Fraunhofer Center for Applied Research on Supply Chain Services

Google Colaboratory (also known as Colab) is a cloud service based on Jupyter Notebooks for disseminating machine learning education and research. It provides a runtime fully configured for deep learning and free-of-charge access to a robust GPU. This paper presents a detailed analysis of Colaboratory regarding hardware resources, performance, and limitations. This analysis is performed through the use of Colaboratory for accelerating deep learning for computer vision and other GPU-centric applications. The chosen test-cases are a parallel tree-based combinatorial search and two computer vision applications: object detection/classification and object localization/segmentation. The hardware under the accelerated runtime is compared with a mainstream workstation and a robust Linux server equipped with 20 physical cores. Results show that the performance reached using this cloud service is equivalent to the performance of the dedicated testbeds, given similar resources. Thus, this service can be effectively exploited to accelerate not only deep learning but also other classes of GPU-centric applications. For instance, it is faster to train a CNN on Colaboratory's accelerated runtime than using 20 physical cores of a Linux server. The performance of the GPU made available by Colaboratory may be enough for several profiles of researchers and students. However, these free-of-charge hardware resources are far from enough to solve demanding real-world problems and are not scalable. The most significant limitation found is the lack of CPU cores. Finally, several strengths and limitations of this cloud service are discussed, which might be useful for helping potential users.

This paper presents a survey of vehicle routing problems with multiple synchronization constraints. These problems exhibit, in addition to the usual task covering constraints, further synchronization requirements between the vehicles, concerning spatial, temporal, and load aspects. They constitute an emerging field in vehicle routing research and are becoming a “hot” topic. The contribution of the paper is threefold: (i) It presents a classification of different types of synchronization. (ii) It discusses the central issues related to the exact and heuristic solution of such problems. (iii) It comprehensively reviews pertinent literature with respect to applications as well as successful solution approaches, and it identifies promising algorithmic avenues.

The increasing importance of sustainable behaviour in business has enhanced its impact on supply chain management. Firms foster sustainability in their supplier base in reaction to growing sustainability requirements in various ways, including sustainable supplier co-operation. Knowledge about the effects of sustainable supplier co-operation on firm performance is limited; therefore, this study tests antecedents and implications of sustainable supplier co-operation according to the triple bottom line. A survey of Western European firms reveals that sustainable supplier co-operation has generally positive effects on firm performance across social, green and economic dimensions. However, only green practices have positive significant effects on economic performance, not social practices (e.g., child labour rules). In contrast to practitioner perceptions, investments in sustainability, for example through sustainable supplier co-operation does indeed result in sufficient returns.

As digital transformation is changing entire industries, organizations are struggling to keep up with these changes. Scholars are viewing organizational capabilities as a central mean for organizations to master digital transformation. Based on a comprehensive literature review, this study identifies a broad set of relevant organizational capabilities and introduces a conceptual framework in which organizational capabilities are clustered into seven relevant themes for managing digital transformation. These capabilities are then embedded in the logic of the dynamic capability theory, highlighting the development of organizational capabilities throughout the digital transformation process. The results reveal that a differentiated perspective on the digital transformation process is beneficial to account for changing needs of organizational capabilities during the transformation process. Just as organizations themselves change during the process, various capabilities at different time points are needed to support and enable organizations during digital transformation. The developed conceptual framework gives organizations guidance for the development of organizational capabilities throughout the digital transformation process.

Forward-scattering radars (FSRs) acquire great interest when low radar cross section (RCS) targets are willing to be detected. This type of radar provides a countermeasure to stealth technology because, here, the targets' RCS depends only on the size and the shape of their silhouette. Passive radars use transmitters of opportunity as signal source, and they are therefore attractive too, due to their inherit low cost. The advantage of considering Global Navigation Satellite System (GNSS) satellites as transmitters of opportunity is the high availability that these satellites offer. Anywhere on earth, around eight Global Positioning System (GPS) satellites are continuously in view. Due to the large number of new GNSS satellites becoming operational in the near future (American GPS, Russian GLONASS, European Galileo system, and Chinese COMPASS), more than 30 satellites are expected to be constantly in view. This provides an optimum scenario for implementation of a GNSS-FSR system. In this paper, experimental results of a GPS-FSR at different target-receiver scenarios near Nuremberg Airport are analyzed. Disturbances on the signals due to diffraction effects, which take place as the targets cross the receiver-satellite baselines, are discussed and evaluated. For these experiments, a hemispherical antenna has been used, which provides promising results for a future GNSS-FSR implementation.

