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On completion of this case study, students will be able assess new venture opportunities by properly allocating expansion fund in growing the business; analyzing various scaling-up options; applying the Ansoff matrix for growth and expansion; designing a framework for scaling up; and using the business model canvas.

Mr Sreeram established Eruvaka Technologies in Vijayawada, Andhra Pradesh (India), in 2015 to provide products and services related to aquaculture. The company was founded with the goal of assisting prawn farmers who had trouble keeping up with the demands of the industry. Eruvaka Technologies created risk-reducing and productivity-boosting on-farm diagnostic devices for aquaculture growers. The company developed low-cost monitoring and automation solutions for aquaculture by merging sensors, mobile connection and decision tools. Eruvaka’s primary objective was to offer reasonably priced, technologically advanced goods and services to farmers. Eruvaka matured into a promising startup over time, attracting $5m in funding. Sreeram and his team had to detail their plan to their investors about how they intended to use the money from each funding rounds toward growing the business, how the company planned to achieve sustainable and competitive advantage while providing value to its consumers and how they would address critical issues including product acquisition cost, supply chain problem and customer anxiety.

This case study can be taught as part of undergraduate- and postgraduate-level courses and Master of Business Administration courses.

Teaching notes are available for educators only.

CSS 11: Strategy.

This paper aims to present the design and implementation of a circularly polarized co-planar waveguide (CPW) fed wideband pie-shaped monopole antenna for multi-antenna techniques. Multi-antenna techniques are promising solutions for higher data rate and enhanced reliability of wireless applications. They find numerous applications in 4G/5G networks and in most wireless standards such as wireless local area networks (WLAN), wireless fidelity and worldwide interoperability for microwave access systems to enhance the channel capacity without additional spectrum by means of multi-path propagation techniques.

The antenna is designed to operate at three WLAN frequency bands of 4.8, 5.2 and 5.8 GHz. The measured 10 dB impedance bandwidth of the proposed antenna element is 1.2 GHz (24.23 per cent). The proposed CPW fed, pie-shaped monopole antenna has a gain of 5.4 dB and an efficiency of 72.8 per cent at 4.8 GHz.

To use the proposed antenna in a multi-antenna environment, the antennas have to be placed in a close proximity to each other. The close proximity introduces strong mutual coupling between the antennas, which in turn degrades the performance of multi-antenna systems. A multi-antenna system with two antenna elements has been constructed with an edge to edge spacing of 0.24 λ₀ (15 mm), and the mutual coupling level is −17 dB. To enhance the isolation between the antenna elements, a shorting pin-based interconnected semicircles enclosed decoupling structure is proposed, which improves the isolation by a factor of 12.67 dB at 4.8 GHz.

To validate the performance of the proposed multi-antenna in working environment, the performance metrics such as envelope correlation coefficient (ECC), diversity gain (DG) and total active reflection coefficient (TARC) are computed for the proposed multiple-input multiple-output (MIMO) antenna. The ECC value is 0.000366 at center frequency and below 0.09 for the entire operating bandwidth, which is well below the acceptable level of 0.5 as per 3GPP standard. The DG value lies above 9.5 dB for the entire operating bandwidths and it is well above the minimum value of 3 dB. The TARC values are calculated based on S parameters, and it proves that the proposed antenna a good candidate for the multi-antenna systems.

This paper aims to present the design of a compact vertically polarized four-element UWB antenna suitable for MIMO communications.

The unit cell antenna is constructed using a square ring radiator excited through a stepped impedance feed. The proposed antenna covers the Ultra-wideband (UWB) spectrum ranging from 2.2 to 12.3 GHz. The isolation between the unit cell antennas in the array is enhanced using a simple microstrip line resonator. The decoupling element is connected to the ground through a via.

The proposed scheme offers at least 16 dB improvement in the port-to-port coupling. Furthermore, the four-element antenna array is constructed using a specific interlocking scheme. The proposed antenna array’s Multiple Input Multiple Output (MIMO) performance metrics are analyzed.

