A competitive analysis of EU ports by fixing spatial and economic dimensions

Abstract

The purpose of this paper is to evaluate the efficiencies of ten of the leading European ports. The motivation of the research refers to the relevant topic of selection of indicators that can be involved in the comparative analysis. Concerning the theoretical model, the authors’ efforts are especially directed towards the usage of the stochastic frontier analysis (SFA) and of the data envelopment analysis (DEA). These techniques have been widely adopted for benchmarking and performance evaluation by involving indicators based on data from National Accounts. If one of these indicators, such as labour force consistency, is not available at a specific level of aggregation, detailed assumptions are needed to address this complication. The present study proposes an additive model in order to provide an estimation of ports’ economic activities by fixing the port activity boundaries and the spatial perimeter of the firms investigated. Several NUTS (Nomenclature of Territorial Units for Statistics) levels and NACE (EU Statistical Classification of Economic Activities) codes are fixed to offer a useful comparable labour indicator. Empirical results reveal that each port area presents a combination of the NACE categories which significantly impact the efficiency that can reach very high performance values through both the SFA and DEA techniques. Since the managers can choose which sectors to improve, which particular improvement strategies to support, which specific service to add, their decisions impact this performance evaluation, and their performance can be verified through the approaches proposed.

Strategy making in hyper uncertainty: towards a conceptual framework from the seaport industry during Brexit

“…However, the present systematic review argues that deeper interactions and motivations underly the nature of the strategy making processes in context. For example, the tensions inherent in the interaction of CEO, board of directors, government owners and wider contextual influences such as the EU, are now interpretable as a fundamental activity in the strategy making, reflecting, for instance, the recent contributions of Sifakis and Tsoutsos (2021) and Quintano et al (2020). Governance structures have long been subject to change, and are argued as a tool of government policy in context (Brooks, 2004), yet the impact of changed governance structures on strategy making under uncertainty suggests contradictory outcomes in terms of delivering effective strategy (O’Hanlon and Cummins, 2021; de Langen and Van der Lugt, 2018).…”

“…Here relationships at the level of both supply chains (Rodrigue, 2012; Tongzon, 2009) and stakeholders are argued to shape the nature of strategy making, providing a level of level of context and directing strategy making through shaping interventions. Even aside from hyper uncertainty, a level of dynamic is provided to strategy making as resource-based connections to partners (Van der Lugt et al , 2013) and a process of alignment with the goals of partners (Quintano et al , (2020) proceeds. Again, at the initial stage of strategy making pre-hyper uncertainty, the CEO (Kearney et al , 2018) accompanied by top management (Haugstetter and Cahoon, 2010) and other organisational inputs (Dooms et al , 2019) shape a strategy making which is potentially dynamic and innovative (de Langen and Van der Lugt, 2018).…”

“…Government changes, with associated new policies (De Langen and Van der Lugt, 2018), demands for change in the nature of existing relationships (Hollen et al , 2015), information asymmetries between new government staff and intricate industry routines and dynamics (O’Hanlon and Cummins, 2021) all serve to mediate the emerging strategy making. Policy developments emerging from a hyper uncertainty event such as Brexit serve to alter both existing relationships requiring strategy making to at times develop a more creative and innovative form to reach and link with new partners, for example, in the sustainability domain (Quintano et al , 2020). Further, policy developments place demands on existing internal knowledge creation and resourcing, requiring a strategy making sensitive to innovating the internal organisation towards achieving such demands (Henriquez et al , 2022).…”

The Stochastic Frontier Model for Technical Efficiency Estimation of Interconnected Container Terminals

“…Alongside mentioned variables, we have also considered another input variable-berth water depth WDb, closely related to quay length, that represents the average depth along the port/terminal quay in meters, indirectly determining the size of the vessel that can be berthed alongside the quay [11,13,33,40,60]. The introduced variable, which is the most appropriate proxy for the aforementioned equipment data category, is quay cranes QC, representing the number of units used for container handling in ship-to-shore and shore-to-ship relations [16,32,37]. The final first-order input variable associated with both, the equipment and labor data categories, is yard equipment YE.…”

Performance assessment of major European ports

“…Therefore, management can legitimately use consistent efficient scores to evaluate the consequences of policy actions, and the model should be appropriate when aiming towards the dimensions mentioned above. It is necessary to highlight that DEA and SFA approaches might both describe the same erroneous conclusions; hence the above-mentioned consistent outcomes might not validate the method's assumptions, and a comprehensive analysis is needed in future research (Quintano, Mazzocchi and Rocca, 2020b).…”