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This research mainly intends to ascertain the stimulus of investor investment tendencies on the amount of capital investment in the share market.

Utilizing a sample of 477 individual investors who actively trade on the Bangladesh capital market, this empirical study was conducted. The objective of this examination is to ascertain the investment trading behavior of retail investors in the Bangladesh capital market using multiple regression, hypothesis testing and correlation analysis.

The coefficients of market categories, preferred share price ranges and investment source reveal negative predictor correlations; all predictors are statistically significant, with the exception of investment source. Positive predictive correlations exist between investor category, financial literacy degree, investment duration, emotional tolerance level, risk consideration, investment monitoring activities, internal sentiment and correct investment selection. Except for risk consideration and investment monitoring activities, all components have statistically significant predictions. The quantity of capital invested in the stock market is heavily influenced by the investment duration, preferred share price ranges, investor type, emotional toleration level and decision-making accuracy level.

This investigation was conducted exclusively with Bangladeshi individual stockholders. Therefore, the existing study can be extended to institutional investors and conceivably to other divisions. It is possible to conduct this similar study internationally. And the query can enlarge with more sample size and use a more sophisticated econometric model. Despite that the outcomes of this study help the regulatory authorities to arrange more informative seminars and consciousness programs.

The conclusions have practical implications since they empower investors to modify their portfolios based on elements including share price ranges, investment horizons and emotional stability. To improve chances of success and reach financial objectives, they stress the significance of bettering financial understanding, active monitoring and risk analysis. Results can also be enhanced by distributing ownership over a number of market sectors and price points. The results highlight the value of patience and giving potential returns enough time.

This study on the trading behavior of investors in Bangladesh is unique and based on field study, and the findings of this study will deliver information to the stakeholders of the capital market regarding the investors’ trading behavior belonging to different categories, financial literacy level, investment duration, emotional tolerance level and internal feeling.

Coronavirus disease (COVID-19) was declared as a pandemic since COVID-19's widespread outbreak and the hospitality industry has been the hardest hit due to lockdown. Consequently, hospitality workers are suffering from the negative aspects of mental health. In the event of such a crisis, this study aims to explore the link between unemployment and home isolation to the willingness to choose electronic consultation (e-consultation) by exploiting psychological ill-being and behavioural intention (BI) with marital status as a moderator.

A quantitative methodology is applied to primary data collected from 310 workers from the hospitality industry through an online survey.

Findings of this study suggest that the usage of the e-consultation service can be adopted using three levels. There are valid reasons to conclude unemployment and home isolation are linked to higher rates of psychological health behaviours, which can result in stigma, loss of self-worth and increased mortality. The adverse effect is higher for single individuals than for married people.

The study focussed on e-consultation, BI coupled with the Fishbein scale and a classification model for the prediction of willingness to choose e-consultation with the extension of Theory of Planned Behaviour (TPB).

This case study is designed to enable students to formulate the strategic planning process in relation to an organization’s resources; assess the critical tasks required for the company’s business planning for growth and market expansion; and examine the importance of the value delivery process for the company, its customer and its employees. At the end of the case discussion, students will learn how to plan their business in an emerging market by using their existing resources, where the business stands at present and where it may go in the coming future.

The case study discusses how Byju’s, an Indian multinational educational technology company, revolutionized student learning programs through its innovative strategic implementation. It explores the company’s growth and expansion strategy by considering a strength, weakness, opportunity and threats analysis. It elaborates on how Byju’s acquired various companies in India and other countries to become an international technology-based educational brand with 150 million users in 2022. The case study also highlights the marketing and promotional strategy used by the company on online and offline platforms. The case study elaborates on the value delivery process and its importance for customer and employee satisfaction. Despite its success in the Indian market, Byju’s faced tough challenges in the US and European markets, such as lower-than-expected growth rates and lower subscription numbers, even though it followed the same strategy as in the Indian market. The acquisition and celebrity strategy works in emerging economies such as India but not in developed countries. The company’s return on investment was down owing to the high costs it had incurred over the years on market acquisitions and marketing promotions. The growing competition was also expected to bring more challenges for Byju’s. New players such as Tata Studi and YouTube planned to enter the market. Byju Raveendran and his management group had to decide whether to maintain or change the current market offering to reflect market developments to satisfy their customers and employees. They also had to determine whether the main components of the marketing strategy, such as the company’s ongoing value delivery process and ongoing strategy toward the target audience, partners and rivals, are advantageous to the firm or not. The team was in dilemma whether the marketing planning process was going in the right direction and how to make all elements of its businesses more efficient in dealing with the issues. Raveendran kept asking questions about to what extent it is still possible to alter the marketing plan.

