India, Science and Technology:  2008

S&T and Industry

 

 

 

Non-R&D Innovation in Indian Factory Enterprises

 

 

Bikramjit Sinha, Avinash Kshitij,

Yogesh Suman & Parthasarathi Banerjee

 

The system of organized business enterprise is amongst the important actors of the national innovation system. There are several types of ownership in this group from private to public, from public limited to privately held, from single proprietorship to cooperative ownership and more importantly this group has enterprises that are very widely distributed in terms of size of capital invested, number of employees or volume of turnover. The largest could be no less than several hundred times of the small. All these enterprises, however, are in the manufacturing sector. Given the wide variations in ownership, size, nature of competition in relevant business sector and such others there would be similar differences in the depth, extent and types of innovative activities. Quite naturally only few enterprises have departments or units or accounts dedicated to R&D. However, most units appear to be improving upon business performance. A simple but robust definition of innovation is what improves business performance. One must not forget that such a definition of innovation captures certain crucial aspects of innovation that does not necessarily depend upon an accounting head of R&D, and a few such aspects are: process innovation including improvements in productivity, employment of information both technical and business types, product innovations and innovations in services. This section deliberates upon the nature and extent of such non-R&D innovations happening in this large group of organized business units.

The economic system of this group of enterprises is very diverse allowing investigation into changes happening beyond an individual enterprise. Changes happening firstly, in a sector of economy and secondly, in the inter-sector overall economy of manufacturing are often not simple aggregates of changes in individual units. At the simplest level unit, agency of innovation leads to sector innovation and vice versa. However, sector level changes or inter sector changes are often stronger, forcing one individual enterprise to effect changes or else exit the business. It would therefore be worthwhile to examine the sector innovation landscape. Any sector innovation policy, however, is defined upon and targeted to the agency of unit enterprise. Moreover and in turn sector landscape forces inter-sector changes and vice versa. Economy wide innovation in manufacturing as reflected in inter-sector relations and the associated structural changes would be important indeed. Such an examination would go beyond interpretations based upon gains through improvement in the total factor productivity. In short, within the manufacturing group of relatively large enterprises (the smaller units have been considered in the previous section on the MSME) changes towards improved performances that could be described as innovative can be described at minimum three levels of (1) units, (2) sector and (3) inter sector.

 

Policy targets for innovation

Policy driven innovation can target units or sectors or inter sectors. By limiting agency of innovation to the unit enterprise level alone we are liable to lose much insight into both gains through and mechanisms of innovation. Agency of the unit enterprise, to recall, is most often actuated by the systemic policies including those affected in the capital market. Policies could therefore be designed for systemic changes, including changes in system governance. Gains through policies could similarly be measured at the system that is sector or inter sector levels. Further, innovation in one enterprise or at the sector level happens because of plethora of economic policies and therefore we need to look beyond policies relating to promotion of R&D alone.

Indian experience informs us that enterprises having undertaken R&D often experienced fall in market capitalization forcing many firms to ‘derisk’ by way of hiving off own R&D departments into separate business entities. Tax concessions on R&D expenses might incentivize enhanced reporting on R&D. Contrarily, non- R&D innovation (especially, process type) when happening at enterprise level might not get reported in accounting information. Such innovations, however, are crucial. This section will look more closely into non-R&D innovations, the latter might often have been undertaken in response to broader economic policies and economic signals.

 

Innovations at three levels

We should also note that these three level-types of innovations have dissimilar inputs and these happen under different ambient conditions. In fact inputs at both sector and inter sector levels are often macro in nature flowing out of public policies relating to tariffs, taxation, investment allowances, depreciation allowances and such others. Of special importance is the credit provided fillip to innovative activities. Roles of credit, equity and capital markets or more importantly, policies regarding competition including on IPR – lessons from comparative policies suggest, are of crucial importance to innovation.

Typically policies relating to non-R&D innovation during pre-liberalization phase addressed exemptions in customs duty, depreciation and investment allowance and weighted tax deduction for using or commercializing technologies developed in domestic entities. The post-liberalization phase extended to certain other benefits such as duty free imports, depreciation allowance for technologies developed in domestic entities. Further this latter phase also introduced benefits to venture funds by way of tax exemptions on gains from funding in select sectors such as biotechnology. Few more instruments including fund of funds or bank-operated instruments came into force during this latter phase. The SIDBI fund, the Technology Upgradation Fund for the textiles sector, for example, are such funds that hastened as in the latter case quick imports especially of advanced but often second hand machineries. Several ministries and departments initiated during this second phase funds under departmental management for the promotion of new start-ups including the incubation to commercialization. Department managed innovation fund is now fairly well spread although small in sizes and is primarily a post-liberalization policy initiative.

Innovation policy types:  In short the governance mechanism during the later phase embraced two modes – the executive based and executive monitored instruments of taxation and likes broadly under fiscal category, and the second mode of fund based or bank based and bank monitored fund. However, a few small departmental funds for start-ups remained under the management of the executive. Perhaps much overlooked but rather crucial aspect of pro-innovation policy on fund is the mode of transfer through the Finance Commissions. Equally underrated has been – the non-deployment of a small fraction restructuring fund or of funds dedicated to development for undertaking R&D or for promoting innovation or for creating markets for innovative products including of public procurement.  

