Fashionably late: Strategies for competing against a pioneer advantage

JBR-08522; No of Pages 8 Journal of Business Research xxx (2015) xxx–xxx

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Journal of Business Research

Fashionably late: Strategies for competing against a pioneer advantage Ali Besharat a,⁎, Ryan J. Langan b, Carlin G. Nguyen c a b c

University of Denver, 2101 S. University Blvd., Denver, CO 80208, United States Willamette University, 900 State Street, Salem, OR 97301, United States University of South Florida, 4202 E. Fowler Avenue, Tampa, FL 33620, United States

a r t i c l e

i n f o

Article history: Received 30 December 2014 Received in revised form 7 August 2015 Accepted 8 August 2015 Available online xxxx Keywords: Pioneer advantage Late entrant Category-based learning Associative learning First-mover Market entry strategy

a b s t r a c t This study delineates the conditions under which a late entrant is able to outperform a pioneer brand by examining the value relevance of alignable and non-alignable attributes. The first experiment shows that the late entrant can surpass the pioneer by adopting either a distinctive (new, non-alignable attribute) or enhancing (improved, alignable attribute) strategy depending on the value relevance of the new attributes. The second experiment provides evidence that pricing cues become instrumental when the value relevance of the late entrant with a distinctive strategy is low. In this context, the findings show that increasing the price of the product counter-intuitively enhances the preferences for the late entrant. © 2015 Elsevier Inc. All rights reserved.

1. Introduction A pioneer, or “first-mover,” advantage refers to the phenomenon in which brands derive a competitive advantage from being first to market. Pioneer brands can gain this advantage when early success in the market helps them establish brand loyalty, create switching costs for consumers, develop broader product lines to preempt competition, and achieve economies of scale (Jakopin & Klein, 2012; Lieberman & Montgomery, 1998; Robinson & Min, 2002). The pioneer advantage can also arise from consumers' cognitive processes, given that the order of entry influences consumers' preferences for, memory of, and learning about a product and its attribute composition (Carpenter & Nakamoto, 1989; Cunha & Laran, 2009; Kardes & Kalyanaram, 1992). Relative to the abundant research highlighting the benefits associated with a pioneering strategy, little work examines the prospects of success among late entrants (Shamsie, Phelps, & Kuperman, 2004; Shankar, Carpenter, & Krishnamurthi, 1998; Usero & Fernández, 2009; Zhou & Nakamoto, 2007). This is surprising, considering that late entrants are more common than early entrants (pioneers) in any given industry. Prior late entrant research offers different views about the appropriate market-entry strategy needed to surpass the pioneer (Carpenter & Nakamoto, 1990; Zhang & Markman, 1998; Ziamou & Ratneshwar, 2003).

⁎ Corresponding author. Tel.: +1 303 871 4344. E-mail addresses: [email protected] (A. Besharat), [email protected] (R.J. Langan), [email protected] (C.G. Nguyen).

One way late entrants can outperform pioneers is to improve the core attributes of the pioneer (hereinafter, an enhancing strategy). For example, Verizon Communications offers a faster Internet connection (4G vs. 3G) and more access points than its competitor, AT&T. The enhancing strategy is effective because consumers can compare attributes along common dimensions (Lee & Lee, 2007; Zhang & Markman, 1998; Zhou & Nakamoto, 2007). According to Ruiz-Ortega and GarcíaVillaverde (2008), “early followers must develop products whose characteristics can be easily compared with the products developed by pioneers” (p. 340). Another way late entrants can surpass pioneers is to add new attributes that are valuable and relevant to consumers beyond the core attributes of the pioneer (hereinafter, a distinctive strategy). For example, Ford recently introduced the hands-free lift-gate sensor to its Escape line of vehicles. This strategy is effective because new attributes draw attention and improve brand attitude (Carpenter, Glazer, & Nakamoto, 1994; Carpenter & Nakamoto, 1990). While extant research offers valuable insight into how late entrants can use the enhancing and distinctive strategies to compete against early entrants, no studies have investigated the conditions under which each strategy can successfully compete against the pioneer. To address this gap, this study examines how the value relevance of the attribute profile can increase a late entrant's market share at the expense of the early entrant. Building on category-based learning (Fiske & Pavelchak, 1986) and associative-learning theory (Janiszewski & Van Osselaer, 2000), the authors explore conditions under which a late entrant may benefit more from either a distinctive strategy or an enhancing strategy. In particular, the authors argue that a distinctive strategy

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Please cite this article as: Besharat, A., et al., Fashionably late: Strategies for competing against a pioneer advantage, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.010

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will outperform an enhancing strategy when consumers perceive the new attributes of a late entrant as equally valuable to the functionality of the focal product as the rest of the existing attributes. Conversely, when the new attribute appears less valuable than the existing attributes, a late entrant will be better off adopting an enhancing strategy. This research also examines how price information factors into consumers' evaluations of late entrants. Drawing on the price–quality literature (Rao & Monroe, 1989; Völckner & Hofmann, 2007), the authors advance the notion that pricing cues significantly influence the effectiveness of market-entry strategies. Results show that late entrants with less valuable, distinctive attributes can counter-intuitively surpass an early entrant if the late entrants' products are priced higher than the pioneer's.

