This article addresses the potential of reputable brands to overcome the lack of tangibility that characterizes the process of e-commerce. In a sequential argument, the authors propose that (1) the brand becomes more important in online than in offline channels, as a consequence of the intangibility or lack of physical contact in online purchasing processes; (2) the limitations associated with the need for touch and the lack of access to the physical product during the buying process does not have equal importance across all product categories; and (3) the role of the brand in online channels thus is more relevant if the product category is associated with a higher need for touch. To provide empirical evidence regarding the hypotheses, we performed an experiment that combined three treatments: (1) leader versus non-leader brand, (2) online versus offline channel, and (3) product category with higher versus lower need for touch. We show that the most recognized brands exert a positive effect on product evaluations, regardless of the technical characteristics and other objective product attributes. This advantage may be greater in online channels, though only for product categories for which the lack of physical contact with the product during the purchase process is an important limitation. In such cases, brand associations can compensate for intangibility during purchase.We also confirm that the product categories differ in their level of need for touch and the extent to which consumers desire physical contact with the product during the buying process. These results demonstrate that building strong brands is a key competitive advantage for manufacturers. Brand reputation becomes even more crucial when selling products in electronic channels, at least if the product itself entails a greater need for touch prior to purchase. For such products, strong brands can make up for the intangibility of e-commerce, so this effort represents a key competitive strategy in such channels. Moreover, leading brands can leverage their competitive advantage to enhance their performance in the increasingly prominent realm of e-commerce. E-retailers need to make careful decisions regarding the configuration of the assortment, taking into account the nature of the product category. They should strengthen their focus on developing highly recognizable brands, because the lack of physical contact is an important purchase inhibitor in this shopping channel. However, the brand criterion may be less important if the choice between online and offline shopping is not particularly affected by the opportunity to touch or feel the products.

Multichannel sales strategies are now very popular owing to the prevalence of the Internet, which makes it much easier for manufacturers to engage in direct sales. Because direct channels, including catalogs and the Internet, compete against, substitute for, or complement conventional retail channels, finding the best way to utilize them in conjunction with retail channels continues to be a challenge for many firms. Specifically, multiple channels give rise to channel conflict when the channels compete for almost the same market with substitutable products. To avoid this channel conflict, some manufacturers, such as Daimler, Nikon, and Rubbermaid, have used the Internet as a medium to provide information about their products and/or to point users of the Internet to the nearest retailer carrying the product, but without offering the product for sale directly over the Internet. Dell, which is arguably the most successful Internet marketer in the personal computer market, opened kiosk locations in shopping malls across the US from 2002, and has operated full-scale manufacturer-owned stores since late 2006. However, in 2008, Dell shut down all of its kiosks in the US and instead expanded into retail stores, such as Wal-Mart and Best Buy. Furthermore, IBM redirects orders taken at ibm.com to its distributors in an attempt to mitigate the conflict, and HP gives their intermediaries a commission fee for orders placed online. In the context of multichannel management, the question of to what degree a manufacturer should set a direct price to coordinate all channels has commanded significant attention from both academic and practical viewpoints. However, marketing research addressing when a manufacturer should determine the direct price is missing from the existing literature, although it is a critical practical issue for manufacturers that adopt a multichannel sales strategy. Given the current status of the literature, this paper investigates the optimal timing of pricing by a manufacturer managing two types of marketing channel, a retail channel and a direct channel, using a dynamic noncooperative game framework. Traditionally, analytical marketing models describing channel conflict between these two channels examine price competition where the retail and direct prices are established simultaneously. In contrast to this conventional approach, our model demonstrates that such a simultaneous price competition never arises if the manufacturer and retailer can choose not only the level of price, but also the timing of pricing. If the manufacturer has sold products wholesale to a retailer presuming that the manufacturer will set the direct price before the retailer prices, the retailer accelerates the timing of retail pricing prior to the direct price setting by the manufacturer. Our findings suggest that the manufacturer should post the direct price before or upon, but not after, selling products wholesale to a retailer. Such upfront posting of the direct price not only constitutes the unique subgame perfect Nash equilibrium (SPNE) of the noncooperative game between channel members, but also maximizes profits for the manufacturer. The logic behind this outcome is as follows. If the manufacturer determines the Despite the significant amount of marketing research on multichannel management, an overview of the literature suggests that research incorporating the choice of optimal pricing timing into channel operation issues is completely lacking, despite the fact that the timing for posting the direct price is a crucial problem for manufacturers. That is, the existing marketing literature treats the order of moves of channel members as exogenously given, which is rather surprising because each member is expected to maximize its own profits in the context of a standard price-setting game. From a multichannel management perspective, this paper addresses the issue of the endogenous order of moves by adopting the established observable delay game framework (e.g., Hamilton and Slutsky 1990). Therefore, it is worth noting that the present paper is the first to introduce the idea of endogenous choice of decision timing in the field of marketing research. Our findings imply that the addition of a direct channel and the posting of a direct price after the sale of a substantial number of products through a traditional retail channel—a common multichannel strategy in practice—is inferior from the viewpoint of overall profit maximization. If a manufacturer employs such a strategy, it fails to coordinate the marketing channels and to maximize the channel profits. Indeed, as noted at the beginning of this section, many dominant manufacturers in various industries have withdrawn their direct channels. Our model effectively explains such real cases, providing useful managerial insights for business practitioners.

Many measurement methods for understanding consumers’ acceptable price range have been developed. Among these, Price Sensitivity Meter (PSM) is one of the most popular. It has been regarded as a convenient research method because of the ease of data collection and data processing. In particular, PSM requires only four questions to determine the price range. Nevertheless, it also has some problems from a theoretical viewpoint. The purpose of the present research is to develop a new price research method for measuring consumers’ acceptable price range. In particular, applying survival analysis to data prepared for PSM, Japanese consumers’ price acceptance ranges for several categories were estimated.

