AI Chatbot Usage, Social Media Marketing, and Service Innovation–Internal Learning Capability Pathways to SME Business Sustainability in Thailand: An Interval Type-2 Fuzzy Delphi, PLS-SEM, and fsQCA Study

Small- and medium-sized enterprises (SMEs) increasingly use artificial intelligence (AI)-based customer tools and social media marketing to compete in digital markets. However, prior research has not fully explained how customer-facing digital interaction and strategic customer sensing are converted into internal organisational capabilities or how alternative combinations of capabilities lead to business sustainability. In this study, we develop and test a sequential mixed-method framework for Thai SMEs. In Phase I, we applied the Interval Type-2 Fuzzy Delphi Method (IT2FDM) with 21 experts to validate 43 observed variables. In Phase II, we analysed 659 Thai SME responses using Partial Least Squares Structural Equation Modelling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). The PLS-SEM measurement assessment showed that service innovation and internal learning formed a consolidated service innovation–internal learning capability (SILC) construct, with 42 indicators retained in the final measurement model. The structural model supported all hypothesised paths: AI chatbot usage, social media marketing, and customer value anticipation were positively associated with SILC; SILC was positively associated with external learning, business performance, and business sustainability; external learning was positively associated with business performance; and business performance was positively associated with business sustainability. The fsQCA results showed that no single present or absent/low condition was necessary for business sustainability and identified three sufficient pathways, with SILC and business performance present across all primary configurations. One pathway further showed that strong SILC, external learning, and business performance could support business sustainability even when AI chatbot usage, social media marketing, and customer value anticipation were weak or absent. The findings advance SME digital transformation and sustainability research by demonstrating capability conversion, integrated innovation–learning transformation, and multiple compensatory pathways to business sustainability.

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Publication Details

Journal
Sustainability
Published
2026-08-20
DOI
https://doi.org/10.3390/su18168538
Primary Topic
AI in Service Interactions
Type
article
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article

AI Chatbot Usage, Social Media Marketing, and Service Innovation–Internal Learning Capability Pathways to SME Business Sustainability in Thailand: An Interval Type-2 Fuzzy Delphi, PLS-SEM, and fsQCA Study

Sumaman Pankham, Somchai Lekcharoen, Parinya Pattayanun
Sustainability
AI in Service Interactions
article

AI Chatbot Usage, Social Media Marketing, and Service Innovation–Internal Learning Capability Pathways to SME Business Sustainability in Thailand: An Interval Type-2 Fuzzy Delphi, PLS-SEM, and fsQCA Study

Sumaman Pankham, Somchai Lekcharoen, Parinya Pattayanun
article en

Abstract

Small- and medium-sized enterprises (SMEs) increasingly use artificial intelligence (AI)-based customer tools and social media marketing to compete in digital markets. However, prior research has not fully explained how customer-facing digital interaction and strategic customer sensing are converted into internal organisational capabilities or how alternative combinations of capabilities lead to business sustainability. In this study, we develop and test a sequential mixed-method framework for Thai SMEs. In Phase I, we applied the Interval Type-2 Fuzzy Delphi Method (IT2FDM) with 21 experts to validate 43 observed variables. In Phase II, we analysed 659 Thai SME responses using Partial Least Squares Structural Equation Modelling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). The PLS-SEM measurement assessment showed that service innovation and internal learning formed a consolidated service innovation–internal learning capability (SILC) construct, with 42 indicators retained in the final measurement model. The structural model supported all hypothesised paths: AI chatbot usage, social media marketing, and customer value anticipation were positively associated with SILC; SILC was positively associated with external learning, business performance, and business sustainability; external learning was positively associated with business performance; and business performance was positively associated with business sustainability. The fsQCA results showed that no single present or absent/low condition was necessary for business sustainability and identified three sufficient pathways, with SILC and business performance present across all primary configurations. One pathway further showed that strong SILC, external learning, and business performance could support business sustainability even when AI chatbot usage, social media marketing, and customer value anticipation were weak or absent. The findings advance SME digital transformation and sustainability research by demonstrating capability conversion, integrated innovation–learning transformation, and multiple compensatory pathways to business sustainability.

SustainabilityVol. 18(16)
Rangsit University (TH)
Industry, innovation and infrastructure
Openalex Percentile: Top 7%
AI in Service Interactions
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