By notifying users of pertinent goods and services, internet systems aim to promote e-commerce. In this study proposal, we propose a novel method for identifying the factors that influence Arab customers’ decision to shop online. The idea for this study came from earlier research on online purchasing, recommendation systems, and internet-based information systems. Surveys published on e-commerce websites were used to collect additional quantitative data. The early studies and recommendations were examined by systems and information systems experts to conduct a conceptual and descriptive examination of the data generated by most petite square structural equation modelling. Usability, diversity, accuracy, suggestion quality, satisfaction, and ease of use are just a few of the variables that significantly impact customers’ desire to purchase products offered by recommender systems. The strategy and results outlined here will be advantageous to website design, users, customers, and recipients following factors that support their value. User retention could be reliably predicted based on whether or not users were satisfied with the websites. The study’s findings are thoroughly analyzed in this paper. Their theoretical and managerial ramifications are discussed by practitioners concerned with the long-term expansion and performance of the ecommerce sector.
Key Words: cross-border shopping websites; continuance intention; satisfaction;
CHAPTER 1: INTRODUCTION
Introduction and Background to the study
Retail managers must understand and anticipate how various types of customers will behave when purchasing various goods and services to meet their needs in today’s quickly evolving business environment. As a result, to get a competitive advantage in the market, many sellers focus on creating a favourable perception of their products in the minds of consumers (Kidane & Sharma, 2016). Understanding individual customers’ purchasing decisions and how they use their available resources (such as time, money, and energy) to obtain a good or service is the primary goal of consumer behaviour (Kidane & Sharma, 2016).
E-commerce is an essential strategic element because it forms the basis for corporate internationalization. International trade is aided by removing barriers between nations and impacts firms and consumers. E-commerce is crucial to the corporate world. Improving the spread of international institutions and expanding access to global markets. Businesses gain reciprocal pooled resources and advantages (HERZALLAH et al.,2022). Customers find it to be more accessible. Comparing prices and product quality while shopping online can help you save on search fees and ultimately make more informed decisions. E-commerce will also play a significant role in 2019 since it has the potential to be the engine for the subsequent industrial revolution, according to a McKinsey report. It is employed in many developing countries to reduce poverty. According to Yang & Lin(2022), many business people and ordinary citizens in Arab countries like Qatar view e-commerce as the foundation of their economic existence.
Through e-commerce platforms, customers can browse a range of online shops in a single session. Numerous academic studies have examined the effectiveness of such platforms. Numerous studies have been done on recommendation algorithms’ accuracy, particularly about their forecasts’ accuracy. Scholars are considering two intriguing questions.
Provides recommendations for online buying based on prior behaviour and future objectives. Google Trends data shows that professionals frequently look for them. Although websites impact consumers’ tendency to buy, this impact has not been quantified helpfully. We shall address this as the primary research question. Various analytical criteria are used in the review of recent publications. Despite the widespread usage of recommender systems in the online retail sector, very few studies have examined consumer satisfaction and subsequent purchase intent.
Furthermore, few studies have found an association between loyalty and contentment. Studies show that recommendations’ presentation affects consumers’ intentions (Ma et al., 2019). Recommender systems have received very little attention in the e-commerce and commercial websites literature.
Other indicators that do not consider technical issues must be employed further to assess the website’s systems’ health and availability. The effectiveness of these systems is determined by the fact that actual users find them beneficial, not by their technological superiority, quality, or efficacy. The effectiveness of recommender systems can best be assessed using user-centred measures.
Objectives of the study
In order to increase customers’ willingness to buy the products and services that are recommended to them, this research aims to make cross-border ecommerce more dependable and appealing in the Arab world. The study technique and hypothesis testing processes utilized to assess the influence of trust and pleasure on the clientele’s future purchases are also mentioned.
Finding characteristics of recommender systems for online retailers that influence consumers’ inclination to buy is the primary goal of this research. We examine how the I.S. theory and the systems literature have been discussed in this setting. In addition to gathering and evaluating data, this study critically analyses vital ideas. It suggests critical or prospective variables for increasing customer trust and satisfaction with the recommender concept, as demonstrated by Rosário & Raimundo (2019).
What elements affect a consumer’s decision to buy when they shop online?
What elements influence online business transactions?
What are the most typical obstacles to internet shopping?
Will it favourably affect shoppers’ intentions to make purchases online?
H1 Perceived happiness boosts client satisfaction in e-commerce right away.
H2 In the world of e-commerce, perceived trust has a direct positive impact on customer happiness.
