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        검색결과 8

        1.
        2023.07 구독 인증기관·개인회원 무료
        Cryptic marketing is a discreet communication strategy using crypted subculture symbols to avoid negative responses from other consumers. This has been used since marketing towards stigmatized subculture groups is challenging as there is a risk of losing consumers from the majority. Nevertheless, studies about the impact of cryptic marketing on prominent marketing variables are still scant. Thus, this study aims to determine the impact of cryptic marketing on brand attitude between LGBT group and heterosexual group in an unfriendly market (Indonesia) and a friendly market (the Netherlands). Using experiments, we tested the impact of three cryptic ads (low, medium, and high) which differ in the explicitness of LGBT symbols. The results revealed that the LGBT group (i.e., gays) in both markets have a more positive brand attitude towards the high cryptic ad. There were no differences in the brand attitude of heterosexuals, except for the gay-friendly participants in a friendly market which showed a preference for the low cryptic ad. This study contributes to the literature on covert marketing strategy as cryptic marketing is rarely discussed.
        2.
        2023.07 구독 인증기관·개인회원 무료
        Compulsive buying is a problematic behavior that could lead to negative outcomes (e.g., debts and negative relationships with relatives). Due to the COVID-19 pandemic, people changed their shopping behavior and experienced various life events. This research aims at exploring the relationship between life events and compulsive buying in Indonesia. A qualitative approach using in-depth interviews was employed. Nineteen participants who faced changing course of life, either positive (e.g., give birth) or negative (e.g., sudden death of family), during the pandemic were interviewed. We found that positive life events cause people to feel over-excited and over-grateful and shop compulsively. Negative life events that result in self-doubt and lower self-esteem also lead to a compulsive behavior. The study contributes to the compulsive behavior literature by exploring the antecedent of compulsive buying from the live events perspective and provide implications for policy makers and marketers.
        4.
        2018.07 구독 인증기관·개인회원 무료
        Casual mobile games (CMG) is one of the three types of game genres with the highest market share in turnover. This type of games can be distinguished from hardcore games in that their play sessions are usually shorter, the rules are simpler and required commitments are less (Engl & Nacke, 2013). Some of the most popular games with these features are, for example, Angry Birds, Candy Crush Saga, and Hearthstone. The retention rate of players is one of the subjects that sparks most interest to the industry since many players abandon the games only a few hours after downloading them. Companies are very interested in knowing what factors influence a player's decision to continue playing and recommending a game to other players, because it is the loyal players who could potentially pay for upgrades, make in-app purchases or attract indirect revenue through advertising (Hsu & Lin, 2016). Although previous research has extensively studied the antecedents of the continuance intention to use online games on PC and video game consoles, few works have tried to understand the factors that drive loyalty in mobile games (MG) (Hamari, Keronen, & Alha, 2015; Shaikh & Karjaluoto, 2015). MG differ from those developed for PCs and game consoles not only because of hardware limitations but also due to software limitations (Kuittinen, Jultima, Niemelä, & Paavilainen, 2007). The technical characteristics of a game influence perceived value (Choe & Schumacher, 2015) and, consequently, loyalty (Chang, 2013, Su, Chiang, Lee, & Chang, 2016). This study examines the antecedents of loyalty towards CMG from the perspectives of perceived value (i.e. hedonic and utilitarian values) (Babin, Darden, & Griffin, 1994; Chang, 2013; Chang et al., 2014; Davis, Lang, & Gautam, 2013). In addition, it explores the moderating effect of intensity of playing, because intensity can mitigate the impact of satisfaction on loyalty (Lu & Wang, 2008). Based on the literature review a research model was proposed and evaluated using survey data of 372 respondents with structural equation modelling (SEM) approach. The results reveal that hedonic value (i.e. perceived enjoyment and perceived attractiveness) and, to a lesser extent, utilitarian value (i.e. effort expectancy and perceived usefulness) are crucial to the player’s loyalty towards a mobile game. Intensity of playing weakens the relationship between perceived usefulness, perceived enjoyment and loyalty intention. Based on the findings, this research has important theoretical and practical implications in understanding the motivations of players to remain loyal to a mobile game and how these motivations vary depending on the intensity of playing.
        5.
