Verified Rigor RecordRigor Reviewed

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Evaluating the influence of characteristics on the acceptance of artificial intelligence application: An empirical study · 10.1016/j.heliyon.2024.e39460

Name: Verified Rigor Record — Evaluating the influence of characteristics on the acceptance of artificial intelligence application: An empirical study · 10.1016/j.heliyon.2024.e39460
Item: Evaluating the influence of characteristics on the acceptance of artificial intelligence application: An empirical study · 10.1016/j.heliyon.2024.e39460
Rating: 76
Author: Αlpha¹

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Αlpha¹ Editorial

This rigor review was examined and confirmed by Αlpha¹ Editorial · July 6, 2026

Αlpha¹ Rigor Review

Rigor Reviewed

WARN

Warnings to address · Observational Study

Eight dimensions — click a segment for details

Critical

High-priority

Model-reported confidence: highReviewer agreement: moderateEngine: 7.6.0Source: full text

Not verified in this report

No data or code availability links were detected to verify.

This Αlpha¹ Rigor Review uses AI Rigor Reviewers trained on a curated corpus of high-fidelity and retracted papers, with expert supervision and curation. It can still make mistakes; verify each finding against the source before relying on it.

This cross-sectional survey study on continuance intention of a map app has a strong scientific premise and adequate reporting of demographic variables, but is weakened by a missing ethics approval statement, absence of a formal reporting guideline, a vague data availability statement, and incomplete statistical reporting (no assumption checks, threshold p-values, no confidence intervals for path coefficients). The copyedit pass reveals a major internal contradiction in reported AVE values.

This post-publication audit evaluated all eight rigor dimensions; key resources was scored not applicable as the study uses no biological/chemical resources or bespoke software. The study is a survey-based observational study; interventional criteria (randomization, blinding, controls) are not applicable. The statistics verification covered 28 tests (all consistent) but is limited to tests with a test statistic + df or effect estimate + CI; threshold p-values were not verifiable.

12 major claims checked against the paper's own evidence: all adequately supported.

Recomputed 28 tests: 28 consistent, 0 inconsistent, 28 via agent-written checks.

2 integrity concerns flagged (1 high).

Rigor

Eight Dimensions2 pass · 5 warn

12 major claims1 partial11 supported

The introduction cites numerous prior studies on continuance intention of various apps (knowledge payment, fitness, social media) and on the roles of interactivity, richness, reliability, and personalization in user satisfaction and trust. A gap is identified: limited research on AI-powered map applications specifically. The study then formulates explicit hypotheses linking each characteristic to satisfaction and trust, and those to continuance intention. The limitations of prior work are discussed (e.g., few studies used app characteristics as a starting point), and the present study aims to fill that gap.

Sub-criteria

prior work citedADEQUATE

premise rationaleADEQUATE

limitations addressedADEQUATE

Per reviewer (3) — the votes behind the verdict

PASSReviewer 1· 95% conf

The premise is well-established: prior work on app continuance intention, satisfaction, trust, and the chosen characteristics is cited, a clear rationale links concepts to the study's objectives, and limitations of prior research are acknowledged in the introduction.

Evidence

paraphrase[Introduction, paragraph 4–6]

“The introduction reviews studies on continuance intention of various apps and on how interactivity, richness, reliability, and personalization affect satisfaction and trust, establishing the research gap for AI-powered map apps.”

direct quote[Introduction, paragraph 3; Section 2]

“This study aims to fill this gap by exploring how these characteristics—interactivity, richness, reliability, and personalization—impact user satisfaction and trust, and consequently, the intention to continue using map applications.”

direct quote[Introduction, paragraph 7]

“from the existing literature, ... few scholars study the app characteristics as the starting point of its continuance intention.”

PASSReviewer 2· 90% conf

The paper establishes a clear scientific foundation by citing prior work, building a logical rationale, and addressing gaps in the literature.

Evidence

direct quote[Introduction, paragraph 3]

“However, the long-term intention of users to continue using AI-enhanced map applications has not been thoroughly examined.”

direct quote[Section 2.2, Hypotheses developments]

“According to the analysis of the relationship between interactivity characteristics, satisfaction, and trust, the following hypothesis is proposed in this study.”

direct quote[Introduction, paragraph 4]

“Academic research on the continuance intention of apps is more enthusiastic... but studies on map and travel navigation apps are more limited.”

