A VALUE CHAIN ANALYSIS OF THE LEATHER INDUSTRY

PROF. DR. ZAHOOR UL HAQDepartment of Economics

Faculty of Business and EconomicsAbdul Wali Khan University Mardan

Khyber Pakhtunkhwa, Pakistan(zahoor.haq@awkum.edu.pk)

JULY 2015

Post-Doctoral Report prepared for the Gatton College of Business and Economics, University of Kentucky, Lexington KY 40506

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FIRST DRAFT

TABLE OF CONTENTS

1. INTRODUCTION..................................................................................................................1

2. REVIEW OF LITERATURE...............................................................................................3

2.1 VALUE CHAIN ANALYSIS.................................................................................................3

2.1.1 Input-output analysis....................................................................................................4

2.1.2 Geographical and network approaches.......................................................................5

2.1.3 Governance structure approach...................................................................................7

2.1.4 Institutional and transaction cost contexts..................................................................8

2.1.5 Performance measure context.....................................................................................9

2.2 INTERNATIONALIZATION OF FIRMS..............................................................................10

2.2.1 Trade barriers, firms export cost and profitability....................................................11

2.2.2 Firm productivity, quality, research & development and innovation.......................12

2.2.3 International business management..........................................................................13

2.4 Conclusion..................................................................................................................15

3. METHOD..............................................................................................................................17

3.1 SAMPLING FRAME AND SAMPLING...............................................................................17

3.2 ECONOMETRIC ANALYSIS..............................................................................................18

3.3 DESCRIPTION OF VARIABLES........................................................................................20

3.3.1 Dependent and independent variables.......................................................................21

4. RESULTS AND DISCUSSION...........................................................................................21

4.1 DESCRIPTIVE STATISTICS..............................................................................................21

4.2 LEATHER VALUE CHAIN...............................................................................................24

4.3 FIRMS’ PARTICIPATION IN INTERNATIONAL MARKET.................................................32

5. CONCLUSIONS....................................................................................................................38

REFERENCES............................................................................................................................39

ANNEXURE –1: DEFINITIONS OF PERFORMANCE MEASURE INDICATORS........43

ANNEXURE –2: QUESTIONNAIRE.......................................................................................47

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LIST OF TABLES

Table 1.1: Major exports of Pakistan during the last decade...........................................................1

Table 2.1: Dynamics in global value chain governance 5

Table 2.2: Firm specific main and its respective sub-set of factors 16

Table 3.1: Conversion of confidence interval to normal deviate 17

Table 3.2: Sample size for assumed values of K and D

Table 3.3: Description of variables ……………………….. 20

Table 4.1: Descriptive statistics of the firms ……………………….. 24

Table 4.2: Proportion of cost in the selected value chains …………………………………….. 32

Table 4.3: Cost of processing of leather and goods production in the selected value chains …. 33

Table 4.4: Cost and margins of leather processing and good production of the selected value

chains

………………………………………………………………………………. 34

Table 4.5: Probit estimates and marginal effects of factor affecting firms participation in export

market

……………………………………………………………………………… 38

Table 4.6: Heckman two-step estimates of the selection and outcome equations and marginal

effects ……………………………………………………………………………… 40

Table 4.7: Heckman maximum likelihood estimates of the selection and outcome equations and

marginal effects ...

………………………………………………………………… 41

LIST OF FIGURES

Figure 2.1 Value Chain Governance Types.....................................................................................6

Figure 4.1: Value Chain of Leather from Raw Skin to Wet Blue …………………….…………31

Figure 4.2: Value Chain of Leather from Wet Blue to Fine Leather……………………………31

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1. Introduction

In 2012, the value of the country’s exports was $ 24.6 billion (Table 1.1). Cotton and textile

manufactures (52.5%), agrifood products (18.6%) and leather and leather products (5.0%)

collectively accounted for 76.1 percent of these exports (Table 1.1). Between 2003 and 2012,

cotton and textile exports grew by 55.4%, agrifood exports grew by 253.8%, and leather and

leather exports grew by 50% (Table 1.1). However, the individual contribution of the cotton and

textile sector to country exports has been declining, while the massive growth of agrifood

exports continues increasing its share. Due to their major contributions to exports, cotton and

textile manufactures (Hussan, 2011; Khalil, 2011) and agrifood products (Haq, 2011; Haq et al.

2011) are intensively researched, but the leather industry has been rarely studied. This is one of

the reasons for focusing on the $ 1.23 billion Pakistani leather industry in this study.

Pakistan exports 55 percent of its leather and leather products to three countries ― Hong

Kong, China and Italy (GoP, 2012). Those countries are also the world’s top three importers of

these products, and Hong Kong and Italy are also among the top three exporting countries.

Hence, Pakistan has been exporting quality leather products to the world’s top importers as well

as exporters. However, local firms export to these locations of transnational firms (e.g., Hong

Kong) from where the same product goes through the highest value-addition activities and then

exported to another country. This process leads to the creation of global value chains through

increased integration and coordination among the firms involved in output production. Feenstra

(1998) refers to it as the ‘integration’ of trade with ‘disintegration’ of production. Therefore, it is

important to understand that how inter-firms activities are coordinated and contracted. Given the

increase in leather exports, it is expected that both formal and informal contracts may exist

between the exporting and transnational firm, for which the product is produced. However, a

number of unanswered questions need understanding. For example, are Pakistani leather exports

characterized by brand? What factors determine firms’ participation in leather export markets?

How does inter-firm transaction takes place? What factors drive the contracts among local and

transnational firms? Are sections of the value chain that yield high returns or rents retained

within the corporation? Answering these questions is important for making the leather products

and industry more competitive and improving their ability to compete in the global economy.

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Table 1.1: Major exports of Pakistan during the last decadeYear 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Sector Billion US$All Exports 11.9 13.4 16.1 16.9 17.8 20.3 17.6 21.4 25.3 24.6Cotton & textile products 8.3 8.9 10.3 10.9 10.7 10.6 9.6 11.6 13.6 12.9Agrifood 1.3 1.4 2.0 2.0 2.2 3.7 2.9 3.6 5.0 4.6Leather & products 0.8 0.9 1.2 1.1 1.2 1.3 1.0 1.1 1.3 1.2

Total 10.4 11.2 13.4 14.0 14.1 15.6 13.5 16.3 19.8 18.7Percent Share

Cotton & textile products 69.6 66.7 63.9 64.2 60.2 52.4 54.9 54.2 53.6 52.5Agrifood 11.1 10.1 12.2 12.0 12.1 18.2 16.7 16.7 19.7 18.6Leather & products 6.6 6.6 7.2 6.7 6.7 6.3 5.5 5.3 5.0 5.0

Source: Author calculation using ITC trade data, 2003–2012

The leather supply chain typically consists of four stages. The first stage consists of the recovery

of hides and skins from slaughterhouses and butchers. In the second stage, hides and skins are

converted into leather using tanneries. This transformation involves complex chemical

processing. Labor-intensive leather products are produced in the third stage, and marketing, both

domestic and export, is carried out in the fourth stage. Understanding these intra-firm activities

of the leather value chain will help in identifying the type of technologies used in the tannery

industry and their implications for environment and human health in the country. The intra-firm

perspective of the VCA will also help us understand the cost structure of the leather industry and

its contribution to the scale economies at brand or retail levels. Further, the question of the role

that environmental standards play in firms adopting polluting technologies that might make them

more marketplace competitive is investigated here. Such investigation can also help answer the

question of whether the adoption of a particular technology is motivated by the multinational

corporation or brand.

Given the importance and contributions of the leather industry and the challenges it faces,

it is important to study the industry using a holistic approach encompassing both the inter- and

intra-firm perspectives. Hence, the goal of the study is to study the Pakistani exports of leather

products using a global value chain approach starting from the production to its products export.

The specific objectives of the study are to:

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i. Study the value chain of leather production and processing; and

ii. Estimate the effects of different factors on firms’ participation in the leather export

market.

The study will contribute in a number of ways. The conceptual framework to be

developed and employed in the study will contribute to the theory of the value chains analysis.

The study will also investigate the role of different factors determining the costs and margins of

the industry. Such an analysis will help improve the efficiency of intra-firm supply chains and

hence the competitiveness of the leather industry. Another aspect of the analysis covers the

factors determining firms’ participation in export markets having implications for other firms not

only in Pakistan but also in other developing countries. Investigating the efficiency of various

technologies used in leather tanning with respect to environmental externalities will lead to the

development of effective environmental regulations and sustainability in the long run.

The next section presents many analytical and theoretical approaches used to study VCs.

Section three presents the methods employed in investigating the leather value chains of

Pakistan. This section also presents a discussion about the data required for the study.

2. Review of Literature

This part is divided into four sections. The first section focuses on the study of value chains and

is further divided into four sections: input-output analysis (section 2.1.1), geographical and

network approaches (section 2.1.2), a governance structure approach (section 2.1.3), institutional

and transaction cost contexts (section 2.1.4) and performance measure context (2.1.5). Section

2.2 reviews the literature on factors affecting firms’ participation in exports markets and how

much they export i.e. internationalization of firms. This section is divided into three sections.

Section 2.2.1 presents review of literature on trade barriers, firms export cost and profitability,

section 2.2.2 on firms’ productivity, quality, research development and innovation, and section

2.2.3 on international business management.

2.1 Value Chain Analysis

Value Chains are distinguished between producer-driven and buyer-driven (Gereffi, 1994).

Producer-driven chains are large multinational manufacturers, more vertically integrated, having

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backward and forward linkages with other firms in the chain (Gereffi, 1994). These chains

characterize technology-driven products such as automobiles, computers, and semiconductors.

On the other hand, the buyer-driven chains consist of large retailers and distributors such as Wal-

Mart and Tesco and brand producers such as Nike and Reebok. These large retailers, distributors

and brand producers determine the product standards and require suppliers to meet these

standards (Gereffi, 1994). Gereffi (1999) pointed out that footwear is labor intensive and a

relatively low-tech industry making it buyer-driven. In buyer-driven chains, profits are driven by

brand, the outcome of unique combinations of research, design, sales, marketing and financial

services (Gereffi, 1999). Brand also plays a key role in accessing the lucrative international

markets leading to increase in exports. Gereffi and Stark (2010) presented four dimensions for

investigating VCs. These include: (1) an input-output structure; (2) a geographical consideration;

(3) a governance structure; and (4) an institutional context. These are discussed in detail in the

following sections.