2. Theoretical development and hypotheses 2.1. Pioneering advantage and positioning Prior research shows that the order of entry influences the way people learn about brands and evaluate attributes. A successful early entrant can determine how attributes are valued, shape the ideal combination of attributes for a new product, and become highly representative of a product class (Carpenter & Nakamoto, 1990; Song, Zhao, & Di Benedetto, 2013). These findings are robust across both familiar and unfamiliar products (Kardes & Kalyanaram, 1992). Structural mapping theory (Gentner & Markman, 1997; Markman & Gentner, 1996) suggests that similarity comparisons entail common attributes, alignable differences (i.e., common attributes with different values), and non-alignable differences (i.e., attributes that are unique to each alternative). Thus, late entrants can implement three different strategies to position themselves in the market to compete with an early entrant (Table 1). First, late entrants can adopt an enhancing strategy, by providing superior performance along common, alignable attributes (Kim & John, 2008; Zhang, Kardes, & Cronley, 2002). Samsung Galaxy S5, for example, differentiates itself from the iPhone 5S with a larger screen size and longer battery life. Second, late entrants can implement a distinctive strategy, by adding unique features (i.e., nonalignable attributes) to distinguish themselves from the pioneer brand (i.e., distinctive strategy). Samsung Galaxy S5 took a distinctive position against iPhone 5S by adding unique features such as a heartbeat sensor and water resistance. Third, late entrants can adopt a “me-too” strategy, by duplicating the attribute profile of the pioneer brand. This strategy is often practiced by generic and store brands, which positions their products on the basis of price. Prior studies indicate that, in a comparison process, equivalent common attributes between a pioneer and a follower are not diagnostic in that they fail to provide valuable information to consumers' decision making. This perspective suggests that unless a firm has a price advantage, a me-too strategy is not desirable for competing against a pioneering advantage (Zhang & Markman, 1998). Reinforcing this premise, Carpenter and Nakamoto (1989) assert that the

Table 1 Comparison of product attributes. Brand

Attribute

Common

Alignable Non-alignable

iPhone 5s

Galaxy S5

Multi-touch Proximity sensor Ambient light sensor 4.0-in. screen 1560 mAh battery Gorilla glass

Multi-touch Proximity sensor Ambient light sensor 4.7-in. screen 2800 mAh battery Heartbeat sensor Water resistance

more consumers perceive late entrants as similar to the first mover, the less they will prefer them. Thus, this article focuses only on the effectiveness of the enhancing and distinctive strategies. 2.2. Enhancing versus distinctive strategy: The role of attribute value relevance A late-entrant with an enhancing strategy can overcome the firstmover advantage by providing superior alignable attributes that are easily comparable, identifiable, and justifiable (Kim & John, 2008; Zhang et al., 2002). According to reminding-based category learning (Ross, Perkins, & Tenpenny, 1990), the representation of a new brand depends on its similarity to previous brands. Therefore, only common attributes between pioneer and late entrants are highlighted, whereas unique features of a late-entrant are not easily comparable and thus tend to be ignored (Lee & Lee, 2007; Sanbonmatsu, Kardes, & Gibson, 1991). Therefore, late entrants are better off focusing on the performance of alignable differences, rather than adding distinctive attributes to overcome early entrants (Zhang & Markman, 1998). Nevertheless, a cursory review of some examples of late entrants reveals that a distinctive strategy can be effective. While early entrants of pain killers emphasized fast relief of pain, Tylenol positioned itself as a painkiller that caused no adverse side effects on the stomach (a nonalignable attribute). Similarly, unlike early entrants in the MP3 market that promoted the memory capacity of their players, iPod chose to compete on the basis of its non-alignable features (i.e., click-wheel function, firewire cable, design elements). A common property among each of these examples is the value relevance of the new attributes to the functionality of the focal product. To elucidate how consumers evaluate a late entrant with valuerelevant, non-alignable attributes, this research uses two theoretical approaches: associative-learning theory (Janiszewski & Van Osselaer, 2000; Van Osselaer & Janiszewski, 2001) and category-based learning theory (Fiske & Pavelchak, 1986). Associative-learning theory explains how consumers learn the associations between product features and product benefits. Research shows that consumers associate common attributes with the pioneer more strongly than with the late entrant. Conversely, consumers develop stronger associations between the unique attributes of late entrants relative to the pioneer brand. It is reasoned that consumers strategically allocate attention to different cues to protect previously learned associations (Medin & Edelson, 1988). Because unique attributes do not conflict with the previously learned common attributes, they draw people's attention and become a significant predictor of a brand's performance when they are valuable (Cunha & Laran, 2009). Alternatively, category-based learning theory posits that a new stimulus is learned through a comparison process with existing knowledge (Fiske & Pavelchak, 1986). If a new stimulus matches the prevailing category knowledge, people quickly retrieve and apply that knowledge when learning the new stimulus. However, if a new stimulus does not match the existing category knowledge, people tend to evaluate the new information in a piecemeal fashion. Because a new product often comes with both matching (i.e., alignable) and mismatching (i.e., non-alignable) features, consumers use both category-based and piecemeal processing when learning new information (Meyers-Levy & Tybout, 1989). Thus, consumers may evaluate consistent information (e.g., alignable attributes) quickly by retrieving and applying category knowledge. For discrepant information (e.g., nonalignable attributes) in which judgment knowledge is not readily available, consumers need to consider and evaluate each attribute and then make a judgment accordingly. Drawing on these theories, the authors propose that consumers make an entirely different decision if they assess non-alignable attributes according to the benefit or value, rather than making a direct comparison with the attributes of early entrants. The reason is that consumers often use product attributes as cues to predict performance