PASSReviewer 3· 92% conf

The paper provides a thorough review of prior work on app continuance intention and clearly links the cited literature to the study's objectives and hypotheses.

Evidence

paraphrase[Introduction, paragraphs 3-5]

“The authors cite studies on app continuance intention in various domains (knowledge payment, short video, fitness) and state that 'studies on map and travel navigation apps are more limited' and 'few scholars study the app characteristics as the starting point of its continuance intention'.”

direct quote[Introduction, final paragraph; Section 2.2]

“"Exploring this question will yield critical insights for developers and operators of map applications, helping them enhance their offerings and encourage sustained user engagement."”

direct quote[Introduction, paragraph 5]

“"Nevertheless, there is a noticeable lack of research that delves into how these factors interact specifically within the realm of AI-powered map applications. This research seeks to fill this gap..."”

For an observational survey-based SEM study, many traditional design criteria (randomization, blinding, replicate distinction, controls) are not applicable. The sampling method (stratified random) is stated and adequate for obtaining a representative sample. Inclusion/exclusion criteria are partially reported (only 'invalid questionnaires' eliminated, no pre-specified criteria). Outlier handling is not reported. No power analysis or independent replication is mentioned. The study relies on a single survey administration, so no biological replicates or technical controls apply. The questionnaire items and scales are adapted from prior work, which is adequate.

Sub-criteria

controlsN/A

power analysisNOT REPORTED

blinding levelsN/A

outlier handlingNOT REPORTED

randomization unitN/A

inclusion exclusionINADEQUATE

randomization methodN/A

replicate distinctionN/A

independent replicationNOT REPORTED

Per reviewer (3) — the votes behind the verdict

WARNReviewer 1· 85% conf

The study uses an observational cross-sectional survey design with stratified random sampling, but lacks a pre-registered analysis plan, power analysis, explicit outlier handling, and independent replication. The measurement model is well-evaluated via CFA.

Evidence

direct quote[Section 3.1, paragraph 2]

“Stratified random sampling is an effective method to ensure that these distinct groups are well-represented within the sample.”

direct quote[Section 3.1, paragraph 3]

“525 questionnaires were collected, and 460 valid questionnaires were retained after eliminating invalid questionnaires.”

absence[Section 3 and 4]

No power analysis is reported.

WARNReviewer 2· 85% conf

The study design is a cross-sectional survey, which limits causal inference. Inclusion/exclusion criteria are not explicitly stated, and no power analysis or sample size justification is provided.

Evidence

direct quote[Section 3.1, Research subjects and data collection]

“Stratified random sampling is an effective method to ensure that these distinct groups are well-represented within the sample.”

absence[Section 3.1, Research subjects and data collection]

No power analysis or sample size justification is reported.

direct quote[Section 3.1, Research subjects and data collection]

“525 questionnaires were collected, and 460 valid questionnaires were retained after eliminating invalid questionnaires.”

WARNReviewer 3· 85% conf

The study uses a cross-sectional survey with stratified random sampling, but lacks a pre-registration, power analysis, and details on exclusion criteria, and does not define how outliers were handled.

Evidence

absence[Section 3.1]

No a priori power analysis or sample-size calculation is reported.

direct quote[Section 3.1]

“"525 questionnaires were collected, and 460 valid questionnaires were retained after eliminating invalid questionnaires."”

absence[Section 3.1]

No description of how outliers or invalid responses were handled.

The sample demographics are described in detail: gender (282 male, 178 female), age groups (89.1% under 30), education, marital status, and monthly expenditure. The paper provides a justification for the higher proportion of males by stating that males are more inclined to use map apps. Age and health status are not applicable for this context. The study does not involve animal subjects, so species and housing conditions are not applicable.

Sub-criteria

demographicsADEQUATE

sex reportedADEQUATE

sex justifiedADEQUATE

age weight healthADEQUATE

housing conditionsN/A

species strain sourceN/A

Per reviewer (3) — the votes behind the verdict

PASSReviewer 1· 90% conf

The study involves human participants via survey, so sex, age, education, consumption level, and usage duration are reported in the sample demographics. No biological variables (species, strain, housing) apply.

