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Article

Marketing Automation: How to Effectively Lead the Advertising Promotion for Social Reconstruction in Hotels

by
Xue Sun
1,
Yuhao Li
1,
Bo Guo
1 and
Li Gao
2,*
1
School of Business and Management, Shanghai International Studies University, Shanghai 200083, China
2
SILC Business School, Shanghai University, Shanghai 200444, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(5), 4397; https://doi.org/10.3390/su15054397
Submission received: 19 December 2022 / Revised: 13 February 2023 / Accepted: 15 February 2023 / Published: 1 March 2023
(This article belongs to the Special Issue New Perspective of Leadership in Civil Society and Social Reconstruction)
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Abstract

:
With many outdated hotels in urgent need of refurbishment in China, chain hotel groups are under mounting pressure to expand their market share by strengthening advertising performance. This study aims to explore the effects of sender types and anonymous clues on advertising exposure as well as the impacts of the above factors and content narratives on service conversion (e.g., link clicks) for hotel franchise promotion. In addition to increasing exposure action, use of the AA-IDA model can effectively increase the possibility of hotel advertising conversion. Two experiments were employed to examine the impacts of advertising design factors on exposure and conversion rates of hotel franchise promotion. A behavioral experiment and a field experiment were carried out to examine the critical effect of advertising design factors on advertising exposure and conversion. The Wald tests for parameters show that the effect of anonymity on advertising conversion was significant (β = 0.479, p < 0.01). Objective content narratives had a significant positive impact on advertising conversion (β = 0.594, p < 0.01). Furthermore, The ANOVA results show that hoteliers in groups with different design elements applied had significant differences in post-conversion service usage (F = 33.809, p < 0.001). The AA-IDA model provides a new framework for future hotel franchise promotion research. Additionally, the important design factors of promotional ads and their reorganization (e.g., sender types, anonymous clues, and content narratives) had a significant impact on the view action and conversion action.

1. Introduction

At this point of generational change, the global hotel industry needs to transform more than ever for both hotel owners, referred to here as hoteliers, in the “inventory market” of old or even abandoned hotels, and the chain hotel groups [1]. This is particularly so in China, as traditional economy hotels (e.g., Super 8, Home Inn, Jinjiang Inn, etc.), which blossomed under the influence of the reform and opening-up in the early stage of China’s economic development 20 years ago, represent the largest proportion (around 900,000 hotels) in China’s hotel market [2]. Cheap and shabby hotels no longer satisfy travelers in China, so hoteliers need to retrofit these hotels to meet the demands of an increasingly affluent travelling public and address the growing competition of rivals [2]. However, uncertainties presented by events such as the COVID-19 pandemic have made hoteliers increasingly cautious when investing in or renovating hotels. Stable occupancy rates, high RevPAR, the availability of professional services, and the continuous customer source of excellent hotel chains have attracted many hoteliers to franchise chain hotels [3]. For the chain hotel groups, the goal is to expand market share and enhance brand effect by developing the “inventory market” [4,5]. In short, franchising is a win-win strategy for both hoteliers and chain hotel groups [4,6]. Determining how to efficiently promote the matching of information between hoteliers and chain hotel groups has become particularly important. Hotel groups spend considerable time and money on attracting hoteliers through various methods, e.g., website bidding and telemarketing, because the higher the exposure, the more cooperation possibilities emerge. However, publicity involving non-professionalism, shoddy services, or even instances of fraud makes hoteliers more demanding in their screening of hotel advertisements [7,8]. Inappropriate advertising presentation leads to a low input-output ratio [9]. For chain hotel groups, presenting the right message to hoteliers and improving promotional performance by optimizing the design and combination of advertising elements is critical to their expansion.
The conversion rate of promotions is the ultimate test for hotel groups in marketing activities. However, the high input and low output of advertising often leads to marketing failure due to the unequal responses of hoteliers. One reason is that, in the era of information overload, hoteliers are bombarded by advertisements through various channels and forms every day. Unconscious filtering of advertising seems to have become habitual [10]. Consumer perceptions about advertising have been studied using tools from neurophysiology and physiology. The middle temporal gyrus was associated with aversion to advertising, whereas the inferior frontal gyrus was associated with pleasure [11]. Moreover, the use of biomedical technologies (eye-movement) affects consumer attitudes and grabs their attention [12]. Another factor is that, although hoteliers are eager to seek strong chain hotel groups to rely on, the risks of fraud and non-professionalism make them constantly vigilant. Thus, it is particularly important to gain the trust of hoteliers quickly and help them recognize the value of the service, which will improve the conversion rate of franchising promotion.
Several studies have demonstrated the importance of hospitality advertising on hotel group performance at the aggregate level [4,13,14] Although these studies have confirmed the significance of hotel advertising in the hotel chain industry, few articles have discussed how to practically improve the impacts of these ads in the hotel franchise industry. The existing research on the influencing factors of promotion performance is limited to the performance of “push” [15] and pays little attention to ad conversions. The factors affecting the promotion performance of hotel franchising are complex. On the one hand, the degree of trust in promoters affects the outcomes of recommendations [15,16,17]. Compared with unknown promoters, invitations from known or trusted promoters can significantly attract more attention from hoteliers [18]. At the same time, for the hotel franchising sector, conglomeration is also an important basis for hoteliers to judge the degree of service specialization. The brands of hotel groups represent streamlined processing and standardization, and hotel franchising itself reflects the inclinations of hoteliers hoping to make a step up towards the benchmark in the hotel industry [19]. On the other hand, regarding the promotional ad, content presentation affects hoteliers’ judgments of the content itself and their impression of the specialization of the chain hotel group [17].
Benefitting from the convenience and low cost of the Internet, many chain hotel groups have begun to popularize promotion based on mobile technology. Because digital marketing campaigns provoke reactions by using imagery and word connections that trigger emotional responses, they can have an impact on customer behavior [20]. Mobile advertising has evolved into an important tool in the hospitality industry for catching consumer visual attention [21]. It has been effective in visually demonstrating how much attention people pay to hotel marketing [22]. As a result, Ref. [23] strongly recommend that future studies in the hospitality sector employ mobile devices to objectively investigate the associations between consumer behavioral choices. Therefore, against the backdrop of mobile marketing, it is extremely valuable to explore the influencing factors of the promotion performance of hotel franchising from the perspective of promoters and the promotional content itself.
In addition, advertising exposure has proven to be important in increasing the conversion of ads [24]. However, in mobile advertising, users can choose whether to view ads or not autonomously. As a result, mobile advertising exposure should no longer be represented by the transmission rate but should be measured by the acceptance rate [25]. Given these unique properties of mobile advertising, it is particularly important to clarify the connection between exposure and conversion as well as explore how to improve conversion through advertising exposure in the mobile context [26]. There is relatively little research on the factors that influence advertising performance in hotel franchising, with the current literature mainly focusing on the input-output ratio of promotion and marketing [13,27]. Based on the above practice of hotel franchise promotion, the following research questions are proposed:
RQ1: How can we improve the exposure and conversion rates in hotel franchise service promotion through the design and reorganization of advertising elements?
RQ2: How can we enhance the conversion rate by validating advertising exposure in hotel franchise promotion?
To explore these questions, the mobile-based AA-IDA customer journey was established. We first conducted an online experiment to explore the key design elements and their combination effects on the exposure and conversion rates of hotel franchise advertising, respectively. Next, a field experiment was implemented to examine the effects of exposure on advertising conversion and verify the validity of the design elements in real scenarios. This study is innovative in three aspects. First, it proposes a customer journey in the mobile marketing context for the first time, i.e., the AA-IDA model, which provides a new perspective for analyzing customer conversion behavior and emphasizes the importance of exposure in mobile advertising. Second, this study verifies the varying effects of sender types, anonymity, and content narratives on exposure and conversion, respectively. Third, the results also show the essential impact of franchise advertising on hoteliers’ post-conversion behavior. The rest of the paper is organized as follows. Section 2 reviews the relevant literature on the franchise advertising decision process in the hotel industry, and proposes the AA-IDA model along with the hypotheses. Section 3 expounds on the behavioral experiment to examine the effectiveness of advertising design elements. Section 4 elaborates on the field experiment to validate the enhancement of mobile advertising conversion by verifying exposure. Section 5 is the general discussion, demonstrating the AA-IDA model’s theoretical contributions as well as managerial applications.

