Intuitive global sourcing – a study of supplier selection decisions by apparel SMEs

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chris Ellegaard ◽  
Ulla Normann ◽  
Nina Lidegaard
Keyword(s):  
Textile Industry ◽  
Supplier Selection ◽  
Selection Process ◽  
Behavioral Pattern ◽  
Global Sourcing ◽  
Content Type ◽  
Matching Process ◽  
Selection Decisions ◽  
Global Supplier ◽  
High Uncertainty

PurposeThe purpose of this paper is to create knowledge on the intuitive global sourcing process applied by small and medium-sized enterprise (SME) managers.Design/methodology/approachThis study reports on qualitative inquiries with experienced sourcing managers from 10 SMEs in the textile industry. The study follows a three-step semi-structured interviewing process, allowing us to gradually unveil the detailed nature of the intuitive supplier selection process.FindingsNine of the 10 SMEs rely on a highly intuitive supplier selections process, where one supplier at a time is gradually taken into the exchange while testing the supplier’s behavior. The process consists of an early heuristics sub-process, which gradually switches over to a more advanced intuiting behavioral pattern-matching process.Practical implicationsMost OM/SCM research has treated global sourcing and supplier selection as a highly rational, analytical and deliberate optimization problem. This study uncovers a completely different, and frequently successful, intuitive process, which could inspire managers in companies of all sizes, faced with high uncertainty about global supplier selection decisions.Originality/valueIntuition has recently been adopted in the global sourcing literature. However, this study is the first to offer detailed insights into a predominantly intuitive global sourcing process, specifically as it is managed by SMEs.

Resilient supplier selection to mitigate uncertainty: soft-computing approach

2020 ◽  
Vol 15 (4) ◽  
pp. 1339-1361 ◽  
Author(s):  
Dipika Pramanik ◽  
Samar Chandra Mondal ◽  
Anupam Haldar
Keyword(s):  
Decision Making ◽  
Organizational Performance ◽  
Supplier Selection ◽  
Selection Process ◽  
Multiple Criteria Decision Making ◽  
Assessment Method ◽  
Fuzzy Entropy ◽  
Automotive Manufacturing ◽  
Content Type ◽  
Global Supplier

Purpose In recent years, determining the effective and suitable supplier in the supply chain management (SCM) has become a key strategic consideration to the success of any manufacturing organization in terms of business intelligence (BI), as many quantitative and qualitative critical factors are measured from big data. In today’s competitive business scenario, the main purpose of this study is to determine suitable and sustainable suppliers during supplier selection process is to reduce the risk of investment along with maximize overall value to the customer and develop closeness and long-term relationships between customers and suppliers to build a resilient SCM to mitigate uncertainty for automotive organizations. Design/methodology/approach As these types of decisions generally involve more than a few criteria and often necessary to compromise among possibly conflicting factors, the multiple-criteria decision-making becomes a useful approach to solve this kind of problem. Considering both tangible and intangible criteria, the aim of this paper is the presentation of a new integrated fuzzy analytic hierarchy process and fuzzy additive ratio assessment method with fuzzy entropy using linguistic values to solve the supplier selection problem to build the resilient SCM under uncertain data. Fuzzy entropy is used to obtain the entropy weights of the criteria. Findings Organizations gather massive amounts of information known as BD on the basis of historical records of uncertainties from several internal and external sources to manage uncertainty to improve the overall performance of organizations using BI strategy for analyzing and making effective decision to support the managements of automotive manufacturing organizations in an information system. Research limitations/implications Although this study tries to represent a full analysis on suitable and resilient global supplier selection under various types of uncertainty, still there are some improvements that can be made in the future by developing a more refined and more sophisticated approach to further enhance the performance of the proposed scheme to calculate overall rating scores of the alternatives. Originality/value The novelty of this paper is to propose a framework of BI in SCM to determine a suitable and resilient global supplier where all the meaningful information, relevant knowledge and visualization retrieved by analyzing the huge and complex set of data or data streams, i.e. BD based on decision-making, to develop any manufacturing organizational performance worldwide.

