Masters And Doctorate | 78 | 6.4 | 100.0 |
For selection of the statistical test techniques to be applied, independent group data sets consisting of effect values of the factors according to the socio-demographic characteristics were firstly subjected to the Kolmogorov-Smirnov normality test. ANOVA (p < 0.05) was used as test technique for factor interactions with normal distribution and three or more subgroups. Independent sample t-test (p < 0.05) was used for factor interactions in which number of subgroups was two. In structures that do not comply with normal distribution, non-parametric KRUSKAL WALLIS Analysis of Variance (p < 0.05) was used for the factor interactions where the number of subgroups was three or more, and MANN-WHITNEY U test (p < 0.05) was used for the factor interactions where the number of subgroups was two. If significance value (p) is less than 0.05, the hypothesis "There is no difference between the groups" was rejected and counter-hypothesis "At least one group is different from the others" was accepted. In factor-independent group interaction, to determine between which subgroups the difference was, DUNCAN Multiple Range Test was applied if the distribution was normal and the variances were homogeneous in independent group data sets, and TAMHANE'S T2 Test was applied if the distribution was normal and the variances were not homogeneous. In cases where the normal distribution could not be achieved, TAMHANE'S T2 corrected MANN-WHITNEY U pairwise comparison tests were applied.
The effect levels of the factors on purchase decision of furniture, without considering any socio-demographic characteristics, are given in Table 3.
Factors | Frequency | Min. | Max. | Effect Value | Standard Deviation |
---|---|---|---|---|---|
Material | 1218 | 1 | 9 | 7.61 | 1.850 |
Brand Value | 1218 | 1 | 9 | 6.82 | 2.182 |
Quality Certification | 1218 | 1 | 9 | 7.22 | 2.190 |
Lifetime | 1218 | 1 | 9 | 8.26 | 1.418 |
Reliability | 1218 | 1 | 9 | 7.85 | 1.752 |
Aesthetics | 1218 | 1 | 9 | 8.14 | 1.445 |
Size | 1218 | 1 | 9 | 7.53 | 1.753 |
Functionality | 1217 | 1 | 9 | 8.29 | 1.318 |
Price | 1218 | 1 | 9 | 7.66 | 1.853 |
Ease of Assembly | 1218 | 1 | 9 | 6.95 | 2.319 |
Durability | 1218 | 1 | 9 | 7.78 | 1.866 |
Delivery time | 1218 | 1 | 9 | 7.30 | 2.162 |
Warranty | 1218 | 1 | 9 | 7.80 | 1.993 |
After Sales Service | 1218 | 1 | 9 | 7.89 | 1.939 |
As can be seen in Table 3, "Functionality (8.29)" was the most effective factor in furniture purchasing, followed by "Lifetime (8.26)" and "Aesthetics (8.14)". The least effective factor was “Brand Image (6.82)”.
Some descriptive statistical values for the effect values of purchasing decision factors for each gender group are given in Table 4.
Factors | Gender | Effect Value | Standard Deviation | Coefficient of Variation | Min. | Max. |
---|---|---|---|---|---|---|
Material | Male | 7.65 | 1.715 | 0.224 | 1 | 9 |
Female | 7.58 | 1.920 | 0.253 | 1 | 9 | |
Brand Value | Male | 6.79 | 2.134 | 0.315 | 1 | 9 |
Female | 6.82 | 2.210 | 0.324 | 1 | 9 | |
Quality Certification | Male | 6.90 | 2.357 | 0.342 | 1 | 9 |
Female | 7.37 | 2.075 | 0.282 | 1 | 9 | |
Lifetime | Male | 8.13 | 1.443 | 0.177 | 1 | 9 |
Female | 8.33 | 1.401 | 0.168 | 1 | 9 | |
Reliability | Male | 7.59 | 1.924 | 0.253 | 1 | 9 |
Female | 7.99 | 1.630 | 0.204 | 1 | 9 | |
Aesthetic | Male | 8.09 | 1.399 | 0.173 | 1 | 9 |
Female | 8.16 | 1.470 | 0.180 | 1 | 9 | |
Size | Male | 7.36 | 1.721 | 0.234 | 1 | 9 |
Female | 7.62 | 1.764 | 0.231 | 1 | 9 | |
Functionality | Male | 8.16 | 1.314 | 0.161 | 1 | 9 |
Female | 8.36 | 1.316 | 0.157 | 1 | 9 | |
Price | Male | 7.73 | 1.642 | 0.212 | 1 | 9 |
Female | 7.60 | 1.959 | 0.258 | 1 | 9 | |
Ease of Assembly | Male | 6.80 | 2.335 | 0.343 | 1 | 9 |
Female | 7.00 | 2.310 | 0.330 | 1 | 9 | |
Durability | Male | 7.58 | 1.959 | 0.258 | 1 | 9 |
Female | 7.88 | 1.808 | 0.229 | 1 | 9 |
Factors | Gender | Effect Value | Standard Deviation | Coefficient of Variation | Min. | Max. |
---|---|---|---|---|---|---|
Delivery time | Male | 7.25 | 2.214 | 0.305 | 1 | 9 |
Female | 7.31 | 2.135 | 0.292 | 1 | 9 | |
Warranty | Male | 7.51 | 2.177 | 0.290 | 1 | 9 |
Female | 7.94 | 1.870 | 0.236 | 1 | 9 | |
After Sales Service | Male | 7.67 | 2.041 | 0.266 | 1 | 9 |
Female | 7.98 | 1.873 | 0.235 | 1 | 9 |
Results of the Mann-Whitney U and independent sample t-test, which were conducted to determine whether there was a significant difference between the purchasing decision effect values of the factors according to the gender, are given in Table 5.
Factors | Gender | Frequency | Mean Rank | F Value | Effect Value | Significance Value |
---|---|---|---|---|---|---|
Material | Male | 431 | 605.04 | - | 7.65 | 0.727 |
Female | 787 | 611.94 | 7.58 | |||
Brand Values | Male | 431 | - | 1.116 | 6.80 | 0.291 |
Female | 787 | 6.83 | ||||
Quality Certification | Male | 431 | - | 8.291 | 6.92 | 0.004 |
Female | 787 | 7.38 | ||||
Lifetime | Male | 431 | 572.29 | - | 8.13 | 0.001 |
Female | 787 | 629.88 | 8.33 | |||
Reliability | Male | 431 | 560.81 | - | 7.59 | 0.000 |
Female | 787 | 636.16 | 7.99 | |||
Aesthetic | Male | 431 | 584.46 | - | 8.09 | 0.036 |
Female | 787 | 623.21 | 8.16 | |||
Size | Male | 431 | - | 0.564 | 7.36 | 0.453 |
Female | 787 | 7.63 | ||||
Functionality | Male | 430 | 564.61 | - | 8.15 | 0.000 |
Female | 787 | 633.25 | 8.36 | |||
Price | Male | 431 | - | 18.192 | 7.74 | 0.000 |
Female | 787 | 7.61 | ||||
Ease of Assembly | Male | 431 | - | 0.081 | 6.82 | 0.776 |
Female | 787 | 7.02 | ||||
Durability | Male | 431 | 569.40 | - | 7.58 | 0.001 |
Female | 787 | 631.46 | 7.88 | |||
Delivery time | Male | 431 | - | 0.026 | 7.27 | 0.871 |
Female | 787 | 7.32 | ||||
Warranty | Male | 431 | 567.21 | - | 7.53 | 0.000 |
Female | 787 | 632.66 | 7.95 | |||
After Sales Service | Male | 431 | 568.53 | - | 7.69 | 0.001 |
Female | 787 | 631.94 | 8.00 | |||
*Significance level for difference between means 0.05 |
As can be seen from Table 5, since significance values of Mann-Whitney U and independent sample t-test are greater than 0.05; the factors of material type, brand value, size, ease of assembly and delivery time have no effect on purchasing decisions of the individuals in different gender groups. Nevertheless, other factors are effective.
The effects of the factors of quality certification (7.38; 6.92), lifetime (8.33; 8.13), safety (7.99; 7.59), aesthetics (8.16; 8.09), usability (8.36; 8.15), price (7.61; 7.74), durability (7.88; 7.58), warranty (7.95; 7.53) and after sales service (8.00; 7.69) on purchasing decision are higher in women compared to men.
Some descriptive statistical values for the effect values of the factors for each marital status group are given in Table 6.
