A BowTie is a diagram illustrating proactive and reactive risk management at any working environment. This case study applied the bowtie method to provide a simple visual analysis of the hazards that caused fatal accidents at Kaziwiziwi coal mine on 2nd November 2012 and 15th November 2019. Two coal miners were killed on the spot and others injured due to failure of a bucket hoisting system and hanging rock fall. The authors demonstrated that the bowtie method is an effective visualization tool that can be used to analyze the hazard, top event, threats, consequences, barriers and escalation factors of mining accidents; and therefore give an overview of everything not wanted around a certain hazard. Mining companies in Malawi will apply this new knowledge to proactively conduct situational audits of unwanted scenarios, and identify barriers to prevent accidents from happening so far as is reasonably practicable. In addition, the Department of Mines will find this bowtie visualization tool useful when carrying out accident analyses in the future which in turn will promote safety awareness and policy development in the mining industry, and suggest ways on how to keep the normal but hazardous aspects from turning into something unwanted.
{"title":"Application of the BowTie Method in Accident Analysis: Case of Kaziwiziwi Coal Mine","authors":"J. Matsimbe, Steven Ghambi, Abdul Samson","doi":"10.31224/osf.io/drjva","DOIUrl":"https://doi.org/10.31224/osf.io/drjva","url":null,"abstract":"A BowTie is a diagram illustrating proactive and reactive risk management at any working environment. This case study applied the bowtie method to provide a simple visual analysis of the hazards that caused fatal accidents at Kaziwiziwi coal mine on 2nd November 2012 and 15th November 2019. Two coal miners were killed on the spot and others injured due to failure of a bucket hoisting system and hanging rock fall. The authors demonstrated that the bowtie method is an effective visualization tool that can be used to analyze the hazard, top event, threats, consequences, barriers and escalation factors of mining accidents; and therefore give an overview of everything not wanted around a certain hazard. Mining companies in Malawi will apply this new knowledge to proactively conduct situational audits of unwanted scenarios, and identify barriers to prevent accidents from happening so far as is reasonably practicable. In addition, the Department of Mines will find this bowtie visualization tool useful when carrying out accident analyses in the future which in turn will promote safety awareness and policy development in the mining industry, and suggest ways on how to keep the normal but hazardous aspects from turning into something unwanted.","PeriodicalId":296500,"journal":{"name":"EngRN: Systems Engineering (Topic)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128455365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The increasing demand for Intensive Care Unit (ICU) beds requires efficient admission, discharge, and care processes. Although all such efforts require predictions of Length of Stay (LOS) values, it is unclear how accurate those predictions need to be. This study aims to investigate the relationship between accuracy level of LOS predictions and operational performance indicators. To model the ICU patient flows, a discrete event simulation model is developed. A linear function of actual and simulated LOS values is used to measure the accuracy level of the predictions. Multiple configurations of patient mix and patient waiting threshold were included in the simulation scenarios. Performance indicators are average waiting time of patients for an ICU bed and overall admission ratios. Further statistical tests were carried out to evaluate the significance of the results. Results suggest that inaccurate LOS predictions overestimated both average waiting time of patients for an ICU bed and overall admission rates. The gaps increased when more elective patients were included in the patient mix. Moreover, higher waiting thresholds (i.e. maximum amount of time a patient will wait for an ICU bed) yielded higher values in both performance indicators.