The store environment positively impacts H3 Purchase decisions.
H4 The value proposition of e-commerce platforms is positively influenced by perceived diversity.
H5 Purchase decisions are positively impacted by perceived value.
CHAPTER 2: LITERATURE REVIEW
This section analyses prior research on online buying to identify the variables that affect consumers’ intention to shop online (Thomas et al., 2019). Data on user-friendliness, customer trust, satisfaction, perceived value, correctness, attitude, diversity, and authenticity are examined, along with how these factors affect consumers’ intentions to make an online purchase. Consumers continue to define online buying in e-commerce components (Shahrel., 2021). The current shortage is therefore identified, and the research is fair.
The series of choices a consumer makes before making a purchase, starting with the needs they want to meet, make up a purchasing decision. Where to buy, what to buy, what brand, model, and information is needed to make a decision, Size, the date and amount of the purchase, and the mode of payment. Marketers can influence these judgements by providing information about their goods or services to assist customers in making decisions. Consumers usually turn to their past experiences for pertinent knowledge on particular consuming wants before turning to external sources of information. In other words, consumers are said to rely on their internal evidence while making decisions on what to buy. Additionally, many customer judgements are usually formed by fusing information from non-commercial sources and marketing campaigns with past purchasing experiences. Previous studies have revealed that consumers usually seek to lower risk while making purchases (Zaidan, 2021).
The literature on e-commerce has extensively investigated customer happiness. Numerous research has discovered a connection between behaviour and customer satisfaction, demonstrating that customer pleasure is directly tied to customers’ intentions to make purchases. The effectiveness of argumentation, recommendations, and recommender systems is closely related to client satisfaction. There are currently many customer-facing assessment methods in use. This relates to the user’s welfare (Jiang & Shao, 2022). It is possible to refer to customer satisfaction as “happy” or “improved experience”.
The benefits that purchasers obtain from natural self-service and scarcity produce a very high level of risk and trust failure, even though e-commerce has made it simpler to acquire goods and services online. Early studies usually use more research than is advised. Link to a personal computer.
Characteristics of buyer-e-commerce interactions. The concept of trust is central to e-commerce structures. However, there are not many studies that have concentrated mainly on the idea of system dependencies and how they are used in the context of recommender systems. The user’s perception of the system’s overall dependability is reflected in the reliability attribute. Confidence measures a customer’s sensitivity to or readiness to consider the risk of loss when making an online purchase. It appears to be a compilation of individual viewpoints on various characteristics. It states that the service provider will specify the activity’s completion time following the procedure.
Business experts and managers concur that developing a welcoming physical area may help attract and retain customers. There is widespread agreement that atmosphere is essential in the retail marketplace. Color, music, vision, and other clues are considered while determining ambient aspects to influence consumer behaviour and boost sales. Layout and position are essential cues in the eyes of consumers. The term “material” refers to the ambience created by general design, colour, pattern, décor, setting, and beauty. There is a focus on several indications, like the store’s atmosphere. Environment, colour, sound, aroma, taste, layout, and location are all things that buyers take into consideration. Additionally, previous studies have shown that the physical surroundings impact consumer choice and aid in differentiating service providers from rivals. It offers the capacity to gauge consumer perceptions of characteristics in the retail environment.
By ingraining specific brand associations in their minds, strengthening their perception of brand value, increasing purchase intent by reducing costs and time commitments, and concentrating on client acquisition efforts. Service providers can use their physical surroundings to set their businesses apart from rivals and sway customer decisions. Previous studies have shown that the retail environment has a favourable impact on consumer purchase behaviour. For instance, a retail space’s physical surroundings impact Arab customers’ behaviour when making purchases. Similarly, emphasis was placed on creating a welcoming store environment in the past. Many marketers view surveys as a crucial strategic tool for influencing consumer behaviour and improving results. Increasing consumer awareness of the services and quality of supermarket goods.
The platform’s diversity of products significantly impacts users’ enthusiasm for using Cross Border (Hewei, 2022). According to academic literature, the median parallel difference between the suggested product items is the best way to understand “diversity.” We can offer the most possibilities to everyone by using this “diversity strategy.” The level of difference in the list of proposals is also described using the word “diversity.” An item-based honesty assessment measure cannot be used for resolutions to evaluate a supplied list of endorsements. Users may discontinue utilizing the system out of dissatisfaction with its lack of variation.
