In a Pay What You Want (PWYW) setting companies empower their customers to fix the prices buyers voluntarily pay for a delivered product or service. The seller agrees to any price (includ-ing zero) customers are paying. For about ten years researchers empirically investigate customer reactions to and economic outcomes of this pricing method. The present paper distinguishes PWYW from other voluntary payment mechanisms and reviews 72 English- or German-speaking PWYW publications, which appeared between January 2006 and September 2016 and contain 97 independent empirical data sets. Prior PWYW research is structured with the help of a conceptual framework which incorporates payment procedure design, buyer, seller, focal sales object and market context characteristics as factors potentially influencing customer perceptions of the PWYW scheme and their behavioral reactions to PWYW offers. The review discusses both consistent key findings as well as contradictory results and derives recommendations for future empirical PWYW research efforts.

This paper presents a multiobjective ant colony algorithm for the Multi-Depot Vehicle Routing Problem with Backhauls (MDVRPB) where three objectives of traveled distance, traveling times and total consumption of energy are minimized. An ant colony algorithm is proposed to solve the MDVRPB. The solution scheme allows one to find a set of ordered solutions in Pareto fronts by considering the concept of dominance. The effectiveness of the proposed approach is examined by considering a set of instances adapted from the literature. The computational results show high quality results within short computing times.

Nowadays, companies offer product bundles with special discounts in order to sell more products. However, it is important to note that customers show different levels of loyalties to companies, and each segment of the market has unique features, which influences the customers’ buying patterns. The primary purpose of this paper is to propose a novel model for product bundling in e-commerce websites by using market segmentation variables and customer loyalty analysis. RFM model is employed to calculate customer loyalty. Subsequently, the customers are grouped based on their loyalty levels. Each group is then divided into different segments based on market segmentation variables. The product bundles are determined for each market segment via clustering algorithms. Apriori algorithm is also used to determine the association rules for each product bundle. Classification models are applied in order to determine which product bundle should be recommended to each customer. The results demonstrate that the silhouette coefficient, support, confidence, and accuracy values are higher when both customer loyalty level and market segmentation variables are used in product bundling. Accordingly, the proposed model increases the chance of success in direct marketing and recommending product bundles to customers.

This research was conducted with the primary aim to investigate digital governance by examining empirical evidence regarding the application of Technology Acceptance Model (TAM) in public administration. The antecedents of TAM were explored to estimate behavioral intention and actual use in electronic public service in public administration in Indonesia. The research was conducted in Semarang, Central Java, Indonesia by employing simple random sampling techniques to collect a total of 182 respondents. By using Structural Equation Modeling–Partial Least Square (PLS-SEM), the results showed significant effects on perceived usefulness and attitude toward use. The variable of perceived usefulness was also empirically proven to have a significant effect on attitude toward use and behavioral intention. The findings found that attitude toward use had a significant effect on behavioral intention, and then behavioral intention was empirically proven to have an effect on actual use. Mediating analysis from the variables of perceived usefulness, attitude toward use and behavioral intention also found the mediating roles. Theoretically, these findings contribute to the digital governance framework by providing empirical evidence strengthening the relevance and affirming the application of the Technology Acceptance Model (TAM) in the context of public administration. Practically, these findings have managerial implications that the application of TAM in the public administration sector is relevant to be explored with a professional management model and a user-based approach in the development of digital applications and websites.

This study aims to explore whether or not social responsibility disclosure contributes to improve the financial information environment, through examining the impact of quantity and quality of corporate social responsibility (CSR) disclosure on the accuracy of analysts' forecasts and audit fees. Content analysis technique has been used to measure quantity and quality of CSR disclosure in annual reports of Saudi registered companies. OLS regression model is used to examine the relationship between the quantity and quality of CSR disclosure in the annual reports and the quality of the analysts' forecasts, and the audit fees. The results indicated that CSR disclosure provides useful information for outsiders, where it is associated with more accurate analysts’ expectations and reduced audit fees. These results suggest that CSR disclosure is associated with high quality financial information environment. This paper provides comprehensive analysis for financial information environment in Saudi companies. The findings of paper provide useful insights concerning the importance of social responsibility disclosure in Saudi business environment.

