08 March 2012

More Disclosure = Better CSR Reputation?

[This is a reprint of our paper published in the Journal of the Academy of Business & Economics (JABE), presented at the IABE conference in Key West, FL, USA, March 2012]

Christopher J. Hughey, University of Massachusetts Dartmouth
Adam J. Sulkowski, University of Massachusetts Dartmouth


ABSTRACT

This paper contributes to the scholarship of CSR and sustainability reporting by testing whether greater data availability about companies leads to their having better CSR reputations and possibly CSR performance. The authors begin with a brief literature review to develop the hypothesis that greater data availability may be correlated with having a positive CSR reputation. The authors chose the international energy industry as a focus, since these companies were early adopters of sustainability reporting and have the potential to have widespread and either very good or very bad reputations. Leaders and laggards in terms of perceived CSR performance within this industry are identified using scores generated by CSRHub, a sustainability information aggregation service. A regression test is performed and the results indicate a significant positive relationship: the more data is available about a company in the international oil and gas industry, the better its CSR reputation tends to be. Since this study only considers availability of data, and not the quality or content of information, the key finding appears consistent with the old adage that “any publicity is good publicity.” The authors also share some observations about the characteristics of the reputational leaders and laggards and their reputations across various aspects of CSR. For example, consistent with previous findings, CSR reputation leaders are found to be older and larger, while laggards are newer and smaller. The authors conclude with a discussion of implications for managers and scholars and potentially fruitful future veins of inquiry.

Keywords: Corporate Social Responsibility (CSR), Oil and Gas Industry, Energy Industry, International Business, Corporate Governance, Sustainability, Sustainability Reporting, Disclosure, Reputation


1. INTRODUCTION

Thousands of companies around the world, including a majority of the Global Fortune 500, voluntarily report on their environmental, societal, and economic impacts (Scott, 2000). The practice is alternatively known as corporate social responsibility (CSR) reporting, sustainability reporting, citizenship reporting, triple bottom line (TBL), or environmental, societal, and governance (ESG) reporting (Sulkowski and White, 2009).

While the practice of sustainability reporting is growing rapidly, the practice and its benefits are imperfectly understood by practitioners and scholars. The perceived CSR performance of companies is also growing in importance, as various stakeholders continue to take a greater interest in the environmental, economic, and societal impacts of companies in which they may invest, or for which they may work, or from which they may buy.

This paper contributes to the scholarship of CSR and sustainability reporting by testing whether greater data availability leads to companies having better CSR performance ratings in the international energy industry. The authors show that having more data available results in companies, at a minimum, having better CSR reputations. Because the study did not discriminate based on the quality or positive vs. negative nature of the data available, it appears that the volume of data alone impacts reputation. This interpretation is consistent with the old adage that “any publicity is good publicity.” If one accepts performance ratings to be reflective of actual performance, then one may further conclude that greater disclosures and visibility are leading to better mitigation of negative impacts and an increase in positive impacts. The authors also document observations of some characteristics of leaders and laggards in terms of CSR reputations in this industry. The paper concludes with a discussion of implications for managers and researchers.

2. LITERATURE REVIEW

The origins of the term corporate social responsibility in scholarly literature date back to the 1950s (Caroll, 1999). Since then, perceptions of CSR have evolved. The concept of CSR can be defined in many ways. One common definition is "actions that appear to further some social good, beyond the interests of the firm and that which is required by law" (McWilliams and Siegel, 2001). As stated above, sustainability reporting (also known as CSR reporting) is the practice of reporting a company’s environmental, societal, and economic impacts; it is sometimes known as ESG (environmental, societal, and governance) reporting.

Corporate reputation has been defined as “the perceived capacity of a firm’s ability to meet stakeholders’ expectations” (Waddock, 2000), or “the perceived stakeholders’ opinion of a firm which depends on the extent to which the expectation of those stakeholders is met” (Fombrun and Shanley, 1990). Some have suggested that a firm’s reputation is composed both of its own actions and the status of those actions relative to the actions of others, which set the expectations of the firm’s stakeholders (Bertels and Peloza, 2006).

