Investigating Responsiveness of Reverse Logistics for Manufacturing Industries

: Reverse Logistics is support in moving goods from consumer to a facility where re-capturing of value of the End of Life goods is possible. This can be achieved by product recovery management. The recovered material can be reused as raw material in manufacturing giving an edge of cost competitiveness. Besides this, Reverse logistics also mitigates problem of pollution, cheaper raw material, value for waste and making return policy easy in on-line shopping. This paper aims to investigate the responsiveness of reverse logistics using AHP in maintaining cost, product recovery management, environment, customer satisfaction citing examples of major manufacturing sector. The paper highlights the importance of responsiveness of reverse logistics to make it more responsible towards environment and making reverse logistics as a profitable venture. The study also provides roadmap to top management in furnishing their social responsibility to take care of End of Life goods produced from their firms as the human being no more be as wasteful and insensitive towards his surroundings. The best implication of RL may ease the problem of electronics and plastics waste disposal, pollution of land, air and aquatics and vanishing of precious rare metals from the earth.


Introduction and Literature Support
Reverse Logistics (RL) has been defined by Council of Logistics Management as the process of efficient planning and controlling of reverse flow of goods from the point of consumption to the point of origin of the product.RL is a research about the management of the recovery of products once they are no longer desired by the consumers, in order to obtain an economic value from the recovered products.Kusi-Sarpong et al. (2015) pointed out that human being can be no longer wasteful in present scenario, therefore, RL is helping in getting much out of the waste.This helps in recapturing value from returned goods and in preservation of environment (Rubio & Para, 2014).It has now become imperative to realize the importance of utilization of End of Life (EOL) products.Many products made of plastics and metals e.g., mobile phones, computer items and other electronic gadgets are either thrown away or kept lying at consumers end for very long time (Pathak & Srivastava, 2017).These waste products not only create environmental hazards but also result in wastage of important and rare materials which are diminutive in nature.Kusi-Sarpong et al. (2015) reported that as our planet's resources are depleting at faster rate than ever due to huge draining of raw material from it, the scarcity of supply of such raw material has been encountered in many industries.Best example of this is the of shortage of semi-conductors in recent times due to which automobile, computer, mobile phones and electronics industries are facing huge production challenges.Secondly, facilities of return/exchange in e-shopping have increased many folds and shipping back in minimum time to the originator is required to maximize the turnaround time.Alnoor et al. (2019) reported that return of electronics goods sold online requires robust and responsive reverse supply chain to satisfy and assure the customer of the company commitments.This will also give a competitive advantage by retaining customers for longer time.Rubio, et al. (2008), described RL as planned backward flows of EOL goods.Similarly, Mangla et al. (2016), Ramazani et al. (2013), Livio et al. (2021) reported RL is a planned activity which emphasize economic, environmental and social needs for sustainable business.
Industries have started a take-back programme in their supply chains through which some incentives are offered to retailers to collect and return the used products to the manufacturer.Kazemi et al. (2019) have cited the example of Dell which started a take-back programme in 2014 of used products.The company recovered 10% of the plastic as raw material and used them in manufacturing processes of new product and meeting the challenge of cost competitiveness.Another example of using plastic waste from oceans to develop their new line of shoes 'Parley' on a global level by Adidas and reducing enormous carbon foot print.Such initiative not only served the cost cut of raw material but saved the aquatic pollution also.Giri et al., (2017) suggested that EOL of electronics goods such as DVDs, batteries, mobiles, camera, projectors, photocopiers, printers, LEDs and fluorescent lighting etc. can be collected for retrieval of useful rare materials using third-party logistics and e-tail channel.Rubio & Para, (2014) have mentioned remanufacturing, environmental concern, depleting reserve of raw materials, economic recovery from waste and corporate social responsibility (CSR) as main factors of RL.But, timeliness of RL is very important for smooth running of remanufacturing, refurbishment and canalization firms.For this the support team at the back end should be responsive and prompt so that the collected EOL goods are taken care to reach at the proper destination.Prajapati, et al. (2021) has cited Responsiveness of RL (RRL) for Implementation of effective RL.Ramezani et al. (2013) have reported the RRL as quickness of logistics to collect, transport and do required processes on the retuned goods to get competitive advantage in business.RRL depends upon factors such as cost involved in return process, environmental effects, product recovery management, customers' response, return policy of the company, government policies and social awareness.Sukati, et al. (2014) have explained Competitive advantage due to RL by optimized Product Recovery .To understand, how effectively RL is being taken by industries as a venture, a case study of three major sectors of manufacturing firms of India has been explored.After consultation with experts from academia and industries, the three major sectors, where RL can be a major game changer have been considered.These three sectors are automotive, electronics and Paper & Plastics sectors, of which large volume of products are sold in market.The quantities of EOL of these sectors are voluminous as well hazardous and urgently need attentions of policy makers.Recently Government of India has announced scrap policy (2021) based on life of the vehicles.This is again a boost to RL.
Therefore, this paper explores the RRL of three major sectors of manufacturing i.e.Automotive, Electronics and Paper & Plastic industries using Analytical Hierarchal Process (AHP), a Multi-criteria Decision-Making (MCDM) approach Saaty (1980).Also, the developing countries like; India, China, Taiwan, Korea etc. are becoming hub of manufacturing of these three sectors.Usefulness of RL has been felt in these sectors, as EOL of the products are increasing enormously.Therefore, strategic management is required to handle wastes into resourceful manner.Also, while choosing the manufacturing sectors two things are taken into consideration i) It should cover vast area of manufacturing sector and ii) possible gain from operation of RL.The three industries are meeting our requirement; where as other industries can also be considered for better understanding of RRL.Therefore, this study can be generalized with some addition or deletion in enablers of RL.
After keen study of several articles in the field of RL, it has been seen that most of the papers have mentioned to measure the performance of RL and none to explore responsiveness of RL.This paper is aimed to explore RL in terms of Responsiveness of revere logistics (RRL), which is unique in nature.The study can be applied in any other industries to compare the readiness and benefits gained through the RL.Therefore, the main objectives of this paper are three folds.
1. To identify the factors affecting RRL 2. To explore RRL and its benefits in some Indian industries.3. To discuss the managerial implications of this research work and suggest directions for future research

