Uncovering the big players of the web

In this paper we aim at observing how today the Internet large organizations deliver web content to end users. Using one-week long data sets collected at three vantage points aggregating more than 30,000 Internet customers, we characterize the offered services precisely quantifying and comparing the performance of different players. Results show that today 65% of the web traffic is handled by the top 10 organiza- tions. We observe that, while all of them serve the same type of content, different server architectures have been adopted considering load bal- ancing schemes, servers number and location: some organizations handle thousands of servers with the closest being few milliseconds far away from the end user, while others manage few data centers. Despite this, the performance of bulk transfer rate offered to end users are typically good, but impairment can arise when content is not readily available at the server and has to be retrieved from the CDN back-en

Impact in networks and ecosystems: building case studies that make a difference

open accessThis toolkit aims to support the building up of case studies that show the impact of project activities aiming to promote innovation and entrepreneurship. The case studies respond to the challenge of understanding what kinds of interventions work in the Southern African region, where, and why. The toolkit has a specific focus on entrepreneurial ecosystems and proposes a method of mapping out the actors and their relationships over time. The aim is to understand the changes that take place in the ecosystems. These changes are seen to be indicators of impact as increased connectivity and activity in ecosystems are key enablers of innovation. Innovations usually happen together with matching social and institutional adjustments, facilitating the translation of inventions into new or improved products and services. Similarly, the processes supporting entrepreneurship are guided by policies implemented in the common framework provided by innovation systems. Overall, policies related to systems of innovation are by nature networking policies applied throughout the socioeconomic framework of society to pool scarce resources and make various sectors work in coordination with each other. Most participating SAIS countries already have some kinds of identifiable systems of innovation in place both on national and regional levels, but the lack of appropriate institutions, policies, financial instruments, human resources, and support systems, together with underdeveloped markets, create inefficiencies and gaps in systemic cooperation and collaboration. In other words, we do not always know what works and what does not. On another level, engaging users and intermediaries at the local level and driving the development of local innovation ecosystems within which local culture, especially in urban settings, has evident impact on how collaboration and competition is both seen and done. In this complex environment, organisations supporting entrepreneurship and innovation often find it difficult to create or apply relevant knowledge and appropriate networking tools, approaches, and methods needed to put their processes to work for broader developmental goals. To further enable these organisations’ work, it is necessary to understand what works and why in a given environment. Enhanced local and regional cooperation promoted by SAIS Innovation Fund projects can generate new data on this little-explored area in Southern Africa. Data-driven knowledge on entrepreneurship and innovation support best practices as well as effective and efficient management of entrepreneurial ecosystems can support replication and inform policymaking, leading thus to a wider impact than just that of the immediate reported projects and initiatives

Food web topology and nested keystone species complexes

Important species may be in critically central network positions in ecological interaction networks. Beyond quantifying which one is the most central species in a food web, a multi-node approach can identify the key sets of the most central n species as well. However, for sets of different size n, these structural keystone species complexes may differ in their composition. If larger sets contain smaller sets, higher nestedness may be a proxy for predictive ecology and efficient management of ecosystems. On the contrary, lower nestedness makes the identification of keystones more complicated. Our question here is how the topology of a network can influence nestedness as an architectural constraint. Here, we study the role of keystone species complexes in 27 real food webs and quantify their nestedness. After quantifying their topology properties, we determine their keystones species complexes, calculate their nestedness and statistically analyze the relationship between topological indices and nestedness. A better understanding of the cores of ecosystems is crucial for efficient conservation efforts and to know which networks will have more nested keystone species complexes would be a great help for prioritizing species that could preserve the ecosystem’s structural integrity

Establishing and developing strategic relationships - the role for operations managers

Purpose – The objectives of this paper are, first to identify, from the literature, the key themes in the management of strategic relationships, second to apply those themes to understand how exemplary organisations establish and develop strategic relationships and third to determine the role of operations managers in this process. Design/methodology/approach – This empirically based research comprised four phases; interviews with managers to identify exemplars, interviews with managers from 27 organisations, data analysis and testing of the findings. Findings – From a theoretical point of view, a revised definition of strategic relationships has been proposed. Many previously disparate elements of relationships have been brought together into seven dimensions of strategic relationships. The scope and nature of exemplary relationships have been captured within each of these dimensions identifying 24 elements, and suggested the key roles for operations managers in establishing and developing their strategic business relationships. Research limitations/implications – This research has responded to the call to help operations managers understand the skill sets required to help them establish and develop strategic business relationships. It has contributed to the growing literature on business relationships and also provided practical guidance for operations managers. The research has a number of inherent weaknesses including the interpretative nature of the analysis and that the interviews were only carried out with one party to the exemplary relationships. The focus of the research was limited to exemplary strategic relationships and the study was conducted in one sector, though a range of types of organisations were involved. Practical implications – From a practitioner perspective, the outputs from the research have been summarised into a number of guidelines which flesh out the role for operations managers looking to identify, establish, evaluate or strengthen their role in establishing and developing strategic business relationships. Originality/value – The paper provides an original and detailed perspective into the nature of strategic business relationships, irrespective of their position in the supply chain, and identifies how such relationships can be established and developed

Key Players and Key Groups in Teams

This paper contributes to the literature on centrality measures in economics by defining a team game and identifying the key players in the game. As an illustration of the theory we create a unique data set from the UEFA Euro 2008 tournament. To capture the interaction between players we create the passing network of each team. This all allows us to identify the key player and key groups of players for both teams in each game. We then use our measure to explain player ratings by experts and their market values. Our measure is significant in explaining expert ratings. We also find that players having higher intercentrality measures, regardless of their field position have significantly higher market values.