The Effect of Product Placement Strategies on Customer Behavior: A Prospective of Foote, Cone and Belding (FCB) Grid Model
1
College of Economics and Management, Beijing Institute of Petrochemical Technology, Beijing 102617, China
2
Media and Communication Department, City University of Hong Kong, Hong Kong SAR 999077, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(2), 1189; https://doi.org/10.3390/su15021189
Submission received: 2 December 2022
/
Revised: 2 January 2023
/
Accepted: 3 January 2023
/
Published: 9 January 2023
(This article belongs to the Section Economic and Business Aspects of Sustainability)
Abstract
:This paper explores the effect of product placement strategies on customer behavior in the Chinese context and the results will help companies in China select appropriate marketing strategies to achieve sustainable development. Following the Foote, Cone and Belding (FCB) grid model, we construct a product difference model in which products are classified into four types, namely High Involvement/Thinking, High Involvement/High Feeling, Low Involvement/Thinking, and Low Involvement/High Feeling. Further, we conduct a questionnaire survey to analyze the effect of product placement strategies on various behaviors, including awareness, recognition, attitude and purchase intention. The results of repeated measures of General Linger model suggest that Chinese customers accept product placement strategies. Furthermore, among the four product types, the positive effect of product placement strategies on customer behavior is more pronounced in the Low Involvement/High Feeling product type. However, the purchase intention of Chinese customers is stable and hard to change. The results also help the company to avoid misleading advertising and to design sustainable marketing strategies by applying more effective tools in terms of specific product types. As a result, the company will reduce financial expenditure to achieve sustainable development.
1. Introduction
In modern times, more and more product placement strategies appear in TV dramas around the world. Through product placement strategies, many enterprises expose their brand image in popular dramas to increase their brand awareness, and to develop new markets. Among multiple definitions of product placement, one of the most classic ones is that “product placement” is a paid product message aimed at influencing audiences via the planned and unobtrusive entry of a branded product into a movie or television program [1]. From some scholars’ perspectives, the brand concept recognizes that all varieties of communications, including product placement strategies, can contribute to an organization’s brand image and equity [2]. However, the existing market has already been divided into various sectors, and those sectors have various target markets. In order to draw customers from various sectors, items of various types must employ a variety of tactics. To determine their own communication strategy, consumers must pay attention to the heterogeneity among various products. Product placement strategies are becoming more significant in communication campaigns, and TV shows and film adaptations contain many examples of this. For instance, a company called Coffee Bene, founded in 2008, has experienced significant growth in China as a result of its placement in a number of well-liked Korean TV dramas. Chinese women enjoy watching Korean TV dramas, and because Coffee Bene has been featured in so many of these, they like to spend more money there. In mainland China, the company opened a new store every eight hours in 2015 with the use of placement techniques, and the company declared that it would open more than 3000 stores the following year. From the perspective of 21st century media, it is obvious that the business will profit from the impact of media on consumer behaviors if it adopts an effective product placement strategy. A good product placement strategy will also allow the business to develop sustainably by influencing its target audience more effectively and by avoiding misleading marketing. A sustainable marketing plan, which will always explain how a business will invest, advertise, and run with less money consumption during its marketing campaign, is generally necessary for the implementation of sustainable development. When harmful products and deceptive advertising are criticized by the general public, sustainable marketing is frequently utilized as a response. The business will reduce misleading advertisements and cut back on marketing campaign costs with the use of effective product placement strategies. Using green marketing strategies, the company’s sustainable growth will be attained.
2. Literature Review and Hypotheses
2.1. Judgements on Product Placement Strategies
People held different judgements towards product placement strategies before 1995. As [3] discussed, the company may be confused about whether or not to use product placement strategies to promote traditional goods. However, some scholars began to hold a positive attitude towards promotion strategies since 1996. According to [4], product placement strategies will be a powerful communication strategy in TV dramas or movie editions in modern society and there are three main reasons for that. First, movies and TV dramas are attractive. Second, successful TV dramas will also achieve wide coverage at a bargain price. Third, product placement has traditionally been regarded as a neutral and non-aggressive method to promote a brand image. To conclude, previous studies always focus on people’s responses, such as recognition, recall, attitude and purchase intention. There is a study of general audiences’ attitudes toward product placement strategies, conducted by [5]. In the study, over 70 percent of the concepts mentioned in the open-ended questions are positive, and 25 percent of respondents indicated that product placement strategies should be banned. Meanwhile, some studies focus on examining whether consumer brand awareness could be significantly increased after the promotion of product placement strategies [6,7,8]. Their studies argued that product placement strategies are positive for the enhancement of brand awareness, but they might also trigger confusion about product brand image from some customers’ perspectives. Some studies focus on the recall effects of product placement strategies; the author concluded that a product placement strategy may improve brand recall if it has central action and prominent size [9,10] and most predecessors agreed that customers’ acceptability of product placement strategies is high [7]. However, the recall effects may neither be transferred directly to attitudes nor purchase intentions, and there is no necessary connection between memory and attitude [11]. Ref. [12] suggested that previously favored brands can increase 16 percent of purchase intentions. Ref. [13] showed that product placement acceptability of ethically controversial products is generalizable over different cultures, but not product placement acceptability of neutral products. Ref. [14] estimated that around 80 percent of the message receivers adopted a positive attitude toward product placement strategies; therefore, brand awareness and purchase behavior may also be influenced by product placement strategies. Ref. [15] used a case study methodology examining the use of product placement strategies at Walt Disney with primary data obtained from interviews with Disney staff from Disney Interactive Marketing Group and a focus group of consumers of Disney video game products. The results of the study indicated that the branded entertainment approach to product placement enhanced existing awareness of the branded character and the parent Disney brand. In addition, the consumers of the video game product perceived the branded entertainment approach as less intrusive than a traditional product placement in which a branded product was inserted into the video, audio or action content of the video games. In 2013, Ref. [16] provided evidence to prove that brand recall is crucial for resistance to product placement. The study revealed the importance of brand recall as a moderator of resistance processes. Ref. [17] described an experimental study in which children were exposed to different versions of a cartoon movie which included a moderately or frequently placed chips brand. Compared to screen-placements, moderately and frequently presented plot-placements lead to an increase in children’s product choice. In a series of studies, Ref. [18] developed and tested a theoretically-based product placement fit model that recognizes the importance of congruency between consumers’ narrative consumption goals and the manner in which products are placed. Ref. [19] presented an investigation on the impact of product placement in video games on gamers’ decisions regarding the purchase of goods advertised. The results suggested that gamers generally respond positively towards product placement strategies and product placement can indirectly impact emotional responses that will impact consumers’ purchase intention. Therefore, advertising in video games enhances brand recognition and the perception of virtual reality. Ref. [20] offered several implications for theory and practice; he argued that high product involvement strategies directly influence consumer responses through imagination, co-creation, and telepresence. Meanwhile, low-involvement strategies only increase brand engagement and indirectly influence consumer responses through the less cognitively taxing process of interactivity. Ref. [21] argued that frequent use of celebrity advertisements renders consumers skeptical of celebrity advertisements’ profit-making intent, which may adversely affect the sustainable marketing of the brand. This has given rise to a “natural celebrity–brand association” that features celebrities using the brand in real-life settings.
