جستجوی مقالات مرتبط با کلیدواژه "فروشگاه های اینترنتی" در نشریات گروه "مدیریت"

The present study sought to evaluate and elaborate factors affecting online marketing. An applied mixed research method (qualitative and quantitative) was conducted. The statistical population of the qualitative research consisted of 51 university experts were selected and interviewed using targeted sampling. The statistical population of the quantitative study consisted of 400 consumers of the Caspian Sea seashore area in online business, who were randomly selected by clusters sampling method. The qualitative research instrument used was semi-structured interviews, and the instrument used for quantitative data collection was a researcher-made questionnaire based on qualitative results. Coding method was used for qualitative data analysis, and exploratory factor analysis method and SPSS 24 were used for quantitative data analysis. The results demonstrated five primary factors: (1) electronic services (Internet services, complimentary gifts and free services, backup access, website attractiveness, and ease of access), (2) electronic advertisement (online advertising and message content), (3) electronic security (customer trust, guarantee claim, recognized security and trust), (4) electronic support (perceived support, communication control, excellent efficacy, brand promotion, online seller's marketing strategies), (5) electronic customer orientation (customer experience, information transparency, consumer attachment, abundant profitability, uncontrollability, and customer satisfaction and loyalty). The exploratory factor analysis revealed that electronic services had the maximum share and effect in online marketing (81.568%); electronic advertisement ranked the next (79.441%), and then electronic security (73.730%), electronic support (72.156%), and customer orientation (67.162%).

In Most Developing and Developed Countries, Social Media have Covered Almost all Aspects of People's Lives. Paying Attention to Social Media Provides the Basis for Customer Orientation to Online Stores and their Loyalty. This Study Aims to Investigate the Impact of Social Media on the Loyal Behavior of Customers to Commercial Websites, Considering the Mediating Role of Customer Commitment for Online Purchases from Online Stores. This Research is Practical in Nature and Descriptive Correlational in Terms of Data Collection Method. The Statistical Population Includes Customers of Online Stores in Shiraz.To Determine the Members of the Sample, Due to the Large Size of the Community and the Fact that There Was no List of Customers, the Accessible Sampling Method was Chosen. Using This Sampling, 384 Questionnaires Were Collected With a Reliability of 0.92. And a Standard Questionnaire has been Used to Measure the Variables. The Results Showed That Social Media has a Positive and Significant Effect on the Loyal Behavior of Customers to Online Sales Websites Due to the Mediating Role of Customer Commitment. Also, the Regression Coefficient for the Relationship Between Social Media on Customer Commitment Was 0.85 and The Value of the Regression Coefficient for the Effect of Customer Commitment on Loyal Behavior was 0.83.

In the context of online shopping, websites play a critical role in facilitating transactions between buyers and sellers. An online store's website acts as a focal point for a company's online identity and encompasses not only the products and services offered but also the company's aesthetic image and values. Creating a strong online identity helps an online store differentiate itself from competitors, attract and retain customers to strengthen its competitive advantage, and improve brand, product, or service differentiation. On the other hand, understanding the repeat purchase intention of consumers is essential for maintaining growth in this business. This research, by providing a new theoretical perspective for understanding the online shopping behavior of committed customers, shows that a store's website creates a specific identity that itself affects the repeat purchase intention. The present study examines the factors affecting website cultural identity and the repeat purchase intention by testing a conceptual model by King et al. (2016) in order to develop the model. Based on the information gathered from 463 customers of online stores in Tehran, including a segment of students of Islamic Azad University, Science and Research Branch, the results of this research showed that increasing product attractiveness, service attractiveness, customer e-satisfaction, fulfillment, website cultural identity, and website attractiveness leads to an increase in the repeat purchase intention. Increasing website trustworthiness, product attractiveness, service attractiveness, and website attractiveness leads to an increase in website cultural identity. Increasing website attractiveness and fulfillment leads to an increase in customer e-satisfaction. However, increasing website trustworthiness does not lead to an increase in the repeat purchase intention. The results can be a basis for online stores to understand and use website cultural identity as a new strategy for attracting and retaining customers with a focus on the repeat purchase intention.

