Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 20, No. 2, 2025 70 Research on Collaborative Innovation of Clothing Sales Channels Under the OMO Model: Based on The Integration Practice of Offline Stores and Live E- Commerce Yutong Zhou School of Design, Pratt Institute, New York, USA Abstract: In the context of weak growth of traditional sales channels in the clothing industry and limitations in the development of live e-commerce, the OMO model has become the key to the transformation of the industry. This study focuses on the integration of offline stores and live e-commerce, analyzes the theoretical basis of the OMO model and its applicability in the clothing industry, and analyzes the current situation and integration issues of offline stores and live e-commerce. Taking Peacebird as an example, it summarizes the effectiveness of its OMO practice in finance, operations, organization, technology and other aspects, and points out the challenges faced in technology and interest coordination. The study confirms that the OMO model breaks data silos and reconstructs the collaborative mechanism through four-dimensional collaboration such as goods and marketing, significantly improves channel efficiency and consumer satisfaction, and is an important path for the digital transformation of the clothing industry. In the future, it can be further explored in the direction of intelligence and subdivided categories. Keywords: OMO model; Clothing sales; Offline stores; Live e-commerce; Collaborative innovation. 1. Introduction As an important field of traditional retail, the clothing industry has long relied on the dual channels of offline store experience and online e-commerce diversion. However, with the impact of consumption upgrading and digitalization, the traditional model faces growth bottlenecks: offline stores are constrained by high rents and scattered traffic, while online e- commerce is caught in homogeneous competition and rising customer acquisition costs. Although the rise of live streaming e-commerce has injected new momentum into the industry, its limitations of "low-price promotions" and "one- way traffic diversion" make it difficult to meet consumers' demand for seamless omni-channel experience [1]. In this context, the OMO (Online Merge Offline) model has become a key path to solve the industry's dilemma by deeply integrating online and offline resources and reconstructing the relationship between people, goods and places. This study focuses on the collaborative innovation of offline stores and live streaming e-commerce of clothing companies, aiming to explore practical strategies for deeply integrating online and offline resources, and provide theoretical support and practical reference for the digital transformation of the industry [1]. 2. Theoretical Basis of OMO Model 2.1. Definition of the Concept of OMO Model The OMO (Online Merge Offline) model is a business model that deeply integrates online and offline. Its core lies in achieving complementary advantages and coordinated development between online and offline through technical means and innovative operation strategies. In this model, the online platform not only serves as a sales channel, but also undertakes functions such as information dissemination, customer flow, and data analysis; offline stores are not only a place to display and sell products, but also an important platform for providing experience and services. Through the deep integration of online and offline, the OMO model can provide consumers with a seamless shopping experience and meet their needs in different scenarios [2]. 2.2. Analysis of the Applicability of the OMO Model in the Clothing Industry 2.2.1. Characteristics of clothing products Clothing is fashionable, experiential, and seasonal. Fashion requires companies to keep up with the market and promote new products; experiential requires providing physical experience to help consumer decision-making; seasonality requires flexible adjustment of inventory and marketing. Under the OMO model, online can quickly transmit fashion information and display new products, and offline can provide services such as trial wearing, and online and offline data sharing and inventory allocation can cope with seasonal changes and improve operational efficiency [3]. 2.2.2. Characteristics of clothing consumer groups Modern clothing consumer groups are showing a trend of being younger, more personalized, and more social. Young consumers prefer to obtain information and interact through social media, and have high requirements for shopping experience; personalized consumption requires customized products and services; social consumption makes consumers focus on interaction and sharing in shopping [2]. In the OMO model, online can attract young consumers through social media marketing, and offline can enhance personalized experience through customized services, which can meet personalized and social needs and improve loyalty and reputation [4]. 2.2.3. Industry trends The development of digital technology and changes in 71 shopping habits have promoted the development of the apparel industry towards digitalization and fast fashion. Digitalization changes the way of shopping, provides efficient operations and precise marketing methods, and fast fashion requires rapid response to market launches. As a direction of digital transformation, the OMO model can help companies achieve data-driven decision-making and improve supply chain flexibility and response speed [3]. 