Strategic supplier selection under sustainability and risk criteria

Supplier selection is a multi-faceted strategic decision but there is no research that considers factors like sustainabilityand risk, simultaneously. Moreover, when selection criteria are subjective and require decision makers\u27judgment, and each candidate supplier dominates a separate selection criterion, the decision-makingprocess becomes more complex and traditional DEA models cannot differentiate between potential candidates.In this paper, we propose a multi-method approach based on quantitative empirical investigations, and analyticalmodeling. We utilize interval type-2 fuzzy sets to quantify decision makers\u27 inputs and propose an extendedsuper-efficiency DEA model, which includes both desirable and undesirable inputs and outputs to evaluatesuppliers. This approach simultaneously incorporates sustainability and suppliers\u27 risk factors into the supplierselection problem. The model is developed for both risk-neutral and risk-averse decision-makers. The efficiencyand applicability of the proposed framework is demonstrated through a real case. Results show that consideringsustainability criteria or risk factors separately results in inappropriate decisions

Why manufacturers adopt additive manufacturing technologies: The role of sustainability

Emerging manufacturing technologies can affect the performance of manufacturing systems considerably. Hence, a proportionate and purposive choice of such technologies would significantly impact the success of a firm. Additive Manufacturing, a leading and impactful technology, is being implemented in many industrial sectors and for a variety of reasons. It presents huge potential benefits in terms of sustainability perspectives. This paper aims to identify and prioritize the determinants of its adoption as well as to clarify the role of sustainability benefits in the decision to adopt. Then, the research seeks to distinguish the priorities of different application sectors through a multi-stage survey. The results show that environmental sustainability benefits are barely relevant to adoption decisions in practice and this is in contrast with the literature stating the huge sustainability benefits. Moreover, the results prove the pivotal role of economic motives in adoption decisions. The findings also indicate that the capability of additive manufacturing for producing almost any complex design is the key driver of its adoption in all sectors

New indices for assessing changes in seasons and in timing characteristics of air temperature

Abstract Previous studies examining climate change and changes in the timing of seasons have used a fixed temperature threshold for season onset. In this study, the timing of seasons was determined using non-fixed threshold methods. Twelve new timing indices were defined to account for shifts in seasons and season onset day, thermal centroid day, and length. The Mann-Kendall test, Theil-Sen’s slope estimator, sequential Mann-Kendall test, and least square linear regression were used to assess trends. The timing indices were examined using data from two meteorological stations in Iran with 50 years of records. Spatio-temporal variations in each index over 30 years (1987–2016) were then determined for Khuzestan province in southwestern Iran. Trend analysis for several indices indicated that the timing of seasons had probably changed in the south and west of the study area, while mountainous regions showed non-significant trends. Based on the hottest and coldest 90-day periods (summer and winter, respectively), during the three decades studied, spring lengthened by 5–10 days/decade in the plain region of Khuzestan province and autumn shortened by about 5–8 days/decade. The centroid of winter occurred earlier, by 2–5 days/decade, in the plains area, while the thermal centroid of summer did not change significantly. Overall, the difference between the thermal centroid of winter and summer (Cwin-sum) in the plains area significantly decreased, by 6–8 days/decade, in the 30-year period

Projection of future meteorological droughts in Lake Urmia Basin, Iran

Abstract Future changes (2015–2100) in precipitation and meteorological droughts in Lake Urmia Basin were investigated using an average mean ensemble of eight general circulation models (GCMs) with high-resolution datasets in socioeconomic pathway scenarios (SSPs) from the Coupled Model Intercomparison Project (CMIP6). In order to project the drought, the standardized precipitation index (SPI) was calculated. Overall, the results revealed that precipitation in Lake Urmia Basin will decrease by 3.21% and 7.18% in the SSP1-2.6 and SSP5-8.5 scenarios, respectively. The results based on 6-month-timescale SPI indices projected more “Extremely dry” events in SSP5-8.5 scenarios. The frequency of “Extremely dry” months in SSP5-8.5 compared to SSP1-2.6 is expected to increase by 14, 7, 14, 10, 5, 14, and 7 months for the Mahabad, Maragheh, Saqez, Sarab, Tabriz, Takab, and Urmia stations, respectively. In contrast, the frequency of “Extremely wet” months will decline for all stations in Lake Urmia Basin. The results of this study provide useful insight for considering drought prevention measures to be implemented in advance for Lake Urmia Basin, which is currently experiencing various environmental issues