توضیح رفتار تغییر کانال مصرف کنندگان با استفاده از نظریه رفتار برنامه ریزی شده
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|1820||2011||11 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 9323 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Retailing and Consumer Services, Volume 18, Issue 4, July 2011, Pages 311–321
This exploratory study examined channel-switching behavior using the theory of planned behavior in three retail channels: bricks-and-mortar stores, catalogs, and the Internet. This theory assumes that individual attitudes and beliefs, along with subjective norms and control factors, will lead to an intention to perform a certain behavior, whether to switch channels or not. An online survey was administered at four different research sites and resulted in 547 usable surveys. Factor analysis and regression were used for data analysis. Attitude towards channel-switching was significantly influenced by hedonic and utilitarian beliefs in stores and catalogs. However, in the case of the Internet channel, attitude towards channel-switching was only influenced by utilitarian beliefs. Normative beliefs negatively influenced subjective norms in all the channels. Self-efficacy, information, and product type were important factors that impacted perceived behavioral control (PBC) in all channels. Time influenced PBC only in catalogs, and money did not influence PBC in any of the channels. Attitude and subjective norms influenced channel-switching intentions for three channels, whereas PBC was a significant predictor for channel-switching intention for only catalogs and the Internet.
Changing consumer behavior and the advent of new technology has changed the retail industry. With consumers being proactive in their purchase decisions and better educated about products, they are able to communicate with their peers about the value of a company and its services via the Internet, and they are quick to migrate to different channels and retailers if they’re not happy with the current ones (Making Every Interaction Count GameFly Aligns its Customer Experience, 2007). This behavior is called channel-switching, a dynamic process in which a consumer visits one of the channel options – a bricks-and-mortar store, a retailer's catalog, or the Internet (Sullivan and Thomas, 2004) – before making a purchase decision. In other words, consumers are looking for ways to maximize the benefits of shopping and minimize the costs associated with shopping, in terms of money, time, and energy, whether in a brick-and-mortar store, through a catalog, or over the Internet ( Anonymous and August, 1999, Downs, 1961 and Kim and Kang, 1997). That being said, the retail industry is mature, and expansion has slowed to a crawl and retailers have to do more with less. Moreover, the new consumer that shops across all channels is emerging in our society. Consumers expect merchants to adapt to their schedules and to provide products, service, and information to them anyway; any time (Kurt Salmon Associates, 2000). Each channel still has its attractions and detractions for multi-channel shoppers (DoubleClick, 2003). Consumers may therefore switch channels and/or retailers depending on their shopping benefits (Pulliam, 1999). For a retailer, then, it is crucial not only to obtain knowledge about the costs and benefits associated with different channels, but also to develop an optimized channel architecture (Madlberger, 2006), through which that retailer will try to lure consumers to the optimal channel instead of waiting for them to choose one (Myers et al., 2004). It seems that multiple channels will meet the desire for flexibility as consumers shop for what they want, when they want it, and how they want it (Johnson, 1999). The challenge, then, is to understand how and when consumers use bricks-and-mortar stores, catalogs, or the Internet and what influences their channel-switching behavior. The purpose of this study is to examine how attitudes, subjective norms, and perceived behavioral control predict channel-switching across three channels using the theory of planned behavior (TPB). TPB is an appropriate theory for studying channel-switching behavior since it has been suggested that when studying consumers’ purchasing behavior PBC should be taken into consideration as channel-switching does require skills and resources and does not occur merely because consumers decide to act (Shim et al, 2001). TPB has been also been used in studies that have examined multi-channel consumer behavior (Keen et al., 2004 and Kim and Park, 2005). Thus, the choice of TPB for this study is acceptable
نتیجه گیری انگلیسی
It can be inferred from the results of data analysis for this study that there exists similarities as well as differences in the manner the independent variables in each channel predict the dependent variables. In the case of bricks-and-mortar stores, consumers’ attitude toward channel-switching was significantly predicted by hedonic and utilitarian behavioral beliefs; however the regression coefficient for utilitarian values was much higher. This indicates that consumers’ behavioral beliefs for switching channels from stores to either catalogs or the Internet while shopping is anticipated to be influenced both by functional and experiential values, with functional values (i.e. means-to-an-end) being more important than the “fun” factor. This supports the belief that even with the growth of online sales, physical stores will still play an important role in the retail industry, with consumers wanting some of the touch-and-feel aspect and more of the