Healthcare 4.0: trends,challenges and research directions

Abstract

This paper aims at examining the trends, challenges and theoretical gaps in the implementation of Healthcare 4.0 (H4.0) based on a scoping review of the literature. For that, we searched journal articles in four widely known databases and screened the retrieved articles to obtain a publications’ portfolio. Our findings indicate that, despite the recency of the subject, research in H4.0 has been conducted in an interdisciplinary way with a diversified set of applications and functionalities. In terms of its implementation, H4.0 has been more commonly found in hospitals’ information flows, especially the ones related to healthcare treatments. The identified implementation trends, however, neglect a more holistic approach for H4.0, which originated three main research directions for this topic. Although identified as a trending topic in the area of healthcare operations management, literature on H4.0 may be viewed as randomly conceived, lacking academic alignment and practical orientation based on a grounded theory, which we aim at providing with the present study.     

Multivariate log-Birnbaum–Saunders regression models

In this paper, we present a multivariate version of the skewed log-Birnbaum–Saunders regression model. This new family of distributions holds good properties such as marginal variables following univariate skewed log-Birnbaum–Saunders distributions, besides presenting the usual log-Birnbaum–Saunders distribution as a particular case. Furthermore, the model parameters are estimated through maximum-likelihood methods, a closed-form expression for the Fisher’s information matrix is presented, and testing hypothesis for model parameters is performed. Two real datasets are analyzed and results are discussed.     

Welfare State Development in Latin America and the Caribbean (1970s–2000s): Multidimensional Welfare Index,Its Methodology and Results

There is an ongoing debate between focalization and universalization on welfare policies as the best way to develop the welfare state in Latin America and the Caribbean. However, there is a need to develop a measure that exhibits the multidimensional nature of the welfare state, instead of focusing on the social spending dimension. Segura-Ubiergo (The political economy of the welfare state in Latin America: globalization, democracy and development. Cambridge University Press, New York, 2007) constructed a welfare effort index (WEI) to facilitate understand the relative degrees of welfare state development among Latin American countries. The WEI focuses mainly on social spending and ignores the other dimensions of welfare. Based on a comparative analysis of 17 Latin American countries and following the methodology of Segura-Ubiergo, a new index that aims at enriching the WEI was constructed. The new index is multidimensional in that it has eight indicators relating to three dimensions of welfare: social spending, coverage of welfare programs and outcome of welfare institutions. Principal component analysis was used for reducing the indicators into three indexes that represent three proposed dimensions of welfare. The combination of these three indexes gives the multidimensional welfare index. The results of the index account for more than 75 % of the data variance.     

Examining Familial-Based Academic Success Factors in Urban High School Students: The Case of Puerto Rican Female High Achievers

ABSTRACT

This article works to dispel the myth that Puerto Rican female urban high school students living in poverty are not capable of performing at high academic levels. This article attempts to counteract these beliefs by describing the four success factors that seven Puerto Rican female high school students attribute to their high academic achievement. These success factors are: (1) religiosity and extracurricular activities as sources of social capital, (2) affirming and maintaining a Puerto Rican identity, (3) maternal influences on students' academic achievement and, (4) the potential for caring teachers and other school staff to influence high academic achievement. Finally, our findings suggest that opportunities for Latinas and other youth of color are still inequitably structured in large, comprehensive high schools. Hence, we argue that schools must continue to bridge the large gap between themselves and the families/communities they serve and utilize the funds of knowledge and social capital that their students already bring to school.     

Rivalry and strategic groups: what makes a company a rival?

Strategic group literature has generated a significant amount of research over recent decades. However, the rivalry implications of strategic group have remained unclear. This paper analyses rivalry and strategic groups in the house building industry in a small town from a cognitive approach. We consider rivalry as a subjective and directional phenomenon. Estimating rivalry as the direct identification of competitors we try to explain whether similarity affects rivalry and what factors make a company a “rival”. Results show that perceived rivalry is strongly related to size, past performance, subjective similarity and strategic group structure.

A reactive tabu search algorithm for the vehicle routing problem with simultaneous pickups and deliveries

The vehicle routing problem with pickups and deliveries (VRPPD) extends the vehicle routing problem (VRP) by allowing customers to both send and receive goods. The main difficulty of the problem is that the load of vehicles is fluctuating rather than decreasing as in the VRP. We design a reactive tabu search metaheuristic that can check feasibility of proposed moves quickly and reacts to repetitions to guide the search. Several new best solutions are found for benchmark problems.     

Essence taxonomy of Brazilian family businesses and conceptual implications for governance strategy

Journal of Management and Governance - This study advances the discussion on the governance of family businesses in emerging markets by exploring a taxonomy based on the F-PEC model in order to...     

Application of the Hyper‐Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes

The hyper‐Poisson distribution can handle both over‐ and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation‐specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper‐Poisson distribution in analyzing motor vehicle crash count data. The hyper‐Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway‐highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness‐of‐fit measures indicated that the hyper‐Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper‐Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway‐Maxwell‐Poisson model previously developed for the same data set. The advantages of the hyper‐Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper‐Poisson model can handle both over‐ and underdispersed crash data. Although not a major issue for the Conway‐Maxwell‐Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model.     

On the Diaconis-Gangolli Markov chain for sampling contingency tables with cell-bounded entries

The problems of uniformly sampling and approximately counting contingency tables have been widely studied, but efficient solutions are only known in special cases. One appealing approach is the Diaconis and Gangolli Markov chain which updates the entries of a random 2×2 submatrix. This chain is known to be rapidly mixing for cell-bounded tables only when the cell bounds are all 1 and the row and column sums are regular. We demonstrate that the chain can require exponential time to mix in the cell-bounded case, even if we restrict to instances for which the state space is connected. Moreover, we show the chain can be slowly mixing even if we restrict to natural classes of problem instances, including regular instances with cell bounds of either 0 or 1 everywhere, and dense instances where at least a linear number of cells in each row or column have non-zero cell-bounds.     

Environmental and social supply chain management sustainability practices: construct development and measurement

The purpose of this paper is to conceptualise and operationalise the concept of supply chain management sustainability practices. Based on a multi-stage procedure involving a literature review, expert Q-sort and pre-test process, pilot test and survey of 156 supply chain directors and managers in Ireland, we develop a multidimensional conceptualisation and measure of social and environmental supply chain management sustainability practices. The research findings show theoretically sound constructs based on four underlying sustainable supply chain management practices: monitoring, implementing systems, new product and process development and strategy redefinition. A two-factor model is then identified as the most reliable: comprising process-based and market-based practices.