Factors | Marital Status | Effect Value | Std. Deviation | Coefficient of Variation | Min. | Max. |
---|---|---|---|---|---|---|
Material | Married | 7.61 | 1.913 | 0.252 | 1 | 9 |
Single | 7.61 | 1.599 | 0.210 | 1 | 9 | |
Other | 7.38 | 2.174 | 0.294 | 1 | 9 | |
Brand Value | Married | 6.88 | 2.208 | 0.321 | 1 | 9 |
Single | 6.60 | 2.080 | 0.315 | 1 | 9 | |
Other | 6.58 | 2.266 | 0.345 | 3 | 9 | |
Quality Certification | Married | 7.34 | 2.099 | 0.286 | 1 | 9 |
Single | 6.79 | 2.390 | 0.352 | 1 | 9 | |
Other | 6.85 | 2.461 | 0.359 | 2 | 9 | |
Lifetime | Married | 8.25 | 1.457 | 0.176 | 1 | 9 |
Single | 8.26 | 1.317 | 0.159 | 2 | 9 | |
Other | 8.35 | 1.129 | 0.135 | 5 | 9 | |
Reliability | Married | 7.97 | 1.692 | 0.212 | 1 | 9 |
Single | 7.46 | 1.873 | 0.251 | 1 | 9 | |
Other | 7.73 | 1.888 | 0.244 | 2 | 9 | |
Aesthetic | Married | 8.15 | 1.455 | 0.179 | 1 | 9 |
Single | 8.08 | 1.412 | 0.175 | 1 | 9 | |
Other | 8.12 | 1.479 | 0.182 | 4 | 9 | |
Size | Married | 7.57 | 1.777 | 0.235 | 1 | 9 |
Single | 7.41 | 1.691 | 0.228 | 1 | 9 | |
Other | 7.46 | 1.581 | 0.212 | 3 | 9 | |
Functionality | Married | 8.33 | 1.308 | 0.157 | 1 | 9 |
Single | 8.20 | 1.299 | 0.158 | 1 | 9 | |
Other | 8.15 | 1.804 | 0.221 | 2 | 9 | |
Price | Married | 7.60 | 1.900 | 0.250 | 1 | 9 |
Single | 7.84 | 1.648 | 0.210 | 1 | 9 | |
Other | 7.27 | 2.201 | 0.303 | 1 | 9 | |
Ease of Assembly | Married | 7.04 | 2.296 | 0.326 | 1 | 9 |
Single | 6.65 | 2.294 | 0.345 | 1 | 9 | |
Other | 6.15 | 3.003 | 0.488 | 1 | 9 | |
Durability | Married | 7.84 | 1.859 | 0.237 | 1 | 9 |
Single | 7.57 | 1.793 | 0.237 | 1 | 9 | |
Other | 7.62 | 2.684 | 0.353 | 1 | 9 | |
Delivery Time | Married | 7.37 | 2.135 | 0.290 | 1 | 9 |
Single | 7.00 | 2.256 | 0.322 | 1 | 9 | |
Other | 7.73 | 1.756 | 0.227 | 3 | 9 | |
Warranty | Married | 7.89 | 1.958 | 0.248 | 1 | 9 |
Single | 7.46 | 2.112 | 0.283 | 1 | 9 | |
Other | 7.85 | 1.488 | 0.190 | 5 | 9 | |
After Sales Service | Married | 7.95 | 1.918 | 0.241 | 1 | 9 |
Single | 7.62 | 2.024 | 0.266 | 1 | 9 | |
Other | 7.88 | 1.479 | 0.188 | 4 | 9 |
Results of the Kruskal Wallis-H and ANOVA test, which were conducted to determine whether there was a significant difference between the purchasing decision effect values of the factors according to marital status, are given in Table 7.
Factors | Gender | Frequency | Mean Rank | F Value | Effect Value | Significance Value |
---|---|---|---|---|---|---|
Material | Married | 908 | - | 0.190 | 7.61 | 0.827 |
Single | 284 | 7.61 | ||||
Other | 26 | 7.38 | ||||
Brand Value | Married | 908 | - | 2.058 | 6.89 | 0.128 |
Single | 284 | 6.61 | ||||
Other | 26 | 6.58 | ||||
Quality Certification | Married | 908 | - | 7.782 | 7.36 | 0.000 |
Single | 284 | 6.81 | ||||
Other | 26 | 6.85 | ||||
Lifetime | Married | 908 | 612.57 | - | 8.26 | 0.819 |
Single | 284 | 600.24 | 8.26 | |||
Other | 26 | 603.38 | 8.35 | |||
Reliability | Married | 908 | 635.82 | - | 7.97 | 0.000 |
Single | 284 | 527.99 | 7.46 | |||
Other | 26 | 580.60 | 7.73 | |||
Aesthetic | Married | 908 | 616.54 | - | 8.15 | 0.368 |
Single | 284 | 586.91 | 8.08 | |||
Other | 26 | 610.29 | 8.12 | |||
Size | Married | 908 | - | 0.864 | 7.57 | 0.422 |
Single | 284 | 7.42 | ||||
Other | 26 | 7.46 | ||||
Functionality | Married | 908 | 622.49 | - | 8.32 | 0.016 |
Single | 284 | 565.93 | 8.20 | |||
Other | 26 | 631.71 | 8.15 | |||
Price | Married | 908 | 603.58 | - | 7.60 | 0.259 |
Single | 284 | 633.66 | 7.84 | |||
Other | 26 | 552.48 | 7.27 | |||
Ease of Assembly | Married | 908 | - | 4.670 | 7.06 | 0.010 |
Single | 284 | 6.67 | ||||
Other | 26 | 6.19 | ||||
Durability | Married | 908 | 626.17 | - | 7.84 | 0.002 |
Single | 284 | 552.35 | 7.57 | |||
Other | 26 | 651.67 | 7.62 | |||
Delivery Time | Married | 908 | - | 3.827 | 7.38 | 0.022 |
Single | 284 | 7.01 | ||||
Other | 26 | 7.73 | ||||
Warranty | Married | 908 | 631.96 | - | 7.90 | 0.000 |
Single | 284 | 539.47 | 7.48 | |||
Other | 26 | 589.94 | 7.85 | |||
After Sales Service | Married | 908 | 630.19 | - | 7.95 | 0.000 |
Single | 284 | 547.07 | 7.62 | |||
Other | 26 | 568.79 | 7.88 |
As can be seen in Table 7, since Kruskal Wallis-H and ANOVA test significance values are greater than 0.05; material type, brand value, lifetime, aesthetics, size and price factors are not effective on purchasing decisions of the individuals in different marital status groups, while other factors are effective.
The comparison analysis made to determine in which marital status groups the difference between the effect values of the factors that affect the purchasing decision, is given in Table 8.
Factors | Effect Value | (I) Marital Status | (J) Marital Status | Mean Difference (I-J) | Standart Error | Significance Value |
---|---|---|---|---|---|---|
Quality Certification | 7.36 | Married | Single | 0.554* | 0.154 | 0.001 |
Other | 0.514 | 0.487 | 0.659 | |||
6.81 | Single | Married | -0.554* | 0.154 | 0.001 | |
Other | -0.040 | 0.502 | 1.000 | |||
6.85 | Other | Married | -0.514 | 0.487 | 0.659 | |
Single | 0.040 | 0.502 | 1.000 | |||
Reliability | 7.97 | Married | Single | 0.506* | 0.125 | 0.000 |
Other | 0.236 | 0.375 | 0.899 | |||
7.46 | Single | Married | -0.506* | 0.125 | 0.000 | |
Other | 0-.270 | 0.387 | 0.868 | |||
7.73 | Other | Married | -0.236 | 0.375 | 0.899 | |
Single | 0.270 | 0.387 | 0.868 | |||
Functionality | 8.32 | Married | Single | 0.114 | 0.088 | 0.476 |
Other | 0.164 | 0.357 | 0.957 | |||
8.20 | Single | Married | -0.114 | 0.088 | 0.476 | |
Other | 0.050 | 0.362 | 0.999 | |||
8.15 | Other | Married | -0.164 | 0.357 | 0.957 | |
Single | -0.050 | 0.362 | 0.999 | |||
Ease of Assembly | 7.06 | Married | Single | 0.387* | 0.152 | 0.033 |
Other | 0.864 | 0.579 | 0.381 | |||
6.67 | Single | Married | -0.387* | 0.152 | 0.033 | |
Other | 0.477 | 0.589 | 0.810 | |||
6.19 | Other | Married | -0.864 | 0.579 | 0.381 | |
Single | -0.477 | 0.589 | 0.810 | |||
Durability | 7.84 | Married | Single | 0.269 | 0.121 | 0.077 |
Other | 0.158 | 0.487 | 0.984 | |||
7.57 | Single | Married | -0.269 | 0.121 | 0.077 | |
Other | -0.111 | 0.494 | 0.994 | |||
7.62 | Other | Married | -0.158 | 0.487 | 0.984 | |
Single | 0.111 | 0.494 | 0.994 | |||
Delivery Time | 7.38 | Married | Single | 0.370* | 0.149 | 0.040 |
Other | -0.350 | 0.351 | 0.697 | |||
7.01 | Single | Married | -0.370* | 0.149 | 0.040 | |
Other | -0.720 | 0.369 | 0.168 | |||
7.73 | Other | Married | 0.350 | 0.351 | 0.697 | |
Single | 0.720 | 0.369 | 0.168 | |||
Warranty | 7.90 | Married | Single | 0.414* | 0.137 | 0.008 |
Other | 0.050 | 0.299 | 0.998 | |||
7.48 | Single | Married | -0.414* | 0.137 | 0.008 | |
Other | -0.364 | 0.316 | 0.592 | |||
7.85 | Other | Married | -0.050 | 0.299 | 0.998 | |
Single | 0.364 | 0.316 | 0.592 | |||
After Sales Service | 7.95 | Married | Single | 0.330* | 0.132 | 0.038 |
Other | 0.082 | 0.296 | 0.990 | |||
7.62 | Single | Married | -0.330* | 0.132 | 0.038 | |
Other | -0.247 | 0.312 | 0.819 | |||
7.88 | Other | Married | -0.082 | 0.296 | 0.990 | |
Single | 0.247 | 0.312 | 0.819 | |||
*Significance level for difference between means 0.05 |
As can be seen in Table 8, since all significance values are greater than 0.05 in pairwise comparison tests, no difference was found between the effect values of usability, durability and after sales service factors for marital status subgroups.
The differences between the effect values of quality certification, safety, ease of assembly, delivery time and warranty factors belonging to married and single marital status groups is significant, and the differences between the effect values of these two groups and the effect value of the other marital status group are insignificant.
In relation to all factors, since the effect values of married people are higher than those of singles, these factors are more effective in the purchasing decisions of married people compared to the singles.
Some descriptive statistical values for the effect values of the factors for each age group are given in Table 9.
