Push and pull contracts in a supply chain selling two products with different lead times

2018 ◽  
Vol 13 (4) ◽  
pp. 1007-1024
Author(s):  
Zhenyu Zhang ◽  
Zhiying Tao
Keyword(s):  
Supply Chain ◽  
Lead Time ◽  
Lead Times ◽  
Single Product ◽  
Content Type ◽  
Multiple Products ◽  
Supply Chain Efficiency ◽  
Production Quantity ◽  
Short Lead Time ◽  
Push And Pull

Purpose Previous researchers have studied push and pull contracts in the single product scenario, although in practice, supply chains often produce and sell multiple products. In a multiproduct scenario, the sales of a product will be influenced by its complements or substitutes, which requires consideration when the supply chain members negotiate contracts. This paper aims to fill this gap by studying push and pull contracts in a supply chain which distributes two products to a market and discusses how the degree of complementarity/substitutability between the two products affects the supplier’s decisions and supply chain efficiency. Design/methodology/approach The paper uses the model of a single-supplier, single-retailer supply chain which sells a product with a long lead time and another product with a short lead time simultaneously in a market. This research compares the production quantity and supply chain efficiency under a push contract with those under a pull contract. Findings First, when the two products are complements, the equilibrium production quantity of Product 2 is higher under a pull contract than that under a push contract. Second, a pull contract is found to be optimal for both the supplier’s profit and supply chain efficiency when the two products are complements, while if they are substitutes, then a push contract is the better choice in some situations. Originality/value The existing literature discusses push and pull contracts in the single product scenario. The current paper pays attention to the two-product scenario and investigates how the complementarity/substitutability degree between the two products affects the supplier’s decisions and supply chain efficiency.

Supply chain redesign for lead-time reduction through Kraljic purchasing portfolio and AHP integration

2019 ◽  
Vol 26 (4) ◽  
pp. 1194-1209 ◽  
Author(s):  
Augusto Bianchini ◽  
Andrea Benci ◽  
Marco Pellegrini ◽  
Jessica Rossi
Keyword(s):  
Supply Chain ◽  
Business Strategy ◽  
Lead Time ◽  
Small And Medium Enterprises ◽  
Evaluation Criteria ◽  
Portfolio Analysis ◽  
Lead Times ◽  
Content Type ◽  
Lead Time Reduction ◽  
Time Reduction

Purpose The purpose of this paper is to provide a flexible and extensible model for the classification of suppliers, within the purchasing guidelines and market trends of an Italian small company, leader in the production of street lamps. The model is applied to identify critical supply chains with the final objective of lead-time reduction. Design/methodology/approach The model is obtained by the application of the purchasing portfolio analysis through the construction of Kraljic matrix. Profit impact and supply risk criteria are selected according to the main company requirements, and then prioritized by the analytical hierarchy process (AHP). Finally, supply chain lead-times are analyzed with Gantt diagrams. Findings The application of the model allows the determination of company criticalities in terms of high lead-times and of the involved suppliers. The analysis of critical suppliers positioning in the Kraljic matrix allows the definition of some possible strategies to implement for lead-time reduction. Research limitations/implications Purchasing portfolio analysis and Kraljic matrix are practical instruments to quickly frame company purchasing situation, but their application is not simple due to the numerous and different factors involved, especially in small and medium enterprises (SMEs), where resource are scarce and several constraints limit operations. The objective of the research is the development of a practical tool for strategic purchasing, simple and robust to be implemented in SMEs, with limited resources and access to quantitative supplier data. Originality/value Evaluation criteria definition is one of the most difficult phases, such as their univocal and quantitative comparison. The problem of selecting and prioritizing both quantitative and qualitative criteria for suppliers classification is overcome with the combined application of Kraljic matrix and AHP. The newly integration of the two methodologies allows the realization of a reliable and robust model for suppliers classification, which can be easily adapted to company business strategy changes.

An integrated ANP–QFD approach for prioritization of customer and design requirements for digitalization in an electronic supply chain

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Deepu TS ◽  
Ravi V
Keyword(s):  
Supply Chain ◽  
Quality Function Deployment ◽  
Analytic Network Process ◽  
Lead Times ◽  
Customer Requirements ◽  
Content Type ◽  
Supply Chain Efficiency ◽  
Network Process ◽  
Term Basis ◽  
Design Requirements

