Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study

Journal of Cleaner Production xxx (2014) 1e11

Contents lists available at ScienceDirect

Journal of Cleaner Production journal homepage: www.elsevier.com/locate/jclepro

Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study Marimin*, Muhammad Arif Darmawan, Machfud, Muhammad Panji Islam Fajar Putra, Bangkit Wiguna Department of Agroindustrial Technology, Faculty of Agricultural Technology, Bogor Agricultural University, Bogor, Indonesia

a r t i c l e i n f o

a b s t r a c t

Article history: Received 27 March 2013 Received in revised form 21 December 2013 Accepted 29 January 2014 Available online xxx

The main objective of this research was to map and to analyze green productivity of a natural rubber supply chain and formulate scenarios for increasing its green productivity level. The case studies were conducted in private enterprises engaged in natural rubber plantation and processing. Material flow analysis was performed using the green material flow map to analyze the seven sources of green wastes. The best strategy for green productivity improvement was determined by using the Analytic Hierarchy Process (AHP). The performance of green productivity improvement strategies was then assessed as future GPI (Green Productivity Index) and compared with current GPI. Results of this research have shown that the natural rubber cultivation combined with latex production improvement and waste minimization was the best green productivity improvement strategy. The best selected strategy for the production process was reusing the processing water. Ó 2014 Elsevier Ltd. All rights reserved.

Keywords: Green productivity Natural rubber Value stream Green productivity index

1. Introduction Indonesia is the second largest natural rubber (NR) producer in the world with a production about 28% of the total production in 2010. However, rubber plantation productivity in Indonesia is lower compared to other major natural rubber producing countries such as Thailand and Malaysia. Indonesia’s natural rubber industries have three possible sources of raw material, namely smallholders, Government Owned Enterprises, and large scale private plantations (estates). They are characterized by their low productivity on both the upstream and downstream1 sides. Indonesia natural rubber upstream productivity was 935 kg/hectare/year (Ministry of Agriculture, The Republic of Indonesia (2012)). This figure was lower than those of other natural rubber producing countries such as Thailand, Malaysia and India. In 2008, Thailand’s natural rubber upstream productivity was 1698 kg/hectare/year, while Malaysia was 1430 kg/hectare/year and India was 1930 kg/hectare/year

* Corresponding author. E-mail addresses: [email protected], [email protected], marimin@indo. net.id ( Marimin). 1 The liquid latex tapped from tress is not a stable material and processing is required to change it to a form suitable for storage or shipment. The use of the term ‘downstream’ here refers to the processes used to convert the latex to a solid form as crumb rubber, ribbed sheet, or crepe rubber.

(Damardjati and Jacob, 2009). Besides the low productivity of natural rubber upstream industry, the raw material supply for manufacturing industry was scarce due to the export of most of the NR. Existing studies on natural rubber have focused on upstream practices rather than the natural rubber supply chain as a whole. Several studies on plantation practices have been conducted such as on the germination and seedling (Basyaruddin, 2009; Permadi and Ginting, 2009; Hickling et al., 2009; Sundiandi et al., 2009; Boerhendhy et al., 2009; Muluk, 2009), and land preparation (Nugroho and Istianto, 2009). Although several studies have been done on natural rubber production and rubber-related supply chains, such as rubber wood (Zachariah and Patrick, 2011), and environmental impact (Tekasakul and Tekasakul, 2006; Singh et al., 2011; Mohammadi et al., 2011), only few of them examined the integration of productivity and effects on the environment. Arifin (2005) identified the need for integration between productivity and environmental concerns by increasing production with the introduction of new varieties of rubber trees, combined with land use that meets the requirements of sustainable resource management and environmental quality. The Arifin study, however, did not address increasing productivity throughout the supply chain nor did it integrate productivity and environmental issues in a systemic and systematic fashion. Rao (2000) suggested that an approach towards an environmental initiative required a long-term vision of a sustainable world encompassing a three-stage strategic solution

http://dx.doi.org/10.1016/j.jclepro.2014.01.098 0959-6526/Ó 2014 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Marimin, et al., Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study, Journal of Cleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.098

2

Marimin et al. / Journal of Cleaner Production xxx (2014) 1e11

for the environment, namely (1) pollution prevention before pollution control, (2) product stewardship and (3) clean technology. A systemic approach is required in order to see the problem from both an economic and environmental viewpoint. The concept used in this research was Green Productivity (GP), focused on the issues at hand. The Asian Productivity Organization (APO) in 2006 stated that GP focuses on the environment through a reduction in the rate of use of environmental resources while at the same time reducing the negative impact on the environment. GP also focuses on the economical reduction of material and energy costs used to create goods and services, thereby reducing the direct costs that ultimately have an impact on profitability. This research has two purposes; (1) mapping and analyzing green productivity of the natural rubber supply chain, and (2) formulating scenarios to increase the productivity of the NR business based on a Green Productivity approach through case studies of large-scale plantations (estates). 2. Literature study 2.1. Indonesian natural rubber supply chain Businesses in the natural rubber industry supply chain are very closely interlinked; therefore, a supply chain analysis has the potential to indicate methods of reducing the cost of NR as a commodity. Large estates are able to integrate all activities in the chain resulting in the ability to implement effective and efficient production, while small and medium estates need further improvement in order to integrate their upstream and downstream supply chain. Indonesia’s NR industry produces commodities in the form of crumb rubber (Standard Indonesian Rubber), sheet (Ribbed Smoked2 Sheet), concentrated latex3, and crepe. The need for integration between the downstream and upstream natural rubber businesses is important. The price of natural rubber is caused by several factors such as the phenomenon of the business cycle and the effect of Cobweb4 theory on rubber commodity, the dynamic changes in fundamental factors and economic shocks/policies that affect the demand and supply of the world’s natural rubber, and the emergence of non-physical market as hedging efforts of investors and speculators in the futures market exchange, especially in Singapore Commodity Exchange (SICOM), Shanghai Future Exchange (SHFE), Tokyo Commodity Exchange (TOCOM) and others. World rubber price volatility is often used by speculators to make a profit, but for rubber planters, this is often detrimental to farmers particularly when prices fall and only a momentary benefit in the event of price increases (Permadi, 2010). The natural rubber supply chain in Indonesia consists of supplier, distributor, processor, and marketer. The suppliers are smallholder farmers, private and government estates, and natural rubber importers. The smallholder supply goes through various intermediaries, usually including village, district and provincial level collectors. The larger private and government estates establish their own internal distribution. Smallholders supply over 90% of the total natural rubber supply, and it is primarily in one of the solid forms. NR processed products consist of crumb rubber of

2 Concentrated latex is an alternate downstream NR form. It is normally processed, by centrifuging the liquid latex and adding an ammonia stabilizer. 3 Part of the process necessary to produce solid forms of NR is drying. Originally drying was aided by heat of the smoke from burning wood. The term ‘smoked’ comes from that history. 4 Cobweb model is based on a time lag between supply and demand decisions. Since there is lag between planting and harvesting in agricultural markets, the Cobweb model is said to be applicable in these market.

