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Key Findings

All effect sizes, cross-tabulations, t-tests, and ANOVA are computed independently for each of the four primary result groups. This ensures that any finding can be validated against the researcher’s chosen dataset.

Effect Sizes (Cohen’s d)

Cohen’s d measures the standardized difference between group means. Values of |d| < 0.2 are negligible, 0.2–0.5 small, 0.5–0.8 medium, and > 0.8 large. Each comparison is computed separately for each result group.

Conservative Clean (N=80)

Technical (CIO/CTO) vs Non-Technical — n=15 vs n=52

ConstructTech MeanNon-Tech MeanCohen’s dSize
barriers2.72222.8807-0.23small
readiness3.32503.0075+0.54medium
maturity3.10833.0003+0.15negligible

Large Org (5000+) vs Small/Medium — n=17 vs n=63

ConstructLarge MeanS/M MeanCohen’s dSize
barriers3.09192.7515+0.55medium
readiness3.02223.0611-0.07negligible

Flexible Clean (N=127)

Technical (CIO/CTO) vs Non-Technical — n=29 vs n=79

ConstructTech MeanNon-Tech MeanCohen’s dSize
barriers2.64752.8762-0.31small
readiness3.41733.0380+0.57medium
maturity3.27163.0334+0.30small

Large Org (5000+) vs Small/Medium — n=24 vs n=103

ConstructLarge MeanS/M MeanCohen’s dSize
barriers3.08832.7508+0.48small
readiness2.95443.1300-0.27small

Prolific Accepted (N=231)

Technical (CIO/CTO) vs Non-Technical — n=51 vs n=133

ConstructTech MeanNon-Tech MeanCohen’s dSize
barriers2.70972.7974-0.12negligible
readiness3.44023.0718+0.56medium
maturity3.34633.0949+0.31small

Large Org (5000+) vs Small/Medium — n=53 vs n=178

ConstructLarge MeanS/M MeanCohen’s dSize
barriers2.90262.7422+0.22small
readiness3.16663.1321+0.05negligible

All V2 Finished (N=368)

Technical (CIO/CTO) vs Non-Technical — n=91 vs n=206

ConstructTech MeanNon-Tech MeanCohen’s dSize
barriers2.66332.7598-0.12negligible
readiness3.46783.2151+0.35small
maturity3.40843.2395+0.21small

Large Org (5000+) vs Small/Medium — n=84 vs n=284

ConstructLarge MeanS/M MeanCohen’s dSize
barriers2.87812.6993+0.23small
readiness3.26413.2450+0.03negligible

Cross-Tabulations

Cross-tabulations show construct means broken down by respondent subgroups (role, org size). These are computed for each result group to check whether group-level patterns hold across data cleaning levels.

Conservative Clean (N=80)

By Role

GroupnBRM
Technical (CIO/CTO)152.723.333.11
Non-Technical522.883.013.00
Other132.712.923.11

By Org Size

GroupnBRM
Small (<500)382.803.062.98
Medium (500-4999)252.683.062.95
Large (5000+)173.093.023.30

Flexible Clean (N=127)

By Role

GroupnBRM
Technical (CIO/CTO)292.653.423.27
Non-Technical792.883.043.03
Other192.812.852.89

By Org Size

GroupnBRM
Small (<500)572.753.122.98
Medium (500-4999)462.763.153.14
Large (5000+)243.092.953.13

Prolific Accepted (N=231)

By Role

GroupnBRM
Technical (CIO/CTO)512.713.443.35
Non-Technical1332.803.073.09
Other452.792.963.08

By Org Size

GroupnBRM
Small (<500)972.743.053.00
Medium (500-4999)812.753.233.24
Large (5000+)532.903.173.33

All V2 Finished (N=368)

By Role

GroupnBRM
Technical (CIO/CTO)912.663.473.41
Non-Technical2062.763.223.24
Other662.783.023.12

By Org Size

GroupnBRM
Small (<500)1542.663.173.14
Medium (500-4999)1302.743.333.35
Large (5000+)842.883.263.37

Inferential Statistics

Welch’s t-tests compare two groups (unequal variance assumed). One-way ANOVA tests whether means differ across three or more groups. All tests are two-tailed with α = 0.05. Significant results (p < 0.05) are highlighted.

