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In 2000, Cañibano et al. published a literature review entitled “Accounting for Intangibles: A Literature Review”. This paper revisits the conclusions drawn in that paper. We also discuss the intervening developments in scholarly research, standard setting and practice over the past 20+ years to outline the future challenges for research into accounting for intangibles.

We conducted a literature review to identify past developments and link the findings to current accounting standard-setting developments to inform our view of the future.

Current intangibles accounting practices are conservative and unlikely to change. Accounting standard setters are more interested in how companies report and disclose the value of intangibles rather than changing how they are determined. Standard setters are also interested in accounting for new forms of digital assets and reporting economic, social, governance and sustainability issues and how these link to financial outcomes. The IFRS has released complementary sustainability accounting standards for disclosing value creation in response to the latter. Therefore, the topic of intangibles stretches beyond merely how intangibles create value but how they are also part of a firm’s overall risk and value creation profile.

There is much room academically, practically, and from a social perspective to influence the future of accounting for intangibles. Accounting standard setters and alternative standards, such as the Global Reporting Initiative (GRI) and European Union non-financial and sustainability reporting directives, are competing complementary initiatives.

Our results reveal a window of opportunity for accounting scholars to research and influence how intangibles and other non-financial and sustainability accounting will progress based on current developments.

Small and medium-sized enterprises (SMEs) are a major source of employment and revenue growth in developing nations like India, but they also face challenges from resource shortages, shifting consumer demand and heightened competition. This research aims to discover the aspects that enhance SMEs' competitiveness and performance.

By analyzing literature and consulting experts, 10 factors that boost a firm's competitiveness were identified. The total interpretive structural modeling (TISM) method was then used to determine their interaction and structural hierarchy. Neutrosophic-MICMAC analysis was employed to assess the driving-dependence power of each factor.

The study discovered that the factor, namely “entrepreneurial orientation,” was found to be a significant one. “Manufacturing strategy” was found to be extremely dependent on the remaining competitive advantage factors.

This SME-focused framework can be adopted by large businesses to enhance organizational performance by focusing on critical factors. The study depends on experts' judgment, which might be biased. Findings will assist SMEs in identifying significant factors influencing competitive advantage and relationships, increasing awareness of factors contributing to competitive edge.

The results of the research may encourage SME sector managers and practitioners to prioritize the factors that contribute to a firm's competitive advantage.

The majority of research on SME competitive advantage focuses on individual aspects. To add to the body of knowledge on the subject, this study applies the TISM technique to Indian SMEs to identify the contextual interactions among factors that increase long-term competitiveness.

Online employee reviews have emerged as a crucial information source for business managers to evaluate employee behavior and firm performance. The purpose of this paper is to test the relationship between employee personality traits, derived from online employee reviews and job satisfaction and turnover behavior at the individual level.

The authors apply text-mining techniques to extract personality traits from online employee reviews on Indeed.com based on the Big Five theory. They also apply a machine learning classification algorithm to demonstrate that incorporating personality traits can significantly enhance employee turnover prediction accuracy.

Personality traits such as agreeableness, conscientiousness and openness are positively associated with job satisfaction, while extraversion and neuroticism are negatively related to job satisfaction. Moreover, the impact of personality traits on overall job satisfaction is stronger for former employees than for current employees. Personality traits are significantly linked to employee turnover behavior, with a one-unit increase in the neuroticism score raising the probability of an employee becoming a former employee by 0.6%.

These findings have implications for firm managers looking to gain insights into employee online review behavior and improve firm performance. Online employee review websites are recommended to include the identified personality traits.

This study identifies employee personality traits from automated analysis of employee-generated data and verifies their relationship with employee satisfaction and employee turnover, providing new insights into the development of human resources in the era of big data.

This study investigates whether the disclosure of derivatives is value relevant in emerging markets and evaluates the effects of the 2008/2009 global financial crisis on the value relevance of derivative disclosures.