2. Literature and Theoretical Development

2.1. Customer Decision Process in Response to Hotel Franchise Promotion

Most franchise consumers’ conversion decisions are not disconnected actions, but a complex process, which can be considered as a hierarchical process aligning with the guidance of advertising that includes four stages (i.e., awareness, interest, desire, and action). Thus, we introduce the AIDA customer journey model, whose effectiveness in understanding the decision process in customer conversion is supported by related research in the hotel field [28,29]. The Awareness-Interest-Desire-Action (AIDA) customer journey explains the customer conversion process by providing the perspective that a consumer first generates awareness about products, then develops interest and conducts research on them, narrows down options, and finally makes decisions [30]. Research related to the AIDA journey can be divided into two categories. One is the study of the process of customer purchase behavior itself from the customers’ perspective. The main point of view is that customer purchases go through four stages, described in the literature in the context of food delivery apps [16], the travel of the Pop Culture Fan [15], and in other contexts. The other research stream is about how to affect the various components of the AIDA process from the perspective of marketers, i.e., the impact of advertising on AIDA, in contexts such as the hospitality sharing economy platform [19], the choice of tourism product [31], methods of using blogs [32], social media [27], manipulation of advertising formats [17], website aesthetics [19], and information presentation modes [31], all of which in turn promote sales.
Nevertheless, many studies have confirmed that the contrast between traditional and mobile marketing is stark in several ways, such as the user’s more flexible autonomy on the move [33]. Although AIDA can provide a hierarchical framework for various forms of marketing communication, there is little research on the consumer journey based on mobile marketing and reflecting the unique differences between mobile marketing and traditional marketing.

2.2. AA-IDA Model

Based on the AIDA customer journey, by integrating with the characteristics of mobile advertising, we propose a mobile-based AA-IDA, i.e., the Attention-Action-Interest-Desire-Action model, to explain the customer decision process in hotel franchise promotion; see Figure 1.
Significant changes in the nature of persuasion are a function of the likelihood that receivers will engage in elaboration of information relevant to the persuasive problem, according to the elaboration likelihood model (ELM) of persuasion [34]. There are two paths of influence that might lead to a change in attitude: the periphery and the central channel. People who follow the central path of persuasion will critically study the information, but those who follow the peripheral path will require less cognitive effort to establish their attitudes [35]. The periphery and center courses differ in at least three ways [36]. The first distinction is the type of information processed by each of these courses. The central channel processes data pertinent to messages, whereas the peripheral course processes stimuli. Second, processing material in the core course necessitates more cognitive effort than processing information in the peripheral course. Third, a central course necessitates careful consideration of the argument presented, evaluation of the quality of the arguments, integration of the numerous and sometimes contradictory arguments, and subsequent development of a general conclusion, whereas a peripheral course necessitates only the association of the subject with favorable or unfavorable cues [37].
In contrast with the AIDA model, an “Action” is added after “Attention”. The additional “Action” represents advertising exposure in the mobile context, such as users’ advertising view actions. Hoteliers’ attention is evoked through the notification of the mobile advertisement; after the hoteliers realize the advertisement messages, they autonomously decide whether to accept more content of the promotion through their first action (i.e., after advertising exposure, by clicking on ads and viewing details) or not based on brief information in advertising pop-ups. If they choose to view the ads, then these specific products or service content may arouse hoteliers’ interest; next, the pictures and videos in the ads further develop hoteliers’ desire, and finally lead to hoteliers’ conversion actions (e.g., purchasing or accepting services and products). The added action is the typical characteristic of mobile marketing, which is different from that of traditional marketing, meaning that there are more user controls in the mobile context [38,39]. Depending on their inclination to obtain further advertising information about products or services, hoteliers may autonomously choose to continue the follow-up journey. If the hoteliers select “do” in the first action (e.g., clicking on ads to view details), they will proceed to the following stages of interest and desire generated through social clues [3], statistics, and other elements contained in advertising [27], and eventually make conversion decisions. Yet, if the hoteliers choose “undo” (e.g., not clicking on ads), they will immediately end the journey and not view the further stages of promotional content.