Preference Reversal and Discounting Everyone has experienced “procrastination”, for example, in the context of diet, quitting smoking, doing homework, etc. Despite a desirable goal in the long term perspective, people often divert their course for a minor gain of immediate future. “Marriage blue” is a typical example of such preference reversal along a temporal dimension. Wedding seems so desirable when it is planned. But as the wedding date approaches, one starts to focus minor issues in reality and becomes hesitant to get married. Such preference reversal along a time dimension has been considered as irrational behavior, and is often referred to as present bias or time inconsistency. Fields of Behavioral Economics and Behavioral Decision Theory try to explain the phenomenon using “discounting” along a time axis. Previous research has shown three well-known properties of “discounting over time”. (1) Invalidity of exponential discounting A discount rate is not constant, but decreases rapidly at first and later more gradually. (2) Amount effect A discount rate is larger for a small amount of money than for a large amount. (3) Sign effect A discount rate is larger for gain than for loss. The first property is used to explain “procrastination”. Exponential discounting, which assumes a constant discount rate over time, cannot explain the phenomenon because two utility curves, one for a large gain in further future and the other for a small gain in near future, never cross each other over time. On the other hand, hyperbolic discounting, with a declining discount rate over time, permits the crossing, thereby explaining “procrastination”. How about “marriage blue”? Unfortunately, neither exponential nor hyperbolic discounting can explain this phenomenon. By interpreting the initial desirability as gain and the minor issues as loss, the sign effect cannot explain the reversal, either. Perhaps more complicated discounting models are necessary. However, there exist many criticisms and complications for introducing complex discounting models. Construal level theory (CLT) with a minor twist can explain “marriage blue” in a simple manner, as will be shown. What is Construal Level Theory (CLT) ? CLT, which has been receiving increasing attention in Social Psychology and Consumer Behavior Studies, posits that people’s evaluation toward items and incidents differs by the psychological distance between oneself and the object. When the distance is close, people mentally construe the object in terms of low-level, detailed, and contextualized features. In contrast, when the distance is far, they construe the same object in terms of high-level, abstract, and stable characteristics. Such difference in mental construal leads to different evaluation and behavior, and thus preference reversal. Fiedler (2007) discusses different types of psychological distances, including temporal, spatial, social, certainty-related, informational, experiential, affective, and perspective distances. Using these general notions of “distance”, CLT becomes a powerful tool to explain various preference changes. Along social distance, choice of souvenir can differ whether it is for a work supervisor or for a family member. Along spatial distance, excitement toward bungee jump in the birth country of New Zealand when leaving airport in Tokyo can change to uneasiness when arriving at Oakland airport. Along experiential distance, an advanced medical treatment, which seems attractive from an outsider’s viewpoint, can change to anxiety for risk and side effect when you are the one to receive. Because “discounting” is used to explain preference reversal with varying time distance, it is rather natural to introduce this idea into CLT with appropriate adaptation. First, discounting applies not only to time distance but also to psychological distance in general. Then, the second property, “the difference in discount rates between low versus high amount of money” shall be translated to “the difference in discount rates between low versus high construal levels”. This conceptualization, which I refer to as GCLT, can explain “marriage blue” in a straightforward manner, when the high and low construal levels of wedding are interpreted, respectively, as the initial motive and the detail issues. Generalized Construal Level Theory (GCLT) Let us summarize the three propositions of the generalized construal level (GCLT). (1) [Generalization of distance] “Discounting” applies to psychological distances including time. (2) [Amount effect] Discount rate varies depending on the construal level: the higher the construal level, the smaller the discount rate. (3) [Sign effect] Discount rate is smaller for loss than for gain. The relationship between GCLT and CLT are as follows. 1) GCLT models the consequences of CLT using the idea of discounting. It does not mean GCLT can explain what CLT cannot. 2) GCLT introduces the notion of gain and loss into CLT. 3) While CLT usually discretizes the construal level (high vs. low), GCLT regards the construal level as continuous by nature. By modeling the input and output of CLT, GCLT bypasses the complicated and arguably controversial inner mechanism/process of human perception. GCLT can predict preference and behavior shift more easily as distance varies. There is no need to specify the functional form of discounting, such as exponential or hyperbolic. When the distance is limited to time and the construal level is limited to monetary amount, GCLT becomes consistent with the ordinary “discounting” of BDT, as it should. Empirical Studies The survey asks participants to choose one of two lotteries with the same expected return: one with a higher prize amount and the other with a higher winning probability. The reason for selecting a lottery is that attributes resulting in high and low construal levels are clearly defined and same for everyone. Previous research found that, in lottery choices, prize amount and winning probability lead to high and low construal levels, respectively. In other context, it is often ambiguous what attributes result in high and low construals. Moreover, such attributes can differ by people. We investigate how lottery choice changes when the psychological distance with the subject varies. We manipulate time distance through a lottery whose outcome is announced either tomorrow (short) or one month later (longer). We manipulate social distance through a lottery which is purchased either for yourself (short) or for a prize in a party at work (long). Proposition 1 The survey asks a respondent to choose either Lottery A or B, both of which have the same expected winning outcome of 1,000 yen. A half of the sample are asked to consider two cases of time distance (tomorrow and one month later), and the other half are asked to consider two cases of social distance (for yourself and for a prize in a party at work). The design is a within-sample study. The paired McNemar test is conducted to statistically check whether the proportion of respondents valuing prize amount (high construal) over winning probability (low construal) varies by distance. The result confirms the prediction by CLT, in which, for both time and social distances, respondents’ construal levels are higher when the distance is far and vice versa. Proposition 2 A respondent is asked to choose either Lottery A or B when Lottery R, an originally intended for purchase, is unavailable. Both Lotteries A and B have the same gain or loss in expected outcome of 1,000 yen. The difference is whether the gain or loss is due to the change in the prize amount or the winning probability. A half of the sample are asked to respond to two cases of time distance (tomorrow and one month later), and the other half are asked to respond to two cases of social distance (for yourself and for a prize in a party at work). Again, the design is a within-sample study. The paired McNemar test is conducted to statistically check whether the proportion of respondents valuing prize amount (high construal) over winning probability (low construal) varies by distance. The result shows that, for social distance, the respondents’ construal levels are higher when the distance is far and vice versa, under both gain and loss. It implies higher discount rate for a low construal level. For time distance manipulation, however, changing distance did not result in the construal level change under either gain or loss. Proposition 3 A respondent is asked to choose either Lottery A or B with the same expected winning outcome when the distance is far. The survey then asks whether she would switch from her initial choice when the distance becomes close. Switch from Lottery A to B trades off the loss in prize amount over the gain in winning probability. Likewise, switch from B to A trades off the gain in prize amount over the loss in winning probability. According to GCLT, switch is likely to occur from A to B but not in the other direction. This is because discounting of a high construal level (prize amount) in loss is small whereas discounting of a low construal level (winning probability) in gain is large, the net of the loss and the gain is likely to result in sign reversal as the distance becomes close. The chi-square test is conducted to statistically check whether the proportions of respondents switching from A and from B are the same. The result shows that, for both time and social distances, there are more switches from A to B than from B to A as the distance becomes close, thereby supporting Proposition 3. Conclusions Using two samples, students and web users, the survey study largely supports the three propositions of GCLT. The only exception is the amount effect in time distance. Our study could not confirm it using neither students nor web users.

