Supplier Delivery Performance Research Articles

A multinomial modeling approach to assess supplier delivery performance for buyer-supplier alignment

Purpose Untimely delivery of goods and services, especially in a post-COVID landscape, is a critical harbinger of end-to-end fulfillment. Existing literature in supplier delivery modeling is focused on penalizing suppliers for late deliveries built into a contractual transaction, which eventually erodes trust. As such, a holistic modeling technique focused on long-term relationship building is missing. This study aims to design a supplier evaluation model that analytically equates supplier delivery performance to cost realization while replicating a core attribute of successful supply chains – alignment, leading to long-term supplier relationships. Design/methodology/approach The supplier evaluation model designed in this paper uses delivery deviation as a unit of measure as opposed to delivery duration to enhance consistency with enterprise resource planning protocols. A one-sided modified Taguchi-type quality loss function (QLF) models delivery lateness to construct a multinomial probability penalty cost function for untimely delivery. Prescriptive analytics using simulation and optimization of the proposed mathematical model supports buyer–supplier alignment. Findings The supplier evaluation model designed herein not only optimizes likelihood parameters for early and late deliveries for competing suppliers to enhance total landed cost comparisons for on-shore, near-shore and off-shore suppliers but also allows for the creation of an efficient frontier toward supply base optimization. Research limitations/implications At a time of systemic disruptions such as the COVID pandemic, global supply chains are at risk of business continuity. Supplier evaluation models need to focus on long-term relationship modeling as opposed to short-term contractual penalty-based modeling to enhance business continuity. The model offered in this paper is grounded in alignment – a cornerstone of successful supply chain integration, and offers an interesting departure from traditional modeling techniques in this genre. Practical implications The results from this analytical approach offer flexibility to a supply manager toward building redundancies in the supply chain using an efficient frontier within the supply landscape, which also helps to manage disruption and maintain end-to-end fulfillment. Originality/value The model offered in this paper is grounded in alignment – a cornerstone of successful supply chain integration, and offers an interesting departure from traditional modeling techniques in this genre. The authors offer a rational solution by creating an evaluation model that uses penalty cost modeling as an internal quality measure to rate suppliers and uses the outcome as a yardstick for negotiations instead of imposing penalties within contracts.

Improvement of supplier delivery performance under uncertain capacity allocation and delivery time window

PurposeOriginal equipment manufacturers and other manufacturing companies rely on the delivery performance of their upstream suppliers to maintain a steady production process. However, supplier capacity uncertainty and delayed delivery often poses a major concern to manufacturers to carry out their production plan as per the desired schedules. The purpose of this paper is to develop a decision model that can improve the delivery performance of suppliers to minimise fluctuations in the supply quantity and the delivery time and thus maximising the performance of the supply chain.Design/methodology/approachThe authors studied a single manufacturer – single supplier supply chain considering supplier uncertain capacity allocation and uncertain time of delivery. Mathematical models are developed to capture expected profit of manufacturer and supplier under this uncertain allocation and delivery behaviour of supplier. A reward–penalty mechanism is proposed to minimise delivery quantity and time of delivery fluctuations from the supplier. Further, an order-fulfilment heuristic based on delivery probability is developed to modify the order quantity which can maximise the probability of a successful deliveries from the supplier.FindingsAnalytical results reveal that the proposed reward–penalty mechanism improves the supplier delivery consistency. This consistent delivery performance helps the manufacturer to maintain a steady production schedule and high market share. Modified ordering schedule developed using proposed probability-based heuristic improves the success probability of delivery from the supplier.Practical implicationsPractitioners can benefit from the findings of this study to comprehend how contracts and ordering policy can improve the supplier delivery performance in a manufacturing supply chain.Originality/valueThis paper improves the supplier delivery performance considering both the uncertain capacity allocation and uncertain time of delivery.

