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Transforming public services: the impact of big data on e-government implementation in Sri Lanka
Get PDFPurpose: This research examines the usefulness and relevance of metadata in e
government services. It examines how big data, which has the 5V's (Volume, Velocity,
Variety, Veracity, and Value), affects e-government platform efficiency and
effectiveness. The emphasis is on how this integration may boost performance amid
fast technology advancements and increased data complexity.
Design/methodology/approach: A standardized questionnaire is used to collect data
from 242 senior, operational, and intermediate managers in four areas for quantitative
research. Expert ratings and Cronbach's alpha coefficient confirmed the
questionnaire's reliability and validity. SmartPLS 4 was used to evaluate the model's
validity and dependability. The study examined how the 5Vs' big data criteria affect
e-government services.
Findings: The research shows that big data is crucial to e-government service
implementation. The research found that these parameters significantly improve e
government service stacking. Big data analytics helps digitally alter government
services, improve decision-making, and improve service delivery.
Practical implications: The findings emphasize the need for big data analytics in e
government infrastructure to improve service quality and responsiveness. Big data
may help governments increase public engagement, optimize resource allocation, and
provide more personalized services.
Originality value: This paper provides empirical evidence of big data's 5V's impact
on e-government services. The declaration emphasizes metadata and big data analytics
as key tools for public sector digital transformation
Evaluation of five medicinal plants for the management of Sitophilus oryzae in stored rice and identification of insecticidal compound
Get PDFSitophilus oryzae is a kind of stored grain pest. This is controlled by using natural pesticides, which
are more reliable, cost-effective, biodegradable, and eco-friendly than synthetic pesticides.
Several plants show different insecticidal activities against various pests on their different parts
(leaves, seeds, etc.). In this study, methanolic extracts of Lantana camara (leaves), Carica papaya
(seeds), Ricinus communis (leaves), Calotropis gigantea (flowers), and Gliciridia sepium (leaves) were
used to identify the best insecticidal activity against the rice weevil by doing mortality tests for
one week with four replications under laboratory conditions. Gliciridia sepium leaves showed the
highest insecticidal activity (100 ± 0) after seven days, and its extract was fractionated by using
column chromatography and yielded 12 fractions. A contact bioassay of each fraction was per
formed, and fraction-11 showed the highest insecticidal activity against Sitophilus oryzae with a
100 % mortality after four days. Fraction-11 was analyzed by using GC-MS and FT-IR. Results
revealed that the major constituent identified in fraction-11 was 4-C-methyl-myo-inositol.
Therefore, 4-C-methyl-myo-inositol acts as a natural insecticide against rice weevils
A study on the impact of social media marketing on consumer purchase decision in modern supermarkets in Sri Lanka
Get PDFPurpose: The widespread adoption of social media and advancements in digital
marketing have significantly transformed organizational strategies, marketing
structures, and consumer engagement dynamics. Social media, rooted in Web 2.0
technologies, has emerged as a key tool for understanding consumer behavior, brand
perceptions, and purchasing patterns. This study aims to bridge this gap by analyzing
the effects of various social media platforms, content strategies, and engagement
techniques on consumer behavior, thereby offering actionable insights to enhance
marketing practices.
Design/methodology/approach: A quantitative research approach was employed for
this study, systematically collecting numerical data through structured survey
questionnaires from 385 as the quantitative design was deemed appropriate for
capturing the influence of SMM on consumer purchasing behavior in the Sri Lankan
supermarket sector.
Findings: The study found that engagement and relevant content on social media
platforms was found to have a substantial impact on consumer behavior, emphasizing
the need for creative and audience-centered communication. Further, content sharing
emerged as a critical factor, with social proof and the virality of shared posts
significantly influencing purchasing patterns. The research also highlighted the
importance of content quality, demonstrating that high-quality and valuable social
media posts positively affect consumer decisions by fostering trust and engagement.