        2018.07 구독 인증기관 무료, 개인회원 유료
        Introduction Compulsive buying refers to a condition where consumers make purchases repetitively and excessively (Ridgway, Kukar-Kinney & Monroe, 2008; Japutra, Ekinci & Simkin, 2017). Previous literature shows that two types of behaviors characterize compulsive buying: impulsive buying and obsessive-compulsive buying (Ridgeway et al, 2008). Impulsive buying refers to unplanned purchase due to consumers’ inevitable impulse (Kacen & Lee, 2002), and obsessive-compulsive buying reflects a preoccupation in buying to reduce anxiety (Ridgway et al, 2008). Compulsive buying behaviors have been analyzed under the framework of motivation theory (McGuire, 1976). Nevertheless, research is still needed to understand more on the phenomena of compulsive buying (e.g., Kukkar-Kinney et al., 2016; Japutra et al., 2017). This study aims to explore the antecedents of compulsive buying behaviors using implicit theories. According to the implicit theories, mindset shapes the motivation of consumer behaviors (Dweck, 2000; Murphy & Dweck, 2016). Mindset refers to the beliefs about the nature of human characteristics, and individuals may possess two types of mindset – fixed and growth mindset (Murphy & Dweck, 2016). People with a fixed mindset believe that individuals’ qualities such as intelligence and competence are set and hard to change, whereas those with a growth mindset tend to believe that all individuals are able to change and develop through efforts and experiences. We argue that mindsets influence compulsive buying, and we propose that deal proneness mediates the relationship between mindset and compulsive buying. In doing so, we aim to enhance our knowledge in understanding how mindset affects compulsive buying behavior. Literature review and hypotheses According to the implicit theories, consumers with fixed mindsets believe that one’s abilities are fixed and hard to improve, and thus feel the need to prove, to themselves and others, that they have the abilities and/or they are successful (Murphy & Dweck, 2016). Thus, fixed mindset consumers tend to demonstrate their worth by using image-enhancing products and brands (Park & John, 2012). Deals, such as free gifts and offer of coupons, reduce the transaction cost and increase the perceived value of these image-enhancing purchases. In particular, since fixed mindset consumers favor success with little effort (Murphy and Dweck, 2016), deals can help them achieve their goal of image enhancement with lower cost. Thus, we hypothesize that: H1 Fixed mindset is positively related to deal proneness. For consumers with growth mindsets, a major motivation for their consumer behavior is to learn and improve (Murphy & Dweck, 2016). As the research by Blackwell et al. (2007) shows, growth mindset consumers are eager to participate in the self-improving process and achieve mastery. Thus, growth mindset consumers may perceive the information of discounts, free gifts and coupons as part of the adventurous process where they make the cost-benefit analysis and improve their abilities as wiser consumers. Thus, we propose: H2 Growth mindset is positively related to deal proneness. Previous studies show that compulsive buying is associated with high deal proneness (Kukar-Kinney et al, 2012). Deals may imply perceived value of the purchase and enhanced shopping enjoyment (Grewal, Monroe, & Krishnan, 1998), and thus serve as an effective contextual factor in inducing compulsive behaviors (Kukar-Kinney et al, 2016). Furthermore, deals provide an excuse and rationale for the purchase, which can be used to overcome the sense of guilt compulsive buyers often experience after their compulsive buying behavior (O’Guinn & Faber, 1989). Thus, we make the following hypotheses. H3 Deal proneness is positively related to impulsive buying. H4 Deal proneness is positively related to obsessive-compulsive buying. Finally, we argue that deal proneness mediates the relationship between consumer mindsets and compulsive buying behavior. According to the implicit theories, consumer mindsets inspire how consumption goals are pursued (Murphy & Dweck, 2016). Consumers with a fixed mindset pursue a performance goal, and they tend to use brands to feel positive about themselves and improve impression on others (Park & John, 2010). In contrast, consumers with a growth mindset hold that people can always learn and improve and thus are tuned to learning goals (Murphy & Dweck, 2016). Hence, for fixed mindset consumers, deal offers suggest lower costs for image-enhancing purchases, and provide an excuse for the compulsive buying behavior. For growth mindset consumers, deal offers can imply a learning and adventurous process .These consumers may feel that they can make better purchasing decisions by taking advantage of various deals. We thus hypothesize that: H5 Deal proneness mediates the relationship between fixed mindset and impulsive buying (H5a), between fixed mindset and obsessive-compulsive buying (H5b), between growth mindset and impulsive buying (H5c), and between growth mindset and obsessive-compulsive buying (H5d). Method A questionnaire was developed to gather responses and test the hypotheses. All of the items to measure the constructs were developed from existing scales based on previous research. Fixed and growth mindsets were measured using scales developed by Park and John (2012). Deal proneness was measured using items following Lichtenstein et al. (1997). Impulsive buying and obsessive-compulsive buying were measured using items developed by Ridgway et al. (2008). All items were rated on a 7-point Likert scale, ranging from “strongly disagree” (1) to “strongly agree” (7). The questionnaire was administered using an online survey (N=421 respondents). Of these, 57.7% were female, 71.5% had a university degree, 50% were 31-40 years old, 41% were 26-30 