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This paper aims to address the fundamentals of tax planning and seeks to focus on the opportunities and root causes for tax planning.

The paper reviews the current state of tax planning with case studies that reveal fundamental statutory structural opportunities.

While some, possibly many, tax advisers lack integrity and recommend tax structures to their clients that are inconsistent with reasonable interpretations of the tax law, most advisers, even very aggressive and creative advisers, probably do not. The paper suggests that it may be futile to seek to deter tax professionals from designing and marketing tax plans unless legislation makes tax advisers jointly responsible with their clients for their clients’ tax underpayments.

Short of such a radical approach, governments must commit first to altering the basic structure of their tax laws to make aggressive tax planning uninviting.

The paper offers original insights into the inseparability of the legislative process from the creation of unnecessary tax planning opportunities.

This paper aims to explore the common ethical decision-making challenges faced by financial advisers and how they meet these challenges. The purpose is to identify successful decision-making tools used by investment advisers in doing business ethically. Additionally, the authors uncover common challenges and offer decision-making tools to provide support for supplemental ethics training in the future.

Questions were analyzed through a qualitative approach using individual interviews to examine a range of experiences and attitudes of active financial advisers. The sample was represented by 11 practicing financial advisers affiliated with US independent broker-dealers: six women and five men, each with 10 or more years of experience, ranging in age from 35 to 75. Grounded in four ethical decision-making models, this research examines individual ethical decision-making using individual (internal, personal) and organizational (external, situational) factors.

The method used uncovered struggles and revealed strategies used in making ethical decisions. Two research questions were examined: what are the common ethical decision-making challenges faced by financial advisers in the US financial industry? How do financial advisers handle ethical decision-making challenges? Four themes emerged that impacted ethical decision-making: needs of the individual, needs of others, needs of the firm and needs of the marketplace. Financial advisers identified moral obligation, self-control and consulting with others as major considerations when they contemplate difficult decisions.

A limitation of this review is its small sample size. A more robust sample size from investment advisers with a broader range of experiences could have widened the findings from the study.

Investment advisers can use the findings of this study as a tool for improving their own ethical decision-making or designing training for their employees to be better decision-makers.

The study explores the decision-making experiences of investment advisers to reveal multifaceted, often private struggles that qualitative methods can uncover. The study provides support for the development of additional training in ethical decision-making specific to investment advisers.

The COVID-19 pandemic resulted in economic and financial hardships on firms, forcing them to make tough decisions regarding their social and ethical behavior. The purpose of this study is to examine whether the COVID-19 pandemic affected the corporate social responsibility (CSR) performance and disclosures of the US S&P 500 firms. In particular, this study examined the relationship between both CSR performance and COVID-19 and the relationship between CSR disclosures and COVID-19 along with the dimensions of environmental, social, and governance. Using t-tests and panel data analysis for the years 2018 through 2021, we found that CSR performance and CSR disclosure increased after the start of the pandemic for total CSR and for the dimensions of environmental, social, and governance. We also found that CSR performance was impacted by a larger change than CSR disclosures for all dimensions of CSR. This study is one of the first to examine the impact of COVID-19 on CSR and helps stakeholders understand the role that it played on firm decisions. The results further illustrate the importance that firms’ managements place on CSR performance and disclosures, even during a time of significant challenge and uncertainty.

This study aims to provide measurable information that evaluates a company’s ESG performance based on the conceptual connection between ESG, non-financial elements of a company and the UN Sustainable Development Goals (SDGs) for resolving global issues.

A novel data processing method based on the BERT is presented and applied to analyze the changes and characteristics of SDG-related ESG texts from companies’ disclosures over the past decade. Specifically, ESG-related sentences are extracted from 93,277 Form 10-K filings disclosed between 2010 and 2022 and the similarity between these extracted sentences and SDGs statements is calculated through sentence transformers. A classifier is created by fine-tuning FinBERT, a financial domain-specific pre-trained language model, to classify the sentences into eight ESG classes.

The quantified results obtained from the classifier reveal several implications. First, it is observed that the trend of SDG-related ESG sentences shows a slow and steady increase over the past decade. Second, large-cap companies relatively have a greater amount of SDG-related ESG disclosures than small-cap companies. Third, significant events such as the COVID-19 pandemic greatly impact the changes in disclosure content.

This study presents a novel approach to textual analysis using neural network-based language models such as BERT. The results of this study provide meaningful information and insights for investors in socially responsible investment and sustainable investment and suggest that corporations need a long-term plan regarding ESG disclosures.

The study aims to investigate market reactions associated with the JUST 100 rankings published by JUST Capital, a non-profit organization, as well as differences in financial reporting quality and performance between selected firms and their industry peers.

This study uses a sample of 431 firms selected as the 100 America’s Most Just Companies between 2016 and 2020 by JUST Capital. This study performs both an event study to determine whether the rankings are useful to investors and cross-sectional regression analyses on the characteristics of selected firms compared to their peers.

This study finds that investors react positively to selected firms around the time of the release of the JUST 100 rankings, suggesting that the rankings are decision-useful. This study also finds that selected firms exhibit higher accounting quality and financial performance than their peers.

