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One of the most important problems concerning the toll roads is the setting of an appropriate cost for traveling through private arcs of a transportation network. The purpose of this paper is to consider this problem by stating it as a bilevel programming (BLP) model. At the upper level, one has a public regulator or a private company that manages the toll roads seeking to increase its profits. At the lower level, several companies-users try to satisfy the existing demand for transportation of goods and/or passengers, and simultaneously, to select the routes so as to minimize their travel costs. In other words, what is sought is kind of a balance of costs that bring the highest profit to the regulating company (the upper level) and are still attractive enough to the users (the lower level).

With the aim of providing a solution to the BLP problem in question, a direct algorithm based on sensitivity analysis (SA) is proposed. In order to make it easier to move (if necessary) from a local maximum of the upper level objective function to another, the well-known “filled function (FF)” method is used.

The paper proposes and tests two versions of the heuristic algorithm to solve the toll optimization problem (TOP) based upon SA for linear programming (LP) problems. The algorithm makes use of an SA procedure for the LP problem at the lower level, as well as of the “filled” function technicalities in order to reach the global optimum when “jammed” at some local optimum. Numerical experiments with a series of small and medium dimension test problems show the proposed algorithm’s robustness and decent convergence characteristics.

Numerical experiments with a series of small- and medium dimension test problems show the proposed algorithm’s robustness and reasonable convergence characteristics. In particular, while ceding in efficiency to other algorithms when solving small problems, the proposed method wins in the case of medium (higher dimensional) test models. Because of that, one can expect a serious real-life impact on the TOP when the proposed methods and/or their improved versions are developed further to be applicable in practice in the near future.

The proposed algorithms are original and perform well when solving small and medium test numerical problems. The proposed heuristics aim at filling in a gap in a series of numerical approaches to the solution of TOP problem listed in the Introduction. To the authors knowledge, no systematic attempts to apply the SA tools to the toll assigned problem have been recently made. Moreover, the combination of these powerful tools with the “FFs” techniques brings forward some new global optimization ideas. Exactly these features build up the knowledge this specific paper offers in relation to previous relevant works.

This paper focusses on the aftermath of disruptions and the importance of the two largest canals (Suez and Panama), commenting on how during the pandemic the canal fees were lowered. Considering the ongoing efforts to decarbonize shipping, some of the ongoing disruptions will help reach these objectives faster.

Following a literature review of route choice in shipping, and a presentation of significant disruptions in recent years, the author deploys a simplified fuel consumption model and conduct case study analyses to compare different routes environmentally and economically.

The results explain why at times of low fuel prices as in 2020, canals provided discounts to entice ship operators to keep transiting these, instead of opting for longer routes. Considering the ongoing repercussions of the pandemic in supply chains, as well as the potential introduction of market-based measures in shipping, the value of transiting canals will be much higher in the coming years.

The main limitation in this work is that the author used the publicly available information on canal tolls, for the different ship types examined.

The envisioned model is simple, and it can be readily used for any ship and route (port to port) combination available, if ship data are available to researchers.

It is possible that canal tolls will increase, to account for the additional environmental benefits brought to ship operators.

The methodology is simple and transferable, and the author proposes several interesting research questions for follow-up work.

The purpose of this paper is to understand the interactions and their cause/effect consequences of three aspects present inside organizational realities, namely, organizational social capital (OSC), worker resilience and innovation derived from the workers.

A cross-sectional study for analyzing the subjects was chosen. As a quantitative research approach, after the theoretical review, two possibilities were hypothesized for how they act as a system. In order to verify the hypotheses, the authors chose the structural equation model, a suitable instrument for this analysis, as a mathematical tool.

The results show that OSC is a mediator between resilience and innovation in the organizational dynamics. This suggests that workers’ resilience need OSC, acting as the mediator, to improve their level of innovation capacity.

The study gives information at a specific point in time. Follow-up studies are needed to understand the phenomena’s transformation, and no distinction was made between exploratory and exploitative innovation. More empirical studies should be carried out to enhance its understanding.

These findings can help organizations deal better with these resources to reach their goals because the first, as stated in the purpose, is the amalgamated goodwill necessary for individuals to work together; the second is workers’ capacity to bounce back; and the last is the creativity inherent in people. All of which are significant for an enterprise thrive in its market.

The cited dynamic has few studies, and this work provides evidence about its existence and magnitude, shedding light on a critical factors’ relationship net, especially for enterprises based on the creativity of their workers.

This study reports on the effect of demand variation on the optimal location of road-pricing cordons. The optimal road-pricing cordon, in this study, aims to maximise the social welfare function. This optimisation program is categorised as Bi-level optimisation programming which is a NP hard problem. The paper first describes the method developed to solve the optimal toll problem for a given set of chargeable links. The tests were carried out with a small toy network and a larger scale network. For the small network, four single user class demand characteristics were varied individually; these were the elasticity of trip generation with respect to increases in travel cost, value of travel time, volume of traffic, and traffic distribution pattern. For the larger scale network, only elasticity, value of time, and trip volume were tested. The results of the larger scale network are also analysed by including the cost per toll point. The tests with the larger scale network were modified so that the constraint of uniform charge is applied. The results showed that demand variation could influence the best location of toll points. This finding raises the question of whether the implementation of the same cordon all day in an urban traffic network is the optimal approach under the existence of demand variations by time of day, and also whether the evaluation process of the cordon location should consider the effect of different time periods together.