{"doc_desc":{"title":"SLE_2019_WE-FI_v01_M","idno":"DDI_SLE_2019_WE-FI_v01_M_WB","producers":[{"name":"Development Economics Data Group","abbreviation":"DECDG","affiliation":"The World Bank","role":"Documentation of the DDI"}],"prod_date":"2019-11-05","version_statement":{"version":"Version 01 (November 2019)"}},"study_desc":{"title_statement":{"idno":"SLE_2019_WE-FI_v01_M","title":"We-Fi WeTour Women in Tourism Enterprise Survey 2019","alt_title":"WE-FI 2019"},"authoring_entity":[{"name":"Louise Twining-Ward (World Bank - Finance, Competitiveness and Innovation Global Practice, Markets & Technology Unit)","affiliation":""}],"oth_id":[{"name":"Abhishek Saurav","affiliation":"World Bank Group","email":"","role":"Economist"},{"name":"Souleima Hilal","affiliation":"World Bank Group","email":"","role":"Analyst"},{"name":"Wendy Li","affiliation":"World Bank Group","email":"","role":"Coordinator"},{"name":"Fares Khoury","affiliation":"EECI","email":"","role":"Data Collection"}],"production_statement":{"copyright":"\u00a9 2019 The World Bank Group","funding_agencies":[{"name":"World Bank","abbreviation":"","role":"Financing"}],"grant_no":"TF07318"},"distribution_statement":{"contact":[{"name":"Louiset Twining-Ward","affiliation":"World Bank Group","email":"ltwiningward@worldbank.org","uri":""},{"name":"Abhishek Saurev","affiliation":"World Bank Group","email":"asaurav@ifc.org","uri":""}]},"series_statement":{"series_info":"The World Bank We-Fi WeTour Women in Tourism Enterprise Survey was conducted in Sierra Leone and Ghana."},"version_statement":{"version":"Edited, anonymous dataset for public distribution."},"study_info":{"abstract":"The World Bank WeTour Project aimed to contribute to improved knowledge of the characteristics of Women-owned\/led Micro, Small and Medium Sized Enterprises (WSMEs) in tourism in Ghana and Sierra Leone. It is intended that this knowledge and data will be used by projects and programs in those countries to inform the design of gender-targeted tourism SME support services.  This survey is representative of male and female enterprises.","coll_dates":[{"start":"2019-04-22","end":"2019-05-31","cycle":""}],"nation":[{"name":"Sierra Leone","abbreviation":"SLE"}],"geog_coverage":"In Sierra leone, two destination areas were identified as Freetown and the Western Area.","analysis_unit":"Micro, Small and Medium Tourism and tourism-related enterprises","universe":"The universe of MSMEs in Tourism and Tourism-related sectors of Freetown and the Western Area in Sierra Leone comprises 1,067 entities identified individually in the sampling frame.","data_kind":"Sample survey data [ssd]","notes":"The survey collected information from Micro, Small and Medium Tourism and tourism-related enterprises on the following thematic areas:\n\u2022 business characteristics\n\u2022 investment climate\n\u2022 marketing and sales\n\u2022 production and operations\n\u2022 human resources\/ workforce\n\u2022 finance and accounting\n\u2022 business strategy\n\u2022 ICT usage\nThe survey use in Sierra Leone and Ghana was a portion of BESTIN-OPMes, (for Benchmarking Strategy and Innovation \u2013 Operations People Money \u2013 enterprise survey) a larger global enterprise survey that belongs to EECi with additional information available at www.groupeeci.com"},"method":{"data_collection":{"data_collectors":[{"name":"Economic Expertise & Consulting International","abbreviation":"ECCI","affiliation":""}],"sampling_procedure":"The universe  of tourism and tourism related SMEs was constructed in each country using all available sources. For both countries the original sample frame of SMEs was compiled from previous sample frames developed for enterprise surveys by EEC International, the amalgamation of past listings of SMEs from the NSO and other public registries, as well as numerous other sources collated from business associations and other publicly available sources of tourism-related information portals, namely: travel agent reservation systems such as Amadeus and Sabre, tourism and tourism-related websites such as Expedia and TripAdvisor, as well as establishments referenced on Google Maps and appearing on Google Street View.  The sample frame for micro enterprises was planned to result from systematic block enumeration in the targeted locations. During the block enumeration, entities were identified by a number on a list and a geographical reference (map or other description of the location), information on its apparent activity (tourism or tourism-related), as well as visible gender composition (no apparent female, no apparent male, mixed presence). Neither the activity composition nor the gender composition were known at inception. The  validation of the sample frame consisted in ensuring that there were no foreign elements (activities not included in the universe under study). \n\nThe sampling strategy that EECI applied for the Tourism and Tourism related Sectors applying consisted in randomly drawing from the frame of MSMEs a screened sample until the minimum number of male and female respondents targeted was obtained, inclusive of the expected non-response. \n\nFor Sierra Leone, the frame contained a total of 1,067 entities, of which 705 micros and 362 SMEs. A random draw of 323 entities, consisting of 212 micros and 111 SMEs generated through a screening 125 female entities and 198 male entities. The entire group of 125 female entities was directed to interviewing, and the first 125 male entities that were screened, were directed to interviewing, with an expected 120 respondents by genre. For more details see Methodology Note provided under Related Documents.","coll_mode":"Face-to-face [f2f]","act_min":"World Bank Team - Finance, Competitiveness and Innovation Global Practice, Markets & Technology Unit","weight":"The final dataset contains three of weight estimations according to sub-groups of businesses: \n\u2022 by size (two categories - Micro or SME),\n\u2022 by gender (two categories - Male or Female enterprises)\n\u2022 and by size-gender (four categories - Micro-male, Micro-female, SME-male and SME-female).\nThe weight of each category, in each one of the sub-groups of businesses, is the ratio between the actual population in the category and the effective number of respondents in this same category.\nPopulation distribution by size was a known characteristic, while gender distribution was unknown. In order to obtain population composition by gender, screening proportions were used as a proxy.","cleaning_operations":"Data entry and quality controls were implemented by the contractor then data was delivered to the World Bank. The World Bank validated data were validated for logical consistency, flagging problems that were then corrected by the implementing contractor."},"analysis_info":{"response_rate":"The response rate was 96.6% for Sierra Leone. There are slight variations of these indicators by sub-groups of businesses.","sampling_error_estimates":"According to sample design, it is possible to generalize survey results (at a precision of 7.5% and a confidence level of 90%) at the sector level, and the respective gender sub-groups of businesses."}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"Before being granted access to the dataset, all users have to formally agree: \n1. To make no copies of any files or portions of files to which s\/he is granted access except those authorized by the data depositor. \n2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files. \n3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her\/his analysis will be immediately brought to the attention of the data depositor.","required":"yes","form_no":"","uri":""}],"contact":[{"name":"Microdata Library","affiliation":"World Bank","email":"","uri":"microdata.worldbank.org"}],"cit_req":"Twining-Ward, L, Saurav, A. and Hial S.E. (World Bank Group). (2019). Women in Tourism Enterprise Survey for Sierra Leone (WE-FI). Ref (SLE_2019_WE-FI_v01_M). Downloaded from [url] on [date].","conditions":"- Public use files, accessible to all","disclaimer":"The findings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the Directors or Executive Directors of the respective institutions of the World Bank Group or the governments they represent. The World Bank Group does not guarantee the accuracy of the data included in this work."}}},"schematype":"survey","tags":[{"tag":"DOI"}]}