2.2. Limitations of Previous Studies
Despite the fact that product placement strategies have been increasingly explored recently, many academic studies focus more on the reactions of consumers to product placement than on its viability. Which product categories, for instance, lend themselves well to product placement strategies? In addition, most studies do not explore potential differences in clients from other regions and instead concentrate on the American market rather than the Asian one. For instance, Ref. [22] did not devote enough attention to Asia when studying the product placement phenomena in Germany and the UK. The findings of the study may cause other academics to ignore Asian companies and audiences. There is no doubt that, because they come from diverse cultural backgrounds and socioeconomic situations, people have varied perspectives of the same phenomenon. Furthermore, according to some earlier studies, product attributes should also be taken into account when determining how effective a product placement strategy will be and how different product categories will produce varied outcomes [23]. In fact, consumer behavior may be influenced by product placement strategies. For instance, some TV drama followers could follow the advice of their idol and purchase the same things that the idol used in the dramas.
People’s responses differ depending on the product category, and current studies tend to focus on this aspect. Ref. [24] conducted a study that examined the impact of various types of product placement strategies on consumer responses to products promoted in various TV dramas. He proposed that the plots of TV dramas be relevant to consumers’ daily lives in order to influence their actions in their daily lives. However, Ref. [25] indicated that participants’ exposure to prominent placements would have a less positive brand attitude and lower purchase intention towards the products, which contradicts [24]’s conclusion. Ref. [26] further analyzed the mediation role of customers’ attitudes towards product placement strategies in 2015 in terms of social media context and concluded that product placement results may be mediated by people’s attitudes. Some scholars, such as [27], tried to analyze specific sponsored events to prove that successful product placement strategies will be positive to brand image and enhance the market value by influencing consumer attitudes. In 2013, Ref. [28] carried out a comparative study between normal product placement and non-ethical product placement strategies to reveal that customers do not accept non-ethical product placement; people prefer to see “normal” brands in movies. According to [29], diverse ad designs would affect buyers with various values in different ways. For instance, the emotional appeal of an advertisement will positively affect hedonic value, while the rational appeal of an advertisement will positively affect utilitarian value.
In addition, recent product placement studies revealed little evidence of new theories or modules being developed. Ref. [30], who provided a thorough and systematic review of the product placement literature, divided the previous studies into three clusters: (1) fundamental concepts, fundamental research frameworks, and empirical studies on product placement in movies and television programs; (2) empirical studies on product placement in games, with a particular focus on children and food product placements; and (3) empirical studies on the effects and underlying mechanisms of product placement. The majority of studies concentrate on film or television rather than online media platforms such as “Douyin” and “Youtube”, as earlier studies have not kept up with the modern times.
2.3. The Originality of the Study
Based on what we discussed above, this essay intends to categorize product brands based on previous research. We will further analyze the survey data collected from Chinese students and assess Chinese students’ product placement acceptability on Asian TV dramas across different product categories. We will determine which product category has a better product placement effect on students’ consumption behaviors using the theoretical model and data analysis. Meanwhile, the research findings will be a valuable resource for the marketing department as it makes decisions. We focused more on the effect of product heterogeneity in the study. We divided products into four categories and created the same questions for each product category to see how students responded. We employed the FCB Grid model, a comprehensive communication model created by the renowned advertising firm Foot, Cone and Belding (FCB). This model has served the marketing and advertising industries well over the decades [14].
Furthermore, the study discussed not only marketing strategies, but also sustainable development, which has received less attention in marketing strategy discussions in the past. However, with the development of the ESG concept (Environmental, Social, and Governance), companies, particularly those with household names, must find a way to achieve long-term growth. Product placement strategies should be more concerned in the future as an important part of company development strategies. The product types will be reallocated using the FCB model, and their various characteristics and reactions to product placement strategies will be tested in the study. In this way, we will differentiate the features of various product types and assist the company in developing appropriate placement strategies to achieve long-term growth.
As shown in Table 1, the FCB Grid model has two different levels named “involvement” and “feeling”. Based on these two levels, it can be divided into two different sectors. In the model, FCB Grid presents four different sectors, with the first being High Involvement/Thinking (need to think carefully and experience the product before they make a decision to purchase it), a typical example of which is cars. Second is High Involvement/High Feeling (need to experience the product but do not need to think carefully before they make a decision to purchase it); beautiful jewelry can be a good example of this kind of product category. Third is Low Involvement/Thinking (need to think carefully but no need to experience the product before they make a decision to purchase it); for example, food consumption. Last is Low Involvement/High Feeling (no need to think carefully and no need to experience the product before they make a decision to purchase it); this kind of product can always be cheap and desired, such as candy and cigarettes.
2.4. Hypotheses
According to [6], low involvement and high feeling product types have a greater influence on customer behavior. Ref. [31] also demonstrated that video games contain a high level of involvement, which can entice customers to interact with brand images. Meanwhile, [32] found that low involvement customers are more influenced by prices than high involvement customers because involved customers who pay close attention to product experience place less value on advertised prices. As a result, we anticipate that high involvement products will require more customer involvement to improve customer purchase behaviors, implying that product placement strategies will have less impact on high involvement products. Furthermore, we contend that thinking type products will lead to rational decisions, implying that the effect on this product type is limited.
Above all, we propose eight hypotheses according to product heterogeneity. The first two hypotheses aim to measure whether different product categories have a different impact on customers’ brand awareness.
H1.
In terms of high involvement products, the product placement of high involvement/thinking (low feeling) products will have less impact on customers’ brand awareness than that of high involvement/high feeling products.
H2.