Please cite this article as: Besharat, A., et al., Fashionably late: Strategies for competing against a pioneer advantage, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.010

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(Feldman & Lynch, 1988; Van Osselaer & Alba, 2000). According to Kardes and Kalyanaram (1992), novel attributes draw attention, become more salient in inter-brand comparisons (Dhar & Sherman, 1996), and receive greater weight in preference judgments (Mukherjee & Hoyer, 2001). In support of this argument, Ziamou and Ratneshwar (2003) show that explicit comparisons can backfire because they facilitate the assimilation of the new attribute to the existing attributes. Gatignon and Xuereb (1997) also show that the correlation between the similarity of the new entrant to the pioneer and competitive advantage in the market is significantly negative. Finally, Simonson, Carmon, and O'Curry (1994) argue that the presence of a valuable, unique feature serves as a signal to consumers about the attractiveness of an alternative. Thus, the value relevance of the new attribute moderates the market share difference between the enhancing and distinctive strategies used by a late entrant. H1a. When consumers do not perceive the new attribute as valuable, the enhancing strategy will take away more market share from the pioneer than the distinctive strategy. H1b. When consumers perceive the new attribute as valuable, the distinctive strategy will take away more market share from the pioneer than the enhancing strategy.

2.3. The effects of relative price on a late entrant with distinctive strategy Consumers often lack the time, motivation, or knowledge to judge a product's quality. In these instances, consumers rely on available cues (e.g., heuristics) such as the product's country of origin (Chao, 1998), brand name (Teas & Agarwal, 2000), and price (Rao & Monroe, 1989) to simplify their quality judgment task (Simonson et al., 1994). Consumers are able to distinguish between high- and low-diagnostic cues, and according to previous research, price is a more diagnostic cue than other extrinsic cues in determining product quality (Herr, Kardes, & Kim, 1991; Lichtenstein, Ridgway, & Netemeyer, 1993). According to the evaluability hypothesis, the price–quality cue impacts consumers' preference regardless of their level of experience (Hsee, 1996; Rao & Monroe, 1989). The influence of price information on product quality evaluations also depends on the value relevance of the attributes to consumers. When the late entrant improves the existing attributes of the pioneer (e.g., enhancing strategy), consumers may justify spending a premium price due to the relative comparison of alternatives. However, this logic may not necessary work in the case of a distinctive strategy, as new attributes have been added to the existing attribute profile of the pioneer. Therefore, consumers may evaluate the new attribute information piece by piece, rather than relying on category-based information processing (Meyers-Levy & Tybout, 1989). Research shows that when a new attribute is irrelevant to the functionality of a focal product (e.g., Vitamin shampoo), consumers have greater preference for a brand that has a higher price (Carpenter et al., 1994). This is because consumers use price information as a cue to determine the quality of the new product with a less valuable attribute when the information cannot be inferred elsewhere. In the same vein, Chang and Wildt (1996) argue that price affects the perception of products in a cognitively different way than other available information. When differences in product attributes are not related to generating value, consumers become heavily dependent on price to evaluate the quality of products. In contrast, when the attribute information is relevant to value, consumers become less dependent on price for brand evaluation. Accordingly, when consumers perceive non-alignable attributes of a late entrant as valuable, they should prefer the differentiated late entrant (with superior performance on nonalignable attributes), independent of price point. Therefore, the market share gain of a late entrant using a distinctive strategy is a function of the value relevance of the new attribute and the price premium.

