Abstract

The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized allowing comparison between nations and across subnational boundaries over time.

The Education SDIs include teacher effort, teacher knowledge and ability, and the availability of key inputs (for example, textbooks, basic teaching equipment, infrastructure). The indicators provide a snapshot of the learning environment and key resources, which need to be in place for students to learn.

Togo Service Delivery Indicators Education Survey was implemented in May-June 2013 by Togo's Ministry of Education’s National Evaluation Commission (Commission nationale d’évaluation; CNE) in close coordination with the World Bank SDI team. Data collection and processing was carried out by a team of consultants managed by TIMS Services. Information was collected from 200 primary schools, 1,141 teachers, and 1,938 grade four students.

Geographic coverage

National

Analysis unit

Schools, teachers and students

Universe

All primary schools

Kind of data

Sample survey data [ssd]

Sampling procedure

The SDI indicators draw information from a stratified random sample of 200 schools, comprised of 148 public, 28 faith‐based, and 24 private non‐denominational schools. This sample provides a representative snapshot of the learning environment in both public and private schools. The details on the sampling procedure are in Annex 1 of the SDI Report under the Resources tab. The education work was implemented as part of the ongoing work with the Government of Togo on improving educational quality and development of the Ministry of Education’s capacity to produce, analyze, and use statistical information for policy formulation and evaluation. The standard SDI survey instruments were adapted to the Togolese context through a participatory process involving technical discussions, training, and piloting with the Ministry of Education’s National (Education) Evaluation Commission (Commission nationale d’évaluation; CNE).

The education survey was also coordinated with the Global Partnership for Education (GPE) project’s PASEC‐inspired survey. A single team that undertook both surveys went to each school and the supervisors were from the CNE. The survey was implemented by the CNE with support and supervision from the World Bank’s Service Delivery Indicators (SDI) team.

The sample of schools used in the SDI survey was the same as the PASEC‐inspired survey. The sample chosen closely reflects the distribution of school usage across facility types and poverty status. In total, 200 primary schools, of which 74 percent were public schools and the remaining 26 percent either private for‐profit or private not‐for‐profit schools. The survey assessed the knowledge of 831 primary school teachers, surveyed 1,141 teachers as part of the study of the absence rate, and observed 192 grade four lessons. In addition, learning outcomes were measured for 1,938 grade four pupils. Survey implementation was preceded by extensive consultation with Government and key stakeholders on survey design, sampling, and adaptation of survey instruments. Pre‐testing of the survey instruments, training of field staff, and field‐work took place in 2013.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Education Survey Questionnaire consists of six modules:

Module 1: School Information - Administered to the head of the school to collect information about school type, facilities, school governance, pupil numbers, and school hours. Includes direct observations of school infrastructure by enumerators.

Module 2a: Teacher Absence and Information - Administered to head teacher and individual teachers to obtain a list of all school teachers, to measure teacher absence and to collect information about teacher characteristics.

Module 2b: Teacher Absence and Information - Unannounced visit to the school to assess absence rate.

Module 3: School Finances - Administered to the headteacher (or Director, in the case of Togo) to collect information on school finances (this data is not included with the dissemination package).

Module 4: Classroom Observation - An observation module to assess teaching activities and classroom conditions.

Module 5: Pupil Assessment - A test of pupils to have a measure of pupil learning outcomes in mathematics and language in grade four.

Module 6: Teacher Assessment - A test of teachers covering mathematics and language subject knowledge and teaching skills.

Cleaning operations

Done using CSPro

Response rate

Not calculated.

A minimal dataset from a survey of 226 health facilities in Uganda supported by PEPFAR. 206 of the facilities were transitioned from PEPFAR support and 20 were maintained. Variables pertain to service discontinuation and perceived changes in quality and access to HIV services after transition.

Description:This online mapping tool, provided by the Western Cape Government, is designed to assist with spatial information queries in the fields of population and demographics. The dashboard is provided through the Western Cape Government Open Data Portal For more information, please contact the Provincial Data Office (mailto://pdo@westerncape.gov.za).Linage:The data presented on this site originates from various sources and custodians. The demographic data is updated annually.Data Sources:StatsSA Census boundaries (2011)Demogaphic data supplied by ©GEOTERRAIMAGE – 2022Contact Person:julie.verhulp@westerncape.gov.za

Abstract

The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized, allowing comparison between and within countries over time.

The Health SDIs include healthcare provider effort, knowledge and ability, and the availability of key inputs (for example, basic equipment, medicines and infrastructure, such as toilets and electricity). The indicators provide a snapshot of the health facility and assess the availability of key resources for providing high quality care.

The Sierra Leone SDI Health survey team visited a sample of 536 health facilities across Sierra Leone between January and April 2018. The survey team collected rosters covering 5,055 workers for absenteeism and assessed 829 health workers for competence using patient case simulations.

