Analysis and Interpretations

CHAPTER - IV

ANALYSIS AND INTERPRETATIONS

An Overview of Synthetic Gem Industry

An over view of synthetic gem Industry was made with special reference to actual conditions of the manufacturers, labourers and traders prevailing in the industry. This overview emphasizes the financial and marketing conditions of the manufacturers and traders. The socio economic conditions of the workers were also dealt with in detail.

Finance Analysis

The capacity to invest money in any business affects its performance. The ability or the inability of the person dealing with the business affects it either positively or negatively. The synthetic gem industry business also is not an exception. Here, there are two categories of peoples involved. They are traders who buy the stones from the manufacturers and sell them to various types of buyers. The other ones are manufacturers who produce the stones which are sold to traders in lots, who in turn market them. The role of investment or finance which affects the business of the trader and manufacturer is analyzed here:

(1) Traders: The range of investment for traders is anywhere between four to ten lakhs. They always aspire to get maximum profit out of their investment and get back their investment as soon as possible.

133 Main source of funds for these traders are not financial institutions or banks. Most of the traders have their own funds. They don‟t want to depend on any financial institutions for a good reason i.e., they don‟t want to pay interest.

Till last two decades, most of the traders had only cash sales and not credit sales. So, they always managed to do the trade with their own funds and never felt the need to borrow money from the lenders. Now, there is a different situation. The relatives (i.e. in- laws) and one time employees or workers with little knowledge have also preferred to come to this business. Increase in the numbers and ever growing competition also plays a vital role in introducing credit sales.

Earlier traders used to buy finished stones from manufacturers on a lot basis system, which contained all types, sizes and nature of stones. As there was always sa heavy demand for the stones they were compelled to have a good stock of the stones which meant good or heavy investment.

Now as the scene has changed, traders don‟t go for heavy or lot purchase. They try to buy only the required amount of stones and sell them immediately. Thus, the need to invest heavily by the traders has vanished. The burden of investment has shifted to the manufacturers in the form of storage value which has become high for them.

Traders also prefer to bear variable costs rather than bearing the fixed costs, which saves their interest on borrowed capital and nil investment for storage gives them more profit.

(2) Manufacturers: As the majority manufacturers are poor people they don‟t have their own funds and are totally dependent on friends,

134 relatives and financial institutions. They need to invest on installation of machineries, give advance to get hold of a working place and workers and purchase raw-materials and accessories. Also they need to put aside a portion of their investment as a working capital for day-to-day requirements.

Once installation work is established, manufacturers don‟t need much money for investment, because the office and administration expenses are very meager. Much of the investment will go to raw- materials for synthetic stones and payment to labourers.

One important factor to be considered here are most of the bankers does not prefer to lend money to synthetic gem industry because of the low-returns to the manufacturers. Manufacturers are forced to bear the brunt of the financial institutions (private) which charge heavy interests. The short term high interest rate loans doesn‟t permit the manufacturers to run the industry peacefully.

Remedy suggested is Banks should come forward to lend to the manufacturers of gem industry with long term, low interest rate loans. Many factors like non availability of loan, high interest, credit sales, rejection of stones, low profit make the manufacturers earn very less margin. This is the main reason for the deterioration of this industry.

Marketing Analysis

Any product manufactured has to find its way to the buyers or customers. The product must fulfill the need and satisfaction of the customers. Synthetic gem industry also is not an exception. Marketing is a continuously evolving and growing process, which has to fit or suit the

135 demands of the time and period of the industry. The product in the synthetic gem industry finds its way to the customers from manufacturers to traders and from traders to the ultimate users of the stones. Manufacturers and traders have different trends and ways of marketing these stones.

The size, colour, cut and types of stones also determine the factors of marketing techniques adopted each by the manufacturers and traders. Place of marketing, the distance of marketing place from the manufacturing units and their transportation and cost factors also play a significant role in this area.

Difference nature of marketing techniques adopted by the manufacturers and traders are discussed below:

(1) Manufacturers: Manufacturers are the ones who procure raw- materials for the stones and then cut, cone, facet and polish then in the units where they are installed.

Tiruchirappalli District in Tamilnadu State is the hub of synthetic gem stones industry. In and around Trichy there are many small units of installations where the stones are manufactured.

Tiruchirappalli has a very big bazaar known as “Diamond Bazaar” where all types, kinds, shapes, sizes and colours of synthetic gem are traded. Even from Kerala people come to Trichy to market their stones.

Synthetic gems are of two types. One is Imitation and another one is American Diamonds. Imitation stones are marketed by manufacturers in Numbers, whereas American Diamonds are done in Carats in weights (one carat is equal to 20 mg. or five carats are equal to one gram.). Hundred

136 imitation stones up to 20 Jallads (allocation by mesh) are priced. Sometimes, if the size is more than 20 jallads it is weighed in carats and priced accordingly.

Manufacturers adopt piece rate system for producing imitation stones and trade them in 100s. It is a peculiar system adopted for American diamonds manufacturing. They procure raw-materials (Boules or crackles) in kilograms and give them for cutting in kilos. But for coning, faceting and polishing, they adopt piece rate basis. At last for marketing, they go for carat measurements.

While marketing stones, manufacturers use two types of mesh, one each for Imitation Stones and American Diamonds. In both the cases traders are the beneficiaries.

Generally, the manufacturers pack their stones in lots according to their specifications and quality. But once in the market they are unable to sell them and earn profit to their satisfaction (aspiration). The aspirations and expectations of both the manufacturers and traders rarely match. Many a time manufacturers sell the products at the whims and fancies of the traders and loose in the bargain. Their earning thus fluctuates and it never becomes a stable one.

Every time when manufacturers arrive in the bazaar they have to look for traders, for only a few manufacturers have regular traders to sell their stones.

In the end after wandering here and there to find suitable traders to sell their produce they at times under stress forego their profit and sell them at whatever cost they are able to get. There are traders who deal

137 with only high quality stones and give good price to the manufacturers. In these cases efficient manufacturers make a good profit.

Some inefficient manufacturers who are unable to differentiate the quality of stones put them in assortment lot and try to cheat the traders. But the shrewd traders never fall for such trap and in the bargain manufacturer‟s end up losing their businesses.

Another type of dealing is a rule in the market. Imitation stones are segregated size wise ( for example : below 6 jallad stones, 6 – 10 jallad stones, 11 – 13, 14 – 15 jallad stones). But the American Diamonds stones are segregated by -4J, -6J, -8J, -10J, 11 – 13 J, 14 & 15J, etc. Based only on the said sizes stones are priced between the manufacturers and traders.

Red or White colour Imitation Stones of size 6 J as well as 10J are evenly priced. Some scrupulous traders further segregate then as 6, 6 1/4, 6 ½, 6 ¾, 7, 7 ¼, 7 ½, 7 ¾, and 8 Jallads and sell them for different prices to get more profit.

During festivals like Deepawali, Pongal, New Year, Tamil Month Aadi etc. traders create artificial excess supply of stones in the market. i.e., the traders show as if there is no demand for stones and try to grab the stones from the manufacturers at cheaper rate. Here, the manufacturers suffer a lot especially during the festivals seasons. All of them were happy either workers or traders except manufacturers.

Even after the deal is over between the manufacturer and trader, still the trader can choose to reject some stone or bargain them for lesser price or return them.

138 Manufacturers are always willing to give good wages and remuneration to the workers in their installed units. But the prevailing unfavorable conditions in the market frustrate them and slowly manufacturers are losing interest in the business thus causing a deteriorating industry.

(2) Traders: Synthetic gems find their way to the traders from manufacturers. Most of the traders are Saits, Telugu, Tamils and Saurashtra people who market them to the needy because of their well established brand name of their stones and shops.

Tiruchirappalli market had almost 216 registered and innumerable unregistered traders engaged in synthetic gem industry. Now there are only less than 100 registered traders engaged in this field.

Selection process of stones is a hectic task for any trader. After buying qualitative stones in required numbers they match them with their brand name. The traders are known in the market not by their name but by their brand name established over a period in the industry. This they do it from the assorted lot of stones. They are very specific and meticulous in selecting stones either by themselves or with the help of skilled workers for they do not want to spoil their hard earned Brand Name.

Once the selection process is over, they put or pack the stones in specially designed and printed paper packets with cloth and cotton inside to wrap and protect. These packets are used for quality stones only. All relevant information namely number of stones, brand name and specific name for the stones, quality, weight etc. about the stones are printed on these packets. Either Imitation or American Diamond stones weighing up to 20 jallads numbering about 50 stones are put in one packet.

139 Packed stones are ready to be sold. They go places outside Tiruchirappalli and sell them directly to the wholesalers and jewellers. They realize better profit in this type of selling. These trips are known as “Going on Line”. While going for “Going on Line” traders reach places like Villuppuram, Erode, Salem, Madurai, Tirunelveli, Coimbatore, Chennai and other parts of Tamilnadu. They occur even in Union territory of Pondicherry, states like Karnataka, Andhra and other North, East, West States of India. Most of the small sized stones sold in Tamilnadu, Andhra and Karnataka are preferably studded in Gold ornaments.

These sealed packets are sold to the major jewellery manufacturers and stone dealers throughout the country. Each and every trader has his own pricing system and accordingly they sell them either for cash or credit. The dealers or agents are paid commission or brokerage while the dealing is made by the traders.

Traders are forced to have a ready stock of every type of stone for sale at any given time. As manufacturers also not able to provide the acquired type of stones at short notice traders are forced to pile up the stock with huge capital investment.

When going for on line trade, traders often face many difficult situations. Though most of the time, they are able to cater to the need of the buyers, many a time their stones also get rejected because of change in the demand of stones, size, colour and shape wise.

Traders face transport problems like any other business man. Booking train tickets, boarding and lodging problems reaching on time at

140 times cause loss of business to the traders. They wander here and there, looking for buyers which are highly stressful for the traders.

Credit sales are another important factor which affects the business of the traders. Cash dealings have become the things of the past. In addition to paying brokerage or commission to the dealers they bear the brunt of credit sales where the payment occurs after more than three months period.

Credit sales also results in cheating. People who buy the stones on credit abscond with stones paying only part of the amount. This results in heavy loss to the traders.

If a traders is unable to pump more and more money in the business for maintaining heavy stock the dealers switch to other traders instead of the regular ones which many a time unsettles the business of the traders.

Social, Political, Natural calamities as well as Commercial problems also pay a vital role either in the making or marring the Synthetic Gem Industry. But the traders in general one well versed in their trade and by overcoming all the problems listed above they still keep this industry alive.

Socio-economic conditions of the workers

The prevailing socio economic working conditions of the workers of the Synthetic Gem Industry are very pathetic. It is not even comparable with the conditions of other labourers or workers in any field. For example workers in beedi companies, petty shops, teashops, cookies, daily wage earners, watchmen, security guards, and catering workers are all better off than the Synthetic Gem Industry workers.

141 In this industry ratio of female to male is almost equal in urban areas whereas in rural areas females out do the males in number. Now this industry employs workers who are more than 20 years old. Earlier it had child workers. Even low class family parents encouraged their children to opt for this industry than to go for educational institutions or other work. They thought it to be good income potential source for their family. Majority of the workers are illiterate and have education only up to 10th standard. Now the earning is not there because of the import of Chinese stones in large numbers.

They are paid only on piece rate basis though their working hour are not fixed and work at any time as they wish. Their working environment is very congested and polluted. They face health hazards when do any nature of synthetic gem work. The most important one is deteriorating vision which compels them to wear eye glasses. Though they work long hours in squat position their wages do not match their needs of ever day life. They hardly make 50 to 70 rupees per day.

They depend on loans from Local Money Lenders who charge exorbitant rates of interest. There are many cases of workers who have run away from the lenders leaving behind their family. This in turn has even put the manufacturers in a tight spot because they could not recover the advances paid to the workers by them.

At times most of workers turn untrustworthy because of their low income earning capacity and put the manufacturers to face lot of problems like losing the dependable working force, non recovery of advances paid to them, improper work ethics etc. These situations make the manufacturers incur recurring losses.

142 The workers are indirectly affected by the unstable Gold Pricing, Liberalization and Globalization Policy of the Government, non- adaptation of modern technology, import of Chinese stones, etc.

The workers of synthetic gem industry don‟t have any access to Government Assistance. They are almost non-existent in the eyes of the Government.

There are some skilled workers who have interest and involvement in the work but don‟t have the opportunity to exhibit their skills because of low wages.

The industry still has hope for retrieval of its lost shine. Only thing needed to be done is, the workers must be paid proper remuneration. In such a situation, even the migrated workers will be ready to return to the industry. They are willing to return because of this industry„s specific characteristics and facilities such as flexibility in working times, portable nature, readily available advance monetary benefits from the manufacturers at any given time, getting wages in advance for the work to be done, going on leave at their will, etc. It is a rarity in any other industry.

For the purpose of analysis and interpretation of collected data, the following statistical tools were applied to draw valuable solutions. They are: (A) Percentage Analysis

(B) Factor Analysis

(D) Chi-Square Test

(E) Correlation Analysis

143 A. Percentage Analysis

(i) Demographic Profile of Synthetic Gem Manufacturers:

The need for the demographic factors of the synthetic gem manufacturers served as a catalyst which has a direct bearing on the performance of the synthetic gem industry. The demographic factors of the synthetic gem manufacturers were studied on parameters, such as gender, age, marital status, educational qualification and nature of family. A careful study was carried out on these parameters which led to the general understanding of how efficiently the synthetic gem manufacturers run and manage the synthetic gem industry. So, this analysis was carried out to understand the efficiency put in by synthetic gem manufacturers in running their firms which ultimately affects the performance.

Gender: The gender of the synthetic gem manufacturers plays an important role in determining their status in the society. The gender involves the roles, responsibilities, constraints, opportunities and needs of male and female among manufacturers of synthetic gem industry. The analysis of gender led to have a better understanding of social background of synthetic gem manufacturers. Hence, in this study, gender classification is made.

Table - 4.1

Gender-wise Classification of Sample Synthetic Gem Manufacturers

Gender No. of Respondents Percent

Male 183 96.3 Female 7 3.7 Total 190 100 Source: Primary Data

144

3.7%

96.3%

Male Female

The synthetic gem manufacturers consist of 96.30 percent male and 3.70 percent female. Hence, it is generalized that majority of the synthetic gem business are owned by male respondents and only a small portion of the manufacturers are female

Age: Age is an important demographic variable which not only determines an individual‟s physical and mental maturity but also depicts his or her life experiences. It determines whether one is economically active or dependent upon others.

Table - 4.2

Age-wise Classification of Sample Synthetic Gem Manufacturers

No. of Respondents Age Percent 21 - 30 years 14 7.4 31 - 40 years 44 23.2 41 - 50 years 116 61.1 51 and above 16 8.4 Total 190 100

Source: Primary Data

145

16 14 44

116

21 - 30 years 31 - 40 years 41 - 50 years 51 and above

The age of synthetic gem manufacturers consist of 61.10 percent, who belongs to 41-50 years age group, followed by 23.20 percent to 31 to 40 years, 8.40 percent to 51 and above years and 7.40 percent to 21- 30 years age group. From the above data, it is inferred that majority of the synthetic gem manufacturers are in the age group of 41-50 years.

Marital Status: In Indian society, marriage is supposed to be a religious obligation. In social context, it is the prelude to the family formation, expansion or even bifurcation. After marriage, there is a transition in the status of men and women with attendant rights and obligations. It is an important event in one‟s life. It influences the style of living and also the attitude, disposition and commitment towards work.

Table - 4.3

Marriage-wise Classifications of Sample Synthetic Gem Manufacturers

Marital status Frequency Percent Married 183 96.3 Unmarried 7 3.7 Total 190 100

Source: Primary Data

146

183

Married Unmarried

The above table (No.4.3) revealed that, out of the total respondents, 183 of them were married, constituting a significant percentage of 96.30 and only a negligible part of them are unmarried, constituting a meager percentage of 3.70. So, it is revealed that majority of the respondents are married.

Educational Qualification: The educational qualification of the synthetic gem manufacturers ultimately has an influence over the performance. It not only widens knowledge of synthetic gem manufacturers but also provide them courage and confidence in their task. Education helps the person to adopt rational and scientific approach in solving complex problems. Education has a positive impact on social life and quality of life and vice versa with literacy.

147 Table 4 .4

Education-wise Classification of Sample Synthetic Gem Manufacturers

Educational Qualification No. of Respondents Percent

I std. - SSLC 154 81.1 HSC 15 7.9 Under Graduation 15 7.9 Post-Graduation 6 3.2 Total 190 100

Source: Primary Data

I std. - SSLC

HSC Under Graduation

Post-Graduation

From the above table it is observed that 81.10 percent of the synthetic gem manufacturers had varied level of education from 1st standard to S.S.L.C. 7.90 percent each up to HSC and under graduation and only 3.20 percent were post graduates. So, it is inferred that majority of the synthetic gem manufacturers had the educational qualification up to the level of S.S.L.C.

148 Nature of Family: The family background plays an important role in moulding the behaviour of its members. The family provides the recognition and security for the individuals and also serves as their identity. The living arrangements are very crucial for the socio-economic status of a person.

