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The purpose of this paper is to propose a comprehensive theoretical framework to explain the different diffusion dynamics of a technology realized under an open source (OS) regime vs a technology realized under a closed-proprietary (CP) regime.

Following a systematic combining approach, theoretical predictions derived from literature on diffusion of innovation and on open innovation were matched with empirical observations derived from a case study of two mobile operation systems, which were released under different technological regimes.

This paper proposes a theoretical framework and a set of original theoretical propositions that can help to explain the differences in the diffusion dynamics of technologies that are released under different regimes (i.e. CP vs OS).

This paper provides managers a better understanding of the diffusion dynamics of technologies released according to an open innovation strategy. In addition, the empirical case study improves the understanding of an important industry (the MOS industry) that has not been fully investigated from the innovation diffusion perspective. Nevertheless, the efficacy and generalizability of the theoretical framework proposed in this paper require future empirical tests.

This paper makes an original contribution to the open innovation and innovation diffusion literature by linking, in a conceptual model, three antecedents of the diffusion of a new technology that previous literature has considered only separately: the regime under which the technology is released (OS vs CP), the contingencies related to the characteristics of the technology and to the network of its adopters, and the resulting barriers to adoption.

The purpose of this paper is to undertake research on the relationship of firm heterogeneity and innovation diffusion performance, and the role of absorptive capacity in this relationship.

Based on the diffusion of innovation theory, enterprise heterogeneity directly affects the evaluation stage (considering whether to adopt it) and the experimental stage (observing whether it is suitable for one’s own situation) of the diffusion process. Therefore, the paper uses a structural equation model to construct the influencing factors model of enterprise heterogeneity on technology diffusion. Furthermore, questionnaires were distributed to 236 enterprises with different scales, nature and location to explore the impact of heterogeneity on technology diffusion with scientific, objective and comprehensive data.

Firm heterogeneity has a positive effect on absorptive capacity and absorptive capacity has a positive effect on technological innovation diffusion performance. Thus, absorptive capacity plays an intermediary role in the effect on enterprise heterogeneity and technological innovation diffusion performance. More interestingly, the authors get some results that are not entirely consistent with the theoretical assumptions.

Firm heterogeneity plays a central role in the process of innovation diffusion. Enterprises should build internal management platforms to enhance cooperation among employees, and establish links with other enterprises for opportunities for win-win cooperation. In addition, enterprises should control the frequency of internal activities, which will undermine the enthusiasm of enterprise members to participate in technology sharing.

This paper explores the interaction between technology potential, cooperation frequency and absorptive capacity from the perspective of systems theory. The findings enrich the theory of innovation diffusion, and explore the inherent reasons why enterprise heterogeneity affects innovation diffusion. Furthermore, the theory that intra-firm cooperation promotes innovation diffusion is not always correct.

The purpose of this study was to explore and identify factors affecting adoption and implementation of information and communication technology (ICT) in large ICT‐experienced Australian construction organizations. During 2002 the researchers undertook an online survey, supplemented by a hardcopy collection option, to gather data from three major construction organizations with many years experience with implementing and adopting IT. The analysis concentrated on a common class of ICT adopted across the three organizations so that factor analysis could be validly undertaken. Results identified 11 factors that were found to influence ICT diffusion and adoption by the organizations that were grouped into management, individual, technology and workplace environment categories. These concurred with theory from the change management, innovation diffusion and organizational learning literature. Further, in‐depth qualitative analysis through case studies (beyond the scope of this paper) also helped to explain and make sense of the results. The results help to better explain human related factors in particular in terms of the broader and emerging literature of organizational learning and innovation adoption with a clear focus on how the people‐side of ICT diffusion and adoption is undertaken. This ICT diffusion and adoption study is undertaken at the firm‐level (micro analysis) as opposed to the industry level (macro analysis) and so provides insights into the interplay between diffusion and adoption concepts.

