A rule-based multi-criteria approach to inventory classification

The traditional inventory classification method classifies stock keeping units (SKUs) to three classes based on their annual dollar usage, while in real world problems, other criteria are important as well. In this paper, considering multi-criteria situations, a simple, effective and practical rule-based method is designed and implemented in a real world case, using MATLAB software. The most important characteristic of the proposed method is taking into account the inherent ambiguities that exist in the reasoning process of the system of classification. The methodology and the method proposed here may be easily implemented by inventory managers. The results obtained from the case study in this paper are compared with the analytic hierarchy process (AHP) method. Finally concluding remarks and suggestions for future work are provided.     

Multi-criteria ABC inventory classification with mixed quantitative and qualitative criteria

Large firms usually employ the well-known ABC inventory classification technique to have an efficient control on a huge amount of inventory items. While the traditional inventory classification method only considers one criterion, namely the annual dollar usage to classify inventory items, the recent literature shows a focus on multi-criteria inventory classification (MCIC) techniques. Surprisingly, among several methods that have been developed for the MCIC problem, there are just a few, which clearly account for qualitative criteria, while most of the affecting criteria are of qualitative type in nature. This paper presents a modified linear optimisation method that enables inventory managers to classify a number of inventory items in the presence of both qualitative and quantitative criteria without any subjectivity. Furthermore, an efficient procedure is proposed to maximise the minimum importance attached to various criteria leading to improvement of discriminating power among inventory items. For validating the proposed method, it is applied on a case study taken from the literature and a comparative study with the existing competent methods is also provided.     

Zero inventory and firm performance: a management paradigm revisited

According to the ‘zero inventory’ paradigm, inventory reflects waste and should be eliminated in order for performance to rise. In this study, we investigate the effect of inventory holding on firm performance, analysing 3057 firm years of data. Interpreting performance as a function of inventory, results show that firms with the lowest inventory have the worst performance (and vice versa). When understanding inventory as a function of performance, results indicate that low-performing firms carry the least inventory, whereas high-performing firms have the highest stocks. Besides questions of causality, our results do not support a paradigm which suggests that firms should move toward zero inventory.     

Dynamic re-order point inventory control with lead-time uncertainty: analysis and empirical investigation

A new forecast-based dynamic inventory control approach is discussed in this paper. In this approach, forecasts and forecast uncertainties are assumed to be exogenous data known in advance at each period over a fixed horizon. The control parameters are derived by using a sequential procedure. The merits of this approach as compared to the classical one are presented. We focus on a single-stage and single-item inventory system with non-stationary demand and lead-time uncertainty. A dynamic re-order point control policy is analysed based on the new approach and its parameters are determined for a given target cycle service level (CSL). The performance of this policy is assessed by means of empirical experimentation on a large demand data set from the pharmaceutical industry. The empirical results demonstrate the benefits arising from using such a policy and allow insights to be gained into other pertinent managerial issues.     

Inventory performance of some supply chain inventory policies under impulse demands

This paper attempts to study the impact of impulsive demand disturbances on the inventory-based performance of some inventory control policies. The supply chain is modelled as a network of autonomous supply chain nodes. The customer places a constant demand except for a brief period of sudden and steep change in demand (called demand impulse). Under this setting, the behaviour of each inventory policy is analysed for inventory performance of each node. It is found that the independent decision-making by each node leads to a bullwhip effect in the supply chain whereby demand information is amplified and distorted. However, under a scenario where the retailer places a constant order irrespective of the end customer demand, the inventory variance was actually found to decrease along the supply chain. The variance of the inventory remained constant along the chain when only the actual demands are transmitted by each node. The results also showed that the inventory policy which is best for one supply chain node is generally less efficient from a supply chain perspective. Moreover, the policy which performs poorly for one node can be most efficient for the supply chain. In a way, our results also provide a case for coordinated inventory management in the supply chain where all members prepare a joint inventory management policy that is beneficial for all the supply chain nodes. The results have significant industrial implications.     

