Benefits Formulation in Construction Projects: An Exploratory Study through a Social Sustainability Perspective

Abstract

Extant project management literature suggests that project benefits management (PBM) can facilitate social sustainability (SS) through benefits formulation for a wider set of project stakeholders. However, empirical evidence regarding the actual extent of SS considerations in benefits formulation is lacking, especially from large developing economies like India. To fill this gap, a SS-centric analysis of PBM plans of 80 construction projects has been conducted using content analysis to identify the benefits targeted at the internal and external stakeholders, viz., workers and project-affected community. The analysis reveals much higher occurrences of benefits for the affected community compared to those relating to the workers. The project proponents have highlighted the social relevance of projects mostly through ‘trickle down benefits’ – that may possibly accrue to the affected communities due to project investment – as compared to ‘co-created benefits’ – that empower the affected communities but require a deeper understanding of their needs and aspirations. ‘Local employment’ and ‘local business and economic growth’ are the most common benefits across projects. Three areas of improvement have been suggested in the benefits formulation process from a SS perspective – mandating worker-specific benefits, more focus on co-created benefits and specifying numeric measures of benefits along with timelines, to facilitate assessment of actual benefits realization during project implementation and operation phases. This study contributes to research literature on sustainable project management. Its findings offer useful implications for researchers, policymakers and project proponent organizations.

Keywords

Benefits management benefits formulation benefits realization construction project management social sustainability India

Introduction

Project benefits management (PBM) originated in the late 1980s in the context of information technology projects against the project proponents’ concerns about not realizing the planned benefits (Breese, Jenner, Serra, & Thorp, 2015). Since then, PBM has been accepted as a critical area for value creation by aligning project outcomes with organizational strategy. The benefits have been defined as ‘the flows of value that arise from a project’ (Zwikael & Smyrk 2012, p. 11) or the ‘outcome of change which is perceived as positive by a stakeholder’ (Bradley, 2006, p.18). PBM starts with benefits formulation for the identified beneficiaries and fixing responsibilities for realizing these benefits (Chih & Zwikael, 2015). Project success is assessed based on the extent of benefits actually realized (Zwikael, 2016). Benefits formulation under PBM has traditionally focused on value creation for the project proponent organizations and delivery of project outcomes to the intended beneficiaries/end-users. However, of late, such organizations are being increasingly challenged to distribute benefits among a wider set of stakeholders and thus contribute to sustainable development (Keeys & Huemann, 2017a). Among the social, environmental and economic dimensions that constitute sustainable development, PBM has specific relevance to social sustainability (SS), which concerns the ‘people’. PBM can facilitate SS of the project and that of the project outcome by considering the welfare of a wider group of project stakeholders who are directly or indirectly affected by the project (Keeys & Huemann, 2017b). Emphasizing the need to consider social interest in benefits formulation, Esteves, Factor, Vanclay, Götzmann, & Moreira (2017) have stated that ‘Communities can feel cheated when the benefits they expected to receive from a project are not received. […] leading to further loss of trust, production delays, and increased staff time in dealing with conflict’.

The possibilities of benefitting a wider set of a stakeholders are specially present in construction projects (Zuo, Jin, & Flynn, 2012) as their impact on the ‘local economic development, social progress and environmental changes is profound and usually irreversible’ (Zeng, Ma, Lin, Zeng, & Tam, 2015). Construction projects are also one of the largest sources of employment for the unskilled labour worldwide, employing millions of poor and disadvantaged people, especially in the developing economies (ILO, 2001, 2009). Therefore, it is argued that SS-centric benefits formulation in construction projects can benefit organizations as well as other project stakeholders by legitimizing the welfare concerns of the weaker stakeholders and their entitlement to the projects’ benefits (Bonham, Chrysostomidis, Crombie, Burt, van Greco, & Lee, 2016; Franks & Vanclay, 2013; Xia, Qiang, Chen, Fan, Jiang, & An, 2018). Such possibilities are increasing in large developing economies where growth in construction output is affecting millions of poor and disadvantaged people either directly (by way of displacement) or indirectly (affecting the sources of livelihood) (Keeys & Huemann, 2017b; Padel, 2016; Vandycke, 2012; World Bank, 2006). Taken together the extant literature suggests project benefits formulation as a means of SS of and by the project. However, there is a lack of empirical evidence regarding the extent of SS consideration in benefits formulation in the developing economies, where the weaker stakeholders have a ‘historical legacy of disadvantage’ (Franks & Vanclay, 2013, p. 44). This study aims to bridge the gap through a systematic analysis of PBM plan for public construction projects in India, one of the fastest growing developing economies. The scope of the study has been restricted to public projects since a majority of infrastructure and industrial projects in India are undertaken by public authorities and the data regarding projects’ proposed benefits are publicly available. As described later, the proposed benefits have been identified from the environmental impact assessment (EIA) reports obtained from the online database of the Ministry of Environment, Forest and Climate Change (MOEFCC), Government of India. As per the prevailing environmental regulations in India (MOEFCC, 2006), the EIA reports mention the potential negative impacts on the ‘socioeconomic environment’ – concerning the ‘people’ affected by the project – along with the PBM plan containing the proposed benefits for various stakeholders. This regulatory practice is in line with the global policies (e.g., UNDP, 2015) and research, suggesting that impact assessments should be conducted in a manner ‘so that the project-affected people benefit from the development process and do not end up as losers, impoverished forever’ (Mathur, 2016, p. xxv).

