Supplier Selection Process Research Articles

Optimizing Supplier Selection using Fuzzy MCDM

This study explores the supplier selection problem within technology manufacturing by employing the Fuzzy Analytic Hierarchy Process (FAHP). Data was collected from a technology manufacturing company, and expert evaluations were sought from professionals with over 10 years of experience in the industry. The criteria considered for supplier selection included profitability of the supplier (C1), relationship closeness (C2), technological capability (C3), conformance quality (C4), and conflict (C5). The FAHP results indicated that relationship closeness (C2) ranked highest among the criteria, highlighting its significance in the supplier selection process, while conflict (C5) received the lowest ranking. These findings emphasize the importance of nurturing strong relationships with suppliers and vendors to enhance overall supply chain performance. The proposed FAHP model effectively addresses the complexities and uncertainties inherent in supplier evaluation, offering a robust decision-making tool tailored to the specific needs of technology manufacturing companies

Z-NUMBERS BASED MODELING OF GROUP DECISION MAKING FOR SUPPLIER SELECTION IN MANUFACTURING SYSTEMS

The health of the supply chain, the company's performance, and the quality of the production as well as the success of the entire enterprise, directly depends on the reliability of the company's existing suppliers. Processing enterprises that depend on suppliers are trying to find the best option that will satisfy all customer requirements. With high-quality and inexpensive raw materials, the products produced by the enterprise will largely determine its economic indicators such as revenue, profit, and profitability. Therefore, this enterprise is especially faced with the issue of choosing the most appropriate supplier of resources. Basically, for processing enterprises it is very important to consider the parameters such as quality of incoming materials, terms of supply of raw materials, price of received raw materials, terms of contracts. The challenge in determining of supplier is how to choose reliable suppliers that can maintain supply chain continuity in an environment of ever-increasing instability and uncertainty. For this purpose, a methodology for selecting suppliers using Z-numbers was proposed. Using fuzzy Z numbers in supplier selection, decision-makers can assign values to various criteria in a way that reflects both the uncertainty and the confidence associated with those values. This can lead to more nuanced and robust supplier selection processes, considering a wider range of factors and uncertainties.

Perancangan Sistem Pendukung Keputusan Pemilihan Supplier dengan Metode Analytical Hierarchy Process (AHP) Pada CV. Safina Abadi

The contractor industry, including CV Safina Abadi, has a significant need for selecting the right suppliers to ensure smooth project execution. Optimal supplier selection can affect various critical aspects of a construction project, such as product quality, availability, competitive pricing, service, and reputation. However, due to the numerous supplier options available, companies often face difficulties in evaluating and choosing the most suitable supplier based on their needs and criteria. Therefore, utilizing a Decision Support System (DSS) with the Analytical Hierarchy Process (AHP) method presents an effective solution to assist companies in the supplier selection process. By employing AHP, companies can model a hierarchy of selection criteria, from main criteria down to more detailed sub-criteria. AHP further enables companies to measure and compare the relative weights of each criterion and sub-criterion, providing recommendations for the most optimal supplier based on the company's preferences and requirements. This research aims to design and implement a Decision Support System using the AHP method to assist in supplier selection for CV Safina Abadi. It is hoped that this study will contribute to improving the efficiency and effectiveness of supplier selection, thereby enhancing overall project performance in the construction industry.

Revolutionizing Sourcing with AI: Harnessing Technology for Unprecedented Efficiency and Savings

Artificial Intelligence (AI) is transforming the landscape of sourcing, providing unprecedented efficiency and cost savings. This paper explores how AI technologies such as machine learning, natural language processing, and predictive analytics are revolutionizing sourcing processes. We examine case studies across various industries, highlighting the impacts of AI on supply chain optimization, supplier selection, and procurement processes. The findings indicate significant improvements in operational efficiency, decision-making accuracy, and financial performance. For instance, a leading automotive manufacturer reduced procurement costs by 20% using AI-driven sourcing (Smith et al., 2020), while a global retail giant increased supplier quality by 25% through AI-enhanced evaluation (Johnson et al., 2019). Additionally, a healthcare provider optimized inventory management, resulting in a 10% reduction in inventory costs (Williams and Brown, 2021). Future research directions and practical implications for AI-driven sourcing are also discussed, emphasizing the potential for continued innovation and growth in this field. The challenges and opportunities associated with AI implementation in sourcing are addressed, highlighting the need for quality data, integration with existing systems, and skilled personnel to manage AI technologies.