scholarly journals The impact of social media signals on supplier selection: insights from two experiments

2020 ◽  
Vol 40 (5) ◽  
pp. 531-552
Author(s):  
Aneesh Banerjee ◽  
Jörg M. Ries ◽  
Caroline Wiertz
Keyword(s):  
Social Media ◽  
Operations Management ◽  
Supplier Selection ◽  
Design Methodology ◽  
Selection Process ◽  
Content Type ◽  
Selection Decisions ◽  
The Impact ◽  
Source Of Information ◽  
Media Volume

PurposeOnline B2B markets offer buyers a new source of information provided by social media signals about suppliers. These signals have not yet received much attention in the supplier selection literature. This study advances our understanding of how buyers respond to social media signals in the supplier selection process.Design/methodology/approachWe develop a choice-based conjoint experimental design to isolate and manipulate two signals from social media: volume (the number of ratings) and valence (average evaluation of the ratings). We test how these signals are interpreted in the context of varying deal sizes and price points.FindingsBoth volume and valence are positively correlated with supplier selection. However, (1) the signals exhibit diminishing returns and (2) the efficacy of valence is interpreted in the context of volume. We also find that (3) there is no influence of the deal size and that (4) the relationships between signals and supplier selection are negatively moderated by deviations from the reference price.Research limitations/implicationsSocial media signals should be considered in supplier selection decisions as they convey valuable information to the buyer. However, signals go through a process of interpretation which has implications for buyers, suppliers, and owners of online B2B markets.Originality/valueOur research opens new lines of inquiry in behavioural operations management research regarding the mechanisms by which buyers interpret social media signals and how these ultimately influence their choice.

Comparison of ANFIS and FAHP-FGP methods for supplier selection

Kybernetes ◽  
2016 ◽  
Vol 45 (3) ◽  
pp. 474-489 ◽  
Author(s):  
Moloud sadat Asgari ◽  
Abbas Abbasi ◽  
Moslem Alimohamadlou
Keyword(s):  
Performance Measures ◽  
Supplier Selection ◽  
Mean Squared Error ◽  
Selection Process ◽  
Evaluation Criteria ◽  
Absolute Error ◽  
Global Market ◽  
Content Type ◽  
Squared Error ◽  
Fuzzy Delphi

Purpose – In the contemporary global market, supplier selection represents a crucial process for enhancing firms’ competitiveness. This is a multi-criteria decision-making problem that involves consideration of multiple criteria. Therefore this requires reliable methods to select the best suppliers. The purpose of this paper is to examine and propose appropriate method for selecting suppliers. Design/methodology/approach – ANFIS and fuzzy analytic hierarchy process-fuzzy goal programming (FAHP-FGP) are new methods for evaluating and selecting the best suppliers. These methods are used in this study for evaluating suppliers of dairy industries and the results obtained from methods are compared by performance measures such as Mean Squared Error, Root Mean Squared Error, Normalized Root Men Squared Error, Mean Absolute Error, Normalized Root Men Squared Error, Minimum Absolute Error and R2. Findings – The results indicate that the ANFIS method provides better performance compared to the FAHP-FGP method in terms of the selected suppliers scoring higher in all the performance measures. Practical implications – The proposed method could help companies select the best supplier, by avoiding the influence of personal judgment. Originality/value – This study uses the well-structured method of the fuzzy Delphi in order to determine the supplier evaluation criteria as well as the most recent ANFIS and FAHP-FGP methods for supplier selection. In addition, unlike most other studies, it performs the selection process among all available suppliers.

