درخت حوزه‌های تخصصی

This study aims to assess the efficiency of the eHealth program by conducting a comparative study between public and private healthcare settings in Bangladesh and Malaysia. A detailed literature review gathered from leading databases, articles, and case studies was conducted to achieve the study’s objective. After evaluating the literature and utilizing reducing methods the factors were organized and categorized into the four SWOT groups. The study exhibits that the government of Bangladesh has taken multiple approaches to efficient usage of their resources and providing primary healthcare services at grassroots levels. However, compared to a developing country like Malaysia it is far lag and struggling with multiple challenges like inadequate ICT infrastructure interoperability issues, low adoption of services, privacy and trust issues inadequate data security lack of policies and regulations, and insufficient funding along with multiple threats like resistance to change, cultural influence, and native environmental issues. Nonetheless, these challenges can be addressed through the development of adequate infrastructure, technology, financial support, and human resource capabilities. This will help to achieve the goal of universal health coverage and digital healthcare. This paper identified and explored numerous eHealth concerns and institutionalized favorable policy recommendations to establish an effective and successful eHealth system and boost the healthcare sectors of Bangladesh and similar emerging economies.  Being the first to incorporate SWOT analysis and eHealthcare programs, the suggested approaches can have a significant positive impact on the implementation of an effective and sustainable eHealth system.

Purpose: This study extends the current understanding of customer engagement by examining the impact of relationship bonding and relationship quality on customer engagement in value creation for online taxis.Method: A quantitative research design was used to validate the hypotheses proposed in this research. Customer engagement has become an important metric for measuring the quality of relationships between brands and their customers. Despite this, there has been limited research into how relationship bonds affect the effectiveness of building such a relationship in online taxi services. A survey was conducted using the convenience method among 600 users of online transportation services in the city of Urmia, Iran to test the theoretical model. Structural equation modelling in software Amos 23 were used in this study to test the research hypotheses. Findings: Findings showed that relationship bonding (financial, social, and structural) positively affects the quality of online relationships. Moreover, it was found that the quality of online relationships had a positive impact on all four aspects of customer engagement value (lifetime value, influence value, customer knowledge value, and customer referral value).Conclusion: In order to demonstrate the promotion of customer engagement through relationship bonds and online relationship quality, the study adds new data to the literature on online taxis services. Online taxi services are able to offer open innovation structures to help them   increase customer engagement, gather innovative ideas and integrate them into their operations. In this regard, in order to enrich ideas, customers who have successfully come up with new ideas should be rewarded.

Purpose: Start-up businesses have attracted considerable attention regarding the new approach in the modern economy The present study was conducted to investigate the factors affecting the improvement of customers’ online shopping experience in e-commerce start-ups in the healthcare sector.Method: This is an applied research conducted as a descriptive-survey. The target population includes all customers who used the electronic start-up services in the healthcare sector; out of which a sample of 384 individuals was selected using the Morgan table. A self-administered questionnaire was developed to collect the data which were analyzed using partial least squares and Smart-PLS software.Findings: All research hypotheses were confirmed, and it was proved that factors such as customer respect, customer enjoyment, importance of time, information security, convenience, perceived experience, valuable experience, and perceived image experience have a positive effect on improving customers’ online shopping experience in e-commerce start-ups.Conclusion: Applying the proposed model helps e-start-ups increase their performance   by eliminating their shortcomings and boosting their strengths.

The term "clickbait" refers to content specifically designed to capture readers' attention, often through misleading headlines, leading to frustration among social media users. In this study, titled "Mushakkal," which translates to "variety" in Arabic, we utilized a Convolutional Neural Network (CNN)—a deep learning approach—to detect clickbait within an Arabic dataset. We compared three optimizers: RMSprop, Adam, and Adadelta, evaluating various parameter settings to determine the most effective combination for detecting clickbait in Arabic content. Our findings revealed that the CNN model performed best when both pre-processing and Word2Vec techniques were applied. The Adam optimizer outperformed the others, achieving a Macro-F1 score of 77%. The RMSprop optimizer closely followed, attaining a Macro-F1 score of 76%. In contrast, Adadelta proved to be the least effective for classifying Arabic text.

