The dataset concerns the deliberate learning practices of new venture founders in Norway, as well as a self-evaluation of their expertise in key aspects of entrepreneurship. The methodology used was survey research, and the data were collected through an on-line questionnaire. The dataset consists of a sample of founders from the population of limited-liability firms incorporated in Norway in 2018.

Vents and Reefs deep-sea ecosystem study of the 45o North MAR hydrothermal vent field and the cold-water coral Moira Mounds, Porcupine Seabight . This survey took place on board the R.V. Celtic Explorer in July/Augyst 2011 along the mid-Atlantic ridge, led by University College Cork and focuses on two distinct deep-water biogeological systems - hydrothermal vents and cold-water coral reefs. Hydrothermal vents play a key role in replenishing depleted elements in the oceans, supporting unique chemosynthetic ecosystems and depositing ore-grade metal sulphides. Cold-water coral reefs are biodiversity hotspots on continental margins and preserve a unique high resolution geological record of intermediate water depth environmental and climate change. This was a discovery and exploration cruise to document previously undiscovered examples of these important bio-geological systems. Surveys were conducted using the ROV Holland 1. In order to determine the location of high-temperature hydrothermal venting on the seafloor and subsequently obtain water samples for plume studies, 14 CTD deployments were undertaken. Reef areas were mapped with high resolution multibeam. Two geological settings were sampled: ROV based sampling of the active vent site sulphides and surrounding mafic rocks, and dredge based sampling of two flat-topped seamounts. Specific objectives: Our programme has the following specific objectives: 1) Verify the status of reef growth and coral health in the Moira Mound extension field. 2) To study the off-reef and within-reef sedimentary environment to provide evidence for current flow and sediment transport affecting reef development. 3) To study cold-water coral reef biodiversity and sample fauna for ongoing biodiscovery research. 4) To locate the source of active high-temperature hydrothermal fluid venting on the Mid-Atlantic Ridge at 45°N and hence discover the first deep-water hydrothermal vent between the Azores and Iceland 5) To determine and map the geological setting, geochemistry and history of hydrothermal activity of the vent field at 45°N. 6) To characterise MAR macrofaunal communities at the study site by visual, morphological and molecular means, to identify new taxa and establish a sample reference collection. 7) To establish the phylogenetic, phylogeographic or population genetic affinities of the fauna at 45°N, revealing the influences of hydrography, geological history and isolation on vent biogeography. 8) To test whether the vent community at 45°N belongs to a new biogeographic province of chemosynthetic fauna; 9) To elucidate the consequences of isolation on the life-history biologies of taxa shared between 45°N and other known vents, through analysis of their gametogenic development; 10) Isotopic analyses of biomass dominant taxa to elucidate trophic structure; 11) To collect samples of potentially novel organisms for the marine biotechnology community/biodiscovery programme.

To explore the nascent area of sustainable venture capital, a review of related research was conducted and social entrepreneurs & investors interviewed to construct a questionnaire assessing the interests and intentions of current & future ecosystem participants. Analysis of 114 responses received via several sampling methods revealed statistically significant relationships between investing preferences and genders, generations, sophistication, and other variables, all the way down to the level of individual UN Sustainable Development Goals (SDGs).

the survey data has been deidentified for privacy reasons the survey sample may not be suitable for your application IBM SPSS Syntax code has been provided on GitHub to run on your own results the dataset for the separate database (Crunchbase) analysis is unable to be shared as it has a proprietary license

Vietnam BS: Number of Employees: FI: Joint Venture data was reported at 336,054.000 Person in 2016. This records an increase from the previous number of 303,000.000 Person for 2015. Vietnam BS: Number of Employees: FI: Joint Venture data is updated yearly, averaging 253,700.000 Person from Dec 2005 (Median) to 2016, with 11 observations. The data reached an all-time high of 336,054.000 Person in 2016 and a record low of 192,150.000 Person in 2005. Vietnam BS: Number of Employees: FI: Joint Venture data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.S002: The Situation of Enterprises Survey: VSIC 2007: Number of Employees.

