Motivated by the agency theory and the need to examine the effect of separation of ownership and management, this study examines the determinants of profitability in different firm ownership structures and how different ownership structures impact profitability of listed firms between 2003 and 2013, using pooled annual data of 23 Ghanaian listed firms. Employing a number of static models (OLS, Random Effect and 3 Stage Least Squares), we find evidence that while profit determinants vary for listed firms given their ownership structures, ownership structures also affected profitability differently. Specifically, for listed firms, profitability was determined by capital intensity, liquidity, financial risk, age and GDP; for non-family owned listed firms, profitability was determined by capital intensity, liquidity, market share and age; for foreign owned firms, profitability was determined by capital intensity, liquidity, age and GDP; and for non-foreign ownership, profitability is determined by capital intensity, liquidity, financial risk, growth, age and GDP. When we examine the impact of ownership structure on profitability and find that family owned listed firms make 30% less profits compared to non-family owned ones, whilst foreign owned firms make 13% more profits than non-foreign owned ones. These findings confirm the agency theory which posits that separation of ownership and management, though may lead to agency problems, can positively affect profits. The study recommends that family owned listed firms should consider diluting ownership in order to grow more profits.

This work is focused on the influence of different friction stir welding (FSW) parameters on AA6082 T-6 and AA5083-O alloys welding quality, by using Taguchi, Grey Relational and Weight Method. Four welding parameters were investigated, namely tool rotation speed (TRS), welding speed (WS), tool pin profile (TPP) and shoulder diameter (SD). The optimized setting of these input parameters was investigated so that weld parts quality could be optimized. Analysis of variance (ANOVA) was used to investigate the effects of these welding process parameters on response variables, viz. elongation (EL) and ultimate tensile strength (UTS). Single response optimization was carried using Taguchi Technique while grey relational analysis (GRA) was used for simultaneous optimization of two responses. Once the optimal settings of control factors were identified, confirmation experiments were performed for the validation of results. In the multi-response optimization, TRS was found to have the maximum effect (57.9%), followed by WS, SD and TPP. Weight method was applied for providing the priority to the response (i.e. EL and UTS). The response with higher priority presented a weight equal to 0.7, while the lower priority given corresponds to a weight of 0.3.

The aim of this study is to explore the Days sales of inventory (DSI) as an indicator for inventory management among energy companies in Saudi Arabia for the period ranging from 2012 to 2019. The results of this study indicate that Aldrees company is ranked the first in terms of managing its inventory in which the average value of the DSI for the period 2013-2019 was 5 days. The second rank in terms of the DSI value for the period 2012-2019 belongs to Bahri company in which the average DSI was 23 days. While the third rank was Petro Rabigh in which the DSI average was 31 days. The results of this study should be useful to policy makers at the company management and other external stakeholders such as investors, auditors and lenders.

The present study's main objective was to analyze and determine the impact of digital marketing on the management of relationships with university students in times of Covid-19. The study was conducted from a quantitative approach, with a non-experimental transactional correlational transactional research design. A questionnaire was applied to 400 students aged 18 to 37 years belonging to the Continental University of the city of Huancayo in Peru. The analysis of the results was developed through a data structure and tabulation model with the SmartPLS3 program and it was obtained that Content Marketing has a significant influence on the operational management of customer relationships (p<0.05), as well as on the analytical and collaborative management of customer relationships. As for Social Media Marketing, it was identified that it has a significant influence on operational customer relationship management (p<0.05), as well as on analytical and collaborative customer relationship management, due to the fact that the digital media used by Continental University are attractive to parents and families. It is concluded that Digital Marketing has a great impact on the management of relationships with students of the Continental University in the city of Huancayo in Peru.

