• Fashion & Textile Research Journal
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• v.23 no.5
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• pp.586-597
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• 2021

Personalized product recommendation service is receiving attention as a new marketing strategy while supporting consumer information search and purchasing decisions. This study attempted to verify the effect of self-reference on service use behavior through the dual path of cognitive attitude and emotional attachment. Using convenience sampling, an online survey was conducted with 324 women who were in their 20s and 30s. After collecting and compiling the survey data, the reliability and validity of variables constituting the conceptual research model were verified through confirmatory factor analysis using AMOS 22.0. Next, the significance of sequentially mediated pathways was verified using Process 3.5 Model 80. The results showed that self-referencing not only significantly affects service use intention by simply mediating cognitive attitudes but also sequentially mediates cognitive attitudes and additional information search. Furthermore, self-referencing was significant as an indirect path to service use intention by mediating additional information search. However, in the path mediated by emotional attachment, self-referencing was considered as a simple mediated path leading to service usage intention. These results indicate a dual path in the psychological mechanism, through cognitive and emotional evaluation, that prompts consumer behavioral responses to the personalized product information provided in the shopping process.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.297-307
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• 2021

In the vibrant environment, documentation and managing systems are maintained autonomously through education foundations, book materials and libraries at the same time as information are not voluntarily accessible in a centralized location. At the moment Libraries are providing online resources and services for education activities. Moreover, libraries are applying outlets of social media such as Facebook as well as Instagrams to preview their services and procedures. Librarians with the assistance of promising tools and technology like analytics software are capable to accumulate more online information, analyse them for incorporating worth to their services. Thus Libraries can employ big data to construct enhanced decisions concerning collection developments, updating public spaces and tracking the purpose of library book materials. Big data is being produced due to library digitations and this has forced restrictions to academicians, researchers and policy creator's efforts in enhancing the quality and effectiveness. Accordingly, helping the library clients with research articles and book materials that are in line with the users interest is a big challenge and dispute based on Taibah university in Saudi Arabia. The issues of this domain brings the numerous sources of data from various institutions and sources into single place in real time which can be time consuming. The most important aim is to reduce the time that lapses among the authentic book reading and searching the specific study material.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.229-237
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• 2021

Our modern 'information-hungry' age demands delivery of information at unprecedented fast rates. Timely delivery of noteworthy information about recent events can help people from different segments of life in number of ways. As world has become global village, the flow of news in terms of volume and speed demands involvement of machines to help humans to handle the enormous data. News are presented to public in forms of video, audio, image and text. News text available on internet is a source of knowledge for billions of internet users. Urdu language is spoken and understood by millions of people from Indian subcontinent. Availability of online Urdu news enable this branch of humanity to improve their understandings of the world and make their decisions. This paper uses available online Urdu news data to train machines to automatically categorize provided news. Various machine learning algorithms were used on news headline for training purpose and the results demonstrate that Bernoulli Naïve Bayes (Bernoulli NB) and Multinomial Naïve Bayes (Multinomial NB) algorithm outperformed other algorithms in terms of all performance parameters. The maximum level of accuracy achieved for the dataset was 94.278% by multinomial NB classifier followed by Bernoulli NB classifier with accuracy of 94.274% when Urdu stop words were removed from dataset. The results suggest that short text of headlines of news can be used as an input for text categorization process.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.53-58
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• 2023

The trend of satisfying consumer needs (payment for mobile communication, music services, cab ordering, banking products, and food delivery) on a unified online platform has shaped a digital ecosystem, an instrument creating a unified space of economic interaction. Representatives of e-commerce are major stakeholders in the development of such tools. In particular, subscription services (multiservice subscriptions) allow users to create their own ecosystems based on their personal preferences. The rate of subscription service use is growing around the world, yet understanding of the peculiarities of development of this e-commerce sphere is limited due to insufficient research.The study aims to determine the motives and barriers to the use of subscription services (multiservice subscriptions) by consumers and their relationship with consumer characteristics.Proceeding from an online survey of 200 users, the study determines the relationship between the gender and income of consumers and their use of subscription services, motives and motivators for using subscription services, and barriers to the choice of a particular subscription service. The obtained results may serve as a basis for managerial decisions in e-commerce and for improving the effectiveness of marketing solutions.

