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This study aims to outline the research field of initial public offerings (IPOs) pricing and performance by combining bibliometric analysis with a systematic literature review process.

The study uses over three decades of IPO publication records (1989–2020) from Scopus and Web of Science databases. An analysis of keyword co-occurrence and bibliometric coupling was used to gain insights into the evolution of IPO literature.

The study categorized the IPO research field into four primary clusters: IPO pricing and short-run behaviour, IPO performance and influence of intermediaries, venture capital financing and top management and political affiliations and litigation risks. The results offer a framework for delineating research advancements at different stages of IPOs and illustrate the growing interest of researchers in IPOs in recent years. The study identified future research potential in the areas of corporate governance, earning management and investor sentiments related to IPO performance. Similarly, the study highlighted the opportunity to test multiple theoretical frameworks on alternative investment platforms (SME IPO platforms) operating under distinct regulatory environments.

To the best of the authors’ knowledge, this paper represents the first instance of using both bibliometric and systematic review to quantitatively and qualitatively review the articles published in the area of IPO pricing and performance from 1989 to 2020.

This paper aims to quantify the trend of variables used for building a theoretical model with the help of analysing bibliometrics data of inventory management (IM) and Total Quality Management (TQM) practices and their effects on firm performance.

Scopus' research database and the Web of Science (WoS) (including Elsevier, Emerald Group Publishing, Taylor and Francis, Wiley, IEEE, Informs and SAGE) were used to find relevant articles. The articles, review papers and conference proceedings were screened from 1993 to 2021. The articles were analysed to explain the different types of IM practices, TQM practices and their effect on the firm's performance. Thematic analysis was done using a bibliometric package of “R” (Biblioshiny) and VOSviewer to identify the key trends, approaches and research agenda.

The research covered 28 years of publications and summarised 497 articles, review papers and conference papers. Researchers concluded that IM highly correlates with the inventory turnover ratio and has no relation to firm performance. Further, TQM positively affects firm performance, but integrating IM and TQM will be a research scope for future study as none of the researchers previously covered this.

Due to the systematic literature review (SLR) and Bibliometric review, the study is limited to the Scopus and WoS (including Elsevier, Emerald Group Publishing, Taylor and Francis, Wiley, IEEE, Informs and SAGE) databases.

Being the research on a bibliometric and systematic review, relating IM practices with TQM practices would be the novelty of this paper.

This paper aims to propose a composite form of the robust disturbance fuzzy control scheme. The proposed method uses the benefits of fuzzy system modeling and Lyapunov direct methods.

The effciency of the control technique was demonstrated with assistance of numerical simulation in control problems of unmanned aerial vehicle (UAV) simulation.

To evaluate the control performance, the comparison of the proposed controller was made with conventional control techniques. The Lyapunov stability theorem has been used to testify for asymptotic stability and convergence of the closed loop system.

Implementation of the control law in the real world environment can be easier due to significant reduction in the fuzzy rules, tuning parameters and computation stages.

Simulation results confirm that the proposed control scheme performs remarkably well in terms of the robustness and disturbance attenuation.

Entrepreneurship, finance, technology and innovation, general management.

This case is suitable for students in finance, entrepreneurship and general management. The case seeks to understand the challenges of funding in technology startups and how they vary from product to service areas.

Availability of capital, short term and long term, is a major constraint faced by entrepreneurs. In India, in the technology sector, services companies have been able to innovate and grow whereas product-based companies that survived the challenges of funding have been scarce. Aluru Karthik Prasanth is presented in the case as a young entrepreneur with passion and drive to pursue the commercialization of an idea he developed during his undergraduate studies in engineering. Leaving behind the beaten paths ofMTech and employment, he decides to pursue MS entrepreneurship at IIT Madras. As he starts with his program, he analyses the challenges faced by previous technology start ups, Karthik has a dilemma – deciding whether to follow a product idea or change his plans to a technology service.

A detailed analysis of the case would help students address the following questions in entrepreneurial decision making: should an entrepreneur in technology in India pursue a product idea or service idea?. What are the pros and cons of each choice in financing? How can an entrepreneur pursue a product idea and minimize his/her risks? How does an entrepreneur's personal attributes influence his/her course? (e.g. family background, need for control) What are the challenges and opportunities in each kind of funding: debt, venture, angel, etc. in the Indian context?

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This paper adopts a modified Taguchi approach to develop empirical relationships to the performance characteristics (output responses) in terms of process variables and demonstrated their validity through comparison of test data. The method suggests a few tests as per the orthogonal array and provides complete information for all combinations of levels and process variables. This method also provides the estimated range of output responses so that the scatter in the repeated tests can be assessed prior to the tests.

In order to obtain defect-free products meeting the required specifications, researchers have conducted extensive experiments using powder bed fusion (PBF) process measuring the performance indicators (namely, relative density, surface roughness and hardness) to specify a set of printing parameters (namely, laser power, scanning speed and hatch spacing). A simple and reliable multi-objective optimization method is considered in this paper for specifying a set of optimal process parameters with SS316 L powder. It was reported that test samples printed even with optimal set of input variables revealed irregular shaped, microscopic porosities and improper melt pool formation.

Finally, based on detailed analysis, it is concluded that it is impossible to express the performance indicators, explicitly in terms of equivalent energy density (E_0ˆ*), which is a combination of multiple sets of selective laser melting (SLM) process parameters, with different performance indicators. Empirical relations for the performance indicators are developed in terms of SLM process parameters. Test data are within/close to the expected range.

