Supplier Selection Process Research Articles

Selecting Shoes Box Suppliers using DEMATEL-ANP-WZOGP Approach

Supplier selection is an important stage in the procurement of goods and services. The suitable suppliers will streamline the company's business processes to increase profits for the company. Product packaging is one of the vital components of the overall representation of a product. Many industries leave packaging matters to others to focus on their area of specialization. Thus, the selection of packaging suppliers has become one of the critical issues in the industrial world. This study aims to develop a packaging supplier selection model in the shoe industry. The primary packaging for shoes is a shoe box made of cardboard. In developing the packaging supplier selection model, it is necessary to determine the relevant criteria and sub-criteria to support the entire supplier selection process. The integration of the Decision-Making Laboratory and Evaluation Laboratory (DEMATEL), Analytic Network Process (ANP), and Weighted Zero-One Goal Programming (WZOGP) were used in this study to produce a suitable supplier selection model. In the initial step, five criteria and 12 sub-criteria were determined from the literature study and brainstorming with the procurement department. Furthermore, the DEMATEL method supports the development of a model of the relationship between criteria, sub-criteria, and alternatives required in the ANP procedure. Then, the ANP method synergistically assigns weights to each criterion, sub-criteria, and alternative. The weights from the results of the ANP method are used as parameters for the WZOGP optimization model. In this study, quality (28.1%) was ranked as the highest criterion, and shoe box prints that matched the specifications (12.3%) became the sub-criteria with the highest ranking. The selection of the best suppliers using the ANP method sequentially is supplier B (62.22%), supplier A (20.41%), and supplier C (17.38%). The results of the WZOGP optimization model confirm the results of the ANP by setting supplier B as the leading supplier

Hybrid Use of Business Process Management and Analytical Hierarchy Process Method in Supplier Selection in the Automotive Industry

The fact that businesses act with certain systematics while continuing their operations in constantly changing market conditions enables businesses to increase their internal communication activities, reduce their costs, and thus increase their productivity. Business Process Management studies allow businesses to gain these privileges that they should have. The supplier selection process is a complex problem involving many factors simultaneously and many different applications are used to solve these problems. The Analytical Hierarchy Process method is one of the most popular multi-criteria decision-making techniques. It mentioned in many studies in the literature and is known as an effective supplier selection method that uses qualitative and quantitative data together. In this study, the supplier selection operation of an important company in the automotive industry has been made more systematic by using a hybrid of Business Process Management, Analytical Hierarchy Process method and Responsibility Assignment Matrix. It is aimed to fill the gap in this area, guide effective supply chain management integration and supplier selection operation in automotive sector.

PENERAPAN METODE ANALITYCAL HIERARCHY PROCESS DALAM PEMILIHAN SUPPLIER DENGAN PENDEKATAN SISTEM BERORIENTASI OBJEK

The current development of Information Technology, of course, has a major impact on very significant changes in various fields. Until now the supplier selection system at PT. Wika Realty, is not yet web-based because of problems with the system used for supplier data collection, which still uses conventional methods, and in determining the best supplier, you have to look at supplier data one by one, the assessment is still subjective, and there is no system that can determine the ranking of the value of the supplier determination analysis starting from the largest value to the smallest at PT. Wika Realty Jakarta. The purpose of this research is as an alternative to assist leaders in determining the appropriate supplier selection decisions, in selecting suppliers using alternative A, alternative B and alternative C. The method used is the Analytical Hierarchy Process method for the supplier selection process to make it more objective. The Analytical Hierarchy Process method is a process of comparing criteria into alternatives, the greater the value generated, the more important it is for the supplier to be selected, and in the analysis and design of the system, the system design method is object oriented programming using the Unified Modeling Language. Data collection by way of observation, interviews and literature study. The results of the research are in the form of software, namely a web-based decision support system for selecting the best supplier, which can present information on the best supplier data that fits the criteria quickly and precisely and supports digital concepts.