Factors | Age Groups | Effect Value | Std. Deviation | Coefficient of Variation | Min. | Max. |
---|---|---|---|---|---|---|
Material | 15–24 | 7.14 | 2.019 | 0.28 | 1 | 9 |
25–34 | 7.69 | 1.778 | 0.23 | 1 | 9 | |
35–44 | 7.74 | 1.807 | 0.23 | 1 | 9 | |
45–54 | 7.81 | 1.739 | 0.22 | 1 | 9 | |
55 + | 7.37 | 2.338 | 0.32 | 2 | 9 | |
Brand Value | 15–24 | 6.44 | 2.248 | 0.35 | 1 | 9 |
25–34 | 6.83 | 2.220 | 0.33 | 1 | 9 | |
35–44 | 6.96 | 2.055 | 0.30 | 1 | 9 | |
45–54 | 7.16 | 2.097 | 0.29 | 1 | 9 | |
55 + | 6.42 | 2.219 | 0.35 | 2 | 9 | |
Quality Certification | 15–24 | 6.78 | 2.348 | 0.35 | 1 | 9 |
25–34 | 7.15 | 2.231 | 0.31 | 1 | 9 | |
35–44 | 7.50 | 2.022 | 0.27 | 1 | 9 | |
45–54 | 7.62 | 1.965 | 0.26 | 1 | 9 | |
55 + | 7.26 | 1.661 | 0.23 | 3 | 9 | |
Lifetime | 15–24 | 8.07 | 1.672 | 0.21 | 1 | 9 |
25–34 | 8.27 | 1.404 | 0.17 | 1 | 9 | |
35–44 | 8.33 | 1.343 | 0.16 | 1 | 9 | |
45–54 | 8.42 | 1.079 | 0.13 | 3 | 9 | |
55 + | 8.32 | .946 | 0.11 | 6 | 9 | |
Reliability | 15–24 | 7.58 | 1.899 | 0.25 | 1 | 9 |
25–34 | 7.79 | 1.795 | 0.23 | 1 | 9 | |
35–44 | 8.11 | 1.611 | 0.20 | 1 | 9 | |
45–54 | 7.93 | 1.445 | 0.18 | 3 | 9 | |
55 + | 8.21 | 1.316 | 0.16 | 4 | 9 | |
Aesthetic | 15–24 | 7.93 | 1.663 | 0.21 | 1 | 9 |
25–34 | 8.13 | 1.452 | 0.18 | 1 | 9 | |
35–44 | 8.27 | 1.302 | 0.16 | 1 | 9 | |
45–54 | 8.19 | 1.222 | 0.15 | 3 | 9 | |
55 + | 8.16 | 1.385 | 0.17 | 4 | 9 | |
Size | 15–24 | 7.27 | 1.861 | 0.26 | 1 | 9 |
25–34 | 7.54 | 1.704 | 0.23 | 1 | 9 | |
35–44 | 7.63 | 1.804 | 0.24 | 1 | 9 | |
45–54 | 7.80 | 1.585 | 0.20 | 3 | 9 | |
55 + | 7.58 | 1.539 | 0.20 | 4 | 9 | |
Functionality | 15–24 | 8.06 | 1.498 | 0.19 | 1 | 9 |
25–34 | 8.29 | 1.275 | 0.15 | 1 | 9 | |
35–44 | 8.41 | 1.305 | 0.16 | 1 | 9 | |
45–54 | 8.45 | 1.195 | 0.14 | 3 | 9 | |
55 + | 8.53 | .612 | 0.07 | 7 | 9 |
Factors | Age Groups | Effect Value | Std. Deviation | Coefficient of Variation | Min. | Max. |
---|---|---|---|---|---|---|
Price | 15–24 | 7.54 | 2.014 | 0.27 | 1 | 9 |
25–34 | 7.68 | 1.741 | 0.23 | 1 | 9 | |
35–44 | 7.60 | 2.001 | 0.26 | 1 | 9 | |
45–54 | 7.92 | 1.603 | 0.20 | 3 | 9 | |
55 + | 7.47 | 1.806 | 0.24 | 3 | 9 | |
Ease of Assembly | 15–24 | 6.68 | 2.245 | 0.34 | 1 | 9 |
25–34 | 6.83 | 2.402 | 0.35 | 1 | 9 | |
35–44 | 7.22 | 2.226 | 0.31 | 1 | 9 | |
45–54 | 7.26 | 2.165 | 0.30 | 1 | 9 | |
55 + | 6.84 | 2.433 | 0.36 | 2 | 9 | |
Durability | 15–24 | 7.47 | 1.981 | 0.27 | 1 | 9 |
25–34 | 7.75 | 1.915 | 0.25 | 1 | 9 | |
35–44 | 7.94 | 1.756 | 0.22 | 1 | 9 | |
45–54 | 8.02 | 1.666 | 0.21 | 1 | 9 | |
55 + | 8.16 | 1.015 | 0.12 | 5 | 9 | |
Delivery Time | 15–24 | 6.88 | 2.300 | 0.33 | 1 | 9 |
25–34 | 7.25 | 2.135 | 0.29 | 1 | 9 | |
35–44 | 7.59 | 2.075 | 0.27 | 1 | 9 | |
45–54 | 7.50 | 2.113 | 0.28 | 1 | 9 | |
55 + | 7.53 | 2.220 | 0.29 | 1 | 9 | |
Warranty | 15–24 | 7.37 | 2.209 | 0.30 | 1 | 9 |
25–34 | 7.82 | 2.014 | 0.26 | 1 | 9 | |
35–44 | 8.05 | 1.772 | 0.22 | 1 | 9 | |
45–54 | 7.66 | 1.968 | 0.26 | 1 | 9 | |
55 + | 8.11 | 1.370 | 0.17 | 5 | 9 | |
After Sales Service | 15–24 | 7.51 | 2.166 | 0.29 | 1 | 9 |
25–34 | 7.89 | 1.921 | 0.24 | 1 | 9 | |
35–44 | 8.08 | 1.878 | 0.23 | 1 | 9 | |
45–54 | 7.93 | 1.593 | 0.20 | 1 | 9 | |
55 + | 8.16 | 1.573 | 0.19 | 3 | 9 |
Results of the Kruskal Wallis-H and ANOVA tests, which were conducted to determine whether there was a significant difference between purchasing decision effect values of the factors according to age groups, are given in Table 10.
Factors | Age Groups | Frequency | Mean Rank | F Value | Effect Value | Significance Value |
---|---|---|---|---|---|---|
Material Type | 15–24 | 227 | 519.38 | - | 7.14 | 0,000 |
25–34 | 580 | 624.49 | 7.69 | |||
35–44 | 306 | 635.41 | 7.74 | |||
45–54 | 86 | 654.16 | 7.81 | |||
55 + | 19 | 609.03 | 7.37 | |||
Brand Values | 15–24 | 227 | - | 2.709 | 6.44 | 0,067 |
25–34 | 580 | 6.83 | ||||
35–44 | 306 | 6.96 | ||||
45–54 | 86 | 7.16 | ||||
55 + | 19 | 6.42 | ||||
Quality Certification | 15–24 | 227 | 542.60 | - | 6.78 | 0,001 |
25–34 | 580 | 602.11 | 7.15 | |||
35–44 | 306 | 656.92 | 7.50 | |||
45–54 | 86 | 675.28 | 7.62 | |||
55 + | 19 | 572.76 | 7.26 | |||
Lifetime | 15–24 | 227 | 586.75 | - | 8.07 | 0,614 |
25–34 | 580 | 610.79 | 8.27 | |||
35–44 | 306 | 623.01 | 8.33 | |||
45–54 | 86 | 622.63 | 8.42 | |||
55 + | 19 | 565.00 | 8.32 |
Factors | Age Groups | Frequency | Mean Rank | F Value | Effect Value | Significance Value |
---|---|---|---|---|---|---|
Reliability | 15–24 | 227 | 559.16 | - | 7.58 | 0.003 |
25–34 | 580 | 599.56 | 7.79 | |||
35–44 | 306 | 664.88 | 8.11 | |||
45–54 | 86 | 600.44 | 7.93 | |||
55 + | 19 | 663.37 | 8.21 | |||
Aesthetic | 15–24 | 227 | 573.88 | - | 7.93 | 0.231 |
25–34 | 580 | 608.96 | 8.13 | |||
35–44 | 306 | 637.62 | 8.27 | |||
45–54 | 86 | 605.74 | 8.19 | |||
55 + | 19 | 615.76 | 8.16 | |||
Size | 15–24 | 227 | - | 1.956 | 7.27 | 0.099 |
25–34 | 580 | 7.54 | ||||
35–44 | 306 | 7.63 | ||||
45–54 | 86 | 7.80 | ||||
55 + | 19 | 7.58 | ||||
Functionality | 15–24 | 227 | 544.65 | - | 8.06 | 0.001 |
25–34 | 579 | 607.34 | 8.29 | |||
35–44 | 306 | 646.14 | 8.41 | |||
45–54 | 86 | 661.77 | 8.45 | |||
55 + | 19 | 591.37 | 8.53 | |||
Price | 15–24 | 227 | - | 0.776 | 7.54 | 0.540 |
25–34 | 580 | 7.68 | ||||
35–44 | 306 | 7.60 | ||||
45–54 | 86 | 7.92 | ||||
55 + | 19 | 7.47 | ||||
Ease of Installation | 15–24 | 227 | - | 2.605 | 6.68 | 0.182 |
25–34 | 580 | 6.83 | ||||
35–44 | 306 | 7.22 | ||||
45–54 | 86 | 7.26 | ||||
55 + | 19 | 6.84 | ||||
Durability | 15–24 | 227 | 548.46 | - | 7.47 | 0.011 |
25–34 | 580 | 611.05 | 7.75 | |||
35–44 | 306 | 639.16 | 7.94 | |||
45–54 | 86 | 657.25 | 8.02 | |||
55 + | 19 | 597.55 | 8.16 | |||
Delivery Time | 15–24 | 227 | 542.96 | - | 6.88 | 0.001 |
25–34 | 580 | 600.63 | 7.25 | |||
35–44 | 306 | 664.53 | 7.59 | |||
45–54 | 86 | 641.80 | 7.50 | |||
55 + | 19 | 642.89 | 7.53 |
As can be seen from Table 10, since the Kruskal Wallis-H and ANOVA test significance values are greater than 0.05, the factors of brand value, lifetime, aesthetics, size, price and ease of assembly have no effect on purchasing decisions of individuals from different age groups. Other factors are effective.
The comparison analysis performed to determine in which age groups the differences between the effect values of the factors that affect purchasing decision, is given in Table 11.
