Search results

This paper attempts to analyze the relationship between the complementarity degrees of imperfect complementary products and sales strategies and give appropriate sales strategies for a two-stage supply chain.

With respect to two-stage supply chain consisting of two manufacturers who produce imperfect complementary products and one retailer who sells the products, aiming at bundling sales strategy, the authors define complementarity elasticity of products and use it to measure the degree of complementary between two products. Based on Stackelberg game and cooperation, the authors analyze the relationship between the complementarity degrees of imperfect complementary products and appropriate sales strategies.

As the impact of complementarity degree on sales strategy decision-making is better, the authors can pinpoint out which sales decision-making is optimal and which bundling sales strategy is the best for a two-stage supply chain. Considering that the degree of complementarity has a significant impact on the product sales strategy, the authors can point out which sales decision-making is optimal, that is, which bundled sales strategy is the optimal in the secondary supply chain of selling complementary products.

An innovative bundling can expand the sales of existing products and new products. It helps a retailer transcend and defeat competitors by reducing marketing expenses while increasing profits. Proper use of bundling can improve consumers utility and create an overall positive effect for both the enterprises and consumer.

The research can help some retailers to make many appropriate bundling sales strategies.

This study focuses on a specific method of meat production that involves carcass purchase and meat production by packing facilities with a novel two-stage model that simultaneously considers location-routing and inventory-production operating decisions. The considered problem aims to reduce variable and fixed transportation and production costs, inventory holding cost and the cost of opening cold storage facilities.

The proposed model encompasses a two-stage model consisting of a single-echelon and a three-echelon many-to-many network with deterministic demand. The proposed model is a mixed-integer linear programming (MILP) model which was tested with the general algebraic modelling system (GAMS) software for a real-world case study in Iran. A sensitivity analysis was performed to examine the effect of retailers' holding capacity and supply capacity at carcass suppliers.

In this research, the number of products transferred at each level, the number of products held, the quantity of red meat produced, the required cold storage facilities and the required vehicles were optimally specified. The outcomes indicated a two percent (2%) decrease in cost per kg of red meat. Eventually, the outcomes of the first and second sensitivity analysis indicated that reduced retailers' holding capacity and supply capacity at carcass suppliers leads to higher total costs.

This research proposes a novel multi-period location-inventory-routing problem for the red meat supply chain in an emerging economy with a heterogeneous vehicle fleet and logistics decisions. The proposed model is presented in two stages and four-echelon including carcass suppliers, packing facilities, cold storage facilities and retailers.

In the context of the trade war in full swing, the global supply chain systems have experienced a serious shock and become very vulnerable. The purpose of this paper is to explore the intertwining effects between the export-supporting subsidy policy and the import-deterring tariff policy to develop better insights for trade policy-making under the intra-industry-trade (IIT) conflicts. The research results may provide the trade policy makers and international businesses with better insights in making rational trade policy and business decisions.

Two-stage game-/bargaining-theoretical models for the dual competing international supply chains with a unilateral/bilateral tariff imposing or subsidy implementing under six different scenarios of IIT conflict are developed, analyzed and compared. On this basis, the corresponding numerical analyses are conducted to assess the impact of the tariff and subsidy policies and derive the trade policy implications and business insights.

The research results indicate that: (1) the bilateral subsidy implementing from both governments is the best policy for all stakeholders in two countries, which would lead to the highest profits, social welfare and consumer surplus than those of the other scenarios; (2) the bilateral tariff imposing of both governments is the worst policy for all stakeholders in two countries, which would lead to the lowest profits, social welfare and consumer surplus than those of the other scenarios; (3) the fair trade scenario without tariff imposing and subsidy implementing turns out to be the second-best trade policy for the governments. Under the World Trade Organization rule and fair-trade principles, the bilateral subsidy policy is not allowed in most of the cases. Thus, adopting a fair-trade policy may be the most appropriate trade policy for two trading countries.

The modeling approach developed for this study is original and innovative due to the following characteristics. First, based on three trade policy alternatives – fair trade, tariff imposing and subsidy implementing – of two generic governments under IIT conflict, nine different combinations of three policy alternatives are defined. Second, excluding the symmetrical combinations, six IIT conflict scenarios under various tariff/subsidy policy pairs ranging from no conflict to high conflict are assumed for two dual competing international supply chains. Third, a novel two-stage game-/bargaining-theoretical modeling approach is applied to investigate the optimal/equilibrium decisions regarding pricing, ordering quantity and their critical economic outcomes for all possible trade policy scenarios. Fourth, this study lays down a research foundation for the future trade conflict study using a game-theoretical modeling approach.

