“She was a little bit unrealistic”: Choice in healthcare decision making for older people

This paper examines autonomy, choice, options, and power in healthcare decision making for older people. Using discourse analysis and a case study from data gathered as part of an ethnographic field study we critique a common conceptualization of healthcare decision making as patients choosing from an array of options offered by healthcare providers. A discourse of “giving options and being realistic” used by healthcare providers is contrasted with the experience of a single patient's transitional care from hospital to home after hip fracture. This illustrates how a wide variety of actors, institutions, values, and resources take precedence in determining a discharge destination. While the accounts given by healthcare providers cast patient choice in respectful terms, an ethnographic approach illustrates that the “choices” are structured by a discourse which simplifies the complexity of what is offered and who gets to choose. In the case study the patient's choice was subjugated by expertise and institutional concerns; her options were largely illusory; and her autonomy was “at risk” due to her age, poor health, and limited resources. We use Foucault's ideas about discourse and governmentality to question the scope of agency in healthcare decision making. We argue that the conceptualization of informed patients making autonomous choices acts as “misdirection” which deflects problem solving and discussion away from a productive examination of the differences between healthcare system offerings and client needs. We conclude by posing questions to reorient the debate surrounding healthcare decision making for older adults and recommend a more participatory approach to designing social services.     

Market structure,bank conduct and bank performance: Evidence from ASEAN

Whether banks in a concentrated market increase their profits through monopoly pricing is a question of prime concern for antitrust policies. We explore this question by introducing the role of bank conduct into the structure–performance relationship. We apply Two-step System GMM dynamic panel model to commercial banks in the Association of South East Asian Nations over the period of 1999–2014. The results indicate that the higher profits in concentrated banking industries are partially attributable to the anti-competitive conduct of banks. These findings are robust across alternative measures of market structure and bank conduct, and different time horizons. The implications of these findings require regulators to make sure that the consolidation policy for ASEAN is achieving its purpose – i.e. financial stability – and not allowing the banks to earn monopoly rents.     

Overcoming institutional voids as a pathway to becoming ambidextrous: The case of China's Sichuan Telecom

The paper examines how firms develop supply chain financing model to help overcome institutional voids (IVs) and become ambidextrous. This study presents a case analysis of a novel supply chain financing model instigated and implemented by China's Sichuan Telecom (ST) to help supply chain partners overcome IVs in their environments. We identified three unique stages in the evolution of the supply chain ambidextrous financing model: drivers for change (including identifying suppliers' problems and constraints), designing and implementing the supply chain ambidextrous financing model, and the tripartite performance effects. The analysis demonstrated how ST utilized its market power, resources and network ties to harness expertise and competences of small and medium-sized enterprises (SMEs) to overcome IVs and become ambidextrous. Sichuan Telecom aided the SMEs in solving the financing problem through order-based supply chain financing. Based on the analysis, we outline implications of this case for theory and policy.     

A power log-Dagum distribution: estimation and applications

Development and application of probability models in data analysis are of major importance for all sciences. Therefore, we introduce a new model called a power log-Dagum distribution defined on the entire real line. The model contains many new sub-models: power logistic, linear log-Dagum, linear logistic and log-Dagum distributions among them. Some properties of the model including three different estimation procedures are justified. The model exhibits various shapes for the density and hazard rate functions. Moreover, the estimation procedures are compared using simulation studies. Finally, the model with others are fitted to three data sets, and it shows a better fit than the compared distributions defined on the real line.     

Optimal stratification in stratified designs using weibull-distributed auxiliary information

Sampling has evolved into a universally accepted approach for gathering information and data mining as it is widely accepted that a reasonably modest-sized sample can sufficiently characterize a much larger population. In stratified sampling designs, the whole population is divided into homogeneous strata in order to achieve higher precision in the estimation. This paper proposes an efficient method of constructing optimum stratum boundaries (OSB) and determining optimum sample size (OSS) for the survey variable. The survey variable may not be available in practice since the variable of interest is unavailable prior to conducting the survey. Thus, the method is based on the auxiliary variable which is usually readily available from past surveys. To illustrate the application as an example using a real data, the auxiliary variable considered for this problem follows Weibull distribution. The stratification problem is formulated as a Mathematical Programming Problem (MPP) that seeks minimization of the variance of the estimated population parameter under Neyman allocation. The solution procedure employs the dynamic programming technique, which results in substantial gains in the precision of the estimates of the population characteristics.     

Digital remediation: social support and online learning communities can help offset rural digital inequality

ABSTRACT

While all students enter college with varying levels of digital skills, those from rural areas may face extra challenges because their own skills and those of their pre-college networks may be underdeveloped. Without some type of intervention, digital deficits can perpetuate further educational disadvantages. We developed an online learning community (OLC) in two sections of an introductory college course and integrated collaborative learning into students’ weekly activities. Regression analysis of survey data (N?=?373) shows three impacts: access to social support is associated with higher skill assessment and improvements in digital skills; rural status is associated with a clear and significant disadvantage in digital skill assessment; and that involvement in an OLC contributed substantially to improvements in digital skills. We conclude with limitations and considerations for future research.     

Double moving average–EWMA control chart for exponentially distributed quality

A control chart is an ever-popular tool for monitoring the production process. The early detection of a process shift, if any, is the desire of the quality control personnel. In this article, an effective alternative control charting procedure has been developed for the monitoring of exponentially distributed quality characteristic using the double moving average combined with EWMA statistic. The performance of the proposed control chart is examined for different combinations of the shift constant, the EWMA smoothing parameter, the moving average span, and the target in-control average run lengths. It has been observed that the proposed control chart is more efficient in the detection of process shifts as compared to control chart suggested by Khoo and Wang for the same purpose. The proposed control chart is illustrated for practical usage with the help of a synthetic and a real dataset.     

Development of Economic Consequence Methodology for Process Risk Analysis

A comprehensive methodology for economic consequence analysis with appropriate models for risk analysis of process systems is proposed. This methodology uses loss functions to relate process deviations in a given scenario to economic losses. It consists of four steps: definition of a scenario, identification of losses, quantification of losses, and integration of losses. In this methodology, the process deviations that contribute to a given accident scenario are identified and mapped to assess potential consequences. Losses are assessed with an appropriate loss function (revised Taguchi, modified inverted normal) for each type of loss. The total loss is quantified by integrating different loss functions. The proposed methodology has been examined on two industrial case studies. Implementation of this new economic consequence methodology in quantitative risk assessment will provide better understanding and quantification of risk. This will improve design, decision making, and risk management strategies.     

Risk Analysis of Dust Explosion Scenarios Using Bayesian Networks

In this study, a methodology has been proposed for risk analysis of dust explosion scenarios based on Bayesian network. Our methodology also benefits from a bow‐tie diagram to better represent the logical relationships existing among contributing factors and consequences of dust explosions. In this study, the risks of dust explosion scenarios are evaluated, taking into account common cause failures and dependencies among root events and possible consequences. Using a diagnostic analysis, dust particle properties, oxygen concentration, and safety training of staff are identified as the most critical root events leading to dust explosions. The probability adaptation concept is also used for sequential updating and thus learning from past dust explosion accidents, which is of great importance in dynamic risk assessment and management. We also apply the proposed methodology to a case study to model dust explosion scenarios, to estimate the envisaged risks, and to identify the vulnerable parts of the system that need additional safety measures.