Evaluation of the efficiency of logistics activities using Data Envelopment Analysis (DEA)

Lepchak, Alessandro; Voese, Simone Bernardes

doi:10.1590/0104-530X3371-20

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ORIGINAL ARTICLE • Gest. Prod. 27 (1) • 2020 • https://doi.org/10.1590/0104-530X3371-20 copy

Evaluation of the efficiency of logistics activities using Data Envelopment Analysis (DEA)

Avaliação da eficiência das atividades logísticas utilizando a Análise Envoltória de Dados (DEA)

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

This study aimed to analyze the efficiency of activities related to logistics modes, transport and cargo handling in Brazil. The theoretical framework was composed of the logistics efficiency and of the discussion of the characteristics of modes of transport and of variables related to efficiency. The study was classified as descriptive and quantitative, using the technique of data envelopment analysis. As main results, the ancillary activities to air transport stand out as efficient, which reached scores of 100% in the analyzed periods, except in 2010, in which they obtained 91.58%. It is worth noting that the activities cabotage and long-haul and ancillary activities to land transport achieved three maximum efficiency scores. In addition to evaluating the benchmark for the activities of lower efficiency score, the study also included improvements needed for other activities to achieve maximum efficiency. Finally, the central contribution of the article lies in the proposition of a multimodal analysis model.

Keywords:
Logistics efficiency; Data Envelopment Analysis (DEA); Logistics

Author/Year	Objective	Variables	Result
Sarkis (2000)Sarkis, J. (2000). An analysis of the operational efficiency of major airports in the United States. Journal of Operations Management, 18(3), 335-351. http://dx.doi.org/10.1016/S0272-6963(99)00032-7. http://dx.doi.org/10.1016/S0272-6963(99)...	To evaluate the efficiency at 44 US airports.	- expense	High correlations were found as a result of the verification of the correlation among efficiency, external factors and characteristics of airports.
		- number of employees
		- number of companies
		- profit
		- frequency of service
		- number of passengers
		- volume
Taliani & Escobar (2008)Taliani, E. C.,& Escobar, S. G. (2008). Analisis de la eficiência encostes delas empresas de transporte de mercancıa por carretera: uma aproximación empírica del DEA. Revista Ibero-americana de Contabilidade de Gestion, 6(11), 93-120.	To evaluate the technical efficiency of road transportation companies between 2004 and 2006.	- sales	The size of companies influences efficiency. The cost structure may be improved in all respects. Potential for improvement in revenue generation.
		- primary materials
		- personnel expenses
		- depreciation
		- costs and expenses
Savolainen (2007)Savolainen, V-V. (2007). Relative technical efficiency of european transportation systems (Master’s thesis). Lappeenranta University of Technology, Lappeenranta.	To evaluate the efficiency of rail, road and water transports in the United Kingdom.	- capacity	The results of the analysis show that efficiency differences exist in rail operations, however, specialization among the actors exists in both transport subsectors.
		- line numbers
		- labor force
		- volume
Heinen et al. (2012)Heinen, A. C., Diehl, C. A., & Alves, T. W. (2012, November 12-14). Análise de eficiência ambiental na aviação civil comercial brasileira com uso da abordagem DEA. In Anais do Congresso Brasileiro de Custos. São Leopoldo: Associação Brasileira de Custos.	To analyze the environmental technical efficiency of Brazilian airlines.	- Flight and ground employees	For passenger transportation, the most efficient companies are Azul, Tam, Webjet, Gol, and for cargo transportation are Absa and Master Top. Regarding the environmental analysis, it was verified that it is possible to reduce 286.62 GgCO2 from total emissions.
		- Fleet
		- Fuel consumption
		- Earth hours
		- Revenue passenger kilometer (RPK)
		- Revenue ton kilometer (RTK)