Understanding the buyer decision processes has been one of the core subjects for marketing researchers. Decision-making has been referred as a psychological construct, which could be inferred from the behavior as a commitment to an action. The main scope of this project has been centered at a blended approach between economic and psychological models of decision-making with giving more credit to the possible psychological and physiological counterparts of the buying process. The technological developments and interdisciplinary studies especially in the last decade have paved a valuable path for various research tools that could contribute to the classical models of marketing. The contribution of neuroscientific knowledge and methods has provided a considerable insight for the question what is happening inside the brain. Since neuroscience has targeted at investigating the human brain with respect to internal and external factors, an applied form of neuroscience, neuromarketing, has been useful for the marketing research in general and for modeling the buying processes in specific. Thepresent empirical study could be accepted as one of these initial steps and possible contributions in testing the role of neuroscientific methods in buyers’ decision processes and providing a useful insight in interpreting the prefrontal brain dynamics during their possible buying decisions. Buying decisions have been claimed to be “malleable” (Schwartz, 2004) associated with the available information beneath instead of having well-defined preferences (Bettman, Luce, & Payne 1998). It has been demonstrated that excessive prices have an impact on increasing the insular activity and decreasing the activity in the medial prefrontal cortex, which have been shown to be active during monetary decision-making processes (Knutson et al., 2007). It has also been argued that affect factors and unfair prices have a direct interrelationship (Xia, Monroe, & Cox, 2004). These findings have been in line with the somatic markers hypothesis by Bechara and Damasio (2005) who argue that our brains predict the possible outcomes in a setting depending on our interoceptive emotional signals prior to decision-making. These emotional signals have been considered to have direct guidance during decision-making processes like purchasing. Reward processingmagnitude and valence have been associated with economic transactions by using event-related potentials (Yeung&Sanfey, 2004). Prefrontal cortex has been found to be a critical region that is observed to be active during various cognitive processes including decision-making, executive functions and reasoning. The decision-making processes could generally be divided into two main segments: (1) cognitive and (2) emotional counterparts and prefrontal regions could simply be correlated with the cognitive aspects rather than the emotional side which is mostly considered to be driven by the subcortical regions. The neuroscientific studies in the literature shed light into this dissociation with various empirical findings such that nucleus accumbens activation correlates with reward anticipation, and medial prefrontal cortex (MPFC) activation correlates with gain outcomes (Knutson et al., 2001). Option valuation, probability estimation, reward and cost anticipation and strategy formation have been some of the decision processes that are considered to be executed by the prefrontal cortex. Medial prefrontal cortex has been shown to have a direct role in the calculation of values (or valuation) of options like the statement of the preferences with the presented product and it has been demonstrated that the activation in medial PFC has been in correlation with the subjective product preferences (Paulus & Frank, 2003). The preference judgments between healthy and unhealthy food items have also been shown to activate the medial prefrontal cortex during the valuation of the options (Hare et al., 2011). This valuation of options have been shown to be not restricted to product valuation but rather it is possible to speak of a general valuation system that is also effective in valuation of the monetary rewards (Bastenet al., 2010). Functional near-infrared spectroscopy (fNIRS) method has been utilized to investigate various cognitive faculties. Izzetoglu et al. (2007) used fNIR in a series of experiments to study brain activations during several types of tasks that measure cognitive output. They used a videogame-like task called the Warship Commander Task in which the participants tried to manage varying numbers of airplanes and the amount of cognitive load of the participants was quantified by fNIR. In other experiments, n-back task was used to investigate working memory load on the prefrontal cortex and anagram problems of varying difficulty were used to measure brain activations correlated to problem solving efforts. fNIR was also used in a visual oddball paradigm to assess attention levels of the participants. Across this series of studies, fNIR was shown to be a reliable method for quantification of prefrontal cortex activations. The change in the blood flow has already been shown to illustrate the activation level. Kumagai (2012) investigated personal product preference in fNIR study. Subjects were asked which one of the two products presented they would prefer and then were shown the same products consecutively before making a final decision. Researchers were able to classify product preferences by analyzing blood flow changesvia fNIR.A similar study was conducted by Luu and Chau (2009) to detect product preference via fNIR in a single-trial task. Subjects evaluated two possible products to state their preference and a single-trial task was adequate to analyze fNIR signal for preference detection. We have aimed to observe the neural correlates of buying versus non-buying decisions by using optic neuroimaging method, functional near infrared spectroscopy (fNIR). To the best of our knowledge, no study has directly investigated the fNIR correlates of buying versus non-buying. We have mostly adapted the experimental design of Knutson et al. (2007) that could be accepted as a realistic model for an idealized case of a possible buying decision by which the participants see a product image, then its price (under the product image) and finally the decision screen by which the participant has to respond positively or negatively to the buying decision. There have been four main hypotheses for this empirical study. Firstly, the preferences and buying decisions of the participantsduring the experiment are highly correlated with the consumption rates in their lives.The participants in both experiments are likely to choose the products, which they declare in the subjective reports. Secondly, the reaction times of the purchasing versus not purchasing decisions differ depending on the final decisions of the participants.Thirdly, the preference versus non-preference decisions of the participants causes different brain activation patterns via fNIR. Fourthly, the buying versus non-buying decisions of the participants causes different brain activation patterns via fNIR. The buying decisions would elicit more activation in the prefrontal regions due to the possible involvement of monetary-centered decisions as well as the contribution of working memory in these higher-order processes. This empirical project consists of two experiments. First one has been done without a real purchasing outcome –the participants were choosing to buy the products or not but they were not given the products at the end of the experiment. Whereas in the second experiment, the participants had the chance to buy the products they selected to buy. 78 products were used in the task and the total duration of the experiment was 26 minutes.The products consisted of 3 main groups: food, cleaning and personal care products. There were 39 products in the food group (e.g. milk, cheese, coke), 17 products in the cleaning group (e.g. detergents) and 22 products in the personal care group (e.g. deodorant, shampoo, toothpaste). The prices of the products were taken from the supermarkets around Ankara and Istanbul.28 participants have participated in the first round of the experiment, which has done without actual buying endowment but instead participants have pretended to buy the products that they actually preferred. The participants for this experiment were undergraduate students from the Middle East Technical University and they were paid 10 Turkish Liras for their participation in the experiment. The second experiment was performed with the same experimental design but this time each of the participants were given 10 TL for their participation and 40 TL to purchase the products they prefer during the experiment. 11 participants (6 males and 5 females) have attended to this second experiment. The participants were also told that if they do not purchase any products or they do not spend all of the money, they would be able to get half of the unspent money. Since the products have been presented with their actual market prices, it has been much more likely and advantageous for the participants to spend all of their money.The data of one of the participants was excluded due to handedness, and 2 of them were excluded due to excessive artifacts. After the completion of the task, each participant filled out a survey about their frequency of use (Range;1: Never – 5: Frequently) for each of the 78 products. The data obtained from 16 channels via fNIR at a temporal resolution of 2 Hz consists of 4 main parameters: Oxygenation (oxy), Total Hemoglobin (hbt), Hemoglobin (hb) and Hemoglobin 2 (hb2). Each reading is taken for 4 stages (fixation, picture, price, decision). The main underlying assumption has been to observe an increase in the relative concentrations of oxy and hbt values depending on the higher PFC activation during the product demonstration when compared to the fixation screen (that is presented before each block). Almost all of the channels illustrate a difference on average between buying and non-buying conditions. We have also expected to observe a significant difference in activation levels between purchasing and non-purchasing decisions. The processed data has been statistically analyzed with SPSS 20.0. Repeated Measures (RM) ANOVA has been performed in order to observe if the buying versus non-buying decisions had a statistically significant effect on the fNIR signals that are averaged for each block of product, price and decision screens. The independent variable has been the binary buying decisions of the participants. The results of the RM ANOVA test have demonstrated that the first experiment done with preference of the products do not implicate any significant difference between buying and non-buying decisions. Thus our third hypothesis was based on observing a significant change in prefrontal activations due to participants’ product preferences (versus non-preferences). Thus it is more likely that the non-monetary simulated “buying” decisions, which do not actually end with purchasing products, do not elicit sufficient activation in the prefrontal regions to provide a detectable difference between preferred and non-preferred cases. Whereas the same statistical test performed for the results of the second experiment implicate significant difference for the buying versus non-buying decisions for 2 of 16 voxels: V1, V8. For N=11, significant levels of activation was observed on Voxel 1, F(1.00, 9.00) = 8.35 , p < 0.2 (Greenhouse-Geisser corrected) and Voxel 8, F(1.00, 9.00) = 5.50 , p < .05 (Greenhouse-Geisser corrected). The waveforms averaged over 11 subjects show a significant separation among purchase and no purchase decisions especially in Voxels 1 and 8. This finding has been a support for our fourth hypothesis, which has been a modification of the third one. Our third and fourth hypothesis has hold that the buying decisions versus non-buying decisions elicit higher activation among the prefrontal cortices of the participants when the decisions end with the actual purchasing decision. To sum up, this empirical study could be accepted as a step for the specific research field of buying decision processes and neuromarketing research in general. The obtained results clearly implicate that specific prefrontal regions –both lateral and medial- might be activated differently depending on the final buying decisions via the optic neuroimaging device, fNIR. Beside the technical limitations such as the appropriate presentation time, this study performed with fNIR method could be used as a baseline work for understanding the psychological and physiological dynamics of buying decisions and in the short-term several factors can also be investigated with this method. Therefore, it might also be possible for researchers to adapt this methodology for the sector-specific marketing research especially for pricing in the long-run.

