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The unexpected outbreak of COVID-19 has expedited the trend toward online education. To facilitate undisruptive learning, EdTech companies are continuously working on providing solutions to restore teaching and learning practices. This has caused a significant behavioral shift of the investors in the EdTech market. This study aims to analyze the effects of Web Market Traffic on the increased number of investors funding an EdTech Company in the market.

By drawing on the multi-method web analytics approach, this study analyses the nexus between Web Market Traffic and Investor's Behavior in the US and India, proving the hypothesized relationship in the proposed Model using a data sample of 300 EdTech Players.

There is a significant difference between the investor's behavior in India and the US. This study shows that the investors in the US are more inclined towards investing in EdTech companies in comparison to India. The Results demonstrate that monthly visits of consumers and the number of acquisitions by players positively affect the investor's behavior, while bounce rates take a toll on the number of investors.

This Study suggests that EdTech investors in the US and India should harness Web Traffic to capture the EdTech market. Further, this study offers practical implications that EdTech players can use to attract potential investors and increase brand visibility by improving web market traffic parameters.

This paper's original contribution is to empirically shed light on the effects of web market traffic on the investor's behavior. The study emphasizes the quintessentiality of managing the bounce rates and monthly visits for an EdTech market to attract more investors and capital inflow that enhance brand visibility. The study found that the investors behave distinctly in the developed and emerging markets in the US and India.

This study aims to assess how department store websites can add online retail brand equity. A quick, relatively easy and low-cost diagnostic tool for stakeholders (e.g. retailers, investors) is presented.

A content analysis of department store websites in the USA and Latin America was conducted.

The findings show that Latin American and US department store websites exhibit acceptable use of online retail brand equity dimensions related to emotional connection and trust. In contrast, compared to their US counterparts, Latin American department store websites show weak usage on some of the dimensions of responsive service nature, online experience and fulfillment. The results also show that higher online retail brand equity is positively associated with average daily time on site. This indicates the usefulness of this index for developing effective websites to creating online retail brand equity.

This study suggests that Latin American department stores should improve three dimensions of online retail brand equity: responsive service nature, online experience and fulfillment. The online retail brand equity index presented can serve as a diagnostic tool for department store managers to monitor the online retail brand equity they are building on their websites. It is also possible to analyze the websites of competing department stores and monitor the long-term impact of modifications made to their websites and those of competitors.

This paper proposes an easy-to-apply index to assess online retail brand equity through website design partially. In addition, this research is the first to evaluate how Latin American department store websites, compared to those in the USA, are building online retail brand equity.

Pricing studies have largely focused on sellers' pricing strategies and price determinants. To expand earlier work on sellers' pricing decisions, this study considers time as a major factor driving sellers' ticket prices in the secondary market. Specifically, because most secondary market transactions occur in the last moments before a game, this study considers how resellers adjust ticket prices within a few days prior to a game day including an actual game day.

To examine the impact of time on secondary market ticket prices for Major League Baseball (MLB), ticket prices were collected from StubHub (one of the largest secondary ticket markets) four times per game: from 3 days to 1 day prior to a game day and on the actual game day. Additionally, 10 control variables were obtained from previous research on price determinants (N = 19,155). A multiple regression model was created based on the extant literature regarding secondary market ticket prices.

Results indicate the number of days before a game negatively influenced ticket prices: resellers decreased ticket prices consistently during the last few days prior to a game's first inning. Specifically, secondary market ticket prices decreased relatively dramatically on an actual game day. Time had no significant effects on ticket prices 2 days prior to a game day. In addition to the role of time, league affiliation and the number of all-star players were identified as key price determinants in the secondary market. Moreover, changes in weather forecasts and the home team starting pitcher's ERA played significant roles in price changes.

Despite containing a relatively high number of data observations compared with prior pricing studies, this study's findings were limited to certain teams. Additionally, as only MLB secondary market ticket pricing was considered, different outcomes and implications may apply in other major sport ticket markets (e.g. NBA, NFL, NHL and MLS) featuring distinct league structures, policies and demand.

This study offers practical guidance for sellers' pricing decisions. Most secondary ticket market sellers lowered their ticket prices relatively dramatically on an actual game day. Reducing ticket prices prior to a game day can lead to greater chances to avoid unsold tickets that compromise revenue management. This study's results also afford professional sport organizations and secondary ticket market consumers a clearer understanding of the factors resellers consider when setting ticket prices.

