Optimal Coordination in Distributed Software Development

The construction of a software system requires not only individual coding effort from team members to realize the various functionalities, but also adequate team coordination to integrate the developed code into a consistent, efficient, and bug‐free system. On the one hand, continuous coding without adequate coordination can cause serious system inconsistencies and faults that may subsequently require significant corrective effort. On the other hand, frequent integrations can be disruptive to the team and delay development progress. This tradeoff motivates the need for a good coordination policy. Both the complexity and the importance of coordination is accentuated in distributed software development (DSD), where a software project is developed by multiple, geographically‐distributed sub‐teams. The need for coordination in DSD exists both within one sub‐team and across different sub‐teams. The latter type of coordination involves communication across spatial boundaries (different locations) and possibly temporal boundaries (different time zones), and is a major challenge that DSD faces. In this study, we model both inter‐ and intra‐sub‐team coordination in DSD based on the characteristics of the systems being developed by the sub‐teams, the deadline for completion, and the nature of division adopted by the sub‐teams with respect to development and integration activities. Our analysis of optimal coordination policies in DSD shows that integration activities by one sub‐team not only benefit that sub‐team (as is the case in co‐located development) but can also help the other sub‐teams by providing greater visibility, thereby resulting in a higher integration frequency relative to co‐located development. Analytical results are presented to demonstrate how the characteristics of the projects and the sub‐teams, and the efficiency of communication across the sub‐teams, affect coordination and productivity. We also investigate the pros and cons of using specialized integration sub‐teams and find that their advantage decreases as the project schedule becomes tighter. Decentralized decisions and asymmetric subsystems are also discussed.     

Looking Upstream: Optimal Policies for a Class of Capacitated Multi‐Stage Inventory Systems

We consider a multi‐stage inventory system with stochastic demand and processing capacity constraints at each stage, for both finite‐horizon and infinite‐horizon, discounted‐cost settings. For a class of such systems characterized by having the smallest capacity at the most downstream stage and system utilization above a certain threshold, we identify the structure of the optimal policy, which represents a novel variation of the order‐up‐to policy. We find the explicit functional form of the optimal order‐up‐to levels, and show that they depend (only) on upstream echelon inventories. We establish that, above the threshold utilization, this optimal policy achieves the decomposition of the multidimensional objective cost function for the system into a sum of single‐dimensional convex functions. This decomposition eliminates the curse of dimensionality and allows us to numerically solve the problem. We provide a fast algorithm to determine a (tight) upper bound on this threshold utilization for capacity‐constrained inventory problems with an arbitrary number of stages. We make use of this algorithm to quantify upper bounds on the threshold utilization for three‐, four‐, and five‐stage capacitated systems over a range of model parameters, and discuss insights that emerge.     

A Bayesian Inventory Model Using Real‐Time Condition Monitoring Information

Lack of coordination between machinery fault diagnosis and inventory management for spare parts can lead to increased inventory costs and disruptions in production activity. We develop a framework for incorporating real‐time condition monitoring information into inventory decisions for spare parts. We consider a manufacturer who periodically replenishes inventory for a machine part that is subject to deterioration. The deterioration is captured via condition monitoring and modeled using a Wiener process. The resulting degradation model is used to derive the life distribution of a functioning part and to estimate the demand distribution for spare parts. This estimation is periodically updated, in a Bayesian manner, as additional information on part deterioration is obtained. We develop an inventory model that incorporates this updated demand distribution and demonstrate that a dynamic base‐stock policy, in which the optimal base‐stock level is a function of some subset of the observed condition monitoring information, is optimal. We propose a myopic critical fractile policy that captures the essence of the optimal policy, but is easier to compute. Computational experiments indicate that this heuristic performs quite well relative to the optimal policy. Adaptive inventory policies such as these can help manufacturers to increase machine availability and reduce inventory costs.     

