Improving warehouse labour efficiency by intentional forecast bias

Purpose – This paper shows that intentional demand forecast bias can improve warehouse capacity planning and labour efficiency. It presents an empirical methodology to detect and implement forecast bias. Design/methodology/approach – A forecast model integrates historical demand information and expert forecasts to support active bias management. A non-linear relationship between labour productivity and forecast bias is employed to optimise efficiency. The business analytic methods are illustrated by a case study in a consumer electronics warehouse, supplemented by a survey among thirty warehouses. Findings – Results indicate that warehouse management systematically over-forecasts order sizes. The case study shows that optimal bias for picking and loading is 30-70 percent with efficiency gains of 5-10 percent, whereas the labour-intensive packing stage does not benefit from bias. The survey results confirm productivity effects of forecast bias. Research implications – Warehouse managers can apply the methodology in their own situation if they systematically register demand forecasts, actual order sizes and labour productivity per warehouse stage. Application is illustrated for a single warehouse, and studies for alternative product categories and labour processes are of interest. Practical implications – Intentional forecast bias can lead to smoother workflows in warehouses and thus result in higher labour efficiency. Required data includes historical data on demand forecasts, order sizes and labour productivity. Implementation depends on labour hiring strategies and cost structures. Originality/value – Operational data support evidence-based warehouse labour management. The case study validates earlier conceptual studies based on artificial data

Cross-border electronic commerce: distance effects and express delivery in European Union markets

This empirical study examines distance effects on cross-border electronic commerce and in particular the importance of express delivery in reducing the time dimension of distance. E-commerce provides suppliers with a range of opportunities to reduce distance as perceived by online buyers. They can reduce psychological barriers to cross-border demand by designing websites that simplify the search for and comparison of products and suppliers across countries. They can reduce cost barriers by applying pricing strategies that redistribute transportation costs, and they can overcome time barriers offering express delivery services. This study of 721 regions in five countries of the European Union shows that distance is not “dead” in e-commerce, that express delivery reduces distance for cross-border demand, and that e-demand delivered by express services is more time sensitive and less price sensitive than e-demand satisfied by standard delivery. The willingness of e-customers to pay for express services is shown to be affected by income and by the relative lead-time benefits and express charges. Furthermore, the adoption of express delivery is positively associated with e-loyalty in terms of repurchase rates. The results confirm the importance for e-suppliers of cleverly designed delivery services to reduce distance in order to attract online customers across borders

Spare part demand forecasting for consumer goods using installed base information

When stopping production, the manufacturer has to decide on the lot size in the final production run to cover spare part demand during the end-of-life phase. This decision can be supported by forecasting how much demand is expected in the future. Forecasts can be obtained from the installed base of the product, that is, the number of products still in use. This type of information is relatively easily available in case of B2B maintenance contracts, but it is more complicated in B2C spare parts supply management. Consumer decisions on whether or not to repair a malfunctioning product depend on the specific product and spare part. Further, consumers may differ in their decisions, for example, for products with fast innovations and changing social trends. Consumer behavior can be accounted for by using appropriate types of installed base, for example, lifetime installed base for essential spare parts of expensive products with long lifecycle, and warranty installed base for products with short lifecycle. This paper proposes a set of installed base concepts with associated simple empirical forecasting methodologies that can be applied in practice for B2C spare parts supply management during the end-of-life phase of consumer products. The methodology is illustrated by case studies for eighteen spare parts of six products from a consumer electronics company. The research hypotheses on which installed base type performs best under which conditions are supported in the majority of cases, and forecasts obtained from installed base are substantially better than simple black box forecasts. Incorporating past sales via installed base therefore supports final production decisions to cover future consumer demand for spare parts

Landauer-type transport theory for interacting quantum wires: Application to carbon nanotube Y junctions

We propose a Landauer-like theory for nonlinear transport in networks of one-dimensional interacting quantum wires (Luttinger liquids). A concrete example of current experimental focus is given by carbon nanotube Y junctions. Our theory has three basic ingredients that allow to explicitly solve this transport problem: (i) radiative boundary conditions to describe the coupling to external leads, (ii) the Kirchhoff node rule describing charge conservation, and (iii) density matching conditions at every node.Comment: final version, to be published in PR

The value of express delivery services for cross-border e-commerce in European Union markets

