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This chapter explores a descriptive theory of multidimensional travel behaviour, estimation of quantitative models and demonstration in an agent-based microsimulation.

A descriptive theory on multidimensional travel behaviour is conceptualised. It theorizes multidimensional knowledge updating, search start/stopping criteria and search/decision heuristics. These components are formulated or empirically modelled and integrated in a unified and coherent approach.

The theory is supported by empirical observations and the derived quantitative models are tested by an agent-based simulation on a demonstration network.

Based on artificially intelligent agents, learning and search theory and bounded rationality, this chapter makes an effort to embed a sound theoretical foundation for the computational process approach and agent-based micro-simulations. A pertinent new theory is proposed with experimental observations and estimations to demonstrate agents with systematic deviations from the rationality paradigm. Procedural and multidimensional decision-making are modelled. The numerical experiment highlights the capabilities of the proposed theory in estimating rich behavioural dynamics.

In this paper, we investigate whether internal control and whether corporate life cycle would affect firm performance in the emerging markets of China.

We use Chen, Dong, Han, and Zhou’s (2013) internal control index on the effectiveness of internal control and Dickinson’s (2011) definition on firm life cycle. We use multivariate regression analysis.

We find that the internal control improves corporate performance. When dividing firm life cycle into five stages: introduction, growth, mature, shake-out and decline, we find that the impacts of internal control on firm performance vary with different stages. The positive impact of internal control on firm performance is more significant in maturity and shake-out stages than other stages.

Our findings would have implications for the regulators and policy makers with regards to the importance of internal control in corporate governance and the effectiveness of implementing standards and guidelines on internal control in public firms.

In addition, our findings on the various roles of internal control at different stages of firm life cycle would help managers and board of directors find more focus in risk management and board monitoring, respectively.

Although the prior literature have examined the link between internal control, information quality and cost of equity capital (Ashbaugh-Skaife, Collins, Kinney, & LaFond, 2009; Ogneva, Subramanyam, & Raghunandan, 2007), our study would be the first attempt to investigate the link between internal control and firm performance during different stages of firm life cycles.

Since the beginning of the 21st century, China’s outward foreign direct investment (OFDI) is growing steadily and Chinese multinationals (MNCs) are playing an increasingly important role in the global economy. Thus, the number of papers focusing on China’s OFDI and Chinese MNCs has been increasing during the last years. The aim of this chapter is to carry out a review of the empirical papers dealing with Chinese MNCs published between 2002 and 2012 in high-impact international business and management journals.

This chapter reviews 43 empirical papers focusing on Chinese MNCs that were published in nine major scholarly journals between 2002 and 2012.

We report individual and institutional contributions, the theories and methods used, the research topics, and the main findings. We also discuss implications for future research.

Some previous literature reviews have dealt with research on China’s OFDI and Chinese MNCs. Nevertheless, none of the earlier reviews dealt specifically with empirical papers; neither did they provide an analysis of both individual and institutional contributions.

The transformation towards the Green Economy (GE) in Poland is a relatively new topic for researchers, policymakers and business practitioners. A comprehensive picture of the shift towards the GE can help mentioned groups translate theoretical assumptions into practice.

This chapter presents the assessment of Poland's shift towards the GE, measured by the proposed Green Transformation Index (GTI).

The set of GE indicators was elaborated in Structured Literature Review (SLR) variation method. Then, this set of indicators was compared with the Statistics Poland (GUS) secondary data and employed in the taxonometric calculation methods.

In the result, the GTI for the Polish economy was proposed and calculated between 2007 and 2020. The GTI allowed us to present a dynamic analysis of the transformation towards GE in Poland.

Purpose – This chapter provides an overview of issues related to analysing crash data characterised by excess zero responses and/or long tails and how to overcome these problems. Factors affecting excess zeros and/or long tails are discussed, as well as how they can bias the results when traditional distributions or models are used. Recently introduced multi-parameter distributions and models developed specifically for such datasets are described. The chapter is intended to guide readers on how to properly analyse crash datasets with excess zeros and long or heavy tails.

Methodology – Key references from the literature are summarised and discussed, and two examples detailing how multi-parameter distributions and models compare with the negative binomial distribution and model are presented.

Findings – In the event that the characteristics of the crash dataset cannot be changed or modified, recently introduced multi-parameter distributions and models can be used efficiently to analyse datasets characterised by excess zero responses and/or long tails. They offer a simpler way to interpret the relationship between crashes and explanatory variables, while providing better statistical performance in terms of goodness-of-fit and predictive capabilities.

Research implications – Multi-parameter models are expected to become the next series of traditional distributions and models. The research on these models is still ongoing.

Practical implications – With the advancement of computing power and Bayesian simulation methods, multi-parameter models can now be easily coded and applied to analyse crash datasets characterised by excess zero responses and/or long tails.