Geographic coverage

National

Analysis unit

Health facilities and healthcare providers

Universe

All health facilities providing primary-level care

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy for SDI surveys is designed towards attaining indicators that are accurate and representative at the national level, as this allows for proper cross-country (i.e. international benchmarking) and across time comparisons, when applicable. In addition, other levels of representativeness are sought to allow for further disaggregation (rural/urban areas, public/private facilities, subregions, etc.) during the analysis stage.

The sampling strategy for SDI surveys follows a multistage sampling approach. The main units of analysis are facilities (schools and health centers) and providers (health and education workers: teachers, doctors, nurses, facility managers, etc.). The multi-stage sampling approach makes sampling procedures more practical by dividing the selection of large populations of sampling units in a step-by-step fashion. After defining the sampling frame and categorizing it by stratum, a first stage selection of sampling units is carried out independently within each stratum. Often, the primary sampling units (PSU) for this stage are cluster locations (e.g. districts, communities, counties, neighborhoods, etc.) which are randomly drawn within each stratum with a probability proportional to the size (PPS) of the cluster (measured by the location’s number of facilities, providers or pupils). Once locations are selected, a second stage takes place by randomly selecting facilities within location (either with equal probability or with PPS) as secondary sampling units. At a third stage, a fixed number of health and education workers and pupils are randomly selected within facilities to provide information for the different questionnaire modules.

Detailed information about the specific sampling process is available in the associated SDI Country Report included as part of the documentation that accompany these datasets.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Health Survey Questionnaire consists of four modules:

Module 1: General Information - Administered to the health facility manager to collect information on equipment, medicines, infrastructure and other facets of the health facility.

Module 2: Provider Absence - A roster of healthcare providers is collected and absence measured.

Module 3: Clinical Vignettes – A selection of providers are given clinical vignettes to measure knowledge of common medical conditions.

Module 4: Facility finances – Information on facility revenue and expenditures is collected from the health facility manager.

Weights: Weights for facilities, absentee-related analyses and clinical vignette analyses.

Cleaning operations

Quality control was performed in Stata.

Abstract

The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized allowing comparison between and within countries over time.

The Education SDIs include teacher effort, teacher knowledge and ability, and the availability of key inputs (for example, textbooks, basic teaching equipment, and infrastructure such as blackboards and toilets). The indicators provide a snapshot of the learning environment and the key resources necessary for students to learn.

Madagascar Service Delivery Indicators Education Survey was implemented from April 2016 (for enumerator training and pre-testing of the instruments) to May and June 2016 (for fieldwork and data collection) by CAETIC Development, a strong local think-tank and survey firm. The sampling strategy was done by INSTAT the national institute for statistics. Information was collected from 473 primary schools, 2,130 teachers (for skills assessment), 2,475 teachers (for absence rate), and 3,960 pupils across Madagascar. The survey also collected basic information on all the 3,049 teachers or staff that teach in the 473 primary schools visited or are non-teaching directors.

Geographic coverage

National

Analysis unit

Schools, teachers, students.

Kind of data

Sample survey data [ssd]

Sampling procedure

A two-stage sampling method was adopted. First, in each stratum schools were chosen within the selected councils. Once at a selected school, the enumerator selected teachers and pupils depending on the structure of the classrooms.

The schools were chosen using probability proportional to size (PPS), where size was the number of standard two pupils as provided by the 2014 EMIS database. As for the selection of the cluster, the use of PPS implied that each standard four pupil within a stratum had an equal probability for her school to be selected.

Finally, within each school, up to 10 standard four pupils and 10 teachers were selected. Pupils were randomly selected among the grade-four pupil body, whereas for teachers, there were two different procedures for measuring absence rate and assessing knowledge. For absence rate, 10 teachers were randomly selected from the teachers’ roster and the whereabouts of those teachers was ascertained in a return surprise visit. For the knowledge assessment, however, all teachers who were currently teaching in primary four or taught primary three the previous school year were included in the sample. Then a random number of teachers in upper grades were included to top up the sample. These procedures implied that pupils across strata, as well as teachers across strata and within a school (for the knowledge assessment) did not all have the same probability of selection. It was, therefore, warranted to compute weights for reporting the survey results.

The sampling strategy for the SDI in Madagascar was done by INSTAT the national statistics office.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Education Survey Questionnaire consists of six modules:

Module 1: School Information - Administered to the head of the school to collect information about school type, facilities, school governance, pupil numbers, and school hours. Includes direct observations of school infrastructure by enumerators.

Module 2a: Teacher Absence and Information - Administered to headteacher and individual teachers to obtain a list of all school teachers, to measure teacher absence, and to collect information about teacher characteristics.

Module 2b: Teacher Absence and Information - Unannounced visit to the school to assess absence rate.

