The entropies: Some roots of ambiguity

Entropy concepts have developed in four general contexts—thermodynamics, communication theory, statistical information theory and social and life sciences. These concepts have five distinct mathematical forms. Ambiguity and complexity in utilization of the concept has been heightened by this multi-faceted heritage. Effective utilization may be strengthened by a sharper articulation of entropy through combinations of literal, mathematical and graphical modes of expression. Geography and planning as user disciplines have important responsibilities in enhancing cross-disciplinary communication of this important adisciplinary concept. Implications of these arguments for the social sciences include the need for caution in drawing social analogies from the ambiguous entropy concepts of statistical mechanics; and an indication of the potential benefits of social science models based on the unambiguous entropic constructs of statistical information theory.     

Fuzzy-set method in comparative social policy: a critical introduction and review of the applications of the fuzzy-set method

This article critiques the Fuzzy-set Qualitative Analysis (fs/QCA) methodology by examining its applicability in three studies in the field of comparative social policy. In each of these three test cases, I focus on the validity of fuzzy-set’s claimed function—its ability to combine theoretic discourse and evidence analysis. All three studies investigate welfare state reform in the late twentieth century and apply fs/QCA: (1) “Welfare Reform in the Nordic Countries in the 1990s: Using Fuzzy-set Theory to Assess Conformity to Ideal Types,” (2) “States of Welfare or States of Workfare? Welfare State Restructuring in 16 Capitalist Democracies, 1985–2002,” and (3) “The Diversity and Causality of Welfare State Reforms Explored with Fuzzy-sets.” This article begins by discussing the ontology and epistemology of comparative social policy. The fuzzy set logic and set theoretic nature of social science theory is then discussed to align the ontology with fuzzy set methodology. Next, a more detailed introduction of fuzzy-set method (fs/QCA) is followed. This study suggests that fs/QCA is a unique and useful method for comparative social policy. It advances quantitative analysis by exploring cases configurationally and also advances the qualitative analysis by applying the fuzzy set logic and the principle of calibration.     

Social Change: Measurement and Theory*

Societal change, which takes a variety of directions and forms and in no way can be assimilated or reduced to a single dimension, is often accompanied by a perception of insufficient understanding and lack of control. There is a frustrated need for mastering complexity and instability, separating the voluntary from the involuntary, the intended from the unintended, opportunities from risks, getting to the real causes and dominating the uncertain implications of social change. Social change catches us unprepared and confused. In this context statistics are generally considered a fundamental instrument of knowledge, but also part of the problem! In the public debate and in the specialized literature, the ability to measure social phenomena through current statistics and indicators is increasingly questioned. Data-it is claimed-are lacking, particularly longitudinal data; their quality (accuracy, relevance, timeliness, comparability, etc.) should be improved; indicators do not provide early warning signals, policy performance evaluation, and a precise indication of outcomes. Statistics cannot be used as a reliable and timely basis for decision making by individuals, organizations, governments, and for understanding these decisions. In some cases, statistics have been accused of giving a misleading and false picture of reality: do we measure the real extent of social exclusion and unemployment? Do we fully capture the quality of life and the degradation of the environment? Mismeasurement has been deemed by some commentators as being responsible for the wrong focus in inflation and stabilization policies, science and technology, unemployment and poverty. The productivity paradox, the informal economy, failure to measure welfare and the quality of urban life are instances where statistics do not seem to provide complete and satisfactory answers to the demand for information and knowledge. Our paper illustrates how, quite independently of measurement techniques and data production processes, the inadequacy of the conceptual framework may explain mismeasurement in relation to complex (multidimensional) and dynamic social phenomena. It is then to social theories, explanations and interpretations that statisticians need to turn, in order to come to grips with the new challenges in social measurement. We will develop this thesis looking at a few cases where measurement issues can be connected to both theoretical and empirical difficulties. The statistical gap which reveals itself in the mismeasurement or difficult measurement of social phenomena is closely interconnected with the social science gap. Only close collaboration between statisticians and social scientists can bring about continuous advancement in social science and quality improvement in social statistics.     

