Tài liệu Iccrem 2018 analysis of real estate and the construction industry

scelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only ICCREM 2018 Analysis of Real Estate and the Construction Industry Edited by Yaowu Wang; Yimin Zhu; Geoffrey Q. P. Shen; and Mohamed Al-Hussein Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. ICCREM 2018 ANALYSIS OF REAL ESTATE AND THE CONSTRUCTION INDUSTRY PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON CONSTRUCTION AND REAL ESTATE MANAGEMENT 2018 August 9–10, 2018 Charleston, South Carolina SPONSORED BY Modernization of Management Committee of the China Construction Industry Association The Construction Institute of the American Society of Civil Engineers EDITORS Yaowu Wang Yimin Zhu Geoffrey Q. P. Shen Mohamed Al-Hussein Published by the American Society of Civil Engineers Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. 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ICCREM 2018 iii Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Preface We would like to welcome you to the 2018 International Conference on Construction and Real Estate Management (ICCREM 2018). Harbin Institute of Technology, Louisiana State University, Hong Kong Polytechnic University, University of Alberta, Luleå University of Technology, Heriot-Watt University, Marquette University, Karlsruhe Institute of Technology, Guangzhou University. The Conference is a continuation of the ICCREM series which have been held annually since 2003. The theme for this conference is “Innovation Technology and Intelligent Construction”. It especially highlights the importance of innovation technology for construction engineering and management. The conference proceedings include 138 peer-review papers covered fourteen important subjects. And all papers went through a two-step peer review process. The proceedings of the congress are divided into four parts:  Innovative Technology and Intelligent Construction  Sustainable Construction and Prefabrication Analysis of Real Estate and Construction Industry Construction Enterprises and Project Management   On behalf of the Construction Institute, the American Society of Civil Engineers and the 2018 ICCREM Organizing Committee, we welcome you and wish you leave with a wonderful experience and memory at ICCREM 2018. Professor Yaowu Wang Professor Yimin Zhu Harbin Institute of Technology Louisiana State University P. R. of China USA Acknowledgments Organized by Harbin Institute of Technology, P.R. China Louisiana State University, USA Hong Kong Polytechnic University, P.R. China University of Alberta, Canada Luleå University of Technology, Sweden © ASCE ICCREM 2018 iv Heriot-Watt University, UK Marquette University, USA Karlsruhe Institute of Technology, Germany Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Guangzhou University, P.R. China Executive Editors Yue Cao Zhuyue Li Xuewen Gong Jia Ding Xianwei Meng Mengping Xie Jiaqing Chen Tianqi Zhang Yushan Wang Chong Feng Xiangkun Qi Jingjing Yang Xiaoting Li Yu Hua Wenting Chen Xiaowen Sun Hang Shang Shiwei Chen Tongyao Feng Conference website: http://www.iccrem.com/ Email: [email protected] Conference Committee Committee Chairs Prof. Yaowu Wang, Harbin Institute of Technology, P.R. China Prof. Geoffrey Q.P. Shen, Hong Kong Polytechnic University, P.R. China Conference Executive Chair Prof. Yimin Zhu, Louisiana State University, USA Conference Co-Chairs Prof. Mohamed Al-Hussein, University of Alberta, Canada Director Katerina Lachinova, Construction Institute of ASCE.(ASCE members), USA Prof. Thomas Olofsson, Luleå University of Technology, Sweden Prof. Ming Sun, Heriot Watt University, UK Prof. Yong Bai, Marquette University, USA Prof. Kunibert Lennerts, Karlsruhe Institute of Technology, German Prof. Xiaolong Xue, Guangzhou University, P.R. China © ASCE ICCREM 2018 Organizing Committee and Secretariat General Secretariat Asso. Prof Qingpeng Man, Harbin Institute of Technology, P.R. China Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Deputy General Secretariat Asso. Prof. Hongtao Yang, East China University of Science and Technology, P.R. China Asso. Prof. Xiaodong Li, Tsinghua University, P.R. China Asso. Prof. Chengshuang Sun, Beijing University of Civil Engineering and Architecture, P.R. China Committee Members Dr. Yuna Wang, Harbin Institute of Technology, P.R. China Dr. Tao Yu, Harbin Institute of Technology, P.R. China Mr. Yongyue Liu, Harbin Institute of Technology, P.R. China Mr. Zixin Han, Harbin Institute of Technology, P.R. China Mr. Zhenzong Zhou, Harbin Institute of Technology, P.R. China © ASCE v ICCREM 2018 vi Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Contents Indemnification Housing Policy Satisfaction of Low and Middle-Income Group in China: Empirical Study Based on CGSS 2015 Data ................................................ 1 Qiru Ma, Yongxiang Wu, and Zhuowei Wang Labor Productivity in Construction Industry: Investigating the Influence of Internal Psychosocial Stressors .......................................................................................... 