The extent to which people believe they are getting their money’s worth can be used to quantify value. Customers’ perceptions of value are influenced by various aspects, including whether their demands are met, whether the product or service is of high quality and affordable compared to alternatives and whether they are happy with their purchase. Numerous studies have demonstrated that consumer perceptions of value influence purchases in a significant way. We refer to “perceived value” as the judgment a consumer makes about the worth of a good or service based on the price they pay for it. The “perceived value” of a good or service is the “psychological assessment and idea of the perceived advantage of buying the good or service” by the client. Providing value to your clients will make them happier and more devoted. Many academics agree that businesses and customers must have happy clients and high-quality goods.
The projected e-commerce frontier system’s specific qualities that affect consumers’ buying intentions were investigated in this study using TAM. The findings show a variety of perceived qualities, including user fidelity and familiarity, past and present relevance, customer satisfaction, perceived utility, and usability.
Figure 1 conceptual framework
Using a descriptive research design, this investigation. The three main areas of descriptive research are what, where, and how to study events. The phases of data collecting, analysis, and conclusion-making are all included in research methodologies. He pointed out that by gathering information about people’s attitudes, perceptions, behaviours, and values, observational research aims to explain real-world phenomena. Many people can be contacted for free to provide data. The obtained data makes comparisons simple. Additionally, it shows up when there are two or more variables at a particular time.
This information was gathered through surveys that people completed about their experiences shopping in the Arabian Peninsula. We have noticed an increase in online advertising on this website over the last few years. Any item can be bought or sold on their vast internet market. A significant survey was conducted using a random sample of 204 people to evaluate the study model’s validity and test the hypotheses. This study aimed to pinpoint elements in the selected Arabian countries’ retail industries that indicate a consumer’s final purchasing choice. Furthermore, researchers should select quantitative methodologies when a large portion of their sample group is being studied, and there is little requirement for specific expertise or training to complete the questionnaire. The direction that quantitative research can give to scientific undertakings is helpful.
Data analysis and extrapolation to a particular situation to decrease the impacts of response bias and sample error, respondents were informed of the study’s goals and that their responses would remain anonymous. Before data collection, several design factors were considered when developing the questionnaire. A buyer’s tendency to make a purchase is rated on a five-point scale. The CSR indicator utilized in this study was also obtained by measuring social media advertising. Additionally, samples were collected to evaluate the environment of the shop. A total of four items were employed to determine how much people valued various components of the study. All the items were rated using the Likert scale, ranging from “strongly disagree” to “strongly agree.”
Design Analysis and Results
Only 199 of the 204 questionnaires given to Arabian consumers (Qatar) received responses. The demographic split revealed that male respondents made up 45.3% of the total, while female respondents made up 54.7% of the total. According to their responses, most respondents had at least a bachelor’s degree. The respondents were then divided into groups based on their monthly incomes; 15 (5.4%) made between QAR 501 and QAR 1000, while 47 (17.2%) made less than QAR 500. 71% of respondents reported having a monthly income of QAR 4,001 or more (25.4%). Of the total responses, 44 (or 52%) came from those making between QAR 1,001 and QAR 4,000 annually.
In this study, we tested our idea using structural equation modelling. The results showed that Cronbach’s alpha for all construct measurement scales was more significant than 0.70 after reliability assumptions for all constructs were made. We can conclude with confidence that reliability has been met as a result.
The process was carried out on AMOS 18. Think about the measurement model first. A sample of all construct measurement items was chosen for statistical validation. The component analysis results show that the remaining items in each construct had factor loadings more prominent than 0.50, indicating convergent validity. Finally, the structural model is estimated, which contains all residual components. The hypotheses can be tested when the fit indices of the structural model are within the typical range of error.
The evaluation of structural models with residual components. The hypothesis can be tested if the structural model’s fit index falls within a desirable range. The chi-square value was generally 376.333 1 (p = 0.000), as shown in Figure 3, showing that the structural model of this study maintained a decent connection with the data; the values of other parameters were within acceptable bounds. GFI = 0.841, AGFI = 0.792, df = 230, TLI = 0.909, CFI = 0.924, and RMSEA = 0.063 are among the numbers. To determine whether the data set has a normal distribution, multicollinearity for all variables is calculated using AMOS 18. When there is a correlation of 0.90 or higher between two different variables, multicollinearity is present. Table 1 demonstrates that the current dataset, where the correlation between any two variables is less than 0.90, does not contain any indication of multicollinearity. We verified the discriminant validity of the constructs by calculating the average variance extracted (AVE) and the correlation coefficient between each pair of constructs. Discriminant validity is indicated by a correlation between two constructs of less than 1.00.
