FIELD OF THE INVENTION:
The present invention relates to the environment related problems.
More particularly, this invention relates to providing solutions for solving environment pollution.
The present invention relates to examine the measurement model of GSCM practices implementation focusing on its 14 underlying factors and a measurement scale for it. This invention focuses on Indian SMEs, the diversity of organizations (Industry, Number of employee, and Sales Turnover).
OBJECTS OF THE INVENTION:
The main objective of this invention is to investigate the Green Supply Chain Management (GSCM) practices implementation construct and its defining measurement items emphasizing Indian manufacturers with broader implications for application of these scales to other environments (e.g., invention in other countries and further development of environmental and supply chain invention).
Another objective of this invention is to assess the supply chain and environmental management in the small & medium size Indian manufacturing industries.
DETAILED DESCRIPTION OF THE INVENTION:
This invention provides insight into methods, tools and techniques employed for gathering information and analyzing the result for the empirical section of this work. Green-supply chain management has emerged as a proactive approach for improving an environmental performance of products. Various approaches for implementing green supply chain management practices has been proposed and recognized in a number of literatures. Very few investigations have identified the reliability and validity of such approaches particularly in SMEs of India. Management/ Industrialist did begin to realize the importance of the environment, but they have not addressed. Management/Industrialists also have not sufficient knowledge how to start to protect environment through the green supply chain management. The purpose of this invention is to find out the approaches to green supply chain and to create a model that can assist manufacturers in procurement decisions while committing to the environmental objectives. In order to achieve this objective, the supply
3
chain should be fully examined as a whole, and effective methods to evaluate the whole chain should be explored and further proposed.
➢ What is the difference between the traditional supply chain and the environmentally conscious/green supply chain?
➢ What is the current situation?
➢ How can the environmental issue be considered in the traditional supply chain? In other words, what is green supply chain?
➢ How the situation changes will occur after the environment becomes a factor in the traditional supply chain?
➢ How was this extended supply chain to be evaluated under the new circumstances?
➢ “How to design, develop, and evaluate an environmentally conscious/ green supply chain” is still untouched?
All these questions are the promoters that initiated to do this invention. It is the intention to find out how to implement and green the supply chain and to build up a simple model for further studies. As a result of invention, the change of the supply chain which comes from the environmental pressure should be demonstrated. From this, more about the relationships between the phases of the system and how they affect each other can be known. Compared with the traditional supply chain invention, there is a need to evaluate the supply chain not only from an economic perspective but also from environmental perspective. How to make green to the most important phase in the supply will be simply modeled and an example will be provided to show the basic procedure for solving this problem.
In this chapter, the methods, techniques and procedures that were employed the process of implementing the invention design (invention plan) are discussed in detail.
Here, invention strategy, invention design and sampling plan are described. Additionally, the data collection technique for the study is discussed in terms of respective methodologies for inventing Green supply chain management dimensions and its environmental approaches. The analysis of data is discussed in terms of coding and capturing of data, the methods of measurement and the explanation of the statistical methods. The quality of data is discussed in terms of its validity and reliability, the manner in which the data indicated through selection of industries. For any invention, hypothesis design is an important aspect for the methodologies. Hence on the basis of tools and techniques, objectives, the hypothesis is designed and is tested according to its assumptions in the relevant chapters.
4
INVENTION FRAMEWORKS
For meeting the objective of study, survey-based invention was carried out.
Fig 1 illustrates invention framework carried out for Green supply chain management practices. There are main thirteen steps for this invention.
1. Reviewing the already published national and international papers in various reputed journals are reviewed.
2. Developing a survey instrument based on the previously reviewed literature and a series of extensive interviews with different stakeholders/managers/supervisors of the Small and Medium industry of different types supplemented by plant.
3. Revising the questionnaire further to refine and clarify the constructs and items.
4. Framing a preliminary questionnaire on the basis of review considering all the objectives and the present study.
5. Conducting a pilot study on SMEs of different types of manufacturing industries.
6. Testing the reliability value of each statement had been tested by applying Cronbach’s reliability coefficient and making further amendments to the pilot questionnaire, in terms of wording and the sequence of questionnaire.