The Differential and Contingent Impact of Concurrency on New Product Development Project Performance: A Holistic Examination*

This article comprehensively examines how the four facets of new product development (NPD) concurrency, consisting of process and product concurrency groupings, influence NPD project performance under the five contextual conditions of (i) location of product in family stream, (ii) project size, (iii) stage in the product life cycle, (iv) innovativeness of the product, and (v) predictability of market demand. Using data from a large sample of NPD projects in multiple industries, there is support for this hypothesized four‐faceted structure of concurrency, consisting of process and product concurrency groupings, thereby contributing new knowledge to the concurrency literature. All four facets of concurrency display a contingent impact on NPD project performance, even though individual effects vary according to the specific contextual variable under consideration. In particular, the process concurrency facet of dynamic iterative routines was universally effective across all five contextual variables, while the product concurrency facet of cross‐functional coordination was effective in significantly influencing at least one NPD project measure. This article also reports similar, but less strong, contingency patterns, with respect to the process concurrency facet of the implementation of downstream coordination and the product concurrency facet of the use of computer‐based integrated design tools. Theoretical and practical implications of our results are also offered.     

基于不同交货期策略的两供应商-单制造商协同供货模型

构建了基于不同交货期策略的两供应商-单制造商协同供货模型.在对基于交货窗的协议交货期交货策略1和基于费用分担的可控交货期交货策略2进行分析和描述后,根据策略1建立了交货窗下基于协议交货期的两供应商-单制造商的stackelberg对策模型,分析了各自的最优决策;根据策略2建立了费用分担机制下基于可控交货期的两供应商-单制造商协调优化模型,给出了求解最优值的算法.接着分析了策略2优于策略1下的交货期压缩费用分担系数,给出了分担系数的范围,在此基础上建立了基于改进理想点的不对称Nash协商交货期压缩费用分担协调策略.最后通过数例对两种交货策略进行了分析比较并验证了本文的分担协调策略是有效的.     

创新驱动下光伏产业供应链的竞协研究——基于政府竞争政策

将政府竞争政策与技术创新因素引入到两级多晶硅供应链博弈模型中,研究不同情形下政府竞争奖励与技术创新努力水平对于各级制造商最优利润的影响。构建关于硅片批发价与光伏系统销售量的利润博弈模型,求得了各级制造商的最优利润函数,并通过实证研究分析了竞争与协调两种情形下竞争政策与技术创新因素对于各级制造商最优与整体供应链总利润的影响。研究表明：(1)政府竞争政策有利于增加制造商的利润;(2)技术创新努力水平的升高可以较快的增加制造商的利润;(3)与竞争情形相比,协调情形下各制造商的利润及整个供应链总利润更高。     

Value‐Driven Creation of Functionality in Software Projects: Optimal Sequencing and Reuse

We study the problem of optimally sequencing the creation of elements in a software project to optimize a time‐weighted value objective. As elements are created, certain parts of the system (referred to as “groups”) become functional and provide value, even though the entire system has not been completed. The main tradeoff in the sequencing problem arises from elements that belong to multiple groups. On the one hand, creating groups with common elements early in the project reduces the effort required to build later functionality that uses these elements. On the other hand, the early creation of such groups can delay the release of some critical functionality. We formulate the element sequencing problem and propose a heuristic to solve it. This heuristic is compared against a lower bound developed for the problem. Next, we study a more general version of the element sequencing problem in which an element requires some effort to be made reusable. When a reusable element is used in another group, some more effort is needed to specialize the element to work as desired in that group. We study reuse decisions under a weighted completion time objective (i.e., the sum of the completion time of each group weighted by its value is minimized), and show how these decisions differ from those under a traditional makespan objective (i.e., only the final completion time of the project is minimized). A variety of analytical and numerical results are presented. The model is also implemented on data obtained from a real software project. A key finding of this work is that the optimal effort on reuse is never increased (typically lowered) when a weighted completion time objective is used. This finding has implications for managing reuse in projects in which user value influences the order in which functionality is created.     

