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\title{Usage of Business Analytics and Supply Chain Performance -An Empirical Study of Sri Lankan Apparel Sector}
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             \author[1]{Lakpura  D.D}

             \author[2]{Anuththara  K.H.G.M}

             \author[3]{Hansika  P.P.G.C.N}

             \author[4]{Fernando  K.E.H}

             \author[5]{Ranjiva  Munasinghe}

             \author[6]{Madhavika  W.D.N}

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\date{\small \em Received: 15 June 2021 Accepted: 4 July 2021 Published: 15 July 2021}

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\begin{abstract}
        


Advances in technology and innovation require companies to embrace these new trends to compete and stay ahead in the business world. In particular, there is a need for companies to incorporate Business Analytics practices within their organizations. Business Analytics consists of two components: Information Systems and Business Process Orientation. This study aims to investigate the impact of the use of Business Analytics on the Supply Chain Performance in apparel companies in Sri Lanka. This research focuses on discussing the objectives developed to achieve the purpose of the study. To achieve this objective, this current study investigates the relationship between the Information System, Supply Chain Performance and the effect of the use of the Information System in the supply chains of Sri Lankan apparel companies. The study uses a quantitative approach. In this study, for quantitative analysis study performs regression analysis and decision tree analysis. This study identifies a positive relationship between the Information System and the Supply Chain Performance. For further future studies, it is advisable to extend this study by examining the performance of medium-and large-scale companies in the country.

