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Book part
Publication date: 6 September 2021

Rachel S. Rauvola, Cort W. Rudolph and Hannes Zacher

In this chapter, the authors consider the role of time for research in occupational stress and well-being. First, temporal issues in studying occupational health…

Abstract

In this chapter, the authors consider the role of time for research in occupational stress and well-being. First, temporal issues in studying occupational health longitudinally, focusing in particular on the role of time lags and their implications for observed results (e.g., effect detectability), analyses (e.g., handling unequal durations between measurement occasions), and interpretation (e.g., result generalizability, theoretical revision) were discussed. Then, time-based assumptions when modeling lagged effects in occupational health research, providing a focused review of how research has handled (or ignored) these assumptions in the past, and the relative benefits and drawbacks of these approaches were discussed. Finally, recommendations for readers, an accessible tutorial (including example data and code), and discussion of a new structural equation modeling technique, continuous time structural equation modeling, that can “handle” time in longitudinal studies of occupational health were provided.

Details

Examining and Exploring the Shifting Nature of Occupational Stress and Well-Being
Type: Book
ISBN: 978-1-80117-422-0

Keywords

Article
Publication date: 11 April 2016

Tobias Feldhoff, Falk Radisch and Linda Marie Bischof

The purpose of this paper is to focus on challenges faced by longitudinal quantitative analyses of school improvement processes and offers a systematic literature review…

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Abstract

Purpose

The purpose of this paper is to focus on challenges faced by longitudinal quantitative analyses of school improvement processes and offers a systematic literature review of current papers that use longitudinal analyses. In this context, the authors assessed designs and methods that are used to analyze the relation between school improvement processes and student outcomes. Based on this the authors point out to what extent the papers consider different aspects of the complex nature of school improvement (e.g. multilevel structure, indirect and nonlinear effects, reciprocity). The choice of study designs and methods of analysis substantially determines which aspects of this complexity are taken into account.

Design/methodology/approach

The authors searched in four international high-impact journals and in ERIC for articles reporting longitudinal school improvement studies. The database of the review consisted of a total of 428 journal articles. In total, 13 of the 428 papers met the selection criteria and were analyzed in detail.

Findings

The analyzed papers use a wide range of designs and methodological approaches. They support the assumption that sophisticated quantitative longitudinal designs and methods can be applied effectively in school improvement research. However, considering the complexity of school improvement is accompanied by high demands on designs and methods. Due to this none of the papers met the standards applied in this review completely.

Research limitations/implications

In particular, further research is needed to consider a long period of observation, reciprocal indirect and nonlinear processes in a multilevel structure. Moreover, research is required for a better and unambiguous theoretical foundation and empirical validation of the number of and intervals between measurement points.

Practical implications

If more consideration is given to the complex nature of school improvement in future studies, the broader knowledge base will allow a better understanding of the dynamic relation of school improvement and student learning. It would thus be possible to make more appropriate recommendations for the support of school improvement practice.

Originality/value

The original contribution of the paper is to show which aspects of the complexity of school improvement processes – and to what extent – are currently addressed in designs and methods of analysis applied in quantitative longitudinal studies that investigate the relation between schools’ capacity to managing change and student outcomes. Additionally the authors aim at deriving need for further research and giving guidelines how designs and methods in further studies can reflect the complexity appropriately. It is highly important to consider all aspects of this complexity to describe and understand the dynamic relation of school improvement processes and student outcomes.

Details

Journal of Educational Administration, vol. 54 no. 2
Type: Research Article
ISSN: 0957-8234

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Book part
Publication date: 1 August 2004

Henrich R. Greve and Eskil Goldeng

Longitudinal regression analysis is conducted to clarify causal relations and control for unwanted influences from actor heterogeneity and state dependence on…

Abstract

Longitudinal regression analysis is conducted to clarify causal relations and control for unwanted influences from actor heterogeneity and state dependence on theoretically important coefficient estimates. Because strategic management contains theory on how firms differ and how firm actions are influenced by their current strategic position and recent experiences, consistency of theory and methodology often requires use of longitudinal methods. We describe the theoretical motivation for longitudinal methods and outline some common methods. Based on a survey of recent articles in strategic management, we argue that longitudinal methods are now used more frequently than before, but the use is still inconsistent and insufficiently justified by theoretical or empirical considerations. In particular, strategic management researchers should use dynamic models more often, and should test for the presence of actor effects, autocorrelation, and heteroscedasticity before applying corrections.