Factors | Effect Value | (I) Age Groups | (J) Age Groups | Mean Difference (I-J) | Std. Error | Significance Value |
---|---|---|---|---|---|---|
Material | 7.14 | 15–24 | 25–34 | -0.549* | 0.153 | 0.004 |
35–44 | -0.594* | 0.169 | 0.005 | |||
45–54 | -0.673* | 0.230 | 0.039 | |||
55 + | -0.227 | 0.553 | 1.000 | |||
7.69 | 25–34 | 15–24 | 0.549* | 0.153 | 0.004 | |
35–44 | -0.046 | 0.127 | 1.000 | |||
45–54 | -0.124 | 0.202 | 1.000 | |||
55 + | 0.321 | 0.542 | 1.000 | |||
7.74 | 35–44 | 15–24 | 0.594* | 0.169 | 0.005 | |
25–34 | 0.046 | 0.127 | 1.000 | |||
45–54 | -0.079 | 0.214 | 1.000 | |||
55 + | 0.367 | 0.546 | 0.999 | |||
7.81 | 45–54 | 15–24 | 0.673* | 0.230 | 0.039 | |
25–34 | 0.124 | 0.202 | 1.000 | |||
35–44 | 0.079 | 0.214 | 1.000 | |||
55 + | 0.446 | 0.568 | 0.997 | |||
7.37 | 55 + | 15–24 | 0.227 | 0.553 | 1.000 | |
25–34 | -0.321 | 0.542 | 1.000 | |||
35–44 | -0.367 | 0.546 | 0.999 | |||
45–54 | -0.446 | 0.568 | 0.997 | |||
Quality Certification | 6.78 | 15–24 | 25–34 | -0.375 | 0.181 | 0.331 |
35–44 | -0.721* | 0.194 | 0.002 | |||
45–54 | -0.841* | 0.263 | 0.016 | |||
55 + | -0.488 | 0.412 | 0.942 | |||
7.15 | 25–34 | 15–24 | 0.375 | 0.181 | 0.331 | |
35–44 | -0.347 | 0.148 | 0.179 | |||
45–54 | -0.466 | 0.231 | 0.376 | |||
55 + | -0.113 | 0.392 | 1.000 | |||
7.50 | 35–44 | 15–24 | 0.721* | 0.194 | 0.002 | |
25–34 | 0.347 | 0.148 | 0.179 | |||
45–54 | -0.120 | 0.241 | 1.000 | |||
55 + | 0.234 | 0.398 | 1.000 | |||
7.62 | 45–54 | 15–24 | 0.841* | 0.263 | 0.016 | |
25–34 | 0.466 | 0.231 | 0.376 | |||
35–44 | 0.120 | 0.241 | 1.000 | |||
55 + | 0.353 | 0.436 | 0.996 | |||
7.26 | 55 + | 15–24 | 0.488 | 0.412 | 0.942 | |
25–34 | 0.113 | 0.392 | 1.000 | |||
35–44 | -0.234 | 0.398 | 1.000 | |||
45–54 | -0.353 | 0.436 | 0.996 | |||
Reliability | 7.58 | 15–24 | 25–34 | -0.207 | 0.147 | 0.821 |
35–44 | -0.531* | 0.156 | 0.007 | |||
45–54 | -0.353 | 0.200 | 0.564 | |||
55 + | -0.633 | 0.327 | 0.486 | |||
7.79 | 25–34 | 15–24 | 0.207 | 0.147 | 0.821 | |
35–44 | -0.323 | 0.119 | 0.064 | |||
45–54 | -0.146 | 0.173 | 0.994 | |||
55 + | -0.426 | 0.311 | 0.872 | |||
8.11 | 35–44 | 15–24 | 0.531* | 0.156 | 0.007 | |
25–34 | 0.323 | 0.119 | 0.064 | |||
45–54 | 0.178 | 0.181 | 0.981 | |||
55 + | -0.103 | 0.316 | 1.000 | |||
7.93 | 45–54 | 15–24 | 0.353 | 0.200 | 0.564 | |
25–34 | 0.146 | 0.173 | 0.994 | |||
35–44 | -0.178 | 0.181 | 0.981 | |||
55 + | -0.280 | 0.340 | 0.995 | |||
8.21 | 55 + | 15–24 | 0.633 | 0.327 | 0.486 | |
25–34 | 0.426 | 0.311 | 0.872 | |||
35–44 | 0.103 | 0.316 | 1.000 | |||
45–54 | 0.280 | 0.340 | 0.995 | |||
25–34 | -0.028 | 0.344 | 1.000 | |||
*Significance level for difference between means 0.05 |
Factors | Effect Value | (I) Age Groups | (J) Age Groups | Mean Difference (I-J) | Std. Error | Significance Value |
---|---|---|---|---|---|---|
Ease of Assembly | 8.06 | 15–24 | 25–34 | -0.230 | 0.113 | 0.347 |
35–44 | -0.344 | 0.124 | 0.058 | |||
45–54 | -0.392 | 0.163 | 0.158 | |||
55 + | -0.465 | 0.172 | 0.096 | |||
8.29 | 25–34 | 15–24 | 0.230 | 0.113 | 0.347 | |
35–44 | -0.113 | 0.092 | 0.912 | |||
45–54 | -0.162 | 0.139 | 0.942 | |||
55 + | -0.234 | 0.150 | 0.756 | |||
8.41 | 35–44 | 15–24 | 0.344 | 0.124 | 0.058 | |
25–34 | 0.113 | 0.092 | 0.912 | |||
45–54 | -0.048 | 0.149 | 1.000 | |||
55 + | -0.121 | 0.159 | 0.998 | |||
8.45 | 45–54 | 15–24 | 0.392 | 0.163 | 0.158 | |
25–34 | 0.162 | 0.139 | 0.942 | |||
35–44 | 0.048 | 0.149 | 1.000 | |||
55 + | -0.073 | 0.191 | 1.000 | |||
8.53 | 55 + | 15–24 | 0.465 | 0.172 | 0.096 | |
25–34 | 0.234 | 0.150 | 0.756 | |||
35–44 | 0.121 | 0.159 | 0.998 | |||
45–54 | 0.073 | 0.191 | 1.000 | |||
Durability | 7.47 | 15–24 | 25–34 | -0.288 | 0.154 | 0.469 |
35–44 | -0.477* | 0.165 | 0.040 | |||
45–54 | -0.556 | 0.223 | 0.126 | |||
55 + | -0.691 | 0.267 | 0.137 | |||
7.75 | 25–34 | 15–24 | 0.288 | 0.154 | 0.469 | |
35–44 | -0.189 | 0.128 | 0.778 | |||
45–54 | -0.268 | 0.196 | 0.854 | |||
55 + | -0.403 | 0.246 | 0.707 | |||
7.94 | 35–44 | 15–24 | 0.477* | 0.165 | 0.040 | |
25–34 | 0.189 | 0.128 | 0.778 | |||
45–54 | -0.079 | 0.206 | 1.000 | |||
55 + | -0.213 | 0.253 | 0.995 | |||
8.02 | 45–54 | 15–24 | 0.556 | 0.223 | 0.126 | |
25–34 | 0.268 | 0.196 | 0.854 | |||
35–44 | 0.079 | 0.206 | 1.000 | |||
55 + | -0.135 | 0.294 | 1.000 | |||
8.16 | 55 + | 15–24 | 0.691 | 0.267 | 0.137 | |
25–34 | 0.403 | 0.246 | 0.707 | |||
35–44 | 0.213 | 0.253 | 0.995 | |||
45–54 | 0.135 | 0.294 | 1.000 | |||
Delivery Time | 6.88 | 15–24 | 25–34 | -0.374 | 0.177 | 0.297 |
35–44 | -0.714* | 0.193 | 0.002 | |||
45–54 | -0.619 | 0.274 | 0.226 | |||
55 + | -0.645 | 0.532 | 0.934 | |||
7.25 | 25–34 | 15–24 | 0.374 | 0.177 | 0.297 | |
35–44 | -0.340 | 0.148 | 0.201 | |||
45–54 | -0.245 | 0.244 | 0.978 | |||
55 + | -0.271 | 0.517 | 1.000 | |||
7.59 | 35–44 | 15–24 | 0.714* | 0.193 | 0.002 | |
25–34 | 0.340 | 0.148 | 0.201 | |||
45–54 | 0.095 | 0.257 | 1.000 | |||
55 + | 0.068 | 0.523 | 1.000 | |||
7.50 | 45–54 | 15–24 | 0.619 | 0.274 | 0.226 | |
25–34 | 0.245 | 0.244 | 0.978 | |||
35–44 | -0.095 | 0.257 | 1.000 | |||
55 + | -0.026 | 0.558 | 1.000 | |||
7.53 | 55 + | 15–24 | 0.645 | 0.532 | 0.934 | |
25–34 | 0.271 | 0.517 | 1.000 | |||
35–44 | -0.068 | 0.523 | 1.000 | |||
45–54 | 0.026 | 0.558 | 1.000 | |||
*Significance level for difference between means 0.05 |
Table 11. (Continue) Comparison analysis for the differences between age subgroups according to the factors
Factors | Effect Value | (I) Age Groups | (J) Age Groups | Mean Difference (I-J) | Std. Error | Significance Value |
---|---|---|---|---|---|---|
Warranty | 7.37 | 15–24 | 25–34 | -0.452 | 0.169 | 0.074 |
35–44 | -0.676* | 0.178 | 0.002 | |||
45–54 | -0.293 | 0.258 | 0.949 | |||
55 + | -0.735 | 0.347 | 0.359 | |||
7.82 | 25–34 | 15–24 | 0.452 | 0.169 | 0.074 | |
35–44 | -0.223 | 0.131 | 0.608 | |||
45–54 | 0.160 | 0.228 | 0.999 | |||
55 + | -0.283 | 0.325 | 0.993 | |||
8.05 | 35–44 | 15–24 | 0.676* | 0.178 | 0.002 | |
25–34 | 0.223 | 0.131 | 0.608 | |||
45–54 | 0.383 | 0.235 | 0.673 | |||
55 + | -0.060 | 0.330 | 1.000 | |||
7.66 | 45–54 | 15–24 | 0.293 | 0.258 | 0.949 | |
25–34 | -0.160 | 0.228 | 0.999 | |||
35–44 | -0.383 | 0.235 | 0.673 | |||
55 + | -0.442 | 0.379 | 0.944 | |||
8.11 | 55 + | 15–24 | 0.735 | 0.347 | 0.359 | |
25–34 | 0.283 | 0.325 | 0.993 | |||
35–44 | 0.060 | 0.330 | 1.000 | |||
45–54 | 0.442 | 0.379 | 0.944 | |||
After Sales Service | 7.51 | 15–24 | 25–34 | -0.386 | 0.164 | 0.177 |
35–44 | -0.569* | 0.179 | 0.016 | |||
45–54 | -0.424 | 0.224 | 0.461 | |||
55 + | -0.651 | 0.388 | 0.676 | |||
7.89 | 25–34 | 15–24 | 0.386 | 0.164 | 0.177 | |
35–44 | -0.182 | 0.134 | 0.852 | |||
45–54 | -0.037 | 0.189 | 1.000 | |||
55 + | -0.265 | 0.370 | 0.999 | |||
8.08 | 35–44 | 15–24 | 0.569* | 0.179 | 0.016 | |
25–34 | 0.182 | 0.134 | 0.852 | |||
45–54 | 0.145 | 0.203 | 0.998 | |||
55 + | -0.083 | 0.376 | 1.000 | |||
7.93 | 45–54 | 15–24 | 0.424 | 0.224 | 0.461 | |
25–34 | 0.037 | 0.189 | 1.000 | |||
35–44 | -0.145 | 0.203 | 0.998 | |||
55 + | -0.228 | 0.400 | 1.000 | |||
8.16 | 55 + | 15–24 | 0.651 | 0.388 | 0.676 | |
25–34 | 0.265 | 0.370 | 0.999 | |||
35–44 | 0.083 | 0.376 | 1.000 | |||
45–54 | 0.228 | 0.400 | 1.000 | |||
*Significance level for difference between means 0.05 |
The difference between effect values of material on purchasing decision of 15–24 age group and 25–34, 35–44 and 45–54 age groups is significant, but there is no significant difference between 55 and over age group. Apart from this, the difference between 15–24 age group and 55 and over age group is insignificant. According to this result, in 25–34, 35–44 and 45–54 age groups, the material has the same effect (7.81; 7.74 and 7.69) on purchasing decision of individuals, while it is at a lower level effective (7.37 and 7.14) in 15–24 and 55 and over age groups.