In terms of low involvement products, the product placement of low involvement/thinking (low feeling) products will have less impact on customers’ brand awareness than that of low involvement/high feeling products.
The third and fourth hypotheses aim to measure whether different product categories have a different impact on customers’ brand recognition.
H3.
In terms of high involvement products, the product placement of high involvement/thinking (low feeling) products will have less impact on customers’ brand recognition than that of high involvement/high feeling products.
H4.
In terms of low involvement products, the product placement of low involvement/thinking (low feeling) products will have less impact on customers’ brand recognition than that of low involvement/high feeling products.
The fifth and sixth hypotheses aim to measure whether different product categories have a different impact on customers’ brand attitudes.
H5.
In terms of high involvement products, the product placement of high involvement/thinking (low feeling) products will have less impact on customers’ brand attitude than that of high involvement/high feeling products.
H6.
In terms of low involvement products, the product placement of low involvement/thinking (low feeling) products will have less impact on customers’ brand attitude than that of low involvement/high feeling products.
The seventh and eighth hypotheses aim to measure whether different product categories have a different impact on customers’ brand recognition.
H7.
In terms of high involvement products, the product placement of high involvement/thinking (low feeling) products will have less impact on customers’ purchase intention than that of high involvement/high feeling products.
H8.
In terms of low involvement products, the product placement of low involvement/thinking (low feeling) products will have less impact on customers’ purchase intention than that of low involvement/high feeling products.
3. Methodology
We examine the impact of product placement strategies using a mixed method that favors inductive reasoning. First, we define Independent Variables and Dependent Variables based on previous research and observation. Second, we construct hypotheses. Third, we used the Likert scale method to create the questionnaires. The survey had four different brands and each one contains seven product-placement items measured with a 5-point Likert-type scale from 1, “strongly disagree”, to 5, “strongly agree”. Fourth, we distribute questionnaires both online and offline using a convenient sampling method such as snowball sampling. We collected data in this manner by testing respondents’ free recall on product placement in Asian dramas. Then, we analyze the data using repeated measures in General Linear Model and draw our conclusions.
3.1. Variable Measured
We use warrant sources to construct the conceptual framework, which is based on previous studies and research findings. Among these sources, we choose the FCB Grid module as the paper’s basic research framework. Furthermore, we construct a more complex module using our creative ideas from previous studies. As shown in Table 2, the independent variables are involvement, feeling, and gender, while the dependent variables are awareness, recognition, attitude, and purchase intention.
We pick four different brands to represent the four product types shown in Table 1. Lenovo represents high-tech products in the High Involvement/Thinking sector. We choose Coffee Bene to represent products associated with coffee shops for the High Involvement/High Feeling type. Concerning the Low Involvement/Thinking section, we use Citrus Zinger as an analysis objective to represent the Household industry. Finally, as a Low Involvement/High Feeling product type, we select XiangPiaopiao, a milk tea brand in China. Our independent variables were studied concurrently based on the specific factorial design to determine their independent and interactive effects on the dependent variables of customer behaviors.
We draw on previous research to generate four distinct dependent variables: awareness, attitude, recognition, and purchase behavior. We pretend that for “high” involvement (i.e., pleasurable) products, product placement strategies may show both the pleasure from the product and the functional differences among brands in the product categories, according to [33]. We hypothesize that advertising would induce pleasure from presentational elements for “low” involvement products because these products lack the intrinsic motivation to produce pleasure.
3.2. Data Collection and Transformation
We delivered the questionnaires on the Internet, and then shared the web link in open social networks. We used the convenience sampling method and snowball sampling method to collect the survey data. For dependent variables, we used the Likert-type scale, which represents Strongly Disagree as 1, Disagree as 2, Undecided as 3, Agree as 4, and Strongly Agree as 5. This paper defines “awareness” and “recognition” as recall of the specific brand’s name, the name spelling, the frequency of commercial exposure and the attitude towards active information searching, as well as purchase intention in terms of product placement strategies.
We designed four sectors to represent different product categories in the questionnaire. Each sector has seven questions to measure people’s behaviors. Then, we conducted factor analysis to find out the outcomes using SPSS. After analyzing all the factors, we restructured four dependent variables, which are brand awareness, brand recognition, brand attitude and purchase intention, to replace the original seven questions for each section. According to a rotated component matrix, different brands generate different results. Based on most dependent variable results, we needed to integrate our similar sub-items into three variables. However, we still redefined dependent variables into four different categories to represent awareness, recognition, attitude and purchase intention. We use the values of question 1 minus that of question 4 to generate a new dependent variable named “awareness”, which represents the level of customer’s free recall of brand awareness as they were suggested certain brand images. We combined the value of question 2 and that of question 3 to generate a new dependent variable named “recognition”, which represents the impression from product placement in TV dramas. We also combined the results of question 5 and question 6 together to generate a new dependent variable, named “attitude”, to reflect customers’ attitudes towards product placement strategies. The results of question 7 are regarded as a specific one called purchase intention, which measures a customer’s purchasing intention and behavior after viewing product placement in TV dramas. As a result, four dependent variables, brand awareness, brand recognition, brand attitude and purchase intention, can be exactly defined.
Aside from that, we use the general linear model and repeated measures to introduce two new dimensions: involvement and feeling. Using the FCB grid model, we classify our product-independent variables into four categories ranging from low involvement/thinking to high involvement/feeling. Table 3 shows that we create two new independent variables in terms of “product type” here. One is “involvement” and the other is about “feeling”. As a result, we have four different independent categories to construct our product difference model: (1, 1), (1, 2), (2, 1), and (2, 2).
4. Results
4.1. Sample Description
We collected 215 questionnaires from Chinese students and conducted a series of data analyses, the results of which are shown in Table 4, Table 5 and Table 6. Based on the question of “how many TV dramas would you watch in a year?”, we got rid of those who did not watch any dramas. Then, we had 151 questionnaires that were valid. By analyzing the valid questionnaires, we were able to further discuss the impact of product placement strategies on customer behaviors.
