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Resistance spot welding (RSW) is an essential process in the automobile sector to join the components. The steel is the principal material utilized in car generation because of its high obstruction against erosion, toughness, ease of support and its recuperation potential. Due to this, it was planned to study the mechanical properties, hardness and microstructure characteristics of RSW of Stainless steel 304.

In the present research, RSW of 304 stainless steel plates with 1 mm thickness and effect of current intensity, welding time, electrode pressure and holding time on nugget diameter, tensile strength microhardness and microstructure of the joints was investigated. The specimens were prepared according to the dimensions of 30 × 100 mm with 30 mm overlaps joint through the RSW machine. The tensile test of the specimen was carried out on a universal testing machine and microhardness of specimens measured using Vickers’s hardness tester. Taguchi L16 orthogonal array was used to scrutinize the significant parameters for each output.

It has been observed that the tensile strength of the specimen is affected by the current intensity and nugget diameter, and the weld time has a significant effect on the tensile strength. Microhardness is highly influenced by electrode pressure and holding time, as the increase in both these parameters resulted in the increase of microhardness. This is due to rapid cooling, which is done by the cooling water flowing through the copper electrodes.

This study was carried out using a copper electrode with a flat face with selected parameters and response factors. The study can be useful for researchers working on optimization of welding parameters on stainless steel.

This study aims to develop a moderated mediation model that enables the examination of the direct relationship between brand orientation (BO) and export performance, the mediating effects of external and internal branding capabilities on the BO-export performance link, and the moderating influence of institutional environment, i.e. regulatory turbulence and policy support.

A time-lag primary data was collected from two-wave survey of 684 cross-industry exporting small and medium-sized enterprises (SMEs) using an online-email based survey technique, and the research model was validated using ordinary least squares regression analysis in SPSSV.27 and Hayes’ PROCESS macroV.2.13.

Regression findings indicate that the relationship between BO and export performance is not direct, but rather mediated by means of both external and internal branding capabilities. It further helps to uncover the dual role of institutional environment, with regulatory turbulence weakening and policy support strengthening the indirect influences of BO on export performance via external and internal branding capabilities.

This study advances branding literature by conceptualizing and empirically testing the role of BO associated with internal and external branding capabilities and, subsequently, with export performance.

The research findings indicate that brand-oriented SMEs must actively engage in the development of branding capabilities to improve their export performance.

While brand creation is essential for the success and growth of SMEs competing in the worldwide marketplaces, there is a dearth of research explaining the underlying mechanisms and boundary conditions through which BO influences export performance.

Data envelopment analysis (DEA) has wide applications in the agricultural sector to evaluate the efficiency with crisp input and output data. However, in agricultural production, impreciseness and uncertainty in data are common. As a result, the data obtained from farmers vary. This impreciseness in crisp data can be represented in fuzzy sets. This paper aims to employ a combination of fuzzy data envelopment analysis (FDEA) approach to yield crisp DEA efficiency values by converting the fuzzy DEA model into a linear programming problem and machine learning algorithms for better evaluation and prediction of the variables affecting the farm efficiency.

DEA applications are focused on the use of a common two-step approach to find crucial factors that affect efficiency. It is important to identify impactful variables for minimizing production adversities. In this study, first, FDEA was applied for efficiency estimation and ranking of the paddy growers. Second, the support vector machine (SVM) and random forest (RF) were used for identifying the key leading factors in efficiency prediction.

The proposed research was conducted with 450 paddy growers. In comparison to the general DEA approach, the FDEA model evaluates fuzzy DEA efficiency giving the user the flexibility to measure the performance at different possibility levels.

The use of machine learning applications introduces advanced strategies and important factors influencing agricultural production, which may help future research in farms' performance.

This case study would enable students to understand the concept, process and advantages of mergers and acquisitions as a growth strategy with respect to 1mg. Also, the students would be able to use the threats, opportunities, weaknesses and strengths matrix to map 1mg’s strengths, weaknesses, opportunities and threats.

This case study analyses the transformation journey of 1mg to Tata 1mg, one of the most trusted internet pharmacies in India. This case describes a small start-up that was launched in 2013 and had made many acquisitions since then. This case revolves around Tata Digital’s purchase of 1mg. The case starts out by explaining 1mg’s financial situation and why the company was acquired. This case study focuses on how the integration helped Tata Digital and 1mg realize their respective missions. Furthermore, the case study illustrates the benefits and difficulties of this integration.

This case study is basically aimed at postgraduate management students; it can be used in strategic management and health-care courses. Students can understand the concept of diversification and acquisition with the help of this case study. Students can also gain an insight into the organic and inorganic diversification as a growth strategy.

Teaching notes are available for educators only.

CSS 11: Strategy.

BigBasket.com, an online supermarket established in December 2011 in Bangalore, India, had become one of the major players in the Indian online grocery market by the end of March 2016.₁ Run by Innovative Retail Concepts Private Limited, BigBasket.com was operating in more than 23 cities across the country in 2016. The online grocery market in India was in a stage of growth and transformation, fuelled by India's large urban population who sought a lifestyle of convenience and ease. It had also attracted many entrepreneurs who competed fiercely with each other in a market characterised by thin margins. Intense competition ensured that only a few companies were able to survive and sustain themselves. One of these companies was Big Basket, which succeeded in spite of the competition, attracting Series D_a funding worth USD 150_b million from the United Arab Emirates-based Abraaj Group in March 2016.₂