By suitably selecting the excitation port, directional radiation patterns can be realized. The combined radiation pattern covers 360 degrees. A prototype antenna array is fabricated, and the simulation results are verified using real-time experiments. The proposed antenna is a suitable candidate for shark fin housing in automotive communications.

This study aims to demonstrate a modified wire arc additive manufacturing (AM) named non-transferring arc and wire AM (NTA-WAM). Here, the build plate has no electrical arc attachment, and the system’s arc is ignited between tungsten electrode and filler wire.

The effect of various deposition conditions (welding voltage, travel speed and wire feed speed [WFS]) on bead characteristics is studied through response surface methodology (RSM). Under optimum deposition condition, a single-bead and thin-layered part is fabricated and subjected to microstructural, tensile testing and X-ray diffraction study. Moreover, bulk texture analysis has been carried out to illustrate the effect of thermal cycles and tensile-induced deformations on fibre texture evolutions.

RSM illustrates WFS as a crucial deposition parameter that suitably monitors bead width, height, penetration depth, dilution, contact angle and microhardness. The ferritic (acicular and polygonal) and lath bainitic microstructure is transformed into ferrite and pearlitic micrographs with increasing deposition layers. It is attributed to a reduced cooling rate with increased depositions. Mechanical testing exhibits high tensile strength and ductility, which is primarily due to compressive residual stress and lattice strain development. In deposits, ϒ-fibre evolution is more resilient due to the continuous recrystallisation process after each successive deposition. Tensile-induced deformation mostly favours ζ and ε-fibre development due to high strain accumulations.

This modified electrode arrangement in NTA-WAM suitably reduces spatter and bead height deviation. Low penetration depth and dilution denote a reduction in heat input that enhances the cooling rate.

The purpose of this study is to examine the impact of ethics training (ET) on workplace behaviors. The study also aims to test the mediating effect of ethical culture (EC), on the relationship between ET and workplace behaviors.

An experimental model has been developed to address the problem statement. The success of ET intervention has been measured in terms of workplace behavior, which is evaluated by job satisfaction, employee commitment and intention to stay. The proposed research model is empirically tested by data collected from 175 mid-level managers in 30 Indian construction firms.

The results obtained from process macro showed partial mediation. Stronger perceptions of ET were associated with stronger perceptions of EC. EC is related to positive workplace behavior.

The partial mediation suggests that there is a need for exploring other potential mediating variables through which ET interventions can succeed. Future research can investigate group-level variables such as team psychological safety, which can potentially explain the complete mediation.

The results suggest that ET interventions can be used to strengthen the EC in the firms. If the ET intervention is designed purely on the compliance orientation, it will impede the opportunities for long-term development. The focus should not be with the intent to observe ethical conduct. It should be more inclusive and value-oriented. Firms need to sensitize employees and train them on how to deal with ethical dilemmas. Employees are inclined to study in the firms exhibiting a strong EC. In the construction sector, where multiple projects are handled by employees with unique and niche skill sets, retainment of employees is very important. The human resource departments need to think of introducing ET interventions not only from the study of compliance adherence but also with the motive of retaining employees.

The ET literature seldom discussed long term benefits related to creating an EC. The study critiques the intent of human resource (HR) departments while designing an ET intervention. The ethics intervention is often designed with an intent to fulfill the compliance requirements. This study contrasts this intention and shows the importance of ET intervention to create the EC in the firm, which not only includes compliance requirements like code of conduct but also has a significant focus on sensitizing employees about ethical dilemmas and grey areas.

The Internet of Things (IoT), as one of the new digital technologies, has created wide applications in various industries, and one of the most influential industries of this technology is the transportation industry. By integrating the IoT with the transportation industry, there will be dramatic changes in the industry, and it will provide many entrepreneurial opportunities for entrepreneurs to develop new businesses. Opportunity identification is at the heart of the entrepreneurial process, and entrepreneurs identify innovative goods or services to enter a new market by identifying, evaluating, and exploiting opportunities. Despite the desire of transportation managers to invest in the IoT and the increase in research in this area, limited research has focused on IoT-based entrepreneurial opportunities in the transportation industry. Therefore, the present study aims to identify IoT-based entrepreneurial opportunities in the transportation industry and examine their importance.

