SUSTAINABLE ENERGY MANAGEMENT STRATEGIES IN HOSPITALS: EXAMINATION AND ANALYSIS

Background: Sustainable development is often defined as the process of change by which the current needs of society are without hindering the capacity of future generations to meet their needs. Hospitals and medical centers are among the most vital organizations in any society and are among the largest consumers of water and energy and producers of waste. Objective: The purpose of this study was to identify and rank sustainable energy management strategies in Farabi Hospital. Method:  The present study is applied in terms of purpose and descriptive in terms of methodology. For collecting data, a researcher-made questionnaire based on multi-attribute decision-making methods used in this study (test and evaluation decision method, network analysis method, simple weight total, and Linmap) was used, which were completed by ten experts familiar with the topic of sustainable energy management with at least ten years of experience in Farabi Hospital in Bastak city in Hormozgan province. Result: The results of data analysis indicated that reduction of fossil energy consumption, waste recycling, and renewable energy are respectively the most significant criteria for sustainable energy management in hospitals       while employing equipment for reducing water consumption, installing automatic doors, and utilization of rainwater collection system are respectively the most important criteria for optimized, sustainable development Conclusion: According to the study results, the hospital managers are required to adopt combined solutions for energy management in the water and electricity sectors to focus on reducing energy waste and the use of new energy sources such as solar and rainwater. &nbsp

A novel decision model based on mixed chase and level strategy for aggregate production planning under uncertainty: case study in beverage industry

The present study proposes a novel decision model to aggregate production planning (APP) decision making problem based on mixed chase and level strategy under uncertainty where the market demand acts as the main source of uncertainty. By taking into account the novel features, the constructed model turns out to be stochastic, nonlinear, multi-stage and multi-objective. APP in practice entails multiple-objectivity. Therefore, the model involves multiple objectives such as total revenue, total production costs, total labour productivity costs, optimum utilisation of production resources and capacity and customer satisfaction, and is validated on the basis of real world data from beverage manufacturing industry. Applying the recourse approach in stochastic programming leads to empty feasible space, and therefore the wait and see approach is used instead. After solving the model using the real-world industrial data, sensitivity analysis and several forms of trade-off analysis are conducted by changing different parameters/coefficients of the constructed model, and by analysing the compromise between objectives respectively. Finally, possible future research directions, with regard to the limitations of current study, are discussed

Identifying and Prioritizing Arising Claim's Factors by the Combined Approach of DEMATEL and ANP Method (Case Study: Urban Development and Civil Organization of Shiraz Municipality Projects)

Claim management describes the process required to eliminate or prevent construction claims from arising and for the expedition handling of claims when they do occur. The present study aimed to identify the factors affecting the claimed design and their ranking. This research is applied and descriptive. The effective factors have been identified by reviewing the claims filed by the contractors of Shiraz Municipality during one year and have been classified according to their nature in the four main areas of the Claims (scope, time, quality and cost). To collect data, questionnaires based on the multi-adjective decision-making method used in this study were used, which were completed by experts of civil engineering projects in Shiraz Municipality. Data were analyzed using a combined approach of Decision-making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP). According to the results, 3 factors: Deviation from the project schedule plan, Changes in the technical specifications of and the resources of tasks and Not controlling the actual values on-site before execution with the initial estimate of the contract have the most effect and factors: Not to prepare a joint mapping with the presence of the consultant and the contractor at the beginning and Contractor financial loss due to bidding a lower price offer than the market have the least effect on claim. In general, factors related to time and quality areas have a greater effect on claim than factors related to scope and cost areas

Ranking of Shiraz Top Fitness Clubs Regarding Nutritional Knowledge, Attitude, and Performance of Sport Trainers Using Multi-Criteria Decision Making Approach

Background: It is important to know the physiological needs of athletes in relation to the type of sport, exercise, and the competition, about the amount of energy intake, macronutrients, micronutrients and fluids. Therefore, the purpose of this study was to assess the nutritional knowledge, attitude, and the performance of Shiraz top fitness clubs’ sport trainers and ranking the clubs in this regard. Methods: In this descriptive cross-sectional study, the General Nutrition Knowledge Questionnaire of Parmenter and Wardle were used to record nutritional information including nutritional knowledge, attitude, and the performance of the sport coaches of 26 top clubs in Shiraz, southern Iran. To determine the weight of questionnaire’s dimensions, the Shannon entropy method was used and the Topsis technique was used to rank the clubs. Results: The mean scores of the top fitness clubs’ coaches in Shiraz in different aspects of nutritional knowledge, attitude, and performance were 14.367, 9.17, and 3.381, respectively. The ranking of clubs showed that 73% and 27% of the top clubs in Shiraz, respectively, had a moderate and poor status in the knowledge, attitude and performance of the coaches, and none of the clubs been in a good condition. In addition, the highest scale in this ranking was related to nutritional knowledge of coaches. Conclusion: The top sport clubs’ coaches in Shiraz had a low level of nutritional knowledge, attitude and performance, and none of the clubs had a good score in this regard. Therefore, the need for interventional actions to promote these items seems necessary