Switchover to industrial additive manufacturing: dynamic decision-making for problematic spare parts

PurposeIntroducing additive manufacturing (AM) in a multinational corporation with a global spare parts operation requires tools for a dynamic supplier selection, considering both cost and delivery performance. In the switchover to AM from conventional manufacturing, the objective of this study is to find situations and ways to improve the spare parts service to end customers.Design/methodology/approachIn this explorative study, the authors develop a procedure – in collaboration with the spare parts operations managers of a case company – for dynamic operational decision-making for the selection of spare parts supply from multiple suppliers. The authors' design proposition is based on a field experiment for the procurement and delivery of 36 problematic spare parts.FindingsThe practice intervention verified the intended outcomes of increased cost and delivery performance, yielding improved customer service through a switchover to AM according to situational context. The successful operational integration of dynamic additive and static conventional supply was triggered by the generative mechanisms of highly interactive model-based supplier relationships and insignificant transaction costs.Originality/valueThe dynamic decision-making proposal extends the product-specific make-to-order practice to the general-purpose build-to-model that selects the mode of supply and supplier for individual spare parts at an operational level through model-based interactions with AM suppliers. The successful outcome of the experiment prompted the case company to begin the introduction of AM into the company's spare parts supply chain.

Controlling Supplier Supply Stability with High Demand During the Covid-19 Pandemic at PT PQS

<p class="02abstracttext">COVID-19 with a snap into a very influential factor in all sectors of the economy worldwide. The decrease in demand is also strongly felt in the manufacturing sector in Indonesia, even there are some factories were forced to have to lay off thousands of employees because it is not able to pay the salaries of employees. The opposite condition was experienced by PT PQS Indonesia, which experienced an increase in demand by 40% compared to the average demand for 6 months before COVID-19, because some of the company's branches in other countries had stopped production because they had to follow local government policies. Eventually all orders were sent to be produced at PT PQS Indonesia. The increase in demand does not mean that PT PQS Indonesia did not experience obstacles during the COVID-19 pandemic, the problem faced was the decline in delivery performance from suppliers, which impacted on the reduced stock of raw material stock and could even lead to production stops. This is because the suppliers were affected by Covid-19. This is a challenge because PT PQS has dozens of suppliers at home and abroad. To repeat this so that production does not stop, PT PQS Indonesia added a feature to help control supplier delivery performance. In 2018 the average delivery performance is only 60% — 70%, and the management target is 90% for local suppliers and 85% for overseas. This “Supplier Delivery Performance” feature really helps the procurement team to control the arrival of goods and provide information to suppliers related to their delivery performance, as well as being one of the index KPIs to evaluate supplier performance for one year before the Annual Vendor Meeting is held. To create a “Supplier Delivery Performance” index, PT PQS must also create SOPs or standardize them so that all relevant suppliers and procurement teams can easily understand them.<strong> </strong></p>

Dynamic ordering decisions with approximate learning of supply yield uncertainty

We consider the real-life problem of a coach bus manufacturer located in Turkey, facing the problem of setting ordering quantities for a part procured from an unreliable supplier, where the number of items delivered is binomially distributed with an unknown yield parameter, p. We use the well-defined finite-horizon planning context with deterministic demand per period, purchasing, holding, and shortage costs to investigate the effectiveness of a fill-rate based approximate learning scheme in comparison to an exact Bayesian learning scheme, where observations on the supplier's delivery performance are used to update the assumed distribution of p. We formulate the exact optimal learning problem as a Bayes-adaptive Markov decision process and solve the corresponding finite horizon stochastic dynamic program to provide insights on the value of online learning in comparison to the unrealistic perfect information (PI) and no information (NT) benchmarks. We contrast the performance of the so-called Bayesian Updating (BU) policy to other practical approaches such as using an assumed/guessed value of p and implementing a constant safety stock. Noting the significant value of learning, we finally study the effectiveness of an approximate learning formulation that does not enjoy the asymptotic consistency and convergence properties but involves much lower computational burden, and demonstrate its confounding performance, at times beating the BU policy with exact Bayesian updates.

