Journal of International Trade, Logistics and Law, Vol. 9, Num. 1, 2023, 15-27 15 STORE ATMOSPHERE STRATEGIES AND THEIR EFFECTS ON PURCHASE INTENTION Fazli Uğur ÇOLAK İstanbul Ticaret University Özgür ÇENGEL Galata University Received: Dec 02, 2022 Accepted: March 09, 2022 Published: June 01, 2023 Abstract: Retailers must continually adjust to the realities due to the fast speed of today's society, which brings with it constant changes in fashion trends, technology advancements, and also the modification of lifestyle. Even though such improvements and adjustments are unnecessary, they must be made in order to keep the store attractive or to modernize the technical infrastructure and lower operating energy usage in the face of competition from new, similarly minded businesses. The functioning of the retail operation is heavily influenced by the architectural and design solution, where the customer must first arrive at the store, which then needs to draw them in and persuade them to make a purchase. Recent years have seen a rise in the importance of the shopping environment. Many stores rely on the fact that they have the most comfortable atmosphere, which forces the customer to stay in the store as long as possible. Sellers also try to make shopping an experience, making it necessary for the customer to feel satisfied in the store. Shopping atmosphere and control can help higher customer satisfaction. It is therefore very important to monitor the key factors that affect the atmosphere in the store. This article examines selected elements of the shopping atmosphere and its impact on consumers in electronic markets operating in Turkey, Germany, and England. It integrates research, survey, and observation into real terms of selected retail operations. Based on the findings, the conclusion on adapting selected factors influencing the atmosphere is proposed to improve the overall well-being of customers and thus their satisfaction during shopping. Keywords: Store atmosphere, purchase intention, music, lighting, customer 1. Introduction The element that forms the basis of economic development is the high per capita gross product. One of the most important ways to have a high national income is trade, usually exports. The level of economic development and foreign trade balances are directly related. For this reason, companies and even countries resort to many methods in order to improve the foreign trade balance in their favor. One of them is to get ahead of others by differentiating in an environment where the number of competitors is high. The main goals of international profit-seeking companies are generally to increase production and export new products to foreign markets. For this, companies need to develop export and marketing strategies, establish long- term cooperation by focusing on these strategies, and increase their market shares, not their profit margins. The problems caused by distance, which is the biggest of the main difficulties experienced in exports, are gradually decreasing with the developments in technology and communication; globalization and language differences are no longer as big problems as they used to be, thanks to easy access to information; Internet and wireless connections or making online payments faster can be seen as an advantage for companies or for countries when considered in a broader framework (Ahearne, 2010). In addition, although the internet's offering of equal opportunities for everyone who is an entrepreneur seems to be a disadvantage, it creates an excellent opportunity for individuals and organizations with similar activities and financial situations to come together. This is because the internet is open to everyone. While this situation allows to compete on equal terms, it also causes a great disadvantage for those who cannot keep up with the digital age (Manning, 2010). Fazli Uğur ÇOLAK & Özgür ÇENGEL 16 The products used in international markets differ according to the country of origin, culture and even brands. One of the factors affecting the attractiveness of the products is that the products are presented in different ways to the customers in the stores. The design of the stores, the placement of the products sold, the music played, etc. It is thought that these factors can affect the purchase intention in positive or negative ways (Jalil, 2016). The impact of the environment on behavior has long been recognized by retailers, architects, and interior designers (Baker, 1992). Store atmosphere is made up of different components, often referred to as "atmosphere factors", such as music, scents and colors. Dealers have to act accordingly in order to change the consumer's behavior (Kotler, 1973). According to Bitner (1992): “Experimental research and theoretically-based frameworks addressing the role of the physical environment in consumption environments are surprisingly lacking”. More recently, Spangenberg (2005) points out that “although environmental stimuli have been found to influence shopping behavior, empirical knowledge of how these variables interact to influence shoppers' perceptions and actions is lacking.” In 1973, Kotler states that the atmosphere of a store causes various reactions on the consumer, while atmospheric factors can affect positive responses on consumers. Kotler argues that “atmospherics” are a potentially important source of competitive advantage in the retail environment. Bitner (1992) uses the term “service areas” to refer to the physical environment shaped by retailers to facilitate service delivery to consumers. It is also known that the service environment consists of both tangible and intangible elements that make up the service experience (Hoffman and Turley, 2002). In this study, it is examined whether there is a significant relationship between customer purchase intention of display and layout, music, lighting, cleanliness, and participant factors. 2. Purpose of the Study This research will show why store atmosphere can be an important part of a marketing strategy to drive sales and create a positive store image, as well as how it can influence a customer's impulse buying behavior. The study will also inform retailers about the various elements of the store atmosphere that can encourage customers to buy on impulse, as well as how stores can be built and how products can be displayed in stores and used to influence impulse buying by influencing buyer perception. 3. Literature Review The store atmosphere has been defined by Kotler (1973) as "an effort to design purchasing environments to create unique emotional effects in the buyer that increase the probability of purchase". Kotler proposes a five-dimensional sensory system for store atmospheres, and subsequent studies argue that the store atmosphere also includes environmental factors (sound, arousal, smell, sight), product-based factors (crowd, arousal, smell), and vision factors (wall colours). It consists of environmental factors, construction factors and social factors. In the retail environment, it has been found that customers give various reactions through cognitive, emotional and biological ways (Bitner, 1992). According to Shirin (2021), the positive effect of the store environment on consumer behavior is explained by the fact that a customer who is interested in purchasing a product and is enthusiastic about the shopping experience stays in the store longer, spends more money, and enjoys it more when he returns. The amount and quality of lighting, the impression it gives to the product and its effect on the appearance of the retail space are all factors in a successful sale. A customer who is interested in purchasing a product and is excited about the shopping trip will stay longer, spend more money, and return again in the future. The quantity and quality of lighting, the feel it creates about the product and its effect on the appearance of retail spaces are all reasons for good sales. Durai and Stella (2020) say that the store atmosphere is a pleasant shopping environment created by retailers based on consumer emotional value. Retailers use store atmospheres to create a positive experience for customers, which leads to hedonic motivation. Stores operating in real places give more importance to the in-store environment and enrich the customer's shopping experience with innovative products. Ideas, charm, and excitement are terms that come to mind when thinking of the word "pleasure." The store atmosphere is a combination of elements that can be felt, heard or seen that cause people to buy products they do not need. The retail business states that a store's atmosphere includes the physical aspects, sanitation, equipment and mural, the display of goods, attractive decorations, aroma, melody and other intangible aspects all exist simultaneously. Consumers' emotions are affected by the atmosphere, which can lead to impulse purchases. Store Atmosphere Strategies and Their Effects on Purchase Intention 17 Arti (2020) argues that music, cleanliness, and participant have a direct impact on customer behavior intention. Besides store display and layout, light has a significant impact on emotional enjoyment. Customer behavior intent is significantly influenced by store taste, but not by arousal or customer retail experience. The literature suggests that in order to lead the market, all retail stores must constantly improve themselves, because business sustainability requires satisfying existing customers and gaining new customers. To do this, retailers adopt new systems to sustain themselves in the competitive market. Visual merchandising is one of the dominant concepts that enables retailers to attract new customers in-store (Michelle et al., 2019). Batista (2020) examined the use of visual merchandising and concluded that it is limited to retail stores. Visual merchandising is a technique of creating a store