The Effect of Digital Marketing Strategy, Brand Trust, and Customer Expectations on Online Purchasing Decisions on E-Commerce in West Java

This study investigates the impact of digital marketing strategy, brand trust, and customer expectations on online purchase decisions in the e-commerce sector in West Java, Indonesia. Through quantitative analysis involving 145 respondents, data was collected using a structured questionnaire to measure the specified constructs. Structural Equation Modeling (SEM) with Partial Least Squares (PLS) was used to analyse the relationships between variables. Drawing upon theoretical frameworks and empirical evidence, hypotheses are formulated to investigate the relationships between digital marketing strategy, brand trust, customer expectations, and online purchasing decisions. The findings contribute to a deeper understanding of consumer behaviour in digital marketplaces and offer actionable insights for businesses aiming to optimise their marketing strategies and increase consumer engagement in the e-commerce sector in West Java.


INTRODUCTION
The exponential growth of technology has revolutionized consumer behavior and reshaped traditional modes of commerce.The advent of e-commerce platforms has provided consumers with unparalleled convenience, enabling them to browse, select, and purchase products or services easily, irrespective of geographical constraints.This trend is evident in Indonesia, where the province of West Java serves as a prominent hub for e-commerce activities.The digital transformation sweeping across the nation is reflected in the increasing adoption of e-commerce in West Java [1], [2].
The e-commerce sector in Indonesia has experienced rapid growth in recent years, fuelled by several factors such as increased internet penetration, smart phone adoption, and evolving consumer preferences [3].The growth of e-commerce in Indonesia is significant especially in West Java, the most populous province in Indonesia [4].West Java's diverse demographic profile and dynamic socio-economic landscape present both opportunities and challenges for businesses looking to capitalise on the digital market [5].The province's major urban centres, such as Bandung and Jakarta, provide a large and diverse consumer base for e-commerce players [6].However, businesses operating in West Java need to consider factors such as website design quality, trust in online shopping, and website security to improve user-friendliness and increase consumer trust and adoption [7].Policymakers should also focus on improving e-commerce infrastructure and raising awareness about the benefits of online shopping to further encourage adoption among Indonesian consumers.
Understanding the determinants of online purchasing behavior is crucial for businesses operating in West Java's e-commerce ecosystem.In a competitive environment with evolving consumer expectations, firms need to comprehend consumer decision-making processes to develop effective marketing strategies and gain a competitive edge.Research studies have identified several factors that influence online consumer behavior, including trust, product variety, convenience, privacy, perceived usefulness, perceived risk, attitude, perceived ease of use, social influence, subjective norms, perceived enjoyment, security, web design quality, and demographic factors.
These factors significantly affect online consumer behavior and should be considered by businesses to sustain and achieve success in the dynamic world of e-commerce [8]- [12].
The primary aim of this study is to quantitatively analyze the effect of digital marketing strategy, brand trust, and customer expectations on online purchasing decisions in West Java's ecommerce sector.To achieve this aim, the study will pursue several objectives, including assessing the impact of digital marketing strategies on consumer purchasing decisions, evaluating the relationship between brand trust and online purchasing behavior, analyzing how customer expectations influence online shopping decisions, and determining the combined effect of digital marketing strategy, brand trust, and customer expectations on online purchasing decisions in West Java.Through addressing these objectives, this research aims to provide valuable insights for both academic scholarship and practical implications for businesses operating in the dynamic ecommerce market of West Java.

Digital Marketing Strategy and Online Purchasing Decisions
Digital marketing strategy encompasses a multitude of techniques aimed at promoting products or services through various digital channels, including but not limited to social media, search engines, email marketing, and content creation [13]- [16].
The advent of digital technologies has transformed the way businesses engage with consumers, offering unprecedented opportunities for targeted advertising, personalized communication, and data-driven marketing campaigns.
Several studies have underscored the significant influence of digital marketing strategies on consumer purchasing decisions in the e-commerce domain.For instance, [17] found that personalized advertisements and social media engagement positively impact consumer behavior by increasing brand awareness, fostering engagement, and building trust.Similarly, effective content marketing strategies have been shown to enhance customer engagement and drive conversions in the online sphere [18], [19].
In the context of West Java's e-commerce landscape, the effectiveness of digital marketing strategies may be influenced by factors such as technological infrastructure, internet penetration rates, and cultural preferences.Thus, understanding how various digital marketing channels and techniques resonate with consumers in West Java is crucial for businesses seeking to optimize their marketing efforts and drive online sales.

