Future Unique Technology Influences Consumer Behavioral Change
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| Author | : Johnny Ch LOK |
| Publisher | : |
| Total Pages | : 127 |
| Release | : 2019-07-10 |
| Genre | : |
| ISBN | : 9781079695205 |
Nowadays, the current technological changes of humans and machines , but rather an opportunity for work to truly become a channel though which human recognize full potential. As US is a high technological developed country. I assume many US employers will choose to act to be the first high technological and invention manufacturing leader to encourage which labors need to learn high technological production methods to prepare manufacture any new technological products to sell in the future US domestic or foreign both markets. Thus, it is possible that future high technological manufacturing labor numbers will be shared large go e.g. 50 to 60% future total US labor market.How can future US labor market affect job creation and productivity growth? US future economic growth requires factor reallocation across US firms and continuous replacement of technologies. US labor market influences US economy dynamism by their impact on the supply of a key factor, skilled workers to US new and expanding firms, US growth -favoring labor market includes portable pension plans and health insurance united to the current US employers, individualized wage-setting and US public income insurance systems that encourage mobility and risk taking. US future economic growth arises as production shifts from less to more successful firms though the reallocation of factors of production . US labor market can advance restructuring. Overly regulations tend to create a system in which a large share of economic activity occurs in US small firms without the ability to grow. US labor market should be organized to promote potential high growth US firms, especially through decentralized and individualized wage setting, portable jobs.In the future, US will have many key importance of high growth firms. US capitalism entails a process of creative destination. New ideas continuously challenges act structures, giving rise to structural transformation as successful innovations and new products firms and industries will arise and obsolete ones will decline in US society.
| Author | : Johnny Ch Lok |
| Publisher | : |
| Total Pages | : 128 |
| Release | : 2019-07-31 |
| Genre | : |
| ISBN | : 9781086534252 |
Artificial Intelligent Socio-economic development technologyIN the future, many people choose to drive auto-mannal vehicle, and many workers like to apply robots to assist them to manufacture any products in factories. So, artificial intelligence learning needs will raise. US development practitioners are increasingly aware of the role that US social and political structures play in future shaping US's development paths and results. In this context, US macro social analysis needs to understand the ways in which power relations act to circumscribe the opportunities available to poor US people to improve their situation. For example, US donor organizations need to understand of relevant US social structures, such as informal institutions or other relevant US social practices in US. This provides an entry point for understanding the broader US political environment or challenges in a particular sector or process. Furthermore, any US donor organizations need to place greater emphasis on the analysis of livelihoods and economic opportunities and their relationship to reduce the unequal of gap between rich and poor US citizen in US societies . Thus, US government needs to encourage donor organization participants choose to do the reasonable donor behavioral to aim to reduce the unfair donor spending to the unneeded donor assistance beneficiaries. To let us socio-economic has more balance chance to every US poor citizen in US society. So, it can also raise average every US poor citizen feels better quality of life in US society.How does the rise of US exports to East Asia factor influence US economy change? Export have become an increasing important source of revenue for both national and regional forms in the United States. How does the primary growth market for US exports to influence US economy growth? I recommend the developing nations in East Asia will the developing nations in East Asia will soon rival today's industrial nations as the most important US trading partner . In view of the rapid growth of US exports and their geographic shift toward developing nations.
| Author | : Nripendra P. Rana |
| Publisher | : Springer Nature |
| Total Pages | : 337 |
| Release | : 2019-11-11 |
| Genre | : Business & Economics |
| ISBN | : 3030243745 |
This book examines issues and implications of digital and social media marketing for emerging markets. These markets necessitate substantial adaptations of developed theories and approaches employed in the Western world. The book investigates problems specific to emerging markets, while identifying new theoretical constructs and practical applications of digital marketing. It addresses topics such as electronic word of mouth (eWOM), demographic differences in digital marketing, mobile marketing, search engine advertising, among others. A radical increase in both temporal and geographical reach is empowering consumers to exert influence on brands, products, and services. Information and Communication Technologies (ICTs) and digital media are having a significant impact on the way people communicate and fulfil their socio-economic, emotional and material needs. These technologies are also being harnessed by businesses for various purposes including distribution and selling of goods, retailing of consumer services, customer relationship management, and influencing consumer behaviour by employing digital marketing practices. This book considers this, as it examines the practice and research related to digital and social media marketing.
