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This study examines the importance of social network size and structural holes within the network to the entrepreneurial opportunity recognition process.

The increase of containership sizes driven by the need to create greater economies of scale seems to be an endless process. Vessels of more than 21,000 TEU are presently on order. The purpose of this paper is to question whether a positive effect still remains at present mega ship sizes and, even if this was the case, whether such presumably small effect would be outweighed by costly operational impacts for the lines and the ports out of the huge ship sizes.

The effect of increasing ship sizes on the three major cost items in container shipping have been investigated by extrapolating founded regression curves, applying respective physical laws and referring lumpsum crewing cost (as the major part of the vessel’s running costs) to various ship sizes.

In this paper, it is shown that further effects of lower slot costs lessen while ships get larger. Hence, a further increase in ship sizes would not significantly reduce transport costs anymore. In contrast, the necessary efforts to prepare the ports for ships of ever-increasing size are growing over proportionally with every additional metre of draught and/or beam. It is shown that an ongoing increase of containership sizes, e.g. in the Europe-Far East trade, does not bring any further benefit, neither for the ports and their terminals nor even for the lines itself and not even for the shippers! It is an amazing mechanism that all stakeholders act rationally on their own, but the overall effect for all of them (including the public) has turned into negative.

The results may pave the way for a closer cooperation among ports, e.g. within the Hamburg-Le Havre range. Ports and terminals may see the opportunity to escape the spiral of ongoing efforts for deepening and widening the fairways and installing ever-bigger gantry cranes by agreeing on a joint policy with regard to maximum ship size.

This is an empirical study of family firm size, as measured by the number of employees, and the relationship of a firmʼs size to a variety of management activities, styles, and characteristics. A statistical analysis of data drawn from 159 American family businesses indicates significant differences by size with regard to the number of nonfamily members in top management, use of outside advisors, time spent engaged in strategic management, use of sophisticated methods of financial management, proportion of women family members involved in firm management, and level of conflict between family members. Implications are offered for family firm owner-managers, for those who assist such businesses, and for researchers in the field of family business.

This paper aims to propose two solution approaches to determine the number of ground transport vehicles that are required to ensure the on-time delivery of military equipment between origin and destination node pairs in some geographic region, which is an important logistics problem at the US Transportation Command.

The author uses a mathematical program and a traditional heuristic to provide optimal and near-optimal solutions, respectively. The author also compares the approaches for random, small-scale problems to assess the quality and computational efficiency of the heuristic solution, and also uses the heuristic to solve a notional, large-scale problem typical of real problems.

This work helps analysts identify how many ground transport vehicles are needed to meet cargo delivery requirements in any military theater of operation.

This research assumes all problem data is deterministic, so it does not capture variations in requirements or transit times between nodes.

This work provides prescriptive details to military analysts and decision-makers in a timely manner. Prior to this work, insights for this type of problem were generated using time-consuming simulation taking about a week and often involving trial-and-error.

This research provides new methods to solve an important logistics problem. The heuristic presented in this paper was recently used to provide operational insights about ground vehicle requirements to support a geographic combatant command and to inform decisions for railcar recapitalization within the US Army.

The volumes of international containerized trade substantially increased over the past years. In the meantime, marine container terminal (MCT) operators are facing congestion issues at their terminals because of the increasing number of large-size vessels, the lack of innovative technologies and advanced handling equipment and the inability of proper scheduling of the available resources. This study aims to propose a novel memetic algorithm with a deterministic parameter control to facilitate the berth scheduling at MCTs and minimize the total vessel service cost.

A local search heuristic, which is based on the first-come-first-served policy, is applied at the chromosomes and population initialization stage within the developed memetic algorithm (MA). The deterministic parameter control strategy is implemented for a custom mutation operator, which alters the mutation rate values based on the piecewise function throughout the evolution of the algorithm. Performance of the proposed MA is compared with that of the alternative solution algorithms widely used in the berth scheduling literature, including a MA that does not apply the deterministic parameter control strategy, typical evolutionary algorithm, simulated annealing and variable neighborhood search.

Results demonstrate that the developed MA with a deterministic parameter control can obtain superior berth schedules in terms of the total vessel service cost within a reasonable computational time. Furthermore, greater cost savings are observed for the cases with high demand and low berthing capacity at the terminal. A comprehensive analysis of the convergence patterns indicates that introduction of the custom mutation operator with a deterministic control for the mutation rate value would provide more efficient exploration and exploitation of the search space.

This study does not account for uncertainty in vessel arrivals. Furthermore, potential changes in the vessel handling times owing to terminal disruptions are not captured.

The developed solution algorithm can serve as an efficient planning tool for MCT operators and assist with efficient berth scheduling for both discrete and continuous berthing layout cases.

The majority of studies on berth scheduling rely on the stochastic search algorithms without considering the specific problem properties and applying the guided search heuristics. Unlike canonical evolutionary algorithms, the developed algorithm uses a local search heuristic for the chromosomes and population initialization and adjusts the mutation rate values based on a deterministic parameter control strategy for more efficient exploration and exploitation of the search space.

The purpose of this paper is to investigate the impact of shipyard and shipowner heterogeneity on the price formation for individual newbuilding contracts.

The model controls for the shipbuilding market cycle, input costs, firm size, yard experience and contract-specific variables and captures the impact of yard and owner heterogeneity in fixed-effects regressions. The data sample contains contract information on 3,759 tankers, bulkers and container vessels constructed at 77 shipyards between 1990 and 2014.

