Integrated Procurement Planning in Multi‐division Firms

For large multi‐division firms, coordinating procurement policies across multiple divisions to leverage volume discounts from suppliers based on firm‐wide purchasing power can yield millions of dollars of savings in procurement costs. Coordinated procurement entails deciding which suppliers to use to meet each division's purchasing needs and sourcing preferences so as to minimize overall purchasing, logistics, and operational costs. Motivated by this tactical procurement planning problem facing a large industrial products manufacturer, we propose an integrated optimization model that simultaneously considers both firm‐wide volume discounts and divisional ordering and inventory costs. To effectively solve this large‐scale integer program, we develop and apply a tailored solution approach that exploits the problem structure to generate tight bounds. We identify several classes of valid inequalities to strengthen the linear programming relaxation, establish polyhedral properties of these inequalities, and develop both a cutting‐plane method and a sequential rounding heuristic procedure. Extensive computational tests for realistic problems demonstrate that our integrated sourcing model and solution method are effective and can provide significant economic benefits. The integrated approach yields average savings of 7.5% in total procurement costs compared to autonomous divisional policies, and our algorithm generates near‐optimal solutions (within 0.75% of optimality) within reasonable computational time.     

Supplier competition and its impact on firm׳s sourcing strategy

Most research on firms׳ sourcing strategies assumes that wholesale prices and reliability of suppliers are exogenous. It is of our interest to study suppliers׳ competition on both wholesale price and reliability and firms׳ corresponding optimal sourcing strategy under complete information. In particular, we study a problem in which a firm procures a single product from two suppliers, taking into account suppliers׳ price and reliability differences. This motivates the suppliers to compete on these two factors. We investigate the equilibria of this supplier game and the firm׳s corresponding sourcing decisions. Our study shows that suppliers׳ reliability often plays a more important role than wholesale price in supplier competition and that maintaining high reliability and a high wholesale price is the ideal strategy for suppliers if multiple options exist. The conventional wisdom implies that low supply reliability and high demand uncertainty motivate dual-sourcing. We notice that when the suppliers׳ shared market/transportation network is often disrupted and demand uncertainty is high, suppliers׳ competition on both price and reliability may render the sole-sourcing strategy to be optimal in some cases that depend on the format of suppliers׳ cost functions. Moreover, numerical study shows that when the cost or vulnerability (to market disruptions) of one supplier increases, its profit and that of the firm may not necessarily decrease under supplier competition.     

Price and Service Competition in an Outsourced Supply Chain

We consider a buyer who outsources the manufacturing of a product to multiple symmetric make‐to‐stock suppliers who compete on price and service (fill rate). The buyer allocates demand to the suppliers using a score function with an exponential form, which specifies the relative importance of price vs. service, in order to minimize his costs, while the suppliers choose their prices and fill rates to maximize their profits. For the case of dual‐sourcing, we characterize the optimal parameter of the exponential score function, considering the impact of the buyer's decisions on the suppliers, and considering how the suppliers compete against each other to earn a portion of the buyer's demand. We prove the existence of a unique equilibrium and characterize the equilibrium behavior of the system. We then consider a general number of suppliers and show that the equilibrium prices and fill rates, and the buyer's cost, are increasing in the number of suppliers. We compare these results to a model of single‐sourcing, in which the buyer is the Stackelberg leader and extracts all profits from the supplier. We find that the buyer always prefers single‐sourcing to multisourcing. Finally, we study a centralized system and use the results to develop a coordinating contract for the decentralized system.     

Production systems and supplier selection: a multi-phase process model

Abstract

Purpose: This paper presents a combined multi-phase supplier selection model. The process repeatedly revisits the criteria and sourcing decision as the development process continues. This enables a structured adoption of product and production system innovation from strategic suppliers, where previously the literature purely focuses on product innovation or cost reduction. Design/methodology/approach: The authors adopted an embedded researcher style, inductive, qualitative case study of an industrial supply cluster comprising a focal automotive company and its interaction with three different strategic stamping suppliers. Findings: Our contribution is the multi-phased production and product innovation process. This is an advance from traditional supplier selection and also an extension of ideas of supplier-located product development as it includes production system development, and complements the literature on working with strategic suppliers. Specifically, we explicitly articulate the previously unreported issue of whether a supplier chosen for its innovation capabilities at the start of the new product development process will also be the most appropriate supplier during the production system development phase, when an ability to work collaboratively may be the most important attribute, or in the large-scale production phase when an ability to manufacture at low unit cost may be most important. Originality/value: The paper identifies a multi-phase approach to tendering within a fixed body of strategic suppliers which seeks to identify the optimum technological and process decisions as well as the traditional supplier sourcing choice. These areas have not been combined before and generate a valuable approach for firms to adopt as well as for researchers to extend our understanding of a highly complex process.     

