Table 3 Future research agenda TCM-ADO...

Table 3

Future research agenda

TCM-ADO	Proposed research question (RQ)
Theories	RQ1. How can socio-technical systems theory and digital capability theory explain the integration of human, technological, and organizational elements in sugarcane digital transformation?
	RQ2. How can resource-based view and dynamic capability theory clarify how agroindustries gain sustainable advantage from digitalization?
	RQ3. How can institutional and innovation diffusion theories explain the adoption behavior of smallholders in sugarcane-based value chains?
Contexts	RQ1. What are the contextual variations in digital maturity between major sugarcane-producing countries (Brazil, India, Thailand, Indonesia)?
	RQ2. How do upstream (cultivation) and downstream (processing, logistics) digital transformation differ in challenges and outcomes?
	RQ3. How do infrastructural readiness and cultural factors affect adoption in rural-based sugarcane agroindustries?
	RQ4. How do scale heterogeneity (smallholders vs large estates) and national digital policies shape adoption patterns?
Methods	RQ1. How can digital twin simulation and system dynamics modeling be applied to measure efficiency and sustainability in sugar mills?
	RQ2. How can mixed methods and longitudinal approaches capture the evolution of digital transformation impacts?
	RQ3. How can interpretable AI models enhance transparency and trust in agri-digital decision-making?
Antecedents	RQ1. What socio-technical, institutional, and organizational drivers influence digital transformation adoption?
	RQ2. How do leadership readiness, digital literacy, and infrastructure availability interact in driving adoption?
	RQ3. What role does policy support or government incentive play in accelerating digital transformation in the sugarcane sector?
	RQ4. How does trust among farmers, processors, and technology providers mediate the success of collaborative digital transformation initiatives?
Decisions	RQ1. How can optimization and AI-based DSS support investment and operation prioritization?
	RQ2. How can decision-support systems integrate IoT, AI, and blockchain for real-time procurement, harvesting, and logistics decisions?
	RQ3. How can digital maturity models be operationalized to guide transformation of roadmaps?
	RQ4. How can adaptive multi-agent decision-support systems dynamically respond to uncertainty in supply, demand, and climate conditions in sugarcane supply chains?
Outcomes	RQ1. Which dimensions of efficiency (resource, energy, time) are most impacted by digital transformation in sugarcane systems?
	RQ2. How can digitalization contribute to emission reduction and circular economy practices?
	RQ3. How does digital transformation influence smallholder welfare, equity, and resilience across the sugarcane value chain?

TCM-ADO	Proposed research question (RQ)
Theories	RQ1. How can socio-technical systems theory and digital capability theory explain the integration of human, technological, and organizational elements in sugarcane digital transformation?
	RQ2. How can resource-based view and dynamic capability theory clarify how agroindustries gain sustainable advantage from digitalization?
	RQ3. How can institutional and innovation diffusion theories explain the adoption behavior of smallholders in sugarcane-based value chains?
Contexts	RQ1. What are the contextual variations in digital maturity between major sugarcane-producing countries (Brazil, India, Thailand, Indonesia)?
	RQ2. How do upstream (cultivation) and downstream (processing, logistics) digital transformation differ in challenges and outcomes?
	RQ3. How do infrastructural readiness and cultural factors affect adoption in rural-based sugarcane agroindustries?
	RQ4. How do scale heterogeneity (smallholders vs large estates) and national digital policies shape adoption patterns?
Methods	RQ1. How can digital twin simulation and system dynamics modeling be applied to measure efficiency and sustainability in sugar mills?
	RQ2. How can mixed methods and longitudinal approaches capture the evolution of digital transformation impacts?
	RQ3. How can interpretable AI models enhance transparency and trust in agri-digital decision-making?
Antecedents	RQ1. What socio-technical, institutional, and organizational drivers influence digital transformation adoption?
	RQ2. How do leadership readiness, digital literacy, and infrastructure availability interact in driving adoption?
	RQ3. What role does policy support or government incentive play in accelerating digital transformation in the sugarcane sector?
	RQ4. How does trust among farmers, processors, and technology providers mediate the success of collaborative digital transformation initiatives?
Decisions	RQ1. How can optimization and AI-based DSS support investment and operation prioritization?
	RQ2. How can decision-support systems integrate IoT, AI, and blockchain for real-time procurement, harvesting, and logistics decisions?
	RQ3. How can digital maturity models be operationalized to guide transformation of roadmaps?
	RQ4. How can adaptive multi-agent decision-support systems dynamically respond to uncertainty in supply, demand, and climate conditions in sugarcane supply chains?
Outcomes	RQ1. Which dimensions of efficiency (resource, energy, time) are most impacted by digital transformation in sugarcane systems?
	RQ2. How can digitalization contribute to emission reduction and circular economy practices?
	RQ3. How does digital transformation influence smallholder welfare, equity, and resilience across the sugarcane value chain?

Source(s): Authors’ own work

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