Opportunities and challenges in digital marketing for enterprises in vietnam a consumer behavior study

INTRODUCTION

Introduction

The rise of internet usage among consumers across multiple devices has created both opportunities and challenges in digital marketing, making the understanding of online consumer behavior essential for businesses (Pomirleanu et al., 2013) In today's competitive and globalized online marketplaces, it is vital to redefine the factors influencing decision-making, considering the unique aspects of online purchasing compared to traditional offline behaviors As e-commerce continues to expand rapidly, particularly in Vietnam, businesses must find ways to leverage these opportunities while addressing the challenges presented by this dynamic online environment.

This research explores online customer buying behavior in Vietnam to identify opportunities and challenges for Small and Medium Sized Enterprises (SMEs) The study aims to uncover critical factors influencing actual online purchases, using purchase intention, hedonism, influencing factors, online sales strategy, and utilitarianism as independent variables Data was gathered through an ad-hoc questionnaire, and empirical analysis will lead to recommendations designed to enhance online purchasing behavior, ultimately improving the online performance of SMEs in Vietnam.

This research is structured as follows: Chapter 1 introduces the study, while Chapter 2 reviews relevant literature to identify key factors influencing online consumer purchases Chapter 3 details the research methodology, including data collection techniques Chapter 4 presents and visualizes empirical findings through a structural equation model The study concludes with practical recommendations.

11 for SMEs in Vietnam are proposed in the light of increasing the online actual purchase and ultimately their online performance.

Problem Statement

From the global perspectives, there are many controversial views by previous researchers (Bucko et al, 2018 and Deng, 2021) arguing over the factors impacting on consumer’s purchasing intentions and decisions

Previous global researchers (Kumar, 2022 and Brown, 2021) also argued about the challenges of SMEs in adopting digital marketing

According to Ms Hawley, managing director of Nielsen, the Covid-19 outbreak has significantly disrupted the lives of billions globally, including those in Vietnam As a result, Vietnamese consumers have altered their buying attitudes, expectations, and behaviors.

During the pandemic, 76% of consumers focused on purchasing hygiene products, while 22% canceled their travel plans Additionally, 63% opted to cook and eat at home Notably, around 64% of Vietnamese consumers expressed their intention to continue utilizing food delivery services and online shopping even after the pandemic subsides.

According to Mediaradar.com (2021), shopping behaviors have permanently shifted, with consumers preferring online orders for better prices, faster delivery, and sustainability This trend presents a significant opportunity for digital marketing, particularly as online shopping continues to rise in Vietnam (Pham, Do, and Ha, 2020).

Digital retail competition is intensifying as companies develop their own eCommerce platforms and omnichannel advertising services However, SMEs in Vietnam encounter significant challenges in the online retail market, including limited budgets, inadequate content creation skills, difficulties in generating quality leads, and a struggle to enhance visibility.

Research is essential to understand Vietnamese online consumer behavior, including the factors influencing their purchasing decisions and the challenges faced by SMEs in digital marketing to succeed in the competitive landscape.

The researchers will provide actionable recommendations for SMEs in Vietnam to improve their online performance and effectively address challenges in digital marketing.

Research Aims & Objectives

This study evaluates the opportunities and challenges faced by SMEs in Vietnam regarding online consumer purchasing behavior, with the goal of developing effective online strategies and policies to improve the online performance of these businesses in the region.

 Unfolding which elements are crucial in the online consumer behavior in Vietnam, which might lead the Purchase Intention and ultimately the Actual Purchase

 Identify the opportunities and challenges faced by the SMEs in Vietnam in digital marketing

 Provide recommendations to SMEs in Vietnam to enhance their digital marketing strategies

 Provide recommendations to SMEs in Vietnam to overcome their challenges in digital marketing.

Research Scope

This study examines the opportunities and challenges of digital marketing for SMEs in Vietnam, focusing on the online shopping behaviors of young Vietnamese consumers aged 18 to 41 It analyzes key factors such as Purchase Intention, Unitarianism, Hedonism, types of products purchased, online sales channel strategies, and various influencing factors The research includes diverse groups based on academic levels, job statuses, and monthly incomes to provide a comprehensive understanding of consumer behavior in this demographic.

Theoretical Framework

Based on the thesis and anti-theses from the review of literature, the research framework for this research is presented as follows:

Paradigm of Study

The study's framework is illustrated in the accompanying chart, which highlights the demographic data of respondents Key input variables include gender, age, highest level of education, employment status, and monthly income, all of which are essential for the analysis conducted in this research.

Independent variables (IVs) include Purchase Intention, Unitarianism,

This article explores the relationship between hedonism, product types, online sales channel strategies, and influencing factors that affect actual purchasing behavior A comprehensive analysis of these variables will be provided in Chapter 3, which focuses on Methodology and Data Analysis Additionally, the empirical model will undergo rigorous testing to ensure its reliability and validity.

Figure 1.2: Paradigm of the Study

The output of this paradigm is the actual purchase, highlighting the impact of identified variables on both purchasing intention and actual buying behavior Online consumer behavior presents both opportunities and challenges for SMEs in Vietnam's digital marketing landscape This article will provide actionable recommendations aimed at improving the digital marketing strategies of SMEs.

Significance of Research

Previous research has explored digital marketing among SMEs in various Asian countries (Weforum.org, 2022; Yoshino and Taghizadeh-Hesary, 2016), but this study appears to be the first focused specifically on Vietnamese SMEs and their engagement with local consumers This research could pave the way for future studies in this area.

