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Freight carriers operating in a spot-market environment are faced with uncertain future capacity demand, actual revenues, and properties of freight items. They require information about the expected future consumption of limited capacity to derive suitable request acceptance decisions. The purpose of this paper is to present a new idea to improve the handling of inaccurate information on the weight and volume of upcoming requests.

The authors start with the definition of a new mathematical optimization model as the backbone of a capacity control system. This model is embedded within a rolling-horizon decision-making process involving consecutively arriving requests. Computational simulation experiments are carried out to evaluate the applicability and efficiency of the proposed decision support system. The authors investigate how the new model contributes towards keeping the negative impacts of inadequate forecasts of the expected volume of future requests as low as possible.

In traditional application fields of capacity control (airline ticketing or hotel reservations) the physical extent of a request is always 1 (set/bed/room). In road-based freight transportation the variety of the physical extent of requests is much more complicated and complex. The major finding is that existing capacity control approaches are unable to meet the special requirements of road-haulage. Innovative capacity control features are necessary in order to cope with the higher request portfolio complexity.

This paper addresses the requirements of a capacity control system for road-based freight transportation. An innovative decision support system is evaluated. For the first time, the authors present a comprehensive quantitative simulation study dedicated to this complicated decision-making situation.

The coping of demand oscillation is an important challenge in dynamic transport planning. A reliable request fulfillment must be provided even if the number of incoming requests temporarily climbs over the expected demand and resource scarceness appears. The aim of this paper is to propose an innovative planning approach that enables a transportation fleet to maintain a sufficiently high percentage of timely‐fulfilled customer requests even in demand peak situations.

The effectiveness of the new approach is verified in computational simulation experiments. Quantifications for the system's responsiveness are proposed. Then, the quantified knowledge about the intermediate responsiveness is exploited to adjust the decision model representing the next schedule update task in a rolling horizon re‐planning.

The observed simulation results suggest the suitability of the proposed approach. An adjustment of the plan update model supports the maintenance of a high percentage of timely completed requests during and after the demand peak.

The generic approach presented and evaluated here motivates an adaptation to other more practical problem settings, in order to show its general applicability.

The proposed methodology contributes to the current demand for computational support for increasing the responsiveness of logistic systems.

The original contribution of this paper is the autonomous feedback‐controlled adjustment of decision preferences which enables a rolling horizon re‐planning framework to maintain a stable output performance even if the input oscillates significantly over time.

Since the first Volume of this Bibliography there has been an explosion of literature in all the main areas of business. The researcher and librarian have to be able to uncover specific articles devoted to certain topics. This Bibliography is designed to help. Volume III, in addition to the annotated list of articles as the two previous volumes, contains further features to help the reader. Each entry within has been indexed according to the Fifth Edition of the SCIMP/SCAMP Thesaurus and thus provides a full subject index to facilitate rapid information retrieval. Each article has its own unique number and this is used in both the subject and author index. The first Volume of the Bibliography covered seven journals published by MCB University Press. This Volume now indexes 25 journals, indicating the greater depth, coverage and expansion of the subject areas concerned.

This paper aims to investigate the relationship between job satisfaction and distributive justice on employee perceptions of absence legitimacy. This paper also examined the moderating effects of turnover intentions on the relevant relationships.

The authors used convenience sampling to collect data from 298 employees working in private and public sector organizations in the manufacturing and service sectors in Ghana. Drawing on institutional theory, this study investigates the effects of employee perceptions of the legitimacy of absenteeism on their attitudes toward their job and pay. Structural equation modeling was used to test the direct and moderation effects.

Job satisfaction and perceived distributive justice were found to be significantly related to the absence of legitimacy. Additionally, turnover intentions moderated the relationship between job satisfaction and absence legitimacy; however, unexpectedly, this was associated only marginally with distributive justice.

The main limitation of this study was that it was cross-sectional, but the analysis did not show a common method bias. This study was conducted in a developing country where valid and accurate absence data are non-existent. The hypotheses were supported. When employees felt a sense of inequity and were dissatisfied with their jobs, they were likely to perceive absenteeism as legitimate behavior. These relationships were more pronounced when employees intended to leave their organizations.

From a practical standpoint, as employees are likely to engage in absenteeism as a means to reduce their perceptions of imbalance and because absenteeism is a costly behavior, it would be in the employer’s best interest to mitigate these high costs. It behooves employers to comprehend the factors that lead to the legitimization of absences. Doing so, they would be able to implement attendance management systems and strategies that would delegitimize some of these factors, thus improving attendance and potentially increasing productivity and job satisfaction and reducing turnover intentions.

This study contributes to absenteeism research because, unlike most studies in the area, it examined employee cognitions of the behavior. Such cognitions should provide insights into how employee perceptions of the legitimacy of absences would affect attitudinal variables such as job satisfaction, feelings of equity and turnover intentions. Moreover, even though the study was conducted in Ghana, absence legitimacy can be investigated in different settings at different levels of analysis. This is because it is free from contamination such as, dissimilar absence reporting systems within and across organizations and nations that affect the validity and accuracy of absence data.