Soppe et al. (2011) offer an excellent summary of the theoretical framework and a model for gauging CSR reputation. Siltaoja (2006) points out that there is no single “right” set of criteria for CSR reputation. Both Fombrun (1998) and Lewis (2001) suggest that CSR reputation is comprised of the following criteria: (1) environmental impacts, (2) treatment of employees, (3) financial performance, (4) product quality, and (5) quality of management or organizational issues. To this list of criteria that they hold in common, Fombrun (1998) adds (6) community involvement, while Lewis (2001) adds (6) customer service and (7) social responsibility. Schultz et al., (2001) and others have offered variations on what comprises CSR reputation.

The concept of disclosing data on CSR-related issues gained traction in the mid 1990’s through the work of John Elkington (1994 and 1998). Clarke and Gibson-Sweet (1999) suggest that companies are motivated to publish CSR performance data by the strategic need to manage their reputation and legitimacy. Ullmann (1985) offers a model for predicting such CSR activities based on a stakeholder theory of strategic management. Some have been critical of CSR reporting, arguing that it does not lead to better conduct, but rather that the exclusive aim and outcome is to manage reputation (Moneva et al., 2006; Gnepa, 2005). Others articulate variations upon this central theme of data disclosure being motivated by a desire to legitimize management decisions and heighten the company’s image as socially and environmentally responsible (Eden, 2000). Empirical studies show that “measures of stakeholder power, strategic posture, and economic performance are significantly related to levels of corporate social disclosure” (Roberts, 1992). Hasseldine et al. (2005) confirmed that CSR disclosures positively impact reputations.

As of the second decade of the 2000s, there is a nascent consensus among researchers that there is a positive relationship between the publicized CSR activities of a company and its financial performance and value. Tsoutsoura (2004) found a positive relationship between financial performance and CSR activities in 500 companies worldwide over a five year period. Rossi (2009) found that the firms comprising the Bovespa Corporate Sustainability Index (ISE) are traded at a premium. While not every study proves such a connection (Wu et al. 2010), the weight of empirical evidence suggest CSR activities and financial performance are positively related (Van Beurden and Gössling, 2008). Findings to the contrary typically cite to out-of-date data (Van Beurden and Gössling, 2008). A review of 52 scholarly articles found the same consensus, and further concluded that CSR reputation was the means by which CSR activity boosts financial performance (Orlitzky et al., 2003).

Executives agree that there is a link between reporting on their CSR activities, managing CSR reputations, and ultimately company performance and value, as evidenced by the popularity of sustainability reporting. In 2011, KMPG researched the sustainability reporting practices of the largest 100 companies (N100) in each of 34 countries (KPMG, 2011). This resulted in the following list of the percentage of the N100, by country, that reported on CSR activities: UK (100%), Japan (99%), South Africa (97%), France (94%), Denmark (91%), Brazil (88%), Spain (88%), Finland (85%), United States (83%), Netherlands, (82%) Canada (79%), Italy (74%), Sweden (72%), Hungary (70%), Portugal (69%), Nigeria (68%), Mexico (66%), Switzerland (64%), Slovakia (63%), Germany (62%), China (59%), Russia (58%), Australia (57%), Bulgaria (54%), Romania (54%), Ukraine (53%), South Korea (48%), Singapore (43%), Taiwan (37%), Greece (33%), Chile (27%, New Zealand (27%), India (20%), Israel (18%). To summarize: over 50% of the N100 in 26 out of the 34 countries in the study reported on CSR activities.

Its 2011 study was the latest of three surveys by KPMG that also surveyed executives about their motivations for sustainability reporting. The percentage of executives at the largest 250 companies in the world (the Global Fortune 250) who chose “reputation or brand” as a motivation for sustainability reporting grew from 27% (KPMG, 2005) to 55% (KPMG, 2008) to 67% (KPMG, 2011). Other prominent drivers of sustainability reporting included “employee motivation”, encouraging “innovation and learning” and “access to capital or shareholder value”. The rise of “reputation or brand” from the seventh most commonly chosen response (KPMG, 2005) to the most popular response (KPMG, 2011) reflects a widespread and growing conviction among executives that CSR data disclosure impacts reputation.

3. HYPOTHESIS AND EXPECTATIONS

Based on the foregoing literature review and data, the following hypothesis is proposed:

H1: Greater availability of CSR data about a company leads to having a better CSR reputation.

Conversely, the null hypothesis is that there is no significant CSR reputation difference between companies based on the availability of data on their CSR performance.