ABSTRACT A growing number of firms are considering the incorporation of environmental thinking into their business strategies, hoping to improve their competitiveness. In this paper, we analyze the effects of pollution prevention and service stewardship capabilities on firm differentiation advantage in the third‐party logistics industry. Since prior research claims that complementary assets play an important role in fully understanding the environmental‐management‐competitiveness link, we furthermore examine the moderating role of environmental communication on the pollution‐prevention‐differentiation and the service‐stewardship‐differentiation linkages. We theoretically base our research in natural‐resource‐based thinking. Drawing on survey data, we apply multivariate regression and moderation analysis. The results highlight that pollution prevention and service stewardship capabilities can help third‐party logistics providers to achieve a differentiation advantage. Also, the results show that environmental communication moderates the effect of pollution prevention on differentiation advantage and can hence be considered a valuable complementary asset. Copyright © 2012 John Wiley & Sons, Ltd and ERP Environment.

Internet of Things (IoT) technologies are transforming the focus of business processes from physical products to data-driven services. The authors propose a reference process for digital transformation of the company that goes beyond traditional technology-driven approaches that solely focus on the identification, specification, and implementation of IoT solutions to also include a strategy-driven approach that takes into account complementary technologies and innovations, considers potential barriers to digital transformation, and develops suitable countermeasures.

The contribution of this paper is a comparison of the state of the art of scientific research on and commercial software for modelling and solving vehicle routing problems. To this end, the paper presents a compact review of vehicle routing literature and an overview of the results of a recent study of commercial vehicle routing software systems with respect to the problem features these systems are able to handle and the solution methods the systems use for automatic generation of vehicle routes. In this way, existing application and research gaps are identified.

As of April 2007, the European Union has new regulations concerning driver working hours. These rules force the placement of breaks and rests into vehicle routes when consecutive driving or working time exceeds certain limits. This paper proposes a large neighborhood search method for the vehicle routing problem with time windows and driver regulations. In this method, neighborhoods are explored using a column generation heuristic that relies on a tabu search algorithm for generating new columns (routes). Checking route feasibility after inserting a customer into a route in the tabu search algorithm is not an easy task. To do so, we model all feasibility rules as resource constraints, develop a label-setting algorithm to perform this check, and show how it can be used efficiently to validate multiple customer insertions into a given existing route. We test the overall solution method on modified Solomon instances and report computational results that clearly show the efficiency of our method compared to two other existing heuristics.

Handling missing values is a crucial step in preprocessing data in Machine Learning. Most available algorithms for analyzing datasets in the feature selection process and classification or estimation process analyze complete datasets. Consequently, in many cases, the strategy for dealing with missing values is to use only instances with full data or to replace missing values with a mean, mode, median, or a constant value. Usually, discarding missing samples or replacing missing values by means of fundamental techniques causes bias in subsequent analyzes on datasets. AIM: Demonstrate the positive impact of multivariate imputation in the feature selection process on datasets with missing values. RESULTS: We compared the effects of the feature selection process using complete datasets, incomplete datasets with missingness rates between 5 and 50%, and imputed datasets by basic techniques and multivariate imputation. The feature selection algorithms used are well-known methods. The results showed that the datasets imputed by multivariate imputation obtained the best results in feature selection compared to datasets imputed by basic techniques or non-imputed incomplete datasets. CONCLUSIONS: Considering the results obtained in the evaluation, applying multivariate imputation by MICE reduces bias in the feature selection process.

A low temperature thermal energy harvesting system to supply power to wireless sensing modules is introduced. The thermoelectric generator module (TEG) makes use of the temperature gradient between the human body (the heat source) and the ambient to deliver a low voltage output that is up-converted by means of a power management circuit. This regulated power source is able to reliably supply a wireless communication module that transmits the collected temperature, current and voltage measurements.