As above, we found more than 73% of respondents are female (N = 151), 72% of respondents are 21–25, and 66% of respondents only watch 1–2 TV series during the year. Since young people are the main purchase power holders, the age distribution is quite favorable. However, the gender distribution is a little unbalanced. As shown in Table 7 and Table 8, we found that Cronbach’s Alpha of Zigrus and Xiang Piaopiao are quite reliable, and Bene’s is acceptable. However, the reliability of Lenovo is not perfect due to the result being much lower than 0.7. We reviewed the data and concluded that the reason was that maybe Lenovo’s brand image had already been very popular among customers. Therefore, the specific response from different respondents to the brand image of Lenovo can be varied. The KMOs of all brands are around 0.6. This means we can create new variables to integrate seven sub-items. As the KMO of Xiang Piaopiao is close to 1, that means the value of seven sub-items is quite similar to one another. Therefore, these sub-items can be integrated into one variable. Based on the rotated component matrix method, we integrate seven sub-items into four dependent variables which are “brand awareness”, “brand recognition”, “brand attitude” and “purchasing intention”.
4.2. Product Difference
Using repeated measures, we analyzed the effect level of different products based on different dependent variables.
4.2.1. Brand Awareness
As multivariate tests results show in Table 9, the feeling’s effect on brand awareness is significant and the co-effects of feeling and involvement on brand awareness are also significant. The effects of involvement and feeling on brand awareness can be concluded as follows: (1) If the product brand image belongs to the type of low involvement, the effect of product placement strategies on a thinking-type product (low feeling) is larger than that of the high feeling-type product; (2) If the product brand image belongs to the type of high involvement, the effect of product placement on high feeling-type product is much larger than that of the thinking-type product (see Figure 1). In Figure 1, the value represents the level of effects: the higher the value, the larger effects on brand awareness.
As a result, the effects on awareness change with a difference of the involvement and feeling level and the effect on low involvement/thinking type product is the largest one.
4.2.2. Brand Recognition
As multivariate tests results showed in Table 10, the feeling’s effect on brand recognition is significant and involvement’s effect on brand recognition is significant; the co-effects of feeling and involvement on brand recognition are significant.
The effects of involvement and feeling on brand recognition can be concluded as follows: the effect on a thinking-type product is smaller than that on a feeling-type product. In Figure 2, the value represents the level of effects: the higher the value, the larger the effects are on brand awareness. However, if the product belongs to the type of high involvement, the difference is small. We can see that the effect on a thinking-type product has a negative relationship with the involvement level (see Figure 2).
4.2.3. Brand Attitude
As multivariate tests results showed in Table 11, the feeling’s effect on brand attitude is significant and the co-effects of feeling and involvement on brand attitude are significant too.
The effects of involvement and feeling on brand attitude can be concluded as follows: the effect on a thinking-type product is smaller than that on a feeling-type product. The value in Figure 3 represents the level of effects: the higher the value, the larger the effects are on brand awareness. However, if the product belongs to the high involvement type, the difference is small. Meanwhile, as Figure 3 showed, for the high feeling-type products, the difference in the effect is small. However, the effect on a thinking-type product will decrease with the involvement-type change from low to high.
4.2.4. Purchase Intention
As the multivariate tests result show in Table 12, the feeling’s effect on purchase intention is not significant and the co-effects of feeling and involvement on purchase intention are not significant either.
The effects of involvement and feeling on intention can be concluded as follows: the effect on a thinking-type product is smaller than that on a feeling-type product. In Figure 4, the value represents the level of effects: the higher the value, the larger the effects are on brand awareness. However, if the product belongs to the high involvement type, the difference is small. As shown in Figure 4, the high feeling-type product presents an increasing trend. That means product placement strategies will have the largest impact on a low involvement/high feeling product type.
4.2.5. Product Difference
As shown in Figure 5, the effects of different product types are totally different from one another. (1, 1) represents the high involvement/high feeling product type; (1, 2) represents the high involvement/thinking product type; (2, 1) represents the low involvement/high feeling product type; and (2, 2) represents the low involvement/thinking product type. The results of brand awareness are much smaller than others because we transfer data using Q1 value minus Q4 value. Q1 value represents the current brand awareness, and Q4 value represents the previous brand awareness. In this way, we can get rid of existing awareness of Lenovo. In addition to that, the product placement strategies will have a huge impact on liking (low feeling) a type of product based on “brand recognition” and “purchasing intention”. When it comes to “attitude”, most product types have a high value, which means students in China hold an acceptable attitude towards product placement strategies. As for “awareness”, the effect strength on (2, 1) type product is the smallest and product placement strategies may have the least impact on the high involvement/thinking product type.
4.3. Findings
We review the eight hypotheses and found that most hypotheses can be accepted; however, H2 is rejected. We found that the product in the low involvement/high feeling type had the highest scores of all the dependent variables in our samples and it is reasonable to fit our entire target objects at a 0.05 level. Finally, we test our hypotheses based on our output results and draw a conclusion.
In terms of high involvement products, the product placement of high involvement/thinking (low feeling) products will have much less impact on customers’ brand awareness and brand recognition than that of high involvement/high feeling products. In terms of low involvement products, the product placement of low involvement/thinking (low feeling) products will have less impact on customers’ brand recognition and brand attitude than that of low involvement/high feeling products. In terms of high involvement products, the product placement of high involvement/low feeling (liking) products will have less impact on customers’ purchase intention than that of high involvement/high feeling products and low involvement/high feeling products. However, in terms of low involvement products, the product placement of low involvement/thinking (low feeling) products will have a larger impact on customers’ brand awareness than that of low involvement/high feeling products.
Above all, Xiang Piaopiao, representing low involvement/high feeling type, has the highest efficient performance. This implies that the product placement strategies of the low involvement/high feeling products have a more positive effect on Chinese customers’ consumption behavior. Based on the inductive reasoning method, we agree that products such as Xiang Piaopiao (low involvement/high feeling type product) obtain the best effect out of product placement strategies in TV dramas for Chinese customers. However, we do not think customers will change their purchasing intention easily, even if the company conducts product placement strategies. Even if product placement strategies change the purchase intention, they only work on the low involvement/high feeling products. Moreover, the company must consider regional and cultural differences; people from different cultural backgrounds or areas will produce different results. Thus, we conclude in this study that customers in China have an acceptable attitude toward product placement strategies in Asian TV dramas, and the study findings may not be applicable in other regions. Low involvement/high feeling product types will benefit the most from placement strategies. If a company intends to use placement strategies to achieve sustainable development, it must avoid low-feeling product types, such as house and household items.
