In the fourth quarter of 2023, Uber's ridership worldwide totaled 2.6 billion trips. This compares to 2.1 billion trips in the first quarter of 2022, representing an increase of 24 percent year-on-year. A brief overview of Uber Technologies Uber Technologies Corporation started as a ridesharing company to disrupt the traditional taxi services industry. Having observed the global lucrativeness of the sharing economy in the upcoming years, Uber expanded its business profile to reshape the entire transportation industry, from food delivery and logistics to transport of people. As a result of strategic market positioning, the company experienced strong growth. The net revenue of Uber increased over 75 times in ten years, up from 0.5 billion U.S. dollars in 2014 to 37.3 billion U.S. dollars in 2023. Uber Technologies reported being profitable for the first time since 2018, posting a net profit of roughly 1.9 billion U.S. dollars during the fiscal year of 2023. Competition in the sharing economy Uber has been operating in a highly competitive environment since it introduced its first differentiated cab services. One of the major competitors of Uber Technologies is the San Francisco-based Lyft. Although Lyft is a latecomer into the ride-sharing business, Lyft progressively worked on weaknesses exhibited by Uber to strengthen its position against Uber and other competitors. Besides, Lyft is one of the major innovators in the sharing economy along with Uber Technologies. In 2022, Lyft Corporation invested nearly 556 million U.S. dollars into research and development globally, which has been scaled back in recent years. Lyft generated 4.4 billion U.S. dollars in global revenue during 2023.

The Measurable AI Amazon Consumer Transaction Dataset is a leading source of email receipts and consumer transaction data, offering data collected directly from users via Proprietary Consumer Apps, with millions of opt-in users.

We source our email receipt consumer data panel via two consumer apps which garner the express consent of our end-users (GDPR compliant). We then aggregate and anonymize all the transactional data to produce raw and aggregate datasets for our clients.

Use Cases Our clients leverage our datasets to produce actionable consumer insights such as: - Market share analysis - User behavioral traits (e.g. retention rates) - Average order values - Promotional strategies used by the key players. Several of our clients also use our datasets for forecasting and understanding industry trends better.

Coverage - Asia (Japan) - EMEA (Spain, United Arab Emirates) - Continental Europe - USA

Granular Data Itemized, high-definition data per transaction level with metrics such as - Order value - Items ordered - No. of orders per user - Delivery fee - Service fee - Promotions used - Geolocation data and more

Aggregate Data - Weekly/ monthly order volume - Revenue delivered in aggregate form, with historical data dating back to 2018. All the transactional e-receipts are sent from app to users’ registered accounts.

Most of our clients are fast-growing Tech Companies, Financial Institutions, Buyside Firms, Market Research Agencies, Consultancies and Academia.

Our dataset is GDPR compliant, contains no PII information and is aggregated & anonymized with user consent. Contact business@measurable.ai for a data dictionary and to find out our volume in each country.

Dataset

This dataset was created by Ankit Kumar Rana

Released under CC0: Public Domain

Contents

Opah labs 3227 specializes in providing third-party software solutions for last-mile delivery services in North America, excluding the United States. Established in 2015, their primary focus is on business-to-business (B2B) services. Their platform streamlines delivery operations, overseeing orders, drivers, and historical data, including Ecommerce data. They have a database containing 5,632,203 records spanning from August 5, 2021, to March 23, 2022, with no duplicates. They serve 1,134,167 unique users, with an 82.30% similarity rate. Their mission is to enhance last-mile delivery efficiency through software and data-driven solutions.

The data is sourced from an application that facilitates various deliveries, acting as a backend for providers. The company offers ETL services and can adjust delivery frequency, including daily collection. It has data coverage for Ozempic, Saxenda, Orlistat, and Hydrogel.

The dataset includes prescription delivery data and consumer goods data for users. This information offers insights into geographical transactions at a consumer level, with implications for consumer behavior and publicly traded companies.

Restaurant & Food Delivery Transaction Data is part of Opah 3227's comprehensive dataset, providing valuable insights into the dynamics of the food delivery industry. | Volume and Stats | Industry records undergo an unmatched refresh every two weeks. Many prominent sales and marketing platforms rely on curating firsthand data.

Delivery formats: JSON, XLS, CSV

| Data Points | With an impressive average of over 1,255,918 unique users. Key fields include Location, Payment Method, transit times, branch locations, and products.

| Use Cases | Pharma, Restaurant & Food Delivery Transaction, Ecommerce Pharma Data pertaining to the pharmaceutical industry. Restaurant & Food Delivery Transaction Details of transactions in the restaurant and food delivery sector. Ecommerce Online transactions, including products, purchases, and customer behavior, vital for optimizing online retail operations.

| Data Use Cases | Understand consumer purchasing and delivery behavior within the Mexico market

Data provides insights into pharmaceutical usage within the Mexico Market Insights into food consumption and food delivery usage

Insights into delivery applications transactions within the Mexico market, Rappi, Uber Eats, Ivoy, etc

Verified delivery consumer, email address, address information, etc

Geospatial, latitude, longitude, ping data coordinate values for consumers with timestamps

Geospatial, latitude, longitude, ping data coordinate values for delivery drivers

Insights into Mexico Farmacia brands delivery transactions

Insights to build targeted marketing campaigns for Mexico market consumers

| Delivery Options | Choose from various delivery options such as flat files, databases, APIs, and more, tailored to your needs.

| Other key features | Free data samples

Tags: Third-party software, On-Demand delivery, Last-mile, Drivers, Transit times, Branch locations, Products, Payments, Customer data, Food delivery, E-commerce, Pharmacy, Prescription action, Order processing, Efficiency, Customer behavior, Demand forecasting, Route optimization.

This is NOT a raw population dataset. We use our proprietary stack to combine detailed 'WorldPop' UN-adjusted, sex and age structured population data with a spatiotemporal OD matrix.

The result is a dataset where each record indicates how many people can be reached in a fixed timeframe (3 hours in this case) from that record's location.

The dataset is broken down into sex and age bands at 5 year intervals, e.g - male 25-29 (m_25) and also contains a set of features detailing the representative percentage of the total that the count represents.

The dataset provides 48420 records, one for each sampled location. These are labelled with a h3 index at resolution 7 - this allows easy plotting and filtering in Kepler.gl / Deck.gl / Mapbox, or easy conversion to a centroid (lat/lng) or the representative geometry of the hexagonal cell for integration with your geospatial applications and analyses.

A h3 resolution of 7, is a hexagonal cell area equivalent to: - ~1.9928 sq miles - ~5.1613 sq km

Higher resolutions or alternate geographies are available on request.

More information on the h3 system is available here: https://eng.uber.com/h3/

WorldPop data provides for a population count using a grid of 1 arc second intervals and is available for every geography.

More information on the WorldPop data is available here: https://www.worldpop.org/

One of the main use cases historically has been in prospecting for site selection, comparative analysis and network validation by asset investors and logistics companies. The data structure makes it very simple to filter out areas which do not meet requirements such as: - being able to access 70% of the UK population within 4 hours by Truck and show only the areas which do exhibit this characteristic.

