Water Resources Allocation Using Solution Concepts of Fuzzy Cooperative Games: Fuzzy Least Core and Fuzzy Weak Least Core

In this paper, two new solution concepts for fuzzy cooperative games, namely Fuzzy Least Core and Fuzzy Weak Least Core are developed. They aim for optimal allocation of available water resources and associated benefits to water users in a river basin. The results of these solution concepts are compared with the results of some traditional fuzzy and crisp games, namely Fuzzy Shapley Value, Crisp Shapley Value, Least Core, Weak Least Core and Normalized Nucleolus. It is shown that the proposed solution concepts are more efficient than the crisp games. Moreover, they do not have the limitation of Fuzzy Shapley Value in satisfying the group rationality criterion. This paper consists of two steps. In the first step, an optimization model is used for initial water allocation to stakeholders. In the second step, fuzzy coalitions are defined and participation rates of water users (players) in the fuzzy coalitions are optimized in order to reach a maximum net benefit. Then, the total net benefit is allocated to the players in a rational and equitable way using Fuzzy Least Core, Fuzzy Weak Least Core and some traditional fuzzy and crisp games. The effectiveness and applicability of the proposed methodology is examined using a numerical example and also applying it to the Karoon river basin in southern Iran.     

The impact of a STEM-based entrepreneurship program on the entrepreneurial intention of secondary school female students

Despite dedicated effort and research in the last two decades, the entrepreneurship field is still limited by little evidence-based knowledge of the impacts of entrepreneurship programs on the entrepreneurial intention of students in pre-university levels of study. Further, gender equity continues to be an issue in the entrepreneurial sector, particularly in STEM-focused entrepreneurship. In this context, this study was designed to explore the effects of a one-day female-focused STEM-based entrepreneurship program (for brevity, we call it the OzGirlsEntrepreneurship program) on the entrepreneurial intention of secondary school female students. The study collected data from two surveys completed by 193 secondary school female students, aged 14–16 years, who participated in the OzGirlsEntrepreneurship program. This program encouraged girls to develop and implement creative computational solutions to socially relevant problems, with an Internet of Things (IoT) component using the micro:bit device. The findings reveal that a key factor in the development of entrepreneurial attitudes in young female students is associated with soft-skills development, particularly in the areas of creative thinking, risk-taking, problem-solving, and leadership development. The importance of meaningful human connections, including positive role modelling and peer to peer learning were also important factors in fostering entrepreneurial intent. With these factors in mind, our findings highlight that the OzGirlsEntrepreneurship program substantially increased the entrepreneurial intention of secondary school female students. In addition, this study offers actionable implications and recommendations to develop and deliver entrepreneurship education programs for secondary school level students.

     

A Demand Management Based Crop and Irrigation Planning Using the Simulation-Optimization Approach

Coupled simulation-optimization models are useful tools for solving optimum water allocation and crop planning problems. In this study, the optimum crops pattern in the Arayez plain in the Karkheh river basin in Iran is determined by integration of a network flow programming (NFP) based simulation model and the shuffle frog leaping optimization algorithm (SFLA) in the form of a simulation-optimization approach. MODSIM applies NFP for finding water allocations which by use of its customization ability, the benefit of water supply for the agricultural crops is calculated based on the agronomic equations. The objective function is to maximize the total net benefit gained from crops production where the decision variables which are the irrigation depths and the cultivation areas are optimized by SFLA. Results show that by use of the coupled SFLA-NFP model, the net benefit increases 12% comparing the present situation in the plain. Also, the sensitivity analyses on effective parameters indicate that the potential maximum yield and the net price of the crops yield in the market have a direct impact on the crops optimum cultivation area.     

An Ultimatum Game Theory Based Approach for Basin Scale Water Allocation Conflict Resolution