2.3. Hypotheses

In the AA-IDA customer journey, anonymity clues and sender types affect both the first action (i.e., advertising exposure) and the second action (i.e., advertising conversion). The outcome variables of hotel advertising research in previous studies were mostly attitude and behavioral intention [40], and there was no further distinction between exposure and conversion in attitude and behavioral intention. Based on the AA-IDA customer journey, this study implies that the first action (e.g., view) is mainly affected by attention (A). Anonymity clues and sender types mainly affect hoteliers’ attitudes and behavioral intentions (i.e., exposure) towards mobile ad viewing by attracting attention. The conversion action is mainly affected by Interest (I) and Desire (D). Unlike the view action, in the conversion action, the anonymity clues and sender types mainly affect hoteliers’ attitudes and behavioral intentions (i.e., conversion) towards mobile ad content by arousing hoteliers’ interest and desire.
Therefore, we propose the following hypotheses:
Hypothesis 1.
Awareness can positively influence exposure behaviors and conversion behaviors, whereas interest and desire positively influence conversion behaviors. The details are as follows.
The sender type is an important feature of mobile ads that affects attention towards mobile messages. The sender type is relevant to psychological distance [41,42], which affects attitudes towards the ads [43]. The mobile messages sent by a personal sender are usually perceived to demonstrate shorter psychological distances than those from a company sender. The shorter the psychological distance is from senders to recipients, the more attention is paid to the messages by the recipients. It is also believed that most of the messages from a company sender are sent in groups. In contrast, the messages from a personal sender imply more personalization and can receive more attention and promote the decision to view the mobile ad [40,44,45]. Hence, the mobile ads of personal senders are more likely to get exposure. On the other hand, mobile ads (i.e., SMS ads) sent by a company sender have the abbreviation of the company showing brand information. Research has found that, compared with excluding brand information, adding company brands to mobile messages can increase the customer’s incentive [45,46]. Furthermore, the incentive can positively influence customer conversion (e.g., link clicks) [47,48,49,50]. Meanwhile, studies have found that branded advertisements can gain more trust from customers and then facilitate customer conversion [46,51]. Thus, the mobile ads of company senders are more likely to achieve conversions.
Anonymity clues can also affect communication effectiveness via mobile messages [50]. Mobile messages with non-anonymous clues are more likely to gain credence from the recipient than anonymous messages when making view decisions. Hoteliers will allocate more attention to the messages they trust, meaning that non-anonymous mobile messages are more likely to be viewed. Also, anonymity clues are often used in research on marketing ad conversion, especially in mobile marketing, because there are many fraudulent activities, such as scams and virus links, on the Internet. Research has found that trustworthiness attributes can play a positive role in promoting the generation of the “desire” of customers [52]. Thus, it is inferred that non-anonymous mobile ads may gain more conversions. Additionally, adding the sender’s name in mobile ads can prompt recipients to associate the ad with their past encounters with this person and treat non-anonymous clues as person-related information, which drives hoteliers to generate greater interest. In this regard, anonymity clues can also affect the mobile ad conversion decision. Therefore, the following hypothesis is proposed:
Hypothesis 2.
Personal senders and non-anonymity in the attention stage positively affect the possibility of advertising exposure, whereas company senders and non-anonymity in the interest and desire stage have stronger positive impacts on the possibility of advertising conversion.
We consider both informativity and rational appeal regarding the impact of content narratives on mobile ad conversion decisions. The informativeness of mobile ads about things such as the number of existing users, service rating, etc., can significantly affect the conversion of customers [53,54,55,56]. The use of objective expressions enriches the informativeness of mobile ads. Benefitting from the characteristics of digital expression, readers are able to capture valuable information in mobile ads quickly. Also, they are more likely to generate hoteliers’ interest. This, in turn, increases the possibility of customer conversion. In the context of service promotion in the hotel industry, objective expressions can also reflect the professionalism of the chain hotel groups, thereby enhancing the desire of hoteliers to accept the recommended services [57]. Meanwhile, Ref. [58] have found that users who read mobile ads thoroughly and thoughtfully seem to be more willing to get more information. Therefore, the following hypothesis is proposed:
Hypothesis 3.
Objective content narratives in the interest and desire stage positively affect the possibility of advertising conversion.
Advertising exposure refers to the number of users an ad reaches in a given period. Numerous studies have shown the relationship between exposure and conversion. This is because, with the rise of exposure, awareness is established among more potential users, who may consider the focal service or product to be an alternative option, and thus the conversion rate will be improved. Unlike traditional advertising, in hotel franchise promotion, hoteliers independently choose whether to view the ads or not, rather than passively accepting them. More ad views mean higher exposure, and high exposure leads to high conversion. These pieces of evidence provide support for the likelihood of enhancing conversion rates by increasing users’ view actions. Therefore, based on the mobile advertising context, it is reasonable to conclude that an increase in advertising exposure behaviors (e.g., the advertising viewing action) in the AIDA framework will improve the performance of advertising conversion, and help explain the advertising decision process more accurately. Therefore, the following hypothesis is proposed:
Hypothesis 4.
The addition of exposure action in the AA-IDA model can effectively increase the possibility of hotel advertising conversion.
A behavioral experiment and a field experiment were employed to examine the effects of design elements and exposure on mobile advertising conversion in order to test the hypotheses. Study 1 used a behavioral experiment to explore the impacts of sender types, anonymous clues, and content narratives on the exposure and conversion rates of hotel franchise promotions to measure Hypothesis 1. Study 2 used a field experiment to verify the effectiveness of the AA-IDA framework on hotel franchise promotion performance in order to measure Hypothesis 4.

3. Methods and Procedures

3.1. Study 1: Behavioral Experiment

This study aims to explore the effects of sender types and anonymous clues on ad exposure (e.g., ad views) and the impacts of the above factors, as well as content narratives, on service conversion (e.g., link clicks) for hotel franchise promotion.

