Relationship Cultivation via Social Media During the COVID-19 Pandemic: Evidence From China and the U.S

This study explored the relationship cultivation and social media strategies companies used to cultivate relationships with their publics in two culturally distinct markets of China and the U.S. during the COVID-19 pandemic. A quantitative content analysis of Weibo ( n = 756) and Twitter ( n = 645) posts from Fortune 500 companies in China ( n = 30) and the U.S. ( n = 30) respectively was conducted to examine the effects of their relational efforts on public engagement. Results showed that certain relationship cultivation strategies and use of social media functions effectively increased public engagement in both China and the U.S., although on different levels. Both Chinese and U.S. companies most frequently adopted the strategy of openness. While the openness strategy was most effective at raising engagement levels in the U.S., publics of Chinese companies became more engaged when companies used the access strategy. Also, publics of Chinese companies showed higher levels of engagement and more positive emotions toward companies’ social media messages than their U.S. counterparts. The findings advance our understanding of organization-public relationships in a worldwide disaster setting, with insights informing the global public relations theory and practices.

Integrating Keyword Segmentation and Budget Allocation Decisions in Sponsored Search Advertising

Budget constrained sponsored search advertisers must decide how to allocate their advertisement budget across ad campaigns and individual keywords. In this paper, a simulation model that integrates the complex issues involved in keyword segmentation and campaign organization is used to evaluate performance of various budget allocation strategies. Using the buying funnel model as the basis for keyword segmentation and campaign organization, we analyze Volume-based, Cost-based, and Clicks-based budget allocation strategies and evaluate their performance implications for different firms. The simulation model is empirically evaluated using four Fortune 500 companies and their keyword data obtained from a leading provider of keyword research technology. The results and statistical analyses show significant improvements in budget utilization using the proposed allocation strategies over a Baseline commonly used in practice. The study offers useful insights into the budget allocation problem by leveraging a theoretical framework for keyword segmentation and campaign management.

A 21st Century Technical Infrastructure for Digital Preservation

Digital preservation systems and practices are rooted in research and development efforts from the late 1990s and early 2000s when the cultural heritage sector started to tackle these challenges in isolation. Since then, the commercial sector has sought to solve similar challenges, using different technical strategies such as software defined storage and function-as-a-service. While commercial sector solutions are not necessarily created with long-term preservation in mind, they are well aligned with the digital preservation use case. The cultural heritage sector can benefit from adapting these modern approaches to increase sustainability and leverage technological advancements widely in use across Fortune 500 companies.

Transforming the Generative Pretrained Transformer Into Augmented Business Text Writer

This study uses transformers architecture of Artificial neural networks to generate artificial business text for a given topic or theme. The implication of the study is to augment the business report writing, and general business writings process with help of Generative pretrained transformers (GPT) networks. Main focus of study is to provide practical use case for GPTs models with help of big data. Our study model has 355 million model parameters and trained for three months on GPU enable devices using 2.3 billion text tokens(is available as open-source data now). Text tokens are collected with help of rigorous preprocessing, which includes; shortlisting of Subreddits of Fortune 500 companies and industries, listed on US-based social news aggregation online portal called "Reddit". After shortlisting, millions of submission of users during the five years, are parsed to collect the URLs out of it. 1.8 million working URLs are scrutinized. Business text is parsed, cleaned, and converted into word embeddings out of URLs. The result shows that both models; conditional interactive and random sampling, generate text paragraphs that are grammatically accurate and stick to the given topic.

Codes of Ethics: Extending Classification Techniques with Natural Language Processing

Language is an indicator of how stakeholders view an ethics code’s intent, and key to distinguishing code properties, such as promoting ethical-valued decision-making or code-based compliance. This article quantifies ethics codes’ language using Natural Language Processing (NLP), then uses machine learning to classify ethics codes. NLP overcomes some inherent difficulties of “measuring” verbal documents. Ethics codes selected from lists of “best” companies were compared with codes from a sample of Fortune 500 companies. Results show that some of these ethics codes are different enough from the norm to be distinguished by an algorithm; indicating as well that lists of “best” companies differ meaningfully from each other. Results suggest that NLP models hold promise as measurement tools for text research of corporate documents, with the potential to contribute to our understanding of the impact of language on corporate culture and enhance our understanding of relationships with corporate performance.

