Identifying productivityblemishes in Pakistan automotive

industry: a case studySheikh Zahoor Sarwar, Azam Ishaque, Nadeem Ehsan and

Danial Saeed PirzadaEngineering Management, Center for Advanced Studies in Engineering,

Islamabad, Pakistan, and

Zafar Moeen NasirBusiness Studies, Pakistan Institute of Development Economics, Islamabad,

Pakistan

Abstract

Purpose – The purpose of this research is to identify the prevalent condition of productivity in theautomotive manufacturing industry of Pakistan and to indicate the possible areas for enhancingproductivity.

Design/methodology/approach – Secondary data for the last ten years were gathered. Totalproductivity and all partial productivities were computed using methodology proposed by Sumanth,and total factor productivity (TFP) was computed using Cobb-Douglas production function.Regression analysis and Pearson correlations were run to determine labor elasticity and capitalelasticity.

Findings – Results indicated very low levels of labor productivity and capital productivity, resultingin huge losses and stagnant growth of these firms. Increasing returns to scales (IRTS) with high valuesof labor elasticity and low and even negative value of capital elasticity were computed. Low values ofTFP showed minimal utilization of technology in these firms.

Research limitations/implications – One of the limitations of this research is that only twoautomotive manufacturing companies of Pakistan i.e. Honda Atlas and Indus Motors were targeted,which limits the generalizability of findings.

Practical implications – Findings of this research revealed that effective utilization of technologycan enhance the productivity of Pakistani manufacturing firms significantly. IRTS with high values oflabor elasticity and low value of capital elasticity depict the areas of productivity enhancement.

Originality/value – In Pakistan not enough effort has been put into measuring the productivity ofmanufacturing industry. The contribution of this paper is that it indicates the productivity blemishesin this industry and also the areas of focus for productivity enhancement.

Keywords Productivity analysis, Productivity rate, Automotive industry, Manufacturing,Productivity enhancement, Pakistan

Paper type Research paper

1. IntroductionGlobalization is a phenomenon, which has changed many concepts of competitiveness.With the expansion of businesses and the vastness of the global economy,geographical boundaries are no more a limit. The complete world has become acommon market, anyone from anywhere, can potentially enter the field of competition.With this changing scenario, methodologies used for measuring productivity, and even

The current issue and full text archive of this journal is available at

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Received February 2011Revised August 2011

Accepted August 2011

International Journal of Productivityand Performance Management

Vol. 61 No. 2, 2012pp. 173-193

q Emerald Group Publishing Limited1741-0401

DOI 10.1108/17410401211194671

defining productivity, need more thorough research and study. In the past few decadesmany research studies have been carried out on productivity (Sumanth, 1994; Kumar,2006; Azadeh, 2000; Azadeh and Ebrahimipour, 2002, 2004; Hunnula, 2002;Mahadevan, 2002; Park, 2003; Hossler et al., 2006; Wang and Szirmai, 2008), butunfortunately in Pakistan insufficient efforts have been put in to describe and measurethe productivity of manufacturing industry (Sarwar et al., 2010).

The difficulties faced in defining productivity are several, different objectives ofdifferent situations being the main issue. The objectives of firms and nation aremultidimensional and not necessarily coincident. The objectives of a nation are toimprove the living standards of the citizens, increase employment and create morejobs. While the main objectives of a firm are to win market shares both domesticallyand internationally, enhance profits, and compete globally. Basic methodologies tomeasure productivity are not in use; rather nonstandard tools are being used inindustry to measure and evaluate productivity (Sumanth, 1994). A key basic reason isthat knowledge about the concept of productivity is largely misunderstood. Adrawback of non-standard tools is that time factor is not considered in thesemethodologies. Whereas time factor is very important in defining when aprofit-earning activity will achieve its desired output or when a government policywill render its effectiveness in terms of the citizen’s and the nation’s benefit.

In this paper the importance of productivity in present times, its impact on our livesand drawbacks have been discussed and highlighted. This research aims at identifyingthe prevalent condition of productivity in the automotive industry of Pakistan byfocusing on measurement of productivity in the two largest automotive manufacturingcompanies of Pakistan. This research indicates the major productivity flaws of theautomotive industry of Pakistan by pointing out the resources which are not beingutilized to their optimum. For parsimony this research focuses upon identification offlaws on certain parameters and variables which are defined in the succeedingparagraphs.

