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PurposeThe purpose of this paper is to systematically investigate the patient flow and waiting time problems in hospital emergency departments (EDs) from an integrated voice of customer (VOC) and voice of process (VOP) perspective and to propose a new lean framework for ED process.Design/methodology/approachA survey was conducted to better understand patients' perceptions of ED services, lean tools such as process mapping and A3 problem-solving sheets were used to identify hidden process wastes and root-cause analysis was performed to determine the reasons of long waiting time in ED.FindingsThe results indicate that long waiting times in ED are major concerns for patients and affect the quality of ED services. It was revealed that limited bed capacity, unavailability of necessary staff, layout of ED, lack of understanding among patients about the nature of emergency services are main causes of delay. Addressing these issues using lean tools, integrated with the VOC and VOP perspectives can lead to improved patient flow, higher patient satisfaction and improvement in ED capacity. A future value stream map is proposed to streamline the ED activities and minimize waiting times.Research limitations/implicationsThe research involves a relatively small sample from a single case study. The proposed approach will enable the ED administrators to avoid the ED overcrowding and streamline the entire ED process.Originality/valueThis research identified ED quality issues from the integration of VOC and VOP perspective and suggested appropriate lean tools to overcome these problems. This process improvement approach will enable the ED administrators to improve productivity and performance of hospitals.

In order to evaluate and monitor the impacts of improvement initiatives in terms of the overall leanness level, it is important to identify right performance metrics to measure the current and desi...

Efficient and uninterrupted energy supply plays a crucial role in the quality of modern daily life, while it is obvious that the efficiency and performance of energy supply companies has a significant impact on energy supply itself and on determining and finetuning the future roadmap of the sector. In this study, the performance and efficiency of energy supply companies with respect to productivity is investigated with reference to a case study of an electricity distribution company in Turkey. The factors affecting the company’s performance and their corresponding weight have been determined and obtained using the analytical hierarchy process (AHP) and the Fuzzy AHP methods, two well-known multi-criteria decision-making methods, which are widely used in the literature. The results help demonstrate that the criteria obtained to evaluate the company’s energy supply performance play a crucial role in developing strategies, policies and action plans to achieve continuous improvement and consistent development.

Innovation-based economic growth is considered to be a vital strategic aim for all economies, but environmentally friendly concepts and sustainable development (SD) must also be considered. The literature on the Global Innovation Index (GII) shows various investigations relevant to innovation, yet the lack of comprehensive consideration within the GII of environmental concerns represents a critical challenge. This paper aims to provide a holistic-perspective evaluation model for the top 15 manufacturing countries worldwide in order to resolve this. The efficiency-based Global Green Manufacturing Innovation Index (GGMII) was developed by formulating an input-oriented data envelopment analysis model. Criteria such as the value added to the gross domestic product (GDP), corresponding CO2 emissions, and unemployment rates were examined in order to represent the economic, environmental, and social dimensions of SD, respectively. Other scientific and technological dimensions were also considered. The data corresponding to all ten of the criteria were collected from World Bank Open Data. The results show a mismatch between the original GII and the proposed GGMII for the top eight manufacturing countries (the United States, the United Kingdom, Germany, Korea, France, China, Japan, and Canada), while the remaining countries (Italy, Spain, Russia, India, Mexico, Brazil, and Indonesia) occupied the same rank in both indices, but showed a sizable diminution in their original GII scores. The proposed GGMII might be utilized as a benchmarking instrument for all countries worldwide in the future.

Fairness is a key issue that requires the attention of human resource management practitioners. Having a robust methodical procedure for identifying the value of job positions in an enterprise is essential. Consequently, there is a need for a job evaluation system that ensures fair compensation for each position. A poorly defined job evaluation system creates the dilemma of mismatches between employees and their competencies for their responsibilities and, accordingly, their wages. This results in employee dissatisfaction, which ultimately exacerbates attrition, which is costly because of the loss of talented employees. This paper proposes a VIKOR algorithm as an innovative approach to job evaluations. Engineering-related positions in an international aviation company were analyzed to illustrate the appropriateness of the proposed approach for managing the job evaluation dilemma. The results indicate that 29 job grades would be appropriate for this firm. In addition, the proposed algorithm was found to be superior to other multiple-criteria decision-making techniques at managing the job evaluation dilemma.