The aim of the present research is to explore the neural features of intertemporal choice. Intertemporal choice concerns the phenomenon of temporal discounting which demonstrates consumers’ tendency to devalue a future reward as the receipt of money reward is delayed further distantly into the future. It is also called the ‘present bias,’ a special kind of attachment consumers place to immediate a cash reward which consumers are willing to take even at a discount, instead of saving it for the future. The urge to choose an immediate reward at some discounting rates, i.e., temporal impulsivity, is deeply embedded in our instinct. On the other hand, the choice for a delayed option is made as a result of effortful and deliberate cognitive control, by suppressing the urge for instant gratification and shifting focus to the long-term gain. Neuroscience researchers have found the prefrontal cortex as a key brain region behind deliberate and analytic decision-making such as reward delay. The experimental paradigm used in this study adopted from Kirby, Petry, & Bickel (1999). There were ten intertemporal investment choices representing six different levels of discounting rates. Participants (N=21) were given the two investment options, as “take it now” and a “save for later” options, and they were asked to indicate a preferred option. The brain waves were recorded using a 32 channel EEG system. We conducted noise control by using Independent Component Analysis (ICA) in EEGLAB and analyzed the Event-Related Potentials (ERP) particularly focusing on the phase when each participant was examining the future-oriented “save for later” option. The behavioral responses were divided into two groups, one in which the present option was selected and the other in which a future-oriented “save it for later” option was selected. Custom-written Matlab codes were used to compare the differences in ERPs between the two choice responses. A greater positive component of P3 after 300 milliseconds at the onset of the future option was observed in the fronto-parietal regions when the “save it for later” options were chosen compared to when the “take it now” choices were made. Hence, during intertemporal choice, the fronto-parietal regions are likely to play a key role in enabling the long-term perspective and consequently, precipitate the choice of a future-oriented deal. The P3 signal across the fronto-parietal regions may potentially be a proximal indicator of a future-oriented choice during intertemporal financial decision-making.

