A comprehensive conceptual and bibliometric study of person-centered methodologies

Person-centered approaches, such as latent profile analysis (LPA) and qualitative comparative analysis (QCA), have gained in popularity in organizational scholarship because of their ability to provide insight into how interrelations between a group of conditions can lead to a particular outcome. Despite the growing acceptance of person-centered approaches in social science research, traditional variable-centered approaches continue to prevail, although their dominance is increasingly questioned. This paper offers in-depth analysis of the current state of QCA and LPA from both a conceptual and a bibliometric perspective. This study thus aims to contextualize the role of person-centered methodologies in organizational scholarship. This aim is important, given the significance of exploring novel approaches to advance knowledge in organizational research. This paper provides scholars with quantifiable and readily comparable information on the use of these emerging but promising methods in organizational studies. Ultimately, this scientific contribution sheds light on the current and prospective applications of person-centered methods in research. Moreover, it offers scholars who are considering applying these methods objective analysis of the scientific production in this area thus far.

     

Multiple Comparisons with the Best: Bayesian Precision Measures of Efficiency Rankings

A large literature measures the allocative and technical efficiency of a set of firms using econometric techniques to estimate stochastic production frontiers or distance functions. Typically, researchers compute only the precision of individual efficiency rankings. Recently, Horrace and Schmidt (Journal of Applied Economics 15, 1–26, 2000) have applied sampling theoretic statistical techniques known as multiple comparisons with a control (MCC) and multiple comparisons with the best (MCB) to make statistical comparisons of efficiency rankings. As an alternative, this paper offers a Bayesian multiple comparison procedure that we argue is simpler to implement, gives the researcher increased flexibility over the type of comparison, and provides greater, and more intuitive, information content. For these methods and a parametric bootstrap technique, we carry out multiple comparisons of technical efficiency rankings for a set of U.S. electric generating firms, estimated using a distance function framework. We find that the Bayesian method provides substantially more precise inferences than obtained using the MCB and MCC methods.Jel Classification: C11, C32, D24.     

A statistical procedure for testing social reciprocity at group,dyadic and individual levels

This paper examines statistical analysis of social reciprocity, that is, the balance between addressing and receiving behaviour in social interactions. Specifically, it focuses on the measurement of social reciprocity by means of directionality and skew-symmetry statistics at different levels. Two statistics have been used as overall measures of social reciprocity at group level: the directional consistency and the skew-symmetry statistics. Furthermore, the skew-symmetry statistic allows social researchers to obtain complementary information at dyadic and individual levels. However, having computed these measures, social researchers may be interested in testing statistical hypotheses regarding social reciprocity. For this reason, it has been developed a statistical procedure, based on Monte Carlo sampling, in order to allow social researchers to describe groups and make statistical decisions.     

在深入实施西部大开发战略中做强做精画院美术事业

在新一轮西部大开发的背景下,本文对书画院如何在新一轮西部大开发中抢抓机遇,加快画院美术事业又好又快发展,为全区文化大繁荣大发展做出新的贡献,更好地服务于宁夏经济社会科学发展、跨越式发展,进行了一些思考。     

Advancing Theory with Review Articles

Reviewing a body of work presents unique opportunities for making a theoretical contribution. Review articles can make readers think theoretically differently about a given field or phenomenon. Yet, review articles that advance theory have been historically under-represented in Journal of Management Studies. Accordingly, the purpose of this editorial is to propose a multi-faceted approach for fashioning theoretical contributions in review articles, which we hope will inspire more authors to develop and submit innovative, original, and high-quality theory-building review articles. We argue that advancing theory with review articles requires an integrative and generative approach. We propose a non-exhaustive set of avenues for developing theory with a review article: exposing emerging perspectives, analysing assumptions, clarifying constructs, establishing boundary conditions, testing new theory, theorizing with systems theory, and theorizing with mechanisms. As a journal, Journal of Management Studies is a journal of ideas – new ideas; ideas drawn from reflections on extant theory and ideas with potential to change the way we understand and interpret theory. With this in mind, we think that advancing theory with review articles is an untapped source of new ideas.     

Revisiting the difference between mixed methods and multimethods: Is it all in the name?

