93 research outputs found

    A Gravity Approach to Assess the Effects of Association Agreements on Euromediterranean Trade of Fruits and Vegetables

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    The paper is intended to draw on a gravity methodology to assess the impact of EuroMediterranean Association Agreement on Fruit and Vegetable trade from Mediterranean Partner Countries (MPC) to the EU. The Association Agreements appear to be significant as an explanatory of both fruit and vegetables’ trade flows to the EU. However, while the impact of such arrangements has contributed to boost MPC’s horticultural exports, it has not been sufficient to compensate the export loss related to the nature of MPCs as third countries. MPCs may have obtained gains from the EuroMed Agrements but the Barcelona process is still far to achieve its initial goals, at least concerning crucial products for the MPCs’ export strategy. The presented approach supplies a method to monitor future developments in the EuroMediterranean process.agricultural trade; Euro-Mediterranean agreements; fruit and vegetables

    Modelling Euro-Mediterranean Agricultural Trade

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    This paper examines the methodological problems to define a modelling approach to assess the impact of full or limited bilateral liberalisation of agricultural trade flows in the Euro-Mediterranean region. The bilateral trade liberalisation process in the region is framed by complexity, in policy instruments and in the characteristics of the products, in particular fruits and vegetables. Advantages and disadvantages of the general equilibrium and partial equilibrium approaches to simulate trade policy impacts are assessed. Caveats of existing models are related to the representation of specific policy instruments (tariffs, entry prices and other non-tariff measures) and on the seasonal nature of horticultural trade, which is of major importance in the Euro-Mediterranean Free Trade Are. The paper provides an illustration of how an imperfect substitute product model could be helpful to describe the trade effects of bilateral price changes, for given seasons.

    F&V Trade Model to Assess Euro-Med Agreements. An Application to the Fresh Tomato Market

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    The complexity derived from the bilateral trade liberalisation process in the Mediterranean region is difficult to represent in a trade model, not only because of the range of instruments still constraining trade but also because of the special nature of the most important traded goods (product differentiation and seasonality). Tariff-rate quotas (TRQ's) and the entry price system are clearly defined on a monthly basis for the fruits and vegetables trade flows towards the European Union (EU). This point makes efforts to model such a trade in yearly basis not representative of reality. We propose a static partial equilibrium model tailored to model trade impacts of specific policy instruments which considers imports from different sources as imperfect substitutes, following the non-linear Armington type model. Different policy scenarios have been run using the model, considering changes in TRQ's and Entry Price regimes, its tariffication and preference erosion. The results of model runs show that, as regards to EU producers, bilateral trade liberalisation with extension of TRQs would be the least dramatic scenario. By contrast, the phasing out of the entry price system would have serious consequences on EU producers. The model has also given detailed information on Morocco's interests in the negotiation, although it could easily include a larger number of suppliers. Morocco appears to be interested in multilateral liberalisation as well as in bilateral liberalisation. In fact, multilateral liberalisation will not cause a great deal of preference erosion against Moroccan exporters, unless tariff reductions only affect MFN suppliers.International Relations/Trade,

    The Reform of the CMO in Fruits and Vegetables: A Holistic Approach

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    The main characteristics of EU's market in fruits and vegetables are trend towards overproduction, price fluctuations, and relatively low protection and public support. The key instruments of the CMO are processing aids and support to Operational Funds. The current regulation has been more successful in encouraging improvements in quality and marketing than in stabilising prices and guaranteeing adequate income levels, mainly in fruits and in the great southern countries. The lack of common European action in the fields of import control and access to new foreign markets creates more pressure in the common market. The proposal of CMO's reform comes after the great CAP's change of 2003 -and its new paradigm- and the budget agricultural agreement until 2013. In practice, this reduces the real policy options for the new regulation. Main changes should occur in processing aids, where forces to decouple are strong; given that exports refunds are already phasing out and markets withdrawals are in decline. The main political defy is how to promote horizontal concentration through PO and to avoid the price crisis. To solve the issue of stability (or decline) of the human consumption, more can be done from the policy. The farmer's influence in political decision seems weak. The scope for radical changes in fund distribution will be possible at national level.Agricultural and Food Policy, Marketing,

