The Effects of furniture specifications on purchasing decisions according to some socio-demographic consumer characteristics

DOI: https://doi.org/10.21203/rs.3.rs-2752527/v1

Abstract

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.

1. Introduction

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.

2. Materials And Methods

2.1. Questionnaire, Sample Size and Data Collection

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).

Table 1

The form used to record the effect levels of furniture specifications

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.

Table 2

Descriptive statistics on some socio-demographic characteristics of the participants

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

2.2. Statistical Data Analysis

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.

3. Results And Discussion

The effect levels of the factors on purchase decision of furniture, without considering any socio-demographic characteristics, are given in Table 3.

Table 3

Effect levels of the factors on purchase decision of furniture without considering any socio-demographic characteristics

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)”.

3.1. Effects of the factors on purchasing decision by gender

Some descriptive statistical values for the effect values of purchasing decision factors for each gender group are given in Table 4.

Table 4

Some descriptive statistical values for the effect values of the factors for each gender group

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

Table 4

(Continue) Some descriptive statistical values for the effect values of the factors for each gender group

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.

Table 5

Mann-Whitney U and independent sample t-test results depending on the factors and gender groups

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.

3.2. Effects of the factors on purchasing decision by Marital Status

Some descriptive statistical values for the effect values of the factors for each marital status group are given in Table 6.

Table 6

Some descriptive statistical values for the effect values of the factors for each marital status group

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.

Table 7

Kruskal Wallis-H and ANOVA test results depending on the factors and marital status groups

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.

Table 8

Comparison analysis for differences between marital status subgroups according to the factors

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.

3.3. Effects of the factors on purchasing decision by Age

Some descriptive statistical values for the effect values of the factors for each age group are given in Table 9.

Table 9

Some descriptive statistical values for the effect values of the factors for each age group

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

Table 9

(Continue) Some descriptive statistical values for the effect values of the factors for each age group

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.

Table 10

Kruskal Wallis-H and ANOVA test results depending on the factors and age groups

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

Table 10

(Continue) Kruskal Wallis-H and ANOVA test results depending on the factors and age groups

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.

Table 11

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

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

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

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.

3.4. Effects of the factors on purchasing decision by educational status

Some descriptive statistical values for the effect values of the factors for each educational status group are given in Table 12.

Table 12

Some descriptive statistical values for the effect values of purchasing decision factors for each educational status group

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

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

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.

Table 13

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

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

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

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.

Table 14

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

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

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

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.

4. Conclusions

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.

Declarations

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.  

