Showing papers in "Communications of The ACM in 1996"
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1,857 citations
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TL;DR: A leading computer industry information service firm indicated that it “expects most business process reengineering initiatives to fail through lack of attention to data quality”.
Abstract: of an organization. A leading computer industry information service firm indicated that it “expects most business process reengineering initiatives to fail through lack of attention to data quality.” An industry executive report noted that more than 60% of surveyed firms (500 medium-size corporations with annual sales of more than $20 million) had problems with data quality. The Wall Street Journal also reported that, “Thanks to computers, huge databases brimming with information are at our fingertips, just waiting to be tapped. They can be mined to find sales Anchoring Data Quality Dimensions Ontological Foundations
1,468 citations
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TL;DR: A relatively new development—information extraction (IE)—is the subject of this article and can transform the raw material, refining and reducing it to a germ of the original text.
Abstract: here may be more text data in electronic form than ever before, but much of it is ignored. No human can read, understand, and synthesize megabytes of text on an everyday basis. Missed information— and lost opportunities—has spurred researchers to explore various information management strategies to establish order in the text wilderness. The most common strategies are information retrieval (IR) and information filtering [4]. A relatively new development—information extraction (IE)—is the subject of this article. We can view IR systems as combine harvesters that bring back useful material from vast fields of raw material. With large amounts of potentially useful information in hand, an IE system can then transform the raw material, refining and reducing it to a germ of the original text (see Figure 1). Suppose financial analysts are investigating production of semiconductor devices (see Figure 2). They might want to know several things:
962 citations
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TL;DR: The Horus system offers flexible group communication support for distributed applications, allowing applications to only pay for services they use, and for groups with different communication needs to coexist in a single system.
Abstract: The Horus system offers flexible group communication support for distributed applications. It is extensively layered and highly reconfigurable, allowing applications to only pay for services they use, and for groups with different communication needs to coexist in a single system. The approach encourages experimentation with new communication properties and incremental extension of the system, and enables us to support a variety of application-oriented interfaces.
754 citations
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TL;DR: Information on the Web is sufficiently structured to facilitate effective Web mining, according to the structured Web hypothesis, and preliminary Web mining successes are surveyed and directions for future work are suggested.
Abstract: Skeptics believe the Web is too unstructured for Web mining to succeed. Indeed, data mining has been applied traditionally to databases, yet much of the information on the Web lies buried in documents designed for human consumption such as home pages or product catalogs. Furthermore, much of the information on the Web is presented in natural-language text with no machine-readable semantics; HTML annotations structure the display of Web pages, but provide little insight into their content. Some have advocated transforming the Web into a massive layered database to facilitate data mining [12], but the Web is too dynamic and chaotic to be tamed in this manner. Others have attempted to hand code site-specific “wrappers” that facilitate the extraction of information from individual Web resources (e.g., [8]). Hand coding is convenient but cannot keep up with the explosive growth of the Web. As an alternative, this article argues for the structured Web hypothesis: Information on the Web is sufficiently structured to facilitate effective Web mining. Examples of Web structure include linguistic and typographic conventions, HTML annotations (e.g., ), classes of semi-structured documents (e.g., product catalogs), Web indices and directories, and much more. To support the structured Web hypothesis, this article will survey preliminary Web mining successes and suggest directions for future work. Web mining may be organized into the following subtasks:
613 citations
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TL;DR: Today’s enterprise computing facilities are only an approximation of the vision of an information utility, and some businesses are redefining their business processes to use the utility to bridge formerly isolated component activities.
