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Today’s digital and mobile learning environment has contributed to the increased availability of and interest in e-textbooks, and many school systems are conducting trials to evaluate their effectiveness. The purpose of this paper is to identify and analyze instructors’ levels of use (LoU) of e-textbook features and innovations at a southeastern US community college. This study also evaluated the effectiveness of e-textbooks compared to paper textbooks on student achievement during a pilot period of e-textbook implementation.

Using a survey research design, the LoU of the Innovation framework was applied to identify and analyze instructors’ LoU rankings for eight e-textbook features. The study also used historical data on student demographics and final course grades to evaluate student achievement between text formats. Descriptive and inferential statistics were used to answer the research questions.

Results showed that e-textbook features were used at a low to non-existent level by instructors and that there was no significant difference in grade average between text formats among students. However, interactions between text format, age and gender were found.

This study added to the body of knowledge regarding e-textbook efficacy. While many studies stop with the conclusion that there is no difference in student outcomes between text formats, this study addressed a gap in literature on how to improve student performance with e-textbook technology by using the LoU of an innovation framework.

Building trust and living interpersonal trust are crucial corporate executive virtues that are needed today. Once you have developed and solidified a high level of genuine interpersonal trust with all your stakeholders, especially customers, suppliers, and employees, then you are on the right path of managing and transforming your company. A high level of interpersonal trust between all stakeholders and corporates in a business situation will break down communication barriers, foster serious conversation and sharing of ideas, and will eliminate corporate transactional anxieties of fear, mistrust, guilt, rigidity, blame, and resentment. When stakeholders trust you and you trust them, then you speak freely, they speak freely, and your mutual sustained transparency is a gateway to survival, revival, and sustained corporate recovery and transformation, and steady growth and prosperity. Conversely, when there is low trust, high mistrust, and high distrust among stakeholders in a business situation, communications and conversations are stressed and fragmented, teamwork and team spirit are very low, and the company is heading toward its ruin and extermination. Such is the crucial role of interpersonal trust in business. This chapter explores the crucial phenomenon of corporate interpersonal trust. We review various cases, models, concepts, definitions, and theories of trust from the management literature in general, and from the marketing field in particular, to derive psychological, behavioral, ethical, and moral principles of corporate trust, trusting relations, and trusting strategies.

Critics say cryptocurrencies are hard to predict and lack both economic value and accounting standards, while supporters argue they are revolutionary financial technology and a new asset class. This study aims to help accounting and financial modelers compare cryptocurrencies with other asset classes (such as gold, stocks and bond markets) and develop cryptocurrency forecast models.

Daily data from 12/31/2013 to 08/01/2020 (including the COVID-19 pandemic period) for the top six cryptocurrencies that constitute 80% of the market are used. Cryptocurrency price, return and volatility are forecasted using five traditional econometric techniques: pooled ordinary least squares (OLS) regression, fixed-effect model (FEM), random-effect model (REM), panel vector error correction model (VECM) and generalized autoregressive conditional heteroskedasticity (GARCH). Fama and French's five-factor analysis, a frequently used method to study stock returns, is conducted on cryptocurrency returns in a panel-data setting. Finally, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to a portfolio makes a difference.

The seven findings in this analysis are summarized as follows: (1) VECM produces the best out-of-sample price forecast of cryptocurrency prices; (2) cryptocurrencies are unlike cash for accounting purposes as they are very volatile: the standard deviations of daily returns are several times larger than those of the other financial assets; (3) cryptocurrencies are not a substitute for gold as a safe-haven asset; (4) the five most significant determinants of cryptocurrency daily returns are emerging markets stock index, S&P 500 stock index, return on gold, volatility of daily returns and the volatility index (VIX); (5) their return volatility is persistent and can be forecasted using the GARCH model; (6) in a portfolio setting, cryptocurrencies exhibit negative alpha, high beta, similar to small and growth stocks and (7) a cryptocurrency portfolio offers more portfolio choices for investors and resembles a levered portfolio.

One of the tasks of the financial econometrics profession is building pro forma models that meet accounting standards and satisfy auditors. This paper undertook such activity by deploying traditional financial econometric methods and applying them to an emerging cryptocurrency asset class.

This paper attempts to contribute to the existing academic literature in three ways: Pro forma models for price forecasting: five established traditional econometric techniques (as opposed to novel methods) are deployed to forecast prices; Cryptocurrency as a group: instead of analyzing one currency at a time and running the risk of missing out on cross-sectional effects (as done by most other researchers), the top-six cryptocurrencies constitute 80% of the market, are analyzed together as a group using panel-data methods; Cryptocurrencies as financial assets in a portfolio: To understand the linkages between cryptocurrencies and traditional portfolio characteristics, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to an investment portfolio makes a difference.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.