The adoption of Web 2.0 services: An empirical investigation

The paper investigates the factors associated with the intensity of use of three Web 2.0 services - video sharing, social networking and social bookmarking - by looking at the users' characteristics and at the technological features. It relies upon a theoretical framework that combines the diffusion of innovation model with the technology acceptance model. However, it goes beyond them by focusing not simply on the determinants of adoption, but on the determinants of the intensity of use, and by introducing variables related to the social influence. The empirical analysis is based upon a survey of 300 users of Web 2.0 services. We find that the compatibility with users' needs and behaviours plays an important role for the intensity of usage of both video sharing and social networking services, while the ease of use positively affects the intensity of usage of social networking services, but has a negative effect on the intensity of usage of video sharing services. Extrinsic job-related motivations are important drivers of the intensive usage of social bookmarking and social networking services, while sharing contents is relevant for video sharing and social networking services. Finally, individual characteristics such as age, education and IT endowment also play an important role.     

Producing state of the future indexes using the international futures model

This paper reports on the introduction of the State of the Future Index (SOFI) into the University of Denver's International Futures (IFs) modeling system, a synthesis that will permit the calculation and comparison of the SOFI for all nations covered in the model. The SOFI is an index designed to show whether the future outlook is improving or not; it is also useful in policy analysis since it can be used to demonstrate whether contemplated policies appear to change the future, overall, for the better. It is one of the few indexes that are forecasted.The capability to calculate SOFI has been added to the IFs model; this addition now permits the model to calculate SOFI for all of the countries in the model. With this capability national SOFIs can be computed by anyone and for any country, set of countries, region, or globally. The model, its database, and now the SOFI calculation are available online at no cost to the users. This opens the opportunity to produce an annual or biennial publication that tracks and ranks the State of the Future Index for countries, regions, and the world as a whole.     

A choice-based multi-product diffusion model incorporating replacement demand

This study proposes an integrated forecasting model that incorporates both first purchase diffusion and replacement component of sales in predicting multi-product diffusion patterns. The model consists of a two-stage procedure that customers undertake during purchase occasions according to a diffusion process or replacement process, and at each occasion, they make purchase incidence decisions and product choices according to a choice model. By incorporating various exogenous factors in the choice model, the model can identify the impact of each factor on customers' purchase incidence decisions and choice decisions among various product sub-categories. This approach enables us to understand the overall process of customers' purchasing behavior and to separate total sales amount into sales to three consumer segments: first-time buyers, customers who repurchase the same product category and customers who change their previous product category. We applied the proposed model in the forecasting multi-product framework; forecasting sub-category level automobile sales and brand level mobile terminal sales in the South Korean market. The results of the empirical studies showed that incorporating the replacement components into the multi-product diffusion framework is useful not only in understanding the demand interaction among automobile categories and among mobile handset brands, but also in producing more accurate long-term sales forecasts compared to previous multi-product diffusion models.     

A conceptual framework for misfit technology commercialization

The emerging literature on outbound open innovation has highlighted innovation processes, which presuppose active outward technology transfer to increase firm profits. To contribute to this discourse, our paper goes beyond the emphasis on core-related technologies and knowledge that currently dominates the technology management literature and develops the novel concept of misfit technology. This concept captures technologies that are not aligned with a focal firm's current knowledge base and/or business model, but which may still be of great value to the firm if alternative commercialization options are considered. By developing a framework that acknowledges (1) Sources of misfit technology, (2) Environmental uncertainty, (3) Organizational slack, (4) Industry appropriability regime and (5) Technological complexity, we theorize on how different modes of commercialization relate to misfit technology commercialization success. The paper is conceptual and is presented with the purpose to spawn further research on this important topic, but simultaneously touches upon the issues of utmost relevance to R&D management practice.     

Institutional capacity to dynamically innovate: An application to the Portuguese case

The present paper addresses the dynamics of innovation, by extending the analysis beyond a static-economic perspective. It offers a dynamic-institutional mapping of relational capacities to dynamically innovate. Its main goal is to contribute to the above-mentioned research theme by presenting a new methodology able to pinpoint different trends in the relational capacities of institutions when they are innovative. Thereby, major characteristics in the networks of innovation are identified. This investigation uses an extended set of private institutions and public organizations located in Portugal, evaluated by their WebPage contents. To this data set a new combination of multivariate statistical methods is applied to detect group performances, to compare them, and to identify gradients of capacity to dynamically innovate. The results demonstrate that this method can provide extremely useful and tailor-made information for policy evaluation at regional or national levels.     

A systematic approach for integrated trend analysis—The case of etching

Understanding technology development trends is of critical importance to countries, industries and enterprises to be sustainable in global competition. Attempts have been made to establish trend analysis by bibliometric and patent analyses. Also text-mining uncovers hidden and important information from structured or unstructured documents which serve as knowledge carriers. This study aims to provide a systematic approach for integrated trend analysis that takes into account bibliometric analysis, patent analysis and text-mining analysis. Etching is selected as the case study for integrating trend analysis method proposed in this study. Also, validity and applicability of the integrated analysis are evaluated.     