Multiple criteria ABC inventory classification using two virtual items

ABC inventory classification is one of the most popular techniques for organisations to efficiently plan and control thousands of inventory items. Its traditional way is solely based on a single criterion; however, it has been recognised that multiple criteria need to be considered in practice. An alternative approach to multiple criteria inventory classification (MCIC) is proposed by using two virtual items and incorporating the TOPSIS. The proposed approach improves some previous allied methods as it provides a more reasonable and comprehensive performance index and a unique inventory classification without any subjectivity. Comparisons with other allied methods are illustrated through a case study.     

Analyzing the effect of inventory policies on the nonstationary performance with transfer functions

In this paper we apply transfer function methods to analyze the performance of supply chains in response to nonstationary demand and, in particular, we investigate how various inventory policies and demand forecasting parameters affect supply chain responsiveness. In a single-echelon inventory system we investigate the performance of a common base stock policy. Specifically, we describe the order and inventory trajectories using discrete transfer functions, and we derive closed-form analytical expressions for the transient behavior in response to a step change in demand. We introduce performance measures commonly used to analyze nonstationary performance and derive closed-form expressions for these measures. Next, we study the performance of a two-echelon supply chain under installation stock and echelon stock policies. We explicate the performance tradeoff in response to stationary versus nonstationary demand, and show that the transient response of orders and inventory levels can be either underdamped or overdamped depending on the exponential smoothing parameter. We show that the echelon stock policy is more responsive than the installation stock policy when both policies have similar stationary performances.     

On measuring company performance within a supply chain

Emerging research strengthens the connection between supply chain performance and a company's financial performance (D’Avanzo, R., Von Lewinski, H. and Van Wassenhove, L. N., 2003. The link between supply chain and financial performance. Supply Chain Management Review, November/December, 40–47). The focus on integrating functional internal processes has expanded to include the need for integrating these with external processes of business partners (Edwards, P., Peters, M. and Sharman, G., 2001. The effectiveness of information systems in supporting the extended supply chain. Journal of Business Logistics, 22(1), 1–27). This need for enterprise efficiency is compelling companies to review, to identify, and to adopt supply chain initiatives. This research investigates the use of common measurement metrics in an attempt to determine which one(s) are most useful for measuring performance as companies implement SCM practices. For firms that were engaged in SCM we found inventory and cycle time to be the most significant metrics.     

Antecedents of effective performance measurement system implementation: an empirical study of UK manufacturing firms

This paper examines the antecedents to effective performance measurement system (PMS) implementation. There have been only a few studies which have investigated this topic, and to-date there is no consensus about what factors are significant. Using empirical data collected from 349 UK manufacturing firms, we identify six potential factors from an item pool derived from an extensive literature review. Subsequent regression analysis reveals that all six factors have a significant influence on PMS implementation effectiveness. We characterise these factors into two sub-sets, with the technical sub-set accounting for most of the variance in the dependent variable. We also demonstrate that ‘softer’ social factors additionally have a significant, albeit comparatively small, effect. These, we argue, are essential in order to bind an organisation’s approach to performance measurement into one cohesive whole. Our findings provide managers with a clearer view of the factors which may influence the effectiveness of their PMS implementation. Moreover, we anticipate that the findings should provide empirical stimulation of an important debate about how to ensure that organisations can implement PMSs that are adequate for their purposes. As such, while the findings have current utility, their additional value is in providing a platform for subsequent research.     

