The gains from preferential tax regimes reconsidered

The EU policy against harmful tax competition aims at eliminating tax policies targeted at attracting the internationally mobile tax base. We construct an imperfectly competitive model of costly trade between two countries. In setting their corporate taxes, governments non-cooperatively decide whether to discriminate between internationally mobile and immobile firms. We find the Nash equilibrium tax regimes. When trade costs are high countries impose a uniform tax on all firms while nations will discriminate between mobile and immobile firms when costs are low. At some trade costs, fiscal competition results in tax discrimination despite uniform taxation being socially preferable

The moral legitimacy of entrepreneurs: An analysis of early-stage entrepreneurship across 26 countries

This article develops our socio-cultural understanding of entrepreneurship by examining the influence of the moral legitimacy of entrepreneurs upon an individual’s engagement in early-stage entrepreneurship. A multilevel analysis conducted across 26 countries demonstrates that the higher the perceived degree of moral legitimacy, the more likely an individual is to consider starting a business, to begin preparing a business and to progress to actually found and run the business. We conclude that moral norms in society are an important influence upon early-stage entrepreneurship; thus, it is critical to legitimize the position of entrepreneurs as moral and beneficial for society as a whole

Suitability of pesticide risk indicators for less developed countries: a comparison

Pesticide risk indicators provide simple support in the assessment of environmental and health risks from pesticide use, and can therefore inform policies to foster a sustainable interaction of agriculture with the environment. For their relative simplicity, indicators may be particularly useful under conditions of limited data availability and resources, such as in Less Developed Countries (LDCs). However, indicator complexity can vary significantly, in particular between those that rely on an exposure–toxicity ratio (ETR) and those that do not. In addition, pesticide risk indicators are usually developed for Western contexts, which might cause incorrect estimation in LDCs. This study investigated the appropriateness of seven pesticide risk indicators for use in LDCs, with reference to smallholding agriculture in Colombia. Seven farm-level indicators, among which 3 relied on an ETR (POCER, EPRIP, PIRI) and 4 on a non-ETR approach (EIQ, PestScreen, OHRI, Dosemeci et al., 2002), were calculated and then compared by means of the Spearman rank correlation test. Indicators were also compared with respect to key indicator characteristics, i.e. user friendliness and ability to represent the system under study. The comparison of the indicators in terms of the total environmental risk suggests that the indicators not relying on an ETR approach cannot be used as a reliable proxy for more complex, i.e. ETR, indicators. ETR indicators, when user-friendly, show a comparative advantage over non-ETR in best combining the need for a relatively simple tool to be used in contexts of limited data availability and resources, and for a reliable estimation of environmental risk. Non-ETR indicators remain useful and accessible tools to discriminate between different pesticides prior to application. Concerning the human health risk, simple algorithms seem more appropriate for assessing human health risk in LDCs. However, further research on health risk indicators and their validation under LDC conditions is needed

Developmental Neurotoxicity Study of Dietary Bisphenol A in Sprague-Dawley Rats

This study was conducted to determine the potential of bisphenol A (BPA) to induce functional and/or morphological effects to the nervous system of F1 offspring from dietary exposure during gestation and lactation according to the Organization for Economic Cooperation and Development and U.S. Environmental Protection Agency guidelines for the study of developmental neurotoxicity. BPA was offered to female Sprague-Dawley Crl:CD (SD) rats (24 per dose group) and their litters at dietary concentrations of 0 (control), 0.15, 1.5, 75, 750, and 2250 ppm daily from gestation day 0 through lactation day 21. F1 offspring were evaluated using the following tests: detailed clinical observations (postnatal days [PNDs] 4, 11, 21, 35, 45, and 60), auditory startle (PNDs 20 and 60), motor activity (PNDs 13, 17, 21, and 61), learning and memory using the Biel water maze (PNDs 22 and 62), and brain and nervous system neuropathology and brain morphometry (PNDs 21 and 72). For F1 offspring, there were no treatment-related neurobehavioral effects, nor was there evidence of neuropathology or effects on brain morphometry. Based on maternal and offspring body weight reductions, the no-observed-adverse-effect level (NOAEL) for systemic toxicity was 75 ppm (5.85 and 13.1 mg/kg/day during gestation and lactation, respectively), with no treatment-related effects at lower doses or nonmonotonic dose responses observed for any parameter. There was no evidence that BPA is a developmental neurotoxicant in rats, and the NOAEL for developmental neurotoxicity was 2250 ppm, the highest dose tested (164 and 410 mg/kg/day during gestation and lactation, respectively)

