140,086 research outputs found

    A framework for accelerated product innovation in a big data environment

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    This dissertation is concerned with the best approaches for accelerated product innovation in a big data environment. It describes the development and examining of a framework consisting of three sets of different phases to support managers to attain accelerated product innovation in high-tech industries. This research also investigates the roles of big data in facilitating new product development, and the factors for successful implementation of big data. Accelerated product innovation has become increasingly important for both theory and practice in today’s rapidly changing business environment. The phenomenon is reinforced by the increasing amounts of data available to business and the associated big data efforts in innovation by new information and communication technologies, as well as by new business models and organisational forms. There are two important issues associated with accelerated product innovation. Firstly, there is an underlying question as to which specific approaches for accelerated product innovation will be successful for a particular company. That is, even as more and more firms begin to acknowledge the significance of accelerated product innovation, they still suffer from a lack of knowledge about how to attain it. Secondly, how do companies apply big data to support accelerated product innovation in new product development? The specific benefits of accelerated product innovation may be summarised as: greater opportunity to incorporate the latest technology; increased market share; higher value; and more accurate forecasts of customer needs. Although previous studies have pointed out that firms can facilitate their product innovation by leveraging the huge potential value of big data, no studies have systematically investigated how firms can apply big data to facilitate accelerated product innovation. The research was carried out in two stages. Stage one proposed a set of approaches for accelerated product innovation based on the literature studies. The approaches identified were categorised into four innovation phases. Then, the phases were refined from empirical research. The refined phases were further examined in three cases to develop a framework. During the second stage, a set of propositions were established according to the best approaches identified from the framework. The propositions were examined in five in-company case studies, in which qualitative data collection was applied. As well as this, the qualitative investigation through multiple case studies of diverse companies were executed to explore and compare key elements of big data in the context of product innovation, and more specifically in different phases of new product development. The primary outcome of this research has been the development and examination of a framework for accelerated product innovation in a big data environment. The approaches identified from the framework demonstrated a high utility in practice. The traditional role of innovation in competitive success has been redefined to reflect a time-based requirement. Accordingly, accelerated innovation is associated with maximisation of the product success rates, higher profitability and competitive advantage. All five companies in the present case study were applying approaches in product development for accelerating NPD, better understanding of customers’ needs, higher revenue growth, and faster launch of new products to market. The empirical findings also show that the role of big data in product innovation is highly dependent on the ability to understand a specific objective or problem, and to examine whether using big data is the right approach for solving that problem. There is a prerequisite for securing distinct resources and organisational capabilities to succeed with implementing big data into new product development. Other important factors that need to be well considered by organisations when forming an implementation strategy are organisations’ data maturity and effective change management, especially if the organisation is utilising more traditional innovation processes. However, novel methods rely heavily on extensive and varied data which translates in an adoption urgency to sustain competitive advantage and secure responsive innovation. The main contributions of this research is that it usefully extends the accelerated product innovation literature by clearly defining the concept of accelerated product innovation, and by developing a conceptual framework with six propositions about how, specifically, big data and ICTs can contribute to accelerated product innovation. Then, it offers qualitative evidence from five case studies involving world-leading firms, and explaining how product innovation can most appropriately be accelerated in a big data environment

    Technology, governance, and a sustainability model for small and medium-sized towns in Europe

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    New and cutting-edge technologies causing deep changes in societies, playing the role of game modifiers, and having a significant impact on global markets in small and medium-sized towns in Europe (SMSTEs) are the focus of this research. In this context, an analysis was carried out to identify the main dimensions of a model for promoting innovation in SMSTEs. The literature review on the main dimensions boosting the innovation in SMSTEs and the methodological approach was the application of a survey directed to experts on this issue. The findings from the literature review reflect that technologies, governance, and sustainability dimensions are enablers of SMSTEs’ innovation, and based on the results of the survey, a model was implemented to boost innovation, being this the major add-on of this research.info:eu-repo/semantics/publishedVersio

    A theory-grounded framework of Open Source Software adoption in SMEs

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    This is a post-peer-review, pre-copyedit version of an article published in European Journal of Information Systems. The definitive publisher-authenticated version Macredie, RD and Mijinyawa, K (2011), "A theory-grounded framework of Open Source Software adoption in SMEs", European Journal of Informations Systems, 20(2), 237-250 is available online at: http://www.palgrave-journals.com/ejis/journal/v20/n2/abs/ejis201060a.html.The increasing popularity and use of Open Source Software (OSS) has led to significant interest from research communities and enterprise practitioners, notably in the small business sector where this type of software offers particular benefits given the financial and human capital constraints faced. However, there has been little focus on developing valid frameworks that enable critical evaluation and common understanding of factors influencing OSS adoption. This paper seeks to address this shortcoming by presenting a theory-grounded framework for exploring these factors and explaining their influence on OSS adoption, with the context of study being small- to medium-sized Information Technology (IT) businesses in the U.K. The framework has implications for this type of business – and, we will suggest, more widely – as a frame of reference for understanding, and as tool for evaluating benefits and challenges in, OSS adoption. It also offers researchers a structured way of investigating adoption issues and a base from which to develop models of OSS adoption. The study reported in this paper used the Decomposed Theory of Planned Behaviour (DTPB) as a basis for the research propositions, with the aim of: (i) developing a framework of empirical factors that influence OSS adoption; and (ii) appraising it through case study evaluation with 10 U.K. Small- to medium-sized enterprises in the IT sector. The demonstration of the capabilities of the framework suggests that it is able to provide a reliable explanation of the complex and subjective factors that influence attitudes, subjective norms and control over the use of OSS. The paper further argues that the DTPB proved useful in this research area and that it can provide a variety of situation-specific insights related to factors that influence the adoption of OSS

