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A real-time in-memory discovery service : leveraging hierarchical packaging information in a unique identifier network to retrieve track and trace information
The research presented in this book discusses how to efficiently retrieve track and trace information for an item of interest that took a certain path through a complex network of manufacturers, wholesalers, retailers, and consumers. To this end, a super-ordinate system called \"Discovery Service\" is designed that has to handle large amounts of data, high insert-rates, and a high number of queries that are submitted to the discovery service. An example that is used throughout this book is the European pharmaceutical supply chain, which faces the challenge that more and more counterfeit medicinal products are being introduced. Between October and December 2008, more than 34 million fake drug pills were detected at customs control at the borders of the European Union. These fake drugs can put lives in danger as they were supposed to fight cancer, take effect as painkiller or antibiotics, among others. The concepts described in this book can be adopted for supply chain management use cases other than track and trace, such as recall, supply chain optimization, or supply chain analytics.
Book
Learning from Inventory Availability Information: Evidence from Field Experiments on Amazon
Many online retailers provide real-time inventory availability information. Customers can learn from the inventory level and update their beliefs about the product. Thus, consumer purchasing behavior may be impacted by the availability information. Based on a unique setting from Amazon lightning deals, which displays the percentage of inventory consumed in real time, we explore whether and how consumers learn from inventory availability information. Identifying the effect of learning on consumer decisions has been a notoriously difficult empirical question because of endogeneity concerns. We address this issue by running two randomized field experiments on Amazon in which we create exogenous shocks on the inventory availability information for a random subset of Amazon lightning deals. In addition, we track the dynamic purchasing behavior and inventory information for 23,665 lightning deals offered by Amazon and use their panel structure to further explore the relative effect of learning. We find evidence of consumers learning from inventory information: a decrease in product availability causally attracts more sales in the future; in particular, a 10% increase in past claims leads to a 2.08% increase in cart add-ins in the next hour. Moreover, we show that buyers use observable product characteristics to moderate their inferences when learning from others; a deep discount weakens the learning momentum, whereas a good product rating amplifies the learning momentum.
This paper was accepted by Serguei Netessine, operations management.
Journal Article
Getting a virtual forester fit for the challenge of climatic change
1. The empirical study of forest ecosystem dynamics is difficult because of the longevity of trees. Many types of models were developed to assist with this problem, all of them with advantages and disadvantages. The strengths of gap models are that they are able to simulate forest dynamics under changing climatic conditions and are therefore suitable for exploring future forest dynamics. 2. Most temperate and boreal forests are managed, making it important to incorporate harvesting functions depicting a wide range of silvicultural practices into the models and to test them under different climatic conditions. This is a necessary prerequisite to the application of these models under climatic change scenarios. Most gap models, however, do not feature such submodels, which disqualifies them as decision support tools. 3. We implemented a management submodel in the gap model ForClim that is able to simulate a wide range of cutting and thinning techniques, including continuous cover forestry ('plentering'). We tested the new submodel against long-term data (72-111 years) from eight growth and yield research plots across climatic conditions ranging from warm-dry to cold-wet. 4. Stem numbers were simulated accurately in nearly all cases, basal area showed a good fit on Qwercws-dominated plots, but an over/underestimation on Fagus sylvatica-dominated and Picea abies-dominated plots. The diameter distributions simulated for the time of the most recent inventory did not differ significantly from empirical data except for two cases. Harvested basal area and stem numbers mostly agreed well with empirical data, but showed the same deviation from reality as simulated basal area. 5. Simulations run with an accurate management plan taken from foresters' reports for the plots yielded nearly the same results as those run with a generic management setting. 6. Synthesis and applications. We have demonstrated that (i) the management submodel adequately depicts silvicultural treatments, including continuous cover forestry; (ii) a generic harvesting setting can be substituted for a very detailed one, thus eliminating a major source of uncertainty in assessments of future forest dynamics; and (iii) as the new version of ForClim is able to deal with widely differing current climates, it can be employed with reasonable confidence to simulate future management strategies under climatic change. Overall, this modelling work is a major step towards the use of succession models as decision support tools in forest management.
Journal Article
Parameter Uncertainty Analysis of the Life Cycle Inventory Database: Application to Greenhouse Gas Emissions from Brown Rice Production in IDEA
The objective of this paper is to develop a simple method for analyzing the parameter uncertainty of the Japanese life cycle inventory database (LCI DB), termed the inventory database for environmental analysis (IDEA). The IDEA has a weakness of poor data quality because over 60% of datasets in IDEA were compiled based on secondary data (non-site-specific data sources). Three different approaches were used to estimate the uncertainty of the brown rice production dataset, including the stochastic modeling approach, the semi-quantitative DQI (Data Quality Indicator) approach, and a modification of the semi-quantitative DQI approach (including two alternative approaches for modification). The stochastic modeling approach provided the best estimate of the true mean of the sample space and its results were used as the reference for comparison with the other approaches. A simple method for the parameter uncertainty analysis of the agriculture industry DB was proposed by modifying the beta distribution parameters (endpoint range, shape parameter) in the semi-quantitative DQI approach using the results from the stochastic modeling approach. The effect of changing the beta distribution parameters in the semi-quantitative DQI approach indicated that the proposed method is an efficient method for the quantitative parameter uncertainty analysis of the brown rice production dataset in the IDEA.
