As about the supermarket. also, customers may

Asmany buying decision are made in retail stores, it is interesting to determinewhich factors, such as noise, lights, music, colours, visual communication havea significant influence on customers’ buying behaviour in a supermarket.

Objective: Theaim of this study was to examine the role of the various environmental factorsin the supermarket as well as how servicescape influences customers’ buyingbehavior. Methodology: Thequestionnaire is customized to collect data on facets in regards to the role ofservicescape and customers’ buying behaviour in the supermarket. A supermarketchain- Dmart was used for this purpose.

The collected data was analysed withthe means of factor analysis and multiple regression methods in order to obtainfactors that can influence customers’ behaviour in the supermarket. Findings and Conclusion: Theconducted study resulted that lighting, noise, colours, signs and symbols aswell as space conditions such as layout and equipment are the factors thatgenerate emotionally pleasant environment in the supermarket. Thus, thesefactors influence customers’ moods, attitudes or certain beliefs about thesupermarket.

also, customers may feel happier, more satisfied or relaxed in thesupermarket, which lead to arousal – stimulation or excitement. As well as, theenvironmental factors explain the approach behaviour such as exploring thesupermarket, spending more time on browsing the products which, consequently, refer to an increased number of items bought. Keywords- Servicescape, Service environment, Customers’ buyingbehavior outcomes.  1 Introduction 1. 1  Background TheIndian retail industry has emerged as one of the most dynamic and fast-pacedindustries due to the entry of several new players. It accounts for over 10 percent of the country’s Gross Domestic Product (GDP) and around 8 per cent of theemployment. India is the world’s fifth-largest global destination in the retailspace. Indian Retail Industry has immense potential as India has thesecond largest population with affluent middle class, rapid urbanisation andsolid growth of internet.

India’s retail market is expected to grow at a Compound AnnualGrowth Rate (CAGR) of 10 per cent to US$ 1. 6 trillion by 2026 from US$ 641billion in 2016. While the overall retail market is expected to grow at 12 percent per annum, modern trade would expand twice as fast at 20 per cent perannum and traditional trade at 10 per cent. Indian retail market is dividedinto “ Organised Retail Market” which is valued at $60 billion which is only 9per cent of the total sector and “ Unorganised Retail Market constitutes therest 91 per cent of the sector. India’s Business to Business (B2B) e-commerce market is expectedto reach US$ 700 billion by 2020. Online retail is expected to be at par withthe physical stores in the next five years. India’s total potential of Business to Consumer (B2C) isestimated to be US$ 26 billion, of which $3 billion can be achieved in the nextthree years from 16 product categories, according to a study by Federation ofIndian Chambers of Commerce and Industry (FICCI) and Indian Institute ofForeign Trade (IIFT).

India has replaced China as themost promising markets for retail expansion, supported by expanding economy, coupledwith booming consumption rates, urbanizing population and growing middle class. Supermarketsare not just buildings filled with products on the shelves. The supermarketconsists as well of a certain atmosphere inside the store. There are manyfactors such as noise, lighting, music, colour, layout or visual communicationthat can be taken into consideration in order to build an environment ascustomer-friendly as possible. Since the suitable environment of thesupermarket can influence customers to spend more time inside the store, thiscan lead to an increased number of items bought. Therefore, many marketers aretrying to adapt supermarkets’ interiors to increase customer satisfaction, loyalty, and by doing so, to increase the sales volume. 1. 2 Problem Sinceservicescape has been identified as an important factor in shaping theconsumer’s experience in a retail setting.

In a retail store majority ofactivities happening are services from the time customer enters and exits thestore. Theenvironment of the supermarket has big potential to be a powerful and aneffective marketing tool if marketers would better understand how to utilizeit. Since marketers and retailers want their customers to spend more time inthe supermarket, it is necessary to create a relaxed and comfortableenvironment. What is more, the environmental factors are considered to becrucial elements that determine success for the marketers. Even if one has notbeen in a particular supermarket, one’s first impression may have a greatinfluence on buying intentions (Nguyen & Leblanc, 2002). Moreover, sincebuying decisions made in the supermarket can be influenced by the environmentalfactors, retailers and marketers should take as much advantage as possible(Converse & Spencer, 1942).

