Nowadays, using Blockchain Technology (BCT) is growing faster in each country. It is essential to apply BCT in Supply Chain Network Design (SCND) and is considered by the designer and manager of SC. This research indicates Viable Supply Chain Network Design (VSCND) by applying BCT. A new form of two-stage robust optimization is suggested. Facility locations and activation BCT for VSCND is the first stage of decisions; finally, we determine flow transshipment between components in the next stage. The GAMS-CPLEX is used for solving the model. The results show that running BCT will decrease 0.99% in costs. There is an economic justification for using BCT when demand is high. A fix-and-optimize and Lagrange relaxation (LR) generate lower and upper bound to estimate large scale in minimum time. The gap between the main model and fix-and-optimize is better than the LR algorithm. Finally, this research suggests equipping VSCND by BCT that becomes more resilient against demand fluctuation, sustainable, and agile.

No abstract

The successful deployment of the solar water heater (SWH) in the residential sector relies on the household’s bounded rational decision-makers to accept this system. The decision is shaped by a wide spectrum of predictors that form heterogeneous behaviour. Over the past years, research has employed a wide range of these predictors to understand their role in the decision and predict the behaviour and diffusion rate of SWHs. This review primarily identifies economic and technical predictors of 100 quantitative and qualitative studies on the residential SWH adoption decision. For the identified predictors, their characteristics and popularity are explored in a structured and coherent framework. The review further investigates the correlation between the identified predictors and the adoption decision from 97 of the 100 initially reviewed studies. The outcome of the research revealed 123 (56 economic and 67 technical) predictors that were classified into seven categories. ‘Financial incentives’ and ‘perceived attitude towards government policies’ are among the most popular economic predictors, whereas ‘house type’ and ‘knowledge of SWH’ were the most frequent technical factors in the research. Analysing the correlation between 99 predictors and the decision also unfolded that certain attitudinal attributes have a stronger influence on the residential SWH take-up than some common factors (e.g., electricity cost, technical variables).

No abstract

No abstract

No abstract

No abstract