A theory of formal conceptual definitions: developing theory-building measurement instruments

This study develops the need for formal conceptual definitions (sometimes called nominal definitions) and how to develop better measurement instruments for theory-building. It develops the underlying theory for ‘good’ formal conceptual definitions by defining terms, demonstrating that formal conceptual definitions are needed for all theory-building empirical research, explains how and why ‘good’ formal conceptual definitions are used to develop properties and their measures, and last, it logically explains that good formal conceptual definitions are necessary conditions for construct validity (content validity, criterion validity, convergent validity, and discriminant validity) while statistical tests are sufficient conditions for validity. This theory development explains why formal conceptual definitions are necessary before any traditional statistical empirical validity tests are performed. This study suggests that any statistical validity tests are not meaningful if the concept is not formally defined.In short, the theory of formal conceptual definitions provides a structure to develop ‘good’ measures of the formal theory that leads to ‘good’ empirical theory-building.     

Some Basic Issues Related to Contextual Performance and Organizational Citizenship Behavior in Human Resource Management

This article examines some basic issues that might pose conceptual challenges in applying ideas related to contextual performance and organizational citizenship behavior to human resource management. It considers labeling issues and differences between the origins and definitions of the terms, contextual performance, and organizational citizenship behavior, and argues that the labeling issues are less important than careful definition and measurement of the behavioral dimensions that these terms embrace. It also considers the conceptual status of organizational citizenship behavior and contextual performance as latent constructs or aggregate constructs according to distinctions presented by Law, Wong, and Mobley. And finally, it explores questions related to consequences of behavioral patterns connoted by these terms for organizational effectiveness and individual motivation, job satisfaction, and commitment.     

International Comparisons of Public Sector Performance

Abstract

Measuring and comparing the overall performance of countries' public sectors requires agreement on definitions and objectives of government. I argue that such an agreement is about finding a consensus rather than about finding better definitions. Measuring government requires a number of leaps of faith, where certain definitions, assumptions and statistics are accepted as good enough for measurement and comparison. The political science and economic research community have a different tradition of dealing with such agreements and leaps of faith, and this is reflected in their approaches to measuring and comparing the performance of public sectors. The implications of these traditions are particularly visible in the usefulness of measurement and indicators for policy makers.     

Social influence in technology adoption: taking stock and moving forward

Social influence has been shown to profoundly affect human behavior in general and technology adoption in particular. Over time, multiple definitions and measures of social influence have been introduced to the field of technology adoption research, contributing to an increasingly fragmented landscape of constructs that challenges the conceptual integrity of the field. Consequently, this paper sets out to review how social influence has been conceptualized in technology adoption research. In so doing, this paper attempts to inform researchers’ understanding of the construct, reconcile its myriad conceptualizations, constructively challenge extant approaches, and provide impulses for future research. A systematic review of the salient literature uncovers that extant interpretations of social influence are (1) predominantly compliance-based and as such risk overlooking identification- and internalization-based effects; (2) primarily targeted at the individual level and non-social technologies, thereby precluding the impact of socially enriched environments; and (3) heavily reliant on survey-based and US/China-centric samples, which jeopardizes the generalizability and predictive validity of the findings. Building upon these insights, this paper develops an integrated perspective on social influence in technology adoption research that encourages scholars to pursue a multi-theoretical understanding of social influence at the interface of users, social referents, and technology.     

Intercoder reliability indices: disuse,misuse, and abuse

Although intercoder reliability has been considered crucial to the validity of a content study, the choice among them has been controversial. This study analyzed all the content studies published in the two major communication journals that reported intercoder reliability, aiming to find how scholars conduct intercoder reliability test. The results revealed that some intercoder reliability indices were misused persistently concerning the levels of measurement, the number of coders, and the means of reporting reliability over the past 30 years. Implications of misuse, disuse, and abuse were discussed, and suggestions regarding proper choice of indices in various situations were made at last.     

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.     

