Regional Variations in Construction Labor Productivity--The Case of Two Indian States.
| Author | Salunke, Sanjeet B. |
| Position | Maharashtra and Arunachal Pradesh, India |
Introduction
Construction sector is one amongst the largest contributors to the economy of the world. Every year approximately US$10 trillion is being spent on activities related to construction goods and services all over the world (Barbosa et al., 2017). Construction sector has employed more than 35 million people (as in October 2016) and is expected to become the largest employer in India having more than 75 million people by 2022 (KPMG, 2016). The spending on infrastructure in the construction sector has grown to 9% of GDP in 2017. Consequently, tremendous efforts are being made to understand the growth drivers and constraints in this sector. One of the constraints has been the low productivity of the construction industry. In fact, the growth rate of construction labor productivity is the lowest; during the period from 1980 to 2008, the growth in labor productivity was just at an annual rate of 0.72 percent in the Indian construction sector (Goldar et al., 2014) while in other sectors such as manufacturing it is growing at 3.6% (Barbosa et al., 2017). It appears that if the same trend continues, it would be difficult to suffice the growing housing and infrastructure needs of the world. It is estimated that investment in infrastructure by 2022 will be around Rs 50 trillion (US$ 777.73 billion) in order to ensure sustainable development in India (India Brand Equity Foundation, 2019). This demand, if supported by proper utilization of resources through improved labor productivity, shall lead to the economic development of the nation.
Productivity determines the measure of the efficiency of conversion of resources including human and material to goods and services. Construction being a labor intensive sector and the major productive resource being the labor force, its productivity fundamentally depends on human effort and performance (Rojas & Aramvareekul, 2003). In addition, it is observed that the labor component is of great significance with respect to the four constraints of project management, i.e., time, cost, scope, and quality. Out of the total project cost, 30% to 50% consists of the labor costs in the construction phase of a project (Harmon & Cole, 2006). These labor costs, if efficiently tapped, shall portray a clear image of the economic success of the project. Workforce related aspects consistently rank high among causes of delay in construction projects (Assaf et al., 1995; Kaming, Paul O Olomolaiye, et al., 1997; Al-Khalil & Al-Ghafly, 1999; Odeh & Battaineh, 2002).
The Indian construction industry is facing a shortage of both skilled and unskilled labor (Venkatesh et al., 2012). The bulk of the workforce (82.45%) constitutes unskilled workers, 10% constitutes skilled workers and the rest by engineers, foremen, workers and staff (KPMG, 2013). Construction labor productivity (CLP) being one of the most important and flexible resources, it is used as a major performance indicator to evaluate the success and completion of a construction project. Hence, improving labor productivity is of great interest to practitioners (Abdul Kadir et al., 2005; Liu & Ballard 2008).
The actual status of CLP in the country or a region can be best estimated only if we know the state of affairs at the regional level. Until now, majority of the studies have been carried at the national level, whereas the disparities in CLP at the regional level have been generally neglected. As a result, the objective of this study is to assess and compare labor productivity factors at the regional level. In the present study, the researchers aim to determine the differences in the perceptions of the relative importance of the factors affecting CLP through interviews with government officials of Maharashtra and Arunachal Pradesh. Accordingly, the researchers focus on the perceptions of the government officials designated to supervise or overlook the construction activities in both the states rather than comparing the actual productivity differentials by using activity-based sampling techniques or the labor productivity data.
Construction Labor Productivity
It has been observed that there are notable differences in labor productivity across the majority of the countries and also at regional levels (Enflo & Hjertstrand, 2009). The patterns of labor productivity within industries, regions, and industries within regions show statistically significant differences. The contribution of each industry to each region is different, and the patterns have evolved with time (Webber & Horswell, 2009). Comparison of the CLP among the United States, United Kingdom and Jordan on the basis of standard baseline productivity data showed that differences existed due to differences in skill level and work methods of the labor (Sweis et al. 2011). Comparison of the changes in labor and partial factor productivity of construction labor in Canada and United States suggests that the growth of labor productivity has almost stagnated in the US while it is still growing in Canada, although in absolute terms, the CLP in Canada is still lower than in the US (Nasir et al., 2014). When the activity-based CLP is compared between the United States and China, significant gaps were found in equipment intensive construction activities, whereas there were smaller gaps in labor intensive construction activities (Shen et al. 2011). CLP of seven Indonesian regions shows differences on the basis of the output, working time, skills and motivation of artisans (Kaming et al, 2002). Labor productivity is thus seen to have variations with region.
