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Evaluating the Factors that Affect the Reverse Logistics Performance in Plastic Supply Chain
(Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka, 2022) Thilakarathne, H. G. K. L. S.; Wijayanayake, A. N.; Peter, S.
Reverse Logistics includes all the processes involved in moving goods from their typical final destination to recapture value or for proper disposal. This study aims to identify the factors affecting reverse logistics performance within the plastic supply chains in Sri Lanka and the identification of factors that would facilitate the enhancement of reverse logistics performance. Factors were identified through literature review and by industry experts. Factors were classified under five domains: economic and market factors, knowledge and awareness factors, policy and legislature factors, management and leadership factors, and technology and infrastructure factors. Factors were analyzed using the Partial Least Squares, Structural Equation Modelling (PLS-SEM) technique to evaluate their effect on reverse logistics performance. Results of the analysis show that the policy and legislature factors are the only significant factor to affect reverse logistic performance in plastic supply chains in Sri Lanka. All the remaining factors do not show a significant relationship with the reverse logistics performance though they show a positive correlation with the performance.
Developing a model to identify the factors affecting customer satisfaction and their impact on third party logistics services in Sri Lanka
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Egodawela, S. M. D. T. K.; Peter, S.; Wijayanayake, A.
Locating on a major east-west trade route near India, Sri Lanka has significant geographic advantages that are necessary to become a major logistics hub in South Asia. Despite its underdeveloped economy, the island country's total trade volume is around $ 88.9 billion (2018), making it a major hub for the region. A number of shipping lines use this site to, consolidate and deconsolidate cargo for transhipping to various destinations. Considering logistics performance, Sri Lanka was ranked 94th out of 167 countries according to the World Bank’s 2018 Logistics Performance Indicator (LPI). Therefore, Sri Lankan Logistics and Freight Forwarder Association has identified that the country needs to move up on the index, while providing a competitive service to the customers’ need. Both practitioners and scholars recognize the fact that embracing corporate sustainability as well as enhancing customer satisfaction can produce several relevant business benefits such as decrease of the intention to switch. Although past research captures the relationship between customer satisfaction and service quality through a combination of the SERVQUAL (service quality) model or the SERVPERF (service performance) model, however, the controllable factors may influence this relationship when considering the Third Party Logistics (3PL) industry in Sri Lanka. The model developed explores both service and performance, and other controllable factors affecting on customer satisfaction and their impact on the 3PL industry in Sri Lanka. It considered all key influencing factors and their relationship with each other using a systematic review process and complemented by reviews from industry experts. The model constructs include relationship performance as the independent variables while the impact of the 3PL industry on customer satisfaction has been measured using customer loyalty, customer switching behaviour and customer complaints which also been considered as dependent variables. Tech initiation has been recognized as a moderator variable for the operational performance and the Organizational image has been recognized as a controllable variable of customer satisfaction. The study results show that there is a statistically significant impact of the overall dimensions on the customer’s satisfaction and it implies that 8.09% of customer Loyalty depends on the above four independent variables and 18.85% of Switching Behaviour and 6.30% of Customer Complaints depends on all the independent variables. The proposed model which has verified will lead 3PL service providers, to distinguish significant factors, which have a considerable effect on the customer satisfaction. Further, the outcomes would assist the 3PL providers to minimize customer switching behaviour and switching costs, as they have a clear idea about the expectations of customers that should be fulfilled when delivering 3PL services.
Classifying risk and vulnerability in the supply chain during an epidemic outbreak
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Perera, M.A.S.M.; Wijayanayake, A.; Peter, S.
Companies always try to maximize shareholders' value by reducing the cost and maximizing profits in the long terms. However, one of the primary difficulties they face in doing so, is because of disruptions in the supply chain (SC). The supply chain can be disrupted due to natural disasters, manmade catastrophes, strikes, legal disputes, and special cases like epidemic outbreaks. The study explores what causes the supply chain to be disrupted in a company during an epidemic outbreak. It focuses on the Sri Lankan apparel industry as it contributes 6% to Sri Lanka’s GDP and 44% percent to Sri Lanka’s National Export Revenue, which is a significant proportion of the country’s economy. The primary objective of this study is to identify the supply chain risks in order to be prepared, mitigate the effects and ensure business continuity. The study proposes a model to identify the SC risks and vulnerabilities during an epidemic outbreak, and which risks should be prioritized. The model was primarily developed through a systematic review of literature and information collected from experts in the apparel sector was used to validate the findings. Leading apparel manufacturing companies in Sri Lanka were selected through convenience sampling and managers with more than five years’ experience were selected through random sampling. Using the output, the identified risks are then analysed and mapped in a vulnerability matrix considering cost and time factors. The model was tested and validated using 80%-20% rule. 80% of the collected data was used to develop the model and 20% of the collected data was used for testing and validation. Moreover, experts’ opinions were also used to validate the vulnerability matrix. Loss of local key supplier, loss of international key supplier, local port closure, international port closure, transportation link disruption (other than ports), raw materials delays and shortages, human resource shortages, product demand variations, order cancellations and lead time variations are SC risks which are considered for this study. The loss of international key suppliers and order cancellations were classified as high risks, whereas, human resource shortages were classified as the least risk. Though, a generalized vulnerability model is developed in this study considering cost and time factors, it can be customized using different factors and risks depending on the experience and needs of the company. Participants for the survey assumed that customers are international, and suppliers are both local and international. The study can be further developed to identify the SC strategies which should be taken to mitigate the SC disruptions during an epidemic outbreak or during a major global crisis.
