The Influence of Individual Drivers on Purchase Intention from Customize Products Through Brand Experience and Intention to Use Customization Toolkit

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^1,2School of Economics and Business Telkom University, Bandung, West Java, Indonesia

Email: [email protected]¹, [email protected]^2*

Abstract

Companies providing custom sportswear in Indonesia have seen a significant increase in demand for custom designs, particularly since the onset of the pandemic. As a result, there is a growing need for businesses to improve productivity by adopting self-design virtual services through websites or applications, similar to practices in other countries. This enables more efficient design processes and reduces the workload of full-time design staff. Despite this trend, limited research has explored the role of brand experience in influencing consumers' intentions to purchase customized products, especially in the context of self-design services. Therefore, this study aims to fill this research gap by analyzing the individual driving factors that significantly influence purchase intention through brand experience and the intention to use customization toolkits. In addition to factors like innovation, variety seeking, prior experience, and product involvement, this research incorporates perceived ease of use, perceived control, and perceived enjoyment to deepen the understanding of what motivates individuals to engage with customization services. Conducted through a quantitative survey of 462 respondents�comprising sports players and customers who have purchased sportswear in Indonesia�the study employs the PLS-SEM method to test the model and hypotheses. The findings reveal that perceived ease of use, perceived enjoyment, and innovativeness are the most significant individual drivers of purchase intent through brand experience and intention to use customization toolkits. These factors account for 45.4% of the variance in brand experience, 50.6% in the intention to use customization toolkits, and 53.7% in purchase intention.

Keywords: �Renewable Energy, Gender Equality, Social Capital, Sumba.

This article is licensed under a Creative Commons Attribution-ShareAlike 4.0 International

INTRODUCTION

The development and modernization of culture is inevitable, which requires humans to continue to move and be busy with their respective activities. These activities are inseparable from the development of increasingly advanced science and technology (Richta, 2018). The rapid development of technology, coupled with the pandemic period that has changed work patterns and habits, allows us to do many things just by staying at home or without the need to change places. This phenomenon created a trend known as a sedentary lifestyle or physical inactivity, where most of the time is spent in a sitting or lying position. This has a significant impact on Health (Ministry of Health of the Republic of Indonesia, 2023). To avoid this, we must maintain a healthy lifestyle in terms of the food we consume and balance it with regular exercise (Cobb-Clark et al., 2014). professional sportsman. Based on the results of the Asia Pacific Health Inertia survey in 2021, the COVID-19 pandemic has increased public awareness of exercise and a healthy lifestyle. The survey also revealed that 64 per cent of consumers in Indonesia began to exercise more often during the pandemic (NAUFAL, 2021). In the post-pandemic era, in addition to a healthy lifestyle, online shopping habits are still a practical and affordable solution for the people of Indonesia. According to the Ministry of Industry of the Republic of Indonesia, a report states that e-commerce users in Indonesia in 2022 will reach 179 million, and in 2023, it is predicted to reach 196 million. Bank Indonesia also predicts that the value of Indonesia's e-commerce transactions by the end of 2023 can reach IDR 572 trillion (2023). The latest We Are Social report with Meltwater shows that at the beginning of 2023, the percentage of Indonesian consumers who made online shopping transactions reached 62.6 per cent, a jump of 3.3 per cent on an annual basis compared to January 2022.

The National Sports Development Index (2024) report states that participation in sports has a very strong relationship with the sports economy. The study showed that there are 56% or around 110.45 million people in Indonesia who spend their money on sports needs in the form of shopping for goods, such as buying shoes and clothes. It is estimated that the sports spending of the people of Indonesia reaches Rp 43.8 trillion per year. Spending on sporting goods is mostly in the form of sports shoes, which is 33.9%, followed by sportswear spending at 27.4%, and sports equipment spending at 13.2% (Cholik, et al., 2021). The percentage of types of sporting goods purchased by the people of Indonesia can be seen in Figure 1.

