Analysis of Factors Influencing Consumer Purchasing Decisions in the Jakarta Metropolitan Area: A Study on Clothing Retail in Jabodetabek

 

Shafia Ashma Khairunnisa1, Triana Rahajeng Hadiprawoto2

1,2University of Indonesia, Jakarta, Indonesia

Email : [email protected], [email protected]

Abstract

The retail fashion industry in Greater Jakarta (Jakarta, Bogor, Depok, Tangerang, Bekasi) is highly competitive, necessitating an understanding of the factors influencing consumer purchasing decisions. This research examines the impact of store design and atmosphere on these decisions, with a particular focus on window display, mannequin display, visual merchandising, music, light and color, and signage. The study aims to analyze the direct influence of store design and atmosphere, their mediating roles, the moderating effect of perceived service quality, and the direct impact of product, price, and promotion on purchasing decisions. Utilizing a quantitative, descriptive approach, data were collected and analyzed using Structural Equation Modeling (SEM) and model fit evaluation with SPSS 26 and SmartPLS 3.0. The results indicate that store design and atmosphere significantly impact consumer purchasing decisions, with window display, mannequin display, visual merchandising, music, light and color, and signage serving as mediators. Additionally, perceived service quality moderates this relationship, while product, price, and promotion have a direct impact on purchasing decisions. The study concludes that fashion retailers in metropolitan Jakarta should prioritize store design, atmosphere, and service quality to enhance purchasing decisions and develop effective consumer strategies.

Keywords:

department store, store design and atmosphere, shoppers' purchase decisions, perceived service quality, specialty store

 

INTRODUCTION

The fashion industry is a major driver of online transactions in Indonesia, the largest e-commerce market in Southeast Asia (Suzianti et al., 2023). In 2023, the growth of Indonesia's e-commerce industry is particularly notable in the fashion and clothing segments, which are the most popular categories on platforms like Tokopedia, Shopee, and Lazada (Mondor Market, 2024, 2024; Yusra, 2023).

However, this digital shift poses challenges for physical retail stores, which remain crucial for providing a tangible shopping experience despite the rise of e-commerce (Mudjahidin et al., 2021). However, in this competitive retail industry, the ability to respond quickly and understand consumer behavior is one of the significant factors influencing a retail business's success. This fierce competition requires companies to continue to follow trends and anticipate consumer needs efficiently. (Fink et al., 2021; Hidayah, 2022; Joewono et al., 2020)

Factors influencing consumer purchasing decisions in retail include store design, interior and exterior features, and atmospheric elements like color, music, and lighting. These elements impact store perception and consumer choice. Retailers are increasingly focusing on creating an attractive store atmosphere through storefront arrangement, music selection, visual merchandising, and other appealing elements (Khan et al., 2023; Lopienski, 2023).

Store atmosphere, encompassing exterior, general interior, layout, and interior display, can significantly enhance consumer interest and purchasing enjoyment. Effective store design and atmosphere management can influence purchasing decisions and encourage consumer loyalty.

While existing research highlights the influence of store atmosphere on consumer behavior, there is a gap in understanding the urgency of rapid response and deep insight into shopper behavior in the competitive retail landscape. This study aims to address this gap by emphasizing the importance of store design and atmosphere management in achieving competitive advantage and meeting customer preferences (Khan et al., 2023).

The retail mix, which includes products, prices, promotions, services, locations, and store atmosphere, is a strategic tool for influencing consumer purchasing decisions (Joewono et al., 2020; Kilay et al., 2022; Syuhada & Gambett, 2013; Warburton, 2020). Management can use this mix to assess and enhance their marketing strategies, aligning them with consumer preferences. In urban areas, shopping centers are pivotal, with department stores offering diverse product categories and specialty stores focusing on specific product lines (Prihananto et al., 2024).

The increasing existence of retail markets in urban areas depends on shopping centers, where the largest retail space is generally owned by department stores, namely, a retail area with various types of product categories. On the other hand, shopping centers are filled by other forms of retail that focus on selling limited product categories, referred to as specialty stores.

