- ERP tools:
Opportunities and obstacles for supply chain integration the implementation of ERP enables the companies to move towards an extended enterprise business model that enhances value across the total supply chain. In order to gain supply chain efficiencies, companies need to exchange large amount of planning and operational data, ranging from information for annual contracts and periodic progress reporting to real-time delivery and invoicing data. The advantages and obstacles of ERP tools have been discussed in several research papers. Next we quote some relevant statements from the recent articles that underline our research problems and approaches: Although ERP packages strive to integrate all the major processes of a firm, customers discover that some essential functionality is lacking Traditional ERP infrastructures failed to support an extended business model across the supply chain. The challenge is to figure out what, how, where, who, when, and why manufacturing operations can feed the ERP beast.
Since ERP philosophy is process based, rather that function based, it necessitates disruptive organizational changes. ERP systems mostly adopt a myopic view of planning, based on pure deterministic planning methods. ERP provides several tools; the two most important for supply chain integration are the real-time transaction tracking and the internal process integration. Next we outline the four main opportunities offered and the obstacles of using them. The traditional vertically integrated business model requires re-evaluation.
The ERP software vendors saw the above problems and started providing advanced decision support tools that are the new ERP software extensions. Among them the most important directions are: the Advanced Planning and Scheduling (APS), Demand Planning and Revenue Management (DPRM), Customer Relationship Management (CRM), Sales Force Automation (SFA), and Supply Chain Management (SCM).
In this paper, we concentrate on the inventory management aspects of supply chain coordination. With our quantitative analysis we try to present results in information systems area by providing guidelines for transaction tracking, promoting visibility of information for the supply chain, and by supporting coordination among business partners. In the decision support area we try to improve the quality of ordering and transportation decisions (for SCM and DPRM), provide quantitative tools to find the joint optimal policy and help in contract negotiations (for SCM, APS, and CRM), estimate the fair amount of compensation necessary (for CRM), promote cooperation between the buyer and the supplier (for CRM).
Different theories are available to support supply chain cooperation. Management theory states that efficient supply chain requires cooperation. Quantitative modeling proves that the total system cost can be reduced by coordinated policy. At the same time, practice and theory shows several barriers in organizational factors (organizational theory) and subjective factors (behavioral theory). Few results integrate the results and combine the quantitative and organizational effects. Our goal is to provide quantitative modeling, numerical and sensitivity analysis to measure the potential monetary value of cooperation, combine it with organizational and management factors, and integrate in a multi-level framework of policy coordination.
- Sustainable supply chain management (SSCM):
In the area of sustainable practices, Mukherjee and Mandal examined relevant issues in managing the photocopier remanufacturing industry with the help of Interpretive Structural Modeling (ISM) methodology. Impact of workplace environment and use pattern of returns and issues related to marketing of remanufactured product were found to have the highest driving power. Product design issues relevant to remanufacturing process, level of technology and tools for remanufacturing, issues relevant to successful disassembly and reassembly planning, and role of skill and expertise of workforce had the highest dependence power. Faisal presented an approach to effectively adapt sustainable practices in a supply chain by analyzing the dynamics between various enablers that help transform a supply chain into a truly sustainable entity. ISM approach was used to present a hierarchy-based model.
Consumer concern towards sustainable practices, regulatory framework, awareness about sustainable practices in a supply chain and metrics to quantify sustainability benefits in a supply chain were found to have the highest driving and dependence power. Grzybowska identified the enablers to sustainability in the supply chains (SC) and explored their mutual relationships. 16enablers were identified out of which commitment from top management, and adequate adoption of reverse logistic practice (Environmental performance) had the highest driving and dependence power. Hussain presented a modeling framework of different enablers for sustainable supply chains and analyzed their inter-relationships and proposed alternatives for sustainable supply chain development .Enablers were identified and insights on the triple bottom line concept (environment, social, economic) of sustainability were provided. An R.D. Raut et al. Renewable and Sustainable Energy Reviews ISM approach was used to establish the relationship among various enablers for each dimension of sustainability and the results of ISM were used as an input to analytic network process (ANP) along with a potential list of alternatives to determine the best alternative(s) for developing sustainable supply chains.
