This study explores the historical development of international accounting standards (IAS) and the initiatives of the prominent organizations involved in international standard setting. It also explains why countries differ in national standards, why the process of harmonization of standards among countries has been slow, and why countries should now converge their accounting standards. Many papers on IAS generally deal with the contents of the individual standards. This writer, however, believes that accountants, as social scientists, are also interested in tracing the development of social forms over time and comparing those developmental processes across cultures. Thus, this paper addresses the interest of accountants to learn how some contemporary events or institutions—like the IAS—came into being. In like manner, accountants are interested in finding out the varied reasons why the issue of coming up with a global set of accounting standards has taken a long while. Indeed, these are perspectives that substantially differ from those commonly presented in professional forum and scholarly exercises.
{"title":"Empirical Study on International Accounting Standards and Accounting Quality","authors":"","doi":"10.46632/jbab/2/3/2","DOIUrl":"https://doi.org/10.46632/jbab/2/3/2","url":null,"abstract":"This study explores the historical development of international accounting standards (IAS) and the initiatives of the prominent organizations involved in international standard setting. It also explains why countries differ in national standards, why the process of harmonization of standards among countries has been slow, and why countries should now converge their accounting standards. Many papers on IAS generally deal with the\u0000contents of the individual standards. This writer, however, believes that accountants, as social scientists, are also interested in tracing the development of social forms over time and comparing those developmental processes across cultures. Thus, this paper addresses the interest of accountants to learn how some contemporary events or\u0000institutions—like the IAS—came into being. In like manner, accountants are interested in finding out the varied reasons why the issue of coming up with a global set of accounting standards has taken a long while. Indeed, these are perspectives that substantially differ from those commonly presented in professional forum and scholarly exercises.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":"27 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81257507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An organization's ability to recruit, assess and choose the best candidates with the necessary abilities, expertise, and expertise to support its stated objectives and goals is crucial to its success. A methodical approach that starts with a clear comprehension of the company's requirements and wants for a specific role is necessary for effective candidate selection. In line with the strategic goals of the organisation, this process entails developing descriptions of roles, identifying essential abilities, and establishing hiring requirements.
{"title":"Candidate Selection in an Organization Using WSM Method","authors":"","doi":"10.46632/jbab/2/3/3","DOIUrl":"https://doi.org/10.46632/jbab/2/3/3","url":null,"abstract":"An organization's ability to recruit, assess and choose the best candidates with the necessary abilities, expertise, and expertise to support its stated objectives and goals is crucial to its success. A methodical approach that starts with a clear comprehension of the company's requirements and wants for a specific role is necessary for effective candidate selection. In line with the strategic goals of the organisation, this process entails developing descriptions of roles, identifying essential abilities, and establishing hiring requirements.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":"11 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73177689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research study delves into the realm of economic optimization using numerical techniques and mathematical modelling. With a focus on addressing complex challenges in production planning and supply chain optimization, this paper employs a combination of real-world case studies and mathematical calculations to demonstrate the practical application and effectiveness of numerical optimization methods. Through two case studies – one optimizing production planning in a manufacturing plant and the other optimizing supply chain operations – the study showcases how numerical optimization techniques can minimize costs, enhance efficiency, and inform strategic decision-making in intricate economic systems. The results and insights gained from these case studies underscore the power of numerical optimization techniques in tackling real-world economic challenges, while the scope for future research points towards advanced algorithms and dynamic scenarios. Overall, this study contributes to advancing economic theory and practical decision-making through the lens of optimization.