The predicting role of sustainable supplier selection on lead-time performance in public procurement: relational capability as a moderator

PurposeWith increasing concerns regarding the performance of public procurement, especially concerning timely delivery, this study aims to investigate the predictive role of sustainable supplier selection (SSS) in enhancing lead-time performance in public procurement, while also examining the moderating effect of relational capability.Design/methodology/approachThe study collected primary data from 179 accredited public organizations in Tanzania through structured questionnaires and used partial least squares structural equation modeling for data analysis.FindingsThe results reveal that SSS and relational capability influence lead-time performance in public procurement. Regarding the moderating effect of relational capability, the study establishes that relational capability strengthens the influence of SSS on lead-time performance. Therefore, based on the collected data from surveyed public organizations, relational capability positively moderates the relationship between SSS and lead-time performance in public procurement.Social implicationsThe study offer valuable implications for public procurement practitioners, academics and other stakeholders. Public organizations should consider contemplate integrating sustainability aspects into supplier selection processes. Furthermore, the study contributes to advancing efforts toward achieving sustainable development goals (i.e. SDG12) within Tanzania, particularly by advocating for sustainable public procurement practices aligned with national policies and priorities.Originality/valueThis study not only enhances the understanding of public procurement performance by investigating lead-time improvement, incorporating considerations of SSS and relational capability, but it also offers empirical evidence of the moderating role of relational capability within the unexplored Tanzanian context.

Comparison of MAGIQ, MABAC, MARCOS, and MOORA Methods in Multi-Criteria Problems

Determining the best alternative from many criteria is one of the core problems in decision making, both routine and non-routine problems. One of them is in the problem of determining egg suppliers. Eggs are one of the basic needs of the community so that the demand for eggs is always increasing, this makes the emergence of many egg agents in distributing and fulfilling needs. Selective and careful selection is needed in order to get a supplier that meets the desired expectations. Problems then arise in the selection of egg suppliers that are not in accordance with the expectations of the manager. In determining egg suppliers that have been carried out by UD Taluh Subur, only by means of a simple comparison between several factors such as price, production quantity, and quality without considering other factors. In addition to this, business managers have limited knowledge in statistical and business decision making. To optimize the supplier selection process, a Decision Support System can be used to help provide recommendations for selecting prospective suppliers of fixed eggs. Based on the situation of decision makers who have limited knowledge in statistical decision making, the MAGIQ method is suitable for weighting. To provide a more accurate ranking, additional methods such as the MABAC, MARCOS, and MOORA methods are used. The purpose of this research is to focus on which method is most recommended for the case study faced in the research based on the analysis results of the sensitivity test. The results of the sensitivity test show that the MAGIQ-MABAC method has the highest value of 4.42737%, then the MAGIQ-MOORA method with a value of 2.34415% and the MAGIQ-MARCOS method with a value of 0.45729%.

A hybrid multi-criteria decision-making and machine learning approach for explainable supplier selection

Supplier selection has become increasingly complex regarding selection criteria caused by expanded data collection processes and supplier numbers due to globalisation effects. This complexity has led to the consideration of Artificial Intelligence (AI) techniques to facilitate and enhance supplier selection. However, the AI techniques most often applied are unfamiliar to stakeholders and have limited explainability, posing a significant barrier to adopting intelligent approaches in supply chains. To address this issue, we propose a hybrid supplier selection framework that combines interpretable data-driven AI techniques with multi-criteria decision-making (MCDM) approaches: the former aims to reduce the complexity of the supplier selection problem, while the latter ensures familiarity to supply chain stakeholders by retaining MCDM at the heart of the supplier selection process. The framework is validated through two real-world case studies supporting supplier selection decisions in oil, gas, and aerospace manufacturing companies. Preliminary results from our case studies suggest that the framework can achieve comparable performance to approaches utilising only machine learning while offering the added benefits of end-to-end explainability and increased familiarity.