Everyyear retailers spend large amounts of money to build, design and refurbishstores. However, marketers are unable to inspect the appropriate mix of theenvironmental factors/servicescape that attracts customers’ in supermarkets andmake them to spend more time in supermarkets. 1. 3ScopeSinceservicescape is a marketing tool through which marketers attract customers andgive them extra utility. Its really important to understand which environmentfactor influence the most, so marketers can get appropriate mix of environmentfactors and spend accordingly.

Thisresearch study is going to help the marketers to understand appropriate mix ofenvironment factors, get the maximum return on their investment as well as helpthem to attract and satisfy maximum number of customers.  1. 4Objectives1-Todetermine which environment factors influence customers’ buying behaviour inthe supermarket. 2-Toprovide the appropriate mix of environment factors to marketers.   2. Methodology2. 1Research DesignThequestionnaire is customize to determine which environment factors influence thecustomers’ buying behavior and to find appropriate mix of environment factors.

Questionnairewas made on the close ended questions, which were base on Likert scale. 2. 1. 1 Quantitativeresearch method thequantitative method was chosen, the quantitative research method is widely usedwhile examining customers’ attitudes and opinions. Since we wanted toinvestigate which environment factors influence the customers’ buying behaviorthe quantitative research method was justified to be used in this study. Also, one of the main advantages of using quantitative research is its clarity, sincenumbers can be easier to understand and interpret in comparison with hundredsof coding categories. 2. 1.

2Descriptive research It is a Descriptive research study that aims to determinewhich environment factors influence the customers’ buying behavior and to findappropriate mix of environment factors. 2. 2Sampling Size and MethodAsample of 245 customers is selected from Dmart. Primary data will be collectedby a pre-tested questionnaire.

In this study, judgementalnon-probability sampling was used. In the judgemental sampling, the units wereselected based on the researchers’ judgement about which units would be themost suitable, useful or representative in the research.  2. 3 DataCollection and MethodPrimary data was collected based on asurvey, a structured questionnaire created to determine which environment factorsinfluence the customers’ buying behavior and to find appropriate mix ofenvironment factors.  Questionnairewas made on the close ended questions, which were base on Likert scale.

2. 3. 1QuestionnaireThe questionnaire was composedof four types of questions. Questions were related to: (1) ambient conditions, (2) space/function,(3) signs, symbolsand artifacts, (4) customers’ behaviour in thesupermarket. These four types of questionscontain seven environment factors, (1) Lightning and colours, (2) Signs andsymbols, (3) Customers’ behaviour in Dmart, (4) Space/function and noise, (5)Design and music (6) Products and browsing, (7) Bright colour and darklightning Questions in the first sectionwere asked in order to understand what respondents think about colours, lighting and the noise level in Dmart. also, respondents also had to give theiropinion whether they would like to hear music in Dmart.

Questions in the second sectionwere asked in order to understand whether customers are satisfied with the layoutof Dmart. Questions in the third sectionwere asked in order to analyze respondents’ opinion when it comes to, billingdesk, directional signs and other types of communication, displayed in Dmart. Questions in the forth sectionwere asked in order to analyze general customers’ attitude towards Dmart. Likert scale allows therespondent to choose a degree of disagreement or agreement with each of thestatements. In the research, 7-point Likert scale was adopted.

Respondents wereasked to indicate in each statement a degree they agree or disagree withparticular statements from strongly disagree (= 1) to strongly agree (= 7).          3 Data AnalysisTo analyze the data, twomultivariate techniques were conducted. These techniques are suitable foranalyzing data when there is more than one measurement of each element and thevariables are analyzed simultaneously, factor analysis and multiple regressionwere conducted. 3.

