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Community Religion, Employees, and the Social License to Operate

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Abstract

The World Bank recently noted: “Social license to operate has traditionally referred to the conduct of firms with regard to the impact on local communities and the environment, but the definition has expanded in recent years to include issues related to worker and human rights” (World Bank 2013, http://go.worldbank.org/FZ88VMOM90). In this paper, we examine a factor that can influence the kind of work conditions that can facilitate or obstruct a firm’s attempts to achieve the social license to operate (SLO). Specifically, we examine the empirical association between a company’s employee practices and the religiosity of its local community by investigating their fixed and endogenous effects. Using a large and extensive U.S. sample, we find a positive association between the “employee friendly” practices of a firm and the religiosity of the local community after controlling for several firm characteristics. In addition, after mitigating endogeneity with the dynamic panel system generalized method of moment and after employing several other econometric tests, we still find a robust positive association between the religiosity of the local community and employee-friendly practices. Since recent research has shown that the firm’s treatment of its stakeholders is a key to achieving an SLO, and since employees constitute a highly significant stakeholder group, we interpret our results as supporting the view that religion is an important influence on the kinds of employee practices that can increase the likelihood that a firm will acquire the SLO.

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Notes

  1. The term “social license to operate” was coined in 1997 by James Cooney, an executive with PlacerDome, a mining company, during a meeting with the World Bank. The World Bank subsequently adopted the term in its dealings with other mining companies and gave it wide currency (Boutilier et al. 2012).

  2. Social license exists outside formal regulatory processes, and there is ample evidence that a failure to gain and maintain this social license can lead to conflict, delays, or cost for the proponents of a project (Yates and Horvath 2013).

  3. The meaning of “religiosity” is contested (Stark 2001; Zinnbauer et al. 1997). Here, we adopt the definition of McDaniel and Burnett (1990) and define religiosity as the degree to which an individual or group adheres to a belief in God, accompanied by a commitment to follow principles believed to be set by God.

  4. The majority of the U.S. population—76 %—identifies itself as Christian according to the 2008 American Religious Identification Survey (ARIS) on which the Bureau of the Census relies for its own estimates of the U.S. religious demographics. (Kosmin and Keysar 2009). Of this religious majority, according to ARIS, 33 % are Catholic and the other 67 % are members of Protestant denominations including Baptist (20.8 %), Methodist (6.5 %), Lutheran (5 %), Presbyterian (2.8 %), Mormon (1.8 %), Episcopal (1.4 %), Church of Christ (1.2 %), Evangelical (1.2 %), Jehovah’s Witness (1.2 %), Assemblies of God (.6 %), Seventh Day Adventist (.6 %), United Church of Christ (.4 %), and “Unspecified” Christian(9.5 %) or “Unspecified” Pentecostal (3.2 %). In addition to those Americans who identified themselves to ARIS as members of a Christian denomination, 3.9 % stated that they were members of non-Christian religions (such as Jewish, 1.2 %, Muslim, .6 %, and Buddhist, .5 %) and 15 % state that they have no religion, while the remaining 5.2 % provided no response when asked about their religious affiliation. In his Gallup study, Newport (2011) reports numbers that are similar to those of ARIS. Newport (2011) reports that based on 327,244 interviews, 78 % of American adults identify with some form of Christian religion, including Protestant (52.5 %), Catholic (23.6 %), and Mormon (1.9 %). The remainder are adherents of Judaism (1.6 %), Islam (0.5 %), other non-Christian religions (2.4 %), atheist (15 %), and no response given (2.5 %).

  5. Popes were writing encyclicals long before the nineteenth century, of course, but the first encyclical to address social/economic issues was the 1891 encyclical The Condition of Labor. Other sources of CST besides the encyclicals include the teachings of Church Councils such as Vatican II, the addresses of the Popes, and official summaries such as the Compendium of the Social Doctrine of the Church.