{"title":"Optimization of Production Planning in Complex Economic Systems","authors":"","doi":"10.46632/jbab/1/3/9","DOIUrl":"https://doi.org/10.46632/jbab/1/3/9","url":null,"abstract":"This research study delves into the realm of economic optimization using numerical techniques and mathematical modelling. With a focus on addressing complex challenges in production planning and supply chain optimization, this paper employs a combination of real-world case studies and mathematical calculations to demonstrate the practical application and effectiveness of numerical optimization methods. Through two case studies – one optimizing production planning in a manufacturing plant and the other optimizing supply chain operations – the study showcases how numerical optimization techniques can minimize costs, enhance efficiency, and inform strategic decision-making in intricate economic systems. The results and insights gained from these case studies underscore the power of numerical optimization techniques in tackling real-world economic challenges, while the scope for future research points towards advanced algorithms and dynamic scenarios. Overall, this study contributes to advancing economic theory and practical decision-making through the lens of optimization.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":"15 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76761823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays, wearable techniques are widely used in machine learning. Among the various application, IoT based machine learning devices are used widely in health care application for reducing the risk factor. So, this project introduced a sensor-based wearable device for sportspersons' continuous health monitoring system. The goal of the project is to assists each athlete's health and to reduce the coach’s work using machine learning. Firstly, the dataset will be collected from the previous athletes who wore this device. The device will be trained with the dataset by pre-processing feature selection data. The main use of this device is to suggest an athlete run fast/slow based on surroundings. And also assists athlete in what to eat and how to train. It will monitor the athlete’s health condition and compare data with the dataset with the use of the Machine Learning Algorithm J48. J48 algorithm creates a decision tree for machine learning is applied to obtain the athlete’s health condition. The accuracy level of the J48 algorithm is 97.73%.
{"title":"Continuous Athlete Monitoring Wearable Device Using Machine Learning","authors":"","doi":"10.46632/jdaai/2/3/12","DOIUrl":"https://doi.org/10.46632/jdaai/2/3/12","url":null,"abstract":"Nowadays, wearable techniques are widely used in machine learning. Among the various application, IoT based machine learning devices are used widely in health care application for reducing the risk factor. So, this project introduced a sensor-based wearable device for sportspersons' continuous health monitoring system. The goal of the project is to assists each athlete's health and to reduce the coach’s work using machine learning. Firstly, the dataset will be collected from the previous athletes who wore this device. The device will be trained with the dataset by pre-processing feature selection data. The main use of this device is to suggest an athlete run fast/slow based on surroundings. And also assists athlete in what to eat and how to train. It will monitor the athlete’s health condition and compare data with the dataset with the use of the Machine Learning Algorithm J48. J48 algorithm creates a decision tree for machine learning is applied to obtain the athlete’s health condition. The accuracy level of the J48 algorithm is 97.73%.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":"10 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77761371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The estimates taken far and wide to deal with the SARS-CoV-2 pandemic, limiting travel, shuttering superfluous organizations and implementing all social separating arrangements, are having serious monetary consequences. a noteworthy decrease in economic action spread over the economy the world, lasting in excess of a few months, typically clear in genuine GDP. Where it is formally announced a downturn. To quicken a strong expected recuperation with rising protectionism and unilateralism. There is a requirement for individuals to come out and face the circumstance. Despite the fact that it is established that separating individuals and investigating their contacts would be inadequate to control the SARS-CoV-2 pandemic, in light of the fact that there would be an excess of deferral between the beginning of indications and seclusion. Consequently, in these sorts of conditions it is to keep people groups from infection influence and early anticipation of these tainted individuals may prompt re development the economy too. We built up a numerical model utilizing profound Deep reinforcement learning (DRL) which is poised to revolutionize the field of artificial intelligence and the use of central algorithms in deep RL, specifically the deep Q-network (DQN), trust region policy optimization (TRPO). The proposed astute checking framework can be utilized as a reciprocal apparatus to be introduced at better places and consequently screen individuals receiving the security rules. With these prudent estimations, people will have the option to win this battle against SARS-CoV-2.