5. Discussion
The purpose of this study is to explain the impact of product placement strategies on customer behavior in China. Furthermore, we show that different product categories have different effects even with the same product placement strategy. Interestingly, we discover that most Chinese interviewers accept product placement strategies in Asian TV dramas, as [14] previously discussed. According to [14], in the American market, more than 70% of the concepts mentioned in open-ended questions were favorable to product placement strategies. As a result, if the company in China wants to carry on such strategies in the Chinese market, it may be able to refer to product placement strategies and experience directly from the American market in the future. However, as previously stated, product placement strategies should take regional limitations into account. However, just because American and Chinese customers have similar interests in TV dramas, it does not mean they have similar interests in other media platforms. Whether or not there is an obvious difference in product placement strategies used in China versus other regional markets should be discussed further in the future.
5.1. Theoretical and Practical Implications
Based on the FCB grid model, we agree that product placement strategies have a positive impact on customers’ behaviors when it comes to the low involvement/high feeling product type and have a less positive impact when it comes to the high involvement/low feeling product type. As a result, when it comes to product placement strategies, businesses must pay closer attention to product categories. A good breakthrough is the low involvement/high feeling type product.
From the standpoint of long-term marketing, while customers in China are accepting of product placement strategies, decision-makers must develop flexible product placement strategies for different product categories. Companies in China should exercise caution when marketing low-feeling items. To avoid wasting money, the placement strategies could be promoted through online platforms that are more popular among young target customers rather than TV dramas. In this way, the company can put so-called sustainable marketing strategies into practice in order to achieve long-term sustainable development and avoid wasting money. Audiences relate to brands because of familiarity, a feel-good judgment of placement fit, increasingly appealing attitudes toward placement strategies, and their level of association with the film or TV drama.
Contextualizing a suitable product placement strategy as a message within a system of sociocultural, marketing communications, and textual cross-reference messages results in positive audience outcomes, as audiences become more in tune with brands and products they recognize from a placement. A suitable and sustainable product placement strategy is also an alternative way for brands to reach consumers that is more modest than traditional advertising. Sustainable marketing strategies do not only raise brand awareness for these companies, but also influence the purchasing intention to make more sustainable choices.
After working in the set dressing and decorating departments on feature films for many years, Bell, the founder of Green Product Placement, was familiar with the use of product placement strategies to dress and prop features. He shared his experience, claiming that when they choose products for placement, the product should not only fit into the ethos of the sponsor company, but it should also be more aesthetically pleasing, look better on camera, and thus be more desirable for set decorators and prop people to use in their projects. According to Bell’s perspective, “The positive effect of brand and behavioral recall dovetails with how the UNEP says we jump sustainable behaviors with consumers. By framing these products and behaviors in content, being used by actors, and shown as part of everyday occurrences, this helps to shape positive changes in the way consumers behave…We like to say that we make green normal through product placement strategies. It’s known as positive placement.”
As a result, brand managers and practitioners should concentrate on how to select appropriate products to carry out placement strategies. On the one hand, the low involvement/high feeling type of product is much easier to promote and influence target customers. A suitable and sustainable product placement strategy, on the other hand, will improve people’s recall ability of the brand image and brand awareness.
5.2. Limitations and Future Research
This study has several limitations. First, we found it hard to eliminate the influence of unrelated factors completely, especially for the existing brand awareness and recognition of big names such as Lenovo. The brand images of these big names are already deeply ingrained in their minds before Chinese people even see them in TV dramas. Thus, we will distinguish the effect of product placement strategies in TV dramas from those big names in further research. Second, people completed the questionnaire independently based on their free recall. This will have a negative impact on their final response, which means the questionnaire results may be uncertain. Third, the unbalanced gender distribution may have an uncertain impact on our research findings. Fourth, the type of placement (subtle/prominent) and repetition (low/moderate), according to [34], will interact to influence the brand image and people’s attitudes. The repetition of prominent placements for well-known brands may have an adverse effect on brand attitudes. Last but not least, the placement strategy has a regional limitation. The same strategy may not have the same impact in other parts of the world, such as the EU. Even if different media platforms implement the same strategy, the results may differ. However, the study lacks sufficient data to analyze the potential difference by taking into account the repetition factor, different media platforms, and regional limitations; all of these factors should be taken into account and discussed further in future studies.
6. Conclusions
In a positive light, this study examined people’s attitudes toward product placement strategies in China and compared the potential differences between people from different backgrounds. This study constructed a unique module based on the FCB grid and divided product types into four different categories with the help of previous studies. The findings show that the product placement strategies would have different effects on different product categories. We can conclude that product placement strategies in Asian TV dramas are acceptable to Chinese customers. Product placement strategies have a positive effect on customer behaviors for the low involvement/high feeling product type but have less impact on the high involvement/thinking product type. The business should also take the regional limitation into account when they carry on practical placement strategies.
To achieve sustainable development, the company must focus on the effectiveness of product placement strategies and develop a series of long-term sustainable marketing strategies in the near future. The company’s marketing campaign will impress target customers while using appropriate product placement strategies for specific product types. As a result, the placement strategies will be more effective on target customers while also being less expensive.
However, as previously stated, the study cannot completely eliminate the influence of unrelated factors, and the questionnaire cannot balance gender distribution; therefore, the research output cannot be applied directly in the non-China market. In the future, we hope to invite people from various cultural backgrounds and create a questionnaire that reflects people’s true thoughts and feelings rather than free recall. Furthermore, we will consider how to eliminate the influence of big names on interviewer responses and how to improve the research’s practical value.
Author Contributions
Methodology, N.L.; Software, N.L.; Validation, Y.W.; Formal analysis, N.L. and Y.W.; Investigation, N.L.; Resources, Y.W.; Writing—original draft, X.Z.; Writing—review & editing, N.L., Y.W. and Y.S.; Funding acquisition, X.Z. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by The National Soft Science Research Fund for Study on the Chinese Science and Technology Innovative Outstanding Talents Training (project number: 2014GXS4K051), The National Social Science Foundation (project number: 19FGLB025) for Research on Management and Management Science Reform in the Era of Intelligent Interconnection, Beijing Planning Office of Philosophy and Social Science for research on intellectual capital transformation pathways in collaboration with Beijing University and Enterprise (Project Number: 14JGB051), BIPT Breeding Project of Outstanding Academic Leaders (project number: BIPT-BPOAL-2015).