Brand Trust and Online Purchasing Decisions
Brand trust plays a pivotal role in shaping consumers' attitudes and behaviors towards e-commerce brands.Trustworthy brands are perceived as reliable, credible, and transparent, thereby mitigating the perceived risks associated with online transactions [20]- [22].Establishing and maintaining trust is imperative for e-commerce businesses to foster long-term relationships with customers and cultivate brand loyalty.
Research suggests that brand trust significantly influences consumers' online purchasing decisions.[23], [24] found that consumers are more likely to make purchases from brands they trust, even if alternative options are available.Factors such as brand reputation, product quality, and customer service contribute to building and sustaining trust in e-commerce contexts.
In West Java, where consumers may exhibit distinct cultural preferences and trust dynamics, understanding the nuances of brand trust is essential for e-commerce businesses seeking to establish a foothold in the market.By prioritizing transparency, reliability, and customer-centricity, brands can engender trust among consumers and differentiate themselves in a competitive marketplace.

Customer Expectations and Online Purchasing Decisions
Customer expectations encompass the anticipated benefits, experiences, and outcomes that consumers associate with a particular brand or product.Meeting or exceeding customer expectations is paramount for fostering satisfaction, loyalty, and repeat purchase behavior in the e-commerce real [25]- [27].E-commerce businesses must align their offerings, services, and marketing strategies with customer expectations to deliver value and enhance the overall shopping experience.
Studies have shown that customer expectations significantly influence online purchasing decisions.[27], [28] demonstrated that consumers are more likely to make repeat purchases from brands that consistently meet or exceed their expectations in terms of product quality, delivery speed, and customer service.Furthermore, aligning marketing messages and promotions with customer preferences can enhance perceived value and drive purchase intent [28].
In West Java's e-commerce market, where consumer preferences and expectations may vary across demographic segments and socio-cultural contexts, businesses must employ a nuanced understanding of customer expectations to tailor their offerings and marketing strategies effectively.By anticipating and addressing the evolving needs and preferences of consumers, e-commerce brands can foster trust, loyalty, and long-term relationships with their target audience.

Conceptual Framework
Based on the synthesized literature, the conceptual framework that underpins this study, illustrates the hypothesized relationships between digital marketing strategy, brand trust, customer expectations, and online purchasing decisions in the context of ecommerce in West Java, Indonesia.H1: There is a significant positive relationship between brand trust and online purchasing decisions among consumers in West Java, Indonesia.H2: There is a significant positive relationship between customer expectations and online purchasing decisions among consumers in West Java, Indonesia.
H3: There is a significant positive relationship between digital marketing strategy and online purchasing decisions among consumers in West Java, Indonesia.

Research Design
This study adopts a quantitative research approach to empirically analyze the relationships between digital marketing strategy, brand trust, customer expectations, and online purchasing decisions.Specifically, a cross-sectional survey design is utilized to collect primary data from ecommerce consumers in West Java.

Sampling
The target population for this study comprises individuals who have engaged in online shopping through e-commerce platforms in West Java.A convenience sampling technique is employed to select respondents due to its practicality and accessibility.A sample size of 145 respondents is deemed sufficient to achieve an acceptable level of statistical power for the analysis.

Data Collection
Primary data is collected through structured questionnaires administered electronically to the identified sample of e-commerce consumers in West Java.The questionnaire is designed to capture relevant information on respondents' demographics, online shopping behavior, perceptions of digital marketing strategies, brand trust, customer expectations, and online purchasing decisions.

Variables and Measures
The following variables are operationalized and measured in this study: 1) Digital Marketing Strategy: Assessed using items related to the frequency, effectiveness, and perceived impact of various digital marketing channels and techniques employed by e-commerce platforms (e.g., social media marketing, email marketing, search engine optimization).2) Brand Trust: Measured using validated scales examining consumers' perceptions of brand reliability, credibility, transparency, and overall trustworthiness.Items include statements such as "I trust this e-commerce brand to deliver high-quality products/services" and "I believe this e-commerce brand is honest and transparent in its dealings."3) Customer Expectations: Gauged through items assessing consumers' anticipated benefits, service quality, delivery expectations, and overall satisfaction with ecommerce brands.Statements include "I expect timely and reliable delivery of products/services from this e-commerce brand" and "I anticipate a positive overall experience when interacting with this e-commerce brand."4) Online Purchasing Decisions: Operationalized based on respondents' reported frequency of online purchases, average transaction value, satisfaction with past purchases, and likelihood of future purchases from the e-commerce platform under study.

Data Analysis
The collected data will undergo analysis utilizing Structural Equation Modeling (SEM) with Partial Least Squares (PLS) 3 software, a robust multivariate statistical technique ideal for exploring intricate relationships among multiple variables pertinent to this study.The analytical process will encompass several steps: firstly, data preprocessing will ensure completeness, accuracy, and consistency through techniques like imputation or deletion for any missing or erroneous data.Next, the reliability and validity of the measurement model will be scrutinized, evaluating internal consistency, convergent validity, and discriminant validity.Following this, the structural relationships between latent constructs and the dependent variable will be examined using SEM-PLS, assessing the strength and significance of path coefficients to delineate direct and indirect effects.Model fit will be evaluated using various indices, and hypothesis testing will be conducted through bootstrapping techniques to ascertain the significance of relationships.Finally, the findings will be interpreted and discussed within the context of research objectives, theoretical framework, and existing literature, offering insights for both theory and practice and identifying avenues future research [29].