The literature on mixed methods and multimethods has burgeoned over the last 20 years, and researchers from a growing number and diversity of fields have progressively embraced these approaches. However, rapid growth in any movement inevitably gives rise to gaps or shortcomings, such as “identity crises” or divergent conceptual views. Although some authors draw a clear and sometimes opinionated distinction between mixed methods and multimethods, for others, they are synonymous. The concepts underlying both terms therefore have become blurred and generated much confusion. The aim of this article is to explore the origins of the confusion, describe our view of mixed methods and multimethod studies, and by doing so, help to clearly delineate the two concepts. The authors have presented their opinion of how these terms and concepts should be distinguished and call for a constructive debate of the issues involved in the mixed methods and multimethod literature. This is a way truly to propel the field forward.     

On the Review Process and Journal Development

abstract    This paper describes the editorial and review process currently operating at JMS and offers the Editors' perspective on the journal's growth over the past three years. We first outline what we think is the essence of a JMS article. Then, we describe the review process from the editor's initial decision, to the reviewers' comments, to the editor's final editorial decisions, and including the process of accepting a paper. We suggest four main reasons for rejecting a paper: lack of contribution, failure to develop a theoretical contribution, fatal flaws in methods and deficiencies in analysis. With respect to the journal's progress, we show that JMS has significantly increased its position in the ISI rankings to 19th and its impact factor to 1.180. In addition, the journal experienced a 222 per cent increase in submissions from 2003 to 2005.     

Methods for Handling Dropouts in Longitudinal Clinical Trials

This paper focuses on the monotone missing data patterns produced by dropouts and presents a review of the statistical literature on approaches for handling dropouts in longitudinal clinical trials. A variety of ad hoc procedures for handling dropouts are widely used. The rationale for many of these procedures is not well-founded and they can result in biased estimates of treatment comparisons. A fundamentally difficult problem arises when the probability of dropout is thought to be related to the specific value that in principle should have been obtained; this is often referred to as informative or non-ignorable dropout. Joint models for the longitudinal outcomes and the dropout times have been proposed in order to make corrections for non-ignorable dropouts. Two broad classes of joint models are reviewed: selection models and pattern-mixture models. Finally, when there are dropouts in a longitudinal clinical trial the goals of the analysis need to be clearly specified. In this paper we review the main distinctions between a 'pragmatic' and an 'explanatory' analysis. We note that many of the procedures for handling dropouts that are widely used in practice come closest to producing an explanatory rather than a pragmatic analysis.     

Computer assisted text analysis in the social sciences

We use the term “Computer Assisted Text Analysis” in a broad sense to refer to a range of current techniques from quantitative social science and content analysis to ‘data mining’ and ‘text classification’, including the analysis of open-ended survey questions, transcribed interviews and speeches, wherever, in fact, the researcher is confronted with data in the form of natural language texts of social scientific interest. These methods are often used in exploratory data analysis, but can also be applied systematically with moderate statistical rigour in the development and testing of hypotheses at various theoretical levels, ranging from the statistics of word usage to changes within or between discourses over time. The general approach is in the tradition of content analysis, by which words which occur together in relatively close proximity in the same context are interpreted as relating to a common theme or concept in the discourse studied. We review a comprehensive set of tools to identify and visualize structures of co-occurrence of words and concepts both within, and in comparing, a number of texts. These produce results not essentially different from those reached by representing word co-occurrences in terms of network analysis or neural network programming using schematic linguistic templates of various kinds. A comparison of the relational data analysis vs. a dictionary-based MDS approach shows that these provide very close if not identical results, despite the fact that the underlying assumptions are frequently represented as different theoretical approaches.     

Corporate Social Responsibility: Three Key Approaches

abstract    Corporate social responsibility remains an embryonic and contestable concept. This paper assesses three key approaches and offers a perspective gauging little prospect of theoretical synthesis. Ethical responsibility theory advocates strong corporate self-restraint and altruism duties and expansive public policy strengthening stakeholder rights. Economic responsibility theory advocates market wealth creation subject only to minimalist public policy and perhaps customary business ethics. These two viewpoints embed competing moral frameworks and political philosophies. Any theoretical synthesis must discover some subset of ethical principles yielding corporate competitive advantage. Corporate citizenship language invokes a political metaphor providing neither true intermediate positioning nor theoretical synthesis. Two conflicting interpretations abandon responsibility language without adopting the economic viewpoint. An instrumental citizenship interpretation expands philanthropy as a strategic lever for increasing corporate reputation and market opportunities while retaining managerial discretion. An ideal citizenship interpretation restates ethical responsibility into voluntarism language intended to influence managerial discretion concerning universal human rights.     

