The impact of IT capabilities on firm performance: The mediating roles of absorptive capacity and supply chain agility
01 Feb 2013-Vol. 54, Iss: 3, pp 1452-1462
TL;DR: A model to examine how IT capabilities affect firm performance through absorptive capacity and supply chain agility in the supply chain context is proposed and concludes with implications and suggestions for future research.
Abstract: Researchers and practitioners regard information technology (IT) as a competitive tool. However, current knowledge on IT capability mechanisms that affect firm performance remains unclear. Based on the dynamic capabilities perspective and the view of a hierarchy of capabilities, this article proposes a model to examine how IT capabilities (i.e., flexible IT infrastructure and IT assimilation) affect firm performance through absorptive capacity and supply chain agility in the supply chain context. Survey data show that absorptive capacity and supply chain agility fully mediate the influences of IT capabilities on firm performance. In addition to the direct effects, absorptive capacity also has indirect effects on firm performance by shaping supply chain agility. We conclude with implications and suggestions for future research.
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Swansea University1, University of Bradford2, Loughborough University3, University of Bedfordshire4, Prin. L. N. Welingkar Institute of Management Development and Research5, Aston University6, University of Edinburgh7, Indian Institute of Technology Delhi8, Delft University of Technology9, Copenhagen Business School10, Norwich University11, Government of Tamil Nadu12, University of Greenwich13, Indian Institute of Management Tiruchirappalli14, Symbiosis International University15, University of Essex16, University of the West of England17, Capgemini18
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References
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TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
Abstract: The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi square test, in addit...
56,555 citations
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01 Jan 1973
TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
Abstract: Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each.
Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today - e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations.
Table of Contents
1. Introduction.
I. PREPARING FOR A MULTIVARIATE ANALYSIS.
2. Examining Your Data.
3. Factor Analysis.
II. DEPENDENCE TECHNIQUES.
4. Multiple Regression.
5. Multiple Discriminant Analysis and Logistic Regression.
6. Multivariate Analysis of Variance.
7. Conjoint Analysis.
8. Canonical Correlation Analysis.
III. INTERDEPENDENCE TECHNIQUES.
9. Cluster Analysis.
10. Multidimensional Scaling.
IV. ADVANCED AND EMERGING TECHNIQUES.
11. Structural Equation Modeling.
12. Emerging Techniques in Multivariate Analysis.
Appendix A: Applications of Multivariate Data Analysis.
Index.
37,124 citations
TL;DR: In this paper, the authors argue that the ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends is critical to its innovative capabilities.
Abstract: In this paper, we argue that the ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends is critical to its innovative capabilities. We label this capability a firm's absorptive capacity and suggest that it is largely a function of the firm's level of prior related knowledge. The discussion focuses first on the cognitive basis for an individual's absorptive capacity including, in particular, prior related knowledge and diversity of background. We then characterize the factors that influence absorptive capacity at the organizational level, how an organization's absorptive capacity differs from that of its individual members, and the role of diversity of expertise within an organization. We argue that the development of absorptive capacity, and, in turn, innovative performance are history- or path-dependent and argue how lack of investment in an area of expertise early on may foreclose the future development of a technical capability in that area. We formulate a model of firm investment in research and development (R&D), in which R&D contributes to a firm's absorptive capacity, and test predictions relating a firm's investment in R&D to the knowledge underlying technical change within an industry. Discussion focuses on the implications of absorptive capacity for the analysis of other related innovative activities, including basic research, the adoption and diffusion of innovations, and decisions to participate in cooperative R&D ventures. **
31,623 citations
"The impact of IT capabilities on fi..." refers background in this paper
...Furthermore, absorptive capacity ensures efficient internal knowledge processing [10,18,69,71,82]....
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...Absorptive capacity refers to a firm's ability to recognize the value of new external knowledge as well as assimilate and commercialize it [10,18,71,82]....
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...Absorptive capacity refers to a firm's ability to value, assimilate, and apply new knowledge received from external sources, such as customers, suppliers, or alliance partners [18,42,82]....
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..., customers, suppliers, competitors, and other channel partners) and to apply the new knowledge to identify business opportunities in the market [18,42,82]....
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...Absorptive capacity involves a collection of routines to manage knowledge and the cumulative influences of continuous learning in the firm [10,18,71]....
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TL;DR: The dynamic capabilities framework as mentioned in this paper analyzes the sources and methods of wealth creation and capture by private enterprise firms operating in environments of rapid technological change, and suggests that private wealth creation in regimes of rapid technology change depends in large measure on honing intemal technological, organizational, and managerial processes inside the firm.
Abstract: The dynamic capabilities framework analyzes the sources and methods of wealth creation and capture by private enterprise firms operating in environments of rapid technological change. The competitive advantage of firms is seen as resting on distinctive processes (ways of coordinating and combining), shaped by the firm's (specific) asset positions (such as the firm's portfolio of difftcult-to- trade knowledge assets and complementary assets), and the evolution path(s) it has aflopted or inherited. The importance of path dependencies is amplified where conditions of increasing retums exist. Whether and how a firm's competitive advantage is eroded depends on the stability of market demand, and the ease of replicability (expanding intemally) and imitatability (replication by competitors). If correct, the framework suggests that private wealth creation in regimes of rapid technological change depends in large measure on honing intemal technological, organizational, and managerial processes inside the firm. In short, identifying new opportunities and organizing effectively and efficiently to embrace them are generally more fundamental to private wealth creation than is strategizing, if by strategizing one means engaging in business conduct that keeps competitors off balance, raises rival's costs, and excludes new entrants. © 1997 by John Wiley & Sons, Ltd.
27,902 citations
"The impact of IT capabilities on fi..." refers background in this paper
...Dynamic capability refers to a firm's ability to integrate, build, and reconfigure internal and external competencies [68,77]....
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...The dynamic capabilities perspective is awidely applied paradigm to explain variance in performance across competing firms [5,68,77,83,84]....
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...Hence, absorptive capacity enables the firm to sense and seize business opportunities that can directly affect firm performance [12,68,77]....
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TL;DR: This book deals with probability distributions, discrete and continuous densities, distribution functions, bivariate distributions, means, variances, covariance, correlation, and some random process material.
Abstract: Chapter 3 deals with probability distributions, discrete and continuous densities, distribution functions, bivariate distributions, means, variances, covariance, correlation, and some random process material. Chapter 4 is a detailed study of the concept of utility including the psychological aspects, risk, attributes, rules for utilities, multidimensional utility, and normal form of analysis. Chapter 5 treats games and optimization, linear optimization, and mixed strategies. Entropy is the topic of Chapter 6 with sections devoted to entropy, disorder, information, Shannon’s theorem, demon’s roulette, Maxwell– Boltzmann distribution, Schrodinger’s nutshell, maximum entropy probability distributions, blackbodies, and Bose–Einstein distribution. Chapter 7 is standard statistical fare including transformations of random variables, characteristic functions, generating functions, and the classic limit theorems such as the central limit theorem and the laws of large numbers. Chapter 8 is about exchangeability and inference with sections on Bayesian techniques and classical inference. Partial exchangeability is also treated. Chapter 9 considers such things as order statistics, extreme value, intensity, hazard functions, and Poisson processes. Chapter 10 covers basic elements of risk and reliability, while Chapter 11 is devoted to curve fitting, regression, and Monte Carlo simulation. There is an ample number of exercises at the ends of the chapters with answers or comments on many of them in an appendix in the back of the book. Other appendices are on the common discrete and continuous distributions and mathematical aspects of integration.
19,893 citations
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