This paper examines the effectiveness of implementing artificial intelligence (AI) in the Google Ads advertising service. The study analyzes the advantages and disadvantages of AI integration, focusing on attribution models and end-to-end analytics. The findings show that traditional metrics, such as CTR, CPC, and ROI, used to evaluate advertising campaign performance, exhibit significant statistical errors when AI tools are applied, with errors reaching up to 35%, exceeding typical business margins. A comparative analysis in the construction industry highlights discrepancies of 10% to 35% between traditional and AI-driven models. The study concludes that universal AI algorithms often fail to account for industry-specific dynamics, leading to inaccurate evaluations. The practical significance of this research lies in proposing an alternative approach that combines traditional evaluation methods with AI-based tools, offering a more reliable framework for assessing campaign effectiveness

Purpose: The purpose of this research was to provide a model for Validating and Presenting Brand-Customer Interaction Model in Digital Platform in the Cosmetics Industry.Method: This research was applied in its purpose and utilized a mixed approach (qualitative and quantitative). In this regard, this study was conducted with the aim of presenting and validating the brand-customer interaction model in Instagram Platform. The present study is a descriptive survey in terms of its practical-developmental purpose and data collection method. The statistical population in the qualitative section includes marketing professors and cosmetics industry managers, 20 of whom were selected by purposive sampling. The statistical population in the quantitative section also includes customers of cosmetics and health products, 384 participants were selected using the convenience sampling. The data collection tools were a semi-structured interview and a researcher-made questionnaire. First, thematic analysis method was used to analyze the expert interviews. Next, the identified pattern was validated using partial least squares method. Thematic analysis and partial least squares were done with MaxQDA software and Smart PLS software, respectively.Findings: The criterion to achieve data saturation has been to achieve repetition in extracting codes. 235 codes were identified in the open coding stage. Finally, three overarching themes, eight organizing themes, and 49 basic themes were obtained through axial coding. Based on the structural equation model, the proposed model was fitted and confirmed.Conclusion: Based on the results, effective marketing and digital content marketing are the basic elements of the model, which increase brand recognition and brand identity among customers by increasing interaction with customers. Brand recognition and identity contribute to positive word-of-mouth marketing, which in turn affects brand positioning on Instagram. Finally, in this way, it is possible to create a constructive and interactive brand-customer relationship.

Purpose: In the present research   the relationship between the dimensions of mental image, brand awareness and brand recognition in attracting customers, has been investigated and analyzed with   marketing of electronic services (the case study of Iran Postbank) especially taken into account. E-marketing has greatly facilitated the banking operation.Method: This research is applied in terms of purpose and descriptive-survey and correlational as regards the nature of data collection. The statistical population of the research includes managers and senior supervisors of Iran Postbank. The sample size of the research is 168 people, and simple sampling method was used, and 117 people were selected for the research. A questionnaire was used to collect data. The validity of the questionnaire was confirmed through content validity and its reliability using Cronbach's alpha coefficient. To analyze the data, structural equation modeling was used with the help of PLS ​​software.Findings: The results of this research showed that the variables of mental image, brand awareness and brand recognition have a significant and positive impact on the marketing of electronic services, also the marketing of services has a positive and significant impact on customer attraction and the marketing of electronic banking services will increase customer attraction.Conclusion: Given the increasing competition among Iranian banks and the challenge of attracting new customers and keeping current customers, as discussed in this research, brand awareness is one of the most important factors affecting customer attraction in the bank.