Table – 4.5

Family-wise Classification of Sample Synthetic Gem Manufacturers

Nature of family No. of Respondents Percent

Nuclear 117 61.6 Extended 73 38.4 Total 190 100

Source: Primary Data

Extended , 73 Nuclear , 117

Nuclear Extended

The nature of family of the synthetic gem manufacturers consist of 61.60 percent nuclear and 38.40 percent are extended type of family. Hence, the majority of the synthetic gem manufacturers are considered to be of nuclear type family.

149 (ii) Performance of Manufacturers:

Years of experience in synthetic gem business: The performance of synthetic gem manufacturers depends on the years of experience put in by them on their business. The performance of the synthetic gem manufacturers enhances proportionately with their field experience.

Table – 4.6

Experience-wise Classification of Sample Synthetic Gem Manufacturers

Years of experience No. of Respondents Percent

Below 15 36 18.9 16 - 20 44 23.2 Above 20 110 57.9 Total 190 100 Source: Primary Data

19%

58% 23%

Below 15 16 - 20 Above 20

The synthetic gem manufacturers of 57.90 percent have had the field experience of more than 20 years, followed by 23.20 percent in the category of 16 – 20 years of experience, 18.90 percent were 11-15 years of experience. So, it is observed that majority of the respondents have the field experience of more than 20 years.

150 Sources of funds - Manufacturers: Manufacturers mainly run their businesses by using borrowed funds. It is one of the reasons for their low profit. In addition to establishing the synthetic gem unit, manufacturers struggle to maintain their working capital due to credit sales, rejection of goods, under estimated quality of their produce, administration commitments, etc. In such a situation, they do not have any valuable things or properties to pledge for loan at low rate of interest.

Table – 4.7

Sample Sources of Funds of Manufacturers

Sources No. of Respondents Percent Owned 32 16.8 Borrowed 106 55.8 Both owned and borrowed 52 27.4 Total 190 100

Source: Primary Data

52 32

106

Owned Borrowed Both owned and borrowed

It is illuminated that, 55.8 percent of manufacturers mainly relied on borrowed funds and 27.4 percent of manufacturers utilize both borrowed and owned funds. Only 16.8 percent of manufacturers rely on their own funds.

151 Table-4.8

Sample Borrowings of Synthetic Gem Manufacturers

Sources No. of Respondents Percent Nil 32 16.80 Bank 12 6.30 Finance Company 47 24.80 Money Lenders 76 40.00 Friends and Relatives 23 12.10 Total 190 100.00

Source: Primary Data

23, 12% 32, 17% 12, 6% 76, 40% 47, 25%

Nil Bank Finance Company Money Lenders Friends and Relatives

It is interpreted from the above table that 40.0 percent of manufacturers wholly relied on money-lenders. Next, 24.80 percent of manufacturers relied on finance companies. Only 12.1 percent and 6.3 percent of manufacturers borrow funds from friends and relatives and the bank respectively.

152 Problems in Production: Synthetic gem manufacturers are facing lot of problems in the process of production because of the influence of so many factors. They admit themselves about the existence of problems but still go on producing because of their commitment and involvement in the field.

Table – 4.9

Sample Opinions on Problems in Production

Opinion No. of Respondents Percent Yes 172 90.5 No 18 9.5 Total 190 100

Source: Primary Data

180 160 140

120 100 80 60 40 20 0 Yes No

In the process of production of synthetic gem 90.50 percent of the respondents are admitting that there are vital problems in their business, while 9.50 are giving the opinion of smooth running of their production process without any problem.

153 Type of Industry: The type of industry affects the performance of synthetic gem manufacturers in a considerable way. It is felt among the synthetic gem manufacturers those who own a production unit gives an indication of the status symbol.

Table – 4.10

Sample Type of Industry

Industry No. of Respondents Percent Cottage 170 89.5 Small Scale Industry 20 10.5 Total 190 100

Source: Primary Data

180

160

140

120

100

20 0 Cottage Small Scale Industry

Of the total respondents, 89.50 percent possess own cottage production unit and only a meager percent of 10.50 possess small scale industry type of production unit. Hence, it is inferred that majority of synthetic gem manufacturers are the owners of the cottage industry.

154 Usage of raw-materials in synthetic gem business: The performance of the synthetic gem manufacturers and their usage of raw materials are proportionately or disproportionately related. In other words, the performance rests on how efficiently and effectively they utilize the raw materials and not the size of the production unit.

Table – 4.11

Sample Usage of Raw-materials

Raw Materials No. of Respondents Percent Boules 7 3.7 Cutting Stones 94 49.5 Faceting Stones 89 46.8 Total 190 100

Source: Primary Data

Boules Cutting Stones Faceting Stones

The cutting stones used by majority of synthetic gem manufacturers constitute the highest of 49.50 percent, followed by 46.80 percent of faceting stones, but boules are used by a meager percent of 3.70 only. So, it indicates that majority of the respondents engage in production of cutting stones in their production unit.

155 Nature of manufacture: The nature of manufacture plays a pivotal role to engage them in selling their finished product as per the needs and expectations of the traders. As, the synthetic gem manufacturers are generally lacking adequate educational and informational expertise, they engage in particular nature of manufacturing with an aim of reaping a maximum profit in their synthetic gem business.

Table – 4.12

Sample Nature of Manufacturing

Nature No. of Respondents Percent Cutting and Faceting 7 3.7 Coning and Faceting 22 11.6 Polishing only 89 46.8 Coning, Faceting and Polishing 72 37.9 Total 190 100

Source: Primary Data

100 80 60 40 20 0 S1 Cutting Coning Polishing and and Coning, only Faceting Faceting Faceting and Polishing

46.80 percent of the synthetic gem manufacturers are engaged in polishing task only, followed by 37.90 percent in coning, faceting and polishing work, 11.60 percent in coning and faceting and only 3.70 percent of the respondents are engaged in cutting and faceting work. Hence, it is concluded that majority of the respondents are engaged in the task of polishing only.

156 Design of manufacture: The performance of synthetic gem manufacturers and design of their manufacture of finished product are inter-related. The design of manufacture determines the demand for the product and also reduces the risk of normal loss to the synthetic gem manufacturers to a significant extent. This not only reduces the risk of loss but also enhances the overall performance of synthetic gem manufacturers over a period of time.

Table – 4.13

Sample Design of Manufacturing

Design No. of Respondents Percent Round 153 80.5 Square 20 10.5 Square and Rectangle 12 6.3 Others 5 2.7 Total 190 100

Source: Primary Data

200 150

100 Others 50

0 Round 1

Round Square Square and Rectangle Others

The data reveals that 80.50 percent of the synthetic gem manufacturers are using round design, but 10.50 percent are using square and 6.30 percent are using square and rectangle. But, only 2.70 percent of the respondents are engaged in other type of design.

157 Kinds of synthetic gem stones manufactured: Kinds of synthetic gem stones manufactured is also an important factor on the part of synthetic gem manufacturers in fulfilling the specifications made by the traders and accomplishing their objectives of earning reasonable profit by satisfying the expectations of customers.

Table – 4.14

Sample Kinds of Synthetic Gemstones Manufactured

Kinds No. of Respondents Percent Imitation White 7 3.7 Imitation Red 66 34.7 Imitation White and Red 12 6.3 A.D. White 54 28.4 A.D. White and Imitation Red 14 7.4 Emerald Green 6 3.2 A.D. Assorted Colours 13 6.8 A.D. Colours Carat Size 18 9.5 Total 190 100

Source: Primary Data

40 30 20 10 0 Imitation White Imitation White and A.D. White and A.D. Assorted Red Imitation Red Colours

158 The above table (No. 4.14) shows that 34.70 percent of the synthetic gem manufacturers are manufacturing red imitation stones and 28.40 percent manufacture A.D. white. A.D. colour carat size is manufactured by 9.50 percent, A.D. white and imitation red by 7.40 percent, A.D. assorted colours by 6.80 percent and imitation white and red by 6.30 percent. Imitation white kind is manufactured by 3.70 percent and finally the least percent of 3.20 manufacturers is manufacturing emerald green kinds.

Method of manufacture: Method of manufacture is also an important factor on the part of synthetic gem manufacturers in order to accomplish their objectives of earning maximum profit and also to fulfill the expectations of customers.

Table – 4.15

Sample Method of Manufacturing

Methods No. of Respondents Percent Single Cutting 81 42.6 Double Cutting 68 35.8 Triple Cutting 12 6.4 Single and Double Cutting 23 12.1 Double and Triple Cutting 6 3.1 Total 190 100

90 80 70 60 50 40 30 20 10 0 Single Cutting Double Triple Cutting Single and Double and Cutting Double Triple Cutting Cutting 159 The method of manufacture of synthetic gems shows in the above table (No. 4.15) that 42.60 percent of the synthetic gem manufacturers are adapting single cutting, but only 35.80 percent are adapting double cutting. Single and double cutting is 12.10 percent, Triple cutting is 6.40 percent and finally the least percent of 3.10 percent is for the method of double and triple cutting.

Type of wage system: The wage system affects the performance of synthetic gem manufacturers in a considerable way. It is felt among the synthetic gem manufacturers that type of wage system was adapted in the following manner.

Table – 4.16

Sample Type of Wage System

Type No. of Respondents Percent Piece rate system 175 92.1 Time rate system 15 7.9 Total 190 100

Source: Primary Data

Piece rate system Time rate system

Of the total respondents, 92.10 percent of the respondents are paying wages to their workers by way of piece rate system, while only 7.90 percent are paying wages under time rate system. Hence, it is inferred that majority of synthetic gem manufacturers are practicing only piece rate system.

160 Mode of Payment of Wages: The performance of the synthetic gem manufacturers and the mode of payment of wages to their workers are proportionately or disproportionately related. In other words the performance rests on how efficiently and effectively the payment of wages is discharged.

Table – 4.17

Sample Mode of Payment of Wages

Mode No. of Respondents Percent Daily 14 7.4 Bi-Weekly 36 18.9 Weekly 140 73.7 Total 190 100

Source: Primary Data

140 120 100

0 Daily Bi-Weekly Weekly

Majority of the synthetic gem manufacturers are making weekly payment of wages which constitute 73.70 percent, followed by 18.90 percent paying bi-weekly wages and daily wages percent constitute only 7.40 percent.

161 Imitation Stones produced per week: The performance of synthetic gem manufacturers depend on the total number of stones produced per week. It determines the strength of each manufacturing unit. The production of stones relates only to the Imitation type of manufacturing. Imitation is nothing but where in the production of stones the raw material used is Boules. It includes white, red, blue, green colours.

Table – 4.18

Samples of Imitation Stones Produced per Week

Production per week(in Nos.) No. of Respondents Percent Not Produced 112 58.9 0 – 4000 28 14.7 4001 – 8000 43 22.6 8001 - 12000 7 3.8 Total 190 100

Source: Primary Data

120 100 80 60 112 40 43 20 28 7 0 Not 0 - 4000 4001 – 8001 - Produced 8000 12000

From the table it is clear that 58.90 percent of the synthetic manufacturers do not produce imitation stones. 22.60 percent of them produce 4001-8000 and 14.70 percent 1-4000. Only 3.70 percent of the manufacturers are producing 8001-1200 imitation stones per week.

162 Production of American Diamonds per week: The performance of synthetic gem manufacturers also depends on the total number of carats produced per week. The American Diamonds relates to other than the Imitation type of manufacturing. American Diamond is nothing but where the raw material used is Crackles. Crackles include colours like white, red, blue, green, black, honey, orange, yellow, pink, etc.

Table-4.19

Sample of Production of American Diamonds per Week

Production per week (in Carats) No. of Respondents Percent

Not Produced 78 41.1 1 – 500 22 11.6 501 – 1000 31 16.3 1001 – 1500 23 12.1 1501 – 2000 19 10 2001 and above 17 8.9 Total 190 100

Sources: Primary Data

40 20

0 Not 501 – 1501 – Produced 1000 2000

163 The table (No. 4.19) reveals that 41.10 percent of the synthetic gem manufacturers are not involved in producing A.D. stones. 16.3 percent are producing 501 - 1000 carats, 12.1 percent are producing 1001 - 1500 carats, 11.6 percent producing up to 500 carats of stones per week, 10.0 percent are producing 1501 - 2000 carats and only 8.9 percent are producing above 2001 carats of stones per week.

Place of sales: The performance of synthetic gem manufacturers and the place of executing their sales are inter-related. The varieties of the finished product are usually sold locally or sent through their representatives for sales in other districts of Tamil Nadu as well as to other states of India.

Table – 4.20

Sample of Place of Sales

Places No. of Respondents Percent Local 8 4.2 Main-Bazaar 137 72.1 Intra-State 14 7.4 Inter-State 23 12.1 Local, Inter and Intra-State 8 4.2 Total 190 100

Source: Primary Data

Local, Inter and Intra-State Inter-State

Intra-State

Main-Bazaar

Local

0 20 40 60 80 100 120 140

164 The above table (No.4.20) reveals that 72.10 percent of the synthetic gem manufacturers are selling their produce at main-bazaar of Tiruchirappalli only. 12.10 percent are selling inter-state, 7.40 are selling intra-state and 4.20 percent are selling in locally and local, inter and intra- state respectively. Hence, it is inferred that majority of synthetic gem manufacturers are selling their produce only in the main-bazaar of Tiruchirappalli District.

Value of Sales per Week: The performance of synthetic gem manufacturers and the value of sales are most inter-related activity. The varieties of the finished product are usually sold in bulk every week by the manufacturers. Table below reveals the value of sales made by the manufacturers per week.

Table – 4.21

Sample Total Values of Sales per Week

Value (In Rs.) No. of Respondents Percent 1 – 5000 22 11.6 5001 – 10000 63 33.2 10001 – 15000 55 28.9 15001 – 20000 29 15.3 Above 20000 21 11.1 Total 190 100

Source: Primary Data

15.3% 28.9% 11.1%

11.6% 33.2%

165 The table (No.4.21) reveals that 33.20 percent of the synthetic gem manufacturers are selling their produce for 5001 -10000 Rupees. 28.90 percent are selling for 10001 - 15000 Rupees, 15.30 percent for 15001 - 20000 Rupees, 11.60 percent for 1 - 5000 Rupees. For 11.10 percent of the synthetic gem manufacturers the selling exceeds beyond Rs.20000 per week.

Manufacturer’s Profit per week: The quantum of profit earned by synthetic gem manufacturers per week affects the performance of synthetic gem manufacturers in a considerable way. It is felt among the synthetic gem manufacturers that profit earned per week was adapted in the following manner.

Table – 4.22 Sample of Manufacturer’s Profit per Week

Amount (In Rs.) No. of Respondents Percent 1 – 2000 155 81.6 2001 – 4000 35 18.4

Total 190 100

Source: Primary Data

81.6%

1 – 2000

2001 – 4000 18.4%

Of the total respondents, 81.60 percent are earning a profit up to Rs.2000 per week but the remaining people were earning Rs. 2001 - 4000 per week. Hence, it is inferred that majority of synthetic gem manufacturers are earning a profit up to Rs. 2000 per week only.

166 (iii) Demographic Profile of Synthetic Gem Traders:

The need for the demographic factors of the synthetic gem traders served as a catalyst which has a direct bearing on the performance of the synthetic gem industry. The demographic factors of the synthetic gem traders were studied on parameters, such as gender, age, marital status, educational qualification and nature of family. A careful study was carried out on these parameters which led to the general understanding of how efficiently the synthetic gem traders procure and sell their produce. So, this analysis was carried out to understand the efficiency put in by synthetic gem traders in running their firms which ultimately affects the performance.

Gender: The gender of the synthetic gem traders plays an important role in determining their status in the society. The gender involves the roles, responsibilities, constraints, opportunities and needs of male and female among manufacturers of synthetic gem industry. The analysis of gender leads to have a better understanding of social background of synthetic gem traders. Hence, in this study, gender classification is made.

Table - 4.23

Gender-wise Classifications of Sample Synthetic Gem Traders

Gender No. of Respondents Percent Male 134 97.1 Female 4 2.9 Total 138 100

Source: Primary Data

167

140 120 100 80 134 60 40 20 4 0 Male Female

The synthetic gem traders consist of 97.10 percent male and 2.90 percent female. Hence, it is generalized that majority of the synthetic gem business are owned by male respondents and only a small portion of the traders are female.

Table - 4.24

Age-wise Classification of Sample Synthetic Gem Traders

Age No. of Respondents Percent 21 - 30 years 6 4.3 31 - 40 years 28 20.3 41 - 50 years 68 49.3 51 and above 36 26.1 Total 138 100

Source: Primary Data

The table reveals that 49.30 percent of synthetic gem traders are in the age group of 41-50 years. It is followed by 21 percent in the age group

168 of 51 years and above, 20.30 percent in the age group of 31-40 years. A meager 4.30 percent of traders is in the age group of 21-30 years. Hence it is inferred that majority of the traders belong to age group of 41-50 years.