Finding the right one: understanding the supplier selection process of social enterprises

PurposeThis study aims to develop an in-depth understanding of how supplier selection helps social enterprises achieve their social missions while maintaining commercial viability.Design/methodology/approachThe paper applies a multiple-case design to study the supplier selection processes of 15 Dutch social enterprises.FindingsSocial enterprises tend to build supply relationships through existing networks and evaluate suppliers based on value alignment, relationship commitment, resource complementarity, and cost. Depending on the possibility of social value creation in supplier selection, the importance of these criteria varies across different social enterprise models and between key and non-key suppliers. Moreover, suppliers’ long-term relationship commitment can help reconcile tensions between the social and commercial logic of a social enterprise and facilitate impact creation.Research limitations/implicationsData collection is limited to the perspectives of buyers – the social enterprises. Future research could collect supplier-side data to explore how they engage with social enterprises during the selection process.Practical implicationsManagers of social enterprises can use our research findings as guidance for selecting the most suitable suppliers, while organizations that want to collaborate with social enterprises should actively build network ties to be identified.Originality/valueWe contribute to the cross-sector collaboration literature by showing the underlying reasons for the preference for network reinforcing and indirect networking in supplier identification. We contribute to the social impact supply chain literature by revealing the critical role of supplier selection in shaping collaboration outcomes.

Navigating Supply Chain Resilience: A Hybrid Approach to Agri-Food Supplier Selection

Globalization and multinational commerce have increased the dynamism and complexity of supply networks, thereby increasing their susceptibility to disruptions along interconnected supply chains. This study aims to tackle the significant concern of supplier selection disruptions in the Thai agri-food industry as a response to the aforementioned challenges. A novel supplier evaluation system, PROMETHEE II, is suggested; it combines the Fuzzy Analytical Hierarchy Process (FAHP) with inferential statistical techniques. This investigation commences with the identification of critical indicators of risk in the sustainable supply chain via three phases of analysis and 315 surveys of management teams. Exploratory factor analysis (EFA) is utilized to ascertain six supply risk criteria and twenty-three sub-criteria. Following this, the parameters are prioritized by FAHP, whereas four prospective suppliers for an agricultural firm are assessed by PROMETHEE II. By integrating optimization techniques into sensitivity analysis, this hybrid approach improves supplier selection criteria by identifying dependable solutions that are customized to risk scenarios and business objectives. The iterative strategy enhances the resilience of the agri-food supply chain by enabling well-informed decision-making amidst evolving market dynamics and chain risks. In addition, this research helps agricultural and other sectors by providing a systematic approach to selecting low-risk suppliers and delineating critical supply chain risk factors. By bridging complexity and facilitating informed decision-making in supplier selection processes, the results of this study fill a significant void in the academic literature concerning sustainable supply chain risk management.

Influence of Procurement Process on Availability of Essential Drugs in Public Health Facilities in Mombasa County, Kenya

Purpose: Procurement process and practices are crucial components in the successful realization of universal healthcare and in particular the availability of essential drugs. Despite multifaceted efforts and inputs to promote the quality of the procurement process challenges still exists in the availability of essential drugs. This study aimed to establish the influence of procurement planning, supplier selection, procurement financing and needs assessment on availability of essential drugs in the public health facilities in Mombasa County, Kenya. This was a cross-sectional descriptive study design which targeted level 4 and 5 health facilities in Mombasa County. The study target population was 1216 health workers who included medical laboratory personnel, clinical officers and medical officers, nurses, pharmacists and pharmaceutical technologists. The study sample was 301. Methodology: Stratified sampling approach was used to distribute the sample among the cadre and random sampling method was used to select the respondents from each strata. Quantitative data was collected using a structured questionnaire. Findings: The study found that procurement planning, supplier selection, procurement, financing and needs assessment were significant factors in influencing the availability of essential drugs with P<0.05. Unique Contribution to Theory, Policy and Practice: The study recommended that counties conduct a comprehensive and regular need assessment of essential drugs in public health facilities, that they develop a robust procurement planning strategy that aligns with the identified needs and available financing, that there should be a transparent and competitive supplier selection process, and to establish strategic partnerships with international organizations, non-governmental organizations, or donor agencies that are committed to improving healthcare access.