Operationalization,a superfluous concept

This paper discusses a number of issues in the methodology of social and behavioral sciences which concern how concepts are defined and related to observations, how theories are constructed, and how we proceed in actual research. Examples are mainly taken from experimental psychology, and from social psychology, but the problems and answers apply to the whole of behavioral and social sciences. These issues are related to philosophy of science. They are, however, presented from the point of view of a researcher who asks himself how to proceed in actual research, and who is critical about the present status of social and behavioral science. The main point is a pledge for a renewed empiricism. This is close to what can be called logical empiricism but should not be identified with any particular-ism. Some issues raised by critics of logical empiricism are addressed in the final section. The first problem deals with how to clarify concepts in behavioral and social science. This will show an unresolvable circularity in operationalization of theoretical constructs. The position and role of measurement is discussed in relation to the objectives of behavioral and social research. Subsequently, it is pointed out that a clear distinction between empirical concepts and theoretical constructs solves many, if not all of the problems of defining and clarifying concepts, thereby obviating the need for a so-called operationalization. It should, however, be very clear from the beginning that we cannot do without operational definitions of theoretical concepts, and that to some extent we must return to the original spirit of operationism, although in a manner which is different from current practice. An important element of the advocated approach is the definition of the empirical domain of a theory in terms of observational categories. Guttman's facet design can be a useful tool to define domains, especially for non-experimental research.     

Social Ecological Economics: Understanding the Past to See the Future

The attempt to provide insight into the interactions between the economy and the environment has been an on‐going struggle for many decades. The rise of Ecological Economics can be seen as a positive step towards integrating social and natural science understanding by a movement that aims to go beyond the confines of mainstream economics towards a progressive political economy of the environment. However, this vision has not been shared by all those who have associated themselves with Ecological Economics and there has been conflict. An historical analysis is presented that shows the role of mainstream theory in delimiting the field of environmental research. The argument is put forward that rather than employing a purely mechanistic objective empirical methodology there is a need for an integrating interdisciplinarity heterodox economic approach. In order to distinguish this approach—from the more mainstream multidisciplinary linking of unreconstituted ecological and economic models—the name Social Ecological Economics is put forward as expressing the essential socio‐economic character of the needed work ahead.     

Interdisciplinary social science: a methodological analysis

Since the 1930's, interdisciplinarity has been advocated in the social sciences for the purpose of achieving more comprehensive explanations of observable social phenomena. However, the realization of this promising perspective has been rather poor. This article argues that two main causes of the failure to create interdisciplinary social science can be distinguished, i.e., methodological and theoretical problems. Methodological problems stem either from taking a reductionist approach towards interdisciplinarity, or by mistaking measurement issues for theoretical topics. Theoretical problems result from the poor state and rate of theory formation within psychology. The implications of these problems are that the validity and reliability of explanations of macro social phenomena, which are provided by disciplines such as sociology and macro economics, are seriously at stake.     

Leadership as an Ideograph: A Rhetorical Analysis of Military Leadership Training Material

The current rhetorical study used McGee's theory of ideographs to identify how cultural politics influence efforts to portray “leadership” in a military setting. Such an approach seeks to better address some of the enigmas that have complicated the understanding of military leadership—and leadership in general—for decades. McGee's theory emphasizes that language reflects political as well as referential qualities and, in some instances, these attributes come into conflict. Acknowledging this reality in an applied setting can help address ambiguous issues that escape the net of prevailing social‐science approaches to leadership inquiry. The rhetorical analysis, which examines U.S. Air Force leadership training material, documents the manner in which ideographic portrayals of leadership were pervasive in each training program, and it considers practical implications of such a situation. Most notably, the analysis provides an explanation of how ideographic portrayals of leadership implicitly emphasize cultural indoctrination over promoting social influence skills. Such an orientation fortifies the military hierarchy and perpetuates romantic views of the military profession, but it also blurs key distinctions between social control and social influence. It is suggested that because ideographs reflect vital cultural motives, associated problems are inherently difficult to remedy.     