Module 3: School Finances - Administered to the headteacher to collect information about school finances (this data is unharmonized).

Module 4: Classroom Observation - An observation module to assess teaching activities and classroom conditions.

Module 5: Pupil Assessment - A test of pupils to have a measure of pupil learning outcomes in mathematics and language in grade four.

Module 6: Teacher Assessment - A test of teachers covering mathematics and language subject knowledge and teaching skills.

Cleaning operations

Data quality control was performed in Stata.

Abstract

This study examines various dimensions of primary health care delivery in Uganda, using a baseline survey of public and private dispensaries, the most common lower level health facilities in the country.

The survey was designed and implemented by the World Bank in collaboration with the Makerere Institute for Social Research and the Ugandan Ministries of Health and of Finance, Planning and Economic Development. It was carried out in October - December 2000 and covered 155 local health facilities and seven district administrations in ten districts. In addition, 1617 patients exiting health facilities were interviewed. Three types of dispensaries (both with and without maternity units) were included: those run by the government, by private for-profit providers, and by private nonprofit providers, mainly religious.

This research is a Quantitative Service Delivery Survey (QSDS). It collected microlevel data on service provision and analyzed health service delivery from a public expenditure perspective with a view to informing expenditure and budget decision-making, as well as sector policy.

Objectives of the study included: 1) Measuring and explaining the variation in cost-efficiency across health units in Uganda, with a focus on the flow and use of resources at the facility level; 2) Diagnosing problems with facility performance, including the extent of drug leakage, as well as staff performance and availability;
3) Providing information on pricing and user fee policies and assessing the types of service actually provided; 4) Shedding light on the quality of service across the three categories of service provider - government, for-profit, and nonprofit; 5) Examining the patterns of remuneration, pay structure, and oversight and monitoring and their effects on health unit performance; 6) Assessing the private-public partnership, particularly the program of financial aid to nonprofits.

Geographic coverage

The study districts were Mpigi, Mukono, and Masaka in the central region; Mbale, Iganga, and Soroti in the east; Arua and Apac in the north; and Mbarara and Bushenyi in the west.

Analysis unit

• local dispensary with or without maternity unit

Universe

The survey covered government, for-profit and nonprofit private dispensaries with or without maternity units in ten Ugandan districts.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey covered government, for-profit and nonprofit private dispensaries with or without maternity units in ten Ugandan districts.

The sample design was governed by three principles. First, to ensure a degree of homogeneity across sampled facilities, attention was restricted to dispensaries, with and without maternity units (that is, to the health center III level). Second, subject to security constraints, the sample was intended to capture regional differences. Finally, the sample had to include facilities in the main ownership categories: government, private for-profit, and private nonprofit (religious organizations and NGOs). The sample of government and nonprofit facilities was based on the Ministry of Health facility register for 1999. Since no nationwide census of for-profit facilities was available, these facilities were chosen by asking sampled government facilities to identify the closest private dispensary.

Of the 155 health facilities surveyed, 81 were government facilities, 30 were private for-profit facilities, and 44 were nonprofit facilities. An exit poll of clients covered 1,617 individuals.

The final sample consisted of 155 primary health care facilities drawn from ten districts in the central, eastern, northern, and western regions of the country. It included government, private for-profit, and private nonprofit facilities. The nonprofit sector includes facilities owned and operated by religious organizations and NGOs. Approximately one third of the surveyed facilities were dispensaries without maternity units; the rest provided maternity care. The facilities varied considerably in size, from units run by a single individual to facilities with as many as 19 staff members.

Ministry of Health facility register for 1999 was used to design the sampling frame. Ten districts were randomly selected. From the selected districts, a sample of government and private nonprofit facilities and a reserve list of replacement facilities were randomly drawn. Because of the unreliability of the register for private for-profit facilities, it was decided that for-profit facilities would be identified on the basis of information from the government facilities sampled. The administrative records for facilities in the original sample were first reviewed at the district headquarters, where some facilities that did not meet selection criteria and data collection requirements were dropped from the sample. These were replaced by facilities from the reserve list. Overall, 30 facilities were replaced.

The sample was designed in such a way that the proportion of facilities drawn from different regions and ownership categories broadly mirrors that of the universe of facilities. Because no nationwide census of for-profit health facilities is available, it is difficult to assess the extent to which the sample is representative of this category. A census of health care facilities in selected districts, carried out in the context of the Delivery of Improved Services for Health (DISH) project supported by the U.S. Agency for International Development (USAID), suggests that about 63 percent of all facilities operate on a for-profit basis, while government and nonprofit providers run 26 and 11 percent of facilities, respectively. This would suggest an undersampling of private providers in the survey. It is not clear, however, whether the DISH districts are representative of other districts in Uganda in terms of the market for health care.