This research highlights key factors influencing actual purchases and explores the opportunities and challenges faced by SMEs in Vietnam's digital marketing landscape It offers recommendations for enhancing online performance and overcoming digital marketing obstacles, providing valuable insights and statistical evidence for future researchers interested in this field.

Furthermore, this study helps academically to ascertain the relevance and confirmation of theories and concepts related to digital marketing and online shopping based on previous researchers published works

This study highlights the key age and income demographics that significantly influence purchasing decisions in Vietnam, while also identifying critical factors that affect both purchasing intentions and actual purchases Furthermore, it addresses the challenges that small and medium-sized enterprises (SMEs) encounter in the realm of digital marketing.

This study offers essential recommendations for SMEs, serving as a valuable guide for digital marketing practitioners and managers in crafting effective digital marketing strategies informed by the study's findings.

Summary of Chapter 1

This article explores the opportunities and challenges of Digital Marketing for Small and Medium Sized Enterprises (SMEs) in Vietnam, providing a comprehensive overview of the research framework, problem statement, aims, and objectives The primary focus is on understanding online customer behaviors that drive purchase intentions and actual purchases, with a particular emphasis on identifying critical factors such as hedonism, influencing factors, online sales strategies, and utilitarianism The significance of this research is underscored by the rapid growth of e-commerce in Vietnam, highlighting the need for SMEs to recognize and leverage these factors to navigate the online marketplace effectively Ultimately, the study aims to inform strategies and policies that enhance SME performance in the evolving digital landscape.

LITERATURE REVIEW

Theoretical Conceptualization

2.1.1 SMEs and Its Growth Under Digital Economy

Small and medium enterprises (SMEs) are defined differently across countries based on various criteria, including sales, assets, capital, and number of employees.

In Vietnam, small and medium enterprises (SMEs) are defined by Degree No 80/2021/NĐ-CP (2021) as businesses with fewer than 100 employees or less than 200 employees, and those with annual sales revenues of less than 100 million or 300 million Vietnam Dong, respectively.

Small and medium-sized enterprises (SMEs) play a crucial role in economic development by creating jobs and reducing unemployment, allowing for workforce re-engagement during economic recovery (Michael, 2014) They contribute to economic stability and growth by leveraging low investment capital and a plentiful labor force, resulting in a diverse range of products that meet consumer needs and stimulate consumption (OECD, 2014) Additionally, SMEs utilize local resources, promoting economic restructuring, especially in remote areas where large enterprises are scarce (OECD, 2014) Furthermore, the presence of SMEs fosters a dynamic economy, enabling adaptability to market fluctuations and alignment with global economic trends (Kurma, 2022).

Nowadays, under the light of digital technology advances, SMEs have further opportunities to grow and expand outside their local environment (Ruzzier et al.,

2006) Using the internet, SMEs are now able to reach internationally (Buttriss & Wilkinson, 2003) with much less market borders and obstacles The power of digital

Information technology has significantly enhanced global business operations by fostering greater creativity (Lewis & Cockrill, 2002) As a result, more than half of rapidly growing SMEs are embracing digital transformation, as reported by SAP (2016).

2.1.2 Digital Marketing: Opportunities and Challenges

 The Technology-Based Evolutionary Process of Digital Marketing

With the evolution of technologies, such as email, social media, mobile phone, a more interactive environment and content creation by users was enable

Figure 2.1 highlights the use of social media worldwide between 2019 and

In 2024, social media users are expected to surpass nearly 3 billion, reflecting significant growth since 2019, with over 80% of these users actively engaging on various platforms.

Figure 2.1: Social Network Users Worldwide between 2019 and 2024 (in billions,

% change, and % of internet users) (Source: Insider Intelligence 2021)

Figure 2.2 shows the exponential adoption of smartphone between 2012 and

In 2012, the number of smartphone users exceeded 1 billion, and projections indicate that this figure will surpass 3 billion by 2021 This significant growth underscores the importance for businesses to prioritize the development of innovative strategies in social media and mobile marketing, as these factors play a crucial role in influencing customer behavior and decision-making processes.

Figure 2.2: Number of smartphone users worldwide from 2012 to 2021 (in billions) (Source: Statista, 2021)

In the midst of a technological revolution, Digital Marketing is evolving and adapting through innovative strategies and policies to leverage new opportunities presented by digital tools Today, marketers employ a multichannel strategy to promote their products and brands across various virtual platforms A global survey conducted in 2016 with 275 marketing professionals identified the most challenging and effective tactics in Digital Marketing, as illustrated in Figure 2.3.

Figure 2.3: Preferred Internet Market Approach in 2016 (Source: Bala and

Email and website marketing emerge as the most effective and easiest tactics to implement, while mobile marketing campaigns and social media marketing are identified as the most challenging strategies in comparison.

The rise of social media and smartphone usage has made it increasingly challenging for marketers to capture and retain customer attention amidst the overwhelming noise in advertising As a result, marketers must enhance their skills and strategies to effectively leverage these powerful digital marketing tools and maximize their potential.

In 2017, various digital marketing activities significantly influenced commercial success, with Content Marketing Communities and Big Data management leading the way Following these, Marketing Automation, Mobile Marketing, and Social Media also played important roles in enhancing business performance.

