مشخصات مقاله | |
ترجمه عنوان مقاله | توسعه تجارت با استفاده از دادههای بزرگ در بخش خردهفروشی شرکتهای کوچک و متوسط امارات متحده عربی: چشماندازها و سؤالات |
عنوان انگلیسی مقاله | Business Development Using Big Data within UAE SMEs Retail Sector: Prospects & Questions |
انتشار | مقاله سال ۲۰۲۲ |
تعداد صفحات مقاله انگلیسی | ۶ صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه IEEE |
نوع نگارش مقاله |
مقاله پژوهشی (Research article) |
مقاله بیس | این مقاله بیس میباشد |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
فرضیه | ندارد |
مدل مفهومی | دارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مدیریت – مهندسی فناوری اطلاعات |
گرایش های مرتبط | مدیریت بازرگانی – مدیریت سیستم های اطلاعاتی |
نوع ارائه مقاله |
ژورنال – کنفرانس |
مجله / کنفرانس | چهاردهمین کنفرانس بین المللی مهندسی کامپیوتر و اتوماسیون – ۱۴th International Conference on Computer and Automation Engineering |
دانشگاه | DBA Scholar SP Jain School of Global Management, United Arab Emirates |
کلمات کلیدی | خرده فروشی – شرکت های کوچک و متوسط – کلان داده ها – تحول دیجیتال – تجزیه و تحلیل خرده فروشی – مزیت رقابتی – مدل پذیرش فناوری |
کلمات کلیدی انگلیسی | Retail – SME – big data – digital transformation – retail analytics – competitive edge – technology adoption model |
شناسه دیجیتال – doi |
https://doi.org/10.1109/ICCAE55086.2022.9762414 |
کد محصول | e16638 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract Introduction Literature Review Case Review of Retail Sector in UAE Conclusion References |
بخشی از متن مقاله: |
Abstract Despite research on big data analytics being conducted in past, there are no studies focused on the opportunities i.e., growth prospects and its associated challenges in specific industries in UAE. In this study, big data analytics were used in SMEs retail sector in UAE region to assess the use of these technologies. Companies can use these to gain new understandings from their customers and suppliers perspective utilizing big data analytics techniques to take informative decisions on pricing, inventory management, payment solutions and marketing decisions. Big data can be used to help SMEs foresee the needs and preferences of their target audiences. The focus of this study is on SMEs since these are the pillar of every economy and can make quick adjustments to productivity changes. It aims to analyze and identify major chances and threats of Big Data and propose the best ways for SMEs to utilize it for improving their efficiency and business practices. Introduction The COVID-19 viral pandemic has had a significant impact on corporate growth across several industries. Small and midsized enterprises (SMEs) are among the most economically disadvantaged, a fact that has prompted governments of all views to enact unprecedented measures to help small businesses – such as tax holidays, soft loans, and implementation of digital technology to increase operational efficiency and ultimately revenue generation. On a regional level, several regulators and authorities have taken proactive measures to mitigate the impact on small enterprises. The ability of a small business to pivot and adapt to a new reality reflects its financial vulnerability, and it has been seen that businesses are innovating in the face of adversity – whether it’s changing existing services, catering to the requirements of newly housebound consumers, or adjusting product offerings to support government efforts to combat the coronavirus [1]. Most bigger firms are undergoing much-needed digital transformations on a small or large scale in order to stay competitive and be very customer-centric. Economic growth is bolstered by a growing SME sector, which decreases unemployment and poverty as well as encourages entrepreneurial activity and thus making it important for any country [1]. The Emirate is working to transition from an oil and gas dependent GDP to a free – market economy focused on trade, services, and manufacturing [2]. The contemporary market economy, on the other hand, relies heavily on SMEs, which account for over 40% of Dubai’s GDP [3]. Conclusion There has been a dramatic increase in the amount of data generated by both real and virtual worlds in the last few decades. Companies of allsizes use big data toolsto manage vast amounts of data and obtain comprehensive information that advances their business intelligence and allows them to make smart decisions. The retail business is one of the most diverse businesses, and some retailers are among the UAE’s top corporations. Simultaneously, the retail industry has many tiny “mom-and-pop” establishments, making it vital to many families’ livelihoods. Big Data Analytics has the potential to help these people. By analyzing data and creating correlations between diverse things, Big Data Analytics can enable these stores to discover new changes in their units. Finally, Big Data Analytics must be recognized as a crucial aspect in making the SMEs retail sector’s business a success story, considering all the facts, figures, and prospects covered in the article. If SMEs want to take advantage of Big Data’s capabilities, they must first undergo a cultural transformation. This necessitates them investigating data-handling tools and procedures outside of their smaller organizations, as well as being prepared to actively use Big Data in their decision-making processes. They must be prepared to dive in and explore the ever-expanding ocean of data that awaits them out there. Sayings alone, however, will not be enough to get SMEs on the path to data analytics. All shareholders, including domestic and worldwide regulators, the IT diaspora, the industry group, and the digital transformation community, face a difficult dilemma as a result of the previously identified issues. Further investigation and research can be done by doing empirical study and collecting raw data from various SMEs in retail sector in U.A.E. And then meaningful information can be extracted for further analysis to demonstrate the feasibility and reliability of the model mentioned in the paper |