Unsold Versus Unbought Commitment: Minimum Total Commitment Contracts with Nonzero Setup Costs

We study a minimum total commitment (MTC) contract embedded in a finite‐horizon periodic‐review inventory system. Under this contract, the buyer commits to purchase a minimum quantity of a single product from the supplier over the entire planning horizon. We consider nonstationary demand and per‐unit cost, discount factor, and nonzero setup cost. Because the formulations used in existing literature are unable to handle our setting, we develop a new formulation based on a state transformation technique using unsold commitment instead of unbought commitment as state variable. We first revisit the zero setup cost case and show that the optimal ordering policy is an unsold‐commitment‐dependent base‐stock policy. We also provide a simpler proof of the optimality of the dual base‐stock policy. We then study the nonzero setup cost case and prove a new result, that the optimal solution is an unsold‐commitment‐dependent (s, S) policy. We further propose two heuristic policies, which numerical tests show to perform very well. We also discuss two extensions to show the generality of our method's effectiveness. Finally, we use our results to examine the effect of different contract terms such as duration, lead time, and commitment on buyer's cost. We also compare total supply chain profits under periodic commitment, MTC, and no commitment.     

Inventory Management for Customers with Alternative Lead Times

It is common for suppliers operating in batch‐production mode to deal with patient and impatient customers. This paper considers inventory models in which a supplier provides alternative lead times to its customers: a short or a long lead time. Orders from patient customers can be taken by the supplier and included in the next production cycle, while orders from impatient customers have to be satisfied from the on‐hand inventory. We denote the action to commit one unit of on‐hand inventory to patient or impatient customers as the inventory‐commitment decision, and the initial inventory stocking as the inventory‐replenishment decision. We first characterize the optimal inventory‐commitment policy as a threshold type, and then prove that the optimal inventory‐replenishment policy is a base‐stock type. Then, we extend our analysis to models to consider cases of a multi‐cycle setting, a supply‐capacity constraint, and the on‐line charged inventory‐holding cost. We also evaluate and compare the performances of the optimal inventory‐commitment policy and the inventory‐rationing policy. Finally, to further investigate the benefits and pitfalls of introducing an alternative lead‐time choice, we use the customer‐choice model to study the demand gains and losses, known as demand‐induction and demand‐cannibalization effects, respectively.     

PRICE‐DEPENDENT INVENTORY MODELS WITH DISCOUNT OFFERS AT RANDOM TIMES*

We consider an inventory model with a supplier offering discounts to a reseller at random epochs. The offer is accepted when the inventory position is lower than a threshold level. We compare three different pricing policies in which demand is induced by the resellers price variation. Policy 1 is the EOQ policy without discount offers. Policy 2 is a uniform price, stock‐independent policy. Policy 3 is a stock level‐dependent, discriminated price policy. Assuming constant demand rates, expressions are obtained for the optimal order quantities, prices, and profits. The numerical experiments show that if it is better to accept a suppliers discount, then it benefits the reseller to transfer the discount to downstream customers.     

电子商务环境下合作采购效益分析

合作采购是一种重要的企业间电子商务应用模式,成功实施合作采购需要供应链成员的积极参与。本文针对供应商采取的两种批发价定价策略,比较分析了协调成本对买主间合作采购动力及其总体采购成本的影响。其结果表明,只要协调成本较小,买主便具有合作采购动力,且无论供应商采取固定价格策略还是采取数量折扣策略,都存在一个协调成本临界值,当协调成本小于该临界值时,合作采购将同时减少买主与供应商的总体成本;当协调成本大于该临界值时,则总有一方的总体成本在合作采购中增加。     

Myopic Analysis for Multi‐Echelon Inventory Systems with Batch Ordering and Nonstationary/Time‐Correlated Demands

We provide an exact myopic analysis for an N‐stage serial inventory system with batch ordering, linear ordering costs, and nonstationary demands under a finite planning horizon. We characterize the optimality conditions of the myopic nested batching newsvendor (NBN) policy and the myopic independent batching newsvendor (IBN) policy, which is a single‐stage approximation. We show that echelon reorder levels under the NBN policy are upper bounds of the counterparts under both the optimal policy and the IBN policy. In particular, we find that the IBN policy has bounded deviations from the optimal policy. We further extend our results to systems with martingale model of forecast evolution (MMFE) and advance demand information. Moreover, we provide a recursive computing procedure and optimality conditions for both heuristics which dramatically reduces computational complexity. We also find that the NBN problem under the MMFE faced by one stage has one more dimension for the forecast demand than the one faced by its downstream stage and that the NBN policy is optimal for systems with advance demand information and stationary problem data. Numerical studies demonstrate that the IBN policy outperforms on average the NBN policy over all tested instances when their optimality conditions are violated.     