Figure 2.4: Digital Marketing Commercial Impact in 2017 (Source: Bala and

The evolution of Digital Marketing is closely linked to the digital transformation driven by the Internet, websites, cookies, social media, and mobile technology These advancements have led to the development of new strategies that enable businesses to gain deeper insights into customer habits, needs, and preferences, allowing for the creation of customized products for target markets Looking ahead, the technological evolution of Digital Marketing will continue to progress with innovations in Artificial Intelligence, Machine Learning, Big Data management, and Marketing Automation Currently, researchers and practitioners are concentrating on enhancing Digital Marketing Intelligence through these technologies to effectively analyze and predict consumer behavior patterns.

20 customer behaviours, which enable personalized and one-to-one Digital Marketing enhancing customer satisfaction and sales

 Impacts of Covid-19 Upon Consumer Behavior and a Shift Towards E- Commerce

Research by McKinsey & Company (2020) indicates that COVID-19 is transforming consumer behavior in various aspects of life, leading to significant trends such as increased online activity, a growing preference for digital entertainment, changes in media consumption habits, a surge in e-commerce, a heightened focus on trusted brands, and a decrease in shopping frequency.

Nielsen report (2020) shows that Vietnamese people have changed their daily media habits due to Covid-19, with 40% of Vietnamese spending more time watching

Vietnamese consumers are increasingly shifting their habits, with 35% dedicating more time to online content and over 50% visiting supermarkets less frequently Additionally, 25% have ramped up their online shopping activities This trend highlights a significant opportunity for marketers to enhance their digital strategies and establish a stronger online presence On average, Vietnamese individuals spend 6 hours and 42 minutes daily on the Internet, particularly among young urban consumers who are well-versed in digital technology and lead busy lifestyles, making them more receptive to e-commerce (Deloitte, 2020)

Deloitte's research reveals a significant shift in consumer buying behavior in Vietnam due to the Covid-19 pandemic, which has introduced e-commerce to many previously uninterested shoppers The convenience of online shopping, free from face mask requirements and social distancing, has led to a notable increase in spending For instance, after the outbreak, Vietnamese consumers on Shopee's platform increased their shopping time by over 25%.

The Vietnam E-commerce Association reports that due to shifts in consumer habits triggered by the pandemic, the country's e-commerce market is projected to experience a 30% growth this year, sustaining its upward trajectory.

Online Consumer Behavior Influencing Factors

Several key factors influence online consumer behavior, including demographic and social factors, the online shopping experience, internet and computer literacy, website design, and social media presence Additionally, situational factors, facilitating conditions, product characteristics, sales promotions, payment options, delivery services, and after-sales support are crucial in shaping online shopping decisions (Pandey et al., 2019) Other significant elements impacting consumers' purchase intentions include switching costs, marketing content, types of digital devices, online advertising methods, and the balance between hedonistic and utilitarian motivations (Kumar, R., 2022; Angell, A., 2020).

Demographic factors include variables such as race, age, income, marital status, and educational achievement, among others (Igiglobal.com., 2022) Demographic factors have a significant influence on buying behavior (Bhattacharjee et al., 2019)

Research by Pascual-Miguel et al (2015) indicates that women view online shopping as riskier compared to men, while Bhattacharjee et al (2019) discovered that younger consumers tend to allocate more of their spending on lifestyle, entertainment, and fashion items, in contrast to older shoppers who primarily invest in health-related products.

However, a study conducted by Chahal (2015) revealed that the perception of online shoppers is independent of their age and gender but not independent of their education and income

Demographic factors significantly impact buying behavior, enabling online businesses to efficiently categorize their products and services while developing effective marketing strategies and market segmentation (Bhattacharjee & Chetty, 2019).

Social influence plays a crucial role in consumer behavior, as individuals often perceive others to possess greater knowledge about brands or products This belief leads them to rely on the insights of others to make informed purchasing decisions.

Social influence primarily stems from reference groups, including social circles, work teams, family, and close friends Additionally, opinion leaders and aspirational reference groups play a significant role, as consumers often look up to these popular and well-known figures for guidance and inspiration.

Online consumer behavior is significantly influenced by word-of-mouth (WOM) within virtual groups, with positive electronic word-of-mouth (eWOM) enhancing consumers' trust and attitudes toward vendors Research indicates that eWOM not only boosts brand awareness but also fosters trust and loyalty among shoppers, ultimately leading to increased sales.

In the online consumer decision-making process, electronic word-of-mouth (eWOM) plays a significant role Consumers often read online reviews and compare various products and services to identify the company or brand that aligns best with their expectations (Torreno, 2018).

Figure 2.5: Online consumer decision model (Source: www.marketingtutor.net)

According to McEahern's (2014) adaptation of Maslow's hierarchy of needs, online shoppers prioritize safety by seeking secure checkouts, trustworthy product reviews, and credible websites before making purchases Additionally, to satisfy their social needs for belongingness, consumers rely on information from social connections, such as friends and family, which significantly influences their buying decisions.

Figure 2.6: Online Shopper Hierarchy of Needs (Source: McEachern,

Electronic word-of-mouth marketing encompasses several forms, including social shout-outs, user-generated content, recommendations, reviews, press mentions, employee advocacy, and influencer partnerships To foster this type of marketing, businesses should focus on delivering exceptional products and customer service, creating a remarkable shopping experience, curating and sharing user-generated content, and implementing incentives to encourage referrals.

The shopping experience encompasses all interactions and sensations a consumer encounters throughout their purchasing journey with a brand, beginning well before the actual purchase and continuing long after (Schiavini, 2022).