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H2a. When consumers do not perceive the new attribute as valuable, the late entrant will earn more market share at the expense of the pioneer when charging a higher rather than a lower price. H2b. When consumers perceive the new attribute as valuable, the late entrant will earn greater market share at the expense of the pioneer, regardless of the price level.

3. Experiment 1 Experiment 1 tests the prediction that the success of an enhancing versus a distinctive strategy depends on the value relevance of the new attribute. 3.1. Pretest and stimuli development Olive oil served as the familiar shopping good for this experiment so that the participants could easily relate to the product attributes. After consulting with three local grocery store managers, the authors identified eight attributes for olive oil (i.e., country of origin, clarity, density, extra virgin, color, brightness, vitamin E, and harvest date). An internet survey administered via Amazon Mechanical Turk (hereinafter MTurk), an online crowdsourcing marketplace of human capital validated for conducting experiments and surveys (Buhrmester, Kwang, & Gosling, 2011; Mariconda & Lurati, 2015; Paolacci, Chandler, & Ipeirotis, 2010), was used to gather data. The data collected are classified as a convenience sample because MTurk does not verify respondents' information. In order to participate, respondents must have experience shopping for groceries, have purchased olive oil within the last 3 months, be familiar with olive oil and its attributes, and have a 100% approval rating (i.e., participants never had their work rejected by a requester). We made a conscientious effort to ensure the responses were from actively engaged participants. First, we removed subjects that took too little or too long (±3 standard deviations from the average time) to review the stimulus and/or to complete the survey. Second, we removed any participants that failed to correctly answer attention check questions embedded within the survey near the beginning and middle of the sections (Oppenheimer, Meyvis, & Davidenko, 2009). As a result, seven responses were removed from the analysis, leaving a total of 51 qualified responses. The sample consisted of respondents based in the United States with an average age of 31.8 years (SD = 9.03) with 62% being male. Respondents had diverse ethnic backgrounds (52% Caucasian, 26% Asian, 5% African-American, 5% Hispanic, and 12% other), and had incomes ranging from $15,000 to $100,000. For all completed surveys, respondents were compensated 40 cents. Subjects were asked to imagine that they were considering the purchase of a 6.7-oz bottle of olive oil for $10. The authors chose a fictitious brand name for the bottle of olive oil to avoid any influence of the brand on product evaluations. Participants saw the eight attributes in a random sequence and indicated the extent to which each attribute seemed valuable in judging the quality of olive oil on a 7-point asymmetrical scale (1 = not at all valuable, 7 = extremely valuable). Participants' familiarity with the product category measured on a 7-point scale (1 = not familiar at all, 7 = extremely familiar) was high (M = 6.09, SD = .63). Pretest results also revealed that extra virgin (M = 5.29) had the highest value, but this value was not significantly different than the values assigned to country of origin, color, clarity, and density (M = 4.96, M = 4.93, M = 4.91, M = 4.88, respectively; ts b 1.4, ps N .05). Thus, the authors randomly chose four of the five attributes (country of origin, clarity, extra virgin, and density) to represent the valuable attributes in the main study. Conversely, the harvest date was the least valuable attribute for olive oil (M = 2.46), followed by brightness (M = 2.61) and vitamin E (M = 2.73). While the perception of value among these three attributes did not significantly vary

Please cite this article as: Besharat, A., et al., Fashionably late: Strategies for competing against a pioneer advantage, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.010