2. Literature reviewThe expansion of world trade, the globalization of economies, and the emergence ofnew markets has made productivity a critical success factor for any country in theworld. Anticipating these developments, most countries have formulated strategiesand policies to ensure that their local businesses have the capability to compete in theglobal market. Problems faced in developing countries are not only the results ofunderdevelopment but rather of mis-management (Tadaro and Smith, 2008).Numerous studies have been conducted to find out the relationship of job behaviorsof employees with employee commitment, turnover, absenteeism, productivity andoccupational stress (De Nobile, 2003; Luthans, 2002; Singh and Billingsley, 1996;McCormick and Solman, 1992). Productivity has been identified as the most seriouschallenge confronting management.

With the changing situation, methodologies used for measuring productivity andeven defining productivity needs more thorough research and study (Sumanth, 1994,Kumar, 2006). In the past few decades many research studies have been carried out onproductivity all over the world (Sumanth, 1994; Kumar, 2006; Hossler et al., 2006; Wangand Szirmai, 2008). The word “productivity” most probably was used first by Quesnayin 1766, i.e. about 200 years ago (Sumanth, 1994). Since then, different definitions of the

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term have been suggested. Productivity and production are terminologies, which havebeen misused and misunderstood by many people for long. Sumanth (1994)differentiated between these terminologies and explained that production is concernedwith the activity of producing goods and/or services, whereas, productivity isconcerned with efficient utilization of resources (inputs) in producing goods and/orservices (output). Authors have further distinguished between concepts such as partialproductivity, total-factor productivity (TFP), total productivity and total productivitymodel (TPM). Despite clear theoretical demarcation, practical implementation of theseterminologies in industrial applications remains a gray area.

Productivity analyses of industries and organizations have picked up pace all over theworld. The main objectives of these studies have been to indicate the flaws and suggestremedial measures. Tripathy (2006) carried out a detailed analysis of manufacturingindustries in India. The researchers indicated the efficiency gap between foreign anddomestic firms in eleven manufacturing industries. Hossler et al. (2006) indicated theeffectiveness of model techniques for significant productivity enhancement. Researchersstudied the necessity of model-to-model transformations and successfully implementedthe same showing momentous productivity enhancement. Wang and Szirmai (2008)carried out a comprehensive study on the Chinese manufacturing industry. They studiedthe productivity growth of this sector from 1980 to 2002. The study deliberated upon thestructural changes in this sector and the effects of productivity growth.

Productivity and performance are terms often confused and incorrectly usedinterchangeably along with the terms of efficiency, effectiveness and profitability(Tangen, 2005; Kumar, 2006; Linna and Pekkola, 2010). Many researchers (Sumanth,1994; Jackson and Petersson, 1999) believed that by referring to productivity, peopleactually are working on performance improvement. A similar myth prevailedregarding productivity and profitability that they go hand in hand, so mostorganizations concentrated on profitability and performance in financial terms ratherthan concentrating on productivity enhancement techniques. Many researchers(Tangen, 2002; Grunberg, 2004; Linna and Pekkola, 2010) indicated this myth andelaborated that these three terms must not be taken as similar. Tangen (2005)developed a triple-P model explaining the differences of productivity, profitability andperformance as being physical phenomenon, monetary relationship and an umbrellaterm, for both the first two, with an aim of easy understanding, more accuratemeasurement and enhancement support. After this demarcation, a much research hasbeen carried out across the globe to develop improvement methodologies specificallyfor productivity enhancement (Saad and Patel, 2006; Thomas et al., 2008; Miguel andAndrietta, 2009; Linna and Pekkola, 2010).

The active role played by the governments in Southeast Asia to promote industrialgrowth, both in manufacturing and services sectors, runs contradictory to westerntheories (Zutshi and Gibbons, 1998). The authors argued that government participation,polices and decisions have been the backbone for industrial growth and achievingcompetitiveness in the region. This research reviewed two government-linked companies(GLCs) in Singapore outlining their internationalization process from a contextualperspective. Mahadevan (2002) explained the two different views on governmentinvolvement and public sector role in services and manufacturing: the “Washingtonconsensus” deliberating that excessive and unfair competition from public sector resultsin cutting down the progress of the private sector. Second, the “Developmental state

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view” argues that there is a dire need for government to intervene and for the publicsector to actively participate in economic growth in developing countries. The authorgave the examples of Korea and Singapore, emphasizing that in Asia the active role ofthe public sector is a must to achieve desired developments. Dependence on public sectorindustry, specifically the defense industry, is a must for under-developed countries dueto political and strategic factors (Amara, 2008). The author expressed that arms embargoon these countries has been another major factor for development and enhancement ofthe public sector. The research evaluates the establishment of a defense industry inJordan while also examining the same in Brazil, South Africa, South Korea and Taiwan;pointing out the positive effects they had on their countries’ economy.