AN EMPIRICAL EXAMINATION OF THE UNDERLYING DIMENSIONS OF PURCHASING COMPETENCE

The importance of evaluating the effectiveness of the purchasing function in firms along multiple criteria has attracted considerable attention. However, few studies have identified the defining elements that constitute purchasing competence. This paper introduces the construct of purchasing competence using a second‐order factor structure derived from purchasing practices identified from the literature. The validity of the construct (purchasing competence) is tested using data from a sample of 179 firms. The results indicate (1) the construct validity of purchasing competence and (2) the predictive validity of purchasing competence, which has a significant positive influence on total quality management performance and customer satisfaction. The implications of these findings for additional research are discussed.     

Global sourcing in integrated network structures: The case of hybrid purchasing organizations

An issue for companies in globally competitive markets is to adapt their organizational structures and governance in increasingly complex organizations. At the functional level of purchasing, companies are turning to hybrid purchasing organizations in order to leverage global sourcing benefits. One of the key challenges in this context is to distinguish between categories to be integrated across sites and those that are to remain under the authority of each purchasing location in order to maximize purchasing synergies.This paper presents a purchasing portfolio model that provides a comprehensive view of relevant global synergy dimensions. Based on a literature review, a theoretically-grounded purchasing portfolio model for global sourcing is developed. The theoretical basis stems from information processing theory, organizational buying behavior (OBB) and transaction cost economics. The validity of the model is explored by means of case study research. Complementing the extant literature, the theoretical contribution of the paper lies in not only addressing category selection criteria for exploiting economies of scale, but also for economies of information and learning and economies of process. Furthermore, it provides insights regarding integrated network coordination mechanisms at the functional level of purchasing.     

Consumer preference analysis: A data-driven multiple criteria approach integrating online information

Multiple criteria approaches can assist the product manager to know the consumer preferences in the context of e-commerce. Consumer preference analysis explains what aspects of a product affect and how they affect a consumer’s purchasing decision. This issue plays an important role in e-commerce platforms from its relevance in marketing decisions such as advertisements, recommendations and promotions. In this regard, we propose a data-driven multiple criteria decision aiding (MCDA) approach to integrate online information, such as explicit (e.g., reviews and ratings) and implicit (e.g., clicks and purchases) feedback from consumers. However, MCDA approaches present a critical challenge that even an experienced product manager could find it difficult to pre-define the criteria on which a product is evaluated. To address this issue, our proposed approach first utilizes text-mining techniques to assist the product manager identify the criteria, and then determines and collects the relative importance of the criteria and their values. Given the criteria information, we use a sampling process to provide two indices, the consumer preference index and rank acceptability index. The first index helps in prioritizing the pairwise comparisons of products, while the second one helps in deriving a default ranking list for first-time-registered consumers. We record the products viewed by consumers and generate their preference information in the form of pairwise comparisons for analyses within an aggregation-disaggregation paradigm. We also provide a representative value function to help the product manager gain insight into the preferences. Finally, we describe how a real-world application including the product manager and consumers exploits the proposed approach on an e-commerce platform to take a large step toward aiding more realistic and data-driven multiple criteria decision making.     

