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This study aims to theorize and empirically examine the relationship between “purchase intention and conversion rate”, “website satisfaction and conversion rate” and “purchase intention and conversion rate”. E-Commerce conversion rate represents the percentage of visits to an e-tailer’s website that includes a purchase transaction. Despite the importance of conversion rates for e-tailers, prior research predominantly used purchase intention and website satisfaction as main dependent variables and implicitly assumed that these variables will influence the actual purchase.

Data on 85 US retail websites were used to test the hypotheses. The unit of the analysis is the online retail website. Regression analysis was used to perform the data analysis.

The results indicate that both purchase intention and website satisfaction positively influence conversion rates. It was also found that website satisfaction positively influences purchase intention.

Only data from 85 US e-tailers from the top-100 US online retailers are used to test the hypotheses. Also, conversion rate is only one of the several important success metrics used by e-tailers.

This study not only examines antecedents of e-commerce conversion rates, but also theorizes and tests if there is a statistically significant relationship between “purchase intention and conversion rate” and “website satisfaction and conversion rate”. This is because, although previous studies used purchase intention and website satisfaction as main dependent variables and proxies for actual purchase behavior, they did not validate this relationship. This study shows that: there is a statistically significant relationship between “purchase intention and conversion rate” and “website satisfaction and conversion rate”, there is also a statistically significant relationship between “website satisfaction and purchase intention” and this study used firm-level data to theorize, measure and analyze the data, whereas prior literature used only individual-level data.

The aim of this paper is to examine the impact of three main technologies on converting browsers into customers: impact of review rating (location rating and service rating), recommendation and search listings.

This paper estimates conversion rate model parameters using a quasi-likelihood method with the Bernoulli log-likelihood function and parametric regression model based on the beta distribution.

The results show that a high rank in search listings, a high number of recommendations and location rating have a significant and positive impact on conversion rates. However, service rating and star rating do not have a significant effect on conversion rate. Furthermore, room price and hotel size are negatively associated with conversion rate. It was also found that a high rank in search listings, a high number of recommendations and location rating increase online hotel bookings. Furthermore, it was found that a high number of recommendations increase the conversion rate of hotels with low ranks.

The findings show that hotels’ location ratings are more important than both star and service ratings for the conversion of visitors into customers. Thus, hotels that are located in convenient locations can charge higher prices. The results may also help entrepreneurs who are planning to open new hotels to forecast the conversion rates and demand for specific locations. It was found that a high number of recommendations help to increase the conversion rate of hotels with low ranks. This result suggests that a high numbers of recommendations mitigate the adverse effect of a low rank in search listings on the conversion rate.

This paper contributes to the understanding of the drivers of conversion rates in online channels for the successful implementation of hotel marketing.

It is generally recognised that companies spend approximately 50% of their marketing budget on promotional activities. Advertising belongs to the most visible areas of a company’s activity. Therefore, it should not be surprising that the average recipient associates marketing with advertising, competitions and leaflets about new promotions delivered to houses or offices. Advertising, especially Internet advertising, is one of the most effective forms of marketing and one of the fastest developing areas of business. New channels of communication are emerging all the time – the Internet, digital television, mobile telephony; accompanied by new forms, such as the so-called ambient media. Advertising benefits from the achievements of many fields of science, that is, psychology, sociology, statistics, medicine and economics. At the same time, it combines science and the arts – it requires both knowledge and intuition. Contemporary advertising has different forms and areas of activity; yet it is always closely linked with the operations of a company – it is a form of marketing communication.

The indices of marketing communication presented in this chapter are generally known and used not only by advertising agencies but also by the marketing departments of many organisations. Brand awareness, advertising scope and frequency, the penetration index or the response rate belong to the most widely used indices; others, like the conversion rate or the affinity index, will get increasingly more significant along with the process of professionalisation of the environment of marketing specialists in Poland and with increased pressure on measuring marketing activities. Marketing indices are used for not only planning activities, but also their evaluation; some of them, such as telemarketing, mailing and coupons, provide an extensive array of possibilities of performance evaluation.

This paper aims to explore the promotion decisions of heterogeneous sellers on a decentralized platform under competitive conditions and analyze how seller behaviors impact platform profit, seller revenue, buyer surplus and social welfare.

This paper considers a Cournot model consisting of a platform charging a commission rate and two sellers with different conversion rates and browsing costs. Promotion efforts by sellers can increase traffic, but they also incur promotion costs for sellers. The sellers decide on promotion effort by weighing these two effects. The authors also explore the equilibrium when the platform charges a fixed usage fee.

The seller’s profit improves as its conversion rate increases and worsens as browsing costs increase. Also, increasing the commission rate charged by the platform makes the seller invest less in promotional efforts. Therefore, the platform must consider this trade-off to determine an optimal rate. The analysis shows that the seller with a high conversion rate and high browsing cost plays a greater role in generating more overall revenue. When the market favors such a seller, the platform tends to charge less in order not to impair its profitability.

This paper incorporates conversion rate, buyer’s browsing cost, unit promotion cost and the fee charged by the platform into the model to study sellers’ promotion decisions on decentralized platforms.

This purpose of this article is to solve the problem of bidding on keywords in newly set-up search engine advertising campaigns. Advertisers setting up search engine advertising campaigns for the first time need to place bids on keywords, but typically lack experience and data to determine ranks that maximize a keyword’s profit (generally referred to as a cold-start problem).

The authors suggest that advertisers collect data from the Google Keyword Planner to obtain precise estimates of the percentage increases in prices per click and click-through rates, which are needed to calculate optimal bids (exact approach). Together with the profit contribution per conversion and the conversion rate, the advertiser might then set bids that maximize profit. In case advertisers cannot afford to collect the required data, the authors suggest two proxy approaches and evaluate their performance using the exact approach as a benchmark.