Studies on the Comparability of Consumer Price Indices

Comparability of statistical data between countries is a major objective for international statistical organisations such as EUROSTAT. The convergence criteria set down in the Maastricht Treaty explicitly require comparable consumer price indices in the European Union. We present an empirical analysis, largely based on simulations with Swedish and Finnish CPI data, of various potential sources of non-comparability, conceptual as well as technical ones.     

光散射式数字粉尘测试仪的标定及不确定度分析

传统的称重法是最可靠的检测粉尘浓度的方法,但由于其费时费力,近年来,便携式粉尘测试仪得到人们的青睐,其中光散射式数字粉尘测试仪以性能稳定、灵敏度高、测量方便等优势得到广泛应用,但测量结果是粉尘仪的相对浓度,所以,为保证测量结果既有称重法的可靠性,又有直测法的方便性,依据滤膜称重原理使用校准粒子对美国TSI生产的AM510进行校准,并进行测量结果的不确定度分析,既实现了粉尘仪的量值溯源,也提供了测量结果的可靠性保证。     

Rationality-in-Relations

A BSTRACT . If in a game with multiple proper coordination equilibria there is a single one that is best for all participants, it is rational for each participant to choose the strategy that has the best equilibrium as one of its possible outcomes. This seems so obvious that any plausible theory of rationality should be expected to be applicable to such situations. However, this is not true for the "orthodox" theory of rational choice, as Robert Sugden has convincingly shown. In this paper, I shall argue that this failure is due to an implicit individualistic understanding of intentionality . John R. Searle's concept of collective intentionality (as put forth in his Construction of Social Reality ) and his more recent theory of Rationality in Action provides important conceptual tools pertaining to a more comprehensive theory of rationality. The account I shall develop differs from Searle's own, as for reasons to be found in his overall project, Searle's departure from the orthodox view of rationality gets stuck half-way.     

Philosophical foundations of sociological measurement: a note on the three level model

Even a cursory perusal of the social science literature suffices to show the prevalence of dichotomous thinking. Many of these dichotomies deal with some aspect of the “conceptual versus empirical” distinction. This paper shows that while dichotomies predominate for some reason, the actual research process that they are designed to represent deals minimally with three separate and necessary levels. We term these the conceptual level (X), the empirical level (X′), and the operational or indicator level (X″). This minimal three level model is applied to an analysis of philosophical foundations of measurement, specifically the formulations of Northrop and Bridgman. It is shown that both of these formulations are essentially dichotomous, while the phenomena they deal with are trichotomous. For example, Northrop's “concepts by postulation” and “concepts by intuition” are purportedly separate levels connected by an epistemic correlation. Application of the three level model reveals that both are true concepts, and thus belong on the same level of analysis (X). Similarly, application of the three level model to Bridgman's formulation shows that both mental and physical concepts belong on the same level (X). Bridgman's formulation is valuable in pointing out that operations are not restricted to one level of analysis, and in fact we see them to be crucial on all three levels. The three level model is not a panacea, but does provide an efficacious framework for the difficult but important task of analyzing the philosophical underpinning of measurement.     

QUANTITATIVE ANALYSES OF MANAGEMENT SALARY DIFFERENTIALS

Abstract This paper reviews the practical value of a number of quantitative models of management pay structures at the level of the firm. The aim is to identify the practical, operational value of these models to salary administrators. Models developed in the last twenty years by Roberts (1956), Peason (1967), Simon (1957), Lydall (1959), Thorelli (1965) and Paterson (1972) are reviewed and their practical weaknesses highlighted. It is concluded that models of this nature are of considerable conceptual value in relating some of the economic and organizational factors involved in management pay. Most quantitative models appear to have mainly academic value. However, the paper demonstrates how an approach using a mixed Pearson and Paterson model can be applied in a practical fashion to yield useful salary administration guidelines. The Pearson model is based on a Pareto distribution of managerial salaries within the firm, while Paterson's model provides definitions of authority levels associated with management jobs. The combined Pearson/Paterson approach provides the administrator with a helpful framework which allows comparison of his firm's salary structure with those of companies in similar industries as well as measurement of changes within his salary structure over a selected time period.     