Specialty stores like Zara, Bershka, The Executive, and 3Second cater to market preferences and needs. Store design and atmosphere elements such as window displays, mannequins, visual merchandising, music, light and color, and signage are crucial in influencing consumer purchasing decisions. This study seeks to explore additional variables that might affect the impact of store design and atmosphere on purchasing decisions (Khan et al., 2023; Monoarfa et al., 2023).

Indoor environmental quality (IEQ) and store design and atmosphere (SDA) are interrelated concepts, with IEQ focusing on indoor air quality, thermal comfort, and lighting, and SDA focusing on visual and atmospheric elements. Both concepts aim to enhance shopping experiences and influence purchasing decisions. Moderation variables like perceived service quality (PSQ) can further elucidate the relationship between store design, atmosphere, and shopper purchase decisions (Dang et al., 2021).

This research examines and analyzes the direct influence of store design and atmosphere on shoppers� purchase decisions in retail fashion in the Greater Jakarta area (Jabodetabek). Additionally, the study aims to investigate the mediating role of store design and atmosphere in the relationship between window display, mannequin display, visual merchandising, music, light and color, and signage with shoppers� purchase decisions. Furthermore, the research seeks to evaluate the moderating effect of perceived service quality on the relationship between store design and atmosphere and shoppers� purchase decisions. Moreover, the study aims to assess the direct impact of products on shoppers� purchase decisions, analyze the direct influence of price on shoppers� purchase decisions, and determine the direct effect of promotion on shoppers� purchase decisions in retail fashion in Jabodetabek.

 

RESEARCH METHODS

This research uses quantitative methods with a descriptive approach. This method was chosen to explore the relationship between design factors and store atmosphere with consumer purchasing decisions in fashion retail stores. The object of this research is a fashion retail store that applies various design elements and store atmospheres such as window display, mannequin display, visual merchandising, music, light and color, and signage.

The source of data in this study is primary data obtained through direct surveys to consumers who shop at fashion retail stores. Secondary data were obtained from literature studies related to store design, atmosphere, and consumer purchasing decisions. The population in this study is all consumers who have shopped at fashion retail stores in the study area. The study sample was determined using purposive sampling techniques, namely selecting respondents who have experience shopping in stores that apply the design elements and atmosphere studied.

The data collection technique used is a survey using questionnaires as a research tool. The questionnaire contains questions designed to measure consumers' perceptions of store design and atmosphere and their influence on purchasing decisions. The collected data were analyzed using descriptive and inferential statistical analysis techniques. Descriptive analysis is used to describe the characteristics of respondents and the distribution of their answers. Inferential analysis, such as multiple linear regression, is used to examine the relationship between the independent variable (window display, mannequin display, visual merchandising, music, light and color, signage) and the dependent variable (consumer purchase decision). This study also looks at the role of moderators of perceived service quality in the relationship between store design and atmosphere and consumer purchasing decisions to gain a more comprehensive understanding of the factors that influence purchasing decisions.


RESULTS AND DISCUSSION

Pilot Test

Validity Test

 