Clients often combine different datasets either for different timeframes of interest, or to understand different populations, such as that of the unemployed, or those with particular qualifications within areas reachable as a commute.

With the taxi sector booming exponentially in the country, the ride hailing industry has been the source of employment for a number of people across India. The market is dominated by two players, Uber and Ola. The number of employees in OlaCabs was over 500 thousand as of July 2016. This snowballing growth of the cab industry has been creating problems for local rickshaw and auto drivers with people opting to take a ride in an online taxi as opposed to an auto-rickshaw.

Battle of the Giants

Even after the arrival of the San-Francisco based Uber, it is the native company doing the heavy lifting in the market. Ola held the highest share of taxi apps installed across the country in 2017, whereas Uber suffered more de-installations in the same time frame.

A cab wherever you are

High penetration is presumably one of the major factors for the success of the native company. As opposed to its main competitor, OlaCabs had a reach of an additional 20 percent among smartphone users in tier 1 cities in 2017. The firm operates in more than 100 cities, twice more than its counterpart, leading to this development. Despite the differences in their services and revenue streams, both companies still seem to thrive for greater success with new developments in the now fast-moving economy of India. With the announcement of an outpost in Australia, the home-grown startup from India does not seem willing to stop at just one destination.

This data set was collected from various sources: the research team, ANAS employees, and Uber drivers. The method for data collection and data processing for each dataset can be found in the related works.

DE: Der Datensatz enthält Transkripte der qualitativen, teilstrukturierten Experteninterviews mit Erwerbstätigen in Unternehmen, NGOs oder gesetzlichen Interessenvertretungen in Deutschland oder Österreich, zum Einsatz von algorithmischen Verfahren für das Risikomanagement ("Predictive Risk Intelligence" oder PRI) in zunehmend komplexen Wertschöpfungsnetzwerken, welche Ausfallwahrscheinlichkeiten von Maschinen oder Infrastruktur vorhersagen. Das Projekt untersucht, wie und mit welchen Konsequenzen für die betriebliche und überbetriebliche Mitbestimmung Predictive Risk Intelligence (PRI) von Unternehmen bereits eingesetzt wird. Zudem wird untersucht, wie algorithmische Vorhersagesysteme (ähnlich zu PRI oder auch neuartig) von Arbeitnehmer:innenvertretungen genutzt werden können, um Mitbestimmung in Zeiten der Entsolidarisierung weiterzuentwickeln. Hierzu wurden über einen Zeitraum von acht Monaten dreißig Interviewpartner:innen aus drei Stakeholdergruppen (Merchants, Customers und Audience) rund um PRI in Lieferketten mit leitfadengestützten Experteninterviews befragt. Schwerpunkte der Interviews waren die Einordung der eigenen Organisation im Kontext von globalen Lieferketten und Risikomanagement, Erfahrungen oder Einschätzungen zum Einsatz von PRI sowie die Beziehungen zu anderen Stakeholdergruppen. Ein sekundärer Untersuchungsgegenstand war zudem die Auswirkungen des in Deutschland eingeführten Lieferkettensorgfaltspflichtengesetz (LkSG) auf Praktiken des Risikomanagements. Die Gruppenzuweisung der Interviewten wird im Datensatz durch den Zusatz M (für Merchants), A (für Audience) und C (für Customers) kenntlich gemacht. Als Merchants gelten Vertreter:innen von Softwarelösungen für das Risikomanagement, zur Audience-Gruppe gehören Interessenvertretungen für Risikomanagement in Lieferketten, Customers stellen (potenzielle) Kund:innen von PRI-Anbietern dar, die überwiegend aus den Bereichen des Einkaufs und Supply-Chain-Managements stammen. Von den 30 Interviewteilnehmer:innen haben 18 der Nachnutzung ihrer Daten zugestimmt.EN: The dataset consists of qualitative, semi-structured expert interviews with professionals in companies, NGOs or or legal interest groups in Germany and Austria about the use of algorithmic methods for risk management ("Predictive Risk Intelligence" or PRI) in increasingly complex value networks that predict the failure probabilities of machinery or infrastructure. This project examines how Predictive Risk Intelligence (PRI) is already being used by companies and its consequences for corporate and inter-corporate participation. Furthermore, it explores how algorithmic prediction systems (similar to PRI or new ones) can be utilized by employee representatives to further develop participation in times of decreasing solidarity. For a period of eight months, thirty interviewees from three stakeholder groups (Merchants, Customers and Audience) were questioned about PRI in supply chains through guided expert interviews. These interviews focused on assessing the interviewees' own organizations in the context of global supply chains and risk management, their experiences or expectations of PRI implementation, as well as their relationships with other stakeholder groups. Another incidental subject of investigation was the impact on risk management practices triggered by the introduction of the Supply Chain Due Diligence Act (LkSG) in Germany. Within the dataset, the assignment of the interviewees to the three groups are indicated by the letter M (for Merchants), A (for Audience), and C (for Customers). Merchants refer to representatives of software solutions for risk management, the Audience group includes interest groups for risk management in supply chains, Customers represent (potential) customers of PRI providers, mainly stemming from purchasing departments and supply chain management. Out of the 30 interview participants, 18 have agreed to the reuse of their data.

This repository contains four datasets about the number of active users of selected mobile apps purchased from Selectivv company (https://selectivv.com/). Details regarding the data may be found below:

How data was collected: Selectivv uses programmatic advertisements systems that collect information on about 24 mln smartphone users in Poland

Apps:

Transportation: Uber, Bolt Driver, FREE NOW, iTaxi,

Delivery: Glover, Takeaway, Bolt Courier, Wolt;

Unit: an active user of a given app. Active = used given app at least 1 minute in a given period (e.g. 1 unit during whole month, half-year).

Period: 2018-2018; monthly and half-year data

Spatial aggregation: country level, city level, functional area level, voivodeship level. Functional area is defined as here https://stat.gov.pl/en/regional-statistics/regional-surveys/urban-audit/larger-urban-zones-luz/

Activity time: measured by activity time of given app (in hours; average and standard deviation)

Datasets:

gig-table1-monthly-counts-stats.csv -- the monthly number of active users;

gig-table2-halfyear-demo-stats.csv -- the half-year number of active users by socio-demographic variables;

gig-table3-halfyear-region-stats.csv -- the half-year number of active users by spatial aggregation;

gig-table4-halfyear-activity-stats.csv -- the half-year activity time by working week, weekend, day (8-18) and night (18-8).

