scholarly journals Comparing and Identifying Influential Factors of Technological Innovation Efficiency in Manufacturing and Service Industries Using DEA: A Study of SMEs in South Korea

2021 ◽  
Vol 13 (23) ◽  
pp. 12945
Author(s):  
Chae Hyun Im ◽  
Keun Tae Cho
Keyword(s):  
South Korea ◽  
Technological Innovation ◽  
Manufacturing Industry ◽  
Service Industry ◽  
Influential Factors ◽  
Service Industries ◽  
Innovation Activity ◽  
Tobit Regression ◽  
Factors Affecting ◽  
Tobit Regression Analysis

Although technological innovation is critical for growth and future survival, small and medium scale enterprises (SMEs) are at a disadvantage compared to larger organizations given the resources available. It is important to examine the possible methods for making research and development more efficient. This study analyzes the technological innovation efficiency of SMEs in the manufacturing and service industries in South Korea and determines the factors affecting efficiency. The models of data envelopment analysis and Tobit regression analysis were used. According to the analysis results, the technical and pure technical efficiencies were higher in the service industry than in the manufacturing industry. The factors affecting efficiency were also different between the two industries. This study is significant because it evaluates the innovation activity efficiency of small and medium manufacturing and service companies in South Korea and provides specific criteria and a rationale to improve the efficiency.

scholarly journals Research on Influences of Employment in Manufacturing Industry on that in the Service Industry Based on Bayes Model

2018 ◽  
Vol 2 (3) ◽  
pp. 77
Author(s):  
Yue Sun
Keyword(s):  
Manufacturing Industry ◽  
Service Industry ◽  
Service Industries ◽  
Nonlinear Functions ◽  
Bayes Model ◽  
Cardinal Spline ◽  
Error Terms ◽  
Partial Linear ◽  
Stable Growth ◽  
The Impact

Using the data of 285 prefectural and the above-level cities from 2004 to 2016, this thesis reveals the impact of employment in China's urban manufacturing industry on the employment of service industries with the Bayesian model. Under the Bayesian framework, partial linear semi-parametric model is proposed.  The nonlinear functions are fitted by using truncation base cardinal spline and considering the random error terms of mixed normal fitting models. The results show that: employment in the urban manufacturing industry in China has significant influence on the employment in the service industry. When the number of employees in the manufacturing industry changes from 0 to 650,000, the manufacturing industry has less influence. When the number of the employees in the manufacturing industry changes from 650,000 to 900,000, the employees of the service industry will dramatically increase. When the number of the employees in the manufacturing industry is more than 900,000, the employees in the service industry will be prone to stable growth.

The prioritization of technologies and public R&D roles between the manufacturing and service industries in the fourth industrial revolution

foresight ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 680-694 ◽  
Author(s):  
Jinwon Kang ◽  
Jong-Seok Kim ◽  
Seonmi Seol
Keyword(s):  
Artificial Intelligence ◽  
Manufacturing Industry ◽  
Market Failure ◽  
Industrial Revolution ◽  
Service Industry ◽  
Service Industries ◽  
Delphi Survey ◽  
Smart Factory ◽  
Content Type ◽  
Fourth Industrial Revolution

