The Use Of Neuromarketing Research

Published Date: 02 Nov 2017

Abstract

The aim of this research paper is to explore whether the use of the new field of marketing research which called "Neuromarketing" can magnify user co-development in the service innovation process. To accomplish this goal a comparative experimental study using focus groups and EEG will be employed. A structural equation modeling analysis along with confirmatory factor analysis are thought to be appropriate analysis vehicles for identifying and proving the argued causal influence of the neuromarketing research in magnifing customer co-development of service innovations in Egyptian universities.

Keywords: Neuromarketing, Neuroscience, Service Innovation, Consumers co-development, Universities

Introduction

As the service sector continues to grow, new players are gradually attracted, technologies change, and user needs shift. Continuous innovation efforts, thus, become imperative for existing service providers to reduce costs, enhance existing service quality, and expand current service offerings to increase market share from potential markets or to enter new ones (Skiba and Herstatt, 2012). To decrease the risk of market failure of innovations, future user needs must be anticipated and translated into innovative services early in the process of designing such market offerings. Successful innovation management needs rather to balance the capability to listen to and understand external demand as the primary impetus for innovations – both incremental and radical ones – with the capability to internally develop need-based technologies as the basis for a product and its production process (Skiba and Herstatt, 2012).

The importance of involving customers or users in product and service innovation is stressed in the literature. Collaboration between suppliers and users can lead to a mutual understanding of the users’ needs and wishes, as well as an understanding of the technological opportunities (Magnusson, 2003). Customer interaction may shorten the development cycle and improve the quality of innovations. Successful user involvement, however, requires that the organization has methods and processes to gather and analyze user data as well as to integrate user data in the design process.

The aim of this research paper is to explore whether the use of the new field of marketing research which called "Neuromarketing" can magnify user co-development in the service innovation process. Neuromarketing represents a new way to help marketers understand consumers easily and more efficiently. Neuromarketing was born by combining two fields, Consumer behavior and Neuroscience. The paper will be organized in five parts. The first part will tackle the literature review for Customer Co-development of service innovation and then for neuromarketing. The second part will discuss the conceptual framework for both Customer Co-development of service innovation and then for neuromarketing. The third part will present the research model and proposition formulation. The fourth part focus on the proposed methodology and finally the last part of the paper will present the concluding remarks.

Literature review:

The literature review will be organized in two major sections. The research stream concerning Customers co-development of service innovation will be discussed in the first section whereas; the second section will focus on Neuromarketing research.

Section 1: Customer Co-development of service innovation

Customer co-development of service innovation literature focused on three directions. The first one is tackling the extent of customer contribution in the service innovation process. The second direction handling activities performed by customers in the different staged of new service development whereas, the final direction focus on the impact of Customers involvement in service innovations.

Martin and Horne (1993, 1995) relate the extent of customer involvement to overall success of a new service initiative. In a survey of 217 firms across a variety of service industries, Martin and Horne (1993) found no significant difference in the extent of customer involvement between successful and unsuccessful service innovation programs. But when the authors, in their 1995 study, compared successful versus unsuccessful innovations within the same firm, they found in a sample of 88 firm that the most successful projects (based on sales volume and profitability) had a higher level of direct customer participation than did the least successful projects. The mixed results may be attributed to differences in how each study measured customer involvement (use of customer information i.e., passive, low intensity customer involvement vs. direct customer participation i.e., high intensity involvement). Martin and Horne (1995) findings supported by Kristensson et al. (2002) research effort. Kristensson et al. (2002) empirically examined how user involvement affects the originality of new service ideas in service innovation. Their findings indicated that users produced more original ideas than the company’s professional service developers. One of the most detailed researches on customer involvement in the various stages of NSD was conducted by Alam (2002), who investigated several aspects of user involvement in each of ten sequential stages of the NSD process. In-depth interviews of managerial and customer respondents in 12 financial services case studies addressed purpose, stages, intensity, and modes of users’ involvement in service innovations. Based on the finding four levels of user involvement were outlined: Passive acquisition of input, Information and feedback on specific issues, Extensive consultation with users and Representation. As extension to Alam (2002) research effort, Alam and Perry (2002) found that, overall, customers were involved in all stages, but highest frequency of customer involvement was recorded for idea generation, service design, and service testing and pilot run. Customer activities at the previously cited stages were:

Idea generation – state needs, problems and their solution, criticize existing service, identify gaps in the market, provide a wish list (service requirements), and state new service adoption criteria.