Although the newbuilding price benchmarks (market conditions) and gross domestic product per capita (salary costs) are influential covariates, the main conclusion is that shipyards and, particularly, shipowners play an influential role on the US$ per Compensated Gross Tonnage price level in individual contracts.

The paper represents the first study of the impact of buyer and seller heterogeneity at the micro level in the shipbuilding market.

The purpose of this paper is to move beyond individual level characteristics of founders to explain the performance gap between white and black majority owned new ventures. It specifically investigates three potential mediators: demographic characteristics of venture’s location, financial size of the venture and its credit riskiness.

The Kauffman Firm Survey, a longitudinal data set of 4,928 new ventures started in the USA in 2004, has been utilized in this paper. Pooled OLS and Logit regression models were employed for direct effects. Mediation effects were tested using two different approaches: the Baron and Kenny approach and decomposition analysis.

The paper finds that the financial size and credit riskiness mediate the relationship between majority race ownership and the performance of a venture.

The data were collected for a single cohort (2004) of nascent firms; furthermore, the sample draws from firms based in the USA. Future studies could replicate this research utilizing samples of different cohorts and from other parts of the world.

The paper provides important guidance to policy makers. In general, to reduce the performance gap between black and white owned ventures, providing access to subsidized assets, capital and credit could be very helpful.

Past research suggests that the majority race ownership of a new venture impacts its performance and attributes these differences to heterogeneous endowments, usually of the primary owner. In this paper, analyses are conducted at multiple levels and new mechanisms through which the internal resources and capabilities of a new venture mediate the relation are discovered.

This paper aims to examine containership routing and speed optimization for maritime liner services. It focuses on a realistic case in which the transport demand, and consequently the collected revenue from the visited ports depend on the sailing speed.

The authors present an integer non-linear programming model for the containership routing and fleet sizing problem, in which the sailing speed of every leg, the ports to be included in the service and their sequence are optimized based on the net line's profit. The authors present a heuristic approach that is based on speed discretization and a genetic algorithm to solve the problem for large size instances. They present an application on a line provided by COSCO in 2017 between Asia and Europe.

The numerical results show that the proposed heuristic approach provides good quality solutions after a reasonable computation time. In addition, the demand sensitivity has a great impact on the selected route and therefore the profit function. Moreover, the more the demand is sensitive to the sailing speed, the higher the sailing speed value.

The vessel carrying capacity is not considered in an explicit way.

This paper focuses on an important aspect in liner shipping, i.e. demand sensitivity to sailing speed. It brings a novel approach that is important in a context in which sailing speed strategies and market volatility are to be considered together in network design. This perspective has not been addressed previously.

Marine transportation has been faced with an increasing demand for containerized cargo during the past decade. Marine container terminals (MCTs), as the facilities for connecting seaborne and inland transportation, are expected to handle the increasing amount of containers, delivered by vessels. Berth scheduling plays an important role for the total throughput of MCTs as well as the overall effectiveness of the MCT operations. This study aims to propose a novel island-based metaheuristic algorithm to solve the berth scheduling problem and minimize the total cost of serving the arriving vessels at the MCT.

A universal island-based metaheuristic algorithm (UIMA) was proposed in this study, aiming to solve the spatially constrained berth scheduling problem. The UIMA population was divided into four sub-populations (i.e. islands). Unlike the canonical island-based algorithms that execute the same metaheuristic on each island, four different population-based metaheuristics are adopted within the developed algorithm to search the islands, including the following: evolutionary algorithm (EA), particle swarm optimization (PSO), estimation of distribution algorithm (EDA) and differential evolution (DE). The adopted population-based metaheuristic algorithms rely on different operators, which facilitate the search process for superior solutions on the UIMA islands.

The conducted numerical experiments demonstrated that the developed UIMA algorithm returned near-optimal solutions for the small-size problem instances. As for the large-size problem instances, UIMA was found to be superior to the EA, PSO, EDA and DE algorithms, which were executed in isolation, in terms of the obtained objective function values at termination. Furthermore, the developed UIMA algorithm outperformed various single-solution-based metaheuristic algorithms (including variable neighborhood search, tabu search and simulated annealing) in terms of the solution quality. The maximum UIMA computational time did not exceed 306 s.

Some of the previous berth scheduling studies modeled uncertain vessel arrival times and/or handling times, while this study assumed the vessel arrival and handling times to be deterministic.

The developed UIMA algorithm can be used by the MCT operators as an efficient decision support tool and assist with a cost-effective design of berth schedules within an acceptable computational time.

A novel island-based metaheuristic algorithm is designed to solve the spatially constrained berth scheduling problem. The proposed island-based algorithm adopts several types of metaheuristic algorithms to cover different areas of the search space. The considered metaheuristic algorithms rely on different operators. Such feature is expected to facilitate the search process for superior solutions.

Marketing orientation refers to a culture in which organizations strive to create superior value for their customers (and superior performance for the business) by focusing on customer needs and long-term profitability. Some studies have found that firms with a high degree of marketing orientation experience improved performance; others have found mixed or nonsignificant results. The marketing orientation of small businesses has not been thoroughly investigated, however. This study of more than 200 small business CEOs examines the marketing orientation levels of small to medium-sized firms (SMEs) as well as the impact of various internal variables (sales/profit performance, company characteristics, and CEO characteristics) on marketing orientation levels. The results confirm some earlier research on marketing orientation and provide new insights into this important strategic dimension.