{"title":"Analysing the Value of Intensive Care Unit Length of Stay Information Through Its Operational Performance","authors":"E. Bahalkeh, Imran Hasan, Yuehwern Yih","doi":"10.2139/ssrn.3679697","DOIUrl":"https://doi.org/10.2139/ssrn.3679697","url":null,"abstract":"The increasing demand for Intensive Care Unit (ICU) beds requires efficient admission, discharge, and care processes. Although all such efforts require predictions of Length of Stay (LOS) values, it is unclear how accurate those predictions need to be. This study aims to investigate the relationship between accuracy level of LOS predictions and operational performance indicators. To model the ICU patient flows, a discrete event simulation model is developed. A linear function of actual and simulated LOS values is used to measure the accuracy level of the predictions. Multiple configurations of patient mix and patient waiting threshold were included in the simulation scenarios. Performance indicators are average waiting time of patients for an ICU bed and overall admission ratios. Further statistical tests were carried out to evaluate the significance of the results. Results suggest that inaccurate LOS predictions overestimated both average waiting time of patients for an ICU bed and overall admission rates. The gaps increased when more elective patients were included in the patient mix. Moreover, higher waiting thresholds (i.e. maximum amount of time a patient will wait for an ICU bed) yielded higher values in both performance indicators.","PeriodicalId":296500,"journal":{"name":"EngRN: Systems Engineering (Topic)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124362572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Probability bounds on the sum of $n$ pairwise independent Bernoulli random variables exceeding an integer $k$ have been proposed in the literature. However, these bounds are not tight in general. In this paper, we provide three results towards finding tight probability bounds on the sum of pairwise independent Bernoulli random variables. Firstly, for $k = 1$, the tightest upper bound on the probability of the union of $n$ pairwise independent events is provided. Secondly, for $k geq 2$, the tightest upper bound with identical marginals is provided. Lastly, for general pairwise independent Bernoulli random variables, new upper bounds are derived for $k geq 2$, by ordering the probabilities. These bounds improve on existing bounds and are tight under certain conditions. The proofs of tightness are developed using techniques of linear optimization. Numerical examples are provided to quantify the improvement of the bounds over existing bounds.
{"title":"Tight Probability Bounds with Pairwise Independence","authors":"Arjun Ramachandra, K. Natarajan","doi":"10.2139/ssrn.3622258","DOIUrl":"https://doi.org/10.2139/ssrn.3622258","url":null,"abstract":"Probability bounds on the sum of $n$ pairwise independent Bernoulli random variables exceeding an integer $k$ have been proposed in the literature. However, these bounds are not tight in general. In this paper, we provide three results towards finding tight probability bounds on the sum of pairwise independent Bernoulli random variables. Firstly, for $k = 1$, the tightest upper bound on the probability of the union of $n$ pairwise independent events is provided. Secondly, for $k geq 2$, the tightest upper bound with identical marginals is provided. Lastly, for general pairwise independent Bernoulli random variables, new upper bounds are derived for $k geq 2$, by ordering the probabilities. These bounds improve on existing bounds and are tight under certain conditions. The proofs of tightness are developed using techniques of linear optimization. Numerical examples are provided to quantify the improvement of the bounds over existing bounds.","PeriodicalId":296500,"journal":{"name":"EngRN: Systems Engineering (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116314106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Customer is a king and Customers are the mainly focused in making new marketing strategy. In the banking field a unique relationship exists between the customers and the bank. But because of various reasons like lack of training ,new technology literacy, financial targets, risk of failure etc., some banks are still following the traditional ways of marketing and another hand some are making attempts to adapt CRM. It is with this background, the researcher has made a modest attempt towards the idea that CRM can be adapted uniformly in the banking industry for betterment of Banking Services. Understanding on Customer Relationship Management is always a concern among the service providers especially banks. Banks makes their own way of managing their relationships new and existing customers. The aim of this paper is to examine the Customer Relationship Management as a new methodology looks forward to identify and attract consumers through the process of developing relationships (business - customer). The methodology of the CRM aims to maintain customer satisfaction and increase consumer loyalty. The purpose of this paper is to study the importance of CRM systems and in-depth knowledge of methods and management techniques customer relationships. The main issue of this study is that CRM has become a multi-faceted and complex phenomenon that is ridden by various factors. Due to this complexity, a number of different variables have been used to measure CRM which investigated by several prior studies. However, most of businesses need to know and look at the particular measures and dimensions of the CRM that have a significant impact on customer satisfaction and loyalty, which would enrich the business' performance, especially with the increase in competition as well as lack of differentiation in providing a service. This paper aimed to review literature on CRM and to identify its impact on customer satisfaction and customer loyalty. The studies are analyzed on the basis of some general characteristics and variables that significantly enhance CRM and its influence on customer satisfaction and customer loyalty. For this purpose, we investigate the existing literature on the impact of CRM on customer satisfaction and customer loyalty along with its spread among publications to identify the potential development in the field.
