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Mohamad, Nordin Haji
- Decomposing Total Factor Productivity Growth in Small and Medium Enterprises, SMEs
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Authors
Affiliations
1 Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur, MY
2 Faculty of Economics and Administration, University of Malaya, 50603 Kuala Lumpur, MY
1 Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur, MY
2 Faculty of Economics and Administration, University of Malaya, 50603 Kuala Lumpur, MY
Source
Indian Journal of Science and Technology, Vol 5, No 5 (2012), Pagination: 2706-2712Abstract
Small and Medium Enterprises (SMEs) are one of the principal driving forces in economic development and are the backbones of most economies, developing as well as developed. The purpose of this paper is to model and investigate the total factor productivity growth of SMEs with reference to technological and technical efficiency change which are synonym to adoption and adaptation of technology. To do this, we utilize the linear programming based operations research technique known as Data Envelopment Analysis methodology of Malmquist Total Factor Productivity, TFP index. TFP measures the overall efficiency with which products are produced due to non-physical change. Improvement in TFP will enable the economy to generate a larger output from the same available resources, and hence shifting it to a higher frontier. The technological change component of productivity growth provides a measure of innovation or adoption of new technology and captures shifts in the frontier technology. Technical inefficiency, on the other hand, is measured by the difference between the frontier output and the realized output. Thus decomposition of TFP growth into technical efficiency improvement (adaptation or catching up) and technological change is therefore useful in distinguishing innovation or adoption of new technology by 'best practice' firms from the diffusion of technology. The study utilizes data on SMEs from 42 selected economies (29 European Union and 13 APEC countries) for the period 2004-2008. Results obtained are analyzed and discussed, and some policy implications are suggested.Keywords
Data Envelopment Analysis, Malmquist Total Factor Productivity, Technical Efficiency, Technological Change, Small And Medium EnterprisesFull Text
References
- Afonso A and Fernandes S (2006) Measuring local government spending efficiency: Evidence from the Lisbon region. Regional Studies. 40(1),39-53.
- Ardabili JS, Aghayi N and Monzali A (2007) New efficiency using undesirable factors of data envelopment analysis. Adv. Modeling & Optimization. 9(2), 249-255.
- Azar A, Olfat L, Khosravani F and Jalali R (2011) A BSC method for supplier selection strategy using TOPSIS and VIKOR. A case study of part maker industry. Manage. Sci. Lett. 1(4),559-568.
- Banker RD, Chang H, Janakiraman SN and Konstans C (2004) A balanced scorecard analysis of performance metrics. Euro.J. Operational Res. 154(2), 423-436.
- Barkema HG, Baum JAC and Mannix EA (2002) Management challenges in a new time. Acad. Manage. J. 44(5), 916-930.
- Barros CP and Dieke PUC (2008) Technical efficiency of African hotels. Int. J. Hospitality Manage. 27(3), 438-447.
- Bhandari AK and Maiti P (2007) Efficiency of Indian manufacturing firms: textile industry as a case study. Int.J. Bus. & Econ. 6(1), 71-88.
- Boame AK (2004) The technical efficiency of Canadian urban transit systems. Transportation Res. Part E, 40(5), 401-416.
- Chakraborty T, Ghosh T and Dan PK (2011) Application of analytic hierarchy process and heuristic algorithm in solving vendor selection problem. Bus. Intelligence J. 4(1), 167-177.
- Chelliah S, Sulaiman M and Yusoff YM (2010) Internationalization and performance: small and medium enterprises (SMEs) in Malaysia, Int. J. Bus. & Manage. 56(6), 27-37.
- Chen T and Lu LY (2006) Innovation and the operational performance of IC design industry in Taiwan: a data envelopment analysis. Conference paper presented at Intenational Conference on Management of Technology (IAMOT2006), Beijing, China. ISBN: 0-9712964-8.0, 2006.
- Coli M, Nissi E and Rapposelli A (2007) Efficiency evaluation by means of data envelopment analysis: strengths and weaknesses. In: Methods, models and information technologfies for decision support systems. First Part: Methodologies. D’Ambra L, Rostirolla P & Squillante M (Eds.), FranceAngeli, Milano.
- Emrouznejad A, Barnett RP and Tavares GT (2008) Evaluation of research in efficiency and productivity: A survey analysis of the first 30 years of scholarly literature in DEA. Socio-Economic Planning Sci. 42(3),151-157.
