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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.

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.

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.

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.

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

The authors propose a framework to estimate the probability of being poor in a dynamic setting based on a large information set that includes individual characteristics and macro-economic variables. The joint inclusion of personal characteristics along with contextual factors allows separation of idiosyncratic shocks from aggregate shocks affecting poverty. The authors combine data from different cross-sectional surveys and fit a dynamic logistic hierarchical model within a Bayesian framework using standard Markov chain Monte Carlo techniques. The authors’ approach is exemplified by estimating household poverty status in Kyrgyz Republic as a function of time, regions, country, regional level variables and household level socio-demographic characteristics.

This study aims to investigate patterns in adolescent gun access and household gun storage in 2021 and 2022.

Data were collected from two cross-sectional surveys of Pennsylvania parents with a teenage child at home.

The results indicated that about 20% of gun owners in each survey stored their guns loaded; a similar percentage stored their guns unlocked. Very few gun owners reported that their children could access their guns without adult supervision. This study found no change in gun storage practices between 2021 and 2022, but higher rates of gun ownership in 2022. The factors associated with gun storage behaviors did change between the two time points. COVID-related uncertainties and transitions in the household were linked to gun ownership and less safe storage practices in 2021, but not in 2022.

This study identified factors associated with teen gun access at distinct points during the pandemic. This study found little evidence of any association between child mental health and household firearm storage.

This study aims to examine workers' distributive and interactional justice perceptions at three different moments in time over a period of eight years, assess their degree of stability and identify their most stable antecedents and outcomes.

Data was collected through an overlapping repeated cross-sectional design. Of the participants involved, 334 were surveyed in 2000, 259 participated in 2004, and 285 participated in 2008.

Distributive justice is more stable than interactional justice. Organizational support is the most stable predictor of distributive justice, and the quality of supervisor practices is the most stable predictor of interactional justice. Contrary to expected, interactional justice has a stronger relationship to workers' attitudes directed both at the organization and supervisor, and at the immediate work context.

This study adopts a long-term perspective covering an eight-year period. Furthermore, it focuses on two dimensions of justice that have been less studied over time.

A common understanding of what events to regard as production disturbances (PD) are essential for effective handling of PDs. Therefore, the purpose of this paper is to answer the two questions: how are individuals with production or maintenance management positions in industry classifying different PD factors? Which factors are being measured and registered as PDs in the companies monitoring systems?

A longitudinal approach using a repeated cross-sectional survey design was adopted. Empirical data were collected from 80 companies in 2001 using a paper-based questionnaire, and from 71 companies in 2014 using a web-based questionnaire.

A diverging view of 21 proposed PD factors is found between respondents in manufacturing industry, and there is also a lack of correspondence with existing literature. In particular, planned events are not classified and registered to the same extent as downtime losses. Moreover, the respondents are often prone to classify factors as PDs compared to what is actually registered. This diverging view has been consistent for over a decade, and hinders companies to develop systematic and effective strategies for handling of PDs.

There has been no in-depth investigation, especially not from a longitudinal perspective, of the personal interpretation of PDs from people who play a central role in achieving high reliability of production systems.

Previous research has shown that in contemporary societies, women have a healthier dietary intake than men. However, no research has examined how this gender gap develops over the long term. The present study examined how gender differences in fresh vegetable intake frequency have evolved from 1979 to 2017 in Finland and whether differences are affected by age or educational level.

The data were derived from annually repeated, nationally representative “Health Behaviour and Health among the Finnish Adult Population” and “Regional Health and Well-being (RHW)” surveys on the health habits of the Finnish population. The dataset is a time series of repeated cross-sectional surveys. In total, the data sample comprised 161,996 Finns aged 20–64 years. Descriptive methods and logistic regression were used for the analysis.

During 1979–2017, the prevalence of daily vegetable intake increased from 12 to 35% among men and from 18 to 56% among women. Thus, the magnitude of the gap between genders doubled across the study period. The increased vegetable intake was partly explained by the changing education and age structures of society. Potential explanations and avenues for future research are also discussed. Policy implications depend on whether the findings are interpreted as a case of health differences or health inequality.

This study used a long time series to analyse how gender differences in vegetable intake have evolved in a Nordic welfare state context. It showed that the gap in fresh vegetable intake between men and women has widened.