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This study aims to examine the behavior of cash raised through market timing efforts and the success of such efforts in creating value to shareholders.

It is shown that in two quarters, subsequent to raising equity, cash balance of market timers is higher but after that, there is no significant difference between timers and non-timers. Results of speed of adjustment regressions indicate that market timers move faster toward their target cash levels.

Market timers are small firms that suffer from asymmetric information. They have limited access to capital market, and raising external capital is an opportunity that should be timed. The results suggest that, on average, these firms are managed by more able executives, who are 10 per cent more likely to time the market; however, it is found that timing efforts are unsuccessful in creating value to shareholders even after controlling for the mitigating effect of managerial ability. Subsequent to market timing, on average, market timers earn significantly lower abnormal return over different holding periods relative to their comparable non-timer counterparts.

Overall, the results undermine the validity of market timing as a value-maximizing financial policy.

After a seven-year period of being stuck in the zero lower bound (ZLB) range, the target rate was raised by 25 basis points on December 16, 2015. Prior to the rate hike, the important issues that the Federal Reserve dealt with were the magnitude, timing, and the information conveyed by a first-time rate hike from the ZLB period. The purpose of this paper is to use the data from the ZLB period and simulate the impact of an increase in the proxies for the federal funds rate: effective federal funds rate and shadow rate, and measure the impact on the resulting changes in credit default swap (CDS) spreads across 11 industries. Increases in both proxies predict a significant decrease in CDS spreads which is indicative of an economic recovery. This prediction is confirmed by the announcement effect of the actual rate increase on December 16, 2015 and the three subsequent rate increases.

In the absence of target rate changes in the ZLB environment, the authors use a recursive vector autoregressive (VAR) model to simulate the rate increases in proxies for target federal rate and predict the impact on the economy by observing the reaction in CDS spreads and stock returns across 11 industries.

The impulse response indicates that an increase of one standard deviation in the effective rate (approximately 25 basis points) results in a statistically significant decrease in the spreads of CDS contracts in 8 of the 11 sectors studied in this research. Similar results obtain for an increase in shadow rate thus providing a robustness check. These results suggest a rate increase from the ZLB period and the resulting dynamics captured in the VAR system is indicative of an economic recovery.

Prior studies have used the event study methodology to evaluate the impact of rate changes on credit spreads. The ZLB environment does not contain data on target rate changes and renders the event study methodology as ineffective. This paper is the first to simulate the implications of a first-time rate increase from the ZLB environment in the context of a recursive VAR model. The results are very helpful to the Federal Reserve of countries experiencing a ZLB environment such as Japan and Europe.

The purpose of this paper is to test whether investors take flight to safety when sentiment is low. In other words, do safe firms perform better than risky firms following periods of low sentiment.

Using cash flow volatility and the percent of bullish investors as proxies for risk and investor sentiment the paper tests the relationship between sentiment and returns conditional on risk this performance. Second, a cross-sectional analysis is conducted based on individual firm characteristics and sentiment to explain annual returns.

The paper finds that there is a negative relationship between investor sentiment and the return of risky companies, which is contrary to prior studies. All told, risky companies perform worse following periods of high investor sentiment.

This paper presents evidence contrary to extant literature and that there is no concerted flight to safety. Investor sentiment has little influence on safe stocks.

This study aimed to predict and understand the academic libraries' probability of successful adoption of blockchain within the lens of integrated technology acceptance model (TAM) and technology organization and environment theory (TOE) framework.

A mixed approach was employed to gather data from librarians (292) and system analysts (46) totaling 338 respondents. The total enumeration sampling technique was considered. Qualitative data were analyzed thematically, while quantitative data were analyzed using structural equation model (SEM).

Perceived usefulness and policy are the important factors that influence academic libraries' blockchain adoption intentions. Unlimited access to both print and electronic resources, security of users' information and easy collaboration between users and library staff were found to be the benefits of blockchain application to academic libraries' operations. Major challenges to the adoption of blockchain in academic libraries include the cost of infrastructure related to blockchain applications, privacy issues and a lack of understanding of blockchain technology among librarians.

Future studies would need to include more relevant items to the observed variables of the independent variables that were found insignificant in this study.

The findings of this study will create a roadmap for government and polytechnic management on the factors that could strengthen the adoption of blockchain in the libraries.

The outcome of this study came at a crucial moment when the majority of academic libraries in developing nations like Nigeria were skeptical about the deployment of blockchain technology in their libraries.