3.1.1. Experiment Design

A 2 (sender types: company sender vs. personal sender) by 2 (anonymity clues: anonymity vs. non-anonymity) by 2 (content narratives: subject vs. objective) mixed-design experiment was conducted to test the proposed hypotheses. Sender types and anonymity clues were within-subject designs, whereas the content narrative was a between-subject design. We employed SMS, a widely used mobile marketing method, to verify the effectiveness of the AA-IDA model. SMS enables marketers to target consumers at specific times and locations [41,59]. Although users in different countries have different attitudes towards SMS acceptance [59], studies indicate that it is more suitable in a high-context cultural environment (e.g., China) in achieving a favorable commercial performance [60] than other mobile approaches (e.g., email). SMS is still the main advertising method in China’s hotel industry and has the advantage of collecting data rapidly. Therefore, we tested the performance of mobile ads in franchise promotion using SMS.
We manipulated these 3 variables as follows. For sender types, we used long numbers with 20 digits beginning with 1069 (a typical Chinese company number) and including company abbreviations in previews for the company sender group. The personal sender group was shown an 11-digit personal phone number (a typical Chinese personal number) (see Figure A1a,b). For anonymity clues, non-anonymous SMS messages revealed the sender’s name in the first sentence, whereas anonymous SMSs will not (see Figure A2a,b). For content narratives, we manipulated subject content narratives by using qualitative descriptions (e.g., “Thanks for following our company. The hotel industry research report (2021) has been released, which is well received by many people in the hotel industry. To obtain the industry information, click on https://zndls.com/DTgIvUS6 to view.”) (This link is accessed on 1 December 2021) to recommend the services. Additionally, the objective content narrative employed quantitative descriptions (e.g., “Thanks for following our company. The hotel industry research report (2021) has been released, the industry experience of more than 100 specialists has been taught. The positive rating from industry insiders exceeds 80%. Click on https://zndls.com/DTgIvUS6 to view.”) (The link is accessed on 1 December 2021). The descriptions of contributors and ratings in the content imply social [3,61] and statistical [27] clues, respectively, to raise hoteliers’ interest and desire. For the details of the 8 groups of ads, see Table A1.
We conducted a pretest on these materials to examine the validity of these manipulations. We showed participants a screenshot of an SMS, and then asked them about their perception of the SMS sender, using a 5-point scale (1 means “It must be a company”; 5 means “It must be a person”). Similarly, we tested anonymity materials. The text preview was displayed to the participants. Then the agreement with the anonymity of the text message was evaluated using a 5-point scale (1 represents “strongly agree”, 5 represents “strongly disagree”). Forty-four people recruited from wjx.cn participated in the pretest. The results of the t-test show that our manipulation of sender types and anonymity was significant. Participants rated their perception of personal senders more highly than that of company senders (Meancompany = 2.30, Meanperson = 3.48, p < 0.001). Similarly, participants’ anonymity perception of anonymous SMS messages was significantly higher than that of non-anonymous ones (Meananonymity = 2.70, Meannon-anonymity = 3.05, p < 0.001).

3.1.2. Procedure

Participants were required to read a piece of material. To put them into the role of hotelier, we asked participants to imagine that they are hoteliers and are now considering renovating their hotels. The material was followed by the question “What is your identity?” to test the validity of the prompt material. Only the participants who answered “I am a hotelier” could enter the following process.
The procedures were divided into two stages. In the first stage, participants saw an ad notification with the sender number and a text preview (see Figure A3a). Then they were asked, “Will you click on this SMS to view the content?” If the participant chose not to view the message (YAE = 0), they proceeded directly to the next SMS. Otherwise (YAE = 1), the participant passed the advertising exposure stage and entered the next stage. In the second stage, the participant saw the whole content of the focal ad (see Figure A3b). In the text, a hotel-related service link was embedded. After reading the content, the participant was asked, “Will you click on the link?” If the participant chose to click on the link (YAC = 1), the participant was considered to have accepted the recommendation in the SMS ad, and therefore had passed the advertising conversion stage. The process of the experiment is shown in Figure 2.
Each participant proceeded through four SMS messages (2 Sender types × 2 Anonymity clues). We employed the between-subject Latin square design to avoid the effect caused by the presentation order of the SMSs in the advertising exposure stage. According to our setting, only those who chose to view the SMSs in the advertising exposure stage (YAE = 1) entered the next stage. This limitation is in line with the reality that only when people come to view the content of a pop-up ad will they have a chance to be persuaded. Participants were required to complete a demographic questionnaire after completing all the trials.

3.1.3. Participants

In the current study, the sample size was calculated by G power analysis. The estimated sample size was 345; further, by excluding the samples who failed to meet the experiment requirements (e.g., missing trials) or did not answer “I am a hotelier.”, the samples used for the formal analysis were 255 people. The participants, who were recruited from wjx.cn, were concentrated in the 30–40-year age group, and females made up 46.70% of all participants. Of them, 79.2% reported their monthly household income to be above RMB 15,000. See Table A2 for details.

3.2. Study 2: Field Experiment

This study aims to examine the effect of exposure on advertising conversion and verify the validity of the AA-IDA model in real scenes of the hotel franchise industry.

3.2.1. Experiment Design

This field experiment followed a 2 (sender types: company sender vs. personal sender) by 2 (anonymity clues: anonymity vs. non-anonymity) by 2 (content narrative: subjective vs. objective) between-subject design. The three variables, namely sender types, anonymity clues, and content narrative, were manipulated in a manner consistent with Study 1. At the suggestion of the cooperating company, we pushed a hotel industry report with franchise ads embedded in the text instead of directly publishing the franchise advertising in the promotion messages. We inserted the link for the service recommended by the company to hoteliers in the SMS ads. The link contained the 2021 China Hotel Industry Research Report, to which the franchise promotion ad was attached, and it was shown at the bottom of each page that the cooperating company promoted the report. We used Yunzhan.com (www.yunzhan365.com) (The link is accessed on 1 December 2021), a platform specializing in the production, publication, and statistics of electronic magazines, to generate eight sets of links, and the content (i.e., the report and franchise promotion ad) in the eight sets of links was entirely consistent. Finally, we analyzed the field experiment results by collecting data about the browsing history of the eight links recorded on Yunzhan.com. We sent information to the company sender group through the company SMS service provided by Tencent Cloud. To reduce the word count of the SMS ads, we used the short link function in Tencent Cloud to shorten the length of the eight links provided by Yunzhan.com.