2.1.1 Input-output analysis

An input-output structure describes the technologies and processes involved in the

transformation of raw materials into final products. The input-output view of the VC investigates

the process of bringing a product or service from initial conception to the consumer’s hands and

thereafter. Hence, it includes all the activities from production to marketing through consumption

and recycling. The value chain is represented by boxes connected by arrows showing the flow of

tangible and intangible goods and services at different stages of production. This approach is

useful in studying the value chain of leather and leather products. Rameshraja and Suresh (2011)

used it to understand the water and environmental pollution generated by leather industry during

the tannery process. Better measurement provides reliable information to policy-makers. Input-

Out (IO) technique is important in understanding the various stages involved in leather

processing. They report that IO is one of three methods used to study VCs. One of the other

methods is survey data collected from firm about product specific processes. For example, Xing

and Detert (2010) found that China contribute only 3.6% of $2.0 billion of export of iPhone to

the US. The rest is contributed by Germany, Japan, Korea, the US and other countries. Such

analysis also provides useful insights about VCs as part of multinational enterprises working in

different countries. The second approach relies on trade statistics-based measurements. Trade

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statistics can also provides insights on trade flows and patterns of products among countries,

indicting countries of origin and destination. The third approach consists of IO model using IO

tables to study inter-industry relationships. An international IO table presents detailed data about

both inter-country (trade data) and inter-industry (IO) linkages. Hence, analysis of VCs can be

carried-out using these international IO databases. The concept of IO is more popularly used in

the study of value addition and primarily contributes to the identification of important factors

shaping the business strategy of a firm.

2.1.2 Geographical and network approaches

The geographical consideration includes the study of industrial clusters, their locations within or

outside of national boundaries, and the activities carried out in these geographically dispersed

firms. The South (developing countries) offers raw materials and low-cost skilled labor while the

North (developed countries) carries out product innovation. Most of the leather processing firms

in Pakistan are located in Punjab and Sind provinces. The approach helps in understating why an

industry is developed in a particular area. Companies have horizontal, vertical and business

support relationships with other companies in support of input and services, and that these can all

be studied using a network approach. The theory considers trust, reputation and power in

addition to economic factors as the basis for relationships. Van Dijk & Trienekens (2012) also

finds social capital theory, a branch within network theory, important for firms to get easier

access to information, technologies and financial support.

Geographic and network approach perspectives present a number of rationales for

organizing production activities on a regional basis. The approach investigates the allocation of

activities, processes and operations in the value-chain across different locations. These

perspectives include the benefits arising from inter-firm transactions organized within a network

(Bchir & Fouquin, 2006), efficient exchange and spillovers of business knowledge due to close

proximity (Fan & Scott, 2003), information sharing on resources and inputs and economies of

scales (Chen, 1999). However, the increasing complexity in VCs has made it difficult to identify

who produces what kind of value for whom by what kind of activity in the chain.

Individual districts and clusters are also analyzed using geographic and network

approach. Dunford (2006) defined industrial districts as dense concentrations of interdependent

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small- and medium- sized enterprises (SMEs) in a single sector and in auxiliary industries and

services. Becattini (1979) reported that districts are “communities of firms and people”, hence

the unit of analysis in such a case is district. Dunford (2006) noticed that industrial industries are

more common in textiles, clothing, knitwear, and shoes sectors where fashion and seasonal

factors are a stimulus for change in products. Hence, “development cycles are short, prototyping

is rapid, batches of products are small, the variety of products is great, and costs are spread

across a wide range of goods”. These sectors have higher rates of return on investment and on

equity due to higher productivity (value added per worker) and lower capital and wage costs. The

research also focused on related issues of external economies, vertical disintegration, productive

decentralization, and ownership concentration, the emergence of groups of companies, joint

venture, subcontracting, the role of foreign direct investment and many other aspects related to

social and political aspects of production in a district. Dunford (2006) further asserts that the

context of analysis also includes strategies for increasing corporate profit, which primarily

include cost reduction strategies, development of new or improved products, entry into new

markets, changes in the importance of functional roles of participants within a value chain, and

disinvestment and movement into another value chain. Humphrey and Schmitz (2002) point to

the fact that the analysis of industrial clusters focuses on the role of local linkages while

investigation of global value chain emphasizes international linkages between firms. How these

two streams of research could be reconciled and bring together. One of the ways is to insert the

local firm in the global value chain and then investigate the effect of insertion on up-gradation of

the local industry. This is very relevant in the case of footwear and garment industries.

Humphrey and Schmitz (2002) further indicate that there are two major types of chain

coordination between firms. First, a continuum of arm’s-length market relationships through a

hierarchical governance (vertical integration). Second, network associating firms with similar

competencies and quasi hierarchy in which one or the other firm has asymmetric competence and

powers in coordination. This leads to the governance structure approach, which further

elaborates the relationships and coordination among firms in a global value chain setup. The

approach is discussed in detail in the next section.

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2.1.3 Governance structure approach

The governance structure viewpoint of the value chain explains the organizational structure,

control and coordination among the actors. Gereffi and Stark (2010), Gereffi et al. (2009) and

Gereffi et al. (2005) used three variables: 1) complexity of information and knowledge transfer;

2) extent to which the information can be codified; and 3) the capabilities of the suppliers in

relation to the requirement of the transaction to present five governance structures in VC. These

governance structures include markets, modular, relational, captive, and hierarchy (Figure 2.1

and table 2.1). In market governance, it is easy for the supplier to make the product because

information is easily transmitted between the buyer and supplier, and the latter has the internal

capability to make the product. In modular governance, suppliers in chains make products to a

customer’s specifications using generic machinery and take responsibility for process

technology. Linkages among the chain actors are more complex than the market governance

because of the high volume of information flowing across the firms. However, because of

codification, complex information is exchanged between firms with little coordination, and the

cost of switching to a new partner is low. Relational governance occurs when buyers and sellers

use complex information that is not easily shared, resulting in frequent interactions and

knowledge sharing between parties, while producing differentiated products. Captive chain

mechanisms occur when the ability to codify increases, because the cost of partner switching is

high and small suppliers are dependent on lead buyers. Lead firms perform a high degree of

monitoring and control. Lead firms seek to lock in suppliers to exclude others from the benefits

of their innovation. Captive suppliers perform very narrow specialized tasks. Hierarchical

governance is based on vertical integration and control by the lead firms; it is used when

products are characterized by specifications which cannot be codified or competent suppliers

cannot be found.

Hence, increase/decrease in complexity of transactions makes harder/easier to codify

transactions leading to effective decrease/increase in supplier competence (Table 2.1, �/�);

better codification of transactions is possible in open standards, computerization (Table 2.1, �)

de-codification of transactions is carried in new products/process development(Table 2.1, �);

increase/decrease supplier competence is due to decreased/increased complexity, better

codification and learning/new technologies and new entrants in market(Table 2.1, �/�).

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Table 2.1: Dynamics in value chain governance

Governance Type

Complexity of transactions

Ability to codify transactions

Capabilities in the supply-base

Market Low High High

Modular � High � High � High

Relational High � Low � High �

Captive High High Low

Hierarchy High Low Low

Source: Gereffi and Stark (2005)

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Materials

Customers

Suppliers

Price

End Use

Market Modular

LeadFirm

Component and

Material Suppliers

Turn-key

Supplier

Relational

Captive Suppliers

Captive

LeadFirm

Component and

Material Suppliers

Val

ue

Cha

in

Hierarchy

Integrated

Firm

Low HighDegree of Explicit Coordination

Degree of Power Asymmetry

LeadFirm

Relational

Supplier

Full-packageSupplier

Figure 2.1 Value Chain Governance Types Source: Gereffi and Stark (2005)

2.1.4 Institutional and transaction cost contexts

Van Dijk & Trienekens (2012) presented different theoretical approaches to study value chain.

He extended the list of theoretical approaches of Gereffi and Stark (2010) by adding new

institutional economics (NIE). In his view, NIE uses the transaction cost and agency theories to

investigate VCs. In transaction cost theory, transaction between firms is the basic unit of

analysis. The scope of the analysis primarily focuses on the minimization of transaction costs.

Transaction cost economics explains the formation of organizations in terms of transactional

efficiency with respect to the cost of gathering and processing the information needed to carry a

transaction, reaching to decisions within an organization, negotiating contract with other firms

and policing and enforcing contracts (Williamson, 1981). Organizational transaction is the unit

of analysis of the theory. The approach has been applied at three levels to the study of

organizations. The first is the overall structure of the enterprise, i.e., how one operating parts

should be related to another. Second, which production and processing activities should be

carried out within the firm and which ones outside the firm. Getting efficiency is the goal of this

analysis. Third, is on how organizations organize their human assets. The first and second are the

scope of this analysis.

Asset specificity, uncertainty about future economic outcomes (of prices, quality,

demand, technology, etc.), the frequency of transactions and the number of buyers and sellers are

the different dimensions of transaction costs. The cost of asset redeployment determines the cost

of asset specificity. Asset specificity could be location specific i.e., when assets are located close

to minimize costs; physical asset specificity i.e., the asset has little value on its own but has value

only for the use; and human asset specificity implying the importance of human skills in

transactions. Given, leather exports by Pakistani firms to Hong Kong, Italy and China and their

further distribution to the rest of the world, it is imperative that inter-firm contracts will facilitate

these marketing transactions. Making exports involves search costs of finding a partner and

hence, transaction costs theory could be one of the important tools to understand Pakistani

leather exports.

2.1.5 Performance measure context

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Performance measure is another approach to study VCs. Lusine et. al. (2007) presented the

various performance measures to assess the success of supply chains. The authors used four

criterion including efficiency, flexibility, responsiveness and food quality to assess value chain

performance (Annexure-1). Efficiency points to the utilization of resources in the supply chain

and its measures include production costs, profit, return on investment and inventory. Flexibility

indicates the degree of responsiveness of the supply chain to a changing environment and

measured through customer satisfaction, volume flexibility, delivery flexibility, and lost sales.

Responsiveness shows the time spent in the fulfillment of a request and measured through fill

rate, product lateness, customer response time, lead-time, shipping errors, and customer

complaints. Food quality, the fourth and final criteria of performance measure is further divided

into product and process quality. Product quality consists of product safety and health, sensory

properties, shelf-life, and product reliability and convenience (Annexure-1). Trienkens (2012)

and Sanogo (2010) presented a supply chain view for the study of value chains. They

recommended systematically mapping the actors taking part in the production, distribution,

marketing, and sales of a product. The map characterizes the actors, profit, cost structures, flows

of goods throughout the chain, employment characteristics, and the destination and volumes of

domestic and foreign sales. They emphasize the identification and estimation of the share of

costs and benefits of each actor in the chain and determination for the quality enhancement

within the chain.

The input-output approach can be used to study the intra-firm aspects of the value chain of

leather industry in Pakistan. It helps in understanding the process carried-out in various stages of

the VC, which is appropriate in the case of leather industry. Hence, it can help in the

identification of the type of technologies used in processing of leather and manufacturing of

leather products.

