Article link: http://asq.sagepub.com/content/58/4/669
Question 1. Our first question is about the motivation behind this particular paper; we’re curious about the story of how this paper came to be.
This paper comes out of a program of work that Professors Paul Ingram, Hayagreeva Rao, and I have conducted since 2007. What motivated us to do this research was to understand large and consequential organizations that play key roles in the daily lives of people. Our first paper from this research program was published on the American Journal of Sociology. That paper investigates the anti-Walmart protests, and we found that community protests can be very effective in the sense that they not just directly deter large corporations, as the prior literature has argued, but also influence large corporations’ decisions by serving as market signals. Our second paper was published on the American Sociological Review. In that paper, we found that a local community’s pro- or anti-business climate will magnify or reduce, respectively, the effectiveness of corporate efforts in fending off activists’ attacks.
Regarding this paper, we extended the research program to another big box store and incorporated interorganizational dynamics into our analyses of the contention between activists and large corporations. Initially, what caught our attention was the striking difference in the protest rates experienced by Walmart and Target. When we looked at the media reports, we found ones that attributed the difference to the two corporations’ citizenship behaviors. These reports suggested that Target experienced a low protest rate because the company did a lot of CSR and donated to local communities. But the answer was not satisfying to us because we knew from our prior research that Walmart also donated to local communities. Why was Walmart particularly bad? Moreover, our media search also discovered plenty of reports that suggested that the Walmart and Target are very similar in their business models, wage levels, and welfare policies. After we put the proposals by Walmart and Target to open stores from 1998 to 2008 on the map, we found that they were interested in entering the same markets, and that Target’s proposals tended to be one or two years later than Walmart’s. This was the “Aha” moment—we knew that we got a new explanation for the different protest rates experienced by the two retailers.
Question 2. Our next question is about the datasets you used in the study. Your data collection work seems like it would be daunting; collecting data from the Sprawl-Busters database, the news-media, and activist websites—and then matching them to the associated opening proposals. What were your biggest challenges in the data collection stage of the paper?
Continuing along the data collection theme, what are your thoughts on using social media data to measure protest activity? If, instead of collecting data from 1998-2008 you were collecting data from, say, 2011-2016, would you include social media postings on sites like Twitter or Facebook into your data collection? If so, where do you think that data best fits into a study like this one?
The data collection is a painstaking process, but it is also very rewarding. By going to the original data and reading the news reports, you can gain a lot of insights. You also obtain rich knowledge about the research context, such as who are the protestors, why they protest, whether they succeed, and how they interact with big-box stores. For example, in one report, Walmart’s spokeswoman said Walmart opted for secrecy when choosing store sites because it did not want Target to follow it. Her words provided direct evidence that supports the mechanism that we argued.
Social media have progressed greatly in the past few years, and they have played a significant role in the social movements like the Arab Spring. They also provide a rich set of data. Mining the social media data can be very beneficial for future research. But one thing researchers have to bear in mind is what constitutes a protest event in the new situation. Twitting a few messages is different from turning out on the street with friends. These different ways of communication and interpersonal interaction may also have different implications for movement effectiveness, community cohesion, and social capital. In addition, researchers need to be aware that the demographics of the groups that are heavy users of the social media may be different from the traditional activists. These are all questions that future research should take into account.
Question 3. We’re also curious about the firms you selected for the study. Wal-Mart and Target are interesting firms because the public perception of the two firms are so different from one another (though, as you mention in the paper, on a policy level the two firms may not be so dissimilar at all). How do you think your results would be different if you had looked at different firms—Home Depot and Lowes, for example.
This is particularly interesting because your dataset includes data from 2008-2010, which was when the financial crisis hit America. Is it possible that during these years, some people were primed to protest against Wal-Mart’s image as a capitalistic monolith (similar to Bank of America, for example) due to macroeconomic factors? Did you think about controlling for a possible financial crisis effect? Do you think such a control would be useful?
The big-box store is a category of retailers. When one company spoils the image of the category, other retailers also suffer as a result of being a member of that category. There is a mutuality effect between them. Direct competitors watch each other closely, and they imitate and learn from each other. There are protests against Home Depot and Lowes, and it would be interesting to extend the research to these big-box stores.
The effect of financial crisis is complicated. One consequence is that Walmart slowed down on the construction of new stores during the financial crisis, which decreased the number of protests they received. Walmart also became more popular during the financial crisis period because their low price was appealing to many. Target was the one that faced financial difficulty in the recent past financial crisis. We did control for the financial crisis effect in the unreported analysis, but it was not particularly significant in any direction.
Question 4. As you note, the protest with general claims variable has a negative coefficient but it insignificant in all models, excepted when tested alone. You mention in the paper that you believe that that the lack of a robust effect for this variable may be due to the fact that general claims against big-box stores are often vague, and without specific targets. Our understanding of the way this variable is operationalized is that if a protest made claims about Wal-Mart and also general big box stores, it would be coded as a general protest; do you think that this suggests that protesters are doing themselves a disservice when they broaden their protest activity to try to cast a wider net?
Additionally, do you think it could be possible that that general claims could have been insignificant because they lack coordination among protesters? Or because there may not be an organization (such as a labor union) or a strong leader in charge of those types of protests? Do you have qualitative data on these protests? If so, have you thought about analyzing the motivation or the network structure behind the general claims? If so, how would you go about doing that?
General claims are not particularly effective in deterring Target from proposing to open a store in a community after controlling for other variables. It would certainly be helpful to analyze the organizational structures of activists. It remains an interesting research question for future scholars to investigate why activists made specific claims in some situations but generalized ones in others. It is an empirical issue to test whether activists’ level of organization influences their targeting decision.
Question 5. One of your most interesting variables, in our opinion, involves union involvement. You used union-led protest as a proxy for protests that are spearheaded by protest-prone activists that are sponsored by national organizations (under the theory that these protests send different signals than protests that are locally-grown from within a community). In your experience coding the data, did you find that protesters were generally proud to talk about their connections with these national organizations? It seems like a lot of social action today is funded by large groups that make an effort to appear disconnected from the root of the movement (the phenomenon of “astroturfing”). How “leaky” do you think these types of information cover-ups are in practice?
The idea of astroturfing relates back to one of your implications for the strategies of protesters; perhaps the groups that funnel resources into movements will see your research as further evidence to suggest that they need to do more to hide their involvement in “local” protests?
The leadership by national organizations is helpful in that these organizations supply skills, personnel, and facilities of mobilization and they also help to solve the collective action problem that often prohibits the mobilization by local residents. Meanwhile, the protests connected with the national organizations also run the risk of being perceived as untrustworthy, inauthentic, and funded by special interests, especially when the mobilization is unable to connect with the community that genuinely care about the issue for its own purposes. To some extent, the association with the national organizations is a double-edged sword for local activists. But covering up the association may not be in the best interest of either local activists or the national organizations, because once people discover who act behind the curtain, there is likely to be backlash against protestors. There is research showing that campaigns that are authentic, transparent, and have a genuine base in the community tend to be more successful.