The concept of shopping experience is not new and not limited to digital environment Customers no longer base their loyalty on price or product but on their

26 experience, which makes the brand different and shopping experience is important to create customer loyalty, generate brand awareness and win over customers and their recommendations (Dourado, 2020)

Gullick (2022) stated on that to enhance the customer experience, ecommerce businesses should provide easy to Navigate Website; a fast website; easy payment options; great customer service and personalised options

To enhance the online shopping experience, it's essential to ensure fast site loading on both computers and mobile devices Focus on intuitive navigation and a robust site search feature, as well as high-quality images that effectively showcase products Keep content concise, include customer reviews, and leverage color psychology to influence purchasing decisions Clearly indicate product availability and backorder dates on product pages, and facilitate easy customer contact, quotes, and email sign-ups Implement live chat support, provide a self-service FAQ page, and streamline the checkout process by allowing cart saves and offering free shipping options.

To enhance the online shopping experience, Schiavini (2022) recommends several strategies: understanding your customer, maintaining transparency, providing a diverse range of options, and offering resources to familiarize customers with products Additionally, sharing knowledge and information, recommending relevant items, personalizing the shopping experience, embracing cause marketing, and ensuring excellent after-sales service are crucial for success.

2.2.4 Knowledge of Using Internet and Computer

With the evolution of technologies, such as email, social media, mobile phone, a more interactive environment and content creation by users was enable

Since the launch of the first iPhone in 2007, internet accessibility has significantly improved, allowing consumers to effortlessly access technology from virtually anywhere.

In 2012, the number of smartphone users surpassed 1 billion, and projections indicated it would exceed 3 billion by 2021 (Statista, 2021) Additionally, mobile commerce sales increased from £25.5 billion in 2017 to £29 billion in 2018, demonstrating a continuous upward trend in the market (Springfair.com, 2019).

Figure 2.7: Number of smartphone users worldwide from 2012 to 2021 (in billions) (Source: Statista, 2021)

Between 2019 and 2024, global social media usage has seen significant growth, with nearly 3 billion users reported in 2019 Projections indicate that this number will continue to rise, with over 80% of users remaining active on social media platforms (Insider Intelligence, 2021).

Chapter 2 showed the scholarly literature of previous researchers that are relevant to this study The reviews provided the understanding and knowledge of enterprises and its growth under digital economy

Recent reviews highlight the opportunities and challenges that businesses face due to the increasing use of digital devices, particularly in light of the shifts in consumer buying behavior and attitudes during and after the COVID-19 pandemic.

Research indicates that the intention to purchase is influenced by various significant factors, including demographic and social variables, online shopping experience, internet and computer proficiency, website design, social media presence, situational conditions, facilitating factors, product attributes, promotional strategies, payment options, switching costs, marketing content, types of digital devices, online advertising methods, and the balance between hedonistic and utilitarian motivations.

These reviews help to identify possible gap(s) in the scholarly literature for further research and to compare against findings resulting from the current study The

Despite 36 reviews offering various analyses, there is a notable lack of insights for Vietnamese enterprises seeking to identify opportunities and challenges in digital marketing Specifically, there is insufficient information on the expectations of Vietnamese consumers, considering their demographic and social factors, experiences, types of digital devices, and preferences for online advertising channels This gap in research highlights the need to investigate how these factors influence consumer behavior in online shopping Consequently, the study aims to provide actionable recommendations for Vietnamese businesses to enhance their digital marketing strategies.

METHODOLOGY AND DATA ANALYSIS

Research Problems

As consumers increasingly rely on the internet and technology for product research and purchases, SMEs benefit from direct sales and potentially reduced client acquisition costs This shift towards online shopping not only presents significant challenges but also opens up lucrative opportunities for businesses to thrive in the digital marketplace.

This study addresses the gap in understanding effective digital marketing strategies and consumer behaviors that can enhance online market share for SMEs in Vietnam Key research questions include identifying crucial elements of online consumer behavior that influence actual purchases and exploring the opportunities and challenges faced by SMEs in digital marketing The primary aim is to analyze online shopping behaviors to offer actionable recommendations that improve digital marketing strategies and help SMEs navigate their challenges in the Vietnamese market.

To effectively address the research questions, selecting an appropriate research method along with specific data collection and analysis techniques is essential, as these choices significantly impact the results and recommendations This comprehensive process encompasses various aspects of the study, including the topic, target population, sampling procedures, and quality control measures The forthcoming overview will detail the research methods and quality control procedures employed, with a particular emphasis on understanding consumer behaviors in relation to digital marketing strategies.

Research Method and Design

This study utilizes a quantitative approach to analyze the impact of purchase intention, hedonism, influencing factors, online sales strategies, and utilitarianism on actual online purchases by consumers The foundation of this research lies in the descriptive data collected from the target population, derived from respondents' feedback and observed behaviors (Taylor et al., 2015).

This research study analyzed consumer behaviors and online trends, providing valuable insights into participants' thought processes and actions The choice of data collection methods significantly influences the relevance and quality of research outcomes In this study, consumer questionnaires were utilized, with web-based formats proving to be an innovative and efficient way to gather responses Compared to traditional manual survey methods, web-based questionnaires are less time-consuming, more convenient, and highly cost-effective.

Research Population and Sample

Selecting a representative research sample is crucial for the success of any study, as emphasized by Knechel (2019) This means that the characteristics of the sample should closely match those of the larger population In this research, which focuses on consumer behavior in response to digital marketing and online performance, the target population is specifically defined to include individuals aged 18 to 45 who meet certain criteria.

According to key indicators from Statista published by Ngoc Nguyen (2022), the number of online consumers in Vietnam reached nearly 51.8 million in 2021, with expectations for continued growth in the coming years The majority of online shoppers fall within the age range of 25 to 44 years old (Statista, 2020), making this demographic crucial for estimating the total population of online consumers aged 18 to 45 for research purposes.