An empirical examination of the assumptions of the Square Root Law for inventory centralisation and decentralisation

The Square Root Law (SRL) is a popular formula for assessing inventory levels at varying numbers of warehouses. Its popularity is probably due to its simplicity and the ample opportunities for its application to the managerial dilemma of inventory centralisation vs. decentralisation. However, researchers disagree about which parts of inventory it can be applied to and its underlying assumptions. To address these questions, this study algebraically derives the assumptions necessary for the SRL to apply to regular, safety and total stock. Afterwards, the paper empirically examines to what extent these assumptions hold in practice by analysing four case studies and data from a sample of 280 German manufacturing and trading companies. Most companies do not fulfil the assumptions of the SRL and therefore cannot apply it with accurate results. Trading companies, however, seem to fulfil more assumptions than manufacturing ones, retailers more than wholesalers, industrial goods manufacturers more than consumer goods manufacturers. Although the SRL has traditionally been mainly considered for safety stock, companies, especially trading companies, appear to rather fulfil the assumptions for applying the SRL to cycle stock. Some assumptions seem to be complementary, whereas others appear to be competing, so that it is difficult to fulfil all of them.     

On the demand distributions of spare parts

Spare parts have become ubiquitous in modern societies, and managing their requirements is an important and challenging task with tremendous cost implications for the organisations that are holding relevant inventories. Demand for spare parts arises whenever a component fails or requires replacement, and as such the relevant patterns are different from those associated with ‘typical’ stock keeping units. Such demand patterns are most often intermittent in nature, meaning that demand arrives infrequently and is interspersed by time periods with no demand at all. A number of distributions have been discussed in the literature for representing these patterns, but empirical evidence is lacking. In this paper, we address the issue of demand distributional assumptions for spare-parts management, conducting a detailed empirical investigation on the goodness-of-fit of various distributions and their stock-control implications in terms of inventories held and service levels achieved. This is an important contribution from a methodological perspective, since the validity of demand distributional assumptions (i.e. their goodness-of-fit) is distinguished from their utility (i.e. their real-world implications). Three empirical datasets are used for the purposes of our research that collectively consist of the individual demand histories of approximately 13,000 SKUs from the military sector (UK and USA) and the Electronics Industry (Europe). Our investigation provides evidence in support of certain demand distributions in a real-world context. The natural next steps of research are also discussed, and these should facilitate further developments in this area from an academic perspective.     

Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects

Big data has recently been recognised as one of the most important areas of future technology. It has attracted the attention of many industries, since it has the potential to provide companies with high business value. This paper examines the forms of business value that companies can create from big data analytics investments, the direct impacts it has on the financial performance of a firm, and the mediating effects of market performance and customer satisfaction. Drawing on the resource-based view theory, this study demonstrates that the business value achieved from investments in big data analytics leads to advantages in terms of the financial performance of a firm. The results offer evidence of the existence of a customer satisfaction mediation effect and of the absence of a market performance mediation effect. Theoretical and practical implications are discussed at the end of the paper.     

An empirical investigation of antecedents to information exchange in supply chains

In this investigation, following the principal-agent theory, possibilities to reduce existing information asymmetries are derived and their effects on the information exchange are examined. Results of an empirical investigation based on a structural equation model confirm that monitoring measures and frequent meetings positively influence the exchange of information while explicit contracts have rather negative effects. Premiums and specific investments, however, seem to play insignificant roles. Measures, such as building a reputation mechanism, will probably prove to be effective only in the long run.     

On deficiencies of common ordering policies for multi-level inventory control

We consider two common types of ordering policies for multi-level inventory control: installation stock (R,Q)-policies and echelon stock (R,Q)-policies. The batch quantities are assumed to be given, but each policy is optimized with respect to its reorder point R. We demonstrate that there is no bound for the worst case performance ratio of these policies when applied to distribution inventory systems with a central warehouse and a number of retailers.     