• Journal of Distribution Science
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• v.22 no.3
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• pp.21-31
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• 2024

Purpose: The primary aim of this study is to explore how social media marketing influences customer purchase intention, focusing on the roles of customer engagement and trust as mediators. Research Design, Data, and Methodology: The investigation utilized an online survey conducted in Chinese on the Questionnaire Star platform. It targeted male and female consumers aged 18 and above who purchase products online, yielding 1107 valid responses from across major Chinese cities. Results: Analysis reveals that social media marketing significantly affects customer purchase intention in a positive manner. It also enhances customer engagement and trust, which serve as crucial mediating variables linking social media marketing to purchase intention. The study found that engagement and trust facilitate brand identification and alignment, thereby directly boosting purchase intention. Conclusion: The findings offer essential insights for businesses aiming to improve their social media marketing impact on consumer behavior. It highlights the importance of fostering user engagement and trust, as well as creating a favorable brand image. These elements are key to influencing consumer purchase decisions within social media contexts. The study advises businesses to engage deeply with consumers and build trust, providing practical recommendations for navigating the evolving social media environment towards sustainable growth.

• Asia pacific journal of information systems
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• v.29 no.3
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• pp.382-406
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• 2019

We study the antecedents to tie formation on an (Facebook-like) enterprise social media platform implemented to support cross-boundary connections. Research has produced mixed findings regarding the role of social media in cultivating bridging vs. closed networks. We examine the tie formation patterns of 1,386 enterprise social media users over a two-year period. Specifically, we observe who became (or chose not s become) "friends" with whom at the dyadic level and relate the decisions to various mechanisms that affect one's network to expand, constrain, or bridge. Using logistic and OLS regressions, we find that users tend to form ties via reciprocity and transitivity (with friends of friends), both of which help expand one's network. We also find strong networking tendency toward functional and hierarchical homophily (same business unit and same rank, respectively), which is likely to constrain one's network (closed network structure). We find that one's participation in various online interest groups is likely to open one's network (bridging network structure) while no evidence found for preferential attachment. Overall, we find that enterprise social media offers features, some of which are likely to foster bridging while others foster closed networks via different mechanisms.

• Smart Structures and Systems
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• v.33 no.3
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• pp.227-241
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• 2024

Safety and structural integrity of civil structures, like bridges and buildings, can be substantially enhanced by employing appropriate structural health monitoring (SHM) techniques for timely diagnosis of incipient damages. The information gathered from health monitoring of important infrastructure helps in making informed decisions on their maintenance. This ensures smooth, uninterrupted operation of the civil infrastructure and also cuts down the overall maintenance cost. With an early warning system, SHM can protect human life during major structural failures. A real-time online damage localization technique is proposed using only the vibration measurements in this paper. The concept of the 'Degree of Scatter' (DoS) of the vibration measurements is used to generate a spatial profile, and fractal dimension theory is used for damage detection and localization in the proposed two-phase algorithm. Further, it ensures robustness against environmental and operational variability (EoV). The proposed method works only with output-only responses and does not require correlated finite element models. Investigations are carried out to test the presented algorithm, using the synthetic data generated from a simply supported beam, a 25-storey shear building model, and also experimental data obtained from the lab-level experiments on a steel I-beam and a ten-storey framed structure. The investigations suggest that the proposed damage localization algorithm is capable of isolating the influence of the confounding factors associated with EoV while detecting and localizing damage even with noisy measurements.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.107-113
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• 2016