Marital Status: In Indian society, marriage is supposed to be a religious obligation. In social context, it is the prelude to the family formation, expansion or ever bifurcation. After marriage, there is a transition in the status of men and women with attendant rights and obligations. It is an important event in one‟s life. It influences the style of living and also the attitude, disposition and commitment towards work.

Table - 4.25

Marriage-wise Classification of Sample Synthetic Gem Traders

Marital status Frequency Percent Married 132 95.7 Unmarried 6 4.3 Total 138 100

Source: Primary Data

The above table revealed that, out of the total traders, 132 of them were married, constituting of significant percentage of 95.70 and only a negligible part of them are unmarried, constituting a meager percentage of 4.30. So, it is revealed that majority of the respondents are married.

Educational Qualification: The educational qualification of the synthetic gem traders ultimately has an influence over the performance. It not only widens knowledge of synthetic gem traders but also provide them courage and confidence in their task. It helps to take strategic decision making for the betterment of their career. Education helps the person to adopt rational and scientific approach in solving complex

169 problems. Education has a positive impact on social life and quality of life and vice versa.

Table- 4.26

Education-wise Classification of Sample Synthetic Gem Traders

Educational Qualification No. of Respondents Percent Up to S.S.L.C 12 8.7 HSC 70 50.7 Under Graduation 33 23.9 Post-Graduation 23 16.7 Total 138 100

Source: Primary Data

The table shows that 50.70 percent of the traders studied HSC. 23.90 and 16.70 percent of traders studied graduation and post graduation respectively. Only 8.70 percent of traders studied up to S.S.L.C. Here the majority of them belong to HSC.

Nature of Family: The family background plays an important role in moulding the behaviour of its members. The family provides the recognition and security for the individuals and also serves as their identity. The living arrangements are very crucial for the socio-economic status of a person.

Table – 4.27

Family-wise Classification of Sample Synthetic Gem Traders

Nature of family No. of Respondents Percent Nuclear 82 59.4 Extended 56 40.6 Total 138 100

Source: Primary Data

170

40.6% Nuclear

59.4% Extended

The nature of family of the synthetic gem traders consist of 59.40 percent nuclear and 40.60 percent extended type of family. Hence, the majority of the synthetic gem traders are considered be nuclear type of family.

(iv) Performance of Traders:

Years of Experience in synthetic gem business: The performance of synthetic gem traders depends on the years of experience put in by them in their business. The performance of the synthetic gem traders enhances proportionately with their field experience.

Table – 4.28

Experience-wise Classification of Sample Synthetic Gem Traders

Years of experience No. of Respondents Percent 10- 15 18 13.1 16 - 20 46 33.3 Above 20 74 53.6 Total 138 100

Source: Primary Data

171

13.1%

53.6% 33.3%

10 - 15 16 - 20 Above 20

The synthetic gem traders of 53.60 percent have had the field experience of more than 20 years, followed by 33.30 percent in the category of 16 - 20 years of experience, and finally 13.10 percent of traders who had only 11-15 years of experience. So, it is observed that majority of the traders had the field experience of more than 20 years. No traders were found with less than 11 years of experience.

Sources of funds of Traders: Synthetic Gem Traders are having special knowledge of utilization of the sources of funds. Specifically, they don‟t go for loans and pay interest and lose their profit. The motto of not to pay an interest is an income, they feel. Even if they borrow, it is only up to a manageable level with a guarantee of minimum profit.

Table-4.29

Sample Sources of Funds of Traders

Sources No. of Respondents Percent Owned 78 56.5 Borrowed 12 8.7 Both owned and borrowed 48 34.8 Total 138 100

Source: Primary Data

172

20 0 1 2

Owned 78 56.5 Borrowed 12 8.7

Both owned and 48 34.8 borrowed

It is expounded that 56.5 percent of the traders utilize their own funds and 8.7 percent borrowed from outsiders. But, 34.8 percent of traders utilize both borrowed and owned funds.

Table-4.30

Sample Borrowings of Synthetic Gem Traders

Sources No. of Respondents Percent Nil 78 56.5 Bank 10 7.2 Finance Company 23 16.7 Money Lenders 5 3.6 Friends and Relatives 22 16 Total 138 100

Source: Primary Data

It is clarified that, 56.5 percent of traders don‟t borrow any funds from the outsiders. 16.7 percent of traders borrowed from finance companies. Next, 16.0 percent of traders borrowed from their friends and relatives. But, only 7.2 percent and 3.6 percent of traders borrowed from bank and money lenders.

173 Problems in Trade: Synthetic gem traders are facing many type of problems in their process of selling because of the influence of so many factors. They admit themselves about the existence of problems. Still they do procuring and selling because of their commitment and involvement in the field.

Table – 4.31

Sample Opinions on Problems in Trade

Opinion No. of Respondents Percent Yes 89 64.5 No 49 35.5 Total 138 100

Source: Primary Data

In the process of production of synthetic gem 64.50 percent of the traders admitted problems in their business, while 35.50 are gave opinion of smooth running of their trade.

Category of Traders: The nature of Trade plays a pivotal role in selling their products by the traders as per the needs and expectations of the goldsmiths, jewelry makers or jewelry shop owners. As, the synthetic gem traders are generally lacking adequate educational and informational expertise, they engage only in particular category of trade with an aim of reaping a maximum profit in their synthetic gem business.

174 Table – 4.32

Category-wise Classifications of Sample Synthetic Gem Traders

Category No. of Respondents Percent Manufacturer and Trader 40 29 Trader 93 67.4 Others 5 3.6 Total 138 100

Source: Primary Data

The table reveals that the maximum of 67.40 percent are only traders, followed by 29.00 percent who are both trader as well as manufacturer of synthetic gems and only 3.60 percent of people are coming under the category of others. Hence, it is concluded that majority of the traders are engaged in trading only.

Kinds of stones traded: The performance of synthetic gem traders and the kinds of stones traded by them were studied which are most inter- related activities. The varieties of the stones are usually sold out to jewelry owners and goldsmiths.

Table – 4.33

Sample Kinds of Stones Traded

Kinds No. of Respondents Percent Imitation white, red and AD 22 15.9 Imitation Red 13 9.4 A.D. White 8 5.8 Imitation and Chinese stone 12 8.7 Imitation, AD and Chinese stone 83 60.2 Total 138 100

Source: Primary Data

175

90 80 70 Imitation white, red and 60 50 AD 40 Imitation Red 30 20 10 A.D. White 0 S1 Imitation and Chinese stone Imitation, AD and Chinese

stone

red and AD and red

A.D. White

Imitation white,

and Chinese and Imitation, AD

The table reveals that maximum of 60.20 percent of the synthetic traders are selling Imitation, American Diamond and Chinese stones while 15.90 percent are selling Imitation and American Diamond only. 9.40 percent are selling Imitation red only but 5.80 and 8.70 percent of traders are selling AD white and Imitation and Chinese stones respectively. So, it is revealed that majority of the synthetic gem traders are engaged in the sales of three kinds of stones i.e., Imitation, American Diamond and Chinese stones.

Total Value of Sales per Year: The performance of synthetic gem traders depends on the total value of sales per year. The performance of the synthetic gem traders enhances proportionately to their field experience.

176 Table – 4.34

Sample Total Values of Sales per Year

Sales in Rupees No. of Respondents Percent 1 – 5,00,000 16 11.6 5,00,001 – 10,00,000 47 34 10,00,001 – 15,00,000 52 37.7 15,00,001 and above 23 16.7 Total 138 100

Source: Primary Data

1 – 5,00,000 5,00,001 – 10,00,000 10,00,001 – 15,00,000 15,00,001 and above

The table shows that 37.70 percent of the traders are selling the stones for Rupees 10,00,001 to 15,00,000 per year. 34.00 percent are selling between Rupees 5,00,001 and 10,00,000, 16.70 percent are selling above Rupees 15,00,000 . Only 11.60 percent of traders are selling up to 5,00,000 per year.

177 (v) Demographic Profile of the Synthetic Gem Workers:

Work force plays a key factor in the success of every industry. The same situation is prevailing in the synthetic gem industry also. The present scenario in the industry is well-known to everybody. The profitability of this industry is deteriorating because of many factors. As the working capital requirements of both manufacturers and traders of the industry have continuously come down they are unable to pay the workers a good remuneration for their work. Many entrepreneurs have diversified their business because of continuous loss. The workers are also forced to follow them and look for job elsewhere. But, the mind-setting of the workers of this industry is unique in a way that they do not want to leave this skillful endeavor. They still love their job even though they are paid very less. Yet they need to feed themselves and their family members. Owing to increasing price of essential commodities they are compelled to switch over to some other job which helps them to bear their everyday livelihood. The researcher has carefully analyzed their socio-economic background and demographic profile.

Gender: The gender of the synthetic gem workers plays an important role in determining their status in the society. The gender involves the roles, responsibilities, constraints, opportunities and needs of male and female among workers of synthetic gem industry. The analysis of gender leads to have a better understanding of social background of synthetic gem workers. Hence, in this study, gender classification is made.

178 Table - 4.35

Gender-wise Classifications of Synthetic Gem Workers

Gender No. of Respondents Percent Male 217 76.1 Female 68 23.9 Total 285 100

Source: Primary Data

Female 23.9%

Male 76.1%

The synthetic gem workers consist of 76.10 percent male and 23.90 percent female. Hence, it is generalized that majority of the synthetic gem jobs are done by male respondents and only a small portion of the workers are female.

179 Table - 4.36

Age-wise Classifications of Sample Synthetic Gem Workers

Age No. of Respondents Percent 21 - 30 years 20 7 31 - 40 years 47 16.5 41 - 50 years 148 51.9 51 and above 70 24.6 Total 285 100

Source: Primary Data

The age of synthetic gem workers consist of 51.90 percent, who belong to 41-50 years age group, followed by 24.60 percent 51 and above years, 16.50 percent to 31 - 40 years and only 7.00 percent are 21 - 30 years age group. So, it is inferred that majority of the synthetic gem workers are in the age group of 41-50 years.

Table - 4.37

Marriage-wise Classification of Sample Synthetic Gem Workers

Marital status Frequency Percent Married 263 92.3 Unmarried 22 7.7 Total 285 100

Source: Primary Data

180 The above table (No. 4.37) revealed that, out of the total respondents, 263 of them were married, constituting a significant percentage of 92.30 and only a negligible part of them are unmarried, constituting a meager percentage of 7.70. So, it is revealed that majority of the respondents are married.

Educational Qualification: The educational qualification of the synthetic gem workers ultimately has an influence over the performance. It not only widens knowledge of synthetic gem workers but also provide them courage and awareness in their task. Education helps the person to adopt rational and scientific approach in solving complex problems. Education has a positive impact on social life and quality of life and vice versa.

Table 4 .38

Education-wise Classification of Sample Synthetic Gem Workers

Educational Qualification No. of Respondents Percent Illiterate 58 20.4 I - V Std 114 40 VI - X Std 90 31.6 Above X Std 23 8.1 Total 285 100

Source: Primary Data

120 100

60 114 90 40 58 20 23 0 Illiterate I - V Std VI - X Std Above X Std

181 The table (No. 4.38) specifies that the education level of synthetic gem workers consist of 40.00 percent who have studied up to I to V Standard, VI to X Standard 31.60 per cent and 20.40 percent illiterate and only 8.10 percent studied above X Standard. So, it is inferred that majority of the synthetic gem workers have had the educational qualification of only up to V Standard.

Table – 4.39

Sample Nature of Family of Synthetic Gem Workers

Nature of family No. of Respondents Percent Nuclear 216 75.8 Extended 69 24.2 Total 285 100

Source: Primary Data

The nature of family of the synthetic gem workers consist of 75.80 percent which is nuclear and only 24.20 percent an extended type of family. Hence, the majority of the synthetic gem workers are considered to be nuclear type of family.

182 (vi) Performance of Workers:

Length of service in synthetic gem production: The performance of synthetic gem workers depends on the length of service put in by them on synthetic gem production. The performance of the synthetic gem workers enhances proportionately with their field experience.

Table – 4.40

Sample Length of Service of Synthetic Gem Workers

Length of service in Years No. of Respondents Percent 06-10 24 8.4 11-15 49 17.2 16-20 122 42.8 Above 20 90 31.6 Total 285 100

Source: Primary Data

Above 20

06 - 10 16 - 20 11 - 15

11 - 15 16 - 20 Above 20 06 - 10

0 50 100 150

The synthetic gem workers of 42.80 percent have had the total service of 16 – 20 years, followed by 31.60 percent in the category of above 20 years of service, 17.20 percent were 11 – 15 years of service and 8.40 percent possessed only 6-10 years of service. So, it is observed that majority of the respondents have the total service of 16 – 20 years.

183 Nature of work: Synthetic gem workers are usually practicing a specific type of task in the production of synthetic gems and they are developing their skills in that specific type of work. So, the performance of synthetic gem workers and their type of work has its own significance.

Table – 4.41

Sample Nature of Work of Synthetic Gem Workers

Nature No. of Respondents Percent Cutting 12 4.2 Coning 23 8.1 Faceting 34 11.9 Coning and Faceting 28 9.8 Polishing 188 66 Total 285 100

Source: Primary Data

188 200

150

100 34 50 23 28 12 0

Regarding the nature of production of synthetic gems 75.80 percent of synthetic gem workers are engaged in polishing, while 11.90 percent are doing faceting, 9.80 percent are doing coning and faceting, 8.10 percent are doing coning and 4.20 percent are doing only the cutting work. So, it is observed that majority of the workers are engaged in the task of polishing.

184 Earnings per Day: Everybody in this world engage themselves in many type of tasks mainly for the purpose of earning money. The synthetic gem workers are applying their skills and talents in production of various designs and colorful gems. Whether the compensation received for their work by the workers is really satisfying their needs was analyzed. The workers are paid only daily wages which does not match the prevailing economic situation.

Table – 4.42

Sample Daily Wages of Synthetic Gem Workers

Earnings per Day (in Rs.) No. of Respondents Percent 26 – 50 15 5.2 51 – 75 88 30.9 76 – 100 127 44.6 Above 100 55 19.3 Total 285 100

Source: Primary Data

5.2% 19.3% 30.9%

44.6%

26 - 50 51 - 75 76 - 100 Above 100

In the process of production of synthetic gem 44.60 percent of the respondents have admitted that they are earning rupees 76 - 100 per day, while 30.90 per cent gave the opinion of earning rupees 51 - 75 per day,

185 19.30 percent of the respondents are earning more than rupees 100 per day and only 5.20 percent of workers are earning rupees 26 - 50 per day. Hence, it is concluded that majority of the respondents are earning only in between rupees 76 and 100 per day.

(vii) Opinion on Prospects of Synthetic Gem Industry:

Factors influencing opinion of synthetic gem industry players towards prospects of their industry:

There are various key factors which have a direct influence among the players (traders, manufacturers and labourers) towards prospects of the synthetic gem industry. These factors are generally identified with the use of frequency table. Hence, in this respect, frequency table has been used to identify and analyze the key or principal factors which influence the synthetic gem industry players on their performance and prospects. In this regard, several statements regarding various aspects of prospects have been framed. These statements have to be analyzed for the betterment of the industry. The opinion of traders, manufacturers and labourers are presented/represented in a tabular form with regard to „Ban on Import of Chinese stones‟ , „Indigenous production of raw materials‟, ‟ Stability in Gold Prices‟, „Strengthening of labour force‟, „Adaptation of new technology in production‟, „Incentives, subsidies and assistance from the Government‟ and Influence of Liberalization and Globalization. Their opinion was categorized as „Most needed‟, „Needed‟ and „No need‟ and „Yes‟ and „No‟.

Ban on Import of Chinese Stones: The prospects of synthetic gem industry and ban on Chinese stones are much inter-related. After admitting and accepting the Liberalization and Globalization, these

186 Chinese stones easily and totally captured the Indian Synthetic Gem Market and destroyed the indigenous synthetic gem industry. The views and thoughts of the synthetic gem players prove the statements and seek remedy for it.

Table – 4.43

Sample Opinion on Ban on Import of Chinese Finished Synthetic Gem Stones

Opinion Traders Manufacturers Labourers Frequency Percent Frequency Percent Frequency Percent Most needed 70 50.70 153 80.50 80 28.10 Needed 40 29.00 37 19.50 205 71.90 No need 28 20.30 0 0.00 0 0.00 Total 138 100.00 190 100.00 285 100.00

Source: Primary Data.

250

200

150

100

0 Frequency Percent Frequency Percent Frequency Percent

Most needed Needed No need

The statement reveals that 50.7 percent of traders, 80.5 percent of manufacturers and 28.1 percent of labourers are for most needed to ban the import of Chinese stones. 29.0 percent, 19.5 percent and 71.9 percent of traders, manufacturers and labourers are for needed to ban the Chinese stones and only 28.0 per cent of traders are for no need to ban the Chinese stones. But the manufacturers and labourers are not opposing the ban on import of Chinese stones.

187 Indigenous Production of Raw-materials: The Indigenous production of raw-materials influence prospects of synthetic gem industry. Today, the industry expects its raw-materials only from outside India. There existed one Indo-Swiss Company, Mettupalayam which produced world-class raw-materials to satisfy the need of indigenous manufacturers of synthetic gems. The company is not producing raw-materials any more. It could not withstand the continuous raise in the cost of production of raw- materials. Foreign companies occupied their position.