The case study is appropriate for discussion in courses such as marketing management, service marketing and strategic marketing management, whether they are part of an undergraduate program (Bachelor of Business Administration [BBA]), a postgraduate program in business management (Master of Business Administration [MBA]) or an executive-level program (executive MBA). The breadth of business topics addressed and the intricacy of the scenario make this case study best suited to be used after the semester as either a culminating project or as a seminar discussion for undergraduates (BBA). The case study can also be discussed in the marketing management course (graduation level) under the marketing and service strategy chapters.

CSS8: Marketing

Teaching notes are available for educators only.

This study aims to demonstrate a modified wire arc additive manufacturing (AM) named non-transferring arc and wire AM (NTA-WAM). Here, the build plate has no electrical arc attachment, and the system’s arc is ignited between tungsten electrode and filler wire.

The effect of various deposition conditions (welding voltage, travel speed and wire feed speed [WFS]) on bead characteristics is studied through response surface methodology (RSM). Under optimum deposition condition, a single-bead and thin-layered part is fabricated and subjected to microstructural, tensile testing and X-ray diffraction study. Moreover, bulk texture analysis has been carried out to illustrate the effect of thermal cycles and tensile-induced deformations on fibre texture evolutions.

RSM illustrates WFS as a crucial deposition parameter that suitably monitors bead width, height, penetration depth, dilution, contact angle and microhardness. The ferritic (acicular and polygonal) and lath bainitic microstructure is transformed into ferrite and pearlitic micrographs with increasing deposition layers. It is attributed to a reduced cooling rate with increased depositions. Mechanical testing exhibits high tensile strength and ductility, which is primarily due to compressive residual stress and lattice strain development. In deposits, ϒ-fibre evolution is more resilient due to the continuous recrystallisation process after each successive deposition. Tensile-induced deformation mostly favours ζ and ε-fibre development due to high strain accumulations.

This modified electrode arrangement in NTA-WAM suitably reduces spatter and bead height deviation. Low penetration depth and dilution denote a reduction in heat input that enhances the cooling rate.

The need for precise synthesis of customized designs has resulted in the development of advanced coating processes for modern nanomaterials. Achieving accuracy in these processes requires a deep understanding of thermophysical behavior, rheology and complex chemical reactions. The manufacturing flow processes for these coatings are intricate and involve heat and mass transfer phenomena. Magnetic nanoparticles are being used to create intelligent coatings that can be externally manipulated, making them highly desirable. In this study, a Keller box calculation is used to investigate the flow of a coating nanofluid containing a viscoelastic polymer over a circular cylinder.

The rheology of the coating polymer nanofluid is described using the viscoelastic model, while the effects of nanoscale are accounted for by using Buongiorno’s two-component model. The nonlinear PDEs are transformed into dimensionless PDEs via a nonsimilar transformation. The dimensionless PDEs are then solved using the Keller box method.

The transport phenomena are analyzed through a comprehensive parametric study that investigates the effects of various emerging parameters, including thermal radiation, Biot number, Eckert number, Brownian motion, magnetic field and thermophoresis. The results of the numerical analysis, such as the physical variables and flow field, are presented graphically. The momentum boundary layer thickness of the viscoelastic polymer nanofluid decreases as fluid parameter increases. An increase in mixed convection parameter leads to a rise in the Nusselt number. The enhancement of the Brinkman number and Biot number results in an increase in the total entropy generation of the viscoelastic polymer nanofluid.