Theoretical background

Project benefits management

PMI (2017, p. 33) defines project benefit as ‘an outcome of actions, behaviors, products, services, or results that provide value to the sponsoring organization as well as to the project’s intended beneficiaries’. It also suggests that apart from managing the ‘iron triangle’, viz. time, cost and scope/quality, the project benefits also need to be managed through a formal PBM plan. Recent project management research literature differentiates the success of projects from that of project management. Researchers have emphasized PBM through case studies wherein despite meeting the iron triangle, the projects were deemed unsuccessful for failing to provide the formulated benefits (Chih & Zwikael, 2015; Dupont & Eskerod, 2016; Serra & Kunc, 2015; Zwikael, Meredith, & Smyrk, 2019). Importance of PBM surpasses the project level as it seeks to create ‘strategic value for the businesses […] to support the successful execution of business strategies’ (Serra & Kunc, 2015, p. 53). Accordingly, researchers have called to move from ‘traditional output-focused project management approach’ to ‘benefit-oriented project management’ (Chih & Zwikael, 2015, p. 353) by identifying, in early project phases, the intended beneficiaries and corresponding benefits along with the timelines and accountabilities for benefits realization (Breese, 2012; PMI, 2017; Zwikael et al., 2019).

Social Sustainability and PBM

Project-based and project-oriented organizations that realize value creation and change through projects are increasingly facing the challenge of mainstreaming societal welfare in their policies and practices through explicit attention to SS (Silvius, 2017; Walker & Lloyd-Walker, 2019). The normative and instrumental determinants of this requirement include increase in public awareness, end-user demands, government regulations, attempts to espouse a positive corporate image and avoidance of public opposition (Goel, Ganesh, & Kaur, 2019a). SS requires explicit attention to the needs and well-being of various internal and external project stakeholders, especially those who belong to the weaker or disadvantaged sections (Montalbán-Domingo, García-Segura, Sanz, & Pellicer, 2018a; Zuo et al., 2012).

The requirement of considering societal welfare through projects has enlarged the scope of PBM by way of redefining the ‘intended beneficiaries’. Traditionally, these beneficiaries are the ‘primary stakeholders, project owners, suppliers, contractors and customers’ (Keeys & Huemann, 2017b, p. 1201). But SS considerations necessitate ‘identifying and formulating benefits for broad groups of stakeholders’ by engaging with them and determining what holds value to them (Keeys & Huemann, 2017b, p. 1200). In essence, the literature advocating SS concerns in PBM argues that the ‘project stakeholders who receive large benefits from […] projects have an obligation to share those benefits with people who suffer as a result of the projects’ (Xia et al., 2018, p. 342). The literature also points to two such sets of stakeholders, viz. the workers and the project affected community, who face numerous negative impacts of construction projects, particularly in the developing economies, and therefore need to be considered in the benefits formulation for ensuring SS (Franks & Vanclay, 2013; Mathur, 2016; Venter & Leong, 2018; Xia et al., 2018).

In India, the workers and affected community have a legacy of bearing the negative impacts of construction projects. On the one hand, workers have been subjected to exploitation with unsafe working conditions, unfair wages and gender discrimination (Goel, Ganesh, & Kaur, 2019b; Loganathan & Kalidindi, 2016; Wuttke & Vilks, 2014); on the other, the ‘development projects in the last 60 years or so are estimated to have displaced over 60 million people, some of them more than once, reducing most of them to a state of permanent poverty’(Mathur, 2016, p. 1). As per the report from the Planning Commission of India (PCI, 2013), 83 per cent of construction workers are unskilled and mostly comprise poor migrants who work at construction sites during lean agricultural seasons. They belong to the ‘unorganized sector’ and are temporarily employed by intermediaries or labour contractors without formal employment contracts (Gupta, Hasan, Jain, & Jha, 2018). This apathy has led to high labour absenteeism and turnover (Loganathan & Kalidindi, 2016). Similarly, the project-affected community has also borne the negative impacts, at the same time not getting adequate benefits from the projects. Rajaram and Das (2006, p. 123) suggest that ‘the benefits of development are mostly cornered by those who are able to manipulate the social and political system or by the urban middle classes’. Unequal benefit distribution has been a ‘common source of dissatisfaction’ among the affected community (Diduck, Pratap, Sinclair, & Deane, 2013, p. 173) leading to public opposition and protests against construction projects in India. Similar observations have been made by many other authors too (e.g., Choudhury, 2014; Diduck, Sinclair, Pratap, & Hostetler, 2007; Rathi, 2017). Yet, these studies have focussed on the broader EIA process for construction projects in India and do not present any systematic analysis of the projects’ benefits formulation.

Against this background, this exploratory study seeks to present empirical evidence regarding benefits formulation in public construction projects in India from a SS perspective. This study is the first such attempt and its findings can be useful for policymakers and practitioners, especially the project proponents, regarding possible areas of improvement for making construction projects and their outcomes socially sustainable. To meet the broader aim of this research, following three specific objectives have been formulated:

To assess the PBM plan of public construction projects from the perspective of SS-centric benefits formulation.

