Purpose This study attempts to find the response of the real estate market to economic changes by identifying cause-effect relationships between mortgage, residential investment, and Saudi employment. Design/methodology/approach A quantitative approach to analytically examine the relationship among the variables. To find out the impact of investment, mortgage and Saudi employment on the Saudi real estate growth from 1970 to 2019. All data sets were obtained from the General Authority for Statistics (GAST), Saudi Central Bank (SAMA) and World Bank Group. Findings This study reveals a positive relationship between the mortgage and GDP in the Saudi Arabian real estate market. The same results for employment and investment; both have a positive effect on the GDP of the real estate market. Research limitations/implications Analyzing the impact of real estate financing on various industries and the extent to which it is related to employment and unemployment rates is essential for future research. Moreover, this research can be applied to different countries and compared based on similarities and differences in implementing mortgage-related policies. Practical implications The government must encourage investment in various ways and establish a stable structure that ensures market stability and finds a balance between supply and demand. Social implications This study reflects the importance of real estate financing not only to individuals and governments but also to investors and business workers, and it is essential to analyze the impact of real estate financing on various industries, as well as the extent to which it is related to employment and unemployment rates. This research can be applied to different countries and compared based on similarities and differences in the implementation of mortgage-related policies. Originality/value This study contributes to testing this study’s hypothesis: that mortgage positively impacts the real estate market of Saudi Arabia.

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This paper aims to analyze the level of technical efficiency and determinants of technical inefficiency of transport manufacturing firms in Malaysia using Stochastic Frontier Analysis (SFA) approach from 2005 to 2010. Through SFA approach, hypothesis test is conducted in order to select Cobb-Douglas or Translog production function and testing the effects of technical inefficiencies. While the determining factors that been taken into account include the capital-labor ratio, training expenses, education level ratio, wage rate, information and communication technology expenditure, and firm size. Hypothesis test results show that the Cobb-Douglas production function is rejected. While the test for the effect of technical inefficiency shows its existence. Training expenses, secondary and tertiary education level ratios, wage rates and information and communication technology expenses are significant determinants for transportation manufacturing firms. However, the capital-labor ratio was found that it has reduced the level of technical efficiency. The implications of these results show that firms need to focus on investing in human capital, information technology and increase motivation among employees such as rising wage rates and reducing the use of capital appropriate to the technology.

Managers’ political motives refer to intention of managers to implement motivational and punishment motives in performance appraisal systems. The ability of managers to appropriately implement such political motives in appraising employee performance may have a significant impact on work outcomes (i.e., distributive justice and turnover intention). Although the relationship has extensively been examined, the predicting variable of managers’ political motives is given little emphasis in the performance appraisal research literature. Thus, this study was done to investigate the effect of managers’ political motives in performance appraisal systems on work outcomes. Self-report questionnaires were used to obtain data from employees at a military oriented tertiary educational institution in West Malaysia. The results of SmartPLS path analysis model displayed two essential findings: first, motivational and punishment motives were significantly associated with distributive justice. Second, motivational and punishment motives were insignificantly associated with turnover intention. These findings highlight that managers’ political motives in performance appraisal systems are significant predictors of employees’ distributive justice, and managers’ political motives in performance appraisal systems are not significant predictors of employees’ turnover intention in the selected organization. Further, this study offers discussion, implications and conclusion. Keywords: motivational motive; punishment motive; distributive justice; turnover intention