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The purpose of this paper is to review phytochemical potential of acacia and its associated health advantages. Acacia a moderate-sized, deciduous tree and recognised as health-promoting species because of availability of essential bioactive components. The bioactive compounds such as tannins, flavonoids, alkaloids, fatty acids and polysaccharides (gums) present in the plant parts of acacia, namely, bark, leaves, flowers, fruits, twigs and seeds, have medicinal value and thus are used to overlay the formulations of plant-based drugs and value-added foods.

Major well-known bibliometric information sources such as Web of Science, Scopus, Mendeley and Google Scholar were searched with keywords such as “nutrition value of acacia”, “bioactive compounds”, “health benefits”, “processing and safety” were chosen to obtain a database of 1,428 papers. The search considered papers in the English language from the past 18 years of publication in journals (2004–2022). The article selection process consisted of the screening of titles and abstracts, based on inclusion and exclusion criteria. Articles that did not have acacia components as a study objective were taken into consideration for exclusion. A final database of 87 scientific sources was made after sorting and classifying them according to different criteria based on topic relevance, country of origin and year of publication. Articles with other random descriptors were also searched to complement the discussion of the results obtained.

The literature reflected that acacia contains all necessary phytochemicals like polyphenols, flavonoids, terpenoids, glucosinolates, alkaloids and carotenoids along with essential macro, micro-nutrients. Furthermore, processing methods such as soaking, cooking, roasting and dehusking significantly reduced the anti-nutritional factors present in acacia seeds of different species. This review also focused on the processing methods that are used to eliminate or lower down the anti-nutritional factors from the seeds. Previous findings related to acacia plant parts with respect to food development are explored and mentioned.

This review emphasised mainly on recent studies that had been reported on ethnomedical acacia plants therapeutically, commercially and exponentially for further studies to increase the utilisation in food processing.

The increasing prevalence of a wide range of infectious diseases, as well as the underwhelming results of vaccination rates that may be traced back to problems with vaccine procurement and distribution, have brought to the fore the importance of vaccine supply chain (VSC) management in recent years. VSC is the cornerstone of effective vaccination; hence, it is crucial to enhance its performance, particularly in low- and middle-income countries where immunization rates are not satisfactory.

In this paper, the authors focus on VSC performance improvement of India by proposing supply contracts under demand uncertainty. The authors propose three contracts – wholesale price (WSP), cost sharing (CS) and incentive mechanism (IM) for the government-operated immunization program of India.

The authors' findings indicate that IM is capable of coordinating the supply chain, whereas the other two contracts are inefficient for the government. To validate the model, it is applied to a real-world scenario of coronavirus disease 2019 (COVID-19) in India, and the findings show that an IM contract improves the overall efficiency of the system by 23.72%.

Previous studies focused mainly on the influenza VSC industry within developed nations. Nonetheless, there exists a dearth of literature pertaining to the examination of supply contracts and their feasibility for immunization programs that are administered by the government and aimed at optimizing societal benefits. The authors' findings can be beneficial to the immunization program of India to optimize their VSC cost.

This paper aims to analyze and give directions for advancing research in stock market volatility highlighting its features, structural breaks and emerging developments. This study offers a platform to research the benchmark studies to know the research gap and give directions for extending future research.

The author has performed the literature review, and, reference checking as per the snowballing approach. Firstly, the author has started with outlining and simplifying the significance of the subject area, the review illustrating the various elements along with the research gaps and emphasizing the finding.

This work summarizes the studies covering the volatility, its properties and structural breaks on various aspects such as techniques applied, subareas and the markets. From the review’s analysis, no study has clarified the supremacy of any model because of the different market conditions, nature of data and methodological aspects. The outcome of this research work has delivered further magnitude to research the benchmark studies for the upcoming work on stock market volatility. This paper has also proposed the hybrid volatility models combining artificial intelligence with econometric techniques to detect noise, sudden changes and chaotic information easily.

The author has taken the research papers from the scholarly journal published in the English language only and the author may also consider other nonscholarly or other language journals.

To the best of the author’s knowledge, this research work highlights an updated and more comprehensive framework examining the properties and demonstrating the contemporary developments in the field of stock market volatility.

Crude oil, gold and interest rates are some of the key indicators of the health of domestic as well as global economy. The purpose of the study is to find the shock volatility and price volatility effects of gold and crude oil market on interest rates in India.

This study finds the mutual and directional association of the volatility of gold, crude oil and interest rates in India. The bi-variate GARCH models (Diagonal VEC GARCH and BEKK GARCH) are applied on the sample data of gold price, crude oil price and yield (interest rate) gathered from November 30, 2015 to November 16, 2020 (weekly basis) to investigate the volatility association including the volatility spillover effect in the three markets.

The main findings of the study focus on having a long-term conditional correlation between gold and interest rates, but there is no evidence of volatility spillover from gold and crude oil on the interest rates. The findings of the study are of great importance especially to the policymakers, as they state that the fluctuations in prices of gold and crude oil do not adversely impact the interest rates in India. Therefore, the fluctuations in prices of gold and crude may generally impact the economy, but it has nothing to do with interest rate in particular. This implies that domestic and foreign investments in the country will not be affected by gold and crude oil that are largely driven by interest rates in the country.

