Technology in Society
About: Technology in Society is an academic journal. The journal publishes majorly in the area(s): Government & Population. It has an ISSN identifier of 0160-791X. Over the lifetime, 2068 publication(s) have been published receiving 35377 citation(s).
Papers published on a yearly basis
01 Jan 2006-Technology in Society
TL;DR: In this paper, the authors provide a broad overview of the recent patterns and trends of urban growth in developing countries, and the challenges of achieving sustainable urban development will be particularly formidable in Africa.
Abstract: The purpose of this paper is to provide a broad overview of the recent patterns and trends of urban growth in developing countries. Over the last 20 years many urban areas have experienced dramatic growth, as a result of rapid population growth and as the world’s economy has been transformed by a combination of rapid technological and political change. Around 3 billion people—virtually half of the world’s total population-now live in urban settlements. And while cities command an increasingly dominant role in the global economy as centers of both production and consumption, rapid urban growth throughout the developing world is seriously outstripping the capacity of most cities to provide adequate services for their citizens. Over the next 30 years, virtually all of the world’s population growth is expected to be concentrated in urban areas in the developing world. While much of the current sustainable cities debate focuses on the formidable problems for the world’s largest urban agglomerations, the majority of all urban dwellers continue to reside in far smaller urban settlements. Many international agencies have yet to adequately recognize either the anticipated rapid growth of small and medium cities or the deteriorating living conditions of the urban poor. The challenges of achieving sustainable urban development will be particularly formidable in Africa. q 2005 Elsevier Ltd. All rights reserved.
01 Jan 2002-Technology in Society
TL;DR: It is concluded that the adoption of real-time TA can significantly enhance the societal value of research-based innovation.
Abstract: Social science scholarship has identified complex linkages between society and science, but it has been less successful at actually enhancing those linkages in ways that can add to the value and capability of each sector. We propose a research program to integrate natural science and engineering investigations with social science and policy research from the outset — what we call “real-time technology assessment” (real-time TA). Comprising investigations into analogical case studies, research program mapping, communication and early warning, and technology assessment and choice, real-time TA can inform and support natural science and engineering research, and it can provide an explicit mechanism for observing, critiquing, and influencing social values as they become embedded in innovations. After placing real-time TA in the context of scholarship on technology assessment, the paper elaborates on this coordinated set of research tasks, using the example of nano-scale science and engineering (nanotechnology) research. The paper then discusses issues in the implementation of real-time TA and concludes that the adoption of real-time TA can significantly enhance the societal value of research-based innovation.
01 Apr 2005-Technology in Society
TL;DR: In this article, the authors reviewed and summarized important ideas and arguments in the recent theorizing on regional innovation systems and examined such issues as (a) definition confusion and empirical validation; (b) the territorial aspect of regional innovation system; and (c) the role of institutions.
Abstract: In recent years, the concept of regional innovation systems has evolved into a widely used analytical framework that generates the empirical foundation for innovation policy making. Yet, the approaches that utilize this framework remain ambiguous on such key issues as the territorial dimension of innovation, i.e. the region, and the apparently important role played by ‘institutions’ or the institutional context in the emergence and sustenance of regional innovation systems. This paper reviews and summarizes important ideas and arguments in the recent theorizing on regional innovation systems. It also examines such issues as (a) definition confusion and empirical validation; (b) the territorial aspect of regional innovation systems; and (c) the role of institutions.
01 Aug 2002-Technology in Society
TL;DR: The concept of Regional Systems of Innovation (RSI) has recently become popular among academics of various disciplines as mentioned in this paper, which results from a territorially embedded institutional infrastructure and a production system.
Abstract: The concept of Regional Systems of Innovation (RSI) has recently become popular among academics of various disciplines. RSI results from a territorially embedded institutional infrastructure and a production system. The central idea is that the innovative performance of an economy depends on the innovative capabilities of firms and research institutions, and on the ways they interact with each other and public institutions. In this paper, discussion is structured around four key questions: (1) From which theoretical perspectives has the concept of RSI originated?; (2) Does this concept derive from other forms of industrial organization?; (3) Can different forms of RSI exist?; (4) What does the RSI concept fail to address?
01 Nov 2002-Technology in Society
TL;DR: While differing approaches abound in the realm of data mining, the use of some type of datamining is necessary to accomplish the goals of today’s customer relationship management philosophy.
Abstract: Advancements in technology have made relationship marketing a reality in recent years. Technologies such as data warehousing, data mining, and campaign management software have made customer relationship management a new area where firms can gain a competitive advantage. Particularly through data mining—the extraction of hidden predictive information from large databases—organizations can identify valuable customers, predict future behaviors, and enable firms to make proactive, knowledge-driven decisions. The automated, future-oriented analyses made possible by data mining move beyond the analyses of past events typically provided by history-oriented tools such as decision support systems. Data mining tools answer business questions that in the past were too time-consuming to pursue. Yet, it is the answers to these questions make customer relationship management possible. Various techniques exist among data mining software, each with their own advantages and challenges for different types of applications. A particular dichotomy exists between neural networks and chi-square automated interaction detection (CHAID). While differing approaches abound in the realm of data mining, the use of some type of data mining is necessary to accomplish the goals of today’s customer relationship management philosophy.
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