Purpose The purpose of this study is to reveal the similarities and differences between the manufacturing and service industries in their prioritization of technologies and public research and development (R&D) roles, along with the complementation of properties of technology and public R&D role in the context of Fourth Industrial Revolution. Design/methodology/approach Two rounds of Delphi surveys were designed to meet the purpose of this study, which used rigorous triangulation techniques. The Delphi method was combined with the brainstorming method in the first-round Delphi survey, while the second-round Delphi survey focused on experts’ judgments. Finally, language network analysis was performed on the properties of technology and public R&D roles to complement the data analyses regarding prioritization. Findings This study identifies different prioritizations of five similar key technologies in each industry, so that it can note different technological impacts to the two industries in the Fourth Industrial Revolution. Smart factory technology is the first priority in the manufacturing industry, whereas artificial intelligence is the first priority in the service industry. The properties of the three common technologies: artificial intelligence, big data and Internet of things in both industries are summarized in hyper-intelligence on hyper-connectivity. Moreover, it is found that different technological priorities in the service and manufacturing industries require different approaches to public R&D roles, while public R&D roles cover market failure, system failure and government failure. The highest priority public R&D role for the service industry is the emphasis of non-R&D roles. Public R&D role to solve dy-functions, focus basic technologies and support challenging areas of R&D is prioritized at the highest for the manufacturing industry. Originality/value This study of the different prioritizations of technologies in the manufacturing and service industries offers practical lessons for executive officers, managers and policy-makers. They, by noting the different technological impacts in the manufacturing and service industries, can prepare for current actions and establish the priority of technology for R&D influencing the future paths of their industries in the context of the Fourth Industrial Revolution. While managers in the service industry should pay greater attention to the technological content of hyper-intelligence and hyper-connectivity, managers in the manufacturing industry should consider smart factory and robot technology.

scholarly journals Analysis of Driving Factors of Photovoltaic Power Generation Efficiency: A Case Study in China

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 355 ◽  
Author(s):  
Tao Yi ◽  
Ling Tong ◽  
Mohan Qiu ◽  
Jinpeng Liu
Keyword(s):  
Power Generation ◽  
Economic Development ◽  
Tobit Regression ◽  
Generation Efficiency ◽  
Factors Affecting ◽  
Energy Demands ◽  
Photovoltaic Power ◽  
Important Research Topic ◽  
Tobit Regression Analysis ◽  
Efficient Power

With the increasing consumption of fossil energy and changes in the ecological environment, meeting the energy demands required for industrial and economic development with clean and efficient power generation is a major challenge of our society. Solar energy is considered to be one of the most renewable and sustainable energy sources, and photovoltaic power generation has become an important research topic. This study combines data envelopment analysis (DEA) with Tobit regression analysis to assess the efficiency of photovoltaic power generation in China and analyze factors affecting efficiency to improve the efficiency of photovoltaic power generation. The results show that there are obvious regional differences in photovoltaic power generation efficiency in China. The phenomenon of focusing on economic development at the expense of the use of solar power generation still exists. The establishment of photovoltaic demonstration projects, the implementation of differential electricity price policies, and the promotion of photovoltaic precision poverty alleviation can alleviate economic pressure and effectively improve the efficiency of photovoltaic power generation.

scholarly journals Does Reduction of Material and Energy Consumption Affect to Innovation Efficiency? The Case of Manufacturing Industry in South Korea

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1178 ◽  
Author(s):  
Jaeho Shin ◽  
Changhee Kim ◽  
Hongsuk Yang
Keyword(s):  
Energy Consumption ◽  
Manufacturing Industry ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Major Objective ◽  
Manufacturing Enterprises ◽  
Industry Type ◽  
Show Difference ◽  
Tobit Regression Analysis ◽  
The Relationship

“Reduction of material and energy consumption” (RMEC) exists as a major objective of innovation and it is proved to affect positively to innovation performance from previous literature. Though innovation should be measured in efficiency rather than performance itself, however, the relationship between material and energy reduction on innovation efficiency is still unanswered. In this paper, we analyzed the effect of RMEC on innovation efficiency considering both innovation inputs and outputs. We utilized data of 388 manufacturing enterprises in Korea, and performed data envelopment analysis (DEA) and tobit regression analysis. According to the result, firms show difference by industry type in terms of innovation efficiency and RMEC. Moreover, the effect of RMEC on innovation efficiency turned out to be negative. The result indicates a possibility that input used for innovation might overweigh the output yielded when firms pursue innovation for the RMEC.

scholarly journals Impact of Innovation Culture, Organization Size and Technological Capability on the Performance of SMEs: The Case of China

