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The present study approaches multinational corporations as internal networks that are constantly newly organized on the basis of relationships, operations, activities, and tasks at hand. It combines MNCs-as-networks view with the research on supplier–customer relationship development to conceptualize the relational dynamics in the MNCs. The dynamics are seen created as the interplay of organizing within internal networks and managing of the global customer relationships. Through an empirical study on a project business MNC and analysis of the events in its global customer relationship the study defines strategies of political compromising in MNC internal networks.

As markets become increasingly competitive, it is important for multinational corporations to generate value. Both headquarters and subsidiaries are responsible for contributing to value generation, albeit they may do so in different ways. This builds on the notion from the literature that it is possible to discern two separate concepts that relate to the generation of value, namely, value creation and value added. These concepts are often used interchangeably, without a clear distinction what they de facto reflect or what the underlying mechanisms of value creation and value added are.

Based on a set of assumptions regarding headquarters–subsidiary relations conceptual arguments related to value generation are developed.

Teasing out the differences between the concepts becomes important as it leads to a fuller understanding of what a headquarters do in different situations and of what a headquarters–subsidiary relationship entails for value generation.

In this chapter, it is argued that value-adding activities tend to be conducted by a headquarters, but are dependent on varying knowledge situations of headquarters, while the value creation process tends to take place at the subsidiary level.

For over four decades, IB scholars have been conceptualizing and empirically examining the organizational structure of the multinational corporation (MNC) without really placing relationships at the center of attention. It therefore remains unclear what characterizes those relationships beyond subunits’ roles, motivation, or control mechanisms. Relationship as a term has often been used but rarely defined in the IB literature on intra-firm networks. We develop arguments that position such relationships as the focal unit of analysis. We extend current IB literature to examine in detail the nature and dynamics of relationships in MNCs by borrowing insights from Industrial Marketing and Purchasing research, which focuses on the relational nature and dynamics of interactions between actors. We offer a theoretical framework and develop a conceptual model that brings to the fore the multiplexity and temporality of relationships in MNCs. We also argue that intra-MNC network relationships can be seen as an evolving process and advocate for shifting away from variance-based and typological views toward a process view for examining relationships. Theoretically, understanding what characterizes the nature of MNC intra-firm relationships and what processes contribute to structuring them provides important insights into the global configuration of the MNC and the required organizational design mechanisms needed for MNC existence and resilience. The study is timely and practically relevant in the sense that considering intra-firm relationships deserves even more attention in the current global economic environment when accessing external resources becomes costly and/or inefficient.

Despite increased interest in headquarters (HQ) and their activities, we still lack a comprehensive understanding of the drivers of HQ relocations and their consequences. We seek to address this gap by examining whether HQ relocations are primarily driven by cost-reduction or value-creation motives, whether these motivations vary by HQ type and how these relocation patterns vary over time. We explore these questions on the basis of a unique hand-collected database of 227 HQ relocations in Europe between 2000 and 2012. Our findings illustrate that different types of HQ units play their orchestrating role in different ways and that their relocations are driven by different motives. Furthermore, our data suggest that although all types of HQ units are increasingly mobile, the implications of relocations for the MNC may differ considerably by HQ type. These findings contribute to a more fine-grained understanding of the drivers of HQ relocations and open up various new avenues for future research on HQ relocation and the role of HQ units in the orchestration of MNCs’ internal networks.

This article aims to provide an insight into the work carried out by a consortium of organizations that have an interest in space activities and to provide a focus on the knowledge architecture that is needed to ensure a viable short‐ and long‐term plan for implementing a successful knowledge management program.

The data for the study were collected by analyzing documents, interviews, group discussions, reviewing technical specifications, and by participating in online group discussions via a dedicated knowledge management portal created for the group

Generating and maintaining organizational knowledge and identifying lessons learned from space project management activities is a crucial activity for planning future projects. One of the most important elements in transferring knowledge is creating a knowledge management system that supports the organizational processes and is based on a sound technical foundation.

