Human capital in public research laboratories: a method proposal for assessing actual and target scores

2020 ◽  
Vol 12 (5) ◽  
pp. 1189-1208 ◽  
Author(s):  
Driss El Kadiri Boutchich
Keyword(s):  
Human Capital ◽  
Data Envelopment Analysis ◽  
Research Policy ◽  
Public University ◽  
Data Envelopment ◽  
Content Type ◽  
Research Activities ◽  
Starting Point ◽  
Target Values ◽  
The Impact

PurposeThis work aims to propose an alternative method of human capital calculation for research laboratories of public university, taking into account some drawbacks of the methods currently applied in this field.Design/methodology/approachThis method is implemented via a linear program extracted from Data Envelopment Analysis based on slack movement. This is the formulation of Copper et al. (2000), which is used as the starting point for developing the proposed method through important transformations.FindingsThe proposed method is supported by an illustration related to a Moroccan public university. This illustration showed that 57 per cent of the laboratories and all the research activities that they perform are in deficit with respect to target scores.Research limitations/implicationsThe proposed method has technical limitations related to scores equal to 1 and to variables when those are numerous. To solve them, it is possible to use peer benchmarking system for the first limitation, and methods of regrouping the variables when those are numerous for the second limitation. Equally, the proposed method does not associate slack with important factors like governance and the impact analysis of research on innovation, competitiveness, and societal aspects. Likewise, it does not use the slack to measure individual efficiency at the same laboratory. Future research can fill these gaps.Practical implicationsThis work allows making appropriate budgetary and research policy within university, through budgeting process and management control by using raw and adjusted target values as well as actual ones. Also, the highlighting of the excessive slacks leads the university to take actions to reduce them, according to the most loss-making research activities.Originality/valueThe proposed method is original, since it fills a deficit in terms of human capital target values calculation and of the slack movement concept in relation to the efficient frontier. Additionally, it transforms the Data Envelopment Analysis program into a program that eliminates the slacks linked to the inputs, the radial movement related to the outputs and treats only the outputs and slacks related to these outputs.

Benchmarking the efficiencies of Indonesia’s municipal water utilities using Stackelberg data envelopment analysis

2015 ◽  
Vol 22 (4) ◽  
pp. 588-609 ◽  
Author(s):  
Andreas Wibowo ◽  
Hans Wilhelm Alfen
Keyword(s):  
Data Envelopment Analysis ◽  
The Body ◽  
Water Utilities ◽  
Data Envelopment ◽  
Two Stage ◽  
Restrictive Assumption ◽  
Content Type ◽  
Second Stage ◽  
Municipal Water ◽  
The Impact

Purpose – The purpose of this paper is to present a yardstick efficiency comparison of 269 Indonesian municipal water utilities (MWUs) and measures the impact of exogenous environmental variables on efficiency scores. Design/methodology/approach – Two-stage Stackelberg leader-follower data envelopment analysis (DEA) and artificial neural networks (ANN) were employed. Findings – Given that serviceability was treated as the leader and profitability as the follower, the first and second stage DEA scores were 55 and 32 percent (0 percent = totally inefficient, 100 percent = perfectly efficient), respectively. This indicates sizeable opportunities for improvement, with 39 percent of the total sample facing serious problems in both first- and second-stage efficiencies. When profitability instead leads serviceability, this results in more decreased efficiency. The size of the population served was the most important exogenous environmental variable affecting DEA efficiency scores in both the first and second stages. Research limitations/implications – The present study was limited by the overly restrictive assumption that all MWUs operate at a constant-return-to-scale. Practical implications – These research findings will enable better management of the MWUs in question, allowing their current level of performance to be objectively compared with that of their peers, both in terms of scale and area of operation. These findings will also help the government prioritize assistance measures for MWUs that are suffering from acute performance gaps, and to devise a strategic national plan to revitalize Indonesia’s water sector. Originality/value – This paper enriches the body of knowledge by filling in knowledge gaps relating to benchmarking in Indonesia’s water industry, as well as in the application of ensemble two-stage DEA and ANN, which are still rare in the literature.

