How Do Journal Quality, Co-Authorship, and Author Order Affect Agricultural Economists' Salaries?

Utilizing an original data set containing annual salaries and peer-reviewed publication histories for 326 faculty members from top-ranked Ph.D.-granting programs, we examine the labor market for academic agricultural economists. The results suggest that higher quality publications have a greater impact on annual earnings, that sole authored articles have a higher return than multi-authored articles, and that no wage premium exists for being the lead author of a non-alphabetic article.     

Seeing the wood for the trees: How machine learning can help firms in identifying relevant electronic word-of-mouth in social media

The increasing volume of firm-related conversations on social media has made it considerably more difficult for marketers to track and analyse electronic word-of-mouth (eWOM) about brands, products or services. Firms often use sentiment analysis to identify relevant eWOM that requires a response to consequently engage in webcare. In this paper, we show that sentiment analysis of any kind might not be ideal for this purpose, because it relies on the questionable assumption that only negative eWOM is response-worthy and it is not able to infer meaning from text. We propose and test an approach based on supervised machine learning that first decides whether eWOM is relevant for the brand to respond, and then—based on a categorization of seven different types of eWOM (e.g., question, complaint)—classifies three customer satisfaction dimensions. Using a dataset of approximately 60,000 Facebook comments and 11,000 tweets about 16 different brands in eight different industries, we test and compare the efficacy of various sentiment analysis, dictionary-based and machine learning techniques to detect relevant eWOM. In doing so, this study identifies response-worthy eWOM based on the content instead of its expressed sentiment. The results indicate that these machine learning techniques achieve considerably higher accuracy in detecting relevant eWOM on social media compared to any kind of sentiment analysis. Moreover, it is shown that industry-specific classifiers can further improve this process and that algorithms are applicable across different social networks.     

Language and market inclusivity for women entrepreneurship: the case of microfinance

Inclusive markets are key to fostering female entrepreneurship, and the microfinance sector has recognized and acted on this. Existing research has studied how institutions and organizational factors facilitate the process by which microfinance and other financial intermediaries tackle gender-based financial exclusion. But while the role of cultural institutions has been recognized as important, little research has systematically integrated culture in the study of gender-based financial exclusion. We posit that language is a cultural institution that influences the extent to which financial intermediaries are successful in outreaching women and supporting female entrepreneurship. Inspired by a performativity approach, we develop a set of hypotheses that delineate how a specific feature of language, gender marking in grammar, moderates the role of institutional (state capacity) and organizational (NGO status and global ties) factors in shaping microfinance outreach to women. Using the ratio of female to male borrowers in 2361 microfinance organizations from 115 countries during the period 1995–2015, we confirm that market inclusion of women depends on organizational and institutional factors, and that gender marking in grammar influences those relationships.     

Bribes as entrepreneurial actions: Why underdog entrepreneurs feel compelled to use them

Entrepreneurs often need external resources to found their new ventures. These can be obtained from many sources, but government sponsored programs are an important and often desirable one because they do not require repayment of the funds provided. Resources from such programs should, in principle, be equally available to all entrepreneurs, but in fact, some entrepreneurs—ones often described as underdogs – have restricted access to them. This disadvantage stems, in part, from personal factors they cannot readily change (e.g., gender, age, race, ethnicity, current occupation, family background, experience). The negative effects of being an underdog are especially harmful to entrepreneurs in the context of poor economic conditions, when competition for available resources is intense. In order to overcome such adversity, underdog entrepreneurs offer bribes to persons who control these resources. We hypothesized that there would be a positive relationship between the perception by entrepreneurs that local economic conditions are poor and their use of bribes, and that this relationship would be stronger for “underdog” entrepreneurs than for other entrepreneurs. We also hypothesized that the use of bribes by entrepreneurs and their perception that these bribes will be effective would interact to influence entrepreneurs' decisions to close their new venture. Specifically, bribes would influence such decisions only when they were viewed as effective. Results offered support for these hypotheses, thus providing new insights into why underdog entrepreneurs use bribes to overcome the adversity they face.     