PurposeSupply chain efficiency can be enhanced by integrating the activities in supply chain through digitalization. Advancements in digital technologies has facilitated in designing robust and dynamic supply chain by bringing in efficiency, transparency and reduction in lead times. This research tries to identify and prioritize the customer requirements and design requirements for effective integration of supply chain through digitalization.Design/methodology/approachThe key nine customer requirements and 16 design requirements applicable for an electronics company were shortlisted in consultation with the experts from the company and academia. An integrated analytic network process (ANP) and quality function deployment (QFD) methodology has been applied for prioritizing the customer and design requirements. The relative importance and interdependence of these requirements were identified and a House of Quality (HOQ) is constructed.FindingsThe HOQ constructed has prioritized and identified interrelationships among customer requirements and design requirements for effective supply chain digitalization. These findings could be effectively used by managers for planning the objectives on long-term, medium-term and short-term basis.Originality/valueThis study tries to bridge the gap of identifying and prioritizing the design and customer requirements for effective supply chain integration through digitalization. The results could aid practicing managers and academicians in decision-making on supply chain digitalization process.

Wholesalers perspectives on mango supply chain efficiency in India

2019 ◽  
Vol 9 (2) ◽  
pp. 175-200 ◽  
Author(s):  
Saurav Negi ◽  
Neeraj Anand
Keyword(s):  
Factor Analysis ◽  
Supply Chain ◽  
Lead Time ◽  
Poor Quality ◽  
Food Supply Chain ◽  
Content Type ◽  
Supply Chain Efficiency ◽  
Operational Issues ◽  
High Lead ◽  
Improve Supply Chain

Purpose The purpose of this paper is to identify the factors and most significant reasons leading to supply chain inefficiency with respect to high cost, high lead time and poor quality at wholesale stage of mango supply chain in India, and also to find out the measures which may be taken to improve supply chain efficiency. Design/methodology/approach The paper opted for an exploratory study using the quantitative and qualitative method of research. The study was conducted at Asia’s largest and world’s second largest fruits and vegetable wholesale market (Mandi) in Azadpur, Delhi. Factors have been identified using factor analysis and the measures to improve supply chain efficiency in fruits sector have been found out through semi-structured interviews with agri- and food-supply chain experts. Findings Based on the factor analysis, three factors were identified for high cost, namely, operational charges, labour and resources; four factors were identified for high lead time, namely, operational issues, labour, resources and infrastructure; and four factors were identified for poor quality, namely, operational issues, infrastructure, resources and poor ambience. It was also found that operational factor is the most significant factor leading to supply chain inefficiency. The study also highlighted the measures for improving supply chain efficiency based on the outcome of the interviews. Research limitations/implications This study is limited to the wholesale stage of fruit supply chain with the focus on Azadpur Mandi, Delhi, India, with specific reference to mango. Also, the measures have been identified for only the most significant reasons under each factor leading to supply chain inefficiency with respect to cost, time and quality. Originality/value There is a dearth of literature on improving the supply chain efficiency pertaining to the wholesale stage of fruits and vegetable sector in India. This paper tries to fulfil the gap and contributed to the literature on agriculture supply chain, which may be helpful for the researchers as well as the practitioners to improve food supply chain pertaining to developing countries.

scholarly journals A Data Envelopment Analysis Approach to Supply Chain Efficiency

2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
Alireza Amirteimoori ◽  
Leila Khoshandam
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Lead Times ◽  
Data Envelopment ◽  
Competitive Strategies ◽  
Usual Procedure ◽  
Supply Chain Efficiency ◽  
Efficiency Decomposition ◽  
Low Costs ◽  
Effective Design

Supply chain management is an important competitive strategies used by modern enterprises. Effective design and management of supply chains assists in the production and delivery of a variety of products at low costs, high quality, and short lead times. Recently, data envelopment analysis (DEA) has been extended to examine the efficiency of supply chain operations. Due to the existence of intermediate measures, the usual procedure of adjusting the inputs or outputs, as in the standard DEA approach, does not necessarily yield a frontier projection. The current paper develops a DEA model for measuring the performance of suppliers and manufacturers in supply chain operations. Additive efficiency decomposition for suppliers and manufacturers in supply chain operations is proposed.

