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This study applies organizational information processing theory (OIPT) to investigate managing production process variability in uncertain environments using information technology (IT) capabilities.

We conduct an empirical analysis using the three-stage least squares (3SLS) technique on 1,612 manufacturing firms over ten years.

The findings show that IT capability plays a dual role: it reduces the positive impact of environmental uncertainty on production process variability and mitigates the negative relationship between production process variability and operational performance.

Our findings suggest that managers should focus on reducing production process variability by strengthening their firms' IT capabilities. This is particularly crucial in volatile environments where external uncertainties can significantly impact operational processes.

Variability in the production process is a significant source of inefficiency and disruption within business processes. Using OIPT, our study contributes to the field by empirically analyzing the role of IT capabilities in reducing production process variability under environmental uncertainty.

The purpose of the study is to examine the relation between board structure and firm performance variability in an international setting. The authors further explore the effect of national culture in shaping such relations.

The authors’ international sample contains 4,911 firms across 49 countries over the 2002–2017 period. The authors use national culture values on individualism and power distance developed by Hofstede (1980, 2001, 2011). The authors focus on within-firm, over-time variability of firm performance and estimate multivariate linear regressions with fixed effects. The authors address the endogeneity concern using the instrumental variable approach, and the authors’ results are robust to alternative measures of variables and different subsamples.

The authors find that firms with larger board size, greater board independence and less powerful CEOs have less variable performance. Individualism has a magnifying effect while power distance has a mitigating effect in shaping such relations.

To the best of the authors’ knowledge, this study is among the first to answer the call of Adams, Hermalin and Weisbach (2010) for research on corporate boards in an international setting. It is also one of the few studies which examine the variability of firm performance, while the majority of existing literature focuses on the level of firm performance. Most importantly, to the best of the authors’ knowledge, this study is the first to explore the role of national culture in shaping boardroom interactions that affect the decision-making process of corporate boards, which, in turn, affects firm performance variability.

Past studies have mainly concentrated on the impact of stress and self-employment on physical health. However, little research has paid attention to firm-level determinants of entrepreneurs’ physical health. This study aims to investigate the relationship between performance variability and entrepreneurs’ physical health as well as the moderating effect of prior failure experience.

This study uses data drawn from 255 start-ups across the Bohai Economic Rim in China over a period of three years (2015–2017). The results are still robust after several robustness checks.

Results show that performance variability is positively related to the probability of entrepreneurs showing poor health. This confirms that performance variability has an adverse effect on entrepreneurs’ physical health. Moreover, this relationship is moderated by the prior failure experience of entrepreneurs.

First, entrepreneurs should gain more information about the firm’s daily operation to reduce the potential threat of performance variability. Second, it is imperative for entrepreneurs to build a stable relationship with their stakeholders to avoid the potential costs related to performance variability. Finally, entrepreneurs should take health consequences into consideration when making strategic decisions.

First, this paper contributes to the studies on the antecedents of entrepreneurs’ physical health by introducing a firm-level determinant (i.e. performance variability). The findings enhance the understanding of the association between entrepreneurs and new ventures. Second, this paper also enriches the extant literature on the outcomes of performance variability. Finally, this paper attempts to offer new insights into prior failure experience by establishing its moderating effect on the performance–health relationship.

The study investigates the impact of inflation on the variability of relative prices in the context of Lebanon.

Unlike the traditional method, which relies on the variance of cross-sectional price changes measured at specific points in time to gauge the variability in relative prices, we employ a more appropriate approach. Under this approach, we capture the dispersion in relative prices by estimating how widely (or closely) a set of commodity prices drift apart over a span of time, offering a more comprehensive assessment. Firstly, we employ Johansen’s cointegration test on rolling subsamples to determine the number of statistically significant cointegrating vectors among the prices of 12 major commodity groups. Under this approach, an increase in the number of significant cointegrating vectors indicates a reduction in relative price variability, while a decrease suggests the opposite. Subsequently, we employ ordinary least squares regression to analyze how the fluctuations in inflation affect the variability in relative prices. The sample period ranges from December 2007 to April 2021.

The empirical results indicate that there exists a certain threshold inflation rate corresponding to which the variability in relative prices is minimized. More importantly, consistent with the theoretical predictions, the results suggest that it is not inflation per se, but the deviation of inflation from the 3% threshold level in either direction that causes higher dispersion in relative prices.