    A Gravity Approach to Assess the Effects of Association Agreements on Euromediterranean Trade of Fruits and Vegetables

    Get PDF
    The paper is intended to draw on a gravity methodology to assess the impact of EuroMediterranean Association Agreement on Fruit and Vegetable trade from Mediterranean Partner Countries (MPC) to the EU. The Association Agreements appear to be significant as an explanatory of both fruit and vegetables’ trade flows to the EU. However, while the impact of such arrangements has contributed to boost MPC’s horticultural exports, it has not been sufficient to compensate the export loss related to the nature of MPCs as third countries. MPCs may have obtained gains from the EuroMed Agrements but the Barcelona process is still far to achieve its initial goals, at least concerning crucial products for the MPCs’ export strategy. The presented approach supplies a method to monitor future developments in the EuroMediterranean process

    Modelling Euro-Mediterranean Agricultural Trade

    Get PDF
    This paper examines the methodological problems to define a modelling approach to assess the impact of full or limited bilateral liberalisation of agricultural trade flows in the Euro-Mediterranean region. The bilateral trade liberalisation process in the region is framed by complexity, in policy instruments and in the characteristics of the products, in particular fruits and vegetables. Advantages and disadvantages of the general equilibrium and partial equilibrium approaches to simulate trade policy impacts are assessed. Caveats of existing models are related to the representation of specific policy instruments (tariffs, entry prices and other non-tariff measures) and on the seasonal nature of horticultural trade, which is of major importance in the Euro-Mediterranean Free Trade Are. The paper provides an illustration of how an imperfect substitute product model could be helpful to describe the trade effects of bilateral price changes, for given seasons

    Incorporating physiologically relevant mobile phases in micellar liquid chromatography for the prediction of human intestinal absorption

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    Micellar liquid chromatography (MLC) is a popular method used in the determination of a compounds lipophilicity. This study describes the use of the obtained micelle/water partition coefficient (log Pmw) by such a method in the prediction of human intestinal absorption (HIA). As a result of the close resemblance of the novel composition of the micellar mobile phase to that of physiological intestinal fluid, prediction was deemed to be highly successful. The unique micellar mobile phase consisted of a mixed micellar mixture of lecithin and six bile salts, i.e. a composition matching that found in the human intestinal environment, prepared in ratios resembling those in the intestine. This is considered to be the first method to use a physiological mixture of biosurfactants in the prediction of HIA. As a result, a mathematical model with high predictive ability (R2PRED= 81 %) was obtained using multiple linear regression. The micelle/water partition coefficient (log Pmw) obtained from MLC was found to be a successful tool for prediction where the final optimum model included (log Pmw) and polar surface area (PSA) as key descriptors with high statistical significance for the prediction of HIA. This can be attributed to the nature of the mobile phase used in this study which contains the lecithin-bile salt complex, thus forming a bilayer system therefore mimicking absorption across the intestinal membrane

    Determinants of Agri-food Firms Participation in Public Funded Research and Development

