Limits to the diffusion of innovation: A literature review and integrative model

By Jason MacVaugh, Francesco Schiavone. 2010

308 citations recorded by the source corpus.

Subfields: Computer Science Applications, Management Science and Operations Research, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/09b1211782353e5ee2e203d319d0ff916082585d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Science Applications

1. Ellen Enkel
2. Shaldon Leparan Suntu
3. Samwel Macharia Chege
4. Daoping Wang
5. Iis P. Tussyadiah

In Management Science and Operations Research

1. Tariq Iqbal Khan
2. Anna Bergek
3. Ellen Enkel
4. Shaldon Leparan Suntu
5. Samwel Macharia Chege
6. Daoping Wang
7. Iis P. Tussyadiah

In Sociology and Political Science

1. Ingrid Mignon
2. Tariq Iqbal Khan
3. Anna Bergek
4. Ellen Enkel
5. Shaldon Leparan Suntu
6. G. Sundberg
7. Samwel Macharia Chege
8. Daoping Wang

Citations in the corpus

• Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices (2016, background): “Whereas theory on new product development and marketing assumes that utility is a main determinant for adoption, sociological theory explains adoption and resistance in terms of interaction between the technology and its social context (MacVaugh and Schiavone, 2010).”
• Innovation & Its Diffusion in Business: Concept, Stages & Procedural Practices (2020, background): “However, innovation becomes beneficial only when it is diffused through communication over time through certain channels among the social system members.”
• Who invests in renewable electricity production? Empirical evidence and suggestions for further research (2013, background): “…(MacVaugh and Schiavone, 2010),13 (ii) its compatibility with existing values and needs (Rogers, 1983) as well as with complementary technologies (MacVaugh and Schiavone, 2010) and (iii) understandability, which is influenced by, for example its degree of complexity and the trialability and…”
• Impact of information technology innovation on firm performance in Kenya (2019, methodology): “In this model, technological innovation is not only linked to the evolution of innovation, but also to the way in which it is di ff used within the organization (Macvaugh & Schiavone, 2010).”
• A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism (2020, background): “…offers information on concepts underlying organizational adoption and diffusion of innovation (Frambach, 1993; Frambach & Shillewaert, 2002; MacVaugh & Schiavone, 2010) and transformational leadership (Bass, 1990), a factor proven in the literature to accelerate technological innovation in…”