Details

Research Methodology in Strategy and Management
Type: Book
ISBN: 978-1-84950-235-1

Abstract

Economists and sociologists have proposed arguments for why there can exist wage penalties for work involving helping and caring for others, penalties borne disproportionately by women. Evidence on wage penalties is neither abundant nor compelling. We examine wage differentials associated with caring jobs using multiple years of Current Population Survey (CPS) earnings files matched to O*NET job descriptors that provide continuous measures of “assisting & caring” and “concern” for others across all occupations. This approach differs from prior studies that assume occupations either do or do not require a high level of caring. Cross-section and longitudinal analyses are used to examine wage differences associated with the level of caring, conditioned on worker, location, and job attributes. Wage level estimates suggest substantive caring penalties, particularly among men. Longitudinal estimates based on wage changes among job switchers indicate smaller wage penalties, our preferred estimate being a 2% wage penalty resulting from a one standard deviation increase in our caring index. We find little difference in caring wage gaps across the earnings distribution. Measuring mean levels of caring across the U.S. labor market over nearly thirty years, we find a steady upward trend, but overall changes are small and there is no evidence of convergence between women and men.

Details

Gender Convergence in the Labor Market
Type: Book
ISBN: 978-1-78441-456-6

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Article
Publication date: 2 December 2019

Torsten Doering, Nallan C. Suresh and Dennis Krumwiede

Longitudinal investigations are often suggested but rarely used in operations and supply chain management (OSCM), mainly due to the difficulty of obtaining data. There is…

Abstract

Purpose

Longitudinal investigations are often suggested but rarely used in operations and supply chain management (OSCM), mainly due to the difficulty of obtaining data. There is a silver lining in the form of existing large-scale and planned repeated cross-sectional (RCS) data sets, an approach commonly used in sociology and political sciences. This study aims to review all relevant RCS surveys with a focus on OSCM, as well as data and methods to motivate longitudinal research and to study trends at the plant, industry and geographic levels.

Design/methodology/approach

A comparison of RCS, panel and hybrid surveys is presented. Existing RCS data sets in the OSCM discipline and their features are discussed. In total, 30 years of Global Manufacturing Research Group data are used to explore the applicability of analytical methods at the plant and aggregate level and in the form of multilevel modeling.

Findings

RCS analysis is a viable alternative to overcome the confines associated with panel data. The structure of the existing data sets restricts quantitative analysis due to survey and sampling issues. Opportunities surrounding RCS analysis are illustrated, and survey design recommendations are provided.

Practical implications

The longitudinal aspect of RCS surveys can answer new and untested research questions through repeated random sampling in focused topic areas. Planned RCS surveys can benefit from the provided recommendations.

Originality/value

RCS research designs are generally overlooked in OSCM. This study provides an analysis of RCS data sets and future survey recommendations.

Book part
Publication date: 31 July 2014

David S. DeGeest and Ernest H. O’Boyle

To review and address current approaches and limitations to modeling change over time in social entrepreneurship research.

Abstract

Purpose

To review and address current approaches and limitations to modeling change over time in social entrepreneurship research.

Methodology

The article provides a narrative review of different practices used to assess change over time. It also shows how different research questions require different methodologies for assessing changes over time. Finally, it presents worked examples for modeling these changes.

Findings

Our review suggests that there is a lack of research in social entrepreneurship that takes into account the many different considerations for addressing how time influences outcomes.

Originality/value

This chapter introduces an analytic technique to social entrepreneurship that effectively models changes in predictors and outcomes even when data are non-normal or nested across time or levels of analysis.

Details

Social Entrepreneurship and Research Methods
Type: Book
ISBN: 978-1-78441-141-1

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Article
Publication date: 17 October 2016

Ellen Roemer

The purpose of this paper is to provide a systematic overview with guidelines how to use partial least squares (PLS) path modeling in longitudinal studies. Practical…

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Abstract

Purpose

The purpose of this paper is to provide a systematic overview with guidelines how to use partial least squares (PLS) path modeling in longitudinal studies. Practical examples from a study of the acceptance of battery electric vehicles (BEVs) in corporate fleets are used for demonstration purposes.

Design/methodology/approach

In this study, data at three points in time were collected: before the initial use of a BEV, after three and after six months of extensive usage of BEVs.

Findings

Three different models are identified depending on the research objective and on the data basis. Multigroup analyses are suggested to test the difference between the path coefficients of latent variables at different points in time. Limitations for the use of repeated cross-sectional data have to be observed.

Originality/value

Academics and practitioners will benefit from this paper by receiving an overview of the different PLS path models in longitudinal studies. A decision-tree enables them to make a choice regarding the most appropriate model and suggests a sequence of complementary analyses. So far, there is a lack of a tutorial type paper delivering such guidance.

