Analysis of the Advantages and Disadvantages of Ecosystem Chain

Coupling: A Case Study of Xiaomi Smart Home

Chenyang Mao

School of Cyber Science and Engineering, Nanjing University of Science and Technology, Shengli Village Road, Xuanwu

District, China

Keywords: Coupling Degree, Economic Benefits, Smart Home, Mi Home Ecosystem.

Abstract: With the rapid development of the technology industry, Xiaomi has attracted numerous companies to its smart

hardware and consumer goods network through its unique ecosystem model. This paper focuses on Xiaomi's

smart home ecosystem to explore the degree of coupling between Xiaomi and its ecosystem companies in

terms of technology reliance, data sharing, and supply chain integration, and how these relationships impact

the companies' economic performance. The study adopts a qualitative analysis approach, analyzing typical

cases such as Huami and Roborock, and, combined with literature review and ecosystem theory, reveals that

high coupling can help companies reduce costs and rapidly capture the market in the short term, but may also

limit their independence and compress profit margins in the long term, even causing data privacy disputes.

The research further indicates that Xiaomi's ecosystem success is due to dynamic coupling management.

Companies need to adjust strategies based on their development stage to achieve sustainable growth. This

paper aims to provide practical insights for the collaborative development of ecosystem companies while

contributing new thoughts on the competition and cooperation mechanisms in the platform economy.

1 INTRODUCTION

The smart home industry is developing rapidly,

driven by the integration of the Internet of Things

(IoT) and Artificial Intelligence (AI), enabling

innovations ranging from smart speakers to wearable

devices. According to industry reports, the global

market size surpassed $150 billion in 2023, with an

annual growth rate of about 18%. Xiaomi has built a

network covering home appliances and transportation

tools through its "hardware + software + services"

ecosystem model, integrating resources. In contrast to

Apple's closed ecosystem (focused on self-developed

integration) and Huawei's open-source HarmonyOS

(emphasizing cross-device connectivity), Xiaomi's

ecosystem is "open but tightly coupled." Xiaomi

accelerates the incubation of businesses by sharing

technology and supply chains but also faces issues

such as brand dilution and risk transmission. Studying

the coupling degree of Xiaomi's ecosystem not only

reveals the mechanisms behind its success but also

provides references for the design of smart hardware

ecosystems to mitigate risks. By 2023, Xiaomi had

https://orcid.org/0009-0002-9211-9473

invested in over 300 companies, generating over 120

billion yuan in revenue in 2022, with successful cases

including Huami and Roborock. High coupling

promotes collaborative innovation; for example,

companies leverage the Mi Home IoT platform to

accelerate product development and optimize design

through data sharing. However, it also leads to

privacy concerns, such as the increased compliance

burden resulting from the EU GDPR review in 2020,

which led Huami to invest millions of dollars to revise

its data systems. In the supply chain, Xiaomi lowered

the entry barriers, but issues such as the 2021 chip

shortage led to delivery delays for many companies.

For example, Roborock’s revenue growth slowed by

about 10% in 2021, exposing dependency risks.

Roborock, which had overly relied on Xiaomi’s

channels in the early stages, faced limited brand

recognition. Its strategy of "de-Xiaomi branding"

helped strengthen brand independence, increasing its

gross margin from 15% to 50%, thus demonstrating

the value of managing coupling degrees.

The study of coupling degrees has both theoretical

and practical significance. Ecosystem theory suggests

482

Mao, C.

Analysis of the Advantages and Disadvantages of Ecosystem Chain Coupling: A Case Study of Xiaomi Smart Home.

DOI: 10.5220/0013847800004719

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on E-commerce and Modern Logistics (ICEML 2025), pages 482-487

ISBN: 978-989-758-775-7

that value creation relies on enterprise collaboration,

but high coupling may weaken autonomy (Adner,

2017). Research on the platform economy highlights

that core companies control ecosystems through

technology and data (Jacobides, 2018). Existing

studies have rarely focused on the multidimensional

coupling of smart hardware, and the Xiaomi case fills

this gap. This study, taking Xiaomi's smart home

ecosystem as a case, focuses on the coupling degree

of technology, data, and supply chains, exploring its

impact on profitability and competitiveness.