3.2.2. Procedure

The SMS ads of the company sender group were sent through Tencent Cloud, and the SMS ads of the personal sender group were sent through personal mobile phones. Considering that the time to receive messages may affect users’ view behavior [62,63], we sent SMS ad messages between 18:30 and 20:30 every day. We sent all messages within 10 days. The links were left open for a month because of the possibility of users’ delayed investigations. Hoteliers who received the message could click on the message to view the details of the SMS ads and click on the link to view the pushed service. The hoteliers’ link click data was recorded by Yunzhan.com and collected for analysis.

3.2.3. Participants

We cooperated with a hotel management company in China, providing hotel business solutions services, such as hotel franchise consulting. We had access to a unique data set from the company’s CRM system, collected through website bidding, etc. We sent the SMS ads to 10,728 hoteliers, who were divided into eight groups with 1341 people in each group. The cluster sampling technique was used. Their phone numbers were stochastically assigned with eight conditions.

4. Results

4.1. Results of Study 1: Behavioral Experiment

4.1.1. Advertising Exposure

We used logistic regression [64,65] to examine the effects of sender types and anonymity on advertising exposure. The specifications were as follows:
P(YAE = 1) =
Ui = a0 + a1 ∗ Senderi + a2 ∗ Anonymityi + a3 ∗ Senderi ∗ Anonymityi +
ΔControlVars + εi
where i indicates the recipient of the mobile ad; YAE = 1 means that the participant accepts the information, i.e., views the text message; a0 represents the intercept; Senderi and Anonymityi are two dummies; Senderi = 1 means mobile ads sent by company senders; Anonymityi = 1 means non-anonymous ads; a1, a2, and a3 represent the slope coefficients of sender type and anonymity, and the interaction between them, respectively; ControlVars are control variables, including age and gender; and εi is the error term.
The evaluation of advertising exposure is shown in Table 1. Overall, the statistical fit of the model was satisfactory, with the HL test indicating that the model fit the data (p > 0.05) well. The Wald tests for parameters indicate that the sender type was negatively significant (β = −0.31, p < 0.05) in explaining the likelihood of viewing messages, indicating that the SMS ads sent by personal senders were more likely to be viewed, and the anonymity clue was insignificant (β = −0.095, p > 0.05), indicating that displaying names does not promote message-viewing behavior. The interaction of these two factors is significant (β = −0.357, p < 0.01). In terms of the odds ratio, the odds of viewing messages were 0.734 times less if the company sender sent the SMS ads. According to the advertising exposure rate, non-anonymous ads sent by personal senders had the highest exposure rate of 69%, followed by anonymous ads sent by companies, anonymous ads sent by individuals, and non-anonymous company ads, with the lowest exposure rate of 58.4%. Furthermore, the value of the scales’ validity shows that the variable loading factor (VIF) was applied to all study variables, and it was found that values ranged from 1 to 1.5. It means that there is no serious multicollinearity problem in the data.

4.1.2. Advertising Conversion

We employed logistic regression to test the effect of sender type, anonymity, and content narrative on advertising conversion. Because advertising conversion occurs only when the advertising exposure stage has been passed, i.e., YAC = 1 is under the condition of YAE = 1, we used the following specifications to evaluate the advertising conversion:
P (YAC = 1|YAE = 1) =
Vi = b0 + b1 ∗ Senderi + b2 ∗ Anonymityi + b3 ∗ Contenti + b4 ∗ Senderi ∗ Anonymityi ∗ Contenti + εi
where I indicates the recipient of the mobile ad; YAC = 1 means that the participant accepts the recommendation, i.e., clicks on the link; b0 represents the intercept; Senderi, Anonymityi, and Contenti are dummies; Senderi = 1 means mobile ads sent by company sender; Anonymityi = 1 means non-anonymous ads; Contenti = 1 means objective content; b1, b2, b3, and b4 represent the slope coefficients of sender type, anonymity, content narrative and the interaction between them, respectively; εi is the error term.
The evaluation of advertising conversion is shown in Table 2. The statistical fit of the model was satisfactory, with the HL test indicating that the model fit the data (p > 0.05) well. The Wald tests for parameters show that the effect of anonymity was significant (β = 0.479, p < 0.01) on advertising conversion, but was insignificant on advertising exposure. This indicates that the services (links) recommended by non-anonymous SMSs were more likely to be accepted, but that non-anonymous SMSs had an invalid effect on the viewing of SMSs. The interesting finding is that, compared with the negative effect on advertising exposure, the company sender had a significantly positive impact on advertising conversion (β = 0.375, p < 0.05), indicating that, although an SMS from a personal sender was more likely to be viewed, services (links) recommended by company sender were more likely to be accepted. Regarding content narratives, objective content had a significant positive impact on advertising conversion (β = 0.594, p < 0.01), indicating that objective expressions were more likely to be accepted in service recommendations. The three-factor interaction was also significant (β = −0.778, p < 0.01). In addition, gender and income were significant in both models. In terms of the odds ratio, the odds of clicking links were 1.615 times greater if the SMS ads were non-anonymous, 1.615 times greater if the company sender sent the SMS ads, and 1.811 times greater if the content was organized objectively. Furthermore, as shown in Table 2, the demographic variables gender and monthly income had a significant association with advertising conversion, whereas participants’ age had a non-significant association with advertising conversion.
This study examined the effect of sender types, anonymous clues, content narratives, and their interactions on the exposure and conversion rates of hotel franchise promotion, wherein the subjects imagined that they were hoteliers, with lacking ecological validity [41,66]. Furthermore, the relationship between exposure and conversion in the AA-IDA journey was not clear. To verify the validity of the above model in practice and clarify the effect of exposure, a field experiment was conducted.

