The objective of this work is to generalize the three echelon supply chain model proposed by Jaber and Goyal (2008) [Jaber, M. Y., & Goyal, S. K. (2008). Coordinating a three-level supply chain with multiple suppliers, a vendor and multiple buyers. International Journal Production Economics, 116, 95-103.] for multi-items where single item was considered in production and distribution. This paper develops the coordination amongst different parties in a three-echelon supply chain with a centralized decision process. Producer, suppliers and retailers are the parties of the supply chain where multiple suppliers deliver various types of raw materials to a producer; producer produces different types of items, multi-items, in different units of the factory and supplies the items to multiple retailers. Different deterioration rates for finished items and raw materials are also considered. The model developed of this paper guarantees that the local costs for the members either remain the same as before coordination, or decrease as a result of coordination. A numerical example along with graphical illustrations is considered and the sensitivity analysis is provided to test the feasibility of the proposed model.

This study develops an effective method to measure value chain performance and rank them based on qualitative criteria and to determine the ranking order of the various forms of performance under study. This approach integrates the advantage of grey systems theory and TOPSIS to evaluate and rank value chain performance. Grey-TOPSIS approach has been applied to measure and rank the value chain performance of various firms. The results indicate that the proposed model is useful to facilitate multi-criteria decision-making (MCDM) problem under the environment of uncertainty and vagueness. The model also provides an appropriate ranking order based on the available alternatives. The Grey-TOPSIS approach that will be useful to the managers to use for solving the similar type of decision-making problems in their firms in the future has been discussed. Even though, the problem of choosing a suitable performance option is often addressed in practice and research, very few studies are available in the literature of Grey-TOPSIS decision models. Also, Grey-TOPSIS model application in the tea processing firms is non-existence hence this study is the very first to apply this model in evaluating value chain performance in the tea processing firms.

In this paper, computational intelligence technique are presented for solving multi-point nonlinear boundary value problems based on artificial neural networks, evolutionary computing approach, and active-set technique. The neural network is to provide convenient methods for obtaining useful model based on unsupervised error for the differential equations. The motivation for presenting this work comes actually from the aim of introducing a reliable framework that combines the powerful features of ANN optimized with soft computing frameworks to cope with such challenging system. The applicability and reliability of such methods have been monitored thoroughly for various boundary value problems arises in science, engineering and biotechnology as well. Comprehensive numerical experimentations have been performed to validate the accuracy, convergence, and robustness of the designed scheme. Comparative studies have also been made with available standard solution to analyze the correctness of the proposed scheme.

Online transportation has widely spread across the globe in the past three years. It provokes changes in transportation management. Driver’s quality improvement is crucial to prevent problems related to accidents and driver-passenger relationships. This paper employs regression analysis to identify the effect of driving attitude, self-awareness, and social self-supervision on aberrant driving behavior in online taxi drivers in Indonesia. One hundred Grab and Go-Jek drivers are selected from the DKI Jakarta area. Data are collected via questionnaires. Data analysis, as well as statistical calculation, reveals the negative effects of social self-supervision on aberrant driving behavior.

This paper aims to determine factors that affect consumers’ intention to re-purchase by combining consumers’ attitudes and satisfaction in mobile shopping via sharing economy platforms. The research sample consists of 367 valid participants in the metropolitan area of Ho Chi Minh City who experienced buying products from brick and mortar retailers by using crowdshipping service, using PLS-SEM. The results confirm that Personal Innovativeness significantly affected Perceived Ease of Use (PEOU) and trust. Consumers' attitudes toward buying products via crowdshipping services in sharing economy platforms are determined by PEOU and trust, and their satisfaction of an purchasement is impacted by Check out attributes and Delivery attributes, leading to re-purchase an order via this platform. Brick and mortar retailers need to create a corporation with crowdshipping service platforms to increase sales during COVID-19 pandemic. Besides, shipping quality should be ensured to satisfy consumers which leads to long-term usage.

