AJIBM  Vol.8 No.8 , August 2018
An Online Productivity Measuring and Analyzing System: Proof-of-Concept
Abstract: The principle aim of this applied research is to design and build up an Online Productivity Measuring and Analyzing System (OPMAS): Proof-of-Concept1 to measure and analyze the economic growth and its major sources; the multifactor productivity and factor-intensity at the firm, sub-industry (ISC 2-digit), and industry levels. Special features of this applied research are the instantaneous productivity measuring and analyzing. In addition, it is developing an educational and training HUB for productivity awareness and improvements for both researchers and organizations. Thus, the HUB comes with a prompt measuring tools/models (OPMAS) of the economic performance; the multifactor productivity and singly-factor productivity growth of a firm using its one-year loss/profit statement or/and time series data. Besides to the hub’s prompt measuring of productivity, the firm will also be provided with an instant-reporting about its economic performance in-compression to its related industry at two different levels (2-digit and i-digit ISC). For example, a firm operating within Food and Beverages manufacturing industry, it will be compared with the performances of the Food and Beverages manufacturing industry 2-digit ISC and with the performance of the overall Manufacturing Industry, D-ISC. Furthermore, a simulation model (Productivity Analytics) for investigating the impact of various policies on the firm’s economic performance could be proposed. The policies which they could be analyzed including environmental regulations, import and export taxes, and the provision of infrastructure.
Cite this paper: Shebeb, B. (2018) An Online Productivity Measuring and Analyzing System: Proof-of-Concept. American Journal of Industrial and Business Management, 8, 1861-1878. doi: 10.4236/ajibm.2018.88126.

[1]   Andrews, D., Criscuolo, C. and Gal, P.N. (2015) Frontier Firms, Technology Diffusion and Public Policy: Micro Evidence from OECD Countries. OECD Productivity Working Papers, No. 2, OECD Publishing, Paris.

[2]   Byrne, D.M., Fernald, J.G. and Reinsdorf, M.B. (2016) Does the United States Have a Productivity Slowdown or a Measurement Problem? Brookings Papers on Economic Activity, Washington DC.

[3]   Syverson, C. (2016) Challenges to Mismeasurement Explanations for the U.S. Productivity Slowdown. NBER Working Paper 21974.

[4]   Diewert, W.E. (1976) Exact and Superlative Index Numbers. Journal of Econometrics, 4, 115-145.

[5]   Gollop, F.M. (1983) Growth Accounting in an Open Economy, in Developments in Econometric Analysis of Productivity: Measurement and Modeling Issues. Kluwer-Nijhoff Publishing, London.

[6]   Hulten, C.R. (1978) Growth Accounting with Intermediate Inputs. Review of Economic Studies, 45, 511-518.

[7]   Diewert, W.E. and Nakamura, A. (2007) The Measurement of Aggregate Total Factor Productivity Growth. In: Heckman, J.J. and Leamer, E.E., Eds., Handbook of Econometrics, Elsevier Science Publishing, Amsterdam, 4502-4530.

[8]   Shebeb, B. (2016) Adjusted-Productivity Growth for Resource Rent: Kuwait Oil Industry. Applied Economics and Finance, 3, 128-135.

[9]   Oliner, S. and Sichel, D. (2002) Information Technology and Productivity: Where Are We Now and Where Are We Going? Federal Reserve Bank Atlantic Economic Review, Summer, 15-44.