Evidence

direct quote[Section 3.1, paragraph 4]

“282 (61.3 %) were male, and 178 (38.7 %) were female. There are significantly more males than females, mainly because males are more inclined to use map apps compared to females.”

direct quote[Section 3.1, paragraph 4]

“Among them, 89.1 % were under 30 years old, 8.1 % were between 30 and 50 years old, and 2.8 % were over 50 years old.”

paraphrase[Section 3.1, paragraph 4]

“Education level (bachelor's, master's, doctoral), monthly expenditure categories, and continuous usage time are tabulated and described.”

PASSReviewer 2· 95% conf

The paper adequately reports demographic variables such as sex, age, education, marital status, and consumption level, which are appropriate for a human survey study.

Evidence

direct quote[Section 3.1, Research subjects and data collection]

“In terms of gender, 282 (61.3 %) were male, and 178 (38.7 %) were female. There are significantly more males than females, mainly because males are more inclined to use map apps compared to females, while females travel relatively less.”

direct quote[Section 3.1, Research subjects and data collection]

“Among them, 89.1 % were under 30 years old, 8.1 % were between 30 and 50 years old, and 2.8 % were over 50 years old.”

direct quote[Section 3.1, Research subjects and data collection]

“In terms of education, there were 154 bachelor's degree holders, 244 master's degree holders, and 62 doctoral degree holders.”

N/AReviewer 3· 100% conf

The study is a survey of human users; no biological variables (sex, age, health, species, strain, housing) are relevant to the research question or study objects.

Evidence

paraphrase[Section 3.1, Table 1 notes]

“Descriptive statistics on gender, age, marital status, education, and consumption level are provided but are not used as biological variables in the model.”

The paper's 'Ethics approval' section reads: 'Not Applicable.' The authors append a parenthetical note: '(non-biological or non-medical manuscripts do not need to write this part).' This is not a valid justification for waiving ethics review when collecting self-report data from human subjects. No named IRB or ethics committee approval is reported, and no informed consent statement is provided (beyond the implication of voluntary questionnaire participation). For a survey study of human participants, an ethics statement is required; failing to provide one for non-public human-subject data constitutes inadequate reporting.

Sub-criteria

iacuc statementN/A

informed consentNOT REPORTED

irb ethics statementNOT REPORTED

regulatory complianceNOT REPORTED

Per reviewer (3) — the votes behind the verdict

WARNReviewer 1· 90% conf

Although the study involves human subjects (collecting data via questionnaire), the ethics section states 'Not Applicable,' with the note 'non-biological or non-medical manuscripts do not need to write this part.' This is inadequate: survey-based research with human participants requires ethical review or a stated exemption.

Evidence

direct quote[Ethics approval section]

“Not Applicable.”

direct quote[Ethics approval section]

“(non-biological or non-medical manuscripts do not need to write this part)”

WARNReviewer 2· 90% conf

The paper states 'Not Applicable' for ethics approval, but this is a human subjects survey and ethics approval should have been obtained. No informed consent statement is provided.

Evidence

direct quote[Ethics approval section]

“Ethics approval (non-biological or non-medical manuscripts do not need to write this part) Not Applicable.”

absence[Ethics approval section]

No informed consent statement is provided.

absence[Ethics approval section]

No regulatory compliance statement is provided.

WARNReviewer 3· 70% conf

The paper states ethics approval is 'Not Applicable' and provides no details on approval or consent, yet the study collected survey data from human participants, which requires appropriate ethics oversight.

Evidence

direct quote[Ethics approval section]

“"Not Applicable."”

absence[Sections 3.1 and Ethics approval]

No informed consent process is described.

The study uses questionnaire data and analyses it with structural equation modeling via 'Amous 24.0' (likely a typo for 'Amos 24.0'). This is a standard statistical software package; its version and vendor could be identified but the standard nature makes this not applicable for key resources. No antibodies, cell lines, organisms, plasmids, or novel reagents are used. The dimension is scored not_applicable because no key biological/chemical resource, investigational product, or bespoke software was used.

Sub-criteria

mycoplasma testingN/A

reagents identifiedN/A

organisms identifiedN/A

antibodies identifiedN/A

cell line authenticationN/A

software tools identifiedN/A

Per reviewer (3) — the votes behind the verdict

N/AReviewer 1· 95% conf

The study is a human-subjects survey with no drugs, biologics, devices, wet-lab reagents, cell lines, antibodies, or bespoke software (Amos 24.0 is a standard tool). No key biological or chemical resources are used, and the only software used (Amos 24.0) is a standard commercial package, not a novel tool requiring full identification.