A business ecosystem perspective of supply chain justice practices

Purpose The purpose of this paper is to investigate the influence of supply chain (SC) justice practices in shared value-supplier delivery performance relationship and the contingent role of trust in SC ecosystem operation. Design/methodology/approach The authors collect and analyze dyadic survey data from a marina resort SC ecosystem in Indonesia. Findings The results suggest the differential moderating effects of two types of perceived SC justice – perceived procedural justice and perceived interactional justice – on the relationship between shared value and supplier delivery performance. More specifically, we find that perceived procedural justice strengthens the shared value-supplier delivery performance relationship, but that perceived interactional justice weakens such a relationship. Furthermore, the findings demonstrate a positive three-way interaction effect between shared value, perceived SC justice and trust on supplier delivery performance. Originality/value The study is the first to introduce the role of SC justice practices in SC ecosystem operation. The authors examine how shared value interacts with perceived SC justice and trust in order to determine supplier delivery performance.

A framework for the impact of lean six sigma on supply chain performance in manufacturing companies

The use of lean six sigma in manufacturing industry has been more intense in the past decade. This method comprises two concepts: lean and six sigma, each with its own objectives. Lean is a concept that aims to optimize the value stream process by eliminating all kind of waste. Meanwhile, the goal of six sigma is to increase process capability in the value stream by aiming for zero defects and reduced process variation. The supply chain performance of manufacturing companies is determined by the ongoing internal activities reflected in the value stream, therefore both lean and six sigma applications are hypothesized to have an impact on the performance. Based on the reviewed literature, this study aims to produce a framework that can be used to explain the impact of lean and six sigma on supply chain performance. In the proposed framework, lean indicators are reflected in just-in-time, quality management and employee involvement, whereas six sigma indicators are characterized by the six sigma variables. At the other end of the equation, supply chain performance is defined by four constructs which are supplier selection, production, delivery and logistic performance, and warehouse.

Consistency and Recovery in Retail Supply Chains

Practitioners and researchers describe inventory service level with metrics that communicate the likelihood of demand fulfillment without considering the ongoing capabilities of the supplier, for example, in‐stock and fill rate. We develop a method for measuring inventory service level that incorporates such supplier capabilities, namely consistency (the ability of a supplier to fulfill orders repeatedly) and recovery (the ability of a supplier to fulfill orders after a lapse in service). Using data from two retail supply chains, we illustrate our approach. To demonstrate the impact of consistency and recovery on supply chain performance, we model a retailer purchasing from competing suppliers with different levels of consistency and recovery. The model incorporates the retailer's uncertainty about demand and the retailer's uncertainty about its suppliers' service levels. We characterize how the retailer's orders and profitability change with a supplier's delivery performance through numerical experiments calibrated with field data. We find notable differences in market share across suppliers with similar traditional inventory service level metrics but differences in consistency and recovery. Further, we observe that a retailer can increase its profitability by determining orders via consistency and recovery in lieu of common metrics like in‐stock. Given the influence of consistency and recovery on supply chain outcomes, we discuss implications for practice and future research.

The impact of supplier performance measurement systems on supplier performance

PurposeThe purpose of this paper is to empirically investigate the impact of a mature supplier performance measurement system (SPMS) adoption all along its lifecycle phases (i.e. design, implementation, use and review) on the suppliers’ performance.Design/methodology/approachThe research hypotheses have been tested on a final sample of 147 pairs of buyer-supplier responses, collected by means of a dyadic survey involving manufacturing firms and one key supplier of their choice. The research framework has been tested through a structural model using PLS regression.FindingsConsidering the joint effect of all the four SPMS phases on supplier performance, the findings show that the system use and review play a prominent effect: the former have a positive impact on supplier quality, delivery and sustainability performance; the latter positively affects supplier delivery, innovation and sustainability. A mature design displays a positive effect on supplier sustainability performance, while a mature implementation results to negatively affect supplier innovation performance. Finally, cost performance is not impacted by any of the four phases.Originality/valueThis study contributes to the open debate regarding the relationship between SPMSs and actual supplier performance improvement. In particular, the lifecycle perspective is introduced to clearly distinguish among each phase of adoption and assess their relative impact on supplier performance. Besides, the dyadic nature of the study allows to investigate different subcomponents of supplier performance jointly considering the buyer company and supplier company perspective, thus achieving a more insightful and robust information.

