Multi-directional Efficiency Analysis Research Articles

A Modular IoT-Based Architecture for Logistics Service Performance Assessment and Real-Time Scheduling towards a Synchromodal Transport System

Logistics is significantly impacted by quality/quantity issues associated with data collection and data sharing restrictions. Nonetheless, public data from national entities and internet-of-things (IoT) solutions enable the development of integrated tools for performance analysis and real-time optimization of logistics networks. This study proposes a three-module data-driven system architecture that covers (a) logistics data collection tools, (b) logistics services performance evaluation, and (c) the transition to synchromodal systems. Module 1 integrates multisource data from national logistics platforms and embedded devices placed within intermodal containers. A multigraph representation of the problem is conceived. Environmental, economic, and operational data are generated and injected into a digital twin. Thus, key performance indicators (KPIs) are computed by simulation or direct transformation of the collected data. Module 2 uses Multi-directional Efficiency Analysis, an optimization algorithm that benchmarks multimodal transportation routes of containers using prior KPIs. Outputs are a technical performance index relevant to logistics clients and improvement measures for logistics service providers. A real case study application of the solution proposed for Module 2 is presented. Module 3 provides real-time scheduling and assignment models using CP-sat solvers, accommodating varying system dynamics and resource availability, minimizing makespan and operational costs.

Evaluation, Driving Mechanism and Spatial Correlation Analysis of Atmospheric Environmental Efficiency in the “2+26” Cities Based on the Nonradial MEA Model

The “2+26” cities are 26 cities in Beijing, Tianjin and the surrounding cities, constituting a region characterized by economic prosperity and diverse industries but plagued by severe atmospheric pollution. As a focal area for atmospheric pollution control, a scientific assessment of atmospheric environmental efficiency in the “2+26” cities that measures the degree of coordination between the economy and air pollution is very important for winning the battle of blue sky defense. Based on this, this study comprehensively used the nonradial multi-directional efficiency analysis (MEA) model, Global Reference Malmquist Model and spatial correlation analysis to evaluate the atmospheric environmental efficiency, calculate the driving factors and explore the spatiotemporal distribution characteristics of the “2+26” cities from 2009 to 2018. The research findings indicate the following: (1) Atmospheric environmental efficiency showed a trend of first decreasing and then increasing, with a significant improvement potential of 26.7% in the future. (2) There was a significant discrepancy between the best- and worst-performing cities, with the best being 0.910 and the worst being 0.573, demonstrating imbalanced development between cities. The relatively low-efficiency cities were mainly located in Hebei, Shanxi and Henan provinces. (3) A value of technological efficiency change (EC) less than 1 was the main restrictive factor for improving atmospheric environmental efficiency, whereas a value of technological change (TC) greater than 1 enhanced it. (4) The atmospheric environmental efficiency presented a distinct spatial distribution pattern of high–high and low–low aggregation, forming high-value areas centered in the Beijing–Tianjin region and along the Zibo–Zhengzhou line. The western and central regions were relatively low, whereas the northern and eastern regions were relatively high, with significant regional differences in spatial distribution. The conclusions from this article’s empirical analysis can help concerned developing countries determine key factors to improve their atmospheric environmental efficiency and then formulate policies for sustainable economic and environmental development.

Performance Evaluation and Explainability of Last-Mile Delivery

The demand for last-mile delivery (LMD) services worldwide increased following online sales growth, so better methods to assess efficiency issues are paramount. This work explores a data-driven approach to evaluate LMD services and inform logistics service providers about possible improvement directions. It uses multi-directional efficiency analysis to benchmark LMD services based on process variables, such as delivery time and service cost. Then, by fitting machine learning models and using explainability algorithms with new metrics, characterizes factors that influence LMD performance. Early discussions with experts show that the approach produces understandable and integrable results that generate valuable insights, e.g., regarding the impact of each variable on service quality informing the direction for further improvement action.

