A network approach to modeling the multi-echelon spare-part inventory system with backorders and interval-valued demand

A multi-echelon inventory system implies the existence of a hierarchy of stocking locations, and the dependence and interaction between them. We consider a multi-echelon, spare-part inventory management problem with outsourcing and backordering. The problem is characterized by deterministic repair time/cost, and supply and demand that lie within prescribed intervals and that vary over time. The objective is to minimize the total inventory and transportation costs. We develop a network model for problem analysis and present a network flow algorithm for solving the problem. We prove that the Wagner-Whitin property, known for the lot-sizing problem, can be extended to the spare-part inventory management problem under study.     

A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty

Manufacturers need to satisfy consumer demands in order to compete in the real world. This requires the efficient operation of a supply chain planning. In this research we consider a supply chain including multiple suppliers, multiple manufacturers and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem under uncertainty. First a new robust multi-objective mixed integer nonlinear programming model is proposed to deal with APP considering two conflicting objectives simultaneously, as well as the uncertain nature of the supply chain. Cost parameters of the supply chain and demand fluctuations are subject to uncertainty. Then the problem transformed into a multi-objective linear one. The first objective function aims to minimize total losses of supply chain including production cost, hiring, firing and training cost, raw material and end product inventory holding cost, transportation and shortage cost. The second objective function considers customer satisfaction through minimizing sum of the maximum amount of shortages among the customers’ zones in all periods. Working levels, workers productivity, overtime, subcontracting, storage capacity and lead time are also considered. Finally, the proposed model is solved as a single-objective mixed integer programming model applying the LP-metrics method. The practicability of the proposed model is demonstrated through its application in solving an APP problem in an industrial case study. The results indicate that the proposed model can provide a promising approach to fulfill an efficient production planning in a supply chain.     

Strategic safety stock placement in supply chain design with due-date based demand

We present a strategic safety stock placement model in supply chain design for assembly-type product with due-date based demand, where demand data are based on dates when company has to ship to customers rather than order receiving dates. We formulate multi-echelon stock placement by guaranteed-service model with demand propagation equations through backward explosion, where demand can be either stationary or nonstationary. The stock placement model is incorporated into network design problem and its optimization procedure is provided. We show effectiveness of the optimization procedure and other significant features of the model through numerical examples of a machinery product supply chain.     

An integrated distribution routing model in multi-supply center system

A distribution routing problem with time constraint is one of the important problems in distribution and supply center management. This research is concerned with an integrated distribution routing problem for multi-supply centers based on improved genetic algorithm and graphical user interface (GUI)-type programming. In this research, we proposed a method based on a three-step approach: in step 1 a sector clustering model is developed to transfer the multi-supply center problem to single supply center problems which are easier to be solved; in step 2 we developed a vehicle routing model with time constraints and in step 3 we developed a GA-TSP model which can improve the vehicle routing schedules. The objective of the problem is to minimize the logistic cost for a set of customers without being tardy or exceeding the capacity or travel time of the vehicles. For computational purpose, we developed a GUI-type computer program according to the proposed methods and the sample outputs show that the proposed method is very effective on a set of standard test problems, and it could be potentially useful in solving the distribution routing problems.     

The Impact of Frictions in Routine Execution on Economies of Scope

Research summary: Based on a detailed database of a beverages producer‐distributor that expanded its product variety by leveraging its logistic network, we show that product diversification generates economies of scope and also higher operational costs. The result is an inverted‐U relationship between variety and productivity: When the firm offers few additional categories, productivity grows, but as the number of categories rises, the costs of executing the operational routines increase rapidly and productivity falls. The negative effect on productivity increases if the added product category is more dissimilar to previous ones, and decreases with learning from operational experience. Our results highlight how frictions at the operational level can limit the benefits of diversification, even in the absence of other sources of diseconomies, such as increased coordination needs. Managerial summary: One of the prevalent reasons for companies to expand to adjacent product lines is attaining economies of scope. However, such growth strategy also generates operational frictions, even if the day‐to‐day routines do not appear to change at all. Product diversity is disruptive for routine execution, as it requires coordination and exception handling, and may ultimately overcome any efficiency obtained from growth. We estimate the relevance of such operational friction using data from a beverages distribution network. When product variety is low, additional categories do generate efficiency, but after reaching a given threshold, friction prevails. We find that operational friction increases when products are more dissimilar, but is attenuated when workers learn from their own and other's experience. Copyright © 2017 John Wiley & Sons, Ltd.     