Fuzzy C-means based data envelopment analysis for mitigating the impact of units’ heterogeneity

Kybernetes ◽  
2016 ◽  
Vol 45 (3) ◽  
pp. 536-551 ◽  
Author(s):  
Seyed Hossein Razavi Hajiagha ◽  
Shide Sadat Hashemi ◽  
Hannan Amoozad Mahdiraji
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Negative Impact ◽  
Positive Impact ◽  
Efficiency Score ◽  
Data Envelopment ◽  
Content Type ◽  
Fuzzy C Means ◽  
The Impact ◽  
Decision Making Units

Purpose – Data envelopment analysis (DEA) is a non-parametric model that is developed for evaluating the relative efficiency of a set of homogeneous decision-making units that each unit transforms multiple inputs into multiple outputs. However, usually the decision-making units are not completely similar. The purpose of this paper is to propose an algorithm for DEA applications when considered DMUs are non-homogeneous. Design/methodology/approach – To reach this aim, an algorithm is designed to mitigate the impact of heterogeneity on efficiency evaluation. Using fuzzy C-means algorithm, a fuzzy clustering is obtained for DMUs based on their inputs and outputs. Then, the fuzzy C-means based DEA approach is used for finding the efficiency of DMUs in different clusters. Finally, the different efficiencies of each DMU are aggregated based on the membership values of DMUs in clusters. Findings – Heterogeneity causes some positive impact on some DMUs while it has negative impact on other ones. The proposed method mitigates this undesirable impact and a different distribution of efficiency score is obtained that neglects this unintended impacts. Research limitations/implications – The proposed method can be applied in DEA applications with a large number of DMUs in different situations, where some of them enjoyed the good environmental conditions, while others suffered from bad conditions. Therefore, a better assessment of real performance can be obtained. Originality/value – The paper proposed a hybrid algorithm combination of fuzzy C-means clustering method with classic DEA models for the first time.

Integrated data envelopment analysis and multicriteria decision-making ranking approach based on peer-evaluations and subjective preferences: case study in banking sector

2020 ◽  
Vol 54 (4) ◽  
pp. 551-582
Author(s):  
Jolly Puri ◽  
Meenu Verma
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Decision Maker ◽  
Multicriteria Decision Making ◽  
Peer Evaluation ◽  
Data Envelopment ◽  
Content Type ◽  
Multicriteria Decision ◽  
Subjective Preference ◽  
The Impact

PurposeThis paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making units (DMUs) based on cross-efficiency technique and subjective preference(s) of the decision maker.Design/methodology/approachSelf-evaluation in data envelopment analysis (DEA) lacks in discrimination power among DMUs. To fix this, a cross-efficiency technique has been introduced that ranks DMUs based on peer-evaluation. Different cross-efficiency formulations such as aggressive and benevolent and neutral are available in the literature. The existing ranking approaches fail to incorporate subjective preference of “one” or “some” or “all” or “most” of the cross-efficiency evaluation formulations. Therefore, the integrated framework in this paper, based on DEA and multicriteria decision-making (MCDM), aims to present a ranking approach to incorporate different cross-efficiency formulations as well as subjective preference(s) of decision maker.FindingsThe proposed approach has an advantage that each of the aggressive, benevolent and neutral cross-efficiency formulations contribute to select the best alternative among the DMUs in a MCDM problem. Ordered weighted averaging (OWA) aggregation is applied to aggregate final cross-efficiencies and to achieve complete ranking of the DMUs. This new approach is further illustrated and compared with existing MCDM approaches like simple additive weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prove its validity in real situations.Research limitations/implicationsThe choice of cross-efficiency formulation(s) as per subjective preference of the decision maker and different orness levels lead to different aggregated scores and thus ranking of the DMUs accordingly. The proposed ranking approach is highly useful in real applications like R and D projects, flexible manufacturing systems, electricity distribution sector, banking industry, labor assignment and the economic environmental performances for ranking and benchmarking.Practical implicationsTo prove the practical applicability and robustness of the proposed integrated DEA-MCDM approach, it is applied to top twelve Indian banks in terms of three inputs and two outputs for the period 2018–2019. The findings of the study (1) ensure the impact of non-performing assets (NPAs) on the ranking of the selected banks and (2) are enormously valuable for the bank experts and policy makers to consider the impact of peer-evaluation and subjective preference(s) in formulating appropriate policies to improve performance and ranks of underperformed banks in competitive scenario.Originality/valueTo the best of the authors’ knowledge, this is the first study that has integrated both DEA and MCDM via OWA aggregation to present a ranking approach that can incorporate different cross-efficiency formulations and subjective preference(s) of the decision maker for ranking DMUs.

scholarly journals Data envelopment analysis and data mining to efficiency estimation and evaluation