2020 ◽  
Vol 12 (4) ◽  
pp. 1355
Author(s):  
GuoXiang Tang ◽  
Kwangtae Park ◽  
Anurag Agarwal ◽  
Feng Liu
Keyword(s):  
Firm Performance ◽  
Manufacturing Industry ◽  
Service Industry ◽  
Technological Capability ◽  
Service Industries ◽  
Organization Size ◽  
Innovation Culture ◽  
Rapid Economic Growth ◽  
Service Sectors ◽  
Apply Regression Analysis

Small and medium-sized enterprises (SMEs) in both the manufacturing and service sectors have been viewed as an important driving force behind the rapid economic growth in China. There are multiple factors that drive the success of SMEs. In this paper, we study the effect of innovation culture, technological capability, and organization size on the performance of SMEs in China. We hypothesize that firm performance is positively affected by each of these factors. We use data from 1124 SMEs in China and apply regression analysis to test our hypotheses. We find that technological capability and organization size have a statistically positive effect on the performance of SMEs. Because manufacturing and service industries have distinct characteristics, we also compare the effects of these factors on firm performance within these industries. We find that technological capability is positively and statistically significantly related to firm performance in the manufacturing industry but not in the service industry, while innovation culture is positively and statistically significantly related to firm performance in the service industry but not in the manufacturing industry.

scholarly journals Technical Efficiency of Cabbage Farming (Brassica oleracea) With Stochastic Frontier Analysis (SFA) Approach in Purwodadi - Pasuruan

HABITAT ◽  
2021 ◽  
Vol 32 (1) ◽  
pp. 26-36
Author(s):  
Suaibatul Miskiyah ◽  
Syafrial Syafrial ◽  
Sujarwo Sujarwo
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
High Efficiency ◽  
Sampling Technique ◽  
Influential Factors ◽  
Organic Fertilizers ◽  
Tobit Regression ◽  
Npk Fertilizers ◽  
Factors Affecting ◽  
Frontier Analysis

This study was aimed to analyze the factors affecting the cabbage production, the level of technical efficiency of cabbage farming, the factors affecting technical inefficiency, and the profits of cabbage farming. The location was determined purposively on the basis that it is the center of vegetable cultivation. The respondents were 67 farmers chosen using the Yamane formula sampling technique. This research used frontier software 4.1 data analysis method with Maximum Likelihood Estimation (MLE) approach and Tobit regression. The results showed that land, labor, seeds, organic fertilizers, urea fertilizers, za fertilizers and npk fertilizers were real influential factors. Meanwhile, pesticides were insignificantly influenced. The mean technical efficiency in the research site was 0.903 for the distribution of technical efficiency, so that the cabbage production was rated as high efficiency. Age, education and credit access dummy contributed a major impact on technological inefficiency. The income from cabbage farming per planting season per hectare was Rp35,524,300 from cash costs and Rp31,051,800 from total costs.

scholarly journals Efisiensi teknis usahatani kentang pada luas lahan yang berbeda di kabupaten Pasuruan

Agromix ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 102-110
Author(s):  
Desy Cahyaning Utami ◽  
Wenny Mamilianti
Keyword(s):  
Technical Efficiency ◽  
Agricultural Land ◽  
Potato Production ◽  
Vegetable Crops ◽  
Tobit Regression ◽  
Land Area ◽  
Factors Affecting ◽  
The Family ◽  
Tobit Regression Analysis ◽  
Douglas Production Function

Potatoes are upland vegetable crops, which is the superior plant of Tosari District, Pasuruan Regency. Tosari potatoes are the largest contributor to production in East Java. The farmer profession is the main profession in this area, inherited from the family. The land area owned is inherited from the family. The agricultural land area varies, but still found farmers with a land area of more than one hectare. In this study, respondents were divided into two groups, namely farmers with a land area of ≥ 1 hectare called cluster I and respondent farmers with a land area of ≤ 0.5 hectares called cluster II. The purpose of this study was to analyze the effect of production inputs on potato production, to analyze the level of technical efficiency of potato farmers with different land areas, to analyze the factors affecting the level of technical efficiency. The study was conducted by interviewing 49 respondent farmers in Cluster I and 70 respondent farmers in Cluster II. This study uses the Cobb Douglas production function, the analytical methods used are the Stochastic Analysis Frontier (SFA) and the Tobit regression analysis. The results showed that the production inputs that had a significant effect on production in cluster I were seeds, fertilizers, and manure, while in cluster II were fertilizers and pesticides. The level of technical efficiency of farmers who have a land area of ≥ 1 hectare is greater than farmers with a land area of ≤0.5 hectares. The land area has a significant effect on the level of technical efficiency.