The economic growth of a nation depends upon its major industries. For example,the automotive industry throughout the world has flourished enormously. Productivityanalyses of this industry show that they have added substantially to the GDP ofvarious countries. In the recent past the automotive industry in many countries hasbeen recognized to be a major contributor of growth, technology, employment and GDP(Gottschalk and Kalmbach, 2007). In today’s globally competitive world theautomotive industry has to face enormous challenges like hyper-competition, latestand advanced production technologies, strict safety requirements, and enhancedenvironment protection laws (Gallasch et al., 2004). Due to the importance of the roleplayed by this industry in the economic growth and development of a country muchresearch has been conducted in different countries. For example, Hitt et al. (2003)examined the Honda Motor Company and reported that by adoption of flexibleproduction systems in small car and small volume operations Honda Motors reducedits production costs by 30 percent. Research on BMW and Mercedes-Benz cars byMacMillan and Mcgrath (1997) revealed that the companies have the edge in superiorengineering, elevated stature and excellent quality. Studies have been carried out onthe effects of task rotation and working methods on enhancement of soft issues likemotivation and job satisfaction in automotive setups in Malaysia (Dawal et al., 2009).Research on Lexus, a division of Toyota Motor Co Ltd, has been conducted byMarkides (1999) that identifies the need for integration in the value chain. Hill andJones (2004) elaborated several different strategies adopted by automobilemanufacturers for customer satisfaction. Authors identify examples of GM’s midsizeCadillac, and Ford’s mid-sized products. Authors have also highlighted that Toyota,Ford, Daimler-Chrysler, and Mercedes Benz have employed strategies like integratedcost-leadership and differentiation to attain competitive advantage.

Pakistan came into the race of productivity enhancement a bit later than others; forexample recently the long-awaited Productivity Association of Pakistan was launched on25 April 2009, in Islamabad. The automotive industry of Pakistan has shown someimprovements, mainly due to enhanced capital inputs, but still its contribution to the GDPand employment is of modest size. In particular, once comparison is made with otherAsian countries like Japan, Korea, Malaysia, China and Thailand a remarkable differencecan be observed. In these countries the automotive industry has exploited the catalyticrole in promoting broad-based manufacturing sector growth (Asian Development Bank,2008). In Pakistan, not much research has been carried out on the operational proceduresand productivity enhancement possibilities of the automotive industry.

Changing government policies in Pakistan have resulted in slow economic growth.In the beginning, mainly the private sector was relied upon for manufacturing and

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services, but then policies shifted towards nationalization in early 1970s. In late 1980sand 1990s, once it was realized that public sector organizations were not performing asper the desired expectations, the declining private sector was given relief throughsympathetic polices. The Privatization Act 2000 was the first milestone achieved thatgave a remarkable boost to the private industry (Asian Development Bank, 2008). Thisact gave private sector a big boost and Pakistan’s output rose to 13 percent in2005-2006 from 5.67 percent in 1959-60 (Ministry of Finance, 2006-2007). The FederalBureau of Statistics Pakistan (2006) conducted a survey and found that manufacturingindustry of Pakistan contributes 19 percent of the GDP. In the latest survey conductedin 2010 (Federal Bureau of Statistics Pakistan, 2010), it states that manufacturingindustry is presently contributing 18.5 percent to GDP. To improve productivity onehas to pay attention to a fast-changing world and improve the organization’s capacityto adjust to change. It is necessary to recognize the importance of all major factors,which contribute to or detract from productivity growth. An important aspect to realizeis that quality without productivity is of no use. This research seeks to measure andevaluate the productivity of leading automotive manufacturing companies of Pakistan,while highlighting the flaws in the existing systems.

3. Research methodology3.1 Data collectionThe automotive manufacturing industry of Pakistan prospered in the 1980s and 1990sdue to the inflow of foreign direct investment (FDI). World-renowned automotivemanufacturing companies like Honda, Toyota and Suzuki launched theirmanufacturing plants in the country. After 2000 this industry flourished due to thefavorable polices of the Pakistan Government. At present, there are 21 automotivemanufacturing companies in Pakistan, but of these only four are car manufacturers.Out of these four companies two major market-share holding companies were selectedfor this research. These are Indus Motors (whose principal is Toyota Motors) andHonda Atlas (principal is Honda Motors). A detailed productivity analysis of thesecompanies was carried out over a span of ten years, i.e. 2000 to 2010.