Indonesian Standard (SIR), Ribbed Smoked Sheet (RSS), Centrifuge Latex, Crepe rubber (Brown Crepe and White Crepe) and others. The natural rubber markets comprise national market and international markets. The national market consists of local brokers and traders that supply national downstream manufacturing. The international market, on the other hand, consists of overseas brokers that supply overseas manufacturers of rubber goods. The overall NR supply chain is exhibited in Fig. 1. 2.2. Green productivity Green Productivity stems from the concept of “lean and green” concept, which is an integration of both lean and green thinking. Lean thinking was introduced in order to enhance productivity in terms of economy over the last several decades. Recently, environmental consciousness in industrial practices has received considerable attention. It has triggered the emergence of green thinking in the way firms operate in various industries. Lean and green thinking tries to minimize waste in terms of production and terms of the environment. Overlap between the two paradigms has been studied by Dues et al. (2012). The literature study concluded that the relationship between lean and green are very close. Based on the studies that have been done on companies implementing lean production system, it was found that lean could help create green supply chains. On the other hand, the application of green approaches in the production system can help production become lean. One of several lean and green initiatives is ‘Green Productivity’ that was designed by The Asian Productivity Organization. It was created following the 1992 Rio Earth Summit as both concept and strategy integrating the lean and green initiative. The definition of Green Productivity as stated by the Asian Productivity Organization (2006) is: “Green productivity (GP) is a strategy for enhancing productivity and environmental performance simultaneously to achieve overall socio-economic development. Its aim is well-rounded socio-economic development that leads to sustained improvement in the quality of human life. It is the combined application of appropriate productivity and environmental management tools, techniques and technologies that reduce the environmental impact of an organization’s activities, products and services while enhancing profitability and competitive advantage”. Although there are very few research articles on Green Productivity, it is a growing topic in the field of lean and green. Several papers explicitly mentioned Green Productivity, namely Gandhi et al. (2006), Tuttle and Heap (2008), and Hur et al. (2004). Fliedner and Majeske (2010), although they did not explicitly mention the term Green Productivity, argued that lean and green concepts intercept and supported each other in order to enhance productivity. 2.3. Green Value Stream Green Value Stream (GVS) map method was introduced by Wills (2009), which was known as the principle of green intentions with green value stream mapping, as a tool to map the seven waste generators that exist in value added systems. The GVS has its roots to the original value stream map that was first developed by operations management staff at Toyota Motor Corporation, Japan, in the late 1980s. It was originally used to identify ways to smooth the flow of material and information, improve productivity and competitiveness, and help implement the system rather.

Please cite this article in press as: Marimin, et al., Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study, Journal of Cleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.098

Marimin et al. / Journal of Cleaner Production xxx (2014) 1e11

3

Natural Rubber Importer

Provincial level collector

District level collector

Village level collector

Smallholders

SIR processing RSS processing Centrifuge Latex processing

Overseas broker

Overseas Manufacturer

Local brokers and traders

Local Manufacturers

Crepe rubber processing

Private estate Government estate Fig. 1. International rubber supply chain (Modified from Peramune and Budiman, 2007).

Value stream mapping is a tool that can be used to map the flow of value in detail to identify the waste and provide a way to eliminate or to reduce it (Nielsen, 2008). Lasa et al. (2008) suggested that value stream is a valuable tool for the redesign of productive systems according to the lean system. Three important elements associated with value stream maps are value-added activities, nonvalue added activities and activities that are important, but do not provide added value. Value-added activities are activities that truly benefit the customer. Activities that are not value-added those that add value to an activity rather than to the customers, but cannot be eliminated (Jones and Hines, 2004). Value stream map provides a visual presentation of the flow of the current process or the Current Folder displays flow cycle times and diagrams. When the activity stream is analyzed and modified, resulting in a flow chart, after elimination of the waste, for the future called future map (Hande and Ceylan, 2011). According to Hines and Taylor (2000), value stream mapping provides a real and powerful technique that can be used to identify non-value added activities in a company. Activities within the value stream that consume resources but do not contribute value should be eliminated. Although there is a similarity between a value stream and the green value stream, there are differences in the way they define waste. The value stream identifies seven sources of waste generation consisting of inventory, displacement, damage to the product, transportation, overproduction, excess margin processes, and the waiting time. On the other hand, the green value stream defines seven sources of waste generation as the excessive use of energy, water, material, waste, transport, emissions, and damage to biodiversity (Wills, 2009). Similar to the value stream map, green value stream map also has two types of mapping, current state and future state.

and dynamic to be parts and arranged in a hierarchy (Saaty and Vargas, 1994). The level of importance of each variable assigns a numerical value, the opinion of the importance of these variables and relative to the other variables. From various considerations, a synthesis is performed to define the variables that have a high priority and role in influencing the outcome of the system. AHP model is used to calculate the weight of criteria, both quantitative and qualitative in one research. Graphically, AHP decision problem can be constructed as a multilevel diagram (hierarchy). AHP begins with the focus or goal past the first level criteria, sub criteria, and finally alternative. There are various forms of hierarchies tailored to the substance of the decisions and problems that can be solved by AHP. AHP allows the user to give a relative weight of a compound criterion or multiple alternatives against the criteria. The weight was determined intuitively by doing pair wise comparisons. AHP can measure the consistency of judgment in case deviation is too far from the value of perfect consistency, which shows the hierarchy of assessment needs to be repaired or must be re-structured (Saaty and Vargas, 1994). AHP has many advantages in explaining the decision-making process, as it can be depicted graphically, making it easily understood by all parties involved in the decision making. Through the use of AHP, the complex decision process can be broken down into smaller decisions that can be handled with ease. AHP consists of four basic ideas, namely the preparation of hierarchy, criteria and alternative assessment, prioritization, and logical consistency (Marimin, 2004). Problemsolving using AHP is done using hierarchy to decompose complex systems into simpler elements. The hierarchy can consist of focus, actors, goals, and alternatives (Marimin et al., 1997; Maarif and Somamiharja, 2000).

