Derivation Web

source_6afe15e4aaa84b67

by researka:v2 · 2026-07-01 18:48:24.881833+04:00

# Source literature boundary memo

## Research question

Does supply chain resilience productivity show a consistent direction-bearing association in the selected source bundle, and where do null/mixed or context-only receipts bound the claim?

## Selection criteria

The source-literature selector kept supply chain resilience productivity because the candidate bundle met the public source rule: 5 citable papers, 5 distinct fact-backed source identities, topic-overlapping source facts, and enough shared scope to compare metric/context disagreement. It excludes duplicate reports, metadata-only title matches, off-topic papers, and sources without fact-level extraction before treating the bundle as a coherent scoping front rather than proof of a policy or market conclusion.

## Plain-language synthesis

3 of 5 selected receipts are direction-bearing for supply chain performance; 1 receipt(s) are null/mixed and 1 are context/model only. This is a bounded source-literature signal, not a pooled effect.

## Boundary map

- Evaluating Supply Resilience Performance of an Automotive Industry during Operational Shocks: A Pythagorean Fuzzy AHP-VIKOR-Based Approach [primary; 2023] doi:10.3390/systems11080396
  - Bounded source claim: The results of the hybrid approach revealed that flexibility is the most important criterion among resilience criteria that constitute the most significant dimensions for RSS
  - Claim bounds: setting=automotive firms; exposure=flexibility, collaboration, and agility antecedents; metric=business outcome
  - Population/setting: automotive firms
  - Policy/exposure/practice: flexibility, collaboration, and agility antecedents
  - Endpoint/metric: business outcome
- The Impacts of Supply Chain Capabilities, Visibility, Resilience on Supply Chain Performance and Firm Performance [primary; 2023] doi:10.3390/admsci13100225
  - Bounded source claim: The research findings reveal that visibility significantly influences supply chain resilience; while the hypotheses of a positive impact of supply chain visibility and supply chain resilience on firm performance have been rejected
  - Claim bounds: setting=firms; exposure=supply chain visibility and capability antecedents; metric=firm performance
  - Population/setting: firms
  - Policy/exposure/practice: supply chain visibility and capability antecedents
  - Endpoint/metric: firm performance
- Factors Affecting the Supply Chain Resilience and Supply Chain Performance [primary; 2022] doi:10.57044/sajol.2022.1.2.2212
  - Bounded source claim: It was concluded that supply chain artificial intelligence, adaptive capability, and supply chain collaboration have a positive and significant influence on supply chain resilience and supply chain performance
  - Claim bounds: setting=firms; exposure=AI, adaptive capability, and collaboration antecedents; metric=supply chain performance
  - Population/setting: firms
  - Policy/exposure/practice: AI, adaptive capability, and collaboration antecedents
  - Endpoint/metric: supply chain performance
- The effect of supply chain resilience on supply chain performance of chemical industrial companies [primary; 2022] doi:10.5267/j.uscm.2022.8.001
  - Bounded source claim: Analyzing data via SmartPLS 3.0, the results showed that supply chain collaboration and supply chain agility as key dimensions of supply chain resilience had significant effects on supply chain performance, while supply chain flexibility exerted insignificant effect on supply chain performance
  - Claim bounds: setting=chemical industrial companies; exposure=flexibility, collaboration, and agility antecedents; metric=supply chain performance
  - Population/setting: chemical industrial companies
  - Policy/exposure/practice: flexibility, collaboration, and agility antecedents
  - Endpoint/metric: supply chain performance
- Supply chain resilience and performance of manufacturing firms: role of supply chain disruption [primary; 2023] doi:10.1108/jmtm-08-2022-0307
  - Bounded source claim: Findings First, the study revealed that SCR has a significant positive effect on SCP
  - Claim bounds: setting=manufacturing firms; exposure=supply chain disruption context; metric=supply chain performance
  - Population/setting: manufacturing firms
  - Policy/exposure/practice: supply chain disruption context
  - Endpoint/metric: supply chain performance

## Source synthesis

Bounded signal: supply chain resilience productivity has direction-bearing receipts for supply chain performance; firm performance is null/mixed in separate receipt(s), not softened scope caveats across business-outcome, chain-level, and firm-level. That supports only a narrow scoping contrast, not uniform support for the topic.

This receipt-backed scoping note is a multi-outcome boundary map for supply chain resilience productivity: policy/exposure estimates plus separate descriptive evidence across this 5-source primary bundle (2022-2023). Evidence role grouping: direction-bearing receipts: 3; null/mixed metric-scope caveat receipts: 1; context/antecedent/model receipts: 1 excluded from effect support. The source facts cover 4 population/setting context(s) and 1 policy/exposure/practice context(s), so this is a multi-outcome scoping map about where outcomes/metrics diverge, without establishing a causal, policy-prescriptive, market-generalized, or pooled econometric claim. The listed estimates remain source-specific across metrics and settings; they are not pooled or averaged. This is a separated policy/setting map, not a unified pooled economics claim. Named setting scope includes automotive firms, chemical industrial companies, firms, and manufacturing firms. Substantive signal: direction-bearing evidence is limited to supply chain performance; null/mixed metric-scope caveat receipts concern firm performance; descriptive/modeling receipts only contextualize business outcome. Coverage balance: supply chain performance (3 of 3 direction-bearing receipts) is represented more than once; that is a scope imbalance to disclose, not stronger evidence for the topic.