7. Retaining the 105 dimensions out of 118 dimensions whose coefficient value was more than 0.6.
8. Designing the final questionnaire by classifying into two segments with different objectives as to the industry profile and respondent profile through questionnaire by keeping the instrument for Green Supply Chain Management practices.
9. Using a 5-point Likert scale for getting the information of the dimensions with the survey instrument being a set of 105 dimensions already given to the industries for providing the data required for analysis.
10. Then focusing on comparative analysis of mean score of the various green supply chain parameters on the basis of types of industry, employee size and sales turnover by employing the methods, techniques and procedures in the process of testing various hypothesis pertaining to green supply chain parameters to find out most significant factors and attributes in both small scale and medium enterprises.
11. Explaining various parameters of Factor Analysis such as Reliability, Validity, Communalities, Eigen value, loading and Variance along with the detailed extracted factors and green supply chain effective Strategies corresponding to each factor, developing Green Supply Chain model.
5
12. Examining the impact of various green supply chain factors on green supply chain effectiveness in both SME by Multiple Regression Analysis.
13. Developing the Supply Chain Operation Reference (SCOR) Board for Green Supply Chain.
The questionnaire/survey instrument (appendix 1) consists of total 14 factors with 105 underlying dimensions (questions/statements/item).
Figure 1: Invention framework carried out by the inventor
The invention starts with an abstract idea, followed by a measurement procedure, and ends with empirical data (precise numerical information), capable of being analyzed by statistical
Step 1: Designing Questionnaire
Step 2: Pilot Study
Step 3: Designing Final Questionnaire
Step 4: Data Collection
Step 5: Comparative analysis of GSCM factors in Small and medium industry, employees, sales turn over, type of industry
Step 6: Factor Analysis
- Cronbach’s Alpha
- KMO
- Determine Dimensions
- Component Matrix
- Rotated Component Matrix
- Communalities
Step 7: Green supply chain model developed
Step 8: Multiple Regression Analysis (MRA) & Hypothesis Testing
Step 9: SCOR Board for Green Supply Chain
On the basis of GSCM practices
Checking Consistency
Checking missing entries
6
methods or other computational methods, representing the abstract ideas. Therefore, quantitative invention is highly formalized and explicitly controlled, with a range that is exactly defined and that is relatively close to the physical sciences.
The questionnaire was tested on respondents having characteristics similar to those of the target group of respondents. Only after the necessary modifications concerning the usage of language and the sequence of questions made, the questionnaire was presented to the full sample of respondents. The responses are collected through a questionnaire survey containing 105 Quality dimensions (questions/statements/item) relevant to an industry. The survey data thus collected are analyzed through factor analysis and other statistical tests in order to get a robust instrument.
A total number of 199 questionnaires were collected between October 2010 and Feb 2011. After checking the consistency, only 119 respondent data were selected. A total of 48 questionnaires were filled incomplete and 32 questionnaires were wrongly entered. Finally, 119 respondents have been used in the invention framing. Therefore, the sample size of the study is 119.
The constraint of this study limited it to one interview per respondent at a specific point in time. It would be of value to conduct a series of interviews over a period of time.
The present inventioncan becarriedin any place for any type of industry.
Examples:
A convenience sampling technique was employed but sample industries were selected on the basis of pre-specified criteria mentioned. The sampling strategy called for soliciting the participation of 119 industries with greater than 34 employees; distributed multiple areas, and with the types of organization as: Textile, Chemical, Rubber/Plastic, Fabrication, Machinery, Electrical, Electronics, Automotive, and Pharmaceutical, Steel/Iron, Food, Fire Fighting and other.
Although testing for differencesbetween strata was not the goal of the study, this approach provided a broad range of plants for the purposes of testing the reliability and validity of the instrument.Characteristics of the sample are provided in tables further in description.
Responses were scored from 1 to 5, with a value of 1 indicating “Below average” and a value of 5 indicating “Excellent”. Reverse-worded items were reverse scored, so that a value of 1 indicated “Below average” and a value of 5 indicated “Excellent”, permitting rationalinterpretation of scale scores. In every case, a higher scale score indicated the use
7
of better qualitymanagement practices. Some open end questions such as eco label products and environment level performance measurement systems were asked.