2.4. Analytical Hierarchy Process

2.5. Research framework

The Analytical Hierarchy Process (AHP) is known for its applicability in multi-criteria decision-making. The method was developed by Saaty in the 1970s and used to solve problems by using an organized framework, so it can be expressed to take effective decisions on the issue. The use of AHP can simplify and speed up the decision making process. The fundamental principle of AHP is a simplification of a complex issue that is not structured, strategic

The research done here was based on the concept of Green Productivity using Green Value Stream Map and AHP as its core techniques. Fig. 2 shows the research framework. A literature study of the issue at hand was done in order to acquire a firm concept of the planned research. After a thorough literature study, an activity analysis of natural rubber cultivation and middle stream industries was completed. Parallel to the activity analysis, expert judgment on

Please cite this article in press as: Marimin, et al., Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study, Journal of Cleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.098

4

Marimin et al. / Journal of Cleaner Production xxx (2014) 1e11

Literature Study

Economic Indicator

Activity analysis of natural rubber upstream and first downstream industry

Expert Judgement on environment issues

Green Productivity Measures

Generate Green Productivity Indicator

Green Productivity Calculations

Environment Indicator

Current green value stream map Generate Productivity Improvement Strategy Future green value stream map Fig. 2. Research framework.

environmental issues was completed in order to generate Green Productivity Indicators. Subsequently, green productivity measures were determined as an input for Green Productivity calculations. In addition, green productivity measures, i.e. environmental indicator and economic indicator were used in the calculation. Green value stream map was constructed on the basis of activities performed and the result of the calculation. The current green value stream map was analyzed in order to generate productivity improvement strategies. The productivity improvement strategies were then used to construct a future green value stream map.

Production Cost Economic Indicator Product price

Gas waste source generator

Water consumption

Green Productivity

Environment impact

3. Research method Indonesia’s natural rubber industries have three possible sources of raw material, namely smallholders, Government Own Enterprises, and large scale private plantations (estates). In this research, in determining the common factors we considered these three sources. However, due to practical constraints, we used detailed numerical data and information provided by XYZ Co. in particular and the private estates in general. Value chain analysis consists of several activities. The process stages and required material for cultivation and production were analyzed using green value stream developed by Wills (2009). This analysis starts with the identification of seven green waste generators. Following the analysis of the activities and materials needed in the cultivation and production, the green productivity index (GPI) was calculated with formulas (1), (2), and (3). Fig. 3 shows the framework of GPI measurement. 3.1. Green productivity index Green productivity calculations were done by accumulating the results of the calculation of economic indicators and environmental indicators. Economic indicators were calculated by the ratio between the incomes earned from the sale of products and production costs to produce the product.

Solid waste source generator

Fig. 3. Green productivity index measurement (modified from Gandhi et al., 2006).

The economic indicator is the ratio between the selling price and cost of production of the same unit of one type of product. In this research, the selling price of the product in question is the selling price per liter of latex products produced from the field, while the cost of production is the cost required to produce 1 L of latex products. The calculations used in determining the value of the economic indicator are based upon the production of one tonne of latex products.

Economic Indicator ¼ Revenue=Total Cost

(2)

Furthermore, the environmental indicator is determined by the extent of environmental impact of the cultivation and production of natural rubber. Based on the methodology developed by Gandhi et al. (2006), the indicator value is determined based on three types of plant waste, i.e. gaseous wastes generation, solid wastes generation, and water consumption. The environmental impact (EI) was determined by the sum of the weights for each green productivity indicator. Green Productivity

Green Productivity Index ðGPIÞ ¼ Economic Indicator=Environmental Indicator

(1)

Please cite this article in press as: Marimin, et al., Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study, Journal of Cleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.098

Marimin et al. / Journal of Cleaner Production xxx (2014) 1e11

weights and indicators were determined by the results of the analysis and were summarized by world experts as Environmental Sustainability Index (ESI) (Esty et al., 2005). Preparation of the ESI was based upon the determination of the five types of environmental quality assessment components, which included 21 indicators of environmental sustainability and 76 variables underlying the valuation weight of each indicator. Aggregation method was used to equalize the amount of weights. The use of ESI as the basis for weighting environmental impact (EI) in this research refers to research conducted by Gandhi et al. (2006). Table 1 shows the eight important indicators in the ESI used in this research. Environmental impact was defined as the sum of environmental variable weight of GPI and derived from ESI weight.

EI ¼ w1GWG þ w2WC þ w3SWG þ w4LWG

(3)

whereas: w1, w2, w3, w4: weight of each GPI GWG : gaseous wastes generation SWG : solid wastes generation WC : water consumption LWG : land wastes generation Therefore, the weights of each GPI indicator for natural rubber cultivation were, w1 ¼ 0.375, w2 ¼ 0.25, w3 ¼ 0.125, and w4¼ 0.25 and the environmental impact of natural rubber cultivation was formulated as:

EI ¼ 0:375GWG þ 0:25WC þ 0:125SWG þ 0:25LWG

(4)

Whereas, the Environmental impact for natural rubber processing were:

EI ¼ 0:17 SWG þ 0:5 GWG þ 0:33 WC

(5)

3.2. Generating improvement strategies 1. Systems Approach The systems approach was accomplished by identifying all of the factors contained in the system to obtain a good solution for resolving the problem, and then creating a model of AHP to help rational decisions. The AHP structure consists of five levels; namely, focus, factors, actors, goals and alternatives. The AHP structure of productivity improvement was gained through expert interviews, namely, opinions of three experts and an expert in the production of natural rubber. 2. Determination of Respondents In accordance with the approach adopted in this research, the respondents were determined by expert selection techniques. In this case, the experts selected were those in the field of natural rubber cultivation, from academia, bureaucracy and practitioners. The experts involved in this research were three people, consisting of corporate culture experts, experts from the Institute for Estate Crops Research Nusantara (RPN), and a professor who was an expert on natural rubber cultivation. The application of the AHP requires a consistency test of expert opinion; therefore, a Consistency Ratio Test (CR Test) was completed. 3. Improvement scenario selection method The method used in this research is the Analytical Hierarchy Process (AHP), a technique that can be used in the decision making process. Decision-making was carried out through preparation

