Uber and its main competitor Lyft are competing aggressively to attract more drivers and in turn limit the access of their competitors in the drivers’ supply base. To control the supply side, it is important to analyze the ride-sharing platforms from drivers’ perspective. Using Uber and Lyft drivers’ online reviews, it is shown that drivers are slightly rating Uber higher than Lyft. Additionally, comparing Uber and Lyft rating trend over time, the analysis shows that they are closely competing to attract more drivers. On the aggregate level, drivers count job flexibility, work/life balance, and meeting new people as the main advantages of working in the ride-sharing platforms. On the other hand, the results show that drivers suffer from insufficient compensation of their op-erating costs, poor job security, experiencing bad riders’ behavior, and poor customer service.

Inconel 600 is a super alloy known for its properties like low thermal conductivity and work hard-ening. The work hardening property of this alloy makes it harder and harder during successive passes of the tool during machining. Therefore, machining of this type of material demands inno-vation in tool material, selection of proper combination of parameters and their levels for economical machining. Coated carbide tool inserts are most widely used for machining Inconel alloys. These inserts are coated with special materials by PVD or CVD technique to reduce flank wear, improve surface finish of machined components and increase the material removal rate (MRR). In this work carbide insert coated with nanocomposite coatings like AlTiN and TiAlSiN commercially known as Hyperlox and HSN2 were used and their performance during machining of Inconel 600 was studied. As improper selection of process parameter influences on the quality of products and productivity, it is important to identify the optimum combination of input process parameters. Most of the time the influence of the input process parameters on the output parameters like MRR, surface roughness and flank wear is studied independently. Information obtained through single objective optimization may not be sufficient because industries desire to optimize all the output parameters, simultaneously. Multi-objective optimization is the only solution to satisfy the requirements of industries and genetic algorithm based multi-objective optimization is adopted in this work in order to get the optimum combination of input process parameters to obtain maximum material removal rate, minimum surface roughness and minimum flank wear simultaneously.

In this study, the efficiency of integration between Taguchi and TOPSIS in multi-response optimi-zation of powder mixed electrical discharge machining (PMEDM) process was evaluated. The in-put parameters, such as workpiece and tool electrode material, polarity, pulse on time (ton), pulse off time (toff), Current (I) and powder concentration have been selected to optimize two responses; namely surface roughness (Ra) and surface hardness (HV). The results show that titanium powder mixed dielectric fluid improves multi-response optimization efficiency in PMEDM. In addition, machining conditions, such as tool electrode material, powder concentration, pulse on time, polarity, current density, A×G and B×G interactions play a very important role on S/N ratio of C* whereby powder concentration has the strongest influence. TOPSIS -Taguchi is a potential method for multi-response optimization in PMEDM. However, the optimal results using ANOVA analysis show that there is a necessity to have more studies in TOPSIS-Taguchi to improve the in-tegration efficiency between two methods for optimizing multiple responses in PMEDM.

Form deviation of machined components need to be controlled within the required tolerance values for proper assembly and to serve the intended functional requirements. Methods like minimum zone circle (MZC) method, minimum circumscribed circle (MCC) method, maximum inscribed circle (MIC) method and least square circle (LSC) method are used to evaluate roundness error. Roundness error evaluation includes collection of co-ordinate points on the surface of the compo-nent and measurement using any of the above methods. Since, manual measurement of roundness error from these coordinate points is time consuming and less accurate, use of algorithms is highly appreciated. A detailed study of various optimization techniques showed that all evolutionary and swarm intelligence-based optimization algorithms require common control parameters and algorithm specific parameters. Improper tuning of these parameters either increases the computational effort or results in local optimal solution. Teaching Learning Based Optimization (TLBO) algorithm is used in this work as it does not require any algorithm specific parameters for the evaluation of roundness error. The results obtained are then compared with the results of Particle Swarm Optimization (PSO) algorithm to know the merits and demerits of both the algorithms when used for form measurement.

The NanoMQL technique is used to overcome the limitations of wet grinding due to economic and ecological problems. The performance measure is largely influenced by the process parameters such as table speed, depth of cut, air pressure, coolant flow rate and nanofluid concentration. In this paper, the performance of NanoMQL technique in terms of surface roughness was evaluated for hard and soft EN31 steel. The Experiments were conducted by response surface methodology (RSM) using statistical software to develop regression model of surface roughness and optimization was carried out using Jaya algorithm. The result shows that lowest value of surface roughness was obtained for NanoMQL of hard steel in comparison with soft steel under grinding environ-ments such as wet, MQL and NanoMQL. Hence to improve the performance of soft steel, the modeling and optimization of surface roughness were carried out. The significant parameters were considered for model development and validity of model determined through ANOVA (Analysis of variance). Lastly, the optimal values were determined using Jaya algorithm for minimum surface roughness and the percentage error observed to be close with the experimental test.

