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Online Free Access Handbook of Industrial Engineering includes all modules of IE Online Course Notes.
New. Popular E-Book on IE,
Introduction to Modern Industrial Engineering. #FREE #Download.
In 0.1% on Academia.edu. 3600+ Downloads so far.
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Lesson 306 of IEKC Industrial Engineering ONLINE Course Notes.
Productivity management is one of the important functions of industrial engineering departments in companies. Productivity measurement facilitates planning and controlling productivity levels in the companies.
Productivity can be calculated for each individual input into an operation, process or product. Such productivity measurements for individual inputs are called partial productivity measures. At this measurement level, potential productivity for recent developments in technology can be defined or determined.
Productivity can be defined as output/input. Both output and input can be in numbers or quantity. When multiple outputs come from an input and if one wants to calculated combined productivity, the output may be converted into monetary terms or equivalent product units.
Productivity is calculated for combinations of inputs. Such a calculation becomes necessary, when increase in one input leads to decrease in another input. So an optimal or maximum profit combination is to be found, specified and monitored.
When all inputs into a process are considered in the denominator, we come to total factor productivity.
Productivity - Definitions
Productivity was mentioned probably for the first time in an article by Quesnay in 1766.
In 1883, Littre defined productivity as the "faculty to produce," that is, the desire to produce.
In 1950, the Organisation for European Economic Cooperation (OEEC) provided the following definition of productivity:
"Productivity is the quotient obtained by dividing output by one of the factors of production. In this way it is possible to speak of the productivity of the capital, investment, or raw materials according to whether output is being considered in relation to capital, investment, or raw materials, etc."
Productivity may be defined as follows:
Productivity = Output/Input (Kanawaty, ILO Work Study)
The term productivity can be used to assess or measure the extent to which a certain output can be extracted from a given input. The inputs of an enterprise are land and buildings, materials, plant machines and equipment, energy and human resources. The outputs are saleable products and services.
Life of a cutting tool is a productivity measure. If the life can be extended through design of cutting process parameters and if this change gives benefit at the overall process level to reduce total time including the time spent for tool sharpening and tool change, it is productivity improvement that is driven by the tool life. For each part, one can calculated output per machine per hour. This can be used as a productivity measure to compare alternative processes or process plans.
Measurement of productivity for single input and single output is relatively used. But to calculate productivity for single machine used for multiple outputs is relatively more difficult. We have to use some common output measure to calculate weekly productivity to compare at week level. When multiple input and multiple parts/products are there, the calculation is much more complex and we have different methods proposed by different persons or organizations.
Productivity Measures proposed and used by economists and accountants
I. Kendrick – Creamer Model :[1]
Kendrick and Creamer (1965) introduced productivity indexes at the company level in their book, "Measuring Company Productivity". They proposed two types of indices: total productivity and partial productivity.
Partial productivity of labour, capital or material productivity index can be calculated as:
Partial productivity index for a period = (Output in base period price) / (Any one Input in base period price)
Partial productivity of labour, capital or material productivity index can be calculated as:
Partial productivity index for a period = (Output in base period price) / (Any one Input in base period price)
Total productivity index for given period = (Measured period output in base period price) / (Measured period input in base period price)
Total factor productivity index = net output/total factor input
Net output = Gross output – intermediate goods and services
Total factor input = manhour input and total capital
II. Craig –Harris Model :
Craig and Harris (1972, 1973) [2,3] defined total productivity measure:
PT= OT / ( L+C+R+Q )
Where;
PT = total productivity,
OT= total out put.
L = labor input factor,
C = capital input factor,
R = raw material input factor and
Q = other miscellaneous goods and services input factor
The output is defined as the summation of all units produced times their selling price, plus dividends from securities and interest from bonds and other such sources-all adjusted to base-period values.
III. Hines (1976)[4] proposed some measurement improvements to various individual items in productivity measurement models.