Details

Industrial Management & Data Systems, vol. 116 no. 9
Type: Research Article
ISSN: 0263-5577

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Book part
Publication date: 28 August 2007

Michael C. Sturman

This article reviews the extensive history of dynamic performance research, with the goal of providing a clear picture of where the field has been, where it is now, and…

Abstract

This article reviews the extensive history of dynamic performance research, with the goal of providing a clear picture of where the field has been, where it is now, and where it needs to go. Past research has established that job performance does indeed change, but the implications of this dynamism and the predictability of performance trends remain unresolved. Theories are available to help explain dynamic performance, and although far from providing an unambiguous understanding of the phenomenon, they offer direction for future theoretical development. Dynamic performance research does suffer from a number of methodological difficulties, but new techniques have emerged that present even more opportunities to advance knowledge in this area. From this review, I propose research questions to bridge the theoretical and methodological gaps of this area. Answering these questions can advance both research involving job performance prediction and our understanding of the effects of human resource interventions.

Details

Research in Personnel and Human Resources Management
Type: Book
ISBN: 978-0-7623-1432-4

Article
Publication date: 9 March 2010

Juan Ramón Oreja‐Rodríguez and Vanessa Yanes‐Estévez

This paper aims to propose a method for the longitudinal analysis of the environment considering both firms' and environmental variables.

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Abstract

Purpose

This paper aims to propose a method for the longitudinal analysis of the environment considering both firms' and environmental variables.

Design/methodology/approach

The study is based on a sample of firms in Canary Islands (Spain) for 2000 and 2003. Managerial perceptions are considered, based on the cognitive perspective. The measurements used are the result of applying the Rasch model and the rack and stack analyses. This approach provides information about how dynamic the firms perceive the environment and also about how the items are perceived.

Findings

The results show that most firms perceive that dynamism increased between 2000 and 2003. From the perspective of the environmental variables, the most dynamic are perceived to be competition, demand, consumer motivation and technological resources.

Originality/value

This paper proposes a longitudinal method for environmental scanning that include both firms' and environmental variables. It considers managerial perceptions, that is the information entering the decision making process. It is one of the first papers to study environmental scanning with Rasch model and one of the few about longitudinal environmental analyses. It opens a field of research and applications of the Rasch model in the management literature.

Details

Management Decision, vol. 48 no. 2
Type: Research Article
ISSN: 0025-1747

Keywords

Open Access
Article
Publication date: 27 December 2021

Nengchao Lyu, Yugang Wang, Chaozhong Wu, Lingfeng Peng and Alieu Freddie Thomas

An individual’s driving style significantly affects overall traffic safety. However, driving style is difficult to identify due to temporal and spatial differences and…

Abstract

Purpose

An individual’s driving style significantly affects overall traffic safety. However, driving style is difficult to identify due to temporal and spatial differences and scene heterogeneity of driving behavior data. As such, the study of real-time driving-style identification methods is of great significance for formulating personalized driving strategies, improving traffic safety and reducing fuel consumption. This study aims to establish a driving style recognition framework based on longitudinal driving operation conditions (DOCs) using a machine learning model and natural driving data collected by a vehicle equipped with an advanced driving assistance system (ADAS).

Design/methodology/approach

Specifically, a driving style recognition framework based on longitudinal DOCs was established. To train the model, a real-world driving experiment was conducted. First, the driving styles of 44 drivers were preliminarily identified through natural driving data and video data; drivers were categorized through a subjective evaluation as conservative, moderate or aggressive. Then, based on the ADAS driving data, a criterion for extracting longitudinal DOCs was developed. Third, taking the ADAS data from 47 Kms of the two test expressways as the research object, six DOCs were calibrated and the characteristic data sets of the different DOCs were extracted and constructed. Finally, four machine learning classification (MLC) models were used to classify and predict driving style based on the natural driving data.

Findings

The results showed that six longitudinal DOCs were calibrated according to the proposed calibration criterion. Cautious drivers undertook the largest proportion of the free cruise condition (FCC), while aggressive drivers primarily undertook the FCC, following steady condition and relative approximation condition. Compared with cautious and moderate drivers, aggressive drivers adopted a smaller time headway (THW) and distance headway (DHW). THW, time-to-collision (TTC) and DHW showed highly significant differences in driving style identification, while longitudinal acceleration (LA) showed no significant difference in driving style identification. Speed and TTC showed no significant difference between moderate and aggressive drivers. In consideration of the cross-validation results and model prediction results, the overall hierarchical prediction performance ranking of the four studied machine learning models under the current sample data set was extreme gradient boosting > multi-layer perceptron > logistic regression > support vector machine.

Originality/value

The contribution of this research is to propose a criterion and solution for using longitudinal driving behavior data to label longitudinal DOCs and rapidly identify driving styles based on those DOCs and MLC models. This study provides a reference for real-time online driving style identification in vehicles equipped with onboard data acquisition equipment, such as ADAS.

Details

Journal of Intelligent and Connected Vehicles, vol. 5 no. 1
Type: Research Article
ISSN: 2399-9802

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