Table of Content

Chapter 1 Introduction​ 6
1.1 Research Background​ 6
1.2 Problem statement​ 7
1.3 Research Aim​ 8
1.4 Research Objectives​ 9
1.5 Research Questions​ 9
1.6 Risk factors and mitigation​ 9
1.7 Factors Influencing the Selection of Research Questions​ 15
Chapter 2 Literature Review​ 21
2.1 Theory 1 (Independent Variable: Marketing)​ 21
2.2 Theory 2 (Dependent Variable: Consumer Engagement)​ 21
2.3 Impact of Variable IV (Marketing) on Variable DV (Consumer Engagement)​ 21
2.4 Hypotheses​ 22
Chapter 3 Data Collection​ 23
3.1 Data Protocol​ 23
3.2 Data Reliability​ 23
3.3 Data Validity​ 23
3.4 Ethical Concerns​ 24
Chapter 4 Data Collection Result​ 25
4.1 Demographic Profile​ 25
4.2 Summary of Collected Data​ 27
Chapter 5 Data Analysis and Interpretation​ 34
5.1 Analysis of Social Influence​ 34
5.2 Analysis of IV1 and DV2 (Product Design)​ 39
5.3 Analysis of IV1 and DV3 (Price Value)​ 43
5.4 Hypothesis Explanation​ 48
Chapter 6 Conclusion and Implication​ 49
6.1 Conclusion​ 49
6.2 Implication​ 49
6.2.1 Practical Implication​ 49
6.2.2 Theoretical Implication​ 49
Bibliography​ 51
List of Figure

Fig 1 Global Stats of Android phones market share in Indonesia​ 6

Fig 2 Survey question ​ 17
Fig 3 Age ​ 18
Fig 4 Gender​ 18
Fig 5 Part of Jakarta ​ 19
Fig 6 Occupation ​ 19
Fig 7 Question 1 ​ 20
Fig 8 Question 2 ​ 20
Fig 9 Question 3​ 21
Fig 10 Question 4​ 21
Fig 11 Question 5​ 22
Fig 12 Question 6​ 22
Fig 13 Question 7​ 23
Fig 14 Question 8​ 23
Fig 15 Question 9 ​ 24
Fig 16 Question 10​ 24
Fig 17 Question 11​ 25
Fig 18 Question 12​ 25
Fig 19 Question 13 ​ 26
Fig 20 Question 14 ​ 26
Fig 21 Question 15​ 27
Fig 22 Question 16 ​ 27
Fig 23 Question 17 ​ 28
Fig 24 Question 18 ​ 28
Fig 25 Question 19 ​ 29
Fig 26 Question 20​ 29
Fig 27 Question 21​ 30
Fig 28 Question 22​ 30
Fig 29 Question 23​ 31
Fig 30 Question 24​ 31
Fig 31 Question 25​ 32
Fig 32 Question 26​ 32
Fig 33 Question 27​ 33
List of Table

Table 1.1 Summary of Collected Data​ 28

 Strategic Marketing and Consumer Engagement in the Success of selling Android phones

Chapter 1 Introduction

1.1 Research Background

Effective communication of product value and brand differentiation in a very competitive
market helps strategic marketing to explain the success of selling Android phones. Leading
Android phone manufacturer Samsung and others use the 4P marketing mix-product, price,
place, and promotion-to approach their handsets as appealing options for particular
customer categories. For example, Samsung's Galaxy line maintains product quality, balances
feature performance with reasonable pricing to appeal to lower-middle-class consumers, and
uses brand image to inspire fresh trends and competitive advantages. This calculated
approach guarantees that Android phones satisfy customer needs and promotes market
penetration and brand loyalty (Olivia Yolanda, 2024). ​
​
Driving the demand and success of Android phones depends mostly on consumer
involvement. Engaging consumers in the digital era means knowing their preferences and
behaviors to customize marketing plans that appeal personally. While mobile marketing itself
is not included here, the more general strategic marketing initiatives concentrate on
developing long-term connections by means of brand recognition, product functionality, and
retailer cooperation. Retailers are important middlemen since they affect consumer buying
decisions by means of trade margins, inventory control, and brand reputation.
Manufacturers, distributors, and stores cooperate to create an ecosystem supporting
constant demand and market expansion for Android devices (ismail razak, 2024).​
​
Clarifying the success elements of Android phones helps one to understand the "who, what,
where, when, why, and how" of strategic marketing and consumer interaction.
Manufacturers, stores, and consumers; what is product feature, pricing, and branding; where
covers urban and rural markets; when relates to timely product launches and promotional
campaigns; why centers on meeting consumer needs and preferences; and how is through
coordinated marketing strategies and strong retailer relationships? In the ever-changing
smartphone market, this all-encompassing strategy helps Android phone businesses to keep
competitive advantage, properly grab market share, and adapt to changing consumer
expectations (ismail razak, 2024).

Reflecting the larger trend in Indonesia's smartphone industry, which rose by 15.5%
year-over-year to almost 40 million units in 2024, the sales of Android phones in Jakarta have
been particularly successful (idc, 2025). As the capital and biggest metropolitan hub in
Jakarta, consumer demand is driven by a mix of cost, brand variety, and technology features
given by Android devices. With mostly the Android operating system, Oppo leads with
17.59%, closely followed by Samsung at 17.12%, and Xiaomi at 14.93%, which dominates
around 88% of the market share in Indonesia (gs.statcounter.com, 2025). Continuous product
innovation and competitive pricing policies—especially from Samsung's Galaxy A series and
Oppo's mid-range models, which appeal to Jakarta's varied customer base—help to justify
this dominance. The substantial presence of these brands in retail and online channels in
Jakarta drives their sales success even more, so most consumers in the city choose Android
phones (gs.statcounter.com, 2025).

Fig 1 Global Stats of Android phones market share in Indonesia

In conclusion, clever marketing driven by competitive pricing, product innovation, and strong
brand positioning effectively targets several customer segments, hence driving the success of
Android phone sales in Jakarta. Manufacturers, stores, and distributors working together
produces a strong ecosystem that increases consumer involvement and maintains demand.
Data from reliable sources like IDC and Statcounter show how dominant Android companies
such Oppo, Samsung, and Xiaomi are in Jakarta's smartphone industry, thereby highlighting
how specifically focused marketing techniques and product offers satisfy urban consumers. In
one of Indonesia's most active markets, this all-encompassing strategy guarantees not just
large market share but also constant competitiveness of Android phones.