The differences between the effect values of quality certification on purchasing decision of 15–24 age group and 35–44 and 45–54 age groups are significant, while the differences between effect values of 25–34 and 55 and over age groups are insignificant. Except for 15–24 age group, the differences between effect values of pairwise comparison of other age groups are insignificant. According to this data, compared to other age groups, quality certification is more effective in purchasing decisions of 35–44 and 45–54 age groups.
The differences between effect values of usability, durability and delivery time on purchase decision of 15–24 and 35–44 age group are significant; the differences between effect values of other age groups are insignificant. Except for 15–24 age group, the differences between dual comparison effect values of other age groups are insignificant. According to this data; compared to other age groups, usability, durability and delivery time are more effective in purchasing decisions of 35–44, 45–54 and 55 and over age groups.
The differences between effect values of reliability, warranty and after sales service on purchase decision of 15–24 and 35–44 age groups are significant, the differences between effect values of other age groups are insignificant. Except for 15–24 age group, the differences between pairwise comparison effect values of other age groups are insignificant. According to this; compared to other age groups, warranty, reliability and after sales service are more effective in purchasing decisions of 35–44 and 55 and over age groups.
Some descriptive statistical values for the effect values of the factors for each educational status group are given in Table 12.
Factors | Educational Status Groups | Effect Value | Standard Deviation | Coefficient of Variation | Min. | Max. |
---|---|---|---|---|---|---|
Material | Primary School and Below | 6.41 | 2.695 | 0.424 | 1 | 9 |
Elementary and Middle School | 7.04 | 2.536 | 0.360 | 1 | 9 | |
High School | 7.54 | 1.975 | 0.262 | 1 | 9 | |
Vocational High School | 7.38 | 1.953 | 0.265 | 1 | 9 | |
Associate's Degree | 7.70 | 1.641 | 0.213 | 1 | 9 | |
Bachelor's Degree | 7.87 | 1.518 | 0.193 | 1 | 9 | |
Postgraduate | 7.87 | 1.352 | 0.172 | 4 | 9 | |
Brand Value | Primary School and Below | 5.56 | 2.699 | 0.488 | 1 | 9 |
Elementary and Middle School | 6.84 | 2.484 | 0.365 | 1 | 9 | |
High School | 6.98 | 2.242 | 0.322 | 1 | 9 | |
Vocational High School | 6.71 | 2.309 | 0.345 | 1 | 9 | |
Associate's Degree | 6.96 | 2.226 | 0.321 | 1 | 9 | |
Bachelor's Degree | 6.90 | 1.900 | 0.276 | 1 | 9 | |
Postgraduate | 6.23 | 2.142 | 0.344 | 1 | 9 |
Factors | Educational Status Groups | Effect Value | Std. Deviation | Coefficient of Variation | Min | Max |
---|---|---|---|---|---|---|
Quality Certification | Primary School and Below | 6.41 | 2.374 | 0.372 | 1 | 9 |
Elementary and Middle School | 7.38 | 2.126 | 0.289 | 1 | 9 | |
High School | 7.58 | 1.914 | 0.253 | 1 | 9 | |
Vocational High School | 7.51 | 1.978 | 0.264 | 1 | 9 | |
Associate's Degree | 7.43 | 1.958 | 0.264 | 1 | 9 | |
Bachelor's Degree | 6.99 | 2.361 | 0.339 | 1 | 9 | |
Postgraduate | 6.45 | 2.591 | 0.404 | 1 | 9 | |
Lifetime | Primary School and Below | 7.53 | 2.178 | 0.290 | 1 | 9 |
Elementary and Middle School | 8.13 | 1.645 | 0.202 | 1 | 9 | |
High School | 8.39 | 1.331 | 0.159 | 1 | 9 | |
Vocational High School | 8.30 | 1.497 | 0.181 | 1 | 9 | |
Associate's Degree | 8.30 | 1.349 | 0.163 | 2 | 9 | |
Bachelor's Degree | 8.26 | 1.326 | 0.161 | 1 | 9 | |
Postgraduate | 8.22 | 1.383 | 0.168 | 1 | 9 | |
Reliability | Primary School and Below | 7.56 | 2.191 | 0.291 | 1 | 9 |
Elementary and Middle School | 8.11 | 1.824 | 0.225 | 1 | 9 | |
High School | 7.93 | 1.805 | 0.228 | 1 | 9 | |
Vocational High School | 7.99 | 1.624 | 0.203 | 2 | 9 | |
Associate's Degree | 8.03 | 1.489 | 0.185 | 1 | 9 | |
Bachelor's Degree | 7.69 | 1.762 | 0.229 | 1 | 9 | |
Postgraduate | 7.46 | 1.978 | 0.265 | 1 | 9 | |
Aesthetic | Primary School and Below | 7.47 | 1.830 | 0.245 | 3 | 9 |
Elementary and Middle School | 8.08 | 1.653 | 0.205 | 1 | 9 | |
High School | 8.20 | 1.527 | 0.186 | 1 | 9 | |
Vocational High School | 8.06 | 1.660 | 0.206 | 1 | 9 | |
Associate's Degree | 8.18 | 1.342 | 0.164 | 1 | 9 | |
Bachelor's Degree | 8.16 | 1.313 | 0.161 | 1 | 9 | |
Postgraduate | 8.17 | 1.200 | 0.147 | 5 | 9 | |
Size | Primary School and Below | 6.97 | 2.007 | 0.288 | 3 | 9 |
Elementary and Middle School | 7.36 | 1.840 | 0.250 | 3 | 9 | |
High School | 7.55 | 1.891 | 0.251 | 1 | 9 | |
Vocational High School | 7.52 | 2.011 | 0.268 | 1 | 9 | |
Associate's Degree | 7.58 | 1.734 | 0.229 | 2 | 9 | |
Bachelor's Degree | 7.62 | 1.602 | 0.210 | 1 | 9 | |
Postgraduate | 7.37 | 1.406 | 0.191 | 4 | 9 | |
Functionality | Primary School and Below | 7.76 | 1.990 | 0.257 | 1 | 9 |
Elementary and Middle School | 7.83 | 1.692 | 0.216 | 2 | 9 | |
High School | 8.39 | 1.349 | 0.161 | 1 | 9 | |
Vocational High School | 8.36 | 1.428 | 0.171 | 1 | 9 | |
Associate's Degree | 8.34 | 1.201 | 0.144 | 3 | 9 | |
Bachelor's Degree | 8.35 | 1.126 | 0.135 | 2 | 9 | |
Postgraduate | 8.29 | 1.175 | 0.142 | 3 | 9 | |
Price | Primary School and Below | 6.59 | 2.743 | 0.416 | 1 | 9 |
Elementary and Middle School | 7.07 | 2.430 | 0.345 | 1 | 9 | |
High School | 7.75 | 1.862 | 0.241 | 1 | 9 | |
Vocational High School | 7.50 | 2.011 | 0.268 | 1 | 9 | |
Associate's Degree | 7.76 | 1.702 | 0.219 | 2 | 9 | |
Bachelor's Degree | 7.83 | 1.576 | 0.201 | 1 | 9 | |
Postgraduate | 7.67 | 1.601 | 0.209 | 2 | 9 | |
Ease of Assembly | Primary School and Below | 6.91 | 2.314 | 0.335 | 1 | 9 |
Elementary and Middle School | 6.90 | 2.532 | 0.368 | 1 | 9 | |
High School | 7.25 | 2.210 | 0.306 | 1 | 9 | |
Vocational High School | 7.23 | 2.347 | 0.325 | 1 | 9 | |
Associate's Degree | 7.03 | 2.250 | 0.320 | 1 | 9 | |
Bachelor's Degree | 6.77 | 2.337 | 0.347 | 1 | 9 | |
Postgraduate | 6.36 | 2.261 | 0.356 | 1 | 9 | |
Durability | Primary School and Below | 7.09 | 2.522 | 0.357 | 1 | 9 |
Elementary and Middle School | 7.71 | 2.211 | 0.288 | 1 | 9 | |
High School | 7.90 | 1.848 | 0.234 | 1 | 9 | |
Vocational High School | 7.98 | 1.727 | 0.217 | 1 | 9 | |
Associate's Degree | 7.89 | 1.786 | 0.227 | 1 | 9 | |
Bachelor's Degree | 7.72 | 1.797 | 0.233 | 1 | 9 | |
Postgraduate | 7.58 | 1.799 | 0.238 | 1 | 9 |
Table 12. (Continue) Some descriptive statistical values for the effect values of purchasing decision factors for each educational status group
Factors | Educational Status Groups | Effect Value | Std. Deviation | Coefficient of Variation | Min | Max |
---|---|---|---|---|---|---|
Delivery Time | Primary School and Below | 6.44 | 2.629 | 0.412 | 1 | 9 |
Elementary and Middle School | 7.19 | 2.431 | 0.339 | 1 | 9 | |