For the exit poll, 10 interviews per facility were carried out in approximately 85 percent of the facilities. In the remaining facilities the target of 10 interviews was not met, as a result of low activity levels.

Sampling deviation

In the first stage in the sampling process, eight districts (out of 45) had to be dropped from the sample frame due to security concerns. These districts were Bundibugyo, Gulu, Kabarole, Kasese, Kibaale, Kitgum, Kotido, and Moroto.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available:

• District Health Team Questionnaire;
• District Facility Data Sheets;
• Uganda Health Facility Survey Questionnaire;
• Facility Data Sheets;
• Facility Patient Exit Poll Questionnaire.

The survey collected data at three levels: district administration, health facility, and client. In this way it was possible to capture central elements of the relationships between the provider organization, the frontline facility, and the user. In addition, comparison of data from different levels (triangulation) permitted cross-validation of information.

At the district level, a District Health Team Questionnaire was administered to the district director of health services (DDHS), who was interviewed on the role of the DDHS office in health service delivery. Specifically, the questionnaire collected data on health infrastructure, staff training, support and supervision arrangements, and sources of financing.

The District Facility Data Sheet was used at the district level to collect more detailed information on the sampled health units for fiscal 1999-2000, including data on staffing and the related salary structures, vaccine supplies and immunization activity, and basic and supplementary supplies of drugs to the facilities. In addition, patient data, including monthly returns from facilities on total numbers of outpatients, inpatients, immunizations, and deliveries, were reviewed for the period April-June 2000.

At the facility level, the Uganda Health Facility Survey Questionnaire collected a broad range of information related to the facility and its activities. The questionnaire, which was administered to the in-charge, covered characteristics of the facility (location, type, level, ownership, catchment area, organization, and services); inputs (staff, drugs, vaccines, medical and nonmedical consumables, and capital inputs); outputs (facility utilization and referrals); financing (user charges, cost of services by category, expenditures, and financial and in-kind support); and institutional support (supervision, reporting, performance assessment, and procurement). Each health facility questionnaire was supplemented by a Facility Data Sheet (FDS). The FDS was designed to obtain data from the health unit records on staffing and the related salary structure; daily patient records for fiscal 1999-2000; the type of patients using the facility; vaccinations offered; and drug supply and use at the facility.

Finally, at the facility level, an exit poll was used to interview about 10 patients per facility on the cost of treatment, drugs received, perceived quality of services, and reasons for using that unit instead of alternative sources of health care.

Cleaning operations

Detailed information about data editing procedures is available in "Data Cleaning Guide for PETS/QSDS Surveys" in external resources.

STATA cleaning do-files and the data quality reports on the datasets can also be found in external resources.

Abstract

This ICMA signature survey, conducted every five years, examines the service delivery choices, practices, and policies of local governments. Survey topics covered include adopting, evaluating private service delivery and obstacles in private service delivery.

Methodology

ICMA’s database of local governments includes approximately 11,000 U.S. municipalities and 2,900 U.S. counties with populations of 2,500 or greater, as well as a majority of municipalities and counties with populations under 2,500 (https://icma.org/survey-research). The survey was distributed to chief administrative officers of local governments.

Usage

Available documentation is contained in zip files labelled by survey year (see

Supporting Files). Documentation will always include the survey instrument; where available, documentation may also include codebooks and response rates.

For all years except 2017, each year's survey data was split across multiple files. Consequently, in Redivis, a single year of data is split into multiple tables. Users can JOIN the tables on shared variables (keys) like IMISID, USTATE, etc.

Abstract

This survey is the first detailed study on the phenomena of teacher absenteeism in Indonesia obtained from two unannounced visits to 147 sample schools in October 2002 and March 2003. The study was conducted by the SMERU Research Institute and the World Bank, affiliated with the Global Development Network (GDN). Similar surveys were carried out at the same time in seven other developing countries: Bangladesh, Ecuador, India, Papua New Guinea, Peru, Uganda, and Zambia.

This research focuses on primary school teacher absence rates and their relations to individual teacher characteristics, conditions of the community and its institutions, and the education policy at various levels of authority. A teacher was considered as absent if at the time of the visit the researcher could not find the sample teacher in the school.

This survey was conducted in randomly selected 10 districts/cities in four Indonesian regions: Java-Bali, Sumatera, Kalimantan-Sulawesi, and Nusa Tenggara.

Geographic coverage

Java-Bali, Sumatera, Kalimantan-Sulawesi and Nusa Tenggara regions

Analysis unit

• Teachers
• Schools

Kind of data

Sample survey data [ssd]

Sampling procedure

Information from Indonesian Statistics Agency (BPS) and the Ministry of Education was used as a basis to build a sample frame. The data gathered included the amount of total population, a list of villages and primary school facilities in each district/city. Due to limited time and resources, this research only focused on primary schools. In Indonesia, there are two types of primary education facilities: primary schools and primary madrasah. Primary schools are regulated by the Ministry of National Education, using the general curriculum, while primary madrasah are regulated by the Ministry of Religious Affairs, using a mixed (general and Islamic) curriculum.