Regional Variations in India
Productivity growth is seen to be higher in countries with sufficient and systematic provision of infrastructure services, thereby leading to the economic growth of the region (World Bank,1994). It is essential to understand the linkages of labor productivity and economic growth with the level of infrastructure development of a region. Increased spending and investment in infrastructure services improve the labor productivity of the region (Agenor, 2010). Unbalanced application of technology in construction is a major barrier to growth in improving CLP (Ma & Liu, 2018). Thus, in order to achieve economic development, it is imperative to provide infrastructure services to ensure that the demands of the business, families and users are adequately met (Srinivasu & Srinivasa, 2013). Reliability of infrastructure services is one of the major considerations in decisions related to investment by the private investors. It has been observed that as economic output grows, there is parallel growth in the infrastructure capacity also. Further, infrastructure is seen to have a significant positive influence on Foreign Direct Investment (FDI) in the Indian context (Mukherjee, 2011). As infrastructure development impacts labor productivity, it is used as an assessment tool to select the states in India for the comparison of CLP. The extent of infrastructure development and its quality is used as the criterion to select the states of India for this comparative study. The review of the extent and quality of infrastructure has been limited to the traditional infrastructure sectors such as roads, railways, airports, and seaports.
Analysis of the data based on the above- mentioned criteria shows that significant differences exist across the Indian states in terms of the extent of road and rails infrastructure. As evident from Table 1, Maharashtra and Arunachal Pradesh seem to lie fairly on the opposite sides of the spectrum of the considered criteria. In addition, the cumulative FDI equity inflows from January 2000 to December 2017 at the Mumbai region (covering Maharashtra, Dadra & Nagar Haveli, and Daman & Diu) and Guwahati region (covering Assam, Arunachal Pradesh, Manipur, Meghalaya, Mizoram, Nagaland, and Tripura) are US $ 114047.05 million and US $ 103.81 million respectively. While the Mumbai region contributed 30.93%, the Guwahati region had a share of only 0.03% of the total FDI inflows in the stipulated period, and this goes to show the vast differences in the investments made in both the regions. Compared to the ten airports in Maharashtra with the Mumbai airport itself handling 31.98 million domestic passengers (as of February 2019), commercial flights have recently started in Arunachal Pradesh from 2018 (India Brand Equity Foundation, 2019a). With no direct connectivity to the sea or the ocean, opportunities are being searched to utilize the perennial rivers in Arunachal Pradesh for inland water transport and boost the local economy. On the other hand, the two major ports, namely Mumbai Port Trust and Jawaharlal Nehru Port Trust in Maharashtra collectively handled traffic of 131.29 million tons during 201819 (India Brand Equity Foundation, 2019b). States like Maharashtra and Arunachal Pradesh, which are although parts of the same country have a vast variation in the utilization of infrastructure services for the local economy. It thus becomes necessary to have good quality infrastructure in attracting local and foreign investments to the region (Coughlin et al., 1991; Khadaroo & Seetanah, 2008). Taking into consideration the huge differences in Maharashtra and Arunachal Pradesh, it has been decided to compare the perspectives of government officials and see if similar observations are obtained in terms of the factors affecting CLP.
Construction Labor Productivity Factors
In order to determine the factors affecting CLP, an extensive search for relevant articles on CLP was carried out on the bibliographic database, Scopus. In order to ensure that all the credible papers are covered, the method adopted by (Al-sharif & Kaka, 2004; Ke et al., 2009; Lin et al., 2014; Yi & Chan, 2014; Darko & Chan, 2016) was followed. This method involved a three-stage review of the relevant literature.
For the first stage, the method of Yi and Chan (2014) was replicated to search for relevant papers in Scopus. Under the...
To continue reading
Request your trialCOPYRIGHT GALE, Cengage Learning. All rights reserved.
