Industry 4.0 will affect the complexity of supply chain networks. It will be necessary to
adapt more and more to the customer and respond within a time interval that is willing
to accept the product waiting. From these considerations, there is a need for a different way
of managing the supply chain. The traditional concept of supply chain as a linear system,
which allows optimizing individual subsystems, thus obtaining an optimized supply chain, is
not enough. The article deals with the issue of supply chain management reflecting demand
behaviour using the methodology Demand Driven MRP system. The aim of the publication
is to extend the knowledge base in the area of demand-driven supply logistics in the
The objectives of this research are to study the direct influence on the competitive advantage
and pattern development of variables affecting the competitive advantage of the Thai oil
palm industry. This research employs a quantitative research method. The population for
the study consists of 150 oil palm industrial operators in Thailand. Questionnaires are used
in the data collection and the data are analyzed by using SEM. The research results reveal
that the Knowledge Management Process and Supply Chain Integration positively influence
the competitive advantage in the quality, delivery, and cost. The competitive advantage
receives a positive direct impact from the Knowledge Management Process and Supply
Chain Integration. The variation of competitive advantage can be explained as 84%. The
obtained results can be used for developing the industry to create economic growth and
sustainable competitive advantage.
Performance measurement system in supply chain management (SCM) has been receiving increasing
attention by business organizations as a way to evaluate efficiency in supply chain
activities. Assessing the performance of supply chain uncovers the gap between planning
and actual performance as to trace the potential problems thus ascertain necessary areas
for improvement. This research aims to investigate the application of performance measurement
system in SCM as well as exploring its relationship with organization’s performance
among Malaysian manufacturing firms. By utilizing the questionnaire method, respondents
involved were requested to indicate the extent to which they use a number of 24 selected
performance measures that are related to SCM. The results show that the majority of the
observed manufacturing firms utilize specific performance measurement tools in evaluating
the supply chain performance. The current performance measurement techniques, the Balanced
Score Card is adopted by around a quarter of the total responding firms followed
by Supply Chain Operations References Model – SCOR, which attracts total users of only
a fifth of the total respondents. In particular, performance measures under customer service
category recorded the highest number of usage followed by cost-based performance measures
and operations management. The results of this investigation also unveil few major points
that are important to be highlighted. Firstly, the obtained outcomes of this study bring to
light the significant relationships between the utilization of supply chain performance measures
under customer service, operations management and organizational performance. In
addition, this study discovered a significant correlation between the size of the organization
and the extent of use of supply chain performance measures and how these two variables
positively correlated. Lastly, the findings also suggested that the performance measures for
SCM has been playing a crucial role in enhancing the performance of the organizations and
is increasingly operated as the firms grow in size. Based on the brief highlighted points listed
above, it is not an exaggeration to say that this research contributes new information to the
body of knowledge in performance measurement system in SCM and its associations with
organizational performance.
This paper addresses supply chain transparency improvement in a triadic manufacturersupplier-
supplier relationship. It investigates the problem of improving transparency using
a set of interviews; then, a detailed problematization and a simulation model is formulated
based on the results. The interview results show that there are two key issues to be considered:
information systems issues related directly to transparency and capability issues related
to utilizing transparency. The simulation results support developing capabilities by illustrating
the effects of different options for coordinating material flow. The results of the study
also indicate that while solutions to improve transparency can be relatively straightforward
to implement, developing the capability to benefit from it can be more challenging, even in
a well-established close partnership. In addition, suppliers may be hesitant to collaborate
without active manufacturer involvement.
The article presents a new optimization tool supporting supply chain management in the multi-criteria aspect. This tool was implemented in the EPLOS system (European Logistics Services Portal system). The EPLOS system is an integrated IT system supporting the process of creating a supply and distribution network in supply chains. This system consists of many modules e.g. optimization module which are responsible for data processing, generating results. The main objective of the research was to develop a system to determine the parameters of the supply chain, which affect its efficiency in the process of managing the goods flow between individual links in the chain. These parameters were taken into account in the mathematical model as decision variables in order to determine them in the optimization process. The assessment of supply chain management effectiveness was carried out on the basis of the global function of the criterion consisting of partial functions of the criteria described in the mathematical model. The starting point for the study was the assumption that the effectiveness of chain management is determined by two important decision-making problems that are important for managers in the supply chain management process, i.e. the problem of assigning vehicles to tasks and the problem of locating logistics facilities in the supply chain. In order to solve the problem, an innovative approach to the genetic algorithm was proposed, which was adapted to the developed mathematical model. The correctness of the genetic algorithm has been confirmed in the process of its verification.
The paper refers to planning deliveries of food products (especially those available in certain seasons) to the recipients: supermarket networks. The paper presents two approaches to solving problems of simultaneous selection of suppliers and transportation modes and construction of product flow schedules with these transportation modes. Linear mathematical models have been built for the presented solution approaches. The cost criterion has been taken into consideration in them. The following costs have been taken into account: purchase of products by individual recipients, transport services, storing of products supplied before the planned deadlines and penalties for delays in supply of products. Two solution approaches (used for transportation planning and selection of suppliers and selection of transportation modes) have been compared. The monolithic approach calls for simultaneous solutions for the problems of supplier selection and selection of transportation modes. In the alternative (hierarchical) solution approach, suppliers are selected first, and then transportation companies and their relevant transportation modes are selected. The results of computational experiments are used for comparison of the hierarchical and monolithic solution approaches.
In this article, we review the research state of the bullwhip effect in supply chains with
stochastic lead times. We analyze problems arising in a supply chain when lead times are
not deterministic. Using real data from a supply chain, we confirm that lead times are
stochastic and can be modeled by a sequence of independent identically distributed random
variables. This underlines the need to further study supply chains with stochastic lead times
and model the behavior of such chains.
The Bulletin of the Polish Academy of Sciences: Technical Sciences (Bull.Pol. Ac.: Tech.) is published bimonthly by the Division IV Engineering Sciences of the Polish Academy of Sciences, since the beginning of the existence of the PAS in 1952. The journal is peer‐reviewed and is published both in printed and electronic form. It is established for the publication of original high quality papers from multidisciplinary Engineering sciences with the following topics preferred: Artificial and Computational Intelligence, Biomedical Engineering and Biotechnology, Civil Engineering, Control, Informatics and Robotics, Electronics, Telecommunication and Optoelectronics, Mechanical and Aeronautical Engineering, Thermodynamics, Material Science and Nanotechnology, Power Systems and Power Electronics.
Journal Metrics: JCR Impact Factor 2018: 1.361, 5 Year Impact Factor: 1.323, SCImago Journal Rank (SJR) 2017: 0.319, Source Normalized Impact per Paper (SNIP) 2017: 1.005, CiteScore 2017: 1.27, The Polish Ministry of Science and Higher Education 2017: 25 points.
Abbreviations/Acronym: Journal citation: Bull. Pol. Ac.: Tech., ISO: Bull. Pol. Acad. Sci.-Tech. Sci., JCR Abbrev: B POL ACAD SCI-TECH Acronym in the Editorial System: BPASTS.