WEDM has evolved as a well admired technique for machining of difficult to cut materials such as superalloys. WEDM produces intricate shape and profiles of superalloys by thermoelectric erosion process. But as the process is carried out at very high temperature, the formation of heat affected zone, microcracks, recast layer, porosity etc. resulted in decreased surface integrity of machined specimen and becomes a big problem in WEDM. Discharge energy is the most influencing param-eters that affect the surface integrity of WEDmed samples. In this study, Inconel 825, widely used in aerospace industry for making of combustor casing and turbine blades, was machined with WEDM under different discharge energy. The surface topography of the WEDMed specimen was carried cut by using SEM, XRD and EDX techniques. It was observed from the SEM micrograph that the machined surface includes cracks, pockmarks, craters, and pulled out material. The density and sice of craters increase with increase in discharge energy. Surface crack density of 0.0138 μm/μm2 and recast layer thickness of 34.62μm was obtained for the machined sample at high value of discharge energy while at low value surface crack density of 0.0016 μm/μm2 and recast layer thickness of 20.99μm was observed. EDX and XRD analysis of the specimen showed that an ap-preciable amount of elements viz. Fe (Ferrous), Cr (Chromium), Cu (Copper), Ni (Nickel) are mi-grated to the surface of the workpiece at high value of pulse on time.

This study aims to determine the effect of advertising exposed by Lazada Indonesia on Facebook toward online purchase intention among the youth in Aceh, particularly the students of Syiah Kuala University. This study uses the Hierarchy-Effect Model to determine the advertising impact. This study used a simple linear regression test. The data were collected through a survey on 155 respondents selected using quota sampling technique from the 12 faculties of Syiah Kuala University. The results of simple linear regression analysis show that the exposure of advertising posted by Lazada Indonesia on Facebook significantly influenced the online purchase intention of Syiah Kuala University students with the impression of 73.2%. The higher the exposure of Lazada advertising on Facebook, the higher the online purchase intention of Syiah Kuala University students.

In recent time, corporate social responsibility (CSR) has been a critical item on the agenda for many business firms. Organizations now go beyond their economic obligations and are particular-ly meticulous in considering and assessing the impact of their activities on the environment. The objectives of the study are to examine the effect of Environmental focused CSR activities on cor-porate image and also to investigate the effect of Ethical CSR activities on Customer Relation. 240 copies of questionnaire were administered to Nigeria brewery staffs in Ogun State, Nigeria to get primary data that treated and tested appropriate research questions and hypotheses accordingly. The study adopted survey method and Cronbach Alpha for test retest reliability. The study found out that there was a significant relationship between ethical activity and customer relations and the relationship between environment activities and corporate image was significant. The study recommends the managements should ensure they plan strategically to enhance corporate social responsibility.

This research intends to formulate a new system for the promotion of online news in Indonesia. By using Information System Success Model (DeLone and McLean), this study develops a new system for promoting news through social media. The study focuses on journalistic work with Ethnographic methods from James Spardley. After doing Ethnographic research, this study pro-vides a comprehensive system, which can be used for all online mass media in order to promote the news to get the maximum number of readers.

This study explores the role of organizational culture (OC) in the relationship between entrepre-neurial orientation (EO) and Bangladeshi small and medium enterprises (SMEs) performance. Their relationship obtains a substantial scholarly attention, however very few empirical studies have been conducted among Bangladeshi SMEs. Generally, SMEs contribute to the economy through employment generation, poverty reduction, innovation, social cohesion, and so on, which in turn contribute to the growth domestic product (GDP) of Bangladesh. Hence, SMEs are considered as a key reactor of economic growth in Bangladesh. Grounded on the literature and theoretical fact, a model was developed and intended to examine this relationship. A quantitative survey technique was exercised and the data were collected from the randomly selected 384 owners of SMEs in Dhaka–Bangladesh. The data were analyzed by using SEM-AMOS. Based on the statistical results, EO and OC were significantly related to SME performance and OC was found to mediate the relationship between EO and SME performance. This study will help entrepreneurs as well as policy makers make better decisions for maximizing SME performance through improving OC in the competitive global economy.