Search results

Destinations have in the scholarly literature been labeled as communities of interdependent organizations that collectively coproduce a variety of products and services. The paradigm comes close to describing destinations as firms which are embedded in interfirm networks. Recent studies provide crucial insights into an understanding of destinations' orchestration and structuration as coproducing interfirm networks. However, systematic knowledge about how these systems evolve and develop is lacking. This chapter addresses this issue and elaborates how the concepts of scale-free and small-world networks together can explain the process of destination evolution. The discussion also suggests how such theorizing can spur avenues for future research.

One of the main lessons of the recent financial crisis is that the network structure of the banking system has to be taken into account to assess systemic risk.

In this chapter, we analyze the topological properties of the network of the Euro Area banking sector with the primary aim of assessing the importance of a bank in the financial system with respect to ownership and control of other credit institutions.

The network displays power law distributions in both binary and weighted degree metrics indicating a robust yet fragile structure and a direct nexus between an increase of control diversification and a rise in the market power. Therefore, while in good time the network is seemingly robust, in bad times many banks can go into distress simultaneously. This behavior opens a narrow for Central bank’s actions. In particular, we investigate whether the Single Supervisory Mechanism introduced by the European Central Banks and based on banks’ total asset is a good proxy to quantify their systemic importance. Results indicate that not all the financial institutions with high value of total asset are systemically important but only few of them.

This chapter discusses the emerging network science approach to the study of complex adaptive systems and applies tools derived from statistical physics to the analysis of tourism destinations. The authors provide a brief history of network science and the characteristics of a network as well as different models such as small world and scale free networks, and dynamic properties such as resilience and information diffusion. The Italian resort island of Elba is used as a case study allowing comparison of the communication network of tourist organizations and the virtual network formed by the websites of these organizations. The study compares the parameters of these networks to networks from the literature and to randomly created networks. The analyses include computer simulations to assess the dynamic properties of these networks. The results indicate that the Elba tourism network has a low degree of collaboration between members. These findings provide a quantitative measure of network performance. In general, the application of network science to the study of social systems offers opportunities for better management of tourism destinations and complex social systems.

Purpose — The purpose of this discussion is, first, to review the concept of truth claim and how it forms the framework for four research traditions: science, social science, law, and judgments of excellence. Then, the operational mechanisms of networks are reviewed. The discussion concludes by introducing three philosophic perspectives that might deepen the meanings nascent in the concept of “search.”

Methodology/approach — The methodology includes a historical approach to outline brief but sufficient definitions for how truth claims are built in four established research traditions. Each tradition is then analyzed with a view to testing its methods. The tests suggest a number of pathways to reframe search engine results in order to evaluate their relationship to the previously established types of truth claims.

Findings — The findings constitute an outline of the research traditions in the four areas of science, social science, law, and judgments of excellence. These are followed by a review of the current configurations of networks, their infrastructures, and their capabilities, including a brief section on the importance of search engine mechanisms. Crawling, indexing, and then ranking form the operational mechanisms that search engines employ in delivering search results. It is clear that each operation introduces logical problems. Then, the final sections outline three widely ranging philosophic perspectives on the nature of search: (1) an aesthetic theory of indexing, (2) understanding search from the psychology of learning, and (3) an exploration of the relationship between performativity and recent economic models of how data accumulates in today's world.

Research implications — It is suggested that exploration of a deeper philosophical perspective will assist library and information science (LIS) scholars to reframe Web search in ways that allow linkages to the established research traditions.

Originality/value of the paper — The idea of testing the “truth claim” as connected to traditional research methods was presented initially by Rall (2002, 2004). This area has been neglected in the literature as many Internet scholars find that the philosophy of research methodologies remains outside of their knowledge base. Overall, LIS scholars have focused on information seekers, on the politics of search engines, as well as documenting the computational problems that are present in search engine results. The consideration of how truth claims are formed and subsequently tested will allow LIS researchers to explore the linkages between their current studies and the established frameworks of scholarly research.

Standard financial risk management practices proved unable to provide an adequate understanding and a timely warning of the financial crisis. In particular, the theoretical foundations of risk management and the statistical calibration of risk models are called into question. Policy makers and practitioners respond by looking for new analytical approaches and tools to identify and address new sources of financial risk. Financial markets satisfy reasonable criteria of being considered complex adaptive systems, characterized by complex financial instruments and complex interactions among market actors. Policy makers and practitioners need to take both a micro and macro view of financial risk, identify proper transparency requirements on complex instruments, develop dynamic models of information generation that best approximate observed financial outcomes, and identify and address the causes and consequences of systemic risk. Complexity analysis can make a useful contribution. However, the methodological suitability of complexity theory for financial systems and by extension for risk management is still debatable. Alternative models drawn from the natural sciences and evolutionary theory are proposed.

Resource reconfiguration enables firms to adapt in dynamic environments by supplementing, removing, recombining, or redeploying resources. Whereas prior research has underscored the merits of resource reconfiguration and the modes for implementing it, little is known about the antecedents of this practice. According to prior research, under given industry conditions, resource reconfiguration is prompted by a firm’s corporate strategy and by characteristics of its knowledge assets. We complement this research by identifying learning from performance feedback as a fundamental driver of resource reconfiguration. We claim that performance decline relative to aspiration motivates the firm’s investment in knowledge reconfiguration, and that this investment is reinforced by the munificence of complementary resources in its industry, although uncertainty about the availability of such resources limits that investment. Testing our conjectures with a sample of 248 electronics firms during the period 1993–2001, we reveal a clear distinction between exploitative reconfiguration, which combines existing knowledge elements, and exploratory reconfiguration, which incorporates new knowledge elements. We demonstrate that performance decline relative to aspiration motivates a shift from exploitative reconfiguration to exploratory reconfiguration. Moreover, munificence of complementary resources mitigates the tradeoff between exploratory and exploitative reconfigurations, whereas uncertainty weakens the motivation to engage in both types of reconfiguration, despite the performance gap. Nevertheless, codeployment, which extends the deployment of knowledge assets to additional domains, is more susceptible to uncertainty than redeployment, which withdraws those assets from their original domain and reallocates them to new domains. Our study contributes to emerging research on resource reconfiguration, extends the literature on learning from performance feedback, and advances research on balancing exploration and exploitation.