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Supply Chain Event Management (SCEM) addresses a fundamental business problem: inter‐organizational processes rarely execute as scheduled, since they happen in an environment prone to failure and disturbance. SCEM attempts to identify, as early as possible, the resulting deviations between the plan and its execution across the multitude of processes and actors in the supply chain to trigger corrective actions according to predefined rules. Despite SCEM's well documented attractiveness for practitioners, it has received little attention as a field of academic research. This paper provides an introduction into SCEM from three complementary perspectives: SCEM as a management concept; as a software solution; and as a software component. Each is analyzed in detail and potential fields of research on SCEM are presented.

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.

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.

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.

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.

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.

Academic discussion in the field of supply chain management is influenced by descriptive, case‐oriented and consultancy‐driven research outcomes. The debate is often limited to the search for valid definitions and models of observable facts. The present research makes an alternative effort. This article deals with the question of whether there are any common suggestions that can be condensed to nine process‐based principles that contribute to the management of such chains. The applicability of these principles was evaluated using Thomas and Tymon's notions of “necessary properties of relevant research”.

The purpose of this paper is to understand value creation of information technology (IT) in supply chain planning (SCP). The impact of different IT components in SCP remains unclear and requires some thorough research. In addition, an analysis of the optimization dimension provides insights into intra-functional, inter-functional and cross-company optimization.

A survey was conducted among German companies using a continuous production flow. In total, 47 of 193 contacted companies completed the web survey, which corresponds to a response rate of 24 percent.

IT functionality for SCP is widely spread. The value of IT functionality in SCP is tremendous. Implementations in demand fulfillment and available-to-promise (ATP) have the biggest value creation potential. Supply chain performance indicators can be improved by investments in certain functional domains. Packaged standard software is widely distributed and should be considered as the first option. IT functionality to improve intra-functional processes is significantly more often implemented than IT functionality for inter-functional or cross-company process optimization although the realized value is comparable.

Respondents of the survey are limited to the German continuous production flow industry. Future research could be interesting in the discrete manufacturing industry.

The paper provides empirical insights into the value of IT in SCP where data are less available than in the ERP context. Furthermore, this paper provides first insights into the optimization dimension whether processes are optimized intra-functional, inter-functional or cross-company.

The steady increase of data on human behavior collected online holds significant research potential for social scientists. The purpose of this paper is to add a systematic discussion of different online services, their data generating processes, the offline phenomena connected to these data, and by demonstrating, in a proof of concept, a new approach for the detection of extraordinary offline phenomena by the analysis of online data.

To detect traces of extraordinary offline phenomena in online data, the paper determines the normal state of the respective communication environment by measuring the regular dynamics of specific variables in data documenting user behavior online. In its proof of concept, the paper does so by concentrating on the diversity of hashtags used on Twitter during a given time span. The paper then uses the seasonal trend decomposition procedure based on loess (STL) to determine large deviations between the state of the system as forecasted by the model and the empirical data. The paper takes these deviations as indicators for extraordinary events, which led users to deviate from their regular usage patterns.

The paper shows in the proof of concept that this method is able to detect deviations in the data and that these deviations are clearly linked to changes in user behavior triggered by offline events.

The paper adds to the literature on the link between online data and offline phenomena. The paper proposes a new theoretical approach to the empirical analysis of online data as indicators of offline phenomena. The paper will be of interest to social scientists and computer scientists working in the field.

This paper aims to investigate the role of upper management in designing performance measurement systems (PMS) that account for external turbulence of the organization and to show how this PMS design for turbulence impacts organizational resilience and distribution service performance.

Hypotheses are developed by integrating management accounting and strategic management perspectives into supply chain management and subsequently tested based on data from 431 logistics organizations (i.e. both logistics companies and internal logistics departments of manufacturing and retailing companies).

Attention focusing usage type of the PMS by the upper management fosters incorporating the element of risk into the PMS of the company. Further, PMS design for turbulence enhances organizational resilience, and, indirectly, this also leads to improved distribution service performance.

This paper is the first to introduce the concept of PMS design for turbulence to the literature and to show that it is relevant for supply chain risk management by fostering the capabilities and the performance of logistics organizations. Further, it is shown that a seemingly detached issue such as the general PMS use focus of the upper management impacts supply chain risk management.

Current business challenges force companies to exchange critical and sensitive data. The data provider pays great attention to the usage of their data and wants to control it by policies. The purpose of this paper is to develop usage control architecture options to enable data sovereignty in business ecosystems.

The architecture options are developed following the design science research process. Based on requirements from an automotive use case, the authors develop architecture options. The different architecture options are demonstrated and evaluated based on the case study with practitioners from the automotive industry.

This paper introduces different architecture options for implementing usage control (UC). The proposed architecture options represent solutions for UC in business ecosystems. The comparison of the architecture options shows the respective advantages and disadvantages for data provider and data consumer.

In this work, the authors address only one case stemming from the German automotive sector.

Technical enforcement of data providers policies instead of relying on trust to support collaborative data exchange between companies.

This research is among the first to introduce architecture options that provide a technical concept for the implementation of data sovereignty in business ecosystems using UC. Consequently, it supports the decision process for the technical implementation of data sovereignty.