Increasing water consumption via competitive demands has resulted in serious water conflicts and the subsequent environmental crisis in the Gavkhouni Watershed with the Gavkhouni swamp in the most downstream located in the central part of Iran. In this research, a two-player ultimatum game theory approach is adopted to not only address the water conflicts with the purpose of environmental reclamation of the drying swamp, but also to ensure economic satisfaction for the upstream landowners and farmers. The Ministry of Energy (MoE) and its subsidiary regional water authority represent the responsible organizations for providing water while the Ministry of Agriculture (MoA) is the primary body in charge of water consumption in the watershed. MoE and MoA are considered as two players in the game, whereas MoE has more power than MoA in terms of allocating water. Five strategies are studied namely: 1 and 2) decreasing water allocation to irrigated agriculture as much as the annual shortage of the Gavkhouni swamp with and without compensation to MoA (D-L), 3 and 4) decreasing water allocation to irrigated agriculture twice as much the annual shortage of the swamp with and without compensation for MoA (D-2 L) and 5) giving up Gavkhouni swamp’s reclamation plan (D). Moreover, three scenarios regarding the relations between environmental and agricultural utilities are designated. According to the results, D-2 L with paying compensation to MoA is chosen as the best alternative in scenario 1 when the environmental utility was assumed to be greater than the agricultural utility. Ultimatum Game Theory has no final solution for scenarios 2 and 3 where the environmental utility is considered to be equal and smaller than agricultural utility. The swamp’s annual environmental water shortage as 324 million cubic meters is supplied by application of both strategies D-L and D-2 L. Ultimatum Games are efficient in assessment of water conflicts to resolve them through careful and planned negotiations.     

Optimal Design and Operation of a Hydropower Reservoir Plant Using a WEAP-Based Simulation–Optimization Approach

Water Resources Management - Optimal design and operation of a hydropower reservoir is a complex optimization problem in terms of formulation and solution. In this study, a...     

A Comparative Study of Artificial Intelligence Models and A Statistical Method for Groundwater Level Prediction

Today, various methods have been developed to extract drinking water resources, which scientists use to simulate the quantitative and qualitative water resources parameters. Due to Iran's geographical and climatic characteristics, this region is located on the drought belt in Asia. In this research, some Artificial Intelligence (AI) and mathematical models have been used for groundwater level prediction. The AI models used for this research are Extreme Learning Machine (ELM), Least Square Support Vector Machine (LSSVM), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Multiple Linear Regression (MLR) model. In this study, simultaneously, these models were used to simulate and estimate groundwater level (GWL). The database used in the simulation is the data related to the Total Dissolved Solids (TDS), Electrical Conductivity (EC), Salinity (S), and Time (t) parameters. The results showed that ELM was more accurate than other methods. In Uncertainty Wilson Score Method (UWSM) analysis, ELM had an Underestimation performance and was determined as the more precise model.

     

The customer experience ecosystem in two cultural contexts

This study focuses on the development of a customer experience ecosystem during a journey which is embedded in meso- and macro-layers. Using the critical incident technique, the author collected in-depth interview data from bank customers in Switzerland and Iran to empirically study this ecosystem, including customer–company interaction in the micro-layer and social context of the meso-layer. Moreover, in a macro-layer analysis, the Hofstede cultural dimension was employed to show the role of cultural context in this ecosystem. The findings indicate that customer experience in the pre-encounter stage is mostly shaped by customer past experience and social context rather than company touchpoint. The importance of these factors is different in the two cultural contexts. Although customer experience in the encounter stage is mainly the result of customer and company interactions, other people have a role in this stage and cultural differences between the two countries largely explain these differences. Moreover, in the post-encounter stage, customers in different cultural contexts use various factors to evaluate their experiences and the effects on their emotional and behavioral responses. The findings provide key managerial implications for national and international companies with respect to the role of multiple layers in customer experience management.     

A Multi-Objective Risk-Based Game Theoretic Approach to Reservoir Operation Policy in Potential Future Drought Condition

In this paper, by using the concept of Conditional Value at Risk (CVaR), a Leader-Follower game (LFG) based multi-objective optimization model is developed to determine the optimum 12-month operation policy of a reservoir in potential future dry periods. The minimization of CVaRs of storage loss and agricultural and environmental deficits along with maximization of planned allocation to agricultural sector are considered as leader’s objectives, while the followers try to maximize their share of water rights using Nash bargaining (NB) method. This framework is then used to model the operation policy of Dorudzan basin in Fars province, southwestern Iran. Water demand and daily climate data in the period of 2003 to 2015 for this basin, as well as future projections from fifteen IPCC-AR4 global circulation models (GCMs) for 2018–2030 under A2, B1 and A1B emission scenarios are considered to evaluate future dam operation policies. Future projections are downscaled using the LARS-WG model, which then feeds the HMETS watershed model to simulate the corresponding reservoir inflow time-series. Thereafter, three-hundred 12-month rainfall, evaporation and inflow time series with least inflow volume are used as input for the optimization model, which is solved using NSGA-II and GA algorithms. The results show while the model can determine the operation policy that keeps the associated risks in the acceptable range, it can satisfy the followers demands with respect to the available resources. The results also show that the agricultural sector of the study area can be hugely affected by potential future droughts.