Presently the availability of raw-material has become scarce and its prices are not constant due to various reasons. This does not help the manufacturers. Therefore, they feel the need for indigenous raw-materials with constant price to help them produce quality gem stones.

Table – 4.44

Sample Opinion on Indigenous Production of Raw-materials

Traders Manufacturers Labourers Opinion Frequency Percent Frequency Percent Frequency Percent Most needed 70 50.70 167 87.90 205 71.90 Needed 52 37.70 23 12.10 80 28.10 No need 16 11.60 0 0.00 0 0.00 Total 138 100.00 190 100.00 285 100.00

Source: Primary Data

188

250

200

150 100

0 1 2 3

Most needed Needed No need

From the above table (No.4.44), it is found that 50.7 percent of the traders, 87.9 percent of the manufacturers and 71.9 percent of labourers were for most needed of the indigenous raw-materials. 37.7 percent of traders, 12.1 percent of manufacturers and 28.1 percent of labourers were for needed of Indigenous raw-materials and only 11.6 percent of traders were for no need of indigenous raw-materials. Here, cent percent of labourers and manufacturers badly needed the indigenous raw-materials.

Stability in Gold Prices: Gold Price is the determining factor for marketing of synthetic gems. It directly reflects the prospects of synthetic gem industry. The demand for synthetic gems increases when the price of Gold comes down and vice-versa. General aspiration of the industry people is to put the gold price in a stable level for the betterment of their livelihood.

189 Table – 4.45

Sample Opinion on Stability in Gold Prices

Traders Manufacturers Labourers Opinion Frequency Percent Frequency Percent Frequency Percent Most needed 72 52.1 137 72.1 88 30.9 Needed 53 38.4 53 27.9 197 69.1 No need 13 9.5 0 0 0 0 Total 138 100 190 100 285 100

Source: Primary Data

200

150

100

0 Most needed Needed No need

Series1 Series2 Series3

It is inferred from the table that 52.1 percent of the traders, 72.1 percent of the manufacturers and 30.9 percent of the labourers are for most needed for stabilization of gold prices. 38.4 percent, 27.9 percent and 69.1 percent are for needed. Only 9.5 percent of traders do not have the same view and they don‟t even consider this view. Over all, both Manufacturers and labourers strongly emphasized the need for stable Gold price.

190 Strengthening of Labour Force: This Synthetic gem industry is a Labour-intensive industry. Labour is the predominant factor. The industry is run by labour force. But, the labour force is totally switching over to some other jobs due to lack of income. Therefore, the total industry is in a collapsed condition now. Labour force retrieval is the main requirement today for the benefit of overall industry. Everyone realizes the importance of labour, now.

Table – 4.46

Sample Opinion on Strengthening of Labour Force

Traders Manufacturers Labourers Opinion Frequency Percent Frequency Percent Frequency Percent Most needed 62 44.90 37 19.50 92 32.30 Needed 43 31.20 153 80.50 193 67.70 No need 33 23.90 0 0.00 0 0.00 Total 138 100.00 190 100.00 285 100.00

Source: Primary Data

200 180 160 140 120 Series1 100 Series2 80 Series3 60 40

20 0 Most needed Needed No need

191 It is exposed from the above table (No. 4.46) that 44.9 percent of traders, 19.5 percent of manufacturers and 32.3 percent of labourers were for most needed of the strengthening of labour force. 31.2 percent, 80.5 percent and 67.7 percent of traders, manufacturers and labourers respectively were for needed. Only 23.9 percent of traders is for no need of the strengthening of labour force.

Adaptation of new technology in production: Another reason for failure of this industry is non-adaptation of new technology in production. Foreign countries especially China adopts latest technology in production and produce stones in large-scale with least cost. This led them to capture the Indian Market easily. So, this factor very much influences the overall prospects of the industry.

Table – 4.47

Sample Opinion on Adaptation of New Technology in Production

Traders Manufacturers Labourers Opinion Frequency Percent Frequency Percent Frequency Percent Most needed 70 50.70 45 23.70 48 16.80 Needed 54 39.10 145 76.30 176 61.70 No need 14 10.20 0 0.00 61 21.50 Total 138 100.00 190 100.00 285 100.00

Source: Primary Data

192

180 160 140 120 100 80 60 40 20 0 Most needed Needed No need

Series1 Series2 Series3

Of the total respondents, 50.70 percent of the traders, 23.70 percent of the manufacturers and 16.80 percent of the labourers were for habitually most needed of the adaptation of new technology in production. Traders, Manufacturers and labourers representing 39.10 percent, 76.30 percent and 61.70 percent respectively needed the adaptation of new technology and 10.20 percent of traders and 21.50 percent of labourers said as no need to adapt new technology in production.

Incentives, Subsidies and Assistance from the Government: Incentives, subsidies and assistance from the government affect the prospects of the industry in a considerable way. It is felt that if the government extends its hands through these bounties, the industry will definitely get converted from sick position to superior position without any doubt.

193 Table – 4.48

Sample Opinion on Incentives, Subsidies and Assistance from the Government

Traders Manufacturers Labourers Opinion Frequency Percent Frequency Percent Frequency Percent Most needed 59 42.80 51 26.80 79 27.70 Needed 56 40.60 139 73.20 206 72.30 No need 23 16.60 0 0.00 0 0.00 Total 138 100.00 190 100.00 285 100.00

Source: Primary Data

250

200

150

100

0 Most needed Needed No need

Series1 Series2 Series3

The table exhibit that 42.80 percent of traders, 26.80 percent of the manufacturers and 27.70 percent of labourers were for most needed of the Government assistance, benefits, etc. 40.60 percent, 73.20 percent and 72.30 percent of traders, manufacturers and labourers were for needed of the government subsidies, incentives, etc. Only 16.70 percent of traders did not require the government benefits.

194 Influence of Liberalization and Globalization: It is 100 percent true that Liberalization and Globalization has influenced the industry in its downfall. This allowed the import of raw-materials and finished goods of synthetic gem from so many countries like Germany, Korea, Taiwan, Thailand, Indonesia and China. Especially China involved in this field and completely captured the Indian Market by giving calibrated raw-materials or finished goods at low cost. This was possible for them due to their large-scale production and its cost-benefit and utilization of modern technology.

Table – 4.49

Sample Opinion on Influence of Liberalization and Globalization

Traders Manufacturers Labourers Opinion Frequency Percent Frequency Percent Frequency Percent Yes 102 73.90 190 100.00 276 96.80 No 36 26.10 0 0.00 9 3.20 Total 138 100.00 190 100.00 285 100.00

Source: Primary Data

300

250

200

150

100

0 Yes No

Traders Manufacturers Labourers

195 It is illuminated from the table (No. 4.49) that 100.0 percent of manufacturers accepted the view that Liberalization and Globalization has affected the synthetic gem industry. 73.9 percent of Traders and 96.8 percent of labourers have also held the same view. But, only 26.1 percent of Traders and 3.2 percent of labourers differed.

196 B. Factor Analysis

This statistical technique has been used to explain the factors influencing effective commitment among the manufacturers and the traders of Synthetic Gem Industry

Output of factor analysis is obtained by requesting principle component analysis and specifying the interpretation. In the factor extraction process, where in objective is to identify how many factors are to be extracted from the data. The most popular method is called principal component analysis. There is also a rule of thumb based on the computation in Eigen value, to determine how many factors to extract. The higher the Eigen value of a factor, the higher is the amount of variance explained by the factor.

Factor Analysis I

Table - 4.50

Factors Contributing to Performance of Infra-structural facilities

Initial Eigen values Rotation Sums of Squared Loadings Components % of Cumulative % of Cumulative Total Total Variance % Variance % 1 1.111 37.024 37.024 1.103 36.758 36.758 2 1.033 34.435 71.460 1.041 34.701 71.460 3 0.856 28.540 100.000

Extraction Method: Principal Component Analysis.

The above table explained that factor analysis by principal component method with varimax rotation has revealed two Eigen values such as 1.111and 1.033. This indicated that the Eigen values greater than 1

197 led to the existence of two major factors with 71.46 percent of variance (Table – 4.50). These factors are subjected to continuous varimax rotation with respect to the correlation values and component-wise segregation which is given below:

Table - 4.51

Rotated Component Matrix on Factors influencing in Infra-structural facilities

Components Variables / Factors 1 2 Availability of Raw Materials -0.024 0.903 Power Supply 0.697 0.382 Modernized Equipments and Machinery 0.785 -0.282

The rotated component matrix in the above table explained the variable loadings in each predominant factor influencing the performance of infra-structural facilities. It is observed that the infra-structural factors consisted of three variables such as Availability of Raw Materials, Power Supply and Modernized equipment and Machinery. The variables Power Supply (0.697) and Modernized Equipment and Machinery (0.785) are loaded in component factor one. The remaining variable of Availability of Raw-material (0.903) is loaded in component factor two.

It is also observed from the above table that the synthetic gem manufacturers are affected by the infra-structural facilities.

198 Factor Analysis II

Table -4.52

Factors Contributing to Performance of Government Assistance

Initial Eigen values Rotation Sums of Squared Loadings Components % of Cumulative % of Cumulative Total Total Variance % Variance % 1 1.623 32.455 32.455 1.477 29.534 29.534 2 1.144 22.887 55.342 1.290 25.808 55.342 3 0.929 18.578 73.920 4 0.751 15.021 88.941 5 0.553 11.059 100.000

Extraction Method: Principal Component Analysis.

The above table explained that factor analysis by principal component method with varimax rotation has revealed two Eigen values such as 1.623 and 1.144. This indicated that the Eigen values greater than 1 led to the existence of two major factors with 55.34 percent of variance (Table – 4.52). These factors are subjected to continuous varimax rotation with respect to the correlation values and component-wise segregation which is given below:

Table- 4.53

Rotated Component Matrix on Factors influencing in Government Assistances

Components Variables / Factors 1 2 Government Policy and Support 0.567 0.416 Subsidies for Import of Raw-materials and Machinery 0.048 -0.647 Regulated Market 0.826 0.11 Training and Educational Programs 0.322 0.673 Cluster Formation -0.706 0.583

199 The rotated component matrix in the above table explained the variable loadings in each predominant factor influence the performance of Government Assistances. It is observed that the Government Assistance factors consisted of five variables such as: Government Policy and Support, Subsidies for Import of Raw-materials and Machinery, Regulated Market, Training and Educational Programs and Cluster Formation. The variables of Government Policy and Support (0.567) and Regulated Market (0.826) are loaded in factor one. The variables of Training and Educational Programs (0.673) and Cluster Formation (0.583) are loaded in factor two. The variable of Subsidies for import of raw-materials and machinery is not loaded in either component 1 or component 2 because it does not attain the loading level 0.500

It is also observed from the above table that the synthetic gem manufacturers are affected by the majority factors of Government assistances.

200 Factor Analysis III

Table -4.54

Factors Contributing to Performance of Labour

Initial Eigen values Rotation Sums of Squared Loadings Component % of Cumulative % of Cumulative s Total Total Variance % Variance % 1 1.406 20.090 20.090 1.271 18.157 18.157 2 1.263 18.037 38.127 1.248 17.829 35.986 3 1.163 16.619 54.746 1.246 17.800 53.786 4 1.060 15.147 69.893 1.127 16.106 69.893 5 0.758 10.830 80.723 6 0.752 10.744 91.467 7 0.597 8.533 100.000

Extraction Method: Principal Component Analysis.

The above table explained that factor analysis by principal component method with varimax rotation has revealed four Eigen values such as 1.406, 1.263, 1.163 and 1.060. This indicated that the Eigen values greater than 1 led to the existence of four major factors with 69.89 percent of variance (Table – 4.54). These factors are subjected to continuous varimax rotation with respect to the correlation values and component- wise segregation which is given below:

201 Table -4.55

Rotated Component Matrix on Factors influencing in Labour

Components Variables / Factors 1 2 3 4 Availability of Labour -0.048 0.787 -0.068 0.269 Labour Cost 0.005 -0.658 -0.120 0.567 Migration of Labourers 0.774 -0.141 0.052 -0.077 Labour Turnover 0.788 0.107 -0.097 0.084 Workers’ Participation in Mgt. 0.089 0.209 0.847 -0.107 Quality Production 0.011 0.076 0.056 0.876 Technical Knowledge Up gradation -0.199 -0.340 0.703 0.214

The rotated component matrix in the above table explained the variable loadings in each predominant factor that influence the performance of Labour. It is observed that the Labour factors consisted of seven variables such as: Availability of Labour, Labour Cost, Migration of Labourers, Labour Turnover, and Workers‟ Participation in the Management, Quality Production and Technical Knowledge Up gradation.

The variables of Migration of labourers (0.774) and Labour Turnover (0.788) are loaded in component factor one. The variable of Availability of Labour (0.787) is loaded in component factor two. The variables of Workers‟ Participation in Management (0.847) and Technical Knowledge Up gradation (0.703) are loaded in component factor three. The remaining variables of Labour Cost (0.567) and Quality Production (0.876) are loaded in component factor four.

It is also observed from the above table that the synthetic gem manufacturers are influenced by the factors of performance of labour.

202 Factor Analysis IV

Table - 4.56

Factors Contributing to Performance of Financial Assistance

Initial Eigen values Rotation Sums of Squared Loadings Component % of Cumulativ % of Cumulative s Total Total Variance e % Variance % 1 1.411 28.222 28.222 1.255 25.090 25.090 2 1.284 25.678 53.900 1.227 24.543 49.634 3 1.012 20.240 74.140 1.225 24.506 74.140 4 0.694 13.886 88.026 5 0.599 11.974 100.000

Extraction Method: Principal Component Analysis.

The above table explained that factor analysis by principal component method with varimax rotation has revealed three Eigen values such as 1.411, 1.284, and 1.012. This indicated that the Eigen values greater than 1 led to the existence of three major factors with 74.14 percent of variance (Table – 4.56). These factors are subjected to continuous varimax rotation with respect to the correlation values and component-wise segregation which is given below:

Table - 4.57

Rotated Component Matrix on Factors influencing in Financial Assistance

Components Variables / Factors 1 2 3 Accessibility of Bank Loan 0.276 0.578 -0.587 Hassle free bank loan formalities 0.799 0.261 0.181 Rate of Interest -0.056 0.838 0.151 Support from other funding agencies 0.730 -0.306 -0.255 Mode of Repayment 0.059 0.172 0.872

203 The rotated component matrix in the above table explained the variable loadings in each predominant factor influencing the performance of Financial Assistance. It is observed that the financial assistance factors consisted of five variables such as: Accessibility of Bank Loan, Hassle free Bank Loan Formalities, Rate of Interest, Support from other Funding Agencies and Mode of Repayment.

The variables of Hassle Free Bank Loan Formalities (0.799) and Support from other Funding Agencies (0.730) are loaded in factor one. The variables of Accessibility of Bank Loan (0.578) and Rate of Interest (0.838) are loaded in factor two. The variable of Mode of repayment (0.872) is loaded in factor three.

It is also observed from the above table that the synthetic gem manufacturers are affected by the financial assistances.

204 Factor Analysis V

Table -4.58

Factors Contributing to Performance of Marketing

Initial Eigen values Rotation Sums of Squared Loadings % of Cumulative % of Cumulative Components Total Variance % Total Variance % 1 1.599 19.988 19.988 1.395 17.435 17.435 2 1.232 15.397 35.385 1.259 15.742 33.177 3 1.097 13.712 49.097 1.205 15.065 48.242 4 1.056 13.197 62.294 1.124 14.051 62.294 5 0.960 12.000 74.294 6 0.819 10.238 84.532 7 0.650 8.119 92.651 8 0.588 7.349 100.000

Extraction Method: Principal Component Analysis.

The above table explained that factor analysis by principal component method with varimax rotation has revealed four Eigen values such as 1.599, 1.232, 1.097 and 1.056. This indicated that the Eigen values greater than 1 led to the existence of four major factors with 62.29 percent of variance (Table – 4.58). These factors are subjected to continuous varimax rotation with respect to the correlation values and component- wise segregation which is given below:

205 Table -4.59

Rotated Component Matrix on Factors influencing in Marketing Performance

Components Variables / Factors 1 2 3 4 Storage Facilities 0.840 -0.068 0.131 0.036 Quality Segregation 0.137 -0.259 0.669 -0.207 Support from market intermediaries 0.064 0.646 0.508 -0.049 Selling price of stones 0.078 0.767 -0.170 0.018 Commission of Brokers 0.076 -0.108 -0.633 -0.281 Credit Sales and Debt Collection Period -0.177 -0.311 0.193 0.598 Seasons 0.215 0.182 -0.100 0.800 Annual Turnover 0.760 0.203 -0.076 0.015

The rotated component matrix in the above table explained the variable loadings in each predominant factor influence the performance of synthetic gem marketing. It is observed that the marketing performance factors consisted of eight variables such as: Storage facilities, Quality Segregation, Support from Market intermediaries, Selling Price of stones, Commission of Brokers, Credit Sales and Debt Collection Period, Seasons and Annual Turnover.

