Inventory Management with Raw Materials Costs Subject to Quotation: The Analysis of the Jewellery Industry

This thesis has the objective to present the particular inventory management problem in case of procurement of raw materials subject to quotation, a subject that goes beyond traditional stock control policies proposed by literature, where purchase price is typically assumed as a constant and therefore not even considered in the decision of when and how much to order

Evaluation of production control strategies for the co-ordination of work-authorisations and inventory management in lean supply chains

A decision support framework is proposed for assisting managers and executives to possibly utilise lean production control strategies to coordinate work authorisations and inventory management in supply chains. The framework allows decision makers to evaluate and compare the suitability of various strategies to their system especially when considering conflicting objectives, such as maximising customer service levels while minimising Work in Process (WIP) in a business environment distressed by variabilities and uncertainties in demand stemmed from customer power. Also, the framework provides decision guidance in selecting and testing optimal solutions of selected policies control parameters. The framework is demonstrated by application to a four-node serial supply-chain operating under three different pull-based supply chain strategies; namely CONWIP, Kanban, and Hybrid Kanban-CONWIP and exhibiting low, medium, and high variability in customer demand (i.e., coefficient of variation of 25%, 112.5%, and 200%). The framework consists of three phases; namely Modelling, Optimisation and Decision Support; and is applicable to both Simulation-Based and Metamodel-Based Optimisation. The Modelling phase includes conceptual modelling, discrete event simulation modelling and metamodels development. The Optimisation phase requires the application of multi-criteria optimisation methods to generate WIP-Service Level trade-off curves. The Curvature and Risk Analysis of the trade-off curves are utilised in the Decision Support phase to provide guidance to the decision maker in selecting and testing the best settings for the control parameters of the system. The inflection point of the curvature function indicates the point at which further increases in Service Level are only achievable by incurring an unacceptably higher cost in terms of average WIP. Risk analysis quantifies the risk associated with designing a supply chain system under specific environmental parameters. This research contributes an efficient framework that is applicable to solve real supply chain problems and better understanding of the potential impacts and expected effectiveness of different pull control mechanisms, and offers valuable insights on future research opportunities in this field to production and supply chain managers

An Inquiry into Supply Chain Strategy Implications of the Sharing Economy for Last Mile Logistics

As the prevalence of e-commerce and subsequent importance of effective and efficient omnichannel logistics strategies continues to rise, retail firms are exploring the viability of sourcing logistics capabilities from the sharing economy. Questions arise such as, “how can crowdbased logistics solutions such as crowdsourced logistics (CSL), crowdshipping, and pickup point networks (PPN) be leveraged to increase performance?” In this dissertation, empirical and analytical research is conducted that increases understanding of how firms can leverage the sharing economy to increase logistics and supply chain performance. Essay 1 explores crowdsourced logistics (CSL) by employing a stochastic discrete event simulation set in New York City in which a retail firm sources drivers from the crowd to perform same day deliveries under dynamic market conditions. Essay 2 employs a design science paradigm to develop a typology of crowdbased logistics strategies using two qualitative methodologies: web content analysis and Delphi surveys. A service-dominant logic theoretical perspective guides this essay and explains how firms co-create value with the crowd and consumer markets while presenting a generic design for integrating crowdbased models into logistics strategy. In Essay 3, a crowdsourced logistics strategy for home delivery is modeled in an empirically grounded simulation optimization to explore the logistics cost and responsiveness implications of sharing economy solutions on omnichannel fulfillment strategies

Values of blockchain for risk-averse high-tech manufacturers under government’s carbon target environmental taxation policies

AbstractToday, high-tech industries such as consumer electronics commonly face government rules on carbon emissions. Among the rules, carbon emission tax as well as extended producer responsibility (EPR) tax are two important measures. Using blockchain, the policy makers can better determine the carbon target environmental taxation (CTET) policy with accurate information. In this paper, based on the mean-variance framework, we study the values of blockchain for risk-averse high-tech manufacturers who are under the government’s CTET policy. To be specific, the government first determines the optimal CTET policy. The high-tech manufacturer then reacts and determines its optimal production quantity. We analytically prove that the CTET policy simply relies on the setting of the optimal EPR tax. Then, in the absence of blockchain, we consider the case in which the government does not know the manufacturer’s degree of risk aversion for sure and then derive the expected value of using blockchain for the high-tech manufacturers. We study when it is wise for the high-tech manufacturer and the government to implement blockchain. To check for robustness, we consider in two extended models respectively the situations in which blockchain incurs non-trivial costs as well as having an alternative risk measure. We analytically show that most of the qualitative findings remain valid.</jats:p