Purpose: The development of e-commerce and online shopping has given rise to emerging concepts of consumer behavior, including webrooming. Due to the novelty of the concept of webrooming in this study, an attempt has been made to provide a conceptual framework to explain this behavior and the factors affecting its formation.Method: In this regard, a field survey study was conducted by distributing questionnairy among a sample consisting of 384 gold and jewelry customers in Tehran. The questionnaires consisting of 9 dimensions and 38 items were distributed among the members of the statistical sample after ensuring reliability and validity. Data analysis along with partial least squares technique and Smart PLS software were used.Findings: According to the results, the benefits of online and offline channels have a significant impact on webrooming attitude; It was also discovered that attitude, perceived risk, anticipated regret, subjective norms and behavioral control have a significant impact on behavioral inclination and webrooming.Conclusion: The results of goodness of fit showed that the proposed model in this research has a good validity and fit. Given that webrooming has a negative impact on online sales; the results help online retailers mitigate this phenomenon by targeting webrooming antecedents.

Purpose: The purpose of this research was to provide a model for choosing the best content for the activity of service guilds.Method: In inferential statistics, the K-S test is used for the normality of research hypotheses. For this purpose, Pearson's correlation coefficient and linear regression tests have been used through SPSS 21 software, and the best content generated using genetic algorithms and forbidden search were introduced.Findings: Analysis of research and implementation results with two collective intelligence algorithms shows that Instagram has a positive and significant effect on all four dimensions and thus leads to the success of the service classes that have used Instagram.Conclusion: In this article, a combination model of genetic algorithm and forbidden search algorithm was chosen for users so that the best content, which of course does not contain malicious ads and cookies, etc., is introduced for the continuation of the service industry.

Smart packaging plays a pivotal role in food distribution by integrating innovative technologies to enhance product safety, quality, and efficiency throughout the supply chain. Leveraging smart packaging minimizes waste, reduces spoilage, and enables real-time monitoring. However, producers face a few challenges with smart packaging, including high initial investment costs, compatibility issues with existing infrastructure, and regulatory hurdles concerning data privacy and safety standards. Additionally, ensuring widespread adoption and addressing consumer acceptance pose significant challenges and the need for continuous innovation to keep pace with evolving market demands and technological advancements. Therefore, this study aims to identify the current landscape of smart packaging within food distribution, outline the main themes within this field, highlight potential areas for further study, and provide a roadmap for future research endeavors. To fulfill this aim, a comprehensive bibliometric analysis was undertaken, utilizing data extracted from the Scopus database. A total of 1,094 documents relevant to the chosen keywords were successfully gathered for analysis. Frequency analysis was conducted using Microsoft Excel, while citation metrics and further analysis were performed utilizing R package software. The outcomes of this investigation are presented using standard bibliometric metrics, encompassing publication year, authorship, subject area, document type, source title, citation analysis, keyword analysis, active institutional participation, geographic distribution, and language. The analysis revealed a significant increase in publications concerning smart packaging within food distribution since 1990. This upward trend underlines the crucial role of technology in the food industry, potentially impacting the environment, economy, and societal dynamics.

Cyberbullying involves using hurtful or offensive language that goes against basic rules of respect and politeness. It harms the online environment and can negatively affect people by causing harassment, discrimination, or emotional pain. To combat this, it is crucial to develop automated methods for detecting and preventing the dissemination of such content. Deep learning, a branch of artificial intelligence, leverages neural networks to learn from data and perform complex tasks, effectively capturing semantic and grammatical nuances to differentiate between abusive and non-abusive language. This survey paper reviews current techniques and advancements in deep learning-based approaches for detecting cyberbullying content on online platforms, aiming to provide a comprehensive understanding of existing methodologies and identify potential avenues for future research to mitigate the spread and impact of such behaviors on the internet.

