How to pick your staff? Using data envelopment analysis

2014 ◽  
Vol 37 (9) ◽  
pp. 815-832 ◽  
Author(s):  
Susanne Warning
Keyword(s):  
Data Envelopment Analysis ◽  
Personnel Selection ◽  
Multiple Criteria ◽  
Data Envelopment ◽  
Human Resource Managers ◽  
Content Type ◽  
Optimal Weights ◽  
Resource Managers ◽  
Using Data ◽  
The Individual

Purpose – This purpose of this paper is to present a tool for facilitating personnel selection when multiple heterogeneous human resource managers use multiple criteria. Two problems result from such a situation. First, when multiple criteria are applied, it is unusual for one candidate to dominate the other candidates in all areas, which requires assigning weights to the different criteria to be able to rank the candidates. Second, in a heterogeneous selection committee, finding weights that accurately reflect the individual preferences of all members is difficult. Design/methodology/approach – To deal with the multidimensional setting of selecting personnel, this paper introduces data envelopment analysis with assurance region (DEA-AR) to determine individually optimal weights for each applicant. Findings – DEA-AR leads to a score for each applicant that can serve as a signal for productivity and, thus, for evaluating the candidate. Based on linear programming, DEA-AR not only aggregates multiple dimensions into a single score but also incorporates managers’ preferences. In addition, the procedure is transparent and fair. It seems to be highly appropriate for selecting personnel. Based on a simulated dataset of applicants, the use of DEA-AR for selecting personnel is illustrated and discussed. Originality/value – DEA-AR provides a tool for supporting personnel selection or pre-selection. This model is based on a mechanical procedure and considers managers’ ideas about weights.

Exploring the effect of online banking on bank performance using data envelopment analysis

2019 ◽  
Vol 27 (1) ◽  
pp. 137-165 ◽  
Author(s):  
Kwame Owusu Kwateng ◽  
Edna Edwina Osei-Wusu ◽  
Kofi Amanor
Keyword(s):  
Data Envelopment Analysis ◽  
Banking Sector ◽  
Principal Component ◽  
Internet Banking ◽  
Bank Performance ◽  
Data Envelopment ◽  
Content Type ◽  
Banking Service ◽  
Using Data ◽  
And Cluster Analysis

Purpose Increased competition in the banking sector coupled with long queues in the banking hall has necessitated the introduction of internet banking among banks in Ghana. As a result, internet banking has attracted a great deal of attention from both academicians and practitioners. The purpose of this paper is to examine the effect of internet banking on the performance of banking institutions in Ghana. Design/methodology/approach In total, 20 banks in Ghana were selected from the Bank of Ghana website for the study. The financial information about the banks’ operations was retrieved from the financial statements of the respective banks for the end of the year 2016. The data envelopment analysis-bootstrap approach with principal component analysis and cluster analysis was used to estimate 49 models. Findings The findings of the study indicated that the integration of internet banking into traditional banking methods has led to superior bank performance in Ghana. It was observed that while the independent application of internet banking as a strategy to raise performance was not yielding higher returns due to the low patronage of internet services among banking consumers, its integration with possible traditional methods is widely observed among the top performers in the banking industry. Practical implications Traditional banking methods, integrated banking service strategies and the internet banking service-oriented strategy emerged as the main banking strategies among the banks. Originality/value Extant literature is quite silent on the effect of internet banking on bank performance in Africa. However, this paper is among the first significant attempts to examine the effect of internet banking on bank performance.

A new approach to determine the weights of project activities using data envelopment analysis: a case of Mobarakeh steel company

2020 ◽  
Vol 13 (6) ◽  
pp. 1187-1217
Author(s):  
Negin Berjis ◽  
Hadi Shirouyehzad ◽  
Javid Jouzdani
Keyword(s):  
Data Envelopment Analysis ◽  
Business Environment ◽  
Second Phase ◽  
Data Envelopment ◽  
Weight Factor ◽  
Steel Company ◽  
New Approach ◽  
Content Type ◽  
Weight Factors ◽  
Using Data