The purpose of this paper is to investigate capacity coordination in services supply chain (SSC). It provides discussion and application of various contracts in a two-stage single period SSC.

This paper considers a two-stage serial supply chain with demand uncertainty and price insensitivity. A model is developed to represent a global IT SSC incorporating services specific factors like over-capacity cost and higher degree of substitution resulting in flexibility to meet unplanned demand. At first, centralized and competitive solutions of the model are studied. Then, the paper studies coordination in this supply chain using some of widely used contract templates.

This paper finds several key insights for the researchers and practitioners in this area around adverse impact of over-capacity cost on demand, positive effect of delivery team’s exposure to market on contracting terms and better understanding of efficient frontiers for selected contracting mechanism.

This paper has limited its analysis to three key and most widely used contracts and made assumptions about risk-neutrality of the firms. Future research can study other contracting templates and/or relax for the model as laid out in this paper.

An automated software agent can be built leveraging the closed form equations developed here to help decide on optimal capacity investment and devise coordinating contracts.

This paper established that because of higher degree of substitution, perishability and non-trivial over-capacity cost, SSC behave bit differently than the physical goods supply chain and coordination of participating firms needs to be studied in a services specific context for improving system-wide performance.

The purpose of this paper is to develop a framework for mapping the Indian Public Distribution System (PDS) using multi-agent system (MAS). The entire PDS supply chain from purchase to the distribution is mapped in detail by integrating stages of PDS supply chain.

Literature related to PDS, food grain supply chain (FGSC) and MAS is reviewed and critically assessed. Based on this a framework is proposed which will help in improving functioning of PDS.

The PDS has many shortcomings arising from its complex structure and practices which are used to implement it. The authors propose an MAS to model it in which each entity will be modelled as an agent. The authors propose two stages of supply chain. First stage models the processes from procurement to storage of food grain and second stage model the distribution process.

This paper will be of interest to the policy makers and decision makers involved in the PDS by providing the shortfalls in the system and also suggesting a method to model the PDS based on practices of food supply chains.

This paper provides the decision makers in the PDS, a framework to model and assess the entire supply chain. This will help them in effective implementation of the PDS and also improve in the areas of concerns which are pointed the study.

Purpose – To describe the evolution of an integrated ‘lean’ and ‘agile’ supply chain process that employed Just‐in‐time (JIT) lean manufacturing approaches at an electronics company. Design/methodology/approach – A case study was designed to examine the links between specific efficiencies and cost savings that derived from transitions in the evolution of the integrated lean and agile supply chain. The case study focused on the company's supply chain management innovations that led to specific improvements in production processes that in turn resulted in enhanced financial outcomes. Findings – The data revealed how specific quality enhancing and lean manufacturing components evolved over a period of seven years in a two stage transition from a ‘lean’ supply chain to one that represented an integrated lean and agile paradigm based on the decoupling point approach (Christopher & Towill, 2001). Research limitations/implications – A single site case study limits the generalizability of the findings. Additional research is necessary to replicate the findings in other firms/industries. Practical implications – By incorporating improvements in production processes in the supply chain, managers can determine how inefficiencies in the supply chain process can be tracked and eliminated to improve a firm's financial performance. Originality/value – Research that documents links between different managerial functions, e.g. supply chain management, improved manufacturing processes, and accounting issues (e.g. cost reduction and improved profitability), is particularly useful.

This paper aims to focus on production ramp up modeling on built‐to‐order (BTO) manufacturers facing customized demand. The general purpose is to present a novel approach to managing collaboration, by considering information exchange between the manufacturer and the supplier.

The methodology applies feedback control mechanism to analyze supplier responsiveness and customer order decoupling point to represent the need for collaboration. A two‐stage game is applied ahead of control system application to optimize the capacity decision, with the ultimate goal being profit maximization.

The results show that a higher product commonality degree gives more opportunity for quick response BTO supply chains, which are managed by feedback control, and at the same time to possibly mitigate the bullwhip effect caused by demand information noise.

The analytical model here focused on one product family development, so the applicability of the proposed model to the whole product portfolio should be investigated in the future.

This paper helps the manufacturer to act optimally by considering the possibility of information exchange with the supplier and deciding on the product commonality degree, in taking into account the customer's lead time requirement.

A control system model of “BTO Supply Chain” is proposed by including product commonality and response analysis in the simulation model. Furthermore, a contribution to collaborative supply chains is shown by applying a synchronized supply model to represent supplier and manufacturer communication.

Due to the rapid development and innovation in the Internet-based technology, conventional banks are under pressure and have to compete with Internet-based finance. This has made banks adopt measures to improve operational efficiency and reduce input and increase output.

