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  • 1. Carbonara, Nunzia
    et al.
    Tavassoli, Sam
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    The Role of Knowledge Heterogeneity on the Innovative Capability of Industrial Districts2013In: Entrepreneurial Knowledge, Technology and the Transformation of Regions / [ed] Karlsson, Charlie; Johansson, Börje; Stough, Roger, New York: Routledge , 2013Chapter in book (Refereed)
    Abstract [en]

    This paper seeks to contribute to the ongoing debate concerning the role of heterogeneity for the innovative capability of industrial districts. With this aim, using a knowledge-based approach, the paper focuses on different sources of industrial district knowledge heterogeneity and studies how the different level of heterogeneity affects the innovative capability of industrial districts. Four theoretical hypotheses concerning the effects of knowledge and knowledge heterogeneity on the Industrial District innovativeness are formulated. To test the hypotheses, an econometric analysis on 32 Italian District Provinces is applied. Empirical results show that knowledge heterogeneity matter for increasing the innovative capability of industrial districts.

  • 2. Holgersson, Thomas
    et al.
    Norman, Therese
    Tavassoli, Sam
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    In the quest for economic significance: Assessing variable importance through mean value decomposition2014In: Applied Economics Letters, ISSN 1350-4851, E-ISSN 1466-4291, Vol. 21, no 8, p. 545-549Article in journal (Refereed)
    Abstract [en]

    Economic significance is frequently assessed through statistical hypothesis testing, which however, does not always correspond to the implicit economical questions being addressed. In this article we propose using mean value decomposition to assess economic significance. Unlike most previously suggested methods the proposed one is intuitive and simple to conduct. The technique is demonstrated and contrasted with hypothesis tests by an empirical example involving the income of Mexican children, which shows that the two inference approaches provide different and supplementary pieces of information.

  • 3.
    Karlsson, Charlie
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Tavassoli, Sam
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics. CIRCLE.
    Innovation Strategies and Firm Performance: Simple or Complex Strategies?2016In: Economics of Innovation and New Technology, ISSN 1043-8599, E-ISSN 1476-8364, Vol. 25, no 7, p. 631-650Article in journal (Refereed)
    Abstract [en]

    This paper analyzes the effect of various innovation strategies (ISs) of firms on their future performance, captured by labor productivity. Using five waves of the Community Innovation Survey in Sweden, we have traced the innovative behavior of firms over a decade, that is, from 2002 to 2012. We defined ISs to be either simple or complex (in various degrees). We call an IS a simple IS when firms engage in only one of the four types of Schumpeterian innovations, that is, product, process, marketing, or organizational, while a complex IS is when firms simultaneously engage in more than one type. The main findings indicate that those firms that choose and afford to have complex ISs are better off in terms of their future productivity in comparison with those firms that choose not to innovative (base group) and also in comparison with those firms that choose simple ISs. The results are mostly robust for those complex innovators that have a higher degree of complexity and also keep the balance between technological (product and process) and non-technological (organizational and marketing) innovations.

  • 4.
    Karlsson, Charlie
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Tavassoli, Sam
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Innovation Strategies of Firms: What Strategies and Why?2016In: Journal of Technology Transfer, ISSN 0892-9912, E-ISSN 1573-7047, Vol. 41, no 6, p. 1483-1506Article in journal (Refereed)
    Abstract [en]

    This paper analyzes various innovation strategies of firms. Using five waves of the Community Innovation Survey in Sweden, we have traced the innovative behavior of firms over a 10-year period, i.e. between 2002 and 2012. We distinguish between sixteen innovation strategies, which compose of Schumpeterian four types of innovations (process, product, marketing, and organizational) plus various combinations of these four types. First, we find that firms are not homogenous in choosing innovation strategies, instead, they have a wide range of preferences when it comes to innovation strategy and some of the innovation strategies are “commonly” used among firms. Second, using Transition Probability Matrix, we found that firms also persist to have such a diverse innovation strategy preferences. Finally, using Multinomial Logit model, we explained the determinant of each and every innovation strategies, while we gave special attention to the commonly used innovation strategies among firms.

  • 5.
    Kianian, Babak
    et al.
    Blekinge Institute of Technology, School of Engineering, Department of Mechanical Engineering.
    Larsson, Tobias
    Blekinge Institute of Technology, School of Engineering, Department of Mechanical Engineering.
    Tavassoli, Mohammad
    Blekinge Institute of Technology, School of Management.
    Manufacturing Renaissance: Return of manufacturing to western countries2013Conference paper (Refereed)
    Abstract [en]

    Manufacturing Renaissance, i.e. return of manufacturing to west, has been recently observed. This paper analyzes the patterns observed within each of the four main drivers behind this new phenomenon and delves more deeply into the driver that centers on the new manufacturing technologies such as Additive Manufacturing (AM) and 3D Printing. Next, this paper will make the case that the location of manufacturing will be in west, relying on the established theory that has been able to explain the location of manufacturing, i.e. Product Life Cycle Model (PLC).