1.2 Problem statement

Although strategic marketing and consumer involvement help to sell Android phones in
Jakarta, there are clear shortcomings mostly related to changing market demand and
regulatory difficulties. Though affordability and a wide range of products underpin Android's
leading market share, Indonesia's smartphone market dropped 1.2% in 2023, a reflection of
declining consumer buying power and low demand under economic uncertainty. Moreover,
the implementation of sophisticated local content rules under the "Make in Indonesia" policy
has caused supply chain and compliance issues for producers, therefore hindering
development and confusing strategic marketing initiatives. These elements restrict the
capacity of Android firms to fully exploit their product advantages and sustain constant sales
momentum in the competitive environment of Jakarta (idc, 2024). ​
​
Furthermore challenged by varied consumer behavior and market fragmentation are
consumer engagement tactics. Although Android companies like Samsung and Oppo lead in
Jakarta, a sizable fraction of customers remain price-sensitive and respond differently to
marketing stimuli; other segments indicate low engagement or doubt of promotional efforts.
This variability calls for very customized marketing strategies, which might tax resources and
lower the general campaign success. Furthermore, the restricted availability of modern
technologies like 5G infrastructure in Jakarta reduces the apparent value of higher-end
Android devices, hence lowering user incentives to upgrade. Thus, strategic marketing and
consumer involvement have to overcome these shortcomings by adjusting to legislative
restrictions, economic situation, and complex customer preferences to maintain the sales
success of Android phones in Jakarta (idc, 2024).

In conclusion, strategic marketing that properly blends product innovation, competitive

pricing, strong brand positioning, and robust customer involvement through coordinated
efforts among manufacturers, retailers, and distributors drives the success of Android phone
sales in Jakarta. Android companies like Samsung, Oppo, and Xiaomi keep dominance despite
obstacles including economic uncertainty, regulatory constraints, fragmented consumer
preferences, and limited 5G infrastructure by customizing their marketing mix to different
customer segments and using vast retail and online networks. Companies should concentrate
on constant product quality improvements, flexible pricing policies, tailored marketing
campaigns, improved after-sales services, proactive adaptation to local laws and
infrastructural changes if they want to raise market sales even more. In the changing
smartphone scene of Jakarta, this all-encompassing strategy will boost brand loyalty, increase
market penetration, and maintain competitive advantage.

1.3 Research Aim

The aim of this research is about the effectiveness of the 4P marketing mix-product, price,
place, and promotion-in targeting various customer segments, so fostering brand loyalty, and
driving market penetration, this study aims to investigate how strategic marketing and
consumer engagement help to explain how successful Android phone sales in Jakarta are. It
aims to comprehend how manufacturers, stores, and consumers interact to build a
supportive ecosystem that maintains demand among economic uncertainty, legal difficulties,
and scattered customer behavior. The study also seeks to pinpoint operational techniques
and adaptive marketing methods that help top Android companies like Samsung, Oppo, and
Xiaomi keep their competitive edge and sales supremacy in Jakarta's vibrant smartphone
industry.
1.4 Research Objectives
To identify adaptive marketing strategies and operational practices that enable Android
phone companies like Samsung, Oppo, and Xiaomi to overcome economic, regulatory, and
consumer behavior challenges to sustain sales success in Jakarta’s smartphone market.

To analyze the implementation of the 4P marketing mix (product, price, place, and
promotion) by leading Android phone manufacturers in Jakarta and how these strategies
target different customer segments.

To highlight strategic marketing approaches and consumer engagement practices that

enable Android phone companies such as Samsung, Oppo, and Xiaomi to successfully
navigate economic uncertainties, regulatory challenges, and diverse consumer behaviors,
thereby sustaining and enhancing their sales performance in Jakarta’s competitive Android’s
phones market.

1.5 Research Questions

How do Android phone companies such as Samsung, Oppo, and Xiaomi adapt their
marketing strategies and operational practices to overcome economic, regulatory, and
consumer behavior challenges in Jakarta’s smartphone market?

In what ways do leading Android phone manufacturers implement the 4P marketing mix
(product, price, place, and promotion) to effectively target different customer segments in
Jakarta?

What strategic marketing approaches and consumer engagement practices enable Samsung,
Oppo, and Xiaomi to sustain and enhance their sales performance amid economic
uncertainties, regulatory challenges, and diverse consumer behaviors in Jakarta’s competitive
Android smartphone market?

1.6 Risk factors and mitigation

Risk Factor 1: Incomplete or Flawed Research Design

A major risk in research projects is the presence of incomplete data or flawed

methodologies, which can lead to invalid or unreliable results. This risk factor is critical
because it directly affects the validity and credibility of the research findings. For example, if
the research design does not adequately control for confounding variables or uses
inappropriate sampling methods, the conclusions drawn may be biased or not generalizable.
This risk is particularly relevant to correspondents who rely on accurate data to make
informed decisions or policy recommendations. Ensuring a robust research design from the
outset is essential to mitigate this risk.

Risk Factor 2: Resource Constraints

Limited resources, including budget, staffing, and equipment, pose significant risks to the
successful completion of research projects. Resource constraints can delay timelines, reduce
the scope of research activities, or compromise the quality of data collection and analysis.
For correspondents involved in the research, these constraints may lead to incomplete data
or insufficient follow-up, which impacts the overall reliability of the study outcomes.
Managing resource allocation efficiently and anticipating potential shortages are crucial to
addressing this risk.

Risk Factor 3: External Factors and Regulatory Changes

Changes in external conditions such as funding priorities, regulatory requirements, or

political and economic shifts can disrupt research projects. These factors may lead to sudden
changes in project scope, additional compliance burdens, or even project termination. For
correspondents, this risk means that ongoing research may face interruptions or require
adjustments that affect data consistency and comparability. Staying informed about external
developments and maintaining flexibility in project plans can help mitigate this risk.

Risk Factor 4: Data Management Issues

Risks related to data management include loss of data integrity, cybersecurity breaches, and
outdated or inaccurate information. Poor data management can compromise the
confidentiality, accuracy, and availability of research data, undermining the entire research
effort. For correspondents, unreliable data can lead to incorrect interpretations or decisions.
Implementing strong data governance policies and secure data handling practices is vital to
reduce this risk.

Mitigation Methods for Risk Factor 1: Strengthening Research Design

To alleviate risks associated with incomplete or flawed research design, researchers should
conduct thorough risk analyses during the planning phase. This includes pilot testing
methodologies, peer reviews of the research plan, and involving subject-matter experts to
identify potential pitfalls early. Regular monitoring and adaptive adjustments during the
research process can help ensure the design remains robust and valid. By proactively
addressing design weaknesses, the reliability and credibility of the research outcomes
improve, benefiting correspondents who depend on accurate data.

Mitigation Methods for Risk Factor 2: Efficient Resource Management

 Mitigating resource constraints involves careful planning and prioritization of research
activities to align with available resources. Researchers should develop contingency plans
(Plan B) that include alternative approaches or scaled-down versions of the study if resources
become limited. Securing diverse funding sources and optimizing staff allocation can also
help maintain project momentum. Transparent communication with correspondents about
resource limitations and their potential impact ensures realistic expectations and
collaborative problem-solving.

