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1 – 10 of over 1000Christos Kollias and Panayiotis Tzeremes
Using composite indices, the paper examines the nexus between militarization, globalization and liberal democracy. The democratic peace theory, the conflict inhibiting effects of…
Abstract
Purpose
Using composite indices, the paper examines the nexus between militarization, globalization and liberal democracy. The democratic peace theory, the conflict inhibiting effects of international trade – a key and dominant facet of globalization – and the democracy promoting globalization hypothesis form the theoretical underpinnings of the empirical investigation.
Design/methodology/approach
To probe into the issue at hand, the paper adopts a dynamic panel VAR estimation procedure. Given the usual data constraints, the sample consists of 113 countries, and the estimations span the period 1995–2019.
Findings
The findings from the dynamic panel VAR estimations suggest the presence of a negative and statistically significant nexus between the level of globalization and the level of militarization. No statistically traceable nexus between globalization and liberal democracy was found.
Research limitations/implications
The findings offer empirical support to the hypothesis that the strong links of interdependence shaped by globalization reduce the need for military preparedness. The results lead to a tentative inference in favor of the doux commerce thesis. Nonetheless, given that the estimations span a historically specific period – the entire post-bipolar era – the inferences that stem from the findings should be treated with caution.
Originality/value
To the best of the authors’ knowledge, the composite indices Bonn International Centre for Conflict Studies (BICC) militarization index, the globalization index of the Swiss Economic Institute (Konjunkturforschungsstelle) (KOF), LibDem, polyarchy have not hitherto been jointly used in previous studies to examine the nexus between militarization, globalization and liberal democracy.
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Freddy H. Marín-Sánchez, Julián A. Pareja-Vasseur and Diego Manzur
The purpose of this article is to propose a detailed methodology to estimate, model and incorporate the non-constant volatility onto a numerical tree scheme, to evaluate a real…
Abstract
Purpose
The purpose of this article is to propose a detailed methodology to estimate, model and incorporate the non-constant volatility onto a numerical tree scheme, to evaluate a real option, using a quadrinomial multiplicative recombination.
Design/methodology/approach
This article uses the multiplicative quadrinomial tree numerical method with non-constant volatility, based on stochastic differential equations of the GARCH-diffusion type to value real options when the volatility is stochastic.
Findings
Findings showed that in the proposed method with volatility tends to zero, the multiplicative binomial traditional method is a particular case, and results are comparable between these methodologies, as well as to the exact solution offered by the Black–Scholes model.
Originality/value
The originality of this paper lies in try to model the implicit (conditional) market volatility to assess, based on that, a real option using a quadrinomial tree, including into this valuation the stochastic volatility of the underlying asset. The main contribution is the formal derivation of a risk-neutral valuation as well as the market risk premium associated with volatility, verifying this condition via numerical test on simulated and real data, showing that our proposal is consistent with Black and Scholes formula and multiplicative binomial trees method.
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Dave C. Longhorn and John Dale Stobbs
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
This work helps analysts identify how many ground transport vehicles are needed to meet cargo delivery requirements in any military theater of operation.
Research limitations/implications
This research assumes all problem data is deterministic, so it does not capture variations in requirements or transit times between nodes.
Practical implications
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.
Originality/value
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.
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Dave C. Longhorn and Joshua R. Muckensturm
This paper aims to introduce a new mixed integer programming formulation and associated heuristic algorithm to solve the Military Nodal Capacity Problem, which is a type of supply…
Abstract
Purpose
This paper aims to introduce a new mixed integer programming formulation and associated heuristic algorithm to solve the Military Nodal Capacity Problem, which is a type of supply chain network design problem that involves determining the amount of capacity expansion required at theater nodes to ensure the on-time delivery of military cargo.
Design/methodology/approach
Supply chain network design, mixed integer programs, heuristics and regression are used in this paper.
Findings
This work helps analysts at the United States Transportation Command identify what levels of throughput capacities, such as daily processing rates of trucks and railcars, are needed at theater distribution nodes to meet warfighter cargo delivery requirements.
Research limitations/implications
This research assumes all problem data are deterministic, and so it does not capture the variations in cargo requirements, transit times or asset payloads.
Practical implications
This work gives military analysts and decision makers prescriptive details about nodal capacities needed to meet demands. Prior to this work, insights for this type of problem were generated using multiple time-consuming simulations often involving trial-and-error to explore the trade space.
Originality/value
This work merges research of supply chain network design with military theater distribution problems to prescribe the optimal, or near-optimal, throughput capacities at theater nodes. The capacity levels must meet delivery requirements while adhering to constraints on the proportion of cargo transported by mode and the expected payloads for assets.
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