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The purpose of this study is to provide a new way to optimize a portfolio and to show that combining the Hurst exponent and wavelet analysis may help to increase portfolio returns.

The authors use the Hurst exponent and wavelet analysis to study the long-term dependencies between sovereign bonds and sectoral indices of India. The authors further construct and evaluate the performance of three portfolios constructed on the basis of Hurst standard deviation (SD) – global minimum variance (GMV), most diversified portfolio (MDP) and equal risk contribution (ERC).

The authors find that an ERC portfolio generates positive superior return as compared other two. Since our sample includes periods of two crisis – post-2007 financial crisis and the ongoing pandemic, this study reveals that combining government bond with equities and gold provides a higher returns when the portfolios are constructed using the risk exposures of each asset in the overall portfolio risk.

The findings provide guidance to portfolio managers by helping them to select assets using the Hurst approach and wavelet analysis thereby increasing the portfolio returns.

In this study, the authors use a combination of Hurst exponent and wavelet analysis to understand the long-term dependencies among various assets and provide a new methodology to optimize a portfolio. As far as the authors’ knowledge, no study in the past has attempted to provide a joint framework for portfolio optimization and therefore this study is the first to apply this methodology.

The purpose of this study is to empirically investigate the variables having an impact on profitability of public private partnerships (PPPs) in India using a balanced panel data of 171 unlisted PPPs from different infrastructure sectors such as road, power generation, real estate and ports.

Estimations were done using Arellano–Bond dynamic panel data estimation and seemingly unrelated regression models on a balanced panel data of 855 firm-years for 171 unlisted PPPs in India. To further test the estimation robustness, panel-corrected standard errors model was used.

The study findings indicate that in firm-specific factors, leverage, size, non-debt tax shield, growth and risk have significant positive impact on PPPs’ profitability, whereas in macroeconomic factors, only inflation has significant positive relationship. Although the relationship of all determinants is in sync with various theories and approaches, but these are not significant. Using the robustness test, the results are found to be robust and consistent with resource-based view and strategy-structure-performance approaches.

As PPPs are gaining prominence in the development of infrastructural resources, their profitability is of significant importance to drive private investments in infrastructure development, the identification of factors which determine profitability is critical for researchers, practitioners, policymakers and fund providers such as equity investors and debt providers.

The empirical literature on profitability determinants is focused on various sectors including small and mid-size enterprises (SMEs) and micro firms, but to the best of the authors’ knowledge, this is the first study, in both developed and developing economies, to empirically investigate the determinants of profitability for PPPs.

The International Journal of Organizational Analysis (IJOA) is a leading journal that has published high-quality research focused on various facets of organizational analysis since 1993. This paper aims to conduct a retrospective analysis of the IJOA journey from 2005 to 2020.

The data used in this study was extracted using the Scopus database. The bibliometric analysis, using several indicators, is adopted to reveal the major trends and themes of the journal. The mapping of bibliographic data is carried using VOSviewer and Biblioshiny.

The study findings indicate that IJOA has grown for publications and citations since its inception. Five significant research directions emerged, i.e. organizational diagnostics, organization citizenship behaviour, organizational commitment to employee retention, psychological capital and firm performance, based on cluster analysis of IJOA’s publications.

To the best of the authors’ knowledge, this is the first study to conduct a comprehensive bibliometric analysis of IJOA. The study presents the key themes and trends emerging from a leading journal, considered a high-quality journal, for researching various facets of organizational functioning by academicians, scholars and practitioners.

International Journal of Emerging Markets (IJoEM) is a leading journal that publishes high-quality research focused on emerging markets. In 2020, IJoEM celebrated its fifteenth anniversary, and the objective of this paper is to conduct a retrospective analysis to commensurate IJoEM's milestone.

Data used in this study were extracted using the Scopus database. Bibliometric analysis, using several indicators, is adopted to reveal the major trends and themes of a journal. Mapping of bibliographic data is carried using VOSviewer.

Study findings indicate that IJoEM has been growing for publications and citations since its inception. Four significant research directions emerged, i.e. consumer behaviour, financial markets, financial institutions and corporate governance and strategic dimensions based on cluster analysis of IJoEM's publications. The identified future research directions are focused on emergent investments opportunities, trends in behavioural finance, emerging role technology-financial companies, changing trends in corporate governance and the rising importance of strategic management in emerging markets.

