Corporate Criminal Compliance and Corporate Fraud Prevention
Description
This dataset contains the bibliographic records, screening outputs, relevance assessments, and consolidated evidence tables used to support the article on corporate criminal compliance, corporate fraud prevention, and related mechanisms of transparency and governance. The files include both raw and processed data in Excel format. Raw_Data.xlsx preserves intermediate search and screening outputs across multiple worksheets, including search results, preliminary relevance filtering, full-text review extracts, and thematic article tables. Data(1).xlsx contains the consolidated datasets used for analysis, including a combined corpus on corporate compliance research and a complementary corpus on blockchain, transparency, auditability, and corporate governance. The variables included across the spreadsheets comprise bibliographic metadata and analytical descriptors such as paper title, publication year, publication type, journal or publication title, author names, DOI, PDF link when available, open access status, citation count, Google Scholar identifier, abstract, relevance notes, TL;DR summaries, and relevant excerpts. These data were organized to facilitate article screening, thematic classification, comparative analysis, and bibliometric interpretation. The dataset is intended for transparency, reproducibility, and secondary analysis. It may be useful for researchers working on corporate compliance, fraud prevention, corporate governance, blockchain-enabled transparency, audit quality, regulatory effectiveness, and bibliometric methods. The files do not contain personal sensitive data or human subject data. Missing values may appear in fields such as DOI, citation count, abstract, publication title, or year, depending on source availability at the time of extraction and screening.
Files
Steps to reproduce
To reproduce the dataset, first define the research scope around corporate criminal compliance, fraud prevention, program effectiveness, corporate governance, blockchain, transparency, and auditability. Next, conduct systematic literature searches in academic databases and scholarly search engines using combinations of relevant keywords related to compliance programs, fraud prevention, regulatory effectiveness, blockchain, financial transparency, and corporate governance. Export the retrieved records and compile them in spreadsheet format. Then, perform an initial screening based on title, abstract, year, document type, and thematic relevance. After this, carry out a second-stage review to classify the studies according to their relevance to the research objectives. Extract and standardize bibliographic metadata for each record, including title, publication year, publication type, source title, author names, DOI, open access status, citation counts, abstract, and analytical notes. Organize the records into structured worksheets separating raw search outputs, screened records, and consolidated analytical corpora. Finally, merge the eligible records into the final datasets used for bibliometric and thematic analysis, including one consolidated dataset on corporate compliance research and another on blockchain, transparency, auditability, and governance.
Institutions
- Universidad Autónoma del PerúLima Province, Lima