Optimal sample size will be decided according to Krejcie and Morgan Table

In research involving a population exceeding 1,000,000, the optimal sample size is determined to be 384, as indicated in Table 3.1 Consequently, the study's sample of 432 respondents is considered ideal for accurate results.

Table 3.1: Krejcie and Morgan Table (Source: Krejcie and Morgan, 1970)

Respondents

This research study examines online consumer behavior, targeting participants who engage in digital marketing or online shopping The sample will consist of knowledgeable young individuals with a certain income level residing in urban areas This judgment sampling method for the questionnaires is expected to yield relevant and high-quality data.

Data Gathering Instrument

For this study, consumer questionnaires were utilized as the primary data gathering instrument A comprehensive questionnaire was developed to initiate the research process To enhance academic reliability, validity, and quality, an expert review was conducted with assistance from a former marketing staff member, ensuring the questions were well-structured and effective.

40 appropriate to elicit responses that effectively support answering research questions Google Form platform was utilized to facilitate consumer questionnaires for the study.

Consumer Questionnaire

The creation of the consumer questionnaire involved a careful analysis of the research topic, problem, question, and purpose, as outlined in Table 3.1 and Appendix A This process focused on formulating targeted consumer questions and metrics that address key areas of digital marketing strategies and consumer behaviors The objective was to craft engaging, sequential questions that would provide valuable insights into consumer preferences, perceptions, influences, and behaviors.

Table 3.1: Variables investigated and their measured

- What is your age range?

- What is the highest level of school you have completed?

- Which of the following categories best describes your employment status?

- What is the range of your monthly income?

2 Respondent’s profile on online purchasing questions

- Please evaluate the competitive factors affecting your choice to buy online over in person?

- Please rate the marketing content that influences your online purchases (Videos, live streaming, storytelling, user-generated contents, photos, and infographics)

- Please rate how often you use your devices for online purchases

(Mobile phones, Desktop computer, Laptop, Tablets, and E-readers)

When considering online purchases, the influence of various information sources is crucial Friends and word-of-mouth recommendations often hold significant sway, while online consumer reviews provide valuable insights into product quality Additionally, the opinions of influential figures can shape purchasing decisions Business websites serve as a primary source of information, yet other online resources like blogs and forums also play an important role in informing consumers Understanding the impact of these diverse sources can enhance decision-making in the digital marketplace.

Rating questions using Likert scale from 1-

- Does changing a purchase channel affect you?

- Did switching to a buying channel bring you some inconvenience?

- Did changing the purchase channel bring you some trouble?

- Was it difficult for you to switch to buying on a new channel?

- If you stop using the current purchase channel, you feel that you will lose many benefits and incentives from using this retail channel

Rating questions Likert scale from 1-5

4 Online advertising channel strategy questions

- Please rate the impact of online advertising channel on your purchase intention among social networking platforms, microblogging platforms, business networking platforms, photo and

41 video-sharing platforms, search engines, instant messaging apps, e- commerce platforms, and trade exchange platforms

When evaluating the impact of various online advertising types on purchase intention, please rate each method—banners, sponsored content on social media, search engine ads, mobile advertising, email marketing, video advertising, and location-based advertising—on a scale from 1 to 5.

5 Online sales channel strategy questions

- Please rate how often you buy from online sales channel among

Hybrid (B2B, B2C, C2C) e-commerce platforms, specialized online retailers, business to business platforms, business to consumer platforms, mobile applications, and individual brand websites

- Please rate the impact of online sales strategies on your purchase intention among price discounts, vouchers, samples, money back guarantee, bundle products, free shipping, and retailer’s warranty

Rating questions using Likert scale from 1-5

- Please rate the influence of the following social factors on your purchasing decision

- Before buying a product, I am interested in the brand of that product

- My friends and I tend to buy products of the same brand

- Before I buy a product, I need to find out how the product has been rated by people

- I am interested in the brands that people are buying

- I am often interested in the advantages of products that other people have purchased

- In the last 30 days, how often have you purchased the following products among fashion, electronic device, house, cosmetics, health, mother and baby, and sports/travel

- I can buy the above products back within the next 30 days

- I may buy products of the same brand again in the near future

8 Past buying experience (proxy for actual purchase) questions

- In the past year, how many times have you purchased products from a business on that business's website?

- In the past year, how much money did you spend on purchasing products from 1 business/purchase channel?

- In the past year, how many times have you purchased products from a business/sales channel through online commerce platforms

- In the past year, how many times have you visited online sales channels?

9 Hedonism/Utilitarianism (Babin et al., 1994)

- Please rate your satisfaction during your purchase

- I'm satisfied even though I can't buy what I really need

- I am satisfied because while shopping I found the items I needed to buy

- I am frustrated that I have to go to other places/sales channels to buy the item I need

- Please rate the impact of shopping on you

- I continue to buy a product not because I need it, but because I want to buy it

- I continue to buy a product not because of the necessity of the product, but because I want the product of that brand

- For me, buying is really a hobby compared to other hobbies of myself

- I feel happy when I can buy products when I want

- I get excited when I find the product I want to buy

- I can forget about the daily hassles of the shopping process using Likert scale from 1-5

Analysis Tools

This research utilized structural equation modeling, specifically partial least squares structural equation modeling, to analyze data related to digital marketing opportunities and challenges for small and medium-sized enterprises (SMEs) in Vietnam This established technique effectively handles complex models with latent variables, revealing intricate cause-and-effect relationships within the context of the study.