2.2 Internationalization of Firms

Globalization has lead to the integration of trade but disintegration of production. The increase in

the industrial capabilities of developing countries and disintegration of transnational cooperation

are some of the reasons of production disintegration (Gereffi et al., 2005). Local firms export to

the industrial locations of transnational firms from where the same product goes through the

highest value-addition activities and then exported to another destination. This process has

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changed the competitive dynamics of nations, industries and firms. Firms in developing countries

perform a particular function of the VC and then hand the product over to another firm for

another function of the same VC. Hence, it is important to know what factors determine,

developing and developed countries firms to internationalize. Internationalization refers to a

firm’s decision to export or extend its sales to new markets abroad (Welch and Luostarinen,

1988). The following review presents various explanations to this and the following questions:

o What factors determine what and where to export if a firm has the ability to export?

o Once a firm overcomes the fixed cost of export then is it more likely to export the same

product to other destinations?

o Does experience of exporting play any role?

o Does an existing trade relationship influence the probability of new products export?

o Does a firm entering a new global market create spillover effect for other firms?

Finding answers to these questions will help us understand the internationalization of leather

firms in the country.

2.2.1 Trade barriers, firms export cost and profitability

Helpman et al., (2008) use the profitability of a firm to explain their participation in export

market. They report that firms have different levels of productivity and only the more productive

firms find it profitable to export. The profitability of exporting firms varies by destination and it

is higher when firms export to countries with larger markets, having lower fixed and variable

export costs. Hence, for every importing country i, there is a marginal exporter in country j that

just breaks even by exporting to country i. Firms in country j with higher productivity than the

marginal exporter receive positive profits from exporting to country i. The study also

decomposes the impact of trade friction on trade flows into the intensive and extensive margins.

The intensive margin is the volume of trade per exporter while the extensive margin refers to the

number of exporters. Chaney (2008) found that variable trade costs, market size, and remoteness

affect both extensive and intensive margins of trade. While, fixed costs, once paid, do not

influence an exporter’s revenue.

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Ottaviano and Martincus (2011) categorized studies investigating factors affecting firms’

participation in export market into two groups: sunk export costs and forces affecting the

profitability of exporting net of sunk costs, including firms’ individual characteristics, actions,

and environment. Sunk costs models the interactions between export specific sunk costs and

expectations formed in an uncertain environment. Experience plays an important role in forming

this interaction. Evidence verified the theoretical prediction that sunk costs is a significant source

of export persistence. Further, heterogeneity of firm characteristics plays an important role in

export market participation. Size, measured by the number of workers or the capital stock, is

positively related to export propensity. Size may account for productivity and scale economies

effect as firms with lower average or marginal costs and higher efficiency tend to grow relative

to the others. Age, may also account for cost differences across firms as older firms tend to be

more competitive due to cost advantage. Ownership structure also affects the odds of exporting

as multinationals are more likely to export due to their multimarket presence. Firms’ action such

as increasing product quality is an important factor to enter certain export markets. Similarly,

inputs’ quality and source may affect final products’ quality as imported inputs may be better.

They may increase the efficiency of production process by allowing for a better match between

the input mix and the production technology. Firms may also import inputs due to requirements

as part of licensing agreements.

2.2.2 Firm productivity, quality, research & development and innovation

Barrios, et. al. (2003) argue that exporters are high-performing firms because they compete in

foreign markets, face higher trade barriers and different consumer tastes. However, these firms

become more competitive because they become aware of the innovations taking place in

importing countries and may assimilate these. Hence, investment on Research and Development

(R&D) needs to be made to adopt the foreign technologies and compete successfully in foreign

markets. Barrios, et. al. (2003) estimate the effect of different factors on a firm’s decision of

whether or not to export and the determinants of the export ratio (measured as exports over total

sales) using Spanish manufacturing firms data for the period 1990–98. Their results show that a

firm’s own R&D investment and appropriate knowledge are important determinants of not only

whether or not the firm becomes an exporter but also how much a firm exports. Such

investments also raise firms’ efficiency and product quality. Bleaney and Wakelin (2002),

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Wakelin (1998) and Greenhalgh (1990) also provide evidence in support of the positive

association between firm’s R&D investment and exports. Stalley (2009) observes that it is

generally believed that integration enhances access to cleaner technology, exposes local firms to

norms of environmentalism, and compels local firms to meet the environmental standards of

importing countries or risk losing market access. The study finds only modest environmental

standards induced environmental performance among Chinese companies. Further, Chinese

firms integrated in global economy are either no better than local firms or, in the case of large

exporting firms, are worse.

Serti and Tomasi (2014) reported that productive firms self-select into export markets.

Alternatively, ex-ante, exporting firms are more productive than those who do not export. In

addition to productivity level, characteristics of the importing countries, trade costs, market size,

and the remoteness of the country from the rest of the world are the other factors affecting firms

export. Given firm productivity, an increase in trade costs or decrease in market size decreases

profits, remoteness makes a market less competitive and more profitable and finally profits

increase with decrease in fixed and variable costs. Girma et al., (2004) found that although

exporting firms have high productivity, and self-select in export market, however, exporting

further increases firms’ productivity. This finding is in contrast to other studies, showing a one

way relationship between productivity of firms and exports.

Hallak and Sivadasan (2009) emphasize that demand for quality products is high in

developed countries, where consumers have a lower marginal utility of income. Afenyo and

Alemna (2009) also found quality as an important determinant of non-traditional African

exports. Hence, firms producing quality products may self-select into developed countries.

Martincus and Carballo (2010) observe that public policies such as export promotion activities

affect firms’ decision to enter a new market. They found that export promotion activities have

helped firms in Uruguay to find new export destinations and exported differentiated products

demanded in new markets.

2.2.3 International business management

Rock (2010) integrates business environment and firm-specific factors affecting firms’ export

competitiveness. He identified business-environment factors (BEF), external and internal factors,

and firm-specific factors, affecting export success and growth of a firm. The framework

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integrates strategic, functional, and operative factors affecting exporting firms’ performance.

Business environment factors included factors related to national comparative advantages and

endowments, national base of resources, industry specific factors including its comparative

advantage and government policies.

Factors determining national comparative advantages stem from natural resources such as

labor and capital, geographic location, climate, land, and risk perception. All resources

accumulated historically are included in the national base of resources and consists of

transformation of natural resources, international exchanges and investments in human, physical,

and technological resources. Individualism, power distance, attitudes toward integration and

cooperation, moral discipline, physical infrastructure, educational and training systems, scientific

and technological research institutions, and telecommunications systems are some of the factors

included in this category. Innovation, technology intensiveness, factor-input conditions, demand

conditions, rivalry, regulations, suppliers, local clusters, knowledge exchange, knowledge

spillovers, inter-firm relationships, and utilization of shared resources are part of national

industry-comparative advantages. Home government policies considers programs focused on

technology-upgrading, export-service, market development, access to financing, input subsidies

and assistance for improving production competitiveness, and foreign relationship support.

Factors related to firm strategic management, firm’s resources, export strategy and success in

accessing international markets, and international strategic implementation are included in Firm-

Specific Factors. The subset of factors included in each of the factor is given in table 2.3.

Fabian et al., (2009) use cognitive perspective drawing on the aspects of competitive

factors, macro-environmental and neo-institutional factors to study firms’ internationalization.

Competitive factors explain the decision-making process using competitive variables, such as

perceptions about the relationships both with clients and suppliers, and rivalry among

competitors. The macroeconomic factors include economic and socio-political factors, such as

currency instability, socio-political uncertainty, and economic growth (or decay), shortfall in

supply of raw materials, and inflation. The neo-institutional factors considers the role of

legitimacy in promoting information transfer, reducing risks, and increasing knowledge about

foreign markets by establishing social networks and facilitating interactions among firms. They

14

found that as compared to macro-environmental and neo-institutional factors, competitive

perspective of entrepreneurs plays important roles in firms’ decisions to internationalize.

Calia and Ferrante (2013) categorized heterogeneous firms into different

internationalization patterns and modeled their decisions on the forms of internationalization

such as traditional export modes (including commercial penetration operations and agreements),

the off-shoring of production and the outsourcing of services abroad. The study investigated the

complementarily/substitutability relationships between types of internationalization. They

conclude that neglecting some types could lead to an incomplete representation of the firm’s

internationalization strategy. Also, firm’s characteristics influence the type of

internationalization selected and complementarily between forms of internationalization is

preferred over substitution.

2.4 Conclusion

Section two has presented literature on two distinct objectives of this study under investigation.

The first part presents various approaches to study value chains while the second part indentifies

the factors affecting firms’ participation in export markets. Input-output view of the value chain

analysis is relevant to this study as the approach considers all the processes involved in bringing

a product from initial conception to final use. The approach will help in identification and

application of various processes involved in the value chain of leather processing; one of the two

main objectives of this study. The second part identifies a number of factors affecting

internationalization of a firm. These factors are related to trade barriers, firms’ productivity and

quality of product and business management factors, which are internal and external to a firm.

Data on these factors will be collected using a questionnaire given in Annexure-2.

15

Table 2.2: Firm specific main and its respective sub-set of factorsMain Factor Sub-Factor Minor Factors

Firm Strategic Thrust

StrategicDefinitions

strategic capability, extent of international business involvement, attitudes to international business, international risk perception, and expectations, or attractiveness

Firm’s Resources

human resources, R&D capabilities, physical resources, intangible resources such as knowledge, idiosyncratic, brand and reputation, informational resources, communication , technical know-how capabilities, managerial ability, financial resources, organizational resources such as quality control systems, and corporate culture legal such as trademarks and licenses, relational like relationships with competitors, suppliers, and customers, renewal competences, and prompt proactive innovations and ability to learn

InternationalCore Competences

international experience, internalization advantages, ownership specific advantages, innovation capabilities, location advantages, manufacturing capabilities for specialty products, technological superiorities, capabilities for new product development, organizational learning, international relationships with competitors, suppliers, and customers, planning systems

International Strategies

business strategy, networking setting strategy, vertical integration strategy, foreign-market entry strategy, degree of country- market diversification, foreign co-operative alliances, diversification, inter-firm cooperation, quality

International Strategic Implementation

managerial commitment, international involvement, and international structures

Export-Operative Strategy

---- Export marketing strategy, market knowledge, identify customers' needs, product characteristics such as culture specificity, patent strength, and uniqueness, product adaptation, promotion, competitive, pricing, distribution, marketing mix adaptation to market target, customer service, image and quality

Success for Overcoming Barriers

---- Size, regulatory framework, legal framework, export market potential demand, degree of cultural difference, differences in language, differences in political systems, level of education, level of industrial development, degree of rivalry, customers' familiarity with the product, customers' brand knowledge, export procedures, import/export restrictions and transport arrangements, exchange rate fluctuations, development of distribution channels, financial barriers, and information, collection of money, payment assurance, international marketing services, and tax implications of exporting

Access to Foreign Comparative Advantages

---- foreign investment, joint research and development program, foreign suppliers and foreign knowledge access

Source: Rock (2010)

16

3. Method

3.1 Sampling Frame and Sampling

The study investigates the value chain of leather production and processing and manufacturing of

selected products in Punjab and Khyber Pakhtunkhwa. Since it is costly to survey the entire

industry, therefore, sampling is carried out to select a representative sample from population.

