There is a growing literature on how the beneficial impacts of horizontal mergers and acquisitions (M&A) should be measured. Thus far, however, there have been few studies addressing endogeneity between technical efficiency and value creation: they tend to present a bidirectional and simultaneous relationship. This research contributes to the debate by investigating the impact of voluntary horizontal M&A on these metrics in Nigeria between 1995 and 2012, in light of the individual performance of bidders, targets, and the resulting corporate companies. First, technical efficiency, technology gap ratio, and returns‐to‐scale estimates were computed based on a meta‐frontier DEA approach, together with a set of contextual variables that encompass performance indicators which reflect the value creation process. Then, robust regressions were used to discriminate these efficiency estimates in terms of such business‐related variables, correcting for endogeneity and controlling for industry and trend effects. The results reveal that these contextual variables significantly impact virtual efficiency and returns‐to‐scale levels, and that there is a trade‐off between efficiency and value creation at some point in the merging process. Managerial implications are derived.
ChatGPT, a language-learning model chatbot, has garnered considerable attention for its ability to respond to users’ questions. Using data from 14 countries and 186 institutions, we compare ChatGPT and student performance for 28,085 questions from accounting assessments and textbook test banks. As of January 2023, ChatGPT provides correct answers for 56.5 percent of questions and partially correct answers for an additional 9.4 percent of questions. When considering point values for questions, students significantly outperform ChatGPT with a 76.7 percent average on assessments compared to 47.5 percent for ChatGPT if no partial credit is awarded and 56.5 percent if partial credit is awarded. Still, ChatGPT performs better than the student average for 15.8 percent of assessments when we include partial credit. We provide evidence of how ChatGPT performs on different question types, accounting topics, class levels, open/closed assessments, and test bank questions. We also discuss implications for accounting education and research.
Purpose The purpose of this paper is to investigate the voluntary horizontal M&A impact on operating performance in Nigeria between 1995 and 2012 under different complementary approaches. Design/methodology/approach Residual income valuation (RIV), economic value-added (EVA), data envelopment analysis (DEA) and stochastic frontier analysis (SFA). Findings Results showed a statistically significant improvement in the technical efficiency of both bidder and target companies, the reduced efficiency levels of the bidder firms under DEA scores reveals the specifics of the productive technology. This may suggest that resulting merged companies in Nigeria may have not even become too big in scale or even reached the most productive scale size, despite their almost monopolistic position in the sector. This happens because the scale size of the sector is small per se, implying that the investments necessary to achieve synergistic gains have to be partially covered by price increases. Practical implications This study will guide both the M&A practitioners, investment banks, and the policy makes. In terms of having to review M&A policy as well as seeing to the improvement in the infrastructural needs. Social implications With improved performance, employment can be created thereby giving employment to the youths. This will reduce social problems. Originality/value From the literature and records, no long-term operating performance on voluntary mergers and acquisitions has not been carried out in Nigeria. The paper seeks to know the fundamental value of the firms after these transactions with the current methodology that is acceptable from the literature.
This research study measures Uber’s community support initiatives’ return on investment (ROI). The company examined is Uber Technologies Inc. (Uber), which donates time and resources to support communities in need after natural disasters or lack social support. This study will take a quantitative approach by measuring the value of Uber’s community support initiatives’ earned media. The research will use a case study analysis to investigate how companies like Uber generate and assess the ROI of their social enterprise investments. This research is timely as it speaks to the current discourse on practical ways for businesses to create social impact and how to measure that impact. In addition, the research will use a combination of primary and secondary sources. This study will collect primary data through social media, and the secondary data will come from media valuation indices and sentiment analysis. The findings of this study will have implications for both Uber and other companies that engage in community support initiatives. For Uber, this study will provide insights into how the company can optimize its community support initiatives to generate the most significant ROI. For other companies, this study will serve as a case study for effectively measuring the ROI of community support initiatives.
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