The aim of this paper is to provide a theoretical analysis on the mechanical power of the mass spring’s system. Some tests are conducted to experimentally evaluate the theoretical analysis and to investigate the mechanical energy ability of this concept. The authors suggest a system used for applications of energy harvesting from roads. The system is able to transform the kinetic energy produced by the passage of vehicles on the road for electrical energy based on the mass-spring using two technologies. The hybrid system has two goals. First, supply the entourage by a mechanism to produce significant electrical power used mainly for public lighting. A device is also provided for storing electrical energy for later use, for home lighting at night or in the case of bad weather. Second, the piezoelectric subsystem controls the spring’s health through analyzing the amplitude and shape of the voltage generated by a piezoelectric material. Finally, an experimental validation of the designed smart speed bump is presented.

The purpose of this study is to analyze the effects of the application of e-government, e-billing and e-SPT on taxpayer compliance. This type of research is quantitative research. The variables in this study consist of one dependent variable and three independent variables. The dependent variable is taxpayer compliance, while the independent variables are application of e-government, application of e-billing, and application of e-filing (e-SPT). The population in this study is Indonesian taxpayer. The sample in this research was 430 respondents who filled out the Likert Scale questionnaire. The sampling technique in this study was incidental sampling, with research instruments using online questionnaires distributed via social media. The data analysis technique in this study used a structural equation model (SEM) with SmartPLS 3.0 software. The results of this study indicate that the application of e-government had a positive and significant effect on taxpayer compliance, the application of e-billing had a positive and significant effect on taxpayer compliance, and the application of e-SPT had a positive and significant effect on taxpayer compliance.

This study aims to determine and analyze the effect of taxpayer awareness, tax knowledge, tax sanctions, and public service accountability on taxpayer compliance. The population of this study is the motor vehicle taxpayer in Kendari City. Samples are determined using accidental sampling techniques and the number of samples is determined using the Slovin formula. Based on the results of data analysis using multiple linear regression, the study found that taxpayer awareness, tax knowledge, tax sanctions, and public service accountability had positive and significant effects on taxpayer compliance in meeting tax obligations. This means that the higher the level of taxpayers’ awareness, tax knowledge, tax sanctions, and public service accountability, the better the taxpayer compliance.

Learning curves monitor the performance of workers for the given new task as well as it is a mathematical representation of the same learning process which can be analyzed after frequent repetitions. Now-a-days learning curve is a promotion effective tool for management concern with designing and controlling the process of imperfect production and redesigning unbalanced business operations in the production of goods or services related to scheduling, uncontrolled inventory management, quality management as well as inspection. Learning effect has direct impact in calculation of profit or loss. Generally, a business seller, in order to increase his sale prefers to lend his products to buyers for a definite period of time. There is no penalty before or during this definite time period however after the duration of lending time period is over, he will assign some extra charges. For this action, seller offers a trade credit financing period to his buyer. Assuming when buyer receives a lot he separates the defective and non-defective items by a screening process and defective items are then sold at a discounted price. The percentage of defective items decreases per lot according to learning curve. Seller too plans which condition is beneficial for good coordination of retailers and analysts. Different cases are explained broadly in this model to get maximum profit. In this paper, a fiscal construction feature model for imperfect quality items with trade credit policy is analyzed under the effects of learning. Total profit function per cycle has been derived with the help of involvement of different costs and related parameters for the retailers and a numerical example given ahead shows the verification of results. The impacts of key parameters of the model are studied by sensitivity analysts to deduce managerial insights.

Successful flow-shop scheduling outlines a more rapid and efficient process of order fulfilment in warehouse activities. Indeed the way and the speed of order processing and, in particular, the operations concerning materials handling between the upper stocking area and a lower forward picking one must be optimized. The two activities, drops and pickings, have considerable impact on important performance parameters for Supply Chain wholesaler companies. In this paper, a new flow shop scheduling algorithm is formulated in order to process a greater number of orders by replacing the FIFO logic for the drops activities of a wholesaler company on a daily basis. The System Dynamics modelling and simulation have been used to simulate the actual scenario and the output solutions. Finally, a t-Student test validates the modelled algorithm, granting that it can be used for all wholesalers based on drop and picking activities.