High School | 7.44 | 2.248 | 0.302 | 1 | 9 | |
Vocational High School | 7.86 | 1.897 | 0.242 | 1 | 9 | |
Associate's Degree | 7.57 | 1.831 | 0.242 | 2 | 9 | |
Bachelor's Degree | 7.02 | 2.196 | 0.313 | 1 | 9 | |
Postgraduate | 7.26 | 2.029 | 0.280 | 1 | 9 | |
Warranty | Primary School and Below | 6.44 | 3.093 | 0.487 | 1 | 9 |
Elementary and Middle School | 7.41 | 2.440 | 0.330 | 1 | 9 | |
High School | 7.96 | 1.996 | 0.251 | 1 | 9 | |
Vocational High School | 8.30 | 1.534 | 0.185 | 1 | 9 | |
Associate's Degree | 8.03 | 1.686 | 0.210 | 1 | 9 | |
Bachelor's Degree | 7.71 | 1.920 | 0.249 | 1 | 9 | |
Postgraduate | 7.49 | 2.094 | 0.280 | 1 | 9 | |
After Sales Service | Primary School and Below | 6.47 | 3.285 | 0.515 | 1 | 9 |
Elementary and Middle School | 7.53 | 2.325 | 0.310 | 1 | 9 | |
High School | 8.12 | 1.898 | 0.234 | 1 | 9 | |
Vocational High School | 8.14 | 1.721 | 0.212 | 1 | 9 | |
Associate's Degree | 8.13 | 1.564 | 0.193 | 1 | 9 | |
Bachelor's Degree | 7.80 | 1.882 | 0.242 | 1 | 9 | |
Postgraduate | 7.73 | 1.898 | 0.245 | 2 | 9 |
Results of the Kruskal Wallis-H and ANOVA tests, which were conducted to determine whether there was a significant difference between the purchasing decision effect values of the factors according to the educational status groups, are given in Table 13.
Factors | Educational Status Groups | Frequency | Mean Rank | F Value | Effect Value | Significance Value |
---|---|---|---|---|---|---|
Material | Primary School and Below | 34 | 442.54 | - | 6.41 | 0.011 |
Elementary and Middle School | 112 | 566.02 | 7.04 | |||
High School | 241 | 609.70 | 7.54 | |||
Vocational High School | 125 | 568.84 | 7.38 | |||
Associate's Degree | 216 | 616.04 | 7.70 | |||
Bachelor's Degree | 412 | 640.58 | 7.87 | |||
Postgraduate | 78 | 627.01 | 7.87 | |||
Brand Value | Primary School and Below | 34 | - | 3.499 | 5.56 | 0.002 |
Elementary and Middle School | 112 | 6.84 | ||||
High School | 241 | 6.98 | ||||
Vocational High School | 125 | 6.71 | ||||
Associate's Degree | 216 | 6.96 | ||||
Bachelor's Degree | 412 | 6.90 | ||||
Postgraduate | 78 | 6.23 | ||||
Quality Certification | Primary School and Below | 34 | - | 5.405 | 6.41 | 0.000 |
Elementary and Middle School | 112 | 7.38 | ||||
High School | 241 | 7.58 | ||||
Vocational High School | 125 | 7.51 | ||||
Associate's Degree | 216 | 7.43 | ||||
Bachelor's Degree | 412 | 6.99 | ||||
Postgraduate | 78 | 6.45 |
Factors | Educational Status Groups | Frequency | Mean Rank | F Value | Effect Value | Significance Value |
---|---|---|---|---|---|---|
Lifetime | Primary School and Below | 34 | 495.00 | - | 7.53 | 0.131 |
Elementary and Middle School | 112 | 604.92 | 8.13 | |||
High School | 241 | 638.48 | 8.39 | |||
Vocational High School | 125 | 629.46 | 8.30 | |||
Associate's Degree | 216 | 619.09 | 8.30 | |||
Bachelor's Degree | 412 | 597.10 | 8.26 | |||
Postgraduate | 78 | 583.41 | 8.22 | |||
Reliability | Primary School and Below | 34 | - | 2.442 | 7.56 | 0.024 |
Elementary and Middle School | 112 | 8.11 | ||||
High School | 241 | 7.93 | ||||
Vocational High School | 125 | 7.99 | ||||
Associate's Degree | 216 | 8.03 | ||||
Bachelor's Degree | 412 | 7.69 | ||||
Postgraduate | 78 | 7.46 | ||||
Aesthetics | Primary School and Below | 34 | 488.63 | - | 7.47 | 0.326 |
Elementary and Middle School | 112 | 622.26 | 8.08 | |||
High School | 241 | 631.67 | 8.20 | |||
Vocational High School | 125 | 610.22 | 8.06 | |||
Associate's Degree | 216 | 611.86 | 8.18 | |||
Bachelor's Degree | 412 | 603.85 | 8.16 | |||
Postgraduate | 78 | 597.53 | 8.17 | |||
Size | Primary School and Below | 34 | 510.38 | - | 6.97 | 0.183 |
Elementary and Middle School | 112 | 581.89 | 7.36 | |||
High School | 241 | 628.66 | 7.55 | |||
Vocational High School | 125 | 632.20 | 7.52 | |||
Associate's Degree | 216 | 622.57 | 7.58 | |||
Bachelor's Degree | 412 | 613.34 | 7.62 | |||
Postgraduate | 78 | 540.25 | 7.37 | |||
Functionality | Primary School and Below | 34 | 521.56 | - | 7.76 | 0.011 |
Elementary and Middle School | 112 | 531.11 | 7.83 | |||
High School | 241 | 642.44 | 8.39 | |||
Vocational High School | 125 | 646.55 | 8.36 | |||
Associate's Degree | 216 | 614.08 | 8.34 | |||
Bachelor's Degree | 411 | 608.55 | 8.35 | |||
Postgraduate | 78 | 589.13 | 8.29 | |||
Price | Primary School and Below | 34 | - | 4.959 | 6.59 | 0.000 |
Elementary and Middle School | 112 | 7.07 | ||||
High School | 241 | 7.75 | ||||
Vocational High School | 125 | 7.50 | ||||
Associate's Degree | 216 | 7.76 | ||||
Bachelor's Degree | 412 | 7.83 | ||||
Postgraduate | 78 | 7.67 | ||||
Ease of Assembly | Primary School and Below | 34 | - | 2.433 | 6.91 | 0.024 |
Elementary and Middle School | 112 | 6.90 | ||||
High School | 241 | 7.25 | ||||
Vocational High School | 125 | 7.23 | ||||
Associate's Degree | 216 | 7.03 | ||||
Bachelor's Degree | 412 | 6.77 | ||||
Postgraduate | 78 | 6.36 | ||||
Durability | Primary School and Below | 34 | - | 1.640 | 7.09 | 0.133 |
Elementary and Middle School | 112 | 7.71 | ||||
High School | 241 | 7.90 | ||||
Vocational High School | 125 | 7.98 | ||||
Associate's Degree | 216 | 7.89 | ||||
Bachelor's Degree | 412 | 7.72 | ||||
Postgraduate | 78 | 7.58 |
Table 13. (Continue) Kruskal Wallis-H and ANOVA test results depending on the factors and educational status groups
Factors | Educational Status Groups | Frequency | Mean Rank | F Value | Effect Value | Significance Value |
---|---|---|---|---|---|---|
Delivery Time | Primary School and Below | 34 | - | 4.464 | 6.44 | 0.000 |
Elementary and Middle School | 112 | 7.19 | ||||
High School | 241 | 7.44 | ||||
Vocational High School | 125 | 7.86 | ||||
Associate's Degree | 216 | 7.57 | ||||
Bachelor's Degree | 412 | 7.02 | ||||
Postgraduate | 78 | 7.26 | ||||
Warranty | Primary School and Below | 34 | 451.32 | - | 6.44 | 0.000 |
Elementary and Middle School | 112 | 587.34 | 7.41 | |||
High School | 241 | 648.66 | 7.96 | |||
Vocational High School | 125 | 699.46 | 8.30 | |||
Associate's Degree | 216 | 630.79 | 8.03 | |||
Bachelor's Degree | 412 | 578.13 | 7.71 | |||
Postgraduate | 78 | 551.84 | 7.49 | |||
After Sales Service | Primary School and Below | 34 | 463.56 | - | 6.47 | 0.000 |
Elementary and Middle School | 112 | 578.44 | 7.53 | |||
High School | 241 | 664.25 | 8.12 | |||
Vocational High School | 125 | 654.96 | 8.14 | |||
Associate's Degree | 216 | 635.28 | 8.13 | |||
Bachelor's Degree | 412 | 576.94 | 7.80 | |||
Postgraduate | 78 | 576.09 | 7.73 |
As can be seen from the Table 13, since the Kruskal Wallis-H and ANOVA test significance values are greater than 0.05, the factors of lifetime, aesthetics, size and durability have no effect on purchasing decisions of the individuals from different educational status groups. Other factors are effective.