This sample will be used to derive estimates about the tannery industry and exports of leather

products. Therefore, it should be designed in such a way that sampling error, the uncertainty

attributed to estimates from the sample, is minimized. Sampling frame and estimate of the

variance of the variable under study are required towards this end. Casley and Kumar (1988)

provided the following relationship to determine a single-stage random sample.

n=K 2V 2

D2 (1)

where n is the required sample size, K is the standard normal deviate for required confidence

interval and V is the coefficient of variation (i.e. standard deviation as proportion of mean) of the

variable under study and D is the margin of error, expressed in absolute percentage points and

represents the largest acceptable error in the estimates. The values of K for two- and one-sided

intervals are given in the following table.

Table 3.1: Conversion of confidence interval to normal deviate

Two-sided interval One-sided interval Normal Deviate (K)75 87.5 1.1580 90.0 1.2885 92.5 1.4490 95.0 1.6495 97.5 1.96

Source: Casley and Kumar (1988)

While the values of K and D can be assumed, there is no prior information available on

the estimates of V for any variable under study. The Industrial Establishments Directory of the

Government of Punjab was used to not only develop sampling frame, consisting of leather and

leather products manufacturers, but also get estimates of V for a variable of interest. The

17

directory provides information on name, location and phone of the unit, the products it produces,

year of its establishment, initial investment, number of employees and annual installed capacity

of the establishment. The study uses annual installed capacity of the establishment as a variable

of interest for measurement of V because it is a good indicator of the output of the establishment.

However, the directory may not be complete, as it may not include all the leather producers in

the province. Further a number of leather products manufacturers are not registered in the

directory as leather tanners rather they are included in leather products manufacturers. However,

these manufacturers also own tanneries to produce their own leather. With all its limitations, but

being the only official and recognized source, it is considered for derivation of the sampling

frame.

The directory consists of 405 tanneries, out of which 317 establishments have consistence

units of installed capacity. Their average capacity is about 396 ± 274.5 thousand square feet per

year, given to the calculated value 0.693 for V. Assuming a 10 percent error and various

confidence intervals, value of sample size ranges from 64 to 184 are calculated and given in table

3.2. The study proposes to collect data from 80 tannery establishments based on the assumption

of 90 percent one-sided, corresponding to 80 percent two-sided confidence level.

Table 3.2: Sample size for assumed values of K and D

Confidence Level K (Normal Deviate)

V (Coefficient of Variation)

D (Margin of error)

Sample Size

75% 2-sided & 85.5% 1-sided 1.15 0.693 0.10 63.4780% 2-sided & 90.0% 1-sided 1.28 0.693 0.10 78.6385% 2-sided & 92.5% 1-sided 1.44 0.693 0.10 99.5290% 2-sided & 95.0% 1-sided 1.64 0.693 0.10 129.0995% 2-sided & 97.5% 1-sided 1.96 0.693 0.10 184.37

3.2 Econometric Analysis

One of the objectives of the study is to estimate the effects of different factors on firms’

participation in the leather export market. The phenomenon of leather exports is characterized as

a two-steps decision process. First, firms decide to whether participate in the export market and

second how much to export. A binary variable for “export participation” will be used as the

dependent variable. Therefore, the Limited Dependent Variable Models such as the Probit and

18

Logit models are the candidates for modeling the decision to participate in the export market.

The general forms of Probit model is given as equations 3.1.

t i=Φ (α+β ' Z i )(3.1)

where t i is a dichotomous indicator variable such that 1 shows firms participating in export

market and zero otherwise, Φ represents the standard normal distribution yielding the Probit

regression, α is the intercept, β 'is the vector of parameters and Zi are firm i specific matrix of

exogenous variables affecting firm’s participation in export market. Details of these variables are

given in table 3.4.

Then firms decide how much to export. The dependent variables is the value of exports of

leather products to various markets. These two decisions can be approximated using Heckman

selection model. The Heckman selection model consists of a selection and an outcome equation.

The selection equation models firms participation in export market as a Probit model, and the

outcome equation models the factors affecting firms exports using least squares technique.

Consider the following sample selection equation,

t i¿=η' Zi+u i(3.2❑)

where t i¿ is a latent variable and not observed but we do observe if firms export or not, such that

t i=1 if t i¿>0 and t i=0 if t i

¿=0 and Zi is a vector of variables that affects t i¿. In the outcome

equation (equation 3.2) let, T i be the value of firm i’s exports and Xi is the vector of independent

variables determining X i, so

T i=γ ' X i+εi(3.3)

The errors ui andε i, i=1,...,N have a bivariate normal distribution with zero means, standard

derivation of σ u and σ ε and correlation ρ. Greene (2003) and Hoffmann and Kassouf (2005)

show that

E [T i∨ti=1 ]=γ ' X i+ ρ σ ε λ i ( αu )(3.4)

19

where the function λ i (α u )=ϕ ( η' z

σu )Φ ( η' z

σu) is the Inverse Mills Ratio (IMR), ϕ is the standard normal

density function and Φ is the cumulative standard normal distribution function. Equation (3.4)

estimates the expected values of T i when trade is observed. Greene (2003) shows that due to the

correlation between Xi and the IMR a least squares regression of T i on Xi, omitting λ i (α u )

produces an inconsistent estimator of γ '. Also, standard regression techniques assume that ρ=0,

thus eliminating the IMR in equation (3.4) and producing biased estimation results if the IMR is

statistically significant.

Let X f denote regressors common to both the selection and outcome equations and consider

ρ σ ε=β λ, then the marginal effect for the regressor is

∂ E [T i∨t i=1 ]∂ X f

=γf −ηf

σuβ λ λi (α u ) [ λi (α u )−αu ]=γ f −

η f

σ uβλ δi(3.5)

where δ i=λ i ( αu ) [ λi (α u )−αu ]. The marginal effect given in (3.5) is composed of a change in the

value of trade (T i) due to a change in X f for the bilateral trade partners participating in trade.

Hence, this effect is conditional on the bilateral partners trading non-zero values of product f and

it is called the conditional marginal effect. Greene (2003) and Hoffmann and Kassouf (2005)

also derive the conditional marginal effect for a common binary variable. Assume now that Z f is

a binary variable. Let z0 be the vector of explanatory variables in the selection equation with X f

equal to zero, and all other variables at their mean values and z1 be the same vector when X f k is

equal to one. Then the change in the IMR (∆ λ) for z, when it moves from z1 to z0 is

ϕ( η' z1

σu)

Φ( η' z1

σu)−

ϕ ( η' z0

σ u)

Φ( η' z0

σu). Hence, the conditional marginal effect for the binary variable is

∂ E [ ΔT i∨ti=1 ]∂ Z f

=γ f +β λ ∆ λ(3.6)

20

3.3 Description of Variables

The questionnaire used in the study is attached as annexure 2. The questionnaire is primarily

focused on the activities and process carried out in converting skin into fine leather. The

questionnaire collects data on the cost and return structure of the leather production and

processing including the technologies employed in these processes. This information will be

used in describing the value chain of leather processing. It also collects data on firms specific

variables to be employed in econometric estimation. These variables are discussed in the next

section.

3.3.1 Dependent and independent variables

The dependent and independent variables to be used in econometric analysis are given in the

following table.

Table 3.4: Description of variables

Variable DescriptionDependent VariablesValue of Exports Rupee value of exports of a firmti Dummy variable, 1 indicating firms’ particpiation in export

market zero otherwiseIndependent VariablesNumber of employees Number of employees of a firm Ownership structure Owner-managed, sole proprietor and Owner-managed,

partnershipFlushing machine Firms having flushing machineMechanical Stretcher Number of mechanical stretchers a firm ownsExperience Years of exportsExport age Number of years exportsNumber of certificates Number of ISO and other certificates a firm hasContract Number of export contracts during last five yearsForeign Visits Number of foreign visits of CEO during last five years

4. Results and Discussion

4.1 Descriptive Statistics

The data is collected in three districts, Kasure, Sialokot and Gujranwala, of Punjab province.

Kasur, formally part of district Lahore is situated adjacent to the Indo-Pak border. It is very well

known for tannery industry and leather production not only in the country but also in the world.

21

Niaz Nagar, a town in Kasur is the hub of tanneries and fine leather production. Sialkot is located

in the northeast of Punjab province and is known for its exports of sports and surgical products to

the entire world. It produces about 70 percent of the world’s footballs and is the world's largest

producer of hand-sewed footballs. The footballs used in the 2014 FIFA World Cup's soccer were

made in Sialkot. The district hosts some of the biggest leather tanneries of Asia. Gujranwala is

known as the industrial city of the country and situated about 80 kilometres south from Lahore.

Hence, all the three districts are very close to Lahore, the provincial capital of Punjab province.

Two-third of the respondents are taken from Kasur due to the bigger tannery industry and the rest

one third from Sialkot and Gujranwala.

Survey results how that tannery industry is predominately family owned, run as sole

proprietorship and seldom merged. Only 20 percent of the establishments use only bovine

animals skin while the rest use more than one type of skins. Only one-third of the Chief

Executive Officer of the establishments visit foreign countries with respect to exports and 18

percent has business contracts with some of the biggest brand names in the leather industry such

as Frontier and Levis. Forty three out of 151 establishments reported exports and 42 percent of

these have more than 10 years of exporting experience. Very few (18 out of 151) have one or

more certification. Those who do not export predominately report lack of information about

foreign markets and lack of financial resources.