Like It or Not: When Corporate Social Responsibility Does Not Attract Potential Applicants

Companies increasingly recognize the importance of communicating corporate social responsibility (CSR) including their engagement toward employees, the community, the environment and other stakeholder groups to attract applicants. The positive findings on the effect of CSR on applicants’ reactions are commonly based on the assumption that companies send a clear signal about their commitment to CSR. However, communication is always contextualized and has become more ambiguous through the increased availability of information online. External stakeholders including actual and potential applicants are confronted with inconsistencies between the way companies communicate CSR activities and their overall CSR performance. Drawing on signaling theory, this article raises the question of how the interaction between strong CSR communication and low CSR performance influences organizational attractiveness. We propose that low CSR performance dampens the effect of CSR communication on organizational attractiveness. Hence, the inconsistency between CSR communication and CSR performance decreases organizational attractiveness. To test our hypotheses, we scraped 67,189 posts published on corporate Facebook career pages by 58 Fortune 500 companies from the time they began their respective career page until June 2018. Surprisingly, our results show that a low CSR performance strengthens the effect of CSR communication on organizational attractiveness. Thus, inconsistencies between CSR communication and CSR performance seem to lead to positive evaluations among applicants.

Majority of Fortune 500 Companies in 2018 Did Not Recognize Risk of Epidemics Such as COVID-19

Infectious disease threats, like the 2002 severe acute respiratory syndrome coronavirus (SARS-CoV) disease, 2009 pandemic influenza A (H1N1), and the current coronavirus disease 2019 (COVID-19), pose multisectoral risk with the potential for wide-ranging socioeconomic disruption. In our globally intertwined economy, the impact of such events can elicit economic shock waves that reach far beyond the country of origin. Review of the 2018 Fortune 500 company 10-K filings shows the majority did not document perceived risks associated with epidemics, outbreaks, or pandemics. Enhanced engagement and investment of the public and private sectors in advancing global health security is needed to effectively prevent, detect, and respond to infectious disease events and ensure U.S. economic security.

Silence has no place: a framing analysis of corporate statements about racial inequity, immigration policy and LGBTQ rights

PurposeThis study explores the framing of messages delivered by 105 Fortune 500 companies across 21 sectors in June 2020 in response to three social justice issues that took prominence that month in the United States: racial inequity, immigration laws and LGBTQ rights.Design/methodology/approachResearchers compiled a list of the top five companies in each sector on the 2020 Fortune 500 list, with a resulting list of N = 21 sectors and N = 105 companies. A database of corporate statements was compiled along with a comprehensive list of recurring themes. Quantitative framing analysis was used to examine each corporate statement.FindingsSeventy percent of the companies examined made statements about the issue of racial injustice, 58% about LGBTQ issues and only 6% about immigration policy. Coders identified the most frequent message type coded on each social justice issue: racial inequity –“Working Together”; immigration policy – “Celebration”; LGBTQ rights – “Celebration.”Research limitations/implicationsThis study relied on a quantitative analysis of themes, but it did not analyze the specific language or media used. Further examination of rhetorical choices could uncover additional meanings in the messages.Practical implicationsCompanies are increasingly called upon to speak out on controversial issues. This can be challenging for communicators who are deciding how to respond. This study sheds light on the common frames used in corporate statements.Originality/valueNo studies to date have adopted a content analysis approach to assess the content of corporate activist statements. Examining the messages is important because, as more companies become increasingly vocal about social issues, stakeholders utilize this information to judge the sincerity of both the company and the message.

Relational cultivation strategies and community building on Fortune 500 company corporate blogs

PurposeAs the number of corporate blogs has continued to increase over the years, this study examines the use of relationship cultivation strategies of Fortune 500 companies on their corporate blogs. Moreover, it focuses on how companies use corporate blogs as interactive online communication channels to create a sense of community among their publics.Design/methodology/approachA content analysis of Fortune 500 company corporate blogs was conducted to examine the use of relational cultivation strategies and their methods of promoting a sense of community.FindingsFindings indicate that networking and sharing tasks are used most frequently among all relational cultivation strategies on corporate blogs, and that there are statistically significant differences among industries for using relationship cultivation strategies on corporate blogs. The most frequently used dimension of sense of community on corporate blogs is shared emotional connection.Originality/valueStudies analyzing social media as public relations tools have not yet focused on community building. In fact, few studies have examined the community building aspect of corporate blogs in the public relations field. To fill this gap, this study focuses on community building and analyzes how companies use corporate blogs as an interactive online communication channel to create a sense of community among their publics.

The Impact of Carbon Disclosure on Financial Performance under Low Carbon Constraints

In the context of low-carbon constrained development, in order to avoid the risk brought by climate change, more and more companies choose to disclose carbon information, respond to the national policy of carbon emission reduction and focus on the sustainable development of enterprises. This paper will investigate the impact of carbon disclosure on financial performance based on the 2011–2018 CDP report, taking the Fortune 500 companies as a sample. The study finds that for carbon-intensive industries, carbon disclosure cannot significantly contribute to the improvement of financial performance in the current period, but for carbon-non-intensive industries, carbon disclosure can significantly contribute to the improvement of financial performance in the current period, and the positive impact of carbon disclosure on financial performance in the current period can be extended to the next period. Finally, based on the findings of the empirical study, this paper puts forward policy recommendations for the construction of China’s carbon disclosure system.