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    A database of over 2,700 agri-food businesses in the region of Valencia, Spain was used to test the influence of internal characteristics of the firm and of external characteristics linked to local systems on the willingness to participate in R&D activities promoted by knowledge supporting institutions. A Probit model was estimated, correcting possible intragroup correlations when group variables are combined with individual data. Results show that R&D activities are enhanced in medium and large firms, co-ops, experienced firms and better physical access to technological centers.The authors gratefully acknowledge the support received from the projects AGL2012-39793-C03-01 and 02, funded by the Ministry of Economy and Competitiveness (Spain).GarcĂ­a Alvarez-Coque, JM.; Mas VerdĂș, F.; Sanchez Garcia, M. (2015). Determinants of Agri-food Firms Participation in Public Funded Research and Development. Agribusiness. 31(3):314-329. doi:10.1002/agr.21407S314329313Albors-Garrigos, J., Zabaleta, N., & Ganzarain, J. (2010). New R&D management paradigms: rethinking research and technology organizations strategies in regions. R&D Management, 40(5), 435-454. doi:10.1111/j.1467-9310.2010.00611.xAlarcĂłn, S., & SĂĄnchez, M. (2013). External and Internal R&D, Capital Investment and Business Performance in the Spanish Agri-Food Industry. Journal of Agricultural Economics, 64(3), 654-675. doi:10.1111/1477-9552.12015Alecke, B., Alsleben, C., Scharr, F., & Untiedt, G. (2006). Are there really high-tech clusters? The geographic concentration of German manufacturing industries and its determinants. The Annals of Regional Science, 40(1), 19-42. doi:10.1007/s00168-005-0014-xAlfranca, O. (2005). Private R&D and Spillovers in European Agriculture. International Advances in Economic Research, 11(2), 201-213. doi:10.1007/s11294-005-3016-7Alston , J. 2010 The benefits from agricultural research and development, innovation and productivity growth http://dx.doi.org/10.1787/5km91nfsnkwg-enAudretsch, D. B., Lehmann, E. E., & Warning, S. (2005). University spillovers and new firm location. Research Policy, 34(7), 1113-1122. doi:10.1016/j.respol.2005.05.009Avermaete, T., Viaene, J., Morgan, E. J., & Crawford, N. (2003). Determinants of innovation in small food firms. European Journal of Innovation Management, 6(1), 8-17. doi:10.1108/14601060310459163Balasubramanian, N., & Lee, J. (2008). Firm age and innovation. Industrial and Corporate Change, 17(5), 1019-1047. doi:10.1093/icc/dtn028Baldwin, J., Hanel, P., & Sabourin, D. (2002). Determinants of Innovative Activity in Canadian Manufacturing Firms. Innovation and Firm Performance, 86-111. doi:10.1057/9780230595880_5Barge-Gil, A., SantamarĂ­a, L., & Modrego, A. (2011). Complementarities Between Universities and Technology Institutes: New Empirical Lessons and Perspectives. European Planning Studies, 19(2), 195-215. doi:10.1080/09654313.2011.532665Batabyal, A. A., & Nijkamp, P. (2012). A multi-region model of economic growth with human capital and negative externalities in innovation. Journal of Evolutionary Economics, 23(4), 909-924. doi:10.1007/s00191-012-0293-1Batterink, M. H., Wubben, E. F. M., Klerkx, L., & Omta, S. W. F. (Onno). (2010). Orchestrating innovation networks: The case of innovation brokers in the agri-food sector. Entrepreneurship & Regional Development, 22(1), 47-76. doi:10.1080/08985620903220512Bayona-SĂĄez, C., GarcĂ­a-Marco, T., Sanchez-GarcĂ­a, M., & Cruz-CĂ zares, C. (2013). The impact of open innovation on innovation performance: the case of Spanish agri-food firms. Open Innovation in the Food and Beverage Industry, 74-94. doi:10.1533/9780857097248.1.74Bayona, C., Garcı́a-Marco, T., & Huerta, E. (2001). Firms’ motivations for cooperative R&D: an empirical analysis of Spanish firms. Research Policy, 30(8), 1289-1307. doi:10.1016/s0048-7333(00)00151-7Becattini G. Industrial districts: A new approach to industrial change 88 111Beckeman, M., & Skjöldebrand, C. (2007). Clusters/networks promote food innovations. Journal of Food Engineering, 79(4), 1418-1425. doi:10.1016/j.jfoodeng.2006.04.024Belderbos, R., Carree, M., Diederen, B., Lokshin, B., & Veugelers, R. (2004). Heterogeneity in R&D cooperation strategies. International Journal of Industrial Organization, 22(8-9), 1237-1263. doi:10.1016/j.ijindorg.2004.08.001Belussi, F., & Sedita, S. R. (2009). Life Cycle vs. Multiple Path Dependency in Industrial Districts. European Planning Studies, 17(4), 505-528. doi:10.1080/09654310802682065Bhattacharya, M., & Bloch, H. (2004). Determinants of Innovation. Small Business Economics, 22(2), 155-162. doi:10.1023/b:sbej.0000014453.94445.deBougheas, S. (2004). Internal vs External Financing of R&D. Small Business Economics, 22(1), 11-17. doi:10.1023/b:sbej.0000011569.79252.e5Cantner, U., Conti, E., & Meder, A. (2010). Networks and Innovation: The Role of Social Assets in Explaining Firms’ Innovative Capacity. European Planning Studies, 18(12), 1937-1956. doi:10.1080/09654313.2010.515795Capitanio, F., Coppola, A., & Pascucci, S. (2009). Indications for drivers of innovation in the food sector. British Food Journal, 111(8), 820-838. doi:10.1108/00070700910980946Capitanio, F., Coppola, A., & Pascucci, S. (2010). Product and process innovation in the Italian food industry. Agribusiness, 26(4), 503-518. doi:10.1002/agr.20239Cantwell, J., & Piscitello, L. (2005). Recent Location of Foreign-owned Research and Development Activities by Large Multinational Corporations in the European Regions: The Role of Spillovers and Externalities. Regional Studies, 39(1), 1-16. doi:10.1080/0034340052000320824Capello, R., & Lenzi, C. (2013). Territorial Patterns of Innovation and Economic Growth in European Regions. Growth and Change, 44(2), 195-227. doi:10.1111/grow.12009Copus, A., Skuras, D., & Tsegenidi, K. (2009). Innovation and Peripherality: An Empirical Comparative Study of SMEs in Six European Union Member Countries. Economic Geography, 84(1), 51-82. doi:10.1111/j.1944-8287.2008.tb00391.xCrescenzi, R., Pietrobelli, C., & Rabellotti, R. (2013). Innovation drivers, value chains and the geography of multinational corporations in Europe. Journal of Economic Geography, 14(6), 1053-1086. doi:10.1093/jeg/lbt018Donald, S. G., & Lang, K. (2007). Inference with Difference-in-Differences and Other Panel Data. Review of Economics and Statistics, 89(2), 221-233. doi:10.1162/rest.89.2.221European Commission 2011 Proposal for a regulation of the european parliament and of the council on support for rural development by the European Agricultural Fund for Rural Development (EAFRD)Eurostat 2014 Science and technology indicators http://epp.eurostat.ec.europa.eu/portal/page/portal/science_technology_innovation/data/databaseEvans, D. S. (1987). The Relationship Between Firm Growth, Size, and Age: Estimates for 100 Manufacturing Industries. The Journal of Industrial Economics, 35(4), 567. doi:10.2307/2098588Fearne, A., MarĂ­a GarcĂ­a Álvarez‐Coque, J., LĂłpez‐GarcĂ­a Usach Mercedes, T., & GarcĂ­a, S. (2013). Innovative firms and the urban/rural divide: the case of agro‐food system. Management Decision, 51(6), 1293-1310. doi:10.1108/md-12-2011-0482De Lucio, I. F., Mas-Verdu, F., & Tortosa, E. (2009). Regional innovation policies: the persistence of the linear model in Spain. The Service Industries Journal, 30(5), 749-762. doi:10.1080/02642060802398093Fernandez-Vazquez, E., & Rubiera-Morollon, F. (2013). Estimating Regional Variations of R&D Effects on