Service design and process system design – review and jointly develop the blue prints, suggest improvements by identifying fail points, observe the service delivery trial by the firm personnel.

Service testing and pilot run – participate in simulated service delivery processes, suggest final improvements and design change.

Alam and Perry (2002) provide no indication of how they determined the frequency of customer involvement at each stage, but they did publish a very useful figure summarizing activities performed by customers for each stage of the NSD process. Alam (2002) and Alam and Perry (2002) research was focused on the extent and effect of customer involvement in all stages of NSD while, Magnusson, et al. (2003) focus only on the idea generation stage. They conducted an experiment that demonstrates users’ new service ideas can be as good or better than ideas produced by professional service designers. Three groups were given 12 days to come up with new uses for text messaging with mobile phones. One group consisted of professional developers from the R&D unit of a Swedish mobile phone company; the other two groups were made up of university student volunteers. The experiment showed that users can generate service ideas as potentially beneficial to a firm as those of in-house professional developers, and the potential producibility and profitability of those ideas improves when users are given the right amount of training/consultation as to what is or isn’t technically feasible. When users get too much help, they begin to think more like unimaginative internal developers rather than representatives of the buying public; when they get too little help, their ideas are less producible. The study demonstrates that customer involvement in idea generation improves the product-market fit (i.e., service marketability) of a service innovation. Matthing, et al. (2004) argued more broadly, based on the same study findings, that customer involvement in service development helps a firm "anticipate customers’ latent needs and develop new services" to meet those needs

Carbonell et al. (2009) aimed (1) to investigate the effects of customer involvement on operational dimensions (i.e., innovation speed and technical quality) and market dimensions (i.e., competitive superiority and sales performance) of new service performance; (2) to examine the effect of technological novelty and technological turbulence on customer involvement; and (3) to explore the moderating effect of the stage of the development process on the relationships among technological novelty, technological turbulence and customer involvement, and customer involvement and new service performance. In a survey of 807 Spanish service firms in a varied set of industries, Carbonell et al. (2009) revealed that, customer involvement in NSD has a positive direct effect on technical quality and innovation speed; it has an indirect effect on competitive superiority and sales performance through both technical quality and innovation speed. Their study also revealed a positive effect of technological novelty as well as technological turbulence on customer involvement.

Scupola and Nicolajsen (2010) Investigate whether management and employees in Danish academic libraries involve users in library service innovations and what these user roles are. Findings show that customers participate to service innovation mainly through the roles "customer as a user", which is the most important one, and "customer as a resource". The role "customer as co-creator" is only about to be introduced in the form of content provider – not service designer. This implies that customers are mainly involved in the implementation stage of the innovations and are given very little power and influence in the innovation process. The main conclusion is that there are unexplored possibilities for customer involvement in library service innovations. Oliveira and Hippel (2011) empirical findings showed that, in the case of important banking services, users frequently develop and self provide what they need before banks or non-bank financial service producers offer commercial services to serve their needs.

Section 2: Neuromarketing research

Recently, neuromarketing research literature are tackling the traditional marketing-mix instruments such as product (Erk et al., 2002), price (knutson et al., 2007 and Lauri, (2010), communication (Rossiter and Silberstein, 2001), and distribution policies (Deppe et al., 2007), as well as brand research (McClure et al., 2004; Yoon et al. (2006); Koenigs and Tranel, 2008; and Plassmann et al., 2007). Neuromarketing research have been also used as a tool to test the validity of traditional marketing research techniques (e.g., questionnaire) as done by Dietvorst et al., 2009.

The investigations by Erk et al. (2002) provided the first insights into how the brain processes differently designed goods (e.g., sports cars, limousines, and small cars). The FMRI results of their investigations showed that reward-related brain areas are activated by objects that have gained a reputation as status symbols through cultural conditioning. In relation to the perceived attractiveness of the products, pictures of the cars in their study led to activation in the left anterior cingulate, the left orbitofrontal, and bilateral prefrontal cortex, as well as in the right ventral striatum. Erk et al. (2002) concluded that the relative activation in the ventral striatum can be seen as an indicator for how attractive a visual stimulus (i.e., product design or shape) is evaluated to be. The activity changes in the reward system of the brain induced by an attractive product design can be applied in order to predict purchasing behavior, assuming a relation between product design and purchase decision.