To identify specific benefits for the internal stakeholders viz. the workers and the external stakeholders, viz. the project affected community, and,

To investigate potential relationships between the SS-centric stakeholder benefits and project characteristics.

Methodology

In this research, benefits formulation in construction projects has been studied through content analysis (CA). CA ‘is a systematic, replicable technique for compressing many words of text into fewer content categories based on explicit rules of coding (Lu, Ye, Flanagan, & Ye., 2015, p. 4). It has been commonly used to evaluate sustainability considerations in a variety of published documents (e.g., Goel et al., 2019b; Lu et al., 2015; Montalbán-Domingo, García-Segura, Sanz, & Pellicer, 2018b). CA provides more realistic assessment of clients’ ‘perceptions and real practices’ as compared to opinion-based methods like questionnaire survey and interviews (Xia, Skimore & Zuo, 2012). Additionally, for sensitive topics like sustainability, the secondary empirical sources used in CA provide ‘unobtrusive access […] and may reduce distortion due to imperfect recall and social desirability bias’ (Harris, 2001, p. 201). CA is suited for both qualitative and quantitative approaches. The former emphasizes unravelling the meaning of data through coding text into various categories and the latter is based on the frequency of occurrences of text segments in each of the categories (Xia, Skitmore & Zuo, 2012). In this study the quantitative approach to CA has been adopted to meet the research objectives. While there ‘is no simple right way to do content analysis’ (Weber, 1990, p. 13), it is generally accepted that CA follows sequential steps as shown in Figure 1 (Goel et al., 2019b; Harris, 2001; Lu et al., 2015; Xia et al., 2012). Following Mariano and Walter (2015), and as described later, results of the CA are complemented with a qualitative assesment by developing text-clusters using the ‘VOSviewer’ text analysis software.

Figure 1.

Source: The authors.

After finalization of the research questions/objectives, one of the first important decisions in CA is to decide the unit of analysis. It is ‘the size or type of response to be counted in the analysis’ (Harris, 2001). It may range from a word to a complete document and is suitably selected by the analyst to meet the research objectives. Here, as the objective was to identify and assess SS considerations in PBM plans and not to count the occurrence of any specific words, a phrase – varying from one word to complete sentences – was chosen as the unit of analysis.

The ‘material’ or the text to be studied through CA in this study was mostly obtained from the environmental clearance portal¹ of MOEFCC – a publicly accessible portal through which project proponents (the ‘clients’) submit requisite documents (including the EIA reports) to obtain environmental clearance. As the portal did not provide a separate sampling frame for all public construction projects, a random sampling of the reports was not possible and therefore a non-random sample was obtained. This method was also deemed appropriate to ensure broader coverage in terms of the nature of work, project value, project clients and projects’ geographical spread across India.

The portal classified the projects under the following seven categories: industrial, building and townships, infrastructure, thermal power plants, coal and non-coal mining, river valley and hydroelectric and coastal regulatory zone. To collect the reports, the first author began with the latest available reports (as of 30 June 2019) for each category and then proceeded backwards in date while excluding privately funded, mining and coastal zone projects. The process was continued till a sizable sample of 80 project reports was obtained from various categories.

A coding schema was developed before coding of the source documents (Krippendorff, 2004). It improves consistency of the coding process by ensuring that different coders ‘code the same text in the same way’ (Weber, 1990, p. 12). Table 1 represents the schema – developed iteratively from the extant literature as well from the EIA reports – that served as the protocol for the coding process. It consists of 13 subcategories representing the potential benefits, spread across internal and external project stakeholders. The benefits specific to the external stakeholders are divided into two categories, viz. trickle down benefits (TDBs) and co-created benefits (CCBs). TDBs are the benefits resulting ‘from any increase in economic activity’ (Harding, 1991, p. 303) which, in the case of construction projects, is attributable to project investment (Vandycke, 2012). Worldwide experiences characterize TDBs as uncertain as they manifest in ways such as local employment and local business and economic growth that are generally much lower than expected, albeit rarely measured (Persky, Daniel, & Virgina. 2004; Vandycke, 2012). CCBs are the benefits formulated after engaging with the stakeholders to identify their needs and their perception of what holds value to them (Keeys & Huemann, 2017a, b). Four subcategories (CCB₁ to CCB₄) of CCBs are identified. In addition to the benefits, important project characteristics, which could possibly influence the inclusion of SS-centric benefits in the reports, were also identified from the literature. These characteristics included (a) project type: building, infrastructure, and industrial projects (Montalbán-Domingo et al., 2018b; Sanz-Calcedo et al., 2015), (b) project size (based on estimated cost specified in the reports): small (<$100M), large (≥$100M to ≤ $1000M) and mega (> $1000M) (Montalbán-Domingo et al., 2018; Xia et al., 2012). Further, to check for any temporal patterns in benefits formulation, the year of the report was also included as a project characteristic and the reports were put into one of the three categories: 2007–2010, 2011–2014 and 2015–2019.

Table 1.