Diffusion of many successful communication technologies, like telephony and television technology, follows an almost perfect S‐shaped curve. This curve implies that, after their introduction, subsequent sales of products on the basis of these technologies can be predicted accurately. However, the diffusion of other breakthroughs in communication technologies, like interactive television, videotelephony or broadband mobile communication technology, shows a more erratic pattern. Introduction of these technologies is often postponed or, once introduced, they are quickly withdrawn from the market after the first disappointing results. Rather than distinguishing alternative patterns, this article shows that the S‐shaped curve and the more erratic patterns represent subsequent phases in one pattern of development and diffusion of breakthrough communication technologies. Three phases are distinguished in this pattern. Managerial implications of the differences between these phases are discussed. the paper shows that a company trying to introduce a new communication technology has to adopt different strategies in each phase.

The purpose of this paper is to investigate the diffusion patterns of knowledge in inspiring technological innovations and to enable monitoring development trends of technological innovations based on patent data analysis, thus, to manage knowledge wisely to innovate.

The notion of knowledge innovation potential (KIP) is proposed to measure the innovativeness of knowledge by the cumulative number of patents originated from its inspiration. KIP calculating formula is regressed in forms of two specific diffusion models by conducting a series of empirical studies with the patent-based indicators involving forward and backward citation numbers to reveal knowledge managing strategies regarding innovative activities.

Two specific diffusion models for regressing KIP formula are compared by empirical studies with the result indicating the Gompertz model has higher accuracy than the Logistic model to describe the developing curve of technological innovations. Moreover, the analysis of patent-based indicators over diffusion stages also revealed that patents applied at earlier diffusion stages normally has higher forward citation numbers indicating higher innovativeness meanwhile the patents applied at the latter stages usually requiring more knowledge inflows observed by their larger non-patent citation and backward citation amounts.

Although there is a large body of literature concerning knowledge-based technological innovation, there still room for discussing the mechanism of how knowledge diffuses and inspired knowledge. To the best of authors' knowledge, this study is the first attempt to quantitate the innovativeness of knowledge in technological innovation from the knowledge diffusion perspective with findings to support rational knowledge management related to innovation activities.

An integrating model which, based on a review of the most recent theoretical and empirical studies, offers an overall view of the factors affecting the adoption of Advanced Manufacturing Technologies (AMTs) is presented. The model is intended to be a base for the managers′ analysis of the implementation of AMTs, and enables the four areas affecting adoption (Industry, Firm, Technology and Supply) to be approached in a more integrated way.

Advanced construction technologies (ACTs) are transforming infrastructure projects, yet there has been little research into and theorization of the process by which these innovations are diffused. The purpose of this paper is to address this paucity of research by exploring the problems of information asymmetries between vendors and customers in the ACT diffusion process. Specifically, the paper explores whether information asymmetries exist between vendors and customers in the ACT diffusion process and what forms they take.

A structured survey of 153 vendors and customers of advanced construction technologies was undertaken across three international ACT exhibitions in Australia.

By comparing the perspectives of both customers and vendors across 15 technology diffusion process variables using importance-performance analysis and principal component analysis, significant differences are found between vendors’ and customers’ perceptions of how effectively information flows in the ACT diffusion process. The results show that vendors are significantly more optimistic than customers about information asymmetries on a wide range of diffusion variables. They also highlight significant potential for information asymmetries to occur which can undermine the advanced technology diffusion process.

The results provide important new conceptual and practical insights into an under-researched area, which is of increasing importance to a major industry, which is being transformed by advanced technological developments.

In the literature, technology has been shown to perform two major roles, one functionalist and the second symbolic. The purpose of this paper is to explore how cultural expressions in the form of symbols impact on technology diffusion.

Data were obtained primarily through qualitative research (semi‐structured interviews, document analysis and field notes/observation). Data analysis and coding was conducted using template analysis (Atlas.ti).

The findings of the research suggest that an understanding of the symbolic role of technology in the form of “space”, physical structures, communication facilitators and a status symbol may enhance the success of its adoption among indigenous agribusinesses.

The study is limited by its focus on a select set of symbolic dimensions of culture. Emphasising a limited set of cultural dimensions assumes that other imperatives may not have a high impact on technology diffusion.