Although previous studies have uncovered essential elements influencing ticket prices and consumer demand in the secondary ticket market, little work has examined how time affects sellers' pricing decisions within a few days prior to a game day. Little is known about the elements that significantly influence sellers’ decisions to adjust (i.e. increase or decrease) ticket prices in the secondary market as well. This topic deserves ongoing attention, as new outcomes can supplement previous studies' findings due to changing market environments.

The purpose of this paper is to develop a commercialization model based on gaining economic benefits through the transfer of technological capabilities in the oil and gas industry. Since commercialization models are mostly based on the implement of technology to produce and sell new products, this study focuses on developing a specific independent technology commercialization model.

The method of this research is qualitative based on the grounded theory. For this purpose, general variables with content analysis were extracted by reviewing documents (Literature review) and then for identifying special components, interviewing experts in the Iranian oil and gas industry. Participations were selected using snowball sampling for semistructured interviews.

The findings of this research were extracted based on grounded theory with data analysis in MAXQDA software. In this research, first, 210 open codes were identified based on qualitative content analysis of relevant documents and results of interviews with experts. Then the classification of open codes was done, and 46 subcategories (variables) were determined in the commercialization model. Finally, 46 subcategories were classified into 10 categories as axial codes in grounded theory as components of the commercialization model.

The results of this research have led to the creation of new practical and theoretical implications. In this research, a new perspective of commercialization with the aim of transferring technology and obtaining its economic benefits for oil and gas industry companies was discussed. Also, based on the practical implications explained in this research, policymakers can use the suggested model to effectively implement independent technology commercialization to acquire economic benefits.

This study is purely original and the outcome of the research conducted by the authors. The research findings are the outcome of in-depth study on technology commercialization in the Iranian oil and gas industry.

The paper’s main goal is to examine the relationship between the video marketing of financial technologies (Fintechs) and their vulnerable website customers’ brand engagement in the ongoing coronavirus disease 2019 (COVID-19) crisis.

To extract the required outcomes, the authors gathered data from the five biggest Fintech websites and YouTube channels, performed multiple linear regression models and developed a hybrid (agent-based and dynamic) model to assess the performance connection between their video marketing analytics and vulnerable website customers’ brand engagement.

It has been found that video marketing analytics of Fintechs’ YouTube channels are a decisive factor in impacting their vulnerable website customers’ brand engagement and awareness.

By enhancing video marketing analytics of their YouTube channels, Fintechs can achieve greater levels of vulnerable website customers’ engagement and awareness. Higher levels of vulnerable customers’ brand engagement and awareness tend to decrease their vulnerability by enhancing their financial knowledge and confidence.

Fintechs should aim to increase the number of total videos on their YouTube channels and provide videos that promote their customers’ knowledge of their services to increase their brand engagement and awareness, thus reducing their vulnerability. Moreover, Fintechs should be aware not to over-post videos because they will be in an unfavorable position against their competitors.

This research offers valuable insights regarding the importance of video marketing strategies for Fintechs in promoting their vulnerable website customers’ brand awareness during crisis periods.

ChatGPT is a versatile technology with practical use cases spanning many professional disciplines including marketing. Being a recent innovation, however, there is a lack of academic insight into its tangible applications in the marketing realm. To address this gap, the current study explores ChatGPT’s application in marketing by mining social media data. Additionally, the study employs the stages-of- growth model to assess the current state of ChatGPT’s adoption in marketing organizations.

The study collected tweets related to ChatGPT and marketing using a web-scraping technique (N = 23,757). A topic model was trained on the tweet corpus using latent Dirichlet allocation to delineate ChatGPT’s major areas of applications in marketing.

The topic model produced seven latent topics that encapsulated ChatGPT’s major areas of applications in marketing including content marketing, digital marketing, search engine optimization, customer strategy, B2B marketing and prompt engineering. Further analyses reveal the popularity of and interest in these topics among marketing practitioners.

The findings contribute to the literature by offering empirical evidence of ChatGPT’s applications in marketing. They demonstrate the core use cases of ChatGPT in marketing. Further, the study applies the stages-of-growth model to situate ChatGPT’s current state of adoption in marketing organizations and anticipate its future trajectory.

The purpose of this research is to undertake a bibliometric analysis of digital marketing research in small and medium enterprises (SMEs). The study examines papers over the last two decades and performed performance analysis, co-citation analysis, bibliographic coupling and scientific mapping.