Improving the performance of a Malaysian pharmaceutical warehouse supply chain by integrating value stream mapping and discrete event simulation

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ahmed Abideen ◽  
Fazeeda Binti Mohamad
Keyword(s):  
Supply Chain ◽  
Lead Time ◽  
Discrete Event ◽  
Integrated Approach ◽  
Value Stream Mapping ◽  
Content Type ◽  
Value Stream ◽  
Future State ◽  
The Future ◽  
Value Stream Map

Purpose Lean implementation is vastly incorporated in core manufacturing processes; however, its applicability in the supply chain and service industry is still in its infancy. To acquire performance excellence and thrive in the global competitive market, many firms are adopting newer methodologies. But, there is a stringent need for production simulation systems to analyze supply chains both inbound and outbound. The era of face validation is slowly disappearing. Lean tools and procedures that provide future state assumptions need advanced tools and techniques to measure, quantify, analyze and validate them. The purpose of this study is to enable dynamic quantification and visualization of the future state of a warehouse supply chain value stream map using discrete event simulation (DES) technique. Design/methodology/approach This study aimed to apply an integrated approach of the value stream mapping (VSM) and DES in a Malaysian pharmaceutical production warehouse. The main focus is diverted towards reducing the warehouse supply chain lead time by initially constructing a supply chain value stream map (both present state and future state) and integrating its data in a DES modelling and simulation software to dynamically visualize the changes in future state value stream map. Findings The DES simulation was able to mimic the future state lead time reductions successfully, which assists in better decision-making. Improvements were seen related to total lead time, process time, value and non-value-added percentage. Warehouse performance metrics such as receiving, put away and storage rates were substantially improved along with pallet processing time, worker and forklift throughput usage percentage. Detailed findings are clearly stated at the end of this paper. Research limitations/implications This study is limited to the warehouse environment and further additional process models and functional upgrades in the DES software systems are very much needed to directly visualize and quantify all the possible Lean assumptions such as radio frequency image identification/Andon (Jidoka), 5S, Kanban, Just-In-Time and Heijunka. However, DES has a leading edge in extracting dynamic characteristics out of a static VSM timeline and capture details on discrete events precisely by picturizing facility modification and lead time related to it. Practical implications This paper includes all the fundamental pharmaceutical warehouse supply chain processes and the simulations of the future state VSM in a real-life context by successfully reducing supply chain lead time and allowing managers in inculcating near-optimal decision-making, controlling and coordinating warehouse supply chain activities as a whole. Social implications This integrated approach of DES and VSM can involve managers and top management to support the adoption of anticipated changes. This study also has the potential to engage practitioners, researchers and decision-makers in the warehouse industry. Originality/value This study involves a powerful DES software package that can mimic the real situation as a virtual simulation and all the data and model building are based on a real warehouse scenario in the pharmaceutical industry.

Comparative multi criteria analysis and dependent optimisation through integrated supply chain

2014 ◽  
Vol 63 (8) ◽  
pp. 1046-1069 ◽  
Author(s):  
Sanjay Sharma ◽  
Akshat Sisodia
Keyword(s):  
Supply Chain ◽  
Lead Time ◽  
Service Level ◽  
Inventory Level ◽  
Inventory Policies ◽  
Inventory Cost ◽  
Content Type ◽  
Customer Service Level ◽  
Integrated Supply Chain ◽  
Different Levels

Purpose – The purpose of this paper is to compare various inventory policies and their effect on various performance metrics at different levels of a multi stage supply chain. Later the model is integrated to include optimization of entire supply chain through implementation of collaborative supply chain model. Design/methodology/approach – Alternative inventory policies have been developed at different echelons and a comparison reflecting the usability on various factors such as inventory level, inventory cost and service level is presented so as to support the decision-making process. Various inventory policies such as economic order quantity, periodic ordering (T, M) and stock to demand have been considered. Along with the basic assumptions; lead time, demand variability, variability in demand during lead time, stock out costs have also been included to make the model more applicable to practical situations. Findings – After the selection of most appropriate inventory policy at each level through a decision matrix, the total cost of operating such a supply chain is calculated along with other parameters such as service level and inventory turns. The approach is of aggregating the optimized value at each echelon referred to as aggregated supply chain in the paper. Then the concept of integrated supply chain is introduced which optimizes the supply chain as a whole, rather than aggregating local optima. The comparison is made between the two approaches that prove the integrated supply chain's superiority. Furthermore, dependent optimization is run as it is not practically possible for each echelon to optimize at the same time. Originality/value – Each echelon is allowed to optimize at a time and other echelons assume corresponding values. This final comparative multi criterion analysis is based on the three factors, i.e. inventory cost, customer service level and inventory turnover with different weights assigned to each factor at different levels of a supply chain. Finally a consolidation of results is made to reflect the overall preference which proves that an integrated supply chain best serves all the parameters combined together.

