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Tuesday 28 February 2017

Routes to Technological Learning and Development An Assessment of Malaysia's Innovation Policy and Performance

Published Date
Technological Forecasting and Social Change
November 1999, Vol.62(3):239257doi:10.1016/S0040-1625(99)00047-5
  • Author 
  • Joseph Tidd ,,
  •  
  • Michael Brocklehurst

Abstract

In this article we review the range of policy options pursued by national governments for generating innovation within domestic firms. Against this context we examine Malaysia's formal policies for technology acquisition and their implementation. Our analysis draws on an assessment of formal government policy, interviews at public organisations responsible for the implementation of policy, and private domestic and transnational firms, which are active in the target sectors. In total, thirty private and public organisations were visited. It is clear that the Malaysian government has developed a coherent set of policies, which aim to move the economy from its current focus on manufacturing to higher value-added activities such as research and development (R&D), marketing, and distribution. However, we found little evidence of the implementation of such aspirations. In almost all cases transnational companies have confined Malaysian subsidiaries to manufacturing activities, albeit in “high-technology” sectors, and have located development and marketing functions overseas. In fact, growth of value-added and capital intensity have been lower in those sectors dominated by FDI, than in other sectors. Nevertheless, there are isolated cases of indigenous companies which have been able to exploit joint ventures as an opportunity for learning from overseas companies, and this approach appears to offer greater opportunity for achieving the Malaysian government's objectives.



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Vitae


JOSEPH TIDD are faculty at the Imperial College Management School, University of London, London, UK.
MICHAEL BROCKLEHURST are faculty at the Imperial College Management School, University of London, London, UK.

  • *
    Address correspondence to Dr. Joe Tidd, Imperial College Management School, Imperial College of Science, Technology & Medicine, University of London, 53 Prince's Gate, Exhibition Road, London SW7 2PG, UK.
Copyright © 1999 Elsevier Science Inc. All rights reserved.
For further details log on website :
http://www.sciencedirect.com/science/article/pii/S0040162599000475

Neural network and multiple linear regression to predict school children dimensions for ergonomic school furniture design

Published Date
Applied Ergonomics
November 2012, Vol.43(6):979984, doi:10.1016/j.apergo.2012.01.007
  • Author 
  • Salah R. Agha ,
  • Mohammed J. Alnahhal
  • School of Industrial Engineering, Islamic University-Gaza, Gaza Strip, Occupied Palestinian Territory


Abstract

The current study investigates the possibility of obtaining the anthropometric dimensions, critical to school furniture design, without measuring all of them. The study first selects some anthropometric dimensions that are easy to measure. Two methods are then used to check if these easy-to-measure dimensions can predict the dimensions critical to the furniture design. These methods are multiple linear regression and neural networks. Each dimension that is deemed necessary to ergonomically design school furniture is expressed as a function of some other measured anthropometric dimensions. Results show that out of the five dimensions needed for chair design, four can be related to other dimensions that can be measured while children are standing. Therefore, the method suggested here would definitely save time and effort and avoid the difficulty of dealing with students while measuring these dimensions. In general, it was found that neural networks perform better than multiple linear regression in the current study.

Highlights

► The paper uses neural networks and multiple linear regression techniques. ► To predict dimensions needed for ergonomic furniture design from easy-to-measure dimensions. ► Out of the five dimensions needed, four can be predicted from dimensions measured while standing. ► Results further show that neural networks outperforms multiple linear regression in general.

Keywords

  • School furniture
  • Ergonomics
  • Multiple linear regression
  • Neural network

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    • ∗ 
      Corresponding author.
    Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/S000368701200021X

    Production planning in furniture settings via robust optimization

    Published Date
    Computers & Operations Research
    February 2012, Vol.39(2):139150, doi:10.1016/j.cor.2011.02.022
    • Author 
    • Douglas José Alem a,
    • Reinaldo Morabito b,,
    • aUniversidade Federal de São Carlos, Production Engineering Department, Rodovia João Leme dos Santos (SP-264), Km 110, Sorocaba, SP 18052-780, Brazil
    • bUniversidade Federal de São Carlos, Production Engineering Department, Rodovia Washington Luís (SP-310), Km 235, São Carlos, SP 13565-905, Brazil