To date there is only one study that has investigated how favorable brand associations alter experienced value signals (Plassman et al., 2012). McClure et al. (2004) investigated differences in brain activity during consumption of sodas when the subjects knew they were drinking Coke or Pepsi vs. when they did not know which brand they were consuming. Unbeknownst to the subjects, they were consuming Coke and Pepsi in both conditions (brand-cued and non-brand-cued trials). The study showed that the experienced value signals depended on brand associations. In particular, the authors found that subjects' knowing they were drinking Coke vs. not knowing what they were drinking correlated with activity changes in their memory/association areas (hippocampus, dlPFC/SFG). No such difference could be found for Pepsi.

Yoon et al. (2006) investigated brand personality associations. The authors compared whether judgments about personality attributes of people are represented in the same neural system as judgments about personality attributes of brands and whether this differs when these judgments refer to the self or others. They found that brain areas involved in making judgments about human traits for people do not overlap with brain areas involved in making judgments about human traits for brands. These first findings challenge the view that we associate brands with personalities and are able to form relationships with brands the same way we form relationships with people (Plassman et al., 2012).

Knutson et al. (2007) Combined neural and attitudinal measures to predict consumers’ purchases. The authors decomposed the purchasing process into three steps – (1) viewing a product, (2) viewing product and price information, (3) pressing buttons to indicate whether one wishes to buy the product at the end of the experiment – and investigated neural correlates of the preference formation stages (1, 2) and the price processing stage (2). They found that product preference correlated positively with activity changes in, amongst other areas, the nucleus accumbens (NAcc), a region thought to be involved in reward prediction mechanisms, and that net value (WTP-price) correlated positively with activity changes in the medial prefrontal cortex (MPFC), anterior cingulate cortex (ACC), and frontopolar cortex. During the choice stage (3), purchasing correlated negatively with activation in the bilateral insula, a region known to be involved in risk and pain processing, and positively with activity changes in the ventromedial prefrontal cortex (VMPFC), a region shown to encode preference signals at the time of choice. When distinguishing purchased-item trials from non-purchased-item trials, the authors found significant differences in NAcc activation during preference formation, and both medial prefrontal cortex and insula deactivation during price processing, in line with their a priori hypotheses. They then estimated brain activity in these three regions of interests and entered them as covariates in a logistic regression, along with self-report measures of preference and net value, to predict subsequent purchasing decisions. Results indicated that the full model (i.e., including the neural measures) was a significantly better predictor than one including only self-report measures.

A study by Plassmann et al. (2007) identified the neural correlates of retail brand loyalty. In their FMRI study, subjects had to choose between retail brands for the purchase of an identical garment, selecting the brand which they would prefer. With the results of that FMRI session and previously collected information about subjects’ buying behavior, the researchers were able to identify the favorite retail brand of the participants. Next, subjects were divided into two groups, according to their average buying behavior labeled ‘‘loyal customers and disloyal customers’’ Data analysis showed that loyal customers integrate emotions into the decision making process in a more intense way, through the activation in the ventromedial prefrontal cortex, and that the favorite retail brand can act as a relevant rewarding stimulus on a behavioral level. In contrast, a comparable activation in these regions was not measurable for disloyal participants. Plassmann et al. (2007) developed an interesting conclusion from their results: the use of emotional reinforces in marketing and within the distribution policy can constitute the base for sustainable, long-term customer retention.

Koenigs and Tranel (2008) investigated how preferences for Coke vs. Pepsi in patients with damage in the vmPFC changed during blind vs. open tasting of both sodas. They found that brand associations in the open tasting did not influence the lesion patients, only the control patients. In other words, patients with a lesioned vmPFC did not reverse their preferences when they knew what brand of soda they were consuming. Koenigs and Tranel (2008) investigation conducted based on a different methodological approach, namely lesion studies. According to Plassman et al. (2012), the advantage of using lesion patients as compared to FMRI is that causal and not "only" correlational links between mental processes and brain functioning can be established.

(Dietvorst et al., 2009) aimed at developing a sales force–specific Theory-of-Mind (ToM) scale in two steps. First, they developed a personality scale measuring salespeople's interpersonal mentalizing skills—that is, a salesperson’s ability to "read the minds" of customers in the sense of first recognizing customer intentionality and processing subtle interpersonal cues and then adjusting volitions accordingly—based on questionnaires. Second, they validated the questionnaire-based scale by comparing high- and low-scoring salespeople on the scale when they worked on interpersonal-mentalizing and control tasks while having their brains scanned using fMRI. Interestingly, they found that salespeople who scored high on their sales force-specific ToM scale also showed more activation in brain areas involved in ToM during the interpersonal-mentalizing tasks but not during the control tasks. The study is one of the first to test the validity of measures of a scale not only in traditional ways but also by adopting procedures from neuroscience.