In the first part we aim to present a new tool to better understand implicit consumer associations, perceptions and impact. The second one is to show how this tool uncovers new and often counterintuitive insights regarding emotional percepts of soccer megastars, including Lionel Messi. BIOCODE™ is a reaction time based method, determines the strength of implicit, i.e. instinctive, immediate, automated or emotional conviction people have to things they say, such as perceptions of a brand or a celebrity, reactions to an ad, liking of a product or intent to vote for a political candidate. It captures how consumers are impacted by brands, ads, products, packages and concepts in contrast to what they overtly say in a declarative, more considered, explicit realm. In essence, we ask to answer (on-line or central location) simple questions about a brand, a person or a product. Consumers’ explicit and rational statements are important but assessing those responses in the context of the time their brains need to produce an answer gives a new perspective and competitive edge. The standardized reaction time index reveals consumers’ true and unbiased reactions. Importantly, these implicit emotional reactions tend to predict actual behavior closer than explicit rational declarations. The Implicit Association Test (IAT) - the first method based on assessing reaction times - was developed in 1998 by Anthony Greenwald to finally capture racial prejudice and other sensitive issues. Before IAT traditional paper & pencil questionnaires due to overt or hidden distortions had hard time proving the existence of racism. What is the cognitive mechanism beyond reaction time based methodology? By recording how much time a consumer’s brain needs to produce an indication of an attitude or preference we discover how easily accessible (and thus how instrumental) such emotion is. The quicker the indication is, the more accessible it gets. The foundations of this neuropsychological phenomena were first described by Donald Hebb in his ‘Consolidation of the Memory Trace’ theory (1948) and then refined by Russell Fazio in his ‘Attitude Accessibility’ model (1989), Daniel Schacter’s ‘Implicit Memory’ theory (1992) as well as Mahzarin Banaji & Anthony Greenwald in their concept of ‘Implicit Social Cognition’ (1994). Rafal Ohme and his team began working with the original, academic form of IAT. Their goal was to bridge the use of the tool to market research applications. Now with over 15 years of subsequent R&D in this area, they have created simplified, user friendly research applications that are unequaled in their ability to measure previously unanswerable questions about the degree of emotional valence or “felt intensity” that is associated with what people say. BIOCODE™ is the second generation of latency measures. Comparing with IAT - the first generation of academic reaction time methods it is: easier, simpler, clearer, looks better and there is no need for repetitions which saves a lot of precious on-line time. BIOCODE™ is based upon highly refined technology that calibrate individual response speeds and eliminate biasing variables. The technology includes: noise reduction algorithm; quality control module; context procedures; calibration. It secures the highest validity of measurements. In the test – retest validation conducted on 11 studies held internally and externally in 2009-2013 the correlations obtained ranged from r = 0,840 to r = 0,960 (conducted on various target groups of high incidence that met all the criteria for the test; demographic characteristics were controlled and groups were homogenous. Together with Manabu Mori from Rakuten Research - one of the top on-line research company – Rafal Ohme have designed the first ever cross-cultural reaction time test on soccer celebrities. Nearly 900 on-line respondents from three continents: South America, Europe and Asia were asked to indicate (on a computer screen, using a regular mouse or a key-pad) whether they agree or disagree (5-point Likert’s scale) with the attitudinal statements on specific personality traits of soccer celebrities, eg. hard working, talented, famous, loving their country. This explicit rational response has been accompanied by implicit emotional reaction. The aim of the study was to by-pass the “rationality bias” and reveal true emotional reactions about soccer celebrities including: Leo Messi, Christiano Ronaldo, Wayne Rooney, Neymar jr, Shinji Kagawa. The selected findings will be disclosed during the presentation. Concluding, BIOCODE™ is a sensitive detector of consumer ‘lip service’ that is often driven by benefit of the doubt, political correctness and simple deference to leadership brands. If we want to understand consumers, it serves to know the gap between what people say and how they feel. It is a very promising, fast growing method with established advanced applications for copy testing, tracking, brand strategy, political polling, product, package and concept testing worldwide. Moreover it is effective as a module embedded within more traditional surveys for providing a seamless integrated perspective on both explicit and implicit aspects of consumer behavior to enrich our understanding of what consumers truly feel and what drives their behavior.

The luxury consumption has been pertinent to those aged around forties to fifties in the upper class. Recently, luxury product market became wide and is varying in age segments. Young consumers’ luxury consumption shows a rapid growth worldwide. Despite the global financial crisis, advanced information technology and globalized marketing strategies accelerate luxury consumption rate in vast. This phenomenon of luxury consumption is critically relevant to consumer social psychology. While people have various relationships with others in their own societies, they carry out impression management for themselves. Consumers try to identify themselves with goods, services, and images of brands or products. More importantly, congruency between their ideal images of themselves and consuming objects plays an important role in luxury consumption in recent years.

The study tests a theoretical framework for examining the consumer decision-making process with regards to ethically questionable behavior. The results indicate that subjective norms, perceived behavioral control and self-efficacy are significant predictors of consumer intentions to engage in ethically questionable behavior. Attitude was not found to be a significant predictor.

Many examples of sub-optimal decisions in the marketplace have captivated the attention of media, business institutions, and public policy in recent years. For instance, the sub-prime mortgage crisis in the United States that led to the 2008 recession, the insufficient health care architecture that bolsters the debates among US houses on health care reform, and the problem of food epidemic resulting in obesity and various other health-related problems among the growing number of young people worldwide. Despite these examples, more work is needed to learn about the processes that contribute to better decision outcomes among the market participants. In all of these instances, decisions must have some objective quality (e.g., the probability of choosing the optimal choice) and not just subjective quality (e.g., feeling confident or satisfied). In light of the ever-increasing use of handheld devices (e.g., tablets and smart phones) and the expanding digital media sources to access marketplace information, there is a proliferation of global visual culture (e.g., Pinterest, Instagram, Facebook, etc. See for example: Walter, 2012). Thus, it is important to examine the effects of two major information presentation formats – visual vs. textual – on consumer decision outcomes. This paper focuses its research question on examining the effect of information presentation formats on consumer decision outcomes in complex choice environments (e.g., financial products). Using construal level theory (Trope & Liberman, 2003; Trope & Liberman, 2010), an experiment was conducted to examine the effect of information presentation formats (visual vs. textual) on a set of credit card products. Preliminary analysis reveals that significantly more participants opted for the textual information format for choosing a credit card offer. However, there is no difference in participants’ readiness and ability to make a choice based on the information format in the context of credit card offers. In addition, there is a non-significant difference between participants who felt ready to make a choice based on the information in their chosen format, and those who stated unable to make a choice. The seemingly apparent reason for this weak support for the visual effect in this study is the population of the sample. The participants were junior or sophomore students, 84 percent of whom aged between 20 and 22 years old. In a further examination of why participants felt unready/unable to make a choice, they stated the strong necessity to consult with parents, desire for more research and understanding, and the (lack of) usefulness of having a credit card for daily usage in their stage of life.

Consumers often make a series of decision in which one choice follows another. Consumers' choice, however, is not always based on economic rationality. Most choice research focuses on the decision processes by which consumers choose among a set of alternatives, independent of the way they arrive at the choice (Khan & Dhar, 2006). Recent research sggests that prior decisions can also serve as a license to choose options that are inconsistent with the salient self by boosting a person’s self-concept. Specifically, self-licensing occurs when past moral behavior makes people more likely to do potentially immoral things without worrying about feeling or appearing immoral. (Merritt, Effron & Monin, 2010). This research examined the influence of licensing effect on consumer choice. In other words, the process underlying the licensing effect may be largely nonconscious. Also individuals frequently encounter self-control dilemmas in which long-term goals conflicts with temptation. Thus, an understanding of goal fulfillment processes is of substantial importance for understanding consumer behavior at the individual level. Therefore, this research is to examine the consumer response in the licensing situation and additionally, for deeply understanding of licensing effect of consumers, qualitative research approach is needed.