Thematic content analysis using supervised machine learning: An empirical evaluation using German online news

In recent years, two approaches to automatic content analysis have been introduced in the social sciences: semantic network analysis and supervised text classification. We argue that, although less linguistically sophisticated than semantic parsing techniques, statistical machine learning offers many advantages for applied communication research. By using manually coded material for training, supervised classification seamlessly bridges the gap between traditional and automatic content analysis. In this paper, we briefly introduce the conceptual foundations of machine learning approaches to text classification and discuss their application in social science research. We then evaluate their potential in an experimental study in which German online news was coded with established thematic categories. Moreover, we investigate whether and how linguistic preprocessing can improve classification quality. Results indicate that supervised text classification is generally robust and reliable for some categories, but may even be useful when it fails.     

Socially and environmentally responsible procurement: A literature review and future research agenda of a managerial issue in the 21st century

This literature review offers a rigorous approach, incorporating both quantitative and qualitative techniques, to examine research to date in the field of socially and environmentally responsible procurement (SERP). It identifies that the SERP literature is at a critical juncture in its development and that researchers should be aware of the literature's shortcomings and potential points of fragmentation. This is of considerable importance if the field is to become a salient issue in the wider management literature. As such, this review not only takes stock of the existing literature, but it provides a comprehensive and systematic analysis of existing contribution and their implications for practitioners. In addition, we highlight the avenues for future research, which has so far been neglected by academics, but which is critical from a practitioners and implementation perspective.     

Health Effects of Air Pollution: A Statistical Review

We critically review and compare epidemiological designs and statistical approaches to estimate associations between air pollution and health. More specifically, we aim to address the following questions:

• 1 Which epidemiological designs and statistical methods are available to estimate associations between air pollution and health?
• 2 What are the recent methodological advances in the estimation of the health effects of air pollution in time series studies?
• 3 What are the the main methodological challenges and future research opportunities relevant to regulatory policy?

In question 1, we identify strengths and limitations of time series, cohort, case‐crossover and panel sampling designs. In question 2, we focus on time series studies and we review statistical methods for: 1) combining information across multiple locations to estimate overall air pollution effects; 2) estimating the health effects of air pollution taking into account of model uncertainties; 3) investigating the consequences of exposure measurement error in the estimation of the health effects of air pollution; and 4) estimating air pollution‐health exposure‐response curves. Here, we also discuss the extent to which these statistical contributions have addressed key substantive questions. In question 3, within a set of policy‐relevant‐questions, we identify research opportunities and point out current data limitations.     

Probabilistic population forecasting: Short to very long-term

Population forecasts are used by governments and the private sector for planning, with horizons up to about three generations (around 2100) for different purposes. The traditional methods are deterministic using scenarios, but probabilistic forecasts are desired to get an idea of accuracy, assess changes, and make decisions involving risks. In a significant breakthrough, since 2015, the United Nations has issued probabilistic population forecasts for all countries using a Bayesian methodology that we review here. Assessment of the social cost of carbon relies on long-term forecasts of carbon emissions, which in turn depend on even longer-range population and economic forecasts, to 2300. We extend the UN method to very-long range population forecasts by combining the statistical approach with expert review and elicitation. While the world population is projected to grow for the rest of this century, it will likely stabilize in the 22nd century and decline in the 23rd century.     

HRM institutional entrepreneurship for sustainable business organizations

As businesses experience greater pressures from a variety of stakeholders concerned with promoting a balanced approach to managing the competing demands for increased profitability, improved social conditions, and restoring the health of planet earth, new opportunities arise for HRM scholars and professionals to contribute to the pursuit of sustainability. However, the foundational logic of sustainability diverges significantly from the dominant perspective in today's business environment. Building upon the institutional theory literature, we introduce the concept of HRM institutional entrepreneurship to examine the paradoxes and emerging opportunities associated with the urgent need for more sustainable approaches for managing business organizations. As a guide to future work, we describe how the actions of HRM scholars and professionals can stimulate evolution from an HRM philosophy that relies on financial indicators to assess effectiveness towards an HRM philosophy that promotes a tripartite approach to sustainability, showing equal concern for economic, environmental and social performance. Focusing on organizational changes that improve environmental performance, we apply the concept of HRM institutional entrepreneurship to consider ways for HRM professionals to engage internal and external stakeholders in order to create value in organizations pursuing sustainability. Ultimately, activities that constitute HRM institutional entrepreneurship for sustainable business drive the development of capabilities that characterize ambidextrous organizations.     