Figure 1. Types of Sporting Goods Purchased by the Public

Source: National Sport Development Index Report 2021 of the Ministry of Youth and Sports of the Republic of Indonesia

A survey of several samples of custom sportswear companies in Indonesia said that as a result of increasing sales and demand for custom designs, companies have obstacles because they have to serve the wishes of customers through personal conversations, and customers also feel dissatisfied because conversations are not immediately replied to while free time is not always appropriate, so the time needed in the production process is not always appropriate, also long. In several countries such as the United States, Europe, the United Kingdom, Switzerland, Italy, India, and America, the sale of custom jerseys and sportswear has adopted technology with a direct design feature that is done online� (virtual self design custom) through the website or applications. Customer engagement on a product has a significant positive impact on the customer experience with the brand, so customers who invest in product categories from custom product offerings are more likely to engage with the brand and take advantage of customization tools (Pallant et al., 2022). Previous research has also explained that customer experience in performing a behaviour can affect their satisfaction and translate into future loyalty and repetition of behaviour (Srivastava & Kaul, 2016).

Engaging in the customization process provides consumers with unique and memorable products and experiences that can deepen brand relationships and allow consumers to express their individual self-concept (Coelho et al., 2020), with technological advancements in recent years. This technology provides greater opportunities to facilitate brand interaction and build brand experience (Kumar & Kaushik, 2020). It's important to consider the relationship between consumers and brands, including the impact each customer has when considering brand experience. These considerations will make it easier to understand how important it is to improve the brand experience, as opposed to the innate characteristics of individual consumers that are more difficult to influence. Their involvement will more easily influence individual characteristics in the brand experience (Das et al., 2019).

In the previous study, a concept was made regarding the factors that encourage consumers to use customization toolkit and intend to purchase customized products based on factors in individual consumers (intrinsic) and brand value (extrinsic) (Trentin et al., 2014). In this study, the development of a previous research concept based on the problems that have been explained according to the conditions in Indonesia is carried out to deepen information about the influence of Individual Driver factors on Purchase Intention from Customize products through Brand Experiences and Intention to Use Customization Toolkit.

This research seeks to fill this gap by examining how brand experience influences consumer engagement in the context of custom products in Indonesia. Unlike previous studies that primarily focus on intrinsic factors driving customization toolkit usage, this study will explore the extrinsic factors, such as brand experience, that contribute to purchase intentions. By understanding the role of brand experience, companies offering custom products can better tailor their strategies to improve consumer satisfaction and engagement. Moreover, this research aims to provide practical insights that can help companies overcome the challenges of managing custom product demand and enhance their overall business performance.

RESEARCH METHODS

Based on the purpose of the study, this study uses causal descriptive methods with a quantitative approach. The research strategy is a survey using questionnaires from respondents.

Collection Techniques

The measurement scale uses a Likert scale of 1-5 (1 for strongly disagree and 5 for strongly agree). This study uses a non-probability sampling technique with purposive sampling because the selection of samples under deliberate conditions to samples that are relevant to this study, so that they can represent appropriate information. To determine the size of the sample, the authors applied the Cochran formula and used it to determine a confidence level of 95%, with a significance level of 5%. According to Indrawati (2015), the sample is the members of the population who are selected to be involved in the research, either to be observed, given treatment, or asked for their opinion on what is being studied. The questionnaire was distributed to respondents who had criteria, namely sports players and had bought custom sportswear products. The distribution of questionnaires is carried out through dissemination in sportswear companies or brands and sports communities in Indonesia. To determine the minimum number of samples using the Cochran formula, which is 385 respondents. In this study, a sample of 462 respondents was collected.

Data Analysis

The purpose of this study is to develop theories and make predictions on constructs, as well as analyze individual consumer driving factors for the intention to buy custom sportswear through brand experience and the intention to use the customization toolkit. In this study, modifications to the theoretical framework and variable indicators were carried out. The method used in this study is partial least square (PLS) which uses a variance-based technique in structural equation modeling (SEM) or called PLS-SEM. The data obtained from the respondents through questionnaires in this study was processed using SmartPLS 4.1.0.6 software

RESULT AND DISCUSSION

Measurement Model Evaluation

The measurement model can be assessed from the validity of convergence to determine the accuracy of each research item by testing the indicator of the factor loading (FL) value. An item is considered valid or acceptable with a minimum value of 0.50 and an ideal value of more than 0.70 (Hair et al., 2019), with a value category of 0.40 � 0.70 with a moderate correlation, a value of 0.70 � 0.90 with a high correlation, and 0.90 � 1.00 with a very high correlation (Indrawati, 2015). Then a test was carried out on the value of the AVE (Average Variance Extracted) indicator on convergent validity to find out whether a variable met the criteria considered valid or not. The AVE value that must be met in order for a variable to be said to have sufficient convergent validity is 0.50 (Indrawati, 2015).