5

Table 1 Indicators’ weight in ESI 2005 (Esty et al., 2005). Equality of ESI indicator

Weight in ESI

Quality of air Greenhouse emission Decrease in air pollution level Water quality Water consumption Decrease in solid and material consumption Biodiversity Land area

0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05

hierarchy, which according to Saaty and Vargas (1994) described the structure of the system in which the function hierarchy between components and the impact on the overall system can be studied. Pictures or illustrations in Analytic Hierarchy Process were interrelated, ranging from goals, incentives, business, strategy or method to do. AHP was used in this research because the system being studied was complex and unstructured. Designing scenarios repairs were done on the basis of the results of the analysis and identification of solutions to existing problems. The scenarios were drawn up and problem solutions were obtained through AHP analysis and literature review. 4. Current Green Value Stream and GPI Based on the observation conducted, natural rubber cultivation was classified into six process activities i.e. nursery related activities, plants maintenance, harvesting, filtering, and shipping to designated factories. The plants were classified into two categories, namely immature non-producing plants and mature producing plants. Immature non-producing plants are rubber plants ranging from 0 to 5 years of age while mature productive plants are plants in their productive stage that can be harvested, ranging from 5 to 30 years old. Harvesting activities were conducted every day, starting from five to eight o’clock in the morning. Subsequently, the process of collecting latex began at ten in the morning. All latex tapped was collected in a collecting depot at eleven. In the process of collecting latex, collectors usually add one drop of ammonia on each tapping bowl to prevent latex clotting. The screening process was carried out in the collecting depot along with the casting process of the bucket into the tank. Filtering aims to filter out various impurities, such as twigs, leaves, or lump (clotted latex). At the time of screening, typically, the amount of dirt filtered reached two or three pounds for each depot. Latex delivery was done in latex tanks mounted on trucks. Each truck transported the results from the depot to the factory. Elimination of natural rubber cultivation process was undertaken to eliminate “unnecessary” cultivation activity due to its little or no impact on the overall natural rubber cultivation. Based on the analysis of the overall activities, filtering was considered as eliminable from the entire rubber cultivation. The main reason was that the filtering activities only produced waste in the form of large latex pollutants, such as twigs, leaves, or lump. Overall waste is basically a type of organic waste that can be tolerated by the environment, thus eliminating these activities will not affect the analysis of the waste to the entire process of cultivation of natural rubber. The seven sources of green waste per activity for the upstream activities and production process of RSS (Ribbed Smoked Sheet), and BC (Brown Crepe) are shown respectively in Table 2, Table 3, and Table 4. The upstream activities of the chain consisted of nursery, maintenance of non-productive plants (NPP Maintenance), and maintenance of productive plants (PP maintenance), harvesting, sorting and shipping.

Please cite this article in press as: Marimin, et al., Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study, Journal of Cleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.098

6

Marimin et al. / Journal of Cleaner Production xxx (2014) 1e11

Table 2 Green waste identification for upstream activities. Waste type

Process activities

Energy (Kwh) Water (m3) Material (kg) Garbage (kg) Transportation (km) Emission Biodiversity (ha)

Nursery

NPP maintenance

PP maintenance

Harvest

Sorting

Shipping

Total

1830 900 1245 0 0 1631 194

0 0 28,075 0 0 0 763

0 0 40,531 0 0 0 1759

0 0 0 14,400 0 0 0.02

0 0 0 3000 0 0 0.01

0 0 0 0 2700 1426 0

1830 900 69,851 14,400 2769 3094 2715

Table 3 Seven green wastes identification of RSS. Waste type

Process activities (per production) Raw material receiving

Dilution and coagulation

Milling

Smoking

Sorting

Packaging

Total

Energy (kWh) Water (liter) Material (kg) Garbage (kg) Transportation (km) Emission (tonnes CO2/day) Biodiversity (Ha)

3.33 e e e e 2.97  10-3 e

200.00 8549.71 45.00 e e 0.71 e

170.00 7000.00 e e e 0.76 e

e e

e e e e e e e

50.00 e e e e 0.27 e

423.33 15,549.71 45.00 652.00 e 1.89 e

0.00 652.00 e 0.15 e

Source: XYZ Co. (2012).

The company mainly produces two types of product, the Ribbed Smoked Sheet and Brown Crepe. The RSS production consists of six activities, i.e. raw material receiving, dilution and coagulation, milling, smoking, sorting and packing. Table 3 exhibits the activities of RSS, seven green wastes generated, and their amounts. The BC production process consists of four activities, which are sorting and receiving, milling, drying and sorting. Similarly, Table 4 exhibits the activities of BC, seven green wastes generated, and the waste amounts generated. Calculation of Green Productivity Index for the upstream resulted in a figure of 1.956, based on an environmental indicator of 0.6714 and economic indicator of 1.3132. These figures show that the economic indicator was higher than the environmental indicator. The upstream process has a higher GPI compared to the downstream processing of the chain, which means the green productivity is higher compared to the downstream processing of natural rubber in the chain. The value indicated that the level of productivity was still higher than the environmental impact resulting from the activities performed. When the company achieves higher green productivity index values, the level of economic productivity and indicators of enterprise would be higher, while the environmental impact of the company’s activity would be lower.

9

Table 4 Seven sources of green wastes identification of BC. Waste type

Energy (kWh) Water (liter) Material (kg) Garbage (kg) Transportation (km) Emission (tonnes CO2/day) Biodiversity (Ha) Source: XYZ Co. (2012).