environment by using various elements such as design, architecture, decoration, and visual communication to attract the customer to the shopping environment. Existing customers have higher purchasing power due to their changing and demanding needs. Research by Nell (2017) found that visual merchandising displays unconsciously affect consumer purchasing behavior, and a pleasant shopping environment leads to a purchase by making the customer stay in the store longer. The study finds that the atmosphere of opinion influences consumers to buy directly or indirectly. Sondakh (2020) found that marketers try to take advantage of consumers' impulsive purchases to increase their sales. The study finds that store layout significantly influences customer's impulsive buying behavior. Timonia (2020) attempts to evaluate retailers' use of combined assortment to increase sales and revenue. The study compares proposed heuristics with three types of planning strategies for business insights. The three types of planning strategies examined in the study are the absence of variable products received by retailers, cross-selling ignored by retailers, and fixed maximum space allocation for products. In the case of cross-selling by retailers, it has been found that variable product variety significantly increases profitability. Iyer et al. (2019) conducted an analysis to understand the relationship between consumers' impulse buying behavior and its internal and external determinants, and reported that characteristics, motives, consumer resources and marketing stimuli are the main determinants of impulse buying. In addition, consumers' mood and self-control were also reported to mediate the emotional and psychological processes of impulse buying. Soomru (2017) tried to investigate the effect of visual merchandising on consumer attention and found that color and lighting, showcase and store interiors were positive and significant on consumer attention. In the study, it was found that the store layout was negative, which significantly affected the attention of the consumer. Thus, he concluded that retailers should focus on visual merchandising to increase consumer foot traffic. Gowrishankkar (2017) tries to examine the effect of the store environment on the purchasing behavior of consumers. He argues that store ambience stimulates a consumer's perception and emotions, which in turn influences consumers' purchasing decisions. 4. Research The aim of this research is to examine the factors affecting the purchase of electronic household goods in different countries. In this context, the effects of factors such as cleaning, lighting, music, display/layout, shopping options and participants’ factors in stores selling electronic household goods in Turkey, Germany and England on the intention to shop again from these stores were investigated. In accordance with this purpose of the research, a quantitative research design and relational survey model were used in the research. According to the research purpose, 6 hypotheses were tested: H1: Music playing in stores that sell electronic household goods affects the intention to shop from this store again. H2: Lighting in stores selling electronic household goods affects the intention to shop from this store again. H3: Cleanliness of stores selling electronic household goods affects the intention to shop at this store again. H4: Display/layout in stores selling electronic household goods affects the intention to shop from this store again. H5: Shopping options of stores selling electronic household goods affect the intention to shop from this store again. H6: Participant factors affect the intention to shop from the store where electronic household goods are sold. The population of the study consisted of adults over the age of 20 living in Turkey, Germany and England. The sample of the study consisted of 300 people who were selected from this participant universe by using the convenience sampling technique and people who accepted to participate in the research. In the sample, attention was paid to the presence of participants of different genders, ages and different education levels, 100 people from each country were chosen. Fazli Uğur ÇOLAK & Özgür ÇENGEL 18 The data of this study were collected by the survey method. In order to measure the variables of the research, a questionnaire form was developed by the researcher with the support of an expert. Since the questionnaire was applied in three different countries, it was prepared in three different languages: Turkish, German and English. The questionnaire consists of three parts. In the first part, 8 questions were asked to measure the demographic information of the participants. In the second part, 12 questions were asked about the behavior of the participants in purchasing electronic household goods. In the third and last part of the questionnaire, there were 37 questions of 5- point Likert type aiming to measure the factors of cleanliness, lighting, music, display/layout, shopping options, participants factors and purchase intention. The data of the research were collected between Q4 2021 and Q3 2022. The questionnaire was prepared with Survey Monkey and shared with the researcher's contacts on the LinkedIn platform. These contacts were also asked to share the questionnaire with their own contacts. The completed questionnaires were collected online again. The data of the research were analyzed on the SPSS 26.0 program. Factor analysis, reliability test, descriptive statistics, Pearson product-moment correlation test and multiple regression tests were used for the analyses. 