scholarly journals Method for Dissemination of Results from Sample Survey of Innovation Activities at Enterprises for Population

2017 ◽  
pp. 6-14
Author(s):  
I. A. Zhukovych ◽  
G. I. Tereshchenko
Keyword(s):  
General Population ◽  
Survey Data ◽  
International Comparisons ◽  
Sample Survey ◽  
Community Innovation Survey ◽  
Innovation Activities ◽  
Analogous Data ◽  
Statistical Survey ◽  
Dissemination Of Results ◽  
Methodological Guidelines

The procedure for application of survey results on general population, which is a key phase in the official statistical survey of innovation activities at enterprises, conducted on sample basis, is analyzed. The tool for conducting the survey in Ukraine is the questionnaire “Survey of Innovation Activities at Enterprises”, the analogue of the questionnaire used by the Community Innovation Survey. The survey is conducted once in two years by the methodological recommendations of the Community Innovation Survey. The sample survey of innovation activities at enterprises and application of its results for the general population involves computation of statistical weights as part of the indicators assessment. The following issues are reviewed: computation of basic weights of reporting units; editing of data obtained from the survey; correction of statistical weights to account for non-response and change of key parameters of enterprises. A central issue under discussion is quality control of the statistical weights system. Approaches to indicators assessment using the survey data are highlighted. Elaborated within the framework of the Strategy for Development of Official Statistics till 2017, this method is part of the methodological guidelines on the innovation statistics. Once used by the State Statistics Service of Ukraine, the method will enable for producing high quality statistical data on innovation activities at enterprises from the survey data, adapted to the standards of European statistics and fit for international comparisons, first and foremost with the analogous data of EU countries.

scholarly journals Innovation strategy choices in the urban economy

Urban Studies ◽  
2017 ◽  
Vol 55 (6) ◽  
pp. 1185-1202 ◽  
Author(s):  
Sverre J Herstad
Keyword(s):  
Survey Data ◽  
Urban Economy ◽  
Innovation Policy ◽  
Innovation Strategy ◽  
Community Innovation Survey ◽  
Estimation Strategy ◽  
Innovation Activities ◽  
Knowledge Dynamics ◽  
Innovation Strategies

This paper analyses how the innovation strategies of individual firms reflect the density, diversity and international connectivity of their urban locations. It makes three contributions. Theoretically, it argues that observed strategies reflect a series of inter-related choices, and that each may be influenced differently by the knowledge dynamics of firms’ locations. Empirically, it uses Norwegian Community Innovation Survey data to demonstrate how firms in the Capital are less inclined to engage in innovation activities, but also more likely to commit strongly once engaged, than are comparable firms located elsewhere. Methodologically, it illustrates how the results of sequential regressions on inter-related strategy choices differ from those obtained using a more conventional estimation strategy. Implications for innovation policy and research are drawn.

scholarly journals Strengthening the Innovation Resilience of Polish Manufacturing Firms in Unstable Environments

2021 ◽  
Author(s):  
Anna Wziątek-Kubiak ◽  
Marek Pęczkowski
Keyword(s):  
Public Support ◽  
Probit Model ◽  
Manufacturing Firms ◽  
Community Innovation Survey ◽  
Innovation Activities ◽  
Turbulent Times ◽  
Unstable Environment ◽  
Innovative Resources ◽  
Accuracy Of Prediction ◽  
Second Period

AbstractThis study examines factors that increase resilience in innovation of Polish manufacturing firms in an unstable environment. Organizational resilience in innovation is the ability to continuously perform innovation in a turbulent environment and increase knowledge accumulation. In 2008–2012, Poland did not have crisis itself. Short-term slowdown of the economy was accompanied by a breakdown of innovation activities, with a medium-term effect. Based on the Polish Community Innovation Survey panel data for two periods: the innovation crisis (2008–2010), and the innovation pessimism period (2010–2012), this study shows which innovative resources change the probability of innovation continuity in the second period. In our probit model, we explore 42 factors of innovations. We found that financing, R&D and marketing increased the probability of continuity of innovation, but the influence of financing was the strongest. Persistence in innovation in turbulent times hence requires a change in the structure of innovation resources used. Due to the fact that public support on innovation did not increase the likelihood of the continuity of the innovation, a policy change is required. Reliability of our estimation is confirmed by accuracy of prediction of firms, which was 78.2%.

Innovation in Slovenian tourism organisations

2015 ◽  
Vol 21 (1) ◽  
pp. 51-62
Author(s):  
Maja Uran Maravić ◽  
Dejan Križaj ◽  
Miha Lesjak
Keyword(s):  
Design Methodology ◽  
Mean Value ◽  
Sample Survey ◽  
Research Activity ◽  
Main Hypothesis ◽  
Innovation Activities ◽  
Innovation Climate ◽  
High Level ◽  
Innovation Practices ◽  
First Time

The purpose – Slovenian tourism organisations must constantly focus on developing variety innovations for organisations. In this paper, we present a study conducted on innovation practices in Slovenian tourism organisations. Design/methodology – In a survey conducted on Slovenia tourism organisations, we obtained data and identified their innovation performance and the innovation climate in their area of business. There are three main hypothesis tested. Findings – The research sample of 41 organisations found that most innovation in tourism organisations came through the introduction of new services (90%), followed by innovation through new organisational methods (73%), and found a high-level climate for innovation. Worse was its assessment of research activity within organisations and cooperation with external institutions (eg. universities and research institutes) and investment in innovation activities within their research and development. Results obtained from the research showed a mean value for the innovation climate-instrument of 3.83 indicating a high innovation climate for the Slovenian tourism companies included in the sample survey. Mostly, (publicly known as) more innovative active organisations responded to our survey. From such results, we find that tourism organisations included in the survey are aware of the importance of innovation, teaching organisations to communicate well and network with other organisations, are adaptable to change and engaged with their own ideas in support of the organisation's management. Originality of the research – The contribution of the research is that it has applied the generic instrument for measuring innovation climate on tourism and the first time climate is measured in Slovenia.