To measure productivity the most important aspect is to collect a reliable, valid anddetailed data set that includes all aspects required. It was intended to measure TotalProductivity as proposed by Sumanth (1994), all partial productivities and Total FactorProductivity (TFP) using Cobb-Douglas production function. Data were required of thenumber of employees, wages of these employees, total man-hours consumed, fixedcapital input, working capital input, cost of materials used, cost of energy utilized, costof all other expenses including taxes, traveling expenses, and all other overheads. Theoutputs both in quantity and in value terms were also required. Meeting all thesedetails required secondary data from the organizations. Generally, asking companiesabout their capital investment including fixed and working capital, employmentdetails including wage rates, materials cost, energy expenses and other overheads is asensitive issue; especially in a country like Pakistan where a research culture is still inits development stages. Inquiries like these offend people at times. Similar problemswere faced with other data collection for this research. Failure to directly collectcomplete data from companies and consideration of these problems, led to resorting toan internet search. Two associations were found namely; Pakistan AutomotiveManufacturers Association (PAMA) and Pakistan Association of Automotive Parts

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and Accessories Manufacturers of Pakistan (PAAPAM). These associations maintaindetailed data of the Pakistan automotive industry. Much information and data weregathered from these associations. However, the data were incomplete forcomprehensive productivity measurements. Secondly, Government organizationswere consulted for data collection where all organizations render their organizationaldetails. These organizations include Ministry of Industries and Production of Pakistan(MOIP), Engineering Development Board of Pakistan (EDB), Securities and ExchangeCommission of Pakistan (SECP) and Federal Bureau of Statistics, Pakistan. Someimportant information was retrieved but unfortunately it was found that available datawere incomplete. Another major problem with the available data was that it was notgathered for measurement of productivity rather it was more suitable for financialissues only. The biggest problem in Pakistan was the lack of awareness of basicconcepts of productivity. The research also revealed that there is hardly anymanufacturing company in Pakistan, which has a productivity department or anyemployee/manager specifically looking after the productivity issues. Hence, noinfrastructure for formal and regular productivity measurement, evaluation, planningand enhancement exists in the automotive manufacturing industry of Pakistan. Thisaspect made accurate data collection for productivity analysis a tedious job.

Another source explored was audit reports of these two companies. Audit reportswere selected because they are one of the most reliable and valid sources of data of anycompany. The data extracted from these reports filled a huge gap in compiling theproductivity analysis of the automotive industry. However, two key drawbacks of thisdata were observed. First, available data on these reports was compiled with a view topresent financial status of the companies and not for measuring productivity. Second, inthese reports sales of products were the main aspect of emphasis; whereas, forproductivity analysis data such as quantity produced were required. In order to retrieverequired data from the productivity point of view, several calculations were made.Output values of the products were taken from the firms and ex-factory prices wereconsidered. For fixed capital, the book value of property, plant and equipment was takenfrom the annual reports of the firm as they are the most valid and authenticated data.

Data were gathered in financial year’s terms. Another problem faced was that allgovernment organization and Indus Motors use June to May as financial year whereas,Honda Atlas has financial year of March to February. So, several adjustments were tobe made to bring all data to a similar time frame.

3.2 Data analysisTo understand the productivity status of these two automotive manufacturing firmsthe overall production status of the complete automotive manufacturing industry ofPakistan was analyzed over a span of six years i.e. 2005 to 2010. These data weregathered through PAMA and PAAPAM associations. Then productivity analyses ofthese two firms were carried out as per the data gathered as explained in previoussection. The detailed data of these companies were compiled into Excel sheets. Todeflate all the values to a base year, i.e. 2000, a GDP deflator was used. The problemwith using CPI was that it requires details of all materials and other inputs used whichwere not available. As only the monetary values of these inputs were available so aGDP deflator was used. For computing value-added output double deflation wascarried out. Partial productivity measurement tools as suggested by previous study

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(Sumanth, 1994; Hunnula, 2002; Kumar, 2006) were utilized to measure the productivitystatus of these automotive manufacturing companies of Pakistan:

Partial productivity of one class of input ¼Gross output

Input value of one class of inputð1Þ

Separate columns were constructed for all partial productivity measures, i.e. laborproductivity, material productivity and capital productivity. Formulae of thesemeasures were entered into these columns for ease of calculation. Different graphswere plotted for graphical representation of the analysis.

