An Empirical Analysis of the Effect of Supply Chain Disruptions on Long‐Run Stock Price Performance and Equity Risk of the Firm

This paper investigates the long‐term stock price effects and equity risk effects of supply chain disruptions based on a sample of 827 disruption announcements made during 1989–2000. Stock price effects are examined starting one year before through two years after the disruption announcement date. Over this time period the average abnormal stock returns of firms that experienced disruptions is nearly –40%. Much of this underperformance is observed in the year before the announcement, the day of the announcement, and the year after the announcement. Furthermore, the evidence indicates that firms do not quickly recover from the negative effects of disruptions. The equity risk of the firm also increases significantly around the announcement date. The equity risk in the year after the announcement is 13.50% higher when compared to the equity risk in the year before the announcement.     

Study on lumbar kinematics and the risk of low back disorder in female university students by using shoes of different heel heights

The study was taken up to investigate the effects of heel heights on lumbar kinematics and the risk of Low Back Disorder (LBD) in females. Nineteen female university students (24.5 ± 3.36 yrs) volunteered in the study. Lumbar kinematics was measured by using Industrial Lumbar Motion Monitor (iLMM). The volunteers were asked to walk for a distance of 50 meters in 3 different given conditions i.e bare foot (Heel 0), with flat heels (Heel 1) and with high heels (Heel 2). Heights of Heel 1 and Heel 2 were 1.5 ± 0.84 cm and 5.5 ± 1.70 cm respectively. The Lumbar kinematic parameters studied were- Average Twisting Velocity (ATV), Maximum Sagital Flexion (MSF) and Maximum Lateral Velocity (MLV). It was observed that all the above mentioned Lumbar kinematics - ATV, MSF and MLV increases with increase of heel heights, which in turn increases the risk of LBD. As a result of increase in Lumbar kinematic values with increase in heel heights, LBD risk has also increased. Mean and SD of the LBD risk with Heel 0, Heel 1 and Heel 2 were 16.79 ± 6.04%, 19.00 ± 7.38% and 22.11 ± 6.98% respectively. Lower stature with high heels showed higher risk of LBD than the higher stature with high heels.     

Trust,Social Networks and Subjective Wellbeing in China

Using data from the World Values Survey, this study examines the associations among trust, social networks and subjective wellbeing in China. We address the endogenous nature of trust and social networks, and examine how these elements of social capital affect subjective wellbeing. We also explore the interplay between trust and social networks. Existing literature suggests that trust and social networks positively impact wellbeing, with one strand of the literature suggesting that in developed countries social capital is a stronger determinant of wellbeing than income. However, we find that this is not the case for China (a developing country) where the effects of trust and social networks on wellbeing are found to be relatively weaker compared to the effect of income.     

The Effect of Antenatal Care on Professional Assistance at Delivery in Rural India

Delivering births in a medical institution or at home with professional medical assistance has been shown to promote safe motherhood and child survival. Yet three-quarters of births in rural India continue to take place at home, most of them without the assistance of any trained health worker. This study examines the role of antenatal care (ANC) in promoting professional assistance at delivery, using data from India’s 1992–93 and 1998–99 National Family Health Surveys (NFHS-1 and NFHS-2). We estimate the effect of number of antenatal care visits (0, 1–2, 3+) on professional assistance at delivery (no assistance, professional assistance at home, delivery in a medical institution), using multinomial logistic regression, controlling for demographic, geographic, and socioeconomic factors, pregnancy complications, and two measures of access to health facilities. The results indicate that, after controlling for other variables (including ANC), pregnancy complications and access to health facilities do not have much effect on assistance at delivery. By contrast, ANC has a large effect, even after all other variables are controlled. The effect of ANC on professional assistance at delivery is larger in South India than in North India, and predicted percentages receiving professional assistance are higher in South India than in North India. A policy implication is that increased antenatal care coverage can be an effective means of increasing professional assistance at delivery, especially delivery in a medical institution.

Modelling the factors that influence the acceptance of digital technologies in e-government services in the UAE: a PLS-SEM Approach

Abstract

The digital technologies such as Internet play a crucial role in the management of operations of organisations in both public and private sectors. Such technologies support the implementation of effective digital business strategies. By reviewing the extant literature, this paper aims to identify factors that influence the intention to use digital technologies in order to develop a theoretical model which is then tested empirically using the PLS-SEM approach. While many studies have focused solely on the importance of social influence, perceived usefulness, perceived ease of use, awareness, perceived trust in technology, perceived trust in government, perceived cost and perceived risk, this article brings them together to explain their linkage, and quantifies the relationship. This study is the first empirical attempt to explore the factors influence e-government services adoption in the UAE. Most specifically, this article emphasises the role of social influence, perceived ease to use and perceived trust in technology as the important determinants of the intention to digital technology adoption. The paper expands the traditional discussion by incorporating six variables in a model that acts as facilitator or barrier in the intention to use digital technologies. This article helps practitioners to understand of which factors should be given emphasis in enhancing the intention to use digital technologies. The model developed in this paper is not only a response to the need to understand what causes the variation in the intention to use digital technologies from the operation management perspective, it is also a response to practitioner needs to use an appropriate construct to ensure the effective operation and use of the digital technologies in e-government services. The paper will help to identify the key issues surrounding the digital technologies adoption that may lead the successful operations of e-government.     