{"title":"Deep Q-Network (DQN): Reinforcement Learning Based Approach for Secure Social Distancing Adherence with SARS-CoV-2 in Public Places","authors":"","doi":"10.46632/jdaai/2/3/11","DOIUrl":"https://doi.org/10.46632/jdaai/2/3/11","url":null,"abstract":"The estimates taken far and wide to deal with the SARS-CoV-2 pandemic, limiting travel, shuttering superfluous organizations and implementing all social separating arrangements, are having serious monetary consequences. a noteworthy decrease in economic action spread over the economy the world, lasting in excess of a few months, typically clear in genuine GDP. Where it is formally announced a downturn. To quicken a strong expected recuperation with rising protectionism and unilateralism. There is a requirement for individuals to come out and face the circumstance. Despite the fact that it is established that separating individuals and investigating their contacts would be inadequate to control the SARS-CoV-2 pandemic, in light of the fact that there would be an excess of deferral between the beginning of indications and seclusion. Consequently, in these sorts of conditions it is to keep people groups from infection influence and early anticipation of these tainted individuals may prompt re development the economy too. We built up a numerical model utilizing profound Deep reinforcement learning (DRL) which is poised to revolutionize the field of artificial intelligence and the use of central algorithms in deep RL, specifically the deep Q-network (DQN), trust region policy optimization (TRPO). The proposed astute checking framework can be utilized as a reciprocal apparatus to be introduced at better places and consequently screen individuals receiving the security rules. With these prudent estimations, people will have the option to win this battle against SARS-CoV-2.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":"6 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75231217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The practice of extracting hidden predictive information from a database and structuring it for later use is known as data mining. Web mining, text mining, sequence mining, graph mining, temporal data mining, spatial data mining, distributed data mining, and multimedia mining are some of the diverse domains in data mining. Financial data analysis, the retail and telecommunications sectors, science and engineering, and intrusion detection and prevention are a few fields where data mining is used. Worldwide, big data analytics is a burgeoning research field in computer science and many other fields. We covered text mining methods and their uses in this paper. Text mining is becoming a significant topic of study. Text mining is the process of automatically finding new, previously undiscovered information using a computer.
{"title":"An Analysis of Text Mining in Big Data","authors":"","doi":"10.46632/jdaai/2/3/8","DOIUrl":"https://doi.org/10.46632/jdaai/2/3/8","url":null,"abstract":"The practice of extracting hidden predictive information from a database and structuring it for later use is known as data mining. Web mining, text mining, sequence mining, graph mining, temporal data mining, spatial data mining, distributed data mining, and multimedia mining are some of the diverse domains in data mining. Financial data analysis, the retail and telecommunications sectors, science and engineering, and intrusion detection and prevention are a few fields where data mining is used. Worldwide, big data analytics is a burgeoning research field in computer science and many other fields. We covered text mining methods and their uses in this paper. Text mining is becoming a significant topic of study. Text mining is the process of automatically finding new, previously undiscovered information using a computer.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":"13 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77271905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aimed to investigates agricultural marketing and its operation in India. Agrarian marketing in India involves bringing farm-produced goods to consumers, with 70% of workers involved. The 11th Five-Year Plan focuses on improving marketing facilities, market information systems, human resource capacity, and exports and foreign trade. Indian Constitution introduced model farming statutes in 2017, but state implementation delayed, leading to APMC mandis under Central government control. The current study utilized primary data collected through a structured questionnaire consisting of 34 questions from 49 respondents. The research used descriptive statistics and found that (i) the majority of agricultural households lack access to literacy skills. (ii) there is Insufficient awareness about Minimum Support Price (MSP) persists among farmers. (iii) farmers in the agricultural marketplaces have reported issues concerning grading and standardization. Various variables such as occupation and family size serve as the foundation of this study and suggested multiple factors concerning these background characteristics.