Based on extensive analysis of the SS316 L data using modified Taguchi approach, the optimized process parameters are laser power = 298 W, scanning speed = 900 mm/s and hatch distance = 0.075 mm, for which the results of surface roughness = 2.77 Ra, relative density = 99.24%, hardness = 334 Hv and equivalent energy density is 4.062. The estimated data for the same are surface roughness is 3.733 Ra, relative density is 99.926%, hardness is 213.64 Hv and equivalent energy density is 3.677.

Even though equivalent energy density represents the energy input to the process, the findings of this paper conclude that energy density should no longer be considered as a dependent process parameter, as it provides multiple results for the specified energy density. This aspect has been successfully demonstrated in this paper using test data.

Applying discrete linear optimal control to robot manipulators faces two challenging problems, namely nonlinearity and uncertainty. This paper aims to overcome nonlinearity and uncertainty to design the discrete optimal control for electrically driven robot manipulators.

Two novel discrete optimal control approaches are presented. In the first approach, a control-oriented model is applied for the discrete linear quadratic control while modeling error is estimated and compensated by a robust time-delay controller. Instead of the torque control strategy, the voltage control strategy is used for obtaining an optimal control that is free from the manipulator dynamics. In the second approach, a discrete optimal controller is designed by using a particle swarm optimization algorithm.

The first controller can overcome uncertainties, guarantee stability and provide a good tracking performance by using an online optimal algorithm whereas the second controller is an off-line optimal algorithm. The first control approach is verified by stability analysis. A comparison through simulations on a three-link electrically driven robot manipulator shows superiority of the first approach over the second approach. Another comparison shows that the first approach is superior to a bounded torque control approach in the presence of uncertainties.

The originality of this paper is to present two novel optimal control approaches for tracking control of electrically driven robot manipulators with considering the actuator dynamics. The novelty is that the proposed control approaches are free from the robot's model by using the voltage control strategy. The first approach is a novel discrete linear quadratic control design supported by a time-delay uncertainty compensator. The second approach is an off-line optimal design by using the particle swarm optimization.

Purpose: Green computing is a way of using the computer resource in an eco-friendly while maintaining and decreasing the harmful environmental impact. Minimising toxic materials and reducing energy usage can also be used to recycle the product.

Need for the Study: The motivation of the study is to use green computing resources to decrease carbon emissions and their adverse effect on the environment.

Methodology: The study uses a qualitative method of collecting resources and data to address the opportunities, challenges, and future trends in green computing for Sustainable Future Technologies. The study focusses on multiple kinds of cloud computing services collected and executed into single remote servers. The service demand processor offers these services to the client per their needs. The simultaneous requests to access the cloud services, processing and expertly managing these requests by the processors are discussed and analysed.

Findings: The findings suggest that green computing is an upcoming and most promising area. The number of resources employed for green computing can be beneficial for lowering E-waste so that computing can be environmentally friendly and self-sustainable.

Practical Implications: Green computing applies across all industries and service sectors like healthcare, entertainment, tourism, and education. The convergence of technologies like Cloud Computing, AI, and Internet of Things (IoT) is greatly impacting Green Supply Chain Management (GSCM) market.

The paper aims to study the influence of rounded corners on the flow-induced oscillation of a square cylinder that is free to oscillate in two degrees of freedom.

The finite volume code in conjunction with the moving mesh scheme was implemented via a user-defined function to carry out the computations in two dimensions. The Reynolds number (Re) chosen for the present study is fixed at 100, and the frequency ratio, F_r = f_s/f_n (where f_s is the vortex shedding frequency and f_n is the natural frequency of cylinder) is used as a varying parameter. The computational model was validated for flow past a stationary cylinder with R/D = 0 and 0.5, and the results showed good agreement with the literature.

The aerodynamic characteristics, amplitude response, trajectories of cylinder motion and vortex shedding modes are obtained by conducting a series of simulations under different frequency ratios of the cylinder. It was found that the minimum transverse amplitude, drag force and lift force obtained for a naturally oscillating square cylinder are quite different when compared with a stationary and forced oscillating cylinder, where the maximum drag and lift forces were observed for a square cylinder and a minimum around R/D = 0.2 was observed.

The present work identified the significant effect of the varying frequency ratio and R/D on the VIV modes of the cylinder. It was observed that the cylinder wake exhibits the (2S) vortex shedding mode for R/D = 0 to 0.2 at all F_r, whereas the C (2S) mode appeared for R/D > 0.2 at F_r = 1.1.

Efficient resource utilization in wireless sensor networks is an important issue. Clustering structure has an important effect on the efficient use of energy, which is one of the most critical resources. However, it is extremely vital to choose efficient and suitable cluster head (CH) elements in these structures to harness their benefits. Selecting appropriate CHs and finding optimal coefficients for each parameter of a relevant fitness function in CHs election is a non-deterministic polynomial-time (NP-hard) problem that requires additional processing. Therefore, the purpose of this paper is to propose efficient solutions to achieve the main goal by addressing the related issues.

This paper draws inspiration from three metaheuristic-based algorithms; gray wolf optimizer (GWO), incremental GWO and expanded GWO. These methods perform various complex processes very efficiently and much faster. They consist of cluster setup and data transmission phases. The first phase focuses on clusters formation and CHs election, and the second phase tries to find routes for data transmission. The CH selection is obtained using a new fitness function. This function focuses on four parameters, i.e. energy of each node, energy of its neighbors, number of neighbors and its distance from the base station.

The results obtained from the proposed methods have been compared with HEEL, EESTDC, iABC and NR-LEACH algorithms and are found to be successful using various analysis parameters. Particularly, I-HEELEx-GWO method has provided the best results.

This paper proposes three new methods to elect optimal CH that prolong the networks lifetime, save energy, improve overhead along with packet delivery ratio.