4. SELECTION OF SOURCE FOR DATA ON CSR REPUTATION

To test their hypothesis, the authors used the CSRHub performance rating tool, available online at www.csrhub.com. CSRHub’s objective is “to provide consistent ratings of Corporate Social Responsibility (CSR) performance for as broad a range of companies as possible.” As described on the company’s website: “[o]ur search system allows CSRHUB users to find and compare the ratings of companies in different industries and countries. Both consumers and businesspeople can use this information to make economic decisions, look for employees or jobs, organize buycotts and boycotts, and make purchasing or supply chain decisions.”

It is vital to stress that the authors do not offer any conclusions or observations as to whether CSRHub’s tool is indicative of actual CSR performance of companies. Regardless of whether or not CSRHub’s ratings reflect realities of comparative CSR performance, the authors simply used its ratings as a fair indicator of CSR reputations.

To elaborate: inherently, judging CSR performance involves choices by the judging entity: what data to consider, how many sources to reference, what metrics to use, how much weight to assign to certain aspects of CSR performance, and many other decisions about which reasonable and informed experts may disagree. The creators of CSRHub, as described below, acknowledge this.

Access to CSRHub was purchased and the authors have no financial stake or any other vested interest in or sense of loyalty to CSRHub or its founders that would undermine their objectivity in carrying out the present study.

The authors chose CSRHub because it is the most comprehensive CSR information aggregation tool that could be identified: the methodology of CSRHub ratings uses 125 sources of CSR information, with the largest contribution of data coming from aggregating five of the eight leading Environmental, Social, and Governance (ESG) research firms. The CSRHub source database also includes information from publishers, non-governmental organizations (NGOs), and three government agencies. Using a proprietary system for mapping and normalizing this broad range of information, CSRHub provides ratings on around 5,000 companies in 65 countries.
The 125 CSR information sources referenced by CSRHub use different metrics to assess CSR performance (e.g., money donated to charity vs. hours volunteered by employees), produce different results (“Top 50” rankings vs. numerical scores vs. symbols like “+” and “-“), track different industries, cover different geographic regions, evaluate at the product, subsidiary, or parent company level, and update their analyses at different time intervals,

CSRHub’s proprietary system endeavors to remove bias and inconsistency by mapping to a central schema (over two million data elements are assigned to 12 subcategories of CSR performance), converting data to numerical scales, normalizing to adjust for detected biases among sources, aggregating (weighting sources for credibility and value, generating ratings at 12 subcategory levels, and then further consolidating these ratings to four main category levels), and, finally, trimming approximately 1,500 ratings when there is inadequate information. CSRHub further states that it researches each rated company and determines its appropriate category of industry. The result is a database of hundreds of companies, searchable by industry or other characteristics, with overall CSR performance ratings ranging from 0 to 100, with 100 being the ideal. Again, the authors emphasize that, for the purpose of this study, the score is taken, at a minimum, as being indicative of widespread overall CSR reputation.

The authors used CSRHub’s default weight-of-importance assigned to the four main categories of CSR performance (community, governance, employees, and environment). CSRHub offers the option of either using the default user profile (and its weights-of-importance) or customizing a personal profile that reflects a user’s own personal convictions as to the comparative importance of different aspects of CSR performance (for example, some users may find environmental issues to be more important than social issues, or visa-versa). If a user chooses to raise the importance, for example, of environmental impacts, this would change the weights of certain factors and alter the final ratings of companies.

5. SELECTION OF INDUSTRY AND DATASET

The authors started by selecting the international oil and gas extraction industry as a focus because they were among the first to regularly publish reports on their environmental impacts starting in the 1980s (Patten, 1991), and therefore there is a potentially great abundance of data available about these companies. Also, the companies have a large potential to have widespread and either very good or very bad reputations. On the one hand, some major industry members are easily to isolate and vilify for their role in a carbon-intensive energy economy that contributes to global climate change. On the other, they have enormous resources to advertise whatever steps they may be taking to improve engines, fuel blends, and negative side effects of production, transportation, refinement, and distribution. In the human rights arena, fossil fuel companies have been castigated for their working relationships with murderous dictatorships (as in Nigeria and Burma), yet, again, have the resources to make and publicize humanitarian and charitable donations. To mention one more (but by no means the only other) basis for notoriety, the safety performance of the fossil fuel industry occupies headlines after a fiasco such as the 2010 Deep Water Horizon offshore drilling platform disaster and subsequent oil spill in the Gulf of Mexico. The subsequent positive and negative aspects of efforts to arrest damage and make amends have the potential to ruin or burnish a company’s CSR reputation.