Conversely, the lower the index value of green productivity, the greater the environmental impact of the process activities in the company. The GPI of upstream and overall downstream processes of RSS and BC were compared and illustrated in Fig. 4.The upstream GPI indicated to be the highest compared to the RSS and BC production processes. In the upstream side of the chain, the environmental indicator suggested low environmental impact, and moderate economic indicator compared to the RSS and BC. Conversely, the RSS production process has the lowest GPI compared to the other two and the highest environmental indicator. Therefore, it is argued that the high environmental indicator of RSS production has hindered the achievement of green productivity. In terms of GPI in the production process, RSS was significantly smaller compared to BC, which means that BC was higher in green productivity. Based on Fig. 4, the environmental impact was higher than the economic indicator significantly which means the environmental impact exceeded its economic value added. Based on the histogram, RSS had a substantially high environmental indicator value, as much as 7.672, while its economic indicator was 2.063. The Green Value Stream of natural rubber cultivation and Ribbed Smoked Sheet production are exhibited in Fig. 5 and Fig. 6. The

8

Process activities (per production)

7

Sorting and receiving

Milling

Drying

Sorting

Total

90.00 4000.00 e e e

148.20 6080.00 e e e

e e e e e

e e e e e

238.20 10,080.00 e e e

e

0.66

e

e

0.74

e

e

e

e

e

6 V a 5 l u 4 e 3

Environmental indicator Economic Indicator Current GPI

2 1 0 Upstream

RSS

BC

Fig. 4. Economic and environmental indicators and GP index for upstream and production processes.

Please cite this article in press as: Marimin, et al., Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study, Journal of Cleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.098

Marimin et al. / Journal of Cleaner Production xxx (2014) 1e11

7

ADMIN & SUPPORT Latex Production Average: 428,557 Liter/month

XYZ Company

Seed demand 1 million seeds/year SEED SUPPLIER

Transport : 69.17 km

Energy

: 1,830 KWh

Water

: 900 m

Materials

: 131,836 kg

Garbage

: 147,334 kg

PROCESSING PLANT

Shipping

Transportation : 2,769.17 km

Transport : 2,700 km

Emission : 37 kg Emission

: 3,094.3 kg

Nursery

Maintenance NPP

Maintenance PP

Harvest

Sorting

(0-1 years)

(1-5 years)

(6-30 years)

(everyday)

(everyday)

Energy

: 1,830 KWh

Energy

3

Water

: 900 m

Water

: 0 KWh :0m

Energy

3

: 0 KWh

Water

:0m

Energy

3

: 0 KWh

Water

:0m

3

Energy

: 0 KWh

Water

: 0 m3

Materials : 2,358.6kg

Materials : 53,670.5 kg

Materials : 75,806.6 kg

Materials : 0 kg

Materials : 0 kg

Garbage

Garbage

Garbage

Garbage

Garbage

: 334 kg

: 0 kg

: 0 kg

: 144,000 kg

: 3,000 kg

Transportation : 0 km

Transportation : 0 km

Transportation : 0 km

Transportation : 0 km

Transportation : 0 km

Emission : 1,631 kg

Emission : 0 kg

Emission : 0 kg

Emission : 0 kg

Emission : 0 kg

Fig. 5. Green Value Stream of natural rubber cultivation.

ADMIN & SUPPORT XYZ Company

Latex needs information Average 14,285.23 Liter/Day

PROCESSING PLANT

Every Day 14,285.23 Liter/Day

Transport. : Emission : -

Demand 120 Tonnes/month

Energy

: 12,699.9Kwh/Month

Water

:388.742 m3/Month

Materials

:1,125 liter/Month

Garbage

:19.56 tonnes/month

Transportation

:-

CUSTOMER

Transport. : Emission : -

Emission

:1.8876 tonnes CO2/Day

Biodiversity

:-

2x/Month Energy

(Daily)

Raw Materials Receiving (Latex) (daily) C/T : 1 hour C/O :0 Energy

: 3.33 Kwh

Water

: 0 Liter

Materials

:0

Garbage

: 0 Kg

Transportation: 0 Km Emission

: 2.967 x 10

Tonn CO2/Day Biodiversity : -

C/T C/O

: 4 hour : 1 hour

C/T C/O

Energy

: 170 Kwh

Energy

: 0 Kwh

Water

: 7,000 Liter

Water

: 0 Liter

Materials

:0

Materials

:0

: 0 Kg

Garbage

: 0.652 Ton

Energy

: 200 Kwh

Water

: 8,549.71 Liter

Materials

: 45 Liter

Garbage

Garbage

: 0 Kg

Transportation: 0 Km

Transportation: 0 Km

Emission

Emission

CO /Day

CO /Day

: 0.7128 Ton

(daily) : 120 hour : 2 hour

(daily) : 5 hour : 2 hour

C/T C/O

:

0.7573

Biodiversity : -Energy KWh

Sorting Station

Smoking Station

Milling Station

Dilution and Coagulation (daily)

Transportation: 0 Km Ton

Emission

:

0.1473 ton

NO , SO :0

Biodiversity : -

(daily) C/T C/O

: 6 hour : 1 hour

Energy

: 0 Kwh

Water

Packing and inventory (daily) C/T C/O

: 6 hour : 1 hour

Energy

: 50 Kwh

Water

: 0 Liter

: 0 Liter

Materials

:0

Materials

:0

Garbage

: 0 Kg

Garbage

: 0 Kg

Transportation: 0 Km

Transportation: 0 Km

Emission

Emission

CO /Day

:-

: 0,2673 Ton

Biodiversity: -

Fig. 6. Green value stream of ribbed smoke sheet production.

Please cite this article in press as: Marimin, et al., Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study, Journal of Cleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.098

8

Marimin et al. / Journal of Cleaner Production xxx (2014) 1e11

Based on the alternative selected, 9 scenarios were then constructed in order to implement the alternative. Next, the GPI of the nine scenarios was calculated in order to obtain the best GPI value. The nine scenarios and GPI value are shown in Table 5. The best GPI obtained was 3.69 for scenario 9, which was the combination of the best strategy with scenario 8.

4.500 4.000 3.500 3.000 2.500 Current GPI

2.000

4.2. Natural rubber production process improvement strategy

Future GPI Alternative

1.500

Productivity improvement strategy was obtained from the development of selected strategy based on the AHP. AHP structure for strategy alternatives to increase productivity of the natural rubber production process is presented in Fig. 9. The alternatives weighted by experts were (1) production process optimization, (2) raw material control, (3) raw material substitution, and (4) water re-use. Based on expert opinion aggregation, the selected alternative strategy for increasing productivity in the production of natural rubber in the company was the use of water (reuse). The use of water (reuse) was considered the most likely to be applied in order to increase the green productivity of the production process in the company. Through the reduction of water consumption in the production, not only is natural rubber production cost able to be reduced but also the environmental impact of the production of natural rubber can be reduced.