Coding Schema for Content Analysis

Stakeholder	Codes	Categories	Sub-codes	Subcategories	Broad Description	Literature
Internal (Workers)	WB	Worker benefits	WB₁	Fair wages	Providing wages equal to or above the minimum wages	Goel et al. (2019b); Loganathan & Kalidindi (2016)
			WB₂	Skill building	Providing skill building training	Esteves et al. (2017); Franks & Vanclay (2013)
			WB₃	Gender equality and encouraging female workers	Encouraging female participation and providing them equal wages	Baruah (2010); Goel et al. (2019b); Vandycke (2012)
			WB₄^a	Education for workers’ children	Providing facilities for educating workers’ children	–
External (Project affected community)	TDBs	Trickle down benefits	TDB₁	Local employment	Providing employment to affected community	Bonham et al. (2016); Esteves et al. (2017); Franks & Vanclay (2013)
			TDB₂	Local procurement	Procuring materials, products from local markets	Bonham et al. (2016); Esteves et al. 2017)
			TDB₃	Local business and economic growth	Local economic growth due to project investment	Bonham et al. (2016)
			TDB₄	Local land and property appreciation	Increase in land and property value due to project investment	Venter & Leong (2018)
			TDB₅	Local de-congestion and cleaner environment	De-congestion due to project outcome and thereby reduced pollution and cleaner environment	Venter & Leong (2018)
	CCBs	Co-created benefits	CCB₁	Community-centric social and physical infrastructure	Developing infrastructure to serve the affected community	Wang, Lassoie, Dong, & Morreale (2013); Xia et al. (2018)
			CCB₂	Community capacity building	Capacity building training to the affected community to improve avenues for livelihood	Bonham et al. (2016); Franks & Vanclay (2013)
			CCB₃	Emancipation of women, vulnerable or disadvantaged sections	Benefits formulation specifically for the women and vulnerable or disadvantaged sections	Esteves et al. (2017); Franks & Vanclay (2013); Xia et al.(2018)
			CCB₄	Promotion of local culture	Promoting local culture through project and its output	Esteves et al. (2017); Goel et al. (2019b)

Source: The authors.

Note: ^a identified from the reports.

Each of the 80 reports was carefully read and the relevant text segments (phrases) were manually coded to the categories of the coding schema. Following Lu et al. (2015) for manual coding, a MS Excel sheet was created for the coding process. If a report contained a SS-centric benefit, it was marked ‘Yes’ in the excel sheet under the corresponding category and subcategory, else it was marked ‘No’. This process was continued for all 80 projects and the 13 indicators of the SS-centric benefits, and it resulted in the development of a large, 80 × 13 matrix. Examples of the coded text phrases are presented in Appendix 1.

The coding process may involve subjective judgement in assigning text segments to categories. Therefore, measures to ensure consistency of this process are required. For this purpose, we followed Lu et al. (2015) and used a second coder (here, the second author) to code the text segments independently and to produce a second MS-Excel sheet with the 80 × 13 matrix. Both sheets were then compared row-by-row and any inconsistencies were mutually discussed and resolved. This discussion ensured allocation of the text segments to a single, most relevant category (and subcategory). For example, the authors discussed and agreed that the provisions related to skill building of the female members of the community affected by the project are allocated to category CCB₃ and not CCB₂. Lu et al. (2015) suggest this method of consistency checking as more exhaustive and therefore preferable to the traditional inter-rater reliability coefficients like Cohen’s kappa, which are often calculated by taking a random sample from the overall text corpus.

After finalization of the coding process, an occurrence-based quantitative assessment was performed by counting the frequency of ‘Yes’ and ‘No’ against each of the 13 subcategories. Thereafter, descriptive and inferential statistical analyses of the frequency data were conducted. The latter were performed to meet the third research objective of investigating potential relationships between inclusion of SS-centric benefits and the project characteristics. Chi-square (χ²) test, commonly used to explore potential relationships between categorical variables (Field, 2009), and often used in the quantitative CA (Montalbán-Domingo et al., 2018; Xia et al., 2012), has been used here for the statistical analysis

After the quantitative assessment, a qualitative assessment of the text segments was performed using VOSviewer, a freely accessible text analysis software that uses information from bibliographic databases or a text corpus to develop ‘term maps’ (Waltman, Van Eck, & Noyons, 2010). These maps contain text-clusters, with each cluster having a group of terms (or words) based on their co-occurrences in source text (Van Eck & Waltman, 2011). In this study, all the text phrases identified during the coding phase were collated into a MS-Word file which served as the source text corpus for developing the term maps. As described later, the authors used these maps to complement the quantitative assessment by relating the terms in each cluster to the frequency data of benefits across different categories.

Results and Discussion

Based on the process described earlier, impact assessment reports for 80 projects were collected and systematically analysed. These projects – from 65 different government organizations – were spread across 19 states in India and collectively had an estimated value of $62 billion.² Figure 2 presents the distribution of reports in terms of project characteristics and the year.

Figure 2.

Source: The authors.

Table 2 presents a descriptive analysis of the SS-centric benefits based on the manual coding process. On an aggregate level, this data indicates that in line with global practices the impact assessment process in India is being directed towards societal welfare by formulating benefits targeted at the affected community and the workers. At the same time, the data illustrates that the benefits formulation has focussed much more on the affected community compared to the workers: 99 per cent of the projects had at least one benefit for the former while only 14 per cent projects had the same for the latter.