Table 4.1: Descriptive statistics of the firmsVariable Number of cases PercentDistrictKasur 115 76.2Sialkot 31 20.5Gujranwala 5 3.3Total 151 100.0Ownership structureSole proprietor 133 88.1Partnership 17 11.3Other specify 1 0.7Family ownershipYes 119 78.8No 32 21.2Has the business been merged?Yes 17 11.3

22

Variable Number of cases PercentNo 134 88.7Type of skin used in processingBovine animals 30 19.9Bovine and others 121 80.1Number of the foreign visits of the CEO during the last five yearsNo visit 109 72.2Less than five visits 28 18.5Five to ten visits 8 5.3More than 10 vists 6 4.0Number of contract with the importing firm during the last 5 yearsNo contract 130 86.1Had contract 27 17.9Frontier 6 22.2Warrior 2 7.4Seven Diamonds 1 3.7ZARA 3 10.1Hush Puppies & Services 1 3.7Five Diamonds 1 3.7Levis 4 14.8M&S 2 7.4Moody 1 3.7Mainpol Leather 2 7.4H&M 1 3.7Guess 1 3.7Tommy Hilfiger 1 3.7Adidas 1 3.7Exporting yearsUp to five years 15 34.9More than 5 and less than 10 years 10 23.3More than 10 years 18 41.9Certification made and steps taken to access export marketISO 9001 11 61.1ISO-900 7 38.9SA-8000, ISO19000, OHSAS, SEDEX, CHRRN 1 5.6BCSI 1 5.6CE 5 27.8Total 18 11.9Don’t have certification 134 88.7Export barriers*

23

Variable Number of cases PercentLack of information about foreign markets and contacts 83 74.8Complex export procedure 28 25.2Entry into new markets is risky 41 36.9Inadequate financial resources 54 48.6Insufficient government support 43 38.7Do not know how to export 22 19.8Did not report 87 78.4

Source: Survey data* Figures do not sum to 100 due to reporting of multiple barriers. 4.2 Leather Value Chain

Leather is created through the tanning of hides and skins of cattle by converting the putrescible

skin into a durable, long-lasting and versatile natural material. The survey shows that leather

value chain can be identified in two stages. Stage first takes raw skin and ends with the

production of wet blue (Figure-4.1). The second stage takes wet blue and converts it into fine

leather (Figure-4.2).

The first step of leather processing is the recovery of hides and skins from

slaughterhouses and butchers. Skin collectors collect fresh skins from butcher houses while

individual butchers supply skins to collectors. Skins are sorted according to quality. More than

90 percent of the tanneries reported that skins are checked for wounds, scar, cuts and diseases

before buying. During data collection tanneries having at least three drums were selected for the

study. The study ignored those very small tanneries which use pets for soaking and subsequent

leather processing. This has done to collect data from tanneries involved in at least wet blue

production.

Skin collectors treat skin with salt before storing these. At a tannery, skins are sorted by

quality and specie and then placed in drums for cleaning, soaking and removal of salt. The

average price of raw skin, irrespective of its size, is about Rs. 3,150. About 96 percent of the

tanneries reported that they store skins after receiving. Skins are stored for 4 days. The average

weight of a skin before moisturizing is 25.6 kgs. About 6 drums are installed per tannery with

two drums per tannery are used in soaking. These drums are used for 3 days a week in soaking. It

takes about 36 hours for a drum to complete the soaking process. The average capacity of a drum

is about 437 kgs. Hence on average 17 skins of various sizes and weights are processed in a

drum. It is important to mention that soaking is carried out for rehydration of skin. Soaking

24

involve the use of biocides, soda ash, detergent and a preservative. Biocides prevent the growth

of bacteria which can damage the hides or skins during the soaking process. Degreasers help

with the removal of natural fats and greases from the hides or skins. Soda ash is used during the

soaking or liming processes to help raise the pH of the hides or skins.

It is followed by liming to chemically remove unwanted proteins and hair and open up

skin pores using a lime. Calcium carbonate, sodium sulphide and sodium hydrosulphide are used

for these purposes. Caustic soda is used during the liming process to help swell the skins.

Sodium hydrosulphide chemically destroys the hair on skins. It does not create as much swelling

as sodium sulphide does.

Fleshing is the next operation and it involves removing of subcutaneous material of skins.

Flesh from the inside of the skin is removed with a mechanical fleshing machine. About 55

percent of the tanneries reported to have mechanical flushing machine. In small tanneries

laborers manually carry out this process. Manual fleshing leads to a number of skin problems in

laborers. Flushed material consists of the hard flesh (i.e. subcutaneous material of skins) and

liquids having all the chemicals used in the liming process. The hard flesh material is sold to the

adhesive industry. The average value of flushed material is about Rs. 207,567. About 56 percent

of the 151 respondents reported disposing off the liquid fleshed material into nullah while 24

percent did not respond to the question.

Reliming with enzyme solution is carried to further treat hide/skin in order to get more

opening up of pores and protein and interfiber removal. The enzyme treatment to remove

proteins and to assist with softening of the pelt is also known as bating. A number of enzymes

are used in bating. Enzymes like proteases, lipases and amylases have an important role in the

soaking, dehairing, degreasing, and bating operations of leather manufacturing. Proteases are the

most commonly used enzymes. Enzymes do not damage collagen or keratin, but dissolves

proteins such as hydrolyse casein, elastin, albumin, globulin-like proteins and non-structured

proteins. Ammonium sulphate is used during the deliming process and helps remove lime from

the hides or skins. Ammonium chloride is used during the deliming process and helps remove

lime from the hides or skins. Sodium metabisulphite is used during the deliming process and

helps prevent the formation of toxic hydrogen sulphide gas during deliming. It also acts as a

bleaching agent. The average weight of skin at this stage is about 22 kgs implying that about 3.6

kgs per skin of flushed material is produced. About 3 drums are used in reliming and it takes

25

about 41 hours for a drum to complete this process. Bleach is also used during deliming to

modify dark pigments and accomplish lighter colored pelt, a stripped animal skin ready for

tanning.

It is followed by pickling to lower the pH value of pelt and help the penetration process

of tanning agents. Salt is used during the pickling process to prevent acid swelling of the hides

or skins. Formic acid is used during the pickling process to lower the pH of the hides or skins.

Sulphuric acid is used during the pickling process to lower the pH of the hides or skins.

Tanning converts raw skin into a stable and flexible material which does not become

putrid when wetted back as compared to raw hides which can be putrefied when wetted back.

Tanned skin is suitable for a wide variety of end applications. Different tanning methods and

materials are used in the tanning process. However, the choice of method and tanning material

depends on the use of leather. Tanning methods include vegetable and chrome tanning.

Vegetable tanning uses vegetable matter such as tree bark, tara extract and pyrogallol tanning

agents and other such sources. Chrome tanning uses chromium, leaving leather pale blue,

commonly called as “wet blue”. The acidity of hides before either vegetable or chrome tanning is

between pH of 2.8-3.2.

In vegetable tanning, skins are weighed and placed in a rotating drum with water and the

appropriate measure of tanning agent. After ensuring even absorption of tanning material, skins

are removed from drums and hanged over wooden horses to drain tanning material and allow

tannage to fix. It generates brown color leather with the exact shade depends on the mix of

chemicals. Vegetable-tanned leather discolor in water, shrinks when gets dry and become harder.

About 61 percent of the total and 92 percent of the valid observations reported to the use of

chrome as tanning agent. In chrome tanning hides are loaded in a drum and immersed in tanning

liquor. Hides are loaded in drums having tanning liquor, which are allowed to soak as drum

slowly rotates. During this process tanning liquor slowly penetrates into hide. Quality assurance

of penetration is ensured through observing the cross section of a hide. After complete

penetration of tanning material, the pH of skins is raised to 3.8-4.2 in a process called

basification. Basification fixes the tanning material to the pelt and increases stability of leather.

Chromium sulphate is the tanning agent used to make wet blue. Sodium formate is used during

the tanning process to assist with the penetration of chromium tanning salts into the hides or

26

skins. Magnesium oxide is used during basification and raises the pH of the hide or skin to allow

the chromium or aldehyde to chemically bind to the skin protein. Fungicides are chemicals that

are used to prevent the growth of moulds or fungi on tanned hides or skins. Chrome drained from

leather suing wooden horses. About 78 percent of the respondents are aware of the chrome

recovery system. Of these, 70 percent wanted to be part of any chrome recovery system if

installed by the government. However, only five percent want to be part of this system on

payment and none reported how much they are willing to pay for it. Hence, very few are willing

to pay for such a system. This process yield wet blue and about 70 percent of the tanneries

produce only wet blue leather. During all the above chemical processes, questions were asked

about the tests carried at each stage to ensure quality of processing. Majority of the tanneries use

litmus test to keep eye on pH level and no other specific tests were reported.

Moisturizing, liming, deliming and flushing collectively cots 63 percent of the processing

cost of tanneries producing wet blue while the rest is accounted by chroming (table 4.2). As the

number of operations in the value chain increases, the proportion of these costs reduces. These

costs decrease to 47 percent if splitting and shaving is added to the value chain; it further reduces

to 3 percent for final leather producers and 18 percent to those who produce leather based goods

(table 4.2). The respective rupee value of these proportions is given in table 4.3 and margins are

given in table 4.4.

Splitting of pelt is carried to cut it into two or more horizontal layers depending on the

demand from buyers. Splitting is simultaneously carried with shaving to make the surface of pelt

smoother and even. About 62 percent of the tanneries reported to carryout splitting and shaing.

More than 80 percent of these tanneries reported ensuring less than 2mm thickness of skin at

splitting stage. During splitting and shaving, pieces of leather are left over which are sold. About

88 percent of the tanneries reported selling of the left-over leather generating about Rs. 2.79

million during per year. In some tanneries, the leveled/split skins are sorted by appropriate

character and grain for each order. Splitting cost around 20 percent (table 4.2).

Splitting and shaving is followed by re-chroming and fatliquoring (a process to re-

lubricate the skin fibers with natural oils in a combination of animal, vegetable, and mineral

oils). Leather is soaked in oil and agitated for absorption. Finalization involve toggling of dyed

skin in the drying room, then re-staked and polished or burnished, which involves rubbing with a

27

metal or glass tool to bring up the shine. Once the leathers have been measured for square

footage, they are ready for sale and use.

Tanneries buying raw skins and converts these into fine leather generate a net margin of

Rs. 38.4 per square foot of fine leather (table 4.4) . This margin is about Rs. 41 per square foot if

tanneries produce only wet blue and Rs. 33 for tanneries involved in processing of raw skin to

splitting. Fine leather producers use leather to produce goods for foreign markets, increasing

their net margins. Unfortunately, the net margin of good producers could not be calculated due to

non-provision of data by the respondents involved in this value chain.