Therefore, the fundamental reason for using SEM-PLS is its flexibility to handle data and, secondly, that this technique allows the researchers of this study to

SMART-PLS is the preferred software for estimating complex models with numerous constructs, indicator variables, and structural paths, as it does not require distributional assumptions on the data (Hair et al., 2018) Its effectiveness in producing accurate estimations has led to extensive use of SEM-PLS in the marketing field (Hair et al., 2011; Hult et al., 2018).

Descriptive Analysis

The research targeted young consumers aged 18 to 40 who are familiar with online shopping and digital marketing Participants were required to have sufficient income to purchase regular online products at reasonable prices from small and medium-sized enterprises (SMEs).

Variables Mean Median Min Max StdDev

Table 3.3: Frequencies of Gender (GEN)

Levels Counts % of Total Cumulative %

Table 3.4: Frequencies of Age (AGE)

Table 3.5: Frequencies of Academic level (EDU)

Table 3.6: Frequencies of work status (EMP)

There is no job/ looking for a job 193 44.7 % 99.1 %

Table 3.7: Frequencies of monthly income (INC)

In this study, 68% of respondents were female, with 77% of participants aged between 18 and 25 years, indicating that the predominant demographic is young females.

Doctor Master Bachelor High school

Self -business/ business owner There is no job/ looking for a job

Among the respondents, 47% are employed either full-time or part-time, while 44.7% are not currently working or seeking employment Additionally, 70% of these individuals hold a bachelor's degree, and nearly 74% earn less than 10 million Vietnamese Dong per month.

In consequence, this research is likely to closely represent the factors that influence the actual online purchase for young females with a bachelor’s level and a monthly salary of 10 million

The tables and lists in Appendix B show the items used on the survey for each variable and the corresponding descriptive statistics results from the collected data in this research.

Consumers are increasingly using digital tools for online purchases, creating opportunities for businesses, especially SMEs This research aims to identify effective digital marketing strategies and consumer behaviors that can guide SMEs in developing their digital marketing approaches Consequently, relevant research questions and questionnaires were formulated, focusing on factors influencing online purchasing among young individuals with a monthly income of 10 million.

RESULTS AND DISCUSSIONS

Path Coefficients

Path coefficients represent the direct effects and causal relationships between statistical variables, expressed in a standardized form (Hair et al., 2014) This standardization allows for the comparison of relative effects among variables within a regression model In structural equation modeling, standardized path coefficients are interpreted similarly to standardized regression coefficients, indicating that a one standard deviation change in the independent variable corresponds to a change of beta standard deviations in the dependent variable (Rodríguez-Entrena, Schuberth, and Gelhard, 2016).

Table 4.1 presents the path coefficients illustrating the causal relationships among the surveyed variables, along with additional statistical data Notably, the only insignificant coefficient pertains to the relationship between online advertising types and online sales strategy, indicated by a p-value exceeding 0.05 However, the indirect effect analysis reveals a significant indirect influence of this relationship, warranting its inclusion in the model despite the direct effect being insignificant.

The relationship between types of marketing content and influencing factors shows a strong impact, with a beta value nearing 0.5 and a significant p-value A one standard deviation increase (0.051) in marketing content types is associated with a predicted increase of 0.491 standard deviations in influencing factors This highlights the crucial role that marketing content plays in shaping customer behaviors.

It observes that utilitarianism relevantly and significantly affects the purchase intention, as well as online sales strategy and influencing factors on utilitarianism

Online sales strategies and influencing factors play a crucial role in shaping utilitarianism, which in turn significantly impacts purchase intention To boost purchase intention and drive actual purchases, firms should focus on enhancing their online sales strategies Our research indicates a direct relationship between purchase intention and actual purchases, with a beta value of approximately 0.2 and a highly significant p-value Specifically, a one standard deviation increase in purchase intention (0.051) is associated with a predicted increase of 0.228 standard deviation units in actual purchases.

Hedonism significantly boosts purchase intention, while the impact of product types on online purchases is comparatively lower To increase purchase intention, companies should primarily cultivate a sense of hedonism among customers This can be partially achieved through social influence, switching costs, and positive word of mouth, as indicated in Table 4.1.

Our research indicates that online sales strategies can be significantly improved through effective online advertising channel strategies, while the direct impact of online sales channel strategies on overall sales is comparatively weaker Additionally, the influence of digital devices and switching costs on key factors and utilitarianism is minimal.

Table 4.1: Path Coefficients of Causal Relations Between Variables

Causal Relations Between Variables Coefficients Sample

Mean Std.Deviation T Statistics P-Values

Digital Devices Types -> Influencing Factors 0.094 0.096 0.046 2.030 0.043

Online Advertising Channel Strategies -> Online Sales

Online Advertising Types -> Online Sales Strategy 0.011 0.012 0.056 0.187 0.852

Online Sales Channel Strategy -> Online Sales Strategy 0.225 0.225 0.055 4.065 0.000

Types of Marketing Contents -> Influencing Factors 0.491 0.494 0.051 9.531 0.000

Types of Products Purchased Online -> Actual Purchase 0.184 0.189 0.052 3.506 0.000

Types of Products Purchased Online -> Purchase Intention 0.128 0.132 0.050 2.559 0.011

The levels of statistical significance for individual coefficients are determined by P-values, with thresholds set at 0.001 for high significance, 0.01 for moderate significance, and 0.05 for acceptable significance P-values exceeding 0.05 are highlighted in red to indicate statistical insignificance.

