scholarly journals Are small and medium-size food industry firms profitable? Explaining differences in their performance: The case of the Valencia Region

2021 ◽  
pp. 1-24
Author(s):  
Silvia Andrés González-Moralejo ◽  
Mildrey García Cortés ◽  
Juan Francisco López Miquel
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
Panel Data ◽  
Food Industry ◽  
Common Factors ◽  
Medium Size ◽  
Small Enterprises ◽  
Economic Cycle ◽  
Valencian Region ◽  
Financial Profitability

The main aim of this study was to determine the factors that influenced profitability of companies involved in the Valencia food industry between 2006 and 2015. For this, macroeconomic, sector and company variables were the key elements used in the statistical analysis, together with their dependenceon the economic cycle in indicating the present state of the sector in the Valencian Region. The panel data was obtained from the sabi data base and combined with transverse data and time series. Economic and financial profitability are both influenced by certain common factors, especially the sales margin. The higher the margin the higher the profit, although this relationship also depends on where the business company is located. Rotation of assets also contributes to raising profits in times of economic expansion. The Economic Crisis saw profits fall in 2009 and 2012, two of its worst years. Finally, differences were also found between large and small enterprises.

Assessment of small businesses activities in Ukraine

2019 ◽  
pp. 40-47
Author(s):  
Igor Ponomarenko ◽  
Kateryna Volovnenko
Keyword(s):  
Comparative Analysis ◽  
Statistical Analysis ◽  
Small Business ◽  
Small Businesses ◽  
Government Agencies ◽  
Small Enterprises ◽  
The Subject ◽  
Business Entities ◽  
The Impact ◽  
Micro Enterprises

The subject of the research is a set of approaches to the statistical analysis ofthe activities of small business entities in Ukraine, including micro-enterprises. The purpose of writing this article is to study of the features of functioningof small business entities in Ukraine. Methodology. The research methodology isto use a system-structural and comparative analysis (to study the change in thenumber of small enterprises by major components); monographic (when studyingmethods of statistical analysis of small businesses); economic analysis (when assessing the impact of small business entities on socio-economic phenomena andprocesses in Ukraine). The scientific novelty consists to determine the features ofthe functioning of small businesses in Ukraine in modern conditions. The influenceof the activities of the main socio-economic and political indicators on the activities of small enterprises in recent periods of time has been identified. It has beenestablished that there is flexibility in the development of strategies by small businesses in conditions of significant competition, which makes it possible to quicklyrespond to changing situations in specific markets. Conclusions. The use of acomprehensive statistical analysis of small businesses functioning in Ukraine willallow government agencies to develop a set of measures to optimize the activitiesof these enterprises, which ultimately will positively affect the strengthening oftheir competitiveness and will contribute to the growth of the national economicsystem.

Analysis of Entrepreneurship Education Model of Technology-Driven Agri-Food Industry Applying Line-by-line Coding Method of Grounded Theory

2019 ◽  
Vol 118 (8) ◽  
pp. 266-274
Author(s):  
Byung- MoonSeol ◽  
Young-Lag KIM
Keyword(s):  
Grounded Theory ◽  
Comparative Analysis ◽  
Statistical Analysis ◽  
Food Industry ◽  
Entrepreneurship Education ◽  
Theory Approach ◽  
Coding Method ◽  
Open Coding ◽  
Education Model ◽  
Grounded Theory Approach

Background/Objectives: This paper investigated and analyzed the phenomena in implementing the curriculum and characteristics of an entrepreneurship education model existing technology-driven agri-food industry. Methods/Statistical analysis: The line-by-line coding method of grounded theory approach by Strauss & Corbin was applied for this study and the collected data was analyzed with the NVIVO 12 program from QSR which is a tool for analyzing quality comparative analysis for better efficiency in open coding.

scholarly journals Proposal for Tower Crane Productivity Indicators Based on Data Analysis in the Era of Construction 4.0

Buildings ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 21
Author(s):  
Thomas Danel ◽  
Zoubeir Lafhaj ◽  
Anand Puppala ◽  
Sophie Lienard ◽  
Philippe Richard
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Statistical Analysis ◽  
Data Collection ◽  
Structural Phase ◽  
Sampling Technique ◽  
Construction Site ◽  
Data Logger ◽  
Tower Crane ◽  
Productivity Indicators

This article proposes a methodology to measure the productivity of a construction site through the analysis of tower crane data. These data were obtained from a data logger that records a time series of spatial and load data from the lifting machine during the structural phase of a construction project. The first step was data collection, followed by preparation, which consisted of formatting and cleaning the dataset. Then, a visualization step identified which data was the most meaningful for the practitioners. From that, the activity of the tower crane was measured by extracting effective lifting operations using the load signal essentially. Having used such a sampling technique allows statistical analysis on the duration, load, and curvilinear distance of every extracted lifting operation. The build statistical distribution and indicators were finally used to compare construction site productivity.

Detecting common breaks in the means of high dimensional cross-dependent panels

2021 ◽  
Author(s):  
Lajos Horváth ◽  
Zhenya Liu ◽  
Gregory Rice ◽  
Yuqian Zhao
Keyword(s):  
Panel Data ◽  
Common Factors ◽  
Real Data ◽  
Change Points ◽  
High Dimensional ◽  
Asymptotic Results ◽  
Cross Sectional ◽  
Data Set ◽  
Monte Carlo Simulation Study ◽  
Cross Sectional Dependence

Abstract The problem of detecting change points in the mean of high dimensional panel data with potentially strong cross–sectional dependence is considered. Under the assumption that the cross–sectional dependence is captured by an unknown number of common factors, a new CUSUM type statistic is proposed. We derive its asymptotic properties under three scenarios depending on to what extent the common factors are asymptotically dominant. With panel data consisting of N cross sectional time series of length T, the asymptotic results hold under the mild assumption that min {N, T} → ∞, with an otherwise arbitrary relationship between N and T, allowing the results to apply to most panel data examples. Bootstrap procedures are proposed to approximate the sampling distribution of the test statistics. A Monte Carlo simulation study showed that our test outperforms several other existing tests in finite samples in a number of cases, particularly when N is much larger than T. The practical application of the proposed results are demonstrated with real data applications to detecting and estimating change points in the high dimensional FRED-MD macroeconomic data set.

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