Technical efficiency and assessment of input excess in all European farms by a non-parametric methodology and the conditional inference tree

The technical efficiency is a fundamental tool in order to evaluate the performances of farms. The main purpose of this study was to investigate the technical efficiency in all European farms part of the FADN dataset using a non-parametric approach such as the DEA. The estimation of the technical efficiency has pointed out a dichotomy between new and older member states of the European Union. The further stage of this research has been addressed in evaluating the excess of input able to impact to technical inefficiency patterns using a new approach such as the Multi-directional Efficiency Analysis. The Multi-directional Efficiency Analysis is a novelty in the literature because it estimates the percentage of excess in input involved in the inefficiency overcoming the main bottleneck in the estimation on efficiency using the DEA. By the estimation of the technical efficiency, it has been possible also to assess the impact of financial subsides allocated by the CAP. Results have corroborated as CAP subsidies have reduced the technical efficiency in farms. In the third stage of this research, it has been possible to assess by the machine learning using the conditional inference tree the excess of input and how the excess impacts on the technical efficiency with an accuracy of more 90%. The conditional inference tree is also a novelty in the literature about the technical efficiency estimation in farms combining the estimation of the technical efficiency with the patterns and reasons of inefficiency.

Un modelo dinámico no paramétrico para medir eficiencia

Conventional efficiency evaluation systems present little diversity in the type of variables considered. This aspect generally leads to errors in the application of the models and in the corresponding interpretation of results. This study proposes a dynamic model to measure the efficiency of decision-making units, based on non-parametric Multidirectional Efficiency Analysis (MEA). The model presented here considers a complete structure, which includes intertemporal variables (desirable/undesirable intermediate inputs and outputs), discretionary/non-discretionary inputs; desirable/undesirable inputs and outputs. Dynamic score is defined first in a particular version and then in a more general version, considering two optimization problems. The directional contribution of each variable is examined, showing excess inputs and deficit outputs. In addition, a dynamic inefficiency index to measure the number of times each input was used inefficiently, is presented for both desirable and undesirable cases.

The role of CAP subsidies in all European Union member states: an analysis of technical inefficiency

The purpose of this research was to assess the impact of CAP payments made to farms included in the European FADN dataset between 2004 and 2019 and, considering this financial aid as an environmental variable, identify patterns of inefficiency in EU farming. The study has adopted a twofold quantitative approach, applying both two-stage DEA and Multidirectional Efficiency Analysis. The results reveal significant imbalances between EU member states over the period of investigation, and underline the specific effect that total CAP disbursed subsidies and second pillar CAP support have on technical inefficiency.

Emigration and Common Agricultural Policy in Romanian Rural Areas: An Analysis of Patterns of Inefficiency

Romanian rural areas have suffered a significant permanent emigration since the early 1990s and the European Union by the Common Agricultural Policy has tried to slow down this negative phenomenon. The main research question was to assess if the Common Agricultural Policy has been a leverage of socio-economic development in Romanian rural areas reducing the permanent emigration from the countryside since 2010 to 2020. The quantitative approach has used the Data Envelopment Analysis and the Multi-directional Efficiency Analysis in order to assess the patterns of inefficiency due to an excess of some variables impacting to the permanent rural emigration.

Disentangling the sources of bank inefficiency: a two-stage network multi-directional efficiency analysis approach.

To disentangle the sources of bank inefficiency, this paper presents an extended two-stage network multi-directional efficiency analysis (NMEA) approach by taking the internal structure of the banking system into account. The proposed two-stage NMEA approach extends the conventional "black-box" MEA approach, providing a unique efficiency decomposition and identifying which variables drive the inefficiency for banking systems with a two-stage network structure. An empirical application of Chinese listed banks from 2016 to 2020 during the 13th Five-year Plan reveals that the overall inefficiency of sample banks is primarily sourced from the deposit-generating subsystem. Additionally, different types of banks display differentiated evolution modes over different dimensions, confirming the importance of applying the proposed two-stage NMEA approach.

