Sustainable Chatbot Services

Why Are Filipino Online Sellers Falling Behind in AI?

While Southeast Asian neighbors like Thailand and Vietnam rapidly adopt AI-powered business tools, Filipino online sellers are hesitating at the starting line. According to a Lazada–Kantar study, only 35% of Philippine e-commerce sellers fully utilize AI—the lowest rate in the region. Many cite cost, complexity, and usability as major barriers. In fact, over two-thirds still rely on manual processes, despite AI’s promise to boost speed, sales, and scalability.

Yet ironically, the most widely used AI tool in Philippine e-commerce is the chatbot. It’s already embedded in platforms like Lazada and Shopee, offering round-the-clock support to customers. This means that the shift toward AI is not just possible—it’s already underway. The real challenge is sustainability: building long-term systems, training programs, and user-centered designs that help small and medium-sized sellers stay competitive. Chatbots may be the entry point, but only with infrastructure and policy support can they become a pillar of inclusive digital growth.

Who Can Use These Topics?

This research is ideal for students and professionals pursuing the following courses or strands:

College Programs:

• BS in Information Technology

• BS in Computer Science (with AI/UX/UI focus)

• BS in Business Administration major in E-Commerce or Digital Marketing

• BS in Entrepreneurship

• BS in Communication (with focus on digital media and automation)

• BS in Environmental Science (for AI-enabled sustainability systems)

Senior High School Strands:

• Humanities and Social Sciences (HUMSS)

• Science, Technology, Engineering, and Mathematics (STEM)

• Accountancy, Business, and Management (ABM)

• TVL-ICT

• General Academic Strand (GAS)

Why This Topic Needs Research

Chatbots offer scalable solutions, but several gaps remain in ensuring their sustained use and impact—especially in small-business ecosystems like Philippine e-commerce.

• Lack of long-term data on behavioral change: Majid et al. (2024) proposed that chatbots can nudge users toward sustainable actions but emphasized the need to test these models empirically and across different user types and industries—not just tourism.

• No cross-sector validation of sustainability benefits: Brightwood et al. (2024) outlined best practices for chatbot use in supply chains but noted that these strategies remain theoretical, lacking real-world validation across retail, logistics, and SME sectors.

• Unclear impact of design elements on trust: Kwangsawad and Jattamart (2022) highlighted how interface complexity, privacy concerns, and tech anxiety affect continued use, but more research is needed on how interface design and dialog flow impact Filipino sellers' trust in chatbot tools.

• Gap between intention and actual use: Nguyen et al. (2021) stressed that while users may express intent to reuse chatbots, continued adoption depends on motivation, tech readiness, and satisfaction, areas that remain underexplored in the local e-commerce scene.

• Need for cross-platform system improvement: Cao et al. (2024) identified user frustrations with Shopee and Lazada chatbots, recommending deeper investigation into how natural language processing and system architecture can improve reliability and relevance.

• Scenario-based vs. real-world engagement: Um et al. (2020) pointed out that most studies simulate chatbot scenarios rather than assess actual consumer interactions, leaving a gap in understanding how users react to service failures or recovery strategies in live settings.

• No models for public-scale implementation: Gebrewold (2024) built a sustainability chatbot for city use but noted the absence of studies on environmental footprint, civic adoption, and scaling AI chatbots across diverse Filipino municipalities or economic zones.

Feasibility & Challenges by Target Group

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References

Brightwood, S., Godwin, O., & Steve, M. (2024). Best Practices for Implementing AI-Powered Chatbots in Sustainable Supply Chain Management.

Cao, J., Ornum, S. C. Q., Sy, P. G. G., & Tan, L. J. S. (2024). Optimizing Customer Support: Identifying Factors to Enhance the AI Customer Service Chatbots of Shopee and Lazada in the Philippines.

Gebrewold, R. A. (2024). Development and evaluation of a Sustainability chatbot for the city administration of Freiburg: a sustainable approach.

Kwangsawad, A., & Jattamart, A. (2022). Overcoming customer innovation resistance to the sustainable adoption of chatbot services: A community-enterprise perspective in Thailand. Journal of Innovation & Knowledge, 7(3), 100211.

Majid, G. M., Tussyadiah, I., & Kim, Y. R. (2024). Exploring the potential of chatbots in extending tourists’ sustainable travel practices. Journal of Travel Research, 00472875241247316.

Nguyen, D. M., Chiu, Y. T. H., & Le, H. D. (2021). Determinants of continuance intention towards banks’ chatbot services in Vietnam: A necessity for sustainable development. Sustainability, 13(14), 7625.

Um, T., Kim, T., & Chung, N. (2020). How does an intelligence chatbot affect customers compared with self-service technology for sustainable services?. Sustainability, 12(12), 5119.

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