For calculating total productivity of these firms the formula as suggested bySumanth (1994) was utilized:

Total productivity ¼Gross output

IL þ IM þ IF;C þ IW ;C þ IE þ IXð2Þ

However, only the operational total productivity was calculated in which:

Output ¼ value of finished units produced þ value of partial units produced

For all further references in the paper Total productivity will mean operational totalproductivity. IL is labor input wages in value terms, IF.C is fix capital input, IW.C isworking capital input, IM is materials input in value terms, IE is energy consumed andIX is all other expenses of the firm including taxes, traveling charges and all otheroverheads. Total Productivity (only operational total productivity) of the firms wascalculated and productivity indices for ten years were computed. Graphs were drawnfor pictorial representation of the data.

To calculate TFP Cobb and Douglas (1928) production function was used as it is themost widely used method in economics:

Q ¼ ALaK b ð3Þ

Where Q is gross output in value terms, K is fixed capital, L is labor man-hours utilized(another variance using number of employees was also used), a and b are elasticity,respectively for L and K and A is role of technology.

Another variance of this function was also utilized:

Y ¼ ALaK b ð4Þ

Where Y is value added output i.e. gross output minus the intermediate goods andservices utilized. Rest all variables remaining similar.

These equations were transformed into a log equation so that regression would berun on them. So the equation 3 and 4 became:

LnðQÞ ¼ ln A þ a ln L þ b ln K ð5Þ

LnðYÞ ¼ ln A þ a ln L þ b ln K ð6Þ

Simple and multiple regressions were run on these equations in SPSS version 17 todetermine the elasticity of both labor (L) and capital (K). The value of ln A wastransformed into a numeric term by using exponential factor. In mathematics

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exponential function is often used to model relationship between dependent andindependent variable. Basically the inverse function is the natural logarithm because ofthis it is also written as anti-logarithm. This is the main reason for using it here tocompute the value of Ln A:

Ln A ¼ 2x ¼ e2x ¼ z

4. ResultsTo understand the present-day status of these companies in the context of the entireindustry, first the production status of the complete automotive industry was analyzed.Figure 1 shows the production trend line of the industry over a span of five years,i.e. FY 2005-2010. It shows that production levels suffered a drop in FY 2007-2008 andFY 2008-2009 was the worst year for the whole automotive industry of Pakistan. FY2009-2010 however showed an improvement from the declining trend. This trend lineof the industry was an important factor in analyzing the productivity status of the twoautomotive manufacturing firms under study.

To understand the business status of these two firms, profit and loss statements ofthese firms were analyzed. Figure 2 shows the profit and loss (PLS) status of bothIndus Motors and Honda Atlas from FY 2000-2010. It shows that both firms were atapproximately similar profits level in the base year. In FY 2001-2002 Honda Atlas tookthe lead. But in FY 2002-2003 Indus Motors enhanced its profits by four times. Sincethen it continued to increase its profits except for FY 2007-2008 and FY 2008-2009where profits declined; which parallels the overall situation for the Industry. Thepoorer performance in these two years can be attributed to the overall political andeconomical instability in the country. Indus Motors however showed remarkableprofits in FY 2009-2010. Honda Atlas on the other hand could never catch up withIndus Motors since FY 2002-2003; rather it showed reduced profits in 2004-2005 andthen in FY 2006-2007 the firm showed a huge loss. In FY 2007-2008 it recovered fromloss but again in 2008-2009 it showed a loss and especially in FY 2009-2010 the firmshowed a loss of 8.5 22 billion rupees – the biggest loss by any automotivemanufacturing company in Pakistan. The trend shown by Honda was totally different

Figure 1.Showing production trendline of Pakistanautomotive industry fortotal production ofcommercial and privatevehicles

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from rest of the industry and warranted further investigation and probing to identifythe reasons for this state.

Figure 3 shows the trend line for total production volume depicting a similar pictureas has been elaborated in the P&L graph. To further augment the findings capacityverses output graphs of both firms were plotted and are shown in Figure 4. Thesegraphs depict that Indus Motors had been producing nearly at the optimum level ofcapacity since FY 2002-2003 except for FY 2008-2009, which is in line with the trend ofthe industry. Honda Atlas on the other hand was producing more than its capacity tillFY 2005-2006. A point of detail here is that Honda shows its capacity on a single-shiftbasis whereas Indus shows capacity on a double-shift basis. Again these graphsshowed that something drastically went wrong in FY 2006-2007 and since then theperformance of Honda Atlas has been deteriorating. Another interesting point is that inFY 2006-2007 and after the production levels of the company kept on decreasing butcapacity level was enhanced to a maximum level of 50,000 units, which is notunderstandable. Why capacity is being enhanced for a manufacturing plant, which isloss-making and is not able to produce even 50 per cent of the previously availablecapacity. To carry out the detailed investigation of the reasons for these puzzlingtrends; productivity analyses of both firms were necessary.