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(ts b 1, ps N .05), significant differences in value perception existed between this set of attributes and the former set (ts N 3, ps b .01). As a result, the researchers selected brightness and vitamin E from the set of three attributes to denote the non-valuable attributes in the main stimuli. Because of multiple comparisons among attribute values, the Bonferroni method was chosen to adjust the confidence level. 3.2. Data collection and sample Experiment 1 was conducted online using MTurk. Similar to the requirements outlined in the previous section, respondents were required to be pre-qualified to participate in the survey. A total of 189 respondents met these standards. However, 22 responses were removed due to failed attention checks or lack of engagement. Thus, a total of 167 useable responses were included in the analysis. The sample consisted of respondents based in the United States with an average age of 30.66 years (SD = 7.23) with 54% being male. The sample reflected a range of ethnicities (57% Caucasian, 22% Asian, 4% African-American, 3% Hispanic, and 14% other) with incomes ranging from $15,000 to $100,000. For all completed surveys, respondents were paid 40 cents. 3.3. Design and stimuli This experiment is a 2 (value relevance of the attribute: low vs. high) × 2 (late entrant strategy: enhancing vs. distinctive) betweensubject factorial design. In each condition, participants were presented with three brands, A, B, and C. Brand A was described as a successful pioneer and was presented more frequently than the other brands (Kardes & Kalyanaram, 1992; Zhang & Markman, 1998), while brand B served as a distractor late entrant. Brands A and B stayed the same across conditions. Brand C, a late entrant, varied on the strategy employed and the value relevance of its attributes. Brand C was objectively superior to brands A and B; the brand either enhanced one of the existing attributes of the pioneer (e.g., density was improved from low to high) or added a new attribute to the existing attributes profile (e.g., the term “extra virgin” was added). According to Meyers-Levy and Tybout (1989, p. 48), companies often “introduce new products that differ from existing alternatives only on one attribute.” Consequently, the manipulation was limited to one attribute to avoid the possible confounding effects associated with multiple attributes (Sujan & Bettman, 1989) and to maintain ecological validity. Using the attribute values obtained from the pretest, the authors ensured that participants perceived brand A (the pioneer) and brand B (the distractor late entrant) as equally attractive in the pairwise choice. The distractor late entrant (brand B) was added as a manipulation check to ensure that the pioneer (brand A) was always preferred in the choice set. Both brands (A and B) were represented using three attributes; however, brand A was presented with a higher attractiveness value on one attribute than brand B, while brand B always had a higher attractiveness value on another attribute than brand A. The attributes that varied between the two brands were chosen from a list of equally valuable pretested attributes. The third attribute, country of origin, was held constant across brands. All the design elements (i.e., brand names and order of attributes) were fully randomized to ensure that the results would hold regardless of which brand/attribute was being manipulated. In addition, the compositions of valuable and non-valuable attributes in the set were randomized. Appendix A presents sample stimuli for the four experimental conditions. 3.4. Procedure Participants were informed that they would evaluate the attributes of different brands of olive oil using a three-section questionnaire. Participants were required to finish all three consecutive sessions to be eligible for the financial compensation. They first read a brief description about the product class and its attributes. Then, they learned that brand

A was the successful pioneer and saw the attributes information in a table format. To ensure participants reviewed the attributes descriptions and values carefully, respondents were asked to evaluate the brand on a 7-point semantic differential scale (1 = unsatisfactory, unfavorable, bad; 7 = satisfactory, favorable, good) and to indicate their confidence in their judgment (Zhou & Nakamoto, 2007). Next, participants took a short filler task to refresh the short-term memory effects of brand evaluations. In Section 2, participants were reminded that brand A was the same brand they saw previously and were presented the attributes information of brand B along with those of brand A in a table format. Similar to the previous section, the participants again read the attribute information and evaluated both brands on the same scale. Then, they took another short distracter task to refresh the short-term memory effects of brand evaluations. Section 3 introduced brands A and B as the brands participants saw previously and presented the attributes information about a new brand, C. The attributes of brand C were configured to represent either the enhancing or distinctive strategy given the manipulation condition. Finally, participants responded to questions related to the measurement of the dependent variable, value perceptions of attributes, manipulation checks, level of involvement with the experimental task, and demographic information. 3.5. Dependent variable A sliding scale next to each brand measured preference judgments by recording the amount of points participants wanted to allocate to each alternative. The online response format only allowed participants to allocate 100 points across brands A, B, and C. Research shows that this measure can serve as a proxy for the market share distribution among brands (Carpenter & Nakamoto, 1989). Then, to measure the market share (dis)advantage of the late entrant strategies in comparison with the early entrant, the difference in preference between the late entrant and early entrant in the choice set (i.e., Δ preference = number of points assigned to brand C–brand A) was calculated and used as the dependent variable. 3.6. Results 3.6.1. Manipulation checks All manipulations were successful. First, while the perception of value among non-valuable attributes (ts b 1, ps N .05) and valuable attributes (ts b 1, ps N .05) did not vary significantly, significant differences existed in value perception between these two sets of attributes (ts N 3, ps b .01). Second, successful manipulation of the early entrant was established because participants always preferred brand A to the distractor late entrant, brand B, across all conditions (Mbrand A = 34.16 vs. Mbrand B = 11.83; t(1, 163) = 7.52, p b .05). 3.6.2. Support for H1 We performed a 2 (value relevance of the new attribute: low vs. high) × 2 (late entrant strategy: enhancing vs. distinctive) analysis of variance, with the difference in preference between the late and early entrants as the dependent variable. The results revealed a significant main effect of value relevance of the new attribute (F(1, 163) = 4.26, p b .05) and a significant interaction between value relevance of the new attribute and late entrant strategy (F(1, 163) = 9.53, p b .05), as Fig. 1 illustrates. Neither covariate (i.e., product familiarity and involvement) significantly interacted with the main factors or had significant effects on the dependent variable. Follow-up contrasts showed that the difference in preference between the late entrant with enhancing strategy and the early entrant (Menhanced late entrant–early entrant = 20.82) was significantly greater than the difference in preference between the late entrant with distinctive strategy and the early entrant (Mdistinctive late entrant–early entrant = 8.67)