The empirical findings from this study have crucial implications for the operation of monetary and fiscal policy. In particular, these findings suggest that stabilizing long-term inflation around a certain threshold rate will not only help to anchor inflation expectations effectively but will also minimize the welfare costs associated with inflation.

Given the rising inflationary pressure in the recent past and its welfare costs, the study assumes crucial importance in understating how fluctuations in inflation distort the relative price structure and eventually cause resource misallocations and economic inefficiency.

Medical diagnosis and treatment processes exhibit a high degree of variability, as during the process execution, healthcare professionals can decide on additional steps, change the execution order or skip a task. Process models can help to document and to discuss such processes. However, depicting variability in graphical process models using standardized languages, such as Business Process Model and Notation (BPMN), can lead to large and complicated diagrams that medical staff who do not have formal training in modeling languages have difficulty understanding. This study proposes a pattern-based process visualization that medical doctors can understand without extensive training. The process descriptions using this pattern-based visualization can later be transformed into formal business process models in languages such as BPMN.

The authors derived patterns for expressing variability in healthcare processes from the literature and medical guidelines. Then, the authors evaluated and revised these patterns based on interviews with physicians in a Danish hospital.

A set of business process variability patterns was proposed to express situations with variability in hospital treatment and diagnosis processes. The interviewed medical doctors could translate the patterns into their daily work practice, and the patterns were used to model a hospital process.

When communicating with medical personnel, the patterns can be used as building blocks for documenting and discussing variable processes.

The patterns can reduce complexity in process visualization. This study provides the first validation of these patterns in a hospital.

This study establishes a method for predicting ground vibrations caused by railway tunnels in unsaturated soils with spatial variability.

First, an improved 2.5D finite-element-method-perfect-matching-layer (FEM-PML) model is proposed. The Galerkin method is used to derive the finite element expression in the ub-pl-pg format for unsaturated soil. Unlike the ub-v-w format, which has nine degrees of freedom per node, the ub-pl-pg format has only five degrees of freedom per node; this significantly enhances the calculation efficiency. The stretching function of the PML is adopted to handle the unlimited boundary domain. Additionally, the 2.5D FEM-PML model couples the tunnel, vehicle and track structures. Next, the spatial variability of the soil parameters is simulated by random fields using the Monte Carlo method. By incorporating random fields of soil parameters into the 2.5D FEM-PML model, the effect of soil spatial variability on ground vibrations is demonstrated using a case study.

The spatial variability of the soil parameters primarily affected the vibration acceleration amplitude but had a minor effect on its spatial distribution and attenuation over time. In addition, ground vibration acceleration was more affected by the spatial variability of the soil bulk modulus of compressibility than by that of saturation.

Using the 2.5D FEM-PML model in the ub-pl-pg format of unsaturated soil enhances the computational efficiency. On this basis, with the random fields established by Monte Carlo simulation, the model can calculate the reliability of soil dynamics, which was rarely considered by previous models.

This study aims to examine the phenomenon of climate variability and its implications for pastoralists and agro-pastoralists food security in Amibara and Awash Fentale districts of the Afar region, Ethiopia.

The study relied on meteorological records of temperature and rainfall in the study area between 1988 and 2018. Besides, literature on the topic was reviewed to make caveats on the literal picture that comes from quantitative data, and that is the contribution of this study to the existing debate on climate change and variability. The spatiotemporal trend was determined using the Mann–Kendall test and Sen’s slope estimator, while variability was analyzed using the coefficient of variation and standardized anomaly index, and standardized precipitation index/standardized precipitation evapotranspiration index were applied to determine the drought frequency and severity.

The result reveals that the mean seasonal rainfall varies from 111.34 mm to 518.74 mm. Although the maximum and minimum rainfall occurred in the summer and winter seasons, respectively, there has been a decrease in seasonal and annual at the rate of 2.51 mm per season and 4.12 mm per year, respectively. The study sites have been experiencing highly seasonal rainfall variability. The drought analysis result confirms that a total of nine agricultural droughts ranging from moderate to extreme years were observed. Overall, the seasonal and annual rainfall of the Amibara and Awash Fentale districts showed a decreasing trend with highly temporal variations of rainfall and ever-rising temperatures, and frequent drought events means the climate situation of the area could adversely affect pastoral and agro-pastoral households’ food security. However, analysis of data from secondary sources reveals that analyzing precipitation just based on the meteorological records of the study area would be misleading. That explains why flooding, rather than drought, is becoming the main source of catastrophe to pastoral and agro-pastoral livelihoods.