Arenas of expectations for hydrogen technologies

Technological development is often described as an evolutionary process of variation, selection and retention. Different technologies are seen as variations, while the market and other institutions operate as a selection environment. It is less understood, however, how variation and selection relate in the case of emerging technologies. In this paper we introduce the concept of arenas of expectations to examine the relationship between variation and selection processes. Expectations are of particular interest in a pre-market phase of innovation, when performance, cost and other market criteria are less articulated and not stable. In arenas of expectations ‘enactors’ of particular technological variations voice and maintain expectations, while ‘selectors’ will compare and assess the competing claims. We analyse the expectations work of both parties in a case study on metal hydrides for the on-board storage of hydrogen for automotive applications. The paper concludes with a framework of ‘arenas of expectations’ as the linchpin between the processes of variation and selection of emerging technologies.     

Beyond the obvious: Examining ways of consolidating early detection schemes

In the domain of futures studies, the need to develop methods and concepts to identify risks or opportunities “early enough” has become an issue and almost a discrete sub-field with its own debates, specialties and schools of thought.Our examination of the literature in this domain shows that early detection, early warning or weak signal analysis, to mention just a few of the terms being used, tends to convey the idea that finding faint evidence of possible futures is actually rather easy. We, however, believe that it is far from being an off-the-shelf process for whoever wants to detect early signs of changes. At the very least it raises cost/benefit questions, and it may have some shortcomings which, if ignored, could substantially increase the vulnerability of an organization. Our goal in this paper is to explore ways of going beyond an overly optimistic approach and provide a basis for the pragmatic use of weak signals and similar notions in strategic management and policy-making processes.After browsing through the several approaches that propose methods for the “early” tackling of trends, uncertainties, risks or opportunities to come, we will focus on the approaches defined by 1) weak signals and 2) early warnings or equivalents for the analysis of possible futures. We will in particular examine how mainstream claims have been presented then improved in the last 25 years, as well as how some of the problems involved have been insufficiently addressed so far. We will then show how these problems (closely linked to how the early perception claims are configured — how they are framed and modeled but also made affordable and useful) can directly impact the performance and management style of the organizations and societal settings in which they are deployed. The concluding section will propose a pragmatic approach to the problems raised: paradigmatic weaknesses or forms of blindness. This precautionary principle should lead to a real option approach in terms of futures to be considered and evaluated, so as to enhance the chances of avoiding risks, as well as following up promising directions, radical innovations or, more generally, strategic decision-making processes in both the corporate and policy-making arenas.     

Modelling intervention options to reduce GHG emissions in housing stock — A diffusion approach

The building sector is regarded as having one of the highest benefit-cost ratios from greenhouse gas (GHG) emission reduction strategies. However, because of uncertainties around household behaviour patterns, it is very difficult to assess and compare the GHG reduction impacts of different intervention schemes for whole housing stock. Intervention schemes include policy instruments such as incentives or rebates for energy efficient appliances or renewable energy, and regulatory building code requirements for energy efficiency. This paper presents a decision support tool based on mathematical diffusion that evaluates the adoption levels of different schemes or pathways towards reducing GHG emissions in housing stock. It is an extension of the Bass diffusion model that accommodates financial and non-financial benefits, ceilings of adoption and interactions between intervention options. The model capability was tested using a case study of seven suburbs in Brisbane, Australia, comprising of 25,000 houses and units. Estimates of GHG emission reductions to 2019 of a household rebate scheme for solar panels and a rebate scheme for solar hot water compared to a base case of no rebates were presented and analysed. Modelling also allowed identification of important characteristics of adoption trends that could assist policy makers and industry to substantially improve the design of effective intervention options.     

A systematic quantitative backcasting on low-carbon society policy in case of Kyoto city

In order to realize a low-carbon society (LCS), it is necessary to formulate a comprehensive policy consisting of a large number of “options” (i.e., policies as well as technical and behavioral measures). Based on the concept of backcasting, this paper proposes a methodology and a model, called the backcasting model (BCM), that organizes a system of various LCS options and projects their detailed schedule toward a given target year. The methodology and model mainly focus on describing a complex system of LCS options and the consistency of their schedule. Other aspects such as the costs of LCS measures, stock dynamics of technologies, and effects of economic instruments are not explicitly considered. To permit quantitative treatment of various types of options, they are classified into several categories. The BCM calculates the schedule of the options under given quantitative information on the options and relationships between them. The methodology and model were applied to Kyoto City as an example. First, a quantitative snapshot of socioeconomic status and greenhouse gas (GHG) emissions was described. In the snapshot, a 45% reduction of GHG emissions compared with 1990 was achieved with moderate economic growth. The BCM was applied to about 130 options shown in an action plan of the Kyoto Municipal Government, and a schedule of the options was calculated. This methodology treats wide-ranging and complex low-carbon options in a quantitative and consistent manner and supports the policymaking process toward the realization of a low-carbon society.