scholarly journals The Influence of Industrial Structure Upgrade on Coupling and Coordinated Development—Empirical Analysis From Chinese Pharmaceutical Manufacturing and Pharmaceutical Service Industries

2021 ◽  
Vol 9 ◽  
Author(s):  
Meng Hu ◽  
Chunhai Tao ◽  
Hao Zhou
Keyword(s):  
Regression Model ◽  
Manufacturing Industry ◽  
Medical Service ◽  
Industrial Structure ◽  
Service Industry ◽  
Service Industries ◽  
Pharmaceutical Manufacturing ◽  
Coordinated Development ◽  
The Impact ◽  
Coordination Degree

The degree of coupling and coordination between the pharmaceutical manufacturing industry and the medical service industry crucially requires improvement by promoting the development of the pharmaceutical manufacturing industry through industrial structure upgrading to narrow the gap between them. First, this article uses the coupling coordination degree model to measure the coupling coordination degree of the Chinese pharmaceutical manufacturing industry and medical service industry; then, it theoretically analyzes the mechanism through which upgrading the pharmaceutical manufacturing industry's industrial structure can improve the coupling coordination degree. Finally, we empirically test the impact of upgrading the pharmaceutical manufacturing industry's industrial structure on the coupling and coordination degree between it and the medical service industry. The main conclusions are as follows: (1). The quantile regression model shows that having an advanced pharmaceutical manufacturing industry positively affects its coupling and coordination with the medical service industry; (2). A threshold regression model is tested, and it is found that only when the pharmaceutical manufacturing industry reaches an advanced level can it significantly promote joint and coordinated development with the medical service industry; (3). Rationalizing the pharmaceutical manufacturing industry structure will inhibit a high level of coordination between it and the medical service industry and their coordinated development.

Benchmarking aircraft maintenance performances using data envelopment analysis

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Thomas O'Neal ◽  
Hokey Min ◽  
Daniel Cherobini ◽  
Seong-Jong Joo
Keyword(s):  
Data Envelopment Analysis ◽  
Ad Hoc ◽  
Aircraft Maintenance ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Content Type ◽  
Factors Affecting ◽  
Comparative Efficiency ◽  
Tobit Regression Analysis ◽  
Maintenance Performance

PurposeThe authors employed the three different versions (Charnes–Cooper–Rhodes, Banker–Charnes–Cooper and slack-based measure of efficiency) of data envelopment analysis (DEA) to evaluate the comparative efficiency/inefficiency of aircraft maintenance performance during the previous 41 months in United States Air Force (USAF). As a complimentary tool, the authors also adopted Tobit regression analysis to identify factors affecting efficiencies and inefficiencies.Design/methodology/approachThis paper aims to measure the relative efficiency of maintenance performances for a type of USAF aircraft in an effort to enhance aviation safety and combat readiness.FindingsThrough this study, the authors have two noteworthy findings. These are (1) an increased number of “cannibalization” (extracting necessary parts from the existing aircraft) practices tended to reduce maintenance efficiency; (2) The number of mission-capable aircraft turned out to be the most important factor for maintenance performance efficiency.Originality/valueThis paper is one of the first studies on aircraft maintenance that considered popular but neglected cannibalization practices as a new variable for assessing the maintenance efficiency. In addition, this paper is one of the few studies that performed a post-ad hoc analysis as a follow-up to DEA analysis.

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