Determinant of Factors affecting Customer Satisfaction ...

Determinant of Factors affecting Customer Satisfaction: Case of the Logistics Industry in Sri Lanka

S. M. D. T. K. Egodawela, A. N. Wijayanayake*, and P.L.S. Peter

Department of Industrial Management, Faculty of Science

University of Kelaniya Sri Lanka

[email protected] [email protected]*

[email protected]

Abstract Sri Lanka is a key transshipment hub on the important East-West trade route. In terms of logistics performance, Sri Lanka ranked 94th out of 167 countries according to the World Bank's Logistics Performance Indicator (LPI) for 2018. If Sri Lanka is to exploit and leverage its positioning to its fullest potential, then it is imperative that the country must improve on its overall positioning in the index, by being competitive, improving on efficiency and being sensitive to customer needs. Improving customer satisfaction is crucial for business sustainability, and importantly act as a deterrent to prevent customer switching. Although previous research has captured the relationship between customer satisfaction and service quality through a combination of the SERVQUAL (Service Quality) or SERVPERF (Service Performance) model, there are other controllable factors that can influence this relationship. The study examines from both a service as well as the performance perspectives and incorporates other controllable factors that influence customer satisfaction. The study is based on the third-party logistics (3PL) industry in Sri Lanka. It considered all the important influencing factors and their relationships with each other in a systematic review process and was supplemented by reviews from industry experts and data inputs from 3PL customers. It was found that customer handling, tech initiation, competitive prices, and flexibility, have a significance impact over the all the dependent variables (Customer Loyalty, Switching Behavior, Customer Complaints). The results could be used by the service providers, to realign their offerings to suit the demands of its customers and help the country become a logistics hub for the region. Keywords Customer satisfaction, Third Party Logistics (3PL), Logistics management, Logistics performance, Sri Lanka

1. Introduction

Sri Lanka has significant geographic advantages that are necessary to become a major logistics hub in South Asia, lying on the important East-West trade route. Despite its underdeveloped economy, the country's total trade volume is around $ 88.9 billion (2018), making it a major hub for the region. This site is used by various shipping companies to consolidate and deconsolidate their cargo for transshipping to several destinations. Despite having those resources and location advantages, Sri Lanka was ranked 94th out of 167 countries in the World Bank’s 2018 Logistics Performance Indicator (LPI). Compared to India’s 3.18, UAE’s 3.89, Hong Kong’s 3.92, and Singapore’s 4.00, Sri Lanka has scored 2.60 on competence and quality of its logistics services. This indicates that if Sri Lanka is aspiring to become a major regional transshipment hub in the region, it should carry out continuous improvements in its logistics services, as well as make substantial investment in its infrastructure “hardware”- ports, roads, and railways. Importantly, the Government of Sri Lanka has identified that the logistics performance is an essential index in the mix of variables that it has identified, as it plans to attract foreign direct investment into the country. Customer satisfaction plays an important role in the logistics performance index. The appropriate selection of elements in the logistics performance index is important in addressing this aspect and unlocking and creating new value to the customer. This value should be understood as attracting and retaining loyal customers and as mentioned above, one of the key elements of competitive advantage as well. The effectiveness and efficiency of logistics customer service activities depend on understanding the essential components of services and providing customers with such solutions to meet their needs. Both practitioners and scholars recognize the fact that embracing corporate sustainability as well as

Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management Singapore, March 7-11, 2021

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enhancing customer satisfaction can produce several relevant business benefits, including the curtailment of customer switching behavior.

1.1 Objectives:

Although many studies have examined the determinants of customer satisfaction in various industries, there are few local and global studies to determine the important factors influencing 3PL customer satisfaction in the logistics market. The results of the study will provide 3PL providers to distinguish the important factors that have a significant impact on the satisfaction of their customers. Addressing and taking appropriate action, would enable the 3PL providers to increase efficiency, including reduction of costs as they clearly understand the customer expectations that need to be met in the delivery of 3PL services, and importantly be customer centric in-service delivery, minimizing customer change behavior. The outsourcing process for logistics companies will help 3PL suppliers and their customers to create an effective platform and atmosphere to maintain a flexible, reliable, and efficient long-term cooperative relationship and ultimately improve financial performance. of both parties. The main objective of this study is to examine the factors influencing the customer satisfaction, focusing on the 3PL logistics market. It explores both service and performance perspectives and other controllable factors affecting customer satisfaction and their impact on the third-party logistics industry in Sri Lanka and proposes a model which consists of all key influencing factors on customer satisfaction.