The procedure adopted for the development of scale;
• A definition of the construct and generation of statement for inclusion in an item pool
• Selection of type of scaling to be used
• Item analysis of the preliminary scale
• Reliability testing of the scale and
• Validity of the final scale
Based on review of studies, the invention had prepared 118 dimensions. The invention had arrived at set of 105 dimensions after eliminating the redundant items by submitting the dimensions to respondents and discussing with experts, who were believed to have knowledge of the subject for fair judgment. A large number of dimensions were necessary to measure the construct respondent perception of green supply chain factor, Likert scales were used for measuring the attitudes of the respondent for each dimension. Thetarget respondents of the survey were requested to indicate, using a five-point Likertscale to the extent to which they perceived their companies implementing each of the dimensions of GSCM practices.
1 – below average,
2 – average,
3 – good,
4 – very good,
5 – excellent.
The respondent’s score on each dimension were summed together to measure his or her perception toward Green Supply Chain performance.
In general, the empirical study of green supply chain factors on various industries employ a survey methodology was adopted. The purposive sampling method is used to collect the data which belong to 119 Small and Medium enterprises. Data is collected using questionnaire format where the description of critical incident forms is the basis for coding the responses. The critical incidence technique requires respondent to recall a specific service experience that they remember clearly. Even though memory decay may be potential source of bias in respondents responses, retrospective measurement are regularly employed. During the collection of data, the time limitation is also an important aspect for measuring. During the collection of data, a memory recall technique was also used.
8
All the 105dimensions found in the preliminary inventory were given to conveniently selected industries of 119 respondents who hailed from different organizations. The summated dimension scores in respect of all the respondents were ordered from highest to lowest for this preliminary scale. Dimension analysis was conducted for each of the 105 dimensions between the highest and lowest group through a t-test. Based on the results, 105 dimensions were found significantly differentiating the two groups and thus were retained for the reliability analysis.
The reliability of the scale was examined through already well-known three reliability tests: Split-half reliability test, Gutman’s Formula and Cronbach’s Coefficients.
The two are used to measure the internal consistency of the items and, one is used to measure the temporal stability of the scale.
The split-half reliability test was conducted to estimate the scale’s internal consistency at a single point of time. This method estimates the equivalence that would exist if the subjects were administered to different scales to measure the same construct to form 2 different sets. By computing the correlation coefficient for these two scores for all the respondents the split-half reliability is established. Respondents for this analysis were respondents from 119 industries who were administered 105 dimensions. A split-half reliability using Gutmann’s formula yielded the reliability coefficient, which is quite satisfactory. Cronbach’s alpha was then calculated for each dimension. The permissible alpha values can be 0.60. A criterion α value of 0.60 was used. After the calculation of Cronbach’s α, three possibilities existed. First; the dimension was accepted without any changes if it had a strong α value (0.70) with consistent item/dimension inter correlation values. Second; dimensions with acceptable but not high, α values were further analyzed to determine whether alpha could be improved by the removal of some items/dimensions. The dimension inter-correlation matrix served as a guide in determining which dimension contributed least and, thus, were the best respondent’s opinion for deletion. If their removal did not significantly alter the content of the scale, the relevant items were eliminated. Third; a similar elimination analysis was performed on the scales which failed to achieve the minimum criterion alpha value. If the scale still failed to achieve the criterion after elimination of items/dimensions with lower item/dimension inter correlations, the entire scale was discarded.
The main drawback of this split-half method of examining the internal consistency of the scale is that the different coefficient are obtained depending upon how the items are split thereby making difficult to determine the real reliability coefficient. The Cronbach’s coefficient α overcomes the weakness and is the most popular method of estimating scale’s reliability coefficient.
9
Once the reliability of the scales had been established, several approaches to establishing validity were followed. These dealt with content validity, construct validity and criterion-related validity.
The statistical methods have been employed to find out whether the Green Supply Chain factors have any significant impact on the basis of types of industries (small and medium), no. of employees, sales turnover, and classification of industries (steel, automotive, chemical etc.).
For this, competitive mean score with its‘t’ value having 5% significant level has been used. Descriptive Analysis and Multiple Regression Modelhas been applied for the study. In Descriptive Analysis, mean score has been measured and for testing of hypothesis, Levene’s F-value has been taken. For measuring the impact of service attributes on overall satisfaction, Regression Model is used separately for small, medium and pooled (Small and Medium) industries step by step. Emphasis is on validating the best model from the models extracted through R2, Adj R2 and ANOVA. For testing the null hypothesis, t-values of specific attributes have been analyzed.
