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The purpose of this paper is to study the impacts of time segment modeling approach for berth allocation and quay crane (QC) assignment on container terminal operations efficiency.

The authors model the small time segment modeling approach, based on minutes, which can be a minute, 15 min, etc. Moreover, the authors divided the problem into three sub-problems and proposed a novel three-level genetic algorithm (3LGA) with QC shifting heuristics to deal with the problem. The objective function here is to minimize the total service time by using different time segments for comparison and analysis.

First, the study shows that by reducing the time segment, the complexity of the problem increases dramatically. Traditional meta-heuristic, such as genetic algorithm, simulated annealing, etc., becomes not very promising. Second, the proposed 3LGA with QC shifting heuristics outperforms the traditional ones. In addition, by using a smaller time segment, the idling time of berth and QC can be reduced significantly. This greatly benefits the container terminal operations efficiency, and customer service level.

Nowadays, transshipment becomes the main business to many container terminals, especially in Southeast Asia (e.g. Hong Kong and Singapore). In these terminals, vessel arrivals are usually very frequent with small handling volume and very short staying time, e.g. 1.5 h. Therefore, a traditional hourly based modeling approach may cause significant berth and QC idling, and consequently cannot meet their practical needs. In this connection, a small time segment modeling approach is requested by industrial practitioners.

In the existing literature, berth allocation and QC assignment are usually in an hourly based approach. However, such modeling induces much idling time and consequently causes low utilization and poor service quality level. Therefore, a novel small time segment modeling approach is proposed with a novel optimization algorithm.

This paper presents a generic simulation model to determine the equipment mix (quay, yard and intra-terminal transfer) for a Container Terminal Logistics Operations System (CTLOS). The simulation model for the CTLOS, a typical type of discrete event dynamic system (DEDS), consists of three sub-models: ship queue, loading-unloading operations and yard-gate operations. The simulation model is empirically applied to phase 1 of the Yangshan Deep Water Port in Shanghai. This study considers different scenarios in terms of container throughput levels, equipment utilization rates, and operational bottlenecks, and presents a sensitivity analysis to evaluate and choose reasonable equipment ratio ranges under different operational conditions.

The librarian and researcher have to be able to uncover specific articles in their areas of interest. This Bibliography is designed to help. Volume IV, like Volume III, contains features to help the reader to retrieve relevant literature from MCB University Press' considerable output. Each entry within has been indexed according to author(s) and the Fifth Edition of the SCIMP/SCAMP Thesaurus. The latter thus provides a full subject index to facilitate rapid retrieval. Each article or book is assigned its own unique number and this is used in both the subject and author index. This Volume indexes 29 journals indicating the depth, coverage and expansion of MCB's portfolio.

Behavioral solutions to our cognitive biases have long been studied in the literature. However, there is still ample evidence of behavioral biases in decision-making, with only limited improvement in the medium/long term even when debiasing methods are applied. The purpose of this paper is to describe how financial investors could benefit from a proactive management of emotions combined with a set of learning and decision-making heuristics to make more efficient investments in the long run.

First, the authors offer a classification of the appropriate quantitative and qualitative methodologies to use in different ecological environments. Then, the authors offer a list of detailed heuristics to be implemented as behavioral principles intended to induce more long-lasting changes than the original rules offered by the adaptive toolbox literature. Finally, the authors provide guidelines on how to embed artificial intelligence and cognitive diversity within the investment decision architecture.

Improvements in decision skills involve changes that rarely succeed through a single event but through a succession of steps that must be habitualized. This paper argues that implementing a more conscious set of personal and group principles is necessary for long-lasting changes and provides guidelines on how to minimize systematic errors with adaptive heuristics. To maximize their positive effects, the principles outlined in this paper should be embedded in an architecture that fosters cognitively diverse teams. Moreover, when using artificial intelligence, the authors advise to maximize the interpretability/accuracy ratio in building decision support systems.

The paper proposes a theoretical reflection on the field of behavioral research and decision-making in finance, where the chief goal is to offer practical advices to investors. The literature on debiasing cognitive biases is limited to the detection and correction of immediate effects. The authors go beyond the traditional three building blocks developed by the behavioral finance literature (search rules, stopping rules and decision rules) and aim at helping investors who are interested in finding long-term solutions to their cognitive biases.

In the last four years, since Volume I of this Bibliography first appeared, there has been an explosion of literature in all the main functional areas of business. This wealth of material poses problems for the researcher in management studies — and, of course, for the librarian: uncovering what has been written in any one area is not an easy task. This volume aims to help the librarian and the researcher overcome some of the immediate problems of identification of material. It is an annotated bibliography of management, drawing on the wide variety of literature produced by MCB University Press. Over the last four years, MCB University Press has produced an extensive range of books and serial publications covering most of the established and many of the developing areas of management. This volume, in conjunction with Volume I, provides a guide to all the material published so far.