To the best of the authors' knowledge, this is the first study to conduct a comprehensive bibliometric analysis of IJoEM. The study presents the key themes and trends emerging from a leading journal considered a high-quality research journal for research on emerging markets by academicians, scholars and practitioners.

The objective of this systematic literature review (SLR) is to outline the existing research in the field of infrastructure project finance (IPF). This paper aims to summarise the academic and practitioner research to highlight the benefits of adopting IPF structures in uncertain environments. By highlighting all conceptual and applied implications of IPF, the study identifies future research directions to develop a holistic understanding of IPF.

The SLR is based on 125 articles published in peer-reviewed journals during 1975–2019. After providing a brief overview of IPF, research methodology and citation, publication and author analysis, the SLR presents the various domains around which existing research in IPF is focussed and provides future research propositions in each domain.

The study found that despite the increased usage of IPF, academic and practitioner research in the field is lagging. Also, with increased usage of IPF in emerging and under-developed economies, IPF structure presents a perfect setting to understand how investment and financing are interlinked and how to overcome the institutional voids, socio-economic risks and inter-partner differences by IPF structures.

This literature review paper is based on the research in IPF between 1975 and 2019. To the best of the authors’ understanding, the SLR is the first focussed study detailing a methodical and thorough compendium of existing studies in the IPF domain. By focussing on various domains of IPF research, this paper presents future research avenues in the field.

This study empirically investigates the interdependency of select Asian emerging economies along with the financial stress index during the times of the global financial crisis, the Euro crisis and the COVID-19 period. Moreover, it inspects the long-memory effects of the different crises during the study period.

To address the objectives of the study, the authors apply different statistical tools, namely the adjusted correlation coefficient, fractionally integrated generalised autoregressive conditional heteroskedasticity (FIGARCH) model and wavelet coherence model, along with descriptive statistics.

Financial stress is having a prodigious effect on the economic growth of select economies. From the data analysis, it is found that the long-memory effect is noted in the gross domestic product (GDP) for India and Korea only, which implies that the volatility in the GDP series for these two nations demonstrates persistence and dependency on previous values over a lengthy period.

The study is unique of its kind to consider multi-segments within the period of the study to get a clear idea about the effects of the financial stress index on select Asian emerging economies by applying different econometric tools.

This study aims to explore peer performance as the motivation behind gross profit manipulation through two different channels, namely, cost of goods sold (COGS) misclassification and revenue misclassification.

Gross profit expectation model (Poonawala and Nagar, 2019) and operating revenue expectation model (Malikov et al., 2018) are used to measure COGS and revenue misclassification, respectively. The panel data regression models are used to analyze the data for this study.

The study results show that firms engage in gross profit manipulation to meet the industry’s average gross margin, implying that peer performance is an important benchmark that firms strive to achieve through misclassification strategies. Further results exhibit that firms prefer COGS misclassification over revenue misclassification for manipulating gross profit, implying that firms choose the shifting strategy based on the relative advantage of each shifting tool.

The findings suggest that firms that just meet or slightly beat industry-average profitability levels are highly likely to engage in classification shifting (CS). Thus, investors and analysts should be careful when evaluating such firms by comparing them with other firms in the same industry.

First, this study is among earlier attempts to investigate CS motivated by peer performance. Second, this study investigates both tools of gross profit manipulation by taking a uniform sample of firms over the same period and provides compelling evidence that firms prefer one shifting tool over another depending on the relative advantage of each shifting tool.

This research lies in the domain of Vedic mathematics, and it explores the application of the related Vedic sutras in different branches of mathematics, science, education, and engineering across Asia and Europe.

The study embraced a qualitative research design followed by a systematic literature review (SLR) approach which describes the significance of Vedic mathematics. The study made use of purposive sampling through which the data were collected from 102 articles by using inclusion and exclusion criteria. It includes publication years, the types of research methods, and uses of Vedic mathematics sutras in different branches of knowledge stated by the researchers. Its goal is to offer a more thorough explanation and an evaluation of how the inquiry affected the conclusions. The articles examined in this review included all the journal articles and doctoral theses from the databases of Google Scholar, Science Direct, Scopus, and Sodhganga which were published during the period 2010–2022.