Evidence

direct quote[Section 3.3]

“this study uses Amous 24.0 to analyze the collected data”

PASSReviewer 2· 95% conf

The study uses only a questionnaire and statistical software; the software (Amos 24.0) is identified, and no other biological or chemical resources are applicable.

Evidence

direct quote[Section 3.3, Analysis method]

“As in previous Structural Equation Modeling (SEM) data methods, this study uses Amous 24.0 to analyze the collected data.”

N/AReviewer 3· 95% conf

The study used a survey questionnaire as its only instrument; no biological/chemical resources, investigational products, or bespoke analysis software beyond standard proprietary SEM tools were used.

Evidence

paraphrase[Section 3.1, 3.2]

“The study uses a questionnaire measuring perceived characteristics, satisfaction, trust, and continuance intention, and analyzes data with Amos 24.0.”

The tests used (SEM path analysis) are named, and fit indices are reported. However, normality and other assumptions of maximum-likelihood estimation are not explicitly verified (though CFA and model fit tests are conducted, which partially address this). Exact p-values are presented in Table 3 for most paths (e.g., '∗∗' p<0.01, '∗∗∗' p<0.001), but the table uses asterisks rather than exact numbers — this is typical but not as precise as full exact p-values. Effect sizes (standardized beta coefficients) are reported, but no confidence intervals for these coefficients are given. The software (Amos 24.0) is identified. Data presentation: the paper shows loading tables, model fit, and path diagrams, but no individual data points, and error bars (SD/SEM) are not used because it's a latent-variable model. The mathematical plausibility is not applicable because the data are Likert-scale composites, not integer counts where a GRIM test would apply.

Sub-criteria

tests namedADEQUATE

exact p valuesINADEQUATE

effect sizes ciINADEQUATE

data presentationADEQUATE

software identifiedADEQUATE

assumptions verifiedINADEQUATE

mathematical plausibilityN/A

Per reviewer (3) — the votes behind the verdict

WARNReviewer 1· 85% conf

The study reports path coefficients, p-values, model fit indices, and reliability/validity metrics adequately, but fails to verify standard test assumptions (normality, homoscedasticity), reports p-values as thresholds (e.g., p<0.01) rather than exact values in some cases, and does not provide effect sizes or confidence intervals for path coefficients. Data presentation shows individual loadings but no raw data points or error-bar definitions relevant.

Evidence

direct quote[Table 2 and Section 4.1]

“CFI >0.9 0.974 Pass; RMSEA <0.08 0.041 Pass; TLI >0.9 0.970 Pass; GFI >0.9 0.943 Pass”

paraphrase[Section 4.1]

“The paper reports convergent and discriminant validity and model fit, but does not explicitly mention testing normality or homoscedasticity assumptions for the SEM.”

direct quote[Table 3]

“p-value ∗∗ Supported; p-value ∗∗∗ Supported”

WARNReviewer 2· 85% conf

Statistical tests are named, exact p-values are reported, and model fit indices are provided. However, assumptions (normality, equal variance) are not verified, and effect sizes with confidence intervals are not reported.

Evidence

direct quote[Table 2, Results of model fit for structural model]

“CFI >0.9 0.974 Pass, RMSEA <0.08 0.041 Pass, TLI >0.9 0.970 Pass, GFI >0.9 0.943 Pass, NFI >0.9 0.943 Pass, χ2/df <3 1.785 Pass, AGFI >0.8 0.925 Pass”

direct quote[Table 3, Results of regression analyses for hypotheses testing]

“∗p < 0.05. ∗∗p < 0.01. ∗∗∗p < 0.001.”

absence[Section 3.3, Analysis method]

Assumptions such as normality and equal variance are not verified.

WARNReviewer 3· 80% conf

Statistical tests (path coefficients) are clearly reported, exact p-values and significance levels are given, and model fit indices are comprehensive; however, effect sizes (standardized coefficients) are reported but not with confidence intervals, and no assumption verification (normality, linearity) for SEM is provided.

Evidence

absence[Section 3.3]

No verification of SEM assumptions (e.g., multivariate normality) is reported.

paraphrase[Tables 3 and Figure 2]

“Standardized coefficients are reported (e.g., β=0.180, β=0.296) but no confidence intervals are provided for these estimates.”

