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Problem description: Measuring quality in the service industry remains a challenge. Existing methodologies are often costly and unscalable. Furthermore, understanding how elements of service quality contribute to the performance of service providers continues to be a concern in the service industry. In this paper, we address these challenges in the restaurant sector, a vital component of the service industry. Academic/practical relevance: Our work provides a scalable methodology for measuring the quality of service providers using the vast amount of text in social media. The quality metrics proposed are associated with economic outcomes for restaurants and can help predict future restaurant performance. Methodology: We use text present in online reviews on Yelp.com to identify and extract service dimensions using nonnegative matrix factorization for a large set of restaurants located in a major city in the United States. We subsequently validate these service dimensions as proxies for service quality using external data sources and a series of laboratory experiments. Finally, we use econometrics to test the relationship between these dimensions and restaurant survival as additional validation. Results: We find that our proposed service quality dimensions are scalable, match industry standards, and are correctly identified by subjects in a controlled setting. Furthermore, we show that specific service dimensions are significantly correlated with the survival of merchants, even after controlling for competition and other factors. Managerial implications: This work has implications for the strategic use of text analytics in the context of service operations, where an increasingly large text corpus is available. We discuss the benefits of this work for service providers and platforms, such as Yelp and OpenTable. 

Abstract Healthcare industry players make payments to medical providers for non-research expenses. While these payments may pose conflicts of interest, their relationship with overall healthcare costs remains largely unknown. In this study, we linked Open Payments data on providers’ industry payments with Medicare data on healthcare costs. We investigated 374,766 providers’ industry payments and healthcare costs. We demonstrate that providers receiving higher amounts of industry payments tend to bill higher drug and medical costs. Specifically, we find that a 10% increase in industry payments is associated with 1.3% higher medical and 1.8% higher drug costs. For a typical provider, for example, a 10% or $25 increase in annual industry payments would be associated with approximately $1,100 higher medical costs and $100 higher drug costs. Furthermore, the association between payments and healthcare costs varies markedly across states and correlates with political leaning, being stronger in more conservative states. 

Science is undergoing rapid change with the movement to improve science focused largely on reproducibility/replicability and open science practices. This moment of change—in which science turns inward to examine its methods and practices—provides an opportunity to address its historic lack of diversity and noninclusive culture. Through network modeling and semantic analysis, we provide an initial exploration of the structure, cultural frames, and women’s participation in the open science and reproducibility literatures ( n = 2,926 articles and conference proceedings). Network analyses suggest that the open science and reproducibility literatures are emerging relatively independently of each other, sharing few common papers or authors. We next examine whether the literatures differentially incorporate collaborative, prosocial ideals that are known to engage members of underrepresented groups more than independent, winner-takes-all approaches. We find that open science has a more connected, collaborative structure than does reproducibility. Semantic analyses of paper abstracts reveal that these literatures have adopted different cultural frames: open science includes more explicitly communal and prosocial language than does reproducibility. Finally, consistent with literature suggesting the diversity benefits of communal and prosocial purposes, we find that women publish more frequently in high-status author positions (first or last) within open science (vs. reproducibility). Furthermore, this finding is further patterned by team size and time. Women are more represented in larger teams within reproducibility, and women’s participation is increasing in open science over time and decreasing in reproducibility. We conclude with actionable suggestions for cultivating a more prosocial and diverse culture of science.