  6. Based on a comprehensive dataset from the CSR wire news service, Griffin and Sun (2013) find that firms disclose less in locations with strong religious beliefs (high adherence) but disclose more in locations with more non-evangelicals (high affiliation).

  7. In our unreported tabulation of 503 counties, we found that Norfolk county, MA, has the highest percentage of Catholic adherents (55.2 %), and Winnebago county, IA, has the highest percentage of mainline Protestant adherents (67.7 %), while Jones county, MS, has the highest percentage of evangelical Protestant adherents (53.6 %). The tabulated results are available from the authors upon request.

  8. Since the religiosity indices are provided on a county-level basis, we match the datasets using the counties where the firms’ headquarters are located. However, since the COMPUSTAT dataset for the most part does not provide the counties where firms’ headquarters are located, we utilize their ZIP codes instead. But while the ZIP codes of the firms are provided in the COMPUSTAT database, the ARDA only provides county codes, i.e., FIPS. We therefore match the FIPS codes with the ZIP codes, which enables us to obtain our final sample set.

  9. Due to the cross-sectional and time-series combined panel structure of our data, we conduct the Hausman (1978) test to select between a fixed effects and a random effects model. The test suggests the use of the fixed effects modeling.

  10. In our untabulated results, we also employ the EMPREL net scores, i.e., EMPREL strength scores minus EMPREL concern scores, instead of EMPREL index, and find that the main results remain qualitatively the same. Furthermore, when we add the profitability measure of return on assets (ROA), our untabulated results remain qualitatively the same.

  11. These results are available from authors upon request.

  12. In our untabulated results, the correlations between demographic variables and other control variables of governance, political affiliations of a county’s residents, a regulatory variable, and whether a firm is located in an urban or rural area and whether it is a multinational firm are very high. As a result, when we included both demographic variables and other control variables, the multicollinearity problems become serious (variance inflation factor is higher than 10), and our empirical results become unstable and insignificant. In econometrics, the variance inflation factor(VIF) quantifies the severity of multicollinearity in the regression analysis. It provides an index that measures how much the variance (the square of the estimate’s standard deviation) of an estimated regression coefficient is increased because of collinearity. Because a VIF number larger than 10 indicates a serious multicollinearity problem (Greene 1993), we decide to include the demographic variables and other control variables separately in the subsequent analyses.

  13. The dynamic panel GMM model, in particular, enables us to estimate the employee relation scores (EMPREL) and religiosity association by dealing with (i) past EMPREL activities due to autocorrelation problem of EMPREL scores; (ii) fixed effects to account for the dynamic aspects of the EMPREL–religiosity relation; and (iii) time-invariant unobservable heterogeneity, respectively.

  14. We obtain the County Distance Data from the National Bureau of Economic Research (NBER) website. http://www.nber.org/data/county-distance-database.html. County Distances are great-circle distances calculated using the Haversine formula. The Haversine formula is an equation important in navigation, giving great-circle distances between two points on a sphere from their longitudes and latitudes. It is a special case of a more general formula in spherical trigonometry, the law of Haversines, relating the sides and angles of spherical triangles (source: Wikipedia).

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Authors and Affiliations

  1. Leavey School of Business, Santa Clara University, 500 El Camino Real, Santa Clara, CA, 95053-0388, USA

    Hoje Jo & Manuel G. Velasquez

  2. School of Business, Korea University, Seoul, Korea

    Jinhua Cui

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  1. Jinhua Cui
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  2. Hoje Jo
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  3. Manuel G. Velasquez
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Correspondence to Hoje Jo.

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We appreciate special issue guest editors, Geert Demuijnck and Bjorn Fasterling, for their guidance and two anonymous reviewers for many insightful comments.

Appendix

Appendix

See Table 12.

Table 12 KLD employee relations
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Cui, J., Jo, H. & Velasquez, M.G. Community Religion, Employees, and the Social License to Operate. J Bus Ethics 136, 775–807 (2016). https://doi.org/10.1007/s10551-015-2865-0

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