The Variables of Storage Facilities (0.840) and Annual Turn Over (0.760) are loaded in factor one. The variables of Support from Market Intermediaries (0.508) and Selling Price of Stones (0.767) are loaded in factor two. The variable of Quality Segregation (0.669) is loaded in factor three. The Variables of Credit Sales and Debt Collection Period (0.598) and Seasons (0.800) are loaded in factor four. The factor Commission of Brokers is not loaded significantly (i.e. above 0.500) in none of the component factors. It is also observed from the above table that the synthetic gem manufacturers are affected by the performance of marketing.

206 Factor Analysis VI

Table -4.60

Factors contributing to Problems in Marketing

Initial Eigen values Rotation Sums of Squared Loadings Components % of Cumulative % of Cumulative Total Total Variance % Variance % 1 2.934 17.257 17.257 2.234 13.144 13.144 2 2.283 13.430 30.687 2.114 12.433 25.576 3 2.037 11.980 42.667 1.956 11.505 37.082 4 1.703 10.018 52.685 1.837 10.804 47.886 5 1.447 8.510 61.195 1.662 9.779 57.665 6 1.348 7.928 69.123 1.616 9.504 67.169 7 1.166 6.859 75.982 1.498 8.813 75.982 8 0.853 5.016 80.998 9 0.674 3.964 84.962 10 0.610 3.587 88.549 11 0.461 2.712 91.261 12 0.417 2.451 93.712 13 0.304 1.786 95.498 14 0.279 1.642 97.140 15 0.227 1.336 98.476 16 0.184 1.084 99.560 17 0.075 0.440 100.000

Extraction Method: Principal Component Analysis.

The above table explained that factor analysis by principal component method with varimax rotation has revealed seven Eigen values such as 2.934, 2.283, 2.037, 1.703, 1.447, 1.348 and 1.166. This indicated that the Eigen values greater than 1 led to the existence of seven major factors with 75.98 percent of variance (Table – 4.60). These factors are subjected to continuous varimax rotation with respect to the correlation values and component-wise segregation which is given below:

207 Table -4.61

Rotated Component Matrix on Factors influencing in Problems in Marketing

Components Variables / Factors 1 2 3 4 5 6 7 High Storage of Raw-materials 0.008 -0.375 0.113 0.399 0.029 -0.019 0.566 and Finished stones Order of particular sizes, colours 0.035 0.177 0.698 0.468 0.279 0.061 -0.022 and types Particular size selection 0.760 -0.210 -0.107 0.193 0.167 -0.090 0.293 Quality underestimated -0.118 0.599 0.262 -0.065 -0.273 0.090 0.313 Rejection / Return of goods 0.193 0.808 0.081 0.115 0.151 -0.011 -0.126 Low – price quoted -0.106 -0.121 0.049 0.563 0.189 -0.148 0.093 No Constant Price 0.726 -0.023 0.279 0.048 0.372 -0.061 0.154 High Commission of brokers -0.026 -0.129 0.049 0.616 0.596 -0.024 0.173 Competition 0.012 0.125 0.078 0.377 0.009 0.843 0.006 Ineffective sales 0.148 -0.406 -0.021 -0.155 0.235 0.741 0.159 Credit Sales 0.570 -0.447 0.002 0.131 0.240 -0.512 0.015 Delayed payment 0.042 0.652 -0.500 0.034 -0.008 -0.159 0.147 High Debt Collection Period 0.152 -0.077 0.882 -0.046 0.027 -0.029 0.081 Illegitimate buying -0.044 0.033 0.056 -0.129 0.884 0.101 -0.068 Affected by seasons -0.024 0.134 0.05 -0.084 0.006 0.082 0.844 Exploitation by the trader 0.210 0.154 0.596 -0.179 -0.123 0.045 0.372 Irregular sales -0.066 -0.003 -0.021 -0.186 0.539 -0.045 -0.082

The rotated component matrix in the above table explained the variable loadings in each predominant factor influence the problems in marketing. It is observed that the problems in marketing factors consisted of seventeen variables such as High Storage of Raw-materials and Finished stones, Orders of Particular Size, Colour and Types, Particular size selection, Quality underestimated, Rejection/Return of Goods, Lesser price, No Constant Price, High Commission of Brokers, Competition,

208 Ineffective Sales , Credit Sales, Delayed Payment, High Debt Collection Period, Illegitimate buying, Affected by seasons, Exploitation by the Traders and Irregular Sales.

The variables of No Constant Price (0.726), Particular size selection (0.760) and Credit Sales (0.570) are loaded in factor one. The variables of Quality Underestimated (0.599), Rejection / Return of goods (0.808) and Delayed Payment (0.652) are loaded in factor two. The variables of Order of Particular Size, Colour and Types (0.698), High Debt Collection Period (0.882) and Exploitation by the trader (0.596) are loaded in factor three. The variables of Low-Price Quoted (0.563) and High Commission of Brokers (0.616) are loaded in factor four. The variables of Illegitimate buying (0.884) and Irregular Sales (0.539) are loaded in factor five. The variables of Competition (0.843) and Ineffective Sales (0.741) are loaded in factor six. The variables of High Storage of Raw-Materials and Finished Stones (0.566) and Affected by Seasons (0.844) are loaded in factor seven.

It is also observed from the above table that the synthetic gem manufacturers are affected by the problems in marketing.

209 Factor Analysis VII

Table - 4.62

Factors contributing to Performance of Traders

Initial Eigen values Rotation Sums of Squared Loadings Components % of Cumulative % of Cumulative Total Total Variance % Variance % 1 5.147 32.169 32.169 3.843 24.019 24.019 2 2.398 14.985 47.154 2.903 18.147 42.166 3 2.106 13.161 60.315 2.878 17.985 60.151 4 1.322 8.265 68.581 1.349 8.429 68.581 5 0.997 6.231 74.811 6 0.920 5.749 80.560 7 0.801 5.006 85.566 8 0.591 3.693 89.259 9 0.496 3.098 92.358 10 0.393 2.459 94.816 11 0.279 1.745 96.562 12 0.238 1.489 98.050 13 0.126 0.787 98.838 14 0.102 0.637 99.474 15 0.049 0.308 99.783 16 0.035 0.217 100.000

Extraction Method: Principal Component Analysis.

The above table explained that factor analysis by principal component method with varimax rotation has revealed four Eigen values such as 5.147, 2.398, 2.106 and 1.322. This indicated that the Eigen values greater than 1 led to the existence of four major factors with 68.58 percent of variance (Table 4.62).These factors are subjected to continuous varimax rotation with respect to the correlation values and component-wise segregation which is given below:

210 Table -4.63

Rotated Component Matrix on Factors influencing in Performance of Traders

Components Variables / Factors 1 2 3 4 Availability of synthetic gems 0.027 -0.080 0.183 0.826 Power supply -0.094 0.397 0.597 -0.031 Transportation -0.027 0.316 0.795 0.017 Government Policy 0.882 0.097 0.010 0.064 Support of Association 0.238 0.446 0.545 0.070 Availability of skilled labour 0.800 -0.011 0.339 -0.148 Cost of labour 0.694 -0.008 0.394 -0.118 Labour turnover 0.352 0.086 0.770 -0.108 Accessibility of bank loan 0.074 0.847 0.166 0.211 Hassle free bank loan formalities -0.019 0.788 0.256 -0.312 Interest on loan 0.040 0.656 -0.102 0.534 Support from other funding agencies 0.318 0.595 0.007 -0.253 Storage facilities -0.010 0.091 0.662 0.269 Annual turnover 0.843 -0.047 0.023 0.203 Selling price 0.753 0.320 -0.172 -0.047 Sales promotional activities 0.606 0.433 0.350 0.047

The rotated component matrix in the above table explained the variable loadings in each predominant factor influence the performance of synthetic gem traders. It is observed that the factors of performance of traders consisted of sixteen variables such as Availability of synthetic gems, Power supply, Transportation, Government policy, Support of Association, Availability of skilled labour, Cost of Labour, Labour turnover, Accessibility of bank loan, Hassle free bank loan formalities, Interest on loan, Support from other funding agencies, Storage facilities, Annual Turnover, Selling price and Sales Promotional activities.

211 The variables of Government Policy (0.882), Availability of skilled labour (0.800), Cot of labour (0.694), Annual Turnover (0.843), Selling Price (0.753) and Sales Promotional Activities (0.606) are loaded in Component Factor one. The variables of Accessibility of Bank Loan (0.847), Hassle Free Bank Loan Formalities (0.788), Interest on Loan (0.656), and Support from other funding agencies (0.595) are loaded in Component Factor two. Power Supply (0.597) Transportation (0.795), Support of Association (0.545), Labour Turnover (0.770) and Storage Facilities (0.662) variables are loaded in Component Factor three. The remaining factor of Availability of Synthetic Gems (0.826) is loaded in Component Factor four.

It is also observed from the above table that the synthetic gem traders are affected by the performance factors of traders.

212 C. One-way Anova Analysis

Influence the Profile Factors of Synthetic Gem Manufacturers on the Factors of Performance of Synthetic Gem Manufacturers.

The six predominant performance factors of synthetic gem manufacturers as revealed by factor analysis on profile factors of synthetic gem manufacturers have been analyzed to measure their influence. The said performances have been taken as dependent variables and profile of synthetic gem manufacturers such as years of experience, type of industry, nature of manufacture and type of stones manufacturing as independent variables. One-way Analysis of Variance (ANOVA) is applied to find out the influence of independent variables on dependent variables.

The following ANOVA tables clearly indicated the influence of factors of synthetic gem manufacturers‟ opinion on performance of their manufacture on years of experience of manufacturers, type of industry, nature of manufacture and type of stones manufactured.

213 ANOVA – 1

Table -4.64

Influence of Performance Factors of Synthetic Gem

Manufacturers on Years of Experience

Sum of Mean Variables / Factors Squares df Square F Sig. Between Groups 3.662 3 1.221 2.535 0.048 Modernized Equipments and Within Groups 89.580 186 0.482 Machinery Total 93.242 189

Between Groups 15.244 3 5.081 8.63 0.000

Government Policy and Support Within Groups 109.519 186 0.589

Total 124.763 189

Between Groups 12.867 3 4.289 8.568 0.000

Availability of Labour Within Groups 93.112 186 0.501

Total 105.979 189

Between Groups 10.433 3 3.478 5.403 0.001

Accessibility of Bank Loan Within Groups 119.719 186 0.644

Total 130.152 189

Between Groups 8.304 3 2.768 4.619 0.004 Support from market Within Groups 111.465 186 0.599 intermediaries Total 119.769 189

Between Groups 11.983 3 3.994 6.497 0.000

Annual Turnover Within Groups 114.359 186 0.615

Total 126.342 189

The Anova analysis on table 4.64, shows the component of years of experience of manufacturers has significant difference across the Modernized equipment and machinery (F-value = 2.535, p<0.05), across the Government policy and support (F-value = 8.630, p<0.05), across the availability of labour (F-value = 8.568, p<0.05), across the accessibility of bank loan (F-value = 5.403, p<0.05), across the support from market

214 intermediaries (F-value = 4.619, p<0.05), and across the annual turnover (F-value 6.497, p<0.05). So, it is revealed that the performance factors of manufacturers are influenced by the years of experience.

ANOVA – 2

Table - 4.65

Influence of Performance Factors of Synthetic Gem

Manufacturers on Type of Industry

Sum of Mean Variables / Factors Squares Df Square F Sig.

Between Groups 2.863 1 2.863 4.416 0.037 Modernized Equipments and Within Groups 121.900 188 0.648 Machinery Total 124.763 189

Between Groups 0.780 1 0.780 1.587 0.209

Government Policy and Support Within Groups 92.462 188 0.492

Total 93.242 189

Between Groups 2.576 1 2.576 4.684 0.032

Availability of Labour Within Groups 103.403 188 0.550

Total 105.979 189

Between Groups 0.026 1 0.026 0.038 0.846

Accessibility of Bank Loan Within Groups 130.127 188 0.692

Total 130.153 189

Between Groups 3.165 1 3.165 5.104 0.025

Support from market intermediaries Within Groups 116.603 188 0.620

Total 119.768 189

Between Groups 0.089 1 0.089 0.133 0.716

Annual Turnover Within Groups 126.253 188 0.672

Total 126.342 189

215 The Anova analysis on table 4.65, shows the component type of industry has significant difference across the Modernized equipment and machinery (F-value = 4.416, p<0.05), across the availability of labour (F- value = 4.684, p<0.05), and across the support from market intermediaries (F-value = 5.104, p<0.05). So, it is revealed that the above three performance factors of manufacturers are influenced by the type of industry.

But the type of industry has no significant difference across the Government policy and support (F-value =1.587, p>0.05), across the accessibility of bank loan (F-value = 0.038, p>0.05), and across the annual turnover (F-value = 0.133, p>0.05).So, the rest of these three performance factors of manufacturers are not influenced by the type of industry.

216 ANOVA – 3

Table -4.66

Influence of Performance Factors of Synthetic Gem

Manufacturers on Nature of Manufacture

Sum of Mean Variables / Factors Squares df Square F Sig.

Between Groups 3.226 2 1.613 3.246 0.043 Modernized Equipments and Within Groups 92.016 187 0.492 Machinery Total 95.242 189

Between Groups 3.533 2 1.766 3.725 0.038

Government Policy and Support Within Groups 121.230 187 0.648

Total 124.763 189

Between Groups 5.927 2 2.963 5.539 0.005

Availability of Labour Within Groups 100.052 187 0.535

Total 105.979 189

Between Groups 15.202 2 7.601 12.365 0.000

Accessibility of Bank Loan Within Groups 114.951 187 0.615

Total 130.153 189

Between Groups 11.509 2 5.754 9.940 0.000 Support from market Within Groups 108.260 187 0.579 intermediaries Total 119.769 189

Between Groups 5.729 2 2.864 4.441 0.013

Annual Turnover Within Groups 120.613 187 0.645

Total 126.342 189

The Anova analysis on table 4.66, shows the component nature of manufacture has significant difference across the Modernized equipment and machinery (F-value = 3.246, p<0.05), across the Government policy and support (F-value = 3.725, p<0.05), across the availability of labour (F-value = 5.539, p<0.05), across the accessibility of bank loan (F-value =

217 12.365, p<0.05), across the support from market intermediaries (F-value = 9.940, p<0.05), and across the annual turnover (F-value 4.441, p<0.05). So, it is revealed that the performance factors of manufacturers are influenced by the nature of manufacture.

ANOVA – 4

Table -4.67

Influence of Performance Factors of Synthetic Gem

Manufacturers on Kinds of Stones Manufacture

Variables / Factors Sum of Squares df Mean Square F Sig.

Between Groups 4.827 3 1.609 2.884 0.046 Modernized Equipments Within Groups 91.414 186 0.491 and Machinery Total 96.241 189

Between Groups 19.531 3 6.510 11.507 0.000 Government Policy and Within Groups 105.232 186 0.566 Support Total 124.763 189

Between Groups 4.368 3 1.456 2.665 0.049

Availability of Labour Within Groups 101.611 186 0.546

Total 105.979 189

Between Groups 4.575 3 1.525 2.740 0.047

Accessibility of Bank Loan Within Groups 127.079 186 0.683

Total 131.654 189

Between Groups 7.740 3 2.580 4.284 0.006 Support from market Within Groups 112.028 186 0.602 intermediaries Total 119.768 189

Between Groups 7.914 3 2.638 4.143 0.007

Annual Turnover Within Groups 118.428 186 0.637

Total 126.342 189

218

The Anova analysis on table 4.67, shows the component kinds of stone manufacture has significant difference across the Modernized equipment and machinery (F-value = 2.884, p<0.05), across the Government policy and support (F-value = 11.507, p<0.05), across the availability of labour (F-value = 2.665, p<0.05), across the accessibility of bank loan (F-value = 2.740, p<0.05), across the support from market intermediaries (F-value = 4.284, p<0.05), and across the annual turnover (F-value 4.143, p<0.05). So, it is revealed that the performance factors of manufacturers are influenced by the kinds of stones manufacture.

219 D. Chi-Square Test

Chi-square, symbolically written as (Pronounced as Ki-square), is a statistical measure used in the context of sampling analysis for comparing a variance to a theoretical variance. It is a technique possible to test the goodness of fit and significance association between two attributes. It can also be used as a test of independence.

This statistical technique has been used to test the significant association between the specific factors of manufacturers and the performance factors of synthetic gem industry.

Chi-Square Test – 1

(i) Association between Age of Synthetic Gem Manufacturers and Modernized Equipment and Machinery

The Chi-square Test analysis is performed between the cluster of Age of manufacturers of synthetic gems and their varied opinion on Modernized Equipments and Machinery. Further, chi-square test is applied to test the proximity of the same.

