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Road network performance (RNP) is a key element for urban sustainability as it has a significant impact on economy, environment, and society. Poor RNP can lead to traffic congestion, which can lead to higher transportation costs, more pollution and health issues regarding the urban population. To evaluate the effects of the RNP, the involved stakeholders need a real-world data base to work with. This paper develops a data collection approach to enable location-based RNP analysis using publicly available traffic information. Therefore, we use reachable range requests implemented by navigation service providers to retrieve travel times, travel speeds, and traffic conditions. To demonstrate the practicability of the proposed methodology, a comparison of four German cities is made, considering the network characteristics with respect to detours, infrastructure, and traffic congestion. The results are combined with cost rates to compare the economical dimension of sustainability of the chosen cities. Our results show that digitization eases the assessment of traffic data and that a combination of several indicators must be considered depending on the relevant sustainability dimension decisions are made from.
Purpose
The purpose of this paper is to explore the impact of information technology (IT) on supply chain performance in the automotive industry. Prior studies that analyzed the impact of IT on supply chain performance report results representing the situation of the “average industry.” This research focuses on the automotive industry because of its major importance in many national economies and due to the fact that automotive supply chains do not represent the supply chain of the average industry.
Design/methodology/approach
A research model is proposed to examine the relationships between IT capabilities, supply chain capabilities, and supplier performance. The model divides IT capabilities into functional and data capabilities, and supply chain capabilities into internal process excellence and information sharing. Data have been collected from 343 automotive first-tier suppliers. Structural equation modeling with partial least squares is used to analyze the data.
Findings
The results suggest that functional capabilities have the greatest impact on internal process excellence, which in turn enhances supplier performance. However, frequent and adequate information sharing also contributes significantly to supplier performance. Data capabilities enable supply chain capabilities through their positive impact on functional capabilities.
Practical implications
The findings will help managers to understand the effect of IT implementation on company performance and to decide whether to invest in the expansion of IT capacities.
Originality/value
This research reports the impact of IT on supply chain performance in one of the most important industries in many industrialized countries, and it provides a new perspective on evaluating the contribution of IT on firm performance.
This research explores logistics-related leverages in the responsibility of retailers for improving the environmental performance of a Fast Moving Consumer Goods (FMCG) distribution network. We examine opportunities for modifying the network carbon footprint by changing network design variables. To do so, a quantitative distribution network model is established, and 150 scenarios are calculated by modifying real-world shipment data from an existing multinational FMCG manufacturer. Four distribution variables are identified for a many-to-many and a hub-and-spoke network structure. Two variables affect the distribution network and two interfere in the shipment structure by manipulating weight and/or the delivery date. This research sheds light on the extent of the changes in greenhouse gas (GHG) emissions of the distribution network that result from modifications in the logistics variables. The greatest effect on the quantity of GHG emissions can be observed when an anticipation horizon for orders is introduced. When shipments are consolidated and delivered only weekly or biweekly from the manufacturer to the retailers, GHG emissions drop significantly. Another opportunity for retailers to cut down GHG emissions is based on the concept of minimum order quantities where shipments to a retailer location are bundled until a certain weight is reached. Additionally, total GHG emissions of distribution may be reduced by raising the tonnage limit, thereby triggering direct shipments between the manufacturer’s facilities and the retailer locations, or by raising the tonnage limit, which triggers direct shipments in the logistics service provider network. The extent of GHG reduction is assessed for all investigated variables.
This research quantifies the impact that regular road traffic congestion has on the CO2 emissions of a real-world distribution network, and it studies the consequences when the number of distribution centers changes. For this purpose, this study makes use of a network model allowing for a detailed representation of all relevant transport operations, including production flows between factories and distribution centers, line haul shipments between distribution centers and customers, and round/delivery trips between transshipment points and retailer locations for the last mile. The processed trip and traffic information does not rely on standard traffic data collection approaches, such as interviews, in situ technologies, or floating car data, but the road traffic data are retrieved from an online navigation service, such as Bing Maps, Google Maps, Inrix, Here, and TomTom. This study proves that online navigation services may considerably contribute to future research projects analyzing CO2 sensitivities and greenhouse gas cutting opportunities in logistics networks.
GHG network analysis FMCG
(2013)
The European Norm EN 16258 was published in 2012 to provide a common methodology for the calculation and declaration of energy consumption and greenhouse gas emissions related to any transport operation. The objective was to offer a pragmatic and scientifically-acceptable approach that allows a wide group of users to prepare standardized, accurate, credible, comparable, and verifiable energy consumption and emission declarations. However, in its current form, EN 16258 contains gaps and ambiguities, and leaves room for interpretation, which makes comparisons of supply chains difficult. This research aims to overcome the shortcomings in the domain of allocating emissions from road freight transport operations to single shipments. Based on a discussion of emission drivers and the results of numerical experiments comparing the allocation vectors created by the EN 16258 allocation rules with those generated by the Shapley value, which is claimed to be the benchmark, ‘distance’ is identified as the single most useful unit for bridging the trade-off between accuracy and simplicity better than the other recommended allocation schemes. Thus, this paper claims that future versions of EN 16258 should only allow the allocation unit ‘distance.’ This will promote the accurateness, simplicity, consistency, transparency, and comparability of emission declarations.
Online-Navigationsdienste ermöglichen die Planung einer Reise von einem Start- zu einem Ziel-Ort. Die Berechnung von Reisedauer und Streckenlänge erfolgt auf Grundlage eines detaillierten Straßennetzes und unter Berücksichtigung Orts- und Zeit-typischer Verkehrsaufkommen. Dieser Beitrag zeigt, inwiefern Online-Navigationsdienste die Planung und Analyse logistischer Systeme unterstützen können. Er thematisiert insbesondere die Qualität der zur Verfügung gestellten Verkehrsinfrastrukturdaten und hebt die komparativen Vorteile des Einsatzes von Online-Navigationsdiensten im Vergleich zu ‚herkömmlichen‘ Verkehrsinformationsquellen hervor. Ein Anwendungsfall, bei dem die durch Transportaktivitäten verursachten CO2-Emissionen eines Güternahverkehrsnetzes untersucht werden, verdeutlicht die gewonnenen Erkenntnisse.
This research studies effects that the average increase in travel times due to road traffic congestion has on characteristics of an existing distribution network. It presents the most detailed estimate of ‘on-the-road’ effects on distribution network characteristics up to now, from the network modelling perspective and from the processed data point of view. A concrete network model allowing for the representation of all relevant transportation flows is presented. The processed traffic information relies on navigation service data. The use of such data allows the requirements that arise for the traffic analysis of a whole distribution network to be met. It is shown that this data source may considerably contribute in forthcoming research. The effects of traffic congestion are quantified to get insights into the extent to which regular traffic congestion affects distribution network characteristics and to understand the mitigating effect when the number of distribution centres is increased.