All spoofer attacks have different requirements, impacts, success rates and objectives; therefore, to assess the threat and to develop appropriate counter measures, a clear classification is needed. Being aware of the different existing types of threats, allows an improved design of preventative measures to counter these attacks. This paper classifies spoofer attacks with a layered model. This allows assessing the risks and strategies of operational spoofers with the goal of prevention. The layered model consists of the deployment architectures, the take-over strategy, the control strategy and the application. The paper expands the strategies to manipulate a position of receiver, highlights operational difficulties and suitable counter measures. This emphasises that even if a signal is successfully spoofed, controlling a target receiver is not trivial. Additionally, the most probable spoofing attacks are presented and the applicable antispoofing methods are outlined.

A key issue in community research is the set of motivations stimulating individuals to participate and contribute voluntarily to communities. This article examines the motivations of employees, who are traditionally not involved in the innovation process, to (not) participate in organizational innovation communities. Building on an in‐depth single case study, we aim to answer the following research questions: (1) What motivates participants of organizational innovation communities to participate? and (2) What motivates nonparticipants of organizational innovation communities to not participate? We find and categorize multiple factors that motivate non‐research and development employees to participate and to not participate. Moreover, we find an overlap as well as differences in the set of motivations of participants and nonparticipants. With nonparticipants normally being a large but barely explicitly recognized group, we argue that the found deviations contribute to the understanding of motivations in the context of organizational innovation communities and allow for direct design implications for innovation managers.

Purpose The purpose of this paper is to identify and systematically discuss generic forms of contract logistics services and their distinct underlying approaches for fulfilling their respective value propositions. A general frame of reference is developed that addresses the value proposition, as well as the value creation architecture that leads to generic business model configurations for contract logistics services. The framework is built upon the basic notions of service theory, competence research and the resource based view. Design/methodology/approach The paper combines service theory with work of organizational theory and develops an analytical framework based on conceptual considerations. First empirical results are additionally used to support and illustrate the key outcomes. Findings Combining the dimensions of integration power and intangible knowledge creation, the authors are able to specify generic types of contract logistics services. Thereby the authors deducted for every type the distinct requirements for service fulfilment and present this in a specific frame of reference. Research limitations/implications The illustrated empirical results are still limited due to a limited sample size for the interviews. Additional empirical work on the whole third party logistics (3PL) market is suggested. Practical implications The paper provides generic types of 3PL services and a characterization of properties and architectures of respective business models. Combined with first empirical results, the paper's results offer insights for practitioners to rethink their value propositions and potentially redesign their service architectures. Originality/value The paper delivers a set of distinct business models for 3PL services reflecting the customer's, as well as the service provider's point of view. It addresses specific aspects of the generation/production of required services that are so far mostly neglected.

This article studies the vehicle routing problem with trailers and transshipments (VRPTT), a practically relevant, but challenging, generalization of the classical vehicle routing problem. The article makes three contributions: (i) Building on a nontrivial network representation, two mixed‐integer programming formulations for the VRPTT are proposed. (ii) Based on these formulations, five different branch‐and‐cut algorithms are developed and implemented. (iii) The computational behavior of the algorithms is analyzed in an extensive computational study, using a large number of test instances designed to resemble real‐world VRPTTs.Copyright © 2013 Wiley Periodicals, Inc. NETWORKS, Vol. 63(1), 119–133 2014