{"title":"Prosects of Agricultural Marketing in India","authors":"","doi":"10.46632/jdaai/2/3/7","DOIUrl":"https://doi.org/10.46632/jdaai/2/3/7","url":null,"abstract":"This study aimed to investigates agricultural marketing and its operation in India. Agrarian marketing in India involves bringing farm-produced goods to consumers, with 70% of workers involved. The 11th Five-Year Plan focuses on improving marketing facilities, market information systems, human resource capacity, and exports and foreign trade. Indian Constitution introduced model farming statutes in 2017, but state implementation delayed, leading to APMC mandis under Central government control. The current study utilized primary data collected through a structured questionnaire consisting of 34 questions from 49 respondents. The research used descriptive statistics and found that (i) the majority of agricultural households lack access to literacy skills. (ii) there is Insufficient awareness about Minimum Support Price (MSP) persists among farmers. (iii) farmers in the agricultural marketplaces have reported issues concerning grading and standardization. Various variables such as occupation and family size serve as the foundation of this study and suggested multiple factors concerning these background characteristics.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":"5 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87922114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Artificial Intelligence may be it is branch of computing. The computer science engineering is creating intelligent machines and especially intelligent computer programs. AI could also be how of making a computer. A computer-controlled robot or software thinks intelligently. AI is accomplished by studying the way to think human brain. How humans learn, decide, and work while trying to unravel a haul. We also create intelligent machines. It is often developing human activities. Some human activities are reading, listening, each and are going to be covered. Machine learning, deep learning may be a part of this AI. The AI projects have a machine control and remote. Mostly AI is machine learning. Current status will be there from AI. Feature goals in AI. Computing system study that plan to model and applying human brain. It is a branch of computer simulating a intelligent behavior. The machine capacity is intimate human behavior. The intelligence has some types are going to be there, linguistic intelligence, musical intelligence, logical-mathematical intelligence, spatial intelligence, intra-personal intelligence, interpersonal intelligence. The intelligence composed by reasoning, learning, problem solving, perception, linguistic intelligence and so on. Ability to calculate a system, reasoning, perceives a relationships and analogs, learn from experience. Store and retrieve information from memory. Solving a problems and complex ideas to use tongue fluently classifying. Generalize and adapt new situation
{"title":"Human Intelligence to Artificial Intelligence: Critical thinking and Emotional Intelligence","authors":"","doi":"10.46632/jdaai/2/3/2","DOIUrl":"https://doi.org/10.46632/jdaai/2/3/2","url":null,"abstract":"Artificial Intelligence may be it is branch of computing. The computer science engineering is creating intelligent machines and especially intelligent computer programs. AI could also be how of making a computer. A computer-controlled robot or software thinks intelligently. AI is accomplished by studying the way to think human brain. How humans learn, decide, and work while trying to unravel a haul. We also create intelligent machines. It is often developing human activities. Some human activities are reading, listening, each and are going to be covered. Machine learning, deep learning may be a part of this AI. The AI projects have a machine control and remote. Mostly AI is machine learning. Current status will be there from AI. Feature goals in AI. Computing system study that plan to model and applying human brain. It is a branch of computer simulating a intelligent behavior. The machine capacity is intimate human behavior. The intelligence has some types are going to be there, linguistic intelligence, musical intelligence, logical-mathematical intelligence, spatial intelligence, intra-personal intelligence, interpersonal intelligence. The intelligence composed by reasoning, learning, problem solving, perception, linguistic intelligence and so on. Ability to calculate a system, reasoning, perceives a relationships and analogs, learn from experience. Store and retrieve information from memory. Solving a problems and complex ideas to use tongue fluently classifying. Generalize and adapt new situation","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":"48 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90712301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recent advances in sensor networks and Internet of Things (IoT) technology have led to the collection of large amounts of data. Searching for this much information requires a more efficient and accurate analysis method. Artificial intelligence (AI) techniques such as machine learning and evolutionary algorithms can provide better, faster and more efficient results in big data. Despite this interest, to the best of our knowledge, there has not been a thorough study of the various artificial intelligence techniques for analyzing big data. Most products in the literature focus on the extraordinary ability of intelligence. Recently, challenges such as security, security, integrity, sustainability and utility have emerged during the development of intelligent systems. As the use of smart technology increases, so do new challenges. Obviously, understanding of issues like security will change as we move from narrow AI to super AI. Also, recent advances in human intelligence cannot take place without considering all the problems in creating intelligent machines.