years old, and 46.3% had a monthly income of 5,001-10,000 RMB. Results and discussion To test the hypotheses within the research model, a Structural Equation Modeling (SEM) approach was employed, using AMOS 18.0. First, a measurement model was created to assess the validity and reliability of the scales. The distribution of the data was checked. The absolute value of the skewness and kurtosis of each items were within +/- 1, suggesting normal distribution was achieved. The measurement model produced good fit (Hair et al., 2010): χ2(109) = 281.21, χ2/df = 2.58, GFI = .93, NFI = .93, CFI = .96, and RMSEA = .06. All values representing the AVE were greater than 0.5 and greater than the squared inter-constructs correlations, indicating convergent and discriminant validity were achieved (Fornell & Larcker, 1981). Cronbach’s alpha values exceeded .70, indicating the constructs were reliable (Hair et al., 1995). The results of the checking common-method variance problem through exploratory factor analysis (EFA) test revealed 3 factors with Eigen values greater than 1. The results accounted for 64.67% of the total variance, where the first factor accounted for 27.55% of the total variance, suggesting that common-method variance did not pose a significant problem since there was no general factor in the un-rotated structure (Podsakoff et al., 2003). Next, a structural model was created. The structural model produced good fit (Hair et al., 2010): χ2(114) = 476.15, χ2/df = 4.18, GFI = .89, NFI = .89, CFI = .91, and RMSEA = .09. Table 1 displays the results of SEM. The results support H1 and H2. Both fixed and growth mindsets are positively associated with deal proneness. The results support H3 and H4, which shows that deal proneness are positively associated with impulsive and obsessive-compulsive buying. The results support H5a, which states that deal proneness mediates the relationship between fixed mindset and impulsive buying. However, the results do not support H5b, H5c and H5d. Conclusion Using the implicit theories, this research aims to gain better insight into compulsive buying behavior. Our findings, obtained from a sample of respondents in China, show that deal proneness serves as a mediator between fixed mindset and compulsive buying behaviors. According to the implicit theories, consumer mindsets inspire how consumption goals are pursued (Murphy & Dweck, 2016). For instance, consumers with a fixed mindset pursue a performance goal. They tend to use brands to feel positive about themselves and improve impression on others (Park & John, 2010). Thus, it is likely that fixed mindset consumers buy compulsively to signal and communicate their “self” to others. In particular, for fixed mindset consumers, deals may increase the perceived value of image-enhancing purchases. Thus, deals provide an excuse for the compulsive purchase where fixed mindset consumers can improve self-image and demonstrate their worth with lower costs. Given this mediating role of deal proneness between fixed mindset and compulsive buying, it will be interesting to test further how consumers with a fixed mindset respond to different types of deals in future research. For firm managers and public policy makers, our findings imply that, to lessen consumers’ overspending, firms should reduce excessive number of deals, and governments should also regulate firms’ advertisement so that it will not overly promote deals.
        4,000원
        6.
        2018.07 구독 인증기관·개인회원 무료
        Increasingly, mobile technology is becoming common in our everyday lives (GFT Technologies, 2016); nevertheless, mobile payments are not one of the most frequently used mobile services (Liébana-Cabanillas, Muñoz-Leiva & Sánchez- Fernández, 2017). Peer-to-peer mobile payment services (P2PM-pay) (also referred to as person-to-person transactions or P2P transactions) allow customers to quickly and easily transfer funds from their bank account or credit card to another individual's account via the internet or a smartphone. Prior studies on payment systems using mobile devices focused on analyzing other types of payment systems, the internal structure and safety protocols for each system, and their adoption by consumers (Ramos-de-Luna, Montoro-Ríos & Liébana-Cabanillas, 2016; Ozturk, Bilgihan, Salehi-Esfahani & Hua, 2017). The aim of this research is to propose a standardized behavioral model of users’ intention to use P2PM-pay. The model has been defined based on a framework involving some of the main theories of technologies adoption from the perspective of social psychology (Fishbein y Ajzen, 1975; Davis, Bagozzi & Warshaw, 1989; Venkatesh & Davis, 2000; Venkatesh & Bala, 2008; Venkatesh, Thong, & Xu, 2012). Based on the literature review and in-depth interviews conducted of professionals from the Fintech (financial technology) sector, the model was structured based on three groups of antecedents (i.e., drivers, inhibitor and psychological dimensions) to explain the intention to use. The model was evaluated using survey data of 701 participants with structural equation modelling (SEM) approach. The proposed model is based on classical technology adoption models but incorporates specific variables from mobile payment systems. It includes a total of eight antecedents of the intention to use the P2PM-pay app. Among these antecedents, three (i.e. perceived usefulness, subjective norms and personal innovativeness) are fundamental to the intention to use, while three others (i.e. individual mobility, perceived risk and perceived trust) have a lesser influence. The results also point out that the relationships of both perceived ease of use and hedonic motivation with the intention to use are not significant. Based on the findings, this research has important theoretical and practical implications in understanding the adoption of P2P mobile payment services.