10 Ahsen Maqsoom, Abdul Mughees, Ammar Khalid Khan, and Muhammad Imran Arif Exploring the Evolution Trends of Urban Resilience Research ............................................ 18 Liang Wang and Xiaolong Xue A General Overview of the Impact of Global Financial Crisis on Construction Industries .......................................................................................................... 28 Baffoe-Twum Edmund, Huojun Yang, and Asa Eric Endogenous Impact of Urban Residents’ Consumption and Housing Price: A Case Study in Harbin City ....................................................................................... 39 Zhuowei Wang, Yongxiang Wu, and Qiru Ma Work-Family Conflict in Construction Workers in First Tier Cities: A Cross-Sectional Study in Beijing City................................................................................. 47 Ziyang Song, Xiaodong Li, and Yifan Geng A Study of Harmonious Residential Construction Systems Using Structural Equation Modeling ................................................................................................ 54 Xiaodong Yang, Jiayu Zhang, and Yongxiang Wu Study of the Allocation of Basic Urban Residential Land Supply from the Perspective of Justice and Fairness ......................................................................... 67 Ke Lu, Ruirui Luo, and Wei Zhang The Development of Construction Industrialization in China: From Government Policies Perspective ............................................................................................ 77 Ankang Ji, Xiaolong Xue, Yuna Wang, Shu Shang, Wenbo Huangfu, Ting Luo, and Yudan Dou Marketing Strategy Analysis of Commercial Real Estate Project Park I of Kaili City.................................................................................................................. 85 Yanju Liang and Zhiguo Gao The Fluctuation Research of Chinese Regional Real Estate Cycle from 1996 to 2015 .................................................................................................................... 91 Tingting Yang, Lin Wang, Liu Wu, and Lifang Huang © ASCE ICCREM 2018 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Empirical Study of Risk Factors in Financial Condition of Chinese Real Estate Listed Companies ................................................................................................ 98 Bainan Yang, Liang Liang, and Yanru Gao Does Land Finance Matter the Tertiarization of Industry Structure? A Perspective Based on Urban Scale .................................................................................... 108 Zhifeng Wang, Shuo Meng, Hao Wang, and Junhua Chen Study on the Real Estate Bubble Early Warning from the Perspective of System Dynamics .............................................................................................................. 116 Yunbo Li and Wenting Chen Analysis of Real Estate Inventory of Changchun Based on System Dynamics Method ................................................................................................................. 125 Xiaoxin Ding and Peijia Xu Measurement of CSR in the Construction Industry ............................................................ 137 Ying Jiang and Xiaolong Xue Factors Affecting the Price of Second-Hand Housing in First-Tier Cities: Empirical Analysis Based on Panel Data .................................................................. 143 Xuefeng Zheng and Fan Dong The Efficiency of Chinese Regional Construction Industry Based on DEA Model: An Empirical Study from 2006 to 2016 ..................................................... 154 Hua Su, Yulong Li, Fanchun Meng, and Zhou Zhou Multi-Stakeholder Risk Analysis for Construction Industry Industrialization: A Review .................................................................................................. 163 Mengping Xie, Yuna Wang, and Kaijun Yang Study on the Efficiency Estimation for Chinese Construction Industry through Three-Stage DEA Model ......................................................................................... 173 Wei Zhang and Xisheng Zhu Econometric Analysis on Chinese Housing Bubble: Evidence from National and Municipal Panel Data ..................................................................................... 181 Junhua Chen, Zhiyuan Zhao, Hao Wang, and Zhifeng Wang Study on the Efficiency Differences and Influencing Factors of China's Regional Construction Industry ........................................................................................... 189 Shen Zhong, Lei Du, and Yuqi Liu Research on Administrative Approval Reform in Engineering Construction Field: Take Guangzhou as an Example ......................................................... 198 Sicong Zhao, Huabo Duan, Bei Wang, and Ruyu Feng © ASCE vii ICCREM 2018 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Study on Radiation Effects of Central Cities in Beijing-Tianjin-Hebei Region .................................................................................................................................... 