The research found that the application of the sutras of Vedic mathematics has been increasing immensely in India. The researchers in this area are fond of qualitative research methods. This research has shown that sutras of Vedic mathematics especially “Urdhvatiryakbhyam” and “Nikhilam Navatascaramana Dasastah” have been frequently used in mathematics and engineering in technical higher education. The impact of other sutras has been quite useful, which augments that in many disciplines where the applications of Vedic mathematics are prevalent, it can be functional. The study concludes by reprising the result, its limitations, and the use of Vedic mathematics as a sustainable source of knowledge.

Vedic mathematics is an area where a lot of potential applications are created in science, mathematics, engineering, and education. Even with the latest technological advancements like learning analytics, artificial intelligence has its connection with this branch of learning, which is the greatest treasure of the Indian knowledge system. The research in this area is not reported in any databases or any standard format so researchers find it difficult to locate and study this broad conceptual domain.

It will help the reader and other academic stakeholders to widen their view on the new and innovative techniques of Vedic mathematics. It is advised that additional studies would look at and evaluate papers published after this time so that readers may get a wider view of the concept of Vedic mathematics.

It will help society to know the essence of Vedic mathematics that how useful it is. Vedic mathematics helps learners to learn in a very factual and accurate manner especially while dealing with mathematical calculations. It will enhance the problem-solving skills among learners. It will be beneficial for all types of learners which will help them to become better individuals for a nation.

The paper enriches understanding of the potential applications of different sutras from Vedic literature in different fields of knowledge. The outcome of the research encourages educationists and policymakers to include Vedic mathematics in the curriculum to foster quantitative reasoning and problem-solving at varied levels of learning.

The authors aim at investigating different forms of classification shifting (CS). CS is a novel form of earnings management under which managers misclassify income statement line items and cash flow statement line items with an intent to report favorable operating performance of firms. In particular, the authors check the existence of revenue misclassification, expense misclassification and cash flows misclassification among Indian firms by taking the uniform sample of firms over a single period.

Operating revenue model (Malikov et al., 2018), core earnings expectation model (McVay, 2006) and operating cash flows model (Roychowdhury, 2006) are employed for measuring revenue misclassification, expense misclassification and cash flows misclassification, respectively. The panel data regression models are used to analyze the data for this study.

Based on the sample of 12,870 Bombay Stock Exchange (BSE) listed firm-years observations between 2010 and 2018, we find that, on average, Indian firms are engaged in revenue misclassification rather than expense misclassification to report inflated core earnings. Firms are found to be engaged in cash flows misclassification too. Besides, we find that magnitude of shifting is greater among larger firms. Results also establish that adoption of Ind AS increases the scope of shifting practices. These results are based on several robustness checks.

The results suggest that investors conduct a comprehensive review of the items of financial statements before using them in their portfolio valuation. It suggests auditors check the basis of revenue classification and standard-setting authorities, like ICAI in India, to make more mandatory disclosure requirements for classification of revenues and cash flows. It suggests lenders not to make lending decisions by looking at the operating performance metrics, as CS is the most preferred tool to positively influence the perception of lenders toward operating performance.

It is the first study that investigates different forms of classification shifting jointly for a sample of firms. Most of the earlier studies have examined one kind of classification shifting at a time. This study adds to the existing literature on earnings management by documenting that some firm-specific factors pressurize firms to prefer one form of shifting over another to report inflated core earnings.

The study aims to investigate the psychological mechanism that motivates consumers to pay more for a preferred brand that reflects their actual or ideal self-concept, by examining the shift in attention between consumer’s present, future, and past moments.

First, in a survey setting, the study identifies the relationship between temporal focus and self-congruence. Subsequently, we conduct three experiments to capture the effects of temporal focus on brand preference and willingness to pay (WTP). In these experiments, we manipulate consumers’ self-congruence and temporal focus.

The findings show that consumers with a present focus (distant future and distant past foci) tend to evaluate a brand more preferably when the brand serves to reflect their actual (ideal) selves. However, in the absence of present focus consumers’ WTP is more for a brand that reflects their ideal selves.

The study does not have an actual measure on consumers’ WTP; instead we use single-item measure.

This study sheds new light on branding strategy. The results suggest that authentic and aspirational branding strategies are relevant to publicly consumed products. Brand managers could incorporate consumers’ temporal focus into branding strategy that could significantly influence consumer preference and WTP for their brands.

This study expands our understanding of brand usage imagery congruity by showing that temporal focus is an important determinant of self-congruence. In this regard, this study empirically investigates the relationship of temporal focus, self-congruence, brand preference, and WTP. It further reveals that mere brand preference does not necessarily lead consumers to pay more for symbolic brands.