Demographic Characteristics
The sample population consisted of 145 respondents from various demographic backgrounds.The following demographic variables were analyzed.The sample population comprised 145 respondents from diverse demographic backgrounds, with demographic variables analyzed including age, gender, education level, income level, and occupation.The respondents' ages ranged from 18 to 60 years, with a mean of 32.5 years and a standard deviation of 8.7 years.Gender distribution was approximately equal, with 53% male and 47% female respondents.In terms of education, the majority (65%) held a bachelor's degree, followed by 20% with a master's degree, and 15% with a high school diploma or equivalent.Income levels varied, with 40% reporting annual incomes of less than $20,000, 35% between $20,000 and $40,000, and 25% above $40,000.Occupationally, respondents represented diverse backgrounds, including professionals (40%), students (25%), homemakers (20%), and others (15%).

Measurement Model
The measurement model assessment provides crucial insights into the reliability and validity of the measurement instruments used to operationalize the constructs of digital marketing strategy, brand trust, customer expectations, and online purchasing decisions.Here, we discuss the loading factors, Cronbach's alpha coefficients, composite reliability, and average variance extracted for each construct.The evaluation of the measurement model reveals robust reliability and validity for the constructs of digital marketing strategy, brand trust, customer expectations, and online purchasing decisions.Strong loading factors ranging from 0.752 to 0.965, high Cronbach's alpha coefficients ranging from 0.836 to 0.898, composite reliability values ranging from 0.902 to 0.931, and average variance extracted values exceeding the recommended threshold of 0.5, signify satisfactory convergent validity.These results affirm the strong associations between observed variables and latent constructs.The comprehensive assessment underscores the credibility and consistency of the measurement instruments, augmenting the confidence in the study's findings and conclusions.

Discriminant Validity
Discriminant validity assesses the extent to which constructs in a research model are distinct from one another.This is crucial to ensure that the measurement model accurately captures the unique variance associated with each construct.The values provided represent the square root of the Average Variance Extracted (AVE) for each construct on the diagonal and the correlations between constructs off-diagonal.The examination of discriminant validity for brand trust, customer expectations, digital marketing strategy, and online purchasing decisions reveals compelling evidence.The square roots of the Average Variance Extracted (AVE) for each construct -0.904 for brand trust, 0.873 for customer expectations, 0.886 for digital marketing strategy, and 0.868 for online purchasing decisions -exceed the correlations between these constructs, demonstrating their distinctiveness.Specifically, all correlations between brand trust, customer expectations, digital marketing strategy, and online purchasing decisions are below their respective AVE square roots, reinforcing their discriminant validity.These findings affirm the distinct conceptual domains of each construct, bolstering the credibility of their measurement and supporting their individual contributions to the research framework.The assessment of model fit using various indices yields favorable results, indicating a strong alignment between the proposed model and the observed data.The Standardized Root Mean Square Residual (SRMR), measuring the absolute standardized residual covariance between observed and model-implied covariance matrices, stands at 0.054 for both saturated and estimated models, indicating a good fit.Similarly, the Unweighted Least Squares Discrepancy (d_ULS) and Growth Function Discrepancy (d_G) values, assessing the discrepancy between observed and model-implied covariance matrices and growth functions respectively, are 0.225 and 0.216, affirming a satisfactory fit.The Chi-Square statistic, indicating differences between observed and model-implied covariance matrices, yields a non-significant p-value, corroborating a well-fitted model.Additionally, the Normed Fit Index (NFI) underscores model adequacy, with a value of 0.813 for both models, indicating substantial improvement over the null model.These findings collectively suggest that the proposed model effectively captures the underlying relationships among constructs, providing a robust representation of the data.The R Square and Q2 values provide insights into the explanatory power and predictive relevance of the model concerning online purchasing decisions.The R Square value of 0.292 indicates that approximately 29.2% of the variance in online purchasing decisions is elucidated by digital marketing strategy, brand trust, and customer expectations as specified in the model, suggesting a moderate level of explanatory capacity.This implies that these factors collectively contribute to explaining a considerable portion of the variability observed in online purchasing decisions among respondents in the sample.Similarly, the Q2 value of 0.277 signifies that around 27.7% of the variance in online purchasing decisions can be predicted by the model, highlighting its substantial predictive relevance.This underscores that digital marketing strategy, brand trust, and customer expectations serve as meaningful predictors of online purchasing decisions within the e-commerce landscape of West Java, Indonesia, emphasizing their importance in influencing consumer behavior in online shopping contexts.