Figure 4.1: Value Chain of Leather from Raw Skin to Wet Blue

28

Water, Biocides, Soda

Ash, Detergent, Preservatives

Soaking2

Drums/Tannery

Chrome Tanning 90 % use

wooden horses

Pickling (Drums)

Fleshing (Manual (35%)/

Mechanical (65%))

90% sell waste @ 0.21 Mil/Year

Deliming (Drums)

Weight/Skin = 22 Kgs Water,

Chromium Sulphate, Sodium Format,

Magnesium Oxide,

Fungicide

Water, Salts ( Ammonium

sulphate, chloride, sodium metabisulphite,

Bating Enzymes)

Water (Fleshing machine)

Water, Sodium Hydro

Sulphide, Lime (8 - 10%),

Caustic Soda

Liming/Unhairing

(Drums)

Water, Salts, Sulphuric Acid,

Formic Acid

Wet Blue

Receiving (Storage = 4 days, Weight/Skin =

25.8 Kgs

Figure 4.2: Value Chain of Leather from Wet Blue to Fine Leather

29

Water, Chromium, Syntans

Water, Dyes, Synthetic Oil

Splitting/ShavingLeftover worth Rs. 2.79 MilThickness <= 2 mm (80%) 20% has mechanical stretchers

Re-chroming Retaining (Drums)

Dyeing & Fatliquoring (Drums)

Dry Finishing (Machinery Operation)Finished Leather

Wet Blue

Table 4.2: Proportion of cost in the selected value chainsType of VC Statistics Moisturizing,

liming, de-liming & Flushing

Chroming Splitting & Shaving

Re-Chroming

Fatliqouring Finalization Good Production

Marketing

Wet BlueMean 62.7 39.4            # cases 57 54SD 26.115 25.250            

Raw Skin to Splitting

Mean 46.7 33.3 20.0          # cases 6 6 6SD 10.328 5.164 6.325          

Raw Skin to Re-chroming

Mean 40.7 23.2 18.9 17.1        SD 9.972 5.754 8.128 9.347        

Buy Wet-blue and Produce Fine Leather

Mean 37.3 24.5 19.1 30.0    # cases 11 11 11 7SD   11.037 9.070 5.839 10.000    

Raw Skin to Fine Leather

Mean 23.2 20.9 15.9 13.9 16.5 23.2    # cases 22 22 17 22 20 14SD 11.160 5.209 5.302 5.914 8.751 10.116    

Raw Skin to Goods Production

Mean 17.6 16.5 20.7 11.8 7.9 12.5 15.6 10.8

# cases 9 10 12 11 10 10 12 10

SD 5.812 11.501 14.164 5.930 4.909 5.720 6.640 4.050

All Value Chains

Mean 47.2 30.9 21.9 16.3 15.1 21.3 15.6 10.8

# cases 108 106 60 58 41 31 12 10

SD 26.969 20.726 11.869 8.537 8.285 10.925 6.640 4.050

30

Table 4.3: Cost of processing of leather and goods production in the selected value chainsType of VC Statistics Moisturizing,

liming, de-liming & Flushing

Chroming Splitting & Shaving

Re-Chroming

Fatliqouring Finalization

Good Production

Marketing

Wet BlueMean 136.2 84.3            

# cases 44 41

SD 62.496 95.701            Raw Skin to Splitting Mean 164.9 108.3 59.3          

# cases 6 6 6

SD 92.925 49.976 20.238          Buy Wet-blue and Produce Fine Leather

Mean                

# cases

SD                Raw Skin to Fine Leather Mean 71.6 44.7 32.8 21.7 20.9 40.6    

# cases 5 5 5 5 4 2

SD 29.1 20.7 25.2 21.7 15.2 48.7    Raw Skin to Goods Production

Mean 155.6 117.9 109.3 82.9 61.2 144.1 132.7 94.0

# cases 8 8 8 8 8 6 8 6

SD 81.148 76.465 42.369 41.227 36.989 82.821 68.264 60.067

31

All Value Chains Mean 134.9 86.1 68.5 62.2 47.8 118.2 132.7 94.0

# cases 77 74 33 27 12 8 8 6

SD 65.176 79.390 39.681 45.986 36.435 86.803 68.264 60.067

Table 4.4: Cost and margins of leather processing and good production of the selected value chainsType of VC Statistics Cost without

SkinCost with

SkinFinal Price

Net Margin per Skin

Net Margin per square Foot

Wet Blue Mean 210.0 3370.5 4832.8 1627.0 40.7# cases 43 44 43 43 43

  SD 141.375 1537.480 1831.780 939.041 23.476Raw Skin to Splitting Mean 332.5 2774.2 4083.3 1309.2 32.7

# cases 6 6 6 6 6  SD 149.022 898.317 1212.298 2089.850 52.246

Buy Wet-blue and Produce Fine Leather 

Mean --- 4832.8 5640.0 2300.0 57.5# cases --- 43 5 1 1SD --- 1831.780 1252.200 -- --

Raw Skin to Fine Leather Mean 134.7 3290.6 4600.4 1534.2 38.4# cases 10 27 33 27 33

  SD 73.383 1262.325 1267.680 1767.845  

Wet Blue to Goods Production (Gloves) 

Mean 382.5 3753.0 105.0 --- ---# cases 4 4 7 --- ---SD 38.891 1790.165 72.053 --- ---

32

Raw Skin to Goods Production (Jackets) 

Mean 691.6 3710.3 8294.7 --- ---# cases 8 8 8 --- ---SD 480.322 551.192 3655.776 --- ---

33

4.3 Firms’ participation in international market

Tables 4.5 to 4.8 provide the results of estimating equations (3.1 to 3.4). Table 4.5 presents

estimates of the Probit equation. Dependent variable in this case is an indicator showing whether

a firm participated in an export market or not. The model fitted the data well as the Pseudo R-

squared is 0.44. McFadden (1974) states " Those unfamiliar with rho-squared should be

forewarned that its values tend to be considerably lower than those of the R2 index...For example,

values of 0.2 to 0.4 for rho-squared represent excellent fit". Rho-squared in this case is

represented as pseudo R-squared. The hypothesis that all of the coefficients of the model (except

the constant) are zero, is rejected at the 99 percent level of significance as indicated by the

statistically significant Chi-square value.

Focusing the discussion only the statistically significant variables, the results show that

number of foreign visits of the Chief Executive Officer (CEO) of the business, whether a firm

has a flushing machine, number of mechanical stretchers and number of permanent employees

are statistically significant determinant of tanneries participation in export market. Marginal

effects, elasticities in this case, of all the variables are calculated at means. Number of

mechanical stretcher has the highest elasticity as an infitesimal amount of increase in it leads to

41.8 percent increase in the probability of participation in export market for tanneries. It is

important to mention that stretching is an important activity in leather processing. Tanneries

purchase hides by weight but sell leather by area. Area of leather cane be increased in a

mechanical operations such as sammying, a process in which 45-55% (m/m) water is squeezed

out of the leather. However, this increase is not permanent and may be lost in the subsequent

operations. Permanent increases in area and fine surface of leather can only be accomplished by

drying leather while maintained in a stretched condition. No tannery can produce fine leather

without having a mechanical stretcher. And unless a tannery owns a mechanical stretcher, it is

highly unlikely to manufacture and export leather products based on fine leather. As already

discussed in the value chain, fleshing is a process involving removing of subcutaneous material

of skins from the inside using a mechanical fleshing machine. About 55 percent of the tanneries

reported to have mechanical flushing machine. Without mechanical flushing, fine leather cannot

be produced as quality cannot be maintained in manual flushing. Flushed material consists of the

hard flesh (i.e. subcutaneous material of skins) and liquids having all the chemicals used in the

liming process. Having a flushing machine, increases the probability of participation in export

34

market by 28 percent. Similarly increasing the number of permanent employees raises the

probability of participation in export market by 41.4 percent. Large number of permanent

employees is kept in a tannery involved in an export market. These tanneries operate throughout

the year by producing fine leather. These results show that ownership of machinery used in

leather value chain is a key factor in accessing foreign markets.

While Probit model estimates the effect of different factors on firms participation in

trade, it is also important to understand the effect of different factors on the level of exports.

Firms make these decisions jointly. Hence, Heckman selection models provide the plate-form to

estimate the effect of different factors on both the phenomenon jointly. Tables 4.6 and 4.7

provide the estimated results of the Heckman selection models estimating using Two-step and

maximum likelihood procedures. These tables present results of the selection and outcome

equations as well as marginal effects. It is important to mention that marginal effect of a variable

common to both the selection and outcome equations is not the same as given in the estimates.

These marginal effects are derived using equations 3.5 and 3.6.

The Heckman model requires sufficient variation to identify the parameters of the

selection and outcome equations, requiring identification of separate variables that affect the

inverse mills ration (IMR) from those that determine the outcome equation. In practice this is

seldom possible, because in most cases the variables that determine the selection equation also

determine the outcome equation. However, in our analysis the selection and outcome equations

represent two different phenomena that are functions of different variables. Dependent variable

in the outcome equation is value of exports that is assumed to be determined by the number of

contracts of a local firm with international firm while such a variable does not affect firms

participation in international market as only an exporting firm can get contracts from the foreign

firm. Maddala (1983) suggest that for identification of equations (3.3) and (3.4), either

cov (ui , εi )=0 or there is at least one variable in Xi not included in Zi. This condition is

accomplished in this study hence the models specified in this study do not have any

identification problem. Finally, Greene (2003) shows that the estimates generated with the

Heckman model estimated simultaneously using the maximum likelihood (ML) procedure is

homoskadestic, hence the selection and outcome equations are also estimated using this

procedure.

35

Wald tests of the hypothesis that all of the coefficients in the regression model (except

the constant) are zero is consistently rejected at the 99 percent level of significance for both the

models (Tables 4.6 and 47). Table 4.6 shows that Lambda is statistically significant indicating

that both the selection and outcome equations cannot be estimated separately. Further, the arc

hyperbolic tangent of ρ representing selection bias is statistically significant in table 4.7

confirming the last result that both the equations cannot be separately estimated. Finally, the

likelihood ratio test is used to test the independence of the selection and outcome equations. The

test rejects the hypothesis that the selection and outcome equations can be estimated

independently. Hence, the use of OLS estimating the effect of exogenous variables on the value

of exports in this case would produce biased results (Heckman, 1979).

The elasticities calculated at means in table 4.7 show that a number of contracts,

experience in exports, number of employees and number of foreign visits are statistically

significant and positive. These results show that one year increase in experience increases

exports by 0.06 percent, increasing employees by one, increases exports by 0.16 percent and

each foreign visit of the CEO increases exports by 0.005 percent, keeping other variables

constant. These results are consistent with ML estimates of the Heckman selection model. The

standard errors in the ML estimates are corrected for heteroscadesticity. Comparing the results of

selection equation in tables 4.6 and 4.7 with Probit estimates given in table 4.5 shows that results

are consistent across the techniques and specifications. These results reconfirm the important

role ownership of machinery, foreign visits of the CEO and number of employees play in

participation in exports market.