\end{abstract}


\keywords{business analytics, supply chain performance, information system}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
usiness Analytics (BA) provides a strong foundation for organizations to gain a competitive advantage through 1) cost reduction, 2) improving the operations, and 3) automating business activities, which lead towards the achievement of the organizational objectives. BA methods help to retrieve and analyze large volumes of data, which facilitates strategic decision-making. The adoption of BA practices gradually transforms the current business world \hyperref[b32]{(Shao et al., 2018)}. BA is an umbrella concept, which consists of two components: Information Systems (IS) and Business Process Orientation (BPO) \hyperref[b38]{(Trkman et al., 2010)}.This research intends to study the role of BA and their usage on Supply Chain Performance (SCP) in Sri Lankan apparel companies, examined from the point of view of the company employees. In particular, we focus on the relationship of IS on SCP. With the advances in technology and innovation, the necessity to incorporate BA practices has increased within the business world in particular; this is true for the Sri Lankan garment industry, where there is a lot of intense pressure and competition \hyperref[b40]{(Weeratunge, 2017)}.\par
Previously there are several studies conducted in Sri Lanka regarding SCP and its importance towards the country's economy. To the best of our knowledge, there have not been any studies on the role of BA on SCP within the Sri Lankan context. We aim to address this gap with this research. 
\section[{a) Problem Statement}]{a) Problem Statement}\par
The garment industry in Sri Lanka is one of the main contributors to industrial production, foreign exchange earnings, and employment. In 2006, the textile sector was considered the country's key foreign exchange earner: USD 2.97 billion, which was around 45\% of the country's export revenues \hyperref[b40]{(Weeratunge, 2017)}. In 2008, the clothing industry contributed 40\% of the industrial production of the country and was the largest contributor to the economy with 8\% of the Gross Domestic Production (GDP).Recently, Sri Lanka's share of foreign exports has declined due to the GDP.Sri Lanka faced a decline in its total export earnings in 2012. The increase in the trade deficit in 2011 and 2012 is explained by the performance of the export market \hyperref[b18]{(Kelegama, 2013)}. Based on the existing research, the supply chain in the apparel sector faces critical competitive threats in the volatile market. Designs are changing rapidly in the apparel industry, and suppliers use the lawfulness strategy to maintain their competitiveness in the market \hyperref[b40]{(Weeratunge, 2017)}.\par
The industrial sector of Sri Lanka marked a significant drop of 3.2\% in 2019 compared to 2018. The majority of the plunge was accounted from the apparel sector while the other sectors (Agricultural and Rubber Products) managed to retain their performance. The primary reasons identified for this fall arethe low-quality of products and the high cost of production \hyperref[b11]{(Dheerasinghe, 2009)}. A decline of 50\% is predicted from the apparel sector during the coming quarterdue to the global pandemic situation occurred, which led to a pause in operations in the apparel sector. With the prevailing situation in the country, it is expected to have an export decline of 30\% in 2021 \hyperref[b29]{(Rodrigo, 2020)}.The recent statement released by the Chairman of Joint Apparel Association Forum, A. Sukumaran, states that a 1.5 billion dollars of exports are to contract within the coming months. In 2019, apparel sector records a decline with their contribution. Further, the viral outbreak aroused in 2020 had a significant impact on the country's day-to-day activities. It severely affected the apparel sector operations, which led to a downfall of its performance furthermore. 
\section[{b) Scope of the Study}]{b) Scope of the Study}\par
The scope generalizes the use of BA methods, in particular, IS to increase the efficiency of the supply chain by reducing high costs and improving the quality of manufacturing products relative to the foreign market. The study investigates the relationship between IS and SCP, and its effect on SCP. 
\section[{c) Significance of the study}]{c) Significance of the study}\par
As highlighted in the introduction, there has not been any work done previously about the use of BA in the Sri Lankan Apparel Industry, which looks at the employee perception of BA. In particular, this study aims to look at the usage of BA in terms of the IS and BPO components and its impact on SCP. As per the third objective developed, this current study examines the relationship of IS on SCP from the perception of employees in depth.\par