Please cite this article as: Besharat, A., et al., Fashionably late: Strategies for competing against a pioneer advantage, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.010

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Weilbaker (1988) suggested method, the high- (low-) pricing strategy was determined with a 95% confidence interval by taking one standard deviation above (below) the average price. The results suggested the high- and low-pricing strategies as $8.68 and $3.44, respectively.1 4.2. Data collection and sample Data for this experiment were gathered using MTurk, with identical pre-qualification requirements used in Experiment 1. A total of 171 participants with internet protocol (IP) addresses within the United States were recruited to take part in an online survey, but 15 were excluded due to failed attention checks or lack of engagement, leaving 156 usable respondents (Mage = 27.17 years, SD = 10.51; 56% male). The sample had diverse ethnic backgrounds (68% Caucasian, 9% Asian, 8% AfricanAmerican, 6% Hispanic, and 9% other) and income ranges ($25,000 to $100,000). For all completed surveys, respondents were paid 50 cents. 4.3. Design and stimuli

Fig. 1. Change in preference between pioneer and late entrants as a function of strategy and value relevance. *DV: Δ preference = number of points assigned to late entrant − early entrant. Positive value indicates more preference for late entrant.

This experiment is a 2 (value relevance of the new attribute: low vs. high) × 2 (pricing strategy for the distinctive late entrant: low vs. high) between-subject factorial design. Similar to experiment 1, Brands A and B were equally attractive. But, brand C varied on the value relevance of the new attribute and the level of the pricing strategy. The name of the brands, the order of attributes presentation, and the compositions of the valuable and non-valuable attributes in the set were fully randomized. Appendix B shows sample stimuli for the four experimental conditions. 4.4. Procedure

when the value relevance of the new attribute was low (F(1, 163) = 5.96, p b .05). However, the reverse pattern occurred when the value relevance of the new attribute was high, such that the difference in preference between the late entrant with distinctive strategy and the early entrant was significantly greater than the difference in preference between the late entrant with enhancing strategy and the early entrant (Mdistinctive late entrant–early entrant = 19.18 vs. Menhanced late entrant–early entrant = 6.34; F(1, 163) = 6.25, p b .05). Thus, H1a and H1b were supported.

The pioneer advantage was manipulated similar to the procedure outlined in Experiment 1 using the three-section questionnaire, with the exception that brand C always maintained a distinctive strategy. Participants also responded to the same set of questions used in the previous experiment for the measurement of the dependent variable, value perception of attributes, manipulation checks, and demographic information.

3.7. Discussion

4.5. Results

This experiment demonstrates that the type of strategy late entrants adopt significantly affects their ability to compete with and overcome a pioneer brand. The effectiveness of one strategy over another depends on the value relevance of the alignable attributes. Specifically, when the value of the non-alignable attributes is low, the enhancing strategy will capture greater market share from the pioneer brand than the distinctive strategy. Conversely, when the value of the non-alignable attributes is high, the distinctive strategy is more effective than the enhancing strategy. These findings, while not fully generalizable due to the characteristics of the sample, shed light on the importance of late entrants' attribute profile and the conditions under which they can improve their strategic position.

4.5.1. Manipulation checks First, the value ratings of product attributes confirmed that no significant differences existed in the perceptions of value among non-valuable attributes (ts b 1, ps N .05) and among valuable attributes (ts b 1.6, ps N .05). However, significant differences existed in value perceptions between these two sets of attributes (ts N 2.4, ps b .01). Second, on a 7-point scale (1 = very affordable, 7 = very expensive), participants in the high-price condition indicated that the price of the product was significantly higher than those in the lowprice condition (Mhigh price = 5.12 vs. Mlow price = 3.76; F(1, 154) = 5.38, p b .05). Finally, the results showed that brand A, as an early entrant, was always preferred to the distractor late entrant, brand B, across all conditions (Mbrand A = 27.95 vs. Mbrand B = 10.08; t(1, 154) = 6.84, p b .05). Thus, all manipulations were successful.

4. Experiment 2 Experiment 2 examines the role of price and the value relevance of a new attribute of the late entrant with the distinctive strategy. 4.1. Pretest and stimuli development The purpose of this pretest was to determine two levels of pricing strategy (i.e., low and high) for the focal product. A group of undergraduate students (n = 20) were provided with descriptions of the olive oil and considered the purchase of a 6.7-oz bottle from a grocery store. Then, participants indicated a reasonable price for the product on a sliding scale, ranging from $1 to $15. Adopting Urbany, Bearden and

4.5.2. Support for H2 A 2 (value relevance of the new attribute: low vs. high) × 2 (pricing strategy for the distinctive late entrant: low vs. high) analysis of variance was conducted, with the difference in preference between the late entrant and early entrant as the dependent variable. The results showed a significant main effect of value relevance of the new attribute (F(1, 152) = 4.91, p b .05) and a significant main effect of the pricing strategy (F(1, 152) = 4.52, p b .05). Importantly, the interaction between value relevance of the new attribute and pricing strategy for the distinctive late entrant was significant (F(1, 152) = 6.72, p b .05), as Fig. 2 depicts. No significant effect of covariates was observed.

