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Recently, the popularity of software has grown significantly in the market. Enhancement of software is needed to decrease the burden of getting high-quality and reliable software. To achieve this, the software is upgraded by adding new features to the previous version. Therefore, adding new features in the last version to be consistent with the earlier version is challenging. This paper aims to discuss the optimal software enhancement and customer growth model.

This paper discusses a model when new features are added to the software, and the customers' adoption of the software is presented as a customer growth model. An optimal control problem is introduced to maximize the profit obtained from the software system over the system's lifetime period. Total gain is calculated by the value generated from selling the software over the total expenditure during the software development process. The closed-form solution and some theoretical results are presented using the optimal control-theoretic approach. The theoretical results are supported by a numerical example.

This paper gives several substantive insights during sensitivity analysis and provides essential results. The results discussed here are compatible with the actual scenario and useful in software enhancement.

The authors have proposed a new feature growth and customer growth model to maximize the total profit using optimal control theory.

The present study aims to construct ensemble machine learning (EML) algorithms for groundwater potentiality mapping (GPM) in the Teesta River basin of Bangladesh, including random forest (RF) and random subspace (RSS).

The RF and RSS models have been implemented for integrating 14 selected groundwater condition parametres with groundwater inventories for generating GPMs. The GPM were then validated using the empirical and bionormal receiver operating characteristics (ROC) curve.

The very high (831–1200 km²) and high groundwater potential areas (521–680 km²) were predicted using EML algorithms. The RSS (AUC-0.892) model outperformed RF model based on ROC's area under curve (AUC).

Two new EML models have been constructed for GPM. These findings will aid in proposing sustainable water resource management plans.

In the previous decade, unmanned aerial vehicles (UAVs) have turned into a subject of enthusiasm for some exploration associations. UAVs are discovering applications in different regions going from military applications to activity reconnaissance. The purpose of this paper is to overview a particular sort of UAV called quadrotor or quadcopter.

This paper includes the dynamic models of a quadrotor and the distinctive model-reliant and model-autonomous control systems and their correlation.

In the present time, focus has moved to outlining autonomous quadrotors. Ultimately, the paper examines the potential applications of quadrotors and their part in multi-operators frameworks.

This investigation deals with the review on various quadrotors, their applications and motion control strategies.

The study aims to overview the different types of internal-led cyber fraud that have gained mainstream attention in recent major-value fraud events involving prominent Indian banks. The authors attempted to identify and classify cyber frauds and its drivers and correlate them for optimal mitigation planning.

The methodology opted for the identification and classification is through a detailed literature review and focus group discussion with risk and vigilance officers and cyber cell experts. The authors assessed the future of cyber fraud in the Indian banking business through the machine learning–based k-nearest neighbor (K-NN) approach and prioritized and predicted the future of cyber fraud. The predicted future revealing dominance of a few specific cyber frauds will help to get an appropriate fraud prevention model, using an associated parties centric (victim and offender) root-cause approach. The study uses correlation analysis and maps frauds with their respective drivers to determine the resource specific effective mitigation plan.

Finally, the paper concludes with a conceptual framework for preventing internal-led cyber fraud within the scope of the study. A cyber fraud mitigation ecosystem will be helpful for policymakers and fraud investigation officers to create a more robust environment for banks through timely and quick detection of cyber frauds and prevention of them.

Additionally, the study supports the Reserve Bank of India and the Government of India's launched cyber security initiates and schemes which ensure protection for the banking ecosystem i.e. RBI direct scheme, integrated ombudsman scheme, cyber swachhta kendra (botnet cleaning and malware analysis centre), National Cyber Coordination Centre (NCCC) and Security Monitoring Centre (SMC).

Structured and effective internal-led plans for cyber fraud mitigation proposed in this study will conserve banks, employees, regulatory authorities, customers and economic resources, save bank authorities’ and policymakers’ time and money, and conserve resources. Additionally, this will enhance the reputation of the Indian banking industry and extend its lifespan.

The innovative insider-led cyber fraud mitigation approach quickly identifies cyber fraud, prioritizes it, identifies its prominent root causes, map frauds with respective root causes and then suggests strategies to ensure a cost-effective and time-saving bank ecosystem.