In the Sri Lankan context, apparel manufacturers are exploring new IS to compete with global market competitors in the export sector. A few international academic studies investigated on the usage of IS and its impact on SCP. The findings in these articles lay out the broad and deeper understandings of the effect of IS on SCP and how to improve the supply chain operation. The current literature indicates that supply chains in the garment sector have to face competitive and critical challenges in a very volatile market \hyperref[b40]{(Weeratunge, 2017)}. Apparel companies have rapidly evolved to maintain competitiveness using IS and the new technologies \hyperref[b40]{(Weeratunge, 2017)}. Coordinating IS to manage SCP must result in improving the performance of the supply chain, which deliver (high quality) new choices of garments at a rapid replacement cycle \hyperref[b20]{(Kincade et al., 2001)}. Also, researchers should study how IS has an impact on each SCP area, which leads toward the advancement of the apparel sectors SCP \hyperref[b38]{(Trkman et al., 2010)}. Our research will help assess the role and impact of BA, specifically the IS component, in SCP for Sri Lankan apparel companies. 
\section[{d) Research Questions e) Research Objectives}]{d) Research Questions e) Research Objectives}\par
The objectives developed for the research are as follows: 
\section[{Primary Objective}]{Primary Objective}\par
To determine the overall effect of BA on SCP from the perception of employees in Sri Lankan apparel companies. 
\section[{Sub-Objectives}]{Sub-Objectives} 
\section[{II.}]{II.} 
\section[{Literature Review a) Business Analytics}]{Literature Review a) Business Analytics}\par
BA is an application of various advanced data analytical techniques to answer questions or solve problems related to Supply Chain Management (SCM). BA is not a technology, but a set of strategic approaches, organizational procedures, and tools used in combination with each other to gather information, analyze that information and predict the outcomes of the problem as solutions related to the four areas of the Supply Chain Operations Reference (SCOR) Model (Plan, Source, Make, Deliver) \hyperref[b38]{(Trkman et al., 2010)}. Monitoring and optimizing the SCP has been a progressively complex activity. It involves several management processes, such as the selection of measures, the definition of goals, preparation, communication, monitoring, reporting, and feedback.Thus, an approach based on conventional wisdom in the decision-making withinthe supply chain makes it impossible to manage the use of benchmark or better business practices of the supply chains. Therefore, data analytics becomes the backbone of decision-making in all business practices. Likewise, in supply chain, as accurate decision-making is dependent on large volumes and quantities of external and internal data, facilitated by BA. This ensures and enables the study of gathered data in large capacities \hyperref[b27]{(Nyamasege and Oteki, 2015)}. 
\section[{b) Information System}]{b) Information System}\par
IS plays a vital role in BA, and IS has an impact on SCP \hyperref[b28]{(Ravichandran et al., 2005)}. Also, companies benefit from the use of IS to increase their effectiveness of cost. However, the implementation of IS should be more closely related to the firm's strategies  {\ref (Fairbank et al., 2006)}. Bourgeois (2014) states IS as a set of interlinked components in an operational chain that gathers, processes, stores, and exchange information to support the effective decision-making process, which systems are facilitated through analysis and graphical visualization. Moreover, IS is define as a combination of RQ 1 -What is the relationship of employees' perception about the role of IS on SCP? compilation, storage, and processing of information and dissemination of information within the organization \hyperref[b38]{(Trkman et al., 2010)}. The processes involved with IS includes various information technologies such as computers, applications, databases, networking networks, the Internet, and mobile devices. Some performs various functions to interact with and to inform people in different operational or social contexts \hyperref[b4]{(Boell and Cecez-Kecmanovic, 2015)}. IS evaluates big data in the company using the systems and is the most efficient tool for improving efficiency and achieving difficult outcomes. The use of IS enhance the capability of the internal information processing of the enterprise. 
\section[{c) Supply chain performance}]{c) Supply chain performance}\par