Discriminant Validity is used to indicate whether the measurement results show that these variables are not highly correlated to be able to have discriminatory validity, by comparing each other variables. If the constructively predicted variables are not significantly correlated, then the model is considered to meet the criteria of discriminatory validity (Indrawati, 2015), which can be done with the Fornell-Larcker Criterion, Cross Loading, and Heterotrait-Monotrait (HTMT). The HTMT ratio represents the maximum value of each related variable with a value that must be less than 0.85 in order to be a detectable difference between two variables� Indrawati. Then to test reliability, Cronbach Alpha (CA) and Composite Reliability (CR) values. The minimum CA and CR score is 0.70 to be rated good enough. The following is table 1 of the evaluation of the measurement model:

Table 1.

Results of FL, AVE, CA, and CR.

Variable	Item	FL	AVE	CA	CR
Innovativeness	IN1	0,837	0,685	0,906	0,909
	IN2	0,790
	IN3	0,769
	IN5	0,712
Variety Seeking	VS1	0,852	0,606	0,784	0,796
	VS2	0,805
	VS4	0,810
Prior Experience	PE1	0,856	0,619	0,846	0,845
	PE2	0,829
	PE3	0,765
	PE4	0,874
	PE5	0,856
Product Involvement	PI1	0,858	0,625	0,796	0,804
	PI2	0,886
	PI4	0,782
Perceived Ease of Use	PU1	0,908	0,716	0,898	0,901
	PU2	0,841
	PU3	0,902
	PU4	0,705
	PU5	0,859
Perceived Control	PC1	0,787	0,716	0,867	0,915
	PC2	0,680
	PC3	0,822
	PC5	0,861
Perceived Enjoyment	PJ1	0,945	0,701	0,893	0,897
	PJ2	0,683
	PJ3	0,824
	PJ4	0,908
Intention to use customization toolkit	IU1	0,750	0,711	0,796	0,804
	IU2	0,738
	IU3	0,774
	IU4	0,827
	IU5	0,840
Brand experience	BE1	0,897	0,692	0,852	0,853
	BE2	0,909
	BE3	0,719
	BE4	0,822
	BE6	0,802
	BE9	0,803
Purchase intention	PN1	0,848	0,676	0,764	0,782
	PN2	0,814
	PN3	0,831
	PN4	0,835

Table 2.

Results Heterotrait-monotrait

	BE	IN	IU	PC	PU	PJ	ON	PI	PN	VS
BE
IN	0,607
IU	0,614	0,557
PC	0,469	0,492	0,614
PU	0,652	0,619	0,677	0,477
PJ	0,231	0,252	0,251	0,146	0,289
ON	0,656	0,712	0,699	0,561	0,775	0,235
PI	0,459	0,510	0,469	0,305	0,471	0,419	0,641
PN	0,598	0,591	0,706	0,555	0,654	0,294	0,768	0,464
VS	0,586	0,674	0,653	0,498	0,707	0,371	0,756	0,554	0,573

Figure 2. Outer Model Results

Structural Model Evaluation

Evaluation of the structural model can be acknowledged after the model is considered acceptable. The significance and prediction in hypothesis testing can be seen from the value of path coefficient and t-value (Kock, N., 2016). According to Kock (2016), the prediction and significance in hypothesis testing can be seen from the p-value. According to Kock (2016), with a confidence level of 95% (alpha %), one-tailed, t-statistical value >1.65 (used for direct influence), then H0 is rejected and H1 is accepted.

Indrawati (2015), said that the assessment of the internal model, also known as the structural model, uses the criteria of Path Coefficient and R-square. The path coefficient is considered significant if it has a t-value of at least 1.65 at a significance level of 5%, which is obtained through the bootstrap method. According to Malhotra (2018), an R-square value of 0.60 or higher, is preferred. Garson (2016) also said that the R-square results are 0.67 (strong), 0.33 (moderate), and 0.19 (weak). In addition, to measure the magnitude of the influence on the direct effect using F Square while measuring the magnitude of the mediation effect using the Upsilon (ν) value (Hair et al., 2019) Lachowicz et al., 2018). The interpretation of the values in the direct effect is 0.02 (low), 0.15 (moderate) and 0.35 (high) (Hair et al., 2019). Figure 4 shows the results of SmartPLS which shows the correlation and R-square values.