203 Renhui Liu and Haizheng Wu Measuring the Efficiency of Construction Industry in China Based on DEA and Malmquist Index ................................................................................................... 212 Yanyan Fan, Zhiye Huang, and Yuan Chang Empirical Research on the Effect of the Business Tax (BT) to Value-Added Tax (VAT) Reform on the Financial Performance of Listed Real Estate Companies ............................................................................................................................. 219 Wenguo Ai and Shunyin Fan Study on Cities’ Housing Price Fluctuation and Regional Differentiation Based on the Panel Data of 35 Cities in China ..................................................................... 226 Ruoxing Chen, Jialei Xia, and Guanghong Ma The Moderate Investment Scale Study of Real Estate Promoting Economic Growth ................................................................................................................................... 238 Peili Guo, Xiaojuan Zhang, Jiwei Zhu, and Lingxia Sun Labor Force Production Efficiency Evaluation of American Construction Industry Based on the DEA-Malmquist Model from 2006–2016 ........................................ 247 Jie Lin, Yulong Li, Chao Wang, and Bingzhen He Research on the Causes and Solutions of “Empty Cities” ................................................... 256 Feiyan Zhao and Guang Yang The Effect of Demographic Structure on Housing Demand in Chongqing ........................ 262 Haiyan Jin Evaluation on Efficiency of Listed Companies of Construction Industry in China Based on DEA Model from 2006 to 2016................................................................... 278 Zhou Zhou, Yulong Li, Lili Gao, and Hua Su Evaluating the Impact of Housing Restriction Policy on Urban House Prices with the SDPD Model ............................................................................................................ 287 Juan Li, Qiao Yang, and Kun Wan Analysis on the Path of Supply-Side Structural Reform in Linyi Real Estate Market ................................................................................................................................... 298 Jinyi Wu © ASCE viii ICCREM 2018 1 Indemnification Housing Policy Satisfaction of Low and Middle-Income Group in China: Empirical Study Based on CGSS 2015 Data Qiru Ma1; Yongxiang Wu2; and Zhuowei Wang3 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. 1 Postgraduate, Dept. of Construction and Real Estate, Harbin Institute of Technology, Harbin 150001, China. E-mail: [email protected] 2 Professor, Dept. of Construction and Real Estate, Harbin Institute of Technology, Harbin 150001, China (corresponding author). E-mail: [email protected] 3 Postgraduate, Dept. of Construction and Real Estate, Harbin Institute of Technology, Harbin 150001, China. E-mail: [email protected] ABSTRACT The housing security system has achieved considerable development since China established it in 1998. However, there are still many deficiencies in the indemnification housing system. This research attempts to examine the issue of low and middle-income group's satisfaction with indemnification housing policy from a micro perspective based on CGSS 2015 data. This research used two-step cluster analysis method to define low and middle-income groups, and a multiple linear regression model to explore the influencing factors. It is found that three factors: the housing area, socioeconomic status compared to peers, personal perceived social fairness significantly affect the satisfaction of the low and middle-income groups on the policy. This research gave explanations for satisfaction with indemnification policy among low and middlegroup in China. On the basis of this, suggestions are provided for the formulation of policy. INTRODUCTION Since Engels published “On Housing Problem” in 1870, the research on housing issues has never been interrupted by the social science community. Under the background of China's rapid economic development and accelerating urbanization process, indemnification housing has become the key to solve the problem of government and market failure (Cao and Keivani 2014). Indemnification housing includes：low-rent housing, affordable housing, price-fixed housing and public rental housing. Official definition of object for indemnification housing is for families with low and middle-income and with housing difficulties. The low and middle-income group are the collective names of official protection objects for social security, but in no way do they refer to group divided by income. Therefore, the division of group needs further study. In order to ensure “everybody has housing”, to achieve stable and sustainable development of society, the government has introduced a series of policies. At present, after years of construction and development, the construction of China’s housing security supply system is becoming more and more improved. However, there are problems such as the remoteness of indemnification housing, imperfect supporting facilities, insufficient supply and