The focus in this case is on small‐scale indigenous agribusinesses operating in the Southeast of Nigeria. The authors employ broader social anthropological and sociological theories which lie outside the parameters of standard technology adoption and diffusion of innovation theories to support the study.

Technological innovations provide huge opportunities to expand and revolutionize the scope of products and services offered. This is particularly true for tourism, which is undergoing significant changes due to the development of new technologies. The level of technology diffusion depends on several factors like the exchange of information among peers, and the attitude and shared perception among the contributors. The aim of the study is to explore the diffusion of technology in tourism with a specific focus on the social media discourse around new technologies. Thus, the paper investigates the level of interest in these new technologies analysing the information exchange occurring between individuals on Twitter in order to explore the influence of reciprocal networking.

To capture the attitudes expressed in the industry, the study analyses the ongoing discourse on Twitter as a proxy for the participants “interest in new technologies. Through a social network analysis of the tweets and retweets conducted over a period of nine months, the research maps the level of information exchange about the diffusion of new technologies. Moreover, the sentiment analysis provides an interesting overview of the individuals” attitudes towards the awareness or the adoption of new technologies.

Our analysis has provided several insights: (1) the information network on blockchain in tourism consists of participants who change very quickly over time (high turnover of accounts); (2) some contributors have an extremely important role in influencing the flow of information in the system (information centralization), they can have a generalist (discussing several topics) or a specialist (focusing on a specific topic) behaviour and this strategic choice influences their network's structure; (3) these central nodes also have an impact on the definition of positive and negative sentiment towards a topic (sentiment influencer).

The paper contributes to the literature on technology diffusion, by focusing on one of the preconditions of diffusion that is the shared positive attitude towards technological innovation. More specifically, we adopt a network-based approach, which is useful to explain the level of information exchange and the public discourse that can impact the shared perception and attitude towards technological innovation. The study also highlights the role of knowledge brokers in influencing this public discourse. Future studies can deepen the association between positive perception, higher levels of information exchange and increasing usage of specific technologies. Our results also suggest further exploring the opportunity to combine social media data and other sources of information to shed more light on the technological innovation diffusion processes.

This paper shows how practitioners can benefit from the analysis of information exchange about new technologies in tourism adopting a network perspective with the aim of understanding the level of influence among contributors. Moreover, the increasing interest in blockchain technology and the potential combination between social media data and other sources of information can offer promising insights.

The present study explores the level of technology diffusion through the analysis of information exchange on social media (Twitter). Furthermore, the dynamics of individual user behaviour offers a better understanding about media effects.

While previous research is focused on the users' perception towards the development of new technologies in tourism, the aim of this study is to investigate the dynamics behind the level of diffusion of information and awareness about these new technologies, which still represents an unexplored area of research.

The purpose of this paper is to empirically test the joint impact of trust, technology diffusion and organisational capacity on collaboration and investigate the effect of the interaction among them on business performance.

A conceptual model is formulated to achieve the study’s purpose. The research employs quantitative methodology to test the validity of the model. Pilot interviews were used to select applicable attribute for each of the model’s constructs and to revise the survey questionnaire. The survey is addressed to CEOs and senior managers of 500 electrical product manufacturers in Wenzhou province, China. The questionnaire covers 20 attributes of the model’s constructs, which are measured on a seven-point scale. A structured equation modelling software known as AMOS is used to analyse data.

Results indicate that trust is an antecedent factor for successful collaboration, but not as a factor directly affecting business performance. However, the research shows that collaboration plays a full mediator between trust and business performance. The empirical evidence from this research implied that technology diffusion do not translate properly into collaboration and the organisations do not give adequate attention to the process performance in making collaboration with partners. In addition, the electrical Chinese organisations do not consider that the commitments of their partners exceed the expectations.

This research limits investigation in China only and considers one type of industry, that is, the manufacturers of small products.

The conceptual model can be used as an audit tool for evaluating the effect of collaboration on business performance. Thus, managers could recognise weak attributes and plan for improvement.

This study provides new measurement instrument for evaluating the joint impact of collaboration, technology diffusion, trust and organisational capacity on business performance.