Final Review · Submission #9 — From Tradition to Innovation: A Scoping Review of AI Adoptio…

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The section "Roles" does not describe roles but factors/facets.

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Figures don't have captions

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The section "Norms" is not well structured: same norms are repeated with different terms (e.g., transparency and opacity)

−

The "checklist" is announced but not delivered: the Abstract and Conclusion both promise a "practical adoption checklist," but the body of the paper does not present one as a structured operational tool.

−

Citation list still inconsistent: refs [11] and [17] are cited in-text but missing from the reference list, [8] and [9] are exact duplicates, and the stated count of 21 sources does not match the unique references actually listed.

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Limited critical comparison across sources: despite one acknowledged contradiction in Section 3.3, the framework still largely summarizes rather than contrasts findings.

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Case study still narrates rather than tests the framework: the "In Vino VeritAI" section is richer but continues to apply the framework illustratively to a fictitious firm, without resolving Reviewer 2's request for a real case or Reviewer 7's request for deeper trade-off analysis.

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Residual informal language: the case study contains colloquial constructions, and the AI disclosure in the appendix contains untranslated Italian text and remains informal.

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CCS Concepts and a fully populated coding table are missing: Reviewer 8's request for complete formal sections is only partially met, and Table 1 in the appendix appears truncated.

High

Location

Section 1 (Introduction) and Section 6 (Conclusion), wherever the term "adoption checklist" appears

Issue

The Abstract, Introduction, and Conclusion all promise a "practical adoption checklist for managers," but no such checklist is actually presented in the paper — the framework remains a four-pillar narrative

Suggested Fix

Add a dedicated subsection (e.g., "3.5 The CI Adoption Checklist") containing a numbered or tabular list of operational criteria under each of the four pillars (Roles, Activities, Norms, Values), so the checklist promised in the Abstract becomes a tangible deliverable

High

Location

Appendix A (References)

Issue

References [11] and [17] are cited in-text but missing from the reference list; references [8] and [9] are exact duplicates of the same Qureshi et al. source; and the total unique references do not match the claimed "21 sources" in the methodology

Suggested Fix

Reconcile in-text citations with the reference list: add the missing entries [11] and [17], replace one of the duplicates [8]/[9] with the correct distinct source, and verify that the total count matches the "21 sources" stated in the PRISMA-ScR funnel

High

Location

Sections 3.1–3.4 (Framework)

Issue

The framework synthesizes findings narratively but rarely compares or contrasts conflicting evidence across sources, which several reviewers flagged as the difference between a literature summary and a true scoping review

Suggested Fix

In each of the four pillar subsections, add at least one sentence explicitly contrasting two or more sources with differing perspectives (e.g., studies emphasizing efficiency gains vs. studies highlighting worker stress under surveillance) to demonstrate analytical synthesis rather than aggregation

High

Location

Section 4 (Worked Case: "In Vino VeritAI")

Issue

The case study is more integrated than in the first submission but still applies the framework illustratively rather than testing it against concrete trade-offs, and the firm remains fictitious

Suggested Fix

Restructure the case section around 2–3 explicit managerial tensions (e.g., efficiency vs. artisanal identity; algorithmic prediction vs. master winemaker authority; cost of implementation vs. SME budget constraints), and either anchor the case in a real winery or explicitly justify the fictitious-firm choice as a composite based on documented industry data

High

Location

Appendix F (AI use disclosure)

Issue

The disclosure is informal, mixes Italian and English ("nella parte di chat"), and does not specify which sections were AI-assisted or how human verification was performed

Suggested Fix

Rewrite the AI disclosure in clean English, specify exactly which tools were used for which tasks (search formulation vs. drafting vs. figure generation), and describe the human verification process (who reviewed AI outputs and against what criteria)

Medium

Location

Section 2 (Methodology), Screening and Selection paragraph

Issue

The methodology states that 17 sources were excluded for "insufficient methodological rigor or commercial bias (unreliable whitepapers)" but does not define what "reliability" or "rigor" means operationally, which Reviewer 7 explicitly flagged

Suggested Fix

Add one or two sentences defining the reliability criteria used (e.g., peer-reviewed status, presence of empirical methods, absence of vendor sponsorship) so the exclusion decisions are reproducible

Medium

Location

Title page / Abstract area

Issue

The paper lacks a CCS Concepts section that Reviewer 8 explicitly requested as part of standard ACM-style formal structure

Suggested Fix

Add a short CCS Concepts block immediately after the Keywords section, listing relevant ACM Computing Classification System categories (e.g., "Applied computing → Enterprise computing"; "Social and professional topics → Computing / technology policy")

Medium

Location

Appendix H (Coding Scheme), Table 1

Issue

Table 1 appears truncated — only a subset of the 21 included sources is shown, the "Context" column is cut off, and the table does not visibly map every source to one of the four CI pillars (a mapping Reviewer 5 specifically requested)

Suggested Fix

Complete Table 1 to include all 21 sources, ensure all columns (including Context) are fully visible, and add an explicit column or color-coding linking each source to its primary CI pillar (Roles / Activities / Norms / Values)

Medium

Location

Section 4 (Worked Case), throughout

Issue

The case study contains residual informal phrasing ("they will need to attend a training course," "AI will always need the supervision of the human eye") that lowers the academic register flagged by Reviewers 5 and 6

Suggested Fix

Rewrite informal sentences in a more neutral academic register (e.g., "targeted training programs are required to bridge the data-literacy gap" and "human oversight remains a precondition for algorithmic decision support")

Medium

Location

Figure 1 (PRISMA-ScR diagram) and Section 2 numerical breakdown

Issue

The figure caption is empty ("Figure 1:") and the numbers in the funnel (100 → 50 → 29 → 21) do not perfectly reconcile with the prose, which says 17 + 12 = 29 excluded at full-text stage

Suggested Fix

Add a descriptive caption to Figure 1 (e.g., "Figure 1: PRISMA-ScR screening funnel for source selection") and verify the arithmetic across the prose and the diagram so identification, screening, eligibility, and inclusion totals match exactly

Low

Location

Section 5 (Gaps and Future Work)

Issue

The gaps section is well-structured but does not explicitly engage with opposing viewpoints (e.g., whether monitoring systems may also benefit employees, whether over-regulation could harm SME adoption), as raised by Reviewer 7

Suggested Fix

Add a short paragraph acknowledging counter-arguments to the framework's main claims and identify these as additional avenues for future research, strengthening the review's even-handedness

Low

Location

Section 3.4 (Values and Corporate Responsibility)

Issue

The subsection is the longest and densest, and uses some abstract language ("blockchain-enabled or decentralized communication models") without explanation, which can disrupt readability for non-specialist managerial readers

Suggested Fix

Either briefly define the technical terms in-line or remove them if they are not central to the argument, keeping the subsection focused on the core value-CR-ESG argument

Review Nº 09

The Pros

The Cons

Suggested Changes