Picture fuzzy aggregation approach with application to third-party logistic provider selection process

Picture fuzzy sets (PFSs) are frequently composed of positive, neutral, and negative memberships and have the benefit of precisely capturing the preferences of decision makers (DMs). This paper introduces innovative picture fuzzy aggregation operators (AOs) based on fundamental operations, which have a number of advantages when dealing with real-world scenarios. Unpredictability and fuzziness coexist in decision-making analysis due to the complexity of the decision-making environment. ”Picture fuzzy numbers” (PFNs) outperform ”intuitionistic fuzzy numbers” (IFNs) when dealing with unclear input. This study proposes two aggregation operators (AOs): ”picture fuzzy hybrid weighted arithmetic geometric aggregation (PFHWAGA) operator” and ”picture fuzzy hybrid ordered weighted arithmetic geometric aggregation (PFHOWAGA) operator.” The proposed operators outperform the current PFN-defined operators. The proposed operator is utilised in the multi-criteria decision-making (MCDM) process to third-party logistic provider selection.

Supplier selection for an industry using MCDM techniques

The planning and management of both the actual physical transportation of commodities and the resources employed in the supply process, from raw materials to consumable products, falls under the purview of supply chain management (SCM). However, the demand for collaboration among all components of a supply chain has grown as a result of the always evolving business market difficulties. For decision science experts, the task of allocating orders to providers in order to satisfy various criteria is increasingly perplexing and challenging. Therefore, in order to aid in the decision-making process for the appropriate supplier selection, we apply innovative methodologies known as the multi-criteria approaches. Analytic Hierarchy Process (AHP) and MEthod based on Removal are two Multi Criteria Decision Making (MCDM) methodologies that we first employ in this study.

Selection of Suppliers of Building Materials Using the Analytical Hierarchy Process (AHP) Method at PT. Cipta Nuansa Prima Tangerang

Supplier is one of the most important parts of a construction services provider company. PT. Nuance Prima Cipta Tangerang is a contracting company that offers construction services. Since the number of suppliers, PT. Nuance Prima Cipta Tangerang difficulty in choosing suppliers with their respective advantages. Therefore, use AHP (Analytical Hierarchy Process) for supplier selection process to make it more objective. Broadly speaking, AHP (Analytical Hierarchy Process) is the process of comparing criteria into alternatives, the greater the value is generated, then the main well to the supplier selected. By using the AHP method obtained the final value for each akternatif Lead A 39%, 12% and Supplier B Supplier C 49%

INCREASING PERFORMANCE OF OIL PALM NPK FERTILIZATION WITH RISK MANAGEMENT AND ANALYTIC HIERARCHY PROCESS (AHP)

This research is intended to improve the performance of oil palm fertilization by examining the fertilizer procurement process. The research design that will be carried out in this study is based on the problems studied using descriptive analysis methods. Measurement of priority risk using FMEA and formulation of mitigation strategies using AHP (Analytic Hierarchy Process) by collecting data through observation, questionnaires with stakeholders who have expertise in their respective fields at the research site. One of the plantation crops that are widely cultivated by large plantation companies is oil palm. The moratorium on oil palm plantation permits for the addition of new land for 3 years encourages companies to increase crop productivity on existing plantation lands, one of which is fertilization. Constraints experienced in fertilizing on mature plants are the incompatibility of the fertilizer applied to the planned one. So that the increase in fertilization performance can be done through improvements in the procurement process. The purpose of this research is to study the risk priorities in the planning process to the acceptance of fertilizers in the procurement of fertilizers. The results showed that the priority risk of fertilizer procurement planning is that the budget availability is not in accordance with the recommendations (RPN 27), the supplier selection process is the announcement of the old tender (RPN 18), the dropping/delivery process is a late contract signed (RPN 18), the acceptance process is that the fertilizer is accepted. past the time period (RPN 18). The criteria are fertilizer procurement planning, supplier selection, fertilizer delivery and fertilizer receipts with successive values ​​of 0.575, 0.214, 0.134, 0.077. The alternatives are ensuring budget adequacy, adding fertilizer suppliers, improving communication between fertilizer providers and users, determining the timing of fertilizer application, increasing the frequency of fertilizer quality inspections and using information technology in fertilization. Improving the performance of fertilizer procurement can be done with three main strategies, namely improving the budgeting system, improving procurement documents, selecting suppliers with a multi-winner system.