Productivity Growth by Entropy Econometrics. Spatial Economic Analysis, 8(1), 54-70. doi:10.1080/17421772.2012.753638GarcĂ­a Álvarez-Coque, J. M., Alba, M. F., & LĂłpez-GarcĂ­a Usach, T. (2012). Innovation and sectoral linkages in the agri-food system in the Valencian Community. Spanish Journal of Agricultural Research, 10(1), 18. doi:10.5424/sjar/2012101-207-11Garcia Martinez, M. (2013). Open innovation in the food and beverage industry. doi:10.1533/9780857097248Garcia Martinez, M. (2000). Innovation in the Spanish food & drink industry. The International Food and Agribusiness Management Review, 3(2), 155-176. doi:10.1016/s1096-7508(00)00033-1GELLYNCK, X., & VERMEIRE, B. (2009). The Contribution of Regional Networks to Innovation and Challenges for Regional Policy. International Journal of Urban and Regional Research, 33(3), 719-737. doi:10.1111/j.1468-2427.2009.00887.xGertler, M. S. (2010). Rules of the Game: The Place of Institutions in Regional Economic Change. Regional Studies, 44(1), 1-15. doi:10.1080/00343400903389979Giannakas, K., & Fulton, M. (2005). Process Innovation Activity in a Mixed Oligopoly: The Role of Cooperatives. American Journal of Agricultural Economics, 87(2), 406-422. doi:10.1111/j.1467-8276.2005.00731.xHagedoorn, J. (2002). Inter-firm R&D partnerships: an overview of major trends and patterns since 1960. Research Policy, 31(4), 477-492. doi:10.1016/s0048-7333(01)00120-2Hassink, R. (2005). How to unlock regional economies from path dependency? From learning region to learning cluster. European Planning Studies, 13(4), 521-535. doi:10.1080/09654310500107134Hirsch, S., & Gschwandtner, A. (2013). Profit persistence in the food industry: evidence from five European countries. European Review of Agricultural Economics, 40(5), 741-759. doi:10.1093/erae/jbt007Howells, J. (2006). Intermediation and the role of intermediaries in innovation. Research Policy, 35(5), 715-728. doi:10.1016/j.respol.2006.03.005Huergo, E., & Jaumandreu, J. (2004). Firms’ age, process innovation and productivity growth. International Journal of Industrial Organization, 22(4), 541-559. doi:10.1016/j.ijindorg.2003.12.002Klerkx, L., & Leeuwis, C. (2009). Establishment and embedding of innovation brokers at different innovation system levels: Insights from the Dutch agricultural sector. Technological Forecasting and Social Change, 76(6), 849-860. doi:10.1016/j.techfore.2008.10.001Inkinen, T., & Suorsa, K. (2010). Intermediaries in Regional Innovation Systems: High-Technology Enterprise Survey from Northern Finland. European Planning Studies, 18(2), 169-187. doi:10.1080/09654310903491556Instituto Nacional de EstadĂ­stica Encuesta sobre innovaciĂłn de las empresas Author MadridJacob, J., Belderbos, R., & Gilsing, V. (2013). Technology alliances in emerging economies: persistence and interrelation in European firms’ alliance formation. R&D Management, 43(5), 447-460. doi:10.1111/radm.12028Jonard , F. Lambotte , M. Ramos , F. Terres , J.M. Bamps , C. 2009 Delimitations of rural areas in Europe using criteria of population densityJovanovic, B. (1982). Selection and the Evolution of Industry. Econometrica, 50(3), 649. doi:10.2307/1912606Kang, K.-N., & Park, H. (2012). Influence of government R&D support and inter-firm collaborations on innovation in Korean biotechnology SMEs. Technovation, 32(1), 68-78. doi:10.1016/j.technovation.2011.08.004Karantininis, K., Sauer, J., & Furtan, W. H. (2010). Innovation and integration in the agri-food industry. Food Policy, 35(2), 112-120. doi:10.1016/j.foodpol.2009.10.003Hori, K., & Yamada, K. (2012). Education, Innovation and Long-Run Growth. Japanese Economic Review, 64(3), 295-318. doi:10.1111/j.1468-5876.2012.00588.xKloek, T. (1981). OLS Estimation in a Model Where a Microvariable is