A sample of districts/cities and schools (consisting of primary schools and primary madrasah) were selected using the following steps. First, Indonesia was divided into several regions based on the number of total population: Java-Bali, Sumatera, Kalimantan-Sulawesi, and Nusa Tenggara. Indonesian provinces that were suffering from various conflicts (such as Aceh, Central Sulawesi, Maluku, North Maluku, and Papua) were removed from the sample selection process. Then, from each region, a total of five districts and cities were randomly selected, taking into account the population of each district/city.

Second, 12 schools were selected in each district/city. Before choosing sampled schools, researchers randomly selected 10 villages in each district/city to be sampled, taking into account the location of these villages (in urban or rural areas). One of the 10 villages was a backup village to anticipate the possibility of a village that was too difficult to reach. In each village sampled, researchers asked residents about the location of primary schools/madrasah (both public and private) in these villages. They started visiting schools, giving priority to public primary schools/madrasahs. To meet the number of samples in each district/city, additional samples were selected from private schools.

Third, in each school sampled, the researcher would request a list of teachers. If a school visited was considered to be large, such as schools with more than 15 teachers, then the researcher would only interview 15 teachers chosen randomly to ensure that survey quality could be maintained despite the limited time and resources. Each school was visited twice, both on an unannounced date. From the 147 primary schools/madrasah in the sample, 1,441 teachers were selected in each visit (because this is a panel study, the teacher absence data that were used were taken only from teachers that could be interviewed or whose data were obtained from both visits). If there were teachers whose information was only obtained from one of the visits, then their data was not included in the dataset panel.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available:

• Teacher Questionnaire, First Visit
• Teacher Questionnaire, Second Visit.

Cleaning operations

Detailed information about data editing procedures is available in "Data Cleaning Guide for PETS/QSDS Surveys" in external resources.

The STATA cleaning do-file and the data quality report on the dataset can also be found in external resources.

SSH CENTRE (Social Sciences and Humanities for Climate, Energy aNd Transport Research Excellence) is a Horizon Europe project, engaging directly with stakeholders across research, policy, and business (including citizens) to strengthen social innovation, SSH-STEM collaboration, transdisciplinary policy advice, inclusive engagement, and SSH communities across Europe, accelerating the EU’s transition to carbon neutrality.
SSH CENTRE is based in a range of activities related to Open Science, inclusivity and diversity – especially with regards Southern and Eastern Europe and different career stages – including: development of novel SSH-STEM collaborations to facilitate the delivery of the EU Green Deal; SSH knowledge brokerage to support regions in transition; and the effective design of strategies for citizen engagement in EU R&I activities. Outputs include action-led agendas and building stakeholder synergies through regular Policy Insight events.
This is captured in a high-profile virtual SSH CENTRE generating and sharing best practice for SSH policy advice, overcoming fragmentation to accelerate the EU’s journey to a sustainable future.
The documents uploaded here are part of WP2 whereby novel, interdisciplinary teams were provided funding to undertake activities to develop a policy recommendation related to EU Green Deal policy. Each of these policy recommendations, and the activities that inform them, will be written-up as a chapter in an edited book collection. Three books will make up this edited collection - one on climate, one on energy and one on mobility.
As part of writing a chapter for the SSH CENTRE book on ‘Strengthening European mobility policy - Governance recommendations from innovative interdisciplinary collaborations’, we elicit the opinions of citizens in urban logistics policymaking through a series of surveys in different European cities. The files attached to this Zenodo webpage are therefore the dataset contains raw survey data from a study utilizing Multicriteria Satisfaction Analysis (MUSA) to evaluate public perceptions of cargo bike last-mile delivery in London, Paris, Rome, Dublin, and Warsaw. The data encompasses over 2,000 responses, detailing participants' satisfaction levels with various aspects of cargo bike delivery services, including CO2 emissions, noise, traffic, safety, and shipping costs. This dataset supports comprehensive analyses of urban logistics policies aimed at sustainable mobility solutions in these specific cities.

Zip delivery package of cod survey data 2008 - 2019 to the National Archive for long term preservation.

Abstract

The 2004 National Service Delivery Survey (NSDS) collected information on six selected sectors namely Education, Health, Water and Sanitation, Agriculture, Transport and Governance. The survey was aimed at providing information about the performance of the selected sectors for policy formulation, implementation and monitoring at all levels of governance. Two sets of questionnaires were used to collect information: the household questionnaire (service users) and the questionnaire for service providers.

Geographic coverage

The survey covered the entire country . A representative sample of 18,000 households was randomly selected from all the 56 districts but only 17,608 households were covered.