PurposeThe main purpose of this paper is to propose a new approach to determine the project activities weight factors using data envelopment analysis. Afterward, the model is applied in Mobarkeh Steel Company as a case study. Accordingly, the project schedule and plans can be written on the basis of the gained weight factors.Design/methodology/approachThis study proposed an approach to determine the weights of activities using Data Envelopment Analysis. This approach consists of four phases. In the first phase, project activities are extracted based on the work breakdown structure. In the second phase, the parameters affecting the importance of activities are determined through a review of the related literature and based on the experts' opinions. In the third phase, the proper data envelopment analysis model is chosen and the inputs and outputs are signified. Then, the activities' weights are determined based on the efficiency numbers. Finally, the model is solved for the case of Isfahan Mobarakeh Steel Company.FindingsThe proposed method aimed to calculate the project activities weight factor. Thus, influential parameters on project activities importance include activity duration, activity cost, activity importance which includes successors and predecessors, activity difficulty which includes skill related (education and experience), safety, communication rate, intellectual effort, physical effort, unfavorable work conditions and work related hazards, have been recognized. Then, Projects' data were extracted from the organizational expert's opinions and recorded data in documents. Thereupon, applying DEA, the activities weight factor were calculated based on the efficiency numbers. The results show that the model is applicable and has promising benefits in real-world problems.Originality/valuePlanning is one the most fundamental steps of project management. The ever-growing business environment demands for more complex projects with larger number of activities wants more efficient project managers. Organizational resources are limited; therefore, activities planning is a critical from the perspectives of both managers and researchers. Knowing the importance of the activities can help to manage activities more efficient and to allocate time, budget, cost and other resources more accurate. Different elements such as cost, time, complexity, and difficulty can affect the activity weight factor. In this study, the proposed approach aims to determine the weights of activities using Data Envelopment Analysis.

A multiple-criteria approach to human resource management assessment in organizations with respect to industry

Kybernetes ◽  
2017 ◽  
Vol 46 (3) ◽  
pp. 419-432 ◽  
Author(s):  
Vesna Čančer ◽  
Simona Šarotar Žižek
Keyword(s):  
Factor Analysis ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Human Resource Managers ◽  
Holistic Model ◽  
Content Type ◽  
Resource Managers

Purpose This paper aims to develop a multiple-criteria model for the assessment of human resource management (HRM), focusing on groups of organizations with respect to industry. Design/methodology/approach The approach presented in this paper follows the framework procedure for multiple-criteria decision-making based on the Quantified Dialectical Systems Theory. It considers the factor analysis results in structuring the problem. By considering several experts’ judgments already when measuring the importance of criteria, it enables respondents to omit those sets of criteria for which they are neither experts nor responsible. Findings The paper shows that the factor analysis results can also be used in structuring the multi-dimensional concept in multiple-criteria model for assessing HRM – a step forward to multi-methodology. The obtained aggregate values show human resource managers the key success and failure factors to adopt an integrated/requisitely holistic and innovated strategy related to HRM in organizations. Research limitations/implications The approach presented in this paper helps managers in developing and implementing a requisitely holistic model of HRM, adapted to several groups of organizations, such as with respect to their industry, in any country. Practical implications This paper provides recommendations for HRM in organizations. Originality/value This paper fills the gap in the research on multiple-criteria HRM assessment in organizations with respect to their industry by developing a multiple-criteria model for the assessment of HRM in groups of organizations, with application based on their industries.

Measuring operational efficiency of isolation hospitals during COVID-19 pandemic using data envelopment analysis: a case of Egypt

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahmoud Abdelrahman Kamel ◽  
Mohamed El-Sayed Mousa
Keyword(s):  
Data Envelopment Analysis ◽  
Design Methodology ◽  
Operational Efficiency ◽  
Data Envelopment ◽  
Allocation Of Resources ◽  
Tobit Regression ◽  
Health Crisis ◽  
Content Type ◽  
Dea Analysis ◽  
Using Data

PurposeThis study used Data Envelopment Analysis (DEA) to measure and evaluate the operational efficiency of 26 isolation hospitals in Egypt during the COVID-19 pandemic, as well as identifying the most important inputs affecting their efficiency.Design/methodology/approachTo measure the operational efficiency of isolation hospitals, this paper combined three interrelated methodologies including DEA, sensitivity analysis and Tobit regression, as well as three inputs (number of physicians, number of nurses and number of beds) and three outputs (number of infections, number of recoveries and number of deaths). Available data were analyzed through R v.4.0.1 software to achieve the study purpose.FindingsBased on DEA analysis, out of 26 isolation hospitals, only 4 were found efficient according to CCR model and 12 out of 26 hospitals achieved efficiency under the BCC model, Tobit regression results confirmed that the number of nurses and the number of beds are common factors impacted the operational efficiency of isolation hospitals, while the number of physicians had no significant effect on efficiency.Research limitations/implicationsThe limits of this study related to measuring the operational efficiency of isolation hospitals in Egypt considering the available data for the period from February to August 2020. DEA analysis can also be an important benchmarking tool for measuring the operational efficiency of isolation hospitals, for identifying their ability to utilize and allocate their resources in an optimal manner (Demand vs Capacity Dilemma), which in turn, encountering this pandemic and protect citizens' health.Originality/valueDespite the intensity of studies that dealt with measuring hospital efficiency, this study to the best of our knowledge is one of the first attempts to measure the efficiency of hospitals in Egypt in times of health' crisis, especially, during the COVID-19 pandemic, to identify the best allocation of resources to achieve the highest level of efficiency during this pandemic.

