Current marine navigational practice relies less on long-range visual marine signals such as lighthouses for reference purposes. This is due to the availability of Global Navigation Satellite Systems (GNSS), which are integrated with other navigational aids on ships. Therefore, the objective of this study is to review the function of Pisang Island lighthouse and to propose the most relevant use of Pisang Island for current navigational needs. The function of the lighthouse was reviewed according to the IALA Navigational Guide and the AIS data image. The result showed that the most suitable navigational use of the lighthouse is to act as a reference for Line of Position (LOP). The AIS data image indicated that mariners are not using Pisang Island lighthouse for LOP. The trend in the Straits of Malacca (SoM) was compared with the trend in the Straits of Dover, UK. The selected experts verified that LOP was not practised there. As a specific example, a tanker ship route in the South China Sea was used to further support that LOP was not practised. This evidence supported the view that Pisang Island lighthouse is less relevant for current navigational practice and does not directly support the coastal state VTS operation and the establishment of the marine electronic highway. Furthermore, the existing shore-based VTS radar has limitations on range and the detection of targets near Pisang Island. Therefore, this study proposes the establishment of a new radar station on Pisang Island at the existing site of the lighthouse. The proposed new radar station on Pisang Island will add to the existing coverage of the VTS radar, bridging the coverage gaps to overcome the weakness of the existing shore-based radar and improve the safety and security of marine navigation in the SoM.

Long-range visual marine aids to navigation are not required for current marine navigational practices. Therefore, the objective of this study was to develop a minimum luminous range for major lighthouses that are still in existence to sustain the operation of the lighthouses in the future. Two steps were involved in the determination of the minimum luminous range, namely the modification of the existing geographical range formula, and the finding of a strong linear correlation between the light intensity and the luminous range with the lowest gradient possible in a graph. The application of the minimum luminous range would eliminate the loom of light beyond the geographical range of the lighthouse. This approach was applied to seven major lighthouses in Peninsular Malaysia, which resulted in a minimum luminous range of between 12 nm to 14 nm, which was a reduction from the existing range of 18 nm to 25 nm. The validation of the minimum luminous range was performed in two ways; using a Full Mission Ship Simulator (FMSS), and matching the proposed minimum luminous range with the lighting system available. The results of the validation by using the FMSS between the luminous range of 25 nm and 14 nm showed that the light could be sighted and identified at 58.7 nm and 58.6 nm, respectively, which was, therefore, not significant. The validation by matching with the lighting equipment available in the market showed that the eight-tier VLB-44, which has replaced the rotating lighting system in the US since 2008, was highly matched with the proposed minimum luminous range. This further validated the minimum luminous range. The minimum luminous range is sufficient for current navigational uses and may reduce the costs for procuring and maintaining lighting systems, and will be able to sustain the operations of lighthouses in this GNSS age.

The main objective of this paper is to examine the applicability of Linan and Chen’s entrepreneurial intention model (EIM) in predicting the entrepreneurial intention. EIM is an adaptation of the Theory of Planned Behavior that focuses on entrepreneurial intention and hypothesizing slightly different patterns of relationship with regards to subjective norms. The model also includes human capital and demographic factors. Snowball sampling method was used to collect data using the entrepreneurial intention questionnaire (EIQ) through several social media platforms. The survey indicates that the overall entrepreneurial intention of Saudi students is high (mean = 5.41). Eight out of the seventeen hypothesized relationships were found to be significant. Among the demographic variables, gender-personal attitude was significant whereas self employment experience and years of business education were found to be significantly related with perceived behavioral control. The statistical analysis using partial least square structural equation modelling validated the model. All the three antecedents of entrepreneurial intention were significantly related with entrepreneurial intention. The results of this study will help policy makers to get deep understanding into the phenomenon of entrepreneurship among Saudi university students and thereby develop a conducive environment. This study also validates the entrepreneurial intention model in a different cultural context.

The main aim of the study is to test a house pricing model by combining hedonic and asset-based pricing models. An understanding of the relationship between house pricing and its return (the rental income) helps to establish houses as a significant asset class. The model tested the relationship between house pricing (dependent variable) and the house attributes (independent variables) derived from Freeman’s framework of housing attributes. This study uses a large data-set of 1,899 sample of new, high-end houses purchased between 2016 and 2019 collected from the national capital region of India (Delhi-NCR). The algorithm was built in R-Script, and stepwise multiple linear regression was used to analyze the model. The analysis of the model proves that the three significant variables, namely, carpet area, pay-off, and annual maintenance charges explain the price function. Further, the model is statistically fit. The major contribution of the study is to understand the key factors and their influence on the house pricing. The model will be helpful in risk assessment in the housing investment and enhance the chances of investment. Policy-makers can use information about the underlying valuation drivers of the house prices to stabilize the market and also in framing the tax policies.