scholarly journals Sustainable procurement practices in the supplier selection process: an exploratory study in the context of Brazilian manufacturing companies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alex Moysés Barbanti ◽  
Rosley Anholon ◽  
Izabela Simon Rampasso ◽  
Vitor William Batista Martins ◽  
Osvaldo Luiz Gonçalves Quelhas ◽  
...  
Keyword(s):  
Supplier Selection ◽  
Local Community ◽  
Manufacturing Sector ◽  
Selection Process ◽  
Correlation Method ◽  
Manufacturing Companies ◽  
Content Type ◽  
Sustainable Procurement ◽  
Starting Point ◽  
Criteria Importance

Purpose This paper aims to evaluate the adoption of sustainable procurement practices adopted by Brazilian manufacturing companies in supplier selection; additionally, it is aimed to understand which of these practices enable a better differentiation of the analysed companies. Design/methodology/approach A systematic literature review was performed to compose the theoretical base of this research. In addition, a detailed study of ISO 20400 standard was conducted. The guidelines of ISO 20400 were used as a base to structure a questionnaire used in a survey with professionals working in procurement sphere of manufacturing companies in Brazil. The data were analysed via frequency and CRITIC (Criteria Importance Through Intercriteria Correlation) method. Findings A moderate dispersion in the adoption level of sustainable procurement practices in supplier selection process of the manufacturing companies was observed; in practices associated with social aspects, the dispersion is greater. A negative issue to be highlighted is that almost 20% of analysed companies did not even considered in their supplier selection process if their candidates accomplish philanthropic activities, generate jobs in local community and fulfill the Universal Declaration of Human Rights of United Nations (UN). Those two last practices are the ones with the best capacity to differ the companies in the sample. Originality/value There are few studies that focuses on understanding the adoption of sustainable procurement practices in manufacturing companies' supplier selection process. The main contribution of this study to the literature is to evidence that social requirements in supplier selection process are considered in a clear and well-structured form only by few Brazilian manufacturing companies. Despite the sample size, companies analysed in this research are prominent organisations in manufacturing sector. Thus, if this situation occurs in these companies, a more critical scenario will be evidenced in other organisations. This study has implication for practice and academy. For companies' managers, information present here can be used to debate the theme in the organisational context and the nine practices and scale can be used to perform a critical analysis of company's practices. For researchers, the information present here can be used as starting point for futures studies.

scholarly journals Construction of capital procurement decision making model to optimize supplier selection using Fuzzy Delphi and AHP-DEMATEL

2018 ◽  
Vol 25 (5) ◽  
pp. 1528-1547 ◽  
Author(s):  
Anil Kumar ◽  
Amit Pal ◽  
Ashwani Vohra ◽  
Sachin Gupta ◽  
Suryakant Manchanda ◽  
...  
Keyword(s):  
Decision Making ◽  
Automobile Industry ◽  
Supplier Selection ◽  
Selection Process ◽  
Strategic Decision ◽  
Extensive Literature ◽  
Content Type ◽  
Fuzzy Delphi ◽  
Selection For ◽  
Decision Making Model

Purpose Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. The purpose of this paper is to construct capital procurement decision-making model to optimize supplier selection in the Indian automobile industry. Design/methodology/approach To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria, although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria. Findings The results show that the total cost of ownership (TOC) is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, TOC, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier. Originality/value The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.

Improving logistics supplier selection process using lean six sigma – an action research case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huay Ling Tay ◽  
Hui Sen Aw
Keyword(s):  
Health Care ◽  
Six Sigma ◽  
Supplier Selection ◽  
Selection Process ◽  
Lean Six Sigma ◽  
Content Type ◽  
Logistics Services ◽  
Health Care Company ◽  
Care Company

