This paper assesses the effectiveness in scheduling independent jobs with earliness/tardiness costs and variable setup times applying the Overall Equipment Effectiveness (OEE). The OEE is a common metric for measuring the manufacturing productivity. We defined a mixed-integer linear programming formulation of the parallel machine scheduling problem with four different objective functions in order to compare different scheduling configurations. Real data, from a plastic container manufacturing company located in the Basque Country (Spain), were used to validate this approach. A sensitivity analysis was performed with different production capacities and earliness/tardiness costs in order to evaluate the trade-offs between economic performance (i.e., costs) and the partial rates of OEE (i.e., quality, performance and availability). The objective of this study is to propose a guideline to help management make decisions regarding the measurement and improvement of scheduling effectiveness through contemplating earliness, tardiness and variable setup times.

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.

Digitalization is impacting almost every aspect of people’s life and is greatly affecting supply chain processes. At the same time, supply chains are becoming progressively more aware of their impacts on people, the planet and profits (triple bottom line perspective) and the concept of sustainable supply chain has received increasing attention among scholars and practitioners. In this context, this article aims to analyze scientific research on supply chain management in the field of sustainability and digitalization using a bibliometric approach. To this end, this article analyses 484 papers from Scopus database according to the following parameters: chronology, discipline, source, center, country and citations. The dataset consisted of articles from scientific journals published over the period 2002–2018. In addition, VOSviewer software is used to map the bibliographic material using the co-occurrence of keywords and most influential journals. The analysis reveals that: sustainability and digitalization are important emerging fields within supply chains that have increased significantly during the last ten years; the USA is the most influential country; and the topic is structured around 2 clusters (1) Supply chain management, concepts and practices and (2) energy related technologies. The results may facilitate the planning, designing, running and publishing of future research on this topic.