Model for consumer purchasing behaviour of Generation Z
(4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Kahawandala, N.; Peter, S.
The free market economy and the lifting of restriction of trade across national boundaries have provided the consumer, the opportunity to choose from an increasing product range. As the consumer is spoilt for choice, manufacturers face intense competition to catch the attention of the discerning customer. Generation Z consumers have been identified as unique as they are the first generation of digital natives who are born with digital chromosomes in their DNA. Therefore, this segment of the market differs in their characteristics, needs, attributes and work style from other generations. Their influence and economic power are expected to increase rapidly and their buying power is currently estimated as more than $44 billion. They spend approximately a quarter of their time online, but are known to selectively filter this digital information first, before making the purchase decision. In order to cater their demands with a proper strategy, it is important to investigate the determinant factors of these buyer’s, characteristics and actions. Although there are models like Technology Acceptance Model; theory in information system and theory of reasoned action; theory in social psychology which has been used previously to investigate purchasing behaviour, their ability to factor the unique characteristics of this market segment is questionable. The purpose of this paper is to develop and test an extended research model based on the Theory of Planned Behaviour (TPB) that identifies factors influencing the purchasing behaviour of generation Z. TPB is a well-known psychological theoretical framework which links one’s beliefs and behaviour. It states that attitudes towards behaviour, subjective norm, and perceived behavioural control together shape an individual’s behavioural intentions. The proposed extended model of TPB incorporates the additional constructs of market mavenism, technology self-efficacy and social identity to capture the specific characteristics of the Generation Z. Expert opinion from selected personnel in academia and industry were used to validate the proposed model. Implications of this validated model can be utilized to assist in predicting potential consumer adoption behaviour and in designing favourable shopping environments that are compatible with these specific consumer traits
Supply chain risk assessment model for a small scale apparel manufacturer
(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Erandi, M.P.H.; Peter, S.
The adoption of free trade, and advances in communication and information technology and transport systems have propelled globalization of trade. Local supply chains have rapidly become complex intertwined international supply chains, facilitating efficient manufacture at very competitive rates. However, this benefit is somewhat offset by the increased risk of the complexity of such supply chains. Any disruption to them will have a major ripple effect beyond the initial direct user and have a crippling effect on the company and the national economy. Supply Chain Risk Management (SCRM), has focused on developing models and frameworks using varying techniques and tools. As a risk, it is very contextually dependent, it is a necessity to analyze risks related to different industries and organizations. The objective of this study was to develop a framework to assess supply chain risks, through a case study of a small scale Sri Lankan apparel manufacturer. A modified version of Risk Numeric Analysis model is used as the basis for developing the framework. Initially, supply chain risks were identified from the literature, using a cause and effect diagram. These risks were then narrowed down with the use of industry expertise from the apparel sector. Then, the risk assessment phase was conducted with the Analytical Network Process (ANP) as the tool. The output revealed a list of risk factors with the most critical risk at the top. The critical risk factors identified were supplier quality problems, human errors, referring to one supplier and lack of production flexibility. These factors were used to calculate a total risk score for the customer order in consideration, with reference to the output from ANP and the relevant probabilities of risks. The initial validation of the framework was done using two contrasting customer orders. i. e. successful versus unsuccessful order. The developed framework was able to discriminate the two orders with varying risk scores, making it a viable and effective methodology for assessing risks in supply chain in the apparel industry.
Evidence of maturing of the Colombo Stock Exchange: Informational efficiency perspective
(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Upeksha, P.G.S.; Peter, S.
Due to the dynamic nature of capital markets, understanding the informational efficiency of financial markets has become crucial for investors. An implication of an efficient market hypothesis is that no excess returns can be gained from available information, since it is believed that information is priced already in the stock. The objective of this study is to assess market efficiency of the Colombo Stock Exchange (CSE) in Sri Lanka, which is one of the emerging markets in the world. In order to test for weak form efficiency, stationarity of the selected time series is tested using Augmented Dickey-Fuller test. Sri Lanka stock market as a whole and the top three sectors with the highest market capitalization, exhibit random walk processes. Event study methodology is used to assess semi-strong efficiency. Preliminary analysis using both market model and GARCH model revealed that information disclosure of the selected companies has no significant impact on the returns in the CSE as a whole or on the returns of the particular sector.