Supplier selection framework to evade pseudo-resilience and to achieve sustainability in supply chains

PurposeDue to increasing uncertainty in the global business scenario, research on supply chain resilience is gaining significance. The outbreak of the COVID-19 pandemic has accelerated and magnified the issues already pertaining in the supply chain thereby increasing the vulnerabilities in the network. This study attempts to build the concept of pseudo-resilience in supplier selection and evaluation for supply chain sustainability.Design/methodology/approachA combination of multi-criteria decision-making methods AHP and R is adopted, and an integrated method called Combined AHP–R method is used to identify and include the property of pseudo-resilience into supplier selection processes.FindingsThe authors identified various factors contributing to pseudo-resilience considering supplier selection process and found the most important attribute. Using the combined AHP–R method, the suppliers were evaluated, considering the attributes contributing to the pseudo-resilience of supply chains and best supplier was selected.Originality/valueTo the best of our knowledge, this is the first study addressing a supplier selection problem for sustainable supply chains, considering pseudo-resilience. Also, this is the first study to apply the AHP–R method for supplier selection in the resilience or sustainability context.

Development of Contract Management SOP with it Service Providers Supplier Based on the Framework Cobit 5 and ITIL V3 Hospital Case Study Dr Ramelan Navy

RSAL Dr. Ramelan is a naval hospital in Surabaya. It is currently developing its Management Information Systems (MIS) with the supplier of IT (Information Technology) service providers. Problems arose when the management change interfere with MIS development. The current management wanted to change MIS supplier before the development process is completed. This can cause financial and time losses. The process of supplier selection, negotiation, contracting and fulfillment control of supplier contracts to always fit the needs of the business is conducted at the Supplier Management. This study aims to make a reference to the management of IT service provider suppliers contracts in the form of SOP (Standard Operating Procedure) which is based on the COBIT 5 framework domain APO10 Manage Supplier and ITIL V3 Supplier Management. Formulation of IT service providers supplier contract management in RSAL Dr. Ramelan SOP document is carried out in four stages. The first stage is the observation of IT services in RSAL Dr. Ramelan. The second stage is the stage of the analysis. This stage is to identify COBIT 5 Manage Supplier and ITIL V3 Supplier Management activities and mapping the activities. Having formed a new activity, adjustments are made to the Regulation of the President of the Republic of Indonesia No. 54 of 2010 concerning the Procurement of Goods and Services. In the third stage, SOP document preparation is done by decomposition of these activities to become sequential action steps. The last stage is the stage of evaluation and improvement, which begins with the verification done in RSAL Dr. Ramelan, then the improvement is done based on the results of verification. The result of this study is an IT service providers supplier contract management SOP document that has been tailored to the condition in RSAL Dr. Ramelan. From the result of the evaluation, it is known that the SOP produced was still in need for improvement in terms of grammar, role and order activity. The SOP document that has been evaluated before has been corrected and improved based on the feedback given by RSAL Dr. Ramelan. Key Words : Supplier Management , COBIT 5 , ITIL , Standard Operating Procedure , Underpinning Contract . The SOP document that has been evaluated before has been corrected and improved based on the feedback given by RSAL Dr. Ramelan. Key Words : Supplier Management , COBIT 5 , ITIL , Standard Operating Procedure , Underpinning Contract . The SOP document that has been evaluated before has been corrected and improved based on the feedback given by RSAL Dr. Ramelan.

An interval-valued intuitionistic fuzzy-based CODAS for sustainable supplier selection

With the advent of information age, supplier selection has attracted researchers’ attention in the field of supply chain management. Optimal supplier selection meets the competitiveness of industries and satisfaction of customers in the supply chain management. However, considering sustainable factors including environmental and social parameters, alongside customers’ expectations are the main challenge of supplier selection. Moreover, incomplete and hesitation among experts’ judgment result in uncertainty that leads the more complex assessment of criteria. In this paper, an innovative multi-criteria decision-making method was developed to address supplier selection process and supplier order allocation based on customers’ expectations with respect to the sustainable primers. The proposed method was based on fuzzy combinative distance-based assessment (CODAS) extended with interval-valued intuitionistic fuzzy (IVIF) for multi-criteria sustainable supplier selection. The proposed model was combined with hesitation linguistic set to provide two goals including a: dealing with experts’ hesitation as well as imprecise and vague of decision makers’ knowledge in order to express assessment values. b: coping with missing or nonexistence of attribute assessment values. The proposed method was performed on a steel mill as a case study to illustrate the effectiveness of decision process on four suppliers in detail. The results showed that the presented model could consider conflicting parameters and enhance high-order imprecision and uncertainty.

