Small scale industries play a major role in economic development processes of developing countries because of poverty and unemployment being the priority hurdles in such poor economies (Gamage,2003). Further, the existence of small industries also increases the local economic activities by using local raw material and local skills for its operation. Silk industry also deserve such status in India, which can be understood from its second position in production of the raw silk after China and the biggest consumer of raw silk and silk fabrics and has the unique distinction of producing all the four varieties of silk viz., Mulberry, Tasar, Eri and Muga (Giridharet al., 2010) India ranks second and its share was 15.75 per cent. Sericulture industry in India is entrenched in Karnataka, Andhra Pradesh, Maharastra, Orissa, Madhya Pradesh, Manipur, Uttarakhand, Tamil Nadu, West Bengal, Jammu and Kashmir and Bihar. Among these, Karnataka tops in the list followed by Andhra Pradesh, Tamil Nadu, West Bengal and Jammu and Kashmir in production. Estimated total area under mulberry in India during 2010-11 was about 188,000 hectares and the production was 16,957 metric tonnes. Compared to the production of 16,322 metric tonnes in 2009-10, it has increased by 3.89 per cent during 2010-11.

Kashmir in view of its favourable climatic conditions could be converted into Silkworm gene bank for sustaining the sericulture of the whole world. Jammu and Kashmir is the only state of the country which is in the same altitude in which leading bivoltine Sericulture countries of the world lie. Even the Sericulture experts of Japan have recognized the superiority of natural climatic conditions in the state favourable for the development of Sericulture and for the production high grade raw silk of international quality. Women play a dominant role in this sector, as the activities are mostly home-based. Women have been contributing to all the sectors of Sericulture starting from on-farm activities to fabric production, marketing and consumption. The involvement of women in different activities of Sericulture is well above 53 per cent (Gangopadhyay, 2008).  Sericulture has played an eminent role in the economy of Jammu & Kashmir (J&K). Sericulture as a sector has been the backbone of Kashmir economy.  J&K is the only state which produces the best quality Bivoltine silk.

Geographically, Asia is the main producer of silk in the world and manufactures over 95 % of the total global output. Although there are over 40 countries on the world map of silk, bulk of it is produced in China and India, followed by Japan, Brazil and Korea. China is the leading supplier of silk to the world with an annual production of 104000 MT (2008), out of which the Mulberry raw silk production is 70980 MT (Nagaraju, 2008). Many researchers have put their efforts to find critical factors for the continuity and long sustenance of the industry. Asare, (2012) studied the critical success factors for the revival of the textile sector and elements critical for sustainability and competitiveness in the industry in Ghana Textile. The findings showed that there are critical elements that are vital for increasing the competitiveness of this sector. Price, quality, location, fast lead times, creativity, innovation, technology upgrading, delivery reliability, conformance to standards and packaging were all considered as critical elements. It was concluded that management, government support, marketing and collaboration with local dressmakers/fashion designers are four main critical success factors significant. The sustainable development of sericulture industry and the various difficulties and problems faced by Sericulture Industry is critical for its survival. Islam et al. (2010) studied the existing problem and future expectations of silk industry in Bangladesh. Direct interview methods with the help of structured questionnaire were collected from the silk mills. Some of the problems were old technology, poor advertising, limited showroom, shortage of raw materials, inadequate capital, insufficient governmental facilities etc. were studied. They also find out some prospects of this industry like growth of sales and market share, low cost of labour, increasing demand, good geographical location, employment opportunity etc. The authors suggested that it is essential to make effective plan and proper execution of that plan to get back the glorious position of silk industry as well as to help the economic development of country. Kramer et al. (2009) has worked on the assessment of the potential of silk production as a sustainable livelihood activity for rural households in Cambodia. The findings were that silk production can bring a significant additional income to the rural households while at the same time providing producers with skills and knowledge unique to the traditional silk production in the area. It was found that that the biggest constraint of the silk producers is the difficulties of marketing their products, indicating current unsustainable economic conditions. It was suggested that stronger cooperation among producers could improve the ability to meet market demands.

The Silk industry has a distinctive position in India, and plays a significant role in Textile Industry and Export. India is the 2nd largest producer of silk in the world with 19690 MT (2008-09) and also the largest consumer of silk in the world and contributes 15% of the total world raw silk production (Dun and Bradstreet, 2009). Anitha, (2011) studied the performance of Indian silk industry in the global scenario, and analysed the strengths and problems of Indian silk industry. It was suggested imparting knowledge among the farmers regarding farm disease and rationalization of marketing and stabilization of prices of silk cocoons and raw silk, can cause a rapid growth in the industry . According to this study, the various problems facing the Indian Silk Industry are use of poor quality seeds, low production of bivoltine seeds, use of non-graded and diseased seeds, poor knowledge of farm disease amongst farmers, poor supply chain management, huge unorganized and decentralized sector, high production cost, recurring droughts and increased import of silk from China. Prabha and Sinha, (1992) have made an exploratory study on ‘Raw silk Market in India’ and analysed the qualitative and quantitative demand for silk yarn from the main silk weaving centres of India. The study analysed in detail the area wise reputation for different yarns from traditional regions of Karnataka i.e., Sidlaghatta filature raw silk and Kollegal charka raw silk. The significant finding of this study wasthat within a changing market, characterised by increasing role of power looms and emerging consumer demand for non-traditional plain and coarse fabrics, there has been a decline in the demand for charka silk. The share of charka silk in domestic production has fallen from 55 percent in mid-80's to around 37.5 percent during 1990- 91.

