The constrained applications of conventional machining processes in generating complex shape ge-ometries with the desired degree of tolerance and surface finish in various advanced engineering materials are being gradually compensated by the non-traditional machining (NTM) processes. These NTM processes usually have higher procurement, maintenance, operating and tooling cost. Hence, in order to attain their maximum machining performance, they are usually operated at their optimal or near optimal parametric settings which can easily be determined by the application of dif-ferent optimization techniques. In this paper, 133 international research papers published during 2012-16 on parametric optimization of NTM processes are extensively reviewed to have an idea on the selected process parameters, observed responses, work materials machined and optimization techniques employed in those processes while generating varying part geometries for their industrial use. It is observed that electro discharge machining is the mostly employed NTM process, applied voltage is the identified process parameter with maximum importance, surface roughness and material removal rate are the two maximally preferred responses, different steel grades are the mostly machined work materials and grey relational analysis is the most popular tool utilized for para-metric optimization of NTM processes. These observations would help the process engineers to attain the machining performance of the NTM processes at their fullest extents for different work material and shape feature combinations.

Increased demand for transportation is inevitable along with the growth of social welfare and economic development. Furthermore, providing cheap transportation services has brought about a bulk of benefits in the ever-expanding development of countries. Therefore, the optimization of fuel consumption in the transportation sector is essential for the continued low cost of transportation and reduced amount of pollution caused by the traffic. A major strategy for optimizing fuel consumption and transportation costs in the transportation of goods and passengers is the proper design of transportation networks. Accordingly, in this study, hub covering location problem is modeled taking into account the queuing system in order to minimize the cost of the whole network as well as to minimize emissions of greenhouse gases. The model presented in this study includes uncertain parameters of demand and transportation costs. To control the parameters, a robust-box optimization method is used. As the hub covering network model is multi-objective and NP-hard, three meta-heuristic algorithms; namely MOPSO, NSGA II and MOALO are presented. Computational results show the high efficiency of the MOALO algorithm for obtaining efficient problem-solving in large sizes.

Distribution centers selection is a vital task of any company to reduce costs, improve efficiency of transport flows, which yields customer satisfaction. To select the suitable distribution centers, many quantitative and qualitative criteria must be considered in the selection process. Therefore, distribution centers selection can be seen as a multi-criteria decision making (MCDM) problem under vague environment. Single-valued complex neutrosophic sets (SVCNSs), which is generalized of fuzzy sets, complex fuzzy sets and intuitionistic fuzzy sets; can better represent the vague information than the other sets. This paper aims to propose a new the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach based on SVCNSs to select the locations of distribution center. In the proposed TOPSIS approach, the importance weights of criteria, the ratings of alternatives, and their aggregated values are assessed and evaluated using SVCNSs. Then, this paper defines the operational rules of SVCNSs and calculates the aggregated weighted ratings of alternatives. Furthermore, the score, accuracy and certainty function are developed to rank the alternatives. Last, an application to the distribution center location selection is presented to show the advantages of the proposed approach.

The purpose of this study is to find answers to the research problem posed, namely the implementation of the long-term cooperation strategy between suppliers and companies through supplier commitment factors with companies and supplier communication with companies that can improve the company's supply chain performance. The populations in this study are suppliers of manufacturing companies listed on the Indonesia Stock Exchange (BEI) in 2016-2020. Data were collected using a questionnaire containing questions related to research. Furthermore, in this study a theoretical model was developed by proposing 5 hypotheses to be tested using Structural Equations Modeling (SEM) using AMOS software. The results showed that the function and existence of the antecedents of the Long-Term Cooperation Strategy have a high role in determining Supply Chain Performance. Based on the influence analysis, it can be concluded that Communication has a higher influence on Supply Chain Performance compared to Commitment.

This study is carried out to investigate the effect of five factors of the Total quality management practices in healthcare on employee’s performance in public hospitals in Turkey. The TQM practices are Top management commitment, customer focus, people management, continuous improvement, and process management. The study adopted a quantitative research method through a survey questionnaire at three public hospitals, 200 valid responses were collected and used as a source of data to test the hypotheses of the study. Hierarchical multiple regression was used for analyzing the collected data, the study indicated that TQM factors have a significant effect on employees’ performance and the moderating effect of training has increased the correlation between employees’ performance and the TQM factors.

The study aims to examine the impact of supply chain linkages on the performance of businesses. Quantitative research is used by implementing the analysis of the SEM linear structure model. A survey is conducted consisting of 598 samples - experienced managers who had the knowledge of the management of supply chain activities in enterprises in Vietnam. Research results show that supply chain linkages, although not having a direct impact, has an indirect impact on the business performance of enterprises through the intermediary factors of trust and business strategy and the opportunistic behaviors of the participating members. Also, research has demonstrated that opportunistic behaviors have negative effects on trust among members of the supply chain.

The study examines the effect of the supply chain finance (SCF) on the corporate financial performance measured in terms of Return on Assets (ROA), Tobin's Q, and Gross Operating Profit (GOP) in the material sector of Saudi Arabia. The study selects a sample of 42 companies from the material sector listed on Tadawul starting in 2008 and ending 2019. A panel regression in terms of pooled OLS, fixed and random effects, and panel GMM is estimated to report the empirical results. The results report a negative and significant effect between the financial performance variables and supply chain finance, specifically with ROA with pooled OLS and fixed and random effects models. The results of panel GMM also show a negative and significant effect between all the financial performance variables and financing supply chain. The results are useful to academicians and the managers in the materials, inventory, and sales sections, and supply chain managers to integrate finance and SCM to achieve corporate benefits.

The objective of the research was to determine the impact of Digital Marketing on customer relationship management (CRM) in an educational institution in central Peru. The study was carried out from the quantitative approach, with a non-experimental correlational transactional research design. A questionnaire was applied to 228 parents between the ages of 30 and 50 who belong to an educational institution in the city of Concepción in Peru. Using the structural equations model, it was found that Content Marketing has a significant influence on the operational management of customer relationships (p <0.05), as well as on the analytical management of customer relationships (p <0.05). Regarding the Marketing of social networks, it was identified that it has a significant influence on the operational management of customer relationships (p <0.05), as well as on the analytical management of customer relationships (p <0, 05), because the media used by educational institutions are attractive to parents. It is concluded that Digital Marketing has a great impact on customer relationship management (CRM) in the educational sector of a city in central Peru.

This study examines the mediating effect of supply agility on the relationship between trust and commitment and supply chain performance. The study examines the direct effect of trust and commitment on supply chain performance, trust and commitment on supply agility and supply agility on supply chain performance. The study also examines the indirect effect of trust and commitment on supply chain performance with supply agility as an intervening variable. The research sample consists of 100 respondents who sell chicken meat in seven districts in Lebak Regency, Banten Province, Indonesia. Data are collected using purposive sampling technique. The statistical tool used is the SmartPLS 3.0 application. The results of this study indicate that; trust has no effect on supply chain performance, commitment has a significant effect on supply chain performance, trust has a significant effect on supply agility, commitment has a significant effect on supply agility, and supply agility has a significant effect on supply chain performance.

The goal of this research is to investigate the relationship between human resource management and tourism supply chain management, as well as the effects of human resource and tourism supply chain on customer satisfaction and operation performance. The research was carried out in Vietnam at several tourist destinations. The study found 297 viable samples after screening the sample. A Partial Least Squares (PLS) algorithm was used to process the data. The study's findings revealed a link between human resources and supply chain management in the tourism business. Furthermore, the study discovered that human resource management uncertainty had an impact on organizational performance.