Abstract: he computing facilities of largescale enterprises are evolving into a utility, much like power and telecommunications. In the vision of an information utility, each knowledge worker has a desktop appliance that connects to the utility. The desktop appliance is a computer or computer-like device, such as a terminal, personal computer, workstation, word processor, or stock trader’s station. The utility itself is an enterprise-wide network of information services, including applications and databases, on the localarea and wide-area networks. Servers on the local-area network (LAN) typically support files and file-based applications, such as electronic mail, bulletin boards, document preparation, and printing. Local-area servers also support a directory service, to help a desktop user find other users and find and connect to services of interest. Servers on the wide-area network (WAN) typically support access to databases, such as corporate directories and electronic libraries, or transaction processing applications, such as purchasing, billing, and inventory control. Some servers are gateways to services offered outside the enterprise, such as travel or information retrieval services, news feeds (e.g., weather, stock prices), and electronic document interchange with business partners. In response to such connectivity, some businesses are redefining their business processes to use the utility to bridge formerly isolated component activities. In the long term, the utility should provide the information that people need when, where, and how they need it. Today’s enterprise computing facilities are only an approximation of the vision of an information utility. Most organizations have a wide variety of heterogeneous hardware systems, including personal computers, workstations, minicomputers, and mainframes. These systems run different operating systems (OSs) and rely on different network architectures. As a result, integration is difficult and its achievement uneven. For example, local-area servers are often isolated from the WAN. An appliance can access files and printers on its local server, but often not those on the servers of other LANs. Sometimes an application available on one local area server is not available on other servers, because other departments use servers
602 citations
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TL;DR: This article presents a comprehensive introduction and summary of the main basic concepts and bibliography in the area of Data Mining, nowadays and can be considered as a good starting point for newcomers in the field.
Abstract: The term knowledge discovery in databases or KDD, for short, was coined in 1989 to refer to the broad process of finding knowledge in data, and to emphasize the “high-level” application of particular Data Mining (DM) methods (Fayyad, Piatetski-Shapiro, & Smyth, 1996). Fayyad considers DM as one of the phases of the KDD process. The DM phase concerns, mainly, the means by which the patterns are extracted and enumerated from data. The literature is sometimes a source of some confusion because the two terms are indistinctively used, making it difficult to determine exactly each of the concepts (Benoît, 2002). Nowadays, the two terms are, usually, indistinctly used. Efforts are being developed in order to create standards and rules in the field of DM with great relevance being given to the subject of inductive databases (De Raedt, 2003) (Imielinski & Mannila, 1996). Within the context of inductive databases a great relevance is given to the so called DM languages. This article presents a comprehensive introduction and summary of the main basic concepts and bibliography in the area of DM, nowadays. Thus, the main contribution of this article is that it can be considered as a good starting point for newcomers in the area. The remaining of this article is organized as follows. Firstly, DM and the KDD process are introduced. Following, the main DM tasks, methods/algorithms, and models/patterns are organized and succinctly explained. SEMMA and CRISP-DM are next introduced and compared with KDD. A brief explanation of standards for DM is then presented. The article concludes with possible future research directions and conclusion. BACKGROUND
570 citations
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TL;DR: The concept of data mining as a querying process and the first steps toward efficient development of knowledge discovery applications are discussed.
Abstract: DATABASE MINING IS NOT SIMPLY ANOTHER buzzword for statistical data analysis or inductive learning. Database mining sets new challenges to database technology: new concepts and methods are needed for query languages, basic operations, and query processing strategies. The most important new component is the ad hoc nature of knowledge and data discovery (KDD) queries and the need for efficient query compilation into a multitude of existing and new data analysis methods. Hence, database mining builds upon the existing body of work in statistics and machine learning but provides completely new functionalities. The current generation of database systems are designed mainly to support business applications. The success of Structured Query Language (SQL) has capitalized on a small number of primitives sufficient to support a vast majority of such applications. Unfortunately, these primitives are not sufficient to capture the emerging family of new applications dealing with knowledge discovery. Most current KDD systems offer isolated discovery features using tree inducers, neural nets, and rule discovery algorithms. Such systems cannot be embedded into a large application and typically offer just one knowledge dis-The concept of data mining as a querying process and the first steps toward efficient development of knowledge discovery applications are discussed.