The comparison analysis performed to determine in which educational status the difference between the effect values of the factors that affect the purchasing decision, is given in Table 14.
Factors | Effect Value | (I) Educational Status Groups | (J) Educational Status Groups | Mean Difference (I-J) | Std. Error | Significance Value |
---|---|---|---|---|---|---|
Material | 6.41 | Primary School and Below | Elementary and Middle School | -0.624 | 0.500 | 0.994 |
High School | -0.124 | 0.457 | 0.325 | |||
Vocational High School | -0.964 | 0.472 | 0.636 | |||
Associate's Degree | -0.292 | 0.453 | 0.138 | |||
Bachelor's Degree | -0.455 | 0.445 | 0.050 | |||
Postgraduate | -0.460 | 0.465 | 0.063 | |||
7.04 | Elementary and Middle School | Primary School and Below | 0.624 | 0.500 | 0.994 | |
High School | -0.500 | 0.271 | 0.768 | |||
Vocational High School | -0.340 | 0.295 | 0.998 | |||
Associate's Degree | -0.668 | 0.264 | 0.232 | |||
Bachelor's Degree | -0.831* | 0.251 | 0.025 | |||
Postgraduate | -0.836 | 0.284 | 0.075 |
Factors | Effect Value | (I) Educational Status Groups | (J) Educational Status Groups | Mean Difference (I-J) | Std. Error | Significance Value |
---|---|---|---|---|---|---|
Material | 7.54 | High School | Primary School and Below | 0.124 | 0.457 | 0.325 |
Elementary and Middle School | 0.500 | 0.271 | 0.768 | |||
Vocational High School | 0.159 | 0.214 | 0.000 | |||
Associate's Degree | -0.168 | 0.169 | 0.000 | |||
Bachelor's Degree | -0.331 | 0.148 | 0.417 | |||
Postgraduate | -0.337 | 0.199 | 0.870 | |||
7.38 | Vocational High School | Primary School and Below | 0.964 | 0.472 | 0.636 | |
Elementary and Middle School | 0.340 | 0.295 | 0.998 | |||
High School | -0.159 | 0.214 | 0.000 | |||
Associate's Degree | -0.328 | 0.205 | 0.917 | |||
Bachelor's Degree | -0.491 | 0.188 | 0.186 | |||
Postgraduate | -0.496 | 0.230 | 0.501 | |||
7.70 | Associate's Degree | Primary School and Below | 0.292 | 0.453 | 0.138 | |
Elementary and Middle School | 0.668 | 0.264 | 0.232 | |||
High School | 0.168 | 0.169 | 0.000 | |||
Vocational High School | 0.328 | 0.205 | 0.917 | |||
Bachelor's Degree | -0.163 | 0.134 | 0.995 | |||
Postgraduate | -0.168 | 0.189 | 0.000 | |||
7.87 | Bachelor's Degree | Primary School and Below | 0.455 | 0.445 | 0.050 | |
Elementary and Middle School | 0.831* | 0.251 | 0.025 | |||
High School | 0.331 | 0.148 | 0.417 | |||
Vocational High School | 0.491 | 0.188 | 0.186 | |||
Associate's Degree | 0.163 | 0.134 | 0.995 | |||
Postgraduate | -0.005 | 0.170 | 0.000 | |||
7.87 | Postgraduate | Primary School and Below | 0.460 | 0.465 | 0.063 | |
Elementary and Middle School | 0.836 | 0.284 | 0.075 | |||
High School | 0.337 | 0.199 | 0.870 | |||
Vocational High School | 0.496 | 0.230 | 0.501 | |||
Associate's Degree | 0.168 | 0.189 | 0.000 | |||
Bachelor's Degree | 0.005 | 0.170 | 0.000 | |||
Quality Certification | 6.41 | Primary School and Below | Elementary and Middle School | -0.963 | 0.440 | 0.508 |
High School | -0.165 | 0.412 | 0.143 | |||
Vocational High School | -0.100 | 0.430 | 0.253 | |||
Associate's Degree | -0.014 | 0.415 | 0.332 | |||
Bachelor's Degree | -0.574 | 0.410 | 0.980 | |||
Postgraduate | -0.037 | 0.485 | 0.000 |
Table 14. (Continue) Comparison analysis for the differences between educational status subgroups according to the factors
Factors | Effect Value | (I) Educational Status Groups | (J) Educational Status Groups | Mean Difference (I-J) | Std. Error | Significance Value |
---|---|---|---|---|---|---|
Quality Certification | 7.38 | Elementary and Middle School | Primary School and Below | 0.963 | 0.440 | 0.508 |
High School | -0.202 | 0.229 | 0.000 | |||
Vocational High School | -0.137 | 0.260 | 0.000 | |||
Associate's Degree | -0.051 | 0.235 | 0.000 | |||
Bachelor's Degree | 0.390 | 0.226 | 0.849 | |||
Postgraduate | 0.926 | 0.344 | 0.154 | |||
7.58 | High School | Primary School and Below | 0.165 | 0.412 | 0.143 | |
Elementary and Middle School | 0.202 | 0.229 | 0.000 | |||
Vocational High School | 0.065 | 0.210 | 0.000 | |||
Associate's Degree | 0.151 | 0.178 | 0.000 | |||
Bachelor's Degree | 0.591* | 0.165 | 0.008 | |||
Postgraduate | 0.128* | 0.308 | 0.008 | |||
7.51 | Vocational High School | Primary School and Below | 0.100 | 0.430 | 0.253 | |
Elementary and Middle School | 0.137 | 0.260 | 0.000 | |||
High School | -0.065 | 0.210 | 0.000 | |||
Associate's Degree | 0.086 | 0.216 | 0.000 | |||
Bachelor's Degree | 0.527 | 0.206 | 0.209 | |||
Postgraduate | 0.063* | 0.331 | 0.034 | |||
Quality Certification | 7.43 | Associate's Degree | Primary School and Below | 0.014 | 0.415 | 0.332 |
Elementary and Middle School | 0.051 | 0.235 | 0.000 | |||
High School | -0.151 | 0.178 | 0.000 | |||
Vocational High School | -0.086 | 0.216 | 0.000 | |||
Bachelor's Degree | 0.440 | 0.173 | 0.212 | |||
Postgraduate | 0.977* | 0.312 | 0.045 | |||
6.99 | Bachelor's Degree | Primary School and Below | 0.574 | 0.410 | 0.980 | |
Elementary and Middle School | -0.390 | 0.226 | 0.849 | |||
High School | -0.591* | 0.165 | 0.008 | |||
Vocational High School | -0.527 | 0.206 | 0.209 | |||
Associate's Degree | -0.440 | 0.173 | 0.212 | |||
Postgraduate | 0.537 | 0.305 | 0.832 | |||
6.45 | Postgraduate | Primary School and Below | 0.037 | 0.485 | 0.000 | |
Elementary and Middle School | -0.926 | 0.344 | 0.154 | |||
High School | -0.128* | 0.308 | 0.008 | |||
Vocational High School | -0.063* | 0.331 | 0.034 | |||
Associate's Degree | -0.977* | 0.312 | 0.045 | |||
Bachelor's Degree | -0.537 | 0.305 | 0.832 |
Table 14. (Continue) Comparison analysis for the differences between educational status subgroups according to the factors
Factors | Effect Value | (I) Educational Status Groups | (J) Educational Status Groups | Mean Difference (I-J) | Std. Error | Significance Value |
---|---|---|---|---|---|---|
Delivery Time | 6.44 | Primary School and Below | Elementary and Middle School | -0.746 | 0.482 | 0.943 |
High School | -0.003 | 0.450 | 0.489 | |||
Vocational High School | -0.423 | 0.457 | 0.067 | |||
Associate's Degree | -0.128 | 0.445 | 0.276 | |||
Bachelor's Degree | -0.578 | 0.440 | 0.990 | |||
Postgraduate | -0.815 | 0.485 | 0.887 | |||
7.19 | Elementary and Middle School | Primary School and Below | 0.746 | 0.482 | 0.943 | |
High School | -0.256 | 0.267 | 0.000 | |||
Vocational High School | -0.676 | 0.278 | 0.286 | |||
Associate's Degree | -0.382 | 0.257 | 0.957 | |||
Bachelor's Degree | 0.168 | 0.249 | 0.000 | |||
Postgraduate | -0.069 | 0.321 | 0.000 | |||
7.44 | High School | Primary School and Below | 0.003 | 0.450 | 0.489 | |
Elementary and Middle School | 0.256 | 0.267 | 0.000 | |||
Vocational High School | -0.420 | 0.218 | 0.692 | |||
Associate's Degree | -0.125 | 0.190 | 0.000 | |||
Bachelor's Degree | 0.425 | 0.179 | 0.314 | |||
Postgraduate | 0.188 | 0.271 | 0.000 | |||
7.86 | Vocational High School | Primary School and Below | 0.423 | 0.457 | 0.067 | |
Elementary and Middle School | 0.676 | 0.278 | 0.286 | |||
High School | 0.420 | 0.218 | 0.692 | |||
Associate's Degree | 0.295 | 0.206 | 0.970 | |||
Bachelor's Degree | 0.845* | 0.196 | 0.000 | |||
Postgraduate | 0.608 | 0.282 | 0.505 | |||
7.57 | Associate's Degree | Primary School and Below | 0.128 | 0.445 | 0.276 | |
Elementary and Middle School | 0.382 | 0.257 | 0.957 | |||
High School | 0.125 | 0.190 | 0.000 | |||
Vocational High School | -0.295 | 0.206 | 0.970 | |||
Bachelor's Degree | 0.550* | 0.164 | 0.018 | |||
Postgraduate | 0.313 | 0.261 | 0.996 | |||
7.02 | Bachelor's Degree | Primary School and Below | 0.578 | 0.440 | 0.990 | |
Elementary and Middle School | -0.168 | 0.249 | 0.000 | |||
High School | -0.425 | 0.179 | 0.314 | |||
Vocational High School | -0.845* | 0.196 | 0.000 | |||
Associate's Degree | -0.550* | 0.164 | 0.018 | |||
Postgraduate | -0.237 | 0.253 | 0.000 | |||
7.26 | Postgraduate | Primary School and Below | 0.815 | 0.485 | 0.887 | |
Elementary and Middle School | 0.069 | 0.321 | 0.000 | |||
High School | -0.188 | 0.271 | 0.000 | |||
Vocational High School | -0.608 | 0.282 | 0.505 | |||
Associate's Degree | -0.313 | 0.261 | 0.996 | |||
Bachelor's Degree | 0.237 | 0.253 | 0.000 |
Table 14. (Continue) Comparison analysis for the differences between educational status subgroups according to the factors
Factors | Effect Value | (I) Educational Status Groups | (J) Educational Status Groups | Mean Difference (I-J) | Std. Error | Significance Value |
---|---|---|---|---|---|---|
Warranty | 6.44 | Primary School and Below | Elementary and Middle School | -0.970 | 0.549 | 0.842 |
High School | -0.521 | 0.515 | 0.108 | |||
Vocational High School | -0.855* | 0.517 | 0.020 | |||
Associate's Degree | -0.591 | 0.512 | 0.074 | |||
Bachelor's Degree | -0.265 | 0.509 | 0.313 | |||
Postgraduate | -0.046 | 0.553 | 0.754 | |||
7.41 | Elementary and Middle School | Primary School and Below | 0.970 | 0.549 | 0.842 | |
High School | -0.552 | 0.260 | 0.528 | |||
Vocational High School | -0.885* | 0.264 | 0.020 | |||
Associate's Degree | -0.622 | 0.254 | 0.279 | |||
Bachelor's Degree | -0.296 | 0.246 | 0.996 | |||
Postgraduate | -0.076 | 0.329 | 0.000 | |||
7.96 | High School | Primary School and Below | 0.521 | 0.515 | 0.108 | |
Elementary and Middle School | 0.552 | 0.260 | 0.528 | |||
Vocational High School | -0.333 | 0.183 | 0.776 | |||
Associate's Degree | -0.070 | 0.167 | 0.000 | |||
Bachelor's Degree | 0.256 | 0.156 | 0.890 | |||
Postgraduate | 0.475 | 0.268 | 0.819 | |||
