This research study examines the impact of information technology on firm profitability and stock returns. Using a comprehensive dataset of firms across various industries, this research employs rigorous statistical analysis techniques to investigate the relationship between IT investments, firm profitability metrics, and stock returns. The study focuses at how IT investments affect financial performance measures including return on assets (ROA) and return on equity (ROE), with P-values of 0.34 and 0.12, respectively. Furthermore, the study investigates the influence of IT on stock returns, taking into account market capitalization, industry trends, and macroeconomic variables. This study's conclusions center on the beneficial association between IT investments and corporate profitability. The T-value for the IT investment has risen to 6.5. The analysis reveals that firms that strategically leverage IT investments tend to experience higher profitability metrics. Additionally, the research demonstrates the impact of IT on stock returns, highlighting the significance of IT as a driver of firm value and investor confidence. Moreover, this study delves into the mechanisms through which IT investments contribute to firm profitability and stock returns. It investigates the mediating role of factors such as process innovation, customer relationship management, and supply chain optimization, which facilitate the translation of IT investments into improved financial performance. The implications of this research are significant for both practitioners and policymakers. The findings provide valuable insights for firms seeking to enhance their profitability and create shareholder value through strategic IT investments. Additionally, policymakers can use these findings to formulate policies and initiatives that promote the adoption and effective utilization of IT in businesses across various sectors
The purpose of this research was to investigate the beneficial effects of phosphatidylcholine in reducing changes in both lipid and protein profiles in addition to atherogenic index in adult rats with fructose-induced metabolic syndrome. Thirty-six mature Wistar Albino female rats (Rattus norvegicus) (aged 12-15 weeks and weighing 200±10 g) were divided randomly into four groups (G1, G2, G3, and G4); then variable treatments were orally administered for 62 days as follows: G1 (Control group), received distilled water; G2, treated with phosphatidylcholine (PC) orally (1 g/kg BW); G3 (Fr), orally dosed with 40% fructose and 25% fructose mixed with drinking water; G4 (Fr+PC), were also intubated with 40% fr
... Show MoreThe traction property is one of the important mechanical properties, especially the rotary parts which are subjected to constant and variable loads There are many methods used to improve this property, and the shoot peening by metal balls is considered the most critical one. the study focuses on this characteristic of steel CK35 used in many engineering applications as the rotating shafts and railway This study shows that the fatigue strength is improved by14% after shoot peening with metal balls. The study includs the rehabilitation of damaged samples as a result of fatigue corrosion. The standard solution adopted was 36% MgCl2 with a 30 days immersion period. These samples has been improved by 6% after it decreased by18% d
... Show Moreplanning is among the most significant in the field of robotics research. As it is linked to finding a safe and efficient route in a cluttered environment for wheeled mobile robots and is considered a significant prerequisite for any such mobile robot project to be a success. This paper proposes the optimal path planning of the wheeled mobile robot with collision avoidance by using an algorithm called grey wolf optimization (GWO) as a method for finding the shortest and safe. The research goals in this study for identify the best path while taking into account the effect of the number of obstacles and design parameters on performance for the algorithm to find the best path. The simulations are run in the MATLAB environment to test the
... Show MoreThe synthesis of new substituted cobalt Phthalocyanine (CoPc) was carried out using starting materials Naphthalene-1,4,5, tetracarbonic acid dianhydride (NDI) employing dry process method. Metal oxides (MO) alloy of (60%Ni3O4 40%-Co3O4 ) have been functionalized with multiwall carbon nanotubes (F-MWCNTs) to produce (F-MWCNTs/MO) nanocomposite (E2) and mixed with CoPc to yield (F-MWCNT/CoPc/MO) (E3). These composites were investigated using different analytical and spectrophotometric methods such as 1H-NMR (0-18 ppm), FTIR spectroscopy in the range of (400-4000cm-1), powder X-rays diffraction (PXRD, 2θ o = 10-80), Raman spectroscopy (0-4000 cm-1), and UV-Visib
... Show MoreEriobotrya japonica Lindl., named as loquat, is a subtropical fruit tree of the family Rosaceae which is well known medical plant originated in Japan and China. Loquat portions, like leaves, peels and fruits have been shown to possess various health usefulnesses. In Chinese classical medicine, it is vastly utilized in many illnesses, like gastroenteric disorders, diabetes mellitus, pulmonary inflammatory diseases and chronic bronchitis. Loquat plant contain many active constituents, such as flavonoids, carotenoids, vitamins, polyphenolic compounds, other that have many biological effects like anti-tumor, anti-diabetic, anti-inflammatory, anti-mutagenic, antioxidant, antiviral, antitussive, hepatoprotective and hypoli
... Show MoreThe method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.
In this, search the comparison between binary lo
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