THE IMPACT OF LOCAL CONTENT RULES ON GLOBAL SOURCING DECISIONS

Many governments have established, for various reasons, local confent purchasing rules for companies that wish to operate in their country. These requirements force firms to purchase a certain amount of components from suppliers located in that country. This paper describes local content rules and develops models to select suppliers while satisfying local content provisions. The single plant model can be transformed into a knapsack problem that is solved by a ranking procedure, and the solution provides insight as to the manner in which local content rules impact more generalized models. Furthermore, we illustrate possible negative effects to local industry that may result when governments set the local content percentage too high, and we discuss methods for companies to circumvent local content rules. Finally, we address the issue of local content rules in the context of multi-plant global sourcing decisions, and we provide an efficient solution procedure for the classical plant location model extended to include local content rules at each site     

Examining the Impact of Interorganizational Systems on Process Efficiency and Sourcing Leverage in Buyer–Supplier Dyads

Manufacturing firms are increasingly seeking cost and other competitive advantages by tightly coupling and managing their relationship with suppliers. Among other mechanisms, interorganizational systems (IOS) that facilitate boundary‐spanning activities of a firm enable them to effectively manage different types of buyer–supplier relationships. This study integrates literature from the operations and information systems fields to create a joint perspective in understanding the linkages between the nature of the IOS, buyer–supplier relationships, and manufacturing performance at the dyadic level. External integration, breadth, and initiation are used to capture IOS functionality, and their effect on process efficiency and sourcing leverage is examined. The study also explores the differences in how manufacturing firms use IOS when operating under varying levels of competitive intensity and product standardization. In order to test the research models and related hypothesis, empirical data on buyer–supplier dyads is collected from manufacturing firms. The results show that only higher levels of external integration that go beyond simple procurement systems, as well as who initiates the IOS, allow manufacturing firms to enhance process efficiency. In contrast, IOS breadth and IOS initiation enable manufacturing firms to enhance sourcing leverage over their suppliers. In addition, firms making standardized products in highly competitive environments tend to achieve higher process efficiencies and have higher levels of external integration. The study shows how specific IOS decisions allow manufacturing firms to better manage their dependence on the supplier for resources and thereby select system functionalities that are consistent with their own operating environments and the desired supply chain design.     

A Multi‐Supplier Sourcing Problem with a Preference Ordering of Suppliers

We study a sourcing problem faced by a firm that seeks to procure a product or a component from a pool of alternative suppliers. The firm has a preference ordering of the suppliers based on factors such as their past performance, quality, service, geographical location, and financial strength, which are commonly included in a supplier scorecard system. Thus, the firm first uses available inventory from supplier 1, if any, then supplier 2, if any, and so on. The suppliers differ in costs and prices. The buyer firm seeks to determine which suppliers to purchase from and in what quantities to maximize its total expected profit subject to the preference ordering constraint. We present the optimal solution to this problem, and show that it has a portfolio structure. It consists of a sub‐set of suppliers that are ordered by their underage and overage costs. This portfolio achieves a substantial profit gain compared to sourcing from a unique supplier. We present an efficient algorithm to compute the optimal solution. Our model applies to component sourcing problems in manufacturing, merchandizing problems in retailing, and capacity reservation problems in services.     

Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing

This paper presents a stochastic mixed integer programming approach to integrated supplier selection and customer order scheduling in the presence of supply chain disruption risks, for a single or dual sourcing strategy. The suppliers are assumed to be located in two different geographical regions: in the producer's region (domestic suppliers) and outside the producer's region (foreign suppliers). The supplies are subject to independent random local disruptions that are uniquely associated with a particular supplier and to random semi-global (regional) disruptions that may result in disruption of all suppliers in the same geographical region simultaneously. The domestic suppliers are relatively reliable but more expensive, while the foreign suppliers offer competitive prices, however material flows from these suppliers are more exposed to unexpected disruptions. Given a set of customer orders for products, the decision maker needs to decide which single supplier or which two different suppliers, one from each region, to select for purchasing parts required to complete the customer orders and how to schedule the orders over the planning horizon, to mitigate the impact of disruption risks. The problem objective is either to minimize total cost or to maximize customer service level. The obtained combinatorial stochastic optimization problem will be formulated as a mixed integer program with conditional value-at-risk as a risk measure. The risk-neutral and risk-averse solutions that optimize, respectively average and worst-case performance of a supply chain are compared for a single and dual sourcing strategy and for the two different objective functions. Numerical examples and computational results are presented and some managerial insights on the choice between the two sourcing strategies are reported.     