For analysis of Green Supply Chain model the inventor had employed certain statistical tools and techniques. These techniques had certain assumptions and by reviewing all the assumptions, the inventor had selected suitable techniques such as Factor Analysis for studying the dimensions of Green Supply Chain factors, Comparing Mean Score of Green Supply Chain factors and dimensions and its t-value for Green Supply Chain model, Regression Analysis for testing most important dimension of Green Supply Chain factors for small, medium and pooled (Small and Medium) industries. ANOVA was used to analyze the association between categorically independent variable and respective continuous dependent variable. Chi-square test was used to test the significance for nominal data.
The 5% level of significance is used throughout, which means that the probability of wrongly rejecting the null hypothesis should be less than 5%. The p-value was used to decide whether to accept or reject the statistical hypothesis.
Green Supply Chain models are developed and tested on the basis of the factors and on the basis of attributes in the factor.
Green supply chain management, also known as ESCM (environmental supply chain management) or SSCM (sustainable supply chain management), combines green purchasing, green manufacturing/materials management, green distribution/marketing and reverse logistics. All stages of a product’s life cycle will influence a supply chain’s
10
environment burden, from resource extraction, to manufacturing, use and reuse, final recycling, or disposal. Beyond this definition with adding the “green (eco)” component, it refers to green supply chain management which is defined as “eco-resources, eco-design, eco-purchasing, eco-production, and eco-logistics”. “Green Supply Chain Management includes material sourcing and selection, product design, manufacturing processes, delivery of the final product to the consumers, and end-of-life management of the product after its useful life”.
Green supply chain management (GSCM) involves traditional supply chain management practices, which integrate environmental criteria, into organizational purchasing decision and long-term relationships with suppliers.
The purpose of GSCM is to eliminate or minimize waste (energy, emissions, chemical hazardous, solid wastes) along supply chain. Current strategy in supply chain management is based on the balance between cost and customer service. In a competitive market cost, differentiation or a combination of cost and differentiation can be taken as a basic strategy in a firm. In supply chain management, cost strategy is seeking internal cost efficiency, and differentiation strategy is to improve the customer service and design better products /services to meet customers’ needs. In a green manufacturing environment, a process can use certain renewable materials, the ability to utilize reusable or remanufactured materials, and the reduction of wastes. An environmentally friendly innovation is best implemented during the manufacturing stage of the supply chain, as this part is the most internally focused and the organization can judge the benefits of implementing environmentally friendly processes. A green supply chains aims at confining the wastes within the industrial system in order to conserve energy and prevent the dissipationof dangerous materials into the environment. It recognizes the disproportionate environmental impact of supply chain processes within an organization.
Reverse logistic (RL) plays an important role in achieving ‘‘green supply chains’’ by providing customers with the opportunity to return the warranted and/or defective products to the manufacturer. The aim of green supply chain is mainly confining the wastes within the industrial system in order to conserve energy and prevent the dissipation of dangerous materials into the environment. It identifies the disproportionate environmental impact of supply chain processes within an organization. Reverse logistics is the process of planning, implementing and controlling the effective inbound flow and storage of secondary goods and related information for the purpose of recovering value. Reverse logistics is defined as “all issues related to logistics activities carried out in source reduction, recycling, substitution,
11
reuse of materials, and disposal". Reverse Logistics present a new challenge to companies: To retrieve all possible goods and waste materials, affecting the economic value which still remains in the goods returned. The values of economic returns already exist in real supply chains (goods, packaging, etc.). Therefore the question arises of how to manage them. This in turn necessitates the change from Reverse Logistics towards Reverse supply chains, at all levels (strategic, tactical and operative) with the involvement of all companies of the forward supply chain. This approach revolutionizes the working patterns because it leads to a process of revision of chain operations, with a special emphasis on the final consumer as the stigma needed to re-design the Forward Supply Chain (FSC) and the Reverse Supply Chain (RSC). Reverse distribution can be channelized through the original forward channel, through a separate reverse channel, or through combinations of forward and reverse channel. Due to scarcity of the equipment reverse product movement cannot be controlled by logistics systems. Transportation, storage and handling of returned goods have different characteristics compared to outgoing goods both in terms of complexity and cost of required operations.
