Assessing the impact of infrastructure quality on firm productivity in Africa : cross-country comparisons based on investment climate surveys from 1999 to 2005

This paper provides a systematic, empirical assessment of the impact of infrastructure quality on the total factor productivity (TFP) of African manufacturing firms. This measure is understood to include quality in the provision of customs clearance, energy, water, sanitation, transportation, telecommunications, and information and communications technology (ICT). Microeconometric techniques to investment climate surveys (ICSs) of 26 African countries are carried out in different years during the period 2002–6, making country-specific evaluations of the impact of investment climate (IC) quality on aggregate TFP, average TFP, and allocative efficiency. For each country the impact is evaluated based on 10 different productivity measures. Results are robust once controlled for observable fixed effects (red tape, corruption and crime, finance, innovation and labor skills, etc.) obtained from the ICSs. African countries are ranked according to several indices: per capita income, ease of doing business, firm perceptions of growth bottlenecks, and the concept of demeaned productivity (Olley and Pakes 1996). The countries are divided into two blocks: high-income-growth and low-income-growth. Infrastructure quality has a low impact on TFP in countries of the first block and a high (negative) impact in countries of the second. There is significant heterogeneity in the individual infrastructure elements affecting countries from both blocks. Poor-quality electricity provision affects mainly poor countries, whereas problems dealing with customs while importing or exporting affects mainly faster-growing countries. Losses from transport interruptions affect mainly slower-growing countries. Water outages affect mainly slower-growing countries. There is also some heterogeneity among countries in the infrastructure determinants of the allocative efficiency of African firms.Transport Economics Policy&Planning,Economic Theory&Research,E-Business,Labor Policies,Infrastructure Economics

Assessing the impact of infrastructure quality on firm productivity in Africa: Cross-country comparisons based on investment climate surveys from 1999 to 2005

This paper provides a systematic, empirical assessment of the impact of infrastructure quality on the total factor productivity (TFP) of African manufacturing firms. This measure is understood to include quality in the provision of customs clearance, energy, water, sanitation, transportation, telecommunications, and information and communications technology (ICT). We apply microeconometric techniques to investment climate surveys (ICSs) of 26 African countries carried out in different years during the period 2002–6, making country-specific evaluations of the impact of investment climate (IC) quality on aggregate TFP, average TFP, and allocative efficiency. For each country we evaluated this impact based on 10 different productivity measures. Results are robust once we control for observable fixed effects (red tape, corruption and crime, finance, innovation and labor skills, etc.) obtained from the ICSs. We ranked African countries according to several indices: per capita income, ease of doing business, firm perceptions of growth bottlenecks, and the concept of demeaned productivity (Olley and Pakes 1996). We divided countries into two blocks: high-incomegrowth and low-income-growth. Infrastructure quality has a low impact on TFP in countries of the first block and a high (negative) impact in countries of the second. We found heterogeneity in the individual infrastructure elements affecting countries from both blocks. Poor-quality electricity provision affects mainly poor countries, whereas problems dealing with customs while importing or exporting affects mainly faster-growing countries. Losses from transport interruptions affect mainly slower-growing countries. Water outages affect mainly slower-growing countries. There is also some heterogeneity among countries in the infrastructure determinants of the allocative efficiency of African firms.Africa, Infrastructure, Total factor productivity, Investment climate, Competitiveness,

Loss systems in a random environment

We consider a single server system with infinite waiting room in a random environment. The service system and the environment interact in both directions. Whenever the environment enters a prespecified subset of its state space the service process is completely blocked: Service is interrupted and newly arriving customers are lost. We prove an if-and-only-if-condition for a product form steady state distribution of the joint queueing-environment process. A consequence is a strong insensitivity property for such systems. We discuss several applications, e.g. from inventory theory and reliability theory, and show that our result extends and generalizes several theorems found in the literature, e.g. of queueing-inventory processes. We investigate further classical loss systems, where due to finite waiting room loss of customers occurs. In connection with loss of customers due to blocking by the environment and service interruptions new phenomena arise. We further investigate the embedded Markov chains at departure epochs and show that the behaviour of the embedded Markov chain is often considerably different from that of the continuous time Markov process. This is different from the behaviour of the standard M/G/1, where the steady state of the embedded Markov chain and the continuous time process coincide. For exponential queueing systems we show that there is a product form equilibrium of the embedded Markov chain under rather general conditions. For systems with non-exponential service times more restrictive constraints are needed, which we prove by a counter example where the environment represents an inventory attached to an M/D/1 queue. Such integrated queueing-inventory systems are dealt with in the literature previously, and are revisited here in detail

