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This paper aims to study whether exporting enterprises are more productive in export-intensive industries. It also aims to identify the action area and policy direction for enhancing productivity in Indian textile manufacturing. Global integration has increased the volume of international trade. It is crucial for countries to have competitive enterprises to capture a larger share of the global economy. Improvement in productivity performance not only enhances competitiveness but also promotes growth in an economy.

A productivity analysis for the Indian textile manufacturing industry using firm-level panel data is conducted. The data are collected for 160 firms relevant to the period from 2007-2008 to 2012-2013 from Ace Equity database. Using the technique of data envelopment analysis, the output oriented Malmquist productivity index is computed and the sources of productivity change are identified. Also, a comparison between the productivity performance of the exporting and non-exporting firms has been made.

The results suggest that exporting firms are exhibiting better productivity performance and resource utilisation during the study period. Technology change and scale efficiency seem to be the major sources of productivity gain for exporting firms.

The research is limited to a single industry, reference database and methodology. There is scope for further in-depth, micro-level research to analyze the differences in drivers of productivity for exporting and non-exporting firms.

This paper provides validation to export promotional policies in the Indian textile industry by establishing better productivity performance of exporting firms. It also provides direction for managerial action by identifying efficiency component as the factor pulling down productivity.

The purpose of this paper is to develop a sensitive and cost effective colorimetric sensor for detection of methyl parathion (MP) using simple circuitry. A simple and sensitive concept of colorimetric sensor instrument represents a rapidly expanding field of sensor techniques to monitor MP neurotoxins is described within certain conditions of producing color in samples. The variation of intensity of color with concentration provides discrimination between different concentrations of MP. The colorimetric instrument displays well‐defined signals towards hydrolyzed samples of MP.

The principle of light intensity measurement has been applied to measure various concentrations of MP based on Lambert‐Beer theory. This device and its processes are useful for quantitative analysis of MP. The detection limits were found within a range of 0.1‐1.5 ppm.

The experiments from sophisticated analytical techniques are costly and time‐consuming processes that validate the proposed system.

This paper's original proposition of using quantification of MP with colorimetric sensor instrument obtained promising results.

The colorimetric sensor instrument provides a new method for quantification of MP in unknown samples within detection limits.

Evaluation of mechanical properties of undamaged and damaged steel rebars at elevated temperature finds its applications in development of steel material models likely to be used in designing reinforced concrete structural members subjected to earthquake triggered fire. In the present experimental investigation, 84 rebar specimens (cylindrical) of length 700 mm and diameters 8 mm, 10 mm, 16 mm and 20 mm were tested. Test specimens were prepared from the materials used in construction of full-scale reinforced concrete frame subjected to earthquake and fire. The specimens were initially stressed to a certain known limit (0.58 times yield stress f_y) to simulate damage caused by an earthquake. After inducing the damage, they were exposed to a desired temperature level (20 °C, 250 °C, 500 °C and 750 °C) in a circular furnace arrangement coupled with a 400 kN universal testing machine. The temperature was sustained inside the furnace for about 30 minutes to ensure a steady state heat transfer inside the specimen. The bars were then tested under uniaxial tensile loading conditions to failure. The elongation was recorded by using two LVDTs fixed between gauge lengths of 265 mm at the mid-height. Results obtained in the tests were utilized to carry out multiple linear regression analysis and propose constitutive models for damaged steel rebars and various relationships: Tensile Strength, Peak-Strain, Elongation and Elastic Modulus vs. Temperature, Stress vs. Strain at elevated temperatures.

Internet of things (IoT) is essential in technical, social and economic domains, but there are many challenges that researchers are continuously trying to solve. Traditional resource allocation methods in IoT focused on the optimal resource selection process, but the energy consumption for allocating resources is not considered sufficiently. This paper aims to propose a resource allocation technique aiming at energy and delay reduction in resource allocation. Because of the non-deterministic polynomial-time hard nature of the resource allocation issue and the forest optimization algorithm’s success in complex problems, the authors used this algorithm to allocate resources in IoT.

For the vast majority of IoT applications, energy-efficient communications, sustainable energy supply and reduction of latency have been major goals in resource allocation, making operating systems and applications more efficient. One of the most critical challenges in this field is efficient resource allocation. This paper has provided a new technique to solve the mentioned problem using the forest optimization algorithm. To simulate and analyze the proposed technique, the MATLAB software environment has been used. The results obtained from implementing the proposed method have been compared to the particle swarm optimization (PSO), genetic algorithm (GA) and distance-based algorithm.

Simulation results show that the proper performance of the proposed technique. The proposed method, in terms of “energy” and “delay,” is better than other ones (GA, PSO and distance-based algorithm).

The paper presents a useful method for improving resource allocation methods. The proposed method has higher efficiency compared to the previous methods. The MATLAB-based simulation results have indicated that energy consumption and delay have been improved compared to other algorithms, which causes the high application of this method in practical projects. In the future, the focus will be on resource failure and reducing the service level agreement violation rate concerning the number of resources.

The proposed technique can solve the mentioned problem in the IoT with the best resource utilization, low delay and reduced energy consumption. The proposed forest optimization-based algorithm is a promising technique to help enterprises participate in IoT initiatives and develop their business.

Switching behavior is predominantly seen in the consumer buying behavior of the mobile industry. This research aims to identify the factors influencing consumers to switch from their present mobile service provider. The consumer of the mobile industry operates in a dynamic and ever-changing environment that is difficult to predict, so this paper aims to focus on these issues.