I/O	Variables	Acronym for Identification	Composition of variables	Empirical theoretical reference
*Input*	Modes of transport	ACQUIS_ TRANSP	Total acquisition of modes of transport.	- Martín-Cejas (2002)Martín-Cejas, R. R. (2002). An approximation to the productive efficiency of the Spanish airports networks through a deterministic cost frontier. Journal of Air Transport Management, 8(4), 233-238. https://doi.org/10.1016/S0969-6997(01)00056-4. https://doi.org/10.1016/S0969-6997(01)00...
	Modes of transport	ACQUIS_ TRANSP	Total acquisition of modes of transport.	- Uri (2001)Uri, N. D. (2001). Technical efficiency, allocative efficiency, and the impact of incentive regulation in telecommunications in the United States. Structural Change and Economic Dynamics, 12(1), 59-73. http://dx.doi.org/10.1016/S0954-349X(00)00031-X. http://dx.doi.org/10.1016/S0954-349X(00)...
	Personnel expenses	MOD	It includes the total amounts of wages and bonuses as well as other values, among them profit sharing and social contribution taxes.	- Sarkis (2000)Sarkis, J. (2000). An analysis of the operational efficiency of major airports in the United States. Journal of Operations Management, 18(3), 335-351. http://dx.doi.org/10.1016/S0272-6963(99)00032-7. http://dx.doi.org/10.1016/S0272-6963(99)...
				- Taliani & Escobar (2008)Taliani, E. C.,& Escobar, S. G. (2008). Analisis de la eficiência encostes delas empresas de transporte de mercancıa por carretera: uma aproximación empírica del DEA. Revista Ibero-americana de Contabilidade de Gestion, 6(11), 93-120.
				- Savolainen (2007)Savolainen, V-V. (2007). Relative technical efficiency of european transportation systems (Master’s thesis). Lappeenranta University of Technology, Lappeenranta.
				- Heinen et al. (2012)Heinen, A. C., Diehl, C. A., & Alves, T. W. (2012, November 12-14). Análise de eficiência ambiental na aviação civil comercial brasileira com uso da abordagem DEA. In Anais do Congresso Brasileiro de Custos. São Leopoldo: Associação Brasileira de Custos.
	Costs	COSTS	Costs of services, consumables and other expenses, except fuel.	- Sarkis (2000)Sarkis, J. (2000). An analysis of the operational efficiency of major airports in the United States. Journal of Operations Management, 18(3), 335-351. http://dx.doi.org/10.1016/S0272-6963(99)00032-7. http://dx.doi.org/10.1016/S0272-6963(99)...
	Costs	COSTS		- Taliani & Escobar (2008)Taliani, E. C.,& Escobar, S. G. (2008). Analisis de la eficiência encostes delas empresas de transporte de mercancıa por carretera: uma aproximación empírica del DEA. Revista Ibero-americana de Contabilidade de Gestion, 6(11), 93-120.
	Fuel	FUEL	Total fuel costs in the analyzed period.	- Taliani & Escobar (2008)Taliani, E. C.,& Escobar, S. G. (2008). Analisis de la eficiência encostes delas empresas de transporte de mercancıa por carretera: uma aproximación empírica del DEA. Revista Ibero-americana de Contabilidade de Gestion, 6(11), 93-120.
*Output*	Revenue	REVENUE	Proxy used in the place of volume.	- Taliani & Escobar (2008)Taliani, E. C.,& Escobar, S. G. (2008). Analisis de la eficiência encostes delas empresas de transporte de mercancıa por carretera: uma aproximación empírica del DEA. Revista Ibero-americana de Contabilidade de Gestion, 6(11), 93-120.

Mode	Activity
Railway	1. Rail freight transport
Roadway	2. Road freight transport
Waterway	3. Cabotage and long-haul
	4. Inland navigation
	5. Support navigation
	6. Other modes of water transport
Airway	7. Air freight transport
Ancillary Activities	8. Cargo handling and storage
	9. Ancillary activities to land transport
	10. Ancillary activities to water transport
	11. Ancillary activities to air transport
	12. Organizing activities of cargo transport

		REVENUE	FUEL	MOD	COSTS	ACQUIS_ TRANSP
REVENUE	Correlation	1	.962**	.982 ^**	.983**	.952**
	Sig. (2-tailed)		.000	.000	.000	.000
	Sum of Squares and Cross-products	1.484E16	2.181E15	1.120E14	1.516E15	1.340E15
	Covariance	2.515E14	3.696E13	1.899E12	2.569E13	2.271E13
	N	60	60	60	60	60
** Significance index lower than 1%

Num	Description	2008	2009	2010	2011	2012
1	Rail freight transport	78.63%	83.47%	100.00%	100.00%	75.50%
2	Road freight transport	57.76%	56.97%	54.61%	55.60%	54.49%
3	Cabotage and long-haul	100.00%	100.00%	100.00%	91.52%	81.07%
4	Inland navigation	49.82%	55.95%	51.34%	55.05%	56.33%
5	Support navigation	47.41%	42.70%	41.85%	42.60%	38.43%
6	Other modes of water transport	36.62%	36.16%	38.61%	38.76%	37.93%
7	Air freight transport	100.00%	77.75%	72.84%	80.07%	100.00%
8	Cargo handling and storage	74.73%	64.80%	61.24%	66.03%	74.29%
9	Ancillary activ. to land transport	96.37%	100.00%	100.00%	100.00%	98.59%
10	Ancillary activ. to water transport	100.00%	100.00%	95.60%	95.76%	68.91%
11	Ancillary activ. to air transport	100.00%	100.00%	91.58%	100.00%	100.00%
12	Organizing activ. of cargo transport	76.72%	71.64%	57.10%	70.12%	64.00%
	MEAN	76.50%	74.12%	72.06%	74.63%	70.80%
	MINIMUM	36.62%	36.16%	38.61%	38.76%	37.93%
	STANDARD DEVIATION	0.193644	0.194157	0.21273	0.199318	0.174462