        7.
        2016.07 구독 인증기관 무료, 개인회원 유료
        Many studies in the marketing literature focus on investigating the effects of brand attachment and self-congruence on favorable consumer behavior, such as brand loyalty, positive Word-of-Mouth, resilience to negative information (Thomson et al., 2005, Japutra et al., 2014a). However, limited studies examine the relationship between brand attachment, self-congruence and negative consumer behavior. For instance, Johnson et al. (2011) posit that when consumers are in relationships with brands and more self-relevant, they are more likely to induce retaliatory actions when the relationship ends. Highlighting the dark side of brand attachment, Japutra et al. (2014b) show that stronger brand attachment leads to a wide range of unwanted consumer behaviors including trash-talk, Schadenfreude, and anti-brand actions. These studies show how brand attachment is capable of hurting consumers. However, only limited studies pay attention on the negative consequences of brand attachment (e.g. Johnson et al., 2011; Japutra et al., 2014b). The purpose of this study is to investigate the effect of self-congruence and brand attachment on compulsive buying behavior.
        4,000원
        8.
        2016.07 구독 인증기관 무료, 개인회원 유료
        Increasingly, there is a rise of interests from practitioners and academics on the topic of consumer-brand relationships (CBR). It has been argued that consumer build relationship with a brand in consonance with its personalities. Thus, this study investigates the role of brand personality in predicting prominent CBR constructs, such as brand awareness, brand trust, and brand loyalty. Researchers consider brand personality as one of the prominent constructs in predicting consumer preferences and choices (e.g. Eisend & Stokburger-Sauer, 2013; Gordon, Zainuddin, & Magee, 2016; Guèvremont & Grohmann, 2013). It has been established that brands are capable to have personalities (Aaker, 1997; Geuens, Weijters, & De Wulf, 2009). The study of brand personality flourished since Aaker (1997) created a brand personality scale (BPS). According to her, brand personality reflects five main dimensions: sincerity, excitement, competence, sophistication, and ruggedness. Out of these dimensions, many studies mainly focus on two dimensions, sincerity and excitement respectively (e.g. Aaker, Benet-Martinez, & Garolera, 2001; Hosany, Ekinci, & Uysal, 2006; Ivens & Valta, 2012; Sung, Choi, Ahn, & Song, 2015). These studies consider these two dimensions to be of important since these dimensions appear to capture much of the variance in personality ratings of brands (Aaker, 1997) and are considered prominent to the marketing landscape (Aaker, Fournier, & Brasel, 2004; Guèvremont & Grohmann, 2013; Toldos-Romero & Orozco-Gómez, 2015). Although Aaker's BPS represents the most prominent operationalization of brand personality (Eisend & Stokburger-Sauer, 2013; Matzler, Strobl, Stokburger-Sauer, Bobovnicky, & Bauer, 2016; Freling, Crosno, & Henard, 2011), her model has been the subject of several critiques. Researchers argue that the scale measures brand identity rather than brand personality (Azoulay & Kapferer, 2003), the scale is too general and simplistic (Austin, Siguaw, & Mattila, 2003), the scale does not include negative factors (Bosnjak, Bochmann, & Hufschmidt, 2007), and the scale is non-generalizable and non-replicable cross culturally (Arora & Stoner, 2009; Geuens et al., 2009). These shortcomings led researchers to construct an alternative to Aaker’s BPS. Geuens et al. (2009) develop a new measure of brand personality, which includes five dimensions: responsibility, activity, aggressiveness, simplicity, and emotionality. Although many studies scrutinize on Aaker’s brand personality scale, only limited studies apply Geuens et al.’s BPS (e.g. Garsvaite & Caruana, 2014; Goldsmith & Goldsmith, 2012; Gordon et al., 2016; Matzler et al., 2016). Thus, the present study investigates the relationships between brand personality, using Geuens et al.’s (2009) scale, and three important consumer-brand relationships (CBR) constructs. These three constructs are brand awareness, brand trust, and brand loyalty. Aaker (1991) conceptualize brand equity to include five important constructs, which includes brand awareness and brand loyalty. Meanwhile, Keller (1993) notes that brand knowledge is an important component of brand equity, consists of brand awareness and brand image. In addition, brand trust has been considered to be essential in influencing brand performance (Chaudhuri & Holbrook, 2001). Hence, the focus of the present study lies on these three variables. As it has been discussed above, researchers consider sincerity and excitement to be essential in investigating consumer behavior. In light of a shortage of studies in applying Geuens et al.’s (2009) BPS, the present study examines two personality dimensions, which are conceptually similar