A critique of diffusion theory as a managerial framework for understanding adoption of software engineering innovations

Bayer, Judy; Melone, Nancy Paule

doi:10.1109/hicss.1988.11820

Cited by 26 publications

(37 citation statements)

References 4 publications

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“…Firms tend to adopt a technology based on their innate characteristics, which fall into five categories: (1) innovative firms with a higher tolerance for the risk of uncertain results in an acceptable time frame, (2) early adopters, (3) early majority, (4) late majority, and (5) laggards .Characteristics of the innovation emphasized by the theory include relative advantage of the innovation compared to existing practices such as convenience, efficiency, and profitability. Other characteristics include whether the new technology is compatible with existing processes and the ease (or complexity) of its use (Bayer & Melone, 1989;Zmud, 1982).…”

Section: Diffusion Theory Overviewmentioning

confidence: 99%

Software Adoption in Law Firms: IT Staff Opinion Leader Influence on Top Management

Quttainah¹,

Paczkowski²

2015

JMPP

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Law firms have characteristics that inherently inhibit the adoption of technology that increases efficiency. Ironically, efficiency reduces revenue in law firms. Billable hours spent on inefficient tasks, such as manual billing or legal research using books rather than computer software, is generally directly billed to clients. In order to facilitate diffusion of new software technology, the top management decision-makers must be convinced by reliable and trusted opinion leaders backed by an innovation champion that it would be profitable to do so. In law firms, these opinion leaders are predominantly embodied in the firms' dedicated information technology (IT) staff.

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Section: Diffusion Theory Overviewmentioning

confidence: 99%

Software Adoption in Law Firms: IT Staff Opinion Leader Influence on Top Management

Quttainah¹,

Paczkowski²

2015

JMPP

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“…Results of the cross-loading analysis showed that all items load higher on their respective intended latent variable compared to other latent variables. 2 Therefore, discriminant validity at the indicator level is ensured. Figure 2 shows all the path coefficients, significance levels and variance explained in the research model.…”

Section: Ds1mentioning

confidence: 99%

“…For the purpose of evaluating the construct both actual usage and intention of the future usage of OTC CCP by organizations have been employed. Adopters may make a binary decision to adopt or reject, or may choose differing levels of CCP usage (Bayer and Melone, 1989). Concerning adoption alone, a binary variable is applied based on whether an organization uses/is a member of OTC CCP or not.…”

Section: Adoption Constructmentioning

confidence: 99%

Adoption of a Centralised Post-Trade Processing Market Infrastructure after the Credit Crisis

Lewandowska

2010

Lecture Notes in Business Information Processing

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The recent credit crisis has heightened the awareness of credit risk among financial markets' regulators and participants. However, despite the public discussion on centralized processing systems for the off-exchange traded (Over-The-Counter, OTC) transactions no research has been conducted on the factors that could explain their adoption among market participants. With this study, an attempt is made to cover this gap, in parallel opening the space for further scientific investigation on centralized clearing for OTC derivatives. Based on the Diffusion of Innovation Theory, this first empirical study in the OTC clearing area introduces a model aimed at identifying the drivers and inhibitors for the adoption of an IT-enabled innovation in the form of centralized clearing by the financial organizations. The partial least squares structural equation modeling technique was applied to analyze the results of the survey with the Heads of Clearing/ Operations in various international financial institutions.

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“…A study of technology adoption in the Brazilian medical equipment industry showed that organization factors are the largest contributors to the adoption of an innovation, specifically the presence or absence of leadership supporting the implementation (Zilber et al 2006). Similarly, a study sponsored by the Software Engineering Institute showed that social systems are the main enablers of innovation diffusion in software engineering organizations (Bayer and Melone 1989).…”

Section: Experience In Systems Engineering Cost Estimationmentioning

confidence: 99%

From Research to Reality: Making COSYSMO a Trusted Estimation Tool in Your Organization

Valerdi

Miller

2007

INCOSE International Symp

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Abstract. As the COSYSMO model transitions from the development phase into the adoption phase, industry stakeholders are beginning to embrace the model and integrate it into their existing measurement processes. To date, much of the guidance provided by the COSYSMO development team has been focused on the usage of the model. In the adoption phase, users need guidance on how to adopt the model as they work to convince management to invest resources in competition with other process improvement initiatives. This paper outlines a process which provides guidance on the piloting and institutionalization of COSYSMO designed to help scope the effort needed for successful adoption and implementation. The process has been developed as a result of interactions with over a dozen organizations that have participated in the industry calibration of the model and have begun to integrate the model into their internal processes. The knowledge obtained from working with these organizations is reflected in this process. Experience in Systems Engineering Cost EstimationThe motivation for this adoption process came from witnessing several organizations struggle with the adoption of credible tools as a result of organizational obstacles. Literature on the topic of technology and innovation adoption points to organizational factors as the main drivers of adoption. A study of technology adoption in the Brazilian medical equipment industry showed that organization factors are the largest contributors to the adoption of an innovation, specifically the presence or absence of leadership supporting the implementation (Zilber et al 2006). Similarly, a study sponsored by the Software Engineering Institute showed that social systems are the main enablers of innovation diffusion in software engineering organizations (Bayer and Melone 1989).The COSYSMO working group has had an influx of new members. These members lack the historical discussions and background that drove key decisions and assumptions in COSYSMO during its six year development. An organization looking at COSYSMO for the first time may have tacit knowledge of cost modelling in general but may struggle when adopting a new model like COSYSMO. Organizations are jumping on the bandwagon with little or no training and limited knowledge of parameter definition discussions in the absence of any substantial implementation guidance or lessons learned to leverage. In an attempt to help prevent COSYSMO from falling into the silver bullet trap (i.e., "We tried to use COSYSMO but it didn't work"), this paper is aimed at providing just that guidance. By following the systematic

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A critique of diffusion theory as a managerial framework for understanding adoption of software engineering innovations

Cited by 26 publications

References 4 publications

Software Adoption in Law Firms: IT Staff Opinion Leader Influence on Top Management

Software Adoption in Law Firms: IT Staff Opinion Leader Influence on Top Management

Adoption of a Centralised Post-Trade Processing Market Infrastructure after the Credit Crisis

From Research to Reality: Making COSYSMO a Trusted Estimation Tool in Your Organization

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