The reasons for the drop in global exports (and thus of its contribution to the Sri Lankan GDP as a percentage) stated by the past studies are; 1) the quality of the operations and 2) the performance in the supply chain of the companies \hyperref[b40]{(Weeratunge, 2017)}. Competition is high, with exporters needing to deliver high-quality products at lower prices, thus placing a lot of pressure on the operations and SCP \hyperref[b40]{(Weeratunge, 2017)}. According to Cousin's strategic supply wheel model, there are several financial and non-financial factors affecting the SCP of the companies (Cousins et al., 2007). Tracing and improving the performance of a Supply chain has become an increasingly complex task for which BA is one of the current trending solutions. Most of the businesses within the world use BA as a bridge to seek solutions for their problems and investigate new ways to gain a competitive advantage \hyperref[b12]{(Flynn et al., 2016)}. According to the globally conducted studies, a positive relationship is observed and analyzed between BA and SCP \hyperref[b38]{(Trkman et al., 2010)}. BA can help with the following factors  {\ref (Wachira,}  BA improves the quality of the supply chains through proper integration and collaboration. BA deployment enables the management of large volumes of data \hyperref[b23]{(Mithas et al., 2011)}, thus allowing to make the supply chain activities within the company more productive and effective. BA facilitates knowledge sharing and strategic decision-making, which reduces the operational cost and helps in identifying the proper market trends of the industry \hyperref[b16]{(Hedgebeth, 2007)}. 
\section[{III.}]{III.} 
\section[{Conceptualization Framework}]{Conceptualization Framework}\par
The conceptualization framework describes the research objectives by interpreting the interaction between BA and SCP with their dimensions derived from past literature. BA functions as an independent variable, while SCP acts as a dependent variable. The BA dimension is IS, and SCP has six dimensions, which include efficiency, goal achievement, cost reduction, flexibility, product quality, and customer satisfaction.   
\section[{Hypotheses}]{Hypotheses}\par
The hypotheses tested in this study are;\par
V. 
\section[{Data and Methodology of the Study}]{Data and Methodology of the Study}\par
This research study used a deductive approach since the study constructed hypotheses at the beginning. The sample consists of eight key players out of the thirteen key players listed in the apparel sector in the EDB report published in the Industry Capability Report in January 2020. This current study uses the total number of supply chain professionals in each sample company in deciding the number respondents for the data collection. The design proceeds with both quantitative based on primary and secondary data sources. The study conducted surveys for the data collection. Due to the current Covid-19 pandemic situation, the questionnaire sent via e-mail to the respondents. The Krejcie and Morgan sampling technique facilitated in selecting the number of respondents of each sample company. The study utilized SPSS version 25 and R software for quantitative data evaluation.\par
The study began with a pilot study to assess the reliability and validity of the data collected. Therefore, the study used Cronbach's Alpha in achieving this purpose. The application of the decision tree analysis, the regression analysis in the research achieved the quantitative analysis objectives. The study conducts binary logistic regression since the data obtained are categorical and ordinal. The dependent variable related questions are categorical, that is, "Yes or No" questions. Therefore, the responses are categorical. Independent variables consist of symmetrical one to five Likert scale questions. It consist of ordinal responses. The Likert scale degrees are as follows;1 -? Extremely Disagree 2 -? Disagree 3 -? Neutral 4 -? Agree 5 -? Extremely Agree VI. 
\section[{Results and Discussion}]{Results and Discussion} 
\section[{a) Decision Tree Analysis}]{a) Decision Tree Analysis}\par
The decision tree analyses the best predictor of the independent variable IS, with each question inside the six dimensions of the SCP. Binary regression analysis measures the impact of IS on SCP. The rattle () package in R software performed the decision tree analysis. Figure 2 shows the best predictors resulted from the decision analysis;    The alpha value in determining the significance is 0.05. If the Significant coefficient is less than the standard significant coefficient, which is the P-value, the hypothesis is true and if the coefficient result is higher than the standard significance value, then the observation is false. 
\section[{IS1-IE}]{IS1-IE}\par
According to the chi-square test allocation, the p-value of IS and IE is 0.002. It concludes that the relationship between IS and IE is significant, since the pvalue between IS and the selected question (IE) through the decision tree is smaller than the alpha value of 0.05. This concludes that the organizations IS currently supports the supply chain process, and it significantly increased the efficiency of the supply chain of the company. 
\section[{IS2 -QG}]{IS2 -QG}\par
The p-value of IS and QG is 0.007. Therefore, there is a significant relationship between IS and QG since the p-value of IS and the selected question (QG) is lesser than the alpha value of 0.05. The organizations IS currently supports the order commitment process, and it is significantly increases the quality of goods produced in the company. 
\section[{IS3 -CR}]{IS3 -CR}\par
The P-value between IS and CR is 0.001, which is lower than the standard alpha P-value therefore, there is a significant statistical relationship between IS and cost reduction in the supply chain. In other words, the proper distribution management within the production with the use of IS reduces the supply chain cost. 