4.1. Findings 4.1.1. Demographic Characteristics of Participants According to the findings in Table 1, 300 people participated in the study in equal numbers from three different countries, Turkey, Germany and England. About half of the participants are male (51.0%) and approximately the other half are female (49.0%). 19.7% of the participants were between 20-30 years old, 53.3% were between 31-40 years old and 27.0% were 41 years old and over. Slightly more than half of the participants are married (56.7%). The rate of single participants is 37.3% and the rate of those living separately is 3.0%. While 9.3% of the participants are high school graduates, 40.7% are university graduates. The rate of participants with a master's degree is 40.7%, and the rate of those with a doctorate is 9.3%. Looking at the professions of the participants, it is seen that 40.7% of the participants are managers and 18.7% are senior managers. The rate of those holding a sub-manager position is 15.7%. While the rate of retired participants is 6.0%, the rate of participants who are students is 6.3% and the rate of participants who do not work in a job is 12.7%. The monthly income of 44.7% of the participants is over 5000€/5000£/20000TL. The monthly income of 43.0% of the participants is between 2000€/2000£/10000TL - 5000€/5000£/20000TL. 9.3% of the participants have a monthly income below 2000€/2000£/10000TL and 3.0% of the participants do not have a monthly income. Table 1. Demographic Findings of the Participants Variables Groups f % Country Turkey 100 33.3 Germany 100 33.3 England 100 33.3 Gender Male 153 51.0 Female 147 49.0 Age 20-30 years 59 19.7 31-41 years 160 53.3 over 41 years old 81 27.0 Marital status married 170 56.7 single 112 37.3 separate 9 3.0 Store Atmosphere Strategies and Their Effects on Purchase Intention 19 Other 9 3.0 Educational Status High school 28 9.3 University 122 40.7 master 122 40.7 Doctorate 28 9.3 Monthly Income None 9 3.0 Less than 2000€/2000£/10000TL 28 9.3 Between 2000€/2000£/10000TL - 5000€/5000£/20000TL 129 43.0 Over 5000€/5000£/20000TL 134 44.7 Job Executive 122 40.7 sub-manager 47 15.7 senior manager 56 18.7 Retired 18 6.0 Non working 38 12.7 Student 19 6.3 4.1.2 Findings Regarding Purchasing Behavior According to the findings in Table 2, the majority of the participants (86.3%) purchased electronic household goods at least once and at most 5 times in the last year. 11.4% of the participants purchased electronic household goods six or more times last year. The rate of participants who have never purchased electronic household goods is 2.3%. It was found that 68% of the participants examined the products and brands of electronic household goods purchased 1-5 times before making the purchase. 18% of the participants examined different products and brands 6 or more times. In the last year, the rate of purchase of a major (major) electronic household item by the participants or a member of the family is 30.0%. When the sources used by the participants to purchase electronic household goods are examined, it is seen that the participants mostly prefer online media (35.3%), electronic product sellers (28.7%) and large retail stores (26.0%). Purchasing points were found to be predominantly official sellers (51.7%), online sales (19.0%) and retail stores (18.7%). Table 2. Findings Regarding the Purchasing Behavior of the Participants Variables Groups f % Number of purchases last year none 7 2.3 1-5 times 259 86.3 6-10 times 20 6.7 11 and more 14 4.7 Number of different products/brands reviewed none 42 14.0 1-5 times 204 68.0 Fazli Uğur ÇOLAK & Özgür ÇENGEL 20 last 6-10 times 34 11.3 11 and more 20 6.7 A family member's purchase of an item in the past year yes 90 30.0 no 210 70.0 Resources used to buy items Large retail stores 78 26.0 Electronic product vendors 86 28.7 online media 106 35.3 Written newsletters 20 6.7 Other 10 3.3 points of purchase Official seller 155 51.7 retail store 56 18.7 Online sales 57 19.0 sales representatives 17 5.7 Fair outlet sales 15 5.0 4.1.3. Factors Affecting Buying Behavior Related Findings According to the findings in Table 3, the primary purpose of the participants in purchasing electronic household goods is their own use (42.3%) or the use of other members of the family (38.3%). The primary criterion used by half of the participants (50.7%) when purchasing electronic household goods is quality. The primary criterion used by 37.3% of the participants is the performance of electronic household goods. While 5.7% of the participants use the energy consumption, 3.3% of the participants use the appearance criterion. It was determined that 47.0% of the participants were most affected by internet advertisements, 26.0% of the participants were most affected by TV, and 9.0% of the participants were most affected by billboards. It is seen that the participants are similarly affected by different types of campaigns in purchasing electronic household goods. 