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data is unavailable due to privacy.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Balasubramanian, S.K.; Karrh, J.A.; Patwardhan, H. Audience response to product placements: An integrative framework and future research agenda. J. Advert. 2006, 35, 115–141. [Google Scholar] [CrossRef] [Green Version]
- Delorme, D.E.; Nowak, G.J. Developing integrated marketing communications message delivery strategies: Challenges and opportunities associated with the brand contact concept. In Proceedings of the Association for Education in Journalism and Mass Communication Conference, Chicago, IL, USA, 30 July–2 August 1997. [Google Scholar]
- Agrawal, M. Review of a 40-year debate in international advertising: Practitioner and academician perspectives to the standardization/adaptation issue. Int. Mark. Rev. 1995, 12, 26–48. [Google Scholar] [CrossRef]
- d’Astous, A.; Chartier, F. A study of factors affecting consumer evaluations and memory of product placements in movies. J. Curr. Issues Res. Advert. 2000, 22, 31–40. [Google Scholar] [CrossRef]
- Nebenzahl, I.D.; Secunda, E. Consumers’ attitudes toward product placement in movies. Int. J. Advert. 1993, 12, 1–11. [Google Scholar] [CrossRef]
- Babin, L.A. Advertising via the box office: Is product placement effective? J. Promot. Manag. 1996, 3, 31–52. [Google Scholar] [CrossRef]
- Gupta, P.B.; Gould, S.J. Consumers’ perceptions of the ethics and acceptability of product placements in movies: Product category and individual differences. J. Curr. Issues Res. Advert. 1997, 19, 37–50. [Google Scholar] [CrossRef]
- Karrh, J.A. Brand placement: A review. J. Curr. Issues Res. Advert. 1998, 20, 31–49. [Google Scholar] [CrossRef]
- Gupta, P.B.; Lord, K.R. Product placement in movies: The effect of prominence and mode on audience recall. J. Curr. Issues Res. Advert. 1998, 20, 47–59. [Google Scholar] [CrossRef]
- Gould, S.J.; Gupta, P.B.; Grabner-Kräuter, S. Product placements in movies: A cross-cultural analysis of Austrian, French and American consumers’ attitudes toward this emerging, international promotional medium. J. Advert. 2000, 29, 41–58. [Google Scholar] [CrossRef]
- Russell, C.A. Investigating the effectiveness of product placements in television shows: The role of modality and plot connection congruence on brand memory and attitude. J. Consum. Res. 2002, 29, 306–318. [Google Scholar] [CrossRef]
- Morton, C.R.; Friedman, M. “I saw it in the movies”: Exploring the link between product placement beliefs and reported usage behavior. J. Curr. Issues Res. Advert. 2002, 24, 33–40. [Google Scholar] [CrossRef]
- Eisend, M. A cross-cultural generalizability study of consumers’ acceptance of product placements in movies. J. Curr. Issues Res. Advert. 2009, 31, 15–25. [Google Scholar] [CrossRef]
- Yang, G.Y. Audience’s Acceptability of Product Placement: A Comparison of Chinese and Korean Young Consumers. Ph.D. Thesis, City University of Hong Kong, Hong Kong, China, 2010. [Google Scholar]
- Bigné, E.; Küster, I.; Hernández, A.; Suemanotham, T.; Vila, N. Product placement in video games as a marketing strategy: An attempt to analysis in Disney company. In Advances in Advertising Research; Gabler: Wiesbaden, Germany, 2011; Volume 2, pp. 3–20. [Google Scholar]
- Tessitore, T.; Geuens, M. PP for ‘product placement’or ‘puzzled public’? The effectiveness of symbols as warnings of product placement and the moderating role of brand recall. Int. J. Advert. 2013, 32, 419–442. [Google Scholar] [CrossRef]
- Naderer, B.; Matthes, J.; Marquart, F.; Mayrhofer, M. Children’s attitudinal and behavioral reactions to product placements: Investigating the role of placement frequency, placement integration, and parental mediation. Int. J. Advert. 2018, 37, 236–255. [Google Scholar] [CrossRef]
- Gillespie, B.; Muehling, D.D.; Kareklas, I. Fitting product placements: Affective fit and cognitive fit as determinants of con-sumer evaluations of placed brands. J. Bus. Res. 2018, 82, 90–102. [Google Scholar] [CrossRef]
- Chernikova, A.; Branco, M. Product placement in computer/video games: An analysis of the impact on customers purchasing decision. Innov. Mark. 2019, 15, 60. [Google Scholar] [CrossRef]
- Cowan, K.; Ketron, S. A dual model of product involvement for effective virtual reality: The roles of imagination, co-creation, telepresence, and interactivity. J. Bus. Res. 2019, 100, 483–492. [Google Scholar] [CrossRef]
- Zhang, K.; Hung, K. The Effect of Natural Celebrity–Brand Association and Para-Social Interaction in Advertising Endorsement for Sustainable Marketing. Sustainability 2020, 12, 6215. [Google Scholar] [CrossRef]
- Gibbons, T.; Katsirea, I. Commercial influences on programme content: The German and UK approaches to transposing EU rules on product placement. J. Media Law 2012, 4, 159–188. [Google Scholar] [CrossRef]
- Toomey, D.A. The Influence of Product Placement on Pre-Teen Decision-Making; Anderson University: Anderson, SC, USA, 2011. [Google Scholar]
- Liang, A.R.D.; Hsiao, T.Y.; Cheng, C.H. The effects of product placement and television drama types on the consumer responses of college students. Asia Pac. J. Tour. Res. 2015, 20, 1212–1233. [Google Scholar] [CrossRef]
- Chan, F.F.Y.; Petrovici, D.; Lowe, B. Antecedents of product placement effectiveness across cultures. Int. Mark. Rev. 2016, 33, 5–24. [Google Scholar] [CrossRef]
- Adis, A.A.A.; Ing, G.P.; Osman, Z.; Razli, I.A.; Pang, Y.X.; Sondoh, S.L.; Majid, M.R.A. Mediation role of attitude towards product placement in social media. J. Sustain. Dev. 2015, 8, 79. [Google Scholar]
- Marchand, A.; Hennig-Thurau, T.; Best, S. When James Bond shows off his Omega: Does product placement affect its media host? Eur. J. Mark. 2015, 49, 1666–1685. [Google Scholar] [CrossRef]
- Roozen, I. The Effectiveness of Product Placements in Music Videos: Some Experimental Empirical Results. Rom. Market. Rev. 2010, 4, 7–31. [Google Scholar]
- Kim, C.; Jeon, H.G.; Lee, K.C. Discovering the Role of Emotional and Rational Appeals and Hidden Heterogeneity of Con-sumers in Advertising Copies for Sustainable Marketing. Sustainability 2020, 12, 5189. [Google Scholar] [CrossRef]
- Guo, F.; Ye, G.; Hudders, L.; Lv, W.; Li, M.; Duffy, V.G. Product placement in mass media: A review and bibliometric analysis. J. Advert. 2019, 48, 215–231. [Google Scholar] [CrossRef]
- Küster, I.; Vila, N.; Hernández, A.; Canales, P.; Castillo, V. Product Placement in Video Games: Image Transference among Emotions. In Engaging Consumers through Branded Entertainment and Convergent Media; IGI Global: Hershey, PA, USA, 2015; pp. 127–148. [Google Scholar]
- Dagger, T.S.; David, M.E. Uncovering the real effect of switching costs on the satisfaction-loyalty association: The critical role of involvement and relationship benefits. Eur. J. Mark. 2012, 46, 447–468. [Google Scholar] [CrossRef]
- Chaudhuri, A.; Buck, R. Affect, reason, and persuasion: Advertising strategies that predict affective and analytic-cognitive responses. Human Commun. Res. 1995, 21, 422–441. [Google Scholar]
- Homer, P.M. Product placements. J. Advert. 2009, 38, 21–32. [Google Scholar] [CrossRef]
Figure 1.
