Business Models for Cloud Computing: Experiences from Developing Modeling & Simulation as a Service Applications in Industry

The potential of cloud computing is gaining significant interest in Modeling & Simulation (M&S). The underlying concept of using computing power as a utility is very attractive to users that can access state-of-the-art hardware and software without capital investment. Moreover, the cloud computing characteristics of rapid elasticity and the ability to scale up or down according to workload make it very attractive to numerous applications including M&S. Research and development work typically focuses on the implementation of cloud-based systems supporting M&S as a Service (MSaaS). Such systems are typically composed of a supply chain of technology services. How is the payment collected from the end-user and distributed to the stakeholders in the supply chain? We discuss the business aspects of developing a cloud platform for various M&S applications. Business models from the perspectives of the stakeholders involved in providing and using MSaaS and cloud computing are investigated and presented.

Methods, Models & Systems for Dealing with Some Business, Management & Engineering Problems

This keynote presentation will report some of our research work and experience on the development and applications of relevant methods, models, systems and simulation techniques in support of different types and various levels of decision making for business, management and engineering. In particular, the following topics will be covered. Modelling, multi-agent-based simulation and analysis of the allocation management of carbon dioxide emission permits in China (Nanfeng Liu & Shuliang Li Agent-based simulation of the dynamic evolution of enterprise carbon assets (Yin Zeng & Shuliang Li) A framework & system for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps: a big data perspective (Jin Xu, Zheng Li, Shuliang Li & Yanyan Zhang) Open innovation: intelligent model, social media & complex adaptive system simulation (Shuliang Li & Jim Zheng Li) A framework, model and software prototype for modelling and simulation for deshopping behaviour and how companies respond (Shawkat Rahman & Shuliang Li) Integrating multiple agents, simulation, knowledge bases and fuzzy logic for international marketing decision making (Shuliang Li & Jim Zheng Li) A Web-based hybrid intelligent system for combined conventional, digital, mobile, social media and mobile marketing strategy formulation (Shuliang Li & Jim Zheng Li) A hybrid intelligent model for Web & social media dynamics, and evolutionary and adaptive branding (Shuliang Li) A hybrid paradigm for modelling, simulation and analysis of brand virality in social media (Shuliang Li & Jim Zheng Li) Network configuration management: attack paradigms and architectures for computer network survivability (Tero Karvinen & Shuliang Li)

Forecasting overseas visitors into the United Kingdom using continuous time and autoregressive fractional integrated moving average models with discrete data

This paper applies Gaussian estimation methods to continuous time models for modelling overseas visitors into the UK. The use of continuous time modelling is widely used in economics and finance but not in tourism forecasting. Using monthly data for 1986–2010, various continuous time models are estimated and compared to autoregressive integrated moving average (ARIMA) and autoregressive fractionally integrated moving average (ARFIMA) models. Dynamic forecasts are obtained over different periods. The empirical results show that the ARIMA model performs very well, but that the constant elasticity of variance (CEV) continuous time model has the lowest root mean squared error (RMSE) over a short period.

Inflation targeting and the consistency of monetary policy decisions in Mexico: an empirical analysis with discrete choice models

This paper examines the nature of monetary policy decisions in Mexico using discrete choice models applied to the Central Bank's explicit monetary policy instrument. We find that monetary policy adjustments in Mexico have been strongly consistent with the CB's inflation targeting strategy. We also find evidence that monetary policy responds in a forward-looking manner to deviations of inflation from the target and that observed policy adjustments exhibit asymmetric features, with stronger responses to positive than to negative deviations of inflation from the target and a greater likelihood of policy persistence during periods when monetary policy is tightened, compared with periods when policy is loosened.

A framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps

There is still a lack of effective paradigms and tools for analysing and discovering the contents and relationships of project knowledge contexts in the field of project management. In this paper, a new framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps under big data environments is proposed and developed. The conceptual paradigm, theoretical underpinning, extended topic model, and illustration examples of the ontology model for project knowledge maps are presented, with further research work envisaged.

Teacher educators: proposing new professional development models within an English further education context

At a time of increasing public and government focus on the quality of teacher education, little is known about the professional development needs of those who teach teachers in further education (FE). Yet they are crucial players. Efforts are intensifying across a significant number of countries to promote the professional development of teacher educators, but there is little support for new or experienced practitioners and no substantive professional standards regarding this role in English FE. This has an impact on the professional practice and career trajectories of teacher educators themselves. Based on a series of semi-structured interviews, an online survey and focus groups, this mixed-methods study uses a sequential exploratory design. The study captures the voices of English FE teacher educators who identified mentoring, induction and a choice of continuous professional development sessions as important strategies to improve the effectiveness of their role over time. This article will propose flexible models of professional development, following an analysis of new and experienced teacher educators’ needs in FE in England. The article recommends that new professional standards for teacher educators could be written collaboratively by practitioners, within a policy and institutional framework which supports the scholarship and research requirements of teacher educators.