Strategies to Enhance the Productivity of an Automotive Company Throughout the Supplier Selection Process Method

The study aims to determine strategies for selecting suppliers to improve productivity at the automotive company. Supplier selection methods are vital for purchasing and procurement departments, as they directly influence organizational success. By carefully assessing suppliers, these departments can ensure cost efficiency by negotiating favorable terms and prices and guaranteeing high-quality products or services that meet established standards. By employing qualitative research methods, the research scrutinizes the criteria, decision-making processes, and challenges in selecting suppliers through analysis of the methods. The result indicates that the Fuzzy AHP emerges as the most prominent method. The findings of this research contribute to the existing body of knowledge by offering valuable insights and practical implications for improving supplier selection processes within automotive companies. This research identifies and ranks criteria for supplier selection and monitoring, as well as explains where supplier selection strategies could be improved, with the ultimate goal of improving supply chain management and overall organizational performance in the automotive sector

ROLE OF ARTIFICIAL INTELLIGENCE (AI) IN ENHANCING OPERATIONAL EFFICIENCY IN MANUFACTURING MEDICAL DEVICES

Artificial Intelligence (AI) plays a crucial role in enhancing operational efficiency in manufacturing medical devices by revolutionizing various aspects of the production process. The integration of Artificial Intelligence (AI) technologies within the manufacturing processes of medical devices has significantly transformed operational efficiency. This abstract delves into the pivotal role of AI in optimizing various aspects of manufacturing medical devices, ranging from design and production to quality control and maintenance. AI-driven design methodologies enable the creation of complex medical devices with enhanced functionality and precision. Machine learning algorithms assist in analysing vast datasets related to materials, performance metrics, and user feedback, facilitating the development of innovative device prototypes. In manufacturing, AI optimizes production workflows by predicting demand, managing inventory, and automating assembly processes. Predictive maintenance powered by AI ensures the continuous functionality of manufacturing equipment, reducing downtime and operational costs. Quality control is strengthened through AI-enabled inspection systems that can detect microscopic defects and ensure compliance with stringent regulatory standards. Real-time monitoring of manufacturing processes using AI-driven analytics enhances product consistency and minimizes errors. Furthermore, AI enhances supply chain management by optimizing logistics, procurement, and supplier selection processes, ensuring timely delivery of components and materials essential for medical device manufacturing.AI-driven technologies revolutionize medical device manufacturing through enhanced quality control, predictive maintenance, process optimization, supply chain efficiency, regulatory compliance, customization, cost reduction, and data-driven decision support, optimizing reliability and efficiency while ensuring regulatory standards.

Analysis Of The Purchasing Mechanism For The Procurement Process Of Housekeeping Department Goods At The Four Pointby Sheraton Hotel Medan

The purpose of this study is to describe and explain the role of Purchasing in procuring goods at Four Point by Sheraton Medan Hotel. The results of the research are expected to be a reference and consideration for the Finance Department and more precisely for the Purchasing Department regarding the role of Purchasing in the procurement of Housekeeping Department goods. Purchasing is an important part of an organization where Purchasing's job is to provide all thegoods needed by the company starting from physical goods, services and services This type of research uses case studies of data collected by observation, interviews, documentation,and literature study techniques. The variables are the Purchasing Mechanism and Procurement of Goods (Y). this research itself uses a qualitative approach with descriptive analysis. The results of the analysis of observations and interviews conducted with Mr. Agus as Purchasing Officer stated that the role of Purchasing in the process of ordering goods, procuring goods, and distributing Housekeeping Department goods must be in accordance with the Standard Operational Procedure (SOP). In the Supplier selection process must be carried out in a transparent manner and must have at least 3 suppliers in order to avoid the unavailability of goods requested by the user. Behind that in order to minimize sudden requests made by users, of course this will help the work / activities of a Purchasing without having to make direct purchases.

A two-stage decision model for sustainable-resilient supplier selection and order allocation under uncertain environment

PurposeThe paper aims to propose an innovative two-stage decision model to address the sustainable-resilient supplier selection and order allocation (SSOA) problem in the single-valued neutrosophic (SVN) environment.Design/methodology/approachFirst, the sustainable and resilient performances of suppliers are evaluated by the proposed integrated SVN-base-criterion method (BCM)-an acronym in Portuguese of interactive and multi-criteria decision-making (TODIM) method, with consideration of the uncertainty in the decision-making process. Then, a novel multi-objective optimization model is formulated, and the best sustainable-resilient order allocation solution is found using the U-NSGA-III algorithm and TOPSIS method. Finally, based on a real-life case in the automotive manufacturing industry, experiments are conducted to demonstrate the application of the proposed two-stage decision model.FindingsThe paper provides an effective decision tool for the SSOA process in an uncertain environment. The proposed SVN-BCM-TODIM approach can effectively handle the uncertainties from the decision-maker’s confidence degree and incomplete decision information and evaluate suppliers’ performance in different dimensions while avoiding the compensatory effect between criteria. Moreover, the proposed order allocation model proposes an original way to improve sustainable-resilient procurement values.Originality/valueThe paper provides a supplier selection process that can effectively integrate sustainability and resilience evaluation in an uncertain environment and develops a sustainable-resilient procurement optimization model.