Table 1. Validity Test Results

Variable

Code

SME

Anti-Image Correlation Matrix

Component Matrix

Information

Window display

WD01

0,736

0,763

0,874

Valid

WD02

0,757

0,881

Valid

WD03

0,691

0,860

Valid

WD04

0,737

0,732

Valid

Mannequin display

MD01

0,808

0,851

0,789

Valid

MD02

0,839

0,805

Valid

MD03

0,771

0,860

Valid

MD04

0,789

0,839

Valid

Visual merchandising

MV01

0,762

0,797

0,858

Valid

MV02

0,826

0,757

Valid

MV03

0,751

0,879

Valid

MV04

0,710

0,889

Valid

Music

MS01

0,722

0,839

0,547

Valid

MS02

0,684

0,827

Valid

MS03

0,811

0,754

Valid

MS04

0,675

0,855

Valid

Light and color

LC01

0,81

0,797

0,837

Valid

LC02

0,797

0,837

Valid

LC03

0,828

0,810

Valid

LC04

0,821

0,821

Valid

Signage

SG01

0,818

0,852

0,807

Valid

SG02

0,848

0,807

Valid

SG03

0,780

0,868

Valid

SG04

0,804

0,844

Valid

Product

PD01

0,827

0,816

0,870

Valid

PD02

0,834

0,840

Valid

PD03

0,837

0,837

Valid

PD04

0,825

0,863

Valid

Price

PR01

0,739

0,717

0,883

Valid

PR02

0,750

0,730

Valid

PR03

0,794

0,846

Valid

PR04

0,705

0,806

Valid

Promotion

PM01

0,88

0,873

0,851

Valid

PM02

0,882

0,885

Valid

PM03

0,856

0,909

Valid

PM04

0,921

0,864

Valid

PM05

0,873

0,862

Valid

Shoppers' purchase decisions

SPD01

0,789

0,773

0,833

Valid

SPD02

0,738

0,833

Valid

SPD03

0,808

0,840

Valid

SPD04

0,866

0,838

Valid

SPD05

0,812

0,892

Valid

Store design and atmosphere

SDA01

0,881

0,916

0,878

Valid

SDA02

0,828

0,774

Valid

SDA03

0,86

0,845

Valid

SDA04

0,875

0,813

Valid

SDA05

0,874

0,861

Valid

SDA06

0,818

0,738

Valid

SDA07

0,883

0,825

Valid

SDA08

0,825

0,780

Valid

SDA09

0,888

0,794

Valid

SDA10

0,938

0,746

Valid

SDA11

0,915

0,755

Valid

SDA12

0,922

0,761

Valid

SDA13

0,89

0,695

Valid

SDA14

0,925

0,796

Valid

Perceived service quality

PSQ01

0,835

0,87

0,734

Valid

PSQ02

0,814

0,778

Valid

PSQ03

0,928

0,798

Valid

QSP04

0,814

0,768

Valid

PSQ05

0,81

0,815

Valid

QSP06

0,726

0,766

Valid

QSP07

0,901

0,856

Valid

 

The validity test results against the pilot test involving 164 respondents showed that all indicators showed a strong correlation. This is shown by the KMO, Anti-Image Correlation, and component matrix values > 0.5. Then all variables pass the validity test and are able to describe the independent variable well.

Reliability Test

 

Table 2. Reliability Test Results

No

Variable

Cronbach�s Alpha

Limitation

Information

1

Window display

0,859

0,600

Reliable

2

Mannequin display

0,836

0,600

Reliable

3

Visual merchandising

0,867

0,600

Reliable

4

Music

0,722

0,600

Reliable

5

Light and color

0,844

0,600

Reliable

6

Signage

0,845

0,600

Reliable

7

Product

0,873

0,600

Reliable

8

Price

0,829

0,600

Reliable

9

Promotion

0,923

0,600

Reliable

10

Shoppers' purchase decisions

0,901

0,600

Reliable

11

Store design & atmosphere

0,952

0,600

Reliable

12

Perceived service quality

0,898

0,600

Reliable

 

Based on the results of reliability tests conducted on pilot tests with 164 respondent data, the table above each variable has a Cronbach's Alpha value of > 0.600, then all variables show consistent results (Cronbach's Alpha value > 0.600) and are considered to pass the validity test and are able to measure the dependent variable well.

Main Test

Validity Test

 

