A comparison of non-fi nancial strategy disclosure in the annual reports of South African and Indian listed companies

This study focuses on non-fi nancial strategy disclosure in the annual reports of listed companies in South Africa and India. South Africa and India are both developing nations that face similar socioeconomic conditions, including the threats presented by the HIV/AIDS pandemic and affi rmative action policies and regulations. The fact that integrated reporting is fast becoming a necessity for emerging markets to gain entrance to developed economies validates the contribution of this research. This study, which replicated the studies of Santema and Van de Rijt (2001) and Padia and Yasseen (2011), compared the top 40 listed companies in South Africa with the top 40 listed companies in India based on market capitalisation for the year 2012. The results were statistically analysed using principal component analysis and Hotelling’s t-square tests. The fi ndings concluded that South African companies divulge more information in terms of their non-financial strategy disclosure than their Indian counterparts. In addition, the Hotelling’s t-square test found that there were no signifi cant differences in terms of four of the variables when comparing South African companies with Indian companies. Overall, however, there are vast differences in the levels of non-fi nancial strategy disclosure in both countries, which is attributed to stock exchange regulation in the respective countries.Key words: affirmative action, annual reports, HIV/AIDS, India, integrated reporting, nonfinancial disclosure, South Africa, strateg

The perceptions of South African accounting practitioners on the post-implementation of IFRS for SMEs in an institutionalised environment

Orientation: Small and medium-sized entities (SMEs) play a crucial role in the South African economy. The financial reporting framework applicable to SMEs may contribute to the success of the SME. This study was exploratory in nature and followed an interpretive approach to seek an in-depth understanding of the application of the International Financial Reporting Standards for Small and Medium-Sized Entities (IFRS for SMEs) in South Africa. Research purpose: This article explores the perceptions of South African accounting practitioners regarding the post-implementation of the IFRS for SMEs in the South African SME sector. Motivation for the study: South African research on IFRS for SMEs is scarce. This study was designed to contribute to the scarce body of literature on IFRS for SMEs and will benefit both the South African and international accounting profession. Research approach/design and method: In-depth semi-structured interviews with 21 accounting practitioners were carried out during 2017 and 2018. An interpretive approach was adopted to analyse the data into themes providing the insight into the perceptions of South African practitioners. Main findings: Overall, there appears to be an approval of IFRS for SMEs. The uniformity associated with IFRS for SMEs is one of the significant advantages, while factors such as the age of the practitioners, the use of automated software systems and South African legislative requirements affect the relative merit of using the standard. Practical/managerial implications: The use of the interpretive style will assist professional accounting organisations, standard setters and regulators in understanding the various benefits and drawbacks of the IFRS for SME framework. Contribution/value-add: This article is the first to explore the in-depth views of accounting practitioners after IFRS for SMEs was adopted in South Africa. The article also highlights the challenges faced by accounting practitioners in developing economies that service SMEs

Learning Attentive and Hierarchical Representations for 3D Shape Recognition

© 2020, Springer Nature Switzerland AG. This paper proposes a novel method for 3D shape representation learning, namely Hyperbolic Embedded Attentive Representation (HEAR). Different from existing multi-view based methods, HEAR develops a unified framework to address both multi-view redundancy and single-view incompleteness. Specifically, HEAR firstly employs a hybrid attention (HA) module, which consists of a view-agnostic attention (VAA) block and a view-specific attention (VSA) block. These two blocks jointly explore distinct but complementary spatial saliency of local features for each single-view image. Subsequently, a multi-granular view pooling (MVP) module is introduced to aggregate the multi-view features with different granularities in a coarse-to-fine manner. The resulting feature set implicitly has hierarchical relations, which are therefore projected into a Hyperbolic space by adopting the Hyperbolic embedding. A hierarchical representation is learned by Hyperbolic multi-class logistic regression based on the Hyperbolic geometry. Experimental results clearly show that HEAR outperforms the state-of-the-art approaches on three 3D shape recognition tasks including generic 3D shape retrieval, 3D shape classification and sketch-based 3D shape retrieval