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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.

This article advocates that networking is an inherent tool of marketing that is wholly compatible with entrepreneurial decision-making characteristics in relation to marketing activities in SMEs.

The rapid growth in cruise shipping coupled with increasing public awareness of climate change has led to increasing concerns about the impact cruise shipping poses on the environment, especially regarding air emissions. This study analyses the cruise shipping network of ports in and around the emission control areas (ECAs) to understand the structural properties of the network and ports.

A complex network approach was used to analyse the network data of 239 voyages serviced by 14 international cruise lines, visiting 127 ports across 44 countries in the Caribbean Sea.

It is found that the network has a small-world property with a short average path length and a high clustering coefficient. The regulations affect connections among ports, in which most ports in ECAs have lower connections than ports outside ECAs. A few ports in ECAs play important key roles, but many ports outside ECAs play a more important role in the network because the regulations are barriers for cruise ships entering the ports.

The findings of this study have drawn useful guidelines for cruise lines and port authorities to improve their operations. Constrictive recommendations are suggested to policymakers for designing reasonable regulations to attract more cruise shipping to travel in ECAs.

The study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns.

This work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network.

This research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance.

This research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity and post-processing requirements.

This research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.

This paper introduces a new heuristic algorithm that aims to solve the military route vulnerability problem, which involves assessing the vulnerability of military cargo flowing over roads and railways subject to enemy interdiction.

Graph theory, a heuristic and a binary integer program are used in this paper.

This work allows transportation analysts at the United States Transportation Command to identify a relatively small number of roads or railways that, if interdicted by an enemy, could disrupt the flow of military cargo within any theater of operation.

This research does not capture aspects of time, such as the reality that cargo requirements and enemy threats may fluctuate each day of the contingency.

This work provides military logistics planners and decision-makers with a vulnerability assessment of theater distribution routes, including insights into which specific roads and railways may require protection to ensure the successful delivery of cargo from ports of debarkation to final destinations.

This work merges network connectivity and flow characteristics with enemy threat assessments to identify militarily-useful roads and railways most vulnerable to enemy interdictions. A geographic combatant command recently used this specific research approach to support their request for rapid rail repair capability.

Supply chains need to balance competing objectives; in addition to efficiency, supply chains need to be resilient to adversarial and environmental interference and robust to uncertainties in long-term demand. Significant research has been conducted designing efficient supply chains and recent research has focused on resilient supply chain design. However, the integration of resilient and robust supply chain design is less well studied. The purpose of the paper is to include resilience and robustness into supply chain design.

The paper develops a method to include resilience and robustness into supply chain design. Using the region of West Africa, which is plagued with persisting logistical issues, the authors develop a regional risk assessment framework and then apply categorical risk to the countries of West Africa using publicly available data. A scenario reduction technique is used to focus on the highest risk scenarios for the model to be tractable. Next, the authors develop a mathematical model leveraging this framework to design a resilient supply network that minimizes cost while ensuring the network functions following a disruption. Finally, the authors examine the network's robustness to demand uncertainty via several plausible emergency scenarios.

The authors provide optimal sets of transshipment hubs with varying counts from 5 through 15 hubs. The authors determine there is no feasible solution that uses only five transshipment hubs. The authors' findings reinforce those seven transshipment hubs – the solution currently employed in West Africa – is the cheapest architecture to achieve resilience and robustness. Additionally, for each set of feasibility transshipment hubs, the authors provide connections between hubs and demand spokes.

While, at the time of this research, three other manuscripts incorporated both resilience and robustness of the authors' research unique solved the problem as a network flow instead of as a set covering problem. Additionally, the authors establish a novel risk framework to guide the required amount of redundancy, and finally the out research proposes a scenario reduction heuristic to allow tractable exploration of 512 possible demand scenarios.

This study aims to identify the characteristics of the maritime shipping network in Northeast Asia as well as compare the level of port connectivity among these container ports in the region. In addition, this study analyses the change in role and position of 20 ports in the region by clustering these ports based on connectivity index and container throughput and route index.

This study employs Social Network Analysis (SNA) to delineate the international connectivity of major container ports in Northeast Asia. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to identify each port's connectivity index and container throughput index, and the resulting indexes are employed as the basis to cluster 20 major ports by fuzzy C-mean (FCM).

The results revealed that Northeast Asia is a highly connected maritime shipping network with the domination of Shanghai, Shenzhen, Hong Kong and Busan. Furthermore, both container throughput and connectivity in almost all container ports in the region have decreased significantly due to the coronavirus disease 2019 (COVID-19) pandemic. The rapid growth of Shenzhen and Ningbo has allowed them to join Cluster 1 with Shanghai while maintaining high connectivity, yet decreasing container throughput has pushed Busan down to Cluster 2.

The originality of this study is to combine indexes of SNA into connectivity index reflecting characteristics of the maritime shipping network in Northeast Asia and categorize 20 major ports by FCM.

The use of queueing network models was stimulated by the appearance (1975) of the exact product form solution of a class of open, closed and mixed queueing networks obeying the local balance principle and solved, a few years later, by the popular mean value analysis algorithm (1980). Since then, research efforts have been produced to approximate solutions for non-exponential services and non-pure random mechanisms in customer processing and routing. The purpose of this paper is to examine the suitability of modeling choices and solution approaches consolidated in other domains with respect to two key logistic processes in container terminals.

In particular, the analytical solution of queueing networks is assessed for the vessel arrival-departure process and the container internal transfer process with respect to a real terminal of pure transshipment.

Numerical experiments show the extent to which a decomposition-based approximation, under fixed or state-dependent arrival rates, may be suitable for the approximate analysis of the queueing network models.

The limitation of adopting exponential service time distributions and Poisson flows is highlighted.

Comparisons with a simulation-based solution deliver numerical evidence on the companion use of simulation in the daily practice of managing operations in a finite-time horizon under complex policies.

Discussion of some open modeling issues and encouraging results provide some guidelines on future research efforts and/or suitable adaption to container terminal logistics of the large body of techniques and algorithms available nowadays for supporting long-run decisions.

One key determinant of entrepreneurial success is entrepreneurial self-efficacy (ESE), defined as an individual’s confidence in his or her ability to perform entrepreneurial tasks. Whereas previous research has examined how individual and business factors influence ESE, the purpose of this paper is to analyze the influence of entrepreneurs’ social networks upon ESE. The paper examines such relationships for black and white entrepreneurs.

In total, 110 black and white entrepreneurs responded to a survey measuring ESE and critical constructs representing elements of the quality of entrepreneurs’ networks: emotional carrying capacity (ECC) and network ethnic diversity.

The authors found significant, positive relationships between both ECC and network ethnic diversity on ESE for white entrepreneurs but only found a significant positive relationship between ECC and ESE for black entrepreneurs.

While research is clear about the role that ESE plays in entrepreneurial activities, few studies have focused on the factors that improve ESE. In the present work, the authors study the role of context by examining how entrepreneurs’ social networks influence ESE. The authors examine such influences for both white and black entrepreneurs to better understand the implications of ethnicity.

Research into entrepreneurial networking activities has ignored an aspect that is important to the entrepreneurs‐does it make sense to pay dues to an organization that promises networking opportunities to help build their business? This study looked at that aspect of networking by comparing revenue growth rates and average number of employees between those businesses whose owners belong to paid membership organizations and those who do not. No differences were found between the two groups of entrepreneurial firms. While there are still benefits to joining these organizations, entrepreneurs should not expect to grow their business because of membership.