Practically, this research guides enterprises: during

the startup phase, coupling can reduce costs, while in

the mature phase, decoupling is necessary to enhance

competitiveness. Xiaomi's experience also offers

lessons for other industries, such as the new energy

vehicle sector. In the context of supply chain

fluctuations and stricter regulations, optimizing the

coupling degree is crucial for ecosystem governance

and industrial security.

2 LITERATURE REVIEW

Business ecosystems are economic communities

comprising multiple organizations and individuals,

including suppliers, manufacturers, competitors, and

other stakeholders, collaborating to create value

(Awano and Tsujimoto, 2021). Research highlights

that ecosystems transcend traditional industry

boundaries, strengthening interdependence and

symbiotic relationships among firms, and

emphasizing openness and collaboration (Adner,

2017). Key indicators include partner numbers,

network density, and a firm’s centrality in the

network. In business ecosystems, co-opetition

(cooperation and competition) is particularly

relevant, involving interconnected systems that form

a “co-opetition” structure (Riquelme, 2022). Firms

must balance value co-creation and competition,

relying on stakeholders to optimize business models

(Hannah & Eisenhardt, 2018; Zott and Amit, 2015).

Globalization and digitalization have shifted

competition from vertically integrated firms to

decentralized supply chain networks, fostering

platform ecosystems (Kapoor, 2021). Digital

platforms enable resource sharing and

complementary innovations through modular

technologies, such as smart devices expanding

functionality via applications, and enhancing user

experiences (Cenamor, 2021). Platform ecosystem

success depends on external complementary

networks, where third parties innovate to add value,

creating new market opportunities (Schreieck, 2021).

However, platform owners must balance value co-

creation and capture, as excessive control may stifle

co-creation, while excessive openness may reduce

profits. From an ecosystem perspective, platform

openness enhances hardware differentiation but

increases complementary ecosystem complexity,

creating friction between hardware development and

complement production, as hardware firms pursue

differentiation while complementors prioritize low-

cost, mass-market strategies (Chen, 2022).

The rapid advancement of IoT technology has

transformed the smart home industry (You, 2019).

Early smart home products focused on single

functionalities, whereas the current stage emphasizes

platform ecosystem integration (Tang and Inoue,

2021). Research identifies technical barriers—such as

inadequate device interoperability, installation

complexity, and obsolescence risks due to rapid

iteration-as constraints on ecosystem development

(Struckell, 2021). In IoT platforms like smart homes,

network effects from product technical

configurations enhance platform value, enabling

broader firm participation (Hein, 2018). Smart home

ecosystems often exceed individual firms’

capabilities, requiring external networks to converge

around standardized solutions or dominant designs,

providing essential resources (knowledge, data,

technology, and capital). However, excessive

standardization may lead to product homogenization,

compelling firms to pursue differentiation strategies

(Struckell, 2021).

Taking Xiaomi’s smart home ecosystem as an

example, its ecosystem connects diverse smart

hardware through a unified platform, with

smartphones as the core, integrating various product

categories under the Mijia brand. Xiaomi’s open

model attracts partners to launch innovative products,

supported by supply chain, funding, and sales

channels, significantly reducing operational burdens

for startups (Li, 2024). Its large user base and active

community provide market traction and brand

exposure. However, ecosystem firms may face

autonomy challenges due to over-reliance on

Xiaomi’s brand, with some encountering low gross

margins and limited market recognition when

developing their own brands, and certain products

even competing with Xiaomi (Huang, 2023).

Existing research provides a foundation for

analyzing the coupling degree of Xiaomi’s smart

home ecosystem, elucidating inter-firm collaboration,

platform economies, and IoT technology’s role in

smart homes. However, studies primarily focus on

single coupling dimensions, lacking systematic

exploration of multidimensional coupling and

Analysis of the Advantages and Disadvantages of Ecosystem Chain Coupling: A Case Study of Xiaomi Smart Home

483

dynamic management strategies. Current analyses

also underexplored the impact of high and low

coupling on innovation efficiency, ecosystem control,

and partner autonomy. This study evaluates the

multidimensional characteristics of Xiaomi’s

ecosystem coupling degree, explores dynamic

management pathways, and addresses these research

gaps.