Lauri, (2010) research question was to understand how marketing assets in the retail store affect the customer’s degree of willingness to purchase in different phases of consultative selling process. His research was based on a behavioral and the neuromarketing research. The test subjects participated in the experiment while the neurophysiological responses were measured. The research setting was a virtual consumer journey where consumer perception to the retail marketing assets could be analyzed. The analysis was made separately from the results of behavioral and neurophysiological research. The results of the neuromarketing research indicate that from the moment of an offer, a physiological response can be observed in the Inferior Frontal Gyrus. The results suggest that even if the elevated degree of willingness to Purchase did not remain in the behavioral test results until the latter phases of the consultative selling process, the physiological results indicated plateau of the blood signal until the end of the marketing exchange.

Conclusion from literature review

Overall, the literature points to beneficial results from customer involvement, specially, in the idea generation and service process/market testing stages of new service development.

The literature to date also has analyzed the role that neuromarketing research play in areas like trust, brand preferences, advertising, pricing and negotiation. However, a slowly growing number of studies have analyzed its role in the area of innovation.

Conceptual framework

The exploratory evidences from the literature review and qualitative in-depth interviews were the bases on which the conceptual framework is grounded. The conceptual framework proposes that the use of neuromarketing research can magnify user co-development in the service innovation process as depicted in figure 1.

Consumer as user (test and support)

Consumer as co-creators (design)

Consumers as resources (ideation)

Degree of customer co-development of service innovation

Neuromarketing Techniques

Figure 1: The Conceptual Framework

Service innovation

The introduction of new services to satisfy customers and improve firm value is becoming a critical issue for managers in both services- and goods-dominant firms as economies in developed and developing countries are increasingly driven by services (Popadiuk & Choo, 2009 and World bank, 2008). Indeed, the Marketing Science Institute’s (MSI) member companies have identified service innovation as one of the priority research topics (Marketing Science Institute 2008). Formally, service innovation is the exploitation of an idea for a performance that is new to the firm and perceived by customers to offer new benefits (Berry et al. 2006). Service innovations can be categorized as (1) Internet-enabled service innovations (IESIs) and traditional or non-Internet-enabled service innovations (NIESIs) (Lee and Grewal, 2004). (2) (Service) product innovation and service innovation (Oke, 2007).

Identifying the key drivers of successful service innovation is a main concern in the literature on service innovation. Success factors can be divided into structural- and people-related factors (Dorner et al., 2011).

Structural factors refer to using a systematic new service development process, specific innovation (funnel) tools and multifunctional teams as well as the availability of resources, market testing and market research. A systematic new service development process involves defined stages and milestones. The stages should include market launches and testing as part of a new service development process (Dorner et al., 2011). A frequently cited development process for services is the 15-step model of Scheuing and Johnson (1989) based on survey responses from a modest sized sample of financial services firms. Their sequence of development activities included (1) formulation of new service objectives and strategy, (2) idea generation, (3) idea screening, (4) concept development, (5) concept testing, (6) business analysis, (7) project authorization, (8) service and design testing, (9) process and system design and testing, (10) marketing program design and testing, (11) personnel training, (12) service testing and pilot run, (13) test marketing, (14) full-scale launch, and (15) post-launch review. The Johnson, et al. (2000) model groups development activities into the four sequential stages of design, analysis, development and full launch, and identifies a variety of enablers which affect the process outcome, i.e., people, technology, systems, product, tools, teams and organizational context (Melton, 2007). Alam and Perry (2002) paper showed that services were developed in a ten-stage process. Their ten step NSD process model consisted of (1) strategic planning, (2) idea generation, (3) idea screening, (4) business analysis, (5) formation of cross-functional team, (6) service design and process/system design, (7) personnel training, (8) service testing and pilot run, (9) test marketing, and (10) commercialization. One benefit of a more formalized innovation process is claimed to be a more predictable and manageable process (Dorner et al., 2011). Contrary to conventional wisdom in new service development, Menor & Roth (2008) have found that formalized processes play a lesser role in the success of new service development compared with the other dimensions – market acuity, new service development strategy and Information technology use and experience. Instead, market acuity – which captures the firm’s ability to see the competitive environment clearly and to anticipate and respond to customers’ evolving needs and wants – was the most important new service development competence indicator.

