Challenges of Transporting Goods through Sub-Saharan Africa by David on June 8, Even at the best of times there are many challenges that those involved in the road freight and logistics industry must confront when chartering territory in Africa.
A sample of possible research topics in this area is presented below. In addition to the following sample topics, please contact us at consulting etcoindia.
The concept of demand forecasting is diminishing as more and more companies are now focusing on getting accurate and timely demand information rather than depending upon forecasts.
This is carried out by effective integration of information from all the nodes of the supply chain and disseminating upstream as well as downstream.
However, there are many industries that will continue to depend upon push strategy and demand forecasting. The students Thesis transportation of goods like to study about the drawbacks of traditional forecasting methods like time series forecasting, moving averages, trend analysis, etc.
Many companies want to incorporate real time data in their forecasting models and focus on forecasting for shorter periods. This requires lots of additional knowledge over and above the traditional ways of working upon past demand data.
The modern forecasting models may be based on accurate knowledge of customer segments, major factors that influence forecasting accuracy, information integration, bullwhip effect, scenario planning, simulations, external factors, risks, and causal Fishbone or Ishikawa analysis.
Most of the studies may be qualitative or triangulated. Aggregation is carried out by a company to determine the levels of pricing, capacity, production, outsourcing, inventory, etc.
Aggregation planning helps in consolidation of the internal and external stock keeping units SKUs within the decision and strategic framework for reducing costs, meeting demands and maximising profits.
It may be viewed as the next step of either demand forecasting push strategy or demand information accumulation pull strategy for carrying out estimations of the inventory level, internal capacity levels, outsourced capacity levels, workforce levels, and production levels required in a specified time period.
Aggregation planning in modern supply chains is carried out using advanced planning tools comprising of 2D layout maps, 3D spatial maps, structural maps, data association with map items, spatial data mining, location-aware data mining, analytical hierachy planning, etc.
The students may like to conduct qualitative case studies and modeling-based quantitative studies to research about modern practices of aggregation planning in various industrial and retail sectors.
I Global Supply Chains: In the modern world, suppliers in a country are facing direct competition from international suppliers as if the latter are operating within the country. This has happened due to modernization of information management and dissemination, supply routes, payment channels, electronic contracts, leading to improved reliability and reduced lead times of international suppliers.
E-Supply Chains are linked with E-Businesses that use Internet as their medium for accepting orders and payments, and then using the physical channels to deliver the products. E-supply chain is an excellent example of pull strategy and short term demand forecasting.
Information flow across the supply chain is instantaneous because both end points and the intermediate agents work through a single Internet enabled portal. E-Bay and Amazon are viewed as the two most successful companies using this concept at global scales with built-in electronic contract signing and management, electronic payment processing, and electronic delivery processing.
The students can find various case studies on E-Supply chains, although the empirical theories are still evolving. The research studies would be quite challenging, modern and unique as the field is still evolving.
K Supply Chain Risk Management: Supply chain risk management is gaining immense popularity due to globalization of competitive landscapes, and growing threats and uncertainty. Risk management in supply chains is directly linked with supply chain agility and hence it needs to be done in very organized and objective manner, incorporating quantitative models.
The root of the problems lie somewhere in the uncertainties in upstream as well as downstream flows of materials, funds, and information.
For example, if there are errors in calculating economic order quantities EOQ and reorder levels, the ordering process may not synchronize well with the lead-times. On the other hand, the lead-times are uncertain due to various delay factors and fluctuation in costs if a transportation mode is changed.
Holding inventory is the safest haven for logistics managers, but I am sure the top management of any organisation will never like it.
The primary purpose of this subject matter is to keep lowest possible inventories while ensuring consistent, timely, and accurate supplies to the end users. The challenges are in the following areas: You will appreciate, supply chain risk is also a floating entity just like materials, funds and information.
If the entire chain is integrated through an extranet portal system, and updates of every consignment code are uploaded periodically by all agents connected with the portal, there can be proactive risks generated by the software for the logistics managers such that they can take operating level, tactical level, and even strategic level mitigation actions.
Although such a system is still in its conceptual stage, academic researchers can contribute to its overall conceptualisation and design. It may be integrated as a layer above the traditional SCM software. An agent sensing any variations in delay or cost may log a threat and its probability against a consignment code.Another issue is return of load cargo in Sub-Saharan Africa; if you have an empty return leg these costs must be sufficiently factored into the price of moving the goods.
At the same time the costing must be reasonable in order to remain competitive. Angola is again a good example where the probability of one way movement of goods is very high.
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