Explained by Aggregates and Contemporaneous Disturbances are Equicorrelated. Econometrica, 49(1), 205. doi:10.2307/1911134Koput, K. W. (1997). A Chaotic Model of Innovative Search: Some Answers, Many Questions. Organization Science, 8(5), 528-542. doi:10.1287/orsc.8.5.528La Caixa 2009 Spanish estatistical yearbook, 2009 http://www.anuarieco.lacaixa.comunicacions.com/java/X? cgi=caixa.anuari99.util.ChangeLanguage&lang=espLaforet, S. (2008). Size, strategic, and market orientation affects on innovation. Journal of Business Research, 61(7), 753-764. doi:10.1016/j.jbusres.2007.08.002Laursen, K., & Salter, A. (2005). Open for innovation: the role of openness in explaining innovation performance among U.K. manufacturing firms. Strategic Management Journal, 27(2), 131-150. doi:10.1002/smj.507Lee, C.-Y., & Sung, T. (2005). Schumpeter’s legacy: A new perspective on the relationship between firm size and R&D. Research Policy, 34(6), 914-931. doi:10.1016/j.respol.2005.04.006Lin, F.-J., & Lin, Y.-H. (2012). The determinants of successful R&D consortia: government strategy for the servitization of manufacturing. Service Business, 6(4), 489-502. doi:10.1007/s11628-012-0157-7LĂłpez Estornell, M. (s. f.). Empresa innovadora, conocimiento y distrito industrial. doi:10.4995/thesis/10251/10080Maietta , O. 2014 Innovation Systems Research in the Italian Food Industry, Centre for Studies and Economics FinanceMaravelakis, E., Bilalis, N., Antoniadis, A., Jones, K. A., & Moustakis, V. (2006). Measuring and benchmarking the innovativeness of SMEs: A three-dimensional fuzzy logic approach. Production Planning & Control, 17(3), 283-292. doi:10.1080/09537280500285532Moulton, B. R. (1986). Random group effects and the precision of regression estimates. Journal of Econometrics, 32(3), 385-397. doi:10.1016/0304-4076(86)90021-7Moulton, B. R. (1990). An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Units. The Review of Economics and Statistics, 72(2), 334. doi:10.2307/2109724Muscio, A. (2007). THE IMPACT OF ABSORPTIVE CAPACITY ON SMEs’ COLLABORATION. Economics of Innovation and New Technology, 16(8), 653-668. doi:10.1080/10438590600983994Naranjo-Gil, D. (2009). The influence of environmental and organizational factors on innovation adoptions: Consequences for performance in public sector organizations. Technovation, 29(12), 810-818. doi:10.1016/j.technovation.2009.07.003North, D., & Smallbone, D. (1996). Small business development in remote rural areas: The example of mature manufacturing firms in Northern England. Journal of Rural Studies, 12(2), 151-167. doi:10.1016/0743-0167(96)00009-5(2006). The New Rural Paradigm. OECD Rural Policy Reviews. doi:10.1787/9789264023918-enOECD 2013 Entrepreneurship at a Glance OECD PublishingOECD 2014 Research and Development Statistics http://stats.oecd.orgOleaga , M. Caladrero , A. Ugalde , I. 2008 Prospective innovation challenges in the food and drink sector(Onno) Omta, S. (2002). Innovation in chains and networks. Journal on Chain and Network Science, 2(2), 73-80. doi:10.3920/jcns2002.x019O’Regan, N., Ghobadian, A., & Sims, M. (2006). Fast tracking innovation in manufacturing SMEs. Technovation, 26(2), 251-261. doi:10.1016/j.technovation.2005.01.003Paladino, A. (2008). Analyzing the Effects of Market and Resource Orientations on Innovative Outcomes in Times of Turbulence*. Journal of Product Innovation Management, 25(6), 577-592. doi:10.1111/j.1540-5885.2008.00323.xPavitt, K., Robson, M., & Townsend, J. (1987). The Size Distribution of Innovating Firms in the UK: 1945-1983. The Journal of Industrial Economics, 35(3), 297. doi:10.2307/2098636Pezzini, M. (2001). Rural Policy Lessons from OECD Countries. International Regional Science Review, 24(1), 134-145. doi:10.1177/016001701761013024Pisano, G. P. (1990). The