Sustainable supply chain management in Indian organisations: an empirical investigation

The present work is an attempt to investigate the adoption of sustainable supply chain management (SSCM) practices amongst manufacturing and process based organisations in India and its impact on organisational performance encompassing all three dimensions of sustainability. SSCM practices conceived in the present study include environmental management practices (EMP), socially inclusive practices for employees (SPE), socially inclusive practices for community (SPC), operations practices (OP) and supply chain integration (SCI) which were treated as exogenous variables. Organisational performance considered in this study includes five dimensions, namely environmental performance (EPR), employee-centred social performance (ESP), community-centred social performance (CSP), operations performance (OPR) and competitiveness, which were regarded as endogenous variables. The analysis was carried out with the help of structural equation modelling considering natural logarithm of manpower as a control variable. Few major findings are mentioned. EMP does not have any significant association with OPR, nor does it result in competitiveness. However, when jointly mediated through both EPR and OPR, EMP leads to competitiveness. SPC has significant negative association with competitiveness, when only direct relationship is considered. However, indirect relationship between SPC and competitiveness shows significant positive association when mediated through CSP. The resultant total effect between SPC and competitiveness turns out to be insignificant. Further, OPR fully mediates the relationship between OP and competitiveness. Managerial implications of the findings are discussed.     

Throughput/inventory dollar-days: TOC-based measures for supply chain collaboration

As the semiconductor industry moves away from vertical integration, performance measures play an increasingly important role to ensure effective collaboration. This paper demonstrates that the theory of constraints (TOC)-based measures, Throughput and Inventory Dollar-Days (T/IDD), induce autonomous supply chain (SC) links to function as a synergistic whole and thereby, improve the performance of the whole SC network significantly. We model an SC network of a well-known TOC case study using discrete event simulation and discuss managerial implications of these measures via a set of scenarios. The scenarios explain how these measures – without sharing sensitive financial data – allow members of an SC network to monitor both the effectiveness (TDD) and efficiency (IDD) of SC members and lead them to create win-win solutions following well-known TOC-based planning and control concepts. We conclude this paper by discussing some limitations of the proposed research and provide directions for future theoretical research.     

Tool path generation via the multi-criteria optimisation for flat-end milling of sculptured surfaces

A method of generating optimal tool paths for sculptured surface machining with flat-end cutters is presented in this paper. The inclination and tilt angles, as well as the feed directions of the cutter at each cutter contact point on a machining path are optimised as a whole so that the machining width of the tool path can be as large as possible, and concerns such as smooth cutter motion, gouging avoidance, scallop height and machining widths overlap are also considered when calculating a path. A multi-criteria tool path optimisation model is introduced, and it is converted into a single objective optimisation with the weighted sum method. The Differential Evolution (DE) algorithm is suitable for solving this highly non-linear problem. However, the searching process of the DE algorithm may be trapped in local minima due to large number of design variables. Therefore, an algorithm combining the DE algorithm and the sequence linear programming algorithm is developed to solve this optimisation model. The proposed method is applied to two freeform surfaces to illustrate its effectiveness.     

基于供应链技术的铜盘管季节性库存问题研究

总结铜盘管市场特点,详细分析季节性库存过程中存在的库存产品积压风险、库存产品质量风险、铜价波动风险以及资金短缺风险,提出利用供应链库存管理技术、延迟化策略、套期保值、融通仓等现代供应链管理理论来降低季节性库存所面临的各种风险。     

Vendor-managed inventory and the effect of channel power

We analyze decentralized supply chains that follow general continuous review (Q, R) inventory policies subject to vendor-managed inventory agreements where the supplier chooses the order quantity Q, and the retailer chooses the reorder point R. Within the VMI scenario, we explore the effect of divisions of channel power on supply chain and individual agent performance by examining different game theoretic models. Optimal policies and analytical results, including existence and uniqueness proofs for equilibrium solutions under VMI, are derived. Numerical results are provided to compare the effectiveness of VMI and to analyze different channel power relationships under a variety of environmental conditions. We find that VMI can result in considerable supply chain savings over traditional relationships and that the relative division of channel power can significantly effect the performance of VMI. Interestingly, we find that the greatest system benefits from VMI arise in asymmetric channel power relationships, but that individual agents lack the incentive to assume a leadership role.