The data_availability_statement is present but inadequate: it only says 'Data will be provided on reasonable request from the corresponding author,' with no mention of a repository, managed-access platform, or data-access committee. No repository deposit or accession numbers are provided. Code sharing is not applicable because the study used standard software (Amos) and no custom code. For a survey study, anonymized data could be deposited in a public repository; not doing so and having only a vague 'reasonable request' statement makes this a warning.

Sub-criteria

code sharingN/A

accession numbersN/A

repository depositNOT REPORTED

data availability statementINADEQUATE

Per reviewer (3) — the votes behind the verdict

WARNReviewer 1· 95% conf

A data availability statement exists ('Data will be provided on reasonable request from the corresponding author'), but this is a vague mechanism with no platform, conditions, or timeframe, which corresponds to reported_but_inadequate. No code is shared, and no repository deposit or accession numbers are provided. The statement is a bare 'on request' without any concrete access route.

Evidence

direct quote[Availability of data and materials section]

“Data will be provided on reasonable request from the corresponding author.”

absence[Availability of data and materials section; whole paper]

No code sharing or repository deposit mentioned.

WARNReviewer 2· 90% conf

A data availability statement is present but vague ('available on reasonable request'), and no code sharing is provided. The paper does not deposit data in a repository.

Evidence

direct quote[Availability of data and materials]

“Data will be provided on reasonable request from the corresponding author.”

absence[Availability of data and materials]

No repository deposit or accession numbers are provided.

absence[Availability of data and materials]

No code sharing is reported.

WARNReviewer 3· 85% conf

A data availability statement is present but is vague ('provided on reasonable request'), without a repository, platform, or conditions; no code is shared.

Evidence

direct quote[Availability of data and materials]

“"Data will be provided on reasonable request from the corresponding author."”

absence[Entire manuscript]

No code is shared or mentioned.

The methods section (3.1–3.3) provides sufficient detail on sampling, questionnaire items, and analysis for an independent researcher to follow the approach. The study is a survey, so trial registration and CONSORT are not applicable. No reporting checklist is mentioned (e.g., STROBE for cross-sectional studies). All outcomes pre-specified in the hypotheses are reported in tables and figures. Limitations are discussed (single-source data, omitted factors, generalizability), though they are somewhat brief and generic. Conclusions match the SEM results — no overclaiming to causality beyond associations. Funding is stated as 'Not Applicable' and a conflicts-of-interest statement is present. The overall transparency is moderate.

Sub-criteria

funding coiADEQUATE

trial registrationN/A

reporting guidelineNOT REPORTED

methods completenessADEQUATE

all outcomes reportedADEQUATE

limitations discussedADEQUATE

conclusions proportionalADEQUATE

Per reviewer (3) — the votes behind the verdict

WARNReviewer 1· 90% conf

Methods are described in adequate detail for replication (sampling, measurement, analysis), but no reporting guideline (e.g., STROBE) is referenced, the study is not registered (though not required for a non-interventional survey), the limitations section is present but somewhat generic, the conclusions are proportional to the evidence, and a funding/COI statement is provided ('Not Applicable' for funding, and a competing interests statement is present). However, the lack of a formal reporting guideline and the incomplete ethical oversight reporting lower the transparency.

Evidence

absence[Section 3 and 4]

No reporting guideline (e.g., STROBE) is mentioned.

direct quote[Section 5.4]

“First, this study provides empirical evidence ... relying primarily on online questionnaires for data collection. However, this single-source data approach may limit the study's scope.”

direct quote[Funding statement; Declaration of competing interest]

“Funding statement Not Applicable.; Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.”

PASSReviewer 2· 85% conf

The paper provides detailed methods, discusses limitations, states funding and conflicts of interest, and draws conclusions proportional to the evidence. No trial registration or reporting guideline is mentioned, but these are not standard for this type of study.

Evidence

direct quote[Section 5.4, Research limitations and future research development]

“First, this study provides empirical evidence on mobile map app usage in the context of mobile internet research, relying primarily on online questionnaires for data collection.”

direct quote[Funding statement and Declaration of competing interest]

“Funding statement Not Applicable. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.”

absence[Throughout paper]

No reporting guideline is referenced.

WARNReviewer 3· 80% conf

Methods are described in sufficient detail for replication, limitations are discussed, and conclusions are proportional to the evidence; however, no trial registration (not applicable), no reporting checklist is referenced, and the funding/conflict-of-interest statements are present but minimal.

Evidence

absence[Entire manuscript]

No reporting checklist (e.g., STROBE) is referenced.

direct quote[Funding statement]

“"Not Applicable."”