Finally, personalization in SMM, such as tailored advertisements and targeted
promotions, was shown to be highly effective in driving purchase intentions,
indicating that customized approaches resonate well with consumers. Together, these
findings provide a comprehensive understanding of the pivotal elements of SMM that
contribute to consumer purchasing behavior in the context of Sri Lanka’s modern trade
supermarkets
Grain-size distribution dataset of lagoonal and riverine coastal placer deposits along the southeastern coast of Sri Lanka
Get PDFThe dataset contains grain size data of placer and non-placer
sediments in lagoonal and riverine beaches of southeastern
part of Sri Lanka. A total of 124 swash sediment samples
were collected from a 70 km long coastline with an interval of 500 m. Placer sediments in the area mainly have mineralogy of ilmenite, zircon and almandine while non-placers
are quartz, albite and calcite. After dry sieving, the grain size
distribution (GSD) analyses were carried out on each sample using the Gradistat Excel template. Placer deposits result coarse-skewed leptokurtic to platykurtic fine sand distributions while non-placers are medium sand-grained. The
dataset can be used to interpret the deposition environment
and transportation dynamics. Further, they can be used to
study the southwestern coastline of the Bay of Bengal, juvenile crust sediments of Grenvillian age, alongshore and fluvial sediment dynamics, depositional and erosion processes,
geohazards assessments and heavy mineral deposits
Ensembling methods for protein-ligand binding affinity prediction
No full textProtein-ligand binding affinity prediction is a key element of computer-aided drug discovery. Most of the existing deep learning methods for protein-ligand binding affinity prediction utilize single models and suffer from low accuracy and generalization capability. In this paper, we train 13 deep learning models from combinations of 5 input features. Then, we explore all possible ensembles of the trained models to find the best ensembles. Our deep learning models use cross-attention and self-attention layers to extract short and long-range interactions. Our method is named Ensemble Binding Affinity (EBA). EBA extracts information from various models using different combinations of input features, such as simple 1D sequential and structural features of the protein-ligand complexes rather than 3D complex features. EBA is implemented to accurately predict the binding affinity of a protein-ligand complex. One of our ensembles achieves the highest Pearson correlation coefficient (R) value of 0.914 and the lowest root mean square error (RMSE) value of 0.957 on the well-known benchmark test set CASF2016. Our ensembles show significant improvements of more than 15% in R-value and 19% in RMSE on both well-known benchmark CSAR-HiQ test sets over the second-best predictor named CAPLA. Furthermore, the superior performance of the ensembles across all metrics compared to existing state-of-the-art protein-ligand binding affinity prediction methods on all five benchmark test datasets demonstrates the effectiveness and robustness of our approach. Therefore, our approach to improving binding affinity prediction between proteins and ligands can contribute to improving the success rate of potential drugs and accelerate the drug development process
Impact of occupational stress factors on job performance: study on teaching staff of south eastern university of Sri Lanka
Get PDFPurpose: This study aims to evaluate the impact of occupational stress on job
performance among teaching staff at South Eastern University of Sri Lanka. The
factors of occupational stress examined include workload, working environment, and
home-work interference.
Design/Methodology/Approach: The study population comprised 244 teaching
employees at South Eastern University of Sri Lanka, from which a simple random
sample of 150 employees was selected. Data were collected using a standardized
questionnaire administered via Google Forms and emailed to the teaching staff,
yielding 116 valid responses for analysis. The data were analyzed using SPSS 26.
Findings: Outputs of the correlation analysis indicated that each factor; workload,
working environment, and home-work interference had a strong negative and
significant relationship with job performance. Furthermore, multiple regression
analysis demonstrated a strong negative impact of occupational stress on job
performance.
Practical Implication: These results enhance our understanding of the significant
inverse relationship between occupational stress factors and job performance,
highlighting the urgent need for stress management interventions to mitigate the
adverse effects of stress on the teaching staff’s job performance.
Originality/Value: Future research could build on this study by including a larger
sample size and examining additional private and state universities, and other
educational institutions. This study also provides a new contribution to the education
industry in Sri Lanka regarding occupational stress and job performance
Development of a suitable invitro protocol for nymphaea leaf culture
Get PDFNymphaea is commercially important aquatic plants propagated through
cross pollinated seeds cause trait variations in the offsprings, the
morphological features of flowers are different from one plant to another and
cause major problem by commercial producers and vendors. Therefore,
multiplication through micropropagation is a viable option. Hence, this
research focused on establishing a robust in vitro protocol for Nymphaea leaf
culture. The young leaves of Nymphea were excised from a single mother
plant and cut into (5mm x5mm) pieces were used as explants. Then five
sterilization methods (Factor 1) viz: 0.2% of HgCl2 (T1), 0.1% of HgCl2 (T2),
5% NaOCl (T3), 10% NaOCl with Tween20 (T4), 10% NaOCl (T5) were
employed. Then two types of media (Factor 2), namely 1/2MS (M1),
comprising 50 ml of A stock, 2.5 ml of B stock, 5 ml of C stock, along with
glycine, pyridoxine, nicotinic acid, thiamine, BAP, 2.4-D, Myo-inositol, and
sugar, consistent and favorable results were observed across various
sterilization techniques. Conversely, media 2 (M2), with a similar
composition but supplemented with BA, NAA, and kinetin were employed.