YEAR	DMU	Input				Output
YEAR	DMU	MOD %	FUEL %	COSTS %	ACQUIS_ TRANSP %	REVENUE %
2008	Anc. activ. to land transport	0.00	0.00	0.00	0.00	3.77
2008	Organizing activ. of cargo transport	0.00	0.00	0.00	-67.44	30.35
2008	Cargo handling and storage	0.00	0.00	0.00	0.00	33.82
2008	Support navigation	0.00	0.00	0.00	-89.26	110.92
2008	Inland navigation	0.00	-0.45	-69.22	-43.24	100.73
2008	Other modes of water transport	0.00	0.00	0.00	-5.01	173.09
2008	Rail freight transport	0.00	-8.73	0.00	-11.50	27.18
2008	Road freight transport	0.00	0.00	0.00	-85.81	73.12
2009	Organizing activ. of cargo transport	0.00	0.00	0.00	-5.08	39.58
2009	Cargo handling and storage	0.00	0.00	0.00	-28.74	54.31
2009	Support navigation	0.00	0.00	0.00	-88.28	134.18
2009	Inland navigation	0.00	-19.33	-75.95	-67.62	78.74
2009	Other modes of water transport	0.00	0.00	0.00	0.00	176.55
2009	Air freight transport	0.00	0.00	0.00	0.00	28.62
2009	Rail freight transport	0.00	-3.94	0.00	-62.36	19.81
2009	Road freight transport	0.00	0.00	0.00	-90.92	75.53
2010	Anc. activ. to air transport	0.00	0.00	0.00	-11.77	9.20
2010	Anc. activ. to water transport	0.00	0.00	0.00	0.00	4.60
2010	Organizing activ. of cargo transport	0.00	0.00	0.00	0.00	75.12
2010	Cargo handling and storage	0.00	0.00	0.00	-0.52	63.30
2010	Support navigation	0.00	0.00	0.00	-89.95	138.97
2010	Inland navigation	0.00	-9.78	-75.78	-66.23	94.80
2010	Other modes of water transport	0.00	0.00	0.00	0.00	159.00
2010	Air freight transport	0.00	0.00	0.00	0.00	37.28
2010	Road freight transport	0.00	0.00	0.00	-84.08	83.12
2011	Anc. activ. to water transport	0.00	0.00	0.00	0.00	4.43
2011	Organizing activ. of cargo transport	0.00	0.00	0.00	-8.11	42.60
2011	Cabotage and long-haul	0.00	0.00	-41.28	-96.56	9.27
2011	Cargo handling and storage	0.00	0.00	0.00	-53.08	51.45
2011	Support navigation	0.00	0.00	0.00	-93.31	134.72
2011	Inland navigation	0.00	0.00	-78.34	-73.31	81.65
2011	Other modes of water transport	0.00	0.00	-34.41	-15.97	158.01
2011	Air freight transport	0.00	0.00	0.00	0.00	24.89
2011	Road freight transport	0.00	0.00	0.00	-87.99	79.87
2012	Anc. activ. to water transport	0.00	0.00	0.00	0.00	45.11
2012	Anc. activ. to land transport	0.00	0.00	-27.04	0.00	1.43
2012	Organizing activ. of cargo transport	0.00	0.00	0.00	-20.25	56.24
2012	Cabotage and long-haul	0.00	0.00	-19.35	-82.75	23.35
2012	Cargo handling and storage	0.00	0.00	0.00	-71.30	34.61
2012	Support navigation	0.00	0.00	0.00	-90.93	160.20
2012	Inland navigation	0.00	0.00	0.00	-21.65	77.52
2012	Other modes of water transport	0.00	0.00	0.00	0.00	163.61
2012	Rail freight transport	0.00	0.00	0.00	-5.94	32.44
2012	Road freight transport	0.00	0.00	0.00	-89.79	83.52
	MEAN	0.00	-0.96	-9.58	-38.84	70.24
	MAXIMUM	0.00	0.00	0.00	0.00	176.55
	MINIMUM	0.00	-19.33	-78.34	-96.56	1.43
	STANDARD DEVIATION	0.00	1.72	15.67	36.25	42.63

Universidade Federal de São Carlos Departamento de Engenharia de Produção , Caixa Postal 676 , 13.565-905 São Carlos SP Brazil, Tel.: +55 16 3351 8471 - São Carlos - SP - Brazil
E-mail: gp@dep.ufscar.br

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[1] Source: Research data (2014).