The study identified new factors that influence blockchain adoption intention.

This chapter has been seminal work of Dr K.S.S. Iyer, which has taken time to develop, for over the last 56 years to be presented here. The method in advance predictive analytics has developed, from his several other applications, in predictive modeling by using the stochastic point process technique. In the chapter on advance predictive analytics, Dr Iyer is collecting his approaches and generalizing it in this chapter. In this chapter, two of the techniques of stochastic point process known as Product Density and Random point process used in modelling problems in High energy particles and cancer, are redefined to suit problems currently in demand in IoT and customer equity in marketing (Iyer, Patil, & Chetlapalli, 2014b). This formulation arises from these techniques being used in different fields like energy requirement in Internet of Things (IoT) devices, growth of cancer cells, cosmic rays’ study, to customer equity and many more approaches.

This paper aims to investigate the implications of governance quality on a firm’s information environment in the context of voluntary changes in hedging disclosures made by oil and gas companies.

The research utilizes a Factiva-guided search to hand-collect public disclosures related to changes in hedging policies along with the hand collection of financial derivatives positions and operational hedging contracts data using 10-K filings. The paper addresses self-selection bias, which typically plagues voluntary disclosure studies, by implementing a Heckman (1979) two-step model to estimate the decision process, make changes in their hedge program and, conditional on making changes to their hedging activities, provide disclosure.

Oil and gas firms with relatively poor governance are more likely to voluntarily disclose hedging changes and do so more frequently (substitution hypothesis). There is evidence that poorly governed firms in the presence of large shareholders (i.e. high institutional ownership) are more likely to provide transparency of hedging policy changes.

This is the first study to combine hand-collected changes in hedging voluntary disclosures and hand-collected derivative position data to investigate the interaction of corporate governance and voluntary disclosure. The sample allows for analysis between three sub-samples: companies that do not make changes in hedging and do not hedge, firms that make changes in their hedging policies but do not disclose the changes during a given year and companies that change their hedging activities and provide voluntary disclosure. This unique setting helps to alleviate concerns of self-selection bias associated with voluntary disclosure.

A few nitrones such as N‐benzilidene aniline‐N‐oxide, N‐(O‐hydroxy benzilidene) aniline‐N‐oxide (HN) and N‐(α‐naphthylidene) aniline‐N‐oxide (NN) have been synthesised and investigated for evaluating their efficiency as inhibitors for the corrosion of mild steel in 1M HCl at different concentrations of nitrones ranging from 0.025‐1.0mM and at different temperatures ranging from 30‐70°C. Among these compounds NN gives the best performance even at higher temperatures. Potentiodynamic polarisation studies reveal the fact that all compounds behave as mixed type inhibitors. Hydrogen permeation studies reveal the fact that all the compounds bring down the permeation current. The absorption of these compounds on the mild steel surface from 1M HCl obeys Temkin’s absorption isotherm.

Time overrun is one of the most significant issues being faced by Ethiopian construction industry today. For effective time performance, the successful execution of construction projects and keeping them within prescribed schedule is very important. The purpose of this paper is to determine the factors responsible for impacting performance of Ethiopian public construction projects.

Based on the literature and personal interviews of key construction professionals in Ethiopia, a list of 35 project performance attributes having strong effect on performance of the projects were identified and a questionnaire using these attributes were prepared and administered in Ethiopia. Statistical analysis of responses on the attributes segregated them into distinct sets of success attributes and failure attributes. The attributes were also subjected to factor analysis separately for better understanding and it resulted into six success factors and six failure factors. The relative importance of these factors was established with multiple regression analysis.

It is concluded that the success factor “owners’ competence” can significantly contribute to schedule performance of Ethiopian public construction projects. On the other hand, “conflict among project participants,” “poor human resource management,” and “project manager’s ignorance and lack of knowledge” are detrimental to schedule performance of Ethiopian public construction project.

As with any other opinion-based study, the present study also has some limitations. The majority of respondents have evaluated the projects in their execution stage only and very few have evaluated the performance of projects in planning and operation stages and also the study has been carried out in the Ethiopian context. Hence the study has a limitation in these regard.

The results presented in this study provide sufficient evidence and useful understanding to researchers and industry practitioners to focus on a few factors than giving attention to all the factors and take proactive measures for the timely delivery of public construction projects.