The Effect of Procurement Practices on the Public Project Performance: The Case of North Showa Zone, Oromiya Region, Ethiopia

The overall objective of this study was to assess the effects of procurement practices on the performance of public projects in the case of North Shoa Zone. The specific objectives of the study were, to find out the effects of procurement planning, supplier selection process, procurement contract management and procurement staff competency on the performance of projects. The study took a quantitative research approach and explanatory research design. A census sampling technique was employed to select 114 employees related to project procurement practices and project management as respondents. All of the questionnaires were submitted back for analysis, representing a response rate of 100%. A structured questionnaire was administered to collect data from the respondents. The data was finally analyzed using Statistical Package for Social Sciences (SPSS) V.28 to compute descriptive statistics such as the mean and standard deviation and inferential statistics like Pearson’s correlation analysis to obtain findings vital for the research study. In addition, regression analyses were conducted to estimate the average effects of procurement practices on public project performance. Majority of the respondents indicated that procurement practices affect project performance to a large extent. The regression analysis result indicated that procurement planning, supplier selection process, procurement contract management, and procurement staff competency had significant positive influence on performance of projects. The analysis further revealed that the four independent variables in this study accounted for around 68 % of change in project performance. It therefore recommended that implementing procurement practices effectively helps to improves projects performance.

Achieving sustainability in manufacturing: the nexus of green supplier selection, green performance and outcome and process controls

PurposeThe principal research objective entails examining the nexus between green supplier selection and green performance while scrutinizing the moderating role of governance mechanisms, specifically process control and outcome control, in shaping this association.Design/methodology/approachTo assess our hypotheses, this study obtained data from Chinese manufacturing sectors and utilized regression analysis on a dataset consisting of 295 samples.FindingsThis study enriches the sustainable supply chain management literature by emphasizing the influence of green supplier selection on a firm’s green performance and the moderating effects of outcome and process control, offering practical insights for industry professionals.Originality/valueThis study enriches the sustainable supply chain management literature by emphasizing the influence of supplier selection on a firm’s environmental performance and the moderating effects of outcome and process control, offering practical insights for industry professionals.

Sourcing for high technology innovation: Engaging to absorb knowledge pre-contract

This study investigates how firms can identify, access, and capitalize on viable innovation in the high technology supply market during the pre-contractual phase of relationships. The industrial landscape is changing rapidly due to technological advancements like automation and electrification, leading traditional industries to explore new avenues for knowledge and partner selection. However, identifying, assessing, and trusting suppliers with whom firms can enter a relationship is a complex task. Therefore, the study adopts the absorptive capacity perspective for conceptualizing the supplier selection process, focusing on the pre-contractual phase. Based on two in-depth case studies in the automotive industry, we find that supplier selection can be assisted with higher levels of engagement, coordination, and alignment internally with different firm stakeholders and externally with the larger supply market. This study illustrates that new actors bring disruptive innovation into the automotive industry, and the knowledge is absorbed during supplier selection, facilitated by fostering higher levels of engagement, coordination, and alignment both internally among various stakeholders within the firm and externally within the broader supply market. This study significantly advances the understanding of supplier selection practices in the context of high technology innovation. The theoretical contributions made through our empirical investigations enhance the knowledge base on sourcing strategies, shed light on the complexities of supplier selection, and offer practical implications for firms aiming to navigate the rapidly changing landscape of technological advancements.

Strategic supplier selection and order allocation for sustainable development of small and medium-sized enterprises: insights from a case study