Technology innovation affects both the public and private non-financial sectors, the zakat institution (Islamic social finance) included. The institution uses an online system to communicate with zakat payers and zakat recipients to ensure its effectiveness in terms of collection and distribution. This research focuses on the adoption of a technique known as AD/AC and ZP/ZR, which is mainly utilized by partially and non-privatized State zakat institutions in Malaysia. To this end, three (3) techniques pertaining to appraising the performance of Malaysia’s Zakat institutions in managing Zakat funds were established. The analysis also includes the adverse impact of Covid-19 pandemic on the performance of zakat collection of the respective zakat institutions in Malaysia. In this relation, a quantitative approach was adopted using the primary and secondary data collected from JAWHAR and various states’ zakat institutions. By utilizing a technique of online data collection and applying the AD/AC as well as ZP/ZR methods, the performance of Malaysia’s zakat institutions is appraised. Furthermore, with the help two (2) ratios and eight (8) scenarios the performance of the innovative technique of AD/AC and ZP/ZR for zakat collection and disbursement, efficiency and sustainability of zakat institutions in Malaysia were evaluated. The results show that most zakat institutions, particularly those that deal with zakat payments, have begun to use the technique AD/AC and ZP/ZR within their organizations. The performance of zakat institutions in all states in terms of zakat distribution and disbursement do not have a consistent trend for the period 2016-2020. However, there is still a dearth of technology being used for zakat disbursements and fund reporting. From the observed data, with 2016 being the exception, for each remaining year, a state in Malaysia is ranked as the best technology performer or the most efficient. Selangor - fully privatized state (2017), Pulau Pinang - fully privatized state (2018), Federal Territory - partially privatized state (2019) and Negeri Sembilan-partially privatized state (2020) are the most efficient for the respective year. The sustainability of each zakat institution in Malaysia in the presence of Covid-19 pandemic was ascertained as well. Interestingly, contrary to the efficiency result, all non-privatized states (Kedah, Sabah and Kelantan) and one partially privatized state (Negeri Sembilan) were sustainable in coping with Covid-19 pandemic, while all fully privatized states (Selangor and Pulau Pinang) were not. Overall, it was conjectured that the technique AD/AC as well as ZP/ZR would help to improve the operations of zakat institutions to become more efficient and successful in distributing zakat fund to the poor. However, as zakat collecting and distribution involved millions of records, its management is still debatable by all parties.

In today’s world, there is a notable focus on incorporating disabled people within the community and the workplace. Advancements in artificial intelligence (AI) have the potential to significantly impact empowering individuals with disabilities to enhance inclusivity and autonomy for this demographic in the era of Society 5.0. This paper aims to offer a bibliometric analysis of the increasing number of publications addressing the potential impact of AI on disabled individuals and their future employment. To conduct this analysis, Scopus served as the bibliographic source, using Disability, Employment, and Future Workforce as the search terms, yielding 203 publications on the subject of study from 1973 to 2024. The analysis was conducted using VOS viewer. The results indicate that as Society 5.0 evolves, advancements in AI have the potential to significantly empower individuals with disabilities, enhancing inclusivity and autonomy for this demographic.

With the advancement of communication technology, e-hailing services are becoming more widespread in Malaysia. Even though e-hailing services offer relative advantages compared to other types of public transport, research on the service quality aspects and customer satisfaction is essential to ensure customers receive worthwhile service with the money they spend on the services. Therefore, the growth of the e-hailing sector in Malaysia has drawn attention from the government, service providers, passengers, and even academics to the issues of service quality and customer satisfaction. Much research on service quality has been conducted in Malaysia; however, limited research has yet to be done on e-hailing services specifically for the state of Sarawak (East Malaysia) compared to peninsular areas. Thus, this research aims to measure the service quality performance of e-hailing in Sarawak and investigate the factors influencing passenger satisfaction. Three hundred ninety-two e-hailing users voluntarily participated in the survey, which was conducted in 2023. The partial least squares structural equation modeling (PLS-SEM) was performed to assess the measurement and structural model. The analysis revealed that vehicle condition, customer service, and reliability have a significant one-percent relationship with passenger satisfaction. To ensure e-hailing vehicles are always in good condition, e-hailing companies and government agencies must make it mandatory for e-hailing cars to be maintained periodically. Next, the driver should improve communication skills and show a good attitude to provide excellent customer service. Besides, prompt response to customer orders is a must to ensure e-hailing services are reliable public transportation.