The authors had proposed a two-stage fairness concern efficiency model based on the classical theory of data envelopment analysis (DEA) and performed an empirical study to measure agricultural loan efficiency in the 20 major Chinese banks.

The findings of the empirical analysis are as follows: (1) peer-induced fairness concern has no impact on deposit efficiency in a centralized bank supply chain; (2) The China Merchants Bank (CMB) has the third lowest deposit efficiency; (3) monotonicity of loan efficiency with input allocation depends on a bank's ownership structure; (4) efficiency ranks are strongly affected by the fairness concern; (5) most Chinese banks show a low agricultural loan efficiency.

This paper contributes to the literature in several ways. First, to the best of the authors’ knowledge, this is the first attempt to analyze agricultural loan efficiency for a bank supply chain system with the fairness concern. This work reveals the hidden factor that restricts loan efficiency of Chinese banks. Second, the proposed fairness concern two-stage DEA model has shown good ability for full ranking. It can provide a new perspective to the classical DEA literature for ranking decision-making units (DMUs). Third, the authors have demonstrated empirical bank efficiency for the 20 major Chinese banks.

In the hybrid electricity market, renewable energy power generator faces the uncertainty of power market demand and the randomness of the renewable energy generation output. In order to improve the grid-connected quantity of green power, the purpose of this paper is to design the pricing mechanism for renewable energy power generator with revenue-sharing contract in a two-stage “multi-single” electricity supply chain which contains a single dominant power retailer and two kinds of power suppliers providing different power energy species.

Considering the dual uncertainties of renewable energy power output and power market demand, the authors design the full-cooperative contract decision-making model, wholesale price contract decision-making model and revenue-sharing contract decision-making model to compare and optimize grid-connected pricing in order to maximize profit of different parties in power supply chain. Then, this paper performs a numerical simulation, discusses the existence of the equilibrium analytical solutions to satisfy the supply chain coordination conditions and analyzes the optimal contract parameters’ variation characteristics and their interaction relationship.

The authors find that the expected profits of the parties in the hybrid power supply chain are concave about their decision variables in each decision-making mode. The revenue-sharing contract can realize the Pareto improvement for all parties’ interest of the supply chain, and promote the grid-connected quantity of green power effectively. The grid-connected price will reduce with the increase of revenue-sharing ratio, and this impact will be greater on the renewable energy power. The greater the competition intensity in power supply side, the smaller the revenue-sharing ratio from power purchaser. And for the same rangeability of competition intensity, the revenue-sharing ratio reduction of thermal power is less than that of the green power. The more the government subsidizing green power supplier, the smaller the retailer sharing revenue to it.

Facing with the dual uncertainties of green power output and market demand and the competition of thermal power in hybrid electricity market, this study can provide a path to solve the problem of renewable energy power grid-connecting. The results can help green power become competitive in hybrid power market under loose regulations. And this paper suggests that the government subsidy policy should be more tactical in order to implement a revenue-sharing contract of the power supply chain.

This paper studies the renewable energy electricity grid-connected pricing under the uncertainty of power supply and market demand, and compares different contract decision-making strategies in order to achieve the power supply chain coordination. The paper also analyzes the competition between thermal power and renewable energy power in hybrid electricity market.

Information sharing is one of essential collaboration methods for building effective system-level disruption responses and communication for supply chain resilience. However, supply chain members are often reluctant to share the members' business information for fear of losing competitiveness. To facilitate the cooperation among these members, the supply chain members' should be made aware of the value of information. As a result, the purpose of this paper is to quantify the benefit of information sharing and evaluate its magnitude under various factors.

In this paper, information sharing is measured in a two-stage supply chain containing a manufacturer and a retailer. A demand function is constructed as a linear combination of a first-order autoregressive [AR(1)] process, the retail and reference prices. The values of information sharing are quantified for four scenarios: (1) no information sharing, (2) full information sharing, (3) limited information sharing and (4) partial information sharing. Based on the four scenarios, the conditions for valuable information sharing are determined. In addition, the impact of several demand parameters on the usefulness of information sharing is analyzed.

When the demand function is a pure AR(1) process (i.e. there is no impact from the retail and reference prices), information sharing is always valuable regardless of the autoregressive coefficient. Under the influence of the retail price and consumer behavior via the reference price, information sharing is not always beneficial. The boundaries for useful information sharing are analytically constructed. In addition to full information sharing, this study also quantifies the value of information under a partial sharing scheme. The results indicate that the information is more valuable as long as the information is inducible.

This study highlights several specific conditions for a beneficial information sharing agreement in consideration of consumer behaviors. These conditions enable supply chain members to design a sustainable partnership.