Table 3.

Hypothesis Test Results

Hypothesis	Hypothesis	*Path Coefficients*	*T-Statistics*	*P Values*
H1	IN �BE�IU�PN	0,068	1,967	0,025
H2	VS �BE�IU�PN	0,078	1,872	0,023
H3	PE �BE�IU�PN	0,235	1,690	0,041
H4	PI �BE�IU�PN	0,022	1,674	0,043
H5	PU �BE�IU�PN	0,177	2,145	0,016
H6	PC �BE�IU�PN	0,134	1,700	0,044
H7	PJ �BE�IU�PN	0,045	1,939	0,024
H8	IU�PN	0,214	4,471	0,000
H9	BE�PN	0,190	3,674	0,000

Table 4.

R-square and Q-square results

Variable	R2	Q2
Brand Experience	0,454	0,435
Intention to use customization toolkit	0,506	0,470
Purchase intention	0,537	0,488

Based on the results of hypothesis testing, the coefficient of the innovation pathway to purchase intention through brand experience and intention to use the customization toolkit was obtained at 0.068, indicating that the positive or unidirectional influence, meaning that the better the innovation, the brand experience, intention to use customization toolkit, and purchase intention the better. The influence of innovation on purchase intention through brand experience and intention to use the customization toolkit was significant, with a t-statistical value of 1.967 greater than the t-table or 1.967>1.65 and a p-value of 0.025 smaller than alpha 5% (0.05). Thus, H1 is accepted, meaning that the individual driver innovativeness factor has a positive and significant effect on purchase intention through brand experience and intention to use the customization toolkit.

The second hypothesis, Variety Seeking has a significant positive effect on brand experience, intention to use customization toolkit, and purchase intention of customized products with a coefficient value of 0.078 with a t-statistical value of 1.872. The results of the analysis show that variety seeking or individual consumer behavior in seeking variety has a positive impact on brand experience, providing opportunities and challenges in consumer experience when using customization toolkit services and processes in purchasing custom sports products it can be a consumer assessment in getting the right product and the intention to buy the product. This means that variation search behaviour also means that companies must continue to evolve and innovate in their offerings to attract variety seekers, who are likely to turn to other alternatives (Martenson, 2018).

The third hypothesis, Prior Experience has a significant positive effect on brand experience, intention to use customization toolkit, and purchase intention of customized products with a coefficient value of 0.235 with a t-statistical value of 1.690. Prior experience is still important to be considered as a driving factor because, according to Ajzen (2015) it is also said that the prior experience of consumers in buying customized products encourages repurchase intention, and future behaviour predicts future intentions.

Hypothesis Fourth, Product Involvement has a significant positive effect on brand experience, intention to use customization toolkit, and purchase intention of customized products with a coefficient value of 0.022 with a t-statistical value of 1.674. The results of the analysis show that product involvement is significant to purchase intention through brand experience and intention to use customization toolkit, but not significant if it is not influenced by brand experience, as said in the same study by Jessica (2022) that consumers who are highly involved in products that use the customization toolkit Just for hedonistic reasons rather than necessity, the relationship between brand experience and hedonistic benefits has been well known in the previous brand experience literature (Zollo et al., 2020).

The fifth hypothesis, Perceived ease of use has a significant positive effect on brand experience, intention to use customization toolkit, and purchase intention of customized products with a coefficient value of 0.177 with a t-statistical value of 2.145. This means that consumers need services or systems that are perceived to be easy to use, especially for systems that are new to use. Convenience, in this case, is the service facilities, and the quality of the website or application used is important to pay attention to. In accordance with the previous research reference which said that when consumers feel comfortable in using the facilities provided, it is positively related to satisfaction related to the intention to buy (Bons�n Ponte et al., 2015)

Hypothesis Sixth, Perceived Control has a significant positive effect on brand experience, intention to use customization toolkit, and purchase intention of customized products with a coefficient value of 0.134 with a t-statistical value of 1.700. The results of the study show that perceived control is proven to have a positive and significant effect, which means that consumers who are used to controlling or researching their products before buying, with virtual self-design customs, consumers participate directly in making appropriate products, so that consumers can reduce anxiety because customers get direct control. It is generally known that customers with high control needs experience anxiety caused by uncertainty and risks associated with services (Faqih, 2022).