Table 2.

Descriptive Data for the Project Benefits

Categories	Sub-codes	Subcategories	Projects with SS-centric benefits (numbers)	Projects with SS-centric benefits (frequency)
Worker benefits	WB₁	Fair wages	4	5%
	WB₂	Skill building	4	5%
	WB₃	Gender equality and encouraging female workers	7	9%
	WB₄	Education for workers’ children	3	4%
Trickle down benefits	TDB₁	Local employment	79	99%
	TDB₂	Local procurement	11	14%
	TDB₃	Local business and economic growth	59	74%
	TDB₄	Local land and property appreciation	11	14%
	TDB⁵	Local de-congestion and cleaner environment	28	35%
Co-created benefits	CCB₁	community-centric social and physical infrastructure	41	51%
	CCB₂	Community capacity building	31	39%
	CCB₃	Emancipation of women, vulnerable or disadvantaged sections	29	36%
	CCB₄	Promotion of local culture	14	18%

Source: The authors.

The results (Table 2) also show higher occurrences of TDBs as compared to CCBs. Two of the most common community benefits are also TDBs (TDB₁: 99%, TDB₃: 74%). Literature suggests that TDBs are uncertain and are ‘often highlighted and invariably overstated’ (Persky et al., 2004, p. 128). Experiences from World Bank financed projects also suggest that ‘results of any trickle down have been slow […] the poverty impact of sector-based interventions has also proved complex to achieve and demonstrate’ (Vandycke, 2012, p. 13). Here also a majority of the reports contained indications regarding the temporary or short-term nature of the TDBs. For example TDB₁ has been mentioned in almost all projects but with caveats regarding temporary employment, mostly during the construction phase and that too predominantly for the unskilled labour (see the representative text segments in Appendix 1). Considering these shortcoming of TDBs, the World bank (Vandycke, 2012, World Bank, 2006) as well recent research literature (e.g., Keeys & Huemann, 2017a, 2017b) recommend CCBs, which are formulated after identifying communities’ needs and aspirations by engaging with them. In the present study, CCBs were found to be largely neglected and the most frequent benefit (CCB₁) was mentioned only in 51 per cent projects. Considering the early evidences that CCBs provide long term societal welfare, thus improving the affected communities’ quality of life (Bonham et al., 2016; Franks & Vanclay, 2013; Xia et al., 2018), there is a scope to improve benefits formulation process in India by focusing more on CCBs. For example, Xia et al. (2018, p. 50) reported that through a benefitsharing CCB, communities can become ‘true beneficiaries of the project rather than “compensation receivers,” and their attitudes towards the projects are likely to become more positive’.

To support the inferences drawn through occurrence-based quantitative CA, a qualitative assessment of the text corpus was performed using VOSviewer that produced ‘term maps’ containing text-clusters using the compiled text segments from all 80 reports. The authors decided to develop the term maps only for the text corpus corresponding to community-centric benefits, leaving the worker benefits out as the latter had extremely low occurrences with insufficient text corpus to produce rich text-clusters. As the sizes of the clusters reflect the number of co-occurring terms, it was expected that the terms from categories that had a higher frequency of benefits in the CA would be a part of such large clusters. The authors attempted to map each of the text-clusters to the categories in the coding schema (Table 1) by reading through the co-occurring terms.

Figure 3 presents the term map from the text corpus having all text segments corresponding to TDBs from the 80 projects. It shows three text-clusters, each in a different colour, with red and green clusters being the largest two in terms of the number of co-occurring terms. The largest cluster (red) – having co-occurring terms like ‘job’, ‘employment’, ‘employment opportunity’, ‘local person’, ‘local population’, ‘construction activity’, ‘operation phase’ – could be clearly related to the subcategory with the highest frequency (TDB₁: 99%) after reading through the text segments (see Appendix 1). Similarly, the green cluster with terms like ‘business’, ‘economy’, ‘growth’, ‘increase’, ‘demand’, ‘tourism’, ‘positive impact’, etc. was mapped to the second most common TDB (TDB₃: 74%). The last cluster (blue) was mapped to the third most common TDB (TDB₅: 35%) which had terms like ‘congestion’, ‘noise pollution’, ‘reduction’, ‘quality’, ‘improvement’, used in the text segments to denote corresponding benefits of the project to the local community. Notably, the red and green clusters, mapped to TDB₁ and TDB₃ respectively, were located closer in the term map (Figure 3), which indicates ‘relatedness’ (Van Eck & Waltman, 2011) of the terms contained in these clusters. This seems plausible considering that increased employment in the affected community may contribute to the local economic growth due to increased spending by the community members (Persky et al., 2004).

Figure 3.

Source: The authors.

Figure 4 presents the term map for all text segments corresponding to the CCBs. It consists of three text-clusters in red, green and blue. The largest of them (red) was mapped to subcategory CCB₁ (51%) due to terms like ‘need’, ‘support’, ‘construction’, ‘school’, ‘toilet’, ‘drinking water’ and ‘water supply’. In the text segments corresponding to CCB₁ (refer Appendix 1), these terms have been used in the context of developing social and economic infrastructure for the community. The green and blue clusters contained terms which could be related to CCB₂ (e.g., ‘improvement’, ‘quality’, ‘life’, ‘training’, ‘self-employment’, ‘income’) and CCB₃ (e.g., ‘women’, ‘employment’, ‘skill’, ‘assistance’, ‘vocational training’) respectively.