{"title":"Artificial Intelligence Approaches and Mechanisms for Big Data Analytics: A Systematic Study","authors":"S. Gomathi Meena, S. Dharani","doi":"10.46632/jdaai/2/3/1","DOIUrl":"https://doi.org/10.46632/jdaai/2/3/1","url":null,"abstract":"Recent advances in sensor networks and Internet of Things (IoT) technology have led to the collection of large amounts of data. Searching for this much information requires a more efficient and accurate analysis method. Artificial intelligence (AI) techniques such as machine learning and evolutionary algorithms can provide better, faster and more efficient results in big data. Despite this interest, to the best of our knowledge, there has not been a thorough study of the various artificial intelligence techniques for analyzing big data. Most products in the literature focus on the extraordinary ability of intelligence. Recently, challenges such as security, security, integrity, sustainability and utility have emerged during the development of intelligent systems. As the use of smart technology increases, so do new challenges. Obviously, understanding of issues like security will change as we move from narrow AI to super AI. Also, recent advances in human intelligence cannot take place without considering all the problems in creating intelligent machines.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":"13 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84783235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This abstract outline some of the crucial tactics that companies should take into account while creating an e-commerce platform. First and first, it's important to comprehend the target audience and their preferences. In order to better understand client demands, expectations, and purchasing patterns, firms can modify their platforms and marketing initiatives by doing market research and utilising data analytics. Second, it is crucial to design an interface that is simple and easy to use. To improve the customer experience, the e-commerce platform should offer easy navigation, simple search features, and simplified checkout procedures. Given the increased popularity of mobile shopping, investing in adaptable design and mobile optimisation is also essential. Thirdly, merchandising and product display are crucial in promoting sales. The many methods and processes used to create and expand prosperous online enterprises are referred to as ecommerce development strategies. These methods cover everything from creating an online store to generating traffic, improving conversion rates, and guaranteeing customer pleasure. Ecommerce companies can better understand their target market by conducting research on consumer preferences, behaviour, and trends. Businesses can use market research to determine the requirements and preferences of potential customers, which can inform decisions about what products to offer at what prices, and how to best sell their services. Businesses can study their rivals' plans, strengths, and weaknesses through research to learn more about them. Depending on how closely a set of options fit an ideal answer, they are assessed and ranked using a decision-making method known as TOPSIS, or Technique for Order of Preference by Similarity to Ideal response. It is a method for MCDA (multi-criteria decision analysis), which aids individuals or groups in making decisions by taking a variety of preferences and considerations into account. The TOPSIS strategy aids decision-makers in methodically analysing and contrasting choices based on a variety of factors while taking their preferences and priorities into consideration. It increases transparency and comprehension of the decision-making process and offers a systematic strategy to enhance decision-making. Alternative Parameters: E-customization and personalization, Social E-commerce adoption model, Strong search engine optimization (SEO) Evaluate parameter: Feasibility of the strategy, Implementation speed, Compliance with the corporate strategy, Compliance of the strategy with the mission and vision of the company, General acceptance The evaluation criteria may also include the following additional factors: general acceptance, speed of implementation, compliance with corporate strategy, e-customization and personalization, social search engine optimisation, and compliance with the strategy's mission and vision The effective application of these tactics will enable firms to build a strong
这篇摘要概述了公司在创建电子商务平台时应该考虑的一些关键策略。首先，了解目标用户和他们的喜好是很重要的。为了更好地了解客户的需求、期望和购买模式，公司可以通过进行市场研究和利用数据分析来修改他们的平台和营销计划。其次，设计一个简单易用的界面是至关重要的。为了改善客户体验，电子商务平台应该提供方便的导航、简单的搜索功能和简化的结账程序。鉴于移动购物的日益普及，投资于适应性设计和移动优化也是必不可少的。第三，推销和产品展示是促进销售的关键。用于创建和扩展繁荣的在线企业的许多方法和过程被称为电子商务发展战略。这些方法涵盖了从创建在线商店到产生流量、提高转化率和保证客户满意度的所有内容。电子商务公司可以通过对消费者偏好、行为和趋势进行研究，更好地了解他们的目标市场。企业可以利用市场调查来确定潜在客户的需求和偏好，这可以决定以什么价格提供什么产品，以及如何最好地销售他们的服务。企业可以通过研究来了解竞争对手的计划、优势和劣势。根据一组选项与理想答案的接近程度，将使用一种被称为TOPSIS的决策方法对它们进行评估和排名，即“理想回答相似性偏好排序技术”。它是MCDA(多标准决策分析)的一种方法，它通过考虑各种偏好和考虑因素来帮助个人或团体做出决策。TOPSIS战略帮助决策者系统地分析和对比基于各种因素的选择，同时考虑到他们的偏好和优先事项。它增加了决策过程的透明度和理解，并提供了加强决策的系统战略。备选参数:E-customization and personalization, Social ecommerce adoption model, Strong search engine optimization (SEO)评估参数:战略的可行性，实施速度，与企业战略的合规性，战略与公司使命和愿景的合规性，总体接受度评估标准还可能包括以下附加因素:普遍接受度、实施速度、符合企业战略、电子定制和个性化、社会搜索引擎优化以及符合战略使命和愿景。这些策略的有效应用将使企业能够建立强大的在线存在，提高客户满意度，并在竞争激烈的电子商务行业中增加收入。随着消费者偏好和技术的变化，企业必须适应和磨练自己的策略，以保持领先地位。通过拥抱创新，了解客户，跟上市场趋势，企业可以在动态的电子商务世界中保持成功。
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