220 Table – 4.68

Age of Synthetic Gem Manufacturers and Modernized

Equipment and Machinery

Modernized Equipments and Factors Machinery Total

Low Medium High Count 7 7 0 14 21-30 years Expected Count 9.2 3.1 1.7 14 Count 37 0 7 44 31-40 years Age of Expected Count 28.9 9.7 5.3 44 Traders Count 76 27 13 116 41-50 years Expected Count 76.3 25.6 14 116 Count 5 8 3 16 Above 50 years Expected Count 10.5 3.5 1.9 16 Count 125 42 23 190 Total Expected Count 125 42 23 190

From the above table it was found that the synthetic gem Manufacturers with the maximum of 116 who are in the age of 41 -50 years opined about their performance of their field. 76 out of 116 respondents of 41 - 50 years of age opined that their performance of their field is low.

221 The following table indicated the nature of association between age of synthetic gem manufacturers and clusters of modernized equipments and machinery.

Table- 4.69

Association between Age of Synthetic Gem Manufacturers and

Modernized Equipment and Machinery

Tests Value Df Sig.

Pearson Chi-Square 28.913 6 0.000**

Likelihood Ratio 37.964 6 0.000**

Linear-by-Linear Association 2.903 1 0.088

N of Valid Cases 190

**significant at 1% level

Ho – There is no association between the Age of Synthetic Gem Manufacturers and Modernized Equipment and Machinery

The chi-square test divulged that the Pearson chi-square value is equal to 28.913 and likelihood ratio of 37.964 along with linear by linear association of 2.903. All the probabilistic values are significant at 5 percent level. ( Hence, the null hypothesis is rejected. Therefore, it is concluded that there is an association found between the age of manufacturers and modernized equipments and machinery of synthetic gem industry.

222 (ii) Association between Age of Synthetic Gem Manufacturers and Government Policy and Support

Now, the association between Age of synthetic manufacturers and Government Policy and support were analyzed by using the Chi-square test. The significant relationships of the above variables were extracted by taking the opinion of the respondents which is explained below:

Table – 4.70

Age of Synthetic Gem Manufacturers and Government Policy and Support

Government Policy and Support Factors Total Low Medium High Count 13 0 1 14 21-30 years Expected Count 7.8 3.2 3 14 Count 19 7 18 44 31-40 years Age of Expected Count 24.5 10 9.5 44 Traders Count 58 36 22 116 41-50 years Expected Count 64.7 26.3 25 116 Count 16 0 0 16 Above 50 years Expected Count 8.9 3.6 3.5 16 Count 106 43 41 190 Total Expected Count 106 43 41 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 116 who are in the age of 41 -50 years opined about their performance of their field. 58 out of 116 respondents of 41 - 50 years of age opined that Government Policy and Support is low.

223 The following table indicated the nature of association between Age of synthetic gem manufacturers and clusters of Government policy and support.

Table- 4.71

Association between Age of Synthetic Gem Manufacturers and Government Policy and Support

Tests Value Df Sig.

Pearson Chi-Square 35.082 6 0.000**

Likelihood Ratio 42.413 6 0.000**

Linear-by-Linear Association 1.571 1 0.210

N of Valid Cases 190

**significant at 1% level

Ho – There is no association between the Age of Synthetic Gem Manufacturers and Government Policy and Support

The chi-square test divulged that the Pearson chi-square value is equal to 35.082 and likelihood ratio of 42.413 along with linear by linear association of 1.571. All the probabilistic values are significant at 5 percent level. ( Hence, the null hypothesis is rejected. Therefore, it is concluded that there is an association found between the Age of Synthetic Gem manufacturers and Government policy and support of synthetic gem industry

224 (iii) Association between Age of Synthetic Gem Manufacturers and Availability of Labour

The Chi-square Test analysis is performed between the clusters of age of manufacture of synthetic gem manufacturers and their varied opinion on availability of labour. Further, chi-square test is applied to test the proximity of the same.

Table – 4.72

Age of Synthetic Gem Manufacturers and Availability of Labour

Availability of Labour Factors Total Low Medium High Count 9 1 4 14 21-30 years Expected Count 8 3.8 2.2 14 Count 41 0 3 44 31-40 years Age of Expected Count 25 12 6.9 44 Traders Count 50 43 23 116 41-50 years Expected Count 65.9 31.7 18.3 116 Count 8 8 0 16 Above 50 years Expected Count 9.1 4.4 2.5 16 Count 108 52 30 190 Total Expected Count 108 52 30 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 116 who are in the age of 41 -50 years opined about their performance of their field. 50 out of 116 respondents of 41 - 50 years of age opined that Availability of Labour is low.

225 The following table indicated the nature of association between Age of synthetic gem manufacturers and clusters of Availability of labour.

Table- 4.73

Association between Age of Synthetic Gem Manufacturers and

Availability of Labour

Tests Value df Sig.

Pearson Chi-Square 42.876 6 0.000**

Likelihood Ratio 56.255 6 0.000**

Linear-by-Linear Association 5.187 1 0.023*

N of Valid Cases 190

**significant at 1% level *significant at 5% level

Ho – There is no association between the Age of Synthetic Gem Manufacturers and Availability of Labour

The chi-square test divulged that the Pearson chi-square value is equal to 42.876 and likelihood ratio of 56.255 along with linear by linear association of 5.187. All the probabilistic values are significant at 5 percent level ( Hence, the null hypothesis is rejected. Therefore, it is concluded that there is an association found between the age of manufacturers and Availability of Labour of synthetic gem industry.

226 (iv) Association between Age of Synthetic Gem Manufacturers and Annual Turnover

The Chi-square Test analysis is performed between the clusters of age of manufacture of synthetic gem manufacturers and their varied opinion on annual turnover. Further, chi-square test is applied to test the proximity of the same.

Table – 4.74

Age of Synthetic Gem Manufacturers and Annual Turnover

Annual Turnover Factors Total Low Medium High Count 9 5 0 14 21-30 years Expected Count 6.7 3.9 3.4 14 Count 34 2 8 44 31-40 years Age of Expected Count 21.1 12.3 10.7 44 Traders Count 45 38 33 116 41-50 years Expected Count 55.6 32.4 28.1 116 Count 3 8 5 16 Above 50 years Expected Count 7.7 4.5 3.9 16 Count 91 53 46 190 Total Expected Count 91 53 46 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 116 who are in the age of 41 -50 years opined about their performance of their field. 45 out of 116 respondents of 41 - 50 years of age opined that their annual turnover is low.

227 The following table indicated the nature of association between Age of synthetic gem manufacturers and clusters of their annual turnover.

Table- 4.75

Association between Age of Synthetic Gem Manufacturers and

Annual Turnover

Tests Value df Sig.

Pearson Chi-Square 31.489 6 0.000**

Likelihood Ratio 38.612 6 0.000**

Linear-by-Linear Association 16.113 1 0.000**

N of Valid Cases 190

**significant at 1% level or 0.01 level

Ho – There is no association between the Age of Synthetic Gem Manufacturers and Annual Turnover.

The chi-square test divulged that the Pearson chi-square value is equal to 31.489 and likelihood ratio of 38.612 along with linear by linear association of 16.113. All the probabilistic values are significant at 5 percent level. ( 31.489, d.f. = 6, p<0.05). Hence, the null hypothesis is rejected. Therefore, it is concluded that there is an association found between the age of manufacturers and Annual Turnover of synthetic gem industry.

228 Over all test – 1: The Association between the Age of Manufacturers and the Performance Factors of Synthetic Gem Industry.

Hypothesis: There exist an association between the Age of Manufacturers and the Performance Factors of Synthetic Gem Industry.

The association between Age of Manufacturers and the Performance Factors was examined through chi-square test.

The table below describes the result of Chi-square analysis and various components of performances, chi-square values, p values and their significance on the age of the manufacturers in Synthetic Gem Industry. The overall performance components are Modernized Equipment and Machinery, Government Policy and Support, Availability of Labour and Annual Turnover

Table – 4.76

Association between Age of Manufacturers and Performance factors:

Pearson Sl. No Performance Factors Chi-square p-value Value

1 Modernized Equipment and Machinery 28.913 0.000**

2 Government Policy and Support 35.082 0.000**

3 Availability of Labour 42.876 0.000**

4 Annual Turnover 31.489 0.000**

* Significant at the 0.05 level **significant at 0.01 level

It is evident that the Age of manufacturers is statistically significant and positively associated with Modernized Equipment and Machinery, Government Policy and Support, Availability of Labour and Annual

229 Turnover. Hence the age of the manufacturers influences the factors of performance of synthetic gem industry. It is found from the table that the hypothesis is accepted with all components of performance factors. The table reveals that there is a Significant Association between the Age of Manufacturers and the Performance Factors of Synthetic Gem Industry.

Chi-Square Test – 2

(i) Association between Educational Qualification of Synthetic Gem Manufacturers and Modernized Equipments and Machinery:

The Chi-square Test analysis is performed between the clusters of Educational Qualification of synthetic gem manufacturers and their varied opinion on Modernized Equipments and Machinery. Further, chi-square test is applied to test the proximity of the same.

Table – 4.77

Educational Qualification of Synthetic Gem Manufacturers and

Modernized Equipments and Machinery

Modernized Equipments Factors and Machinery Total

Low Medium High Count 96 35 23 154 Up to SSLC Expected Count 101.3 34 18.6 154

Count 15 0 0 15 HSC Expected Count 9.9 3.3 1.8 15 Count 8 7 0 15 UG

Expected Count 9.9 3.3 1.8 15 Manufacturer Count 6 0 0 6 PG

Educational Qualification of Expected Count 3.9 1.3 0.7 6 Count 125 42 23 190 Total Expected Count 125 42 23 190

230 From the above table it was found that the synthetic gem manufacturers‟ with the maximum of 154 who studied up to S.S.L.C opined about their performance of their field. 96 out of 154 opined that their opinion on modernized equipments and machinery is low.

The following table indicated the nature of association between Educational Qualification of synthetic gem manufacturers and clusters of Modernized Equipments and Machinery.

Table- 4.78

Association between Educational Qualification of Synthetic Gem Manufacturers and Modernized Equipments and Machinery

Tests Value df Sig.

Pearson Chi-Square 18.508 6 0.005**

Likelihood Ratio 25.947 6 0.000**

Linear-by-Linear Association 4.320 1 0.038*

N of Valid Cases 190

**significant at 1% level *significant at 5% level

Ho – There is no association between the Educational Qualification of Synthetic Gem Manufacturers and Modernized Equipments and Machinery.

The chi-square test divulged that the Pearson chi-square value is equal to 18.508 and likelihood ratio of 25.947 along with linear by linear association of 4.320. All the probabilistic values are significant at 5 percent level. ( 18,508, d.f. = 6, p<0.05). Hence, the null hypothesis is rejected.

Therefore, it is concluded that there is an association found between the

231 Educational Qualification of manufacturers and Modernized Equipments and Machinery of synthetic gem industry.

(ii) Association between Educational Qualification of Synthetic Gem Manufacturers and Government Policy and Support

The Chi-square Test analysis is performed between the clusters of Educational Qualification of synthetic gem manufacturers and their varied opinion on Government Policy and Support. Further, chi-square test is applied to test the proximity of the same.

Table – 4.79

Educational Qualification of Synthetic Gem Manufacturers and

Government Policy and Support

Government Policy and Support Factors Total

Low Medium High Count 92 36 26 154 Up to SSLC Expected Count 85.9 34.9 33.2 154

Count 3 7 5 15 HSC Expected Count 8.4 3.4 3.2 15 Count 8 0 7 15 UG

Expected Count 8.4 3.4 3.2 15 Manufacturer Count 3 0 3 6 PG

Educational Qualification of Expected Count 3.3 1.4 1.3 6 Count 106 43 41 190 Total Expected Count 106 43 41 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 154 who studied up to S.S.L.C opined

232 about their performance of their field. 92 out of 154 opined that their opinion on Government Policy and Support is low.

The following table indicated the nature of association between Educational Qualification of synthetic gem manufacturers and clusters of Government Policy and Support.

Table- 4.80

Association between Educational Qualification of Synthetic Gem Manufacturers and Government Policy and Support

Tests Value df Sig.

Pearson Chi-Square 21.701 6 0.001**

Likelihood Ratio 24.948 6 0.000**

Linear-by-Linear Association 6.509 1 0.011*

N of Valid Cases 190

**significant at 1% level *significant at 5% level

Ho – There is no association between the Educational Qualification of Synthetic Gem Manufacturers and Government Policy and Support.

The chi-square test divulged that the Pearson chi-square value is equal to 21.701 and likelihood ratio of 24.948 along with linear by linear association of 6.509. All the probabilistic values are significant at 5 percent level. ( 21.701, d.f. = 6, p<0.05).Hence, the null hypothesis is rejected.

Therefore, it is concluded that there is an association found between the Educational Qualification of manufacturers and Government Policy and Support of synthetic gem industry.

233 (iii) Association between Educational Qualification of Synthetic Gem Manufacturers and Availability of Labour

The Chi-square Test analysis is performed between the clusters of Educational Qualification of synthetic gem manufacturers and their varied opinion on Availability of Labour. Further, chi-square test is applied to test the proximity of the same.

Table – 4.81

Educational Qualification of Synthetic Gem Manufacturers and

Availability of Labour

Availability of Labour Factors Total

Low Medium High Count 75 52 27 154 Up to SSLC Expected Count 87.5 42.1 24.3 154

Count 15 0 0 15 HSC Expected Count 8.5 4.1 2.4 15 Count 13 0 2 15 UG

Expected Count 8.5 4.1 2.4 15 Manufacturer Count 5 0 1 6 PG

Educational Qualification of Expected Count 3.4 1.6 0.9 6 Count 108 52 30 190 Total Expected Count 108 52 30 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 154 who studied up to S.S.L.C opined about their performance of their field. 75 out of 154 opined that their opinion on Government Policy and Support is low.

234 The following table indicated the nature of association between Educational Qualification of synthetic gem manufacturers and clusters of Availability of Labour.

Table- 4.82

Association between Educational Qualification of Synthetic Gem Manufacturers and Availability of Labour

Tests Value df Sig.

Pearson Chi-Square 24.680 6 0.000**

Likelihood Ratio 35.487 6 0.000**

Linear-by-Linear Association 8.830 1 0.003**

N of Valid Cases 190

**significant at 1% level

Ho – There is no association between the Educational Qualification of Synthetic Gem Manufacturers and Availability of Labour.

The chi-square test divulged that the Pearson chi-square value is equal to 24.680 and likelihood ratio of 35.487 along with linear by linear association of 8.830. All the probabilistic values are significant at 5 percent level. ( 24.680, d.f. = 6, p<0.05). Hence, the null hypothesis is rejected.

Therefore, it is inferred that there is an association found between the Educational Qualification of traders and Availability of Labour of synthetic gem industry.

235 (iv) Association between Educational Qualification of Synthetic Manufacturers and Annual Turnover

The Chi-square Test analysis is performed between the clusters of Educational Qualification of synthetic gem manufacturers and their varied opinion on Annual Turnover. Further, chi-square test is applied to test the proximity of the same.

Table – 4.83

Educational Qualifications of Synthetic Gem Manufacturers and

Annual Turnover

Annual Turnover Factors Total

Low Medium High Count 66 46 42 154 Up to SSLC Expected Count 73.8 43 37.3 154

Count 9 2 4 15 HSC Expected Count 7.2 4.2 3.6 15 Count 10 5 0 15 UG

Expected Count 7.2 4.2 3.6 15 Manufacturer Count 6 0 0 6 PG

Educational Qualification of Expected Count 2.9 1.7 1.5 6 Count 91 53 46 190 Total Expected Count 91 53 46 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 154 who studied up to S.S.L.C opined about their performance of their field. 66 out of 154 opined that their opinion on Annual Turnover is low.

236 The following table indicated the nature of association between Educational Qualification of synthetic gem manufacturers and cluster of Annual Turnover.

Table- 4.84

Association between Educational Qualifications of Synthetic

Gem Manufacturers and Annual Turnover

Tests Value df Sig.

Pearson Chi-Square 14.686 6 0.023*

Likelihood Ratio 20.735 6 0.002**

Linear-by-Linear Association 10.910 1 0.001**

N of Valid Cases 190

**significant at 1% level *significant at 5% level

Ho – There is no association between the Educational Qualification of Synthetic Gem manufacturers and Annual Turnover.

The chi-square test divulged that the Pearson chi-square value is equal to 14.686 and likelihood ratio of 20.735 along with linear by linear association of 10.910. All the probabilistic values are significant at 5 percent level. ( 14.686, d.f. = 6, p<0.05). Hence, the null hypothesis is rejected. Therefore, it is inferred that there is an association found between the Educational Qualification of manufacturers and Annual Turnover of synthetic gem industry.

237 Overall Test – 2: The Association between the Educational Qualification of Manufacturers and the Performance Factors of Synthetic Gem Industry.

Hypothesis: There exist an association between the Educational Qualification of Manufacturers and the Performance Factors of Synthetic Gem Industry.

The association between the Educational Qualification of Manufacturers and the Performance Factors was examined through chi- square test.