21 copyedit issues flagged (1 major): mostly clarity, consistency, typo.

Checked 127 references: 13 verified — 114 not checked.

Αlpha¹ Rigor Action ItemsFinal pass before journal submission

As a published paper, an informed reader should weigh the missing ethics oversight and the internal contradiction in the reported AVE values as the most serious concerns. The paper would benefit from a correction or erratum addressing the AVE discrepancy, and the authors should clarify the ethics approval status. The statistical results appear consistent where checked, but the lack of assumption verification and confidence intervals limits interpretability.

1.
HIGHreporting
Correct the stated AVE range in Section 4.1 (currently '0.840 to 0.922') to match the actual values listed (0.661 to 0.707).
This is a clear numerical contradiction that undermines the reporting of convergent validity and must be corrected in an erratum.
2.
HIGHethics
Add the name of the IRB/ethics committee that approved the survey, along with a protocol number, in the Ethics approval section; if no formal approval was obtained, state the reason for exemption and provide the institutional policy that permits this.
The current statement ('Not Applicable') is insufficient for a human-subjects survey; an informed reader cannot verify that ethical oversight was in place.
3.
HIGHethics
Add an informed consent statement in Section 3.1 describing how participants were informed and that consent was obtained (or explicitly waived with justification).
The paper reports collecting survey data from human participants but provides no description of consent procedures.
4.
HIGHdata code
Deposit the de-identified survey dataset in a public repository (e.g., Zenodo, Figshare, Harvard Dataverse) and update the Data Availability statement with the DOI and repository name.
The current vague 'reasonable request' statement does not meet transparency standards and prevents verification.
5.
HIGHstatistics
In Table 3, replace threshold asterisks with exact p-values (e.g., p = 0.002) and add 95% confidence intervals for all standardized path coefficients.
Threshold p-values are less precise and confidence intervals provide needed effect-size precision for informed interpretation.
6.
HIGHstatistics
In Section 3.3, report verification of SEM assumptions (e.g., Mardia's coefficient for multivariate normality, linearity checks) and state how any violations were handled (e.g., Bollen-Stine bootstrap, robust ML).
The absence of assumption checks weakens confidence in the SEM results.
7.
HIGHreporting
Reference the STROBE checklist for cross-sectional studies in the Methods section and indicate that the manuscript adheres to it.
Using a recognized reporting guideline improves transparency and facilitates critical appraisal.
8.
MEDIUMother
In Section 3.1, define the criteria used to determine 'invalid questionnaires' (e.g., minimum completion time, attention checks, missing data threshold) and report how many were excluded for each reason.
Without these criteria, the validity of the final sample cannot be assessed.
9.
MEDIUMother
Add a power analysis or sample-size justification in the Methods (Section 3.1), citing the expected effect size, alpha, and power for the SEM analysis.
The adequacy of N=460 for detecting the modeled path coefficients is not justified.
10.
MEDIUMother
Add a section on outlier handling in Section 3.1, stating whether any responses were excluded due to outliers and the criteria used, or note that no outliers were removed.
The paper does not address how extreme or inconsistent responses were identified or handled.
11.
MEDIUMreporting
In the Funding statement, provide specific details: either list the funding source(s) or state explicitly that the research received no external funding.
The current 'Not Applicable' is ambiguous; readers need to know whether funding was received but not disclosed.
12.
LOWcopyedit
Correct the typo 'Amous 24.0' to 'Amos 24.0' throughout the manuscript (Sections 3.3).
The software name is misspelled, which could cause confusion.
13.
LOWcopyedit
Fix the incomplete reference in Table 3 footnote: 'consistent with and ' should read 'consistent with H1a and H1b, respectively'.
The incomplete reference to hypotheses is unclear.
14.
LOWcopyedit
Correct the reference spelling 'Bhattacharjee' to 'Bhattacherjee' in Section 3.2.
The commonly cited author for continuance intention is Bhattacherjee.
15.
LOWcopyedit
Fix the inconsistent numbering 'RECL4' to 'REC4' in Table 1 to match the pattern.
Inconsistent item labels could confuse readers.
16.
LOWcopyedit
Remove the duplicate sentence in Section 2.2.2 (Richness, satisfaction, and trust) that appears verbatim twice.
Duplicate text is a distraction and suggests a copy-paste error.

Full text (61,895 chars)Analyzed: Jul 6, 2026

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