Air quality monitoring and assessment are essential issues for sustainable environmental protection. The monitoring process is composed of data collection, evaluation, and decision-making. Several important pollutants, such as SO2, CO, PM10, O3, NOx, H2S, location, and many others, have important effects on air quality. Air quality should be recorded and measured based on the total effect of pollutants that are collectively prescribed by a numerical value. In Canada, the Air Quality Health Index (AQHI) is used which is one numerical value based on the total effect of some concentrations. Therefore, evolution is required to consider the complex, ill-defined air pollutants, hence several naive and noble approaches are used to study AQHI. In this study, three approaches such as hybrid data-driven ANN, nonlinear autoregressive with external (exogenous) input (NARX) with a neural network, and adaptive neuro-fuzzy inference (ANFIS) approaches are used for estimating the air quality in an urban area (Jeddah city—industrial zone) for public health concerns. Over three years, 1771 data were collected for pollutants from 1 June 2016 until 30 September 2019. In this study, the Levenberg-Marquardt (LM) approach was employed as an optimization method for ANNs to solve the nonlinear least-squares problems. The NARX employed has a two-layer feed-forward ANN. On the other hand, the back-propagation multi-layer perceptron (BPMLP) algorithm was used with the steepest descent approach to reduce the root mean square error (RMSE). The RMSEs were 4.42, 0.0578, and 5.64 for ANN, NARX, and ANFIS, respectively. Essentially, all RMSEs are very small. The outcomes of approaches were evaluated by fuzzy quality charts and compared statistically with the US-EPA air quality standards. Due to the effectiveness and robustness of artificial intelligent techniques, the public’s early warning will be possible for avoiding the harmful effects of pollution inside the urban areas, which may reduce respiratory and cardiovascular mortalities. Consequently, the stability of air quality models was correlated with the absolute air quality index. The findings showed notable performance of NARX with a neural network, ANN, and ANFIS-based AQHI model for high dimensional data assessment.

Energy consumption constantly increases day-by-day, which enforces suppliers and consumers in to plan the needs for the short and long terms. This obliges studying to device useful and accurate ways to predict the need for use in corresponding periods of the time. One of these fields of study is the efficient and uninterrupted energy supply over distribution infrastructures. It is obvious that the efficiency and performance of energy supply companies plays an important role in energy supply itself and has a critical value in determining and finetuning the future roadmap of the sector. In this study, the performance and efficiency of energy supply companies with respect to productivity is investigated over a case study of an electricity distribution company in Turkey. The factors affecting the company’s performance and their corresponding weights have been determined and elicited using analytical hierarchy process (AHP) and the Fuzzy AHP methods, as two well-known multi-criteria decision-making methods. The AHP method differs from other methods in that it can evaluate qualitative and quantitative expressions together, calculate the consistency rate, and show the hierarchical structure between sub-criteria and alternatives depending on the criteria. In addition, it is a decision-making method that is widely used in the literature. The Fuzzy AHP method, on the other hand, reflects the evaluations of people better than the classical AHP method and provides convenience during the evaluation. The results help demonstrate that the criteria elicited to evaluate the company’s energy supply performance plan a crucial role in developing strategies, policies and action plans to achieve continuous improvement and consistent development.

Green entrepreneurship is a novel sustainability term. A strategy has recently been put forward to make a business greener by minimizing the harmful impact on the environment and committing to sustainability while maintaining financial imperishability. However, some barriers prevent its implementation to its full potential. This study aims at investigating such barriers following the interpretive structural modeling (ISM) approach for analyzing relationships among them and for their prioritization, for the effective construction of green entrepreneurship. The study revealed that collaboration among stakeholders of business activities is vital to green entrepreneurship. Results also show that R&amp, D and technology are foundational to overcoming other barriers, such as the costs associated with green initiatives, lack of knowledge and subjective awareness in the market, shortage of investors and involvement of private sectors, government regulations, cultural differences, dominating industries, lack of incentive and support mechanism, and bureaucracy. Subsequently, the results indicated that overcoming these barriers will enable us to change the short-term mindset of investors towards green entrepreneurship. Implications of this study include using the revealed set of barriers and their modeled relationships for policymaking as well as the development of better targeted and more effective strategies to overcome these barriers, enabling its implementation to its full potential.