In a green manufacturing environment, the supply chain decisions include the possibility that a process can use certain renewable materials, the ability to utilize reusable or remanufactured materials, and the reduction of wastes. In some cases, an environmentally friendly innovation is best utilized during the manufacturing stage of the supply chain, as this part is the most internally focused and the organization can more directly predict the benefits of implementing environmentally friendly processes. Greening the supply chain is the process of incorporating environmental criteria into organizational purchasing decisions and long-term relationships with suppliers. There are three approaches involved to Green Supply Chain (GSC): environment, strategy and logistics. Working with GSC means to work in the interface of those areas because the GSC is totally related to environmental protection.
For further development of supply chains for recyclable and recycled materials, it will be necessary to get better recycling technologies, to allow recyclable materials to be reprocessed into recycled materials of adequate quality that they can compete with virgin materials. With increasing customers’ demand for environmentally products, enterprises and manufacturers of final products are exerting pressure on their suppliers to increase their environmental standards. The enterprises and manufacturers have been trying to develop products that are energy efficient, less toxic and less hazardous to the
12
environment. The concept of Green Supply Chain has been introduced and manufacturers are changing product designs to be greener and environment friendly.
It is a well-known fact that pollution in the environment has been increasing continuously thereby causing adverse effect on environment, society, industries etc. It has been felt necessary to control the pollution by introducing Green Supply Chain Management. The Green Supply Chain Managementwill help in reducing the pollution and negative environmental effect. This chapter explains the industry profile under study and also focuses on comparative analysis of mean score of the various green supply chain parameters on the basis of types of industry, employee size and sales turnover. In this chapter the methods, techniques and procedures that were employed in the process of testing various hypothesis pertaining to green supply chain parameters are discussed which leads to find out the most significant factors and attributes in both small scale and medium enterprises.
Exhaustive survey of various invention papers on Green Supply Chain Management was carried. Industries were also visited before carrying the survey. Based upon industrial visits, it was analyzed that these 14 factors may be responsible for effective implementation of Green Supply Chain Management. The questionnaire was prepared on the basis of these factors.
Table 1 explains about the comparative analysis of the effect of green supply chain factors on the basis of type of industry. As 14 supply chain factors have been considered in the study,each factor has its own importance for effective green supply chain performance. 119 industries as a whole out of which 60 (50.42%) from small scale industry & 59 (49.58%) from medium scale industry in the diversified areas have been taken.
As per the literature review andexperts view, Likert scale (1-5) has been used inthe questionnaire, where 1 – below average, 2 – average, 3 – good, 4 – very good, 5 – excellent. Each scale signifies how these factors in the industry are effective for green supply chain factors. The competitive ‘mean’ score with ‘t’ value has been calculatedby taking null (0) hypothesis that no significant differences of green supply chain factors on the basis of type of industry. An alternate hypothesis that there are significant differences of green supply chain factors on the basis of type of industry.
Here ‘p’ is the probability of acceptance (The p-value is a numericalmeasure of the statistical significance of a hypothesis test. It tells how likely it is thatsample data have responded even if the null hypothesis is true. By convention, if thep-value is less than 0.05, it is concluded that the null hypothesis can be rejected).
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Examples:
The following examples and data are for the purposes of illustration only and therefore should not be construed to limit the scope of the invention:
SAMPLE SURVEY CONDUCTED AND RESULTS FOR GREEN SUPPLY CHAIN FOR INDIAN ENTERPRISES
Please rate the degree or extent of practice for each variable on 1 to 5 scale where:
(1-Below average, 2-Avearge, 3-Good, 4-Very good, 5-Excellent)
Table: 1
1. ECO-PROCUREMENT
i
Provides design specification to suppliers that include environmental requirements for purchased item
1
2
3
4
5
ii
Co-operation with suppliers for environmental purchasing
1
2
3
4
5
iii
Existence of cell for environmental audit for suppliers internal management
1
2
3
4
5
iv
Procurements mainly from ISO14000 certified suppliers
1
2
3
4
5
v
Second-tier supplier’s environmentally friendly practice evaluation
1
2
3
4
5
vii
Implementation of eco-labeling/eco-logo of products
1
2
3
4
5
vii
Work with other business functions to discuss and improve purchasing procedures.