Table 3. Validity Test Results

Variable

Code

SME

Anti-Image Correlation Matrix

Component Matrix

Information

Window display

WD01

0,745

0,727

0,843

Valid

WD02

0,776

0,688

Valid

WD03

0,726

0,848

Valid

WD04

0,774

0,733

Valid

Mannequin display

MD01

0,743

0,757

0,746

Valid

MD02

0,772

0,702

Valid

MD03

0,800

0,739

Valid

MD04

0,686

0,855

Valid

Visual merchandis-ing

MV01

0,757

0,753

0,765

Valid

MV02

0,792

0,680

Valid

MV03

0,742

0,788

Valid

MV04

0,753

0,758

Valid

Music

MS01

0,767

0,794

0,747

Valid

MS02

0,719

0,834

Valid

MS03

0,808

0,730

Valid

MS04

0,772

0,754

Valid

Light and color

LC01

0,752

0,767

0,754

Valid

LC02

0,796

0,836

Valid

LC03

0,748

0,724

Valid

LC04

0,711

0,887

Valid

Signage

SG01

0,77

0,719

0,857

Valid

SG02

0,858

0,694

Valid

SG03

0,830

0,768

Valid

SG04

0,739

0,828

Valid

Product

PD01

0,781

0,749

0,829

Valid

PD02

0,833

0,717

Valid

PD03

0,764

0,802

Valid

PD04

0,798

0,795

Valid

Price

PR01

0,779

0,852

0,707

Valid

PR02

0,816

0,769

Valid

PR03

0,770

0,825

Valid

PR04

0,727

0,865

Valid

Promotion

PM01

0,845

0,840

0,779

Valid

PM02

0,837

0,791

Valid

PM03

0,856

0,763

Valid

PM04

0,839

0,763

Valid

PM05

0,857

0,723

Valid

Shoppers' purchase decisions

SPD01

0,852

0,865

0,745

Valid

SPD02

0,869

0,805

Valid

SPD03

0,838

0,801

Valid

SPD04

0,876

0,773

Valid

SPD05

0,822

0,837

Valid

Store design and atmosphere

SDA01

0,952

0,969

0,729

Valid

SDA02

0,968

0,801

Valid

SDA03

0,957

0,754

Valid

SDA04

0,927

0,801

Valid

SDA05

0,934

0,802

Valid

SDA06

0,954

0,804

Valid

SDA07

0,968

0,781

Valid

SDA08

0,968

0,820

Valid

SDA09

0,948

0,812

Valid

SDA10

0,941

0,768

Valid

SDA11

0,962

0,846

Valid

SDA12

0,949

0,815

Valid

SDA13

0,947

0,825

Valid

SDA14

0,945

0,792

Valid

Perceived service quality

PSQ01

0,901

0,919

0,762

Valid

PSQ02

0,932

0,705

Valid

PSQ03

0,867

0,814

Valid

QSP04

0,910

0,744

Valid

PSQ05

0,926

0,724

Valid

QSP06

0,866

0,776

Valid

QSP07

0,906

0,724

Valid

 

Based on the validity test, each indicator has a KMO, Anti-Image Correlation, and Component Matrix value of > 0.5. Then, all variables pass the validity test and can describe independent variables well.

Reliability Test

 

Table 4. Reliability Test Results

No

Variable

Cronbach�s Alpha

Limitation

Information

1

Window display

0,782

0,600

Reliable

2

Mannequin display

0,750

0,600

Reliable

3

Visual merchandising

0,738

0,600

Reliable

4

Music

0,763

0,600

Reliable

5

Light and color

0,804

0,600

Reliable

6

Signage

0,791

0,600

Reliable

7

Product

0,795

0,600

Reliable

8

Price

0,790

0,600

Reliable

9

Promotion

0,819

0,600

Reliable

10

Shoppers' purchase decisions

0,851

0,600

Reliable

11

Store design and atmosphere

0,955

0,600

Reliable

12

Perceived service quality

0,870

0,600

Reliable

 

Based on the reliability test, each variable has a Cronbach's Alpha value of >0.600, then all variables pass the reliability test and are able to measure the dependent variable well.

Analysis SEM-PLS

Outer Model

This model aims to measure construct validity, the extent to which latent variables represented by measurement indicators are observed. The outer model serves to evacuate the quality of measurement of variables that cannot be observed directly by utilizing observational variables that can be measured directly. The significance of this function in SEM analysis is very important because it favors the understanding and validation of the constructs of latent variables, which are an important aspect of research. Outer model analysis in SmartPLS involves three main aspects, namely outer loading, construct validity and reliability, and discriminant variables. Here is the development of the outer model in this study (Hair et al., 2018, 2019).