Detailed description:

1. gig-table1-monthly-counts-stats.csv

Structure:

month - YYYY-MM-DD -- we set all dates to 15th of given month but actually the data is about the whole month (active users in whole period); 2018-01-15 to 2021-12-15

app -- app name (Uber, Bolt Driver, FREE NOW, iTaxi, Glover, Takeaway, Bolt Courier, Wolt)

number_of_users -- the number of active users

category -- Transportation, Deliver

1. gig-table2-halfyear-demo-stats.csv

Structure:

gender -- men, women

age -- 18-30, 31-50, 51-64

country -- Poland, Ukraine, Other

period -- 2018.1, 2018.2, 2019.1, 2019.2, 2020.1, 2021.2

apps -- app name (Uber, Bolt Driver, FREE NOW, iTaxi, Glover, Takeaway, Bolt Courier, Wolt)

number_of_users -- the number of active users

students -- the share of students within a given row

parents_of_children_0_4_years -- the share of parents of 0-4 years children in a given row

parents_of_children_5_10_years -- the share of parents of 5-10 years children in a given row

women_planning_a_baby -- the share of women planing a baby in a given row

standard -- the share of standard smartphones in a given row

premium_i_phone -- the share of iPhone smartphones in a given row

other_premium -- the share of other premium smartphones in a given row

category -- Transportation, Delivery

1. gig-table3-halfyear-region-stats.csv

Structure:

group -- Voivodeship, Functional Area, Cities

period -- 2018.1, 2018.2, 2019.1, 2019.2, 2020.1, 2021.2

region_name:

Cities -- Białystok, Bydgoszcz, Gdańsk, Gdynia, Gorzów Wielkopolski, Katowice, Kielce, Kraków, Łódź, Lublin, Olsztyn, Opole, Poznań, Rzeszów, Sopot, Szczecin, Toruń, Warszawa, Wrocław, Zielona Góra

Functional Area -- Functional area - Białystok, Functional area - Bydgoszcz, Functional area - Gorzów Wielkopolski, Functional area - GZM, Functional area - GZM2, Functional area - Kielce, Functional area - Kraków, Functional area - Łódź, Functional area - Lublin, Functional area - Olsztyn, Functional area - Opole, Functional area - Poznań, Functional area - Rzeszów, Functional area - Szczecin, Functional area - Toruń, Functional area - Trójmiasto, Functional area - Warszawa, Functional area - Wrocław, Functional area - Zielona Góra

Voivodeship -- dolnośląskie, kujawsko-pomorskie, łódzkie, lubelskie, lubuskie, małopolskie, mazowieckie, opolskie, podkarpackie, podlaskie, pomorskie, śląskie, świętokrzyskie, warmińsko-mazurskie, wielkopolskie, zachodniopomorskie

apps -- app name (Uber, Bolt Driver, FREE NOW, iTaxi, Glover, Takeaway, Bolt Courier, Wolt)

number_of_users -- the number of active users

category -- Transportation, Delivery

Please note that:

the number of active users in a given functional area = number of active users in a city and a functional area of this city

the number of active users in voivodeship = number of active users in a city, its functional area and the rest of the voivodeship where this city and functional area is located

More details here: https://stat.gov.pl/en/regional-statistics/regional-surveys/urban-audit/larger-urban-zones-luz/

1. gig-table4-halfyear-activity-stats.csv

Structure:

period -- 2018.1, 2018.2, 2019.1, 2019.2, 2020.1, 2021.2

apps -- app name (Uber, Bolt Driver, FREE NOW, iTaxi, Glover, Takeaway, Bolt Courier, Wolt)

day -- Mondays-Thursdays, Fridays-Sundays

hour -- day (8-18), night (18-8)

activity_time -- in hours

statistic -- Average, Std.Dev. (standard deviation)

category -- Transportation, Delivery

The crisis barometer on the COVID-19 pandemic in Germany was conducted by USUMA on behalf of the Konrad Adenauer Foundation. During the survey period from 30.03.2020 to 04.07.2020, 4228 respondents aged 18 and over living in private households in Germany were interviewed by telephone (CATI) on the following topics: pessimism/optimism; trust in institutions, crisis competence of political parties, effects of the Corona crisis, reception of news about Corona, Corona disease, Sunday question. Respondents were selected through multi-stage random sampling from an ADM selection frame including landline and mobile numbers (dual-frame sampling). The study was conducted week-by-week as a rolling cross-section survey. Pessimism or optimism about the future in general and for Germany; party preference (Sunday question); confidence in institutions (state government of the federal state, federal government, European Union, federal armed forces, police, health authorities, authorities, courts, German Bundestag); most competent party to deal with the crisis; assessment of measures as appropriate, going too far, or not going far enough; expected extent of the impact of the Corona crisis for the respondent; reception frequency of news about the Corona crisis; respondent has contracted the Corona virus COVID 19 himself; number of people in his circle of acquaintances who have tested positive for the Corona virus. Demography: sex; age; education; employment status; federal state; number of people 18 years and older who also regularly use the cell phone used; number of cell phone numbers used to reach the respondent by phone; number of landline phone numbers; household size. Additionally coded were: respondent ID; day of interview; weighting factor. Das Krisenbarometer zur COVID-19-Pandemie in Deutschland wurde von USUMA im Auftrag der Konrad-Adenauer-Stiftung durchgeführt. Im Erhebungszeitraum vom 30.03.2020 bis 04.07.2020 wurden 4228 in Privathaushalten in Deutschland lebende Prsonen ab 18 Jahren in telefonischen Interviews (CATI) zu folgenden Themen befragt: Pessimismus/Optimismus; Institutionenvertrauen, Krisenkompetenz der Parteien, Auswirkungen der Corona-Krise, Rezeption von Nachrichten über Corona, Corona-Erkrankung, Sonntagsfrage. Die Auswahl der Befragten erfolgte durch eine mehrstufige Zufallsauswahl aus einem ADM-Auswahlrahmen unter Einschluss von Festnetz- und Mobilfunknummern (Dual-Frame Stichprobe). Die Studie wurde wochenweise als Rolling-Cross-Section Survey durchgeführt. Pessimismus oder Optimismus im Hinblick auf die Zukunft allgemein und für Deutschland; Parteipräferenz (Sonntagsfrage); Institutionenvertrauen (Landesregierung des Bundeslandes, Bundesregierung, Europäische Union, Bundeswehr, Polizei, Gesundheitsamt, Behörden, Gerichte, Deutscher Bundestag); kompetenteste Partei zur Bewältigung der Krise; Bewertung der Maßnahmen als angemessen, gehen zu weit oder gehen nicht weit genug; erwartetes Ausmaß der Auswirkungen der Corona-Krise für den Befragten; Rezeptionshäufigkeit von Nachrichten über die Corona-Krise; Befragter ist selbst am Corona-Virus COVID 19 erkrankt; Anzahl der positiv auf das Corona-Virus getesteten Menschen im Bekanntenkreis. Demographie: Geschlecht; Alter; Bildung; Erwerbsstatus; Bundesland; Anzahl Personen ab 18 Jahren, die das genutzte Handy ebenfalls regelmäßig nutzen; Anzahl der Handynummern, über die der Befragte telefonisch erreichbar ist; Anzahl der Festnetz-Rufnummern; Haushaltsgröße. Zusätzlich verkodet wurde: Befragten-ID; Befragungstag; Gewichtungsfaktor.

This dataset contains the traffic volumes & Speeds in the area of the city of Münster, which were recorded as part of the campaign “Stadtradeln” of the Klima-Bündnis e.V. by users of the Stadtradeln-App in a 3-week period.