  • 6.
    Kianian, Babak
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Tavassoli, Sam
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Larsson, Tobias C
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    The Role of Additive Manufacturing Technology in job creation: an exploratory case study of suppliers of Additive Manufacturing in Sweden2015In: Procedia CIRP, Elsevier , 2015, Vol. 26, p. 93-98Conference paper (Refereed)
    Abstract [en]

    his paper investigates how Additive Manufacturing (AM) technologies, as a process innovation, may contribute to a job creation. Further, the various mechanisms in which AM may contribute to an increase in job creation as well as the types of jobs are analyzed. The analysis also goes beyond AM technologies and incorporates other non-technological factors which foster job creation, i.e. higher wages in BRIC countries, lower quality in BRIC countries, and a rising demand for western-made products. The analysis is based on a case study and the data collected was through interviews with three prominent actors within the AM technologies field in Sweden: technology developers, leading suppliers and users. The main findings indicate that AM (i) contributes to job creation in both the manufacturing sector and in the service sector, (ii) does not bring back mass production jobs from emerging economies such as BRIC, (iii) contributes to job creation in product development stages (e.g. rapid prototyping), and (iv) contributes to job creation in production stages of low-volume batches mainly of complex products. The findings also suggest there are barriers for full exploitation of AM in several areas, including education systems.

  • 7.
    Kianian, Babak
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Tavassoli, Sam
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Larsson, Tobias C.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Diegel, Olaf
    Lund Univ, Fac Engn LTH, Design Sci Dept, Lund, Sweden..
    The Adoption of Additive Manufacturing Technology in Sweden2016In: 13TH GLOBAL CONFERENCE ON SUSTAINABLE MANUFACTURING - DECOUPLING GROWTH FROM RESOURCE USE, 2016, p. 7-12Conference paper (Refereed)
    Abstract [en]

    This paper analyzes the adoption of Additive Manufacturing (AM) technologies in Sweden. The dataset consists of a recent and representative sample of Swedish AM users (companies, universities, and research institutes). The authors investigate two questions. Firstly, what are the current applications of AM in Sweden (e.g. Rapid Prototyping (RP), production)? Secondly, what are the factors that can explain the variation in AM adoption among the users? Using a regression analysis technique, the main findings are as follows. (i) There is a variation among users' choice of AM application, and the majority of users are expanding their AM applications beyond RP. (ii) There are two factors that positively affect the decision of firms to expand classical RP and also incorporate production and management. These two factors are using multiple AM technologies (as opposed to single Fused Deposition Modeling technology) and being small companies. The authors discuss the implication of these results. (C) 2016 Published by Elsevier B.V.

  • 8.
    Kianian, Babak
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Tavassoli, Sam
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Larsson, Tobias
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Diegel, Olaf
    The Adoption of Additive Manufacturing Technology in Sweden2015In: 3D Printing and Additive Manufacturing, ISSN 2329-7662, Vol. 2, no 4, p. 152-158Article in journal (Refereed)
    Abstract [en]

    This article analyzes the adoption of additive manufacturing (AM) technologies in Sweden. The data set consists of a recent and representative sample of Swedish AM users (companies, universities, and research institutes). The authors investigate two questions. First, what are the current applications of AM in Sweden (e.g., rapid prototyping [RP], production)? Second, what are the factors that can explain the variation in AM adoption among the users? Using a regression analysis technique, the main findings are as follows. (i) There is a variation among users' choice of AM application, and the majority of users are expanding their AM applications beyond RP. (ii) There are two factors that positively affect the decision of firms to expand classical RP and incorporate production and management as well. These two factors are using multiple AM technologies (as opposed to single fused deposition modeling technology) being small companies. The authors discuss the implication of these results.

  • 9.
    Siddiqui, Rafid
    et al.
    Blekinge Institute of Technology, School of Computing.
    Khatibi, Siamak
    Blekinge Institute of Technology, School of Computing.
    Bitra, Sridhar
    Blekinge Institute of Technology, School of Computing.
    Tavassoli, Sam
    Blekinge Institute of Technology, School of Computing.
    Scene perception by context-aware dominant surfaces2013Conference paper (Refereed)
    Abstract [en]

    Most of the computer vision algorithms operate pixel-wise and process image in a small neighborhood for feature extraction. Such a feature extraction strategy ignores the context of an object in the real world. Taking geometric context into account while classifying various regions in a scene, we can discriminate the similar features obtained from different regions with respect to their context. A geometric context based scene decomposition method is proposed and is applied in a context-aware Augmented Reality (AR) system. The proposed system segments a single image of a scene into a set of semantic classes representing dominant surfaces in the scene. The classification method is evaluated on an urban driving sequence with labeled ground truths and found to be robust in classifying the scene regions into a set of dominant applicable surfaces. The classified dominant surfaces are used to generate a 3D scene. The generated 3D scene provides an input to the AR system. The visual experience of 3D scene through the contextually aware AR system provides a solution for visual touring from single images as well as an experimental tool for improving the understanding of human visual perception.