Gold and crude oil are two very important commodities that have their importance not only for domestic affairs but also for international business. They veritably influence the economy including forex exchange for any nation. In addition to this, the researchers believe the findings will provide insights to policymakers, stakeholders and investors.

Gold and crude oil undoubtedly influence the exchange rates but their impact on the interest rates in an economy is not definite and remains ambiguous owing to the mixed findings of the studies. The lack of studies related to the impact of gold and crude oil on the interest rates, despite them being essentials for the health of any economy is the main motivation of this study. This study is novel as it investigates the volatility impact of crude oil and gold on interest rates and contributes to the existing literature with its findings.

In recent times, fuzzy logic is gaining more and more attention, and this is because of the capability of understanding the functioning of the system as per human knowledge-based system. The main contribution of the work is dynamically adapting the important parameters throughout the execution of the flower pollination algorithm (FPA) using concepts of fuzzy logic. By adapting the main parameters of the metaheuristics, the performance and accuracy of the metaheuristic have been improving in a varied range of applications.

The fuzzy logic-based parameter adaptation in the FPA is proposed. In addition, type-2 fuzzy logic is used to design fuzzy inference system for dynamic parameter adaptation in metaheuristics, which can help in eliminating uncertainty and hence offers an attractive improvement in dynamic parameter adaption in metaheuristic method, and, in reality, the effectiveness of the interval type-2 fuzzy inference system (IT2 FIS) has shown to provide improved results as matched to type-1 fuzzy inference system (T1 FIS) in some latest work.

One case study is considered for testing the proposed approach in a fault tolerant control problem without faults and with partial loss of effectiveness of main actuator fault with abrupt and incipient nature. For comparison between the type-1 fuzzy FPA and interval type-2 fuzzy FPA is presented using statistical analysis which validates the advantages of the interval type-2 fuzzy FPA. The statistical Z-test is presented for comparison of efficiency between two fuzzy variants of the FPA optimization method.

The main contribution of the work is a dynamical adaptation of the important parameters throughout the execution of the flower pollination optimization algorithm using concepts of type-2 fuzzy logic. By adapting the main parameters of the metaheuristics, the performance and accuracy of the metaheuristic have been improving in a varied range of applications.

The purpose of this paper is to examine the impact of the future of trading on volatility as well as the efficiency of the stock market of BRIC (Brazil, Russia, India and China) countries. This study also investigates the presence of day‐of‐the‐week effect in BRIC countries' stock market.

This study uses closing prices of IBrx‐50 for Brazil, RTSI for Russia, Nifty for India and CSI300 for China to represent the stock market of BRIC countries. The Run and ACF tests are used to see impact on market efficiency. GARCH M model is used to see the impact on volatility and day‐of‐the week effect.

The insignificant coefficient of variance in the conditional mean equation of GARCH M implies that the market doesn't provide higher returns during the high volatility period. The results of the Run test showed that the Russian stock market became efficient after introduction of future trading. However, ACF showed no effect of introduction of future trading on autoregressiveness of stock returns. The result of GARCH M indicates that future trading led to reduction in the volatility of the Indian stock market. There are some evidences of presence of day‐of‐the‐week effect in the Indian stock market.

This paper will help regulators to form appropriate policies as the market would have to pay a certain price, such as loss of market efficiency, for the sake of market stabilization. This will also help investors to make investment decisions, especially investing in these indices as the existence of the significant day‐of‐the‐week effect and the inefficiency in the stock market would be very useful for developing investment strategies.

This paper will be useful for both investors and regulators in decision making.

The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility.

This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area.

The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with “cryptocurrencies” and “bitcoin” during “COVID-19.” The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area.

This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results.

This paper aims to argue that the polarization index (φ) represents a valid loyalty measure for evaluating changes over time.

The brand performance measures (BPM) are a valid and useful tool for marketing managers in measuring the loyalty consumers attach, in a single time period, to a product or brand. However, the BPM reflect other attributes and not only loyalty. Over time, what might appear to be a change in loyalty may actually be a change in market size or market share. The polarization index (φ) is not biased in this manner and is more appropriate for evaluating changes over time. The study compares the results obtained with three well known BPM utilised for the analysis of loyalty – the purchase frequency, the share of category requirements and the repeat rate – with those obtained with the φ on the purchases of wine made by Italian consumers in the retail sector over two three‐year periods (2003‐2005 and 2006‐2008).

The study shows that the BPM are a fundamental source of information on the loyalty consumers attach to brands and products at one point in time. However, their strong relationship with market share risks providing results that do not reflect actual trends in loyalty. By comparison, φ provides a valid and useful analysis of the ways in which loyalty evolves over time.

Although several researchers have studied the uses of φ on one‐year and three‐year periods, none observed how the index offers more valid results than the BPM over time. The paper shows that marketing managers should always compare the results obtained with the BPM with those derived from the φ before drawing conclusions on the real loyalty trends of their products and brands.