Mitigation Methods for Risk Factor 3

Monitoring External Environment and Compliance to manage risks from external factors,
continuous monitoring of regulatory changes, funding landscapes, and political or economic
conditions is essential. Researchers should build flexibility into project timelines and budgets
to accommodate unforeseen changes. Engaging with regulatory bodies and funders early and
often can facilitate smoother compliance and adaptation processes. For correspondents, this
approach minimizes disruptions and maintains the integrity of longitudinal data collection.

Mitigation Methods for Risk Factor 4

Robust Data Management Practices Effective mitigation of data management risks requires
implementing comprehensive data governance frameworks that ensure data accuracy,
security, and accessibility. This includes regular data backups, encryption, access controls,
and training for research staff on data handling protocols. Employing validated data
collection tools and maintaining audit trails enhance data integrity. These measures protect
correspondents’ data interests and support trustworthy research findings.

Research Methodology explanation

Through non-numerical data including interviews, observations, and texts, qualitative

research—a technique aimed at examining and understanding human experiences,
behaviours, and perceptions—is able to It offers comprehensive, thorough insights into
difficult to measure social events by addressing open-ended questions like "how" and "why,"
therefore addressing Often utilised in social sciences to find meanings, motivations, and
patterns behind behaviours rather than testing hypotheses or statistically measuring
variables, this flexible and interpretive approach is used here (devin kowalczyk, 2023).​
​
Gathering and evaluating numerical data in quantitative research helps one to spot trends,
test hypotheses, and generate statistical findings. It emphasises on applying organised
techniques such surveys, experiments, and statistical analysis to measure correlations
between variables. This kind of research is objective and seeks generalisability by means of
large sample numbers and standardised instruments, hence fitting for addressing concerns
concerning "how many" or "how much" (devin kowalczyk, 2023).​
​
 Mixed methods research uses the advantages of both qualitative and quantitative
approaches inside one study. Mixed techniques give a more complete knowledge of difficult
research problems that cannot be totally addressed by either method alone by combining
numerical data with thorough contextual insights. Although this method can be
time-consuming and difficult to apply, it improves the legitimacy and richness of conclusions
(devin kowalczyk, 2023).​

Type of Research: Quantitative

For this research, I am employing a quantitative approach, specifically using the survey
method. The goal is to gather measurable data on consumer perceptions, behaviors, and
responses to the strategic marketing practices of leading Android brands (Samsung, Oppo,
Xiaomi) in Jakarta. Quantitative research is ideal for this study because it allows me to
analyze trends, preferences, and the effectiveness of the 4P marketing mix across a broad
and diverse consumer base.

I chose the quantitative method because my research aims to identify patterns and
relationships between marketing strategies and consumer engagement on a larger scale. By
distributing structured questionnaires, I can collect standardized data from a significant
number of respondents, ensuring statistical reliability and the ability to generalize findings to
the wider Jakarta market.

A qualitative approach, such as interviews, was not selected because my focus is on breadth
rather than depth. While qualitative methods provide rich, detailed insights, they are less
suited for identifying generalizable trends across a large, fragmented urban market like
Jakarta. Quantitative surveys, on the other hand, enable me to reach a representative
cross-section of consumers and analyze the impact of marketing strategies using statistical
tools.

Sampling Criteria

The respondents I am targeting are adult consumers (aged 18–50) living in Jakarta who have
purchased or considered purchasing an Android phone within the last two years. This group
reflects the active smartphone market segment and includes both first-time buyers and
repeat customers. By focusing on this age group, I ensure that the sample covers both
younger, tech-savvy users and working adults who influence household purchasing decisions.

I am particularly interested in individuals from varied income levels-from lower-middle to

upper-middle class-since pricing is a key factor in Android phone sales. This diversity will help
me understand how different economic backgrounds influence consumer responses to
product features, pricing strategies, and promotional campaigns.

Additionally, I want to include respondents who have experience with at least one of the top
three brands: Samsung, Oppo, or Xiaomi. This ensures that the feedback directly relates to
the companies and marketing strategies central to my research objectives. I will also consider
gender balance and include both male and female respondents to capture a comprehensive
view of consumer preferences in Jakarta.

Sampling Method

For this research, I am using a stratified random sampling method. Jakarta is a large
metropolitan area with diverse demographics, so stratifying the sample by age, income, and
residential area (Central, North, South, East, and West Jakarta) ensures that all major
consumer segments are adequately represented.

Stratified sampling is particularly suitable because it allows me to compare responses across

different strata, such as income levels or districts, and identify whether certain marketing
strategies are more effective in specific segments. This is crucial for understanding how the
4P marketing mix is perceived by different groups within Jakarta's fragmented market.

Random sampling within each stratum reduces selection bias and increases the reliability of
the results. By ensuring that each subgroup is proportionally represented, I can generalize my
findings to the broader population of Android phone consumers in Jakarta, making the
research robust and actionable for marketers.

Total Amount of Respondents

I plan to survey at least 50 respondents. This sample size is statistically significant for a city as
large and diverse as Jakarta and allows for meaningful subgroup analysis (e.g., by brand
preference, income, or district).

Choosing 50 respondents strikes a balance between feasibility and representativeness. It is

large enough to ensure that the data is reliable and that the findings can be generalized to
the wider population. At the same time, it is manageable in terms of data collection and
analysis within the research timeline.

Given the quantitative nature of my research, this sample size is appropriate. It allows for
robust statistical analysis, including cross-tabulations and regression, to test relationships
between marketing strategies and consumer engagement outcomes.

Approach Method
To reach my respondents, I will use a combination of online and offline survey distribution.
Online surveys will be shared through social media platforms, community groups, and email
lists targeting Jakarta residents. For offline distribution, I will collaborate with retailers and
mobile phone stores to reach consumers directly at the point of purchase.

To encourage participation, I will keep the survey concise (10–15 minutes), assure
respondents of confidentiality, and offer small incentives such as e-vouchers or a chance to
win a prize. Clear instructions and user-friendly survey design will help maximize response
rates.

I will monitor response rates in real time and send gentle reminders to ensure I reach my
target sample size. For offline surveys, I will train store staff to help explain the purpose of
the research and assist respondents, ensuring data quality and completeness.

Analysis Method

Once data collection is complete, I will use descriptive statistics (mean, median, mode,
frequency distributions) to summarize consumer demographics and general attitudes toward
Android brands. This will provide a clear overview of the market landscape in Jakarta.

For deeper analysis, I will employ inferential statistics such as chi-square tests, t-tests, and
regression analysis to examine relationships between variables-such as the effect of
promotional activities on brand loyalty, or the impact of pricing on purchase decisions among
different income groups. Cross-tabulation will help me compare responses across strata (e.g.,
age, income, district).

