International experiential diversity and performance at project organizations: The case of national football teams

Purpose– The purpose of this paper is to shed new light on the link between diversity in project teams and team performance by examining the effects of players’ international career diversity on the performance of national football teams. Design/methodology/approach– The paper draws upon the literature on project organizations and experiential diversity in teams. Using data on players’ international career backgrounds and team performance from the FIFA World Cup 2006, the authors test two hypotheses linking experiential diversity in teams and a measure of relative team performance. The dataset includes detailed individual background profiles of the 736 participating players and performance data from the 64 games played at the tournament. Findings– The findings suggest that different types of experiential diversity have contrasting effects on team performance in a time‐limited project team setting. Research limitations/implications– These findings encourage team diversity researchers to further examine the impact of experiential diversity in teams on team process and performance outcomes in future research. Practical implications– The findings particularly highlight the need to carefully manage experiential diversity in project team settings in order to benefit from access to diverse tacit resources, while at the same time avoiding that the integrative capacities of teams becoming overstretched. Originality/value– The paper is a step towards a better understanding of how diversity of individual career backgrounds affects team performance outcomes in project teams.

Internal equity financing and the performance of multinational subsidiaries in emerging economies

We examine the internal equity financing of the multinational subsidiary which retains and reinvests its own earnings. Internal equity financing is a type of firm-specific advantage (FSA) along with other traditional FSAs in innovation, research and development, brands and management skills. It also reflects subsidiary-level financial management decision-making. Here we test the contributions of internal equity financing and subsidiary-level financial management decision-making to subsidiary performance, using original survey data from British multinational subsidiaries in six emerging countries in the South East Asia region. Our first finding is that internal equity financing acts as an FSA to improve subsidiary performance. Our second finding is that over 90% of financing sources (including capital investment by the parent firms) in the British subsidiaries come from internal funding. Our third finding is that subsidiary-level financial management decision-making has a statistically significant positive impact on subsidiary performance. Our findings advance the theoretical, empirical and managerial analysis of subsidiary performance in emerging economies.

Computationally efficient rule-based classification for continuous streaming data

Advances in hardware and software technologies allow to capture streaming data. The area of Data Stream Mining (DSM) is concerned with the analysis of these vast amounts of data as it is generated in real-time. Data stream classification is one of the most important DSM techniques allowing to classify previously unseen data instances. Different to traditional classifiers for static data, data stream classifiers need to adapt to concept changes (concept drift) in the stream in real-time in order to reflect the most recent concept in the data as accurately as possible. A recent addition to the data stream classifier toolbox is eRules which induces and updates a set of expressive rules that can easily be interpreted by humans. However, like most rule-based data stream classifiers, eRules exhibits a poor computational performance when confronted with continuous attributes. In this work, we propose an approach to deal with continuous data effectively and accurately in rule-based classifiers by using the Gaussian distribution as heuristic for building rule terms on continuous attributes. We show on the example of eRules that incorporating our method for continuous attributes indeed speeds up the real-time rule induction process while maintaining a similar level of accuracy compared with the original eRules classifier. We termed this new version of eRules with our approach G-eRules.

The financial and environmental performance of firms exposed to the EU Emissions Trading Scheme

This thesis is an empirical-based study of the European Union’s Emissions Trading Scheme (EU ETS) and its implications in terms of corporate environmental and financial performance. The novelty of this study includes the extended scope of the data coverage, as most previous studies have examined only the power sector. The use of verified emissions data of ETS-regulated firms as the environmental compliance measure and as the potential differentiating criteria that concern the valuation of EU ETS-exposed firms in the stock market is also an original aspect of this study. The study begins in Chapter 2 by introducing the background information on the emission trading system (ETS), which focuses on (i) the adoption of ETS as an environmental management instrument and (ii) the adoption of ETS by the European Union as one of its central climate policies. Chapter 3 surveys four databases that provide carbon emissions data in order to determine the most suitable source of the data to be used in the later empirical chapters. The first empirical chapter, which is also Chapter 4 of this thesis, investigates the determinants of the emissions compliance performance of the EU ETS-exposed firms through constructing the best possible performance ratio from verified emissions data and self-configuring models for a panel regression analysis. Chapter 5 examines the impacts on the EU ETS-exposed firms in terms of their equity valuation with customised portfolios and multi-factor market models. The research design takes into account the emissions allowance (EUA) price as an additional factor, as it has the most direct association with the EU ETS to control for the exposure. The final empirical Chapter 6 takes the investigation one step further, by specifically testing the degree of ETS exposure facing different sectors with sector-based portfolios and an extended multi-factor market model. The findings from the emissions performance ratio analysis show that the business model of firms significantly influences emissions compliance, as the capital intensity has a positive association with the increasing emissions-to-emissions cap ratio. Furthermore, different sectors show different degrees of sensitivity towards the determining factors. The production factor influences the performance ratio of the Utilities sector, but not the Energy or Materials sectors. The results show that the capital intensity has a more profound influence on the utilities sector than on the materials sector. With regard to the financial performance impact, ETS-exposed firms as aggregate portfolios experienced a substantial underperformance during the 2001–2004 period, but not in the operating period of 2005–2011. The results of the sector-based portfolios show again the differentiating effect of the EU ETS on sectors, as one sector is priced indifferently against its benchmark, three sectors see a constant underperformance, and three sectors have altered outcomes.