structural imbalances occurred in China's construction of the housing security system. In 2015, 10050 sets of affordable housing in the Baisha Bay Area of Qingdao received only 200 applications within two years of open sales. In 2017, the vacancy rate of affordable housing in Longgang District, Shenzhen exceeded 1/3. Therefore, it is necessary to evaluate the satisfaction of the policy of indemnification housing so as to solve the problem of inconsistency between policy orientation and people's needs (Ibem and Aduwo 2013). For indemnification housing satisfaction, the academia focuses on the factors that cause © ASCE Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. ICCREM 2018 2 household dissatisfaction, and studies it from two dimensions: one is to regard indemnification housing as “commodity” and to compare the actual experience of the occupant with expected expectations; the other is to evaluate the overall experience in habitation, which is more instructive to the design of indemnification housing (Wu and Chen 2013). In the first dimension of study, different researchers have focused on different factors, which can be roughly divided into the following: the influence of demographic characteristics, the impact of housing characteristics, the impact of psychological experience, and the influence of the community environment (Ding 2010; He and Yang 2011). In the second dimension of study, through the investigation of low-rent housing in Shanghai, Zhou and Long (2009) analyzed the specific satisfaction of low-rent housing tenants in eight aspects, such as bedtime, children's learning, and washing, and then summed up the overall satisfaction of housing, and pointed out problems with the use and design of space. For indemnification housing policy, most studies started from a certain angle or a certain object, and explored the shortcomings of current policies. Starting from the perspective of the residents' ability to pay, Li (2017) illustrated that the residents' renting ability is stronger than buying ability, and relevant policy recommendations are proposed. Lv et al. (2010) put forward a theoretical model, from the perspective of unified urban and rural development and planning, in order to solve the problem of urban migrant population housing. Peng and Tang (2012) studied housing policies to implement the social integration of migrant workers from the aspect of social system's rejection of low-income migrant workers. For indemnification housing policy satisfaction, few studies are related with it. Chen et al. (2013) conducted research on housing conditions of low and middle-income group. With the purpose of improving people's livelihood, the article finally settled on the reformation of housing system. Indemnification housing policy satisfaction was mentioned as one of the indicators. Item Education background Table 1. CGSS Questions Used for Cluster Analysis. CGSS Survey Questions The highest level of education you have at present (including the current degree in reading)? Response options: No education, Literacy classes, Primary school, Primary middle school, High school, Poly-technical school, College, University, Postgraduate. Status of The status of your account registration? Response options: Agricultural household Account, Non-agricultural account, Resident account, Military account, registration No account. Work What is your work experience and status? Response options: Currently experience and engaged in non-agricultural work, Currently engaged in agricultural work, status Currently no work, Never worked before. Annual income Approximately, what’s the average annual income of your family? per capita Socioeconomic Approximately, how is your socioeconomic status compared to your status peers? Response options: Above the average, Average, Below the average. According to above analysis, we may see that researches related to the topic are from two separate perspectives: the satisfaction of the existing residents and the rationality of the policy, the problems of the indemnification housing system or design. Therefore, this study aims to fill © ASCE ICCREM 2018 3 in the research gap by studying the factors that affecting the low and middle-group's satisfaction of the indemnification housing policy in a micro perspective. Influence factor General evaluation Individual characteristic Table 2. Variables Setup and Definitions. Variable Definition of Variable Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Satisfaction of the indemnificatory Actual value housing policy (Y) Per capita housing area Actual value (sq. meters) (x1) Socioeconomic status compared to Above the average = 1, peers (x2) Average = 2, Below the average = 3 Modified annual income per capita Actual value (Yuan) (x3) Housing Building age (Year) (x4) <1950 = 1, characteristics 1950~1959 = 2, 1960~1969 = 3, 1970~1979 = 4, 1980~1989 = 5, 1990~1999 = 6, 2000~2009 = 7, >2010 = 8, Daily sunshine time of the house in <1 = 1, winter (Hours) (x5) 1~2 = 2, 2~3 = 3, 3~4 = 4, 4~5 = 5, 5~6 = 6, 6~7 = 7, 7~8 = 8, >8 = 9 The proportion of housing expenditure