Conservative Clean

Welch’s t-test: Technical vs Non-Technical(ntech=15, nnon-tech=52)

ConstructtdfpSig.
barriers-0.75821.1<.001
readiness1.90823.8<.001
maturity0.47420.3<.001

Welch’s t-test: Large vs Small/Medium Org(nlarge=17, nsm/med=63)

ConstructtdfpSig.
barriers2.16328.3<.001
readiness-0.23424.0<.001
maturity1.57222.4<.001

One-way ANOVA: by Role(Technical (CIO/CTO), Non-Technical, Other)

ConstructFdfpSig.
barriers0.5942, 770.555
readiness2.2122, 770.116
maturity0.2042, 770.816

One-way ANOVA: by Organization Size(Small (<500), Medium (500-4999), Large (5000+))

ConstructFdfpSig.
barriers2.3072, 770.106
readiness0.0312, 770.970
maturity1.5122, 770.227

Flexible Clean

Welch’s t-test: Technical vs Non-Technical(ntech=29, nnon-tech=79)

ConstructtdfpSig.
barriers-1.45052.6<.001
readiness2.88359.6<.001
maturity1.43155.3<.001

Welch’s t-test: Large vs Small/Medium Org(nlarge=24, nsm/med=103)

ConstructtdfpSig.
barriers2.15535.5<.001
readiness-1.12832.9<.001
maturity0.38931.4<.001

One-way ANOVA: by Role(Technical (CIO/CTO), Non-Technical, Other)

ConstructFdfpSig.
barriers1.0782, 1240.343
readiness5.4362, 1240.005
maturity1.5202, 1240.223

One-way ANOVA: by Organization Size(Small (<500), Medium (500-4999), Large (5000+))

ConstructFdfpSig.
barriers2.1942, 1240.116
readiness0.7212, 1240.488
maturity0.6412, 1240.528

Prolific Accepted

Welch’s t-test: Technical vs Non-Technical(ntech=51, nnon-tech=133)

ConstructtdfpSig.
barriers-0.71188.8<.001
readiness3.49395.8<.001
maturity1.90390.5<.001

Welch’s t-test: Large vs Small/Medium Org(nlarge=53, nsm/med=178)

ConstructtdfpSig.
barriers1.45286.8<.001
readiness0.30276.7<.001
maturity1.72979.6<.001

One-way ANOVA: by Role(Technical (CIO/CTO), Non-Technical, Other)

ConstructFdfpSig.
barriers0.2852, 2260.752
readiness7.7702, 226<.001
maturity2.0432, 2260.132

One-way ANOVA: by Organization Size(Small (<500), Medium (500-4999), Large (5000+))

ConstructFdfpSig.
barriers1.0352, 2280.357
readiness1.5712, 2280.210
maturity3.6792, 2280.027

All V2 Finished

Welch’s t-test: Technical vs Non-Technical(ntech=91, nnon-tech=206)

ConstructtdfpSig.
barriers-0.950170.6<.001
readiness2.837174.9<.001
maturity1.700179.2<.001

Welch’s t-test: Large vs Small/Medium Org(nlarge=84, nsm/med=284)

ConstructtdfpSig.
barriers1.880136.7<.001
readiness0.209130.7<.001
maturity1.261129.9<.001

One-way ANOVA: by Role(Technical (CIO/CTO), Non-Technical, Other)

ConstructFdfpSig.
barriers0.5942, 3600.553
readiness8.1682, 359<.001
maturity2.6562, 3590.072

One-way ANOVA: by Organization Size(Small (<500), Medium (500-4999), Large (5000+))

ConstructFdfpSig.
barriers2.1312, 3650.120
readiness1.8002, 3640.167
maturity3.4242, 3640.034

Forthcoming Analyses

The following additional analyses are planned for future releases:

Regression ModelsFactor Analysis

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