Further growth of cross-border e-commerce in the European Union markets requires improved express delivery services. The framework presented in this paper identifies relevant contextual factors that affect express delivery adoption rates in European cross-border e-commerce. This framework leads to a set of hypotheses, both on the effects of express deliveries on financial performance indicators (order incidence, order size, and repurchase rate) and on the factors that drive demand for express deliveries (consumer income, logistic costs, and lead-time benefits). A case study provides empirical tests of the hypotheses, using data on about forty thousand sales transactions from a consumer electronics manufacturer’s cross-border online shop. The findings are that express delivery has positive effects on financial performance, as it leads to higher order incidence, larger order size, and higher repurchase rates in cross-border transactions. Demand for express delivery services increases with higher income, larger lead-time benefits, and lower logistic costs. Managers can employ the presented framework to formulate and analyse their own targets for performance and express delivery services

Dynamics of fullerene coalescence

Fullerene coalescence experimentally found in fullerene-embedded single-wall nanotubes under electron-beam irradiation or heat treatment is simulated by minimizing the classical action for many atom systems. The dynamical trajectory for forming a (5,5) C$_{120}$ nanocapsule from two C$_{60}$ fullerene molecules consists of thermal motions around potential basins and ten successive Stone-Wales-type bond rotations after the initial cage-opening process for which energy cost is about 8 eV. Dynamical paths for forming large-diameter nanocapsules with (10,0), (6,6), and (12,0) chiral indexes have more bond rotations than 25 with the transition barriers in a range of 10--12 eV.Comment: 4 pages, 2 figures, 1 supplementary movie at http://dielc.kaist.ac.kr/yonghyun/coal.mpeg. To be published in Physical Review Letter

Improving warehouse labour efficiency by intentional forecast bias

Purpose – This paper shows that intentional demand forecast bias can improve warehouse capacity planning and labour efficiency. It presents an empirical methodology to detect and implement forecast bias. Design/methodology/approach – A forecast model integrates historical demand information and expert forecasts to support active bias management. A non-linear relationship between labour productivity and forecast bias is employed to optimise efficiency. The business analytic methods are illustrated by a case study in a consumer electronics warehouse, supplemented by a survey among thirty warehouses. Findings – Results indicate that warehouse management systematically over-forecasts order sizes. The case study shows that optimal bias for picking and loading is 30-70 percent with efficiency gains of 5-10 percent, whereas the labour-intensive packing stage does not benefit from bias. The survey results confirm productivity effects of forecast bias. Research implications – Warehouse managers can apply the methodology in their own situation if they systematically register demand forecasts, actual order sizes and labour productivity per warehouse stage. Application is illustrated for a single warehouse, and studies for alternative product categories and labour processes are of interest. Practical implications – Intentional forecast bias can lead to smoother workflows in warehouses and thus result in higher labour efficiency. Required data includes historical data on demand forecasts, order sizes and labour productivity. Implementation depends on labour hiring strategies and cost structures. Originality/value – Operational data support evidence-based warehouse labour management. The case study validates earlier conceptual studies based on artificial data

Spare part demand forecasting for consumer goods using installed base information

When stopping production, the manufacturer has to decide on the lot size in the final production run to cover spare part demand during the end-of-life phase. This decision can be supported by forecasting how much demand is expected in the future. Forecasts can be obtained from the installed base of the product, that is, the number of products still in use. This type of information is relatively easily available in case of B2B maintenance contracts, but it is more complicated in B2C spare parts supply management. Consumer decisions on whether or not to repair a malfunctioning product depend on the specific product and spare part. Further, consumers may differ in their decisions, for example, for products with fast innovations and changing social trends. Consumer behavior can be accounted for by using appropriate types of installed base, for example, lifetime installed base for essential spare parts of expensive products with long lifecycle, and warranty installed base for products with short lifecycle. This paper proposes a set of installed base concepts with associated simple empirical forecasting methodologies that can be applied in practice for B2C spare parts supply management during the end-of-life phase of consumer products. The methodology is illustrated by case studies for eighteen spare parts of six products from a consumer electronics company. The research hypotheses on which installed base type performs best under which conditions are supported in the majority of cases, and forecasts obtained from installed base are substantially better than simple black box forecasts. Incorporating past sales via installed base therefore supports final production decisions to cover future consumer demand for spare parts

Intrinsic Coulomb blockade in multi-wall carbon nanotubes

Carbon nanotubes provide a new class of molecular wires that display new and exciting mesoscopic transport properties. We provide a detailed theoretical description for transport in multi-wall nanotubes, where both disorder and strong interactions are important. The interplay of both aspects leads to a particularly effective intrinsic Coulomb blockade for tunneling. The relation to recent experiments is discussed.Comment: 13 pages, incl 2 figs, for: Special issue "Transport in Molecular Wires" in Chemical Physics, ed. by P. Hanggi, M. Ratner, S. Yalirak