1,706 research outputs found
BUSINESS PROCESS OUTSOURCING AND MARKET VALUE OF FIRMS
Recent trends suggest that business process outsourcing is an important contemporary phenomenon that is likely to have profound effects on organizations. This study examines whether there is a relationship between business process outsourcing and firm valuation and whether this relationship depends on the nature of the process outsourced and the location it is outsourced to. Using 375 public announcements of process outsourcing initiatives of Fortune 1000 firms we empirically test our hypotheses using an event study methodology. Our results indicate that business process outsourcing creates modest positive above normal returns. We also found that outsourcing knowledge intensive processes is more value adding than outsourcing labor intensive processes and offshore outsourcing is more value adding than onshore outsourcing. Interestingly, we found that among the options explored offshore outsourcing of knowledge intensive processes could reduce firm valuation
Software Process Management: An Organizational Learning Perspective
We draw from the quality management and organizational learning literatures to develop a descriptive model of software process management. These literature streams suggest that the concepts of process design, process control, learning through experimentation and learning through knowledge codification and reuse are important in the development of process capability. We define each of these concepts as latent constructs, and then propose a descriptive model of software process management. The model was tested using data collected from 123 IS units in Fortune 1000 firms and large government agencies. Our empirical results suggest that process design efficacy and process control have a positive relationship with software process capability. Furthermore, both learning through experimentation and learning through knowledge codification and reuse enable the design of efficacious processes and facilitate the development of appropriate standards to control the development process. Implications of our findings for IS research and practice are discussed
Influence of Confining Pressure on the Crack Growth Behavior in a Highly Filled Elastomer
Quality Management in Systems Development: An Organizational System Perspective
We identify top management leadership, a sophisticated management infrastructure, process management efficacy, and stakeholder participation as important elements of a quality-oriented organizational system for software development. A model interrelating these constructs and quality performance is proposed. Data collected through a national survey of IS executives in Fortune 1000 companies and government agencies was used to test the model using a Partial Least Squares analysis methodology. Our results suggest that software quality goals are best attained when top management creates a management infrastructure that promotes improvements in process design and encourages stakeholders to evolve the design of the development processes. Our results also suggest that all elements of the organizational system need to be developed in order to attain quality goals and that piecemeal adoption of select quality management practices are unlikely to be effective. Implications of this research for IS theory and practice are discussed
Strategic Implications of Information Systems Resources and Capabilities: A Competence-Based Model
This paper examines the relationship between information systems capabilities and firm performance using resource-based theory as the theoretical lens. We identify and define three key constructs: IS resources, IS capabilities and IS competencies. We develop a research model that relates these constructs and firm performance. The basic premise of our model is that IS competencies have a direct impact on firm performance where as IS resources and capabilities are antecedents to IS competencies. Implications of this study for future research and practice are discussed
Structure and Liquidity of B2B Hubs: An Industrial Organization Economics Theoretic Framework
Impact of Information Systems Resources and Capabilities on Firm Performance: A Resource-Based Perspective
In this paper, we draw from the resource-based theory to examine how information systems resources and capabilities impact firm performance. A basic premise of this paper is that variations in firm performance can be explained by how effective it is in using information technology to support and enhance its core competencies. In contrast to past studies that have implicitly assumed that information systems assets could have direct effects on firm performance, this study draws from the resource complementarity arguments and posits that it is the targeted use of information systems assets that is likely to be rent yielding. We develop the theoretical underpinnings of this premise and propose a model that interrelates IS resources, IS capabilities, IT support for core competencies, and firm performance
Managerial Response to Online Compliments: Helpful or Harmful?
There is limited systematic research on managerial response strategies to online consumer compliments and positive e-WOM. In this paper, we synthesize altruism theory, social exchange theory and psychological reactance theory to develop our theoretical model that explores the mechanism through which online consumer compliments influence consumer attitudes and the mechanisms through which managerial responses can alter these influences. We test our model using data from TripAdvisor.com—a leading travel review platform. Using advanced text analytics we extract and code the variables in our model from the reviews and the managerial responses to these reviews in Tripadvisor.com
Analyzing the Impact of Genetic Parameters on Gene Grouping Genetic Algorithm and Clustering Genetic Algorithm
Genetic Algorithms are stochastic randomized procedures used to solve search and optimization problems. Many multi-population and multi-objective Genetic Algorithms are introduced by researchers to achieve improved performance. Gene Grouping Genetic Algorithm (GGGA) and Clustering Genetic Algorithm (CGA) are of such kinds which are proved to perform better than Standard Genetic Algorithm (SGA). This paper compares the performance of both these algorithms by varying the genetic parameters. The results show that GGGA provides good solutions, even to large-sized problems in reasonable computation time compared to CGA and SGA. Keywords: Stochastic, randomized, multi-population, Gene Grouping Genetic Algorithm, Clustering Genetic Algorithm
Characteristics of Interorganizational Relationships and the Structure of Interorganizational Systems: An Exploratory Study
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