About this dataset

Context

The dataset tabulates the Point Venture population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Point Venture. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 975 (62.82% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Point Venture population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Point Venture is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Point Venture is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Point Venture Population by Age. You can refer the same here

This database presents a sample of 175 Spanish technology-based ventures. It shows information on different aspects of the entrepreneur and the start-up firm, such as founding teams, entrepreneur’s resources, sources of knowledge, entrepreneur's training and experience, technology strategy, innovation, and firm’s performance (foreign market performance, total market performance, superior financial outcomes, and survival). The study is longitudinal and uses data from 2008 and 2014, which was collected from two sources of information and at two moments of time. To conduct the fieldwork and data collection we proceeded in two phases as follows.

First phase (in 2009). We built an online questionnaire to collect the data and the link to the questionnaire was sent by e-mail to NTBFs’ founder-managers. We first used the SABI database for identifying NTBFs using the following criteria: the venture has fewer than 250 employees; is not integrated into a corporate group; operates in a high-technology sector, following the OECD’s classification of industries based on technology; and finally, at the time of the fieldwork, the firms would be operational for up to 8 years, and so should be “new” according to Wang and Chen (2016) and Nuscheler et al. (2019), who consider the limit to qualify a firm as new as 10 years. This fieldwork was carried out from January to July 2009. Questions refer to resources available within the NTBF at or near the firm’s inception and the venture’s performance up to 2008. We obtained 175 valid responses.

Second phase (in 2016). We carried out a new process of information gathering in 2016. We collected data available in the SABI database for those NTBFs participating in the first phase of our study (the ones that had answered the survey in 2009). Specifically, we observed and took data concerning financial outcomes for 2008 and 2014 and survival information for 2014 (five years after the survey was conducted). Specifically, the most up-to-date data on firms available in 2016 refers to 2014.

Mountain Town Benchmarking Data Project survey results for Mountain Ventures Summit, CA conducted by FlashVote

Citizen respondents rank what's most important on a government Open Data site. Survey responses are broken down along several dimensions including, Region, Education Level, Gender and Household (HH) Income.

This record contains the underlying research data for the publication "Board representation in international joint ventures" and the full-text is available from: https://ink.library.smu.edu.sg/lkcsb_research/5038Relatively little attention has been paid to boards in international joint ventures (IJVs), and the composition of these boards in particular. We examine the determinants of foreign partners' representation on IJV boards in order to advance our knowledge of this facet of IJV governance. We argue that a foreign partner's representation on the IJV board is related to its equity contribution. However, we hypothesize that this relationship is moderated by IJV and host country characteristics that affect the importance of the internal and external roles IJV boards serve. These results provide insights into the conditions under which a partner might wish to secure greater board representation for its level of equity, or utilize less board representation than might be suggested by its equity level alone.

About this dataset

Context

The dataset tabulates the data for the Point Venture, TX population pyramid, which represents the Point Venture population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Point Venture, TX, is 16.4.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Point Venture, TX, is 33.3.
• Total dependency ratio for Point Venture, TX is 49.7.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Point Venture, TX is 3.0.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Point Venture population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Point Venture for the selected age group is shown in the following column.
• Population (Female): The female population in the Point Venture for the selected age group is shown in the following column.
• Total Population: The total population of the Point Venture for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Point Venture Population by Age. You can refer the same here