  • 10.
    Tavasolli, Sam
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Tsagdis, Dimitrios
    Critical success factors and cluster evolution: A case study of the Linköping ICT cluster lifecycle2014In: Environment and planning A, ISSN 0308-518X, E-ISSN 1472-3409, Vol. 46, no 6, p. 1425-1444Article in journal (Refereed)
    Abstract [en]

    This paper investigates the variation in the importance of critical success factors (CSFs) in the evolution of the Linköping ICT (information and communication technology) cluster in Sweden. The international empirical evidence of CSFs in ICT clusters reported in the literature is systematically reviewed. On this basis an object-oriented conceptual model is developed encompassing fifteen CSFs; each attributed to one or more objects: for example, firms, institutions, entrepreneurs. The lifecycle of the Linköping ICT cluster is delineated and its stages segmented. The existence and importance of each CSF at each stage of the cluster lifecycle is established empirically on the basis of interviews with key experts. The main findings comprise a stage-specific group of CSFs whose importance varies across the cluster's lifecycle stages with different patterns. The findings are aimed to stimulate policy makers and researchers alike to pursue further the line of enquiry developed in this paper.

  • 11.
    Tavassoli, Mohammad
    Blekinge Institute of Technology, School of Management.
    Emerging clusters: Theoretical, empirical and political perspectives on the initial stage of cluster evolution2012In: Papers in regional science (Print), ISSN 1056-8190, E-ISSN 1435-5957, Vol. 91, no 2, p. 475-477Article, book review (Other academic)
  • 12.
    Tavassoli, Sam
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Determinants and Effects of Innovation: Context Matters2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Innovation and technological change is the major factor of production, renewal, and competitiveness of firms and nations in the contemporary “knowledge economy”. The overall purpose of this dissertation is to investigate the innovative behavior of firms in various sectors and regions. In particular, I have analyzed the determinants (driving forces) of firms’ innovation on the one hand (in paper 1 and 2), and the effect of firms’ innovation on the other hand (in paper 3 and 4). In addition, a central concern in this dissertation is that context, in which firms operate and innovate, matters for innovation. I take into account several contexts in the analyses of both the determinants and effects of innovation. These contexts are: the regions in which firms are located, the dynamics of industries, and the dynamics of cluster in which firms belong to. This dissertation consists of four separate papers plus an introductory chapter. Each paper can be read independently, but all of them deal with either determinants or effects of the innovation of firms. The first paper analyzes the effect of various firm-specific determinants on firms’ innovation output. It also considers the stages of the Industry Life Cycle (ILC) as a context in which firms operate and innovate. Using the Community Innovation Survey data for manufacturing and service sectors in Sweden during 2002-2004, I find that the importance of various determinants of firms’ innovation depends on the stages of the ILC in which they operate. The second paper is again investigates the determinants of innovation, but this time incorporates another context that affect the innovation, i.e. the regions that firms belong to. Using the patent applications data as a measure of innovation in all functional regions in Sweden during 2002-2007, we find that both the internal knowledge generated within the region and the inflow of external knowledge matter for innovation of firms located in the regions. Moreover, the extent of related variety of knowledge in the region has the superior role to promote innovation. The third paper examines the effect of a firm’s innovation output on firm’s performance. Export behavior of firms is chosen as a performance indicator. Particular attention is devoted to distinguishing between innovation input and innovation output and to isolate their effects on export behavior of firms. Using two waves of Swedish Community Innovation Survey data during 2002-2006 merged with registered firm-level data, I find that what really matters for enhancing the export behavior of firms is the innovation output of firms, rather than the innovation input (mere efforts in investing in innovation activities). The fourth paper also analyzes the effect of innovation on performance measures but this time incorporates another context, i.e. the life cycle of the regional cluster that firms belong to. This paper delves into a particular cluster, i.e. Linköping ICT cluster. Using data collected through interviews during 2009 and 2012 on key cluster actors, we find that innovation is among the factors that are always highly important at any given stage of the cluster’s evolution, however, it has slightly greater importance during the “growing” stage.