Another related set of policies not directly targeted for innovation and R&D, provided vital lifelines to innovative activities. These set of policies could be described under broadening and deepening of market. Competition policy including on monopolies and restrictive trade practices, as especially lessons from recent European Union initiative indicate, constitute perhaps the most important aspect. Given the fact that much of R&D relates to corporate policies on barriers to entry and collusion, the competitive aspects of corporate non-R&D innovation assume larger significance especially for a country such as India facing both dumping and liberalized import. In this report the competition dimension will not be addressed, however. Other policies under market dimension, such as the Electricity Act providing for opening up selling of cogenerated power in a few states inducing in turn innovation in sugar mills or the recent Warehousing (Development & Regulation) Act 2007 opening up immense fillip to innovations in post-harvest and related areas by way of generating encashability of warehouse receipts or the opening up of commodities trading platforms including its link-up with spot deliveries – belong to non-fiscal often legal market development sets of pro-innovation instruments and institutions.

Both market related and bank related sets of policies appear to be more important for two robust reasons: (1) fiscal types of policies as experience shows could not often match expectations, and (2) fiscal related instruments might be more incumbent friendly hence less restructuring. A related but important issue is that a legal instrument frees governance structures and therefore helps generate non-executive modes of governance of innovation. Reading into comparative policies informs us that several countries have been using very effectively legal policy instruments of limited duration. Advantage of legal policies is that agency of innovation then shifts to institution. Further, capital market policies wield immense influence on innovative behavior although our current discussion will be limited to non capital market issues.

Policy and governance of innovative changes: A related and important aspect is who manages and monitors or governs the process of change. Often neglected but this important issue of governance has been found to be of crucial importance to the incubation and handholding of entrepreneurial startups in USA for example. Taking cues from the lessons of innovation in other countries we can classify the governance of innovation under three broad types: (a) executive based; (b) bank based; and (c) market based. Several countries have followed a mix of two types of policies. Issue of governance of the innovative transition assumes crucial importance when we talk about normative policies and normative intervention especially by public agencies. Most systemic policies force unit enterprises towards innovation and such directed innovations are normative. Indian policies in the pre-liberalization phase has been dominantly executive based while in the post liberalization phase we may observe minor influence of bank based policies although dominance of executive based has continued. The market based governance appears to have insignificant influence on innovation outcome.

Further, several units and in a few cases respective associations of enterprises have been having transactions with public R&D systems and the university systems. Public R&D laboratories provide knowledge and handhold building up of capabilities. Agency of funding or taxation is crucially different from the agency of the flow of knowledge. Systemic knowledge, the social flow of skill and the abundance of skill pools and similar other social capital are major actors in the system of innovation but different from the agency of the executive. Examination of changes could suggest that beyond policy driven agency, there could be social linkages between change agents and complex helix of social interrelations might as well actuate innovations while not governing the transition. Therefore we can add another type of governance to the above three types namely the fourth as the social knowledge pool based governance.

Innovation policy schematic:: We may for the convenience of description devise a simple schematic of policy types. The first tier might be described in terms of governance. We have four types there, namely, executive-, bank-, market-, and social-based. The second tier could be policies classified under fiscal-, fund-, infrastructure-, managerial-, legal-, and asset-based. Fiscal includes tax and similar; fund includes bank based and similar; infrastructure includes cluster, S&T parks or public R&D lab/training; managerial includes handholding, VC manager guided and similar; legal includes laws relating to company, patents, competition and similar; and asset includes an item with future exchange value such as a patent. There could be a third tier to indicate the target of the policy. This tier could have unit enterprise, sector, inter sector, and finally institution.

Nature of innovative changes:  Improvement in enterprise performance may happen in multiple manners such as cost containment or improvement in labor productivity or factor productivity, reductions in specific items such as in cost of fuel, cost of inventories, or reductions in cost of wages or emoluments, reductions in materials loss or intensity, and similar others. Such changes when effected in a few units of a sector forces through competitive pressures changes in most units of that sector. Imports too, bring about such changes. In the following sections we examine how changes have happened on average in broad sectors. This average picture would conceal active innovator units; however, effects on improvement at sector would be captured. In short this part of the study would present the large picture of innovative improvements in terms primarily of cost containments.

Changes in inter sector input-output relations or structural balances moreover, present us with the broad picture of the directions of the economy. In case more value adding sectors secure higher weightings in a subsequent period than what had prevailed earlier, we could describe the economy as having experienced innovative changes. Such analyses could be undertaken rigorously however; in this section we will provide an indicative pointer towards the direction of innovation in the economy. A few sectors of crucial importance to higher value addition in the entire economy, such as machine tools, transport equipments, other machineries or feedstock would be specially picked up to observe whether their intensive or larger use brought about the inter sector restructuring towards higher value addition.

A description of this large group is best afforded by the data from the Annual Survey of Industries (ASI) series. The data is non-accounting and is on organized manufacturing factory sectors classified according to the NIC. This could be further deepened through additional observations secured through a study on the input-output tables of the economy. In this case the data is again non-accounting but including entire economy of unorganized, agricultural and services or the non-factory sectors as well. Classification of the types is as per the CSO definitions. Further insights on innovation would be captured through examining the stock-exchange listed companies/firms based upon their accounting data. Here we would be using data provided by CMIE. In the first two types we will examine primarily the sector-level and inter-sectors level while for the last source of data we would look at sector and unit-level. In the subsequent sections specific observations on innovative outcomes have been drawn.

