Assessing the technological innovation efficiency of China's high-tech industries with a two-stage network DEA approach

As significant strategic players in China's economy, high-tech industries need to evaluate and analyze the technological innovation activities from a system point of view to understand and improve their technological innovation efficiency and, thereby, promote their development. Different high-tech industries have different characteristics and thus benefit from different industrial development policies. However, few studies to date have discussed this issue from a systematic perspective. In this study, technological innovation activities are divided into a research and development (R&D) stage and a commercialization stage. A high-tech industrial evaluation framework of technological innovation efficiency based on two-stage network data envelopment analysis (DEA) is constructed with shared inputs, additional intermediate inputs, and free intermediate outputs. Our empirical results indicate that the overall efficiency of most industries is relatively low and the differences between the five high-tech industries (i.e., sub-sectors) we examined are large. The Spearman correlation shows that overall efficiency and R&D efficiency are more correlated than overall efficiency and commercialization efficiency. Additionally, R&D has better average efficiency. The sub-sector with the highest average efficiency is computers and office equipment, and the one with the lowest average efficiency is medicines. These findings indicate the inadequacy but potential for breakthroughs in the evolution of high-tech industries in China. The analysis proves that it is necessary to create different industrial policies to encourage effective progress in certain high-tech industries, and some guidelines for doing so are provided.     

Measurement of technical efficiency in farrow-to-finish swine production using multi-activity network data envelopment analysis: evidence from Taiwan

This study aims to propose a dynamic multi-activity network data development analysis (DMNDEA) model to measure the technical efficiency of farrow-to-finish swine production in Taiwan. Production phases are explicitly divided into two activities; namely, the breed-to-farrow phase and the wean-to-finish phase. By using this model, the problem of shared inputs and dynamic intermediates among activities that characterize pig production are taken into account in an integrated framework, simultaneously with the consideration of non-zero slack, allowing us to examine aspects of production in a more comprehensive and factual manner. For the empirical results based on sample data from 2006 to 2007, it is shown that the overall technical inefficiencies obtained from DMNDEA are not obviously different from those obtained using a traditional one-stage model. However, the DMNDEA results explicitly show us that the sources of inefficiency for each farm are different. Furthermore, second-stage bootstrapping regression results reveal that the determinants of efficiency for each production phase are not the same, indicating the need to identify the influential factors for each production phase separately.     

Efficiency aggregation with enhanced Russell measures in data envelopment analysis

In aggregation for data envelopment analysis (DEA), a jointly determined aggregate measure of output and input efficiency is desired that is consistent with the individual decision making unit measures. An impasse has been reached in the current state of the literature, however, where only separate measures of input and output efficiency have resulted from attempts to aggregate technical efficiency with the radial measure models commonly employed in DEA. The latter measures are “incomplete” in that they omit the non-zero input and output slacks, and thus fail to account for all inefficiencies that the model can identify. The Russell measure eliminates the latter deficiency but is difficult to solve in standard formulations. A new approach has become available, however, which utilizes a ratio measure in place of the standard formulations. Referred to as an enhanced Russell graph measure (ERM), the resulting model is in the form of a fractional program. Hence, it can be transformed into an ordinary linear programming structure that can generate an optimal solution for the corresponding ERM model. As shown in this paper, an aggregate ERM can then be formed with all the properties considered to be desirable in an aggregate measure—including jointly determined input and output efficiency measures that represent separate estimates of input and output efficiency. Much of this paper is concerned with technical efficiency in both individual and system-wide efficiency measures. Weighting systems are introduced that extend to efficiency-based measures of cost, revenue, and profit, as well as derivatives such as rates of return over cost. The penultimate section shows how the solution to one model also generates optimal solutions to models with other objectives that include rates of return over cost and total profit. This is accomplished in the form of efficiency-adjusted versions of these commonly used measures of performance.     

Regional technical efficiency of Chinese Iron and steel industry based on bootstrap network data envelopment analysis

This paper analyses the regional technical efficiency of Chinese iron and steel industry from 1996 to 2010 by a network DEA procedure, and provides the smoothed bootstrap network DEA strategy for the sensitivity analysis of the efficiency measure to sampling variation of the estimated frontier. Furthermore, the evolution and convergence characteristics of regional technical efficiency are examined by a dynamic regression model based on different regional divisions of China. The empirical results show that there exist significant geographical differences in the technical efficiency of Chinese iron and steel industry. On the one hand, the technical efficiency of the eastern area, the central area and the western area is unbalanced, with a lower efficiency in the west and a higher one in the east. On the other hand, technical efficiency of Central Bohai, Yangtze River Delta and Pearl River Delta economic zones is higher than that of the other economic zones. In addition, the technical efficiency has a significant improvement during the period of the Eleventh Five-Year Plan. Following the convergence notation in economic growth theory, this paper also gives some convergence evidence of the technical efficiency towards the efficient frontier due to the catching-up effect. Finally, this paper explores the determinants of the technical efficiency, and discusses policy implications for Chinese iron and steel industry.     

