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Momentum strategies exhibit quarterly seasonality, earning significantly higher average strategy returns in the third month of the quarter than the first month. The authors evaluate the magnitude of quarterly seasonality in various momentum strategies to examine the relation between quarterly seasonality and risk-adjusted monthly returns.

The authors construct long-short portfolios for various types of momentum strategies and calculate the average returns of these portfolios in the three months of the quarter. They also calculate the average changes in institutional ownership across the different portfolios.

The authors demonstrate that quarterly seasonality is directly associated with quarterly changes in net purchases by institutional investors. Additionally, they show that near-term price momentum exhibits more seasonality than other momentum strategies, consistent with institutional investor incentives.

Researchers studying momentum should understand that quarterly seasonality increases the standard deviation of monthly returns for different types of momentum strategies.

Individual investors and investment managers should consider whether it is early or late in the calendar quarter when implementing momentum strategies.

Quarterly seasonality explains several seemingly independent findings in the momentum literature. In cases where researchers show one momentum strategy outperforms another on a risk-adjusted basis, the authors find that the superior strategy exhibits less quarterly seasonality. This pattern holds across types of momentum strategies, strategy formation periods and asset classes.

DuPont financial analysis is generally used in micro-economic studies to compare an individual firm’s financial performance with industry averages. The purpose of this paper is to undertake a macro-economic cross-sectional analysis of the determinants of return-on-equity (ROE) in USA, German and Japanese manufacturing firms.

The authors use cross-sectional log-linear multivariate regression analysis to determine the elasticity of ROE to changes in net profit margin (NPM), total assets turnover (TAT) and equity multiplier (EQM) in USA, German and Japanese manufacturing firms. The authors obtain the data for the analysis from the COMPUSTAT Research Insight/Global Vintage database.

With data for all manufacturing firms, the authors find that the most important determinant of ROE is NPM in all three countries. The least important determinant of ROE is TAT in the USA and Germany, and EQM in Japan. Electronics is the most important manufacturing industry in all three countries, the authors also apply the analysis to data for the electronics manufacturing firms in the three countries. The authors find that an increase of 10 percent in NPM increases ROE by about 9.8 percent in Germany, by about 8.3 percent in the USA, and by about 6.9 percent in Japan. An increase of 10 percent in TAT increases ROE by about 2.2 percent in Germany and by about 1.5 percent in Japan. An increase of 10 percent in EQM increases ROE by about 1.9 percent in Germany and by about 1.5 percent in the USA.

The empirical findings of this study can provide useful insights for financial managers regarding the determinants of ROE they should focus on to achieve the greatest impact on ROE.

DuPont analysis is generally used as a micro-economic tool at the firm level. This study is a macro-economic application of the tool to study the cross-sectional determinants of ROE at the industry level.

Blockchain possesses the potential to disrupt and reshape a plethora of industries in the next decade. However, blockchain adoption rates in technology developed countries, such as Ireland, are relatively low. Motivated by blockchain’s potential to transform sociotechnical systems, the lack of systematic inquiry pertaining to blockchain studies from an information system perspective, the authors propose the following research question: “How do organizational factors influence blockchain adoption in organizations based in a developed country?” Specifically, the purpose of this paper is to elucidate the impact of organizational factors on the adoption of blockchain and the adoption of blockchain in companies based in Ireland.

A comprehensive literature review was conducted, and the methods of qualitative content analysis were used to identify the most important technology–organization–environment (TOE) blockchain adoption factors. Organizational factors are often viewed as the most significant determinants of IT innovation adoption in organizations. Consequently, using a multiple-case study of 20 companies based in Ireland, the authors investigate how the top three organizational factors identified from the blockchain literature affected these companies decision to adopt or not adopt blockchain.

The literature review on blockchain adoption identified specific technological, organizational and environmental factors. Furthermore, the case study findings identified three patterns: top management support and organizational readiness are enablers for blockchain adoption, and large companies are more likely to adopt blockchain than small to medium-sized enterprises (SMEs). The authors explain these patterns by examining the nature of blockchain and the characteristics of Ireland as a developed country. Practical and scientific contributions are also presented.

This study makes several important scientific contributions. First, the findings revealed that top management support and organizational readiness are significant enablers of blockchain adoption. Ireland is recognized as a technology developed country; however, the findings in relation to top management support contradict existing IT adoption literature pertaining to developed countries. Second, previous IT innovation adoption literature suggests that organizations size has a positive influence on a company’s IT innovation adoption process. This study demonstrates that large organizations are more likely to not only adopt blockchain but are also more likely to conduct increased levels of blockchain research and development activities. Finally, and most significantly, the authors identified several patterns, which relate specifically to Ireland as a developed country that influenced the findings. These findings could hold particular relevance to governments and organizations of other developed countries in terms of accelerating blockchain adoption.

The findings about the low level of blockchain awareness and the lack of information pertaining to viable business use cases indicate that the Irish government could play a more significant role in promoting the benefits of blockchain technologies. Further, the findings could also encourage IT providers to formulate enhanced strategies aimed at disseminating information pertaining to blockchain technologies. Second, the positive influence of top management support and organizational readiness, particularly about core competencies, on blockchain adoption suggests that equipping managers with the requisite knowledge and skills will be crucial in adopting these IT innovations. Finally, organizations who adopted blockchain used cloud-based blockchain platforms and tools to overcome the constraints of their initial low levels of organizational readiness.

This is one of the first studies to identify specific TOE blockchain adoption factors. Further, the authors examine how the three most identified organizational adoption factors impact organizations decisions to adopt blockchain. Finally, the authors discuss how the resulting three patterns identified by examining the nature of blockchain and the characteristics of Ireland as a technology developed country.