22.0% of the participants are from attractive advertisements, 19.0% from word of mouth, 17.0% from sales representatives' promotions, 17.0% from product reviews, 15.0% from discounts and 10.0% of them are influenced by celebrities. The most striking pricing options for the participants were found to be affordable prices (57.3%), offers and discounts (27.0%) and being eligible for credit (15.7%), respectively. It was determined the factors that the participants were most affected by in store shopping were design (51.3%), social factors (34.7%) and ambiance (14.0%), respectively. Table 3. Findings Related to Factors Affecting Participants' Purchasing Behavior Variables Groups F % Purchasing purpose for my own use 127 42.3 Gift for someone in the family 33 11.0 Gift for someone outside the family 25 8.3 For other members of the family to use 115 38.3 Store Atmosphere Strategies and Their Effects on Purchase Intention 21 Criteria used in purchasing Performance 112 37.3 Brand 3 1.0 Quality 152 50.7 Energy consumption 17 5.7 Appearance 10 3.3 Guarantee 3 1.0 Customer service 3 1.0 The type of ad that influences the purchase TV commercials 78 26.0 Internet ads 141 47.0 Billboard ads 36 12.0 newspaper ads 27 9.0 radio ads 18 6.0 Most notable campaigns Word of mouth 57 19.0 Attractive ads 66 22.0 celebrities 30 10.0 Product presentation by sales representatives 51 17.0 Discounts 45 15.0 Product reviews 51 17.0 Most notable pricing options Reasonable price 172 57.3 Offers and discounts 81 27.0 Suitable for credit use 47 15.7 Factors affecting buying in store Social (store employees and other customers) 104 34.7 Ambience (temperature, music, light) 42 14.0 Design (Color, display, architecture) 154 51.3 4.1.4. Exploratory Factor Analysis and Reliability Analysis Three different exploratory factor analyzes were carried out in accordance with the structures of the scales in the survey form of the research. Firstly, factor analysis was performed for the 5-item purchase intention scale. Secondly, factor analysis was conducted for the music, lighting and obliging scales, which consisted of a total of 15 items Fazli Uğur ÇOLAK & Özgür ÇENGEL 22 related to the store atmosphere. Finally, the analysis was carried out for the scales of display/layout, shopping options and participant factors, consisting of a total of 17 items related to shop orientation. Principal components method was used for factor analysis and Varimax technique was preferred from factor rotation techniques. 4.1.4.1. Intention to Purchase Scale Factor Analysis According to the first factor analysis for the 5-item purchase intention scale, the KMO value was found to be 0.78, and the p -value for the Bartlett sphericity test was found to be less than 0.05. Afterwards, Extraction values for each item were examined, which shows how much the items are related to each other as an indicator of measuring the same structure. The value of the IntentiontobuyB item was found to be 0.20, and since this value was less than 0.30, this item was excluded from the scale. It was observed that none of the recalculated Extraction values were below 0.30. It was found that the 4-item purchasing scale had a single factor structure and this single factor structure explained a 72.0% variance (Table 4). The internal consistency coefficient of the scale was also calculated as 0.83. Table 4. Intention to Purchase Factor loads Factor loads Cronbach Alpha IntentiontobuyA 0.58 0.83 IntentiontobuyC 0.94 IntentiontobuyD 0.91 IntentiontobuyE 0.91 4.1.4.2. Store Atmosphere Substances Factor Analysis Factor analysis was conducted for the music, lighting and obliging scales, which consist of a total of 15 items related to the store atmosphere. According to the first factor analysis for these 15-item scales, the KMO value was found to be 0.68, and the p -value for the Bartlett sphericity test was found to be less than 0.05. It was observed that all of the calculated Extraction values were above 0.30. Factor analysis showed that this scale formed a 5-factor structure. However, since the difference in the weights of the LightingC item under more than one factor was less than 0.10 (conjoined), it was excluded from the scale. As a result of the factor analyzes performed on 14 items, it was