Data is available as heatmaps in hexagon cells (H12) according to Uber’s system for the years 2018 to 2020. This data was processed in the course of the research project MOVEBIS at TU Dresden. This is a mFUND project of the Federal Ministry of Transport and Digital Infrastructure.

The data are licensed under CC-BY-NC, i.e. they may not be re-used for commercial purposes, and the author must be named: “Grubitzsch P., Lißner S., Huber S., Springer T., [2021] Technische Universität Dresden, Chair of Computer Networks and Chair of Transport Ecology”

In this dataset there are only the data for the Münster area. The Germany-wide data can be found at: https://www.mcloud.de/web/guest/suche/-/results/suche/relevance/stadtradeln/0/detail/3096DB7A-9EE4-4C14-B2AA-79E33A7FFF01 Included in some cases are geocoordinates outside the federal territory.

Further data sets of the action “Stadtradeln” from the years 2018-2020 can be found on the mFUND website at the following link: https://www.mcloud.de/web/guest/suche/-/results/suche/relevance/stadtradeln/0

https://opendata.stadt-muenster.de/sites/default/files/vorschau-stadtradeln-heatmap-2018.png" style="width: 559px; height: 400px;"/> (Heatmap visualisation of cycling volumes 2018, produced by Gerald Pape)

Information on the volume of cycling data For easier further use, the raw data originally available as CSV was additionally converted to the GeoJSON format. Thank you for this conversion to Gerald Pape. For more information, see CodeForMünster’s Github repository: https://github.com/codeformuenster/stadtradeln-vis

Information on the speed data The speed data was prepared by the MITFAHR|DE|ZENTRALE. An interactive visualisation of the data can be found at: https://heatview.de/?kreis=05515 The source code of this visualisation can be found at https://github.com/mfdz/heatview-website

Change of subjective attitudes of the people in Eastern Germany. Topics: Development of personal situation in life in the next few weeks; importance of areas of life; time consciousness; general contentment with life; satisfaction with areas of life; comparison of retrospective satisfaction with current; eligibility to vote and election participation at the last Federal Parliament election; the question of memory of the election; self-classification on a left-right continuum; assessment of socialism as an idea; satisfaction with democracy in the Federal Republic; preferred forms of political participation (scale); political commitment; goals in life (scale); strength of influence of various groups of persons on municipal politics; importance of support by family, relatives, friends, colleagues, government and church facilities in situations of need; expectations of family and friends of the conduct of respondent; opinion on the adaptation of living conditions in Eastern and Western Germany and expected time period; judgement on one's own economic situation; preferred leisure activities; activities to structure one's own situation in life; expected social changes in the next few years; self-assessment of condition of health; relationship to various parties; membership in trade union, club, association, citizen initiative; discussion about the affairs of the municipality in these organizations; frequency of activity in these organizations; gatherings such as group of regulars, hen party, sociable circle of friends, environment and peace groups; sources of information on municipal affairs; participation in citizen initiatives or collecting signatures; readiness for participation in municipal politics; criticism of conditions in the new states within the circle of friends; cultural gains and losses since the turning point; postmaterialism questions; existence of building loan contract, life insurance, other capital insurance policies, loans; residency at place of residence and in part of town; length of residence in current residence; solidarity with place of residence; interest in municipal politics; relatives in same place of residence; subjective classification of social class; possession of a telephone and entry in telephone book; personal jeopardy to job; religious affiliation; solidarity with church; place of birth in the new states; time of move to the new states. Wandel der subjektiven Einstellungen der Menschen in Ostdeutschland. Themen: Entwicklung der persönlichen Lebenssituation in den nächsten Wochen; Wichtigkeit der Lebensbereiche; Zeitbewußtsein; allgemeine Lebenszufriedenheit; Zufriedenheit mit den Lebensbereichen; Vergleich der retrospektiven Zufriedenheit mit der aktuellen; Wahlberechtigung und Wahlbeteiligung bei der letzten Bundestagswahl; Wahlrückerinnerungsfrage; Selbsteinstufung auf Links-Rechts-Kontinuum; Einschätzung des Sozialismus als Idee; Zufriedenheit mit der Demokratie in der Bundesrepublik; präferierte Formen der politischen Partizipation (Skala); politisches Engagement; Lebensziele (Skala); Stärke des Einflusses verschiedener Personengruppen auf Kommunalpolitik; Wichtigkeit der Unterstützung durch die Familie, Verwandtschaft, Freunde, Arbeitskollegen, staatliche und kirchliche Einrichtungen bei Notsituationen; Erwartungen der primären Umwelt an das Verhalten der Befragten; Meinung über die Anpassung der Lebensverhältnisse in Ost- und Westdeutschland und erwarteter Zeitraum; Beurteilung der eigenen wirtschaftlichen Lage; präferierte Freizeitaktivitäten; Aktivitäten zur Gestaltung der eigenen Lebenssituation; erwartete gesellschaftliche Veränderungen in den nächsten Jahren; Selbsteinschätzung des Gesundheitszustandes; Verhältnis zu verschiedenen Parteien; Mitgliedschaft in Gewerkschaft, Verein, Verband, Bürgerinitiative; Diskussion über die Angelegenheiten der Gemeinde in diesen Organisationen; Häufigkeit der Betätigung in diesen Organisationen; Treffen wie Stammtisch, Kaffeekränzchen, geselliger Freundeskreis, Umwelt- und Friedensgruppen; Informationsquellen für kommunale Angelegenheiten; Beteiligung an Bürgerinitiativen oder Unterschriftensammlungen; Bereitschaft zur Mitarbeit in der Kommunalpolitik; Kritik an den Zuständen in den neuen Bundesländern innerhalb des Freundeskreises; kulturelle Gewinne und Verluste seit der Wende; Postmaterialismus-Fragen; Existenz von Bausparvertrag, Lebensversicherung, anderen kapitalbildenden Versicherungen, Kredit; Ansässigkeit am Wohnort und im Ortsteil; Wohndauer in jetziger Wohnung; Verbundenheit mit dem Wohnort; Interesse an der Kommunalpolitik; Verwandtschaft im gleichen Wohnort; subjektive Schichteinstufung; Telefonbesitz und Telefonbucheintrag; eigene Arbeitsplatzgefährdung; Religionszugehörigkeit; Verbundenheit mit Kirche; Geburtsort in den neuen Bundesländern; Zeitpunkt des Umzuges in die neuen Bundesländer.