Rankings may not be free from bias because of JUST Capital’s ownership of an exchange-traded fund.

The findings validate the rankings as well as the methodology used by JUST Capital, as they show market participants value firms that engage in socially responsible actions through their commitment to positively impact five key stakeholder groups: employees, customers, communities, environment and shareholders.

To the best of the authors’ knowledge, this is the first study that shows the importance of the JUST 100 rankings for investment decisions. Considering the growing push for companies to disclose environmental, social and governance (ESG) activities, this study provides evidence to support ESG disclosure regulations.

In recent years, investing with robo-advisors has gained momentum and is seen as a simplifying approach for individual investors to participate in financial markets. This chapter contributes to a better understanding of the concept of a robo-advisory and its implications for private investors by discussing its past, present, and future. It explores key issues, like cost-efficiency, historical performance, and automation levels, based on research and industry insights. Moreover, this chapter examines a robo-advisor's benefits, limitations, and challenges, like behavioral biases, regulation, and risk profiling. Finally, the importance of the ongoing megatrends of AI and green investing is examined concerning a robo-advisory.

This study examines the Robo-Advisors (RA) based on Artificial Intelligence (AI), a new service that digitises and automates investment decisions in the financial and banking industries to provide low-cost and personalised financial advice. The RAs use objective algorithms to select portfolios, reduce behavioural biases, and improve transactions. They are inexpensive, accessible, and transparent platforms. Objective algorithms improve the believability of portfolio selection.

This study adopts a qualitative approach consisting of an exploratory examination of seven different RA case studies and analyses the RA platforms used in the banking industry.

The findings provide two different approaches to running a business that are appropriate for either fully automated or hybrid RAs through the realisation of two platform model frameworks. The research reveals that relying solely on algorithms and not including any services involving human interaction in a company model is inadequate to meet the requirements of customers in decision-making.

This study emphasises key robo-advisory features, such as investor profiling, asset allocation, investment strategies, portfolio rebalancing, and performance evaluation. These features provide managers and practitioners with new information on enhancing client satisfaction, improving services, and adjusting to dynamic market demands.

This study fills the research gap related to the analysis of RA platform models by providing a meticulous analysis of two different types of RAs, namely, fully automated and hybrid, which have not received adequate attention in the literature.

This study aims to espouse the concept of sustainable environment, social and governance (ESG) practices as the proxies of sustainability reporting (SR). In the presence of smart technology adoption (STA), ESG drives total quality management (TQM) of sustainability matters in advanced medical device (AMD) companies post-pandemic.

This study uses two stages of rigorous data collection. Two focus groups comprising board members, investment advisers and senior managers of AMD were formed to establish the external validity of the constructs proposition. It then used a Web survey to solicit 240 respondents from AMD. Data were analysed using the partial least squares structural equation modelling (PLS-SEM) to provide robustness of predictive power in the model estimation.

Results show SR has positively impacted TQM. It reveals positive relationships between SR and ESG and ESG and TQM. Findings indicate that STA moderates the relationships between ESG and TQM with large effect sizes.

This study offers direction to expedite strategies and action plans by sustainability practitioners in an asymptotic quest for ESG and TQM best practices. Future research should focus on the protection of sustainable social using qualitative methodology.

Using the lens of corporate sustainability, this study develops a framework that integrates ESG, TQM and STA to examine the synergistic effects post pandemic. It provides evidence that ESG practices and STA adoption drive TQM in transition to attain sustainability among the AMD at the country level.

As an alternative to hiring financial specialists or investment consultants, robo-advisors offer financially automated investment services. This study aims to investigate how robo-advisors' service attributes, risk attitude and financial self-efficacy influence customers' choice preferences of adopting robo-advisors.

Two hundred fifty-one online surveys were used to collect data, and choice-based conjoint analysis was conducted.

Results show that increasing annual fees negatively impact customers' choice preferences. Promotion, general investment education and additional human assistance have a positive impact. Furthermore, risk-seeking and risk-averse customers require more human assistance than risk-neutral customer and customers with high levels of financial self-efficacy prefer more general investment education and additional human assistance than those with lower levels. In addition, customers in the older age group prefer promotion, general investment education and additional human assistance, while wealthy customers prefer lower annual fees, higher general investment education and more additional human assistance compared to middle-class and low-income groups.

This study contributes to robo-advisor providers to provide appropriate service attributes for each customer group.

This study explores the association between institutional investors’ stewardship activity, disclosed under Japan’s Stewardship Code, and the R&D investments of their investee companies.

Recognizing the pivotal role of R&D investment in long-term value creation, this study uses comprehensive data from institutional investor disclosures to assess the impact of stewardship activity on their investee companies.

The findings show that investor stewardship activity is a factor that influences strategic R&D investment. Specifically, a positive association is found between code-compliant institutional investor shareholding and R&D investment, contingent on high levels of stewardship activity.

By using stewardship disclosures to measure stewardship activity, this study sheds new light on institutional investors’ role in promoting R&D investment. The findings suggest that stewardship regulation is a valid governance policy mechanism to the extent that it promotes stewardship activity. Moreover, the findings show that stewardship disclosures provide valuable information about the potential value enhancement associated with institutional shareholding.