The analysis of temperature and rainfall dynamics in the Afar region, hence the inception of all development interventions, must take the hydrological impact of the neighboring regions which appears to be useful direction to future researchers.

The research is originally conducted using meteorological and existing literature, and hence, it is original. In this research, we utilized a standardized and appropriate methodology, resulting in insights that augment the existing body of knowledge within the field. These insights serve to advance scholarly discourse on the subject matter.

The inherent variability on process times and demand are the factors that prevent the efficient application of lean philosophy in multi-project product development (PD) environments. Considering this variability, a hybrid push–pull project control system is developed, and value stream costing (VSC) analysis is performed to reflect the relation between project lead time, capacity and project cost. The assessment of the push/pull project control on lead time improvement and long-term savings on capacity have been aimed with the proposed complete design structure.

In a team-based structure, formed through clustering, push control techniques for planning tasks within cross-functional teams and pull control techniques for planning tasks between cross-functional teams are developed. The final step evaluates the proposed structure through VSC and long-term savings have been pointed out, especially in terms of freed-up capacity. For the validation of the proposed methodology, an office furniture manufacturing firm’s PD department has been considered and the performance of the hybrid system has been observed through simulation experiments and based on the simulation results, the lean system is evaluated by VSC.

The results of simulation experiments show a superior performance of the proposed hybrid push/pull project control mechanism under different settings of cycle time between projects or shortly project cycle time, dispatching rules within teams and variability levels. The results of the Box-Score (tool to apply VSC) indicate increased capacity in the long term to add extra projects during the planning period with the same project lead time and without additional cost.

Although extensive simulation experiments have been performed to quantify the effect of project control structure and positive results have been reported on lead time and cost, the proposed design structure has not been tested in all existing PD environments.

To the best of authors’ knowledge, the quantification of the effect of hybrid project control with VSC is the first attempt to be applied in lean PD projects.

The study aims to assess the effectiveness of prevailing methods for quantifying physical climate risks. Its goal is to evaluate their utility in guiding financial decision-making within the real estate industry. Whilst climate risk has become a pivotal consideration in transaction and regulatory compliance, the existing tools for risk quantification frequently encounter criticism for their perceived lack of transparency and comparability.

We utilise a sequential exploratory mixed-methods analysis to integrate qualitative aspects of underlying tool characteristics with quantitative result divergence. In our qualitative analysis, we conduct interviews with companies providing risk quantification tools. We task these providers with quantifying the physical risk of a fictive pan-European real estate portfolio. Our approach involves an in-depth comparative analysis, hypothesis tests and regression to discern patterns in the variability of the results.

We observe significant variations in the quantification of physical risk for the pan-European portfolio, indicating limited utility for decision-making. The results highlight that variability is influenced by both the location of assets and the hazard. Identified reasons for discrepancies include differences in regional databases and models, variations in downscaling and corresponding scope, disparities in the definition of scores and systematic uncertainties.

The study assists market participants in comprehending both the quantification process and the implications associated with using tools for financial decision-making.

To our knowledge, this study presents the initial robust empirical evidence of variability in quantification outputs for physical risk within the real estate industry, coupled with an exploration of their underlying reasons.

The purpose of this paper is to investigate the influence of employees’ trait rumination on the variability of their state rumination and the continuing influence on their negative affect at home.

A time-lagged experience sampling method was used for the data collection from full-time employees in the hotel industry. The hypotheses were tested with multilevel modeling using a random coefficient modeling approach.

Hotel employees who are high in trait rumination generally show high levels of state rumination and greater within-person variability in state rumination over time. Additionally, the negative effects of workplace state rumination can last until employees come home and the next day before going to work. Furthermore, employees who are high in trait rumination are more likely to be influenced by state rumination, as they experience more negative affect after arriving home.

Rumination has been shown to decrease hotel employee overall well-being. The findings of this study provide suggestions for remedial measures that can be taken by hotel organizations to help employees address ruminative thinking.

Drawing on response styles and work/family border theories, this study contributes to the rumination literature by considering both trait rumination and state rumination in a broader context. For a comprehensive understanding of the dynamic temporal characteristics of state rumination, this study considers the net intraindividual variability of state rumination as the outcome of trait rumination.