Intelligent materials rely heavily on the critical characteristic of viscoelasticity, which displays both viscous and elastic effects. Viscoelastic models provide a comprehensive framework for capturing a range of polymeric characteristics, such as stress relaxation, retardation, stretching and molecular reorientation. Consequently, they are a valuable tool in smart coating technologies, as well as in various applications like supercapacitor electrodes, solar collector receivers and power generation. This study has practical applications in the field of coating engineering components that use smart magnetic nanofluids. The results of this research can be used to analyze the dimensions of velocity profiles, heat and mass transfer, which are important factors in coating engineering. The study is a valuable contribution to the literature because it takes into account Joule heating, nonlinear convection and viscous dissipation effects, which have a significant impact on the thermofluid transport characteristics of the coating.

The momentum boundary layer thickness of the viscoelastic polymer nanofluid decreases as the fluid parameter increases. An increase in the mixed convection parameter leads to a rise in the Nusselt number. The enhancement of the Brinkman number and Biot number results in an increase in the total entropy generation of the viscoelastic polymer nanofluid. Increasing the strength of the magnetic field promotes an increase in the density of the streamlines. An increase in the mixed convection parameter results in a decrease in the isotherms and isoconcentration.

This research explores the determinants and consequences of salesperson polychronicity in a business-to-business (B2B) sales environment. Additionally, the study examined the link between the antecedents and consequences of salesperson polychronicity using resistance to change (RC) and manager trust in salesperson (MT) as moderators.

A conceptual framework was developed by testing eight hypotheses based on data collected from 378 salesperson-manager dyads.

The authors find that opening leader behavior is positively associated with salesperson polychronicity, while closing leader behavior negatively influences salesperson polychronicity. In addition, salesperson polychronicity positively affects service recovery performance and customer-directed organizational citizen behaviors (OCB). Finally, the RC and MT significantly and positively moderate the linkage between the antecedents and consequences of salesperson polychronicity.

This study is original because this is the first study to address polychronicity as an individual trait in a B2B environment where multitasking behavior is of paramount importance.

Artificial intelligence (AI) has sparked interest in various areas, including marketing. However, this exhilaration is being tempered by growing concerns about the moral and legal implications of using AI in marketing. Although previous research has revealed various ethical and legal issues, such as algorithmic discrimination and data privacy, there are no definitive answers. This paper aims to fill this gap by investigating AI’s ethical and legal concerns in marketing and suggesting feasible solutions.

The paper synthesises information from academic articles, industry reports, case studies and legal documents through a thematic literature review. A qualitative analysis approach categorises and interprets ethical and legal challenges and proposes potential solutions.

The findings of this paper raise concerns about ethical and legal challenges related to AI in the marketing area. Ethical concerns related to discrimination, bias, manipulation, job displacement, absence of social interaction, cybersecurity, unintended consequences, environmental impact, privacy and legal issues such as consumer security, responsibility, liability, brand protection, competition law, agreements, data protection, consumer protection and intellectual property rights are discussed in the paper, and their potential solutions are discussed.

Notwithstanding the interesting insights gathered from this investigation of the ethical and legal consequences of AI in marketing, it is important to recognise the limits of this research. Initially, the focus of this study is confined to a review of the most important ethical and legal issues pertaining to AI in marketing. Additional possible repercussions, such as those associated with intellectual property, contracts and licencing, should be investigated more deeply in future studies. Despite the fact that this study gives various answers and best practices for tackling the stated ethical and legal concerns, the viability and efficacy of these solutions may differ depending on the context and industry. Thus, more research and case studies are required to evaluate the applicability and efficacy of these solutions in other circumstances. This research is mostly based on a literature review and may not represent the experiences or opinions of all stakeholders engaged in AI-powered marketing. Further study might involve interviews or surveys with marketing professionals, customers and other key stakeholders to offer a full knowledge of the practical difficulties and solutions. Because of the rapid speed of technical progress, AI’s ethical and regulatory ramifications in marketing are continually increasing. Consequently, this work should be a springboard for more research and continuing conversations on this subject.