Enablers of RRL
Singh, (2015) described Responsiveness of Reverse Logistics (RRL) is promptness of reverse supply chain or reverse flow of material.This will depend upon promptness to collect, transport, processes and making ready for reuse of the flowed material/goods.Daaboul et al. (2014) suggested that cost effectiveness, product recovery management, global environmental pressure, customer's (returnee) cooperation and return policy are important enablers of RRL.Discussing about the main enablers of RL Mangla et al. ( 2016) have mentioned environmental, customer awareness, economical gains and attractive return policy.Kazemi et al. (2019) have reviewed of reverse logistics and outline the important factors as; development of facility of remanufacturing, rewarding end customer for readily disposing of EOL goods, long term impact of RL etc. Jack, et al. (2010), highlighted the need of economical transportation and warehousing in RL.Gurita et al. (2018) have stressed upon the development of remanufacturing facilities of e-waste to use benefits of RL.
However, Wang et al. (2021) pointed out an uncertainty factor in Responsiveness of RL.It is quite possible that the quality, duration, accident, strike, traffic jam, relationship etc. are important in deciding the RRL.But, Lee & Dang, (2009) suggest that it is impossible to capture every single uncertainty in the RL as nature of reverse flow of material may differ even though the uncertainty influences decision making.The uncertainty due to changing technology and market mood are taken care with prior planning.This study has been carried in ideal conditions, where uncertainty factors have been taken care by proper planning; Implementing advanced tracking systems and real-time monitoring.Also, the study of RL is mainly focusing the area of reuse, remanufacture and recycle out of the collected waste and not the online shopping, where uncertainty of return of items are very high.Therefore, we have not considered uncertainty factor as enabler of RRL.
Finally on the basis of exhaustive literature reviews and consultations with the experts from industries and academia, following five enablers are outlined, mentioned in section in Table 1.The table enlists the enablers and sub-enablers of RRL along with the researcher citations.

Methodology
This paper uses AHP to find out the best performing manufacturing sector in respect of responsiveness of the reverse logistics.
Initially important enablers and sub-enablers are selected from the available literature.The final selections of the enablers are done in consultation of the experts.A hierarchy model of the RRL enablers, sub-enablers and industries are prepared.Expertbased Decision Matrices (DM's) have been prepared for enablers and sub-enablers of RRL.

Analysis of Responsiveness of RL using AHP
RRL based on comparative performance of enablers in three industries are illustrated here.Those enablers are; 'cost effectiveness, product recovery management, environmental consideration, customer's impact and return policy,' for relative performance AHP has been used.The three industries are selected arbitrary, seeing the most vulnerable area, where applying Reverse logistics will be profitable venture.For example (1) Automotive (AM) (2) Electronics (EL) and (3) Paper & Plastic industries (PP) are chosen keeping in view of high return from even scraps of these products (Luthra et.al. 2017).Most of the parts can be recovered from the waste of automotive equipment's similarly; electronics and plastics waste disposal in efficient way is need of the world to reduce continued deteriorations of land, water and air (Tosarkani & Amin 2018).Also, recovering of paper from the waste is making high sense, as it saves lot of deforestation as well is key to its survival and growth.Secondly these three sectors are very vast and can be generalized for any kind of industries using RL.It is also made clear here that any other industries can be compared using our present study, however minor chances to vary the enablers and sub-enablers are not avoided.
Of course, using AHP is an old Multi-Criteria Decision Analysis (MCDA) but is very easy and logical to apply.The AHP is not only using the text opinion, but also uses numeric values of each opinion.In this study, we have used Likert scale (1-9) for giving relative advantage of the enablers and sub-enablers while comparing.Ishizaka and Nemery (2013) opined the main goal of MCDM is not to suggest the best decision, but to aid the decision makers in selecting shortlisted alternatives in line with their preferences.The methodology is quite suitable and simple to meet the objective of this study.