People related factors refer to direct customer involvement, the involvement of customer contact personnel, senior management, and non-contact personnel (Dorner et al., 2011). Leiponen (2005) argued that the likelihood of accomplishing innovation is higher if efforts are made to acquire external knowledge from, for example, customers and competitors than if innovation efforts are based only on internal incremental learning (Dorner et al., 2011).

The changing customer role has been stressed in recent service innovation literature. Up until the mid 1970s, most marketers viewed customers as passive buyers whose participation would disrupt organizational routines and procedures and constrain potential operating efficiencies. Thompson (1967) went as far as advising firms to buffer their service delivery from customers’ disturbances. Against this backdrop, Peters and Waterman (1982) and Wilson (1994) warned that there was still no theory that could explain co-production. This warning directed research attention to customers’ active role in the production and delivery of service offerings. Since then, interest in co-production has been gradually, but steadily, rising (Zolfagharian, 2007). Consequently, many models of the customer involvement in NPD and NSD process have been developed in the literature. Alam (2002) suggested a model based on the degree of communication between the organization and the customers throughout the development process. In his model, the intensity of the communication ranges from passive acquisition of input, information and feedback on specific issues and extensive consultation with customers, to full membership on the NSD team: (1) passive acquisition of input, (2) information and feedback on specific issues, (3) extensive consultation with users, and (4) representation. For most of the cases, level of intensity was information/feedback and extensive consultation, which took less time, money and effort to effectively involve customers. Voss (1985) suggests five categories of customer integration: (1) User developed, not transferred, (2) User developed, transferred, (3) User innovation, (4) User initiated supplier innovation and (5) Supplier innovation. It is noteworthy that the main source of idea generation in the first three categories is the user, while the supplier is the dominating party in the last two categories Whereas, Voss (1985) takes the innovation as his point of origin, Edvardsson et al. (2010) preferred to look at the organizational view of the customer. Edvardsson et al. (2010) Suggested classification system showing a gradually changing view of the customer ranging from the customer as buyer, the customer as a subject of interest, a customer as a provider of information, the customer as co-developer and finally the customer as developer. Alam and Perry(2002) have developed a stage model of new service development. This framework takes into account the core element in user involvement in new service development highlighting the objective/purpose of involvement, the stages of involvement in the organizational innovation process, the intensity of involvement and the modes of involvement. Nambisan (2002) has likewise looked at the roles of customers in new product innovation which he categorizes as customers as resource, customers as co-creators and customers as users. Table 1 provides a Summary of innovation process stages, new service development (NSD) stages and customer roles in the different stages.

Table 1: Summary of innovation process stages, new service development (NSD) stages and customer roles in the different stages.

Innovation Process Stages

10 stages of NSD

Customer’s roles in NSD

Initiation Step 1. Agenda setting is the general organizational problems that may create a perceived need for innovation.

strategic planning

Initiation Step 2. Matching is fitting a problem from the organization’s agenda with an innovation.

idea generation

idea screening

Customer as resource

Implementation Step 1. Redefining/restructuring is when the innovation is modified and re-invented to fit the organization, and when the organizational structures are altered.

business analysis,

formation of cross functional team,

service and process design,

personnel training,

Customer as co-creator

Implementation Step 2. Clarifying is the relationship between the organization and the innovation is defined more clearly

service testing and pilot run,

test marketing,

Customer as user

Implementation Step 3. Routinizing is when the innovation becomes an ongoing element in the organization’s activities

commercialization

Customer as user

Source: Scupola and Nicolajsen (2010)

Customer as a resource found that it is definitely possible to get innovative and original ideas from potential customers. There are a number of challenges related to involving customers as a resource in idea generation including customers’ selection, creation of incentives to foster participation and capture of knowledge (Nambisan, 2002).

Customer as co-creator, As co-creators, customers can participate in a number of activities varying from for example service design activities to service development activities.

Customer as user, In such a role customers can provide value in two ways: product or service testing and product or service support. Customer involvement in product testing can be used to identify problems early in the development phase, thus minimizing the costs of redesign and re-development. Regarding product or service support, customers can acquire significant knowledge or expertise on various aspects of usage, which they can use to help or provide support to other customers. In addition "expert customers may discover new ways of product usage, as well as shortcuts and other methods to enhance the overall value of the product (Nambisan, 2002).