A simulation testing and analysis of aggregate production planning strategies

In this study, a hybrid discrete event simulation (DES) and system dynamics (SD) methodology is applied to model and simulate aggregate production planning (APP) problem for the first time. DES is used to simulate operational-level and shop-floor activities incorporated into APP and estimate critical time-based control parameters used in SD model of APP and SD is used to simulate APP as a collection of aggregate-level strategic decisions. The main objective of this study is to determine and analyse the effectiveness of APP strategies regarding the Total Profit criterion by developing a hybrid DES–SD simulation model for APP in a real-world manufacturing company. The simulation results demonstrated that the priority of APP strategies with regards to Total Profit criterion is: (1) the pure chase strategy, (2) the modified chase strategy, (3) the pure level strategy, (4) the modified level strategy, (5) the mixed strategy and (6) the demand management strategy, respectively. The APP system is first simulated under mixed strategy (basic scenario) conditions to include all APP capacity and demand options in constructed SD simulation model to show a comprehensive view of APP components and their interdependent interactions. Then, the obtained results will be used as Total Profit measure to compare with system's performance under some experimental scenarios applying different APP strategies

Prioritizing factors affecting the hospital employees' productivity from the hospital managers' viewpoint using integrated decision-making trial and evaluation laboratory and analytic network process

Objectives: This study aimed to identify and prioritize factors affecting the hospital employees' productivity from the viewpoint of hospital managers working in the teaching hospitals affiliated to Iran, Shiraz University of Medical Sciences, in 2017. Materials and Methods: This was an applied, cross-sectional, and descriptive-analytical study conducted in 2017 in all teaching hospitals affiliated to Iran, Shiraz University of Medical Sciences. After identifying factors affecting hospital employees' productivity using the results of previous studies, all hospital managers (56 managers) were selected as the study population using census method to prioritize the factors. The decision-making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP) techniques were used for analyzing the collected data through Excel 2010 and Super Decision 2.8. Results: Fifteen factors affecting employees' productivity were determined using the results of previous studies which were classified into four clusters. The results of DEMATEL technique showed that “employees' attitude toward the organization” was the most affecting factor (r = 11.928) and also the most affected factor (c = 12.120), as well as the most important factor affecting the employees' productivity (r + c = 24.048). In addition, the results of ANP showed that the cluster of “leadership and management styles” (relative weight [RW] = 0.274) and its factors, especially “involving employees in the decision-making processes” (L1) (RW = 0.102) and “delegation of authority to the employees” (L2) (RW = 0.100) were the most important factors affecting the employees' productivity. Conclusion: According to the results, adopting an appropriate leadership style and providing participatory management, involving the employees in the hospital decision-making processes, etc., had significant effects on the increases in the employees' motivation and productivity

Aggregate production planning under uncertainty: a comprehensive literature survey and future research directions

This is the first literature survey of its kind on aggregate production planning (APP) under uncertainty. Different types of uncertainty, such as stochasticity, fuzziness and possibilistic forms, have been incorporated into many management science techniques to study APP decision problem under uncertainty. In current research, a wide range of the literature which employ management science methodologies to deal with APP in presence of uncertainty is surveyed by classifying them into five main categories: stochastic mathematical programming, fuzzy mathematical programming, simulation, metaheuristics and evidential reasoning. First, the preliminary analysis of the literature is presented by classifying the literature according to the abovementioned methodologies, discussing about advantages and disadvantages of these methodologies when applied to APP under uncertainty and concisely reviewing the more recent literature. Then, APP literature under uncertainty is analysed from management science and operations management perspectives. Possible future research paths are also discussed on the basis of identified research trends and research gaps

Evaluating the performance of aggregate production planning strategies under uncertainty in soft drink industry

The present study is to evaluate the performance of different aggregate production planning (APP) strategies in presence of uncertainty. Therefore, the relevant models for APP strategies including the pure chase, the pure level, the modified chase, the modified level and the mixed chase and level strategies are constructed by using both multi-objective programming and simulation methods.The models constructed for these strategies are run with respect to the corresponding objectives/criteria in order to provide business insights to operations managers about the effectiveness and practicality of various APP strategies in presence of uncertainty. The real world operational data are collected from soft drink industry to validate and implement the models.In addition, multiple criteria decision making (MCDM) methods are used besides multi-objective optimisation to assess the overall performance of each APP strategy. A detailed sensitivity analysis is also conducted by changing the criteria weights in MCDM methods to evaluate the impacts that these weight changes can have on the final rank of each APP strategy.The results of the simulation models are compared to those of multi-objective optimisation models. In general, in both mathematical programming and simulation models, the pure chase and the modified chase strategies presented the best performance, followed by the pure level strategy

An integrated fuzzy QFD and fuzzy goal programming approach for global facility location-allocation problem

Companies pursuing extension of their activities and new companies in establishment phase are using various concepts and techniques to consider location decision, because location greatly affects both fixed and variable costs and on the overall profit of the company. This paper suggests a new use of quality function deployment (QFD) for facility location selection problem instead of applying it to traditional product quality promotion. Fuzzy sets concept is also incorporated to deal with imprecise nature of the linguistic judgments of decision makers. First, fuzzy QFD as a stand-alone approach is presented to address international facility location selection decision. To consider resource limitations and operational constraints, fuzzy goal programming is combined with fuzzy quality function deployment to present a developed approach to deal with global facility location-allocation decision. A demonstration of the applicability of proposed methodologies in a real-world problem is presented