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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.
Produktionswirtschaft
(2020)
Dieses Buch gibt einen umfassenden Überblick über wichtige Bereiche der Produktionswirtschaft. Der Schwerpunkt liegt auf dem operativen Produktionsmanagement. Es zeigt den Einsatz der Produktionsfaktoren Mensch, Betriebsmittel und Material, erklärt die Bedeutung von Informationen für die betriebliche Führung und bietet anhand zahlreicher Beispiele einen breiten Einblick in die Planung und Steuerung industrieller Produktion. Ausführlich werden neben produktionswirtschaftlichen Grundlagen der Ablauf und Inhalt von Planungs- und Steuerungsprozessen erläutert. Auch das aktuelle Thema Industrie 4.0 sowie cyber-physische Systeme werden dargestellt.
In der 2. Auflage wurden umfangreiche Überarbeitungen hinsichtlich Sprache und Aufbau vorgenommen sowie anschauliche Beispielaufgaben, neue Unternehmensbeispiele und hilfreiche Hintergrunderklärungen ergänzt.
Prior research studies on supplier selection factors assess vendor reputation as a low ranked criterion. Reputation in these articles, however, only refers to the position in the industry, without considering the role of the final customer. Our results from a survey with 565 individuals suggest that the end user as a stakeholder should be also considered when analyzing a vendor’s prestige. We demonstrate that a supplier’s standing has negative as well as positive reputational effects on the buyer. Depending on the relevance of the purchased good as well as the reputation of the supplier and the buyer, low/high-ranked ingredients significantly decrease/increase the final customer’s perception of the buyer.
The 0-1 multidimensional knapsack problem (MKP) is a well-known combinatorial optimization problem with several real-life applications, for example, in project selection. Genetic algorithms (GA) are effective heuristics for solving the 0-1 MKP. Multiple individual GAs with specific characteristics have been proposed in literature. However, so far, these approaches have only been partially compared in multiple studies with unequal conditions. Therefore, to identify the “best” genetic algorithm, this article reviews and compares 11 existing GAs. The authors' tests provide detailed information on the GAs themselves as well as their performance. The authors validated fitness values and required computation times in varying problem types and environments. Results demonstrate the superiority of one GA.
Die Projektauswahl stellt eine Herausforderung insbesondere für mittelständische Industrieunternehmen dar. Abhängigkeiten verschiedener Alternativen und vorgegebene Investitionsbudgets führen bei Anwendung von in der Praxis standardmäßig eingesetzten Verfahren regelmäßig zu suboptimalen Projektkombinationen. In enger Abstimmung mit einem Automobilzulieferer wurde ein Ansatz zur Projektauswahl unter Berücksichtigung von Ressourcen und laufenden Projekten entwickelt sowie technisch umgesetzt. Implementierte Praxistests belegen Verbesserungen bei der Projektauswahl, aber auch bei der Budgeteinhaltung, der Fixkostenreduzierung sowie der Angebotspreisbestimmung.
CO-Emissionen sind ein wichtiger Indikator für die Beurteilung der ökologischen Nachhaltigkeit von Unternehmen. In der Praxis sind sie jedoch schwierig zu bestimmen. Insbesondere für Logistik-und Transportaktivitäten, auf die ein Großteil der Emissionen entfällt, sind zuverlässige Methoden zur Ermittlung und Reduktion des Schadstoffausstoßes erforderlich.
Purpose
Tooling is a common component of an industrial product’s manufacture. Specific tooling is devised to serve the fabrication of a particular product, while generic tooling can be used in the manufacture of multiple products. In the latter case, companies are confronted with the problem of fairly allocating the indirect costs of the tooling. This article studies how to allocate costs of generic tooling to single production orders.
Methodology
Ten allocation methods (AMs) are described that are in principle suited to the distribution of generic tooling costs to production orders. Since the presented methods have for the most part been discussed in differing contexts, we apply them to a specified generic tooling problem for comparison. Evaluation of the various methods is based on 16 criteria. Reasoning is supported by a computational Monte Carlo simulation. Furthermore, we suggest using the Analytical Hierarchy Process (AHP) to elaborate one final proposition concerning the most preferable allocation scheme.
Findings
The article reports the single allocation rules’ performances for different allocation scenarios. The described characteristics refer to fairness, efficiency, and simplicity as well as to empty-core performance. Using AHP analysis allows for the aggregation of the rules’ criteria ratings. Thus, especially suitable allocation schemes for the problem at hand are identified.
Practical implications
An allocation is required for budgeting reasons and also for the definition of projects’ bottom-up sales prices. Selecting the “right” AM is important, as a suboptimal AM can result in unfair allocation vectors, which will act as incentives to stop using the common resource, potentially leading to higher total costs.
Originality/value of the article
Research on the comparison of AMs is typically performed for certain purposes, such as enterprise networks, horizontal cooperative purchasing scenarios, or municipal service units. This article will augment the research evaluating AMs by introducing a novel set of evaluation criteria and by providing an in-depth comparison of AMs suited for the allocation of generic tooling costs.
Unternehmen sind häufig mit Situationen konfrontiert, in denen schnell Entscheidungen bezüglich der Auswahl mehrerer Handlungsalternativen gefunden werden müssen. Mathematische Verfahren können hierbei unterstützen, z. B. für die Ermittlung einer ersten Diskussionsbasis. Verfügbare Softwarelösungen errechnen zwar häufig optimale Ergebnisse, zeigen jedoch Schwächen bei der praktischen Anwendbarkeit. So ist eine Einarbeitung in komplexe Optimierungssoftware für die teilweise sporadisch auftretenden Probleme in der Regel für Unternehmen nicht möglich, unter anderem auch unter Anbetracht der teilweise hohen Kosten der Standardsoftware und dem benötigten hohen Einarbeitungsaufwand. Gerade Problemstellungen in Fachbereichen, die nicht auf mathematische Problemlösung spezialisiert sind, münden daher regelmäßig in Ineffizienzen. Basierend auf den in der Literatur diskutierten Lösungsansätzen wurde ein praxisorientierter Ansatz zur Entscheidungsunterstützung für Rucksackprobleme bzw. 0–1 Probleme mithilfe von Genetischen Algorithmen (GA) entwickelt und technisch in Microsoft Excel® umgesetzt. Ein Praxistest bei einem chinesischen Textilunternehmen belegt erhöhte Effektivität und Effizienz. Die Software kann kostenfrei nach MIT Lizenz unter http://www.solvega.de/ heruntergeladen werden.
Customer project selection is a challenge for many industrial companies. An inappropriate project selection approach can lead to constraint violations, high fixed costs, and suboptimal portfolios. To overcome these problems a cash-flow-based linear optimization model was developed in partnership with a tier-1 automotive supplier. Implementation barriers had been verified through a case study conducted at two organizational hierarchies. Results suggest that an application at the operating levels is possible. At higher levels, though, product and firm complexity require major implementation efforts. This article serves theorists as well as practitioners in multiple regards. First, an overview of existing project selection methods and their application in practice is provided. Additionally, the supplier's current appraisal process is depicted. Second, operations research implementation barriers are identified and validated for the adoption of the proposed mathematical project selection approach. Third, a guideline including procedures to overcome experienced difficulties is presented.