How does information sharing affect first-tier suppliers’ flexibility? Evidence from the automotive industry in Sweden

This study addresses the critical research issue of how supplier delivery performance can be enhanced by integrating information sharing into volume and delivery flexibility. This study developed a research model to relate information sharing on demand forecasts and inventory data between original equipment manufacturers (OEMs) and first-tier suppliers. Based on a sample of 52 suppliers from automotive industry in Sweden, partial least squares structural equations modelling (PLS-SEM) was used to assess the model. The results confirm that sharing demand forecasts is a key enabler of supplier volume and delivery flexibility while sharing inventory data is not. The study contributes to enlarging the knowledge about supply chain management from the suppliers’ perspective. It also contributes to knowledge by validating the conceptual model and operationalisation of constructs. The study also has practical contribution in which management should focus on improving communication and collaboration practices with OEMs for effective sharing of demand forecasts.

Exploring supplier performance risk and the buyer's role using chance-constrained data envelopment analysis

Current sourcing paradigms are described by greater complexity in managing suppliers' performance in purchasing cycle execution, product quality and logistics competence. When we combine the stages of the order fulfillment cycle with the buyer's information sharing factors, a more complete view of the buyer-supplier exchange becomes useful for performance evaluation of both the suppliers and the buyers. Using operational data obtained from a large telecommunications firm, which placed strategic importance on measuring the performance in the purchase order fulfillment cycle stages, this study offers a new context for supplier evaluation. This context also conceptualizes several on-time delivery disruption scenarios as supplier delivery performance risk, and investigates the sensitivity of both the buyer's information sharing and the suppliers’ performance capabilities to on-time delivery disruptions. We evaluate supplier performance and segment suppliers through recourse to chance-constrained data envelopment analysis at high and low discriminatory power levels. Our results show that there are statistically significant relationships between the dimensions of information sharing by the buying firm and the classification of supplier firms at varying levels of on-time delivery performance risk. We also identify robust suppliers demonstrating the capability to remain efficient across disruption levels despite poor buyer performance on information sharing factors, and provide managerial insights on buyer-supplier exchange.

An optimization framework for improving supplier delivery performance

Given the growing importance of supplier delivery performance in buyer–supplier alignment and end-to-end fulfillment of supply chains, we investigate the managerial implications of a buyer who financially invests to improve a supplier’s delivery performance by demonstrating an optimization model for the buyer’s investment decision to reduce untimely delivery. We illustrate how improving supplier delivery performance leads to better supplier management. Our analysis utilizes the ingenious zeta transforms widely used in engineering to showcase its applicability in today’s complex supply landscapes that use multiple suppliers to create efficient frontiers for diverse sourcing initiatives.

A delayed product customization cost model with supplier delivery performance

Abstract The concept of delayed product differentiation has received considerable attention in the research literature in recent years. However, few analytical models explain and quantify the benefits of delayed product differentiation strategy with additional consideration of supplier delivery performance. This paper proposes a delayed product differentiation model in which a supply of raw materials is integrated at the beginning of the production process to match uncertain demand in a cost-effective way given the constraint of lead time delivery window. It develops insights regarding a delayed product differentiation strategy and shows that with respect to delivery windows, supplier delivery performance plays an important role in the determination of the optimal point of differentiation. This study also shows that when the “ on-time ” and the “ late ” portions of the delivery window are constant, the proposed cost function coincides with similar models found in the literature. An extension of this work also reveals that when the customer service level varies across various production stages, its choice affects the decision to delay or postpone the customization point. A mini industrial case involving the customization of a personal desktop computer is used to illustrate the applicability of the resulting framework.

