Jan Čapek, Miloslav Hub
The ubiquitous Internet connectivity has led to the introduction of an ever-increasing list of diverse online services ranging from financial transactions to online gaming and the other e-commerce purposes. For example, with cloud computing on the rise, geographically distant employees of organizations are able to access and share sensitive organizational resources online. The mentioned trend has increased the amount of user authentication processes. The aim of authentication is to decide whether a subject in question is in fact the subject that he claims to be. As an example can be mentioned traditional authentication, when end users authenticate themselves on computers by using the pair of username and password. In the past, many sophisticated authentication methods were developed. Generally, they can by divided to the three basic types of authentication depending on what kind of identification feature is used: authentication by knowledge, authentication by ownership of something, and authentication by biometrics. Each of these ways has its advantages and disadvantages.
Patricija Bajec, Monika Kontelj, Aleš Groznik
The objective of this study is to propose a trustworthy, valid and consistent methodological approach for measuring the efficiency of a logistics platform, where an entire country constitutes a logistic platform. Traditional Data Envelopment Analysis (DEA) is found to be an appropriate tool – if its weaknesses are eliminated. DEA results are highly influenced by the choice of appropriate inputs and outputs variables, but the method itself does not provide guidance for their identification. The authors therefore propose to integrate traditional DEA by combining the Delphi technique with the Analytical Hierarchy Process (AHP) method, which will assist in identifying proper, consistent input/output variables, evaluated by their relevance. The proposed framework allows the performance evaluation of the selected platform’s element or elements. It is thus a useful decision support tool for enterprises (private, public, both) that are managing logistics platforms and trying to improve their productivity in order to sustain or improve their position on the competitive market. This methodology allows comparative efficiency analyses to be estimated for similar countries. The presented methodology on one hand enables tailor-made solutions, but on the other hand is very general, and, with minor adjustments, can be applied by a variety of firms and industries. It can be applied in private sector firms in production and service industries, to analyse the relative performance of diverse logistics and non-logistics services, and in public profit or non-profit organisations.
Sarfaraz Hashemkhani Zolfani, Morteza Yazdani, Edmundas Kazimieras Zavadskas, Hamidreza Hasheminasab
“Multiple Attribute Decision Making (MADM)” is an expert based field which is working based on real data and experts’ opinions. So many studies have been doing based on MADM methods which they usually use qualitative data based on experts’ ideas. Decisions based on the experts’ opinion shall be carefully designed to cope the real problems uncertainty. This uncertainty will be even more intricate if combining the problem with the ambiguity of the future study. Prospective MADM is a future based type of MADM field which is concentrating on decision making and policy making about the future. Prospective MADM (PMADM) can have both explorative and descriptive paradigms in the studies but it will more useful to be applied for strategic planning. In this regard, experts’ role would be even more challenging because one/some possible future/futures will be partially designed based on their opinions. Future and prediction always complicates the decision environment, especially methodologies founded on experts’ judgement. Considering experts’ preferences, attitude, and background, they may be a major source of inaccurate results. Causal Layered Analysis (CLA) is well-known “Futures Studies” method which is qualitative and usually is supporting other methods such as “Backcasting” and “Scenario Planning”. CLA has a deep point of view to the subjects to support a future with all those changes which are necessary for the main goal/goals. In this study, this idea will be proposed that CLA can be added to PMADM outline to decrease the risk of unsuitable decisions for the future and for this aim a case study about energy and CO2 consumption in policy making level proposed and a hybrid MADM method based on BWM-CoCoSo applied in the PMADM outline for the procedure.
Pawel Tadeusz Kazibudzki, Jiří Křupka
Presumably complex systems can be better understood when they are broken down into their constituent elements and structured hierarchically. Then, judgments about these elements can be synthesized on the basis
of their relative importance at each level of the hierarchy into a set of overall priorities. By breaking down a reality into homogenous clusters and subdividing them into smaller ones, it is possible to integrate large amounts of information into the structure of a problém and form a more comprehensive picture of the whole system. There is a decision support methodology (DSM) which conforms to the above prescription. It is called the Analytic Hierarchy Process (AHP) and was devised at the Wharton School of Business by Thomas Saaty (1980). Its contemporary applications can be found, for example in Lidinska and Jablonsky (2018), Abdelmaguid and Elrashidy (2016), Kramulová and Jablonský (2016), and Ponis et al. (2015).
Globalization increases the complexity of supply chain and companies are faced with competitive pressure and environmental uncertainties as well as increasing customer demand (Thomas & Esper, 2010). To satisfy the fluctuating customer demand and to make various players in a supply chain align with customer requirement, collaboration between the players based on the timely communication is required. Moreover, sharing important
information such as customer demand and on-hand inventory level with other players is required to coordinate the players’ activities. With respect to the inventory management, various collaborative policies such as QR (Quick Response), ECR (Efficient Customer Response), VMI (Vendor Managed Inventory) and CPFR (Collaborative Planning, Forecasting and Replenishment) have been developed so as to overcome the limitation of standalone inventory management policies. These collaborative inventory management policies are based on the sharing of customer demand information between players in the supply chain.