Perceived Age Discrimination as a Mediator of the Association Between Income Inequality and Older People's Self-Rated Health in the European Region

Objectives. The relative income hypothesis predicts poorer health in societies with greater income inequality. This article examines whether the psychosocial factors of perceived age discrimination and (lack of) social capital may help explain the adverse effect of inequality on older people's health. Methods. Self-rated health, perceived age discrimination, and social capital were assessed in the 2008/9 European Social Survey (European Social Survey Round 4 Data, 2008). The Gini coefficient was used to represent national inequalities in income in each of the 28 European Social Survey countries. Mediation analyses (within a multilevel structural equation modeling paradigm) on a subsample of respondents over 70 years of age (N = 7,819) were used to examine whether perceived age discrimination mediates the negative effect of income inequality on older people's self-rated health. Results. Perceived age discrimination fully mediated the associations between income inequality and self-rated health. When social capital was included into the model, only age discrimination remained a significant mediator and predictor of self-rated health. Discussion. Concrete instances of age discrimination in unequal societies are an important psychosocial stressor for older people. Awareness that the perception of ageism can be an important stressor and affect older patient's self-reported health has important implications for the way health practitioners understand and treat the sources of patient's health problems in later life.info:eu-repo/semantics/acceptedVersio

Drivers of Innovation Using BIM in Architecture, Engineering, and Construction Firms