3. Analysis of the Current Status of Offline Clothing Stores and Live E- Commerce 3.1. Current Status of Offline Stores (1) Business layout and characteristics: Traditional offline clothing stores are distributed in layers according to the positioning of business districts. The core business districts are mainly brand flagship stores, focusing on scene display and high-end image building; community stores focus on fast fashion and mass brands, emphasizing convenience and adaptation to daily consumption scenarios. However, excessive reliance on physical space and geographical location has highlighted limitations under the wave of digitalization. (2) Core competitive advantages: Offline stores build irreplaceability with deep experience scenarios and instant services. Consumers can solve the pain point of "fit" by trying on clothes, and store staff can provide one-on-one dressing suggestions to enhance consumer trust. For example, Uniqlo combines "smart matching screen" with professional shopping guides to increase the conversion rate of try-on to 35%. At the same time, physical space is also an important carrier of brand culture. (3) Development difficulties and transformation needs: Offline stores are currently facing multiple challenges. The annual rent increase in the core business districts of first-tier cities has reached 8%, and the operating pressure has increased dramatically; traffic fragmentation has caused the cost of acquiring customers to soar, and the average annual decline in offline customer traffic is 15%; traditional promotional methods are difficult to reach young customers; inventory management is extensive, and the inventory turnover days of some companies exceed 90 days. These difficulties force companies to accelerate OMO transformation and seek online traffic and data-driven operational breakthroughs. 3.2. Current status of live e-commerce (1) Explosive growth: Since its inception in 2016, the scale of the live e-commerce market has surged from 433.8 billion yuan in 2019 to 4.9 trillion yuan in 2023, of which clothing categories account for more than 30%, becoming the main growth force. Platforms such as Tik Tok and Taobao help brands achieve "overnight sales" through algorithm recommendations and traffic support [4]. (2) Diversified operation models: Clothing live broadcasts are mainly live broadcasts by experts and self-broadcasts by merchants. The former relies on the influence of KOLs, makes profits through slot fees + commissions, and focuses on the promotion of new products; the latter emphasizes regular operations, which is conducive to private domain precipitation. Both use "limited-time discounts + speech guidance" to stimulate consumption and form a marketing closed loop. (3) Advantages and shortcomings coexist: Live e- commerce has significantly improved conversion rates and reduced marketing costs with strong interactivity and precise delivery, but the industry is in chaos. Some anchors exaggerate their publicity, resulting in a high return rate for clothing, and it is difficult to protect rights after sales, which affects consumer trust [5]. 3.3. The Current Situation of The Integration of The Two Some brands have transformed stores into live broadcast bases, such as URBAN REVIVO, which sets up live broadcast rooms in stores and uses real scenes to enhance the persuasiveness of products; the "online ordering + offline pickup" model has gradually become popular. Bosideng has realized the delivery of online orders to the nearest store through omni-channel inventory sharing, and the fulfillment time has increased by 40%. In addition, innovative forms such as the onlineization of offline activities and the feedback of online traffic to offline activities continue to emerge [5]. 4. Summary of OMO Experience and Challenges Faced by Clothing Companies 4.1. Case Effectiveness Evaluation and Experience Summary 4.1.1. Quantitative evaluation of collaborative innovation effectiveness Financial data performance: Since the launch of the OMO strategy in 2018, the average annual growth rate of online channels has exceeded 30%. In 2022, online sales accounted for 42%, driving overall revenue to exceed 8.5 billion yuan and net profit to increase by 15% year-on-year. Through live broadcast and community operations, its online conversion rate during the "Double Eleven" period increased to 18%, and the average customer price increased by 20%. Optimization of operating indicators: Through the "cloud warehouse + store" model, Peacebird's inventory turnover rate was shortened from 120 days to 75 days, and the proportion of unsaleable items decreased by 10%; offline stores increased customer traffic by 35% and the try-on conversion rate reached 65% through the "online appointment and try-on" function. Improved customer satisfaction: According to a 2022 customer survey, the satisfaction of PEACEBIRD's OMO model reached 89%, among which "seamless return and exchange" and "cross-channel service" received the highest experience scores, and the repurchase rate increased by 12% year-on-year. 4.1.2. Summary of key factors for success Flexible adjustment of organizational structure: Establish an "OMO Strategic Committee" to integrate the resources of the e-commerce department, store retail department, and IT department to break down departmental barriers. For example, connect online live broadcast orders with offline store inventory to achieve "nearby delivery". In-depth application of technological innovation: Introduce Alibaba Cloud's "intelligent order distribution system" and combine RFID technology to track product dynamics in real time; develop the "PEACEBIRD Member" applet to integrate online and offline consumption data and build user portraits. Scenario-based marketing innovation: Through the "store 72 live broadcast + celebrity store visit" model, offline activities are converted into online traffic. For example, the 2021 joint spokesperson Zhang Liang's live broadcast attracted more than 5 million online viewers, and simultaneously guided them to try on stores across the country, driving a 40% increase in sales that month. 