Political attitudes of Soviet citizens. Questions on French-Soviet relations. Topics: judgement on selected government measures in connection with the 27th party convention of the Communist Party of the Soviet Union; attitude to ´Perestroika´; expected influence of ´Perestroika´ on increase in food prices; perception of drug addiction as a danger to the country; judgement on quality of television programs; knowledge about Sacharow; satisfaction with the achievements of the public health system; most significant historical and modern-day personality of the Soviet Union; attitude to the death penalty; expected influence of changes taking place in the USSR on the relationship to the West and the international situation; preferred type of music; assessment of the probability of another accident in a Soviet nuclear power plant as well as of the efforts of the Soviet Government to prevent further nuclear accidents; judgement on relations of the USSR to the USA, France, the Federal Republic of Germany, Great Britain, China and India; satisfaction with the status of the relations between the USSR and France and judgement on changes in these relations in the last year; judgement on economic, cultural and political cooperation between the USSR and France; area with the greatest progress in cooperation; spontaneous naming of three French words; naming preferred representatives of France; knowledge of selected events from French-Soviet history; country with the closest friendship to France; positive or negative judgement on the French people; spontaneous naming of persons associated with France; knowledge about the nationality of the space ship of the first flight of a French Cosmonaut; perceived threat to the Soviet Union or France from nuclear weapons as well as conventional, non-nuclear weapons of the respective other country; knowledge about the French language; use of French-language media and type of media used; judgement on the objectivity of information from French sources or Soviet media; perceived intervention of France in internal matters of the USSR; attitude to nuclear weapons as well as a nuclear or conventional conflict in Europe, an increase and modernization of the French nuclear arsenal, first use of nuclear weapons by the USSR or France as well as peaceful solution of European problems and contribution of abstaining from nuclear weapon tests to the reduction in the arms race; knowledge about the Berlin Wall as well as attitude to removal of the wall; attitude to removal of all nuclear weapons in Europe; preferred area of a pan-European cooperation; judgement on the military balance of powers between NATO and the Warsaw Pact; preferred travel countries outside of the East Bloc; probability of outbreak of a third world war; desire for a meeting between Gorbachev and Reagan as well as judgement on the chances for success of negotiations; perceived danger from a simultaneous reduction in Soviet and American medium-range missiles; judgement on progress in the area of military technology regarding greater security or additional danger of war; most important friend and greatest enemy of the Soviet Union. Demography: age (classified); sex; marital status; respondent has children; current education level; employment; institution at which respondent is studying (e.g. college, technical college, vocational technical school); occupational position; earlier participation in surveys; optimistic or pessimistic future expectations. Politische Einstellungen von Sowjet-Bürgern. Fragen zu den französisch-sowjetischen Beziehungen. Themen: Beurteilung ausgewählter Regierungsmaßnahmen im Anschluß an den 27. Parteitag der KPdSU; Einstellung zur "Perestroika"; vermuteter Einfluß der "Perestroika" auf die Erhöhung der Lebensmittelpreise; Wahrnehmung der Drogensucht als Gefahr für das Land; Beurteilung der Qualität der Fernsehprogramme; Kenntnisse über Sacharow; Zufriedenheit mit den Leistungen des Gesundheitswesens; bedeutendste historische und heutige Persönlichkeit der Sowjetunion; Einstellung zur Todesstrafe; vermuteter Einfluß der sich in der UdSSR vollziehenden Veränderungen auf das Verhältnis zum Westen und die internationale Lage; präferierte Musikrichtung; Einschätzung der Wahrscheinlichkeit eines erneuten Unfalls in einem sowjetischen Atomkraftwerk sowie der Bemühungen der Sowjetregierung zur Verhinderung weiterer Atomunfälle; Beurteilung der Beziehungen der UdSSR zu den USA, Frankreich, der Bundesrepublik Deutschland, Großbritannien, China und Indien; Zufriedenheit mit dem Stand der Beziehungen zwischen der UdSSR und Frankreich und Beurteilung der Veränderungen in diesen Beziehungen im letzten Jahr; Beurteilung der wirtschaftlichen, kulturellen und politischen Zusammenarbeit zwischen der UdSSR und Frankreich; Bereich mit der fortgeschrittensten Zusammenarbeit; spontane Nennung von drei französischen Wörtern; Nennung von präferierten Repräsentanten Frankreichs; Kenntnis ausgewählter Ereignisse aus der französisch-sowjetischen Geschichte; Land mit der engsten Freundschaft zu Frankreich; positive oder negative Beurteilung des französischen Volkes; spontane Nennung von Personen, die mit Frankreich assoziiert werden; Kenntnis der Nationalität des Raumschiffes beim ersten Flug eines französischen Kosmonauten; empfundene Bedrohung der Sowjetunion bzw. Frankreichs durch die Atomwaffen sowie die konventionellen, nicht-atomaren Waffen des jeweils anderen Landes; Kenntnis der französischen Sprache; Nutzung französischsprachiger Medien und Art der genutzten Medien; Beurteilung der Objektivität der Informationen aus französischen Quellen bzw. aus sowjetischen Medien; empfundene Einmischung Frankreichs in die inneren Angelegenheiten der UdSSR; Einstellung zu Atomwaffen sowie einem atomaren bzw. konventionellen Konflikt in Europa, einer Aufstockung und Modernisierung des französischen Atomarsenals, dem Ersteinsatz von Kernwaffen durch die UdSSR bzw. Frankreich sowie zur friedlichen Lösung europäischer Probleme und zum Beitrag des Verzichts von Kernwaffentests auf die Abschwächung des Wettrüstens; Kenntnis der Berliner Mauer sowie Einstellung zu einer Beseitigung der Mauer; Einstellung zur Beseitigung aller Kernwaffen in Europa; präferierter Bereich einer gesamteuropäischen Zusammenarbeit; Beurteilung des militärischen Kräfteverhältnisses zwischen der NATO und dem Warschauer Pakt; präferierte Reiseländer außerhalb des Ostblocks; Wahrscheinlichkeit des Ausbruchs eines Dritten Weltkriegs; Wunsch nach einem Treffen zwischen Gorbatschow und Reagan sowie Beurteilung der Erfolgschancen von Verhandlungen; wahrgenommene Gefahr durch einen gleichzeitigen Abbau sowjetischer und amerikanischer Mittelstreckenraketen; Beurteilung der Fortschritte auf dem Gebiet der Militärtechnik hinsichtlich größerer Sicherheit oder zusätzlicher Kriegsgefahr; wichtigster Freund und größter Feind der Sowjetunion. Demographie: Alter (klassiert); Geschlecht; Familienstand; Befragter hat Kinder; gegenwärtiger Bildungsstand; Erwerbstätigkeit; Institution, an der der Befragte lernt (z.B. Hochschule, Technikum, berufstechnische Schule); berufliche Position; frühere Teilnahme an Befragungen; optimistische oder pessimistische Zukunftserwartungen. Random selection. In Moscow they were obtained from telephone lists and in Indjavino from the voter list.