The Intersection of Power, Trust and Supplier Network Size: Implications for Supplier Performance

This paper examines the intersecting effects of power, trust and supplier network size on five dimensions of supplier performance (delivery, quality, cost, innovation and flexibility). When assessing main effects, coercive power shows a negative relationship with supplier quality and innovation, referent power shows a positive relationship with all dimensions of supplier performance and legitimate power shows a positive relationship with supplier delivery, cost and flexibility. The supplier's trust in the buyer also shows a positive relationship to all five supplier performance dimensions. While exhibiting no main effects, supplier network size moderates these power–performance relationships. Increasing supplier network size appears to attenuate the impacts of coercive and referent power upon supplier performance, while strengthening this connection in the case of legitimate power. Contrary to our hypotheses, expert power use exhibits a negative relationship with supplier delivery performance, an effect which is exacerbated with increasing supplier network size. Overall, this study suggests that while not as independently important as perhaps thought, selecting the right number of suppliers may have considerable contextual influence on the interplay between power, trust and performance in buyer–supplier relationships.

Buyer perceptions on the buyer-supplier collaborative relationship and performance: a service example

Increasing need to improve efficiency and/or productivity and achieve competitive advantage causes organisations to look into collaborative relationships with their supply chain partners. This study examines how buyer-supplier collaboration contributes to relationship outcomes as measured by supplier delivery performance, buyer perceived business performance and revenue. Surveys collected from 57 managers of a US service organisation reveal the significance of knowledge transfer in improving buyer performance and supplier delivery performance. Also, knowledge transfer is a key mediator explaining the association between supplier relationship management and performance constructs when buyer-supplier relationship length is added to the model. If buyer and suppliers are in a trustworthy and sustainable relationship, they will be more likely learn from each other, respond to each other’s concerns and problems that in turn improve business performance. Buyer and suppliers can use these results to better understand the implications of knowledge management in the supply chain.

Supplier delivery performance in ugandan public procurement contracts

The purpose of this paper is to develop a comprehensive framework of achieving supplier delivery performance based on contract governance mechanisms, justice perceptions and ethical behavior using cross sectional survey data from public procuring and disposing entities (PDEs) in Uganda. Public procurement contract governance covers the design, development, implementation and enforcement of contracts. It serves to align interests of the contracting parties, reduce opportunistic behavior, lower transaction costs, promote justice perceptions, improve ethical behavior and achieve value for money procurement. Poorly managed procurement contracts result in conflicts, yet in many developing countries only rich suppliers can afford to resolve disputes through courts. For other suppliers, justice is out of reach. While it has been assumed that contracts result in good performance, little research has been carried out to corroborate this assumption. In this paper we provide theoretical, empirical and policy implications of supplier delivery performance.

Procurement Mechanism Design in a Two-Echelon Inventory System with Price-Sensitive Demand

This paper studies a buyer's procurement strategies in a two-stage supply chain with price-sensitive demand. The buyer procures a product from a supplier and then sells to the marketplace. Market demand is stochastic and depends on the buyer's selling price. The supplier's production cost is private information, and the buyer only knows the distribution of the cost. Both the buyer and the supplier can hold inventories to improve service, and a periodic review inventory system is considered. The buyer takes two attributes into consideration when designing the procurement mechanism: quantity attribute (i.e., the total purchase quantity) and service-level attribute (i.e., the supplier's delivery performance). We first identify the optimal procurement mechanism for the buyer, which consists of a nonlinear menu of contracts for each of the two attributes. It can be shown that the optimal mechanism induces both a lower market demand and a lower service level compared to the supply chain optimum. In view of the complexity of the optimal mechanism, we proceed to search for simpler mechanisms that perform well for the buyer. We find that the above two attributes have different implications for procurement mechanism design: The value of using complex contract terms is generally negligible for the service-level attribute, while it can be highly valuable for the quantity attribute. In particular, we demonstrate that a fixed service-level contract, which consists of a target service level and a price-quantity menu, yields nearly optimal profit for the buyer. Additionally, the price-quantity menu is essentially a quantity discount scheme widely observed in practice.