The study examines 247 documents retrieved from the Scopus database using bibliometric analysis, performance analysis and thematic clustering. The study looked at the scientific productivity of papers, prolific authors, most influencing papers, institutions and nations, keyword co-occurrence, thematic mapping, co-citations and authorship and country collaborations. VOSviewer was employed as a tool in the research to conduct the performance analysis and thematic clustering.

The most productive year was 2021 with 56 publications and the most impactful institute and countries are the University of Birmingham, UK, and the country is United Kingdom, respectively. Similarly, the most influential journal is “Industrial Marketing Management”, and the most productive journal is “International Journal of Internet Marketing and Advertising”. Furthermore, the most cited article is “Usage, barriers and measurement of social media marketing: An exploratory investigation of small and medium B2B brands”. The authors also identified five thematic clusters of digital marketing research in SMEs.

It informs and directs researchers on the current state of study in the field of digital marketing literature in SMEs. It also outlines future research directions in this field.

This is the first study which provides the performance analysis and scientific mapping of the digital marketing literature in SMEs.

The purpose of the paper is to analyze the supply and demand of marketing and communication consulting services and evaluate actual and perceived gaps.

The paper uses two different datasets to assess the gap. The supply database comes from desk research carried out in the province of Bergamo (n. 159 consulting agencies). The demand dates are the results of 100 structured interviews with local companies that requested marketing and communication consulting services both inside and outside the province.

Findings show that there is no significant shortage in local service supply. Nonetheless, a limited gap exists between the provision of specific services and their overall quality. Conversely, the perceived gap is wider, leading to an impression of scarce availability – a notion disproven by the analysis of the actual supply.

The study suggests that local agencies may overcome their “myopic” attitude and need to increase their visibility, competencies and expertise by investing in these areas and improving networking.

There are no previous studies that compare the supply and demand for marketing and communication consulting services. The paper also provides insights into actual and perceived gaps in a hypercompetitive environment.

The smart destination can be defined as a destination that deploys information communications technologies (ICTs) and other technological tools for interactive/participative engagement with prospective visitors. The rationale is to enhance the residents' quality of life as well as the tourists' experiences of the destinations they visit. This chapter discusses about digitization strategies and on marketing superstructures affecting destinations. It advances a conceptual framework through the development of an Attracting, Stay, and Return (ASR) Model that is suitable for smart destinations. It relies on descriptive case studies to conceptualize smart tourism destinations. This contribution reiterates the importance of having a well-designed website that presents appropriate content to entice the prospective travelers' curiosity about destinations. It offers valuable insights and advances new knowledge on smart marketing approaches that are intended to increase the destination management organizations' outreach with tourists at each stage of the ASR Model.

The purpose of this paper is to understand the market for various e-learning platforms existing globally. The global pandemic transformed the traditional education sector into an e-learning industry and impacted the digital education sector proportionally. The wide impact on people to maintain a social distance shortened the space and enhanced student engagement with digital screens. The merchandise of electronic gadgets and e-learning platforms boosted global revenues ever before.

A digital data analytical tool retrieved the data for e-learning companies. While screening companies, the authors came up with more than 150 and later narrowed it to 71. Furthermore, revenues and market capitalisation data were collected from open-source websites of respective e-learning platforms at national and international stock exchanges. The data from the year 2018 to 2021 was used to predict the compound annual growth rate (CAGR) of the 2022–2027 market value of e-learning companies. The demographics of the statistical data were plotted using GraphPad Prism and Python Plotly. Also, the study attempted to underpin the association of annual revenue with market capitalisation for e-learning companies using Statistical Package for the Social Sciences (SPSS).

The financials of the e-learning platforms were compared from 2018 to 2021 based on the stock market exchange, which showed a gradual increase in revenues and influenced the market capitalisation by the 2022 financial year. Also, simultaneously validating the CAGR of 13.16%, the expected revenues from 2022 to 2027 were $830bn. The data plotted on the atlas choropleth exhibiting the e-learning users increased globally by 2022. The Web traffic data validated by the browsing gadget helped to validate the increase in revenues of the electronic gadget companies.

To the best of the authors’ knowledge, this is one of the pioneer studies postulating the study of e-learning demographics comparing the e-learning influence on the global digital market, Web user traffic and the education sector. The demographics of e-learning users by age, gender and gadget distribution validate the e-learning induction globally.