4.2. Results of Study 2: Field Experiment

We employed logistic regression to test the effects of sender type, anonymity, and content narrative on advertising conversion.
P (YAC = 1) =
Qi = c0 + c1 ∗ Senderi + c2 ∗ Anonymityi + c3 ∗ Contenti + εi
where i indicates hoteliers; YAC = 1 means that the hoteliers accept the recommendation, i.e., click on the link; c0 represents the intercept; Senderi, Anonymityi and Contenti are dummies; Senderi = 1 means mobile ads sent by company sender; Anonymityi = 1 means non-anonymous ads; Contenti = 1 means objective content; c1, c2 and c3 represent the slope coefficients of sender type, anonymity, and content narratives, respectively; and εi is the error term.
The result is shown in Table 3. The statistical fit of the model was satisfactory, with the HL test indicating that the model fit the data (p > 0.05) well. The Wald tests for parameters show that the effect of sender type was significant (β = 0.833, p < 0.001), indicating that the services (links) of SMS ads recommended by a company sender were more likely to be accepted compared with those of a personal sender in general. The effect of anonymity clues was insignificant (β = 0.833, p > 0.065). Regarding content narratives, objective content had a significant positive impact on advertising conversion (β = 0.49, p < 0.01), indicating that objective expressions were more likely to be accepted. We also examined the interaction, and the result shows no statistical significance (β = −0.145, p > 0.625). Regarding the odds ratio, the odds of link clicks were 2.299 times greater if the company sender sent the SMS ads, and 1.632 times greater if the content was organized objectively in general.
The rate of each group accepting the SMS ads’ recommended service is shown in Figure 3, to give a better intuition for the performance distinctions. The group with the highest acceptance rate was the Company sender-Anonymity-Objective group, with an acceptance rate of 0.027, followed by the Company sender-Non-anonymity-Subjective group, with an acceptance rate of 0.013, and the group with the lowest acceptance rate was the Personal sender-Non-anonymity-Subjective group, with an acceptance rate of only 0.004; this figure also represents the previous average performance of our cooperating company.
To further verify Hypothesis 4, we examined the effect of exposure on advertising conversion in the AA-IDA model. According to the results of advertising exposure in Study 1, non-anonymous ads sent by personal senders and anonymous ads sent by company senders were defined as the high exposure group, and the non-anonymous ads sent by company senders and anonymous ads sent by personal senders were defined as the low exposure group. Logistic regression was employed to compare the conversion rates of the two groups under the conditions of objective and subjective content narratives, respectively. It was found that under both objective (β = 0.723, p < 0.01) and subjective (β = 0.600, p < 0.05) conditions, the high exposure group had a significantly higher conversion probability than the low exposure group. This result verifies Hypothesis 4, indicating that in hotel franchise promotion, it is necessary to improve conversion by validating advertising exposure in the customer decision process.
To obtain more results, we also analyzed the hoteliers’ reading time of the linked report; see Figure 4. The ANOVA results show that hoteliers in groups with different design elements had significant differences in post-conversion service usage (F = 33.809, p < 0.001). Among the eight conditions, the Company sender-Anonymity-Objective group had the longest reading time (Mean = 17.61 s), followed by the Company sender-Non-anonymity-Subjective group (Mean = 12.67 s); the one with the shortest reading time was the Personal sender-Anonymity-Subjective group (Mean = 1.86 s).
In terms of conversion ratio and reading time, objective ads sent anonymously by the company sender had the highest conversion ratio and the longest reading time compared with the other seven groups. Regarding a company sender’s messages, anonymous messages were more likely to be converted than non-anonymous messages at some point in the process. One possible reason is that, once a person’s name appeared, the message content was likely to be regarded by recipients as the views of someone in the company instead of the official opinion of the firm. This, in turn, reduced the perceived credibility and professionalism of the content of mobile ads. We further examine the different reading time periods associated with each factor. The reports recommended by company senders received longer reading duration than those from personal senders (Meancompany = 9.7, Meanpersonal = 6.2, p < 0.01). The reports recommended anonymously received longer reading durations than those recommended non-anonymously (Meananonymity = 8.7, Meannon-anonymity = 7.2, p < 0.05). The reports recommended objectively received longer reading durations than those recommended subjectively (Meanobjective = 10.8, Meansubjective = 5.2, p < 0.001).

5. General Discussion

This study used digital technologies to evaluate the impact of exposure on advertising conversion and confirm the accuracy of the AA-IDA model in actual hotel franchise industry circumstances. The study’s conclusions can benefit researchers in the hospitality industry and hotel advertising. According to [67], decision-makers should mix customer viewpoints to boost the effectiveness of mobile advertising. This study backs up this idea through the evaluation of collected objective visual data from users with mobile AA-IDA technology (i.e., opinions of customers). The results reveal that non-anonymous advertisements significantly enhanced customer conversion and behavioral intention after viewing, but anonymous advertisements had higher fixation counts. This research implies that visual attention influences consumer decision-making.
The non-anonymous ads sent by personal senders and the anonymous ads sent by companies were defined as the high exposure group and the non-anonymous ads sent by company senders and the anonymous ads sent by personal senders were defined as the low exposure group, based on the results of an advertising exposure study [34]. It was discovered that the high exposure group had a much higher conversion probability than the low exposure group under both objective and subjective circumstances. In order to increase conversion, hotel franchise promotion must demonstrate that advertising exposure influences consumer choice [20]. The Personal sender-Anonymity-Subjective group had the quickest reading time among the eight circumstances, followed by the Company sender-Anonymity-Objective group and the Company sender-Non-anonymity-Subjective group.

5.1. Theoretical Contributions

Previous studies on hotel franchise promotion were mainly focused on two aspects, the input-output ratio of advertising and the push effect of service promotion. However, little research has been undertaken to understand the process for users to accept hotel franchise ads (i.e., exposure, conversion, and post-conversion), as well as the factors impacting this process. The theoretical significance of this study is manifested in the following aspects.
This research is the first to propose a journey based on mobile marketing to clarify the process from awareness to conversion by adding an additional “Action” to the AIDA customer journey; this is, namely, the AA-IDA model, which addresses deficiencies in the current AIDA customer journey, such as neglect of the technical features of mobile compared to traditional marketing. The AA-IDA model addresses this, and improves on the AIDA’s applicability to the franchise context, thereby improving the conversion rate of hotel franchise promotion. The AA-IDA model provides a new framework for future hotel franchise promotion research. Additionally, the important design factors of promotional ads and their reorganization (e.g., sender types, anonymous clues, and content narratives) were shown to impact both view action and conversion action significantly. These findings expand our understanding of the scope of factors affecting hotel franchise promotion. Finally, it was found in the field experiment that the design factors of promotional ads also have impacts on post-conversion. This finding provides clues for the correlation between the ads’ efficacy during pre-conversion as well as their performance post-conversion (e.g., word-of-mouth, upselling, etc.).

