All articles by Divya Narang

Impact of inter-industry mergers and acquisitions on the profitability

Inter-industry mergers and acquisitions have become common in today’s business world due to the benefits associated with them. The effect of mergers and acquisitions manifests in many ways determining a firm’s financial performance.

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Synergies in mergers and acquisitions

Synergies are a form of value addition created in merger and acquisition (M&A) activities. The value addition is a representation of the finances in the form of revenues and costs that these merged businesses can achieve. The value addition is not possible when businesses operate as separate entities. Formation of synergies can help businesses attain higher output, better placement of staff and good facilities (Ogada, Njuguna and Achoki, 2016). However, the past decade has witnessed a transformation in the formation of synergies. Traditionally, organizations merged to reduce costs or to expand their geographical presence. However, in the modern value creation process, businesses merge to expand their business capabilities into new domains (Loukianova, Nikulin and Vedernikov, 2017).

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The challenges of using forecasting techniques in logistics

Quantitative forecasting techniques refers to the approaches of forecasting used for examining the future trends by analysing the historical data. These forecasting techniques are applied through static methods like time series forecasting and casual forecasting (Spedding & Chan, 2010). The casual forecasting is conducted using simple or multiple regression models. On the other hand, casual forecasting is executed through the use of autoregressive moving average models. In logistics, time series forecasting focuses on analyzing the change in business strategies over a period of time. This forecasting is done using moving average and exponential smoothing which uses mathematical formulas to identify the forthcoming claim of the consumers addressed (Dombi, et al., 2018).

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Determinants of cross-country mergers and acquisitions

The 21st-century corporate world has witnessed the phase of globalization. It has led to technological advancement and the removal of trade barriers across countries. This is important as the competitive advantages of different organizations differ in terms of availability of raw material, investment, technology and so on. Therefore, in order to ensure long term growth potential, organizations have started forming cross country mergers and acquisitions (M&A). In contrast to the domestic mergers, cross country mergers help businesses in realizing the scope of new market opportunities. This is evident from the rise in the volume of cross border M&A.

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E-views advantages and disadvantages

E-views is the statistical package widely used by economists, researchers and analysts for statistical analysis, forecasting and model simulations (Aljandali and Tatahi, 2018).  It is used as a menu-driven object-oriented user interface. It allows writing simple programs in E-views programming.  This package offers multi-window design features that allow automation and presentation features. This article explains the comparative analysis of E-views advantages and disadvantages in the time series and panel data analysis. The advantages and disadvantages of the E-views are considered by comparing some of the commonly used statistical packages like STATA and SPSS.

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How to perform panel data analysis in E-Views?

E- Views offer an impressive toolkit that involves the series or the group of series that allows estimating panel data analysis ranging from the simplest to the complex types.  Performing data analysis in E-views is easier to understand as all the necessary statistical modelling can be performed by estimating the regression equation.  In addition to this, E-views allows the work files or the database from MS Excel, SAS, SPSS, STATA and Text file.  These work files can be used to perform a variety of statistical E-views including unit root test for checking stationarity, GARCH tests for heteroscedasticity, autocorrelation LM test, Granger causality test and least square test for performing the linear regression as steps in panel data analysis.

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The inflow of FDI in the key industries of India

India highly depends on foreign investments in the form of foreign direct investments (FDI) to fund its economic growth (Demirhan & Masca, 2008). Amongst all the sectors, the manufacturing sector and service sector has undergone a transformation and experienced high growth rates in the past few years. However, from the data on FDI, it can be observed that few key industries belonging to these two sectors have boosted at a faster rate than the others and attracted more FDI than the others.

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Challenges of using DEA-Solver for data envelopment analysis

Data Development Analysis (DEA) was developed in 1978, as a benchmarking technique for evaluating the efficiency or performance of a group of entities (Cooper, Seiford, & Tone, 2007). DEA analysis has emerged as a powerful tool of efficiency and benchmarking-based analyses, as it uses linear programming methodology. DEA analysis remains possible over various software. However, DEA Solver is the most recent and popular software for DEA analysis. Data Envelopment Analysis using DEA Solver, which is basically an MS Excel plugin and downloadable freely from DEA solver 8.0 includes 28 clusters of DEA models (“User ’ s Guide to DEA-Solver-Learning Version,” 2015). However, there are two versions of DEA solver, free and paid versions and can compute the results for maximum 50 decision-making units (DMUs). Read more »

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