There has been extensive research on methods that facilitate individual customer engagement in innovation and NPD (Schirr, 2008). Methods of involvement included face-to-face interviews, user visits and meetings, brainstorming, users’ observation and feedback, phone/fax/e-mail, idea competitions and focus group discussions. Over all the stages, interviews and group meetings at company sites were most frequently used, due to cost and time constraints; brainstorming occurred only in the idea generation and screening stages (Alam, 2002).

Kleef et al. (2005) identified the 10 most common consumer research methods and techniques in NPD are:

Empathic design,

Category appraisal (including preference analysis),

Conjoint analysis,

Focus group,

Free elicitation,

Information acceleration (IA),

Kelly repertory grid,

Laddering,

Lead user technique, and

Zaltman metaphor elicitation technique (ZMET).

Almost all the literature on new service development agreed upon the positive influence of customer involvement in the different stages of these NSD. The Outcomes of consumers involvement in service innovation summarized in table 2.

Table 2: Antecedents of Consumer Co-development of service innovations

Author(s)

Antecedents

Alam (2002)

Found respondents agreeing that the primary objective of user involvement was to develop a successful new service. Respondents also viewed one or more of the following as important objectives (i.e., outcomes) of user involvement: (1) Superior and differentiated service - develop unique, high value services. (2) Reduced cycle time – cut through bureaucracy and save time by getting new offer ideas with "customer perceived value" directly from the customer. (3) User education – involving users in development educates them about uses, attributes and benefits of the new service. (4) Rapid diffusion – involve customers in development to speed up market acceptance of the new offer. (5) Improved public relations – quickly build public support for a new service. (6) Long-term relationships – build customer loyalty and relations over time.

Alam & Perry (2002)

User involvement may have a positive influence in all the phases of new service development, even though user involvement in idea generation and idea screening are found to be the most important. User involvement in strategic planning, personal training and test marketing are of the least importance.

Magnusson (2003)

The service innovations suggested by the users were more creative and useful than those suggested by the professionals.

Matthing et al.

(2004)

Involving users in the innovation process can serve as a means of gaining important understanding of them. User involvement can work as a mutual learning process whereby the developing company, together with the prospective users, explores a new technology, for instance.

Carbonell et al. (2009)

Customer involvement in NSD has a positive direct effect on technical quality and innovation speed; it has an indirect effect on competitive superiority and sales performance through both technical quality and innovation speed. Their study also revealed a positive effect of technological novelty as well as technological turbulence on customer involvement.

Magnusson

(2009)

Ordinary users should not be expected to contribute ideas that can be directly put into the new product development process; rather, ordinary user involvement should be regarded as a process whereby a company learns about users’ needs and is inspired to innovate. User involvement can actually be a stimulus for review of a company’s business strategy.

Schulteß et al. (2010)

The innovation managers clearly indicated the idea evaluation (phase 2) and the service concept and investment decision (phase 3) as the most important determinants of success. Surprisingly, these crucial phases are exactly those in which the customer integration is lowest on average, which can lead to new services being developed with limited customer input. Obvious barriers to the integration of customers in those important phases are the risk of losing confidentiality and the costs of managing the customer involvement.

Melton &

Hartline (2010)

To produce successful new services, firms should involve customers in the design and development stages to help identify market opportunities, generate and evaluate new service ideas, define desired benefits and features of the potential service, and provide extensive feedback for product and market testing.

Neuromarketing

It is only in recent years that consumer behavior and marketing research has started looking towards neuroscience for answers to salient consumer decision motives. It is from here that neuromarketing started to emerge (Simson, 2010). The academic knowledge body of neuromarketing is still in an "embryonic stage" compared to Neuroeconomics and Cognitive Neuroscience. Recent publishing have rather focused on defining neuromarketing and some commercial research streams are developing in advertising and branding (Morin, 2011; Kumlehn, 2011).