Procurement Mechanism Design in a Two-Echelon Inventory System with Price-Sensitive Demand

This paper studies a buyer's procurement strategies in a two-stage supply chain with price-sensitive demand. The buyer procures a product from a supplier and then sells to the marketplace. Market demand is stochastic and depends on the buyer's selling price. The supplier's production cost is private information, and the buyer only knows the distribution of the cost. Both the buyer and the supplier can hold inventories to improve service, and a periodic-review inventory system is considered. The buyer takes two attributes into consideration when designing the procurement mechanism: quantity attribute (i.e., the total purchase quantity) and service-level attribute (i.e., the supplier's delivery performance). We first identify the optimal procurement mechanism for the buyer, which consists of a nonlinear menu of contracts for each of the two attributes. It can be shown that the optimal mechanism induces both a lower market demand and a lower service level compared to the supply chain optimum. In view of the complexity of the optimal mechanism, we proceed to search for simpler mechanisms that perform well for the buyer. We find that the above two attributes have different implications for procurement mechanism design: The value of using complex contract terms is generally negligible for the service-level attribute, whereas it can be highly valuable for the quantity attribute. In particular, we demonstrate that a fixed service-level contract, which consists of a target service level and a price-quantity menu, yields nearly optimal profit for the buyer. Additionally, the price-quantity menu is essentially a quantity discount scheme widely observed in practice.

Multiple retailer supplier performance: An exploratory investigation into using SPC techniques

The relationship between buyers and suppliers is the cornerstone of all supply networks. This exploratory investigation seeks to examine whether an existing approach developed for, and used extensively in the manufacturing quality milieu, could be adapted to the dyadic relationships found at the supply network interface between food multiple retailers and their suppliers. This investigation evaluates the concept of the use of control charts to examine supplier's delivery performance into the retailer's distribution centres and to relate this to on-shelf-availability in the retailer's stores. It was found that these control charts could be adapted to monitor the supplier/retailer interface and that the results could potentially be used to monitor and manage the buyer/supplier relationship effectively.

Uncertainty and contingency plans in ERP‐controlled manufacturing environments

PurposeThis research aims to determine to what extent uncertainties affected manufacturing enterprises' delivery performance, to analyse the performance of their contingency plans in dealing with uncertainties and to explore what technical and organisational factors affected managers' decisions to implement an uncertainty‐diagnosing model.Design/methodology/approachThe methodology included a literature review, postal questionnaire survey and telephone interviews.FindingsA total of 30 companies responded to the questionnaire, 56 per cent of which thought their systems worked well and 80 per cent reported that material shortages were responsible for tardy delivery performance. Tardy delivery was directly or indirectly caused by poor supplier delivery performance in the opinion of 92 per cent of respondents. Seven companies had developed an uncertainty‐diagnosing model. Not all companies needed to adopt the model.Research limitations/implicationsUncertainty and contingency plans were investigated in UK and Chinese organisations using MRP/MRPII/ERP systems. Therefore, the findings will be directly relevant to the organisations, but may be adapted to other similar organisations.Practical implicationsA detection method was proposed to determine the steps required for organisations to adopt the uncertainty‐diagnosing model.Originality/valueThe paper provides some empirical data on uncertainty and the contingency plans used in ERP‐controlled manufacturing environments in organisations in the UK and China. Data on uncertainty are scarce and this research gives further insights into the ways managers perceive and handle uncertainty.