Analysis unit

• Individual
• Household
• Community
• Institution

Universe

The survey covered all the households that fell in the sample and accepted to be interviewed.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design used for collecting primary data was a multi-stage cluster sample. The first stage of sampling involved the selection of Enumeration Areas (EAs). An enumeration area is an area that can be covered by one enumerator at the time of a Census, in most cases this area is equivalent to a village/ cell, while in other cases it is part of the village or many villages. The EAs had been demarcated in preparation for the 2002 Population and Housing Census. A representative sample of at least 30 enumeration areas (EAs) was selected from every district independently.

The sampling process utilized the 2002 Population and Housing Census Sampling Frame using the probability proportional to size (PPS) approach. A total of 1800 EAs (Primary Sampling Units) were targeted in the entire country. A complete listing of households was done in each of the EAs to generate a sampling frame of households from which a sample of households was selected. Within each selected Primary Sampling Unit (PSU), ten (10) households were randomly selected as Secondary Sampling Units (SSU). Overall, the Survey targeted 18,000 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

A household questionnaire was administered in each household, which collected various information on household members including sex, age, literacy, marital status , activity status and ophanhood. The household questionnaire also includes education, health services, immunisation of children under five, housing, water and sanitation, governace, agriculture services, transport services and access to credit (informal and formal) In addition there was a particular section for women aged 15-50years and children under age five.

Cleaning operations

Manual editing and coding was done using a team of ten well trained persons and one supervisor.

For data entry: CSPro was used, quality checks were embedded in the data entry application, type of data entry was manual and used double entry system to ensure quality, Twenty four data entry operators and two supervisors were employed. One computer programmer was in charge of the overall data processing. He did the final cleaning, tabulation and analysis. Cleaning was done in CSPro and SPSS while tabulation and analysis was done in SPSS.

Response rate

A representative sample of 18,000 households was randomly selected from all the 56 districts but only 17,608 (97.8%)households were covered. Some households were not covered due to insecurity in the districts of Gulu, Lira, Katakwi, Kitgum, and Pader; while in Karamoja region (Kotido, Nakapiripirit and Moroto) due to mobility of the pastoralist communities.

These data include the individual responses for the City of Tempe Annual Business Survey conducted by ETC Institute. These data help determine priorities for the community as part of the City's on-going strategic planning process. Averaged Business Survey results are used as indicators for city performance measures. The performance measures with indicators from the Business Survey include the following (as of 2023):1. Financial Stability and Vitality5.01 Quality of Business ServicesThe location data in this dataset is generalized to the block level to protect privacy. This means that only the first two digits of an address are used to map the location. When they data are shared with the city only the latitude/longitude of the block level address points are provided. This results in points that overlap. In order to better visualize the data, overlapping points were randomly dispersed to remove overlap. The result of these two adjustments ensure that they are not related to a specific address, but are still close enough to allow insights about service delivery in different areas of the city.Additional InformationSource: Business SurveyContact (author): Adam SamuelsContact E-Mail (author): Adam_Samuels@tempe.govContact (maintainer): Contact E-Mail (maintainer): Data Source Type: Excel tablePreparation Method: Data received from vendor after report is completedPublish Frequency: AnnualPublish Method: ManualData DictionaryMethods:The survey is mailed to a random sample of businesses in the City of Tempe. Follow up emails and texts are also sent to encourage participation. A link to the survey is provided with each communication. To prevent people who do not live in Tempe or who were not selected as part of the random sample from completing the survey, everyone who completed the survey was required to provide their address. These addresses were then matched to those used for the random representative sample. If the respondent’s address did not match, the response was not used.To better understand how services are being delivered across the city, individual results were mapped to determine overall distribution across the city.Processing and Limitations:The location data in this dataset is generalized to the block level to protect privacy. This means that only the first two digits of an address are used to map the location. When they data are shared with the city only the latitude/longitude of the block level address points are provided. This results in points that overlap. In order to better visualize the data, overlapping points were randomly dispersed to remove overlap. The result of these two adjustments ensure that they are not related to a specific address, but are still close enough to allow insights about service delivery in different areas of the city.The data are used by the ETC Institute in the final published PDF report.

The SDI provides a set of metrics to benchmark the performance of schools and health facilities in Africa. The Indicators can be used to track progress within and across countries over time, and aim to enhance active monitoring of service delivery to increase public accountability and good governance. Ultimately, the goal of this effort is to help policymakers, citizens, service providers, donors, and other stakeholders enhance the quality of services and improve development outcomes. The perspective adopted by the Indicators is that of citizens accessing a service. The Indicators assemble objective and quantitative information from a survey of frontline service delivery units, using modules from the Public Expenditure Tracking Survey (PETS), Quantitative Service Delivery Survey (QSDS), and Staff Absence Survey (SAS). The SDI initiative is a partnership of the World Bank, the African Economic Research Consortium (AERC), and the African Development Bank. More information on the SDI survey instruments and data, and more generally on the SDI initiative can be found at: www.SDIndicators.org and www.worldbank.org/SDI, or by contacting SDI@worldbank.org.