Global Multisourcing Strategy: The Emergence of a Supplier Portfolio in Services Offshoring

In today's global services outsourcing arena, increasing numbers of companies adopt “multisourcing,” that is, they select and combine information technology (IT) and business services from multiple providers. The literature on IT outsourcing and supply chain management has identified critical tradeoffs involved in increasing the number of suppliers and has strongly recommended focusing on a handful of strategic partners to balance these tradeoffs. Committing to a few strategic partners, however, may prevent a firm from discovering new suppliers, or even supply regions. Such missed opportunities may be particularly limiting in the context of offshoring professional services, which has exhibited rapid changes in supplier markets in the last decade. Thus, firms may want to engage in a more intensive multisourcing in services. If they do so, their success will depend on a global sourcing process that effectively addresses the critical tradeoffs involved. To explore how a global sourcing process can support multisourcing, we conducted a qualitative longitudinal case study of a large financial services institution that developed a varied global supply base to obtain offshore professional services. Our analysis results in a theory that emphasizes (i) advantages of a multiple provider strategy in rapidly changing global supply markets; (ii) the critical role of middle managers in enabling continuous innovation in the supplier structure; and (iii) the importance of the global sourcing process combining top–down and bottom–up decision making in multisourcing.     

Pricing and ordering decisions in a supply chain with downward substitution and imperfect process yield

We consider a manufacturer sourcing from two suppliers of asymmetric component quality and producing a quality-differentiated product, namely a low- and high-quality version, with each having deterministic demand. The manufacturer adopts the existing process to produce low-quality products with components from the supplier with low component quality, and develops a new process to produce high-quality products with components from the supplier with high component quality. The new process has imperfect yield, and products that do not meet the specifications for high-quality products can substitute for low-quality products produced with the existing process. We investigate the suppliers’ price decisions and the manufacturer’s ordering and production decisions in a game-theoretical model under dual sourcing. Our analyses reveal that increasing product differentiation or higher yield of high-quality products do not necessarily translate to a higher profit for the manufacturer. In light of the manufacturer’s sourcing strategies, we show that sourcing from a single supplier with high- and low-quality components yields a lower profit than sourcing from one supplier with high component quality and the other with low component quality. Finally, we investigate the manufacturer’s decision-making with endogenous yield rate of high-quality products. Our analyses demonstrate that the manufacturer benefits from setting the yield rate of high-quality products ahead of the suppliers’ price decisions.     

Failure Risk and Quality Cost Management in Single versus Multiple Sourcing Decision

The advantage of multiple sourcing to protect against supplier failures arising from undependable products due to latent defects is examined using a model with nonlinear external failure costs. Prior research has focused only on supplier failures arising from unreliable supply, such as late, insufficient, or no delivery. I derive a closed‐form characterization of the optimal production quota allocation for the LUX (Latent defect‐Undependable product‐eXternal failure) setting. The allocation determines the optimal supply base, with intuitive properties that hold under a mild requirement. The requirement includes the special case of equal procurement costs charged by suppliers but also allows unequal costs without any particular order. The key result of the article is a necessary and sufficient condition determining whether single or multiple sourcing is optimal. Another condition is obtained to determine the exact size of the optimal supply base, provided the mild requirement holds. With minor modifications, the results also hold when a buyer‐initiated procurement contract can be used to elicit private information on the suppliers’ unit variable production costs.     

Managing Supplier Competition and Sourcing Sequence for Component Manufacturing

We consider a setting in which a manufacturer sequentially sources two components and uses reverse auction to select a supplier with the lowest bidding price for each component. The manufacturer chooses a quantity to order from each supplier and a price for selling the final product. We show that the interplay between the direct competition faced by suppliers in providing their respective components and the sequence whereby the manufacturer sources components influence system performance in a subtle, and sometimes dramatic, way. As the direct competition for the early sourced component intensifies, the profit of its supplier will deteriorate while the profits of the other firms will improve. As the direct competition for the late sourced component intensifies, however, the profit of its supplier may improve, and the profits of the other supplier, the manufacturer, and the system can all decrease. Compared with when the manufacturer simultaneously sources the components, sequentially sourcing the components can benefit the manufacturer and every supplier. Furthermore, all the channel parties can unanimously agree on a specific sourcing sequence. All of these signify the importance for manufacturers to take appropriate measures to manage their sourcing procedures and the competition environments faced by their suppliers.     

