Search results

This study aims to measure impact of several firm-specific factors on alternative measures of leverage. The authors also aim to study impact of the subprime crisis on such associations.

The authors utilized an unbalanced panel data of 973 firm-year observations on 47 UK listed non-financial firms for the years 1990–2019. Book-based and market-based long-term and total leverage measures have been used as explained variables. The explanatory variables are profitability, size, two measures of growth, asset tangibility, non-debt tax shields, firm age and product uniqueness. Fixed effect and random effect models with clustered robust standard errors have been utilized for data analysis. To find the effect of subprime crisis, original dataset was split to create pre-crisis and post-crisis datasets.

The authors find that profitability significantly reduces leverage while firms having more tangible assets use significantly more debt in capital structure. Firm size and non-debt tax shield have statistically insignificant positive impact on leverage. Having more unique products reduces use of external debt, albeit insignificantly. Growth, when measured as market-to-book ratio, has inconsistent impact, whereas capital expenditure insignificantly reduces leverage. Age is found to be an insignificant predictor of leverage. After the subprime crisis, firms started relying more on internal fund instead of external debt, more particularly short-term debt. Having more collateral is gradually becoming more important for availing external debt.

Data limitations restrict generalization of the findings.

This is one of the pioneering attempts to show how subprime crisis altered the theoretical domain of capital structure research in the UK.

A new dual‐rail adiabatic logic family is proposed in this paper. Modified dual‐rail improved adiabatic pseudo domino logic with high throughput (MDIAPDL‐HT) is an improved adiabatic logic design aimed at low power and high throughput performance. The basic structure is the same as the MDIAPDL, but with a different clocking system. This results in power savings up to 95 percent compared to the static CMOS. It has higher throughput with a factor of about four compared to MDIAPDL and a factor of two compared to 4ϕ‐IAPDL.

This study aims to identify the gaps in current policy and propose a viable framework for policy improvement regarding people-centered tsunami early warning chain in Padang City. The objectives are: to describe the gaps and flaws in the current policy regarding local tsunami early warning chain, to identify potential actors to be involved in the tsunami early warning chain and to assess the roles and capacity of actors, and their potential for involvement in early warning.

This study is an exploratory study using social network analysis (SNA) on regulations and other legal documents, and primary data sources from a focus group discussion and semi-structured interviews.

The study found that the existed regulation lacks extension nodes to relay warnings to the populations at risk, often referred to as “the last mile.” Moreover, receiving warning information from both formal and informal sources is important to mobilize people evacuation more effectively during an emergency. The study found that mosque communities and disaster preparedness leaders are the potential actors who should be involved in the local early warning chain.

The research findings were presented as a recommendation to Padang City Government and have been legalized as the new tsunami early warning chain procedure in the Padang City Mayor Regulation 19/2018.

This research investigated local tsunami early warning dissemination in Padang City using SNA. The study demonstrates a close collaboration between researchers, practitioners and the community.

This article assesses the state of cash flow reporting by listed South African industrial companies in order to evaluate whether the users of financial statements can accept them as being reliable and use them as a tool to compare the operating performance of various companies. As the cash flow statement has been in use since 1989, it was envisaged that compliance would be high. However, it was found that there are several companies that deviate from some of the requirements of AC 118 regarding cash flow statements.

This paper investigates a problem in a reverse logistics (RLs) network to decide whether to dispose of unsold goods in primary stores or re-commercialize them in outlet centers. By deducting the costs associated with each policy from its revenue, this study aims to maximize the profit from managing unsold goods.

A new mixed-integer linear programming model has been developed to address the problem, which considers the selling prices of products in primary and secondary stores and the costs of transportation, cross-docking and returning unwanted items. As a result of uncertain nature of the cost and time parameters, gray numbers are used to deal with it. In addition, an innovative uncertain solution approach for gray programming problems is presented that considers objective function satisfaction level as an indicator of optimism.

According to the results, higher costs, including transportation, cross-docking and return costs, make sending goods to outlet centers unprofitable and more goods are disposed of in primary stores. Prices in primary and secondary stores heavily influence the number of discarded goods. Higher prices in primary stores result in more disposed of goods, while higher prices in secondary stores result in fewer. As a result of the proposed method, the objective function satisfaction level can be viewed as a measure of optimism.

An integral contribution of this study is developing a new mixed-integer linear programming model for selecting the appropriate goods for re-commercialization and choosing the best outlet center based on the products' price and total profit. Another novelty of the proposed model is considering the matching percentage of boxes with secondary stores’ desired product lists and the probability of returning goods due to non-compliance with delivery dates. Moreover, a new uncertain solution approach is developed to solve mathematical programming problems with gray parameters.

This study aims to identify the ability of gold and cryptocurrency (Cryptocurrency Uncertainty Index (UCRY) Price) as safe haven assets (SHA) for stocks and bonds in both conventional (i.e. stock indices and government bonds) and Islamic markets (i.e. Islamic stock indices and Islamic bonds (IB)).

The authors employed the nonadditive panel quantile regression model by Powell (2016). It measured the safe haven characteristics of gold and UCRY Price for stock indices, government bonds, Islamic stocks, and IB under gold circumstances and level of cryptocurrency uncertainty, respectively. The period spanned from 11 March 2020 to 31 December 2021.