convenience of shopping in a bricks-and-mortar store. For catalogs as well as the Internet, only utilitarian beliefs were significant in predicting the attitude toward migrating channels, which contradicts earlier studies such as Mathwick et al. (2001). It can be inferred that consumers form the attitude to migrate among channels while shopping based on the efficiency and convenience of migrating rather than on experiential values. These contradictory results could be explained by the demographic profile of the respondents. As most of the respondents were students, it can be inferred that they will be more prone to use the digital format of a catalog rather than paper, and hence their channel-switching attitude would be influenced by the convenience factor while channel-switching from catalogs to the stores or the Internet. Similarly, the students are adept at using the Internet, and hence their attitude towards switching from Internet to store or catalogs will be influenced by the convenience factor. Overall it can be stated that utilitarian beliefs are more relevant in predicting attitude toward channel-switching for all three channels. Utilitarian values are functional and incorporate more cognitive aspects of attitude and are a means to an end (Noble et al., 2005). Channel-switching allows consumers to complete their shopping task more efficiently (i.e. utilitarian belief) and hence it can be inferred that attitude towards channel-switching will be significantly influenced by utilitarian beliefs. Normative influence is defined as the tendency to conform to the expectations of others (Bearden et al., 1989). Under normative influence, an individual either adopts a behavior or an opinion because of the belief that the adoption will enhance the individual's self-concept, or complies with others’ with the expectation of awards (Hu and Jasper, 2006). In this study, normative beliefs for each of the channels were significant in predicting subjective norms. However, the relationship was negative contradicting studies such as Lim and Dubinsky (2005)'s on online purchase intention and retail store patronage (Evans et al., 1996). Thus, it can be inferred that subjective norms, which reflect consumer perceptions (i.e. normative beliefs) is in contradiction with group influence. In other words, consumers will act against their referent group when considering switching channels for shopping. This finding is important as “peer-influence” is an important consideration in retail and the absence of this influence while deciding whether to switch channels or not while shopping would have important implications for retail strategy. In bricks-and-mortar stores, self-efficacy, information, utilitarian, and hedonic product are the predictors for the dependent variable, PBC, with self-efficacy having the largest regression coefficient. Other variables of facilitating conditions, (i.e., time and money) did not predict the dependent variable. For catalogs, self-efficacy, time, and hedonic product variables significantly predicted the dependent variable with self-efficacy having the largest beta values. In the case of the Internet, self-efficacy, and information are the independent variables that significantly impacted PBC, information having the larger coefficient value. Self-efficacy was the significant predictor of PBC in all three channels with the largest regression coefficient in brick-and-mortar stores and catalogs but not the Internet. Self-efficacy measures a feeling of self-competence (Salanova et al., 2000), and hence it can be inferred that this is an important variable across all three channels. The higher coefficient value for self-efficacy indicates PBC for both stores and catalogs and will be influenced to a greater degree with respect to a consumer's confidence in their own ability to switch channels from brick-and-mortar stores and catalogs to the others channels vis-à-vis the Internet. In the case of the Internet, self-efficacy is significant in predicting PBC; however, due to the fact most of the respondents were college students who are very adept at using the Internet its’ degree of influence on PBC is lower than the other two channels. Information was a significant predictor for PBC for both bricks-and-mortar stores and the Internet. Knowledgeable consumers are able to attend to, comprehend, and analyze relevant channel information, as opposed to less knowledgeable consumers (Rosen and Olshavsky, 1987), and hence can engage in channel-switching behavior. Information was the strongest predictor of PBC for the Internet channel, indicating that access to information online is more influential than self-efficacy for consumers wanting to switch channels from Internet to brick-and-mortar stores and catalogs. This has important implications for retailers especially with the growth on consumer-generated-content and other media outlets as consumers now are better informed and availability of information is important to the success of channel-switching. Type of product is an important variable that influences consumer choices among goods. Both hedonic and utilitarian goods offer benefits to the consumer, the former primarily in the form of experiential enjoyment and the latter in practical functionality (Batra and Ahtola, 1991, Hirschman and Holbrook, 1982 and Mano and Oliver, 1993). Hedonic product was a significant predictor for bricks-and-mortar stores and catalogs, whereas utilitarian product significantly influenced PBC variable in the bricks-and-mortar stores. Hedonic products lend themselves to the fun aspects of shopping and