Restricted quasi-score estimating functions for sample survey data

2004 ◽  
Vol 41 (A) ◽  
pp. 119-130
Author(s):  
Y.-X. Lin ◽  
D. Steel ◽  
R. L Chambers
Keyword(s):  
Maximum Likelihood ◽  
Survey Data ◽  
Sample Survey ◽  
Likelihood Method ◽  
Sample Surveys ◽  
Estimating Functions ◽  
Limit Theory ◽  
Normal Probability ◽  
Probability Structure ◽  
Sample Survey Data

This paper applies the theory of the quasi-likelihood method to model-based inference for sample surveys. Currently, much of the theory related to sample surveys is based on the theory of maximum likelihood. The maximum likelihood approach is available only when the full probability structure of the survey data is known. However, this knowledge is rarely available in practice. Based on central limit theory, statisticians are often willing to accept the assumption that data have, say, a normal probability structure. However, such an assumption may not be reasonable in many situations in which sample surveys are used. We establish a framework for sample surveys which is less dependent on the exact underlying probability structure using the quasi-likelihood method.

scholarly journals Crowdsourcing LUCAS: Citizens Generating Reference Land Cover and Land Use Data with a Mobile App

2020 ◽  
Author(s):  
Juan Carlos Laso Bayas ◽  
Linda See ◽  
Hedwig Bartl ◽  
Tobias Sturn ◽  
Mathias Karner ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Survey Data ◽  
Target Location ◽  
Low Cost ◽  
Mobile App ◽  
Sample Survey ◽  
In Situ Data

There are many new land use and land cover (LULC) products emerging yet there is still a lack of in-situ data for training, validation, and change detection purposes. The LUCAS (Land Use Cover Area frame Sample) survey is one of the few authoritative in-situ field campaigns, which takes place every three years in European Union member countries. More recently, a study has considered whether citizen science and crowdsourcing could complement LUCAS survey data, e.g., through the FotoQuest Austria mobile app and crowdsourcing campaign. Although the data obtained from the campaign were promising when compared with authoritative LUCAS survey data, there were classes that were not well classified by the citizens, and the photographs submitted through the app were not always of sufficient quality. For this reason, in the latest FotoQuest Go Europe 2018 campaign, several improvements were made to the app to facilitate interaction with the citizens contributing and to improve their accuracy in LULC identification. In addition to extending the locations from Austria to Europe, a change detection component (comparing land cover in 2018 to the 2015 LUCAS photographs) was added, as well as an improved LC decision tree and a near real-time quality assurance system to provide feedback on the distance to the target location, the LULC classes chosen and the quality of the photographs. Another modification was the implementation of a monetary incentive scheme in which users received between 1 to 3 Euros for each successfully completed quest of sufficient quality. The purpose of this paper is to present these new features and to compare the results obtained by the citizens with authoritative LUCAS data from 2018 in terms of LULC and change in LC. We also compared the results between the FotoQuest campaigns in 2015 and 2018 and found a significant improvement in 2018, i.e., a much higher match of LC between FotoQuest Go Europe and LUCAS. Finally, we present the results from a user survey to discuss challenges encountered during the campaign and what further improvements could be made in the future, including better in-app navigation and offline maps, making FotoQuest a model for enabling the collection of large amounts of land cover data at a low cost.

Updating Existing Travel Simulation Models with Small-Sample Survey Data Using Parameter Scaling Methods

1997 ◽  
Vol 1607 (1) ◽  
pp. 55-61
Author(s):  
W. Thomas Walker ◽  
Scott H. Brady ◽  
Charles Taylor
Keyword(s):  
Survey Data ◽  
Primary Source ◽  
Simulation Models ◽  
Small Sample ◽  
Sample Survey ◽  
Secondary Source ◽  
Sample Surveys ◽  
Large Sample ◽  
Scaling Methods ◽  
Home Interview

The travel simulation models for many metropolitan areas were originally developed and calibrated with older large-sample travel surveys that can no longer be undertaken given today’s funding constraints. Small-sample travel surveys have been collected as part of model update activities required by the Intermodal Surface Transportation Efficiency Act and the Clean Air Act Amendments. Although providing useful information, these surveys are inadequate for calibrating elaborate simulation models by traditional techniques. Parameter transfer scaling based on small-sample surveys and other secondary source data can be a cost-effective alternative to large-sample surveys when existing models are being updated, particularly when the models tend to be robust and the required changes are relatively small. The use of parameter scaling methods to update the Delaware Valley Planning Commission’s existing travel simulation models is demonstrated. All available sources of data are incorporated into the update process including current survey data, census work trips from the Census Transportation Planning Package (CTPP), transit ridership checks, highway screenline counts, and Highway Performance Monitoring System travel estimates. A synopsis of experience with parameter scaling techniques including the model changes and resulting accuracy is provided. Overall, small-sample-based parameter scaling techniques were judged to be effective. The census CTPP data were evaluated versus the home interview and were found to be useful in the model recalibration effort as a source of small-area employment data by place of work and as a supplement to home interview data for model validation. However, a home interview survey is required as the primary source of travel data for both work and nonwork trips.

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