determined that the scale was explained with a 5- factor structure. The total variance explained by these 5 factors is 64.4%. The contribution of each factor to the total variance and the factor loadings of the items in each factor are given in Table 5 and the factors are named. In addition, reliability analyzes were performed for the items in each factor and the obtained values are also given in Table 5. It was observed that the internal consistency coefficients used for reliability analysis varied between 0.62 and 0.70. According to these findings, the scales were evaluated as medium reliability scales (Nakip & Yaraş, 2017). Table 5. Store Atmosphere Scale Final Factor Analysis Results Code Expression Factor Load Factor 1 (store cleanline ss and order) Cleanness B Shelves are clean. 0.71 Cleanness C Store is clean. 0.71 Cleanness D Products are tidy and not damaged. 0.69 Store Atmosphere Strategies and Their Effects on Purchase Intention 23 CleannessE The fact that the store is clean and tidy increases my well- being and comfort. 0.63 Cronbach's alpha=0.62; Explained variance=13.77%; Number of items=4 Factor 2 (appropri ateness of the music genre) MusicC The type of music which is played at the store is the kind of music that I usually listen to. 0.69 MusicD Background music is pleasant. 0.85 MusicE Existence of background music increases my well-being and comfort. 0.73 Cronbach's alpha=0.69; Explained variance=13.75%; Number of items=3 Factor 3 (light in terms of store ambiance ) LightingD Different lighting used in each area inside the store is important. 0.81 LightingE Better clarity increases my well-being and comfort. 0.70 Cleanness A Store's floor is clean. 0.83 Cronbach's alpha=0.66; Explained variance=13.65%; Number of items=3 Factor 4 (conform ity of music tone and rhythm) MusicA Rhythm of the background music is adequate. 0.84 MusicB Volume of the background music is adequate. 0.80 Cronbach's alpha=0.70; Explained variance=11.60%; Number of items=2 Factor 5 (light for product visibility ) LightingA Light in the areas of products allows me to evaluate the quality of the products (eg, White lights, yellow lights, brightness). 0.86 LightingB Light at the corners of the store (more hidden areas) is sufficient. 0.88 Cronbach's alpha=0.70; Explained variance=11.58%; Number of items=2 4.1.4.3. Shop Oriention Items Factor Analysis Factor analysis was conducted for the scales of display/layout, shopping options and participant factors, consisting of a total of 17 items related to shop orientation. According to the first factor analysis for these 17-item scales, the KMO value was found to be 0.65, and the p -value for the Bartlett sphericity test was found to be less than 0.05. It was observed that all of the calculated Extraction values were above 0.30. Factor analysis showed that this scale formed a 7-factor structure. However, since the difference in the weights of ParticipantFactorC item under more than one factor was less than 0.10 (conjunctive), it was excluded from the scale. In addition, ParticipantFactorD item was also excluded from the scale because it was loaded on a single factor. As a result of factor analysis performed on 15 items, it was determined that the scale was explained with a 6-factor structure and the total variance explained by these 6 factors was 67.5%. The contribution of each factor to the total variance and the factor loads of the items in each factor are given in Table 6 and the factors are named. In addition, reliability analyzes were made for the items in each factor and the obtained values are also given in Table 6. It was observed that the internal consistency coefficients used for the reliability analysis varied between 0.44 and 0.77. According to these findings, the internal consistency coefficients of factor 5 and factor 6 were considered as low- reliability scales since they were between 0.40 and 0.59, and since the internal consistency coefficients of the other scales were between 0.60 and 0.80, they were considered as medium-reliability scales (Nakip et al. Yaras, 2017). Fazli Uğur ÇOLAK & Özgür ÇENGEL 24 Table 6. Shop Oriention Scale Final Factor Analysis Results Code Expression Factor Load Factor 1 (testabilit y of products) ShoppingOptionA I could try the products hands-on (iron, vacuum, kitchen appliances). 0.65 ShoppingOptionB Sample items were working. 0.78 ShoppingOptionC Product information was clear and available. 0.79 Cronbach's alpha=0.77; Explained variance=15.84%; Number of items=3 Factor 2 (product visibility ) DisplaylayoutC Locations of each department in the store are important. 0.68 DisplaylayoutD Store display window allows me to see displayed products clearly. 0.71 DisplaylayoutE Clear shelf information increases my well-being and comfort. 0.65 Cronbach's alpha=0.67; Explained variance=13.11%; Number of items=3 Factor 3 (custome r mobility in the store) ParticipantsFactor E Crowding shows attractiveness of the store. 