\section[{IS4 -GA}]{IS4 -GA}\par
0.000 is the P-value between IS4 and GA; this is lower than the alpha value. Therefore, there is a significant relationship between IS4 and GA. The use of IS will facilitate for the goal achievement of the company. When the process of making aligns well with IS, the goal achievements boosts as the manufacturing process is organized and integrated with the technology, which prevents the possible faults and risks in the operations. 
\section[{IS5 -F}]{IS5 -F}\par
According to the chi-square test allocation, the P-value of IS and F is 0.000. This concludes a statistical relationship between IS and F since the P-value of IS and the selected question (F) across the decision tree is smaller than the alpha value of 0.05. Finally, we can assume that the IS support source process, and it significantly increased the flexibility. 
\section[{IS6 -CS}]{IS6 -CS}\par
According to the chi-square test allocation, the p-value value of IS and CS is 0.000. There is a significant relationship between IS and CS since the Pvalue of IS and the selected question (CS) across the decision tree is smaller than the alpha value of 0.05. Finally, we can assume that IS currently supports the demand management process, and it significantly satisfy the customers.\par
All dimensions under SCP are significantly improves with the implementation of IS within the supply chain of the apparel company. Thus in the end, we can accept the first hypothesis that is there is a significant relationship between IS and SCP. Binary logistic regression analyzed the impact of independent variables on the dependent variables. This resulted in a positive impact resulted from the independent variable towards each dependent variable through binary logistic regression analysis performed. Omnibus tests of model coefficients interprets that a significant improvement of each dimension of SCP with the use of IS in the company's supply chain. Further, this model shows a good fit in the data; since R2 in model summary tables of each variable is lying between 0\%-100\% and is having a higher value; it indicates that the models are a good fit for the data collected. Finally, the regression coefficient implies that when the independent variable (BA) increased by a unit, the ( ) 
\section[{c) Impact from BA on the Dimensions of SCP}]{c) Impact from BA on the Dimensions of SCP} 
\section[{H}]{H}\par
Year 2021 H 2 -There is an impact from BA on each dimension of SCP from employees' perception. This (RQ 2 ) research objective discusses and explains the findings of the data collected from the survey with the use of binary logistic regression. Further, the objective analyzes how well IS could be used to improve the SCP of apparel companies. dependent variable (SCP) increased by a unit. The summary table in table 2 indicates the coefficients of regression. Therefore, it concludes that there is an impact on each dimension of SCP from employees' perception of IS, which is the second hypothesis of the study.\par
The use of IS in the supply chains facilitates to increase the efficiency, improve the quality of goods, reduce the cost in the supply chain, for higher and effective goals achievement, improve flexibility, and to improve customer satisfaction. The favorable impact on these dimensions shows an improvement in the supply chain of apparel companies. Since IS is a dimension of BA, a tool used to measure BA, it concludes a higher SCP with the use of BA within the supply chains. This facilitates the improvement in SCP while turning the declining nature of exports to a boost in the exports.\par
Through the achievement of each sub-objective and answering all the research questions, at the end achieves the primary-objective, that is to determine the overall employees' perception about the role of BA on SCP among the Sri Lankan large-scale apparel companies. There is a positive perception on the role of BA on SCP. Adding more to it, the use of BA in the supply chain has a positive relationship. The use of BA increases the SCP of the organization through increasing the efficiency, reduction in cost, improving the quality standard of the goods produced, which are the financial dimensions of SCP. The non-financial aspects lead to the improvement of SCP as well, and they are improved goals achievement, customer satisfaction, and flexibility. 
\section[{VII.}]{VII.} 
\section[{Summary and Discussion of Future Research}]{Summary and Discussion of Future Research}\par
