RFID‐Enabled Visibility and Retail Inventory Record Inaccuracy: Experiments in the Field

Accurate inventory records are key to effective store execution, affecting forecasting, ordering, and replenishment. Prior empirical research, however, shows that retailer inventory records are inherently inaccurate. Radio Frequency Identification (RFID) enables visibility into the movement of inventories in the supply chain. Using two different field experiments, the current research investigates the effectiveness of this visibility in reducing retail store inventory record inaccuracy (IRI). Study 1 used an interrupted time‐series design and involved daily physical counts of all products in one category in 13 stores (8 treatments and 5 controls) of a major global retailer over 23 weeks. Results indicate a significant decrease in IRI of approximately 26% due to RFID‐enabled visibility. Using an untreated control group design with pre‐test and post‐test, Study 2 expands the number of categories to five and the number of stores to 62 (31 treatment and 31 control stores). Results show that the effectiveness of RFID in reducing IRI varies by category (ranging from no statistically significant improvement to 81%). Results also suggest that RFID ameliorates the effects of known determinants of IRI and provide the key insight that the technology is most effective for product categories characterized by these determinants.     

Optimal Inattention to the Stock Market With Information Costs and Transactions Costs

Information costs, which comprise costs of gathering and processing information about stock values and costs of deciding how to respond to this information, induce a consumer to remain inattentive to the stock market for finite intervals of time. Whether, and how much, a consumer transfers assets between accounts depends on the costs of undertaking such transactions. In general, optimal behavior by a consumer facing both information costs and transactions costs is state‐dependent, with the timing of observations and the timing and size of transactions depending on the state. Surprisingly, if the fixed component of the transactions cost is sufficiently small, then eventually, with probability 1, a time‐dependent rule emerges: the interval between observations is constant and on each observation date, the consumer converts enough assets to liquid assets to finance consumption until the next observation. If the fixed component of transactions costs is large, the optimal rule remains state‐dependent indefinitely.     

The derivation of a brief Student Nurse Stress Index

The lack of an adequate measure of perceived sources of stress for student nurses led to the construction of the Student Nurse Stress Index (SNSI). Responses from 235 first-year student nurses to 35 items from the Beck and Srivastava Stress Inventory (Beck, and Srivastava, 1991), and 15 new items, were subjected to exploratory factor analysis using principal components analysis and oblimin rotation. A reliable 22-variable solution with a simple oblique structure including Academic load, Clinical sources, Interface worries, and Personal problems factors was obtained in this initial sample, and confirmed at an exploratory level in a further independent validation sample of 188 first-year students. Confirmatory factor analysis established the four-factor model in the first sample, but required that three variables load onto more than one factor. This more complex four-factor model was confirmed using independent data from the validation sample, and the total invariance of factor loadings and factor covariances of this more complex four-factor model was established in both data sets simultaneously using multi-sample techniques. The SNSI shows cross-sample factor congruence, good internal reliabilities, and concurrent and discriminant validity across a range of reporting conditions.     

Development of an integrated information management model: A case of textile industry

For past two decades many organisations have tried to implement integrated information management systems for better production management based on co-ordination of information and therefore activities of different departments. Although Enterprise Resource Planning systems have been in the market for the past decade, many industries find it difficult to implement such systems due to the amount of work involved in streamlining the documentation, customisation and of high costs reported in implementation. An attempt is made through this paper to propose an integrated model, which can be easily understood by production personnel, with specific emphasis on the textile sector.     

On vendor part delivery dates in a stochastic assembly system

This paper describes the development of a model for the determination of optimal mean part delivery dates in a stochastic assembly system for the objective of minimizing the expected cost of subassembly and part inventory. Parts are assembled at each station to a subassembly. The part delivery and processing times at assembly stations follow known probability distributions. An approximate solution technique based on the optimization of individual stations in isolation is developed. The approximation applies a correction factor, as a function of the variability in part delivery and processing time, cost parameters and number of stations, to the decisions from the single station solutions to compensate for interdependence between stations. Results indicate that this is an effective approach and yields good near-optimal solutions with very little computational effort. Insights regarding the effect of the type of distribution used, random processing times, variance of the distribution used and cost parameter values on part delivery dates are also reported.     

Modular design of integrated databases in production management systems

Abstract

Complexity is a serious problem with respect to the application of information technology in the field of production management. This paper presents an overview of the more fundamental problems encountered and proposes a solution for some of those problems in the form of modular decomposition of the conceptual database structure. It is argued that the complexity of information systems is closely connected to the complexity of the organization. Therefore a condition for the realization of integrated information systems for production management is a simplification of the organizational structure by way of defunctionalization and the forming of autonomous units.     