Purpose Outsourcing logistical activities have become a widely used approach for firms to avoid high fixed costs and heavy investment requirements and to achieve competitive advantages. Lean six sigma (LSS) has been accepted globally across sectors as a management strategy for achieving process excellence. The purpose of this paper is to feature the application of LSS for improving the supplier selection process (SSP) of outsourced logistics services in a multinational health-care company. Design/methodology/approach This study is based on an action research case study conducted on the SSP of the freight and distribution department in a multinational health-care company. This paper reports on the application of the LSS define-measure-analyze-improve-control (DMAIC) approach for reducing supplier selection lead time. Findings The study features a real-world case study of the LSS DMAIC application to improve the supplier selection process of a large health-care company. The key issues that were identified are lack of information visibility, top-down changes and unclear communication lines. To counteract these three root causes, the lean six sigma techniques that are implemented are the 5S, stakeholder analysis and standard operating procedure. Research limitations/implications This research provided empirical evidence of how practical challenges in SSP can be managed with the use of LSS. It further proposed plausible solutions for reducing and sustaining improved outcomes. As the study is limited to one case, the validity of the results can be improved by including more organisations and more case studies from other similar organisations. Originality/value Research in supplier selection processes rarely links continuous improvement ideology such as LSS to support strategic selection and procurement of logistics services. This paper could serve as a resource for both practitioners to derive useful implications and to academicians as it contributes to the LSS body of knowledge for further theory testing.

End-to-end sustainability: trade-offs, consumers’ perceptions and decisions beyond B2C interfaces

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Camila Lee Park ◽  
Mauro Fracarolli Nunes ◽  
Alessio Ishizaka
Keyword(s):  
Supplier Selection ◽  
Word Of Mouth ◽  
Corporate Image ◽  
Content Type ◽  
Corporate Credibility ◽  
Trade Offs ◽  
Modern Slavery ◽  
Selection Decisions ◽  
The Usa ◽  
The Impact

Purpose This study aims to examine the extended effects of corporate (ir)responsibilities in supply chains. More specifically, the authors compare the impact of social and environmental initiatives and failures in the reputational capital of supply chain partners. The authors investigate how (and if) companies’ decisions to prioritize different sustainability dimensions in their supplier selection processes (i.e. sustainability trade-offs) affect consumers’ perception of corporate image, corporate credibility-expertise, attitude towards the firm and word-of-mouth. Design/methodology/approach The authors conducted three behavioural vignette-based experiments with 562 participants from the USA, relying on analysis of variance and t-tests analyses. Findings Results show that consumers perceive social irresponsibility cases as more severe than environmental ones in suppliers’ operations, penalizing buyers’ corporate image, corporate credibility-expertise and word-of-mouth. Corporate image, attitude towards the firm and word-of-mouth also have significant differences between social and environmental trade-offs. Statistically significant differences were also found between scenarios that portrayed the discovery of an irresponsible action and ones that reinforced the previous irresponsible practice in companies’ suppliers. Practical implications When types of irresponsibility practices are presented, the discovery of child labour and modern slavery conditions in suppliers damage how consumers perceive the company on corporate image and their attitude towards the organization and how they will spread word-of-mouth, reinforcing the importance of considering sustainability issues when making supplier selection decisions. Originality/value The study contributes to the understanding of how companies are perceived by their consumers regarding irresponsible practices and their impact on firms’ supplier selection decisions. Furthermore, data suggests that consumers might hierarchize sustainability dimensions, perceiving social irresponsibility cases as more severe than environmental irresponsibility ones.

A Multicriteria Multilevel Group Decision Method for Supplier Selection and Order Allocation

2012 ◽  
Vol 3 (1) ◽  
pp. 81-105 ◽  
Author(s):  
Mariya A. Sodenkamp ◽  
Leena Suhl
Keyword(s):  
Supplier Selection ◽  
Group Decision ◽  
Selection Process ◽  
Large Body ◽  
Decision Makers ◽  
Order Allocation ◽  
Decision Factors ◽  
Selection Decisions ◽  
Allocation Decisions

Supplier selection is an integral part of supply chain management (SCM). It plays a prominent role in the purchasing activity of manufacturing and trading companies. Evaluation of vendors and procurement planning requires simultaneous consideration of tangible and intangible decision factors, some of which may conflict. A large body of analytical and intuitive methods has been proposed to trade off conflicting aspects of realism and optimize the selection process. In the large companies the fields of decision makers’ (DMs) expertise are highly distributed and DMs’ authorities are unequal. On the other hand, the decision components and their interactions are very complex. These facts restrict the effectiveness of using the existing methods in practice. The authors present a multicriteria decision analysis (MCDA) method which facilitates making supplier selection decisions by the distributed groups of experts and improves quality of the order allocation decisions. A numerical example is presented and applicability of the proposed algorithm is demonstrated in the Raiffeisen Westfalen Mitte, eG in Germany.