Following the recent advancement in the use of social networks, a vast amount of different online reviews is created. These variable online reviews which provide feedback data of contents' are being used as sources of valuable information to both contents' users and providers. With the increasing importance of online reviews, studies on opinion mining which analyzes online reviews to extract opinions or evaluations, attitudes and emotions of the writer have been on the increase. However, previous sentiment analysis techniques of opinion-mining focus only on the classification of reviews into positive or negative classes but does not include detailed information analysis of the user's satisfaction or sentiment grounds. Also, previous designs of the sentiment analysis technique only applied to one content domain that is, either product or movie, and could not be applied to other contents from a different domain. This paper suggests a sentiment analysis technique that can analyze detailed satisfaction of online reviews and extract detailed information of the satisfaction level. The proposed technique can analyze not only one domain of contents but also a variety of contents that are not from the same domain. In addition, we design a system based on Hadoop to process vast amounts of data quickly and efficiently. Through our proposed system, both users and contents' providers will be able to receive feedback information more clearly and in detail. Consequently, potential users who will use the content can make effective decisions and contents' providers can quickly apply the users' responses when developing marketing strategy as opposed to the old methods of using surveys. Moreover, the system is expected to be used practically in various fields that require user comments.

• The Research Journal of the Costume Culture
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• v.22 no.1
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• pp.126-142
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• 2014

This research aims to analyze jeans possession and perceptions of jeans' fit among women in their 20s to help improve the accuracy of purchase decisions in online shopping and to provide basic data necessary to overcome limits in the fit conveyance method of online shopping malls. A sample of 149 females in their 20s was divided into two groups according to height, waist size, and interest in fashion, and several factors were analyzed: jeans possession status, the fit of purchased jeans, the reason for purchase, and the perception of jeans' fit. The results are as follows. The group with a high interest in fashion owned more skinny jeans, and there was a higher frequency of purchasing skinny jeans during the last year among those with a height of 160 cm or more, a waist size of less than 27 inches, and a high interest in fashion. Of the respondents, 92.6% accurately understood skinny fit, 51.7% understood straight fit, and 56.4% understood regular fit. There was no significant difference in the perception of skinny fit or regular fit, but straight fit was better understood by the group with a waist size of 27 inches or more. Thus, by providing accurate size information and analyzing the body shapes of consumers, online shopping malls will be able to increase customer satisfaction with pants of various fits to reduce the rate of returns.

• Journal of the Korean Society of Costume
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• v.66 no.4
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• pp.32-44
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• 2016

The purpose of this study is to examine the cognitive responses and the corresponding behavior responses of consumers who have experiences in not being able to buy a product in an online shopping mall due to it being sold-out. Responses were gathered from 526 consumers between the ages of 20 to 40 years residing in a metropolitan area. Each person surveyed had experienced a situation in which a product that they wanted to purchase from an online shopping mall was sold-out. SPSS 18.0 was used to perform frequency analysis, factor analysis, reliability analysis, and regression analysis. The first set of results of this study showed positive responses of quality, discernment, scarcity, but also negative cognitive responses of careless management, manipulation of shopping mall management, and common taste. In negative cognitive responses, sold-out situations caused consumers inconvenience. The second set of results revealed that quality, discernment, and careless management had a significant effect on product replacement (Substitute, S); likewise, factors such as quality, discernment, careless management, manipulation by shopping mall designers, and common taste had a significant effect on the delay of purchasing decisions (Delay, D). Scarcity, careless management, manipulation by shopping mall designers, and common taste also demonstrated significant influence on the incomplete leaving of stores (Incomplete Leave, L1), while discernment, scarcity, careless management, manipulation by shopping mall designers, and common taste had a significant influence on the complete leaving of stores (Complete Leave, L2). Previous studies have examined the behavioral response topics of substitute, delay, and leave. These study results suggest that product sellouts at online shopping malls did not have a solely negative effect on consumers. It actually had a positive effect in terms of discernment, scarcity, and the perception of quality of sold-out products. Furthermore, both positive and negative cognitive responses had various effects on behavioral responses.