On behalf of the Press and Information Office of the Federal Government, the opinion research institute forsa has regularly conducted representative population surveys on the subject of the ´Corona crisis´ (COVID-19) from calendar week 12/2020. The individual question areas were adapted according to the survey period. Credibility of the information provided by the federal government on the Corona crisis; assessment of the current political measures to contain the Corona virus (appropriate, go too far or do not go far enough); agreement with various statements with regard to the Corona crisis (the state is interfering too much in our lives in the Corona crisis, citizens are well informed by politicians about the current measures in the Corona crisis, politicians in Germany are doing most things right in dealing with the Corona crisis, people no longer know exactly which measures and rules are actually in place, people´s freedom is being restricted too much in the Corona crisis, worries that many measures and restrictions will not be withdrawn after the Corona crisis, politicians are only using the Corona virus as an excuse to permanently restrict freedom rights, in the Corona crisis, people´s personal responsibility should be emphasized above all instead of strict rules); vaccination status: Number of Corona vaccinations already received (none, one, two, three); willingness to be vaccinated against the Corona virus; willingness to receive a booster vaccination against Corona; own children aged between 5 and 11 years or between 12 and 17 years; basic willingness to vaccinate own children aged between 5 and 11 years or between 12 and 17 years against the Corona virus. Demography: sex; age (grouped); employment; education; net household income (grouped); party preference in the next general election; voting behaviour in the last general election. Additionally coded: region; federal state; weight. Im Auftrag des Presse- und Informationsamts der Bundesregierung hat das Meinungsforschungsinstitut forsa ab Kalenderwoche 12/2020 regelmäßig repräsentative Bevölkerungsbefragungen zum Thema ´Corona-Krise´ (COVID-19) durchgeführt. Die einzelnen Fragegebiete wurden je nach Befragungszeitraum angepasst. Glaubwürdigkeit der Informationen der Bundesregierung zur Corona-Krise; Bewertung der aktuellen politischen Maßnahmen zur Eindämmung des Corona-Virus (angemessen, gehen zu weit oder gehen nicht weit genug); Zustimmung zu verschiedenen Aussagen im Hinblick auf die Corona-Krise (der Staat mischt sich in der Corona-Krise zu sehr in unser Leben ein, die Bürger werden von der Politik gut über die aktuellen Maßnahmen in der Corona-Krise informiert, die Politik in Deutschland macht bei der Bewältigung der Corona-Krise das meiste richtig, man weiß gar nicht mehr genau, welche Maßnahmen und Regeln gerade eigentlich gelten, die Freiheit der Menschen wird in der Corona-Krise zu stark eingeschränkt, Sorgen, dass viele Maßnahmen und Einschränkungen nach der Corona-Krise nicht zurückgenommen werden, die Politik nimmt das Coronavirus nur als Vorwand, um dauerhaft Freiheitsrechte einzuschränken, in der Corona-Krise sollte man vor allem auf die Eigenverantwortung der Menschen statt auf strenge Regeln setzen); Impfstatus: Anzahl der bereits erhaltenen Corona-Impfungen (keine, eine, zwei, drei); Bereitschaft zur Impfung gegen das Coronavirus; Bereitschaft zu einer Auffrischungsimpfung (Boosterimpfung) gegen Corona; eigene Kinder im Alter zwischen 5 und 11 Jahren oder zwischen 12 und 17 Jahren; grundsätzliche Bereitschaft eigene Kinder im Alter zwischen 5 und 11 Jahren bzw. zwischen 12 und 17 Jahren gegen das Coronavirus impfen zu lassen. Demographie: Geschlecht; Alter (gruppiert); Erwerbstätigkeit; Schulabschluss; Haushaltsnettoeinkommen (gruppiert); Parteipräferenz bei der nächsten Bundestagswahl; Wahlverhalten bei der letzten Bundestagswahl. Zusätzlich verkodet wurde: Region; Bundesland; Gewicht.

The German Library Statistics (DBS) is the national statistics of the German library system and contains statistical key figures. It includes public libraries, scientific libraries, as well as specialized scientific libraries. More information can be found at DBS. This dataset contains the following information about scientific libraries in Bavaria in 2005:
Photocopies (by users), access to individual digital documents

Attitudes of young people towards science. Topics: interest in each of the following topics: sports, politics, science and technology, economics, culture and entertainment; interest in each of the following subjects: information and communication technologies, earth and environment, universe, medical discoveries, new inventions and technologies; attitude towards selected statements on science and technology: science brings more benefits than harm, help eliminate hunger and poverty around the world, technology creates more jobs than it eliminates, science is too much influenced by profit, make lives healthier and more comfortable; attitude towards the following statements on the purpose of scientific research: should above all serve the development of knowledge, should above all serve economic development, should above all serve businesses and enterprises; awareness about innovations in the following areas of research: genetically modified food, nanotechnology, nuclear energy, mobile phones, human embryo research, brain research, computer and video surveillance techniques; attitude towards risks and advantages of the aforementioned research areas; most effective measures in tackling green-house effect and global warming; expected development in the following areas in the next twenty years in the own country: food quality, quality of air in cities, health, water quality, communication between people; assessment of the health risks of: air pollution caused by cars, pesticides used in plant production, genetically modified foods, fertilizers in underground water, vicinity of nuclear power plants, use of mobile phones, vicinity of high tension power lines, vicinity of chemical plants, new epidemics; preferred authorities to have biggest influence on decisions with regard to financing research: scientific community, government, citizens, private enterprises, research organisations, European Union, media; attitude towards the following statements on scientists: devoted to the good of humanity, dangerous power due to their knowledge; considerations to take up studies in the following fields: natural sciences, mathematics, engineering, biology or medicine, social sciences or humanities, economics; reasons for not taking up studies in the aforementioned fields; preferred kind of scientific profession: researcher in public sector, teacher, researcher in private sector, engineer, technician, health professional; attitude towards selected statements: young people’s interest in science is essential for future prosperity, girls and young women should be encouraged to take up careers in science, science classes at school are not appealing, national government should spend more money on scientific research, EU should spend more money on scientific research, need for better cooperation between member states and EU. Demography: sex; age; highest completed level of full time education; full time student; occupation of main income earner in the household; professional position of main income earner in the household; type of community. Additionally coded was: respondent ID; interviewer ID; language of the interview; country; date of interview; time of the beginning of the interview; duration of the interview; type of phone line; region; weighting factor. Interesse junger Menschen an Wissenschaft und Technologie. Themen: Interesse an Nachrichten über: Sport, Politik, Wissenschaft und Technologie, Wirtschaft, Kultur und Unterhaltung; Interesse an den Themen: Informations- und Kommunikationstechnologien, Erde und Umwelt, Universum, menschlicher Körper und Medizin, Erfindungen und Technologien; Einstellung zu Wissenschaft und Technologie (Skala): Wissenschaft als Nutzen oder Schaden, Verringerung der Armut, Schaffung von Arbeitsplätzen, Wissenschaft durch Profit beeinflusst, Lebenserleichterung; Zweck von Wissenschaft: Wissensgenerierung, wirtschaftliche Entwicklung, Nutzen für Unternehmen; Kenntnis von Innovationen im Bereich: genetisch veränderten Lebensmitteln, Nanotechnologie, Mobiltelefonie, Atomenergie, Embryonenforschung, Gehirnforschung, Überwachungstechniken sowie Einschätzung der Risiken dieser Forschungsfelder für die Gesellschaft; Lösung des Klimawandels durch Technik, Lebensweise oder Gesetze; Verbesserung der Situation im eigenen Land bei: Lebensmittelqualität sowie der Stadtluft und der Wasserqualität, Gesundheit der Bevölkerung, Kommunikation zwischen Menschen; Einschätzung des Risikos für die Menschheit durch: Luftverschmutzung, Pestizide, genetisch veränderte Lebensmittel, Verschmutzung des Grundwassers durch Düngen, Atomkraft, Mobiltelefone, Hochspannungsleitungen, Chemiewerke, Epidemien; präferierte gesellschaftliche Gruppe mit dem größten Einfluss auf Entscheidungen zur Forschungsfinanzierung; Meinung über Wissenschaftler: hingebungsvolle Menschen, die für das Wohl der Menschheit arbeiten, Gefahr der Wissensmacht; Interesse an einem Studium; Berufsziel; Gründe gegen ein Studium; Meinung zur Bedeutung der Wissenschaft für die Gesellschaft (Skala): entscheidend für zukünftigen Wohlstand, Ermutigung von jungen Leuten, ein wissenschaftliches Studium oder Berufe in der Wissenschaft zu ergreifen, Unattraktivität des Wissenschaftsunterrichts in der Schule, mehr Forschungsförderung durch die eigene Regierung sowie durch die EU, Forderung nach besserer Koordination der Forschung zwischen Mitgliedsstaaten der EU. Demographie: Geschlecht; Alter; höchster Bildungsabschluss; Vollzeitstudent; Beruf des Haupteinkommensbeziehers im Haushalt; berufliche Stellung des Haupteinkommensbeziehers im Haushalt; Urbanisierungsgrad. Zusätzlich verkodet wurde: Befragten-ID; Interviewer-ID; Interviewsprache; Land; Interviewdatum; Interviewdauer (Interviewbeginn und Interviewende); Interviewmodus (Mobiltelefon oder Festnetz); Region; Gewichtungsfaktor.