2. Literature Review:

Satisfaction is the feeling of joy or disappointment that people create when they compare the performance or perceived results of a product to their expectations. (Kotler, 2011). The marketing concept states that achieving business goals depends on understanding the needs and wants of the target market and achieving the desired results better than other competitors (Kotler & Armstrong, 2014). Customer satisfaction depends on the performance expected of the product by the buyer. Satisfaction is a function of the perception and impression of the customer's performance and expectations. If the performance is below expectations, the customer will not be satisfied. If the performance is as expected, customers will be satisfied. When performance exceeds customer expectations, customers are satisfied (Kotler & Armstrong, 2014). In the 3PL industry, the customer is a business. Sheikh and Rana (2012) point out that external logistics service providers are extremely useful in improving customer satisfaction as they support the integration of various processes in the supply chain using advanced technology tools some information. Lucie and Jeremi (2012) have shown that the 3PL industry can solve three problems without costly investment and increase customer satisfaction. These are quality issues that result from a lack of current or clear accountability or training in the IT system. If the company's response makes the customer happy, the customer can be loyal. On the contrary, ineffective responses disappoint customers and cause them to leave the company (Hulten, 2012). In the 3pl industry, when supply chain partners are satisfied with each other, they freely exchange information (Nyaga et al. 2010) and help them maintain and continue their relationship (Janvier-James, 2012). Cooperation leads to satisfaction and motivates business partners and customers to participate in future cooperation activities (Ramanathan and Gunasekaran, 2014). The quality of service, price and convenience of court services have a positive effect on client satisfaction (Kaura et al., 2015). Customer satisfaction turns out to be a mediating variable and is a harbinger of customer loyalty. Santouridis and Trivellas (2010) show that customer service and pricing structures, including billing systems, have a significant positive effect on customer satisfaction, which in turn has a significantly positive effect on customer loyalty. The role of conveying customer satisfaction in the quality of service and customer loyalty is also highlighted. Ganguli and Roy (2011) found that customer service has a positive and significant impact on customer satisfaction and loyalty. By keeping customer satisfaction in line with expectations, it affects customer redemption, and the customer gives word of mouth information to other potential customers about the services provided by the company (Ghalandari et al., 2012). The main research of W. Premarathne (2017) is that the “flexibility” of the 3PL provider was the most important factor in customer satisfaction, while the “customer relationships” of the 3PL provider was the second most common. important. 3PL suppliers in Sri Lanka also always include contract employees. Their lack of engagement resulted in low customer satisfaction. In accordance with the above, customer satisfaction cannot be achieved without the fundamental contribution of the customer contact agents who provide the service. Front-line workers must therefore focus on the needs of clients (Aburoub et al., 2011). Lack of control and coordination are important factors that affect customer satisfaction. Lack of control is the one major factor that reduces customer confidence in the 3PL market in Sri Lanka. Customers see the



reduction in the wait time between deliveries, the adaptation of new technologies and the number of fulfillment channels multiplied by the number of delivery options due to online sales as future challenges on the market. 3PL in Sri Lanka. Similar future challenges were also identified in the 19th Annual Third-Party Logistics Study. (Dr M.A. A. Malkanthie, J.M.D.J.N. Jayamanna, 2017)

2. Method:

Initially a literature review has been conducted to identify the studies that have been previously conducted about the 3PL services, 3PL customer satisfaction as well as the factors affecting 3PL customer satisfaction levels. Subsequently, the fundamental determinants of customer satisfaction of the 3PL industry and the logistics services and resources which need to perform those services were identified. The SERVQUAL and SERVPERF frameworks were used together, as it was apparent that a combination of both service quality and service performance was both necessary. This was combined with other factors identified as relevant for the 3PL industry. This framework is shown in Figure 1. A questionnaire based on the operationalization of the constructs of the model was used to gather information from all three 3PL service providers in Sri Lanka.

Figure 1: Variable declaration for the Methodology

The following hypotheses (in a null form) were formulated for testing based on the main route cause/problem, of the study and objectives,

HA1: There is a statistically significant impact of the overall collective dimensions (Independent variables) on customer loyalty.

HA2: There is a statistically significant impact of the overall collective dimensions (Independent variables) on switching behavior.

HA3: There is a statistically significant impact of the overall collective dimensions (Independent variables) on customer complaints.

3.Data collection:

A mixture of both a qualitative and quantitative research approach was used for this study. Based on the data collected through the questionnaire, ANOVA, factor analysis and multiple regression analysis were used to analyze the data. In



this study, performances of 3PLs are measured from the perspectives of service providers. Numerical data has been collected using a Likert scale (1=strongly disagree, 2=disagree, 3=average, 4=agree 5=strongly agree). Multiple Regression Analysis was used to identify the relationships between the customer satisfaction and the key factors. To evaluate the formulated hypothesis, three models were built which consisted of all independent variables and each of the three dependent variables. Testing model 1 consists of all the independent variables (warehouse operations, transportation operations, customer handling, flexibility, tech initiation, competitive prices, and organizational image) and Customer loyalty as the dependent variable. The relationship between independent and dependent variables have been tested using the model summary and ANOVA table which have been shown below.