3 COUPLING EFFECT ANALYSIS

3.1 Positive Effects: Resource Synergy

and Market Enablement

3.1.1 Technological Sharing Drives

Collaborative Innovation

Xiaomi’s smart home ecosystem reduces R&D costs

and accelerates product development through

technological sharing via the Mijia IoT platform. The

platform provides unified protocols, cloud services,

and AI algorithms, enabling firms to launch Mijia-

compatible hardware swiftly. For example,

Roborock’s Mijia robot vacuum utilized Xiaomi’s

SLAM algorithms and sensor modules, shortening its

R&D cycle from the industry standard of 18 months

to approximately 12 months between 2016 and 2018,

with R&D expenses at 5.3% of revenue, below the

industry average of 7% (Roborock 2018 Annual

Report; IDC, 2022). Ecosystem theory suggests that

technological coupling fosters collaborative

innovation, with device interconnectivity (e.g.,

smartphone control and speaker linkage) increasing

user interaction frequency and ecosystem stickiness

(Adner, 2017). However, reliance on Mijia protocols

may limit compatibility with non-Mijia ecosystems

(e.g., Amazon Alexa), requiring firms like Roborock

to develop additional firmware, and increasing costs.

Analysis indicates that technological sharing

significantly enhances efficiency, but firms must

invest in proprietary technologies to sustain long-

term competitiveness.

3.1.2 Data Integration Optimizes Product

Design

Xiaomi’s ecosystem leverages user data sharing to

help firms gain precise market insights, optimize

product functions, and enhance competitiveness. The

Mijia platform’s collection of user behavior data from

Xiaomi smartphones and smart devices provides

consumption preferences and usage patterns, guiding

product iteration. For instance, Yeelight’s smart

lighting, informed by Xiaomi user data, developed

voice-controlled and scenario-linked lamps (e.g.,

brightness adjustment with Mijia speakers),

achieving significant sales growth (China Smart

Home Market Report, 2022). Data integration enables

rapid responses to user needs, such as Yeelight’s

family-oriented ambiance lamp series, enhancing

product differentiation.

3.1.3 Market Traction and Brand

Enablement

Xiaomi provides market exposure and sales support

through the Mijia brand and e-commerce channels,

significantly reducing marketing costs for startups

and enabling rapid market penetration. Platforms like

Xiaomi Mall and JD.com offer convenient entry

points, with Mijia’s brand endorsement boosting

consumer trust. For example, Huami leveraged

Xiaomi’s wearable brand effect and sales channels to

rank among the top five global wearable device

markets from 2015 to 2018, with a market share of

approximately 10% (Huami 2018 IPO Prospectus).

Market coupling provides startups with growth

shortcuts, with Huami’s early sales through Xiaomi

channels accounting for 80% of its total. However,

long-term reliance on Mijia’s brand may weaken

proprietary brand recognition, limiting premium

pricing (Schreieck, 2021). Huami’s promotion of its

Amazfit brand since 2018 reflects the need for

dynamic market coupling adjustments. Analysis

suggests that market traction accelerates expansion,

but firms must gradually build independent channels

to reduce coupling and enhance brand autonomy and

profitability.

3.2 Negative Effects: Dependency Risks

and Competitive Constraints

High coupling, while yielding synergistic benefits,

also introduces risk propagation, autonomy

constraints, and privacy controversies, particularly

evident in mature firms or during external disruptions.

The following analyzes three sub-dimensions.