2019 ◽  
Vol 12 (2) ◽  
pp. 169-190 ◽  
Author(s):  
Abdel Latef M. Anouze ◽  
Imad Bou-Hamad
Keyword(s):  
Data Mining ◽  
Data Envelopment Analysis ◽  
Predictive Ability ◽  
Conditional Inference ◽  
Bank Performance ◽  
Data Envelopment ◽  
Content Type ◽  
Data Mining Techniques ◽  
Second Stage ◽  
The Impact

PurposeThis paper aims to assess the application of seven statistical and data mining techniques to second-stage data envelopment analysis (DEA) for bank performance.Design/methodology/approachDifferent statistical and data mining techniques are used to second-stage DEA for bank performance as a part of an attempt to produce a powerful model for bank performance with effective predictive ability. The projected data mining tools are classification and regression trees (CART), conditional inference trees (CIT), random forest based on CART and CIT, bagging, artificial neural networks and their statistical counterpart, logistic regression.FindingsThe results showed that random forests and bagging outperform other methods in terms of predictive power.Originality/valueThis is the first study to assess the impact of environmental factors on banking performance in Middle East and North Africa countries.

Dynamic frontier estimation for monitoring team performances

2019 ◽  
Vol 25 (3/4) ◽  
pp. 212-228
Author(s):  
Melike Yılmaz ◽  
Çağlar Aksezer ◽  
Tankut Atan
Keyword(s):  
Data Envelopment Analysis ◽  
Historical Data ◽  
Expert Knowledge ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Content Type ◽  
Frontier Estimation ◽  
Efficiency Measures ◽  
The Impact

Purpose This paper aims to investigate how predictions of football league standings and efficiency measures of teams, obtained through frontier estimation technique, evolve compared to actual results. Design/methodology/approach The study is based on data from the Turkish first division football league. Historical data for five seasons, from 2011 to 2016, are used to compare weekly estimates to de facto results. Data envelopment analysis efficiency measures are used to estimate team performances. After each week, a data envelopment analysis is run using available data until then, and final team standings are estimated via computed efficiencies. Estimations are improved by using a data envelopment analysis model that incorporates expert knowledge about football. Findings Results indicate that deductions can be made about the league’s future progress. Model incorporating expert knowledge tends to estimate the performance better. Although the prediction accuracy starts out low in early stages, it improves as the season advances. Scatter of individual teams’ performances show fluxional behaviour, which attracts studying the impact of uncontrollable factors such as refereeing. Originality/value While all previous studies focus on season performance, this study handles the problem as a combination of weekly performance and how it converges to reality. By tracking weekly performance, managers get a chance to confront their weak performance indicators and achieve higher ranking by improving on these inefficiencies.

scholarly journals Benchmarking—A Way of Finding Risk Factors in Business Performance

2021 ◽  
Vol 14 (5) ◽  
pp. 221
Author(s):  
Jarmila Horváthová ◽  
Martina Mokrišová ◽  
Mária Vrábliková
Keyword(s):  
Risk Factors ◽  
Data Envelopment Analysis ◽  
Heat Supply ◽  
Business Performance ◽  
Data Envelopment ◽  
Performance Factors ◽  
Best Value ◽  
Target Values ◽  
Dea Method ◽  
Comparison Of The Results

The purpose of this study was to emphasize that the Data Envelopment Analysis (DEA) method is an important benchmarking tool which provides necessary information for improving business performance. To fulfil the abovementioned goal, we used a sample of 48 Slovak companies involved in the field of heat supply. As their position in the economic and social environment of the country is essential, considerable attention should be paid to improving their performance. In addition to the DEA method, we applied the Best Value Method (BVM). We found that DEA is a highly important benchmarking tool, as it provides benchmarks for units that have problems with performance and helps us to reveal risk performance factors. The DEA method also allows us to determine target values of indicators. The originality of this paper is in its comparison of the results of the BVM and the DEA methods.

Digital competences of the workforce – a research topic?

2017 ◽  
Vol 23 (3) ◽  
pp. 721-734 ◽  
Author(s):  
Matthias Murawski ◽  
Markus Bick
Keyword(s):  
Research Topic ◽  
Future Research ◽  
Digital Competence ◽  
Content Type ◽  
Research Activities ◽  
Starting Point ◽  
Pros And Cons ◽  
Definition Of ◽  
The Individual ◽  
Practical Implications

