DOI: 10.7910/dvn/r2w8aw
title: A dataset of employers’ hiring decision factors in Oman, examining what organizations look for when recruiting graduates and the underlying reasons

description: The data were generated to investigate the criteria, preferences, and underlying rationales guiding employers’ recruitment decisions for university graduates in the Sultanate of Oman. The study adopted a mixed-methods research design, combining quantitative survey data with qualitative interview data to provide both breadth and depth of analysis.

Data generation procedures and processing methods:

Quantitative data were collected through a structured questionnaire administered to employers and human resource managers across multiple economic sectors, including public, private, and semi-government organizations. The survey instrument was developed based on an extensive literature review and piloted prior to full deployment to ensure validity and reliability. Qualitative data were generated through semi-structured interviews designed to explore employers’ reasoning behind specific hiring preferences. Data cleaning procedures included checking for incomplete responses, removing duplicate entries, coding categorical variables, and anonymizing all personal and organizational identifiers to ensure confidentiality. Quantitative data were processed and analyzed using statistical software (e.g., SPSS), while qualitative interview transcripts were coded thematically using qualitative data analysis software (e.g., NVivo).

Temporal and geographical scope:

Data collection was conducted between 2020 and 2021 across multiple regions of Oman. The geographical scope covers major urban and economic centers, ensuring representation of diverse industries and organizational sizes. The temporal resolution corresponds to cross-sectional data collected during the study period.

Tabular data structure:

The quantitative dataset consists of structured tabular data in spreadsheet format (Dta, .xlsx and .csv). Each row represents a single organizational respondent, while columns represent variables including organizational characteristics (e.g., sector, size), evaluated graduate attributes (e.g., technical skills, soft skills, academic performance, work experience), and rated importance levels (measured using Likert-scale units). Additional columns capture ranking scores and categorical responses. The qualitative dataset includes interview transcripts in .docx and .pdf formats, with coded thematic categories stored in analysis files.

Missing data and data integrity:

Some survey entries contain missing values due to non-response to specific questionnaire items. These are coded consistently (e.g., blank cells or system-missing indicators) and documented in the codebook. Cases with excessive missing data were excluded from statistical analysis. Minor data entry inconsistencies were corrected during the cleaning process. As the dataset relies on self-reported employer responses, potential response bias should be considered when reusing the data.

Data files and formats:

The dataset includes:

A quantitative survey dataset (.xlsx, DTA and .csv formats).
A qualitative interview transcript collection (.docx and .pdf).
A codebook (.pdf) describing variable names, labels, measurement scales, and coding schemes.
A methodological documentation file detailing survey design, sampling strategy, and analytical procedures.
All file formats are compatible with widely available software such as SAS and Stata, Microsoft Excel, SPSS, NVivo, and standard PDF readers. No proprietary or rare file formats are used.