In their examination of the Ludhiana woollen knitwear industry during the COVID-19 outbreak, Mehta and Kaur (2021) identified challenges amounting to 2,000 crore INR. The industry faced skepticism from entrepreneurs and workers regarding new changes, coupled with infrastructural bottlenecks, international and connectivity issues, and an outdated internal system. Akintayo (2020) emphasized strategies for the revival of Nigerian Textile Industries, proposing government intervention in the form of funds, infrastructure development, and improved power supply. Gupta and Bhateja (2020) highlighted revival strategies for the promotion and advancement of MSMEs involved in silk industry, that effective utilization of robotics and artificial intelligence, technical and virtual intellectual knowledge enhancement, can reduce the crisis in market considerations.

Data collection

Survey method was adopted for collection of data and the survey instrument was distributed among the rearers of the districts of Anantnag and Pulwama of Kashmir. As the survey used the rearers in almost a captive environment, it resulted into the highest possible rate of response (100%). The high response rates are due to personal contact and follow up approach used by personal visits. In addition, the secondary data has been obtained from the Journals, Books and Directorate of Sericulture Development Department.

Questionnaire development

A questionnaire (schedule) was developed for the rearers. As the population was the illiterate group, so the schedule was used to collect the data. The items with respect to various dimensions were arranged in an order.  The questionnaire administered was reasonably kept short to attain good response. This was done deliberately because respondents generally did not have enough time during their daily schedule to answer more questions. The questionnaire consists of 25 variables pertaining to the various problems and issues of the rearers.

Since the need was felt to quantify the data, which otherwise were qualitative in nature, therefore, Rensis Lickert’s popularly known as Lickert’s type technique was applied throughout this study. The respondents were asked to respond to each item on a particular issue under study in terms of several degrees of agreements, disagreements, viz., strongly agree; agree; neither agree nor disagree; disagree; and strongly disagree. Responses to >items were scored in such a way that a response indicative of most favourable was given the highest score and vice-versa (strongly disagree = 1, strongly agree = 5).

Data reliability and validation

The data collected in this study was subjected to reliability and validation tests before drawing any conclusion. Since multivariate statistical technique, factor analysis (FA) was used for the analysis of data, therefore the reliability and validation tests were Cronbach’s Alpha Test of reliability and Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy which evaluate the appropriateness of the data for FA. The Cronbach’s Alpha coefficient of the data was 0.750. A high value of this statistic (from 0.5 to 1) indicates the appropriateness of the factor analysis for the data, whereas a low value of statistic (below 0.5) indicates the inappropriateness to the factor analysis (Bajpai and Bajpai, 2014). KMO value of the data was 0.628 indicating the appropriateness of the factor analysis for the data. 

Inferences from questionnaire data

The responses of the rearers collected through questionnaires was analysed by descriptive analysis and factor analysis to identify the priority glinches with the growth of silk industry. The mean score of responses to each question was calculated for each residential area as well as from whole data. It was observed that each place was having different problem. For example, in Pulwama region, the fluctuation in cocoon prices was a major issue revealed by its highest mean score of 4.32 while as for Tral, lack of education among rearers was a major issue (mean score of 4.49) (Table 1). Similarly, for Kakapora town, the mean score was maximum for the ffluctuation in cocoon prices which may be due the geographic location. These two areas are located nearby and it may be that the market factors like customer interests are common.  For other towns, Pampore, Kuthar, Khoverpore, Dachinpora and Kokernag a common trend was observed. The mean score of three problems 1) fluctuation in cocoon prices 2) proper disinfectants and rearing appliances easily availed and 3) lack of education among the rearers was more than 4 in all chosen places. This shows that these three problems are of more concern in each town and solutions to the respective problems may help in the revival of silk industry in Kashmir valley. The scope of the study was whole Kashmir region so an attempt was made to derive the major issues based on the whole collected data. Based on the total data of all eight towns also, the mean score was highest for the same three problems viz problems 1) fluctuation in cocoon prices 2) proper disinfectants and rearing appliances easily availed and 3) lack of education among the rearers. Their mean score calculated from whole data was 4.41, 4.14 and 4.45 respectively. In addition, the marketing problem “Prior information about the auction markets” has also got mean score of 4.01 which mean that as a whole there is a problem of advertising among the rearers. This may be a consequence of the lack of education as well which limit the exposure of rearers to modern marketing tools and thereby the information about auctioning of their products. Overall it is revealed from the analysis that the silk industry in Kashmir valley is facing problems mainly in raw material costs which lower their business interest, availability of good rearing techniques which reduce their production, good education which can increase marketing opportunities for the rearers.

