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The purpose of this paper is to examine the effect of financial constraints on firm growth considering six types of ownership structure. According to the theory of financial management and asymmetric information theory, external funds are costly for small firms. However, some ownership structures may alleviate cash flow-growth sensitivity. The paper considers different types of ownership structure to study cash flow-growth relation and its sensitivity.

Results are drawn from a dynamic panel data model under the two specific empirical models. Those designs can capture important empirical meanings.

The sensitivity of growth to cash flow decreases significantly when managers control larger proportions of a firm's stock and when a firm belongs to a conglomerate. The findings also show that small and young firms grow faster. R&D and advertising expenditures also motivate a firm's growth, as do profitability and abundant cash flow.

This paper uses a dynamic panel data model to investigate the effect of cash flow on firms' growth under six types of ownership structure. The sensitivity analysis of growth to cash flow provides new results for traditional literature. In fact, different ownership structures lead to distinct cash flow-growth sensitivity.

This research aims to deal with the analysis of the concept of balance scorecard (BSC) integrated maritime process management in a marine course.

Several research studies found that managers lacked a basic understanding of a BSC approach to evaluate a maritime course. This paper analyzes the theoretical and practical approach of strategic BSC tool, analyzing the risks and threats regarding marine accidents.

The conclusion is that the BSC can be applied as a maritime process management to course design. Students were assigned a BSC project in a foundational course and completed a survey to establish if the BSC enhanced their knowledge and understanding of maritime process within a maritime safety process.

Future research would be advised to include a more geographically and randomly selected maritime accident sample.

Based on the application of BSC, it was concluded that a better understanding of how maritime safety process management operates holistically was attained.

This research sheds light on a phase of the maritime safety process that has been neglected so far in the maritime education training and generates insights for maritime industry how they can formalize this process and how they can deal with it more systematically.

The high-quality development of the real estate industry is crucial to the transformation of China's economy. However, few studies apply the productivity to explore the development path of the real estate industry in China. To fill this gap, this study mainly investigates the total factor productivity (TFP) of the real estate industry of 30 sample provinces in mainland China from 2007 to 2016.

The Malmquist index is applied to estimate the productivity (i.e. TFP) of the real estate industry, based on the data envelopment analysis (DEA). Then, the truncated tobit regression analysis explores the external influencing factors on the TFP of the real estate industry.

Through empirical analysis, it is found that the high-quality development of the real estate industry depends on the technological innovation by the real estate enterprises and the targeted policies by the provincial government. Moreover, the development of the real estate industry has a positive correlation with the growth of China's economy but a negative correlation with the development of other industries.

TFP mainly reveals the development status of the provincial real estate industry and identifies the driving force for exploring the high-quality development mode of the real estate sector. Furthermore, the fluctuation rule of TFP can be applied to predict the development trend of the real estate industry in the future.

As an application, this study measures the TFP of the Chinese real estate industry in different provinces and periods. The results have meaningful policy implications for policymakers regulating the real estate industry.

This study aims to investigate whether intellectual capital (IC) and its subcomponents enhance value and improve the profitability of real estate (RE) and infrastructure (INF) firms in India. In this study, IC is measured through the value-added intellectual coefficient (VAIC) model. The study further extends the VAIC model by incorporating an additional component of social welfare efficiency (SWE).

The study uses the panel data investigation based on the data of 63 firms (22 RE and 41 INF firms), for a period of 10 years (2008–2017). The dependent variables in the study are return on assets (ROA) and market price to book value ratio (PB), whereas the independent variables are VAIC and its components. The panel is tested for stationarity, heteroscedasticity and multicollinearity problems. Finally, to account for heteroscedasticity and endogeneity, Arellano and Bond's (1991) panel regression estimator with robust estimates are used.

The findings of the study suggest that IC has a significant influence on the profitability and value of infra firms, whereas capital-employed efficiency (CEE) positively affects the profitability of both RE and INF firms.

The study is an attempt to find the effect of IC and its components on profitability and value of RE and INF firms in India. The author has also extended the VAIC model, which was introduced by Pulic (2000), by adding an additional IC component, i.e. SWE. The study uses Arellano and Bond's (1991) panel regression estimator with robust estimates, which helps produce robust results.