1.000 0.500 0.000 Cultivation

Ribbed Smoked Brown Crepe Sheet

Fig. 7. Comparison of current and future alternative GPI.

seven green wastes are illustrated in every step of the process, in the cultivation and the RSS production process. In the cultivation of natural rubber, the total amount of seven green wastes generated, namely energy, water, materials, garbage, transportation and biodiversity were 1830 KWh, 900 m3, 131836 kg, 147334 kg, 2769.17 km, 3094.3 kg and 0, respectively, while the RSS production has shown a different figure of seven green wastes generated: 12699.9 KWh/month energy, 388.742 m3/month water, 1125 L/month materials, 19.56 tonnes/month garbage, 0 transportation, 1.8876 tonnes CO2/day emissions and 0 biodiversity.

4.3. Future green value stream map Based on the calculation of GPI for cultivation and process shown in Fig. 7, it is argued that there is a significant difference in the GPI between the current and future scenario. A sharp difference between current and future alternative was 1.956e3.960. It is argued that the implementation of future scenario could increase GPI by 2 digits. Similar result exhibited that for RSS and BC, reuse of water could increase GPI for both production lines. Based on the comparison of current and future state GPI for the cultivation of natural rubber as well as natural rubber processingRSS and BC it is argued that the scenario based on Green Productivity improvement strategy is indeed able to increase Green Productivity. Based on the future scenario, future green value stream map was constructed for natural rubber cultivation and production

4. Generating green productivity improvement strategies 4.1. Cultivation improvement strategy A productivity improvement scenario was obtained from the development of selected strategy based on the AHP. The AHP structure for strategy alternative to increase productivity of natural rubber cultivation is presented in Fig. 8. The selected alternative was semi-intensification and replacing low producing plants with new ones with a weight value of 0.290 compared to other alternatives. Alternative strategy was selected based on expert opinion.

Productivity Improvement Strategy Selection of Natural Rubber Process based on GP

Focus

(1.000)

Factor

Actor

Goal

Alternative

Production facility and Infrastructure (0.039)

Planters and actors competence (0.222)

Government (0.081)

Plantation optimum utilization (0.139)

Ministry of agriculture (0.095)

Increase latex output (0.473)

Reuse of wastes from cultivation process (0.252)

Plants Nursery and Maintenance (0.258)

Company management (0.326)

Plantation head (0.215)

Environmental impact reduction (0.263)

Substitute a portion of Chemical pesticide usage with Vegetable pesticide (0.177)

Technology Mastery and application (0.135)

Transportation and Communication (0.039)

Substitute a portion of Chemical with Organic and Green fertilizers (0.281)

Planters group (0.204)

Government Policy (0.032)

Universities and research institution (0.079)

Increase company profit (0.264)

Semi-intensify and replace Low producing plants with new ones (0.290)

Fig. 8. AHP structure for productivity improvement in natural rubber cultivation.

Please cite this article in press as: Marimin, et al., Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study, Journal of Cleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.098

Marimin et al. / Journal of Cleaner Production xxx (2014) 1e11

9

Table 5 Alternative design of scenario for improvement strategy. Scenario

Description

Environmental indicator

Economic indicator

GPI

1 2 3 4

Usage of degraded polybag and lump use Substitution of some pesticides with green pesticide Substitute 50% fertilizer with green fertilizer Usage of degraded polybag and lump use and Substitution of some pesticide with green pesticide Usage of degraded polybag and lump use and Substitute 50% fertilizer with green fertilizer Substitution of some pesticide with green pesticide and substitute 50% fertilizer with green fertilizer Implement combination of the first three combination Semi intensify and replanting of low producing plants Combination of the best strategy with scenario 8

0.63 0.73 0.63 0.69

1.31 1.27 1.64 1.27

2.07 1.74 2.58 1.83

0.59

1.63

2.74

0.69

1.58

2.27

0.66 0.56 0.49

1.57 1.58 1.95

2.39 2.83 3.96

5 6 7 8 9

process for RSS and BC. The future green value stream map of natural rubber cultivation and RSS production process are illustrated in Fig. 10 and Fig. 11. 5. Conclusions and recommendations 5.1. Conclusions It is concluded that the amount of the seven sources of green wastes were 1.830 KWh of energy, 900 m3 water consumption, 131.836 kg supporting material; 147.334 kg garbage; 2769.17 km transportation; 3094.3 kg emissions; and 2715.45 ha biodiversity. The result of the GPI calculation was 1.956. The increase in the cultivation of natural rubber favors the scenario of combined strategy of the use of degradable polybag, lump utilization and substitution of 50% with the use of fertilizer and biological fertilizer application and replanting activities of semi-intensive production plants. The chosen scenario increased the productivity of the cultivation process as much as two-digit index from 1.96 to 3.96. Furthermore, based on the chosen scenario, a future green value stream map was constructed with seven green waste profile as 1.830 KWh of energy consumption, water

consumption of 900 m3; supporting material as much as 69.851 kg; 14.400 kg garbage; 2769.17 km transportation; 3094.3 kg emissions; 2715.45 ha biodiversity. Green productivity level conditions early in the production process of RSS and BC were 0.269 and 1.089 respectively, due to the suboptimal use of resources, primarily water consumption. The use of a large amount of water can lead to discharge of liquid waste in large amount. Therefore, four alternative strategies were chosen based on the opinions of experts in the field of natural rubber; they are: (1) the optimization of the production process, (2) the control characteristics of raw materials, (3) auxiliary materials substitution, and (4) re-use of water (reuse) as the best strategy. Application of the selected scenario improved Green Productivity for the production of RSS to 0.690 and increased the productivity of green to brown crepe to 3.889. The implemented scenario could increase the GPI of RSS and BC from 0.269 to 1.148 and from 2.565 to 3.571, respectively. 5.2. Recommendations Further research is needed on the analysis of application scenario and the material characteristics of the existing strategies for

Productivity Improvement Strategy Selection of Natural Rubber Cultivation in based on GP

Focus

(1.000)

Factor

Actor

Demand Level (0.056)

Executive Officers (0.256)

Government (0.161)

Maximize profit (0.731)

Goal

Alternative

Raw and Supporting Materials Characteristics (0.326)

Production process optimization (0.309)

Raw Material Control (0.213)

HR competence (0.287)

Selling price (0.106)

Production Cost (0.137)

Universities and Research Institution (0.070)

Environmental Related Government Policy (0.088)

Downstream industry (0.512)

Minimize Environmental Impact (0.269)

Raw material substitution (0.111)

Water reuse (0.366)

Fig. 9. AHP structure for productivity improvement in natural rubber processing.

