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Although scholars argue that artificial intelligence (AI) represents a tool to potentially smoothen the bullwhip effect in the supply chain, only little research has examined this phenomenon. In this article, the authors conceptualize a framework that allows for a more structured management approach to examine the bullwhip effect using AI. In addition, the authors conduct a systematic literature review of this current status of how management can use AI to reduce the bullwhip effect and locate opportunities for future research.

Guided by the systematic literature review approach from Durach et al. (2017), the authors review and analyze key attributes and characteristics of both AI and the bullwhip effect from a management perspective.

The authors' findings reveal that literature examining how management can use AI to smoothen the bullwhip effect is a rather under-researched area that provides an abundance of research avenues. Based on identified AI capabilities, the authors propose three key management pillars that form the basis of the authors' Bullwhip-Smoothing-Framework (BSF): (1) digital skills, (2) leadership and (3) collaboration. The authors also critically assess current research efforts and offer suggestions for future research.

By providing a structured management approach to examine the link between AI and the bullwhip phenomena, this study offers scholars and managers a foundation for the advancement of theorizing how to smoothen the bullwhip effect along the supply chain.

The aim of this study was to explore the reasons for preferring home as a birth delivery place and identify the socio-economic and cultural factors influencing the choice of delivery place in rural Bangladesh.

The data for the study come from a community-based cross-sectional study conducted among 464 mothers in a rural sub-district of Bangladesh in 2019. Respondents were selected randomly from the frame listing all mothers with inclusion criteria, using a two-stage cluster sampling design. Data were collected through a face-to-face interview. Both descriptive and inferential statistics and logistic regression models were used for data analysis.

The results indicate a very high rate (58%) of home delivery. About 20% mothers never received ANC visit. Preference for home delivery was high (63%). Mothers with no education, aged 30 and above, multi-parity, low wealth status, lack of knowledge about institutional delivery, no or <4 ANC visits, received no advice about the delivery place, no pregnancy complications, decision about health care, and prior plan for home delivery were identified as significant predictors of home delivery. Cost of services, cultural practices and attitude towards health facility, lack of a female delivery assistant, perceived fear of caesarian section, poor quality of services, and lack of knowledge about maternity services appeared as important barriers for institutional delivery.

Based on primary data from a rural area, this study would help understand reasons and factors affecting home delivery and developing an appropriate strategy for the improvement of institutional delivery and maternity care services in Bangladesh.

Severe bacterial infection is a major cause of neonatal morbidity and mortality worldwide. Geographical-based demographic laboratory and clinical data are required to get a conclusion about the bacterial infection and their antibiotic susceptibility for the empiric antibiotic treatment in infants who presented with suspected infection. This study was aimed to find the most prevalent bacterial infection and antibiotic sensitivity among infants in the post-neonatal period presented at a tertiary care centre in South India.

A cross-sectional study was designed among infants (29 days to 1 year old) presented with suspected infection in the paediatric department. Infants with positive culture report were analysed for the bacteriological and antibiotic profile from the medical records. Antibiotic sensitivity was determined for the isolated bacteria according to standard procedure and data statically analysed.

Total of 218 samples (138 male and 80 female) were analysed. Most of the samples (171/218, 78.4%) were throat swab (p = 0.0247). Only one sample was cerebrospinal fluid from case of meningitis. Sample from upper RTI was major (162/218, 74.3%) with male dominance followed by stool samples from cases of diarrhoea (22/218, 10.0%). Staphylococcus aureus was the major organism identified in 46/171 (26.9 %) throat swabs. The most sensitive antibiotic against bacteria isolated from throat swab and CSF was gentamicin and cloxacillin. Netilmicin and piperacillin plus tazobactam were the sensitive antibiotics against bacteria isolated from stool, ear secretion and urine samples.

Upper RTI was the prevalent bacterial infection followed by diarrhoea in infants in the post-neonatal period. Klebsiella pneumoniae was the common organism identified in the overall report followed by E. coli and S. aureus. Community-based awareness should be provided to follow good hygiene regularly in child care. Furthermore, avoid delay in seeking treatment and provide the medicine prescribed at the right time and in the right dose to limit the morbidity and bacterial resistance.