• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.1
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• pp.47-57
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• 2022

Purpose - Overall social entrepreneurship has a positive effect on the organization's C.S.R. and overall growth. This study aims to identify the effects of social entrepreneurship in startup companies on corporate social responsibility by identifying gaps in the literature and providing feasible solutions to the gaps. Research design, Data, and methodology - The qualitative content analysis that was conducted by this research takes the form of two research designs. The first step to conducting a conceptual content analysis is to choose the level of analysis, specifically words, phrases, word sense and the second step is the relational content analysis by choosing the concept to be examined, only that the analysis entails examining the relationships between concepts Result - According to the investigation of numerous previous literature review, the current authors found out total six solutions and the application of suggested solutions indicated that the use of innovative models, startup organizations can gain a competitive edge against dominant competitors in their industry of operations, Conclusion - Finally, the conclusion of this research indicates through the use of innovative solution models, startup organizations can gain a competitive edge against dominant competitors in their industry of operations and startup companies may range from an increase in reputation to growth in profitability and entrepreneurs' satisfaction.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.417-422
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• 2020

Vast quantities of environmental pollutants from construction projects are causing significant damage to nearby local communities and thus generate environmental complaints. The construction company, responsible for compensating and resolving environmental complaints, suffers economic damages due to additional expenditures and schedule delays in construction projects. Meanwhile, the construction industry can stagnate from a broader perspective. Therefore, this study aimed to propose a framework for developing an automated management system which consists of two models for environmental complaints in construction projects: (i) the prediction model: a model for predicting environmental complaints based on factors related to environmental complaints; and (ii) the prevention model: a model for providing construction companies with the optimal prevention measure to effectively prevent environmental complaints according to the results of the prediction model. In addition, the algorithm for integrating the developed models into the management system in construction projects was proposed. Eventually, the application of the management system to construction projects can ensure the profitability of construction companies and mitigate damage from environmental pollutants to the nearby local community.

• Journal of Information Technology Applications and Management
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• v.30 no.3
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• pp.1-13
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• 2023

Demand forecasting is a crucial task for an online retail where has to manage daily fresh foods effectively. Failing in forecasting results loss of profitability because of incompetent inventory management. This study investigated the optimal performance of different forecasting models for a very short shelf-life product. Demand data of 13 perishable items with aging of 210 days were used for analysis. Our comparison results of four methods: Trivial Identity, Seasonal Naïve, Feed-Forward and Autoregressive Recurrent Neural Networks (DeepAR) reveals that DeepAR outperforms with the lowest MAPE. This study also suggests the managerial implications by employing coefficient of variation (CV) as demand variation indicators. Three classes: Low, Medium and High variation are introduced for classify 13 products into groups. Our analysis found that DeepAR is suitable for medium and high variations, while the low group can use any methods. With this approach, the case can gain benefit of better fill-rate performance.

• Corrosion Science and Technology
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• v.23 no.2
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• pp.131-138
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• 2024

This paper introduces Primetals Technologies' Through-Process Optimization (TPO) Services and Through-Process Quality Control (TPQC) System, which integrate domain knowledge, software, and automation expertise to assist steel producers in achieving operational excellence. TPQC collects high-resolution process and product data from the entire production route, providing visualizations and facilitating quality assurance. It also enables the application of artificial intelligence techniques to optimize processes, accelerate steel grade development, and enhance product quality. The main objective of TPO is to grow and digitize operational know-how, increase profitability, and better meet customer needs. The paper describes the contribution of these systems to achieving operational excellence, with a focus on quality assurance. Transparent and traceable production data is used for manual and automatic quality evaluation, resulting in product quality status and guiding the product disposition process. Deviation management is supported by rule-based and AI-based assistants, along with monitoring, alarming, and reporting functions ensuring early recognition of deviations. Embedded root cause proposals and their corrective and compensatory actions facilitate decision support to maintain product quality. Quality indicators and predictive quality models further enhance the efficiency of the quality assurance process. Utilizing the quality assurance software package, TPQC acts as a "one-truth" platform for product quality key players.