This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://doi.org/10.1061/9780784482889.023[Otros] Architecture, engineering, and construction (AEC) firms need to innovate in order to increase their business¿ competitiveness. Many companies around the world are considering the possibility of implementing building information modelling (BIM) in their projects without knowing its actual benefits for the business. The current literature recognizes certain barriers to BIM implementation; therefore, considering these barriers, this work proposes a holistic model that allows managers to explain how BIM can play an important role for the success of the AEC companies. The pillars of the model are a collaborative culture and training of employees in order to break down technological barriers. This way, BIM can help AEC companies to innovate. This proposal takes into consideration the three phases of the infrastructure life-cycle. In the design phase, the model considers 3D shape, scheduling (4D), costs (5D), and sustainability (6D). In the construction phase, the model focuses on supply chain and quality management. During the operation phase, the model is related to the virtual management of maintenance activities. Drivers of innovation should consider several facets: marketing, technology, organization, processes, and products. This model aims to enlighten the positive effects of a good strategic management using BIM on innovation activities in each of the phases of the infrastructure life-cycleVillena, F.; García-Segura, T.; Pellicer, E. (2020). Drivers of Innovation Using BIM in Architecture, Engineering, and Construction Firms. American Society of Civil Engineers. 210-222. https://doi.org/10.1061/9780784482889.023S210222Aibinu, A., & Venkatesh, S. (2014). Status of BIM Adoption and the BIM Experience of Cost Consultants in Australia. Journal of Professional Issues in Engineering Education and Practice, 140(3), 04013021. doi:10.1061/(asce)ei.1943-5541.0000193Alshubbak, A., Pellicer, E., Catalá, J., & Teixeira, J. M. C. (2015). A MODEL FOR IDENTIFYING OWNER’S NEEDS IN THE BUILDING LIFE CYCLE. Journal of Civil Engineering and Management, 21(8), 1046-1060. doi:10.3846/13923730.2015.1027257Autodesk Inc. (2012). Building information modelling [online] [8-06-2012]. Available from Internet: http://usa.autodesk.comAzhar, S., Khalfan, M., & Maqsood, T. (2015). Building information modelling (BIM): now and beyond. Construction Economics and Building, 12(4), 15-28. doi:10.5130/ajceb.v12i4.3032Blayse, A. M., & Manley, K. (2004). Key influences on construction innovation. Construction Innovation, 4(3), 143-154. doi:10.1108/14714170410815060Boland, R. J., Lyytinen, K., & Yoo, Y. (2007). Wakes of Innovation in Project Networks: The Case of Digital 3-D Representations in Architecture, Engineering, and Construction. Organization Science, 18(4), 631-647. doi:10.1287/orsc.1070.0304Bryde, D., Broquetas, M., & Volm, J. M. (2013). The project benefits of Building Information Modelling (BIM). International Journal of Project Management, 31(7), 971-980. doi:10.1016/j.ijproman.2012.12.001Chen, Y.-S. (2007). The Driver of Green Innovation and Green Image – Green Core Competence. Journal of Business Ethics, 81(3), 531-543. doi:10.1007/s10551-007-9522-1Cheng, Y.-M. (2018). Building Information Modeling for Quality Management. Proceedings of the 20th International Conference on Enterprise Information Systems. doi:10.5220/0006796703510358Chesbrough, H., & Crowther, A. K. (2006). Beyond high tech: early adopters of open innovation in other industries. R and D Management, 36(3), 229-236. doi:10.1111/j.1467-9310.2006.00428.xDavies, R., & Harty, C. (2013). Implementing ‘Site BIM’: A case study of ICT innovation on a large hospital project. Automation in Construction, 30, 15-24. doi:10.1016/j.autcon.2012.11.024Du Plessis, M. (2007). The role of knowledge management in innovation. Journal of Knowledge Management, 11(4), 20-29. doi:10.1108/13673270710762684Eastman, C., Teicholz, P., Sacks, R., & Liston, K. (2008). BIM Handbook. doi:10.1002/9780470261309Elmualim, A., & Gilder, J. (2013). BIM: innovation in design management, influence and challenges of implementation. Architectural Engineering and Design Management, 10(3-4), 183-199. doi:10.1080/17452007.2013.821399Erdogan, B., Anumba, C. J., Bouchlaghem, D., & Nielsen, Y. (2008). Collaboration Environments for Construction: Implementation Case Studies. Journal of Management in Engineering, 24(4), 234-244. doi:10.1061/(asce)0742-597x(2008)24:4(234)Fox, S., & Hietanen, J. (2007). Interorganizational use of building information models: potential for automational, informational and transformational effects. Construction Management and Economics, 25(3), 289-296. doi:10.1080/01446190600892995Franco, J., Mahdi, F., & Abaza, H. (2015). Using Building Information Modeling (BIM) for Estimating and Scheduling, Adoption Barriers. Universal Journal of Management, 3(9), 376-384. doi:10.13189/ujm.2015.030905Hameed, M. A., Counsell, S., & Swift, S. (2012). A conceptual model for the process of IT innovation adoption in organizations. Journal of Engineering and Technology Management, 29(3), 358-390. doi:10.1016/j.jengtecman.2012.03.007Harness S. H. (2008). 