A decision method for supplier selection in multi-service outsourcing

Although supplier selection in multi-service outsourcing is a very important decision problem, research concerning this issue is still relatively scarce. This paper proposes a decision method for selecting a pool of suppliers for the provision of different service process/product elements. It pioneers the use of collaborative utility between partner firms for supplier selection. A multi-objective model is built to select desired suppliers. This model is proved to be NP-hard, so we develop a multi-objective algorithm based on Tabu search for solving it. We then use an example to show the applicability of the proposed model and algorithm. Extensive computational experiments are also conducted to further test the performance of the proposed algorithm.     

The Effect of "Front-Loading" Problem-Solving on Product Development Performance

In recent years, there has been a growing interest in the link between problem‐solving capabilities and product development performance. In this article, the authors apply a problem‐solving perspective to the management of product development and suggest how shifting the identification and solving of problems—a concept that they define as front‐loading—can reduce development time and cost and thus free up resources to be more innovative in the marketplace. The authors develop a framework of front‐loading problem‐solving and present related examples and case evidence from development practice. These examples include Boeing's and Chrysler's experience with the use of “digital mock‐ups” to identify interference problems that are very costly to solve if identified further downstream—sometimes as late as during or—after first full‐scale assembly. In the article, the authors propose that front‐loading can be achieved using a number of different approaches, two of which are discussed in detail: (1) project‐to‐project knowledge transfer—leverage previous projects by transferring problem and solution‐specific information to new projects; and (2) rapid problem‐solving—leverage advanced technologies and methods to increase the overall rate at which development problems are identified and solved. Methods for improving project‐to‐project knowledge transfer include the effective use of “postmortems,” which are records of post‐project learning and thus can be instrumental in carrying forward the knowledge from current and past projects. As the article suggests, rapid problem‐solving can be achieved by optimally combining new technologies (such as computer simulation) that allow for faster problem‐solving cycles with traditional technologies (such as late stage prototypes), which usually provide higher fidelity. A field study of front‐loading at Toyota Motor Corporation shows how a systematic effort to front‐load its development process has, in effect, shifted problem‐identification and problem‐solving to earlier stages of product development. They conclude the article with a discussion of other approaches to front‐load problem‐solving in product development and propose how a problem‐solving perspective can help managers to build capabilities for higher development performance.     

A vendor managed inventory supply chain with deteriorating raw materials and products

Fast deteriorating raw materials such as raw milk, fruit and vegetables are commonly used to produce slowly deteriorating finished products such as milk powders, cheeses, and pastas. This paper studies a Vendor Managed Inventory (VMI) type supply chain where the manufacturing vendor decides how to manage the system-wide inventories of its fast deteriorating raw material and its slowly deteriorating product. The decision variables are a common replenishment cycle of the product and the replenishment frequency of the raw material. We assume the deteriorating rates are known constants and every retailer's demand is deterministic. We develop an integrated model to calculate the total inventory and deterioration cost for such a system. We prove the convexity of the cost functions, and based on this a golden search algorithm is developed to find the optimal solution of the model. Our numerical results show that the deteriorating rate of the product may increase the total cost by more than 40% compared to the zero-deteriorating rate, while the deteriorating raw material has less impact on the total cost (commonly less than 5% in our numerical examples). This indicates that more attention should be paid to the product than the raw material. Further, an increase in the number of retailers can make the replenishment frequency of the raw material increase significantly but the common replenishment cycle of the product decreases a little. This indicates that adding a new retailer would not be felt strongly by the other retailers but would be felt by the supplier of the raw material.     

Managing seller-buyer new product development relationships for customized products: a contingency model based on transaction cost analysis and empirical test

Sellers often customize their product offerings in order to increase the value offered to individual buyers and gain a competitive advantage over the seller’s competitors. However, such customization has a downside—it usually requires considerable seller-buyer interactions aimed at matching the seller’s technological capabilities with the buyer’s needs, which can pose exchange risks such as the safeguarding and adaptation problems noted in the transaction cost analysis literature. In the present study, we develop a contingency model to investigate the impact of product customization on sellers’ perceived relationship satisfaction and subsequent expectations of relationship continuity. We draw on the logic of transaction cost analysis to hypothesize that product customization’s effect on satisfaction and continuity may be moderated by three activities that sellers may engage in during the new product development (NPD) process: education, product knowledge generation, and joint new product development.Our substantive hypotheses were tested with data from a national survey of 296 small to medium size firms in several high-tech industries using a series of hierarchical OLS regression models. Overall, we found mixed support for our hypotheses. The results indicated that joint new product development reduced the negative effect of product customization on seller satisfaction and enhanced customization’s positive effect on continuity, as expected. Contrary to our expectations, product knowledge generation activities increased the negative effect of customization on satisfaction; it also had no significant moderating impact on continuity. Buyer education activities were found to reduce the negative impact of customization on satisfaction, but showed no moderating effect on continuity.This study offers important theoretical and managerial implications. It is one of the first to rely on transaction cost analysis as a basis for examining how various relationship activities conducted during the new product development process moderate product customization’s effect on qualitative outcomes. Whereas traditional NPD processes have emphasized unilateral approaches to product development, our study provides evidence of how bilateral approaches to NPD can benefit sellers of innovations. We provide new insights for managers to consider when deciding whether to engage buyers early on and then continue interacting with them throughout the product development process when developing customized products.     

