Nowadays, wage and salary system form the most important issues in any society, and its phenomenon takes dimensions with an expansion of a public organization and NGOs. Organizations provide employees satisfaction through different pay programs, which force them to work down more with higher quality. In this paper, we consider a survey of the payment system in an Iranian university as a case study. The population of this study consists of the existing documents, observations, working managers, supervisors and experts. This study is carried out from the desired community based on the data collected for a period of 18 months and the sample size is about 97 people. We use descriptive statistics to analyze the descriptive data. We also use the one-sample Kolmogorove-Smirnov test, t-test and Friedman test for the questions. The results of the existing payment system show that there is no any good condition and the employee & apos; s attitude towards this system are negative based on the collected data. Finally, some suggestions are recommended to improve the existing situation.

Emergency medical services (EMS) stations reduce mortality and irreparable damage from injuries through the timely treatment of patients. After performing the initial measures at the scene of the accident, if necessary, they transfer the patient to the hospital. In such cases, the goal is to save human lives. Thus, suggestions and solutions that can improve the performance of these centers are very welcome. One of the most important parameters in providing high-quality EMS is the timing of these services. Therefore, the location of these centers plays a key role in diminishing the response time to demand. In that regard, the location of these centers in cities, especially large and densely populated cities, is very important. In this study, in order to answer the mentioned questions, a linear mathematical model based on the maximum expected coverage model is presented. In this model, by considering the relative coverage conditions, the best locations in the city, as well as the coverage of demand points and distance traveled by the vehicles will be obtained. Furthermore, robust optimization (RO) is used to provide better situations for the operation of the model. Finally, according to the results, it is found that the proposed model has a better resolution time than nonlinear models and is also able to solve cases with high input data. The proposed model is implemented in District 10 of Tehran, Iran.

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.

The purpose of this study is to analyze the effect of green innovation (GI) on environmental performance (EI), the effect of green supply chain management (GSCM) on GI, and finally the effect of GI on environmental performance (EP) in the digital era. The study uses quantitative research methods and descriptive statistics. The sampling technique used is non-probability sampling with the type of purposive sampling. Respondents used in this study were 190 employees of small and medium enterprises (SMEs). Data was obtained by distributing online questionnaires through social media. The analytical technique used in this research is based on descriptive analysis and Structural Equation Model (SEM) using Partial Least Square (PLS). The results of this study indicate that GSCM practices have a significant positive effect on EI, GSCM practices have a significant positive effect on GI, GI has a significant positive effect on EP and, finally, GI mediates the relationship between GSCM and EP.

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.

Portfolio selection is a business process which has helped organisations identify an area of com-petitive advantage and it is a major concern to industrial players in the banking sectors. In order to enhance bank portfolio selection, cost, profitability, time and location are important parameters that decision-makers often consider. This study implements a fuzzy-TOPSIS (Technique for Or-der Preference by Similarity to Ideal Solution) framework to evaluate three potential portfolios (automated teller machine gallery, quick service point and branch) for a bank using the infor-mation from three decision-makers. An illustrative example of real bank information is used to demonstrate the proposed framework applicability. The complex proportional assessment of al-ternatives (COPRAS) method is also used as an evaluation technique and the results are com-pared, which yields that the results from the ranking order of fuzzy-TOPSIS and COPRAS were different. However, there is a consistency between the aggregation of intuition-based, fuzzy-TOPSIS and COPRAS ranks and fuzzy-TOPSIS ranking results. The presented framework is an easy-to-apply tool that improves portfolio selection decision in the banking system.

This study aims to explain the partial and simultaneous effect of green innovation, competitive advantage and empowerment on marketing performance. Quantitative research method is used through data collection from online surveys with a sample of 130 respondents. Green innovation variable with innovation indicators in processes and products, competitive advantage variable with unique product indicators, flexibility, customer relationships and empowerment variables are measured from the dimensions of market development, knowledge and facilities. The marketing performance variable is expressed in three dimensions, namely sales, growth, and market share. The measurement of respondents' answers to the questions in the questionnaire adopts a Likert scale consisting of seven alternative answers. Furthermore, the results of the questionnaire are analyzed using multiple linear regression with the help of the SPSS program. The results of the research indicate that competitive advantage and empowerment have a positive and significant effect on marketing performance, however, green innovation has a negative and insignificant effect on marketing performance. Simultaneously there is a positive and significant effect of green innovation, excellence competitiveness and empowerment on SME marketing performance.

Historically, cash dividends are the most important form of payout policy; however, they have been losing popularity relative to share repurchases. This paper examines the signaling effect of the payout decisions namely, cash dividends and share repurchases by BSE 500 index companies. It attempts to uncover the underlying forces behind the firm’s choices of payout policy in the Indian context. Using the standard ‘Event Standard Methodology’, a strong case of positive signaling is reported in case of repurchase announcements vis-a-vis cash dividend announcements. It is observed that cash dividends are not perceived by investors as positive signals as they prefer their earnings to be retained by the companies for growth prospects. In case of share repurchases, the existence of undervaluation, signaling and wealth transfer hypotheses is reported, consistent with the fact the share repurchases are welcomed by the Indian companies. The results would provide insights into the economics of the choice between cash dividends versus share repurchases as payout mechanism adopted by the sample companies. The findings would also be useful to the academia as well as industry in understanding the payout practice and the extent to which the Indian managers use the assumptions, models and decision rules regarding payout.

Liver disease indicates inflammatory condition of the liver, liver cirrhosis, cancer, or an overload of toxic substances. A liver transplant may reinstate and extend life if a patient has severe liver disease. In the last few years, machine learning (ML) based diagnosis systems have played a vital role in assessing liver patients which eventually leads to proper treatment and saves human life. In this study, we try to predict liver patients by adopting a hybrid feature extraction method to enhance the performance of the ML algorithm. Medical data frequently exhibits non-linear patterns and class imbalances. This is undesirable for the majority of ML algorithms and degrades performance. Here, we present a hybrid feature space that combines t-SNE, Isomap nonlinear features, and kernel principal components that can explain 90% of the variation in the data as a solution to this issue. Before feeding the ML model, data preprocessing techniques including class balancing, identifying outliers, and impute missing values are used. A simulation study and ensemble learning also conducted to justify the proposed prediction performances. Our suggested hybrid non-linear feature exhibits a 2-20 % improvement over existing studies and the ensemble classifier achieved an ideal and outstanding accuracy of 91.33 %.

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.