Involvement × Feeling Effects on Awareness. Note: Thinking represents a low feeling.
Figure 2.
Involvement × Feeling effects on recognition. Note: Thinking represents a low feeling.
Figure 3.
Involvement × Feeling Effects on attitude. Note: Thinking represents a low feeling.
Figure 4.
Involvement × Feeling Effects on Purchasing Intention. Note: Thinking represents a low feeling.
Figure 4.
Involvement × Feeling Effects on Purchasing Intention. Note: Thinking represents a low feeling.
Figure 5.
Involvement × Feeling effects on product difference.
Table 1.
Foote, Cone and Belding Grid.
| Thinking (Low Feeling) | High Feeling | |
|---|---|---|
| High Involvement | Example: | Example: |
| Car | Jewelry | |
| House | Cosmetics | |
| Furnishings | Fashion goods | |
| New products | ||
| Low Involvement | Example: | Example: |
| Food | Cigarettes | |
| Household items | Liquor | |
| Candy |
Table 2.
Concept/variables, Operationalization, and Possible sources.
| Concept/Variable | Operationalization | Likely Data Source |
|---|---|---|
| Independent Variables | ||
| 1. Product Difference | ||
| High Involvement/Thinking | Suitable classification from previous research | Questionnaire |
| High Involvement/High Feeling | ||
| Low Involvement/Thinking | ||
| Low Involvement/High Feeling | ||
| Dependent Variables | ||
| 1. Acceptability | ||
| Awareness | Suitable classification from previous research | Questionnaire |
| Recognition | ||
| Attitude | ||
| Purchase Intention | ||
Table 3.
Specific product categories.
| Feeling (1: Thinking; 2: High Feeling) | Product | |
|---|---|---|
| 1 | 1 | Citrus Zinger |
| 2 | Xiang Piaopiao | |
| 2 | 1 | Lenovo |
| 2 | Coffee Bene |
Table 4.
Gender distribution.
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
|---|---|---|---|---|---|
| Valid | 1 | 111 | 73.5 | 73.5 | 73.5 |
| 2 | 40 | 26.5 | 26.5 | 100.0 | |
| Total | N = 151 | 100.0 | 100.0 | ||
Note: Here 1 represents female and 2 represents male. The number of our accepted samples is 151.
Table 5.
Age distribution.
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
|---|---|---|---|---|---|
| Valid | 1 | 10 | 6.6 | 6.6 | 6.6 |
| 2 | 109 | 72.2 | 72.2 | 78.8 | |
| 3 | 18 | 11.9 | 11.9 | 90.7 | |
| 4 | 9 | 6.0 | 6.0 | 96.7 | |
| 5 | 5 | 3.3 | 3.3 | 100.0 | |
| All | N = 151 | 100.0 | 100.0 | ||
Note: Here 1 represents 15–20 years old, 2 represents 21–25 years old, 3 represents 26–30 years old, 4 represents 31–40 years old, and 5 represents 41 years old and above.
Table 6.
Watching times distribution.
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
|---|---|---|---|---|---|
| Valid | 1 | 100 | 66.2 | 66.2 | 66.2 |
| 2 | 23 | 15.2 | 15.2 | 81.5 | |
| 3 | 13 | 8.6 | 8.6 | 90.1 | |
| 4 | 15 | 9.9 | 9.9 | 100.0 | |
| All | N = 151 | 100.0 | 100.0 | ||
Note: Here 1 represents 1–2 dramas per year that the participants would watch, 2 represents 3–4 dramas per year, 3 represents 5–6 dramas per year, and 4 represents more than 7.
Table 7.
Reliability analysis.
| Lenovo | Bene | Zigrus | Xiang Piaopiao | |
|---|---|---|---|---|
| Cronbach’s Alpha | 0.19 | 0.565 | 0.75 | 0.862 |
Note: The Alpha value > 0.7 will be considered very reliable.
Table 8.
Factor analysis and rotated component matrix.
| Lenovo | Bene | Zigrus | ||||||
|---|---|---|---|---|---|---|---|---|
| KMO Value | 0.604 | 0.595 | 0.604 | |||||
| R.C.M | C1 | C2 | C3 | C1 | C2 | C3 | C1 | C2 |
| Q1 | 0.888 | 0.874 | 0.847 | |||||
| Q2 | 0.61 | −0.72 | 0.58 | 0.615 | 0.8 | 0.405 | ||
| Q3 | 0.755 | 0.811 | 0.621 | |||||
| Q4 | 0.848 | 0.789 | 0.935 | |||||
| Q5 | 0.918 | 0.896 | 0.673 | −0.432 | ||||
| Q6 | 0.954 | 0.866 | 0.814 | |||||
| Q7 | 0.768 | 0.775 | 0.573 | 0.511 | 0.777 | |||
Note: Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization, C N means Component N, Q N means Question N.
Table 9.
