Search results

The equation of unified knowledge says that S = f (A,P) which means that the practical solution to a given problem is a function of the existing, empirical, actual realities and the future, potential, best possible conditions of general stable equilibrium which both pure and practical reason, exhaustive in the Kantian sense, show as being within the realm of potential realities beyond any doubt. The first classical revolution in economic thinking, included in factor “P” of the equation, conceived the economic and financial problems in terms of a model of ideal conditions of stable equilibrium but neglected the full consideration of the existing, actual conditions. That is the main reason why, in the end, it failed. The second modern revolution, included in factor “A” of the equation, conceived the economic and financial problems in terms of the existing, actual conditions, usually in disequilibrium or unstable equilibrium (in case of stagnation) and neglected the sense of right direction expressed in factor “P” or the realization of general, stable equilibrium. That is the main reason why the modern revolution failed in the past and is failing in front of our eyes in the present. The equation of unified knowledge, perceived as a sui generis synthesis between classical and modern thinking has been applied rigorously and systematically in writing the enclosed American‐British economic, monetary, financial and social stabilization plans. In the final analysis, a new economic philosophy, based on a synthesis between classical and modern thinking, called here the new economics of unified knowledge, is applied to solve the malaise of the twentieth century which resulted from a confusion between thinking in terms of stable equilibrium on the one hand and disequilibrium or unstable equilibrium on the other.

Develops an original 12‐step management of technology protocol and applies it to 51 applications which range from Du Pont’s failure in Nylon to the Single Online Trade Exchange for Auto Parts procurement by GM, Ford, Daimler‐Chrysler and Renault‐Nissan. Provides many case studies with regards to the adoption of technology and describes seven chief technology officer characteristics. Discusses common errors when companies invest in technology and considers the probabilities of success. Provides 175 questions and answers to reinforce the concepts introduced. States that this substantial journal is aimed primarily at the present and potential chief technology officer to assist their survival and success in national and international markets.

This study analyzes the policy initiatives that have been adopted by the US government since the 1930s. We document the institutional bodies responsible for the implementation of trade policy, as well as the objectives and decision making practices that are associated with policy formation. We also examine the new institutional movement of the Trump Administration’s neo-protectionist “America First” trade policy and its potential impact on the Asian region. Finally, our study examines the recent renegotiation of Korea-US FTA from a perspective of each country’s internal decision making process and discusses a number of issues that have relevant applications for Korea. The results from our analysis show that U.S trade policy show that despite a long period of an open and liberalized trade policy focus, recent neo-protectionist measures by President Trump could lead to potential trade wars and a return to the beggar-thy-neighbor policies of the 1930s. Such an anti-globalization agenda could have dire consequences for export dependent countries in the Asian region.

This paper explores the effects of US President Donald Trump's Twitter messages (tweets) on the stock prices of media and non-media companies.

The authors’ empirical analysis considers all Twitter messages posted by Donald Trump from May 26, 2016 (the date he passed the threshold of 1,237 delegates required to guarantee his presidential nomination) to August 30, 2018. The authors accessed President Trump's tweets through http://www.trumptwitterarchive.com, which provides links to all Twitter messages the President has ever posted. Of the 6,983 presidential tweets during our sample period, the authors select 513 messages that mention companies that are publicly traded in the United States for this study. The selected messages are then classified as having a positive, neutral or negative sentiment. The authors employ a series of univariate and multivariate tests as well as Heckman two-step regressions and partial least squares regressions to examine the effect of the President's tweets on the stock prices of the firms he tweets about.

For media firms, the authors find that positive tweets have a pronounced positive stock price impact, whereas negative and neutral tweets have little or no effect. For non-media firms, the authors observe the opposite: negative tweets tend to be associated with significant stock price declines, whereas neutral and positive tweets incur weakly positive stock price reactions. To a large extent, these stock price declines reverse on the following day. The authors further find that the President's reiteration of information that is already known by the market incurs an additional stock price reaction. The President's attitude towards the news appears to play a major role in this context.

The authors contribute to the literature by offering various new insights regarding the effect social media has on the stock markets. In addition, this paper expands the emerging strand of literature that explores how President Trump affects the stock prices of firms he tweets about. This paper differs from prior studies in this area by considering a broader range of tweets, by controlling for potential selection biases, by differentiating between Trump's tweets about media and non-media firms and by exploring the impact of “old” vs “new” news based on whether the President repeats information that is already known to the market. If social media posts by single influential people are found to affect markets, they may create trading opportunities for investors and financial managers and risk arbitrage opportunities for arbitrageurs. In the political science field, the findings of this research provide valuable insights into how politicians can employ social media platforms to affect the public, and the differential influence of nominees and politicians in office. Finally, our study gives corporations that wish to back a certain campaign or a candidate in an election a better idea of the possible risks and benefits of their actions, considering that candidates or politicians could post negative messages on social media platforms targeting companies that backed their opponents.

This paper seeks to address the question: should the world's top universities be led by top researchers, and are they?

The lifetime citations are counted by hand of the leaders of the world's top 100 universities identified in a global university ranking. These numbers are then normalised by adjusting for the different citation conventions across academic disciplines. Two statistical measures are used – Pearson's correlation coefficient and Spearman's ρ.