both brick-and-mortar stores and catalogs allow consumers to browse more products to enjoy the different experiential qualities of hedonic products. Conversely, Internet is used more than often for utilitarian product shopping where consumers’ main focus is on the attribute and functional differences among products. Hence, it is reasonable to expect that type of product is likely to be an important driver of PBC. Time and money were not significant predictors in any of the three channels. This is clearly a counter-intuitive result. The perception of time available for a task has been shown to impact the shopping outcome. Conceptualized as a secondary purchase cost (Bender, 1964), time has been shown to affect a consumer's choice of shopping strategy (Holman and Wilson, 1982 and Berry and Cooper, 1992) and store patronage intentions (Baker et al., 2002). Similarly, price has always been one of the salient, performative attributes that determine consumer store choice (Blakney and Sekely, 1994 and Arnold et al., 1996). These results could be explained based on the demographic characteristics of the respondents. Most of the respondents were college students and adept in using a variety of channels for shopping; hence, they were not constrained by the parameters of time. Additionally, it can be assumed that most of the college students are financially dependent on their parents and hence their concept of spending money is different than the other respondents (i.e., faculty and staff). This is an important finding, as it can be inferred that for some consumer segments the criteria for switching channels is not based on the availability of resources such as time and money. This has important retail implications. Attitude and subjective norms were the predictors of the channel-switching intention for all three channels. Previous studies on consumers’ behavioral intentions have supported a causal relationship between a favorable attitude and the intention (e.g., Chang et al., 1996 and Shim et al., 2001). In consumer research, attitude has been considered the most important predictor of a person's behavioral intention (e.g., Chang et al., 1996). Yet, this assumption is not supported in the current study, with only the bricks-and-mortar channel reporting a larger regression coefficient value with respect to the channel-switching intention vis-à-vis subjective norms. The findings of this study support a study by Ajzen (1991), which stated that the weight of each belief (i.e., attitude, subjective norms) in influencing a person's behavioral intention may vary based on the nature of the behavior under investigation. Subjective norms suggests that behavior is instigated by ones desire to act as important referent others (e.g., friends, family, or society in general) think one should act, or as these others actually act (Bearden et al., 1989). In other words, subjective norms are the perceived social pressure an individual faces when deciding whether to behave in a certain way. Applied to the focal behaviors, subjective norm reflects consumer perceptions (normative belief) as to whether this channel-switching behavior is accepted, encouraged, and implemented by the consumer's circle of influence. Subjective norms had the larger regression coefficient values with respect to other variables for both catalogs and the Internet. This finding supports Shim and Drake's (1990) findings, which indicated that even though attitude and subjective norms influenced intentions, the subjective norm component was more influential, because of the nature of the new shopping behavior (i.e., individuals attempted to fit in with perceived opinions of important others due to the use of shopping via channel-switching). Thus, it can be inferred that consumer intention to switch channels in case of catalogs and the Internet is influenced more by subjective norms than by attitude. The finding is important especially when viewed with respect to normative beliefs. As stated earlier, subjective norms were negatively influenced by normative beliefs, conversely subjective norms positively influenced channel-switching intention. Thus, it can be inferred that while an individual will not conform to peer/family influence with respect to channel-switching, their channel-switching intention is positively influenced by their social environment. Perceived behavioral control was a significant predictor for both catalogs as well as the Internet. Earlier research has shown that consumers may feel that perceived control is as real as actual control and can enhance the evaluation and value of the experience (Ajzen, 1988, Bateson and Hui, 1987 and Langer and Saegert, 1977) or channel-switching intention. The findings of this study indicate that when switching from catalogs to either store or the Internet, consumers are influenced by the level of perceived control they have over the act, with more control leading to a greater likelihood of channel-switching intention. The result is similar to what has been indicated by earlier studies for innovation adoption (Taylor and Todd, 1995a and Taylor and Todd, 1995b). For the Internet, there is a negative relationship between perceived control and channel-switching intention. The result is similar to the research findings in Lim and Dubinsky's (2005) study of online shopping. It can be inferred that when consumers have higher perceived control over their abilities for switching channels from the Internet to stores or catalogs, they are less likely to switch channels than when they had lower perceived behavioral control over channel-switching.