Potential improvements approach in composite indicators construction: The Multi-directional Benefit of the Doubt model

The aim of the present paper is to propose an innovative method to construct composite indicators, starting from an attractive frontier approach called Multi-directional Efficiency Analysis (MEA), and making it suitable to aggregate simple indicators. The main advantage of this method is the separation of the benchmark selection issue from that of efficiency measurement. The novel method, called Multi-directional Benefit of the Doubt, combines the MEA with the Benefit of the Doubt approach adding some valuable properties to the obtained composite indicator. The proposed method is tested on simulated data for illustrative purposes, and then, an empirical application on OECD ”Better life index” is provided. Results suggest that the method could be a good tool for local policy makers alongside the OECD BLI to investigate and improve some non-performing well-being dimensions.

Workers benchmarking using multi-directional efficiency analysis in a manufacturing production system

The human factor plays a relevant role in all manual or partially automatic production systems, specially, the ones showing reliable and balanced dynamics. In the literature, parametric or survey-based models are quite common for performance evaluation of production workers. In this work, multi-directional efficiency analysis is used instead, for root cause analysis of product reworks and bottlenecks occurrence, according to four worker-related parameters: experience time, wage, delay time and response time. The approach allows to identify individual inefficiencies per tuple worker/working shift and to cluster them according to similar inefficiency parameters. In addition, this work opens a path to new applications of multi-directional efficiency analysis to problems in the manufacturing industry.

Un modelo no-paramétrico y multidireccional en investigación cuantitativa

In this work, a non-parametric and deterministic approach based on multidirectional efficiency analysis (MEA) is presented. The proposed model involves MEA with other important mathematical techniques in data analysis, such as the calculation of the NC value for the analysis of groups with different levels of efficiency. This model allows us to examine the factors that influence the behavior of decision-making units in different contexts such as business efficiency, educational quality, energy efficiency, circular economy, among others. Particularly in this work, we show the results obtained in 1787 Portuguese companies in the materials manufacturing sector (manufacture of wood and paper; manufacture of rubber products, plastics and other non-metallic mineral products; manufacture of common metals and metallic products, except machinery and equipment) in an eight-year period (2006-2013) of study. The results allow, not only a characterization of the financial structure of the sector and a diagnosis through indices that identify the strategic positioning of companies in terms of efficiency scores; but also a characterization of the most efficient units and an analysis of the variables that must be addressed differently, to obtain better results, in terms of economic performance.

Rationalising inefficiency in dairy production: evidence from an over-time approach

AbstractWe argue that inefficiency can be part of a strategic self-repositioning adjustment process beyond the general interpretation of poor performance. Based on the rational inefficiency hypothesis, we examine the simultaneous dynamics of efficiency and animal welfare improving investments over time in dairy farms. Using rotating panel data from Swedish dairy farms and implementing multidirectional efficiency analysis and Markov transitional dynamic analysis, the paper provides evidence that for some farms inefficiency is temporary and part of rational decision along their trajectory towards multi-efficiency (high efficiency-high animal welfare). The findings show the importance of time dynamics in efficiency achievements with implications to cross-sectional view.

Factors Influencing the Economic Behavior of the Food, Beverages and Tobacco Industry: A Case Study for Portuguese Enterprises

In today's world, it is increasingly important to conduct economic and financial analyzes of enterprises in all sectors to determine strengths, identify weaknesses and adopt strategies that allow them to be at the highest competitive level. In particular, the food sector plays an essential role in the economy of any country, representing a significant contribution to gross domestic product, total employment, and disposable income of households. In this work, we adopt a methodology for measuring efficiency based on the multidirectional efficiency analysis and other mathematical techniques (the calculation of the normal distribution intersection coefficient (NC value), analysis of clusters and principal components, and model fitting) in order to examine the factors that influence the performance of Portuguese enterprises in the food, beverages and tobacco industry for the period of 2006-2013. The results show a characterization of the financial structure of the sector and diagnosis through indexes that identify the strategic positioning of the enterprises in terms of efficiency scores. In addition, we also show that an analysis of the variables that must be approached differently to obtain better results regarding economic performance. Although there is an increase in credit with the acquisition of long-term debts, there is no evidence that this implies the ability of enterprises to grow faster, which affects profitability.

Dynamic evaluation on the energy and environmental performance of China's transportation sector: a ZSG-MEA window analysis.