This study aims to obtain an understanding of the impact of personal cultural orientation on potential consumers’ intention toward the purchase of high-involvement green products, specifically, electric two-wheelers in India, which is one of the largest emerging markets of the world.

A self-administered questionnaire comprising a total of 30 items was administered over a sample of 582 respondents. The structural equation modeling using partial least square was used to analyze the relative impact of different cultural dimensions on consumers’ green purchase intention. Geert Hofstede’s typology of culture was used to represent personal cultural orientation and four of the five dimensions, namely, collectivism, long-term orientation (LTO), masculinity and uncertainty avoidance were studied.

Findings of the study revealed that collectivism, LTO and masculinity appear to be significant cultural dimensions that influence Indian consumers’ intention to purchase electric two-wheelers. Collectivism is the most influential dimension, followed by LTO and masculinity.

This study helps in expanding literature in the area of green purchase by providing insight on how consumers’ individual cultural orientation influences their purchase of eco-friendly products such as electric two-wheelers.

The findings of the study offer insights, which can be useful for marketers in developing various promotional strategies, as consumers’ cultural values have significant implications for decisions with respect to the advertisement content.

This study illustrates the relative impact of different dimensions of national culture (measured at consumers’ personal level) on consumers’ green purchase intention. Such a study appears to be important in extending current knowledge on green purchase behavior in one of the largest emerging markets such as India.

The study intends to evaluate the impact of inflation expectation on the performance of listed commercial banks in India during 2005–2021. Inflation expectation is considered as a direct policy tool by the policymakers for stability of the economy. The study explores how inflation expectation affects the performance indicators of the Indian banking industry while controlling for a wide range of bank-specific factors.

The study applies the generalized method of moments (GMM) on a panel sample of 27 listed bank to analyse the impact of inflation expectation on banking sector performance. The data on inflation expectation are obtained from the household inflation expectation survey introduced in India by the Reserve Bank of India in 2005. Return on assets (ROA), return on equity (ROE) and Tobin's Q have been considered as the banking performance indicators in this study.

Empirical results exhibit that inflation expectation is instrumental in deciding the banking sector's performance. Inflation expectation has been found to have a significant and positive impact on accounting-based measures of banking performance. At the same time, it shows negative impact on the marketing-based measure.

The study gives a clear picture about how inflation expectation affects the banking performance and the monetary policy of the country. The study provides crucial insights to develop strategic decisions for the Indian banking sector. The adoption of proper macroeconomic policies, taking into account inflation expectation levels, is instrumental in enhancing bank's performance and in achieving economic growth.

This study contributes to the growing body of literature on the impact of inflationary conditions on banking performance. The originality lies in capturing the role of inflation expectation solely in determining banking sector performance.

In Nepal, not much is known about the adoption of improved vegetable varieties. Also, there are reasons to expect that the determinants of adoption may vary between subsistence and commercial farmers, given their different production/market orientations. Therefore, the paper aims to examine the adoption intentions of commercial and subsistence vegetable farmers.

A logistic regression model was used to empirically test the determinants of the intention to adopt and recommend improved vegetable varieties. The paper also uses propensity score matching (PSM) to assess the causal effects of production/market orientation on household dietary patterns. Cross-sectional data of 600 Nepalese vegetable farmers are analyzed.

Compared to subsistence farmers, commercial vegetable farmers obtain seeds mainly from formal sources and use hybrid seeds. The most consistent covariates of vegetable adoption intentions were risk preferences and experience growing vegetables. Overall, adoption intentions were higher among commercial farmers, and commercial vegetable households tend to consume more vegetables.

Considering that vegetable farming provides an important supplementary food production system for the household, adopting improved vegetable varieties is pivotal to increasing productivity and improving household level dietary diversity in developing countries. Actions to promote wider adoption of vegetable varieties and encourage healthier dietary patterns could be successful if these efforts also focus on subsistence farmers. The findings in this paper will be useful to policymakers to better prioritize dissemination strategies.

The paper highlights the differences in characteristics and adoption intention towards new vegetable varieties between subsistence and commercial farmers. The impact of commercial production on healthier household dietary patterns is accentuated.