    Abstract

    Production planning procedures in small-size furniture companies commonly consists of decisions with respect to production level and inventory policy, while attempting to minimize trim-loss, backlogging and overtime usage throughout the planning horizon. Managing these decisions in a tractable way is often a challenge, especially considering the uncertainty of data. In this study, we employ robust optimization tools to derive robust combined lot-sizing and cutting-stock models when production costs and product demands are uncertainty parameters. Our motivation over the traditional two-stage stochastic programming approach is the absence of an explicit probabilistic description of the input data, as well as avoiding to deal with a large number of scenarios. The results concerning uncertainty in the cost coefficients were illustrative and confirmed previous studies. Regarding uncertainty in product demands, we provide some insights into the relationship between the budgets of uncertainty, fill rates and optimal values. Moreover, when uncertainty affects both costs and demands simultaneously, optimal values are worse for large variability levels. Numerical evidence indicated that less conservative budgets of uncertainty result in reasonable service levels with cheaper global costs, while worst-case deterministic approaches generate relatively good fill rates, but with prohibitive global costs.

    Keywords

  • Lot-sizing
  • Cutting-stock
  • Robust optimization
  • Furniture industry

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    • ⁎ 
      Corresponding author.
    Copyright © 2011 Elsevier Ltd. All rights reserved.

    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/S0305054811000645

    Eco-innovation of a wooden childhood furniture set: An example of environmental solutions in the wood sector

    Published Date
    Science of The Total Environment
    1 June 2012, Vol.426:318326, doi:10.1016/j.scitotenv.2012.03.077
    • Author 
    • Sara González-García a,b,,,
    • Raúl García Lozano c
    • Mª. Teresa Moreira a
    • Xavier Gabarrell c
    • Joan Rieradevall i Pons c
    • Gumersindo Feijoo a
    • Richard J. Murphy b
    • aDepartment of Chemical Engineering, School of Engineering, University of Santiago de Compostela, 15782-Santiago de Compostela, Spain
    • bDivision of Biology, Department of Life Sciences, Sir Alexander Fleming Building, Imperial College of London, South Kensington Campus, London SW7 2AZ, UK
    • cSosteniPrA (UAB-IRTA-Inèdit), Institute of Environmental Science and Technology (ICTA), Universitat Autònoma de Barcelona (UAB), School of Engineering, Campus de la UAB, Bellaterra (Cerdanyola del Vallès) 08193 Barcelona, Catalonia, Spain


    Abstract

    The environmental profile of a set of wood furniture was carried out to define the best design criteria for its eco-design. A baby cot convertible into a bed, a study desk and a bedside table were the objects of study. Two quantitative and qualitative environmental approaches were combined in order to propose improvement alternatives: Life Cycle Assessment (LCA) and Design for Environment (DfE). In the first case Life Cycle Assessment (LCA) was applied to identify the hot spots in the product system. As a next step, LCA information was used in eco-briefing to determine several improvement alternatives. A wood products company located in Catalonia (NE Spain) was assessed in detail, dividing the process into three stages: assembly, finishing and packaging. Ten impact categories were considered in the LCA study: abiotic depletion, acidification, eutrophication, global warming, ozone layer depletion, human toxicity, fresh water aquatic ecotoxicity, marine aquatic ecotoxicity, terrestrial ecotoxicity and photochemical oxidant formation. Two processes can be considered the key environmental factors: the production of the wooden boards and electricity, with contributions of 45–68% and 14–33% respectively depending on the impact categories. Subsequently, several improvement alternatives were proposed in the eco-design process (DfE) to achieve reductions in a short–medium period of time in the environmental impact. These eco-design strategies could reduce the environmental profile of the setup by 14%. The correct methodological adaptation of the concept of eco-briefing, as a tool for communication among environmental technicians and designers, the simplification of the analytical tool used and the LCA, could facilitate the environmental analysis of a product. The results obtained provide information that can help the furniture sector to improve their environmental performance.

    Highlights

    ► An environmental evaluation of a wooden childhood furniture set was performed. ► Two environmental methodologies have been integrated. ► Ten impact categories have been assessed in detail. ► Proposed eco-design strategies were evaluated from technological, economic and social perspectives. ► Valuable information to improve the furniture sector’s environmental performance and sustainability is proposed.

    Keywords

  • Eco-design
  • Environmental impacts
  • Furniture
  • Life Cycle Assessment
  • Wood products

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    • ⁎ 
      Corresponding author at: Department of Chemical Engineering, School of Engineering, University of Santiago de Compostela, 15782-Santiago de Compostela, Spain. Tel.: + 34 881816020.
    Copyright © 2012 Elsevier B.V. All rights reserved.

    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/S0048969712004810

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