Panel regression models using sub-samples and a crisis interaction term were applied to a sample of the 200 largest non-financial firms by market capitalization listed on the Johannesburg Stock Exchange (JSE) from 2005 to 2017 to assess the consequences of the financial crisis.

The results suggest that the disclosure of derivatives is value relevant in the hitherto understudied context of emerging markets. The 2008/2009 financial crisis had a significant impact on derivatives use and the value relevance of derivatives disclosure by JSE-listed companies.

Companies should reconsider both how they employ derivatives as part of their risk management practices and how they communicate derivatives use to stakeholders in the financial statements. The findings facilitate a comparative analysis across various market contexts by researchers and assist investors in better decision-making. The findings can influence regulatory practices and can help standard setters to review disclosure requirements.

The benefits of corporate hedging were studied from an emerging market perspective, using an original dataset and approach to investigate the effects of international financial volatility on emerging markets. The authors tested whether companies are valued differently, based on their disclosure of the use of derivatives in the financial statements, and the effect of the financial crisis on the value relevance derivatives disclosures.

Some researchers regard discretionary accrual (DA) as one of the factors that drive corporate managers to conduct tax planning (Scott, 2009; Basri and Buchari, 2017). Based on agency theory and positive accounting theory, corporate managers can transform accounting information and manipulate firm earnings to reduce tax liability. There is a lot of research concerning earnings management and tax planning in the developed economy. These studies include Wang and Chen (2012) and Pettersson and Wu (2015). In the emerging economies, it includes Jamei and Khedri (2016), Kurniasih and Sulardi Suranta (2017), Prastiwi (2017), Almashaqbeh et al. (2018), Bayunanda et al. (2018), Rani et al. (2018) and Kałdoński and Jewartowski (2019). It is important to note that none of the research mentioned above has evaluated the impact of real earnings management (REM) on tax planning in Nigeria. While in the developed economy only Kałdoński and Jewartowski (2019) used REM as an explanatory variable, while the majority of studies used DA. Consequently, no study has used REM to moderate the relationship between financial attributes and tax planning. Despite the widespread notion, as well as positive accounting theory, tax planning theory that financial attributes (profitability, leverage, liquidity and firm growth), REM and DA motivate tax planning, previous investigations have produced mixed results (Dwenger and Steiner, 2009; Wang and Chen, 2012; Chen and Zolotoy, 2014; Aghouei and Moradi, 2015; Pettersson and Wu, 2015; Ribeiro, 2015; Chen et al., 2016; Jamei and Khedri, 2016; Ogbeide, 2017; Yuniawati et al., 2017; Chen and Lin, 2017; Firmansyah and Febriyanto, 2018; Prastiwi, 2018; Rani et al., 2018; Kibiya and Aminu, 2019; Kałdoński and Jewartowski, 2019 and Siyanbonla, 2021). This study aims to use REM as a moderator to examine the relationship between financial attributes and tax planning whether it will strengthen or weaken the relationship.

The study examines the impact of financial attributes on the corporate tax planning of listed manufacturing firms in Nigeria. It also tests for the moderating effect of REM on the relationship between financial attributes and tax planning. Data for the study was sourced from the annual reports of sampled manufacturing firms. The study used the panel data methodology for analysis. The study used fixed effect estimation to interpret the parsimonious model and random effect was used to interpret the moderated model. The study documented that financial leverage has a positive significant influence on the tax planning of the sampled manufacturing firms. While firm growth has a negative significant impact on the tax planning of listed manufacturing firms in Nigeria. REM has a positive significant impact on tax planning. Also, REM moderate significantly the relationship between financial attributes on one hand and tax planning on the other. The study recommends that firms should go for more debt to take advantage of the tax shield of interest on the debt. Also, firm management should use non-current debt to finance non-current assets and use current debt to finance current assets to avoid the risk of taking over or liquidation. The study also recommends that firm management should engage in intercompany and intracompany transactions by selling their goods to affiliates in countries with low prices and low tax rates. A firm should also overproduce goods to have high production costs and high closing inventory since real earning management significantly reduces tax liabilities by deferring income into a later year.

