Search results

In the era of generative artificial intelligence (AI), big data analytics, business analytics and mega global digital corporations, the profession of marketing is at a crossroads between ‘Prosumer-Marketing’ and ‘Market Grooming’. Whereas prosumer (producers + consumers) marketing means a process of exchange in which producers and consumers have equal, just, control, voluntary, fully aware engagement and control over the process of design, development and exchange of goods, services and values. On the other hand, ‘Market Grooming’ is a one-sided, unethical process of conditioning or influencing, deceiving, or persuading or manipulating and even exploiting customers by the marketing organisations, without customers' voluntary consent, permissions, awareness, etc. As the consumers have asymmetric access to information, asymmetric and lesser favourable levels of control, and lesser power in the process of exchange, as customers trust the marketers or are dependent on popular brands, the markers tend to exploit the situation. The process of market grooming has become easier due to the power of AI, generative AI, ChatGPT, TikToketing, machine learning and big data analytics leading to the development of sophisticated predictive models and persuasive models. This chapter explores and analyses a range of techniques in marketing such as permission marketing, flywheel marketing, subliminal marketing, neuromarketing, cyberstalking, ethical marketing, etc., in the era of AI. The arguments for high concerns pertaining to potential market grooming are supported by theories of ethics, theories of digital marketing and models of AI. The chapter concludes with some strategic recommendations.

The growth of Artificial Intelligence (AI)–enabled marketing has led to motivating customers purchase goods and services where they are ‘nurtured’ or ‘groomed’ to make a purchase decision. Consumer grooming as the name suggests involves changing or influencing an individual's behaviour and decision-making abilities by repeated personalised messaging. We have entered an era where AI is driving marketing in almost all industries and influencing customer decision-making. The healthcare industry is quite a concern as it involves the health of the poor and vulnerable impacted by AI decision-making, also deeply affecting the conventional doctor–patient relationships. AI in healthcare marketing involves using marketing gimmicks by marketing organisations where individuals are targeted with individualised medical messaging, changing the trust dynamics between patients and doctors. The marketing gimmicks often impact the healthcare decision-making of patients, leading to induced healthcare purchases through these marketing messages, rather on advisory of doctors or other healthcare professionals. As a result of this constant patient grooming or medical brainwashing, patients end up making a wrong decision regarding their healthcare. Therefore, it is required that stakeholders in the health ecosystem prioritise more transparency, authenticity and patient empowerment to mitigate the challenges of patient grooming in the healthcare sector. The establishment of more stringent controls on medical marketing techniques, the development of health literacy, and the cultivation of open communication channels within the healthcare ecosystem are all necessary because of this. In the end, AI-driven marketing presents prospects for personalised healthcare experiences; yet its unregulated expansion raises substantial ethical and patient safety issues.

The inclusion of esports as an official event in the Hangzhou Asian Games is an important step towards the institutionalisation of esports. The significance of this event marks that Asia once again takes a lead in the global esportisation. This chapter investigates a series of history events in the inclusion process of esports into the comprehensive Games in Asia using process sociology and actor network theory (ANT). This study will analyse the type characteristics of esports events in Hangzhou Asian Games, whilst examining how key stakeholders' interact and balance in the network composed of international sports organisations, host of the event, emerging esports organisations and esports game companies. The chapter also examines the functions of global game industrial economic geography, local cultural politics, esports geopolitics and Olympic values in esports sportization, aiming to reveal the implications of esports inclusion in the Asian Games on the debate of whether esports meets the criteria to be classified as a ‘sport’ and its enlightenment of digital strategy to the inclusion esports in the Olympics.

This paper investigated the relationship between intellectual capital (IC)/its components, and the business performance of Vietnamese small and medium enterprises (SMEs).

The panel data set was obtained from the Vietnam SME database. Using the value-added intellectual coefficient (VAIC) approach for IC measurement, this paper employs various panel data estimation approaches, including fixed effects (FE) and the generalized method of moments (GMM), to examine the relationship between IC and the financial performance of SMEs in Vietnam.

The result suggests that the value creation activities of SMEs in Vietnam mainly occur on the basis of physical and financial capital. In other words, the findings indicate that Vietnamese SMEs mainly depend on physical and financial capital to profit: they have not fully utilized their human capital and structural capital, two main components of IC for value creation.

The results underline the urgency of effective management of tangible and IC to boost the utilization of human and structural capital to increase the profitability of Vietnamese SMEs. The results lead to suggesting a series of policy recommendations to achieve the objective.

This paper is the first to examine the relationship between IC and the financial performance of SMEs in Vietnam, contributing to the literature on IC in emerging countries.

The purpose of this study paper is to identify and prioritize the factors affecting the knowledge flow in high-tech industries.

This research is applied in terms of purpose and descriptive-survey in terms of data collection method. This research has been done in a qualitative–quantitative method. In the qualitative part, due to the nature of the data in this study, expert interviews have been used. The sample studied in this research includes 35 managers and expert professors with experience in the field of knowledge management working in universities and high-tech industries who have been selected by the method of snowball. In the quantitative part, the questionnaire tool and DANP multivariate decision-making method have been used.

In this study, a multicriteria decision-making technique using a combination of DEMATEL and ANP (DANP) was used to identify and prioritize the factors affecting the knowledge flow in high-tech industries. In this study, the factors affecting the knowledge flow, including 8 main factors and 31 subfactors, were selected. Human resources, organizational structure, organizational culture, knowledge communication, knowledge management tools, knowledge characteristics, laws, policies and regulations and financial resources were effective in improving knowledge flow, respectively.

By studying the research, it was found that the study area is limited, and the previous work has remained at the level of documentation and little practical use has been done. In previous research, the discussion of knowledge flow has not been very open, and doing incomplete work causes limited experiences and increases cost and time wastage, and parallel work may also occur. Therefore, to complete the knowledge management circle and fully achieve the research objectives, as well as to make available and transfer the experiences of people working in this field and also to save time and reduce costs, the contents and factors of previous models have been counted. It is designed for high-tech industries, a model for the flow of knowledge.