An efficient hybrid genetic algorithm for the multi-product multi-period inventory routing problem

The inventory routing problem (IRP) addressed in this study is a many-to-one distribution network consisting of an assembly plant and many distinct suppliers where each supplies a distinct product. We consider a finite horizon, multi-periods, multi-suppliers and multi-products where a fleet of capacitated homogeneous vehicles, housed at a depot, transport products from the suppliers to meet the demand specified by the assembly plant in each period. The demand for each product is deterministic and time varying. A mathematical formulation of the problem is given and CPLEX 9.1 is run for a finite amount of time to obtain lower and upper bounds. A hybrid genetic algorithm, which is based on the allocation first route second strategy and which considers both the inventory and the transportation costs, is proposed. In addition to a new set of crossover and mutation operators, we also introduce two new chromosome representations. Several medium and small sized problems are also constructed and added to the existing data sets to show the effectiveness of the proposed approach.     

Using least squares support vector machines for the airframe structures manufacturing cost estimation

Accurate cost estimation plays a significant role in industrial product development and production. This research applied least squares support vector machines (LS-SVM) method solving the problem of estimating the manufacturing cost for airframe structural projects. This research evaluated the estimation performance using back-propagation neural networks and statistical regression analysis. In case studies, this research considered structural weight and manufacturing complexity as the main factors in determining the manufacturing labor hour. The test results verified that the LS-SVM model can provide accurate estimation performance and outperform other methods. This research provides a feasible solution for airframe manufacture industry.     

A Product and Process Model of the Technology-Sourcing Decision

The technology‐sourcing decision traditionally has examined the choice either to innovate internally or to acquire technology from outside sources. The increasing complexity of this decision requires a move beyond the simple “make‐versus‐buy” dichotomy. We seek to test factors that influence the technology decision of subsidiaries for product and process technology across the continuum of options from internal development to outsourcing. We also explore concordance between the research streams of new product development and technology sourcing. Regression models are used to analyze data from 187 subsidiaries that suggest product and process technology development decisions sometimes are associated with similar factors and at other times they diverge. In particular, we find that external product and process technology acquisition decisions are associated negatively with differentiation goals and associated positively with product dynamism. While external product acquisition is associated negatively with a low cost goal and positively with increasing distance between primary marketing and R&D operations, external process technology acquisition is associated positively with high competitive intensity. Implications include the following: (1) While external product technology acquisition may provide quicker or even less expensive initial solutions, external reliance makes it difficult to maintain a long‐term positional advantage; (2) When greater distances separate key functional activities, external partners may provide solutions that are more responsive to local consumer needs, and the potential for improved communication may allow for quicker adaptation and increased flexibility; (3) In highly dynamic product situations, internal development, while providing greater control, can be expensive and can result in technologies that are not accepted by the marketplace; and (4) As competitive intensity increases, strategic imperatives may reduce the focus on product design and development and may require increasing concentration on manufacturing costs and efficiencies.     