Outer Loading

 

 

 

Table 5. Outer Loading Value, Average and Standard Revision of Each Indicator

Variable

Code

Rata-rata

Standard Deviation

Outer Loading

Information

Window display

WD01

4.312

0.839

0.796

Valid

WD02

4.130

0.891

0.729

Valid

WD03

4.098

0.843

0.835

Valid

WD04

4.301

0.853

0.750

Valid

Mannequin display

MD01

4.153

0.860

0.734

Valid

MD02

4.035

0.892

0.742

Valid

MD03

4.183

0.812

0.743

Valid

MD04

3.996

0.730

0.822

Valid

Visual merchandising

MV01

4.167

0.947

0.770

Valid

MV02

4.039

0.880

0.727

Valid

MV03

4.094

0.898

0.784

Valid

MV04

4.118

0.879

0.704

Valid

Music

MS01

4.075

0.914

0.783

Valid

MS02

4.253

0.803

0.801

Valid

MS03

4.124

0.893

0.764

Valid

MS04

4.090

0.822

0.707

Valid

Light and color

LC01

4.47

0.708

0.745

Valid

LC02

4.566

0.639

0.840

Valid

LC03

4.279

0.785

0.740

Valid

LC04

4.511

0.633

0.875

Valid

Signage

SG01

4.248

0.779

0.854

Valid

SG02

4.035

0.903

0.723

Valid

SG03

4.161

0.792

0.772

Valid

SG04

4.029

0.837

0.797

Valid

Product

PD01

4.301

0.710

0.828

Valid

PD02

4.348

0.598

0.733

Valid

PD03

4.332

0.668

0.787

Valid

PD04

4.318

0.655

0.795

Valid

Price

PR01

4.297

0.723

0.749

Valid

PR02

4.548

0.548

0.738

Valid

PR03

4.501

0.565

0.823

Valid

PR04

4.538

0.549

0.852

Valid

Promotion

PM01

4.371

0.688

0.793

Valid

PM02

4.389

0.673

0.788

Valid

PM03

4.232

0.768

0.758

Valid

PM04

4.375

0.671

0.743

Valid

PM05

4.316

0.790

0.735

Valid

Shoppers' purchase decisions

SPD01

4.432

0.636

0.748

Valid

SPD02

4.305

0.578

0.817

Valid

SPD03

4.434

0.610

0.797

Valid

SPD04

4.248

0.653

0.767

Valid

SPD05

4.308

0.652

0.832

Valid

Store design and atmosphere

SDA01

4.338

0.612

0.730

Valid

SDA02

4.238

0.718

0.800

Valid

SDA03

4.44

0.765

0.754

Valid

SDA04

4.483

0.840

0.799

Valid

SDA05

4.422

0.863

0.800

Valid

SDA06

4.251

0.837

0.804

Valid

SDA07

4.016

0.951

0.782

Valid

SDA08

4.183

0.924

0.820

Valid

SDA09

3.998

0.836

0.811

Valid

SDA10

3.914

0.938

0.768

Valid

SDA11

4.108

0.954

0.846

Valid

SDA12

4.12

0.914

0.815

Valid

SDA13

4.141

0.948

0.826

Valid

SDA14

4.136

0.877

0.793

Valid

Perceived service quality

PSQ01

4.615

0.503

0.749

Valid

PSQ02

4.560

0.520

0.732

Valid

PSQ03

4.391

0.554

0.809

Valid

QSP04

4.391

0.551

0.741

Valid

PSQ05

4.428

0.546

0.722

Valid

QSP06

4.432

0.550

0.774

Valid

QSP07

4.485

0.543

0.719

Valid

In this study, each variable has indicators with varying average and outer loading values. In the variable window display (WD), the WD03 indicator shows the highest outer loading value of 0.835, while the highest average is held by WD01 with a value of 4.312. Meanwhile, in the variable mannequin display (MD), the MD04 indicator has the highest outer loading value of 0.822, while the highest average is held by MD01 with a value of 4.153. This difference shows that each variable has the strongest aspect in influencing the measured factor and has the highest respondent perception. For example, in the store design and atmosphere (SDA) variable, the SDA11 indicator has the highest outer loading value of 0.846, while the highest average is held by SDA03 with a value of 4.440. Based on the table also shows that the outer loading value of each indicator has an outer loading value of >0.7. Therefore, all indicators can be used in research and do not need to be excluded.