{"title":"Role of CRM in Indian Banking Sector","authors":"Virendra M. Chaudhari","doi":"10.31033/ijemr.10.1.11","DOIUrl":"https://doi.org/10.31033/ijemr.10.1.11","url":null,"abstract":"Customer is a king and Customers are the mainly focused in making new marketing strategy. In the banking field a unique relationship exists between the customers and the bank. But because of various reasons like lack of training ,new technology literacy, financial targets, risk of failure etc., some banks are still following the traditional ways of marketing and another hand some are making attempts to adapt CRM. It is with this background, the researcher has made a modest attempt towards the idea that CRM can be adapted uniformly in the banking industry for betterment of Banking Services. Understanding on Customer Relationship Management is always a concern among the service providers especially banks. Banks makes their own way of managing their relationships new and existing customers. The aim of this paper is to examine the Customer Relationship Management as a new methodology looks forward to identify and attract consumers through the process of developing relationships (business - customer). The methodology of the CRM aims to maintain customer satisfaction and increase consumer loyalty. The purpose of this paper is to study the importance of CRM systems and in-depth knowledge of methods and management techniques customer relationships. \u0000The main issue of this study is that CRM has become a multi-faceted and complex phenomenon that is ridden by various factors. Due to this complexity, a number of different variables have been used to measure CRM which investigated by several prior studies. However, most of businesses need to know and look at the particular measures and dimensions of the CRM that have a significant impact on customer satisfaction and loyalty, which would enrich the business' performance, especially with the increase in competition as well as lack of differentiation in providing a service. This paper aimed to review literature on CRM and to identify its impact on customer satisfaction and customer loyalty. The studies are analyzed on the basis of some general characteristics and variables that significantly enhance CRM and its influence on customer satisfaction and customer loyalty. For this purpose, we investigate the existing literature on the impact of CRM on customer satisfaction and customer loyalty along with its spread among publications to identify the potential development in the field.","PeriodicalId":296500,"journal":{"name":"EngRN: Systems Engineering (Topic)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131128930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we quantify the effects that product stock-outs led consumer dissatisfactions have on consumer behavior. The study yields a practical solution that retailers could use to determine how a representative consumer is likely to respond to a stock-out situation and hence be proactive in relationship management. We also determine backorder costs that captures both the short term and long term effects of stock-outs and helps retailers in assortment planning. We use the concept of dissatisfaction and the theory of dissatisfaction dynamics to link past temporal patterns in stock-outs to the current dissatisfaction levels and its effects of consumer choice (substitution, postponement, and abandonment). The richness in consumer behavior and the variability in the dissatisfaction levels allow us to: (a) Confirm the existence of a nonlinear relationship between dissatisfaction and consumer behavior and even characterize it as an asymmetric S-shape; and (b) Develop realistic estimates of the backorder costs as a weighted sum of the probabilities of various consumer actions times the costs associated with each action.
{"title":"Dynamics of Consumers’ Dissatisfaction Due to Stock-Outs","authors":"S. Koos, N. I. Shaikh","doi":"10.2139/ssrn.3122010","DOIUrl":"https://doi.org/10.2139/ssrn.3122010","url":null,"abstract":"In this paper, we quantify the effects that product stock-outs led consumer dissatisfactions have on consumer behavior. The study yields a practical solution that retailers could use to determine how a representative consumer is likely to respond to a stock-out situation and hence be proactive in relationship management. We also determine backorder costs that captures both the short term and long term effects of stock-outs and helps retailers in assortment planning. We use the concept of dissatisfaction and the theory of dissatisfaction dynamics to link past temporal patterns in stock-outs to the current dissatisfaction levels and its effects of consumer choice (substitution, postponement, and abandonment). The richness in consumer behavior and the variability in the dissatisfaction levels allow us to: (a) Confirm the existence of a nonlinear relationship between dissatisfaction and consumer behavior and even characterize it as an asymmetric S-shape; and (b) Develop realistic estimates of the backorder costs as a weighted sum of the probabilities of various consumer actions times the costs associated with each action.","PeriodicalId":296500,"journal":{"name":"EngRN: Systems Engineering (Topic)","volume":"945 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116427470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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