According to him, discriminant validity exists when there is a correlation of less than 0.95 between two constructs. The findings suggest that these constructs have discriminant validity in general. After finding a satisfactory fit for the structural model and satisfying the conditions of reliability and validity, the study’s hypothesis was validated. The data in Table 1 demonstrated that CSR had a considerable positive impact on purchasing decisions (b = 0.188, C.R. = 1.803, p = 0.10), which led to the acceptance of the conclusions presented in H1. Customer satisfaction had no discernible impact on purchasing decisions, contrary to predictions, as seen by the results of H2 (b = 0.165, C.R. = -1.536, p > 0.05). H3 was acceptable because the study also demonstrated that the store atmosphere had a beneficial impact on purchasing decisions (b = 0.351, C.R. = 2.637, p = 0.05). H4 was disproved since the findings also indicated a detrimental impact on perceived diversity (b = 0.158, C.R. = 2.035, p = 0.05) and purchase decisions. Finally, the findings of this study demonstrate that it significantly influences purchase decisions (b = 0.593, C.R. = 4.142, p 0.05), supporting the validity of hypothesis 5. These elements account for 72% of the variance in purchasing decisions overall.
CHAPTER 4: RESULTS
The evaluation of structural models with residual components. The hypothesis can be tested if the structural model’s fit index falls within a desirable range. The chi-square value was generally 376.333 1 (p = 0.000), as shown in Figure 3, showing that the structural model of this study maintained a decent connection with the data; the values of other parameters were within acceptable bounds. GFI = 0.841, AGFI = 0.792, df = 230, TLI = 0.909, CFI = 0.924, and RMSEA = 0.063 are some of the numbers. To determine whether the data set has a normal distribution, multicollinearity for all variables is calculated using AMOS 18. When there is a correlation of 0.90 or higher between two different variables, multicollinearity is present. Table 1 demonstrates that the current dataset, where the correlation between any two variables is less than 0.90, does not contain any indication of multicollinearity. We verified the discriminant validity of the constructs by calculating the average variance extracted (AVE) and the correlation coefficient between each pair of constructs. A correlation between two constructs of less than 1.00 implies discriminant validity.
According to him, discriminant validity exists when there is a correlation of less than 0.95 between two constructs. The findings suggest that these constructs have discriminant validity in general. After finding a satisfactory fit for the structural model and satisfying the conditions of reliability and validity, the study’s hypothesis was validated. The data in Table 1 demonstrated that CSR had a considerable positive impact on purchasing decisions (b = 0.188, C.R. = 1.803, p = 0.10), which led to the acceptance of the conclusions presented in H1. Because of the unexpected results and the finding that customer satisfaction had no discernible impact on purchasing decisions, hypothesis 2 was rejected (b = 0.165, C.R. = -1.536, p > 0.05). H3 was acceptable because the study also demonstrated that the store atmosphere had a beneficial impact on purchasing decisions (b = 0.351, C.R. = 2.637, p = 0.05). H4 was disproved since the findings also indicated a detrimental impact on perceived diversity (b =0.158, C.R. = 2.035, p = 0.05) and purchase decisions. Finally, the findings of this study demonstrate that it significantly influences purchase decisions (b = 0.593, C.R. = 4.142, p 0.05), supporting the validity of hypothesis 5. These elements account for 72% of the variance in purchasing decisions overall.
CHAPTER 5: DISCUSSION AND CONCLUSION
Discussion and Conclusion
This study examines the effects of customer satisfaction, trust, the store environment’s perceived purpose, and perceived value on consumer choices in the Arab retail market. According to survey findings, customer trust influences purchases favourably, which is consistent with other studies. People are more likely to buy goods and services from consumers if they feel that the customers believe in them and the community. This essay’s second objective is to investigate the relationship between consumer pleasure and purchasing behaviour. The research revealed that, in contrast to expectations, customer satisfaction marketing had minimal impact on consumers’ purchase choices. Lack of or ineffective client satisfaction-related marketing endeavours in the chosen retail outlets may cause insignificant results. Additionally, negative word-of-mouth influences consumer satisfaction, which may lower consumer buying propensity.
The results of this study also show that the retail environment has a significant favourable influence on purchasing decisions. The retail environment has been established to affect consumers’ buying decisions significantly. It was emphasized that the retail setting aids brand differentiation, resulting in favourable customer selections. As a result, retailers use the store environment as a critical tool to influence customer behaviour and purchases. The results also show that perceived diversity hurts purchasing choices.