The study documented that financial leverage has a positive and significant influence on the tax planning of the sampled manufacturing firms. While firm growth has a negative but significant impact on the tax planning of listed manufacturing firms in Nigeria. REM has a positive and significant impact on tax planning. Also, REM moderate significantly the relationship between financial attributes on one hand and tax planning on the other.

There is a lot of research concerning earnings management and tax planning in the developed economy. These studies include Wang and Chen (2012) and Pettersson and Wu (2015). In the emerging economies, it includes Jamei and Khedri (2016), Kurniasih and Sulardi Suranta (2017), Prastiwi (2017), Almashaqbeh et al. (2018), Bayunanda et al. (2018), Rani et al. (2018) and Kałdoński and Jewartowski (2019). It is important to note that none of the research mentioned above has evaluated the impact of REM on tax planning in Nigeria. While in the developed economy only Kałdoński and Jewartowski (2019) used REM as an explanatory variable, while the majority of studies used DA. Consequently, no study has used REM to moderate the relationship between financial attributes and tax planning.

This study aims to investigate the relation between corporate social responsibility (CSR) and disclosure transparency by examining over 12,000 disclosures of financial statements extending over 20 years. The purpose is to understand how CSR ratings relate to the level of disaggregation in financial statement line items. The study considers additional factors, such as firm size and governance, that can accentuate or moderate this relation.

This study applies regression analysis, including interactions, to test the magnitude of the relation between CSR ratings and disclosure transparency. CSR is measured as a composite score that ranks firms on their reputation over numerous indicators compiled by Morgan Stanley Capital International. Disclosure transparency is measured as the level of disaggregation in financial statement line items.

The study reveals evidence consistent with the notion that firms which are more CSR conscious are also more transparent with financial statements. Evidence shows that the level of transparency is more sensitive to changes in CSR for firms less CSR conscious. Firm size is found to moderate this relation, whereas enhanced governance accentuates it.

There is limited research on the relation between CSR ratings and disclosure transparency. To the best of the authors’ knowledge, this is the first empirical evidence on the relation between CSR ratings and the disaggregation of financial statement line items. Results from this study help us understand the drivers of disclosure transparency, which can aid regulators, investors and other stakeholders in knowing how such drivers impact managerial decisions on the disaggregation of financial statements. Accountants play a central role in producing transparent and disaggregated accounting disclosures, and their role is pivotal in effectively integrating CSR into accounting and reporting models.

The purpose of the article is to contribute to the body of research on digital transformation among members of the supply chain operating in an emerging economy. This paper researches the digital transformation trends happening across Vietnamese supply chains, by investigating the current adoption rates, predicted impact levels and financial investments being made in key Industry 4.0 technologies.

By using a semi-structured online survey, the experiences of 281 supply chain professionals in Vietnam were captured. Subsequently, statistical techniques examining variances in means, regression analysis and Monte Carlo simulation were applied.

The findings of this study offer a comprehensive understanding of Industry 4.0 technology in Vietnam, highlighting the prevalent technologies being prioritized. Big data analytics and the Internet of things are expected to have the most substantial impact on businesses over the next 5–10 years and have received the most financial investment. Conversely, Blockchain is perceived as having less potential for future investment. The study further identifies several technological synergies, such as combining advanced robotics, artificial intelligence and the Internet of things to build effective and flexible factories, that can lead to more comprehensive solutions. It also extends diffusion of innovation theory, encompassing investment and impact considerations.

This study offers valuable insights into the impact and financial investment in Industry 4.0 technologies by Vietnamese supply chain firms. It provides a theoretical contribution via an extension of the diffusion of innovation theory and contributes toward a better understanding of the current Industry 4.0 landscape in developing economies. The findings have significant implications for future managerial decision-making, on the impact, viability and resourcing needs when undertaking digital transformation.