Whereas the interest in the area of corporate crises and crisis response strategies has been increasing during the last decades (e.g. Coombs, 2007; Dawar & Pillutla, 2000), little is known on the spillover effects that an organizational crisis can induce towards other firms within the same industry. Though over the years, a variety of reputational collapses of single companies have become memorable by causing whole industries to suffer. Following these considerations, the aim of this study is to extend prior research on corporate crises and crisis management by focusing on intra-industry spillover effects. We investigate the topic by means of an experiment taking as an example the sportswear industry. We randomly assigned participants interested in sports to a scenario with either a personally relevant scandal or a personally irrelevant one about one major sportswear brand. We then measured the corporate reputation, purchase intentions and willingness to recommend the brand for an overall of five sportswear companies as dependent variables. We find a significant negative spillover and reduction of corporate reputation and behavioral intentions for different sportswear brands and thereby distinguish between the unexplored effects of scandal relatedness to the customer. We are the first to investigate the degree of personal relevance of upcoming negative information, finding no significant influence on the strength of scandal spillover. Furthermore, we argue against existing literature and question the role of reputation as protective shield and buffer against negative spillover, finding especially companies with high corporate reputation to suffer from scandal spillover. In a next step, we employed three different response strategies, namely active, defensive and collective (Dawar & Pillutla 2000) in order to find the best spillover correction method for competing brands. Conversely, we found none of the three response strategies to be suitable spillover correction methods placing managers of spillover-affected companies into a blind alley.

This study explores influencing factors for firms’ willingness to participate in open innovation. We identify commitment and trust, switching cost, and IT infrastructure as the key predecessors. The study further examines how these variables affect the firms’ participation in open innovation using datasets from the UK biotechnology industry.

Introduction A market orientation is a fundamental concept of strategic marketing that reflects a thorough understanding of both customer needs and competition (Narver & Slater, 1990; Kohli & Jaworski, 1990; Salavou et al., 2004). Market orientation as organizational culture increases firms’ interest in providing greater value for its customers, and, consequently enhances business performance (Narver & Slater, 1990). Thus, it is important to understand processes related to development and management of market-oriented culture (Zhou, Gao, Yang, & Zhou, 2005). As practitioners are encountering many difficulties in implementing market orientation in their organizations (Day, 1994; Mason & Harris, 2005), more detailed studies have been called to investigate managerial processes of deploying and developing market-oriented culture (Harris, 2000). Recent studies have found that market orientation can be enhanced by top management emphasis and reward systems (Kirca, Jayachandran, & Bearden, 2005; Kumar, Jones, Venkatesan, & Leone, 2011). However, fewer studies have specifically looked into the remuneration of the management in this setting (Ruekert, 1992), and particularly how the different parts of employee compensation, such as incentive schemes, are structured. Although our understanding of how compensation structure effects on development of market-oriented culture is limited, compensation structures have been studied extensively in finance literature (see Murphy 2012 for an extensive review). The structure of employee incentive schemes may be used to shift personnel’s myopia and risk-taking behavior (Murphy, 1999). Thus, these schemes provide a classic solution to the agency problem between shareholders and management (Jensen & Murphy, 1990) and have been predominantly postulated to be beneficial for the shareholder (Murphy, 1999). The underlying rationale is that the managers perceive risk differently from the shareholders and because of this asymmetry the managers may be hesitant to undertake projects that would be optimal for the shareholder value (Core, Guay, & Larcker, 2003). In this study, our aim is investigate how the structure of the employee incentive schemes affects to the market orientation of the firm. Given that the benefits of market orientation take time to become fully realized, the importance of top management both emphasizing and supporting a market-oriented culture is paramount (Kumar, Jones, Venkatesan, and Leone, 2011). Since developing market orientation is by its nature a long-term and risky investment (Jaworski & Kohli, 1993), and is linked to superior firm performance, we postulate the development of market orientation as an activity that stock-based compensation is meant to promote. Literature review and hypotheses development Market orientation as organizational culture is “the set of beliefs that puts the customer's interest first, while not excluding those of all other stakeholders, such as owners, managers and employees, in order to develop a long term profitable enterprise” (Deshpande Farley, & Webster, 1993, p. 27). As positive relationship between market orientation and business performance has been empirically proven (Huhtala et al., 2013; Deshpande & Webster, 1989; Narver & Slater, 1990), recent studies have focused on investigating possible antecedents of market orientation, such as reward systems (Kirca et al., 2005; Kumar et al., 2011; Sarin & Mahajan, 2001, Wei, Frankwick, & Nguyen, 2012). Studies have found that proper reward systems, such as participation based rewards, may facilitate market orientation (Sarin & Mahajan, 2001; Wei et al., 2012). Development of our hypotheses is based on the understanding that, firstly, market orientation is only acquired through risky and time-consuming projects (Jaworski & Kohli, 1993), and, secondly, stock-based incentive schemes are specifically designed to mitigate risk aversion and myopic investment choice challenges (Murphy, 1999). The benefits of a market orientation take time to realize, and especially management support is needed to instill a market-oriented culture (Kumar et al., 2011). This type of management involvement is also reflected in Jaworski and Kohli's (1993) statement that risk-averse management leads to subordinates being less likely to focus activities that increase overall market orientation. The reward and compensation system is a critical factor as it can either encourage or impede managers’ actions (Hambrick & Snow, 1989), and, therefore, has an impact on market orientation (Wei et al., 2012). We argue that stock-based incentive schemes address the challenges of developing market orientation that has been found in extant literature (see Mason & Harris, 2005). The incentives should both motivate employees to focus more on long-term value creating activities as well as encourage them to overcome their risk aversion. As the market-based incentive systems aim to promote longer-term focus and reduce risk-aversion, which are major factors causing managers’ inertia to develop market orientation. In line with incentive and reward systems literature we propose that: H1(a)/(b): An increase in (a)option/(b)stock incentive schemes' total average value per employee involved increases a firm's market orientation (and its constituent factors) Organizations should provide more bonuses and long-term incentives to high level managers, since decision-makers in the upper echelons can have impact on the organization (Wang, Venezia, & Lou, 2013; Gerhart & Milkovich, 1990; Hambrick & Mason, 1984). We argue that top managers are the priority when designing stock-based compensation and the larger the proportion of employees benefiting from an incentive scheme within a firm is, the better the relevant decision-makers and experts have been incentivized. Thus, we propose: H2(a)/(b): An increase in the proportion of employees benefiting from an (a)option/(b)stock incentive scheme increases a firm's market orientation (and its constituent factors) Data and methods The incentive scheme data was obtained from Alexander Incentives, a remuneration scheme consultancy that administers a broad database of publicly disclosed information on the remuneration and incentives of public and private companies in Finland. We use data from 2008 to 2012 comprising 67 firms. Over this period the average year specific value of an option based incentive scheme was 4.7 million € and corresponding value of a stock based incentive scheme was 7.6 million €. On an average year, an option based scheme comprised 595 grantees and a stock based scheme comprised 317 grantees. Measurement of market orientation was conducted through survey using the questionnaire items developed by Narver and Slater (1990). The survey was conducted in the spring of 2008, 2010 and 2012. The survey was sent to all companies in Finland with more than 5 employees in the previous year resulting 1157, 1134, and 952 completed answers, respectively. The respective firm-level response rates were 16%, 10% and 9%. However, in this study, we are investigating only the companies that were publicly listed at the time of conducting the survey and who have disclosed personnel incentives. Such companies answering the survey totaled 55 firms in year 2008, 39 in 2010, and 28 in 2012. The final sample consisted of firms that responded to the survey in one or more years and from which we were able to obtain incentive scheme data. The sample comprises 122 firm-years collected from 65 unique firms (n = 122). The items measuring market orientation were evaluated with confirmatory factor analysis (CFA) using SPSS AMOS version 21.0. The latent variables measuring the dimensions of market orientation (customer orientation, competitor orientation, and interfunctional coordination) were included in a single second-order CFA model. Following suggested guidance for the model fit index thresholds (Bagozzi & Yi, 2012; Bentler, 1990), the second-order CFA model shows a good fit (χ2 = 58.08, df = 24, χ2/df = 2.42, RMSEA = .10, SRMR = .047, NNFI = .94, and CFI = .96). All items loaded significantly on their respective second-order (standardized loadings ranged between .90 and .95) and first-order latent constructs (standardized loadings ranged between .68 and .96), indicating convergent validities. All model maximum likelihood estimates were found to have statistically significant critical ratio values. We conclude that the tests proved the factorial validity of the second-order CFA model. Additional financial data was used to formulate control variables and was obtained from Worldscope and Datastream. We are using annual and quarterly financial statements data to control the size of the companies and the volatility of the environment. Stock market data were used to control the riskiness of the firms. We are controlling for the size of the firm with the logarithm of the total assets. To control for the environment, we are using the volatility of the quarterly revenues within a year. We also use the monthly volatility of the stock market performance to control for the investors’ perceptions of riskiness. Detailed descriptive statistics of the sample are available upon request. Results The impact of the employee stock-based incentives on the market orientation of the firm was investigated using multiple regression analysis. We used the market orientation as the dependent variable. As the independent we used the value of the incentive scheme (option and stock based) per grantee and the percentage of total employees who were grantees. Total assets, quarterly revenue volatility, and monthly stock returns volatility were control variables. The variable for market orientation significantly correlated with option scheme value (p < .10), presenting a low correlation of -.17. Quarterly sales volatility significantly correlated with monthly stock return volatility at -.21 (p < .05). Other correlations were found statistically insignificant and ranged between -.14 and .23. Table 1 reports the regression results predicting market orientation. Models 2 and 4 test Hypotheses 1(a) and 2(a). Models 3 and 4 test Hypotheses 1(b) and 2(b). All Models 1 through 4 were found statistically significant based on the F-statistic (p < .01). Hypothesis 1(a) proposed increase in option incentive scheme’s total average value per employee predicts increase in a firm's market orientation. As indicated in Model 2 and 4, there is no strong support for the hypothesis. Although the coefficient for option scheme value is significant (p < .10), the coefficient is negative instead of being positive as was hypothesized. Hypothesis 2(a) postulated the option scheme coverage to have a positive impact on the market orientation of the firm. The coefficient in both Models 2 and 4 was positive, however not significant. Thus, the Hypothesis 2(a) is clearly rejected.