For this analysis first the partial productivities of both firms were computed usingequation 1. Figure 5a shows the labor productivities of both Indus Motors and HondaAtlas over a span of ten years, i.e. FY 2000-2010. The labor productivity graph for both

Figure 2.Profit and loss status of

Indus Motors and HondaAtlas

Figure 3.Line graph showing

production trend line ofIndus and Honda Motors

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the firms showed a remarkable resemblance to the output graphs of the firms showingpresence of strong correlation between the two. The labor productivity of Honda Atlaskept on growing but in FY 2006-2007 had a big dip identical to the dips in productionoutputs and loss. It can be inferred from these graphs that inefficient utilization oflabor caused these slumps in the performance of the firm. Material productivities of thefirms are shown in Figure 5b. This graph depicts that material productivity of both thefirms kept on growing without any significant drop. So it can be inferred that no

Figure 4.

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Figure 5.Partial productivities ofHonda Atlas and Indus

Motors

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problem of inefficient utilization of materials prevailed in both the firms. However, thegraph also portrays that Indus Motors had a big jump in FY 2009-2010 in materialproductivity showing better and more efficient utilization of materials in this financialyear. This can be a big contributor to the enlarged outputs and profits of Indus Motorsin the same fiscal year. Capital productivity graphs of both firms are shown inFigure 5c. This graph explains probably the most logical and relevant reason for thepoor performance of Honda Atlas since FY 2006-2007 and onwards. Poor capitalutilization, as can be seen here, looks like the prime cause for the drop in the profits andoutputs of the firm from this year onwards. The huge capital invested in 2006 shouldhave given more profits but instead its poor utilization resulted in very low capitalproductivity. The huge losses shown by the firm most probably were the result of thisaspect, which needed to be explored.

Total operational productivities and total productivity indices of the firms were alsocomputed over a similar span of ten years. Figure 6 shows total productivities of thefirms and Figure 7 shows total productivity indices of the firms. Comparison of the twofirms give similar results as in previous graphs, a sudden drop of productivity of

Figure 6.Total productivities ofHonda Atlas and IndusMotors

Figure 7.Total productivitiesindices of Honda Atlasand Indus Motors

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Honda Atlas from FY 2006-2007 and onwards. However another important aspect to berecognized here is that productivity analyses of firms in different countries (Ito, 2004)have shown that automotive firms grow from a low productivity levels to highproductivity levels of even 5 and above over a span of five to six years. But in Pakistaneven a flourishing firm like Indus Motors has shown a limited increase of productivityfrom 0.97 to a maximum of 1.88 over a span of ten years time.

To confirm the existence of relationships between profit of the firm, output produced,total productivity, partial productivities Pearson’s product moment correlations were runin SPSS version 17. The results are presented in Tables I and II. In the top matrix resultsare presented for Honda Atlas and in the bottom matrix results are presented for IndusMotors. For Honda Atlas profits of the firm were moderately (g ¼ 0:49 to 0.61) correlatedto all partial productivities and total productivity of the firm with statistically significantresults ( p , 0.05 and p , 0.1). Total productivity was found to be strongly correlated(g 0:781; p , 0.01) with capital productivity and strongly correlated (g 0.813; p , 0.01)with labor productivity at statistically significant levels. Labor productivity was foundto be strongly correlated (g 0.80; p , 0:01) with output and moderately correlated (g 0.5;p , 0.1) with number of employees. Employee number was found to be stronglycorrelated (g 0.887; p , 0.01) with output of the firm. For Indus Motors profits of the firmwere moderately (g ¼ 0:549) to strongly (0.8561) correlated with partial productivities ofthe firm with statistically significant results ( p , 0.01 to p , 0.1). Profits were found outto be strongly correlated (g 0.80; p , 0.01) with total productivity. Total productivitywas found to be strongly correlated (g 0.983; p , 0.01) with material productivity andstrongly correlated (g 0.891; p , 0.01) with labor productivity at statistically significantlevels. Labor productivity was found to be strongly correlated (g 0.879; p , 0:01) withoutput and strongly correlated (g 0.744; p , 0.1) with number of employees. Employeenumber was found to be strongly correlated (g 0.946; p , 0.01) with output of the firm.Output of the firm were found to be strongly correlated (g 0:899; p , 0.01) with totalproductivity of the firm.