Today, virtual businesses need to innovate in order to have a better market performance. But the ability of companies to acquire innovation is one of the serious challenges of online stores; Based on this, the present research has been done with the aim of designing a model for innovation on the market performance of online shopping websites with the approach of narrative analysis. This study has a qualitative approach. The statistical population included all narratives related to the dimensions of innovation and market performance of prominent online shopping websites in the country. With the help of judgmental sampling method, 69 narratives were examined. Narratives have been analyzed by searching websites and blogs and using the three-step open, central and selective coding method in the form of a topic network. The results indicated 7 organizing themes and 161 basic themes. The identified dimensions include the business model innovation dimension (the sub-dimension of business model type and revenue flow), the organizational innovation dimension (the structure innovation sub-dimension, strategic innovation and innovation culture), the marketing innovation dimension (the product innovation sub-dimension, price innovation, distribution innovation , promotion innovation, advertising innovation, customer segmentation innovation, value proposition innovation and customer relationship innovation), process innovation dimension (technology innovation sub-dimension and safety innovation), credibility innovation dimension (trust innovation sub-dimension and expertise innovation) and market performance dimension ( sub-dimensions of financial performance and non-financial performance) which were included under the overarching themes of innovation and performance of prominent online shopping websites in the country.

These days, Emergence of e-commerce web sites is one of the important consequences of the Internet in modern times, but products data is growing exponentially. In such environment, customers face a problem in finding optimized information among huge data bases about the items or desired products. In order to assist buyers, large e-commerce companies are planning to introduce their own recommender systems to help their customers in making a better choice among the items. Due to high percentage error , a basic method to build such systems is not usually being applied. In this essay, two methods have been suggested in order to improve recommendations in recommender systems. Collaborative filtering method is one of the most successful methods used in the system, but using this method that it has common problem the increasing number of users and products, therefore system do not inability to request the requirement of cold start and data sparsity. Two methods have been suggested in order to improve recommendations in recommender systems. To resolve this problem, a new method has been introduced in which by integrating rating time by Pearson also combining semantic technology with social networks offers a solution to reduce issues such as "cold start" and generally "data sparsity" in recommender systems. The result of simulating showed that the proposed approach provided better performance and more accurate predictions in addition of more consistent with user preferences.

In recent years internet shops have had considerable growth. Performance measures are needed for these shops to maximize the use of resources and getting closer to the aims, to provide the identification of strengths and weaknesses along with minimizing resource inputs to improve the situation. Data Envelopment Analysis (DEA) method is a nonparametric method for measuring technical efficiency and performance of a set of units. This study given the importance of assessing the performance of internet shops and using multiple input-oriented CCR model, measure the performance of internet shops. In this study, internet shop production process is divided into two stages: marketability and profitability. So to calculate the efficiency, a two-stage model of data envelopment analysis is used. Based on the data collected, the efficiency of 37 Internet stores evaluated. Results include overall efficiency and efficiency of marketability and profitability stages. After determining the efficiency of marketability and profitability stages, inefficient stages were identified and solutions were proposed to improve it.

Complementary to the increasing popularity of the internet and WWW, e-commerce has become a significant global economic force. The online retail stores need to attract more visitors and convert them to customers. To achieve this goal these stores need to be trustworthy for the visitors and customers. This study investigates the factors influencing customers’ trust in online stores. The research design includes both qualitative and quantitative phases. In the qualitative phase, a cognitive map of the factors influencing online trust using Delphi method is developed. The model carries out 78 factors influencing online trust and has 83 links between these factors. In the quantitative phase, the links in the model are weighted using fuzzy analysis method. The findings show that previous purchase experience, perceived risk, related laws and regulations, culture, online payment risks, updated security systems among all the factors in the model have the strongest effect on online trust. The study is significant as it presents a new and indigenous integrative model.