RL in Automotive industries:
Luthra, et al. ( 2017) has reported that RL plays a significant role in automobile industry in the salvage of parts and retrieval of useful materials from EOL vehicles.These parts/materials can be used in remanufacturing of the automobile parts/components.Society of Indian Automobile Manufacturers Association (SIAM) in its report claims to recover 1.5 million tons of steel scrap, 180,000 tons of aluminum scrap and 75,000 tons of recoverable plastic and rubber from scrapped automobile.Ravi (2014), have reported that recovered materials can be used to cater the demand of automotive parts.Some of the automotive components such as engines, alternators, starters and transmissions mechanisms may be reused after some refurbishment.Of course reuse of such components needs to be tested for its worthiness.RL helps to collect and continuous supply of EOL vehicles to the refurbishment/ manufacturing center.To maintain the continuous supply a quick collection and transportation of these EOL goods is urgently required.Reuse, refurbishment and recovery of material is a great step towards low carbon production system.

RL in Electronics industries:
The need to use EOL of electronics goods in any form is urgently required reported by Poppelaars et al. (2020).The RRL in EL industries are needed as quick lifecycle for these high velocity products and evolving technology.It is being sensed by the companies that RL will become a more defined competitive advantage for entities that can reclaim lost revenues quickly in EL industries.E-waste is posing threat to the environment and quick attention is urgently needed, which gives an edge to companies to develop RRL chains.

RL in Paper & Plastics industries:
Plastic and papers are quickly recyclable and gives competitive advantage in usage of packaging, toys, automotive parts, computers etc. Plastics is being used in civil constructions like making of roads mainly by recycling of plastic carry bags, disposable cups, medical plastic waste, water bottle etc.This is helping in reduction of use of cement and other constructional materials.RL is playing very important role in collecting and fetching the used papers and plastic waste to the remanufacturing center.The raw materials for the Paper are already in a critical state.Pati et al. (2004);, reported increase of paper industries by 8% per annum.But, there is a shortage of the basic raw material, wood pulp used in making paper reported by Ravi and Shankar (2006).Similar shortage can be seen in raw plastic raw materials.This leads to a big gap between the supply and demand; this could be minimized by recycling of the post-consumer waste paper (PCW).The reuse of EOL goods of plastics and paper not only economical but is a bold step towards low carbon emission.

Application of AHP
Here AHP will be applied in two steps to explore RRL of the above said three sectors of manufacturing industries.
Step 1: Setting up Expert team In AHP relative weightage to each enabler is given.For this, three teams of experts from academia and industry were invited.Experts from each industry i.e.Automotive, Electronics and Paper &Plastics industries, who were handling SC operation at senior position and three academicians at professor level specialized in SC have been contacted (refer table 4 of Appendix).The relative weightage given by the experts were used to make Decision Matrices (DM).
Step 2: Preparing Decision Matrices: DM in respect of enablers and sub-enablers were formed based on opinion given by experts.Finalising of DM has been carried out in three stages.
Stage 1: In the first stage, all factors affecting RL i.e. enablers and sub-enablers (table-1) from literature with a final opinion of experts have been finalised.After this a hierarchy in finding Responsiveness of RL (RRL) has been framed.Fig 1 is showing the Hierarchy in which the Goal to derive Index of RRL is at the top.At the bottom of this hierarchy the three industries where RRL is to be evaluated on the basis of interlinking of the enablers and sub enablers are shown.

Stage2:
In this stage, we will find enablers scoring highest weightage.For this DM containing fall enablers (here five) is prepared (table 2).The expert's relative weightage (1-9) has been used in DM, table 1 of appendix may be referred.For example, cost effectiveness is 8 times more important than PRM.Therefore, PRM is lesser important than CE by 0.125 times.The Local weight (LW) has been calculated by using several iterative steps of AHP.For example, LW of Environmental consideration (EC) is 0.4234.This is the highest weightage, among the five enablers.It indicates that the CE remained the key factor in deciding RRL.For checking consistency of the result, table no 2 &3 of appendix can be referred.This stage will be discussed in two steps.In first step; DM of sub-enablers of each enabler are prepared and LW is calculated (Table 3).Thus five DMs are obtained (refer appendix for these 5 tables).In second step, DMs of sub-enablers in context of the three industries are obtained.Thus, fifteen DMs, five for each sector i.e. for auto, EL and P&P are obtained.The results of these fifteen matrices are conveyed in Table 4 in column 6 a, b, c.As numbers of iterative steps are involved in making 15 DMs, hence those matrices are not shown in text.Only one table-3 is shown for the example.Finally, GWs are found for each industry by multiplying column 5 to 6a, b, c to get column 7a, b, and c.All the GWs found against each sub-enabler for an industry are summed to find out RRL index of that industry, which is shown in respective cell at the bottom.It is observed that highest Index of RRL is of Paper and plastics industries, followed by Automotive and Electronics sector.The detail discussion on result has been given in section 5 of this article.