Purpose Efforts to implement supplier selection and order allocation (SSOA) approaches in small and medium-sized enterprises (SMEs) are quite restricted due to the lack of affordable and simple-to-use strategies. Although there is a huge amount of literature on SSOA techniques, very few studies have attempted to address the issues faced by SMEs and develop strategies from their point of view. The purpose of this study is to provide an effective, practical, and time-tested integrated SSOA framework for evaluating the performance of suppliers and allocating orders to them that can improve the efficiency and competitiveness of SMEs. Design/methodology/approach This study was conducted in two stages. First, an integrated supplier selection approach was designed, which consists of the analytic hierarchy process and newly developed measurement alternatives and ranking using compromise solution to evaluate supplier performance and rank them. Second, the Wagner-Whitin algorithm is used to determine optimal order quantities and optimize inventory carrying and ordering costs. The joint impact of quantity discounts is also evaluated at the end. Findings Insights derived from the case study proved that the proposed approach is capable of assisting purchase managers in the SSOA decision-making process. In addition, this case study resulted in 10.89% total cost savings and fewer stock-out situations. Research limitations/implications Criteria selected in this study are based on the advice of the managers in the selected manufacturing organizations. So the methods applied are limited to manufacturing SMEs. There were some aspects of the supplier selection process that this study could not explore. The development of an effective, reliable supplier selection procedure is a continuous process and it is indeed certainly possible that there are other aspects of supplier selection that are more crucial but are not considered in the proposed approach. Practical implications Purchase managers working in SMEs will be the primary beneficiaries of the developed approach. The suggested integrated approach can make a strategic difference in the working of SMEs. Originality/value A practical SSOA framework is developed for professionals working in SMEs. This approach will help SMEs to manage their operations effectively.

Profound changes in global sourcing? The country of origin theory and its effects on sourcing decisions

PurposeThis study aims to examine decision factors for global sourcing, differentiated into transcontinental and continental sourcing to obtain insight into locational aspects of sourcing decisions and global trends. This study analyzed various country perceptions to reveal their influence on sourcing decisions. The country of origin (COO) theory explains why certain country perceptions and images influence purchasing experts in their selection of suppliers.Design/methodology/approachThis study used a two-study approach. In Study 1, the authors conducted discrete choice card experiments with 71 purchasing experts located in Europe and the USA to examine the importance of essential decision factors for global sourcing. Given the clear evidence that location is a factor in sourcing decisions, in Study 2 the authors investigated purchasers’ perceptions and images of countries, adding country ranking experiments on various perceived characteristics such as quality, price and technology.FindingsStudy 1 provides evidence that the purchasers’ personal relationship with the supplier plays a decisive role in the supplier selection process. While product quality and location impact sourcing decisions, the attraction of the buying company and cultural barriers are less significant. Interestingly, however, these factors seem as important as price to respondents. This implies that a strong relationship with suppliers and good quality products are essential aspects of a reliable and robust supply chain in the post-COVID-19 era. Examining the locational aspect in detail, Study 2 linked the choice card experiments with country ranking experiments. In this study, the authors found that purchasing experts consider that transcontinental countries such as Japan and China offer significant advantages in terms of price and technology. China has enhanced its quality, which is recognizable in the country ranking experiments. Therefore, decisions on global sourcing are not just based on such high-impact factors as price and availability; country perceptions are also influential. Additionally, the significance of the locational aspect could be linked to certain country images of transcontinental suppliers, as the COO theory describes.Originality/valueThe new approach divides global sourcing into transcontinental and European sourcing to evaluate special decision factors and link these factors to the locational aspect of sourcing decisions. To deepen the clear evidence for the locational aspect and investigate the possible influence of country perceptions, the authors applied the COO theory. This approach enabled authors to show the strong influence of country perception on purchasing departments, which is represented by the locational effect. Hence, the success of transcontinental countries relies not only on factors such as their availability but also on the purchasers’ positive perceptions of these countries in terms of technology and price.

An Exploratory Examination of Sustainable Food Purchasing by Restaurants in Paris, France, by Product Category

While executive chefs invariably search for consistent quality, reliable delivery and a competitive price, few studies have sought to demonstrate how the importance of the supplier selection criteria differs by product category for sustainable food ingredients. For this study, 49 executive chefs in Paris, France, were interviewed using a structured questionnaire to explore the importance of the criteria chefs employed in purchasing five groups of food products: meat, fish, fresh fruit and vegetables, dairy products and baked products. Cluster analysis revealed the presence of two distinctly different groups of chefs: those who were primarily concerned about price and those who sought to purchase sustainably produced food ingredients. For those chefs purchasing primarily on price, there were no significant differences in the importance of the criteria utilized in the supplier selection process across the five product categories. However, for those chefs who sought to buy sustainably produced food ingredients, sourcing product from a desired geographic region was significantly less important for baked products. Similarly, in considering whether the food ingredients had been produced ethically and grown locally and sustainably, each of these criteria were ranked significantly lower for baked products than any other food category. Conversely, the availability of products all year round, proximity to the restaurant and the physical appearance of the product were all ranked significantly higher for baked products than any other food category.