Brexit Report - Impact on Business Models of Scottish Companies

The Brexit Business Model Report is a preliminary assessment of research, interviews and survey results regarding the impact of Brexit on the business models of Scottish companies as they prepare for post-Brexit scenarios. The survey was used to compile data to support research questions gathered during the research and interview process for this graduate class project. Questions were designed to assess how Brexit is impacting the ability of Scottish companies in the areas of business model, contingency planning, supply chain, staffing, innovation, global reach, risk assessment, and opportunities. The questions reflected areas of the business model that may have present and future implications. The answers help measure the Brexit impact on Scottish firms’ business models and the potential for international growth. The upper management of Scottish companies from the “Insider Top 500” list, “FactSet list, and various trade organizations were selected to receive the survey. The focus of this study was on the potential impact of Brexit on Scottish companies’ business models. The survey findings show the importance of understanding the elements of a business model in the Brexit context (see Additional File, Executive Summary below for Business Model Brexit Implications on Scottish Companies based on Key Findings table)

Using the markstrat business simulation to develop strategic management behaviours

It is well understood that experiential learning provides an incentive and impetus for accelerated learning, especially in humanities and business-focussed studies. ICT-based synthetic and virtual environments can provide a rich and varied context within which to achieve this. Specifically, this paper attempts to provide empirical, survey-based analysis of the application of a business simulation game, MarkStrat, on undergraduate and postgraduate programmes in this vein. The paper subsequently posits the pedagogic benefit of using such business simulation games for the development of strategic management behaviours across student sample populations and derives subsequent results to highlight associated learning behaviours

Intelligent data analysis approaches to churn as a business problem: a survey

Globalization processes and market deregulation policies are rapidly changing the competitive environments of many economic sectors. The appearance of new competitors and technologies leads to an increase in competition and, with it, a growing preoccupation among service-providing companies with creating stronger customer bonds. In this context, anticipating the customer’s intention to abandon the provider, a phenomenon known as churn, becomes a competitive advantage. Such anticipation can be the result of the correct application of information-based knowledge extraction in the form of business analytics. In particular, the use of intelligent data analysis, or data mining, for the analysis of market surveyed information can be of great assistance to churn management. In this paper, we provide a detailed survey of recent applications of business analytics to churn, with a focus on computational intelligence methods. This is preceded by an in-depth discussion of churn within the context of customer continuity management. The survey is structured according to the stages identified as basic for the building of the predictive models of churn, as well as according to the different types of predictive methods employed and the business areas of their application.Peer ReviewedPostprint (author's final draft

A survey on context awareness in big data analytics for business applications

The concept of context awareness has been in existence since the 1990s. Though initially applied exclusively in computer science, over time it has increasingly been adopted by many different application domains such as business, health and military. Contexts change continuously because of objective reasons, such as economic situation, political matter and social issues. The adoption of big data analytics by businesses is facilitating such change at an even faster rate in much complicated ways. The potential benefits of embedding contextual information into an application are already evidenced by the improved outcomes of the existing context-aware methods in those applications. Since big data is growing very rapidly, context awareness in big data analytics has become more important and timely because of its proven efficiency in big data understanding and preparation, contributing to extracting the more and accurate value of big data. Many surveys have been published on context-based methods such as context modelling and reasoning, workflow adaptations, computational intelligence techniques and mobile ubiquitous systems. However, to our knowledge, no survey of context-aware methods on big data analytics for business applications supported by enterprise level software has been published to date. To bridge this research gap, in this paper first, we present a definition of context, its modelling and evaluation techniques, and highlight the importance of contextual information for big data analytics. Second, the works in three key business application areas that are context-aware and/or exploit big data analytics have been thoroughly reviewed. Finally, the paper concludes by highlighting a number of contemporary research challenges, including issues concerning modelling, managing and applying business contexts to big data analytics. © 2020, Springer-Verlag London Ltd., part of Springer Nature

Is Sustainability Attractive for Corporate Real Estate Decisions ?