- Fare R, Grosskoph S, Norris M and Zhang Z (1994) Productivity growth, technical progress and efficiency change in industrialised countries. Am. Econ. Rev. 84(1), 63-83.
- Hasanov S and Nomman AM (2011) Agricultural efficiency under resource scarcity in Uzbekistan: A data envelopment analysis. Bus. & Econ. Horizon. 4(1), 81-87.
- Hossain MZ and Al-Amri KS (2010) Use of Cobb_Douglas production model on some selected manufacturing industries in Oman. Edu., Bus. & Soc. Contemporary Middle Eastern Issues. 3(2), 78-85.
- Kao C and Hung H (2008) Efficiency analysis of university departments: An empirical study. OMEGA, The Int. J. Manage. Sci. 36(4),653-666.
- Laforet S and Tann J (2006) Innovative characteristics of small manufacturing firms. J. Small & Enterprise Dev. 13(3), 363-390.
- Laine J, Finne-Soveri UH, Bjorkgren M, Linna M, Noro A and Hakkinen U (2005) The association between quality of care and technical efficiency in long-term care, Int. J. Quality Health Care. 17 (3), 259-267.
- Mohamad NH and Said F (2010a) Measuring the performance of 100 largest listed companies in Malaysia. Afr. J. Bus. Manage. 4(13), 3178-3190.
- Mohamad NH and Said F (2010b) Decomposing productivity growth in Malaysian food manufacturing industry. Afr. J. Bus.Manage. 4 (17), 3522-3529.
- Mohamad NH and Said F (2011a) Efficiency and innovation in selected Malaysian government-linked companies for the period 2003-2008. Afr. J. Bus. Manage. 5(25),10259-10270.
- Mohamad NH and Said F (2011b) Comparing macroeconomic performance of OIC member countries, International J. Econ. & Manage. Sci. 1(3):90-104.
- Mostafa M (2007) Benchmarking top Arab banks’ efficiency through efficient frontier analysis.Ind. Manage. & Data Systems. 107(6), 802-823.
- Radam A, Abu M and Abdullah AM (2008) Technical efficiency of small and medium enterprises in Malaysia: a stochastic frontier production model. Int. J. Econ. & Manage. 2(2), 395-408.
- Shackleton C (2007) Developing key performance indicator for corporate communication in the information technology industry. Unpublished Master Thesis, Faculty of Economics and Management Sciences, University of Pretoria.
- Shazali AM, Alias R and Rossazana AR (2004) Technical efficiency on furniture industry in Malaysia, The Asian Economic Rev. J. Indian Institute of Econ. 46(2), 377-384.
- Tavares G (2002) A bibliography of data envelopment analysis (1978-2001). Rutcor Res.Report, RRR 01-02, January 2002.
- Wanke PF, Barbastefano RG and Hijjar MF (2011) Determinants of efficiency at major Brazilian port terminals. Transport Rev. 31(5), 653-677.
- Yahya AZ, Othman MS, Othman AS, Rahman IA and Moen JA (2011) Process innovation: a study of Malaysian small medium enterprises (SMEs). World J. Manage. 3(1),146- 156.
- Yang J (2006) The efficiency of SMEs in the global market: Measuring the Korean performance, J.Policy Modeling. 28(8), 861-876.
- Integer Linear Programming Approach to Scheduling Toll Booth Collectors Problem
Abstract Views :515 |
PDF Views:0
Authors
Affiliations
1 Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur, MY
2 Faculty of Economics and Administration, University of Malaya, 50603 Kuala Lumpur, MY
1 Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur, MY
2 Faculty of Economics and Administration, University of Malaya, 50603 Kuala Lumpur, MY
Source
Indian Journal of Science and Technology, Vol 6, No 5 (2013), Pagination: 4416-4421Abstract
A general daily staff scheduling problem with hourly requirement patterns is considered and formulated into an integer linear programming problem. A numerical illustrative example of scheduling toll booth collectors of full-timers and part-timers is presented and solved by LINDO.Keywords
Integer Linear Program, Scheduling, Toll Booth CollectorsFull Text
References
- Akarro R R J (2009). A linear programming model as an approximation for media advertisement selection on HIV/AIDS spread in Dar es Salaam, Tanzania, European Journal of Scientific Research, vol 26(3), 417-429.