In recent years, the exploration of the quantifiable effects of market-based intangible assets on firm performance has become increasingly important in marketing and management literature. Corporate reputation, considered as a one of the key marketing metrics for maintaining and enhancing companies’ competitiveness in the globalized economy, plays an essential part in this context. Numerous studies show the impact of reputation on measures of financial performance, justifying companies’ endeavors to install and dedicate effort towards systematic reputation management and tracking. A possible consequence of a good reputation that has so far been neglected in academic research is a decrease in a company’s cost of equity capital, a measure that constitutes an important basis for the decision to invest in future projects, thus playing a vital part in the creation and preservation of strategic competitive advantages. A firm’s cost of equity is defined as the required rate of return, given the market’s perception of the firm’s riskiness. It is based on investors’ expectations about future returns and estimated by means of residual income models with varying assumptions and restrictions (in this study: Claus and Thomas 200, Gebhardt et al. 2001, Ohlson and Juettner-Nauroth 2005, and Easton 2004), equating the current stock price to future cash flows that are discounted with the firm’s implied cost of equity. To account for industry-specific idiosyncrasies, each firm’s cost of equity is adjusted by the monthly industry median. Corporate reputation is defined as an attitudinal mindset towards a company. Following the model of Schwaiger (2004), it is conceptualized as a two-dimensional construct comprising a cognitive (competence) and an affective (likeability) component; reputation is the linear combination of these two dimensions. Corporate reputation data was collected in 13 semi-annual waves from large-scale samples representing the general public in Germany. By applying panel data analysis on a set of the 30 largest publicly listed German companies during a seven-year time-span (2005-2011) and controlling for commonly known factors, I show that corporate reputation significantly reduces a firm’s cost of equity. This relationship holds when reputation is corrected for prior financial performance and industry affiliation. My results should help managers to further strengthen their argument that reputation management is value-relevant. This study should be seen as a starting point for further research to gain a deeper understanding of the reputation-cost of capital-interface.

Although the relationship marketing literature acknowledges the importance of switching costs for increasing customer retention in general, little is known about its relevance in industrial markets. In particular, it is unclear whether switching costs and its dimensions impact relevant behavioral outcomes of buyer-seller relationships in business-to-business (B2B) markets. Against this background, our research intends to make two main contributions: Since we assume differential effects for different types of switching costs, our research first explores the dimensions of switching costs for the B2B domain. Second, it tests the relative impact of the dimensions of switching costs on business customers’ actual purchase behavior. Results suggest that switching costs in B2B settings are a multi-faceted construct, including (i) procedural, (ii) financial, and (iii) relational switching costs. Moreover, we find relational switching costs to be most important for securing B2B buyer-seller relationships since they impact a customer’s (a) share-of-wallet, (b) cross buying behavior, and (c) actual switching behavior. While procedural switching costs only influence share-of-wallet, financial switching costs solely impact customer’s cross-buying behavior across a firm’s product and services categories. These findings contribute to a better understanding about how to secure B2B buyer-seller relationships.