Figure 4.1 presents the comprehensive structural equation model, illustrating the strength of relationships between variables through path coefficients, with R-squared values displayed within the circles A detailed analysis of the R-squared results will be provided in a subsequent section.

Figure 4.1: Structural Equation Model Employed,

Indirect Effects

This section presents our findings on the total indirect effects among variables that lack direct linkages to utilitarianism, purchase intention, and actual purchase behavior, with detailed results available in Table 4.2.

Our research indicates that online sales strategies and switching costs significantly influence purchase intention, with coefficients exceeding 0.1 Therefore, businesses should prioritize developing effective online sales strategies and managing switching costs to enhance customer purchase intentions Additionally, other influencing factors also play a role in shaping purchase intention, albeit with a more moderate impact.

50 online advertising channel strategies, online sales channel strategy, social influence, types of marketing contents, and word of mouth

Online advertising channel strategies and marketing content types significantly influence utilitarianism, which in turn has the highest indirect effect on actual purchase behavior (0.074) To boost sales performance, companies should focus on enhancing utilitarianism in customers' perceptions through tailored online advertising strategies and content Additionally, other factors such as hedonism, online sales strategy, and switching costs also positively impact purchase intention, with hedonism playing a crucial role in this relationship, as evidenced by our findings.

Research indicates that purchase intention exerts a significantly greater indirect influence on consumer behavior compared to actual purchases For example, the coefficient for word of mouth affecting purchase intention is 0.071, while its impact on actual purchases is only 0.016 This trend is consistent across all observed relationships As noted in the path coefficients section, an increase in purchase intention does not guarantee a proportional rise in actual purchases, as not all intentions translate into completed transactions.

It emerges also from Table 4.2 that several relationships are insignificant characterized by higher p-values over 5%, and several variables have low impact on their dependent variables

Table 4.2: Total Indirect Effects on Utilitarianism, Purchase Intention and Actual Purchase

Relationship Variables Coefficients Sample Mean Std Deviation T Statistics P Values

Digital Devices Types -> Actual Purchase 0.002 0.002 0.001 1.349 0.177

Digital Devices Types -> Purchase Intention 0.007 0.007 0.004 1.605 0.109

Online Advertising Channel Strategies -> Actual Purchase 0.011 0.011 0.004 2.577 0.010

Online Advertising Channel Strategies -> Purchase Intention 0.047 0.047 0.014 3.396 0.001

Online Advertising Channel Strategies -> Utilitarianism 0.144 0.146 0.031 4.591 0.000

Online Advertising Types -> Actual Purchase 0.000 0.000 0.002 0.177 0.860

Online Advertising Types -> Purchase Intention 0.001 0.001 0.007 0.180 0.857

Online Sales Strategy -> Actual Purchase 0.027 0.027 0.009 2.988 0.003

Online Sales Strategy -> Purchase Intention 0.119 0.119 0.029 4.074 0.000

Online Sales Channel Strategy -> Actual Purchase 0.006 0.006 0.003 2.299 0.022

Online Sales Channel Strategy -> Purchase Intention 0.027 0.027 0.010 2.705 0.007

Online Sales Channel Strategy -> Utilitarianism 0.082 0.082 0.024 3.469 0.001

Social Influence (Norms) -> Actual Purchase 0.015 0.015 0.006 2.534 0.011

Social Influence (Norms) -> Purchase Intention 0.068 0.067 0.021 3.277 0.001

Types of Marketing Contents -> Actual Purchase 0.008 0.009 0.004 2.330 0.020

Types of Marketing Contents -> Purchase Intention 0.036 0.037 0.012 3.007 0.003

Types of Marketing Contents -> Utilitarianism 0.112 0.114 0.029 3.803 0.000

Word of mouth -> Actual Purchase 0.016 0.016 0.006 2.488 0.013

Word of mouth -> Purchase Intention 0.071 0.072 0.024 2.955 0.003

The statistical significance of individual coefficients is determined by P-values, with thresholds set at 0.001 for high significance, 0.01 for moderate significance, and 0.05 for acceptable significance P-values exceeding 0.05 are highlighted in red to indicate statistical insignificance.

Table 4.3 outlines the specific indirect effects of our estimation, highlighting the mediation relationships among variables Notably, online advertising channel strategies and marketing content types exert significant influence on utilitarianism, which is mediated by online sales strategy and influencing factors Utilitarianism demonstrates the strongest indirect effect on actual purchases through purchase intention (0.074), while hedonism also plays a relevant role (0.061) Therefore, firms should focus on enhancing utilitarianism and hedonism by developing attractive online advertising strategies and marketing content to boost actual purchases and improve overall performance Additionally, other factors that indirectly affect actual purchases include the types of products bought online and the online sales strategy.

While a rise in purchase intention doesn't directly translate to a proportional increase in actual purchases, several key factors can significantly enhance purchase intention These include the types of marketing content, switching costs, influencing factors, online sales channel strategies, social influence, word of mouth, and online advertising strategies Companies should implement effective strategies and policies to strengthen these variables, keeping in mind that the resulting increase in actual purchases may be less pronounced than the rise in purchase intention.

Several relationships are deemed insignificant, as indicated in red, while other relationships exhibit a marginal indirect impact on utilitarianism, purchase intention, and actual purchase, as detailed in Table 4.3.