To further investigate the problems of low productivity, especially in Honda Atlas,regression analyses were run in SPSS version 17. For regression tests Cobb-Douglasproduction function dully transformed in log equations were computed as per equation5 and 6. Descriptive statistics are presented in Table III. Unstandardized coefficients ofregression tests are shown in Table IV. Unstandardized coefficients of the regressiontests showed significant values (b ¼ 27.26036, p , 0.05), for Ln man hours(b ¼ 1.707, p , 0.01) and marginally acceptable significant values for Ln Capital(b ¼ 20.137, p , 0.1). Relationship showed a high value of R (0.979) and highcoefficient of determination (R 2 ¼ 0.958; p , 0.01). Adjusted R 2 showed a value of0.946 but there was no significant change in R 2.

The regression equations of log function and Cobb-Douglas production function forvalue added computed for Honda Atlas are:

ln ðY Þ ¼ 27:263 2 0:137 ln ðKÞ þ 1:707 ln ðLÞ

A ¼ e27:263 ¼ 0:0007

TFPðYÞ ¼ 0:0007L 1:71K 20:13

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Table I.Pearson’s productmoment correlation forHonda Atlas and IndusMotors

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Table II.Pearson’s product

moment correlation forHonda Atlas and Indus

Motors

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The regression equations of log function and Cobb-Douglas production function forgross output computed for Honda Atlas are

ln ðQÞ ¼ 2 3:331 2 0:234 ln ðKÞ þ 1:606 ln ðLÞ

A ¼ e23:331 ¼ 0:036

TFPðQÞ ¼ 0:036L 1:606K 20:234

For both methods very low values of the role of technology (0.036 and 0.0007) wereattained, showing much room for improvement for technology introduction. Low andnegative elasticity’s for capital K showed over injection of capital. Whereas increasingreturns to scale resulted as a whole, giving values of (1.606 and 1.707) for labordepicted high volumes of returns by marginal increment of labor.

5. DiscussionIn Pakistan automotive manufacturing industry quality is given due importance butthe concept of productivity is a most neglected aspect. The biggest evidence for this isthat there is not even one automotive firm in Pakistan, which has a formal productivitymeasurement, evaluation, planning and productivity enhancement program. There areno productivity departments in these firms neither any manpower is hired for this mostimportant activity of performance enhancement. Continuous productivitymeasurement programs are the key tools, which indicate which input resource isinefficiently and ineffectively utilized. On the basis of these programs’ findings, firmsdecide how to enhance their profits and overall performance. In Pakistan automotivefirms these aspects are absent.

This research has been conducted with the view to indicate how productivitymeasurements can indicate flaws in the manufacturing process. The productivityanalyses of two major market-share holders of the Pakistan automotive manufacturingindustry have depicted several areas where low productivity levels are evident.Specifically, the productivity analysis of Honda Atlas has shown that inefficient

Mean Std. deviation n

Ln value added out put 15.0658 0.59355 10Ln manhours 14.1842 0.38529 10Ln capital 13.7191 0.89002 10

Table III.Descriptive statistics

Unstandardized coefficientsModel B Std. error

1 (Constant) 27.263 1.805Ln Manhours 1.707 0.164Ln Capital 20.137 0.071

Notes: Dependent variable: Ln value added out put

Table IV.Unstandardizedcoefficients of regression

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utilization of labor and capital has resulted in huge losses. The major reason for thelosses of this firm can be attributed to the low level of capital productivity. Thisargument is further augmented by the occurrence in 2005-2006 that this firm injected ahuge capital sum of 16.478 Bn rupees, which was further enhance by 19.488 Bn rupeesin 2006-2007. So in just two years Honda Atlas injected a huge sum of 35.967 Bn rupeesin their manufacturing plants. From the correlation matrix it is evident that there is astrong positive correlation between capital investment and profit. So it is logical tobelieve that enhanced capital investment must result in enhanced overall productivityand also TFP, but it was not the case with this firm. This scenario has to be consideredin conjunction with another important aspect that in 2006 Honda Atlas launched a newproduct, the Honda Reborn. This expensive product replaced the previous very famousand high sales product, the Honda Civic. The high price product could not attract manycustomers, so this might have been the reason for the big drop in sales. Honda Atlasinvested huge capital for production of this product. It can be easily assumed on thebasis of results that this product introduction is one of the reasons for poorperformance of this firm. To further clarify the phenomenon a product-wiseproductivity analysis can be carried out as a future research, which will give moredefinitive results. Another important finding of this study is that all partialproductivities and total productivity are directly and positively related with profits andoutputs of the firms. So by continuously measuring productivities and enhancingproductivities of the firms we can enhance the overall performance and profits of theindustry, thus making greater contribution to the GDP of Pakistan.