Actual value (%) in household expenditure (x6) Psychological Personal perceived social fairness (x7) Completely unfair = 1, experience Relatively unfair = 2, Neutral = 3, Relatively fair = 4, Completely fair = 5 Psychological Life happiness (x8) Completely unhappy = 1, experience Relatively unhappy = 2, Neutral = 3, Relatively happy = 4, Completely happy = 5, Income level (x9) Completely reasonable = 1, Reasonable = 2, Unreasonable = 3, Completely unreasonable = 4 © ASCE ICCREM 2018 4 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. EMPIRICAL RESEARCH Data sources: The original data used in the empirical analysis of this paper was derived from the 2015 Chinese General Social Survey (CGSS) conducted by the China Survey and Data Center of Renmin University of China. The survey was published on January 1st, 2018. This paper filters out missing values and error values of variables, and samples aged 18 to 65 years old. Finally, we obtained 1440 samples. Variables and methods: The analytic steps consist of the following three stages: Data are analyzed using a two-step cluster analysis approach that accounts for both continuous and categorical data (Shortell et al. 2014). Cluster analysis can formulate groupings based on several characteristics. Education background, status of household registration, work experience and status, annual income per capita, and socioeconomic status were chosen to reflect the official definitions of such group. CGSS questions used for cluster analysis is as Table 1. The result of two-step clustering is analyzed, and the characteristics of each category are determined according to the relevant variables. Select low and middle-income group that meet the characteristics from the result. From three aspects of individual characteristics, housing characteristics, and psychological experience, the relevant variables were selected as independent variables, and the satisfaction of indemnification housing policies was used as the dependent variable to perform linear regression. Variables setup is as Table 2. The model is established with this formula: Indemnification housing policy satisfaction= f (individual characteristics, housing characteristics, psychological experience). Result from the model: (1) The result of Two-Step Cluster Analysis As we can see from Figure 1 and Figure 2, the classification result is valid. Samples were divided into two categories, in which the proportion of the large cluster was 55.1%. After analysis, cluster 2 should be protected by indemnification housing policy. Related description is provided in Table 3. According to the grouping standards of the National Bureau of Statistics, urban residents are divided into the lowest income households (10%), low-income households (10%), middle-level households (20%), middle-income households (20%), and middle-level households (20%), Highincome households (10%), Highest income (10%). It can be seen that the classification result is approximately consistent with the reality. Model Summary Algorithm TwoStep Inputs 5 2 Clusters Cluster Quality Poor Fair Good -1.0 -0.5 0.0 0.5 1.0 Silhouette measure of cohesion and separation Figure 1. Cluster summary. (2) The result of Multiple Linear Regression Analysis As group 2 is the group that should be covered by the indemnification housing policy, their satisfaction with the policy is more © ASCE ICCREM 2018 5 Cluster Sizes Cluster 1 2 55.1% 44.9% Figure 2. Cluster sizes. According to the Model Summery and ANOVA table (not given due to space limitations), R 2 = 0.332, D-W value = 2.034, P=0.000<0.05, and as is shown in Figure 3, regression standardized residual approximately subjects to normal distribution. All of above guarantees the effectiveness of the regression model. The coefficient result is shown in Table 4. ANALYSIS AND DISCUSSION About the individual characteristics: All the personal factors have obvious influence to the satisfaction of the indemnificatory housing policy. Per capita housing area have greatest positive impact on the dependent variable. The larger the housing area, the higher the satisfaction was. Other than the housing area, socioeconomic status and annual income also play an important role. As is shown in Table 1 and Table 2, with the increase in the socioeconomic status and annual income, satisfaction increased. The recognition of one's economic status will affect the satisfaction of indemnification housing. The low and middle-income groups are sensitive and self-conscious about their status. The special property of this kind of housing will amplify this effect. All the above can prove the fact that: economic ability is the most important factor that restricts the satisfaction of policies. 100 80 Frequency Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. valuable. So, we performed multiple linear regression analysis on samples in group 2. Inspect the data with t test, screen out 7 variables that are closely related to the dependent variable. Building age (x4) and Daily sunshine time of the house in winter (Hours) (x5) fail to pass significance texts. The model fits well after the removal of these 2 variables, and the specific results are shown in the Table 3. 