The Management of Strategic Alliances - Performance Impact Factors and Alliance Management Capabilities in the Context of Logistics Alliances

The proliferation of logistics alliances has continued to grow, due to ongoing deregulation, globalization, increasingly demanding customers, and the constant pressure for efficiency improvements in logistics operations. Logistics alliances are voluntary and long-term agreements in which two or more independent supply chain entities render logistics activities together to achieve strategic goals for mutual competitive advantages. Partnering firms strive for revenue and/or costs gains, service improvements and better market positions through resource, information, and risk sharing among them. Every second Logistics Service Provider (LSP) already engages in a logistics partnership (either vertical or horizontal). The majority of German LSP (about 60%) cooperates with at least one competitor. Despite this proliferation of logistics alliances, about 70 per cent of logistics alliances have difficulties in meeting partners’ expectations and may even be considered failures. While scholars have spent considerable efforts over the last decades studying logistics alliances, major gaps remain in our understanding and explanation of logistics alliances and their evolution (both success and failure). Given the wide acknowledgement and increasing importance of logistics alliances on the one hand, but their well-established diagnosis of high failure rate on the other hand, this thesis identified four central research questions: (1) What are performance impact factors of logistics alliances? (2) Why are some firms more successful in their logistics alliances than others? And how may specific logistics alliance management capabilities explain these differences? (3) What are reasons for logistics alliance failure? And how can firms prevent failure and improve logistics alliance performance? (4) What are logistics-specific alliance management capabilities? And why are some firms not able to deploy them successfully? To answer the identified research questions, the aim of this thesis is to identify and explain logistics-specific (1) alliance performance impact factors, (2) alliance management capabilities, (3) reasons for alliance failure, and (4) barriers for the deployment of logistics alliance management capabilities. Thereby, the thesis wants to elaborate the current understanding and explanation of logistics alliances, and to help firms to prevent logistics alliance failure and to improve logistics alliance performance. Accordingly, the thesis builds on four independent research studies. Each of these four independent research studies provides a comprehensive account of logistics alliances. Thereby, this thesis adds to our understanding and explanation of logistics alliances and their performance. More specifically, it contributes to the logistics alliances scholarship in three ways: (1) Explanation of performance impact factors of logistics alliances (2) Introduction of new theoretical constructs (3) Providing empirical insights. Thereby, the thesis contributes both to the existing logistics alliance scholarship and to practice by helping firms to prevent failure and improve logistics alliance performances

Metadata Schema x-econ Repository

Since May 2017, the x-hub project partners OVGU Magdeburg, University of Vienna, and GESIS dispose of a new repository, called x-econ (https://x-econ.org). The service is dedicated to all experimental economics research projects to disseminate user-friendly archiving and provision of experimental economics research data. The repository x-econ contains all necessary core functionalities of a modern repository and is in a continuous optimization process aiming at functionality enhancement and improvement. x-econ is also one pillar of the multidisciplinary repository x-science (https://x-science.org). The present documentation, which is primarily based on the GESIS Technical Reports on datorium 2014|03 and da|ra 4.0, lists and explains the metadata elements, used to describe research information

Livro de atas do XVI Congresso da Associação Portuguesa de Investigação Operacional

Fundação para a Ciência e Tecnologia - FC

The Roles of Corporate IT Infastructure and their Impact on IS Effectiveness

In the strategic alignment model of Henderson and Venkatraman (1993) [1] IT infrastructure has an important but only implicitly defined role. According to evolving literature, IT infrastructure serves many different purposes in large companies. We outline the main missions (roles) of the corporate-wide IT infrastructure and its contribution to IS effectiveness and study the relationship of IT infrastructure with alignment processes and strategic integration. Our empirical tests with data from almost one hundred large companies resulted in three IT infrastructure roles, which reflect the IS communality, strategic, and flexibility dimensions of the corporate-wide IT infrastructure. The roles were not symmetrically related to the IS effectiveness and alignment perspectives. IT infrastructure roles had a significant interplay with strategic integration in improving IS effectiveness. However, the interplay of IT infrastructure roles with alignment perspectives had only marginal effects. Implications of the results for research and practice are discussed

D8.6 OPTIMAI commercialization and exploitation strategy

Deliverable D8.6 OPTIMAI commercialization and exploitation strategy 1 st version is the first version of the OPTIMAI Exploitation Plan. Exploitation aims at ensuring that OPTIMAI becomes sustainable well after the conclusion of the research project period so as to create impact. OPTIMAI intends to develop an industry environment that will optimize production, reducing production line scrap and production time, as well as improving the quality of the products through the use of a variety of technological solutions, such as Smart Instrumentation of sensors network at the shop floor, Metrology, Artificial Intelligence (AI), Digital Twins, Blockchain, and Decision Support via Augmented Reality (AR) interfaces. The innovative aspects: Decision Support Framework for Timely Notifications, Secure and adaptive multi-sensorial network and fog computing framework, Blockchain-enabled ecosystem for securing data exchange, Intelligent Marketplace for AI sharing and scrap re-use, Digital Twin for Simulation and Forecasting, Embedded Cybersecurity for IoT services, On-the-fly reconfiguration of production equipment allows businesses to reconsider quality management to eliminate faults, increase productivity, and reduce scrap. The OPTIMAI exploitation strategy has been drafted and it consists of three phases: Initial Phase, Mid Phase and Final Phase where different activities are carried out. The aim of the Initial phase (M1 to M12), reported in this deliverable, is to have an initial results' definition for OPTIMAI and the setup of the structures to be used during the project lifecycle. In this phase, also each partner's Individual Exploitation commitments and intentions are drafted, and a first analysis of the joint exploitation strategies is being presented. The next steps, leveraging on the outcomes of the preliminary market analysis, will be to update the Key Exploitable Results with a focus on their market value and business potential and to consolidate the IPR Assessment and set up a concrete Exploitation Plan. The result of the next period of activities will be reported in D8.7 OPTIMAI commercialization and exploitation strategy - 2nd version due at month 18 (June 2022

Journal of Air Transportation, Volume 6, No. 2

No abstract availabl

Comparative analysis of partnership case studies (draft)

This detailed report is a comparison of findings from six case studies conducted among the larger IDRC partnerships with various donors, in different regions, based on themes that reflect the diversity of IDRC Programming Areas. Each of the case studies explores factors that influence partnership effectiveness. The comparison aims to strengthen IDRC knowledge base on donor partnering