The transportation sector is one of the important energy consumption and carbon emission sources. This paper extends the multi-directional efficiency analysis (MEA) to zero-sum game MEA (ZSG-MEA) with considering the CO2 emission as a fixed-sum undesirable output to measure the energy and environmental performance (EEP) of the transportation sector. The ZSG-MEA window analysis is applied to dynamically evaluate the EEP of China's transportation sector in 30 provincial-level regions during 2008-2017. Some interesting findings are obtained: (i) the EEP of the transportation sector in most regions has not been performed well but the average EEP of the transportation sector in most regions has been gradually improved since 2011. A general trend is that the transportation sector in the east area wins the best average EEP, and the average EEP of the central area is better than that of the west area, but their gap is narrowing from 2012. (ii) The EEP fluctuation verifies the greatest imbalance of EEP among the east area's regions. Both the east area and the central area are narrowing the imbalance in recent years, but the west area has an inverse trend. (iii) The performance of CO2 emissions is better than that of energy consumption in all three areas, which implies that China's transportation sector seems to have paid more attention on emission reduction than energy conservation. Besides, the east area has the best performance of energy consumption and CO2 emissions from an overall perspective. And the energy consumption and CO2 emissions in the central area perform better than the west area before 2013, but then shows an entangled state from 2013. (iv) From the average variable specific ZSG-MEA efficiency, the industrial added value of transportation sector performs better than other variables in the east area and central area, but the situation in the west area is inverse. Some useful insights are provided according to these findings.

Exploring the regional efficiency of the Swedish agricultural sector during the CAP reforms ‒ multi-directional efficiency analysis approach

When designing structural reforms for rural areas, the regional dimension is crucial. This study implemented a multi-directional efficiency approach in a regional, rural development context with the aim of analysing the regional efficiency of agricultural resources. The efficiency patterns of each input and output were observed over three Common Agricultural Policy (CAP) periods (1998-2013). Efficiency of labour, assets and diversified output vary the most. Over the CAP periods, the efficiency gap across the counties decreases, indicating that changes in the policy help for regions cohesion. Future policies should keep compensating for generation of public goods, and creating opportunities for diversification.

Circular economy in plastic waste - Efficiency analysis of European countries

The way plastics are currently produced, used and disposed does not capture the economic benefits of a more ‘circular’ approach and is dramatically harming the environment. It is relevant to determine which European countries can be considered more or less efficient in the end-of-life of plastic products processes, what the sources of the inefficiencies are, and how those less efficient countries could improve their performance towards a more circular economy. Although some countries have developed a variety of quantitative indicators, there is scarcity of adequate metrics for performance measurements.This paper estimates the efficiency of 26 European countries in the context of Circular Economy, for the period 2006–2016, considering the generation of waste, recovery and recycling of plastic, with a methodology based on the Multidirectional Efficiency Analysis. Apart from identifying the most efficient countries in the studied period, results show that efficiency increases for most countries with time, and that many countries reach the full efficiency by the end of the study period, and especially by 2016. Input analysis shows that increasing capital seems to be a main driver towards efficiency, since the other inputs are used with a similar efficiency by most countries. Output analysis suggest that the difference among countries efficiency is not in their reduction of total waste or emissions, but rather in the improvement of their economic growth in a circular way, that is, improving GDP but also the recovering and recycling activities. These results could be useful to design policies towards a more efficient and circular use of plastics.

Inclusive and sustainable industrial development in China: An efficiency-based analysis for current status and improving potentials