This article has resulted from the sharing of knowledge, procedures, and details of technical systems between space organizations from around the world. This approach should be considered by other sectors.

The article describes an architectural approach to creating a knowledge management system.

The postcolonial era in Botswana started with what the author referred to as the neocolonial interlude. During this period, elites who worked to gain independence ruled Botswana. They lacked legitimacy because of their closeness to the colonial masters and their actions to marginalize the traditional institutions. The postcolonial era started with the election of a former chief as the President. He began dismantling the colonial mentality that did not help Botswana and instead integrated the traditional institutions into the modern governance structures in postcolonial governance. He realized that leveraging on the collective contributions of the people was the best way to craft a path of success for Botswana. The chapter described the integration of the traditional and postcolonial institutions to get a system that drove economic development and the people's collective identity in the nation. Botswana achieved what other African countries with similar colonial experiences did not achieve because they valued the traditional institutions and changed them to fit the postcolonial reality.

Big Data analysis is one of the key challenges to the provision of health care to emerge in the last few years. This challenge has been spearheaded by the huge interest in the “4Ps” of health care (predictive, preventive, personalized, and participatory). Big Data offers striking development opportunities in health care and life sciences. Healthcare research is already using Big Data to analyze the spatial distribution of diseases such as diabetes mellitus at detailed geographic levels. Big Data is also being used to assess location-specific risk factors based on data of health insurance claims. Other studies in systems medicine utilize bioinformatics approaches to human biology which necessitate Big Data statistical analysis and medical informatics tools. Big Data is also being used to develop electronic algorithms to forecast clinical events in real time, with the intent to improve patient outcomes and thus reduce costs.

Yet, this Big Data era also poses critically difficult ethical challenges, since it is breaking down the traditional divisions between what belongs to public and private domains in health care and health research. Big Data in health care raises complex ethical concerns due to use of huge datasets obtained from different sources for varying reasons. The clinical translation of this Big Data is thus resulting in key ethical and epistemological challenges for those who use these data to generate new knowledge and the clinicians who eventually apply it to improve patient care.

Underlying this challenge is the fact that patient consent often cannot be collected for the use of individuals’ personal data which then forms part of this Big Data. There is also the added dichotomy of healthcare providers which use such Big Data in attempts to reduce healthcare costs, and the negative impact this may have on the individual with respect to privacy issues and potential discrimination.

Big Data thus challenges societal norms of privacy and consent. Many questions are being raised on how these huge masses of data can be managed into valuable information and meaningful knowledge, while still maintaining ethical norms. Maintaining ethical integrity may lack behind in such a fast-changing sphere of knowledge. There is also an urgent need for international cooperation and standards when considering the ethical implications of the use of Big Data-intensive information.

This chapter will consider some of the main ethical aspects of this fast-developing field in the provision of health care, health research, and public health. It will use examples to concretize the discussion, such as the ethical aspects of the applications of Big Data obtained from clinical trials, and the use of Big Data obtained from the increasing popularity of health mobile apps and social media sites.

The construction sector has significantly evolved in recent decades, in parallel with a huge increase in the amount of data generated and exchanged in any construction project. These data need to be managed in order to complete a successful project in terms of quality, cost and schedule in the the context of a safe project environment while appropriately organising many construction documents.

However, the origin of these data is very diverse, mainly due to the sector’s characteristics. Moreover, these data are affected by uncertainty, complexity and diversity due to the imprecise nature of the many factors involved in construction projects. As a result, construction project data are associated with large, irregular and scattered datasets.

The objective of this chapter is to introduce an approach based on a fuzzy multi-dimensional model and on line analytical processing (OLAP) operations in order to manage construction data and support the decision-making process based on previous experiences. On one hand, the proposal allows for the integration of data in a common repository which is accessible to users along the whole project’s life cycle. On the other hand, it allows for the establishment of more flexible structures for representing the data of the main tasks in the construction project management domain. The incorporation of this fuzzy framework allows for the management of imprecision in construction data and provides easy and intuitive access to users so that they can make more reliable decisions.