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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.

The purpose of this study is to broadly examine the role of marketing–finance interface factors for value creation. Specifically, the study investigates the influence of discretionary expenditures such as advertisement on valuation of brands and firms within the framework of risk factors.

To test the model and hypotheses of this study as it has the possibilities of multiple causations among different variables used in the system. Some independent variables are not truly independent and there is a possibility of biased estimation and inconsistent results. Hence a dynamic simultaneous equation model is used including the instrumental variable approach.

The study provides evidence for direct association between brand value and firm value which is represented by the joint impact of both operating and stock market performance. The results establish the direct relationship between brand and firm value and signify the relevance of intangible value creation.

This study addresses the gap in the research which examines the role of marketing decisions on value creation which jointly impacts both operating and stock market performance.

This study aims to evaluate the influence of corporate governance index (CGI), ownership concentration (OC) and other features on the dividends of listed Indian pharmaceutical companies. The other features included are leverage, excess return over cost of equity and stock-market return. This study thus helps to provide more insights on the dividend distribution issues for a shareholder in the challenging and demanding pharma industry, especially when stakes are high.

The data for all 26 pharmaceutical companies which form part of the NSE NIFTY-500 index for six years (2014–2019) is procured using Centre for Monitoring Indian Economy’s (CMIEs) Prowess database. An eight-pointer scale (unweighted scale) is used to develop the CGI. For OC, this paper considers the proportion of promoters’ shareholding, domestic institutional investors’ shareholding and foreign owners’ shareholding. Both static and dynamic panel data models are used to evaluate the effect of CGI and OC on dividends.

The panel data analysis depicts that CGI significantly positively influences the dividends of pharmaceutical companies in India. Thus, the authors find support for La Porta et al.’s outcome agency model. The results also reveal that only promoters’ holdings are significantly inversely related to dividends out of the three OC variables used for this study. This discussion implies that family-run pharmaceutical companies in India tend to retain profits instead of distributing dividends.

This study provides two direct insights for policymakers and stakeholders. First, because this study shows that CGI significantly positively influences dividends, corporate governance (CG) is an essential factor for determining dividends. Second, because the results also reveal that OC in the hands of promoters hurts dividends, it implies that the higher the promoter holding, lesser is the dividend distributed by the company. Both these results can be used as a quantitative tool by investors to assess Indian pharmaceutical companies better. However, a similar study could be directed to assess the impact of CGI and OC on dividends of other industries. Moreover, additional variables of CG and OC can also be evaluated in further detail. There is also a need to empirically validate the impact of CG and OC on a company’s performance.

The results are robust and reveal that variation in CGI does impact dividend policy. This aids in confirming that CG is a crucial aspect influencing dividends. The findings also add to the increasing studies across the globe evaluating the influence of CG and OC on dividends.

The purpose of this paper is to propose a model for a two-agent multi-target-searching scenario in a two-dimensional region, where some places of the region have limited resource capacity in terms of the number of agents that can simultaneously pass through those places and few places of the region are unreachable that expand with time. The proposed cooperative search model and Petri net model facilitate the search operation considering the constraints mentioned in the paper. The Petri net model graphically illustrates different scenarios and helps the agents to validate the strategies.

In this paper, the authors have applied an optimization approach to determine the optimal locations of base stations, a cooperative search model, inclusion–exclusion principle, Cartesian product to optimize the search operation and a Petri net model to validate the search technique.

The proposed approach finds the optimal locations of the base stations in the region. The proposed cooperative search model allows various constraints such as resource capacity, time-dependent unreachable places/obstacles, fuel capacities of the agents, two types of targets assigned to two agents and limited sortie lengths. On the other hand, a Petri net model graphically represents whether collisions/deadlocks between the two agents are possible or not for a particular combination of paths as well as effect of time-dependent unreachable places for different combination of paths are also illustrated.

The problem addressed in this paper is similar to various real-time problems such as rescue operations during/after flood, landslide, earthquake, accident, patrolling in urban areas, international borders, forests, etc. Thus, the proposed model can benefit various organizations and departments such as rescue operation authorities, defense organizations, police departments, etc.

To the best of the authors’ knowledge, the problem addressed in this paper has not been completely explored, and the proposed cooperative search model to conduct the search operation considering the above-mentioned constraints is new. To the best of the authors’ knowledge, no paper has modeled time-dependent unreachable places with the help of Petri net.

Visco‐elastic fluid flow and heat transfer in a porous medium over a non‐isothermal stretching sheet have been investigated. The flow is influenced by linearly stretching the sheet in the presence of suction, blowing and impermeability of the wall. Thermal conductivity is considered to vary linearly with temperature. The intricate non‐linear problem has been solved numerically by shooting technique with fourth order Runge‐Kutta algorithm after using perturbation method. The zeroth order solutions are obtained analytically in the form of Kummer’s function. An analysis has been carried out for two different cases, namely prescribed surface temperature (PST) and prescribed heat flux (PHF) to get the effect of porosity and visco‐elasticity at various physical situations. The important finding is that the effect of visco‐elasticity and porosity is to increase the wall temperature in case of blowing and to decrease in both the cases of suction and when the stretching sheet is impermeable.

Presents a numerical solution of the two‐dimensional laminar boundary layer problem on free and forced convection of an incompressible visco‐elastic fluid immersed in a porous medium over a stretching sheet. Here, the driving force for the flow is provided by an impermeable sheet stretched with a velocity proportional to the distance from a slit and buoyancy effects due to both temperature and concentration gradients. The resultant governing boundary layer equations are highly non‐linear and coupled form of partial differential equations, and they have been solved by employing a numerical shooting technique with fourth order Runge‐Kutta integration scheme. Numerical computations are carried out for the non‐dimensional physical parameters. The results are analyzed for the effect of different physical parameters like visco‐elasticity, permeability of the porous medium, Grashof number, Schmidt number and Prandtl number on the flow, heat and mass transfer characteristics. One of the several important observations is that the combined effect of thermal diffusion and diffusion of species is to increase the horizontal velocity profile and to decrease the temperature and concentration profiles in the boundary layer flow field.

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 paper aims to epistemologically extend and explore the present theories from prior research conducted in the area of responsiveness. Furthermore, it determines to benchmark the prominent theories, characteristics, context and methodologies (TCCM) used in the domain since its inception to advance the science and practice of marketing and logistics discipline.

A seven-step methodology (SSM) has been introduced to create a comprehensive dataset. Based upon the selection criteria of high-ranked journals and language, the research studies have been retrieved from Scopus, Web of Science, Business Source Complete and journal homepage to avoid the error of exclusion. Moreover, the dataset has been compiled using manual and electronic searches without any limitation of time.

The search for a suitable dataset retrieved 642 documents by identifying “1969” as the beginning year of research in the subject domain. The analysis found that responsiveness has been prominently studied in the manufacturing industry. The results also advocate responsiveness as the vital antecedent to performance and satisfaction. Frameworks have been proposed with significant propositions for future empirical testing and theory inventiveness by researchers.

The study pioneers its utility for retailers to recognize the firms' inherent abilities and strengths, which can be promoted to create responsiveness more than ever. The analysis results can act as the compelling force to understand the driving power of various factors influencing responsiveness.

The case describes the performance evaluation system that has been put in place by Ravi Kumar, the MD to ensure that Oystar Hassia is able to design, deliver, service, sell its packaging machines seamlessly in all parts of the world. The performance evaluation system is periodic, regular, able to take track the progress of the people within the system. The benefits accrued from performance evaluation system are also detailed in this case.