Modelling of critical factors for responsiveness in supply chain

2015 ◽  
Vol 26 (6) ◽  
pp. 868-888 ◽  
Author(s):  
Rajesh Kumar Singh
Keyword(s):  
Supply Chain ◽  
Inventory Management ◽  
Lead Time ◽  
Product Life Cycle ◽  
Strategy Development ◽  
Top Management ◽  
Critical Factors ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Use Of Resources

Purpose – In globalized economy, product life cycle is reducing continuously, customers demands are changing fast, and lead time for response is decreasing. In such scenario, ability of firms to quickly respond to changes in their external environment is a primary determinant of firm’s performance. This can be only possible when whole of the supply chain (SC) is responsive. For this, firms have to manage internal operations effectively to enable SC, responsive for market requirements. The purpose of this paper is to identify different factors for responsive SC. Design/methodology/approach – Based on literature review, total 17 critical factors for the responsive SC have been identified. Some of these factors are process oriented and some are result oriented. To develop structural relationship among these factors from strategic perspective, interpretive structural modeling (ISM) approach has been applied. Findings – It is observed that top management commitment, strategy development, resource development, use of technology, risk and reward sharing are major drivers for responsive SC. By managing these enablers, organizations can also benefit in terms of inventory management, lead time reduction and agility. Research limitations/implications – ISM has got some limitations. Major limitation is that the relationships developed are subjective and there are chances of biasing. Therefore findings need to be validated with case studies and empirical findings. Practical implications – Top management should strive for effective use of resources and technology to improve SC capabilities to meet market changes. Originality/value – This study develops structural relationships between different factors and it will help organizations in taking initiatives for improving responsiveness.

Low Volume Plastics Manufacturing Strategies

2007 ◽  
Vol 129 (12) ◽  
pp. 1225-1233 ◽  
Author(s):  
Ruchi Karania ◽  
David Kazmer
Keyword(s):  
Injection Molding ◽  
Product Development ◽  
Lead Time ◽  
Development Time ◽  
Numerical Control ◽  
Production Costs ◽  
Lead Times ◽  
Total Production ◽  
Fused Deposition ◽  
Production Quantity

Plastic components are vital components of many engineered products, frequently representing 20–40% of the product value. While injection molding is the most common process for economically producing complex designs in large quantities, a large initial monetary investment and extended development time are required to develop appropriate tooling. For applications with lower or unknown production quantities, designers may prefer another process that has a lower development cost and lead time albeit with higher marginal costs and production times. A methodology is presented that assists the designer to select the most appropriate manufacturing process that trades off the total production costs with production lead times. The approach is to develop aggregate component cost and lead-time models as a function of production quantity from extensive industry data for an electrical enclosure consisting of two components. Binding quotes were secured from multiple suppliers for a variety of manufacturing processes including computer numerical control machining, fused deposition modeling, selective laser sintering, vacuum casting, direct fabrication, and injection molding with soft prototype and production tooling. The methodology yields a Pareto optimal set that compares the production costs and lead times as a function of the production quantity. The results indicate that the average cost per enclosure assembly is highly sensitive to the production quantity, with average costs varying by more than a factor of 100 for production quantities varying between 100 and 10,000 assemblies. Each of the processes is competitive with respect to total production cost and total production lead time under differing conditions; a flow chart is provided as an example of a decision support tool that can be provided to assist process selection during the product development process and thereby reduce the product development time and cost.

scholarly journals An Empirical Study of Supply Chain Frangibility and Risk Management in Indian Automobile Industry

2021 ◽  
Author(s):  
Arora Ankit ◽  
Rajagopal Rajesh
Keyword(s):  
Risk Factors ◽  
Supply Chain ◽  
Automobile Industry ◽  
Lead Time ◽  
Risk Mitigation ◽  
Transportation Network ◽  
Demand Forecasting ◽  
Bullwhip Effect ◽  
Effect Analysis ◽  
Supply Chain Efficiency

Abstract The automobile sector in India is one the key segment of Indian economy as it contributes to 4% of India’s GDP and 5% of India’s Industrial production. The supply chain of any firm is generally dependent on six driving factors out of which three are functional (information, inventory, and facilities) and 3 are logistic (sourcing, pricing, and transportation). The risk causing factors in supply chains consists of various levels of sub-factors under them. Say for instance, under supply risk, the sub-factors can be poor logistics at supplier end, poor material quality etc., under demand risk, the sub-factors can be inaccurate demand forecasting, fluctuating demand, bullwhip effect, and under logistics risk, the sub-factors can be poor transportation network, shorter lead time, stock outs. Through this study, we observe to find the effect of these factors in the supply chain. We use Failure Mode and Effect Analysis (FMEA) technique to prioritize the various types of risk into zones namely high, medium and low risk factors. Also, we use the Best Worst Method (BWM), a multi-criteria decision-making technique to find out the overall weightings of different risk factors. The combination of these methods can help an organization to prioritize various risk factors and proposing a proper risk mitigation strategy leading to increase in overall supply chain efficiency and responsiveness.

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