Indicative measures were also suggested in order to address these problems and help in revival of the silk industry. For the fluctuations in costs of cocoon, the government can play an important role by regulating the prices and preventing the stake holders to control the market. Subsidies can help the rearers to maintain or increase the production even during events of financial dip. Regarding the absence of modern rearing appliances and use of effective disinfectants, the local government can help rearers to avail them. Low cost equipment can be purchased by rearers by themselves but sophisticated tools can be made available to rearers on rent basis. The same can be provided either by the local government authority or private stakeholders approved by them. For the lack of education among rearers, the same can be contributed by the local government and non-government organizations. Seminars, public lectures, training programs can help the rearers to acquire a competitive information about production and marketing of silk products. Eventually, it may solve the problem of lack of information about auctioning.

Inferences from factor analysis of the data

The output from the factor analysis include screen plot which is used to determine the optimum number of factors to be retained in the final solution. The objective of the scree plot is to visually isolate an elbow, which can be defined as the point where the eigen values form a linear descending trend (Bentler & Yuan, 1998).

In this study, eight factors were obtained explaining 78 % of total variance in the dataset. Total variance in the data set is explained by these factors as shown in Table 2. The first factor of questionnaire dataset explained highest percentage of variance which was 25%. The second factor explained 11% and remaining factors explained less than 10% of total variance each. Unrotated factor matrix maximizes the variance to be accounted by first and subsequent factors and hence the data compression causes most variables to get substantially loaded on more than one factor. Rotation of the axis in factor analysis provides a more understandable output in which the overlap of loadings between factors is considerably reduced. The factors obtained in this study were rotated by varimax rotation, an orthogonal rotation in which the actual coordinate system is not changed but the whole orthagonality is re aligned to make it easy to treat each variable as separate factors. Thus, factor analysis of the present dataset was further condensed by removing the influence of less significant variables obtained from unrotated factor matirx. The obtained rotated factor matrix with factor loadings of each problem of silk worm rearers is shown in Table 3. The obtained factor loadings were categorized according to Liu et al. (2003) which consider absolute loading values of >0.75, 0.75–0.50 and 0.50–0.30 as  strong, moderate, and weak respectively.

Following this, factor 1 has strong positive loadings on the marketing and supply related questions of questionnaire such as easy access to quality mulberry leaves=0.830, prior information about the auction markets=0.837, fluctuations in the cocoon prices=0.566. This suggested that these may be problems of highest concern because the factor 1 explained maximum variation (24%) of whole dataset. The factor 2 has strong positive loadings on the accessibility questions of the questionnaire such as cocoon markets organized well in time=0.760, easy access to the cocoon markets=0.774, technical advancements well incorporated=0.742). The strong positive loadings of these questions to factor 2 can suggest that after marketing problems, there is lack of appropriate accessibility to the rearers which has influenced the growth of the silk industry in Kashmir valley. Similarly, the higher loading for factor 3 which explained 10% of total variance on demographic related questions such as favorable climatic conditions=-0.838, training institutes are nearby from home=0.788, sericulture income sufficient for livelihood=-0.785. The essence of these questions was that the rearers lack such facility of nearby training centres which make them less competitive and inefficient in their skills. The factor 4 explained 9% of total variance and has higher loading of this factor were on the questions related to societal problems such as lack of education among rearers = 0.924, positive attitude of society= 0.645, migration of workers to other jobs= -0.843.Quality problem related questions such as quality awareness programs satisfactorily=0.681, quality check easily available=0.499 have higher loading on factor 5. The variance explained by this factor 5 was 8%. The remaining three principal factors (6, 7 and 8) explained the variance of 6%, 5%, 4%. Though the factors have eigen value greater than 1 but they have the low contribution in explaining the data variance for which there loadings would have limitations.

From factor analysis, the analysis results therefore showed that most of the problem in the silk industry are associated with marketing, accessibility and supply because these issues were more correlated with maximum variance explaining factors i.e. factor 1 and 2. This may suggest that the opportunities available for the revival of the industry can be provided through best marketing facilities to the rearers and easy supply of various requirements including raw material and rearing appliances. The requirements can be also managed through subsidies on various products that are required in silk production. The problem of absence of good rearing techniques was also shown by descriptive analysis of the data as explained in previous section.

Table 3 Factor loading of various variables on extracted principle factors.Table 3 Factor loading of various variables on extracted principle factors.

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