Supplier selection with multiple criteria in volume discount environments

Supplier selection is a multi-criteria decision making problem which includes both qualitative and quantitative factors. In order to select the best suppliers it is necessary to make a trade-off between these tangible and intangible factors some of which may conflict. When business volume discounts exist, this problem becomes more complicated as, in these circumstances, buyer should decide about two problems: which suppliers are the best and how much should be purchased from each selected supplier. In this article an integrated approach of analytical hierarchy process improved by rough sets theory and multi-objective mixed integer programming is proposed to simultaneously determine the number of suppliers to employ and the order quantity allocated to these suppliers in the case of multiple sourcing, multiple products, with multiple criteria and with supplier's capacity constraints. In this context, suppliers offer price discounts on total business volume, not on the quantity or variety of products purchased from them. A solution methodology is presented to solve the multi-objective model, and the model is illustrated using two numerical examples.     

On models for the operation of a class of electronic marketplaces

Innovation in information technology and the use of the Internet have enabled electronic marketplaces to become an important mechanism for linking suppliers and customers in a cost-efficient fashion. Previous research has generally focused on the benefits of electronic marketplaces from transaction cost economics and strategic perspectives. Yet very little academic research has addressed how to actually operate such a marketplace. In this paper, after reviewing the status of electronic marketplaces research, we focus on an operational perspective. A model of an electronic marketplace linking customers and suppliers either directly or via an intermediary is given and solved under various scenarios. This model uses a single cost-minimizing objective and the extensions address issues such as (1) a physical presence for the electronic marketplace, which can provide value-added services and preserve anonymity; and (2) sole sourcing or dual sourcing. An additional model explicitly represents the diverse objectives of the multiple players in the market using goal programming. The contribution of this research to practitioners is to offer a cost-effective alternative to current forms of allocating supply and demand. The cost-minimizing and multiple criteria models and extensions in this study make a contribution to research by expanding the horizons of previous studies on the operation of electronic marketplaces.     

Sourcing Decisions with Stochastic Supplier Reliability and Stochastic Demand

Supplier sourcing strategies are a crucial factor driving supply chain success. In this paper, we investigate the implications of uncertain supplier reliability on a firm's sourcing decisions in an environment with stochastic demand. In particular, we characterize specific conditions under which a firm should choose a single versus multiple supplier sourcing strategy. In an environment with both uncertain demand and supply, we characterize the total order quantity, the number of suppliers selected for order placement, and the allocation of the total order quantity among these selected suppliers. For deeper managerial insight, we also examine the sensitivity of the optimal sourcing decisions to interactions between uncertainties in product demand and supply reliability. We show that sourcing from a single supplier is an optimal strategy for environments characterized by high levels of demand uncertainty or high salvage values. A numerical analysis based on data obtained from an office products retailer further reinforces our analytical results. In addition, we also find that when minimal order quantities are imposed, there are situations where it is not optimal to place an order with the lowest cost supplier.     

A taxonomy of international manufacturing networks

Abstract

Manufacturing firms with multiple product groups do not need to involve all factories in the production of all product groups. Some factories may specialize on a small set of products, while others participate in the manufacturing of a broader set of products. However, current theories on international manufacturing networks do not explain in detail how organizations design international manufacturing networks for different products or product groups involving different sets of factories. This research investigates 20 product group networks at five global manufacturing firms. We distinguish between three types of factories: component manufacturing factories, assembly factories, and integrated factories (having both component manufacturing and assembly). Furthermore, we identify four network types: linear, divergent, convergent, and mixed structures. These four types exhibit distinctly different characteristics in terms of key characteristics, factory roles, product types, process types, market types, sourcing, and key managerial challenges. Most networks are relatively small – on an average consisting of four factories and some contain a number of subnetworks that are self-sufficient in terms of material flow and serve separate market regions. We identify two new types of factory roles related to component manufacturing competences, which we call ‘strategic feeder’ and ‘full lead’.     

The supplier selection problem with quantity discounts and truckload shipping

To minimize procurement expenditures both purchasing and transportation costs need to be considered. We study a procurement setting in which a company needs to purchase a number of products from a set of suppliers to satisfy customer demand. The suppliers offer total quantity discounts and transportation costs are based on truckload shipping rates. The goal is to select a set of suppliers so as to satisfy product demand at minimal total costs. The resulting optimization problem is strongly NP-hard. We develop integer programming based heuristics to solve the problem. Extensive computational experiments demonstrate the efficacy of the proposed heuristics and provide insight into the impact of instance characteristics on effective procurement strategies.