To maximize the network total profit by calculating the difference between costs and revenue (first objective function). To maximize the positive impact on the environment by integrating GSCM factors in RL (second objective function). To calculate the efficiency of disassembly centers by SDEA method, which are selected as suppliers and maximize the total efficiency (third objective function). To evaluate the resources and total efficiency of the proposed model to facilitate the allocation resource process, to increase resource efficiency and to improve the efficiency of disassembly centers by Inverse DEA.

The design of a closed-loop logistics network for after-sales service for mobile phones and digital cameras has been developed by the mixed-integer linear programming method (MILP). Development of MILP method has been performed by simultaneously considering three main objectives including: total network profit, green supply chain factors (environmental sustainability) and maximizing the efficiency of disassembly centers. The proposed model of study is a six-level, multi-objective, single-period and multi-product that focuses on electrical waste. The efficiency of product return centers is calculated by SDEA method and the most efficient centers are selected.

The results of using the model in a case mining showed that, due to the use of green factors in network design, environmental pollution and undesirable disposal of some electronic waste were reduced. Also, with the reduction of waste disposal, valuable materials entered the market cycle and the network profit increased.

(1) Design a closed-loop reverse logistics network for after-sales services; (2) Introduce a multi-objective multi-echelon mixed integer linear programming model; (3) Sensitivity analysis use Inverse-DEA method to increase the efficiency of inefficient units; (4) Use the GSC factors and DEA method in reverse logistics network.

This paper examines the relationships between bank switching and both customer vulnerability and consumer-oriented policies (financial education and disclosure practices).

The analysis employs microdata from the Special Eurobarometer on Financial Products and Services, for 24 European nations. It carries out a probit estimation on the factors explaining propensity of bank switching, focusing on three characteristics associated with customer vulnerability: an advanced age, low educational attainment and residence in a rural or a relatively poor region.

The authors report that the probability of bank switching is significantly lower for three groups of vulnerable customers: the elderly, the less educated and those living in deprived regions. Further the authors identify that national financial education policies and disclosure practices have no significant effects on bank switching.

Based on these results, the authors propose more targeted policies recognising customers' heterogeneity are required to increase bank switching behaviour.

This paper exploits a unique source of information on bank switching behaviour and customer characteristics across European nations. These data are complemented with information about consumer financial education policies and disclosure practices from the World Bank and geographical, market and regulatory factors at the regional and national levels. The paper contributes to two academic areas. First, it presents further evidence on heterogeneity of bank customer switching behaviour, addressed at improving the understanding of customer vulnerability in banking services. Second, it examines the efficacy of consumer-oriented policies (financial literacy and disclosure practices) in encouraging bank switching.

Amid increasing frequency of disaster across the globe, humanitarian supply chain (HSC) has gained significant attention in recent times. This work aims to contribute towards improving the decision-making capabilities of relief organisations by offering more comprehensive understanding of the critical success factors (CSFs) concerning HSC. Hence, the current work attempts to classify CSFs as cause-and-effect factors and explore their relative importance in the stated significance.

Current work takes an explorative and deductive approach. It uses literature and experts' input to identify the CSFs for HSC and to develop a structural model for assessing these factors. Intuitionistic fuzzy DEMATEL (IF-D) is employed for modelling and analysing the cause-effect linkages among the CSFs. IF-D method is chosen as it is robust to vagueness of data and small samples.

The findings indicate that “motivated and committed employees” is the most influencing causal factor followed by “IT infrastructure”, and among effect factors, “physical network” carries the most significance followed by “anticipation capabilities.”

Relief organisations and stakeholders at various levels may put more emphasis on cause group factors with more influence on most critical effect factors to build more efficient and effective HSC to execute more impactful relief programs.

Current work explores the cause–effect relationships among the CSFs concerning HSC by implementing IF-D, which can be considered as the original contribution.