8.30 | Vocational High School | Primary School and Below | 0.855* | 0.517 | 0.020 | |
Elementary and Middle School | 0.885* | 0.264 | 0.020 | |||
High School | 0.333 | 0.183 | 0.776 | |||
Associate's Degree | 0.264 | 0.174 | 0.948 | |||
Bachelor's Degree | 0.590* | 0.163 | 0.007 | |||
Postgraduate | 0.809 | 0.272 | 0.072 | |||
8.03 | Associate's Degree | Primary School and Below | 0.591 | 0.512 | 0.074 | |
Elementary and Middle School | 0.622 | 0.254 | 0.279 | |||
High School | 0.070 | 0.167 | 0.000 | |||
Vocational High School | -0.264 | 0.174 | 0.948 | |||
Bachelor's Degree | 0.326 | 0.146 | 0.419 | |||
Postgraduate | 0.545 | 0.262 | 0.573 | |||
7.71 | Bachelor's Degree | Primary School and Below | 0.265 | 0.509 | 0.313 | |
Elementary and Middle School | 0.296 | 0.246 | 0.996 | |||
High School | -0.256 | 0.156 | 0.890 | |||
Vocational High School | -0.590* | 0.163 | 0.007 | |||
Associate's Degree | -0.326 | 0.146 | 0.419 | |||
Postgraduate | 0.219 | 0.255 | 0.000 | |||
7.49 | Postgraduate | Primary School and Below | 0.046 | 0.553 | 0.754 | |
Elementary and Middle School | 0.076 | 0.329 | 0.000 | |||
High School | -0.475 | 0.268 | 0.819 | |||
Vocational High School | -0.809 | 0.272 | 0.072 | |||
Associate's Degree | -0.545 | 0.262 | 0.573 | |||
Bachelor's Degree | -0.219 | 0.255 | 0.000 |
In pairwise comparison tests, no significant difference was found between the effect values of usefulness and after-sales service factors for educational status groups.
Material type is important on the purchasing decisions and the differences between the effect values of interaction groups of primary school and below - bachelor's degrees, elementary and middle school-bachelor's degree, high school-vocational high school-associate's degrees; postgraduate-associate's degree and bachelor's degrees-postgraduate are significant. The differences between the effect values of other educational groups are insignificant. According to these data, compared to the individuals in other education groups, material type is more effective in purchasing decisions of the individuals with associate degrees, bachelor’s degrees and vocational high school education levels.
Quality Certification is important on purchasing decisions and the differences between the effect values of interaction groups primary school and below-post graduate, elementary and middle school-high school-vocational high school-associate's degrees, high school-vocational high school-associate degrees-bachelor’s degrees-postgraduate, vocational high school-associate degree and associate degree-postgraduate are significant. The differences between the effect values of other education groups are insignificant. According to these data, compared to the individuals in other education groups, quality certification is more effective in purchasing decisions of the individuals with high school, vocational high school, associate degrees and elementary and middle school education levels.
The differences between the effect values of the brand value for the individuals with bachelor’s degrees-associate degree-high school and the individuals with vocational high school-elementary and middle school are insignificant. According to these data, compared to individuals in other education groups, brand value is the most effective in purchasing decisions of the individuals at high school, associate degree and bachelor’s degree education levels, while it is least effective in the individuals with primary school and below education level.
While reliability is the most effective in purchasing decision of high school graduates, it is followed by associate degrees at second and vocational high school, elementary and middle school and bachelor’s degrees equally at third. The education group in which safety has the least effect on the purchase decision has been the individuals with primary school and below education level.
While price is the most effective in purchasing decisions of elementary and middle school, bachelor’s degrees, associate degrees and high school graduates, it is followed by vocational high school, postgraduate and primary school and below individuals, respectively.
Ease of assembly is most effective in purchasing decisions of the individuals with associate degrees and high school graduates, followed by the individuals with postgraduate, vocational high school, elementary and middle school and bachelor’s degrees. Ease of assembly has the lowest effect on the individuals with primary school education and below.
The differences between effect values of delivery time for elementary and middle school- bachelor’s degrees, high school-elementary and middle school-postgraduate, vocational high school-bachelor’s degrees, the associate degrees-high school-bachelor’s degrees, postgraduates-elementary and middle school-bachelor’s degrees, associate-undergraduate degree, undergraduate-graduate degree education levels are significant. The differences between other education levels are insignificant. According to these data, compared to the individuals in other education groups, delivery time is more effective in purchasing decisions of the individuals with vocational high school, high school and associate degree education levels.
The differences between effect values of warranty for vocational high school education-elementary and middle school-bachelor’s degrees, bachelor’s degrees-postgraduates, postgraduates-elementary and middle school education levels are significant. The differences between effect values of other education levels are insignificant. According to these data, compared to the individuals at other education levels, warranty is more effective in purchasing decisions of the individuals at vocational high school, associate degrees and high school education levels.
The aim of this study is to determine priorities of the furniture specifications in purchasing and the effect levels of the each specification on furniture purchase decision according to the some socio-demographic characteristics.
Regardless of any socio-demographic characteristics, functionality with an effect value of 8.29 is the most influential factor in furniture purchasing,, followed by lifetime with an effect value of 8.26 and aesthetics with an effect value of 8.13. Ease of assembly is the least effective factor with an effect value of 6.93.
The factors of material type, brand value, size, ease of assembly and delivery time are ineffective on purchasing decisions of individuals in different gender groups, while other factors are effective. The product specifications such as quality certification, lifetime, reliability, aesthetics, size, functionality, durability, warranty and after-sales services are more effective in women's purchasing decisions than men's.
The factors of brand value, lifetime, aesthetics, size, price and ease of assembly factors are ineffective on purchasing decisions of individuals from different age groups. Concerning the purchasing decisions of the individuals in different age groups, effect value of material type is higher in 25–34, 35–44 and 45–54 age groups than those of 15–24 and 55 and over age groups. The quality certification in 35–44 and 45–54 age groups, the reliability in 35–44 and 55 and over age groups, the functionality, durability and delivery time in 35–44, 45–54 and 55 and over age groups, and the warranty and after-sales service in 35–44 and 55 and over age groups are more effective compared to the other age groups.
The factors of lifetime, aesthetics, size, durability, functionality and after sales service were found to be ineffective on the purchasing decisions of the individuals at different education levels. Regarding purchasing decisions of the individuals at different education levels, material type is more effective in graduates of vocational high school, associate degree and bachelor’s degree, the quality certification in high school, vocational high school, associate degree and elementary and middle school, the price in elementary and middle school, bachelor’s degree, associate degree and high school, the ease of assembly in associate degree and high school, the delivery time in vocational high school, high school and associate degree, the warranty in vocational high school, associate degree and high school, the brand value in high school, associate degree and bachelor’s degree, and the reliability in high school.
The effects levels of the factors that are effective in purchasing decision of furniture, which are called furniture product specification, differ according to the socio-demographic characteristics of consumers. For example, the expectations of the consumers in upper-upper income group regarding the furniture specifications such as material, aesthetic, size, etc. will not be same as the expectations of the consumer in the middle-lower income group. In determining which criteria will be prioritized in product design, the expectations depending on the socio-demographic structure of the selected target market should be taken as a basis. The results obtained from this research will be useful in making such decisions.
Ethics
There are no ethical issues after the publication of this manuscript.
Acknowledgements
This research was produced from the preliminary data obtained within the scope of the doctoral thesis study that supported by the Gazi University Scientific Research Projects Unit under grant the project numbered 07/2019-29.
Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.