Supplier selection management has been considered as an important subject for industrial organizations. In order to remain on the market, to gain profitability and to retain competitive advantage, business units need to establish an integrated and structured supplier selection system. In addition, environmental protection problems have been big solicitudes for organizations to consider green approach in supplier selection problem. However, finding proper suppliers involves several variables and it is critically a complex process. In this paper, the main attention is focused on finding the right supplier based on fuzzy multi criteria decision making (MCDM) process. The weights of criteria are calculated by analytical hierarchical process (AHP) and the final ranking is achieved by fuzzy technique for order preference by similarity to an ideal solution (TOPSIS). TOPSIS advantage among the other similar methods is to obtain the best solution close to ideal solution. The paper attempts to express better understanding by an example of an automobile manufacturing supply chain.

Suitable project manager has a significant impact on successful accomplishment of the project. Managers should possess such skills in order to effectively cope with the competition. In this respect, selecting managers based on their skills can lead to a competitive advantage towards the achievement of organizational goals. selection of the suitable project manager can be viewed as a multi-criteria decision making (MCDM) problem and an extensive evaluation of criteria, such as Technical skills, experience skills, Personal qualities and the related criteria must be considered in the selection process of project manager. The fuzzy set theory and MCDM methods appears as an essential tools to provide a decision framework that incorporates imprecise judgments and multi criteria nature of project manager selection process inherent in this process. This paper proposes the joint use of the Fuzzy DEMATEL (FDEMATEL) and Fuzzy VIKOR methods for the decision-making process of selecting the most suitable managers for projects. First, with the opinions of the senior managers based on project management competency model (ICB-IPMA), all the criteria required for the selection are gathered. Then the FDEMATEL method is used to prioritize the importance of various criteria and FVIKOR used to rank the alternatives in a preferred order to select the best project managers from a number of alternatives. Next, a real case study used to illustrate the process of the proposed method. Finally, some conclusions are discussed at the end of this study.

The Covid-19 pandemic has forced people to maintain physical distance during everyday contact, known in popular terms as physical distancing, which triggers the banking industry to accelerate its digital transformation to maximize service to customers. It aims to make business processes to work more efficiently and to drive force that will create various business opportunities. This study aims to explain the main factors that contribute and influence the adoption of internet and mobile banking services, which are antecedents of customer attitudes towards the intention to use these services. This study uses primary data and the unit of analysis is 200 respondents of Bank Bukopin customers who are users of its internet and mobile banking services with a replication of the technology acceptance model (TAM) in the context of internet service adoption and mobile banking. This study uses non-probability sampling with purposive sampling technique, and to analyze the research model, the Partial Least Square (PLS) method is used with the SmartPLS 3.0 M3 program as a tool. The research findings indicate that the intention to reuse is directly affected significantly by perceived ease of use, trustworthiness, and attitude to use. Perceived benefits do not have a significant effect on directly affecting intention to use, but have a positive and significant effect if they get a mediating role from the attitude of using. This study proves the existence of a mediating role for perceived benefits and beliefs on attitudes to use. This study also strengthens the evidence that attitudes have a strong and positive and significant effect on intention to reuse, and are able to fully mediate the effect of perceived ease of use, perceived usefulness and trust on intention to reuse. Bank Bukopin management and bankers are also expected to use the results of this study to evaluate and take corrective action on aspects that are deemed incapable of encouraging the adoption of their internet and mobile banking services and creating customer loyalty to continually use the services they provide.

In this paper, an attempt is made to characterize the preservation technology for deteriorating items to reduce the deterioration rate. This model assumes a single producer and single supplier and formulates a production model with a time varying rate of deterioration rate. Here production and demand are treated as a fuzzy variables and total cost is minimized for both the crisp and fuzzy model. Shortage is allowed on the supplier’s part, which is partially backlogged. A solution procedure is presented to determine an optimal replenishment cycle and total cost per unit time, which is a convex function of preservation technology cost. Results have been validated with relevant example. In a way, the proposed model provides a unique theory to reduce the deterioration rate for the production model.

The research conducted by this researcher intends to analyze the effect of trust and ease of use on purchase decisions and repurchase intention. The data collection method in this study uses a questionnaire with 130 consumers who have purchased at an online store. The analytical method used is descriptive analysis, and the test instrument uses SEM AMOS. in this study using four variables, thirteen dimensions and twenty-six indicators. The results show that trust and ease of use have a significant effect on buying decisions and also have a significant effect on repurchase intention, and purchase decisions have a significant and significant effect on repurchase intention. so it can be said that trust and ease of use are the entry points that make consumers start to move to the next stage, therefore online store marketers need to pay attention.