Browsing by Author "Rathnaweera, D"

Now showing 1 - 6 of 6

Open Access
Deciphering Online Consumer Behaviour: Uncovering Factors Affecting Purchase Intentions for Electronic Items in Sri Lanka Using Ordered Probit Model
(SAGE, 2025-05-29) Rathnaweera, D; Jayathilaka, R
This study identifies key determinants of Sri Lankan consumers’ online purchase intention for electronic goods and quantifies their impact using an ordered probit regression model. The findings reveal that a 1% increase in online reviews is associated with a 0.33 percentage point increase in high purchase intention, while trust and word-of-mouth similarly exert strong positive effects (0.30 and 0.21 percentage points, respectively). Notable, delivery terms, although significant, play a lesser role compared to online reputation factors. These insights offer strategic implementation for e-commerce businesses, emphasizing the need for enhanced consumer trust mechanisms, proactive reputation management and optimized delivery strategies. Policy can leverage these findings to develop consumer protection frameworks that ensure reliability in online transactions, fostering long-term e-commerce growth in emerging markets.
Open Access
Does Working from Home Affect Work-Life Balance? A Look into the Factors that Affect Work-Life Balance
(General Sir John Kotelawala Defence University,Management, Social Sciences & Humanities, 2021-12-20) Rathnaweera, D; Jayathilaka, R
The COVID-19 pandemic has triggered major social, political, and economic ramifications around the world. Amidst social mobility measures imposed to combat the spread of the virus, this pandemic was a major challenge for people in meeting their daily needs and demands of employers. These transformed work habits, moving from physical to a virtual setting, which had mixed effects on employees' lives. The objective of this research was to determine which factors affect the most regrading work-life during the working from the home period. A research gap exists as a result of the lack of studies on this subject in the Sri Lankan context. This study collected data from 270 respondents who were working from home through an online self-developed questionnaire. A factor analysis model was used for data analysis. Both the working and non-working environment factors were identified as having substantial effects during the working from the home period. The unique outcomes associated with working environment factors (Working days during working from home and working time), non-working environment factors (Gender and number of children), and work-life balance factors (Depression and distress and future psychological problems), make it explicit that employers need to concentrate on providing proper prerequisites to maximize the productivity during work from home period to improve employees’ quality of life. Employers need to pay particular attention to female workers with children, skilled workers, and others who can adapt to virtual platforms. It is recommended that employers should revamp their attendance policies and produce family-friendly flexible schedules and policies. Further, conducting training programs, providing facilities to enhance employee engagement, and build strong and transparent communication channels by supporting a healthy work environment with various activities are also recommended.
Open Access
Does Working from Home Affect Work-Life Balance? A Look into the Factors that Affect Work-Life Balance
(KDU IRC 2021, 2021) Rathnaweera, D; Jayathilaka, R
The COVID-19 pandemic has triggered major social, political, and economic ramifications around the world. Amidst social mobility measures imposed to combat the spread of the virus, this pandemic was a major challenge for people in meeting their daily needs and demands of employers. These transformed work habits, moving from physical to a virtual setting, which had mixed effects on employees' lives. The objective of this research was to determine which factors affect the most regrading work-life during the working from the home period. A research gap exists as a result of the lack of studies on this subject in the Sri Lankan context. This study collected data from 270 respondents who were working from home through an online self-developed questionnaire. A factor analysis model was used for data analysis. Both the working and non-working environment factors were identified as having substantial effects during the working from the home period. The unique outcomes associated with working environment factors (Working days during working from home and working time), non-working environment factors (Gender and number of children), and work-life balance factors (Depression and distress and future psychological problems), make it explicit that employers need to concentrate on providing proper prerequisites to maximize the productivity during work from home period to improve employees’ quality of life. Employers need to pay particular attention to female workers with children, skilled workers, and others who can adapt to virtual platforms. It is recommended that employers should revamp their attendance policies and produce family-friendly flexible schedules and policies. Further, conducting training programs, providing facilities to enhance employee engagement, and build strong and transparent communication channels by supporting a healthy work environment with various activities are also recommended
Open Access
In employees’ favour or not?—The impact of virtual office platform on the work-life balances
(Public Library of Science, 2021-11-19) Rathnaweera, D; Jayathilaka, R
Social mobility and physical restrictions imposed to contain the spread of the COVID-19 pandemic have posed a severe challenge to operate under conventional nine to five work practices in a physical office setting. As a coping strategy for the survival of business, economy, and livelihoods, certain organisations were compelled to transform to virtual office platforms. This was a sudden transformation of work practices and consequently, impacting with mixed outcomes on lifestyles of workers. Given that very limited studies have shed light into the context, this study contributes immensely to fill research gap. The main objective of this study is to identify the impact of the virtual office platform on work-life balance in the Sri Lankan context. The methodology adopted for this study is quantitative. An online questionnaire to collect data was primarily distributed to employees in the virtual platform. Analysis of this study is based on three regression models and results ascertain that both working and non-working environments have highly significant impact on the work-life balance, although non-working environment has a bigger influence on work balance (Gender and no of children). Findings are useful and unique, enabling both employers and employees to adopt a focused approach to maximize the potential of virtual platforms to enhance employee well-being so that mutual benefits can be materialized.
Embargo
On The Effectiveness of Using Machine Learning and Gaussian Plume Model for Plant Disease Dispersion Prediction and Simulation
(IEEE, 2020-05-29) Miriyagalla, R; Samarawickrama, Y; Rathnaweera, D; Liyanage, L; Kasthurirathna, D; Nawinna, D; Wijekoon, J
Agriculture plays a vital role in the economic development of the entire world. Similarly, in Sri Lanka, 6.9% of the national GDP is contributed by the agricultural sector and more than 25% of Sri Lankans are employed in the field of agriculture. But the frequent fluctuations of climate conditions have caused the spread of diseases such as late blight which eventually has led to the devastation of entire plantations of Sri Lankans. To this end, this paper proposes to forecast the possible dispersion pattern and assist the farmers in identifying the possibility of the disease getting dispersed to nearby crops to provide early warning. Eventually, it leads the farmers to take precautions to save the plants before reaching a critical stage. The yielded results show that the proposed method successfully performed disease diagnosis and disease progression level identification with 90-94 % accuracy and dispersion pattern analysis.
Embargo
On the effectiveness of using machine learning and Gaussian plume model for plant disease dispersion prediction and simulation
(IEEE, 2019-12-05) Miriyagalla, R; Samarawickrama, Y; Rathnaweera, D; Liyanage, L; Kasthurirathna, D; Nawinna, D; Wijekoon, J. L
Agriculture plays a vital role in the economic development of the entire world. Similarly, in Sri Lanka, 6.9% of the national GDP is contributed by the agricultural sector and more than 25% of Sri Lankans are employed in the field of agriculture. But the frequent fluctuations of climate conditions have caused the spread of diseases such as late blight which eventually has led to the devastation of entire plantations of Sri Lankans. To this end, this paper proposes to forecast the possible dispersion pattern and assist the farmers in identifying the possibility of the disease getting dispersed to nearby crops to provide early warning. Eventually, it leads the farmers to take precautions to save the plants before reaching a critical stage. The yielded results show that the proposed method successfully performed disease diagnosis and disease progression level identification with 90-94 % accuracy and dispersion pattern analysis.