 

Innovation patterns in select sectors of organized factory-based industries

The Indian economy has been growing by more than 9% for the last three years and the growth rate of 9.6% during 2006-07 is the highest in the last 18 years. Simultaneously, exports are also growing at 30% CGAR. Industrial sector contributes a major share in this growth. These developments and innovation are among the factors that have made Indian economy as one of the stars of global economics in recent years. This growth rate has been possible due to the market reforms, large foreign direct investment (FDI), rising foreign exchange reserves and a flourishing capital market. In addition, maintaining such a steady rate of growth has been possible due to the increased capital and labor productivity and rising emphasis on innovation, increase in the R&D investments, employing state of the art technologies and similar others. Innovation has been one of the most important factors helping growth of the Indian economy. However, over emphasis on R&D has somewhat shadowed the important gains in enterprise performances achieved through non-R&D investments or non-R&D innovative activities. The scrutiny tries to realize the pattern of non-R&D based innovation in the organized manufacturing.

Innovation trends and patterns in a few select sectors of Indian industry, that are generic, employment generating or high technology, would hold higher promises than innovation in other sectors. Accordingly we might look into the following categories: Manufacturing; Automobiles; Leather; Electronics and Computers; Small Electronics Equipment industries; Tools Manufacturing; and Processed Food Industries.

Cost containment is perhaps the principal feature of innovation in Indian industry. Other aspects like development of new products or entering new markets are important as well although from the present data we cannot infer anything about these other features. Following parameters were taken into consideration to study cost cutting innovation patterns in the industry: fixed capital; total emoluments; fuel consumed; material consumed; and total stock.

Ratio of these parameters with respect to ‘value of output’ and ‘net value added’ when calculated exhibits several modes of cost cutting. A lower value of the ratio indicates consumption of fewer resources to achieve one unit of output or net value added. These ratios were calculated for different sectors on aggregate basis as grouped in the above mentioned categories. Results are shown in the following section.

 

Pattern of innovation in the total manufacturing industries

In the post liberalization period, there has been a great surge in the activities of Indian industries with number of units increasing from 110179 in 1990-91 to 136353 in 2004-05 with an annual growth rate of 1.62 per cent. Fixed as well as the invested capital grew by around 11 per cent per annum, net income and gross capital formation by around 15 per cent or gross fixed capital formation by about 14% annual growth which indicates increased productivity of the capital invested (Figure 1). Other parameters which indicate innovation is higher annual growth rate of net value added (13.56%) although the wages to workers and total emoluments grew by only around 8 and 9% respectively. Overall, the intensity of capital use increased significantly. Labour productivity in the overall factory based manufacturing too grew. However the disconcerting aspect was very high growth of addition to stocks during this same period. High growth in stocks would indicate higher gross delink inter sector or inter-factory.

  

 

Fig 1: Average annual growth rate (AAGR) of Indian industries during 1990-91 to 2004-05

Source: ASI data

 

From table 1 it is apparent that during the period 1990-91 to 2004-05, there has been a drastic improvement in the performances of the Indian industries. Only the three parameters related to manpower namely averages of workers per enterprise, employees per enterprise and total persons engaged per enterprise are showing a declining trend which is actually an indication of increase in labour productivity. Improvement in performance happens owing both to increased labour productivity and improvements in managerial functioning. The latter is evidenced further in the increased wages and increased emoluments per factory. In fact, this increase indicates that skill level and knowledge level in use by a factory has increased significantly. Increase in gross fixed capital formation per factory exhibits increased use of advanced and recent machineries.

 

Table 1: Performances of industry between 1990-91 and 2004-05

Parameter	1990-91	2004-05		Change (%)
Number of factories	110179	136353	23.76
Workers per Factory	57.24	48.40	-15.45
Employees per Factory	74.08	61.48	-17.01
Persons engaged per Factory	75.15	62.00	-17.50
Wages to workers per Factory	11.97	24.67	106.02
Total Emoluments per Factory	18.68	47.23	152.80
Fixed capital per factory	121.30	376.28	210.21
Working Capital per factory	38.59	117.38	204.16
Invested Capital per factory	176.91	556.95	214.83
Fuels consumed per Factory	18.97	62.96	231.93
Material consumed per Factory	151.52	751.25	395.81
Total inputs per factory	189.68	999.57	426.98
Value of output per factory	245.57	1226.64	399.51
Net value added per factory	46.76	190.61	307.68
Net income per factory	32.44	163.48	403.97
Net fixed capital formation per factory	12.92	18.73	45.02
Gross fixed capital formation per factory	22.05	55.19	150.30
Gross capital formation per factory	29.55	80.73	173.18
Profits per factory	10.34	106.05	925.90
Addition of stocks per factory	7.50	25.54	240.39

Source: Annual Survey of Industries

 

An increasing trend for material consumed with respect to ‘Net Value Added’ indicates more material is being consumed to achieve value addition to one unit of output, a trend perhaps not welcome; however, it could contrarily indicate increased commodity prices and hence might not indicate increased consumption of material weights/ quantities (figure 2). A word of caution would be appropriate: the data refers to prices and not to quantity – hence, even lower quantity but at higher relative price of materials might inflate. However, the increases in stocks are perhaps owing to unsold stocks failing to add to value. Factories having introduced advanced capital machineries are likely to have increased both per unit throughput and decreased materials loss. However, in-process inventory or gate-inventory owing to weak inter-factory linkages added to both stocks and materials intensity of value add. In other words, stocks per value add could be considered a macro or systemic indicator of innovation. For ‘Fixed capital, with respect to ‘Value of output’ and ‘net value added’, under the condition of enhanced capital stock- a declining trend in the ratio could represent increase in innovation because of enhanced capital productivity.