Purpose Considering working in the digital age, questions on the consequences for the individual workers are, so far, often neglected. The purpose of this paper is to deal with the question of whether the digital competences of the workforce is a research topic. The authors argue for the thesis that it is indeed a research topic. Design/methodology/approach In addition to a literature analysis of the top IS, HR, and learning publications, non-scientific sources, as well as the opinions of the authors, are included. The authors’ thesis is challenged through a debate of corresponding pros and cons. Findings The definition of digital competences lacks scientific depth. Focussing on the workforce is valid, as a “lifelong” perspective is not mandatory for research. Digital competence research is a multidisciplinary task to which the IS field can make a valuable contribution. Research limitations/implications Although relevant references are included, some aspects are mainly driven by the opinions of the authors. The theoretical implications encompass a call for a scientific definition of digital competences. Furthermore, scholars should focus on the competences of the workforce, including occupations, roles, or industries. The authors conclude by providing a first proposal of a research agenda. Practical implications The practical implications include the alignment of multiple stakeholders for the design of “digital” curricula and the integration by HR departments of the construct of digital competences, e.g. for compensation matters and job requirements. Originality/value This paper is one of very few contributions in the area of the digital competences of the workforce, and it presents a starting point for future research activities.

Could CSR improve the financial performance of developing countries’ firms? Analyses of mediating effect of intangible resources

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohamed Hamdoun ◽  
Mohamed Akli Achabou ◽  
Sihem Dekhili
Keyword(s):  
Developing Countries ◽  
Human Capital ◽  
Financial Performance ◽  
Competitive Advantage ◽  
Mediating Effect ◽  
Social Dimension ◽  
Content Type ◽  
Intangible Resources ◽  
The Impact

Purpose This paper aims to examine the link between corporate social responsibility (CSR) and financial performance in the context of developing countries. More specifically, the mediating role of a firm’s competitive advantage and intangible resources, namely, human capital and reputation are studied. Design/methodology/approach The study considered a sample of 100 Tunisian firms. The analysis makes use of the structural equation modelling method to explore the relationship between CSR and financial performance, by including mediator variables. Findings The results confirm that CSR has no significant direct effect on financial performance. In particular, they indicate that the social dimension of CSR has a negative impact on performance. However, CSR does have a positive impact on competitive advantage via the two intangible resources considered, human capital and company reputation. Research limitations/implications The research fills a gap that occurred in the previous literature. In effect, previous studies focussed only on the direct link between CSR and financial performance. In addition, it enriches the limited literature on CSR strategies in the context of developing countries. However, further studies should explore the opposite relationship, i.e. the impact of financial performance on CSR strategy. In addition, the authors believe that amongst other potential research avenues, it would be interesting to study the moderating role of the activity sector. Practical implications From a practical point of view, this study suggests new applications with respect to the link between CSR and financial performance. To enhance their company’s financial performance, managers need to ensure that intangible resources are managed efficiently. Originality/value The paper contributes to the literature by examining how a firm’s intangible resources mediate between CSR and competitive advantage and how competitive advantage mediates between intangible resources and financial performance. Second originality is related to the study of the link between CSR and the financial performance of business organisations in the context of a developing country.

Fuzzy preference programming formulation in data envelopment analysis for university department evaluation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dyanne Brendalyn Mirasol-Cavero ◽  
Lanndon Ocampo
Keyword(s):  
Data Envelopment Analysis ◽  
Real Life ◽  
The Philippines ◽  
Data Envelopment ◽  
Data Accessibility ◽  
Content Type ◽  
Proposed Model ◽  
University Department ◽  
Fuzzy Dea ◽  
Fuzzy Preference

Purpose University department efficiency evaluation is a performance assessment on how departments use their resources to attain their goals. The most widely used tool in measuring the efficiency of academic departments in data envelopment analysis (DEA) deals with crisp data, which may be, often, imprecise, vague, missing or predicted. Current literature offers various approaches to addressing these uncertainties by introducing fuzzy set theory within the basic DEA framework. However, current fuzzy DEA approaches fail to handle missing data, particularly in output values, which are prevalent in real-life evaluation. Thus, this study aims to augment these limitations by offering a fuzzy DEA variation. Design/methodology/approach This paper proposes a more flexible approach by introducing the fuzzy preference programming – DEA (FPP-DEA), where the outputs are expressed as fuzzy numbers and the inputs are conveyed in their actual crisp values. A case study in one of the top higher education institutions in the Philippines was conducted to elucidate the proposed FPP-DEA with fuzzy outputs. Findings Due to its high discriminating power, the proposed model is more constricted in reporting the efficiency scores such that there are lesser reported efficient departments. Although the proposed model can still calculate efficiency no matter how much missing and unavailable, and uncertain data, more comprehensive data accessibility would return an accurate and precise efficiency score. Originality/value This study offers a fuzzy DEA formulation via FPP, which can handle missing, unavailable and imprecise data for output values.

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