The table below describes the result of Chi-square analysis and various components of performances, chi-square values, p values and their significance on the educational qualification of synthetic gem manufacturers. The overall performance components are Modernized Equipment and Machinery, Government Policy and Support, Availability of Labour and Annual Turnover

Table – 4.85

Association between Educational Qualification of Manufacturers and Performance factors

Pearson Sl. No Performance Factors Chi-square p-value Value

1 Modernized Equipment and Machinery 18.508 0.005**

2 Government Policy and Support 21.701 0.001**

3 Availability of Labour 24.680 0.000**

4 Annual Turnover 14.686 0.023*

**significant at the 0.01 level * Significant at the 0.05 level

238 It is evident that the Educational Qualification of manufacturers is statistically significant and positively associated with Modernized Equipment and Machinery, Government Policy and Support, Availability of Labour and Annual Turnover. Hence the Educational Qualification of the manufacturers influences the factors of performance of synthetic gem industry. It is found from the table that the hypothesis is accepted with all components of performance factors.

The table reveals that there is a Significant Association between the Educational Qualification of Manufacturers and the Performance Factors of Synthetic Gem Industry

239

Chi-Square Test – 3

(i) Association between Type of Industry and Modernized Equipments and Machinery

The Chi-square Test analysis is performed between the clusters of Type of Industry and their varied opinion on Modernized Equipments and Machinery. Further, chi-square test is applied to test the proximity of the same.

Table – 4.86

Type of Industry and Modernized Equipments and Machinery

Modernized Equipments and Factors Machinery Total

Low Medium High Count 116 33 21 170 Cottage Type of Expected Count 111.8 37.6 20.6 170 Industry Count 9 9 2 20 SSI Expected Count 13.2 4.4 2.4 20 Count 125 42 23 190 Total Expected Count 125 42 23 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 170 who owned Cottage Industry opined about their performance of their field. 116 out of 170 opined that their opinion on Modernized Equipments and Machinery is low.

240 The following table indicated the nature of association between Type of Industry of synthetic gem manufacturers and clusters of Modernized Equipments and Machinery.

Table- 4.87

Association between Type of Industry and Modernized

Equipments and Machinery

Tests Value df Sig.

Pearson Chi-Square 6.851 2 0.033*

Likelihood Ratio 5.938 2 0.051

Linear-by-Linear Association 1.582 1 0.209

No of Valid Cases 190

*significant at the 0.05 level

Ho – There is no association between the Type of Industry and Modernized Equipments and Machinery.

The chi-square test divulged that the Pearson chi-square value is equal to 6.851 and likelihood ratio of 5.938 along with linear by linear association of 1.582. All the probabilistic values are significant at 5 percent level ( 6.851, d.f. =2, p<0.05). Hence, the null hypothesis is rejected.

Therefore, it is found that there is an association between the Type of Industry and Modernized Equipments and Machinery of synthetic gem industry.

241 (ii) Association between Type of Industry and Government Policy and Support

The Chi-square Test analysis is performed between the clusters of Type of Industry and their varied opinion on Government Policy and Support. Further, chi-square test is applied to test the proximity of the same.

Table – 4.88

Type of Industry and Government Policy and Support

Government Policy and Support Total Factors

Low Medium High Count 90 41 39 170 Cottage Type of Expected Count 94.8 38.5 36.7 170 Industry Count 16 2 2 20 SSI Expected Count 11.2 4.5 4.3 20 Count 106 43 41 190 Total Expected Count 106 43 41 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 170 who owned Cottage Industry opined about their performance of their field. 90 out of 170 opined that their opinion on Government Policy and Support is low.

242 The following table indicated the nature of association between Type of Industry of synthetic gem manufacturers and clusters of Government Policy and Support.

Table-4.89

Association between Type of Industry and Government Policy and Support

Tests Value df Sig.

Pearson Chi-Square 5.313 2 0.070

Likelihood Ratio 5.748 2 0.056

Linear-by-Linear Association 4.337 1 0.037*

No of Valid Cases 190

*significant at the 0.05 level

Ho – There is no association between the Type of Industry and Government Policy and Support.

The chi-square test divulged that the Pearson chi-square value is equal to 5.313 and likelihood ratio of 5.748 along with linear by linear association of 4.337. All the probabilistic values are significant at 5 percent level. 5.313, d.f. =2, p>0.05). Hence, the null hypothesis is accepted.

Therefore, it is found that there is no association between the Type of Industry and Government Policy and Support of synthetic gem industry.

243 (iii) Association between Type of Industry and Availability of Labour

The Chi-square Test analysis is performed between the clusters of Type of Industry and their varied opinion on Availability of Labour. Further, chi-square test is applied to test the proximity of the same.

Table – 4.90

Type of Industry and Availability of Labour

Availability of Labour Factors Total

Low Medium High Count 91 51 28 170 Cottage Type of Expected Count 96.6 46.5 26.8 170 Industry Count 17 1 2 20 SSI Expected Count 11.4 5.5 3.2 20 Count 108 52 30 190 Total Expected Count 108 52 30 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 170 who owned Cottage Industry opined about their performance of their field. 91 out of 170 opined that their opinion on Availability of Labour is low.

244 The following table indicated the nature of association between Type of Industry of synthetic gem manufacturers and clusters of Availability of Labour.

Table-4.91

Association between Type of Industry and Availability of Labour

Tests Value df Sig.

Pearson Chi-Square 7.679 2 0.022*

Likelihood Ratio 9.255 2 0.010**

Linear-by-Linear Association 4.594 1 0.032*

No of Valid Cases 190

**significant at the 0.01 level *significant at the 0.05 level

Ho – There is no association between the Type of Industry and Availability of Labour.

The chi-square test divulged that the Pearson chi-square value is equal to 7.679 and likelihood ratio of 9.255 along with linear by linear association of 4.594. All the probabilistic values are significant at 5 percent level. ( 7.679, d.f. =2, p<0.05). Hence, the null hypothesis is rejected.

Therefore, it is found that there is an association between the Type of Industry and Availability of Labour of synthetic gem industry.

245 (iv) Association between Type of Industry and Annual Turnover

The Chi-square Test analysis is performed between the clusters of Type of Industry and their varied opinion on Annual Turnover. Further, chi-square test is applied to test the proximity of the same.

Table – 4.92

Type of Industry and Annual Turnover

Annual Turnover Factors Total

Low Medium High Count 82 45 43 170 Cottage Type of Expected Count 81.4 47.4 41.2 170 Industry Count 9 8 3 20 SSI Expected Count 9.6 5.6 4.8 20 Count 91 53 46 190 Total Expected Count 91 53 46 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 170 who owned Cottage Industry opined about their performance of their field. 82 out of 170 opined that their opinion on Annual Turnover is low.

246 The following table indicated the nature of association between Type of Industry of synthetic gem manufacturers and clusters of Annual Turnover.

Table-4.93

Association between Type of Industry and Annual Turnover

Tests Value Df Sig.

Pearson Chi-Square 1.997 2 0.369

Likelihood Ratio 1.984 2 0.371

Linear-by-Linear Association 0.133 1 0.715

No of Valid Cases 190

Ho – There is no association between the Type of Industry and Annual Turnover.

The chi-square test divulged that the Pearson chi-square value is equal to 1.997 and likelihood ratio of 1.984 along with linear by linear association of 0.133. All the probabilistic values are significant at 5 percent level ( 1.997, d.f. =2, p>0.05). Hence, the null hypothesis is accepted.

Therefore, it is found that there is no association between the Type of Industry and the Annual Turnover.

247 Over all Test – 3: The Association between the Type of Industry and the Performance Factors of Synthetic Gem Industry.

Hypothesis: There exist an association between the Type of Industry and the Performance Factors of Synthetic Gem Industry.

The association between the Type of Industry and the Performance Factors was examined through chi-square test.

The table below describes the result of Chi-square analysis and various components of performances, chi-square values, p values and their significance on the type of industry. The overall performance components are modernized Equipment and Machinery, Government Policy and Support, Availability of Labour and Annual Turnover.

Table – 4.94

Association between Type of Industry and Performance Factors

Pearson Sl. No Performance Factors Chi-square p-value Value

1 Modernized Equipment and Machinery 6.851 0.033*

2 Government Policy and Support 5.313 0.070

3 Availability of Labour 7.679 0.022*

4 Annual Turnover 1.997 0.369

*Significant at the 0.05 level

It is evident that the type of industry is statistically significant and positively associated with modernized equipment and machinery and availability of labour. But, the type of industry is statistically not

248 significant and not positively associated with government policy and support and annual turnover factors.

Hence the type of industry influences the performance factors of modernized equipment and machinery and availability of labour of synthetic gem industry. But, the type of industry does not influence the performance factors of government policy and support and annual turnover. It is found from the table that the hypothesis of existence of association between type of industry and the performance factors of modernized equipment and machinery and availability of labour are accepted. But, the hypothesis of existence of association between type of industry and the performance factors of government policy and support and annual turnover are not accepted.

The table reveals that there is Partly Significant Association and Partly Non-significant Association between the Type of Industry and the Performance Factors of Synthetic Gem Industry respectively.

249 Chi-Square Test – 4

(i) Association between Years of Experience of the Manufacturers and Modernized Equipments and Machinery

The Chi-square Test analysis is performed between the clusters of Years of experience of Manufacturers and their varied opinion on Modernized Equipments and Machinery. Further, chi-square test is applied to test the proximity of the same.

Table – 4.95

Years of Experience of Manufacturers and Modernized

Equipments and Machinery

Modernized Equipments and Factors Machinery Total

Low Medium High

Count 28 7 1 36 11-15 years Expected Count 23.7 8 4.4 36 Count 28 17 8 53 16-20 years Expected Count 34.9 11.7 6.4 53 Count 69 18 14 101 Above 20 years Years Experienceof Expected Count 66.4 22.3 12.2 101 Count 125 42 23 190 Total Expected Count 125 42 23 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 101 who is having above 20 years of experience opined about their performance of their field. 69 out of 101 opined that their opinion on Modernized Equipments and Machinery is low.

250 The following table indicated the nature of association between Years of Experience of Manufacturers and Modernized Equipments and Machinery.

Table- 4.96

Association between Years of Experience of Manufacturers and

Modernized Equipments and Machinery

Tests Value df Sig.

Pearson Chi-Square 9.810 4 0.046*

Likelihood Ratio 10.779 4 0.034*

Linear-by-Linear Association 0.840 1 0.360

N of Valid Cases 190

*significant at the 0.05 level

Ho – There is no association between the Years of Experience of Manufacturers and Modernized Equipments and Machinery.

The chi-square test divulged that the Pearson chi-square value is equal to 9.810 and likelihood ratio of 10.779 along with linear by linear association of 0.840. All the probabilistic values are significant at 5 percent level ( 9.810, d.f.=4, p<0.05). Hence, the null hypothesis is rejected.

Therefore, it is found that there is an association between the Years of Experience of Manufacturers and Modernized Equipments and Machinery of synthetic gem industry.

251 (ii) Association between Years of Experience of Manufacturers and Government Policy and Support

The Chi-square Test analysis is performed between the clusters of Years of experience of manufactures and their varied opinion on Government Policy and Support. Further, chi-square test is applied to test the proximity of the same.

Table – 4.97

Years of Experience of Manufacturers and Government Policy and Support

Government Policy and Factors Support Total

Low Medium High

Count 16 7 13 36 11-15 years Expected Count 20.1 8.1 7.8 36 Count 38 3 12 53 16-20 years Expected Count 29.6 12 11.4 53 Count 52 33 16 101 Above 20 years

Years Experienceof Expected Count 56.3 22.9 21.8 101 Count 106 43 41 190 Total Expected Count 106 43 41 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 101 who is having above 20 years of experience opined about their performance of their field. 52 out of 101 opined that their opinion on Government Policy and Support is low.

252

The following table indicated the nature of association between Years of Experience of synthetic gem manufacturers and Government Policy and Support.

Table – 4.98

Association between Years of Experience of Manufacturers and

Government Policy and Support

Tests Value df Sig.

Pearson Chi-Square 20.069 4 0.000**

Likelihood Ratio 21.887 4 0.000**

Linear-by-Linear Association 1.529 1 0.216

N of Valid Cases 190

**significant at the 0.01 level

Ho – There is no association between the Years of Experience of Manufacturers and Government Policy and Support.

The chi-square test divulged that the Pearson chi-square value is equal to 20.069 and likelihood ratio of 21.887 along with linear by linear association of 1.529. All the probabilistic values are significant at 5 percent level. ( 20.069, d.f.=4, p<0.05). Hence, the null hypothesis is rejected.

Therefore, it is propounded that there is an association found between the Years of Experience of Manufacturers and Government Policy and Support of the Synthetic Gem Industry.

253 (iii) Association between Years of Experience of Manufacturers and Availability of Labour

The Chi-square Test analysis is performed between the clusters of Years of experience of manufacturers and their varied opinion on Availability of Labour. Further, chi-square test is applied to test the proximity of the same.

Table – 4.99

Years of Experience of Manufacturers and Availability of Labour

Availability of Labour Factors Total Low Medium High

Count 31 1 4 36 11-15 years Expected Count 20.5 9.9 5.7 36 Count 35 9 9 53 16-20 years Expected Count 30.1 14.5 8.4 53 Count 42 42 17 101 Above 20 years Years Experienceof Expected Count 57.4 27.6 15.9 101 Count 108 52 30 190 Total Expected Count 108 52 30 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 101 who is having above 20 years of experience opined about their performance of their field. 42 out of 101 opined that their opinion on Availability of Labour is low.

254 The following table indicated the nature of association between Years of Experience of synthetic gem manufacturers and Availability of Labour.

Table- 4.100

Association between Years of Experience of Manufacturers and

Availability of Labour

Tests Value df Sig.

Pearson Chi-Square 28.468 4 0.000**

Likelihood Ratio 32.639 4 0.000**

Linear-by-Linear Association 12.786 1 0.000**

N of Valid Cases 190

**significant at the 0.01 level

Ho – There is no association between the Years of Experience of Manufacturers and Availability of Labour.

The chi-square test divulged that the Pearson chi-square value is equal to 28.468 and likelihood ratio of 32.639 along with linear by linear association of 12.786. All the probabilistic values are significant at 5 percent level ( 28.468, d.f.=4, p<0.05). Hence, the null hypothesis is rejected. Therefore, it is stated that there is an association found between the Years of Experience of Manufacturers and Availability of Labour of the Synthetic Gem Industry.

255 (iv) Association between Years of Experience of Manufacturers and Annual Turnover

The Chi-square Test analysis is performed between the clusters of Years of Experience of Manufacturers and their varied opinion on Annual Turnover. Further, chi-square test is applied to test the proximity of the same.

Table – 4.101

Years of Experience of Manufacturers and Annual Turnover

Annual Turnover Factors Total Low Medium High

Count 25 7 4 36 11-15 years Expected Count 17.2 10 8.7 36 Count 38 5 10 53 16-20 years Expected Count 25.4 14.8 12.8 53 Count 28 41 32 101 Above 20 years Years Experienceof Expected Count 48.4 28.2 24.5 101 Count 91 53 46 190 Total Expected Count 91 53 46 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 101 who is having above 20 years of experience opined about their performance of their field. 41 out of 101 opined that their opinion on Annual Turnover is medium level of satisfaction.

256 The following table indicated the nature of association between Years of Experience of synthetic gem man.

Table- 4.102

Association between Years of Experience of Manufacturers and

Annual Turnover

Tests Value df Sig.

Pearson Chi-Square 37.083 4 0.000**

Likelihood Ratio 39.491 4 0.000**

Linear-by-Linear Association 21.270 1 0.000**

N of Valid Cases 190

**significant at the 0.01 level

Ho – There is no association between the Years of Experience of Manufacturers and Annual Turnover.

The chi-square test divulged that the Pearson chi-square value is equal to 37.083 and likelihood ratio of 39.491 along with linear by linear association of 21.270. All the probabilistic values are significant at 5 percent level. =37.083 d.f. = 4, p< 0.05). Hence, the null hypothesis is rejected. Therefore, it is stated that there is an association found between the Years of Experience of Manufacturers and the Annual Turnover.

257 Over all Test – 4: The Association between the Years of Experience of Manufacturers and the Performance factors of Synthetic Gem Industry.

Hypothesis: There exist an association between the Years of Experience of Manufacturers and the Performance Factors of Synthetic Gem Industry.

The association between the Years of Experience of Manufacturers and the Performance Factors was examined through chi-square test.

The table below describes the result of Chi-square analysis and various components of performances, chi-square values, p values and their significance on the Years of experience of the manufacturers in Synthetic Gem Industry. The overall performance components are modernized Equipment and Machinery, Government Policy and Support, Availability of Labour and Annual Turnover.

Table – 4.103

Association between Years of Experience of Manufacturers and

Performance factors

Pearson Sl. No Performance Factors Chi-square p-value Value

1 Modernized Equipment and Machinery 9.810 0.046*

2 Government Policy and Support 20.069 0.000**

3 Availability of Labour 28.468 0.000**

4 Annual Turnover 37.083 0.000**

* Significant at the 0.05 level **significant at the 0.01 level

258 It is evident that the Years of Experience of manufacturers is statistically significant and positively associated with modernized Equipment and Machinery, Government Policy and Support, Availability of Labour and Annual Turnover. Hence the Years of Experience of the Manufacturers influences the factors of performance of synthetic gem industry. It is found from the table that the hypothesis is accepted with all components of performance factors.