Consumer behavior models and microfinance in Sri Lanka: A systematic review of literature.
(International Research Symposium on Pure and Applied Sciences, 2017 Faculty of Science, University of Kelaniya, Sri Lanka., 2017) Senasinghe, V.; Peter, S.
Study of consumer behavior helps enterprises understand the psychology of the customers on how they make their purchase decisions. The objective of this paper is to present a comprehensive review of the literature on the models of consumer behavior. The studies on consumer behavior and consumer decision making have developed various theories and models to explain the consumer behavioral patterns. There are two types of cognitive models that are widely used. Analytical models provide a framework of the key elements that are purported to explain the behavior of consumers and prescriptive models provide a framework to organize how consumer behavior is organized. The theory of buyer behavior is an analytical model and it provides a sophisticated integration of various social, psychological and market influences on consumer decision making. There is, however, widespread questioning of the model’s validity due to the lack of empirical work. In the consumer decision model, many of the elements are similar to those presented in the buyer behavior model. However, the structure of presentation and relationship between the variables somewhat differs. The model is also critiqued to be too restrictive to adequately accommodate the variety of consumer decision making situations. Theory of reasoned action is a prescriptive model and it is a further development of the Fishbein model which proposed that a person’s overall attitude toward an object is derived from his beliefs and feelings about various attributes of the object. Theory of planned behavior which is an extension of theory of reasoned action is developed including an additional mediating variable between intentions and behavior. The model of goal directed behavior can be described as humanistic in its approach as it seeks to explore concepts introspective to the individual consumer rather than describe generic processes. Microfinance relates to the provision of financing to those traditionally unable to obtain funds due to lack of formal income sources. Due to the mushrooming of companies offering the product due to the low default and the high interest rates charged, assessing risk behavior of these customers have become critical. Misuse of the product may cause the entire industry to fail and deprive legitimate customers from obtaining much needed finance to uplift their economic status. In the literature, there are no models relating to the customer risk behavior in microfinance. Therefore, the general consumer behavior models are used to try and explain customer risk behavioral patterns in the microfinance. Though the contexts differ in these two instances, since the loans could also be considered as products and a customer is involved, the models used in consumer behavior are assumed to depict the same type of behavior in the microfinance industry as well.
A multi-pronged approach to assess informational efficiency of the Colombo Stock Exchange.
(International Research Symposium on Pure and Applied Sciences, 2017 Faculty of Science, University of Kelaniya, Sri Lanka., 2017) Upeksha, P. G. S.; Peter, S.
With the dynamic nature of the capital market environment, understanding informational efficiency of financial markets has become crucial. Efficient market is one in which prices fully reflect the available information. An implication of an efficient market is that no excess returns can be made from the available information, since it has already been reflected on the current prices. Efficient markets where information can be trusted, channeled to market participants, absorbed and reflected in the stock prices, are important characteristics that global investors look for when deciding to invest, especially in the emerging markets. The objective of this study is to assess the market efficiency of the Colombo Stock Exchange (CSE), Sri Lanka, which is one of the emerging markets in the world. In the post millennium period, a number of studies that have assessed market efficiency at the CSE. However, after the end of the Sri Lankan civil war, the economy underwent dramatic change with the indices showing rapid growth and achieving new heights. Therefore, due to the difference in the sentiment and behavior of the market and investors post conflict, it would be prudent to review whether the results seen previously for weak form and semi-strong form of efficiency still holds. In order to test for weak form efficiency, existence of any correlations of share returns are evaluated. This is done by testing the autocorrelation nature of the selected time series. In order to assess semi-strong efficiency, ‘Event study’ methodology is applied. In event study, the following approaches have been used to derive the abnormal returns. Arbitrage Pricing Theory (APT) Model is a multifactor model. It permits the researchers to choose the best factors. However, it cannot explain variation in asset return in terms of a limited number of easily identifiable factors. Capital Asset Pricing Model (CAPM) accounts for systematic risk. However, it imposes an additional restriction (the intercept equals the risk-free rate) that the variance of the error will be larger than in the market model. Market Model is the vastly used and widely accepted method in short return windows in the event studies. Market Model usually outperforms CAPM. GARCH Model estimates volatility. It is a preferred method because, with asset returns volatility seems to vary during certain periods of time. It further aims to minimize errors in forecasting by accounting for errors in prior forecasting, enhancing the accuracy of ongoing predictions. Taking into consideration the context of the local stock exchange, market participation, and institutional activity, two alternative methods were identified to derive the abnormal returns, i.e. Market Model and GARCH Model. The study expects to use dividend announcements as the primary informational source, and it is expected to identify whether evidence of abnormal returns is shown after the announcement, in order to determine whether CSE is semi-strong efficient.