To achieve the research objective, the authors applied a mixed approach. First, adapting the lens of the industry value chain theory, a comprehensive literature review, besides a qualitative approach including semi-structured interviews with experts and thematic analysis, was conducted to identify the entrepreneurial opportunities. The identified opportunities were confirmed in the second stage using a quantitative survey method, including the Student t-test and factor analysis. Finally, the identified opportunities were weighted and ranked using the best worst method (BWM).

Entrepreneurial opportunities are classified into five main categories, including “smart vehicles”, “business partners/smart transportation supply side”, “supporting services”, “infrastructures”, and “smart transport management and control”. The infrastructures group of opportunities ranked the highest amongst the identified groups.

This study adds to the digital entrepreneurship opportunity recognition literature by addressing opportunities in a smart industry propelled by digital technologies, including developing new products or new applications of the available technologies. Additionally, inspired by the industry value chain theory, this article develops a framework including various digital entrepreneurial opportunity networks which are necessary to add value to any industry and, thus, could be applied by entrepreneurs to recognize opportunities for new intermediaries to enter other digital-based industries. Finally, the present study identifies the IoT-based entrepreneurial opportunities in the smart transportation industry and prioritizes them, providing practical insights regarding the creation of entrepreneurial ecosystems in the field of smart transportation for entrepreneurs and policymakers.

The utilisation of renewable energy sources for generating electricity and potable water is one of the most sustainable approaches in the current scenario. Therefore, the current research aims to design and develop a novel co-generation system to address the electricity and potable water needs of rural areas.

The cogeneration system mainly consists of a solar parabolic dish concentrator (SPDC) system with a concentrated photo-voltaic module at the receiver for electricity generation. It is further integrated with a low-temperature thermal desalination (LTTD) system for generating potable water. Also, a novel corn cob filtration system is introduced for the pre-treatment to reduce the salt content in seawater before circulating it into the receiver of the SPDC system. The designed novel co-generation system has been numerically and experimentally tested to analyse the performance at Karaikal, U.T. of Puducherry, India.

Because of the pre-treatment with a corn cob, the scale formation in the pipes of the SPDC system is significantly reduced, which enhances the efficiency of the system. It is observed that the conductivity, pH and TDS of seawater are reduced significantly after the pre-treatment by the corncob filtration system. Also, the integrated system is capable of generating 6–8 litres of potable water per day.

The integration of the corncob filtration system reduced the scaling formation compared to the general circulation of water in the hoses. Also, the integrated SPDC and LTTD systems are comparatively economical to generate higher yields of clean water than solar stills.

This study aims to review the features and challenges of the flood relief chain, identifies administrative measures during and after the flood occurrence and prioritizes them using two machine learning (ML) and analytic hierarchy process (AHP) methods. This paper aims to provide a prioritization program based on flood conditions that optimize flood management and improves society’s resilience against flood occurrence.

The collected database in this paper has been trained by using ML algorithms, including support vector machine (SVM), Naive Bayes (NB) and k-nearest neighbors (kNN), to create a prioritization program. Furthermore, the administrative measures in two phases of during and after the flood are prioritized by using the AHP method and questionnaires completed by experts and relief workers in flood management.

Among the ML algorithms, the SVM method was selected with 91.37% accuracy. The prioritization program provided by the model, which distinguishes it from other existing models, considers five conditions of the flood occurrence to prioritize actions (season, population affected, area affected, damage to houses and human lives lost). Therefore, the model presents a specific plan for each flood with different occurrence conditions.

The main limitation is the lack of a comprehensive data set to determine the effect of all flood conditions on the prioritization program and the relief activities that have been done in previous flood disasters.

The originality of this paper is the use of ML methods to prioritize administrative measures during and after the flood and presents a prioritization program based on each flood’s conditions. Therefore, through this program, the authority and society can control the adverse impacts of flood more effectively and help to reduce human and financial losses as much as possible.