Hypothesis Seventh, Perceived Enjoyment has a significant positive effect on brand experience, intention to use customization toolkit, and purchase intention of customized products with a coefficient value of 0.045 with a t-statistical value of 1.939. This means that virtual self-design custom can produce positive and effective process value assessment actualization, which will be a good sign to increase consumer satisfaction with the brand and intent to purchase customized products. By understanding the nature of the entertainment value of customization and promoting engaging experiences during the online process, success can be achieved because it entices consumers in a co-design experience, and mass customization significantly increases perceived enjoyment.

Hypothesis Eighth, Brand experience has a significant positive effect on the intention to use the customization toolkit and purchase intention of customized products with a coefficient value of 0.214 with a t-statistical value of 4.471. Then, the ninth hypothesis, the Intention to use a customization toolkit, has a significant positive effect on the purchase intention of customized products with a coefficient value of 0.190 and a t-statistical value of 3.674.

R-square values for variable brand experience is 0.454, which means individual factors drivers (innovativeness, variety seeking, prior experience, product involvement, perceived ease of use, perceived control, dan perceived enjoyment) affect brand experience by 45.4%. The R-square for the variable intention to use customization toolkit is 0.506, which means that the individual drivers factor (innovativeness, variety seeking, prior experience, product involvemnet, perceived ease of use, perceived control, dan perceived enjoyment) affecting the intention to use customization toolkit by 50.6%. The R-square for variable purchase intention is 0.537, which means the individual drivers factor (innovativeness, variety seeking, prior experience, product involvement, perceived ease of use, perceived control, dan perceived enjoyment) had an effect on purchase intention by 53.7%.

CONCLUSION

The individual driver factors that venjoyment, and innovativeness. All the proposed hypotheses are supported by previous research. However, based on the R-squared value, individual driver factors have the strongest influence on purchase intention, while their effect on brand experience is comparatively weaker. This may be attributed to the limited exposure of Indonesian consumers to purchasing custom sportswear using a customization toolkit. Recent studies from the last five years highlight the growing importance of customization technology in enhancing brand experience, which suggests that more research is needed to explore this in the Indonesian context.

1. Managerial Implication

The research findings indicate that consumers' perceptions of ease and enjoyment in the process of buying custom sportswear via a customization toolkit are crucial. Therefore, companies should focus on developing engaging and educational marketing content that highlights the benefits of using this toolkit. This content is essential as it influences consumer decisions regarding brand selection, toolkit usage, and eventual purchase. Given the increasing adoption of customization technology, marketing strategies must reflect this trend to boost consumer interest and engagement. Recent studies also emphasize that marketing initiatives are a key factor driving consumer interest in brands, particularly in tech-enhanced shopping environments.

2. Advice for Companies

Innovativeness, variety-seeking behavior, prior experience, product involvement, perceived ease of use, perceived control, and perceived enjoyment are the primary individual drivers that positively and significantly impact purchase intention through brand experience and the intention to use a customization toolkit. Companies should focus on enhancing the quality of both content and services to better meet consumer needs. In Indonesia, where the use of custom virtual self-design remains limited, companies have a unique opportunity to educate the market and promote products tailored to consumer preferences. By making the process of purchasing custom sportswear more enjoyable and less anxiety-inducing, companies can increase consumer adoption. The growing global trend of virtual self-design for custom products, as evidenced by recent research, suggests that implementing this technology can accelerate the product manufacturing process and drive higher sales in the sportswear sector.

3. Suggestions for Further Research

At the time this research was conducted, no custom sportswear company in Indonesia offered virtual self-design services, limiting consumer awareness of this purchasing process. Future studies should focus on assessing consumer satisfaction with custom virtual self-design compared to traditional, manual methods involving direct interaction between buyers and sellers. Additionally, this study only examined the interest in purchasing custom sportswear in select regions of Indonesia, particularly Java. Expanding the research to other regions or countries could yield more comprehensive results, as recent studies have demonstrated that regional differences significantly impact consumer behavior towards customization technology.

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Copyright holders:

Indrawati, Shafira Damayanti (2024)

First publication right:

AJEMB � American Journal of Economic and Management Business