This study discovered three findings, including: (1) gold is a strong safe haven for stocks and bonds in conventional and Islamic markets under bearish conditions; (2) UCRY Price is a strong safe haven for conventional stocks and bonds but only a weak safe haven for Islamic stocks under high crypto uncertainty; and (3) gold offers a safe haven in both emerging and developed countries, while UCRY Price provides a better safe haven in developed than in emerging countries.

Gold always wins big for safe haven properties during unstable economy. It can also win over investors who consider shariah compliant products. Therefore, it should be included in an investor's portfolio. Meanwhile, cryptocurrencies are more common for developed countries. Thus, the governments and regulators of emerging countries need to provide more guidance around cryptocurrency so that the societies have better literacy. On top of that, the investors can consider crypto to mitigate risks but with limited safe haven functions.

The originality aspects of this study include: (1) four chosen assets from conventional and Islamic markets altogether (i.e. stock indices, government bonds, Islamic stock indices and IB); (2) indicator countries selected based on the most used and owned cryptocurrencies for the SHA study; and (3) the utilization of UCRY Price as a crypto indicator and a further examination of the SHA study toward four financial assets.

The purpose of this study is to provide an extensive bibliometric literature review on authentic leadership as a term and concepts to deliver authentic leadership research with Publish and Perish (PoP) software, Mendeley software, and databases from Google Scholar index. Article located through PoP software based on a Scopus index database. A total of 122 articles refined and analyzed from various qualifying journals starts on January 1999 to December 2018 (20 years). The Mendeley software is used to help manage the references and brief resumes of each article. This chapter presents five clusters to review authentic leadership literature. The clustering process assisted by the VOSviewer software by matching words that often appear in each group, namely antecedents, commitment, performance, positive effects, organizational behavior, and leadership effectiveness. Each of these clusters shows authentic leadership research areas. The five clusters produced through the VOSviewer software provide an overview and research stream of the authentic leadership. Researchers and practitioners need to pay attention to trends and research areas in authentic leadership for improving authentic leadership development.

The purpose of this paper is to describe the design and delivery of a lesson study unit in mathematics to pre-service primary teachers and to identify the opportunities and challenges resulting from the need to deliver the unit wholly online due to the COVID-19 pandemic.

Cross-case analysis, using a before-and-after design, was used to compare the development and delivery of the unit in 2019 and 2020, with the pivotal event of interest between the before-and-after cases being the onset of the COVID-19 pandemic.

The content and structure of the unit, as well as its collaborative aspects, remained substantially the same in the before-and-after cases. While there was a low level of engagement with pre-recorded lectures, there was a high level of engagement and participation in the online synchronous seminars, together with a marked increase in overall satisfaction with the unit. Pre-service teachers were unable to teach and observe one another's planned research lessons in school. Instead, after a detailed examination of the task, the lesson plan and student solutions, they observed a pre-recorded video of a research lesson at a local school and participated in a streamed post-lesson discussion. Pre-service teachers regarded this new component as a highlight of the unit and an important connection between the theory and practice of lesson study.

The inclusion of the video-recorded research lesson in 2020 introduced a new level of authenticity for pre-service teachers, allowing them to observe a high quality structured problem solving mathematics lesson taught in a local public school, as part of a local implementation of lesson study-something that is not generally possible. While there is often a view that the benefits of lesson study result mainly from collaborative planning and teaching of the research lesson, this paper highlights the value of involvement for all participants in research lesson observation and post-lesson discussion, as well as the opportunities afforded by the use of “virtual lesson study”.

This paper reviews studies that have examined how accounting information impacts commercial lending judgments. Issues discussed involve the usefulness of accounting data in lending decisions, effects of different accounting methods on lenders’ judgments, bankruptcy and default judgments, and decision processes pertaining to the use of accounting information in lending decisions. Additionally, the paper reviews the research on how audits and other forms of assurance influence commercial loan officers’ judgments. Topics include the way perceived auditor independence influences loan officers’ judgments, the impact of financial statement audits and audit opinions on lending decisions, how internal control reports and other CPA firm reports influence loan decisions, ways in which audit report disclosures and wording impact lending decisions, how perceived auditor quality affects lending decisions, and the effects of limited assurance engagements on loan officers’ judgments.

Purpose: The purpose of this chapter is to elaborate on the major conceptual and practical considerations of the use of robots, artificial intelligence and service automation (RAISA) in travel, tourism, and hospitality companies (TTH).

Design/methodology/approach: The chapter develops a conceptual framework of the major issues related to the use of RAISA in the travel, tourism and hospitality context.

Findings: The findings indicate that while there is a creeping incursion of RAISA into TTH, there are major concerns that the TTH industry has to consider in regard to automating TTH services.

Practical implications: In a practical sense, the chapter identifies the decisions that TTH industry professionals need to take when dealing with RAISA technologies. Furthermore, the chapter elaborates on the impacts RAISA have on business operations, marketing management, human resources and financial management of TTH companies. The TTH industry has to adjust its practices and communicate with its workforce in ways as not to increase Luddite tendencies and resistance among employees.

Social implications: The analysis shows that there is an upcoming era in which automation of services will be so advanced that wealthy countries may not need to import labour to make up with its own aging workforce, suggesting that RAISA and its further development has the potential for disrupting society and international relations.

Originality/value: This chapter provides a comprehensive review of the issues related to the use of RAISA in the TTH industry, including the drivers of RAISA adoption in tourism, advantages and disadvantages of RAISA technologies compared to human employees, decisions that managers need to take, and the impacts of RAISA on business processes. It shows how macroenvironmental pressures shape the microeconomic decisions to use RAISA in a TTH context.