60 Mean = -2.89E-17 Std. Dev. = 0.996 N=793 40 20 -4 -2 0 2 Figure 3. Regression Standard Residual. © ASCE Note: Input (predictor) importance: © ASCE 2 1 Group that should be protected by indemnification housing policy Group that can rely on market to solve housing problems Label 1.0 0.8 The majority of them hold an agricultural account, used to be or currently is a farmer, undereducated, and with low capita income The majority of them hold a nonagricultural account, are engaged in nonagricultural work, are well educated, and with high per capita income Description 55.1%(793) 44.9%(647) Size What is the home economic status of your family? What is the home economic status of your family? Inputs Annual income per capita (modified). Annual income per capita (modified). Educational background. Educational background. Work experience and status. Work experience and status. Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. Status of household registration. Status of household registration. ICCREM 2018 6 Table 3. Description of Clusters. 0.6 0.4 0.2 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. ICCREM 2018 7 About the housing characteristics: According to common sense, building age and daily sunshine time of the house in winter should have impact on the comfort of living. However, these two variables did not pass the significance test. But the proportion of housing expenditure in household expenditure has a significant negative effect on the dependent variable. There are two reasons for this. Firstly, in the long run, middle-income group's savings are still far from enough to pay for comfortable housing. Therefore, the group pays more attention to the daily expenses brought by the housing rather than buying one-time consumption. Secondly, in the short term, this group aims at earning more incomes. The cost of housing directly affects the purchase of basic household items, which in turn significantly affects the quality of life. Therefore, their requirements for living experience are relatively low. Table 4. Coefficient Results. Unstandardized Coefficients Model B Std Error (Constant) 65.60 6.29 Per capita housing area (sq. meters) .09 .02 Socioeconomic status compared to peers -4.27 1.37 Modified annual income per capita (Yuan) .00 .00 The proportion of housing expenditure in-11.50 4.96 household expenditure Personal perceived social fairness 3.32 .69 Life happiness 1.39 .84 Income level -2.29 1.27 Standardized Coefficients Beta t .16 -.11 -.09 -.08 10.43 *** 4.79 *** -3.13 *** -2.58 *** -2.32 ** .17 .06 -.07 4.81 *** 1.66* -1.81* Note: a. Dependent Variable: Satisfaction of the indemnificatory housing policy *** Significant at 0.01. ** Significant at 0.05. * Significant at 0.1. About the psychological experience: Personal perceived social fairness is more important than life happiness and income level. The recognition of social equity among low and middleincome group will significantly increase their satisfaction with housing security policies. This is due to the social nature of indemnification housing, the purpose of which is to maintain social fairness, balance arises from social inconsistencies caused by inequality between classes. The fairness of society directly reflects in whether the distribution of income is reasonable or not. Therefore, the more reasonable the income distribution, the higher the degree of satisfaction. In terms of personal experience, the stronger the sense of well-being in life, the more satisfied the low and middle-income group are. It should be pointed out that this is a mutually reinforcing process: a good policy of affordable housing will enable this stratum to live in order to increase its well-being, the increase in happiness can improve the class's impression of housing security policies and increase satisfaction. CONCLUSIONS From the analysis of the above-mentioned data, we shall raise relative suggestions accordingly: The reform of the household registration system should be promoted. This paper divided © ASCE Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. ICCREM 2018 8 samples according to 5 variables. It is found that the proportion of group covered by housing security accounts for more than half, posing a challenge to the national housing security policy. Migrant workers, laid-off workers and new employees consist of this group. The root cause of its low level of satisfaction is the dual urban-rural system in the household registration system. As social welfare and household registration are tied together, the government should first advance the reform of the household registration system to make this group enjoy the same treatment and benefits as local residents. Personal perceived social fairness and socioeconomic status comparing to peers are two key factors resulting in dissatisfaction among the low and middle-income group. Because of the large gap between the rich and the poor, low and middle-income group are in a weak position in society. The lack of recognition of social