Inclusive and sustainable industrial development (ISID) is a call for action to promote industrialization by minimizing the environmental footprint and enhancing social inclusion. This study proposes a new framework of an evaluation system to assess the ISID for 30 provinces in China (2011–2016). As there does not exist a generally accepted evaluation system of ISID, this study proposes a dual-formulation of ISID to rationalize the trade-offs among externalities brought by industrialization: (i) ISID represents the aspiration of countries to promote industrialization and consequently sustain economic growth by reducing the adverse environmental and social effects which manifest in the overall economy (ii) ISIDsdg9 considers the same aspects of ISID but limits the externalities within the industrial sector. This study applied two newly developed efficiency evaluation approaches, Multi-Directional Efficiency Analysis (MEA) and Range-Adjusted Measure (RAM), to evaluate and analyze the ISID for China. This study finds that: Among the 30 provinces, (i) Beijing and Tianjin are the benchmark provinces for promoting ISID and ISIDsdg9 regimes, respectively. (ii) Throughout the 2011–2016, the overall performance of China on ISID and ISIDsdg9 regimes has improved modestly. (iii) Based on the analysis of the barrel effect, SO2 emission is the key binding constraint to achieving the frontier status of ISID and ISIDsd9 regimes (v) Under the evaluation of ISID and ISIDsdg9 regimes, the average annual growth potentials of industrial value added (IVA) is 280.52 billion CNY and 927.54 billion CNY, respectively. This present study recommends local government in China to advance their ISID performance by exploiting the policies targeting emission mitigation concerning fossil fuels while considering Beijing and Tianjin as the benchmark provinces.

A data envelopment analysis and local partial least squares approach for identifying the optimal innovation policy direction

The paper proposes a novel two-step approach that evaluates countries’ innovation efficiency and their responsiveness to expansions in their innovation inputs, while addressing shortcomings associated with composite indicators. Based on our evaluations, we propose innovation policies tailored to take into account the diverse economic environments of the many countries in our study. Applying multidirectional efficiency analysis on data from the Global Innovation Index, we obtain separate efficiency scores for each innovation input and output. We then estimate different sensitivities for each country, by applying partial least squares on explanatory and response matrices which are determined by the nearest neighbors of the country under consideration. The findings reveal substantial asymmetries with respect to innovation efficiencies and sensitivities, which is indicative of the diversity of national innovation systems. Considering these two dimensions in combination, we outline three policy directions that can be followed, offering a platform for better-informed decision-making.

Improvement path, the improvement potential and the dynamic evolution of regional energy efficiency in China: Based on an improved nonradial multidirectional efficiency analysis

As a globally important energy-using country, China's energy efficiency improvement is crucial to achieving its energy-saving goals and economic transformation. This paper explores the improvement path, the improvement potential and the dynamic evolution of regional energy efficiency in China from 2005 to 2016 with an improved multidirectional efficiency analysis and the Markov model. The results indicate that (1) China's provincial energy efficiency is olive-shaped, and there is a significant spatial imbalance. (2) Most central provinces and a small number of eastern and western provinces need to adopt a one-way breakthrough path for their weak links. Most western provinces should adopt a step-by-step progressive or leap-forward path to improve energy efficiency. (3) The energy saving potential of the eastern and western regions is relatively large, and the potential value of CO2 emission reduction in the central region are relatively large. (4) In the short run, the comprehensive energy efficiency of different provinces aren't highly fluid between different levels; In the long run, the equilibrium state of energy efficiency in China will be at a mid-low level. Accordingly, it is recommended to strengthen exchanges between different regions, give full play to the resource advantages of each region, and differentiated and targeted energy efficiency policies should be carried out in different provinces.

Energy production and C02 emisson efficiency of eight European countries in the manufacturing area

An energy efficiency comparison of manufacturing sectors of eight European countries, between 2008-2013, is performed in order to understand how the world economical crisis affected their performance. The analysis rely in a combination of multidirectional efficiency analysis blended with other techniques, as nc-value, principal component analysis mixed with a dimensionality test. The purpose is to analyse three different approaches organized by: (a) a general viewpoint on countries/sectors; (b) sectors and inefficiency input usage; and (c) intensive versus non-intensive energy sectors. We also consider non-normalized and normalized data, by the total number of firms. The results indicate that the great majority of sectors/countries analyzed show a decrease in the CO2 emissions. Since the calculated inefficiency indexes expose the sectors which used inputs in excess, we found that the most efficient sectors were: basic metals; rubber and plastic products, products of wood and cork; textiles, wearing apparel and of leather products; whereas chemical products and food; beverages and tobacco products were the most inefficient sectors. Our approach also give indicators about the way each sector/country was affected by the crisis and how they were able to react or adapt to it.