Risk and protective factors in problem gambling: an examination of psychological resilience

Psychological resilience – successful adaptation when faced with adversity – is a product of the balance of risk and protective factors relevant to an outcome. This study examined if protective factors (perceived resilience; mindfulness; grit; self-efficacy) explained variance in problem gambling tendencies (assessed with the Problem Gambling Severity Index) beyond the HEXACO personality traits (honesty-humility, emotionality, extraversion, agreeableness, conscientiousness, openness to experience) and risk factors for problem gambling (gender; age; socio-economic status; high frequency gambling behaviour; harsh unpredictable childhood environments; sensation-seeking; impulsivity; self-control; stress). This study used a crowdsourced community sample (n = 469) recruited from Amazon Mechanical Turk. Bivariate analyses showed that risk factors and some HEXACO traits (especially honesty-humility) were associated with problem gambling issues. Among protective factors, only trait mindfulness showed a bivariate association with problem gambling issues. Somewhat surprisingly, regression analyses revealed that protective factors did not explain variance in problem gambling beyond HEXACO traits and risk factors. However, in exploratory analyses, mindfulness and self-efficacy – both modifiable protective factors – moderated the relationship between high-frequency gambling (a key proximate antecedent of problem gambling) and problem gambling tendencies. These results suggest mindfulness and self-efficacy may serve as ‘buffers’ against the development of problem gambling issues and may be promising targets for clinical interventions.     

Characteristics for the Effectiveness of Women’s Self-Help Groups in Bihar

This study examines whether group heterogeneity and group structure and process predict the effectiveness of women’s self-help groups in terms of their financial performance, self-reliance of the group, members’ decision-making ability at the household level, and access to non-financial benefits. Data were collected using an interview schedule from 210 women’s self-help groups in six districts of Bihar and data were analyzed using partial least squares structural equation modeling. The findings suggest that the group heterogeneity directly predicts the effectiveness of women’s self-help groups and it is fully transmitted through group structure and process to positively predict the effectiveness of the women’s self-help groups. The group structure and process is found to be a full mediator between group heterogeneity and group effectiveness. The predictive accuracy of the model is found to be high. The findings have implications to bring in more diversity in members castes, education, and their reasons for joining women’s self-help groups at the formation stage and variations in members’ skills and expertise at the performing stage of the groups. The members’ awareness on group norms and trust in financial transactions, and leadership styles together with cooperation and cohesion among members, transparency in financial transactions, group attendance, and networking with the bank and the federation foster the effectiveness of women’s self-help groups.     

Exploring the Urban–Rural Incarceration Divide: Drivers of Local Jail Incarceration Rates in the United States

ABSTRACT

A large body of research has focused on understanding mass incarceration in the United States through the lens of federal and state prison growth. However, local jail systems, with 11 million admissions each year, have received less research attention despite their broad impact on communities. Preliminary analysis conducted by the Vera Institute of Justice (Vera) uncovered geographical disparities in county jail incarceration rates. Contrary to assumptions that incarceration is an urban phenomenon, Vera discovered that, in recent decades, pretrial jail rates have declined or remained flat in many urban areas, whereas rates have grown in rural counties. In an effort to uncover factors contributing to continued jail growth in rural areas, Vera joined forces with Two Sigma’s Data Clinic, a volunteer-based program that leverages Two Sigma employees’ data science expertise. Determinants of local jail rates from 2000–2013 were examined using a generalized estimating equations (GEE) model to account for correlations within counties over time. Results revealed that county-level poverty, police expenditures, and spillover effects from other county and state authorities are significant predictors of local jail rates. Investigation of model residuals revealed clusters of counties where observed rates were much higher than expected conditioned upon county variables.     

The Measurement of Socio-Economic Status: Investigation of Gender-and Age-Specific Indicators in Australia: National Health Survey 1995

Objective: To investigate thecorrelations between age- and gender-specificmeasures of socio-economic status versus healthstatus as measured by the SF-36. Design: Population based study. Participants: 38187 people aged between18 to 79 years who participated in the NationalHealth Survey in 1995. Results: Factor analysis producedconsistent results that were interpreted interms of five conceptually meaningful domains(employment, housing, migration, family unitand education). The relative rank of thefactors differs between groups and in somecases factor composition requires items to beadded or deleted from the conceptual domains. Conclusions: Age- and gender-specific SESscores based on these factors had strongerassociations with the physical and mentalcomponents of SF-36 than either an area basedindex or scores derived from males aged 40–44years. Overall the results supported thehypothesis that SES measures composed of socialand demographic items exhibit important age-and gender-specific differences which arerelevant for health.     

Development of Dose‐Response Models to Predict the Relationship for Human Toxoplasma gondii Infection Associated with Meat Consumption

Toxoplasma gondii is a protozoan parasite that is responsible for approximately 24% of deaths attributed to foodborne pathogens in the United States. It is thought that a substantial portion of human T. gondii infections is acquired through the consumption of meats. The dose‐response relationship for human exposures to T. gondii‐infected meat is unknown because no human data are available. The goal of this study was to develop and validate dose‐response models based on animal studies, and to compute scaling factors so that animal‐derived models can predict T. gondii infection in humans. Relevant studies in literature were collected and appropriate studies were selected based on animal species, stage, genotype of T. gondii, and route of infection. Data were pooled and fitted to four sigmoidal‐shaped mathematical models, and model parameters were estimated using maximum likelihood estimation. Data from a mouse study were selected to develop the dose‐response relationship. Exponential and beta‐Poisson models, which predicted similar responses, were selected as reasonable dose‐response models based on their simplicity, biological plausibility, and goodness fit. A confidence interval of the parameter was determined by constructing 10,000 bootstrap samples. Scaling factors were computed by matching the predicted infection cases with the epidemiological data. Mouse‐derived models were validated against data for the dose‐infection relationship in rats. A human dose‐response model was developed as P (d) = 1–exp (–0.0015 × 0.005 × d) or P (d) = 1–(1 + d × 0.003 / 582.414)^?1.479. Both models predict the human response after consuming T. gondii‐infected meats, and provide an enhanced risk characterization in a quantitative microbial risk assessment model for this pathogen.