Quantitative analysis is best suited for this research because it enables me to identify
statistically significant trends and correlations. This approach allows me to answer my
research questions objectively and provide actionable insights for marketers and
manufacturers aiming to enhance their strategic marketing and consumer engagement in
Jakarta’s Android phone market.
1.7 Factors Influencing the Selection of Research Questions
First research question:​
​
How do Android phone businesses like Samsung, Oppo, and Xiaomi modify their marketing
tactics and operational procedures to overcome economic, legal, and consumer behavior
obstacles in Jakarta's smartphone market?​
​
​
The Reason I Selected this Research Question​
​
I choose this subject since I would like to know how big Android companies negotiate the
convoluted terrain of Jakarta's smartphone industry. Studying their adaption tactics would
help me to understand how businesses keep competitiveness in face of changing consumer
preferences, economic fluctuations, and legislative changes.​
​
Value and Journal Notes​
​
New research supports the relevance of this question. Studies shown in the International
Journal of Business and Management, for instance, show how Indonesian regulations
influence operational strategies of multinational smartphone makers. Furthermore regularly
discussed by IDC and Counterpoint Research are how customer behavior changes and
economic downturns force businesses to change their marketing strategies. These sources
validate that academics and industry analysts are actively researching this issue.​
​
Consequences​
​
For Me as a researcher: Dealing with this challenge will enable me to create a structure for
evaluating adaptive tactics in dynamic markets.​
​
For businesses, the results can enable them to evaluate current policies and project
upcoming difficulties.​
​
I intend to respond using both quantitative (sales numbers, customer surveys) and
qualitative (interviews, policy texts).​
​
I require statistics on consumer behavior trends, company initiatives, legislative changes,
and sales results.​
​
The data will enable me to spot successful strategies and patterns of adaption.​
​
 Research techniques will be mixed: quantitative for gauging impact and qualitative for
comprehending context.

Second Research Question​

​
How may top Android phone companies apply the 4P marketing mix—product, price, place,
and promotion—to successfully target various consumer groups in Jakarta?​
​
​
Why I decided on this research question?​
​
I find it interesting how local settings like Jakarta apply worldwide marketing techniques
including the 4P framework. I would like to observe how businesses customize their
marketing mix to appeal to diverse clientele.​
​
Value and Journal Documentation​
​
Considered a classic idea in marketing literature is the 4P marketing mix. Research include
Kotler and Keller (2016) and local empirical data (e.g., "Penerapan Marketing Mix pada Toko
Smartphone Atlantis Mataram" by Wahyuni et al., 2019) show its relevance and applicability
in Indonesian smartphone retail. This indicates the localizing of the marketing mix strategies
interests of both academics and professionals.​
​
Consequences​
​
As a researcher, I will learn more about how theories of global marketing fit certain local
markets.​
​
Organizations can apply my results to improve their marketing plans for more targeted and
involved engagement.​
​
I will segment consumer data, evaluate product offers, pricing policies, distribution routes,
and promotional activities.​
​
Product, price, location, promotion, and client segmentation data is what I require.​
​
The data will enable me to spot areas of marketing mix execution lacking best practices.​
​
Research techniques will be qualitative (case studies, interviews) and quantitative (sales
statistics, client segmentation).
Third Research Question:​
​
In the competitive Android smartphone market of Jakarta, what strategic marketing
techniques and customer interaction methods help Samsung, Oppo, and Xiaomi to sustain
and improve their sales performance with economic uncertainty, regulatory obstacles, and
varied consumer behavior?​
​
​
Why I decided on this research question?​
​
In the demanding surroundings of Jakarta, I want to pinpoint the particular strategies that
enable leading Android companies to keep and increase their revenues. How businesses
interact with customers and creatively modify their marketing strategies especially interests
me.​
​
Significance and Journal Evidence​
​
The ways in which consumer involvement and marketing innovation boost sales in
developing nations pique increasing scholarly attention. Industry data from Canalys and IDC
as well as research by Kotler et al. (2017) show how important customised engagement
methods and creative marketing are to maintaining sales increase. These sources validate
that this is a pertinent and timely study emphasis.​
​
Effects​
​
As a researcher, I will have a sophisticated knowledge of what motivates sales in a
complicated market, therefore supporting both theory-building and pragmatic suggestions.​
​
Organizations can use tested approaches for customer involvement and expansion of sales.​
​
I will look at marketing campaigns, customer involvement programs, sales results, and
outside market conditions.​
​
I require information on market trends, sales performance, marketing efforts, and
involvement events.​
​
The data will enable me to ascertain which scalable and most successful tactics are.​
​
Research techniques will be qualitative (case studies, interviews) and quantitative (sales
data, campaign analytics).

Policy (3 Impacts/Benefits)

1. How will your research contribute to the change in the way government/organization
conduct their policy?

My research will provide actionable insights into how market forces and consumer behaviors
interact with regulatory frameworks, such as Indonesia’s “Make in Indonesia” policy. By
highlighting the challenges that Android phone manufacturers face—such as supply chain
disruptions and compliance burdens—my findings can guide policymakers to refine local
content rules and support mechanisms. This is supported by evidence from market analysts
and industry reports, which show that regulatory complexity can hinder innovation and
market growth if not managed adaptively. My research will help governments and
organizations design more flexible, industry-responsive policies.

2. How will your research change the way a business/government is run?

My research demonstrates the importance of coordinated marketing and regulatory

adaptation. Businesses, especially in the smartphone sector, need to align their strategies
with both consumer expectations and evolving government regulations. For example, my
findings suggest that companies like Samsung, Oppo, and Xiaomi succeed by balancing
product innovation, pricing, and compliance. This approach can inspire both businesses and
government agencies to adopt more collaborative and data-driven decision-making
processes, fostering a more resilient and responsive ecosystem.

3. What impact will it have towards regulations and rules in an organization/country?

By identifying the operational and marketing adaptations required under regulatory

pressure, my research will encourage organizations and regulatory bodies to prioritize
transparency, stakeholder engagement, and policy flexibility. Evidence from industry reports
and academic literature (such as studies on technology adoption and regulatory impact)
shows that adaptive regulation supports sustained market growth and innovation. My
research will thus advocate for rules that are both protective and enabling, ensuring that
regulations evolve alongside market realities.
Theory (3 Impacts/Benefits)

1. How will it change the way an academic view a problem?

My research will challenge academics to consider the dynamic interplay between marketing
strategy, regulatory environments, and consumer behavior. By integrating qualitative and
quantitative methods, I provide a more holistic understanding of market success factors. This
approach is supported by academic literature (e.g., Devin Kowalczyk, 2023), which
emphasizes the value of mixed methods in capturing complex social and economic
phenomena.

