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This paper aims to examine the association between financial reporting quality in target companies and acquisition profitability in a sample of 280 acquisitions in South Korea between 2002 and 2011.

Using the accruals quality measure developed by McNichols (2002) as a proxy for financial reporting quality, it was found that high-quality financial reporting in target companies is associated with more profitable acquisitions for the acquirer, as measured by the acquirer’s announcement returns.

It was found that high-quality financial reporting in target companies is associated with more profitable acquisitions for the acquirer, as measured by the acquirer’s announcement returns. This finding suggests that higher-quality accounting information leads to better decision-making during acquisitions. It was also found that the importance of financial reporting quality increases when information about the target company is scarce. In addition, it was found that the financial reporting quality of target companies is less important when the agency costs of the acquirer are high.

This analysis also complements several recent papers that examine target firm accounting information and mergers and acquisitions (M&A) returns (Shalev and Martin, 2009; McNichols and Stubben, 2012). By expanding this analysis, the authors help to provide a more complete understanding of how target firm’s accounting quality relates to the valuation of the target company and future expected synergies in M&A deal practice.

This study is one of a growing body of literature on the relations between financial reporting quality and investment decisions (Bens and Monahan, 2004; Biddle and Hilary, 2006; Hope and Thomas, 2008; McNichols and Stubben, 2008; Biddle et al., 2009; Francis and Martin, 2010). These results extend and generalize the results of prior studies, in that data pertinent to acquisition profitability of M&As in South Korea are used.

Although the business model field of study has been a focus of attention for both researchers and practitioners within the past two decades, it still suffers from concern about its identity. Accordingly, this paper aims to clarify the intellectual structure of business model through identifying the research clusters and their sub-clusters, the prominent relations and the dominant research trends.

This paper uses some common text mining methods including co-word analysis, burst analysis, timeline analysis and topic modeling to analyze and mine the title, abstract and keywords of 14,081 research documents related to the domain of business model.

The results revealed that the business model field of study consists of three main research areas including electronic business model, business model innovation and sustainable business model, each of which has some sub-areas and has been more evident in some particular industries. Additionally, from the time perspective, research issues in the domain of sustainable development are considered as the hot and emerging topics in this field. In addition, the results confirmed that information technology has been one of the most important drivers, influencing the appearance of different study topics in the various periods.

The contribution of this study is to quantitatively uncover the dominant knowledge structure and prominent research trends in the business model field of study, considering a broad range of scholarly publications and using some promising and reliable text mining techniques.

Finding the optimal maintenance schedules is the primitive aim of preventive maintenance scheduling (PMS) problem dealing with the objectives of reliability, risk and cost. Most of the earlier works in the literature have focused on PMS with the objectives of leveling reserves/risk/cost independently. Nevertheless, very few publications in the current literature tackle the multi-objective PMS model with simultaneous optimization of reliability, and economic perspectives. Since, the PMS problem is highly nonlinear and complex in nature, an appropriate optimization technique is necessary to solve the problem in hand. The paper aims to discuss these issues.

The complexity of the PMS problem in power systems necessitates a simple and robust optimization tool. This paper employs the modern meta-heuristic algorithm, namely, Ant Lion Optimizer (ALO) to obtain the optimal maintenance schedules for the PMS problem. In order to extract best compromise solution in the multi-objective solution space (reliability, risk and cost), a fuzzy decision-making mechanism is incorporated with ALO (FDMALO) for solving PMS.

As a first attempt, the best feasible maintenance schedules are obtained for PMS problem using FDMALO in the multi-objective solution space. The statistical measures are computed for the test systems which are compared with various meta-heuristic algorithms. The applicability of the algorithm for PMS problem is validated through statistical t-test. The statistical comparison and the t-test results reveal the superiority of ALO in achieving improved solution quality. The numerical and statistical results are encouraging and indicate the viability of the proposed ALO technique.

As a maiden attempt, FDMALO is used to solve the multi-objective PMS problem. This paper fills the gap in the literature by solving the PMS problem in the multi-objective framework, with the improved quality of the statistical indices.

The purpose of this paper is to examine public–private partnership (PPP) approaches for the construction of rental retirement villages in Australia and to allocate the investment proportions under a certain project return rate among three investors which are the government, private sectors and pension funds. The apportionment will achieve a minimum overall investment risk for the project.

Capital structure, particularly determination of investment apportionment proportions, is one of the key factors affecting the success of PPP rental retirement villages. Markowitz mean-variance model was applied to examine the investment allocations with minimum project investment risks under a certain projected return rate among the PPP partners for the construction of rental retirement villages.

The research findings validate the feasibility of the inclusion of pension funds in the construction of PPP rental retirement villages and demonstrate the existence of relationships between the project return rate and the investment allocation proportions.

This paper provides a quantitative approach for determination of the investment proportions among PPP partners to enrich the theory of PPP in relation to the construction of rental retirement villages. This has implications for PPP partners and can help these stakeholders make vital contributions in developing intellectual wealth in the PPP investment area while providing them with a detailed guide to decision making and negotiation in relation to investment in PPP rental retirement villages.