This study investigates how stakeholders throughout the state of California view the potential impacts of ridehailing services such as Uber or Lyft, to transportation systems, and how to address such impacts. Ridehailing is one of several emerging shared use mobility alternatives, poised to impact transportation systems, for better or worse. For better if these new services catalyze the development and maturation of well-integrated multi-model transportation systems that serve all travelers and reduce vehicle miles travelled (VMT) and transportation emissions. For worse if these new services serve merely as a less expensive taxi, allowing more people to forego alternative modes of transportation like public transit and biking, thereby leading to increases in VMT and emissions and worsening congestion impacts. The high degree of uncertainty surrounding the impacts of these services presents challenges to stakeholders involved in transportation planning and policymaking. How transportation stakeholders view the potential positive and negative impacts of ridehailing and what to do about them is an open question, and one that warrants investigation as these services become more popular and their impacts begin to be understood. Through interviews, we investigate the viewpoints of 42 transportation stakeholders throughout the state of California. We find the diversity of interviewees is reflected in the sentiments they have about ridehailing, what issues are important and potential obstacles to achieving positive outcomes. Nonetheless, interviewees agree that regulations should balance local control with state level guidance.

Information on working conditions of young people in Hesse. Topics: characterization of training and terms of employment; company size and number of trainees in the company; works council and youth representation; membership in trade union or professional association; particular workplace arrangements and reason for them; detailed information about daily working hours with begin, end and break times; public posting about arrangement of working hours; overtime; overtime compensation; weekend and holiday work; leisure time compensation for holiday work; work in the company during times for teaching by topics; time off received in compensation for vocational school instruction on work-free weekdays; information on vocational school instruction times; cancellation of vocational school instruction due to work in the company; classroom instruction in the company doing the training; number of days of vacation; distribution of the days of vacation throughout the calender year; vacation on vocational school holidays; piecework or time-dependent work; directions received at the start of training on accident and health risks and in the further course of training; medical examination before start of training; medical prohibition of certain activities and observation by employer; medical follow-up examination; survey on personal job situation regarding the factory inspectorate official; knowledge about the youth industrial health and safety laws; posting about protection rules in the company. Angaben über die Arbeitsbedingungen Jugendlicher in Hessen. Themen: Charakterisierung des Ausbildungs- und Beschäftigungsverhältnisses; Betriebsgröße und Anzahl der Auszubildenden im Betrieb; Betriebsrat und Jugendvertretung; Mitgliedschaft in Gewerkschaft oder Berufsverband; besondere Arbeitsplatzregelungen und Gründe dafür; detaillierte Angaben über die tägliche Arbeitszeit mit Beginn, Ende und Pausenzeiten; öffentlicher Aushang über Arbeitszeitregelung; Überstunden; Überstundenausgleich; Wochenend- und Feiertagsarbeit; Freizeitausgleich für die Feiertagsarbeit; Arbeit im Betrieb während der Blockunterrichtszeiten; erhaltene Ausgleichsfreizeit für Berufsschulunterricht an arbeitsfreien Werktagen; Angaben über die Berufsschulunterrichtszeiten; Ausfall von Berufsschulunterricht wegen Arbeit im Betrieb; theoretischer Unterricht im Ausbildungsbetrieb; Anzahl der Urlaubstage; Verteilung der Urlaubstage auf das Kalenderjahr; Urlaub in Berufsschulferien; akkord- oder tempoabhängiges Arbeiten; erhaltene Unterweisung über Unfall- und Gesundheitsgefahren bei Ausbildungsbeginn und im weiteren Verlauf der Ausbildung; ärztliche Untersuchung vor Ausbildungsbeginn; ärztliches Verbot bestimmter Tätigkeiten und Beachtung durch den Arbeitgeber; ärztliche Nachuntersuchung; Befragung zur persönlichen Arbeitssituation seitens Gewerbeaufsichtsamtbeamter; Kenntnis der Jugendarbeitsschutzgesetze; Aushang über Schutzregeln im Betrieb. The choice of occupational groups took place on the suspicion of particular problems in enforcing the youth protection law. Die Auswahl der Berufsgruppen geschah nach der Vermutung besonderer Probleme bei der Durchführung des Jugendschutzgesetzes.