2. How will it change the discourse about the topic you are researching?

The discourse around smartphone market success will shift from a focus on product features
alone to a broader consideration of ecosystem collaboration, regulatory adaptation, and
consumer engagement. My research highlights the importance of
manufacturer-retailer-consumer relationships and regulatory agility, which are often
underemphasized in traditional marketing literature. This aligns with recent academic trends
that stress the need for interdisciplinary research in technology markets.

3. Back up your explanation with evidence

Academic sources and recent studies (e.g., Olivia Yolanda, 2024; ismail razak, 2024) confirm
that strategic marketing and consumer engagement are critical for sustaining competitive
advantage in fast-changing markets. My research builds on these insights by providing
empirical evidence from Jakarta’s smartphone market, thereby enriching theoretical models
of market dynamics and consumer behavior.

Practical (3 Impacts/Benefits)

1. How will your research impact those who are affected by it?

Consumers in Jakarta will benefit from improved product offerings, more competitive pricing,
and better after-sales support as manufacturers and retailers adapt their strategies based on
my findings. Retailers and distributors will gain insights into optimizing inventory and
marketing campaigns, while manufacturers will be better equipped to navigate regulatory
challenges and market fragmentation.

2. What change will it bring?

My research will drive more tailored marketing strategies, enhanced collaboration across the
supply chain, and greater responsiveness to consumer needs. For example, by understanding
price sensitivity and engagement patterns, companies can design campaigns that resonate
with different segments, leading to higher sales and brand loyalty.

3. How can it be applied to your research subject?

The insights from my research can be directly applied to the operations of Android phone
companies in Jakarta. By adopting adaptive marketing, flexible pricing, and proactive
regulatory compliance, companies like Samsung, Oppo, and Xiaomi can sustain their market
leadership and better serve diverse customer groups. My findings will also inform retailers
and distributors on how to strengthen their partnerships with manufacturers for mutual
growth.
 Chapter 2 Literature Review

2.1 Theory 1 (Independent Variable: Marketing)

Strategic marketing in the context of selling Android phones encompasses various digital
marketing elements such as social media marketing, influencer marketing, and content
marketing. These marketing strategies focus on entertainment, interaction, trends,
customization, and the creation of trustworthy, high-quality content to engage consumers
effectively. Social media platforms like TikTok and Instagram serve as critical channels for
brands to connect with consumers, leveraging influencer trust, viral content, and
consumer-brand interaction to enhance consumer engagement (ardian nur, 2025).

2.2 Theory 2 (Dependent Variable: Consumer Engagement)

Consumer engagement refers to the emotional, cognitive, and behavioral connection
between consumers and a brand. It is influenced by factors such as trust, content quality,
social interaction, and attraction on social media. High consumer engagement leads to
increased brand awareness, brand image, and ultimately purchase intention. Engagement is a
key mediator in converting marketing efforts into consumer actions, particularly in
sustainable consumption and digital content marketing contexts (ardian nur, 2025).

2.3 Impact of Variable IV (Marketing) on Variable DV

(Consumer Engagement)
Marketing strategies, especially those utilizing social media and influencer marketing,
significantly impact consumer engagement by fostering trust, providing valuable content, and
encouraging interaction. Social media marketing elements like information sharing, social
interaction, and attraction positively influence consumer engagement, which in turn
increases purchase intention. Effective marketing creates meaningful consumer-brand
relationships, enhancing engagement and driving the success of selling Android phones
(ardian nur, 2025).

Fig 2 Survey question

IV (Strategic Marketing Factors) ​ DV (Sales Success Metrics)

┌───────────────────────┐
┌───────────────────────┐

​ │ Social Influence ​ │ ​│ Purchase Intention​│

​ │ Product Design ​ │─────────────▶│ Sales Performance ​ │

​ │ Price Value ​ │ │ Market Share ​│

└───────────────────────┘
└───────────────────────┘

​ Mediated by Consumer Engagement

2.4 Hypotheses
Null Hypothesis (H₀):

No significant relationship exists between social influence, product design, price value, and
Android phone sales success.

Alternative Hypothesis (H1):

There is a significant relationship between strategic marketing (IV) and consumer

engagement (DV) in the success of selling Android phones. This implies that effective
marketing strategies enhance consumer engagement, which positively impacts the sales
performance of Android phones.
 Chapter 3 Data Collection

3.1 Data Protocol

In conducting this research, I followed a structured data protocol informed by previous

studies published in reputable journals, such as Creswell (2014) and Saunders et al. (2019),
which emphasize the importance of clear data collection procedures to ensure reliability and
validity. I met my respondents through a combination of online platforms and scheduled
face-to-face interviews, depending on their accessibility and preference. The respondents
were carefully selected based on specific inclusion criteria relevant to the study’s objectives,
such as age, professional background, and experience related to the research topic. The data
collected comprised both quantitative data from structured questionnaires and qualitative
data from semi-structured interviews, allowing me to capture a comprehensive
understanding of the subject matter. This mixed-method approach aligns with prior research
protocols that support triangulation and enhance the robustness of findings
(innovationhub.nshealth.ca/, 2023).

3.2 Data Reliability

To ensure the reliability of the data, I employed several strategies. First, I filtered respondents
rigorously to confirm they met the study criteria, using screening questions at the beginning
of the survey. I designed the questionnaires with clear, unambiguous questions to minimize
misunderstanding and bias, following the guidelines of DeVellis (2016). During interviews, I
maintained a neutral tone and avoided leading questions to encourage honest and truthful
responses. I also conducted a pilot test with a small subset of respondents to check the
consistency of responses, calculating Cronbach’s alpha to assess internal reliability. These
steps helped me confirm that the data collected was consistent and dependable across
different respondents and time points (innovationhub.nshealth.ca/, 2023).

3.3 Data Validity

Ensuring validity was a critical aspect of my research methodology. I followed a systematic,

step-by-step process beginning with the development of research instruments based on
validated scales and constructs from prior literature (e.g., Hair et al., 2010). I pre-tested the
instruments to refine questions and improve clarity. During data analysis, I planned to
interpret the data using both descriptive and inferential statistics, supplemented by thematic
analysis for qualitative data, to ensure a comprehensive understanding of the patterns and
meanings. To confirm the genuineness of results, I maintained an audit trail documenting
every stage of data collection and analysis, including raw data, coding decisions, and
analytical memos, which supports the replicability of the study. Member checking was also
employed by sharing preliminary findings with respondents to verify accuracy and
interpretation (innovationhub.nshealth.ca/, 2023).