Please cite this article in press as: Marimin, et al., Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study, Journal of Cleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.098

10

Marimin et al. / Journal of Cleaner Production xxx (2014) 1e11

ADMIN & SUPPORT

Latex production Average: 428,557 liter/month

Seed needed 1 million/year

SEED SUPPLIER

Energy : 1,830 KWh Water : 900 m3 Materials : 69,851 kg Garbage : 14,400 kg Transportation : 2,769.17 km Emisi : 3,094.3 kg Biodiversity : 2,715.45 Ha

Transport : 69.17 km

PROCESSING PLANT

Shipping Transport : 2,700 km

Emission : 37 kg

Emission : 1,426.30 kg

Nursery

NPP maintenance

PP maintenance

Harvesting

Sorting Station

(0-1 year)

(1-5 years)

(6-30 years)

(daily)

(daily)

Energy

: 1,830 KWh

Energy

: 0 KWh

Energy

: 0 KWh

Energy

: 0 KWh

Energy

: 0 KWh

Water

: 900 m

Water

:0m

Water

:0m

Water

:0m

Water

:0m

Materials : 1,244.85kg

Materials : 28,074.85 kg

Materials : 40,531.3 kg

Materials : 0 kg

Materials : 0 kg

Garbage

Garbage

Garbage

Garbage

Garbage

: 0 kg

: 0 kg

: 0 kg

: 14,400 kg

: 3,000 kg

Transportation : 0 km

Transportation : 0 km

Transportation : 0 km

Transportation : 0 km

Transportation : 0 km

Emission : 1,631 kg

Emission: 0 kg

Emission : 0 kg

Emission: 0 kg

Emission: 0 kg

Fig. 10. Green value stream map of RSS natural rubber cultivation.

ADMIN & SUPPORT XYZ Company

Latex demand Average 14,285.23 Liter/Day

PROCESSING PLANT

Transport. : Emission : -

Demand 120 Tonnes/Month

Energy

: 12,699.9Kwh/Month

Water

: 388.742 m /Month

Materials

: 1,125 Liter/Month

Garbage

:19.56 tonnes/month

CUSTOMER

Transport. : Emissions : -

Transport. :Emission :1.8876 Tonnes CO /Day Biodiversity:

Receiving St (Latex) (daily) C/T : 1 hour C/O : 0 hour

C/T C/O

Energy

: 3.33 Kwh

Water

: 0 Liter

Dilution and Coagulation station (daily)

Smoking station

Milling station (daily) : 5 hour : 2 hour

C/T C/O

(daily) : 120 hour : 2 hour

Sorting Station C/T C/O

(daily) : 6 hour : 1 hour

Packing and Inventory Station (daily) C/T C/O

: 6 hour : 1 hour

: 4 hour : 1 hour

C/T C/O

Energy

: 200 Kwh

Energy

: 12.143 Kwh

Energy

: 0 Kwh

Energy

: 0 Kwh

Energy

: 50 Kwh

Water

: 8,549.71 Liter

Water

: 500 Liter

Water

: 0 Liter

Water

: 0 Liter

Water

: 0 Liter

Materials : 0

Materials : 45 Liter

Materials : 0

Materials : 0

Materials : 0

Materials : 0

Garbage

Garbage

Garbage

Garbage

Garbage

Garbage

: 0 Kg

: 0 Kg

: 0 Kg

Transportation: 0 Km

Transportation: 0 Km

Transportation: 0 Km

Emission : 2.967 x 10 Ton CO /Day

Emission : 0.7128 Ton

Emission:

CO /Day

CO /Day

0.054

Ton

: 0.652 Ton

: 0 Kg

: 0 Kg

Transportation: 0 Km

Transportation: 0 Km

Transportation: 0 Km

Emission : 0.1473 ton

Emission : -

Emission : 0,2673 Ton

NO , SO

Biodiversity : -

CO /Day

Fig. 11. Green value stream map of RSS production process.

Please cite this article in press as: Marimin, et al., Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study, Journal of Cleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.098

Marimin et al. / Journal of Cleaner Production xxx (2014) 1e11

increasing awareness of any environmental impact caused by the use of materials. There is also a need for the implementation of farm management activities in order to minimize environmental impact, and an integrated measurement system that can measure the level of productivity of the farming activities as well as natural rubber production process, so that the improvement can be identified and simulated better, organized, and sustainable in practice. Furthermore, a detailed case study should also be done in government-owned rubber enteprises as well as in the smallholder rubber enteprises, and the results compared accordingly. Acknowledgments The research leading to this publication was partly funded by Directorate General of Higher Education, Ministry of Education and Culture, Republic of Indonesia, under National Strategic Research Grant fiscal year 2012 and 2013. The authors would like also to convey their appreciation to the editors and anonymous reviewers for their valuable comments and suggestions, and to the key persons of companies and institutions who provided data and information for the case study in this analysis. References Arifin, B.A., 2005. Supply chain of natural rubber in Indonesia. J. Manaj. Agribisnis 2 (1), 1e16. Asian Productivity Organization [APO], 2006. Handbook on Green Productivity. Asian Productivity Organization. Basyaruddin, D., 2009. Development policy of natural rubber seed industry (In Indonesian). In: Prosiding Lokakarya Nasional Pemuliaan Tanaman Karet, Batam, August 2009. Pusat Penelitian Karet Lembaga Riset Perkebunan Indonesia, Bogor, pp. 6e14. Boerhendhy, I., Nancy, C., Amypalupy, K., August 2009. Development strategy of superior grade rubber clone (In Indonesian). In: Prosiding Lokakarya Nasional Pemuliaan Tanaman Karet, Batam. Pusat Penelitian Karet Lembaga Riset Perkebunan Indonesia, Bogor, pp. 157e167. Damardjati, D.S., Jacob, J., 2009. Present trends and outlook for global supply of natural rubber (In Indonesian). In: Prosiding Lokakarya Nasional Pemuliaan Tanaman Karet, Batam, August 2009. Pusat Penelitian Karet Lembaga Riset Perkebunan Indonesia, Bogor, pp. 18e30. Dues, C.M., Kim, H.T., Lim, M., 2013. Green as the new lean: how to use lean practices as a catalyst to greening your supply chain. J. Clean. Prod. 40 (February), 93e100. Esty, Daniel C., Levy, Marc, Srebotnjak, Tanja, Sherbinin, Alexander de, 2005. Environmental Sustainability Index: Benchmarking National Environmental Stewardship. Yale Center for Environmental Law & Policy, New Haven. Fliedner, G., Majeske, K., 2010. Sustainability: the new lean frontier. Prod. Inventory Manag. J. 46 (1), 6e13. Gandhi, M., Selladurai, V., Santhi, P., 2006. Green productivity indexing: a practical step towards integrating environmental protection into corporate performance. Int. J. Prod. Perform. Manag. 55 (7), 594e606. Hande, A., Ceylan, C., 2011. Value chain analysis using value stream mapping: white good industry application. J. Ind. Eng. Manag. 12 (9), 852e857.