For a dataset, the authors chose the 190 companies classified as being in the oil and gas extraction industry by CSRHub. Their respective CSR scores were retrieved from CSRHub’s database on November 1, 2011. To better be able to make some observations about the reputational outliers, the 35 companies with the best overall CSR rating in this dataset and the 35 companies with the worst overall CSR rating were identified. Among those 70 companies, the authors then further identified those at the extremes, as defined by being at least 10 points below (among the worst) or 10 points above (among the best) the subset’s average overall score. This brought the total number of companies in the dataset to 53. This identification of CSR “leaders” and “laggards” is consistent with the methodology employed by Jenkins and Yakovleva (2006) in their analysis of CSR disclosures based on case studies of ten mining companies.

The authors further excluded a few companies for the following reasons. Oil Sands Quest (Canada) and OGX (Brazil) were excluded because they had zero revenue, as both are still in the exploration-only phase. Petrohawk was excluded because it is a wholly-owned subsidiary of Billiton. Parallel Petroleum was excluded because it is privately held by an asset management company, meaning key financial data was unavailable. Franco-Nevada was excluded because they are primarily focused on gold mining, not oil and gas. Addax Petroleum was excluded because it is a wholly-owned subsidiary of Sinopec. Finally, China Blue Chemical and Bill Barrett Corporation were excluded because they only were referenced by two data sources.

After this scrutiny and screening, a final dataset of 45 companies remained, 25 being outliers with extremely good reputations and 20 being outlines with extremely bad reputations.

5. RESULTS

The analysis of the data indicates a significant positive relationship: the reputational scores of the companies in the dataset are strongly correlated to the amount of data on each company. On average, the twenty-five companies with the best reputations are associated with over four times as many data sources as the twenty companies with the worst reputations. The relationship appears to be causal.

STATISTICAL TEST RESULTS

Multiple R 0.7223
R Square 0.5217
Adjusted R Square 0.5106
Standard Error 8.4357
Observations 45

ANOVA
df SS MS F Significance F
Regression 1.0000 3337.2636 3337.2636 46.8972 0.00000002136
Residual 43.0000 3059.9364 71.1613
Total 44.0000 6397.2000


Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 14.4303 1.2666 11.3929 0.00000000000001426 11.88 16.98 11.88 16.98
X Variable 0.6753 0.0986 6.8482 0.00000002135787324 0.476 0.874 0.476 0.874





6. LIMITATIONS, DISCUSSION, AND FURTHER OBSERVATIONS

It is important to acknowledge the limitations of this study. First, the study relies upon the methodology of CSRHub in generating scores that the authors have accepted as broadly representative of, at the least, company CSR reputations. Second, the total sample size of 45 is not a large dataset.

Nonetheless, the results suggest that more data being available about a company in the international oil and gas extraction industry will cause its CSR reputation to be better. The converse is also true. Depending on whether one accepts that CSRHub’s methodology and scores are also indicative of actual CSR performance, one may also conclude that the more data is available about such a company, the better will be its actual performance, and vice-versa.

Might it be true that the twenty CSR laggards are in fact not such bad companies, but rather that they are just not reporting information or are under-researched? The authors are not inclined to believe that these negative CSR performance scores are utterly baseless, because the authors deliberately excluded any company associated with fewer than three data sources (and, to begin with, CSRHub’s methodology claims to eliminate results that are based on an inadequate number of sources). There is publicly available data concerning all the companies in the dataset that stakeholders, opinion leaders, and analysts use to judge CSR performance and upon which the CSR reputations are based.

To produce the graph below, the authors grouped the 45 companies in the dataset into groups of five companies each, starting with the twenty-five CSR leaders, represented by the numbers one through five (the best five) and moving down the dataset through the laggards, represented by the numbers six through nine (the worst five). Clearly, the CSR score and number of data sources trend downwards together, though not completely smoothly.


CHART: THE RELATIONSHIP BETWEEN NUMBER OF DATA SOURCES AND CSR SCORE


Blue line on Y-axis = CSR score of each of nine 5-company subsets compared to the dataset average
Red line on Y-axis = average number of data sources related to companies in each 5-company subset

X-axis: 5-company subsets (from 1 = best of leaders, to 9 = worst of laggards)




One might speculate that there are differences in terms of the composition of the CSR leader and laggard cohorts based on company nationality, or the country with which they are primarily associated. Among the twenty-five companies with the best reputations, only one (Petroleo Brasileiro of Brazil) was primarily associated with an emerging economy. By contrast, the twenty laggards include three companies from developing countries. However, U.S. and Canadian companies are twice as well represented in the cohort of the twenty companies with the worst reputations than among the twenty-five best. Therefore, it seems that this study does not support generalizations regarding the likelihood of developing vs. developed market companies being leaders or laggards in terms of CSR reputation or performance.