| Author | : Johnny Ch Lok |
| Publisher | : |
| Total Pages | : 80 |
| Release | : 2021-03-26 |
| Genre | : |
| ISBN | : |
Nowadays, the current technological changes of humans and machines, but rather an opportunity for work to truly become a channel though which human recognize full potential. As US is a high technological developed country. I assume many US employers will choose to act to be the first high technological and invention manufacturing leader to encourage which labors need to learn high technological production methods to prepare manufacture any new technological products to sell in the future US domestic or foreign both markets. Thus, it is possible that future high technological manufacturing labor numbers will be shared large go e.g. 50 to 60% future total US labor market.How can future US labor market affect job creation and productivity growth? US future economic growth requires factor reallocation across US firms and continuous replacement of technologies. US labor market influences US economy dynamism by their impact on the supply of a key factor, skilled workers to US new and expanding firms, US growth -favoring labor market includes portable pension plans and health insurance united to the current US employers, individualized wage-setting and US public income insurance systems that encourage mobility and risk taking. US future economic growth arises as production shifts from less to more successful firms though the reallocation of factors of production . US labor market can advance restructuring. Overly regulations tend to create a system in which a large share of economic activity occurs in US small firms without the ability to grow. US labor market should be organized to promote potential high growth US firms, especially through decentralized and individualized wage setting, portable jobs.In the future, US will have many key importance of high growth firms. US capitalism entails a process of creative destination. New ideas continuously challenges act structures, giving rise to structural transformation as successful innovations and new products firms and industries will arise and obsolete ones will decline in US society. Martin, J. P. (2012) studies pointed to high-growth forms ( sometimes known as gazelles) as the main drivers of this process. In the US, an estimated 1% of firms creation 40% of all new jobs and 5% create almost 70% of new jobs. A review of the studies of US firms growth reveals some common findings . US high-growth firms are crucial to net job growth, generating a large share of all net jobs . This is particularly pronounced in recessions, when US high-growth firms continue to grow when other US firms deadline. US small firms are over-represented among high-growth firms, but these US firms come in all sizes . A small subgroup of large high growth firms are major job creators. Such as US high -growth firms are younger on average, US young and small high high-growth firms grows, not through mergers and acquisition and make a larger contribution to net employment growth than do US larger and older higher growth firms, high growth firms are present in all industries. Through they are slightly overrepresented in service industries in US.Some economists predict that future US will be a flexible labor market, the marginal product of labor and the average wage in an industry should tend toward equally across US firms. Taking advantage of a legislative change to raise cost to US employers a study measured the gap between the marginal product of labor and the average wage in an industry before and after the reform. The gap increased after the legislation, which suggests that the legislation reduced allocative efficiency. Their studies have suggested that total factor productivity could increase by as much as 30% in China and India of they were to attain the US level of allocation efficiency across firms within individual industries.
| Author | : Johnny Ch Lok |
| Publisher | : Independently Published |
| Total Pages | : 400 |
| Release | : 2019-03-27 |
| Genre | : Business & Economics |
| ISBN | : 9781091760240 |
However, (AI) big data gather tool will encounter these challenges when any business plans and implements to apply it to predict consumer behavior in retail industry. The challenges include that as below:1.The high cost and difficulty of implementing new technologies . The (AI) big data gather tool needs capital and capabilities to be designed to implement to be applied to different retail industry users. so, expensive barriers to innovation, an organization and the skillsets of its people to support a new design of (AI) big data gather tool, highly digital technology may be required.2.Slow pace of cultural change. Consumers need to adapt or accept (AI) new technology consumption model in the traditional retail industry. The rate of change is outpacing the ability of businesses to keep up. (AI) big data gather tool needs to be designed to adopt in new or evolved business model requires, in most cases, a new level of customer behavioral predictive machine operation will impact to influence any retail businesses' consumer behavioral changes at a minimum, an organization's structure, capabilities, culture and decision making. If the retail business expects to apply (AI) big data gather tool to predict how to change its consumer behaviors and how their consumption behaviors will tend to change in order to achieve to change their positive emotion from negative emotion before they choose to buy its product or consume its service in success.6.3Challenge to using (AI) neural networks to predict customer behavior from big data gather tool(AI) big data gather tool will encounter the challenge: How can predict customer behavior be represented as sequential data describing the interactions of the customer with a company or an (AI) data gather system through the time, e.g. these interactions are items that the customer purchase or views ? So, every customer data gather, (AI) needs to spend time to analyze how and why to cause whose consumption behavioral choice. It is too difficult matter or judgement for (AI) learning. So, (AI) needs to spend time to learn how to analyze every customer's shopping behavior or actin in order to gather all different consumers' past shopping action information in order to help business owners to predict future its potential customer shopping behavior how to change more clear and accurate prediction. (AI) big data gather tool needs to learn to know that how to judge every customer interaction likes purchases over time can be represented with sequential data. Sequential data has the main property that the order of the information is important. Many (AI) machine learning models are not suited for sequential data, as they consider each input sample independent from previous ones. Therefore, at the end of the sequence, (AI) big data gather learn machines need to keep in their internal state of every customer purchase data, kind of product or service, price, whole year consumption times form all previous inputs, making them suitable for this type of data.