A Hybrid Model Based on SEM and Fuzzy TOPSIS for Supplier Selection

How to select the right suppliers has become a crucial strategic decision for manufacturing companies facing various performance measures. This study proposed a hybrid selection model integrating factor analysis, structural equation modeling (SEM), and the fuzzy Technique for Order Performance by Similarity to Ideal Solution to (TOPSIS) design a supplier selection model. The study distilled 70 original selection criteria from the relevant literature and identified eight main influencing factors based on factor analysis. The relevance of factors was evaluated by SEM and the performance of suppliers assessed by fuzzy TOPSIS. The model was applied in a manufacturing company in China to verify its practical significance. By combining different methods, the model can select relevant and important supplier selection criteria and include unquantifiable, incomplete, and vague information in the decision model. The hybrid model merges the advantages of each method and takes into account of uncertainty associated with supplier selection process.

Probabilistic Approach to Multi-Stage Supplier Evaluation: Confidence Level Measurement in Ordinal Priority Approach.

A popular framework of the supplier selection process is usually characterized by problem definition, criteria formulation, supplier screening, and supplier selection. The literature review suggested limitations of this framework as it ignores the screening of criteria (beyond criteria weighing) and evaluators (buyers) and its inability to guide the supplier selection problems where a measure of confidence or trust is needed to confirm the reliability of the selected supplier. While extending de Boer’s influential supplier selection framework, the current study argues that the supplier selection problem is not merely about ranking suppliers based on given criteria; instead, it involves evaluating criteria and evaluators as well. Guided by the theory of statistics and the Ordinal Priority Approach (OPA), the study pioneers a probabilistic approach of supplier evaluation and selection under incomplete information using a novel Confidence Level measure. The study suggests, the probability that a supplier shortlisted for selection is actually the optimum choice or not can be explained through a probability distribution, called W-distribution, therefore, confidently preventing the decision-makers from selecting the sub-optimum suppliers. The study presents a novel contribution to the theory of multiple-attribute decision-making through the OPA. The proposed approach can help build intelligent decision support systems to aid managers while providing them with early warning tools and suggestions to improve confidence in their selection.

Supplier Selection in Highly Uncertain Environments: The Fuzzy Stratified Best-Worst Method

The literature suggests the application of multi-criteria decision-making (MCDM) methods for supplier selection. MCDM methods commonly require decision makers to assign weightings of importance to the decision-making criteria based on which the available suppliers are ranked. Such rankings, however, may not sufficiently support the supplier selection process. This is because the selected supplier will be used for a relatively long period of time. The decision criteria, therefore, need to have weightings that take into consideration uncertainty that is related to the future in which the supplier will still be used (especially in the current challenging world after COVID-19). This research gap is important because the current literature may guide authorities to select a supplier which may suit their current situation but may not be the best option in the near future. This may result in the need to change their supplier in the near future or tolerate the consequences of a wrong selection. To address this gap, this paper suggests the application of an MCDM technique, namely the stratified MCDM (SMCDM) in combination with fuzzy logic and the best-worst method (BWM). Therefore, while this paper addresses the supplier selection problem in an uncertain environment, it also proposes a novel decision-making framework to support decision making in uncertain environments.

Strategy development for supplier selection process with smart and sustainable criteria in fuzzy environment

Supply chain management has been mutated to adapt to the developments over the last couple of decades. Smart paradigms, one of today's most significant paradigm shifts, occur in almost every moment of our daily lives. On the other hand, the importance of sustainability has increased more and more, reducing available resources of our world and increasing the effect of climate change and environmental degradation. In this context, this study it is aimed to develop a strategy for the supplier selection process by investigating the impacts of using different fuzzy environments and different decision-making methods on smart and sustainable supplier selection. The applicability of the proposed approaches has been demonstrated by a supplier selection case study of Company V, an automobile spare parts manufacturer. With the comparative analyzes made, it has been observed that although different fuzzy environments or varying decision-making methods in supplier selection create minor differences in criterion weights, it does not make any difference in supplier evaluations. For this reason, it has been concluded that it does not affect supplier selection. In addition, it was investigated how different supplier distributions in the strategies developed with the scenario analyzes affected each purpose of Company V, and an increase was observed in purchasing costs, carbon emission rates, quality rates, and on-time delivery rates when their importance levels increased from sustainable to smart criteria. To the authors' best knowledge, strategy development for the smart and sustainable criteria-based supplier selection process is a pioneering work in this field as it has never been studied before in the literature.

