Towards the Development of a Simulator for Investigating the Impact of People Management Practices on Retail Performance

Often models for understanding the impact of management practices on retail performance are developed under the assumption of stability, equilibrium and linearity, whereas retail operations are considered in reality to be dynamic, non-linear and complex. Alternatively, discrete event and agent-based modelling are approaches that allow the development of simulation models of heterogeneous non-equilibrium systems for testing out different scenarios. When developing simulation models one has to abstract and simplify from the real world, which means that one has to try and capture the 'essence' of the system required for developing a representation of the mechanisms that drive the progression in the real system. Simulation models can be developed at different levels of abstraction. To know the appropriate level of abstraction for a specific application is often more of an art than a science. We have developed a retail branch simulation model to investigate which level of model accuracy is required for such a model to obtain meaningful results for practitioners.Comment: 24 pages, 7 figures, 6 tables, Journal of Simulation 201

The Impact of Trust on Acceptance of Online Banking

Major benefits of Online Banking include for banks cost savings, and for customers convenience. Nevertheless, many people perceive Internet banking as risky. This paper introduces a tentative conceptual framework. Trust will be integrated into the Technology Acceptance Model – TAM - (Davis, 1989). Recent research showed that Trust has a striking influence on user willingness to engage in online exchanges of money and personal sensitive information. Detailed literature about Online Banking and Trust is provided. TAM is discussed in depth; external variables that are suitable for the Online Banking context is suggested. In addition the theoretical justification for the conceptual framework integration is discussed. Finally managerial implications and recommendations for Online Banking acceptance are suggested

Network effects in mass communication - an analysis of information diffusion in markets

In this thesis we investigate the diffusion of information like news, announcements, and commercials in social networks. Such information propagates through a mix of mass communication and interpersonal communication. For example, people who watch a TV spot about a new car will discuss it with their friends. Both communication methods influence the awareness, preferences, and opinions that people display towards certain topics, products, and services. The effects of mass and inter-personal communication on the diffusion process have been studied intensively in several areas, for example, in sociology, economics, social psychology, political science, and marketing. Most of these studies highlight the role of inter-personal relation structures, that is, the network of social ties, in the diffusion process. However, a concise diffusion model that quantifies the effects of social networks and helps to improve mass communication towards structured populations is still in demand. Our purpose is first to analyse the drivers of social networks, then to model the diffusion of information on social networks, and finally to quantify the network effects on the diffusion process. We describe and construct social networks as graphs and present anthropological, psychological, and random factors that shape them. Based on one of these factors, structural balancing, we propose an evolutionary model of social networks, suggesting that the structure of social networks can change dramatically over time. For modelling diffusion processes on social networks, we follow a two-step procedure. We first combine three different generation methods, the generalised random graph, the small-world model, and a third method (random graph with a given assortment structure) to design realistic networks. Then we simulate the propagation of information on these networks. As the computer requirements for such simulations can be expensive, we introduce an efficient computer algorithm that is widely applicable to complex diffusion studies in markets, organisations, and societies. One result of the simulations is a robust closed-form approximation to the diffusion's trajectory in networks. Such an approximation allows marketing and PR managers to predict aggregate market outcomes such as the popularity of a commercial through surveys prior to the launch of a promotional campaign. The simulations also indicate the impact of the network's structure on the diffusion. To measure the network effects on the propagation of information, we run regression analyses with the communication intensity and the different network features as explanatory variables. These network features are the degree distribution, the transitivity (clustering), degree correlation, and the average path length. The regressions show, above all, that network effects are conditional on the intensity of mass communication: the less intensive mass communication, the more important become network effects. For mass communication typical in marketing and PR, the network structure can have a strong impact on the diffusion process. The regressions quantify the respective contribution of each network feature on the diffusion process over time. Our findings confirm and partly reconcile contradictionary results of comparable studies in epidemics and sociology. Finally, our analysis allows us to prioritise different network effects. This can be useful in various situations, for example, when estimating a diffusion process with incomplete network data

The Contractual Pillar of Maritime Decarbonisation: A study on the challenges and potential of improving energy efficiency in shipping through contractual means

Climate change has grown into an increasingly important concern for the shipping industry, but the contractual infrastructure of bulk shipping has not fully evolved to reflect this. As a result, this thesis examines the challenges and potential of improving energy efficiency in shipping through contractual means. In particular, we focus on how charterparties could be adapted to both encourage and enable more efficient ship operations, while also recognising that stakeholders such as shipowners, charterers and cargo owners often have conflicting interests. Furthermore, we also examine the key challenges in revising chartering contracts both generally and specific to different efficiency-oriented contractual solutions. Properly aligning charterparties and all stakeholders’ interests with operational efficiency is important since chartering contracts serve as the underlying framework of international shipping. We combine a literature-based analysis with interviews of key stakeholders in the shipping value chain to not only synthesise previous research results, but also explore how industry experts currently perceive the promise and limits of efficiency-oriented contractual changes. Firstly, we expand the literature by examining the common barriers to revising chartering contracts. Secondly, we review the current status of just-in-time arrivals, particularly when requiring contractual changes, and analyse how policy interventions such as carbon pricing and the upcoming CII regime could also contribute to tackling operational inefficiencies through contractual means. Finally, we evaluate more recent efficiency-linked contractual innovations and assess the challenges they are facing or might face in the future. Our findings suggest that policy interventions are necessary to incentivise more efficient ship operations, but their effectiveness depends heavily on stakeholders’ willingness to adapt contractual structures and fixture behaviour accordingly. As the status quo is maintained by stakeholders’ vested interests, external stimuli are generally required to motivate widespread contractual changes. Furthermore, although charterers and cargo owners play a crucial role for revising charterparties, they have varying responsiveness to price signals and interest in proactively reducing their shipping emissions, which creates some difficulties for improving energy efficiency through contractual means.nhhma

Application of lean scheduling and production control in non-repetitive manufacturing systems using intelligent agent decision support

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Lean Manufacturing (LM) is widely accepted as a world-class manufacturing paradigm, its currency and superiority are manifested in numerous recent success stories. Most lean tools including Just-in-Time (JIT) were designed for repetitive serial production systems. This resulted in a substantial stream of research which dismissed a priori the suitability of LM for non-repetitive non-serial job-shops. The extension of LM into non-repetitive production systems is opposed on the basis of the sheer complexity of applying JIT pull production control in non-repetitive systems fabricating a high variety of products. However, the application of LM in job-shops is not unexplored. Studies proposing the extension of leanness into non-repetitive production systems have promoted the modification of pull control mechanisms or reconfiguration of job-shops into cellular manufacturing systems. This thesis sought to address the shortcomings of the aforementioned approaches. The contribution of this thesis to knowledge in the field of production and operations management is threefold: Firstly, a Multi-Agent System (MAS) is designed to directly apply pull production control to a good approximation of a real-life job-shop. The scale and complexity of the developed MAS prove that the application of pull production control in non-repetitive manufacturing systems is challenging, perplex and laborious. Secondly, the thesis examines three pull production control mechanisms namely, Kanban, Base Stock and Constant Work-in-Process (CONWIP) which it enhances so as to prevent system deadlocks, an issue largely unaddressed in the relevant literature. Having successfully tested the transferability of pull production control to non-repetitive manufacturing, the third contribution of this thesis is that it uses experimental and empirical data to examine the impact of pull production control on job-shop performance. The thesis identifies issues resulting from the application of pull control in job-shops which have implications for industry practice and concludes by outlining further research that can be undertaken in this direction