1
2
3
4
5
viii
Provision of education/assistance to suppliers on environmental matters in order to increase supply chain efficiency.
1
2
3
4
5
ix
Communication regarding environmental procurement criteria/requirements to marketing staff, employees, stakeholders, and customers
1
2
3
4
5
x
Co-operation with customers for environmental packaging
1
2
3
4
5
2. ECO-ACCOUNTING
i
Environmental costs associated with operations and processes (e.g. monitoring and abatement equipment, waste disposal etc.) are taken care
1
2
3
4
5
ii
Accounting the costs to the customers associated with the use and disposal of the products
1
2
3
4
5
iii
Communication of environmental costs to customers and within the industry in key business functions
1
2
3
4
5
14
iv
Assisting in evaluation of environmental cost with respect to capital purchases and new technology
1
2
3
4
5
v
Generate activity based costing in various department or business function
1
2
3
4
5
3. ECO-LOGISTICS DESIGN
i
Reverse logistics applied in stock planning
1
2
3
4
5
ii
Application of environmental issues in the design of logistics management
1
2
3
4
5
iii
Identification, Collection & distribution of products/parts that will be recycled, reused
1
2
3
4
5
iv
Recollection planning for packaging material
1
2
3
4
5
v
Minimizing the use of packaging considered
1
2
3
4
5
4. ECO-PRODUCT DESIGN
i
Design of products for optimum consumption of material/energy
1
2
3
4
5
ii
Product designed for reuse, recycle, recovery of material, components parts
1
2
3
4
5
iii
Design consideration of products to avoid or reduce use of hazardous of products
1
2
3
4
5
iv
Design of products to reduce waste & costs
1
2
3
4
5
v
Products are design & develop meet environmental regulation and safety standards
1
2
3
4
5
vi
Co-operation & feedback with customer in developing eco-design
1
2
3
4
5
vii
Products are design & developed for ease in dismantling & remanufacturing
1
2
3
4
5
viii
Application of value engineering/analysis in the design of products
1
2
3
4
5
ix
Evaluation of product durability
1
2
3
4
5
x
Possibility of eliminating secondary processes (polishing/painting etc.) considered.
1
2
3
4
5
15
5. ECO-MANUFACTURING
i
Possibility of product being recyclable, reusable
1
2
3
4
5
ii
Avoid or minimize the amount of hazardous material used in product production
1
2
3
4
5
iii
Are designers using life cycle engineering to improve the environmental performance and production efficiency of the products
1
2
3
4
5
iv
Measures taken to reduce material, water & energy used in manufacturing
1
2
3
4
5
v
Optimizing the use of energy generated from renewable sources in manufacturing operations
1
2
3
4
5
vi
Inclusion of recycling program for manufacturing operation
1
2
3
4
5
vii
Industry has established program to increase the service intensity of the products
1
2
3
4
5
viii
Determination of environmental impacts and costs of the products throughout their life-cycle
1
2
3
4
5
ix
Minimizing toxic/hazardous waste during manufacturing
1
2
3
4
5
x
Optimum energy consumption during manufacturing process
1
2
3
4
5
xi
Integrated environmental & efficiency criteria implementation in process design
1
2
3
4
5
xii
Minimizing use of natural resources during manufacturing is considered
1
2
3
4
5
xiii
Consideration of environmental issue in the process of production planning and control
1
2
3
4
5
xiv
Environmental issue considered during selection of manufacturing process
1
2
3
4
5
xv
Reduced setup time
1
2
3
4
5
6. MARKETING &AWARENESS
i
Assisting customers to improve their environmental performance
1
2
3
4
5
ii
Environmental requirement and activities of customer
1
2
3
4
5
16
concern are monitored
iii
Awareness regarding environmental information to new and existing employees
1
2
3
4
5
iv
Departmental interaction and exchange of information regarding environment, performance, efficiency etc.