This dataset contains raw, unprocessed data files pertaining to the management tool group focused on 'Strategic Alliances' and 'Corporate Venture Capital' (CVC). The data originates from five distinct sources, each reflecting different facets of the tool's prominence and usage over time. Files preserve the original metrics and temporal granularity before any comparative normalization or harmonization. Data Sources & File Details: Google Trends File (Prefix: GT_): Metric: Relative Search Interest (RSI) Index (0-100 scale). Keywords Used: "strategic alliance" + "corporate venture capital" + "strategic alliance strategy" Time Period: January 2004 - January 2025 (Native Monthly Resolution). Scope: Global Web Search, broad categorization. Extraction Date: Data extracted January 2025. Notes: Index relative to peak interest within the period for these terms. Reflects public/professional search interest trends. Based on probabilistic sampling. Source URL: Google Trends Query Google Books Ngram Viewer File (Prefix: GB_): Metric: Annual Relative Frequency (% of total n-grams in the corpus). Keywords Used: Corporate Venture Capital + Strategic Alliance + Strategic Alliances Time Period: 1950 - 2022 (Annual Resolution). Corpus: English. Parameters: Case Insensitive OFF, Smoothing 0. Extraction Date: Data extracted January 2025. Notes: Reflects term usage frequency in Google's digitized book corpus. Subject to corpus limitations (English bias, coverage). Source URL: Ngram Viewer Query Crossref.org File (Prefix: CR_): Metric: Absolute count of publications per month matching keywords. Keywords Used: ("strategic alliance" OR "strategic alliances" OR "corporate venture capital") AND ("management" OR "strategy" OR "corporate" OR "development" OR "partnership" OR "approach" OR "implementation") Time Period: 1950 - 2025 (Queried for monthly counts based on publication date metadata). Search Fields: Title, Abstract. Extraction Date: Data extracted January 2025. Notes: Reflects volume of relevant academic publications indexed by Crossref. Deduplicated using DOIs; records without DOIs omitted. Source URL: Crossref Search Query Bain & Co. Survey - Usability File (Prefix: BU_): Metric: Original Percentage (%) of executives reporting tool usage. Tool Names/Years Included: Strategic Alliance (1993); Strategic Alliances (1996, 1999, 2000, 2002, 2004, 2006, 2008, 2010, 2012, 2014, 2017); Corporate Venture Capital (2022). Respondent Profile: CEOs, CFOs, COOs, other senior leaders; global, multi-sector. Source: Bain & Company Management Tools & Trends publications (Rigby D., Bilodeau B., Ronan C. et al., various years: 1994, 2001, 2003, 2005, 2007, 2009, 2011, 2013, 2015, 2017, 2023). Data Compilation Period: July 2024 - January 2025. Notes: Data points correspond to specific survey years. Sample sizes: 1993/500; 1996/784; 1999/475; 2000/214; 2002/708; 2004/960; 2006/1221; 2008/1430; 2010/1230; 2012/1208; 2014/1067; 2017/1268; 2022/1068. Bain & Co. Survey - Satisfaction File (Prefix: BS_): Metric: Original Average Satisfaction Score (Scale 0-5). Tool Names/Years Included: Strategic Alliance (1993); Strategic Alliances (1996, 1999, 2000, 2002, 2004, 2006, 2008, 2010, 2012, 2014, 2017); Corporate Venture Capital (2022). Respondent Profile: CEOs, CFOs, COOs, other senior leaders; global, multi-sector. Source: Bain & Company Management Tools & Trends publications (Rigby D., Bilodeau B., Ronan C. et al., various years: 1994, 2001, 2003, 2005, 2007, 2009, 2011, 2013, 2015, 2017, 2023). Data Compilation Period: July 2024 - January 2025. Notes: Data points correspond to specific survey years. Sample sizes: 1993/500; 1996/784; 1999/475; 2000/214; 2002/708; 2004/960; 2006/1221; 2008/1430; 2010/1230; 2012/1208; 2014/1067; 2017/1268; 2022/1068. Reflects subjective executive perception of utility. File Naming Convention: Files generally follow the pattern: PREFIX_Tool.csv, where the PREFIX indicates the data source: GT_: Google Trends GB_: Google Books Ngram CR_: Crossref.org (Count Data for this Raw Dataset) BU_: Bain & Company Survey (Usability) BS_: Bain & Company Survey (Satisfaction) The essential identification comes from the PREFIX and the Tool Name segment. This dataset resides within the 'Management Tool Source Data (Raw Extracts)' Dataverse.