1Factor AnalysisFactoranalysis is a technique that is used to reduce and summarize  a large number of variables into fewernumbers of factors.  This technique extracts maximum common variance fromall variables and puts them into a common score.  As an index of allvariables, we can use this score for further analysis.  Factor analysis ispart of general linear model (GLM) and this method also assumes severalassumptions: there is linear relationship, there is no multicollinearity, itincludes relevant variables into analysis, and there is true correlationbetween variables and factors. Thevariables that were investigated are following: ‘ ambient conditions’, ‘ space/function’ and ‘ signs, symbols and artifacts’. 3. 1.

1Principle Component AnalysisPrinciplecomponent analysis method was used. This is the most common method used byresearchers.  PCA starts extracting the maximum variance and puts theminto the first factor.  After that, it removes that variance explained bythe first factors and then starts extracting maximum variance for the secondfactor.  This process goes to the last factor. 3. 2Multiple RegressionMultipleregression is an extension of simple linear regression.

It is used when we wantto predict the value of a variable based on the value of two or more othervariables. The variable we want to predict is called the dependent variable (orsometimes, the outcome, target or criterion variable). The variables we areusing to predict the value of the dependent variable are called the independentvariables (or sometimes, the predictor, explanatory or regressor variables). Multipleregression is a general as well as an flexible data analytic system. Accordingto Cohen, Cohen, West and Aiken (2003), it can be conducted when a quantitativevariable (a dependent variable) is to be studied in relationship to any factorsof interest (independent variables). In this case the dependent variable was ‘ customers’ behaviour in Dmart’, and the rest of the variables wereindependent variables. Multipleregression analysis was conducted to see the impact of the servicescapevariables and customers’ behaviour in Dmart.

It is usually used to derterminehow much of the variance in dependent variable (‘ customers’ behaviour in Dmart’) can be explained by independentvariables (‘ lightingand colours’, ‘ signs and symbols’, ‘ space/function and noise’). Since only four factors were retainedafter conducting factor analysis, three of them were used as independentvariables and one as the dependent.  4 Results and Discussions4. 1Descriptive Statistics Descriptive statistics is a wayto summarize numerical data to make it easier to interpret, also, it includesmean and standard deviation. The 7-point Likert scale was used in thequestionnaire, where 1 means ‘ stronglydisagree’ and 7 ‘ strongly agree’. Inthis case, the statement ‘ Thelighting in Dmart is appropriate’has a mean of 5.

68. It indicates, that the respondents agreed and had apositive opinion towards this question. On the other hand, ‘ I think that Dmart has too manyproducts for the size of the store’has a mean of 2. 6 which points out that the majority of the respondents ratherdisagreed with this statement. Standard deviation measures thespread of a set of observations. The larger the standard deviation was, themore spread out the observations. A low score means that the responses wereconcentrated, hence, the respondents had the same opinion about a statement andscored similar. For example, ‘ Iam satisfied with the general impression of Dmart’ has the standard deviation of 1.

132. and, the higherstandard deviation means that the respondents had different opinion towards thesame statement. For example, the statement ‘ I would prefer if Dmart would play music’, formed the standard deviation of2. 165.  4. 2 FactorAnalysis Tomeasure the reliability of factors, the Cronbach ? s Alpha was used.

The scoresof the Cronbach ? s Alpha for ‘ lightningand colours’, ‘ signs and symbols’, ‘ customers’ behaviour in Dmart’, ‘ space/function and noise’ factors formed high reliability thatleads to acceptable scales (respectively 0. 890; 0. 867; 0. 823; 0. 764). It can beconcluded that the higher the respondents scored the questions about ‘ lightning and colours’, ‘ signs and symbols’, ‘ customers’behaviour in Dmart’, ‘ space/function and noise’, the higher their intensions to stayor explore Dmart. A part from that, the scores of the Cronbach ? s Alpha for ‘ design and music’, ‘ products and browsing’ and ‘ brightcolours and dark lightning’formed low reliability which leads to unacceptable scales (respectively 0.