547 citations
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TL;DR: When Totem delivers multicast messages, it invokes operations in the same total order throughout the distributed system, resulting in consistency of replicated data and simpli ed programming of applications.
493 citations
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TL;DR: This research on parallel algorithms has not only improved the general understanding of par-allelism but in several cases has led to improvements in sequential algorithms.
Abstract: In the past 20 years there has been treftlen-dous progress in developing and analyzing parallel algorithftls. Researchers have developed efficient parallel algorithms to solve most problems for which efficient sequential solutions are known. Although some of these algorithms are efficient only in a theoretical framework, many are quite efficient in practice or have key ideas that have been used in efficient implementations. This research on parallel algorithms has not only improved our general understanding ofpar-allelism but in several cases has led to improvements in sequential algorithms. Unf:ortunately there has been less success in developing good languages f:or prograftlftling parallel algorithftls, particularly languages that are well suited for teaching and pro-totyping algorithms. There has been a large gap between languages that are too low level, requiring specification of many details that obscure the meaning of the algorithm, and languages that are too high level, making the performance implications of various constructs unclear. In sequential computing many standard languages such as C or Pascal do a reasonable J·ob of bridging this gap, but in parallel languages building such a bridge has been significantly more difficult.
458 citations
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TL;DR: The Blacksburg Electronic Village (BEV), in operation since October 1993, is a technologically advanced community network that helps facilitate interaction among individuals who are physically remote—in distributed work groups and interest groups.
Abstract: facilitate interaction among individuals who are physically remote—in distributed work groups and interest groups. Why would anyone want a network connection to their next-door neighbor? In fact, community networks are a big idea. Over the past 20 years, since the Community Memory project in Developing the Almost half the population of Blacksburg, Virginia are Internet veterans, having spent the past three years at the core of one of the most advanced community network projects in the U.S. Berkeley, Calif., the idea has caught on in hundreds of community networks across North America and the world. They provide forums for community discussion and access to government, public health information, economic development , and public education. In most cases, they started as outreach or service projects of universities , as initiatives of local governments, and as public interest projects of energetic citizens. They offer a unique vision of grassroots technology development [1–3, 5, 11]. In January 1994, we became professors at Vir-ginia Tech, residents of Blacksburg, Virginia, and participant-observers in the Blacksburg Electronic Village. This article is an overview of our observations, discussions, and projects within the local community network. The Blacksburg Electronic Village (BEV), in operation since October 1993, is a technologically advanced community network. The project was originally constituted as a partnership among the town of Blacksburg, Virginia Tech, and Bell Atlantic to improve community networking service to the level available on the Vir-ginia Tech campus. Bell Atlantic agreed to install a Number 5 ESS digital electronic switch and to run T1 ethernet to the public library as well as to several hundred apartments and some
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TL;DR: In this article, the authors investigated outsourcing decisions at two levels: the first level deals with the initial outsourcing decision of client firms and the second level pertains to the intention to continue the relationships with current outsourcing vendors in the future.