Figure 4.

Source: The authors.

Overall, both the term maps (for TDBs and CCBs) agreed with the results of quantitative CA with the cluster sizes reflecting a similar pattern as the frequency count of various categories (Table 2). Further, the term maps did not have any text-cluster that could be mapped to TDB₂, TDB₄ and CCB₄. This also agrees with the CA findings as these categories had very low occurrence across the projects. Therefore, the terms corresponding to these categories were not among the top 60 per cent of the co-occurring terms that are included in the term maps by the default algorithm of the software, excluding the bottom 40 per cent.

To check if the identified benefits in the reports were linked to the project characteristics, each benefit’s occurrence was tabulated for various project characteristics and a series of Chi-square (χ²) analyses were performed. Considering the extremely low frequency count of the benefits against the category ‘worker benefits’ and its four constituent subcategories (WB₁ to WB₄), the authors decided to perform statistical analysis only for the categories pertaining to the project affected community. Tables 3 and 4 present the result of the Chi-square (χ2) test for TDBs and CCBs respectively.

It is found that the TDBs have significant relationship with the project type and size but not with the year in which the impact assessment was carried out (Table 3). Infrastructure projects are found to have much higher occurrence of TDBs in comparison to building or industrial projects. This could be attributed to the larger size of infrastructure projects, both in terms of the projects’ ground footprint and value (Vandycke, 2012). In this study also 80 per cent of the infrastructure projects were either large (≥$100M to ≤ $1000M) or Mega projects (>$1000 M). This argument is also supported by a significant relationship between project size and the TDBs, and also by much higher occurrence of TDBs in ‘Large’ and ‘Mega’ projects as compared to small projects (Table 3). It also agrees with the worldwide experiences that large infrastructure projects supposedly produce multiple TDBs (e.g., employment creation), albeit the actual impacts have been found to be much lower (World Bank, 2006; Vandycke, 2012).

Table 3.

Chi-Square Test for Project Characteristics and the Occurrences of TDBs

Benefits → Project Characteristic ↓	No. of projects	TDB₁	TDB₂	TDB₃	TDB₄	TDB₅	Total	χ²
a) Project type								9.969 (p = 0.007^*, d.f. = 2)
Infrastructure	44	7	37	8	23	44	119 (54)
Buildings	2	0	10	1	0	11	22 (37)
Industrial	24	4	12	2	5	24	47 (39)
c) Project Size								6.068 (p = 0.048^*, d.f. = 2)
Small (< $ 100M)	27	26	1	14	4	7	52 (39)
Large (≥$100M to ≤ $1000M)	36	36	8	32	5	13	94 (52)
Mega (> $1000 M)	17	17	2	13	2	8	42 (49)
d) Year								3.803 (p = 0.149, d.f. = 2)
2007–2010	9	8	0	3	1	3	15 (33)
2011–2014	21	21	2	13	5	10	51 (49)
2015–2019	50	50	9	43	5	15	122 (49)

Source: The authors.

Notes: * indicates significance, at level of significance, α = 0.05. figures in parenthesis indicate the frequency of occurrence.

For the CCBs, the statistical analysis found that occurrences of benefits had a significant relationship with the project type but not with either the project size or the year of the reports (Table 4). Unlike TDBs in infrastructure projects, the industrial projects were found to have the highest occurrences of CCBs. This was despite the much smaller size of industrial projects as compared to the infrastructure projects. Against 52 per cent and 27 per cent of infrastructure projects, only 33 per cent and 8 per cent industrial projects were large and mega projects respectively. The higher occurrence of CCBs in industrial projects could be attributed to their peculiar nature wherein raw material inputs (e.g., iron ore) are processed in a useful output (e.g., iron) through a complex and resource-intensive process during which a ‘large amount of energy is used […], and significant amounts of waste are generated, which can be harmful and dangerous’ (Yun & Jung, 2017, p. 4). Consequently, industrial projects face more public resistance, fuelled by the ‘not in my backyard’ syndrome (He, Chen, Zhang, & Lu, 2018). This necessitates increased community engagement and continued co-creation of benefits during the operation phase for mitigating the social risks (Blood, 2013). On the other hand, a similar risk is not generally associated with either infrastructure or building projects (Yun & Jung, 2017).

Table 4.

Chi-Square Test for Project Characteristics and the Occurrences of CCBs

Benefits → Project Characteristic ↓	No. of projects	CCB₁	CCB₂	CCB₃	CCB₄	Total	χ²
a) Project type							8.064 (p = 0.018^*, d.f. = 2)
Infrastructure	44	24	14	14	10	62 (35)
Buildings	12	4	3	3	0	10 (21)
Industrial	24	13	14	12	4	43 (45)
c) Project Size							1.051 (p = 0.591, d.f. = 2)
Small (< $ 100M)	27	13	11	9	2	35 (32)
Large (≥$100M to ≤ $1000M)	36	19	13	15	6	53 (37)
Mega (> $1000 M)	17	9	7	5	6	27 (40)
d) Year							5.07 (p = 0.079, d.f. = 2)
2007–2010	9	2	2	2	1	7 (19)
2011–2014	21	11	6	6	7	30 (36)
2015–2019	50	28	23	21	6	78 (39)

Source: The authors.