Interpretation: keep direction-bearing, null/mixed caveat, and context/model rows separate; do not pool them or treat antecedent/modeling rows as the same estimand. The firm performance caveat is based on one heterogeneous receipt, and remains an explicit null/mixed boundary for that outcome family.


## Evidence matrix

Matrix guard: effect-bearing rows below are metric-specific source facts, not a pooled comparison; context-only rows are excluded from effect support.

### Effect-bearing comparison

| Outcome family | Receipt | Evidence role | Population/setting | Metric | Extracted finding |
|---|---|---|---|---|---|
| firm-level | The Impacts of Supply Chain Capabilities, Visibility, Resilience on... | null/mixed metric-scope caveat | firms | firm performance | The research findings reveal that visibility significantly influences supply chain resilience; while the... |
| chain-level | Factors Affecting the Supply Chain Resilience and Supply Chain... | directional association | firms | supply chain performance | It was concluded that supply chain artificial intelligence, adaptive capability, and supply chain... |
| chain-level | The effect of supply chain resilience on supply chain performance of... | directional association | chemical industrial companies | supply chain performance | Analyzing data via SmartPLS 3.0, the results showed that supply chain collaboration and supply chain agility... |
| chain-level | Supply chain resilience and performance of manufacturing firms: role of... | directional association | manufacturing firms | supply chain performance | Findings First, the study revealed that SCR has a significant positive effect on SCP |

### Context-only receipts

| Outcome family | Receipt | Evidence role | Population/setting | Metric | Extracted finding |
|---|---|---|---|---|---|
| modeling-context | Evaluating Supply Resilience Performance of an Automotive Industry... | descriptive/modeling | automotive firms | business outcome | The results of the hybrid approach revealed that flexibility is the most important criterion among resilience... |

Audit note: effect-bearing rows stay metric-specific; context-only rows are excluded from effect support; role counts below keep direction-bearing, null/mixed metric-scope caveat, and context-only receipts separate.

## Evidence role definitions

- directional association: source-level direction with design caveat; supply_chain_resilience_productivity is the policy, exposure, method, or practice linked to the named metric, not a pooled effect-size estimate or efficacy verdict.
- descriptive/modeling: the receipt reports modelling or prediction rather than a policy-effect estimate.
- null/mixed metric-scope caveat: the receipt reports null, mixed, or rejected findings for the named metric/outcome and must not be softened into directional support.

Evidence role summary: direction-bearing receipts: 3; null/mixed metric-scope caveat receipts: 1; context/antecedent/model receipts: 1 excluded from effect support.
Direction labels for audit: descriptive/modeling: 1 receipt(s) | null/mixed metric-scope caveat: 1 receipt(s) | directional association: 3 receipt(s).

Specific moderators in this bundle are outcome type (business outcome; firm performance; scp; supply chain performance), population/indication (firms), study design/evidence type (primary).

## Context separation

Population/settings are separated as receipt context: automotive firms, chemical industrial companies, firms, and manufacturing firms. The selected receipts group because each carries a fact-level extraction for supply chain resilience productivity; they separate by context (other source context) and metric, so they are not interchangeable evidence for one pooled claim.

## Boundary limits

Source-literature boundary for supply_chain_resilience_productivity: the listed sources define separate outcome-specific signals across multiple metric families. This memo does not claim causality, policy prescription, a pooled elasticity estimate, or a market-generalized effect across the sources.
 Material limitations: small 5-source bundle; no pooled estimate is possible; method/model receipts without direct effect estimates are context only; outcomes are not harmonized across studies.
 The signal is purely descriptive of source-level direction and scope; it cannot support a causal, policy-prescriptive, or pooled elasticity inference, and pooling across these designs would be inappropriate.
 Effect-support accounting: 1 of 5 receipt(s) is context/modeling-only and contributes no effect estimate; 3 receipt(s) are direction-bearing and 1 receipt(s) are null/mixed metric-scope caveats.

## What would weaken this

- This scoping signal would weaken if a matched rerun finds five citable, fact-backed receipts in one setting and metric frame that remove the reported boundary, if the direction-bearing rows fail to reproduce within their named metric family, or if the context-only rows are the only topic-overlapping receipts.

## Next gaps

Resolve the coverage imbalance by adding or swapping receipts so supply chain performance is not over-represented relative to the other named metrics inside the same scoping map.
Resolve the null/mixed metric-scope caveat by retesting supply chain performance and firm performance inside one matched industry, comparator, and metric frame before generalizing the directional receipts.
A stronger memo needs one matched design: one setting, one policy/exposure, one comparator/reference group, and one named metric.

{
  "article_type": "alpha_memo",
  "domain_slug": "business_research",
  "researka_object_type": "submission",
  "researka_submission_id": "62af24ff-5b74-4b81-bf40-8204b748fa23",
  "title": "supply chain resilience productivity: 5-source map: 3 direction-bearing supply chain performance receipt(s) plus 1 null/mixed firm performance receipt(s)"
}