Diversity perception has a detrimental impact on consumer purchasing decisions. This study demonstrates that because lower-priced items typically have lesser quality, perceived variety hurts consumers’ perceptions of brand quality. People consequently held common perceptions of variation. The brand structure is unaffected, and brands, particularly well-known ones, may be less affected.
Finally, the results of this study show that perceptions of value significantly influence purchasing choices. Perceived value has a significant impact on consumer purchase decisions. This shows that value-added marketing techniques boost customer purchases while boosting business profitability. Therefore, in a highly competitive market environment, retailers are advised to build their customer value to gain a competitive advantage. Retailers should focus on explaining to customers the value of their products, evaluating their prices compared to competitors, and tracking how their prices affect customers’ purchase decisions, claims the research.
Abraham, M. M., & Choe, P. (2021, July). Factors Affecting e-Commerce Satisfaction in Qatar: A Cross-Cultural Comparison. In International Conference on Human-Computer Interaction (pp. 481-494).
Springer, Cham. Al-Adwan, A. S., Alrousan, M. K., Yaseen, H., Alkufahy, A. M., & Alsoud, M. (2022). Boosting Online Purchase Intention in High-Uncertainty-Avoidance Societies: A Signaling Theory Approach. Journal of Open Innovation: Technology, Market, and Complexity, 8(3), 136.
Hadi, M. N., Hadi, A. N., & Abdulrab, M. A. (2019). Effect of Vendor Characteristics and Relationship Quality on Consumer Re-Purchase Intention in the B2C E-Commerce in Yemen. International Journal of Research in Business and Social Science (2147- 4478), 8(4), 172-184.
Hasan, M., & Sohail, M. S. (2021). The influence of social media marketing on consumers’ purchase decision: investigating the effects of local and nonlocal brands. Journal of International Consumer Marketing, 33(3), 350-367.
Hewei, T. (2022). Factors affecting clothing purchase intention in mobile short video app: Mediation of perceived value and immersion experience. Plos one, 17(9), e0273968.
HERZALLAH, F., AYYASH, M. M., & AHMAD, K. (2022). The Impact of Language on Customer Intentions to Use Localized E-Commerce Websites in Arabic Countries: The Mediating Role of Perceived Risk and Trust. The Journal of Asian Finance, Economics and Business, 9(1), 273-290.
Jiang, H., Lin, Y., Luo, X., & Shao, T. (2022). Understanding the Selection of Cross-Border Import E-Commerce Platforms Through the DANP and TOPSIS Techniques: A MultiStudy Analysis. Journal of Global Information Technology Management, 25(1), 26-53.
Kidane, T. T., & Sharma, R. R. K. (2016, March). Factors Affecting Consumers’ purchasing Decision through ECommerce. In Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management Kuala Lumpur, Malaysia (Vol. 8, No. 10, pp. 159-165).
Ma, Y., Ruangkanjanases, A., & Chen, S. C. (2019). Investigating the impact of critical factors on continuance intention towards cross-border shopping websites. Sustainability, 11(21), 5914. Rosário, A., & Raimundo, R. (2021). Consumer Marketing Strategy and E-Commerce in the Last Decade: A Literature Review. Journal of Theoretical and Applied Electronic Commerce Research, 16(7), 3003-3024.
Santoso, A., Bidayati, U., & Hendar, H. (2019). Factors Influencing Online Purchase Intention: A Consumer Behavioral Study on Indonesia.
Shahrel, M. Z., Mutalib, S., & Abdul-Rahman, S. (2021). PriceCop-Price Monitor and Prediction Using Linear Regression and LSVM-ABC Methods for E-commerce Platform. International Journal of Information Engineering & Electronic Business, 13(1).
Tan, K. L., Tan, H. H., & Loo, T. K. (2022). FACTORS INFLUENCING THE CONSUMER PURCHASE INTENTION IN E-COMMERCE. International Journal of Business and Economy, 4(3), 98-111.
Thalji, Z. (2022). Using Multiple linear regression model to predict The Customers’ Purchase Decision based on After-Sales Services.
Yang, Y., & Lin, W. L. (2022). The Impact of Consumer Trust and Consumer Loyalty on Sustainable Development of Cross-border E-commerce. Specialusis Ugdymas, 1(43), 523-538.
Zaidan, M. N., & Raju, V. (2021). Factors affecting the online purchase intention among Iraqi using enhanced technology acceptance model. IJAR, 7(7), 52-61. 18