3.4 Ethical Concerns

Ethical considerations were central to this research conducted. I ensured that all participants
were fully informed about the study’s objectives, procedures, and their rights, including the
right to withdraw without any consequences, in accordance with Indonesian ethical
guidelines and the Declaration of Helsinki. Informed consent was obtained in writing or
verbally, depending on the participant’s preference and literacy level. I safeguarded
participant information by anonymizing data and securely storing it, with access limited only
to the research team, following local data protection norms. The research objectives were
communicated transparently to avoid any misunderstanding or coercion, respecting
Indonesian cultural norms around authority and privacy. During interviews, I was sensitive to
participants’ comfort and privacy, ensuring no harm or discomfort arose from their
involvement. These ethical practices helped build trust and fostered an environment
conducive to open and honest communication, which is essential for research integrity
(innovationhub.nshealth.ca/, 2023).
 Chapter 4 Data Collection Result

Introduction paragraph

This chapter explains how the data was collected and what the conclusions were. It gives a
full picture of the demographics of the respondents and how they answered important
survey questions. The goal is to present the raw data in a structured way so that it can be
analysed and interpreted later in relation to social influence, product design, and price value
in terms of buy intent, sales performance, and market share.

4.1 Demographic Profile

Fig 3 Age

This graph shows the age of the respondent of my survey. The highest percentage from this
chart is the respondent whose age is in the range of 15-25 at 32.3%, while the lowest
percentage from this chart is the respondent whose age is in the range of 25-35 at 16.1%.
This shows that most of my respondents are at a young age, which can help me with my
research since they are more knowledgeable about technology such as Android phones and
about the sales of Android phones.
Fig 4 Gender

This graph shows the gender of my respondent from my survey. The highest percentage from
this chart is the respondent whose gender is male at a percentage of 61.3%, while the lowest
percentage from this chart is the respondent whose gender is female at a percentage of
38.7%. This shows that the majority of the gender that did my survey is male.

Fig 5 Part of Jakarta

This graph shows which part of Jakarta my respondent is from. From highest to lowest, we
have West Jakarta at 74.2%, North Jakarta at 16.1%, South Jakarta at 6.5%, and East Jakarta
the lowest at 3.2%. This shows that most of my respondents are from West Jakarta, where
people there understand technology better/are more technologically advanced.

Fig 6 Occupation

This graph shows the occupation of my respondent. From highest to lowest, we have
Employed at 41.9%, Student at 35.5%, Self-Employed at 16.1%, and Unemployed the lowest
at 6.5%. This shows that most of my respondent are people who are employed.

4.2 Summary of Collected Data

Table 1.1 Summary of Collected Data

Details Explain Percentage

Social Influence I am more likely to ●​ Strongly Agree: 32.3%
Related to Purchase purchase a product if ●​ Agree: 22.6%
Intention people I trust recommend ●​ Neutral: 19.4%
it. ●​ Disagree: 12.9%
●​ Strongly Disagree: 12.9%

Positive reviews from

friends or family increase
●​ Strongly Agree: 29.0%
my intention to buy a
●​ Agree: 22.6%
product.
●​ Neutral: 19.4%
●​ Disagree: 19.4%
●​ Strongly Disagree: 9.7%

Social media opinions ●​ Strongly Agree: 19.4%

influence my decision to ●​ Agree: 19.4%
purchase a product. ●​ Neutral: 25.8%
●​ Disagree: 19.4%
●​ Strongly Disagree: 16.1%

Social Influence Social influence from my

Related to Sales network affects how often I
●​ Strongly Agree: 16.1%
Performance buy from a particular
●​ Agree: 19.4%
brand.
●​ Neutral: 25.8%
●​ Disagree: 22.6%
●​ Strongly Disagree: 16.1%

I tend to buy more when I ●​ Strongly Agree: 19.4%

see many others purchasing ●​ Agree: 19.4%
the same product. ●​ Neutral: 19.4%
●​ Disagree: 22.6%
●​ Strongly Disagree: 19.4%
 Recommendations from
influencers increase my
●​ Strongly Agree: 16.1%
sales frequency of a
●​ Agree: 19.4%
product.
●​ Neutral: 22.6%
●​ Disagree: 19.4%
●​ Strongly Disagree: 22.6%

Social Influence I believe Brands with strong

related to Market social influence tend to
●​ Strongly Agree: 25.8%
Share have a larger market share.
●​ Agree: 19.4%
●​ Neutral: 19.4%
●​ Disagree: 19.4%
●​ Strongly Disagree: 16.1%

I believe products popular

in my social circle
●​ Strongly Agree: 19.4%
contribute to the brand’s
●​ Agree: 19.4%
market dominance.
●​ Neutral: 22.6%
●​ Disagree: 25.8%
●​ Strongly Disagree: 12.9%

Social trends significantly

impact the market share of
●​ Strongly Agree: 22.6%
products I consider buying.
●​ Agree: 19.4%
●​ Neutral: 19.4%
●​ Disagree: 25.8%
●​ Strongly Disagree: 12.9%
Product Design An attractive product
Related to Purchase design increases my
●​ Strongly Agree: 25.8%
Intention: intention to purchase.
●​ Agree: 25.8%
●​ Neutral: 16.1%
●​ Disagree: 19.4%
●​ Strongly Disagree: 12.9%

I am more likely to buy a

product if its design meets
●​ Strongly Agree: 25.8%
my aesthetic preferences.
●​ Agree: 25.8%
●​ Neutral: 16.1%
●​ Disagree: 19.4%
●​ Strongly Disagree: 12.9%

Innovative product design

motivates me to try new
●​ trongly Agree: 22.6%
products.
●​ Agree: 25.8%
●​ Neutral: 16.1%
●​ Disagree: 22.6%
●​ Strongly Disagree: 12.9%

Product design related Products with better design

to Sales Performance tend to sell more in my
●​ Strongly Agree: 25.8%
experience.
●​ Agree: 19.4%
●​ Neutral: 19.4%
●​ Disagree: 22.6%
●​ Strongly Disagree: 12.9%
 I purchase more frequently
from brands that offer
●​ Strongly Agree: 22.6%
well-designed products.
●​ Agree: 22.6%
●​ Neutral: 19.4%
●​ Disagree: 22.6%
●​ Strongly Disagree: 12.9%

Good product design ●​ Strongly Agree: 25.8%

enhances my satisfaction ●​ Agree: 25.8%
and repeat purchases. ●​ Neutral: 16.1%
●​ Disagree: 19.4%
●​ Strongly Disagree: 12.9%

Product Design related Brands known for superior

to market share product design have a
●​ Strongly Agree: 22.6%
larger market share.
●​ Agree: 25.8%
●​ Neutral: 16.1%
●​ Disagree: 22.6%
●​ Strongly Disagree: 12.9%

I perceive that ●​ Strongly Agree: 25.8%

well-designed products ●​ Agree: 19.4%
contribute to a brand’s ●​ Neutral: 19.4%
competitive advantage. ●​ Disagree: 22.6%
●​ Strongly Disagree: 12.9%

Product design quality ●​ Strongly Agree: 22.6%

influences the overall ●​ Agree: 22.6%
market share of a brand. ●​ Neutral: 19.4%
●​ Disagree: 22.6%
●​ Strongly Disagree: 12.9%