IV. American Productivity Centre Model :[5]
American Productivity Center has measure that expresses profitability as a product of productivity and price factor. The way it is done is:
Profitability = Sales / Cost
= (Output quantity) *(Price) / (input quantity)* (unit cost)
= (Output quantity) *(Price) / (input quantity)* (unit cost)
= (Productivity)* (Price recovery factor)
= [(Output quantity)/(input quantity)]*[(Price)/(unit cost)]
= [(Output quantity)/(input quantity)]*[(Price)/(unit cost)]
Where; productivity = output quantity / input quantity
V. Sumanth’s Total Productivity Model (1979) [6]
Total productivity (TPM) = total tangible output/total tangible input
Where
Total tangible output = (value of finished units produced + value of partial units produced
+ dividends from securities + interest from bonds+ other income)
and
Total tangible input = value of (human + material + capital + energy + other expenses) inputs used.
Sumanth provided a structure for finding productivity at product level and summing product level productivities to total firm level productivity. The model also has the structure for finding partial productivities at the product level and aggregating them to product level productivities.
Is productivity measurement in practice today?
The answer is yes.
In FY 2006 the study group on the Creation of a Productivity Database on Japanese, Chinese, and South Korean Companies at the Japan Center for Economic Research (JCER) created the East Asian Listed Companies Database 2007 ("EALC 2007") along with the Hitotsubashi University Center for Economic Institutions (CEI), the CENU Center for China and Asian Studies (CCAS; Professor Tomohiko Inui as project representative), and the Center for Corporate Competitiveness of Seoul National University (Professor Keun Lee as project representative). EALC 2007 in principle targets all listed firms in Japan, China, and South Korea (not including the financial sector). It includes data necessary to measure total factor productivity at the company level and the periods covered are 1985 through 2004 for Japanese firms, 1985 through 2005 for South Korean firms, and 1999 through 2004 for Chinese firms.
Based on direct comparison of the total factor productivity of listed firms in Japan, China, and South Korea, the researchers analyzed the following questions. 1) In which industries in particular are South Korean and Chinese companies catching up to Japanese ones? 2) Has productivity growth in Japanese firms stagnated since the 1990s? 3) If it has stagnated, in which industries is this most remarkable? 4) What are the characteristics of disparities in productivity among companies in the same industries in each country? The reports (in Japanese) cover the results of the research on these questions[6].
The Japan Center for Economic Research, the Hitotsubashi University Center for Economic Institutions, the CENU Center for China and Asian Studies, and the Center for Corporate Competitiveness of Seoul National University plan to continue joint research in FY 2007, including revising and updating the EALC database, expanding the countries targeted, and analyzing results.
References
1. Kendrick, J.W., and D. Creamer, “Measuring Company Productivity: Handbook with Case Studies.” Studies in Business Economics, No. 89, National Industrial Conference Board, New York, 1965.
2. Craig, C.E., and C.R. Harris, “Productivity Concepts and Measurement- A Management Viewpoint,”Unpublished Master’s thesis, M.I.T., Cambridge, Massachusetts, 1972.
3. Craig, C.E., and C.R. Harris,“Total Productivity measurement at the firm level,” Sloan Management Review, Vol 14, No. 3, 1973, pp. 13-29.
4. Ruch, W.A., “Your Key to Planning Profits”, The Productivity Brief 6, Oct.1981, by American Productivity Cente,r Houston. TX-77024.
