The Mediating Effect of Consumers’ Purchase Intention: A Perspective of Online Shopping Behavior among Generation Y

Young consumers spend most of their time online in comparison to the working adults due to their great potential of buying power as well finding that online shopping is more convenient. The objective of this study is to investigate factors determining online purchase intention among the university students whereby variables such as attitude, subjective norm, trust, purchase intention and behavior were tested. Total of 800 questionnaires were distributed and 662 questionnaires were usable. A quantitative research was undertaken through the distribution of survey questionnaires and the data were analyzed using Structural Equation Modelling (SEM) to test the relations among variables. The analyses have proven that purchase intention has functioned effectively as a mediator between the independent variables (attitude, subjective norm and trust) and dependent variables (online shopping behavior).The results of this study offer some new frontiers in supporting as well as enriching more studies in the scope of online shopping behaviors. This study contributes to the dynamics of the causative relations between examined variables and highlights the significance of attitude, subjective norm, trust and consumer behavior in ascertaining the purchase intention in the context of Malaysian online purchases. Keywords: Purchase intention, Attitude, Subjective norm, Trust, Consumer behavio

Drivers of Retail Supply Chain Efficiency: Moderating Effect of Lean Strategy

The retail chain store business is an infant stage of growth and development in Bangladesh and so are the supply chain management practices in this sector. The main objective of this study is to identify the key drivers of retail supply chain efficiency. Moreover this study aims at examining the moderating effect of lean supply chain strategy on the link between supply chain drivers and performance. For the purpose of the study, data were collected with a structured questionnaire from 115 participants consisting of outlet and supply chain managers of some selected retail chain stores in Bangladesh. Collected data were analyzed using partial least squares (PLS) structural equation modeling with the support of the software Smart PLS 2.0 M3. Findings revealed that out of five supply chain drivers, four namely inventory management, use of IT, transportation management and coordination were the most significant determinants of retail supply chain efficiency while suppliers role was found to be negatively correlated. Moderating effect of lean strategy was also noticed on the link between two drivers namely transportation management and coordination with retail supply chain efficiency

Predicting the GDP of the new economy based on the human capital using neural network approach

Human capital has become important because knowledge is a critical ingredient for gaining competitive advantages, particularly in the New Economy era.It has been described as becoming the preeminent resource for creating economic wealth. To date, several studies have been conducted to determine the relationship between human capital and company performance.The relationship between human capital and economic growth has been explored.However, past literature reveals that artificial intelligence techniques have not been utilized in understanding the effect of human capital on economic growth.Artificial intelligence techniques such as neural networks have been successfully applied to business and financial problems.To this end, the neural networks approach was used to determine the impact of human capital on the New Economy.This paper discusses the results of the exploratory study for predicting demand for human capital. Data from 1971 to 1996 was collected for this study.The variables used for the prediction were based on Canadian’s Human Capital Measurement as suggested by Laroche and Merrette (2000).The exploratory study indicated that neural network is a potential approach for predicting the GDP based on human capital. In conjunction with neural network approach, statistical methods were also used to explain the relationships between variables in the study

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Liquidity risk underlying debt financing and economic condition: A Panel data analysis of Islamic Bank in Malaysia

The objective of this paper is to analyze the determinants of Islamic bank liquidity risk in Malaysia with special focus on debt financing. Based on this objective, this study utilized unbalanced panel dataset of 17 Islamic banks in Malaysia over the period 1998-2012.The method use is this study is panel data regression analysis. The results show that the level of capital is significant with the liquidity risk.For debt financing variable, the results signify that the higher volatility of debt financing modes will cause some liquidity risk.For macroeconomic condition, the result shows that impact of inflation rate could decrease the nominal value deposits in Islamic bank and finally the relationship of liquidity risk and Islamic bank deposit rate is negative.The implication of this study is that when the Islamic banks consider on their liquidity risk management, the have to look upon the behaviour of debt financing, inflation rate and Islamic bank deposit rate