In today’s competition inherited business world, managing inventory of goods is a major challenge in all the sectors of economy. The demand of an item plays a significant role while managing the stock of goods, as it may depend on several factors viz., inflation, selling price, advertisement, etc. Among these, selling price of an item is a decisive factor for the organization; because in this competitive world of business one is constantly on the lookout for the ways to beat the competition. It is a well-known accepted fact that keeping a reasonable price helps in attracting more customers, which in turn increases the aggregate demand. Thus in order to improve efficiency of business performance organization needs to stock a higher inventory, which needs an additional storage space. Moreover, in today’s unstable global economy there is consequent decline in the real value of money, because the general level of prices of goods and services is rising (i.e., inflation). And since inventories represent a considerable investment for every organization, it is inevitable to consider the effects of inflation and time value of money while determining the optimal inventory policy. With this motivation, this paper is aimed at developing a two-warehouse inventory model for deteriorating items where the demand rate is a decreasing function of the selling price under inflationary conditions. In addition, shortages are allowed and partially backlogged, and the backlogging rate has been considered as an exponentially decreasing function of the waiting time. The model jointly optimizes the initial inventory and the price for the product, so as to maximize the total average profit. Finally, the model is analysed and validated with the help of numerical examples, and a comprehensive sensitivity analysis has been performed which provides some important managerial implications.

Employee productivity is one of the important management topics that received significant research attentions from several scholars and considered as a primary mechanism to enhance organizational success. Knowing what are the key factors that influence productivity is vital to ensure long term performance. This study examines the effect of work engagement on employee productivity in higher education sector. To accomplish this purpose, the primary data using survey instrument were collected from a sample of 242 employees at public universities in northern Malaysia using an online survey method. The collected data was analyzed using SPSS and Structural equation modelling on AMOS. The results indicated that work engagement had significant positive effect on employee productivity. Moreover, this study provides an evidence that all of the dimensions of work engagement namely vigor, dedication, and absorption have significant positive effects on employee productivity.

In this paper, a weighted transfer point location problem is developed in which demand points have probabilistic coordinates. The proposed model is formulated as a probabilistic unconstrained nonlinear programming and the optimum values of decision variables are obtained in the form of probability distribution functions. Because of the complexity in solving the developed model by using the traditional solution approaches, a new stochastic inference method called Probabilistic Role Base (PRB) is developed based on the derived optimum probability distribution functions of the decision variables. This method is used to infer the optimum or near optimum values of all decision variables without solving nonlinear programming model, directly. Finally, to demonstrate the efficiency of the developed algorithm, a numerical example is presented and the results are compared with the optimum solution.

The purpose of this research is to analyze the influence of social media marketing on small market purchase decisions and to analyze the influence of the store environment on small market purchase decisions. The study also analyzes the influence of sales promotion on small market purchase decisions as well as the effect of perceived value on small market purchase decisions. The study uses a quantitative method and data collection is performed by distributing questionnaires to 170 respondents who have bought goods in the small market. The research method in this study uses structural equation modeling (SEM) analysis using SmartPLS software. The results of this study reveal that all independent variables have some positive effects on consumer buying decisions. More specifically, the variables of small market environmental conditions, sales promotions, and profit values have significant influences on consumer buying decisions, while social media marketing variables has no significant effect on consumers' buying decisions.

The use of cement concrete as a stronger and more durable material than asphalt concrete in construction of the pavements has been increased during the past decades. This review paper investigates the effect of various input variables for the design of continuously reinforced concrete pavements. A literature review is prepared based on the efforts performed by many researchers to investigate the effect of different factors including temperature change, shrinkage, material properties of the concrete, and concrete slab/ subbase bond properties on the displacements and stresses in the concrete slab. It is found that the important role of concrete slab/ subbase bond strength has not been investigated properly as compared to other input variables.

Vendor managed inventory (VMI) is one of the most effective methods for reducing bullwhip effect. This paper presents a mathematical VMI model where there are three levels of central storage, multi distribution centers and various retailors. The problem is formulated as a mixed integer programming by considering uncertainty on different input parameters. To cope with uncertainty, the study uses rectangular fuzzy numbers. We also propose two metaheuristics; namely, genetic algorithm and particle swarm optimization to solve the resulted problems for some large instances. The preliminary results have indicated that genetic algorithm could solve the proposed model faster than particle swarm optimization in terms of CPU time reaching to slightly better objective functions.