3.2.1 Supply Chain Risk Propagation

Xiaomi ecosystem firms, heavily reliant on a unified

supply chain, face significant risk propagation during

global supply chain disruptions, resulting in

production delays and cost surges. The 2021 global

chip shortage broadly impacted Xiaomi’s ecosystem,

with firms dependent on core suppliers (e.g.,

Qualcomm, MediaTek) experiencing rapid disruption

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propagation. For instance, Roborock’s robot vacuums

faced production constraints due to chip shortages,

with third-quarter 2021 net profits declining 20%

year-on-year (Roborock 2021 Q3 Report). Gartner’s

Global Semiconductor Market Report (2021) notes

that chip shortages extended smart home industry

delivery cycles by an average of 30%. Supply chain

coupling optimizes costs through centralized

procurement but exposes vulnerabilities under

external shocks, with single-supplier dependence

exacerbating production uncertainty. Roborock’s

supply chain diversification since 2022, incorporating

non-Xiaomi suppliers, mitigated risks. Analysis

suggests that high-coupling supply chains enhance

efficiency but require diversified layouts to reduce

risk propagation and strengthen ecosystem resilience.

3.2.2 Brand Dependency and Autonomy

Constraints

Xiaomi ecosystem firms, deeply reliant on Mijia’s

brand and channels, face challenges of limited

proprietary brand recognition and constrained gross

margins, particularly in the mature stage. While

Mijia’s endorsement aids market entry, long-term

dependency weakens brand autonomy and premium

pricing. For example, Huami’s Xiaomi wearable

products achieved rapid sales growth from 2015 to

2018, but its 2018 launch of the Amazfit brand faced

low market recognition and below-average gross

margins (Huami 2019 Annual Report). To reduce

brand dependency, Huami increased investments in

proprietary channels and expanded overseas, raising

gross margins to 40% by 2024, with proprietary brand

products accounting for over 85% of revenue (Huami

2024 Annual Report). Research indicates that

independent brand firms achieve average gross

margins of 45%, while ecosystem firms typically lag.

Brand coupling aids market penetration in the startup

phase but constrains globalization and premium

pricing in maturity. Analysis suggests firms must

pursue brand independence and channel

diversification to reduce coupling, enhancing

competitive advantage and long-term growth

potential.

3.2.3 Data Privacy and Regulatory Pressure

High coupling in Xiaomi’s ecosystem enhances

product intelligence through data sharing but raises

user privacy controversies and regulatory pressures,

increasing compliance costs. The Mijia platform’s

unified data management enables device

interconnectivity and functionality optimization but

risks privacy breaches due to centralized storage. The

2020 EU GDPR review scrutinized Xiaomi

ecosystem firms’ data sharing, with Huami investing

approximately $5 million to overhaul its data systems,

resulting in a 15% net profit decline in 2020 (Huami

2020 Annual Report). Forrester’s Global Data

Privacy Report (2021) indicates that smart home

industry compliance costs due to privacy issues rise

20% annually. Such incidents increase operational

burdens, with some firms redesigning data

architectures to meet regulatory requirements. While

data coupling enhances product competitiveness,

privacy controversies may erode consumer trust and

brand image. Analysis suggests firms must optimize

data management, such as adopting localized storage

or anonymization, to mitigate regulatory risks while

balancing data sharing and privacy protection for

ecosystem sustainability.

4 RECOMMENDATIONS

Based on the analysis of the positive and negative

effects of Xiaomi’s smart home ecosystem coupling

degree, this chapter offers practical recommendations

from the perspectives of ecosystem firms and the

platform (Xiaomi). These aim to help firms balance

resource dependency and autonomy across

development stages, enhance competitiveness, and

guide Xiaomi in optimizing ecosystem rules to

improve overall resilience. Recommendations are

divided into startups, mature firms, and the Xiaomi

platform.

4.1 Startups: Leverage High Coupling

for Rapid Expansion

Startups with limited resources should fully utilize

Xiaomi’s high-coupling advantages, leveraging

technology, data, and market support to enter markets

quickly while building core technologies to mitigate

long-term dependency risks. Xiaomi’s Mijia IoT

platform and supply chain support significantly

reduce R&D and procurement costs. Firms should

collaborate deeply with Xiaomi, using unified

technical standards to develop products and Xiaomi’s

channels to boost sales. Simultaneously, firms must

invest in proprietary technology patents to avoid

complete reliance on Xiaomi’s algorithms or

protocols. Resource dependency theory supports

startups leveraging external resources for competitive

advantage, but excessive dependency risks stifling

innovation (Pfeffer & Salancik, 2015). Firms should

develop technology reserve plans to lay the

Analysis of the Advantages and Disadvantages of Ecosystem Chain Coupling: A Case Study of Xiaomi Smart Home

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foundation for future decoupling within high-

coupling frameworks.