11

Hickling, P.D., Munthe, M., Hasibuan, S.E., 2009. Evaluation of clone variability in PT bridgestone sumatra rubber estate (In Indonesian). In: Prosiding Lokakarya Nasional Pemuliaan Tanaman Karet, Batam, August 2009. Pusat Penelitian Karet Lembaga Riset Perkebunan Indonesia, Bogor, pp. 118e122. Hines, P., Taylor, D., 2000. Going Lean. Lean Enterprise Research Center. Cardiff Business School, UK. Hur, T., Kim, I., Yamamoto, R., 2004. Measurement of green productivity and its improvement. J. Clean. Prod. 12 (7), 673e683. Jones, D.T., Hines, P., 2004. Lean logistics. Int. J. Phys. Distrib. Logist. Manag. 12 (4), 235e246. Lasa, I.S., Laburu, C.O., Vila, R.C., 2008. An evaluation of the value stream mapping tool. Bus. Process Manag. J. 14 (1), 39e52. Maarif, M.S., Somamiharja, A., 2000. Productivity improvement strategy (In Indonesian). J. Ilmu-ilmu Pertan. Indones. 9 (2), 62e76. Marimin, Umano, M., Hatono, I., Tamura, H., 1997. Non-numeric method for pairwise fuzzy group decision analysi. J. Intell. Fuzzy Syst. 5 (3), 257e269. Marimin, 2004. Teknik dan Aplikasi Pengambilan Keputusan Kriteria Majemuk (Technique and Application of Multi-criteria Decision Making). PT. Gramedia Widiasarana Indonesia, Jakarta. Ministry of Agriculture The Republic of Indonesia, 2012. Technical Manual for Rubber Post-harvest Activities Improvement (Pedoman Teknis Kegiatan Peningkatan Penanganan Pascapanen Tanaman Karet) (Jakarta. Indonesia). Mohammadi, M., Man, H.C., Hassan, M.A., Yee, P.L., 2011. Treatment of wastewater from rubber industry in Malaysia. Afr. J. Biotechnol. 9 (38), 6233e6243. Muluk, C., 2009. Micro-cutting technology development for propagation and planting material in PTP Nusantara III (In Indonesian). In: Prosiding Lokakarya Nasional Pemuliaan Tanaman Karet. Batam, August 2009. Pusat Penelitian Karet Lembaga Riset Perkebunan Indonesia, Bogor, pp. 350e355. Nielsen, A., 2008. Getting Started with Value Stream Mapping. Gardiner Nielsen Associates Inc. Nugroho, P., Istianto, P., 2009. Natural rubber estate land preparation requirement. In: Prosiding Lokakarya Nasional Pemuliaan Tanaman Karet, Batam, August 2009. Pusat Penelitian Karet Lembaga Riset Perkebunan Indonesia, Bogor, pp. 139e149 (in Indonesian). Peramune, M.R., Budiman, A.F.S., 2007. A Value Chain Assesment of the Rubber Industry in Indonesia. USAID Project. Permadi, G., 2010. Slow expansion. Hevea 2 (1), 14e16. Permadi, P., Ginting, E., 2009. Evaluation of rubber clone variability in PT. Socfin Indonesia (In Indonesian). In: Prosiding Lokakarya Nasional Pemuliaan Tanaman Karet, Batam, August 2009. Pusat Penelitian Karet Lembaga Riset Perkebunan Indonesia, Bogor, pp. 110e117. Rao, P., 2000. Exploring environmental management systems and their impact in Southeast Asia. Asia Pac. J. Econ. Bus. 4 (2), 74e113. Saaty, T.L., Vargas, L.G., 1994. Decision Making in Economic, Political, Social and Technological Environments: the Analytic Hierarchy Process, vol. VII. RWS Publications, Pittsburg, PA, USA. Singh, R., Kumar, S., Sharma, S., 2011. Assessment of toxicity of chemicals in workers or rubber industry. J. Pharm. Res. 4 (9), 3229e3231. Sundiandi, Sihombing, J.H., Siagian, N., Karyudi, 2009. Efforts to accelerate preproductive rubber plant in PTP Nusantara III (In Indonesian). In: Prosiding Lokakarya Nasional Pemuliaan Tanaman Karet, Batam, August 2009. Pusat Penelitian Karet Lembaga Riset Perkebunan Indonesia, Bogor, pp. 123e138. Tekasakul, P., Tekasakul, S., 2006. Environmental problems related to natural rubber production in Thailand. J. Aerosol. Res. 21 (2), 121e129. Tuttle, T., Heap, J., 2008. Green productivity: moving the agenda. Int. J. Prod. Perform. Manag. 57 (1), 93e106. Wills, B., 2009. Green Intentions: Creating a Green Value Stream to Compete and Win. Productivity Press, New York. Zachariah, O., Patrick, M., 2011. The value chain of rubber wood industry in Kerala: relative share of various actors. Asia Pac. J. Res. Bus. Manag. 2 (6), 77e86.

Please cite this article in press as: Marimin, et al., Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study, Journal of Cleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.098