Table 4.3: Specific Indirect Effects Through Mediation Relationships

Relationship of Variables Coefficients Sample

Switching Costs -> Hedonism -> Purchase Intention -> Actual Purchase 0.018 0.018 0.007 2.732 0.006 Influencing Factors -> Utilitarianism -> Purchase Intention -> Actual Purchase 0.017 0.017 0.007 2.417 0.016 Types of Marketing Contents -> Influencing Factors -> Utilitarianism -> Purchase

Online Sales Channel Strategy -> Online Sales Strategy -> Utilitarianism ->

Online Advertising Types -> Online Sales Strategy -> Utilitarianism -> Purchase

Online Advertising Channel Strategies -> Online Sales Strategy -> Utilitarianism 0.144 0.146 0.031 4.591 0.000 Types of Marketing Contents -> Influencing Factors -> Utilitarianism 0.112 0.114 0.029 3.803 0.000 Online Advertising Channel Strategies -> Online Sales Strategy -> Utilitarianism

Switching Costs -> Hedonism -> Purchase Intention 0.078 0.077 0.023 3.406 0.001

Types of Products Purchased Online -> Purchase Intention -> Actual Purchase 0.029 0.031 0.014 2.043 0.041 Digital Devices Types -> Influencing Factors -> Utilitarianism -> Purchase

Utilitarianism -> Purchase Intention -> Actual Purchase 0.074 0.075 0.023 3.173 0.002

Influencing Factors -> Utilitarianism -> Purchase Intention 0.074 0.075 0.023 3.269 0.001

Hedonism -> Purchase Intention -> Actual Purchase 0.061 0.061 0.020 3.030 0.002

Online Sales Strategy -> Utilitarianism -> Purchase Intention -> Actual Purchase 0.027 0.027 0.009 2.988 0.003 Online Advertising Types -> Online Sales Strategy -> Utilitarianism -> Purchase

Online Sales Channel Strategy -> Online Sales Strategy -> Utilitarianism ->

Table 4.3: Specific Indirect Effects Through Mediation Relationships

Relationship of Variables Coefficients Sample

Digital Devices Types -> Influencing Factors -> Utilitarianism 0.021 0.022 0.012 1.772 0.077 Digital Devices Types -> Influencing Factors -> Utilitarianism -> Purchase

An effective online sales channel strategy significantly impacts purchase intention, with utilitarianism playing a crucial role Social influence, particularly through norms, also enhances hedonistic motivations that drive purchase intentions The direct correlation between online sales strategy and utilitarianism further emphasizes its importance in influencing consumer behavior However, the type of online advertising does not significantly affect the online sales strategy or utilitarianism Moreover, various types of marketing content serve as influential factors that ultimately shape utilitarianism and, consequently, purchase intentions.

Word of mouth -> Hedonism -> Purchase Intention 0.071 0.072 0.024 2.955 0.003

Switching Costs -> Utilitarianism -> Purchase Intention 0.045 0.045 0.018 2.481 0.013

Social Influence (Norms) -> Hedonism -> Purchase Intention -> Actual Purchase 0.015 0.015 0.006 2.534 0.011 Online Advertising Channel Strategies -> Online Sales Strategy -> Utilitarianism

Switching Costs -> Utilitarianism -> Purchase Intention -> Actual Purchase 0.010 0.010 0.005 2.152 0.031 Word of mouth -> Hedonism -> Purchase Intention -> Actual Purchase 0.016 0.016 0.006 2.488 0.013

Total Effects

The total effects, presented in Table 4.4, highlight that all types of online advertising exhibit insignificant relationships, while the remaining coefficients show significant differences from zero.

The types of products purchased online significantly impact both purchase intention and actual purchases, indicating that consumer attitudes may vary by sector Additionally, switching costs play a crucial role in influencing hedonism, purchase intention, and utilitarianism Notably, marketing content types exert the strongest influence on these factors, although their overall effect on purchase intention and actual purchases is relatively minor according to our findings.

The intention to purchase is significantly influenced by factors such as hedonism, online sales strategies, switching costs, and utilitarianism, although these factors have a relatively lower impact on actual purchases Research indicates that an increase of one standard deviation in purchase intention (0.051) correlates with an increase of 0.228 standard deviation units in actual purchases, aligning with previous findings.

The influence of hedonism, online sales strategies, utilitarianism, and switching costs plays a crucial role in shaping purchase intentions and actual buying behavior Enhancing purchase intention can be achieved by focusing on these key variables.

● Hedonism is fostered by social influence and word of mouth

● Online sales strategy is relevantly influenced by online advertising channel strategies and online sales channel strategy

● Utilitarianism is significantly fostered by the following variables: influencing factors, types of marketing contents, online advertising channel strategies, and online sales strategy

Switching costs significantly influence purchase intentions, potentially leading to actual purchases, albeit to a lesser extent, as not all intentions result in completed transactions.

To boost customer purchase intentions and drive actual sales, companies should craft their marketing strategies around enhancing hedonism, optimizing online sales tactics, emphasizing utilitarian benefits, and addressing switching costs.

Digital Devices Types -> Actual Purchase 0.002 0.002 0.001 1.349 0.177

Digital Devices Types -> Influencing Factors 0.094 0.096 0.046 2.030 0.043

Digital Devices Types -> Purchase Intention 0.007 0.007 0.004 1.605 0.109

Online Advertising Channel Strategies -> Actual Purchase 0.011 0.011 0.004 2.577 0.010 Online Advertising Channel Strategies -> Online Sales Strategy 0.396 0.399 0.063 6.283 0.000 Online Advertising Channel Strategies -> Purchase Intention 0.047 0.047 0.014 3.396 0.001 Online Advertising Channel Strategies -> Utilitarianism 0.144 0.146 0.031 4.591 0.000