5. Sumanth, David J., Productivity Engineering and Management, McGraw Hill Book Company, 1984.
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Productivity Measurement - Additional Bibliography
Annual Review of Economics
Vol. 11:591-614 (Volume publication date August 2019)
First published as a Review in Advance on May 17, 2019
https://doi.org/10.1146/annurev-economics-080218-030439
Daniel E. Sichel
Department of Economics, Wellesley College, Wellesley, Massachusetts 02481, USA,
National Bureau of Economic Research, Cambridge, Massachusetts 02138, USA
https://www.annualreviews.org/doi/abs/10.1146/annurev-economics-080218-030439?journalCode=economics
Productivity measurement in an age of multinational companies and new technologies
Finn Schuele and David Wessel, November 19, 2018
Govind SinghRawat, Ashutosh Gupta, Chandan Juneja
Materials Today: Proceedings
Volume 5, Issue 1, Part 1, 2018, Pages 1483-1489
https://www.sciencedirect.com/science/article/pii/S2214785317325051
https://www.oecd-ilibrary.org/economics/productivity-measurement-with-natural-capital-and-bad-outputs_5jz0wh5t0ztd-en
OECD: Measuring Productivity – OECD Manual
11 Sep 2017
https://www.un.org/development/desa/capacity-development/tools/tool/oecd-measuring-productivity-oecd-manual/
This Manual presents the theoretical foundations to productivity measurement, and discusses implementation and measurement issues. The text is accompanied by empirical examples from OECD countries and by numerical examples to enhance its readability. The Manual also offers a brief discussion of the interpretation and use of productivity measures.
What is productivity, and how do you measure it?
https://www.weforum.org/agenda/2016/07/what-is-productivity-and-how-do-you-measure-it/
Thomas R. Gulledge, C.A. Knox Lovell
Springer Science & Business Media, Nov 11, 2013 - 200 pages
International Applications of Productivity and Efficiency Analysis features a complete range of techniques utilized in frontier analysis, including extensions of existing techniques and the development of new techniques. Another feature is that most of the contributions use panel data in a variety of approaches. Finally, the range of empirical applications is at least as great as the range of techniques, and many of the applications are of considerable policy relevance.
https://books.google.co.in/books?id=VaW-BwAAQBAJAli Dogramaci, Nabil R. Adam
Springer Science & Business Media, Dec 6, 2012 - 246 pages
A. Dogramaci and N.R. Adam Productivity of a firm is influenced both by economic forces which act at the macro level and impose themselves on the individual firm as well as internal factors that result from decisions and processes which take place within the boundaries of the firm. Efforts towards increasing the productivity level of firms need to be based on a sound understanding of how the above processes take place. Our objective in this volume is to present some of the recent research work in this field. The volume consists of three parts. In part I, two macro issues are addressed (taxation and inflation) and their relation to productivity is analyzed. The second part of the volume focuses on methods for productivity analysis within the firm. Finally, the third part of the book deals with two additional productivity analysis techniques and their applications to public utilities. The objective of the volume is not to present a unified point of view, but rather to cover a sample of different methodologies and perspectives through original, scholarly papers.
https://books.google.co.in/books?id=f_nxCAAAQBAJ(Chapter 8 is an interesting paper with propositions on technical efficiency of technology in electric utility companies)
Volume 24, Issue 10, 2006
Construction equipment productivity estimation using artificial neural network model
Seung C. Oka & Sunil K. Sinhaa*
pages 1029-1044
http://www.tandfonline.com/doi/abs/10.1080/01446190600851033?journalCode=rcme20
An Introduction to Efficiency and Productivity Analysis
Tim Coelli
Springer Science & Business Media, Jul 22, 2005 - 349 pages
The second edition of this book has been written for the same audience as the first edition. It is designed to be a "first port of call" for people wishing to study efficiency and productivity analysis. The book provides an accessible introduction to the four principal methods involved: econometric estimation of average response models; index numbers; data envelopment analysis (DEA); and stochastic firontier analysis (SFA). For each method, we provide a detailed introduction to the basic concepts, give some simple numerical examples, discuss some of the more important extensions to the basic methods, and provide references for further reading. In addition, we provide a number of detailed empirical applications using real-world data. The book can be used as a textbook or as a reference text. As a textbook, it probably contains too much material to cover in a single semester, so most instructors will want to design a course around a subset of chapters. For example, Chapter 2 is devoted to a review of production economics and could probably be skipped in a course for graduate economics majors. However, it should prove useful to undergraduate students and those doing a major in another field, such as business management or health studies.
https://books.google.co.in/books?id=NMYB0Mh8ljcCUpdated 25 Jan 2022, 1 Oct 2020. 13 April 2020, 1 November 2019, 20 Nov 2016, 12 June 2016, 19 June 2015
First published on 10 Feb 2012
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It is knol 10.
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