Multivariate tests on awareness.
| Effect | Value | F | Hypothesis df | Error df | Sig. | |
|---|---|---|---|---|---|---|
| involvement | Pillai’s Trace | 0.494 | 146.370 b | 1 | 150 | 0 |
| Wilks’ Lambda | 0.506 | 146.370 b | 1 | 150 | 0 | |
| Hotelling’s Trace | 0.976 | 146.370 b | 1 | 150 | 0 | |
| Roy’s Largest Root | 0.976 | 146.370 b | 1 | 150 | 0 | |
| feeling | Pillai’s Trace | 0.265 | 54.124 b | 1 | 150 | 0 |
| Wilks’ Lambda | 0.735 | 54.124 b | 1 | 150 | 0 | |
| Hotelling’s Trace | 0.361 | 54.124 b | 1 | 150 | 0 | |
| Roy’s Largest Root | 0.361 | 54.124 b | 1 | 150 | 0 | |
| involvement and feeling | Pillai’s Trace | 0.341 | 77.626 b | 1 | 150 | 0 |
| Wilks’ Lambda | 0.659 | 77.626 b | 1 | 150 | 0 | |
| Hotelling’s Trace | 0.518 | 77.626 b | 1 | 150 | 0 | |
| Roy’s Largest Root | 0.518 | 77.626 b | 1 | 150 | 0 |
Note: Intercept is involvement + feeling + involvement × feeling.
Table 10.
Multivariate tests on recognition.
| Effect | Value | F | Hypothesis df | Error df | Sig. | |
|---|---|---|---|---|---|---|
| involvement | Pillai’s Trace | 0.494 | 146.370 b | 1 | 150 | 0 |
| Wilks’ Lambda | 0.506 | 146.370 b | 1 | 150 | 0 | |
| Hotelling’s Trace | 0.976 | 146.370 b | 1 | 150 | 0 | |
| Roy’s Largest Root | 0.976 | 146.370 b | 1 | 150 | 0 | |
| feeling | Pillai’s Trace | 0.265 | 54.124 b | 1 | 150 | 0 |
| Wilks’ Lambda | 0.735 | 54.124 b | 1 | 150 | 0 | |
| Hotelling’s Trace | 0.361 | 54.124 b | 1 | 150 | 0 | |
| Roy’s Largest Root | 0.361 | 54.124 b | 1 | 150 | 0 | |
| involvement and feeling | Pillai’s Trace | 0.341 | 77.626 b | 1 | 150 | 0 |
| Wilks’ Lambda | 0.659 | 77.626 b | 1 | 150 | 0 | |
| Hotelling’s Trace | 0.518 | 77.626 b | 1 | 150 | 0 | |
| Roy’s Largest Root | 0.518 | 77.626 b | 1 | 150 | 0 |
Note: Intercept is involvement + feeling + involvement × feeling.
Table 11.
Multivariate tests on recognition.
| Effect | Value | F | Hypothesis df | Error df | Sig. | |
|---|---|---|---|---|---|---|
| involvement | Pillai’s Trace | 0.418 | 107.748 b | 1 | 150 | 0 |
| Wilks’ Lambda | 0.582 | 107.748 b | 1 | 150 | 0 | |
| Hotelling’s Trace | 0.718 | 107.748 b | 1 | 150 | 0 | |
| Roy’s Largest Root | 0.718 | 107.748 b | 1 | 150 | 0 | |
| feeling | Pillai’s Trace | 0.88 | 1101.245 b | 1 | 150 | 0 |
| Wilks’ Lambda | 0.12 | 1101.245 b | 1 | 150 | 0 | |
| Hotelling’s Trace | 7.342 | 1101.245 b | 1 | 150 | 0 | |
| Roy’s Largest Root | 7.342 | 1101.245 b | 1 | 150 | 0 | |
| involvement × feeling | Pillai’s Trace | 0.517 | 160.787 b | 1 | 150 | 0 |
| Wilks’ Lambda | 0.483 | 160.787 b | 1 | 150 | 0 | |
| Hotelling’s Trace | 1.072 | 160.787 b | 1 | 150 | 0 | |
| Roy’s Largest Root | 1.072 | 160.787 b | 1 | 150 | 0 |
Table 12.
Multivariate tests on purchase intention.
| Effect | Value | F | Hypothesis df | Error df | Sig. | |
|---|---|---|---|---|---|---|
| involvement | Pillai’s Trace | 0.415 | 106.339b | 1 | 150 | 0 |
| Wilks’ Lambda | 0.585 | 106.339b | 1 | 150 | 0 | |
| Hotelling’s Trace | 0.709 | 106.339b | 1 | 150 | 0 | |
| Roy’s Largest Root | 0.709 | 106.339b | 1 | 150 | 0 | |
| feeling | Pillai’s Trace | 0.893 | 1253.930b | 1 | 150 | 0 |
| Wilks’ Lambda | 0.107 | 1253.930b | 1 | 150 | 0 | |
| Hotelling’s Trace | 8.36 | 1253.930b | 1 | 150 | 0 | |
| Roy’s Largest Root | 8.36 | 1253.930b | 1 | 150 | 0 | |
| involvement × feeling | Pillai’s Trace | 0.558 | 189.478b | 1 | 150 | 0 |
| Wilks’ Lambda | 0.442 | 189.478b | 1 | 150 | 0 | |
| Hotelling’s Trace | 1.263 | 189.478b | 1 | 150 | 0 | |
| Roy’s Largest Root | 1.263 | 189.478b | 1 | 150 | 0 |
Note: Intercept is involvement + feeling + involvement × feeling.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Zhang, X.; Li, N.; Wang, Y.; Sun, Y. The Effect of Product Placement Strategies on Customer Behavior: A Prospective of Foote, Cone and Belding (FCB) Grid Model. Sustainability 2023, 15, 1189. https://doi.org/10.3390/su15021189
AMA Style
Zhang X, Li N, Wang Y, Sun Y. The Effect of Product Placement Strategies on Customer Behavior: A Prospective of Foote, Cone and Belding (FCB) Grid Model. Sustainability. 2023; 15(2):1189. https://doi.org/10.3390/su15021189
Chicago/Turabian StyleZhang, Xiaohong, Na Li, Yanbo Wang, and Yanqi Sun. 2023. "The Effect of Product Placement Strategies on Customer Behavior: A Prospective of Foote, Cone and Belding (FCB) Grid Model" Sustainability 15, no. 2: 1189. https://doi.org/10.3390/su15021189
APA StyleZhang, X., Li, N., Wang, Y., & Sun, Y. (2023). The Effect of Product Placement Strategies on Customer Behavior: A Prospective of Foote, Cone and Belding (FCB) Grid Model. Sustainability, 15(2), 1189. https://doi.org/10.3390/su15021189
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