Journal Article
Non-instantaneous deterioration effect in ordering decisions for a two-warehouse inventory system under advance payment and backlogging
The process of deterioration may not start immediately after the consignment reaches the go down; there generally occurs a delay. In certain cases, deterioration might begin after a certain period which may further prolong due to the introduction of better methods of inventory management. To take into cognizance of these situations, in contrast to the ordinary assumption in the existing models, we have considered that the decay in owned warehouse begins earlier than that in case of rented warehouse as the latter always provides for better inventory management and facilities. Applying these phenomena, a two-storage inventory model has been formulated with advance payment under three different situations according to different possibilities of starting times of deterioration in both warehouses. In this model, demand depends upon the selling price wherein shortages are considered partially with fixed backlogging rate. Analyzing and investigating the proposed problem, three different optimization problems are formulated and the optimality of these problems is proved theoretically. To solve the model, an algorithm is proposed. Then, to illustrate the model numerically, an example is considered and solved. Finally, post optimality is performed in order to investigate the effects of changes of different system parameters.
Journal Article
Managing Perishable Inventories in Retailing: Replenishment, Clearance Sales, and Segregation
We study joint replenishment and clearance sales of perishable goods under a general finite lifetime and a last-in-first-out (LIFO) issuing rule, a problem common in retailing. We show that the optimal policies can be characterized by two thresholds for each age group of inventory: a lower one and a higher one. For an age group of inventory with a remaining lifetime of two periods or longer, if its inventory level is below its lower threshold, then there is no clearance sales; if it is above its higher threshold, then it will be cleared down to the higher threshold. The optimal policy for the age group of inventory with a one-period remaining lifetime is different. Clearance sales may occur if its inventory level is above its higher threshold or below its lower threshold. The phenomenon that a clearance sale happens when the inventory is low is driven by the need to segregate the newest inventory from the oldest inventory and is unique to the LIFO issuing rule. The optimal policy requires a full inventory record of every age group and its computation is challenging. We consider two myopic heuristics that require only partial information. The first requires only the information about the total inventory and the second requires the information about the total inventory as well as the information about the inventory with a one-period remaining lifetime. Our numerical studies show that the second outperforms the first significantly and its performance is consistently very close to that of the optimal policy.
Journal Article
Product Quality in a Distribution Channel with Inventory Risk
In many industries, product design and manufacturing lead times are sufficiently long that both the quality level of a product and the amount of inventory produced must be determined before a firm knows what the actual demand will be. In this paper, we conduct a theoretical analysis of such a setting. We first consider a centralized channel and characterize the optimal decisions by establishing relationships that must hold between the elasticity of cost of quality and the elasticity of revenue and show that quality and inventory are strategic substitutes. Next, we consider a decentralized channel with a wholesale price contract, in which a manufacturer determines quality and wholesale price, while a retailer determines inventory and retail price. We find that, different from the case without endogenous inventory, product quality can be higher in a decentralized channel compared to a centralized channel, and this is because a wholesale price contract shields the manufacturer from inventory risk. For both centralized and decentralized channels, we find that as demand uncertainty increases, quality decreases, while, different from the case without endogenous quality, inventory can be U-shaped. Interestingly, to mitigate the impact of demand uncertainty on profit, quality can be a more effective lever than inventory in a centralized channel; however, in a decentralized channel, quality is less responsive and inventory is more responsive to demand uncertainty than in a centralized channel.
The online appendix is available at
https://doi.org/10.1287/mksc.2017.1041
.
Journal Article
A Country-Specific Water Consumption Inventory Considering International Trade in Asian Countries Using a Multi-Regional Input-Output Table
Interest in the impacts of water use in the life cycle of products and services are increasing among various stakeholders. The water footprint is a tool to identify critical and effective points for reducing the impact of water use through the entire life cycle of products, services, and organizations. The purpose of this study was to develop a water consumption inventory database that focused on identifying of Asian water consumption using an input-output (IO) framework. An Asia International Input-Output table (AIIO) was applied in this study. The amount of water consumption required for agricultural products was estimated by modeling; for other sectors it was estimated from statistical reports. The intensities of direct water consumption in each sector were calculated by dividing the amount of water consumption by the domestic production. Based on the IO analysis using Leontief’s inverse matrix, the intensities of water consumption from cradle to gate were estimated for all goods and services. There was high intensity of water consumption in the primary industry sectors, together with a high dependency on rainwater as an input water source. The water consumption intensities generally showed a larger reduction in secondary sectors, in comparison with the tertiary sectors, due to the use of recycled water. There were differences between this study and previous studies due to the use of site-specific production data and the temporal resolution of crop production. By considering site-specific conditions, it is expected that the dataset developed here can be used for estimating the water footprint of products, services, and organizations in nine countries (Japan, South Korea, China, Taiwan, Thailand, the Philippines, Malaysia, Singapore, Indonesia, and USA).
Journal Article