This study was conducted to measure the level of economic linkage in key economic zones in central Vietnam generally and to measure the level of economic linkage in the tourism sector. Secondary data were collected from the Statistical Yearbook published by the General Statistics Office and the Local Bureau of Statistics and primary data collected from surveys of 102 hotels and tourism firms in the center of Vietnam. We used the Moran Index (I) to quantify overall economic aggregation across the region and that scoring method was used to measure the degree of linkage in regional tourism. The results show that the level of overall regional economic linkages was very low and this was also relevant when analyzing the tourism sector in some areas of the center of Vietnam. Based on the results, some recommendations are given for strengthening economic linkages in key economic regions of Vietnam.

The scaling of social innovation is an important issue in social enterprises for sustainability. The scenario is due to the social enterprise capabilities to ensure the social program’s impact on society to become wider and deeper. Thus, social innovation helps to identify the social problems and target actions to address the social complex problems by social enterprise capabilities. This study investigates the factors of social enterprise capabilities in enhancing social innovation for sustainabil-ity and for eliminating the social barriers. In addition, the study discusses the relationship between social enterprise capabilities to scale social innovation. The study uses cross-sectional design and collects the necessary data from 136 social enterprises in Malaysia for the survey. The findings show that social enterprise capabilities for earning generation, replicating, and stimulating had a positive relationship with scaling social innovation when the level of significance was 0.05. Accordingly, the social enterprise owners are required to improve their capabilities to reach a higher scale of social innovation for growth and sustainability.

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.

Poor urban planning and traffic congestion lead to excessive delays in workers’ transit times and decrease their quality of life, especially in emerging countries. Several medium and large companies have a need to hire a transport service for their staff. In this type of transportation system, there is a heterogeneous fleet of vehicles, which are assigned to a set of predefined routes. However, the total transport delay can be even greater if the private transportation system is inefficient or not controlled. The approach proposed in this study seeks to optimize the private transport service by defining the best allocation of its fleet to its routes. A mathematical model is proposed to minimize user wait times. This approach is validated using real data obtained from a transport company in Co-lombia. The results demonstrate the quantitative benefits that can be achieved when the proposed approach is implemented, represented by a considerable reduction in user wait times.

Financial management faces 3 important decisions, namely funding, investment and dividends. The purpose of this study is to determine the effects of the fundamental factors such as leverage in financial management. Leverage is one of the factors of funding, investment and dividends that interdependently affect the value of the company. The method used in this study uses 2SLS (two-stage least square). There are 4 (four) equations in this study, namely the equation of leverage, investment, dividend and company value. Interdependence is shown based on leverage, investment and dividends. In the interdependence equation leverage, investment and dividends not only on one side act as endogenous variables but also act as exogenous variables on the equation of the company values. The results of the research on leverage equations show that investment affects leverage but dividends do not affect leverage. The investment equation shows the results of both leverage and dividend variables would not affect investment decision. Dividend equation also shows that leverage and investment variables also do not affect dividends. Moreover, the results of the company value equation show that the leverage variable would not affect the value of the company. But in-vestment and dividend variables affect the value of the company. The conclusion of this study is that there was a mutually influential relationship between the three variables of financial management before influencing company value.

Management towards control of risk issues appeared as an important area in E-supply chain for researchers in the present fast growing market. Extensive research has been accomplished in this area, but still there are several risks and uncertainties. The present research aims to identify and consolidate various e-supply risk factors for developing a constructive measurement model. The study also assesses the influence of risk factors over e-supply chain operation in Indian mechanical industries. Thus, after a thorough research and detailed discussion, 38 Risks factors are identified through literature to prepare the questionnaire. A questionnaire based survey is carried out for collecting the primary data from 148 experts of mechanical manufacturing industries located in the national capital region of India. The research methodology is combined with descriptive statistics and factor analysis. SPSS 21 software tools is used for investigating the reliability and Amos Graphics 21 software is used for the fitment validation of the theoretical construct. The results suggest that all risk issues create significant negative influence e-supply chain process. The results also show negative effects of risks over e-supply chain performance. The current research outcome develops a stochastic model based on the e-supply chain risk factors used for reducing risks in e-supply chain operation.

Work engagement has gained much prominence over the recent decades. With the aim of address-ing the global engagement crisis, the current study examined how prominent job resources such as supervisor support, coworker support and meaningful work perceptions can influence work engagement. The study also tested the moderation of meaningful work on these relationships. 537 questionnaires were distributed among the employees of six large banks of Pakistan. Structural equation modeling using Smart PLS 2.0 resulted in strong positive relationship of supervisor support and coworker support with work engagement. The findings also concluded strong positive relationship between meaningful work and work engagement. Notably, the bootstrapping results also played significant moderation of meaningful work on the relationship between supervisor support and coworker support with work engagement. The study forwards theoretical and practical implications for future.

Human resource management (HRM) was first developed as a corporate business strategy that aimed to retain employees in the workplace and to develop personnel who generated results and whose capabilities could be effectively utilized. In recent years, human resource perspectives have been emphasized in personnel management by hospital nursing organizations. This study examined effective HRM strategies for creating an attractive nursing practice environment from the perspec-tive of “magnetism.” A questionnaire (“32 Items Regarding Effective Human Resource Management Policies”) was developed. The Practice Environment Scale of the Nursing Work Index was employed to assess the type of environment in which nurses wished to continue working, and factors contributing to a desirable nursing practice environment were defined as “magnetic.” Analysis of data obtained from nursing managers (n=305) yielded five factors that were effective HRM policies for hospital nursing organizations. It was also shown that the nursing practice environment was made more attractive by incorporating more of these policy elements. The following six strategies were identified: (1) enhancement of personal career development and organizational develop-ment; (2) goal management and personnel evaluations to assure the quality of patient care and pro-mote team collaboration; (3) flexible hiring and transfer policies based on business execution; (4) promoting outside interactions to make the organization an open system; (5) ensuring support for career development; and (6) supporting a safe and healthy nursing practice environment by enhancement of manpower.

In the present scenario, the Six Sigma tools and techniques are used by various manufacturing industries, exporting industries and even service organizations. It focuses on improving the quality of the products, cutting down the extra costs, reducing the variations and satisfying the customers. This case study follows the Six Sigma tools called DMAIC methodology to identify and analyze various root causes of the capacitors rejection problems, which influence the performance of the company and suggests solutions to counter with it. The issue not only causes financial loss to the company but also hinders future growth in form of customer dissatisfaction. The results of the implementation indicate significant improvement in the quality of the product and cost reduction.