The global international trend for energy policies is leading toward placing major efforts in utilizing alternative sources of energy. Collectively, the G20 economies account for around 85% of the gross world product (GWP), 80% of the world trade, and two-thirds of the world population. Without doubt, G20’s future energy policies will formulate the economy of the future all around the word. In this paper, The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as a tool to rank the G20 countries is employed with respect to the electricity produced from various energy sources. This study provides a clearer insight on what direction to consider in formulating a future energy policy. Generally, it can be concluded that the energy policies of the G20 countries have a great potential for improvement toward a more efficient, contingent, and balanced sustainable economic growth improvement when placing the German energy policy as a benchmark.

Saudi Arabia is the world’s top oil exporter and producer. Saudi Arabia is the largest oil-consuming nation in the Middle East. Gasoline and diesel fuel in the Kingdom cost about 16 cents and 6 cen...

The Kingdom of Saudi Arabia has rich geothermal energy resources. In Saudi Arabia, the studies on geothermal resources exploration were started in 1980. Saudi Arabia is among the most geothermally ...

Renewable energy is a promising alternative solution for the energy requirements because it is clean and environmentally safe. Projections are important tools for long-term planning and policy settings. According to estimates, by 2040 approximately half of the global energy supply would be from renewable sources. Biomass can be converted into electric power through several methods. Heat is used to thermochemically convert biomass into a fuel oil which is then burned like petroleum to generate electricity. Biomass can also be burned directly to produce steam for electricity production or manufacturing processes. One alternative for producing electricity from biomass in a gas turbine is direct combustion of biomass as a primary energy source. Biomass is burned directly to produce steam, the steam turns a turbine which derives a generator thus electricity is generated.

In the current paper we quantified and evaluated the energy saving potential in air conditioners and chiller systems. We also showed how to reduce the cost of air conditioners and chiller systems in existing facilities on the basis of payback periods. Among the measures investigated were: 1) installing higher efficiency air conditioners, 2) installing higher efficiency chillers, 3) duty cycling air conditioning units, and 4) utilizing existing economizers on air conditioning units. For each method, examples were provided from Arizona, USA. In these examples, the amount of saved energy, the financial evaluation of this energy, and the investment cost and pay back periods were calculated.

In this review, strategies for crude oil desulfurization are evaluated by reviewing desulfurization literature. The most important characteristics of crude oil that affect the market price are its sulfur content and gravity. Low sulfur content of crude oil is particularly preferred. Petroleum includes crude oil, natural gas, and heavy oil. Petroleum refineries convert crude oils and other input streams into dozens of refined (co)products. Two properties are especially useful for quickly classifying and comparing crude oils: API gravity (a measure of density) and sulfur content. Sulfur is naturally present as an impurity in fossil fuels. The removal of organosulfur compounds from crude oil is an important aspect of all countries to reduce air pollution. The sulfur compounds from gasoline are generally removed by treatment with an alkaline solution sodium plumbite. At large scales, the most economical technology for converting hydrogen sulfide into sulfur is the Claus process. This well-established process ...

The purpose of this paper is to provide a practical approach for prioritizing the most practiced Critical Success Factors (CSFs) for six sigma implementation. The most commonly accepted CSFs for six sigma were identified from the literature. Then, the interactions among twelve CSFs have been studied using one of the mathematical/soft-operational research tools, that is, the Interpretative Structural Modeling (ISM). The developed model was illustrated using a case study selected from an automotive service industry. The findings implied that almost all of the CSFs are classified as linkage variables. The developed model provides a road map that assists practitioners to understand the process through which six sigma is practiced in a certain enterprise. Although the studied case was selected from the automotive service industry, the outcome of the proposed ISM model supported the results of the previous empirical studies in a sense that all factors for six sigma implementation were in fact critical (i.e. none of them was located within the autonomous category).