2008 documents AIA advance the use of BIM and integrated project delivery [online] [5 Diciembre 2008]. Available from Internet: http://www.aia.orgHobday, M. (2005). Firm-level Innovation Models: Perspectives on Research in Developed and Developing Countries. Technology Analysis & Strategic Management, 17(2), 121-146. doi:10.1080/09537320500088666Hong Y. Hammad A. Sepasgozar S. and Akbarnezhad A. (2019). "BIM adoption model for small and medium construction organizations in Australia" Engineering Construction and Architectural Management 26(2) 154-183. https://doi.org/10.1108/ECAM-04-2017-006410.1108/ECAM-04-2017-0064Hurley, R. F., & Hult, G. T. M. (1998). Innovation, Market Orientation, and Organizational Learning: An Integration and Empirical Examination. Journal of Marketing, 62(3), 42-54. doi:10.1177/002224299806200303Khosrowshahi, F., & Arayici, Y. (2012). Roadmap for implementation of BIM in the UK construction industry. Engineering, Construction and Architectural Management, 19(6), 610-635. doi:10.1108/09699981211277531Kleinschmidt, E. J., de Brentani, U., & Salomo, S. (2007). Performance of Global New Product Development Programs: A Resource-Based View. Journal of Product Innovation Management, 24(5), 419-441. doi:10.1111/j.1540-5885.2007.00261.xLee, S., Yu, J., & Jeong, D. (2015). BIM Acceptance Model in Construction Organizations. Journal of Management in Engineering, 31(3), 04014048. doi:10.1061/(asce)me.1943-5479.0000252Lu, Q., & Lee, S. (2017). Image-Based Technologies for Constructing As-Is Building Information Models for Existing Buildings. Journal of Computing in Civil Engineering, 31(4), 04017005. doi:10.1061/(asce)cp.1943-5487.0000652Miettinen, R., & Paavola, S. (2014). Beyond the BIM utopia: Approaches to the development and implementation of building information modeling. Automation in Construction, 43, 84-91. doi:10.1016/j.autcon.2014.03.009Motamedi, A., Hammad, A., & Asen, Y. (2014). Knowledge-assisted BIM-based visual analytics for failure root cause detection in facilities management. Automation in Construction, 43, 73-83. doi:10.1016/j.autcon.2014.03.012Oduyemi O Okoroh MI Fajana OS. (2017). "The application and barriers of BIM in sustainable building design" Journal of Facilities Management 15(1):15−34. https://doi.org/10.1108/JFM-03-2016-0008.10.1108/JFM-03-2016-0008Olawumi, T. O., Chan, D. W. M., Wong, J. K. W., & Chan, A. P. C. (2018). Barriers to the integration of BIM and sustainability practices in construction projects: A Delphi survey of international experts. Journal of Building Engineering, 20, 60-71. doi:10.1016/j.jobe.2018.06.017Ozorhon, B., & Oral, K. (2017). Drivers of Innovation in Construction Projects. Journal of Construction Engineering and Management, 143(4), 04016118. doi:10.1061/(asce)co.1943-7862.0001234Papadonikolaki, E. (2018). Loosely Coupled Systems of Innovation: Aligning BIM Adoption with Implementation in Dutch Construction. Journal of Management in Engineering, 34(6), 05018009. doi:10.1061/(asce)me.1943-5479.0000644Pellicer, E., Yepes, V., Correa, C. L., & Alarcón, L. F. (2014). Model for Systematic Innovation in Construction Companies. Journal of Construction Engineering and Management, 140(4). doi:10.1061/(asce)co.1943-7862.0000700Poirier, E., Forgues, D., & Staub-French, S. (2016). Collaboration through innovation: implications for expertise in the AEC sector. Construction Management and Economics, 34(11), 769-789. doi:10.1080/01446193.2016.1206660Poirier, E., Staub-French, S., & Forgues, D. (2015). Embedded contexts of innovation. Construction Innovation, 15(1), 42-65. doi:10.1108/ci-01-2014-0013Rowlinson S. Collins R. Tuuli M. and Jia A. (2010). Implementation of Building Information Modeling (BIM) in Construction: A Comparative Case Study. AIP Conference Proceedings. 1233. 572-577. 10.1063/1.3452236.Selçuk Çıdık, M., Boyd, D., & Thurairajah, N. (2017). Innovative Capability of Building Information Modeling in Construction Design. Journal of Construction Engineering and Management, 143(8), 04017047. doi:10.1061/(asce)co.1943-7862.0001337Stock, R. M., Six, B., & Zacharias, N. A. (2012). Linking multiple layers of innovation-oriented corporate culture, product program innovativeness, and business performance: a contingency approach. Journal of the Academy of Marketing Science, 41(3), 283-299. doi:10.1007/s11747-012-0306-5Succar, B., & Kassem, M. (2015). Macro-BIM adoption: Conceptual structures. Automation in Construction, 57, 64-79. doi:10.1016/j.autcon.2015.04.018Succar, B. (2009). Building information modelling framework: A research and delivery foundation for industry stakeholders. Automation in Construction, 18(3), 357-375. doi:10.1016/j.autcon.2008.10.003Taylor, J. E., & Bernstein, P. G. (2009). Paradigm Trajectories of Building Information Modeling Practice in Project Networks. Journal of Management in Engineering, 25(2), 69-76. doi:10.1061/(asce)0742-597x(2009)25:2(69)Tekla Corporation. (2013). Basic concepts [online] [ 16 Enero 2013]. Available from Internet: http://www.tekla.comVillena Manzanares, F., & Galiano Coronil, A. (2017). EL DESARROLLO URBANO SOSTENIBLE Y SUS IMPLICACIONES PARA LAS EMPRESAS Y LOS TERRITORIOS. Revista de Estudios Empresariales. Segunda Época, (1). doi:10.17561/ree.v0i1.3185Volk, R., Stengel, J., & Schultmann, F. (2014). Building Information Modeling (BIM) for existing buildings — Literature review and future needs. Automation in Construction, 38, 109-127. doi:10.1016/j.autcon.2013.10.023Whyte, J., Bouchlaghem, N., Thorpe, A., & McCaffer, R. (2000). From CAD to virtual reality: modelling approaches, data exchange and interactive 3D building design tools. Automation in Construction, 10(1), 43-55. doi:10.1016/s0926-5805(99)00012-6Wischnevsky, J. D., Damanpour, F., & Méndez, F. A. (2011). Influence of Environmental Factors and Prior Changes on the Organizational Adoption of Changes in Products and in Technological and Administrative Processes. British Journal of Management, 22(1), 132-149. doi:10.1111/j.1467-8551.2010.00700.xWong, K., & Fan, Q. (2013). Building information modelling (BIM) for sustainable building design. Facilities, 31(3/4), 138-157. doi:10.1108/02632771311299412Yepes, V., Pellicer, E., Alarcón, L. F., & Correa, C. L. (2016). Creative Innovation in Spanish Construction Firms. Journal of Professional Issues in Engineering Education and Practice, 142(1), 04015006. doi:10.1061/(asce)ei.1943-5541.0000251Yusof N. Seng Lai K and Mustafa Kamal E. (2017). "Characteristics of innovation orientations in construction companies" Journal of Engineering Design and Technology 15(4) 436-455. https://doi.org/10.1108/JEDT-06-2016-003710.1108/JEDT-06-2016-0037Zhou, Y., Yang, Y., & Yang, J.-B. (2019). Barriers to BIM implementation strategies in China. Engineering, Construction and Architectural Management, 26(3), 554-574. doi:10.1108/ecam-04-2018-015