Please cite this article as: Besharat, A., et al., Fashionably late: Strategies for competing against a pioneer advantage, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.010

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Fig. 2. Change in preference between the distinctive late entrant and the pioneer as a function of price and value relevance. *DV: Δ preference = number of points assigned to distinctive late entrant − early entrant. Positive value indicates more preference for distinctive late entrant.

Additional planned contrasts showed that under high value relevance for the new, non-alignable attribute, no significant difference existed in preferences between the distinctive late entrant and the early entrant for the low-pricing (Mdistinctive late entrant–early entrant = 11.31) and highpricing (Mdistinctive late entrant–early entrant = 5.24) strategies (F(1, 152) = 2.81, p N .05). However, the difference in preference between the distinctive late entrant and the early entrant was significantly greater for the high-pricing strategy (Mdistinctive late entrant–early entrant = 20.52) than for the low-pricing strategy (Mdistinctive late entrant–early entrant = 1.63) when the value relevance of the new attribute was low (F(1, 152) = 8.39, p b .05). Thus, H2a and H2b were supported. 4.6. Discussion Consistent with the findings from Experiment 1, Experiment 2 demonstrates that the perceived value of non-alignable attributes has a significant effect on the ability of late entrants to gain market share from pioneer brands. Experiment 2 also provides strong support for the effect of pricing cues on market-entry strategies. Despite the limited generalizability associated with the nature of the data, interesting findings emerged for this experiment. In particular, the study shows that when consumers place a high value on the non-alignable attributes, price cues have no effect on the effectiveness of the distinctive strategy. However, when the value of the non-alignable attributes is low, a late entrant priced higher than the pioneer can garner significantly more market share than a lower priced late entrant. 5. General discussion and conclusions This research contributes to the first-mover literature by examining the attribute profile of late entrant products and investigating how different late entrant strategies (distinctive vs. enhancing) can successfully compete against early entrants. This article is the first to elucidate the effectiveness of each late entrant strategy by examining the value relevance of alignable and non-alignable attributes. The two experiments show that late entrants may benefit from either a distinctive strategy (i.e., introducing new attributes to the existing attributes of the pioneer) or an enhancing strategy (i.e., improving the existing attributes of the pioneer), depending on the value relevance of the new attributes.

Prior studies indicate that late entrants with superior performance in non-alignable attributes are not favored because their attributes are incomparable to early entrants (Ruiz-Ortega & García-Villaverde, 2008). The present results qualify this position by showing that a strategy that competes against a pioneer brand on enhanced, alignable attributes is indeed more effective than non-alignable attributes, when the nonalignable attributes are not valued. However, when products possess non-alignable attributes that consumers perceive as valuable to the functionality of the product, a distinctive strategy can seize greater market share from a pioneer brand than an enhanced strategy. These findings answer Finney, Lueg, and Campbell's (2008) call for research to explore the outcomes associated with multiple firms following an early entrant to market. In addition, this research sheds additional light on market-entry strategies by examining the role of price in the context of nonalignable attributes. By extending the work of Carpenter et al. (1994) into the domain of market entrant strategies, this research finds that when consumers value a non-alignable attribute, price differentials do not affect the ability of a late entrant to seize market share from a pioneer brand. However, when consumers do not value the non-alignable attributes of a late entrant, higher-priced products are able to gain significantly more market share from a pioneer brand than lower-priced products. This evidence indicates that pricing cues only become relevant when consumers do not value the non-alignable attribute. These results also extend the work of Lowe and Alpert (2010, p. 846), who maintain that “reference price perceptions are shaped by what the pioneer does, rather than what the follower does.” A consideration of the present findings would restrict this view to followers that choose to compete on the basis of common or alignable attributes. Price perceptions can be shaped by late entrants that compete against pioneer brands on the basis of non-alignable attributes, especially when these attributes are not valued. Managers of late entrant brands gain meaningful insights from the findings of this research. Despite empirical evidence that cautions late entrants from competing against pioneer brands head on (Jakopin & Klein, 2012), results from Experiment 1 suggests that late entrant brands can successfully compete against pioneer brands if they enhance alignable attributes. Furthermore, these results underscore the importance of investing in innovation, as late entrants that are able to develop highly valued, non-alignable attributes stand to acquire the most market share from pioneer brands. The results from Experiment 2 suggest that when failed marketing research or evolving consumer needs put brands in a position such that their non-alignable attributes are not valued, they should consider increasing the price of their product in new markets. In other words, late entrants whose attributes are irrelevant to consumers should have a relatively higher price than the early entrant, because a low price will further undermine consumers' evaluations of those attributes.