An integrated supplier selection approach incorporating decision maker’s risk attitude using ANN, AHP and TOPSIS methods

Kybernetes ◽  
2019 ◽  
Vol 49 (9) ◽  
pp. 2263-2284 ◽  
Author(s):  
Chunxia Yu ◽  
Zhiqin Zou ◽  
Yifan Shao ◽  
Fengli Zhang
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Ahp ◽  
Evaluation Criteria ◽  
Risk Attitude ◽  
Integrated Approach ◽  
Fuzzy Topsis ◽  
Ann Model ◽  
Content Type ◽  
Selection Approach

Purpose The purpose of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the artificial neural network (ANN), analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods. Design/methodology/approach In the proposed approach, the ANN model is used to classify decision maker’s risk attitude; the fuzzy AHP method is used to determine the relative weights of evaluation criteria; and the fuzzy TOPSIS method is used to evaluate ratings of suppliers. Finally, experiments are conducted to verify the feasibility and efficiency of the proposed integrated approach. Findings Experiments results show that the proposed integrated approach is effective and efficient to help decision makers to select suitable suppliers according to their risk attitudes. Originality/value The aim of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the ANN, AHP and TOPSIS methods. The decision maker’s risk attitude toward procurement transaction is originally considered in supplier selection process.

Modelling the supplier selection process enablers using ISM and fuzzy MICMAC approach

2015 ◽  
Vol 30 (5) ◽  
pp. 536-551 ◽  
Author(s):  
Sudarshan Kumar ◽  
Shrikant Gorane ◽  
Ravi Kant
Keyword(s):  
Questionnaire Survey ◽  
Supplier Selection ◽  
Design Methodology ◽  
Selection Process ◽  
Model Development ◽  
Top Management ◽  
Content Type ◽  
Micmac Analysis ◽  
Fuzzy Micmac ◽  
Practical Implications

Purpose – The purpose of this paper is to present an approach to successful supplier selection process (SSP) by understanding the dynamics between SSP enablers (SSPEs), using interpretive structure modelling (ISM) methodology and find out driving and the dependence power of enablers, using fuzzy MICMAC (Matriced’ Impacts Croisés Appliquée á un Classement) analysis. Design/methodology/approach – The group of experts from industries and the academics were consulted and ISM is used to develop the contextual relationship among various SSPEs for each dimension of supplier selection. The results of the ISM are used as an input to the fuzzy MICMAC analysis to identify the driving and the dependence power of SSPEs. Findings – The research presents a hierarchy-based model and mutual relationships among SSPEs. The research shows that there is a group of SSPEs having a high driving power and low dependence, which requires maximum attention and is of strategic importance, while another group consists of those SSPEs that have high dependence and low driving power, which requires the resultant actions. Research limitations/implications – The weightage obtained for the ISM model development and fuzzy MICMAC are obtained through the judgment of academician and few industry experts. It is the only subjective judgment and any biasing by the person who is judging the SSPEs might influence the final result. A questionnaire survey can be conducted to catch the insight on these SSPEs from more organizations. Practical implications – This category provides a useful tool for top management to differentiate between independent and dependent SSPEs and their mutual relationships which would help them to focus on those key SSPEs that are most significant for effective supplier selection. Originality/value – Arrangement of SSPEs in a hierarchy, the categorization into the driver and dependent categories, and fuzzy MICMAC are an exclusive effort in the area of supplier selection.

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