0.57 ParticipantsFactor F Existence of high-end products increases the luxury perception of the store. 0.67 ParticipantsFactor G The fact of having a reasonable number of customers in the store increases my well-being and comfort. 0.67 Cronbach's alpha=0.65; Explained variance=11.91%; Number of items=3 Factor 4 (service related) ShoppingOptionD I have been offered product options that I can bundle up together. 0.79 ShoppingOptionE Better shopping experience increases my well- being and comfort. 0.71 Cronbach's alpha=0.52; Explained variance=9.68%; Number of items=2 Factor 5 (Staff Quality) ParticipantsFactor A Appearance of the employees is important. 0.70 ParticipantsFactor B Politeness of employees is important. 0.53 Cronbach's alpha=0.44; Explained variance=8.87%; Number of items=2 Factor 6 (store design) DisplaylayoutA Corridors in the store allow a good circulation. 0.67 DisplaylayoutB Product organization allows me to identify the location of products in the store easily. 0.57 Cronbach's alpha=0.38; Explained variance=8.12%; Number of items=2 Store Atmosphere Strategies and Their Effects on Purchase Intention 25 4.1.5 Impact Analysis In this section, whether the variables of store cleaning, store design, store mobility, lighting in terms of store ambiance, lighting in terms of product appearance, music type, music sound/rhythm, testability of products, visibility of products, personnel quality and service quality affect the variable; if it does. the extent to which they affect them was investigated (Table 7). Table 7. Multiple Regression Analysis Dependent Variable: Purchase Intent Independent variable B Q. Error β t p VIF DW Still 2.17 0.62 3.49 0.00 1.99 Store Cleaning 0.42 0.08 0.29 5.12 0.00 1.07 Design of the Store 0.05 0.06 0.05 0.89 0.37 1.13 Customer Mobility 0.23 0.05 0.28 4.96 0.00 1.06 Lighting in terms of Store Ambiance -0.14 0.08 -0.10 -1.76 0.08 1.09 Lighting in terms of Product Appearance 0.01 0.05 0.01 0.09 0.92 1.10 Music genre -0.07 0.05 -0.08 -1.31 0.19 1.19 Music Voice/Rhythm -0.01 0.05 -0.01 -0.12 0.91 1.20 Testability of Products -0.10 0.05 -0.14 -2.17 0.03 1.36 Visibility of Products 0.01 0.06 0.01 0.11 0.91 1.20 Staff Quality -0.05 0.06 -0.05 -0.89 0.37 1.06 Service Quality 0.01 0.05 0.01 0.22 0.83 1.28 R: 0.40 F : 5.10 Adjusted R 2 : 0.13 p : 0.00 The findings in Table 7 show that the Durbin Watson value is greater than 1.0 and the VIF values are less than 10. In the regression analyzes based on these findings, it was accepted that there was no auto-correlation, the independent condition of the errors was met, and there was no multicollinearity problem (Nimon, 2010). 5. Conclusion In conclusion, the aim of this study is to investigate the relationship between electronic retail store atmospheric characteristics, customer experience and behavioral intentions of customers in Turkey, Germany and England. There Fazli Uğur ÇOLAK & Özgür ÇENGEL 26 are two goals that can be achieved in this study: to see the effect of store atmosphere factors on customer purchase intention and to see the approaches of these factors according to different countries. The findings in Table 7 have 13% on the purchase intention of the variables of store cleanliness, store design, store mobility, lighting in terms of store ambiance, lighting in terms of product appearance, music genre, music sound/rhythm, testability of products, product visibility, personnel quality and service quality. showed that it explained a variance of . In other words, 13% of the intention to shop at the same store again can be explained by these 11 factors. However, the findings again showed that only 3 of these 11 factors had a statistically significant effect on purchase intention. While the factors of store cleanliness and customer mobility have a positive and significant effect on the purchase intention, the effect of the testability factor on the purchase intention is negative (respectively; β = 0.29, p <0.05, β = 0.28, p <0, 05 and β = -0.14, p <0.05). According to these findings, as the perception levels of the participants about store cleaning and activity in the store increase, the intention of the participants to shop again from the same store also increases. On the other hand, as the testability levels of the products in the stores increase, the intention of the participants to shop from the same store again decreases. Other than these three factors, store design, lighting in terms of store ambiance, lighting in terms of product appearance, music genre, music sound/rhythm, visibility of products, personnel quality and service quality did not have a significant effect on the intention to shop from the same store again. Thus this research shows why store atmosphere can be an important part of a marketing strategy to drive sales and create a positive store image, as well as how it can influence a customer's impulse buying behavior. 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