However, two observations about the two cohorts merit further discussion and future research: CSR reputation leaders are older and larger than the laggards. The leaders have been in existence for an average of seventy years, while on average the laggards have been in existence for only twenty years. While it is more common to measure company size by their market capitalization, the authors compared the companies based on revenue per annum in U.S. dollars, because sales are more indicative of the scale of operations than equity markets’ valuation of their worth. The CSR reputation leaders were, on average, much larger than the laggards - by a factor of thirty. All but one of the CSR reputation leaders were multi-billion dollar companies and the group as a whole had an average annual revenue stream of over 92 billion dollars. By contrast, the twenty laggards were much smaller companies with average revenue of just 3 billion dollars.

The positive relationship between measures of CSR performance and the age and size of companies has been documented by previous empirical studies (e.g. Wei et al., 2011; Wagner et al., 2002; Waddock and Graves, 1997; Henriques and Sadorski, 1996). The theoretical model for such an effect is based on the reality that larger firms are generally more publicly visible and therefore have more to gain if they are seen to be conducting business responsibly (Wei et al., 2011). The larger the firm, the more susceptible it may be to public scrutiny by third parties (such as news media, business analysts, and stakeholder NGOs), and hence larger firms may feel more external pressure to actually perform better in terms of CSR. Conversely, the worst offenders may not just seem worse because they disclose less; perhaps they are worse actors partly as a result of being less noticed. With fewer people and groups scrutinizing them, smaller companies may feel less pressure to improve their CSR performance and hence may be comparatively less responsible with regard to impacts on the environment and society.

On this issue the authors would like to proffer a provocative postulation. One might speculate that these results reveal a phenomenon analogous to the concept of the environmental Kuznets curve (the controversial theory that people accept the degradation of their environment during early stages of economic development, but later demand a better environment to accompany their improved lifestyles (Stern, 2004). Is it possible that something similar occurs among stakeholders in organizations? Are shareholders, entrepreneurs, employees, clients, neighbors, and activists who otherwise demand more in term of CSR conduct from a large and established company such as Shell or BP willing to turn a blind eye in the case of smaller companies? Could lower CSR expectations for newer, smaller companies be based on the idea that CSR is a luxury they cannot afford during early stages of development? This would be consistent with the phenomenon of “bolting-on” CSR activities rather than building CSR into core business activities; perhaps stakeholders and managers delay having higher expectations of responsibility with the assumption that a company can always reactively address CSR later in the lifecycle of the enterprise.

Aside from the differences in company characteristics, there are differences in CSR scores between and among the CSR reputation leaders and laggards that merit discussion. First, as illustrated below, the twenty-five leaders are better in all of the four major aspects of CSR performance (community, governance, employees, and environment), than the twenty laggards. The widest gulf between the leaders and laggards was in the environmental aspect, where there was a twenty-nine point gap between the groups’ respective averages. The smallest difference was a nineteen point gap between the leader and laggard cohorts’ community scores.



CHART: AVERAGE CSR SCORE OF LEADERS VS. LAGGARDS ON FOUR ASPECTS OF CSR

Zero on the y-axis = respective average score of 190 companies in the oil and gas extraction industry





The second observation about CSR scores is that the companies – not just the average of the cohorts of CSR reputation leaders and laggards – are clearly differentiated and either score very well across all aspects of CSR performance or do very badly across all categories. No company among the twenty laggards achieved a score over 48 in any category, while no company in the top twenty-five had a score under 48 in any category. The third observation about CSR scores is that the twenty-five CSR leaders demonstrated much less variation across the four categories of reputational performance (community, governance, employees, environment), with a standard deviation of just under four. Among the twenty companies with the worst reputations, the standard deviation across the four categories was more than five. Therefore, the study supports the proposition that CSR leaders tend to be consistently positive in terms of various aspects of their environmental, societal, and governance reputations (and, possibly, CSR activities) while laggards tend to have not only much lower, but also greater variation in their low performance across various aspects of CSR reputation (and, possibly, CSR activities).