This statistic shows the results of a survey conducted in the United States in 2018 on online shopping. Some 37 percent of the respondents stated that a quick delivery of clothing is important for them. The Survey Data Table for the Statista survey Online-Shopping in the U.S. 2018 contains the complete tables for the survey including various column headings.

Background: “In 2006, the Seattle Police Department began surveying members of the public (customers) who had personal contact with an officer after calling 9-1-1. The surveys have been conducted two to four times a year, and a total of 44 surveys have been conducted to date. These surveys have been designed to assess customers’ experiences and satisfaction with the service provided by the Seattle Police Department, and the results of the surveys have been used to assess service delivery; examine differences between precincts; identify strategies and tactics to achieve specific service objectives; and provide feedback to officers, precinct captains, and watch lieutenants. This report presents the results of the September 2019 customer survey and compares the September 2019 survey results to results from the 13 other surveys conducted since March 2016.” Research Methods. “Similar to the previous surveys, 200 customers who called 9-1-1 and had an officer dispatched to provide assistance were interviewed by telephone for this survey. All of the customers interviewed had called 9-1-1 between August 21 and August 29, 2019, and were randomly selected from lists of 9-1-1 callers who had an officer dispatched to provide assistance, excluding sensitive cases such as domestic violence calls. The interviews were completed between September 3 and September 10, 2019. The interviews were approximately 10 to 12 minutes long. The questionnaire used in the interviews was developed with Department input and approval. During the course of this research, some questions have been added to or deleted from the survey questionnaire to reflect the changing information needs of the Department. However, questions about customers’ overall satisfaction with their experience with the Department after calling 9-1-1, experiences with and opinions of the officer who first visited after the call to 9-1-1, opinions of the Seattle Police Department overall, and satisfaction with the service provided by the 9-1-1 operator have been included in every survey. Since late 2006 and early 2007, the surveys also included questions about customers’ feelings of safety in Seattle.”

Abstract

The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized, allowing comparison between and within countries over time.

The Health SDIs include healthcare provider effort, knowledge and ability, and the availability of key inputs (for example, basic equipment, medicines and infrastructure, such as toilets and electricity). The indicators provide a snapshot of the health facility and assess the availability of key resources for providing high quality care.

The Tanzania SDI Health survey team visited a sample of 383 health facilities across Tanzania between August and October 2016. The survey team collected rosters covering 5,160 workers for absenteeism and assessed 498 health workers for competence using patient case simulations. The technical report and field manual are unavailable for Tanzania 2016. The questionnaire is the same as Tanzania 2014.

Geographic coverage

National

Analysis unit

Health facilities and healthcare providers

Universe

All health facilities providing primary-level care

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy for SDI surveys is designed towards attaining indicators that are accurate and representative at the national level, as this allows for proper cross-country (i.e. international benchmarking) and across time comparisons, when applicable. In addition, other levels of representativeness are sought to allow for further disaggregation (rural/urban areas, public/private facilities, subregions, etc.) during the analysis stage.

The sampling strategy for SDI surveys follows a multistage sampling approach. The main units of analysis are facilities (schools and health centers) and providers (health and education workers: teachers, doctors, nurses, facility managers, etc.). The multi-stage sampling approach makes sampling procedures more practical by dividing the selection of large populations of sampling units in a step-by-step fashion. After defining the sampling frame and categorizing it by stratum, a first stage selection of sampling units is carried out independently within each stratum. Often, the primary sampling units (PSU) for this stage are cluster locations (e.g. districts, communities, counties, neighborhoods, etc.) which are randomly drawn within each stratum with a probability proportional to the size (PPS) of the cluster (measured by the location’s number of facilities, providers or pupils). Once locations are selected, a second stage takes place by randomly selecting facilities within location (either with equal probability or with PPS) as secondary sampling units. At a third stage, a fixed number of health and education workers and pupils are randomly selected within facilities to provide information for the different questionnaire modules.

The Tanzania 2016 survey is a repeated panel of the 2014 survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Health Survey Questionnaire consists of four modules:

Module 1: General Information - Administered to the health facility manager to collect information on equipment, medicines, infrastructure and other facets of the health facility.

Module 2: Provider Absence - A roster of healthcare providers is collected and absence measured.

Module 3: Clinical Vignettes – A selection of providers are given clinical vignettes to measure knowledge of common medical conditions.

Module 4: Facility finances – Information on facility revenue and expenditures is collected from the health facility manager.

Weights: Weights for facilities, absentee-related analyses and clinical vignette analyses.

Cleaning operations

Quality control was performed in Stata.

