Diffusion of innovations

About: Diffusion of innovations is a research topic. Over the lifetime, 2139 publications have been published within this topic receiving 191397 citations. The topic is also known as: diffusion of innovation & diffusion of innovations theory.

The Role of Social Networks in the Diffusion of Bio-Waste Products: The Case of Mulching Films Derived from Organic Waste in Province of Foggia

Abstract: In this work we consider the biodegradable mulching film containing soluble bio-based substances (SBOs), as a new Sustainable Agricultural Practice (SAP) potentially useful in both broadening the spectrum of Organic Fraction of Municipal Solid Wastes (OFMSW) management, and improving agricultural sustainability. Of course, the exploitation of such advantages depends on the actual adoption of the novelty from a critical mass of users. Among the various factors influencing this process, we stress the importance of interpersonal channels involving a face-to-face exchange. This implies the fact that people adopt an innovation when sufficient information has reached them, and shows the relevance of the role of social networks in the diffusion of innovations. Specifically, the network position of an actor affects the power and influence he can exert on its immediate neighbors as well as on the collective behavior of the members. This influence can be viewed as a strategic resource for innovation diffusion purpose in a marketing or policy context. The success as injection points, namely, the actors where the novelty is first inoculated, is typically measured as the proportion of actors who adopts the innovation at the end of the process. Following this line of reasoning, the aim of this work is to identify the network characteristics associated with effective injection points. In order to capture the network characteristics of the actors we used typical Social Network Analysis (SNA) measures. From an operative perspective, our purpose is to find the SNA measures associated with high adoption rates. However, being the innovation process new in nature, there are not available experimental data to conduct this kind of analysis. Therefore, we chose to simulate the diffusion process among agents by means of an Agent Based Model (ABM) depicting a population of farmers. The model was calibrated on real world data gathered from the case of a network of specialist vegetables producers in the Province of Foggia. Both SNA measures and rate of adoption are simulated data. The results achieved represent the basis for the breaking down of a tailored SAP diffusion strategy within an environmental and sustainability oriented development policy in a rural context, like the one studied. In particular, this study offers valuable hints on the kind of spreaders that should be enrolled, indicating, at the same time, the path for further research. This includes a more in depth analysis on various structure of networks (e.g. very dense and very sparse, very randomized and very regular, with high and low medium degree) and the investigation on the effects of the number of exposures of the agents to the promotional strategy.

Desires of an Adopter's Heart: Which Product Characteristics Influence Brand Loyalty among Different Types of Adopters?

Abstract: EXECUTIVE SUMMARY Consumers differ greatly in their readiness to try new products, so researchers classify them according to different adopter categories based on the relative rate that they adopt innovations. This study examines the impact of product benefits on consumer loyalty between two adopter categories in the software industry. Research findings conclude that the impact of software benefits on consumer loyalty differs between the early and the late adopter categories. Early adopters value price, quality, and entertainment value more than late adopters do; however, ease of use is more important to late adopters. Managerial implications are discussed at the conclusion. Keywords: Product lifecycle, Brand loyalty, Product benefits, Diffusion of innovation, and Adopter category INTRODUCTION Maintaining customer loyalty has become a strategic mandate in today's competitive market (Ganesh et al., 2000; McMullan & Gilmore, 2008). Heskett et al. (1989) suggest that it costs three times as much to obtain a customer than to hold one. When companies increase 5% of their customer base, they increase their profit by 25-95% (Reichheld, 2001). Therefore, customer loyalty leads to a significant profit increase, more predictable sales and profit streams, and positive word-of-mouth (Arnould et al., 2002; Hoisington & Naumann, 2003). Value signifies an important element of managing long-term customer relationships (Pride & Ferrell, 2010). Traditionally, value can be classified according to its relative utilitarian and hedonic nature (Babin et al., 1994; Bridges & Florsheim, 2008; Chandon, Wansink, & Laurent, 2000; Homer, 2008). Utilitarian value can help customers maximize the utility, efficiency, and economy of products. Hedonic value is more subjective and personal, and results more from fun and playfulness than from task completion (Chandon, Wansink, & Laurent, 2000). Products can be tentatively classified as utilitarian due to their definition, e.g., affordable price, high quality, complexity, convenience, and ease of use (Chandon, Wansink, & Laurent, 2000; Monroe & Lee, 1999; Monsuwe, 2004). In contrast, products have hedonic value if they are entertaining, fun, novel, intrinsically rewarding, and related to emotions and pleasure (Chandon, Wansink, & Laurent, 2000; Lim & Ang, 2008; Monroe & Lee, 1999). Previous studies (Andreassen & Lindestad, 1998; Chandon, Wansink, & Laurent, 2000; Chiu et al., 2005; Monsuwe, 2004; Pura, 2005; Ryu, Han, & Jang, 2010) indicate that utilitarian and hedonic values impact customer loyalty, which leads us to believe that customer perceptions of these benefits may increase their loyalty. This paper focuses on technology products, software in particular, for the following reasons. First, although the computer software industry is growing rapidly and is increasingly critical for the international competitiveness of other high-technology industries, it has received relatively little attention from previous scholars (Mowery, 1995). Second, the software industry, as part of the high-tech industry, possesses three important characteristics: market uncertainty, technology uncertainty, and competitive volatility (Mohr, Sengupta, & Slater., 2005). For example, Burruss and Kuettner (2003) indicate that typical electronic consumer products have a life cycle ranging from nine to 18 months. Such an uncertain environment and short product life cycle make it critical for companies to formulate an effective customer loyalty strategy (Mohr, Sengupta, & Slater, 2005). Finally, in such a competitive environment, Moen, Gavlen, and Endresen (2004) suggest that a software company must focus on enhancing value in order to establish customer relationships. Therefore, maintaining customer relationships by providing value has become crucial for marketers in this industry. In the innovation diffusions theories, although originally based on a study of agricultural innovations, Rogers' (1983) framework on the diffusion of innovations has provoked similar research within the fields of software (Prescott & Conger, 1995; Kautz & Larsen, 2000). …

Designing a User-Centered Approach to Improve Acceptance of Innovations on the Shop Floor Using Rogers’ ‘Diffusion of Innovations’

Abstract: Analyzing innovation implementation processes in theory and in the industry different approaches are observable. Whilst in Rogers’ ‘Diffusion of Innovations’ the future user is the initiator of the implementation process, the situation is different for shop floor innovations. Mostly, it is a planner or an innovation scouting department, who decide to implement a new technology. The workers as future users will be involved later for the purpose of a proof-of-concept. This late time of user involvement often leads to a low acceptance rate. In order to enhance user acceptance in a shop floor context this paper proposes a user-centered approach of innovation implementation based on Roger’s model. As a first step of the industrial application, I conduct guided interviews to involve workers into the process of my innovation use-case on smart glasses in order picking processes.

Diffusion of Abstractive Summarisation to Improve Ease of Use and Usefulness

Abstract: Even though the abstractive summarisation method has been in existence for over four decades, its popularity, adoption and diffusion have been slow, or limited, in both business and academic domains. This has retarded advances of the innovation and hampered its potential benefits to users. Thus, this qualitative, empirical study was undertaken to examine and understand how the abstractive summarisation method can be diffused to increase its spread and usefulness across business and academic environments. The 1995 theory of Diffusion of Innovation (DOI) by Rogers was employed in the analysis of the existing works. Based on analysis, five main factors were identified as influencing the adoption of the abstractive summarisation method. The factors are complexity, practical effectiveness, experimental, shortened output and lack of friendliness. These factors were discussed towards gaining a better understanding of how the diffusion of abstractive summarisation method can be improved in both business and academic environments.