  • 13.
    Tavassoli, Sam
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Innovation determinants over industry life cycle2015In: Technological forecasting & social change, ISSN 0040-1625, E-ISSN 1873-5509, Vol. 91, p. 18-32Article in journal (Refereed)
    Abstract [en]

    This paper analyzes how the influence of firm-level innovation determinants varies over the industry life cycle. Two sets of determinants are distinguished: (1) determinants of a firm's innovation propensity, i.e. the likelihood of being innovative and (2) determinants of its innovation intensity, i.e. innovation sales. By combining the literature emphasizing firms' internal resources (micro-level) with the research strand on the role of the industry context (meso-level), the paper develops hypotheses about the relative importance of firm-level innovation determinants over the industry life cycle. Estimation of a firm-level model of innovation in Sweden, while acknowledging the stage of the life cycle of the industry a firm belongs to, shows that the importance of the determinants of innovation propensity and intensity is not equal over the stages of an industry's life cycle.

  • 14.
    Tavassoli, Sam
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Carbonara, Nunzia
    The role of knowledge variety and intensity for regional innovation2014In: Small Business Economics, ISSN 0921-898X, E-ISSN 1573-0913, Vol. 43, no 2, p. 493-509Article in journal (Refereed)
    Abstract [en]

    This paper analyses the effect of variety and intensity of knowledge on the innovation of regions. Employing data for Swedish functional regions, the paper tests the role of the variety (related and unrelated) and intensity of (1) internal knowledge generated within the region and also (2) external knowledge networks flowing into the region in explaining regional innovation, as measured by patent applications. The empirical analysis provides robust evidence that both the variety and intensity of internal and external knowledge matter for regions’ innovation. When it comes to variety, related variety of knowledge plays a superior role.

  • 15.
    Tavassoli, Sam
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Jienwatcharamongkhol, Viroj
    The Impact of Individual Characteristics and Regional Agglomeration on the Survival of Self-Employed Firms2014Conference paper (Refereed)
    Abstract [en]

    Self-employed firms are known to have a very high mortality rate. The literature on the success of firms offers several explanations. I attribute the firm’s survival to internal and external factors by relying on the resource-based view and agglomeration economies, respectively. This paper aims at investigating whether individual characteristics of the founding entrepreneur and agglomeration economic variables (urbanization, related and unrelated variety, and specialization) have a significant impact on the survival of self-employed firms. Tracing the cohorts of newly established firms in Sweden from 1990 to 2010, I conclude that: (i) firms face a greater mortality rate when entrepreneur’s age increases, entrepreneurs are female, or immigrant, even after controlling for industry heterogeneity, (ii) the survival of firms with female entrepreneur is lower in the manufacturing sector whereas immigrant firms has a lower survival in knowledge-intensive sector, (iii) highly educated entrepreneurs are more likely to survive in services and knowledge-intensive business sectors, and (iv) self-employed firms barely benefit from agglomeration economies. Therefore, for a self-employed firm, it seems what matter is who you are, rather than where you are.

  • 16.
    Tavassoli, Sam
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Karlsson, Charlie
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Persistence of various types of innovation analyzed and explained2015In: Research Policy, ISSN 0048-7333, E-ISSN 1873-7625, Vol. 44, no 10, p. 1887-1901Article in journal (Refereed)
    Abstract [en]

    This paper analyzes the persistency in innovation behavior of firms. Using five waves of the Community Innovation Survey in Sweden, we have traced the innovative behavior of firms over a ten-year period, i.e., between 2002 and 2012. We distinguish between four types of innovations: process, product, marketing, and organizational innovations. First, using transition probability matrix, we found evidence of (unconditional) state dependence in all types of innovation, with product innovators having the strongest persistent behavior. Second, using a dynamic probit model, we found evidence of "true" state dependency among all types of innovations, except marketing innovators. Once again, the strongest persistency was found for product innovators. (C) 2015 Elsevier B.V. All rights reserved.

  • 17.
    Tavassoli, Sam
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Tsagdis, Dimitrios
    Developing an Object Oriented Model of Critical Success Factors for Clusters: The Linköping Information and Communication Technologies Cluster Test-Case2010Conference paper (Refereed)
    Abstract [en]

    An object oriented model (OOM) of critical success factors (CSFs) for clusters is developed on the basis of an extensive and critical review of the literature. The model is tested, as a proof of concept, in the Linköping information and communication technologies (ICT) cluster, Sweden. The model is flexible, scalable, and open-ended, applying equally to particular clusters as well as to clusters in general. The model aims to act both as a diagnostic tool for CSFs in particular clusters as well as a framework for policy and research in general. The model encompasses some 21 CSFs (e.g. trust, vision, knowledge) that belong or depend on one or more objects (e.g. firms, institutions, entrepreneurs) relevant to a cluster. A Venn diagram is initially developed on the basis of the literature to help delineate the relevant objects and is subsequently translated into the aforementioned model. The testing of the model follows a cluster life-cycle approach and ranks the 21 CSFs in terms of their relevance during different stages in the life-cycle of the Linköping ICT cluster. It is argued that the importance of different CSFs varies throughout a cluster´s life-cycle concluding with some relevant policy implications and areas of further research.

1 - 17 of 17
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