Abstract: O UTSOURCING is the contracting of various systems to outside information systems (IS) vendors. Ever since the Eastman Kodak--IBM partnership was reported in 1989 [15], outsourcing has emerged and has been recognized as a key method of managing IS. In previous studies of outsourcing [4, 5, 12, 15, 17, 20], two gaps are noticeable. The first relates to the fact that requirements for outsourcing are not uniform, and managers have different approaches to the process. Yet most previous research studies have phrased their inquiries unidimensionally in terms of the extent or degree of outsourcing: either as a binary variable or as size of contract in terms of the percentage of total IS budget [5, 15]. Neither unidimensional gauge is sufficiently expressive; neither allows representation of diverse patterns of outsourcing. Second, even though the IS industry had not used the term “outsourcing” explicitly in the past, outsourcing is not a new concept and has existed for many years in one form or another. Even though firms have repetitively used outside vendors for years, researchers have neither considered prior relationships in their studies of IS outsourcing nor studied the intentions of client firms to continue the partnership with the outsourcing vendors in the future. In this study, IS outsourcing decisions are investigated at two levels. The first level deals with the initial outsourcing decision of client firms. The second level pertains to the intention to continue the relationships with current outsourcing vendors in the future. The following three research questions are explored at these two levels (in contrast to the singlelevel approach taken by most researchers): • What are the dimensions of outsourcing decisions? Two dimensions, extent of substitution by vendors and strategic impact of IS applications, are proposed in order to conceptualize the diverse types of outsourcing relationships between clients and vendors. Based on these two dimensions, four types of outsourcing relationships are proposed. • What are the determinants that affect the dimensions of outsourcing decisions at the first level? The concepts derived from incomplete contracts [2, 9] and transactions cost economics [23, 24] theory are used with information technology (IT) organizational contexts and processes as a foundation to study the determinants of the two dimensions of outsourcing decisions. Information Syst
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TL;DR: There is a revolution taking place in education, one that deals with the philosophy of how one teaches, the relationship between teacher and student, of the way in which a classroom is structured, and the nature of curriculum.
Abstract: There is a revolution taking place in education, one that deals with the philosophy of how one teaches, of the relationship between teacher and student, of the way in which a classroom is structured, and the nature of curriculum. At the heart is a powerful pedagogy, one that has been developing over the past hundred years. It embraces social issues, the culture of the classroom, life-long learning concerns, and perhaps both last and least, technology.
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TL;DR: Enough to be generally useful and to keep the algorithm analysis tractable to produce a better program in practice.
Abstract: enough to be generally useful and to keep the algorithm analysis tractable. Ideally, producing a better algorithm under the model should yield a better program in practice. The Parallel Random Access Machine (PRAM) [8] is the most popular model for representing and analyzing the complexity of parallel algorithms. A LogP A Practic
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TL;DR: He great Internet explosion during the past two years is largely fueled by the prospect of performing business online, but consumers and businesses alike seem wary of this new medium for conducting business on a large scale.
Abstract: HE great Internet explosion during the past two years is largely fueled by the prospect of performing business online. Prophets tell of the day when even the most mundane transactions will be handled through the Internet, along with the most sophisticated bank transfers in use today. The Internet can bring down physical barriers to commerce, almost immediately giving even the smallest business access to untapped markets around the world. By the same token, consumers can conduct business and make purchases from organizations previously unavailable to them. Armed with these goals, individuals have flocked to the Internet, and most businesses have set out to set up storefronts on the Internet and its WorldWide Web. Just about every major business in the U.S., perhaps in the world, has a home page on the Internet on which can be found information about their services and products. Despite the forecasts, however, consumers and businesses alike seem wary of this new medium for conducting business on a large scale. Given the potential for both consumers and businesses, why the apprehension? Insecurity The original Internet was designed for research, not as a commercial environment. As such, it operated A n i s h B h i m a n i Consumers as well as businesses wary of exposing secret financial data through the Internet's frail protection select from numerous patchwork security options incorporating protocols that may or may not turn out to be adopted as standards.
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TL;DR: It is argued that a market-based approach to privacy protection would be far more effective and efficient in protecting individual information than current approaches.
Abstract: Since the 1960s privacy advocates have relied on regulatory and legislativeapproaches to privacy protection in the United States, Canada and Europe. Whileimportant progress has been made in certain areas, there are large gaps andsignificant loopholes in existing legislation. I argue that a market-based approachto privacy protection would be far more effective and efficient in protectingindividual information than current approaches.