Feature selection (FS) has attracted the attention of many researchers in the last few years due to the increasing sizes of datasets, which contain hundreds or thousands of columns (features). Typically, not all columns represent relevant values. Consequently, the noise or irrelevant columns could confuse the algorithms, leading to a weak performance of machine learning models. Different FS algorithms have been proposed to analyze highly dimensional datasets and determine their subsets of relevant features to overcome this problem. However, very often, FS algorithms are biased by the data. Thus, methods for ensemble feature selection (EFS) algorithms have become an alternative to integrate the advantages of single FS algorithms and compensate for their disadvantages. The objective of this research is to propose a conceptual and implementation framework to understand the main concepts and relationships in the process of aggregating FS algorithms and to demonstrate how to address FS on datasets with high dimensionality. The proposed conceptual framework is validated by deriving an implementation framework, which incorporates a set of Phyton packages with functionalities to support the assembly of feature selection algorithms. The performance of the implementation framework was demonstrated in several experiments discovering relevant features in the Sonar, SPECTF, and WDBC datasets. The experiments contrasted the accuracy of two machine learning classifiers (decision tree and logistic regression), trained with subsets of features generated either by single FS algorithms or the set of features selected by the ensemble feature selection framework. We observed that for the three datasets used (Sonar, SPECTF, and WD), the highest precision percentages (86.95%, 74.73%, and 93.85%, respectively) were obtained when the classifiers were trained with the subset of features generated by our framework. Additionally, the stability of the feature sets generated using our ensemble method was evaluated. The results showed that the method achieved perfect stability for the three datasets used in the evaluation.

The purpose of this study is to identify different types of technology-based retail services (TBRS) for brick and mortar environments and analyze them by developing a framework that can be used to classify TBRS in respect of their dimensions, categories and category elements. The research design is twofold. First, this study conducts a systematic literature review to identify a relevant body of various TBRS in scientific literature. Second, it uses grounded theory as a method to analyze the identified TBRS from part one, in order to expose TBRS classification dimensions for developing a classification framework. This study identified 35 TBRS from 124 peer-reviewed articles, published worldwide between 2003 and 2019. It shows that TBRS can be classified along four dimensions: (1) participant issues, (2) technology issues, (3) information issues, and (4) intended purposes. The findings indicate that the majority of TBRS has technology-generated customer contact and is a fixed in-store totem with a low task complexity. Most TBRS enhance customer experience or improve store management. This study addresses a significant and on-going change in retailing. It provides insights into the TBRS market and offers an analytical classification framework to take TBRS to pieces, showing their elements and purposes. The framework can both guide future research and aid retail practitioners in analyzing TBRS.

Roadway infrastructure is reaching maximum capacity in urban areas because of expanding urbanization, demographic changes, and continuously increasing freight volumes. An overview of the latest research on city logistics is needed to address these challenges, and a review of the scientific literature is presented. A specifically designed framework for systematic literature review was used to analyze 92 relevant articles from prominent electronic databases. A taxonomy of city logistics literature was created to aid academics and practitioners and to stimulate interest of other parties in this area.

ABSTRACT YouTube is the most important online platform for streaming video clips. The popularity and the continuously increasing number of users pose new challenges for Internet service providers. In particular, in access networks where the transmission resources are limited and the providers are interested in reducing their operational expenditure, it is worth to efficiently optimise the network for popular services such as YouTube. In this paper, we propose different resource management mechanisms to improve the quality of experience (QoE) of YouTube users. In particular, we investigate the benefit of cross‐layer resource management actions at the client and in the access network for YouTube video streaming. The proposed algorithms are evaluated in a wireless mesh testbed. The results show how to improve the YouTube QoE for the users with the help of client‐based or network‐based control actions. Copyright © 2013 John Wiley & Sons, Ltd.

Decision-makers in hospital management are currently facing the challenge of improving hospital services with respect to the equity, efficiency, costs and quality of health care. This entails ensuring that the required resources are available at each point of care while taking qualitative and economic criteria into consideration. Hospital decision-makers have certain priorities regarding the supply of resources to the different departments of a hospital, and the question is as follows: What are the developmental options to expand the current capabilities of the hospital contract logistics service providers on the basis of the priorities of the decision-makers in the German hospital sector? Therefore, it is necessary to identify the different needs and perspectives of the hospital, the management and the health professionals. Additionally, factors important for the design of supply chains provided by external contractors need to be identified and possible further developments described. Structured interviews with German hospital management and logistics service providers were carried out as part of a long-term study from 2004 to 2010. The demands, aims and strategies of both the providers and customers were a particular focus. It was found that the wide range of different goods supplied and the various hospital objectives require different varieties of logistics services design. It also became clear that particularly logistics fields seen by the management as having middle-to-low priority are contracted out. At the same time, external contracted logistics service providers also strive to offer a wide range of comprehensive services.