Finally, it is vital to note that this study focused on the volume of data that was available about each CSR leader and laggard. The study did not identify the quality or the type of data related to companies. Similarly, this study was blind as to whether positive vs. negative information or narratives were communicated. Some of the largest players in the oil and gas extraction industry experience a glut of negative media exposure and stakeholder scrutiny. As mentioned above, some have had to communicate about calamities such as the Deep Water Horizon oil drilling platform accident and disastrous aftermath in the Gulf of Mexico. Others, such as Halliburton, have recently grappled with voluminous negative publicity surrounding practices such as hydraulic fracturing in the U.S. that may endanger human health. The controversial exploitation of the Canadian tar sands is another issue about which large companies such as Shell have had to communicate. Regardless, there appears to be a near perfectly positive relationship between the availability of data about companies and their CSR reputations. Further, the largest companies – which tend to attract the most negative publicity – are found to be CSR reputation leaders. The results may therefore be interpreted as an example of the old adage that “any publicity is good publicity” (which has not been conclusively attributed to any one individual) and are possibly even consistent with the notion of “succès de scandale” (success from scandal). The concept originated during the Belle Époque in Paris at the turn from the 19th to 20th century when artists (including Oscar Wilde, Edouard Manet, Igor Stravinsky, and Richard Strauss) leveraged shocking negative news into fame and success. Similarly, contemporary celebrities (such as Hugh Grant, Charlie Sheen, Madonna, and Paris Hilton) have demonstrated that “any press is good press” by profiting from notoriety for shocking behavior. Perhaps a key implication of this study’s findings (including but not necessarily limited to corporations) is that visibility and transparency – regardless of the nature or quality of conduct – may ultimately have a positive impact on reputation. Further studies such as content analyses of sustainability reports and news stories related to CSR leaders and laggards could further substantiate this possibility. It may also be possible that it is not solely data availability, but rather the masterful corporate communication strategies of large companies with superior resources that allow them to be CSR leaders regardless of whether they must grapple with disasters or have positive information to communicate.

7. CONCLUSION

The key contribution of this study to the fields of CSR and sustainability reporting is the finding that increased availability of data about a company results in, at the least, better CSR reputations for companies in the international oil and gas extraction industry. If one assumes aggregated reputational scores to reflect actual CSR performance, then one could further conclude that increased availability of data leads to improved CSR conduct. Among oil and gas extraction companies, older and larger companies tend to be among the leaders in terms of CSR reputation while CSR laggards are smaller and newer. This is consistent with existing theoretical frameworks and previous findings of empirical studies. Further, the leaders and laggards are clearly differentiated by a large gap in CSR reputational scores across all four major aspects of CSR (community, governance, employees, and environment), but especially in terms of reputation for conduct related to the environment. CSR leaders in this industry tend to be perceived as more consistently good across all four aspects of CSR performance, while CSR laggards tend to have greater variation in their negative scores across the four aspects of CSR performance. Finally, the authors point out that the study took into account only the amount of data available about each company, not the quality or whether it communicated positive or negative facts and narratives. Given that it is just the volume of available data that appears to positively impact reputation, the results appear consistent with the old adage that: “any publicity is good publicity”. The implications of this study for managers are that greater disclosures related to CSR will likely improve a firm’s CSR reputation and that transparency may possibly even lead to better conduct. For scholars, this study suggests several fruitful veins of future research. This study could be repeated using data from other industries, using different measures of CSR reputation and conduct, over varying periods of time, and by measuring changes in CSR reputation and conduct over time as companies grow.


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AUTHOR PROFILES

Christopher J. Hughey earned his undergraduate degree in languages and international studies from the Universitetet i Bergen (University of Bergen, Norway) in 1995. He is currently Executive Vice-President of EC Innovations, Inc., a China-based translation and localization company. This paper builds on the research he undertook while doing graduate studies in international business from the University of Massachusetts (Dartmouth), where he earned a graduate certificate in that field in 2012.

Adam J. Sulkowski is an Associate Professor of Business Law and Sustainable Development. He earned his JD and MBA at Boston College in 2000. He is recipient of several awards for teaching, research and service excellence. He mentored MBA students to produce the first GRI-guided sustainability report by a university anywhere in the world to achieve an A level of compliance with the premier global standard for reporting on CSR performance.

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