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AI-driven Digital Transformation Framework for Traditional SMEs
PptxGenJS Presentation
Miss Pimpakan Srinoi
Miss Pimpakan Srinoi
1
2026-05-25T04:27:15Z
2026-05-25T04:27:15Z
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研究計画書DOCTORAL RESEARCH PROPOSAL · MEXT SCHOLARSHIPAI-driven Digital TransformationFramework for Traditional SMEsAn Action Research Study in ThailandPrepared by Miss Pimpakan Srinoi · Applied AI Transformation ResearcherInformation Systems · Digital Transformation · Technology ManagementPK
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02BackgroundWhy this research, and why now 01SMEs are the backboneSmall and medium-sized enterprises make up the vast majority of firms and jobs in both Thailand and Japan, yet many still operate offline and manually. 02A demographic squeezeAging populations and labor shortages are raising costs and limiting capacity — already acute in Japan, and now emerging in Thailand. 03The transformation gapTraditional, low-maturity SMEs lack a structured, low-risk path to adopt AI — most DX research targets large firms, not them.Thailand serves as a fast, lower-cost living laboratory; Japan provides the theoretical lens and the high-stakes application context.PK
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03Problem StatementSix interlocking constraints converge on one root condition 1Manual, owner-dependent operations 2Stalled or all-or-nothing DX attempts 3AI seen as only for large firms 4No internal IT or automation skills 5Cultural resistance to change 6Rising wages & labor shortage THE ROOT VARIABLELow DigitalMaturityThe six constraints compound into a single systemic condition. Because maturity is the root variable, it becomes the construct this study measures, models, and moves.PK
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04Objectives & Research Questions MAIN OBJECTIVETo design, implement, and empirically validate a practical AI-driven digital transformation framework that raises the digital maturity and measurable performance of traditional, labor-intensive SMEs through human–AI collaboration.Sub-objectives: identify barriers · design the phased framework · implement across cases · measure KPIs · build the maturity model · derive lessons for Japan. RQ1How can a phased framework enable low-maturity SMEs to adopt AI-driven transformation sustainably? RQ2What measurable effects do human–AI workflows have on operational and commercial performance? RQ3–5Which barriers predict success; which KPIs capture value; how does maturity relate to durability? RQ6–7How transferable are the findings to Japan, and how does culture shape AI as augmentation?PK
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05MethodologyAction Research × Multiple Case Study · Mixed Methods (QUAL + QUAN) 1DiagnoseMap maturity,workflows,baseline KPIs 2PlanCo-design theinterventionwith the owner 3ActImplementhuman–AIworkflows 4ObserveCollect KPIs,interviews,usage data 5ReflectCompare, refine,carry into thenext caseIterative cycles inside each firm build the framework; cross-case analysis generalizes the findings.PK
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06The SMEs AI Transformation FrameworkFive sequential phases — each de-risks the next; humans stay in the loop 1AssessmentDiagnose maturity& set KPI baseline 2DigitalFoundationDigitize records& channels 3WorkflowAutomationAutomate routinetasks, human checks 4AIIntegrationHuman–AI comms,content, decisions 5OptimizationMeasure, refine,sustain improvementLow maturity (Manual SME)AI-driven SMEPK
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07Expected OutcomesMeasurable KPI change, and movement up the maturity ladder ≈ −95%First-response time +8 ptsLead conversion 4×Content output +15 ptsCustomer satisfactionIndicative design targets — to be established empirically per case.SME AI Maturity Model12345Manual → Digital Comms → CRM → Workflow Automation → AI-drivenPK
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08Relevance to JapanA structural connection, not a rhetorical one SHARED PRESSURES · THAILAND ↔ JAPANAging societyA shrinking, older workforce raising costs and limiting capacity.Labor shortageDifficulty recruiting and retaining staff for routine work.SME DX gapMany small firms remain under-digitized despite available tools. WHY JAPAN, ACADEMICALLYJapan leads scholarship on productivity, manufacturing excellence, and technology management, and treats SME revitalization as a frontier research agenda.The dissertation explicitly tests whether the Thai findings transfer to the Japanese SME environment — turning one country’s evidence into insight meaningful in another.PK
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FUTURE IMPACTA contribution that is academic, practical, and regionalAcademicSeeds a comparative research stream on SME digital maturity across aging economies, with reusable framework and maturity instruments.PracticalBecomes a professional playbook for advising SMEs — bridging academia and applied transformation work.RegionalExtends to ASEAN economies with similar SME structures, lowering the barrier to AI for the firms least able to access it.Miss Pimpakan Srinoi · Doctoral Research Proposal · Japanese Government (MEXT) ScholarshipPK
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