The selection of factors was made with the help of qualitative study and quantitative research methods for further findings; with the help of a structured questionnaire, a total of 514 valuable responses were collected to get the results. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to analyze the data.

The finding shows that technology and edge-on-competition (TEC) and pricing have a negative influence on customer switching behavior. The switching cost (SC) is the most significant factor and has a positive impact, while service encounter failure (SEF) also positively impacts switching behavior.

The findings provide important implications for consumers switching brands if they are finding alternative offers that are cost-effective and SEF from service providers

The study of one of the largest mobile markets is learning lessons for other markets around the world. This study will be helpful for mobile service provider companies in their branding and marketing strategies. This study will also be helpful to practitioners, educators and researchers in understanding the consumer behavior of mobile users.

The learning of the largest mobile market will be a great learning lesson for other mobile markets around the world. Consumer behavior will help marketers follow ethical practices and make their strategy so a consumer does not switch brands and remain satisfied with the existing brand.

The study provides unique learning for practitioners, educators and researchers to understand the consumer behavior of mobile users. This will help marketers create factors that stop consumers from switching brands and develop strategies to retain customers.

To prolong engine life and reduce exhaust pollution caused by gasoline engines, the aim of this paper was to compare the lubrication properties of biofuel (ethanol) blends and pure unleaded gasoline.

Biofuels with a concentration of 0, 1, 2, 5 and 10 per cent were added to unleaded gasoline to form ethanol-blended fuels named E0, E1, E2, E5 and E10. Next, the ethanol-blended fuels and unleaded gasoline were used to power engines to facilitate comparisons between the pollution created from exhaust emissions.

Using ethanol as a fuel additive in pure unleaded gasoline improves engine performance and reduces exhaust emissions. Because bioethanol does not contain lead but contains low aromatic and high oxygen content, it induces more complete combustion compared with conventional unleaded gasoline.

Using biofuels as auxiliary fuel reduces environmental pollution, strengthens local agricultural economy, creates employment opportunities and reduces demand for fossil fuels.

Friction stir processing (FSP) is overviewed with the process variables, along with the thermal aspect of different metals.

With its inbuilt advantages, FSP is used to reduce the failure in the structural integrity of the body panels of automobiles, airplanes and lashing rails. FSP has excellent process ability and surface treatability with good corrosion resistance and high strength at elevated temperatures. Process parameters such as rotation speed of the tool, traverse speed, tool tilt angle, groove design, volume fraction and increase in number of tool passes should be considered for generating a processed and defect-free surface of the workpiece.

FSP process is used for modifying the surface by reinforcement of composites to improve the mechanical properties and results in the ultrafine grain refinement of microstructure. FSP uses the frictional heat and mechanical deformation for achieving the maximum performance using the low-cost tool; the production time is also very less.

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The purpose of this study is to investigate the flow interaction between the cavities and its impact on heat transfer. The role of the openings is examined and three strategies are considered: one opening, two openings on single side and two openings on double sides.

A two-dimensional laminar natural convection heat transfer in multilayered open cavities was numerically investigated. The governing equations in primitive variables were discretized by the finite volume method and solved by SIMPLE algorithm.

The results show that for the cavities with one opening, the flow in the cavities is connected with each other. The exhaust hot fluid from the lower cavity was entrained into the upper cavities by thermal buoyancy and hence the heat transfer in the upper cavities was decreased because of thermal accumulation. Two openings on the single side could strengthen the flow interaction between the cavities and then enhance the heat transfer. However, the double-sided openings eliminated the flow interaction between the cavities and thus the fluid flow and heat transfer characteristics in all cavities are independent. It was concluded that the flow interaction between the multilayered open cavities has an importance effect on the heat transfer in the cavities.

The flow interaction between the multilayered open cavities was illustrated. The effect of flow interaction on the heat transfer in the cavities was investigated. The role of openings in the flow interaction and heat transfer in cavities was explored. The cavity below affects above cavity for the openings on single side. No interaction exists between the cavities with openings on double sides.

By disentangling the impact of positive and negative shocks of GDP, FDI and oil consumption on electricity consumption, the purpose of this paper is to investigate whether this bifurcation significantly determines the level of electricity consumption in the short run and long run.

Using the recently developed nonlinear autoregressive distributed lag (NARDL) bounds approach, the study investigates the changes in the level of electricity consumption over a period of 1980–2015. The inclusion of a dummy variable for the possible structural break makes the electricity demand function more reliable. After checking the stationarity of data series, the study has employed the bounds test, which confirms the existence of the long run stability in the system. Further, using the VECM, the causality among the comprised variables has also been examined.

The findings confirm that not only the positive shocks but also the negative shocks in GDP have a positive and significant impact on electricity consumption in the long run. Similarly, the increased FDI has widened the scope of electricity consumption in the region, whereas the negative shocks’ impact is found negative in the long run. In comparison to GDP and FDI, the influence of the increased oil consumption on electricity demand is found negative and significant in India, which reveals that electricity acts as a significant substitute for oil consumption in the long run.

To the best of the literature evidences available, none of the studies in the past has examined electricity demand in an NARDL framework. The study may help in estimating the demand for electricity consumption comprehensively, as this approach captures the separate influence of favourable and unfavourable changes while determining the level of electricity consumption. This approach may be crucial for policy makers, especially in an energy importer country, such as India.