5.1. Limitations and directions for future research The study's findings and conclusions should be assessed in light of the limitations. First, it is important to note that the results were derived from a controlled, scenario-based experimental setting, with data collected using MTurk. Recognizing the potential concerns about the accuracy of self-reported data, the possibility of repeat participants and issues related to selection bias within MTurk, careful attention was given to the identification of appropriately qualified subjects who possessed the pre-requisite knowledge of and experience shopping for the target products. Although the results of Experiment 1 were replicated in Experiment 2, the results were nevertheless obtained using a nonprobabilistic sampling method and may not necessarily generalize to consumers outside of the MTurk community. Furthermore, the findings may only be generalizable to consumers purchasing low involvement, low priced products. Thus, future investigations should consider the

Please cite this article as: Besharat, A., et al., Fashionably late: Strategies for competing against a pioneer advantage, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.010

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extent to which the present findings hold using probabilistic sampling methods across different product categories. Second, prior research shows that the effectiveness of entrance strategies varies across stages of the product life cycle (Lambkin, 1988). Additional research could explore how successful enhancing and distinctive strategies are against pioneer brands throughout the product life cycle. Do distinctive strategies become more effective as product novelty declines? Or do more mature markets accentuate the relative advantage of an enhancing strategy? Expanding the price range to an exaggerated price with one standard deviation above and below the average price, as Urbany et al. (1988) show, provides unique insights. However, this method limits the ability to capture individual perceptions of what constitutes “high” and “low” prices. Future research may wish to consider alternate approaches to manipulate price (Adaval & Monroe, 2002; Lee & Zhao, 2014). Subsequent studies may, for example, choose to establish price points by asking respondents to indicate the highest and lowest prices they would pay for the product; the average off those prices would serve as a proxy for the high and low prices. Finally, it is worth noting that the market share taken from the pioneer brand using an enhancing strategy in Experiment 1 (M = 20.82) is nearly identical to the market share acquired by a late entrant that had a relatively higher price and lower attribute value in Experiment 2 (M = 20.52). The separation of studies does not allow for direct comparisons; however, the similarity in values triggers additional questions. For example, if firms do not have the capacity to enhance an alignable attribute, can they be equally successful in acquiring market share from pioneer brands by introducing a higher-priced product with an irrelevant non-alignable attribute?

(continued)

Appendix A. Stimuli: Experiment 1

References

Late entrant with an enhancing strategy: Valuable attribute Attributes Country of origin Clarity Density

Brand A Spain High Low

Brand B Spain Low High

Brand C Spain High High

Late entrant with an enhancing strategy: Non-valuable attribute Attributes Country of origin Vitamin E Brightness

Brand A Spain High Low

Brand B Spain Low High

Brand C Spain High High

Late entrant with a distinctive strategy: Valuable attribute Attributes Country of origin Clarity Density Extra Virgin

Brand A Spain High Low –

Brand B Spain Low High –

Brand C Spain High Low Yes

Late entrant with a distinctive strategy: Non-valuable attribute Attributes Country of origin Clarity Brightness Vitamin E

Brand A Spain High Low –

Brand B Spain Low High –

Brand C Spain High Low Yes

Appendix B. Stimuli: Experiment 2

Late entrant with a distinctive strategy: Valuable attribute–lower price Attributes Country of origin Price

Brand A Spain $6.06

Brand B Spain $6.06

Brand C Spain $3.44

7

Late entrant with a distinctive strategy: Valuable attribute–lower price Clarity Density Extra virgin

High Low –

Low High –

High Low Yes

Late entrant with a distinctive strategy: Valuable attribute–higher price Attributes Country of origin Price Clarity Density Extra virgin

Brand A Spain $6.06 High Low –

Brand B Spain $6.06 Low High –

Brand C Spain $8.68 High Low Yes

Late entrant with a distinctive strategy: Non-valuable attribute–lower price Attributes Country of origin Price Clarity Brightness Vitamin E

Brand A Spain $6.06 High Low –

Brand B Spain $6.06 Low High –

Brand C Spain $3.44 High Low Yes

Late entrant with a distinctive strategy: Non-valuable attribute–higher price Attributes Country of origin Price Clarity Brightness Vitamin E

Brand A Spain $6.06 High Low –

Brand B Spain $6.06 Low High –

Brand C Spain $8.68 High Low Yes

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