Redistribution Through Education and Other Mechanisms Under Capital‐Market Imperfections and Uncertainty: A Welfare Effect Analysis

Abstract. This paper considers a two‐period model of endogenous human capital formation under the credits‐market imperfection and uncertainty assumptions. We compare in the first part of the paper ex‐ante and ex‐post general‐equilibrium effects of the education subsidy policy to those of the negative income tax and the unskilled wage subsidy regimes. We show that the education subsidy policy raises an efficiency‐inequality trade‐off issue, and therefore it is optimal unless the degree of inequality aversion is relatively high and financing the subsidy is not too distorsive. Public loans are generally claimed to provide a solution for such issue. We explore the implications of implementing the public loan under several schemes in the second part of the paper. We show that combining between a pure public loan and education subsidies provides higher levels of welfare than these two policies taken separately provided that the inequality aversion degree is high. For low degrees of inequality aversion, the pure public loan is the optimal policy.     

有限需求信息下基于回购契约的供应链鲁棒协调策略

研究了仅知需求均值和区间信息条件下,基于最小最大后悔值准则的供应链回购契约协调问题。针对未知需求具体分布形式的两级供应链系统,在回购契约框架下,建立了以鲁棒决策和最优决策下的供应链及其成员绩效之差为目标函数的供应链协调模型。在仅知需求区间和均值信息条件下,采用鲁棒优化方法求解了最小最大后悔值准则下的集成供应链鲁棒订货策略和分散供应链鲁棒契约协调策略及其绩效偏差。分析了不同服务水平和契约参数条件下,由于信息缺失而未能实现最优运作的供应链及其成员绩效损失情况。最后,进行了数值计算,验证了通过鲁棒优化方法得到的供应链回购契约协调策略的鲁棒性和有效性。结果表明,基于回购契约的供应链鲁棒协调策略能够有效抑制需求不确定性对系统及其成员运作绩效的影响,同仅知需求区间信息相比,额外获得需求均值信息能够有效改进供应链运作绩效。     

不同信息透明度对分销系统及各成员的影响

考虑由一个供应商和多个零售商组成的分销系统。研究高、中、低三种不同信息透明度模式下系统的最优补货及分配策略以及相应的系统和各个零售商的期望成本。证明无论从系统的角度还是从零售商的角度,并非信息透明度越高,期望成本越低。从整个系统的角度来讲,虽然系统的期望成本总在高信息透明度模式下取得最低,但是,中低两种信息透明度模式谁取得第二低的系统期望成本取决于系统内各节点之间的距离以及零售商所面对客户需求的性质。从零售商的角度,高信息透明度并不能降低零售商的期望成本。零售商是否可以从较高的信息透明度水平中获益则取决于零售商在送货路线上所处的位置,系统内各节点之间的距离,以及零售商所面对客户需求的性质。     

Storing Fresh Produce for Fast Retrieval in an Automated Compact Cross‐Dock System

We study temporary storage of fresh produce in a cross‐dock center. In order to minimize cooling cost, compact storage systems are used. A major disadvantage of these systems is that additional retrieval time is needed, caused by necessary reshuffles due to the improper storage sequence of unit loads. In practice therefore, a dedicated storage policy is used in which every storage lane in the system accommodates only one product. However, this policy does not use the planned arrival time information of the outbound trucks. To exploit this information, this study proposes a mathematical model for a shared storage policy that minimizes total retrieval time. The policy allows different products to share the same lane. In order to solve real‐sized problems, an effective and efficient heuristic is proposed, based on a greedy construction and an improvement part, which provides near optimal solutions. The gaps between the results of the heuristic and the lower bound are mostly less than 1%. The resulting shared storage policy is generally robust against disturbances in arrival or departure times. We compare our shared storage heuristic with dedicated storage to determine which policy performs best under which circumstances. For most practical cases, shared storage appears to outperform dedicated storage, with a shorter response time and better storage lane utilization.     