Social cross-functional vendor selection in technologically uncertain sourcing situations

Based on an in-depth case study of an automotive manufacturer sourcing parts for high technology projects, this study investigates the intentions and structure of socialization within and between firms during the supplier selection process in technologically uncertain sourcing situations. Here, we aim to answer the question of how socialization can hedge against the high levels of uncertainty for manufacturers selecting suppliers of high technology resources. The case represents a major automotive manufacturer in Northern Europe, and is based on 38 semi-structured interviews with representatives of the different functions involved in the sourcing for the new development projects. Our data suggest that internal and external socialization during the supplier selection process can improve internal alignment and problem solving, and external familiarity towards the sourcing task. In this context, socialization took place on functional, cross-functional, and (inter)corporate levels, with higher functional autonomy during the assessment, and higher cross-functional integration during negotiations and decision making, adding to the debate on whether functions should be integrated or separated. • In some industries firms need to source technology from outside their existing supply base. • This has increased the uncertainty with future relationships and inclusion of input from multiple functions internally. • Higher level of socialization during supplier selection can increase familiarity with the supplier and reduce uncertainty. • Higher levels of internal socialization during supplier selection can improve alignment of the decision making.

Multicriteria Approach for Supplier Selection: Evidence from a Case Study in the Fashion Industry

Worldwide manufactures are redesigning supply chains, often outsourcing with the aim of maintaining a competitive advantage and gaining market share. When selecting and purchasing fabrics, firms should actively cooperate with suppliers, to meet customers’ needs. In this view, the supplier selection process plays a key role in keeping a competitive edge in global markets. Therefore, this study proposes a multicriteria decision-making model (MCDM) to ease supplier evaluation and selection. Supply chain operation reference metrics (SCOR metrics) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) are combined to build a model for supplier selection. The former allows us to conduct a very thorough fact-based analysis of all features in the supply chain, while the combination of fuzzy theory and SCOR model allows us to deal with uncertainty. The main novelty of this method is that it incorporates a consolidated supply chain management criteria within the framework of fuzzy set theory and multicriteria decision-making model (MCDM) facilitating their application into practice. The proposed approach is tested by considering the case of a manufacturing firm in the fashion industry willing to designate the most appropriate supplier within a set of three potential ones.

The application of factor analysis (FA) in evaluating supplier selection criteria in PT. Wijaya Karya Beton Tbk and ranking suppliers using integration of analytical hierarchy process (AHP) and adaptive ratio assessment (ARAS)

The selection of a concrete iron supplier is critical for a long-term supply chain in the infrastructure industry. Due to the participation of various qualitative and quantitative elements, the evaluation process of concrete iron supplier selection is a difficult work for decision specialists. Because uncertainty is widespread in concrete iron supplier selection challenges, improving integrated criteria selection and supplier selection procedures has proven to be one of the most efficient and superior ways to represent practical difficulties. The current study presents a novel framework for evaluating and selecting a preferred concrete iron supplier based on Factor Analysis and the ARAS (Adaptive Ratio Assessment) method, as well as the AHP (Analytical Hierarchy Process) methodology. An enhanced technique is used in the proposed method to determine the criteria weights based on expert preferences. Next, an actual case study of the concrete iron supplier selection problem is conducted in a comprehensive setting to demonstrate the effectiveness and practicability of the suggested methodology. A sensitivity analysis is also undertaken to ensure that the stated methodology is stable. Finally, the strength of the resulting result is tested by comparing it to current methodologies. The final results show that the established framework is more consistent and powerful than other approaches already in use.

Application of Data Envelopment Analysis (DEA) in the Selection of Sustainable Suppliers: A Review and Bibliometric Analysis

