Network DEA Models for Evaluating Couriers and Messengers

Chodakowska, Ewa; Nazarko, Joanicjusz

doi:10.1016/j.proeng.2017.03.130

Cited by 18 publications

(13 citation statements)

References 6 publications

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“…(Pinto, 2016) apply both constant and variable returns to scale Data Envelopment Analysis network model to estimates the relational and sub-process efficiency of the production process of the hospital's acute care services. (Chodakowska & Nazarko, 2017) apply a network DEA models in evaluating courier and messenger companies. In their work the authors consider an hypothetical chains consisting of two types of members, i.e.…”

Section: Materials Studiedmentioning

confidence: 99%

“…The NDEA approach, however, provides that the modeling (note 1) is adapted to the specific system. NDEA applications are relatively recent but growing [for example (Chodakowska & Nazarko, 2017), (Kao & Hwang, 2008), (Kawaguchi, Tone, & Tsutsui, 2014), (Pinto, 2016), (Prieto & Zofio, 2007), (Sexton & Lewis, 2003), (Wanke & Barros, 2014), (Wanke, Maredza, & Gupta, 2017), ( (Despotis, Koronakos, & Sotiros, 2015), (Chilingerian & Sherman, 2004), (Cook, Hababou, & Tuenter, 2010)]. In this paper we develop a relational multiplicative type NDEA model assuming constant returns to scale for the entire process and for its parts and with four interconnected subsystems.…”

Section: Introductionmentioning

confidence: 99%

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Measure the Relative Efficiency of a Four-Stage Production Process with NDEA

Pinto¹

2020

IJBM

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The measurement of the relative efficiency of a production process with the DEA approach considers the process itself as a "black box" that uses inputs to produce outputs. In reality, many production processes require the carrying out of many activities grouped into phases and interconnected with each other. For this reason, modeling a production process as a network system in which its sub-parts are differently interconnected certainly represents a modeling closer to reality. The NDEA approach born within the DEA methodology has developed several models to measure the relative efficiency of network systems such as independent models, or connected models or relational models. The latter differs from the other two in that it allows you to measure the relative efficiency of the entire process and its parts once the operations between the parts of the system have been considered. In this paper, as well as modeling a production process with four stages with shared variables, we propose a relational NDEA model under different preference systems in the distribution of resources between sub-processes to measure their relative efficiency. The proposed NDEA model is in the multiplicative version. We will use non-real data to solve the model. Our conclusions are that 1) a four-stage production process can represent numerous real processes, 2) the proposed NDEA model can therefore be used for multiple different applications and 3) the system of preferences on the distribution of resources among subs processes influences the measurement of relative efficiency both for the whole process and for its sub-processes.

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Section: Materials Studiedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Measure the Relative Efficiency of a Four-Stage Production Process with NDEA

Pinto¹

2020

IJBM

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“…-contribution of a product/service to economic efficiency and welfare VSocial -contribution of a product/service to addressing social problem(s) VEnv -contribution of a product/service to protecting the natural environment t0 -time before the introduction of innovation t1 -time after the introduction of innovation α -weight of the economic criterion β -weight of the social criterion γ -weight of the environmental criterion ocialt1 + γVEnvt1 > αVEcont0 + βVSocialt0 + γVEnvt0 oduct/service to economic efficiency and welfare oduct/service to addressing social problem(s) oduct/service to protecting the natural environment oduction of innovation duction of innovation mic criterion criterion onmental criterion inconsistencies in judgments, 2) Inputs can be actual measurements, but also subjective opinions (Goepel, 2018). Another interesting evolution of this approach could be the application of Data Envelopment Analysis (DEA) to managing innovation projects portfolio with the focus on their "responsibility potential" (Chodakowska and Nazarko, 2017). Competing innovation roadmaps/trajectories could be evaluated with DEA with the view on how well they transform inputs (e.g.…”

Section: Veconmentioning

confidence: 99%

Operationalising Responsible Research and Innovation – tools for enterprises

Nazarko

Melnikas

2019

Engineering Management in Production and Services

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Responsible Research and Innovation (RRI) is an emerging paradigm and a novel approach to governing science and innovation with the aim of making them ethically acceptable and socially desirable. RRI concept has become a popular term as a result of making it a cross-cutting theme for the Horizon 2020 Framework Programme. Up to date, research on the topic has focused on conceptual problems (relation with similar concepts as well as ethical, moral, philosophical, cultural underpinnings and assumptions) and on the possibilities of making the concept relevant to the Research & Innovation community in Europe and worldwide. Despite some initial efforts, there is still a need to further develop methods and techniques that could make RRI a useful framework for conducting innovation activities, especially in the business environment. The aim of this paper is to propose a range of approaches that help operationalise RRI. The approaches employ methods such as weighted indicators, maturity models and scorecards.

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“…The analysis was performed using the Data Envelopment Analysis (DEA) method. The DEA has been a recognised and popular method of analysing efficiency in various areas of economy and administration as well as the non-profit sector [9][10][11]. The world literature on the DEA method has been extensive and is constantly growing.…”

Section: Introductionmentioning

confidence: 99%

Assessing the performance of Polish Regional Funds for Environmental Protection and Water Management using DEA model

Nazarko

Chodakowska

2020

MATEC Web Conf.

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The public sector is under growing pressure to increase its efficiency. Expectations from the political authorities, local communities, stakeholders and media towards the public-sector entities are high. Modern management methods must be introduced to meet them. Data Envelopment Analysis (DEA) is an important method used in comparative studies of public sector efficiency. Voivodeship Funds for Environmental Protection and Water Management (VFEPWMs) are public entities that financially support actions aimed at environmental protection and water management. Their task is to acquire and redistribute financial resources to support projects related to environmental protection. VFEPWMs face the challenge of increasing the use of available funds and the efficiency of their use. The paper presents the use of DEA method — which is as a modern engineering management tool — to evaluate the VFEPWMs performance. In the DEA performance analysis of VFEPWM, it is assumed that each unit may be characterised by their input resources, effects, environmental variables and transformation processes that transform resources into effects. VFEPWMs have better performance if they transform resources into desirable effects (actions) more efficiently. The results of the conducted analysis allow comparing the performance of particular VFEPWMs, to identify model units and to develop benchmarking graphs. The analysis is performed not only to assess the current level of VFEPWM performance but also to acquire information allowing to remove inefficiency.

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Network DEA Models for Evaluating Couriers and Messengers

Cited by 18 publications

References 6 publications

Measure the Relative Efficiency of a Four-Stage Production Process with NDEA

Measure the Relative Efficiency of a Four-Stage Production Process with NDEA

Operationalising Responsible Research and Innovation – tools for enterprises

Assessing the performance of Polish Regional Funds for Environmental Protection and Water Management using DEA model

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