 

 

Fig 2: Selected indicators of industrial innovation

Source: Annual Survey of Industries

 

 

For total emoluments and fuel consumption there is negligible variation with respect to ‘net value added’, indicating a stagnant trend in innovation. On the other hand, there is declining trend with respect to ‘Value of output’ indicating increase in innovation (figure 3). Stagnant emoluments to value add might indicate increase in salary caused by supply side constraints on the flow of managerial employees. This is supported by the twin facts of increase in total emoluments with decrease in number of white collar workers. However, lower value add might also indicate failure to innovate organizationally or in business processes, or this might also indicate low level of knowledge of white collar employees. Fuel bill suffers from supply constraints too because ordinarily a factory would not enjoy the flexibility to switch fuel corresponding to shifts in relative prices of a few fuels. However, lower attention to the importance of energy related innovation cannot be excluded. Most significant innovation in the factory sector appears to be in the increase in labour productivity. Relatively lower level of innovation could be noticed in the very low value of improvements in white collar productivity or in other words in the organization of the business. Significant fluctuations in stocks per value add would indicate economy-wide delink or an issue that should be addressed by policies targeted to enhanced inter-dependencies towards better lean production systems. The period is too small to have suffered from business cycles.

 

 

Fig 3: Indicators of innovation across industries in general

 

Another description of innovation in factory sector:

A simple but not robust approach to capturing structural changes in the organized manufacturing sector over a rather short period of four years could be as follows: note the percentage share of a sector’s value add to the total value add by all sectors for two periods; then note the change in relative share of each sector between the two periods – then observe the peculiarities including whether the overall economy has moved towards higher value adding sectors. This method is weak, however, it informs quickly on the structural changes in the output sectors vis-à-vis increased value addition. Table-2 presents this data for two years and in the upper part of table, the top 21 sectors could increase relative shares while the bottom 36 sectors lost their relative shares over this period of four years.

The percentage share of value added in each industry sector to total value added by industries shows that iron and steel manufacturing industries recorded the maximum growth (8.8) followed by manufacture of refined petroleum products (6.2). And surprisingly, more than half of the industry sectors show a decline in the percentage share in net value added. Manufacture of basic chemicals lost most share preceded by spinning, weaving and finishing of textiles. This table indicates innovative sector performance and structural shift of the economy towards value added activities in transport equipments, auto components, coke oven, certain types of instruments, electrical equipments, electrical control & distribution equipments, certain other types of transportation, and such others indicating an overall structural shift towards added value chains in most parts of transportation and a general shift towards those sectors.

A significant loser is the drugs and pharmaceutical sector under the manufacture of other chemical products class. This sector, as is also evidenced in analysis of the CMIE data, has lost in relative share of value added. However, the relative losers appear to be most sectors related to textiles and apparel, general purpose and special purpose machinery, electronic components, computers, several areas of food processing, furniture, and such others. Perhaps several sectors that are mostly located in small urban areas and with relatively higher number of employees as well as with lower invested capital in machineries are the losers.

 

Table-2: Changes in the percentage share of value added for each industry sectorwith respect to the value added in the total industries

NIC Code	Industry type	% share in total value added by industry sector		Change in percentile points
		2000-01	2004-05
271	Manufacture of Basic Iron & Steel	6.3338	15.1778	8.844
232	Manufacture of refined petroleum products	4.7406	10.9497	6.209
272	Manufacture of basic precious and non-ferrous metals	2.4195	3.1556	0.736
359	Manufacture of transport equipment	1.8863	2.5311	0.645
231	Manufacture of coke oven products	0.1547	0.6702	0.515
343	Manufacture of parts and accessories for motor vehicles and their engines	2.3500	2.7838	0.434
369	Manufacturing of Jwellery,musical instruments,coins,sprts goods,games, toys etc.	1.0865	1.2448	0.158
332	Manufacture of optical instruments and photographic equipment	0.1069	0.1975	0.091
353	Manufacture of aircraft and spacecraft	0.0378	0.1161	0.078
014	Agricultural and animal husbandry service activities, except veterinary	0.1982	0.2634	0.065
331	Manufacture of medical appliances and instruments and appliances for measuring	0.6280	0.6829	0.055
319	Manufacture of other electrical equip ment	0.2585	0.3106	0.052
342	Manufacture of bodies (coach work) for motor vehicles; manufacture of trailers	0.0488	0.0958	0.047
261	Manufacture of glass and glass products	0.4566	0.4944	0.038
142	Mining and quarrying	0.0034	0.0276	0.024
312	Manufacture of electricity distribution and control apparatus	0.7627	0.7817	0.019
351	Building and repair of ships & boats	0.1596	0.1741	0.014
352	Manufacture of railway and tramway locomotives and rolling stock	0.2096	0.2208	0.011
371	Recycling of metal waste and scrap(aluminum, utensil, containers)	0.0024	0.0118	0.009
223	Reproduction of recorded media	0.0180	0.0221	0.004
372	Recycling of metal waste and scrap from non metallic items	0.0004	0.0027	0.002
182	Dressing and dyeing of fur; manufacture of articles of fur	0.0056	0.0038	-0.002
322	Manufacture of television and radio transmitters and apparatus for line telephony	0.3883	0.3678	-0.021
202	Manufacture of products of wood, cork, straw and plaiting materials	0.1771	0.1360	-0.041
273	Casting of metals	0.6596	0.6159	-0.044
191	Tanning and dressing of leather, manufacture of luggage handbags etc	0.2411	0.1880	-0.053
315	Manufacture of electric lamps and lighting equipment	0.2414	0.1658	-0.076
281	Manufacture of structural metal products, tanks, reservoirs & steam generators etc	0.9743	0.8809	-0.093
314	Manufacture of accumulators, primary cells and primary batteries	0.4260	0.3104	-0.116
300	Manufacture of office, accounting and computing machinery	0.5746	0.4197	-0.155
333	Manufacture of watches and clocks	0.2195	0.0506	-0.169
173	Manufacture of knitted and crocheted fabrics and articles	0.7591	0.5826	-0.176
172	Manufacture of other textiles	0.8010	0.6198	-0.181
192	Manufacture of footwear	0.5632	0.3315	-0.232
321	Manufacture of electronic valves and tubes and other electronic components	0.8798	0.5708	-0.309
153	Manufacture of grain mill products, starches and starch products etc	1.5181	1.2047	-0.313
151	Production, processing and preservation of meat, fish, fruit vegetables, oils etc	1.4659	1.1450	-0.321
293	Manufacture of domestic appliances,	0.6297	0.2401	-0.390
289	Manufacture of other fabricated metal products; metal working service activities	1.8516	1.4404	-0.411
323	Manufacture of television and radio receivers, sound or video recording	0.9104	0.4943	-0.416
155	Manufacture of beverages	1.1894	0.7353	-0.454
313	Manufacture of insulated wire and cable	0.7475	0.2546	-0.493
251	Manufacture of rubber products	1.7253	1.2179	-0.507
181	Manufacture of wearing apparel, except fur apparel	2.2370	1.7160	-0.521
292	Manufacture of special purpose machinery	2.9381	2.3777	-0.560
291	Manufacture of general purpose machinery	3.1567	2.5854	-0.571
242	Manufacture of other chemical products	9.6783	9.0611	-0.617
269	Manufacture of non-metallic mineral products	4.9234	4.0890	-0.834
160	Manufacture of tobacco products	2.8378	1.9186	-0.919
243	Manufacture of man-made fibers	1.2707	0.3488	-0.922
210	Manufacture of paper and paper product	2.6097	1.3034	-1.306
154	Manufacture of other food products	5.2507	3.0280	-2.223
171	Spinning, weaving and finishing of textiles	7.2894	4.3715	-2.918
241	Manufacture of basic chemicals	10.2185	7.0328	-3.186

 

 

Innovation across different types of ownership of enterprises

In the publicly owned industries, all the selected parameters show an increasing trend indicating lack of innovation, whereas in case of public limited and private limited companies, all the ratios are decreasing over the years indicating the occurrence of innovation. A large number of privately owned/ managed enterprises have higher dividend payouts, and very high cash reserves, and sometimes a few of them have gone in for share buy-backs and all this might have resulted in lower investment in fixed capital. Rising fixed capital that we observe in the public ownership is towards building up of capacities and the gross fixed capital formation especially under plants and machineries are redeeming indeed. On this aspect of investment in plants and machineries the private owned entities appear to have slackened, however, they seem to have made such capital albeit low in value to higher efficient use as compared to the public ownership. The latter, in fact, often paid out handsome dividends too.

The emoluments have risen sharply in the public sector and the ratio to gross output rose sharply especially in contrast to the situation under other modes of ownership. The ratio of emoluments to net value added for public enterprises exhibit similar trend, however, having cooperative ownership having risen has now fallen indicating perhaps that organizational innovation has set in. Private limited ownership has often indifference or poor improvements while public limited companies have exhibited perhaps the most improvements. The industries in the cooperative societies show a very fluctuating pattern of all the parameters indicating there is no consistency in the innovation process.

 

Fig 4: Fixed capital/gross output

 

Fig 5: Fixed capital/net value added 

      

Fig 6: Total emoluments/gross output

 

Fig 7: Total emoluments/net value added

 

Innovation patterns in rural and urban industries

Industries based in both the rural as well as in the urban areas undertook almost similar patterns of innovations during the period 1989-90 to 2004-05. In both rural as well as urban industries few ratios mainly invested capital per gross output, wages per gross output and invested capital per net value added exhibit decreasing trend. These declining ratios indicate innovation in manufacturing; but the decrease in wages per gross output is very small indicating little gains in labour productivity and the recorded innovation is perhaps due to the use of advanced or efficient technologies.

 

Fig 8: Innovation pattern in the rural industries

 

An increasing input to output ratio in both the rural and urban industries is an indication of overall low productivity. However, the degree of increase of the input to output ratio is higher in the urban industries (0.79 to 0.82) indicating that the urban industries are comparatively less productive than their rural counterparts whose input to output ratio has increased from 0.79 to 0.81 during the same period.    

 

Fig 9: Innovation pattern in the industries located in the urban areas

 

Inter-state comparison in industrial innovation

Two patterns of innovation trend can be observed among the states. The variables considered for this inter-state comparison are the same as above, and therefore capital intensity of output and of net value added, and emoluments intensity of output and net value added for a few states have been mapped for the period 1998-99 to 2004-05.

 

 

Fig 10: Indicators of innovation among the better performing states

 

 

Some states such as Andhra Pradesh, Uttar Pradesh, Gujarat, and Karnataka exhibit a continuously decreasing trend of the parameters under consideration (fig. 10). This clearly indicates that the innovation process in the industries of these states is a nearly continuous one excepting a few kinks. In the remaining states, the ratios show a fluctuating pattern, increasing first and then decreasing which indicates these states are also at last becoming innovative. These states are West Bengal, Bihar, Tamil Nadu, Punjab, Maharashtra and Madhya Pradesh (fig. 11).

However, if we consider states having lower values of the ratios as more innovative, then in general Maharashtra and Punjab go neck-in-neck to top the list of most innovative states. Rest of the states in descending order of innovativeness or more efficient use of capital and white collar employees or the organizational processes – would be like Uttar Pradesh> Karnataka> Gujarat> Andhra Pradesh> West Bengal> Tamil Nadu> Bihar> Madhya Pradesh.

 

Fig 11: Indicators of innovation among the states having fluctuating trend of innovation

 

Innovations in sectors – Non R&D aspects:

Innovations across several sectors can be appreciated from decreasing per unit consumption of materials, fuels, emoluments, fixed capital, and stock-held for every value added or every value of output. The period of data is very small, only 5 years from 2000-01 onwards. A secular decrease in particular a steep fall would indicate that the corresponding factory sector has done remarkably well in innovation. In several cases, however, we will notice indifference and in many cases irregular features exhibiting no regular trend. We should note that value add includes wages or emoluments and additionally also the capability of that sector to price its output, and also the capability to manage cash and intangibles including organizational management. In as far as value addition is constrained by the emoluments; a ratio between these two would be superfluous. However, value adds by reflecting other aspects beyond emoluments enables taking a ratio as well as drawing certain observations on innovativeness of that sector.

Most importantly, investments in innovation are not captured in data on R&D expenditure. The fact that sectors undertake innovation and incur expenditure on R&D aspects is pointers to this often ignored dimension of innovation. Tax gains as policy may not have influenced the undertakers of the innovation, neither do these undertakers use innovation as signals to the capital market. In contrast such innovations appear to have been influenced by the sector competition landscape and inter sector’s competition landscapes. Policies that are targeted to competition and other legal dimensions including a few non-R&D aspects of fiscal policies have together influenced the sector innovation outcomes. Input prices, including of commodity, for example, might have been more influential than gains through tax deductions on R&D expenses to invest in innovation. Further, an estimate of expenses/ investment on these non-R&D innovations could be made based upon say, the savings achieved.

 

Sector - Automobile Industries:

In the automobile sector, there were 4412 industries in 2000-01 which increased to 4957 during 2004-05. In this sector, material consumption is decreasing in terms of value of output and net value added to the product (fig. 12).

 

Fig 12: Indicators of innovation in Automobile industries

 

The sharp fall evidences significant innovation in automobiles. Great gain in the productivity of capital signifies another dimension of innovation. The ratio of emoluments paid to the employee (Worker/ Supervisor) to both output value and net value added, however, shows indifference. Another important dimension of innovation that relates more to inter sector than to the sector is about the stock held. In fact higher value of stock goes against the spirit of lean production, which in turn depends upon the relations between enterprises that are in a value chain or more properly in a logistics chain. High value of stock to per unit value add is therefore a drag on the company and the automobile sector exhibits a near indifference to this ratio over this five year period.

 

Leather Industries:

In leather manufacturing, material consumption per unit value of output as well as per net value added shows fluctuations or an increasing trend, exhibiting poor state of innovation in materials efficiency.

 

Fig: 13 Leather industry

 

However, innovation in capital employed especially fixed capital per value of output has shown slight improvement over the period. The total salary paid to the employee (worker/supervisor) is almost constant over the same period. Emoluments trend exhibits indifference to innovation. The total number of enterprises in this sector was 2378 in 2000-01 which decreased to 2293 in 2004-05. In this sector there appears to be insignificant innovation in terms of fuel consumption as well as in terms of addition of stocks.

 

Electronic/Computer Industries:

This sector exhibits poorer show on innovation compared to the previous two sectors especially compared to automobiles. In the electronic and computer sector, material consumption in terms of value of output as well as materials consumed per net value added is increasing indicating inefficiency in material consumption. Whereas fixed capital invested in terms of net value added or value of output is decreasing over the period 2001-05. Wages per value of output or net value added is almost constant exhibiting indifference to innovation. There is no significant innovation in fuel consumption also. In this sector, the number of industries increased marginally from 3742 in 2000-01 to 3797 in 2004-05.

Fig 14: Electronic/Computer Industries

 

Small Electronic Equipment Industries:

Similar to the sector above, the small electronic equipment industries sector exhibits a poor show in innovative activities with negative or indifferent trends on a few aspects. In this sector material consumption in terms of value of output as well as materials consumed per net value added shows upward trend over the period 2001-05 indicating material consumption inefficiency. Fixed capital invested per value of output as well as net value added is almost constant. On other aspects, such as stock held or on emoluments related business innovation, this sector remained indifferent. In this sector, the number of industries has reduced from 2167 in 2000-01 to 1993 in 2004-05.

 

Fig 15 :Small Electronic Equipment Industries

 

Tools Manufacturing:

Perhaps the poorest show of innovation is evidenced in this sector. Material consumption in terms of value of output as well as materials consumed per net value added shows a continuous increase over the period 2001-05.

 

Fig 16: Tool Manufacturing Industries

 

The stocks held too shows upward trend. Materials consumption could be reduced per value add through innovations within the enterprise while innovations in stock held would require improvements in cross-sector linkages of systemic nature. But fixed capital invested per value of output as well as net value added is showing a decreasing trend, exhibiting marginal innovative gains along this aspect alone. Number of units was 8600 and 8681 in 2000-01 and 2004-05 respectively.

 

Processed Food Industries:

Another sector with negative or indifferent state of affairs in innovative activities with marginal improvements only in stock held aspect of innovation and that too only in the later part of the period. In the processed food sector, material consumption in terms of value of output as well as materials consumed per net value added is increasing or indifferent. Fixed capital investment per value of as well as net value added is also indifferent. This sector is having the highest number of industries among the sectors under consideration. During 2000-01, the number of industries in this sector was 22171 which have increased to 23216 during 2004-05.

 

Fig 17: Processed food Industries

 

Textiles

Another poor show of innovative activity or absence of non-R&D innovation is evidenced in the textiles sector enterprises. In the industries involved in textiles material consumption in terms of value of output as well as materials consumed per net value added is almost constant over the period 2001-05. Fixed capital investment per value of output as well as net value added is also almost constant, however, with marginal improvements exhibiting better utilization of capital. This sector has the second highest number of enterprises after those in the processed food sector. The number of industries was 16914 and 16906 during 2000-01 and 2004-05 respectively. There is a slight decline in the number of industries.

 

Fig 18: Textile Industries

 

 

 

 

 

 

Annexure I: Concepts and Definitions of items used in ASI

Reference Year is the accounting year of the factory ending on 31st March 2005 while the survey was conducted in 2005-06.

Factory is one that is registered under sections 2m (i) and 2m (ii) of the Factories Act, 1948. i.e. an industrial unit employing 10 or more workers using power; and those employing 20 or more workers without using power.

Fixed Capital represents the depreciated value of fixed assets owned by the factory as on the closing day of the accounting year. Fixed assets are those that have a normal productive life of more than one year such as land, buildings, plant & machinery, furniture and fixtures, transport equipment, etc.

Physical Working Capital is the total inventories comprising of raw materials and components, fuels and lubricants, spares, stores and others, semi-finished goods and finished goods as on the closing day of the accounting year. It does not include the stock of the materials, fuels, stores, etc. 

Working Capital is the sum total of the physical working capital and the cash deposits in hand and at bank and the net balance receivable over amounts payable at the end of the accounting year. It excludes unused overdraft facility, fixed deposits, advances for acquisition of fixed assets, loans and advances by proprietors and partners, long-term loans and investments.

Productive Capital is the total of fixed capital and working capital as defined above

Invested Capital is the total of fixed capital and physical working capital as defined above.

Gross Value of Plant and Machinery represents the total original (un-depreciated) value of installed plant and machinery at the end of the accounting year. It includes the book value of the newly installed plants and machinery and the approximate value of rented in plants and machinery at the time of renting-in but excludes the value of rented-out plants and machinery.

Outstanding Loans represent all loans outstanding according to the books of the factory as on the closing day of the accounting year.

Workers are defined to include all persons employed directly or through any agency whether for wages or not and engaged in any manufacturing process or in cleaning any part of the machinery or premises used for manufacturing.

Employees include all workers and persons receiving wages and holding clerical or supervisory or managerial positions.

Total Persons Engaged include the employees and all working proprietors and their family members who are actively engaged in the work of the factory even without any pay, and the unpaid members of the co-operative societies who worked in or for the factory in any direct and productive capacity.

Wages and Salaries includes (a) direct wages and salary (i.e., basic wages/salaries, payment of overtime, dearness, compensatory allowance, house rent and other allowances), (b) remuneration for the period not worked, (c) bonuses and ex-gratia payment paid both at regular and less frequent intervals. It also excludes imputed value of benefits in kind, employer's contribution to old age benefits and other social security charges, direct expenditure on maternity benefits and crèches and other group benefits. Travelling and other expenditure incurred for business purposes and reimbursed by the employer are excluded.

Total Emoluments is the sum of wages and salaries, employers’ contribution as provident fund and other funds and workmen and staff welfare expenses as defined above. 

Total Input comprises total value of fuels and materials consumed as well as expenditures such as cost of contract and commission work done by others on materials supplied by the factory, cost of materials consumed for repair and maintenance of factory's fixed assets, inward freight and transport charges, rates and taxes (excluding income tax), postage, telephone and telex expenses, insurance charges, banking charges, cost of printing and stationery and purchase value of goods sold in the same condition as purchased . 

Total Output comprises total ex-factory value of products and by-products manufactured as well as other receipts such as receipts from non-industrial services rendered to others, work done for others on material supplied by them, value of electricity produced and sold, sale value of goods sold in the same condition as purchased, addition in stock of semi- finished goods and own construction. 

Depreciation is consumption of fixed capital due to wear & tear and obsolescence during the accounting year and is taken as provided by the factory owner or is estimated on the basis of cost of installation and working life of the fixed assets. 

Net Value Added is arrived by deducting total input and depreciation from total output.

Nature of ASI data

The Annual Survey of Industries (ASI) was started by the Government of India in the year 1960 with 1959 as the reference year for collection and compilation of data relating to the national industrial sector. This survey was designed so as to overcome and replace the earlier surveys like Census of Manufacturing Industries (CMI) of 1946 and the Sample survey of Manufacturing Industries (SSMI) of 1949. The ASI refers to the factories defined in accordance with the Factories Act 1948, and thus has coverage wider than that of the CMI and SSMI put together.

Geographically, the survey covers the whole country except Arunachal Pradesh, Mizoram, Sikkim and Lakshadweep. It covers all factories registered under Sections 2m(i) and 2m(ii) of the Factories Act, 1948 i.e. those factories employing 10 or more workers using power; and those employing 20 or more workers without using power. The ASI frame is based on the lists of registered factories/units maintained by the Chief Inspector of Factories (CIF) in each State/UT and those maintained by licensing authorities in respect of bidi and cigar establishments and electricity undertakings. Data for the period 1989-90 to 1997-98 were arranged as per NIC 1987 while those for the period 1998-99 to 2003-04 are as per NIC 1998 and the latest classification; NIC 2004 has been followed for ASI data beginning 2004-05.

The ASI data provides statistical information to assess and evaluate, objectively and realistically, the changes in the growth, composition and structure of organized manufacturing sector comprising activities related to different industrial sectors in India. The data is collected under following heads for different sectors of Indian industry.

 

1. Number of Factories	2. Fixed Capital
3. Working Capital	4. Invested Capital
5. Outstanding Loans	6. Number of Workers
7. Total Persons Engaged	8. Wages to Workers
9. Total Emoluments	10. Prov. Fund and Other Welfare Exp.
11. Fuels Consumed	12. Materials Consumed
13. Total Inputs	14. Products & By-products
15. Value of Output	16. Depreciation
17. Net Value Added	18. Rent Paid
19. Interest Paid	20. Rent Received
21. Interest Received	22. Net Income
23. Net Fixed Capital Formation	24. Gross Fixed Capital Formation
25. Addition in Stock of (a) Materials, Fuels etc. (b) Semi-Finished Goods (c) Finished Goods

 

One thing to be noted here is that there is no head which could give information about R & D investments, however the element of innovation can be estimated by observing the growth trends under heads like fuel and material consumed, wages and emolument paid and the number of workers involved in achieving a particular value of output or value.

Classification of industry under different sectors: The sectors in the Indian industry are classified on the basis of the UN International Standard Industrial Classification (UNISIC) of all Economic Activities 1958 (Rev. 1). This classification known as National Industrial Classification (NIC) has developed gradually on the basis of UNISIC 1968(Rev.2). The NIC-1987 that strictly followed UNISIC 1968 was adapted for ASI surveys in 1989-90 to 1997-98.  The NIC-1998, developed on the basis of UNISIC, 1990 (Rev. 3) was used from 1998-99 to 2003-04. The latest classification, i.e. NIC-2004, developed on the basis of UNISIC 2002 (Rev. 3.1) has been adopted since 2004-05.

 

 

 

Suggested readings:

• CSO. 2004. National Industrial Classification 2004 (NIC 2004). New Delhi: Government of India.
• Dutz MA. 2007. Unleashing India's Innovation: Toward Sustainable and Inclusive Growth. The World Bank Publications, 2007. 224 pages.
• Ghosh B & Neogi C. 1993. Productivity, efficiency, and new technology: The case of Indian manufacturing industries. The Developing Economies, 31 (3): 308-327.
• Hulten CR, Bennathan E & Srinivasan S. 2006.  Infrastructure, Externalities, and Economic Development: A Study of the Indian Manufacturing Industry. The World Bank Economic Review, 20 (2):291-308.
• Humphrey J. 1995. Industrial Organization and Manufacturing Competitiveness in Developing Countries: Introduction, World Development, 23 (1): 1-7.
• Kathuria V & George AS. 2007. Spatial location of Indian manufacturing industries— an exploratory analysis. Indian Journal of Economics and Business. Available at http://findarticles.com/p/articles/mi_m1TSD/is_2_6/ai_n25015741.
• Majumdar SK. 1996. Fall and Rise of Productivity in Indian Industry: Has Economic Liberalisation Had an Impact? Economic and Political Weekly, Vol. 31, No. 48: pp. M46-M53.
• Singh L & Gill A. 2002. Post-Reform Employment Growth in the Organised Manufacturing Sector of India: A Disaggregative Analysis, Manpower Journal, 38 (1):87-98.

 

 

 

 

 

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