The Vital Role of Problem‐Solving Competence in New Product Success*

Problem solving, a process of seeking, defining, evaluating, and implementing the solutions, is considered a converter that can translate organizational inputs into valuable product and service outputs. A key challenge for the product innovation community is to answer questions about how knowledge competence and problem‐solving competence develop and sustain competitive advantage. The objective of this study is to theoretically examine and empirically test an existing assumption that problem‐solving competence is an important variable connecting market knowledge competence with new product performance. New product projects from 396 firms in the high‐technology zones in China were used to test the study's theoretical model. The results first indicate that problem‐solving speed and creativity matter in new product innovation performance by playing mediator roles between market knowledge competence and positional advantage, which in turn sustains superior performance. This new insight suggest that mere generation of market knowledge and having a marketing–research and development (R&D) interface will not affect new product performance unless project members have the ability to use the information and to interact to identify and solve complex problems speedily and creatively. Second, these results suggest that different market knowledge competences (customers, competitors, and interactions between marketing and R&D) have distinct impacts on problem‐solving speed and creativity (positive, negative, or none), which underscore the need to embrace a more fine‐grained notion of market knowledge competence. The results also reveal that the relative importance of some of these relationships depends on the perceived level of turbulence in the environment. First, competitor knowledge competence decreases problem‐solving speed when perceived environmental turbulence is low but enhances problem‐solving speed when perceived turbulence is high. Second, competitor knowledge competence has a positive relationship with new product performance when the environmental turbulence is high but no relationship when the environmental turbulence is low. Third, the positive relationship between problem‐solving speed and product advantage is stronger when the perceived environmental turbulence is high than when it is low, which implies that problem solving is more important for creating product advantage when environmental turbulence is high and change is fast and unpredictable. Fourth, the negative relationship between problem‐solving speed and new product performance is stronger when the perceived environmental turbulence is high than when it is low, which means that problem‐solving speed is more harmful for new product performance when change is fast and unpredictable. And fifth, the positive relationship between product quality and new product performance is stronger when perceived environmental turbulence is low than when it is high, which implies that product quality may more likely lead to new product performance when the environment is stable and changes are easy to predict, analyze, and comprehend.     

Cartel sustainability in retail markets: Evidence from a health service sector

This paper studies the role of cost asymmetries and product differentiation on cartel sustainability by drawing data from a failed retail cartel. Unlike the extensive theoretical literature, little empirical evidence exists on these relationships. First, we analyze cartel compliance and find that players are more likely to comply when cost is symmetric and own cost is high. Next, based on a structural model and counterfactual experiments, we show that a cartel price that satisfies all cartel members does not exist. This result indicates an inherent difficulty of sustaining collusion in retail markets with heterogeneous players. We also show that firm heterogeneities, especially product differentiation rather than cost asymmetries, hinder collusion more. Finally, we derive the level of patience (or the discount factor) required for cartel sustainability when firms split profits based on the Shapley value.     

Transaction cost implication of private branding and empirical evidence

Branding and transaction cost economics represent two research streams that rarely cross paths in the literature. In this study, I explore the transaction cost implication of private branding, a practice whereby products supplied by unaffiliated manufacturers are sold under private brands owned by retailers. The main thesis is that private branding can preempt a special case of asset specificity called brand specificity, where retailers also invest in the marketing of an outsourced product, but subsequent reputation effects (positive or negative) are specific to the manufacturer who brands the product. Retailers, thus, will not be fully motivated to optimize their investment in product marketing unless they take over the branding right. With potential barriers to private branding being controlled, data obtained from a national chain reveal that the retailer deploys its marketing resources according to the branding status of a product, implying that private branding can deflect the transaction cost of solving the brand specificity problem. The results offer new theoretical insights into branding and transaction cost analysis. This efficiency‐based approach to private branding also provides practitioners with useful guidelines for crafting a branding strategy that will facilitate cooperation between manufacturers and retailers. Copyright © 2009 John Wiley & Sons, Ltd.     

Mutual impacts of product standardization and supply chain design

This paper deals with two major issues for industries; the product design and the supply chain design. These problems are usually solved separately, but in recent years, approaches were proposed to tackle these two problems together. In this paper, we investigate more precisely the links between the standardization of products or components, and the design of the supply chain. First, we show on a little example that there is a great interest to consider simultaneously these two decisions, and that solving these interdependent problems separately could result in a suboptimal, or even a bad, decision. Then, on a simplified problem issued from an industrial case study, we outline the impact of standardization choices on the structure of the supply chain and the gain that can be obtained from solving the problem as a unique compound optimization model. To illustrate the solutions of the problem, we propose graphics in order to visualize, in function of quantities and/or transportation costs, the best decision for the product standardization and for the supply chain design. Graphics also permit to anticipate the impacts of a variation of either quantities or transportation costs, from a specific situation. Such graphics they could be used in a decision aid tool to help companies in their choices. Finally, we show that costs and supply chain structure are highly impacted.     

Strategic Suppliers' Technical Contributions to New Product Advantage: Substitution and Configuration Options

