No abstract

Purpose -Green supply chain management (GSCM) has become an important issue with increasing awareness of environmental protection. A firm's environmental approach is not only relevant to its inner efforts, but its suppliers' environmental performance is also important. The aim of this study is to propose an integrated multi-criteria decision-making (MCDM) approach based on intuitionistic fuzzy set (IFS) and grey relational analysis (GRA) for green supplier selection. Design/methodology/approach -Green supplier selection is a MCDM process that contains different kinds of uncertainties. Because of the vagueness and imprecision of decision makers' evaluations and subjectivity of the criteria, IFS and GRA are exploited to handle these uncertainties. Findings -A numerical example is presented for the proposed approach. The analyses of the results show that fuzzy set theory and grey theory can be used jointly for green supplier selection problems in uncertain environments. Originality/value -There are different kinds of uncertainties in the supplier selection process. The novelty of this study is to use proper uncertainty methods in different steps instead of denoting the whole selection process by the same uncertainty theory. Supplier selection problems occupy wide space in operations research literature. Different criteria are used in different papers. In this study, detailed literature review has been carried out and some criteria among frequently confronted ones proposed for green supplier selection.

PurposePersonnel selection is an important process in management due to the high cost of unfavorable employee procurement. The multi criteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. The purpose of this paper is to propose a grey theory‐based hybrid approach to solve personnel selection problems in uncertain environments.Design/methodology/approachThe work procedure is as follows: first, grey analytic network process (GANP) is applied to calculate selection criteria weights and then candidates are ranked by using grey possibility degrees. Finally, an example of a selection problem of sniper for a military unit was used to illustrate the proposed approach.FindingsThe analyses of the results show that grey theory‐based methods have enormous chance of success for personnel selection problems in uncertain situations.Originality/valueAlthough there are some applications for personnel selection problems that used grey system theory in the literature, the combination of GANP and grey possibility degrees is used for personnel selection problem in this study.

Purpose -The relationship between energy consumption (EC) and economic growth is a well-known and more studied subject in literature. In this study, Turkey's EC and gross domestic product (GDP) relation is analyzed. The aim of this study is to find out the relative importance of energy components on GDP for Turkey. Hence, the authors can make some strategic implications up to the importance of energy components on GDP. Design/methodology/approach -In this study, two methods are used to find out the importance of energy types on economic growth for Turkey. First, grey relational analysis (GRA) is used to determine the most influential energy types on GDP. Then regression analysis is used to compare outcomes which are yielded by GRA. Findings -The analyses of the results show that the most important energy sources are oil and renewables for Turkey. Both energy sources have equal importance with economic growth. However, it is implied that this balance should be destabilized for the sake of renewable production and usage to have less carbon footprint. Originality/value -There are many econometric models used for defining EC and economic growth causality. But the authors could not come across any study which investigates relationship between economic growth and EC by GRA. The method that is newly used for this subject and applying analysis for a developing country is the importance of this study.

Purpose The purpose of this paper is to present a mixed integer programming model for simple assembly line balancing problems (SALBP) with Type 1 when the annual demand and task durations are uncertain and encoded with grey numbers. Design/methodology/approach Grey theory and grey numbers are used for illustrating the uncertainty of parameters in an SALBP, where the objective is to minimize the total number of workstations. The paper proposes a 0-1 mathematical model for SALBP of Type 1 with grey demand and grey task durations. Findings The uncertainty of the demand and task durations are encoded with grey numbers and a well-known 0-1 mathematical model for SALBP of Type 1 is modified to find the minimum number of workstations in order to meet both the lower and upper bounds of the uncertain demand. The results obtained from the proposed mathematical model show a task-workstation assignment that does not distribute precedence relations among tasks and workstations and the sum of task durations in each single workstation is less than or equal to the grey cycle time. Originality/value The grey theory and grey numbers have not been previously used to identify uncertainties in assembly line balancing problems. Therefore, this study provides an important contribution to the literature.