Hypothesis Testing
Hypothesis testing involves evaluating the statistical significance of the relationships between independent variables (such as brand trust, customer expectations, and digital marketing strategy) and the dependent variable (online purchasing decisions).This is typically done using tstatistics and p-values derived from the sample data.Below, we discuss the results of hypothesis testing for each hypothesis: The results of hypothesis testing underscore the significance of the relationships between brand trust, customer expectations, digital marketing strategy, and online purchasing decisions in West Java's e-commerce sector.With t-statistics ranging from 4.782 to 8.105 and p-values of 0.000 for all three relationships, strong evidence against the null hypothesis is provided, indicating statistically significant effects.Consequently, brand trust, customer expectations, and digital marketing strategy are found to exert significant positive influences on online purchasing decisions.These findings not only validate the theoretical framework but also emphasize the pivotal roles of brand trust, customer expectations, and digital marketing strategies in shaping consumer behavior within the competitive e-commerce environment of West Java, Indonesia.Therefore, fostering brand trust, meeting customer expectations, and deploying effective digital marketing strategies are imperative strategies for enhancing online sales and bolstering consumer engagement in the region's dynamic e-commerce landscape.

Discussion
The discussion chapter serves as the interpretative component of the research, where the findings from the analysis are synthesized, contextualized, and compared with existing literature.In this chapter, we delve deeper into the implications of the results obtained from the statistical analysis of the original sample, focusing on the relationships between brand trust, customer expectations, digital marketing strategy, and online purchasing decisions.
The significant positive correlation between brand trust and online purchasing decisions, supported by a t-statistic of 8.105 and a p-value of 0.000, highlights the pivotal role of brand trust in shaping consumer behavior within e-commerce.The consistency between the original sample mean (O) and the sample mean (M) further validates the robustness of this relationship, indicating its substantive rather than statistical significance.This finding resonates with existing research, emphasizing the criticality of brand trust in assuaging consumer concerns, enhancing confidence, and ultimately driving online purchase intentions and behaviors [30]- [32].
The statistically significant association between customer expectations and online purchasing decisions, as indicated by a t-statistic of 4.782 and a p-value of 0.000, underscores the profound impact of consumer expectations on e-commerce transactions.Despite a marginal deviation between the original sample mean (O) and the sample mean (M), the persistent statistical significance reaffirms the reliability of this relationship.This underscores the imperative for businesses to comprehend and fulfill customer expectations to bolster satisfaction and foster repeat purchases in the fiercely competitive e-commerce arena [33]- [35].
The statistically significant correlation between digital marketing strategy and online purchasing decisions, underscored by a t-statistic of 6.222 and a p-value of 0.000, accentuates the influential role of digital marketing in shaping consumer behavior within e-commerce platforms.Although a minor disparity exists between the original sample mean (O) and the sample mean (M), the enduring robustness of this relationship signifies its credibility.This underscores the imperative for businesses to employ effective digital marketing strategies to heighten brand visibility, engage consumers, and ultimately sway their online purchasing decisions, thereby enhancing [36], [37].

Implications and Future Research
1) The findings of this study have important implications for practitioners and policymakers in the e-commerce sector, highlighting the significance of building brand trust, meeting customer expectations, and implementing effective digital marketing strategies.2) Future research could explore additional factors influencing online purchasing decisions, such as website usability, social influence, and cultural differences, to provide a more comprehensive understanding of consumer behavior in e-commerce.
3) Additionally, longitudinal studies could be conducted to examine the dynamics of these relationships over time and assess their long-term impact on consumer behavior and business performance.

CONCLUSION
In conclusion, this study provides valuable insights into the factors shaping online purchasing decisions in the e-commerce landscape of West Java, Indonesia.The analysis reveals significant relationships between digital marketing strategy, brand trust, customer expectations, and online purchasing decisions, highlighting their interconnectedness and importance in influencing consumer behavior.Specifically, brand trust emerges as a key determinant of online purchasing decisions, underscoring the importance of building consumer confidence and credibility in the digital marketplace.Moreover, the study emphasizes the need for businesses to align their marketing strategies with evolving consumer expectations and leverage digital channels effectively to enhance brand visibility and engagement.By understanding and addressing these factors, businesses can foster positive online shopping experiences, drive customer loyalty, and ultimately achieve success in the competitive e-commerce environment.Moving forward, further research is warranted to explore additional factors impacting consumer behavior and to validate the findings across diverse geographical and cultural contexts.

Table 2 .
Measurement Model

Table 3 .
Model Fit Results Test