In this paper we explore competition as a firm process, rather than as a background economic variable. We contribute by refining firm competition as a process of goal seeking within a context of many actors. First we consider past research on structural and socially constructed competition. We develop a research framework inside relational time, based on the priority of a firm’s line of action, the direction of a firm’s activities, whether primarily towards the customer or first focusing on the activities of another firm. We explore the theoretical distinctions between non-competitive, competitive and rivalry firm activity through an analysis of exporters and importers of fine wine to Denmark from South Australia. We distinguish firm competition from other more complex interactions in a network context. We conclude with managerial implications and the opportunities for future research. The concept of competition in the business-to-business literature shifts meaning depending on the context. The meaning seems to extend along a continuum from rivalry (Porac, Thomas, Wilson, Paton & Kanfer 1995) to coopetition (Bengtsson & Kock 2000). According to McNulty (1968, 639) “There is probably no concept in all of economics that is at once more fundamental and pervasive, yet less satisfactorily developed, than the concept of competition.” In the business-to-business literature competition is defined as structural, where firms seek the same customer or goal (Macdonald & Ryall 2004), or competition is regarded as socially constructed (Porac et al. 1995). Competition is also considered as an interaction process undertaken over time between firms (cf Easton & Araujo 1994; Turnbull, Ford & Cunningham 1996). We pursue only an understanding of the competition process based on a single firm’s activities. Our approach is to focus on this simple form and develop a process based framework to understand competition. We see this as a single step, the first advance towards a framework for analyzing cooperation and competition together (Jarillo 1988).

Power asymmetry in highly concentrated retail markets is an unavoidable consequence within supplier-retailer relationships. This paper investigates the existence of power asymmetry in an Australian context and outlines the impacts on the industry. A documentary analysis was undertaken using documents from three major investigations into the grocery retail sector in recent years. These documents allowed us to gain insights into the industry using reports submissions and transcripts of public hearings. In addition in-depth interviews were carried out with suppliers of the two major supermarket chains. Combining these two approaches provided rich data. This paper contributes to the literature on power in supply channels. The findings support the existence of power asymmetry across many product categories but contrary to other studies find that the major supermarket chains are not averse to exerting coercive power for their own benefit. We find that the highly concentrated nature of the grocery retail market sees the power imbalance exaggerated in this context. We conclude that power asymmetry in the short-term is benefitting consumers but the long-term impacts on the supply chain may be detrimental to the food industry in Australia if nothing is done to curb the market power of the two major supermarkets chains.

A well-known dilemma in strategic marketing is whether a firm can be simultaneously both efficient in its existing business and innovative in creating new business (Atuahene-Gima 2005; Christensen 1997). Beleaguered companies such as AOL, Kmart, Motorola, Nokia, Polaroid, and Sears are examples that were once highly efficient in serving customers, but partly due to that efficiency in their existing business, paradoxically failed to introduce innovations. The potential tension “between innovation and efficiency—is one that’s bedeviling CEOs everywhere” (Hindo 2007). Two questions regarding the efficiency–innovation tradeoffs are especially intriguing to researchers and managers alike. First, to what extent are such tradeoffs driven by efficient firms’ lack of eagerness or willingness to innovate in the first place, or lack of ability to innovate and promote innovations? Second, can certain strategic marketing factors mitigate the tension of such tradeoffs? Indeed, anecdotal evidence indicates that not all firms that are efficient in their current business (e.g., Charles Schwab, Capital One) lack innovative thrust. In fact, efficient firms may actually be eager to innovate: Nokia, for instance, originally innovated an online “app store” service as well as touchscreen smartphones and Internet tablets in the 1990s and 2000s, much earlier than Apple (Ben-Aaron 2009; MobileGazzette 2008). Similarly, Polaroid was originally a pioneer in developing digital cameras and imaging services in the 1980s (Tripsas and Gavetti 2000). The eventual failures of Nokia’s and Polaroid’s innovation efforts, thus, do not seem to be due to their lack of eagerness to innovate, but perhaps the inability to manage the efficiency–innovation tension. In contrast, other companies seem to be able to manage this tension. For instance, in financial services, Charles Schwab is often commended both for its efficiency and its innovativeness, and the firm itself feels the “need to invest in innovation to maintain a competitive edge” (Gilson 2012). Against this backdrop, we focus on two questions: (1) What exactly are the tradeoffs and tensions between a firm’s existing efficiency, innovativeness in its new offerings, and new offering performance? And (2) how can strategic marketing assets such as customer base and advertising intensity mitigate the tradeoffs? Should such assets help to alleviate the inherent tension, they would give executives tools to pursue both efficiency and innovation at the same time and succeed with their new innovative offerings. Empirically, we focus on the service sector, whereby the actual technical development of innovations is not very costly in tangible financial terms (Crawford and di Benedetto 2008; Droege et al. 2009; Thomke 2003)―making the intangible firm capabilities most likely determinants of (innovation) performance rather than tangible resources (cf. Vorhies, Morgan, and Autry 2009). Therewith, we examine our research questions with a comprehensive census dataset of all new service introductions (n≈500) in one national market: The Finnish mutual funds industry (1997–2010). The sector of financial services is especially relevant for the efficiency–innovation tradeoffs because in this sector, many firms are compelled to engage in both efficient operations and effective (financial) innovations. Our empirical focus on all firms in one market precisely identifies and measures the efficiency levels of all competing firms, relative to the best-performing competitors, as well as innovativeness (earliness) in introducing new services compared to all rivals. For a marketing perspective, we focus on firms’ existing customer-perceived service efficiency (over the entire portfolio of existing services, i.e., funds)—defined through the ratio of output value that customers obtain from the firms’ current services to the (customer) cost inputs. We also carefully delineate between (a) innovativeness of a new service introduction and (b) its performance. Doing so can reveal the potentially contradictory effects of existing efficiency on new service innovativeness (willingness to innovate) vis-à-vis new service performance (ability to make innovations succeed). As our key results, we firstly identify and explicate the baseline efficiency–innovation tradeoffs. Specifically, our results suggest that while existing service efficiency increases the innovativeness of new services introduced by the firm, it simultaneously (1) leads to decreased business performance for the new services introduced and (2) diminishes the positive influence of innovativeness on performance. In sum, these findings imply that on the baseline, highly efficient service firms may be too eager to innovate, considering the sub-par performance they are likely to receive for those innovations. Secondly, our results reveal two strategic marketing factors, which have the potential to mitigate the tradeoffs. We find that the firm’s (a) focused customer base and (b) high advertising intensity can nullify the negative effect of existing service efficiency on innovativeness and the negative moderating effect of efficiency on the innovativeness–performance link.