Why Distinguish Between Statistics and Mathematical Statistics–The Case of Swedish Academia

A separation between the academic subjects statistics and mathematical statistics has existed in Sweden almost as long as there have been statistics professors. The same distinction has not been maintained in other countries. Why has it been kept for so long in Sweden, and what consequences may it have had? In May 2015, it was 100 years since Mathematical Statistics was formally established as an academic discipline at a Swedish university where Statistics had existed since the turn of the century. We give an account of the debate in Lund and elsewhere about this division during the first decades after 1900 and present two of its leading personalities. The Lund University astronomer (and mathematical statistician) C. V. L. Charlier was a leading proponent for a position in mathematical statistics at the university. Charlier's adversary in the debate was Pontus Fahlbeck, professor in political science and statistics, who reserved the word statistics for ‘statistics as a social science’. Charlier not only secured the first academic position in Sweden in mathematical statistics for his former PhD student Sven Wicksell but also demonstrated that a mathematical statistician can be influential in matters of state, finance as well as in different natural sciences. Fahlbeck saw mathematical statistics as a set of tools that sometimes could be useful in his brand of statistics. After a summary of the organisational, educational and scientific growth of the statistical sciences in Sweden that has taken place during the last 50 years, we discuss what effects the Charlier–Fahlbeck divergence might have had on this development.     

The use of axiomatic fuzzy set theory in AHP and TOPSIS methodology to determine strategies priorities by SWOT analysis

Strengths, weaknesses, opportunities and threats (SWOT) matrix is one of the most used tools for strategic planning, specially in the stage of extracting strategies. While the use of SWOT analysis is quite common and popular, it still continuous to have certain structural problems such that: the lack of considering uncertain and boolean (two sided) factors, lack of prioritization of the factors and too many extractable strategies. In this paper, we deal with the analytic hierarchy process (AHP) to find weights of SWOT groups and weights of sub-factors within each groups; and we make use of the technique for order preference by similarity to ideal solution (TOPSIS) methodology to determine strategies priority. In addition, in order to deal with uncertainty and vagueness, we incorporate axiomatic fuzzy set (AFS) theory instead of traditional fuzzy set theory. AHP and TOPSIS are applied to the light of AFS theory. The advantages of dealing with AFS theory in the proposed approach are that: it can directly be applied to the data, the features of the data-sets can be mixed; however, the traditional fuzzy set theory deals with fuzzy numbers and it’s clear that different fuzzy numbers will lead to different results; hence the inconsistency of previous methodologies, described in the literature, copes with the methodology proposed in this paper.     

Shrinking cities: urban challenges of globalization

Urban shrinkage is not a new phenomenon. It has been documented in a large literature analyzing the social and economic issues that have led to population flight, resulting, in the worse cases, in the eventual abandonment of blocks of housing and neighbourhoods. Analysis of urban shrinkage should take into account the new realization that this phenomenon is now global and multidimensional — but also little understood in all its manifestations. Thus, as the world's population increasingly becomes urban, orthodox views of urban decline need redefinition. The symposium includes articles from 10 urban analysts working on 30 cities around the globe. These analysts belong to the Shrinking Cities International Research Network (SCIRN), whose collaborative work aims to understand different types of city shrinkage and the role that different approaches, policies and strategies have played in the regeneration of these cities. In this way the symposium will inform both a rich diversity of analytical perspectives and country-based studies of the challenges faced by shrinking cities. It will also disseminate SCIRN's research results from the last 3 years.     