Signaling by early stage startups: US government research grants and venture capital funding

Entrepreneurship researchers have documented that early stage startups rely on signals to demonstrate the transitions in their identities that they must make when they cross organizational life cycle thresholds. However, early stage startups in emerging industry contexts tend to have few good signals upon which to rely. Public agencies can play a valuable role in this process, but prior research has not sufficiently examined how startups effectively leverage this support. In this paper, therefore, we develop a framework to investigate the role that signals can play for early stage startups when they win prestigious government research grants. We test this framework in the setting of the emerging U.S. clean energy sector and find that in comparison to a matched sample of clean energy startups that have not won prestigious research grants, startups with these grants were 12% more likely to acquire subsequent venture capital (VC) funding. Another significant result is that the value of this signaling is greater for startups that have fewer patents. The important contribution of this finding is that it shows that signaling has the potential to redistribute benefits rather than just provide an additional accrual of advantages to the already high status actors. Together these results highlight the advantages for startups in emerging industries of pursuing signaling strategies with public agencies when they attempt to make important transitions through the stages of their organizational life cycles.

Going pro-social: Extending the individual-venture nexus to the collective level

The aim of this Special Issue is to demonstrate how drawing on multidisciplinary insights from the literature on prosociality can broaden the individual-opportunity nexus to make room for a variety of actors. Five feature articles emphasize the collective level of the analysis, underscoring the social distance between the entrepreneurs and the different communities they serve. Leveraging construal level theory, we abductively derive an organizing framework that helps us articulate how stretching or compressing social distance can transform initial opportunities into occasions for serving the greater good. We identify two distinct mechanisms present in all five empirical studies that explain how the needs and hopes of many others may add creativity, consistency and connectivity to one's venture. We also connect these abductive insights with the two editorials that follow this introduction and nudge our collective attention towards the research opportunities awaiting our academic community once we begin to relax the egocentric reference point that, until recently, has defined the discipline of entrepreneurship.     

Market performance implications of modularization: Evidence from global auto firms operating in China

Auto firms play an increasingly important role in national economies. However, their internationalization strategies, especially the trend towards modularization has been underexplored in the international business literature. Drawing on the resource based theory, we develop hypotheses on the link between modularization and market performance. Analyzing a sample of 262 auto parts suppliers in China, the study shows the positive influence of modularization on firm performance and the moderating role of knowledge sharing tools and physical proximity in this relationship. In addition, these relationships are channeled by firms’ strategic actions to maintain superior business performance against competitors (firm positional advantage).     

Ad wearout wearout: How time can reverse the negative effect of frequent advertising repetition on brand preference

This paper reports a surprising reversal in the effect of advertising repetition over time. A field study shows higher annoyance with a more frequently advertised brand at the time of advertising, but greater preference for this same brand several weeks later. A longitudinal online experiment replicates the reversal in brand preference across four time points and tests an underlying mechanism for this reversal. It shows that initial annoyance with frequent ad repetition is highly susceptible to decay over time, whereas brand memory remains relatively stable. Through these two processes, brands with heavier advertising exposure move over time from lower preference to higher preference. Finally, a third experiment demonstrates a crucial condition for this reversal — product relevance at the time of consideration. This study shows that the reversal occurs only if at the later time the product category is relevant. We discuss the substantial implications of these findings for marketing theory and practice.     

Too much of a good thing? Consumer response to strategic changes in brand image

The current research investigates a potential disadvantage of building brand associations that resonate with consumers' identities and facilitate consumer–brand bonding. The authors propose a theory of consumer response to changes that either dampen or augment the associations central to brand image (e.g., due to brand acquisitions or repositioning). The results show that consumers with a high degree of self–brand connection respond more negatively than others do to changes that dampen brand associations. Counterintuitively, changes augmenting brand associations can also lead to unfavorable consumer sentiments in certain instances. When brand connection was linked to an ideal self-identity (i.e., self-enhancement motives), changes that augmented the brand image increased the brand's ability to signal an ideal identity. Conversely, when brand connection was linked to the actual self-identity (i.e., self-verification motives), augmenting brand image reduced the perceived similarity between the self and the brand, thus causing brand identification to deteriorate.