Construct Validity and Reliability

Cronbach�s Alpha

 

Table 6. Cronbach's Alpha Value of Each Variable

Variable

Cronbach's Alpha

Information

Shoppers� purchase decisions

0.852

Reliable

Store design & atmosphere

0.956

Reliable

Light and color

0.813

Reliable

Mannequin display

0.758

Reliable

Music

0.766

Reliable

Perceived service quality

0.870

Reliable

Price

0.802

Reliable

Product

0.794

Reliable

Promotion

0.822

Reliable

Signage

0.795

Reliable

Visual merchandising

0.738

Reliable

Window display

0.784

Reliable

 

Cronbach's alpha is used to measure the internal consistency of a data set or questionnaire, with higher values close to 1 indicating a better level of consistency. In this analysis, the store design and atmosphere variables dominated with the highest value, reaching 0.956, indicating very high consistency in store design and atmosphere measurements. In contrast, the visual merchandising variable has a relatively lower value, 0.738, indicating a fairly good level of consistency in measuring the effect of visual appearance on the shopping experience. Meanwhile, other variables, such as perceived service quality with a value of 0.870 and shoppers' purchase decisions with a value of 0.852, showed high reliability in measuring the variables used in this study. Furthermore, all variables listed have values above 0.7. Therefore, all variables used in this study showed high reliability in each measurement. Thus, all of these variables are worthy of use in this study, are considered reliable, and have consistent values.

Composite Reliability

 

 

Table 7. Composite Reliability Value of Each Variable

Variable

Composite Reliability

Information

Shoppers� purchase decisions

0.894

Reliable

Store design & atmosphere

0.961

Reliable

Light and color

0.878

Reliable

Mannequin display

0.846

Reliable

Music

0.849

Reliable

Perceived service quality

0.900

Reliable

Price

0.870

Reliable

Product

0.866

Reliable

Promotion

0.875

Reliable

Signage

0.867

Reliable

Visual merchandising

0.834

Reliable

Window display

0.860

Reliable

 

Based on the composite reliability value of all variables above 0.700, the store design and atmosphere variables showed the highest value of 0.961, indicating the highest level of construct reliability in measurement. This suggests that store design and atmosphere factors tend to provide high consistency. On the other hand, the second highest value was found in the shoppers' purchase decisions variable with a value of 0.894, emphasizing strong reliability in measuring factors related to customer purchase decisions. However, the lowest value in this analysis was on the visual merchandising variable, with a value of 0.834, which indicates that there is slightly more variation in measurement consistency related to the visual appearance of products in stores. The overall average composite reliability for all variables was 0.879, indicating that the constructs observed in this study had an adequate degree of reliability in measurements. This shows that each variable used in this study meets the composite reliability standard of > 0.700. Therefore, all variables can be used in research.

Average Variance Extracted (AVE)

 

Table 8. Average Variance Extracted test results

Variable

Average Variance Extracted (AVE)

Shoppers� purchase decisions

0.628

Store design and atmosphere

0.635

Light and color

0.644

Mannequin display

0.579

Music

0.585

Perceived service quality

0.563

Price

0.628

Product

0.619

Promotion

0.584

Signage

0.621

Visual merchandising

0.558

Window display

0.606

The table above shows that each variable has an average variance extracted value that exceeds 0.5. The highest AVE value is for the light and color variable, with an AVE of 0.644, while the lowest value is for the visual merchandising variable, with a value of 0.558. The average AVE value for all variables is about 0.613. This shows that every variable used in this study can be used in the study without needing to be excluded.

Discriminant Validity

Fornell-Larcker Criterion

 

Variable

L&C

MD

MS

QSP

PR

PD

PM

SPD

SG

SDA

VM

WD

Light and color

0,802