Equilibrium Joining Strategies and Optimal Control of a Make‐to‐Stock Queue

We consider a make‐to‐stock, finite‐capacity production system with setup cost and delay‐sensitive customers. To balance the setup and inventory related costs, the production manager adopts a two‐critical‐number control policy, where the production starts when the number of waiting customers reaches a certain level and shuts down when a certain quantity of inventory has accumulated. Once the production is set up, the unit production time follows an exponential distribution. Potential customers arrive according to a Poisson process. Customers are strategic, i.e., they make decisions on whether to stay for the product or to leave without purchase based on their utility values, which depend on the production manager's control decisions. We formulate the problem as a Stackelberg game between the production manager and the customers, where the former is the game leader. We first derive the equilibrium customer purchasing strategy and system performance. We then formulate the expected cost rate function for the production system and present a search algorithm for obtaining the optimal values of the two control variables. We further analyze the characteristics of the optimal solution numerically and compare them with the situation where the customers are non‐strategic.     

Dynamic Pricing and Inventory Management with Regular and Expedited Supplies

We consider a periodic‐review inventory system with regular and expedited supply modes. The expedited supply is faster than the regular supply but incurs a higher cost. Demand for the product in each period is random and sensitive to its selling price. The firm determines its order quantity from each supply in each period as well as its selling price to maximize the expected total discounted profit over a finite or an infinite planning horizon. We show that, in each period if it is optimal to order from both supplies, the optimal inventory policy is determined by two state‐independent thresholds, one for each supply mode, and a list price is set for the product; if only the regular supply is used, the optimal policy is a state‐dependent base‐stock policy, that is, the optimal base‐stock level depends on the starting inventory level, and the optimal selling price is a markdown price that decreases with the starting inventory level. We further study the operational impact of such supply diversification and show that it increases the firm's expected profit, reduces the optimal safety‐stock levels, and lowers the optimal selling price. Thus that diversification is beneficial to both the firm and its customers. Building upon these results, we conduct a numerical study to assess and compare the respective benefit of dynamic pricing and supply diversification.     

Order Progress Information: Improved Dynamic Emergency Ordering Policies

Technologies such as radio‐frequency identification and global positioning systems can provide improved real‐time tracking information for products and replenishment orders along the supply chain. We call this type of visibility order progress information. In this paper, we investigate how order progress information can be used to improve inventory replenishment decisions. To this end, we examine a retailer facing a stochastic lead time for order fulfillment. We characterize a replenishment policy that is based on the classical (Q, R) policy and that allows for releasing emergency orders in response to the order progress information. We show that the optimal structure of this policy is given by a sequence of threshold values dependent on order progress information. In a numerical study we evaluate the cost savings due to this improved replenishment policy.     

Work Design and Integration Glitches in Globally Distributed Technology Projects

In a technology project, project integration represents the pooling together of complete, interdependent task modules to form a physical product or software delivering a desired functionality. This study develops and tests a conceptual framework that examines the interrelationships between the elements of work design, project integration challenges, and project performance. We identify two distinct elements of work design in technology projects: (i) the type of project organization based on whether a technology project spans a firm boundary (Domestic‐Outsourcing) or a country boundary (Offshore‐Insourcing) or both boundaries (Offshore‐Outsourcing) or no boundaries (Domestic‐Insourcing), and (ii) the joint coordination practices among key stakeholders in a technology project—namely, Onsite Ratio and Joint‐Task Ownership. Next, we measure the effectiveness of project integration using integration glitches that capture the incompatibility among interdependent task modules during project integration. Based on analysis of data from 830 technology projects, the results highlight the differential effects of distributed project organizations on integration glitches. Specifically, we find that project organizations that span both firm and country boundaries (Offshore‐Outsourcing) experience significantly higher levels of integration glitches compared to domestic project organizations (Domestic‐Outsourcing and Domestic‐Insourcing). The results further indicate that the relationship between project organization type and integration glitches is moderated by the extent of joint coordination practices in a project. That is, managers can actively lower integration glitches by increasing the levels of onsite ratio and by promoting higher levels of joint‐task ownership, particularly in project organization types that span both firm and country boundaries (Offshore‐Outsourcing). Finally, the results demonstrate the practical significance of studying integration glitches by highlighting its significant negative effect on project performance.