{"doc_desc":{"title":"zaf-ria-rias-2011-2012-v1","idno":"DDI_AFR_2011_RIAS_v02_M","producers":[{"name":"DataFirst","abbreviation":"","affiliation":"University of Cape Town","role":"Metadata producer"}],"prod_date":"2019-06-26","version_statement":{"version":"DDI Document  - Version 02 - (04\/27\/21)\n This version is identical to DDI_AFR_2011_RIAS_v01_M but country field has been updated to capture all the countries covered by survey.\n\n Version 01 (September 2019): This DDI is identical to 'zaf-ria-rias-2011-2012-v1' which was downloaded from the DataFirst website."}},"study_desc":{"title_statement":{"idno":"AFR_2011_RIAS_v01_M","title":"Household and Small Business ICT Access and Usage Survey 2011-2012","alt_title":"RIAS 2011-2012"},"authoring_entity":[{"name":"Research ICT Africa","affiliation":""}],"distribution_statement":{"contact":[{"name":"DataFirst Support","affiliation":"","email":"support@data1st.org","uri":"support.data1st.org"}]},"series_statement":{"series_name":"Other Household Survey [hh\/oth]"},"version_statement":{"version":"Version 01: Edited, anonymised dataset for licensed distribution","version_date":"2012","version_notes":"Version 01 of the dataset was received from Research ICT Africa in July 2015."},"study_info":{"abstract":"Research ICT Africa (RIA) is a non-profit, public interest, research entity which undertakes research on how information and communication technologies are being accessed and used in African countries. The aim is to measure the impact on lifestyles and livelihoods of people and households and to understand how informal businesses can prosper through the use of ICTs. This research can facilitate informed policy-making for improved access, use and application of ICT for social development and economic growth. RIA collects both supply-side and demand-side data. On the demand-side nationally representative surveys are conducted on ICT use and demand in African countries. This survey dataset consists of data collected by household and business surveys in thirteen African countries in 2011-2012.","coll_dates":[{"start":"2011","end":"2012","cycle":""}],"nation":[{"name":"Botswana","abbreviation":"BWA"},{"name":"Cameroon","abbreviation":"CMR"},{"name":"Ethiopia","abbreviation":"ETH"},{"name":"Ghana","abbreviation":"GHA"},{"name":"Kenya","abbreviation":"KEN"},{"name":"Mozambique","abbreviation":"MOZ"},{"name":"Namibia","abbreviation":"NAM"},{"name":"Nigeria","abbreviation":"NGA"},{"name":"Rwanda","abbreviation":"RWA"},{"name":"Tunisia","abbreviation":"TUN"},{"name":"Tanzania","abbreviation":"TZA"},{"name":"Uganda","abbreviation":"UGA"},{"name":"South Africa","abbreviation":"ZAF"}],"geog_coverage":"The surveys had national coverage. Survey countries included Botswana, Cameroon, Ethiopia, Ghana, Kenya, Mozambique, Namibia, Nigeria, Rwanda, South Africa, Tanzania, Uganda, and Tunisia.","analysis_unit":"Households and individuals","universe":"The data is nationally representative on a household and individual level for individuals 16 years of age or older.","data_kind":"Sample survey data [ssd]","notes":"Data collected on households includes: Dwelling type, household expenditure, access to electricity, ownership of goods, data on postal address and bank accounts, access to, use of, and expenditure on internet and landline, as well as household remittances. \n\nData collected on household members includes: Age, sex, relationship to household head, marital status, highest education level, main economic activity, income and other earnings, and mobile phone ownership. A household member was selected at random to provide more detailed data. Data collected on the Randomly Selected Individual includes: Contribution to household expenses, literacy, language, ownership of CD\/MP3 player\/ipod, social networks, money and banking, use of TV, radio, public phones, work phone, internet, detailed data on mobile phone usage."},"method":{"data_collection":{"sampling_procedure":"The random sampling was performed in four steps for households and businesses, and five steps for individuals.\n\u2022 Step 1: The national census sample frames was split into urban and rural Enumerator areas (EAs).\n\u2022 Step 2: EAs were sampled for each stratum using probability proportional to size (PPS).\n\u2022 Step 3: For each EA two listings were compiled, one for households and one for businesses. The listings serve as sample frame for the simple random sections.\n\u2022 Step 4: 24 Households and 10 businesses were sampled using simple random sample for each selected EA.\n\u2022 Step 5: From all household members 15 years or older or visitors staying the night at the house one was randomly selected based on simple random sampling.","coll_mode":"Face-to-face [f2f]","weight":"Three weights were constructed, for households, individuals and for small businesses. The weights are based on the inverse selection probabilities and gross up the data to national level when applied."}},"data_access":{"dataset_use":{"contact":[{"name":"DataFirst","affiliation":"University of Cape Town","email":"support@data1st.org","uri":"support.data1st.org"}],"cit_req":"Research ICT Africa. RIA ICT Access Survey 2011-2012 [dataset]. Version 1. Cape Town: RIA [producer], 2013. Cape Town: DataFirst [distributor], 2015. 10.25828\/mef4-3810","conditions":"Licensed use files, available with restrictions","disclaimer":"The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses."}}},"schematype":"survey","tags":[{"tag":"noDOI"}]}