In the case of COVID-19, researchers have found a statistically significant improvement in public health protection against COVID-19 with social media platforms. Multiple studies suggest that evidence of social media's influence on health knowledge, behaviors, and outcomes indicates its potential benefits in meeting the needs of individuals and populations. Therefore, this study aims to investigate the influence of social media on public health protections against COVID-19 in terms of public health awareness and behavioral changes. It adopted a quantitative research design to identify the relationship and used questionnaires to collect the data. Data was collected throughout Malaysia using convenience sampling. The results underscore the potential of social media as a valuable tool for disseminating crucial health information and promoting positive behavioral changes during public health crises like the COVID-19 pandemic.

Today, users generate various data increasingly using the Internet when choosing a product or service. This leads to the generation of data about the purchases and services of various consumers. In addition, consumers often leave feedback about the purchase. At the same time, consumers discuss their attitudes about goods and services on social networks, messengers, thematic sites, etc. This leads to the emergence of large volumes of data that contain useful information about various manufacturers of goods and services. Such information can be useful to both ordinary users and large companies. However, it is practically impossible to use this information due to the fact that it is located in different places, that is, it has a raw, unstructured character. At the same time, depending on the target group of users, not the entire data set is needed, but a specific target sample. To solve this problem, it is necessary to have a tool for structuring information arrays and their further analysis depending on the set goal. This can be done with the help of various frameworks that use methods of machine learning and work with data. This work is devoted to elucidating the problem of creating means for evaluating consumer preferences based on the analysis of large volumes of data for its further use by the target audience.  The goal of the development of big data analysis systems is obtaining new, previously unknown information. The methodology of application of algorithms of work with large data sets and methods of machine learning is used, namely the pandas library for operations on a data set and logistic regression for information classification As a result, a system was built that allows the analysis of lexical information, translate it into numerical format and create on this basis the necessary statistical samples. The originality of the work lies in the use of specialized libraries of data processing and machine learning to create data analysis systems. The practical value of the work lies in the possibility of creating data analysis systems built using specialized machine learning libraries.

In terms of storage and consumption, blockchain technology is poised to transform the way we manage healthcare data. The primary goal is to empower individuals to take charge of their health records, allowing them to become independent of the institutions or organizations they use. Elec-tronic Health Records (EHRs) can be tracked in a novel and unique way through blockchain tech-nology and smart contracts. This technology can give patients more control over their data. Health practitioners and institutions, such as hospitals, may be granted access to patient data controlled by other organizations. This research highlights how blockchain technology can be used to manage EHRs while improving operational efficiency through process simplification and transparency. Additionally, the study proposes an architecture for managing and sharing healthcare data across enterprises. The suggested approach could significantly reduce the time required to transfer patient data among various health organizations while lowering overall costs.

Online review sites and social media platforms have become crucial sources of information for consumers, greatly influencing their purchasing behavior and decision-making, especially in the food and beverage industry. However, not many studies have been carried out to understand how social media influences customers’ purchase intentions at fast-food restaurants. This paper examines the growing influence of social media attributes on purchase intentions, with a focus on the Malaysian context. Previous studies highlight the increasing importance of social media platforms as marketing tools and their impact on customers’ purchase intentions. The research explores the relationship between habit and informativeness and their influence on purchase intentions among young adults in fast-food restaurants. A purposive sampling method was utilized to gather data from 142 fast-food customers through a cross-sectional online survey. The research hypotheses were analyzed using the partial least square structural equation modeling. Key findings found that habit and informativeness have a significant positive impact on customers’ intentions to purchase at fast-food restaurants. The study contributes to the existing literature by highlighting the growing influence of social media on consumer behavior in the context of fast-food restaurants. It adds to our understanding of how social media platforms serve as effective marketing tools, particularly among young adults, and how they can influence purchase intentions. By understanding the interplay of habit, informativeness, and purchase intentions, businesses can develop more effective marketing strategies and foster stronger relationships with their customers.