The supplier selection process is a strategic decision-making process that influences the company’s sustainability. Lately, the sustainability concept has been highlighted as an organization’s source of success and profitability. Therefore, the selection of a sustainable supplier has become an imperative for organizations and is the focus of this manuscript. Suppliers are key stakeholders in the supply chain, and their proper selection is a key factor in a successful and sustainable supply chain. For this reason, it is crucial to determine how and which methods are mostly used by companies when choosing sustainable suppliers with the aim of examining whether the Data Envelopment Analysis (DEA) contributes to the same. This article is the first to present a comprehensive bibliometric analysis of 87 articles dealing with the application of DEA in the sustainable supplier selection in the period 2010–2022, with the application of the keywords “Data Envelopment Analysis”, “Supplier”, and “Sustainable” in Scopus and Web of Science databases. The main goal of this manuscript is to explore the applications of DEA in a sustainable supplier selection and to provide an analysis and visualization of bibliometric data to reveal the annual trends of published articles in this area, the top contributing journals, the most cited papers, the most contributing authors, citations, affiliations, and countries’ analysis, and an in-depth keyword visualization analysis. The findings of this study provide valuable insights and emphasize the ever-growing trend toward the selection of sustainable partners and suppliers in business using DEA methodology. Notably, this work shows the applicability and efficacy of DEA in specialized areas of supply chain management and should contribute to the construction of an overview of the existing literature on DEA studies regarding the process of selection of sustainable suppliers in supply chain management as well as stimulate the interest in the topic. This article gives an overview of a research field that is actually insufficiently explored through the scientific literature and presents a wide area and guidelines for future work.

Decision-making framework for supplier selection using an integrated MCDM approach in a lean-agile-resilient-green environment: evidence from Indian automotive sector

PurposeToday, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully for retaining operational excellence. Accordingly, varieties of paramount practices, i.e. Lean, Agile, Resilient and Green practices, are integrated in present study with the objective to develop a Decision Support Framework (DSF) to select robust supplier under the extent of Lean-Agile-Resilient-Green (LARG) practices for a manufacturing firm. The framework is developed and validated in the Indian automotive sector, where the primary data is collected based on perceptions of the respondents working in an automotive company.Design/methodology/approachLARG metrics can ponder ecological balance, customer satisfaction, associations, effectiveness and sustainability and thus, the study consolidated LARG practices in one umbrella to develop a DSF. The analytical approach under DSF is developed by the integration AHP, DEMATEL, ANP, Extended MOORA and SAW techniques in present study to evaluate a robust supplier under the aegis of LARG practices in SC. DSF is developed by scrutinizing and categorizing LARG characteristics, where the selected LARG characteristics are handled by fuzzy sets theory to deal with the impreciseness and uncertainty in decision making.FindingsThe study has identified 63 measures (15 for Lean, 15 for Agile, 14 for resilient and 19 for Green) to support the robust supplier selection process for manufacturing firms. The findings of study explicate “Internal communication agility”, “Interchangeability to personnel resources”, “Manufacturing flexibility”, “degree of online solution”, “Quickness to resource up-gradation”, “Manageability to demand and supply change”, “Overstocking inventory practices” as significant metrics in ranking order. Additionally, “Transparency to share information”, “Internal communication agility”, “Manufacturing Flexibility”, “Green product (outgoing)” are found as influential metrics under LARG practices respectively.Practical implicationsA technical DSF to utilize by the managers is developed, which is connected with knowledge-based theory and a case of an automobile manufacturing firm is presented to illustrate its implementation. The companies can utilize presented DSF to impose service excellence, societal performance, agility and green surroundings in SC for achieving sustainable outcomes to be welcomed by the legislations, society and rivals. The framework represents an important decision support tool to enable managers to overcome imprecise SC information sources.Originality/valueThe study presented a proficient platform to review the most significant LARG alternative in the SC. The study suggested a cluster of LARG metrics to support operational improvement in manufacturing firms for shifting gear toward sustainable SC practices. The present study embraces its existence in enrolling a high extent of collaboration amongst clients, project teams and LARG practices to virtually eradicate the likelihood of absolute project failure.

Optimal Strategy for Supplier Selection in a Global Supply Chain Using Machine Learning Technique

This paper proposes an optimization strategy for the best selection process of suppliers. Based on recent literature reviews, the paper assumes a selection of commonly used variables for selecting suppliers and using logistic regression algorithm technique to build a model of optimization that learns from customer requirements and supplier data and then makes predictions and recommendations for best suppliers. The supplier selection process can quickly at times turn into a complex task for decision-makers to deal with the growing number of suppliers. But logistics regression technique makes the process easier in the ability to efficiently fetch customer requirements with the entire supplier base list by predicting a list of potential suppliers meeting the actual requirements. The selected suppliers make up the recommendation list for the best suppliers for the requirements. And finally, graphical representations are given to showcase the framework analysis, variable selection, and other illustrations about the model analysis.