The results of Cobb-Douglas production function and TFP calculated by thismethodology have clearly indicated increasing returns to scales (IRTS), whichaugment the new growth theories of the economy (Tadaro and Smith, 2008). Thenegative elasticity of capital for Honda Atlas and low value of elasticity of capital forIndus Motors have shown that in these manufacturing firms capital investment,especially in plant, machinery and land, is a burden. The low values of the role oftechnology for both the firms have indicated a very important aspect and that there is ahuge opportunity of investment in latest technologies instead of investing in newmachinery and plant that uses older technology. Pakistan is a developing country witha labor-rich infrastructure. Economic development of this country can be achieved byinvesting in labor-augmenting technologies and capital-saving technologies. Thisaspect is further amplified by the high value of elasticity of labor that resulted from theCobb-Douglas production function. The IRTS values clearly indicate that by investingmore in labor, then more than double the outputs can be achieved.

Based on the conclusions of this study it is our recommendation that automotivemanufacturing companies of Pakistan must focus on investing in technology instead ofonly investing in land, buildings, and equipment. The role of technology has beenconsidered as one of the most crucial factors affecting productivity of an organization(Azadeh, 2000; Azadeh and Ebrahimipour, 2002, 2004). As per the Webster dictionarythe word technology is formed of two Greek words techno meaning “art, skill or craft”and – logia meaning “the study of something or the branch of knowledge of adiscipline”. Technology is mostly thought of as being consisting of latest gadgetry,computers and most modern machines. Sumanth (1994) indicated this misconceptionabout technology and elaborated that technology is defined as “any means toaccomplish an objective or task”. Sumanth discussed that there are four types of

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technologies, product technology, process technology, information technology andmanagerial technology.

Efficient and effective product designs, process optimizations, latest managerialtechnologies like zero inventory (ZI), just in time (JIT), flexible manufacturing system(FMS), optimized production technology (OPT), computer integrated manufacturing(CIM), activity-based costing (ABC), Quality function development (QFD), total qualitymanagement (TQM), total preventive maintenance (TPM), 5S, Kaizan, benchmarking,Toyota production system (TPS), theory of constraints (TOC), business processreengineering (BPR), lean manufacturing and Supply chain management are the keyswhich can enhance production, productivity and profits of these organizations.

Our second recommendation is that IRTS as calculated in this study and low capitalproductivity of both the firms as calculated show that Pakistan, because it is adeveloping country, must focus on labor-intensive technologies instead ofcapital-intensive technologies. Another important recommendation of this study isthat all automotive manufacturing companies must incorporate continuousproductivity measurement, productivity planning, productivity evaluation andproductivity enhancement programs. Productivity departments must be included intheir organizational charts and specialized productivity staff must be hired to staff thedepartments.

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Credit Research Foundation (2007), “Collection productivity analysis 2008”, available at: www.crfonline.org/surveys/prodsurvey/collectionproductivityresults.pdf

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About the authorsSheikh Zahoor Sarwar is a PhD Scholar at Center for Advanced Studies in Engineering,Islamabad, Pakistan. He is basically a mechanical engineer and undertaking a PhD inEngineering Management. His area of specialty is productivity analysis and working onproductivity enhancement techniques for manufacturing industry. Presently, he is working asGeneral Manager, Productions at Ravi Autos (Pvt) Ltd, Lahore, Pakistan. Sheikh Zahoor Sarwaris the corresponding author and can be contacted at: zahoorsarwar@yahoo.com orzahoor14mm@yahoo.com

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Azam Ishaque is a PhD Scholar at Center for Advanced Studies in Engineering, Islamabad,Pakistan. He is basically a computer engineer and is undertaking a PhD in EngineeringManagement. His area of research is industrial informatics.

Dr Nadeem Ehsan has a PhD in Construction Engineering Management from University ofMichigan, Ann Arbor, Michigan, USA. His areas of interest are knowledge management andproject management. Presently, he is working as Chairman in the Engineering ManagementDepartment, Center for Advanced Studies in Engineering, Islamabad, Pakistan.

Dr Danial Saeed Pirzada has a PhD in Mechanical Engineering from Washington StateUniversity, USA. His area of speciality is manufacturing technologies. Presently, he is teachingin Engineering Management Department, Center for Advanced Studies in Engineering,Islamabad, Pakistan.

Dr Zafar Moeen Nasir has a PhD in Economics from Kansas State University, Manhattan,USA. Presently, he is working as Chief of Research and Dean Business Studies in PakistanInstitute of Development Economics, Islamabad, Pakistan.

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