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Vietnam BS: Number of Enterprises: FI: Joint Venture data was reported at 1,702.000 Unit in 2015. This records an increase from the previous number of 1,663.000 Unit for 2014. Vietnam BS: Number of Enterprises: FI: Joint Venture data is updated yearly, averaging 1,259.000 Unit from Dec 2005 (Median) to 2015, with 11 observations. The data reached an all-time high of 1,702.000 Unit in 2015 and a record low of 845.000 Unit in 2005. Vietnam BS: Number of Enterprises: FI: Joint Venture data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.S001: The Situation of Enterprises Survey: VSIC 2007: Number of Enterprises.

Vietnam BS: Capital Resources: FI: Joint Venture data was reported at 870,300.000 VND bn in 2016. This records an increase from the previous number of 794,000.000 VND bn for 2015. Vietnam BS: Capital Resources: FI: Joint Venture data is updated yearly, averaging 637,200.000 VND bn from Dec 2005 (Median) to 2016, with 11 observations. The data reached an all-time high of 873,400.000 VND bn in 2014 and a record low of 221,218.000 VND bn in 2005. Vietnam BS: Capital Resources: FI: Joint Venture data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.S003: The Situation of Enterprises Survey: VSIC 2007: Capital Resources.

This dataset provides processed and normalized/standardized indices for the management tool group focused on 'Strategic Alliances' and 'Corporate Venture Capital' (CVC). Derived from five distinct raw data sources, these indices are specifically designed for comparative longitudinal analysis, enabling the examination of trends and relationships across different empirical domains (web search, literature, academic publishing, and executive adoption). The data presented here represent transformed versions of the original source data, aimed at achieving metric comparability. Users requiring the unprocessed source data should consult the corresponding Strategic Alliances/CVC dataset in the Management Tool Source Data (Raw Extracts) Dataverse. Data Files and Processing Methodologies: Google Trends File (Prefix: GT_): Normalized Relative Search Interest (RSI) Input Data: Native monthly RSI values from Google Trends (Jan 2004 - Jan 2025) for the query "strategic alliance" + "corporate venture capital" + "strategic alliance strategy". Processing: None. Utilizes the original base-100 normalized Google Trends index. Output Metric: Monthly Normalized RSI (Base 100). Frequency: Monthly. Google Books Ngram Viewer File (Prefix: GB_): Normalized Relative Frequency Input Data: Annual relative frequency values from Google Books Ngram Viewer (1950-2022, English corpus, no smoothing) for the query Corporate Venture Capital + Strategic Alliance + Strategic Alliances. Processing: Annual relative frequency series normalized (peak year = 100). Output Metric: Annual Normalized Relative Frequency Index (Base 100). Frequency: Annual. Crossref.org File (Prefix: CR_): Normalized Relative Publication Share Index Input Data: Absolute monthly publication counts matching Strategic Alliance/CVC-related keywords [("strategic alliance" OR ...) AND (...) - see raw data for full query] in titles/abstracts (1950-2025), alongside total monthly Crossref publications. Deduplicated via DOIs. Processing: Monthly relative share calculated (Alliance/CVC Count / Total Count). Monthly relative share series normalized (peak month's share = 100). Output Metric: Monthly Normalized Relative Publication Share Index (Base 100). Frequency: Monthly. Bain & Co. Survey - Usability File (Prefix: BU_): Normalized Usability Index Input Data: Original usability percentages (%) from Bain surveys for specific years: Strategic Alliance (1993); Strategic Alliances (1996-2017); Corporate Venture Capital (2022). Processing: Semantic Grouping: Data points across "Strategic Alliance", "Strategic Alliances", and "Corporate Venture Capital" were treated as a single conceptual series representing this domain. Normalization: Combined series normalized relative to its historical peak (Max % = 100). Output Metric: Biennial Estimated Normalized Usability Index (Base 100 relative to historical peak). Frequency: Biennial (Approx.). Bain & Co. Survey - Satisfaction File (Prefix: BS_): Standardized Satisfaction Index Input Data: Original average satisfaction scores (1-5 scale) from Bain surveys for specific years (same names/years as Usability). Processing: Semantic Grouping: Data points treated as a single conceptual series. Standardization (Z-scores): Using Z = (X - 3.0) / 0.891609. Index Scale Transformation: Index = 50 + (Z * 22). Output Metric: Biennial Standardized Satisfaction Index (Center=50, Range?[1,100]). Frequency: Biennial (Approx.). File Naming Convention: Files generally follow the pattern: PREFIX_Tool_Processed.csv or similar, where the PREFIX indicates the data source (GT_, GB_, CR_, BU_, BS_). Consult the parent Dataverse description (Management Tool Comparative Indices) for general context and the methodological disclaimer. For original extraction details (specific keywords, URLs, etc.), refer to the corresponding Strategic Alliances/CVC dataset in the Raw Extracts Dataverse. Comprehensive project documentation provides full details on all processing steps.

