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.

Frenemies: Overcoming Audiences’ Ideological Opposition to Firm–Activist Collaborations

Collaborations between organizations from different sectors, such as those between firms and nonprofits or governments, can offer effective solutions to complex societal problems like climate change. But complications arise because organizations operating in different sectors rely on the approval of different audiences, who may not view these relationships positively, for resources and survival. I show how concerns about audience approval impede cross-sector collaborations forming between firms and social movement organizations (SMOs) despite their potential societal benefits. Firms wanting to signal their efforts in support of a movement’s cause may be eager to form collaborations with SMOs. But when SMOs’ supporters and/or peers define their identity in opposition to firms—when they are oppositional audiences—collaborations do not form. I argue and find that SMOs who cooperate, and don’t compete, with oppositional peers can better navigate the constraint of oppositional audiences. Firms, in contrast, aggravate the constraint of oppositional audiences. Firms’ inclination to seek collaborations to repair their reputations with their own audiences after being contentiously targeted by a movement compounds the challenge to SMOs of partnering with the enemies of their friends. My arguments on countervailing audience effects stifling collaborations are corroborated in 25 years of data on interactions between SMOs in multiple environmental movements and Fortune 500 firms.

My Manager Moved! Manager Mobility and Subordinates’ Career Outcomes

How do managers’ moves across jobs affect the subordinates they leave behind? Manager mobility disrupts established manager-subordinate relationships, as subordinates must now learn to work with a replacement. We explore how this relational disruption affects subordinates’ objective career success—specifically, their financial rewards and subsequent promotion chances. We argue that manager mobility may have both positive and negative implications for subordinate outcomes. The loss of an established relationship may reduce subordinates’ performance and managers’ propensity to reward them; on the other hand, relational disruption may make subordinates more willing and able to seek out valuable opportunities elsewhere in the organization. We also argue that these effects are likely to be greatest for those subordinates who had worked with the previous manager for longer. Using eight years of personnel data from the U.S. offices of a Fortune 500 healthcare company, we show how managers’ mobility is associated with a decrease in subordinates’ financial rewards but an increase in their promotion prospects.

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.