Classification of Poverty Condition Using Natural Language Processing

Social Indicators Research - This work introduces a methodology to classify between poor and extremely poor people through Natural Language Processing. The approach serves as a baseline to...     

Conducting systematic literature review in operations management

Systematic literature review (SLR) is a well-known research method. However, there is a paucity of detailed SLR guidelines in operations management (OM). The recent interest in SLR in OM has not been followed by the same rigour observed in disciplines as medical sciences and public policy. There are no OM-specific SLR protocols, detailed step-by-step methods and reporting procedures. Therefore, this paper provides a step-by-step approach to SLR for OM scholars and an overview of SLR’s evolution as a research method in OM and the resulting progression of themes. The step-by-step approach aims to serve as a guideline sufficiently broad to avoid skipping any significant step, but still being easy to be understood and applied. The paper describes procedures for rigourous SLR, reveals a growing use of literature review in OM, specially for qualitative SLR and traditional narrative reviews, assesses contemporary and emerging themes in OM, and provides a research agenda.     

Analyzing Precautionary Regulation: Do Precaution,Science, and Innovation Go Together?

In this article we argue that the precautionary principle, as applied to the regulation of science and technology, cannot be considered in any general manner inconsistent with the norms and methods of scientific knowledge generation and justification. Moreover, it does not necessarily curtail scientific‐technological innovation. Our argument flows from a differentiated view of what precaution in regulation means. We first characterize several of the most relevant interpretations given to the precautionary principle in academic debate and regulatory practice. We then use examples of actual precaution‐based regulation to show that, even though science can have varying functions in different circumstances and frames, all of those interpretations recur to scientific method and knowledge, and tend to imply innovation in methods, products, and processes. In fact, the interplay of regulation and innovation in precautionary policy, at least in the case of the interpretations of precaution that our analysis takes into account, could be understood as a way of reconciling the two fundamental science and technology policy functions of promotion and control.     

Involving academics in the accounting standard setting process: an application of the Delphi methodology to the assessment of IASB proposals

The aim of this paper is to highlight the relevance of academic input to the accounting standard setting process by way of both ex-ante research and direct participation. We propose the Delphi methodology as a rigorous scientific way to analyse the perception of a new IASB accounting regulation from an “ex-ante” constituency perspective. We argue that this tool can be used as a useful complementary analysis to introduce timely and comprehensive additional feedback to standard-setters’ deliberations regarding the potential effects of their proposals when some conditions are met, and that gaining academic input in the process could make a difference. We apply this to the specific case of the IASB Management Commentary project. The main contribution of this study is to show how this research yields different perceptions that can add to the analysis of comment letters in the deliberations of the IASB. The most remarkable findings are (1) that the introduction of academic opinions (practically absent in the formal consultation process) yields important and different inputs and (2) that the characteristics of this tool allow for additional arguments, which are not usually evident in the formal comment letters, to be obtained from constituents. This study attempts to respond to the recent standard-setter call for more academic contributions to the standard-setting process.     

Bayesian fractional polynomials

This paper sets out to implement the Bayesian paradigm for fractional polynomial models under the assumption of normally distributed error terms. Fractional polynomials widen the class of ordinary polynomials and offer an additive and transportable modelling approach. The methodology is based on a Bayesian linear model with a quasi-default hyper-g prior and combines variable selection with parametric modelling of additive effects. A Markov chain Monte Carlo algorithm for the exploration of the model space is presented. This theoretically well-founded stochastic search constitutes a substantial improvement to ad hoc stepwise procedures for the fitting of fractional polynomial models. The method is applied to a data set on the relationship between ozone levels and meteorological parameters, previously analysed in the literature.     

Social capital in the field of power: the case of Norway

This paper analyses social capital structures in the field of power, based on data from the Norwegian Power and Democracy Survey on elites. Separating between objectified, institutionalised, embodied, and inherited social capital, and inspired by Bourdieu's approach, we analyse the relations between social capital and the other forms of capital by way of specific multiple correspondence analysis and ascending hierarchical cluster analysis. First, we find that the level of institutionalised social capital varies from one fraction of the Norwegian elite to another. Secondly, the range of networks established through previous work experiences is related to field seniority. Thirdly, the positions of highest endogamy are situated in the religious field, and to a lesser extent, in the scientific field, and in the juridical field. Finally, the ‘core of the core’ is defined by actors who are strongly interconnected inside what is called ‘the tripartite system’, with a high level of multipositionality and intersectorial connections.     

Distribution of cost inefficiency in stochastic frontier approach: evidence from Spanish banking

The aim of the paper is to demonstrate the appropriateness of an a priori analysis to determine the distributional assumption of the inefficiency term in a stochastic frontier model. To this end, theoretical distributions of estimated inefficiency were obtained when the inefficiency term is assumed to be distributed as a half normal and an exponential in a cost frontier model. Comparisons of such theoretical distributions with the respective cost inefficiency estimators using the goodness of fit test allow selecting the most appropriate distributional assumption. The application on three data sets of Spanish banking system in 2009 demonstrated the relevance of the research question. First, the results of estimated cost inefficiency with a half normal assumption are larger than with an exponential distribution significantly. Besides, half normal assumption was rejected and exponential was not rejected as the most appropriate distribution of inefficiency term in Spanish banking data set. However, the adjustment of saving banks data had been better with the former distribution than the latter. In the case of banks, any distribution results appropriate. To sum up, this work demonstrate that the distributional assumption on inefficiency term in Stochastic Frontier Approach must be established in a justified way, as it can significantly bias the results of estimated inefficiency and therefore, influences improving policies and strategies in the Spanish banking sector.