Table 3 Summary of research gaps and... | Emerald Publishing

Table 3

Summary of research gaps and corresponding sub-research questions

Identified research gap	Description	Corresponding RQ(s)	Implications for DSS
Gap 1: Topic visibility in practitioner discourse	Project-level ESG communication is fragmented and filtered through strategic external disclosures; practitioner narratives remain under-analyzed	RQ1: What topics and themes emerge most frequently across ESG discourse in infrastructure projects?	Highlights the need for DSS pipelines capable of mining operational texts to reveal latent sustainability priorities
Gap 2: Positioning and bias of digital transformation	Digital tools are often celebrated as enablers of sustainability, yet little is known about how they are linguistically framed or whether this reflects substantive outcomes	RQ4: How are digital technologies positioned in relation to ESG themes?	Supports the development of DSS models that detect optimism bias and distinguish rhetorical from functional digitalization
Gap 3: Internal framing and pillar asymmetry	Most studies focus on external ESG reports; few examine how practitioners internally frame environmental, social, and governance issues differently	RQ2 and 3: How are ESG priorities emphasized or downplayed through language?/Are there discernible differences in lexical framing between E, S, and G components?	Encourages DSS designs sensitive to linguistic and affective asymmetries across ESG pillars
Gap 4: Computational-interpretive integration	Existing NLP models privilege predictive accuracy over interpretive insight; qualitative meaning is seldom linked to algorithmic output	RQ1 – 3	Necessitates explainable, human-in-the-loop DSS that combine scalable computation with discourse interpretation

Identified research gap	Description	Corresponding RQ(s)	Implications for DSS
Gap 1: Topic visibility in practitioner discourse	Project-level ESG communication is fragmented and filtered through strategic external disclosures; practitioner narratives remain under-analyzed	RQ1: What topics and themes emerge most frequently across ESG discourse in infrastructure projects?	Highlights the need for DSS pipelines capable of mining operational texts to reveal latent sustainability priorities
Gap 2: Positioning and bias of digital transformation	Digital tools are often celebrated as enablers of sustainability, yet little is known about how they are linguistically framed or whether this reflects substantive outcomes	RQ4: How are digital technologies positioned in relation to ESG themes?	Supports the development of DSS models that detect optimism bias and distinguish rhetorical from functional digitalization
Gap 3: Internal framing and pillar asymmetry	Most studies focus on external ESG reports; few examine how practitioners internally frame environmental, social, and governance issues differently	RQ2 and 3: How are ESG priorities emphasized or downplayed through language?/Are there discernible differences in lexical framing between E, S, and G components?	Encourages DSS designs sensitive to linguistic and affective asymmetries across ESG pillars
Gap 4: Computational-interpretive integration	Existing NLP models privilege predictive accuracy over interpretive insight; qualitative meaning is seldom linked to algorithmic output	RQ1 – 3	Necessitates explainable, human-in-the-loop DSS that combine scalable computation with discourse interpretation