The empirical study shows that both proxy approaches perform reasonably well, the easier approach to implement (Proxy 2) sometimes performs even better than the more sophisticated one (Proxy 1). As a consequence, advertisers might just use this very simple proxy when bidding on keywords in newly set-up search engine advertising campaigns.

This research extends the stream of literature on how to determine optimal bids, which so far focuses on campaigns that are already running and where the required data to calculate bids are already available. This research offers a novel approach of determining bids when advertisers lack the aforementioned information.

The first research objective is to understand the role of digital [artificial intelligence (AI)] technologies on user engagement and conversion that has resulted in high online activities and increased online sales in current times in India. In addition, combined with changes such as social distancing and lockdown due to the COVID-19 pandemic, digital disruption has largely impacted the old ways of communication both at the individual and organizational levels, ultimately resulting in prominent social change. While interacting in the virtual world, this change is more noticeable. Therefore, the second research objective is to examine if a satisfying experience during online shopping leads to repurchase intention.

Using primary data collected from consumers in a developing economy (India), we tested the theoretical model to further extend the theoretical debate in consumer research.

This study empirically tests and further establishes that deploying AI technologies have a positive relationship with user engagement and conversion. Further, conversion leads to satisfying user experience. Finally, the relationship between satisfying user experience and repurchase intention is also found to be significant.

The uniqueness of this study is that it tests few key relationships related to user engagement during this uncertain period (COVID-19 pandemic) and examines the underlying mechanism which leads to increase in online sales.

Change in ownership among U.S. community hospitals has been frequent and, not surprisingly, remains an important issue for both researchers and public policy makers. In the past, investor-owned hospitals were long suspected of pursuing financial over other goals, culminating in several reviews that found few differences between for-profit and nonprofit forms (Gray, 1986; Sloan, 2000; Sloan, Picone, Taylor, & Chou, 2001). Nevertheless, continuing to the present day, several states prohibit investor-ownership of community hospitals. Conversions to investor-ownership are only one of six types of ownership change, however, with relatively less attention paid to the other types (e.g., for-profit to nonprofit, public to nonprofit). This study has two parts. We first review the literature on the various types of ownership conversion among community hospitals. This review includes the rate at which conversions occur over time, the relative frequency in conversions between specific ownership categories and the observed effects of conversion on hospital operations (e.g., strategic direction and decision-making processes) and performance (e.g., access, quality, and cost). Overall, we find that the impact of ownership conversion on the different measures is mixed, with slightly greater evidence for positive effects on hospital efficiency. As one explanation for these findings, we suggest that the impact of ownership conversion on hospital performance may be mediated by changes in the hospital's strategic content and process. Such a hypothesis has not been proposed or examined in the literature. To address this gap, we next study the role of strategic reorientation following hospital conversion in a field study. We conceptualize ownership conversion within a strategic adaptation framework, and then analyze the changes in strategy content and process across sixteen hospitals that have undergone ownership conversions from nonprofit to for-profit, public to for-profit, public to nonprofit, and for-profit to nonprofit. The field study findings delineate the strategic paths and processes implemented by new owners post-conversion. We find remarkable similarity in the content of strategies undertaken but differences in the process of strategic decision making associated with different types of ownership changes. We also find three main performance effects: hospitals change ownership for financial reasons, experience increases in revenues and capital investment post-conversion, and pursue labor force reductions post-conversion. Membership in a multi-hospital system, however, may be a major determinant of both strategy content and decision-making process that is confounded with ownership change. That is, ownership conversion may mask the impact of system membership on a hospital's strategic actions. These findings may explain the pattern of performance effects observed in the literature on ownership conversions.

Cold calling being one of the most preferred modes of sales strategies in the past, with all digital platforms setting in, is it still the best option a B2B service firm has? To seek answer to this interesting question is the purpose of this paper. The study seeks to understand the contributions of both the sales force and the digital marketing team towards lead conversion. The paper also aims to derive a sense-making model for lead conversion based on a few propositions of the study.

The authors have adopted mixed method approach. The authors have chosen a small enterprise offering B2B services to understand the sales process. The past one-year cold calling data were analyzed. In addition, 15 in-depth interviews were conducted among the managers and the executives of the firm. The study adopts the AIDA model of customer response and the stages of selling process to better map the sales process of the firm. Based on the analysis, a new model is proposed to aid lead conversions.

The findings suggest that cold calling is not an effective mode of sales strategies in this case as the firm experienced a very low conversion rate. However, with the integration of digital marketing efforts with sales process, the sales team could achieve higher conversion rate.

Very few studies in the literature examines the effectiveness of cold calling strategy integrated with digital marketing efforts. This is one of the few studies examining cold calling strategy in B2B service firm in India.

Examines the implications of European Monetary Union (EMU) for property managers of operational and investment property portfolios. In the first section, the background to the introduction of a single currency is reviewed and the proposed timetable and method of introducing the Euro is discussed. The next section analyses the property management areas which may be affected by EMU. It is argued that the costs and benefits of the introduction of the Euro will be unequally distributed. Key factors will include the pattern of property interests and liabilities in potential member countries. A key variable will be the rate at which the existing currency is converted to the Euro. This will be a determinant of the future value of assets and liabilities and will, therefore, impact on corporate costs, profitability and competitiveness. The degree to which a firm benefits from the elimination of exchange rate uncertainty and transaction costs will depend on its financial structure. Firms which meet liabilities in non‐sterling currencies from revenues raised in such currencies will not benefit to a great extent. The paper argues that the legal implications for continuity of contract will be minimal for property managers. It is suggested that the need to amend information systems and records will be the major cost to many organisations.