New developments in generative BOM processing systems

Abstract

The principle of generative bill-of-material (BOM) processing systems is that different BOMs belonging to different product variants can be represented by a single, so-called source BOM. The BOM processing systems comprise additional data structures which hold information on the relationships between product characteristics of parent product variants and component product variants, and on the relationships between characteristics of a parent product variant and its BOM data. These relationships allow the automatic generation of the individual BOM of each represented product variant. There are several alternative ways of implementing a generative BOM processing system. The oldest concept known is the variant BOM concept. This concept provides a relatively simple solution to deal with large varieties of final product variants. However the concept has a number of drawbacks such as the representation of product variety at lower levels in the product structure and data redundancy which hampers data maintenance. In this paper an improved concept for generative BOM processing systems is introduced and described: the generic BOM concept. The generic BOM concept does not focus on representing final product variants only, but takes a broader view towards representing any range of product variants at any level in the product structure. This starting point solves a number of draw-backs implied by the variant BOM concept but it also requires new definitions of BOM relationships and the introduction of new data structures to support the generation of individual BOMs.     

Setups and effective capacity: the impact of lot sizing techniques in an MRP environment

This study investigates how lot sizing techniques influence the profit performance, inventory level, and order lardiness of an assembly job shop controlled by MRP. Four single-level lot sizing techniques are compared by simulation analysis under two levels of master schedule instability and two levels of end item demand. A second analysis investigates the influence of a multilevel lot sizing technique, the generalized constrained-K (GCK) cost modification, on the four single-level techniques at low demand and low nervousness. The analyses reveal a previously unreported phenomenon. Given the same inventory costs, the single-level lot sizing techniques generate substantially different average batch sizes. The lot sizing techniques maintain the following order of increasing average batch size (and decreasing total setup time):

economic order quantity (EOQ)

period order quantity (POQ)

least total cost (LTC)

Silver-Meal heuristic (SML)

The causes for different average batch sizes among the lot sizing techniques are analysed and explained. Demand lumpiness, inherent in multilevel manufacturing systems controlled by MRP, is found to be a major factor. The number of setups each lot sizing technique generates is the primary determinant of profit performance, inventory level, and order tardiness. EOQ, a fixed order quantity technique, is less sensitive to nervousness than the discrete lot sizing techniques. EOQ_, however, generates the smallest average batch size, and, therefore, the most setups. Since setups consume capacity, EOQ, is more sensitive to higher demand. SML generates the largest average batch sizes, and is, therefore, less sensitive to increased demand. At low demand, the other lot sizing techniques perform better on all criteria. They generate smaller batches and, therefore, shorter actual lead times. The GCK cost modification increases the average batch size generated by each lot sizing technique. GCK improves the profit and customer service level of EOQ the lot sizing technique with the smallest batches. GCK causes the other lot sizing techniques to generate excessively large batches and, therefore, excessively long actual lead times.     

Hierarchical model to design manufacturing systems applied to a metal-mechanic company

This paper describes the application of a model to design and manage the manufacturing process through an integrated system, using a Hierarchical methodology-by means of different aggregation and disaggregation stages with an appropriate time horizon. The hierarchical model obtained allows interfacing between the master schedule and the schedule of the orders. At each level of the hierarchical model some decisions have to be made in order to design the manufacturing system, but having a model that also takes into consideration the management of the system. To do this it is necessary to use aggregated information concerned with the level at which decisions are made. It is obtained from the database, which contains the information at the highest level of aggregation. This model has been applied to a metal mechanic company, that makes final products such as car washers, etc. The benefits of this approach for the company are addressed in this paper.     

Better know an HRD scholar: a conversation with Monica Lee

This article contains a conversation with Monica Lee, and is part of a series that focuses on different HRD scholars – the aim being to better understand the people behind the names we see in print. Monica is a Life Member of Lancaster University, was a founding member of the University Forum of HRD, and was the founding editor of Human Resource Development International. The conversation explores Monica's background, how she got into HRD, how she overcame dyslexia and recovered from her cerebral hemorrhage, how the University Forum was created, and how HRDI came about. The conversation also considers the consequences of placing boundaries around HRD, about how we are guided by our subconscious, and about the impact on HRD of future changes to organizations and structures.