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TL;DR: The “Wiredville” story illustrates some of the finer points that motivated the work in the Transis project, a large-scale multicast service designed with the following goals:
Abstract: In the local elections system of the municipality of “Wiredville”,1 several computers were used to establish an electronic town hall. The computers were linked by a network. When an issue was put to a vote, voters could manually feed their votes into any of the computers, which replicated the updates to all of the other computers. Whenever the current tally was desired, any computer could be used to supply an up-to-the-moment count. On the night of an important election, a room with one of the computers became crowded with lobbyists and politicians. Unexpectedly, someone accidentally stepped on the network wire, cutting communication between two parts of the network. The vote counting stopped until the network was repaired, and the entire tally had to be restarted from scratch. This would not have happened if the vote-counting system had been built with partitions in mind. After the unexpected severance, vote counting could have continued at all the computers, and merged appropriately when the network was repaired. The “Wiredville” story illustrates some of the finer points that motivated our work in the Transis project [1], a large-scale multicast service designed with the following goals:
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TL;DR: In this study, IS outsourcing decisions are investigated at two levels: the first level deals with the initial outsourcing decision of client firms and the second level pertains to the intention to continue the relationships with current outsourcing vendors in the future.
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TL;DR: Transis as mentioned in this paper is a large-scale multicast service designed with the following goals: large scale multicast support for large scale elections, large scale election counting, and the ability to send votes to all the computers in the network.
Abstract: In the local elections system of the municipality of “Wiredville”,1 several computers were used to establish an electronic town hall. The computers were linked by a network. When an issue was put to a vote, voters could manually feed their votes into any of the computers, which replicated the updates to all of the other computers. Whenever the current tally was desired, any computer could be used to supply an up-to-the-moment count. On the night of an important election, a room with one of the computers became crowded with lobbyists and politicians. Unexpectedly, someone accidentally stepped on the network wire, cutting communication between two parts of the network. The vote counting stopped until the network was repaired, and the entire tally had to be restarted from scratch. This would not have happened if the vote-counting system had been built with partitions in mind. After the unexpected severance, vote counting could have continued at all the computers, and merged appropriately when the network was repaired. The “Wiredville” story illustrates some of the finer points that motivated our work in the Transis project [1], a large-scale multicast service designed with the following goals:
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TL;DR: The author's eight system study begins to define reuse benefits in an OO framework, most notably in terms of reduce defect density and rework as well as in increased productivity.
Abstract: Although reuse is assumed to be especially valuable in building high quality software as well as in Object Oriented (OO) development, limited empirical evidence connects reuse with productivity and quality gains. The author's eight system study begins to define such benefits in an OO framework, most notably in terms of reduce defect density and rework as well as in increased productivity.
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TL;DR: The Platform for Internet Content Selection (PICS 1) establishes Internet conventions for label formats and distribution methods while dictating neither a labeling vocabulary nor who should pay attention to which labels.
Abstract: 87 W ith its recent explosive growth, the Internet now faces a problem inherent in all media that serve diverse audiences: Not all materials are appropriate for every audience. Societies have tailored their responses to the characteristics of the various media [1, 3]. In most countries, there are more restrictions on broadcasting than on the distribution of printed materials. Any rules about distribution, however, will be too restrictive from some perspectives yet not restrictive enough from others. We can do better. We can meet diverse needs by controlling reception rather than distribution. In the TV industry, this realization has led to the V-chip, a system for blocking reception based on labels embedded in the broadcast stream. On the Internet, we can do better still, with richer labels that reflect diverse viewpoints and more flexible selection criteria. The Platform for Internet Content Selection (PICS 1) establishes Internet conventions for label formats and distribution methods while dictating neither a labeling vocabulary nor who should pay attention to which labels. It is analogous to specifying where on a package a label should appear and in what font size it should be printed without specifying what it should say. The PICS conventions have caught on quickly. and other software vendors announced PICS-compatible products. AOL, AT&T WorldNet, CompuServe, MSN and Prodigy provide free blocking software that will be PICS-compliant by the end of 1996. RSACi and SafeSurf are offering their particular labeling vocabularies through online servers that produce PICS-formatted labels. A labeling infrastructure for the Internet offers a flexible means of content selection and viewing. Without Censorship 1 PICS is an effort of the WorldWide Web Consortium at MIT's Laboratory for Computer Science, drawing on the resources of a broad cross-section of the industry. Project history, a long list of supporting organizations, and details of the specifications may be found at http://w3.org/PICS.