1
2
3
4
5
v
Use of environmental information during product marketing & communications material
1
2
3
4
5
7. ECONOMIC PERFORMANCE
i
Waste discharge methodology for reducing cost
1
2
3
4
5
ii
Reduction in cost for materials purchasing without affecting the quality of the product
1
2
3
4
5
iii
Reduction in cost of energy consumption
1
2
3
4
5
iv
Effective waste treatment management for reducing cost
1
2
3
4
5
v
Reduction of the fine for environmental accidents
1
2
3
4
5
8. ENVIRONMENTAL PERFORMANCE
i
Minimization of air emission
1
2
3
4
5
ii
Minimization of solid waste
1
2
3
4
5
iii
Improve production procedure/method for reducing waste/scrap
1
2
3
4
5
iv
Recovery through sale of scrap and used/rejected material
1
2
3
4
5
v
Recovery through sale of excess capital equipment
1
2
3
4
5
vi
Recovery through sale of old/obsolete equipment
1
2
3
4
5
vii
Recycling of waste water
1
2
3
4
5
viii
Optimization of man power resources in production process
1
2
3
4
5
ix
Reduction of consumption for hazardous materials
1
2
3
4
5
x
Reduction in frequency of environmental accidents
1
2
3
4
5
9. CUSTOMER CO-OPERATION
i
Co-operation from customers for eco-design
1
2
3
4
5
17
ii
Co-operation from customers for cleaner production
1
2
3
4
5
iii
Co-operation from customers for green packaging
1
2
3
4
5
iv
Co-operation from customers for using less energy during product transportation
1
2
3
4
5
v
Co-operation with customers for environmental procurement
1
2
3
4
5
10. HUMAN AND TECHNOLOGICAL RESOURCES
i
Improvement in worker safety
1
2
3
4
5
ii
Motivate workers for environmental consciousness
1
2
3
4
5
iii
Increase supervisor training
1
2
3
4
5
iv
Use of energy efficient technologies
1
2
3
4
5
v
Consultation with environmental experts before using new technology
1
2
3
4
5
11. INTERNAL ENVIRONMENTAL MANAGEMENT PERFORMANCE
i
Promotion of quality circles
1
2
3
4
5
ii
Existence of environmental and auditing program
1
2
3
4
5
iii
Provision of training in environmental management
1
2
3
4
5
iv
Implementation of ISO 14001 certification
1
2
3
4
5
v
Commitment of green supply chain management policy by senior managers
1
2
3
4
5
vi
Awareness about the green supply chain management measures adopted by the competitors
1
2
3
4
5
vii
Existence of total quality environmental management
1
2
3
4
5
viii
Updating the current and proposed environmental regulations and legislation that may impact on business
1
2
3
4
5
ix
Existence of policy related to green supply chain management linking environmental, economic, process performances
1
2
3
4
5
x
Support for green supply chain management from junior & middle level managers/executive
1
2
3
4
5
18
12. OPERATIONAL PERFORMANCE
i
Reduced inventory level
1
2
3
4
5
ii
Reduction in scrap
1
2
3
4
5
iii
Promote environmental quality products
1
2
3
4
5
iv
Optimization of capacity utilization
1
2
3
4
5
v
Amount of goods delivered on time
1
2
3
4
5
vi
Monitoring the environmental and implementation for the improvement within industry
1
2
3
4
5
vii
Program to promote and track the reduction of waste
1
2
3
4
5
viii
Waste management program for compliance with all applicable regulations
1
2
3
4
5
ix
Selection and use of energy efficient equipments and fixture for electrical, mechanical and lighting application
1
2
3
4
5
x
Development of a prevention program to identify and eliminate sources of pollution
1
2
3
4
5
13. STAKEHOLDERS
i
Consideration & application of environmental issues because of regulatory concerns
1
2
3
4
5
ii
Consideration & application of environmental issues because of suppliers
1
2
3
4
5
iii
Consideration & application of environmental issues because of trade organizations
1
2
3
4
5
iv
Consideration & application of environmental issues because of employee concerns
1
2
3
4
5
v
Consideration & application of environmental issue because of customer & market pressure
1
2
3
4
5
14. VENDOR MANAGEMENT
i
Environmental performance is an important criteria in vendor selection
1
2
3
4
5
ii
Environmental awareness among the vendors
1
2
3
4
5
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iii
Environmental certified vendor is considered
1
2
3
4
5
iv
Environmental issues are regularly shared by vendors.