As an umbrella concept, BA helps to improve the SCP of apparel firms in Sri Lanka. Based on the analysis undertaken in Sri Lanka using eight sample companies from the thirteen apparel companies identified in the industrial report published by EDB at the end of January 2020.The sample consists of key players in the apparel industry in Sri Lanka. The Integration allows companies to increase their production and productivity, contributing to success in the supply chain of firms. The current study is a discussion on the effect of IS on SCP in detail. Quantitative analysis is use to test the hypotheses and to achieve the objectives set for the current study on the basis of the hypotheses and objectives set for the present study. This quantitative analysis discusses and shows the use of IS had a positive effect on SCP. It also concludes an improvement in performance by integrating the supply chain with BA. The authors suggests further research to determine the efficiency of the supply chain by using medium and small apparel firms in Sri Lanka as a whole.\par
Further, to explore whether BA could even improve SCPs in other sectors.\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-3.png}
\caption{\label{fig_1}}\end{figure}
     \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.020066585956416465\textwidth}P{0.06688861985472155\textwidth}P{0.7285714285714285\textwidth}P{0.034473365617433416\textwidth}}
Variable\tabcellsep Dimension\tabcellsep \tabcellsep Que stion\\
\tabcellsep IE1\tabcellsep \multicolumn{2}{l}{Reduced lead time in manufacturing}\\
\tabcellsep IE2\tabcellsep \multicolumn{2}{l}{Improve Resource Planning ability}\\
\tabcellsep IE3\tabcellsep \multicolumn{2}{l}{Increase operational efficiency}\\
\tabcellsep IE4\tabcellsep \multicolumn{2}{l}{Increased efficiency of distribution planning}\\
\tabcellsep QG1\tabcellsep \multicolumn{2}{l}{Quality of goods delivered has improved}\\
\tabcellsep QG2\tabcellsep \multicolumn{2}{l}{Decreased supplier rejection rate}\\
\tabcellsep QG3\tabcellsep \multicolumn{2}{l}{Market share has increased}\\
\tabcellsep QG4\tabcellsep \multicolumn{2}{l}{Increased ability to respond to and accommodate new}\\
\tabcellsep CR1\tabcellsep \multicolumn{2}{l}{Decreased operational cost per operational hour}\\
\tabcellsep CR2\tabcellsep \multicolumn{2}{l}{Inventory carrying out cost has decreased}\\
\tabcellsep CR3\tabcellsep \multicolumn{2}{l}{Improve Cost effectiveness of products}\\
Dependent (SCP)\tabcellsep CR4 GA1\tabcellsep \multicolumn{2}{l}{Total cost of distribution, including transpor tation and handling Profitability has increased}\\
\tabcellsep GA2\tabcellsep \multicolumn{2}{l}{Return on investment has increased}\\
\tabcellsep GA3\tabcellsep \multicolumn{2}{l}{Market share has increased}\\
\tabcellsep GA4\tabcellsep \multicolumn{2}{l}{Our company can quickly introduce new products, new}\\
\tabcellsep F1\tabcellsep \multicolumn{2}{l}{Has a higher flexibility of service systems to meet particular}\\
\tabcellsep F2\tabcellsep \multicolumn{2}{l}{Increased flexibility in ope rational plans}\\
\tabcellsep F3\tabcellsep \multicolumn{2}{l}{Adjust delivery capacity/ capability and quickly respond to}\\
\tabcellsep F4\tabcellsep \multicolumn{2}{l}{Improve responsiveness to changing market needs}\\
\tabcellsep CS1\tabcellsep \multicolumn{2}{l}{Improvement of rapid handling of customer complains}\\
\tabcellsep CS2\tabcellsep \multicolumn{2}{l}{Our company can quickly modify products to meet our major}\\
\tabcellsep CS3\tabcellsep \multicolumn{2}{l}{Our company has an outstanding on time delivery records to}\\
\tabcellsep CS4\tabcellsep \multicolumn{2}{l}{Our company provide a high level of customer's services to}\\
\tabcellsep IS1\tabcellsep \multicolumn{2}{l}{Organization's Information System Currently suppor t the}\\
\tabcellsep IS2\tabcellsep \multicolumn{2}{l}{Organization's Information System currently suppor ts the order}\\
Independent (IS)\tabcellsep IS3 IS4\tabcellsep \multicolumn{2}{l}{Information System suppor ts the distribution management The Information System currently supports the process (Make)}\\
\tabcellsep IS5\tabcellsep \multicolumn{2}{l}{The Information System support this process (Source)}\\
\tabcellsep IS6\tabcellsep \multicolumn{2}{l}{Information System currently suppor t the demand management}\\
\tabcellsep \multicolumn{2}{l}{Variables}\tabcellsep Significance value (P-value)\\
\tabcellsep \tabcellsep IS1-IE\tabcellsep 0.002\\
\tabcellsep \multicolumn{2}{l}{IS2-QG}\tabcellsep 0.007\\
\tabcellsep \multicolumn{2}{l}{IS3-CR}\tabcellsep 0.001\\
\tabcellsep \multicolumn{2}{l}{IS4-GA}\tabcellsep 0.000\\
\tabcellsep \tabcellsep IS5-F\tabcellsep 0.000\\
\tabcellsep \multicolumn{2}{l}{IS6-CS}\tabcellsep 0.000\end{longtable} \par
 
\caption{\label{tab_0}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.17641509433962266\textwidth}P{0.25660377358490566\textwidth}P{0.14834905660377357\textwidth}P{0.2686320754716981\textwidth}}
Variables\tabcellsep Omnibus Tests of Model Coefficients\tabcellsep R Square \%\tabcellsep Coefficient of the regression (B) \%\\
IS1-IE\tabcellsep 0.44\tabcellsep 2\%\tabcellsep 0\%\\
IS2-QG\tabcellsep 0.015\tabcellsep 1.2\%\tabcellsep 83.1\%\\
IS3-CR\tabcellsep 0.008\tabcellsep 1.5\%\tabcellsep 84.2\%\\
IS4-GA\tabcellsep 0.007\tabcellsep 1.5\%\tabcellsep 87.7\%\\
IS5-F\tabcellsep 0.000\tabcellsep 4.7\%\tabcellsep 20\%\\
IS6-CS\tabcellsep 0.000\tabcellsep 6\%\tabcellsep 78.7\%\end{longtable} \par
 
\caption{\label{tab_1}Table 2 :}\end{figure}
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\end{document}