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TL;DR: There is a relationship between the activity of data mining and the data warehouse—the architectural foundation of decision support systems—which sets the stage for effective data mining.
Abstract: THERE IS A SYMBIOTIC RELATIONSHIP between the activity of data mining and the data warehouse—the architectural foundation of decision support systems. The data warehouse sets the stage for effective data mining. Data mining can be done where there is no data warehouse, but the data warehouse greatly improves the chances of success in data mining. How does the data warehouse set the stage? Consider the nature of a data warehouse, which includes:
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TL;DR: Empirical and theoretical concerns are raised in an attempt to capture the structure and dynamics of computer adoption and use in the home.
Abstract: DESPITE THE RECENT DRAMATIC TRENDS IN THE DIFfusion of information technology, the significance of these developments is still not clear. Also lacking is a critical understanding of these developments and a sound theoretical and empirical base from which to observe and analyze them. Supporting such an analysis, this article raises both empirical and theoretical concerns in an attempt to capture the structure and dynamics of computer adoption and use in the home. Computers and Other Interactive Technologies for the Home A l l a d i V e n k a t e s h
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TL;DR: The author examines attitudes toward CASE usage in a wide variety of organizations and finds that one year after introduction, 70% of the respondents indicated good profitability of CASE investments while 31% assessed it as poor.
Abstract: group, and 5% are widely used, but not to capacity. Aaen et al. [1], based on a survey of 102 CASE user organizations in Denmark and Fin-land, report that less than 20% of the organizations were close to routine users of CASE tools, even though 24% had used them more than three years. About half the respondents had used the tools for two projects or less, and in the majority of the organizations, less than one-fourth of the analysts used CASE tools. Kusters and Wijers [14] found in their analysis of 262 Dutch organizations that in 20% of the organizations more than 75% of analysts used CASE tools on a regular basis and in 18% the rate was between 51% and 75%. Even so, in 37% of the organizations, 25% or less of the analysts used CASE tools on a regular basis. Besides the waste of the initial investment in CASE tools, the low rate is alarming because most empirical studies indicate positive rather than negative impact of CASE tools on systems development effectiveness. Norman and Nunamaker [17] reported that software engineers generally perceived their productivity being improved with the use of CASE technology. Banker and Kauffman [2] found an order of magnitude increase in software development productivity in their analysis of 20 projects that applied a CASE tool emphasizing reusability. Aaen et al. [1] found that about 72% of their sample perceived the objectives of improved quality of systems, improved systems development procedures, and increased standardization were met to a significant degree, but about 60% of respondents assessed the objective of improved productivity was met only to a minor degree. 47% of the respondents indicated good profitability of CASE investments while 31% assessed it as poor. The author examines attitudes toward CASE usage in a wide variety of organizations. CASE (Computer-Aided Software/Systems Engineering) tools are claimed to increase information systems and software development effectiveness in terms of productivity of systems development and the quality of the developed systems. However, the results of prior research on CASE adoption [1, 6, 14, 17] are to some extent paradoxical. While most research reports positive rather than negative impact on the quality of developed systems , and to a lesser extent on the productivity of the development process, the actual use of CASE technology has been much less than one would expect. Kemerer [13], for example, reports that one year after introduction, 70% …
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TL;DR: An exploratory evaluation of the T HE Theory of Reasoned Action and extensions are presented to attempt to better understand ethical decisions in computer use.
