Can ports increase traffic while reducing inputs? Technical efficiency of Spanish Port Authorities using a directional distance function approach

Regional Port Productivity in APEC

“…However, in face of unprecedented, intensive competition and environmental flux, determining a method to improve a country's port productivity has become a major challenge to policymakers [52]. Discrete distance functions seemed to be a potentially useful tool for policy makers, allowing management with measurable indicators, and making it possible to improve productivity without increased investment [15]. Cullinane and Song [53] recommended an appropriate grouping of ports to be conducted before comparison to identify the source impact of efficiency and measures for improvement.…”

“…This result is slightly higher than the results for Trujillo and Tovar [49], who found that the average capacity utilization of European ports was 60%. Tovar and Wall [15] also suggested the over-investment to be replaced by the maximization of current capacity utilization The mean of gMMPI of DCs was 0.6695, higher than that of APEC, suggesting that the productivity of DCs is higher than that of LDCs. Apparently, the productivity frontier of DCs was closer to the metafrontier than that of LDCs, indicating that on average, DCs had a greater potential for better productivity than LDCs.…”

“…The findings suggested that the competition intensity among ports seemed to lead to a decline in port efficiency, and the difference in time between the equipment investment and the actual utilization of the equipment was the key factor. Tovar and Wall [15] applied directional technology distance functions to analyze the production technology and the technical efficiency of 20 Spanish port authorities from 1993 to 2012, and suggested that the Spanish ports should maximize the capacity of existing ports to provide services, rather than to over-invest in technology. Song and Cui [16] used the Malmquist index to study the changes in the productivity of Chinese container ports during the period 2006 to 2011.…”

Metrics for Assessing Overall Performance of Inland Waterway Ports: A Bayesian Network Based Approach

“…Chang and Tovar [21,22] Technical efficiency Stochastic Distance Function (SDF) Tovar and Wall [23] Port productive efficiency Directional technology distance function approach Bichou and Gray [24] Terminology for classifying seaport Conceptual framework Hosseini and Barker [25,26] Resilience Bayesian approach Sierra et al [27] Harbour operability Numerical Model Ugboma et al [28] Port selection Analytical Hierarchy Process (AHP) Chang et al [29] Port selection factor Exploratory factor and confirmatory factor analyses Gohomene (2008) Port selection Analytical Hierarchy Process (AHP) Nur et al [31] Port selection Stochastic Analytical Hierarchy Process (SAHP) Song and Yeo [32] Competitiveness of container ports Analytical Hierarchy Process (AHP) Yeo et al [33] Competitiveness of container ports Fuzzy methodology overall inland port performance and translate these criteria into BN model to assess the probability of PPI. From this, belief propagation and sensitivity analyses are presented, respectively.…”

“…The current body of the literature is replete with other theoretical and empirical studies that focus on the subject of port performance and different types of port efficiencies. Interested readers can refer to the works of Coto-Millan et al [15], Notteboom et al [16], Barros [17], Díaz-Hernández et al [18], Panayides et al [19], Wanke [20], Chang and Tovar [21,22], and Tovar and Wall [23]. Likewise, there are some analytical studies that have been devoted to other aspects pertaining to seaports, such as seaport characterization and classification (e.g., [24]), port operations and resilience (e.g., [25][26][27]), port selection (e.g., [28][29][30][31]), and port competitiveness (e.g., [32,33]).…”