Voice of customer, governmental regulations, and risk management were found to have the highest driving and dependence power. Diabat and Kannan developed a model of the drivers affecting the implementation of green supply chain management (GSCM) practices in organizations using an ISM methodology. Government regulation and legislation, reverse logistics and green design, and integrating quality had the highest driving and highest dependence power. Mathiyazhagan et al. analyzed the barriers for the implementation of GSCM concepts, which was divided into two phases – identification of barriers and qualitative analysis barriers were identified based on literature and in consultation with industrial experts and academicians, and ISM analysis was used to understand the mutual influences amongst them. Dashore and Sohani presented a hierarchical sustainable framework for evaluating the barriers to the implementation of GSCM in an organization. A total of 14 barriers were identified and ISM technique was applied to develop a structural model. Lack of government initiative system for GSCM practitioners and supplier’s flexibility to change towards GSCM were the barriers with highest driving and dependence power. Muduli et al. explored various behavioral factors affecting GCSM practices and their interactions, which help attain green-enabled needs of Indian mining industries.
An ISM approach was employed to extract the interrelationships among the identified behavioral factors. Top management support and green innovation were identified as the factors having the highest driving and dependence power. Luthra et al. identified various factors important for implementing GSCM relevant to Indian manufacturing industries. A contextual relationship among these factors was established using the ISM technique.
Out of the ten identified factors, international environmental agreements and innovative green practice factors had the highest driving and dependence power. Kumar et al. contributed towards an empirical research approach and collected primary data to rank different variables for effective customer involvement in green concept implementation in a supply chain. An ISM-based model was deployed to establish contextual relationships among the variables. For the research purpose, ten variables were identified, out of which green labeling and awareness level of customers were having the highest driving and dependence power. Sharma et al. analyzed 12 barriers hindering the successful implementation of reverse logistics (RL). An ISM methodology was used to understand the mutual influences among the barriers. Lack of awareness and limited forecasting and planning had the highest driving and dependence power. Kannan et al. developed a multi-criteria group decision making (MCGDM) model in fuzzy environment to guide the selection process of best third party reverse logistics provider (3PRLP). The analysis was done through the ISM methodology and fuzzy technique for order preference by similarity to ideal solution (TOPSIS).
Technical/engineering capability criteria had the highest driving power while reverse logistics cost had the highest dependence power. Kannan et al. used ISM methodology for identifying and summarizing the relationships among specific attributes for selecting the best third party reverse logistics provider. It was concluded that attributes, namely reverse logistics functions and third party logistics services had the highest driving and dependence power. Sarkis et al. analyzed 11 barriers in the adoption of environmentally conscious manufacturing (ECM) practices with an ISM approach. Inappropriate evaluation and appraisal approaches and poor design-for-environment (DFE) interfaces had the highest driving and dependence power. Ojo et al. identified drivers and barriers of GSCM practices adoption in Nigerian construction firms by using the ISM approach. The study showed that the lack of public awareness, lack of knowledge and environmental impacts, poor commitment by the top management and lack of legal enforcement and government represented the main barriers facing adoption of GSCM practices. Balasubramanian presented a hierarchical sustainability framework by using ISM technique for evaluating the 12 barriers to the adoption of GSCM in the United Arab Emirates (UAE) construction sector. Shortage of resources and lack of understanding among stakeholders were found to have the highest driving dependence power.
Luthra et al. identified 11 barriers in implementing GSCM practices in Indian automobile industries and contextual relationship among these barriers was established. A hierarchy structural model was prepared using the ISM technique, lack of government support policies, and market competition and uncertainty had the highest driving and dependence power. Sandeep et al. identified 15 important enablers to implement green concepts in the Indian auto-mobile supply chain by using ISM. Government support and regulation and relative advantage had the highest driving and dependence power. In the area of implementation of renewable energy projects, Eswarlal et al. analyzed 14 critical factors associated with sustainable development in India, using the ISM methodology. Leadership and sustainable growth and return on investment had the highest driving and dependence power. Eswarlal et al. determined the 14 key CSFs of renewable energy implementation for sustainable development, and it was found that sustainable growth and return and public awareness were having the highest driving and dependence power.