Getting nowhere, going elsewhere: the impact of perceived career compromises on turnover intentions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dirk De Clercq
Keyword(s):  
Human Resource ◽  
Turnover Intentions ◽  
Human Resource Managers ◽  
Personal Factors ◽  
Content Type ◽  
Career Compromise ◽  
Resource Managers ◽  
Conditional Effects ◽  
The Individual ◽  
The Impact

PurposeThe purpose of this article is to investigate the unexplored relationship between employees' perceptions that they have made compromises in their careers (i.e. perceived career compromise) and their turnover intentions, as well as how it might be moderated by two personal factors (materialism and idealism) and two contextual factors (abusive supervision and decision autonomy).Design/methodology/approachSurvey data were collected among employees who work in the education sector in Canada.FindingsEmployees' frustrations about unwanted career adjustments lead to an enhanced desire to leave their organization. This process is more likely among employees who are materialistic and suffer from verbally abusive leaders, but it is less likely among those who are idealistic and have more decision autonomy.Practical implicationsFor human resource managers, these results provide novel insights into the individual and contextual circumstances in which frustrations about having to compromise career goals may escalate into the risk that valuable employees quit.Originality/valueThis study contributes to human resource management research by detailing the conditional effects of a hitherto overlooked determinant of employees' turnover intentions, namely, their beliefs about a discrepancy between their current career situation and their personal aspirations.

Supplier evaluation and classification in a Colombian motorcycle assembly company using data envelopment analysis

2019 ◽  
Vol 32 (2) ◽  
pp. 159-180 ◽  
Author(s):  
Rodrigo Restrepo ◽  
Juan G. Villegas
Keyword(s):  
Data Envelopment Analysis ◽  
Current Trend ◽  
Superior Performance ◽  
Just In Time ◽  
Supplier Evaluation ◽  
Data Envelopment ◽  
Content Type ◽  
Ordinal Variables ◽  
Using Data

Purpose The purpose of this paper is to present a case study in which data envelopment analysis (DEA) is used to evaluate and classify the suppliers of a Colombian motorcycle assembly company. This tool allows the integration of several attributes into single performance measures (cross-efficiency and diversity efficiency) and subsequent classification based on the values obtained for these two metrics. Design/methodology/approach The classification uses a methodology based on two main tools. The first is an input-oriented cross-efficiency DEA model with ordinal variables to evaluate the suppliers’ performance, and the second is a classification of these into categories that identifies those with good performance for features that make them outstanding. Findings The assembly company segments its suppliers according to supply frequency. The results show that suppliers working under a just-in-time system achieve superior performance with respect to other suppliers. Practical implications The application of this methodology in a real-world case illustrates how DEA can be a useful tool to support the evaluation and classification of suppliers (a process of increasing complexity given the current trend to include multiple strategic measures together with classical operational measures). Moreover, the methodology illustrated in the study can be adapted to other similar settings. Originality/value The main contributions of this paper are twofold. First, to the best of our knowledge, this is the first study to illustrate the use of DEA in a real case related to supplier evaluation. Second, the presence of ordinal variables (e.g. quality or environmental ratings) gives rise to DEA variants seldom used in this context.