Abstract: The authors present the results of an exploratory survey identifying users' attitudes and behavior when computer privacy and resource-ownership situations are encountered. T HE Theory of Reasoned Action (TRA), frequently used to describe ethical decision-making behavior, relates attitudes and social norms to individual behavioral intentions [2, 17]. The components of this theory appear to be present in ethical decision situations [11], but they may be insufficient in their usual characterizations to completely describe an ethical decision process [17, 18]. Computer users face an increasing number of ethical dilemmas in their use of computers, and novel situations appear with each new technology. This article presents an exploratory evaluation of the TRA and extensions to attempt to better understand ethical decisions in computer use.
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TL;DR: This study examines the reasons for IS outsourcing from a somewhat different perspective----that of labor market economics, which reflects the increasing trend toward “taking the workers back out” in IS outsourcing.
Abstract: growing trend. I N recent years, information systems (IS) outsourcing has become so pervasive it can no longer be ignored. An important question is why firms choose to outsource IS work. This question has been considered from a number of perspectives. Lacity and Hirschheim [14], for example, showed how the dynamics of internal politics led to IS outsourcing. Loh and Venkatraman [15] suggested that the outsourcing behavior of a prominent blue-chip company, such as Eastman Kodak, can lead to imitative behavior throughout the IS community. In contrast, our study examines the reasons for IS outsourcing from a somewhat different perspective----that of labor market economics. From this perspective, outsourcing is a result of how firms respond to the costs and benefits of employment arrangements with their IS workers. In the classic economic view of labor markets, workers move freely and frequently between jobs to take advantage of better employment opportunities. According to Doeringer and Piore [8], the traditional long-term employment arrangement replaced the open labor market because it afforded principals (employers) greater control and influence over agents (their employees). More recently, however, firms have been moving away from the traditional, long-term employment arrangement (insourcing) to relatively shorter-term, market-mediated arrangements (outsourcing). Outsourcing reflects the increasing trend toward “taking the workers back out” [19], in which organizations alter the work relationship with their employees by reducing the duration of employment and their degree of administrative control over workers. In IS outsourcing, taking the workers back out can occur in many ways. A firm can either contract directly with an IS professional for his or her services or contract indirectly with an employee leasing company, a consulting firm, or an IS service provider. Such practices can benefit both the firm and the IS worker. Although the Eastman Kodak outsourcing arrangement represents total IS outsourcing and has become a popular practice in industry, firms can also choose to selectively outsource for particular IS skills or jobs. But why do firms choose to selectively or completely outsource IS? From a labor market perspective, outsourcing is the response of firms to the costs and disadvantages of the traditional permanent work arrangement that arise from dynamic changes in technology and the environment. Due to the increasingly rapid evolution of information technology (IT), IS work is characterized by skills deterioration and specific skills shortages [16, 25]. Thus, a firm’s ability to find and acquire the necessary IS skills is paramount. Under these circumstances, relying on retraining a permanent work force may be cost prohibitive. In addition, because IT evolves so rapidly, by the time a firm invests in and trains its IS staff on a certain technology, that technology may be obsolete. There are indications that firms face increasing turbulence in the environment. As firms become inteEmployment Outsourcing
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TL;DR: GVU's WWW User Surveys were initially conducted during January 1994 and thereafter surveys were administered approximately every six months thereafter, using non-random sampling techniques.
Abstract: Background Vast amounts of attention and resources have recently been devoted towards the World Wide Web (WWW) [Berners-Lee 94], but relatively little research has been conducted that examines Web usage and societal implications. With the goals of understanding the Web user population and promoting the Web as a viable surveying medium, GVU's WWW User Surveys were initially conducted during January 1994. Subsequent surveys were administered approximately every six months thereafter. The surveys employ non-random sampling techniques, which limit the ability of the results to generalize to the entire Web population. Each survey is conducted using the limited interactivity of the Web, where users point and click on responses within their Web browsers and submit results to a centralized server for processing. Each survey is conducted for a one month period.