Leveraging Big Data Analytics to Improve Quality of Care in Healthcare Organizations: A Configurational Perspective

Big data analytics (BDA) is beneficial for organizations, yet implementing BDA to leverage profitability is fundamental challenge confronting practitioners. Although prior research has explored the impact that BDA has on business growth, there is a lack of research that explains the full complexity of BDA implementations. Examination of how and under what conditions BDA achieves organizational performance from a holistic perspective is absent from the existing literature. Extending the theoretical perspective from the traditional views (e.g. resource‐based theory) to configuration theory, the authors have developed a conceptual model of BDA success that aims to investigate how BDA capabilities interact with complementary organizational resources and organizational capabilities in multiple configuration solutions leading to higher quality of care in healthcare organizations. To test this model, the authors use fuzzy‐set qualitative comparative analysis to analyse multi‐source data acquired from a survey and databases maintained by the Centres for Medicare & Medicaid Services. The findings suggest that BDA, when given alone, is not sufficient in achieving the outcome, but is a synergy effect in which BDA capabilities and analytical personnel's skills together with organizational resources and capabilities as supportive role can improve average excess readmission rates and patient satisfaction in healthcare organizations.     

Measuring open source software success

Since the mid-1990s, there has been a surge of interest among academics and practitioners in open source software (OSS). While there is an abundance of literature on OSS, most studies on OSS success are either qualitative or exploratory in nature. To identify the factors that influence OSS success and establish generalizability, an empirical study measuring OSS success would enable OSS developers and users to improve OSS usage. In this study, we develop an OSS success model from a previous Information Systems success model incorporating the characteristics of OSS. Using the proposed model, we identify five determinants for OSS success as well as a number of significant relationships among these determinants. Our findings demonstrate that software quality and community service quality have significant effects on user satisfaction. Software quality and user satisfaction, in turn, have significant effects on OSS use. Additionally, OSS use and user satisfaction have significant effects on individual net benefits. This research contributes towards advancing theoretical understanding of OSS success as well as offering OSS practitioners for enhancing OSS success.     

Optimal Descending Mechanisms for Constrained Procurement

Descending mechanisms for procurement (or, ascending mechanisms for selling) have been well‐recognized for their simplicity from the viewpoint of bidders—they require less bidder sophistication as compared to sealed‐bid mechanisms. In this study, we consider procurement under each of two types of constraints: (1) Individual/Group Capacities: limitations on the amounts that can be sourced from individual and/or subsets of suppliers, and (2) Business Rules: lower and upper bounds on the number of suppliers to source from, and on the amount that can be sourced from any single supplier. We analyze two procurement problems, one that incorporates individual/group capacities and another that incorporates business rules. In each problem, we consider a buyer who wants to procure a fixed quantity of a product from a set of suppliers, where each supplier is endowed with a privately known constant marginal cost. The buyer's objective is to minimize her total expected procurement cost. For both problems, we present descending auction mechanisms that are optimal mechanisms. We then show that these two problems belong to a larger class of mechanism design problems with constraints specified by polymatroids, for which we prove that optimal mechanisms can be implemented as descending mechanisms.     

An advertising effect model

A model of advertising effects has been developed based on a distinction between “persuasion” advertising and “trigger” advertising. The former is designed to induce prospective purchasers to try the product and to establish a “product image”. The latter is aimed at “triggering” a purchase on the part of an individual whose image of the product has already been formed. The distinction has major implications for the type and timing of advertising. The model can be applied to determining an optimum distribution of advertising effort in the introduction of a new product, and the optimum advertising media mix.     

Children's Cognitive Perceptions of 6/49 Lottery Tickets

Recent studies have shown the high prevalence of youth gambling behavior. In particular, lottery ticket purchases among children and adolescents appear to be a highly preferred activity. Despite this fact, most research has focused on the underlying erroneous cognitions used by adults when selecting lottery tickets. This study examines the cognitive perceptions of children while engaged in selecting 6/49 lottery tickets. One hundred sixty-seven children (61 females; 106 males) from grades 3, 5, and 7 were asked to rank pre-selected 6/49 lottery tickets which were classified into a) long series, b) specific patterns, c) non equilibrated numbers, or d) perceived random selections. Children verbalized their rationale for selecting each ticket and were permitted to change the numbers on the lottery tickets they liked least in order to make them to more likely to be the winning ticket. Findings, in general, revealed small developmental differences in the types of underlying cognitive heuristics used by the children. The use of cognitive heuristics underlying the concept of randomness and the use of significant and meaningful numbers was observed to increase as children got older. Children between 9 and 11 were found to have employed the cluster heuristic more frequently than older children, ages 12–13. The results are interpreted in terms of the cognitive developmental changes in children's perceptions and the potential implication for gambling prevention programs are provided.     

A learning vector quantization neural network model for the classification of industrial construction projects

In several key functional areas of contemporary engineering and management science, neural networks have steadily been gaining recognition as robust and reliable tools for classification problems. This paper describes a new application of the learning vector quantization neural network: the classification of the degree of modularization appropriate for the construction of an industrial facility. This neural network uses variables related to plant location, labor issues, organizational issues, plant characteristics, project risks, and environmental issues as inputs to perform the classification. The neural network training and performance evaluation is also discussed.     

Time series analysis of out patients at Urban Health Centre, Suraj Kund, Meerut

Time series analysis of out-patients at Urban Health Centre, Suraj Kund, Meerut, was done using the out-patient attendance of last five years, with the aim to find out the values to help in coping up with the problem of health administration and management. The least square method and ratio-to-trend method were adopted for calculating the secular trend and seasonal variations respectively. There was an increasing trend in out-patients attendance indicating the increasing popularity of the Urban Health Centre. It was found that in second and third quarter of the year the out-patient attendance increased extraordinarily due to various reasons. The two more aspects of time series, i.e. cyclical trend and irregular flactuation could not be analysed due to their insignificant impact over the health management system.     

Workforce‐constrained Preventive Maintenance Scheduling Using Evolution Strategies

Heavy equipment overhaul facilities such as aircraft service centers and railroad yards face the challenge of minimizing the makespan for a set of preventive maintenance (PM) tasks, requiring single or multiple skills, within workforce availability constraints. In this paper, we examine the utility of evolution strategies to this problem. Comparison of the computational efforts of evolution strategies with exhaustive enumeration to reach optimal solutions for 60 small problems illustrates the ability of evolution strategies to yield optimal solutions increasingly efficiently with increasing problem size. A set of 852 large‐scale problems was solved using evolution strategies to examine the effects of task‐related problem characteristics, workforce‐related variables, and evolution strategies population size (μ) on CPU time. The results empirically supported practical utility of evolution strategies to solve large‐scale, complex preventive maintenance problems involving single‐ and multiple‐skilled workforce. Finally, comparison of evolution strategies and simulated annealing for the 852 experiments indicated much faster convergence to optimality with evolution strategies.     

BUSINESS STRATEGY,MANUFACTURING FLEXIBILITY,AND ORGANIZATIONAL PERFORMANCE RELATIONSHIPS: A PATH ANALYSIS APPROACH

It has been argued in the literature that business strategy and manufacturing flexibility independently affect the performance of an organization. However, no empirical examination of the interrelationship among these three constructs has been performed. In this paper, based on a field study of 269 firms in the manufacturing industry, the identified constructs have been used to test a theoretical model using path analysis techniques. Our results indicate that business strategy contributes both directly and indirectly to organizational performance. The findings provide evidence of direct effects of (i) business strategy on manufacturing flexibility and (ii) manufacturing flexibility on organizational performance.