In this article we offer a view that suggests that a firm's critical resources may span firm boundaries and may be embedded in interfirm resources and routines. We argue that an increasingly important unit of analysis for understanding competitive advantage is the relationship between firms and identify four potential sources of interorganizational competitive advantage: (1) relation-specific assets, (2) knowledge-sharing routines, (3) complementary resources/capabilities, and (4) effective governance. We examine each of these potential sources of rent in detail, identifying key subprocesses, and also discuss the isolating mechanisms that serve to preserve relational rents. Finally, we discuss how the relational view may offer normative prescriptions for firm-level strategies that contradict the prescriptions offered by those with a resource-based view or industry structure view.

https://www.jstor.org/stable/pdfplus/259056.pdf

The Relational View: Cooperative Strategy and Sources of Interorganizational Competitive Advantage

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Ten years ago, we presented the DeLone and McLean Information Systems (IS) Success Model as a framework and model for measuring the complex-dependent variable in IS research. In this paper, we discuss many of the important IS success research contributions of the last decade, focusing especially on research efforts that apply, validate, challenge, and propose enhancements to our original model. Based on our evaluation of those contributions, we propose minor refinements to the model and propose an updated DeLone and McLean IS Success Model. We discuss the utility of the updated model for measuring e-commerce system success. Finally, we make a series of recommendations regarding current and future measurement of IS success.

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The DeLone and McLean Model of Information Systems Success: A Ten-Year Update

计量经济分析 = Econometric analysis

We explore the theoretical foundations of value creation in e-business by examining how 59 American and European e-businesses that have recently become publicly traded corporations create value. We observe that in e-business new value can be created by the ways in which transactions are enabled. Grounded in the rich data obtained from case study analyses and in the received theory in entrepreneurship and strategic management, we develop a model of the sources of value creation. The model suggests that the value creation potential of e-businesses hinges on four interdependent dimensions, namely: efficiency, complementarities, lock-in, and novelty. Our findings suggest that no single entrepreneurship or strategic management theory can fully explain the value creation potential of e-business. Rather, an integration of the received theoretical perspectives on value creation is needed. To enable such an integration, we offer the business model construct as a unit of analysis for future research on value creation in e-business. A business model depicts the design of transaction content, structure, and governance so as to create value through the exploitation of business opportunities. We propose that a firm's business model is an important locus of innovation and a crucial source of value creation for the firm and its suppliers, partners, and customers. Copyright © 2001 John Wiley & Sons, Ltd.

https://uazuay.edu.ec/bibliotecas/e-business/Value_Creation_in_E-Business.pdf

Value creation in E-business

Big data, the authors write, is far more powerful than the analytics of the past. Executives can measure and therefore manage more precisely than ever before. They can make better predictions and smarter decisions. They can target more-effective interventions in areas that so far have been dominated by gut and intuition rather than by data and rigor. The differences between big data and analytics are a matter of volume, velocity, and variety: More data now cross the internet every second than were stored in the entire internet 20 years ago. Nearly real-time information makes it possible for a company to be much more agile than its competitors. And that information can come from social networks, images, sensors, the web, or other unstructured sources. The managerial challenges, however, are very real. Senior decision makers have to learn to ask the right questions and embrace evidence-based decision making. Organizations must hire scientists who can find patterns in very large data sets and translate them into useful business information. IT departments have to work hard to integrate all the relevant internal and external sources of data. The authors offer two success stories to illustrate how companies are using big data: PASSUR Aerospace enables airlines to match their actual and estimated arrival times. Sears Holdings directly analyzes its incoming store data to make promotions much more precise and faster.

Big data: the management revolution.

