In the United States like in many other countries throughout the globe, construction workers are more likely to be injured on the job than workers in any other industry. This poor safety performance ...is responsible for huge human and financial losses and has motivated extensive research. Unfortunately, safety improvement in construction has decelerated in the last decade and traditional safety programs have reached saturation. Yet major construction companies and federal agencies possess a wealth of empirical knowledge in the form of huge databases of digital construction injury reports. This knowledge could be used to better understand, predict, and prevent the occurrence of construction accidents. Unfortunately, due to the lack of a clear methodology and the high costs of manual large-scale content analysis, these valuable data have yet to be extracted and leveraged. Recently, researchers have proposed a framework allowing meaningful empirical data to be extracted from accident reports. However, the resource limitations inherent to manual content analysis still remain. The present study tested the proposition that manual content analysis of injury reports can be eliminated using natural language processing (NLP). This paper describes (1) the overall strategy and methodology used in developing the system, and specifically how key challenges with decoding unstructured reports were overcome; (2) how the system was built through an iterative process of coding and testing against manual content analysis results from a team of seven independent analysts; and (3) the implications and potential uses of the data extracted. The results indicate that the NLP system is capable of quickly and automatically scanning unstructured injury reports for 101 attributes and outcomes with over 95% accuracy. The main contribution of this research is to empower any organization to quickly obtain a large and highly reliable structured attribute and outcome data set from their databases of unstructured accident reports. Such structured data are a necessary prerequisite to the application of statistical modeling techniques, allowing the extraction of new safety knowledge and finally the amelioration of safety management.
•A natural language processing system is proposed.•The system is based on hand-coded rules and dictionaries of keywords.•Injury reports are scanned for 102 attributes and outcomes with over 95% accuracy.•Large databases of unstructured injury reports can now efficiently be leveraged.
The vast increase in online expressions of consumer sentiment offers a powerful new tool for studying consumer attitudes. To explore the narratives that consumers use to frame positive and negative ...sentiment online, we computationally investigate linguistic structure in 900,000 online restaurant reviews. Negative reviews, especially in expensive restaurants, were more likely to use features previously associated with narratives of trauma: negative emotional vocabulary, a focus on the past actions of third person actors such as waiters, and increased use of references to “we” and “us”, suggesting that negative reviews function as a means of coping with service–related trauma. Positive reviews also employed framings contextualized by expense: inexpensive restaurant reviews use the language of addiction to frame the reviewer as craving fatty or starchy foods. Positive reviews of expensive restaurants were long narratives using long words emphasizing the reviewer’s linguistic capital and also focusing on sensory pleasure. Our results demonstrate that portraying the self, whether as well–educated, as a victim, or even as addicted to chocolate, is a key function of reviews and suggests the important role of online reviews in exploring social psychological variables.
Product return is a critical issue due to the uncertainty associated with the price, demand, and quality of the product. Thus, businesses must improve their information transparency to administer the ...product return behaviour of the end-user. Different studies so far have contributed to developing solutions to manage product return issues. This paper provides a comprehensive review of the literature on the product returns management domain to provide the scientific landscape map of existing studies for exploring the state of the current body of knowledge. A systematic literature review of existing literature, quantitative bibliometric analysis, and in-depth content analysis are conducted to accomplish the purpose. A total of 518 published articles from January 1986 to November 2020 are selected, reviewed, classified, and analysed in this study. We classified papers into six identified PRM categories, namely product recovery, forecasting product returns, consumer behaviour, return policy, uncertainty, and technology. Finally, we blended the state-of-the-art research and outlined the future research agenda concerning various themes, methodologies used, and aspects like lean, agility, and disruption in PRM based on research gap analysis.
The sharing economy is a global phenomenon with rapid growth potential. While research has begun to explore segmentation between users and non-users, only limited research has looked at consumer ...segmentation within sharing economy services. In this paper, we build on this research gap by investigating consumer segmentation within a single sharing economy platform: Airbnb. Utilizing a mixed methods approach, with both a quantitative survey and a qualitative content analysis of Airbnb listings, we compare two different types of accommodation offered on Airbnb: shared room and entire home. Our findings indicate that within a single platform, the variety between offerings can create distinct consumer segments based on both demographics and behavioral criteria. We also find that Airbnb hosts use marketing logic to target their listings towards specific consumer segments. However, there is not, in all cases, strong alignment between consumer segmentation and host targeting, leading to potentially reduced matching efficiency.
•Users of shared rooms and entire homes on Airbnb are substantially different.•Income, education, gender, and travel modality predict accommodation choice.•Airbnb hosts strongly target listings for customer segments, such as for age.•Guest choice and host targeting do not align, leading to potential inefficiency.