Reclaiming the local in EU peacebuilding: Effectiveness, ownership, and resistance

Since the early 2000s, the "local turn" has thoroughly transformed the field of peacebuilding. The European Union (EU) policy discourse on peacebuilding has also aligned with this trend, with an increasing number of EU policy statements insisting on the importance of "the local." However, most studies on EU peacebuilding still adopt a top-down approach and focus on institutions, capabilities, and decision-making at the EU level. This special issue contributes to the literature by focusing on bottom-up and local dynamics of EU peacebuilding. After outlining the rationale and the scope of the special issue, this article discusses the local turn in international peacebuilding and identifies several interrelated concepts relevant to theorizing the role of the local, specifically those of effectiveness, ownership, and resistance. In the conclusion, we summarize the key contributions of this special issue and suggest some avenues for further research

Defining a common set of indicators to monitor road accidents in the European Union

BACKGROUND: currently road accidents are mostly monitored through mortality and injury rates. This paper reports the methodology and the results of a project set forth by the European Union (EU) and coordinated by the WHO aimed at identifying and evaluating a core set of indicators to monitor the causal chain of road accident health effects. The project is part of the ECOEHIS (Development of Environment and Health Indicators for European Union Countries). METHODS: a group of experts (WG), identified 14 indicators after a review of the information collected at the EU level, each of them representing a specific aspect of the DPSEEA (Driving, Pressure, State, Exposure, Effect, Action) model applied and adapted to the road accidents. Each indicator was scored according to a list of 16 criteria chosen by the WG. Those found to have a high score were analysed to determine if they were compatible with EU legislation and then tested in the feasibility study. RESULTS: 11 of the 14 indicators found to be relevant and compatible with the criteria of selection were proposed for the feasibility study. Mortality, injury, road accident rate, age of vehicle fleet, and distance travelled are the indicators recommended for immediate implementation. CONCLUSION: after overcoming the limitations that emerged (absence of a common definition of death by road accident and injury severity, underestimation of injuries, differences in information quality) this core set of indicators will allow Member States to carry out effective internal/external comparisons over time