36

Table 4.5: Probit estimates and marginal effects of factor affecting firms’ participation in export market

Variable Coefficient Standard Error z ProbabilityNumber of foreign visits 0.090 0.031 2.94 0.003Education 0.019 0.039 0.49 0.622Number of sources -0.199 0.359 -0.55 0.579Ownership 0.114 0.424 0.27 0.788Family business -0.327 0.358 -0.91 0.361Fleshing Machine 1.121 0.346 3.24 0.001Number of mechanical stretchers 1.280 0.306 4.18 0.000Number of quality certificates 0.155 0.154 1.00 0.316Number of permanent employees 0.008 0.002 4.15 0.000Summary StatisticsChi-Squared 86.1 0.000Pseudo R-Squared 0.443      ElasticitiesNumber of foreign visits 0.199 0.070 2.840 0.005Education 0.232 0.471 0.490 0.622Number of source -0.077 0.137 -0.560 0.576Ownership 0.142 0.530 0.270 0.789Family business -0.441 0.490 -0.900 0.368Fleshing Machine 1.962 0.701 2.800 0.005Number of mechanical stretchers 0.548 0.131 4.170 0.000Number of quality certificates 0.094 0.093 1.000 0.316Number of permanent employees 0.210 0.051 4.140 0.000

37

Table 4.6: Heckman two-step estimates of the selection and outcome equations and marginal effects Variable Coefficient Standard Error t-ratio ProbabilityOutput EquationNumber of contracts 0.211 0.078 2.690 0.007Experience 0.072 0.017 4.160 0.000Ownership -0.068 0.453 -0.150 0.881Family business -0.008 0.460 -0.020 0.985Fleshing Machine -0.685 0.542 -1.260 0.206Number of mechanical stretchers 0.061 0.156 0.390 0.696Number of quality certificates 0.011 0.083 0.130 0.896Number of employees 0.006 0.002 2.810 0.005Number of foreign visits 0.043 0.041 1.040 0.296Selection EquationNumber of foreign visits 0.090 0.031 2.940 0.003Education 0.019 0.039 0.490 0.622Number of sources -0.199 0.359 -0.550 0.579Ownership 0.114 0.424 0.270 0.788Family business -0.327 0.358 -0.910 0.361Fleshing Machine 1.121 0.346 3.240 0.001Number of mechanical stretchers 1.280 0.306 4.180 0.000Number of quality certificates 0.155 0.154 1.000 0.316Number of permanent employees 0.008 0.002 4.150 0.000Selection HazardsLambda -0.914 0.403 -2.270 0.023Summary StatisticsNumber of observations 151Number of censored observations 99Number of uncensored observation 52Wald Chi-Squared (9) 46.550 0.000Elasticities at MeanNumber of contracts 0.008 0.003 2.710 0.007Experience 0.060 0.014 4.220 0.000Ownership -0.004 0.028 -0.150 0.881Family business -0.001 0.030 -0.020 0.985Fleshing Machine -0.058 0.045 -1.300 0.195Number of mechanical stretchers 0.001 0.003 0.390 0.698Number of quality certificates 0.000 0.002 0.130 0.896Number of employees 0.016 0.006 2.870 0.004Number of foreign visits 0.005 0.004 1.030 0.302

38

Table 4.7: Heckman maximum likelihood estimates of the selection and outcome equations and marginal effects Variable Coefficient *Standard Error t-ratio ProbabilityOutput EquationNumber of contracts 0.211 0.090 -2.350 0.019Experience 0.071 0.019 3.660 0.000Ownership -0.121 0.359 -0.340 0.736Family business -0.109 0.421 -0.260 0.796Fleshing Machine -0.527 0.703 -0.750 0.453Number of mechanical stretchers 0.114 0.111 1.020 0.306Number of quality certificates 0.028 0.064 0.440 0.660Number of employees 0.005 0.001 3.940 0.000Number of foreign visits 0.053 0.029 1.850 0.065Selection EquationNumber of foreign visits 0.091 0.040 2.290 0.022Education 0.058 0.049 1.200 0.232Number of sources -0.020 0.406 -0.050 0.961Ownership 0.116 0.349 0.330 0.739Family business -0.401 0.368 -1.090 0.276Fleshing Machine 1.097 0.307 3.580 0.000Number of mechanical stretchers 1.432 0.299 4.780 0.000Number of quality certificates 0.088 0.118 0.750 0.456Number of permanent employees 0.008 0.002 5.080 0.000/athrho -0.724 0.398 -1.820 0.069/lnsigma 0.115 0.143 0.810 0.418Summary StatisticsNumber of observations 151Number of censored observations 99Wald Chi-Squared (9) 60.79 0.000Elasticities at MeanNumber of contracts 0.008 0.003 -2.490 0.013Experience 0.059 0.015 3.940 0.000Ownership -0.007 0.022 -0.340 0.735Family business -0.007 0.028 -0.260 0.796Fleshing Machine -0.045 0.059 -0.760 0.445Number of mechanical stretchers 0.002 0.002 1.000 0.319Number of quality certificates 0.001 0.002 0.440 0.663Number of employees 0.015 0.004 4.060 0.000Number of foreign visits 0.006 0.003 1.870 0.061

Wald test for impendent of equations = 3.31 (0.068). *Robust standard errors.

39

5. Conclusions

This section is focused on the factors affecting firms’ participation in export market. Two

techniques are used to identify the important factors that determine participation of the tannery

industry in export market. First, a dichotomous indicator variable, where one showing

participation in the export market and zero otherwise is used as a dependent variable in a Probit

model, is assumed to be a set of firm specific exogenous variables. Second, Heckman selection

model is used consisting of outcome and selection equations. Value of exports was the

dependent variable in the outcome equation while selection equation was similar in nature to the

Probit model. While results of both the models are consistent, the Heckman selection model

accepts the hypothesis that both the selection and outcome equations should be jointly

estimated.

Both the estimation procedures showed that foreign visits of the Chief Executive Officer

(CEO) of the tannery, ownership of flushing machine and mechanical stretchers and number of

permanent employees are statistically significant determinant of tanneries participation in export

market. Fine leather processing involves very capital intensive processes. These operations

cannot be carried out without machines such as mechanical stretchers and flushing machine.

Even production of wet blue leather is not possible without having a fleshing machine.

Ownership of these machines is a key to access export market. The policy implication is that in

order to increase tanneries participation in export market or increasing exports, government has

to improve access of these tanneries to bank credit for acquiring of machinery involved in

leather processing.

40

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Annexure –1: Definitions of performance measure indicators Categories and indicators Definitions Measurei) Efficiency:Production costs/distribution costs

Combined costs of distribution

The sum of the total costs of inputs used to produce output/services (fixed and variable costs)

Transaction costs The costs other than the money price that are incurred in trading goods or services (e.g. searching cost, negotiation costs, and enforcement costs)

The sum of searching costs (the costs of locating information about opportunities for exchange), negotiation costs (costs of negotiating the terms of the exchange), enforcement costs (costs of enforcing the contract)

Profit The positive gain from an investment or business operation after subtracting all expenses

Total revenue less expenses

Return on investments A measure of a firm’s profitability and measures how effectively the firm uses its capital to generate profit

Ratio of net profit to total assets

Inventory A firm’s merchandise, raw materials, and finished and unfinished products which have not yet been sold

The sum of the costs of warehousing of products, capital and storage costs associated with stock management and insurance

ii) FlexibilityCustomer satisfaction The degree to which the

customers are satisfied with the products or services

The percentage of satisfied customers to unsatisfied customers

Volume flexibility The ability to change the output levels of the products produced

Calculated by demand variance and maximum and minimum profitable output volume during any period of the time

45

Categories and indicators Definitions MeasureDelivery flexibility The ability to change planned

delivery datesThe ratio of the difference between the latest time period during which the delivery can be made and the earliest time period during which the delivery can be made and the difference between the latest time period during which the delivery can be made and the current time period

Backorders An order that is currently not in stock, but is being reordered (the customer is willing to wait until re-supply arrives) and will be available at a later time

The proportion of the number of backorders to the total number of orders

Lost sales An order that is lost due to stock out, because the customer is not willing to permit a backorder

The proportion of the number of lost sales to the total number of sales

iii) ResponsivenessFill rate Percentage of units ordered

that are shipped on a given order

Actual fill rate is compared with the target fill rate

Product lateness The amount of time between the promised product delivery date and the actual product delivery date

Delivery date minus due date

Customer response time The amount of time between an order being made and its corresponding delivery

The difference between the time an order is made and its corresponding delivery

Lead time Total amount of time required to produce a particular item or service

Total amount of time required to complete one unit of product or service

Customer complaints Registered complaints from customers about product or service

Total number of complaints registered

Shipping errors Wrong product shipments The percentage of wrong shipments

iv) Food qualitySensory properties and shelf life; Appearance

First sight of the tomato, combination of different attributes (color, size and form, firmness, lack of

Amount of damage, color scale, size and form scale

46

Categories and indicators Definitions Measureblemishes and damage)

Taste Determined by the sweetness, mealiness and aroma of a vegetable/fruit

Brix value, which is measurement of a soluble dry substance in a liquid (providing an approximate measure of sugar content)

Shelf life The length of time a packaged food will last without deteriorating

The difference in time between harvesting or processing and packaging of the product and the point in time at which it becomes unacceptable for consumption

Product safety and healthSalubrity, Product safety

The quality of the products being healthy and nutritious Product does not exceed an acceptable level of risk associated with pathogenic organisms or chemical and physical hazards such as microbiological, chemica contaminant in products, micro-organisms

Nutritional value and lycopene content Lab checks and monitoring processes according to certification schemes

Product reliability and convenienceProduct reliability

Refers to the compliance of the actual product composition with the product description

Number of registered complaints

Convenience The information provided on the packaging is useful, complete and easy understandable

Number of registered complaints

Process qualityProduction system characteristicsTraceability

Traceability is the ability to trace the history, application or location of an product using recorded identifications

Information availability, use of barcodes, standardization of quality systems

Storage and transport conditions

Standard conditions required for transportation and storage of the products that are optimal for good quality

Measure of relative humidity and temperature,complying with standard regulations

Working conditions Standard conditions that ensure a hygienic, safe working environment, with correct handling and good

Compliance with standard regulations

47

Categories and indicators Definitions Measureconditions

Environmental aspectsEnergy use

The amount of energy used during the production process

The ratio of cubic meters of gas used per square meter of glasshouse

Water use The amount of water used during the production process

The ratio of liters of water used per square meter of land under the vegetables

Pesticide use A permitted amount of pesticides used in the production process

The amount and the frequency of pesticide use complying with standard regulations

Recycling/reuse Collected used product from crop, packaging, etc., that is disassembled, separated and processed into recycled products, components and/or materials or reused, distributed or sold as used, without additional processing

Percentage of materials recycled/reused

MarketingPromotion

Activities intended to increase market share for product (e.g. branding, pricing and labeling)

Increase in number of customers and sales

Customer service he provision of labor and other resources, for the purpose of increasing the value that buyers receive from their purchases and from the processes leading up to the purchase

Ratio of provision of recourses used to increase customer service to increased sales

Display in stores Demonstration of the product in the store

Increase in number of customers and sales

Source: Lusine et. al. (2007)

48

Annexure –2: Questionnaire Facility name, mailing address and location ______________________________________________________________________________

Individual providing information_____________________ ____________ ______________ ____________ __________Name Title Cell Number Landline Edu & Exp

Indicate the ownership structure

Owner-managed, sole proprietor

Owner-managed, partnership

Joint venture with local firm

Joint venture with foreign firm

Other specify

Is the business family owned? Yes/No

Has the business been merged/ammelgated/acquired with any other entity?