fairness and the lack of certainty in their own abilities can significantly affect policy satisfaction. Policy formulation should always be committed to safeguarding social fairness and protecting the interests of vulnerable groups. Instead of comfort, the requirements of housing for low and middle-income group are only reflected in housing area. Personal economic conditions have an impact on satisfaction. Therefore, the essence of improving policy satisfaction is to increase the income of the group. In the construction of indemnification housing, it is necessary to vigorously build houses that do not impose economic burden on the daily lives of low and middle-income group. REFERENCES Cao, J.A. and Keivani, R. (2014). “The limits and potentials of the housing market enabling paradigm: an evaluation of China's housing policies from 1998 to 2011.” Housing Studies, 29(1), 44–68. Chen, C.W., Huang, C. and Qin, J.W. (2013). “The reform of housing system and improvement of the people's livelihood: based on several typical low income groups.” Journal of Social Sciences, Hunan Normal University, 42(06), 60–68. (in Chinese). Ding, X. (2010). “Comparing satisfaction degrees in different affordable housing in Hangzhou.” Planner, 2010(s2), 196–200. (in Chinese). He, L.H. and Yang, C.Q. (2011). “Housing satisfaction of urban residents and its influential factors.” Journal of Public Management, 08(2), 43–51. (in Chinese). Ibem, E.O. and Aduwo, E.B. (2013). “Assessment of residential satisfaction in public housing in Ogun State, Nigeria.” Habitat International, 40(7), 163–175. Li, S.S. (2017). Research on the Housing Policy: An Analysis Based on the Residents' Housing Affordability. Wuhan University, Wuhan, China, (in Chinese). Lv, P., Ding, F.J. and Ma, Y.G. (2010). “China's housing policy in the rapid urbanization process.” China Soft Science, 08(2010), 25–36+60. (in Chinese). Peng, H.M. and Tang, H.H. (2012). “Exclusion and inclusion: housing dilemma and housing guarantee policy for low-income rural workers.” Shandong Social Sciences, 08(2013), 20–29. (in Chinese). Shortell, S.M., Wu, F.M., Lewis, V.A., Colla, C.H. and Fisher, E.S. (2014). “A taxonomy of accountable care organizations for policy and practice.” Health Services Research, 49(6), 1883–99. Wu, Y. and Chen, J.H. (2013). “Housing satisfaction in social housing sector: empirical analysis on Hong Kong public housing survey.” Comparison of Economic and Social Systems, © ASCE ICCREM 2018 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. 4(2013), 109–117. (in Chinese). Zhou, X. H. and Long, T. (2009). “Study on living behavior of low-income families with low income in Shanghai.” Journal of Architecture, 2009(8), 10–13. (in Chinese). © ASCE 9 ICCREM 2018 Labor Productivity in Construction Industry: Investigating the Influence of Internal Psychosocial Stressors Ahsen Maqsoom1 ; Abdul Mughees2 ; Ammar Khalid Khan3; and Muhammad Imran Arif4 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. 1 Assistant Professor, Dept. of Civil Engineering, COMSATS Institute of Information Technology, Islamabad, Pakistan 44000. E-mail: [email protected] 2 Postgraduate, Dept. of Civil Engineering, COMSATS Institute of Information Technology, Islamabad, Pakistan 44000. E-mail: [email protected] 3 Master, Preston Univ., Islamabad, Pakistan 44000. E-mail: [email protected] 4 Lecturer, Dept. of Civil Engineering, Swedish College of Engineering and Technology, Islamabad, Pakistan 44000. E-mail: [email protected] ABSTRACT Employee productivity is an important concern for construction organizations. Stress of any kind if stays longer can considerably reduce the productivity of employees. Recent researches have recognized that tight deadline and late working hours make the working environment stressful; hence influencing the productivity and health of construction workers. This research analyzes the internal psychosocial stressors particularly the stressors related to career development, motivation, stress at work, and social stressors that influence the productivity of construction labors. Data was collected through questionnaire survey filled by 163 middle and lower management staff working at various construction sites. Career development was identified as most critical factor among the internal psychosocial stressors influencing the labor productivity. It is recognized that labor productivity is dependent on the long working hours, work load, lack of promotion, communication gap between worker and supervisor, irresponsible management, lack of training, and insufficient pay for the overtime to workers particularly. INTRODUCTION Labor productivity is an important concern for all type of organizations and it is highly influenced by the psychosocial stressors (Leka and Jain 2010). Psychosocial stressors are defined as stressors reflecting both psychological and social aspects of workers and his surrounding environment. The International Labor Office (1986) defines work-related psychosocial stressors as “interactions between and among work environment, organizational conditions, job content and workers’ capacities, needs, culture, personal extra-job considerations that may, through perceptions and experience, influence health, work performance, and job satisfaction”. The psychosocial work environment includes numerous aspects related to work with psychological job demands, job control, efforts, and rewards comprising the key dimensions (Karasek and Theorel 1990). Other factors of importance are social support, work time arrangement such as long work hours and shift work, organizational culture, organizational climate and job insecurity (Caruso et al. 2006). Psychosocial stressors in construction industry is an important area to be focused, besides its importance related to the stressors influencing the workers’ productivity and project performance has not yet been properly examined. Developing countries’ construction industries particularly the construction industry of Pakistan is facing a lot of problems related to workers’ productivity, hence many of the projects fail due to poor labor performance (Maqsoom and Charroenngam 2014; Razzaq et al. 2016). © ASCE 10 ICCREM 2018 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19. Copyright ASCE. For personal use only; all rights reserved. This study investigates the impact of internal psychosocial stressors on labor productivity in Pakistani construction industry. The internal psychosocial stressors investigated in this study are career development, motivation, work related and social support related stressors. The results of the current study will contribute to the labor productivity literature where there is shortage of literature related to psychosocial stressors. LITERATURE REVIEW Internal psychosocial stressors consist of various stresses related to the career development, motivation, social support and work environment of the employee (International Labor Office 1986). Career development helps to hold and motivate workers through the career development process, workers are assisted in setting realistic goals and to develop the required skills and abilities for achieve their goals (Mwanje 2010). Armstrong (2009) emphasized on the practice of giving internal promotions, to create a feeling that career development offer good career growth opportunity which will motivate the employees to remain in the organization. Greenhaus and Powell (2010) define career development as the pattern of work related experience that spans the course of a person’s life. Multinational construction firms are increasingly paying close attention to the validity of their recruitment practices and are equally paying close attention to develop their employees’ career to assure that they achieve maximum performance both in present and future (Mwanje 2010). Motivation is one of the most important concept of psychology and very essential for managers who direct the growth of their employees towards sensible goal (Adnan 2005). Horge (2004) stated that motivation play an important role in worker’s productivity and managers should know what motivation is and how workers are motivated towards performance. Money is seen as a great motivator of employee however there is a general view that if management can identify other things that can motivate the workforce apart from money, maybe there will be a dramatic reduction in the demand by workers for pay rise and less time will be spent annually on workers’ union negotiation meetings (Badu and Batchison 2010). Other scholars added that reduction in motivational stressors results in increase in productivity of workers and reduced cost of operations (Booth 2004). Workers who spend a major part of their lives at project sites depend upon their several personal needs (Srivastava et al. 2007). Social support leads to believe that employee is cared for loved and valued and the employee belong to the communication series and the mutual obligation (Cobb 1976). Wayne et al. (1997) determined that the social interaction between the supervisor and the related employee is the main key of the employee attitude and the behavior at the site. Interaction and supportive relationships between the coworkers are the main motivation for the worker and also have the positive effect on the worker productivity and well-being (Howard and Frink 1996). Another psychosocial factor which affects the worker productivity is stress at work. Stress at work is caused by various factors like job characteristics, role in the organization, job prospect and co-worker stress. Cooper and Marshall (1976) suggested five sources of stress at work: intrinsic to the job, role in the organization, career development, relationship at work, and organizational structure and climate. Role conflict and role ambiguity often appear among the main stressors, especially in environments and organizations subject to drastic changes. It is considered to be a mental state that reflects the necessity to affective commitment, continuance commitment, and normative commitment to remain in organization (Meyer and Allen 1997). Job satisfaction and organizational relation determines the level of commitment towards the © ASCE 11