STATISTICS IN THE SOCIAL AND BEHAVIORAL SCIENCES

This survey paper gives an impression of the main ways in which statistics is used in disciplines such as sociology and psychology. After an introductory section 1 the negative image of social science research is discussed in section 2. Section 3 is devoted to the enormous influence of modern computing facilities. Measurement of human behaviour has its specific problems (section 4). The use of linear and log–linear models is the topic of section 5. Latent variables are a basic concept for social and behavioral scientists, both in some linear models (section 6) and in item response theory (section 7). In the next section multidimensional and optimal scaling techniques are mentioned, and a selection of other topics is the content of section 9. Some general remarks on the generalizability claim of statistical methods constitute the final section. Because of space limitations and priority considerations, the author has decided to write a paper about topics and not about individual research contributions. For this reason there is no list of references (it would take several pages) and no painful split of all Dutch authors into those mentioned and those omitted. In general the Dutch research community has made quite a few major contributions to the area discussed in this paper.     

FMCG分销渠道风险综合评估研究

FMCG市场竞争激烈,分销渠道种类多而复杂,渠道中存在着各种各样的风险。为了最大限度地减少风险对营销渠道和企业的损害,需要一套完整的风险评价体系来评估风险。论文结合模糊数学的理论知识,构建了FMCG分销渠道风险评价指标体系,采用问卷调查法,以武汉城市圈饮料行业为例,运用层次分析法和模糊综合评价法对渠道风险进行综合评估。     

Ranking of sectors based on fuzzy importance measure

The changing nature of policy variables specific to any planned developmental programme often leads to conflicting decisional problems regarding the identification of thrust areas. Hence the inherent requirement is for a composite index which eases out such ambiguous choice issues. The present paper introduces the measure of sectoral importance which is capable of encompassing different variables with their associated weights and ranks sectors in an economy based on such a measure. However, the term importance suggests the qualitativeness and subjectivity involved in defining such a concept and thus establishes the need for the concepts of fuzzy mathematics. The theory of fuzzy subsets is capable of dealing with qualitative variables within a quantitative framework. The sectoral importance measures derived from the sectoral output linkages, employment multipliers and value added multipliers, have been represented as fuzzy subsets, or to be precise, as fuzzy numbers. A comparison of these numbers through the binary approach of determination of the measure of relative strength provides the basis for the ranking of sectors. The novelty of the approach lies in its simplicity and flexibility in treating qualitative factors which characterise most decision support socio economic planning problems. The validity of the exercise has been tested by applying it to the economy of West Bengal, a State of India.     

Hierarchical integration in production planning: Theory and practice

This paper discusses the issue of integrating various decision levels in hierarchical production planning systems. First the theory is briefly reviewed and then two case studies are presented. It is argued that it is not sufficient to have a good decision model at every level of the decision hierarchy. The different models should be carefully integrated. The potential problems resulting from a lack of integration are discussed. These problems are then illustrated in two case studies in order to be able to focus on actual managerial issues. It is shown how different decision levels supported by decision models were integrated in these two applications. Two important features are the crucial role of crossfunctional managerial committees in the integration process and the introduction of slack to avoid disaggregation problems.We do not claim to be exhaustive in presenting the problems related to integration nor do we claim that the solutions to the cases are the best possible ones. We do, however, hope that this paper motivates production managers to take a serious look at their hierarchical planning procedures.     

浅议统计学教师在社会实践中的重要意义

对经济类人才的培养离不开统计教育,更离不开具有高素质的又有超强实践能力的教师队伍。针对目前统计学的师资状况存在的问题,试图对加强统计教师的社会实践能力提出浅薄的建议,盼望统计教师加强社会实践活动,做到理论与实践的完美结合,力争把统计教学工作做得更好。     

The Political Economy of Low Inflation

What are the politics of inflation? This question is usually raised solely when inflation rates are high. All levels of inflation, however, high and low, are the outcome of political conflicts. But no current approach to the study of inflation — sociological, neoclassical, modern political economy — adequately captures the full range of political issues at stake, and this leads to problems for both theory and policy. This paper critiques the existing perspectives on inflation and then focuses on three theoretical issues raised by those critiques: the economic costs of inflation; the concept of monetary neutrality from economic and political perspectives; and the importance of disaggregating economic growth statistics. Finally, the paper introduces and explores a contending approach to the analysis of the political economy of inflation: a ‘micro‐politics’ perspective. This approach is the only one to address the politics of low inflation, which is of great significance for contemporary political economy.     