Development and validation of the Remote Working Benefits & Disadvantages scale

The changes that are constantly occurring in the labour sector have led organisations and companies to move towards digital transformation. This process was accelerated by the COVID-19 pandemic and  conducted to a massive recourse to the practice of remote working, which in this study is understood as the term for the way of performing work outside the usual workplace and with the support of ICT. Currently, there are no flexible scales in the literature that allow measuring the benefits and disadvantages of remote working with a single instrument. Thus, the distinction between the positive and negative consequences of working remotely, substantiated by a solid literature, provides a framework for a systematical understanding of the issue. The aim of the present study is to develop and validate a scale on remote working benefits and disadvantages (RW-B&D scale). For this end, a preliminary Exploratory Factor Analysis (EFA) with 304 participants, a tailored EFA with a sample of 301 workers and a Confirmatory Factor Analysis (CFA) with 677 workers were conducted. Participants were all Italian employees who worked remotely during the period of the COVID-19 health emergency. Data were collected between October 2020 and April 2021. The psychometric robustness of the model was assessed through bootstrap validation (5000 resamples), fit indices testing and measurement of factorial invariance. The statistical analyses demonstrated the bifactorial nature of the scale, supporting the research hypothesis. The model showed good fit indices, bootstrap validation reported statistically significant saturations, good reliability indices, and convergent and discriminant validity. Measurement invariance was tested for gender and organisational sector. The results suggested that the novel scale facilitates the quantitative measurement of the benefits and disadvantages associated with remote working in empirical terms. For this reason, it could be a streamlined and psychometrically valid instrument to identify the potential difficulties arising from remote working and, at the same time, the positive aspects that can be implemented to improve organisational well-being.

     

Statistical Scale Space Methods

The goal of statistical scale space analysis is to extract scale‐dependent features from noisy data. The data could be for example an observed time series or digital image in which case features in either different temporal or spatial scales would be sought. Since the 1990s, a number of statistical approaches to scale space analysis have been developed, most of them using smoothing to capture scales in the data, but other interpretations of scale have also been proposed. We review the various statistical scale space methods proposed and mention some of their applications.     

Role of line managers in human resource management: empirical evidence from India

Of late, the line management role has been reorganized in business organizations and they are now increasingly taking up responsibility for core HRM functions. Line managers' role in HRM has been recognized in academic research but it is likely impact on the effectiveness of HRM that has remained relatively under researched, especially in India. The focus of the study was, thus, to empirically examine the relationship between dimensions of line managers' role in HRM and effectiveness of HRM in the Indian context. Primary data were obtained from HR managers of top-ranking companies through a single cross-sectional survey based on a research instrument designed by the researcher. The instrument was tested for unidimensionality, reliability and validity. SEM capabilities of LISREL 8.50 were utilized to test the conceptual research model based on the hypothesized relationships. The findings provided mixed support for the conceptual model. The present research has implications for both academicians and practitioners. The study is expected to serve as a guide in understanding the role of line managers vis-a-vis HRM, a largely unexplored area in the Indian context.     

Statistical Integration Through Metadata Management

Faster and more versatile technology is fuelling user demand for statistical agencies to produce an ever wider range of outputs, and to ensure those outputs are consistent and mutually related to the greatest extent possible. Statistical integration is an approach for enhancing the information content of separate statistical collections conducted by an agency, and is necessary for consistency. It has two aspects-conceptual and physical-the former being a prerequisite for the latter. This paper focuses on methods for achieving statistical integration through better management of metadata. It draws on experiences at the Australian Bureau of Statistics in the development and use of a central repository (the "Information Warehouse") to manage data and metadata. It also makes reference to comparable initiatives at other national statistical agencies.
The main conclusions are as follows. First, a prototyping approach is required in developing new functionality to support statistical integration as it is not clear in advance what tools are needed. Second, metadata from separate collections cannot easily be rationalised until they have been loaded to a central repository and are visible alongside one another so their inconsistencies are evident. Third, to be effective, conceptual integration must be accompanied by physical integration. Fourth, there is great scope for partnerships and exchange of ideas between agencies. Finally, statistical integration must be built into the ongoing collection processes and viewed as a way of life.     