    Standardization Framework for Sustainability from Circular Economy 4.0

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    The circular economy (CE) is widely known as a way to implement and achieve sustainability, mainly due to its contribution towards the separation of biological and technical nutrients under cyclic industrial metabolism. The incorporation of the principles of the CE in the links of the value chain of the various sectors of the economy strives to ensure circularity, safety, and efficiency. The framework proposed is aligned with the goals of the 2030 Agenda for Sustainable Development regarding the orientation towards the mitigation and regeneration of the metabolic rift by considering a double perspective. Firstly, it strives to conceptualize the CE as a paradigm of sustainability. Its principles are established, and its techniques and tools are organized into two frameworks oriented towards causes (cradle to cradle) and effects (life cycle assessment), and these are structured under the three pillars of sustainability, for their projection within the proposed framework. Secondly, a framework is established to facilitate the implementation of the CE with the use of standards, which constitute the requirements, tools, and indicators to control each life cycle phase, and of key enabling technologies (KETs) that add circular value 4.0 to the socio-ecological transition

    Segmentation & the Jobs-to-be-done theory: A Conceptual Approach to Explaining Product Failure

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    Based on Christensen et al.’s research the jobs-to-be-done theory tends to hold that (market) segmentation is a theory (2004, 2003, 2003). The criticism expressed is that companies frequently allocate their market segments close to attributes, which are easy to measure and just observe consumers’ behaviour for developing new products. There exists the phenomenon that the vast majority of new products fail within a short period of time after market entry. The jobs-to-be-done theory supports that it is more important to align R&D alongside jobs consumers need to get done, jobs, which facilitate their lives and for which they searched a solution historically. The proposition the jobs-to-be-done theory offers is the identification of such jobs needing solutions, which may lead to the creation of new markets or to the extension of existing ones, which do not provide good enough products. Scholars and academics put much emphasis on the process of segmentation – targeting – positioning, as an important tool to focus organisational resources and capabilities for the achievement of sustainable positioning in a challenging market environment. Therefore, this specific theory challenges what marketing theory considers as an important strategy for market success. The proposition is that both approaches established STP and the approach by the jobs-to-be-done theory need to be well considered within strategic organisational decision making, especially for R&D and product strategy. While the traditional STP-strategy seems salient within incremental product novelties, the jobs-to-be-done theory is suggested to offer assistance for more radical product developments. This way, organisations may find themselves in a dilemma to understand, where a borderline between incremental and more radical developments may be drawn, where it will be advantageous to rely on measuring consumer behaviour by classical market research and data and at which point it will be more promising to follow the propositions of the jobs-to-be-done theory for developing successful new products. The proposition of this paper is that suggestions established by scholars’ for a sound segmentation strategy need to be contrasted with the jobs-to-be-done theory in the understanding that there are market needs for incremental improvements and parallel to these, different markets are expecting more radical solutions to get jobs done, for which existing products are not good enough. The paper’s conclusion will result in propositions of framing both these macro markets and contrasting them against each other. Key Words: Jobs-to-be-done theory, segmentation, STP-strategy, new product developmen

    How innovation intermediaries are shaping the technology market? An analysis of their business model

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    In an era with abundant and widely distributed knowledge across the globe, technology markets became prominent. As technology transactions suffer from several market imperfections, a rapidly increasing number of various innovation intermediaries are facilitating these transactions. We analyse how a subset of these intermediaries create value in a two-sided market and how they can capture part of the value. A detailed analysis of the business model of 12 innovation intermediaries clarifies how these organizations improve the effectiveness of technology markets providing benefits for both sides of the market. We also look at managerial trade-offs between the use of intermediaries’ services and in-house innovation platforms.innovation intermediaries; open innovation; business model; two-sided markets

    Eco‐Holonic 4.0 Circular Business Model to  Conceptualize Sustainable Value Chain Towards  Digital Transition 

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    The purpose of this paper is to conceptualize a circular business model based on an Eco-Holonic Architecture, through the integration of circular economy and holonic principles. A conceptual model is developed to manage the complexity of integrating circular economy principles, digital transformation, and tools and frameworks for sustainability into business models. The proposed architecture is multilevel and multiscale in order to achieve the instantiation of the sustainable value chain in any territory. The architecture promotes the incorporation of circular economy and holonic principles into new circular business models. This integrated perspective of business model can support the design and upgrade of the manufacturing companies in their respective industrial sectors. The conceptual model proposed is based on activity theory that considers the interactions between technical and social systems and allows the mitigation of the metabolic rift that exists between natural and social metabolism. This study contributes to the existing literature on circular economy, circular business models and activity theory by considering holonic paradigm concerns, which have not been explored yet. This research also offers a unique holonic architecture of circular business model by considering different levels, relationships, dynamism and contextualization (territory) aspects

    New innovation management paradigms in the knowledge-driven economy

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    The growing importance of knowledge as a production factor and as a determinant of innovation can be explained by the continuous accumulation of technical knowledge over time. Innovation Management Techniques (IMTs) are critical to support the process of innovation in firms and help them in a systematic way to meet new market challenges
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