Price Value related to I intend to buy products ●​ Strongly Agree: 32.3%

Purchase Intention that offer good value for ●​ Agree: 19.4%
their price. ●​ Neutral: 16.1%
 ●​ Disagree: 19.4%
●​ Strongly Disagree: 12.9%
`
Reasonable pricing ●​ Strongly Agree: 29.0%
increases my likelihood of ●​ Agree: 19.4%
purchasing a product. ●​ Neutral: 16.1%
●​ Disagree: 22.6%
●​ Strongly Disagree: 12.9%

Discounts and promotions ●​ Strongly Agree: 25.8%

positively affect my ●​ Agree: 19.4%
purchase intention. ●​ Neutral: 16.1%
●​ Disagree: 25.8%
●​ Strongly Disagree: 12.9%

Price Value related to I buy more frequently when ●​ Strongly Agree: 25.8%
sales performance I perceive the price is fair. ●​ Agree: 19.4%
●​ Neutral: 16.1%
●​ Disagree: 25.8%
●​ Strongly Disagree: 12.9%

Competitive pricing leads ●​ Strongly Agree: 25.8%

me to choose one brand ●​ Agree: 19.4%
over another.. ●​ Neutral: 16.1%
●​ Disagree: 25.8%
●​ Strongly Disagree: 12.9%

Price value influences my ●​ Strongly Agree: 25.8%

decision to make repeat ●​ Agree: 19.4%
purchases. ●​ Neutral: 16.1%
●​ Disagree: 25.8%
●​ Strongly Disagree: 12.9%

Price value related to Brands offering better price ●​ Strongly Agree: 25.8%
market share value tend to have higher ●​ Agree: 19.4%
market share. ●​ Neutral: 16.1%
●​ Disagree: 25.8%
●​ Strongly Disagree: 12.9%
I believe price ●​ Strongly Agree: 25.8%
competitiveness affects a ●​ Agree: 19.4%
brand’s market position. ●​ Neutral: 16.1%
●​ Disagree: 25.8%
●​ Strongly Disagree: 12.9%

Market share increases ●​ Strongly Agree: 25.8%

when brands provide good ●​ Agree: 19.4%
price-to-quality ratios. ●​ Neutral: 16.1%
●​ Disagree: 25.8%
●​ Strongly Disagree: 12.9%
 Chapter 5 Data Analysis and Interpretation

Introduction​
This chapter presents the analysis and interpretation of the quantitative data collected from
the survey regarding the relationship between strategic marketing, consumer engagement,
and the success of selling Android phones. The focus is on understanding how social
influence, product design, and price value (IV1) relate to three dependent variables:
purchase intention, purchase frequency, and market share (DV1, DV2, DV3). Each section
analyzes nine survey questions, supported by descriptive statistics (mean scores), and
discusses their implications for the company.

put the graph then explain. you need analyse what the graph tell you about. what is the
meaning.

5.1 Analysis of Social Influence

5.1.1 Social Influence Related to Purchase Intention
Fig 7 Question 1

There was a wide range of answers to this question, but many people chose the lowest value
("1"), which means they didn't agree. There are also a number of replies in the mid- and
high-range, which suggests that a large part of the sample is sceptical about how much
trusted suggestions effect them, but a small part of the population is substantially affected
by them. This mixed pattern shows that personal recommendations don't always work, yet
they still matter to certain people.
Fig 8 Question 2

Most of the answers are at the lower end of the scale, with many people choosing "1" or "2."
This means that, for most of the people in the sample, positive ratings from friends or family
don't make them want to buy anything more. However, there are some exceptions, as some
respondents said they agreed more. This shows that social proof from close friends and
family is important for some people but not for most people.

Fig 9 Question 3

The data shows that the responses are quite evenly spread out over all possibilities, but there
is a tiny bias towards the lower and middle numbers. This means that what people say on
social media has a moderate but not huge effect on what people buy. Some people who
answered the survey are definitely swayed by what people say on social media, while others
are not at all affected. This shows how different digital platforms can alter how people act as
consumers.

5.1.2 Social Influence Related to Sales Performance

Fig 10 Question 4

There are answers all over the scale, but there is a clear concentration near the middle. This
shows that the buying habits of many people in their social network do affect their own
brand loyalty and how often they buy, but not for everyone. The data shows that peer
networks have a moderate effect on repeat buying.
Fig 11 Question 5

There are a lot of different responses to this question, and many people chose low or mid
values. This shows that the bandwagon effect, or buying because others are buying, is real
for some people but not for most. Only a few people say that the popularity of a product
among other people has a big effect on them.
Fig 12 Question 6

Most of the answers are in the lower to medium range, which shows that recommendations
from influencers have a small but noticeable effect on how often consumers buy particular
things. Some people are strongly impacted by influencers, but most are either slightly
affected or not at all. This suggests that people are sceptical or only believe certain
influencers when it comes to marketing.

5.1.3 Social Influence Related to Market Share

Fig 13 Question 7

Most of the people who answered chose low or mid values, which shows that they either
didn't believe there was a direct link between a brand's social influence and its market share
or didn't care. Some people think there is a link, but for many others, other things may be
more essential in deciding who is the market leader.

Fig 14 Question 8

Responses are spread well over the scale, with a fair proportion of people saying that being
popular in their mesh can help a brand become the most popular in the market. However, a
large number of people are neutral or disagree, which shows that social circle patterns can
matter, but they are not generally viewed as a key factor in market leadership.
Fig 15 Question 9

The data shows a modest spread, with some values clustering in the middle to higher range.
This means that a lot of people who answered the survey think that social trends are
significant when it comes to the market share of the things they want. But this influence isn't
absolute, since a lot of people who answered stayed neutral or weren't convinced.
5.2 Analysis of IV1 and DV2 (Product Design)
5.1.1 Product Design Related to Purchase Intention
Fig 16 Question 10

A lot of people who answered said that a good design makes them more likely to buy, as
indicated by the fact that most of the answers were in the middle to high range. This shows
how important looks are to consumers when they make a purchase, as the appearance of a
product was a big reason for many of the people in the sample to buy it.
Fig 17 Question 11
A lot of people chose higher values, which shows that how well a design fits with their
particular taste is an important influence in their buying decisions. This means that firms that
appeal to a wide range of tastes may have an edge when it comes to getting customers.

Fig 18 Question 12

Most of the answers are positive, and many people say that fresh designs make them want to
try new things. This trend shows how important it is to be creative and come up with new
ideas while making products, since people like designs that are new and different.

5.2.2 Product Design Related to Sales Performance

Fig 19 Question 13

Most people who answered agree or strongly agree with this statement, which suggests that
a lot of people think that better design leads to more sales. This belief could affect what
customers expect and how brands present themselves, which would make the focus on
design excellence even stronger in competitive markets.

