Browsing by Author "Jayasooriya, S"

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Embargo
Demystifying the concept of IoT enabled gamification in retail marketing: An exploratory study
(IEEE, 2020-09-24) Jayasooriya, S; Alles, T; Thelijjagoda, S
The retail landscape is evolving rapidly as firms embrace innovative technologies in an attempt to stay ahead of the aggressive competition prevalent within the industry. Gamification is one such innovative technology that has been gaining popularity in recent times. This study aims to explore the application of Gamification in the context of Retail Marketing in Sri Lanka and ultimately propose a concept for a Gamified application that can be used by customers of moderntrade retailers. The study took an exploratory qualitative approach where intensive surveys of literature and in-depth interviews with a judgmental purposive sample of seven marketing professionals in the modern-trade retail industry were conducted to determine the current play of technology in retail marketing as well as the drivers & challenges of Gamification adoption. Further, in-depth interviews with the customers of such organizations were conducted in gathering user preferences and design recommendations for a Gamified app. Thematic analysis was carried out in deriving insights. Findings show that the retail firms currently employ several technologies in line with those discussed in existing literature such as loyalty card systems, digital signage, VR technologies, online Gamification amidst others in carrying out their marketing efforts. Gamification is predominantly applied in the online context as opposed to the offline (in-store) context. Furthermore, the key drivers that propel firms to implement novel technology like Gamification are to generate customer insights, enhance customer experience and achieve marketing related KPI targets. Conversely, inadequate technology infrastructure, justifying the focus on a niche crowd of tech-oriented customers and slow ROI pose as challenges in the process of Gamification adoption. Three main themes emerged upon exploring user preferences and design recommendations for a Gamified app and are identified as information at the touch of a fingerprint, automation & integration and use of game mechanics. Ultimately by incorporating these insights gathered, a concept for a Gamified app was proposed.
Embargo
Eigenface based automatic facial feature tagging
(IEEE, 2008-12-12) Wijeratne, S; Jayawardena, S; Jayasooriya, S; Lokupathirage, D; Patternot, M; Kodagoda, N
There are several approaches to search databases of faces. However such methods still require a significant use of humans to interpret an eyewitness account and so forth. In many cases these searches are done using visual building tools as creating a graphical face model. A system that can easily interface with general users should directly search a person by description given verbally or textually. This would reduce costs in the search process. Facial feature characteristics identification would act as a stepping stone in cataloguing large face databases automatically thus providing the possibility of a description based face search by text. This paper presents the possibility of utilizing eigenface approach to recognize different characteristics of a facial feature and assigning descriptive words such as "Large", "Small" to each feature. After training the system, it would automatically attempt to match a pattern in the training set that best describes the input image and output a tag associated with it. This effectively allows an image of a person's face to be tagged by his or her feature characteristics. While utilizing the standard set steps as defined in the eigenface algorithm, slight modifications are done in the algorithm that matches input images with ones in the training set. The training set defined has a very huge impact for the final outcome, and due to the subjective nature of the training, future research would be done on this regard. The investigation showed that the method works fine with well defined features such as eyes but fails for features such as foreheads due to the lack of significant differences or characteristics between such features. Hence it is seen that while eigenface can be used for the categorization of well defined features, it is unable by itself to create a system that can cover all features of a face.
Open Access
Gross domestic product and logistics performance index drive the world trade: A study based on all continents
(Public Library of Science, 2021-03-03) Jayathilaka, R; Jayawardhana, C; Embogama, N; Jayasooriya, S; Karunarathna, N; Gamage, T; Kuruppu, N
The purpose of this study was to examine the impact of Gross Domestic Product (GDP) and Logistics Performance Index (LPI) on international trade of nations across each continent and worldwide. Secondary data collected on 142 countries—37 Asian, 41 European, 41 African, 3 Oceania, 14 Middle East, 11 North American and 9 South American–were analysed across the years 2007, 2010, 2012, 2014, 2016, and 2018. Panel regression technique was applied and the random effect (RE) model was chosen based on the results of the Hausman tests and Breusch–Pagan Lagrange Multiplier test. The findings revealed that the LPI has a positive relationship with net exports globally and specifically within the continents of Asia, Europe, and Oceania. Moreover, while the GDP appears to have a significant negative impact on net exports, specifically within Asia, in contrast, countries in Oceania and the Middle East present a positive relationship. Also on the African continent, GDP has a significant negative impact on the net exports. Findings provide a holistic picture of the impact of LPI & GDP on net exports, which will assist governments in the formulation and revision of its strategies and policies to expedite the growth of exports and in turn, the economy. This study was the first of its kind to explore the impact of GDP and LPI on international trade of nations across worldwide.