| Author | : John Lok |
| Publisher | : Notion Press |
| Total Pages | : 0 |
| Release | : 2024-08-17 |
| Genre | : Business & Economics |
| ISBN | : |
Our sociey is influenced by economic development and consumer behaviors nowadays. Why development economy can help our societies to explain why the matter occurs, predict when the matter occurs, even it can help us to solve any social, organizations, consumer challenges? Technology invention can bring what change to our future societies. However, when technology may bring positive or negative impact to ourselves societies in the same time. Would technology also impact to ourselves as human behavioral change. I assume that technology and human behavior which have close relationship (e.g. working behavior, living behavior), For robot case example, if robots can influence human behavioral change, and future human working environment will need to cooperate with robots or human living environment will depend on robots' helping. How human behavior will be influenced to change in order to adapt to accept robots invention when human needs to live or work with robots together in the same time?
| Author | : Johnny Ch LOK |
| Publisher | : |
| Total Pages | : 181 |
| Release | : 2021-06-29 |
| Genre | : |
| ISBN | : |
Main barriers influence artificial intelligence consumer behavioral prediction to threaten AI marketing development in success. The factors may include: In future, it is possible that these barriers will influence how to apply (AI technology) to predict consumer behavior in success. The barriers may include: Lacking of a (AI) digital data gathering vision and strategy, lacking of efficient workforce readiness, (AI) technology constraints., non reaching (AI) consumer behavioral prediction mature stage, time and money and resource constraints, law and regulations prohibition to develop (AI) consumer behavioral prediction bug data gather technology. However, the recommendation of solutions to attack the barriers to influence artificial intelligence consumer behavioral prediction not success, it may include gaining employee buy in to participate and develop (AI) consumer behavioral prediction technology, making customer experience to a concern (AI) big data gather questionnaire investigation, providing compensation, training to employees in order to achieve (AI) consumer behavioral big data questionnaire investigation research digital technological goals and strategy, task senior leaders manage any (AI) digital big data gather technology changes, putting policies and (AI) big data gather digital technology in place to support a fully remote, flexible workforce in any (AI) digital big data gather questionnaires research projects, teaching all employees how to code/understand (AI) big data gather consumer behavioral prediction software development, appointing a chief (AI) officer to manage any (AI) big data gather customer behavioral prediction projects and automate everything and encourage customers to attempt experience to self-service and (AI) big data gather questionnaire research to earn beneficial consumption aim after they gave feedback to any (AI) digital questionnaire researches. So, in the future, the (AI) digital big data questionnaire researches can include these industries surveyed, such as automat m financial services, public healthcare, private healthcare, technology, telecoms, insurance, life sciences, manufacturing, media and entertainment , oil and gas, retail and consumer products etc. Hence, in the future, any of these industries can attempt to apply (AI) digital big data gather technology to predict how and why consumer behaviors will change in order to avoid reducing consumer number threat occurrence. 10.1 (AI) digital data gather technology predicts food consumer behavior's main barriers What are the main barriers to food industry? When the food manufacturer applies (AI) big data gather technology to predict food consumer behavior? The barriers include that the food manufacturer / provider needs to decide whether when the right time is applied to the right (AI) digital big data prediction tool channel to find the right food consumers to be chose to full food consumption satisfactory questionnaires, how to gather multi-class food consumption classifiers on real-world food consumers transactional data from the food sale domain consistently to show the critical numbers of different kinds of food items at which the predictive performance most accurate? So, any food manufacturer / provider's advanced in (AI) digital data gather warehousing and management technologies can provide that opportunities for food business to enhance long term relationship with the food providers' clients.