PurposeThe purpose of this paper is to assist organizations in understanding the nature of quality management from a resource‐based perspective by investigating the relationship between strategies needed to drive quality enhancement, and resources being allocated to support effective strategy implementation. The resource‐based view of TQM elements led this case study research to deal with quality management from a strategic viewpoint, or what is known as Strategic Quality Management (SQM).Design/methodology/approachThe paper employs the analytic network process (ANP) to model the interactions between eight SQM strategies and the three types of resources (human, organisational and technological) needed for effective strategy implementation. The paper then formulates a goal programming (GP) model in order to identify the extent to which each single strategy is inhibited by a lack of (or overloaded by) resources. Using a case study approach, the hybrid ANP‐GP methodology is employed to illustrate the application in the context of enhancing quality in the food‐processing industry.FindingsThe ANP analysis quantitatively differentiates between the amount of resource support each strategy receives and the support it needs. The GP model offers insight on how to re‐allocate resources to minimize identified discrepancies related to how the company utilizes their resources.Originality/valueThis paper argued that practicing QM with the consideration of the firm's strategic need for resources provides better understanding of why quality gurus still disagree on whether soft or hard TQM is more connected to organizational performance. Therefore, rather than focusing on “generalizing” the TQM model, as has traditionally been done in previous attempts, the main contribution of this paper is to propose a methodology that assesses a firm's utilization of resources considering its strategic need for these resources.

Employee selection is a multi-criteria decision-making (MCDM) problem for selecting suitable applicants from a ready pool. The selection aims to make use of their knowledge, relevant skills, and other characteristics to perform a specific job. The aim of this study is to develop a systematic approach for selecting the best candidates among the air traffic controllers (ATCs) for aviation in Saudi Arabia. Three integrated methods were employed for decision-making in this study. First, a fuzzy decision tree was applied to determine the criteria weights, then the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was employed to rank the attributes. In the last step, the Data Envelopment Analysis (DEA) was used to transform the qualitative variables into quantitative equivalences. A survey was conducted by national and international decision-makers to elicit the necessary information on the criteria and sub-criteria of the air traffic control system. The decision problem was formulated by employing five criteria and ten applicants. The relationship between the fuzzy TOPSIS and fuzzy-weighted average was very positive for decision-making. The outcomes of the fuzzy TOPSIS and DEA encouraged the development of a decision support system for the selection of ATCs. Die kies van werknemers vanuit 'n lys van gepaste aansoeke is 'n multi-kriteria besluitnemingsprobleem. Die seleksie se doel is om gebruik te maak van die potensiële werknemers se relevante vaardighede en ander eienskappe om 'n spesifieke taak te verrig. Die doel van hierdie navorsing is om 'n sistematiese benadering, om die beste kandidate vir lugruimbeheerderposisies in Saoedi Arabië te identifiseer, te ontwikkel. Drie geïntegreerde metodes is ingespan vir die besluitneming in hierdie studie. Eerstens is 'n wasige besluitnemingsboom toegepas om die kriteria gewigte te bepaal. Daarna is die wasige tegniek van Orde Voorkeur deur Ooreenkoms tot die Ideale Oplossing toegepas om die kenmerke te rangskik. Laastens is die Data Omvangs Analise gebruik om die kwalitatiewe veranderlikes tot kwantitatiewe gelykhede om te skakel. 'n Peiling is onder nasionale en internasionale besluitnemers geneem om die noodsaaklike inligting rakende die kriteria en sub-kriteria van die lugruimbeheerstelsel te bepaal. Die besluitnemingsvraagstuk is geformuleer deur vyf kriteria en tien aansoekers in te span. Die verhouding tussen die wasige Orde Voorkeur deur Ooreenkoms tot die Ideale Oplossing en wasig-geweegde gemiddeld was besonder positief vir besluitneming. Die resultate van die wasige Orde Voorkeur deur Ooreenkoms tot die Ideale Oplossing en die Data Omvangs Analise moedig die ontwikkeling van 'n besluitneming ondersteuningstelsel vir lugruimbeheerders aan.