Customer perceived quality management practices and organizational performance: Case of private healthcare sector in Sri Lanka.
(International Research Symposium on Pure and Applied Sciences, 2017 Faculty of Science, University of Kelaniya, Sri Lanka., 2017) Sowmiya, B. A.; Peter, S.
Quality in a healthcare organization is three dimensional: patient quality is what patients say they want, professional quality is what professionals believe patients need (outcome and process), and management quality is the optimisation of resources to provide patients what they want and need, without waste, errors or delay, and within the policy and legal regulation. Therefore, Patient perceived quality is the overall service quality of healthcare organization. Perceived service quality is the customer’s judgment about the service’s overall excellence, based on perceptions of what is received and what is given. Most studies on quality however, have focused on the manufacturing with relatively less focus on the service sector. In Sri Lanka, private healthcare services have flourished with even the middle to lower income people patronizing their services. This growth has had a positive effect on public healthcare service in raising their standards and service level from what they were previously. The study investigates the impact of customer perceived quality management (QM) practices on organizational performance in selected private healthcare providers. The study assesses the extent to which customer perceived QM components have been implemented in these hospitals and to identify which of these customer perceived QM components are associated with improvement of performance at these hospitals. The study was restricted to the Western Province which the Private Health Services Regulatory Council reveals has over 40% of the private hospitals in the country. Hence, the sample included a total of eight healthcare service providers which comprised some of the leading healthcare providers in Colombo. Many previous studies have focused on the customer-perceived quality in services. Parasuraman in his study on customer-perceived quality, reduced the original ten factors that he identified to five: tangibles, reliability, responsiveness, assurance, and empathy. This SERVQUAL model has been successfully used to assess quality in the services industry including the healthcare sector. In general, many studies have found the application of SERVQUAL to be reliable in the health-care context. This study used the SERVQUAL model as a basis to assess the private healthcare sector in the country. It should be noted that interpretation and operationalization of some of the variables were adjusted to suit the local context. Dimensions of SERVQUAL model, reliability, responsiveness, assurance, empathy and tangibles were assessed while performance was measured using both financial as well as non-financial indicators. The study found significant evidence to establish a relationship between customer perceived QM components and organizational performance of healthcare firms. The regression analysis results suggest that customer perceived QM components, reliability, responsiveness, assurance, empathy and tangibles all contributed to the improved performance. The results of the study can be used by hospitals to better understand customer needs and thus enhance the levels of patient satisfaction.
A conceptual framework to assess supply chain risk in the apparel industry.
(International Research Symposium on Pure and Applied Sciences, 2017 Faculty of Science, University of Kelaniya, Sri Lanka., 2017) Erandi, H.; Peter, S.
Along with the advent of globalization and the championing of free trade together with improved communication and transportation systems, enterprises have the ability to source supplies from a globally distributed supply chain. However, on the flip side, due to the complexities in dealing with a dispersed network of suppliers, manufacturing companies are facing risks of disruption to their supply chains. As risk is very context dependent, it is important to identify supply chain risks in different contexts and industries. Sri Lankan apparel industry plays a major role in the country’s economy, making it vital for companies to engage in proper identification and assessment of these risks. Therefore, the objective of this study is to conceptualize a model to assess identified supply chain risks and thereby to generate an overall risk assessment score for an apparel manufacturing company. The initial base for risk identification is through the use of the Ishikawa model. The cause and the effect for supply chain risks were established by analysing the initial data collected and via industry experts, a list of risk classes and sub classes were formed. Thereafter, a modified version of risk numeric analysis model is used to setup each and every class weight where industry experts’ opinion is taken for calculating the appropriate weights. Instead of using Analytical Process Hierarchy (AHP) which was used in the original model, Analytical Network Process (ANP) is used to prioritize the identified risk classes. The decision to use ANP is due to its ability to consider the complex inter relationships and linkages between risk classes and sub classes during the prioritization process. Finally, an aggregate score is developed for the overall company in terms of the supply chain risks by using the scores obtained for each risk class. The model will highlight the different types of supply chain risks that an apparel manufacturing company may face and how a proper mechanism can be developed to quantify these risks. The model would facilitate the company to directly identify the magnitude of each and every supply chain risk and the risk distribution via the overall risk score of the company. The risk score can be used by managers as a flag or an indicator that signals the company about potential risks. Apart from that, this model can be used to compare historical figures to monitor and evaluate the overall risk scores of the company. Furthermore this risk score can be used to compare the company performance with other competitors’ score values and to analyse how competitive the company is within the industry.

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