The purpose of this paper is to propose a new mixed-integer formulation for the time-dependent multi-skilled resource-constrained project scheduling problem (MSRCPSP/t) considering learning effect. The proposed model extends the basic form of the MSRCPSP by three concepts: workforces have different efficiencies, it is possible for workforces to improve their efficiencies by learning from more efficient workers and the availability of workforces and resource requests of activities are time-dependent. To spread dexterity from more efficient workforces to others, this study has integrated the concept of diffusion maximization in social networks into the proposed model. In this respect, the diffusion of dexterity is formulated based on the linear threshold model for a network of workforces who share common skills. The proposed model is bi-objective, aiming to minimize make-span and total costs of project, simultaneously.

The MSRCPSP is an non-deterministic polynomial-time hard (NP-hard) problem in the strong sense. Therefore, an improved version of the non-dominated sorting genetic algorithm II (IM-NSGA-II) is developed to optimize the make-span and total costs of project, concurrently. For the proposed algorithm, this paper has designed new genetic operators that help to spread dexterity among workforces. To validate the solutions obtained by the IM-NSGA-II, four other evolutionary algorithms – the classical NSGA-II, non-dominated ranked genetic algorithm, Pareto envelope-based selection algorithm II and strength Pareto evolutionary algorithm II – are used. All algorithms are calibrated via the Taguchi method.

Comprehensive numerical tests are conducted to evaluate the performance of the IM-NSGA-II in comparison with the other four methods in terms of convergence, diversity and computational time. The computational results reveal that the IM-NSGA-II outperforms the other methods in terms of most of the metrics. Besides, a sensitivity analysis is implemented to investigate the impact of learning on objective function values. The outputs show the significant impact of learning on objective function values.

The proposed model and algorithm can be used for scheduling activities of small- and large-size real-world projects.

Based on the previous studies reviewed in this paper, one of the research gaps is the MSRCPSP with time-dependent resource capacities and requests. Therefore, this paper proposes a multi-objective model for the MSRCPSP with time-dependent resource profiles. Besides, the evaluation of learning effect on efficiency of workforces has not been studied sufficiently in the literature. In this study, the effect of learning on efficiency of workforces has been considered. In the scarce number of proposed models with learning effect, the researchers have assumed that the efficiency of workforces increases as they spend more time on performing a skill. To the best of the authors’ knowledge, the effect of learning from more efficient co-workers has not been studied in the literature of the RCPSP. Therefore, in this research, the effect of learning from more efficient co-workers has been investigated. In addition, a modified version of the NSGA-II algorithm is developed to solve the model.

The traditional dualism view regards stability and change as opposites and separate, two essential but largely incompatible and mutually exclusive elements in an organization, and it advocates contingency theories to handle the paradox situation; more recent research has adopted the paradoxical lens to highlight both the contradiction and the interdependence between the two elements. This paper aims to address how an organization pursues stability and change simultaneously, i.e., how stability and change contradictorily enable each other to promote the development of an organization.

By adopting a case study on the strategic and structural change of Signcomplex in China, this paper attempts to explore the paradoxical relationship between stability and change, especially their interdependence. Multiple approaches were used during data collection to meet the criteria for trustworthiness, and the data analysis went through a five-step process. Through this analysis, the main mechanisms of stability and change were identified. An analysis was also conducted on how these stable and variable mechanisms enable each other, and finally, a framework was set up to show this paradoxical relationship.

The results confirm the paradox of stability and change: stability enables change by supplying security and consistency, offering reserved knowledge and skills and enabling commitment and the provision of resources for a better realization of the change. Change enables a firm to set up a new state of stability through variable mechanisms such as trial-and-error and exploration activities. The results also indicate that the nature of organizational change is to help an organization reach a new stable stage with higher efficiency and that organizational development relies on the paradoxical effects of both stability and change.

This research is constrained by several limitations. The findings need to be further confirmed through the investigation of more organizations; other stable mechanisms, such as habits, tight coupling, commitments, control and low variance, and variable mechanisms, such as search, mindfulness, redundancy and openness, should be considered. As an organization may experience many cross-level or cross-department changes which struggle with each other for resources and with stable mechanisms, to explore the paradox, future research may need to conduct a more in-depth examination of the system of change.

The findings offer some valuable insights for further research and hold important implications for management practices, especially management practices in a Chinese context. The findings extend the existing paradox theory by further revealing how stability and change enable each other and offer a paradoxical perspective to look into the nature of organizational change and organizational development. The results remind managers to rethink the relationship between stability and change, to factor these coexisting concepts into their decision-making and to accept, understand and use this paradoxical relationship to realize synergistic effects for the firm.

In this paper we are concerned with two related topics—management literature and The London Classification of Business Studies. To understand the purposes and structure of the Classification it is essential first to consider the scope and content of management literature. But management literature would not exist, certainly in its present form, without the business schools, and so it is appropriate to begin by attempting a very brief answer to the question—what is management education? This fine new building in which we are meeting, with its lecture theatres, seminar rooms, computing facilities, its important library, its excellent residential accommodation, helps to provide a visual answer. But it is necessary to consider a broader perspective.