Performance analysis of Indian states based on social–economic infrastructural investments using data envelopment analysis

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gaurav Goyal ◽  
Pankaj Dutta
Keyword(s):  
Data Envelopment Analysis ◽  
Social Economic ◽  
Efficiency Analysis ◽  
Data Envelopment ◽  
Competitive Growth ◽  
Social Infrastructure ◽  
Indian States ◽  
Content Type ◽  
Economic Infrastructure ◽  
Using Data

PurposeThis study investigates the performance of Indian states based on infrastructural investment in social and economic sectors using data envelopment analysis (DEA). Most of the studies in the literature are based on how different elements of infrastructure such as transport, energy, education, healthcare system affect the economy of different countries/regions. In this study, we consider these elements under two different sub-systems, namely, social and economic infrastructure and measure the cooperative efficiency for competitive growth.Design/methodology/approachA four-stage DEA approach is proposed for the analysis of a sample of 28 Indian states for the years 2011, 2013 and 2015 under consideration. First stage calculates the per capita GDP contribution, while stage-2 evaluates the efficiency of investments in social infrastructure followed by the efficiency analysis in economic infrastructure in stage-3. Finally, fourth stage evaluates the co-operative efficiency for the overall performance.FindingsThe findings of three different cases based on population sizes, viz., highly populated, moderately populated and less populated regions suggest that the government can identify the top and poor performers. It also studies the variations in efficiency tally of states using Malmquist indices.Practical implicationsThis kind of study will vigilant government and local authorities on the investments made in all the states for social and economic infrastructure and establish a competitive environment among state governments to compete for improved infrastructural growth.Originality/valueThis study is the first of its kind in developing countries like India, which focuses on efficiency analysis using DEA based on two sub-sectors of social–economic infrastructural investments.

Identifying escalation of commitment in B2B new product development projects using data envelopment analysis

2014 ◽  
Vol 29 (3) ◽  
pp. 209-214 ◽  
Author(s):  
Naveen Donthu ◽  
Belgin Unal
Keyword(s):  
Data Envelopment Analysis ◽  
Product Development ◽  
New Product Development ◽  
New Product ◽  
Development Projects ◽  
Data Envelopment ◽  
Escalation Of Commitment ◽  
Content Type ◽  
Development Area ◽  
Using Data

Purpose – Business managers are constantly faced with the decision to continue or abandon new product development projects. However, this type of decision may not be easy. These decisions are usually prone to bias of managers. Managers are known to escalate their commitment toward failed projects. It is also not easy to identify projects that are suffering from escalation of commitment. The purpose of this paper is to propose an objective escalation identification method. Design/methodology/approach – This paper proposes an objective escalation identification method using data envelopment analysis (DEA). The results from DEA are compared with those of subjective methods of identifying escalation. Findings – The objective estimate of escalation given by DEA was comparable to the subjective estimate of escalation given by the managers in the survey. Research limitations/implications – DEA is sensitive to outliers and managers should be careful in selecting projects that are to be included for comparison. DEA does not give statistical fit indices as it is an operational research based technique. Practical implications – DEA is an objective and automatic tool that makes the decision of managers easier. Managers can use this tool by inputting the output and input variables of their projects and then see which ones are escalated, therefore need to be abandoned. As a consequence, escalation of commitment and big losses can be prevented especially in new product development area. Originality/value – By using the proposed objective approach, escalation of commitment and associated big losses can be prevented especially in new product development area.

Measuring the supply chain risk in offshoring countries using data envelopment analysis and the analytic hierarchy process

2017 ◽  
Vol 24 (7) ◽  
pp. 1977-1994 ◽  
Author(s):  
Hokey Min ◽  
Heekeon Park ◽  
Seung Bum Ahn
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Analytic Hierarchy Process ◽  
Data Envelopment ◽  
Wealth Creation ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Using Data ◽  
Supply Chain Risks ◽  
Hierarchy Process

Purpose An indiscreet strategy of offshoring from low-cost countries (LCCs) can do more harm than good, since invisible supply chain risks may increase hidden costs and subsequently more than offset cost-saving opportunities. Considering the potential impact of these risks on offshoring, the purpose of this paper is to identify risk factors that significantly hinder the efficiency of offshoring and then measure specific risks associated with offshoring in foreign countries. Design/methodology/approach This paper develops performance metrics for gauging the offshoring attractiveness of potential sourcing countries using data envelopment analysis and then identifies the benchmark sourcing country using the analytic hierarchy process (AHP). Findings This study reveals that, defying the conventional wisdom, LCCs are not necessarily the most desirable offshoring destinations. This study also discovers that LCCs tend to be less business friendly, less logistically efficient, and riskier to source than their high-income country counterparts. Originality/value This paper is one of the first to introduce the concept of wealth creation efficiency for an offshoring decision and consider a host of key determinants such as wealth creation efficiency, logistics efficiency, business friendliness, and various supply chain risks for selecting the most desirable offshoring destination.

Sign in / Sign up

Export Citation Format

Share Document