Making measurement errors and interpreting path coefficients: a practical perspective

The purpose of this analysis is to provide a practical approach to the assessment of reliability. In particular, we examine the impact of random measurement error upon the magnitude and interpretation of standardized regression coefficients (or path coefficients) and the specification of regression models. With the proper research the relationship between measured and true values can be inferred by using path coefficients. Such inferences allow assessments of the specification of statistical models. Several examples illustrate how researchers can be misled without knowledge of the impact of measurement error.     

Symposium Introduction

This symposium's focus is on connections that might be forged between leadership theory and practice, leadership development, and the theory and practice of design. Our intent in exploring the narratives of and literature about designers is to understand and appreciate how the design leadership crucible might forge more effective research approaches, generative pedagogical experience, and produce more effective leaders who can address adaptive problems. The guest editors and authors for the symposium are Elizabeth Johnston and Anthony Kortens. The symposium includes an introduction to the topic of design using current literature, incorporating a report on a series of conversations with two individuals who have enjoyed long and successful careers in design and leadership. These individuals, Michael Schonhofen and Ben Shaw, were contributing partners who shared their experiences as designers and leaders, as well as tirelessly reviewed the symposium documents and offered insights, interpretations, and suggestions.     

Urban Citizenship,the Right to the City and Politics of Disability in Istanbul

Since the late 1990s, the ‘urban citizenship’ literature has accentuated the burgeoning potential of the city as host to more democratic interpretations of citizenship. A more recent literature highlighted the ‘local trap’ in such assumptions, arguing that the local cannot exist outside of neoliberalization. This article examines some of the recent institutional transformations in Istanbul's local government and seeks to understand where these might be situated in this discussion. Three institutions dealing with disability are scrutinized with regard to their power dynamics, discourses and practices. The argument is that, although superficially such developments seem to represent some of the tendencies highlighted by the urban citizenship literature (in terms of their scale, timing and appeal to a group previously excluded from modern citizenship), deeper analysis shows that these often promote charity‐ rather than rights‐based approaches. This is because the push factors in the emergence of these institutions are not the urban struggles on the part of the disability community, but rather the ruling party's populism, the impact of supranational agencies and the demands of non‐disabled residents at district level. Each of the three institutions examined is shaped primarily by one factor, leading to differing degrees of charity‐ and rights‐based practices. Arguments concerning the prospects of more democratic interpretations of citizenship at local level need to consider experiences in diverse settings.     

Forecasting high resolution electricity demand data with additive models including smooth and jagged components

Short-Term Load Forecasting (STLF) is a fundamental instrument in the efficient operational management and planning of electric utilities. Emerging smart grid technologies pose new challenges and opportunities. Although load forecasting at the aggregate level has been extensively studied, electrical load forecasting at fine-grained geographical scales of households is more challenging. Among existing approaches, semi-parametric generalized additive models (GAM) have been increasingly popular due to their accuracy, flexibility, and interpretability. Their applicability is justified when forecasting is addressed at higher levels of aggregation, since the aggregated load pattern contains relatively smooth additive components. High resolution data are highly volatile, forecasting the average load using GAM models with smooth components does not provide meaningful information about the future demand. Instead, we need to incorporate irregular and volatile effects to enhance the forecast accuracy. We focus on the analysis of such hybrid additive models applied on smart meters data and show that it leads to improvement of the forecasting performances of classical additive models at low aggregation levels.