Freedom and gross in-migration: an empirical study of the post-great recession experience

Determinants of migration, including policy variables such as tax rates, have been extensively studied by regional scientists over the past several decades. The development of the Economic Freedom of North America Index has allowed researchers to test the relationship between migration patterns and economic freedom, with recent studies finding that net in-migration is positively related to economic freedom. Using a new cross-section measure of economic and personal freedom at the state level, we investigate the relationship between gross in-migration and economic freedom on the one hand and then between gross in-migration and total freedom on the other hand. This empirical study of domestic U.S. migration during the post-Great Recession period finds clear evidence that migrants prefer to move to those states affording higher levels of economic freedom and higher levels of total freedom.     

Entrepreneurial migrants from/in emerging economies: breaking taboos and stereotypes

Entrepreneurial migration from/in emerging economies, as grand societal and humanitarian challenges that we currently face, underscores the need for scholarly research. In our role as social science researchers, this special issue aimed to stimulate scholars from different social science fields to rethink more broadly about the opportunities for making an impact with our research focus on entrepreneurial migration from/in emerging economies. This article provides an overview of the theoretical, empirical, managerial, and policy implications of entrepreneurial migrants from/in emerging economies research. It puts forward key concepts and measures, explores the relations within the current broader literature on migration and entrepreneurship, and identifies several gaps that represent future research questions. We also introduce eight papers in a special section of this issue, which offer answers to critical gaps and questioning some taboos/stereotypes related entrepreneurial migrants. We conclude by outlining an agenda for engaging the academic community to extend research on entrepreneurial migrants from/in emerging economies. It is the perfect time to “make a difference” through our research, teaching, and interaction with multiple socioeconomic agents to constitute impacts that “endorse a real transformation” for supporting the migrants’ community.

     

Coordination in the El Farol Bar problem: The role of social preferences and social networks

In this paper, we continue the pursuit of the self-coordination mechanism as studied in the El Farol Bar problem. However, in addition to efficiency (the optimal use of the public facility), we are also interested in the distribution of the public resources among all agents. Hence, we consider variants of the El Farol Bar problem, to be distinguished from many early studies in which efficiency is the only concern. We ask whether self-coordinating solutions can exist in some variants of the El Farol Bar problem so that public resources can be optimally used with neither idle capacity nor congestion being incurred and, in the meantime, the resources can be well distributed among all agents. We consider this ideal situation an El Farol version of a “good society”. This paper shows the existence of a positive answer to this inquiry, but the variants involve two elements, which were largely left out in the conventional literature on the El Farol Bar problem. They are social networks and social preferences. We first show, through cellular automata, that social networks can contribute to the emergence of a “good society”. We then show that the addition of some inequity-averse agents can even guarantee the emergence of the “good society”.     

Monetary incentives and social ties in academic publications

Monetary incentives underlie academic publications, especially in countries where many researchers' incomes are performance-based. Evidence has documented that social ties improve the chances of publication in journals, whereas building and maintaining social ties require resources. We develop a simple model to investigate the consequences of monetary investment on the probability of publication through social ties. The results indicate that monetary incentive can stimulate researchers to make more efforts regarding publication. Through social ties, monetary investment in the process of academic publication distorts researchers' incentive. Monetary investment through social ties improves the probability of publication and then disables the signaling function of publication in terms of researchers’ abilities. Depending on the contribution of different types of researchers to society and the ability of the latter to differentiate the quality of publication in journals, the improvement in publication probability by monetary investment through social ties may improve or reduce the level of social welfare.     

南京市科技进步贡献率测算研究

科技进步贡献率对分析城市经济增长有重要意义。本文依据南京市1993年～2007年统计数据,以柯布-道格拉斯生产函数为基础,运用索洛余值法对南京市经济增长中的科技进步贡献率进行测算,根据测算结果分析出南京市科技贡献率对经济的实际影响并提供政策建议。