Kang et al. developed a comprehensive evaluation model to select a suitable location for developing a wind farm. The factors to be considered were identified and by adopting the ISM technique, the interrelationships among the criteria under each merit were deter-mined. A fuzzy analytic network process was used to calculate the importance of the criteria and to evaluate the expected overall performance of the wind farm projects. Muduli and Barve identified potential barriers that hinder greening effort in the Indian mining industry by using an ISM approach. Lack of top management commitment, and waste management operational strategy had the highest driving and dependence power. Kholil and Tangia chose ISM methodology to design the institutional model appropriate for the conditions surrounding the coral reefs, turtles and diversity of pelagic fish of Bunaken Marine Park to manage it as a sustainable tourist attraction. Nine main criteria and 15 sub-criteria were identified for the research work. Setting the number of visitors and increasing community involvement in the aspects of control were found to have the highest driving power and the highest dependence power. In the case of sub-criteria, national parks board had the highest driving power and two enablers, namely environmental and marine NGOs and the general public that had the highest dependence power.
Muduli et al.quoted that GSCM success in the mining industry has influenced human behaviors, and in their study, such behavioral factors were identified and ranked. Balaji et al.explored ten barriers in the adoption of GSCM practices in the foundry sector and an ISM methodology was used to establish the interrelationship between the barriers. Lack of government regulation and legislation had the highest driving power and lack of acceptance of advancement in new technology had the highest dependence power. Wang et al.investigated the interactions between the 13 major barriers that prevent the practice of energy saving in China. Lack of awareness of energy saving, and lack of experience in technology had the highest driving and dependence power. Tseng and Lin proposed 18 criteria on Taipei metropolitan municipal solid waste management (MSWM) activities to reduce air pollution. It was found that fuel or non-renewable energy consumption, atmospheric emissions and waste production had the highest driving and dependence power.
Kumar et al. identified the nine prime issues that under- score the selection of a supplier based on corporate social responsibility (CSR) and was validated using an ISM approach. It was found that safeguarding mechanism and underage labor had the highest driving and dependence power. Mangla et al. identified different per for-R.D. Raut et al.Renewable and Sustainable Energy Reviews 68 mance-focused criteria to GSCM implementation in their business. Mohanty and Prakash empirically examined the GSCM practices in the Micro, Small and Medium enterprises in India and proposed that MSMEs are facing significant pressures from external stake-holders to adopt GSCM practices. Muduli et al. identified and quantified the adverse impact of barriers hindering GSCM implementation by using the literature review approach, graph theoretic and matrix approach.
Luthra et al. analyzed the key success factors behind successful achievement of environment sustainability in the automobile industry supply chains. Six CSFs to implement GSCM for achieving sustainability and four expected performance measures of GSCM practices implementation were extracted using factor analysis. Further, interpretive ranking process modeling approach was employed to examine the contextual relationships among CSFs and to rank them with respect to performance measures. Luthra et al. empirically analyzed the impact on expected organizational performance outcomes by current GSCM practices adopted by the automobile industry. The results of this study suggested that environmental, economic, social and operational performances are improving with the implementation of GSCM practices. Mangla et al. identified and analyzed several attributes for improving performance in GSCM adoption and implementation in the Indian context.
The organizations will implement GSCM practices if they identify that this will result in specific financial and operational gains.If sustainable practices are more expensive, then they will not be implemented unless they are made mandatory by the government regulations or by customers or community. Regulations should consider changes in the tax code to encourage the organizations for the implementation of sustainable practices
There are various barriers to the successful implementation of SSCM and all the barriers do not carry an equivalent impact on SSCM practices. Therefore, there is a strong need to determine the dominant factors required to adopt the SSCM practices and their impacts.
From the above review, it may be summarized that the past research studies on implementation of sustainable practices has been conducted in different countries as well as industries. Not many studies have covered the importance of SSCM implementation practices/issues in the Indian oil and gas industries. Very few research studies have been carried out in the area of oil and gas industries, and still fewer dealt with sustainable implementation practices. It shows that there is a research gap in the implementation of sustainable practices in the oil and gas sector. Hence, to deal with this issue, this research paper has attempted to identify the numerous CSFs to implement SSCM practices, and to explore the interdependency between them. The objective of this study is to develop a structural model of CSFs to implement SSCM on the sustainable driving and dependency forces in Indian oil and gas industries.