Table 1: Testing model 1 using SPSS

Testing model 2 consists of all the independent variables (warehouse operations, transportation operations, customer handling, flexibility, tech initiation, competitive prices, and organizational image) and Switching behavior as the dependent variable. The relationship between independent and dependent variables have been tested using the model summary and ANOVA table which have been shown below.



Table 2: Testing Model 2 using SPSS

Testing model 3 consists of all the independent variables (warehouse operations, transportation operations, customer handling, flexibility, tech initiation, competitive prices, and organizational image) and Customer complaints as the dependent variable. The relationship between independent and dependent variables have been tested using the model summary and ANOVA table which have been shown below.

Table 3: Testing model 3 using SPSS

4. Results and Discussion:

The main objective of this study is to develop a theoretical model for interpreting factors affecting the customer satisfaction from the 3PL service provider perspective. The graphical test of linearity indicated the fulfillment of this assumption. That is there was a clear linear relationship between individual independent variables (warehouse



operations, transportation operations, customer handling, flexibility, tech initiation, competitive prices, and organizational image) and the dependent variable of customer satisfaction (customer loyalty, switching behavior and customer complaints). The results indicate a statistically significant (F value<0.05) relationship between customer loyalty, switching behavior and customer complaints with the overall dimensions on the customer’s satisfaction. Although the relationships between independent variables (warehouse operations, transportation operations, customer handling, flexibility, tech initiation, competitive prices, and organizational image) and the dependent variable has been statistically significant as proven above, the correlations can be varied. Below table 4 shows the correlations between independent variables (warehouse operations, transportation operations, customer handling, flexibility, tech initiation, competitive prices, and organizational image) and the Customer loyalty as the dependent variable.

Table 4: Correlations of testing model 1 using SPSS (Dependent variable = Customer loyalty)

Transportation operations and the Customer handling can be recognized as most correlated factors to the Customer loyalty according to the table 4. Warehouse operations and the Organizational image shows the least correlation to the Customer loyalty. Below table 5 shows the correlations between independent variables (warehouse operations, transportation operations, customer handling, flexibility, tech initiation, competitive prices, and organizational image) and the Switching behavior as the dependent variable.

Table 5: Correlations of testing model 2 using SPSS (Dependent variable = Switching behavior)

Transportation operations and the Customer handling can be recognized as positive correlated factors to the Switching behavior according to the table 5. All other factors show a negative correlation to the Switching behavior. The main reason for that is the importance of decreasing the switching behavior doe does not depend on all other independent variables (warehouse operations, flexibility, tech initiation, competitive prices, and organizational image) other than Transportation operations and the Customer handling. Below table 6 shows the correlations between independent variables (warehouse operations, transportation operations, customer handling, flexibility, tech initiation, competitive prices, and organizational image) and the Customer loyalty as the dependent variable.



Table 6: Correlations of testing model 3 using SPSS (Dependent variable = Customer complaints)

Transportation operations and the Customer handling can be recognized as most correlated factors to the Customer complaints according to the table 6. Warehouse operations and the Organizational image shows the least correlation to the Customer complaints. In order to identify the significance relationship of each independent variable the coefficient have been tested using coefficient tables which have been shown below. Table 7 shows the coefficients of model 1 which consists all the independent variables (warehouse operations, transportation operations, customer handling, flexibility, tech initiation, competitive prices, and organizational image) and Customer loyalty as dependent variable.

Table 7: Coefficients table of testing model 1 using SPSS

Table 7 shows that Flexibility and Tech initiation are the most statistically impacted independent variables of model 1(f<0.005). Table 8 shows the coefficients of model 2 which consists all the independent variables (warehouse operations, transportation operations, customer handling, flexibility, tech initiation, competitive prices, and organizational image) and Switching behavior as dependent variable.

Table 9: Coefficients of testing model 2 using SPSS Table 8: Coefficients table of testing model 2 using SPSS



Table 8 shows that Customer handling, Competitive prices and Tech initiation are the factors which have a statistically significant relationship in model 2 (f<0.005). Table 9 shows the coefficients of model 3 which consists all the independent variables (warehouse operations, transportation operations, customer handling, flexibility, tech initiation, competitive prices, and organizational image) and Customer loyalty as dependent variable.