Bayesian model averaging (BMA) provides a coherent and systematic mechanism for accounting for model uncertainty. It can be regarded as an direct application of Bayesian inference to the problem of ...model selection, combined estimation and prediction. BMA produces a straightforward model choice criterion and less risky predictions. However, the application of BMA is not always straightforward, leading to diverse assumptions and situational choices on its different aspects. Despite the widespread application of BMA in the literature, there were not many accounts of these differences and trends besides a few landmark revisions in the late 1990s and early 2000s, therefore not accounting for advancements made in the last decades. In this work, we present an account of these developments through a careful content analysis of 820 articles in BMA published between 1996 and 2016. We also develop a conceptual classification scheme to better describe this vast literature, understand its trends and future directions and provide guidance for the researcher interested in both the application and development of the methodology. The results of the classification scheme and content review are then used to discuss the present and future of the BMA literature.
A content analysis of the editorial pages of the Birmingham News from 1960 to 1964 shows that, despite its staunch segregationist stance, the paper's editorial pages, nonetheless, produced strong ...integrationist narratives. This paradox was borne of discordant interpretations of 14th Amendment rights featured in the Supreme Court's Plessy (1896) and Brown (1954) decisions. Rise of staunch segregationist groups and officials after the Court's 1954 Brown decision drove News editors to embrace greater democratic pluralism. The evolution in editorial approach corresponded to the paper's gradual adoption of Brown's interpretations of 14th Amendment rights. Change in the valence of the paper's narratives supports Condit’s (1987) thesis that rhetorical “crafting” of public morality about race brought about greater tolerance and acceptance of racial equality in America.
Widespread specimen digitization has greatly enhanced the use of herbarium data in scientific research. Publications using herbarium data have increased exponentially over the last century. Here, we ...review changing uses of herbaria through time with a computational text analysis of 13,702 articles from 1923 to 2017 that quantitatively complements traditional review approaches. Although maintaining its core contribution to taxonomic knowledge, herbarium use has diversified from a few dominant research topics a century ago (e.g., taxonomic notes, botanical history, local observations), with many topics only recently emerging (e.g., biodiversity informatics, global change biology, DNA analyses). Specimens are now appreciated as temporally and spatially extensive sources of genotypic, phenotypic, and biogeographic data. Specimens are increasingly used in ways that influence our ability to steward future biodiversity. As we enter the Anthropocene, herbaria have likewise entered a new era with enhanced scientific, educational, and societal relevance.
•Panic buying is an emerging phenomenon observed during COVID-19 pandemic.•We aimed to evaluate the nature, extent, and impact of panic buying as reported in the media.•A high proportion of reports ...have been found from the developed countries.•There is a need for further studies to explore the issue as well as to prevent the episodes.
Panic buying is an emerging phenomenon observed during, but not restricted to, pandemic.
We aimed to evaluate the nature, extent, and impact of panic buying as reported in the media.
This study was conducted by collecting the information from the English media reports published till 22nd May 2020. A structured format was developed to collect data. Searching was done by using the keyword “panic buying”. We have excluded the social media posts discussing the panic buying.
The majority of media reporting was from the USA (40.7 %), and about 46 % of reports highlighted the scarce item. Approximately 82 % of the reports presented the causes of panic buying whereas almost 80 % report covered the impact of it. About 25.7 % of reports highlighted the rumor about panic buying and only 9.3 % of reports blamed the government. Only 27.1 % reports described the remedial measures, 30.8 % reports conferred the news on the psychology behind panic buying and 67.3 % news displayed the images of empty shelves.
A high proportion of reports on panic buying have been found from the developed countries discussing the causes & impact of panic buying on the basis of expert opinion.
Drawing from clinical and organizational narcissism research, we develop a novel measure of narcissistic rhetoric, investigating its prevalence in a sample of 1863 crowdfunding campaigns. An ...experiment using 1800 observations further validates our measure and confirms our hypothesized inverted-U relationship between narcissistic rhetoric and crowdfunding performance. Leveraging social role theory, we explore sex, sexual orientation, and race as potential moderators of this relationship. Moderation tests reveal LGBTQ entrepreneurs generally yield greater performance when using narcissistic rhetoric than heterosexuals while racial minorities underperform Caucasians using narcissistic rhetoric. Our findings suggest successful crowdfunding campaigns must balance narcissistic rhetoric with entrepreneurs' perceived social roles.
•Narcissistic rhetoric has an inverted-U relationship with crowdfunding performance.•We create a comprehensive measure of narcissistic rhetoric using content analysis.•Impact of narcissistic rhetoric is shaped by entrepreneurs' adherence to prevalent social roles.•Entrepreneur sex, sexual orientation, and race influence investor responses to narcissistic rhetoric.
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