This study documents a positive correlation between the lifetime citations of a university's president and the position of that university in the global ranking. Better universities are run by better researchers. The results are not driven by outliers. That the top universities in the world – who have the widest choice of candidates – systematically appoint top researchers as their vice chancellors and presidents seems important to understand. This paper also shows that the pattern of presidents' life‐time citations follows a version of Lotka's power law.

There are two main areas of contribution. First, this paper attempts to use bibliometric data to address a performance‐related question of a type not seen before (to the author's knowledge). Second, despite the importance of research to research universities – as described in many mission‐statements – no studies currently exist that ask whether it matters if the head of a research university is himself or herself a committed researcher. Given the importance of universities in the world, and the difficulty that many have in appointing leaders, this question seems pertinent.

The purpose of this study was to explore issues of gender and diversity raised by the 2020 US presidential election.

Samples from two populations (n = 667) described either an ideal president or one of the major-party candidates for president (Donald Trump and Joe Biden) or vice president (Mike Pence and Kamala Harris) on an instrument that assessed self-ascribed masculinity and femininity. Androgyny was calculated as the difference between masculinity and femininity; the closer the score to zero, the more androgynous the candidate.

The ideal president was viewed as androgynous (i.e. balanced in masculine and feminine traits) rather than masculine as in previous studies of presidential leadership. Compared to the White male candidates, Harris, a woman of color, displayed the most androgynous profile. The Democratic ticket represented a “balanced” team, with one candidate (Biden) higher on femininity and the other (Harris) higher on masculinity; in essence, an androgynous ticket. In contrast, the Republican ticket (Trump and Pence) represented a decidedly masculine ticket. Ideal president profiles differed according to respondents’ gender and preferred president.

The Democrats winning the election with an androgynous ticket suggests that a more level playing field for female vis-à-vis male candidates for political leader roles may be arriving.

The finding of an ideal president as androgynous rather than masculine is an original contribution to the literature on presidential leadership.

In both 2007 and 2012 the American Council on Education (ACE) issued reports on the American college president. Each described the demographic characteristics of presidents and the demands of the job. Although these reports provided important information on college presidents nationwide, they focused too little on Latino presidents and the unique barriers those aspiring to the position face on the path to the presidency. Such drawbacks are not uncommon, considering the dearth of basic research on Latino leadership in higher education in general and Latino presidents in particular, along with the fact that many work in the relative obscurity of two-year community colleges. Moreover, such data as exist on Latino presidents tend to be outdated (de los Santos, Jr. & Vega, 2008).

With these large gaps in mind, we invited Latino presidents to describe their rise in academia in the context of their family and community. We reviewed their personal stories for common themes and identified six that we want to highlight: (1) strong family support for education; (2) commitment to education and character at an early age; (3) overcoming discouragement by gatekeepers, (4) the importance of mentoring; (5) the need of Latina presidents to address special issues; and (6) giving back to the Latino community. A description of each theme is presented later in the chapter, and we have integrated a few quotes from these presidents into our brief review of the literature.

Using the methodologies of text mining, this paper examines the implications of US and Chinese policies on bilateral trade. Official speeches by political leaders of the U.S. and China on the issues of trade were collected and analytically examined for US-China gaps in major foreign policies, such as bilateral trade and the Belt and Road Initiative. In this paper, a term frequency-inverse document frequency word cloud, a network similarities index, machine learning-processed latent Dirichlet allocation (LDA), and structural equivalence are applied to examine the meanings of the speeches. The main arguments in this paper are as follows. First, the document similarity between the speeches of Chinese and US leaders appears to be completely different. Also, while the documents from Chinese leaders are considerably similar, the documents from US leaders differ by far. Secondly, LDA topic analysis indicates that China concentrates more on international and collaborative relationships, while the U.S. has more focus on domestic and economic interests. Third, from a word hierarchy analysis, the basic words used by American and Chinese leaders are also completely different. Agriculture, farmers, automobiles, and negotiations are the basic words for American leaders, but for Chinese leaders, the basic words are planning, markets, and education.

The purpose of this paper is to examine the shifts in investor sentiment around the last seven US presidential elections (1988 through 2012).

Investor sentiment is measured by changes in closed-end funds discounts, and the results are corroborated with three robustness tests, including an alternate measure of investor sentiment obtained from the survey conducted by the American Association of Individual Investors.

Closed­end funds discounts are significantly diminished from two weeks before a US presidential election to a week before the election, and persist until the week after the election, suggesting an increase in investors’ optimism during that period, particularly when a Democrat is elected president. More than the particular party prevailing, however, investors appear to be more interested in avoiding the entrenchment of power since the results suggest that they become optimistic when a change in the ruling party takes place, but become pessimistic when there is power continuity in the White House. The increase in investor optimism that is observed around the time of US presidential elections is not replicated during non-election years, which seems to corroborate that the elections are indeed driving the results.

This paper is the first to formally examine the relation between investor sentiment and US presidential elections using closed-end funds discounts as the measure for sentiment.