Neuromarketing defined as:

"The application of neuroscientific methods to analyze and understand human behavior in relation to markets and marketing exchanges" (Lee et al., 2007)

‘The use of neuro-technology to improve marketing decision making’

(Kotler et al., 2008)

"A new branch of marketing, based on the techniques resulted from neurosciences for a better identification and understanding of the cerebral mechanisms that fundament the consumer’s behavior, in the perspective of increasing the efficacy of the commercial actions of companies" (Veronica, 2009)

"A relatively a new field of marketing that utilizes neurosciences, computer-simulated environments, medical technologies, and other scientific means of studying human consumers neurological, sensorimotor, cognitive, and affective responses to marketing stimuli"

(Burris and Sheikh, 2011)

(Lee et al., 2007) definition of neuromarketing has two main upshots: firstly, it moves consideration of neuromarketing away from being solely the use of neuroimaging by commercial interests for their benefit; secondly, the scope of neuromarketing research is widened from solely consumer behavior, to include many more avenues of interest, such as inter and intra-organizational research, which are common in the marketing research literature. Neuromarketing differs from consumer neuroscience as the later refers to academic research at the intersection of neuroscience and consumer psychology. While, neuromarketing, refers to practitioner and commercial interest in neurophysiological tools, such as eye tracking, skin conductance, electroencephalography (EEG), and functional magnetic resonance imaging (fMRI), to conduct company-specific market research (Plassmann at al., 2012). Table 3 provides a detailed description for these neuromarketing techniques. Neuromarketing literature review crystal that EEG is the oldest least expensive technique while FMRI represent the most recently used and expensive one. Many researchers apply mixed techniques to achieve more reliable results.

Table 3: Neuromarketing Technologies

Tool

Description

Functional MRI (FMRI)

The technique uses an MRI scanner to measure the blood oxygenation level-dependent (BOLD) signal*.

Electroencephalography (EEG)

EEG uses electrodes applied to the scalp and measures changes in the electrical field in the brain region underneath. EEG has very high temporal resolution (milliseconds) and can therefore detect brief neuronal events*.

Magnetoencephalography (MEG)

An expensive cousin of EEG, MEG measures changes in the magnetic fields induced by neuronal activity. Thus, MEG has the same advantage of high temporal resolution and, because the magnetic field is less distorted by the skull than is the electrical field, it has better spatial resolution than EEG*.

Measuring of Physiological Responses

A wide battery of tests exists to study biological reactions to the stimuli of interest. Among them, monitoring the heart rate, blood pressure, volume of the stress hormone cortisol provides data on the emotional effects of various stimuli. Similarly, measuring the skin conductivity as affected by sweat – for example on the palms of the hands – is a sensitive gauge of emotional arousal emerging in the social context. Also, studying contractions of the facial muscles –Facial Electromyography– in response to stimuli, informs the researchers of the emotional state of the subjects.**

Response Time Measures

Simply measuring the amount of time taken to respond after the stimulus has been presented can prove quite revealing for the evaluation of the complexity of the stimulus to an individual. The response latency method is easy to implement and is used in conjunction with various psychological and sensory tests..**

Eye tracking

Eye tracking is a useful procedure for the analysis of behavior and cognition. It measures either where the subject is looking (the point of gaze), the motion of an eye relative to the head and the pupil dilation.**

Lesion Studies

The lesion studies focus on the pathological cases of patients with the brain damage. Their primary purpose is to determine how this condition influences behavior of the individual.**

*(Ariely and Berns, 2010)

**(Zurawicki, 2010)

Areas where neuromarketing leaves its print

The most fundamental areas of neuromarketing research are (Lauri, 2010):

The traditional marketing mix (4Ps)

Branding operationalization: Different brand ears as Favorability of brand associations (Deppe et al., 2007; Koenigs and Tranel., 2008; and Plassmann et al., 2008), Different types of brand associations (Yoon et al., 2006; McClure et al., 2004; and Erk et al., 2002), Brand recall and memories (Schaefer et al., 2006), and brand loyalty (Plassman et al., 2007).

Trust: The major questions neuromarketing research tried to answer in the area of trust were whether a trust has been a result of a repeated positive stimulus, and whether different types of trust (between close relatives and parties conducting a marketing exchange) have behaved similarly in the brain.

Negotiation: Negotiation as being a "central concept in marketing" has understandably been subject to neuromarketing research. Studying negotiation interaction with the use of game theory has been an interest for both neuromarketing and neuroeconomics studies.

