Accounting aggregation: User preferences and decision making

This experiment tests the effects of alternative aggregations of accounting data in a simulated portfolio task. Certain entropy-based aggregation criteria were used to prepare differentially aggregated financial statements for use in the task. Subjects made allocations of initial edowments between hypothetical firms, disclosed confidence in their allocation decisions and reported on specific characteristics of the financial statements. Differences in reported usefulness of statement sets furnished were found to be associated strongly with measured information content. The results also provide limited evidence that decisions and judgments of subjects were affected by the information content of the accounting aggregations provided.     

A conceptual model and research agenda for bidding,planning and delivering Major sport events that lever human rights

In this conceptual article, the authors propose a framework for how progressive human rights outcomes may be obtained in the context of bidding, planning and implementing major sport events (MSEs) through the implementation of four pathways, including good governance, the democratic participation of stakeholders, the formalisation of human rights agendas and the deployment of sensitive urban development. The authors argue that there is a need for adherence to internationally recognised standards, such as the Universal Declaration of Human Rights and the United Nations Guiding Principles on Business and Human Rights if rhetorical statements from MSE awarding bodies and host organisers are to be accountable to a wider set of actors. If researchers and practitioners want to address some of the critical issues related to human rights and MSEs, it is imperative that key actors working in the rights sphere are involved in shaping the research agenda and monitoring its implementation. Academics need to take a proactive approach aimed at achieving both theoretically grounded and practically relevant solutions, with engagement occurring over an extended period of time. This approach, avowedly political and concerned with genuine action, is a key way in which MSE stakeholders can be held to account for their actions in regard to human rights.     

THE RETURNS TO INVESTMENT IN RESEARCH ON AUSTRALIAN WOOL PRODUCTION*

A production function approach is used to estimate growth in farm productivity in the Australian wool industry from an estimated level of expenditure on wool production R & D. A market equilibrium model of the wool industry is then used to measure the share of total benefits from this productivity growth accruing to Australia and its wool growers. A net return is estimated after allowing for lags in the development and adoption of technology.     

The effect of rankings on honesty in budget reporting

We conduct an experiment to investigate the effect of rankings, which are pervasive in practice, on the honesty of managers’ budget reports, which is important for sound decision making in organizations. Participants in our experiment are ranked in one of four ways: (1) firm profit, (2) own compensation, (3) both firm profit and own compensation, and (4) randomly, which serves as our baseline condition. None of the rankings affect participants’ remuneration. Compared to our baseline (random rankings) setting, where participants indeed exhibit honesty concerns, we find that rankings based on firm profit significantly increase honesty and that rankings based on own compensation significantly decrease honesty. Participants who received both rankings were significantly more honest than participants in the own compensation rankings condition. We did not, however, find significant differences in honesty between the both rankings and firm profit rankings conditions. As such, participants in the both rankings condition seemed to focus more on the firm profit metric than on the financially congruent own compensation metric. We also find that our results are stable across periods, suggesting that the effects of rankings neither increased nor dissipated over time. We discuss the contributions of our study and concomitant findings to accounting research and practice.     

GP algorithm versus hybrid and mixed neural networks

In the current paper, we present an integrated genetic programming (GP) environment called java GP modelling. The java GP modelling environment is an implementation of the steady-state GP algorithm. This algorithm evolves tree-based structures that represent models of inputs and outputs. The motivation of this paper is to compare the GP algorithm with neural network (NN) architectures when applied to the task of forecasting and trading the ASE 20 Greek Index (using autoregressive terms as inputs). This is done by benchmarking the forecasting performance of the GP algorithm and six different autoregressive moving average model (ARMA) NN combination designs representing a Hybrid, Mixed Higher Order Neural Network (HONN), a Hybrid, Mixed Recurrent Neural Network (RNN), a Hybrid, Mixed classic Multilayer Perceptron with some traditional techniques, either statistical such as a an ARMA or technical such as a moving average convergence/divergence model, and a naïve trading strategy. More specifically, the trading performance of all models is investigated in a forecast and trading simulation on ASE 20 time-series closing prices over the period 2001–2008, using the last one and a half years for out-of-sample testing. We use the ASE 20 daily series as many financial institutions are ready to trade at this level, and it is therefore possible to leave orders with a bank for business to be transacted on that basis. As it turns out, the GP model does remarkably well and outperforms all other models in a simple trading simulation exercise. This is also the case when more sophisticated trading strategies using confirmation filters and leverage are applied, as the GP model still produces better results and outperforms all other NN and traditional statistical models in terms of annualized return.     

Corruption and market attractiveness influences on different types of FDI

Previous studies have proposed that a compensatory model predicts the level of foreign direct investment (FDI) in a country; FDI levels are a result of ‘trade‐offs’ between the positive effect of market attractiveness and the negative influence of corruption. In contrast, we hypothesize and find that the compensatory relationship only holds for market‐seeking investment; for resource‐seeking FDI the model appears to be noncompensatory. Greater market attractiveness mitigates the negative impact of corruption on market‐seeking investment, but the ability of market attractiveness to mitigate the negative impact of corruption on resource‐seeking FDI quickly disappears as corruption levels increase. Implications and future research directions are discussed. Copyright © 2008 John Wiley & Sons, Ltd.     

Revenue Sharing with Heterogeneous Investments in Sports Leagues: Share Media,Not Stadiums

This study examines revenue sharing in sports leagues where franchises engage in multiple types of investments. Previous literature typically treats revenues and investments as homogeneous, but we add to the literature by differentiating between investment types and revenue sources. This is important because investment in talent leads to winning, which is a zero-sum game for the league and therefore owners have an incentive to limit talent investment. However, other investments, such as stadiums, are not a zero-sum game, and therefore the implications of revenue sharing are different for the league. We provide sufficient conditions under which it is more efficient to share media revenue compared to stadium revenue. We conclude by providing applications of this model.