PurposeThis study is undertaken to examine the antecedents and role of big data decision-making capabilities toward decision-making quality and environmental performance among the Chinese public and private hospitals. It also examined the moderating effect of big data governance that was almost ignored in previous studies.Design/methodology/approachThe target population consisted of managerial employees (IT experts and executives) in hospitals. Data collected using a survey questionnaire from 752 respondents (374 respondents from public hospitals and 378 respondents from private hospitals) was subjected to PLS-SEM for analysis.FindingsFindings revealed that data management challenges (leadership focus, talent management, technology and organizational culture for big data) are significant antecedents for big data decision-making capabilities in both public and private hospitals. Moreover, it was also found that big data decision-making capabilities played a key role to improve the decision-making quality (effectiveness and efficiency), which positively contribute toward environmental performance in public and private hospitals of China. Public hospitals are playing greater attention to big data management for the sake of quality decision-making and environmental performance than private hospitals.Practical implicationsThis study provides guidelines required by hospitals to strengthen their big data capabilities to improve decision-making quality and environmental performance.Originality/valueThe proposed model provides an insight look at the dynamic capabilities theory in the domain of big data management to tackle the environmental issues in hospitals. The current study is the novel addition in the literature, and it identifies that big data capabilities are envisioned to be a game-changer player in effective decision-making and to improve the environmental performance in health sector.

Aim: To investigate the most recent estimates of underweight, overweight, and obesity prevalence in Pakistani school-aged adolescents aged 12 to 17 years, Methods: A cross-sectional study was conducted using a convenience sampling approach with 2100 Pakistani from 24 schools in central Punjab province. The CDC US 2000 was used to define underweight < 5th percentile, overweight > 85th to < 95th percentile, and obese equal or greater than 95th percentile, the Chi-square test was used. The Pearson correlation coefficient (r) was used to determine the correlation. The statistical significance level was set at p < 0.05. Results: prevalence of underweight U/W, overweight O/W, and obesity O/B was (21.9%, 5.8%, and 5.4%, respectively. The BMI had a positive relationship with gender, residency school kind and school level. Conclusion: Underweight, overweight, and obesity were prevalent among Pakistani school-aged adolescents. Girls were significantly more than boys to be overweight and obese. Students in urban regions were more likely than those in rural areas to be overweight. The relationship between BMI, behavioral, and other health variables should also be investigated in future research using longitudinal or interventional approaches. Keywords: Body Mass Index, School-aged adolescents, demographic

Voice over Internet Protocol (VOIP) in an efficient manner is a basic requirement of modern era. The real time and non-real traffics demand customized communication provisioning to get guarantee of service. For this we proposed a user fulfillment design for facilitating packets switching in 3G cellular network to insure provisioning of QoS (quality of service) in DiffServ (Differentiated Services) Network. To enhance QoS for real time traffic by reducing delay, packet loss and jitter, we proposed Low latency queuing (LLQ) algorithm. In this paper, we focused on packet scheduling, Diffserv and QoS classes mapping into Universal Mobile telecommunication System (UMTS) classes and buffering. To associate different types of real time multimedia traffic, the QoS provisioning mechanism used different code points of Diffserv. The new idea in LLQ is to map the video and voice traffics against two separate queues and used priority queuing in Low latency queuing for voice traffic. The results got from reproductions shows that proposed calculation meets the QoS prerequisites.

Globally the average annual loss of reservoir capacity is approximately 1%. Pakistan is confronting major issue of sedimentation which is continuously depleting the useful storage of reservoirs. GSTARS3 model was used to determine the rate of deposition and sediment pattern of Chashma Reservoir since its operation. The model was calibrated and validated for bathymetric survey of 2008 and 2012. The results of GSTARS3 were incorporated to a GIS software to visualize sediment accumulation in reservoir. The study reveals that sediment flushing of the Chashma Reservoir can be carried out during flood season at a pond level of 638.15 ft. (194.51 m). However, its negative impact if any on the hydropower generation needs to be analysed. Accordingly, modified operation rules would be required.

Abstract:The main purpose of the study was to determine the contribution of socio-economic development of the beneficiaries through PDBF activities. The