加强高新技术企业R＆D的财务管理

在知识经济时代,R&D资金的管理成为高新技术企业财务管理的核心,如何加强高新技术企业R&D的财务管理成为大众关注的焦点。文章从4个方面对如何加强高新技术企业R&D的财务管理进行了论述。     

Performance evaluation of China's high-tech innovation process: Analysis based on the innovation value chain

The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency.     

Productive efficiency of English football teams—a data envelopment analysis approach

This paper investigates how close to their potential English Premier League Clubs play. Using a deterministic Data Envelopment Analysis Approach, the productive efficiency of 20 teams in the 2000/2001 season is measured and weaknesses of individual teams are disclosed. The sensitivity of results is analyzed with regard to different model specifications and variable combinations. Copyright © 2003 John Wiley & Sons, Ltd.     

Efficiency evaluation of the regional high-tech industry in China: A new framework based on meta-frontier dynamic DEA analysis

This paper proposes a new framework based on the combination of the dynamic DEA, meta-frontier analysis theory, and truncated regression model, and then focuses on the efficiency evaluation of regional high-tech industries in China. For all of the overall technical efficiency, technical efficiency, and scale efficiency scores, the east area is always in the lead, with the central and west areas obviously lagging behind. The eastern area has the highest technology level, whereas the west and central areas fall behind in turn. However, the meta-technology ratio of the west area has rapidly increased and presents a trend of catching up with the east. The variables of GRP per capital, total exports and imports, highway mileage per capita, and ratio of tertiary industry to GRP have positive relationships with technical efficiency, and the time trend exhibits a negative coefficient.     

Reprint of "Performance evaluation of China's high-tech innovation process :Analysis based on the innovation value chain"

The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency.     

Performance evaluation using data envelopment analysis in the presence of time lags

Data Envelopment Analysis (DEA) is a methodology that computes efficiency values for decision making units (DMU) in a given period by comparing the outputs with the inputs. In many applications, inputs and outputs of DMUs are monitored over time. There might be a time lag between the consumption of inputs and the production of outputs. We develop an approach that aims to capture the time lag between the outputs and the inputs in assigning the efficiency values to DMUs. We propose using weight restrictions in conjunction with the model. Our computational results on randomly generated problems demonstrate that the developed approach works well under a large variety of experimental conditions. We also apply our approach on a real data set to evaluate research institutions.     

From mind to market: A global,dynamic analysis of R&D

Existing models of R&D are not easily reconciled with four observable aspects of R&D: initial technologies (ideas) need to be developed further, only a minority of initial ideas are successfully brought to the market, production and process innovations take place simultaneously (whereby, initially, there is no production at all), and process innovations are implemented for technologies that are destined to leave the market. We present a detailed bifurcation analysis for a dynamic model of R&D that captures these observations in one, unifying framework. As we provide a global analysis, we do not limit initial technologies to carry marginal costs that are below the choke price. We show that there always exists a critical value of initial marginal cost above which the firm does not initiate any (R&D) activity; the path to the saddle-point steady state is never globally optimal. We also sketch some tentative policy implications of our analysis.     

Integration of network data envelopment analysis and decision-making trial and evaluation laboratory for the performance evaluation of the financial holding companies in Taiwan

Data envelopment analysis (DEA) has been constantly used to measure the technical efficiency of decision-making units (DMUs). However, the major problem of traditional DEA methods is that they do not consider the possible intermediate effects. Recently, many papers have applied network DEA models to evaluate the efficiency scores. However, the linking activity of DMUs is still hard to be recognized. Hence, we employ DEMATEL to obtain the linking activity of DMUs. Our empirical research shows that the proposed method can soundly deal with the purpose of identifying the relationship between variables and derive the reasonable result in network DEA.     

Microfinance and social capital formation- a social network analysis approach

The microcredit program has emerged as an important poverty alleviation strategy over the last three decades, and several studies have examined its economic impacts on the community well-being. However, far too little attention has been paid to the effects of micro credits on community social connection and solidarity. This paper aims to examine the application of Social Network Analysis (SNA) to explore the impact of the rural microcredit fund on community social capitals. In doing so, the data on interactions of four rural development groups' members before and after the microcredit project implementation were collected using participatory workshops in Neyzar village of Qom province in Iran. The data were analyzed by Ucinet software, and the socio-graphs were produced by the NetDraw application. The results show that, more people have been involved in the social interactions after the project implementation and there was statistically significant increase in density and decrease in centralization of cooperation network. Furthermore, there were no important distinctions in centrality of people with various educational levels before and after the project implementation. Overall, it can be concluded that, the microfinance initiative considerably promotes the community social capital and participation in the rural development activities. Moreover, the SNA techniques are applicable as an impact assessment tool to investigate changes in community social capital.     