This paper provides an analysis of the impact of sustainable principles on corporate property decisions and attractiveness for business districts in the French context. It is based on a behavioural survey conducted across a large sample of corporate property managers and a MCA approach which highlights key factors about the influence of sustainable principles among traditional determinants of territorial attractiveness. This approach allows us to draw up a typology of actors regarding the diffusion of sustainability issues. It emphasizes a general improvement of sustainability on location choice especially for listed companies, owners of their head office and companies located into the main business districts of the Paris metropolitan area.Sustainable City ; Corporate Real Estate Management ; Territorial Attractiveness ; Office Business Districts

Parties, promiscuity and politicisation: business-political networks in Poland

Research on post-communist political economy has begun to focus on the interface between business and politics. It is widely agreed that informal networks rather than business associations dominate this interface, but there has been very little systematic research in this area. The literature tends to assume that a politicised economy entails business-political networks that are structured by parties. Theoretically, this article distinguishes politicisation from party politicisation and argues that the two are unlikely to be found together in a post-communist context. Empirically, elite survey data and qualitative interviews are used to explore networks of businesspeople and politicians in Poland. Substantial evidence is found against the popular idea that Polish politicians have business clienteles clearly separated from each other according to party loyalties. Instead, it is argued that these politicians and businesspeople are promiscuous. Since there seems to be little that is unusual about the Polish case, this conclusion has theoretical, methodological, substantive and policy implications for other post-communist countries

Three-dimensional context-aware tailoring of information

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2010 EmeraldPurpose – The purpose of this paper is to explore the notion of context in ubiquitous computing. Personal Information Managers exploit the ubiquitous paradigm in mobile computing to integrate services and programs for business and leisure. Recognising that every situation is constituted by information and events, context will vary depending on the situation in which users find themselves. The paper aims to show the viability of tailoring contextual information to provide users with timely and relevant information. Design/methodology/approach – A survey was conducted after testing on a group of real world users. The test group used the application for approximately half a day each and performed a number of tasks. Findings – The results from the survey show the viability of tailoring contextual information to provide users with timely and relevant information. Among the questions in the questionnaire the users were asked to state whether or not they would like to use this application in their daily life. Statistically significant results indicate that the users found value in using the application. Originality/value – This work is a new exploration and implementation of context by integrating three dimensions of context: social information, activity information, and geographical position

Estimating the Undercoverage of a Sampling Frame due to Reporting Delays

One of the imperfections of a sampling frame is miscoverage caused by delays in recording real- life events that change the eligibility of population units. For example, new units generally appear on the frame some time after they came into existence and units that have ceased to exist are not removed from the frame immediately. We provide methodology for predicting the undercoverage due to delays in reporting new units. The approach presented here is novel in a business survey context, and is equally applicable to overcoverage due to delays in reporting the closure of units. As a special case, we also predict the number of new-born units per month. The methodology is applied to the principal business register in the UK, maintained by the Office for National Statistics. <br/

The importance of housing and neighbourhood resources for urban microbusinesses

Economic research has rarely considered the significance of the home and neighbourhood context of where business owners’ live for their business. Conversely, urban and neighbourhood research has overlooked how housing and neighbourhood shape business and entrepreneurship outcomes. This paper investigates the importance of housing and neighbourhood resources for microbusinesses using a random sample of microbusinesses in Edinburgh (UK) including those that are informal and home-based, and various characteristics of the neighbourhood in which the business owner lives were attached to the survey records. The data capture whether business owners have business premises outside their homes, have used neighbourhood contacts, housing equity or space in the house for their business. In short, housing and neighbourhood resources are used by a large majority (82%) of microbusinesses. The findings challenge a number of common assumptions on the separation of commercial and residential functions, how neighbourhoods feature in the evolution of businesses, the nested conceptualisation of home within a neighbourhood and on the nature of home-based businesses. It is concluded that multi-use (rather than mixed-use) neighbourhood planning would help foster more flexible and dynamic use of neighbourhoods and urban districts, although recognising that this is a political issue

Denoised Least Squares Forecasting of GDP Changes Using Indexes of Consumer and Business Sentiment

Indexes of consumer and business sentiment are frequently characterized by measurement errors and short-term cyclical fluctuations that can distort their predictive accuracy for GDP changes. While measurement errors arise due to the survey sampling procedures that characterize these surveys, short-term cyclical fluctuations are generally linked with various exogenous and irregular factors that are not necessarily related to the economy. This paper shows, using data on the US economy, that applying wavelet denoising on indexes of consumer and business sentiment in the context of the linear regression model can overcome these limitations and can provide: (a) efficient coefficient estimates in models that explain consumer sentiment index variation; and (b) consistent coefficient estimates and predictions in models for GDP changes when using consumer and business sentiment indexes as predictors.Consumer sentiment index, denoised least squares, index of homebuilders’sentiment, index of manufacturing activity, measurement errors.