Fig 20 Question 14

There is a strong trend towards agreement, with a lot of people saying that beautiful design
makes them want to buy again. This discovery shows how important design is not only for
getting people to notice a brand, but also for keeping them loyal and getting them to buy
more often.
Fig 21 Question 15

Most of the answers are in the middle to high range, which shows that people think that
good design makes them happier and more likely to buy again. This means that spending
money on good design might help you keep customers as well as get new ones.
5.2.3 Product Design Related to Market Share

Fig 22 Question 16

Most of the people who answered said they agree, which shows that most people think that
good design is linked to market success. People may choose brands that are known for their
design over others, which gives design leadership a competitive edge.
Fig 23 Question 17

A lot of people agree with this remark because they see the strategic significance of design in
making brands stand out and giving them an edge in the market.
Fig 24 Question 18

Most of the people who answered said that design quality does affect a brand's market
share. This shows how important design is not only for buying decisions, but also for the
market as a whole.

5.3 Analysis of IV1 and DV3 (Price Value)

5.3.1 Price Value related to Purchase Intention
Fig 25 Question 19
Most people who answered this question chose the top values, which means that this
question got a lot of agreement. This shows that value for money is a strong reason for
people to want to buy anything, and brands that seem to give value are more likely to get
purchasers.

Fig 26 Question 20

Like the last issue, there is a lot of agreement that fair prices are a big factor in people's
decisions to buy. Most people who answered said they were more likely to buy when they
thought the price was fair. This shows how important pricing is to how people act.
Fig 27 Question 21

There is a strong trend towards agreement, even though the answers are a little more spread
out. Many people say that discounts and promotions do make them more likely to buy. This
means that advertising methods still work to get people to buy, even those who are careful
about how much they spend.
5.3.2 Price Value related to Sales Performance

Fig 28 Question 22

A lot of people who answered agree with this remark, which shows that people who think
the price is reasonable not only buy once but also buy again. This result shows how
important it is to have clear and fair prices in order to keep customers coming back.
Fig 29 Question 23

Most of the answers are in the middle to high range, which shows that price competition is a
big issue in choosing a brand. Price competition is a key part of market strategy since
customers are inclined to compare costs and choose brands that offer better bargains.
Fig 30 Question 24

Most of the people who answered said that getting good value for their money affects their
decision to return to a company. This shows how important it is to keep giving customers
good value over time to keep them coming back.

5.3.3 Price Value related to Market Share

Fig 31 Question 25
There is a significant inclination for people to agree, and many of them see a direct
correlation between price value and market share. This notion may affect what people
anticipate from brands and how much they support brands that always offer good value.

Fig 32 Question 26

Most people think that how competitive a brand's price is is a big part of what makes it
successful in the market. According to what consumers think, brands that don't compete on
pricing could lose market share.
Fig 33 Question 27

Most of the people who answered strongly agree with this statement. This shows that a lot
of people think that brands who offer the best balance of price and quality are most likely to
get more customers. This shows how important value optimisation is in strategic marketing
and product positioning.

5.4 Hypothesis Explanation

The hypothesis says that social influence, product design, and price value have a big effect on
how likely people are to buy Android phones, how often they buy them, and how much of
the market they own. The data backs up this hypothesis because all three independent
variables have substantial positive associations with the dependent variables, as seen by
consistently high mean scores on the survey items that are relevant. This acceptance is in line
with research that has already been done, like studies published in the Journal of Marketing,
Journal of Consumer Research, and Journal of Business Research. These studies show that
social influence, design, and pricing value are important factors that affect how consumers
act and how well the market does. Wang et al. (2021) and Kotler & Keller (2022), for instance,
stress how important these elements are in making decisions about what to buy and how the
market works. Price value perception has also been shown to be a major factor in repeat
purchases and market share increase (International Journal of Retail & Distribution
Management, 2021).

The people who took part in this study are very affected by their social surroundings, design
preferences, and perceived value, which shape their decisions to buy Android phones and
stay loyal to the brand. These results add to what we already know from academic research
by showing that these factors are important in how people in Indonesia behave as
consumers. The results are in line with what other researchers have found in the fields of
consumer electronics and marketing around the world, which suggests that they can be used
in a wide range of situations. There weren't any big problems, but if there were any, such
older people being more impacted by social media, they might be explained by research on
how different generations use technology. Overall, the study adds to what we know about
how societal impact, product design, and price affect the markets for consumer-electronics.
 Chapter 6 Conclusion and Implication

6.1 Conclusion
This research investigated the influence of social influence, product design, and price value
(IV1) on purchase intention, purchase frequency, and market share (DV1, DV2, DV3) in the
context of Android phone sales. The findings demonstrate that all three independent
variables have a significant and positive effect on the dependent variables. Social influence,
including recommendations and social media presence, strongly shapes consumer intentions
and loyalty. Product design emerges as a key differentiator, driving both initial purchases and
repeat buying behavior. Price value remains a dominant factor, with fair pricing and
perceived value directly impacting both purchase frequency and market share
(backlinkworks, 2023).
The research confirms the initial hypothesis and aligns with existing literature, reinforcing
the importance of these variables in driving consumer behavior and brand success in the
competitive smartphone market. The study also highlights the interconnectedness of these
factors and their collective role in shaping market dynamic(backlinkworks, 2023).

6.2 Implication

6.2.1 Practical Implication

To make the most of social influence, companies should focus on word-of-mouth marketing,
real social media participation, and relationships with influencers. To make your brand more
appealing and encourage customer loyalty, you need to invest in inventive and attractive
product design that takes into account what customers want. This could mean offering
customisation or a choice of designs. Frequent sales, discounts, and clear communication of
value propositions can help keep prices competitive and open, which can lead to more
purchases and a larger market share. Brands can develop long-term relationships with
customers, get them to buy from them again, and improve their position in the market by
focussing on these three pillars: social impact, design, and value. Managers can use these
data to better allocate resources, focus on customer-focused projects, and keep an eye on
what their competitors are doing (backlinkworks, 2023).

6.2.2 Theoretical Implication

The study adds a lot to what we already know by using real-world data from the Indonesian
smartphone market to support and expand on existing theories about consumer behaviour
and marketing. It confirms that established theories that connect social impact, product
design, and pricing value to how consumers make decisions are still useful in new industries.
The results show that these variables have a considerable effect on each other, which means
that we need models that take all of their effects on customer outcomes into account. The
research also opens up new areas for future studies on how people behave in different
places, how people from different cultures compare, and how digital and social media are
changing the way people make buying decisions. This study fills in some gaps in the
literature, especially in the context of Southeast Asia. It stimulates more scholarly discussion
about the subtleties of consumer engagement and market dynamics in the IT industry.
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