Neuroticism,locus of control,type A behaviour pattern and occupational stress

Abstract

The aim of this study was to investigate the relationship between individual differences in personality and susceptibility to stress in the workplace. Stress in lecturers employed by a computer training organization was assessed by means of self-report and measurement of salivary cortisol output during lecturing and non-lecturing weeks. Neuroticism, Type A behaviour pattern and locus of control were measured. Self-reported stress was found to be much greater during lecturing weeks, but cortisol levels were unaffected by working conditions. There was a significant positive correlation between neuroticism and locus of control and a negative correlation between locus of control and Type A behaviour pattern that approached significance. Multiple regression was employed to explore relations between personality and stress. Subjects with lower neuroticism scores yielded a bigger increase in reported stress, in the lecturing compared with the non-lecturing week, than subjects with high neuroticism scores. Type B subjects showed a progressive decrease in cortisol over the working week while Type A counterparts showed a resurgence of cortisol towards the end of the week. Finally, Type B subjects having an internal locus of control showed a faster decline in cortisol level during the lecturing week than the other subjects. Implications of these results are discussed in terms of the importance simultaneously incorporating a variety of individual differences in personality dimensions and stress indices in research designs.     

The impact of random machine unavailability on inventory policies in a continuous improvement environment

There are production situations where a production facility (e.g. a machine) is used intermittently to produce lot sizes of certain products. Upon completion of production run, the facility may not be available for a random amount of time due to several reasons, such as: the facility needs to be maintained and the maintenance time is random due to unforeseen circumstances; or that the facility is leased by different manufacturers and the demand for the facility is random. As a result of machine unavailability, stock-out situations might arise. This paper extends the work of Abboud et al . (2000, Computers and Operations Research , 27 , 335-351) by assuming learning and forgetting in production. A new mathematical model is developed with numerical examples and sensitivity analysis provided. Furthermore, this paper determines how the overall inventory cost is influenced by the nature of the random variable that represents the unavailability time of the production facility.     

A decomposition technique for quantifying real process performance

A decomposition technique for quantifying the impacts of changes in product mix and process performance on aggregate process-related indicators is presented. Through application of the technique, the real performance of a process can be quantified. Changes in real performance over time can be monitored to provide useful information for process evaluation and production planning. Two case studies, one related to the aggregate defective rate for an assembly line of an integrated circuit fabrication plant and the other to the aggregate inventory turnover for a tyre distribution company, are presented to illustrate the application of the technique.     

Quantifying the effectiveness of VMI and integrated inventory management in a supply chain with uncertain lead-times and uncertain demands

This article considers the inventory management problem in a supply chain with uncertain replenishment lead-times and uncertain demands. The optimal integrated inventory management (IIM) policy is developed using stochastic dynamic programming theory. The IIM policy is contrasted with two pull-type vendor-managed inventory policies (VMI-1 and VMI-2) and a traditional retailer-managed inventory policy (RMI). Computational results show that in such stochastic supply chains, IIM performs about 23, 15, and 3% better than the optimised RMI, VMI-1 and VMI-2 policies, respectively, while two VMI policies are about 8 and 20% better than the best RMI. The basestock-based VMI-2 is a very good form of VMI. The ANOVA analysis reveals that the replenishment lead-times have the largest effect on the relative performance between IIM and other policies. Numerical examples demonstrated that the IIM policy has good structural properties and can be characterised by a set of switching curves.     

Hierarchical production planning at a multiproduct multiprocessor fibreglass manufacturing facility

Abstract

Abstract. A hierarchical production planning model is developed for a forming facility of a major fibreglass manufacturer. The model establishes aggregate quarterly quantities for families of products, monthly disaggregate production quantities for end-items within these families, and a weekly sequencing schedule of end-items. A key feature of the planning system is its ability to decompose total set-up cost into primary and secondary components and to account appropriately for each component at a distinct level of the planning hierarchy. The mathematical programming formulations, the accompanying solution algorithms, and the results of their application to nine months of actual company demand and cost data are presented.     

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.     

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.     

Measuring Sharedness of Team-Related Knowledge: Design and Validation of a Shared Mental Model Instrument

Many researchers have explored how people share and construct similar mental models in teams. They have claimed that successful team performance depends on a shared mental model of team members about task, team, equipment and situation. Most of the literature has illustrated simplified relationships between a team's mental model and their performance without a valid instrument addressing the confined and relevant constructs of a shared mental model. This paper describes the instrument development steps and the conceptual framework for factors associated with shared mental models. After development and refinement, the instrument was finalized for use to measure team-related knowledge. The final instrument consists of 42 items that are linked to the five emergent factors of shared mental models including general task and team knowledge, general task and communication skills, attitude toward teammates and task, team dynamics and interactions, and team resources and working environment.     

Bored employees misbehaving: The relationship between boredom and counterproductive work behaviour

In this study, the relationships among boredom proneness, job boredom, and counterproductive work behaviour (CWB) were examined. Boredom proneness consists of several factors, which include external stimulation and internal stimulation. Given the strong relationships between both the external stimulation factor of boredom proneness (BP-ext) and anger as well as the strong relationship between trait anger and CWB, we hypothesized that examining BP-ext would help us to better understand why employees commit CWB. Five types of CWB have previously been described: abuse against others, production deviance, sabotage, withdrawal and theft. To those we added a sixth, horseplay. Using responses received from 211 participants who were recruited by email from throughout North America (112 of them matched with co-workers), we found support for our central premise. Indeed, both BP-ext and job boredom showed significant relationships with various types of CWB. The boredom proneness factor also moderated the relationship between job boredom and some types of CWB, suggesting that a better understanding of boredom is imperative for designing interventions to prevent CWB.