Vietnam BS: Net Turnover: Business: FI: Joint Venture data was reported at 649,000.000 VND bn in 2015. This records a decrease from the previous number of 654,500.000 VND bn for 2014. Vietnam BS: Net Turnover: Business: FI: Joint Venture data is updated yearly, averaging 497,050.000 VND bn from Dec 2005 (Median) to 2015, with 10 observations. The data reached an all-time high of 654,500.000 VND bn in 2014 and a record low of 231,175.000 VND bn in 2005. Vietnam BS: Net Turnover: Business: FI: Joint Venture data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.S005: The Situation of Enterprises Survey: VSIC 2007: Net Turnover: Business.

Gravity data measures small changes in gravity due to changes in the density of rocks beneath the Earth's surface. The data collected are processed via standard methods to ensure the response recorded is that due only to the rocks in the ground. The results produce datasets that can be interpreted to reveal the geological structure of the sub-surface. The processed data is checked for quality by GA geophysicists to ensure that the final data released by GA are fit-for-purpose. This Cobar Data Joint Venture Infill (P199625) contains a total of 713 point data values acquired at a spacing between 200 and 4000 metres. The data is located in NSW and were acquired in 1996, under project No. 199625 for New South Wales Department of Mineral Resources (NSWDMR).

Vietnam BS: Profit Before Tax: FI: Joint Venture data was reported at 74,514.426 VND bn in 2015. This records a decrease from the previous number of 98,545.000 VND bn for 2014. Vietnam BS: Profit Before Tax: FI: Joint Venture data is updated yearly, averaging 77,070.863 VND bn from Dec 2005 (Median) to 2015, with 10 observations. The data reached an all-time high of 98,545.000 VND bn in 2014 and a record low of 39,423.000 VND bn in 2011. Vietnam BS: Profit Before Tax: FI: Joint Venture data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.S006: The Situation of Enterprises Survey: VSIC 2007: Profit Before Tax.

Citizen respondents rank how they want to interact with and consume government data. Survey responses are broken down along several dimensions including, Region, Education Level, Gender and Household (HH) Income.

description: Summary of the Four Square Mile Survey in the Prairie Pothole Joint Venture from 1989-2006. Information presented in this report is a summary of the survey results for Montana, North Dakota, and South Dakota. Data summaries for breeding pair and recruitment estimates are included.; abstract: Summary of the Four Square Mile Survey in the Prairie Pothole Joint Venture from 1989-2006. Information presented in this report is a summary of the survey results for Montana, North Dakota, and South Dakota. Data summaries for breeding pair and recruitment estimates are included.