Notes: * indicates significance, at level of significance α = 0.05, figures in parenthesis indicate frequency of occurrence.

The analysis also reveals that unlike TDBs, project size has no significant relationship with the occurrences of CCBs. It indicates that even for large and mega projects, no special attention is being paid to share the projects’ benefits with the affected community and the clients rely only on TDBs to demonstrate social relevance of the respective projects. This finding, coupled with the negligible occurrence of worker benefits (Table 2), points to the need of mandatory formulation of CCBs and worker benefits in the impact assessment phase, especially for the large and mega projects. Further, similar to TDBs, the analysis found that occurrence of CCBs had no significant association with the year of the assessment reports. Therefore, it can be argued that the benefit formulation practices for both TDBs and CCBs have not undergone any significant change in the duration corresponding to the reports, viz. 2007 to 2019, and they could be significantly improved by taking cognizance of worldwide experiences (e.g., Frank & Vanclay, 2013).

Conclusion

There is a lack of empirical evidence regarding the extent to which SS considerations are incorporated in the construction project benefits formulation, especially from the developing economies where SS-centric benefits can uplift millions of vulnerable and disadvantaged project stakeholders. Accordingly, a SS-centric analysis of the project benefits formulation has been conducted here through quantitative CA of PBM plans for 80 public construction projects in India. Using CA, various benefits targeted at the external stakeholders, viz. the project affected community and the internal stakeholders, viz. the workers have been identified. The analysis reveals a much higher occurrences of community focussed benefits compared to those related to the workers with 99 per cent of the projects having at least one benefit for the former and only 14 per cent projects having the same for the latter. The authors conjecture that more attention towards the affected community is an instrumental response to avoid social risks. The community-centric benefits have been further categorized into TDBs and CCBs and the former are found to be more common across all projects. Overall, local employment (TDB₁: 99%), local business and economic growth (TDB₃: 74%) and community-centric social and physical infrastructure (CCB₁: 51%) were the top three benefits. To complement these findings, a qualitative assessment of text was also performed by developing term maps, which broadly agreed with the occurrence-based findings. TDBs were found to have a significant relationship with the project type and size while CCBs were associated only with the project type. Infrastructure projects had the highest occurrence of TDBs, primarily due to their larger size that entails much higher TDBs like employment creation. Yet, as the literature suggests, such TDBs may be temporary and may last only during the construction phase. Industrial projects had the highest occurrence of CCBs despite smaller project sizes as compared to infrastructure projects. The authors have argued it to be an organizational strategy for controlling social risks against industrial projects, which are mostly energy intensive and produce hazardous waste and/or impacts.

The findings have multiple theoretical and managerial implications. They can be supplemented through case studies or interviews of industry participants to build a theory regarding SS-centric benefits formulation in construction projects. Further, the benefits formulation, studied here as a nominal variable (‘Yes’ or ‘No’) could be further extended by weighing the proposed benefits based on their desirability by the target stakeholder(s). For practitioners, there are three key implications. First, the findings illustrate a clear need to orient the project benefits to the workers, found largely neglected in this study. This could not only improve quality of life of some of the weakest sections of society but also contribute to meeting skilled labour requirement, and result in higher labour productivity. Second, the project proponents need to focus more on CCBs than TDBs as the latter’s actual impact may be temporary and below expectation. In contrast, CCBs empower the communities and improve quality of life in the short- and long terms. Third, the regulatory agencies could improve the EIA regulations in India by mandating specification of numeric measures of each benefit and timelines of benefits realization. This would facilitate monitoring and assessment of actual benefits realization during subsequent project phases.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Notes