1
2
3
4
5
v
Feedback on environmental issues for the product supplied.
1
2
3
4
5
DETERMINANTS OF GREEN SUPPLY CHAIN FOR INDIAN SMEs
Factor 1: Internal Eco Environmental and Management Performance
Factor 2: Eco Design and Manufacturing
Factor 3: Operational Performance
Factor 4: Customer Cooperation
Factor 5: Environmental Quality Regulations
Factor 6: Waste Management
Factor 7: Scrap Reduction
Factor 8: Reverse Logistics
Factor 9: Eco Labelling
Factor 10: Packaging Design
Factor 11: Environmental Awareness
Factor 12: Application of Environmental Issues
Factor 13: Environmental Audit Cell
Factor 14: Green Packaging
GREEN SCOR AND EFFECTIVENESS
The calculation for green SCOR helps to find effectiveness of Green Supply Chain in industry and to identify the industry which has maximum impact and lowest impact according to their effectiveness. This step helps to improve the performance in future.
Green SCOR and effectiveness of small scale industries
The calculation for green SCOR effectiveness of small scale industries is as:
Where Li=Loading
Si=Dimension/Statement
n1= No. of small scale industries
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Green SCOR and effectiveness of medium scale industries
Where Li=Loading
Si=Dimension/Statement
n2= No. of medium scale industries
The invention highlights various green supply chain parameters and extracts of the factors from these parameters through Factor Analysis and tests their relative significance through Multiple Regression Analysis. This analysis investigates into the impact factors of both small and medium scale enterprises. Thisinvention also recognizes the consistency in the approaches and consequently provides their rankings. It also assesses the relative importance of identified approaches that would affect the GSCM implementation. The measurement scales are verified with the above-mentioned parameters and can be used as a self – diagnostic tool to identify areas where specific improvements are needed. It also can pinpoint the aspects of the manufacturers regarding the implementation of GSCM practices. Different organizations can make use of the model in accordance with their specific situations and requirements. Moreover, the model also can empower the managers to improve their understanding of GSCM practices and enables the decision makers to audit the perception of GSCM at different levels of their organization.

I Claim:
1. An innovative technique to improve environmental performance and reducing pollution, by only modifying the approach so that existing green supply chain managements are better established and recognized such that the technique provides tools to identify the reliability and validity of such approaches for any kind of industry and to create a model to assist manufacturers for environmental protection.
2. The innovative technique as claimed in claim 1, wherein said technique comprises steps to differentiate between the traditional supply chain and the environmentally conscious/green supply chain.
3. The innovative technique as claimed in claim 1, wherein said technique comprises the steps of:
a. Reviewing the already published national and international papers in various reputed journals;
b. Developing a survey instrument based on the previously reviewed literature and a series of extensive interviews with different stakeholders/managers/supervisors of industries;
c. Revising the questionnaire further to refine and clarify the constructs and items;
d. Framing a preliminary questionnaire on the basis of review considering all the objectives;
e. Conducting a pilot study on different types of manufacturing industries;
f. Testing the reliability value of each statement had been tested by applying already known Cronbach’s reliability coefficient and making further amendments to the pilot questionnaire, in terms of wording and the sequence of questionnaire;
g. Retaining the dimensions with coefficient value more than 0.6;
h. Designing the final questionnaire by classifying into two segments with different objectives as to the industry profile and respondent profile;
i. Using a 5-point Likert scale for getting the information of the dimensions with the survey instrument with dimensions already given to the industries for providing the data required for analysis;
j. focusing on comparative analysis of mean score of the various green supply chain parameters on the basis of types of industry, employee size and sales turnover by employing the methods, techniques and procedures in the process of testing various hypothesis to find out most significant factors and attributes;
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k. examining the impact of various green supply chain factors on green supply chain effectiveness by already known Multiple Regression Analysis;
l. Finally developing the Supply Chain Operation Reference (SCOR) Board for Green Supply Chain to provide the best possible practice way.
4. The innovative technique as claimed in claim 1, wherein said technique comprises preferably total 14 factors with 105 underlying dimensions (questions/statements/item).
5. An innovative technique to improve environmental performance and reducing pollution.