The aim of this study is to investigate the influence of logistics and distribution processes on business process reengineering by adopting green innovation for sustainable transformation. Guided by the Resource-Based View (RBV), the study examines logistics and distribution processes in relation to business process reengineering (BPR), through green innovation adoption, towards achieving sustainability goals. Drawing on a conceptual framework based in supply chain management and BPR theories, the study uses Structural Equation Modeling-Partial Least Squares to analyze data collected from respondents within the target industries. The results show that streamlined logistics and distribution processes help to ensure the success of Green Innovation as part of BPR, strengthening the trend towards sustainable transformation. The study accentuates the importance of logistics management in enabling environmental stewardship and enhanced operational efficiency, providing some key ideas for improving both theoretical developments and future directions as well on practice ground to adopt sustainable supply chain trends.

This article examines the possibility of answering the question” can the Arab’s natural gas secure the gas requirements in Europe? “To answer the question, an economic analysis of natural gas was conducted to examine reserve, supply, demand, and international trade first. Second, an economic model to examine distances and transportation costs, for transferring goods from various points of supply to various points of demand, was adopted. The North-West Corner model approach, a QM for Windows-based economic strategy to solve the transportation model problem structure in linear programming, has been used in this regard. Our findings demonstrate that the model is suitable for application since it provides the least distances and the least transportation costs compared to other alternatives. The model estimated that a cost of $309.41 is required to transfer one MMBtu of LNG from origins to final destinations. A decrease of $34.304/MMBtu, 10%, compared to $343.714 /MMBtu. It is concluded that the Arab’s gas could fulfil gas requirements in Europe, and mutual benefit can be accomplished for both parties. European countries will benefit from acquiring new places with less distances and lower delivery costs, and Arab countries would have the chance to get new consumers and play a role in the market given their collective gas reserves and their advantageous strategic locations.

In the existing market, companies confront a fierce competition, so the need for new and efficient process for supply chain has become necessarily important. To this end, supply chain management among multi agent system is proposed for addressing the selection and evaluation process related to the inbound logistics. However, most of recent systems deal solely with the negotiation including the selection of one or multiple suppliers, without supporting the transportation provider selection simultaneously and consider it as decision criterion that affect the final choice of cooperative suppliers. As part of win-win negotiation, active supplier involvement can enhance efficiency and effectiveness of supply chain. Then again, transport cost constitutes the most important factor in the third of the total operational costs of a supply chain. To face this challenge, a new form of supplier selection including transportation provider selection is proposed. For this purpose, we present a multi-issue decision protocol based on ontology to support the negotiation between upstream nodes of supply chain in the proposed multi agent system. Furthermore, the automated multi-criteria analysis model based on combined analytical hierarchy process (AHP) and TOPSIS is judged helpful for decision-makers to make quick decision with less human interactions.

In an operating business amidst fierce competition, the operational process needs to be developed and improved in order to reduce logistics costs which are hidden costs in all business activities. This study aimed to investigate guidelines for reducing logistics costs in the industrial business sector, and to develop a structural equations model. It was conducted quantitatively and qualitatively.

To better meet the qualitative and quantitative requirements of customers or relevant sector managers, workshop environments are implementing increasingly complex task management systems. The job shop scheduling problem (JSSP) involves assigning each task to a single machine while scheduling many tasks on different machines. Finding the best scheduling for machines is one of the challenging optimizations of difficult non-deterministic polynomial (NP) time problems. The fundamental goal of optimization is to shorten the makespan (total execution time of all tasks). This paper is interested in the joint resolution of scheduling and transport problems and more particularly the Job-shop problem with Routing (JSSPR) as opposed to the Job-shop problem with Transport (JSSPT). These two problems are modeled in the form of a disjunctive graph. For the JSSPT, the solution to the transport problem is not linked to any quality of service (QoS) criterion and the solution is therefore often semi-active. The Job-shop with Routing explicitly considers transport operations and uses algorithms from the transport community to solve the transport problem. It is shown that the routing part of the JSSPR is a problem of the vehicle routing family and of the Pickup and Delivery Problem family. QoS in the JSSPR is defined by the duration of tours, the duration of transport of parts and the waiting time for them. A new evaluation function – named Time-Lag Insertion Heuristic (TLH) – is proposed to evaluate a disjunctive graph by simultaneously minimizing the makespan and maximizing the quality of service. Thus, the solution obtained is not semi-active, but a compromise between the different criteria. This evaluation function is included in a metaheuristic. Our numerical evaluations demonstrate that, on the one hand, the TLH evaluation can find almost optimal solutions regarding the QoS criterion; and on the other hand, the TLH evaluation is not very sensitive to the order of insertion of the maximum time-lags during the different minimization steps.

This study was designed to analyze the role of social media marketing in attracting investment capital from enterprises in the development of transport infrastructure in Vietnam. A survey of 378 Vietnamese companies operating in the sector of transport infrastructure investment was collected to compile these statistics. Based on the collected data, the factor analysis method and multivariate regression method are used to analyze the influence of factors on attracting development investment capital for transport infrastructure in Vietnam. The results of this study show that social media marketing had the greatest influence on firm satisfaction when investing in transport infrastructure; the Standardized Coefficient of the Social Media Marketing variable is 0.392. Based on that finding, some solutions to further enhance the value of social media marketing are recommended to increase the attraction of investment capital for the development of transport infrastructure in Vietnam.

The aim of the study was to examine the impact of logistics drivers on the operational performance of large manufacturing industries in Ethiopia. To this end, the researchers employed an explanatory research design with a mixed approach. To select the case industries the researchers used the census sampling technique and stratified sampling technique for respondents’ selection. Both primary and secondary data were accessed about the issue to analyze. After the data collection process, the study used a partial least square structural equation model (PLS-SEM) to find the relationships between the hypothesized constructs. In this study, inferential analysis was made with the support of smart PLS software. The result of the finding depicts that the product of R2 Value specifies that 69.1% of enhancement in an endogenous variable (i.e., Operational performance) is caused by the joint results from the exogenous variable (i.e. Transportation, Inventory, and facility Management). The finding also shows that there are raw materials and currency problems that made the industries produce below their capacity.

A multiproduct pipeline provides an economic way to transport large volumes of refined petroleum products over long distances. In such a pipeline, different products are pumped back−to−back without any separation device between them. The sequence and lengths of such pumping runs must be carefully selected in order to meet market demands while minimizing pipeline operational costs and satisfying several constraints. The production planning and scheduling of the products at the refinery must also be synchronized with the transportation in order to avoid the usage of the system at some peak−hour time intervals. In this paper, we propose a multi−period mixed integer nonlinear programming (MINLP) model for an optimal planning and scheduling of the production and transportation of multiple petroleum products from a refinery plant connected to several depots through a single pipeline system. The objective of this work is to generalize the mixed integer linear programming (MILP) formulation proposed by Cafaro and Cerdá (2004, Computers and Chemical Engineering) where only a single planning period was considered and the production planning and scheduling was not part of the decision process. Numerical examples show how the use of a single period model for a given time period may lead to infeasible solutions when it is used for the upcoming periods. These examples also show how integrating production planning with the transportation and the use of a multi−period model may result in a cost saving compared to using a single−period model for each period, independently.