This study’s findings have several practical implications for marketing professionals. Emphasising openness and explainability: Marketing professionals should prioritise transparency in their use of AI, ensuring that customers are fully informed about data collection and utilisation for targeted advertising. By promoting openness and explainability, marketers can foster customer trust and avoid the negative consequences of a lack of transparency. Establishing ethical guidelines: Marketing professionals need to develop ethical rules for the creation and implementation of AI-powered marketing strategies. Adhering to ethical principles ensures compliance with legal norms and aligns with the organisation’s values and ideals. Investing in bias detection tools and privacy-enhancing technology: To mitigate risks associated with AI in marketing, marketers should allocate resources to develop and implement bias detection tools and privacy-enhancing technology. These tools can identify and address biases in AI algorithms, safeguard consumer privacy and extract valuable insights from consumer data.

This study’s social implications emphasise the need for a comprehensive approach to address the ethical and legal challenges of AI in marketing. This includes adopting a responsible innovation framework, promoting ethical leadership, using ethical decision-making frameworks and conducting multidisciplinary research. By incorporating these approaches, marketers can navigate the complexities of AI in marketing responsibly, foster an ethical organisational culture, make informed ethical decisions and develop effective solutions. Such practices promote public trust, ensure equitable distribution of benefits and risk, and mitigate potential negative social consequences associated with AI in marketing.

To the best of the authors’ knowledge, this paper is among the first to explore potential solutions comprehensively. This paper provides a nuanced understanding of the challenges by using a multidisciplinary framework and synthesising various sources. It contributes valuable insights for academia and industry.

The purpose of this study is to fill the research gap by investigating the impact of brand social initiatives on both the warmth and competence dimensions of the brand, as well as examining the brand's potential to induce pro-environmental behavioral change among consumers.

The study employed a scenario-based survey design and surveyed 415 consumers in India. The data were analyzed using structural equation modeling (SEM) with SmartPLS 4.0.

The results show that social initiatives enhance both dimensions of social perception and increase cooperative intentions. Brand competence is more crucial than warmth in predicting behavioral intentions. Brand-cause fit, CSR commitment and initiatives' impact all influence the brand image. A brand's commitment to the cause is more significant than brand-cause fit in determining how consumers evaluate a brand.

This research provides insights into how social initiatives can enhance brand image and encourage helping intentions through effective communication traits. It can aid brands in building consumer trust, benefiting society and boosting finances. The study offers a framework for effective cause communication strategies, highlighting the importance of commitment to the cause over fitting with the brand's image to elicit desired responses.

This study is a novel attempt that uses the stereotype content model and costly signaling theory to explore how social initiatives influence a brand's warmth and competence and impact consumer behavior. It provides critical insights into the psychological mechanisms behind social initiatives' impact on consumer behavioral intentions.

Since the outbreak of the COVID-19 pandemic, the demand for online services has risen, with e-payment emerging as a prominent option for customers seeking faster and more convenient transactions to complete their online purchases. Nevertheless, e-payment adoption in Egypt remains a challenge that requires further investigation. Thus, this study aims to investigate the factors influencing online customers’ attitudes and intentions towards adopting e-payment for online transactions, social influence, perceived ease of use, perceived usefulness, perceived trust, structural assurance and perceived privacy/security risk.

The data were gathered from 302 customers in Egypt and structurally analysed based on partial least squares structural equation modelling (PLS-SEM).

The findings revealed that social influence, perceived usefulness and perceived trust are significant antecedents of attitude. Furthermore, perceived usefulness, perceived trust, perceived privacy/security risk and attitude directly influence behavioural intention. Structural assurance and perceived trust directly influence perceived privacy/security risk. Moreover, perceived usefulness, perceived trust and attitude were found to have several mediating roles.

This study adds new empirical evidence from a developing country regarding the adoption of e-payment among online customers. In addition, its findings can help the government, practitioners and policymakers understand how to promote customers’ positive attitudes and encourage their intentions towards using e-payment.

The findings of this study can contribute to the digital transformation strategy in Egypt by providing insights into enhancing online shoppers’ attitudes and intentions towards e-payment adoption. This, in turn, can boost Egyptian e-commerce and the country's digital economy as a whole.