to Aaker’s (1997) BPS: responsibility to replace sincerity and activity to replace excitement (see Table 1). To the best of our knowledge, no research has investigated the relationships between these three consumer-brand relationships constructs (i.e. brand awareness, brand trust and brand loyalty) and the two most relevant brand personality dimensions (i.e. responsibility and activity). The present study contributes to the marketing literature in three different ways. First, this study adds to the body of knowledge on the relationship between brand personality and CBR constructs using the new measure of BPS. Second, this study assesses the individual level of the new BPS, particularly responsibility and activity, on the three CBR constructs. In doing so, this study responds Keller and Lehmann’s (2006) and Geuens et al.’s (2009) call to assess the individual capacity of the brand personality dimensions to get consumer preference or loyalty. Third, this study displays which out of the two dimensions of the new BPS (i.e. responsible and active) are more important to predict the three CBR constructs. In this research, data were collected from Spanish respondents using online survey with snowballing technique. In total, 347 respondents participated in the survey. After checking for incomplete questionnaires and missing values, 8 questionnaires were dropped. Hence, 339 questionnaires were used for the analysis. Before conducting multivariate analysis, normality tests were conducted. The measurement and structural models was tested using AMOS 18, employing the Maximum Likelihood (ML) method. We find that brand personality predicts these three CBR constructs. Brand personality explains 56%, 58%, and 45% of the variance in brand awareness, brand trust, and brand loyalty, respectively. The results show that the strongest link is between brand personality and brand trust. Su and Tong (2015) find that there is no relationship between exciting personality and brand awareness. On the contrary, this study displays that being an active brand leads to higher brand awareness. Even the results show that active brands are more likely to build brand awareness compared to responsible brands. However, in order to build brand trust and brand loyalty, responsible brands are more preferred compared to active brands. These results are in line with Eisend and Stokburger-Sauer (2013) that reveal weak relationships between excitement on brand attitude and brand commitment. These days, consumers prefer the brands to be more responsible or sincere. As Kotler (2011) argues that there is a shift in marketing that consumers pay more attention toward social responsibilities. Interestingly, the results show that being too active could negatively affect brand trust and brand loyalty. Although the association is not statistically significant, Banerjee (2016) finds that excitement brand personality has a negative association with brand preference. A study also finds that excitement does not predict employer brand trust (Rampl & Kenning, 2014). One explanation could be that the brands would like to be something that is an opposite of what they are claiming. Guèvremont and Grohmann (2013) argue that when a sincere brand attempts to flatter the consumers, it decreases brand attitude and increases disappointment. However, this does not occur when flattery comes from exciting brands. Brand managers should be very careful in communicating their brands personalities. Communicating to the consumers that their brands are responsible as well as active is good. However, brand managers should understand the interplay between these two opposing personalities. Consumers may believe that the brand is a responsible brand but also a little bit active. However, communicating two different opposing personalities at the same time may confuse the consumers. This is due to consumers’ disconfirmation of expectations (Guèvremont & Grohmann, 2013). Although this study enlightens the literature of brand management, it is not without its limitations. This study collects data from a cross-sectional study in Spain. In order to generalize the results of this study, future studies should replicate the conceptual framework cross culturally. Particularly on the negative effects of active personality toward the three CBR constructs. Furthermore, Spanish has been regarded as individuals with high uncertainty avoidance (Hofstede, 2001). Uncertainty avoidance increases the reliability of the brand personality dimensions, namely sincerity and excitement (Eisend & Stokburger-Sauer, 2013). Thus, it would be interesting to know whether differences occur between high and low uncertainty avoidance respondents. In addition, future studies should also account for other individual differences, such as attachment style. Japutra, Ekinci, Simkin, and Nguyen (2014) note that attachment style plays a prominent role in predicting consumer behaviors.
        3,000원