Research Efficiency in Manufacturing: An Application of DEA at the Industry Level

Schmidt-Ehmcke, Jens; Zloczysti, Petra

doi:10.2139/ssrn.1460765

Cited by 6 publications

(3 citation statements)

References 29 publications

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“…Due to the narrower focus of the current research, particularly on micro and small enterprises, some of the results can differ from the other research. The results in Table 2 differ from those reported by Schmidt-Ehmcke [72] which placed Germany and Denmark on the top of the efficiency ranking. At the same time, the results obtained are in line with previous studies like Krišt'áková et al [27] that the Slovak wood-processing enterprises performed better than the Bulgarian ones in terms of CCR efficiency.…”

Section: Dea Analysiscontrasting

confidence: 82%

Efficiency of Micro and Small Wood-Processing Enterprises in the EU—Evidence from DEA and Fractional Regression Analysis

Neykov,

Sedliacikova,

Antov

et al. 2023

Forests

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Micro and small wood-processing enterprises represent the heart of European forest-based industries, being among the key drivers of economic growth in rural, mountainous, and poor regions. Their economic efficiency is of fundamental importance for their existence and the provision of income for the local population in rural areas. Data Envelopment Analysis (DEA) is used in the current research, which is a nonparametric, linear-programming-based approach that is commonly used to analyse the efficiency of organisational units. The main objective of this study was to investigate and evaluate the economic efficiency of micro and small wood-processing enterprises in EU countries and reveal the hidden inputs that facilitate efficiency generation. The economic efficiency evaluation was carried out on the basis of the official statistical data for the micro and small wood-processing companies in EU member states for the period 2015–2020 by performing a two-stage DEA analysis. The data used were standardised by value per employee. In addition to the first stage of DEA, a fractional regression probit and logit models with four contextual variables were used to reveal the influence of the hidden inputs in the model. The results showed that the micro and small wood-processing enterprises can be regarded as more scale-efficient than technically efficient entities. The only contextual variable affecting the economic efficiency was Investments per Person Employed, improving the efficiency by 2% per 1% increase in the investments.

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Section: Dea Analysiscontrasting

confidence: 82%

Efficiency of Micro and Small Wood-Processing Enterprises in the EU—Evidence from DEA and Fractional Regression Analysis

Neykov,

Sedliacikova,

Antov

et al. 2023

Forests

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“…In this particular study, the output data under publications included international journal publications, local journal publications, international books, international book chapters, local book chapters, international conferences, local conferences and other types of publications such as magazine articles and handbooks. Four of the data sets were related to technology outputs which were the number of patents (Cullman et al, 2009;Schmidt-Ehmcke and Zloczysti, 2009), trademarks, copyrights and industrial designs. Human resources development contained four data sets; postdoctoral, PhD graduate, master graduate and undergraduate.…”

Section: Data and Variables Selectionmentioning

confidence: 99%

An efficiency analysis of grant awarded research projects: a case study of a Malaysian public university

Khurizan

Mustafa

Hamid

2018

IJPSPM

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This paper presents a novel way of evaluating the performance of grant awarded research projects using two multi-criteria decision-making methods, the measuring attractiveness through a category-based evaluation technique (MACBETH) and data envelopment analysis (DEA). This study examines the relative efficiency of the research projects as a whole and according to four groups of research disciplines. A case study of sponsored research projects from the Universiti Sains Malaysia, Penang, Malaysia was presented in this paper. The MACBETH methodology was employed before conducting the DEA analysis to group the output variables and therefore increasing the discrimination power of DEA. A total of two inputs and four outputs, after the MACBETH analysis, were used in the DEA analysis. Also, a non-parametric statistical test, the Kruskal-Wallis test, was employed to compare the performance of the research projects according to research discipline, years sponsored and a number of collaborations. Finally, a potential improvement of selected input and output was discussed as a result of a further investigation of the DEA analysis.

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“…In addition, some national analyses implement richer models in order to test some interesting additional hypotheses. One such example is that of Schmidt‐Ehmcke and Zloczysti (), who differentiate between knowledge production across sectors and Cullmann et al . () who distinguish the impact of private and public R&D and different institutional and regulatory frameworks.…”

Section: Analytical Frameworkmentioning

confidence: 99%

European Knowledge Neighbourhood: Knowledge Production in EU Neighbouring Countries and Intensity of the Relationship with EU Countries

Autant‐Bernard

Chalaye

Gagliardini

et al. 2016

Tijd voor Econ & Soc Geog

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This study aims to analyse the creation of knowledge in the European neighbourhood and the diffusion of knowledge among EU countries and European neighbouring countries (ENCs). We first collate different indicators of knowledge production and diffusion in order to characterise the main feature of ENCs. In this respect, we contribute not only with an overview of potential knowledge interactions between EU and ENCs, but also suggest original ways to account for the different facets of knowledge diffusion. We use these indicators to assess the efficiency of ENC and EU in their use of knowledge resources, relying on data envelopment analysis (DEA). Contrary to the rare DEA studies in the field, inputs are both internal and external. The results show that, despite their weakness, ENCs may benefit from their orientation towards the EU for access to external knowledge, with some of them successfully turning their rare knowledge resources into knowledge creation and innovation.

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Research Efficiency in Manufacturing: An Application of DEA at the Industry Level

Cited by 6 publications

References 29 publications

Efficiency of Micro and Small Wood-Processing Enterprises in the EU—Evidence from DEA and Fractional Regression Analysis

Efficiency of Micro and Small Wood-Processing Enterprises in the EU—Evidence from DEA and Fractional Regression Analysis

An efficiency analysis of grant awarded research projects: a case study of a Malaysian public university

European Knowledge Neighbourhood: Knowledge Production in EU Neighbouring Countries and Intensity of the Relationship with EU Countries

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