United States Diffusion Index: sa: New York Fed: Future Delivery Time: Lower data was reported at 12.800 NA in Jul 2018. This records an increase from the previous number of 12.400 NA for Jun 2018. United States Diffusion Index: sa: New York Fed: Future Delivery Time: Lower data is updated monthly, averaging 11.800 NA from Jul 2001 (Median) to Jul 2018, with 205 observations. The data reached an all-time high of 23.200 NA in Jul 2008 and a record low of 3.300 NA in Jan 2012. United States Diffusion Index: sa: New York Fed: Future Delivery Time: Lower data remains active status in CEIC and is reported by Federal Reserve Bank of New York. The data is categorized under Global Database’s USA – Table US.S009: Empire State Manufacturing Survey.

Abstract

The Service Delivery Indicators ("the Indicators") provide a set of metrics for benchmarking service delivery performance in education and health in Africa to track progress across and within countries over time. The Indicators seek to enhance active monitoring of service delivery by policymakers and citizens, as well as to increase accountability and good governance. The perspective adopted by the Indicators is that of citizens accessing services and facing shortcomings.

The Service Delivery Indicators were piloted in Tanzania and Senegal in the spring/summer of 2010. The main objective of the pilots was to test the survey instruments in the field and to verify that robust indicators of service delivery quality could be collected with a single facility-level instrument in different settings. To this end, it was decided that the pilots should include an Anglophone and Francophone country with different budget systems. The selection of Senegal and Tanzania was also influenced by the presence of strong local research institutes from the AERC network: Centre de Recherche Economique et Sociale (CRES) in Senegal and the Research on Poverty Alleviation (REPOA) in Tanzania. Both research institutes have extensive facility survey experience and are also grantees of the Hewlett-supported Think Tank Initiative.

Geographic coverage

National

Analysis unit

Shool facility, health facility

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was designed to provide estimates for each of the key Indicators, broken down by urban and rural location. To achieve this purpose in a cost-effective manner, a stratified multi-stage random sampling design was employed. Given the overall resource envelope, it was decided that roughly 150 facilities would be surveyed in each sector in Senegal. The sample frame employed consisted of the most recent list of all public primary schools and public primary health facilities, including information on the size of the population they serve.

Sample size:

Health: Urban=102 Rural=49 Total=151 Education: Urban=92 Rural=59 Total=151

Research instrument

The survey used a sector-specific questionnaire with several modules, all of which were administered at the facility level. The questionnaires built on previous similar questionnaires based on international good practice for PETS, QSDS, SAS and observational surveys. A pre-test of the instruments was done by the technical team, in collaboration with the in-country research partners, in the early part of 2010. The questionnaires were translated into French. In collaboration with the in-country research partners, members of the technical team organized a one-week training session, which included three days of testing the instruments in the field. The enumerators and supervisors were university graduates, and in many cases were also trained health and education professionals (teachers, doctors, and health workers) with previous survey experience.

EDUCATION:

• Module 1: Administered to the principal, head teacher or most senior teacher in the school
• Module 2: Administered to (a maximum of) 10 teachers randomly selected from the list of all teachers
• Module 3: Administered to the same 10 teachers as in module 2
• Module 4: Classroom observations
• Module 5: Test of teachers
• Module 6: Test of grade 4 children

HEALTH: - Module 1: Administered to the in- charge or the most senior medical staff at the facility. - Module 2: Administered to (a maximum of) 10 medical staff randomly selected from the list of all medical staff - Module 3: Administered to the same 10 medical staff as in module 2 - Module 4: Health facility observations - Module 5: Test of health workers. Patient case simulations.

The City of Bloomington contracted with National Research Center, Inc. to conduct the 2019 Bloomington Community Survey. This was the second time a scientific citywide survey had been completed covering resident opinions on service delivery satisfaction by the City of Bloomington and quality of life issues. The first was in 2017. The survey captured the responses of 610 households from a representative sample of 3,000 residents of Bloomington who were randomly selected to complete the survey. VERY IMPORTANT NOTE: The scientific survey data were weighted, meaning that the demographic profile of respondents was compared to the demographic profile of adults in Bloomington from US Census data. Statistical adjustments were made to bring the respondent profile into balance with the population profile. This means that some records were given more "weight" and some records were given less weight. The weights that were applied are found in the field "wt". If you do not apply these weights, you will not obtain the same results as can be found in the report delivered to the City of Bloomington. The easiest way to replicate these results is likely to create pivot tables, and use the sum of the "wt" field rather than a count of responses.

This statistic shows the results of a survey conducted in the United States in 2018 on online shopping. Some 38 percent of the respondents stated that UPS is their favorite delivery company. The Survey Data Table for the Statista survey Online-Shopping in the U.S. 2018 contains the complete tables for the survey including various column headings.