An Interpretive Structural Modelling (ISM) based Multi Criteria Decision Making for Supplier Selection with Dynamics of Global Indicators Barrier
The values of the alternatives and the weights of the criteria are thought to be set in classic decision-making issues. In the past, suppliers have been chosen based on their capacity to fulfil the demands for quality, delivery, and pricing. Nonetheless, in contemporary management, cultivating enduring supplier relationships requires taking into account a plethora of additional variables.
One of the most important factors affecting the competitiveness of the entire dynamic global supply chain network is supplier selection and evaluation. A supplier can be chosen carefully to produce high-quality goods at a reduced cost while increasing client satisfaction. Therefore, suppliers are the foundation upon which manufacturers attempt to build their selection process.
An established process for determining and summarising the links between certain things that form an issue or problem is called interpretive structural modelling, or ISM. It offers a way for a group to impose order on the items’ level of complexity. The key selection criteria for suppliers have been examined in order to create an ISM that illustrates how the criteria relate to one another and to different levels. These requirements have also been divided into groups based on how dependent and powerful each driver is. This research aims to determine the key decision factors that are pertinent to the contemporary global business climate before offering a useful instrument for selecting suppliers based on their preferences in relation to the requirements of manufacturing organisations.
Simulating future scenarios: A computational modeling framework for
urban resilience through Sustainable Groundwater Replenishment
Urban sustainability significantly impacts groundwater, with an escalating concern over groundwater depletion. The root cause of this issue lies in the challenge of effectively recharging groundwater. Numerous studies have explored various methods forgroundwater recharge, yet the critical aspect lies in implementing these methods in suitable recharge zones. This study endeavors to elevate the process of identifying optimal recharge zones to a sophisticated Multi-Criteria decision-making (MCDM)approach, considering factors such as rainfall patterns, land-use conditions, aquifer characteristics, transmissivity, thickness, drainage density, lineament densities, and soil types. A notable observation from the literature review is the scarcity of studies incorporating future rainfall scenarios, a crucial perspective for understanding recharge capacity. Furthermore, anticipating the expansion of built-up areas is essential as it directly influences potential recharge zones. To address these gaps, the present study integrates future rainfall projections and land-use projections to identify Groundwater Recharge Potential Zone (GWRPZ). The future rainfall projections are obtained through statistical modeling with Global Circulation Models and land-use projections modeled using land change modeling for the years 2030, 2040, and 2050. An additional contribution to the literature is the utilization of the Ordered Weighted Averaging (OWA)technique within the Multi-Criteria Decision-Making (MCDM) framework, a seldomapplied approach. OWA proves instrumental in offering decision-makers a nuanced array of solutions, accounting for both trade-offs and risks. This study bridges this literature gap by employing the OWA technique to overlay all relevant factor maps. This research not only addresses current challenges but also proposes a tangible solution by suggesting the implementation of 13 strategically located recharge wells within‘good’ category of Groundwater Recharge Potential Zones (GWRPZ). The uniqueness of the approach lies in superimposing the stream order map onto the identified ‘good’ GWRPZ, elucidating the intricate relationship between surface water and subsurface water and their collective contribution to groundwater recharge. This study presents a sustainable urban development by integrating advanced computational modelling techniques focusing the critical issue of groundwater depletion in urban areas. Through meticulous simulation of future rainfall scenarios and land-use changes using Global Circulation Models and land change modeling, this approach goes beyond conventional studies. This study introduces a rarely explored OWA technique empowering decision makers with a diverse array of maps and predictive scenarios. This study can serve as a compass guiding urban landscapes towards a harmonious future.