5.2. Managerial Applications

The “hotel inventory market” is deemed the domain where hotel groups’ success will be decided in the next 20 years. Hotel groups that can grasp the opportunity of the current generational shift will take the lead in the new Chinese hotel market. Service promotion is an important approach that can be used to extend the “inventory market”. Hence, the question of how to customize an effective promotional strategy to improve the efficiency of service promotion is crucial. From the perspective of the service promotion of chain hotel groups, this paper puts forward some strategic suggestions to help chain hotel groups understand the behavior of hoteliers towards promotional ads and to promote the exposure to and conversion of service promotions.
In the context of hotel franchise mobile marketing, exposure is the necessary condition for conversion. If hotel groups expect to increase the conversion rate, they should ensure sufficient exposure first. Furthermore, various combinations of design factors should correspond to varying promotional purposes. For “Push” purposes, such as brand awareness creation, awareness promotion, service change instructions, etc., personal phone numbers should be used to get more exposure (e.g., views) rather than employing company numbers. For “Pull” purposes, such as advertisements embedded with content (e.g., links) that need to be reacted to, such as hotel service promotions, product details instructions, industry report releases, etc., the reverse is true. This insight can help generate a higher conversion rate through publications by a company sender. In addition, promotional messages released by company senders will gain more acceptance if they are sent anonymously, probably because this combination gives hoteliers more official and professional impressions. Additionally, objective content narratives should be used more to increase the conversion rate. Lastly, attention should be paid to the impact of design factors on post-conversion. Service promotions with the characteristics of objectivity (e.g., objective content narratives) and officiality (e.g., company senders and anonymity) will attract more attention from hoteliers after conversion.

5.3. Conclusions

This study explored the factors which impacted the exposure and conversion of mobile advertising in the context of franchise promotion in the hotel industry. The mobile-based AA-IDA was developed based on the AIDA customer journey to explain the customer decision process in response to hotel franchise promotion. A behavioral experiment and a field experiment were implemented to verify the effectiveness of the AA-IDA customer journey, and the findings are presented. Non-anonymous ads significantly increased the conversion rate compared to anonymous ads, regardless of sender type. Further, personal senders and company senders exhibited diametrically opposite effects on promotional exposure and conversion. Additionally, the interaction between company senders and non-anonymous clues showed a significantly greater effect in both stages than other combinations. Although the effects were opposite, i.e., the effect of the interaction between the two was negative in advertising exposure, it was positive in advertising conversion. We also found that content narratives significantly affected advertising conversion under any condition. Moreover, compared with the traditional AIDA, the AA-IDA increased the likelihood of customer conversion by improving advertising exposure. Finally, it was found in the field experiment that these factors also had crucial impacts on the post-conversion experience.

5.4. Limitations and Future Research

Although the conclusions of this study contribute to theories and practices, the study still has some shortcomings. In the behavioral experiment, the participants were not entirely hotel practitioners. In the future, we may recruit real hoteliers to complete the behavioral experiment to verify the robustness of the respective effects of design factors. Due to the limitation of SMS functionality, we could not collect information about individual demographics (such as gender, age, income, etc.) from the recipients. In the future, we will try to use more mobile marketing methods (e.g., apps) to enrich our conclusions. We suggest that in the future, with this model, consumer neuroimaging techniques and neuro-marketing research should be applied to research. This study is an experiential study and urges future researchers to engage in additional qualitative analysis. Further, quantitative analysis also can be carried out as well. Future studies can also carry out a similar study for comparison purposes, or a contextual shift can be incorporated. In the context of China, a comparison of hotelier and leisure service users can be done in the future as well.

Author Contributions

Conceptualization, X.S. and L.G.; methodology, Y.L.; software, B.G.; formal analysis, X.S.; writing—original draft preparation, X.S. and Y.L.; writing—review and editing, X.S. and B.G.; supervision, L.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval was not required for this study. The participants provided their written informed consent to participate in this study. Participants were also advised that their participation was purely voluntary, and they could withdraw anytime if they wished to do so. Since no personal identifiers have been kept or recorded in the database, there are few privacy concerns, and the conclusions of this article will be made available by the authors without undue reservation.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy restrictions.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