Theories from the Lab: How Research on Science Commercialization can Contribute to Management Studies

Universities and research centres have long been used to study management issues. A growing body of research has focused on how science can be effectively commercialized, emphasizing technology commercialization activities, university–industry collaborations, and academic entrepreneurship. While much of this work has documented empirical relationships, our aim in this introductory article of the special issue is to show how research on science commercialization may yield conceptual contributions to the field of management. Hence, we first discuss the importance of context for theory development. We then review how the science commercialization context has been used for theory development, identifying two facets used to conceptualize science commercialization (i.e., managing the transition between institutional contexts, and the multiple goals and impacts of actors engaging in science commercialization). This forms the basis for discussing what makes this context suited for theory development in general management and for outlining a future research agenda. We conclude by summarizing the papers in the special issue.     

Risk‐Utility Paradigms for Statistical Disclosure Limitation: How to Think,But Not How to Act

Risk‐utility formulations for problems of statistical disclosure limitation are now common. We argue that these approaches are powerful guides to official statistics agencies in regard to how to think about disclosure limitation problems, but that they fall short in essential ways from providing a sound basis for acting upon the problems. We illustrate this position in three specific contexts—transparency, tabular data and survey weights, with shorter consideration of two key emerging issues—longitudinal data and the use of administrative data to augment surveys.     

A conceptual framework for tackling knowable unknown unknowns in project management

Understanding and dealing with the unknown is a major challenge in project management. An extensive body of knowledge—theory and technique—exists on the “known unknowns,” i.e., uncertainties which can be described probabilistically and addressed through the conventional techniques of risk management. Although some recent studies have addressed projects where the existence of unknown unknowns (unk unks) is readily apparent or may be assumed given the type of project—e.g., new product development or new process implementation—very little work has been reported with respect to projects in general on how a project manager might assess its vulnerability to unk unks. In this paper, we present a conceptual framework to deal with (i.e., recognize and reduce) knowable unk unks in project management. The framework is supported by insights from a variety of theories, case analyses, and experiences. In this framework, we first present a model of the key factors—relating to both project design and behavioral issues—that increase the likelihood of unk unks and a set of propositions linking these factors to unk unks. We then present a set of design and behavioral approaches that project managers could adopt to reduce knowable unk unks. Our framework fills a gap in the project management literature and makes a significant practical contribution: it helps project managers diagnose a project to recognize and reduce the likelihood of unk unks and thus deal more effectively with the otherwise unrecognized risks and opportunities.     

Governance, Democracy and Poverty Reduction: Lessons Drawn from Household Surveys in Sub-Saharan Africa and Latin America

Public statistics face quite a challenge when it comes to measuring new dimensions of development (institutions, governance, and social and political participation). To take up this challenge, modules on Governance, Democracy and Multiple Dimensions of Poverty have been appended to household surveys by National Statistics Institutes in twelve African and Latin American developing countries. This paper presents the issues addressed and the methodological lessons learnt along with a selection of findings to illustrate this innovative approach and demonstrate its analytic potential. We investigate, for instance, the population's support for democratic principles, the respect for civil and political rights and the trust in the political class; the ‘need for the State’, particularly of the poorest; the extent of petty corruption; the reliability of expert surveys on governance; the perception of decentralization policies at local level; the level and vitality of social and political participation, etc. The conclusive appraisal made opens up prospects for the national statistical information systems in the developing countries. The measurement and tracking of this new set of objective and subjective public policy monitoring indicators would benefit from being made systematic.