References

  1. Amoah, M., Dadzie, P. K., Bih, F. K. & Wiafe, E. D. (2015). Consumer preferences and purchase intentions for rattan furniture. Wood and Fiber Science, 47(3), 225–239. https://wfs.swst.org/index.php/wfs/article/view/2319
  2. Banar, K. & Ekergil, V. (2010). Service Quality of Members of Accounting Profession: The Relationship between Service Quality to Customer Satisfaction Eskişehir Application. Anadolu University Journal of Social Sciences, 10(1), 39–60. https://earsiv.anadolu.edu.tr/xmlui/handle/11421/267
  3. Bumgardner, M., Nicholls, D. & Donovan, G. (2007). Effects of species information and furniture price on consumer preferences for selected woods. Wood and Fiber Science, 39(1), 71–81. https://www.fs.usda.gov/research/treesearch/19637
  4. Güzel, T. A. (2020a). Consumer Attitudes and Preferences about Upholstered Furniture. Gazi University Journal of Science Part A: Engineering and Innovation, 7(3), 69–82.
  5. Güzel, T. A. (2020b). Consumer attitudes toward preference and use of wood, woodenware, and furniture: A sample from Kayseri, Turkey. BioResources, 15(1), 28–37. https://doi.org/10.15376/biores.15.1.28-37
  6. Kaputa, V., Barčić, A. P., Maťová, H. & Motik, D. (2018). Consumer preferences for wooden furniture in Croatia and Slovakia. BioResources, 13(3), 6280–6299. https://doi.org/10.15376/biores.13.3.6280-6299
  7. Khojasteh-Khosro, S., Shalbafan, A. & Thoemen, H. (2020). Preferences of furniture manufacturers for using lightweight wood-based panels as eco-friendly products. European Journal of Wood and Wood Products, 78(3), 593–603. https://doi.org/10.1007/s00107-020-01519-8
  8. Khojasteh-Khosro, S., Shalbafan, A. & Thoemen, H. (2022). Consumer behavior assessment regarding lightweight furniture as an environmentally-friendly product. Wood Material Science & Engineering, 17(3), 192–201. https://doi.org/10.1080/17480272.2020.1847187
  9. Knauf, M. (2015). Understanding the consumer: Multi-modal market research on consumer attitudes in Germany towards lightweight furniture and lightweight materials in furniture design. European Journal of Wood and Wood Products, 73(2), 259–270. https://doi.org/10.1007/s00107-014-0866-9
  10. Kumburu, N. P. & Kessy, J. F. (2021). Consumers’ Preference on Imported and Locally Made Furniture in Dar es Salaam and Arusha, Tanzania. Global Business Review, 22(1), 23–35. https://doi.org/10.1177/0972150918811519
  11. Lihra, T., Buehlmann, U. & Graf, R. (2012). Customer preferences for customized household furniture. Journal of Forest Economics, 18(2), 94–112. https://doi.org/10.1016/j.jfe.2011.11.001
  12. Liu, S.-F., Jiang, M., Lin, J.-Y. & Yang, Z. (2017). Study of the Consumer Life Style and the Shape Preference of Ming Style Furniture. Proceedings of the 2017 International Conference on Organizational Innovation (ICOI 2017), 170–175. https://doi.org/10.2991/icoi-17.2017.1
  13. Oblak, L., Glavonjić, B., Pirc Barčić, A., Bizjak Govedič, T. & Grošelj, P. (2020). Preferences of Different Target Groups of Consumers in Case of Furniture Purchase. Drvna Industrija, 71(1), 79–87. https://doi.org/10.5552/drvind.2020.1932
  14. Oblak, L., Perić, I., Pirc Barčić, A., Nosáľová, M., Kaputa, V. & Jošt, M. (2020). Changes in Customer Preferences for Furniture in Slovenia. Drvna Industrija, 71(2), 149–156. https://doi.org/10.5552/drvind.2020.1967
  15. Öztop, H., Erkal, S. & Gunay, G. (2008). Factors Influential in Consumers’ Furniture Selection and their Preferences regarding Product Features. The International Journal of Interdisciplinary Social Sciences: Annual Review, 3(6), 23–34. https://doi.org/10.18848/1833-1882/CGP/v03i06/52632
  16. Pakarinen, T. J. & Asikainen, A. T. (2001). Consumer segments for wooden household furniture. Holz Als Roh - Und Werkstoff, 59(3), 217–227. https://doi.org/10.1007/S001070100187/METRICS
  17. Paluš, H., Maťová, H. & Kaputa, V. (2012). Consumer Preferences for Joinery Products and Furniture in Slovakia and Poland. Acta Facultatis Xylologiae, 52(2), 123–132.
  18. Pirc Barčić, A., Kitek Kuzman, M., Vergot, T. & Grošelj, P. (2021). Monitoring Consumer Purchasing Behavior for Wood Furniture before and during the COVID-19 Pandemic. Forests, 12(7), 873. https://doi.org/10.3390/f12070873
  19. Soysal, A. N. (2015). Customer satisfaction and perception of service quality at customer oriented approach: The example of a hospital. Pamukkale University.
  20. TSE EN ISO 9000. (2015). Quality management system-Fundamentals and vocabulary. www.tse.org.tr
  21. Viikari, V. (2021). Consumer preferences for secondhand furniture. Aalto University School of Business.
  22. Wulandari, R., Suharjo, B., Soehadi, A. W. & Purnomo, H. (2012). Characteristic and Preferences of Green Consumer Stratification As Bases to Formulating Marketing Strategies of Ecolabel-Certified Furniture. Issues In Social And Environmental Accounting, 6(1), 123. https://doi.org/10.22164/isea.v6i1.67
  23. Yazıcıoğlu, Y. & Erdoğan, S. (2014). Spss Uygulamalı Bilimsel Araştırma Yöntemleri (4th ed.). Detay Publishing. https://www.detayyayin.com.tr/urun/spss-uygulamali-bilimsel-arastirma-yontemleri
  24. Yeşilbayır, S. (2007). Total quality management. Istanbul Technical University.