The DIECovidSurvey was conducted by the German Institute for Adult Education (DIE) in collaboration with the Deutscher Volkshochschul-Verband e.V. (dvv) in fall 2020 to examine the impact of the Corona pandemic on German adult education centers (vhs). The questionnaire was developed jointly by DIE and dvv. The core of the survey is detailed information about the range of events offered during the first lockdown in spring and early summer 2020, when events in attendance were prohibited. The questionnaire collects detailed information for each program area on the number of courses and individual events planned before the lockdown and actually held during the lockdown, as well as the event format (face-to-face/blended learning/online). Further contents of the survey concern the personnel and financial situation, the available space, effects of the pandemic on participant groups, the use of digital technologies including vhs.cloud, the inclusion of corona-related events in the program, assessments of the situation at the time of the survey, as well as future strategies and perceived challenges with regard to digitization and program design. The survey was conducted as an online survey in LimeSurvey, with an invitation to participate sent to all German vhs. (Project) Topics: Pre-pandemic room availability, semester rhythm and corona-related closing times, fee contracts, study trips/travel; Events offered: Politics - Society - Environment, Culture - Design, Health, Languages, Integration Courses and DeuFöV Courses, Qualifications for Working Life, School Leaving Certificates, Basic Education; Changes in course participants, summer programme 2020, current rooms and fee contracts, event planning autumn 2020, comparison of event offers autumn 2020/2019, difficulties in planning face-to-face events, difficulties in planning digital learning offers; Previous experience with digital learning offers & vhs.cloud, use of vhs.cloud, changes in cloud users, experience with digital learning offers in Pandemic, influence of Pandemic on digital learning offers; Failures and repayments of participation fees, public support measures, financial burdens, reference of educational offers to COVID-19, challenges Das DIECovidSurvey wurde vom Deutschen Institut für Erwachsenenbildung (DIE) in Zusammenarbeit mit dem Deutschen Volkshochschulverband (dvv) im Herbst 2020 durchgeführt, um die Auswirkungen der Corona-Pandemie auf die deutschen Volkshochschulen (vhs) zu untersuchen. Der Fragebogen wurde von DIE und dvv gemeinsam entwickelt. Kernstück der Befragung sind detaillierte Angaben über das Veranstaltungsangebot im ersten Lockdown im Frühling und Frühsommer 2020, als Veranstaltungen in Präsenz untersagt waren. Der Fragebogen erhebt detailliert für jeden Programmbereich die Zahl der vor Lockdown geplanten sowie im Lockdown tatsächlich durchgeführten Kurse und Einzelveranstaltungen sowie das Veranstaltungsformat (Präsenz/Blended Learning/Online). Weitere Inhalte der Befragung betreffen die personelle und finanzielle Situation, das verfügbare Raumangebot, Auswirkungen der Pandemie auf Teilnehmendengruppen, die Nutzung digitaler Technologien inklusive der vhs.cloud, die Aufnahme coronabezogener Veranstaltungen ins Programm, Einschätzungen der Lage zum Befragungszeitpunkt, sowie zukünftige Strategien und wahrgenommene Herausforderungen in Bezug auf Digitalisierung und Programmgestaltung. Die Erhebung wurde als Online-Befragung in LimeSurvey durchgeführt, wobei eine Aufforderung zur Teilnahme an alle deutschen vhs erging. (Projekt)

Attitudes towards the Coronavirus (COVID-19) pandemic. Topics: satisfaction with the national government in general; satisfaction with the measures of the national government to fight the Coronavirus pandemic; preferred statement with regard to the consequences of the restriction measures in the own country: health benefits are greater than economic damage, economic damage is greater than health benefits; satisfaction with solidarity between EU member states in fighting the Coronavirus pandemic; awareness of measures taken by the EU to respond to the Coronavirus pandemic; satisfaction with these measures; EU should have more competences to deal with crises such as the Coronavirus pandemic; preferred EU measures to respond to the Corona crisis; preferred statement: fight against the Coronavirus pandemic fully justifies recent limitations to individual freedom, fully opposed to any limitation of individual freedom regardless of the pandemic; attitude towards public authorities using mobile phone applications of citizens to fight the virus’ expansion; current emotional status; concern about the effect of the Coronavirus on: personal health, health of family and friends; personally experienced effects of the Coronavirus pandemic in the own country: loss of income, difficulties paying rent or bills or bank loans, use of personal savings sooner than planned, unemployment, bankruptcy, difficulties having proper and decent-quality meals, asked for financial help to family or friends, other financial issues; impact of the Coronavirus pandemic on personal situation: respondent receives help from people around, respondent helps people in need, more contact to people on the phone or via internet apps, engagement in online debates on the measures against the pandemic; use of selected online social networks in the last week; most trustworthy persons or institutions with regard to information about the Coronavirus pandemic; EU image; impact of the pandemic on EU image; participation in the last elections to the European Parliament. Demography: sex; age; age at end of education; head of household; occupation of main income earner in the household; professional position of main income earner in the household; employment status; marital status; household composition and household size; region. Additionally coded was: respondent ID; country; date of interview; weighting factor. Einstellungen zur Corona-Pandemie (COVID-19). Themen: Zufriedenheit mit der nationalen Regierung im Allgemeinen; Zufriedenheit mit den Maßnahmen der nationalen Regierung zur Bekämpfung der Corona-Pandemie; präferierte Aussage im Hinblick auf die Konsequenzen der beschlossenen Einschränkungen im eigenen Land: gesundheitlicher Nutzen ist größer als der wirtschaftliche Schaden, wirtschaftlicher Schaden ist größer als der gesundheitliche Nutzen; Zufriedenheit mit der Solidarität unter den EU-Mitgliedstaaten bei der Bekämpfung der Corona-Pandemie; Kenntnis über Maßnahmen der EU zur Bewältigung der Corona-Pandemie; Zufriedenheit mit diesen Maßnahmen; EU sollte mehr Kompetenzen im Umgang mit Krisen wie der Corona-Pandemie haben; präferierte EU-Maßnahmen zur Bewältigung der Corona-Krise; präferierte Aussage: Kampf gegen die Corona-Pandemie rechtfertigt die kürzlichen Einschränkungen der individuellen Freiheit vollkommen, Ablehnen jeglicher Einschränkungen der individueller Freiheit unabhängig von der Pandemie; Einstellung zur Nutzung spezieller Apps auf den Mobiltelefonen der Bürger durch öffentliche Behörden zur Verhinderung der Verbreitung des Virus; derzeitiger Gefühlszustand; Besorgnis über den Effekt des Coronavirus auf: persönliche Gesundheit, Gesundheit von Familie und Freunden; persönliche Erfahrungen mit den Auswirkungen der Corona-Pandemie im eigenen Land: Einkommensverlust, Schwierigkeiten bei der Bezahlung von Mieten oder Rechnungen oder Darlehen, Verwendung von Ersparnissen früher als geplant, Arbeitslosigkeit, Konkurs, keine vernünftigen Mahlzeiten, Bitte um finanzielle Unterstützung durch Familie oder Freunde, andere finanzielle Angelegenheiten; Einfluss der Corona-Pandemie auf die persönliche Situation: Befragte/r bekommt Hilfe aus dem persönlichen Umfeld, Befragte/r hilft Bedürftigen, mehr Kontakt zu anderen über Telefon oder Internet-Apps, Engagement in Online-Debatten zu den Maßnahmen gegen die Pandemie; Nutzung ausgewählter sozialer Netzwerke im Internet in der letzten Woche; vertrauenswürdigste Personen oder Institutionen im Hinblick auf Informationen zur Coronavirus-Pandemie; Image der EU; Auswirkungen der Pandemie auf das Image der EU; Teilnahme an den letzten Europawahlen. Demographie: Geschlecht; Alter; Alter bei Beendigung der Ausbildung; Haushaltsvorstand; Beruf des Haupteinkommensbeziehers im Haushalt; berufliche Stellung des Haupteinkommensbeziehers im Haushalt; Beschäftigungsstatus; Familienstand; Haushaltszusammensetzung und Haushaltsgröße; Region. Zusätzlich vercodet wurde: Befragten-ID; Land; Interviewdatum; Gewichtungsfaktor.