The table reveals that there is a Significant Association between the Years of Experience of Manufacturers and the Performance Factors of Synthetic Gem Industry

259 Chi-Square Test – 5

(i) Association between Nature of Manufacture and Modernized Equipments and Machinery

The Chi-square Test analysis is performed between the clusters of Nature of Manufacture and their varied opinion on Modernized Equipments and Machinery. Further, chi-square test is applied to test the proximity of the same.

Table – 4.104

Nature of Manufacture and Modernized Equipments and Machinery

Modernized Equipments and Factors Machinery Low Medium High Total Count 54 28 7 89 Polishing only Expected Count 58.6 19.7 10.8 89 Count 11 8 3 22 Coning and Faceting Expected Count 14.5 4.9 2.7 22 Count 4 0 3 7 Cutting and Faceting Expected Count 4.6 1.5 0.8 7

Coning, Faceting and Count 56 6 10 72 ManufacturingNature Polishing Expected Count 47.4 15.9 8.7 72 Count 125 42 23 190 Total Expected Count 125 42 23 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 89 who is engaged in the work of polishing only opined about their performance of their field. 54 out of 89 opined that their opinion on modernized Equipments and Machinery is low.

260 The following table indicated the nature of association between Nature of Manufacture and Modernized Equipments and Machinery.

Table- 4.105

Association between Nature of Manufacture and

Modernized Equipments and Machinery

Tests Value df Sig.

Pearson Chi-Square 23.134 6 0.001**

Likelihood Ratio 23.875 6 0.001**

Linear-by-Linear Association 0.919 1 0.338

No of Valid Cases 190

**significant at the 0.01 level

Ho– There is no association between the Nature of Manufacture and Modernized Equipments and Machinery.

The chi-square test divulged that the Pearson chi-square value is equal to 23.134 and likelihood ratio of 23.875 along with linear by linear association of 0.919. All the probabilistic values are significant at 5 percent level. =23.134 d.f. = 6, p< 0.05).Hence, the null hypothesis is rejected.

Therefore, it is stated that

There is an association found between the Nature of Manufacture and Modernized Equipments and Machinery of the Synthetic Gem Industry.

261 (ii) Association between Nature of Manufacture and Government Policy and Support

The Chi-square Test analysis is performed between the clusters of Nature of Manufacture and their varied opinion on Government Policy and Support. Further, chi-square test is applied to test the proximity of the same.

Table – 4.106

Nature of Manufacture and Government Policy and Support

Government Policy and Factors Support Total Low Medium High Count 53 7 29 89 Polishing only Expected Count 49.7 20.1 19.2 89 Count 15 7 0 22 Coning and Faceting Expected Count 12.3 5 4.7 22 Count 7 0 0 7 Cutting and Faceting Expected Count 3.9 1.6 1.5 7

Coning, Faceting and Count 31 29 12 72 ManufacturingNature Polishing Expected Count 40.2 16.3 15.5 72 Count 106 43 41 190 Total Expected Count 106 43 41 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 89 who is engaged in the work of polishing only opined about their performance of their field. 53 out of 89 opined that their opinion on Government Policy and Support is low.

262

The following table indicated the nature of association between Nature of Manufacture and Government Policy and Support.

Table- 4.107

Association between Nature of Manufacture and

Government Policy and Support

Tests Value df Sig.

Pearson Chi-Square 38.321 6 0.000**

Likelihood Ratio 46.150 6 0.000**

Linear-by-Linear Association 0.004 1 0.953

No of Valid Cases 190

**significant at the 0.01 level

Ho – There is no association between the Nature of Manufacture and Government Policy and Support.

The chi-square test divulged that the Pearson chi-square value is equal to 38.321 and likelihood ratio of 46.150 along with linear by linear association of 0.004. All the probabilistic values are significant at 5 percent level =38.321, d.f.= 6, p< 0.05). Hence, the null hypothesis is rejected.

Therefore, it is stated that there is an association found between the Nature of Manufacture and Government Policy and Support of the Synthetic Gem Industry.

263 (iii) Association between Nature of Manufacture and Availability of Labour

The Chi-square Test analysis is performed between the clusters of Nature of Manufacture and their varied opinion on Availability of Labour. Further, chi-square test is applied to test the proximity of the same.

Table – 4.108

Nature of Manufacture and Availability of Labour

Availability of Labour Factors Total Low Medium High Count 64 8 17 89

Polishing only Expected Count 50.6 24.4 14.1 89 Count 7 15 0 22 Coning and Faceting Expected Count 12.5 6 3.5 22 Count 7 0 0 7 Cutting and Faceting Expected Count 4 1.9 1.1 7

Count 30 29 13 72 ManufacturingNature Coning, Faceting and Polishing Expected Count 40.9 19.7 11.4 72 Count 108 52 30 190 Total Expected Count 108 52 30 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 89 who is engaged in the work of polishing only opined about their performance of their field. 64 out of 89 opined that their opinion on Availability of Labour is low.

264 The following table indicated the nature of association between Nature of Manufacture and Availability of Labour.

Table- 4.109

Association between Nature of Manufacture and Availability of Labour

Tests Value df Sig.

Pearson Chi-Square 47.296 6 0.000**

Likelihood Ratio 53.190 6 0.000**

Linear-by-Linear Association 4.296 1 0.038*

N of Valid Cases 190

**significant at the 0.01 level *significant at the 0.05 level

Ho – There is no association between the Nature of Manufacture and Availability of Labour.

The chi-square test divulged that the Pearson chi-square value is equal to 47.296 and likelihood ratio of 53.190 along with linear by linear association of 4.296. All the probabilistic values are significant at 5 percent level. =47.296, d.f.= 6, p< 0.05). Hence, the null hypothesis is rejected.

Therefore, it is stated that there is an association found between the Nature of Manufacture and Availability of Labour of the Synthetic Gem Industry.

265 (iv) Association between Nature of Manufacture and Annual Turnover

The Chi-square Test analysis is performed between the clusters of Nature of Manufacture and their varied opinion on Annual Turnover. Further, chi-square test is applied to test the proximity of the same.

Table – 4.110

Nature of Manufacture and Annual-Turnover

Annual Turnover Factors Total Low Medium High Count 51 24 14 89 Polishing only Expected Count 42.6 24.8 21.5 89 Count 10 7 5 22 Coning and Faceting Expected Count 10.5 6.1 5.3 22 Count 3 0 4 7 Cutting and Faceting Expected Count 3.4 2 1.7 7

Coning, Faceting and Count 27 22 23 72 ManufacturingNature Polishing Expected Count 34.5 20.1 17.4 72 Count 91 53 46 190 Total Expected Count 91 53 46 190

From the above table it was found that the synthetic gem manufacturers with the maximum of 89 who is engaged in the work of polishing only opined about their performance of their field. 51 out of 89 opined that their opinion on Annual Turnover is low.

266 The following table indicated the nature of association between Nature of Manufacture and Annual Turnover.

Table -4.111

Association between Nature of Manufacture and Annual-Turnover

Tests Value df Sig.

Pearson Chi-Square 13.196 6 0.040*

Likelihood Ratio 14.512 6 0.024*

Linear-by-Linear Association 8.263 1 0.004**

N of Valid Cases 190

**significant at the 0.01 level *significant at the 0.05 level

Ho – There is no association between the Nature of Manufacture and Annual Turnover.

The chi-square test divulged that the Pearson chi-square value is equal to 13.196 and likelihood ratio of 14.512 along with linear by linear association of 8.263. All the probabilistic values are significant at 5 percent level =13.196, d.f.= 6, p< 0.05).. Hence, the null hypothesis is rejected.

Therefore, it is stated that there is an association found between the Nature of Manufacture and Annual Turnover of the Synthetic Gem Industry.

267 Over all Test – 5: The Association between the Nature of Manufacture and the Performance Factors of Synthetic Gem Industry.

Hypothesis: There exist an association between the Nature of Manufacture and the Performance Factors of Synthetic Gem Industry

The association between Nature of Manufacture and the Performance Factors was examined through chi-square test.

The below table describes the result of Chi-square analysis and various components of performances, chi-square values, p values and their significance on the nature of the manufacture in Synthetic Gem Industry. The overall performance components are modernized Equipment and Machinery, Government Policy and Support, Availability of Labour and Annual Turnover.

Table – 4.112

Association between Nature of Manufacture and Performance Factors

Pearson Sl. No Performance Factors Chi-square p-value Value

1 Modernized Equipment and Machinery 23.134 0.001**

2 Government Policy and Support 38.321 0.000**

3 Availability of Labour 47.296 0.000**

4 Annual Turnover 13.196 0.040*

**significant at the 0.01 level * Significant at the 0.05 level

268 It is evident that the Nature of manufacture is statistically significant and positively associated with modernized Equipment and Machinery, Government Policy and Support, Availability of Labour and Annual Turnover.. Hence the Nature of the manufacture influences the factors of performances of synthetic gem industry. It is found from the table that the hypothesis is accepted with all components of performance factors.

The table reveals that there is a Significant Association between Nature of Manufacture and the Performance Factors of Synthetic Gem Industry.

269 E. Correlation Test

The term correlation refers to the relationship between the variables. Simple correlation refers to the relationship between two variables. When three or more variables are studied simultaneously, it is called Multiple Correlation. If, the values of two variables changed in the same direction, there is positive correlation between the two variables and if there is a change in the opposite direction then it is said to be negative correlation. Here, in this study there are multiple factors influencing one another in the performance of synthetic industry. The analysis had been undertaken and its correlated values had been extracted as follows:

Correlation – 1

Correlation between the value of Cost of Production and Sales of Synthetic Gem Manufacturers:

Ho: There is no relationship between cost of production and sales value of synthetic gem manufacturers:

Table - 4.113

The Number of Manufacturers lies in the value of Cost of Production and Sales per week which is listed below:

Value per week No. of Manufacturer No. of Manufacturer (Cost of Production and Sales) (Cost of production - X) (Sales Value - Y) Rs. 1 – 5000 56 22 Rs. 5001 – 10000 62 63 Rs.10001 – 15000 41 55 Rs.15000 – 20000 19 29 Rs.20001 and above 23 21 Total 190 190

270 Table – 4.114

Descriptive Statistics

Variables Mean (N=5) Std. Deviation

Cost 40.2 19.176

Sales 38 19.621

Table – 4.115

Correlations

Cost Sales

Cost Pearson Correlation 1 0.524

Sig. (2-tailed) 0.036*

N 5 5

*significant at 5% level

Comment: The Karl Pearson‟s co-efficient of correlation between cost of production and sales of synthetic gem manufacturer is 0.5240, which identifies that there exists a significant positive correlation between these two variables and hence the hypothesis is rejected. Therefore, it is established that there exists a relationship between Cost of production and Sales value of synthetic gem manufacturers.

271 Correlation – 2

Analysis of Karl Pearson’s Co-efficient of Correlation of various Performance Factors of Synthetic Gem Traders of Synthetic Gem industry:

Table – 4.116

Inter Correlation Matrix between Different Performance Factors of

Synthetic Gem Traders of Synthetic Gem Industry

Infrastructural Government Labour Financial Marketing Factors facilities Assistance performance Assistance Performance

Infrastructure facilities 1

Government Assistance 0.036(*) 1

Labour performance 0.005(*) 0.286(**) 1

Financial Assistance 0.041(*) -0.031 0.004 1

Marketing performance 0.067(*) 0.069 0.088 0.117 1

** Correlation is significant at the 0.01 level (2-tailed, p≤0.01); N = 138

*Correlation is significant at the 0.05 level (2 – tailed, p≤0.05)

The correlation matrix presented in Table 4.116, shows that there is relation among the different performance factors of synthetic gem traders such as infra-structural facilities, government assistances, labour performance , financial assistance and marketing performances. All the factors, except government assistance with financial assistance, had positive relations among the performance factors under study.

The performance factor variable of infra-structural facilities had significant positive relationship with government assistances (r=0.036, p<0.05), labour performances (r=0.005, p<0.05), financial assistances (r=0.041, p<0.05), and marketing performances (r=0.067, p<0.05).

272 The performance factor variable of government assistance had significant positive relationship with labour performance (r=0.286, p<0.01), and had negative relationship with financial assistance (r=-0.031, p>0.05), and also had a positive relationship with marketing performance (r=0.069, p>0.05).

The performance factor variable of labour performance had positive relation with financial assistance (r=0.004, p>0.05) and marketing performance (r=0.088, p>0.05) variables.

As such it is found that financial assistance had a positive relation with marketing performance ((r=0.117, p>0.05).

Hence, it is inferred from the above information most of the factors relating to the performance of synthetic gem traders are positively correlated which means almost all the factors are changed in the same direction except the factors of relationship between Government assistance and Financial assistance. These are negatively correlated with one another which mean such factors are changed in the opposite direction.

Correlation - 3

Analysis of Karl Pearson’s Co-efficient of Correlation of various Problems Factors of Synthetic Gem Workers:

273 The correlation matrix presented in Table 4.117, (Page No.273 – A) ) shows that there is relation amongst the different problem factors of synthetic gem workers such as timing of work, wages, work environment, repairs and maintenance services, accessories, provision of facilities, lesser or higher work, work pressures, advances, bonus and holidays.

The problems factor of variable timing of work had significant positive relationships with wages (r = 0.163, p<0.01) and provision of facilities (r = 0.174, p<0.01). Timing of work had significant negative relationships with work environment (r= -0.555, p<0.01), repairs and maintenance (r = -0.294, p<0.01), lesser or higher work (r = -0.317, p<0.01), advances (r = -0.129, p<0.05), and bonus factor (r = -0.484, p<0.01). And also, timing of work had positive relationships with work pressure (r = 0.085, p>0.05) and holidays (r = 0.038, p>0.05) but it had a negative relationship with accessories (r = -0.104, p>0.05).

The problems factor of wages variable had significant positive relationships with accessories (r=0.255, p<0.01), provision of facilities (r=0.561, p<0.01), lesser or higher work (r=0.296, p<0.01), advances (r=0.745, p<0.01), and holidays (r= 0.289, p<0.01) variables. Wages had significant negative relationships with work environment (r=-0.185, p<0.01) and repairs and maintenance (r=-0.187, p<0.01) variables. There is positive relationship between wages and work pressure (r= 0.071, p>0.05) and also with bonus variable (r=0.109, p>0.05).

The problems factor variable of work environment had significant positive relationships with repairs and maintenance (r=0.411, p<0.01), lesser or higher work (r=0.184, p<0.01) and bonus (r=0.208, p<0.01). The work environment variable had significant negative relationships with

274 accessories (r=-0.178, p<0.01) and provision of facilities (r=-0.347, p<0.01). Work environment had positive relationships with work pressure (r=0.090, p>0.05) and holidays (r=0.032, p>0.05) variables. And there is a negative relationships between work environment and advances (r=- 0.059, p>0.05).

The synthetic gem workers‟ problem factor variable of repairs and maintenance had significant positive relationships with accessories (r=0.152, p=0.01), and bonus (r=0.310, p<0.01). There is significant negative relationship between repairs and maintenance and advances (r=- 0.278, p<0.01). The variable repairs and maintenance had positive relationships with provision of facilities (r=0.038, p>0.05), work pressure (r=0.075, p>0.05) and holidays (r=0.039, p>0.05). There is negative relationship between repairs and maintenance and lesser or higher work factor (r=- 0.061, p>0.05).

The variable accessories had significant positive relationships with provision of facilities (r=0.237, p<0.01), lesser or higher work (r=0.360, p<0.01), advances (r=0.118, p<0.05) and bonus (r=0.228, p<0.01) variables. Accessories had significant negative relationships with work pressure (r=- 0.201, p<0.01) and holidays (r=-0.133, p<0.05) variables.

There is a significant positive correlation between provision of facilities and advances (r=0.464, p<0.01). There is a significant negative correlation between provision of facilities and work pressure (r=-0.168, p<0.01). Provision of facilities had positive relationship with lesser or higher work (r=0.077, p>0.05) and bonus (r=0.040, p>0.05) variables. There is negative correlation between provision of facilities and holidays (r=- 0.051, p>0.05).

275 The lesser or higher work variable had significant positive relationship with advances (r=0.387, p<0.01), bonus (r=0.222, p<0.01) and holidays (r=0.253, p<0.01) variables. But, there exists negative relationship between lesser or higher work and work pressure (r=-0.072, p>0.05).

The artisans‟ problem factor variable of work pressure had significant positive relationship with bonus (r=0.348, p<0.01) and holidays (r=0.429 p<0.01) variables. There is significant negative relationship between work pressure and advances (r=-0.144, p<0.05).

The variable advances had significant positive relationship with Bonus (r=0.169, p<0.01) and holidays (r=0.211, p<0.01) variables and at last, there exists a positive relationship between bonus and holidays (r=0.043, p>0.05).

Hence, it is inferred from the above information, that out of the fifty- five factors of relationships relating to the problems of synthetic gem workers, about thirty-eight factors are having either significant positive relationship or significant negative relationship and their significant levels are either 0.01 or 0.05. Only seventeen factors out of fifty-five factors are either positively or negatively correlated with one another.

276