4.2. Challenges 4.2.1. Technical difficulties Data security and system compatibility: When online and offline data are interconnected, inventory synchronization was delayed due to the instability of the third-party system interface, which triggered consumer complaints; user privacy protection needs to balance data utilization and compliance risks. Difficulty in implementing intelligent tools: Some store employees are not proficient in the operation of tools such as smart fitting mirrors and AR virtual matching, and the technical value has not been fully released. 4.2.2. Conflicts in interest coordination Channel conflicts: Online promotional activities have caused dissatisfaction among dealers, who believe that they damage the offline price system; disputes over the ownership of live broadcast orders have led to conflicts in the distribution of interests between stores and e-commerce departments. Insufficient motivation for dealers: Some franchisees are worried about online diversion and have low cooperation with the OMO strategy, which affects the overall synergy effect. 4.2.3. Talent shortage bottleneck Lack of compound talents: There is a shortage of talents who understand live broadcast operations, private domain management, and can lead offline experience design, resulting in the reliance of external operation teams for strategy execution. Inertia of traditional thinking: Some store guides have low acceptance of the "online traffic diversion and offline service" model and still tend to think in terms of single channel sales. 4.2.4. Consumer cognition and habit barriers Trust issues: Consumers in third- and fourth-tier cities are skeptical about the "online order and store pickup" model and are worried about differences in service quality; middle-aged and elderly customers are unfamiliar with the operation of mini-programs and prefer cash transactions. High cost of habit change: Traditional offline shoppers find it difficult to adapt to the "online appointment first and then try on" process, resulting in some traffic loss. 4.3. Countermeasures Technical breakthroughs and security assurance require a two-pronged approach. On the one hand, blockchain technology is used to encrypt user data, AI risk control systems are deployed to monitor abnormal access, and open platforms to break through the data barriers of Tmall, Tik Tok and store POS systems; on the other hand, the operation of smart devices is simplified, and the digital operation capabilities of employees are improved through a three-level training system of "headquarters-region-store". The reconstruction of the profit distribution mechanism emphasizes dynamic balance, establishes a commission model of "15% commission for online live broadcast orders returned to stores + offline shopping guides guide registered members to earn points", and sets up a "global sales bonus pool" to bind employee income and overall performance; implements the product differentiation strategy of "online exclusive + offline experience", and clearly divides channel positioning to avoid direct competition. The construction of the talent echelon focuses on the combination of internal and external, cooperates with universities to open "OMO operation" targeted courses, cultivates compound talents who understand live broadcast and community operation, and implements "online mentor + offline coach" dual-track training internally; at the same time, introduces high-end talents in the Internet industry as project directors to coordinate the implementation of global strategies and technologies. Consumer education and experience upgrades focus on scene penetration and trust building. "AR virtual fitting areas" are set up in stores and "online coupon collection - offline verification" activities are carried out to guide users to experience the OMO process; through the "omni-channel worry-free return and exchange" policy, consumer concerns are eliminated, and the shopping habits of conservative users are gradually changed with the help of word-of-mouth communication 5. Conclusion and Outlook 5.1. Research Conclusion The OMO model significantly improves the efficiency of clothing channels through the four-dimensional collaboration of goods, marketing, experience, and supply chain: through omni-channel inventory sharing, companies such as Peacebird have reduced inventory turnover from 120 days to 75 days, and cross-channel sales have increased by 40%; in terms of consumer experience, seamless returns and personalized services have increased satisfaction to 89%. The core innovation lies in breaking the online and offline data silos, reconstructing organizational coordination mechanisms, and relying on technology to enable dynamic matching of "people, goods, and venues". Research has confirmed that the OMO model is the key path to solving the pain points of traditional channels and adapting to the trend of younger consumption. 5.2. Research Prospects Looking forward to the future, the OMO model will develop in the direction of intelligence and socialization, and the integrated application of new technologies such as VR/AR and blockchain will expand its potential. Subsequent research can focus on the differences in OMO strategies for subdivided clothing categories and the comparison of OMO practices of multinational clothing brands in different market environments. This will provide the academic community with richer theoretical resources, provide enterprises with more targeted practical guidance, and help the apparel industry continue to innovate and develop in digital transformation. References [1] Taleizadeh A A, Darabi E S, Thaichon P. Optimizing online selling through an online-to-offline platform: strategic ramifications for local n stores [J]. Journal of Revenue and Pricing Management, 2024, 23(6): 554-574. [2] Li J. 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