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Figure A1. (a) Company sender; (b) Personal sender.
Figure A1. (a) Company sender; (b) Personal sender.
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Figure A2. (a) Non-anonymity (personal sender); (b) Anonymity (personal sender).
Figure A2. (a) Non-anonymity (personal sender); (b) Anonymity (personal sender).
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Table
Table A1. The Content of SMS Ads.
Table A1. The Content of SMS Ads.
Sender TypesAnonymity CluesContent NarrativesIn Chinese (Origin)In English (Translated)
Company SenderAnonymitySubjective narratives【人人宜咨询】感谢关注我司。《2021酒店研究报告》了解行业资讯，受到众多好评 https://zndls.com/DTgIvUS6 查看。退T【Renry Consulting】Thanks for following our company. The hotel industry research report (2021) has been released, which is well received by many people in the hotel industry. To obtain the industry information, click on https://zndls.com/DTgIvUS6 to view. T to unsubscribe
Objective narratives【人人宜咨询】感谢关注我司。《2021酒店研究报告》100余位大咖分享，80%好评 https://zndls.com/DTgIvUS6 查看。退T【Renry Consulting】Thanks for following our company. The hotel industry research report (2021) has been released, the industry experience of more than 100 specialists has been taught. The positive rating from industry insiders exceeds 80%. Click on https://zndls.com/DTgIvUS6 to view. T to unsubscribe
Non-anonymitySubjective narratives【人人宜咨询】我是刘伟，感谢关注我司。《2021酒店研究报告》了解行业资讯，受到众多好评 https://zndls.com/DTgIvUS6 查看。退T【Renry Consulting】I’ m Wei Liu. Thanks for following our company. The hotel industry research report (2021) has been released, which is well received by many people in the hotel industry. To obtain the industry information, click on https://zndls.com/DTgIvUS6 to view. T to unsubscribe
Objective narratives【人人宜咨询】我是刘伟，感谢关注我司。《2021酒店研究报告》100余位大咖分享，80%好评 https://zndls.com/DTgIvUS6 查看。退T【Renry Consulting】I’ m Wei Liu. Thanks for following our company. The hotel industry research report (2021) has been released, the industry experience of more than 100 specialists has been taught. The positive rating from industry insiders exceeds 80%. Click on https://zndls.com/DTgIvUS6 to view. T to unsubscribe
Person SenderAnonymitySubjective narratives感谢关注我司。《2021酒店研究报告》了解行业资讯，受到众多好评 https://zndls.com/DTgIvUS6 查看。Thanks for following our company. The hotel industry research report (2021) has been released, which is well received by many people in the hotel industry. To obtain the industry information, click on https://zndls.com/DTgIvUS6 to view.
Objective narratives感谢关注我司。《2021酒店研究报告》100余位大咖分享，80%好评 https://zndls.com/DTgIvUS6 查看。Thanks for following our company. The hotel industry research report (2021) has been released, the industry experience of more than 100 specialists has been taught. The positive rating from industry insiders exceeds 80%. Click on https://zndls.com/DTgIvUS6 to view.
Non-anonymitySubjective narratives我是刘伟，感谢关注我司。《2021酒店研究报告》了解行业资讯，受到众多好评 https://zndls.com/DTgIvUS6 查看。I’ m Wei Liu. Thanks for following our company. The hotel industry research report (2021) has been released, which is well received by many people in the hotel industry. To obtain the industry information, click on https://zndls.com/DTgIvUS6 to view.
Objective narratives我是刘伟，感谢关注我司。《2021酒店研究报告》100余位大咖分享，80%好评 https://zndls.com/DTgIvUS6 查看。I’ m Wei Liu. Thanks for following our company. The hotel industry research report (2021) has been released, the industry experience of more than 100 specialists has been taught. The positive rating from industry insiders exceeds 80%. Click on https://zndls.com/DTgIvUS6 to view.
Note: The links included are for testing purposes. It is required to specify how to unsubscribe from this ad at the end of text messages sent by a company, e.g., “T to unsubscribe”.
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Figure A3. (a) Ad notification shown in the advertising exposure stage (a non-anonymity ad sent by a company sender); (b) Ad content shown in the advertising conversion stage (a non-anonymity ad sent subjectively by a company sender).
Figure A3. (a) Ad notification shown in the advertising exposure stage (a non-anonymity ad sent by a company sender); (b) Ad content shown in the advertising conversion stage (a non-anonymity ad sent subjectively by a company sender).
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Table
Table A2. Demographic profiles of the respondents in Study 1.
Table A2. Demographic profiles of the respondents in Study 1.
VariablesLevelsFrequencyPercentage (%)
GenderMale13653.30%
Female11946.70%
AgeBelow 297730.20%
30–4016665.10%
Above 41124.70%
OccupationState enterprises and institutions3413.30%
Private/Foreign Enterprises4919.20%
Civil servants145.50%
Business owners7127.80%
Others8734.20%
Monthly Income
(RMB)		Less than 15,0005320.80%
15,001–50,00019375.70%
More than 50,00093.50%

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Figure 1. The AA-IDA model.
Figure 1. The AA-IDA model.
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Figure 2. The experiment process.
Figure 2. The experiment process.
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Figure 3. Conversion ratio.
Figure 3. Conversion ratio.
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Figure 4. Average reading duration.
Figure 4. Average reading duration.
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Table
Table 1. Model estimates for advertising exposure.
Table 1. Model estimates for advertising exposure.
Explanatory VariablesDependent Variables—Message AcceptanceVIF
Model 1Model 2
Constant−0.255
(0.402)		−0.373
(0.392)
Anonymity clues−0.095
(0.142)		 1
Sender types−0.31 *
(0.143)		 1
Anonymity clues * Sender types−0.357 **
(0.16)
Gender0.227
(0.154)		0.229
(0.154)		1.155
Age0.051
(0.095)		0.0521.535
Income0.266 ***
(0.081)		0.265 ***
(0.081)		1.499
Chi-square23.627 ***23.369 ***
Log likelihood1131.3511131.609
HL test (Prob > chi-squared)0.8750.349
Note: ***, **, and *: statistically significant at 1%, 5%, and 10%, respectively.
Table
Table 2. Model estimates for advertising conversion.
Table 2. Model estimates for advertising conversion.
Explanatory VariablesDependent Variables—Advertising Conversion
Model 1Model 2Model 3
Constant−1.381 ***
(0.364)		−0.626 *
(0.298)		−0.59 *
(0.297)
Anonymity clues0.479 **
(0.184)
Sender types0.375 *
(0.184)
Content narratives0.594 **
(0.19)
Anonymity clues * Sender types 0.532 *
(0.225)
Anonymity clues * Sender types * Content narratives −0.778 **
(0.294)
Gender0.402 *
(0.205)		0.417 *
(0.202)		0.437 *
(0.202)
Age0.006
(0.124)		−0.008
(0.121)		−0.02
(0.121)
Income0.464 ***
(0.108)		0.426 ***
(0.105)		0.41 *
(0.104)
Chi-square59.179 ***46.069 ***44.244 ***
Log likelihood690.463703.573705.398
HL test (Prob > chi-squared)0.630.6240.083
Note: ***, **, and *: statistically significant at 1%, 5%, and 10%, respectively.
Table
Table 3. Model estimates for Study 2.
Table 3. Model estimates for Study 2.
Explanatory VariablesDependent Variables—Total Acceptance
Constant−5.113 ***
(0.219)
Anonymity clues−0.347
(0.188)
Sender types0.833 ***
(0.201)
Content narratives0.49 **
(0.191)
Chi-square28.861 ***
Log likelihood1270.179
HL test (Prob > chi-squared)0.164
Note: ***, **: statistically significant at 1% and 5%, respectively.
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Sun, X.; Li, Y.; Guo, B.; Gao, L. Marketing Automation: How to Effectively Lead the Advertising Promotion for Social Reconstruction in Hotels. Sustainability 2023, 15, 4397. https://doi.org/10.3390/su15054397

AMA Style

Sun X, Li Y, Guo B, Gao L. Marketing Automation: How to Effectively Lead the Advertising Promotion for Social Reconstruction in Hotels. Sustainability. 2023; 15(5):4397. https://doi.org/10.3390/su15054397

Chicago/Turabian Style

Sun, Xue, Yuhao Li, Bo Guo, and Li Gao. 2023. "Marketing Automation: How to Effectively Lead the Advertising Promotion for Social Reconstruction in Hotels" Sustainability 15, no. 5: 4397. https://doi.org/10.3390/su15054397

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