Development of a robust and resilient Supply Chain System for selected companies in Gauteng

Abstract: These days, in the extremely competitive nature of business, nearly every big business has to reap the benefits of investing in improvements of its supply chain. The beginning of the upgrades is considered together with the examination concerning profits and most organisations have addressed measures that a supply chain execution and monitor changes in order to drive the benefits of their business. While execution estimation is basic, most organisations either measure excessively or pay little attention to supply chain. Different weaknesses may incorporate; an excessive number of measurements, disconnected measurements, clashing measurements, obsolete measurements, temperamental information, and absence of possession, among others. Some organisations measure incorrect variables in their pursuit of their objectives. This is detrimental to the realisation of these objectives and this affects the organisation. Framework estimations lead to improved framework. "Estimation is the initial step that prompts control and in the long run to progress. In the event that you can't gauge something, you can't get it. On the off chance that you can't get it, you can't control it. On the off chance that you can't control it, you can't improve it" (Harrington, 2012)...M.Ing. (Quality and Operations Management

An investigation into Indian apparel and textile supply chain networks

The activities of the Indian clothing industry supplying Western markets have been investigated, with particular reference to identifying where improvements could be made to supply chain management. Focus group discussions, case studies and questionnaire analysis established that long lead-times in pre-production areas were of great concern. However Indian apparel manufacturers were found to be more cost conscious and rather less conscious about the value of time in pre-production areas. It was found that pre-production activities constituted 73% of total manufacturing lead time and have high positive correlation (0.96) with total manufacturing lead time. Preproduction activities in India mainly consist of prototype making and pre-production sample development; of which approval processes were found to have a high correlation (0.63) with pre-production. A significant (more than 50%) time of all activities consist of waiting time, which has positive influence on total lead time (0.86)

Firm-Network Characteristics and Economic Robustness to Natural Disasters

This article proposes a theoretical framework to investigate economic robustness to exogenous shocks such as natural disasters. It is based on a dynamic model that represents a regional economy as a network of production units through the disaggregation of sectorscale Input-Output tables. Results suggest that disaster-related output losses depend on direct losses heterogeneity and on the economic network structure. Two aggregate indexes, concentration and clustering, appear as important drivers of economic robustness, offering opportunities for robustness-enhancing strategies. Modern industrial organization seems to reduce short-term robustness in a trade-off against higher efficiency in normal times.Natural disasters, Economic impacts, Economic Network.

A quantitative model for disruption mitigation in a supply chain

© 2016 Elsevier B.V. In this paper, a three-stage supply chain network, with multiple manufacturing plants, distribution centers and retailers, is considered. For this supply chain system we develop three different approaches, (i) an ideal plan for an infinite planning horizon and an updated plan if there are any changes in the data, (ii) a predictive mitigation planning approach for managing predictive demand changes, which can be predicted in advance by using an appropriate tool, and (iii) a reactive mitigation plan, on a real-time basis, for managing sudden production disruptions, which cannot be predicted in advance. In predictive mitigation planning, we develop a fuzzy inference system (FIS) tool to predict the changes in future demand over the base forecast and the supply chain plan is revised accordingly well in advance. In reactive mitigation planning, we formulate a quantitative model for revising production and distribution plans, over a finite future planning period, while minimizing the total supply chain cost. We also consider a series of sudden disruptions, where a new disruption may or may not affect the recovery plans of earlier disruptions and which consequently require plans to be revised after the occurrence of each disruption on a real-time basis. An efficient heuristic, capable of dealing with sudden production disruptions on a real-time basis, is developed. We compare the heuristic results with those obtained from the LINGO optimization software for a good number of randomly generated test problems. Also, some numerical examples are presented to explain both the usefulness and advantages of the proposed approaches