Table 9: Coefficients of testing model 3 using SPSS

Table 9 shows that Flexibility and Tech initiation are the most statistically impacted independent variables of model 1 (f<0.005). Coefficient tables (Table 7, 8, 9) shows that though the overall relationship between independent variables and dependent variables is a linear relationship, significance of each independent variable varies. Considering above tables, it reveals that flexibility and tech initiation are the independent variables that have a linear relationship to customer loyalty and customer complaints. Customer handling, competitive prices and tech initiation are most significant factors of the switching behavior. Accordingly, flexibility, tech initiation, customer handling and competitive prices can be considered as factors which can primarily affect customer satisfaction.

5. Conclusions:

The objective of the study was to propose a model for customer satisfaction, with the focus on the 3PL sector in Sri Lanka and to quantify the intensity of relationship among the identified independent variables customer satisfaction. The study has shown that all the independent factors (warehouse operations, transportation operations, customer handling, flexibility, tech initiation, competitive prices, organizational image) influence customer satisfaction. According to the three models which have been discussed in the study, Customer loyalty can be impacted by Flexibility and Tech initiation (Table 1). Coefficients (Table 7) proves that coefficients of each independent variables are less than 0.005. It implies that flexibility of the customer service and improvements of the technology engagement will lead to the customers to continue to full fill their business needs with the same service providers. Model 2 (Table 2) implies that Customer handling, Competitive prices and Tech initiation are most affective factors to the Switching behavior (Table 8). It shows that good customer management with attractive prices and technological advancement would intend customers to switch to other service providers. Complaint handling (Table 3) mostly can be affected by Flexibility and Tech initiation (Table 9). Being flexible to customer enquiries and customer focus services using technological advancement can be led to minimize the complaints from the customers. Considering overall impact of the Customer loyalty, switching behavior and Customer complaints as Customer satisfaction, this study implies that Customer satisfaction can be affected by Flexibility, Tech initiation, Customer handling and Competitive prices of the 3pl service providers. As discussed in section one, the appropriate selection of elements in the logistics performance index is important in addressing this aspect and unlocking and creating new value to the customer. This value should be understood as attracting and retaining loyal customers. The effectiveness and efficiency of logistics customer service activities depend on understanding the essential components of services and providing customers with such solutions to meet their needs. This proposed model enables 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 behavior and switching costs, as they have a clear idea about the expectations of customers that



should be fulfilled when delivering 3PL services. Enhancing customer satisfaction can produce several relevant business benefits, including the curtailment of customer switching behavior.

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Biographies Thamara Egodawela is a final year undergraduate reading for B. Sc. (Honours) in Management and Information Technology in the Department of Industrial Management, University of Kelaniya, Sri Lanka. A dissertation is carried out as a partial fulfillment of the requirement for the degree. An abstract on the similar research was accepted for International Conference on Applied and Pure Sciences 2020.

Annista Wijayanayake received her Doctor of Engineering and Master of Engineering in Industrial Engineering and Management, specializing in Financial Engineering from Tokyo Institute of Technology Japan, respectively in 2001 and 1998. Currently she is serving as a Senior Lecturer at the Department of Industrial Management, University of Kelaniya- Sri Lanka. She had served as a honorary Research Fellow at Royal Melbourne Institute of Technology (RMIT) Australia in 2004 and as a lecturer, at the Faculty of Economics and Business and Faculty of Information Technology Monash University-Australia from 20017-2019. Also, she had served as an Academic Advisor for B.Sc. in Management and Information Technology degree programme, University of Kelaniya from 2003-2008. She won many international awards for her research and teachings. She received the academic excellence award for her Master’s degree by research by Tokyo Foundation- Japan for Inbound Students. She also received the 2019 teaching excellence award from the Department of Econometrics and Business Statistics - Monash University for her teachings. She had worked as the co-investigator of international research on unnatural deaths among women and girls in Sri Lanka, which is funded by United Nation Population fund. Her research has been featured in prestigious journals such as Mathematical Programming, International Journal of Theoretical and Applied Finance, Journal of Global Optimization and in many International Conference Proceedings. Suren Peter is a Senior Lecturer and the Head of Department of the Department of Industrial Management, University of Kelaniya, Sri Lanka. His research interests are in behavior of capital markets, privatization and corporate restructuring, portfolio management and learning. He has over 25 years of teaching, research and consulting experience has served as a National Consultant on several projects for the United Nations (UNIDO and UNDP) and been involved in consulting with several international development organizations, government, and local private sector companies. He also serves on the Board of Directors of several companies engaged in finance and leasing, microfinance, real estate development and health and fitness.



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