How do computers contribute to business performance and economic growth? Even today, most people who are asked to identify the strengths of computers tend to think of computational tasks like rapidly multiplying large numbers. Computers have excelled at computation since the Mark I (1939), the first modern computer, and the ENIAC (1943), the first electronic computer without moving parts. During World War II, the U.S. government generously funded research into tools for calculating the trajectories of artillery shells. The result was the development of some of the first digital computers with remarkable capabilities for calculation—the dawn of the computer age. However, computers are not fundamentally number crunchers. They are symbol processors. The same basic technologies can be used to store, retrieve, organize, transmit, and algorithmically transform any type of information that can be digitized—numbers, text, video, music, speech, programs, and engineering drawings, to name a few. This is fortunate because most problems are not numerical problems. Ballistics, code breaking, parts of accounting, and bits and pieces of other tasks involve lots of calculation. But the everyday activities of most managers, professionals, and information workers involve other types of

/pdf/beyond-computation-information-technology-organizational-3qblot8ccg.pdf

Beyond Computation: Information Technology, Organizational Transformation and Business Performance

The retationship between information technology IT and productivity is widely discussed but little understood. Delivered computing power in the U.S. economy has increased by more than two orders of magnitude since 1970 (Figure 1) yet productivity, especially in the service sector, seems to have stagnated (Figure 2). Given the enormous promise of IT to usher in «the biggest technological revolution men have known» [29], disillusionment and even frustration with the technology is increasingly evident in statements like «No, computers do not boost productivity, at least not most of the time» [13]. The increased interest in the «productivity paradox,» as it has become known, has engendered a significant amount of research, but thus far, this has only deepened the mystery

The productivity paradox of information technology

We investigate the hypothesis that the combination of three related innovations—1) information technology (IT), 2) complementary workplace reorganization, and 3) new products and services—constitute a significant skill-biased technical change affecting labor demand in the United States. Using detailed firm-level data, we find evidence of complementarities among all three of these innovations in factor demand and productivity regressions. In addition, firms that adopt these innovations tend to use more skilled labor. The effects of IT on labor demand are greater when IT is combined with the particular organizational investments we identify, highlighting the importance of IT-enabled organizational change.

/pdf/information-technology-workplace-organization-and-the-demand-lnmkifa9e9.pdf

Information Technology, Workplace Organization, and the Demand for Skilled Labor: Firm-Level Evidence

The "productivity paradox" of information systems IS is that, despite enormous improvements in the underlying technology, the benefits of IS spending have not been found in aggregate output statistics. One explanation is that IS spending may lead to increases in product quality or variety which tend to be overlooked in the aggregate statistics, even if they increase output at the firm-level. Furthermore, the restructuring and cost-cutting that are often necessary to realize the potential benefits of IS have only recently been undertaken in many firms.

Our study uses new firm-level data on several components of IS spending for 1987-1991. The dataset includes 367 large firms which generated approximately 1.8 trillion dollars in output in 1991. We supplemented the IS data with data on other inputs, output, and price deflators from other sources. As a result, we could assess several econometric models of the contribution of IS to firm-level productivity.

Our results indicate that IS spending has made a substantial and statistically significant contribution to firm output. We find that the gross marginal product MP for computer capital averaged 81% for the firms in our sample. We find that the MP for computer capital is at least as large as the marginal product of other types of capital investment and that, dollar for dollar, IS labor spending generates at least as much output as spending on non-IS labor and expenses. Because the models we applied were similar to those that have been previously used to assess the contribution of IS and other factors of production, we attribute the different results to the fact that our data set is more current and larger than others explored. We conclude that the productivity paradox disappeared by 1991, at least in our sample of firms.

/pdf/paradox-lost-firm-level-evidence-on-the-returns-to-23bx7pcv4x.pdf

Erik Brynjolfsson

Papers

Big data: the management revolution.

Beyond Computation: Information Technology, Organizational Transformation and Business Performance

The productivity paradox of information technology

Information Technology, Workplace Organization, and the Demand for Skilled Labor: Firm-Level Evidence

Paradox Lost? Firm-Level Evidence on the Returns to Information Systems Spending