| Author | : Johnny Ch Lok |
| Publisher | : Independently Published |
| Total Pages | : 574 |
| Release | : 2018-10-26 |
| Genre | : |
| ISBN | : 9781729294741 |
I write this book aim to explain how and why whether artificial intelligence ( big data gathering tool) is better method to compare economic or statistics or psychological methods to predict consumer behavior. If future artificial intelligent technology can be developed to apply to predict consumer behavior, what requirements does it need to achieve consumer psychological prediction function? This book aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to assit businesses to predict why and when and how consumer behavior changes. I shall explain why traditional psychological and statistic and marketing methods are applied to predict consumer behaviors, human's judgement and analytical effort will be worse to compare AI machine's judgement and analytical effort. Also, I shall indicate different business organizations why they apply AI big data gathering method to help them to design any questionnaires ( surveys) questions which will be more valid and useful to conclude human's questionnaires ( surveys) design questions method.This book has these two research questions need to be answered?(1)Can apply (AI) learning machine predict consumer behaviors?(2)Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate?Nowadays, many businessmen or marketing research professional hope to apply different methods to predict consumer behaviors in order to know what will be future market activities and market changes to help them to choose to implement what kinds of marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how consumer behavioral changes to influence whose behavioral consumption to the manufacturer products sale within one to two years short term or three to five years middle term, even above five years long term business plans.Hence, if the product manufacturers can apply the most suitable consumer behavioral prediction method to predict how consumers' choice will be changed to influence their products sale easily. It will have more beneficial intangible and tangible advantages to achieve the their product easier sale aim to ensure their businesses' future market share to be increased more easier to their countries' choice target sale markets. Otherwise, if they applied the inaccurate consumer behavioral prediction methods to predict how their consumers' behavioral changes wrongly. Then, it will influence their market shares to be same level, even it will decrease their market shares, when their consumer behavioral prediction inaccurately.In my this book first part, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book.
| Author | : Johnny Ch Lok |
| Publisher | : Independently Published |
| Total Pages | : 174 |
| Release | : 2018-09-08 |
| Genre | : Business & Economics |
| ISBN | : 9781720160410 |
This book has these two research questions need to be answered? (1) Can apply (AI) learning machine predict consumer behaviors? (2) Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate? Nowadays, many businessmen or marketing research professional hope to apply different methods to predict consumer behaviors in order to know what will be future market activities and market changes to help them to choose to implement what kinds of marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how consumer behavioral changes to influence whose behavioral consumption to the manufacturer products sale within one to two years short term or three to five years middle term, even above five years long term business plans. Hence, if the product manufacturers can apply the most suitable consumer behavioral prediction method to predict how consumers' choice will be changed to influence their products sale easily. It will have more beneficial intangible and tangible advantages to achieve the their product easier sale aim to ensure their businesses' future market share to be increased more easier to their countries' choice target sale markets. Otherwise, if they applied the inaccurate consumer behavioral prediction methods to predict how their consumers' behavioral changes wrongly. Then, it will influence their market shares to be same level, even it will decrease their market shares, when their consumer behavioral prediction inaccurately. In my this book first part, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book. In my this book second part, I shall explain why and how human can possible apply (AI) tool to predict consumer individual emotion. I shall indicate case studies to explain how consumer individual better or worse emotion how to influence whose consumption behavior in different suitations. Finally, I shall indicate evidences to conclude how and why (AI) tool that can be used to predict consumer individual emotion and it will have direct relationship to influence consumption behavior, as well as how (AI) tool can assist businessmen to judge whether what reasons case the customer does not choose to buy its product, it is possible because the product high price factor, poor product quality or poor staff service performance or attitude etc. different factors to influence the consumer decides to choose to buy the other product consequently, when the (AI) tool can confirm consumer has good or bad emotion to judge what factors are the causes his decision making at the moment.
| Author | : John Lok |
| Publisher | : Notion Press |
| Total Pages | : 0 |
| Release | : 2022-09-26 |
| Genre | : |
| ISBN | : |
How AI technology influence productivities and service performance ? Whether it can raise productivities and improve service performance?This book aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to assit businesses to predict why and when and how consumer behavior changes. I shall explain why traditional psychological and statistic and marketing methods are applied to predict consumer behaviors, human's judgement and analytical effort will be worse to compare AI machine's judgement and analytical effort. Also, I shall indicate different business organizations why they apply AI big data gathering method to help them to design any questionnaires ( surveys) questions which will be more valid and useful to conclude human's questionnaires ( surveys) design questions method. This book has these two research questions need to be answered? Can apply (AI) learning machine predict consumer behaviors? Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate? Can robots influence human social future behavioral change?