Are We Sick Yet: Assessing Consumer Mortality From Food Contamination In Multiple Distribution Channels

According to the Center for Disease Control approximately 48 million people get sick from food-borne illnesses per year. In 2011, about 80% of illnesses were triggered by unspecified agents transmitted through food. Food contaminations put customers at risk and can be detrimental to the economy since customers rely on the fact that the food system is reliable and resilient. This research aims to compare the vulnerabilities of three food supply chain distribution channels: food retail, food service and food manufacturing. Distribution channels are the last nodes in the supply chain and they dictate how many people interact with contaminated products. This study will evaluate how many people are exposed to illness from an intentional chemical contamination. A discrete time Markov Chain with rewards model is developed to estimate the number of individuals to become ill given a successful attack on the food system. The model incorporates information on purchasing behavior, product shelf life, and the relationship between individual contaminant consumption and illness. Preliminary results show that more customers are expected to experience illness when purchasing from food retail and food service locations. However, food manufacturing has the shortest time frame for imposing an intervention to prevent further illness. The proposed research has the potential to provide insight into timely interventions and influence how intervention policies would need to be tailored to each distribution channel in the event that a chemical contamination occurs

Optimizing a Time-Sensitive Supply Chain with a Power Function Penalty Cost

In a cost-based supply chain delivery performance model, accurately depicting the penalty cost associated with an untimely delivery is an important component of the supply chain’s delivery performance. This paper introduces a two-stage time-sensitive supply chain, where the penalty cost caused by early and late delivery is treated as a power function of the default time. This default time is the deviation in time from the actual delivery time to the delivery window. Both the buyer and the supplier want to reduce the default time. After considering the product’s value over time and the buyers’ attitude with respect to a breach of contract, the penalty cost is constructed as the product of a nonlinear function of default time and as a linear function of the penalty factor. This yields the conditions associated with the optimal delivery window, to minimize the expected penalty with the power function. The paper shows the effect of the delivery window, penalty factor, and time sensitivity factor on supply chain performance, leading to recommendations for improved performance. Numerical results are provided to demonstrate the applicability of the proposed model. The model helps buyers more accurately determine costly losses, enabling them to reduce the impact of any default caused by suppliers. For exponentially distributed lead time, choosing the optimal delivery window position for delivery can reduce the expected penalty cost by as much as seven times. The average delivery time is shortened from 30 days to 20 days, and the expected penalty cost will be reduced by about 50%. This is a powerful tool for use in improving supply chain performance and also provides directions for improving strategies and a theoretical basis for buyers and suppliers wanting to jointly optimize supply chain performance

Factors influencing demand forecasting and demand planning: a case at an apparel retailer.

Masters Degree. University of KwaZulu-Natal, Pietermaritzburg.As supply chains and distribution channels extend globally and fashion trends become more controlled by media, customers are not only influenced to change their minds overnight about offerings but also organisations are pushed to become more flexible and agile with regard to efficient planning and forecasting for demand. Today’s supply chain management is successful when it involves the understanding and management of inventory, the complete satisfaction of the ultimate customer and also the delivery of the right quantity of product to various destinations at a faster rate. The business environment has become highly competitive and complex as customers’ demands have become significantly variable, thus pressuring organisations to invest in better demand forecasting and planning tools in order to become more responsive to these demands. The dynamics of the business environment has become one of the main challenges in the planning and forecasting of demand in apparel supply chains. Such supply chains are affected by external and internal factors such technological advancement, globalisation, economic factors, environmental unpredictability, political and legal matters, social issues, poor internal and external collaboration in the supply chains, and the supply chain structures influencing the performance of organisations in the market. This study aims at identifying the impact that each of these factors have on the apparel industry. Each factor was analysed to determine the impact on the forecasting and planning of demand in the apparel industry. The findings are based on a case study that was conducted with one of the biggest apparel retailers in South Africa, namely, Apparel Retailer A. The results of the research reveal that the factors mentioned have a more negative than positive impact on the planning and forecasting of demand within apparel organisations. It was found that Apparel Retailer A needed to invest in better collaboration systems (that allow for real time replenishment) with its supply chain partners in order to be more responsive to the unexpected changes that the organisation consistently experiences in the industry. Furthermore, participants indicated: a need to maintain consistency in the areas where the organisation was well-equipped; a need to invest in a more agile and sustainable supply chain due to the massive growth of competition in the market; and, most importantly, a need to build strategic relationships with the organisation’s supply chain partners, thus allowing the organisation to plan and forecast better for future demand

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications