Sales and Advertisement Relationship for Selected Companies ...

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Dr. S. Sharma, Dr. J. Sharma - Sales and Advertisement Relationship for Selected Companies Operating in India

2009 Sales and Advertisement Relationship for Selected Companies Operating in India: A Panel Data Analysis

Sales and Advertisement Relationship for Selected Companies Operating in India: A Panel Data

Analysis

Dr. Suparn Sharma

Dr. Jyoti Sharma

Running Head: Sales and Advertisement Relationship

Abstract:

The study tries to examine the growth pattern and trend of sales and advertisement expenses for the selected companies over a period from 1992-93 to 2006-07. Further it seeks to evaluate the effectiveness of advertisement expenses on sales of selected companies operating in India at aggregate and disaggregate levels. It also tries to analyse the behaviour of share of advertisement expenses in total sales for the above mentioned categories. The study is based on panel or pooled secondary data collected for advertisement expenditure and sales revenue of 134 randomly selected sample companies operating in India over the period from 1992/93 to 2006/07 which are further classified on the basis of amount of sales revenue as well as on the basis of type of product produced. In this study of Panel or Pooled data, Fixed Effect approach with and without dummy variables are applied to evaluate the effectiveness of advertisement expenses on sales. Further, annual compound growth rates and summary statistics are also estimated. The contribution has found that the growth rate of sales revenue of manufacturing and companies, whose sales revenue is more than 1000 crore, is highest inspite of the negative compound growth rate of advertising expenses of these two types of companies. Further, in case of non-manufacturing companies, it has been found that these companies are less popular among the consumers and they are also spending less on advertisements as compared manufacturing companies. While answering, how much advertisement expenses need to be incurred, the study concludes that to a large extent it depends on the nature and size of industries. Paper Classification: Research Paper

Key Words: Sales Revenue, Advertisement Expenses, Panel Data, Manufacturing and Non-Manufacturing

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School of Doctoral Studies (European Union) Journal - July, 2009 No. 1

School of Doctoral Studies (European Union) Journal July

Advertising is a prominent feature of modern business operations. One can encounter advertising messages, while watching TV, reading magazines, listening to the radio, surfing the internet, or even simply while walking down the street, as advertisement has a stimulating influence on purchasing behaviour of the customer. This mammoth surge of advertisements from every possible source is basically to fulfil the urge of marketers to reach to a large number of people so that their product may receive optimum exposure. The role of this mass mode of communication in creating brand loyalty, deterring entry and consequently increasing sales revenue and profits of the organisation and causing impact on the business cycle has been emphasised at various points of time by different studies (Robinson, 1933; Kaldor, 1950; Nelson, 1974; Ozga, 1960; Stigler, 1961; Sundarsan, 2007). Broadly the role of advertising expenses in an economy can be classified under two heads. According to one school of thought, advertising increases profits and reduces consumer welfare by creating spurious product differentiation and barriers to entry. While the other school of thought focuses on the informative character of advertising, which makes markets more competitive and reduces profits by informing the customers about prices and quality (Greunes et al, 2000). Inspite of the above mentioned segregation, one cannot deny the fact that ultimate function of advertising expenses is to promote sales revenue. That is why every organisation with the expectation of earning return is investing millions of rupees or dollars on this mode of marketing communication.

Hence, in pursuit of their ultimate objective of increasing sales, every endeavour of each marketer is to make this mode of sales generation more effective. But advertisement effectiveness conveys different meanings to different groups. To the writer or artist, effective advertising is that which communicates the desired message. While to the media buyer, effective advertising is that which reaches to prospective buyers a sufficient number of times. However to the advertising or marketing manager, effective advertising is that which, together with other marketing forces, sells

his brand or product. Whereas according to the general manager, effective advertising produces a return on his firm’s expenditure. Infact to be effective the advertising must achieve the goal of delivering messages to the right audience and thereby creating sales at a higher profit.

The subject of advertisement has remained a topic of debate either on one pretext or another for decades. At the beginning of 19th century, though, it was a subject of little interest to the major researchers, but it became a fertile topic for economic research at the turn of 19th century during which, on one side its constructive role in providing information to customers to satisfy their wants at lower cost was recognised and on the other a wasteful confrontational role by offering little information and doing redistribution of customers from one firm to another was acknowledged. Various studies have been conducted to assess the different aspects of relationship between advertisements and sales at different points of time. A brief review of the studies relating to different dimensions of interrelationship of sales and advertisement is presented in the forthcoming paragraphs.

Review of Selected Literature

The economic effects of advertisement expenses has been a much debated topic and studied widely at different points of time. Verdon et al (1968) while studying the relationship between advertising and aggregate demand found that advertising have a positive relation with aggregate demand. However, Ekelund and Gramm (1969) analysed the relationship between advertising expenditure and aggregate consumption but could not establish any positive relationship between these two. Similarly, Taylor and Weiserbs (1972) studied the relationship between advertising expenditure and aggregate consumption on the basis of Houtakker-Taylor model and showed that advertising affects aggregate consumption and the relationship between advertising and consumption is not found to be unidirectional but simultaneous. Jagpal (1981) while applying the multiproduct advertising sales model to a commercial bank found

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that radio advertising was relatively ineffective in stimulating sales of the joint outputs (number of savings and checking accounts). Sachdeva (1988) studying the trends in advertisement expenditure of India’s large corporate bodies stated that foreign controlled companies single-handly accounted for a dominant share in advertisement expenditure. Consumer goods producing organisations controlled by foreign companies have emerged as one of the most important contributors to advertisement budgets of the corporate world. Another study by Leong et al (1996) using cointegration technique found a strong positive relationship between advertising expenditure and sales. Similarly, Lee et al (1996) found that the variables of advertising and sales are not only integrated of same order but also cointegrated. The results explicated that causal relationship between advertising expenses and sales works in both directions. Leach and Reekie (1996) analysed the effect of advertising on the market share of a brand using variants of the Koyack Distributed Lag model. Further, the results of the Granger causality test showed that advertising expenses caused sales but sales do not simultaneously cause advertising. Elliot (2001) revealed that advertising has a significant positive effect on food industry sales and this relationship between advertising expenditure and sales appears to be stable. Pagan et al (2001) studied the effectiveness of advertising on sales using bivariate Vector Auto Regression model and showed that one time increase in advertising expenditure leads to increase in the sales of orange with a one month lag. It was also found that the impact of advertising expenditure on grape fruit sales is more immediate and relatively large. While analysing the relationship between a company’s advertising expenditure and its sales during the recession, Kamber (2002) found a measurable relationship between advertising expenditure and sales, even after controlling other factors, such as, company size and past sales growth, etc. Guo (2003) examined the relationship between advertising and consumption at macro level using the US data on advertising expenditure, personal consumption and disposable income. The study with the use of unit root tests and cointegration

analysis substantiated the existence of cointegration among variables, which reveals the presence of long-term equilibrium relationship among them. Sundarsan (2007) evaluated the effectiveness of advertising on sales of small and large firms, and for multinational corporations. The results showed that advertising has influenced sales, though its relative effectiveness was not the same for all the categories of firms.

The above review divulges that there is no consensus on the economic effects of advertising expenses on sales revenue. Different studies have shown diverse results. However, in general, majority of the studies have directed positive relationship between the two. Most of the studies have used time series data to capture the long-term effects of advertising on sales. However, it is important to know effects of advertising expenses on sales revenue for Indian corporate sector. Moreover, the area that to what extent advertising’s persuasive character work to alter consumers wants and consequently sales have received scant attention. With this backdrop, the present study has been designed to find out the extent to which advertisement expenses cause impact on sales revenue. More specifically the objectives of the study are to examine the growth pattern and trend of sales revenue and advertisement expenses for the selected companies operating in India. Further, the present contribution aimed to evaluate the effectiveness of advertisement expenses on sales revenue for selected companies at aggregate as well as disaggregate level. The present study will also try to analyse the behaviour of share of advertisement expenses in total sales revenue for the above mentioned categories.

In consequent of the above mentioned objectives, the study has been divided into three sections. The database and research methodology has been discussed in section I. While section II, attempts to study the relationship of sales revenue and advertisement expenses of randomly selected companies operating in India, the summary, conclusions and implications of the study are carried out in section III.

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Database and Methodology

The present study is based on the advertisement expenditure and sales revenue data of 134 randomly selected sample companies operating in India (Annexure-I). The secondary data used in the present study is panel or pooled in nature and collected from PROWESS (2009) of Centre for Monitoring Indian Economy, New Delhi, India for the period 1992/93 to 2006/07. The term advertisement expenditure, here, includes expenses on advertisement as well as all other expenditure incurred under the head of marketing expenses like publicity, promotion expenses, etc.

In this Panel data based study Fixed Effect approach with and without dummy variables are applied to evaluate the effectiveness of advertisement expenses on sales revenue. Further, annual compound growth rates (ACGR) and summary statistics are also estimated. With the purpose to study the behaviour of different categories of companies, the randomly selected companies operating in India are classified on the basis of sales revenues and type of product produced. Accordingly, Type-1 companies are the companies whose sales revenue is less than Rs. 1000 cr and Type-2 companies are the companies whose sales revenue is more than Rs. 1000 cr. Further, Type-3 companies are manufacturing companies and Type-4 companies are non-manufacturing companies, which includes a combination of agro, food, service based units, etc.

MODEL-1 Simple Fixed Effect Model

LnSit = a0 + b1LnAit + uit

Where, S= Sales Revenue, A= Advertisement Expenses, Ln = Natural Logarithm, uit =

Stochastic term

MODEL-2 Differential Intercept Dummy Variable Model

The present model is used to study sales and advertisement relationship for the Type-1 and

Type-2 as well as Type-3 and Type-4 companies. In intercept dummy variable model, slope coefficient beta (b1) is assumed to be the same for two groups. The hypothesis to be tested, here, is ‘there is no difference in the relationship between groups’ (Ramanathan, 2002).

LnSit = a0 + a1D1 + b1Ln Ait + uit

D1 = 0 for Type-1 companies, D1 = 1 for Type-2 companies. LnSit = a0 + a1D2 + b1LnA it + uit

D2 = 0 for Type-3 companies, D2 = 1 for Type-4 companies.

MODEL-3 Differential Slope Dummy Variable Model

In this model, the possibility that the slope coefficient (b1) may be different for different types of companies has been studied. It is assumed that the intercept term ‘a0’ is unchanged. Since the intercept term is assumed to be the same, the regression line starts from the same point but may have different slopes.

LnSit = a0 + b1LnA it + b2LnAit*D1+ uit

D1 = 0 for Type-1 companies, D1 = 1 for Type-2 companies. LnSit = a0 + b1LnA it + b2LnAit*D2+ uit

D2 = 0 for Type-3 companies, D2 = 1 for Type-4 companies.

Results and Discussion

The basic characteristic of the variables under study is delineated in Table I in the form of summary statistics. The average expenditure on advertisement is Rs. 8684.26 cr and similarly the average sales revenue is Rs. 383509.45 cr during the period under study. Further, it is highlighted that high variation has been experienced for the sales revenue of randomly selected 134 companies; however in case of advertisement expenditure the variation is comparatively low.

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TABLE 1 . SUMMARY STATISTICS OF SALES REVENUE AND ADVERTEMENT EXPENSES

(Amount in Rs. Cr.)Summary Statistics Sales Revenue Advertisement

Expenses

Mean 383509.45 8684.26

Median 336491.26 8536.23

Minimum 102746.7 5450.95

Maximum 927601.79 12474.06

Standard Deviation 240470.21 2059.54

Coefficient of Variation 62.71 23.72

No. of Firms 134 134

Source: Calculated from the data available at Prowess (2008), CMIE

TABLE 2. SUMMARY STATISTICS OF SALES REVENUE AND ADVERTISEMENT EXPENSES FOR TYPE-1 AND TYPE-2 COMPANIES

(Amount in Rs. Cr.)

Summary Statistics

Type-1 Sales

Revenue

Type-1 Adverti-sement

Expenses

Type-2 Sales

Revenue

Type-2 Adver-tisement Expenses

Mean 16274.96 546.51 367234.49 8137.76

Median 17388.33 650.66 318720.74 7859.29

Minimum 7994.96 198.89 94751.74 7632.71

Maximum 23932.1 780.18 903669.69 11693.88

Standard Deviation 4534.13 194.07 236385.16 2124.30

Coeffi-cient of

Variation27.86 35.51 64.37 26.11

No. of Firms 79 79 55 55

Source: Same as in the table I

TABLE 3. SUMMARY STATISTICS OF SALES REVENUE AND ADVERTISEMENT EXPENSES FOR TYPE-3 AND TYPE 4 COMPANIES

(Amount in Rs. Cr.)

Summary Statistics

Type-3 Sales

Revenue


Expenses

Type-4 Sales

Revenue


Expenses

Mean 366708.22 8208.97 16801.23 475.29

Median 317117.55 7910.52 19373.71 496.26

Minimum 97460.53 4914.55 5286.17 127.79

Maximum 905304.8 11602.15 22296.99 871.91

Standard Deviation 190635.27 2092.81 5123.45 243.55

Coef-ficient of Variation

51.99 25.49 30.49 51.24

No. of Firms 109 109 25 25

Source: Same as in the table I

The summary statistics of different companies exhibits that the average sales are more in case of Type-2 companies i.e. the companies whose sales revenue is greater than Rs. 1000 cr. Further, the mean expenditure on advertisement is reflected more in case of Type-3 companies, i.e. the manufacturing companies. The coefficient of variation in case of sales revenue is maximum for Type-2 companies and in case of advertising expenses it is higher in Type-4 companies i.e. non-manufacturing companies.

The study of sales revenue and advertisement expenses at aggregate and disaggregate level can help to sketch more precisely its nature and behaviour during the period under study. The total sales revenue and advertisement expenditure of selected companies operating in India presented in Figure I shows that total sales for the period under study are increasing continuously. The sales were at Rs.102746.7 crore in 1992/93 and it had rapidly increased to Rs. 927601.79 crore during the financial year 2006/07. This is being

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reflected by the 16.0 per cent ACGR of total sales revenue over the period of study (refer table IV). Further, it is apparent from figure I that during the initial period of study total advertising expenses of selected companies are increasing but later on during 1994/95 the trend was reversed and similar tendency was observed during 1997/98 to 2000/01 periods and after which it increased continuously till 2006/07. This fluctuation of advertisement expenses over the study period is confirmed by low ACGR of advertisement expenses, which is at the level of -0.6 per cent (refer table IV).

necessary to examine the advertisement expenditure in relation to the size of the company’s sales revenue. Accordingly, the share of advertisements expenses to the sales revenue of selected companies is presented in figure II, displays a downward trend except during 1997/98 to 1998/99. This may be due to the presence of companies which either due to its size or scale or degree of maturity are spending less on advertisements. The reasons like awareness among people regarding the availability of products, economies of scales and services may also be attributed to it.

Sales Revenue

Companies Type-1 Type-2 Type-3 Type-4 Total

ACGR 6.8 16.5 16.4 7.9 16.0

R2 .84 .99 .99 .69 .98

t- value 127.20* 235.60* 247.57* 71.22* 233.85*

Advertisement Expenses

Com-panies Type-1 Type-2 Type-3 Type-4 Total

ACGR 9.3 -1.1 -1.2 14.4 -.6

R2 .76 .03 .04 .95 .01

t- value 72.85* 58.81* 60.83* 118.88* 65.44*

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Source: Same as in the figure I

First part of figure III reflects the sales revenue behaviour of Type-1 companies i.e. companies whose sales revenue is less than Rs. 1000 crore. During 1992/93 the sales revenue of these companies were at Rs. 7994.96 crore and the sales revenue for these types of companies has increased continuously at an ACGR of 6.8 per cent (refer table IV). Further, the figure III infers that the sales revenue of Type-2 companies i.e. the companies, whose sales revenue is more than Rs. 1000 crore, is increasing monotonically and rapidly. The sales revenue was at Rs 94751.74 crore in 1992/93 and it has increased to Rs.903669.69 crore in 2006/07

Source: Same as in the table I. Note: (i) * t- values are significant at 1 per cent level of

significance.


The size of advertisement expenditure incurred by the companies itself may be important, but it is

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at the ACGR of 16.5 per cent (refer table IV), as these are the companies which are well established in the market. The high R2 and t-values are also significant which further validate the results. Figure IV shows that there is consistent increase in advertising expenses of Type-1 companies till 2001/02 but afterwards it decreased during 2002/03 but later on it started following the earlier pattern. The ACGR of advertisement expenses for the whole period under study is 9.3 per cent (refer table IV).


On the same lines, second part of figure VI reflects that there is consistent increase in the advertising expenses of Type-4 companies and ACGR for these type of companies is estimated at 14.4 per cent which shows that this class of companies are using advertisement expenses for increasing their sales revenue. At the same time, the first graph of figure VI gives the evidence of the volatile behaviour of the advertisement expenses of randomly selected manufacturing companies i.e. Type-3 companies due to which ACGR of advertisement expenses of Type-3 companies is -1.2 per cent. It infers that in case of Type-4 companies, continuous attention is being paid on the spending of advertisement expenditure, while in case of Type-3 companies this element is not considered regularly, however, the sales revenue of Type-3 companies are increasing continuously. It may be due to this reason that when companies are new they advertise heavily so as to establish some position in the market and to create some image in the minds of consumers. But when the companies are established in the market then they advertise just to give a reminder regarding their presence in the market. So, they advertise less but their sales increase due to economies of

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While in case of Type-2 companies 1992/93 to 2000/01, the erratic behaviour of advertisement expenditure can be noticed and it exhibits a negative growth (-1.1 per cent).However, still the growth rate of sales revenue of both types of companies is positive and significant and that can be due to the reasons such as the reputation of company, brand name, product quality, etc. On the other side, from the figure V, it is quite clear that there is consistent increase in sales of Type-3 companies during the period under study and ACGR of the same during this period is 16.4 per cent, while for Type-4 companies it was 7.9 per cent.


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Furthermore, the share of advertisement expenses to sales revenue for Type-3 and Type-4 companies revealed a very contrasting picture and same is presented in Figure VIII.

scale with the determinants like the reputation of the company, brand name, product quality etc. Advertising expenses growth rate in case of Type-3 companies is also negative and this, as said earlier, may be due to the reasons that these are well established firms and invested a lot for advertisements in the beginning and afterwards the growth of investment under this head become slower

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Source: Same as in figure I

Similarly, the share of advertisement expenses to total sales revenue for Type-1 and Type-2 companies is drawn in Figure VII, exhibits that the share of advertisement expenses to total sales revenue for Type-1 companies has remained almost constant till 1996/97. Afterwards it has shown an increasing trend at a slow rate till 2000/01, thereafter it has displayed, in general, downward trend. While on the other hand, share of advertisement expenses to sales for Type-2 companies is demonstrating a downward trend except during the time period between 1997/98 and 1999/00, afterwards it has remained constant. It may be because of this reason that Type-2 companies due to their size started enjoying benefits of economies of scale and the expenses on advertisement display a downward trend.

4.504.003.503.002.502.001.501.000.500.00

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Source: Same as in the figure I.

In case of Type-4 companies the share of advertisement expenses to total sales revenue has shown less volatility as compared to Type-3 companies. The reasons attributed for this may be, as discussed earlier, that many of the companies of Type-3 are established ones. Due to which they need to spend less consistently on advertisement that also just to give a reminder regarding their presence in the market for their customers.

The results of the regression for Model-1 i.e. in equation 1 reveal that the coefficient related to the advertising expenditure is significant at 1 per cent level of significance. From the results, it can be seen that there is a strong and positive relationship between sales revenue and advertisement expenses. The advertising elasticity coefficient 0.657 in equation 1 for 1992/93-2006/07 explains that 1 per cent increase in advertising expenditure leads to 0.657 per cent increase in sales. Positive and statistically significant intercept values reveal that

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even if the advertisement becomes zero, there will be some amount of sales. This means that factors other than advertising which determine the sales revenue like the competitors price, the reputation of the company, brand name, product quality, etc. become operative.

Model -1 Simple Fixed Effect Model

Ln Sit= a0 + b1 Ln Ait + uit Ln S it = 4.681 + 0.657Ln Ait ----------------------- Equation (1) (134.61)* (53.63)*

R=0.76, R2=0.58, N=134 Note: (i) t-values are given in the parentheses. (ii)* t- values are significant at 1 per cent level of significance

The dummy variable was introduced to test whether the relationship between advertising expenses and sales revenue is different for various categories of companies. The results in the equation 2 show that the coefficients of dummy variable are statistically significant revealing the existence of difference in relationship of advertising expenses and sales revenue between the Type-1 and Type-2 companies. The results show that the coefficient of determination, i.e., R2, has improved substantially in the case of dummy variable model. Higher coefficient for the dummy variable reveals that the intercept term for the Type-2 companies are much higher as compared to the Type-1 companies. The Type-2 companies sell more for the same level of advertisement as compared to Type-1 companies. This may be due to the reason that the Type-2 companies are better placed, as sales revenue are high, in respect of reputation, brand name and sales promotion as compared to Type-1 companies. Therefore, they sell more for a given level of advertising expenditure.

Model -2 Differentials Intercept Dummy Variable Model

Ln Sa) it = a0 + a1 D1 + b1 Ln Ait + uit

Ln Sales it = 4.391 + 1.578 D1 + 0.454LnA

it -------------------- Equation (2) (138.78)* (35.23)* (27.09)*R=0.83, R2=0.69, N=134

Ln Sb) it = a0 + a1 D2 + b1 Ln Ait + uit

Ln Sales it = 4.767 – 0.417 D2 + 0.652 Ln Ait -------------------- Equation (3) (127.34*) (-5.99)* (53.523)*R=0.77, R2=0.59, N=134 Note: (i) t-values are given in the parentheses. (ii)* t- values are significant at 1 per cent level of significance.

The equation 3 shows the result of intercept shift dummy variable model in the case of Type-3 i.e. manufacturing companies and Type-4 companies i.e. non-manufacturing companies, which includes a combination of agro, food, service, etc. kind of industries. The explanatory power of the model is satisfactory. All the coefficients are statistically significant at 1 per cent level. However, the coefficient of dummy variable is negative. The negative coefficient reveals that the intercept term of Type-4 is lower than that of the Type-3 companies, which implies that the Type-4 companies sell less for a given level of advertising expenses as compared to the Type-3 companies assuming that the slope coefficient is same for both the categories.

Model -3 Differential Slope Dummy Variable Model

a) Ln Sit = a0 + b1Ln Ait + b2Ln Ait*D1+ uit

Ln S it = 4.61 + 0.394Ln Ait +0.385Ln Ait*D1--- Equation (4) (144.42)* (22.60)* (19.66)*

R=0.81, R2=0.65, N=134b) Ln Sit = a0 + b1Ln Ait + b2Ln Ait*D2 +

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uit

Ln S it = 4.60 + 0.689Ln Ait – 0.215Ln Ait*D2 --- Equation (5) (136.77)* (54.29)* (-8.16)*

R=0.77, R2=0.61, N=134 Note: (i) t-values are given in the parentheses.

(ii)* t- values are significant at 1 per cent level of significance

The Model-3 is being estimated to study whether there is any divergence between various categories of companies with respect to the effectiveness of advertising expenses on sales revenue. The equation 4 gives the results of Model-3, which is based on the shift in the slope coefficient of the model. The results show that all the coefficients are statistically significant at 1 per cent level and the R2 is also satisfactory. The coefficient of dummy variable (D1) representing the shift in the slope variable is highly significant revealing that in the case of Type-2 companies, the advertising elasticity is higher as compared to the Type-1 companies, i.e., for a given level of advertising expenses, the increase in sales revenue is more for Type-2 companies than the Type-1 companies.

The advertising effectiveness is higher for Type-2 companies as they can afford to advertise more effectively in relation to the Type-1 companies. The absolute volume of advertising in the case of Type-2 companies is very high and a marginal change in advertising also found to be more effectual. The Type-2 companies can do better use of marketing expenses than the Type-1 companies and can make the advertising more result-oriented and avail the economies of advertising as they continue to advertise for a long period and deal in large volumes. Further, the above model i.e. Model-3 also presents the results of slope shift dummy variable model with respect to Type-3 and Type-4 companies through equation 5. All coefficients including the coefficients of dummy variable are statistically significant. The results are very interesting as the coefficient of dummy variable is negative. The negative coefficient reveals that the increase in sales as a result of increase in advertising expenses is less for Type-4 companies i.e. the effectiveness of

advertisements are more for Type 3 companies comparatively, which indicates the less effective use of advertisement expenses in terms of sales revenue for Type-4 companies as compared to Type 3 companies and Type 4 companies need to spend more advertisement expenses to have the same level of sales revenue. Due to which, they spend more on advertisement as compared to Type-3 companies. This is also verified by having a glance on Figure VI and Figure VII, which as discussed earlier portray an increasing tendency of advertisement expenses for these type of companies.

Conclusions and Implications

Advertisement is a persuasive communication which attempts to change or reinforces ones’ prior attitude and it is basically done not only to inform customers about products, rather it is a process, which further influences and persuades customers to purchase the product. The study is based on secondary data collected for the advertisement expenditure and sales revenue of 134 randomly selected companies operating in India The data is collected from PROWESS (2008) of Centre for Monitoring Indian Economy, New Delhi, India for the period from 1992/93 to 2006/07. In this study for Panel or Pooled data, Fixed Effect Model with and without dummy variables are used to evaluate the effectiveness of advertisement expenses on sales revenue. Further, annual compound growth rates and summary statistics are also estimated. The randomly selected companies for the present study are classified on the basis of sales revenues.

The study has found that the growth rate of sales revenue of Type-2 and Type-3 companies is highest in their respective categories notwithstanding the negative annual compound growth rates of advertising expenses of these two companies. The reason for increase in sales of these companies can be due to the factors such as the reputation of the company, brand name, product quality, etc. This is also reinforced by Model-1 and Model-2, which have demonstrated the presence of positive and statistically significant intercept values. It exhibits that factors other than advertising are also

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in operation and therefore, determine the sales revenue of company besides the advertisement expenses. The Type-4 companies i.e. non-manufacturing companies sell less for a given level of advertising expenses as compared to Type -3 companies i.e. manufacturing companies. It infers that Type 4 companies are less efficient in making utilisation of its advertisement expenses as compared to Type 3 companies.

The findings of the present study indicate the existence of complex relationship between advertisement expenses and sales revenue of the companies. How much advertisement expenses have to be incurred depends to a large extent on the nature and size of industries i.e. whether one is operating a large scale firm/small firm or manufacturing/non-manufacturing firm. The companies which are operating at a large scale can better utilise their marketing expenses due to the economies of scale and hence can be more result oriented for a longer period of time. While for companies functioning in non-manufacturing sector the effectiveness of advertisements is less. So, these kind of firms need to acknowledge that increase in advertisement expenses may not bring the same degree of sales revenue to them, which can be for organisations operating in manufacturing sector. It is to be taken into consideration that advertisement expenses is not the only factor to determine sales revenue of an organisation. Advertisement expenses are one of the various factors, though crucial, which determine sales of any company through increasing popularity of products/services among customers. So, the organisations need to take care of this factor, while formulating their strategies relating to the spending of advertisement expenses.

It can be wrapped up by stating that advertisement is considered as one of the most important medium of communication influencing the organisations’ performance in more than one ways. But its influential role may be suppressed by the operation of other factors which also seeks equal attention at the time of framing of any sales promotion policy.

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Annexure - I List Of Randomly Selected 134 Companies Of Indian

Corpotrate Sector3M INDIA LTD.1.

ABHISHEK INDUSTRIES LTD.2.

ANIK INDUSTRIES LTD.3.

APEEJAY TEA LTD.4.

APEEJAY SHIPPING LTD.5.

ASIAN ELECTRONICS LTD.6.

ASSAM CO. LTD.7.

ASSOCIATED STONE INDS. 8.

(KOTAH) LTD.

AVAYA GLOBALCONNECT LTD.9.

B P L LTD.10.

BHARAT BIJLEE LTD.11.

BHARAT FERTILISER INDS. LTD.12.

BHARAT GEARS LTD.13.

BHARAT HOTELS LTD.14.

BIRLA POWER SOLUTIONS LTD.15.

BIRLA PRECISION 16.

TECHNOLOGIES LTD.

BIRLA TRANSASIA CARPETS 17.

LTD.

BIRLA V X L LTD.18.

BOMBAY BURMAH TRDG. 19.

CORPN. LTD.

BOMBAY CYCLE & MOTOR 20.

AGENCY LTD.

BOMBAY DYEING & MFG. CO. 21.

LTD.

BOMBAY PAINTS LTD.22.

BRABOURNE ENTERPRISES LTD.23.

CHLORIDE INTERNATIONAL 24.

LTD.

CONSOLIDATED FINVEST & 25.

HOLDINGS LTD.

ELECTRONICA MACHINE TOOLS 26.

LTD.

ELECTROTHERM (INDIA) LTD.27.

EUROTEX INDUSTRIES & 28.

EXPORTS LTD.

EVEREADY INDUSTRIES (INDIA) 29.

LTD.

FOSECO INDIA LTD.30.

GANDHI SPECIAL TUBES LTD.31.

GODREJ AGROVET LTD.32.

GODREJ INDUSTRIES LTD.33.

GREAVES COTTON LTD.34.

GULF OIL CORPN. LTD.35.

H E G LTD.36.

H M T (INTERNATIONAL) LTD.37.

H M T BEARINGS LTD.38.

H M T LTD.39.

HARRISONS MALAYALAM LTD.40.

HINDUSTAN BREWERIES & 41.

BOTTLING LTD.

HINDUSTAN COMPOSITES LTD.42.

HINDUSTAN DORR-OLIVER LTD.43.

HINDUSTAN EVEREST TOOLS 44.

LTD.

HINDUSTAN ORGANIC 45.

CHEMICALS LTD.

HINDUSTAN SANITARYWARE & 46.

INDS. LTD.

HINDUSTAN TIN WORKS LTD.47.

HYDERABAD INDUSTRIES LTD.48.

I F B INDUSTRIES LTD.49.

INDIAN SUCROSE LTD.50.

J C T LTD.51.

JAY SHREE TEA & INDS. LTD.52.

JINDAL DRILLING & INDS. LTD.53.

MAHINDRA UGINE STEEL CO. 54.

LTD.

MILKFOOD LTD.55.

NAHAR INVESTMENTS & 56.

HOLDING LTD.

NAHAR SPINNING MILLS LTD.57.

NOVARTIS INDIA LTD.58.

OSWAL CHEMICALS & 59.

FERTILIZERS LTD.

PANASONIC BATTERY INDIA 60.

CO. LTD.

PANASONIC HOME APPLIANCES 61.

INDIA CO. LTD.

RAJSHREE SUGARS & 62.

CHEMICALS LTD.

RAYMOND APPAREL LTD.63.

RELIANCE CHEMOTEX INDS. 64.

LTD.

SANDESH LTD.65.

SHARP INDIA LTD.66.

SINGER INDIA LTD.67.

SUPER FORGINGS & STEELS 68.

LTD.

SUPER SALES INDIA LTD.69.

SUPER SPINNING MILLS 70.

LTD.

SUPERTEX INDUSTRIES LTD.71.

SURYAJYOTI SPINNING MILLS 72.

LTD.

SURYALAKSHMI COTTON MILLS 73.

LTD.

SURYALATA SPINNING MILLS 74.

LTD.

SURYAVANSHI SPINNING MILLS 75.

LTD.

TATA COFFEE LTD.76.

TATA REFRACTORIES LTD.77.

TAYO ROLLS LTD.78.

UNIVERSAL CABLES LTD.79.

A B B LTD.80.

A C C LTD.81.

AGRO TECH FOODS LTD.82.

APAR INDUSTRIES LTD.83.

APOLLO TYRES LTD.84.

ASIAN PAINTS LTD.85.

B E M L LTD.86.

BHARAT ELECTRONICS LTD.87.

BHARAT FORGE LTD.88.

BHARAT HEAVY ELECTRICALS 89.

LTD.

BHARAT PETROLEUM CORPN. 90.

LTD.

BIRLA CORPORATION LTD.91.

BRITANNIA INDUSTRIES LTD.92.

CADBURY INDIA LTD.93.

CASTROL INDIA LTD.94.

CENTURY ENKA LTD.95.

CENTURY TEXTILES & INDS. 96.

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LTD.

CIPLA LTD.97.

CUMMINS INDIA LTD.98.

DABUR INDIA LTD.99.

ELECTROSTEEL CASTINGS 100.

LTD.

EXIDE INDUSTRIES LTD.101.

FORCE MOTORS LTD.102.

GLAXOSMITHKLINE 103.

CONSUMER HEALTHCARE

LTD.

HERO HONDA MOTORS LTD.104.

HINDALCO INDUSTRIES LTD.105.

HINDUSTAN PETROLEUM 106.

CORPN. LTD.

HINDUSTAN UNILEVER LTD.107.

HINDUSTAN ZINC LTD.108.

LTD.

R S W M LTD.122.

RANBAXY LABORATORIES 123.

LTD.

RAYMOND LTD.124.

RELIANCE ENERGY LTD.125.

RELIANCE INDUSTRIES LTD.126.

SINTEX INDUSTRIES LTD.127.

SURYA ROSHNI LTD.128.

TATA CHEMICALS LTD.129.

TATA COMMUNICATIONS 130.

LTD.

TATA MOTORS LTD.131.

TATA POWER CO. LTD.132.

TATA STEEL LTD.133.

TATA TEA LTD134.

I T C LTD.109.

INDIAN OIL CORPN. LTD.110.

ISPAT INDUSTRIES LTD.111.

JINDAL SAW LTD.112.

KIRLOSKAR BROTHERS LTD.113.

MAHANAGAR TELEPHONE 114.

NIGAM LTD.

MAHINDRA & MAHINDRA 115.

LTD.

MARUTI SUZUKI INDIA LTD.116.

MICRO INKS LTD.117.

N T P C LTD.118.

NAHAR INDUSTRIAL 119.

ENTERPRISES LTD.

NESTLE INDIA LTD.120.

PHILIPS ELECTRONICS INDIA 121.

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