- Aslan I (2011). A linear programming approach for different serial machines scheduling with optimizing batch size in a flow oriented synchronized production, 2011 International Conference on Innovation, Management and Service, IPEDR, vol 14(2011).
- Atlason J, Epelman M A et al. (2004). Call center staffing with simulation and cutting plane methods, Annals of Operations Research, vol 127(1-4), 333-358.
- Bahl H C, Taj S et al. (1991). A linear-programming model formulation for optimal product-mix decisions in material-requirements-planning environments, International Journal of Production Research, vol 29(5), 1025-1034.
- Baker K R, and Taylor R E (1979). A linear programming framework for cost allocation and external acquisition when reciprocal services exist, The Accounting Review, vol 54(4), 784-790.
- Bedworth D D, and Bailey J E (1987). Integrated production control systems: Management, analysis, design, 2nd Edn. Wiley, New York, 387-420.
- Billionnet A (1999). Integer programming to schedule a hierarchical workforce with variable demands, European Journal of Operational Research, vol 114(1), 105-114.
- Darby-Dowman K, and Wilson J M (2002). Developments in linear and integer programming, Journal of the ORS, vol 53(10), 1065-1071.
- Ernst A T, Jiang H et al. (2004). Staff scheduling and rostering: A review of applications, method and models, European Journal of Operational Research, vol 153(1), 3-27.
- Jarrah A I Z, Bard J F et al. (1994). Solving large-scale tour scheduling problem, Management Science, vol 40(9), 1124-1144.
- Kottke M W (1987) Application of a linear programming model for estimating the economic impact of tourism development, Storrs Agricultural Experiment Station, Paper 28.
- Lan Y, Lv X et al. (2007). A linear programming model of fuzzy portfolio selection problem, Proceedings of 2007 IEEE International Conference on Control and Automation, Guangzhou, CHINA.
- Li Z, Wang S et al. (2000). A linear programming algorithm for optimal portfolio selection with transaction costs, International Journal of Systems Science, vol 31(1), 107-117.
- Lin C K Y, Lai K F et al. (2000). Development of a workforce management system for a customer hotline service, Computer & Operations Research, vol 27(10), 987-1004.
- Liu H W (2011). Linear programming for portfolio selection based on fuzzy decision-making theory, Proceedings of The Tenth International Symposium on Operations Research and Its Applications (ISORA 2011), Dunhuang, CHINA.
- Mansini R, Ogryczak W et al. (2003). On LP solvable models for portfolio selection, Informatica, vol 14(1), 37-62.
- Miller H E (1976). Personnel scheduling in public systems: a survey, Socio-Economic Planning Science, vol 10(6), 241-249.
- Nanda R, and Browne J (1992). Introduction to employee scheduling, Van Nostrand Reinhold, New York.
- Ogryczak W (2000). Multiple criteria linear programming model for portfolio selection, Annals of Operations Research, vol 97(1-4), 143-162.
- Render B, and Stair R M (1997). Quantitative Analysis for Management. 6th Edn, Prentice-Hall International Inc, USA.
- Salmi T (1976). Multiperiod production and financial planning with two-stage linear programming, The Finnish Journal of Business Economics, vol 25(4), 454-476.
- Thompson G M (1997). Labor staffing and scheduling models for controlling service levels, Naval Research Logistics, vol 44(8), 719-740.
- Tien J M, and Kamiyama A (1982). On manpower scheduling algorithms, SIAM Review, vol 24(3), 257-287.
- van Rensburg R J, and Bredenkamp B V (1997). Optimising nursery operation schedules with multiperiod linear programming, Southern African Forestry Journal, vol 179, 7-11.
- Vohra R V (1987). The cost of consecutivity in the (5, 7) cyclic staffing problem, IIE Transactions. vol 19(3), 13-18.
- Winston W L (1995). Introduction to Mathematical Programming: Applications and Algorithms, 2nd Edn., Duxbury Press, California, USA.
- Young M R (1998). A minimax portfolio selection rule with linear programming solution, Management Science, vol 44(5), 673-683.
- Zhang X, and Bard J F (2006). A multi-period machine assignment problem, European Journal of Operational Research, vol 170(2), 398-415.