Representative Text Segments and the Coded Categories

Project Number	Representative Text Segments	Category	Subcategory
P–39, P–40	Contractors would be required to abide by the labour laws regarding standards on employee working conditions, minimum wages for workers, safety and welfare measures. Conditions of employment would address issues like minimum wages.	WB	WB₁
P–77	Welfare and wellbeing of all workers, including the social security for agricultural and unorganized labour, minimum wages enforcement.
P–41	Conditions of employment would address issues like minimum wages and medical care for the workers.
P–21	As laid down in the policy the contractor shall identify peer educators (1 for every 100 workers) and refer them for professional training to the Employers’ appointed agency for the purpose.		WB₂
P–41	Provide regular basis training program to the labours working on project site.
P–21	Provisions will be made to enhance the female employment opportunities by encouraging female workers to participate even in the construction activities.		WB₃
P–48	Contractors should engage a woman Inspector of Works not below the rank of a Senior Engineer to inspect the construction camps and any other component of work with respect to gender issues.
P–24	The construction workers are mainly mobile groups of people. They are found to move from one place to another taking along their families with them. Thus, there is a need for educating their children at the place of their work. Day crèche facilities will be extended with primary educational facilities.		WB₄
P–42	The construction workers are mainly mobile groups of people. They are found to move from one place to another taking along their families with them. Thus, there is a need for educating their children at the place of their work. For this at least primary schools are required to be planned in the construction camps. Wherever feasible, day crèche facilities could be extended with primary educational facilities.
P–6	The construction phase would lead to generation of temporary employment opportunities and would temporarily increase the income levels of the local popula- tion. Affected Family shall be given preference in employment opportunities in [project name]. This is subject to the availability of vacancies, suitability of the affected person for the employment and other requirement for employment being at par with other candidates.	TDBs	TDB₁
P–13	The proposed project will generate direct and indirect employment opportunities for the local people. The port will create employment for skilled as well as semi-skilled workers directly or indirectly.
P-14	The proposed activities expected to generate direct and indirect employment, as contract laborers will be employed during the construction phase, transportation involving supply of materials and auxiliary and ancillary works as short term, while during operating stage at long term.
P–6	Local businessmen will get opportunity to supply construction materials.		TDB₂
P–26	Some of the construction materials like stone chips & sand will be procured locally.
P–32	The construction materials like stone chips and sand will be procured locally from Identified quarry sites. The other important materials like cement, steel will be procured through various local sources.
P–32	The Infrastructure development shall Induce new establishment and construction of Commercial, Industrial and Residential structure as Hotel, Dhabas, Motel, Restaurant, petrol pumps that provide good business opportunity.		TDB₃
P–22	Development of infrastructure and availability of safe and fastest mode of transport in the isolated hilly terrain of [place name] as a result of the project realization would contribute towards better economic activities in the region as well as in the state and country. Improvement of airport due to the proposed project is likely to boast tourism in the area and revenue generation from the same.
P–37	The proposed airport will also attract industrial and infrastructure development in the region there by generating the additional revenue which will boost the economy.
P–59	The prices of the land are likely to increase with the coming up of the project. Hence the proposed project will have beneficial impact.		TDB₄
P–70	Land and property value will appreciably increase.
P–17	As the water quality of the main drains and that of the River [river name] improves, other intangible benefits include potential value enhancements of property located along the water ways.
P–48	The construction of new expressway will reduce the traffic congestion and wastage of fuel.		TDB₅
P–60	Due to the proposed bridge, traffic load on existing bridges will be reduced and smooth transportation will take place.
P–65	the traffic congestion due to obstructed movement of vehicles will be minimized and thus wastage of fuel and emissions from the vehicles will be reduced reducing air pollution.
P–12	As a part of the Corporate Social Responsibility (CSR) initiatives, it is envisaged to create health infrastructure in the form of primary health centre, which will be beneficial to the employees and also local people living in the region as their dependence on nearby towns and cities for quality medical treatment will be reduced.	CCBs	CCB₁
P–73	Construction or repair work of community halls, Panchayat Ghar, Health Centre, Anganwadi, School Building: Provision of Mobile Health Clinic and upgradation of available medical facilities. Free medical camps would be organized from time to time in project affected villages. Provision of mobile health clinic and upgradation of available medical facilities. Construction or repair work of school building and running useful education programmes.
P–76	It is proposed to upgrade the primary schools in 15 villages in the periphery of the affected villages. The following activities are proposed under LADP activities and to improve drinking water facilities in one primary school in 15 study area villages.
P–12	Implement skill development locally to improve employability of local population. Skill development centres for fisheries and container operation related logistic courses like ship/boat repair, net preparation; crane operations & repair, container freight management, truck terminal and related repair facilities /training.		CCB₂
P–13	Necessary training shall be imparted to local people for any specialized skill to the eligible for such employment in the project on a long-term basis, i.e. during operational and maintenance stages of the project and other tangible benefits like improved standards of living, health, education, etc.
P–24	Project executing agency may help in skill development of PAPs and make them suitable for the jobs taken. One of the strategies for economic sustenance of the PAPs is to help them improve their production level or to impart new skills or up-grade skills through training. As the project affected persons are dependent on livelihood primarily from agriculture, training is an important component of income restoration.
P–12	Development of Seafood Park in association of State Government for export- oriented value addition of marine resources with the aim of employment to women and the marginalised. The women folk of the area may be organized and capacitated to generate better employment opportunities.		CCB₃
P–24	capacity enhancing assistance will be provided that improve the access of women to skills training for off-farm employment such as tailoring and weaving, small goods shops; marketing – buying and selling local produce; processing of locally produced products, […]. Vocational training would be imparted to the women PAPs.
P–30	To take up programs that benefit the communities in and around its offices and results over a period of time, in enhancing the quality of life & economic wellbeing of the local populace, with special care and attention to the weaker section of the society. Imparting skill development and vocational courses, targeted at unemployed rural youth, particularly women and candidates from SC, ST, OBC & BPL families.
P–12	It is proposed to improve and renovate religious and Cultural Properties with landscaping and beautification of the structures.		CCB₄
P–22	The project will bring diverse cultural events and will lead to cultural uplift of the area. A provision of ₹ 5 lakhs has been provided in the estimate to maintain the cultural heritage/events and promote awareness, which should be appropriately utilised by cultural department of local administration.
P–30	Protection of Local historical and cultural artefacts and historical monuments, heritage sites etc • Promotion of local artisans, craftsman, musicians, artists and their art forms etc. for preservation of local heritage, art and culture.

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