Current theory lacks clarity on how different kinds of resources contribute to new product advantage, or how firms can combine different resources to achieve a new product advantage. While several studies have identified different firm‐specific resources that influence new product advantage, comparatively little research has explored the contribution of strategic supplier resources. Combining resource‐based and relational perspectives, this study develops a theoretical model investigating how a strategic supplier's technical capabilities impact focal firm new product advantage and how firms combine different resources to gain this advantage. The model is tested using detailed survey data collected from 153 interorganizational new product development projects in the United Kingdom within which a strategic supplier had been extensively involved. Empirical results support our research hypotheses. First, supplier technical performance is shown to have a significant positive impact on new product advantage. Next, we show that while supplier technical capabilities have a positive influence on supplier technical performance, the a priori nature of the supplier's task moderates the relationship. Finally, our data support our hypotheses related to the positive relationship between relationship‐specific absorptive capacity and new product advantage, and the proposed negative moderation of supplier technical capabilities on this relationship. Based upon these findings, we encourage managers to recognize that strategic suppliers' with greater technical capabilities perform better regardless of the degree of creativity required by their task; but that strategic suppliers with lower technical capabilities may partially compensate (substitute) for their lack of technical capabilities, if they are able to respond to high problem‐solving task requirements. Furthermore, we suggest that the firm's development of relationship‐specific absorptive capacity is much more important when a strategic supplier is less technically capable. A buying firm's relationship‐specific absorptive capacity can, according to our data, substitute for low supplier technical capabilities. On the other hand, where the supplier has strong technical capabilities, investments in relationship‐specific absorptive capacity have no effect on new product advantage. Our findings reinforce recent calls for research on how firms can combine different resources and capabilities to achieve superior performance.     

Machine repairing models for production systems

In this paper we consider manufacturing systems of m identical unreliable machines producing one type of product. The operating time of each machine is exponentially distributed. The repairing process of a machine requires more than one phase. In each phase, the repair time is exponentially distributed and more than one operator may be required for fixing a broken machine. Here we consider two models of manufacturing systems. In the first model, there are r operators assigned in one server to repair a broken machine. The repairing rate in each phase depends on the number of operators there. This is a generalized model discussed in Buzacott and Shanthikumar [11]. We then consider a two-phase repairing model. Two groups of operators are assigned in the two phases. Each operator can handle one broken machine in each phase individually. This model is a generalization of Eben–Chaime's model [8]. Average profits are derived for both models and can be optimized by suitable allocation of the number of machines and operators in the systems.     

The roles of stakeholder support and procedure-oriented management on asset recovery

As the management of returned products is fast becoming a business trend caused by pressure for compliance, asset recovery is increasingly viewed as a fertile area for firms to reduce cost and improve quality. Environmental management is a viable approach for Chinese manufacturers to respond to the escalating international quest for conserving the environment, to tackle the problem of rising raw material costs, and to improve product quality by analyzing returned products. To reach the goals of cost reduction and product quality improvement, manufacturers need to understand how asset recovery can be leveraged through procedure-based practices and stakeholder support to enhance performance. Product type, characterized by different levels of demand uncertainty and time-to-market, may affect the outcomes of asset recovery adoption and should also be taken into account. Drawing on the environmental management and business logistics literature, we provide empirical insights on asset recovery adoption using survey data collected from export-oriented Chinese manufacturers. We find that asset recovery and stakeholder support are complementary in strengthening manufacturers' financial performance regardless of product type. In addition, the performance impact of asset recovery can be substantial when manufacturers' environmental management practices are less procedural, allowing flexibility in the logistics management of product flows.     

Managing platform architectures and manufacturing processes for nonassembled products

The article presents methods for defining product platforms and measuring business performance in process intensive industries. We first show how process intensive product platforms can be defined using the products and processes of a film manufacturer. We then present an empirical method for understanding the dynamics of process intensive platform innovation, allocating engineering and sales data to specific platform and product development efforts within a product family. We applied this method to a major product line of a materials manufacturer. We gathered ten years of engineering and manufacturing cost data and allocated these to successive platforms and products, and then generated R&D performance measures. These data show the dynamic of heavy capital spending relative to product engineering as one might expect in a process intensive industries. The data also show how derivative products can be leveraged from underlying product platforms and processes for nonassembled products. Embedded within these data are strategies for creating reusable subsystems (comprising components, materials, etc.) and common production processes. Hard data on the degree to which subsystems and processes are shared across different products frequently are typically not maintained by corporations for the duration needed to understand the dynamics of evolving product families. For this reason, we developed and applied a second method to assess the degree of reuse of subsystems and processes. This method asks engineering managers to provide subjective ratings on an ordinal scale regarding the use of technology and processes from one product to the next in a cumulative manner. We find that high levels of reuse generally indicate that a product family was developed with a platform discipline. We applied this measure of platform intensity to two product lines of integrated circuits from another large manufacturer. We used this method to gather approximately ten years of information for each product family. Upon analysis, one product family showed substantial platform discipline, emphasizing a common architecture and processes across specific products within the product line. The other product family was developed with significantly less sharing and reuse of architecture, components, and processes. We then found that the platform centric product family outperformed the latter along a number of performance dimensions over the course of the decade under examination.