Result and Discussion
In this section, discussion on result obtained is being presented.Reverse logistics is gaining huge importance in this time of ecommerce.This paper is highlighting the key enablers of RRL in the three major manufacturing sectors.AHP has been used to explore the effectiveness of RL in terms of Responsiveness of RL.A Hierarchical model of RRL is developed taking into consideration of the enablers, sub-enablers and the three manufacturing sectors.The results of AHP are displayed in Table 4.
Referring Table 3, it is seen that the LW of Enablers are; Cost Effectiveness (0.288); Product recovery management (0.05); Environmental consideration (0.423); Customers' impact (0.119) and return Policy (0.120).Pathak and Srivastava (2017) also outline environmental consideration as the most influencing enabler of RRL.GW of these sub-enablers is 0.4132, 0.3506, and 0.4323 in respect of Automotive, electronics and PP industries respectively.It is observed that PP industries are most responsive in business of RL due to three-fold reasons.Firstly, disposing of PP is easy from customer end to its processing units.Secondly, recycled paper and plastics are easily used to make new product.Thirdly, PRM is simple and does not impact environment if due care is taken.The second most responsive industry is automotive manufacturing sector.RL in automotive sector is growing steadily since last decades due to growing demand of used car, vehicles and machinery.Even the parts of used automotive are retrieved for further use by simple processes like; cutting, heating and breaking of automotives and almost whole metal parts are utilized for remanufacturing.
Recovery of useful material from electronics goods is comparatively low due to complex technology involved in its retrieval, whereas the recovered material by PRM is cost competitive.Retrieval of plastic, rare metals and some serviceable components from used computers, TV, camera, mobile, printers, photocopiers etc. can be used as raw material in manufacturing.Valuable metals such as copper, silver, gold, and platinum could be recovered from e-wastes, if better technology is available.Sukati, et al. (2012) have also reported about slow progress of RL in electronics industries.Summarizing the result, it is found that paper & plastics industries are showing highest responsiveness of the RL, whereas, electronics industries are least responsive.This is due to difficulties, complex technology involved in retrieval and low gains of useful material.

Sensitivity Analysis
The result obtained in AHP depends on the relative interlinking of Local Weightage and Global Weightage at each level.The result shows that it is a function of relative weightage and is dependent on the opinions of the experts.Who may be biased, however care has been taken to avoid biasness in AHP result.Sensitive analysis is the tool to check the robustness of these weightage by varying one parameter of any enabler.For this, ranking of the given industries is to be checked by using Sensitive analysis.It is found that after varying data of one enabler result (final Goal, i.e.RRL of Industry) remained unchanged.This establishes the correctness of the result.

Conclusion
RL is reverse supply chain of used goods for purpose of retrieval of useful material or for exchange.Necessity of RL was felt when it was found that waste/ EOL can be reused by doing some modifications, refurbishment, repair or retrieval to get cost competitiveness.RL is also supporting the items under guarantee/warranty.This paper has explored the RRL of the three sectors of manufacturing industries taking five enablers; Cost effectiveness, PRM, Environmental Consideration, Customer impact and Return policies.The Hierarchical model of AHP taking RRL, enablers, sub-enablers and the three industries has been developed.The three industries; automotive, electronics and paper & plastics are placed at the bottom and RRL at the top.With the application of AHP it has been found that Paper and Plastics industries are most responsive to RL.It may be due to easy in processing with good return on investment.The processing of these EOL has become comparatively less hazardous.Electronics industries are least responsive due to complex technology and environmental impacts.the retrieval of useful material from EOL of these products is complex, secondly evolving new technology at faster rate and becoming existing items obsolete.
Figure 1 Hierarchical Diagram of RRL

Figure 2
Figure 2 Graph of Variation in RRL of the three industries with respect to change in LW of PRM

Table 3 DM of Cost Effectiveness
To carry out sensitive analysis Local Weightage of PRM has been changed by 20, 30, 50, 70, 90 percentage, making others' Local Weightage constant.It is seen that overall sum of global weightage changed but the position (rank) of the three sectors of manufacturing industries in respect of responsiveness of RL remains unchanged (table5).The figure 2 displays consistency in the final result.