If yes, what are the name of business merged?

Which kind of skin you use in leather processing: bovine/sheep, goats/other specify _________________

Are you able to supply exactly what customer demand? Yes/No

If No, why? __________________________________________________________________________

Do you sub-contract? Yes/No , if Yes what processes? _____________________Rates_______________

What parts of manufacturing ______________________ rate ______________ Product______________

What is the annual value of sub-contracts: _________________

What are the main barriers in your business?

Shortage of skilled labor Shortage of skilled labor Shortage of raw material Shortage of capitalLimited access to credit market

Shortage of gas Shortage of electricity Other specify

Products or services produced during last one year (please tick)

Pickled Wet blue Finished leather gloves Luggage bagsfootware Jackets Foot/volley balls Other specify

49

Value of output and exports

Product Total Value Exports Markets/Countries*Sole leatherWetbleueFinished leatherLeather garmentsGlovesSports items

Total Sales*Ask for market share if more than one market

What are the main barriers in exports?

The lack of information about foreign markets and contact

The complexities of export documentation and procedures

The risks and uncertainties associated with entry into new markets

To improve and fine-tune existing operations

Inadequate financial resources Insufficient government support

Lack of trustworthy businesscontacts in target market

Lack of know-how on exporting

How did you explore the export market?

Internet Fellow exporter Friend Personal visit SMEDA

Number of foreign visits of the CEO/Director Marketing during last five years _____________Approximately, how much it cost you to explore the export market during the last 5 years? ____________Did you sign any written contract with the importing firm? Yes/No, if Yes, how much it cost: _________ How many contracts you signed during the last 5 years? ______ what is their approximate value:_______From how long your firm has been exporting? ________years

RECEIVING: BEAM-HOUSE (FLESHING)

From where do you receive skins?

Market Name Share Market Name Share Market Name ShareBovine AnimalsSmall Animals

After receiving skins, do you store these? Yes/No If yes, then for how many days? __________days

Are weight of skins taken before moisturizing? Yes/No

Are skins trimmed before moisturizing or washing? Yes/No

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If yes, what parts of skins are trimmed? _________________________________________

Where do you moisturize skins? Pits/Drums/Both How many pits do you have? ___________

How many pits are used in soaking? _________ What is the size of each pit? _______ Square Feet

What is the capacity of each pit? (Number of Skins) _____[Bovine Animals] ______ [Small Animals]

How many days skin processing takes in pets? _____ [Bovine Animals] _____ [Small Animals]

How many drums are installed in the tannery? ______ [Total number of drums]

How many drums are used in soaking? ________ for how many days/week: __________

What is the capacity of each drum? _______ [Large Animals] ______ [Small Animals]

How many hours it takes to process skins in drums? _______ [Large Animals] ______ [Small Animals]

Name the chemicals that you use in drums and pets.

S. No Name Quantity (Kgs)

Price/Kg Price/Unit

Pits/Drums

1 Calcium carbonate (Lime)2 Sodium sulphite3 Detergent45 Water

What is the average price of the skin? _____[ Bovine Animals] ______ [Small Animals]

What quality standards do you follow or in practice in the market while buying skins.

S.No Bovine Animals Small Animals1 Skin is disease free Skin is disease free 2 No wounds/scars on skin No wounds/scars on skin34

What is the cost of moisturizing? Rs/Skin ________ or Rs/drum ________ or Rs/pit ________

Do you have fleshing machine? Yes/No

If No, then how many laborers per day are involved in fleshing? ______

What is the cost of flushing? Rs/Skin ________ or Rs/drum ________ or Rs/pit ________

What is the current value of your fleshing machine? _________(Rs)

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Do you sell waste from fleshing? Yes/No If no, how does waste is disposed off?

If yes, which industry buys the fleshed material? Glue/adhesive industry, ______________

What is the annual contract value of fleshed material? Rs/year ______________ OR

How many trolleys are sold per week? __________ Trolleys, What is the price per trolley: ________

How do you dispose-off water? Drained in nullah/stream/river/municipal sewer, septic tank/other______

TANYARD OPERATION

Deliming:

Are weight of skins taken before dliming? Yes/No What is the average weight of a skin of bovine animal __________ (kgs) small animal _________(kgs)

How many drums are used in tanning? ________ for how many days/week: __________

What is the capacity of each drum? _______ [Bovine Animals] ______ [Small Animals]

How many hours it takes to de-lime skins in drums? _______ [Bovine Animals] ______ [Small Animals]

Name the chemicals , their quantities per drum and price used in de-liming.

S. No Name Quantity Units Price/Unit1 Sodium Format2 By product of steel ______________3 Sulphuric acid45

How do you dispose off water? Drained in nullah/stream/river/other ________

Chroming

What tanning technologies are used in the establishment? Vegetable/Chrome/Both

List the products produced with each technology.

Technology Product Name Product Name Product Name Product Name Product NameVegetable Sole leather BeltsChrome Garments Shoes Upper-leather

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Name the chemicals , their quantities per drum and price used in chroming.

S. No Name Quantity Units Price/Unit1 Chromium sulphate2 Sodium phosphate3 Sulphuric acid45

What is the per piece labor cost of chroming? Rs/skin _______[Bovine Animals] ______[Small Animals]

Shaving, Splitting, re-chroming, neutralization, Retaining, fatliquoring

Do you carryout shaving? Yes/No If Yes, do you have shaving machine? Yes/No

If no, what is the per piece shaving cost? Rs/skin _______[Bovine Animals] ______[Small Animals]

What is the per piece labor cost of shaving? Rs/skin _______[Bovine Animals] ______[Small Animals]

Do you carryout splitting? Yes/No If Yes, do you have splitting machine? Yes/No

If No, do you carry splitting in another establishment? Yes/No

How much you pay for splitting? ______ Rs/Unit

If No, why? ___________________________________________________________________

What are the usual thicknesses of leather ordered by customers? ________ _________ _______

How does the left-over leather from splitting disposed off? Sold/other ___________

If sold, then specify the quantity sold per month and rate _______________________

Do you carryout rechroming? Yes/No If Yes,

what is the per piece labor cost of rechroming? Rs/skin ____[Bovine Animals] ___[Small Animals]

Do you carryout neutralization? Yes/No If Yes,

what is the per piece labor cost of neutralization? Rs/skin ____[Bovine Animals] ___[Small Animals]

Name the chemicals , their quantities per drum and price.

S. No Name Quantity Units Price/Unit1 Sodium format2 Soda34

Do you retain? Yes/No If Yes, what is the per piece labor cost of retaing? Rs/skin ____[Bovine Animals] ___[Small Animals]

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Report the qualities of chemicals used in re-taining per drum.

S. No Name Quantity Units Price/Unit1234

Do you carry fatliquoring? Yes/No If yes, then provide the following information.

Name the oils, their quantities per drum and price used in fatliquoring.

S. No Oil Name Type Quantity Units Price/Unit123Type could be animal, vegetable, and mineral oils or broadly natural and chemical.

What is the per piece labor cost of fatliquoring? Rs/skin _____[Bovine Animals] ______[Small Animals]

How do you drain the tanning agent? Hanging on wooden horse/machine/other _____________

How many drums of leather are tanned in a month? _____________

Do you carryout dying? Yes/No

Do you weigh leather before placing these in drum for dying? Yes/No

If Yes, how much weight is processed at a time in one drum? _________Kgs

What colors are usually ordered? Red/Black/Brown/other

Do you use warm or tap water in dying? Warm/tap water

Name the dying material and chemicals used in dying

S. No Dying Material and Chemicals Quantity Units Price/Unit123

How do you dispose-off water? Drained in nullah/stream/river/municipal sewer, septic tank/other______

How dyed leather is dried? Hanged in sun in open/ room with heaters and fans/other __________

Does leather hand staked after dying? Yes/No

If no, how these are staked? _____________________________________________________

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How leather is dried? Hanged in sun in open/ room with heaters and fans/other ______________

Does leather hand staked after drying? Yes/No

If no, how these are staked? _____________________________________________________

Do you mechanically stretch leather? Yes/No, If yes, how many mechanical stretcher you have? _______

How much time does it take to mechanically stretch leather produced in a drum? ____days/hours

What is the current value of mechanical stretcher you have? ____________Rs

How many laborers per day are involved in this process? ______

Are they permanent employees of the establishment? Yes/No

What is the wage/worker? ________ (Rs/day) OR ___________(Rs/month) OR ___________(Rs/skin)

How much leather is polished/shined per month? __________________ square foot

What is its price per square foot? _____________Rs/Sq. foot

Do you further process leather? Yes/No If yes, then continue the survey.

How do you dispose-off water? Drained in nullah/stream/river/municipal sewer, septic tank/other______

Do you carryout polishing/shining of lather? Yes/No

If No, why? ___________________________________________________________________

If yes, then provide the following information.

Name the material and chemicals used in polishing and/shining

S. No Polishing Material and Chemicals Quantity Units Price/Unit123

How much leather is polished/shined per month? __________________ square footWhat is its price per square foot? _____________Rs/Sq. foot

How do you dispose-off water? Drained in nullah/stream/river/municipal sewer, septic tank/other______

Are you aware of Common Chrome Recovery System? Yes/No

Would you like to be part of Common Chrome Recovery System? Yes/No

Would you like to be part of Common Chrome Recovery System on payment? Yes/No

If yes, how much you are willing to pay? _________

What are the quality management tests used at different levels:

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Salted skin Deliming Tanyard Splitting Dying

Unit Cost Estimates

Rs/Skin Rs/Square FeetLabor costChemicals costProduction cost

Office/managerial cost Rs/Skin _________ Rs/Sq. Foot _________ Rs/Month __________Transport Rs/Skin _________ Rs/Sq. Foot _________ Rs/Month __________Land current value Rs/Skin _________ Rs/Sq. Foot _________ Rs/Month __________Installed machinery value Rs/Skin _________ Rs/Sq. Foot _________ Rs/Month __________Gross profit Rs/Skin _________ Rs/Sq. Foot _________ Rs/Month __________

Please distribute labor cost according to the following (ask for proportion):Beamhouse Deliming Tanyard Splitting Dying

Are you member of any organizations/association? Yes/No, If yes, please list.

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