19; 0. 417; 0. 462). Cronbach’sAlphas for all factors TheCronbach’s Alphas for only the first four factors are scored above 0. 6 whichstands for a reliable scale. This indicates a strong internal consistency amongthe items included in a particular factor. Essentially, this can be interpretthat respondents who selected a low score for one item tended to select lowscores for the other items included in the factor, and conversely, therespondents who tented to select a high score for one item tended to selecthigh scores for the others within the same factor. Hence, knowing the score forone item, it is possible to predict with some accuracy the possible scores forthe other items within the same factor.

The rest factors have a low reliabilityas the Cronbach’s Alphas are scored respectively 0. 187; 0, 425; and 0, 452 –thus, they do not create a reliable scale. which means, that the ability topredict scores from one item is not possible. so, only the first four factorswill be retained for further analysis.   4. 2 Correlationsand multicollinearity Itcan be seen that all independent variables show a relationship with thedependent variable.

correlations suppose to be higher than 0. 3. In this resultwe can see that, ‘ lightningand colours’, ‘ signs and symbols’, and ‘ space/function and noise’ correlate with ‘ customers’ behaviour in Dmart’ (0. 501; 0. 563; and 0. 509) and create apositive correlation, since all scores are between 0 and 1. All three factorscreate large relationships between dependent and independent variables, as theyscore above 0. 5.

Also, we can see that most correlated factor, hence, thestrongest relationship exists between ‘ customers’behaviour in Dmart’ and ‘ signs and symbols’.    5 ConclusionTo conclude, fourmain factors such as ‘ lightningand colours’, ‘ signs and symbols’, ‘ customers’ behaviour in Dmart’, and ‘ space/function and noise’ were obtained. The higher thecustomers scored questions in each of those factors, the higher theirintensions to stay or explore Dmart, as well as more satisfaction. The factor ‘ lightning and colours’ has the highest reliability whichshows a high degree to which each item correlates with a total score. The ‘ lightning and colours’ is followed by the ‘ signs and symbols’ component. Thesefour factors create an emotionally pleasant environment in the supermarket. This means that those factors influence customers’ mood, attitude or certainbeliefs about the supermarket. As well as make customers feel happy, satisfiedand relaxed in the supermarket which leads to stimulation or excitement.

also, environmental factors mentioned above explain the approach behaviour –exploring the supermarket, spending more time on browsing the products whichrefers to the increase of number items bought as well as increase in sales forthe marketers. Multiple correlation wasconducted based on four components created by factor analysis. three factorscreated by factor analysis, namely ‘ lightningand colours’, ‘ signs and symbols’, and ‘ space/function and noise’ stand for the independent variables, whereas ‘ customers’behaviour in Dmart’ for thedependent variable. Multiple correlation showed that all independent variables(‘ lightning andcolours’, ‘ signs and symbols’, and ‘ space/function and noise’) play an important role to influencethe ‘ customers’purchase, customers satisfaction and their revisit in Dmart. To satisfy customers andmake them stay longer and brought more and more product marketers should focusof three main factors suchas ‘ lightning andcolours’, ‘ signs and symbols’, and ‘ space/function and noise’. 5 Limitations of the study1.     Small sample size which did not allow tocome to concrete observations2.     Paucity of time3.

Area constricted to nearby places ofElectronic city, Bangalore. ? 4.     Small sample size in comparison to thewide spread reach and effect of marketing strategies. ?  5 Managerial ImpactIn retail industry servicescape play important role to attract customersand generate sales. Marketers spend good chunk of amount on servicescape, everyyear but appropriate mix of environment factors is still not available.

They don’t know what proportion of money, they should spend onparticular environmental factor. Which factor is going to influence customerthe most and make them stay longer with them.” This study is going to help todiscover environmental factors that creates physical environment in thesupermarket and are used in determining customers’ impression of the store. Since those factors lead to the approach behaviour – such as willingness toexplore the supermarket, spend more time on browsing, which refer to intentionto revisit the supermarket, an increased number of items bought as well asincrease in sales for the marketers; understanding environmental factors allowsboth retailers and marketers to make improvements in these areas. Even thisresearch did not make the attempt to determine what kind of colours customersprefer or what genre of music they would like to hear in the supermarket, thefindings show extra caution and should be carefully considered when designingor redesigning the store”.