• International Journal of Automotive Technology
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• v.6 no.1
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• pp.29-35
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• 2005

The structural integrity of either a passenger car or a light truck is one of the basic requirements for a full vehicle engineering and development program. The results of the vehicle product performance are measured in terms of ride and handling, durability, Noise/Vibration/Harshness (NVH), crashworthiness, and occupant safety. The level of performance of a vehicle directly affects the marketability, profitability and, most importantly, the future of the automobile manufacturer. In this study, the Virtual Proving Ground (VPG) approach has been developed to simulate dynamic nonlinear events as applied to automotive ride & handling. The finite element analysis technique provides a unique method to create and analyze vehicle system models, capable of including vehicle suspensions, powertrains, and body structures in a single simulation. Through the development of this methodology, event-based simulations of vehicle performance over a given three-dimensional road surface can be performed. To verify the predicted dynamic results, a single lane change test was performed. The predicted results were compared with the experimental test results, and the feasibility of the integrated CAE analysis methodology was verified.

• International Journal of Quality Innovation
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• v.9 no.3
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• pp.1-14
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• 2008

Patient satisfaction with the Emergency Department(ED) in a hospital is related to the length of stay, and especially to the amount of waiting time for medical treatments. ED overcrowding decreases quality and efficiency, therefore affecting hospitals' profitability. This paper presents a forecasting and simulation model for resource management of the ED at Moses H. Cone Memorial Hospital. A linear regression forecasting model is proposed to predict the number of ED patient arrivals, and then a simulation model is provided to estimate the length of stay of ED patients, system throughput, and the utilization of resources such as triage nurses, patient beds, registered nurses, and medical doctors. The near future load level of each resource is presented using the proposed models.

• Asia Pacific Journal of Business Review
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• v.2 no.1
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• pp.69-85
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• 2017

Electronic commerce (e-commerce) has seen as the potential to improve profitability and productivity in many areas as well as gaining notable attention in many countries. Despite, there has been some uncertainty about the e-commerce impacts for developing countries. The sufficient basic infrastructural deficiency, socio-political, economic and the lack of government public ICT policies have formed the significant barriers to the adoption and e-commerce growth in developing countries. Even though there are many researchers have found the common barriers to e-commerce in the developing nations, all business models targeting those countries are not equally successful. Small companies' persistence failed to challenge the e-commerce barriers in Cambodia because the firms didn't know the correct business model to succeed in this country online market. Therefore, this study will discuss the existing barriers which lead to limit e-commerce growth in Cambodia and the suggested solutions with the suitable business model for the e-commerce business in the country too.

• International Journal of Automotive Technology
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• v.6 no.4
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• pp.413-419
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• 2005

The United States automotive recycling infrastructure has successfully reduced the amount of automotive waste sent to landfills, especially since the introduction of shredders in the late 1950s. Shredders are necessary to process and recycle automotive hulks and other durable goods. However, this industry faces significant challenges as the automotive manufacturers are increasing the use of nonmetallic components which are difficult to recycle. Additionally, it is becoming obvious that automobiles contain hazardous materials which place heavy burdens on the environment. To address this growing concern, we propose a process planning model for automotive shredders to make tactical decisions regarding at what level to process and at what level to reprocess feed stock materials. The purpose of this paper is to test analytical models to help shredders improve the profitability and efficiency of the bulk recycling processes for end of life automobile returns. The work is motivated by an actual recycling problem that was observed at Capitol City Metals shredding facility in Indianapolis, Indiana.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.493-505
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• 2006

Call center staffing problems have often relied upon queueing models, which are traditionally used to compute average call waiting time. However, the relationship between the in-bound call volume and call abandon rate is not directly explained even with the complex queueing formula while that relationship is a major interest to the hospital due to profitability. In this paper we provide a novel approach for the call center staffing problem by incorporating the relationship between the in-bound call volume and call abandon rate with a nonlinear integer programming, rather than using the traditional queueing model. We perform numerical analyses with actual data obtained from a reservation call center in a hospital.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.780-785
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• 2005

This paper aims to consider an overall benefit-duration optimization (OBDO) problem for the sake of maximizing owner's economic benefits, whilst considering influences of schedule compression incurred opportunity income on the profitability of a large-scale construction project. Unlike previous schedule optimization models and techniques that have focused on project duration or cost minimization, with greater weight on contractors' interests, OBDO facilitates owner's economic benefits through overall benefit-duration optimization. In this paper, the objective function of OBDO model is formulated. An example is illustrated to prove the feasibility and practicability of the overall benefit-duration optimization problem. The significance of employing OBDO model and future research work are also described.