The origins,development and future directions of data envelopment analysis approach in transportation systems

Over the last two decades, application of Data envelopment analysis (DEA) in transportation problems have gained considerable research attention. This paper presents a literature review and classification of the applications of DEA in transportation systems (TSs). First by classifying 40 papers from 2007 to 2018, the origins of DEA in transportation problems have been reviewed. Then the development and an overall view of DEA applications in TSs have been presented. We have classified the applications of DEA into six different contexts. In each context, published papers have deeply been analyzed. Content of analysis includes “Number of published papers during the time”, “target journals”, “countries”, “keyword frequency”, “most cited papers”, “map of most co-cited publications”. More important, we reported the “inputs and outputs variables” used in each paper. Further “a review of the selected papers” and “gaps/future research directions” have been given within each cluster. The results show that DEA is one of the most useful approach in evaluating TSs for policy makers. On the other hand, DEA can help the decision makers in transportation especially regarding environmental factors, sustainable development and eco-design. Finally, we proposed subjects for future researches including guidance for new studies in the field of DEA applications in TSs.     

Using data envelopment analysis to measure the efficiency of non-profit organizations: A critical evaluation

This study examines the potential effects of variable set expansion and data variations upon the efficiency scores generated using the Data Envelopment Analysis (DEA) model. It was found that variable set expansion (either through disaggregation of existing variables or addition of new factors) should produce an upward trend in efficiency scores. In addition, ample opportunity exists for ‘decision-making units’ to increase their efficiency scores through manipulation of reported data. In real-world applications of DEA, these problems must be resolved as much as possible (e.g. increased audit of data) in order to improve DEA's practical usefulness and reliability.     

Decomposing the operational efficiency of major cruise lines: A network data envelopment analysis approach in the presence of shared input and quasi-fixed input

To examine the top cruise lines' operational efficiency in three dimensions, namely, production, marketing, and profitability, this study adopts a network data envelopment analysis approach considering shared and quasi-fixed input factors. The empirical results reveal the following findings. First, the production process tends to outperform marketing and profitability processes. Second, inefficiency of a cruise line mostly stems from overconsumption of the exogenous inputs in each process and the shared input. Third, the relationships between operational efficiency of cruise lines and some categorical factors are examined. Finally, some managerial implications derived from the empirical results are formulated for cruise lines.     

Production frontier estimation to measure efficiency: A critical evaluation in light of data envelopment analysis

The ranking and measurement of efficiency of decision-making units by two methods—data envelopment analysis and frontier production function—may not always lead to identical results. In this framework we attempt here a critical evaluation of the frontier production function theory in terms of theoretical and empirical implications. It is shown that under certain conditions the two approaches to effciency measurement may lead to identical results.     

Measuring the performance of Internet companies using a two-stage data envelopment analysis model

In exploring the business operation of Internet companies, few researchers have used data envelopment analysis (DEA) to evaluate their performance. Since the Internet companies have a two-stage production process: marketability and profitability, this study employs a relational two-stage DEA model to assess the efficiency of the 40 dot com firms. The results show that our model performs better in measuring efficiency, and is able to discriminate the causes of inefficiency, thus helping business management to be more effective through providing more guidance to business performance improvement.     

Effects of intellectual property rights and patented knowledge in innovation and industry value added: A multinational empirical analysis of different industries

Technological innovation drives long-term economic growth, so most countries attempt to provide an innovation-friendly environment that includes tightening protection of intellectual property rights (IPR). However, debate continues on whether strengthened IPR lead to technological development and economic growth: patents promote innovation by protecting appropriation from invention and disclosing knowledge to the public, but they also create excessive monopoly power that may impede further innovation.Using simultaneous equations with cross-country panel data from 12 countries and 3 industries (chemical, electronic, machinery), we estimated the direct effect of IPR on industry value added and the indirect effect of it through enhanced research and development (R&D). The bilateral role of IPR, as measured by patented knowledge, was used to distinguish different characteristics of industries as well as the positive and negative effects of IPR on innovation.Results suggest that IPR generally enhance industry value added, but the positive effect is mitigated with increased enforcement of IPR. Also, IPR enhanced R&D but showed a negative relationship with patented knowledge, suggesting that excessive propertization of knowledge may hinder sequential innovation. The positive role of IPR on R&D predominated in the chemical (discrete) industry and exerted negative effects in the electronic and machinery (complex) industries.     

Eco-efficiency changes of the electricity and gas sectors across 28 European countries: A value-based data envelopment analysis productivity approach

This paper assesses the relative eco-efficiency changes in the electricity and gas sector (E&G)' production and consumption chains in 28 European countries. We propose a novel robustness assessment for the productivity index, specifically adjusted to value-based data envelopment analysis. Overall, results indicate that total factor productivity gains have been mainly driven by the catch-up effect across all chains of the E&G sector. When a more demanding perspective concerning negative environmental externalities is adopted, we find that the number of European countries that achieved productivity gains across all chains decreases. Besides, results depict the existence of lower productivity gains for the direct production chain when compared with the direct and indirect supply chains of the E&G sector. Germany, Luxembourg, and Belgium were consistently viewed as innovators across all chains, according to the environmental perspective. Several Eastern Europe countries usually viewed as policy laggards that resisted adopting the ambitious European decarbonization targets, showed total factor productivity gains in the supply chain of the E&G sector under a more environmental demanding perspective. Czechia was the only country with productivity losses across all chains, due to increasing coal-fired electricity generation in the time horizon assessed. The current partial return to coal as a source of electricity, due to the geopolitical tensions between Russia and Europe, brings additional challenges to the enhancement of the eco-efficiency of the European E&G sector.