Abstract: Factors related to the growth of fashion and textile manufacturing in the Sub-Saharan African (SSA) countries are analyzed in this paper. Important factors associated with the growth of fashion and textile manufacturing in the SSA countries are being identified, underlined, and evaluated in this study. This research performed a SWOT analysis of the garment industries in the SSA region by exploring into various literature in the garment manufacturing and export data. SSA countries need to grow a lot in the fashion and textile manufacturing and export to come in par with the developments in the sector globally. Unlike the developing countries such as Vietnam and Bangladesh, the total export to the US, the EU and other parts of the world has declined. On the other hand, the total supply of fashion and textiles to the domestic market has been in rise. However, the local communities still need to rely on other countries to meet their demand. Import of cheaper clothes from countries like Bangladesh China and Vietnam is one of the main challenges local manufacturers are facing as it is very difficult to be competitive in pricing.
Abstract: For many enterprises, the delocalization of a part or the totality of their supply chain to low cost countries is the best way to reduce costs and remain competitive against the growing globalized market. This new tendency is driven by logistics advantages, as well as, financial and tax discount offered by the host countries. The objective of this article is to examine the new financial challenges introduced by the project of base erosion and profits shifting (BEPS), published in 2015, and also their impact on the decision of delocalization. In fact, the strategy adopted by multinational firms for determining the transfer price (TP) of goods and services, as well as the shared amount of revenues and expenses have a major impact upon group profit and may contribute to divergent results. In order to get more profit, a coherent decision of delocalization should be based on an evaluation of all the operational and financial characteristics associated with such movement. Therefore, it is interesting to model these new constraints and integrate them in a more global decision model. The established model will enable to measure how much these financial constraints impact the decision of delocalization and will give new helpful directives for enterprise managers.
Abstract: With a continuously increasing speed of information exchange on the World Wide Web, retailers in the E-Commerce sector are faced with immense possibilities regarding different online purchase processes like dynamic price settings. By use of Dynamic Pricing, retailers are able to set short time price changes in order to optimize producer surplus. The empirical research illustrates the basics of Dynamic Pricing and identifies six influencing factors of Dynamic Pricing. The results of a structural equation modeling approach show five main drivers increasing the potential of dynamic price settings in the E-Commerce. Influencing factors are the knowledge of customers’ individual willingness to pay, rising sales, the possibility of customization, the data volume and the information about competitors’ pricing strategy.
Abstract: The demand for Urban transportation is characterised by a large scale temporal and spatial variations which causes heavy congestion inside metro trains in peak hours near Centre Business District (CBD) of the city. The conventional approach to address peak hour congestion, metro trains has been to increase the supply by way of introduction of more trains, increasing the length of the trains, optimising the time table to increase the capacity of the system. However, there is a limitation of supply side measures determined by the design capacity of the systems beyond which any addition in the capacity requires huge capital investments. The demand side interventions are essentially required to actually spread the demand across the time and space. In this study, an attempt has been made to identify the potential Transport Demand Management tools applicable to Urban Rail Transportation systems with a special focus on differential pricing. A conceptual price elasticity model has been developed to analyse the effect of various combinations of peak and nonpeak hoursfares on demands. The elasticity values for peak hour, nonpeak hour and cross elasticity have been assumed from the relevant literature available in the field. The conceptual price elasticity model so developed is based on assumptions which need to be validated with actual values of elasticities for different segments of passengers. Once validated, the model can be used to determine the peak and nonpeak hour fares with an objective to increase overall ridership, revenue, demand levelling and optimal utilisation of assets.
Abstract: This study examines the credibility of the signaling as
explanation for IPO initial underpricing. Findings reveal the initial
underpricing and the long-term underperformance of IPOs in Taiwan.
However, we only find weak support for signaling as explanation of
IPO underpricing.
Abstract: Fine-grained data replication over the Internet allows duplication of frequently accessed data objects, as opposed to entire sites, to certain locations so as to improve the performance of largescale content distribution systems. In a distributed system, agents representing their sites try to maximize their own benefit since they are driven by different goals such as to minimize their communication costs, latency, etc. In this paper, we will use game theoretical techniques and in particular auctions to identify a bidding mechanism that encapsulates the selfishness of the agents, while having a controlling hand over them. In essence, the proposed game theory based mechanism is the study of what happens when independent agents act selfishly and how to control them to maximize the overall performance. A bidding mechanism asks how one can design systems so that agents- selfish behavior results in the desired system-wide goals. Experimental results reveal that this mechanism provides excellent solution quality, while maintaining fast execution time. The comparisons are recorded against some well known techniques such as greedy, branch and bound, game theoretical auctions and genetic algorithms.
Abstract: The goal of this paper is to develop a model to
integrate “pricing" and “advertisement" for short life cycle products,
such as branded fashion clothing products. To achieve this goal, we
apply the concept of “Dynamic Pricing". There are two classes of
advertisements, for the brand (regardless of product) and for a
particular product. Advertising the brand affects the demand and
price of all the products. Thus, the model considers all these products
in relation with each other. We develop two different methods to
integrate both types of advertisement and pricing. The first model is
developed within the framework of dynamic programming. However,
due to the complexity of the model, this method cannot be applicable
for large size problems. Therefore, we develop another method,
called hieratical approach, which is capable of handling the real
world problems. Finally, we show the accuracy of this method, both
theoretically and also by simulation.
Abstract: In this paper a new approach for transmission pricing
is presented. The main idea is voltage angle allocation, i.e.
determining the contribution of each contract on the voltage angle of
each bus. DC power flow is used to compute a primary solution for
angle decomposition. To consider the impacts of system non-linearity
on angle decomposition, the primary solution is corrected in different
iterations of decoupled Newton-Raphson power flow. Then, the
contribution of each contract on power flow of each transmission line
is computed based on angle decomposition. Contract-related flows
are used as a measure for “extent of use" of transmission network
capacity and consequently transmission pricing. The presented
approach is applied to a 4-bus test system and IEEE 30-bus test
system.
Abstract: Unlike this study focused extensively on trading
behavior of option market, those researches were just taken their
attention to model-driven option pricing. For example, Black-Scholes
(B-S) model is one of the most famous option pricing models.
However, the arguments of B-S model are previously mentioned by
some pricing models reviewing. This paper following suggests the
importance of the dynamic character for option pricing, which is also
the reason why using the genetic algorithm (GA). Because of its
natural selection and species evolution, this study proposed a hybrid
model, the Genetic-BS model which combining GA and B-S to
estimate the price more accurate. As for the final experiments, the
result shows that the output estimated price with lower MAE value
than the calculated price by either B-S model or its enhanced one,
Gram-Charlier garch (G-C garch) model. Finally, this work would
conclude that the Genetic-BS pricing model is exactly practical.