The data collected over the course of 12 weeks, the results indicate that T4
consistently exhibits the lowest contamination percentage of leaf across both
media formulations, while T3 consistently demonstrates higher
contamination rates. Furthermore, media 1 consistently yields superior
results in terms of tissue culture initiation compared to media 2. By
identifying optimal sterilization techniques and media formulations, this
study provides valuable insights for enhancing mass propagation
Geo-hazards in the North Arabian Sea with special emphasis on Makran Subduction Zone
Get PDFThe intricate convergence of tectonic plates and the interplay between landmasses and oceans in subduction
zones give rise to marine geo-hazards, encompassing catastrophic events in marine environments, posing sig
nificant risks to ecosystems, coastal communities and infrastructure. The Makran Subduction Zone (MSZ), with
its remarkable history of devastating earthquakes and tsunamis, is a subject of significant attention from both
academic and industrial sectors in recent decades. In this comprehensive review, we investigated various marine geo-hazards in the north Arabian Sea (NAS), particularly those associated with the MSZ, providing valuable insights for risk mitigation in the coastal regions with a population of over 45 million. The review employed bibliometric methods to comprehensively analyze relevant publications from databases such as Web of Science, Scopus, and China National Knowledge Infrastructure. By conducting a systematic review of 133 publications, this study deepens our understanding associated with MSZ, uncovering 07 distinct categories of geo-hazards. The earthquakes and tsunamis hazards have received extensive attention, with a tentative recurrence interval of around 500 years, while the remaining categories, including seabed fluid flows, mud-volcanism, sub-marine mass movements, subsidence, and erosion, were similarly explored in their respective order. The eastern side of the MSZ demonstrated greater instability compared to the western side, attributed to the ongoing subduction process. The ‘Gang of Four’, consisting of faults, has been identified as a primary causative factor for seismic activity in the NAS, largely influenced by transpressional tectonics. The identified geo-hazards exhibit complex interdependencies, where the initiation of one hazard can amplify the severity of another. An integrated approach is essential for assessment of the complex and interrelated risks and hazards. The research emphasizes the significance of long-term seafloor observatories in the MSZ for real-time monitoring, enabling proactive management and mitigation strategies to address these geo-hazards effectively
Impact of owner - based and lender - based governance mechanisms on firm financial performance of listed food, beverage and Tobacco Companies in Sri Lanka
Get PDFPurpose: Corporate governance mechanisms play a significant role in solving
agency problems within organizations and it supports in ensuring the stability of
companies by increasing the firm financial performance. Corporate governance
research has concentrated on the governance executed by the shareholders,
among several stakeholders of a firm. Owners and lenders-based mechanisms are
suffering from firm financial performance problems. This study attempted to
answer this problem by identifying the impact of both owner-based and lender
based governance mechanisms on the firm financial performance of listed food,
beverage, and tobacco companies in Sri Lanka.
Design/methodology/approach: The research model was conceptualized by
using independent variables, corporate governance mechanisms along with the
two dimensions OG mechanisms: ownership concentration, board size, board
composition & LG mechanisms: loan amount, loan magnitude and the dependent
variables, firm financial performance along with the three dimensions firm
profitability, firm value, firm distress level. This quantitative study sampled for
twenty companies from 2019-2023 using the simple convenience sampling
method. Descriptive statistics, correlation analysis, and regression analysis were
used as the analytical tools.
Findings: The results indicate that the OG mechanisms would enhance the firm
profitability and firm value while significantly impacts on firm distress level. The
LG mechanism significantly impacts firm profitability, firm value, and firm
distress level. Therefore, both structures of governance must be regarded as
relevant factors in assessing various types of financial success of companies.
Practical implications: The results of this study have significant ramifications
for various parties in order to ensure the financial stability, to mitigate the
weaknesses of good corporate governance
A systematic literature review on integrating disaster risk reduction (DRR) in sustainable tourism (SusT): conceptual framework for enhancing resilience and minimizing environmental impacts
No full textThis literature review meticulously explores the integration of Disaster Risk Reduction (DRR) techniques into sustainable tourism (SusT), placing a focal point on enhancing resilience and mitigating environmental impacts. By examining several disciplines, including tourism management, disaster management, environmental science, green innovation, and sustainable development, this study recognizes major themes, research gaps, and best practices in this emerging subject. It underlines the importance of SusT and the need for effective DRR programs to alleviate the negative effects of catastrophes on tourism destinations and ensure their long-term sustainability and resilience. Science Direct, Springer, SAGE Publications, and Wiley's online library were the selected databases and the inclusion criteria were based on studies that looked at how DRR measures were implemented in SusT practices and how effective they were in increasing resilience and lowering environmental effects. The selected literature reveals many concepts and ways for integrating DRR in tourism, such as pre-disaster planning, risk assessment, capacity building, and stakeholder involvement. The assessment identifies the vital part played by government agencies, local entities, and tourist service providers in organizing and coordinating these programs. It points out potential obstacles to DRR integration within the tourism sector. The review emphasizes the importance of monitoring and measuring the outcomes of DRR programs in tourism, and it suggests the use of metrics and indicators to assess how well resilience-building and environmental impact reduction strategies are implemented. These insights may be utilized by policymakers, academics, and practitioners to design methods that enhnace the resilience of tourism destinations while minimizing environmental consequences