R&D Boundaries of the Firm: An Empirical Analysis. Administrative Science Quarterly, 35(1), 153. doi:10.2307/2393554Pla-Barber, J., & Alegre, J. (2007). Analysing the link between export intensity, innovation and firm size in a science-based industry. International Business Review, 16(3), 275-293. doi:10.1016/j.ibusrev.2007.02.005Rama , R. 2008 Handbook of innovation in the food and drink industry New York Haworth PressRobertson, T. S., & Gatignon, H. (1998). Technology development mode: a transaction cost conceptualization. Strategic Management Journal, 19(6), 515-531. doi:10.1002/(sici)1097-0266(199806)19:63.0.co;2-fSchaper, M. T. (2006). Distribution patterns of small firms in developed economies: is there an emergent global pattern? International Journal of Entrepreneurship and Small Business, 3(2), 183. doi:10.1504/ijesb.2006.008927Schmidheiny , K. 2012 Clustering in the linear model, Short guides to microeconometrics http://www.schmidheiny.name/teaching/clustering.pdfSegarra-Blasco, A., & Arauzo-Carod, J.-M. (2008). Sources of innovation and industry–university interaction: Evidence from Spanish firms. Research Policy, 37(8), 1283-1295. doi:10.1016/j.respol.2008.05.003Sorensen, J. B., & Stuart, T. E. (2000). Aging, Obsolescence, and Organizational Innovation. Administrative Science Quarterly, 45(1), 81. doi:10.2307/2666980Spithoven, A., Clarysse, B., & Knockaert, M. (2010). Building absorptive capacity to organise inbound open innovation in traditional industries. Technovation, 30(2), 130-141. doi:10.1016/j.technovation.2009.08.004Tether, B. S. (2002). Who co-operates for innovation, and why. Research Policy, 31(6), 947-967. doi:10.1016/s0048-7333(01)00172-xTraill, W. B., & Meulenberg, M. (2002). Innovation in the food industry. Agribusiness, 18(1), 1-21. doi:10.1002/agr.10002Triguero, Á., CĂłrcoles, D., & Cuerva, M. C. (2013). Differences in Innovation Between Food and Manufacturing Firms: An Analysis of Persistence. Agribusiness, 29(3), 273-292. doi:10.1002/agr.21335Tsai, K.-H., & Wang, J.-C. (2005). Does R&D performance decline with firm size?—A re-examination in terms of elasticity. Research Policy, 34(6), 966-976. doi:10.1016/j.respol.2005.05.017Un, C. A., Cuervo-Cazurra, A., & Asakawa, K. (2010). R&D Collaborations and Product Innovation*. Journal of Product Innovation Management, 27(5), 673-689. doi:10.1111/j.1540-5885.2010.00744.xVan Hemert, P., Nijkamp, P., & Masurel, E. (2012). From innovation to commercialization through networks and agglomerations: analysis of sources of innovation, innovation capabilities and performance of Dutch SMEs. The Annals of Regional Science, 50(2), 425-452. doi:10.1007/s00168-012-0509-1Vecchiato, R., & Roveda, C. (2014). Foresight for public procurement and regional innovation policy: The case of Lombardy. Research Policy, 43(2), 438-450. doi:10.1016/j.respol.2013.11.003Veugelers, R., & Cassiman, B. (2005). R&D cooperation between firms and universities. Some empirical evidence from Belgian manufacturing. International Journal of Industrial Organization, 23(5-6), 355-379. doi:10.1016/j.ijindorg.2005.01.008Wang, Y., & Zhou, Z. (2013). The dual role of local sites in assisting firms with developing technological capabilities: Evidence from China. International Business Review, 22(1), 63-76. doi:10.1016/j.ibusrev.2012.02.003Webber, D., Curry, N., & Plumridge, A. (2009). Business Productivity and Area Productivity in Rural England. Regional Studies, 43(5), 661-675. doi:10.1080/00343400701874156Zhang, Y., & Li, H. (2010). Innovation search of new ventures in a technology cluster: the role of ties with service intermediaries. Strategic Management Journal, 31(1), 88-109. doi:10.1002/smj.80
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