Controversies regarding neuromarketing

In fact, the application of neuroimaging to market research – what has come to be called ‘neuromarketing’ – has caused considerable controversy within neuroscience circles in recent times (lee et al., 2007). It is unarguable that incorporating cognitive neuroscience theory will help both marketing academics and practitioners to move away from traditional market research methods fraught with systemic limitations and biases. This movement will certainly be towards a greater ability to understand why and/or how consumers make the decisions they do, and also towards research in marketing which has implications for understanding more general organizational and social behavior in a marketing-relevant context. Yet the fantastical notion of controlling consumer perceptions, emotions, and behavior as argued by Martin Lindstrom in his bestselling book "Buy.ology", is no closer now than it was over 50 years ago when Vance Packard in The Hidden Persuaders made the same claim about advertising. Such fanciful claims are likely to be just as dubious now as they were then (Lee et al., 2009). According to Senior and Lee (2008) and Lee et al. (2007), application of brain imaging to investigate intuitively appealing, but scientifically simplistic – and ultimately meaningless – concepts like the "buy button" in the brain cannot be the sole remit of neuromarketing.

However, the growth of Neuromarketing raises an ethical concern whether the marketer is invading into the consumer's privacy of decision making (Wilson et al., 2008). Murphy et al. (2008) go farther and recommend a code of ethics to be adopted by the neuromarketing industry.

Murphy et al. (2008) stated that "The overarching goal of this code of ethics is to promote research and development, entrepreneurship, and profitable enterprise alongside beneficent and non-harmful use of neuroimaging technology at all stages of development, deployment, and dissemination". Their preliminary version of code of ethics covered the following main points [1] :

Protection of research subjects.

Protection of vulnerable niche populations from marketing exploitation.

Full disclosure of goals, risks, and benefits.

Accurate media and marketing representation.

Internal and external validity.

Research proposition

The main proposition: The use of Neuromarketing magnifies consumer co-development in the service innovation process

This main proposition can be divided into the following sub-propositions:

P1.A: The use of Neuromarketing magnifies consumer co-development in the idea generation phase of the service innovation process

P1.B: The use of Neuromarketing magnifies consumer co-development in the design and development phase of the service innovation process

P1.C: The use of Neuromarketing magnifies consumer co-development in the testing and support phase of the service innovation process.

Proposed methodology

Context of the Research

Higher education provides an interesting and important context for the research, since Higher education institutions across the world have become increasingly "marketing-oriented" and students increasingly become "consumers". The higher education service in Egypt faces significant marketing challenges; the demand for higher education is growing and the sector is undergoing considerable change, with a range of new, private providers joining established publicly funded universities (Mourad at al., 2010).

Exploratory Evidence

An exploratory study as a qualitative research was made, using eight in-depth interviews with concerned parties- including under and post graduate students, alumni, instructors, academic professors, and neurologists - at two Egyptian Universities to develop the research framework and to better comprehend the nature of the problem.

Participating instructors and academic professors were asked to describe their approach to student engagement and give examples of recent initiatives and projects. While, students were asked to comment on their experiences in terms of the initiatives and projects identified.

Neurologists were asked about if they are familiar with neuromarketing research and if it is effective from their point of view. They also were asked to identify which neuroimaging tools most suited to the research aim.

Exploratory evidence proposed that students co-development in educational service innovation still a neglected area in the Egyptian Universities. Neurologists also stated that there is no clear indication about the usefulness of applying neuroscience techniques in the field of marketing.

Research design:

A comparative experimental design will be used wherein a real customer co-development scenario will be emulated. Three groups will be created.

Professional service developers group: professors and instructors who will assign the responsibility of evaluating students’ service innovations - in the first phase of NSD based on a 10 point scale. Three dimensions will be included in this scale are originality, user value, and producibility. A score of 1 represent the least original, least valuable, and hardest to produce, similarly a score of 10 corresponded to the most original, most valuable, and easiest to produce.

Ordinary users groups: volunteer students from Egyptian Universities [Cairo and Suez Canal University (SCU)]. Students will be randomly divided into two groups (E, C) one of these groups will serve as a control group (labeled C).

Data collection:

As a first step, the participants will be asked to fill out a form asking for personal data such as age, gender and other personal characteristics to obtain individual background data. Then, an in-depth interview will be conducted with participants in the both groups. Group E will be interviewed while EEG recording and C without the use of EEG.

Concluding remarks

This research aimed to trigger a sparkle on the effectiveness of using neuromarketing research as a tool to magnify and improve customer co-development of service innovations. It tries to shad line on the effect of using these tools upon customer engagement in different stages of new service development and in what stages the beneficial effect of these tools reaches its maximum.

A conclusive causal research design based on a cross sectional data collection is planned to empirically test the above research propositions. A structural equation modeling analysis along with confirmatory factor analysis are thought to be appropriate analysis vehicles for identifying and proving the argued causal influence of the neuromarketing research to magnify customer co-development of service innovations in Egyptian universities.