4.2 Mature Firms: Reduce Coupling to

Enhance Competitiveness

Mature ecosystem firms should reduce coupling with

Xiaomi through brand independence and channel

diversification to enhance premium pricing and

global competitiveness. Analysis shows that brand

dependency limited Huami’s gross margins, but its

self-built Amazfit brand and overseas channels

increased gross margins to 40% by 2024 (Huami

2024 Annual Report). Firms should gradually reduce

reliance on Mijia’s brand, increasing proprietary

brand marketing through social media and offline

stores. Expanding non-Xiaomi channels (e.g.,

Amazon, Walmart) mitigates market risks.

Ecosystem theory emphasizes that mature firms must

pursue differentiation to strengthen network

independence (Adner, 2017). Firms can emulate

Roborock’s “de-Xiaomi” strategy, with overseas

revenue accounting for 53% by 2024, surpassing

domestic markets (Roborock 2024 Annual Report).

Additionally, firms should establish proprietary data

systems, reducing reliance on Xiaomi’s user data,

such as adopting localized storage to comply with

GDPR. Lowering coupling enhances profitability and

market flexibility, enabling resilience to external

changes.

4.3 Xiaomi Platform: Dynamically

Adjust Ecosystem Rules

As the platform, Xiaomi should dynamically adjust

ecosystem rules to balance resource support and firm

autonomy, fostering overall ecosystem resilience and

sustainability. Xiaomi can adopt a tiered cooperation

model, offering high-coupling support (e.g.,

technology licensing) to startups and low-coupling

incentives (e.g., co-branding rather than binding) to

mature firms. Platform economy research suggests

that openness enhances ecosystem vitality (Jacobides,

2018). Xiaomi can emulate Huawei’s HarmonyOS

open strategy, encouraging firms to develop multi-

ecosystem-compatible products to reduce

technological risks. Additionally, Xiaomi should

strengthen data privacy management, establishing

transparent data-sharing protocols to address GDPR

and similar regulations. Dynamic rule adjustments

can enhance ecosystem innovation efficiency and risk

resistance, reinforcing Xiaomi’s competitive

advantage.

5 CONCLUSION

Using a qualitative analysis approach, this study

examines Xiaomi’s smart home ecosystem,

integrating literature reviews and case studies of

typical firms to systematically investigate the impact

of coupling degree across technology, data, supply

chain, and market dimensions on firms’ economic

performance. The findings indicate that high coupling

in the startup phase significantly reduces costs and

accelerates market penetration through resource

sharing and market traction. However, long-term high

coupling may restrict firm autonomy, trigger privacy

controversies, and expose supply chain risks. The

study elaborates on the “double-edged sword” effect

of coupling: technological sharing drives

collaborative innovation but may limit cross-

ecosystem compatibility; data integration optimizes

product design but increases privacy compliance

costs; supply chain coupling enhances efficiency but

is vulnerable to external disruptions; and market

traction aids expansion but fosters brand dependency.

Through multidimensional coupling analysis, this

study validates the dynamic applicability of resource

dependency and ecosystem theories, filling gaps in

smart home coupling degree research and offering

new perspectives on platform ecosystem

collaboration mechanisms.

Startups are advised to leverage Xiaomi’s

technological and market support for rapid market

entry while building proprietary technologies to

mitigate long-term dependency risks. Mature firms

should pursue brand independence and channel

diversification to reduce coupling, enhancing gross

margins and global competitiveness. Xiaomi, as the

platform, should dynamically adjust ecosystem rules

to balance resource support and firm autonomy.

Future research could explore quantitative

coupling degree evaluation methods, such as

developing a coupling degree index model to

precisely measure the intensity of technology, data,

and other dimensions and their dynamic impact on

firm performance. Practically, firms and platforms

should collaborate to develop multi-ecosystem-

compatible technical standards, enhancing product

interoperability to address global regulatory

tightening and market fragmentation.

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